From 6910eb7243dd2aa1ff0b381c0494fc8a9c81eac9 Mon Sep 17 00:00:00 2001
From: mazhurin <mazhurin@gmail.com>
Date: Wed, 9 Mar 2016 15:45:34 +0000
Subject: [PATCH] Interactive 3D scatter plot in jupyter. Banjax log in
 barplots

---
 requirements.txt                              |   3 +-
 .../Clustering-checkpoint.ipynb               | 677 +++++++++++-------
 src/Clustering.ipynb                          | 605 +++++++++++-----
 src/bothound_tools.py                         |   5 +-
 src/session_computer.py                       |   2 +-
 src/util/es_handler.py                        | 178 ++---
 6 files changed, 942 insertions(+), 528 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index b8602c7..43caffc 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,4 +7,5 @@ certifi
 ua_parser
 bokeh
 pandas
-pycountry
\ No newline at end of file
+pycountry
+plotly
\ No newline at end of file
diff --git a/src/.ipynb_checkpoints/Clustering-checkpoint.ipynb b/src/.ipynb_checkpoints/Clustering-checkpoint.ipynb
index 651826d..5dc0b68 100644
--- a/src/.ipynb_checkpoints/Clustering-checkpoint.ipynb
+++ b/src/.ipynb_checkpoints/Clustering-checkpoint.ipynb
@@ -18,51 +18,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 10,
    "metadata": {
-    "code_folding": [],
-    "collapsed": true
+    "code_folding": [
+     332
+    ],
+    "collapsed": false
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:66: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  inline backend.\"\"\"\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:71: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  'retina', 'jpeg', 'svg', 'pdf'.\"\"\")\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:85: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  use `figure_formats` instead)\"\"\")\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:95: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  \"\"\"\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:114: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  \"\"\")\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/pylab/config.py:44: DeprecationWarning: InlineBackend._config_changed is deprecated: use @observe and @unobserve instead.\n",
-      "  def _config_changed(self, name, old, new):\n",
-      "/usr/local/lib/python2.7/dist-packages/traitlets/traitlets.py:770: DeprecationWarning: A parent of InlineBackend._config_changed has adopted the new @observe(change) API\n",
-      "  clsname, change_or_name), DeprecationWarning)\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:98: DeprecationWarning: DisplayFormatter._formatters_default is deprecated: use @default decorator instead.\n",
-      "  def _formatters_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:677: DeprecationWarning: PlainTextFormatter._deferred_printers_default is deprecated: use @default decorator instead.\n",
-      "  def _deferred_printers_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:669: DeprecationWarning: PlainTextFormatter._singleton_printers_default is deprecated: use @default decorator instead.\n",
-      "  def _singleton_printers_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:672: DeprecationWarning: PlainTextFormatter._type_printers_default is deprecated: use @default decorator instead.\n",
-      "  def _type_printers_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:672: DeprecationWarning: PlainTextFormatter._type_printers_default is deprecated: use @default decorator instead.\n",
-      "  def _type_printers_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.py:677: DeprecationWarning: PlainTextFormatter._deferred_printers_default is deprecated: use @default decorator instead.\n",
-      "  def _deferred_printers_default(self):\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "\n",
        "    <div class=\"bk-banner\">\n",
        "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
-       "        <span id=\"7bd7ce5e-981a-4da3-a3e4-5e2e9dc18e03\">Loading BokehJS ...</span>\n",
+       "        <span id=\"1cd13974-dfa2-437d-b526-37962420ef44\">Loading BokehJS ...</span>\n",
        "    </div>"
       ]
      },
@@ -128,7 +98,7 @@
        "    },\n",
        "    \n",
        "    function(Bokeh) {\n",
-       "      Bokeh.$(\"#7bd7ce5e-981a-4da3-a3e4-5e2e9dc18e03\").text(\"BokehJS successfully loaded\");\n",
+       "      Bokeh.$(\"#1cd13974-dfa2-437d-b526-37962420ef44\").text(\"BokehJS successfully loaded\");\n",
        "    },\n",
        "    function(Bokeh) {\n",
        "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.11.1.min.css\");\n",
@@ -163,51 +133,94 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:106: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=\"\"\"Generate default config file.\"\"\"\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:110: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=\"Specify a config file to load.\"\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:118: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=\"\"\"Full path of a config file.\"\"\",\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:122: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=\"\"\"Answer yes to any prompts.\"\"\"\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:286: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  overwrite = Bool(False, config=True, help=\"Force overwrite of existing files\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:287: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  symlink = Bool(False, config=True, help=\"Create symlinks instead of copying files\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:288: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  user = Bool(False, config=True, help=\"Whether to do a user install\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:289: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  prefix = Unicode('', config=True, help=\"Installation prefix\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:290: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  nbextensions_dir = Unicode('', config=True, help=\"Full path to nbextensions dir (probably use prefix or user)\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:291: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  destination = Unicode('', config=True, help=\"Destination for the copy or symlink\")\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:293: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=\"Verbosity level\"\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:333: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=(\"Which config section to add the extension to. \"\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:364: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  help=(\"Which config section to remove the extension from. \"\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:78: DeprecationWarning: JupyterApp._config_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _config_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:340: DeprecationWarning: EnableNBExtensionApp._config_file_name_default is deprecated: use @default decorator instead.\n",
-      "  def _config_file_name_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:91: DeprecationWarning: JupyterApp._data_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _data_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:73: DeprecationWarning: JupyterApp._jupyter_path_default is deprecated: use @default decorator instead.\n",
-      "  def _jupyter_path_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:69: DeprecationWarning: JupyterApp._log_level_default is deprecated: use @default decorator instead.\n",
-      "  def _log_level_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:97: DeprecationWarning: JupyterApp._runtime_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _runtime_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:15: DeprecationWarning: metadata {'config': True} was set from the constructor.  Metadata should be set using the .tag() method, e.g., Int().tag(key1='value1', key2='value2')\n",
-      "  config_dir = Unicode(config=True)\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning: ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _config_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning: ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _config_dir_default(self):\n"
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:78: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:340: DeprecationWarning:\n",
+      "\n",
+      "EnableNBExtensionApp._config_file_name_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:91: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._data_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:73: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._jupyter_path_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:69: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._log_level_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:97: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._runtime_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning:\n",
+      "\n",
+      "ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning:\n",
+      "\n",
+      "ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n"
      ]
+    },
+    {
+     "data": {
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f=0;r>f;++f)i.push(i[o++]),a.push(0);this._time.push(t);for(var f=r;f>0;--f)i.push(n(l[f-1],u[f-1],arguments[f])),a.push(0)}},u.push=function(t){var e=this.lastT(),r=this.dimension;if(!(e>t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=t-e,l=this.bounds,u=l[0],c=l[1],f=s>1e-6?1/s:0;this._time.push(t);for(var h=r;h>0;--h){var p=n(u[h-1],c[h-1],arguments[h]);i.push(p),a.push((p-i[o++])*f)}}},u.set=function(t){var e=this.dimension;if(!(t<this.lastT()||arguments.length!==e+1)){var r=this._state,i=this._velocity,a=this.bounds,o=a[0],s=a[1];this._time.push(t);for(var l=e;l>0;--l)r.push(n(o[l-1],s[l-1],arguments[l])),i.push(0)}},u.move=function(t){var e=this.lastT(),r=this.dimension;if(!(e>=t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=this.bounds,l=s[0],u=s[1],c=t-e,f=c>1e-6?1/c:0;this._time.push(t);for(var h=r;h>0;--h){var p=arguments[h];i.push(n(l[h-1],u[h-1],i[o++]+p)),a.push(p*f)}}},u.idle=function(t){var e=this.lastT();if(!(e>t)){var r=this.dimension,i=this._state,a=this._velocity,o=i.length-r,s=this.bounds,l=s[0],u=s[1],c=t-e;this._time.push(t);for(var f=r-1;f>=0;--f)i.push(n(l[f],u[f],i[o]+c*a[o])),a.push(0),o+=1}}},{\"binary-search-bounds\":18,\"cubic-hermite\":19}],18:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],19:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){var o=6*i*i-6*i,s=3*i*i-4*i+1,l=-6*i*i+6*i,u=3*i*i-2*i;if(t.length){a||(a=new Array(t.length));for(var c=t.length-1;c>=0;--c)a[c]=o*t[c]+s*e[c]+l*r[c]+u*n[c];return a}return o*t+s*e+l*r[c]+u*n}function i(t,e,r,n,i,a){var o=i-1,s=i*i,l=o*o,u=(1+2*i)*l,c=i*l,f=s*(3-2*i),h=s*o;if(t.length){a||(a=new Array(t.length));for(var p=t.length-1;p>=0;--p)a[p]=u*t[p]+c*e[p]+f*r[p]+h*n[p];return a}return u*t+c*e+f*r+h*n}e.exports=i,e.exports.derivative=n},{}],20:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function a(t,e){var r=e[0],n=e[1],a=e[2],o=e[3],s=i(r,n,a,o);s>1e-6?(t[0]=r/s,t[1]=n/s,t[2]=a/s,t[3]=o/s):(t[0]=t[1]=t[2]=0,t[3]=1)}function o(t,e,r){this.radius=l([r]),this.center=l(e),this.rotation=l(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),r=[].slice.call(r,0,4),a(r,r);var i=new o(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/lookAt\"),c=t(\"gl-mat4/fromQuat\"),f=t(\"gl-mat4/invert\"),h=t(\"./lib/quatFromFrame\"),p=o.prototype;p.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},p.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;a(e,e);var r=this.computedMatrix;c(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;3>l;++l){for(var u=0,f=0;3>f;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r},p.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},p.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},p.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=a[1],s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=a[2],v=a[6],m=a[10],y=g*o+v*s+m*l,b=g*c+v*f+m*h;g-=y*o+b*c,v-=y*s+b*f,m-=y*l+b*h;var x=n(g,v,m);g/=x,v/=x,m/=x;var _=c*e+o*r,w=f*e+s*r,k=h*e+l*r;this.center.move(t,_,w,k);var A=Math.exp(this.computedRadius[0]);A=Math.max(1e-4,A+i),this.radius.set(t,Math.log(A))},p.rotate=function(t,e,r,a){this.recalcMatrix(t),e=e||0,r=r||0;var o=this.computedMatrix,s=o[0],l=o[4],u=o[8],c=o[1],f=o[5],h=o[9],p=o[2],d=o[6],g=o[10],v=e*s+r*c,m=e*l+r*f,y=e*u+r*h,b=-(d*y-g*m),x=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(b,2)-Math.pow(x,2)-Math.pow(_,2))),k=i(b,x,_,w);k>1e-6?(b/=k,x/=k,_/=k,w/=k):(b=x=_=0,w=1);var A=this.computedRotation,M=A[0],T=A[1],E=A[2],L=A[3],S=M*w+L*b+T*_-E*x,C=T*w+L*x+E*b-M*_,P=E*w+L*_+M*x-T*b,z=L*w-M*b-T*x-E*_;if(a){b=p,x=d,_=g;var R=Math.sin(a)/n(b,x,_);b*=R,x*=R,_*=R,w=Math.cos(e),S=S*w+z*b+C*_-P*x,C=C*w+z*x+P*b-S*_,P=P*w+z*_+S*x-C*b,z=z*w-S*b-C*x-P*_}var O=i(S,C,P,z);O>1e-6?(S/=O,C/=O,P/=O,z/=O):(S=C=P=0,z=1),this.rotation.set(t,S,C,P,z)},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;u(i,e,r,n);var o=this.computedRotation;h(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),a(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var s=0,l=0;3>l;++l)s+=Math.pow(r[l]-e[l],2);this.radius.set(t,.5*Math.log(Math.max(s,1e-6))),this.center.set(t,r[0],r[1],r[2])},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e){var r=this.computedRotation;h(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),a(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;f(n,e);var i=n[15];if(Math.abs(i)>1e-6){var o=n[12]/i,s=n[13]/i,l=n[14]/i;this.recalcMatrix(t);var u=Math.exp(this.computedRadius[0]);this.center.set(t,o-n[2]*u,s-n[6]*u,l-n[10]*u),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},p.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var i=t.distance;i&&i>0&&this.radius.set(e,Math.log(i)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":16,\"filtered-vector\":17,\"gl-mat4/fromQuat\":183,\"gl-mat4/invert\":186,\"gl-mat4/lookAt\":187}],21:[function(t,e,r){arguments[4][17][0].apply(r,arguments)},{\"binary-search-bounds\":22,\"cubic-hermite\":23,dup:17}],22:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],23:[function(t,e,r){arguments[4][19][0].apply(r,arguments)},{dup:19}],24:[function(t,e,r){arguments[4][5][0].apply(r,arguments)},{dup:5}],25:[function(t,e,r){arguments[4][6][0].apply(r,arguments)},{dup:6}],26:[function(t,e,r){arguments[4][9][0].apply(r,arguments)},{dup:9}],27:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t){return Math.min(1,Math.max(-1,t))}function a(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),i=[0,0,0];e>Math.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,s=0;3>s;++s)a+=t[s]*t[s],o+=i[s]*t[s];for(var s=0;3>s;++s)i[s]-=o/a*t[s];return h(i,i),i}function o(t,e,r,n,i,a,o,s){this.center=l(r),this.up=l(n),this.right=l(i),this.radius=l([a]),this.angle=l([o,s]),this.angle.bounds=[[-(1/0),-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;16>u;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.up||[0,1,0],i=t.right||a(r),s=t.radius||1,l=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),h(r,r),i=[].slice.call(i,0,3),h(i,i),\"eye\"in t){var c=t.eye,d=[c[0]-e[0],c[1]-e[1],c[2]-e[2]];f(i,d,r),n(i[0],i[1],i[2])<1e-6?i=a(r):h(i,i),s=n(d[0],d[1],d[2]);var g=p(r,d)/s,v=p(i,d)/s;u=Math.acos(g),l=Math.acos(v)}return s=Math.log(s),new o(t.zoomMin,t.zoomMax,e,r,i,s,l,u)}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/invert\"),c=t(\"gl-mat4/rotate\"),f=t(\"gl-vec3/cross\"),h=t(\"gl-vec3/normalize\"),p=t(\"gl-vec3/dot\"),d=o.prototype;d.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},d.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},d.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,i=0,a=0,o=0;3>o;++o)a+=e[o]*r[o],i+=e[o]*e[o];for(var s=Math.sqrt(i),l=0,o=0;3>o;++o)r[o]-=e[o]*a/i,l+=r[o]*r[o],e[o]/=s;for(var u=Math.sqrt(l),o=0;3>o;++o)r[o]/=u;var c=this.computedToward;f(c,e,r),h(c,c);for(var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),b=Math.sin(g),x=this.computedCenter,_=v*y,w=m*y,k=b,A=-v*b,M=-m*b,T=y,E=this.computedEye,L=this.computedMatrix,o=0;3>o;++o){var S=_*r[o]+w*c[o]+k*e[o];L[4*o+1]=A*r[o]+M*c[o]+T*e[o],L[4*o+2]=S,L[4*o+3]=0}var C=L[1],P=L[5],z=L[9],R=L[2],O=L[6],I=L[10],j=P*I-z*O,N=z*R-C*I,F=C*O-P*R,D=n(j,N,F);j/=D,N/=D,F/=D,L[0]=j,L[4]=N,L[8]=F;for(var o=0;3>o;++o)E[o]=x[o]+L[2+4*o]*p;for(var o=0;3>o;++o){for(var l=0,B=0;3>B;++B)l+=L[o+4*B]*E[B];L[12+o]=-l}L[15]=1},d.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r};var g=[0,0,0];d.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;g[0]=i[2],g[1]=i[6],g[2]=i[10];for(var a=this.computedUp,o=this.computedRight,s=this.computedToward,l=0;3>l;++l)i[4*l]=a[l],i[4*l+1]=o[l],i[4*l+2]=s[l];c(i,i,n,g);for(var l=0;3>l;++l)a[l]=i[4*l],o[l]=i[4*l+1];this.up.set(t,a[0],a[1],a[2]),this.right.set(t,o[0],o[1],o[2])}},d.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=(Math.exp(this.computedRadius[0]),a[1]),s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=c*e+o*r,v=f*e+s*r,m=h*e+l*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+i),this.radius.set(t,Math.log(y))},d.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},d.setMatrix=function(t,e,r,a){var o=1;\"number\"==typeof r&&(o=0|r),(0>o||o>3)&&(o=1);var s=(o+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var l=e[o],c=e[o+4],f=e[o+8];if(a){var h=Math.abs(l),p=Math.abs(c),d=Math.abs(f),g=Math.max(h,p,d);h===g?(l=0>l?-1:1,c=f=0):d===g?(f=0>f?-1:1,l=c=0):(c=0>c?-1:1,l=f=0)}else{var v=n(l,c,f);l/=v,c/=v,f/=v}var m=e[s],y=e[s+4],b=e[s+8],x=m*l+y*c+b*f;m-=l*x,y-=c*x,b-=f*x;var _=n(m,y,b);m/=_,y/=_,b/=_;var w=c*b-f*y,k=f*m-l*b,A=l*y-c*m,M=n(w,k,A);w/=M,k/=M,A/=M,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,l,c,f),this.right.jump(t,m,y,b);var T,E;if(2===o){var L=e[1],S=e[5],C=e[9],P=L*m+S*y+C*b,z=L*w+S*k+C*A;T=0>j?-Math.PI/2:Math.PI/2,E=Math.atan2(z,P)}else{var R=e[2],O=e[6],I=e[10],j=R*l+O*c+I*f,N=R*m+O*y+I*b,F=R*w+O*k+I*A;T=Math.asin(i(j)),E=Math.atan2(F,N)}this.angle.jump(t,E,T),this.recalcMatrix(t);var D=e[2],B=e[6],U=e[10],V=this.computedMatrix;u(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,Y=V[14]/q,X=Math.exp(this.computedRadius[0]);this.center.jump(t,H-D*X,G-B*X,Y-U*X)},d.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},d.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},d.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},d.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},d.lookAt=function(t,e,r,a){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter,a=a||this.computedUp;var o=a[0],s=a[1],l=a[2],u=n(o,s,l);if(!(1e-6>u)){o/=u,s/=u,l/=u;var c=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=n(c,f,h);if(!(1e-6>p)){c/=p,f/=p,h/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=o*g+s*v+l*m;g-=y*o,v-=y*s,m-=y*l;var b=n(g,v,m);if(!(.01>b&&(g=s*h-l*f,v=l*c-o*h,m=o*f-s*c,b=n(g,v,m),1e-6>b))){g/=b,v/=b,m/=b,this.up.set(t,o,s,l),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var x=s*m-l*v,_=l*g-o*m,w=o*v-s*g,k=n(x,_,w);x/=k,_/=k,w/=k;var A=o*c+s*f+l*h,M=g*c+v*f+m*h,T=x*c+_*f+w*h,E=Math.asin(i(A)),L=Math.atan2(T,M),S=this.angle._state,C=S[S.length-1],P=S[S.length-2];C%=2*Math.PI;var z=Math.abs(C+2*Math.PI-L),R=Math.abs(C-L),O=Math.abs(C-2*Math.PI-L);R>z&&(C+=2*Math.PI),R>O&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,L,E)}}}}},{\"filtered-vector\":21,\"gl-mat4/invert\":186,\"gl-mat4/rotate\":190,\"gl-vec3/cross\":24,\"gl-vec3/dot\":25,\"gl-vec3/normalize\":26}],28:[function(t,e,r){\"use strict\";function n(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return 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L=0;3>L;++L)j[L]+=k*I[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],j,this.tickColor[A])}if(this.labelEnable[A]){for(var L=0;3>L;++L)j[L]+=k*I[L]*this.labelPad[L]/r[5*L];j[A]+=.5*(s[0][A]+s[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],j,this.labelColor[A])}}},d.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":49,\"./lib/cube.js\":50,\"./lib/lines.js\":51,\"./lib/text.js\":53,\"./lib/ticks.js\":54}],49:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}function i(t){for(var e=[],r=[],i=0,l=0;3>l;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;1>=p;p+=2){r.push(i,i+2,i+1,i+1,i+2,i+3),f[l]=p,h[l]=p;for(var d=-1;1>=d;d+=2){f[u]=d;for(var g=-1;1>=g;g+=2)f[c]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),i+=1}var v=u;u=c,c=v}var m=a(t,new Float32Array(e)),y=a(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),b=o(t,[{buffer:m,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:m,type:t.FLOAT,size:3,offset:12,stride:24}],y),x=s(t);return x.attributes.position.location=0,x.attributes.normal.location=1,new n(t,m,b,x)}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders\").bg,l=n.prototype;l.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;3>s;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),l.disable(l.POLYGON_OFFSET_FILL)}},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":52,\"gl-buffer\":58,\"gl-vao\":68}],50:[function(t,e,r){\"use strict\";function n(t,e,r){for(var n=0;4>n;++n){t[n]=r[12+n];for(var i=0;3>i;++i)t[n]+=e[i]*r[4*i+n]}}function i(t){for(var e=0;e<g.length;++e)if(t=l.positive(t,g[e]),t.length<3)return 0;for(var r=t[0],n=r[0]/r[3],i=r[1]/r[3],a=0,e=1;e+1<t.length;++e){var o=t[e],s=t[e+1],u=o[0]/o[3],c=o[1]/o[3],f=s[0]/s[3],h=s[1]/s[3],p=u-n,d=c-i,v=f-n,m=h-i;a+=Math.abs(p*m-d*v)}return a}function a(t,e,r,a){s(c,e,t),s(c,r,c);for(var l=0,g=0;2>g;++g){p[2]=a[g][2];for(var b=0;2>b;++b){p[1]=a[b][1];for(var x=0;2>x;++x)p[0]=a[x][0],n(f[l],p,c),l+=1}}for(var _=-1,g=0;8>g;++g){for(var w=f[g][3],k=0;3>k;++k)h[g][k]=f[g][k]/w;0>w&&(0>_?_=g:h[g][2]<h[_][2]&&(_=g))}if(0>_){_=0;for(var A=0;3>A;++A){for(var M=(A+2)%3,T=(A+1)%3,E=-1,L=-1,S=0;2>S;++S){var C=S<<A,P=C+(S<<M)+(1-S<<T),z=C+(1-S<<M)+(S<<T);u(h[C],h[P],h[z],d)<0||(S?E=1:L=1)}if(0>E||0>L)L>E&&(_|=1<<A);else{for(var S=0;2>S;++S){var C=S<<A,P=C+(S<<M)+(1-S<<T),z=C+(1-S<<M)+(S<<T),R=i([f[C],f[P],f[z],f[C+(1<<M)+(1<<T)]]);S?E=R:L=R}L>E&&(_|=1<<A)}}}for(var O=7^_,I=-1,g=0;8>g;++g)g!==_&&g!==O&&(0>I?I=g:h[I][1]>h[g][1]&&(I=g));for(var j=-1,g=0;3>g;++g){var N=I^1<<g;if(N!==_&&N!==O){0>j&&(j=N);var T=h[N];T[0]<h[j][0]&&(j=N)}}for(var F=-1,g=0;3>g;++g){var N=I^1<<g;if(N!==_&&N!==O&&N!==j){0>F&&(F=N);var T=h[N];T[0]>h[F][0]&&(F=N)}}var D=v;D[0]=D[1]=D[2]=0,D[o.log2(j^I)]=I&j,D[o.log2(I^F)]=I&F;var B=7^F;B===_||B===O?(B=7^j,D[o.log2(F^B)]=B&F):D[o.log2(j^B)]=B&j;for(var U=m,V=_,A=0;3>A;++A)V&1<<A?U[A]=-1:U[A]=1;return y}e.exports=a;var o=t(\"bit-twiddle\"),s=t(\"gl-mat4/multiply\"),l=(t(\"gl-mat4/invert\"),t(\"split-polygon\")),u=t(\"robust-orientation\"),c=new Array(16),f=(new Array(16),new Array(8)),h=new Array(8),p=new Array(3),d=[0,0,0];!function(){for(var t=0;8>t;++t)f[t]=[1,1,1,1],h[t]=[1,1,1]}();var g=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]],v=[1,1,1],m=[0,0,0],y={cubeEdges:v,axis:m}},{\"bit-twiddle\":55,\"gl-mat4/invert\":186,\"gl-mat4/multiply\":188,\"robust-orientation\":75,\"split-polygon\":76}],51:[function(t,e,r){\"use strict\";function n(t){return t[0]=t[1]=t[2]=0,t}function i(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function a(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}function o(t,e,r){var n=[],i=[0,0,0],o=[0,0,0],c=[0,0,0],f=[0,0,0];n.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var h=0;3>h;++h){for(var p=n.length/3|0,d=0;d<r[h].length;++d){var g=+r[h][d].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=n.length/3|0;i[h]=p,o[h]=v-p;for(var p=n.length/3|0,m=0;m<r[h].length;++m){var g=+r[h][m].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=n.length/3|0;c[h]=p,f[h]=v-p}var y=s(t,new Float32Array(n)),b=l(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),x=u(t);return x.attributes.position.location=0,new a(t,y,b,x,o,i,f,c)}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders\").line,c=[0,0,0],f=[0,0,0],h=[0,0,0],p=[0,0,0],d=[1,1],g=a.prototype;g.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,d[0]=this.gl.drawingBufferWidth,d[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=d,this.vao.bind()},g.drawAxisLine=function(t,e,r,a,o){var s=n(f);this.shader.uniforms.majorAxis=f,s[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=s;var l=i(p,r);l[t]+=e[0][t],this.shader.uniforms.offset=l,this.shader.uniforms.lineWidth=o,this.shader.uniforms.color=a;var u=n(h);u[(t+2)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6);var u=n(h);u[(t+1)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6)},g.drawAxisTicks=function(t,e,r,i,a){var o=n(c);o[t]=1,this.shader.uniforms.majorAxis=o,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=i,this.shader.uniforms.lineWidth=a;var s=n(h);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])},g.drawGrid=function(t,e,r,a,o,s){var l=n(f);l[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=l;var u=i(p,a);u[e]+=r[0][e],this.shader.uniforms.offset=u;var d=n(c);d[t]=1,this.shader.uniforms.majorAxis=d;var g=n(h);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])},g.drawZero=function(t,e,r,a,o,s){var l=n(f);this.shader.uniforms.majorAxis=l,l[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=l;var u=i(p,a);u[t]+=r[0][t],this.shader.uniforms.offset=u;var c=n(h);c[e]=1,this.shader.uniforms.screenAxis=c,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,6)},g.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":52,\"gl-buffer\":58,\"gl-vao\":68}],52:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.line=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"}])};var o=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvoid main() {  \\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n  mat2 planeXform = scale * mat2(cos(angle), sin(angle),\\n                                -sin(angle), cos(angle));\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n  vec4 worldPosition = model * vec4(dataPosition, 1);\\n  \\n  //Compute clip position\\n  vec4 viewPosition = view * worldPosition;\\n  vec4 clipPosition = projection * viewPosition;\\n  clipPosition /= clipPosition.w;\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec4(viewOffset, 0, 0);\\n\\n  //Done\\n  gl_Position = clipPosition;\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.text=function(t){return n(t,o,s,null,[{name:\"position\",type:\"vec3\"}])};var l=\"#define GLSLIFY 1\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  if(dot(normal, enable) > 0.0) {\\n    vec3 nPosition = mix(bounds[0], bounds[1], 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n  colorChannel = abs(normal);\\n}\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] + \\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\";r.bg=function(t){return n(t,l,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":206}],53:[function(t,e,r){(function(r){\"use strict\";function n(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}function i(t,e){try{return l(t,e)}catch(r){return console.warn(\"error vectorizing text:\",r),{cells:[],positions:[]}}}function a(t,e,r,i,a,l){var c=o(t),f=s(t,[{buffer:c,size:3}]),h=u(t);h.attributes.position.location=0;var p=new n(t,h,c,f);return p.update(e,r,i,a,l),p}e.exports=a;var o=t(\"gl-buffer\"),s=t(\"gl-vao\"),l=t(\"vectorize-text\"),u=t(\"./shaders\").text,c=window||r.global||{},f=c.__TEXT_CACHE||{};c.__TEXT_CACHE={};var h=3,p=n.prototype,d=[0,0];p.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,d[0]=this.gl.drawingBufferWidth,d[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=d},p.update=function(t,e,r,n,a){function o(t,e,r,n){var a=f[r];a||(a=f[r]={});var o=a[e];o||(o=a[e]=i(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\"}));for(var l=(n||12)/12,u=o.positions,c=o.cells,h=0,p=c.length;p>h;++h)for(var d=c[h],g=2;g>=0;--g){var v=u[d[g]];s.push(l*v[0],-l*v[1],t)}}for(var s=(this.gl,[]),l=[0,0,0],u=[0,0,0],c=[0,0,0],p=[0,0,0],d=0;3>d;++d){c[d]=s.length/h|0,o(.5*(t[0][d]+t[1][d]),e[d],r),p[d]=(s.length/h|0)-c[d],l[d]=s.length/h|0;for(var g=0;g<n[d].length;++g)n[d][g].text&&o(n[d][g].x,n[d][g].text,n[d][g].font||a,n[d][g].fontSize||12);u[d]=(s.length/h|0)-l[d]}this.buffer.update(s),this.tickOffset=l,this.tickCount=u,this.labelOffset=c,this.labelCount=p};var 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e?this.words[n]=this.words[n]|1<<i:this.words[n]=this.words[n]&~(1<<i),this.strip()},i.prototype.iadd=function(t){if(this.sign&&!t.sign){this.sign=!1;var e=this.isub(t);return this.sign=!this.sign,this._normSign()}if(!this.sign&&t.sign){t.sign=!1;var e=this.isub(t);return t.sign=!0,e._normSign()}var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++){var e=r.words[a]+n.words[a]+i;this.words[a]=67108863&e,i=e>>>26}for(;0!==i&&a<r.length;a++){var e=r.words[a]+i;this.words[a]=67108863&e,i=e>>>26}if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},i.prototype.add=function(t){if(t.sign&&!this.sign){t.sign=!1;var e=this.sub(t);return t.sign=!0,e}if(!t.sign&&this.sign){this.sign=!1;var e=t.sub(this);return this.sign=!0,e}return this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(t.sign){t.sign=!1;var e=this.iadd(t);return t.sign=!0,e._normSign()}if(this.sign)return this.sign=!1,this.iadd(t),this.sign=!0,this._normSign();var r=this.cmp(t);if(0===r)return this.sign=!1,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++){var e=n.words[o]-i.words[o]+a;a=e>>26,this.words[o]=67108863&e}for(;0!==a&&o<n.length;o++){var e=n.words[o]+a;a=e>>26,this.words[o]=67108863&e}if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.sign=!0),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)},i.prototype._smallMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0;n<e.length-1;n++){for(var i=r>>>26,a=67108863&r,o=Math.min(n,t.length-1),s=Math.max(0,n-this.length+1);o>=s;s++){var l=n-s,u=0|this.words[l],c=0|t.words[s],f=u*c,h=67108863&f;i=i+(f/67108864|0)|0,h=h+a|0,a=67108863&h,i=i+(h>>>26)|0}e.words[n]=a,r=i}return 0!==r?e.words[n]=r:e.length--,e.strip()},i.prototype._bigMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0,i=0;i<e.length-1;i++){var a=n;n=0;for(var o=67108863&r,s=Math.min(i,t.length-1),l=Math.max(0,i-this.length+1);s>=l;l++){var u=i-l,c=0|this.words[u],f=0|t.words[l],h=c*f,p=67108863&h;a=a+(h/67108864|0)|0,p=p+o|0,o=67108863&p,a=a+(p>>>26)|0,n+=a>>>26,a&=67108863}e.words[i]=o,r=a,a=n}return 0!==r?e.words[i]=r:e.length--,e.strip()},i.prototype.mulTo=function(t,e){var r;return r=this.length+t.length<63?this._smallMulTo(t,e):this._bigMulTo(t,e)},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.imul=function(t){if(0===this.cmpn(0)||0===t.cmpn(0))return this.words[0]=0,this.length=1,this;var e=this.length,r=t.length;this.sign=t.sign!==this.sign,this.length=this.length+t.length,this.words[this.length-1]=0;for(var n=this.length-2;n>=0;n--){for(var i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);o>=s;s++){var l=n-s,u=this.words[l],c=t.words[s],f=u*c,h=67108863&f;i+=f/67108864|0,h+=a,a=67108863&h,i+=h>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var p=this.words[l]+i;this.words[l]=67108863&p,i=p>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var o=this.length-1;o>=0;o--)this.words[o+n]=this.words[o];for(var o=0;n>o;o++)this.words[o]=0;this.length+=n}return this.strip()},i.prototype.ishrn=function(t,e,n){r(\"number\"==typeof t&&t>=0);var i;i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=n;if(i-=o,i=Math.max(0,i),l){for(var u=0;o>u;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o){this.length-=o;for(var u=0;u<this.length;u++)this.words[u]=this.words[u+o]}else this.words[0]=0,this.length=1;for(var c=0,u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip(),this},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.testn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n)return!1;var a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),0>t?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],\n",
+       "this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),0>t)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(-1===s),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var f=n.clone()._ishlnsubmul(a,1,u);f.sign||(n=f,l&&(l.words[u]=1));for(var h=u-1;h>=0;h--){var p=67108864*n.words[a.length+h]+n.words[a.length+h-1];for(p=Math.min(p/o|0,67108863),n._ishlnsubmul(a,p,h);n.sign;)p--,n.sign=!1,n._ishlnsubmul(a,1,h),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[h]=p)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return 0>a||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(67108863>=t);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(67108863>=t);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),f=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(f).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(f).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(0>i){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;n+1>a;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=0>t;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:t>n?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){i>n?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new h(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;n>i;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(f,s),f.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function y(t){if(m[t])return m[t];var y;if(\"k256\"===t)y=new l;else if(\"p224\"===t)y=new u;else if(\"p192\"===t)y=new c;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);y=new f}return m[t]=y,y},h.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},h.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},h.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},h.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},h.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},h.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},h.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},h.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},h.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},h.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},h.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},h.prototype.isqr=function(t){return this.imul(t,t)},h.prototype.sqr=function(t){return this.mul(t,t)},h.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),f=this.m.bitLength();for(f=new i(2*f*f).toRed(this);0!==this.pow(f,c).cmp(u);)f.redIAdd(u);for(var h=this.pow(f,o),a=this.pow(t,o.addn(1).ishrn(1)),p=this.pow(t,o),d=s;0!==p.cmp(l);){for(var 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2146435072&n&&(i+=1<<20),[r,i]},e.exports.denormalized=function(t){var r=e.exports.hi(t);return!(2146435072&r)}}).call(this,t(\"buffer\").Buffer)},{buffer:300}],111:[function(t,e,r){\"use strict\";function n(t){return i(t[0])*i(t[1])}var i=t(\"./lib/bn-sign\");e.exports=n},{\"./lib/bn-sign\":101}],112:[function(t,e,r){\"use strict\";function n(t,e){return i(t[0].mul(e[1]).sub(t[1].mul(e[0])),t[1].mul(e[1]))}var i=t(\"./lib/rationalize\");e.exports=n},{\"./lib/rationalize\":106}],113:[function(t,e,r){\"use strict\";function n(t){var e=t[0],r=t[1];if(0===e.cmpn(0))return 0;var n=e.divmod(r),o=n.div,s=i(o),l=n.mod;if(0===l.cmpn(0))return s;if(s){var u=a(s)+4,c=i(l.shln(u).divRound(r));return 0>s&&(c=-c),s+c*Math.pow(2,-u)}var f=r.bitLength()-l.bitLength()+53,c=i(l.shln(f).divRound(r));return 1023>f?c*Math.pow(2,-f):(c*=Math.pow(2,-1023),c*Math.pow(2,1023-f))}var i=t(\"./lib/bn-to-num\"),a=t(\"./lib/ctz\");e.exports=n},{\"./lib/bn-to-num\":102,\"./lib/ctz\":103}],114:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0;t>r;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function i(t,e,r,i){for(var a=0,o=0,s=0,l=t.length;l>s;++s){var u=t[s];if(!n(e,u)){for(var c=0;2*e>c;++c)r[a++]=u[c];i[o++]=s}}return o}function a(t,e,r,n){var a=t.length,o=e.length;if(!(0>=a||0>=o)){var s=t[0].length>>>1;if(!(0>=s)){var l,u=f.mallocDouble(2*s*a),c=f.mallocInt32(a);if(a=i(t,s,u,c),a>0){if(1===s&&n)h.init(a),l=h.sweepComplete(s,r,0,a,u,c,0,a,u,c);else{var d=f.mallocDouble(2*s*o),g=f.mallocInt32(o);o=i(e,s,d,g),o>0&&(h.init(a+o),l=1===s?h.sweepBipartite(s,r,0,a,u,c,0,o,d,g):p(s,r,n,a,u,c,o,d,g),f.free(d),f.free(g))}f.free(u),f.free(c)}return l}}}function o(t,e){c.push([t,e])}function s(t){return c=[],a(t,t,o,!0),c}function l(t,e){return c=[],a(t,e,o,!1),c}function u(t,e,r){switch(arguments.length){case 1:return s(t);case 2:return\"function\"==typeof e?a(t,t,e,!0):l(t,e);case 3:return a(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}}e.exports=u;var c,f=t(\"typedarray-pool\"),h=t(\"./lib/sweep\"),p=t(\"./lib/intersect\")},{\"./lib/intersect\":116,\"./lib/sweep\":120,\"typedarray-pool\":121}],115:[function(t,e,r){\"use strict\";function n(t,e,r){var n=\"bruteForce\"+(t?\"Red\":\"Blue\")+(e?\"Flip\":\"\")+(r?\"Full\":\"\"),i=[\"function \",n,\"(\",w.join(),\"){\",\"var \",u,\"=2*\",a,\";\"],l=\"for(var i=\"+c+\",\"+d+\"=\"+u+\"*\"+c+\";i<\"+f+\";++i,\"+d+\"+=\"+u+\"){var x0=\"+h+\"[\"+o+\"+\"+d+\"],x1=\"+h+\"[\"+o+\"+\"+d+\"+\"+a+\"],xi=\"+p+\"[i];\",k=\"for(var j=\"+g+\",\"+b+\"=\"+u+\"*\"+g+\";j<\"+v+\";++j,\"+b+\"+=\"+u+\"){var y0=\"+m+\"[\"+o+\"+\"+b+\"],\"+(r?\"y1=\"+m+\"[\"+o+\"+\"+b+\"+\"+a+\"],\":\"\")+\"yi=\"+y+\"[j];\";return t?i.push(l,_,\":\",k):i.push(k,_,\":\",l),r?i.push(\"if(y1<x0||x1<y0)continue;\"):e?i.push(\"if(y0<=x0||x1<y0)continue;\"):i.push(\"if(y0<x0||x1<y0)continue;\"),i.push(\"for(var k=\"+o+\"+1;k<\"+a+\";++k){var 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e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":179}],171:[function(t,e,r){arguments[4][34][0].apply(r,arguments)},{\"cwise-compiler\":172,dup:34}],172:[function(t,e,r){arguments[4][35][0].apply(r,arguments)},{\"./lib/thunk.js\":174,dup:35}],173:[function(t,e,r){arguments[4][36][0].apply(r,arguments)},{dup:36,uniq:175}],174:[function(t,e,r){arguments[4][37][0].apply(r,arguments)},{\"./compile.js\":173,dup:37}],175:[function(t,e,r){arguments[4][38][0].apply(r,arguments)},{dup:38}],176:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],177:[function(t,e,r){arguments[4][40][0].apply(r,arguments)},{dup:40}],178:[function(t,e,r){arguments[4][41][0].apply(r,arguments)},{\"bit-twiddle\":176,buffer:300,dup:41}],179:[function(t,e,r){\"use strict\";function 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s=o(n,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,s=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,s=!1,r=\"uint8\");var c=0;if(2===n.length)c=t.LUMINANCE,n=[n[0],n[1],1],e=p(e.data,n,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==n.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===n[2])c=t.ALPHA;else if(2===n[2])c=t.LUMINANCE_ALPHA;else if(3===n[2])c=t.RGB;else{if(4!==n[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");c=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,s=!1);var f,h,v=e.size;if(s)f=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var m=[n[2],n[2]*n[0],1];h=g.malloc(v,r);var y=p(h,n,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?d.assign(y,e):b(y,e),f=h.subarray(0,v)}var x=l(t);return t.texImage2D(t.TEXTURE_2D,0,c,n[0],n[1],0,c,u,f),s||g.free(h),new a(t,x,n[0],n[1],c,u)}function h(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(v||n(t),\"number\"==typeof arguments[1])return u(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return u(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1];if(e instanceof HTMLCanvasElement||e instanceof HTMLImageElement||e instanceof HTMLVideoElement||e instanceof ImageData)return c(t,e,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return f(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")}var p=t(\"ndarray\"),d=t(\"ndarray-ops\"),g=t(\"typedarray-pool\");e.exports=h;var v=null,m=null,y=null,b=function(t,e){d.muls(t,e,255)},x=a.prototype;Object.defineProperties(x,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&v.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),m.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&v.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),m.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;2>e;++e)if(y.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return i(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return t=0|t,i(this,t,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t=0|t,i(this,this._shape[0],t),t}}}),x.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},x.dispose=function(){this.gl.deleteTexture(this.handle)},x.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},x.setPixels=function(t,e,r,n){var i=this.gl;if(this.bind(),Array.isArray(e)?(n=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),n=n||0,t instanceof HTMLCanvasElement||t instanceof ImageData||t instanceof HTMLImageElement||t instanceof HTMLVideoElement){var a=this._mipLevels.indexOf(n)<0;a?(i.texImage2D(i.TEXTURE_2D,0,this.format,this.format,this.type,t),this._mipLevels.push(n)):i.texSubImage2D(i.TEXTURE_2D,n,e,r,this.format,this.type,t)}else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>n||r+t.shape[0]>this._shape[0]>>>n||0>e||0>r)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");s(i,e,r,n,this.format,this.type,this._mipLevels,t)}}},{ndarray:247,\"ndarray-ops\":171,\"typedarray-pool\":178}],180:[function(t,e,r){function n(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}e.exports=n},{}],181:[function(t,e,r){function n(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],182:[function(t,e,r){function n(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],f=t[10],h=t[11],p=t[12],d=t[13],g=t[14],v=t[15],m=e*o-r*a,y=e*s-n*a,b=e*l-i*a,x=r*s-n*o,_=r*l-i*o,w=n*l-i*s,k=u*d-c*p,A=u*g-f*p,M=u*v-h*p,T=c*g-f*d,E=c*v-h*d,L=f*v-h*g;return m*L-y*E+b*T+x*M-_*A+w*k}e.exports=n},{}],183:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,f=n*s,h=i*o,p=i*s,d=i*l,g=a*o,v=a*s,m=a*l;return t[0]=1-f-d,t[1]=c+m,t[2]=h-v,t[3]=0,t[4]=c-m,t[5]=1-u-d,t[6]=p+g,t[7]=0,t[8]=h+v,t[9]=p-g,t[10]=1-u-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],184:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,f=n*l,h=n*u,p=i*l,d=i*u,g=a*u,v=o*s,m=o*l,y=o*u;return t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(c+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],185:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],186:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,k=i*u-a*l,A=c*g-f*d,M=c*v-h*d,T=c*m-p*d,E=f*v-h*g,L=f*m-p*g,S=h*m-p*v,C=y*S-b*L+x*E+_*T-w*M+k*A;return C?(C=1/C,t[0]=(s*S-l*L+u*E)*C,t[1]=(i*L-n*S-a*E)*C,t[2]=(g*k-v*w+m*_)*C,t[3]=(h*w-f*k-p*_)*C,t[4]=(l*T-o*S-u*M)*C,t[5]=(r*S-i*T+a*M)*C,t[6]=(v*x-d*k-m*b)*C,t[7]=(c*k-h*x+p*b)*C,t[8]=(o*L-s*T+u*A)*C,t[9]=(n*T-r*L-a*A)*C,t[10]=(d*w-g*x+m*y)*C,t[11]=(f*x-c*w-p*y)*C,t[12]=(s*M-o*E-l*A)*C,t[13]=(r*E-n*M+i*A)*C,t[14]=(g*b-d*_-v*y)*C,t[15]=(c*_-f*b+h*y)*C,t):null}e.exports=n},{}],187:[function(t,e,r){function n(t,e,r,n){var a,o,s,l,u,c,f,h,p,d,g=e[0],v=e[1],m=e[2],y=n[0],b=n[1],x=n[2],_=r[0],w=r[1],k=r[2];return Math.abs(g-_)<1e-6&&Math.abs(v-w)<1e-6&&Math.abs(m-k)<1e-6?i(t):(f=g-_,h=v-w,p=m-k,d=1/Math.sqrt(f*f+h*h+p*p),f*=d,h*=d,p*=d,a=b*p-x*h,o=x*f-y*p,s=y*h-b*f,d=Math.sqrt(a*a+o*o+s*s),d?(d=1/d,a*=d,o*=d,s*=d):(a=0,o=0,s=0),l=h*s-p*o,u=p*a-f*s,c=f*o-h*a,d=Math.sqrt(l*l+u*u+c*c),d?(d=1/d,l*=d,u*=d,c*=d):(l=0,u=0,c=0),t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=u,t[6]=h,t[7]=0,t[8]=s,t[9]=c,t[10]=p,t[11]=0,t[12]=-(a*g+o*v+s*m),t[13]=-(l*g+u*v+c*m),t[14]=-(f*g+h*v+p*m),t[15]=1,t)}var i=t(\"./identity\");e.exports=n},{\"./identity\":185}],188:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*f+w*g,t[1]=b*i+x*l+_*h+w*v,t[2]=b*a+x*u+_*p+w*m,t[3]=b*o+x*c+_*d+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*f+w*g,t[5]=b*i+x*l+_*h+w*v,t[6]=b*a+x*u+_*p+w*m,t[7]=b*o+x*c+_*d+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*f+w*g,t[9]=b*i+x*l+_*h+w*v,t[10]=b*a+x*u+_*p+w*m,t[11]=b*o+x*c+_*d+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*f+w*g,t[13]=b*i+x*l+_*h+w*v,t[14]=b*a+x*u+_*p+w*m,t[15]=b*o+x*c+_*d+w*y,t}e.exports=n},{}],189:[function(t,e,r){function n(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}e.exports=n},{}],190:[function(t,e,r){function n(t,e,r,n){var i,a,o,s,l,u,c,f,h,p,d,g,v,m,y,b,x,_,w,k,A,M,T,E,L=n[0],S=n[1],C=n[2],P=Math.sqrt(L*L+S*S+C*C);return Math.abs(P)<1e-6?null:(P=1/P,L*=P,S*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],u=e[2],c=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],v=e[9],m=e[10],y=e[11],b=L*L*o+a,x=S*L*o+C*i,_=C*L*o-S*i,w=L*S*o-C*i,k=S*S*o+a,A=C*S*o+L*i,M=L*C*o+S*i,T=S*C*o-L*i,E=C*C*o+a,t[0]=s*b+f*x+g*_,t[1]=l*b+h*x+v*_,t[2]=u*b+p*x+m*_,t[3]=c*b+d*x+y*_,t[4]=s*w+f*k+g*A,t[5]=l*w+h*k+v*A,t[6]=u*w+p*k+m*A,t[7]=c*w+d*k+y*A,t[8]=s*M+f*T+g*E,t[9]=l*M+h*T+v*E,t[10]=u*M+p*T+m*E,t[11]=c*M+d*T+y*E,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)}e.exports=n},{}],191:[function(t,e,r){function n(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[4]=a*i+u*n,t[5]=o*i+c*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=u*i-a*n,t[9]=c*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}e.exports=n},{}],192:[function(t,e,r){function n(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}e.exports=n},{}],193:[function(t,e,r){function n(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],f=e[6],h=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],\n",
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u=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]],c=n.prototype;c.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[1,1];return function(){var r=this.plot,n=this.shader,i=this.buffer,a=this.bounds,o=this.numPoints,s=(this.color,r.gl),l=r.dataBox,c=r.viewBox,f=r.pixelRatio,h=a[2]-a[0],p=a[3]-a[1],d=l[2]-l[0],g=l[3]-l[1];t[0]=2*h/d,t[4]=2*p/g,t[6]=2*(a[0]-l[0])/d-1,t[7]=2*(a[1]-l[1])/g-1;var v=c[2]-c[0],m=c[3]-c[1];e[0]=2*f/v,e[1]=2*f/m,i.bind(),n.bind(),n.uniforms.viewTransform=t,n.uniforms.pixelScale=e,n.uniforms.color=this.color,n.attributes.position.pointer(s.FLOAT,!1,16,0),n.attributes.pixelOffset.pointer(s.FLOAT,!1,16,8),s.drawArrays(s.TRIANGLES,0,o*u.length)}}(),c.drawPick=function(t){return t},c.pick=function(t,e){return null},c.update=function(t){t=t||{};var e=t.positions||[],r=t.errors||[],n=1;\"lineWidth\"in t&&(n=+t.lineWidth);var i=5;\"capSize\"in t&&(i=+t.capSize),this.color=(t.color||[0,0,0,1]).slice();for(var a=this.bounds=[1/0,1/0,-(1/0),-(1/0)],o=this.numPoints=e.length>>1,l=0;o>l;++l){var c=e[2*l],f=e[2*l+1];a[0]=Math.min(c,a[0]),a[1]=Math.min(f,a[1]),a[2]=Math.max(c,a[2]),a[3]=Math.max(f,a[3])}a[2]===a[0]&&(a[2]+=1),a[3]===a[1]&&(a[3]+=1);for(var h=1/(a[2]-a[0]),p=1/(a[3]-a[1]),d=a[0],g=a[1],v=s.mallocFloat32(o*u.length*4),m=0,l=0;o>l;++l)for(var c=e[2*l],f=e[2*l+1],y=r[4*l],b=r[4*l+1],x=r[4*l+2],_=r[4*l+3],w=0;w<u.length;++w){var k=u[w],A=k[0],M=k[1];0>A?A*=y:A>0&&(A*=b),0>M?M*=x:M>0&&(M*=_),v[m++]=h*(c-d+A),v[m++]=p*(f-g+M),v[m++]=n*k[2]+(i+n)*k[4],v[m++]=n*k[3]+(i+n)*k[5]}this.buffer.update(v),s.free(v)},c.dispose=function(){this.plot.removeObject(this),this.shader.dispose(),this.buffer.dispose()}},{\"./lib/shaders\":327,\"gl-buffer\":325,\"gl-shader\":385,\"typedarray-pool\":463}],327:[function(t,e,r){e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 pixelOffset;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvoid main() {\\n  vec3 scrPosition = viewTransform * vec3(position, 1);\\n  gl_Position = vec4(\\n    scrPosition.xy + scrPosition.z * pixelScale * pixelOffset,\\n    0,\\n    scrPosition.z);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"}},{}],328:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;3>r;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=h[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],f=n.prototype;f.isOpaque=function(){return this.opacity>=1},f.isTransparent=function(){return this.opacity<1},f.drawTransparent=f.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var f=0;3>f;++f)e.lineWidth(this.lineWidth[f]),r.capSize=this.capSize[f]*u,e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var h=function(){for(var t=new Array(3),e=0;3>e;++e){for(var r=[],n=1;2>=n;++n)for(var i=-1;1>=i;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();f.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;3>u;++u){this.lineOffset[u]=l;t:for(var c=0;s>c;++c){for(var f=r[c],h=0;3>h;++h)if(isNaN(f[h])||!isFinite(f[h]))continue t;var p=n[c],d=e[u];if(Array.isArray(d[0])&&(d=e[c]),3===d.length&&(d=[d[0],d[1],d[2],1]),!isNaN(p[0][u])&&!isNaN(p[1][u])){if(p[0][u]<0){var g=f.slice();g[u]+=p[0][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}if(p[1][u]>0){var g=f.slice();g[u]+=p[1][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},f.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":329,\"gl-buffer\":325,\"gl-vao\":420}],329:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":385}],330:[function(t,e,r){arguments[4][170][0].apply(r,arguments)},{dup:170,\"gl-texture2d\":416}],331:[function(t,e,r){r.lineVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  vec2 dir = (matrix * vec3(d, 0)).xy;\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = 0.5 * width *\\n    normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n}\\n\",r.lineFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\\n\",r.mitreVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 p;\\n\\nuniform mat3  matrix;\\nuniform vec2 screenShape;\\nuniform float radius;\\n\\nvoid main() {\\n  vec3 pp = matrix * vec3(p, 1);\\n  gl_Position  = vec4(pp.xy, 0, pp.z);\\n  gl_PointSize = radius;\\n}\\n\",r.mitreFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\nattribute vec4 pick0, pick1;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = width *\\n    normalize(screenShape.yx * vec2(d.y, -d.x)) / screenShape.xy;\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\\n\",r.fillVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 projectAxis;\\nuniform float projectValue;\\nuniform float depth;\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 p = base.xy / base.z;\\n  if(d.y < 0.0 || (d.y == 0.0 && d.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\\n\",r.fillFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"},{}],332:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.dashPattern=e,this.lineBuffer=r,this.pickBuffer=n,this.lineShader=i,this.mitreShader=a,this.fillShader=o,this.pickShader=s,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0,this.lodBuffer=[]}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=l(r,[1,1]),c=o(r,f.lineVertex,f.lineFragment),h=o(r,f.mitreVertex,f.mitreFragment),p=o(r,f.fillVertex,f.fillFragment),d=o(r,f.pickVertex,f.pickFragment),g=new n(t,u,i,a,c,h,p,d);return t.addObject(g),g.update(e),g}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),f=t(\"./lib/shaders\"),h=n.prototype;h.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[1,0],n=[-1,0],i=[0,1],a=[0,-1];return function(){var o=this.plot,s=this.color,l=this.width,u=(this.numPoints,this.bounds),c=this.vertCount,f=o.gl,h=o.viewBox,p=o.dataBox,d=o.pixelRatio,g=u[2]-u[0],v=u[3]-u[1],m=p[2]-p[0],y=p[3]-p[1],b=h[2]-h[0],x=h[3]-h[1];t[0]=2*g/m,t[4]=2*v/y,t[6]=2*(u[0]-p[0])/m-1,t[7]=2*(u[1]-p[1])/y-1,e[0]=b,e[1]=x;var _=this.lineBuffer;_.bind();var w=this.fill;if(w[0]||w[1]||w[2]||w[3]){var k=this.fillShader;k.bind();var A=k.uniforms;A.matrix=t,A.depth=o.nextDepthValue();var M=k.attributes;M.a.pointer(f.FLOAT,!1,16,0),M.d.pointer(f.FLOAT,!1,16,8),f.depthMask(!0),f.enable(f.DEPTH_TEST);var T=this.fillColor;w[0]&&(A.color=T[0],A.projectAxis=n,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[1]&&(A.color=T[1],A.projectAxis=a,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[2]&&(A.color=T[2],A.projectAxis=r,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[3]&&(A.color=T[3],A.projectAxis=i,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),f.depthMask(!1),f.disable(f.DEPTH_TEST)}var E=this.lineShader;E.bind();var L=E.uniforms;L.matrix=t,L.color=s,L.width=l*d,L.screenShape=e,L.dashPattern=this.dashPattern.bind(),L.dashLength=this.dashLength*d;var S=E.attributes;if(S.a.pointer(f.FLOAT,!1,16,0),S.d.pointer(f.FLOAT,!1,16,8),f.drawArrays(f.TRIANGLES,0,c),l>2&&!this.usingDashes){var C=this.mitreShader;C.bind();var P=C.uniforms;P.matrix=t,P.color=s,P.screenShape=e,P.radius=l*d,C.attributes.p.pointer(f.FLOAT,!1,48,0),f.drawArrays(f.POINTS,0,c/3|0)}}}(),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[0,0,0,0];return function(n){var i=this.plot,a=this.pickShader,o=this.lineBuffer,s=this.pickBuffer,l=this.width,u=this.numPoints,c=this.bounds,f=this.vertCount,h=i.gl,p=i.viewBox,d=i.dataBox,g=i.pickPixelRatio,v=c[2]-c[0],m=c[3]-c[1],y=d[2]-d[0],b=d[3]-d[1],x=p[2]-p[0],_=p[3]-p[1];\n",
+       "this.pickOffset=n,t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(c[0]-d[0])/y-1,t[7]=2*(c[1]-d[1])/b-1,e[0]=x,e[1]=_,r[0]=255&n,r[1]=n>>>8&255,r[2]=n>>>16&255,r[3]=n>>>24,a.bind();var w=a.uniforms;w.matrix=t,w.width=l*g,w.pickOffset=r,w.screenShape=e;var k=a.attributes;return o.bind(),k.a.pointer(h.FLOAT,!1,16,0),k.d.pointer(h.FLOAT,!1,16,8),s.bind(),k.pick0.pointer(h.UNSIGNED_BYTE,!1,8,0),k.pick1.pointer(h.UNSIGNED_BYTE,!1,8,4),h.drawArrays(h.TRIANGLES,0,f),n+u}}(),h.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},h.update=function(t){t=t||{};var e=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);for(var r=t.dashes||[1],n=0,a=0;a<r.length;++a)n+=r[a];for(var o=c.mallocUint8(n),s=0,f=255,a=0;a<r.length;++a){for(var h=0;h<r[a];++h)o[s++]=f;f^=255}this.dashPattern.dispose(),this.usingDashes=r.length>1,this.dashPattern=l(e,u(o,[n,1,4],[1,0,0])),this.dashPattern.minFilter=e.NEAREST,this.dashPattern.magFilter=e.NEAREST,this.dashLength=n,c.free(o);var p=t.positions;this.data=p;var d=this.bounds;d[0]=d[1]=1/0,d[2]=d[3]=-(1/0);var g=this.numPoints=p.length>>>1;if(0!==g){for(var a=0;g>a;++a){var v=p[2*a],m=p[2*a+1];d[0]=Math.min(d[0],v),d[1]=Math.min(d[1],m),d[2]=Math.max(d[2],v),d[3]=Math.max(d[3],m)}d[0]===d[2]&&(d[2]+=1),d[3]===d[1]&&(d[3]+=1);var y=c.mallocFloat32(24*(g-1)),b=c.mallocUint32(12*(g-1)),x=y.length,_=b.length,s=g;for(this.vertCount=6*(g-1);s>1;){var w=--s,v=p[2*s],m=p[2*s+1];v=(v-d[0])/(d[2]-d[0]),m=(m-d[1])/(d[3]-d[1]);var k=w-1,A=p[2*k],M=p[2*k+1];A=(A-d[0])/(d[2]-d[0]),M=(M-d[1])/(d[3]-d[1]);var T=A-v,E=M-m,L=w|1<<24,S=w-1,C=w,P=w-1|1<<24;y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S}this.lineBuffer.update(y),this.pickBuffer.update(b),c.free(y),c.free(b)}},h.dispose=function(){this.plot.removeObject(this),this.lineBuffer.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":331,\"gl-buffer\":325,\"gl-shader\":385,\"gl-texture2d\":416,ndarray:438,\"typedarray-pool\":463}],333:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":385}],334:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;3>n;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;3>r;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=v(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=p(new Array(1024),[256,1,4]),f=0;1024>f;++f)s.data[f]=255;var h=c(e,s);h.wrap=e.REPEAT;var d=new o(e,r,n,i,a,h);return d.update(t),d}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),f=t(\"glsl-read-float\"),h=t(\"binary-search-bounds\"),p=t(\"ndarray\"),d=t(\"./lib/shaders\"),g=d.createShader,v=d.createPickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){this.dirty=!0,\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var e=t.position||t.positions;if(e){var r=t.color||t.colors||[0,0,0,1],i=t.lineWidth||1,a=[],o=[],s=[],l=0,u=0,c=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];t:for(var f=1;f<e.length;++f){var d=e[f-1],g=e[f];o.push(l),s.push(d.slice());for(var v=0;3>v;++v){if(isNaN(d[v])||isNaN(g[v])||!isFinite(d[v])||!isFinite(g[v]))continue t;c[0][v]=Math.min(c[0][v],d[v],g[v]),c[1][v]=Math.max(c[1][v],d[v],g[v])}var m,y;Array.isArray(r[0])?(m=r[f-1],y=r[f]):m=y=r,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]);var b,x;Array.isArray(i)?(b=i[f-1],x=lineWidht[f]):b=x=i;var _=l;l+=n(d,g),a.push(d[0],d[1],d[2],g[0],g[1],g[2],_,b,m[0],m[1],m[2],m[3],d[0],d[1],d[2],g[0],g[1],g[2],_,-b,m[0],m[1],m[2],m[3],g[0],g[1],g[2],d[0],d[1],d[2],l,-b,y[0],y[1],y[2],y[3],g[0],g[1],g[2],d[0],d[1],d[2],l,b,y[0],y[1],y[2],y[3]),u+=4}if(this.buffer.update(a),o.push(l),s.push(e[e.length-1].slice()),this.bounds=c,this.vertexCount=u,this.points=s,this.arcLength=o,\"dashes\"in t){var w=t.dashes,k=w.slice();k.unshift(0);for(var f=1;f<k.length;++f)k[f]=k[f-1]+k[f];for(var A=p(new Array(1024),[256,1,4]),f=0;256>f;++f){for(var v=0;4>v;++v)A.set(f,0,v,0);1&h.le(k,k[k.length-1]*f/255)?A.set(f,0,0,0):A.set(f,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=f(t.value[0],t.value[1],t.value[2],0),r=h.le(this.arcLength,e);if(0>r)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;3>u;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(.5>o?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":333,\"binary-search-bounds\":335,\"gl-buffer\":325,\"gl-texture2d\":416,\"gl-vao\":420,\"glsl-read-float\":336,ndarray:438}],335:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],336:[function(t,e,r){function n(t,e,r,n){return i[0]=n,i[1]=r,i[2]=e,i[3]=t,a[0]}e.exports=n;var i=new Uint8Array(4),a=new Float32Array(i.buffer)},{}],337:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=c*o-s*u,h=-c*a+s*l,p=u*a-o*l,d=r*f+n*h+i*p;return 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l=t(\"barycentric\"),u=t(\"polytope-closest-point/lib/closest_point_2d.js\");e.exports=s},{barycentric:357,\"polytope-closest-point/lib/closest_point_2d.js\":359}],355:[function(t,e,r){var n=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * 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h=n[f][0],p=n[f][1],d=i[f],g=1-d,v=this.positions[h],m=this.positions[p],y=0;3>y;++y)o[s++]=d*v[y]+g*m[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),A.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"opacity\"in t&&(this.opacity=t.opacity),t.texture?(this.texture.dispose(),this.texture=m(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],f=[],h=[],p=[],d=[],g=[],v=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var k=t.vertexNormals,A=t.cellNormals;t.useFacetNormals&&!A&&(A=y.faceNormals(r,n)),A||k||(k=y.vertexNormals(r,n));var M=t.vertexColors,T=t.cellColors,E=t.meshColor||[1,1,1,1],L=t.vertexUVs,S=t.vertexIntensity,C=t.cellUVs,P=t.cellIntensity,z=1/0,R=-(1/0);if(!L&&!C)if(S)for(var O=0;O<S.length;++O){var I=S[O];z=Math.min(z,I),R=Math.max(R,I)}else if(P)for(var O=0;O<P.length;++O){var I=P[O];z=Math.min(z,I),R=Math.max(R,I)}else for(var O=0;O<n.length;++O){var I=n[O][2];z=Math.min(z,I),R=Math.max(R,I)}S?this.intensity=S:P?this.intensity=a(r,n.length,P):this.intensity=o(n);var j=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var O=0;O<n.length;++O)for(var F=n[O],D=0;3>D;++D)!isNaN(F[D])&&isFinite(F[D])&&(this.bounds[0][D]=Math.min(this.bounds[0][D],F[D]),this.bounds[1][D]=Math.max(this.bounds[1][D],F[D]));var B=0,U=0,V=0;t:for(var O=0;O<r.length;++O){var q=r[O];switch(q.length){case 1:for(var H=q[0],F=n[H],D=0;3>D;++D)if(isNaN(F[D])||!isFinite(F[D]))continue t;v.push(F[0],F[1],F[2]);var 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W;W=k?k[H]:A[O],u.push(W[0],W[1],W[2]),f.push(O)}B+=1}}this.pointCount=V,this.edgeCount=U,this.triangleCount=B,this.pointPositions.update(v),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(h),this.edgeColors.update(p),this.edgeUVs.update(d),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(f))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(var o=0;3>o;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;3>o;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;3>o;++o){for(var c=l[12+o],f=0;3>f;++f)c+=l[4*f+o]*this.lightPosition[f];s.lightPosition[o]=c/u}if(this.triangleCount>0){var h=this.triShader;h.bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var h=this.lineShader;h.bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var h=this.pointShader;h.bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var h=this.contourShader;h.bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=T(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=p},{\"./lib/closest-point\":354,\"./lib/shaders\":355,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-shader\":385,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,normals:358,\"simplicial-complex-contour\":360,\"typedarray-pool\":463}],357:[function(t,e,r){\"use strict\";function n(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];\n",
+       "return e}function i(t,e){for(var r=e.length,i=new Array(r+1),o=0;r>o;++o){for(var s=new Array(r+1),l=0;r>=l;++l)s[l]=t[l][o];i[o]=s}i[r]=new Array(r+1);for(var o=0;r>=o;++o)i[r][o]=1;for(var u=new Array(r+1),o=0;r>o;++o)u[o]=e[o];u[r]=1;var c=a(i,u),f=n(c[r+1]);0===f&&(f=1);for(var h=new Array(r+1),o=0;r>=o;++o)h[o]=n(c[o])/f;return h}e.exports=i;var a=t(\"robust-linear-solve\")},{\"robust-linear-solve\":441}],358:[function(t,e,r){var n=1e-6;r.vertexNormals=function(t,e){for(var r=e.length,i=new Array(r),a=0;r>a;++a)i[a]=[0,0,0];for(var a=0;a<t.length;++a)for(var o=t[a],s=0,l=o[o.length-1],u=o[0],c=0;c<o.length;++c){s=l,l=u,u=o[(c+1)%o.length];for(var f=e[s],h=e[l],p=e[u],d=new Array(3),g=0,v=new Array(3),m=0,y=0;3>y;++y)d[y]=f[y]-h[y],g+=d[y]*d[y],v[y]=p[y]-h[y],m+=v[y]*v[y];if(g*m>n)for(var b=i[l],x=1/Math.sqrt(g*m),y=0;3>y;++y){var _=(y+1)%3,w=(y+2)%3;b[y]+=x*(v[_]*d[w]-v[w]*d[_])}}for(var a=0;r>a;++a){for(var b=i[a],k=0,y=0;3>y;++y)k+=b[y]*b[y];if(k>n)for(var x=1/Math.sqrt(k),y=0;3>y;++y)b[y]*=x;else for(var y=0;3>y;++y)b[y]=0}return i},r.faceNormals=function(t,e){for(var r=t.length,i=new Array(r),a=0;r>a;++a){for(var o=t[a],s=new Array(3),l=0;3>l;++l)s[l]=e[o[l]];for(var u=new Array(3),c=new Array(3),l=0;3>l;++l)u[l]=s[1][l]-s[0][l],c[l]=s[2][l]-s[0][l];for(var f=new Array(3),h=0,l=0;3>l;++l){var p=(l+1)%3,d=(l+2)%3;f[l]=u[p]*c[d]-u[d]*c[p],h+=f[l]*f[l]}h=h>n?1/Math.sqrt(h):0;for(var l=0;3>l;++l)f[l]*=h;i[a]=f}return i}},{}],359:[function(t,e,r){\"use strict\";function n(t,e,r,n,s){i.length<n.length&&(i=new Float64Array(n.length),a=new Float64Array(n.length),o=new Float64Array(n.length));for(var l=0;l<n.length;++l)i[l]=t[l]-n[l],a[l]=e[l]-t[l],o[l]=r[l]-t[l];for(var u=0,c=0,f=0,h=0,p=0,d=0,l=0;l<n.length;++l){var g=a[l],v=o[l],m=i[l];u+=g*g,c+=g*v,f+=v*v,h+=m*g,p+=m*v,d+=m*m}var y,b=Math.abs(u*f-c*c),x=c*p-f*h,_=c*h-u*p;if(b>=x+_)if(0>x)0>_&&0>h?(_=0,-h>=u?(x=1,y=u+2*h+d):(x=-h/u,y=h*x+d)):(x=0,p>=0?(_=0,y=d):-p>=f?(_=1,y=f+2*p+d):(_=-p/f,y=p*_+d));else if(0>_)_=0,h>=0?(x=0,y=d):-h>=u?(x=1,y=u+2*h+d):(x=-h/u,y=h*x+d);else{var w=1/b;x*=w,_*=w,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d}else{var k,A,M,T;0>x?(k=c+h,A=f+p,A>k?(M=A-k,T=u-2*c+f,M>=T?(x=1,_=0,y=u+2*h+d):(x=M/T,_=1-x,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)):(x=0,0>=A?(_=1,y=f+2*p+d):p>=0?(_=0,y=d):(_=-p/f,y=p*_+d))):0>_?(k=c+p,A=u+h,A>k?(M=A-k,T=u-2*c+f,M>=T?(_=1,x=0,y=f+2*p+d):(_=M/T,x=1-_,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)):(_=0,0>=A?(x=1,y=u+2*h+d):h>=0?(x=0,y=d):(x=-h/u,y=h*x+d))):(M=f+p-c-h,0>=M?(x=0,_=1,y=f+2*p+d):(T=u-2*c+f,M>=T?(x=1,_=0,y=u+2*h+d):(x=M/T,_=1-x,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)))}for(var E=1-x-_,l=0;l<n.length;++l)s[l]=E*t[l]+x*e[l]+_*r[l];return 0>y?0:y}var i=new Float64Array(4),a=new Float64Array(4),o=new Float64Array(4);e.exports=n},{}],360:[function(t,e,r){\"use strict\";function n(t){for(var e=t.length,r=0,n=0;e>n;++n)r=0|Math.max(r,t[n].length);return r-1}function i(t,e){for(var r=t.length,n=f.mallocUint8(r),i=0;r>i;++i)n[i]=t[i]<e|0;return n}function a(t,e){for(var r=t.length,n=e*(e+1)/2*r|0,i=f.mallocUint32(2*n),a=0,o=0;r>o;++o)for(var s=t[o],e=s.length,l=0;e>l;++l)for(var u=0;l>u;++u){var p=s[u],d=s[l];i[a++]=0|Math.min(p,d),i[a++]=0|Math.max(p,d)}var g=a/2|0;h(c(i,[g,2]));for(var v=2,o=2;a>o;o+=2)(i[o-2]!==i[o]||i[o-1]!==i[o+1])&&(i[v++]=i[o],i[v++]=i[o+1]);return c(i,[v/2|0,2])}function o(t,e,r,n){for(var i=t.data,a=t.shape[0],o=f.mallocDouble(a),s=0,l=0;a>l;++l){var u=i[2*l],h=i[2*l+1];if(r[u]!==r[h]){var p=e[u],d=e[h];i[2*s]=u,i[2*s+1]=h,o[s++]=(d-n)/(d-p)}}return t.shape[0]=s,c(o,[s])}function s(t,e){var r=f.mallocInt32(2*e),n=t.shape[0],i=t.data;r[0]=0;for(var a=0,o=0;n>o;++o){var s=i[2*o];if(s!==a){for(r[2*a+1]=o;++a<s;)r[2*a]=o,r[2*a+1]=o;r[2*a]=o}}for(r[2*a+1]=n;++a<e;)r[2*a]=r[2*a+1]=n;return r}function l(t){for(var e=0|t.shape[0],r=t.data,n=new 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t=[0,0],e=[0,0],r=[0,0];return function(){for(var n=this.plot,i=this.vbo,a=this.shader,o=this.ticks,s=n.gl,l=n._tickBounds,u=n.dataBox,c=n.viewBox,f=n.gridLineWidth,h=n.gridLineColor,p=n.gridLineEnable,d=n.pixelRatio,g=0;2>g;++g){var v=l[g],m=l[g+2],y=m-v,b=.5*(u[g+2]+u[g]),x=u[g+2]-u[g];e[g]=2*y/x,t[g]=2*(v-b)/x}a.bind(),i.bind(),a.attributes.dataCoord.pointer(),a.uniforms.dataShift=t,a.uniforms.dataScale=e;for(var _=0,g=0;2>g;++g){r[0]=r[1]=0,r[g]=1,a.uniforms.dataAxis=r,a.uniforms.lineWidth=f[g]/(c[g+2]-c[g])*d,a.uniforms.color=h[g];var w=6*o[g].length;p[g]&&s.drawArrays(s.TRIANGLES,_,w),_+=w}}}(),c.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,v=s.pixelRatio,m=s.screenBox,y=m[2]-m[0],b=m[3]-m[1],x=g[2]-g[0],_=g[3]-g[1],w=0;2>w;++w){var k=p[w],A=p[w+2],M=A-k,T=.5*(d[w+2]+d[w]),E=d[w+2]-d[w];e[w]=2*M/E,t[w]=2*(k-T)/E}e[0]*=x/y,t[0]*=x/y,e[1]*=_/b,t[1]*=_/b,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var L=c.uniforms;L.dataShift=t,L.dataScale=e;var S=s.tickMarkLength,C=s.tickMarkWidth,P=s.tickMarkColor,z=0,R=6*f[0].length,O=Math.min(l.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),i),f[0].length),I=Math.min(l.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),i),f[0].length),j=z+6*O,N=6*Math.max(0,I-O),F=Math.min(l.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),i),f[1].length),D=Math.min(l.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),i),f[1].length),B=R+6*F,U=6*Math.max(0,D-F);a[0]=2*(g[0]-S[1])/y-1,a[1]=(g[3]+g[1])/b-1,o[0]=S[1]*v/y,o[1]=C[1]*v/b,L.color=P[1],L.tickScale=o,L.dataAxis=n,L.screenOffset=a,h.drawArrays(h.TRIANGLES,B,U),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-S[0])/b-1,o[0]=C[0]*v/y,o[1]=S[0]*v/b,L.color=P[0],L.tickScale=o,L.dataAxis=r,L.screenOffset=a,h.drawArrays(h.TRIANGLES,j,N),a[0]=2*(g[2]+S[3])/y-1,a[1]=(g[3]+g[1])/b-1,o[0]=S[3]*v/y,o[1]=C[3]*v/b,L.color=P[3],L.tickScale=o,L.dataAxis=n,L.screenOffset=a,h.drawArrays(h.TRIANGLES,B,U),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+S[2])/b-1,o[0]=C[2]*v/y,o[1]=S[2]*v/b,L.color=P[2],L.tickScale=o,L.dataAxis=r,L.screenOffset=a,h.drawArrays(h.TRIANGLES,j,N)}}(),c.update=function(){var t=[1,1,-1,-1,1,-1],e=[1,-1,1,1,-1,-1];return function(r){for(var n=r.ticks,i=r.bounds,a=new Float32Array(18*(n[0].length+n[1].length)),o=(this.plot.zeroLineEnable,0),s=[[],[]],l=0;2>l;++l)for(var u=s[l],c=n[l],f=i[l],h=i[l+2],p=0;p<c.length;++p){var d=(c[p].x-f)/(h-f);u.push(d);for(var g=0;6>g;++g)a[o++]=d,a[o++]=t[g],a[o++]=e[g]}this.ticks=s,this.vbo.update(a)}}(),c.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385}],367:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[-1,-1,-1,1,1,-1,1,1]),i=o(e,s.lineVert,s.lineFrag),l=new n(t,r,i);return l}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawLine=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o,s){var l=this.plot,u=this.shader,c=l.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,u.uniforms.start=t,u.uniforms.end=e,u.uniforms.width=o*l.pixelRatio,u.uniforms.color=s,c.drawArrays(c.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"gl-buffer\":325,\"gl-shader\":385}],368:[function(t,e,r){\"use strict\";var n=\"#define GLSLIFY 1\\nprecision lowp float;\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\";e.exports={lineVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\",lineFrag:n,textVert:\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\",textFrag:n,gridVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\",gridFrag:n,boxVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\",tickVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"}},{}],369:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}function i(t){var e=t.gl,r=a(e),i=o(e,u.textVert,u.textFrag),s=new n(t,r,i);return s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,f=i.dataBox,h=i.screenBox,p=i.pixelRatio,d=i.tickEnable,g=i.tickPad,v=i.tickColor,m=i.tickAngle,y=(i.tickMarkLength,i.labelEnable),b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],k=this.labelCount[n],A=l.lt(o,f[n]),M=l.le(o,f[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(h[2+n]-h[n])-1;var T=2/h[2+(1^n)]-h[1^n];e[1^n]=T*c[1^n]-1,d[n]&&(e[1^n]-=T*p*g[n],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n],a.uniforms.angle=m[n],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n]&&(e[1^n]-=T*p*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,k)),e[1^n]=T*c[2+(1^n)]-1,d[n+2]&&(e[1^n]+=T*p*g[n+2],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n+2],a.uniforms.angle=m[n+2],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n+2]&&(e[1^n]+=T*p*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,k))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){for(var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,o=r.titleCenter,u=r.pixelRatio,c=0;2>c;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;2>u;++u){var c=a[u],f=a[u+2],h=f-c,p=.5*(o[u+2]+o[u]),d=o[u+2]-o[u],g=l[u],v=l[u+2],m=v-g,y=s[u],b=s[u+2],x=b-y;e[u]=2*h/d*m/x,t[u]=2*(c-p)/d*m/x}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){for(var e=[],r=t.ticks,n=t.bounds,i=0;2>i;++i){for(var a=[Math.floor(e.length/3)],o=[-(1/0)],l=r[i],u=0;u<l.length;++u){for(var c=l[u],f=c.x,h=c.text,p=c.font||\"sans-serif\",d=c.fontSize||12,g=s(p,h).data,v=1/(n[i+2]-n[i]),m=n[i],y=0;y<g.length;y+=2)e.push(g[y]*d,-g[y+1]*d,(f-m)*v);a.push(Math.floor(e.length/3)),o.push(f)}this.tickOffset[i]=a,this.tickX[i]=o}for(var i=0;2>i;++i){this.labelOffset[i]=Math.floor(e.length/3);for(var g=s(t.labelFont[i],t.labels[i]).data,d=t.labelSize[i],u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.labelCount[i]=Math.floor(e.length/3)-this.labelOffset[i]}this.titleOffset=Math.floor(e.length/3);for(var g=s(t.titleFont,t.title).data,d=t.titleSize,u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.titleCount=Math.floor(e.length/3)-this.titleOffset,this.vbo.update(e)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458}],370:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],371:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-(1/0),-(1/0)],this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}function i(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function a(t,e){return t.x-e.x}function o(t){var e=t.gl,r=s(e,[e.drawingBufferWidth,e.drawingBufferHeight]),i=new n(e,r);return i.grid=l(i),i.text=u(i),i.line=c(i),i.box=f(i),i.update(t),i}e.exports=o;var s=t(\"gl-select-static\"),l=t(\"./lib/grid\"),u=t(\"./lib/text\"),c=t(\"./lib/line\"),f=t(\"./lib/box\"),h=n.prototype;h.setDirty=function(){this.dirty=this.pickDirty=!0},h.setOverlayDirty=function(){this.dirty=!0},h.nextDepthValue=function(){return this._depthCounter++/65536},h.draw=function(){return function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT),t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;2>d;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(var d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind();for(var d=0;2>d;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();for(var b=this.overlays,d=0;d<b.length;++d)b[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),h.drawPick=function(){return function(){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}(),h.pick=function(){return function(t,e){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){\n",
+       "var f=u[c].pick(a,o,l);if(f)return f}return null}}(),h.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},h.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},h.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},h.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;2>u;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.setDirty()},h.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},h.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},h.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},h.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},h.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":365,\"./lib/grid\":366,\"./lib/line\":367,\"./lib/text\":369,\"gl-select-static\":384}],372:[function(t,e,r){\"use strict\";e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",pickFragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],373:[function(t,e,r){\"use strict\";function n(t){if(t in h)return h[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var f=s[0]-o[0],h=s[1]-o[1],p=Math.sqrt(f*f+h*h);f/=p,h/=p,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(a[0],a[1]+1.4),n.push(h,-f),r.push(o[0],o[1]+1.4),n.push(h,-f)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;2>o;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return h[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.offsetBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,f.vertex,f.fragment),a=o(r,f.pickVertex,f.pickFragment),l=s(r),u=s(r),c=s(r),h=s(r),p=new i(t,n,a,l,u,c,h);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),f=t(\"./lib/shaders\"),h={},p=i.prototype;!function(){function t(){var t=this.plot,n=this.bounds,i=t.viewBox,a=t.dataBox,o=t.pixelRatio,s=n[2]-n[0],l=n[3]-n[1],u=a[2]-a[0],c=a[3]-a[1];e[0]=2*s/u,e[4]=2*l/c,e[6]=2*(n[0]-a[0])/u-1,e[7]=2*(n[1]-a[1])/c-1;var f=i[2]-i[0],h=i[3]-i[1];r[0]=2*o/f,r[1]=2*o/h}var e=[1,0,0,0,1,0,0,0,1],r=[1,1];p.draw=function(){var n=this.plot,i=this.shader,a=this.numVertices,o=n.gl;t.call(this),i.bind(),i.uniforms.pixelScale=r,i.uniforms.viewTransform=e,this.positionBuffer.bind(),i.attributes.position.pointer(),this.offsetBuffer.bind(),i.attributes.offset.pointer(),this.colorBuffer.bind(),i.attributes.color.pointer(o.UNSIGNED_BYTE,!0),o.drawArrays(o.TRIANGLES,0,a)};var n=[0,0,0,0];p.drawPick=function(i){var a=this.plot,o=this.pickShader,s=this.numVertices,l=a.gl;this.pickOffset=i;for(var u=0;4>u;++u)n[u]=i>>8*u&255;return t.call(this),o.bind(),o.uniforms.pixelScale=r,o.uniforms.viewTransform=e,o.uniforms.pickOffset=n,this.positionBuffer.bind(),o.attributes.position.pointer(),this.offsetBuffer.bind(),o.attributes.offset.pointer(),this.idBuffer.bind(),o.attributes.id.pointer(l.UNSIGNED_BYTE,!1),l.drawArrays(l.TRIANGLES,0,s),i+this.numPoints}}(),p.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},p.update=function(t){t=t||{};var e=t.positions||[],r=t.colors||[],i=t.glyphs||[],a=t.sizes||[],o=t.borderWidths||[],s=t.borderColors||[];this.points=e;for(var c=this.bounds=[1/0,1/0,-(1/0),-(1/0)],f=0,h=0;h<i.length;++h){f+=l(\"sans-serif\",i[h]).data.length+n(i[h]).coords.length>>1;for(var p=0;2>p;++p)c[p]=Math.min(c[p],e[2*h+p]),c[2+p]=Math.max(c[2+p],e[2*h+p])}c[0]===c[2]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);for(var d=1/(c[2]-c[0]),g=1/(c[3]-c[1]),v=c[0],m=c[1],y=u.mallocFloat32(2*f),b=u.mallocFloat32(2*f),x=u.mallocUint8(4*f),_=u.mallocUint32(f),w=0,h=0;h<i.length;++h){for(var k=l(\"sans-serif\",i[h]),A=n(i[h]),M=d*(e[2*h]-v),T=g*(e[2*h+1]-m),E=a[h],L=255*r[4*h],S=255*r[4*h+1],C=255*r[4*h+2],P=255*r[4*h+3],z=.5*(A.bounds[0]+A.bounds[2]),R=.5*(A.bounds[1]+A.bounds[3]),p=0;p<k.data.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-E*(k.data[p]-z),b[2*w+1]=-E*(k.data[p+1]-R),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1;var O=o[h];L=255*s[4*h],S=255*s[4*h+1],C=255*s[4*h+2],P=255*s[4*h+3];for(var p=0;p<A.coords.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-(E*(A.coords[p]-z)+O*A.normals[p]),b[2*w+1]=-(E*(A.coords[p+1]-R)+O*A.normals[p+1]),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1}this.numPoints=i.length,this.numVertices=f,this.positionBuffer.update(y),this.offsetBuffer.update(b),this.colorBuffer.update(x),this.idBuffer.update(_),u.free(y),u.free(b),u.free(x),u.free(_)},p.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":372,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458,\"typedarray-pool\":463,\"vectorize-text\":465}],374:[function(t,e,r){r.pointVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute float weight;\\n\\nuniform mat3 matrix;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\\n\",r.pointFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],375:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],376:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){4*h>=a?i(0,a-1,t,e,r,n):f(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;e>=o;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],f=a[o],h=o;h>t;){var p=r[h-1],d=n[2*(h-1)];if((p-s||l-d)>=0)break;r[h]=p,n[2*h]=d,n[2*h+1]=n[2*h-1],i[h]=i[h-1],a[h]=a[h-1],h-=1}r[h]=s,n[2*h]=l,n[2*h+1]=u,i[h]=c,a[h]=f}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],f=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=f}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0}function c(t,e,r,n,i,a,o,s){return(e-a[t]||o[2*t]-r||i-s[t])<0}function f(t,e,r,n,p,d){var g=(e-t+1)/6|0,v=t+g,m=e-g,y=t+e>>1,b=y-g,x=y+g,_=v,w=b,k=y,A=x,M=m,T=t+1,E=e-1,L=0;u(_,w,r,n,p,d)&&(L=_,_=w,w=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L),u(_,k,r,n,p,d)&&(L=_,_=k,k=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(_,A,r,n,p,d)&&(L=_,_=A,A=L),u(k,A,r,n,p,d)&&(L=k,k=A,A=L),u(w,M,r,n,p,d)&&(L=w,w=M,M=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L);var S=r[w],C=n[2*w],P=n[2*w+1],z=p[w],R=d[w],O=r[A],I=n[2*A],j=n[2*A+1],N=p[A],F=d[A],D=_,B=k,U=M,V=v,q=y,H=m,G=r[D],Y=r[B],X=r[U];r[V]=G,r[q]=Y,r[H]=X;for(var W=0;2>W;++W){var Z=n[2*D+W],$=n[2*B+W],K=n[2*U+W];n[2*V+W]=Z,n[2*q+W]=$,n[2*H+W]=K}var Q=p[D],J=p[B],tt=p[U];p[V]=Q,p[q]=J,p[H]=tt;var et=d[D],rt=d[B],nt=d[U];d[V]=et,d[q]=rt,d[H]=nt,o(b,t,r,n,p,d),o(x,e,r,n,p,d);for(var it=T;E>=it;++it)if(c(it,S,C,P,z,r,n,p))it!==T&&a(it,T,r,n,p,d),++T;else if(!c(it,O,I,j,N,r,n,p))for(;;){if(c(E,O,I,j,N,r,n,p)){c(E,S,C,P,z,r,n,p)?(s(it,T,E,r,n,p,d),++T,--E):(a(it,E,r,n,p,d),--E);break}if(--E<it)break}l(t,T-1,S,C,P,z,R,r,n,p,d),l(e,E+1,O,I,j,N,F,r,n,p,d),h>=T-2-t?i(t,T-2,r,n,p,d):f(t,T-2,r,n,p,d),h>=e-(E+2)?i(E+2,e,r,n,p,d):f(E+2,e,r,n,p,d),h>=E-T?i(T,E,r,n,p,d):f(T,E,r,n,p,d)}e.exports=n;var h=32},{}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;n>u;++u){var c=t[2*u],f=t[2*u+1],h=e[u];c>=i&&o>=c&&f>=a&&s>=f&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=f,e[l]=h,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var f=.5*o,h=s+1,p=u-s;r[_]=p,x[_++]=c;for(var d=0;2>d;++d)for(var g=0;2>g;++g){var v=i+d*f,m=a+g*f,y=n(t,e,h,u,v,m,v+f,m+f);if(y!==h){if(y-h>=Math.max(.9*p,32)){var b=u+s>>>1;l(v,m,f,h,b,c+1),h=b}l(v,m,f,h,y,c+1),h=y}}}var u=t.length>>>1;if(1>u)return[];for(var c=1/0,f=1/0,h=-(1/0),p=-(1/0),d=0;u>d;++d){var g=t[2*d],v=t[2*d+1];c=Math.min(c,g),h=Math.max(h,g),f=Math.min(f,v),p=Math.max(p,v),e[d]=d}c===h&&(h+=1+Math.abs(h)),f===p&&(p+=1+Math.abs(h));var m=1/(h-c),y=1/(p-f),b=Math.max(h-c,p-f);a=a||[0,0,0,0],a[0]=c,a[1]=f,a[2]=h,a[3]=p;var x=o.mallocInt32(u),_=0;l(c,f,b,0,u,0),s(x,t,e,r,u);for(var w=[],k=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*m,t[2*_+1]=(t[2*_+1]-f)*y;var M=x[_];M!==k&&(w.push(new i(b*Math.pow(.5,M),_+1,A-(_+1))),A=_+1,k=M)}return w.push(new i(b*Math.pow(.5,M+1),0,A)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":376,\"typedarray-pool\":463}],378:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.weightBuffer=n,this.shader=i,this.pickShader=a,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),h=new n(t,i,s,l,u,f);return h.update(e),t.addObject(h),h}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var f=n.prototype;f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},f.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords);var r=t.positions,n=u.mallocFloat32(r.length),i=u.mallocInt32(r.length>>>1);n.set(r);var a=u.mallocFloat32(r.length);this.points=r,this.scales=l(n,i,a,this.bounds),this.offsetBuffer.update(n),this.pickBuffer.update(i),this.weightBuffer.update(a);for(var o=u.mallocFloat32(r.length>>>1),s=0,c=0;s<r.length;s+=2,++c)o[c]=n[s];u.free(i),u.free(n),u.free(a),this.xCoords=o,this.pointCount=r.length>>>1,this.pickOffset=0},f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.scales,o=this.offsetBuffer,l=this.pickBuffer,u=this.bounds,c=this.size,f=this.borderSize,h=n.gl,p=n.pickPixelRatio,d=n.viewBox,g=n.dataBox;if(0===this.pointCount)return r;var v=u[2]-u[0],m=u[3]-u[1],y=g[2]-g[0],b=g[3]-g[1],x=(d[2]-d[0])*p/n.pixelRatio,_=(d[3]-d[1])*p/n.pixelRatio,w=Math.min(y/x,b/_);t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(u[0]-g[0])/y-1,t[7]=2*(u[1]-g[1])/b-1,this.pickOffset=r,e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,i.bind(),i.uniforms.matrix=t,i.uniforms.color=this.color,i.uniforms.borderColor=this.borderColor,i.uniforms.pointSize=p*(c+f),i.uniforms.pickOffset=e,0===this.borderSize?i.uniforms.centerFraction=2:i.uniforms.centerFraction=c/(c+f+1.25),o.bind(),i.attributes.position.pointer(),l.bind(),i.attributes.pickId.pointer(h.UNSIGNED_BYTE);for(var k=this.xCoords,A=(g[0]-u[0]-w*c*p)/v,M=(g[2]-u[0]+w*c*p)/v,T=a.length-1;T>=0;--T){var E=a[T];if(!(E.pixelSize<w&&T>1)){var L=E.offset,S=E.count+L,C=s.ge(k,A,L,S-1),P=s.lt(k,M,C,S-1)+1;h.drawArrays(h.POINTS,C,P-C)}}return r+this.pointCount}}(),f.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.scales,i=this.offsetBuffer,a=this.bounds,o=this.size,l=this.borderSize,u=e.gl,c=e.pixelRatio,f=e.viewBox,h=e.dataBox;if(0!==this.pointCount){var p=a[2]-a[0],d=a[3]-a[1],g=h[2]-h[0],v=h[3]-h[1],m=f[2]-f[0],y=f[3]-f[1],b=Math.min(g/m,v/y);t[0]=2*p/g,t[4]=2*d/v,t[6]=2*(a[0]-h[0])/g-1,t[7]=2*(a[1]-h[1])/v-1,r.bind(),r.uniforms.matrix=t,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointSize=c*(o+l),r.uniforms.useWeight=1,0===this.borderSize?r.uniforms.centerFraction=2:r.uniforms.centerFraction=o/(o+l+1.25),i.bind(),r.attributes.position.pointer(),this.weightBuffer.bind(),r.attributes.weight.pointer();for(var x=this.xCoords,_=(h[0]-a[0]-b*o*c)/p,w=(h[2]-a[0]+b*o*c)/p,k=!0,A=n.length-1;A>=0;--A){var M=n[A];if(!(M.pixelSize<b&&A>1)){var T=M.offset,E=M.count+T,L=s.ge(x,_,T,E-1),S=s.lt(x,w,L,E-1)+1;u.drawArrays(u.POINTS,L,S-L),k&&(k=!1,r.uniforms.useWeight=0)}}}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":374,\"binary-search-bounds\":375,\"gl-buffer\":325,\"gl-shader\":385,\"snap-points-2d\":377,\"typedarray-pool\":463}],379:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;2>c;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":465}],380:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},v={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,f)},r.createOrtho=function(t){return n(t,h)},r.createProject=function(t){return n(t,p)},r.createPickPerspective=function(t){return n(t,d)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,v)}},{\"gl-shader\":385}],381:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,f,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=f,this.pickProjectShader=h,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=S,r=0;2>r;++r)for(var n=0;3>n;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function f(t,e,r,n,a){var o,f=e.axesProject,h=e.gl,p=t.uniforms,d=r.model||x,g=r.view||x,v=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/h.drawingBufferWidth,w[1]=2/h.drawingBufferHeight,t.bind(),p.view=g,p.projection=v,p.screenSize=w,p.highlightId=e.highlightId,p.highlightScale=e.highlightScale,p.clipBounds=b,p.pickGroup=e.pickId/255,p.pixelRatio=e.pixelRatio;for(var _=0;3>_;++_)if(f[_]&&e.projectOpacity[_]<1===n){p.scale=e.projectScale[_],p.opacity=e.projectOpacity[_];for(var S=E,C=0;16>C;++C)S[C]=0;for(var C=0;4>C;++C)S[5*C]=1;S[5*_]=0,o[_]<0?S[12+_]=y[0][_]:S[12+_]=y[1][_],m(S,d,S),p.model=S;var P=(_+1)%3,z=(_+2)%3,R=s(k),O=s(A);R[P]=1,O[z]=1;var I=i(v,g,d,l(M,R)),j=i(v,g,d,l(T,O));if(Math.abs(I[1])>Math.abs(j[1])){var N=I;I=j,j=N,N=R,R=O,O=N;var F=P;P=z,z=F}I[0]<0&&(R[P]=-1),j[1]>0&&(O[z]=-1);for(var D=0,B=0,C=0;4>C;++C)D+=Math.pow(d[4*P+C],2),B+=Math.pow(d[4*z+C],2);R[P]/=Math.sqrt(D),O[z]/=Math.sqrt(B),p.axes[0]=R,p.axes[1]=O,p.fragClipBounds[0]=u(L,b[0],_,-1e8),p.fragClipBounds[1]=u(L,b[1],_,1e8),e.vao.draw(h.TRIANGLES,e.vertexCount),e.lineWidth>0&&(h.lineWidth(e.lineWidth),e.vao.draw(h.LINES,e.lineVertexCount,e.vertexCount))}}function h(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=z,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}f(e,r,n,i,a),r.vao.unbind()}function p(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=d(e),c=d(e),f=d(e),h=d(e),p=g(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:f,size:2,type:e.FLOAT},{buffer:h,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new o(e,r,n,i,u,c,f,h,p,a,s,l);return v.update(t),v}var d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"typedarray-pool\"),m=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=p;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],k=[0,0,0],A=[0,0,0],M=[0,0,0,1],T=[0,0,0,1],E=x.slice(),L=[0,0,0],S=[[0,0,0],[0,0,0]],C=[-1e8,-1e8,-1e8],P=[1e8,1e8,1e8],z=[C,P];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;h(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||0>e)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;3>i;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in t&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-(1/0),-(1/0),-(1/0)],l=t.glyph,u=t.color,c=t.size,f=t.angle,h=t.lineColor,p=0,d=0,g=0,m=n.length;t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_)if(isNaN(x[_])||!isFinite(x[_]))continue t;var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];d+=3*k.cells.length,g+=2*A.edges.length}var T=d+g,E=v.mallocFloat(3*T),L=v.mallocFloat(4*T),S=v.mallocFloat(2*T),C=v.mallocUint32(T),P=[0,a[1]],z=0,R=d,O=[0,0,0,1],I=[0,0,0,1],j=Array.isArray(u)&&Array.isArray(u[0]),N=Array.isArray(h)&&Array.isArray(h[0]);t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_){if(isNaN(x[_])||!isFinite(x[_])){p+=1;continue t}s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_])}var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];if(Array.isArray(u)){var F;if(F=j?u[y]:u,3===F.length){for(var _=0;3>_;++_)O[_]=F[_];O[3]=1}else if(4===F.length)for(var _=0;4>_;++_)O[_]=F[_];\n",
+       "}else O[0]=O[1]=O[2]=0,O[3]=1;if(Array.isArray(h)){var F;if(F=N?h[y]:h,3===F.length){for(var _=0;3>_;++_)I[_]=F[_];I[_]=1}else if(4===F.length)for(var _=0;4>_;++_)I[_]=F[_]}else I[0]=I[1]=I[2]=0,I[3]=1;var D=.5;Array.isArray(c)?D=+c[y]:c?D=+c:this.useOrtho&&(D=12);var B=0;Array.isArray(f)?B=+f[y]:f&&(B=+f);for(var U=Math.cos(B),V=Math.sin(B),x=n[y],_=0;3>_;++_)s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_]);a[0]<0?P[0]=a[0]*(1+M[1][0]):a[0]>0&&(P[0]=-a[0]*(1+M[0][0]));for(var q=k.cells,H=k.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;3>Y;++Y){for(var X=0;3>X;++X)E[3*z+X]=x[X];for(var X=0;4>X;++X)L[4*z+X]=O[X];C[z]=p;var W=H[G[Y]];S[2*z]=D*(U*W[0]-V*W[1]+P[0]),S[2*z+1]=D*(V*W[0]+U*W[1]+P[1]),z+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;2>Y;++Y){for(var X=0;3>X;++X)E[3*R+X]=x[X];for(var X=0;4>X;++X)L[4*R+X]=I[X];C[R]=p;var W=H[G[Y]];S[2*R]=D*(U*W[0]-V*W[1]+P[0]),S[2*R+1]=D*(V*W[0]+U*W[1]+P[1]),R+=1}p+=1}this.vertexCount=d,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(C)),v.free(E),v.free(L),v.free(S),v.free(C),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":379,\"./lib/shaders\":380,\"gl-buffer\":325,\"gl-mat4/multiply\":346,\"gl-vao\":420,\"typedarray-pool\":463}],382:[function(t,e,r){\"use strict\";r.boxVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(f>p||h>d)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*c;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":382,\"gl-buffer\":325,\"gl-shader\":385}],384:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(255>_inline_31_arg0_||255>_inline_31_arg1_||255>_inline_31_arg2_||255>_inline_31_arg3_){var _inline_31_l=_inline_31_arg4_-_inline_31_arg6_[0],_inline_31_a=_inline_31_arg5_-_inline_31_arg6_[1],_inline_31_f=_inline_31_l*_inline_31_l+_inline_31_a*_inline_31_a;_inline_31_f<this_closestD2&&(this_closestD2=_inline_31_f,this_closestX=_inline_31_arg6_[0],this_closestY=_inline_31_arg6_[1])}}\",args:[{name:\"_inline_31_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg4_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg5_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg6_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[\"_inline_31_a\",\"_inline_31_f\",\"_inline_31_l\"]},post:{body:\"{return[this_closestX,this_closestY,this_closestD2]}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64}),f=i.prototype;Object.defineProperty(f,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){s.free(this.buffer);for(var n=this.buffer=s.mallocUint8(u(r*e*4)),i=0;r*e*4>i;++i)n[i]=255}return t}}}),f.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},f.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},f.query=function(t,e,r){if(!this.gl)return null;var i=this.fbo.shape.slice();t=0|t,e=0|e,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),i[0]),o=0|Math.min(Math.max(t+r,0),i[0]),s=0|Math.min(Math.max(e-r,0),i[1]),u=0|Math.min(Math.max(e+r,0),i[1]);if(a>=o||s>=u)return null;var f=[o-a,u-s],h=l(this.buffer,[f[0],f[1],4],[4,4*i[0],1],4*(a+i[0]*s)),p=c(h.hi(f[0],f[1],1),r,r),d=p[0],g=p[1];if(0>d||Math.pow(this.radius,2)<p[2])return null;var v=h.get(d,g,0),m=h.get(d,g,1),y=h.get(d,g,2),b=h.get(d,g,3);return new n(d+a|0,g+s|0,v,[m,y,b],Math.sqrt(p[2]))},f.dispose=function(){this.gl&&(this.fbo.dispose(),s.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":299,\"cwise/lib/wrapper\":319,\"gl-fbo\":330,ndarray:438,\"typedarray-pool\":463}],385:[function(t,e,r){arguments[4][206][0].apply(r,arguments)},{\"./lib/GLError\":386,\"./lib/create-attributes\":387,\"./lib/create-uniforms\":388,\"./lib/reflect\":389,\"./lib/runtime-reflect\":390,\"./lib/shader-cache\":391,dup:206}],386:[function(t,e,r){arguments[4][207][0].apply(r,arguments)},{dup:207}],387:[function(t,e,r){arguments[4][208][0].apply(r,arguments)},{\"./GLError\":386,dup:208}],388:[function(t,e,r){arguments[4][209][0].apply(r,arguments)},{\"./GLError\":386,\"./reflect\":389,dup:209}],389:[function(t,e,r){arguments[4][210][0].apply(r,arguments)},{dup:210}],390:[function(t,e,r){arguments[4][211][0].apply(r,arguments)},{dup:211}],391:[function(t,e,r){arguments[4][212][0].apply(r,arguments)},{\"./GLError\":386,dup:212,\"gl-format-compiler-error\":392,\"weakmap-shim\":408}],392:[function(t,e,r){arguments[4][213][0].apply(r,arguments)},{\"add-line-numbers\":393,dup:213,\"gl-constants/lookup\":397,\"glsl-shader-name\":398,\"sprintf-js\":405}],393:[function(t,e,r){arguments[4][214][0].apply(r,arguments)},{dup:214,\"pad-left\":394}],394:[function(t,e,r){arguments[4][215][0].apply(r,arguments)},{dup:215,\"repeat-string\":395}],395:[function(t,e,r){arguments[4][216][0].apply(r,arguments)},{dup:216}],396:[function(t,e,r){arguments[4][217][0].apply(r,arguments)},{dup:217}],397:[function(t,e,r){arguments[4][218][0].apply(r,arguments)},{\"./1.0/numbers\":396,dup:218}],398:[function(t,e,r){arguments[4][219][0].apply(r,arguments)},{\"atob-lite\":399,dup:219,\"glsl-tokenizer\":404}],399:[function(t,e,r){arguments[4][220][0].apply(r,arguments)},{dup:220}],400:[function(t,e,r){arguments[4][221][0].apply(r,arguments)},{\"./lib/builtins\":401,\"./lib/literals\":402,\"./lib/operators\":403,dup:221}],401:[function(t,e,r){arguments[4][222][0].apply(r,arguments)},{dup:222}],402:[function(t,e,r){arguments[4][223][0].apply(r,arguments)},{dup:223}],403:[function(t,e,r){arguments[4][224][0].apply(r,arguments)},{dup:224}],404:[function(t,e,r){arguments[4][225][0].apply(r,arguments)},{\"./index\":400,dup:225}],405:[function(t,e,r){arguments[4][226][0].apply(r,arguments)},{dup:226}],406:[function(t,e,r){arguments[4][227][0].apply(r,arguments)},{\"./hidden-store.js\":407,dup:227}],407:[function(t,e,r){arguments[4][228][0].apply(r,arguments)},{dup:228}],408:[function(t,e,r){arguments[4][229][0].apply(r,arguments)},{\"./create-store.js\":406,dup:229}],409:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}function i(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r}e.exports=i;var a=n.prototype;a.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map(function(t){return t.slice()}),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},a.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],410:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\nattribute vec2 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  value = f.x;\\n  kill = f.y;\\n  planeCoordinate = uv.xy;\\n  \\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  float interpValue = (value - lowerBound.z) / (upperBound.z - lowerBound.z);\\n  vec4 surfaceColor = texture2D(colormap, vec2(interpValue, interpValue));\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\n\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  vec4 worldPosition = model * vec4(dataCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z = clipPosition.z + zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = dataCoordinate.z;\\n  kill = -1.0;\\n  worldCoordinate = dataCoordinate;\\n  planeCoordinate = uv.zw;\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 || \\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e}},{\"gl-shader\":385}],411:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],412:[function(t,e,r){\"use strict\";function n(t){if(t in l)return l[t];for(var e=[],r=0;t>r;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");for(var n=[\"array\"],i=[\"junk\"],r=0;t>r;++r){n.push(\"array\"),i.push(\"out\"+r+\"s\");var a=o(t);a[r]=-1,n.push({array:0,offset:a.slice()}),a[r]=1,n.push({array:0,offset:a.slice()}),i.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return l[t]=s({args:n,pre:c,post:c,body:{body:e.join(\"\"),args:i.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}function i(t){function e(e){for(var r=a-e.length,n=[],i=[],s=[],l=0;a>l;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),n.push(\"1\"),i.push(\"s[\"+l+\"]-2\"));var u=\".lo(\"+n.join()+\").hi(\"+i.join()+\")\";if(0===n.length&&(u=\"\"),r>0){o.push(\"if(1\");for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\"&&s[\",l,\"]>2\");o.push(\"){grad\",r,\"(src.pick(\",s.join(),\")\",u);for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\",dst.pick(\",s.join(),\",\",l,\")\",u);o.push(\");\")}for(var l=0;l<e.length;++l){var c=Math.abs(e[l])-1,f=\"dst.pick(\"+s.join()+\",\"+c+\")\"+u;switch(t[c]){case\"clamp\":var h=s.slice(),p=s.slice();e[l]<0?h[c]=\"s[\"+c+\"]-2\":p[c]=\"1\",0===r?o.push(\"if(s[\",c,\"]>1){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",h.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>1){diff(\",f,\",src.pick(\",h.join(),\")\",u,\",src.pick(\",p.join(),\")\",u,\");}else{zero(\",f,\");};\");break;case\"mirror\":0===r?o.push(\"dst.set(\",s.join(),\",\",c,\",0);\"):o.push(\"zero(\",f,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[c]=\"s[\"+c+\"]-2\",g[c]=\"0\"):(d[c]=\"s[\"+c+\"]-1\",g[c]=\"1\"),0===r?o.push(\"if(s[\",c,\"]>2){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>2){diff(\",f,\",src.pick(\",d.join(),\")\",u,\",src.pick(\",g.join(),\")\",u,\");}else{zero(\",f,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}r>0&&o.push(\"};\")}var r=t.join(),i=u[r];if(i)return i;for(var a=t.length,o=[\"function gradient(dst,src){var s=src.shape.slice();\"],s=0;1<<a>s;++s){for(var c=[],p=0;a>p;++p)s&1<<p&&c.push(p+1);for(var d=0;d<1<<c.length;++d){for(var g=c.slice(),p=0;p<c.length;++p)d&1<<p&&(g[p]=-g[p]);e(g)}}o.push(\"return dst;};return gradient\");for(var v=[\"diff\",\"zero\"],m=[f,h],s=1;a>=s;++s)v.push(\"grad\"+s),m.push(n(s));v.push(o.join(\"\"));var y=Function.apply(void 0,v),i=y.apply(void 0,m);return l[r]=i,i}function a(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=\"string\"==typeof r?o(e.dimension,r):o(e.dimension,\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var n=0;n<e.dimension;++n)if(t.shape[n]!==e.shape[n])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;var a=i(r);return a(t,e)}e.exports=a;var o=t(\"dup\"),s=t(\"cwise-compiler\"),l={},u={},c={body:\"\",args:[],thisVars:[],localVars:[]},f=s({args:[\"array\",\"array\",\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),h=s({args:[\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"})},{\"cwise-compiler\":316,dup:322}],413:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],a=t,o=1;a instanceof Array;)r.push(a.length),o*=a.length,a=a[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),i(e,t),e)}},{\"./doConvert.js\":414,ndarray:438}],414:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":316}],415:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,f,h,p,d){this.gl=t,this.shape=e,this.bounds=r,this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=f,this._contourVAO=h,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=p,this._dynamicVAO=d,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.dirty=!0}function o(t,e){for(var r=e.axes&&e.axes.lastCubeProps.axis||F,n=e.showSurface,i=e.showContour,a=0;3>a;++a){n=n||e.surfaceProject[a];for(var o=0;3>o;++o)i=i||e.contourProject[a][o]}for(var a=0;3>a;++a){for(var s=D.projections[a],o=0;16>o;++o)s[o]=0;for(var o=0;4>o;++o)s[5*o]=1;s[5*a]=0,s[12+a]=e.axesBounds[+(r[a]>0)][a],k(s,t.model,s);for(var l=D.clipBounds[a],u=0;2>u;++u)for(var o=0;3>o;++o)l[u][o]=t.clipBounds[u][o];l[0][a]=-1e8,l[1][a]=1e8}return D.showSurface=n,D.showContour=i,D}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||R,n.view=t.view||R,n.projection=t.projection||R,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;2>i;++i)for(var a=n.clipBounds[i],s=0;3>s;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.shape=n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V;var l=U;k(l,n.view,n.model),k(l,n.projection,l),A(l,l);for(var i=0;3>i;++i)n.eyePosition[i]=l[12+i]/l[15];for(var u=l[15],i=0;3>i;++i)u+=this.lightPosition[i]*l[4*i+3];for(var i=0;3>i;++i){for(var c=l[12+i],s=0;3>s;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var f=o(n,this);if(f.showSurface&&e===this.opacity<1){this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vao.draw(r.TRIANGLES,this._vertexCount);for(var i=0;3>i;++i)this.surfaceProject[i]&&(this._shader.uniforms.model=f.projections[i],this._shader.uniforms.clipBounds=f.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(f.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var p=this._contourVAO;p.bind();for(var i=0;3>i;++i){h.uniforms.permutation=I[i],r.lineWidth(this.contourWidth[i]);for(var s=0;s<this.contourLevels[i].length;++s)s===this.highlightLevel[i]?(h.uniforms.contourColor=this.highlightColor[i],h.uniforms.contourTint=this.highlightTint[i]):(0===s||s-1===this.highlightLevel[i])&&(h.uniforms.contourColor=this.contourColor[i],h.uniforms.contourTint=this.contourTint[i]),h.uniforms.height=this.contourLevels[i][s],p.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s])}for(var i=0;3>i;++i){h.uniforms.model=f.projections[i],h.uniforms.clipBounds=f.clipBounds[i];for(var s=0;3>s;++s)if(this.contourProject[i][s]){h.uniforms.permutation=I[s],r.lineWidth(this.contourWidth[s]);for(var d=0;d<this.contourLevels[s].length;++d)d===this.highlightLevel[s]?(h.uniforms.contourColor=this.highlightColor[s],h.uniforms.contourTint=this.highlightTint[s]):(0===d||d-1===this.highlightLevel[s])&&(h.uniforms.contourColor=this.contourColor[s],h.uniforms.contourTint=this.contourTint[s]),h.uniforms.height=this.contourLevels[s][d],p.draw(r.LINES,this._contourCounts[s][d],this._contourOffsets[s][d])}}p=this._dynamicVAO,p.bind();for(var i=0;3>i;++i)if(0!==this._dynamicCounts[i]){h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=I[i],r.lineWidth(this.dynamicWidth[i]),h.uniforms.contourColor=this.dynamicColor[i],h.uniforms.contourTint=this.dynamicTint[i],h.uniforms.height=this.dynamicLevel[i],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]);for(var s=0;3>s;++s)this.contourProject[s][i]&&(h.uniforms.model=f.projections[s],h.uniforms.clipBounds=f.clipBounds[s],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]))}p.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function f(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function h(t){var e=t.gl,r=(t.field||t.coords&&t.coords[2]||_([],[0,0]),L(e)),n=C(e),i=S(e),o=P(e),s=d(e),l=g(e,[{buffer:s,size:4,stride:z,offset:0},{buffer:s,size:2,stride:z,offset:16},{buffer:s,size:3,stride:z,offset:24}]),u=d(e),c=g(e,[{buffer:u,size:4}]),f=d(e),h=g(e,[{buffer:f,size:2,type:e.FLOAT}]),p=v(e,1,j,e.RGBA,e.UNSIGNED_BYTE);p.minFilter=e.LINEAR,p.magFilter=e.LINEAR;var m=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,p,i,o,u,c,f,h),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",m.update(y),m}e.exports=h;var p=t(\"bit-twiddle\"),d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),m=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),k=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),M=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),_=t(\"ndarray\"),E=t(\"./lib/shaders\"),L=E.createShader,S=E.createContourShader,C=E.createPickShader,P=E.createPickContourShader,z=36,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],I=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;3>t;++t){var e=I[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var j=265,N=a.prototype;N.isTransparent=function(){return this.opacity<1},N.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},N.pickSlots=1,N.setPickBase=function(t){this.pickId=t};var F=[0,0,0],D={showSurface:!1,showContour:!1,projections:[R.slice(),R.slice(),R.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:R,view:R,projection:R,inverseModel:R.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1},U=R.slice(),V=[1,0,0,0,1,0,0,0,1];N.draw=function(t){return s.call(this,t,!1)},N.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:R,view:R,projection:R,inverseModel:R,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};N.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||R,r.view=t.view||R,r.projection=t.projection||R,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;2>n;++n)for(var i=r.clipBounds[n],a=0;3>a;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount);for(var n=0;3>n;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;u.bind();for(var a=0;3>a;++a){e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=I[a];for(var n=0;n<this.contourLevels[a].length;++n)l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n])}for(var n=0;3>n;++n){l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n];for(var a=0;3>a;++a)if(this.contourProject[n][a]){l.uniforms.permutation=I[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c])}}u.unbind()}},N.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;2>c;++c)for(var f=c?a:1-a,h=0;2>h;++h)for(var p=h?l:1-l,d=i+c,g=s+h,v=f*p,m=0;3>m;++m)u[m]+=this._field[m].get(d,g)*v;for(var y=this._pickResult.level,b=0;3>b;++b)if(y[b]=M.le(this.contourLevels[b],u[b]),y[b]<0)this.contourLevels[b].length>0&&(y[b]=0);else if(y[b]<this.contourLevels[b].length-1){var x=this.contourLevels[b][y[b]],_=this.contourLevels[b][y[b]+1];Math.abs(x-u[b])>Math.abs(_-u[b])&&(y[b]+=1)}r.index[0]=.5>a?i:i+1,r.index[1]=.5>l?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1];for(var m=0;3>m;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},N.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=f(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=f(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\n",
+       "\"colorBounds\"in t&&(this.colorBounds=t.colorBounds);var e=t.field||t.coords&&t.coords[2]||null;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var r=(e.shape[0]+2)*(e.shape[1]+2);r>this._field[2].data.length&&(m.freeFloat(this._field[2].data),this._field[2].data=m.mallocFloat(p.nextPow2(r))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var n=this.shape,a=0;2>a;++a)this._field[2].size>this._field[a].data.length&&(m.freeFloat(this._field[a].data),this._field[a].data=m.mallocFloat(this._field[2].size)),this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2]);if(t.coords){var o=t.coords;if(!Array.isArray(o)||3!==o.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(var a=0;2>a;++a){for(var s=o[a],c=0;2>c;++c)if(s.shape[c]!==n[c])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[a],s)}}else if(t.ticks){var h=t.ticks;if(!Array.isArray(h)||2!==h.length)throw new Error(\"gl-surface: invalid ticks\");for(var a=0;2>a;++a){var d=h[a];if((Array.isArray(d)||d.length)&&(d=_(d)),d.shape[0]!==n[a])throw new Error(\"gl-surface: invalid tick length\");var g=_(d.data,n);g.stride[a]=d.stride[0],g.stride[1^a]=0,l(this._field[a],g)}}else{for(var a=0;2>a;++a){var v=[0,0];v[a]=1,this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2],v,0)}this._field[0].set(0,0,0);for(var c=0;c<n[0];++c)this._field[0].set(c+1,0,c);this._field[0].set(n[0]+1,0,n[0]-1),this._field[1].set(0,0,0);for(var c=0;c<n[1];++c)this._field[1].set(0,c+1,c);this._field[1].set(0,n[1]+1,n[1]-1)}for(var y=this._field,b=(y[2].size,_(m.mallocFloat(3*y[2].size*2),[3,n[0]+2,n[1]+2,2])),a=0;3>a;++a)T(b.pick(a),y[a],\"mirror\");for(var x=_(m.mallocFloat(3*y[2].size),[n[0]+2,n[1]+2,3]),a=0;a<n[0]+2;++a)for(var c=0;c<n[1]+2;++c){var k=b.get(0,a,c,0),A=b.get(0,a,c,1),M=b.get(1,a,c,0),E=b.get(1,a,c,1),L=b.get(2,a,c,0),S=b.get(2,a,c,1),C=M*S-E*L,P=L*A-S*k,z=k*E-A*M,R=Math.sqrt(C*C+P*P+z*z);1e-8>R?(R=Math.max(Math.abs(C),Math.abs(P),Math.abs(z)),1e-8>R?(z=1,P=C=0,R=1):R=1/R):R=1/Math.sqrt(R),x.set(a,c,0,C*R),x.set(a,c,1,P*R),x.set(a,c,2,z*R)}m.free(b.data);for(var I=[1/0,1/0,1/0],j=[-(1/0),-(1/0),-(1/0)],N=(n[0]-1)*(n[1]-1)*6,F=m.mallocFloat(p.nextPow2(9*N)),D=0,B=0,a=0;a<n[0]-1;++a)t:for(var c=0;c<n[1]-1;++c){for(var U=0;2>U;++U)for(var V=0;2>V;++V)for(var q=0;3>q;++q){var H=this._field[q].get(1+a+U,1+c+V);if(isNaN(H)||!isFinite(H))continue t}for(var q=0;6>q;++q){var G=a+O[q][0],Y=c+O[q][1],X=this._field[0].get(G+1,Y+1),W=this._field[1].get(G+1,Y+1),H=this._field[2].get(G+1,Y+1),C=x.get(G+1,Y+1,0),P=x.get(G+1,Y+1,1),z=x.get(G+1,Y+1,2);F[D++]=G,F[D++]=Y,F[D++]=X,F[D++]=W,F[D++]=H,F[D++]=0,F[D++]=C,F[D++]=P,F[D++]=z,I[0]=Math.min(I[0],X),I[1]=Math.min(I[1],W),I[2]=Math.min(I[2],H),j[0]=Math.max(j[0],X),j[1]=Math.max(j[1],W),j[2]=Math.max(j[2],H),B+=1}}this._vertexCount=B,this._coordinateBuffer.update(F.subarray(0,D)),m.freeFloat(F),m.free(x.data),this.bounds=[I,j]}var Z=!1;if(\"levels\"in t){var $=t.levels;$=Array.isArray($[0])?$.slice():[[],[],$];for(var a=0;3>a;++a)$[a]=$[a].slice(),$.sort(function(t,e){return t-e});t:for(var a=0;3>a;++a){if($[a].length!==this.contourLevels[a].length){Z=!0;break}for(var c=0;c<$[a].length;++c)if($[a][c]!==this.contourLevels[a][c]){Z=!0;break t}}this.contourLevels=$}if(Z){for(var y=this._field,n=this.shape,K=[],Q=0;3>Q;++Q){for(var $=this.contourLevels[Q],J=[],tt=[],et=[0,0],a=0;a<$.length;++a){var rt=w(this._field[Q],$[a]);J.push(K.length/4|0);var B=0;t:for(var c=0;c<rt.cells.length;++c)for(var nt=rt.cells[c],q=0;2>q;++q){var it=rt.positions[nt[q]],at=it[0],ot=0|Math.floor(at),st=at-ot,lt=it[1],ut=0|Math.floor(lt),ct=lt-ut,ft=!1;e:for(var ht=0;2>ht;++ht){et[ht]=0;for(var pt=(Q+ht+1)%3,U=0;2>U;++U)for(var dt=U?st:1-st,G=0|Math.min(Math.max(ot+U,0),n[0]),V=0;2>V;++V){var gt=V?ct:1-ct,Y=0|Math.min(Math.max(ut+V,0),n[1]),H=this._field[pt].get(G,Y);if(!isFinite(H)||isNaN(H)){ft=!0;break e}var vt=dt*gt;et[ht]+=vt*H}}if(ft){if(q>0){for(var mt=0;4>mt;++mt)K.pop();B-=1}continue t}K.push(et[0],et[1],it[0],it[1]),B+=1}tt.push(B)}this._contourOffsets[Q]=J,this._contourCounts[Q]=tt}for(var yt=m.mallocFloat(K.length),a=0;a<K.length;++a)yt[a]=K[a];this._contourBuffer.update(yt),m.freeFloat(yt)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},N.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;3>t;++t)m.freeFloat(this._field[t].data)},N.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;3>e;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=m.mallocFloat(12*i[0]*i[1]),o=0;3>o;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],f=this._field[l],h=w(u,r[o]),p=h.cells,d=h.positions;this._dynamicOffsets[o]=n;for(var e=0;e<p.length;++e)for(var g=p[e],v=0;2>v;++v){var y=d[g[v]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),k=b-x,A=1-k,M=+y[1],T=0|M,E=0|Math.min(T+1,i[1]),L=M-T,S=1-L,C=A*S,P=A*L,z=k*S,R=k*L,O=C*c.get(x,T)+P*c.get(x,E)+z*c.get(_,T)+R*c.get(_,E),I=C*f.get(x,T)+P*f.get(x,E)+z*f.get(_,T)+R*f.get(_,E);if(isNaN(O)||isNaN(I)){v&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=I,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),m.freeFloat(a)}}},{\"./lib/shaders\":410,\"binary-search-bounds\":411,\"bit-twiddle\":299,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,\"ndarray-gradient\":412,\"ndarray-ops\":437,\"ndarray-pack\":413,\"surface-nets\":457,\"typedarray-pool\":463}],416:[function(t,e,r){arguments[4][179][0].apply(r,arguments)},{dup:179,ndarray:438,\"ndarray-ops\":437,\"typedarray-pool\":463}],417:[function(t,e,r){arguments[4][42][0].apply(r,arguments)},{dup:42}],418:[function(t,e,r){arguments[4][43][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:43}],419:[function(t,e,r){arguments[4][44][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:44}],420:[function(t,e,r){arguments[4][45][0].apply(r,arguments)},{\"./lib/vao-emulated.js\":418,\"./lib/vao-native.js\":419,dup:45}],421:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;t>=r;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var n=0;t>=n;++n)this.tuple[n]=this.vertices[n];var i=f[t];i||(i=f[t]=o(t)),this.orient=i}function l(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(i>=r)throw new Error(\"Must input at least d+1 points\");var a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new 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i={fontSize:parseInt(c.style(\"font-size\"),10)};a(f[2],i,function(i,a,o){p.selectAll(\"svg.\"+d).remove(),p.selectAll(\"g.\"+d+\"-group\").remove();var s=i&&i.select(\"svg\");if(!s||!s.node())return r(),void t();var l=p.append(\"g\").classed(d+\"-group\",!0).attr({\"pointer-events\":\"none\"});l.node().appendChild(s.node()),a&&a.node()&&s.node().insertBefore(a.node().cloneNode(!0),s.node().firstChild),s.attr({\"class\":d,height:o.height,preserveAspectRatio:\"xMinYMin meet\"}).style({overflow:\"visible\",\"pointer-events\":\"none\"});var u=c.style(\"fill\")||\"black\";s.select(\"g\").attr({fill:u,stroke:u});var f=n(s,\"width\"),h=n(s,\"height\"),g=+c.attr(\"x\")-f*{start:0,middle:.5,end:1}[c.attr(\"text-anchor\")||\"start\"],v=parseInt(c.style(\"font-size\"),10)||n(c,\"height\"),m=-v/4;\"y\"===d[0]?(l.attr({transform:\"rotate(\"+[-90,+c.attr(\"x\"),+c.attr(\"y\")]+\") 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t=u.select(l.Lib.getPlotDiv(o.node())),e=t.select(\".svg-container\"),n=e.append(\"div\");n.classed(\"plugin-editable editable\",!0).style({position:\"absolute\",\"font-family\":o.style(\"font-family\")||\"Arial\",\"font-size\":o.style(\"font-size\")||12,color:r.fill||o.style(\"fill\")||\"black\",opacity:1,\"background-color\":r.background||\"transparent\",outline:\"#ffffff33 1px solid\",margin:[-parseFloat(o.style(\"font-size\"))/8+1,0,0,-1].join(\"px \")+\"px\",padding:\"0\",\"box-sizing\":\"border-box\"}).attr({contenteditable:!0}).text(r.text||o.attr(\"data-unformatted\")).call(s(o,e,r)).on(\"blur\",function(){o.text(this.textContent).style({opacity:1});var t,e=u.select(this).attr(\"class\");t=e?\".\"+e.split(\" \")[0]+\"-math-group\":\"[class*=-math-group]\",t&&u.select(o.node().parentNode).select(t).style({opacity:0});var r=this.textContent;u.select(this).transition().duration(0).remove(),u.select(document).on(\"mouseup\",null),c.edit.call(o,r)}).on(\"focus\",function(){var t=this;u.select(document).on(\"mouseup\",function(){return u.event.target===t?!1:void(document.activeElement===n.node()&&n.node().blur())})}).on(\"keyup\",function(){27===u.event.which?(o.style({opacity:1}),u.select(this).style({opacity:0}).on(\"blur\",function(){return!1}).transition().remove(),c.cancel.call(o,this.textContent)):(c.input.call(o,this.textContent),u.select(this).call(s(o,e,r)))}).on(\"keydown\",function(){13===u.event.which&&this.blur()}).call(i)}r||(r={});var o=this,c=u.dispatch(\"edit\",\"input\",\"cancel\"),f=u.select(this.node()).style({\"pointer-events\":\"all\"}),h=e||f;return e&&f.style({\"pointer-events\":\"none\"}),r.immediate?n():h.on(\"click\",n),u.rebind(this,c,\"on\")}},{\"../constants/xmlns_namespaces\":567,\"../plotly\":595,d3:320}],590:[function(t,e,r){\"use strict\";var n=e.exports={},i=t(\"../constants/geo_constants\").locationmodeToLayer,a=t(\"topojson\").feature;n.getTopojsonName=function(t){return[t.scope.replace(/ /g,\"-\"),\"_\",t.resolution.toString(),\"m\"].join(\"\")},n.getTopojsonPath=function(t,e){return t+e+\".json\"},n.getTopojsonFeatures=function(t,e){var r=i[t.locationmode],n=e.objects[r];return a(e,n).features}},{\"../constants/geo_constants\":563,topojson:460}],591:[function(t,e,r){\"use strict\";function n(t){var e;if(\"string\"==typeof t){if(e=document.getElementById(t),null===e)throw new Error(\"No DOM element with id '\"+t+\"' exists on the page.\");return e}if(null===t||void 0===t)throw new Error(\"DOM element provided is null or undefined\");return t}function i(t,e){t._fullLayout._paperdiv.style(\"background\",\"white\"),P.defaultConfig.setBackground(t,e)}function a(t,e){t._context||(t._context=z.extendFlat({},P.defaultConfig));var r=t._context;e&&(Object.keys(e).forEach(function(t){t in r&&(\"setBackground\"===t&&\"opaque\"===e[t]?r[t]=i:r[t]=e[t])}),e.plot3dPixelRatio&&!r.plotGlPixelRatio&&(r.plotGlPixelRatio=r.plot3dPixelRatio)),r.staticPlot&&(r.editable=!1,r.autosizable=!1,r.scrollZoom=!1,r.doubleClick=!1,r.showTips=!1,r.showLink=!1,r.displayModeBar=!1)}function o(t,e,r){var n=L.select(t).selectAll(\".plot-container\").data([0]);n.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=n.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),P.micropolar.manager.fillLayout(t),\"initial\"===t._fullLayout.autosize&&t._context.autosizable&&(w(t,{}),t._fullLayout.autosize=r.autosize=!0),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=P.micropolar.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var a=t.framework.svg(),o=1,s=t._fullLayout.title;\"\"!==s&&s||(o=0);var l=\"Click to enter title\",u=function(){this.call(P.util.convertToTspans)},c=a.select(\".title-group text\").call(u);if(t._context.editable){c.attr({\"data-unformatted\":s}),s&&s!==l||(o=.2,c.attr({\"data-unformatted\":l}).text(l).style({opacity:o}).on(\"mouseover.opacity\",function(){L.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){L.select(this).transition().duration(1e3).style(\"opacity\",0)}));var f=function(){this.call(P.util.makeEditable).on(\"edit\",function(e){t.framework({layout:{title:e}}),this.attr({\"data-unformatted\":e}).text(e).call(u),this.call(f)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};c.call(f)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),I.addLinks(t),Promise.resolve()}function s(t){var e,r;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1);var n=P.Axes.list({_fullLayout:t});for(e=0;e<n.length;e++){var i=n[e];i.anchor&&\"free\"!==i.anchor&&(i.anchor=P.Axes.cleanId(i.anchor)),i.overlaying&&(i.overlaying=P.Axes.cleanId(i.overlaying)),i.type||(i.isdate?i.type=\"date\":i.islog?i.type=\"log\":i.isdate===!1&&i.islog===!1&&(i.type=\"linear\")),(\"withzero\"===i.autorange||\"tozero\"===i.autorange)&&(i.autorange=!0,i.rangemode=\"tozero\"),delete i.islog,delete i.isdate,delete i.categories,f(i,\"domain\")&&delete i.domain,void 0!==i.autotick&&(void 0===i.tickmode&&(i.tickmode=i.autotick?\"auto\":\"linear\"),delete i.autotick)}void 0===t.annotations||Array.isArray(t.annotations)||(console.log(\"annotations must be an array\"),delete t.annotations);var a=(t.annotations||[]).length;for(e=0;a>e;e++){var o=t.annotations[e];o.ref&&(\"paper\"===o.ref?(o.xref=\"paper\",o.yref=\"paper\"):\"data\"===o.ref&&(o.xref=\"x\",o.yref=\"y\"),delete 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i(t){return new n(t)}var a=t(\"../../plotly\"),o=t(\"../../lib/html2unicode\"),s=t(\"../../lib/str2rgbarray\"),l=n.prototype,u=[\"xaxis\",\"yaxis\"];l.merge=function(t){this.titleEnable=!1,this.backgroundColor=s(t.plot_bgcolor);var e,r,n,i,a,l,c,f,h,p,d;for(p=0;2>p;++p){for(e=u[p],r=t[this.scene[e]._name],n=/Click to enter .+ title/.test(r.title)?\"\":r.title,d=0;2>=d;d+=2)this.labelEnable[p+d]=!1,this.labels[p+d]=o(n),this.labelColor[p+d]=s(r.titlefont.color),this.labelFont[p+d]=r.titlefont.family,this.labelSize[p+d]=r.titlefont.size,this.labelPad[p+d]=this.getLabelPad(e,r),this.tickEnable[p+d]=!1,this.tickColor[p+d]=s((r.tickfont||{}).color),this.tickAngle[p+d]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[p+d]=this.getTickPad(r),this.tickMarkLength[p+d]=0,this.tickMarkWidth[p+d]=r.tickwidth||0,this.tickMarkColor[p+d]=s(r.tickcolor),this.borderLineEnable[p+d]=!1,this.borderLineColor[p+d]=s(r.linecolor),this.borderLineWidth[p+d]=r.linewidth||0;c=this.hasSharedAxis(r),a=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,i=r.mirror||!1,f=c?-1!==String(i).indexOf(\"all\"):!!i,h=c?\"allticks\"===i:-1!==String(i).indexOf(\"ticks\"),a?this.labelEnable[p]=!0:l&&(this.labelEnable[p+2]=!0),a?this.tickEnable[p]=r.showticklabels:l&&(this.tickEnable[p+2]=r.showticklabels),(a||f)&&(this.borderLineEnable[p]=r.showline),(l||f)&&(this.borderLineEnable[p+2]=r.showline),(a||h)&&(this.tickMarkLength[p]=this.getTickMarkLength(r)),(l||h)&&(this.tickMarkLength[p+2]=this.getTickMarkLength(r)),this.gridLineEnable[p]=r.showgrid,this.gridLineColor[p]=s(r.gridcolor),this.gridLineWidth[p]=r.gridwidth,this.zeroLineEnable[p]=r.zeroline,this.zeroLineColor[p]=s(r.zerolinecolor),this.zeroLineWidth[p]=r.zerolinewidth}},l.hasSharedAxis=function(t){var e=this.scene,r=a.Plots.getSubplotIds(e.fullLayout,\"gl2d\"),n=a.Axes.findSubplotsWithAxis(r,t);return 0!==n.indexOf(e.id)},l.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},l.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},l.getLabelPad=function(t,e){var r=1.5,n=e.titlefont.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?-10+n*(r+(i?1:0)):-10+n*(r+(i?.5:0)):\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},l.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},l.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":577,\"../../lib/str2rgbarray\":588,\"../../plotly\":595}],626:[function(t,e,r){\"use strict\";var n=t(\"../../plotly\"),i=t(\"./scene2d\"),a=n.Plots;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex={x:/^x([2-9]|[1-9][0-9]+)?$/,y:/^y([2-9]|[1-9][0-9]+)?$/},r.attrRegex={x:/^xaxis([2-9]|[1-9][0-9]+)?$/,y:/^yaxis([2-9]|[1-9][0-9]+)?$/},r.attributes=t(\"../cartesian/attributes\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=a.getSubplotIds(e,\"gl2d\"),o=0;o<n.length;o++){var s=n[o],l=e._plots[s],u=a.getSubplotData(r,\"gl2d\",s),c=l._scene2d;void 0===c&&(c=new i({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),l._scene2d=c),c.plot(u,e,t.layout)}}},{\"../../plotly\":595,\"../cartesian/attributes\":597,\"./scene2d\":627}],627:[function(t,e,r){\"use strict\";function n(t,e){this.container=t.container,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.updateAxes(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=d(this),this.traces={},this.spikes=f(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;2>r;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/plots\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),f=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),p=t(\"./convert\"),d=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),m=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o){a=document.createElement(\"canvas\");try{o=a.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0})}catch(t){throw new Error([\"Error creating static canvas/context for image server\"].join(\" \"))}}this.canvas=a,this.gl=o}else{var e,r=document.createElement(\"canvas\"),n={premultipliedAlpha:!0};try{e=r.getContext(\"webgl\",n)}catch(t){}if(!e)try{e=r.getContext(\"experimental-webgl\",n)}catch(t){}e||v(this),this.canvas=r,this.gl=e}var i=this.canvas,s=this.pixelRatio,l=this.fullLayout;i.width=0|Math.ceil(s*l.width),i.height=0|Math.ceil(s*l.height),i.style.width=\"100%\",i.style.height=\"100%\",i.style.position=\"absolute\",i.style.top=\"0px\",i.style.left=\"0px\",i.style[\"pointer-events\"]=\"none\";var u=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");u.style.position=\"absolute\",u.style.top=u.style.left=\"0px\",u.style.width=u.style.height=\"100%\",u.style[\"z-index\"]=20,u.style[\"pointer-events\"]=\"none\";var c=this.mouseContainer=document.createElement(\"div\");c.style.position=\"absolute\";var f=this.container;f.appendChild(i),f.appendChild(u),f.appendChild(c)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.glplot.setDirty(!0),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=n-1;s>o;++o,--s)for(var l=0;r>l;++l)for(var u=0;4>u;++u){var c=i[4*(r*o+l)+u];i[4*(r*o+l)+u]=i[4*(r*s+l)+u],i[4*(r*s+l)+u]=c}var f=document.createElement(\"canvas\");f.width=r,f.height=n;var h=f.getContext(\"2d\"),p=h.createImageData(r,n);p.data.set(i),h.putImageData(p,0,0);var d;switch(t){case\"jpeg\":d=f.toDataURL(\"image/jpeg\");break;case\"webp\":d=f.toDataURL(\"image/webp\");break;default:d=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(a),d},y.computeTickMarks=function(){\n",
+       "this.xaxis._length=this.glplot.viewBox[2]-this.glplot.viewBox[0],this.yaxis._length=this.glplot.viewBox[3]-this.glplot.viewBox[1];for(var t=[l.calcTicks(this.xaxis),l.calcTicks(this.yaxis)],e=0;2>e;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=g(t[e][r].text+\"\").replace(/\\n/g,\" \");return t},y.updateAxes=function(t){var e=l.subplotMatch,r=\"xaxis\"+this.id.match(e)[1],n=\"yaxis\"+this.id.match(e)[2];this.xaxis=t[r],this.yaxis=t[n]},y.updateFx=function(t){var e=this.fullLayout;e.dragmode=t.dragmode,e.hovermode=t.hovermode},y.cameraChanged=function(){var t=this.camera,e=this.xaxis.range,r=this.yaxis.range;this.glplot.setDataBox([e[0],r[0],e[1],r[1]]);var n=this.computeTickMarks(),a=this.glplotOptions.ticks;i(n,a)&&(this.glplotOptions.ticks=n,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions))},y.destroy=function(){this.glplot.dispose()},y.plot=function(t,e){var r,n,i=this.glplot,a=this.pixelRatio;this.fullLayout=e,this.updateAxes(e);var o=e.width,u=e.height,c=0|Math.ceil(a*o),f=0|Math.ceil(a*u),h=this.canvas;(h.width!==c||h.height!==f)&&(h.width=c,h.height=f),t?Array.isArray(t)||(t=[t]):t=[];var p,d;for(r=0;r<t.length;++r){if(p=t[r],d=this.traces[p.uid])d.update(p);else{var g=s.getModule(p.type);d=g.plot(this,p)}this.traces[p.uid]=d}var v=Object.keys(this.traces);t:for(r=0;r<v.length;++r){for(n=0;n<t.length;++n)if(t[n].uid===v[r])continue t;d=this.traces[v[r]],d.dispose(),delete this.traces[v[r]]}var y=this.glplotOptions;y.merge(e),y.screenBox=[0,0,o,u];var b=e._size,x=this.xaxis.domain,_=this.yaxis.domain;y.viewBox=[b.l+x[0]*b.w,b.b+_[0]*b.h,o-b.r-(1-x[1])*b.w,u-b.t-(1-_[1])*b.h],this.mouseContainer.style.width=b.w*(x[1]-x[0])+\"px\",this.mouseContainer.style.height=b.h*(_[1]-_[0])+\"px\",this.mouseContainer.height=b.h*(_[1]-_[0]),this.mouseContainer.style.left=b.l+x[0]*b.w+\"px\",this.mouseContainer.style.top=b.t+(1-_[1])*b.h+\"px\";var w=this.bounds;for(w[0]=w[1]=1/0,w[2]=w[3]=-(1/0),v=Object.keys(this.traces),r=0;r<v.length;++r){d=this.traces[v[r]];for(var k=0;2>k;++k)w[k]=Math.min(w[k],d.bounds[k]),w[k+2]=Math.max(w[k+2],d.bounds[k+2])}var A;for(r=0;2>r;++r)w[r]>w[r+2]&&(w[r]=-1,w[r+2]=1),A=this[m[r]],A._length=y.viewBox[r+2]-y.viewBox[r],l.doAutoRange(A);y.ticks=this.computeTickMarks();var M=this.xaxis.range,T=this.yaxis.range;y.dataBox=[M[0],T[0],M[1],T[1]],y.merge(e),i.update(y)},y.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=this.fullLayout;this.cameraChanged();var i=r.x*t.pixelRatio,a=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===n.dragmode)this.selectBox.enabled=!0,this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],t.setDirty();else{this.selectBox.enabled=!1;var o=n._size,s=this.xaxis.domain,l=this.yaxis.domain,c=t.pick(i/t.pixelRatio+o.l+s[0]*o.w,a/t.pixelRatio-(o.t+(1-l[1])*o.h));if(c&&n.hovermode){var f=c.object._trace.handlePick(c);if(f&&(!this.lastPickResult||this.lastPickResult.trace!==f.trace||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var h=this.lastPickResult=f;this.spikes.update({center:c.dataCoord}),h.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(c.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(c.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio];var p=h.hoverinfo;if(\"all\"!==p){var d=p.split(\"+\");-1===d.indexOf(\"x\")&&(h.traceCoord[0]=void 0),-1===d.indexOf(\"y\")&&(h.traceCoord[1]=void 0),-1===d.indexOf(\"text\")&&(h.textLabel=void 0),-1===d.indexOf(\"name\")&&(h.name=void 0)}u.loneHover({x:h.screenCoord[0],y:h.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",h.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",h.traceCoord[1]),text:h.textLabel,name:h.name,color:h.color},{container:this.svgContainer}),this.lastPickResult={dataCoord:c.dataCoord}}}else!c&&this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,u.loneUnhover(this.svgContainer))}t.draw()}},y.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return l.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../lib/html2unicode\":577,\"../../lib/show_no_webgl_msg\":586,\"../../plots/cartesian/axes\":598,\"../../plots/cartesian/graph_interact\":603,\"../../plots/plots\":642,\"./camera\":624,\"./convert\":625,\"gl-plot2d\":371,\"gl-select-box\":383,\"gl-spikes2d\":409}],628:[function(t,e,r){\"use strict\";function n(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var n=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),l=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],u=0,c=t.clientWidth,f=t.clientHeight,h={keyBindingMode:\"rotate\",view:n,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:n.modes,tick:function(){var e=i(),r=this.delay,a=e-2*r;n.idle(e-r),n.recalcMatrix(a),n.flush(e-(100+2*r));for(var o=!0,s=n.computedMatrix,h=0;16>h;++h)o=o&&l[h]===s[h],l[h]=s[h];var p=t.clientWidth===c&&t.clientHeight===f;return c=t.clientWidth,f=t.clientHeight,o?!p:(u=Math.exp(n.computedRadius[0]),!0)},lookAt:function(t,e,r){n.lookAt(n.lastT(),t,e,r)},rotate:function(t,e,r){n.rotate(n.lastT(),t,e,r)},pan:function(t,e,r){n.pan(n.lastT(),t,e,r)},translate:function(t,e,r){n.translate(n.lastT(),t,e,r)}};Object.defineProperties(h,{matrix:{get:function(){return n.computedMatrix},set:function(t){return n.setMatrix(n.lastT(),t),n.computedMatrix},enumerable:!0},mode:{get:function(){return n.getMode()},set:function(t){var e=n.computedUp.slice(),r=n.computedEye.slice(),a=n.computedCenter.slice();if(n.setMode(t),\"turntable\"===t){var o=i();n._active.lookAt(o,r,a,e),n._active.lookAt(o+500,r,a,[0,0,1]),n._active.flush(o)}return n.getMode()},enumerable:!0},center:{get:function(){return n.computedCenter},set:function(t){return n.lookAt(n.lastT(),null,t),n.computedCenter},enumerable:!0},eye:{get:function(){return n.computedEye},set:function(t){return n.lookAt(n.lastT(),t),n.computedEye},enumerable:!0},up:{get:function(){return n.computedUp},set:function(t){return n.lookAt(n.lastT(),null,null,t),n.computedUp},enumerable:!0},distance:{get:function(){return u},set:function(t){return n.setDistance(n.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return n.getDistanceLimits(r)},set:function(t){return n.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1});var p=0,d=0;return o(t,function(e,r,a,o){var s=\"rotate\"===h.keyBindingMode,l=\"pan\"===h.keyBindingMode,c=\"zoom\"===h.keyBindingMode,f=!!o.control,g=!!o.alt,v=!!o.shift,m=!!(1&e),y=!!(2&e),b=!!(4&e),x=1/t.clientHeight,_=x*(r-p),w=x*(a-d),k=h.flipX?1:-1,A=h.flipY?1:-1,M=i(),T=Math.PI*h.rotateSpeed;if((s&&m&&!f&&!g&&!v||m&&!f&&!g&&v)&&n.rotate(M,k*T*_,-A*T*w,0),(l&&m&&!f&&!g&&!v||y||m&&f&&!g&&!v)&&n.pan(M,-h.translateSpeed*_*u,h.translateSpeed*w*u,0),c&&m&&!f&&!g&&!v||b||m&&!f&&g&&!v){var E=-h.zoomSpeed*w/window.innerHeight*(M-n.lastT())*100;n.pan(M,0,0,u*(Math.exp(E)-1))}return p=r,d=a,!0}),s(t,function(t,e){var r=h.flipX?1:-1,a=h.flipY?1:-1,o=i();if(Math.abs(t)>Math.abs(e))n.rotate(o,0,0,-t*r*Math.PI*h.rotateSpeed/window.innerWidth);else{var s=-h.zoomSpeed*a*e/window.innerHeight*(o-n.lastT())/100;n.pan(o,0,0,u*(Math.exp(s)-1))}},!0),h}e.exports=n;var i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":288,\"mouse-change\":426,\"mouse-wheel\":430,\"right-now\":440}],629:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"gl3d\",s),u=e[s]._scene;void 0===u&&(u=new n({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),e[s]._scene=u),u.plot(l,e,t.layout)}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\"),r.initAxes=function(t){var e=t._fullLayout;delete e.xaxis,delete e.yaxis;for(var r=i.getSubplotIds(e,\"gl3d\"),n=0;n<r.length;++n)for(var o=r[n],s=e[o],l=0;3>l;++l){var u=a[l],c=s[u];c._td=t}}},{\"../plots\":642,\"./layout/attributes\":630,\"./layout/defaults\":634,\"./layout/layout_attributes\":635,\"./scene\":639,\"./set_convert\":640}],630:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"sceneid\",dflt:\"scene\"}}},{}],631:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:\"rgb(0,0,0)\"},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},title:n.title,titlefont:n.titlefont,type:n.type,autorange:n.autorange,rangemode:n.rangemode,range:n.range,fixedrange:n.fixedrange,tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,mirror:n.mirror,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:n.tickfont,tickangle:n.tickangle,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:n.showline,linecolor:n.linecolor,linewidth:n.linewidth,showgrid:n.showgrid,gridcolor:i({},n.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:n.gridwidth,zeroline:n.zeroline,zerolinecolor:n.zerolinecolor,zerolinewidth:n.zerolinewidth}},{\"../../../lib/extend\":574,\"../../cartesian/layout_attributes\":605}],632:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"./axis_attributes\"),a=t(\"../../cartesian/axis_defaults\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=function(){};e.exports=function(t,e,r){function l(t,e){return n.coerce(u,c,i,t,e)}for(var u,c,f=0;f<o.length;f++){var h=o[f];u=t[h]||{},c={_id:h[0]+r.scene,_name:h},e[h]=c=a(u,c,l,{font:r.font,letter:h[0],data:r.data,showGrid:!0}),l(\"gridcolor\"),l(\"title\",h[0]),c.setScale=s,l(\"showspikes\")&&(l(\"spikesides\"),l(\"spikethickness\"),l(\"spikecolor\")),l(\"showbackground\")&&l(\"backgroundcolor\"),l(\"showaxeslabels\")}}},{\"../../../lib\":578,\"../../cartesian/axis_defaults\":599,\"./axis_attributes\":631}],633:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=l(this.tickPad),this._defaultLabelPad=l(this.labelPad),this._defaultLineTickLength=l(this.lineTickLength)}function i(t){var e=new n;return e.merge(t),e}var a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;3>r;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":577,\"../../../lib/str2rgbarray\":588,arraytools:298}],634:[function(t,e,r){\"use strict\";var n=t(\"../../../plotly\"),i=t(\"./layout_attributes\"),a=t(\"./axis_defaults\");e.exports=function(t,e,r){function o(t,e){return n.Lib.coerce(u,c,i,t,e)}if(e._hasGL3D){var s,l=n.Plots.getSubplotIdsInData(r,\"gl3d\");delete e.xaxis,delete e.yaxis;var u,c,f=l.length;for(s=0;f>s;++s){var h=l[s];void 0!==t[h]?u=t[h]:t[h]=u={},c=e[h]||{},o(\"bgcolor\");for(var p=Object.keys(i.camera),d=0;d<p.length;d++)o(\"camera.\"+p[d]+\".x\"),o(\"camera.\"+p[d]+\".y\"),o(\"camera.\"+p[d]+\".z\");o(\"domain.x\",[s/f,(s+1)/f]),o(\"domain.y\");var g=!!o(\"aspectratio.x\")&&!!o(\"aspectratio.y\")&&!!o(\"aspectratio.z\"),v=g?\"manual\":\"auto\",m=o(\"aspectmode\",v);g||(u.aspectratio=c.aspectratio={x:1,y:1,z:1},\"manual\"===m&&(c.aspectmode=\"auto\")),a(u,c,{font:e.font,scene:h,data:r}),e[h]=c}}}},{\"../../../plotly\":595,\"./axis_defaults\":632,\"./layout_attributes\":635}],635:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":574,\"./axis_attributes\":631}],636:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;3>e;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":588}],637:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;3>r;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,u=[[],[],[]],c=0;3>c;++c){var f=i[s[c]];if(f._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(f._length)===1/0)u[c]=[];else{f.range[0]=r[c].lo/t.dataScale[c],f.range[1]=r[c].hi/t.dataScale[c],f._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var h=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var p=f.nticks||a.Lib.constrain(f._length/40,4,9);a.Axes.autoTicks(f,Math.abs(f.range[1]-f.range[0])/p)}for(var d=a.Axes.calcTicks(f),g=0;g<d.length;++g)d[g].x=d[g].x*t.dataScale[c],d[g].text=o(d[g].text);u[c]=d,f.tickmode=h}}e.ticks=u;for(var c=0;3>c;++c){l[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(var g=0;2>g;++g)e.bounds[g][c]=t.glplot.bounds[g][c]}t.contourLevels=n(u)}e.exports=i;var a=t(\"../../../plotly\"),o=t(\"../../../lib/html2unicode\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"],l=[0,0,0]},{\"../../../lib/html2unicode\":577,\"../../../plotly\":595}],638:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;4>r;++r)for(n=0;4>n;++n)i[n]+=t[4*r+n]*e[r];return i}function i(t,e){var r=n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])));return r}e.exports=i},{}],639:[function(t,e,r){\"use strict\";function n(t){function e(e,r){if(void 0!==r){if(\"string\"==typeof r)return r;var n=t.fullSceneLayout[e];return p.tickText(n,n.c2l(r),\"hover\").text}}var r=t.svgContainer,n=t.container.getBoundingClientRect(),i=n.width,a=n.height;r.setAttributeNS(null,\"viewBox\",\"0 0 \"+i+\" \"+a),r.setAttributeNS(null,\"width\",i),r.setAttributeNS(null,\"height\",a),w(t),t.glplot.axes.update(t.axesOptions);for(var o=Object.keys(t.traces),s=null,l=t.glplot.selection,u=0;u<o.length;++u){var c=t.traces[o[u]];c.handlePick(l)&&(s=c),c.setContourLevels&&c.setContourLevels()}if(null!==s){var f=y(t.glplot.cameraParams,l.dataCoordinate),h=s.data.hoverinfo;if(\"all\"!==h){var g=h.split(\"+\");-1===g.indexOf(\"x\")&&(l.traceCoordinate[0]=void 0),-1===g.indexOf(\"y\")&&(l.traceCoordinate[1]=void 0),-1===g.indexOf(\"z\")&&(l.traceCoordinate[2]=void 0),-1===g.indexOf(\"text\")&&(l.textLabel=void 0),-1===g.indexOf(\"name\")&&(s.name=void 0)}d.loneHover({x:(.5+.5*f[0]/f[3])*i,y:(.5-.5*f[1]/f[3])*a,xLabel:e(\"xaxis\",l.traceCoordinate[0]),yLabel:e(\"yaxis\",l.traceCoordinate[1]),zLabel:e(\"zaxis\",l.traceCoordinate[2]),text:l.textLabel,name:s.name,color:s.color},{container:r})}else d.loneUnhover(r)}function i(t,e,r,i){var a={canvas:r,gl:i,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1};if(t.staticMode){if(!u){l=document.createElement(\"canvas\");try{u=l.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0})}catch(o){throw new Error(\"error creating static canvas/context for image server\")}}a.pixelRatio=t.pixelRatio,a.gl=u,a.canvas=l}try{t.glplot=c(a)}catch(o){v(t)}if(t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(t){console.log(\"lost context\"),t.preventDefault()}),!t.camera){var s=e.scene.camera;t.camera=m(t.container,{center:[s.center.x,s.center.y,s.center.z],eye:[s.eye.x,s.eye.y,s.eye.z],up:[s.up.x,s.up.y,s.up.z],zoomMin:.1,zoomMax:100,mode:\"orbit\"})}return t.glplot.mouseListener.enabled=!1,t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=n.bind(null,t),t.traces={},!0}function a(t,e){var r=document.createElement(\"div\"),n=t.container,a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.plotArgs=[[],{},{}],this.axesOptions=x(e[this.id]),this.spikeOptions=_(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],!i(this,e)}function o(t,e,r,n){for(var i=0;i<e.length;++i)if(Array.isArray(e[i]))for(var a=0;a<e[i].length;++a){var o=t.d2l(e[i][a]);!isNaN(o)&&isFinite(o)&&(n[0][r]=Math.min(n[0][r],o),n[1][r]=Math.max(n[1][r],o))}else{var 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r=e._size,n=JSON.stringify(r),i=Math.max(e.margin.l||0,0),a=Math.max(e.margin.r||0,0),o=Math.max(e.margin.t||0,0),l=Math.max(e.margin.b||0,0),c=e._pushmargin;return e.margin.autoexpand!==!1&&(c.base={l:{val:0,size:i},r:{val:1,size:a},t:{val:1,size:o},b:{val:0,size:l}},Object.keys(c).forEach(function(t){var r=c[t].l||{},n=c[t].b||{},s=r.val,f=r.size,h=n.val,p=n.size;Object.keys(c).forEach(function(t){if(u(f)&&c[t].r){var r=c[t].r.val,n=c[t].r.size;if(r>s){var d=(f*r+(n-e.width)*s)/(r-s),g=(n*(1-s)+(f-e.width)*(1-r))/(r-s);d>=0&&g>=0&&d+g>i+a&&(i=d,a=g)}}if(u(p)&&c[t].t){var v=c[t].t.val,m=c[t].t.size;if(v>h){var y=(p*v+(m-e.height)*h)/(v-h),b=(m*(1-h)+(p-e.height)*(1-v))/(v-h);y>=0&&b>=0&&y+b>l+o&&(l=y,o=b)}}})})),r.l=Math.round(i),r.r=Math.round(a),r.t=Math.round(o),r.b=Math.round(l),r.p=Math.round(e.margin.pad),r.w=Math.round(e.width)-r.l-r.r,r.h=Math.round(e.height)-r.t-r.b,t._replotting||\"{}\"===n||n===JSON.stringify(e._size)?void 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i=t(\"../cartesian/layout_attributes\"),a=t(\"../../lib/extend\").extendFlat,o=a({},i.domain,{});e.exports={radialaxis:n(\"radial\",{range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},domain:o,orientation:{valType:\"number\"}}),angularaxis:n(\"angular\",{range:{valType:\"info_array\",items:[{valType:\"number\",dflt:0},{valType:\"number\",dflt:360}]},domain:o}),layout:{direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"]},orientation:{valType:\"angle\"}}}},{\"../../lib/extend\":574,\"../cartesian/layout_attributes\":605}],645:[function(t,e,r){var n=t(\"../../plotly\"),i=t(\"d3\"),a=e.exports={version:\"0.2.2\",manager:t(\"./micropolar_manager\")},o=n.Lib.extendDeepAll;a.Axis=function(){function t(t){r=t||r;var u=l.data,f=l.layout;return(\"string\"==typeof r||r.nodeName)&&(r=i.select(r)),r.datum(u).each(function(t,r){function l(t,e){return s(t)%360+f.orientation}var u=t.slice();c={data:a.util.cloneJson(u),layout:a.util.cloneJson(f)};var h=0;u.forEach(function(t,e){t.color||(t.color=f.defaultColorRange[h],h=(h+1)%f.defaultColorRange.length),t.strokeColor||(t.strokeColor=\"LinePlot\"===t.geometry?t.color:i.rgb(t.color).darker().toString()),c.data[e].color=t.color,c.data[e].strokeColor=t.strokeColor,c.data[e].strokeDash=t.strokeDash,c.data[e].strokeSize=t.strokeSize});var p=u.filter(function(t,e){var r=t.visible;return\"undefined\"==typeof r||r===!0}),d=!1,g=p.map(function(t,e){return d=d||\"undefined\"!=typeof t.groupId,t});if(d){var v=i.nest().key(function(t,e){return\"undefined\"!=typeof t.groupId?t.groupId:\"unstacked\"}).entries(g),m=[],y=v.map(function(t,e){if(\"unstacked\"===t.key)return t.values;var r=t.values[0].r.map(function(t,e){return 0});return t.values.forEach(function(t,e,n){t.yStack=[r],m.push(r),r=a.util.sumArrays(t.r,r)}),t.values});p=i.merge(y)}p.forEach(function(t,e){t.t=Array.isArray(t.t[0])?t.t:[t.t],t.r=Array.isArray(t.r[0])?t.r:[t.r]});var b=Math.min(f.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2;b=Math.max(10,b);var x,_=[f.margin.left+b,f.margin.top+b];if(d){var w=i.max(a.util.sumArrays(a.util.arrayLast(p).r[0],a.util.arrayLast(m)));x=[0,w]}else x=i.extent(a.util.flattenArray(p.map(function(t,e){return t.r})));f.radialAxis.domain!=a.DATAEXTENT&&(x[0]=0),n=i.scale.linear().domain(f.radialAxis.domain!=a.DATAEXTENT&&f.radialAxis.domain?f.radialAxis.domain:x).range([0,b]),c.layout.radialAxis.domain=n.domain();var k,A=a.util.flattenArray(p.map(function(t,e){return t.t})),M=\"string\"==typeof A[0];M&&(A=a.util.deduplicate(A),k=A.slice(),A=i.range(A.length),p=p.map(function(t,e){var r=t;return t.t=[A],d&&(r.yStack=t.yStack),r}));var T=p.filter(function(t,e){return\"LinePlot\"===t.geometry||\"DotPlot\"===t.geometry}).length===p.length,E=null===f.needsEndSpacing?M||!T:f.needsEndSpacing,L=f.angularAxis.domain&&f.angularAxis.domain!=a.DATAEXTENT&&!M&&f.angularAxis.domain[0]>=0,S=L?f.angularAxis.domain:i.extent(A),C=Math.abs(A[1]-A[0]);T&&!M&&(C=0);var P=S.slice();E&&M&&(P[1]+=C);var z=f.angularAxis.ticksCount||4;z>8&&(z=z/(z/8)+z%8),f.angularAxis.ticksStep&&(z=(P[1]-P[0])/z);var R=f.angularAxis.ticksStep||(P[1]-P[0])/(z*(f.minorTicks+1));k&&(R=Math.max(Math.round(R),1)),P[2]||(P[2]=R);var O=i.range.apply(this,P);if(O=O.map(function(t,e){return parseFloat(t.toPrecision(12))}),s=i.scale.linear().domain(P.slice(0,2)).range(\"clockwise\"===f.direction?[0,360]:[360,0]),c.layout.angularAxis.domain=s.domain(),c.layout.angularAxis.endPadding=E?C:0,e=i.select(this).select(\"svg.chart-root\"),\"undefined\"==typeof e||e.empty()){var I=\"<svg xmlns='http://www.w3.org/2000/svg' class='chart-root'>' + '<g class='outer-group'>' + '<g class='chart-group'>' + '<circle class='background-circle'></circle>' + '<g class='geometry-group'></g>' + '<g class='radial axis-group'>' + '<circle class='outside-circle'></circle>' + '</g>' + '<g class='angular axis-group'></g>' + '<g class='guides-group'><line></line><circle r='0'></circle></g>' + '</g>' + '<g class='legend-group'></g>' + '<g class='tooltips-group'></g>' + '<g class='title-group'><text></text></g>' + '</g>' + '</svg>\",j=(new DOMParser).parseFromString(I,\"application/xml\"),N=this.appendChild(this.ownerDocument.importNode(j.documentElement,!0));e=i.select(N)}e.select(\".guides-group\").style({\"pointer-events\":\"none\"}),e.select(\".angular.axis-group\").style({\"pointer-events\":\"none\"}),e.select(\".radial.axis-group\").style({\"pointer-events\":\"none\"});var F,D=e.select(\".chart-group\"),B={fill:\"none\",stroke:f.tickColor},U={\"font-size\":f.font.size,\"font-family\":f.font.family,fill:f.font.color,\"text-shadow\":[\"-1px 0px\",\"1px -1px\",\"-1px 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q=F.node().getBBox();b=Math.min(f.width-q.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2,b=Math.max(10,b),_=[f.margin.left+b,f.margin.top+b],n.range([0,b]),c.layout.radialAxis.domain=n.domain(),F.attr(\"transform\",\"translate(\"+[_[0]+b,_[1]-b]+\")\")}else F=e.select(\".legend-group\").style({display:\"none\"});e.attr({width:f.width,height:f.height}).style({opacity:f.opacity}),D.attr(\"transform\",\"translate(\"+_+\")\").style({cursor:\"crosshair\"});var H=[(f.width-(f.margin.left+f.margin.right+2*b+(q?q.width:0)))/2,(f.height-(f.margin.top+f.margin.bottom+2*b))/2];if(H[0]=Math.max(0,H[0]),H[1]=Math.max(0,H[1]),e.select(\".outer-group\").attr(\"transform\",\"translate(\"+H+\")\"),f.title){var G=e.select(\"g.title-group text\").style(U).text(f.title),Y=G.node().getBBox();G.attr({x:_[0]-Y.width/2,y:_[1]-b-20})}var X=e.select(\".radial.axis-group\");if(f.radialAxis.gridLinesVisible){var W=X.selectAll(\"circle.grid-circle\").data(n.ticks(5));W.enter().append(\"circle\").attr({\"class\":\"grid-circle\"}).style(B),W.attr(\"r\",n),W.exit().remove()}X.select(\"circle.outside-circle\").attr({r:b}).style(B);var Z=e.select(\"circle.background-circle\").attr({r:b}).style({fill:f.backgroundColor,stroke:f.stroke});if(f.radialAxis.visible){var $=i.svg.axis().scale(n).ticks(5).tickSize(5);X.call($).attr({transform:\"rotate(\"+f.radialAxis.orientation+\")\"}),X.selectAll(\".domain\").style(B),X.selectAll(\"g>text\").text(function(t,e){return this.textContent+f.radialAxis.ticksSuffix}).style(U).style({\"text-anchor\":\"start\"}).attr({x:0,y:0,dx:0,dy:0,transform:function(t,e){return\"horizontal\"===f.radialAxis.tickOrientation?\"rotate(\"+-f.radialAxis.orientation+\") translate(\"+[0,U[\"font-size\"]]+\")\":\"translate(\"+[0,U[\"font-size\"]]+\")\"}}),X.selectAll(\"g>line\").style({stroke:\"black\"})}var K=e.select(\".angular.axis-group\").selectAll(\"g.angular-tick\").data(O),Q=K.enter().append(\"g\").classed(\"angular-tick\",!0);K.attr({transform:function(t,e){return\"rotate(\"+l(t,e)+\")\"}}).style({display:f.angularAxis.visible?\"block\":\"none\"}),K.exit().remove(),Q.append(\"line\").classed(\"grid-line\",!0).classed(\"major\",function(t,e){return e%(f.minorTicks+1)==0}).classed(\"minor\",function(t,e){return!(e%(f.minorTicks+1)==0)}).style(B),Q.selectAll(\".minor\").style({stroke:f.minorTickColor}),K.select(\"line.grid-line\").attr({x1:f.tickLength?b-f.tickLength:0,x2:b}).style({display:f.angularAxis.gridLinesVisible?\"block\":\"none\"}),Q.append(\"text\").classed(\"axis-text\",!0).style(U);var J=K.select(\"text.axis-text\").attr({x:b+f.labelOffset,dy:\".35em\",transform:function(t,e){var r=l(t,e),n=b+f.labelOffset,i=f.angularAxis.tickOrientation;return\"horizontal\"==i?\"rotate(\"+-r+\" \"+n+\" 0)\":\"radial\"==i?270>r&&r>90?\"rotate(180 \"+n+\" 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n=i.select(this),o=n.style(\"fill\"),s=\"black\",l=n.style(\"opacity\")||1;if(n.attr({\"data-opacity\":l}),\"none\"!=o){n.attr({\"data-fill\":o}),s=i.hsl(o).darker().toString(),n.style({fill:s,opacity:1});var u={t:a.util.round(t[0]),r:a.util.round(t[1])};M&&(u.t=k[t[0]]);var c=\"t: \"+u.t+\", r: \"+u.r,f=this.getBoundingClientRect(),h=e.node().getBoundingClientRect(),p=[f.left+f.width/2-H[0]-h.left,f.top+f.height/2-H[1]-h.top];ht.config({color:s}).text(c),ht.move(p)}else o=n.style(\"stroke\"),n.attr({\"data-stroke\":o}),s=i.hsl(o).darker().toString(),n.style({stroke:s,opacity:1})}).on(\"mousemove.tooltip\",function(t,e){return 0!=i.event.which?!1:void(i.select(this).attr(\"data-fill\")&&ht.show())}).on(\"mouseout.tooltip\",function(t,e){ht.hide();var r=i.select(this),n=r.attr(\"data-fill\");n?r.style({fill:n,opacity:r.attr(\"data-opacity\")}):r.style({stroke:r.attr(\"data-stroke\"),opacity:r.attr(\"data-opacity\")})})}),h}var 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t},a.Legend=function(){function t(){var r=e.legendConfig,n=e.data.map(function(t,e){return[].concat(t).map(function(t,n){var i=o({},r.elements[e]);return i.name=t,i.color=[].concat(r.elements[e].color)[n],i})}),a=i.merge(n);a=a.filter(function(t,e){return r.elements[e]&&(r.elements[e].visibleInLegend||\"undefined\"==typeof r.elements[e].visibleInLegend)}),r.reverseOrder&&(a=a.reverse());var s=r.container;(\"string\"==typeof s||s.nodeName)&&(s=i.select(s));var l=a.map(function(t,e){return t.color}),u=r.fontSize,c=null==r.isContinuous?\"number\"==typeof a[0]:r.isContinuous,f=c?r.height:u*a.length,h=s.classed(\"legend-group\",!0),p=h.selectAll(\"svg\").data([0]),d=p.enter().append(\"svg\").attr({width:300,height:f+u,xmlns:\"http://www.w3.org/2000/svg\",\"xmlns:xlink\":\"http://www.w3.org/1999/xlink\",version:\"1.1\"});d.append(\"g\").classed(\"legend-axis\",!0),d.append(\"g\").classed(\"legend-marks\",!0);var g=i.range(a.length),v=i.scale[c?\"linear\":\"ordinal\"]().domain(g).range(l),m=i.scale[c?\"linear\":\"ordinal\"]().domain(g)[c?\"range\":\"rangePoints\"]([0,f]),y=function(t,e){var r=3*e;return\"line\"===t?\"M\"+[[-e/2,-e/12],[e/2,-e/12],[e/2,e/12],[-e/2,e/12]]+\"Z\":-1!=i.svg.symbolTypes.indexOf(t)?i.svg.symbol().type(t).size(r)():i.svg.symbol().type(\"square\").size(r)()};if(c){var b=p.select(\".legend-marks\").append(\"defs\").append(\"linearGradient\").attr({id:\"grad1\",x1:\"0%\",y1:\"0%\",x2:\"0%\",y2:\"100%\"}).selectAll(\"stop\").data(l);b.enter().append(\"stop\"),b.attr({offset:function(t,e){return e/(l.length-1)*100+\"%\"}}).style({\"stop-color\":function(t,e){return t}}),p.append(\"rect\").classed(\"legend-mark\",!0).attr({height:r.height,width:r.colorBandWidth,fill:\"url(#grad1)\"})}else{var x=p.select(\".legend-marks\").selectAll(\"path.legend-mark\").data(a);x.enter().append(\"path\").classed(\"legend-mark\",!0),x.attr({transform:function(t,e){return\"translate(\"+[u/2,m(e)+u/2]+\")\"},d:function(t,e){var r=t.symbol;return y(r,u)},fill:function(t,e){return v(e)}}),x.exit().remove()}var _=i.svg.axis().scale(m).orient(\"right\"),w=p.select(\"g.legend-axis\").attr({transform:\"translate(\"+[c?r.colorBandWidth:u,u/2]+\")\"}).call(_);return w.selectAll(\".domain\").style({fill:\"none\",stroke:\"none\"}),w.selectAll(\"line\").style({fill:\"none\",stroke:c?r.textColor:\"none\"}),w.selectAll(\"text\").style({fill:r.textColor,\"font-size\":r.fontSize}).text(function(t,e){return a[e].name}),t}var e=a.Legend.defaultConfig(),r=i.dispatch(\"hover\");return t.config=function(t){return arguments.length?(o(e,t),this):e},i.rebind(t,r,\"on\"),t},a.Legend.defaultConfig=function(t,e){var r={data:[\"a\",\"b\",\"c\"],legendConfig:{elements:[{symbol:\"line\",color:\"red\"},{symbol:\"square\",color:\"yellow\"},{symbol:\"diamond\",color:\"limegreen\"}],height:150,colorBandWidth:30,fontSize:12,container:\"body\",isContinuous:null,textColor:\"grey\",reverseOrder:!1}};return r},a.tooltipPanel=function(){var t,e,r,n={container:null,hasTick:!1,fontSize:12,color:\"white\",padding:5},s=\"tooltip-\"+a.tooltipPanel.uid++,l=10,u=function(){t=n.container.selectAll(\"g.\"+s).data([0]);var i=t.enter().append(\"g\").classed(s,!0).style({\"pointer-events\":\"none\",display:\"none\"});return r=i.append(\"path\").style({fill:\"white\",\"fill-opacity\":.9}).attr({d:\"M0 0\"}),e=i.append(\"text\").attr({dx:n.padding+l,dy:.3*+n.fontSize}),u};return u.text=function(a){var o=i.hsl(n.color).l,s=o>=.5?\"#aaa\":\"white\",c=o>=.5?\"black\":\"white\",f=a||\"\";e.style({fill:c,\"font-size\":n.fontSize+\"px\"}).text(f);var h=n.padding,p=e.node().getBBox(),d={fill:n.color,stroke:s,\"stroke-width\":\"2px\"},g=p.width+2*h+l,v=p.height+2*h;return r.attr({d:\"M\"+[[l,-v/2],[l,-v/4],[n.hasTick?0:l,0],[l,v/4],[l,v/2],[g,v/2],[g,-v/2]].join(\"L\")+\"Z\"}).style(d),t.attr({transform:\"translate(\"+[l,-v/2+2*h]+\")\"}),t.style({display:\"block\"}),u},u.move=function(e){return t?(t.attr({transform:\"translate(\"+[e[0],e[1]]+\")\"}).style({display:\"block\"}),u):void 0},u.hide=function(){return t?(t.style({display:\"none\"}),u):void 0},u.show=function(){return t?(t.style({display:\"block\"}),u):void 0},u.config=function(t){return o(n,t),u},u},a.tooltipPanel.uid=1,a.adapter={},a.adapter.plotly=function(){var t={};return t.convert=function(t,e){var r={};if(t.data&&(r.data=t.data.map(function(t,r){var n=o({},t),i=[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]];\n",
+       "return i.forEach(function(t,r){a.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",n.dotVisible===!0?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var n=a.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var i=n.indexOf(t.geometry);-1!=i&&(r.data[e].groupId=i)})}if(t.layout){var s=o({},t.layout),l=[[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]];if(l.forEach(function(t,r){a.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof s.tickLength&&(s.angularaxis.ticklen=s.tickLength,delete s.tickLength),s.tickColor&&(s.angularaxis.tickcolor=s.tickColor,delete s.tickColor)):(s.angularAxis&&\"undefined\"!=typeof s.angularAxis.ticklen&&(s.tickLength=s.angularAxis.ticklen),s.angularAxis&&\"undefined\"!=typeof s.angularAxis.tickcolor&&(s.tickColor=s.angularAxis.tickcolor)),s.legend&&\"boolean\"!=typeof s.legend.reverseOrder&&(s.legend.reverseOrder=\"normal\"!=s.legend.reverseOrder),s.legend&&\"boolean\"==typeof s.legend.traceorder&&(s.legend.traceorder=s.legend.traceorder?\"reversed\":\"normal\",delete s.legend.reverseOrder),s.margin&&\"undefined\"!=typeof s.margin.t){var u=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],f={};i.entries(s.margin).forEach(function(t,e){f[c[u.indexOf(t.key)]]=t.value}),s.margin=f}e&&(delete s.needsEndSpacing,delete s.minorTickColor,delete s.minorTicks,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksStep,delete 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n=t(\"../../components/drawing\");t(\"./constants\");e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},dy:{valType:\"number\",dflt:1},text:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",\n",
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"min:0,dflt:2},shape:{valType:\"enumerated\",values:[\"linear\",\"spline\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\"},smoothing:{valType:\"number\",min:0,max:1.3,dflt:1},dash:{valType:\"string\",values:[\"solid\",\"dot\",\"dash\",\"longdash\",\"dashdot\",\"longdashdot\"],dflt:\"solid\"}},connectgaps:{valType:\"boolean\",dflt:!1},fill:{valType:\"enumerated\",values:[\"none\",\"tozeroy\",\"tozerox\",\"tonexty\",\"tonextx\"],dflt:\"none\"},fillcolor:{valType:\"color\"},marker:{symbol:{valType:\"enumerated\",values:n.symbolList,dflt:\"circle\",arrayOk:!0},opacity:{valType:\"number\",min:0,max:1,arrayOk:!0},size:{valType:\"number\",min:0,dflt:6,arrayOk:!0},color:{valType:\"color\",arrayOk:!0},maxdisplayed:{valType:\"number\",min:0,dflt:0},sizeref:{valType:\"number\",dflt:1},sizemin:{valType:\"number\",min:0,dflt:0},sizemode:{valType:\"enumerated\",values:[\"diameter\",\"area\"],dflt:\"diameter\"},colorscale:{valType:\"colorscale\"},cauto:{valType:\"boolean\",dflt:!0},cmax:{valType:\"number\",dflt:null},cmin:{valType:\"number\",dflt:null},autocolorscale:{valType:\"boolean\",dflt:!0},reversescale:{valType:\"boolean\",dflt:!1},showscale:{valType:\"boolean\",dflt:!1},line:{color:{valType:\"color\",arrayOk:!0},width:{valType:\"number\",min:0,arrayOk:!0},colorscale:{valType:\"colorscale\"},cauto:{valType:\"boolean\",dflt:!0},cmax:{valType:\"number\",dflt:null},cmin:{valType:\"number\",dflt:null},autocolorscale:{valType:\"boolean\",dflt:!0},reversescale:{valType:\"boolean\",dflt:!1}}},textposition:{valType:\"enumerated\",values:[\"top 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r=e[0].trace,u=r.marker,c=\"cb\"+r.uid;if(t._fullLayout._infolayer.selectAll(\".\"+c).remove(),void 0===u||!u.showscale)return void o.autoMargin(t,c);var f=s(u.colorscale),h=u.color,p=u.cmin,d=u.cmax;i(p)||(p=a.aggNums(Math.min,null,h)),i(d)||(d=a.aggNums(Math.max,null,h));var g=e[0].t.cb=l(t,c);g.fillcolor(n.scale.linear().domain(f.map(function(t){return p+t[0]*(d-p)})).range(f.map(function(t){return t[1]}))).filllevels({start:p,end:d,size:(d-p)/254}).options(u.colorbar)(),a.markTime(\"done colorbar\")}},{\"../../components/colorbar/draw\":532,\"../../components/colorscale/get_scale\":540,\"../../lib\":578,\"../../plots/plots\":642,d3:320,\"fast-isnumeric\":324}],735:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20}},{}],736:[function(t,e,r){\"use strict\";function n(t,e,r){var n=r(\"line.shape\");\"spline\"===n&&r(\"line.smoothing\")}var i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"./constants\"),s=t(\"./subtypes\"),l=t(\"./xy_defaults\"),u=t(\"./marker_defaults\"),c=t(\"./line_defaults\"),f=t(\"./text_defaults\"),h=t(\"./fillcolor_defaults\"),p=t(\"../../components/errorbars/defaults\");e.exports=function(t,e,r,d){function g(r,n){return i.coerce(t,e,a,r,n)}var v=l(t,e,g),m=v<o.PTS_LINESONLY?\"lines+markers\":\"lines\";return v?(g(\"text\"),g(\"mode\",m),s.hasLines(e)&&(c(t,e,r,g),n(t,e,g),g(\"connectgaps\")),s.hasMarkers(e)&&u(t,e,r,d,g),s.hasText(e)&&f(t,e,d,g),(s.hasMarkers(e)||s.hasText(e))&&g(\"marker.maxdisplayed\"),g(\"fill\"),\"none\"!==e.fill&&(h(t,e,r,g),s.hasLines(e)||n(t,e,g)),p(t,e,r,{axis:\"y\"}),void 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a=o&&n.opacity(o)?o:s&&n.opacity(s)&&(e.mlw||((t.marker||{}).line||{}).width)?s:\"\",a?n.opacity(a)<.3?n.addOpacity(a,.3):a:(r=(t.line||{}).color,r&&n.opacity(r)&&i.hasLines(t)&&t.line.width?r:t.fillcolor)}},{\"../../components/color\":529,\"./subtypes\":749}],739:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/graph_interact\"),i=t(\"../../components/errorbars\"),a=t(\"./get_trace_color\");e.exports=function(t,e,r,o){var s=t.cd,l=s[0].trace,u=t.xa,c=t.ya,f=function(t){var r=Math.max(3,t.mrc||0);return Math.max(Math.abs(u.c2p(t.x)-u.c2p(e))-r,1-3/r)},h=function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(c.c2p(t.y)-c.c2p(r))-e,1-3/e)},p=function(t){var n=Math.max(3,t.mrc||0),i=Math.abs(u.c2p(t.x)-u.c2p(e)),a=Math.abs(c.c2p(t.y)-c.c2p(r));return Math.max(Math.sqrt(i*i+a*a)-n,1-3/n)},d=n.getDistanceFunction(o,f,h,p);if(n.getClosest(s,d,t),t.index!==!1){var g=s[t.index],v=u.c2p(g.x,!0),m=c.c2p(g.y,!0),y=g.mrc||1;return 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h=i(l.position,l.delaunayColor,l.delaunayAxis);this.delaunayMesh?this.delaunayMesh.update(h):(h.gl=o,this.delaunayMesh=v(h),this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},M.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.textMarkers),this.delaunayMesh.dispose())},e.exports=h},{\"../../constants/gl3d_dashes\":565,\"../../constants/gl_markers\":566,\"../../lib\":578,\"../../lib/gl_format_color\":576,\"../../lib/str2rgbarray\":588,\"../scatter/make_bubble_size_func\":743,\"./calc_errors\":754,\"delaunay-triangulate\":321,\"gl-error3d\":328,\"gl-line3d\":334,\"gl-mesh3d\":356,\"gl-scatter3d\":381}],756:[function(t,e,r){\"use strict\";function n(t,e,r){var n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,f){function h(r,n){return i.coerce(t,e,c,r,n)}var p=n(t,e,h);if(!p)return void(e.visible=!1);h(\"text\"),h(\"mode\"),a.hasLines(e)&&s(t,e,r,h),a.hasMarkers(e)&&o(t,e,r,f,h),a.hasText(e)&&l(t,e,f,h);var d=(e.line||{}).color,g=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",d||g);for(var v=[\"x\",\"y\",\"z\"],m=0;3>m;++m){var y=\"projection.\"+v[m];h(y+\".show\")&&(h(y+\".opacity\"),h(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":752}],757:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":566,\"../../plots/gl3d\":629,\"../scatter/colorbar\":734,\"./attributes\":752,\"./calc\":753,\"./convert\":755,\"./defaults\":756}],758:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../lib/extend\").extendFlat,o=n.marker,s=n.line,l=o.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\"],dflt:\"ISO-3\"},mode:a({},n.mode,{dflt:\"markers\"}),text:a({},n.text,{}),line:{color:s.color,width:s.width,dash:s.dash},marker:{symbol:o.symbol,opacity:o.opacity,size:o.size,sizeref:o.sizeref,sizemin:o.sizemin,sizemode:o.sizemode,color:o.color,colorscale:o.colorscale,cauto:o.cauto,cmax:o.cmax,cmin:o.cmin,autocolorscale:o.autocolorscale,reversescale:o.reversescale,showscale:o.showscale,line:{color:l.color,width:l.width,colorscale:l.colorscale,cauto:l.cauto,cmax:l.cmax,cmin:l.cmin,autocolorscale:l.autocolorscale,reversescale:l.reversescale}},textfont:n.textfont,textposition:n.textposition,hoverinfo:a({},i.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../lib/extend\":574,\"../../plots/attributes\":596,\"../scatter/attributes\":731}],759:[function(t,e,r){\"use strict\";var n=t(\"../scatter/marker_colorscale_calc\");e.exports=function(t,e){var r=[{x:!1,y:!1,trace:e,t:{}}];return n(e),r}},{\"../scatter/marker_colorscale_calc\":744}],760:[function(t,e,r){\"use strict\";function n(t,e,r){var n,i,a=0,o=r(\"locations\");return o?(r(\"locationmode\"),a=o.length):(n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length),a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a)}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"./attributes\");e.exports=function(t,e,r,c){function f(r,n){return i.coerce(t,e,u,r,n)}var h=n(t,e,f);return h?(f(\"text\"),f(\"mode\"),a.hasLines(e)&&s(t,e,r,f),a.hasMarkers(e)&&o(t,e,r,c,f),a.hasText(e)&&l(t,e,c,f),void f(\"hoverinfo\",1===c._dataLength?\"lon+lat+location+text\":void 0)):void(e.visible=!1)}},{\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":758}],761:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\").plot,n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":614,\"../scatter/colorbar\":734,\"./attributes\":758,\"./calc\":759,\"./defaults\":760,\"./plot\":762}],762:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t,n){h(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function i(t){for(var e=t.lon.length,r=new Array(e),n=0;e>n;n++)r[n]=[t.lon[n],t.lat[n]];return{type:\"LineString\",coordinates:r,trace:t}}function a(t,e){function r(e){var r=t.mockAxis;return u.tickText(r,r.c2l(e),\"hover\").text+\"\\xb0\"}var n=e.hoverinfo;if(\"none\"===n)return function(t){delete t.textLabel};var i=\"all\"===n?v.hoverinfo.flags:n.split(\"+\"),a=-1!==i.indexOf(\"location\")&&Array.isArray(e.locations),o=-1!==i.indexOf(\"lon\"),s=-1!==i.indexOf(\"lat\"),l=-1!==i.indexOf(\"text\");return function(t){var n=[];a?n.push(t.location):o&&s?n.push(\"(\"+r(t.lon)+\", \"+r(t.lat)+\")\"):o?n.push(\"lon: \"+r(t.lon)):s&&n.push(\"lat: \"+r(t.lat)),l&&n.push(t.tx||e.text),t.textLabel=n.join(\"<br>\")}}function o(t){var e=Array.isArray(t.locations);return function(r,n){return{points:[{data:t._input,fullData:t,curveNumber:t.index,pointNumber:n,lon:r.lon,lat:r.lat,location:e?r.location:null}]}}}var s=t(\"d3\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"../../plots/cartesian/axes\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,f=t(\"../../lib/geo_location_utils\").locationToFeature,h=t(\"../../lib/array_to_calc_item\"),p=t(\"../../components/color\"),d=t(\"../../components/drawing\"),g=t(\"../scatter/subtypes\"),v=t(\"./attributes\"),m=e.exports={};m.calcGeoJSON=function(t,e){var r,i,a,o,s=[],l=Array.isArray(t.locations);l?(o=t.locations,r=o.length,i=c(t,e),a=function(t,e){var r=f(t.locationmode,o[e],i);return void 0!==r?r.properties.ct:void 0}):(r=t.lon.length,a=function(t,e){return[t.lon[e],t.lat[e]]});for(var u=0;r>u;u++){var h=a(t,u);if(h){var p={lon:h[0],lat:h[1],location:l?t.locations[u]:null};n(t,p,u),s.push(p)}}return s.length>0&&(s[0].trace=t),s},m.plot=function(t,e){var r=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,function(t){return t.uid});r.enter().append(\"g\").attr(\"class\",\"trace 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Array(T),this.scatterOptions.borderWidths=new Array(T),this.scatterOptions.colors=new Array(4*T),this.scatterOptions.borderColors=new Array(4*T);var I,j=w(t),N=t.marker,F=N.opacity,D=t.opacity,B=s(N,F,D,x),U=C(N.symbol,x),V=L(N.line.width,x),q=s(N.line,F,D,x);for(O=i(j,N.size,x),e=0;T>e;++e)for(I=_[e],this.scatterOptions.sizes[e]=4*O[I],this.scatterOptions.glyphs[e]=U[I],this.scatterOptions.borderWidths[e]=.5*V[I],r=0;4>r;++r)this.scatterOptions.colors[4*e+r]=B[4*I+r],this.scatterOptions.borderColors[4*e+r]=q[4*I+r];this.fancyScatter.update(this.scatterOptions)}else this.scatterOptions.positions=new Float32Array,this.scatterOptions.glyphs=[],this.fancyScatter.update(this.scatterOptions);this.scatterOptions.positions=new Float32Array,this.scatterOptions.glyphs=[],this.scatter.update(this.scatterOptions),this.expandAxesFancy(v,m,O)},E.updateLines=function(t,e){if(this.hasLines){this.lineOptions.positions=e;var r=b(t.line.color);this.hasMarkers&&(r[3]*=t.marker.opacity);for(var n=Math.round(.5*this.lineOptions.width),i=(M[t.line.dash]||[1]).slice(),a=0;a<i.length;++a)i[a]*=n;switch(t.fill){case\"tozeroy\":this.lineOptions.fill=[!1,!0,!1,!1];break;case\"tozerox\":this.lineOptions.fill=[!0,!1,!1,!1];break;default:this.lineOptions.fill=[!1,!1,!1,!1]}var o=b(t.fillcolor);this.lineOptions.color=r,this.lineOptions.width=2*t.line.width,this.lineOptions.dashes=i,this.lineOptions.fillColor=[o,o,o,o]}else this.lineOptions.positions=new Float32Array;this.line.update(this.lineOptions)},E.updateError=function(t,e,r,n){var i=this[\"error\"+t],a=e[\"error_\"+t.toLowerCase()],s=this[\"error\"+t+\"Options\"];\"x\"===t.toLowerCase()&&a.copy_ystyle&&(a=e.error_y),this[\"hasError\"+t]?(s.positions=r,s.errors=n,s.capSize=a.width,s.lineWidth=a.thickness/2,s.color=o(a.color,1,1)):s.positions=new Float32Array,i.update(s)},E.expandAxesFast=function(t,e){for(var r,n,i,a=e||10,o=0;2>o;o++)r=this.scene[T[o]],n=r._min,n||(n=[]),n.push({val:t[o],pad:a}),i=r._max,i||(i=[]),i.push({val:t[o+2],pad:a})},E.expandAxesFancy=function(t,e,r){var n=this.scene,i={padded:!0,ppad:r};m.expand(n.xaxis,t,i),m.expand(n.yaxis,e,i)},E.dispose=function(){this.line.dispose(),this.errorX.dispose(),this.errorY.dispose(),this.scatter.dispose(),this.fancyScatter.dispose()},e.exports=c},{\"../../components/errorbars\":553,\"../../constants/gl2d_dashes\":564,\"../../constants/gl_markers\":566,\"../../lib\":578,\"../../lib/gl_format_color\":576,\"../../lib/str2rgbarray\":588,\"../../plots/cartesian/axes\":598,\"../scatter/get_trace_color\":738,\"../scatter/make_bubble_size_func\":743,\"../scatter/subtypes\":749,\"fast-isnumeric\":324,\"gl-error2d\":326,\"gl-line2d\":332,\"gl-scatter2d\":378,\"gl-scatter2d-fancy\":373}],765:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}var d=o(t,e,p);return d?(p(\"text\"),p(\"mode\",d<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&l(t,e,r,p),a.hasMarkers(e)&&s(t,e,r,h,p),p(\"fill\"),\"none\"!==e.fill&&u(t,e,r,p),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/constants\":735,\"../scatter/fillcolor_defaults\":737,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/xy_defaults\":751,\"./attributes\":763}],766:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":626,\"../scatter/colorbar\":734,\"../scatter3d/calc\":753,\"./attributes\":763,\"./convert\":764,\"./defaults\":765}],767:[function(t,e,r){\"use strict\";function n(t){return{valType:\"boolean\",dflt:!1}}function i(t){return{show:{valType:\"boolean\",dflt:!1},project:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},color:{valType:\"color\",dflt:\"#000\"},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!1},highlightColor:{valType:\"color\",dflt:\"#000\"},highlightWidth:{valType:\"number\",min:1,max:16,dflt:2}}}var a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports={z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"data_array\"},zauto:a.zauto,zmin:a.zmin,zmax:a.zmax,colorscale:a.colorscale,autocolorscale:o({},a.autocolorscale,{dflt:!1}),reversescale:a.reversescale,showscale:a.showscale,contours:{x:i(\"x\"),y:i(\"y\"),z:i(\"z\")},hidesurface:{valType:\"boolean\",dflt:!1},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},_nestedModules:{colorbar:\"Colorbar\"}}},{\"../../components/colorscale/attributes\":535,\"../../lib/extend\":574}],768:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){n(e,e.z,\"\",\"z\")}},{\"../../components/colorscale/calc\":536}],769:[function(t,e,r){\"use strict\";function n(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.dataScale=1}function i(t,e){return void 0===e&&(e=1),t.map(function(t){var r=t[0],n=p(t[1]),i=n.toRgb();return{index:r,rgb:[i.r,i.g,i.b,e]}})}function a(t){var e=t.shape,r=[e[0]+2,e[1]+2],n=u(new Float32Array(r[0]*r[1]),r);return h.assign(n.lo(1,1).hi(e[0],e[1]),t),h.assign(n.lo(1).hi(e[0],1),t.hi(e[0],1)),h.assign(n.lo(1,r[1]-1).hi(e[0],1),t.lo(0,e[1]-1).hi(e[0],1)),h.assign(n.lo(0,1).hi(1,e[1]),t.hi(1)),h.assign(n.lo(r[0]-1,1).hi(1,e[1]),t.lo(e[0]-1)),n.set(0,0,t.get(0,0)),n.set(0,r[1]-1,t.get(0,e[1]-1)),n.set(r[0]-1,0,t.get(e[0]-1,0)),n.set(r[0]-1,r[1]-1,t.get(e[0]-1,e[1]-1)),n}function o(t){var e=Math.max(t[0].shape[0],t[0].shape[1]);if(g>e){for(var r=g/e,n=[0|Math.floor(t[0].shape[0]*r+1),0|Math.floor(t[0].shape[1]*r+1)],i=n[0]*n[1],o=0;3>o;++o){var s=a(t[o]),l=u(new Float32Array(i),n);c(l,s,[r,0,0,0,r,0,0,0,1]),t[o]=l}return r}return 1}function s(t,e){var r=t.glplot.gl,i=l({gl:r}),a=new n(t,i,e.uid);return a.update(e),t.glplot.add(i),a}var l=t(\"gl-surface3d\"),u=t(\"ndarray\"),c=t(\"ndarray-homography\"),f=t(\"ndarray-fill\"),h=t(\"ndarray-ops\"),p=t(\"tinycolor2\"),d=t(\"../../lib/str2rgbarray\"),g=128,v=n.prototype;v.handlePick=function(t){if(t.object===this.surface){var e=[Math.min(0|Math.round(t.data.index[0]/this.dataScale-1),this.data.z[0].length-1),Math.min(0|Math.round(t.data.index[1]/this.dataScale-1),this.data.z.length-1)],r=[0,0,0];Array.isArray(this.data.x[0])?r[0]=this.data.x[e[1]][e[0]]:r[0]=this.data.x[e[0]],Array.isArray(this.data.y[0])?r[1]=this.data.y[e[1]][e[0]]:r[1]=this.data.y[e[1]],r[2]=this.data.z[e[1]][e[0]],t.traceCoordinate=r;var n=this.scene.fullSceneLayout;t.dataCoordinate=[n.xaxis.d2l(r[0])*this.scene.dataScale[0],n.yaxis.d2l(r[1])*this.scene.dataScale[1],n.zaxis.d2l(r[2])*this.scene.dataScale[2]];var i=this.data.text;return i&&i[e[1]]&&void 0!==i[e[1]][e[0]]?t.textLabel=i[e[1]][e[0]]:t.textLabel=\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}},v.setContourLevels=function(){for(var t=[[],[],[]],e=!1,r=0;3>r;++r)this.showContour[r]&&(e=!0,t[r]=this.scene.contourLevels[r]);e&&this.surface.update({levels:t})},v.update=function(t){var e,r=this.scene,n=r.fullSceneLayout,a=this.surface,s=t.opacity,l=i(t.colorscale,s),c=t.z,h=t.x,p=t.y,g=n.xaxis,v=n.yaxis,m=n.zaxis,y=r.dataScale,b=c[0].length,x=c.length,_=[u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x])],w=_[0],k=_[1],A=r.contourLevels;this.data=t,f(_[2],function(t,e){return m.d2l(c[e][t])*y[2]}),Array.isArray(h[0])?f(w,function(t,e){return g.d2l(h[e][t])*y[0]}):f(w,function(t){return g.d2l(h[t])*y[0]}),Array.isArray(p[0])?f(k,function(t,e){return v.d2l(p[e][t])*y[1]}):f(k,function(t,e){return v.d2l(p[e])*y[1]}),this.dataScale=o(_);var M={colormap:l,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacity:1,colorBounds:[t.zmin*y[2],t.zmax*y[2]]};\"opacity\"in t&&t.opacity<1&&(M.opacity=.25*t.opacity);var T=[!0,!0,!0],E=[!0,!0,!0],L=[\"x\",\"y\",\"z\"];for(e=0;3>e;++e){var S=t.contours[L[e]];T[e]=S.highlight,E[e]=S.show,M.showContour[e]=S.show||S.highlight,M.showContour[e]&&(M.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,M.levels[e]=A[e],a.highlightColor[e]=M.contourColor[e]=d(S.color),S.usecolormap?a.highlightTint[e]=M.contourTint[e]=0:a.highlightTint[e]=M.contourTint[e]=1,M.contourWidth[e]=S.width):this.showContour[e]=!1,S.highlight&&(M.dynamicColor[e]=d(S.highlightColor),M.dynamicWidth[e]=S.highlightWidth))}M.coords=_,a.update(M),a.highlightEnable=T,a.contourEnable=E,a.visible=t.visible,a.snapToData=!0,\"lighting\"in t&&(a.ambientLight=t.lighting.ambient,a.diffuseLight=t.lighting.diffuse,a.specularLight=t.lighting.specular,a.roughness=t.lighting.roughness,a.fresnel=t.lighting.fresnel),s&&1>s&&(a.supportsTransparency=!0)},v.dispose=function(){this.glplot.remove(this.surface),this.surface.dispose()},e.exports=s},{\"../../lib/str2rgbarray\":588,\"gl-surface3d\":415,ndarray:438,\"ndarray-fill\":431,\"ndarray-homography\":436,\"ndarray-ops\":437,tinycolor2:459}],770:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/defaults\"),a=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}var l,u,c=s(\"z\");if(!c)return void(e.visible=!1);var f=c[0].length,h=c.length;if(s(\"x\"),s(\"y\"),!Array.isArray(e.x))for(e.x=[],l=0;f>l;++l)e.x[l]=l;if(s(\"text\"),!Array.isArray(e.y))for(e.y=[],l=0;h>l;++l)e.y[l]=l;s(\"lighting.ambient\"),s(\"lighting.diffuse\"),s(\"lighting.specular\"),s(\"lighting.roughness\"),s(\"lighting.fresnel\"),s(\"hidesurface\"),s(\"opacity\"),s(\"colorscale\");var p=[\"x\",\"y\",\"z\"];for(l=0;3>l;++l){var d=\"contours.\"+p[l],g=s(d+\".show\"),v=s(d+\".highlight\");if(g||v)for(u=0;3>u;++u)s(d+\".project.\"+p[u]);g&&(s(d+\".color\"),s(d+\".width\"),s(d+\".usecolormap\")),v&&(s(d+\".highlightColor\"),s(d+\".highlightWidth\"))}i(t,e,o,s,{prefix:\"\",cLetter:\"z\"})}},{\"../../components/colorscale/defaults\":538,\"../../lib\":578,\"./attributes\":767}],771:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../heatmap/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"surface\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"noOpacity\"],n.meta={},e.exports=n},{\"../../plots/gl3d\":629,\"../heatmap/colorbar\":690,\"./attributes\":767,\"./calc\":768,\"./convert\":769,\"./defaults\":770}]},{},[262])(262)});\n",
+       "</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -253,13 +266,18 @@
     "    [255, 128, 0],    #Orange\n",
     "]\n",
     "\n",
+    "stram = open(\"../conf/bothound.yaml\", \"r\")\n",
+    "conf = yaml.load(stram)\n",
+    "tools = BothoundTools(conf)\n",
+    "tools.connect_to_db()\n",
+    "\n",
     "def get_palette(N=5):\n",
     "    result = []\n",
     "    for x in range(N):\n",
     "        s = color_set[x % len(color_set)]\n",
     "        result.append([s[0]/255.0,s[1]/255.0,s[2]/255.0,1])\n",
     "    return result\n",
-    "palette = get_palette(30)\n",
+    "palette = get_palette(80)\n",
     "\n",
     "def plot_costs(costs, num_clusters, title):\n",
     "    KK = range(1,len(costs)+1)\n",
@@ -293,7 +311,7 @@
     "    left = [] \n",
     "    for i in range(len(sizes)):\n",
     "        left.append(i-0.5)\n",
-    "    fig = plt.figure()\n",
+    "    fig = plt.figure(figsize=(12,8))\n",
     "    plt.title(title)\n",
     "    ax = fig.add_subplot(111)\n",
     "    ax.bar(left,sizes, color = palette)            \n",
@@ -304,7 +322,7 @@
     "    model.fit(X)\n",
     "    \n",
     "    clusters = model.predict(X)\n",
-    "    plot_clusters(X, clusters, num_clusters)\n",
+    "    plot_clusters(clusters, num_clusters)\n",
     "    return clusters\n",
     "\n",
     "def get_best_clustering_model(X, max_number_of_clusters, title):\n",
@@ -328,14 +346,15 @@
     "\n",
     "    # calculate first derivative\n",
     "    derivative1 = [cost[i+1]-cost[i] for i in range(len(cost)-1)]\n",
-    "    #print derivative1\n",
+    "    #print \"d1\", derivative1\n",
     "\n",
     "    # calculate second derivative\n",
     "    derivative2 = [derivative1[i+1]-derivative1[i] for i in range(len(derivative1)-1)]\n",
-    "    #print derivative2\n",
+    "    #print \"d2\", derivative2\n",
     "\n",
     "    max2 = argrelextrema(np.argsort(derivative2), np.less) \n",
     "    num_clusters = 4 \n",
+    "    #print \"max2\", max2\n",
     "    if(len(max2[0]) > 0):\n",
     "        num_clusters = max2[0][0] + 3\n",
     "    else:\n",
@@ -356,7 +375,73 @@
     "    plot_clusters(clusters, model.n_clusters, title)\n",
     "    return clusters, model.n_clusters, cost\n",
     "\n",
+    "\n",
+    "import plotly\n",
+    "plotly.offline.init_notebook_mode() # run at the start of every notebook\n",
+    "\n",
+    "from plotly.plotly import iplot\n",
+    "from plotly.graph_objs import Scatter3d, Data, Marker\n",
+    "import plotly.graph_objs as go\n",
+    "\n",
     "def plot3(feature_indexes, X, clusters, selected_cluster):\n",
+    "    clusters_plot = []\n",
+    "    num_clusters = max(clusters)+1\n",
+    "    for i in range(0, num_clusters):\n",
+    "        d = X[clusters == i,: ]\n",
+    "        cluster = Scatter3d(\n",
+    "            x=d[:,feature_indexes[0]],\n",
+    "            y=d[:,feature_indexes[1]],\n",
+    "            z=d[:,feature_indexes[2]],\n",
+    "            mode='markers',\n",
+    "            name = \"Cluster {}\".format(i),\n",
+    "            marker=dict(\n",
+    "                color='rgb({}, {}, {})'.format(palette[i][0]*255,palette[i][1]*255,palette[i][2]*255 ),\n",
+    "                size=6,\n",
+    "                line=dict(\n",
+    "                    color='rgb(204, 204, 204)',\n",
+    "                    width=0.0\n",
+    "                ),\n",
+    "                opacity=0.5\n",
+    "            )\n",
+    "        )\n",
+    "        clusters_plot.append(cluster)\n",
+    "\n",
+    "    data = Data(clusters_plot)\n",
+    "    bk_color = \"rgb(224, 224, 224)\"\n",
+    "    layout = go.Layout(\n",
+    "        margin=dict(l=0, r=0, b=0,t=60),\n",
+    "        title='Clusters', \n",
+    "        height = 1000,\n",
+    "        width = 1000,\n",
+    "        scene=go.Scene(\n",
+    "            xaxis=dict(\n",
+    "                title = features[feature_indexes[0]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "           ),\n",
+    "            yaxis=dict(\n",
+    "                 title = features[feature_indexes[1]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "            ),\n",
+    "            zaxis=dict(\n",
+    "                 title = features[feature_indexes[2]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "            )\n",
+    "        ),\n",
+    "    )\n",
+    "    fig = go.Figure(data=data, layout=layout)\n",
+    "    plotly.offline.iplot(fig)\n",
+    "\n",
+    "\n",
+    "def plot3_old(feature_indexes, X, clusters, selected_cluster):\n",
     "    if(selected_cluster >= 0):\n",
     "        X_plot = X[clusters == selected_cluster,: ]\n",
     "        labels_plot = clusters[clusters == selected_cluster]\n",
@@ -487,7 +572,10 @@
     "        cluster_total = bans[clusters_np == cluster]\n",
     "        cluster_banned = cluster_total[cluster_total==1]\n",
     "        banned.append(cluster_banned.shape[0])\n",
-    "        p = float(\"{0:.2f}\".format(cluster_banned.shape[0]*100.0/cluster_total.shape[0]))\n",
+    "        if (cluster_total.shape[0] == 0):\n",
+    "            p = 0\n",
+    "        else:\n",
+    "            p = float(\"{0:.2f}\".format(cluster_banned.shape[0]*100.0/cluster_total.shape[0]))\n",
     "        percentage.append(p)\n",
     "        d[\"data\"].append(cluster_total.shape[0]-cluster_banned.shape[0])\n",
     "          \n",
@@ -514,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {
     "code_folding": [],
     "collapsed": false
@@ -522,27 +610,32 @@
    "outputs": [],
    "source": [
     "#Report Configuration\n",
-    "id_incident = 20\n",
+    "id_incident = 21\n",
     "\n",
     "features = [\n",
-    "    \"request_interval\", #1\n",
+    "    #\"request_interval\", #1\n",
     "    #\"ua_change_rate\",#2\n",
-    "    \"html2image_ratio\",#3\n",
+    "    #\"html2image_ratio\",#3\n",
     "    \"variance_request_interval\",#4\n",
-    "    \"payload_average\",#5\n",
-    "    #\"error_rate\",#6\n",
+    "    #\"payload_average\",#5\n",
+    "    \"error_rate\",#6\n",
     "    #\"request_depth\",#7\n",
-    "    #\"request_depth_std\",#8\n",
+    "    \"request_depth_std\",#8\n",
     "    \"session_length\",#9\n",
     "    #\"percentage_cons_requests\",#10\n",
     "]\n",
     "\n",
-    "max_number_of_clusters = 8\n",
-    "\n",
-    "stram = open(\"../conf/bothound.yaml\", \"r\")\n",
-    "conf = yaml.load(stram)\n",
-    "tools = BothoundTools(conf)\n",
-    "tools.connect_to_db()"
+    "max_number_of_clusters = 15\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## For incident 19: \n",
+    "* features: 3,4,6,8,9  \n",
+    "* no PCA  \n",
+    "* DBSCAN - eps=0.3, min_samples=10"
    ]
   },
   {
@@ -554,9 +647,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
-    "code_folding": [],
+    "code_folding": [
+     0
+    ],
     "collapsed": false,
     "scrolled": true
    },
@@ -565,10 +660,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Incident 20 loaded:\n",
-      "Start: 2016-02-10 07:00:00\n",
-      "Stop : 2016-02-10 07:10:00\n",
-      "(13068, 5)\n"
+      "Incident 21 loaded:\n",
+      "Start: 2016-03-01 14:30:00\n",
+      "Stop : 2016-03-01 19:25:00\n",
+      "(6241, 4)\n"
      ]
     }
    ],
@@ -604,66 +699,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# PCA Clustering"
+    "# PCA Transform"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 84,
    "metadata": {
     "code_folding": [
      0
     ],
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[900]\n",
-      "[228, 672]\n",
-      "[671, 228, 1]\n",
-      "[671, 227, 1, 1]\n",
-      "[641, 225, 1, 32, 1]\n",
-      "[219, 308, 1, 31, 1, 340]\n",
-      "[339, 219, 1, 1, 308, 1, 31]\n",
-      "[339, 219, 1, 1, 30, 308, 1, 1]\n",
-      "[671, 227, 1, 1]\n",
-      "('Num clusters(PCA):', 4)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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wPTBOUnczu1JSJ+AvZvZuhWO6AocRJr5ZXD6GVjXvsdxf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\nP7Tpz17tMGEUAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe839a14ed0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe83ab80510>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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AcAe3tdC3rbqy3kKfNkCnuaKj0ah19+cY+rSEqun6/lysWiRVn7VZP4bNB6hpSVxRFGZt\n7tBdFklFmIMKAPsgJAWADdSrslLFaNLG6qv6LL3JZBLT6XTWQn9+fq7tk9bz+l2sHp6uWiSVjnX1\nikeLpPZr2zmoyXz7vjmoALAeISkA3GJZtWgbQ9GIeKqFPi1curi4sHBpzzy2tEWalzkcDmdzNFMl\n+fwM1PqXRgLU/VtnDmoKtOfVq07NQQWAm4SkADCnvnCpqS30qQV2HfWFS2mhS5Zlked5XF5eNuL+\ndIWQgT5IAeoi8zNQ0/FnPkBdFKR6/9zdOm38m8xBNaMWgD4RkgLQe11soV+2cOnq6srCJWBv1lkk\nVa9CTV/clGV5488uClLbbtFs0UMyBxUAVhOSAtBLXWuhry9cmkwmMRgMZguXsixr3f0BumedALV+\nbE7HtfoiqWUt/I5xd7OrOajpSzhzUAFoIyEpAL1Qb6FPF99JU1roN5Huy6NHj1q/cKne7tmW2wzs\nVj3onG/lr1c51r/cmg9Ql7XwO67c3bpzUJcFqOagAtAGQlIAOqlekVQURVxfX0ee5xHR3mrRegt9\nqhY9PT21cAnotHp4umgW6vwM1PoSKYuk9m/bOajpz5iDCkBTCEkB6IxlLfTT6TSur6/j7OzsyLdw\nM6sWLg0GgxiNRq27TwC7ltq7VwWo858P84ukBKj7cdc5qPXwdL6F3/MDwK4JSQFordta6NOP+s83\n2SYLl4qiOPKt5VBSkABsLgWoi8zPQE1fTM0HqMva+Lmbdeag1kcrLKpCHQwGkee5RVIA7ISQFIBW\nmQ9F+7xwSXgGsL11FknVq1BTUFeW5Y0/Ox+kpr+bu7ltDmpVVfHw4cOFX4Qum4Eq4AZgFSEpAI22\nrIU+or0Ll9Jyi1SxlKpFz8/Pl1Y8zXOR1w+DwUAYDkewToBa/3xKIWp9kdSi8NT7eTfqn4HLFn2Z\ngwrApoSkADRK/cIzVYwmbb2AmW+hPzk5iSzLLFwCaKH659CygG5+kVQ9QH306NHSFn6fB3d3lzmo\n9efFHFSA/hGSAnB06SKy/s+I3YWih67GW7Vw6fLysnXVrwCspx6ezgeoZVnGo0eP4vT09KkvA9MX\nhBZJ7ddd56DWw1NzUAG6R0gKwMHVFy51pYV+3YVLoN0W+uu2RVL1GajzIapFUvu3zhzUNDJnnjmo\nAO0nJAVg77rYQn+XhUsAMO+2ALUenqaOhXqAWg9PBai7d1uAGvHKHNRFf3ZZFWr6dQCOT0gKwF4s\nW7jU1lB0VwuXWG6+rRGAl62zSKpehZpaxcuyfCpAnV8m5bh7d+agAnSDkBSAnai30KdwNGljC32E\nhUuH1KXHUjs9sMi+vghaJ0Ctf3GZQtT0Ob1qBmqXjs3HYg4qQHsISQHYyvxF13Q6nf1aWy+u2rZw\nSRjXPG17zQPdVv8snu94qFc4pirUelBXVdXKGaiOd7thDipAcwhJAVhbW1vol223b/PCpWX3CWDX\nHGu6qR6eLhoZM9/Cnz735xdJLatC3bc+jGjZ1xzUrj9uANsSkgKw1G0t9E0ORpexcAlgc46N/XPX\nRVKrqlC5u23noKYK4XoFqjmoAC8TkgIwU69KqF/4RLQ3FE1talVVxUsvvWThEgDc0bqLpJYFqKuq\nULm7TQLU9HPp906n0xgOh5FlmTmoQO8ISQF6br6F/tGjR5Hn+Y2qgrZZtHApIixcAoA9WzdAXdTG\nH7F4kVT6u3x+391ti6TG4/Hs1+tzUOdHLCyrQgVoMyEpQM/c1kKfqgraFI7etnApIuKll16KLMuO\nfEsBoL/WCVDnv7xNVagR8VRFY/q9Khx3a9VzFLF6Dmo9PDUHFWgbISlAD8yHol1ood9k4VI9CAYA\nmqd+PrJqkVQ6j0lf6j5+/Hg2Z3PZDNS2necc27LHa502/hSgmoMKtJGQFKCD6tWi9S30EcurA5ru\nLguXbIIHgHZLVYopQC3LMh4/fhyXl5crW/jn28Tn/104txvbLpJKUnBqDipwTEJSgA6ot6elitFk\nm2rRJgSKaeFSCkUtXLppMBh0rkK2Ca87ANonBaiLrLNIalUVKnd32xzU9Byl87559QA1PdeeI2Af\nhKQALTU/s2tXLfTHOtlM92d+4VKWZRYu9YDnFoB92HSR1HyAuqoKld1Ydd6azm9XBajzrfyeI2Bb\nQlKAlrht4VIbW+hvW7jUxvsEAOzfopbtTW0aoNbb+CNiYXia/i4B3W7seg5qvYXfcwTME5ICNNSu\nW+ibYNOFSwAAx7BOgDrf1ZOqUCMWB6htPX9rqrvOQZ0PT81BBYSkAA2yrxb6Y7rLwiUAgKapn5Mt\nmoU6PwM1BagpWF01A/XY50VdmQ++zhzUerg9b9EiKXNQofuEpABH1NUW+qYtXKq3XjmxBeAYfAb1\nR1outCpAXdTCX18ktawK9VC3v+vMQQUWEZICHNCi1qykKdWig8FgoyqC+YVLk8kkhsOhhUsAAHNS\ngLrI/Hlimt0+H6Auq0JlN7adg5r+jDmo0F5CUoA9W9ZCH7H6W+wmK8vyRrWohUvwiq60KgJwWJsu\nkkrnYGVZ3vizi4JUduMuc1CLoog8z2dVxmkWf1NGLQBCUoCdu62Fvo0nQRYuNc+mFb8chvcBAPuw\naYBab+OPsEjqEG6bg/r48eMYjUY3Au767100B1WACoclJAXYgflQ1MIlAAAOYZ0Adb6zKbXxR8SN\n8DSd07b5HLbJllX2pufotjmo8wGqSmHYLSEpwBbq1aKLWujb2G6eTszqJ2fHXrgEXWOJGMBu6KZY\nTz3oXLVIKn3JXw/qqqpaOQPV59jurLNIyhxU2D8hKcAa6t/AT6fTuL6+jrIs4/T0tLUnIMsWLqWK\n0YuLi9bdp1VSe3qX7lOXGB8AwKZ8pt9dWiSVAtTJZBJnZ2ezqtJlLfz1RVLL2vh5Rb3LbFN3mYNa\nf17MQYXbCUkBlli2cCmFOdPptHUVo/MLlyIisiyL09PT2cKlhw8fmjEKANBzKUBdZL6Fv6qqWQt/\nPUBdVoXKbtw2B7UecJuDCrcTkgL8n01a6Nty0rBo4VKWZbPZok5UAQDY1KaLpFJAV5bljT+7KEhl\nd25r4zcHFW4SkgK9Nd9C34Ut9BFPL1w6OTmJ0WgU5+fnMRqNWnmfoM+MIQCgTTZdJJXOXeuLpJa1\n8DuP3Z1N5qAu+rPLqlDTr0MbCUmBXlnVQr/JiVeT5ifWvwFOJ5ipWtTCpe5q0muQ/XGRAUCXrFok\nVZ+vWT9fnw9QLZLaP3NQ6SshKdBp9Rb6dLKVtHkL/Xy1aNpCf3l5eed5osI3AAAOrR6eLvqSf34G\najq/T+f7TV4k1aXloZsEqOag0jZCUqBT5tt3ptPp7Nfa3KazzsIlVhP+AgC0V1oktSpAnb8OmF8k\n1cQAtUvWWSS1aA7q/HOUAtT5KlTYNyEp0HrLWugjVs/aaTILlwAAOLS2VjymAHWR+SKKqqpmLfz1\ncG5ZGz+7c9c5qPXw1CIp9kFICrTObS30hwhG91GVuGjhUporauESALRbW8MnaLt1FknVq1BTi3hZ\nljf+7KIgld1Zp40/Baj142lVVXFychJVVUWWZeagcidCUqAV5kPRbRcuNcmqhUsXFxdHbaHXlg5A\nRNz4vIUmETqzC+sEqPUq1BSi1hdJLWvh9/rcnXUC1MePHy89LpiDyrqEpEAj3dZC38YZnPteuLQr\nZndyLH153TXhfQ4ArFYP0OZb+esLiuqLpFIVaqpurFczzlenshvzS6HmrxOXzUGNiPj93//9+Md/\n/MeD3E7aQUgKNEL9W9pUMZq0+dtYC5dgPW18fy/Tl7AXAPqqHp6us0gqLZOtVztaJLVby6pIVz2m\n//3f/73vm0XLCEmBo0nfuNb/GdGeUHRREDLfQj+dTi1caoguVsh27f4AAHTB/CKp6XQa19fXcXFx\n8VSAWi8SEaAelnNp5glJgYOpL1xqewt9/QRlfgt9Wrh0cXFh4RJ743UFAOySwOgw5gPUuvkZqFVV\nzWag1gPURUGqc0O4OyEpsDddbaFP1aJlWcaLL74426SY53lnWuidJMN22nhMA4A6n2XHs84iqXoV\napqBWp91uqgKNf3d3OQxYZ6QFNipeij65MmTyLIsItofis5Xi6Zvf6+urhqzcGlXunRfAACgC9YJ\nUOtVqClETYUqq1r4237+r8CDXRGSAndSb6FPH8YRLy8sevToUfzIj/zIkW/hdua30A8Gg9lc0dFo\nFGVZxsOHD2M0chgFAACWW7ZUaFfqQed8K38KEOst/KkAJF3LrWrhb1OAuultbdN94zBc3QMbmf+G\nMm1qjLhZLdq2JTmrFi6dn58/NecnPQ4AAABNVQ9PF81CnW/hry+RskiKvhGSAreaD0XbtoV+GQuX\n+kewDQDdsO/KPOiL2xZJ1QPU+RDVIim6RkgKPGVZC31Eu4PRtB0y/ejiwiWWa+Nr9jZCXwAA9uW2\nALUenqZrrXqAWg9PBai0gZAUiIh4KhTdVbXoMb/lX7RwaTQaRZZlnVy4tCttG5XQV1187XrdAcDx\n+BxmE+sskqpXoaYilbIsnwpQ6/+e/u5NqCxnV4Sk0FPLWugjYumH3SaO9SG1auFSlmU7u12CRNgt\nJ7ZA17mIpw28RtmFdQLU+vVouoZLHYyrZqDu6jXqWo5FhKTQE/UPolQxmrS9hX6ThUsAAACH5EuS\nV9SvO1ctkkpVqKkzMF3PLgpP05/bxGQyiSzL7n6H6BQhKXRY+lCp/zOi3aFohIVLAAAAXZTmoK4K\nUOvFP+nfIyIePny4sgq1TkjKIkJS6JD6wqV9tNBvKrWk3zW0tHCJXdFWAwAA7bRskdR0Oo0nT57E\n+fn5wkVSn/70p+Mv/uIv4qd+6qdmP37iJ34iIiIePXoUFxcXh74re/PNb34z3vOe98T3vve9GAwG\n8b73vS/e//73x5/+6Z/G3/7t38aP/diPRUTEhz/84filX/qlI9/a5hGSQot1uYW+6QuXujyTtKv3\n7divGQAAYD/mlz/V/eZv/ma84x3viK9+9avxta99Lb72ta/Fv//7v8d//Md/xKtf/er40R/90Xj+\n+efjDW94Qzz//POzH294wxviVa961RHuzfayLIuPfvSj8ba3vS0ePHgQb3/72+Od73xnDAaD+OAH\nPxgf/OAHj30TG01ICi2zbOFSm0PRiMMtXAIAAKA/8jyPN77xjfHGN75x9nPf+c534k/+5E/iH/7h\nH+Jb3/pWfOUrX4mvfOUr8dWvfjX+6Z/+afbv5+fn8fzzz8cnPvGJG3++qZ577rl47rnnIiLi6uoq\n3vzmN8e3vvWtiNBVtw4hKTRcvYU+haPJMVrod2V+4VJZlrNq0fPz84VtFABt4AQUYP8swtk9j+n+\neGybZzKZxGg0iuFwGK973evida97XfziL/7ijd9TVVV897vfja985Svx4z/+40e6pdv7+te/Hp//\n/Ofj53/+5+Nzn/tc/NVf/VV84hOfiJ/92Z+Nv/zLv4xnnnnm2DexcdqZrkCHpUrRoihiPB7HkydP\n4vr6OoqimH24zm/ya6r5tu00K+aHP/xhvPjii/Ho0aOIiLi4uIhnnnkm7t27F2dnZwJSWENXxyIA\nAMAmtjknXmdx02AwiOeeey7e8Y53xOXl5bY37ygePHgQv/ZrvxYf+9jH4urqKv7gD/4g/uu//iu+\n8IUvxGtf+9r4wz/8w2PfxEZSSQoN0NUW+jQs+8mTJ51duORbYaDO8QAA4PA2PQcriiLyPN/TrTmu\nyWQS7373u+O3fuu34l3veldERDz77LOzX//d3/3d+JVf+ZVj3bxGE5LCEdzWQt/WYHR+4VJVVXF9\nfR15njdm4dKudOV+LNLlCsWu3i8AAGB961SStlFVVfHe97433vKWt8QHPvCB2c9/+9vfjte+9rUR\nEfHP//zP8TM/8zPHuomNJiSFA0jBTD0UffDgwWz2ZltD0YjVC5cePnw4C0fh2Nr6HusTITYAAIeQ\nZpJ2zec+97n45Cc/GW9961vjhRdeiIiIP/uzP4tPfepT8YUvfCEGg0H81E/9VPzN3/zNkW9pM3Xv\nFQENsayFPuLlsGY6nbYyHN1k4dLjx4+FHsBa2nYsBABYlxFdzdPVStJ3vOMdNzpVk1/+5V8+wq1p\nHyEp7EhD24oKAAAgAElEQVRXW+gj4kYLfVEUcXJyElmWxcXFRYxGo9beL4A28GUTAMBy24TQXZ5J\nyvaEpHAH86HoJguXmjz3MS1cqs8W7drCpV1Iz2EXQ+Kmvjahb7p4fIG+8tlK03X1vBYW6WolKXcj\nJIUN1KtFF7XQtzU8nF+4VBTFrIX+rguXXBC0j5PjdmjyFy0ALOYzFqAZhKQsIiSFFVIomuaKdqmF\nftXCpSzLdnK/2vrY0F1CRYDNOG7SVFVVtbZAATi+VBgEdV4RMGfZwqW2h6KbLFyCLmrrexfg2Bw/\nAWiybb7QK4pCJSlPEZLSe7ctXNrXN9SHaJW1cGm/tDsDAAC3Ufm8f5te22q3ZxEhKb3T5Rb6pi1c\nEiICAADQNEJSFhGS0gtdbqHf18Il+ku4DQAAdJmQlEWEpHTSsVroN7FtEHWIhUsAx9CXcN5xGoAm\nqqrKZxS9URRFnJ+fH/tm0DBCUjqh3kKfqkWTLlSLWrjUTCou28fz1VxtPUYDAHBc2wT8KklZREhK\nay1roY+I1oei89Wiw+GwlQuXhIg0SVveN+vy/gIAaAdVus1juz2LCElpjdta6NsWjNYDjqYtXAJg\ne8JrAIBmU0nKIkJSGm0+FO3SwqWyLGM8Hsf19bWFSzSKCkXYnmM3wGGozAPuQkjKIkJSGqVeLbqo\nhb7NFZXzLfRVVcVoNOr0wqU+hG1dv38AAABNts2XJtrtWURIylHVFy6litEHDx7E+fn5bPZmW8PD\n2xYuPXnyJIbDYeR5fuybypba+toEAIB5vvynzbYJSUcjkRg3eUVwcMsWLqVANH0L1LYAqksLl6Cr\nnPwDcCxVVbW6K4p+cL2yH85Bm0e7PYsISTmYoiiiKIrOtdDXq0UtXILm6sP4BwAAmkkA3Sza7VlE\nSMrBpNb6NlaJJmleagpF77pwqeuBTR9CqS7evz48b11icUX7eH9BdxRRxJdOvhSvrl4dr61ee+yb\nA8CaVJKyiJCUg7vtYr5pAc18C/1gMIgsy+68cEmo0X6eQ47J669dyrKM8Xg8+yyJiDg5OXnqR5u/\nSIQ++p/B/8T/G/y/+J/B/8Rrp0JSgGPYpmhASMoiQlKYc9vCpeFweOybCNBJTfqC7K5S50EKRsuy\nnI1jqX+O1OdZl2U5O8lPoWl9waEAFZrnx6ofi+fL5+PV8epj3xQANqDdnkWEpPSehUsAx9eF42xV\nVbOw88UXX4zBYBB5nj/1WfL48eOlM7nroWj9x+PHj2dLX1LF6XwFKnB4J3ESb6zeeOybAcCGVJKy\niJCUxjlEu/38wqWIiCzL4vT09GALl5o2VmAf+nAfaRevR3atPqc6fck2GAzi/v37W3UepGrR9DlU\nFEVERJyfnz8Vnqb/d73KVPs+0Bdmcu+ex3R/PLbNIyRlESEpvbBo4VKWZbPZoqpw2EZXQ+D0Xuja\nyVyX7gvHs2gkS/1Ltqqq4oc//OFeRrMMBoMYDodP/d316tPb2vfrVagCVACgC7a5JtNuzyJCUjpr\nvoX+5ORkNldUCz0A60pt9Gm+aPo8WTSSZTqdHvz2zVef1s2370+n01l4qn0fAOgKi5vYBSEpB7Pu\nQWvb6rxl1T3pQvYQLfSbGAwGUZblsW/GXvXhPgLdlLoPxuNxFEURo9Eo8jxv3QK/2wJU7fsAQB8J\nSVlESEprLVq4lLbQX15ezubCAXRZ18YiHMuyL9rOzs4iy7JOPsba9wGAvkpfgkOdVwQHs8mF07JK\n0iYsXIKkqzNJaQ+B1N0sG8vS9y/atO8DwG75Urt5zCRlESEpjVP/8OjywiUBG02WXp9tfX/BMtPp\ndDZbtP6Zsss2+i4f27XvAwBNs811i3Z7FhGS0jip5fHBgwcWLrWcIJgm8Xrsp3ob/Xg8jqqqIs/z\nvbXR9/kzSvs+QLuljgDoC+cZzBOScnRpa3Cq6plOpzEcDuPs7KyRC5cA2I9dhdiL2ujzPI+rq6tW\nttG3PdzXvt9ubX/9NYkODQBoNiEpB7eohb6+cOn6+jpOTk7i9PT02Dd171x4tJ/nEHbjLpW+KWRb\n1EbfxC/bhCSv0L7fDh5TmkjoDMCuCUk5qEePHkVRFBERs7mio9HoxsXReDw+1s07KCd17ec5hONJ\nbfQpGI2Izm+j75tdtO/Xg1YBKgDHoKhi/3xpwq4ISTmoNFt0VaucuYHd4blsL88dTZTCsPF4HEVR\ntL6Nfh1dvE93tU37/uPHj7XvA3BUPmug+YSkHMxgMIgsyxrX9gjQVl0Ps+vjWcbjcZRlGaPRKPI8\nj8vLS58nPGU+QB0MBjGdTuPs7Ez7PgAAKwlJ4Ui6Hm70heewPbzn2qG+zK/eRn9xcRGj0UhgxdZ2\n0b5fr0IVoAIAdIuQlINa52JiMBhEWZYHuDUcQpdDKaEb7EZZllEURUyn07i+vo7hcBhZlsW9e/e0\nQrN327Tvp5/Xvg90ibmOtNG212Ne6ywiJOWgfPD2i+caWGRRG/3JyUkMh0Nt9DTKbQGq9n0AaAaf\nr+yCkBSORBUiTeb1ya7V2+jH4/FsTnVqo3/y5MmsMg/aQPs+AOtQKATtISSlcYQzAN1QlmWMx+NZ\nODoajSLLsrh///5TwRJ0hfZ9AIB2EpICe9P1wNv8XLgptdGnYLQsy8iybO1t9F0+XkCE9n3YJdV5\nAOyakBSOpOsBIjSN99x+pDb6FIwOBoPI83zjbfQudOk77fsAsLltvjBxTcAyQlIOZpMLZQctgNsd\n63iZKtzqbfR5nsf5+bk2etgx7fvAobgGoy+KoojRSBzG07wqAHiKLyuoq6oqiqKYhaKpjf709DSu\nrq4ELnO8dzgU7fvt4thAGzgG7J7REM0zmUwiy7Jj3wwaSEgKR9KHEKrr97Hr949+m2+jPzk5ubGN\n3sn+Yh4XmmJX7fvp97vI3w2PIcDxpU4omOdVQeMIngCOI1WajcfjKIoisiyLLMu00UOHbNu+//Dh\nQ+37AHRCURSR5/mxbwYNJCQFgJ6qt9GPx+OoqiryPI+zs7PIskzwAT2zKECdTqdxfX0d5+fn2vcB\naJxtOh2027OMkJRGUknaDaqCaRKvx5el1tr0I7XRX11dxXA4FGgAC+2qfT/9twAVgGPRbs8yXhU0\nTl9OmAU27dfl57DL961vUmiRZovW2+gvLi4WttwCrGvb9v2qqrTvA3AUKklZRkjKwRn8D7A7i8Ls\n1EafglFt9MAx3Bagat9nW77I3Q/XafvhcW2e6XQqJGUhISkHs8kHQ59OfHxoAtuqHzsWtdHnea6N\nHmgk7fvsguccMJOUXRKS0jh9Odnpw/3Usg37k4KE6+vrePz4cUyn0xiNRpHneWvb6B0vAO37AOyb\nkJRlhKQclJNUukaowyHNt9GXZRknJyedaKNv820HDkP7PgC7YHETy3hV0DiqD2mLLl9YdfF92Nb7\nlFpNx+NxFEURw+Fwto3+4cOHs4AUoM+07wOwrqIoIs/zY98MGkhICkeUQpuun4T34T7CrlRVNauA\nGo/HUZblrI3+8vLyRgWV9xXAatr3gWNzLdQ82u1ZRkgK7I2TAVhPVVU3li5FRGRZFhcXFzEajbyX\nAPZA+z5A+1ncxC4JSWmctrbEAmyiLMvZbNE0FynLsrh3755KJaAx+npOto/2fWg6FY/0hZCUZYSk\ncEQC4Xbz/LGJRW30WZYtbKNfl9cgwGHdpX0/ImI8Hi+sQAXgcIqiEJKykJAU2DvfSreP8G036m30\n4/E4BoNB5HmujR5oFceq9dwWoD58+DCGw+GNL82072/HuSVwFypJWUZISmM5+ekGzyFNcajgN134\n1tvo8zyP+/fvP9W2CUA/pMBzNBrdCFHv0r7vHAvawXXtfplJyi4JSTmodUKKvn2AqNaDdksVQWm+\n6C7a6Gmv9BnmgghYx13a9+eDU+37AOspiiJGI3EYT/OqgCNyEttuWtL7K7XRp2D05OTENvod6Mv7\nadNjR18eF+Cm2wLUFJ6mAFX7PsB6iqKIy8vLY98MGkhISiOlC0gncu0nSKQr6kuX0rfPeZ7H+fm5\nNvodcLxfzOMCLDIYDGI4HD71+aN9n205X6dPtNuzjJAUgKcIt1++WCiKYjZbNLXRn52dRZZlLiYB\naBzt+9yV55u22eaaRUjKMkJSDkrwcpPHA5olVdykH6mN/vLyMobDoQsHAFpL+z7QVZsei4qiEJKy\nkJCURhIe0gZep+2y7Pmab6PPsiyyLGtFG73XIAC7oH0f9scYueZRScoyQlIOzodEvwhxaJp6G/14\nPI6qqiLPc230ADBH+z7QRSpJWUZICkckQITDSJUvEREvvvjirI3+6upKGz0AbOGY7fuKLoC7UEnK\nMkJSDmrdkxnhIRxX29+D6eJsPB7HZDK58W3xq171qoUXdADAbmjfBw4lVa5vQkjKMkJSYO/aHLbd\npsv3rW1SG30KRiPixjb6iIj//d//FZACwJHsqn2//vuFp7vhnJY+0W7PMkJSGqsPH9Rtr9ZbR5dP\nXLt839pi0Tb6PM8XttF3/b1Gu3g9Qv9436+2Sft+Ck8fPny4k/Z9Xubx2o9tKh3ZL5WkLCMkpZF8\nQAOLVFU1m2s2mUxiOp3GaDSKPM/j4uJirRNQVScAHIvPn+3Mt+9Pp9O4vr6O8/Nz7fvAxlSSsoyQ\nFIBGq6rqRrVoxMtt9Ofn5zEajTaadUyzqbICYBO7at+fD1KB9timAKIoihiNxGE8zauCxurLxXLX\n72cfRgp0sTJxMBhEWZZH+/+nSpDxeBxFUcRwOLSNfoEuvb88pwDs0ibt+6lLpSxL7fvQA9rtWUZI\nSiP15QSkL/ezqzx/u1Nvox+Px1GWZWRZFnmex+XlpTlOAMDOzLfvJ/XqU+370F1CUpYRknJQTh6A\npN5GPx6PYzAYRJZlcXFxsVEbPQDALmjfh34QkrKMkJRG6lILKfCKsixjPB7PwtHRaBRZlsX9+/dd\nSNApXRzDAdAUx7hO6Hr7vs+t/fHYNo/FTSwjJOWgfDjc1IcwuA/3keVSG30KRrXR0wc+6wD2r0nH\nWu37cDzbhNAqSVlGSApwBykE7tqJ7F3C7UVt9HmeN6KNvqvPFwDQPJu279cDVe37sD9CUpYRktJI\nqg+hXVJbWb2NPs/zuH///lNVFQAAfbdu+359uWWb2vehybTbs4yQFI6oD2FwH+5jHy1roz89PdVG\nf2DeXwDQLbe179dDVO37sDmVpCwjJAVgLamNPgWjJycnttEfmcccAPqjHnaumn+qfb9ZjHrar20f\nX88JiwhJaSTVh7RF11+rqb1rPB7P2lKyLIvz83Nt9Oxcl99LALBP27bvR8QsLK2qKoqiuFGBCl3k\nnJNlhKRwRIPBYHZyAk2QTo5TtWhqRTk7O4ssy5wsszdeWwCwH+u0708mk4iIpe378//ucxvoIiEp\nsFddr7TsgjTPKv1IJ8DD4TDu37/fqZNgr0eAzThm7kZ6HLv0mUr71cPOFJaen5/f+O9UgZpa+Ovt\n+8sWSEHTeZ2yjJCUg1r3YCTIgP2qL11a1EY/Ho/j+vraCQQAPgtoHNcJ+3fX9v1lC6QAmkxICkck\nDO6GNjyHqY0+zRetqiryPNdGDwC0knOX41mnfT+FqNr3LW7aN48vuyQkBbiDJn8gL2qjz/M8rq6u\nYjgcNvq2AwDQLvWwc1mAqn0faDIhKY1koVF3qJY9nHTiuaiN/uLiYmG71DKet3bwPAEAbaB9nybx\n2mEZISlAi81vo48I2+gBAGgN7ftAUwhJ4YhUgbGNdII4Ho+jKApt9BvwngMAeFoT5zpq3+c2zuvZ\nNSEpjSTI6JYuP5eHeK3W247G43GUZRmj0SjyPI/Ly8uN2uiBw9jlcaHLx1AA2Ib2feo8d+yKkBTY\nKx9Y26mq6sbSpYiYzRYdjUYeV2iwXb4/vdcBYDNNa99vYpUusJiQlIPa5MOhD5UzKmapm2+jHw6H\nkWVZ3Lt37+Dfbnttcmh9es25UAKAw9O+T8QrzzUsIiSlkXzY0AeL2uizLNNGDwCwgoCDXdO+3x/T\n6TRGI1EYi3llAHvV9eqwTe9fvY1+PB7HYDCIPM+10bO1Lr+/AGAZ50wcyl3b9yMiJpPJztr3ecU2\nowwmk0lkWbanW0TbCUlprD5c+Hc9QORlZVnGeDyehaOj0SiyLIv79+8/dbLFfnXtPecEGwDYhS6d\nHx3Kuu37qW1f+34zpOsxWMQrg0by4UCbpTacFIxqowcAoOlcg+1OClDTY3p2djb7Ne37xzWZTCLP\n82PfDBpKSAqwA6mNPgWjbW+j71rFJQAck+3WQHLX9v35KlTt+5spikK7PUsJSWmsPgQ0fQiiunwf\nU8vM48eP48GDBzEajSLP8zg/P9dGDwAArG3d9v30Q/v+9jNJtduzjFcGR3HbwazrB3PaqaqqKIpi\nNlu0LMsYDAaz+aJetwAAwK6lAHXR2C7t+5uxuIlVhKQcVF8PxLTXfBv9yclJZFk2a6N/+PBhK9vp\n+6yrlc0AAPSP9v3NFEVhJilLCUlppC63aM/rw/1s231M376Ox+PZzJosy7TRd0CXT/gAACDRvr+Y\nSlJWEZJycF04sO5KHx6LNtzHehv9eDyOqqoiz/M4OzuLLMtuvQ9tC4HX0acvKtqsa89Tl+4LAPvj\n82L3PKb70dSlbV1p39/mdSskZRUhKdBLqd0k/Uht9FdXVzEcDtf+kG/iSQ+0kfcSAJvwubF7HlMi\n2te+b3ETu+SVQSN1rTqKZphOp7PZovU2+ouLi4XfogIAANCd9v3pdKqSlKWEpHBEfQiDj3kfUxt9\nCkY3baMHAABgtTa172u3ZxUhKdApi9ro8zzfuI0e4C66/gUYAMA6mta+LyRlFSEpjdSHCkt2o/5t\n5GQyiel0GqPRKPI8P0gbfVdfq+4XbM+XMQBARHMXNzXBLtr30++dTqdrV58KSVlFSApHVD+w+/Bc\n33wbfURElmXa6AEAAFpu3fb9oiiiqqq4vr5e2L7/5S9/Oaqqiueffz7Oz88jIma7Kbrkm9/8Zrzn\nPe+J733vezEYDOJ973tfvP/974/vf//78Ru/8RvxjW98I17/+tfHpz/96XjmmWeOfXMbTUjKwW1S\nySU8bL9dVe6l9ovxeBxFUcRwONxqGz0AsD7V99APqToPmm6+fX86ncbZ2dnC9v1//dd/jU996lPx\nzW9+M5599tl4wxveEM8++2yUZRmf+cxn4k1velP85E/+ZOtf+1mWxUc/+tF429veFg8ePIi3v/3t\n8c53vjP+/u//Pt75znfGH/3RH8Wf//mfx0c+8pH4yEc+cuyb22hCUhpJ4EW9jX48HkdZlrM2+svL\ny9Z/kMEuGB8AHILzsrvzxT/Afi1q3//Qhz4UH/rQh2IymcQ3vvGN+PKXvxyf/exn44tf/GJ8+MMf\nji9/+cvx/e9/P55//vl405veFD/90z8db3rTm2b//upXv/qYd2ltzz33XDz33HMREXF1dRVvfvOb\n41vf+lb8y7/8S3z2s5+NiIjf+Z3fiV/4hV8Qkt5CSApHlkIOJ84vX0DUly5FvPyt2MXFRYxGo0Y+\nRkIqAACAw1v3OizLsnj++efj+eefj5deeileeOGF+L3f+72IiHjw4EH853/+Z3z5y1+OL33pS/GZ\nz3wm/vqv/zq+9KUvxete97r44he/uM+7sHNf//rX4/Of/3z83M/9XHz3u9+N17zmNRER8ZrXvCa+\n+93vHvnWNZ+QFNi7VR9eZVnOZotOJpMYjUaRZVncu3dv7eHb7J55uRyDLxwAWIfWcNrCufT+bfr4\nFkURFxcXs/++urqKF154IV544YUbv6+qqnjppZd2chsP5cGDB/Hud787Pvaxj8W9e/du/Fq90pbl\nhKQ0lgrLbph//ha10WdZpo2eg1D521yO9QAA7NtkMok8z2/9fYPBoFVLjiaTSbz73e+O3/7t3453\nvetdEfFy9eh3vvOdeO655+Lb3/52PPvss0e+lc0njeDgXAg/reuhTVVVMR6P4+HDh/Hiiy/GgwcP\noqqquLi4iGeeeSaurq7i9PRUQAoAAMDeTCaTzm23r6oq3vve98Zb3vKW+MAHPjD7+V/91V+Nj3/8\n4xER8fGPf3wWnrKcSlIarevhYUR3Q+N6tWhExJMnTyLP87h///5skHYXDAaDKMvy2DcDAACAW0yn\n086FpJ/73Ofik5/8ZLz1rW+djQ348Ic/HH/8x38cv/7rvx5/93d/F69//evj05/+9JFvafMJSTmK\nddrouxoedlVqo0/zRVMb/enpaRRFEffv3z/2TQQAABYw5ow22uZ1m/ZgdMk73vGOpYU7//Zv/3bg\nW9Nu3Xpl0Ao+fLsjbaNPwejJyclT2+irqoqHDx8e+6ayBXOBAQCALuliuz27IySl0frSbt+m+1lv\noy+KIkajUeR5Hufn551qo4c2aNvxAwCgTxQcNE9RFEJSlhKS0lg+TJqhqqooiiImk8mNNvqzs7PI\nsszzFP0I87vE8wUAAP2kkpRVhKTAU8qynIWi9Tb6y8vLGA6HGwWj6fd29VvULt6nLvN8AQBAN2xz\njamSlFWEpDRaHyq+mtIuO99Gn2VZZFmmjR5gD9Y97nf9iyaAbTgmAsk2i5uEpCwjJKWxnPjsV72N\nfjweR1VVkee5NnpmmhLgQxt57wDQJj636AshKasISaFHlrXRX11dbdxGD7BLfaqY7Pr9A54mgKIN\nfD7tXh/Oa9pGuz2rCElprL5Use3zflZVFWVZxng8jslkcqON/uLiIk5OTvby/52X7mMXTxD68joF\n1tfFYx1wd44NAMenkpRVhKQcnBPE/Upt9CkYjQjb6KGma6F21+4PAACsY5tCHCEpqwhJoQMWtdHn\nea6NHuZ0rfLXexsAANYnJGUVISkHt+5FfdfCjGW2uZ9VVc220U8mk5hOpzEajSLP84O20a+rL89l\n13jeAACALknXzrCIVwa0RFVVN6pFI15uoz8/P4/RaKSi7EgEicCmyrKMsiw7O6sZAHiZ64TmUUnK\nKkJSaLDURj8ej6MoihgOh7bRA7RMvfp/PB5HWZYRETEej2MwGMTJyclTPxzfAZYTPO2ex3R/fKbv\nj5mk7JqQlMbqU4Veup+LLqSzLIs8z+Py8rJxbfQALFZfojcejyPi5er/i4uL2a8Nh8OoqmpWWZqO\n/2VZxmAwmAWoETH7/ennAfrOsXD3PKb0QVEUQlKWEpJCA0yn03j48OGsqihdSHeljb5PgTfN57XI\nvqTwMx3TB4PBwiV6aWTKfBBa/3vq4Wn6M+PxOKqqWlp52oXPCwCAfVJJyipCUjiCsixjPB7f2EZ/\nenoa9+/f12bZMl0OgLt437y32LU0Lzod09Mx/OzsLM7Ozrb6O+fD0/F4HOfn57P3ZApP00iWNN80\n/b+17gMALJbOmWARISmN1aWAJrXRp4voehv9YDCI0Wi09cU00F9dOk62SVVVN77oGg6Hked5nJ+f\nx3A4jB/84AcxHA738v8eDAYxHA6f+vvnw9OiKGY/Z+4pAADcTkgKe1LfRp/a6PM8f6qNfjqd9iLk\n6MN9BO4mhb5NDO/qi/RSm1YajdKEaoRV4emquaf1wFTrPgDslqrF/WrqeSPtJSTl4DY5iLUtWEsX\nn+nHaDSKPM/j/v37e6sqagMfXEAbpdEo4/E4ptPp7JjepkV66849rVefmntKXdvOxQAAtiUkpbHa\n0Ea6rI3+9PS0VRfR3E3TX6fA+tIxfTwez47pZ2dnkWVZpwLCZeFpxNOt+/NzTxfNPu3SYwPQRyry\nAISksLFFSzruso2+DWEwy3X5ZLKrr80u3ie2t+jLrkWjUbb5e9tqk7mnKTw197TbPI931+ZjAkCX\nOB6zipCURmvKASy10Y/H4yiKYjaLLi3pYLWuhm20jwt9Il7+bCmKYnZcj4idBKNdd9e5p/UKVK37\n9JHXPMBuqYBm14SkNNYxD3b1C+h6G30XWy4B+iAd11MrfeoCuLq6iuFw6Lh+B+vOPZ1Op7N/jwhz\nT4GtCUZoC6/V5jESj1WEpPB/0ty19CNdQF9eXu71AnowGMwuGAHYnUXjUQ6xTM/F0MvuOvd0UfUp\nAADsi5CURtt3i3Z9Dp02erZhlADH5PX3tBS4pfEow+Fw1kqvcqA51p17Wg9PzT0FAGCfhKQ01j4u\neubn0FVVFXmea6PfM0FOO3neaIuyLGdt9OkLrzzP4/LyUjDaMreFp+mfq+aeCk8BoPtcp7APQlIO\n7tAXLYva6PM8b9QcOgd4OBzvt26odwJMp9NWzY1u+u1rohSezlu1NCr9uYiYzaE19xTgaencyLGR\nNvK6ZZeEpDTWtlVs6WKpfvE8Go0iy7JGtls6qMPheL8126rjflVVswBsPB5HWZY6Abh1aVQ6D0j/\nvmzuqfAUgH3w5XyzeD64jZCUTqhvLZ5MJhERraoqor20pMP+pGA0tdJHxOwLr9Fo5NjOUvXwtKqq\nOD09nf2auacAHJLPkOaYTqd2j7CSkJTWml/O0cQ2el4mSATWNb+RPiIc29mpdZdGmXsKAN0ymUwi\ny7Jj3wwaTEhKY80Ha/VWy3obfduXcwgQaSqvTQ6l3gr9wx/+cPal171793zbz8GsCk+XzT2tV6xq\n3QeAw0kdIJuYTCYxGonBWM6rg0arqmpWTVRvoz8/P9dqCfRem4Ps+eN7qhK9urryDT+Nctvc0xSe\nmnsKh7NNOAIwmUwiz/Nj3wwaTEhK46Q2+uvr65hOp/HkyZPIsizu3bunta2l2hzkrMvJent0/bXY\nZPUxKandqb5U78UXX2xtVwD9syw8jVg99zSdy2jdB4DDmk6nvoxnJSEpR5NCpUUbi7Msi9FoFGVZ\nxv379499U/eqDwFil7mobRfP1+GVZTlbvNSVMSm74LXYbevOPS2KYvZz5p4Cx+LL/v3x2DZL6l6C\nZYSkHFwKBSeTyWwj/WAwiDzPb2wsLopi1mIPQHvUN9KnL77Ozs4iyzIXCltykdUN2849rQemWvfb\nyRMxBzoAACAASURBVHsYYLe2KTSyuInbCEk5iuvr6yiKIrIsi/v37/s2BxpKlTPrSB0BqY2+LMun\nvvhiex6/7lt37mm9+tTcUwD6bpvFTWaSsoqQlKM4Pz+PiNUHtb60offhfvbhPnaxQqRr94fdqqpq\nVvE/Ho8jIgSjsGN3mXu6rPoUAPoqFWrBMkJSgDty0UlfpGA0tdKfnJxElmVxdXU1206/i/9HF3Tl\nftBc6849nU6ns/DU3FMA+ky7PbcRkgLQK8KrzaQZ0qmV/uTkJPI838uolK4ENV25H7TTXeee1qtP\nvZYB7qaL3WZtNplMYjQSg7GcVweN1YcW7aQP97MP95Hm6+pJ6q5PwFPr7ng8jqIoYjgczlrp+7yR\nHtps3bmnqfK0LMsbfy4izD2FjnKeThttc/5bFIWZpKwkJIUj68NFRh/uYxf16YuKttp1MJqqRVMr\nUp7ncXl5KRiFDrstPL2+vp7997K5p6pPOaR0buK1tlseT/pAuz23EZIC3JEwkbZK7bbj8Tim02lk\nWRanp6dxdXXlYmnPHDNounp4OhgMblTerFoaZe4pAE0lJOU2QlIaS/AEsFsp2EiLl8qyjDzP4+zs\nLLIsE2IAa7ltaVT656q5p8JTAA5NSMpthKQchQD0FX14LPpwH6GpqqqK6XQ6C0YjIrIsi4uLixiN\nRgIKYGdSeDpv1dKoiFganjo+AW3m+me/tnl8i6IQkrKSkJTGsxEQYDNVVUVRFLMZoxEReZ7H1dVV\nDIdDx1TgoNZZGpX+uWruqfAUaCPHrP3ZZnGT7fas4tVBY/kwoS26Wik7GAxmVT5d0dXnKuKVpSpp\nxujJyUnkeR737t3T0go00rLwNMLcUwB2T7s9txGSwpF1ObQB9isdOx48eBBFUcRwOIw8z+P+/fsL\nW14BNnWsjp7b5p4uat0XnsJ2dO7RF0JSbiMkpfF8aLefIBh2J1VU1VvpR6NRXF5eLqzGahvHCvj/\n7N17lGRVff/9zzmnzqnqqpqeHpVhIsGgouMIYjTJL4SEpUJI1BjjUsH4LCURDYlGVxQW/sxFo/6C\nipdEF5Lfg4mPirpYSkwi4jWKYgw+yc8bkUseUDSK3IW59aXObT9/DPtQXV3dXV1dVef2fq01a7Sn\nS+ty6py9P+e7v7t4ijQO2yg8Xa/vaX/Fal5L9zm3AUD+4jhWq9XK+2mgwAhJkYtRQ7MiDcoBIC/9\nO9InSaJGo6EgCNTpdHTgwAE1m81KBKQAMK5R+p72B6h59D1lXAsAkzNOMVUURZqfn5/SM0IVEJIC\nObMndipmy4tKWUxD/470aZrK9321Wi35vl/Zc0VVXxeA/Izb97Q/MGXpfrEwZkZZcKwWD8vtsRlC\nUuRmlIsG4ROQH75/s2WMyYJRO1EPgkDtdluNRoNBNgBM2Kh9T+M4zn5G31MAKK84jglJsSFCUuSC\ngWS9ELahKIp2LBpjFMdx1mNUEsEoAORs3L6nw6pPZ9n3FACwMSpJsRlCUqAAbHDDIBqoPhuM2qX0\nruvK9311u115nsd5AAAKait9T+M4VpqmkiTXdbMl/HEcE54CwASMU/hASIrNEJKi0IpW9QWsh+MU\nGzHGrNqR3nVdBUGg+fn5NZVKqAbOCUB9jNL3NAzD7FowbNOowepTYJYo1kBZbfW4Zbk9NkNICmDq\nqh52M6jEMHYTkDAMFcexPM/LltKzE321cU4AYNml+zb8DIJA0tq+p0mSZOEpfU+BaiB8Lh4qSbEZ\nQlKgIKocIqKcqh5uT4OtFoqiKBuEBUGgTqcztWCUzwkAyme7fU/7q09Zug8Ao0mSRI0GMRjWx9GB\nQqvL5J+BLVBedgIbhqGSJMmC0W63y3cbALAlo/Y9tZWn/X1Ph1Wech0CgAdRSYrNEJICAGpjUjde\nkiTJNl5K01S+76vVasn3fSakAICJ2yw87Q9Q1+t7SngKoErsOW4rCEmxGUJSAFNX9Yrgqr8+HBmE\n9QejkuT7vtrtthqNBpPNCeK7BACj6w88hy3d7+972h+elrnvKX0eAYyLjZuwGUJS5GLUgU1dwqe6\nvE6gTIwxiuM46zEqKVtG73keE7Qp4D0FgMnZqO+pDUs363tapvAUADZDJSk2Q0gKAFhX3cJ7Y0y2\n6VIYhnJdV0EQaMeOHUwSMTEcRwDyZMPTQRttGiXR97TKqM6dDt7X4iEkxWYISZELLhZA8dXle2qD\nUVsx6nmegiDQ/Pz80EkkAABbNU7vvFkbddMoe92k7ymAPI0TQhOSYjOEpCi0uixDr/rr5PWhaGxv\nNhuM+r6f9Rgt+iR2EMcfAGCa1gtPpY37ntqwlKX7AIqCnqTYDCEpAKAW0jTNNl3av3+/fN9XEATq\ndDqlC0ZRPwThAIpos76nw5bu0/cUQF6oJMVmCEkBAJXVvyN9mqbZoGhhYYFgFKVBcACgbDYKT9fr\ne9pfscrSfQDTQEiKzRCSotDqsoy06q+z6q+vysr2uRljsmDUTrqCIFC73Vaj0ZDjOLrvvvuYbAEA\nkINR+56maao4jrOf94em/b/P9RxFxjFaPCy3x2YISQFgm6oaApdlUGeMURzHWY9RSWuCUQAAUFxb\n6XuaJImMMVpcXFxVbcrS/fFVcRyL6hsnhI7jWI0GMRjWx9GBwuOiDWCQDUbtUnrXdeX7vrrdrjzP\nY3IEAEBFDC7dtzdGW63W0MpT+p6Oh/cGdZCm6Zo2IEA/QlIUWp0u1oTBwMaMMat2pHddV0EQaH5+\nnsEOCodzOgBM17h9T4dVn9L3FAAgEZIiJwxCVqv6+2FfH315sFVpmmbBaBzH8jwvW0o/7sZLtj0C\nx2LxVLV1BQBgdrba9zRNU0lat/KU8QIA1AchKQqPCTPKoIrHaV6BVZqmWbWo3YEyCAJ1Oh12pB+C\nYBEAgM1tpe+prTwd3DSqvwKV8BTIF0UPmAZCUhQak3+UAcfp9tmlcGEYKkmSLBjtdrsMflA6HLMA\nUC4bLd1fLzyl7yk2Q4gHlA8hKVAAhGyooyRJso2X0jSV7/tqtVryfZ8BJQAUBOMT1Nl2+54OLttn\nfAMAxUZIikJzHCfrE4Ryow8kjDGrglFjTNZftNFocGwAQEFxfgZWG7XvaX94KhW376ltKwAAdUdI\nCgATQKXNcMYYxXGc9RiVlC2j9zwv90kBAADApIwSntq/N+p7WpTwFADqhpAUKACW25dbVQew4x6X\nxphs06UwDOW6bqGCUb5vAIBZYzVNvY27aRR9T4H1jXNe5buDzRCSIhejnpwIM6qDz7LabDBqK0Y9\nz5Pv+5qfn1/TxwsAAGBcVQucR9k0yrYs2qjvKeFp8VTtWAXqgJAUADAWW+1gg9FGo5H1GKWv1Wxx\nAwIAgGoZZ9Moqbh9TwGgDAhJgQKgyhJlkaZptvFSkiRZMNrpdAhGc8KkBwCA+hh10yi7yoe+pwAw\nOkJSFBrhIcqg6sep3ZE+iiIlSSLf99VqteT7PgNrTFTVv0sAAEzLuH1PXdfNAlZJLN1HKTBexLQQ\nkgKYCcKP8rB9r8IwlDFGBw8eVBAEBKMAAAAltFnf05WVFUmi7ylKZyvHY5IkrHzDpghJgQJwHCfr\nIwTkoT8YDcNQkuT7viRpYWGhUgNiAnsAAIAHw1PXdeX7vhqNI/HARn1PbXg6GKKydH8tW6mLYoii\nKJvfAOshJEWhEWYA02OMURzHWTBqB8jdbjerNOj1egx4AQAAamTUvqdpmiqO4+zn9D1FkRGSYhSE\npACwTWUK820Tf9tj1HVdBUGg+fn5oUuwAAAAAGl7fU/Xqz4FZoWQFKMgJEUu7AXRGMPFsSbKFCRW\njTEmC0WjKJLneQqCQHNzc2uCUQCTwfkOAFAnm/U97a88teEpfU8xrnFyhDiOCUmxKUJSFFpdgrW6\nvE7MTpqmq4JR3/cVBIHa7faWeyNxMwMAABQF45Jy2Sg83azv6WD1KUv3sR1RFGV9d4H1cIQgN1zg\ngMmyg8swDJUkSRaMdrvdsb5vfEfLgZssxcNnAgAokzyuWVvte2o3uaXvKcbFcnuMgpAUwExUPTTI\n67X170ifpql831er1ZLv+wwWN1DlYxEAAGCrijJu3G7f08EK1DxfF1XPxRJFkYIgyPtpoOAISVFo\nVQ/WrLq8zqqa5eDHGLMqGDXGZMvoG40GA7ER8B4BAGaNcR6wfaP2Pe0PT+l7Wk30JMW0EJICQMEZ\nYxTHcdZjVFK2jN7zPAZ5qBSCBABVxfUamI7NwlP793p9TweX7fNdraY4julJik1xhKDwmDCjjowx\n2aZLYRjKdd3cglGWCmFWOM4AAMCk2PB00EabRkn0Pa0qNm7CKDhCUGh1uRDVYbl91V/jJF6bDUZt\nxajnefJ9X/Pz80MHeLNQl+8gAAAA6mGUTaPs3xv1PSU8LRd6kmIUhKQAsE3bGRjZwVcYhorjWJ7n\nZT1GhzWsBwAAADB5424atV7fU1ZjTc84BSr0JMUoCElRaFWvPkQ9pWmabbxkL9ZBEKjT6RCMzkiV\nziucJ+uBzxgAMC1cYzY3yqZRdoPV/qX7vV5PnuexadQUbPV9jKKIkBSbIiRFbpjYP4j3ovrsjvRR\nFClJEvm+r1arJd/3GSjNGO838sYxCADjY8w8HVybxrNReLq0tJT1wBzcNGqjjaMwHYSkGAUhKYCZ\nqFsQ3H8nOQxDpWmqIAhKF4zW7XMDiqgs5wsAmBXOiyg6G3gOBqiDm0bZPQnoezp9LLfHKAhJUQr0\nc0GR2SDRBqN2Kb0k+b6vdrutRqPBMQwAAADU2Lh9T21YOixAxWioJMUoCElRaHU66VOtV07GGMVx\nrDRNtX//fjmOoyAI1O125XlerY5hAAAAAEdsdX43St/TNE0Vx3H2s/U2jar6HGScIipCUoyCkBS5\nYRnvg6p+EbOq8nnbZTG2x6gdiMzPz68Z1AAAUGZVuXYDQB4mMc/bKDztD1AH+54Oqz6t89J9QlKM\ngpAUhWfD1LqezKui7J+fMSYLRaMokud5CoJAc3NzkqRDhw4RkJYIk/7i4rMBAADY3HpL9wfD0/7q\n0zr3PY3jWK1WK++ngYIjJAWAddheQDYc9X1fQRCo3W6vGozYXkFVVMWK76oPAFEMVfveoN44bwLV\nRkFKtWyn7+l61adVwMZNGAUhKXLFBfmIKgZRZdW/I32SJFkw2u12OVZRSFU6f1TptQAAABTNVvqe\n2vC0iH1P6UmKaSEkRW5GPakxaa6GIn+O/TvSp2kq3/fVarXk+z7BKIAt47wBYBCFAQCKbDt9Twcr\nUIu6dJ9KUoyCkBRA7RhjsmDUXuTtMvpGo1HIizoAAACULQsGiq4KN0dG7XuaJEn2nyUVsu8plaQY\nBSEpUABFrrKsCmOM4jjOglFJCoJAnU5Hnudt64LN5wcAAACgLrbb93RY9em0EZJiFISkKDwCKIzL\nGJPtRh+GoVzXzfqLbjcYrZMqfv+q+JoAAACAvI3a97Q/PJ1F31OW22MUhKQAZsJxnGz5xTTZYNRW\njHqeJ9/3NT8/v+ZCjc1VMUiu4msCAAAAimyz8NT+vVHfU/uHjZswLYSkQIFUoW9NHuydSBuMNhqN\nrMcoPasAAACA4ezqGuYgyIsNTwdttGmUfVyapiP3PaWSFKMgJEXh1WG5PYOSrUvTNNuR3l7wbI/R\nvIJRQm7kpernSAAAgDJhbLZ9G20a1ev1JEme5w3te/rOd75TQRBo7969etzjHqdHP/rRlawkPeec\nc/TpT39au3fv1ne/+11J0hvf+Eb9/d//vY466ihJ0lvf+lY9/elPz/NplgohKYCZmETY3b8jfZIk\n8n1frVZLvu/nGk4SjCJPdbiRBAAAUEbMEybPhqeO46wJPW3l6d69e3XdddfpIx/5iG655Rbdcccd\n2rNnj2688UadfPLJ2rdvn/bt26e9e/eq0+nk9Eq27yUveYle9apX6eyzz85+5jiOzjvvPJ133nk5\nPrPyIiRFbrZywahLAEAl4mrGmGxZRRiGStNUQRAUIhitk7p8/1AMHG8AAADYiK0YHWSX7r/gBS/Q\nC17wguzny8vLuuCCC3TSSSfp0KFDuvLKK3XRRRfplltu0dFHH52FpvbPCSecoF27ds3yJY3l1FNP\n1Q9/+MM1P2c8PT5CUhReXYKwurzOzdhg1C6llyTf99Vut9VoNHifZqyq7zcDh2Kq6vEGAACA/MzN\nzcl1XT372c/WYx7zmOznSZLoBz/4gW666SbddNNNuvbaa/X+979fT3nKU3TRRRfl+Iy35+KLL9Zl\nl12mX/zFX9S73vUuLSws5P2USoOQFLlhMgzLGKM4jrNg1HEcBUGgbrcrz/M4VjBRHE8AAJQXK68A\njMNu8NvP8zwdf/zxOv744/Xbv/3bOT2zyXr5y1+uN7zhDZKk17/+9Tr//PP1/ve/P+dnVR6EpCgF\nqr7Kb7BvojFm1Y70rusqCALNz88P3d2w6OzrY9AOAAAAAMVSxY2bhtm9e3f2n1/2spdVJvydFUJS\nFF5dQqc6bL5idyKMokhRFMnzPAVBoLm5uVIGowAAAECZcZN/OnhfiyeO41qEpHfccYd+5md+RpL0\nT//0T3rCE56Q8zMqF0JSAFOVpqmiKNLKyoqSJMl2IWy320ObbaN4qh7eAwAwbQQmADA545xTq1hJ\n+sIXvlDXXHON7r33Xh177LF605vepK985Sv6zne+I8dx9MhHPlKXXnpp3k+zVAhJUXh1qLCsmv4d\n6ZMkUaPRyDZd2rFjR95PD1vAhK4cOEcCAAAA66tiSHr55Zev+dk555yTwzOpDkJSoCDKHgb370if\npql831er1ZLv+3IcR1EUaXl5Oe+nOTVl//zqpkqfFUF2MW12jFXpGAQAACi6uiy3x/YQkgIYizEm\nC0ajKFKapgqCQO12O6saBYqIQBvTxvkPAACgWKpYSYrJIyRFbrYyiSTQKAZjjOI4zpbSS1IQBOp0\nOvI8j2AAAAAAQO3Rh3i6xnl/0zRls2BsipAUhVeXi0tRq9uMMdlu9GEYynVdBUGgbre7pWC0qK8P\nG+NzAwAAqC7GeQDwIEJS5KouAWjZ2GDULqX3PE++72t+fp67b+sgTAS2ry7foyRJlKapkiSR67pc\nCwFgC+pwnZg1rkMAcAQhKXI1Spl8XSbNeUvTNAtG4ziW53lZj1HXdfN+egBQaoOb2zmOk4WljuPI\ndd01f5i0AsBwnB8BbBWZAkZBSAoURB5hcJqm2aTd7vZne4wSjKLKGCRhFuw5ttfrrdrcznVd9Xo9\nNRoNGWNkjFGapll1qd0Mz4an9uf2vxMOAAAAAJNHSArUTP+O9EmSyPd9tVot+b4/1Yk3FcEoiqoF\nTHy3isVW5UdRpAMHDsj3fc3Nza06x6Zpmv2+4zhZ+NmvPzzt9XpKkkRxHMsYs27VadWObQAAyoqx\n2XSNs3ET4ySMgpAUhec4zqoJJbbGGJNVJtllnkEQzCQYrZuqDoaq+rqASemvyrd9Rj3P044dO8Y+\nx/aHp7YFiu/7q6pObSCbpinhKQAABcP1FygfQlKgQCYVRtlg1E7aJcn3fbXbbTUaDS7YU1DV97Sq\nrwvYrsE+zv1V+bZafxrfH8dx5Hnemk30CE8xLdwoAwAAdUFIitwwOVttu++HMUZxHGeTc0kKgkDd\nblee5/F+A8A2GWNW9XFuNBrZeTbvc+xWwtMkSSQpC0w9z2OzKGyI4wKoLm6EoC64lmEUhKQoPPrt\nrc8Yk1UyRVEk13UVBIF27NixZqKcNz5HAGVU5GB0FOuFp/3B6bDNooZVngIAqolzPMpmnJ6kwCgI\nSYGSsRN2uzGI53kKgkBzc3OFC0YBoIwGb0DZYLTT6azZYGkcRRjU2/CzX/9mUYSnwOTYm8R8XwAA\nKDZCUqAgNqq07O99F0WRfN/PeoxOYsKO7atypWzVXleVPyuMbzAYtTeg6nSe7d8sqh/hKYAi4RqO\nMqDSESgnQlIUXl0DjcHdkiddyTRrdf0cy47PDbM06+ONYHQ0o4SnSZIojmM2iwIwE5xLAADTQEgK\nFEiaplpeXlYYhkrTdNVuyQwGAQxDkL01/ZvchWE4tWC0Dp9Jf3jaaDw4pBy2WRThKQAAmIRxxlhJ\nknADHCMhJEUpVHWyaYxRkiTZZN0Yo2azqXa7rUajwaQRACZgMBi1m9zNz89PpZdz3c/d620WRXgK\nAAAmZStjBNuyDtgMISlyt1m/lqpNkOxk3S7xlKQgCOT7vlzXVbvdzvkZYhxU8wHFMutgFJvbSnia\nJImkBzeY8jyPfqcAMAX0zkQdxHG8atULsB6OEuSmThfjYZN13/fV7XbleZ4cx9HS0lKl3xP72hiI\nlQ/hL8pisDrfcRyC0RIYFp6yWRQAoMyY8xQLlaQYFSEpSqGMIc3ghiCbVTFRiYgiquLgju9atQwG\no9KR6vxut0vFQImNslnUKOEp33UAABDHMSEpRsLsAbkaJYApU0hjlwmGYag4jtkpGQCmJEkS9Xq9\nNcGorc5HNY0TnkrS8vIylacAAFTAOFW6VJJiVISkwDalaZpVi9qTbxAE6nQ6BKM1QnUiMH2DG90R\njMJaLzwNw1BJksj3fSVJojiO2SwKAICaiaKIFUYYCUcJSqFo4ZOtUOmffDWbTXW73W1Nror2OifN\nBolMQIHJqvK5oz8YTdM0q85vNBqcS7ApG3o2Go1Vk6Nhm0URngLlUOVrHoDpiKJIQRDk/TRQAoSk\nKLwiTErsZGpwot5qteT7/kSeYxFeJzAMk5Fiq+K5g2AU0zZssyiJ8BQoC753KDrGz8VCT1KMipAU\nWMewzUB832eijlrhOMes9LcuOXjwYOWDUSZPxbSV8DRJEkmS67ryPI9+pwBKiVVe08P7Oh3jjKHo\nSYpREZKi8GbZ69EYoziOs4m6xGYgk1T1vp1Vfm1Vw2dVDP0V+kmSZEHTzp07Od+iUIaFpxttFmX7\no7JZFAAAkzfOxk30JMUoOEpQe8aYbNOlMAzluq6CINCOHTvWVJJMU9UDxKpj4lsefFb5GgxGfd/P\nWpfEcazl5WU+I5TCeptFEZ5iEJV6AJAvepJiVISkqCVjzKod6T3PUxAEmp+fn2kwCgB1YJcnh2Go\nOI7VaDQm2tMZKBLCUwAAioWepBgVISlyNUr15KQqLPsn6bYnie0xOjiRAXAEFc4Yl70Z1R+M2vYl\nBD+oo1HC0yRJFMcxm0UBADBBdiwKbIajBJU2uKzTTtI7nU7hgtE6hFF1eI1Andn2Jb1eb1UwWsRz\nLlAU/eFp/wRu2GZRhKcAUA72XI3JG6eFCRs3YVSEpKic/h3p0zRd1e+OyQOmhQAYecn72LPBqK3S\n9zxPzWaTYBTYpmGbRUmEpwAmi/Er6oCQFKMiJEXh2YH9eneMjDFZMGonCkEQqN1uq9FoMDEAsAYT\ngu0ZFoza8y7B6BEcY5iWrYSnSZJIklzXled59DtF6XFunQ7OB6g6epJiVISkyNW4FVDGGMVxnE3S\nJZU+GM27GgyoizKeH4rAnnd7vR7BKFBAw8JTNotCVXGcAtgKKkkxKkJSlIadoNul9K7ryvd9dbtd\neZ7HYKkECILLic+svoadd4Mg0Nzc3JoqNjyI6xGKYpTNojYLT+3vAgBQBPQkxTQRkiJ3G53k7JJO\nSTpw4EA2QZ+fn2eCjkJxHEdpmub9NCaOsKd+1gtGZ3XeJYwBpm8r4akkLS8vU3kKAFswTpCH6Ynj\nWEEQ5P00UAKEpCgc20crDEPFcZxNynfs2LFq19cqIhwAkAfb29kupXcchxtSQA0NC08PHz6subm5\n7GZgkiSK45jNogAApRFFkbrdbt5PAyVQ7cQJhWcH0GmaZhuA2FL4IAiy3ZHvv//+yve8q8tkgiAY\nKIb+Te/6ezvv2LEjt2C0LudBoGxs8Om67qob1sM2iyI8BQAUDcvtMSpCUuQqSRIdOnRIaZpmwWi3\n210zgKaXZTUwMUJR1PV8sl4wSm/n4qvrMYtiG7ZZlER4CpQJy8JRB+xuj1ERkiJXruuq1WopCAIu\nzii1Kgf5VXtdVTvXjHLs2WC01+tJIhgtGz4jlM2o4WkYhlk/b9d15Xke/U6BHPBdQ5mwcROmiZAU\nuXIcR77vj3SSq1pQM6jKIRvKi0FzefVXjKZpmrUwaTQafK4AcjEsPB22WZStPK3KZlFU6gFAvqgk\nraeVlRWFYbjqJqzjOGo2mw1JxhiTDD6GkBSlwMCyGgiCgekaFoy2222CUQCFNWyzKKke4SmA6uLm\nSLHEcVz5TaCx1tVXX60vfelL2rlzZ9by54Hv5fmSdjiO84/GmG85juOYB4IKjhIAAErM9vk7cOAA\nwSiAyiA8xTAETwDGwXL7eup0Otq9e7darVY2Z3qgzU8iaejO4ISkKI2qVyBSZVl+fH6YFdvLLwxD\nJUkiY4zm5uZGbl8CAGW1WXiaJInSNFUcx2wWBQAVNM7NEpbb19NTnvIUPeUpT8n+ux0XXHDBBe+S\njqy37/9bIiRFSTCIRdFV+RitWvhb1hsSg8Go7/tqtVpyXVeHDx9WEAR5P0UAyM1G4Wn/ZlG26pTw\nFADqg0rSerKB+tLSkj7zmc/os5/9rJaXlyXpw5Ie4jjOXxljrnUcxzXGpBIhKXLGILReyhpO1Rnf\n0XzZCX0Yhtkd8FartapiNEnW9BsHADxg2GZREuEpYNHCAHVASFpPaZrK8zxdeOGFWllZ0X/913/p\n9NNPl6QfS3qIpEMP/CqVpCifqodrBIgApCPnOlsxapvMB0Ggbrdbi0kM50EAszBqeGo3wpMk13VX\n7ZBLv1MA6yF8LhaW29fbzTffrD//8z9XkiQ64YQTZIz5U8dxPizpUZK+K8nRA0EpISlyNeqFgwsM\ngCrbTjBapRssVTrXb/SZ2NfJBAoonmHhKZtFAUC5UUlab51OR1EUadeuXbr11lvlOE5T0h71VZBa\nhKQAZqoqYc6gKgVVmA1jTLaUPoqiLBjtdDpreuoBAPKz2WZRm4Wn/b9LeAoA22PbomwFIWk9IakJ\nZwAAIABJREFU2RueL33pS7Vr1y696lWv0h/+4R9K0mFJl0j6miTZfqQSISlKok4BVJUH0FV9XVVX\nl+/eLAwGo57nKQgCtdttglEAKJmthKfGGC0uLlJ5CgA5ICStt71798rzPO3cuVNXXHGFJK17MBCS\nAgXB4BhFVMXjctY3XQhG66eK3xsAoxsMT5MkUa/X09zcnIwxSpJEaZoqjmM2iwKAGaAnaT0lSSLP\n8/SKV7xC99xzj170ohfpjDPO0CMf+cimpNAMmRQSkgIAMGHGGMVxnPUZdV1XzWaTYBQAamyjytP+\nzaLskn3C07WqvOIK1cKxWixUktaT53kyxugf/uEfdN111+myyy7Tu971Lkn6uKSPO47zT8aYpf7H\nEJKiFFhuXw1V/hyr/NowmmHBaBAEmp+fX7N7MgAA1rDNoiTCU8xGleceqKZxjlm7MSrqxx4rT3zi\nE/XOd75Tb33rW9VsNv+PpA9L+h+SvuE4jmOrSjlKgAJhgAKUC8EoAGAz495EHTU8DcNQaXpkzwnX\ndeV5Hv1OAaAPlaT1du+99+rb3/62Pv/5z+tTn/qUJJ0i6SWSbpSk/mX3hKTIFYM2oNiokF3L9pOz\nwagkNZvN3IJRPiMAKL5JjnmHhafDNouyladsFgWg7uhJWk+2J+lzn/tceZ6nl7zkJXrzm9+sdrv9\nzPUeQ0iKUiAEAJCnYcFoEATqdrvyPI+JJgAgVxv1OyU8BVB3NixDvdhr4jOe8Qydd955ajabmz6G\nkBQokKqHwY7jZMvBqqbqn10VjdLPyO5ITDAKACgjwlNg9pgTTNd2WpigXux874tf/KJ+53d+R49/\n/OM3nQMSkgIAamWUYNRWjBpj5Ps+weiM1OlmA8cSgDxtFp4mSaI0TRXHMZtFAWPiuzE9vLcYhT1O\nTjnlFP3FX/yFzjzzTD384Q/XU5/61FMlOZK+boyJ+h9DSIpSqNPEGcDs9QejaZoqCAK12201Gg0G\nYQCA2tgoPO3fLMpWnRKeAgCK7sc//rEk6fLLL1ev15OkP5e0U9LTJR3o/11CUqBAqh4GV/31Vdko\nS9PLxu4ITDAKAMDGhm0WJc0+PGUcOXlVHOMBgPRgJekHP/jBbKXEAzcBn77eYwhJURoMilB0VTxG\nqzZotsGoJB08eJBgFACAbRg1PLU3JKUjG2l4njd2v1Ou1wCArbj55pv19re/Xd/85jf1b//2b+p0\nOo+W9ExJ//fgcnt3+P8EUCwMhlB0HKPFlaapVlZWdPDgQR04cEBxHEuSdu7cqU6nI9/3+fwAAJgg\nG576vq9ms6l2u61Op6N2u60gCOQ4TrY54uLiohYXF7W8vKxer6coipQkSSVvPgPYPqqfsVV/8Ad/\noOc973nZzTpjzPcl/ZGGFI4SkiJXnNxWYzk6MBlpmqrX660KRlutlhYWFtTtdiVV5/xjXwfnDgBA\nkdlep41GQ0EQqNVqZeHp3NxcdtNyo/DULuUHiowQr3g4b9TboUOH9IxnPENBEKjZbNofR5Liwd9l\nuT2AmSEExjTZXmhhGCqOYzUaDbVaraGVovZYZAALAOuz12zOlZimjTaL6l+2nyRJVmG6uLi4bs9T\nABjEuaHejj32WN1www1aWlrSoUOHtGvXrqdKuk9SMvi7hKQoBcI1IF9FDRSNMdnmSzYYDYJA3W63\nkM8X9cE1CwC2Z1h4GsexwjBUq9VSkiRK01RxHE91sygA5cc5oN4uvvhi/f7v/77279+vZz7zmZL0\nvyU91xiTDv4uISlQMEysy6nKQX7RBhXGGEVRpF6vtyoY7XQ6a6pQAABAtdjgdFjlaf9mUf3L8wlP\n11fV8Suqi2MWW+W6rq6++mr9+Mc/VpIkOu644/Y5jrNj2O8SkqI06nAyZKAGDGeD0TAMFUWRPM9T\ns9kkGEUhcS4HgNmzm0V5nrfq54Snm6vb60X5ccxiVL1eT0972tN0yy236Nhjj5UkOY4zJ+nrkk4c\n/H1CUpQCJ8FqqHK1JSZvWDAaBIHa7TbBaEVxjlgf7wtQXkVtWVMXo4anYRhmOx+7rivP8+h3irFw\nzQbyZ4zRTTfdpO9+97uSpC9/+cuK41hBEEjS0zVk0yaJkBQAUCDGmKzfWBiGBKMAAGAqhoWnwzaL\nspWn/cv8CU+xGY6L4rDfX9RLmqb6xje+ocsvv1xLS0t697vfnZ3PJb1A0vnDHkdIikIY5Q57He7I\nUUVVXvb4rWq1yDSPy8Fg1HVdBUGg+fn5NVUfk8J3DQCA8pn2OGvYZlH2/5fwFCinKIrk+37eTwMz\n5nmezj77bJ199tm69tprdcopp/T/8+8665ykCUmRq1EHDwwyqoNgqnym8f3LIxitMhv6cq6sJkJ9\nAMgX4SlQDHY8tJXvESFpfdlz9DHHHKN3vOMduv/++yVJb33rW98m6X5JFw0+hpAUwMwwKKw3Y4yS\nJMmCUcdxCEYBAEBpbRaeJkmiNE0VxzGbRQE5ISStL8dxdM899+i3fuu39LSnPU379u2zQfudkg4P\newwhKXI3yoCgLlU0dXmdqI/BYFSSgiBQt9tVo8ElCAAAVM9G4Wn/ZlG26jSv8JR5B+ogjmNC0hpb\nXl7WUUcdpYsvvjj72R//8R+/e73fZ4YKABPCkucH9S+llx4MRj3P4/0BAAC1NGyzKCn/8JSx2WQx\nHygWKknrLQgCHXPMMbr22mu1b98+ua6rhYWFjqTQGBMN/j4hKYCZoVK2vEb53PorRo0xBKMAAAAj\nGDU8DcPQ7sws13XleR79TlEr48wl4zhmBVsN2ZsVSZLoX//1X3XVVVfpZ3/2Z+159jpJN0p6tuM4\nnjEmsY/jSEEp1CVcq8vrRLlsNODuD0bTNFUQBGq322o0GoUeqPNdAwAARTcsPGWzKNTdVo/nKIoI\nSWvIHifHHHOMbrrpJjmOoyiKlCSJHvKQh/yKJCNJ/QGpREgKANiisgajAAAAZbfZZlFbCU+BOojj\nWEEQ5P00MGOHDx/WT37yEz3qUY/S9ddfr06no0ajYVsvdCQtDnscISkATFBVqxPTNNXKyorCMFSS\nJASjBUNlLAAA9TZueCpJvV6PylNUFj1J6+nWW2/VRz/6Ub361a/WM57xDD384Q/P9suQ9P9KulbS\nc1luj1KqUwBQ5ddZ9c+xagNK2/sqSRIdPnxYQRCo1WrJ9/3KvVYUgz2u2PAAADAM14et2yg8TdNU\ny8vLko5U281ys6gq4zgtFpbb19NJJ52kk046SZL005/+dPCf9/T95znHceaNMbdLhKQogKoHZ1vB\ne4G82WDUhqO+78t1XbXbbZapAAAAVIQNPR3HUbPZzH4+uFmUrTolPEURjBNAU0laX/Z4sRve2WPH\ndV1HkmOMSSX9kqRflfRXEiEpANSeHQCHYag4juX7/qqK0YMHDzL4BbaIG14AgDIatlmURHiK8qIn\naX31haKrfm6MMc6DJyhfUmz/jZAUpVCnCssqv846fY5FZ4zJKkbjOFaj0VAQBOp2u7UY0HIsYprq\n8B0CMDqW3qIKRg1P7cae0pFgwvM8+p0iV1SSYhO+pJ79L4SkQIEwaCi3ogdvdQ9GAQAAMFnDwtPN\nNotar/IUmAZCUqzDTtx9SdmOToSkKBXuxANbY4zJltLbpuVBEKjT6axZdgAAAABs10abRRGeYjvG\nKUghJK235eVlRVGk+fn57GeO47g6koeGkjxJK/bfCEmRu1Gq77g4AqMbDEY9z1MQBGq322MHo0Wu\nkAUAAEDx1SU8pbBnurb63to9F1AvaZrKdV198pOf1Ne+9jW9973vVZIktur9LEknS3q1pH82xiT2\ncYSkQIEUfbn2pDBwmLxpBKMWn1Xx1eXcAQAAqmej8LS/32kcx2wWhS2jkrSelpeXdeDAAV1//fW6\n5557dPfdd+vuu+/W7t27JelxOrLMXpJWnTQISVEIhGb1UPXPeNZBlTFGcRxnfUZd11Wz2ZxIMFoH\nhIoAAKDOij4HG3WzKFt1SniKYexeDKiXe+65R295y1t05ZVXqtFo6LTTTlMcx0qSRJL2SbrogV9N\n+h/HkYLcjXrBsgEUFzjU2bBgNAgCzc/PrxlAYn2cRwAAKB/mApAIT7E1VJLW03HHHaf3ve99uuCC\nC3T33XfrV3/1V/v/+QX2P5iByhlKjYACYckshrHB6OLiovbv36+lpSW5rqv5+Xnt3LlTc3NzBKSo\nFM6DAABgq2x46vu+ms2m5ubm1Ol01Ol01Gw25XmejDEKw1BLS0taXFzU0tKSer2eoihSkiSMQQpu\nnBslcRwrCIIpPSMUVZqmkqT77rtP+/fvlyR97Wtf07Oe9Sw5jvNXjuPsGvY4QlKUChet8iMIHo0N\nRpeWlnTgwAEdPnw412CUzwyzUpeKjrq8TgAA8jYYnrbbbXU6HbXbbQVBIMdxlCSJer2eFhcXtbi4\nqOXl5bHDUyqei4VK0nqy39nPfvaz+o//+A9J0kc/+lGdfPLJktSU9ApJchxn1aSa5fYoDS40KLrt\nBsDGGCVJki2ll6QgCNTtduV5Xm7fAb57AFBP3CADUFUbbRbVv2w/SZJs2b79/WHL9lFc7G5fb57n\nqdls6stf/rKCINBrX/tavf71r79LUnvY7xOSAgVClWU92TvXRQpGAQCQuFEGoF4mEZ4ynysWKknr\nyY5f9u3bp3/8x3/UJz7xCT3vec+zrRceKum+YY8jJEVpECCiSvorRtM0JRgFAADATDG3Gt1G4Wn/\nZlF9u2crSRI2i5qwcVoZEJLWk71h8fznP19PeMIT9NOf/lS/9Eu/ZAuT/lnSXZJkjGF3ewD5qXPY\nPSwYbbfbajQaDJZmrGrHYdVeDwAAmA3GoNtj+5327xXQ6/UkSY1GIwtPbdWpMWbdJft8FtPBcvv6\nsnOkKIr09a9/Xe12Wz//8z8vSQce+LMGISlQMAQd1ZKmabaUvszBKMclAADj4RoK1IsNQgfDU/tv\n/ZWnhKfTRyVpPaVpKtd1dcUVV+iqq67Sl7/8ZT30oQ+1Ien/lPRVSR9wHMfrryYlJEXuRj3p16FS\nigtgudljNE3TrGI0SRL5vl/KYNQq43MGAKBIuJYC9bLed35Y5am0Njy1BRaSssCVzaLGQyVpPdmQ\n9DOf+Yxe9rKX6YQTTtDKyor951DS0C8RISmAmapq2G0buMdxrKWlJfm+r1arJd/3GcQANVTF8xwA\n5M1W2wFVMyw83cpmUYSn66OStJ7sd2FhYUGHDh3SnXfeqYc+9KH2n7uSeg/851WDdkJS5I4TOcrK\nLpHp9XpKkkSO42RVoxzXQH3x/QcAANu10WZRdQ1Px9m4KY5jNRpEX3VjvzdnnXWWPvnJT+pzn/tc\n9t8lrUj6ygO/SkiKcqpqBWK/OrzGsrPBaBiG2QXXVowuLi6Wdkk9UCScBwEAAIYjPN0altvXk+M4\nStNUp5xyivbu3avHPe5xuuWWW3TmmWfqiiuu+GNjzIokmYGJByEpAGzCGJP1GLXBaBAE6na7qwYW\nVQ65q/a6qvxZlV0dBuvWqNUQdpAHAMAkjVOVh+LaKDzt73cax3GtNotiuX19ua6r22+/XVEU6dnP\nfraCILDfD89xHGcwIJUISQHMWFnCKWNMtpS+PxjtdDq164VVpUFSlZXhewUAAFB1RQufR90sylad\nVi08JSStJzuHP//88/WJT3xCO3fu1MrKit286ZCkMyR9yXEc1xiTVSMQkqI0yhKubUcdXmOR2WA0\nDENFUSTP82objKJcyjhgBQAAQH7KGJ6Os3kbIWk9NRoNpWmqyy+/fNXPv//97+v444+/SNKPHvgR\ny+0BwFovGG232wSjAAAAAGpl1PA0DMOsHZDruvI8r5D9TulJWl+u66rX62XhepIkevSjHy1JT5K0\nR9Itg48hJAUwc3lXyxpjFMdx1md0UsEolcAAAAAAqmhYeFqGzaKoJK0n2/biM5/5jG6//XbNzc3J\n93398Ic/lKSHSLp/2OMISVEadQig6vIa8zAYjLquqyAIND8/v+YuKdaq+nEJAAAAYGs22iyqKOEp\nIWm9/fd//7duvvlmBUGgNE31kIc8RJJ+1xhzq8Tu9iigopTho3oIRiejquF9FV8TAABVVrQNcYBh\nOE6LFZ4SktaTPW5e+cpXrpr7O46jN73pTT9yHMeTlBKSAqg0Y4ySJMmCUcdxCEaxRt0HrgAAAIR5\nmLWNwtP+fqdxHA/dLCpNU7muu6Vjl56k9WSPlb/8y7/UTTfdpF27dsnzPEVRJEnvlRRJ2uE4zv80\nxtxlH8euJCiNqlazDVPl1zmNz9FWjC4tLenAgQM6fPiwJKnb7Wrnzp2am5ubSUBap2MUAAAAACbB\n9jv1fV/NZlNzc3PqdDrqdDpqNpvyPC8LUsMw1OLiopaWlrSysqIwDLNQ1W4k1S+O40oVy5xzzjk6\n+uij9YQnPCH72X333aczzjhDj33sY/Ubv/Eb2r9/f47PsBhsiO44jg4ePKgnPvGJOu200+x7s1PS\nNyX9q6Sl/sdRSQoUCHdyt6Z/Kb0kBUGgbrcrz/N4L1ErBPQAUFy2EgoAsDWDm0WlaSrf9+V53qrK\n0yiKtLi4qCc96Uk6/vjjtW/fPu3bt0+Pf/zjFQRBzq9isl7ykpfoVa96lc4+++zsZ29729t0xhln\n6LWvfa0uuugive1tb9Pb3va2HJ9l/my18Ze+9CVdeeWVOuqooyRJv/u7vyvHcR4u6UvGmB8PPo6Q\nFKVCCID+pfTGGILRGeG7h1kh8AUAAMBGBsNTSZqbm9N3vvMd3Xjjjbrxxht100036aqrrtJ1112n\no446SieeeKJOPPFEnXDCCdnfD2ziUyqnnnqq3aE9c+WVV+qaa66RJP3e7/2envrUp9Y+JLV839c3\nvvEN/dqv/ZqkI3mCpAVJa8uORUiKEmHiXF/9wWiapgqCQO12W41Gg2B0BniPAQAAAORts16kD33o\nQ3Xqqafq1FNPzX72zGc+U1dccYVuuOEGXX/99frWt76lyy67TDfccIN27NiRhaYnnniifvM3f1PH\nHHPMLF7KRN111106+uijJUlHH3207rrrrk0eUX12BceFF16oV77ylXrsYx+rHTt26Oqrr5ak90ka\n+iYRkgIFY8PgqgZTo4bdZQ1GCfLLg88KeSryeQwAAIyvynO5MnIcR3v27NGePXt0+umnZz83xujH\nP/6xrr/+el1//fW65ppr9LjHPa6UIWk/uzkWjjj11FP17//+77rmmmuUpqne/va362EPe9gl6/0+\nISlKhVCj2mwj7jAMlSRJaYJRqwzPEUdQmY5ZYJIEAABQTI7j6BGPeIQe8YhH6JnPfGbeT2dbjj76\naN15553as2eP7rjjDu3evTvvp1QYBw4c0Mc+9jHdeOONete73qW7775bjuM8VdK/GmOSwd+ngzhy\nN+oEkolmNaVpqpWVFR08eFAHDhxQHMdqtVpaWFhQp9OR7/t89gBKhXMWAKAMuJkHVMOzn/1sfehD\nH5IkfehDH9JznvOcnJ9Rcbzyla/Urbfeqk9+8pNaWVnRwx72MEl6t6ShO3pRSQoUTB0q3GwwaitG\nfd9Xq9UiEC2wqh+TwCwZYxTHcXa+Y1kUAIyGUA9A3b3whS/UNddco3vvvVfHHnus3vzmN+t1r3ud\nzjrrLL3//e/Xcccdp49//ON5P83C+Pa3v60Pf/jDuvrqqxUEgXzflyRH0poqUomQFCVSh/CwytI0\nVRRFiqIo6zFKMFoOfD7A9hljFEWRwjBUFEXZ9yoMQxlj5LquPM+T67rZH757AAAADxrnRknVxlOX\nX3750J9/8YtfnPEzKYejjz5aP/nJT7IirTvuuEOSIknxsN8nJAUwNcaYrMdoHMdqNBryPC/rNVo1\nBPnIC8deMRljlCSJer2ewjBcdf4Lw1DSkZ030zTN/iRJkt1MchxHnufJGCNjTPazqg32UVycVwBg\n66h4BorjvPPO0yte8QodOnRIb3jDG3TVVVdJ0v8yxqTDfp+QFCiYsocdw4LRIAjU7XblOI6WlpYY\nNKAQyvw9Q7ElyZHVOwcPHpQkNZtNzc/Py/O8ob9vK0f72VA0TVPFcSxjjJaXl6k6xcxxbAEAgDJK\nkkRJkujSSy/Vv/zLvyiKIv3Jn/yJHvGIR3xyvccQkqI0yh4eVtngMlLP89RsNtXpdNZM/PkcUQRM\n+jFpaZoqDEP1ej2l6ZEb051OR41GY6zjzVaR2mA1SRK1Wq2sOnVY1elgeErVKQAAAOoqSRK98Y1v\n1Le+9S29+MUvHukxhKQAxjIsGLXLSAeDUZQfwTZmqSzH22DlvO/7mpubk+/7uv/++8cOSDfiOI4a\njdXDN7sc34anNji1VafDwlMAAFgWjrLhmMVWOI6jJz3pSbr44ov13Oc+V81mU77va2FhYc4Yszzs\nMYSkKAxOeA8qakBAMLqxqlbJ8r3ELBX9eLM70/d6vVWV87alSB5sxeiwJfsbVZ32h6dUnQJAPXHu\nR5VVcW6G0YVhqE9/+tP653/+Z/3pn/6pgiCw+wJ8T9IxjuM4ZuAgISRF7ka9MFc1gBpUtIGKDQRs\ntZTrumo2mwSjAGql/zzoOE4pbhBRdQoUQx3GrwCO4PteLFEUyff9vJ8GctLpdHTnnXcO+6djHvjb\ndRzneGPM/2f/gZAUwBrDgtEgCDbceGRUjuNk/foAoMjSNM12pjfGZJvQDQaPZbJR1amtOKXqFJg8\nvjNAvfCdLwZCUiRJkn0f7d+u69oK0odIeqek37a/X95RPiqFi8hqedyBtJVFNhCYZDAKFFHV7vRX\n7fXkxfYZ7fV6SpJEvu+r3W5Ppb9okQxuFCU9WHU6uFy/v+p0MDwFgGmiPRdQX+OMdaMoKvXNbWzf\nsCyjb4m9Lynq/zeOFpQGy+0nzwajtmJUEsHoNlT5GK3a66raBKtqr2fWBvstNxoNtVot+b5f6/e2\nv+q0f4Jhg1MbnsZxvKbq1IanVJ0CAIBJ2sq4Io5jBUEwxWeDkvMkhf0/ICQFama9YLTb7WYTWqAf\nxwSqaLB6no3oRtdfdWqXsA1WndqWLYNVp/3hKQAAwDSx3B6boJIUqKv+MEDKLxitcrUlgOKzN4l6\nvZ4kqdlsUj0/AVSdAkD50L4AVcdye0jSyspK1k7wgRv4tiepJ2mx/3c5WlAadQnXJvk6+ytG0zSl\nYhRALaVpmp0LkyThXDhDm1WdpmlK1SkAoDIInouFSlL84Ac/0Ac/+EF1u11dcMEFuv766yXpFyX9\nH2PMLZL+qP/3CUmBihkWjNZh05GiqEOQD5SB7TPa6/UUx7F83595n9FJTpSqdG7przrt1x+c2mB7\nWNWp/cM1DQCA+hhnXEVP0nqyx8r3v/99ve51r1O329Xtt9+uCy64QHfeeack/S9JT3ccxzPGJP2P\nJSQFKsBOJnu9XuGD0SpXBBftvZ6kKn5mVXxNVTHuZ2OMyaoSbZ/RZrOpbrc78+/nJP//qnxu6ddf\ndWoNVp3aG4HDqk7tHwAAAIlK0rq788475Xme/vqv/1pnnXWWJKnb7W74GEJSFMIowVmVw7V+o77O\nweWjvu9rbm6u9rsxY/KqeDxV8TVVxTifTX8w6jiOgiDQzp07CcwqYLtVp2ma1mLsAAAA1qInab3Z\njOT666/P5hi33nqrNNCHtB9HC1Aiw4LRWS8fBVBMdQuC0jTNNqNL0zSrGGUgXA+jVp0mSSJjjJaW\nloYu15/ttdNI2i9p1wz/PwEAqK84jhkb1pAd351wwgn6lV/5FZ1//vnyPE/nnHOObr75Zkn6ywd+\nNR18LEcLSqVuIYB0JAiwffUIRgEMU5dKe2NM1lrEng+L2loEszes6jSKoqwfmQ1PoyhSkiQz73Xa\nbJ4n3/9/tLz8cSXJb07l/wOoOjbFQdFxjE4PPUmxVZ1OR+eee65OPvlkff3rX9fu3bt12mmnaefO\nnddLkhkygSIkRWnU5WLjOM6qCil796vZbCoIgtK/D1UOc6r82oC82A2YwjDMlkxV5XyI2Ri16jSK\nIqVpum5wuv3jzV4f1hQtAEAuCPRQdfQkrbfbbrtNN910k8444wyddNJJkqTvfe97WlhYeJIx5tvD\nHkNIChSErZCyS0d931cQBLlsOAIMIvzFLNkNmOzNItd11Ww21W636TOKiRi116kNTo0x8jxvW1Wn\nvd5fKwxfL2MeOumXAwAAhiAkrSd70/vrX/+6Pv7xj+uMM87Q8vKy5ubmdN1110nSBZL+L3a3R2Ft\npQKvSnc8h1VIua6b7U4PFEFVvm+DCH6Lx/aQXFpayjZgmp+fX1UBCEzTVqtO7e+PVnXqEpDWFNcb\nAMgHIWm9OY6jubk5Scr+7vV6khSu9xhCUpRGVYKawWDU87wsFHVdV0tLS3k/xaljsoC8VeV8UgWD\nG9I5jqNWq6VWq8XnhEIYp+rUdd2h4Snqi88fAGYvjmNC0hqy19xjjz1WKysruvzyy/WsZz1LN9xw\ngz73uc9J0nfWeyxr1lAYVQ7O7FL6w4cPa//+/VpZWVGj0dDOnTs1Pz+vVquVTb6qPoiu8uujJykw\nGntOPHTokA4cOKA4jtVqtbSwsJBV8VX5XIFqsFWkvu+r2Wxqbm5OnU5H7XY765mbJIl6vZ4WFxe1\nuLio5eXlrN+4DVQBANXBeX16xllRSiVpPdl5+S//8i/r1a9+tS699FI95jGP0bnnnqvTTjtNxph3\nS9LgUnuJSlIUxKgnO3uwl2HybHvq2QqpwYpRAKiTYefEZrOpTqfDORGVYitH+1F1CgD1wTm8OAhJ\n68t+D0855RR95StfyX4eRZGG9SK1CEmBCRoMAWx/0a321OMOJIqGY7LYHMdRmhZzx2xbSReGIX1G\nUVvDep1KR86tSZIM7XU6GJ6u3+sUAAAMQ0hab4uLi7rqqqv0+c9/Xr1eT57naf/+/ZL0QkkfcRzH\nNcasmkQRkgLbNKlg1Kr6BIgl6eVT9WMSk2f7jPZ6PaVpqmazqW63O/Iy+jqcIzgXQjpy13lpAAAg\nAElEQVRyHDQaq4fjdqMoG54OVp0OC08BYBxlWaEHjCuOY3U6nbyfBmYsSRJ5nqcPfehD+shHPqJX\nv/rVWlhYyDaI/dSnPvWtB351zWCckBSlUpRJpZ282GCU6ihIxTk+MRo+q8myfUZtv0Xf99Vut9Vo\nNLY0AWOyhrrbbKOoJEmGVp32h6dUnaKK7HWbYxuoJ3qSYquSJNFznvMcnXXWWat+boy58YG/CUmB\ncQ0Go5IUBIG63e6aKhAAxcYEazKMMYqiSGEYKooiNRqN7LzIewxM1rAl+7bqdHC5fn/V6WB4uhXc\nTAIAlFmSJMzVa8iOdx71qEfp05/+tL761a/qxBNPVJqmajQa2rVrV8MYEw97LEcLsIn+pfTSg8Ho\ntHZfphoRQJHZG0a2z6jrumo2m2xKB+Sgv+q0fxLYH5ymaao4jqk6BYAZoIVBsVBJWk82T7n55pt1\n6aWX6mMf+5iMMfJ9X/fcc48kvVrSOx3HWROWEpKiVGYVIPZXjBpjph6M1gkhcDnxmcGeF3u9niTR\nYmQEfG+QlzyqTgEAKBpC0nryPE/GGL3mNa/Ra17zmmG/8k5JGlZNSkgKPKA/GE3TVEEQjNVPD6ja\nHeQqvRZsjd2AKQxDJUmiIAjU6XQ4L46A9wdFs1nVqQ1P+6tO7Y3NKIqyG8Uc2wCAsrB98lE/juMo\nSRLddtttuuWWW3Tw4EG5rqskSfT85z//EcaYHw17HCEpCiGvAXcRg1EqLcuLiSOqwAYivV5PcRyr\n0Wio1WrJ932OcWBCvvENV3fc4eqpT421Y0e+z6W/6tROJG3VaRRFiuM4az00WHVqK085NwDlxJwD\nZcLGTRhVmqZyXVdf/epX9d73vldf+MIXtHfvXi0tLeknP/mJJJ0g6UeO47jGmLT/sYSkKJVJBIjD\nKqPyDkYBYDu2e240xqzqv+x5XlY1Sp9RYPIOHnS0vCytrDjasaN4IYWtGPU8T2maam5uTtLqqlM7\nnhrsddr/h3EVUHx8T1FlVJLWkw1JP/jBD+qP/uiP9OQnP1k/93M/pxe96EU677zz9Dd/8zfBeo8l\nJEUhTPviPBiM+r5PZVROqJRFEXAcHtG/AZMkNZtN+owCM/Brv5ZoaUlaWMj7mWzNZr1O+zeJouoU\nQB1Vre1W2VFJWk/2O9hsNiUdOQ4eqCDVXXfdJUm77K8OPpaQFJVV5mCU8AZFxKCvGuy5sdfrKU1T\nNZtNNqYDZiwIjvypgv5ep/2oOn0Q108AyAchab3t3btXkvT0pz9dF154ob7whS8oSRJJ+t4Dv7Im\neCEkRalsVv2VpqmiKFIYhqXtpVeW54nh7DFapc+xSq+lrowx2U0ju+yoyG1G6nKjqC6vE/U0StWp\n7Q0/rOrU/gGsqo2vAGzNOOcAltvXkx17nH/++dnP/u7v/k7XXXednvzkJ+uoo476miQN9iOVCElR\nAYOT/0ajoSAI1O12GUgVGANdYLpsn9Fer6coikpzbizycwOwPaNWnUZRpCRJall1CgCYHCpJ6+nG\nG2/Ucccdp9tvv1333Xef5ubmFASB9u7dq4MHD2r37t0tY8zKsMcSkqKUhu2+XKVNRqpcXcTEBpge\nY0xWmdXr9eS6rprNptrtdiXOjQCqadSq0yiKss0YhgWnjDEAAP0ISevpAx/4gM4991x94AMf0GWX\nXaaFhQVFUSTXdXXbbbdJ0v+Q9FV2t0ep2cHy8vKyFhcX5Xmems1mZYJRiwE+gK2yAcLBgwdljFEQ\nBGzABKDUtlp1Kh1ZXkfVKTCaKhdl5In3tVhYbl9P73jHOyRJ55xzjt7ylrcM+5WvSiy3RwnZitEw\nDBVFkSTJ933t2LGjUsEoqoNd08uhCp+TDQdsRb3ruup0OoXtMwoAk0DVKTBZfBcmj/e0OOyqU9RL\nGIYKgkAvf/nL9brXvU6nn376yI/laEHhDAajnucpCAK1220tLS2p0WgQkJZcFTc3qjo+s2IY1mqk\n1WplvZm5Uw6gjrZSdZqmqYwxVJ0CQMnYTf62guX29WSD8V/4hV/QN7/5TT3mMY/JCu0ajYa63a5j\n1qmYISRFITiOoziOs3DUdV0FQaC5ublVlQJ1GLxWocINwOTYDZjsBnX2xlF/q5EwDHN+lgBQPMOq\nTiWtCk77q07t71N1CgDVQEhaTzZP+elPf6r3vOc9uuSSS7Rz5041Gg3dcccdkvQ4STc5jrMmLCUk\nRWHYyT999ABASpJEvV4vC0CbzSbnRwCYABuA9tuo6tR13aHhKQCg2AhJ68nOl97znvfob//2b7OC\nkzRNFYah9uzZc4skDasmJSRFYYy6+zJVligyKoGxHfbC3ev1lKapgiBQt9uV53lMyGuO8wowXetV\nnRpjlCTJ0KrTwfCUqlMAKBY2bqq3Vqulu+66S/fdd59WVlb6r/PrXqwJSVEqdRh41iFkq8NrrCI+\ns+mw/UTDMMwGcnNzc/J9vxbnvCrjOwOUn+M4azb92KzqdDA8xWTQGx1lME7fTIxmnHMAGzfVkz1W\nPvWpT+kd73iHrr32Wj360Y/WbbfdpiAIJOloSbcNW27PtxcAsKmqTUryDurtBkyHDx/W/v371ev1\nFASBFhYW1O12FQRB5d5zjI9jASgWW3Xq+76azabm5ubU6XTU6XQUBIFc181apiwuLsoYo16vl226\nZwNVIE+EzqgLjvP6sdfY17/+9brqqqt0+umn65vf/KZ+9KMf6bnPfa4k9R74PZbbo/wYVAIoK9sP\np9fryXVdNZvNkVuN1EkVzvMMyIH6Wa/qdHFxUZ7nZTfINqo65dwBAMBk7NixQ57nKYoife9739OT\nn/xkfec735GkYL3HEJKiVPKu/poFXmP5Vfm1YevSNM02YDLGKAiCiW/AVKXvFAEBgCqx57TBFip2\nyX6SJEN7nfaHp/Q6BQBgdPaauWfPHi0tLenMM8/UW97yFu3evVvtdluSltZ7LCEpAEwQkxhIynrU\n9Xo9JUmiIAjUbrfVaDQ4RgAAQzeKMsasCk+HVZ0OhqcAUBdVKQjA9Nnr48knn6wbb7xRL37xi7Vn\nzx7dfffduvDCC7Vr167713ssISkKYdRBnuM4StN0ys8GwDAMTDZml1GGYagoitRoNNRqtdiACQAw\nElsx6rruqmX7/RtFJUmS9TXtrzq14SlVp0C+6PU6XVt9b5m/1NvOnTv1Z3/2Z0rTVM95znN05pln\nam5ubsPHEJICBcUFFkXCsTicMSbbnCMMQ3mel1WN0mcUADAJ/VWnvu9LWlt1anteD1ad9oenAADU\nybnnnqtzzz1Xd999t973vvfp13/917Vz507953/+Z9MY0xv2GEJSoGDqMIitUv/EYar82qrCfs/G\nvRnRH4xKUrPZnHifUQAA1kPVKQBsjnNcvR0+fFgHDx7Uvffeq4WFBe3bt0933323JK27PJmQFKVS\n9XAN5ceFuLrSNM12pk/TVEEQqNvtUqEDACiMzapO0zSl6hSSWLWGeuAYr7dLLrlEn//853X//ffr\n+c9/vi655BI96lGPkqRovccQkgIAsA5jjMIwVBiGiuNYvu9rbm6OPqMAgNLorzrt1x+c2huBw6pO\n7Z+8r3sUSgD1RrCPrXrYwx6mj3zkI3r4wx8+8mMISYECshWzVb4IMNAtn7p8ZsYYxXGsXq+nKIrk\neZ6azaa63W6hv5N1+XwAAJPRX3VqDVadJkmybtWp/TPr5wwAwChe+tKXbvkxhKQoFZbbVwMD3PKp\nw2dmlx+GYSjHcUq1AVMdPh8As8eYq36qUnUK5KXqhS5A1RGSohC2u4kKUBQE+eViJ3q2Ssb2Ge3f\nBAOzx3cIKA7GZZAmU3XKRlEAgKJjFggUEEEbMD22z6gkHTx4MKsYbTQaTN4KoC7nP441AGU3atVp\nFEVKkoSqUwDbstWCqjqMJzF5hKQojFFOeHWZPFcdnyNmzRijKIoUhqGiKMoqRefn51dVxQAAgO0Z\nteo0iiKlaUrVaU4Yi6PqoiiS7/t5Pw2UDCEpAGAkZRtMG2OUJIl6vZ7CMJTneav6jN5///1MwAAA\nmIGtVJ2maSpjjDzPWxWclm0cUgaMg1BlhKQYByEpSqcOAyQqLcurqp9dmQbRtidar9eTJDWbTSpG\nkYsqngsAYJK2WnUqSSsrK1SdorDYY6M4+lePAaPiiEGpcMEBMEz/BkxJkmQbMHmex3kDAJAbe7OE\na9Ho1qs6jaJIURTJ87w1Vaeu666pPOU9B+otSRIqSbFlhKQAZq6q1ZaYLdtntNfrKY5j+b6vVqsl\n3/eZGCF3HIMAMHmO46wJPfqX6/dXndoqVapOgfIb54YTy+0xDkJSlE5dwrW6vE5gK4wxiuM4qxr1\nPE/NZlPdbnfLk54qhfVVei0AAKxn2LXeBqD9Nup1StUpUA8st8c4OGJQKnUZwNTldVYVYdXk9Qej\njuMoCALt3LlzzaQIAABgWK9T6cFNHYdVnQ6Gp1SdAuVGJSnGQUgKABNU1cF0HpWKaZpmO9OnaZpV\njHJHGAAAjMNxnDXjCLtRlA1PB6tOh4WnVcBN/engfS2OOI4VBEHeTwMlw0wThTFqCFOXC0+VXydL\ng7EeY0y2M71ttt5ut9VoNCozKcHmOD8AAGZlvY2i/n/27j1YkrO+7/+np3u658yZPWdXQgLdkIQk\nkLwSQoBAMsg4tpBRMIpNKq7EcblsJ44rVfnFVKXKVBKq7MSVSpxKuRzKSap8Sxw7IY5xxZQTjLEB\n2caxJUx0w0JCgISE7iDtrvZc+vL08/vj8PT2mTNzztynu+f9qtoCSbtne2Z6+vLp7/P9HlV1Wg5P\n61p1WsdtrgPe19mz1o79vlJJikkQkqJWVuWEsyqvE5DODWBKkqToHRRFkcIw5LsAAACWYtKq0/7w\nFMBy0JMUk2CPAYAZowruaO4Gwy2nb7VaiqJI3W6XPqMrjhtKAEBVHVZ16ipO8zxXlmWNqzoF6oZK\nUkyCkBS1wjLtZmjy59jk1zaL12WMKZbTS1IYhtrY2DgwWGERmvxZAQCAxRk0KMpVnfYv16fqFFgM\nepJiEoSkqAwCi3N4L1A101y453leTKY3xigMQ/V6Pfm+zw3BjHDMAACgWspVp+Ulvy44deHpoKpT\nF55SdQpMjkpSTIKQFAAwc67PaBzHyrJM7XZbnU5H7Xabi30AADC2SQa3VFG56tQFOOWqU7dcP0mS\nA1Wn5fAU1eMeWPP5zB6Dm7AohKSopaZcJAFNYq0tLuqTJJHv+4qiSOvr6/QZBQAAGOKoXqfuV5Ik\nA6tO3a9x7o+4n0LTZVnG4CaMjT0GlXLUyXpVTuRNXzrreZ7yPF/2ZsxFk1/bMOUBTJ7nLbXPKAAA\nQFMc1eu0PCSKqlNgP7eaDRgHISkqgxM4UG3l4N5VM8RxrDzPFUURfUaBOWrygzMAwOhmVXUKNB3L\n7TEJQlLUjquyJIgBFsd97+I4VhzHMsao3W6r2+0qCILafh8JnlAHdf1+AWBJMxZnlKpTY0zR69Tt\nl/0hKlBF9CTFohCSAhVFeIMqcAOYXDVCu91WFEUKw7D2N311335UH8dxAMAyHVZ1GsdxEaKmaSpj\nzEx6na4yHopUCyEpJkFIClRQ00+uTe652oTXZq3d12fUXSCHYahut7vszcMKqPt3CACAKnNhqLVW\nURRJGlx1mqap8jwfGpw2/Z4F9ZZlmdbW1pa9GagZQlLUThNCKKCK3BKsOI4lad8Apu3tbS6EK6xJ\nx8Wm7GdNeR0AgNUwaq9TV3UqSb7vU3WKyqKSFJMgJAUqqimBB6rNNfZPkkTGGIVhqPX19YF9Rtkn\nAQAAmmHUpeGj9jql6hRVw3R7TIKQFKigJlWFDdL011d1rvdUHMfKskxBEKjT6ajdbg+9gOUzAwAA\ny8R1SHWMU3Wa57mstVSdYioMbsKiEJKidghrUGVV3T+ttcqyrKga9X2/qBpd5UmmVfysAKAqOEai\nagjVqm1Q1amkfcFpuerU/X6qTjEPhKSYBCEpKoOT4X7cmGAWygOYPM/b12d01XHMAYCjcawEMC0X\ngJYdVnXaarUGhqdVx3T7amG5PSZBSIpaanqAyMkV03B9RuM4Vp7niqJIvV5Pvu+zbwEAAGDpJqk6\n7Q9PqTrFYQhJMQlCUlTGqCc4ToT1V9Ul6XVmrS2W0rsLgm63O3AA0zR/BwAAADAvq1J1ivFM2pM0\nCIi8MB72GACYsUWFia7PaBzHxUVAGIbq9XozvzjkYrMeWOYFAACaZljVqbVWxhiqTjEQlaSYBCEp\naqnpFW1UWtbXvC++3MWgW07farUURZG63e5KD2BadVz0AwCAcbgqzDrzPO9ApaC1dl942l91Oig8\nRTMxuAmTICRF7XAiwypywWiSJLLWMoBpRngYUU2r8rmsyusEAGBRXMXosCX7xpiBVafl8HTSqlNW\n9FQLISkmQUgKYOGolB2NG8CUJImMMQrDcOZ9RlcZ72E18bkAaBJCE6AaBi3Zd1Wn/cv1y1Wn/eEp\nlmOSe0eW22MShKSopaYHbISIq8taqzRNFcexsixTEATqdDpqt9tcmAENwvcZAIDlKledlpftl4PT\nPM+VZdmBqlMXntLrdHEmGdxESIpxEZKidjgJocomCbjdACZXNer7vsIw1Pr6emV6RRHcAwCAZWpC\nD03UwyhVp+7avVx1Wv593LMuHyEpJkFIisrgRLI6CNz2GGMUx7GSJJEkRVFEn1EAAACgYo6qOi1X\nnG5tbVF1WgEst8ckCElRO6sSsK3Ca1xFrs9oHMfK81xhGKrX6xUXTgCag+M4AKCqOEfNxqCq006n\ncyA87a867Q9PMXtUkmIShKSoFE4Qe3gfmsVaWyyld08019bW6DNaAU26QXAPkNinAADAKLhmmD1X\nLeoqScvKwakrnBjU69T94vM5Z5J2G4SkmAQhKSqFG3zUnQuqXJ/ROI6VpqmCICiqRuu6jzcpUJS4\nMcB8sX8BAICyo3qdun6nw6pOy71PcTRCUkyCkBS1w3L7+mvqZ2itLaZgnjp1Sq1WS1EUqdvt1v6C\nhsAHAAAAmC2qTufHGLOvfywwCvYYoII4ydWLe+LrLl4kMYAJAAAAwERmUXW66oOiqCTFJAhJAWAC\neZ4rTVPFcSxjjMIwVLfbled5Onv2LAEpAAAAgJkZteo0TVMZYxpVdTrpKsQ6vlYsFyEpaqepS7VR\nfdZapWmqJEmKPqOdTmffAKY8z9k/gSnxHcKssC8BABZlWfM1Rq06TdNUeZ7Xtuq06tuHZiAkRWVw\n0Dun6UFwnV6fG8DkltP7vl9Ujda9z+i46vKZjaOJr6nuOBcAAAZhwOtscQ3UbONWnUqS7/uNqDoF\npkFICgADGGMUx7GSJJEkRVG00n1Gm3iB1MTXBOAgvusAMBjHx9UzbtWp+/11qzoFJkVIitrxPK8Y\njgPMkpscGcex8jxXGIbq9XryfZ8LAVRenSq0AWBVcFwGUHXjVJ261mKtVmtgeArUHSEpUEGrEnZU\nYdmUtbZYSp9lmdrtttbW1vb1GZ3kZwIAAEhU6wGop0FVp5L2BaeLqjqtwn0jVgMhKYCFW/YJzvUZ\njeNYaZrK931FUaRerzf1ti37tQEAAABYvFUJ8lwAWkbVKZqCkBS1sypVlpg9N4ApjmO1Wq2VHcA0\nKb53wHJw3gMAAFU2rOrUWitjzMCq0/7wdNa9TgliMQlCUqCCuCGenTzPiwFM1lqFYahjx44pCDj8\njaOpFxl8zwAAAID58DzvwH2XGxTlwtP+qtNB4ekkuM7HJEgJUDmrskxh1bkgeB6fteszGsexjDFF\nxWgQBOxbKPAwAgAArCruubAshw2KGlZ1aq1VmqZFkDrrqlPAISRFZYx6kCPYwCDuxJkkidI0VRAE\n6nQ6Uw1gmoT7u7jwBHAY17OLYwWqjOstVAn7I9Bsh1Wdbm9vS9LAqtPt7W09/PDDuv7663X8+PF9\nP6/JrrjiCm1sbMj3fbXbbd17773L3qRGICQFKoyb58O5p41uOb3v+/QZBRqgKTfC/a+jv8pdkpIk\nGdiXi2MYABzEdTGwWlzFqOd5CsOwuD5yg6KMMXr66af1oQ99SI888ojOO+88nTx5UidPnlSe5/rS\nl76kq6666kCv1CbwPE933323zjvvvGVvSqMQkqJSRr3wacoN9DBcAB7OGFMEDZIURVHxFA1YVU2p\nsm/K8a9cVZ5lmeI43lfl7nme0jSV7/sH+nIZY4rgtByY8uAMAIDqctWNmL/yoKgbbrhBd999t7Is\n0+OPP66HHnpIDz30kJ588km95z3v0fPPP6+TJ0/qxhtv1Bvf+Mbi14kTJ5b9MqbWhGv/qiEkRe1w\ng9gM4wY6eZ4rSRIlSVL0Ge31evJ9n31iAZoSwAGL4lqA7O7uStp7mFOucs+yTNLgvlxuaZmrkHC/\nd2tra2DFKcdAzBP7FwCgDoIg0DXXXKNrrrlG73vf+3TffffpU5/6lM6cOaOHHnpIDz74oB588EF9\n5CMf0UMPPaQTJ07ojW98o2688UZ98IMf1MbGxrJfwlg8z9Ptt98u3/f1Ez/xE/rxH//xZW9SIxCS\nAqgsFzLEcawsy9Rut5fSZ3Rc8xxKhdki+MUslY9Zrmp0koc55eA0CAJZa7W1taX19fV9Aw2SJNnX\nk6scoHL8AQAATTHuvVWapmq325KkjY0NveMd79A73vGO4r/nea4nnnhCDzzwgB544AF1Op2Zb/O8\n/dmf/Zkuuugivfjii3r3u9+ta6+9VrfddtuyN6v2CElRS6sQbKxq0OaWprqqUd/3FUWRer3eyr0X\nmC/2J8yKW05fPma54QP9AwimMWyggRsC5apO3STY/opTlgACAIBV4B5WD9NqtfS6171Or3vd6/T9\n3//9C9yy2bnoooskSRdccIG+//u/X/feey8h6QwQkqJ2CDaaoX/5djkYdY25Nzc3uakHUEmuBUgc\nx7LWKgzDfb2R3RL5eSv35HIVE+Xg1G2nC04HVZxyXgWA1bOKxRhYHVmWKQzDZW/G3Gxvb8sYo2PH\njmlra0uf/OQn9dM//dPL3qxGICQFsDR5nmtnZ6e4gXcVo7OsvAKAWRnUAqTb7SoIgkrdaJaDU6e/\nz2mapsrzXNbagRWnVXo9AADUAcFzdZSX2zfR888/X1TAZlmmv/t3/67uuOOOJW9VM5BEoHZWZYBM\nU1+ntbYYvnT27FmFYVjJkGEaTfzsmviagFEZYxTHseI4VqvVUhRFWl9fn7rSfZHHvP4+p0654nRQ\nn9NygNqUYzSwSIQmADCdSe5BjlpuX3dXXnml7r///mVvRiM1d68BUBmu+ipJkuKE5Xmeer1eo5/w\nAYtGkD077oFOHMcyxiiKIh07dqxxF9yDepWWK07LVaf9fU7HHUgFAAAwqUkHNwHjaNaVPmqParXm\nsNYW1VdJkhTVV91uV61WS2fOnFn2JgKNQlg1PTc4rjydvtPpqN1ur9T7O2y5/mF9TvsrTlfp/QKw\nGFTlAhiVMYaQFBMhJEXtrEqQWtfX6ZZrxnEsSYqiaN8wE6Aq6vodw+yVj1tucJx7oIM9h/U5NcYo\nz/OhfU5dxSnhBgAAWAQqSTEpQlIAU3NVRa7XaBiG6vV6K70Uk/ANmNwivj/9y+k5bo2v3OfUKQ+I\nyvNcWZbR5xQAKobr1Pngfa0OQlJMipAUwEQGTXlexWWpgzTx9VN1iUWZ5/envw2I7/uKokhhGDby\ne7sMg4JTSfsqTst9Tl1YWg5P+SwAYDE43s4e7+nsTdJqo+mDmzA/7DWolFGCmFUKa6r2Ol2/Plc1\n6gKGSaY8r9LnCGC5XLV7HMey1tIGZAk8zztws1KuODXGKMuyoX1OaX0AAABGlWWZwjBc9maghghJ\ngYqq0lPIcuWV69dHwACgygZVu3e7XQVBUKnj6yor9zl1S+IG9Tk1xhTBKX1OAQDAUVhuj0kRkqJy\nRi2nZ8LlfJUrr/I8VxRF6vV6LFsAUGnuoU4cx2q1WhNXu2M5Julz2l9xyrUBAACrjZAUkyLtQO2s\n0s3Popej9w8ymWflVZOX2zf5tTXp4UTTPqemvZ5xWGuLandjTGWW0x/1eazq5zWuUfuc9g+IarVa\nyvN8SVsNAABmYdKepISkmAQhKSqlKeHLLCzqvXBLUpMkKRpcM8gE/dgXUDWuR3Icx8Wxi+Fxq2WU\nPqfGGFlrtbW1daDilOpiAMAsNamYoO5cqyVgXISkwArqn/DslqR2u11uGgFUmqsYjONYnudV9tjF\nTdJy9Pc5TZJEeZ6r3W4X4an7d+U+py5Apc8pUF0EULPDe4mmo5IUkyIkRS25ZaWc3MdTDhckMYAJ\nQC30twIJw1C9Xq8Y3gMcphycOuU+p8YYpWmqPM9lrR1Yccp+BgBAfRCSYlKEpEBFzaq/oKuacb36\nwjDU+vr60ic8N7l/YpNfG7Ao/RXvvu/TCgQzU+5zWl6y76pNh/U5LQeo7IcAAFQTISkmRUgKNJDr\nMxrHsbIso1cfgNpwAdWZM2dkra3MECashkG9SssVp+WqU1ehWg5QOceiHyufAGA6kxxH3SBPYFyE\npKglKvUOckNMXNWoq7paX1+vXK8+1FMT21xwHKmG8oOdNE0lSd1ud+kV74A0fLl+ueq0v89pf8Up\n+zEANF/TrpPrLE1ThWG47M1ADRGSAhU1ahBcXo7qeR59RoERcRG7fO74Fcdx8WCn2+3qzJkzLJFC\npR3W59QYozzPh/Y5dRWnHIMAAJgPlttjUoSkqK1VrgBzVStxHCvPc0VRVLshJk2uBm7ya0N11WW/\nG3T8Kj/YyfN8yVsITKbc59QpD4jK87xY8UGfUwAA5ifLMkJSTISQFJUy6s3BKt5EuOnOSZIUB32W\nowKoA9cOxC2nD4JAa2tr9ElG4w0KTqXhfU5dWFoOT/mOAJg1loWjTibZX6kkxaQISYEKc8v1ysFC\nGIbq9Xpc2ACoPDcdPI5jeZ5XLKenT/J4ON43z1F9To0xyrJsaJ9TvkMAAAxHJVeUwPcAACAASURB\nVCkmRUiKShnnRrAOy0on4fqZZVlWVJc0NVho6mfYVHVZzo3lclXvcRzLGFM82AkCLjmmReVPs5WD\nU3djN6jPqTGmCE77K05nvX+wz6Eq3PUH+yOqimvkaqGSFJPijgW11MQLJFdx5XqVuaqr9fX1ZW/a\nXBC4oQrYB2fDhThuiFwQBIqiSGEYNvJ4DSzKKH1OywOiBlWcTvsd5DsMAKPjmFkNhKSYFCEpsERu\ngEmSJEXFleszurOzs+zNw4QIgOuBi9jp5XleBKPWWkVRpM3NzcZVvQNVclifU1dx6h68lgdE0ecU\nALAqWG6PSRGSopbqHEJZa4s+o1mWKQgCdTqdAwNM6vwaATRX/zGMIXJANXied6CtxWF9TvsrTnm4\nAQCoIgY3YZEISYEFcJOdXdWo7/sKw1Dr6+sre1PieZ7yPF/2ZgAYkTuGxXEs3/cVRdHchsg15QFR\nU14H6mtYn1MXnLoVLeUBUeWKU/ZhAEAdEZJiUoSkwByVe/RJUhRF2tjY2DfNFqgLqpurbR6fjwtQ\n4jhWnucLOYZRjQrMVzk4dcp9Tt3QSNfn1IWps+xzCmC5GMqGpjPGMDQUE2GvQS1VOazpDxXcZGff\n98e6GKHSsr6qvH8CR3GV73EcF0/h19bWDrQEAdAc5T6n5ZvKnZ2dIhQd1Oe0vGSf4wOAVUbwXC1U\nkmJShKSolLqeWKy1xVJ616OPUAGoPsLsc8qV757nKYoidbvdlW0JMi0elqAJXHBavtEsV5yWq077\n+5yO+3C4qTgOAMB06EmKRSIkBSbUX20VBEFRNcpNwdEIELBsfE/PPeCJ41jGmOIYxvKk+WP/Q10N\nW65/WJ/T/orTVdv/V+31AsCyEZJiUtwFoZaWFbBZa4vlZnEcq9Vqza3aihARwDz0D5ILgkCdTofK\ndwATO6zPqTFGeZ7v63M6qOKU4w8Ow1JmAONwqzuBcRGSAiNwwajrxRWGIQOYMFRTA+6mvq5Vkee5\n4jhWHMeS9gbJbW5uspwewFyU+5w65QFReZ4XD2zocwoAmCUqSTEpQlJgCFf1UF6G2u12FQQBF+0z\nQOAGzJ+1tjiOZVmmMAy1vr7OcQzAUgwKTqXhfU5dWFoOTzl2Aagiqp2rhZAUkyIkRS3NK2BzgUKS\nJEWf0WUtQyVEBDAud8xw/ZKTJJHv+4qiiH7JACrrqD6nxhhlWTa0zykV8cB4CPRQJ261wThYbo9J\nEZJi5fX35/N9v6ga5aIbaLamPYjIskynT5+mLQiA2isHp+5Gd1CfU2NMEZz2V5wSAgHAaqKSFJMi\nJMXKMsYUlVbSXn8+AgXMgud5yvN82ZsxF00KFZtw8+we8pSrRmkLAqCpRulzWh4QNajilGMjAKwG\njveYBCEpKmXUA9mkS9HzPC8m0+d5rjAM1ev1ismqVdOkQKof7QTqp4rfkVVVfsjjeZ6iKCqCg6Y8\nNWcpIIBRHNbn1FWcugGc5QFR9DkFgObiPhOTIiRF41lri6X0rjfJ2traUvqMjqPK2wZg8dyxrDxM\nrtfrKQj2TuXb29tL3sLZ4NgHYBY8zyuOj85hfU7LFadVfXgOoLoI5eaHB+dYJEJS1NZhJ6LyEtQ0\nTRlcAqCW+nsmL3OYHADU3bA+py44dcv1d3d36XMKYGwcH6qDzwKTIiRFLQ076LkwIY5jtVotBjAB\nqKU8zxXHseI4lrTXM3lzc5NjGQDMWDk4dcp9To0x+/qc9vc4Zbn+YlBJNlu8nwAwGCEpas+FCa7X\nVBiGOnbs2IElVnXT9J6dTX59TX5tTVOlz8laqzRNFcexsixTGIZaX19nCBMALFi5z2n5erJccTqo\nz2k5QOW4DQBA/dQ7RcLKcktQz5w5U/TmY6IzMF9NC3+rcqzon04/aWuQpn0+TcDnATSLC0DLyhWn\n5apT93vd/6dyDwAmw/UUFomQFLXhqqxcbz7P87S+vk5vPgC1k+d50RrEVcBvbGzsW+4JAKi+Ycv1\nyxWnxhhtbW0V1an9FadcxwLA4SYpHgAmQUiKSnJP2621Msbsq7IKw1BBEBTLUZuq6VVhnLiwasoP\netI0VbvdpgIeABqoHJwaY+T7voIgKK5r3YCoQX1Ofd8nOAVqiGpxoBkISVEp7sTiliuVh5aUq6xc\nDyjUW1M/w6YH3BiPe9DjBspFUcRAuRXAjRKAsnKfU6c8ICrP82IAKX1OAQBYDkJSVE4cx9rd3VUY\nhur1esUTdQCoC2ttsZzeGKMoihoxUA4AMDuDglPp6D6n5fCUa2QAAGaHuzVUThRFiqJo5ausqEZE\n1TR1n5zV8ig3UC6OY6VpqiAI1Ol06Js8IZatAVhVo/Q5zbJMeZ4P7HO66tfQOBrnWNQJ+ysWiZAU\nlTPKAbCpYc0q4TPEss3qYivP82I5ved5CsOQ5fRT4kIYqAbO09VRDk7b7bakc8v1y31OjTFFcNpf\nccqxFcAq4NyFaRCSAsCMEQA3n1tOnyRJMUSuCu1B2O+ACslzhf/u30lJouSDH5S+FWzVDcFadY3S\n57Q8IGpQxWldPl8qyVB17KPVYYyhxRUmxp4DVBRBG1A9bjl9kiTyfV9RFKnX61XiorgK2wCgJE3V\n+spXpCyTdnZqG5KiXg7rc+oqTo0xBwZE0ecUQFO4tlfAJNhzUEsEiAAWJc/zYgiTtVZRFGljY2Nf\nrzhgEahSqZkoUvwv/sVeSLqxseytwYrzPO9AaHBYn9NyxemyV0kAWG3jXv8QkmIa7DkAloKgu35W\n6TOz1ipNU8VxrCzL1G631e12FQQBN4pYCva7erKvec2yNwEYalifUxecuuX6u7u79DkFUBtpmioM\nw2VvBmqKkBSoOCqH6meVwsSmMcYUQ5harZaiKNL6+jpDmAAAK6EcnDrlPqfGmH19Tvt7nLJcH8Cy\nuQIHYBKEpKilVQihuMAE5s/zPOV5XvQaNcawnB4AgJJyn9PyEtZyxemgPqflAJXr2mpxnxPQRCy3\nxzTYc1A5qxCA4hwqZbEM1lplWSZrrU6fPq12u61Op6N2u83+CADACFwAWlauOC1XnfZXm9LnFE3D\nPc18TJILpGlKJSkmRkgKYCm4iMAyuEqXOI6LfXBjY4OnzQCAuVi14GTYcv1y1WmSJMWAqEEVp6v0\nfgEYzTjHhSzL6EmKiXFXiFpalWpT9zq5WEQV1PV7Z60tglFjjMIwVK/Xk+/7OnXqVGOWm9X18wEA\nNNthfU6NMcWAqEF9Tqk4BTAuKkkxDUJSAJgxwqrlczdecRwrSRL5vq8oihSGITdbNcF3CACaq9zn\n1CkPiHL9wl2fU3fuTtOUPqcADkVIimkQkqJyCJhWB5WymDW3jC+OY1lrGcJUU005JnAuA4DRDQpO\npXMrQg7rc+qqT5ty/gAwOQY3YRrsOailVQlSV+V1AtOw1ipNU8VxrCzL1G631e12FQTBkTdLfMcw\nL9yoA8BsuODUWqtOpyNpf59TY4yyLBva57QpbXVmiWuf2bPWsq/NwSQFNfQkxTQISVFJVBcC1VSl\ni2q3nD6OY/m+X/Qa5dgBAECzlfucumW1g/qcGmOK4LS/4nTVrxdW/fWjubIso5IUE2PPQeWMc8Im\nTEUVNbU6sQrftfJy+jzPWU4PAAAkjdbntDwgalDFaRWudQBMh56kmAYhKWppVS5gmhq2OU1/fZgN\na62yLFMcx0WPobW1NbXb7ZU5FgAAgPEd1ufUVZwaY4oBUfQ5BeqPkBTTICQFAFSSu2mJ41ie5ymK\nInW7Xfo9oRG46QaA5fE878By3MP6nJYrTn3f5xgOVJibUQBMgpAUtcZye6BZ3ATbOI5ljCn6jHJD\ncjQqs4/23HPSl7/s6frrrY4fX/bWAACqZFifUxecuuX6u7u79DnFAVyDzcck9/tUkmIahKSorVW5\nCGnyCbepoU5TX9e8uCVvcRwrSRIFQaAoihSG4dy/53xWq+Xppz194xuenn9eOn6czx0AcLhycOqU\n+5waY/b1Oe3vccpy/dXCZ10NhKSYBiEpUGGcaFElsw4U8zwvglFrLUOYMHcnT1qdd57VZZcte0sA\nAOOo0uqxcp/T8pL9csXpoD6n5QB12a+FB8RoMkJSTIOQFLVFBRhQP9ZapWmqOI6LfkHdbldBECz9\nhgHVMo/je6cjXXnlzH8sAABFAFpWrjgtV532V5suo60Q111oqizL1O12l70ZqClCUgDA3GVZVvQa\n9X1fURSp1+txgY6B2C8AAE0wbLl+ueo0SZJiQNSgilPOiVhlk/YkDcNwTluEpiMkReVwIXBO06tl\nm/76qrQ0bBnchX8cx8rznOX0AICVs+rXAjjosD6nxphiQNSgPqeu4pR9ChiO5faYBiEpaqvpARvq\na5UvXK21yrJMcRwrTVMFQaC1tTW12+2Vfl8AAACGKfc5dcoDovI8L1bluD6n/UOiuM5aLh6IVIdr\n6QVMgpAUlcPJBaimwx5MlKfTe56nKIrU7XYP9OaqGh62AACAKhoUnEqj9Tl1ASr3VVhFWZbtG6oG\njIM9B6gwAhxUmbW2WE5vjFEYhur1eit7UbK9LX3mMy2df77VLbcs/nvL8QIAgOY7qs+pMUZZlg3t\nc1r1B9jAtFhuj2ms5p0sGoFAoP74DOunvJw+SRIFQaBOp8NyeklJIsWxdPbssrcEAGaDczRQD+Xg\n1IVDg/qcGmOK6+80TYul+/Q5RVVN0saA5faYBiEpAMyBuwBtygWnG8KUZZnOnj2rKIq0ublJNULJ\n8ePSHXfkiqJlbwmqgoAJALAsh/U53d7elud5+wZE0ecUTUElKaZBSApUGJWWWCZXZRDHsbIsKyoU\nNjY2uGgeotdb9hagKviOAMDsNOnB8zK54NTzPLXb7SJALVecGmP2DYiiz+lo2Eerg0pSTIOQFLVF\ngAjMR3k5ve/7iqJIvV5PWZZpZ2encReAHEcAYLimHfMBHOR53oGe8of1OS1XnPq+z3EClUIlKaZB\nSApgaQi6q8Mtp4/jWHmeK4oibWxs7BsK0ERVuKi/7z5PTz3l6bbbcp04seytqQ6ODQAALM+wPqcu\nOHV9Tnd3d4tl/f0Vp1W4zkK9TVKhS0iKaRCSAhVHUFBPdQiAy0OY3MXE2toaQ5gWbHdXynMpTZe9\nJQAAAMOVg1PH9Tl1FaflPqf9PU5Zro9FYLk9pkFIisoZ9cRZhxBqWlxEYB6MMcVyes/zFEWRut0u\nQ5iW5G1vs9rdtVpfn/5nNeWYyLEPAIB6KA+IKi/ZL1ecDupzWg5QOe9jlqgkxTQISQEszSoE3VVh\nrS2W0xtjFIaher3egf5TWDzf10wCUm4wmo/jJQBgFhYxZMgFoP1/rwtNy1Wn/dWm9DnFNAhJMQ3u\njoGK46YYk3LL6ZMkUZIkCoJAnU5n4uX0hNr189BDnp57TnrnO63W1pa9NZgGN4sAgLobtly/XHWa\nJEkxIGpQxWlVz4dMt5+PSe49CEkxDUJS1NYqBDar8BqbapmfXZ7niuNYcRxLkqIo0ubmJsvpV9DT\nT3s6dUo6fZqQFAAAVM9hfU6NMcWAqEF9Tl3FKeFks437+RpjWC2HibHnAEADWGuVpqniOFaWZQrD\nUOvr6wqCgAvHQ9TlQcTWlvSXf+npkkukq68efXvf+c5cZ85Ir3mN9MgjnpJEuuEGK3YJAFgMqsuA\n8ZX7nJaVK07dainX57R/SBTfu9VFJSmmQUiKWqtDuIHh6hJQVZmbTp8kiXzfVxRF6vV6XBg2zOnT\n0qlTnlotq6uvHv3P9XrSffd5+oM/kP7szzxdf7101VWzGRIFAMCiuCAMq23SPqcuQOX6eDUQkmIa\nhKSorVU4yXmepzzPl70ZqBjXrymOY1lrFYahNjY29i1TQrNcfLH0trflOn786N8bx9Kjj3q67DKr\nEyekM2c8/e7verr/fk+f/7zV9ddLt98+/20GAACYt6P6nBpjlGXZ0D6nhO/Nk2UZISkmRkgKAHMw\n6ypZt5w+SZLi6Wi3213ocnoqf5frootG+31f+5qnL3/Z09aWdOutVrfdlusXfsHXSy9JW1uefu3X\nfL3+9Uavfe3RP+uLX/TkedK11/K5zwPfJwDAoq3CuaccnLqwbFCfU2NMEZz2V5yOc33t3tNVKOJZ\ntEmqyKkkxTQISVE5k5yQUF98hoczxhTL6T3PUxRF6na7PPXGAS7Efu1rrXZ2pMsu2/tuff7zntbX\npbU1qduVokj6q79q6bWvPbxKPY6lBx/cOx5feaVVFM39JezDsQEAgPlZtUBvUJ9TF5y6qtPygCj6\nnNYX7TkwDUJS1NYqVLU1/TU2/fVNylpbLKc3xigMQ/V6PaY0YiSdjnTjjee+V8ePSz/8w1Y332xl\nrXTbbVZXXHH09y6KpLe+NS/+PwAAQJMMGxBVrjg1xuwbEEWfU6DZuOMGgAqw1hZDmNI0VRAE6nQ6\narfbXHzN0SoE9TfdZHXTTZO9xquumvHGjKgp+3zT9y0AAJrI87wDxQlH9TmV9nph+r7fmOsYYBUR\nkqK2GGqEqhslIMnzXHEcK45jSWI5PbBCuIkCAKAehvU5daGpMUZpmmp3d3cmfU6xx1rL+4aFIiQF\nKqzpVW5NDroPO5m7IUxxHCvLsmI5fdWfPDd9fwQAAABG5YJTz/OUJInW1tb29Tl1wanrc9rf45Tl\n+kD1EJICwIK45fRJksj3fUVRpF6vx8UR0EB8rwEAWB3uvF/uc1pesu+W6g/rc1oOULmGAJaHkBS1\nRVUb6iDP82IIk7VWYRhqY2NDvu8ve9MALIG1Evc+ADAeltzODvdPy+EC0LJBy/XzPD9QbVr11WZV\nwz6OaRCSorK4GNrDQb5+3AXPzs6O8jxXu91Wt9tVEATs01gJf/InnuJY+s7vtPpW266BHn3UUxha\nXXnl4rZtmeJY+vjHW1pft7r99mVvDQBgVXE9Wg3lPqdOeUCUK7YoD4jqrzjlswRmi5AUlcOB/pym\nvxdNqwY2xuwbwtRut3Xs2DGGMFVcU/bBKn2fzp71lKZSlg0PSc+cke67b+/i/oor8pWorjRGShKp\n1VqBFwsAAMY2LDi11soYozzPh/Y5dRWnTbqHnKRwinsvTIOQFLVVpUAAq8taWyynN8YoiiIdO3ZM\nu7u7arfbjTpJN/E716SLyCr5ru/KZYy0tjb892xsSCdPWq2trc7y825XuuuuXHTbAFYHK6MATKvc\n57SsXHGaZdm+Pqf9Q6I4DgGjISRFJXEQR5VZa4shTGmaKggCdTodtdtt9l1AUqdz8N/FsXT33S1t\nbFjdeute2H7DDYeH7qdPS3/0Ry1deqnV29/ejIDeBcfWcqwAAKAJlvUwZNI+py5A5b4FOIiQFKiw\nJlbuldXtxJznebGc3vM8hWGobrfbqGpRYF6SRNreliRP0tHHtb0qbSnL3J9brp0dKU33KmABAACq\n6Kg+p8YYZVk2tM8p9zVYdYSkqK2mB4irouqfoVtOnySJsixTGIbq9XpHTplk/wT2O3ZMuv32XGF4\n9O91360LLpDe+958YGXqon3qUy2lqfQ935Or21321gAAAIymHJy2v9UsflCfU2NMEZz2V5wuq7hl\n3Cpd7r8wLUJSAOjjLhjiOFaSJPJ9X1EUqdfr1a76FaiSY8fG/zO93uy3YxLHj1vt7GjoIKpJcCEP\nAFg0+uRCGtzn1AWnruq0PCCqLn1OjTH7qmiBcRGSAhVGNeJi5XleDGGy1iqKIm1sbHCi/RZ3IdS0\ni2u+YxjFO985m/2kPOzNDVkYNJkWqAKOjwCwOoYNiCpXnBpj9g2Iqlqf0zRNi2pZYBKEpKgtAsT6\nq8JnaK1VmqZFYNFut9XtdhUEwdJP8pi/KuyDs9Kk19JErjo9juOiOt0tfXM3HkmSFD3C+oPTVbOz\nI33pSy1ddVVemWriVcW5EFXA+Q1V1rQCgn6e5ykI9kdHh/U5XebDXzdUF5gUew+AlVQOLFqtlqIo\n0vr6+syalRNYAdWxtSXl+cHl/nG8F8YdPz6fv9daWxxnjDH7qtNdVUb/kIT+HmEuOJVUVJ1WpVpj\nnh5+uKUvfrGlnR1Pt9xilr05ACqgycc8oG6G9Tl1walbrr+7u7vQPqdpmiocpQE+MAQhKSqJgGkP\n78NsucAiSZIDgQWA6nvmGemBBzxdfbXVNdeM9mfyXPr0p1syRrrzzlxRdO6/feYzLb300t4wpvPP\nn912GmO0u7tbPIzpdDpqt9sj3QwM6xG2vb2tVqtVHMf6qzWaFpxedVWu7W1P11yTL3tTAADACMrB\nqVPuc2qM2dfntL/H6aDrmHGrdN3KQGBShKSoLQJEjMJaqyzLFMdxsfxinMACQHW88IKne+/19JWv\neHrVq3KdOHH0n2m19oYuZZnUv/pqc9NqZ8crgtPnnpPuvrul666zuvHG8c4v5V6jxhi12221Wi1t\nbGyM9XMGccFpEATFjUd/tUbTgtPjx6XbbqOCFACAOis//C0vgy9fwwzqc+quYcaVZRkFMJgKISmA\npZln0O1OtnEcy/M8RVGkbrc7s+X0q8p9ZnUMXVB/J09avfDC3v9fWxv9z9122+DjzK23Wknn/tvu\nrmSMtL09+s8e1Gs0DENlWSZj5hfyDavWGNQfrIqDFQAAwOrqbzckaV/Fqas6laTt7e2R+5wyuAnT\nIiRFra1CJekqvMZZ6a/kCsNQvV5vadOi+ezqgc+pPtpt6Y475vd5XXGFdN55Rw8K6j/WDGrdsYxj\nzlH9wQhOAQA87EZVDXoAfPbsWUVRVFzPlIdcPvjgg/r0pz+tN77xjbrxxht16aWXrkRP0k984hP6\nwAc+IGOM/v7f//v64Ac/uOxNahRCUtTWKpzcV+E1TssNOHG9RsuVXMt8/2gHUQ98x5rPWmmcj/mw\n1fGDqka/9KVIZ854uuWWan7fJwlOy9UafEcAADgcwfN8uHup/oIX1+e01+tpZ2dHv/Irv6KHHnpI\neZ7ruuuukzFGH/nIR3TTTTfpmmuuadTye2OM/tE/+kf6oz/6I11yySW6+eabddddd+m6665b9qY1\nBiEpKomACUdxPfhc/xqGMAHNMotzwEsvSf/jf7TkedIP/mCuzc1z/21rS1pf3wtRT53S0P6m1tpi\nOuugqtFHHmkpSaRrr7XyvL2fe9llU2/6XI0SnLrBCgSnAABgmfqvO1yf0xtuuEE33HCDpL3rmGee\neUaf/OQn9du//dv6nd/5HX3oQx/SCy+8oBtuuEE33XRT8ev6669XVJ7kWSP33nuvrr76al1xxRWS\npL/9t/+2PvaxjxGSzhAhKWptVYLUpj6dHDcMd2FFHMfF5MJut6sgCBr5/gDjcN+BJhwvZrX9aSo9\n+aSn557z9OpXW73hDXtVpV/+svSXf9nSe9+b69lnpS98wdOb32z11//6uePRyy8bfeUrqS69dEfd\n7vAK9Xe9K9fZs9L550u/8zst7e5Kd96Za2NDeuaZlh57zNONN1oNao817jlsnuc8glNg9tx3lu8H\nAMyX53m65JJL9MY3vlFPPPGEfv7nf16SdPr0ad1///2677779Kd/+qf68Ic/rC9/+cu65ppr9J3f\n+Z369//+3y95y8fz9NNP67LS0/hLL71U99xzzxK3qHkISVFZR93or8IF5yq8xlEMWuLa6/Uq//40\nMcSnyht18upXS//wHxrdc4+nSy+VHnvM0/a29Bu/0dJjj0n33NNSGEqtlrS5Kf3xH1ttbKQ6cWJX\nX/qSpxdfjLS2tqnXvGb4wLcLL9z7JUmve53VqVPSsWN7//zQQ4GSxFMYWj3ySEtXXGH1trfV5/tz\nWHBaHqpAcApg3rj2ADCKLMv29STd3NzUu971Lr3rXe8q/t3u7q6+8IUv6LnnnlvGJk6Fa6v5IyRF\nJfHlh2vMHcex8jyv3XJ69mGgGi6/XLr88r2b66eesnrpJemSSzw9/7ynU6c8RZF07bWZfvVXW7LW\n08mTLb3lLet673s9PfJIS88+K115pVWaSs8/L73qVdJ55537+U8+ubds//zzpZtuOncTn2XSm96U\naXvb6sQJKUmkV16Z/HVU5ZgyaKjCNMHp6dPSo4+2dN11eREuA8AgVTkOAqiuUabbdzodvfWtb13Q\nFs3WJZdcoqeeeqr456eeekqXXnrpEreoeQhJUXtNWFq6qvqrEq21yrJMcRwrTVMFQaC1tTW1220+\nY8wN1Smr47LL9n79m39j9NhjVs8+a/TKK5leecXq//2/dRnj6/zzW+r1rD7xCek3f7OlJ5/cCzg9\nTzp+3OqOO6Qf/mGj48c9bW1Jn/xkS9ddZ/WmN+V6/HFPN99si96nr351rs3Nvf3rfe/Ltb6+xBc/\nR+MGp+XQ9OGH23rsMV+eJ918c77EVwEAwGS4H52PSd7XUULSOnvrW9+qxx57TE888YQuvvhi/dZv\n/ZY+8pGPLHuzGoWQFLW1KiciFyQ2+fUaY4qqUc/zFEWRut2uWq3hS1yBWWjy9wqDGWPU7ca69tpY\nJ0/ute9otyO96U25zjsv16tfLYWhdM89nrpdq+1tT1m292d3djz9+q9Lv/mbgd75Tqs4ll580dMH\nPpDrmWc8/dVfefra16S/+Teter39f295aJQLD621SpJEL78caHvb0+WX28Yc90YJTpMk0WWX7SqO\nw29V63os1QeAOWv6fQVWW9ND0iAI9Iu/+Iv6nu/5Hhlj9Pf+3t9jaNOMEZICWAoXDlhrdebMGYVh\nqF6vJ9/3uXADMFP9E+rDMDzQvuOd79z/Z26/3eqtbzX61/+6pXvukb7whZbOnt37b8ZIf/mXLjz1\n9Iu/6CvLrIzxdPKk9PDDRt/xHS3dcou0sbE3QCoM98LRLMtkjJG0d6FrrdUf/7GvJJHW11OdOLEX\nnvq+rxdfbOnECSmKPBmz1zs1qPGV26DgtNu1uuii/cGptfZAxSnBKQAAOIob7ttkd955p+68885l\nb0Zj1fhSG1iNKssmsdYWQ5iSJClulI8fP964z7CpA46a+rrQTIOGvg2abpUL2AAAIABJREFUUD/M\n8ePSz/2cWwKe69FHpZ/5GU9PPeXp1a/29MUvepL2+px+85uePE966SXp3nsD/cEftPSe96zpG9+Q\n2m2r978/1dvfbrS+3lIQBPsqRq+/3tOpU1avelVbnrc3Tf5rX/P02c+2dMklud7xjkS/9EuRPvWp\njq6/3uoDH0h10UWzf7+WYVjFqTGmqDodFJy6B2qVPXe8/LL8Bx6QectbRLNVAAAWI8syBXV+ooyl\nY+8BKq4JoVSe50Uwaq1VFEXa3NyU53l6+eWXq3uTC6B2XNVoHMfFhNNZDX17wxukj3zEStob5BTH\n0taW9Pu/L/3yL7f0jW+0ign3Z89KH/94R1/7mi9jpI9/vK2/83cyPfOMp3bb6oYbrNpt6a67cl13\nnZXnSbu7La2v74Wn55+/l62dOJEqjhM991xHTz/tK45zffaz0vd9XypJRYVlU5bpS3vnvf4bnLoF\np8H//b9qPfCAZIzMd3/3sjcHAIDaoScploGQFMBc9AcV7XZb3W5XQRAUJ7u6h79A1axydf2gqtFe\nrze396Ld3vvV60k/8iPSj/xILmMy7ezkOn3a6Ktftfo//8fXf/7PHb3yiqdWK9fnPy898kigOLb6\nX//Lk7XSL/2S1dvfbvTlL3taW/N0552ZLrooVauV6Y47YoVhqDA8pn/1rzx9+7en2tqSbr99r/rS\nWruvz6dDcHouOHXv0aKZN79ZMkb5jTcu/O8GACwW9zTVQUiKaRGSotaaUGXZNFmWFUOYFhFUANPi\nGFJNo3wu86waHUe512gQeHrVqzxdeKGvb//2ln72ZxPdf79VFBl99avSb/92rieekJ58MtDZsy35\nfqY/+INAr7wira9LDz/sK0naOv98q09+sqsrrrC68Ubp277N6v3v36s4ffRRXw895Otd77Jqtfb+\nfknFMCiCU3Og/+vOzk7R23QRFaf2oouU3XXX3H4+AKBauNephizL1Ol0lr0ZqDFCUlQSJ5n9qh7i\n5HleBKN5niuKorGCiiZWvhHg10PT9rtVseiq0UHyPC+CyDzP1Wod7DUq7Q1bevObPUmBTp6U3ve+\nvePCN7+ZKE0zxXGqn/zJrra3pQsvtHr44bZOncqVZdKnPhVoa8vTeecZvfRSS76f6y1vybSxEWht\nTbrgglTXX6/S39mS50medzA4Lf+zpCIkXEZw6j31lFqPPCJz8817jV9n+bP7gtMkSZTnuYIgKIJT\nV3FaHgxVpaX6AA5q4rXisnB9iiZL01QbGxvL3gzUGCEpUHFVvSC01irLMsVxXCxrWFtbU7vdHnmb\nq/raMBzhLxZh0LFhUNXosWPHFt6c3wVtLnR0odw4QWOe51pfT5QkiXq9lv7n/0zUbreVJNLTT8f6\n+tet4tjol3850sMPBzp1qqXTpz1Jvv7wD93DJ6vf/M22brlF+o7vyHXBBdLZs55OnrR673tNsT3l\n7crzvAhMlxmctr70JbWefFL2wguVzzgkHWSUitP+4NT9L8EpgCbiuIY6mOSeg+X2mBYhKSppnJCN\nwGaxytPpPc9TFEXqdruNWsIJoDqqUjXqHgy5qlEXoo3K/fkkSWSMUbvd1vr6+r6K+yiSXvc6X697\nnSQFeve7pWeeSfXpT1v97M+G+vrXfUnude+Fpn/xF9K997aU53sDoS6/3OrUqVyveY2ntTWr7W3p\nLW+xOnFiLzB99NG9XqjXXmuL15YkVr5/MDh1/T0PC07PnJG++tWW3vCGXGtro70X5uab9wLSN7xh\n5Pdv1gYFp646OM9zpWlafO4EpwAALMe451s3CwOYFCEpUAPLDoKttcVyemOMwjBUr9dbeAUXgNXg\nwrpXXnmlEVWjSbJXNdpqtRSGobrd7sgX/Rdf7OmHfsjTD/1QJinTPfdI732vr52dvcD0+PFcZ854\nkjylqafHH/f0z/95WydOSE895SlJPJ13Xq6rrrJ6+9ut2m2rTsfT+99v9PrXWz37rK/f+72WfN/T\n931fps1NKQgOVpw++6ynF1+UTp7c67vqgsK/+qu2vvpVT54n3XhjPtqbsrGh/IYbRn4PF8UtvS8j\nOAUAoD6oJMW0SDiAilvWTVe56ilJEgVBoE6nM9Zy+lE0eRr3ssNtoG7KVaOtVktra2tLrxr1PG+q\nqlEX8vZXjU7q7W+XvvENI+ncUKbf/33pn/7TQEEgbW15uvhio+1tT3neljHSSy+1dPq09PnPW7Xb\nnk6cyPX449L551vdeqvV88/vhaz//b8H2ty06nZ9XX211ZvffC70vP9+T6dPS+edl+rSS41eeinX\niRPSlVfmyjJfl11mZMxyepzO02HBqTGmCE7Lv5fgFE5Tr28A7OdWXmD5CEkxLUJS1BrL7Wcvz/Mi\npJCkKIq0ubnJiX9M3BTVB8eQ5RrUazQMw2Jp/aLMqmo0TVMlSSJJY1eNTurOO6U778z2/btvfEP6\nvd8z+sxnWup0cn3uc4GeeaalLJPyXPrTP5Wef76t//SfrIyR1taka67J9Z73SDs70uOPSxdcIF16\nqfSVr3i69NK9qtbLLw/0678e6fOfb+mHfzjV295mdMEFRpJ3oMfpww8H2t319Na35vL95pxDXBjq\nKputtUXFrQtO7enTan3jG7JXXUVwCgDAgrDcHtMiJAUwMKRYX19XEATczGGfpj2YaNr+XafP57Be\no9vb2wvZhllVjRpjlCTJviF2blr6srzqVdKP/qj0oz+6F1xmWaaHHrI6dUp6+GFPp07l+g//wdeZ\nM5K1nra2pAcf9PX1r+d6+eWWjJH+7b8NdMMNucJQuvhiq+/7vlwf+1hLX//6Xl/TvT/na2PjXIXs\nuffU6L77AuW51dVXZ9rYWOxwqEUqvx4XnAYf/ai8Z59V/Df+htIrrlCapjLGFL+vHJw25X0AAGCW\nJqnGp5IU0yIkRe3VJRCY1DxDDzedPkmSpQ1EAbA6mjahvr9qdG1trbLHzyCQbrppb9v+2l+TpJZ+\n8idj/fmfW/3UT4U6c2bvfQjDXC+9tLf8fnfX0+c+dy4A/ehHpVZLuvjiXP/4H6d64omWvvIV6dZb\njV77WikMpa2tlj73uZauvjrQd3+3tLvr6VWvastaqzjO9V//a1utltHf+lup1tbOBafuvW9KYGiv\nvlqS1HrNa4qK6EEVp+XgtByaVuV9aPo1FrCK+F6jydxwTGBShKSotarejFaZGyISx7GstQrDUBsb\nGzPplTeJOlW+jauprwsYl6saTZJEnuep0+nUttdoFatGJ9XrSe9+t6f77kslSdZKL74o3X13pv/y\nX3w9+KCvV17ZqyqVrKz1ZIz01FMt/bN/FqnVkjodq2430Ld9m9HNN+fa3PTUakn339/SD/5gpiuu\nkKS99/iBBwJ9+MOhdnc95XmsH//xrPhcjDFFxYjr7Vbn4NTceqt06637/t2gitM6BKd13LcBHI7v\nNZoqTVOGC2Mq7D3ACnDBQBzHxY19t9tlOf0c8b5i1Q2qGu31eiNfuM7qIcMsqkattcUQO2mvarTT\n6dQyvDuM50kXXij9wA9IP/ADe8Ohzp6VXn5Z+vM/9/Qbv+Hr9Gmr559v6eWXW0oST9vb0unTnp59\nNtCnPiVtblqtrVltb3v63/9b+pmfyXTttdL55+9Vs544YbW7a3X55XshdfkBnQtMy4ORJBUBap2C\nU/8P/1CtZ59V+v7376XRQ0wTnNY1nAfGxUNnVB1D2qqD5faYFiEpKomTzDnTVFr2V29FUaRut1v5\nm0sA9VUe/rbsqlFjTBEuuTBunOOfm1DfhKrRSfV6e78uu8zqB35gbzjUzo7R009Ln/2s9NWvSr/x\nG2298EJLrZanLJOef74la6V77gn0vvf5arWkILC6445EJ05I3/u9Rnfemev556VPf9rXddfletOb\nzk0G3hecvvKK/E98QubCC5XecsuB4LT8eVTp3NZ66il5L78s7+xZ2UNC0kEOC06NMUWrh93dXYJT\nrBT2bWC1THIPzOAmTIuQFLXW5KXak3IVT3EcyxgzdvUWcJgmfuea9nqWYdqq0X6T7mezqhp1r8W1\nJDl27FilArhlW1uTrr5675ck/ct/meqJJ6T77mtpa0v6pV/ydN99beW5lGV7oUaSePrd3+1Ikj7z\nmZb+yT9p6bOfzRTH0qlTnqTBn3dre1v+qVNqSWp9q7enqzQtV55KB4PTZQYqdmtL3nPPyW5uzuTn\nDRp2RXAKAGg6Bjdh0UhNgAZwy+ndctAgCNTpdNRutyt/Y9TE0A31UfXvR9U1qWq03GvU9311Oh1a\nkozhiiukK67YCyt/6Ickyejxx6X/9t9a+oVfCLSzszcM6hxf/+AfpJJaOnMm13/8j0bf9V2tg+/3\nq1+t7Hu/Vzp2rPhX/f05XUjaH5y6c6OkfcvVFyH4i7+Qt7Oj1te+pvzaa+fyd4wSnCZJcqAHL8Ep\nAKCpCEkxLUJS1F7TA7bDQsRyQCFJURRpc3OTiqcKIPzFMixiv5t11eikXL9Gt/x6mqpRFyS518Ix\ndDauvFL60IdyfehDe71cX3pJeu97pQcfbEvydPnlvn7/931Jvu66K9D551u9/e27+tVfjdXp+EWo\n51100aF/T3+fUtdqJsuyYsl6ucdn+c/NKzhNfvIn5b3wgvI3vGHmP/swBKcAgFVGSIppEZKi1lbx\nYn5QQLG+vk7FE4C5qmrV6CRBV3/VaBRFHEMX4LzzpD//c0lKJUkvvCDdemtLzz3ny/OsvvnNlj7+\n8a5++v87rZ/7iS9q+/WvV95uFwOe3C/3mZeVV1SUW80Mqjh1y/LnGpx2OrIXXrg3DWvJpglOATSP\nG4SH2aEwojroSYppEZICNeGm0ydJUtzULzqgmAcqLoHqqmLVqLu5o2q0/i68UPrKV1JJqX7t1zz9\n1E+1FQQt3XHe/9Pa/Y+q+yd/InPrrUovvlim1VJ20UWK41h5nu8LTN0EeN/3FYahut3uwHNjf8Wp\nNKfg1BgFn/60JCl5/eul48cnfIfmZ1hwWu73miR7FcDb29v7+psOCqkBYNVxXJw9ay09SbFwhKSo\nvSYHbO5GzU2nD8NQGxsb+yb/AotEqL0a+qtGl/FQplwxStVo8/3Yj1n92I/thXJ69ttkP7clPfOM\nWl//uro/+7OS7yv52MekbrcYUuQC7zIXbo4a5o0SnJb/WToXMA7dF31f2ZvfLCVJJQPSYVwVafka\n4+zZs+p0OkVw6kLqcsUpwSkAoCoISTEtQlLUWhMvyMvVTmmayvM8tdttra+vN/L1NhVhIuqmalWj\nWZbJWqsgCCaqGnXV93meF8dQHjDVxEUXKb/rLun0ackY+R/9qBSGsr6v5FsrKiQpDEOFYSjP8/ZV\nG7sp75IOLNUfZer9sOC0PBDq0OB0Z0fhhz8stVraveUWqdeb+Vu0SC4IdforTt33zC3RJzg9Z5Iq\nKADA5Fhuj2kRkqKSVvGC0g2aiONYrVZLURSp2+1qd3d3pJs6AOMjzK5G1aikfVWjLmQpV9K7kCsI\ngqEDZtwS4SRJ1Gq1FIah2u02x8+62tyUJO189KN7n+v2ttrtttbW1g7sAy6cK98YlYNT16tUmi44\nLYeFQ4PT7W11nnlGnufJZJm8bwWITTGo4rQcnLqHHASnAIBFo5IU0yIkRa3VPeCw1ipJEsVxLGOM\noijSsWPHFl65tUx1/wyBOqpS1Wie50XV6KBeo+UekcYY7e7u7gtS3e91oQxVo80wqIfssWPHxgob\npwlOR/l7hganQSBtbsoGgfIwlPr66R66VL+mysGpe78JTjErVOQCq2mS737esAeTWLzVSWKAiigv\nA03TVEEQqNPpDK12IkQEMCtVqRp1wegovUaHVa25SeZxHBf/vtVqFf/NWju04hTVVa4GnkcP2f7g\ntDzlfWbBaZrKf/xx2bU1dbpd5d86j5eXqEtj9DitqUmCU/c+E5wCqBOC/PkZ933lc8C0CEmBBSmH\nE5KK5fRNuiHCOU0Nt5v6uppi0OdTp6rRo5TDUWOM2u22er2efN8/MOjJVSAOCrq4gK6WQZ/roqqB\ny+HkoODUPdR0gf4obR/0hS9I3/ymvG9t/2FL9SceDlVTowSnaZoSnAJzRKAHAMMRkqLW3LCGqnLL\n6ZMk2RdOUN0EYN6qWjVanoo9zs/o7zXa7Xb3vRbP84ohT045OC0PciI4rYbylHrP8wZ+rsswLDg9\nrO3Dvh6n550ntVpSGEpDgt6jglP3zxLBKcEpAABYFEJSYA7czXh5ueCk4UTVg+BpUZkIzI6ryNvd\n3W1E1agbaOcmlXa73bFey2HBaZZlxRR0tzTfVQeOOswH43Pvf5IkxXCFtbW1yvfiPmxYkQtO0zTd\nq4R9/nl1JFnfV5ZlIz8YnTQ4dX9uVYLT8vtNcAoAAGap2lekQI24Sqc4jmWtVRRF2tjYYHgIUGFN\nCeld1agLFTudTq2rRl11oaSZVxcOCk5nOcwHg5XbPkh7n2un06n1ezosONUXviDt7Mjb2Tm84nTK\n4LR/yb77easQnDoEpwDQXLSGwDIQkqLSjjowLjvg6O/1V6504oAOiZM75mdQ1ajv+1pbW1MYhgvb\njvKSWBdOTFo12l9duKjWJEcN8xm7JyUK5c/V9311Op1GnyM9z5N3993FP/d6vQNBnuuXO6/g1P1d\nkooA1e3j5T/fBKMEp0mSFO9BOTQlOAUwK1zvA81BSIpKqvpJxt00x3GsVqulKIq0vr4+lxuPZQfB\n89bU11f1fXhSTf286uSwXqNnzpxZ2L7nqkbd8l9XoTluOOp6jUrVqS6cuidlQ7//o3IBvusB69o+\nLPtzXRT7x3+875+HBXmDBo25hwzj9sudJDgt76tN+mwITgEAwKQISYERuZt5V1HEcnoAizKs1+ii\nAzkXurhwtBwwjGrZVaOTGqcn5aoGp4MGbLXb7ZV47YMc9jhpEYPGhgWn7pfbf6WDwWnTevISnALn\n8LAbTcbxGtMiJEVljXKAm3dVW7kaJk1TBUGgTqez0jd9ABZnUNXovKrWj9qOplaNTmOcCsFJg66q\nKw/YMsao3W5rfX19tR8gbm1pd31d+sQnxvpjiwpOy985950eFJy66ysX/Nf5uzrIYd9fF54OCk4Z\n7LZ4LGWePd5P1AGBPpaBkBQYwF0Yu2DCDQ5Z1g0CJwhgdfQ/nGm32yNXjc7ywVF/1egkQ5ikc8fT\nJEmKB01N70k576CrCgaF3rMcsFV7W1sz+THz3p/6+5S6XutpmirLMgVBsO/vK/+58oCopnDvdxnB\nKQAsz7jHVe6bMS1CUuBb+pfTL2s5a7+mX3A3ucele21N/wzrrEr736Cq0WU8nJlV1aibUO96Uh47\ndqxxgcqojgq60jTV7u5usdy53JOyasGLqxqtU6uEphm0P7lK0CzLDuxP5WFjw/ano0Lv/mX55aXq\nDsHpweDUvW8Amqsq15EAZoOQFLU2bcBRXiaYJIl831cURQrDkBs+YADP87jpm6FpqkZnadZVo26S\neRRFja4anUY56IqiSJIO9Ed0AdSgCsFFIvSuPrccvj847Q/ipf37k6SiatT3/aGhd3/Fqfv5EsGp\nUw5OsywrglNJxaDPKj74ADAbfK+rgc8B0yIkxUpywyXiOJa1liFMABaq6VWjqzTJfJZc0NVutyWp\nCJ7KwWmWZft6Kbqq03ncFJQHMRF610///iSd+873h3huf3L73DiDoQ4LTsv/LGnfUKimHSMGBaeu\ndYHnefve8/JgKIJTAJgN10MbmAYhKWpv1EpSdyMfx7GyLFO73Va32638DV+VlgMDmBxVoxhXOUwq\nB6flCsHd3d3ipqC/4nSSz8LtG66SlUFMzVF+oCGp6A8saWYVzMOCU7ffrmJw6nrbO8MqTsvL9F0F\nLsdTAKts3LZl7voamAYhKWptlIOmW04fx7F83y+qnLjwrIYmh8BNfm0YHVWjmKVhE7n7l1aPG5zm\neV48SGy1WgxiapDy8LRhfWTHrWCeJDgt77OHBaeut2eTg9P+ilPXU9Z9D937QnCKeeDaFE1FSIpZ\nICRFZU0TMFlri1Aiz3OW0wNYqEFVo+vr6wuvtHQ32i7scCGHpLGCh/KyaxegtdttbtYr4rDgNMuy\nIujqn4DearX2TTMvr7BAvZWPQeP2kR2lgtkNuXSB37gVzASn+7ml92UEp5gn9hk0ESEpZoGrYNSe\nC1L7Q4kgCLS2tlb7G3mqEVElTd0fx13OM0zTqkZZdl1fw4JTY8y+z9X93na7XYT4s/o+YPHm9UBj\nXhXMZUcFp+6XtBpL9Q8LTt377d6Pcn/TJganTbzuQHNwzqwO11IPmAYhKWrN3czt7OwsPZTAZJiW\njmWaxUVtlapGJRVLY90NszR91SjLrpvBVaS5PrLdble+7+8LXXZ3d4tqtXKFYNNCl6ZxwXf5GDTv\nBxrLDk5XcTiUC0NdtbdrjTBKcFr394LjD7B6JulJymoYTIs9CLVkrd03nT7P86UMQAEO09SqS+yp\nUtVoeTm9qyAd1Dtw2PGRqtHmGrTsur+PrAtdoiiStH+fmnaQD+anv0dwFEXqdDpL/VyqEJy6f5aa\nH5yWX9Nhwak7PzQtOAWAMpbbYxYISVFZ/QGTu/iN41hJkigIAoVhqCzLtL6+vsQtnS+CNqA6qlQ1\nOqjXqO/7Wltb2/ffygFZOYwIgmBfyELVaLNMs+zahSeHDfIZFJwu+nuwqsqfre/7iqKo0u/9UcGp\ne0CT5/m+4NS1CJlncOr+XJPCwkmC03Jo2qT3AsBqSdNUYRguezNQc4SkqDxXrZUkiay1+4Yw5Xmu\nnZ2dZW8igIZzocTu7q4kqdPpLL1q1A0yGdRr1PUgLS85cgGvC7ncsdP93na7TTV+zZUfJs6yInjU\nQT7b29sTVwficPP6bJelHJy6G9pyED9s2NhRVfFlowyHcsdS9/MITglOAdQXPUkxC4SkqCxjjLa2\ntoqDnZu4y81Ws1ApWy+r9HlVuWrUhQTjDmJyPSmlvaA3CILiBtn1MnXhRX8/SlSXa0GTJIkkLaQi\neBHLqrGcz3ZZhj3cOaoqfpbBqdt/Je17GEVwuj845Ttcbwwami3ez/mY5H4jyzJ6kmJq7EGoLHex\n3Ov1hp54ViWwWYXXCCxT+QK3blWjh3EBQ3mgy9ra2r4bXN/3h1YHEnJVm6ssHPbZLtphwWm5inma\nkGtVlL+3ro3GKn7vqhqclj+LVQlOjTHFg7bd3V2CUwALweAmLBp7ECrL9dla9QuuVX/9dbYqIX7d\nuc8pTdOlV41K2rfcdNKqUXcjW64+W1tbO/K1EHJVX/+wnjAMdezYscoGNcP2qVmGXE3RP0Bt0JAt\njBac7u7uFmHmLINT98sdF6XVCk6d/uDUHY8ITgEsEz1JMQuEpACAleVudl955RVJy60adUHkPKtG\nJzFJyOWW6ruba0zP9ed2lYVVH9ZzmKNCLlepVg65mrxP9S+pj6KosUvq52XQPtVfFV/ep/rbiYwz\n0Kz8893/DgtOm/qgdNzgtNzflOAUwLzQkxSzQEiKWnMXWU3vBdPUi2yJakssXn+vUUnqdrsjT/6e\npXKF5jS9Rvt7FnY6nbkGvUcFEsOmn7sbZYymv7Kw7sN6DlPep6IoktT8fcq9riRJKtEuoWlcKFe+\nYR51nxolOB3Up7Qckro+z77vF+ca9/vHPc7XAcEpgGVzRQLANAhJgYrjohFVUudQ292gxXEsa21R\nrXX69OmFVuTNompUUhGeVaUfZX8gUb45Lk/ldmEY/U2Hc/tqkiRqtVqNHtZzmKP2qWEhV5UrbMsP\naerQLqFppglOR/mMrLX72raU++qXq0vLfU7ddhGcngtO+1sjNL0YAsBBk3zvCUkxC4SkADAndQ4U\nm2LQhPput7uUEKW/arR8Qziqcu9Ua22lA5byzfE4g6FcYLxqN8SD2iU0tWp0UqPsU3Eca3t7u3LD\nxgYF38uoXsdBk4bx7vj9/7P35lFyVeX6/1PVNfSQkDCEiIEwBJAxJKST7nj1i8jgcOHKQpxwQAEN\ngjJP4U7cu65y77omDIYZAgiKiAooggpcUdIJZEIgQIAgg4QECJCxu7qrus7vj/z2YffOqapTdaa9\n93k+a/WCJN3Vp+rsc87ez37e5/UrfNdynFI4/eA6Fl/isxTPSTGXolhKdITjUh9Ybk/CgCIpMR4h\nRNn+cLL1PVJIJFFQyzVaa7EZ1RgMyzWqdrpub2/X2i1Xi0b5pmlsDOUVl+CnyRbZSr1mY/XE+LiE\nU9XxTeFbf2qJ8eJeJQRRWdDMZDLuJpyf+3ujUn0131Q+LluF01rXsWhEWK1WsWXLlrqOU9IYMd/h\nZ0ZshE5SEgYUSQnRHE5iCPFHq67RKK6xMF2jchdzGztdN9upupWGKzqiCt9JxyXYRD3BRVyX4roS\nGxdhivHqtVssFiPPCSbRIouT2WzWdZeKsSPuWZs2bWpZjK8lnIqxm3bhdHh4GMVi0RVOxfNBXMdy\nvimFU0LSCUVSEgYUSQkhhBhNs67RKI9DLNxk8SWoa9TkLuatYmtjqLQI3zrSyMUsl0u36mKWS+rT\neu3aitpErVZJfdguZvH68ritJ5yKioU0CKdq5AaFU0IIRVISBhRJibb4nciwXJvoio1jU5f3pGPW\nqFioCoGPrtFwqZcbKJe/6pZFCWybR0nxTA+adTHLTmYhQonvF+OPJfV2ocZhiE24WtduHPEPFE5H\nQuGUEDtpJWquUqmgvb09oiMiaYEiKSEGYHPuqi6iGzEDnVyjQqgVC69WXIx0jbZOK42hhMAVx8KY\n4pmZNONizmQybnOZQqFQVzwjZiGaB4URh6GDcCq+gPSV6vsVTsWzgcIpaRZb12gmUi6Xsd122yV9\nGMRwKJISbeHDhhACfCA2lUola1yjcmkvxbPwiKOkuhHNOs+I/sguZiGUDg0Nuc161DJ7U+IfyEi8\nNjaicvQ308Su1dzcesJp2ptD1RJORYMoCqeEmEmlUhmxyUlIK3AfWvD9AAAgAElEQVQEEeOhE5EQ\nO4nTNVrvHqK6RltpwiReRy65LhQKyOfzXHhFTKOS6nK5jFKpBCBYvqkQV4SQz0ZM9uAnj1LEP4jG\nUDrHP5CRiLiTwcFBAEjMFewn/iHoJk8j4VT8GaBwSuGUEPOoVCrMJCWBoUhKiAFQCDYTnrfmScI1\nWut1w3SNCnGFrlE9kMWIYrEIoHFjKDmLUsAu5nbTjCtYiEiFQmHEz4dZUk3CRXUAt7e3axd3orNw\nKn4ujvtdnOXM9YRT+Vo2VThlaTgxhVbGKhs3kTCgSEqsgEKUuVBINIuozpeuWaNhukZZcq03tRpD\nCWdgqVRyBa5sNusKCMyStQ+5pD6IK7hRFqXYQAlSUk2aR3zuwnFk2sZV0sKpWrIvXi9u4TRO/ObK\nmiqcEmILFElJGFAkJcbDiQchZqJb1qgQKwC6Rsm2zkDZNVqpVNzFrxjDFLjMRs0K9iqpDwNZbJHH\nVpy5uWlEvn4dx0GhUEBHR4c1n6ffWBHHcUaMKfG8Das5lHCaCgFV3Cfln7cFP8KpGG+qaMpr2S5o\n9tAHltuTMKBISogh8AFMbEE316jjOBgYGHBL65p1jMmu0Uwmw0Y9ltEoS9aPwNWMEEHiRYesYD/O\nQFXgkuMfOK5qo57fNLm+G8WK1MtjjlI4lZ+xFE4pnNoCz50e0ElKwoAiKbEC2wVEmx+8LLdPB3LX\n4KGhIeRyOW061BeLRQwPD6NaraK/vx9A4wY+8vsRu9bi/RDzEed3aGjInXDXcgXXE7gqlUpojaFI\nuAjXd6PzmxRe46pRbi7H1QeojdR0O79JocaKAOGPq1rCqfgSoiFA4bSecMpNEEKah05SEgZczRFt\n8Tsp4OSB6AoF4K0LgcHBwRGu0TFjxiTmGhULErFoAbZdkKkLl0qlMqL8XpRtilJsukbtQW3U02pJ\nrh+BS4wr2RXIBj7RYnqjrTgELpOJKzLBNmrlMYctnMrfK0RSP8KpjeevlnAqNmwpnBLCxk0kOSiS\nEkII8Y0f4Vdn16ifrFF1wSheQ7jOxGeQyWTckkXmBZqN7Bpta2truVFPPbyECHY+jwe1i7lNJdeN\nGo4NDg5aP67E5sbg4GDqSuqjQIhwjYRTeaOnWeHUK6e0lnBaqVTc3yU2OW0VTtVqlCiEU3a3JzZD\nkZSEAUVSojV+HuJpcOul4T0S8zHRNVoPL1ehyE5tlEPJvED9UV2FhUIBo0aNim28NtP5nA18mkfe\nrElTIzW14RhgryAvb27kcrlUnN+kqCWcyuNKXGutOuRV4bRarbqRCUJAlH+n/HNpFU7Fc4KOU0K2\nwnJ7EgYUSYnWcLfTfigAm48QCXVwjYrFGtB6h3o1i9LLVVgrh1K4t2qVJ9LdlDw6N3JppfM5BfmR\n1NrcSPNn04wgn81mR4hbugny4j4r7rFxb26QD/CTtdmKIC/nyRYKhW3Eb7Usn8JpbeFUbgxl2iaI\nSXC9qg90kpIwoEhKCCERYbMAnAbXaLNZhZlMBvl83rM8UYhb/f39xru3TEQVVkxyFbKBjz/iiEyw\niVYE+SSFU/kezTxofWlVOJXzvoX4XStPtl6pvhBO5T+L45LdsLbRrONU/J24lnkdER1pRXyuVCps\nokoCwxFEjMdmIUqQhvdIzKBSqcBxHKxfvx65XA4dHR3I5/NGukaBD4QV4YJtb28PzVXYqDyR5dTR\nU61W3ZJ6ACgWi1YIK40archlr7Ir0DbRkK7CcKnlkJeF01Kp5DrU4nAyqyX1FL/No55wWqlUXGFU\nfK94BlerVd/jqpZwKn4PhdOtyJ95uVx2Pxu5TJ/CKTEZOklJGFAkJYRoAUtV9EV1jQLQxjXaSkmd\nVxZlXB2Q/bi3hAihils2LuKiQm60VSsywSb85AXakkMJbOv8tkX81pEknMxqnizFb/uQn8NtbW3o\n6uoakfetRkDIorzfTUQxXtRS/VrCqXBZ2iycis+yUqmgo6MDwAeNssSmIoVTYjLMJCVhQJGUEJIo\nnHDpi5o12tHRgVwuh/Xr18e6eJAX5GIRE8Q1KspxdcmibFaEaLYZRlpQxe9isdh0ZIJNNHJvibFl\nkpNZdn6nQfzWFdXJDIQjnIpreHBwEADFbxtplDcKoOYmYhj3LAqn2yKuZxkhmooNNgqnxBToJCVh\nQJGUaIvfh24aStHT8B5tRJSLmUSjrNE4x6G8MArTNWqCI8mrnLqRK7AZh41N6Cp+60gt4bRWObUq\nyCfxmYqSepGPGafzm/inVgSEEOSFK9TLySw7g5knax9BrmE/ERBBs3MbCafiC7CjVN9P5Za4ntXN\nW1U4lb83zcKpENNJuLSy5qBISsKAIikhhBBP12hSWaPC6Waja7RVWnUFivds6vuuBbMow0PXxlDV\natUVzrLZLAqFQiL3JNIa4r4jHIHAtps94p4FwBVY8/k8BVJL8IrFCOMaTlo4TWtzKFU4FRshfoRT\nGz8PEg+tNG6iSEqCQpGUEJI4winLRVG86NKhHsAIsS9trtFWqecKFI0ZSqUSAHu6nnsJZyzHDZ96\njaGEABFVvqmaJ+tVjkvMRNzT5aZ7YgNLPAMGBgZG5FAKN3MaXfKmIt+n43IG6yCcij8D6RBO5fdV\nTziV53WyaGrb50H0gE5SEgYUSYnxpKUUPQ3vkcRDENeo+J4wRO2wXKN0nH1AI1dglOJWVIgFqBDO\nauXYkehotTGU3wgI5snajyqcebn7azWzCypukXgQzxjh5Er6Pt3oeSg2EoPEi7QqnIqfs+0eR+GU\nJI14VhASBIqkhBgAFwFmopOAL8rexIJAJ9eocEQ26xqVy611WJDpSqN8U7mDsLxITFqAUEs1C4UC\nOjo6eD/UhEb5pn6arPgRzojZtCKcteoKtDVeRGfUvNFisaj1fTpI07EwhFNVQKVwWl841XkDlxBi\nLxRJCSHEYmzLGmW5dXD8NO+RBYi4m/ewg7m5NBK3ZOeW2ESS70vEDqIQzvy6AgF74kV0Rt7EEtmz\nplZwBBFO/Y4tP82hZOFUzJPSKJwODw+jWq261zSF0/TChlgkKSiSEuMxsYN4K+jiSIwCnRyXNkDX\nKGmWVpr3CPE0jMWKV54sO5jbgRhb4noVz2vh+qtWqxgYGMDAwICnK5CYg7qJFbUzOA5xi4ykWq1i\ncHDQbYpo6yZWvVzmJIVT+bO2bQx7ZbeaIpyyr4I+cD1JwoAiKdEePnhYbk/8oZtrVExq6Ro1k1qL\nRCF6l0qlwPmmLLe2HzlPtpaooo6twcFB9Pf3G5Wdm2bEOdOh2ZbfpmOyeM+x1RixUSliE2xuiuhF\nrVxmWTiVx1bYwqn4EgIq0LpwatK6yo9wKjZXdRNOCSHmQpGUaAsfbIQ0xss1ut1220W6QBXOX/Ua\nFa5RMYEXi9BWXaOVSoVNejRCLFZEcxVgZL6pOG+NGqzQGWw/6jkuFAp1RZVGY8urMRS7nieLWlKv\nq/u71aZjFE7NyxuNGz9jK4xmiWpDIzHH8iOc6nY9hkGzwqncGCrt13Qa4PklYUCRlBgPS7WJrkQ5\nNnVyjYqFlHCNtlLKKMqo5CY9dI3qj+yY8epMLecEijEhFnPt7e08x5bhlVPY6jluNjuXXc/jwYYs\nylpjq1ZDu7SJ8jac46TwM7aCivJeOaW1hFNRri++39ZzSOHUTkxyPRO7oEhKtIY3xq3YLgTb/v7C\nQnaNCldH1K7RWoTlGpVLcdmkxw7kfNNCoTCiu7Xc1bxUKqFSqdC1ZQFxNduq1xiqUqmweU+EyPdq\nsTEnnwfToSjvnTdq0zlOiqSFU+Eule+VAFAul92xa+P9sZZwKscXeAmnNl3ThJDW4JOPWAEFNmIz\nurlGAWDLli1oa2tDPp9vehHl5RplCZ9diEZMg4ODAD44x2KxwlJq89Gl3DrppmM202xsgm3UE+Xr\nCaciV9mU8ZX2vNEkiFs4VXODxWvUc5zaOAbqfe7iS1zTzQindDzqA88DCQOKpMR4eDMkNiJcoyLP\nSifXaLFYdCeT/f39ADBCePCawNM1mg7UJj3t7e2ejZhacW3JwhbHTHLE3cG8Fbya98jiQxhNx2xG\nLrcGtt7zGY2xlUaivCluZuaN6kej52KzMRDiZ8U8stZGluo4lf8sjsvLlWkLUQmnhBBzoUhKiAGI\n8lRbsbXcvpX3pbpG29vbtcgalSeGMvWcD6L8XjhHRbZZe3u7lRPttBKW26yWa0t0PPdyBMquLRId\nXpscJjXbajaDUt7wSdMi2KvcmsJxY1RRHmjsZk5KOJU3YHXd5CAf0IqbWYwpvxnvtUr1xT2SwulW\nZOFUfPbimSHMBIDd2a+EpAWKpMQKbBTYSHrQ2TXaKGu01kRSuJBkcT+bzbqTe/FnYi6qozCKZluZ\nTAb5fH6EI1DOVRscHER/fz8dgREhYhPEtWyT26zVDErTSqkbobrNWG4dDl5uZvXeNTw87D5jo753\nyQJ4LpdDZ2cn80YNpd6GouwAB7aK8mKjuplNH3H9y/fHesKp4zjua6dBOFWrFESvAPHMENc/HafB\nYIwBSQo+HYnx8OZJTMU012gj5BxKx3FQKBRQKBTcXXYvV00ci0MSHqqjsFAoxOoolBdgtUqphaBn\na3OVOJAF8La2ttS4zRq5mU0ppfaDV24wS+qjw8+9K2gGpReyIEsB3E7U+3VXVxdyuVzojcconG6L\nmC+LSqm2tra6jlNZNOWchBB9oUhKiCHQLWsHJrtGa+Enh7JRRqBapk9hSy/UjEKdmm35cQSWSiU4\njrNNdq6Ni7ZW8XIUmlRSHxWqmxnYtpS6Uqm447BeNrMOqIJKrdxgEj3NxkA0yqCUX0N1gFMAtw9x\nvxYNt9T7daNSfbHpI56NUQin4kscrzgu24RTeY1Wz3Eqru1yuUzhNALEOoKQoFAkJcZja56ljO0P\nTFvPofy+RLMQXVyjYpIsJnNAc+Xv6iKs2RzKZoQt1W3KCVB8iEX60NCQUc22mu14rruwFSVeAjgF\nlfo0s+mjSwyE2sGcArietBoDIcaWcAczb9ROvJoxNTv3Es/GYrEIwH/jMb8xI/WEU5ubQ9X7bCic\nxoPITCckKBRJidbYKp6RdCAmQBs3brTWNRrmIsyPsCUcWyzTjw4vAdyrI65ptCJsiWvExvGlXsum\nCOA60sgRKATKuGMgbM6UTRN+HIEDAwPu9wohhiK4PYjYDznOKKzNrCCNx8ISTsWfAbuE03rUE07l\nazvNwmmzmaRiE5CQoFAkJcQQKBabg+wadRwn9a7RIDQStpg/GR5py6GsJ2yJDEqv8WVy4x65uUcr\nLiTiH3l8FQoFAI0dgWLzJ+j4Upuq2X4tpxlxrxIZ4LIrzZb83DQjRzTFeS3XazzWSDj1O75aFU7F\nz9k4jv1EcKRdOK2HaExHSFA4iojxpMFtmvaHngl4ZY12dXVhYGDAXSDHhTyZAvR0jbaK3zJ9gAtD\nP6iiWdrLcOuNr0qlYqzwIJfUiwYTLKmPn2ZjIJodX6IMV5QcpvlathV509LLUSi70oBwxxeJD3XT\nsrOzM1Hxp1bjsTiFU1VApXDqLZzKomnahFM6SUlYUCQlhCSOyUJ3vaxRkb0UB2G6RmWHkwkL7UbC\ngxCudcoHTJpqtToiu46iWW1MHl+mZsqmiUaOLTG+asWMqPdsW+IxyEhadRTWG19i3NQbXyReGjVj\n0ol6wqlwOMvjq9X8bz/NoWTh1HEcd9zLP28Tfpu+ic8iLcIpM0lJWFAkJVpjsnhG7EW3DvVhuEbV\n8sxCoZBIREBYsEx/W8TCWLiD8/l84u4UU2km31ReFMYxviiamU0t4cFrfIk5knAHFwoFnmfLkO/Z\nuVwusGjWzPjScePHRoI2Y9IJMb7kCqooxlcrwqn8+mF/ts1mZ0YBhVOW25Pw4CgixpMGITUN79EE\nZNdoW1ubVlmjYoLTims0DaXWjcr0TS2j9oMozxwcHASwtXt5e3u78e9LJ1rpSB1W/qSAOZT2Io8v\nuaxV3J/kazxNGz+2Erdo5ldckct5xf2L46t11OiEYrFoZUWH33LxqIRT8SV+JxCPcKoD9eYm4vP3\nEk7DnJsEoVnxuVwuxx5xRuyEIinRHh1250i06CwC6+oaFROasFyjNk7MGyGXUReLRQDmlFH7Qc2U\nbW9vp2gWI63kT8rCqR+83MG2bnSkGa+GW17uYK98ZiEEqGWuvA/oh9eGVlLP5lY2fijM+yOpZkw6\nEadwKt8nhUjqRzi1UTQFPpibyJgknNaDmaQkLCiSEkKIB0IkE86cpFyj4ljoGo2HemXU4vPTudu5\nV6m1qWV7NlIrH1Dkt5VKJV+LQtmBVK1WUSwW0dHRocUYJOEhN9wC0NBpFnVjKBIN6salrhtaXuOL\nwql/dGvGpButOJqbFU69ckprCafiXim+n8Kp/sIpM0lJWPDOTLTGz01XZxdiWKThPepA2K7RIOdN\nTNYqlUportFMJmNtOVdUyJN2UcLjp0w/7gWubZmyaaFRfpsqzIvS6kqlgra2tlQ6kNJAtVp1u9S3\ntbUFarjlt3GPqY55k1Ebq5m4cVlLOBUbP/WibHQSV6LEpGZMutHI0RxGxnw94VS4SymcbkUWTsX8\nRLhvxbMmyWubmaQkLDiKCCGpRyfXqJh4BHWNskFPdNQr0xeiQ39//wjRQQjcYY4pNbeOiy87UIV5\n2R1cLpfdcSSEcZFNSTeg2Xhdz1G4wFtp3MP8yfDwyhu1rbFaJpNBPp8f4ehKm6PZpmZMuhGHo9mv\ncCr+H4C7qUXhNBzhtBWTCTNJSVhwxUysgdml5pKEU1a3rNGwXKOiBBfYmmfGEtx4iLNMXy3BTWum\nrO14neeuri73PKuiQ6VScRcwdAOagw45lMyfjB4dznOS1HM0y2KiGItqhq4ppKUZk27ELZzKEVaO\n46BQKKCtrW2EkCqOS96YspFWhFP5c2/02Tdz7TCTlIQFRVJiPGmYeLDcPjxU12ixWEShUNDCNSoW\nB0Fdo0FKM0k41CvTr1QqLZXpi7HL82w3asOtWue5njBPN6D+qPmEuuVQNhId6pVR2yoGtILu5zkp\nWnE067z5w2ZM+hGFcCpvdmQyGc/rWc41VRtDieNKo3AqDCHC0CE+n1aE01owk5SEBUVSQoj1JOUa\n9RK3w3KNernM2tvbrZ1w2YA6YffKBlTL9Nva2tzFomjEZFtpJvHuXt5saWarbkCdGo/ZjrypZWI+\nYb2okVpl1EKcT9v4siFvNG5a7XgeRZyNX9iMySwaNbcTmz9CvJPHl3AIN8qJFs9teRzXE07FWsB2\n4VRs7Mo0Ek7F9/ido1QqFV5/JBQ4iggh1kLXKNGZek4auXM5APd7xHhhvIgdyJsdooFTmKWZ9Zw0\n9RzNdAOGi1qCa1MUSq0yavG8K5VKxrgBg5KGvNG4iaNxTyuwGZM9qPcwYGTOfKlUcudiYmyJ+xzg\nr6KRwqk39YRTseE2MDDg23GaFifppZdeiptuugnjxo0DAFx22WX49Kc/nfBR2QVFUmIFwrFn24Rb\nxuZy+zDjBHTLGgXg7krTNUrqoboJ8/k8CoUCstlsXVErrU4tk0kyOsGPozktolbUyC6ztJTgioWr\n3DxDdQMKUUs8E03PN1XzRplDGS1x5E96wWZM6UHMx8QzWhgswmw+1kg4FV9Aukr1hXCazWZRqVTQ\n2dk54hkiHKfz58/Hn/70JxxyyCE49NBDMXXq1NSIpJlMBueeey7OPffcpA/FWiiSEmIAnGg3RlfX\naFtbG/r7+1tqqCKX6+VyOWaZWYoqpHi5Cb1ErXpOrSTLD4k3cpd6naIT/GQDJuHUMhlVBE+7y8zW\nKAjmjepDENd8ozHGZkzpQXYIe4ng9ZqPRS2cCodp2oRT+b3J8+ATTjgBEydOxPLly3HzzTfjr3/9\nK9ra2jB+/Hhs2LAB06ZNQ3d3N3bZZZeE30E02Gye0oFMgw+Ynz5JFDGxaXTTf//99xNzC8ZBtVrF\nhg0bsP322yd9KJEgSik6Ozub+jkv12ixWEzMNSpEEOGQEV+q4CC+p1bDHrnUulAouG5CYg9e0QmF\nQqHlLCUxxoRwKrqKerlNubCLF1vchGqJqzzGVDdgGlFF8GKxOCIigzRGFrXEGAP0i4JQRfCk5h2k\neeS5WKMxxmZM6UB1CAcxWajCqRyzFeZ9TBZOxZ9lbBBOq9UqBgYG0NXV5fv7b7nlFqxcuRI77rgj\nli5dimXLlqFQKKC7u9sVTadNm4YPfehDER99tPzHf/wHbrnlFowZMwbd3d2YM2cOxo4dm/RhmUjN\ni5wiKdEavyLp+vXrMXr0aGsnqbaLpMIJ5/dBqKNrVExQxISk0Zj1mkSJ+7HYqaY4ah9qWaYQwaMY\nu7Lb1GsxyDL96PASwW0UUhoJDmkYYyJDmEJKNNQbY7I4H/Xn7dVcjc9o86klaglEdUdSc0wSHfLG\nlnAI5/P50M+zapQQX61UmNXDj3Aq7lcm3LeaFUkB4Kc//SkKhQJOPvlkAFs/+9deew3Lli1zRdOl\nS5eis7MTs2bNwr/+679GdfiBOeqoo7B27dpt/v4HP/gBent73TzSf/3Xf8WaNWtw8803x32INlDz\ngmO5PdEaTki2EmZmp6kIcUkIqklnjcqu0VaaMImfEa8lmnlks1lXeBWLbhsy29KOLJg16owaFplM\nBvl83ndDFTHOOMZax+YGPV600rTHligIdi+PB68x1qjbeZjCKfNG7UZ224n5l8gEF25SMfdkTrMd\nyNd0JpOJfGOrVtxI2PcxP82hhIAql+rrKpy20mukXC5j1KhR7p8zmQz22GMP7LHHHvj85z/vvu6r\nr76K/v7+UI83bB566CFf33fqqafi2GOPjfho0gdFUmIFFBHtRXfXaCuNmFTBrNYErVZmm7rzrNvE\nhmzFK4MyySYP9RqqVCoVz1xAWTgltVGzCdPqJmw0xkzPN/VyE+qQK5smGgkO4vwEHWPMG00HXs2Y\nvK5pP6KWLRtAtiLHJ8S1WV0LXYRTuYu8qGiTq+FMe7b5adyUyWSw5557xnRE0bBmzRo3a/Wee+7B\nwQcfnPAR2QdFUkIMopVdNROxzTUKjHSY+RXMvBoRyBMory7UnKQnj1cjpihKuMKg1kRdFrSSKm/V\nHXVxTTehN42a9tRrqKLLAk0sroeGhlwRmG5CfZDHmBDoW20MJeeNFgoFXtOW0mwzpkb3MdM3gGym\nWq2613Qul9P2mtZZOJVfX5fnsheVSiUV3e0vuugi/PWvf3UF3+uvvz7pQ7IOiqSEGIDtkyvhBLbR\nNRq2YFav9NDLQUMnYDzYJJg1KtNXJ+lpK9OXBTMAFMxaQN4AKhaLALw3gMLObGsW2fWfy+USdR6R\n5mi0yaiK8+LfRdMtOoTtJMxmTF5jzI84n6bnZZLInerz+XyilTytUk84VaszgszJagmn4kv8TkBv\n4dSPk9QGfvKTnyR9CNZDkZRYAcvtzUWIL+Vy2XVu2OAalUsyoxTM6jlo5GMA6ASMgjQIZrVKqGst\nBG3tdJ5ErmyaaCZ7MsqcZq/yWxMX12RbvMaYEMxEmSkAT0cgr3OzkTesc7kcOjs7R4ibYVFPOBVz\n3VrOedXVTFpDzElsvX83cjWHJc6rTWiFSOpHOA3j825lXZ8WkZRED0VSQkgiyK5R8UDdbrvtrHON\nJiGYqZP0ek5ANoVqDbkkM5/Pp04wa+TSskWc98qgtG3BpSutLATFOGtFbGCDnvSg5o12dna64ybu\nxlAkWnRwEzb7vNQxckR31Az4tN2/43A1e+WU1hJOxXgW39+qcNrs+RseHo5k84OkD44iQgxBTN5N\nfuCrWaPCNSp21+N8b3KnR1HWKRbjzTzI43SNtoofJ6CXs4FNKkbilSvLkswP0MUJGAbMoNSTVsWG\nevcyVTBL24ZHmvCTN9pMeStLqPXEBDe41/NSnpfJkSMmbzRGjdfmlq4Z8HGTtHAq3KVhC6f1oJOU\nhAVFUqI1fh9yLLfXm0ZZo+JBGge2uUZbxU9TqP7+fjaFwrZl1mntXN4szToBdSjTT7tD2ETqiQ1i\njKn3sra2NndxLRxmum1ukXBQHWatbG4FuZexhDo+THaDi3Hid6Mx7a5mdSOzvb2d8zIf+BFOS6WS\nWzpvmnCalsZNJHookhJCIkGerFYqFS2yRsN0jYr3ZNPCupmmUDoIWlFigkPYRJpxAsbVsCcMEYXo\nQz2xQc0ElBtDie/jItsO1LzosB1mLKHWB7UZky2CWavdzm3e0HYcB4ODgyOc/yyvDkazTe5aydH1\nI5zKfxb/Lv7e7z2TTlISFryrEGIQJrhlvVyjo0aNSixrVDzkgWCuUVFmDdjZnMeLWk2h5JLDuAWt\nqDHdIWwiSZXpq+eaDmF7kaMy5AxKeRNIuGfUexkFLbNIMj7Bj6uZTsDwiKsZk040cjXbGgdRrVbd\nKo9cLsdN64hR72WA/02goMKpeP1KpYJcLrfNOk7eCFWhSErCwu4nCUkNaSi313li4+UaHT16dFOT\n1bDOX5iuUbnMmqW3W8lkMsjn8w0FLZMm517nmhPw5PBT2tqqoKWea9vc4GQkwg1e61wL4V1gY/Ox\ntOAnbzRuWi2httkJGAY6NGPSiTiyJ5OC51ofgginfs6Zeq5FRY/sKFUdp47juGM4k8mw3J6EBkVS\nQkjLhOUaDWOCFqVrtKOjQ+tJZJI0ErS8ynTkDtRJopZj8lzri5/S1kqlMqJ8Wha0ZCeh4zg81xaj\nNlgrFou+z3Uzrmb5Xqa70GArJkZlpNUJGBQTmjHpRD3hVI4d8dps1CFHV3Ze81zrS6MGZH6EU1kc\n9TrX4v/le6aXcPrWW29h4cKFOOmkk+J6+8RiKJISYhA6uGXDcI2GhZdrtJXgb7pGw0WenBeLRQDY\npqw1SaFBbcTEc20mjQQtITQIkVTEJ+TzeS62LCSK+IRmG/bIG0E6CA22ojZtEde1qZ93M81U0hYH\nYXIzJt3QPUdX3fTguTaPWu55OapLiN/ivDqO07RLWBZOX+tEaZYAACAASURBVH/9dVxxxRV44YUX\ncNFFF2H69OnRvDmSKjINRJfkFRmSakQGTaOb5pYtW9DW1ob29vaYjix+NmzYgK6ursTylhp1qA9C\nuVzGwMAAtttuO1/fL0/qhPghvprBy0lIASUe5EYq4lxG2RRKdZcVCgUUCgWeawuRHUci0yqbzbqT\ndICNVGxCLrPO5/MoFouxl1nLDi25ooHjLFzUvFFxrtMioshzn1rjzJZcZbUZEzOj40F1Aor7mrxh\nFHY1kJcQbvKmB6mNGFsDAwOoVqvueRZjTY4d2bx5M3K5HMaMGeP5Wi+++CLmzp2Ld955BxdccAEO\nP/xwjhnSLDUHDJ2khJCaxOUa9ZspK0/aWnWNAiNz6ugaTQYvh1Yz5dN+YXOe9OC16eHlQpHHGRup\nmIluZdaNHFocZ8HQMW80CWqVtsoOrf7+fqPHWRqbMemEnxxdtRqo1XGmCuHt7e2cn1mK/Mx2HMdT\nCFfH2e9+9zucd955+PCHP4wpU6Zg6tSpmDZtGnK5HK699loMDw/j4osvRk9PT4LvjNgKnaREaxzH\nQalUopMU8TpJo3SNelGpVLBlyxbP3cJqteo6DoO6RoXgKzIJ6STUG3XCVKlUfJW1ismYKB3L5/Mo\nFAqpXFSnATU+oVl3mZ9xlvY8QF0wucy61jgTzaM4zkbiVXob5TzEFtRxpjq0dM3RVZu2FItFzs80\nptE4qyecejnCKYTbieoSblYIL5fLeP7557Fs2TIsWLAATz/9NF588UXsvvvu+NjHPoZp06ahu7sb\nU6ZMQUdHR5RvhdgJnaTEbtLS3T7K96hT1iiAEaXYQVyjqoDCnWpzaKUplBg3mUyGeVYWowrhQRo7\ntDLOWD4dL/J9PJfLoaOjw7hFdbP5plHEjpiAyUK4DrSao5uEcMpmTOZSa5zJc3e1AVk2m0WlUnGF\n8LQ6wtOAvKbMZDItr71yuRzWrVuHe++9FxMnTsS9996L3XffHc8++yyWLl2KpUuX4tZbb8Xzzz+P\nffbZB93d3e7X5MmT3b4IhDQLnaREa/w6Sfv7+5HJZKzeRdq4cSM6Ojrc8pewEBNUsSBpb2+P3a0h\nnKSjR48O1TXK/En7kc+1ENTF2KE7yz6SFFBUFyDLp6PFSwhPw328Ue5k2HmAuiAy6Ft1hJPmUIXT\nOHN0mUGZHuRzXa1W3b9PWqAn0SBHKARxCVerVTz44IOYN28eJk+ejAsvvBC77bZbze8vlUp45pln\nXOF06dKlGDduHB5++OEgb4fYT82bDkVSojXNiKQA0NnZGcdhJUKYIqmXazTJcpdyuYzNmzcjn8+7\nk6VWxFHVNVooFOgatRRVCBeLLNGgRxUZqtVq6roC24TanEdc20kilxsKkUEHd5bpqNmyaRdQ1NxJ\nr7JW0ZzMxM9ICOEss06eqAV6NmNKF8K1LDa5isWiu5GtCvSO42zjoFejlIi+OI7jGm5E1V4rLuHh\n4WH86le/wo033oiPf/zjOPfcc7Hzzju3dEwizoaQOlAkJWbiVyQdGBiA4zhWi6SbNm1yM7laRTg1\n5PKHpDK+5KxR+b9+Midl6BpNF60K4Y1cgCaLDLbi1ZxH92vbjzuLooA3dBL6Ry1rNU2gZ96oGQTJ\nnZSRr+1cLqfFJheJBrVBj3huNzNH8xLoubmtJ2qjNfHcbpahoSHceeeduO222/DZz34W3//+97H9\n9ttHcMSEjIAiKTETiqQf0KpIqptrVM0aFTmj4hzXExnkHWbxYKZr1H6iKLtt5AKUm1uQeJEn3Ta4\njVimXxs1k5BOwtZJsny6mWOUnYTMGzWPZhqQCXGULmH7CTtCQTjoZdFU5M3bHj1iAvLGR5Bru7+/\nH7fddht+8Ytf4Itf/CJmzZqFUaNGRXDEhHhCkZSYSTMiabVaRVdXV0xHFj/NiqQ6ukaFENVMOb1a\naigm5ACQzWbd0luW5diHKpZFvaAWE3LZnQVsK9BznIWP+OzFxocQwm1s6uCnTL+Rg9501AW1X7cR\naQ7VnSVEBjV6JOrPnU5Cu/ESs8T6sq2tDfl83n128xq3izgjFMJyNpPWEZuaQTc+Nm7ciBtvvBH3\n338/vvnNb+Jb3/oW2tvbIzhiQupCkZSYiRBJG02sSqUShoeHrRdJhQu0Frq6RoWoqbpGm3kdWSwT\n2ZOyKxWgmGUDOoll9bIA2RQqHOS4jGZK82wjLWX68r2cFQDx00hkkB30YZwT5o2mB6+Nj2w2y/Jp\nS1Hv5UmtNSicxoMsjsr5ss2ybt06XHvttXj00Udx2mmn4cQTTwy9ITEhTUCRlJjLwMAARVLAbWzk\nJZLq5hoVwlKzrlEZtcRaOEa9xDKKWeajNmvRVSzzcswA9olZUUOxrDGq29TkHF1VLLPVJWwitRrd\neZW0+hlrzBtNF804CWs5m7nBbQ6qK7zVDMooMT2zWSfk5ltB7uVr1qzBVVddheXLl+Oss87C8ccf\nzw0SogMUSYm5+BFJxQPb5hwTVSRNi2u01RLrRs4sZhnpgdqIycRmLWwK5Q+v/EmKZf4xrUxfbapH\nscwcvDYdgfqbQexcni7CiFCgC9AcVCeh7k0UVRptBlE4/QC1+VaQfNlXX30VV1xxBV5++WWcd955\n+MxnPpP6z5doBUVSYi6lUgkAKJJu3uxORGXXaLFYbLnsISiqa1Q4AqJ0jQY9Xi9nFt2m8aKKJyZO\nuOtRz8WgjrU0YIpL2ETq5egmtRlkW+MtMrKJivr8zGaz7r8JZxnzRu0lrEzCWvjZDOJcLR7UjU3b\nNrq8zBSO43g6m215z/UIUxxduXIl5syZg/Xr1+PCCy/EYYcdFsERExIYiqTEXCiSbn1wbdq0yZ08\n2ugaFYJvnJ1uG5VO020aLmkWT2o5s+JuoBInNriETaOemBW1s1kspuVut3QJ24m8mBbjCwDFLEtR\nxbIgmYRBfn9YkRCkPmGKZabh5WwG7M7SlSsTxVqs1bn5k08+iblz58JxHMyePRvTp0+P4IgJCQ2K\npMRc/IikosRr9OjRcR1WLMhZo47jIJ/Po6ury3jXqCyeCNeoLs4Tuk3DJS6XsGmoZYbiutK1dNov\n6vm2zSVsIo3y2YIIDGr+JM+33TRqtFary7m6GcTxYQZqMyadxLI0illRE6ZYZgvyxmOtsWaqoUKN\nSGlvb2/5fSxcuBCXX345xo4di9mzZ+Oggw6K4IgJCR2KpMRc0iaS1soaHRwcRFtbG9rb22M9njBd\no2JxBZhTcstGPa2hnm+dFle6YnKOrlxSn8lkWs4SJvEQtExfXVzxfNtNkLzRemIWm/XoiYn5sqqY\nJe5tmUzG6oqNMJDPN6s+GmN6lq7X+W7FqOI4Dh555BFcddVV2HPPPXHxxRdj0qRJERwxIZFBkZSY\nS1pEUrVDvZo12t/fj0wmg46OjliOJUrXqK4TB7/U6zotJuNpdZsKF6FN5ztJdB9raom1Tq5w4h8h\nMKiREOpYE5t4QZq1EHMIozmPih+Bgc3uksGEzuXNwLFWHzkCyYbznSQmCKdhne9qtYr7778f1157\nLaZOnYrzzz8fu+66awRHTEjkUCQl5uJHJC2XyxgYGMB2220X12GFQjMd6uMQScNyjXo1asnn89aW\nPdUqZ5XdC7q7MILg1cXa5vOdJDo0hWKJdTqQx1q5XHYdgMKZlc/nWc5qIV75k1Ff340iIUyNHzGF\nqJsx6YSfsZb05mPU1DIvkHDRZayFtflRqVTwy1/+EjfddBM+8YlP4JxzzsG4ceMiOGJCYoMiKTEX\nG0XSRq5RL6ISSYVrVDzAhWsUQFOTZFtdo62i5k3q5gAMA7Uxj3AZmfyeTER1L1QqlUjcC2luvJVG\n1M0ucb5ZOm0njfJGkzieepEQzJwMhpofbVvn8maolaVrW5dzWQzn5mYyNGpCFqZwKoujQTY/BgcH\n8dOf/hS33347jj32WHzve9/D2LFjAx0bIZpAkZSYiy0iqZiQlkqlhq5RLwYGBuA4Djo7O0M5HrpG\n48WP29SEBR8b8+hPmE2h1M0Pcb7pOrEXeWHVKJ/Ob5m+6RtCNmNS/mS9zUcdyllNQOdmTDphS2Mo\n1RmeZjFcV7yydIOI9GGJ4Vu2bMGtt96KX/7yl/jyl7+M73znO+jq6mrlLRKiKxRJibmIzu71HgyV\nSgVbtmzBmDFjYjwyf7TiGvUiDJE0LNco8IGLUGTb0EXYPI0WfDplZakuQjZqMYt6riwvB6BurjIS\nLepCOojrpJ5TJq5ICNIYefPD1DzCejmA6lhL+73LJDFcR+TGUF4Z4bqJ9HIsjuM4FMMNoxWRfnh4\nGKVSyTUwtLLWBIANGzbghhtuwIMPPoiTTz4ZJ510EorFYmjvjRCNoEhKzMVEkbSWazTI5CmISCo/\nbIFgrlE5e5IuwnDRIW9SPR66CO2kngMQgDvuKIbbjeoqi0oMZ4dzPUgibzRu/Ir0ppdO+8W2Zkw6\n0ahZTxJOevmeLowZFMPNRxbp1edoNpt1x2KrRhwAeOedd3D11VdjwYIFOP300/HlL3+ZjRmJ7VAk\nJeZikkgalmvUC7E76LfUIQrXKLMn46dR3mQUblOvCAW6CO1F3CfEPUYICNVq1chICNIY2RmexD2d\nDsB4iUsM15VGriwx5mz6PNLUjEkn4sycVH+vcAo3ikkh5iPf00Vpvhh7qrtZXv95sXr1alx11VV4\n6qmncPbZZ+O4447jvYKkBYqkxFz8iKTDw8PYtGlTIkHSUbhGvfArktI1ajeyuCBcgGG5TdXyyzQ3\n3koDfsRwkyIhSH1kZ7gQTnRyhrNMP3zYbM2bRlm6upVO+4XNmPSkVuZkGBuQdAqnC3nNCWybKey1\nAXnqqafixRdfxJQpUzBt2jR0d3dj8uTJWLNmDS6//HK8/vrrOP/883H00UfzXkHSBkVSYi5CpNNN\nJPVyjUYpItYTSb1co0K4oGvUftTFXjNuU4rh6UO9xpvZ1Kkn0qvlhUQPTM6XreUAVMUFE95LnMiZ\n4cJFSOGkPo3ubTq7m9mMyTyCupuFU1hEIdEpbDdBYhQGBwexYsUKLF26FMuXL8eyZcvwyiuvoFAo\n4PDDD8cxxxyD6dOn48ADD2R5PUkbFEmJuegkkspB6OVyGfl8Hu3t7bEs0oRTddSoUe7fyZMsx3Fc\nx2gYrtF8Ps9FlaH4EbIymYzrOKEYbj+qwyhMMbzZplAkHmx0EbJMvzZpyBuNGy8HIKBPh3M2Y7IH\nv+5mcc55jacD9RoPsuZcvnw55s6di7a2Npx99tnIZrNYsmSJ+/XGG2/gkEMOQXd3N6ZPn47p06dj\nn3324fgiNkORlJiLmAzUu0lXq1Vs2LAB22+/fSTHELdr1AshzI4aNWrEBCqIa5Qdy9ODmHyXy2VU\nKhWIe38ul6OQZTHVatXdAMlkMrFc4/UWe2kXsuJAdRjpVFIfBWqZvri/pSVLly7CePHKCc9kMrG6\nm1linQ7kZp7iC4A73pJoDEXiwStjtlWX54IFC3D55Zdjp512wiWXXIL999/f8/s2btyIZcuWYcmS\nJVi6dCmWLFmC9957D//yL/+CCy64IMjbIURXKJISc0lKJE3SNepFqVRyS+cABHKNyo4y3XLpSPjI\nQhkAd7KlumRYNm0PslAmrvEky6i8hCxgpCOLDqjWkZ9XosNtPp9P7fWrg5AVNUk33yJbibPDOZsx\npQuvDZBcLrfNeDMlFoI0Rr6vB9kAcRwHf/zjH/HjH/8Y++67Ly688ELstddeTb/OO++8g1KphN12\n263pnyXEACiSEnMRzrdGIun69euxww47BP59OrhG1eMRDkCRKScm3s10ZKVrNF3ITVpkoazeeKlV\nNm2TsGAzpuXLsilUcMQGCMtt61NLyDJRWGDeqP406nAuz90ajTc2Y0ofclNFP/mT9SJv0uCmt4Gw\n3OHVahW/+c1vcN1116G7uxvnn38+PvzhD0dwxIRYAUVSYi5+RFLHcfD++++3LJLq5hqtVquuOKpm\njapZk2oZq5hIZTIZukZTiOo8EGJ4K5NjVVig21RPbMmelEsL2d28PhTKgmNSmT7zRs3Hj5Al37cZ\no5A+HMfB4OCg6w4PUmJdrzEUI5b0QRZHg7jDy+Uy7r77bsyfPx9HHHEEzjrrLOy0004RHDEhVkGR\nlJhLlCKprq5RkTUqckYbvXevxgKZTAbVatV1jdJ5YDdqx/KoSi/ZpEcPZKewKL20cQPEK9sUSKe7\nOcrmW2QrupXpUyizF5Hd7LXpDcDdIGLVj/3EkTHbKBYibc/TpJGjM4I8y0ulEu644w789Kc/xXHH\nHYczzjgD2223XQRHTIiVUCQl5tKMSLr99tv7Ll1Sd+6Scl7Vc402g/y+RBmh7Dyl+88+1BzCJEST\nRm5T1d1MgiGX1DuOk7oNkDSON7X0kqJJfPgZb1GU6TNvNH1Uq1WUSiV3o1NsdDNv0l6SzpiV729C\nqOd4ixZ5nVYoFFAsFlv6bDdv3oxbbrkFv/71r3HiiSfi29/+Njo7OyM4YkKshiIpMRc/IikAvPfe\ne3VFUhtco7VeR27K4yWaMGvSLnTPl63lbqbbtHUomtSm3nhT8/9MQnaH53K5hpnCJB78NCFrdSNS\nbbjGGAX7aSSU1YqFYAyJuahCmU4VAY3ydG3ciIwaNS4lSK7w+vXrcd111+GPf/wjTj31VHzjG99A\noVCI4KgJSQUUSYm5BBFJbXaNNtuUR/35Wu4YTrr1RJ1kmVReLcoK1bJpTrrrY/I5T5pa2c1hd5sO\nG2ZPmkmjJmT1NoYYo5A+1CqQZkUT5k2aR9BzniS1Ym/YGKo+8jl3HCdQXMrbb7+Nq6++GgsXLsQZ\nZ5yBL37xiy3n1RJCXCiSEnNpRiQdO3asW2Kuo2u0Wq0CQKSu0VZRJ0HiM2en6WSRS22BcM95ktBt\nWhtbz3mS6N4UitmTduG3TF+IowDPeRqI6jr3kzfJOVwy2Hpv1y2/WSfCPOdvvPEGrrjiCjz33HM4\n55xzcOyxx1KMJiQ8KJISc6lUKiiXy75E0lGjRo1wVybtGhXCo2iglIRrtFXqZRWJSRDLfaND7V5t\ne6ltLbdpNpvdRsSy9TNQm2+JUltb32/SeC3y4m5iITfs4Dm3Gzn2plwuu5umugj1JDrExtfg4GBs\ncSn1NoZYwRE98jnPZrOJrkfigI2hRoqjwqDT6jl/+eWXMXfuXKxevRoXXHABjjzySGs/N0IShCIp\nMZdGIqlYZA4MDCCbzaK9vd0K16iXmyyfzye6gKpXUqhzCaspyE15kmrEpBO2Zk3KsNRWH+JqCsUY\nhXQi543K7vBWy/SJ/sTRtbwZGj1TKdQHR80PF0JZGvEj1NuwblA3QYJsdq5YsQJz5szBwMAALr74\nYnz0ox+N4IgJIf8/FEmJuQh3lRpkr2aNlstljB49OpHJSFiuUQCuYBKna7RVvCZAoqGALSJWHLAp\nj39qZU2a5jaVozPYsVxfajW9ayUWQi3BY4yC/TS7CeKn2zTdf/qTdNfyZgiSp0s+QDdBXFcaNYaS\n1w26jznHcTA4OBiKIL506VLMnTsXhUIBl1xyCaZMmRLy0RJCPKBISsxFFkmFmFQqlQBghGt0/fr1\nGD16dKyTkjBdo2Lx7DiO0W4yW0SsqFEXz3STtUajTtO6CfVq92ohiBMzaCUWgpsg6SPMTDo/7j+O\np+QxuTGPTL2yac7jtsUkQVxX6jUi09HhLD/TgwjijuPgL3/5C6688kp86EMfwuzZs/GRj3wkgiMm\nhNSAIikxl0qlgoGBgYZZo3GJpKprNJPJtPzwVjMIbVw8myZiRY1wEIqcKjoIw0c3oZ4xCnbjdY8T\njnohOIjnFjdB7Mar1DaK51utexyb9MSPrY15ZGxy/4WFEMSFQ7xYLKbmvUeN2IzUzeEsu4WDCOKO\n4+APf/gDfvzjH2P//ffHhRdeiD322CP8AyaENIIiKTGXSqWC999/v6GwsGHDBnR1dUXmygrbNZpm\nwcRrgWdzOWGt5lt0EMZDI6E+KieWLJikoXEDGSmYCBEBAEUsy/HKG41TEGeZfvwk0YxJJxq5/2zc\nAJfdwnLVl03vUVf8NIaK6rkallt4eHgY9957L66//nrMnDkT5557LnbZZZdQj5UQ0hQUSYm5eGWS\nehGFSErXaDzUKydsNvdPJ7wyCJNuvkW2Us+JFaQJmSqIJyGYkPhpJIg3ErHkMUfMQC2v1m3Ds16e\nrq0iVhwwe9Ib2f1Xy+Fsy1zORrewiTRyOAetHJLF0SD393K5jJ///Oe49dZbcfTRR+Oss87CDjvs\n0PTrEEJChyIpMZckRFK6RpNFzf1Tu0zrLihQEDePWl1YZZG+3jmUr3U6TNKDmjHbjGASZlMoEh/C\nQTg0NATAHMHEj4hFh3NtmD3ZPH4czjrnm8puYVaDmEG9+Bs1cqkWcpRCkGzhgYEB3H777bjzzjtx\n/PHH4/TTT8fo0aODvD1CSLhQJCXm4lck3bhxIzo6OpDP51v6PcI1Kh6swjUKoOmJMEWy8KklKIhJ\nT9KLO91dRaR56nX9FeMOgCuO8lpPB1Fd67XKCU0RFGwnrrzROKm1OZTmrEkZW5ox6YSf+JukN8G9\nrnXGI5mL38ZQ1WoVpVIp8LW+adMm3Hzzzbjvvvvw9a9/Haeccgo6OjrCfluEkOBQJCXmErVIGqZr\nVJ5Ms1t5tNRzKPjdLQ4DtcyWjZjsRRYUxBew9Z6Ry+WQz+cTX9yR6JAdhJlMJpZrPak8XfIBSeeN\nxg3L9FleHTeqiFWpVNznapxl+iJKYWhoiM32LEZ11ctrQHGPa+U+99577+G6667Dww8/jO985zv4\n2te+hkKhENXbIIQEhyIpMRcxaQlTJA3TNUqRTB/kEn0x+YmilFCMHVGOQ0E8HahltsI1qor1LF+1\nC7kyIJfLJd50Lao8XfIBXg7CtOZJq/E3No85x3FckYyVAcnRqElP2GMurOxJYg5eGyHZbHabcSfG\n3EMPPYTdd98dBx544DbrzLVr12LevHlYvHgxvv/97+OEE07geoAQM6BISszFr0i6adMmtzyi3mvJ\nzoigrtGhoSGKZBpTy23qN2fS6/VUkYyld/ajxmfUK7OtV74ap8OZBEO9x+u8cOaYC48k3MIm4rdM\n35Qxx2ZM+uOnSY+Yz/m5XtXNbkYppANZHM1kMnVzZuUxd95552HBggVYvXo1DjroIEydOhX77rsv\nlixZgjVr1uC8887DMcccw/FDiFlQJCXmElQkpWuUyPjJmVTdCWpzFiGI87zbS5gimVcpId2memJq\nUx4VL+cfgNjLV03BxrzRuKk15nQu02czJrNpFA3htUEku8QdxzH2Hk+aQ27CFSRndsOGDfj973+P\n3/3ud3jppZewdu1alMtldHd3Y8aMGZg+fTpmzJiBXXbZJYJ3QQgJGYqkxFxaFUmjcI3KpTh0GdiB\n6oiRM/+AreNIDnHnAspuqtWq24gpKieZLnm65ANkJ5mNIplavioy2Fp1YdmC/GxnRUi46Fqmz2ZM\n9iJnTaob4WKcibzT9vZ2RimkADVCo729veV7/NNPP405c+agXC7j4osvRm9vLwDgrbfewpIlS7B4\n8WL3vx0dHa5gOn36dEyfPh1jxowJ860RQoJDkZSYi1+RdPPmzW7zFNk1KiZGQVyjoiSDu832I7pb\nlstlVzCoVqvIZrPbCFgcC/bg5RaOM3cyrjxd8gFe2cJpcpJ5iQmA3s6/MKBIlhyNSqajLNNnM6Z0\nIjdjkud0Xm5TjgV7kNdwQSM0nnjiCcydOxejRo3C7NmzMXny5Lrf7zgOXnnllRGi6Ve/+lWcdtpp\nLf1+QkhkUCQl5uJHJK1Wq9i8eTMAbDPpaQYxgRf5g0mIJSR+GmXM1uswLQunnGCbhVg0Dw0NoVqt\napU7Wc9tamLmn06oYgmzhT/A5qZQzBvVE68GPUB4z1fVSWabS5x4U08kqyfWs5rDbOSqkCAbn47j\n4NFHH8WVV16JXXfdFbNnz8Y+++wTwRET07jgggtw//33o1AoYNKkSbjllltcl/Bll12G+fPno62t\nDVdddRWOPvrohI+WNIAiKTGXeiKpOsFpNQdLLrEFuGhOC0EyZtWmFcPDw9uUrnKCrSfqea8X3K8T\nzJkMhpo7yc7VjbGhKZTtUQq2EVZnczZjSideRgc/572eWG+zs94WwsoXdhwHDzzwAObNm4eDDz4Y\nF154ISZOnBjBERNTeeihh3DEEUcgm83i4osvBgD893//N5577jmceOKJWLJkCVavXo0jjzwSL774\notbzI1JbJKU9jhiHyIisVCpwHMctg5ZvQrIbplQqeQpYmUxmm8lUR0cHJ0GW4+UW7urqanrxJERV\n9XWHh4dRLpdRKpUA0G2qC+p5LxQKLZ33JMlkMsjn88jn8wC2FROEI5Zu05GouZOmnfckEY0O5c9L\nHXNqNIQu9zr1vI8aNSr114IJeI05NRpCRCV4ifWqWMLzng7k814oFJo+7yK3VH6+yhuTYi3BGBy9\nCHre5df59a9/jRtuuAEf+9jH8Itf/ALjx4+P4IiJ6Rx11FHu//f09OBXv/oVAOC+++7DV77yFeTz\neeyxxx7Ye++9sXjxYje7lpgFRVKiPWLyIe/uNsoa9ZrsyALWwMCA+725XA6dnZ10FFmO2rW6UCig\no6MjtHOeyWSQy+VcxwoFLD2QS+odxwn9vCdJPTFBjo8A0uc2VaMUisWiNec9abyer/XudXE2hfLK\nG+V5Nx/5+SqQx5zIFRbkcjl0dHRwXmc5aq50mNe7uF+pm+Gys97rXmdyJIlJiPt80PM+NDSEO++8\nE7fddhs++9nP4v7778f2228fwRETG5k/fz6+8pWvAADefPPNEYLorrvuitWrVyd1aCQgFEmJ1oiF\n7j//8z9jypQp6OnpwYQJE1oWloR4IBo8iQlWqVTaxpXAybUdyO7Btra22NzCrQhYdCWEh1pabUpJ\nfVBUMSFtYr2pUQom0+heF4ezXmyCiWgennf7Ec9KBypVNAAAIABJREFU4fgTgpZozDM4OIj+/n42\nXbQQeTPEcRwUi0V0dnYmOq/zqiIK0iOBbIvXJlir531gYAC33XYb7rrrLnzhC1/Aww8/jFGjRkVw\n1MREjjrqKKxdu3abv//hD3+IY489FgDwgx/8AIVCASeeeGLN1+GzxlwokhLtyWQyOO6447Bo0SJc\neOGFWLNmDfbcc0/09vait7cXBx54YM3GShs3bsTPfvYz7L333ujp6UGhUEB7e7vnZEUuq5En1zY0\nrEgb6kQqSAlOmNQTsIRwalren054dStPe2l1M2K9ydEQ4rwHidAg4eF1r5OfseVy2S1dDSJgqbmT\noiqE2I3ajKnW5mczZfpEf+Sme5lMRovNELWKCPCOJBHfl6aKjrDwEsVbbbq3ceNG3HTTTfjtb3+L\nk046CX/+85/R3t4ewVETk3nooYfq/vutt96KBx54AI888oj7dxMmTMDf//53989vvPEGJkyYENkx\nkmhh4yZiHNVqFatWrUJfXx/6+vrw3HPPoaurC9OnT8fMmTMxffp0vPjii7j55ptx33334WMf+xgu\nuOACdHd3N/VAVctq2NFcf2xwkanNeeS8P4r13nhFKbDxmn9Ut2mlUkmsXLoZvDZDCoUCBQ9DUDtM\ni5xxVUjwOp9q3mirTTqIWYTRjElt0EMBS39kp7iJzdfqNSOjy7k2YYri7777Lq655ho8+uijOO20\n03DiiSe6kTGENMPvf/97nHfeefjzn/+MnXbayf170bhp8eLFbuOmVatW8ZrWG3a3J/biOA7ef/99\nPProo7j55pvx2GOPoaOjAx//+Mdx2GGH4ZOf/CR23333UBZQ9Tqa21a2agpe7kG/3UxNoFZ3aXli\nbZoQHBZqlIJpCyedUR1YOrlN1dLqQqHQsquE6IUq1quNUgC4+cLFYpGbISkhSlGcApa+hCGK64q6\nSSTmduqaQrfNyTgIMz5lzZo1+PGPf4xly5bhzDPPxPHHH2/NGCLJsM8++2BoaAg77LADAGDmzJm4\n5pprAGwtx58/fz5yuRyuvPJKfOpTn0ryUEljKJISe1mxYgWuv/56/OxnP8M//MM/YNasWTjiiCPw\n9NNPY+HChejr68Prr7+OD3/4w+jt7UVPTw+mTJkyIoy9VeSyVbmpFDtfRk+a3YP1hATb3abCPSjK\nxOkejAe1XFrdJIrDbSpE8aGhIXczhKXVdiNvgolqDgDcnEwBXvmDcT3jg7icSXDk+JRCoZAap7jX\nMxaA53PWRrwcw60+41977TVcccUVWLVqFc477zx85jOfsfZzI4S0DEVSYhelUgl33303rr/+erzy\nyis45ZRTcOqpp2LixIme3+84Dl5//XW3RP+pp55CPp/HtGnTXOF0hx12CPwAVTMm6foLHzV7ULhG\n0/yZ1ouGUB0JplKtVt2yK7oH9SAOtylF8fSiusiEKO61OQno4XImwZFLbAEEyh8ME5bpR4/csZz3\n+g82J9X7neyut2HcyVFZQR3DL7zwAubMmYP33nsPF154IQ477DCjPxtCSKRQJCX2MDQ0hEmTJuHA\nAw/ErFmzcMwxxzSdK+M4DjZv3ozFixdjwYIFePzxx/H+++/jIx/5iCua7rvvvqGV6Hu5/uSO5mks\np2kGsWgSjY04eW6MKtabOu68RHG6B/Wkltu0lbJV1Smui1BCosUrPqWRi6xWubRXd2mOH32RhRIT\n4lP8ZDlz3DUmScewidQyY5g47sKMU/jrX/+KOXPmwHEczJ49G9OnTw/5aAkhFkKRlNjFu+++ix13\n3DHU1xweHsazzz7ruk1feukl7LTTTujp6UFPTw+mTZuGjo6OUNymumb96YaaOSkEMn42zWPSuKMo\nbg/1xp2Xy1leNJkglJBwkK95x3ECx6d4lUsD6SlbNQlxzYsYDZNzJ/2MO5bpb0VXx7CJmBYPIT/n\ng2YML1q0CJdffjnGjBmD2bNn46CDDgr5aAkhFkORlJBmcRwHa9eudXNNly1bhmq1iilTpqC3txcz\nZ87E+PHjQxFNZfeV7EZQ3VdpQC2vZefiaPCbMRnn5y47iYKG9RN9qeVyFmPSdKGE+CfMBh2NqDXu\n0pDlrCNyMyabN8IaNSPTaYMyDuQqgaAdy0ltvNz1QLIb43K+dJBr3nEc/N///R+uvPJK7LHHHrj4\n4oux9957R3DEhBDLoUhKSFAcx0GpVMLSpUvR19eHRYsWYe3atdhzzz3R29uL3t5eHHDAAaGUAqvi\nVaVSsX4xpwpkzJyMn1quvygz18TvFI5hMXGmQGY/wklUKpUAwD3njdymxHzka17OG40TNctZLltN\n4wZlHLC0Or1l+o7juI7hoE15SPPUiiWJY20xPDyMUqnkZs0Wi8WWfke1WsXvfvc7XHPNNZgyZQou\nuOAC7LrrrqEeKyEkVVAkJSQKqtUqVq1ahQULFqCvrw/PPfccRo0ahRkzZqC3txfTp0/H6NGjQ2sI\nZVtjHlUgo4NMLxot5oJ0llZL7YKW1xJz8JM92ChT10YRwXbUvFEd3YO1ukuzOU8wWFpdn0axJCYL\n9mHmTpJwqbdRpMaStHKtyo24gmyIVCoV/PKXv8RNN92Eww47DOeccw523nnnpl+HEEIUKJISEgeO\n4+D999/HokWLsGDBAixevBilUgkHHXQQenp60Nvbi4kTJ4baEEqe3CRZKt0MalMWCmTmoHZalV3O\n8rirdS5VgYw5s+lA3hCpVCpuEy6/i2VmTJpL2HmjceLH9WdKE7wkMK0Zk06YXqYvl1YzNskc1Dle\ns4K97BZ3HCfQhsjg4CB+9rOf4fbbb8cxxxyD733vexg7dmyg90cIIRIUSQlJinK5jCeffBJ9fX1Y\nuHAhXn/9dUyYMAG9vb3o6enBIYccgkKhEPj3NCqVbiRexYHaiIkLJvOp12lVdpqKUjuRM8uS+nQQ\npUDGjEm9iTNvNE6abUaWRugeDB9TuprL7kEd3eKkefwI9tls1i2rB4K5xfv7+3Hrrbfi7rvvxpe+\n9CXMmjULXV1dYb8tQgihSEqILjiOg9deew19fX3o6+vDU089hUKhgO7ubvT09KCnpwc77LBDaCX6\n9cSrOBas7FSePoSTQHxVq1UAW0WEfD6vhWBPoiUJx3Ct0kG5VNoGkU53xGaYDd3K/SAajlGwT08z\nJl3wU6Yf1zwv7VmzaUJdX1QqFQg9IZfLuV/N3vM2bNiAG264AQ888ABOPvlkfPOb30SxWIzqbRBC\nCEVSQnTFcRxs2rQJixcvxoIFC/D4449j/fr12G+//dwS/X322SeUhYact6buBoe9kGOn8vSiOobF\nYkkul6Z4ZSeixFKXJlz1HDBpEq+ixoS80ThR4yG87nmmZkyqUCDTi3oO+7DL9Jk1m168KgWAkc9c\n2ZjxyCOP4JBDDvFstLRu3TpcffXVeOyxx/Dd734XX/nKV9jUixASBxRJCTGJ4eFhPPvss1iwYAEW\nLlyIVatWYaeddnKdptOmTUN7e3ukDaHkxZzf3yMWS0NDQyyrThnquW8kktQSr9iYxzy8RJJ8Pq+l\nAOTHbWqLeBUHbMDmH7WztJrnrHvGpAoFMjPwU6bfbK6urVEapDHyuRexWbUETTHu+vv7cdJJJ2HZ\nsmUoFAqYOnUquru7se++++Kxxx7D888/j7PPPhvHHXccn72EkDihSEqIyTiOg7Vr17ol+suWLQMA\nTJkyBT09PZg5cybGjx8fmgNU7e7bqJt5tVp1S+oBLpbShDj3YrFUKBRaOveNGvMw508/1HNv6kK5\nUd4a4yG2hZUCwWkkXsn3PJ0+VzZjMh8/zXm8rmevc0/HXzqQz32rOcPVahWvvvoqHn74YTzyyCN4\n9tlnsWbNGuy5556YMWMGenp6MGPGDBx88MGh9GoghJAGUCQlxCYcx8HAwACWLl2Kvr4+LFq0CG+9\n9Rb22msvVzQ94IADQnFwek2mM5mMuygSoqrsGuViyX7ksmpx7sNeLNUqG1QzdTne4sX2zMlablPV\nYZ9Gx4vt5z5p6olXrVR3hAmbMdlLo1xd0ZRH7lTPc58Owrzun3vuOcydOxcbN27ERRddhI9//OOo\nVCpYsWIFFi9e7H69/PLLmDx58gjhdNKkSZzrEULChiIpIbZTrVbx0ksvuSX6zz33HEaPHo0ZM2ag\nt7cX06dPx6hRowJPMuTdZMdxkMlk4DgO8yVTQNJNuOo1qUhaQLCdZuMUbKNRqbTNblPmjSaHEK/U\n6o44o0nYjCmdyHEK1WrVnesFKdMn5iCLo0IYb/W6f/LJJ/GjH/0IbW1tmD17NqZNm1b3+zdv3oxl\ny5aNEE4vueQSzJo1q6XfT/Tk7rvvxqWXXoqVK1diyZIlOPTQQwEAr776Kvbff3/st99+AICZM2fi\nmmuuSfJQib1QJCUkbTiOg/feew+LFi1CX18fFi9ejFKphIMPPhgzZszAzJkzMXHiRN+T24GBAQAY\n0YxHTJAb5UtyIm02upbW1hIQGsVDEP+I/LGhoSFkMpmW4xRso16ptC1uU2ZO6olXNIm6URl07LEZ\nU7oR515sihSLRVckrVemz1gc8xEbYmFsivT19eHyyy/HjjvuiNmzZ+OAAw5o+biq1arRz1OyLStX\nrkQ2m8WsWbMwZ86cESLpsccei2eeeSbhIyQpoObDikEyhFhKJpPBjjvuiGOOOQbHHHMMgK0C5/Ll\ny9HX14d/+7d/w+uvv45dd90Vvb296OnpweTJk0fkAJXLZdx///248cYb0dXVhdtvvx2jRo3aZqKS\nzWaRzWaRz+cBjFzElctllEolAHT8mYQ4h6JLfaFQQFdXl1YldkJ4l8esvIgTrkcA2wgIHHv1kc99\nLpdDR0cHPzcJETkiNowAjBDshfPORLepmjvY3t6uxaYI2Uomk0EulxsRbyJvVApxq5WxR2E8vcjC\nuOM4KBQK6OzsHHHu1bGnblSWSiVmOhuKKoyPHj26pXPmOA4eeughXHXVVdhnn30wb9487LXXXoGP\njwKpfQinKCE6QicpISnGcRy89tprbon+U089hWKxiP322w9DQ0N44IEHMGHCBJx66qk44YQT0NHR\n0fLvkSfSlUrFOteVLdjWrVp2/HHs1SftJfVh47cxjy6fL/NG7aHZscdmTOklbGG8Xqazzg3J0oga\npRLEMV6tVvHb3/4W1157LaZNm4bzzz8fEyZMiOCoiW0cfvjh2zhJDzroIOyzzz4YM2YM/uu//gsf\n+9jHEj5KYikstyeE1MdxHPzlL3/BVVddhT/+8Y+YMmUKxo0bhzfffBP7778/enp60Nvbi7333juU\nRb1aJi27ruQFHCfR8aAukuU4BduoN/bS6HyRS+oBuseixCseAkjO6UxhPD3UKpUW/ya7hon9iPv+\n4OBg5DE6te57LNNPBtU1HOSZX6lU8Itf/ALz58/HJz/5SZx99tnYaaedIjhqYiJHHXUU1q5du83f\n//CHP8Sxxx4LYFuRdGhoCFu2bMH222+P5cuX47jjjsOzzz6L0aNHx3rsJBWw3J4Q4s3GjRtxxx13\n4JprrsHw8DBOP/10zJ8/H2PGjAGw1V20YsUKLFiwAP/7v/+LVatWYdy4ca5oeuihh6K9vb3pyVUm\nk0E+nx9Roi/cB5VKZUSJPifR0aC6CPL5vHYl9VFQa+zJZfqq29RGwVhuzNDW1saS+hioN/aEkzMO\nt6mXe0wtrSV2IZdKi2fs8PDwiGzxLVu2jBDruVlpH+qGaGdnZ+TCuNd9r16ZPjfKoyFM1/Dg4CDu\nuOMO3HHHHfjc5z6HBx980F03ECJ46KGHmv4ZsVkLAIceeigmTZqEl156yRVRCYkDOkkJSSkrVqzA\nNddcg5///Oc44ogjcPrpp+MTn/iEr8yyNWvWoK+vDwsXLsSyZcsAAFOnTnWF0/Hjx4cysVXLBeWm\nPLLjjzQHnYONqdWMzPQFnJcwHqRrLQmfWo6/MNymaXKMk5H4acbk1RQKwDbPXY4X8xCbYkNDQ64I\nodOGqDr2dI8nMQlZHM1kMoFcw1u2bMH8+fPx61//GieeeCK+/e1vo7OzM4KjJmnh8MMPx49+9CNM\nmzYNALBu3Tpsv/32aGtrw9/+9jf8v//3/7BixQqMHTs24SMlFsJye0LISP7nf/4HpVIJp556aqDc\nIMdxMDAwgCVLlmDhwoVYuHAh3n77bUyaNAk9PT2YOXMm9t9//1Am4/IkWggIAEa4/UwUruJCbsbD\n3Lnm8MpZEyWqJjidbcuaTRP1cnX9igdCGC+Xy8wbTRmqQFIoFJraFPParLRhwygthNmtPG7k+55a\nps8moI2RIxWCzvnWr1+P66+/Hn/4wx9wyimn4KSTThrRNJOQZrnnnntw5plnYt26dRgzZgymTp2K\nBx98EL/61a/w7//+78jn88hms/jP//xP/OM//mPSh0vshCIpISQ+qtUqXnzxRbch1PPPP4/Ro0dj\nxowZmDlzJrq7uzFq1KjAE9t6zSlsLpNuBmYORkct8UBtCJXk+KNz0E5quU1V4UpsjPDaTx9RNWOq\n15iHzfD0IMyGPDqhbhhRtPfGcRzXNSyu/VYjFd5++21cffXV6OvrwxlnnIEvfelLzC0mhNgCRVJC\nSHI4joP33nsPCxcuRF9fHxYvXozBwUFMnjzZFU532223UCa1cs6VTWXSzVKtVl33UDabbdo9RJqn\nUalqnG5TIYyXy2UtSytJuKgbRpVKBWJ+p4rjvAfYjRDGh4aGYnMN13L8JdWQLK2E2ZDHFOqV6adN\ntJc3RnK5XKBrf/Xq1bjiiiuwYsUKnHPOOfinf/qnVHyGhJBUQZGUEKIXQ0NDWL58uVui//e//x27\n7babm2s6efJkN+Q/CKrrRRaubCzXUstqhThCksFPrm5YwpUoqxXNf2xxDxF/eLmGxd/L8SS23vvS\njhDHdHANN4qICPvel3bCzJy0gbSV6ctNGIPmjL/88su4/PLLsXr1apx//vk48sgjrfmcCCFEgSIp\nIURvHMfBq6++ir6+PvT19eHpp59GsVhEd3c3ent70dPTg7Fjx4bWEEoWrWThysTmAKo4lvQCmdSm\nVq5ukMWbLI5ls9nUL5DThrwxUs81rHaUjlq0J9HjpxmTLtS795mQ66wjYWZO2ky9Mn2d4nGaRc6b\nDSqOPvvss5gzZw76+/tx8cUX46Mf/WjIR0sIIdpBkZQQYhaO42DTpk14/PHH0dfXh8cffxwbN27E\n/vvv75boT5o0KRQh0CvfL5PJjFi86Th5pjhmPqpw1UxTHjbjSS9hZQ1HIdqT6BHi2NDQUEvNmHRA\n3PvYFKp5wiyrTisml+mH2Yxr6dKlmDt3LvL5PC655BJMnTo15KMlhBBtoUhKCDGfSqWCFStWuG7T\nv/3tbxg3bpxbon/ooYeiWCxG1hBKnjgnJUaKif3Q0JDrHmDepF3Uasojxp9wDjuOQ9dwypDFMQCh\nZw7Wcpua7riyhaiaMelCLeFKzTZN6/1OPPvlOB0++8NDdZtWKhVkMhltsnXlSI0grnHHcfDYY4/h\niiuuwPjx4zF79mzst99+ERwxIYRoDUVSQoh9OI6DN998020ItXz5cgDA1KlT0dvbi97eXuy8886h\nleirjitZOIi6TFXOHAPgimO2LI5JbeROxSJTF9jW7ZdW4SANJCmOsUw6eZJoxqQLXsKVcJvqIFzF\nQZjOQeIfHcr0xf23VCoFjtRwHAd/+MMfMG/ePOy333648MILsccee4R/0IQQYgYUSQkh9uM4DgYG\nBrB48WIsXLgQixYtwttvv429994bPT09mDlzJvbbb79QFpdxlal6NWNhSX16kJ1DuVzOPf+q208V\nDnSNiCDN4TdvNG68GpLRbRo+OjVj0oValR5eor3J40/eHAvqHCThobqdK5UKHMcJ3e0s5w07jhOo\namB4eBj33Xcfrr/+evT09OC8887DLrvsEuj4CCHEAiiSEkLSSbVaxQsvvOCW6K9cuRLbbbedm2va\n3d2Nrq6uUEr0a2VLNuv2UxdHLKtLF63kTeocEUGaQ23GY4I45iUcAHSbtoJJzZh0oVZEiYnZumGK\nYyQewizTV6uG2tvbW352l8tl3HXXXbjllltw1FFH4ayzzsKOO+7Y9OsQQoilUCQlhBBg6wT03Xff\ndUv0lyxZgsHBQUyePNl1m+66666hLEjquf28mlJEnTdI9Cbs818rIoJNUfTEtuufbtPmsKEZky6Y\nmK0ri2OZTIaNGA1GLdNXGzJ6jb8wz3+pVMJPfvIT3HnnnTj++OPx3e9+F9ttt13Yb5MQQkyHIikh\nhNRicHAQy5cvx8KFC7Fw4UK88cYbmDhxous2Pfjgg5HP5wP/HjFxlt2mAFyH2PDwMNra2tDe3m6M\n64UEp1qtuiXVUeZN1hp/dPsli+3NeASN3KZpdTun5fwnjZ/xl0S2sxDHBwcHef4tplaZvqgQkud/\nuVyupd+xefNm3Hzzzbj33nvxta99Daeeeio6OjrCfBuEEGITFEkJIcQv1WoVr776qlui/8wzz6BY\nLKK7uxszZ87EjBkzMHbs2ECLGLmkTkyOhYiligY6l9mS1vCKVCgWi7Gfa7r9kkPXvNE4qTX+0uB2\nTnMzJl2o57aPOttZ3hzL5XI8/ynDcRyUSiXXOZ7NZrcZf37L9N977z1cf/31ePjhh/Htb38bX/va\n11AoFGJ6J4QQYiwUSQkhpFUcx8HGjRvxxBNPYMGCBXjiiSewceNG7L///m6J/l577eVL4Fq3bp1b\nQpnNZrcpqazVEEoIBmzIYzZq3pgQx3Q5n/XcVqZl++kI8ybro7qdbczWZTMmffHbFCrI+VI3R5LY\nHCPJITvHVXHcq0x/3bp1+PrXv47u7m50d3djxowZ2HvvvZHNZvHWW29h3rx5eOKJJ/C9730PX/jC\nFyi0E0KIfyiSEkJImFQqFTzzzDOu2/SVV17BzjvvjJ6eHvT29mLq1KkoFovuYv7JJ5/Etddei/vv\nvx+33XYbDj/8cF8lVfUWbbJwarJokAbUklrRpd6E86aKVsL5rIpWJryXpGDeZOvYkK1LcdxcvLJN\nATTdlIfieLqRncPNVI4MDg7iiSeewOLFi7F06VIsW7YMAwMD2G233bBhwwacdNJJ+P73v4+ddtop\nhndBCCFWQZGUEEKixHEcrF692m0I9eSTT8JxHIwZMwZr167Fm2++iZNPPhmnnHIKxo8fH/h3ybmS\nJooGaUF0qa9UKsjn81aUVNdyO9Ntui3MmwwfP27TJLIlax2rLI6zGY/5qG4/r40jefxRHE83wjks\n5gBBnMMvvfQS5s6di/Xr12PGjBnYtGmTK56OHz8ePT097teUKVNYck8IIfWhSEoIIXGxdu1aXHfd\ndbj++uvxoQ99CDNnzsTrr7+Od955B3vvvTd6e3vR29uL/fbbLxTBrF5DHopW8SNK6oeGhlKxMG7U\nyTeMElXTsFEc15kksyVrHQ/F8fTgtXEk1leZTCaxzGmSHLI4GtQ5/Mwzz2DOnDkYHBzE7Nmz0dvb\nu83vev755/HEE0+4X6tWrcLBBx+Mnp4efOtb38KUKVPCeFtEM+6++25ceumlWLlyJZYsWYJDDz3U\n/bfLLrsM8+fPR1tbG6666iocffTRCR4pIVpCkZQQQqLEcRwsWrQI8+bNw4MPPogvf/nLOOOMM3DQ\nQQe531OtVvHCCy9gwYIF6Ovrw8qVKzFmzBg313TatGno6uoKZSFdr0Q6jaJVHMjCSDabTbVrTIgG\n8hgE7M7WZUm1PtRym6obR2HfA9mMKd3IzmEAbqRO2pqSpRk5ViHoM2Dx4sWYO3cuOjs7MXv2bBxy\nyCG+f3bz5s1YtmwZnnjiCRx22GHo6elp6RiI3qxcuRLZbBazZs3CnDlzXJH0ueeew4knnoglS5Zg\n9erVOPLII/Hiiy9y3k/ISCiSEkJIFFQqFdx+++2YN28eNm7ciDPOOAPf/OY3MXbs2IY/6zgO1q1b\n55boL1myBOVyGZMnT3azTXfddddQFlFeolUmk0nMaWUTciMOCiPe+MnWNVW4Z96oGagl0pVKJTS3\nKfMm043jOBgcHBzhHFYzx5MS7kn0hLlB5jgOHn30UVx55ZWYMGECZs+ejX333TeCoyY2cfjhh48Q\nSS+77DJks1lcdNFFAIBPf/rTuPTSS7dxIROScmrepBt3DSGEEFKTbDaLhQsX4gc/+AGOPvrophY4\nmUwG48aNw+c+9zl87nOfA7A1pH/58uXo6+vDJZdcgjfeeAMTJ050RdODDz4Y+Xy+6ePMZDLI5XLu\nwk0VrURpuE1dpKNEXRQVCgWMHj2aC9wayIK8yEmTs3VFabpJTiu5EUdbWxs6OjpYUq0x2WwW2WzW\nvX/Wugf6Fa28hJHOzk6e/xQh3wNyuRy6urpqbpDJ90D554VgKu6B4lndTFMokgzyPcBxHBSLxZY3\nyBzHwYMPPoh58+bhoIMOwk033YSJEydGcNQkDbz55psjBNFdd90Vq1evTvCICDELiqSEEBKAbDaL\nG2+8MbTXKxaLmDlzJmbOnAlg6yLqlVdeQV9fH26//XasWLEC7e3t6O7uxsyZMzFjxgyMGTOm6Um5\nl2glL9gGBwfR39+PbDY7okQ67V3MhWtwcHAQ2WyWrsEAiKw+VbSqVCojxCfdhHs1b3TUqFEUxw2k\nWeFeHn8ic5jNmNKJ2oyn1XtAPeFejEE535nPYT0QueODg4OB7wHDw8O45557cMMNN+CjH/0o7rrr\nrsDNPYldHHXUUVi7du02f//DH/4Qxx57rO/X4T2DEP9QJCWEEI3JZrOYNGkSJk2ahG984xtwHAcb\nNmzAE088gQULFuCaa67Bpk2bcMABB7hu07322iu0BZtYrJXLZZRKJQDpbAilZg12dnZuU05JgtHI\naSUL93G7Tb1cgx0dHakY+2milnAv3KbCMQYA+XzeHYMcB+lAjVUIe4PE6x5Y7zks3wc5BqNH3SRt\nb29vWRwdGhrCnXfeidtuuw2f+cxn8Jvf/AY0bCqyAAAgAElEQVQ77LBDBEdNTOehhx5q+mcmTJiA\nv//97+6f33jjDUyYMCHMwyLEaphJSgghhlOpVPDMM89gwYIFWLhwIf72t79h/Pjx6O3tRU9PD6ZO\nnYpisRh4EeU4zginldzF3MZMNfFeh4aGmDWoCWquX6VSARCdYKAuiukaTB/qBkmhUBghXKlNydK0\neZQGdGvIJp7Dasa4SVElpiE/B2plzvplYGAAt912G+666y6ccMIJOO200zB69OiQj5ikjcMPPxw/\n+tGPMG3aNAAfNG5avHix27hp1apVvCcQMhI2biKEkLTgOA5Wr16Nvr4+LFy4EE8++SSy2SymTp3q\nCqfjxo0LrSGUvFAzLVfSC7VDcZCcMRI9akMoIRgEiYlQswYLhQKdwynDbzMmtURa3jxS74PEHOSS\nakDv54Aq2oumUKpwzzHYHHJDrlwuF6gp48aNG3HTTTfht7/9LU466SScfPLJaG9vD/mISdq45557\ncOaZZ2LdunUYM2YMpk6digcffBDA1nL8+fPnI5fL4corr8SnPvWphI+WEO2gSEoIIWnFcRz09/dj\nyZIlWLBgARYtWoR3330Xe++9N3p7e9Hb24uPfOQjoXRkj9vpFyZqIx6xINLxWEltZMFAjEPAX0yE\nmjdaLBYpLKQItRGLEEebvQd4Of0Auk1NwBb3uCzcqxuYHIP1UTfJgoij7777Lq699lr86U9/wqxZ\ns/DVr361peabhBBCQociKSGEkA+oVqtYuXKlW6K/cuVKjB071s017e7uDq1Ts5fTT21EkZQQJcQM\n4RijMGYfakyE1xgUrjEdymlJ/Mju8SiaMdFtqj/VatUdA0FLqnVEzdcVblOvDcy03vtkcTToXGDN\nmjWYN28elixZgjPPPBOf//znQ9mIJoQQEhoUSQkhhNTGcRysW7fOLdFfsmQJyuUyDjnkEFc4nTBh\nQmgl+l5OP7k8OuoSfZNKKUn4yHmzwu0smqakrSlZmvESxuI677XcphyD8RKma9A0OAa3IjZKK5VK\n4Ozx1157DVdccQVeeuklnHfeefjsZz9r/edHCCGGQpGUEEJIc5RKJSxfvhx9fX1YtGgRVq9ejYkT\nJ7ol+gcddFAoZWP1HC5qrmRQkhRFiB545Y22tbXR6Zci5GZMQhRJWhhT3aa1XPdpdvqFiSyMsYJg\nK7Vc93LGs4k547UYHv7/2LvzqKjr/X/gz9kYdhAFFXHBDXFHlplxS6/Zcrt2LU2vedPc8qqZXrcL\nVt+y37W63VDRUit3s8wWzcosd2OGVRRxA/ctcEcEZNbP7w/PfO6AoAYDM8M8H+d0SpPhPfp2dJ68\nFjPKysrEucM1WXCZm5uLBQsW4Pr165gzZw769etXL36OiIjqMYakRERUMxaLBWfPnhVb9HNycuDl\n5YXY2Fio1WrExcUhICDA7guhrP+u7kIoa7WM7axJZwhFqO5UZ6xCxSqrijP96qLimeyn4h2oacVY\nXajJfF2qXMWFXDUJxtxBxaVQFeeMu+JSKNs7UNPxKocOHUJiYiIsFgsSEhIQFxdn59MSEVEtYUhK\nRET2JQgCbt++jdTUVGi1WqSlpaG4uBgdO3YUW/TDw8Pt8ubpQQuhqgoLrC31BoOhRktYyHXZ8w48\nSsWzq4UF7sBey5icwaPM12W16f3q0x1wBhWr7m2/iOmsX0CqeAdqOmInNTUVCxYsgL+/PxISEtCl\nSxc7n5iIiGoZQ1JyvMLCQowfPx5Hjx6FRCLBqlWroFarHX0sIrIjk8mEw4cPi9WmZ8+eRZMmTaBW\nq6FSqRAVFQWlUmmXz2UbmtqGBVKpVHxDZG2ndsXtxFR9dbWh+kFhwR+teCb7qu1lTM6C1aZV4+zp\nuvGoS6Ec8QUk698FysrKANTsDgiCgN27dyMpKQmtWrVCfHw82rZta+8jExFR3WBISo43evRoPPbY\nYxg7dixMJhNKSkoQEBDg6GMRUS0SBAGXLl0SF0IdPHgQMpkMPXr0EKtNGzVqZJc3rdY3QmazGRKJ\nBIIgOH11C9mX7axJa0t9XY5VqFjxbA0LbMOq+hjUORN3nzvsbnMlK1NXXyShqlV2BwGUu4O1+fvS\nNiCv6RdJLBYLtm3bho8//hjdunXD7Nmz0bx581o4NRER1SGGpORYt2/fRlRUFM6cOePooxCRAwmC\ngNLSUqSnp4sLoW7cuIF27dqJ1aYRERGPHGwZjUbxDbHFYhGrRKzVpJVVtzCwql+cfdZkVdWm7hJY\n1RVnXMbkLB42V9J6F139DlYWkMvlckcfi/Boi8ns8VpYMSD39PSs9t02mUz49ttvsWLFCvTt2xf/\n/Oc/ERISUu2zERGRU2FISo516NAhTJw4ER07dkR2djaio6ORlJQEb29vRx+NiBzMYrHg+PHjYot+\nbm4uGjRoIFaaRkdHw9vbu9ybnOvXr2PVqlX47LPPsH79ekRHRz9S4PmwwIrz/FyHq86cdZfAqi44\ne0DuzCp+AcmVw3uLxQK9Xs+A3MU8aFTEH30ttA1HaxqQGwwGfPHFF1i3bh2eeeYZTJ06FYGBgdV6\nLCIicloMScmxMjMzodFooNPpEBsbi+nTp8Pf3x/vvPOOo49GRE5GEARcu3ZNbNHPzMyE0WhE9+7d\nERYWhpycHPz000948skn8eqrryI6OrpGn4vz/FyLbbVYfWmlfVhgxfC+PC7isT9XDO+tAbnJZGJA\nXk9U9VpY1Zxn2z8P5HJ5jUaslJaWYs2aNfj6668xfPhwvPLKK/D19bXn0yMiIufBkJQcq6CgABqN\nBmfPngUAJCcn4/3338ePP/7o4JMRkbOzWCzYvHkz3nvvPeTl5aF3794oKSlB48aNoVaroVar0blz\nZ7u0VVac52cymbjB3Ek4et5oXWJ4Xzl3WcbkLJyx2rRi9bBSqWRAXo9VNedZJpOJ/08ul4tt9dVx\n+/ZtfPbZZ/jpp58wZswYjBkzxm4LJomIyGlV+RcHDuqhOtGkSRM0b94ceXl5aN++PXbu3IlOnTo5\n+lhE5MSKioqwatUqfPTRR2jQoAGmT5+OYcOGwcPDAxaLBWfOnEFycjLWrFmDI0eOwNvbG7GxsVCr\n1YiLi4O/v/8ffuNsrdbz8PAQv882NDUYDDCZTNxgXkcqa6f28/Or9yG1RCKBXC4XK6MqhvdGo7Hc\nPD9Hbo+uCxVnTXp5eXHWZB2QSqWQSqVQKBQA7g/vrRvDbWdK1lZoXbF6WKlU3jeGheofiUQi3i3g\n3mtBWVkZjEaj+OewdRnsH10Kdf36dSxduhT79u3DpEmToNVq+bpCRESsJKW6k52djfHjx8NgMKBN\nmzZYvXo1t9sT0X1OnjyJJUuW4PPPP8cTTzyBadOmQa1WP/ANjyAIuH37NlJSUqDVapGWloaSkhJ0\n6tQJcXFx0Gg0aNWqlV1CpIqVLa7QlupqbDcTA2A7dSWsgZVthRVQd9uj64I1IDcajZw16aT+aHv0\nH2XPLeXkuh40WqHiUiiTyYTc3Fz885//RGxsrPjF05YtW0IqlSI/Px9JSUk4dOgQpk2bhueee67e\nfoGJiIiqxHZ7IiJyfgaDAV27dsXzzz+PyZMnIywsrNqPZTKZkJ2dDa1WC61Wi/Pnz6NJkyZQq9VQ\nqVTo3r273VrqKgsKKlZX8U3Yw9XHeaN1pbKgwBVHRXAZk2urqj3a9g4+yu/pyhbxuHroT3+ctXrY\n+lqgVCof6Q7cvXsXaWlpSE9PR0ZGBjIzMyEIAkJDQ1FcXIzx48djypQp8PPzq4NnQUREToghKRER\nuQaLxVIrgYggCLh06ZIYmh48eBByuRzR0dFQqVRQq9Vo2LChXd6EVzVT0nYRD1v0/8ed5o3WJdsW\nfetdtFb5Ods95DKm+qtieP+galN7LuIh12TvubPHjx/Hhx9+CL1ej6ioKNy6dQupqanIzs5G27Zt\nxdnmarUaERER/IIMEZF7YEhKRERkSxAElJSUID09HVqtFikpKbh58ybat28vhqb2esNkW+VnDQkq\nVvm5W8UkKwbr3qPcw7quNrWtGGT1sHuoqtpUIpFAEAQxHOV8SPdS2dxZhUJR7deCgwcPIjExERKJ\nBAkJCYiJiSn3/w0GA7Kzs5Gamir+c+PGDcTFxUGtVmPEiBGIjIy0x1MjF/H2229jxYoVCA4OBgC8\n9957eOqppxx8KiKqJQxJiYiIHsZsNuP48eNitWleXh6CgoKgUqmgUqkQExMDLy8vu1Wb2s41tfcs\nP2dVcd5oTd8IU838kSo/e39e22VMDMXck+3cWWtlc8XZps5W9Uz2Ze8/E7RaLRYuXIigoCAkJCT8\noUWx165dQ1paGlJTU/Hkk0+iT58+1ToDuaZ58+bBz88PM2bMcPRRiKj2MSQlIiL6owRBwLVr18TQ\nNDMzE2azGd26dYNKpYJGo0HTpk3tFppWtRDKtsrPVUOCiqGYh4cHKwad0MNmStZ0MRmXMdGjtFM7\nY9Uz2Zc9l3IJgoCdO3di8eLFaNOmDeLj49G6detaODXVZ/PmzYOvry9mzpzp6KMQUe1jSEpERGQP\nZWVlyMzMhE6ng06nQ35+Plq1aiWGpp06dbJbRVzFsMp2IZRtlZ8zsw3FOG/UNVW1wbxiWFVVuMHR\nCgTUvJ3aturZ2WfsUtXsuZTLYrHghx9+wLJlyxAdHY1Zs2ahWbNmtXBqcgfz5s3D6tWrERAQgJiY\nGCQmJiIwMNDRxyKi2sGQlIiIqDZYLBacPn1arDY9evQovL29ERsbC41Gg7i4OPj5+dl1IZRtWCWR\nSJwuJLCGIQaDgaFYPWS7mKxi1bNtgA+Ay5jIrhWDFR+X1aauQxAE6PV6u4zYMJlM+Prrr7Fy5Ur0\n798f06dPF+dIEj3IwIEDUVBQcN/3z58/H2q1WrxHb775JvLz87Fy5cq6PiIR1Q2GpERERHVBEAQU\nFhYiNTUVycnJSE9PR0lJCTp37oy4uDhoNBq0bNmyVhdC2QYEddnSznmj7quyalMAkEgkUCgUYkjO\nu+A+7Fkx+Ec+p+0dZLWp49mOWrEu5apuN4Fer8eGDRvw+eef49lnn8WUKVMQEBBg5xMTAefOncOg\nQYOQk5Pj6KMQUe1gSEpEROQoRqMRhw4dgk6ng1arxfnz5xEaGgqVSgW1Wo1u3bpBqVTa5XNVtYjH\ndqakRCKxa0jAeaMElL8HUqkUCoUCAMR7CNSfGbtUNYvFUm4ZkyNHbDyo2tSVxpa4Itt7YP1CSXXv\nQUlJCVavXo1vv/0WI0aMwCuvvAJvb287n5jcXX5+Ppo2bQoAWLhwITIyMvDFF184+FREVEsYkhIR\nETkLQRBw8eJFsUU/Ozsbcrkc0dHRUKlUUKlUaNiwoV1b9G1DAsA+YRXnjRLwaMuYBEEoV+VnMpkY\nVtUzFe+BUql0yl/PysaWACj3esgAv/rMZjMMBkO5Pxeqew8KCwvx6aefYvv27Rg7dixGjx5tty8o\nElU0atQoHDp0CBKJBOHh4fjkk0/QuHFjRx+LiGoHQ1IiIiJnJQgCSkpKkJ6ejuTkZKSkpODWrVuI\niIgQq03bt29vtxb9qsKqR5njx3mjBNhnGRPDqvrBOnfWVV8PbKtNGeBXn/X1wGQy1fgeXLt2DR99\n9BF0Oh0mT56M4cOH220hIhERERiSEtUfZrMZMTExCAsLww8//ODo4xBRLTGbzTh27JhYbXry5EkE\nBQWJoWl0dDS8vLzsVm1a1Rw/a0AgkUjEMATgvFF3ZZ07azAY7L6MiYt4XIftpnqLxQKlUlmvlnIx\nwH90tiF5Te/B5cuXkZSUhJycHEyfPh1//etf+fudiIhqA0NSovpiwYIFOHDgAO7cuYOtW7c6+jhE\nVEcEQcDVq1fF0PTAgQMwm83o1q0b1Go11Go1mjZtatewymQyif8A95bwyOVyKBQKzhx1M7ZLeKRS\nqd02lD/K5+UiHufhrsvZHlZtansX3YE1RC4rK7NLSH769GksXLgQly5dwqxZszBw4MB6f6eIiMih\nGJIS1QeXLl3Cyy+/jNdffx0LFixgJSmRGxMEAWVlZThw4AC0Wi1SUlKQn5+P8PBwqFQqaDQadOzY\nsdotihXnC1ofxzawcteAwJ1UXMplDUcdpapqU9sKPwb49mcNyQ0GAyQSSZ2F5M6sqmrT+ryczLaC\nWBCEGofkR48exYIFC1BcXIz4+Hj06tXLzicmIiKqFENSovrghRdewNy5c1FUVIQPP/yQISkRlWOx\nWHDq1Cmx2vTYsWPw8fFBbGwsNBoNYmNj4efnV+UbWrPZjO3bt8PLywsxMTEPnCtX1UIoazjACj/X\n9ijLmJxFxQo/s9l837gI3sXqEQQBer3eaUJyZ1ax2rSqLyZJJBKXu4sVK4g9PT1rFJIfOHAACxYs\ngEKhQEJCAqKioux5XCIiooep8g8w/i2HyEX8+OOPCAkJQVRUFPbu3evo4xCRE5JKpWjfvj3at2+P\nMWPGQBAE3Lp1C6mpqUhOTkZSUhJKS0vRuXNnsdq0RYsWuHv3Lj7//HMsXboUXl5emDdv3gPDVOB/\nrfdyuRxKpfK+Cj+DwXDfPEl3rzxzdpUtY/Lz83P6CmGpVAqpVAqFQgHg/nERZWVlAHDfIh7exapZ\nLBYxJJfL5fDx8XHakNxZSCQS8Y5Z2X4xyWg0lruLrlBtahuOSiSSGoWjgiAgOTkZixYtQnBwMN59\n911ERkbWwqmJiIiqj5WkRC5i7ty5WL9+PeRyOcrKylBUVIQhQ4Zg3bp1jj4aEbkQo9GIQ4cOQavV\nYteuXcjKykJJSQm6du2KESNGYPjw4fD09LTL57KdJ8kKP+dVm8uYnEXFFn3rXay4EKo+PefqsN1Q\nrlAooFQqnT4kdyWCINw3Z9cZq01tZxBbK4irG+YKgoBffvkFH330ESIiIjBnzhyEh4fXwqmJiIge\nGdvtieqTffv2sd2eiKrt0KFDWLhwIbZu3YoXX3wRL7zwAn7//XfodDpkZ2dDLpcjOjoaarUaKpUK\nQUFBdl8IZQ2sANepqqpvHLWMyRnYVvjxLpbfUP6gMRtkf1WNLnFE5bM9xyuYzWZs3boVy5cvR1xc\nHGbNmoWmTZva+cRERETVwnZ7ovrGXd64EZF9WCwW/PTTT1i4cCHy8vIwdepULFy4EEFBQeKPefHF\nFyEIAoqLi5Geno7k5GSsXLkShYWFiIiIgEqlglqtRrt27aoVoFTWjmobmhqNxnJVVbbVpmQ/FZcx\neXt7u92cSdtxEVYPuovOUuFnT7ZLeKwbyr29vevN83MVlY0usa02LSsrq/XKZ9vXhJqOVzAajfjq\nq6+wevVqDBw4EFu2bEHDhg3tck4iIqLaxkpSIiKieu7rr7/G66+/Dn9/f8yYMQMvvPCCOL/xUZjN\nZhw7dgzJycnQ6XQ4efIkGjZsKIam0dHR8PT0tFu1acW2aNtwlQuhqs+VljE5gwdV+LlytWnFJTw1\n3VBOte9Blc81qTa1nT1b0/EKZWVlWL9+Pb744gs899xzmDx5Mvz9/av1WERERLWM7fZERETu6tdf\nf4WXlxd69+5ttyDzypUr0Gq10Gq1OHDgAARBQLdu3aBWq6HRaNC4cWO7tujbBlUWi6VcSOUuLeLV\nUdkyJrZSV0/F7eUmk0lcTuYKlc/uPF6hPqrJnF17zp4tLi7GqlWrsHnzZowcORLjx4+Ht7d3TZ8e\nERFRbWJISkRERLVDEASUlZUhMzMTWq0WKSkpKCgoQHh4ONRqNdRqNTp27Gi3lu6KQVXFcKC+tUVX\nR8VlTKwWrB2VVT4DKHcXHV35XHG8Qk3mTJLzepRqUwAwGAwwmUw1/oLJrVu3sHz5cuzYsQMTJkzA\nSy+9BA8PD7s9HyIiolrEkJSIiIjqjsViwalTp8QW/WPHjsHX1xexsbHQaDSIiYmBn5+fXVv061tb\ndHWwWtCxqqp8rngX66La1LaV2jrvkuMV3Iv1LhqNRhiNRgDlZ6BWZ7bplStX8PHHHyMlJQWvvvoq\nhg0bxntFRESuhiEpEREROY4gCLh16xZSUlKg1WqRnp6Ou3fvonPnzuJs0xYtWtglPKq4+MS2Lbqu\ng6q6wmpB52V7F633USqV3teib68g256t1OS6rF88KisrExdzKRSK+yrxgXtfULp27Rpyc3OhUqkQ\nGBh43+NdvHgRixYtwvHjxzFjxgwMGjSIX3whIiJXxZCUiIiInIvRaMTBgweh1Wqh0+lw4cIFNGvW\nTGzR79q1q93aN+s6qKorXMbkeqzVprb30R5zdq2b6q2zZ5VKpcvdZ6o562udXq9/pFEb1tA0PT0d\nb731FrKzs9G8eXPExMRApVKhRYsW+O6771BQUIDZs2djwIABvFdEROTqGJISERGRcxMEAefPnxdD\n0+zsbHh4eCA6OhpqtRpxcXEICgqy60Io22pToObbousClzHVP1XN2X1YiF8xELPeBWe8t1S7rHOI\n9Xo9AMDT07NaYbvBYEBOTg5++eUXJCcn4/DhwzAajejZsyc0Gg3UajVUKhUaNGhQG0+DiIioLjAk\nJSIiItciCAKKi4uRlpYGrVaL1NRUFBYWIiIiQnyj3q5dO7uFg5Vti7aGprZLeBylYgjCZUz118NC\nfJlMJo5YAHgX3Jnt64JEIqnxHOKMjAwsWLAAnp6emDt3Lrp164arV68iNTUVqampSElJQWZmJsLC\nwqDRaMTgtGPHjqxid0Pbt2/H9OnTYTabMX78ePzrX/9y9JGIiB4FQ1IiIiJyfWazGUePHhUXQp06\ndQqNGjUS55r26NEDnp6etboQqq43l3MZEwEQQ1ODwSDeRdslPNY7wXvhHmxfF2o6h1gQBOzbtw9J\nSUkIDQ1FfHw8IiIiqvzxJpMJR44cQUpKihicXrlyBevXr8ezzz5b3adELsZsNiMiIgI7d+5Es2bN\nEBsbiy+//BKRkZGOPhoR0cMwJCUiIqL6RxAEFBQUiC36Bw4cgCAI6N69uzjbtHHjxnZt0X/Q5nJ7\nhpdcxkRWld0FmUxWaYhfcUEZQ9P6RRAE6PV6GAwGyOVy8S5U97G2b9+OJUuWoFOnTpgzZw5atmxZ\nrce6fv06FAoFAgICqvXx5HpSUlIwb948bN++HQDw/vvvAwDi4+MdeSwiokdR5V+O+DdtIiIiclkS\niQRNmzbF0KFDMXToUAiCgLKyMmRkZECn02Hjxo24cuUKWrduLYam1W0LlUgkYvBkXShluxBKr9ej\ntLS0xguhKi5j8vHxYRurm7JYLGIgVtldsFaQKpVKCIJQ7j4ajUanGxlB1WcblMvl8hq9LpjNZmze\nvBmffvopevbsiY0bN6JJkyY1Ol+jRo1q9PHkei5fvozmzZuL3w4LC0NaWpoDT0REVHMMSYmIiKje\nkEgk8PLyQt++fdG3b18A98KFkydPQqvV4tNPP8WxY8fg5+eHuLg4qNVqxMbGwtfXt1oVdxKJBAqF\nAgqFAkD5WZImkwllZWUAHl7dV9kyJj8/PwZabsp6F0wm0yPfBWurvTXAB/53r0wmE4xGo3gfbe8i\nq02dmzUoNxqNUCgU8PX1rfbrgtFoxJdffok1a9bgqaeewtatWxEUFGTnE5O74OsGEdVHDEmJyO1c\nvHgRo0aNwtWrVyGRSPDKK6/gtddec/SxiKiWSKVSREREICIiAmPHjoUgCLh58yZSUlKg1WqxcOFC\nlJWVoUuXLuJs0xYtWlQ7NLUGT1a2C3gqq+6zzhYE7i3g8fb25ptPN1QxKFcqlfDy8qrRXbCdWWr9\nHNaREWazGQaDQRwZUbH6mRyrYlBek3D07t27WLduHTZu3IghQ4Zgx44d8PPzs/OJyd00a9YMFy9e\nFL998eJFhIWFOfBEREQ1x5mkROR2CgoKUFBQgO7du6O4uBjR0dHYsmULB80TuTGj0YisrCzodDro\ndDpcuHABYWFhUKvVUKlU6Nq1a7kKvZqwtkQbDAZxa7k1zKrLhVDkHKz3Qa/XQxCEOt9Ub1ttav23\ndWQE72PdqxiOKpXKav/c37lzBytWrMDWrVsxatQojB07Fl5eXnY+Mbkrk8mEiIgI7Nq1C6GhoYiL\ni+PiJiJyFVzcRERUlcGDB2Pq1KkYMGCAo49CRE5CEAScP38eycnJ0Ol0yM7OhlKpRHR0tBicNmjQ\n4A+HFxXnCnp4eEAmk1W6EMq2JZrb7OsfQRBgNBqh1+shkUjExVyO/nV+lAVlrDa1P2tQbq0i9vDw\nqPZduHHjBpYvX47du3fjlVdewd///ndxJAiRPf3888+YPn06zGYzxo0bh4SEBEcfiYjoUTAkJSKq\nzLlz5/DYY4/h6NGj8PX1dfRxiMhJCYKAO3fuIC0tDVqtFqmpqbh9+zY6dOggtui3bdu2yuAoJycH\nSUlJmDFjBsLDw6FUKh8YMtm2RFuDKqlUWq7a1DqDklyLdbyCXq8vt6nemX8tq7qPNVlQRvavIi4o\nKMCSJUuQkZGB1157DUOGDOHSNyIiovsxJCUiqqi4uBj9+vXDG2+8gcGDBzv6OETkYsxmM44cOQKt\nVgutVovTp0+jUaNGYqVp9+7dkZKSgqSkJBw5cgTjx4/HpEmTqrUoxdoSbRtSAQ9fCEXOo2IVsTUc\ndUW2C8qs95LVz4/O3uHohQsXsGjRIuTl5WHGjBl45pln+HNPRERUNYakRES2jEYj/vKXv+Dpp5/G\n9OnTHX0cIqoHBEFAfn4+9u3bh3Xr1kGr1aJBgwbo378//vSnP6F3795o3LixXcILQRDEoMUanLIl\n2jlZFyRZt5NbRyzUNw+rfma1qf1HLOTl5SExMRHXr1/H7Nmz0b9/f7f++SUiInpEDEmJiKwEQcDo\n0aPRsGFDLFy40NHHIaJ6wrokZdGiRQgPD8fMmTPRv39/HDhwADqdDikpKbh69Spat24NtVoNtVqN\nyMhIuwVmtqFpxQU8bImuexUX8Hh4eLhVaG1b/Wy9jwDKVZq6S/Wz7YgFqVQKT0/PGj337OxsJCYm\nwmw2Iz4+HiqVys4nJiIiqtcYkhIRWSZiAogAACAASURBVCUnJ6Nv377o2rWr+Ablvffew1NPPeXg\nkxGRK7p8+TKWLFmCFStWYMCAAZg5cybi4uIq/bEWiwV5eXlii/7x48fh7++PuLg4qNVqxMbGwsfH\nx27VprYt0e4cUtUVazBorwU89U3FhVD1fdZuZfNn5XJ5tR8vNTUVCxYsgL+/PxISEtClSxc7npaI\niMhtMCQlIiIisrdXX30VX3zxBV566SVMnz4d4eHhf+jjBUHAzZs3kZKSguTkZKSnp0Ov16Nr166I\ni4uDRqNB8+bN7RYaVRZSWUNTa0jlTtWO9mLvGZPuor7O2rXn/FlBELBnzx4kJSWhRYsWiI+PR7t2\n7ex8YiIiIrfCkJSIiIjI3nbs2IHo6OhqLWOqisFgQFZWFnQ6HXQ6HS5evIjmzZuLC6G6du0KhUJh\nl89VVUhlW9nHFv2q2XvGpLurOGu3YpBvOzbCGVksFuj1ehiNxhqHoxaLBdu2bcPHH3+Mrl27Ys6c\nOWjevLmdT0xEROSWGJISERERuSJBEHDu3DmxRf/w4cNQKpWIiYkRg9PAwEC7tujbhqYVF0IxBKy8\njdoVKx5dgTXItw1OAZSrNHX0z71tOKpQKKBUKqsd5JrNZnz77bf47LPP0KdPH8yYMQMhISF2PjER\nEZFbY0hKREREVB8IgoA7d+4gLS0NycnJSEtLw+3btxEZGSm26Ldp08Zu1Xa2lX22W8vdcSGUPSsF\nqXpsg3zrnbQG+XVdbWrP5VwGgwFffvkl1q5diz//+c+YOnUqGjRoYOcTExERERiSEhEREdVfZrMZ\nOTk5YrXpmTNnEBwcLFaa9ujRA0qlstYXQrnyHMkHsYZhRqMRHh4eNaoUJPur2KJvMpnEIL82xkaY\nzWaUlZXBbDaL96G6j11aWoq1a9di06ZNGDZsGCZOnAhfX1+7nJOIiIgqxZCUiIiIyF0IgoDff/8d\nOp0OWq0WWVlZkEgkiIqKgkqlglqtRkhIiF0XQrnqHMkHsS5jsoZhNakUpLrzKGMjqnMnbe+DUqmE\nh4dHtX8PFRUV4bPPPsOPP/6Il19+GWPGjIGnp2e1HouIiIj+EIakRERERO5KEATcvXsXGRkZ0Gq1\nSElJwbVr19CmTRuoVCpoNBp06NDBbq3jlc2RlEgktVbZZ0+2m+otFkuNwzByDhVb9B91bITtfRAE\nAUqlEgqFotr34fr161i6dCn27duHSZMmYcSIEXZbxEZERESPhCEpEREREf2PxWJBXl4ekpOTodVq\nceLECQQEBCAuLg5qtRoxMTHw8fGp1YVQtlV9jl4IZbupHkCNwzBybhXHRlR2JwVBsNt9yM/Px+LF\ni5GVlYVp06bh+eefZ1UyERGRYzAkJSIiIqKqCYKAGzduiC36GRkZMBgM6Nq1q7gQKiwszK4t+pVV\n9llDKmtoWtshpXVTvcFggEQigVKpdHhgS45hDU2NRqM4a1cikUAul1d7Sdm5c+ewaNEinD59GjNn\nzsTTTz/Nu0VERORYDEmJiIiI6I/R6/U4ePCg2KJ/8eJFtGjRQgxNu3TpYrdWYWuLvm1oCtTeQihr\nlaDBYIBMJhPDUXJP1rBcr9dDKpXC09MTUqn0vjAfuHcnT548icLCQsTGxsLHx+e+xztx4gQSExNR\nWFiIOXPm4LHHHqvrp0RERESVY0hKRERERDVjsVhw/vx5sUU/JycHnp6eiImJgVqtRlxcHAIDA+3W\nom+7tdxkMtll+Y7FYhE31cvlciiVSrvNYiXXYxuOPkpYbg1NN2/ejCVLluD48eNo37494uLiEBcX\nh6CgIKxfvx5SqRTx8fGIjY2tw2dDREREj4AhKRER1Z7t27dj+vTpMJvNGD9+PP71r385+khEVAcE\nQUBRURHS0tKQnJyMtLQ03LlzB5GRkWK1aevWre02e9E2NLUGp4+yfAcAzGYz9Ho9TCYTFAoFlEol\nZ0K6MYvFIo5ZqElYXlpaiqysLGzbtg3p6ek4fPgwvL290bdvX/Ts2RMajQY9evSAUqmshWdBRERE\n1cCQlIiIaofZbEZERAR27tyJZs2aITY2Fl9++SUiIyMdfTQicgCTyYQjR44gOTkZOp0OZ86cQUhI\nCFQqFdRqNaKioqBUKu26EMq22hRAuWVQ1kpBs9kMDw8PeHh4MBx1Y/asJBYEAbt27cLixYsRHh6O\n+Ph4tG7dGufOnYNOp4NOp0NKSgpyc3PRrVs3MTTt2bMnmjZtaudnRq6kVatW8Pf3h0wmg0KhQHp6\nuqOPRETkThiSEhFR7UhJScG8efOwfft2AMD7778PAIiPj3fksYjISQiCgN9//x1arRY6nQ5ZWVmQ\nSqWIiooSg9Pg4GC7LoSqbPmOQqEQg1OGpO7HbDbDYDDAaDTWuJLYYrHgxx9/xLJlyxAVFYVZs2Yh\nLCysyh9fXFyMjIwMMTRNSUmBn58fNm7cCLVaXd2nRC4sPDwcBw4cQFBQkKOPQkTkjqr8Syen0xMR\nUY1cvnwZzZs3F78dFhaGtLQ0B56IiJyJRCJBs2bNMGzYMAwbNgyCIKC0tBQZGRnQarX4/PPPcf36\ndbRt2xYqlQoajQYRERHVqu6ztuPr9XoAgJeXF+RyuThH0mg0oqysDADE9nxraMqN4/WT7ZgFDw8P\n+Pr6VjscNZlM+Oabb7BixQr069cP33zzDYKDgx/6cb6+vujfvz/69+8P4N49zcvLYzWpm3tIsRIR\nETkAQ1IiIqoRBgtE9EdIJBL4+PigX79+6NevH4B7lXm5ublITk7Gxx9/jBMnTiAgIECcaxodHQ0f\nH58qX29KSkqwatUqaDQadOjQAZ6enpDL5eKPl0qlYmu1tUXf2p5vMBjuWwhl+7HkmqxhuXXMgp+f\nX7V/TfV6PTZs2ID169fj2Wefxc8//4yAgIBqn00ikSAiIqLaH0+uTyKR4PHHH4dMJsPEiRMxYcIE\nRx+JiIjAkJSIiGqoWbNmuHjxovjtixcvPrDtkIioIqlUisjISERGRmLChAkQBAE3btyAVqvF3r17\n8d///hcGgwHdunUTg9NmzZrh+vXrWLZsGVasWIG4uDgMGDAAvr6+D/xcEolEnFnq4eEBoPxCKL1e\nj9LS0kdeCEXOQxAE8dfQbDZDqVTC29u72r9uJSUlWLNmDb755hv87W9/w+7du+Hj42PnU5M70mq1\naNq0Ka5du4aBAweiQ4cO6NOnj6OPRUTk9jiTlIiIasRkMiEiIgK7du1CaGgo4uLiuLiJiOxOr9cj\nKysLWq0Wu3btwsGDB3H37l307t0bo0ePxpNPPgmFQmGXz/WghVDW0FQmkzE0dRK2YxYEQYBSqYRC\noaj2r09hYSE+/fRT/Pzzzxg3bhxGjx7N7fRUa+bNmwdfX1/MnDnT0UchInIXnElKRES1Qy6X46OP\nPsKTTz4Js9mMcePGMSAlIrtTKpXw8/PD4cOHkZ6ejjFjxuD555/HqVOnsHv3biQlJcHT0xMxMTHQ\naDSIi4tDQEBAtYIy22pTK9vQ1Gg0wmw2iz/GttqU6o4gCDAajeIM2pqGo9euXcPHH3+M5ORkTJ48\nGVqtFnI53y6RfZWWlsJsNsPPzw8lJSX49ddf8dZbbzn6WEREBFaSEhEREZGTS05Oxn/+8x9kZGRg\n2rRpmDRpEgIDA8v9GEEQUFRUhNTUVGi1WqSlpaGoqAgdO3YUF0KFh4fbLci0tnZbg1Oz2VwuXOVC\nqNpjG45KJBIolcoazZG9fPkykpKSkJOTg+nTp+Ovf/0rA2+qNWfPnsVzzz0H4F43zsiRI5GQkODg\nUxERuZUq/8LAkJSIiIiInNLOnTvx1ltv4cqVK5g1axZGjx4NLy+vR/54k8mEnJwcJCcnQ6fT4ezZ\ns2jcuDFUKhXUajW6d+8OpVJplyCz4kIos9kMi8VSrj2fC6FqRhAEGAwG6PV6yGQyKJXKGo09OHPm\nDBYuXIgLFy5g1qxZeOKJJ/jrQ0REVP8xJCUiIiIi17Jp0yYAwJAhQ8q1vleXIAi4fPkytFotdDod\nDh48CKlUiqioKKjVaqhUKgQHB9stKLOGprbBqVQqFYNTa2jKYO7BBEGAXq+HwWAQw9GatMEfO3YM\niYmJuHPnDuLj49G7d287npaIiIicHENSIiIiIiJbgiCgtLQUGRkZ0Gq1SElJwfXr19GuXTux2jQi\nIsIuAa3181UMTQEuhKqKxWKBwWCAwWCAXC4XK0erKysrC4mJiZDL5UhISECPHj3seFoiIiJyEQxJ\niYiIiIgexmKx4MSJE2KLfm5uLgIDAxEXFweNRoPo6Gh4e3vbrUXfupndGpxaLJb7QlN3m49psVig\n1+thNBqhUCigVCpr9HOQnJyMRYsWoVGjRkhISOByQSIiIvfGkJSIiIiI6I8SBAHXr18XW/QzMjJg\nNBrRrVs3sdq0WbNmdqv+tA1NrcGpVCotF5zW14VQZrMZer0eJpOpxuGoIAj49ddfsWTJErRv3x7/\n+te/EB4ebucTExERkQtiSEpEREREZA9lZWXIysqCTqeDTqfD5cuX0aJFC6jVamg0GnTu3LlGMzNt\nWRdC2QangiCUWwbl6i36tuGoh4cHPDw8qh2OWiwWbN26FcuXL0dMTAxmzZqF0NBQO5+YiIiIXBhD\nUiIiIiKi2mCxWHD27FmxRf/IkSPw8vJCTEwMNBoNYmNjERAQYPeFULbBqTU0tQanrtCibzKZoNfr\nYTaboVQq4eHhUe2fI6PRiE2bNmHVqlV4/PHHMW3aNDRq1MjOJyYiIqJ6gCEpEREREVFdEAQBt2/f\nRmpqKrRaLdLS0lBcXIyOHTuKLfrh4eF2CzKrWghlrTK1hqbOUG1qPWtZWRksFkuNw9GysjJ8/vnn\n2LBhAwYPHowpU6bA39/fzqcmIiKieoQhKRERERGRo5hMJhw+fBharRZarRbnzp1D48aNoVaroVar\n0b17dyiVSrt8LmuLvm1oWnEhlFwur9PQ1DprVa/XQxAEKJVKKBSKap+huLgYq1atwubNmzFy5EiM\nHz8e3t7edj41EVHts3YDEFGdYUhKREREROQsBEHApUuXoNPpoNVqcejQIchkMkRFRUGtVkOlUqFR\no0a1shDK+u+6WAglCAKMRiP0ej0AwNPTs0YB7a1bt/DJJ5/g119/xfjx4zFq1Ch4eHjY88hERA5R\nVFTESniiusGQlIiIiIjIWQmCgNLSUqSnp0Or1SIlJQU3btxAu3btxNC0Q4cOdm3Rt10IZTKZAKBc\naFqThVC24ahEIoFSqaxROHrlyhV8/PHHSElJwZQpUzBs2DC7LcciIqord+7cwd69exEXF4fGjRsD\nALZv345ly5ZBqVRi9OjReOyxx+Dr6+vgkxLVawxJiYiIXNHs2bPx448/wsPDA23atMHq1asREBDg\n6GMRUR2wWCw4fvy42KKfl5eHBg0aIC4uDmq1GtHR0fD29rbrQijbZVC2C6Fsq00fRBAEGAwG6PV6\nyGQyMRytrkuXLmHRokU4duwY/vnPf2LQoEEusZSKiMiW9fX0zJkzOHPmDAYMGACJRIL8/Hy8/PLL\nePXVV3H79m3s2LEDXbp0waxZsxx9ZKL6jCEpERGRK9qxYwcGDBgAqVSK+Ph4AMD777/v4FMRkSMI\ngoBr166JLfqZmZkwmUzo1q2buBAqNDTUri36tu35D1oIJQgC9Ho9DAYDZDIZPD09azRj79SpU1iw\nYAHy8/Mxe/ZsMVAgInIlFosFOTk5UCqV6NChAwDg3Llz2L59O4YOHYr9+/cjKSkJ+/btg9FoRGZm\nJt59912sXbsWQUFBDj49Ub1V5V8o2KNCRETkxAYOHCj+t0qlwrfffuvA0xCRI0kkEoSEhGDw4MEY\nPHgwgHvb3Q8cOACdToc5c+bg999/R8uWLcWFUJ07d652JadEIoFcLhc/vuJCKIPBAIvFIoakMpkM\n3t7eNaocPXLkCBITE3H37l0kJCRAo9FU+7GIiBxFEARIJBJIpVLk5OQgNzcXcrkcSqUSvXr1ws8/\n/4zIyEhERUVBIpHgwoULaNGiBXx9fREQEICCggKGpEQOwJCUiIjIRaxatQojRoxw9DGIyIl4enqi\nV69e6NWrF4B7VUtnzpyBVqvFmjVrcOTIEXh7eyM2NhYajQaxsbHw9/evVlWmRCIp135vWzkqlUph\nNptRUlICqVRartpUIpE89PNlZGRgwYIFUCqVmDt3Lrp3716tnw8iIkeyfjHJtpLex8cHiYmJiI6O\nxgcffACNRoNt27ZBq9WiSZMm6NWrF9555x2sWLEC165dw927dxEREeHAZ0HkvthuT0RE5GADBw5E\nQUHBfd//7rvvYtCgQQCA+fPnIysri5WkRPSHCIKA27dvIzU1FcnJyUhLS0NJSQk6deoktui3atXq\nked8Xr9+Hd7e3jCZTFAoFFAqleU+1tqib9umP3nyZBiNRqjVamg0GkRFRUGpVEIQBOzfvx+LFi1C\n06ZNkZCQwGCAiFyStXLUqqysDD/88AOeeeYZFBYWIjExESEhIZgyZQp8fX2h0+nwySefYPz48Wjf\nvj2GDh2KBg0a4PTp03j99dfx4osv3veYRGQ3nElKRETkqtasWYPPPvsMu3btgqenp6OPQ0QuzmQy\nITs7W1wIdf78eTRp0gRqtRoqlQrdu3eHUqks9zFZWVn473//i0OHDiEjIwM+Pj6P9OZdEAScO3cO\nWq0WaWlpSEtLw9mzZ9GxY0fcuHEDkZGR+Pe//42oqKjaerpERLXGOnLE+nqo1+uxaNEirF27Ft27\nd0fLli3x/PPPo0mTJpgzZw7+/ve/45lnngFwbzmnl5cX5syZA09PTxw5coRV9ER1gyEpERGRK9q+\nfTtmzpyJffv2oVGjRo4+DhHVQ4Ig4NKlS2JoeujQIcjlcvTo0QPBwcHYsWMHjh07hilTpmDChAnw\n8/Or1ucxm83YsmULVq1ahcjISPj4+CA7OxtpaWliy2nPnj3Rq1cvREREcIu9mxs7dix++uknhISE\nICcnBwBw8+ZNDB8+HOfPn0erVq2wadMmBAYGOvikRPeq7Lds2YIWLVrg999/x6hRo5CWloaJEyci\nNjYWn3zyCebPnw+5XI5//OMfkEgkSEtLw549ezBr1iyEhISIj2UymSCTyVhFSlR7GJISERG5onbt\n2sFgMIjD+zUaDZYuXergUxFRfWaxWPDDDz/g//7v/3Dp0iU89thjuHr1Klq3bi1Wm/6RENNoNGLj\nxo1Ys2YNnnjiCUybNq3cQhKz2YyjR49Cq9VCp9NBq9WisLAQGo1GDE579uwJDw+P2nrK5IR+++03\n+Pr6YtSoUWJIOmfOHDRq1Ahz5szBf/7zH9y6dQvvv/++g09K7koQBBQXF+PDDz9EYWEhGjVqhNmz\nZwMA3nzzTezfvx9DhgzBsWPHMGLECLRt2xaLFy/G1q1b0alTJ3zxxRfw9/d38LMgcksMSYmIiIiI\nqGoWiwXff/893n33XZSWliIhIQF/+9vfIJfLYTabcfz4cbHaNC8vD0FBQVCpVFCpVIiJiYGXl1e5\nyqe7d+9i3bp12LhxI4YMGYJJkyY9chVqfn4+dDqd+M+2bdvQoEGD2nrq5KTOnTuHQYMGiSFphw4d\nsG/fPjRu3BgFBQXo168fTpw44eBTkrtr0qQJnn76aaxevRoAcOLECbzxxhv45ptvAAB9+vRB06ZN\nsW7dOuj1euTl5SE2Nlb8eIvFwsp5orrFkJSIiIiIiO5nrfR877334OPjg9dffx3PPvvsA9+0C4KA\na9euiaFpZmYmzGYzunXrhq5du+L8+fPYuXMnXnrpJYwbNw5eXl51+IyovqgYkjZo0AC3bt0CcO8O\nBgUFid8mqg1msxkymazSJUomkwlyuRyLFi3Ctm3b8OuvvwIAioqKEBgYiKysLGRlZWHnzp3o1q0b\nxo4di+Dg4Psem4jqHENSIiIiIiIqTxAExMTEwN/fH3PnzsXjjz9e7Tl4ZWVlOHDgAL766it4e3vj\n//2//weFQmHnE5M7eVBICgBBQUG4efOmo45H9VjFUNRgMIgjP6z/z/pvo9GIyMhIbNiwASqVCgCw\nbNky/PLLLyguLkZSUhI6derkkOdBRJViSEpERERERPe7fPkymjVr5uhjEN2nsnb7vXv3okmTJsjP\nz0f//v3Zbk+1auvWrVi1ahU6duyIv/zlL+jZs2e5/2+tJn3rrbdw7NgxfP311wDuBamlpaXw8fER\nvy0IAtvqiZxDlSEpf4cSEREREbkxBqTkKp599lmsXbsWALB27VoMHjzYwSei+kAQBJjN5vu+f/fu\n3VizZg3mzp2L0NBQvPHGGzh8+HC5H2Ntl585cybS0tJw6dIlAIBEIoGPj4/42BKJhAEpkQvg71Ii\nIiIiIiJyKiNGjEDPnj2Rm5uL5s2bY/Xq1YiPj8eOHTvQvn177N69G/Hx8Y4+JtUDEolEDDt37dqF\n9PR0AMD+/fvxxBNPIDc3F8uXL0fPnj3RunXr+z7WbDbD398fR48eRVhYWJWPTUTOj+32RERERERE\nROQWKlvCtHz5cuzcuRNZWVno0KEDtm3bhsWLF+P111/H5MmTMW3aNISGhuLu3bswmUzw8/ODIAji\nZnrr43EZE5FLYLs9EREREREREbkni8Uitr7b2rNnD9asWYN3330X69atw7Fjx6DT6dCxY0c8++yz\nGD58OEJDQ5GRkYH4+HicP39eDFplMhkkEglSU1Oxdu1alJSUOOjZEZE9yB19ACIiIiIiIiKi2mSd\nCVpSUoJffvkFAwcOhJ+fHy5evIiePXuiffv2aN++PYYNG4ZvvvkGb731Fk6dOoUpU6YgKCgIV69e\nxYsvvojOnTuLj7l//34sWbJE3GLv7+/vqKdHRHbAdnsiIiIiIiIiqlcqLkwyGAyYN28efv75Z8TE\nxMBisWDq1Kk4efIk9u3bh7fffhsNGzbEoUOHoNFooNVq0aNHD+Tn5+Pw4cN48sknxccuLCzEK6+8\nAoVCgXfeeQdt2rRx1NMkoj+O7fZEREREREREVL9ZC8FkMhmkUqm4uf769eto1aoVUlJSMGbMGKSk\npCAxMRGDBg3ChQsXsHHjRlgsFly9ehWtW7fGzp07AQAhISFiQGoymWCxWBAYGIjly5djw4YNDEiJ\n6hFWkhIRERERERGRS7NYLAD+11ZfUFCAqVOnIjQ0FMOHD0fPnj1RXFyMN954A2lpaZg+fTreeust\nfPXVVzAYDFi5ciV+++03dOvWDX369MHKlSuRmZnpyKdERLWjykpShqRERERERERE5LKsW+YB4MSJ\nEygoKMClS5dw5swZNGvWDCtWrMCWLVsglUoRHx+PDz74AA0bNkTfvn3h5eWFX375BXq9HteuXUPD\nhg0xf/58+Pv7Y86cOQ5+ZkRUC9huT0RERFSZxMRESKVS3Lx509FHISIioke0adMmLFy4EMC96tEj\nR45g3rx5GDJkCGbOnInPP/8cc+fOxbhx49C5c2csX74cJSUlOHXqFI4dO4YlS5YgLi4OwcHBKC4u\nhkKhQFpaGjp16oSSkhK88sorDn6GRFTXWElKREREbuvixYuYMGECcnNzceDAAQQFBTn6SERERFSF\nkpISeHp6QiaT4erVq/D19YWnpyfu3r0LjUaDTp064csvv8R3332HTZs2IT4+Ht27d0dGRgYmTpyI\nlJQUfPvtt1izZg2kUimWLVuG8PBw8fFv3rwJpVIJHx8fBz5LIqplrCQlIiIiqmjGjBn44IMPHH0M\nIiIieoDz589jypQpGDBgAKZPn47Lly8jJCQE77//PmbNmgUfHx8MHToUubm5AICBAwfCz88PmZmZ\nKC0tRWxsLBo3boz58+fjxRdfxLfffovt27eLAal1uVNQUBADUiI3xpCUiIiI3NL333+PsLAwdO3a\n1dFHISIioiqcOXMG48aNQ4MGDbBt2zYUFxdjypQpAIAnnngC27ZtQ1FREV599VVIJBIkJyfDz88P\nffr0QVpaGo4fPw4AWLJkCSZNmgQA8PPzg8ViEcNRmUzmmCdHRE5F7ugDEBEREdWWgQMHoqCg4L7v\nnz9/Pt577z38+uuv4vc9ZAQRERER1aF33nkHTZs2xYQJE/Dvf/8barUawL0/wwcMGIDCwkL07t0b\n4eHhWLp0KeLj4zF06FAkJSWhd+/eGDRoEPbu3StuvW/bti2Ae3/eSyQScdETEZEVZ5ISERGR2zly\n5AgGDBgAb29vAMClS5fQrFkzpKenIyQkxMGnIyIick/WABMANmzYgKVLl0Kr1YpfyJRIJNi1axfW\nrl2LdevWAQD279+PKVOmICMjAzdv3kRMTAx+/PFH9OjRA0ajEQqFwmHPh4icEmeSEhEREVl17twZ\nV65cwdmzZ3H27FmEhYUhKyuLASkREZGDmM1mMSAFgKFDh8LT0xMbNmyARCKBwWAAAFy4cAEBAQHi\nj+vbty98fX2xcOFChIaGYuPGjejatSssFgsUCoVYSUpE9DAMSYmIiMjt2b4pIyIiorpRcS5oUVER\nNm/ejFOnTkGpVOKll17Cp59+CgBQKpUAgFWrVmHMmDEAgLy8PAD3WvBbtGgB4F5oKpfLxXZ6ttUT\n0aPiqwURERG5vTNnziAoKMjRxyAiInILFosFFosFUqkUMpkMer0eFy5cgEajwfr16/GXv/wFd+7c\nwciRI2E2m7FlyxYAwOnTpxEYGIjz58/jz3/+MyZNmoTi4mL86U9/wsiRIx38rIjI1TEkJSIiIiIi\nIqJaZzKZANyr7pRKpSgsLMSUKVPQq1cvLFu2DMuWLcN3332HLl264J133oFCocBLL72EpUuXArg3\nQ/ynn37C4sWL8fLLL2PXrl3w9fUFcG+eKZcwElFNMCQlIiIiIiJycWPHjkXjxo3RpUsX8fvefvtt\nhIWFISoqClFRUdi+fbsDT0ju7M6dO/jhhx/E+aCCIODtt9/Ga6+9hjZt2uCNN97Avn37kJaWBgCY\nN28evvvuO1y9ehUjR47E+fPnVpySzwAAFU1JREFUsWvXLjRt2hS7du3Cnj17MGzYMAAQ2/UlEgnH\n5xBRjXC7PRERERERkYv77bff4Ovri1GjRiEnJwfAvaDJz88PM2bMcPDpyF3ZbpcfO3YsQkNDcejQ\nIUyZMgXnz5/HBx98gOTkZISGhmLVqlU4dOgQ3nzzTQQHB+P5559Hq1atsGDBAnz11Vfo2LFjuS8C\nmM1myGQyRz01InJd3G5PRERERERUX/Xp0wcNGjS47/vZfkyOsHjxYhw7dkwMSPV6PcLCwpCYmIio\nqCg8/fTT+Mc//gGlUonTp08DALp06QKpVIpt27YBAObMmYPbt2/DbDZj+PDh5QJSAAxIicjuGJIS\nERERERHVU0uWLEG3bt0wbtw4FBYWOvo45CaOHz+O//73vzh79iyeeuopPPXUU2jdujX69OmD3r17\niy3yI0eORGJiIgAgMjISzZs3R3JyMkpLS6FWq7Fy5UoxDGXgT0S1je32RERERERE9cC5c+cwaNAg\nsd3+6tWrCA4OBgC8+eabyM/Px8qVKx15RHITZ8+exfDhw9GuXTuMGjUKR44cQWlpKU6fPg2JRIL/\n+7//Q3h4OPR6PSIiIrBhwwb06tULp06dQkBAAIKDg2GxWCCVStlWT0T2xnZ7IiIiIiIidxISEiIu\nsxk/fjzS09MdfSRyE+Hh4ejRowdOnz6NJ598EqNGjYKnpydatWqF06dP48SJEzhx4gSKioowceJE\nHDlyBADQtm1bBAcHQxAESKX34goGpERUVxiSEhERERER1UP5+fnif2/evPm+mY5Etem1117DzZs3\nkZ+fj+DgYLRp0waenp6IjIzE9u3boVKp8MUXXyAhIQETJ04s97HcUk9EjsB2eyIiIiIiIhc3YsQI\n7Nu3D9evX0fjxo0xb9487N27F4cOHYJEIkF4eDg++eQTNG7c2NFHJTfyj3/8A76+vvjwww9x+fJl\nJCUloWHDhhgxYgSCgoLg6+sL4H/zRhmOElEdqPKFhiEpEREREREREdndwYMHMXToUKSmpiI4OBi5\nublo27at2EJvMpkgk8kYjhJRXeJMUiIiIiIiIiKqO1FRURg0aBDOnDkDAIiIiIBMJhMrR+VyOQNS\nInIarCQlIiIiolqxZMkSLF26FDKZDM888wz+85//OPpIREREROTeqvzKjLwuT0FERERE7mHPnj3Y\nunUrDh8+DIVCgWvXrjn6SERE5CBms5lb6onI6bHdnoiIiIjsbtmyZUhISIBCoQAABAcHO/hERETk\nKAxIicgVMCQlIiIiIrs7efIk9u/fD7VajX79+iEzM9PRRyIiIiIiqhLb7YmI6jGLxQKJRMKB+ERU\nKwYOHIiCgoL7vn/+/PkwmUy4desWUlNTkZGRgWHDhomLO4iIiIiInA1DUiKiekwq/V/DgCAIYmhq\n+/1ERNW1Y8eOKv/fsmXL8PzzzwMAYmNjIZVKcePGDTRs2LCujkdERERE9Mj4LpmIqJ7Kz8/Hxo0b\nce7cOQCARCKBTCa7LyAVBAGCIDjghERUnw0ePBi7d+8GAOTl5cFgMDAgJSIiIiKnxUpSIqJ6atu2\nbZg0aRJGjBiBkydPYsyYMTh58iQGDhyIfv36ictUbFvxLRYLALDSlIhqbOzYsRg7diy6dOkCDw8P\nrFu3ztFHIiIiIiKqkuQh1UMsLSIiclHjxo0DACxZsgQLFy6En58fQkJC8N133+G5557DiBEjUFZW\nhqNHjyIwMBBt2rRx8ImJiIiIiIiIalWVCztYSUpEVA8JgoBTp04hMTERe/bswVdffYWQkBC88cYb\naNq0KQ4ePIghQ4bgo48+wrZt21BUVISWLVvi8ccfx+DBg+Hv7w9vb+8qFz5xIRQRERERERHVJ+yn\nJCKqh65cuYKioiJ07NgRR48exd/+9jdMmDABmzdvRnZ2NgIDA7Flyxakp6fjgw8+QGZmJmQyGb75\n5ht4eXkhKSkJs2fPhl6vBwDk5uaipKSkXDs+A1IiIiIiIiKqLxiSEhHVQ5mZmSgtLYW3tzfatGmD\n3377DcOHD0dSUhL27t2LuXPn4uLFi1CpVOjQoQMAoHXr1oiOjkZgYCByc3PRqVMnyOX3Gg5eeOEF\nbNmyBVKpFAcOHMCmTZtw5MgR8fPZjm6xWCwwm80AAKPRWIfPmoiIiIiIiKh6GJISEdVD3bt3x8KF\nCwEAPXv2RFBQEF5++WUsXrwYWq0WhYWFCAgIQE5ODnx9fVFaWgqz2YyWLVvCYrHgwoUL6NSpE2Qy\nGe7evQu9Xo+nn34av/32G3766SdkZ2dj8uTJmDdvHsrKyiCRSHDmzBmUlZVBKpVCJpMBAL788kvs\n27cPQPkglYiIiIiIiMiZMCQlIqqHwsLC8Oc//xlmsxlNmzbFBx98AI1Gg8zMTPz2228IDAxE69at\ncfnyZZw6dQrff/89fvjhB3Tp0gVnzpyBp6cnmjZtCgA4ceIEPD09ERQUhAULFmDPnj0YNGgQvv/+\ne+zcuRNFRUXYv38/pk6d+v/bu/9Yrcv6j+Ovcw6H44kDYZ04x4xGplRkjZPKyUEWYwesGYtgzmpx\njJo2dM7W2cGyVtCYUdMllTWSytYScBmxtpZOmmI78mOGztYQLONXh7kOPzxYIuc+3z/YuccRrL7f\nCL5yPR5/wef82HXuP7h3nryv68rll1+eSy+9NJs3b87evXtz6623prGxMUlO2J4/tHX/4MGDSURU\nAAAAzhwXNwGchSqVyrCJzvPPPz/XX399rr/++urntLe3Z9asWbnuuusyZsyYXH755Rk3blyOHj2a\nN7zhDdXPW7lyZd773vdm586dOXLkSD74wQ/m9ttvz7Zt21KpVLJ79+488sgjmTJlSr7yla9ky5Yt\nGT16dNasWZN9+/blxhtvTEdHRxYvXlzdvp8cO9c0Sa677rp0d3fnkksuycDAgPNOAQAAOO1EUoCz\n0FCAHDI4OFid3BwKp6NGjUpXV1e6urqyYsWK7Ny5M2PGjMkb3/jGjBo1KldccUXmz5+fNWvWZNmy\nZRk5cmRGjRqVj3/84+nu7k6SHDhwII2Njent7c3ixYszceLEfOxjH0uSvPDCC5kwYUI2bNiQzZs3\nZ8SIERkcHDwhgN57773V9Q6tLUkGBgaqfz/+zwAAAHCq2W4PUICamprU1dUNC42Dg4MZGBjI0aNH\ns3v37tTV1aWlpSVJ8r3vfS/r16/PnDlzcu2112bq1KlpbW3NhRdemCVLlqSnpyd/+MMfcs4556RS\nqeRDH/pQ7r///tx777255ZZbkiSrV69Oe3t7GhoaMm3atGGBdCjYPvDAA3nLW96SJNm8eXPWr1+f\nvXv3JhkeTO+444709/dXL4QCgP/Erl27Mn369Lzzne/MxRdfnOXLlydJ+vr60tHRkYkTJ2bmzJk5\ncODAGV4pAHC61PyLM+AcEAdQgCNHjqSvry+tra0nnfYcsmvXrqxcuTI9PT05ePBg7rvvvuzYsSN7\n9uzJ7Nmz89BDD2XVqlVZvXp1pk6dmoULF+YTn/hEXnrppdTX11e/z9GjRzNixIh86Utfyu7du/Pj\nH/84CxYsSE9PTyZNmpTt27fnm9/8ZmbNmpX7778/S5YsydatW5Okur6h6diampoTJmcB4J/p7e1N\nb29vJk+enP7+/lxyySVZu3ZtfvSjH6W5uTnd3d1ZtmxZ9u/fn69//etnerkAwKnzime7+a0SgIwc\nOTKtra1Jhl+wVKlUhk1vjh8/Pl/96lfzm9/8Jo899lje9KY3ZezYsfnVr36Vjo6O3H777Zk/f36S\n5G9/+1ve9773JcmwQHq8Bx98MFdeeWUGBwezc+fOLFy4MD//+c9z5ZVX5uGHH87hw4dz991355ln\nnsmMGTOybt261NTU5B//+Ed1Ora2trZ66dPAwEAqlUp1UhUATqa1tTWTJ09OkjQ1NeUd73hH9uzZ\nk3Xr1qWzszNJ0tnZmbVr157JZQIAp5EzSQF4RS+f0BwKkEOBsqamJm1tbVm1alWSZP/+/Tn33HPz\n4osvZv78+Zk5c2bmzp2bpUuXDvs+Qxc4bd++PdOnT8/27dvT2NiYD3/4w0mS17zmNUmOnZva2NiY\nZcuWZcqUKWltbc2TTz6Zu+66K4899limTp2arq6u6pb9l59b+s+mYgEgSZ599tn8/ve/T3t7e/bt\n21c9eqalpSX79u07w6sDAE4Xk6QA/Ntqa2szYsSIYTFyaNp0cHAw5557bgYHB9PQ0JAvfvGL2bp1\naz7zmc8kObbFPkl16vOPf/xjKpVKWlpasm3btjQ0NGTChAlJjl0Idf755ydJnnrqqXzgAx/IpZde\nmvr6+lx77bXp7OzM1q1b09LSko0bNyZJFixYkMWLF+fuu+/Ok08+mSNHjlS35b9cpVI56XMAytLf\n35+5c+fmzjvvzOjRo4d9rKamxn+0AUBBRFIA/iO1tbXVqdIkw84LPeecc6pTnkPTo0Nb4Xft2pXZ\ns2cnSTZt2pRRo0YlSf785z/n8OHDedvb3pY9e/akUqnkoosuyt///vc88MAD6e/vz8KFC3PVVVfl\nkUceyS9+8YskyeOPP54dO3Zkx44defTRRzNt2rRs3769uq6+vr5hax56PnScwF//+tc8//zz/9XX\nCuBU27RpU6ZMmZK2trZcdtll2bx585le0qvGSy+9lLlz5+aTn/xkPvKRjyQ5Nj3a29ub5Nj7wrhx\n487kEgGA08h2ewBOueOnbxYtWpTm5ubMmDEjbW1t1SnUmTNnZubMmUmSq6++OocPH06SPP3003nh\nhRcybty4PPPMM3n729+e+vr61NfX58CBA7nqqqtyxx13ZOPGjXniiSfS3Nycvr6+HDp0KF/4whcy\nadKkJMmKFSuqU0FPPfVU5s2bl40bN2bDhg3Zu3dvLrvssrS1tVWPFPj2t7+d2tradHV1ZezYsaf1\n9QL4v+ru7s7Xvva1zJo1K7/+9a/T3d2d3/72t2d6Wf/vDQ4O5tOf/nQmTZqUm2++ufp89uzZueee\ne7Jo0aLcc8891XgKAJz9RFIA/qtuuummbNy4MT/4wQ+yZcuWNDY2ZtWqVWltba0Gyne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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe833802550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# perform PCA dimensionality reduction\n",
     "\n",
@@ -672,10 +720,10 @@
     "X = pca.transform(X)\n",
     "\n",
     "# elbow methos fpr PCA\n",
-    "clusters, num_clusters, costs_pca = get_best_clustering_model(X, max_number_of_clusters, \"PCA\")\n",
-    "print (\"Num clusters(PCA):\", num_clusters)\n",
+    "#clusters, num_clusters, costs_pca = get_best_clustering_model(X, max_number_of_clusters, \"PCA\")\n",
+    "#print (\"Num clusters(PCA):\", num_clusters)\n",
     "\n",
-    "plot3([0,1,2], X, clusters, -1)"
+    "#plot3([0,1,2], X, clusters, -1)"
    ]
   },
   {
@@ -687,11 +735,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 13,
    "metadata": {
-    "code_folding": [
-     0
-    ],
+    "code_folding": [],
     "collapsed": false
    },
    "outputs": [
@@ -699,15 +745,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[3610, 6421, 484, 21, 136, 27, 65, 33, 20, 23, 31]\n",
-      "Estimated number of clusters: 11\n"
+      "[4811, 496, 373, 29, 48, 140, 11, 15, 15]\n",
+      "Estimated number of clusters: 9\n"
      ]
     },
     {
      "data": {
-      "image/png": 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WLZKqz9qsH8PmA1SLpPbjPoukIsxBBYB9EJICwAbqVVmpYjRpY/VVfZbeZDKJ6XQ6W7h0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SPTxMnv99cKWDqOQzKZJBwOI7ZvR6xZgxw/vsFtywMOIPaf/yALCoDU8UcIUe93qZTKTNdPnw+l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//40aNMhkuh6C6DXXYC1fjt+nDzI/H//005GbN0NqKv6YMbXyTZ3/+Z96txH629+wliyBcBix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OP+gSu1tbXU1tZi23bJ3I9iEAWnyWSSVCpFJpOhqqoK27YxDCMfQjc3N9PS0kIu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\n4gscRYQkjHa6bsPoGpUFhCy0gdELALuTWsMwqq9Dvl4WB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2mE7vpLwiFfvcM6u4gLzp36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arZZDTUgRzl62NpsNKpVKnvhc088t12o45zXGatOq5Rq8S5LESfW1yK0e+lVVixlA+eD9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\nuLhYHghFRESkNEEQEBUVhaFDh3p6KUREROQBqjv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+      "image/png": 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MAACDQAYAgEEgAwDAIJABAGAQyAAAMAhkAAAYBDIAAAwCGQAABoEMAACDQAYAgEEgAwDA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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe8338b57d0>"
+       "<matplotlib.figure.Figure at 0x7ff7150b6b90>"
       ]
      },
      "metadata": {},
@@ -725,12 +773,12 @@
     }
    ],
    "source": [
-    "# DBSCAN clusterint\n",
+    "# DBSCAN clustering\n",
     "from sklearn.cluster import DBSCAN\n",
     "from sklearn import metrics\n",
     "\n",
     "# Compute DBSCAN\n",
-    "db = DBSCAN(eps=0.1, min_samples=20).fit(X)\n",
+    "db = DBSCAN(eps=0.3, min_samples=10).fit(X)\n",
     "\n",
     "core_samples_mask = np.zeros_like(db.labels_, dtype=bool)\n",
     "core_samples_mask[db.core_sample_indices_] = True\n",
@@ -746,6 +794,28 @@
     "plot3([0,1,2], X, clusters, -1)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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AbXEeSZUNskiqWIWaz0BN03RNgFr8df6zN8OHFgyLkBQqql8LfcTkLlxqNpsx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\nIDZvFlBSwrF+vYjNm0XcfHMQRUUcP/yhgmCQ4Y47gl2tQO6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3lQfbtgl46ikZo0YZuPnm\n+FYlGAZw/DhDba2AW29VAWTmexMhJH4UkhKSAm5ZGm2FFU7v++LkbSfxsZYMWkvlZVmGLMvdltE7\nQXs78OCD5p3RD36gxzRRmfb79LrjDh1NTcDIkUBgYK0GSRjt7cDWrQKmTDGSMm28L9XVOo4cMad8\nEzIQoWHonDk6OjsZpk2zf8ATGqC++64Hx44xzJ8vYOpUo1vvU8MwoOt6159ddlk7BEFAINB9gFS4\n6tNI/H6O/Hwed5uCn/9cwcmTwNq1akzHsqaZwwlHjeKwLiWGDOHw+3lclc9795oVowsW6L1C0NDg\n+Mc/DiRkmF59vdnSYP9+e1wfFBdzFBfzAVXfnn22jpMnGebOtf+xQxLDDffYxF4oJCW25JZQkZBk\nomMkPM55t/6ihmFAluV+l9HbndcLjBt3+nU/fBgoLU3jBpGweh6feXnmVyJ+FunbX/8qYd06EfX1\n+oCGBMXiy1+m/sQk8Xw+pKWyb6BuvDGIAwcEVFWZIRdjDKIoQhRF7N/PcPSo8EXVOe8zQLWW7/es\nPO1reFSoggLggQf6//TpF7+QUVfH8PWvB7tV9OfncwQCDIoS27n2tddkrF+vYPlyDYsXm6Hc+PEG\nvv/9+JbBP/ecuX1DhvCILTysYVYDNXWqgTvvDGLoUHu8xwwezHHnnQNrIVBeznH77c7tjW293zv1\nOjWd6DkjiUIhKSGEOBBdCPRmTei1glFrGb3P54MkSa54zgQB+OpXzRunv/xFwN69DBdeaKCy0h43\nOG4W/OK+LZpBGYnc19yw3yZTbS3DqVMMEycamDxZx+HDDBMnUgURIekwZgzHmDF9H3+PPKLgxAmG\nggKOCROMiMv3e4an1oedoVWrffU/7c/u3QLa2hhaWxn8/tPvmzfcEHuoduyY2TM1O5snLGRcvFjD\n3r0CRo9OXYuF/oZsEUJIpqGQlKRULDd7bqqcocpYQpLDMIyuUFRV1a5p9FlZWRAT0bBrgHbuZHj9\ndQHLlxuoqEjsOaC4mKOuDsjLo3NLsqkq8OST5s38tdcakOWB/TwKPhPnBz/woKMD+M//DHwxxMO5\nFUSExIJz4LnnJOTkcCxblt4PBo4cYXj2WRlnn61h+nQDR48yvPGGhPnzNYwebb5HLVqkYc8eAcOH\nRw4AQ6tPQ4X2PrUqTkOHRwEMf/lLFiSJYfVqDaLYu/r03nuDaGsz3z8H4o03RDz5ZDYuvFDD978f\nxMmTwGOPyZg61cCZZ8b/WsycaWDmzPT3oCXE7azzCSF9oZCU2BLdQNqXFfg6+TWi0Dr94n0NrGX0\nVsWotYxeURT4/X7b9RfdtYvhyBHze6JD0rlzOebOzaz9uLPT7DtZWJja38tY9690MAygro7ZZlmk\nXcyeraO+nqGwkJ4XklmOH2d49VUJjAFLl/buYZlKW7cK2LFDgNcrYvp0A59+KmD7dgFZWSJGjzbb\nBlxwgY7+huhwHv4cG254VCAACAJHW5uBjRu9ADjOPz8Aj8cMUIHTw6NycgTk5QkwjPh6n1qys83v\nOTnmeWffPgGffSagvZ0NKCR1K7rmJnaj6zqkRDT2Ja5EewYhhBBbs6pFrC8AUBQlbcvoYwl4ly41\nUFbGMHEi3SAkwnPPCTh2jOGqq3QMG5a63ytJwHXXmTfb6Qoi3nlHxCefiFiyRKNKoxDXX0+VoyR6\nTv+QN9TQoRxXXaUiJyfx56VYn6Ozz9ahKMCUKea5acECHV4vMH169IHhJ58IePllCRdfrGHGjOjO\nce3twE9/qiArC7jzziBuukmDIAAFBV4AwF/+IkLXgYsvDoJzswI1tPq0r56n0SzfnztXx5QprfB6\nZQASpk0zEAhoGDWKzs3huOW4I/YTz3ldVVXIA10WRFyLQlJiW2761JEqF0miuX2fsm5krGn0oihC\nlmXk5OREHN5gNx4PMH26e1+nVCsoAJqbzQFWqTaQEOLkSbPqayC9Y/PzOWTZ/E4I6e7IEQavl6e8\nyjzdzj038VWL8VxbeDzAOeec3ha/v/v/j0ZLC4NhmP1Co9VzUydPPh1StrcDb78tgXOz0jY3N/Ly\n/dDBUaHDo3oOkLKuP0LfEwQBXwykInb09NMSWloYrr9ejaqveDq56YMcO7NadBHSF9oziC3Rm4N9\nuT2cI+kRuoxeVdWuZTB2XUbvZE6+AF+xwplVOg8+KKKmhuGee3RMmhTf+bO62kB1dd9Tf0+cYHj+\neQnz5ukRJyIT4kZ1dQz33utBTg7HI4/0P+Gc2NOiRTqqqgwMHhz9OdLvB+66KwhR7L1M3+cDbrxR\nha4Dubm9/2245ftA38OjrD+z/o1hGNA0s5VALMOjSGpxDnz2mYBgkOHUKaCoKN1bROxAVVUodk/M\nSdpQSEoIyTgU9NpDz2n0ACDLMrxeL2RZppuNJKDnND0mTOBQVWDIkOScdzZtErBpkwhNA4WkJOP4\nfBxDhvCkHV8kNRiL7xzp8YT/b9Onx3c+jGZ4VCAQ6DU8qmfVac/q00QIBABZNqtXiUlVgV/+Uoai\nADfcoHYLzBkDbr1VRUcHBaTkNE3TaLk9CYtCUmJbbgux3PZ4CImHtYw+EAhA0zS0t7dDURRkZ2dD\nFEUK8UifnH7+vPxyA5dfnryff9ZZOnQ9/kCAuIvTj5dYZWcDP/4xVZDaQTAI2y9nHojQ6lOrp6G1\nZLev6lMrQA39dz3D01iuexoaGB56SMawYRw336zilVckeDwcS5c6Y6k/58CGDSKGDDESOsyysxOo\nrRUgSRyaZobIoYqLM+ucmGni7UlKy+1JOLRnkLTo72TmtqDEbY+H2INTboR1Xe+qFrU+uRVFEZxz\n5OXlpXvziM1R5Xf/fD5g2TJn3CQTd9F1s4orHX2CQx0/zpCXxxO2HR0dwK9+JSM7G7j22uQMBzMM\n4PBhhrIyHnaiu5Ns3izggQcULF2q45pr7DdQbft2cwL9RRdpCQlye97LRFN9an2PNDzK+rJ+Zvef\nZe43hgE0NgKvvGLeyi9cqEesqE2n0PfvffsY/vxnCbm5HP/xH323j4lHTg5wxx1m2wUqDiTRoMFN\nJBIKSUlKUVjofBRY2IOdjyXOOTRN61pKzzmHoijdltFbfUeJ+xw4YN6Mzp9vICcn3VtDSGZK1XvE\nM89IaGxkuOoqFQUFKfmVvezaJeCHP1QwfryBe+5JTPCiqkBbG4Ouc3Deu99lIjz3nIQ//1nGlVeq\nWLlSS/wvSJCtWwU89piMNWs0nH12+PftQMAMzTs7k7s9NTUMJSU85qDzySdl1NYyaBrw3nsSLrxQ\nxQUXJP86JJrep9b30OpTAL2C04IChnvvNaAoDJIEXHGFOYjIrgFpKMYYyss5Zs/WUVqa+PuIoUPp\n3oRET9M06klKwqKQlNiSG4M4tz0eJ3Pj/pVuPfuLCoIAWZZduYye9p/IPvlEwL59DIMHM8ycSc8T\nIW4mCGaAmM5TvM9nVpAWFibufJObC3zlK0FIUvIeW0EBhyhyFBTY+zy5f7+A+noBu3YJEUPSWbMM\nPPxwJ/LzE/v7dR3Ytk3A+PEGPvpIxMMPK1i4UMNtt8VWrbp6tYpt20Tk5nK0tAAHDggA0vthrVV9\n2pNVfRq6hD+0+jQQYFBVAXPmmOGppjFHDI9SFOCyy+z7gYAdOHm4ppNQJSmJhEJSknKZeOKnUIW4\nUeg0equ3j6IoyMrK6vOin2SG+fMNFBczVFXROY8Qt7vsMg2alt4+lGVlHI880jmgMJNz4JFHZGga\nw+23m8t2k90NZulSHeeeq6ckYP7kEwG1tQIuvliLeeDP8uUaRowwUFnZf8/jZAzGeeEFCU8/LWPZ\nMg2zZunweuMb0jVrloFZswxwDowdyzFihH17OIeGnZGW71vVp1Z4ag2PCu15mozhUYTYSTz32BSS\nkkgoJCWExIQC38zFOe/WX9QwDMiyDI/Hg+zsbLoAJwCA4mL7D0k4ftzs45mOdgAffcTwu995cOWV\nAVRXp/73k77t3s2wfbuI5cs16mkXA0Gwx6Cegb79dHYCH3wggXPguuuQ8GrIcFL1tvnoowpaWhjG\njzcwcWJs4aAoAlOnpi9QHD3aQFERR0WFgaoqA7/7Xff1/J2dwIsvSpg82cCkSf1vJ2PAuHH2DUj7\nE83y/dAA1foz69/07IFq9+pTQqJBg5tIItGeQWzJjUGc2x6PGzh9SUsq9ilrGb21lJ4xBkVR4PP5\nIElS3M+fG49xu+EceP11AYYBLF9udN2MZ/rzXlcHPPGEiLw84NZbU7/Ucu9ehoYGYN8+AdXVzr1R\nd5tf/lLB3r0CCgs5Fiywb7/k48fNA9nuH0Q4TVYW8N3vBqBpyQ1IW1qAl1+WMG1adIHeQH/Xp5+K\nmD3bHKRUUyOgosJ555zp0w089lj4RqebNon4wx9kDB5s4Je/DKRwy+wnmuFRVtVp6PL9vsJTN1Wf\n7t7N8NRTMhYv1jF/vn3P7yR1dF2nSlISFoWkhKSAWy4y3MINr0cyH4NhGF3VotYnrbIsIzc3l5bR\nO0ggAGzaZO4n55wD+P3u2PcHyu8Hioo4hgxJz++/9FIDlZUaKitVAHQ82cVFF2nYuFHA1Kn2vYHu\n6ACeekoGY8AttwQdMaylP48+KqOmRsC99wZQWJjebYm1wjIeW7eK2LBBxPHjAiZNStx07748+aSM\n996TcOKEiksu0RBt/02nfZA2daoOWeYQBIb6eobBg2Pb/nXrRNTUMKxapaGhgWHbNgHnnqu7qqI8\n2upTa8WQFaCG/jsnV582NAjo6GBdHzIRQsvtSSQUkhJCSIYLvSgOBoNdy+gVRYHf7+/zoprYB+fA\nCy8IKCriWLDg9M2h1wtccYUOw2Dw+9O4gTbj9wNf+Uryw5BwQYOiAFOmGNBtlsW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NAfSBVBoLbrJgtWw48u8IcmGL5mVyXgiqhEcDGBKD8qKCEbf60bkWpc4xrLQqpbBTSCNdpo2yyt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\nm82qWrWqBgwYo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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f68859f6350>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot3([3,0,1], X, clusters, -1)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -755,33 +825,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 45,
    "metadata": {
     "code_folding": [],
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[13068]\n",
-      "[2046, 11022]\n",
-      "[6918, 1949, 4201]\n",
-      "[4951, 2140, 4201, 1776]\n",
-      "[2140, 4195, 4952, 1776, 5]\n",
-      "[2111, 4195, 1342, 635, 5, 4780]\n",
-      "[4761, 3623, 1337, 2109, 632, 5, 601]\n",
-      "[3623, 4592, 833, 2009, 5, 422, 601, 983]\n",
-      "[4951, 2140, 4201, 1776]\n",
-      "('Num clusters:', 4)\n"
+      "[902]\n",
+      "[842, 60]\n",
+      "[805, 38, 59]\n",
+      "[325, 482, 36, 59]\n",
+      "[465, 34, 318, 26, 59]\n",
+      "[462, 34, 318, 40, 26, 22]\n",
+      "[397, 142, 22, 34, 26, 241, 40]\n",
+      "[40, 393, 141, 25, 29, 240, 12, 22]\n",
+      "[40, 239, 393, 11, 22, 9, 27, 20, 141]\n",
+      "[394, 141, 40, 4, 20, 23, 22, 236, 13, 9]\n",
+      "[331, 40, 23, 128, 20, 132, 22, 182, 4, 11, 9]\n",
+      "[301, 135, 23, 40, 12, 22, 9, 9, 182, 11, 154, 4]\n",
+      "[130, 316, 40, 23, 9, 127, 11, 20, 180, 11, 4, 10, 21]\n",
+      "[293, 182, 40, 9, 133, 23, 19, 11, 5, 12, 4, 145, 22, 4]\n",
+      "[162, 40, 4, 293, 12, 23, 22, 96, 139, 9, 11, 19, 4, 5, 63]\n",
+      "[40, 239, 393, 11, 22, 9, 27, 20, 141]\n",
+      "('Num clusters:', 9)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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WWc+zdKn47LM13HzzAHr2PDLtaM65PFpvd5akQ+PXbpJOKPmovogui/2qkqhf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\naML9jcplaw+cUpE3VPBzuDrEi4irLVY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xxk/Ze++p9O3rvybnXP5lUlV1K3Cjmc2um0i5a0hVVePGTWDMmAf4+utuLFhw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\nkCOPhI8/nswZZ0xh/PjDqyy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9uAbKCw6XNKsJT1//vvILlb+ZS1oe/ewpaYakRyW9L2mU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\n5f8DumuCLHMqTb8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f333dd9ae10>"
+       "<matplotlib.figure.Figure at 0x7f6886ca3750>"
       ]
      },
      "metadata": {},
@@ -789,9 +866,9 @@
     },
     {
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3337b99450>"
+       "<matplotlib.figure.Figure at 0x7f68847b8a50>"
       ]
      },
      "metadata": {},
@@ -799,9 +876,9 @@
     },
     {
      "data": {
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PYjQaxeuvvx6/+7u/G+95z3tOfEvrqbfhgtHVJNTYphb64q+n8Pbbb8d73vOe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\nORt4m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4QrJsR22G5PiFswyxqtq6tDLBYry03YzDUqnEi5vk4ikegjbDmxlcysdVp+4DO2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\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xmrSx+qo+S68sy3jnnXeWLfTT6VTbJ3RUPTzdtkgqVcSn4106BlokdTz7zkFNVtv3zUEF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RiSElHb0X1GPc9DEASwLAuu66JUKvHNlyiGlc5EyXjl/vtx87nnonvuXLzvT39KejlE1AQMgSgr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x00034aGHHkKpVMJHP/pRnHjiiTjppJNw0EEHBfLyqIam8iMOW3YpWHbDc1jplz1BVZvq1Vmm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\nnts3EA0tERsAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f333fc5d850>"
+       "<matplotlib.figure.Figure at 0x7f6886ca3290>"
       ]
      },
      "metadata": {},
@@ -824,7 +901,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": 31,
    "metadata": {
     "code_folding": [
      0
@@ -836,14 +913,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[58, 311, 180, 36, 1, 313, 1]\n"
+      "[22, 319, 34, 461, 40, 26]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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wOeCCFotHs5F9fX2vDddqNWq1WncVm5mNEfV6nXq9PqBlFNE0c7fNIO0KfBO4MyI+32T6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\nf6C3ao90c6mwAAAAAElFTkSuQmCC\n",
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f930823b750>"
+       "<matplotlib.figure.Figure at 0x7f6887295490>"
       ]
      },
      "metadata": {},
@@ -851,9 +928,9 @@
     },
     {
      "data": {
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FgH0QkgLAHTSrslLFaHKf6qtjB2rNWXrT6TRms9mihf7s7GxnbZ/N8QLA8TXD002LpFJF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6VpyuAmrI09BrVyXvjJiR9Sd1sz1HX/dwcw2Yt7+owCANAcFCBUz1aNus7rdeoOidpV1SnQVHY1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\nz+crVb150UUX8dhjj/Gf//yH3Nxc2rRpQ2xsLJ9++ikDBw4kIyODkSNHAvD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xmrSx+qo+S68sy3jnnXeWLfTT6VTbJ3RUPTzdtkgqVcSn4106BlokdTz7zkFNVtv3zUEF\ngN0ISQHgHpuqRdsYikbESy30aeHSYDCIJ0+exHjs9OBY2vZeob/SvMxtAerqsXF1kdQ+AapK7Pvt\nMgc1tfCvqledmoMKAHe5CgKAFfWFS11ooa8vXEoLXbIsizzP4+rqavn1zGYzF8mP5PmjD1KAus7q\nDNR0/FkNUDe18ae/n/0cYg5q+pFGrLT1hiAAPJSQFIDe62IL/aaFS9fX1xYuAUezyyKpehVqunFT\nluWd41L971HleBi7zkGdz+cxm81iMpnc+T3moALQdUJSAHqpay306cI2/RgMBsuFS6mV/j6DwUCr\nK3A0uwSos9nsTpi6ukhqUwt/247ZTVMPUFOFab1aeNc5qOkmnDmoALSRkBSAXqi30KdwNGlrC326\nWJ3P57FYLCxcAlqrHqBWVRUXFxfLX6tXOdZvbq0GqJta+B0LH2/XOaibAlRzUAFoAyEpAJ20Ohdv\nsVgsf62tlUebFi5dXl7GeDxu3dcDsIt0bLtvkVRq468vkXrsIinut+8c1PRn6uFp+mdbP6cBaDch\nKQCd0bUW+l0XLgH0WWrv3hagrn4+rC6SEqAex65zUNNn9urvq4enqy38Xh8ADk1ICkBr3ddC37aL\nKAuXWMecWNjf6mzNutWOg3RjajVA3dTGz+NsC1Aj3g+40+fiaohqkRQAhyYkBaBV6qHo8+fPYzwe\nt7o17xALlwB4uF0WSdWrUFNQV5blnT+7GqSmv5vHOcQc1NUAVcANwDZCUgAabVMLfUTEixcv4vr6\nulVt56sLl8qyXFaLTqfTjRVP9FPaNA2c1i4Bav3zKYWo9UVSm1r4hXSPZw4qAMcgJAWgUeoXnqli\nNFm9gGnLhYyFSwDdUf8cWr2xVZ+zWV8klapQq6ra2sLfhM+Dtt+Yecwc1PrrYg4qQP8ISQE4u3QR\nWf9nRDvnika0e+FS2y+OAc6pHp7uskiqvkSqSYuk2va5uytzUAHYRkgKwMnVFy6tttBvam9ssq4s\nXGrDY+wCQTT0132LpOoB6mqIapHU8d03B7U+MmeVOagA7SckBeDoHtJC3xYWLgFwSPcFqPXwNHUs\n1APUengqQD28XRZJpTmo6/7spirU9OsAnJ+QFICj2LRwqa2hqIVLAJzLLouk6lWoqVW8LMuXAtT6\nv6e/m8cxBxWgG4SkABxEvYU+haPJMVvoj9m6bOES+9BOD5zSLgFq/cZlClHT5/RqeFr/Mz7nHu8x\nc1DT63BxcWEOKsAJCEkB2MvqRddisVj+2qmqRQ/997d54RLN4IIVaJL6Z/Fqx0O9wjFVodZnhb/7\n7rtbZ6A63h3GtucydbCMRiNzUAFOQEgKwM662ELfhYVLAPBQ9fC0HqCmYG4ymdxp4U+f+6uLpNYF\nqT47D2dblXDEfnNQvT4A6wlJAdjovhb6Nl4IWbgEAPd77CKpbVWoPN6+c1CrqnqpAtUcVID3CEkB\nWKpXJdQvfCLaG4pauAQAh7XrIqlNAeq2KlQe7yEBavq5+u/dVoHqNQK6TEgK0HObWugjjrtw6Zgs\nXNqfpUPAOTkGtd+uAeq6Nv6IlxdJpR/p7+ZxdlkkVb/BXP/5+muyqQoVoM2EpAA906UW+sFgsPx6\nLFx6vLa87gAczzG32u8SoK7evE1VqBHrA9S2nbs03bbncpc5qPXw1BxUoG2EpAA9sBqKdqGFPm3g\nffbs2Z0WeguXANrN8buf6ucj60bhrLbwpwA1BavbZqB6Tx3GLm38KUA1BxVoIyEpQAfVq0W70kK/\nbuFSRESe5zGdTp1cA0CHpSrFbQHquhb+1TbxdVWoTdWm8RP7LpJKzEEFmkBICtAB9fa0VDGatLla\n9L6FS++8844ZowDQcylAXWeXRVLbqlDPrQmP4bH2nYOa1APU9Fo36TUCukNICtBSmxYutTkUrVeL\nWrgEADzWQxdJrQao26pQOYxd5qBuC1BXW/m9RsC+hKQALXHfwqU2ttBbuAQAnMtDA9R6G3/E+kVS\n6e8S0B3GoeegWvYFbCMkBWiorrbQp0ULqVr0MQuX0nZ7AIBD2iVAXe3qSVWoEesD1LaevzXVY+eg\nroan5qACQlKABulaC33E+oVLWZbFZDKJLMta+TUBAP1VPyfbtkgqVaGmADUFq9tmoDovOoxd5qDW\nw+1V6xZJmYMK3SckBTijrrbQ37dwiWZSmQsAj5eWC20LUNe18NcXSQ2Hwzu/T4B6WPvOQV0sFsuZ\n+eagQvcISQFOaF1rVtLWatHVhUvz+TxGo5GFSwAAK1KAus7qeWL67+fPn98JUDdVoXIY26pQi6JY\nBqWrc1DTnzEHFdpLSApwZJta6CO238VusrIs71SLWrgE71ONC8A+1s1BraoqLi4u1i6SSudg9UrT\nTbNQOZxts2ojdp+DmmbxG7UAzSEkBTiw1Rb629vbWCwWMZlMWnsX+dALl6CrfB8Abbcu2OH8dlkk\ntamNP8IiqVN46BzU1e+1dXNQBahwWkJSgANYnStaX7iUTojaVl3ZhoVLZmgCAH23S4C62tmU5sZH\nhEVSJ3LfHNT6XP9V6bVZDVBVCsNhCUkB9lCvFl3XQl8/SW3LiYuFS3B86XigUguAU6gHc9sWSaWb\n/OmmfzrXFaCexi6LpBaLhTmocGRCUoAd1O/Ap5PH5L4TkKZWO1q4BADQb2mR1LYAdV0Lf32R1KY2\nfg5jWxv/fXNQ66+LOahwPyEpwAabFi61+a7s6sKliIgsy+Li4sLCJQAAllKAus5qC39VVctOpHqA\nuqkKta1SdW1TmIMKhyUkBfhfD2mhb4t1C5eyLFvOFm37iSqH18SqZwCgWR66SCoFdGVZ3vmz64JU\nDsccVHgYISnQW49poW+y1Rb64XAY4/E4ptNpJ1vohXqH07X3Rld4jwP0U1uP/w9dJJXOXeuLpDa1\n8DtXOZyHzEFd92c3VaGmX4c2EpICvdLFFvp1C5dStWjXFy618fWCh/AeB+i3rn0ObFskVZ+vWT9f\nXw1QLZI6PnNQ6SshKdBp9Rb6dLKVnKqF/tCLm9YtXEpb6K+urpYnIgAA0Bb18HTbIqnUxp/O79P5\nvkVSp/GQANUcVNpGSAp0ymr7zmKxWP5am6tFLVwCoA9WL6YBkrRIaluAunodsLpI6rEBqmPUdrss\nklo3B3X1NUoB6moVKhybkBRovU0t9BHbZ+00mYVLAPSVzzfgoVKAus5qEUVVVcsW/no4t6mNn8N5\n7BzUenhqkRTHICQFWue+Fvq2BqPrFi6luaJdXLgEADSPSjm6ZpdFUvUq1NQiXpblnT87HA7vBK2+\nTw5rlzb+FKDWn/+qqmI4HEZVVZFlmTmoPIqQFGiF1VC0TQuXNs0k3bZw6fLyUgv9jtq6+RUAgPPa\nJUCtV6FGRMzn85jNZhERW1v4m3x90ja7BKjPnz/fGF6bg8quhKRAI93XQt/GANHCpcM79FIsOAXf\n5wDQfPUALbXyp6KG+n/XF0mlKtRU3biphd+5wOGsLoVavU7cNAc1IuJXfuVX4vOf//xJHiftICQF\nGqF+lzZVjCZtvhubQtGyLOOtt96KCAuXaDah8+N5DgE4hBS00Tz18HSXRVL1JVKHXCTF+zZVkW57\nTr/5zW8e+2HRMkJS4GzSHdf6PyPaHYquttAvFosYj9871D558sRgcRrNexMAYLNdZ5Het0iqHqCu\nhqgC1NNxY5tVQlLgZOoLl7rSQh8RL22hTwuXLi8vYzwex2KxiKdPn248UQIAAPrhvgC1Hp5WVbXs\nSqsHqJva+IHHEZICR9PVFvp0spJ+pE2KeZ6vbaFv49cI7Mf3OwCwr10WSdWrUNO1SFmWd/7sapCa\n/m7u8pywSkgKHNSmhUttD0VXq0XTwqXr62sLl85oMBjcCd8BAKCLdglQ69di9d0IEbG1hb/t1zLa\n5jkUISnwKPUW+vRhnLS5hX51C/1gMIgsy2IymcR4PG7t1wUAAHRLPehcbeVPAWK9hT8VgKRruW0t\n/G0KUB/6WNv0tXEaQlLgQVbvUC4Wi+WvtflO5LqFS1mWRZZlMZ1OzfkBAABapx6erpuFutrCX18i\nZZEUfSMkBe7VxRb6iPsXLh3q6xoMBlpAAAB4kF03qXM6XXxN7lskVQ9QV0NUi6ToGiEp8JL7Wujb\nGow+dOES9JFAH6DfUustwH0Baj08Tdda9QC1Hp4KUGkDISkQEfFSKNqFalELl+BhVD0DALCLXRZJ\n1atQU5FKWZYvBaj1f09/90N0scKX8xCSQk+tfljVdXXhUpZlPjw7RqgHAADNskuAWq9CTddwqYNx\n2wzUQ13PuYZgHSEp9ET9gyhVjEZEvPvuu5HneeR53soAsQ0LlwR5AAAAcSfo3LZIKlWhps7AdD27\nLjxNf+4h5vN5ZFn2+C+IThGSQoelD5X6PyPuttCnD5VzB4kPcaqFSwAAAIm27uNLc1C3Baj14p/0\n7xHvFQBtq0KtE5KyjpAUOqS+cKkeika0u4XewiUAAIB+27RIarFYxIsXL2I6na5dJPWXf/mX8du/\n/dvxPd/zPcsf3/3d3x0REc+ePYvLy8tTfykn85u/+ZvxJ3/yJzEcDuMHf/AH43Of+1xcXFyc+2E1\nlpAUWmxTC33E7guXmtgKbuESAAB917RzdGiy1eVPdZ/5zGfi05/+dHzta1+Lr3/96/H1r389/vZv\n/za+9KUvxQc/+MH40Ic+FK+//nq89tpr8frrry9/vPbaa/GBD3zgDF/NYXzjG9+IP/zDP4x/+Zd/\niYuLi/jZn/3Z+PznPx8///M/f+6H1lhCUmiZ+oyWTS30bdSHhUvacwBgO6EQ3OXcER4vz/P4+Mc/\nHh//+MeXP/df//Vf8eu//uvxZ3/2Z/Gf//mf8dWvfjW++tWvxte+9rX4i7/4i+W/T6fTeP311+OP\n//iP7/z5Nri5uYksy+LZs2cxGo3i2bNnywpa1hOSQsPVW+hTOJq0vYW+vnCpLMtlteh0Ol3bRtFW\nTm6Pp4mV0OA9CY/jcxOAY5vP5zEej2M0GsWrr74ar776avz4j//4nd9TVVX893//d3z1q1+N7/qu\n7zrTI93fBz/4wfi1X/u1ePXVV2M6ncZP/uRPxk/8xE+c+2E1WjvTFeiwVClaFEXMZrN48eJF3N7e\nRlEUy0rE1U1+h/h/nkKaFfPOO+/Et7/97Xj27FlERFxeXsYrr7wST548iclk0qmAFNpGwAcA8DLn\nSM21z2uzy+KmwWAQH/nIR+LTn/50XF1d7fvwzuZrX/ta/M7v/E584xvfiG9+85vx9OnT+NM//dNz\nP6xGU0kKDXDOFvpj/t0WLkG7qN56PM8hAHSbz/pmeujrUhRF5Hl+pEfTDP/4j/8YP/ZjPxYf+tCH\nIiLip3/6p+Pv/u7v4jOf+cyZH1lzSSjgDFIoOp/P4/b2Nl68eBGz2SyKooiI99vo2zZjNLXQP3/+\nPN5+++34n//5n3jx4kUMh8O4vr6OV155Ja6vr+Pi4kJACgDQQGaoA32wSyVp233f931f/P3f/308\nf/48qqqKL37xi/H93//9535YjaaSFE4gVYbW54pauNQvaXam5wMAAOC80kzSLvvEJz4RP/dzPxc/\n8iM/EsPhMH7oh34ofvmXf/ncD6vRuv2OgDPa1EIf0ayFSw9dfNOnhUsAAAB0Tx8qSSMiPvvZz8Zn\nP/vZcz+M1hCSwoHct4W+zdWii8ViGYoWRRHD4TCyLIvLy8sYj8et/bpoP9vt6QPvcYB+0oUEu9nn\ne6UPM0l5OCEpPMJqKNqVFnoLlwCaoa2fIwDQNULrbulLJSkPIySFB6hXiza5hf6hyrK800JfFMWy\nhf76+jpGo5ETggNQDQYAAHB+QlLWEZLCFikUTXNFu9RCnxYuzWazWCwWURSFhUtH5PkEAABohlQY\nBHXeEbBi08KltoeimxYuDYfDGI1GcX19fe6HCJyZGa8AALTNPuevqUgI6oSk9N59C5fa2kIfsdvC\npRcvXsRisTj3Q4W9CfUAAKDfHlrMpN2edYSk9E6XW+j3Wbikcow2a+v3KgAAcD5CUtYRktILXW6h\nX60WtXCpmYTRAEAbOF9pDtvUm8Xr0S1CUtYRktJJXW6hTwuX0o/BYGDhEkCLOE4DTec4BXRdURQx\nnU7P/TDwLC08AAAgAElEQVRoGCEpnVBvoU/VokkXqkXXLVzKsiym02mMRqNH/f0qHAEAAGirfap8\nVZKyjpCU1trUQh8RrQ9FV6tFR6PRSwuXAAAAgIez3Z51hKS0xn0t9G0PRh+6cIn2UbF7HJ5XmsZ7\nEgCg2VSSso6QlEZbDUUtXKKtvJ7H4Xk9PAHf43hPAkA3OUfqFiEp6whJaZR6tei6Fvo2V1Q2deGS\nmaRAIuADzs05CdBkzpWaaZ+ZpNrtWUdIylnVFy6litGnT5/GdDpdzt5s6wfRsRcuAQAA3eSGATzM\nPiHpeCwS4y7vCE5u08KlFIimu0BtC0ctXOI+TnYB4H7Ol+B9vh/gOLTbs46QlJMpiiKKouhcC329\nWrStC5eEd8fnBBcAAKAZtNuzjpCUk0mt9W2sEk26uHCpbY8X6szUpY28ZwEAzkslKesISTm5+0K5\npoUeTV24BEB7lGUZs9ls+VkSETEcDl/60eYbiQDQZfssB+I09nlthKSsIySFFRYuAfBYqfMgBaNl\nWS7HsdQ/R+rzrMuyXJ7kp9C0vuBQgAqcgiAI6APt9qwjJKX3+r5wqWmVu13leYbuq6pqGXZ++9vf\njsFgEHmev/RZ8vz5840zueuhaP3H8+fPo6qqOxWnqxWoAADsRiUp6whJaZxThEmrC5ciIrIsi4uL\ni1YtXAI4NGH+w9TnVKebbIPBIG5ubvbqPEjVoulzqCiKiIiYTqcvhafp/12vMtW+DwBwPyEp6whJ\n6YV1C5eyLFvOFlWFA2CR2y7WjWSp32Srqireeeedo4xmGQwGMRqNXvq769Wn97Xv16tQBagAzWXs\nAexun5v82u1ZR0hKZ6220A+Hw+Vc0a630D+ENnDazPuXU0ht9Gm+aPo8WTeSZbFYnPzxrVaf1q22\n7y8Wi2V4qn0fAHYnuG42i5s4BCEpJ7PrQWvf0GNTdU+6kNVCzzkJ86BdUvfBbDaLoihiPB5Hnuet\nW+B3X4CqfR8A6CMhKesISWmtdQuX0hb6q6ur5Vw4ALjPphttk8kksizr5OeJ9n0AoK/STXCo847g\nZB5y4bSp4s7CJQAOZdNYlr7faNO+DwB0nZmkrCMkpXHqF1IWLh2fNnCgTxaLxXK2aP0z5ZBt9F0+\npmrfBwCaZp95sdrtWUdISuOklsenT59auATAo9Tb6GezWVRVFXmeH62Nvs+fUdr3AYA2cZ7BKiEp\nZ5e2BqeqnsViEaPRKCaTiYVLdIaK3eNIJza2jR5OF96n69ro8zyP6+vrVrbRt/010b4P7eIztRna\nfuzvIt8b0H1CUk5uXQt9feHS7e1tDIfDuLi4OPdD7RUf+kBbjwEpZFvXRt/Em21tfZ6PQfs+wGaO\nZwCnJSTlpJ49exZFUURELOeKjsfjOxdHs9nsXA+vl5x8AW2U2uhTMBoRnd9G3zfa9wGAXSj44VCE\npJxUmi26rVVOWzIA66QwbDabRVEUrW+j30UXv6bH0r4PAMAxCEk5mcFgEFmWNa7tEU5B+A8PVx/P\nMpvNoizLGI/Hked5XF1d+TzhJYdq30+/V/UpAEB/CEmBZYDnQhA4t/oyv3ob/eXlZYzHY8cp9vaQ\n9v2IiNvbW+37Z+CGIgBwLkJSTmqXi4nBYLC8QAG4j5C//Vbb6EejUWRZFk+ePNEKzdGtqz4tiiKm\n0+ny+KJ9/7Q8f0ATpeM+zbLvzTWfNawjJOWkBBkArGujz7JMGz2Nc6j2/Xp46jwIAA7P5yuHICQF\nzMs8Ec8xfVZvo5/NZss51droaauHtO+n8FT7PrArxSUApyckpXEEdnSRk1za4pDH37IsYzabLcPR\n8XgcWZbFzc3NS8ESdMV91afa9wEAmklICgBExOPD/NRGn4JRbfS01bFu1mrfBwBoLiEpALC31Eaf\ngtHBYBB5nmujp/VO/d7Vvk8TpBsE3jvwMiMQmmmf10XnKpsISTmZXQ9c2u1Pz3NOm3n/nl6qcKu3\n0ed5HtPpVBs9HJj2fQA4rKIoYjwWh/Ey7wqAExDk0WZVVUVRFMtQNLXRX1xcxPX1tcBlhe91TkX7\nPgA83Hw+jyzLzv0waCAhKQDwktU2+uFwaBv9DjwvNIX2fQBYL3VCwSrvChpHxd3pec6BiPfa6Kuq\nirfffjuKoogsyyLLMm300CHa96EdzL+E4ymKIvI8P/fDoIGEpADQU/U2+tlstgxCJpNJZFnm4gx6\nRvs+AG2zzw0F7fZsIiSlkVQ10jWqdY/Hc/swqbU2/Uht9NfX1xER8fTpU3fWgZdo3wf6TnVvd2i3\nZxPvChrHBw/A4aTQIs0WrbfRX15e3qkYS6EGwK4O3b7vGATAsakkZRMhKSfnDlzzqMSDbklt9CkY\nraoq8jzXRg+c1D7t+xERz549e6l1X/UpAIeyWCyEpKwlJOVkHnJSK7ADeJh1bfR5nsf19XWMRiPB\nAtAom9r3nz59GpPJJCJC+z4A9zKTlEMSktI4TnDpKuE/h1RV1bLyaj6fx2KxiPF4HHmev9RGD9AW\n9RB01T7t++m/ASARkrKJkJSTcpLaTNrtj897n0NYbaOPiMiyTBs90Av7tO+XZXnnz2nf385YrOZw\nbt48vj+6w+ImNvGuoHEEdsBDdfmYkVpNZ7NZFEURo9FouY1eGz3Aeza179erT7Xv0zbeg3AcRVFE\nnufnfhg0kJAUgFbr2gVEvY1+NptFWZbLNvqrqytt9AAPcF/1qfZ9gP7Rbs8mQlIAOLOqqu4sXYp4\nr43+8vIyxuOxC3KgN07Zzqp9H6D9LG7ikISkNI52+9PznB+f55hVZVkuZ4umuUhZlsWTJ0/OWqnk\nfQqgfR+gy4SkbCIkBYATWNdGn2VZo9roXcADbKd9H6D9iqIQkrKWkBQAjqTeRj+bzWIwGESe59ro\nATpI+z50m+323aGSlE2EpDSWD6HT0QpOmzXt/ZsufOtt9Hmex83NzUttmwD0g/Z9gOMwk5RDEpJy\nUruEGU746KomBXkcTmqjT/NFm9hGz+mkzzA3+oBdaN9nE58jcDxFUcR4LA7jZd4VACfgJLdbUht9\nCkaHw6Ft9OzsodXPbrBAP2nfBziOoiji6urq3A+DBhKS0kjpAtKJHNAU9aVL6e5znucxnU610XM0\nPgeBdbTvA+xPuz2bCEmBxs10hCaoqiqKoljOFk1t9JPJJLIsczEJQOM8tn0/nROmLgnt+/Ae10rN\ntc9rIyRlEyEpJyWMA5osVdykH6mN/urqKkajkQtFAFprl/b9oihisVho34cNvOeb6aGvS1EUQlLW\nEpLSSMJUusZ7+nge+9yuttFnWRZZlvWyjd7SIYB+Su37Ee99Lk4mk4jQvg90k0pSNhGScnIuvptn\nMBhEWZbnfhhwEvU2+tlsFlVVRZ7n2ugBYMVj2/frwan2faApVJKyiZAUgM7b1EZ/fX2tjR4A9rBL\n+349QNW+/zAKS+B4VJKyiZCUk9r1g15rMvAY6eJsNpvFfD6/00Z/eXm59oIOADiM1L6/OrZG+/7D\n9PFrhodKlesPISRlEyEpwAkI/o8vtdGnYDQibKMHgAbRvk9bqeztFu32bCIkpbEESqcjwKOt0kXU\nYrGIZ8+exXA4jDzPtdHTeI65AHdp3wdORSUpmwhJaSQnNMA6VVUtL4zm83ksFosYDAYxHo/jyZMn\n2ugBoIO07wOHpJKUTYSkADRaVVV3li5FvNdGP51OYzwex7Nnz2I0GglIAaBntO8D+4xCKIoixmNx\nGC/zrqCxtCKejnb70zHPaDepEmQ2m0VRFDEajWyjBwB2pn0f2ES7PZsISWkkJyB0jff0dvU2+tls\nFmVZRpZlked5XF1dqRI9oXTTxHsWoH/6cvzXvg/9JiRlEyEpJ+XkAUjqbfSz2SwGg0FkWRaXl5cx\nHo8dLwB6yvGfc2lS+35fAuu28Hp0i5CUTYSkNJL2b+imsixjNpstw9HxeBxZlsXNzc2jLySgSVxM\nwcM5ltNk2vehOyxuYhMhKSflRKCZhNIcS2qjT8HoMdroHVdoGu9JgH45Rvs+sJt9bkyrJGUTISnA\nifRl1uO6Nvo8z7XRAwC98tD2/Xqgmn7PYrE4SPs+8D4hKZsISWkklY3QLqmtrN5Gn+d53NzcvFRV\nAQDQd/cFqM+fP4/RaBSDwUD7PhyYdns2EZICQmkebFMb/cXFhW30AACPkALP0WgU4/H7l+yp+rRe\ngbpr+74A9XH60A3WJypJ2URICsBOUht9CkaHw6Ft9AAAJ1IPO7fNP13Xvr8anGrfpyv2DbC991lH\nSEojqWyki9r4vk7tXbPZbNmWkmVZTKfTRrXRt+15bTrPJwCc10M/i+9r30/haeoGShWoEbG2dV+A\nSpc512UTISkAS1VVRVEUy9miqY1+MplElmWNPFluY/jcZE18jQGgjw71mZxa9zdVn+7Svr/6784X\ngC4SkgJCpp5LJ8TpR2qjv7q6Wi4MAACgWx7Svp9a+Ovt+5sWSEHTeZ+yiZCUk9r1YCS0g+OqL11q\nchs9AHA6ltOQaN8H+khICtAD9Tb62WwWVVVFnueNbqMHAKB5+ti+7wZCc3ltOCQhKaBy90RO/Tyv\na6PP8zyur6+10QMAcFDa94G2E5LSSIPBYNmuAewmnXiua6O/vLxc2y7VBY4XAADNpn2fJvHeYRMh\nKUCLpTb6FIxGROO30QMAsF2furz62L4PNJOQFNBu3zLpBHE2m0VRFNroAQA6qO/ndNr3uY9rWA5N\nSEojCe3oon3f1/W2o9lsFmVZxng8jjzP4+rqqrNt9JyH4+9hHPI59HoAwF2nbt+3HKjZvDYcipAU\noIGqqrqzdCkilrNFx+OxEwFosEN+f/peB4CHOUb7PtAPQlJO6iEfMCpn6JvVNvrRaBRZlsWTJ0+c\noEGH+F4GgNN7TPt+/bNb+367pdca1hGS0kg+bE4rPd/aSE5rXRt9lmXa6B9IezgAAI9xX/v+7e3t\n8lrpEO37nM9isYjxWBTGet4ZACdUluVyE/1sNovBYBB5nmujB6D33PBqBucicFcKPauqijzPlz//\nmPZ932eHsU+Rz3w+jyzLjvSIaDshKY3lRJmuSMHoYrGId999N8bjcWRZFjc3Ny+1+gBAnwkOzsv5\nN+zuMe37q8Gp9v3Tmc/nKknZyDuDRvLhQJulNvpUMZra6IfDYUwmk7i4uDj3QwQAoMGMwWqWh74e\n97Xvp+C0Pn5L+/5pzOfzOxXBUCckBSLi/bmOPnz3k7bRp2B0XRv9O++84/kFAIAeGwwGMRqNNlaf\nat8/rqIotNuzkZCUxtLuQ9Olu77px3g8jjzPYzqdaqOn1Rx/AQBOS/v+w+07k1S7PZt4Z3AW9x3M\nun4wp52qqoqiKJahaGqjv7i4iOvr63vft7awH4fn9bAcfwEAmkX7/uFY3MQ2QlJOqq8H4jYQNK23\n2kY/HA4jyzLb6AEAgLPTvv8wRVGYScpGQlIaSWDHOaW7r7PZbDmzJssybfQAAEAraN9fTyUp2whJ\nObkuHFjplnob/Ww2i6qqIs/zmEwmkWWZ9ywAAPRYCg67oivt+/sUVglJ2UZICkRE/6p3U7tJ+pHa\n6K+vr2M0Gh3lQ75vzzEAAA/nfJFzalv7vsVNHJJ3Bo0kTOIYFovFcrZovY3+8vKyU3eGAQBoP91M\nNElX2vcXi4VKUjYSkgKdldroUzCqjb6b3FQBgMPweQrso03t+9rt2UZICnTKujb6PM+P2kYPsErQ\nALSVcyXgkJrWvi8kZRshKY2kMuz02vqc1+9GzufzWCwWMR6PI8/zRrbRt/E5pn+8Tx9HwAAA3ZJC\nOw7nEO376fcuFoudq0+FpGwjJAVaZ7WNPiIiy7LGt9E39XFBnfcpAADntGv7flEUUVVV3N7erm3f\nf/PNN6Oqqnj99ddjOp1GRCx3U3TZt7/97fjFX/zF+Od//ucYDAbxR3/0R/GjP/qj535YrSAk5eQe\nUrHojh1Jar+YzWZRFEWMRqOjb6MHAACgOVbb9xeLRUwmk7Xt+3/9138df/7nfx7/8R//ER/+8Ifj\ntddeiw9/+MNRlmV84QtfiDfeeCM+9rGPNa778LH+z//5P/FTP/VT8Vd/9VdRFEW8++67535IrTG4\nJ6zSb8fB3d7e7hR+futb34rv+I7vEH6dyNtvvx2TySTyPD/3Q4mIu230s9ksyrJcttFnWdbKD7Jn\nz57FYDBY3sXkMObzeTx79iw+8IEPnPuhdMI777wTFxcXjTkWtNFbb70VV1dXMR6vvxc9m81isVi8\n1Fq2TlVV8e6778b19fWhHyZbPH36NK6urpyDnFhZlvH8+fO4uro690Pprdvb2xgMBj4Dzsyxv3me\nP38eWZZt/GznPNK4tclkcu/v+/d///d4880342/+5m/iy1/+cmRZFm+++WZ861vfitdffz3eeOON\n+N7v/d544403lv/+wQ9+8ERfyeG89dZb8clPfjK+/vWvn/uhNNnGEzzf4UBENKPFtqqqO0uXIt5r\no7+8vIzxeNyIx0jzeF8AAF2imw52s2uHapZl8frrr8frr7++DBF/6Zd+KSLeuzH6r//6r/Hmm2/G\nV77ylfjCF74Qf/AHfxBf+cpX4tVXX40vf/nLx/wSDu7f/u3f4ju/8zvjF37hF+Kf/umf4od/+Ifj\nd3/3d+Py8vLcD60VhKTAWZVluZwtOp/PYzweR5Zl8eTJk52Hb7dFW5djAQAANNFDrxeLorgTGF5f\nX8cnP/nJ+OQnP3nn91VVFW+99dZBHuMpFUURX/rSl+L3f//341Of+lT86q/+avzWb/1W/MZv/Ma5\nH1ortK9fld4QKHVTWrr0/PnzeOutt+Ktt96Koigiz/N45ZVX4ubmJqbTqTmjAABAI6ju7Y75fL7T\nSJHBYBCvvPLKCR7RYX30ox+Nj370o/GpT30qIiJ+5md+Jr70pS+d+VG1h0pSTk742UzHfF3qbfSz\n2Ww560obPQCQOD8E4Njm83mnt9t/5CMfiY997GPx5ptvxhtvvBFf/OIX4wd+4AfO/bBaQ0hKozlZ\nbq+0dKneRp/nedzc3Oy0rAQA6B83TgE4psVi0emQNCLi937v9+Izn/lMzGazeO211+Jzn/vcuR9S\nawhJOYtd2hWcJLdL2kaf5ouWZRlZlkWe53F1ddXKbfTHIPg/Ds/r4aj2B+ivqqqcswGtsc8YhFTA\n02Wf+MQn4h/+4R/O/TBaqdvvDBpJ+NlM+wQjqY0+BaPD4dA2+i08H8fheQUAAHbR9XZ7HkdISqOp\nZmqe1EY/m82iKIplG31atgQAAOzPkqDm8Zp0R1EUQlI2EpLSWD6EmiFto0+zRVMb/WQyiSzLvE4A\nAAC0gkpSthGSAi8py/LO0qXURn91dRWj0UgwCgAAwFntU+GrkpRthKQ0mnb706nPF00fHFmWaaM/\nIAtxgGTXY0E68dfmBwDwsn0WNwlJ2URISmO5GDyuehv9bDaLsixjNBrFdDrVRk+rCJ9pIu9JAIDm\nEZKyjZAUemRTG/319XXc3t7GcDiMPM/P/TABOs1NKACA89BuzzZCUhpLddjjVVUVZVnGbDaL+Xx+\np43+8vIyhsPh8vfOZjPPN+DYewBCUADoFmNvukMlKdsISTk5Hy7HldroUzAaETttoxeMHJ/nGACA\n+zhfhN3sE14LSdlGSAodsK6NPs/zuL6+to0eAABaxvk7HIeQlG2EpJzcrh/4qu42q6oqFovFMhRd\nLBYxHo8jz/OX2ugBAGAXWoqBrkvXzrCOdwa0RFVVd6pFI95ro59OpzEejx99QjsYDKIsy0M8VDgp\nN1Rom7IsoyxLYQQAwImpJGUbISk0WGqjn81mURRFjEaj5TZ6bfTtJMyD/qlX/89ms+UNqdlsFoPB\nIIbD4Us/HN8BoBmcvzeXmaQcmpCUxupjddi6C+ksyyLP87i6utJG33JCD+iP+hK92WwWEe9V/19e\nXi5/bTQaRVVVy8rSdPwvyzIGg8EyQI2I5e9PPw8AnJbP324oikJIykZCUjizeht9qipKF9KHaKPf\nVR9DaYBDSuHnYrGId999NwaDwdolemlkymoQWv976uFp+jOz2SyqqtpYeeriDQBgO5WkbCMkhTMo\nyzJms9kyHB2Px5FlWdzc3GizBGiRdKMrHdPTMXwymcRkMtnr71wNT2ezWUyn0+XNrBSeppEsab5p\n+n9r3QcAWC+dM8E6QlIaq0uVjamNPl1Ea6MHmqwrx95jqarqzo2u0WgUeZ7HdDqN0WgUb7/9doxG\no6P8vweDQYxGo5f+/tXwtCiK5c+ZewrQLhb7AZyHkBSOZF0bfZ7nJ2+jpzm6FPw3SfpeckFxGJ7D\n9eqL9FKbVhqN0oQbXdvC021zT+uBqdZ9zs1nJAAP4fyfQxOScnIPOYi17WQ5XXzW2+jzPI+bm5uj\nVRUdigAP4K40GmU2m8VisVge09vUAbDr3NN69am5pwDwPkEc9IeQlMZqQ2i3qY3+4uKiVRfRALwn\nHdNns9nymD6ZTCLLsk5dIG0KTyNebt1fnXu6bvZpl54bzst7CQA4FyEpPNC6JR3n2EYPwOOtu9l1\niNEoTb/Jt81D5p6m8NTcUwCgDdp8jsbxCUlptKYcwFIb/Ww2i6IolrPo0pKOLmhD5W7beY6hGaqq\niqIolsf1iDAzegePnXtar0DVug/NpK0YaBPHLA5NSEpjnfNgV7+ArrfRd7HlEqAP0nE9tdKnLoDr\n6+sYjUaO64+w69zTxWKx/PeIMPcUADg5I/HYRkgK/yvNXUs/0gX01dWVC2houFSl6/uUunXjUU6x\nTM/78D2PnXu6rvoUoA+c0zSL1wP6Q0hKox27Nbk+h66rbfQAD9XmsRApcEvjUUaj0bKVXuVAc+w6\n97Qenpp7CgDAMQlJaaxjXPSszqGrqiryPNdGH+ZlnornmKZr47GgLMtlG3264ZXneVxdXQlGW+a+\n8DT9c9vcU+EpAHRf285XaQchKSd36ouWdW30eZ6bQ8fJea/B4dQ7ARaLRavmRjf98TVRCk9XbVsa\nFWHuKQB0nc90DklISmPtW82ULpbqF8/j8TiyLNNuCdBSVVUtA7DZbBZlWeoEYKelUemf2+aeCk8B\noPtUn3IfISmdUN9aPJ/PIyJaVVXUBG1ssQW6LQWjqZU+IpY3vMbjsWM7G+27NKr+Z4qi0LoPAB2y\nWCzsHmErISmttbqcQxs99JeQvzvW3fRybOeQdlkatVgsoiiK5c+ZewrQX7bbd8d8Po8sy879MGgw\nISmNtRp61Fst6230lnPQFoI8WK+qquVNr/rs6CdPnrjbz8nUw9Pb29uYTCbL4/amuaf1ilWt+8Ch\nOF+E++0TXs/n8xiPxWBs5t1Bo1VVtbxorrfRT6dTrZYALbZ6fB+NRpHneUynU8EojbLL3NPUrm/u\nKXAojhVwePP5PPI8P/fDoMGEpDROaqO/vb2NxWIRL168iCzL4smTJ1rbjkiVI3Bs9TEpqd3JUj3a\nat+5p+lcRus+TaStGOiyxWKh3Z6thKScTToJW7exOMuyGI/HUZZl3NzcnPuhAvTGYDCIsiwP9veV\nZblcvGRMyvuEEN22y9zTsizNPQWAE0rdS7CJkJSTS8HofD5fLucYDAaR5/mdjcVFUSxb7KFLVGkc\nnkroZqlvpE83viaTSWRZ5r2/J8eNbtgWnm6be1oPTLXuA8B+s3stbuI+QlLO4vb2NoqiiCzL4ubm\nxt2cBhAyHZ+LWboqdQSkNvqyLF+68cX+PH/dt+vc03r1qbmnAKfhRmVz7bO4yUxSthGSchbT6TQi\nth/UhHYAzVVV1bLifzabRUQIRuHAHjP3dFP1KQD0VSrUgk2EpADATlIwmlrph8NhZFkW19fXMRqN\nBDA1bvJxbLvOPV0sFsvw1NxTAPpMuz33EZICd2gnAerSDOnUSj8cDiPPc6NStnAM5ZweO/e0Xn16\n6tZ9NxfgPakiHDis+Xwe47EYjM28O2gs7fan5aL+NNL72vNNk1VVFbe3tzGbzaIoihiNRstWehdt\n0E67zj1NladlWUZEnHzuqc9HAHaxzzVVURRmkrKVkBSATnBT5XHKsozZbBYvXrxYtubmeR5XV1eC\nUeiw+8LTeoC6ae7pavUpQJcocOgO7fbcR0gKQOs5cd1ParedzWaxWCwiy7JlC9L19fWZH123CfVp\nunq16H1zT+vhqbmnADSVkJT7CElpLO32p6cVHLotBRtp8VJZlpHneUwmk8iyLAaDQdze3sZ8Pj/3\nQwUa7L6lUemf2+aeCk8BODUhKfcRknIWAlD6ynufU6uqKhaLxTIYjYjIsiwuLy9jPB4LKICDSeHp\nqm1LoyLen3ta/32nXhrFe9wsB9pin2uqoiiEpGwlJKXxnKwBPExVVVEUxXIjfUREnudxfX0do9HI\nMRU4qV2WRlVVFfP5PKqqiufPn6+de3rspVEAtMs+i5tst2cb7w4aywkwwO5SwJBmjA6Hw8jzPJ48\neaKlFWikdeHpYrGIyWRi7im9pusIjkO7PfcRkgJLWsFpq76+d6uqWlaLzufzGI1Gked53NzcrG15\nBWiL++aermvdF57SJd63zaGzsTuEpNxHSErj+VCia/oY5nE4qaIqhaNZli1njK62sgJ0zbbwdNPc\n03rFqtZ9gP4qiiImk8m5HwYNJiTlLHat+nLiStd4T7OP+kb6xWIR4/E48jyPq6srwShA7Db3tB6g\nptZ9c08B2mmfYqr5fB43NzdHekR0gZAUWOpryzI0UX0jfVmWkWVZTCaTyLLMxTucgO+zbtgUnka8\n3Lpfn3taD0y17gN0g3Z77iMk5Wx2ufMjtAP6oqqqZTCaLtTzPI/Ly8sYj8cnuzB33AX6Yte5p0VR\nLH/O3FOA9iqKQkjKVkJSzsKJJMB7F+JFUSxnjEbEWYJRAN6379zTddWnWveh/VJ1Oe2nkpT7CEkB\nTkiV3nG06XlNwWhqpR8Oh5FlWVxfX8doNHIxzXGUZYz/5V+i+sAHYvHRj5770UArPWTuaVEUUZZl\nRNVCXEAAACAASURBVIS5pwBHsM+5v5CU+whJabQ2BR9d4PmG46iq6s5G+uFwGHmex83NzUuVSnRD\n046lw//3/yL7v/834uIingtJ4aAeO/d0XfXpOTTtuNVn+yykgT566PeJdnvuIyQFgCNIF8Oz2SyK\noojRaLRspdey1W1NvLAtP/jBKP4/e3ceJMtZ3vn+l5mVWdVVdfpoRRsIJCS0yxaLYZBBIwGjMIEk\nfIWHsdEwjsAwYcc1NtxATBiBl8DIhIUx4GXg2jjgYkJmR8IsAQaMDAYMwrK1YAgJDQIJHSSd/fSp\nXN73/qHzpqqrq7urq6sqt+8n4oRQny6UXZWd9eavnvd5zjpL5qijij6U0iMowixN2vc0y7I8PC26\n72kZr2EAMAtUkmIzhKQAAMyIMSavFnWLsCiK1Ov1CEZRrCBQ8rM/W/RRADhiu31Ph6tP2boPAJPJ\nskytFjEY1sfZgVJj+/di8XzPH89x/bgb2DiOlWVZHoz2+31uWgEAWzJp31NXeUrfUwCYHJWk2Awh\nKQAAW5RlWT54yRijMAzV6XQUhiE3pACAmdssPB0OUNfre0p4CkyHHrHl5K5xW0FIis0QkgIAKm/e\nFbrW2lXBqCSFYahut6tWq8XCGQBmgJ0WWzcceG7W93Q4PB3X95T3MgB1x+AmbIaQFIWYdBHG1mQA\nRbHWKk3TvMeopHwbfRAEtb6Z5LoLoCh1vrYu2mZDo9w/h/ueStLKygoBKoBaopIUmyEkBZAjlEbT\nWWvzoUtxHMv3fUVRpB07djTmJrEJP2PReI4BFMmFp6OMMTp06JDCMBwbnrJ1f3FYjwPzQUiKzRCS\nohAsptBUBNHl44JRVzEaBIGiKNLy8vLYm0gAAOrIrc9HJz+P9jx175v0PZ0vnj9gY9P0iiUkxWYI\nSVFqBEoA5sH1ZnPBaBiGeY/RrTaABwCgztYbGiVt3PfUhaVs3UfVcT9aH/QkxWYISQHkCKVRZZud\nu8aYfPBSlmVqtVqKoki9Xo9gFKXHtRlAGW3W99T9Gd66Py44JTxF2XF+1gOVpNgMISkAoPLWW7gO\nT6Q3xigMQ3U6HYVhyGIXlcG5CqBqNgpPhwPU0fB0vcpTroMAZoGQFJshJEWpUdmIuuGcni9rbR6M\nupuuKIrU7XbVarW4yQIAYB3T9PfbqvW27o+Gp8YYpWmaf52+pwBmge322AwhKQCg0oZvqgaDgSQR\njAIAUCHb6Xs6rvcp7/1A/U3zwU6apmuG0wHDODtQelTdLQ5VjqgKa63SNM230ktSEATq9/sKgoCb\no23iOgAAKItJ+566ytM69D3lfRiYD2PMmmsJMIyQFKVWlYUMgPmz1q6aSO/7vqIo0vLysgaDgTzP\n45PhGeC6Oxvc4ALAfE3b93Rc9WkZt+6X7XiabBGtKACUA3eTKARvMmgywpPJuW11cRwrTVMFQZBv\npR/XzwwAADTbVvueGmMkqRx9T5NEwf33y+v1pF5vcf9dAIAkQlJUAMHH4rDdfv74gGBzxpi8WtRN\noIyiSL1eb2yvMolzFwAAbGy7fU9HK1DnsaYLfvxjtf7P/1F7eVk69tiZ//8DdUKFL+aBkBSlRvAB\nNIPbChfHsbIsy4PRfr/P4geVwzkLANUyad/T4fB0Hn1PzQknKDt0SMlRR4muiQCweISkAIBCZFmW\nD14yxigMQ3U6HYVhSMgEAAAKt92+p6Pb9jdb39ilJaXnnqvswIF5/lgAgHUQkqLUPM/L+wRhMajc\nxbxYa1cFo9bavL9oq9UiGAUAAJUwad/T4fBUKknfUwDAughJAeRYoM1f01pIWGuVpmneY1RSvo0+\nCALOOQAAUBuThKfunxv1PXWPYZ1UDrwWQHMQkgIAZspamw9diuNYvu8vJBhtUvgMAMCsEQTNz1aH\nRknSoUOH5tL3FKiLaa5Z/O5gM4SkKMSkF6emVd0BVeWCUVcxGgSBwjDU8vLymj5e88CCZ3a47gIA\nsDijfU+ttTp48KB6vV4enLqWRRv1PSU8BYDtIyQFkCMcwVa4agcXjLZarbzH6LhKCQAAAExmmqFR\nEn1PAWA7CEkBYIGqPozMGJMPXsqyLA9Ge70ewSgAYFv4oBbY3KRDo9wun/X6nhKeAsBahKQoNSob\ngeK5ifRJkijLMoVhqE6nozAMWVgDAACUwFb7ng6Hp+O277PGexT3ouXE64J5ISQFkCOUhqRVfa/i\nOJYxRlEUEYwCAOaO9xhg9jbauj8cntL3dH1N/bnLbiuvS5Zl7HzDpghJAQB5MOq20ktSGIbqdrtq\ntVqlXxgS8AMAAGzNNH1PXXg6GqKydR9llySJwjAs+jBQcoSkKDWCD9RRWc5pa63SNM2DUd/3FYah\n+v2+giBgoQsAALBgZVgnTtr31BijNE3zr9P3FGVGSIpJEJICwAIVvUh0Tfxdj1Hf9xVFkZaXl9dU\nEQAAAGDxil4vrmc7fU/Xqz4FFoWQFJMgJEUh3BuitZY3xxKhcreerLV5KJokiYIgUBRFWlpaIhgF\n5oRrKQCgSSbte5qmaR6e0vcU05omR0jTlJAUmyIkRakR2gHTMcasCkbDMFQURep2uzQsx4a47gIA\ngFnZTt/T0erTIrbuU9RTH0mSqNUiAsPGOENQGN5sgNkankifZVkejPb7fX7fgAUiaAZQRVy3sEhb\n7XtqjJEk+p5iamy3xyQISQGswgJ5vmYdngxPpDfGKAxDdTodhWHYqMUioRQAANvXpLUDymm7fU9H\nK1A5p+EkSaIoioo+DJQcISlKjeBjsVhElJ+1dlUwaq3Nt9G3Wi1eQwAAANTSpH1Ph8NT+p7WEz1J\nMS+EpABQctZapWma9xiVlG+jD4KARR4AAAAaa7Pw1P1zvb6no9v2WVvXU5qm9CTFpjhDUHpUkqKJ\nrLX50KU4juX7PsEoAABAzTEoaHZceDpqo6FR0uq+p8OP4XWpNgY3YRKcISg13ogWi/YGi7Hec+yC\nUVcxGgSBwjDU8vLy2AUeAAAAgK2ZZGjUcPWptVYHDx5kaFTF0ZMUkyAkBYAFGl1Eub5JcRwrTVMF\nQZD3GB3XsB4AAADA7I0LT7Ms02Aw0NLSEn1PS2Sawh56kmIShKQoNSobUUfWWh0+fDgPRsMwVBRF\n6vV6BKNT4loxOzyX5cRrAgBAcSYZGuUGrG7U95TwdHa2+jwmSUJIik0RkqIw3IiXD6/J/LiJ9IPB\nQMYYpWmqTqejMAxZKAENw+88AAD1sFF4ul7f0+GKVbbuLw4hKSZBSAoAczD8SXIcxzLGKIoitdtt\nDQYD9fv9og8RQEVwwwQAQLVM0vfUVZ8Ob92n7+n8sN0ekyAkRSUwTRBV4ILROI4Vx7EkKQxDdbtd\ntVoteZ6nNE3zvwMAAABQXrO+D10vPHX/rfX6nrqwlK3706OSFJMgJEWpcdFH2Vlr8+AzjmN5nqco\nitTv9xUEAecwAACoBIoSyoHWV801Sd9T17bLfa2pfU+nuV4RkmIShKQoDP0vy4fXZDJuW0wcx0qS\nRL7vK4oiLS8vr1nUYHE4dwEAQB3UPeDC1kzb93Rc9WmTt+4TkmIShKQoPRfcNfVijnKw1uahaJIk\nCoJAURRpaWmJYLQEuD4AQPW5LaUAgM1N2vd0uPq0yX1P3eBcYCOEpACwDtcLyIWjYRgqiiJ1u92p\nb+Ko1gWagd9zAABQhO30PV2v+rQOGNyESRCSolBUiJZTk1+X4Yn0WZblwWi/32/scwIAAACg+rbS\n99SFp2Xse0pPUswLISkKM+lFjcq7xWlqCDg8kd4YozAM1el0FIZhY58TNJc755v8Ycl28bwBAFAP\nTVkPbafv6WgFalm37lNJikkQkgJoHGttHoy6N3m3jb7VapXyTR0AAAAAFmnSvqdZluX/W1Ip+55S\nSYpJEJICaARrrdI0zYNRSYqiSL1eT0EQLPQNm8ro+eB5BQAAAOZvu31Px1WfzhshKSZBSIrSY7v9\nYrnnuw7VlNbafBp9HMfyfT/vL7roYNSpw/NaRjyvAACgDuqyDkdzTdr3dDg8XUTfU7bbYxKEpABq\nxQWjrmI0CAKFYajl5eU1b9QAAAAAgPnbLDx1/9yo76n7w+AmzAshKYDKc59EumC01WrlPUbHbQEB\nAAAAgM1Q2Tt/LjwdtdHQKPc4Y8zEfU+pJMUkCElRemy3X6yqPN/GmHwivXvDcz1GCUYBAAC2hjAI\nQJlsNDRqMBhIkoIgGNv39IYbblAURTrrrLN09tln68lPfnJjKkmzLNPTn/50Pf7xj9fNN99c9OFU\nDiEpgMoYnkifZZnCMFSn01EYhpVZ1FclhAYAAACAsnHhqed5a0JPV3l61lln6bbbbtMHPvABff/7\n39cDDzygE088UXfeeaee9axn6ZxzztE555yjs846S71er6CfZD7e8Y536Nxzz9X+/fuLPpRKIiRF\nYbYSahEqNZO1Nt9WEcexjDGKoqhywSjmj/AZAAAAaAZXMTrKbd1/6Utfqpe+9KX511dWVvS6171O\nF154ofbv36+bbrpJb33rW/X9739fJ5xwQh6auj/nnXeejj766EX+SDPxox/9SJ/+9Kf1hje8QX/y\nJ39S9OFUEiEpSo8grFlcMOq20ktSGIbqdrtqtVqcD8ACuNCZ3zcAAABU3dLSknzf15VXXqkzzzwz\n/3qWZfrBD36gu+66S3fddZe+9rWv6a//+q91ySWX6K1vfWuBRzyd17zmNfrjP/5j7du3r+hDqSxC\nUhSGm+9yKqIiz1qrNE3zYNTzPEVRpH6/ryAIOFcAAADQCHxICcyHG/A7LAgCnXHGGTrjjDN0xRVX\nFHRks/GpT31Kj3vc43TRRRfpy1/+ctGHU1mEpKgEttHWj7V21UR63/cVRZGWl5fHTjesGxbAAAAA\nQLmxZq+Pug9u+trXvqabbrpJn/70p3X48GHt27dPL3/5y/X+97+/6EOrFEZAo/R4U6oPN4nwwIED\n2rNnjw4fPqxWq6Xl5WXt3LlTS0tLtQ9IOZ8BAAAAYLHSNK11SPqWt7xF9913n37wgx/oxhtv1GWX\nXUZAOgUqSQGsMuvt9saYVRWjYRjmPUbHNdsGAAAAAGA901T41r2SdBTFOdMhJEXpMbW6eoYn0mdZ\nplarpSiK1Ov1CEYxF1wnAAAAAKynSSHpJZdcoksuuaTow6gkQlIAMzE8kd4YozAM1el0FIYhn2IB\naJzNQntCfQAAgMWp+3Z7zAYhKYCpWGvzYDRJEhljFEWRut2uWq0WwegGXNUjzxFQT/xuAwBQD9Za\ndsLVRJMqSTE9QlIUZis3kVTcLM5G25attUrTNN9KLynfRh8EAcEAUBO0LwBQBD5ALBbPfznw/gts\nbprrlTGm9kOCsX2EpCg9FmvFstYqSZI8GPV9X1EUqd/vE4wCAAAAM8b6GgCKQUiKQrEAKCdrbd5f\nNEkSBUGgMAy1vLzMp28AsE1ZlskYoyzL5Ps+74UAAABACRCSolCTlMmz7XMxjDFKkiTfTu8m0ne7\nXfrwzBjn9Oy56whbBVFWo8PtPM/Lw1LP8+T7/po/nMvN0frud+Xv2aP4535O4j0XAICZ4/4LkyAk\nBRrMGJPftLtpf77vq91uq9PpFH14AFBp7ho7GAxWDbfzfV+DwUCtVkvWWllrZYzJq0vdMDwXnrqv\nu38nPK2fzj/8gxTHSp/4RJmTTir6cAAAABqJkBRomOGJ9FmWKQxDdTodhWEoz/N04MABbsABYEqu\nKj9JEu3du1dhGGppaSm/xrrvcTzPy8PPYcPh6WAwUJZlStM0n7I7ruqUa3d1Hb70Uvm7d8uccMLE\nj+m94x0yRx+tlZe/fI5HBgDNxi6lcprmdeF1xCQISVF6nuetuqHE1lhr88okt80ziqJVwSgAYHrD\nVfmuz2gQBNqxY8fU19jh8DRN07w39HDVqQtkjTGEpxWXnnvulr5/6b3vlZ9l8h56aE5HBAAA0DyE\npEANuWDU3bRLUhiG6na7arVaG94w0y9z/niOgepzAeVwuxL34ZOr1p9HOOl5noIgWDNEj/C0WVae\n/Wz1P/1pWV5DAACAmSEkRWG4OZsta63SNM1vziUpiiL1+30FQcDzDQDbZK1d1cfZDbjr9/uFX2O3\nEp5mWSZJeWAaBAHDoqrm7LN14Oyziz4KAHPgPtwCMFuscTAJQlKUHlV367PW5pVMSZLI931FUaQd\nO3asuVEG6s5dK1gAbR/X3ceUORidxHrh6XBwOm5Y1LjKUwAAgDJgzY95ISQFKsbdsLvBIEEQKIoi\nLS0tzSQYJRwB0HSjH0C5YLTX682kuqcMi3oXfg4bHhZFeAoAAGEc0DSEpEAFDPe+S5JEYRjmPUbZ\njgMA2zcajLoPoJp0nR0eFjWM8BRoBrZ5AwCajpAUpdfUysbRacmzrmRCcZp6TgNlQzA6mUnC0yzL\nlKYpw6IAAABQWYSkQIkMT6Q3xqyalsyNJQBs3/CQuziO5xaMNuGDkOHwtNV6bEk5blgU4SkAAJiF\nadZYWZbxATgmQkiKSqjrzaa1Ng9G3U2ku1lvtVqF3DRS5QigbkaDUTfkbnl5eS5D7poe+K03LIrw\nFAAAzMpW1giuZR2wGUJSFG6zZth1u0FyN+tui6ekwoNRoA4I+DFs0cEoNreV8DTLMkmPDZgKgoB+\npwAagUFBwOylabpq1wuwHs4SFKZJb/7jbtbDMFS/31cQBI16LkCYB8zLcHV+HMfyPI9gtALGhacM\niwIAlAGhdT1QSYpJEZKiEqoYKI0OBKlKFZPneTLGFH0YAApWlevuaDAqPVqd3+/3qRiosEmGRRGe\nAgCASaRpSkiKiXD3gEJNcuNSpZsbt00wjmOlacqkZACVVIXrbpZlGgwGa4JRqvPrjfAUAIBmm6a6\nl0pSTIqQFNgmY0xeLeouvlEUqdfrEYwCwAwNV4xaawlGkZskPM2yTGmabjosCgAA1EuSJOwwwkQ4\nS1AJZdv26SpU4jhWlmUKw1Dtdlv9fp8bLEykbOd0XfC81s9wMGqMYdAdtmQ4PB2+ORo3LGo4PJWU\n9xB34Snn2/xxDQcAzEOSJIqiqOjDQAUQkqL0ynBT4m6mRm/UO52OwjAsxTHOCkOF5q9O50uZ8LzW\nB8Eo5m3csCjpsR63hw8fznuLb1Z5yjk5WzyfAMqEwU31QE9STIqQFFjHuGEgYRhyow4AczD8QVSW\nZbUPRvkwqpxceCpJ7XY7//q4ytMsyyRJvu8rCAK27aPyCIPKgfcHYGPT/I7QkxSTIiRF6S2ystFa\nqzRN8x6jEsNAAGBeRoPRMAxrWaGP6htXecqwKADzwrUC2Ng0g5voSYpJcJag8dx2Otdj1Pd9RVGk\nHTt2rNmG1wRstwcwTwSjqItJhkURngIAUDx6kmJShKRoJGvtqon0QRAoiiItLy83MhjFYhFEo2nc\n9uQ4jpWmqVqtFsEoaovwFACAcqEnKSZFSIpCTRIWzSpQGr5Jdz1JXI/R0RsZANVE+Dwbs7juug+j\nhoNR176E4AdNNEl4mmWZ0jQt17AoaxX98z9LWab4P/0nie2KAICKcWtRYDOcJai10W2d7ia91+sR\njAI1Q/BWPNe+ZDAYrApGueYC6xsOT4dv4MYNiyokPDVG/t69kjFSlhGSAmgM94Exa8xymWbIHIOb\nMClWOaid4Yn0xhj63W0RW8EBbIULRl2VfhAEarfbBKPANo0bFiUVEJ4GgQaXXPJoSNpub/OnAgBg\n8QhJMSlCUpSeW9iv94mRtTYPRt2NQhRF6na7arVaBKMoJYJoVNm4YNRddwlGH8XvOOZlK+FplmWS\nJN/3FQTB1P1Obbc7058BAIBFoicpJkVIikJNW7VorVWapvlNuiSCUVQG5yeqyF13B4MBwShQQuPC\nU4ZFAdUzzVZiABujkhSTIiRFZbgbdLeV3vd9hWGofr+vIAhYTMwI2+0BOOOuu1EUaWlpaU0VGx7D\n+xHKYpJhUYSnAIAqoScp5omQFIXb6CLntnRK0t69e/Mb9OXlZW7QAaxCwD8bLjgZDAY6ePAg112g\nhghPMQ7voQDqKk1TRVFU9GGgAghJUTquj1Ycx0rTNL8p37Fjx6qpr0CVcSOCMnG9nd1WemOMgiAg\nGAUaZpLwNMsypWk632FRKAyvG/AYWh/UR5Ik6vf7RR8GKoDECYVybzrGmHwAiCuFj6Ion468e/du\net6hNqh4RBkMD70b7u28Y8cOHTp0SFEUEZACkLQ6PB3+wHrcsCjCUwBA2bDdHpMiJEWhsizT/v37\nZYzJg9F+v79mAU2otDg810B9rReMjvZ25jpQPrweKKNxw6IkwlMAQLkw3R6TIiRFoXzfV6fTURRF\nLI4BYE5cMDoYDCSND0ZRXrxG9eI/9JD8PXuUnnFG0YcyN5OGp3Ecyxgj6dE1oTFGaZrm/865DwAY\nxeAmzBMhKQrleZ7CMJzoIkcVDQBMbrhi1BiTtzBptVoED0CBlm66Sd6+fVr5pV9SdsopRR/OQo0L\nT4f7nQ4Gg1X/ZFgUmog+mMDsUUmKSRGSohJYKCwO22znz/O8vHIGs8O5Oz4Y7Xa7BKNAiSRnn63g\nJz9RdswxRR9KKQz3O43jOO+HPByeuoFRbts+4SmARSCwro80TRkCjYlwlgAAUGFuy6qrvCIYBcot\nfvaziz6EShgOT4cRngIAtort9pgUISkqo+kVYgDguGA0jmNlWaYwDLW0tDRx+xIAKKNJ1nqbhadZ\nluW9TRkWBQD1M02FL9vtMSlCUlQCi1gATTcuGO10OgSjAGpl2uvZRuHp8LAoV3VKeAoAzUElKSZF\nSIpCsQgtH/o6zh/PMSblbujjOM4/AScYBYDJjRsWJRGeAkCTEJJiUoSkqAxCJQBNYK3NK0Zdk/ko\nitTv9xd2g06QD6DuJg1P3SA8SfJ9X0EQ1Lrfad1+HgCQ2G6PyRGSolCTLsRYsAHYTJWDvTIEo5it\njc5F95oyNRcon3HhaVOGRVX1PbROeA3Khffp+qCSFJMiJAWwCjfvwGJYa/Ot9EmS5MFor9db01MP\nAFCczYZF1T08xeJxngDrc21RtoKQFJMiJEUlVLlCDACc0WA0CAJFUaRut0swCgAVQ3gKANVASIpJ\nEZICwIIR+jcLwWjzEHYAzbZZeJplmYwxStOUYVEAsAD0JMWkCEkBAJgxa63SNM37jPq+r3a7TTAK\nAA22UXg6PCzKVZ0SngLAbFBJikkRkqISqLxbLPd8swBH1RR5nRgXjEZRpOXl5TXTkwEAcMYNi5II\nT4GicT9UTtO8Lm4wKrAZzhIAQC0UsYglGAUAzMuk4WkcxzLGSJJ831cQBPQ7BYAhVJJiUoSkKBSL\nNjQRldHV5vrJuWBUktrtNsEoAGAhxoWnDIsCgPXRkxSTIiRFJRAqLRbPN7DauGA0iiL1+30FQVC7\nG02uAQBQLZsNi5okPHXfi+KwvRuYjyzLKGbARAhJAQBYR5ZlGgwGjQhGAQD1s5XwVJJWVlaoPAVQ\natN+mMM1DJMgJAUAYMhwxai1VmEYEoxi5jiXABRpXHh64MABdbtdSY++FxpjlKYpw6IAlA7XHcwL\nISkqga2fqBvO5/mY9nkdDkaNMYqiSN1uV61Wi0UYAKAxNqo8HR4W5bbsE56izmh/ADQPISmANQil\n54vF1nxs9bwlGAUAYDLjhkVJhKcAgHJK01QPP/ywwjBUq9VSq/Vo/BkEgTqdTigps9aa0ccRkqIy\nCO0AbJcxJg9GsywjGAUAYBsmDU/dB5KS5Pu+giCg3ykAYG7uvfde/c7v/I6OPfZYraysKMsy9Xo9\nlyv9jaRbJf2J53n+cFhKSIpKYOEEYFqjwWgYhup0OgrDkGsLAABzMC48HTcsylWeMiwKwKRog4BJ\nHH300brmmmu0Z88effzjH9fy8rKe//zn67vf/a4knSbp6+MeR0iKQnFxKye226Pq3Ja/wWBAMAoA\nQAls1O+U8PRRrL+B+eB3q3mOPfZYXXnllfrCF76gKIr0vve9L/+7N77xjW+S9GuS/kzSqjcUQlIA\nWDBC6Pmw1irLMu3fv19pmqrVahGMbgPnKIBF47rTTISnq9XhZ6gLrkn1we9V8xhj5Pu+kiTRnj17\ntGfPHvm+r16vJ0lnSHJvOoSkqB5CJQDjWGvzrfRJksj3fS0tLanf77MY2gauudvH81ddvHbF4toN\nZ7PwNMsyGWOUpinDojA3nDv1wOvYPO6945JLLtHXvvY1PfOZz9Tznvc83XHHHZL03yS9+si3ZsOP\nIyQFMBY3iSgra22+ld5VjEZRpFarJWOM2u120YcIoOK4mQLKa6PwdHhYlKs6JTwF6oX7VGyF7/t6\nwxveoF//9V/Xt771Lb3yla/UU5/61MslJZJkR04oQlJUBhfDxWHBiLJxwairGA2CQO12W71eL79J\nOnz4cMFHCTyKaygALN64YVES4SlQR/yOYjNuu/0nPvEJfeUrX9Ff/MVf6Morr3R/fbWkZ0n6Lc/z\nAmttXk1KSIpK4CKIOmEr82TGBaNRFKnb7a6pHgHqjmsGAExn0vA0jmMZYyQ9WnkUBEHt+p0CQFOs\nrKxo7969uv322/Xwww9r165devDBB/W4xz1Oks7SY3koPUkBAOVkrVWapnmfUYJRAADmz30Q06Qg\ncFx42tRhUUCdud9fNMtPf/pTveUtb9FNN92kVqulyy67TGmaKssySTpH0luPfCs9SVE+1tpNL1xU\n0SwOlY7Yjju9O/Vd77u6ylylQMGm3z8ajPq+ryiKtLy8vKbqAwAAYF42GxZFeNosriUDqi1JEoVh\nWPRhYMGe9KQn6T3veY9e97rXadeuXbr44ouH//ql7n+M9iTlNx6FmnTxwCIDqI63BW/T/w7+t77h\nfWPd73Fb6Q8ePKg9e/bo0KFD8n1fy8vL2rlzp5aWlrYckBLuo654DwSAYrkg1A2L7HQ66na76vV6\nWlpaUhiG8jxPWZZpMBjo4MGDOnjwoFZWVjQYDJQkibIs23SdMknhCNBk01S9E5I2k2uf8sgjEwoj\n0gAAIABJREFUj2jPnj2SpH/6p3/Si170Inme92bP844e9zhCUgAoQJ3DvP9q/qsuM5fpAnvBqq+7\nitFDhw5p7969MwlGAQAAirJZeNpqPbpxM01THT58WAcPHtShQ4d0+PBhxXGsNE3zIVIA5oOQtJnc\ndfUzn/mMvvnNb0qS/vZv/1bPetazJKkt6TckyfO8VTegbLdH4Sb5FIgKscXi+Z6vulcIXG4u1+W6\nXNKjb05ZluVb6SUpiiL1+/38xgHl43le/ukrAADYmo227Q8Pi3Jb9oe3dbsPld2W/bqvG4F5S9OU\nkLTBgiBQu93Wl770JbXbbV177bV64xvf+KCk7rjv5w4VADBzwz1GpceC0SAIWOwDQNVlmcI77lB2\n3HEyJ59c9NEAlTFuWJT0WHjqtuWPhqfj+p2yngImQyVpM7lr5LnnnquPfvSj+vCHP6yXvOQliqJI\nko6V9Mi4xxGSAgBmYrhi1FpLMAoANRX85CcK/+3f1Or3tfLiFxd9OEDlufDUDYhaWlqStLbyNI7j\nfKeH7/sKgoBhUWiUaXY7pmnKDrYG8n1f1lpdffXVOu+887R//3499alPdUU8n5C068i3dj3PO2St\nzSRCUlQE27+BchoORo0xiqJI3W5XrVaLhToA1FR2wglKzzpL2fHHF30oQK2Nqzx1QaoLTocrT90W\n/3GVp9g6BmmV01ZfkyRJCEkbyuVIZ599dv61Ix9IfWOoF+kbJX1Q0r9KhKQAxiCUni/3xl7VhVdZ\ng9Emnrd3eXfpm9439V/Mf9FJOqnowwHQFK2W4mc8o+ijABppo36nhKfAWmmaui3WaKAJrnOhpNT9\nCyEpAGBTbotXHMfKsqw0wWjT3ePdowe9B3Wfd59OsoSkAABU2XY+7CU8BcajJyk2QUiK6mlihRhQ\ntNFgNAxDdTodhWHI4rkkLjOX6XTvdD3FPqXoQwEAADMw6zXWRuHpcL/TNE0ZFoVaYrs9NkFIinIh\nAC0nXpNmIhitliUt6Rx7TtGHAQCouKq2AML0xvU7ldaGp67qlPAUZTDNtYpKUmyiJSkb/hcAWIXg\nejHKckPiFsBxHCtNU4JRYAa4hgJbY2S019urnnpFHwrQaISnjynLWh3bQ0/SZsuyTD/96U/10EMP\n5YH5BRdccIGkH0g6IOk1R/4piZAUFUFoh7opesFlrc0rRtM0VavVUhRF6vf7hR8bisc1d3v4HQK2\n7iOtj+ifd/yzXmFfofPt+UUfDoARk4anbrCnJPm+ryAI6HeKQlFJ2kxZlikIAt10001605vepJWV\nFR199NHurz8n6b9J+oqkA9Za4/6CkBQAGqLuwSjBHgBUV1tt+dZXJKp9gCoZF54yLAplQkjaTK4P\n87vf/W5df/31etGLXjT81ye7/zEckEqEpKgYtjwshud5+SfAqDZrbb6V3jUtj6JIvV5vTQN/AACK\nclV6lZ5z4Dk6une0xFIPqLSNhkURnmI7pimIICRtpn379mnnzp069dRTlSSJsizTYDBQq9VSu90O\nrbXJuMcRkqJwk1R/8eYITG40GA2CQFEUqdvtEowCAErJWqtIEWs+oMYITzELW33t3cwFNMuHPvQh\n3X333dq5c6euv/56ffazn9WTnvQkd/78rud5f2mt/fHo4whJAaAAs94aTjAKAABQbU3dNbdReDrc\n7zRN09oPi8LsUUnaTMccc4z2798vY4yuueYapWmqNE3dXweSxt6ME5KiFJq6ICgrejtWg7VWaZrm\nfUZ931e73SYYBQAAQOVNOizKVZ3OOjzlHrUe3CwGNMvVV18tSfrwhz+syy+/XMvLy/nfvf71r/9n\nSWy3RzlN+sbjgjveqNBk44LRKIq0vLy8ZgHZRIT7AAAA9VZ0eIpqoZK0mfbv368dO3bohhtu0Ikn\nnqhnP/vZ2r9/v4466ihJep2k35D0U8/zPDt0E0lICgAlZ63NG00TjK6PRS4AAEBzTRqexnGcD6n1\nfV9BENDvtCKmKZpK01S9Xm9OR4Syuu2223TzzTfr7rvv1jvf+U7deOONeb9jST1J+8Y9jpAUlUKV\nGOpis5YGLhh1FaOS1G63CUaxELTcmD9uwAAAWIxx4ekkw6LcDi4XovLeXU1UkjbTqaeeqiuuuELf\n/OY39aIXvUjHHnusDh06pKWlJb33ve99gbX2YUmyIzc9hKSoDN6UFoeApBjjgtEoitTv9xUEAb8D\nAIBC+A89pNY99yi+4AJpaanow8Ec0NIKTbPRsCgXnmZZpizL8oFR7vvHbdtHeTHdvplOPfVUnXrq\nqfrSl76kXbt26e6779ZRRx2lM888U5J2r/c4QlIAKNjwVnqJYBQAUC7hv/2bgh/9SKbbVXr++UUf\nDgDMzWh42ul08gKSzSpPCU/LiUrSZnIf/n3iE5/Q61//ep1wwgnq9/u69dZbJelVnuf9v9babPRx\nhKSoDKobUSfWWg0GAx08eFDGGIJRAEBpJRdcINvvK3vyk4s+FKDWqOgtr40qT4f7nbqqU4ZFzcc0\nvyOEpM3kzpVrr71WN998s8466yxJeWXxayR9TNKu0ccRkgIYi0B69oa30ruFVLfbVavVYrE0I5y3\nADB75vjjFR9/fNGHAQClM+mwKFd1Sni6eGy3byb3+/TEJz5RQRAoTVOlaapOpyNJP5WUjnscISmA\nNXiDnh1jTL6V3lWMdrtdHTp0SJ1OhzfsGeK8BQAAQBkQnpYHlaTN5H5vLrjgAr3sZS/TS17yEu3c\nuVMf+chHJOk/JF3ueZ6R9FFrbR6YEpKicJNe9Nluj6owxuQVo1mWKQzDNRWjLHYAAACAZpk0PHUF\nFpLk+76CIKDf6ZSoJG22KIp06aWX6v7779c999yjpzzlKfr85z+fSnqepLakjw9/PyEpAMzAuGDU\nVYqyiAGahw/1MFfGKLj3XpmTTpJl2jwAVN648JRhUbNBJWmz/dEf/ZEOHTok3/fdVnv92Z/92f9c\n7/v99f4CWBQu5OVD1e5k3Fb6ffv2ae/evXmPk6OOOkr9fl9RFHF+Aw3E7z3mLbz9di3dfLPa//AP\nRR8KANSSuxcq8j3dBaGtVktRFKnT6ajb7arX62lpaSkvxsiyLB8Ie/DgQa2srGgwGChJEmVZVqv7\numkGN6VpqlaL+sCm+upXv6orrrhCp59+urIs0+233y7P8/7Q87yxeShnCiqD4A5l4HoHxXGcv+FO\nUzHK+Ywy4/wEys30elKrJdvtFn0oAIAFc31KfX91xkPl6Xhst2+2V7/61brxxhv1y7/8ywqCQOef\nf74k/V/W2jeM+35CUgDYhLU230rvgtEoitTv9xuxsKgKgj1UzaTVEJ7n5X3JAEny9+2T0lTe/v1F\nHwqAGZqmSg5wNgpPh/udpmnaqGFRbLdvrizL5Pu+zjzzzHwtnSSJJA3WewwhKYA1CJseXUwkSaLB\nYLAqGO31emsWHgAALFJy3nlSlik7/fSiDwXAjNUpnEI5TDosylWd1i08JSRtLmOMzjzzTH3lK1/R\n4cOHtW/fPt14442SdM96jyEkRWUQ3GHeXDAax7GSJFEQBASjAIDyiSIlT3960UeBGqGCEWieKoan\n7hi2gpC0ucIw1Nvf/nb96q/+qvbv368LLrhA5513niS9ar3HEJICaLT1gtFutzvXYJTQHwAAAEDZ\nTBqexnGcb2H2fV9BEJSy3yk9SZtpz549CoJAO3bs0Gc+8xnFcSzP89wskd3rPY6QFEDjWGuVpmne\nZ3RRwSgAAACA8qO6eq1x4WkVhkVRSdo8hw8f1lve8hZ1u10ZY3To0CH1+335vu96kv7fkt4x7rGE\npKgMKu8Wp47P9Wgw6vu+oijS8vLymk9JAQDAYtVt3QEATbDRsKiyhKeEpM10yimnyFqrL37xi9q1\na5euuOIK7d69W5/61Kck6SmS5HmeZ0cWIISkKByf0GFeCEabpY7hPgA0CWtCAKiHMoWnhKTN0+l0\n9Fu/9VvavXu3Pv7xj+vrX/96/nevfe1rdcopp5x95F89SYSkAOrLWqssy/Jg1PM8glFgCgTOAAAA\nmKWNwtPhfqdpmo4dFmWMke/7W2qHQE/S5nHnx759+7R//37t3r1brVZLS0tLuv/++yVpeb3HEpKi\nMqgSW5yqPdejwagkRVGkfr+vVqucl7mqPcdoFqq5AABYPPpgoqkmHRblBka5XYKjfyStCWDTNK11\nscx9992nl7/85dq1a5c8z9OrXvUqvfrVry76sArlrqMnnHCCXvziF+t5z3uerrrqKj344IOuqvTt\nR751zQ15OdMDAJjA8FZ66bFgNAgCFpgAgNLyH35Ytt2W7feLPhQAwBgE1uUwGp4aYxSGoYIgWBWc\nJkmigwcP6qKLLtIZZ5yhc845R+ecc47OPfdcRVFU8E8xX2EY6u1vf7t+9md/VgcOHNDTnvY0veAF\nL9A555xT9KEVrtPp6E1vepN+8Rd/Ubfccoue/OQn67rrrtPJJ5/8wSPf4nue17XW7nePISRFpVB5\nh+GKUWstwSgAoFK83bvV/eAHZbtdHXzFK4o+HAAAKmdc5enS0pL+9V//VXfeeafuvPNO3XXXXfrU\npz6l2267Tccff7zOP/98nX/++TrvvPPyfx5zzDEF/hSzceKJJ+rEE0+UJPX7fZ1zzjm6//77CUmP\nsNbqggsu0AUXXJB/zfM831prJJ0j6TeO/JFESIoKYXvy4pXlE9ThYNQYoyiK1O121Wq1SnF8AABM\nynY6MkcdJXPUUUUfCgAAlbLZ/emxxx6r5zznOXrOc56Tf+2FL3yhPvzhD+uOO+7Q7bffrltvvVXv\nf//7dccdd2jHjh15aHr++efr8ssv1ymnnLKIH2Uu7r33Xn3nO9/RM5/5zKIPpTTWOV9csBRKSob/\ngpAUwBplCB7rHowS+s+eOy/KEu4DG+EcbbClJR367/+96KMAAKARPM/Lqy2f97zn5V+31uq+++7T\n7bffrttvv13/+I//qLPPPruyIemBAwf0kpe8RO94xzvUp53PpEJJ8fAXCElRKYRK9TbciDvLstoF\nowCahcAeQFVwvQLQNJ7n6dRTT9Wpp56qF77whUUfzrYkSaKrr75a11xzjV784hcXfTilZx8LlkJJ\ng+G/IyRF4SZdkLFwq6fRYDQMQ3U6HYVhyGsOoJK4dgEAAGARrLV6xSteoXPPPVe//du/XfThlMpg\nMNBgMNDy8nL+NWOMgiAIrbWJxmy39xd8jAAqYp7bwY0xOnz4sPbt26e9e/cqTVN1Oh0dddRR6vf7\niqKIkAFAbVlrlaapsiyTMYZdEgAASeyaKxOqq1EVX/3qV/WBD3xAX/rSl3TRRRfpoosu0mc/+9mi\nD6sUbrvtNl133XWrvvbNb35Tkv7oyL9+XdINw39PJSkqgx6O1WaMUZIkiuNYaZpSMSoWwigvrrez\nZ63Nr4FJkuTXvTiOZa2V7/sKgkC+7+d/mnptBIAm49oPrG+a8Lruv1M///M/L2NM0YdRKoPBQIcO\nHdK3vvUt3XPPPUqSRD/5yU900kkn6e6775akJxz51tRae3j4sYSkAObGWptvpU/TVK1WS1EUqd/v\n1/7NajOEUED9WWuVZZkGg4HiOFYQBHmv5Th+tEe87/syxuR/sixTkiQyxsjzPAVBIGutrLX515p+\n/QQAAADW89BDD+m6667Thz70IUVRpMc//vH5YOjTTz9dkv6/I9+6Jl0mJAUwUwSjKJILnznXUKQs\nyyRJ+/btkyS1220tLy8rCIKx3+8qR4e5UNQYozRNZa3VysoKVacAAADABk455RT9zd/8jX73d39X\n3/72t3X11VePfsvNkmStJSRFdVF5t1hbeb5Ht5EGQaB2u61er7fmxh8A6sgNoRsMBvmWp16vp1ar\nNVWA6apIXbCaZZk6nU5enTqu6nQ0PKXqFAAAAE3jimaMMTruuOMkSd/73vf0l3/5lzr55JN17bXX\n9q21B8Y9lpAUwFTGBaNuGynBKIAmGK2cD8NQS0tLCsNQu3fvnjog3YjneWq1Vi/f3HZ8F5664NRV\nnY4LTwEAwPrYmVROvC6YxJEJ9vrc5z6nb3/727rkkkv0vve9Tz/5yU9cVvE7kn7H87zAWpsNP5aQ\nFKXBBa/8CEZnx32yBaBa3GT6wWCwqnK+yJYirmJ03Jb9japOh8NTqk4BbJe3d6/8hx9W9qQnSawL\nAZQAO1GbzfM8HXvssbrjjju0e/duvfOd79TnP/95Seqv9xhCUhRu0psyttsvlnu+XSDgqqV831e7\n3SYYBdAow9dBz/Mq8QERVacAFin69rflP/KI4lZL2amnFn04AKAkSRSGYdGHgQVz69eTTz5Zt9xy\ni974xjfqiU98oo4//ng9+OCDkhSv91hCUgBruJvolZUVpWkq3/cVRdGGg0cAoG6MMflkemttPoRu\nNHisko2qTl3FaZmrTr39+9X5zGeUnXKK4osvLuQYgDqaxY6u9LTTFLTbMscfP6Ojah521gGzRUja\nTG6de+WVV+qkk07S97//ff3CL/yCjDH6mZ/5GUm68ci3MrgJ5cRioHiusmg4EAjDkGAUlULFObbL\n9RkdDAbKskxhGKrb7c6lv2iZjA6Kkh77wGx0u/5w1eloeDr34zx0SP7+/bIPPTT3/xaArclOO03Z\naacVfRgAamqaNX6SJJX+cBvb94QnPEH333+/7rvvPh199NG68MILJelOSbJjTirOFlQG4cfsuWDU\nbSGVlFeMHjhwQO12m4B0TjifUWZNOz9H+y23Wi11Oh2FYVjrYHQzw1WnwzcYLjh14WmapmuqTl14\nOuuqU3PCCVq56iqZXm9m/58oByroAACT2Mp7RZqmiqJojkeDMjLGyPd9feMb39Cf//mf6xOf+ITe\n9KY36cILL9Sb3/xmSfqfkt7O4CYA6waj/X4/v6GVmheSAGiW0ep5BtFNbrjq1G1hG606dT1cR6tO\nh8PTaZnjjpvVjwIAwFh8cFMPbLdvJpdjfOQjH9Hll1+u5z//+frBD34gSer3+5K0tN5jCUmBhhgO\nA6TxwSgA1J37kGgwGEiS2u02bUVmoIxVpwAAoNnYbt9svV5Pxhg98MADeUXx/v37Jenweo/hbEFl\nUNm4dcMVo8YYglEAjWSMya+FWZZxLVygzapOjTFzrToFAADNRSVpM7ldYc997nN1yy236Atf+IJ+\n7ud+Tr/3e7+nH/3oR5L0xSPfyuAmoO7GBaPTDB0hlJ4/nt/54HmF9Fif0cFgoDRNFYbhwvuMznKr\nXp3O6+Gq02HDwakLtsdVnbo/hKcAADTHNOsqepI2k+d5yrJMl112mU477TT5vq//+I//0M6dO/Wu\nd71LH/3oR//V8zyPwU1ATbmbycFgsK1gFIvD6zIfPK/NZq3NqxJdn9F2u61+v7/wc2OW/72mnNfD\nVafOaNWp+yBwXNWp+wMAVUUfTGC2qCRtriAI9OCDDyoIAv3mb/6moiiS7/tK01TjBjY5hKQohUmq\nFqlsXG10+2gYhlpaWmr8NGYAzTMcjHqepyiKtHPnTgKzGqDqFABQBALreqAnaTNlWaYgCPSnf/qn\n+qu/+isdc8wxeV/8I9vtr5L0MabbAxU3Lhhd9PZRACgDY0w+jM4Yk1eMshBuhllUnVZuUJS1Cr/z\nHdl+X+lTnlL00QAAUHppmrI2bCC3Prz++ut1/fXX5x+k33LLLbr55pt1ww03fP/It9KTFNXWxEpS\nY0zeV2+RwSiVu0BzlfX331qbtxZx10Nai8CZtOo0SRJlWbZu1WlZ+Q8/rPYtt0i+rwNnnilxzgMA\nGoSepNgqdz/jeZ7SNNVzn/tcvfvd75akMyX9uyRP0qqbHkJSVEaTboBdEBDHcf7pV7vdVhRFjXoe\n6qysIRRQNm4AUxzH+ZYprofYikmrTpMkySsN3PtwmapOzTHHKH7602X7/bkFpN6hQ2p//vMyxx2n\n+OKL5/LfQDmxJgFQR/QkbSYXqH/jG9/QAw88oKWlJUVRpF27dunuu++WpL3rPZaQFCiJccFoFEWF\nDBwBqowbveqz1irLsnw7ve/7arfb6na7pa70Q3VsVHWaZZkOHz6cB/TGGFlrFQRBsb1OfX/+weXh\nw/IPHKBKtaFYbwKoG0LSZnIh6Re+8AV9+ctfVr/fV5Zl6vf7uv7663XZZZd98cj3sd0e5bSVqro6\nNdEeVyEVRZF6vV7hQQCVjqiiulwbmsr1kBwMBpKkKIq0vLy8qgIQmCcXnHqep3a7LWnzqtPR8LQM\nVafTsscco5UXvlDqdIo+FAAAto2QtJlclnLdddfpuuuuW/V3xhhJ8o7kHWsCD0JSVEZVbzhGjQaj\nQRAoiiIqpAA00uhAOvdBEX1GURZb6XXqqk593x8bnlaBPfroog8BaCSKE8rFXctRbWmaEpI2kDFG\nvu/rve99r2699VYdffTRCsNQaZq6D8H/H0l9z/PeY6398fBjCUlRGnWqEB1FMIpxWAyjqdw1cTAY\n5IvXRQykA2ZpXK9TSauC09Gq09HwtMpVpwDmg2sCMN40eQGVpM32wx/+UF/+8pd16aWX6glPeII+\n+clPqt/vS1JX0tiJXoSkKIVJL3ZuC3gVFg/WWqVpmldIEYxiWBXOYWCWxl0T2+12KdqLALPkAtBh\nda06BQCgzAhJm8kVI/3Lv/yL/u7v/k7nnXeeJOnaa6/VVVddJUkfs9b+uzdmwUVICszQaAjg+35l\ne+rRkxTALAwPYPI8r7LXRGA71qs6dYOiqDoFAGD2CEmbLY5jfe9739MZZ5yhOI7V7/e1a9cuSVq3\nQoOQFNimOgWjQNUR7peD6zM6GAxkjFG73Va/31cQBIQ8R3CuQnr0PGi1Vi/H3aAoF56OVp2OC08B\nAMBaaZqq1+sVfRhYMLej5zWveY3+4A/+QJ/73Od0yimn6JOf/KQuueQSff3rX79HEoObUH1lual0\nNy8uGKU6CkCduNBlK+1NrLX5NdH1Ge12uwxgArZos0FRWZaNrTodDk+pOgWA7eM6Wi70JMWkXG70\nwhe+UM94xjP093//9zp48KDe85736KlPfare9ra37V/vsYSkwIRGg1FJiqJI/X5/TRVIHZQlkK4r\nnl/UwehQularlV8XubEAZmvcln1XdTq6XX+46nQ0PAUAbI51ej1kWVbLe3VszvM8HT58WN/5znf0\n0EMP6dWvfrXiONa///u/68ILLwyttcm4x3G2AJsY3kovPRaMsm0UQBO5D4xcn1Hf99VutxlKBxRg\nuOp0+CZwODg1xihNU6pOAQCNQyVpM7mq4z/8wz/Uvffeq89+9rP6lV/5FZ144ol65StfKUnHSXpg\n3GMJSVEpi6q+G64YtdYSjAJoPHddHAwGkkSLkQlQhYKiVLHqlN+XYrnzAMWZZisxgI0RkjaTu55+\n7GMf0x133KFLL700X+ckSSJJZr3HEpICRwwHo8YYRVHU+H563LAAzeaGxsRxrCzLFEWRer1eo6+L\nk+L5QdlsVnXqwtNxVacuPJ131Sm/NwCAWXJ98tEsbj3xhCc8Qffff78OHjwoY0xe7CFp7FZ7iZAU\nJVHUophgdH1N//nnjZ6k88Hzun2uz6gk7d27V2EYqtPpKAxDrgtADQ1XnbobyeGqU7dd3+2uGQ5O\nh8NTAADmicFNmJQ7Ty6++GL9/u//vh566CF98IMf1Ec/+lG97GUv06233rp3vccSkqJSZhGAGGPy\nYNRVRhGMAmgya+2q/stui+7OnTvZTg800HDV6bDh4NStp8ZVnbo/rKsAVBXtD+qBStJm+9jHPqZ3\nvetdOv/88/Xwww/rhhtu0MUXX6zXvva12XqPISRFKcz7DWg0GKUyCgC0agCTJLXb7bzP6COPPEJ/\nOgCrbNbrdHhIFFWnAICiUUnabOeee65+9KMf6ZprrlG73ZYxRgcPHlSv11v3MYSkqC2C0e1h2zJQ\nT+7aOBgMZIxRu91mMB1QId6ePVr61KeUnnGG4mc9q+jDmVnVKQAAs0ZI2mw//OEP9Wu/9ms64YQT\n1O125Xme0jTVXXfd5Vtrxw5vIiRFpWwW3A0PGUnTVK1Wi2AUpUQIjUWy1uYfGrltR5u1GXHnKNfO\n+eEagGn4jzwi/5FHFNx3n1SCkHQ9k1Sdut7ww9eaOI4JTwEAa0yzLmW7fbN97nOfk+/7StNUWZbl\na4/jjjuO6faor9Gb/1arpSiK1O/3ubkH0Fiuz+hgMFCSJFwbgZrITj9dKy9+scyxxxZ9KFu2UdVp\nkiRKkiT/31mW0esUjcIHk8DsUUnabN1ud8uPISRFJbkF9GAwWBWM9no9qg6ABmt6ha61Nq/MGgwG\n8n1f7XZb3W6XayNQI9mppxZ9CDM1HIa2221J46tOkySRMWbd4JSACQAwjJAUW0VIispwi+WVlRUd\nPHhQQRCo3W4TjM5J08MmoEpcMOq2rUZRlA9gAoAqmrTXqas6laQgCKg6BTATVPbWA9vtsVWEpCg1\nVzEax7GSJJEkhWGoHTt2EIwCaDQXDgwGA2VZpiiKNu0zCgCVZIzaX/iCZK0GL3jBRL1OqToFALhd\np8CkOFtQOqPBaBAE+c3/oUOH1Gq1CEhRee7mjE+pm+FhPay7vbv1DPsMeZr+9R7XaoThdABqL03V\n+vGPHw1J41jqdFb99VaqTo0xstZSdTqC9QiAsrPWbjkHYLs9toqQFKXgeZ7SNM3DUd/3FUWRlpaW\nVlUKsHhbHLbbA7Pz5tab9R3vO/q99Pf0n+1/3tJj3QAmt53efXBEqxEAjRFFWrniCsnaNQHpRjzP\nW1N1KmlVcDpcdeq+n6pTAKgHQlJsFSEpSsPd/NNHD8B2lDHcf5p5mnb7u3WaPW3ix2RZpsFgoDiO\nJUntdpvrI4DGMscdN7P/LxeADtuo6tT3/bHhKQCg3AhJsVWEpCiNSacvlzEAAVAOZb1pvcZco2vM\nNZt+nzEmn0xvjFEURer3+wqCYOE/G9Xkj/qa9zX92Puxfsn8UqHHwWsBzNd6VafWWmXPvTeTAAAg\nAElEQVRZNrbqdDQ8peoU28F1vlxoQVEPDG7CVhGSolJ4o1osFmvz5UIozutms9bmW+ndQm5paYk+\noyVxXes6HdRBnWfP07n23C09lmsoUH2e560Z+rFZ1em48BSYBOcKsL5p7psY3ISt4mwBMBaLNGB+\nXJ/RwWCQD6hrt9vq9/v87pXMK7NX6ofeD3WGPaOwY+CcAMpl2qrT4fCUqlMAWAyutdgKQlJUDpU5\nAKrKDWAaDAbyfV/tdnviViMoxi+bX57qcSzIgeZZr+p0ODyl6hQAgPIiJEWl0CMPQNUYY/IBTNZa\nRVHEACYAaAhXMbreoKgsy6g6BQCgJAhJAYxFII2qKsN566qFBoOBsixTFEXqdrtqtVrc6AIAxm7Z\nd1Wno9v1h6tOR8NTALNXhrUk1uJ1wSIQkqIUJl3keZ4nY8ycjwZYDILo2SvyObXWKkkSxXGsJEnU\narXU6XQYwAQAmMhw1enwtv3hQVFZlilN0zVVpy48peoUmB1+l8pnq68J91rYKkJSAACm5PrMue30\nQRDkVaP0GQWKkSnTX4R/obbaelXyqqIPBxOaZmpxUwxXnYZhKGlt1anreT1adTocngIAgI0RkgIY\ni8U0sL7hYFSS2u02fUaBktijPfpK6yvy5et/JP9DbbWLPiRg5mZddUpIXTxeA2D2+J3CVhGSolLY\nnrxYPNfAY4wx+WR6Y4yiKFK/369thQ7XW1TVsTpW/2vwvxQpIiBF42xWdWqMGVt16nZG0OsUQJ1w\nPcNWEZICQEEIocrPWqs4jhXHsdI0VRiGWlpaos8oUHJPM08r+hCA0hiuOh02Gpy68HS06tT94X0P\nQJGotsYiEJICAGplu8GztVZpmmowGChJEgVBoHa7rX6/z8IMAFAbw1WnSZKo3W7nVaXDW/bX63Xq\n/gB1QxgHNBchKSqFyrvF4blGFW1nQesqaFwVDQOYAABNM0nVqWs/M67XKVWnAIAqIyRFKdA0HkAR\njDH5ACZrbd5ndHgIBgAATTdcdeqM9jrdrOp0eFAUAABlxF0gABSIat3Fc31GB4OBsizLK0ZbrRY3\nb1gYzjUAVTdp1WmSJMqyjKpTANuy1YIq7rMwDUJSlMYkFzy2gC8e1b3zw/O6ONZaJUmiOI6VJIla\nrZY6nQ4DmAAAmLFJq06TJJExhqrTI7jHAWYrSRKFYVj0YaBiCEkBjNW0hSnqx1qrLMvy7fRBENBn\nFACAAmyl6tQYI2utgiBoXNVp3X8+YJEISTENQlJUDp+yAliP53kyxmhlZUWDwUCS1G63tby8vKqi\nBZPhers9PH8AsLGtVp2672961Snmi5109eB2jwFbwRmDSuHNCsA4btLu4cOH8617/X5fQRBw3ZgS\nzxsAoAjTVJ36vj82PAXQXFmWUUmKLSMkBbAu1wOWReZ80GN3e1yf0cFgoDRNFYahwjCUMUa9Xq/o\nw0PDcd1sAGulOJba7aKPBNi2Kqz3xlWdSloVnFJ1CtSTu2fayu8v2+0xDUJSVA6hEtBc1lqlaao4\njvM+o+12W/1+X57naTAYKEmSog8TQAO0v/hFte6+WytXXCFz0klFHw7QWC4AHUbVKQC222ManDGo\nFBYwQDMNB6Oe5ymKIu3cuZMBTACK4z605cNboHTWqzp1Qx3HVZ2OhqdUnQLVRiUppkFICmBdbAdH\nkYwx+WR6Y0xeMconwgDKYHDZZRpcfLG0tFT0oQCYkOd5a9YRblCUC09Hq07HhafzwJq7PHgt6iFN\nU0VRVPRhoGK400RpTBrI8aaFuiCEXstaqziONRgM8mbr3W5XrVZropsSnlMAC+P7BKRADWw0KGqj\nqtPh8HRWVadUrpYHr0W5TNM3mUpSTIOQFJXCmxVQP24AUxzHee+gdrutKIr4nQcAAIWYtup0NDwF\nUAx6kmIanDEAgIVzNxhuO73v+2q32+p2u/QZBQAApbRR1amrODXGKE3TuVedAtgYlaSYBiEpKoWt\ntIvF841Zy7Is304vSVEUaXl5ec1gBRSP33+gvIJ771X0rW9pcPHFMiedVPThAI03blCUqzod3a6/\nXtUpgNmiJymmQUiK0uCGHE3UhHPeGJNPps+yTFEUqd/vKwgCKikAYAqtu+9W8MADav3wh4prEpJO\n028OKLPhqtPhLb8uOHXhqas6dY9xIapbJ/F7AUyHSlJMg5AUAApS50Wv6zM6GAyUpqnCMFSn01EY\nhrX+uQFgEeJnP1vZiScqPfPMog8FwBYNV526AMdam++y8TxPaZoqjuM1VafD4Snmhw9tyofBTVgU\nQlJUEm9ci9OESkfMhrU2X9THcawgCNRut9Xr9Ra2jYyKdABNYJeWlJ53XtGHAWBGXMWo53mrtgcP\nV526nTmjvU6H/3B/BDwmTVMGN2HLOGNQKpuFn7zxLxbPNyYxPIDJLe7pMwoAQHVQgFA8VzU6bLNe\np8NDoqg6BVZzu9mArSAkRWnwBg5Uh6tmGAwGMsao3W7TZxSYIyqkAQDS6l6nw6g6BVZjuz2mQUiK\nynHbaXljR9VVbWu4tTYPRrMsUxiG6na7arVa/D4Cc8Tv12JV6boMAM4kVadZlq3b69T9AcqInqRY\nFEJSAOuqWoiH2XMDmOI4VpIkarVaarfbiqKI4AbYBNfP6uL6BqAOJq06TZJEWZZRdYpaISTFNAhJ\nAQCrWGtX9Rn1fV/tdlvdbrcSFQYEUwAAAOubtOo0SRIZY9YNTusanrJrsR7SNNXS0lLRh4GKISRF\n5VDdCMyH24I1GAwkqZIDmFjQzg7X2u3hXAQAVMlWq04lKQgCqk5RWlSSYhqEpADWRUgyX2V4fl1j\n/ziOlWWZoihSr9ejzygAAACoOkVlMd0e0yAkBYCGcX1GB4OB0jRVq9VSp9NRGIYsYAEAAApQ9Afn\nW7GVqlNjjKy1VJ1iWxjchEUhJEXllKH6Dqgaa63SNM2rRoMgyKtGq9BnFAAAoO6qHhqOqzqVtCo4\nHa46dd9P1SnmgZAU0yAkRWnwZgjM3vAAJs/zKtlnFAAAANXlAtBhG1Wd+r4/NjxdFAY31QPb7fH/\ns3fncZJV9dnAn3PX6urq7hlG1gEEhkGHZUYImyCLKCgguCARxCQYt4SooEjUiPiCK2o0Amp8BTXm\nTVARE2UNIjECChhAZhSFAUSRHYbZuqvucs55/+g5l9vV1Vttd6nn62c+MtPV1aeqbt/lub/zO+1g\nSEqFxErS/mDVbu/14v01fUaDIIBSCr7vo1arwbZtnvARERHRFDzXoyy0U3XaHJ6y6pRmw5CU2sGQ\nlHJjvgc4HgipLLq5LWutk6n05oSgWq0O3AJMDPaJiIjaM0jnC5RfRas6pf5otyep4zDyooXhFkNE\nVFCmz2gQBMlJgOd5qNVqPDkkIiIiolKYqepUaw0pJatOqSVWklI7GJJSIbFSrH/4XueLORk00+kt\ny4Lv+6hWq1yAibqKVblERESUZ0KIaZWCWusp4Wlz1Wmr8JTKiQs3UTsYklLh8EDWP3yv88MEo2EY\nQmvNBZiISoAhNBERUXeZitGZpuxLKVtWnabDUy7cVA4MSakdDEmJiDIyV6WeWYApDENIKeF53kD2\nGSUiIiIqOwZzvdVqyr6pOm2erm8+C6XUlPCUn0922rmxzOn21A6GpFRIrL6hstJaI4oiBEGAOI7h\nOA4qlQpc1+WJ2TxwijgVBX+fiYiIspWuOk1P26/X60koqpRCHMfTqk5NeMpep/3TzsJNDElpoRiS\nUuHwINQ/DJz6wyzAZKpGbduG53kYHh5mn1EiIhoIPN8gorwwYWg6YGuuOjXn7ulep83hKWWLISm1\ngyEp5QYPJDRozJ3pDRs2AAB832efUSIiGlg8FySivJqp6tQEp+nwlFWn+cDp9tQOhqRUOKxupCIz\nfUaDIEhOoGq1Gu84E5UQj1VERETllu51agK5dNWpKYpg1Wn/sZKU2sGQlHKFB4h8MX14qDNa62Qq\nvbmjOTQ0lPx7+m40ERERERFlp9NFtNJVp83Pa4JTUzjRqurU/OG18fNMwLwQDEmpHbwyp1zhqo5U\nFqbPaBAEiKIIjuPA8zzUarVkGw/DMONRElGv8FhGREREaemqU6O56lRKOWPVqflD88OQlNrBkJQK\nh9PtKa+01smJTRAEsCwLvu+jWq3yhKZPuH/oHr6XRESDgUUK+cBj7mBi1WnvSCk5Y48WjFsMEVGH\nTDBq7vp6nscFmIiIiIhoQRh0kdGNqtNBXyiKlaTUDoakRDQjVpLNTCmFKIoQBAGklPA8D9VqFY7j\nzPtkhO8vERERERHNx3yrTqMogpSyVFWn7V4zFfG1UrYYklLhMFiirGitEUURwjBM+oxWKhW4rssD\nMBERERER9d18q06jKIJSqrBVp3kfH5UDQ1LKDe70KI/MAkxmOr1t20nVKPuMEhERERGVSxn69C60\n6hQAbNsuRdUpUScYkhLRjAa5aldKiSAIkhXofd9nn1EiIiIiIiqshVadmscXreqUqF0MSalwhBBQ\nSmU9DCohs3JkEARQSsHzPNRqNdi23ZMTgUEOoXvFfE5lqAAgIiIiIuq1hVSdKqWShaJahadERceQ\nlIgGmtY6mUofxzFc18XQ0BD7jBIRUabshx+GWrQIetGirIdCREQDqFXVKYApwWm/qk5ZAEH9wpCU\niAaO6TMaBAGiKIJt2/B9H7VajQdfohRWOhNlw370UQxdcw3U2Bgm3vKWrIdDRH3AEIiKwgSgaaw6\npbJgSEqFwynK/VO299oswBQEASzL4gJMRLMo2+9/kfGzGDxq8WLI7baD3GGHrIdCREQ0p5mqTrXW\nkFK2rDptDk+73euUQSy1gyEpEZWaUipZgElrDc/zMDIyAsfh7o+IiPJJV6uon3RS1sOgAcEKRqKp\n+DvRPUKIadddZqEoE542V522Ck/bwRvM1A6mBJQ7PChRp0yf0SAIIKVMKkYdx8nVtsXqMCIiIiIi\nGiSzLRQ1U9Wp1hpRFCVBarerTokMzjGl3JjvTo7BUv8U6b02wejmzZuxfv16hGGISqWCRYsWYXh4\nmAsxDZAibbc0uEzPLm6rRERERM9XnXqeh0qlgmq1iuHhYQwNDSWPiaII9Xod4+PjmJiYQKPRwLp1\n63DLLbdg/fr1056vzK6//nq8+MUvxvLly3HhhRdmPZzSYCUpERWWudtoptPbts0+o0SUG80BaHOV\nOwCEYdiyLxf3YdnQ0PiN9RssFotRRTXr4RAR0RZBAPh+1qOgfjMVo0IIeJ6XnB+ZhaKklHj00Udx\n7rnn4ne/+x222mor7LXXXthrr72glML999+PZcuWTeuVWnRSSrz73e/GjTfeiKVLl+KAAw7AiSee\niBUrVmQ9tMJjSEq5Mt+7Pay8GWxSyiRoAADf9zE6Olq6gx8RFZc5nmmtEccxgiBAFEVwHAeVSgVC\nCERRBNu2p/XlklImwWk6MGU7mt5ba63FNdY1WIIleCfemfVwiIgIwHXXWbjmGhcPP6xwyy0ejjkm\nxPe+F2U9LMpQeqGoffbZBz/96U8RxzF+//vfY82aNVizZg3++Mc/4tWvfjWefPJJ7LXXXli1ahVW\nrlyZ/Fm8eHHWL6Ntd9xxB3bffXfssssuAIBTTjkFP/zhDxmSdgFDUiocXiAOJqUUwjBEGIZJn9Fa\nrQbbtgu7TXBaOFF5md5ZjUYDwOTNnHSVexzHAFr35TILGpgKCfPY8fHxlhWnRd0H5tH2anvsjJ3x\nwuiFgJf1aAYLbwLQIDPng/wdmE4p4KMfreCppwQ2bdJQCrjpJhdA70JS7o+KyXEcLF++HMuXL8cJ\nJ5yAu+++Gz/5yU+wceNGrFmzBqtXr8bq1atx+eWXY82aNVi8eDFWrlyJVatW4YMf/CBGR0ezfgnz\n9uijj2KnnXZK/r7jjjvi9ttvz3BE5cGQlIhmlHWIZ0KGIAgQxzFc10WlUmF/USLKpfQ+y1SNtnMz\nJx2cOo4DrTXGx8cxPDw8ZUGDMAynrASbDlC5j2zPCEZwSnQKgjhgSJoBbrdE1MyygN13V7BtC2ee\nWceXvlTBuefWsx4W9dlCg+soiuC6LgBgdHQUhx56KA499NDk60opPPzww7jnnntwzz33oFKpdH3M\nvcTjZe8wJKVCYvVdeZmpqaZq1LZt+L6PWq3GgwFRHwkhoJTKehiFYKbTp/dZZvEBx+neqZZ5zjRT\ncZquOjUrwTZXnLbb5/Ru6248K57Fy+XLYYNtTbJjqqbcTEdBRNRv3/lOI/nvs89mQEpzMzerZ2JZ\nFnbbbTfstttueP3rX9/HkXXH0qVL8cgjjyR/f+SRR7DjjjtmOKLyYEhKhcOgrJzSwahpzD02NsbF\nS2jBsq6ApsFgWoAEQQCtNTzPm9Ib2UyR77V0Ty5TMZEOTs04TXDaquJ0ruPqT5yfIECAPdWe2EHv\n0I+XRdM0UK2+HIDGxMR/Axia6xuIiPqi0QDGxwWWLOG5F+VHHMfwvPJOCdl///2xdu1aPPzww9hh\nhx3w3e9+F5dffnnWwyoFhqRENKNeh01KqaT6SimVVIx2s/IqzxjmERVLqxYg1WoVjuPk6gZeOjg1\nmvucRlEEpRS01i0rTtOv54T4BDwnnsP2evssXg4BACSEmACgAcisB0M00BoN4LbbbKxYobDttjyP\n+/d/d/H44wKnnx5h6VK+H5QP6en2ZeQ4Di655BK86lWvgpQSb3vb27hoU5cMRhJBpcJgqdi01kn1\nlZQytyEDEZEhpUQQBAiCAJZlwfd9DA8Pd1zp3s99XnOfUyNdcdqqz6lt29jd2p19TjM3jPHxn235\n71qmIyEadPfcY+GWW2w8/rjAqaf2Z9ZAni1ZorFhg8DQUDmuz3idmT/tfCZzTbcvg2OPPRbHHnts\n1sMonXJvNUSUC6b6KgzD5IDl+z48z+NFNxHlUvMNHd/3MTIyUroT7la9StMVp+mq0+Y+pwtdkIo6\nNZb1AKikuJL3wqxYofDUUwp7782qbgB47WvLGRTzdyJ/2l24iWghynWmT4XHKtHy0Fon1VdhGCbV\nV9VqlX1GiSiXzMJx6dXpK5UKXNcdqIulmabrz9bnNB2ezqfPKRFRUY2OAiec0N1gkNc/RN1lZiwS\nLRRDUiocBqn90857baZrBkEAAPB9f8piJjQdKzi6j/sIWoj0fsssHMcbOlPN1udUSgml1Ix9Tk3F\nKfdzREQz4z6SqHtYSUrtYkhKRB0zVUVhGEJKCc/zUKvVOBVzDnxveoPvK81H83R67rcWLt3n1Egv\nEKWUQhzHLfuctlogioiIiKgbGJJSuxiSElFbWq3yPIjTUomoOJrbgNi2zf7IXdYqOAUwpeI03efU\nhKXp8JSfBRERERntzLobhIWbqDe41VCuzGd6N6fb9585MJl+faZq1AQM3VjlmYjypUz7WlPtHgQB\ntNZsA5IBIcS0i5V0xamUEnEcz9jnlMcYIiLqB7bBKoc4juF5XtbDoAJiSEpEMzInCKZfXxiGSb8+\nBgxElGetqt2r1Socx+HFT06k+5yaKXGt+pxKKZPglH1OiYiIaC6cbk/tYkhKuTPfu3e8y9dbpvIK\nADZt2gTf91Gr1ThtoctMtR63ZaLuMNPpgyCAZVmsdi+YdvqcNleccn9KREQ02BiSUruYdlDh8OKn\nd5oXMjEHlrGxMQYMVChlmSZO86O1TvqMSilzM51+ru2Q2+n8zLfPafMCUexzSkREVHzt9iRlSErt\nYEhKucKLmP4zU1LDMEwaXKcXMnnuueeyHiLRgnA/MhhMj+QgCJJ9FxePGywL7XPaXHHKm39ElBec\nVUTUXabVEtFCMSQlGkDNKzybKanVapUXjUSUa6ZiMAgCCCFyu+/ixW42ZupzaoJT00omvUAUK06J\niIjKhZWk1C6GpFRI7OPYnnS4AIALMOUEp9wSza65FYjneajVasniPUSzSQenRrrPqZQSURRBKZVM\n1zeLRrHPKQ0CnlMTPY+/D+XAkJTaxZCUqORM1Yzp1ed5HoaHh+e9wrMJpKk3eBJG1Fpzxbtt21Na\ngRB1It3nND1l3ywMFUVRyz6n6Sn73A6JiIjyiSEptYshKVEJmT6jQRAgjmP26iOiBcvqBolSKglG\ntda5WYSJBoMJQuM4RqVSAYApFafpqtPmPqesbCYiIuq+dqp7zUKeRAvFkJQKidWN05lFTEzVqKm6\nGh4ezl2vPqJe4v6heJpv7Liui2q1Ou+Kd+quJ8WTAIBt9bYZjyQfZpquP1uf0+aKU27Hc+N+m/JG\na4C/ukTFFEURPM/LehhUQAxJiQouPR1VCME+o0RUGGb/FQRBcmOnVqsxUMpQAw1c7F0MAPjb4G/x\nef/z2IzNeFP0Juyp98QOeoeMR5gPs/U5lVImPU1Nn9NWFafczqfje0J5ceWVDu65x8K73hVh6VIG\n+ERFw+n21C6GpFRYg1xxYKpWgiCAUioJFnox1Y9Veb3F95cGTav9F2/s5IcLFy9ULwQA/Mn6E35m\n/wybxCY8YD2Al6mX4fzgfFjg7IRW0n1OjfQCUabfKfucEuXfxo0CUSRQr/fn5/FcMD+4cFM5mJlJ\nRAvFkJRyZb4HpEE8cJnVncMw5HRUIioU0w4kCAJEUQTHcTA0NMQ+yTlkw8Y7oncAACQkzgnOwX3W\nfbCFjWVqGQPSBWoVnAIz9zk1YWk6POXvCFH/nXZahE2bBJYs6V94yd91otbaCa5ZSUrtYkhKlGOt\nggXP8zgdlYgKwawOHgQBhBDwfR/VapV9khcoq/29DRunyFMAmcmPL7W5+pxKKRHH8Yx9Tvk7RNRb\nnoe+BqRE1F2sJKV2MSSlXFnIhWBZp6WYfmamz6hlWZkGC5wOTkQLYaregyCAlDK5seM4POXoFKcA\nlls6ODUXdq36nEopk+C0ueKU2wcRERErSal9vGKhQirjRYCpuDK9yrgA02BgCN19fE/7r/nmjuM4\n8H0fnueVcn9N1C/z6XOaXiCqVcUpfweJiGjQMCSldjEkJcqQWcAkDMOk4op9RomoKJRSSTCqtYbv\n+xgbG+NUYKIemq3Pqak4NTde0wtEsc8pUfGsXSuw/fYatVrWIyEqFk63p3YxJKVCKnKlmNYaURQh\nCALEcQzHcVCpVHK9gElR32siat9M+9nmfRgXkSPKByHEtLYWs/U5ba445c2NwcVWHvm0erWFb33L\nxfLlCn/7t1HWwxkY/H3IHy7cRP3EkJSoD8wCTKZq1LZteJ6H4eHh3F+U8CSBiAAk+7AgCGDbNnzf\n5yJyc+ANJsraTH1OTXBqZrSkF4hin1OibEQR8OtfW3jxixVGRoBtt9XYemuNZctU1kMjKhyGpNQu\nhqREPZTu0QcAvu+zzyhNwyCF8kprjUajgSAIoJTiPoyoBNLBqZHucyqlnNLntFXFKYNTou7SWuPW\nWz3ccIOL/feXOO20GNtuq/HhD4dZD42okKSUXDSU2sKthgopz9PtTVWGCRXMys62bfOigqbhNkF5\nYyrf6/V6Mj13aGgo1y1BiKgz6T6n6YvKdMVpqz6n6QCV+weizuy+u8R992nsvTcrR4k6xUpSahdD\nUsqVop5ga62TqfSmR19ZQoU8B9JErXCbbU+68t30NtRao8bVItrS7e0wQgQNDYFiH1OoWFr1Kk1X\nnKarTpv7nPLmMNHC7LSTwllnsXKUqBl7klI/MSQlapOptgqCAFEUwXGcpGqUFwVEVATmBk8QBJBS\nJvswx3EQRRGklFkPsbQWcpx4XDyOz4x+BntZe2GVWoUHrQexQq3AvmrfHo6QqLWZpuvP1ue0ueKU\n50lElGfcRxUfQ1JqF0NSKqSsKsW01sl0syAIYFkWfN9HtVrN/QJMRETA9IXkHMdBpVIpReV7WcWI\noaAQiADfc7+HX9q/xHK5HOdE5+DF6sVZD49o1j6nUkoopWbsc8qKUyLKE85GKgczu5NooRiSEs2D\nCUZNLy7P87h4CXUFp4ZTvyilEAQBgiAAMLmQ3NjYGG/wFMBOeif8w+Z/wJLqEvzK/hWWqCUYwQh2\nUDtkPTSiGaX7nBrpBaKUUskNm/RxMN3zlOEpERG1g5Wk1C6GpEQzMFUP6Wmo1WoVjuMM1Ek7Qzyi\n4tJaJ/uxOI7heR6Gh4fnvR/j735+jOgRuHBxoDoQB6oDsx4OUVtaBafA5L6mXq9DCDGlz6kJS9NT\n9gfpHIyIiNrDkJTaxZCUCqlXwZ0JFMIwTPqMchoqERWN6ZcchiFs24bv+wvul8x9HhH1iwlPHceB\n40xenqQrTqWUiON4xj6nrIinomtnYRqiQWFmGCwEp9tTuxiS0sBr7s9n23ZSNcqTbqLiGdTqZ7NY\nShAEbAtCRIWX7nNqLnRb9TmVUibBaXPFKUMnIqLBxEpSahdDUhpYUsqk0gqY7M/HQGG6QQ2c+oXv\nL3XC3OQJgiA5GRzEtiBENBjm0+c0vUBUq4pT7hunYxUj0fP4+1Ae/BypHQxJKVfmuyNrN1hKV1op\npeB5Hmq1GldWJaJCSd/kEULA931WvxNRobV7w3C2Pqem4tQswJleFIp9TomIyotFKNQuhqRUelrr\nZCq96U0yNDTEPqNEVChmX5ZeTK5WqyX9+4iIiq6b52Wmx2nabH1O0xWnhb15HgRwfvxjyD33hN5t\nt6xHQ0TUFazupX7ilRUV1mx3h5qnoLa7cAlN4p04omw090zmYnJERO2bqc+pCU7NdP1Go1HIPqf2\nnXfCufpqWL/5DcIPfjDr4RARZSbP+2rKN4akVEgz7fRMmBAEASzL4gJMXcCemVRERd9mlVIIggBB\nEACY7Jk8NjbGfRkRUZelg1Mj3edUSjmlz2lzj9M8TdeX++wDceihUKtWZT0UIiKiQmJISoVnwgTT\na8rzPIyMjHAKKhUCQ+juK+p7qrVGFEUIggBxHMPzPAwPD3MRphx5Fs/iTtyJA3AAFmNx1sMhoh5J\n9zlNn0+mK05b9TlNB6iZ7LdHRhD/xV/0/+dSx4p43kJEVEZMkaiQzBTUjRs3Js0f+7sAACAASURB\nVL35uKIzERWRaQ0ShmGuWoMUNWzupbfZb8ON9o3YXm+PtdFarMd63CnuxKH6UFRQmfZ4vn9E5WIC\n0LR0xWm66rS52rSwfU5z5rnnAK2BrbbKeiTdx+0jH8yND8oPnk9RPzEkpcIwVVamN58QAsPDw+zN\n12NCCCilsh4GUakopZLWIKYCfnR0dMp0T8qfXfQusGChiioA4ArrCvzc+jnG1ThOVCdmPDoaJK77\nz3CcG9BoXAytl2Y9nIE203T9dNVpGIbJAlGtKk55Hjs/QQB87GM+tAYuvDBAtZr1iIioXxa6n+R+\nldrFkJRyyaxgp7WGlHJKlZXneXAcJ5mOSkRUBOkbPVEUwXVdVsAXzD+pf8IF4QWooQYAOEgfhPV6\nPVYp9v+j/nKca2Db98Cy1kBKhqR5M1ufUyllskBUqz6npuKUx4XpbBt4wQs0lAK2rLtFRETUVQxJ\nKVfMCaGZrpRetCRdZWV6QBEVHac0l5+50WMWlPN9nwvKFdgoRpP/XqlXYqVc2fJxDDiolxqNi2Hb\nv4GUr8p6KDRP6T6nRnqBKKVUsgBprvqc5ojjAOedF2Y9DCIiKjGGpJQ7QRCg0WjA8zzUajX2cMoY\n33sqoqyDZ611Mp1eSgnf97mgHBF1jda7II53yXoY1KFWwSkwvz6nJjzleRoREVH38GqNcsf3ffi+\nzyqrHMk6cCJaiKwuGM2CckEQIIoiOI6DSqXCvslERLQgc/U5lVIijuMZ+5wu9ByaC9UQPc+0faP8\n4GdC/cSQlHJnPjtATlEmorxQSiXT6YUQ8DyP0+mJiKir0sGpu6UhZ6s+p1LKJDhtrjhlyEBEg4A5\nAXWCISkRUcZ4IC8eM50+DMNkETm2ByEion6aT5/T9AJRrSpOeczKB1bzEnWPlJItrqht3HKIaFas\n2u2t9MXJzeJmXGpfir+Wf40j9BEZjopmYqbTh2EI27bh+z5qtRovMomIKBdm63NqKk6llFMWiDLn\neQxOiagMTNsronZwy6FCYnBHZfSMeAYSEs+IZwBu3rmhlEoWYdJaw/d9jI6OTukVV0bcz+YPe3J1\n5jHxGBpoYDe9W9ZDIeo7IcS00MBUnAZBMOX/zdT+9JR97nuIKCsLPf9hSEqd4JZDRJQTr1Ovw75q\nX7wQL8x6KIXWjXBPa40oihAEAeI4huu6qFarcByHF4qUCW53nVFQON8/HwECfD74PF6gX5D1kIgy\nlw5DTa/T9FR9M12/0WiwzykRFUYURfA8L+thUEExJCWiObGarD8EBHbBLlkPY6BJKZNFmCzLgu/7\nGB4eZp+wHHkcj+NmcTMO04dhe2yf9XCoICxY2Efug/ViPUb0SNbDIcqt9AJRRrrPqZRySp/T5h6n\nnK5PRcdZG8VnChyI2sGQlAqJ00D7hycJvcVtOXtmEaYgCCClHJjp9EV1lnMWbrBuwKgexav1q3FB\nfAG2xbZZD4sK4N3Ru7MeAlEhpfucpqewpitOm/ucNi8SxfNJIuoXTrenTnDLodxhaEREvaa1ThZh\nMidSlUoFruvyQi7nDlQH4hbrFnjwsB7rsV6sx7aaISkRUb+ZADQtXXGarjptrjZln1Mimo92coEo\nilhJSm1jSEpERAPDVLoEQQAhBDzPQ7Va5XT6AjlbnY2zw7OxERuxDuvYooKIaJ5uuMGG6wIvf7ns\n2c+Yabp+uuo0DMNkgahWFaeDGJ5yijfR7Bby+xHHMXuSUtsYklIhsdq0f/heU9E1T6f3PA+1Wo1V\nLAU3uuV/REQ0t2efBf7lXyYrqw46SKJanfr1Xh4PZ+tzKqVMFohq1efUHKt5vCai+WIlKXWCISkR\nUYYYQnefEAJKqWQ6fRiGsG0bvu/D8zxeaBER5RAr6XpryRLgjW+M4bqYFpBmcR6S7nOaHke66jSO\n4yl9TpsXieL2Qr3AfVHxMSSlTjAkpdxhaERE7TLT+OI4xubNm7kIUwe4L+4c3z8iypPXvz7Oegiz\nahWcAvPrc2oCVIZbRMSFm6gT3HKokHjx3j98rynvtNaIoghBECCO42RK3+joKC+WKDPc9ohokKxb\nB/g+MDzc/eeeq8+plBJxHM/Y55R9x4mKq53KXvYkpU4wJKVc4jQHIpqLlBJBECAIAti2nfQaNYEp\n9yFERES99/TTAu9/v4/FizUuuijoy89MB6dmWm2rPqdSyiQ4ba445XkCUTnFccxKUmobtxzKnYWc\nsDBMpTJgpe78men0QRBAKcXp9ERERBlzXY1KBRjNeC29+fQ5TS8QxT6nROXEnqTUCYakVEg8gaGy\n4LY8N611sgiT6TE0NDQE13X5/hEREWVs0SLga19rII+z2mfrc2oqTqWUUxaIyqLPKW+YE3UPQ1Lq\nBENSIpoVe5JSVsxFi5k67/s+qtXqnL3FuM1SETDgJ6IyyWNAOhshxLTpuLP1OU1XnNq23ZN9OI8L\n+cCZisUXxzFDUmobQ1IqNB7EiMpFa50Eo1LKpM9ory5IiIiIiICZ+5ya4NRM1280GuxzStQn7Vzv\ns5KUOsGQlAqLJyFE5WCmvAVBgDAM4TgOfN+H53n8PSciIqLMpINTI93nVEo5pc9pc49T9jkl6j+G\npNQJhqRENCtOXe6tQX5/lVJJMKq15iJMRERElHvpPqfpKfvpitNWfU7TASqDU6LeYUhKnWBISoU1\nyOESUVFprRFFEYIgSPoFVatVOI7DC4acMZ8H25oQEZUbz6e7wwSgaemK03TVaXO1KT8Dou6J4xjV\najXrYVBBMSQlIqKei+M46TVq2zZ830etVutZ+MaLDSIiovnjzbDemGm6frrq1FScNhqNlhWn/Gz6\nh+eP+dNuT1LP83o0Iio7hqSUOzwRICoHc+IfBAGUUn2bTs99CBEREeVVq+B0fHw8CXXMAlGt+pya\nhSx5rtNbfH+LjdPtqRMMSamwON2+PzjltrfKth1rrRHHMYIgQBRFcBwHQ0NDcF2X2w8RERHRDEwY\naqQXiFJKJbNyTJ/T5kWieJ5FNMm09CJqB0NSyh0e4ImKJ706vRACvu+jWq1O681FRERERHNLLxCV\nNp8+pyZA5XUVDaI4jqcsqka0ENxyiIioLVrrZDq9lBKe56FWq/GkpAUNjQlMYBjDWQ+FiIgKTIhH\n4Dg/RByfCK13zno4lIG5+pxKKRHHMZRSScjaXHVKVGacbk+d4JUsFVbZpinnmXmveTeatNZTqkYd\nx0GlUuF0+jl82f4yrrOuwwXxBfgz/WdZD4eIiArKca6D49wAwEYU/W3Ww6GcSAenJhwy0/WllEmf\nUyllEpw2V5zyPI7yqJ1rUE63p04wJCUiojkppRAEAYIgAAD4vo+xsTFWI8xThAgaGhIy66FQH/FG\nHhF1Wxy/FoCNOD4u66FQzrWart/c5zS9QBT7nHINhrJgJSl1giEpEVGG8lwRrbVGFEUIgiC5Izs8\nPAzHcXJ9ApnH9/RMeSbeKt+KRViU9VCoT/L8O0JExaX1toiit2U9DCqo2fqcmopTKeWUBaLY55SK\nhpWk1AmGpFRYeQxCiMrArE4fhiFs24bv+6jVajwp7oAFqysB6VXWVRjWwzhKH9WFUc2NrTaIiPrH\ncX4AIZ5DFL0VgITrfg1ab404flPWQ6OSE0JM6yk/W5/TdMWpbds8T6BcYSUpdYIhKRHNiYF0+Sml\nkkWYlFLwfR+jo6NTFgWgbD2Gx3CxfTEEBA6LDoOL6Sd/CgoW2AKBiIqHN2QUXPdbACTi+GgAMRzn\nOgAuQ9IBkMfz7Jn6nJrg1EzXbzQa7HNKPdPOsYEhKXWCISkR0YDSWidVo+ZkYmhoiIsw5dR22A5/\nLv8coxhtGZBeb12PL9pfxJnyTByn2KuOiKhYLIThORBiQ7JqfRi+B1q/oOc/mQF1PhThM0gHp0a6\nz6mUckqf0+Yep5yuT/3A6fbUCYaklDvzPXCyupHKIIvtOL06vRACvu+jWq1yEaacs2Dh7ertM359\nHdZBQWEd1vVxVERE1Ln1ADSkPGzKv0r56myGQ7QA6T6n6Sn76YrTVn1O0wEqg1PqJlaSUicYkhLR\nnBhIF5/WOplOL6WE53mo1WrT+k+VwaBur6eqU3GoOhQ7Y+esh0I9MojbNdGclIJ1111Qe+wBjI5m\nPZo21DE09A4ACvX6twEMZz0goq4wAWhauuI0XXXaXG2aVZ9TVlWXA0NS6kT5ro6JiAjA89PpwzBE\nGIZwHAeVSoXT6UtKQOCFeGHWw6Ae4e8sUWv2DTfA+6d/gjzkEITnnZfZOIR4FJb14JZq0Obf1/Ww\nrEeg1D4tvtOG1mMAJHhpRmU303T9dNVpGIbJAlGtKk55PBws7dwgZkhKneCRmAprUKvFiOailEIQ\nBAiCAADg+z7GxsY4nZ6IiEpH77Yb9NKlUCtXZjoO3/8EhHgIQXABlDpo2tcsaw3C8HxIeXDTd3po\nNL6+5b8Z/tDgma3PqZQyWSCqVZ9TU3HK4LTcFvr5SilLOVuO+oNbDhFRDnQ6vUdrjSiKEAQB4jiG\n53kYHh6G4zg8cSQiotJSe+yBxmWXZT0MxPGRsO1haL37tK8ptReEeBZK7TDDd/M4TZSW7nOalq44\nNbOlTJ/T5kWieP47uFhJSp1gSEqFxkrS/mDVbu90egJnVqcPwxC2bcP3fdRqNZ4YUle087v/JJ7E\nBCawK3bt0aiIiPLDsu6E75+PKDoVQfD5lo+Jorciit7a55ERlU+7fU5NgMrz48HAkJQ6wZCUCosH\nORpUpl9TEATQWsPzPIyOjk6ZpkSUlb9x/gYbxUb8a/Sv2AEzVU0REZWDEE9BiDos67Gsh0IFZW5G\n8tqmPXP1OZVSIo7jGfucpkNXLtxUDnEcMySltjEkJSIqADOdPgzD5O5otVrldPoWWPmcrRfpF+FJ\nPIkRjGQ9lNzjdkpUfFIei3p9d2jNhfOI8iIdnJqwrFWfUyllEpyasNQ8jufX+WDaKSwEK0mpEwxJ\nKXcWckDiBWZ/MHTKjpQymU4vhIDv+6hWq1yEiXLrM/IzWQ+BqCM83tFCab086yEQ0Rxa9Tk1gWi6\nz6lSCuPj4+xzWmDtBKtEBkNSKiwGd1QWZls2J15a62Q6vZQSnuehVqtxlUYiIqIesu1b4Tj/iTA8\nA1qzrzJR2TUHp5ZlIYoiVCqVpOJUSjllgSj2OSUqN15xExHlQHp1+iiK4DgOKpUKXNflyRdRQfFG\nHlGx2PaNsO07Ydu3I46nh6SWdT98/wOI41cjis7IYIS9wanFRFMJIaYVJ8zW5zRdcWrbNn+fiAqM\nISkVlhACSqmsh0HUEaUUtNbYtGkTAHA6PdEA4UUUUb5E0d9AqZcgjo9p+XUhnoEQm2BZj/R5ZESU\ntZn6nJrg1PQ5bTQaU/qcpitOedxfON7EoX5jSEpEc2Jrg+5KV43GcQwAqFarrBolIiKaSb0O6957\noV7yEiC1inU3ab0t4vi1M35dykNQr18Krbfvyc8nomwtNJBLB6fp5zDhqZQSURQlRRHNPU45XZ8o\nfxiSEhH1SRzHySJMtm3D933UajVs2LCBU3O6KN3ble8ppd0n7sPjeBxH6iN7/rO47RF1l3fJJXCu\nvhrhGWcgftObpn1diCeg9RIAvV3RWOtlPX1+Gjw8XymXdJ/T9JT9dMVpqz6n6QCV2wNRdhiSUmGx\nupGKQCmVLMKktYbneRgdHZ1yx5kor8q2n32/8348h+dwWXwZVugVWQ+HiBZArVgBfccdULvvPu1r\ntn0bfP+DiONXIAzPW9Dz+v65EOJPaDS+BGCsS6MlIprKBKBp6YrTdNVpc7UpiykWpkznrtR/DEkp\nt3hXNT/KFpT0WvN0etd1Ua1W4TgOt2miDB0vj8eD4kHsrHfOeiiUc9xX50/8mtcgfs1rWn5N6woA\nG0Btwc9rWb+BEM9BiI3QmiEpEfXPTNP101WnYRgmC0S1qjjl8YqouxiSUu5wR09FJaVEEAQIggCW\nZcH3fQwPD3MRJqKcOEOVZzVqokFg3XcfvI9/HPHrXof4jW+c8XFKvQQTE9cD8Bb8MxqNrwHYBK13\nan+gRERdMlufUyllskBUqz6npuK0TNfT7RRO8dqLOsGthwqL1Y2UB1prBEGAjRs3YuPGjQCAkZER\njI2NoVKp8CBNVFJXWFfg29a3sx4GlZxYuxb+e98L++absx5Kz3nerbDt/5nyb9batbD+8AfYd901\nn2do6+dqvQ37jBIRgPzOZDRVpK7rwvd9DA0NYXh4eMrCr3Eco16vY3x8HBMTEwiCAFEUQUrJa2ai\nBWAlKeVSHg9ORIbWOlmEKYoiOI6DSqXS9ur0DPyJimUCE/i8/XkAwNHqaGyPha90zeMczYd9++2w\n77oLetEiyMMO68pzWvffD+260Lvu2pXn6471GB09H5Zlo17/Fjzvm4jjwxEfdxz0VltB7rnnvJ7F\nsn4Ly7obcXwyABdC/AG2fSvi+PUAhnr6CoiI+q3dPqem+pTnIkTTMSQlojkxxJuklEqm0wsh4Hke\nqtUqq0VzyGyzPPmjXqiiinPkOaij3lZASjRf8UknAbUa5CGHdOX5xDPPoPKOdwCOg4nrrwfc3q4E\nP7cInvePUGo71Ouvhe/7sKz7Yds/hRBPQcpjFvTaPe+zsKz7ofXWkPJoeN7FsO1fALARx2/q3csg\nIsqJufqcSikRx/GMfU55XUODjiEpFRaDO+oHrTXCMEQYhojjGJ7noVarcZVJogH3RjVzf0Sirhka\nQvy613Xt6XStBrXXXtC1GuBkfxkgxMNwnKugtY/1638EIWoAQoThRki534KfL4pOhW3/HFLuDwCI\n49cBcCBld6pwiXqB1zPUa+ng1N1yc6xVn1MpZRKcNlecZnXds9CiB/4+UaeyPzsiIsoZc8IQBAHC\nMIRt2/B9H7VajcEoEXUNT+Sp7yoVNL7yleSv4qmn4F56KeLjjoN6yUsW/HTOd74D+/bbEZx7LrBk\nyYK/X+vlCMMPQqltUv/qtV31KeUxkPKY1N9fBilf1tZzDQqzH+L5Tbb4/lO/meAzXTlqglNTdZpe\nIKpVxWket1sp5ZQqWqKFYkhKRHMalKpdpRTCMEQQBNBaw/d9jI6O9vxAOyjvLxUTt83uMtXpQRAg\njuPkRkzzyrRE/WDfcAOcq66CeO45BO2EpFddBeuhh2D/9reQL5tfGGn/7Gdwrr0W4XvfC73DDojj\nE7fsZ8YX/POJiKh7WgWnAKZUnEopEYZhEpzmrc9pFEVJtSxROxiSUmExWKJu0FojiqIksHBdF9Vq\nFY7jZH6QJ8oafwe6x1SnB0GQVKebqW/mwiMMw6RHWHNwStQL8fHHQ2zYAHn00W19f3DBBbDuv3/W\nvqETmMAz4hks1Uthw4bzgx/Avu022Pvth/jP/3za44V4BLb9K8TxsZi8VFGw7dsh5V5wnGvguv+J\nIPg4lNqjrTETEc2E/exbE0LAaWrRMluf0yxv/ppFdYnaxa2HiAZSOrCwLAu+72N4eJjNyomoa7TW\nyX5GSjmlOt1UZTQvktDcI8wEpwCSqtPp1Rob4TjXQKnFUGoVwMWkOmI99BD81auB178eKHtAvXgx\nor/7u7a/XS9bBrls2ayPude6F0+Lp6GUwm6/bSA+7jjI/fdHfMIJLR/v+5+CZd0FQCCOXwPH+Q94\n3mch5dEA6hDiD7CstQxJiYgyNFOfUxOcmun6jUajr31OoyiC53ldf14aHAxJKZdYJUq9YAKLMAyn\nBRZULtyHUJaklGg0GsnNmEqlAtd153UxMFOPsImJCViWlezH0tUa1eq/wPO+Ast6AlpvDaWWAaih\n0fgqtF4MYDOAsZ693rIZ+vjHYf3udwgXLYJ85SuzHk5u2DfeCO/rX0dwzjlQ++8/7+/bMdoOeuPT\n2NodQuVtpwFaY+Laa4GhoZaPj+Pj4LpPQ6lFAACl9oDWSyHlvojjo2Dbv4OUB3XlNRERUfekg1Mj\n3edUSjmlz2lzj9NW0/UXWt1rZgYStYshKRUWQ5D+EUIklUxFo7VGHMcIgiCZfrGQwKJfuC0TFVu6\n16iUEq7rwrIsjI6OdvzcJjh1HCe58EhXa4Th4bDtn8Hz1kGpCixrNQALQvwcrns7HOcniKK3wLKe\nQBC8H8BWHY+pzMITToA9Nga1alXWQ1mYiQlYa9ZAHXAAsJBZERs2wP7FLyCPPBKoVGZ8mP3LX0I8\n9BDsn/50QSHpzhd+G7v9x38g+MQnIA8+GFAKqNVmfLxSyyDEH+H7n0K9fi2U2gf1+g+Sr0v50nn/\nbCIiylb65m96Gny64rRVn1MToC5UHMcsgKGOMCQlolIyB9sgCCCEgO/7qFaruZxOn6ewlogWplWv\nUc/zEMcxpJQ9+7lTqzVWIYquQBhqKBXBcb4NYBzj44dhePgWWJaCZV0Ly3oKQrwMSr2K+51ZRG94\nAyZOOAFDM1Q65pX3+c/DueoqhGefjfiUU+b/fRdfDKfx/4BVo2gs+b9QXusFnML3vAfWHXfA/e53\nIV/xCqh9953X8+tabbJtwcgIgn/8xzkfr9SOkPIATqcnIiqx5nZDAKZUnJqqUwCYmJiYd59TLtxE\nnWJISoXG6jtKa67k8jwPtVqNq0UTUVc172tate7IYp8zGZx60PrtAIBqFVDqUxgf3wghHoEQd6Ne\nfymUGs/lirTUhokJ2HfeCXnwwVB77w19xx1QO+wA53vfg3zFK6CXLJnzKeQhh8DBd2DZD6Hyz2dg\n4r0/b/3AWg1qn31grVs3GXymCLEWWi8FUJ32bdF734voXe8CfH/ysQ89BPfyyxG95c0Qu66D512K\nMDwJwMFbvmMUQfDlBbwJRMXGxYKIJrWarr9582b4vp8EqOlFLlevXo2bbroJK1euxKpVq7DjjjsO\nVE/Sc845B1dffTU8z8OyZcvwzW9+E2NjbK/UKYakVFg8meifPLc2MAucmF6j6UoubiNE1E0zVY3m\neV8jhAPb3gqTU+xXoVqdeUXa5tCUwWn+eZdcAue730X0znciete7EL/hDXC//GW43/gG4t/9DuF5\n5835HPKoo1B/7kcY+szJwM8B68jVUCtXtnxseMEFiPSj0GKH5N9c96vw/fOh1NaQ8lgEwacw7RJj\nS0AKAO53vzu5wn3lFljnPQDAhePU8HxISkSUDTPdm/LBXH82F7yYPqe1Wg31eh2XXnop1qxZA6UU\nVqxYASklLr/8cuy7775Yvnx5aaffH3PMMbjwwgthWRY+9KEP4dOf/jQ+85nPZD2swmNISrmU51CO\n8kEplQSjWmsuwkTTcB9C3aC1TlZnLcuCb3OtSJteWIHBab7JVatg33rrlP6p8sgjYa9eDXnMMdO/\nYd06ONdeC3nssVOqTPXi3RAc9Sn4P/4w/AsuQP3732/58xznB/D9TyAM34ooeg8AQIgnAEgI8Qxs\n+6cANmK2vrfRaacBrgu85RkI/RTi+GSE4V+28eqJiGgQNJ93mD6n++yzD/bZZx8Ak+cxjz32GG64\n4QZcccUVuPLKK3Huuefiqaeewj777IN99903+bP33nvDT928K6qjjz46+e+DDjoIV155ZYajKQ+G\npFRoDEEGiwkrgiBIVi6sVqtwHKfQF+28KdB9Rd4e8mSQt81+VI0u9L3t5WfB4LRfYnjeJwAMIQw/\n2PGzyVe9CvVXvWrKv6m99kLja19r+fjqySfD+s1vEN5/P8ILLpj6XAcfDHn88ZAHHgg0GvD/4R+g\nt9sO4d//PVz3MgjxDKTcC1oLpKfVh+FHIOXLofUQJi8tZl8YTO+8M8IPfACARjhxLoDalm17fMGv\nn4iICJg8j1m6dClWrlyJhx9+GF/4whcAABs2bMCvfvUr3H333bj55ptx0UUX4YEHHsDy5ctx5JFH\n4ktf+lLGI++Ob3zjGzj11FOzHkYpMCSl3JqrPw8vyAZHq7CiVqtxGyCiripj1WgnZgtO04sqMDid\nPyHWwXV/CK1thOF7AXR3cSjLWg3P+wKi6O2Q8mXTHxBFgG1Dbqm8mWJsDMHHPz45zt//Hs4NNwCb\nNkG9ZDHc110CISxE0Q8wMXFL07g9SHlkG6MVAGZe5Z76g/0wiahM4jie0pN0bGwMRxxxBI444ojk\n3xqNBn7961/jiSeeyGKIC3L00Ue3HOenPvUpnHDCCQCAT37yk/A8D29+85v7PbxSYkhKucSTtXzJ\noprMNOYOggBKqYEPK4iod4rQazQvY2m1qAKD0/nTehs0Gl/AZMjY3YAUAGz7Ztj2r6DUTZMhaRwD\nUiY9QRv/+I+ovO1t8L75TdRPPnnmce66K6KTToJ7xTdQ2eMc6PEliB44Dc7PbkJ0+ulA6lDsOD+E\n1ttCysmeop53IWz7djQaX4HW23X9NRIREc1kPqvbVyoV7L///n0aUWd+/OMfz/r1b33rW7j22mvx\nk5/8pE8jKj+GpFR4vANeHlprxHGMIAgQRREcx8HQ0BBc1+VnTERdxarR7llocJoOTTsKTqUEGg1g\neLhLr6Q/pHz5vB9rX3cdvEsuQfiRj0Aecsicj4+i06H1dojjlwNaY+jkkyGefnpyNfr3OLD/+U7g\nTwHkHnsAWkM88ACwu4CwN0Opl0w+ybp1EJs3I/zQhyCeeQzu4z+CHt0Jzt/8FOKAxyCeehjh9hcA\nELCs++D750HrIUxM3DY5ZvtOWNZDEOJRhqREVCi8rsyXdj6P+YSkZXH99dfjc5/7HP7nf/4HlUol\n6+GUBkNSKiwewMpDSplUjQoh4Ps+qtXqwKwuOch9H4n6LQ9VoyY81FojDMMpq7aWZb83n+DULLw3\nd3C6EZZ1P5TaG8DzFwH+WWfBvu02NP7t36D22KP7LyKOgTAEqtW5H9supYDnngNSiyil2XffDetP\nf4K1Zs28QlJgGHF8EqAUnO9+B+LZZyE2bIB48kmIXz4L3B8DFQ/1L30J7mWXwbvoIuA9AXBWBfX6\nNwHY8E/9e1h/+hPqF1+M4MtfR/DcZ4HFi+G8+wfwj3s/3MU/QlQ/HVovGsibEgAAIABJREFUg1K7\nIopeB613TEbQaFwCIR6FUvt25z0iKjmeAxJ1zyCFpO95z3sQhmGygNNLX/pSfOUrX8l4VMXHkJSI\n5tSLEM+EA0EQQEoJz/NQq9WmhAVEneBFBxnNVaOe52VSNaqUQhzHkFICABzHgdY6CQ8BJOGp2Rea\nP2XQbnBaq50B170OUu6Jev3m558vDCdDxjjuyXgrp58O68EHUf/+96GXLu3Jz/D/7u/g3HwzGhdd\nBHnUUbBvvBHupZdCHn44ojPOQPi+90EedhjkwQfP/WTr1sG/8ELIww6DfsEL4H/601Bbbw1RrwON\nBvQVi6CXjkJ+8UhUln0U8bbHAI4DFS+C/foHUPnq30Bstw5qmx0hbvsTqqeeivF774XeEuDGr38D\n4AAiehpa77blh3oIw/OnDEPrbaD1Nl1+p4jKrSz7eaKsmcV9B8HatWuzHkIpMSSlQjPhHU8sikFr\nnVRxhWEIx3Fy2fuPio/bEwH5qRo14agJ/xzHmVYxakJS8/h0cJpeZd5MWS+LmYJTKWUSnobhTnAc\nB0pVEARBEqDWL7oIYnwc2Gr21dTbHlsUPd/Tcz7iGM73vw+1ciXUnnvO+XD7pz+Fc801kz/HtmHf\neisqZ5wBsXEjRL2O6IwzgKEhyMMOm9ePt++4A85118F66CHUL7sM2nFg338/EAaAqxGd9lrEB58E\n/6WfhhBPInztWYhOOhXuv30ZuKsO8fPHIE4KgX+vQe+8FbCdgHYmADxf5RrHb5jfe0FERJSBOI7h\nOIy5qH3ceoio55RSSTCqtYbv+xgbGyvVhT4R5YOpGg2CIFnhNIuqURNs1uv1aQsYtWL+Pf31OI4R\nhiGiKEqmoJuKy/T3CSFKtT8VQky5wNH609i8+aOQUiTvQVJxWqnATgWn3ay8rX/720C9DixaNK/H\n2//93/A/+Umo5ctR/8EPAADOVVcBExOI3/SmaY9XL3wh1MqViI88EvKIIyD++EeoFSugRkeBkRFY\nv/0t1IoVz3/Dxo2wV6+enHbf4vOWRx2F8OyzIffbD2JiAuKJJ4Dx8cnA88A6xEeeg8KLAYSQ/7sM\n9n/fAvsv/wviNRH0ZS7wCR/xKw5HXDkB8qHDMTR8Iob021Gv/1db7x8REVEn2JOUssCQlIjmZaFT\nl5uDCtd1Ua1W4TgOq/xa4NRwos60qhqt1WqZVY0qpWDb9rQFi9J/Wo3N7DvDMIRSCp7nYWRkJAlB\nm6flp6erG+UMTqtoLgyZXnE6faq+eZ99/2OwrD8iit4CIIKUx879Q30/WRV+PuR++yF+5SshDz10\n8h8mJuB/+MOTXzvsMOgddpg6/l13Rf3qq5//+847o/7DH8K78EJ4F10E58YbMXHTTdA77gjx+OPw\n3/c+2GvWIHjf+yBf8Qro0VHAtiGefRb2vfciPv54RH/1V8nzqf33h3XnnRD1DcDtMfDJCYhzn4IQ\n62B/6k+w714LefNSaKcCDEtgd6ARXQrb/zks5x4AI9C6da/UbuOsICIi6gaGpNQphqRUaFzwpj8W\ncuFiKp+yDCqKhu8N5VXe97F5qRpN9xo1lYyu68LfErCZMC/dd9OEqOnANI7jpGrU8zy4rjtt/9Cq\n4nRwg1MxbUpdOjg1xyOtNYaGboBlbYTv3wEhBMbHVwDYpen5nobWi9sf0JIlCL74xef/Xq0iOuUU\n6KEhOFdcARGGCD/wAUAIWLffDv+zn0X47ndDvnzqavfRX/0VnO99D2J8HGLtWrhf+Qqcm26C9dBD\n0K6LyoXnAV/4CLT/AuiRJRCPPAKxeTPq3/wm5GteA6xfD+f66xEffjjwylfC9S+DtdUfoDfvDPfM\nf4F6ZjdEb34TnF2uQnT066Cvuw32ObdBL90eorEJlcpZACyMj/8cQK3994OIqGB4w6b44jjmSu/U\nEYaklEs8OBWLUioJRpVS8H0/k6CCiAZDnqpGTSA3U69R4Pkwb+oUcp2Eoo1GIwmjTfWj+RnTV3qf\nbj7BafrvZkzmzyAEpxMT/wLgWdj2LRDiWWzePAbbfr4Vgufdjmr1XYjj4xDHn4Zt3w/P+y9E0Vuh\n9dbTf9CGDYBSEBs2QO+yy5Qv2bfeCuvuu6G32w7u5ZcjPuYYODfcAACITj8deuutYd9+O6y77oLz\nne9MC0n1dtth4sYbYT39NLzzzoPzX/81WdGq9WT/0oMD4DQN/Oc66Ae2g0Ad8G2o3XcHAAydeirs\nO+6A3morqB13hFi/GerPdof+6tbwDvy/0KEPfO4J2G9cDcgqGodfBs/7HBzxnxDiSUTRGwFUwICU\niIiKJooijI6OZj0MKjCGpETUFnOBHwRBMq1haGioZeUTURbyXAFJC9eqanRkZKTvzfnT0+mB50O5\nhQSN5sZSGIawLAuVSiWZGmaqTc3+tbni1Ewjbzc4NYHpoAWnQrwIAKD1IdAaGB6eWnGqtUKlIhBF\nDqIowuLF74Tj3A/b/hnq9aunPuGmTageeyzE008DjoPgM59BfNxxwJbP0PvEJ2A99BDC00+H9n2o\nF70IjWOOgYhj6GoV3uc+B7XttgAA5/bbEd96K5wf/hDh+/8OlnsHlD4A4uk6ho47DuLZZwHLQnzc\ncYjf8AaI8Gl4+30A4n8jiPsiYEcN8Ugd+igfQ3/910AQwHrgAcBxEL3iFfAe/w9g7xAYlvBu/Sfg\nPyKIzQ683f4VUu6NOH4VAMCyHoQQz0GIpxCG/6dvnw0REdFM2jmX53R76hRDUsql+YZseZ8KWhbp\n9zm9Ov1knzcf1Wq1VBfUVHwM6ssjL1Wj5sZQur/oQvZ75vvDMISUEq7rYnh4eFrFfauK024Hp+mf\nOVtwavp7ljU4nRqwH47x8V9AqQqEkGg0jke1+iwmJg5Do1Gf8pkLIQDPhhgah1Y+7CuvROUf3oHo\nkBMQfP0yRCefjMrHPgb/y1+G3morxMcfD714MSpnnQXvwgthPfgg5L77Qu23H9ToKPyzz4ZYtw5i\nj8fgfP1aaDGGxqe/AbFhw/PjffxxxK95DaAbsOUNcE69BvhdCPt3vwG218ArQ1ibfg38NwANII7g\n/uJK4FcB4ALiwPXAjxT0F4aAlwOW9QiU2htx/OcAgEbjc7CsP0Kpvfr6OVD2OL04e/wMiGa20N8N\nsxYGUbsYkhLRnEyPu40bN0JKCc/zUKvV+l7BVVYM+4mmKnPVqOd5qFarC7oZ2BycpheISk/XN4Gp\n4zjzXul9ocGpGVMZg1PLGtmyaLxAvX4OgPOgtYLrTr7fZhEuDUBd9z6MjH4YSi+H/cF7gYsbcH98\nBdw3XIfgovdC3TUC8b8KemgJtOvCWr0a9q23Tlaf+j7iww+H961vwX72WUBKyJe8BHqdBh5RwFtj\nVPZ8B3BwDNyCyWn969bB/8BZcK6+HvF++wG/AWADqNeBnQBxnALeAODNAH4CQAMiCoDHASwD8GYF\n3A8ER54Ff6tvAHgOSi1PvfoRBqRERFR4rCSlTjHhIKKW0lVPZuELMyWUd7uJqBfyWDUqhOioatSE\nvK2qRttl+mg2B6fphaFMoNlccdqN4NT8AQYhOLWmvZ7J138sJqJ1iKJVEO99AGOjZ0KsbwAPboY3\n9FXgGz6UWg7b+V/U7lkB3CkQn3oo5IFnQj9Tm1yZXinooSGIDRsgGpvg3HwvMKEgdtww2RJ0FYAV\nAG4DrPt+C2vRb4HHAPexx4B9t3z93zBZPXoUgF8B+CKAvwDwIIDNAAQA2wc+FADwIMdPRhCsgNZb\nQcrD+/U2EhEVAqt6i48hKXWKISkVGivwuk8plYQUAJKQYnx8HJ7nZTw6IiqbslWNRlGEMAwBYMFV\no50wYV76wmC+wel8XuNswal53sEKTocAvB2uC+ht9scm/Wq4234F4qN/RLTVvqjI70MpF7ZTB/YC\nsDXgPP4/sPe6B2LTRmC9gv4ooB7ZDvYvN0Kc9geIj+rJUPN8ANcDuBnA1wD8GYCPAfhFahBrMVkl\numTL3xWAEQAegH0AVDH5XDUAiKHUixBFb4fWuyOOd+/5e0RERJQFTrenTjEkJaKWIcXw8DAcx4EQ\nIrkQJiLqljJVjZoQMr2InanazFJzcGpapzA47a7J17MY8oSPTP4dQKPxLmgdQcqvwnF+BOfehyCc\nEEpUYS9ZDywCxEmALZ4AtgbE7xuT37gCwJkAzgIQA3g/gAMAHAHgKgC7AzgIwB8wORX/AkyGpz/Y\nMpgAwLMALgJQAeQ2uyEO/hJRdCYm5+cTEREVQzuVvawkpU4xJKXCY3jXPrMISBiGmYUUhCSIpu5h\nlXl3dPt9LHvV6NDQUK73n+lwcqbgNAgCSCmTwLibwelsPU7N95UrOPWg1JkIwzMRHrzlvQ407OBS\nuP7/g/vE/RBeHdhaA7tictr8KICbMFkJegCAjQDeCeBEABNbvh4DWI/JAPVJAKcC2IDJXqQrAXwf\niHZ+C6Lor6DqB/X5lRMREWXHLI5J1C6GpFRoeb4YzSuziEgQBNBaw/M8jI6Odq1XHhFRMxO+hWEI\nIQQqlQqrRnNipuA0PVU/HZyaRaHSPU7nMp/gVEqZVIxoraf0Ai1XcCqg8U6E0TsR7ralSmbzddAa\ncJf+GH7j3yAWNSanyR8N4DAAL9vyBC4mq009AFsD+PaWf48AbAPAEaj/8/mQS94MBNv0+dURERFl\nL4oiLi5MHeHWQzQATDAQBEFyYV+tVpPp9HNhVR4RLVSrqtFarVbIqlGtdbKIHTBZNVqpVEoT3jVL\nV5EazcFpFEWQUsKyrJaLQ81lPotDmUpTE6CWNTgFjoMQQBwfh9j5IvQhGvj5H+A+cgnUngGG9H9C\nRBsmQ9LkG7f8AaDdJQgOOBPxFWdl8AqIqFM8xybqHk63p04xJKVcKmpFTt40V2/5vo9qtVqai0si\nyp/04m9ZV42aQM+EfsDCwjWzQn1ZqkY7kdfgNP3cZTm2CSGA4V0Qv/jzgALGxy+erDh96ip423wY\nrvsIzNv55JOAZd27pSo6Htjtk6jo+HubD1zdPl/auYHAhZuoUwxJqdBY4TidqXgy0yOzqt4iosFR\ntqpR81pMS5KRkZHSBHDdlGVwav409zhNB6fmTxkIIYBFJyIMT8SWgmZorTE0NHkzwPTIbTQaSfsE\n006CwSkRERUVF26ifmNqQlQCZjq9mQ7qOA4qlQpc1+3qhRHvrvYGw34qqjJVjaZ7jdq2jUqlMu+W\nJPS82YLTOI6T91kpNSU4NWH2fIPT9GdrQtJWwan5+SYoLFPYne4na6QX4jI9yJt78DI4pTSefxBR\nmTAkpU4xJKXCG+STu3RAAQC+72NsbKzrF4G8kKKiYfDcO3mqGjXBKNBZ1agJksxrKVOQlgczBafm\n80sHp83VpvMJTlv1KZ0pODXbi3k8g1MGp8TzPCIqD4ak1CmGpFRog3hS1yqgGB4eZsUTEfVUXqtG\n2wm6mqtGfd/nPrTPTKidDtfTn61ZbLAXwamZlj9TcFq2GywMTomIaFCwJyl1iiEpUUGYC8YwDJOL\n+n4HFEQ0WEyIsmnTptxUjZpVzlk1Wj5ZB6dmO4vjGMBkNYp5/KBUnKb7vbYKTuf7XhMRFU3ZbpCV\nQTut3lhJSp1iSEqFV+YDmrlISS8gMjo6OmXKYr+Y6cu8MOo+Tg2nvDFVo2EYQgiBoaEhVo1SJuYT\nnDYajaTvaDvBqQkHwy0rIrmuC9d1Wy4MZcbUKmQsutn6yZo/JqRmcEpEZcV9WbExJKVOMSSlQivj\nQSxd7WR28tVqlRf1RNRTrVp5eJ6XLGLUL92qGv3/7N15sFxlmT/w77m3+3T3XZIQIIwQgqyyxoQs\n98bBYobFKS0YHErFoXSwUERFR1nCEC3nP5eZ+iVhR5B1QFFQBhxGR2BmsMhNyCUJAmHfA8gWIWS7\nvZ/fH5mn8973nu4+a5/t+6lKzSAh6XTO+n2f93nUqsN8Po/BwcFIFpgoeHbBqXrcyJR3AFOCU3Xi\nvR6gl0qlSdvL1eNFDUwZnNoHp7JFn8EpkTtyryMi/7jdnvxiSEqxlMWH6kaj0er319fXh0KhgIGB\nAT40EVGo9F6jaiuPnTt39uxzqEN8vFaNSjVgtVpFX18fTNNEPp/P5D0layScU1+M1OC0Wq1OCjSl\nJ6f09e4WoMtx6DQ4ldAji8GpVPi6CU65U4WIiILASlLyiyEpJVrStylbltXaTt9oNFAoFDA8PNzz\nfn9EaZP0a0PY4jShvtlsol6v+64alRCMVaMk1OBUbV8jIR+w62VKKkn1rfpOfn2AwSkwOTiVl1M3\nwSkREZHOywKa3GeIvGISQ9Rj6jbQWq2GXC6HYrEY+2onhk7h4ndLvdCparTXn6NerwdeNTowMBDr\n6yj1lvQu1RcD9ApItcepWnEaRnAqP4BsbdXvFpzKM0atVmsFqDyXiYjI7b2A9w7yiyEpUY+o4QQA\nbqenFt7MKUysGqWskV0aMoipU4CuhpNqkCfBqSxqSqAvoV8ul5vUv7STTsGpVJhmPThVz+tarTap\n4lQCaganRBQmtv0gIoAhKSWcYRitF4s4Ul/U9CoW3oSJKExxrRpVp2K7+TVYNUrdSCVotVpFPp+f\nMojJqXbBqdrjtFwuo9FotEI8fThUN92CU/ln+XOpnyuNwakEoDIkTq84ZXBKREREvcCQlCgEUnlS\nrVbR398fWTgRJG63J4o/qcgql8upqBpVt0rn83kMDAywZzNNIpXS1WoVzWYTpmlieHg48BCx07Ai\nCU5rtVokwan8d2kLTttt1Ve/bwanREREFCS+aRAFRB0KYVkWCoUCpk2bxm2gRBHJUqgfZtWom+8x\nqKpRCb2AzlulKbv06uJCoYBcLtfT4yTq4FTfsi+/XhaCU8Hg1D9uMY4e/w6I7PHcoCgwJKVY63Zh\njLq6Ue/1p1Y68YJOTkV9HKdRFr7TdlWjQbbzcPI9qltiJZzwWjVarVZRq9V8bZWm9EpCT1onQZ5U\nvYYVnMrvBaAVoEpQqP73aeD0+5bvQA1NGZwSERGRjiEpxVLcH1plC2ilUmlVsAwODqbqxcNO2kMn\noiSIW69R2f5rGIancFQfsFMsFlN/LSV39OpiGXwY92cF0S7IkxBPD05lKJQEemEFp2oom6ZzjsEp\nEXnF85+IGJISOSQv8zLlNmvb6fnQQBSdXlSNOiGhi4SjasDgFKtGySlZkEzjcSKLCmqPXTU4ld7m\nzWZzSrWp3+BUfkhwCEwNTuVHWjA4JaJuWAySDrxek18MSSm2nFzgwt5SK2GAvKTlcjkUi0Xk83le\ngIkodHZVo1FUrbNqlHqlV4OY4qhXwan6Xco5bRecyu8vwWna/g46VfhKeGoXnKpBMhERhYfBNUWB\nISmRDXkwlmBCBoek7QWB4iEL/TPJOX1xJp/PR1Y16ndCPbD7elqtVlsLTezbTDpZEKjVaujv749k\nEFMchR2c2vUpbRecynZ9+flpDU7V7xpgcEpEFCW311W+U5FfDEmJ/o++nT6q7axxxSCPkiZpx6td\n1WgUizNq1ai89MvEaKchTJarAcm5JAxiiiO74FRd1KjVaiiXy60qUPkhobOf4FS25TM4ZXBKRESU\nRgxJKdH8BnfykFupVFCtVlvVK6Zp8qGWKMGScv7GqWpU7TUq21Dz+TwKhULrs0r1mh7CyKAZAKjV\naqjX66wGpLZkEJMMP5TdGjxOvJNt9Hpwqp+zAKYsdjA4da9bcCrhv1wj5e+HwSnZSdqiLlGc8fpK\nfjEkpUxqNputqlHLsjI3hImIohXHqlGgc69RtXpNglO1cq1SqbR+rtrnz7IsPrCS7cCugYGBKUET\nBUeCuXw+3/rf9EFFEmjaVYk7+fXV/yu/PrA7OFX/GcCkoVAMThmc0m78+48en1eSr9FopO7eQr3H\nJ1NKPKerr7L9s1KpoF6vT3pB4w2xO35HRP7EvWrUa69R6SE5MDDQCkbVXomNRqMVHujVa5R+6r0X\n4MCuqOnBqVSAhh2cSmDaLjhVh0WliZfgVG1lwuskEWWZ2+Banq+J/GBISonm5KIp2+krlQr6+/tb\nvUb54OketwOFg/1e0y2JVaPt2PUaHRoamvJr6CGMvu1XVvrttv1SOughOgd2xZNa1dkpOK3X65Om\nwXsJTtXdOhKYyoKK/Pq1Wq3V2zNLFafSU1ZaUcj304vglNVzRJQWDEkpCAxJKbb8BEeWZbVCiWaz\nye30RNRTdlWjg4ODPQ+J1CBCKjrlOugmeJAWJdVqtdVDMp/PO/qzqMGKkOC0Xq+3Qhiv07kpPvRB\nTO1CdIq3dsGputgRRJW4LLj09/ejVCq1jhO7itO0B6dS4auKMjgl6rW+R/rQ90Yf6p+oAwNRfxpK\nKoakFASGpJR4EqTqoUQul0OpVHL8Ik9E6RFVdW7aqkbDmjzeLjiVAEau5Xpw6nQ6N/WWXYjOQUzp\n0mmxw2mVuNqXVtoe2V1T7CpO1cAQyEaP007BqXzf8n2o/U0ZnFIS9T3bB+N9A8ZmA9Ycm+e37wC4\nDcDmXn8yShK5txD5wZCUEk0euicmJiIPJdKOW8KJ7GWharQXgZc6GErId9ttOjev971nN4gpqBCd\nksFNcCrPEIZhtPoxB7FVP2vDoSQMleuktEZwEpym7bugdKl/sg7jvTYBKYCBGwdgwEBtWg3VrdUe\nfzqKipeepBwISX7xCKJEsixr0nT6ZrMZyQAUoiAwgE6mOFWNSiABxK9q1A8JVNxM55atv7wXhEPu\nv9XqrpdU0zRRKpX4fROAycGpLLio1aUSbm7bts1zX+Juwan8M5D+4FT9M3UKTiWoZnBKsbUnYO3Z\n/Vm4jnpoH4H9eZOP2+0pCAxJKbb04EgefiuVCqrVKnK5HEzTRL1ex+DgYISflIiyglWj0bObzq0G\np+VymYOhQqAPYiqVSvxOaQr1WU0WXGQRW/95ct7KAk2z2Zx03spiT5jBqfx3aQoL3Qan8t/U63UG\npxFhONfdzq07o/4IlAC1Wg2maUb9MSjhGJJS7Em1VrVahWVZk4YwNZtNTExMRP0RM4PVjpRVEibK\ndu9isRh51agMMvFTNVqv12GaZiyqRr3y0itRqk05GKozdVGg2WxyEBO1ZVkWarUaKpUKAHRdcFHP\nW3mhVRd+ghjo1ik41bfsq2Fh1oJT+Z71ilO12jRN3wURpRd7klIQGJJSbDUaDezYsaN1sRsYGOh5\ntRbtxu+dsibOVaMSEritGpVp0kD3ECPJvA6GYnC6i12FMYcgkh1ZyJYK42Kx6Pka2a4vcZDnbbfg\nVBZXAExajEp7cCotY7pt1ZfvmlXkRBQ2L8U59XqdPUnJNx5BFFvysDw0NNSxEoHVjZQW3G4VHD/X\nhrRVjerDdbK6TbpbACODoSzLmlRtKt9V2r8vdZt0GiqMKTx2W+rDOlbiGpyq19C0Bqd6xWmj0Wgt\ntpXLZQanRNQTHNxEvcYjiGKrv78fhUKBD1yUejzGoxeXqlEAk7abBlk1yuE6U6kBTKFQANB9MJQa\nwKSB3SCmtFYYkz9xOVacBKfqgkeQwan8kAAVyFZwKvTgVLbsMzilJGOxQvKxJykFgSEpETnCql1K\nozhVjTabTdTrdVaNRsxuMJR8txKkS4CtVpsm7XuWY6VarfJYoY6SMLTLLjjV+xL7rRTXe3NKSOok\nOE1TaAq4D07V/qZxO3aIKD3Yk5SCwJCUEk0esrjyR0ROxalqVIJRP1WjdtVdxWIxdS/lUVHDADU4\n7TQYKq7BqQzXkfDCNE0MDw/zWKEp1AFv6pT6JB0r+oIH4LxS3ElwatentF1wKr+P/Pw4BadBPUMz\nOCWiqMlzPZEfDEmJiCgT5AWtUqnAsiwUCoXEVo0CaAUYrBrtvXaDodTQ2+9k7iDpg5gKhQIHIZIt\nfdFFrpNpOVb8BKdOrtGdglOpLk1CcBoUr8Fp1obosdiDaCov5wVDUgoCQ1IicsQwjNaDPgVP2hnw\nITlYdlWjAwMDsagaVV8InZJKQAl6WQkYH+2C024DZuRYDPp4tKsE5CAmakfdUp/L5TK16NKpxQaD\n0+C1C07Vnq9yrcxycEpE7nG7PQWBISklHsMlIrLTaDSwdevWVFSN6j0Bi8UiKwEToN2AGQnLpU8i\nENxgqLRXAlJw9CDdNM3EbakPQ7sWG+16E4cVnKr/rH6utAan7arzGZwSkVOsJKUgMCQlIqJUUKtG\nq9UqDMOITa9RP1Wjav9IBhjJZxgG8vm8q+2+MmSm03HcaDQmVUxnqRKQ3FGDdMMwIptSnyROehNL\ncOq1N3G74FR+Hwank4NTCaybzWarGpjBKfnBopvkY0hKQWBISkREiWbXa3RwcBCVSqWnD0rqi5u8\ntAVRNcr+kelnt91XDV/K5bJt+NLX19eqBOQgJuomy1vqw9ApxAtqqJucy+rv0Sk4lR0LWQhO9esl\ng1MiYkhKQWBISrHl9EFGtttTuPg9h4vfrzvdeo3WarWefRapGpUXVdlizapR8qpb+CLHvlwzGKZT\nO9xS31sMTnuPwSlROnmp7K3X6ygWiyF9IsoKhqRERJQYcZpQL+GDvHh56SPJqlFyo9lstgIWdcu+\nulVfHwzFICCbZEt9pVJBX18ft9RHKA7BqfwApm7VT+MWYy/BqVwreb0kSq5arYZp06ZF/TEo4RiS\nUmzxAYWIgN0TwsvlsqsJ9WFU5gZVNapOOufUcepEgtFOYZc+GEoNXsrlMizLmtTbVIIX3mfTR+9N\nK9dKipd2wamcu+qih7Rucbvo0Sk4lbYw0jsb2BUuZKXHabvgtFar9Tw45S4iouDU63Xe88g3HkGU\neNym3Bv8nqnX/FSNBvkyo1eNehnCJL+ODEuRsCufzzOooikkxJAqYzdhlwT3uVwOhUIBQPfBUG6m\nclP86Asv7E2bTOq5K9TgVP079lot3tfX1zpeJBQtFAro7+9vLf5ldThU1MEpnwXigX8PyVav19mT\nlHxjSEpEFAMMoXfxWjUahiCrRiWYYtUodSK9aSuVCgDANE0Ui0UEFAJfAAAgAElEQVTfwYTdYCg5\n1yR4aTQarWPc7VZfigYXXtIvyOC02Wy2qoxlcFe7hRe14lT+GZgcnMp1KUvBqVqlz6366cPn8Hjx\n0gqEg5soCAxJKRV4UyNKtrj2Gg2yapT9AKkdvTdtsVgMdWFArQrrFAL46ZFI4dG31HPhJVvcBqeG\nYbQqI50O7nIyHEqGQsn1ICvBqWBwShQ/DEkpCAxJKfH44EGUTKwapSyL29TxTiGA9C3kYKjoSJWx\n/B1wSz2p9OBUHdwl/94wjNb1Rs5dud8GNRxKKk0lQJWQUP3v08JJcFqtVlvfgxqa8ppJFA5ut6cg\nMCQlIke4HZyCkuaqUenvxqpRaidJVcbdhsu02+rrJnihzvTjpVAoRLKQRMmgHi/9/f2tLfVyvOiV\nj+VyGcDU/sRhBqdqNTqD093fhZetxUQ0GStJKQgMSSkVGN4RxZsEK5VKBdVqFblcLvFVo/LnkVVr\nTpGmduwGMSW1yrjdVl+pNu0UvKQtEAmTVBkn/Xih3nDagkHvTwwEP9itXXAqPyQ0lM/N4HTX971j\nx45JFaduwmoi2oWVpBQEvs1RbDl9KODDA6VBWit1LctCpVKZVDU6ffr00F+C9O9T7aEmA2rkhcXN\nZ2k2m60trwBiXQVI0ZMtr+rxUiqVUne8GIaBfD7vKniRAVFp+y780LfUFwqFQAZ3UTrJ4oRUc3tt\nwdBpsFuQwan6cyUkdRKcpvH4V4NTy7KwY8cODA4OotFotK6ddlv1GZyGi9W88cLBTRQVhqRE5Eha\nQzwKXlqrRtWqrlKpxICH2tIHMWXxeLELXtTgtFwuczDU/+GWenJDXXwxDAOmaSKfzwd2vLQb7KYH\np/V6fVLY5yY4tetT2i44lYBWfn7aglMJguT5RP93DE6JnGNISkFgSEqx5uSGz/COKB6iqhrVyctE\ns9nEzp07J73ouQ1H9SpAVnVRO3ZVXVEOYoobp736ZDq0Wm2axiEn6uKLbA/klnrqpNlstrbU93rx\npV1wqp6/lUpl0k4NOX+dfsZOwalUl2YlOBXdglNpy8HglGgXbrenIDAkpVjjtgei+JNgKA5Vo/Ky\nZlkW8vl8q0dipVJxtM2XVaPklt0gpiCrutLM62CoJAen6pZ6y7JS24KBgqHuzGg0Gsjn87FZfHGy\n8FGr1XxVjDM4ncpNcCrXSganlBWsJKUgMCQlIoqBpFVEx6lqtF2vUdM0W59VHSzTbptvvV5HrVZr\n/besGqV29MFdpmmyCjAg7QZD6RO5JQDQq9XiGgDoU8e5pZ46sQvTk9D/Oi7BqfrP8rnUati08RKc\nqotNcT+uKJu8FEvV63UOUSXfeARR4iUtXEoqfs8ETK0aLZVKkVTN6VNhO/UalRcACU2B3S9t6pAU\nYNdLlwQXEq7y5YGEXQuGJAQXSacGp4VCAUDwE7nDwC315FYa+9NGGZzK78PgdBfp9yrPP/LdMDjd\nhe85ycdKUgoCQ1IiIuoozlWjXrbU6ROkTdOEaZowDGNKtRoQr9CFoiFBV7VaZQuGmOg0kVsWc+Q6\noVab9uLvTa4xlUoFALilnrqSynR5wU97mN4tOJXKR7VHsVSOO221Ifdq9ffoFJxKX880B6dy3VQx\nOJ0sC3/GNGNPUgoCQ1IiIrIVx6pReYlxO6EemDpx3K5Cp1O1moQunMadDXZh+vDwcCpfnNPAyWAZ\nv9Vq3ehb6ovFYuKrACk80gZGKqGzfo1Rg1O1XY6cv+pwN689ihmcTtUpOJXrZtaDU0oOVpJSEBiS\nUmw5velyG3hv8HvOhrhUjQKY9GIUZNWom6EXdtVq7aZxq9VqSR0qQ+nc7ppVnarVpEex39DFbrBO\n2qsAyR+9bUehUGDbjja69SgOYrhbt+BUfgDhbNWPY1sfefZRv3e74FT9uQxOKWhe3jsZklIQGJIS\nEcVA1CF0nKpGJcAIu2rUC7fTuPXglOJJr+hi0JVebs9hdZuv+vLP/rTkVrPZbG2p7+/vZ9sOj6IO\nTrM6HEoPTqXFiZPgNI3fB/WGl8FNDEnJL4akREQZFaeqUbWyK6qqUa/sXtg6DZXRp3FTdFjRRUD7\n0EWuSWqP4r6+vlYwwKCLurEb3tWL+1LWxCE4lX8GshGcqn+uTsGp+lynhqZp+z4oHlhJSkFgSEqJ\nF3UFHlHSpK1qVN8ebZpmJH8eVbdt+na9Ed0MpCB/9CEpDLpIZxgG8vk88vl8KzDV+xI3m03s3Llz\n0jnM44iAyYt2lmVxeFcEui1gyuKH9NrUFzDDDE7lv0tbUJj04DSOrQ/IHVkIIfKDISkROcIwOtmk\nYk5eCOJUNSrbX91WjSZpe7TX3oj6Fl/yjoOYyC27SmN1AUZf/CiXyxzulnHsaRxv+gIm0Hnnh34O\nBzUcSn6PRqMxZWBU2u5JfoJTXjuJKAoMSYmIYiCsEDoLVaNJ3R7dqTdivV6ftMXXbnsgOaP3AWRo\nQd3oPY3bVRp3WvywG+6mVquxajxd5O+6Wq3GftGOJvMTnLoZAin/vZBFu3q9jlwuNyk4leekLFac\nSnAsz0AMTrNLzgOiXmNISolnGEZr9ZWIWDWaZN22B+rbfVmpZi9LxwwFQz9mvPY09joYisFp8tgd\nM6xOTwe7ljnqeew1OLU7ZkqlUuu/UatK5d4P7A5O1Xt92o4zu96tDE7JLe56pCAwJKXYY3+YeOHf\nR3zFrWpUHmpZNepPt/6mdtv0sxq4yEtUpVLJ9DFDzvVieFe3oTJB9Eak3uHAt+xRA7x2waksYqoL\nJep5LPcmoP0x026rvvxQt+UzOG20nhObzSaDUyIKDENSii3e2OKFfx/xZFc1Om3atEgq5qRqVB7g\nJRjwWjVar9dhmiYrADVOKtXkeFDDlrRu01enR8sgpoGBgUmBFJFOPWZkUamXL9VqcFooFAAEv8WX\ngqUu3HVqw0DZ0C44tdv9IT8/l8shn8+7avmiDzSSZywnwWkarxVug1N1MBTP1/Tj3y8FgW8QlHgc\nKERp4eY4jlPVqASbat89L1Wj0p8LACsAXeq2TV8PXPRKtSSSQUyVSqW1QFAsFlP5UkjBCGpLfVg6\nbfGVa75UqukLIEk9j5NAXbhj6w7qREI5YPdQplwuB9M0W+dypVLBzp07PbfNsetT2i44lfu+/HwG\np52DU+6Wixf+fVBUGJJSrPHCSFnh5FhXq0abzWYqqkb1CkBW5gSn2zZ9mSabtIEy+lCdYrHIQUzU\nkVw7k9aGwUmlmn4eMzgNhizCSLBSKBRQKpX4nVJH6mJGp0WYoM/jTsGpVJcyON39vcsPPTgFdn1f\nvH4SZRtDUkoFVpL2hlTt8sGht+JaNeplCJP8OnrVKF8+w+dloIwEp1H3RYx7BSDFkz5xPA1tGNqd\nx+qQPPYp9k4P1AuFAhdhqCO5P8n900mP2k7nMYPT8HT63uUaaldxyutncvDviIKQ7CdFIvBiSOmk\nvqg1Gg1WjVIoOg2UUUNJYHJfxF6FBhzeRW7pgUUWJo57WQBRz2OeT1N71HJLPXWjDvAyDMN3oN7t\nPFYXQLzuAHESnKr/LJ/LriozLdTvvVKpoFQqAZg8MEuunwxOibKBISkRUYzoVaPFYjHRVaP6FGDT\nNNk3Mub04NSuL6Kffmrd2AXqDCyoG6lQV7fUR3HtjIt2CyBSbVqr1VAulwFkdzAUK9TJi14O8Oq0\nkNlpASSI4FQC06wHp0KtOJXvXgJrtb8pg1Oi5GNISqnA7fa9wSFZ4VADqHK5nPiqUWD3oAtWjSZf\nt76I6vY0P9t77QJ1tmGgbmQQCgP17gzDQD6fb53HQOcBb3rLjbRQh74BcLQ9mkiuNVEP8OplcKr+\n+ToFp5ZltX7tpAan3d5v1OBUfxZicBoOtnijqDAkpcTjxZOSSq0alYfeoaGhRFeNqtPGs7DNNavU\nlwXTNAFMfUlzWqWmD2JioE7dZHFLfVi6DXgrl8upGQzVywpASgd1In2cq40ZnAbHzfXAS3Aq3zmD\nU6L4YkhKRNRD7XqNVqvVnq+YBlU1ymnjBNi/pOlVavV6vfVSYRgGGo1Ga9BFHF88KV70HrUcqhM8\nJwNl/PZF7DWpdo+6ApCSIw3Vxt2CU2m5YVlWaMGp/ACyuVW/XXBaq9UYnIZAFvSI/GJISonHLeCU\nBFKRE5deo/KQLA9zAFw9WMgLhLwsx7W6gqKlV6mpW6PVY19eGOIetlA09PYdDLl6y+tgqCjPZbuJ\n42zfQd2oC9l9fX2pW/RVg9NCoQBg8mJmp17FToe8dQpOORyKwWmY5BmByC+GpBRrDEDjhX8f7riZ\nUG8YRuuhMQxhVY2ykou6Ubcr1uv1VqAu50G3sEXticjjLDv0hZhCocChbzHitkpNzuOwz2U95OI9\nipyQCea1Wg25XC5TCzH6YibQvVdx0MGp/DPA4FQPrbMcnLrdYSe7BYj8YkhKRBQwVo0S2Q9istuu\n2G0Kd1aGydAu3FKfXN2q1DqFLX7vJ+oCXi6Xw8DAwKRrCpEdvRUDn212setVrD5PBnEuew1O5b9L\n49+Tk3YnWQ9OO5HrP5FfPIoo8VjdSHHgpmo0bOrDFMCqUeotOW6q1Sry+byn4Sj6FG71BU2GQqVl\nmAztrkBk38j06RS2SOW413M5KUN1KF7YisE9taIzquBUD1CDDk7jOkndbXCqhqZZC05ZSUpBYUhK\nRI4xkJ4qjVWj6ssDwwpywq7aOMhp4+1e0NTpsfJ7x6UnInWnHjeWZcE0TYYVKdftXJYX/k7BaRqG\n6lDvqbsbDMOAaZqRPK+lRafgVHaCyAKGPJPqbTeccDIcSg1OLctqBYTqf58mTgfsyXeRleCUPUkp\nKAxJKdYYylEcpbFqVN/iypcHciLKrdHqS4JpmgDseyICwW/tJX/U44ZV6tTphV9tu9FsNlvPher1\nhuczdaJfb7zsbiBnJDiVezLgfhHECS/Bqfrrp/GaweCU2+0pODyKKPEYpFKvqFWj/f39gVaNujmO\n7apG5QHHS9WobJFi1Sg5EefjxklPxHq93vp53KbfO9xST26oL/xSkSaV4n19fbAsC5VKBRMTE5PO\nYwnbeT6THDe1Wg2mafJ6ExGn28XDCk7lh/yegH1wmkbtvvtGo9H6/u2C07gMy3TbAkHOdSK/GJJS\n7MW1RwxlQ1yrRuWBJqiqUW5VpG70QUxJ2eJq1xOx3cuZGpympbIiavrWaG6pJyec9o3Uz2VWj2eb\nXZ/aIFu/UDB6GZyqf/cSktoFp2oBgtuigySRRWJVkoLTTtiTlILCkJSIHMtS1a48ZFcqlcCrRr18\nFlaNUlTUahyvg5jipFNlhTpMRqrW9OCUnNG3uBaLRW6pp67UhUknrV/0RRBgavW4PkxGzmkei+nB\nPrXJ53S7uDqgyG1wqvcp1fup5/P5Sb+n+t8xOI1/cMqepBQUhqQUa04uulkK7ihccasalX5sQVWN\nGobBFwdyJOxBTHGjbtMXDFrc06u4uBhDTsl5Jj3lBgYGPPeW61Y9Xi6XfVeoUTzooToXY9Kl26Km\nGpy6GdqoVqpbloVCoTBpMUbfls/gdBc1OJXCC2lbINfdKINT9iSloPAoIqLMi0PVqIT96qAKP1Wj\n6gtnPp/39cJJ2dFsNltVo1kfqGMXtKhTe+2CFlnIyNr3Zbelnosx1I3d1uihoaHAQwcvFWqyCJLF\n8zkJ1HtVLpfjYkyG2C1qdtoNoi+CyL+XwgG7Zxy94hRgcAr0Njj1UgDFnqQUFL4xU2qwd2n40lS1\nG7eqUXmw27Fjx6TtvW5/Han+A9j7j5xhKwZnOk3t1SdwZ2WQjB6qJ70VA/VGHEJ1t203nFaoUbgk\nVJfeg2GE6pQ83YJT6Vcs7zDyc90cO06CU/Wf5XPJj7Qep16CU/U62u1a6uZay56kFBSGpJR4fFAl\nN/Sq0UKhANM0IzmO1HAF2PXQZlnWlMETnbb12lWNMqggJyRUVysqWP3nTregJY2DZOy21DOoICfi\n3qfWTdCi9ytO60JIHDgd4kWkkmBSBkDlcrnWIqefrfqqdsGpBKYMTneTNmLy7Cnfj5fgtB32JKWg\nMCQlotSLW9Vou16j8vDWaVuvugWwXq+jVqsB2FWJUywWU/vARcFo14qBoXpw1KClUCgAmNzfVK5D\nSeuHKNdRqVRnqE5O6dV/SapU73Y+2/UrTvpCSFzYDWOKaoAmJUu3iuN2/cf1hRC9UMFNcKpe4zoF\np/IukPbgVLbeq7oFp/JznH739XqdrcUoEDyKiCi14lo1Kjf7di9R7bb12m0Z8jrQibJFfdmUIQUM\n1Xun2yAZtR+iWp0Wh229aqjOLfXklF79F1a/0Si061esbtNP4kJIXOgVx7zmkFPq+ef0mqOfz4Dz\nhRAGp/50Ck7lO5+YmHBccZq1StLly5dj6dKl2Lx5M2bOnBn1x0kVhqSUCtIrkw9Q4UpCT9I4Vo1K\nXx6vgaZdBZc8BKgPcfV6nS9lNIkecMVte2tWue2HqAenYdP71KYp4KJwqfcrWexLe/WfGmS0WwiR\nLb+8R7cn96tqtZq4imOKjl07Br+7HPwEp07vk92CU/kBZGurvnz3smNuYGBg0vVUKk5vvPFG/O//\n/i8++tGP4thjj8X8+fMzFZK+9tpruP/++3HAAQdE/VFSiSEpEaVCHKtG5eFGtuu5faBRXxhyuZxt\nwNXupUwCjiwNkaFdGHAlk10/xE4vZXo/xCBwSz15pU8bL5VKmd722G4hpNugt7hUkPeK3uPYNE0M\nDw/zfkVd9bodQ6cK8l4Ep1kdDqX+2eSeYlkWPvOZz2DOnDnYsGEDbrjhBvzxj39Ef38/9tlnH3zw\nwQdYsGABFi5ciA996EMR/wnCccEFF+Bf//Vfcdppp0X9UVLJ6FIVFu+SMUo96bnY7aL//vvvR1Yt\nmCU7duxoVaPFgV3VaKFQiKxqVMIpqRq120bSjTz0ycuTaZowTdPzg4+6BVAe5ABnQ6EoWdQtitLj\nNu0VXFmj9yuWH2p1mizIuPl7VyuOZbgFrwvUjd0Qr0KhkMoX9bCoIYv8yMLipvqsY1lW61knTX9G\nCof67N/f3w/TNGOzQ0YPTtU2W0H2LFaDU/lnVRqC02aziYmJCQwODjr++TfddBOeeeYZ7Lnnnli3\nbh3Wr18P0zSxcOHCVmi6YMEC/MVf/EXInz5c99xzDx588EGsXLkSBx54INavX8/t9t60vWhkd4mX\nUiUON8YsiMt2+zRXjcq26EKhEMhDn16d1mkolBqaZqmSJcnsBjFxi2J6tetX3K06zS5kYcUxeaVX\ncJmmyYpjj7pVkEsfciAdg6HUgKuvry+wZx1KP3UhOJfLxfJZx0nrDVlUknPfS+uNbhWn8s/A5IpT\n+e+SeO3opq+vD8ViEYsXL8bZZ58NYNd3/+qrr2L9+vVYt24dLrvsMqxbtw4DAwM499xz8f3vfz/i\nT93eySefjLfeemvK//6DH/wAP/rRj3Dfffe1/rc4vJunDStJKdbkha/bxXzLli0YHh6O3c0ybXbu\n3AnDMFAqlXr+e8tLmYR6caoa7TSEqZOgq0a9alfJoj+8pfGhKqn0bdGswiFVtwpyCVVZcUxu6AN1\n4lTBlXZqyJLEXSF6OwY5doi60ReCZadDkunBqd2ukCDa6bQbDiXiHJxKoDwwMOD4v7n55puxxx57\n4Atf+ELbn2NZFl555RXs3LkTRx11VBAftac2btyIE088sfW9vP7669hvv/0wPj6OWbNmRfzpEoeV\npJRucalwpOCxajR8TnohcihUPHDSODlhd07LgkylUmndM2WxRybH8lgiO3IfZrV6dOz6Iar3aX1X\nSFzu03Ls1Ot15PN5VquTY+qxk7adDp16Fgc57M3JcChZcJGep2qrsKR9304GNxmGgQMPPLBHnyh4\nRx99NN5+++3WP3O7fTgYkhKRK70Io+2qRqOcUB9W1WicH/g6vZBxKFRv6ZNb437sUHzYHTulUgl9\nfX1TXsg4RIZUdscOB+rEh5OQRc7pXrfTsZs2XiqVeB2hrrJ87MQ5OFV//TjfA2QxJkuycG5EgSEp\nETkWdsVuGqtG0zJMR314k36I6pZeu75pcd/+F3dpOXao95rNZqtnZLtjp90LmTpwolwuw7Istt7I\nELWVh/S/5XUnGZyc0xI+hbEY0utp45QePHbsdQpO9T7kfhZD2gWn8kPdqh/n4NRJJWnavPTSS1F/\nhFRiSEqpwO32yaVXjZqmmYqqUXUgSlq3J3IoVPDUadGyxSyNxw6FQ98WPTAw4Krvn5PWG2ovRDU8\n5TmdbGrPSLbySA+7c1oNTuX5y24xxOnOEL1XLY8dckpflCkWi+xz3EWvFkPUbffA7kFQToLTIEJT\nL+/1WQxJKRwMSYkoElmpGs3SxN92k7ftHtxYmTaZ3SCmLB075F3Y26K79ULUt/9xMSQ51EUZWdBj\nK4/0U4PTQqEAoPNiSLt7tdojO67Txime7IJ1DvLyrttiSBDBqV2f0nbBqVw/5Od7DU7dPkM0Gg0e\nRxQIHkVE5JhhGFMmI7oRx6pReYCQlVnA3baRrFSNesWhUJ3Jd1CtVpHP51mBQ47pizK9GgDnpYpF\nbb3BYzt6ao9sy7K4KEO2iyFqSx0J0iXwkDCEPbLJDbVincF6uKIOTqW6NOjgtBNWklJQGJJSrDl9\nYOd2+3hj1SipulWmpX0olN0QLw5EIafiOGm808uYuogEwPa8pt6IKlin5JH7rdyr1Z6Rav9DWejM\n4iInOae2EWLFenScBKfSfiOJwWkWBzdROBiSElEo1Adq6a2YpqpR9osMTqfKtDQNhWJAQV7pwXqh\nUECxWIz1S2a7nsVqBcvOnTszW0XeS3EM1ikZpBWMDIHTe0a2GyITxmAoSha9nYcsCPM4iJduO77s\nnsHd9i12Epyq/yz/Xv53p886rCSloDAkJaJA2VWNDg0NRVY1Kjd5wF/VqAQUAPtF9kJahkKxHQP5\nkaZgXa9MAyZXkct5woAlGPq1hxXr5IbeM7LdEDivQ2TStDuEJlP7ZFuWhUKhwGfmhNF3fAHO+xb7\nDU7VVly5XG7Ke5z6LKFjSEpBYUhKqcDt9r3R7nu2qxodHh6OpHl2kFWj6lAC9ouMlpuhUPrU7ShC\nAQ5iIj8k3KrVaqmuWFcDFjm37bb+AZ0HyNBu+rWHAQW5oW+L9nLt8VOZxvM6udR3AcMwEr2oR1P5\nCU6dnNf6tUcW9dSKUr3i1LKs1iKqYRjcbk+BYUhKRJ5lpWq0VCrxIS+G4jgUSt/WymCdnLLbUp/F\na4/T81p+Hrfp76IORJFp0Vn/TsgZu6rjoHtGeglYkthWJ4vUlgy89mRLp4FvToNTNRy1u/bI/68u\n1tgFp2+//TZWr16Ns846q1d/fEoxo0v1HUvzKFLy0N/tQW379u3I5/MoFAo9+mTZVKlUUK1WUSgU\nJt3QZLW41+yqRr00/rarGjVNkw95KaAPhZKhXUFu+7MbxGSaJitiyBF9W6tpmqy+6UI/r+VH3Ntv\nBE29d0kFTaFQ4LWHHFEr/4BdVcf5fD6yc6bbec0FkXhR7125XA6FQiGVOx7IH71dlvrOJv8+n897\n7rO+adMmXHrppXj22Wdx9tln44wzzpi064yog7Y3EoakFGtOQ9IdO3agv78fxWKxR58sexqNBnbu\n3IlardZ6GIpyQr3cZGWrhfxww25LdD6f5wtmyunbeb1Wr+iVWwy3yCm7cEsWZsgb9byWH+qCiHpe\nJ/0cVRdmLMtqLcwk/c9FvWFZVmvRO+73rnYLnX19fVPa6sTx86eRvi2aCzPklNynJyYm0Gw2W4sy\ndgsi27dvRy6Xw/Tp021/reeeew4rVqzAu+++i6VLl+Kv//qveQ0gtxiSUjIxJI2W3ms0l8vBsixM\nmzYtks+jr0B6qRoFJvf7Y9UotVvltqtKAzBlEBPDLXJKr9xiuBUuu/MaSO523jQN8qLeUxf2klz5\n121BhMFpOKT3u7Rk4I4ZcspumJdeta4viNx555248MILse+++2LevHmYP38+FixYgFwuh2uuuQaN\nRgOXXHIJRkZGIvyTUcIxJKVksiwL5XKZIWmP2fUaNU2z9XI/PDzcs8/SbDbRbDZRr9d9V43K51cr\nb/iAR3b0lzA5/oQcP0l8waTe45b6eFD7panhady380rVcbVabVVu8dpDTmUh3LLbIWJZlm3f4jid\n23GnhlvSK5sLe+SUvjBcLBZdPfvUajU8/fTTWL9+PVatWoXHH38czz33HA444AAcd9xxWLBgARYu\nXIh58+ahVCqF+UehdGp7IHJwE6UCp9v753RCfa++ZwlG/VaNqr1GJUhnOEHdyNRtAFNetmS1e/v2\n7RweQ23JS7uEE14nRVNwJCDRB01I9YpUicehKs1umI5M+yXqxi7cGhgYSO39SR34JvMJgpy8nTVx\n61dLyaIeP4ZheH73yuVy2Lx5M+6++27MmTMHd999Nw444AA8+eSTWLduHdatW4ebb74ZTz/9NA49\n9FAsXLiw9WPu3LmcVUKesZKUYs1pJenOnTthGAZXkTyQl/hqtdq6kbVbJa7VapiYmAhtu33QVaMc\npENe2E0Zt+tV24uhUJQ83FKffN36FocZrui9shlOkBvq8WMYBlsyKJJaSd5L6qR6tvQgt9TjR3Yi\nehns22w28bvf/Q5XXnkl5s6di4svvhj7779/259fLpfxxBNPtILTdevWYe+998YDDzzg549D6cft\n9pRMbkJSABgYGOjFx0o8u6pRJzeysEJSvWpUKn38Vo1ySyu5EcTxE9RQKEoeDvJKN33qdr1eD7SS\nXG/JIFvqefyQEzx+vNEXO7ManNodP17CLcomfRhcsVj0tGum0Wjg17/+NX7605/i4x//OC644ALM\nmjXL02eSAW9EHXC7PaUbt9s7Iy/x6vaHoaGhyCbU61WjuVwukKrRoaEh3hjJEbstrX6OH33Ln165\nUi6X2w6FSvMLWFrZbann9SedZOHObpt+o9FArVZrndtupsvC3HIAACAASURBVG7L9UcmRbMlA7mh\nTxrn8eOOtNZRvzM5t2WhMy4tOMKgD/Pi8UNuqOG6n+OnWq3i9ttvxy233IJPfepTuPfee7HHHnv4\n+mx8DiM/GJISpZxd1ejQ0JCnFeIgwmi7qlEv2xb1qj9uCSI39CnRpmmG0q+tXQ9EtRpNesapoSn7\npMWb3ZboNPf7o6nahStOzm3DMKa09CiVSjx+yBF9cYaLw8Fye24nsb2OGq7z+CG31HDdz+Lwzp07\nccstt+COO+7A5z73OTzwwAMYGhoK4RMTucOQlFKDlaSTxbFqtNFotLY/eK0aVR9OWTVBbshLjoTr\nUR0/arWp0AdMBL2Vl4KhL86USiX+vVCL03NbyKR6LvCRE3bDdLg40xvdzu1arYZyuQwgvoOh9HCd\nizPkll657jUc3bp1K37605/i3nvvxZe+9CX84Q9/QLFYDOETE3nDkJQSwbKsjjdx3uB3CbJqNAhS\nNdpsNgHsfsh0e0O1q/rjIAtySq/6M00zdi8G3bby2m33S1LVSpIF3ZKBsqWvr691DNXrdeRyOZim\nOSmw2Llz56QeiHKf5LlNwNRhOl4nRVOw9Ps2MHVRRO1LrleT94paYGBZFsN1ck2vPB4eHvZ0/Gze\nvBnXXHMNHnzwQXzta1/DqlWrJp0/RHHBwU0UexMTE12DAOnzNzg42MNPFh92VaNhTFNuNBrYvn07\npk+f3vGzyAOZVI16nVCvBhP5fB6mabJqlBxL2yAvDoXqLU4ZJz/swnXTNG3vhXoPRNl1wUWRbNP7\nRcowJkqOKAdDqYUThmGwap1ck3BdKo+9vlu++eabuPzyy7FhwwZ8+9vfxumnn86FZooDTren5HIS\nkspDZJb6mHidUO9Ho9HAtm3bMGPGjCn/zq5q1Es4yqpR8kNvydApmEg6fSiU/vLFoVDeqOG6VP0x\nfCan7LZEe7mHdVsUidtWXgqOPsyrUCjw7zlF9OBULSpwM/St06+vThqXcJ33MHLCrvLY63vYK6+8\ngksvvRQvvvgiLrzwQnzyk5/kcUhxwpCUkkt6/DAk3UWvGi0UCigUCj256eghqV416nUIE6tGyS+G\n67uowYpekcahUO25qfojsqNeg8IKJvRgpVcVaRQ+fYHPT9UWJU+ne7e+KNLumGDlMfkRZDj6zDPP\nYPny5diyZQsuvvhiHH/88SF8YiLfGJJScjEkjaZq1I6EpNOmTQu8alQC3ywGW+SN2tNPzguG61Pp\nW/04FGo3dUu9YRiZDdfJO73qr5fXoHYVaW6CFYoWr0HUjl01uWVZU+7d8izNymPyIsi2DI8++ihW\nrFgBy7KwbNkyLFq0KIRPTBQYhqSUXE5CUmloPzw83KuP1RNRVo3afRYJSfP5/KTKNDfsJoxLr0gi\nJ+wGMbHixjknwUra+x9ySz35EeeqP1aTJ0MvKo8pfeyqyQG0tuqrbXaIOrEbCOf1GrR69WqsXLkS\nM2bMwLJly3D00UeH8ImJAseQlJIrayFpXKpGhdprVF6+5CFNX9HutPLYbDZRq9UYbJFnEmxVq9VJ\nFVs8hvzLwlCoLPWrpXDoL5VJGYRiNzgGiHbidlbJ7odarcbdD+Sa3X0sn89PGfzGNhzUjnofkwUa\nL++YlmXhv//7v3H55ZfjwAMPxCWXXIKDDz44hE9MFBqGpJRcWQlJ41Y16qTXqLx4tRsa09fX1wp9\n1apRPqyRU3L8VKtVBls9lKahULJAI8EWt7OSW3aVx0ne/SDnt3pu68GK3MN5nvintoZhz2Pyws1A\nOH23CINTAiZXr/vpWdtsNnHvvffimmuuwfz583HRRRdh9uzZIXxiotAxJKXkchKS1mo1TExMYNq0\nab36WIGIc9Uo4L7XqDyYSY82+XXUbUBJqLqh6OmDmJJSsZVm6vmdhG28asUW23qQW1kLtjqd31lp\nwxE0N8EWkZ2gqtednN9JWfgkd4Ia6FWv1/GrX/0K119/Pf7qr/4K559/Pvbee+8QPjFRzzAkpeRK\nY0gax6pReWiSqlEArl4G2/UaNQyj7TagJFWjUfj0CeO9HoJC7sVtKBS31JNfDLZ2s6smB2AbrNBu\nSW3LQPGhV/2FscjXqX8xF0aSTw1H/Qz0qlQq+NnPfoZbb70Vp556Kr75zW9ixowZIXxiop5jSErJ\nlZaQVF7ey+VyKqpGhd0QnXw+3/bX0R/K6vU6gHT1PiR3OIgpPaIaCqVXHnNLPbmlD9KRUILH0GR2\ng2O4jXcXvWKL1evkll2xQS8Xijv1L+bCSDLIDgh51/S6ULxjxw7cfPPN+NWvfoXPf/7z+OpXv4rB\nwcEQPjFRZBiSUnJVKhVYltXxgbter2PHjh2YPn16Dz+ZM2msGgUmD9FRXwa8/Lna9TbVt/Bm8aUr\nzey2Q2f15TrNwhwKpR9DXreRUXapL5SsXnfPycJI2u/h+jHktWKLsiuoYCsMHPyWDI1GA+VyudUe\nxuu75gcffIDrrrsOv/vd73D22WfjrLPOQqFQCOETE0WOISklVxJD0nZVo1E9RKgPOIC/qtFeDNFh\ntWl6cRAT+R0KxWOI/NLbMhQKBVavB8juHm5Z1pQ2HEk+Z3kMkV963+OkHEMcDBUvch3yewy9++67\nuOqqq7Bq1Sp84xvfwOc//3lWwlPaMSSl5EpSSJr2qtFarRbZNkRWmyabug2RW1lJ52QolGEYrZ61\n7PNHXui9ItmWoXfSUo3GnrXkVxqPoXYV5XxOD4e6SGNZlq9j6I033sDll1+Oxx57DN/5znfw6U9/\nOtELWEQuMCSl5HISkjYaDWzbti2SRtKsGo0Gq03jj4OYyA+5ltVqtVYlGgDkcrlEhSoUPXWhj70i\n46FbNVrcBjvqPWujfM6jZFL7r0shRZoX+pwMhorTOZ4E6jsn4C9gf+mll7By5Ups2rQJF110ET7x\niU/w74GyhiEpJZeEdHELSe2qRqMKEe2qRuWhI4lVo16x2jQems1mq0pCzo2kV0lQb+mLNOqQu14P\nhaJk0reyxm2hj6bqFqqoi5+9OsfV/uvse0xe2AXsWV2ksetRnrZWHGFQq4/9BuxPPfUUVqxYga1b\nt+KSSy7BcccdF8InJkoEhqSUXHEKSdXtDTIopFgsxqJq1LKsVsVoEFWj+Xw+8S8CrDbtHfmu7aay\n8vslp9xOGA9zKBQlk76VVcJRHgPJZNe/GIDt4kjQvycDdvJDbTOUy+UYsLfRqRVH1oNTvUWMn3fO\nDRs2YMWKFejv78eyZctw7LHHhvCJiRKFISkll2zV7XRzbDab+OCDD7DHHnuE8hniVDUKYNKDhJ+q\nUTWQyEp/NlabBsuu4i+fz2fyYZa8UQP2ICaMtzvH47iFl4LjNmCnZOo2+M3P0Bj1fmZZFgN28kSd\nVC/Vx3wmci7Mczwp1HDUb/XxqlWrsHLlSuy111747ne/iyOOOCLgT0uUWAxJKbmiCknjWDUqg038\nVo2yT+RurDb1JsltGSgeelXx52QoVFarVNJAAolardY6hrJ6P8sqtb+pnOdueh/q1Vpp7xVJwbOr\nPo5qcGsadethnJbgVF3s81N9bFkW7rvvPlxxxRU47LDDcPHFF+Oggw4K4RMTJRpDUkouGdrRLSTd\nsmULZs6c6fv3i1vVqPpyz6rR3mC1qT27gJ0VEuRWHCr+2m3v0/uiZe0cTwp1ETOOgwUpet0WQOX8\nrtVqHOhFnulTxll93DudFkCTNhgqqNYMzWYTv/nNb/CTn/wECxcuxEUXXYR99903hE9MlAptLwx8\nEqBU8Hvzs6saHRoailXVaC6XC6RqdHBwkFU2XUiFbj6fBzC176FMlcxKtaldwD4wMJDaPy8FT6+y\nifpaZHeOq8GptI/gUKh40adDc7GP2jEMA7lcblLoKee4uqUe2L04Auw6xng8UTdBDtIhbwzDaN2f\nhf68LgtpUQ5/60QNR+Xd08tiX61Ww5133okbb7wRJ554Iu666y7stddeIXxiomxgSEqZZlc1OjAw\nEJuqUXkACKJqlKGWd51etiQ0TVu1qd0gJgbs5Jbdlvo4Xou6vWzVarXMLY7EiV5lUyqVWPFHrqj3\ntEaj0eqfrZ/n7GFMnei9IkulEu8DMdLpeV09/4FoB0OpfWtN0/QcjpbLZdx222342c9+hk9/+tP4\nr//6L0ybNi2ET0yULdxuT7HnZLu9ZVl4//33sccee3R9ULGrGo1yBTiMXqNy02Vvtt5Jy5RttVIL\n4GRo8kYNtdLUs5ZDoXrHrvqY7T3ILX2hRsLRdueovk1f38Ibt0o06o2gekVSPLRruaP3Kg/6HJf3\nT799a7dv346bbroJd911F84880ycc845GBgYCPSzEmUAe5JScjkJSQHgvffe6xiSxr3XqPQZ9VI1\nKlvHAIZacaL3StKrTeO0fZeDmMgvu1Ar7Qs1HAoVvF4N9KJ0C7L3sSxC2wUqSVoEJff0HTVcqEmn\nMAdD6c9G8v7p5XqxZcsW/OQnP8F9992Hr3zlK/iHf/gHmKbp+tchIgAMSSnJ/ISkaa4a1R/cJIzg\nQ3p8dao2DXPlutPn4fAT8ovVx5NxKJQ3cRjoRcmnPhuFVfFnWVbrfm5XVc7zPPn0ij8+G2WPHpzW\n63U0m03HrbX0oV7dqtg7eeedd3DVVVdh9erVOO+88/C5z32OLWeI/GNISsnlJiSdMWMG+vr6Yls1\n2mw2AYBVowRg94uWXqES9rAYu561HH5Cbulb6iWM4HE0WbsXrSRO4A2DVNioC5lprj6mcEQdaqnn\nudzTeZ4ni75w7Kfij9KpWzsOOcdlsQbo3uKjk9dffx2XXnopnnrqKZx//vk49dRTGdYTBYchKSVX\nvV5HrVZzFJIODQ1N2RYTZdWoPHDJyiOrRqmbsKpN9eOIPWvJC7X3MftEepeWHsZesYqdgqBXasVt\n4bjbec52HPHgtm8tkUqtKq/Vaq2CGKk4VfuVO/Xiiy9ixYoVeOONN7B06VKcdNJJPB6JgseQlJKr\nW0gq1UwTExPo6+tDsVhMRdWo3RbWfD7Ph+mM8Vttyq3QFAT9OOJLZPCyMBRKPY4Mw2AVO3miH0dR\nLoi7pbfjqNfrrYnc3KbfW+qk+r6+vkQdRxQf6nEku2oMw5hyrgO7Fkhuv/12zJ49GwsWLMDee+89\n6dfauHEjli9fjomJCVxyySX42Mc+FsUfiSgr2l7s2cyCYq9bnxeprjQMA0NDQ5H0aLGrGvVaHSBV\nWvLnKpVKfGDOMAk/1cbsanVKrVZDuVwGMLnaFECrNUMul+NxRJ7oA714HIVHFtPy+TyAyUOh1KrL\nJA6F0lsz8DgiL/S+taVSKXF9+dqd5+o9XR/ymIYFkjjRj6OBgYHEHUcUPcuyUKlU2h5H/f39k85z\neXbftGkTfvnLX+Lxxx/Hnnvuifnz5+PAAw/E+Pg4Zs2ahX/+53/GvHnzovpjERFYSUoJIC/p0mu0\nWq22QiG1anTLli0YHh7u6fbhIKtGZauPumUsCS+/FD212lS2QQNoVafIj6B7m1I66ccSr0fxkaSh\nUPpEX7ZmIK/kOKrX65NaDqVVp76HSVsgiRN1sSasoV6UfmrI7uc4qtVq+PWvf417770X7777LrZu\n3YoXXngBBx10EBYtWtT6MXfuXE6wJwoHt9tTctXrdUxMTHTtNdqrkFSvGjUMw/PDql6lxWm+5IU+\niEke2PTtu4D/3qaUXtwKnTxxHAoli37VajWWfSIpGbhYM1m7BZKs9DH2Qw/ZuVhDXqghu5/jyLIs\n/P73v8cVV1yBI444AhdffDE+/OEPAwCq1SqeeOIJPPLII60fL774Io466igsXrwYixYtwkknnYT9\n9tsv4D8dUSYxJKXkqtfreP/997s+IH/wwQcYHBwMbctM0FWj1WqVAyvIM7sBOp2qa/z2NqX0Uhdr\ncrkcB8MlnJNhMWEsxtkt1nDRj9ziEB1n2t3Tpd2TnOdZ3aavV7JzUj15FVTI3mg0cPfdd+Paa6/F\nkiVLcMEFF+BDH/pQ1/9ux44dePTRR1uh6RlnnIHTTjvNyx+FiCZjSErJpW637ySMkJRVoxQ3QQ5i\n6hSmsNo03VillS1hDoWSF0i1uoZbWMktffgJn5HcU/sY69v0s7IYqs4ssCyLITt5poajfp6RarUa\nfvGLX+Dmm2/GJz7xCXz729/GzJkzQ/jEROQSBzcRuWFXNSor8m7YVY0ODQ0xiCDX9CAiiMEnas/S\nQqEwpTJFBkhk6QUr7fRpvqZpYmBggH+fKRf0UCi7kH14eJj3NnJN7xM5ODjIkN0jWchXv79Ogx71\nlhxJplYgG4bBSnbyTO6JUoFcKpU8HUcTExO49dZbcfvtt+P000/Hfffdh+Hh4RA+MREFjSEppYZh\nGOhSGd2RVI3Kw6Q8bAJw/fCoV43yYY28sAvZwwwiJPxUG8R3esFitWlyyDWpWq0in89zmm/GtQtT\nZIFEHQCnh6ZyTQJ2bYVmyE5eSMguVVpcQA6HvhgKTO5vKmGQuk0/Sfd1fcJ4EAvIlD3yrFsul9Fs\nNn3d27Zt24YbbrgB99xzD774xS/iwQcfRKlUCuFTE1FY+IZEmRdk1ahakZPP51kRQZ6ovf2iDtm7\nVZtKgMtq0/jRr0ms9qNODMNAPp+fUm0q2/Rl+yqwKzjN5/O8v5Er+jXJT5UWedeuslyCU7v7eq8H\nwHXDCmQKQpDtGd577z385Cc/wQMPPICvfvWreOihhziVniih2JOUYk8ehLq92G/duhWlUqn10Nft\n1wyqalQfVsGJ0OSF20FMcSLnktoHDWC1aVR4TaKgqNV+ck3Sz3cg/KFQlGxqL23ZrcBrUrypz8h6\nf1MnLTnCwkn1FAR9QFyxWPR873rrrbdw5ZVXYnx8HN/61rfwmc98JhHP7kTEwU2UYE5D0m3btrWm\nV3b6tdQQx8+E+qQGWhQvzWZzSh+tpL886lUpUqmtByl8sQkWB+hQENQ2H5ZldR0OF+ZQKEo2u10R\nXDBLLvW+3usFUbVPJAcNkldB9q7dtGkTLr30Ujz77LO44IILcMopp/DaRpQsDEkpufyGpKwapbiR\n41H61qohe1qPJVabhsOuby1fHskL/f7m9eWx04TtKCvQqHf0aj8uIqeT3n5HXyRRF0S93Nvt2jN0\nWrAhakcdWqm2sfLiueeew4oVK/DOO+9g6dKlOOGEE3hMEiUTQ1JKLq8haRhVozJggA/85IUeaEnV\naBbDgm7VpmoFGk0VVKBFpA/1CqMC2S5IASYPheIiSbLJQhir/bKt0yKJ077l+lboNOywoWjog72K\nxaLn+9vjjz+O5cuXo1ar4ZJLLsHo6GjAn5aIeowhKSWX05B0+/btrWESatWorGD7qRpNyzZoioZa\nNdrf3w/TNBlo2WhXbcogZTdZsOGWevJDbxnT60BLXySRH3EeFEP2GGhRN512kuj3dqn24+If+aG+\nw8ngUa/PSmvXrsWKFSswNDSEZcuWYe7cuQF/WiKKCENSSi4nIWmz2cT27dsBYMoLlhvttkF73ZJB\n2WXXt5YDBtxhtekurECmoKgDdIB4BVpqWxwOhYo/dfsqAy1yS7+3q7u+8vk88vl85hdFyT15Z1QX\nkr08K1mWhQcffBCXXXYZZs+ejWXLluHQQw8N4RNTGixfvhxLly7F5s2bMXPmzKg/DjnX9gbD5IcS\nTa9AkYATwJQgpdODlgzPkf/WNE2USiU+nJFrdn1rBwYGeCx5IP2D1dV/tSJFAmggndWm3FJPQdEH\n6JRKpdidJ4ZhIJfLtap+gMlDoSqVCnbu3BlYv0PyRg0hcrkcBgcHWc1OrklwJYuf+Xy+VZDQaDQw\nMTExZZs+q8upHb0P8tDQkOdw9Le//S2uvPJKHHPMMbj++usxZ86cED4xpcVrr72G+++/HwcccEDU\nH4UCxJCUEqfZbLb6HVmWhb6+vimTstUXq3K5PGUbnwQNetVoHF8cKf7sKpD54hgONUgBplabSrVl\nUqtN9WPJNE0eS+SZ2k87idcl6SOez+cBTO13qJ7vHAoVLv1Y8hpCEKmBlmmabY8lvbq8XC7Dsqwp\ni6I8DrPL6bHk5Ne56667cN111+G4447DHXfcgX322SeET0xpc8EFF+Bf//Vfcdppp0X9UShADEkp\n9iSwVKtGu/UatXuxkv+2VqthYmKi9XNzuRwGBgZYoUWu6VtXWYHce2mpNlW31FuWxWOJPLNrz5CW\nY6nd+a6Gpkk435PCbrp4Wo4l6i19sJeTY0lfFAUwZVFUbcuhnvM8RtNNrktOj6V2qtUqbr/9dtxy\nyy341Kc+hXvvvRd77LFHCJ+Y0uiee+7B7Nmz2ac2hRiSUqzJy973vvc9zJs3DyMjI9hvv/08rxpL\ncCIDnuShrVwuT6lGYWhK7eiDmIrFIo+XGElStam+DZpb6smrrPaIVHsYAlPP91qtxqFQLqnDmAzD\ngGmaseldS8miLwAWCgVfLYjaVZfr57u05VDv7zx+k81u0cbrsTQxMYFbbrkFv/zlL/HZz34WDzzw\nAIaGhkL41JR0J598Mt56660p//sPfvAD/OhHP8J9993X+t+6zPqhBOHgJoo1uSGuWbMGa9aswerV\nq/Hmm2/iwAMPxOjoKEZHR3HUUUe1Hay0detW/PznP8chhxyCkZGR1oN+u209Uo0i/5cPWST0h7Ne\nT4OmYLWbttuL6jN1S71sXTVNM1HboCk+1EUbv1N800rdTSLnPcChUDq7RRtW5ZEX6k4bwzB6umij\nn++NRsN2YdQwDB7bCaA+f0vQ7nXRZuvWrbj++uvxH//xHzjrrLNw9tlno1gshvCpKe02btyIE088\nEQMDAwCA119/Hfvttx/Gx8cxa9asiD8dOcTp9pQezWYTL7zwAsbGxjA2NoannnoKg4ODWLRoEZYs\nWYJFixbhueeeww033IB77rkHxx13HJYuXYqFCxe6uqHqvc/Ulypu6ckOu0FMrKhJH70aRYZJBFlt\nqlZnAWgF7TyWyC15aZTtply0cU/tXS7nfVaHQknQXq1WWxOhGbSTF5ZloVKpTNkdEbV2C6NcKIkv\nvaLdT9D+5z//GVdffTUefPBBfO1rX8OZZ57ZqkYmCsKBBx6I9evXc7p9sjAkpfSyLAvvv/8+Hnzw\nQdxwww146KGHUCqV8PGPfxzHH388TjjhBBxwwAGBvDyqoan8iMOWXQqW3fAcVvplT1DVpnp1lmma\nfBkjT/Sg3U9FDU2mL4y2qz5Lyz1e7xHJoJ38aDabqFQqialotyzL9h6vLpSwGCIaQbaOefPNN3HF\nFVdg/fr1+Md//EecfvrpsT4uKbkOOuggrFu3jiFpsjAkpfTauHEjrr32Wvz85z/HX/7lX+Lcc8/F\niSeeiMcffxyrV6/G2NgYNm3ahH333Rejo6MYGRnBvHnzYJqm79/b7gFLHSyRpUqUNLAbxMRKPxJu\nqk31AIJb6skPboOOhtqGp9dtOcJiNySO9znySp0uLlXISQ3a1Xu8nPfqPZ79jMOlhqN+q5BfffVV\nXHrppXjhhRdw4YUX4pOf/CT/zohIx5CU0qVcLuPOO+/Etddei5dffhlf/vKX8ZWvfAVz5syx/fmW\nZWHTpk2tLfqPPfYY8vk8FixY0ApOZ86c6fsG2u4BS32hYgVZ/KhbDdUKCP49UTf6Qkm9XodhGLAs\nqzVQJskvjRQt2VLP3rXxoC+U6DtK4hyiZHWwF4VDnS5umiYKhUIqjyUn/YzTVGEeBXUR0G8V8rPP\nPovly5fjvffew8UXX4zjjz8+lcclEQWCISmlR7VaxcEHH4yjjjoK5557Lk455RTXfWUsy8L27dsx\nPj6OVatW4eGHH8b777+Pj3zkI63Q9LDDDgtsi776cCXbeSQ4lZcU3sR7S62m4SAm8ku2GkqlX39/\nf+vlKs1bdil4dhN8WekXX3EfCqVvg5Z2H0Ru6QN0slqFrC+UyOJokivMoxBki4Y//vGPWL58OSzL\nwrJly7Bo0aKAPy0RpRBDUkqXP//5z9hzzz0D/TUbjQaefPLJVrXp888/j7322gsjIyMYGRnBggUL\nUCqVAqk21UNTgAOhekUfxMRqGvJKH57TrmpU37Krv1CxLQcBrPRLkzgMhUrTNmiKVpADdNKoXYW5\nnPPq4ii/s8nhqN9r05o1a7By5UpMnz4dy5Ytw9FHHx3wpyWiFGNISuSWZVl46623Wn1N169fj2az\niXnz5mF0dBRLlizBPvvsE0hoqoYoap9DNTTly413dmEWt62SV3rvWrfDczr1PeM5nz3qkDhW+qVT\nr4ZCsQqZgmTXI5KL+M7oFebtzvks7SRTF2787N6yLAv/8z//g8suuwwf/vCHcckll+CQQw4J4RMT\nUcoxJCXyy7IslMtlrFu3DmNjY1izZg3eeustHHjggRgdHcXo6CiOPPLIQF5u7SrPuCLtHgcxUZDU\nMCvoF8ZO5zyrTdOHk8UpyKFQaqUf4H7hhkgVZI9I2q3dOW8XnKZJo9FAuVz23b+22WziP//zP3H1\n1Vdj3rx5WLp0KWbPnh3CJyaijGBIShSGZrOJF154AatWrcLY2BieeuopDA0NYfHixRgdHcWiRYsw\nPDwc2EAotdoUSP+DlVcSPshWHqka5fdDbulVyL0Ks1htmk4Ms6gdL0Oh1DCLlX7kl7oQyBYN4ZOd\nZJ1acyS5BZc63MtPVXu9XsevfvUrXH/99Tj++ONx/vnnY9asWSF8YiLKGIakRL1gWRbef/99rFmz\nBqtWrcL4+DjK5TKOPvpojIyMYHR0FHPmzAl0IJT6YKUPisjSwy0HMVGQ/G6pD+szsdo0mfQwS7bU\n8++KOmk3FErua41GA7lcDsVikZV+5Jk+qZ7PTtHptEDabrEkTvThXn6enSqVCn7+85/j1ltvxSmn\nnIJvfvObmDFjRgifmogyiiEpUVRqtRoeffRRjI2NYfXq1di0aRP2228/jI6OYmRkBB/96Edhmqbv\n36fdQKi0D4dh+EBBsusPGdcqDlabxp9a1S7hA8Msb/0pdwAAIABJREFU8kLu8bJtVY6jKIZCUfKx\nf21ydBr4qgenUX7Ger2OcrkMwN/C8s6dO3HzzTfjzjvvxBlnnIFzzz0Xg4ODQX9kIiKGpERxYVkW\nXn31VYyNjWFsbAyPPfYYTNPEwoULMTIygpGREcycOTOwLfqdApSkhokcxERBimpLfRhYbRo9u/Ah\nn88n8nii6OmVWXpv7V4NhaJ0YMuPdNBbc9TrdRiG4amnsR/q8WQYBgqFgud3iw8++ADXXXcdfvvb\n3+Lss8/Gl770JRQKhRA+NRERAIakRPFlWRa2bduG8fFxrFq1Cg8//DC2bNmCww8/vLVF/9BDDw3k\nBUcNUOT/JmkgVLPZbG2pB/hwT/6oW+oNw4Bpmqk7nlht2jvqJOi+vr5UHk/UO/rx5CZ86DQgRj3v\neWxmh5/jieKvXU/jvr6+Kff6oIZNqseTtPzw8mtv3rwZV111FR566CF8/etfx9///d8HMgSXiKgL\nhqRESdJoNPDkk09i1apVWL16NV544QXstdderUrTBQsWoFgshjoQKk4vUlLlx0FMFATZUl+tVlvH\nU5YeyFltGiy7Fg1ZOp4oWHbDmPweT16GQlE6hHE8UTLoPY2DWCRVw1G/x9Of/vQnXHbZZXjsscfw\nne98B5/+9Ke5YEtEvcSQlCjJLMvCW2+91dqiv379egDAvHnzMDIygiVLlmCfffYJ5OVG37anvkj1\nctuePoiJW1bJD30LdJK31AeN1abuycsnh51QUOR4qtfrPZks3m4olD4AkqFpMjWbzVY/5Fwuh0Kh\nwJZEZLtYAmDKc75+3qthu9/j6eWXX8bKlSvxyiuv4KKLLsLf/M3f8DpDRFFgSEqUJpZlYWJiAuvW\nrcPY2BjWrFmDt99+GwcddFArND3yyCMDeSCWFyk1ODUMI7SqM7Uqi4OYyC9p0cAt0O7Y9TtjtenU\nfn56f0giN+z6IRcKhciOJ/W811vyZPm8T5Jeh+2UbJZl2bbnkPO+r6+vdT2Q48nru8VTTz2FFStW\nYOvWrfinf/onfPzjHw/4T0NE5ApDUqK0azabeP7551tb9J966ikMDw9j8eLFGB0dxaJFizA0NBTa\nQCi14sxtqGk3iIkP9uSHOlXc74M9sdpU37LKxRvyIynDczqd9xwKFR96ZTsn1ZMf6s4bKYywLMu2\nytzJMfboo4/i//2//4f+/n4sW7YMCxYs6MGfgoioK4akRFljWRbee+89rFmzBmNjYxgfH0e5XMYx\nxxyDxYsXY8mSJZgzZ05gW/Ttqk/kBardw5QaPLDKj/zilvreykLVmRq2y/HEsJ28SkPYzqFQ8aHe\n8yzLim3YTsmhViKrz1Bqew45/wHg8ssvR7PZxMKFC7Fw4ULMmjWr9WuNjY1h5cqV2HPPPbFs2TIc\neeSRUf2xiIjsMCQlIqBWq2HDhg2tLfqbNm3C7NmzMTo6ipGREcydOxemafr+fdo9TKkvT/V6PZDt\nO0R62M6pvdHQB8EltdqUYTsFTR/ulaZ7Xq+natPkSmTDMHjPI9/UylGnbT+azSbuv/9+/OEPf8D6\n9evx2GOPYc8998Thhx+OF154AUcddRR++MMfMhwlorhiSEpEU1mWhVdffbW1Rf+xxx5DoVDAggUL\nWsHpHnvsEdgWfanIEkkLTyheuKU+/pJUbSpTe6vVKgzDYGU7+aYHD1kJ2zkUKhyWZaFSqUyaVM+q\nXfIqyDYNzWYT99xzD372s59h5syZ6Ovrw5NPPomnn34aRx55JBYvXozFixdjZGQEH/nIRzJxHSSi\n2GNISkTdWZaFbdu2Ye3atRgbG8PDDz+MLVu24IgjjsDIyAhGR0dxyCGHuHq4qdfrqNVqUwYxyb+z\nGwyj9jnjwz+ppIKmWq2i2Wy2thfygTsZ4lhtqk+Bli31vPaQF3olMvtD7pKkBZO44aR6ClKQbRrq\n9TruuOMO3HjjjTjhhBPwne98B3vttVfr309MTODRRx/F+Pg41q5di/HxcWzevBkLFy7EyMgITjrp\nJJxwwglB/vGIiJxiSEpE3jQaDWzcuLFVbfrCCy9g7733boWmxx57LIrF4qSHq1qtht/85je47rrr\ncOaZZ+KMM87oWkGjhyd65YkEKHyByiZuqU+vTuFJWAsmegUNh8WRX3olMq9RnXEoVHecVE9BCnJg\nXKVSwW233YbbbrsNp512Gs477zxMnz7d0X+7efNmjI+PY3x8HNOnT8f555/v+vcnIgoAQ1IiCoZl\nWXjzzTcxNjaG1atXY/369QCA+fPn47DDDsNLL72E22+/HXPmzME555yD008/HYVCwdPvpb9ANRqN\nKdv1+MKQbvV6vdXLj4NzsqFdtalaaeo1fNJfEuWYYpBFXunDmCQcJfc4FGqXrLZpoHAE2cN2x44d\nuPHGG3HXXXfhzDPPxDnnnIOBgYEQPjURUegYkhJROKRx+7/8y7/g4YcfxoIFC1AqlbDXXnthZGQE\nS5YswRFHHBFIsNVuIJS8PHG7XjqoW+oty2KQRb6rTdMwVZziRa/y4wJO8LI0FIptGihoUt1eqVR8\n97DdsmULrr32Wvz+97/Hl7/8ZZx11lmBDHolIooQQ1IiCtbWrVtx22234eqrr0az2cQ3vvENfPGL\nX8T06dPRbDbx3HPPtbboP/300xgeHsbixYuxZMkSLFy4EENDQ4ENhLLbrqcGp3zJSAYGWeSU02pT\ntZcfh3uRX3qbBlb59Z6ToVBJ2qYf5BZoIsB+wJfX6vZ33nkHV111FcbGxnDeeefhjDPOYKU8EaUF\nQ1IiCsbGjRtx9dVX4xe/+AVOPPFEnHfeeTj++OM7PtBbloX33nsPq1evxtjYGMbHx1GpVDB37txW\ncLr//vsH8lKgbtfrVX9D8k5eeKvVKiuyyBd1waRer6PZbAIA+vr6kM/nWwO+eO6TWwyy4i2JQ6HU\nKj/22aYgqAvNfgd8vfHGG7j00kuxceNGnH/++fjbv/3bxCw8EBE5xJCUiPxrNBoYHR3FKaecgnPO\nOQf77ruv51+rWq1iw4YNWL16NVavXo3XXnsN+++/f2sg1Ny5c5HP531/5k4DobLU4yxu2BuSgqYP\nzsnn8+jv759UdRZUb1PKBgZZyRTnoVDsYUtBs9sx4fXYfvHFF7Fy5Uq88cYbuOiii3DSSSfxekdE\nacWQlIjizbIsvPLKKxgbG8PY2Bgef/xxFAoFLFy4EKOjoxgZGcGMGTMCeVjTt+mqA6E4UTdc3FJP\nQVNfELv1XfPb25SyQT2m/FZkUTzIrgX13g/0bsFUD7K4Y4L80vsi+wlHn3zySSxfvhw7d+7EJZdc\ngo997GMBf1oiothhSEpEyWJZFrZt24aHH34YY2NjePjhh7F161YcccQRrS36Bx98cCBhpt3Lk2EY\nsd6qlyR6Hz++IJJfdseUlxdEp71Nee5nQ71en9T6w0/oQPHWq6FQapDFHrYUhCCPqXXr1mHFihXI\n5/P47ne/i/nz5wf8aYmIYoshKRElX71ex8aNG1vVpi+99BL23nvv1hb9Y489FoVCIbSBUAxO3OGW\negqaHFPVahWWZYVyTLHaNFs4VZxEUEOh9EUcHlMUBLlO+T2mLMvCQw89hEsvvRT77LMPli1bhsMP\nPzyET0xEFGsMSYkofSzLwp/+9KfWQKgNGzYAAObPn4/R0VGMjo5i1qxZgW3RtwtOJDSR0JQvQe62\nPxM5obZp6HVvSLu+xpZlcdEk4fQetqZpchgTTeFmKJS+iMMBX+SXBO7lctn3Io5lWfj973+PK6+8\nEocffjguvvhifPjDHw7+Q1Piff/738dvfvMbGIaBPffcEzfffDP233//qD8WUdAYkhJR+lmWhYmJ\nCYyPj2P16tVYs2YN3nnnHRxyyCEYGRnBkiVLcPjhhweyzVutOJEXJyC7A6GC2v5MpJJjSh1IEYc2\nDXqlOatNk8NucE6WrtXkT7udJhKS9vX1cdcE+aZWuPsN3BuNBu655x5ce+21GBkZwYUXXogPfehD\nIXxqSott27ZheHgYAHDFFVfgsccew/XXXx/xpyIKHENSIsqmZrOJZ599trVF/5lnnsG0adNafU0X\nLlyIwcHBQLboy0OtvDzJNF29v1maqNVYAFg5Q77JeVStVtFoNBLRx8+u2hSYvE2X1abRUgN3Oabi\nELhTclmWhUqlgkql0lokkQVDILuLpuSd3qaoWCx6vnfUajX88pe/xE033YSTTz4Z3/72t7HnnnsG\n/ZEp5X70ox/hgw8+wI9//OOoPwpR0BiSEhEBux5A//znP7e26D/yyCOoVCqYO3duq9p09uzZgbzM\nqKGpBCdpqTZrNBqoVqvcUk+BSVvgzmrT6OkV7kkI3Cn+1JYyuVxuSoW7vmga1lAoSg81HDUMw1dL\nmXK5jH/7t3/D7bffjtNPPx1f//rXMW3atBA+NaXZ9773Pdx6660YGBjAww8/jBkzZkT9kYiCxpCU\niKidSqWCDRs2YPXq1Vi9ejVef/11zJkzp1VteswxxyCfz/v+fbpVm8nLU1xfmpJY4Ufxl5Uett2G\nwsT9/E8SvRor6YE7xYM6VdxtS5mghkJRusjiYKVSad3/crmcp19r+/btuOGGG3D33XfjC1/4Ar7y\nla+gVCoF/IkpLU4++WS89dZbU/73H/7whzj11FNb//zjH/8Yzz77LG666aZefjyiXmBISkTkVLPZ\nxCuvvNLaov/EE0+gUChg4cKFWLJkCRYvXowZM2YEOhBKrTjRt+hG/dKUtgo/igcJ3L0EDmnRrtqU\n1WbeqIFDrwd8UXqpU8VN00ShUAh1IKTdUChKF2nVIL2Ri8Wi5/Yf7733Hq699lo88MADOOecc/CF\nL3wBpmkG/IkpqzZt2oRPfepT2LhxY9QfhShoDEmJiLyyLAtbt27F2rVrsWrVKqxduxZbt27FEUcc\n0dqif9BBBwUS8LQbCCWhSS9fmtQt9blcrtXDjy9s5JU+/ZkDTiZjtak33bY/E7mlD87pxbWq3VAo\n/fzP2mJSmqiD4/xeq95++21ceeWVWLt2Lb75zW/is5/9LK97FIjnn38ehx56KIBdg5vGx8dx6623\nRvypiALHkJSIKEj1eh1PPPFEq9r05ZdfxqxZszAyMoLR0VHMnz8/kGqTTi9NanAa1Isbt9RTGNQX\nQ1b4ucNq0/b8bH8mshO3Vg2ycKKe/wCHQiWNupDj91r12muvYeXKlXjmmWdwwQUX4NRTT+XfPwXq\nM5/5DJ599ln09/fj4IMPxjXXXINZs2ZF/bGIgsaQlIgoTJZl4Y033mgNhHr00UdhGAbmz5+P0dFR\njI6OYu+99w58IJS+Rc/rQBh1S71hGDBNk1vqyTepRq5Wq60XQ1a6+JP1alO1wq/ZbKJQKLAamXyz\n6w0Zx/OIQ6GSJciFnOeffx4rVqzA22+/jaVLl+KEE07g3zERkXcMSYmIesmyLOzcuROPPPIIxsbG\nsGbNGrz77rs45JBDWqHp4YcfHkhg1GkgVLdKE26pp6CxGrn3slBtGrcKP0qHILc/R4VDoeJHDUf9\n3gOfeOIJLF++HJVKBcuWLcPo6GjAn5aIKJMYkhIRRa3ZbOLZZ5/FqlWrMDY2hmeeeQbTp09v9TVd\nsGABBgcHAxsIoVeaqC9LAFCtVtFsNhliUSA44Cs+0lRtqoZYca7wo2RRq9xlGFOa7oEcChUNdciX\n3yr38fFxrFixAgMDA1i2bBk++tGPBvxpiYgyjSEpEVHcWJaFzZs3t7boP/LII6jVapg7d26rt+ns\n2bMD26Jfq9VQq9VagYlhGJEMhKJ0YYiVDEmrNmWrBgqDPqk+KwuEHAoVniBbgFiWhQcffBCXXXYZ\n9ttvPyxbtgyHHXZYCJ+aiCjzGJISESVBpVLBhg0bWlv0X3/9dcyZM6cVmh5zzDHI5/Oufk3Z9iUD\nA2RLvd0LkxqYcLAOdSJb6qXXmhxXlAxxrDaVz5TFEIvCwz629jgUyh/1uLIsy9fuCcuy8Lvf/Q5X\nXnkljj76aFx88cWYM2dOCJ+aiIj+D0NSIqIkajabePnllzE2NoaxsTFs3LgRxWIRCxcuxJIlS7B4\n8WJMnz59ykN5rVbDPffcgxtuuAFXXXUV9t13365hQ7vteWq1qWEYfGHKMKlIllYNDBvSJapqU/W4\nsiyrFY7yuCI/2MfWHQ6FckY9rgzDQKFQ8Lyo3Gg08O///u+47rrr8LGPfQwXXngh9tlnnxA+NRER\naRiSEhGlgWVZ+OCDD7B27VqsWrUKa9euxbZt23DkkUdiZGQEH/nIR3D//ffjpptuwv77749zzz0X\nf/d3fwfTND39XnpoCrDKJIvUyc99fX2+XgopOcKuNuVxRWHgcRUcu2uAZVmTngGysk0/yOOqWq3i\n9ttvxy233IJPfvKT+Na3voWZM2eG8KmJiKgNhqRERGlVr9dxxx134PLLL8ejjz6K0dFRzJo1C/Pn\nz8fI/2fvzuOiqvf/gb9mmIVFUEjEPcgF1xRZZibLJa9ldt3SyrJyzW7ZNbumSXXv7WvddlBLLdOy\nrpZLmaYtVlbXLjNsboR7qZggKCICisx2Pr8/+p1zBxQ15sCwvJ6PR48eOMB8Bo+j85r3YjIhJiYG\nRqPR6xeIVatMXC6XMtOsapUJNQ7yXEin09lgNz+TutSoNpUkSRkBotPpYDAYoNPp6vBRUGN0ufnI\nvK7U19SWQnmGo95eVxcvXsSHH36IdevWYdy4cfjLX/6C4OBglU9MRETXgCEpEVFj43Q6sWHDBrz1\n1ls4ceIEZsyYgWnTpiEsLAx5eXmwWq2w2WzYvXs3tFotYmJiYDabYTKZEB4ertpCKM+wxOVyKS+W\nPBdBNJYXS02B/HvqcDg4F5Ku6koV51WrTeV5o/Ic28a2UZx8o2rozjdz6ta1LoVqaON6hBCw2+1w\nOBxeX1elpaVYsWIFtmzZgokTJ2LKlCnw9/dX+cRERPQHMCQlImosTp06hWXLlmHZsmXo2rUr/vrX\nv2LkyJHVVjYIIVBeXo7MzEykpKQgNTUVRUVF6Ny5M8xmM8xmM6Kjo1V5USm/WPKsNgV8uwyGrg3n\n95FaPJ8DPBfCAKgUjvLaIm8wdK+/GvJSKDVD96KiIrz99tv48ccf8cgjj2DChAl/ePkmERHVCoak\nRESNQV5eHnr37o27774bjz/+OHr37l2j7yNJEg4ePIiUlBTYbDYcPHgQLVq0gMlkgtlsRlxcHAID\nA1V5AXO59lzPWWZyax75xuVaVOvri1dqODxDdyGEErhXDUz45gn9EXL4Zrfb4Xa7uTyugWgIS6E8\nw1FvQ/f8/HwsXrwYmZmZmDlzJsaOHcvqZiKi+oUhKRFRY1FWVqb6DCshBM6cOaO06GdmZsLpdKJP\nnz5KcNquXTvVWvQv154rv1BqbPPM6quqVVgGg4Ev4shr1xK6X0tgIi9E4fMAAf8bAyKH7qx0b/jq\ny1Ioz78LvR0vc/z4cSxcuBC//PILZs+ejeHDh/MaJSKqnxiSEhHRH1NRUYFdu3bBarUiNTUVeXl5\n6Nixo9Ki36tXL1Xaxq40z6xqYELe8QwaJEliFRapxtslX1eabVrf23Op9nhWJGs0Gm6qb+TqcimU\n2+1GRUWFMnvbmwWXhw4dQnJyMs6cOYO5c+di0KBBvEaJiOo3hqREROQdSZJw7NgxpUU/OzsbAQEB\niI+Ph9lsRkJCApo3b676QqiqL5S4EOqP89zOq9VqGTSQKqq2Pqu55Ku6atOqozpYbdo4XW6jOEPy\npqc2lkLJbxSqMa5hz549SEpKgiRJSExMREJCQo2+DxER1TmGpEREpC4hBEpKSpCWlgar1Yr09HSc\nP38ePXr0UFr0o6KiVAtMqlsIxSqz6lWt7jMYDNUu+CK6VlVbn+VwtLb//LHatPHjpnq6mposhVJ7\nXENaWhqSk5MREhKCxMTEGs+HJyIin2FISnVvypQp+PLLL9GqVStkZ2cDAM6ePYt7770Xx48fR2Rk\nJNavX48WLVr4+KREpBaXy4Wff/5ZqTY9duwYWrduDbPZDJPJhJiYGBiNRlXu63IbtKtWlzTFhVC1\nWd1HTVt9q0hmtWnjwU31VFNXmnEsh6VOpxMA4O/vX+NwVAiBH374AYsWLUJkZCTmzZuHzp07q/1w\niIiobjAkpbr33//+F82aNcNDDz2khKRz585Fy5YtMXfuXLz66qsoLi7GK6+84uOTElFtEUIgNzdX\nWQi1e/du+Pn5oV+/fkq1acuWLVVdCOX5Qkmj0dTKLLP6yHN2HwAuNiHVXG4ZU32tSGa1acPi2frM\nN3RILZ7PWbKaLoWSJAlfffUVlixZgj59+mDOnDno0KFDbR6fiIhqH0NS8o2cnByMGDFCCUm7deuG\n7du3IyIiAgUFBRg0aBAOHjzo41MSUV0RQqC8vBwZGRnKQqiioiJ06dJFqTaNjo5Wpb2yullmni+S\nGsNczqoBltxS39AfF/leY6juY7Vp/cMFclRbqla7+/v7K2+KXG4p1MWLFzFv3jzEx8cjPj4effr0\nUbpdXC4XNmzYgBUrVmDAgAF48skn0apVKx8/QiIiUglDUvKNqiFpaGgoiouLAfz+D5mwsDDlYyJq\nmiRJwoEDB5QW/UOHDiE0NFSpNI2NjUVgYKAqL6Cr25wrB6cNKSyRAyyn06lUYHF2H3lLDrAcDkej\nre5jtalvsNqdasvlFn1drdpdCIGysjJ88sknyMjIwM6dO3H8+HH06tULbdu2xd69ezFy5Eg899xz\nCA0NraNHQkREdYQhKfnGlUJSAAgLC8PZs2d9dTwiqoeEECgsLFRa9Hfs2AGn04m+ffsiISEBFosF\nbdu2VbVFv6GEJZerwNLr9Y0qwCLfaMoBFqtNa1d9m2VLjYdnJ4W3i77Ky8uxYsUK/PTTTwgKCkJ5\neTl27NgBPz8/pdPFbDYjLi4OQUFBKj8SIiKqYwxJyTcu127/n//8B61bt0Z+fj4GDx7MdnsiuqqK\nigrs3LkTNpsNNpsNJ0+exPXXXw+z2Qyz2YxevXqpMiOxaljicrkgSdIloWldh5JVQwaDwdBkAiyq\nXUII2O12jmuooqG9gVIfNaRZttSwSJKkdFJ4G46WlJRg+fLl+PLLLzF58mRMnjxZabkXQuD48eNI\nS0tDWloa0tPT8fPPPysjgsxmM2699VZ07NhRzYdHRES1jyEp+UbVkHTu3Lm47rrr8PTTT+OVV17B\nuXPnuLiJiP4wSZJw9OhRpUV/7969CAwMRHx8PMxmMxISEhASEqJatalnhZnL5VK25sphSW0thHK7\n3XA4HMoLQTnAIvKWmiFDU3ClN1BYbVqZ57Wl1+s5CoRUU/Xa8mZO8pkzZ7B06VJs374djz76KO6/\n//5r+vvVbrcjKytLCU6HDRuGhx56qEZnICIin2FISnXvvvvuw/bt23HmzBlERERg/vz5GDVqFO65\n5x789ttviIyMxPr169GiRQtfH5WIGjghBEpKSpCamgqr1Yr09HRcuHABPXv2VFr0IyMjVakAlRdC\neYYlACoFJd5UmMkVbNz4TLWB28TVI/9Z9XwTBWi61aaei754bZGa1Ly28vPzsWjRIuzZswdPPPEE\nxowZw+uUiKjpYUhKRERNi8vlQlZWFqxWK6xWK44fP47WrVsrs8X69u2rtNR5S14I5RmWVK0wu9qL\nsKozIeUXgk0lYKHaw23idUN+A8Wz6vxy1aaNKZCp+qYOry1SU9U3dYxGY42vrWPHjmHhwoU4duwY\nZs+ejWHDhvE6JSJquhiSEhFR0yaEQG5urhKa7t69GzqdDrGxscpChuuuu65WF0LJ1WVyUKLRaC6Z\n28eZkKQWeZatw+GARqPhwhwfaKzVpp7BuxCiSS36otqldvB+4MABJCUloaSkBE8//TQGDBig8omJ\niKgBYkhKRETkSQiBCxcuICMjA1arFampqTh79iy6du2qhKbR0dGqtuh7hiWSJEGj0UAIocyE5LxR\nUsPlFuY0xCCuMbpatannnOP6iME71Ra1g/fdu3cjKSkJGo0GiYmJiIuLU/nERETUgDEkJSIiuhq3\n240DBw4o1aaHDx9GWFgYTCYTTCYT4uLiEBAQ4NW8Uc/2QbmiVA5M6mohFDVOnnP7uDCn4aiu2tSz\n0tTXIbcQAna7nZvqSXVVR814G45arVYsWLAAYWFhSExMRM+ePdU8LhERNQ4MSYmIiP4oIQQKCwuV\n0HTHjh1wu93o06cPTCYTLBYL2rRpc9UXc6WlpTh69Cg6deoEjUYDg8FwyYvAKy2EashtuVS7uOir\n8alP1aae28TlincG76QGz3DU26pkIQS2bduGN998E506dcK8efNwww031MKpiYiokWBISkREpIaK\nigrs2LEDNpsNNpsN+fn5iIyMVELTnj17KhVWR48exdKlS7F27Vo88MADePHFF/9Q0OkZmlZdCFXf\n23KpdqldfUX1W11Xm1atSjYajXyuIVXIIxvsdrvX40AkScKWLVvw9ttvIzY2Fk899RTatWtXC6cm\nIqJGhiEpERFRbZAkCUeOHFGqTffu3QuHwwG9Xo/Dhw9j/PjxmDFjBqKiory+r8sFJRqN5pLN2QzK\nGi/PgEGr1XImZBNVW9WmVbeJsyqZ1KLmyAaXy4VPPvkE7733HgYPHoxZs2YhPDxc5RMTEVEjxpCU\niIioNjkcDqxfvx4LFy5ESUkJ7rjjDjRr1gyZmZm4cOECevXqhYSEBFgsFlx//fW1uhDKs7qMAVrj\nwLZnupqaVptWXZgjh6N83iA1eC6S8/a5y26346OPPsLq1asxcuRIzJgxA82bN1f5xNTYzJkzB198\n8QUMBgM6deqElStX8rohIoakREREtaGwsBDLli3D0qVL0bNnT8yaNQt33HFHpRDU6XRiz549sNls\nsFqtOH78ONq2bQuTyQSz2Yw+ffrAaDSqcp6q1WXyQig5KJFDUwYgDYPL5YLD4WDbM/1hV6s29fPz\nUyqTAY5sIHV5vrHj7SK5CxcuYOXKldiwYQOM8WiLAAAgAElEQVTuu+8+TJ8+HYGBgSqfmBqr7777\nDkOGDIFWq8W8efMAAK+88oqPT0VEPsaQlIiISE2HDh3C66+/jg0bNmDcuHF44okn0KtXr2v6WiEE\nTpw4obToZ2VlQafTITY2FiaTCSaTCdddd50qYYVcXeYZmgJcCFWfeVb2SZIEo9HIyj5ShXxtycE7\nAGVkB58PSA1utxsOh0MJR715Y+fcuXN49913sXXrVkyZMgUTJ05U7Q1Fapo2btyIDRs2YPXq1b4+\nChH5FkNSIiIiNW3ZsgVZWVl45JFHvJ6FJoTAhQsXkJGRgZSUFKSmpqK4uBjR0dFKtWnXrl1Va9GX\ng5Kq1WWeIQmrFeueXNXncDig0WhgMBhY2UequVzbs1arrZXZptT0eC778naebWFhIRYvXgybzYbH\nHnsM9957b43nlxJ5GjFiBO677z7cf//9vj4KEfkWQ1IiIqKGxO12Y//+/Uq16S+//IKwsDAlNI2N\njUVAQIBq1aaecwxdLhe0Wu0lIQnDutrhGV55u+2ZqKo/WtlX09mm1DR5Lvvytuo9Ly8PixYtQnZ2\nNmbNmoVRo0YxoKdrMnToUBQUFFzy6y+99BJGjBgBAPjXv/6FXbt2YcOGDXV9PCKqfxiSEhERNWRC\nCJw+fVoJTXfu3Am3240+ffrAbDbDbDajTZs2qoWmkiRVqjYFcEl1GUMS78iVV06nU6m84jImUota\nm+qvNtuU1aZNjxykV1RUqDIS5MiRI1iwYAFyc3Px1FNPYejQofz7hVT1wQcfYPny5fj+++/h7+/v\n6+MQke8xJCUiImpMhBCoqKjAzp07YbVakZqaivz8fERFRcFkMsFisaBHjx6qtSjKIYlndZlnVZlO\np2NIcg3kcEGN8IqoqrqaZ8tq06bJ8/oSQni97Gvfvn1ITk7G+fPnMW/ePPTv31/lExMBW7duxezZ\ns7F9+3a0bNnS18chovqBISlRU/byyy9j9erV0Gq16N27N1auXMnB90SNkCRJ+PXXX5Vq0/379yMo\nKAjx8fGwWCyIj49HcHBwrS6EkkMSOTRlSPI7IQScTifsdjsAbhIndfn6+vKsNpWfD1ht2nhUvb78\n/f2h0+lqfH3t3LkTycnJ0Ov1SExMRExMjJrHJaqkS5cucDgcCAsLAwBYLBYsXbrUx6ciIh9jSErU\nVOXk5ODWW2/FgQMHYDQace+992L48OGYOHGir49GRLVMCIHi4mKkpaUhJSUFGRkZKC8vR69evZRq\n044dO6q2EKq6kMQzOG1qoaC8jMlut0Or1cJoNDbJnwPVjvp8fV1u1rFGo2G1aQPiGY5qNBqvri8h\nBFJSUrBw4UKEh4cjMTER3bt3r4VTExERXVW1f5FxTSBRIxcSEgK9Xo/y8nL4+fmhvLwc7dq18/Wx\niKgOaDQahIWFYfjw4Rg+fDgAwOl0Ys+ePbBarXj++efx22+/oW3btspCqD59+sBgMNTovuTQQ/56\nz5DEbrejvLy8ySyEkiRJmTeq0+kQFBTEeaOkmqrLvgIDA+vd9m+NRgO9Xg+9Xg/g0jdSHA4Hq03r\nKc/w3c/PDwEBATUOtIUQ+Oabb7B48WJER0dj6dKliIqKqoVTExEReY+VpERNwLvvvovZs2cjICAA\nt99+O1atWuXrIxFRPSGEwG+//Qar1QqbzYasrCzodDrExsbCbDbDZDIhLCys1hdCeVaXNeTQVA6E\nXS7XNW0SJ/ojqobvRqOxQYfvV6s25diOuiWEgN1uV8J3uXK0JtxuNzZv3ox33nkHCQkJeOqpp9Cm\nTRuVT0xERFQjbLcnaqqOHDmCESNG4L///S+aN2+Ou+++G+PGjcOECRN8fTQiqoeEEDh//jwyMjKQ\nkpKCtLQ0nDt3DtHR0Uq1aZcuXVQL/jxD06oLoRpKZVldLcuhpquphO/XMrajITwnNDSelcnehu9O\npxPr1q3DypUrMXToUDzxxBO47rrrVD4xERGRVxiSEjVV69atw3fffYcVK1YAAFatWoW0tDQsWbLE\nxycjoobC7XZj//79SElJgc1mwy+//ILrrrtOCU1jY2Ph7++v6kIoz+DUs5W/PlWW+XpZDjVu8p8F\nu90Ot9sNg8EAo9HY5K6vy1WbymM76ttzQkPjWZnsbfheUVGBVatW4eOPP8aYMWPw2GOPISQkROUT\nExERqYIhKVFTlZWVhQkTJiAzMxP+/v6YNGkSEhISMGPGDF8fjYgaKCEETp06BavVCqvVip07d0II\ngT59+sBsNsNisSAiIkLVFv2qlWWeVWV1vaim6jxIueqKIQ2pwbMyWQjB8L0KVpt6T83K5PPnz+P9\n99/Hxo0bMWHCBEybNg2BgYEqn5iIiEhVDEmJmrLXXnsNH374IbRaLfr164cVK1YoixSIiLwlhEBF\nRQV27NgBq9WK1NRUFBQUICoqCmazGWazGT169FBtsYwckHiGJFqtttIcQ41Go3qo5Ha7lXBUDhYa\n8jxIql/U3CTe1LDa9Np4hqMGgwEGg6HG4WhxcTHeeecdfPfdd3j44Yfx4IMP1mjpHxERkQ8wJCUi\nIqK6I0kSfv31V6VFf//+/WjWrBni4+NhsVgQFxeH4OBgVVv0PUNTQJ2FUJdrefYmWCCqquomcVYm\ne4/VppXJlclut9vrmcmnTp3CkiVLkJqaiscffxz33HMP3ywiIqKGhiEpERER+Y4QAsXFxUhNTYXV\nakVGRgYuXryIXr16KbNNO3bsqEpoIYSoVFnmcrn+cEAiV/U5HA4IIZRwlMEVqaWxbaqv75patan8\nBk9FRYUqC+VOnDiBhQsX4sCBA/jb3/6GESNGNJqfFRERNTkMSYmIiKh+cTqd2L17N6xWK2w2G377\n7Te0a9dOadG/8cYbVWvfvFJAIgencmgqV/VptVq2PJPqmsqm+vqusVabqj3T9tdff0VycjLy8/Mx\nZ84cDBkyhM+HRETU0DEkJSIiovpNCIHjx48roWlWVhYMBgNiY2NhNpuRkJCAsLAwVRdCeVabyv8m\n0mq1rBwl1Xm2PHNsQ/3kOe+4oVWbes60BQB/f3+v3uDJzs5GUlIS7HY75s2bB4vFouZxiYiIfIkh\nKRERETUsQgicP38e6enpsFqtSEtLw7lz5xAdHQ2z2QyTyYQuXbp4FTR5VvXJ1WOeQYkcjngGJETX\nyrOqT42WZ6pbDaHaVO2FX5mZmUhOToa/vz+eeeYZ9OnTR+UTExER+RxDUiIiImr43G439u3bpyyE\n+vXXX9GyZUtlrmm/fv3g7+9/xYBAkiR8//33SEhIUEKFywVX1S2EksOR+lxVRr5VtarP25Znqj88\n30SRnxd8UW16uYVfOp2uxt9r+/btWLRoEdq2bYt58+YhOjpa5RMTERHVGwxJiYiIqPERQqCgoEBp\n0d+5cyeEEOjbt68y2zQiIgIajQYVFRVYs2YN3nrrLfj5+WHdunWIioq65jDjWqrKOL+0afMMrjjT\ntmmoOrqjtqtNhRCw2+1wOBxeL/wSQmDr1q1466230LNnT8ydOxfXX3+9KuckIiKqxxiSEhERUeMn\nhEBFRQUyMzNhs9lgs9mQm5sLrVaLEydOIDo6Gk8++SSGDh2qSmjhuRCqalWZ50IohmSNmyRJcDgc\ncDgcXlf1UcNXG9WmnteYt+Go2+3Gxo0b8e677+Kmm27C3/72N7Ru3bpG34uIiKgBYkhKRERETcuR\nI0ewYMECfPzxxxg8eDDMZjMOHjyI/fv3Izg4GAkJCTCbzYiPj0ezZs1qbSEUgEuqyhiaNg6SJMFu\nt8PpdEKv18NgMNQ4uKLGy5tq06rXmNForPEbPE6nE2vWrMEHH3yAYcOGYebMmQgLC/P24RERETU0\n1f5DnG9xExERUaNis9mQlJSEn376CdOnT8e+ffvQpk0b5XYhBM6ePYvU1FRYrVYsWLAAFRUV6N27\ntzLbtGPHjjUKMjUajRJ4yDzDEafTWWkhlGe1KTUcngu/DAYDmjVrxt9DqlZ1zwtyYGq32y+pQgeg\nPF94e41dvHgR//73v7F27VqMHTsW3333HYKDg1V5bERERI0JK0mJiIiowRNC4LPPPsMbb7yB06dP\n48knn8TkyZMRFBR0TV/vdDqxa9cupUX/t99+Q/v27WE2m2EymXDjjTfCYDCodlbPNly3210pROFC\nqPpJ/n2TAy1uqic1ydWmTqcTDocD8ms0b2Yel5WVYcWKFdi8eTMeeughTJkyBQEBAbX1EIiIiBoK\nttsTERFR4yWEwMMPP4zhw4dj1KhRXrc8CyFw/PhxpKSkwGazISsrC0ajEbGxsUpwGhoaqmqLftWF\nUJ5tuFz+4zvy3Fm73Q4hBDfVU62QrzHPAF4O5qvONtVoNFi/fj3i4+PRo0ePS57vioqK8M477+CH\nH37A9OnT8cADD0Cv1/vokREREdU7DEmJiIiIakoIgbKyMqSnp8NqtSItLQ0lJSXo1q2b0qLfuXNn\n1Vquq1v8UrWijEFd7ZE31TscDmg0Gm6qJ9X90QBefkOluLgYc+bMQWZmJoqKihATE4OEhAT07NkT\naWlpyM7OxsyZMzF27FjOyCUiIroUQ1IiIiIiNbndbuzduxdWqxVWqxVHjhxBy5YtlUrTfv36wd/f\nX7Vq06qhKcCFULVBCAG73V5pUz1/tqQmNauTT506hW+//RZbt25FdnY2Tp48icjISFgsFuW/7t27\nc2YuERHR/zAkJSIiIqpNQgjk5+fDarXCZrNh165dEEIgJiZGqTaNiIhQLTSVgxY5OL3Wbdl0eZ5b\nxHU6nRKOEqlFCAGn0wm73a5KdfLhw4eRlJSEM2fOYM6cORg8eLDy5k1qaqryX2FhIUwmkxKamkwm\ntGjRQuVHR0RE1GAwJCUi8qVz585h2rRp2LdvHzQaDd5//32YzWZfH4uIapEQAhcvXkRmZiZsNhtS\nU1Nx+vRp3HDDDTCbzTCbzejevbtqQZxnaCoHp57bsuXQlBWRlXluqtfr9TAajQyXSVXy6Aa73Q6t\nVgt/f3+vqpOzsrKQlJQEt9uNefPmwWQyXfHzCwsLkZaWpoSmO3bswEMPPYQlS5bU6P6JiIgaOIak\nRES+NHHiRAwcOBBTpkyBy+XChQsX0Lx5c18fi4jqmCRJOHz4sNKif+DAAYSEhCAhIQFmsxnx8fEI\nCgpSdSGUZ7UpgErLoJpyG7nnohyDwQCDwcBwlFTlGY7Koxt0Ol2Nv19aWhqSk5MREhKCxMRE9O7d\nu0bfx+Vyobi4GOHh4TU+CxERUQPGkJSIyFdKSkoQExODo0eP+vooRFTPCCFw9uxZpKamIiUlBRkZ\nGbDb7bjxxhuRkJAAi8WCDh06qBZkyguhPCtO5dBUDk4bc1BYdRakHI421aCYaockScrSL29HNwgh\n8OOPP2LRokXo2LEj5s2bhy5duqh8YiIioiaFISkRka/s2bMHjzzyCHr06IGsrCzExsZi0aJFCAwM\n9PXRiKgecjgc2LVrF2w2G2w2G06cOIEOHTooC6FuvPFG6PV6Ve6ruoVQcpWpHJo29BDRcxYkAK8W\n5RBVR825tpIk4auvvsKSJUtw4403Yu7cuejQoYPKJyYiImqSGJISEfnKjh07YLFYYLPZEB8fj1mz\nZiEkJATz58/39dGIqAEQQiAnJ0dp0f/5559hNBoRFxenBKctWrRQtUXfMzStuhDKm0Uzde1y7c5N\necQA1Q7PcNTbubZutxsbNmzA8uXLccstt+Bvf/sbWrVqpfKJiYiImjSGpEREvlJQUACLxYJjx44B\nAFJSUvDKK6/giy++8PHJiKghEkKgrKwM6enpSElJQXp6OkpKStC9e3elRb9Tp06qtc17LoSS/1/f\nF0Kp2e5MVB3PpV/ezrV1OBxYs2YNPvzwQwwfPhx//etfERoaqvKJiYiICFcISWs+OZyIiK5J69at\n0aFDBxw+fBhdu3bFtm3b0LNnT18fi4gaKI1Gg5CQEAwdOhRDhw4F8HtYk52dDavVildffRVHjx5F\neHi4Umnar18/GI3GGgWZGo0Ger1eafH3XAjlcrlQUVEBAJVCU19Va7rdbiUcNRgMCAoKYjhKqnO7\n3aioqFCWfgUHB9f4ei8vL8eHH36I9evX45577sG2bdvQrFkzlU9MRERE14KVpEREdSArKwvTpk2D\nw+FAp06dsHLlSm63J6JaI4TAyZMnYbPZYLVasWvXLmg0GsTExMBkMsFsNqNVq1aqLoTyXAbluRDK\ns9q0tqhZ0UdUHXnpl9vthtFo9GrpV2lpKZYvX44vvvgCkyZNwuTJk+Hv76/yiYmIiOgy2G5PRERE\n1FQJIXDx4kVkZmbCarUiNTUVhYWF6NSpE0wmEywWC7p166Za1aW8EMozONVoNJWCU29b9D031UuS\n5HVoRXQ5nteZEMLrpV9nzpzB0qVLsX37djz66KO47777VFvERkRERNeEISkRERER/Y8kSTh8+DBS\nUlJgtVpx8OBBNG/eHAkJCTCbzYiLi0NQUFCtLoTybM+/1oVQ3FRPdUEOR+VxEt5eZ/n5+XjzzTex\na9cuPPHEE7jrrrtY7UzX7JNPPsHzzz+PgwcPIjMzE/369fP1kYiIGjKGpERERERUPSEEioqKlBb9\nzMxMOBwO3HjjjcpCqPbt26vaoi9XmXouhJKDUzk0le/Pc1O9VquF0Wi85mCV6Fp5hvAajcbr6ywn\nJwcLFy7EkSNHMHv2bNxxxx28ZukPO3jwILRaLR555BEkJSUxJCUi8g5DUiIiIiL6Y+x2O3bv3q20\n6J84cQIdO3ZUQtPevXur1iost+h7hqbA7wuh5Nv8/Pzg7+8PnY67R0ldVUN4f39/rxaQHTx4EElJ\nSTh37hzmzp2LgQMHqnxiaooGDx7MkJSIyHvcbk9EREREf4zRaITZbIbZbAbwe/Xn8ePHkZKSgtWr\nVyM7Oxv+/v6Ii4uD2WxGQkICWrRoUaNgSaPRQKfTQafTwWg0KsuYnE4ntFottFqtslXcs02fLcvk\nDc9w1M/PD4GBgV6F8Lt370ZSUhI0Gg3mzZuH+Ph4FU9LREREtYkhKRERERFdE61Wi6ioKERFReHB\nBx+EEAKlpaVIT09HSkoK3nnnHZSVlaF79+5KtekNN9zwh4JMp9MJp9MJl8sFvV6P4OBg5evlOZFu\ntxsOhwMulwtarVZpz5dDU7Yz09VIkgSHwwGHwwGdToegoCCvFpfZbDYsWLAAoaGheOGFF9CzZ08V\nT0tNwdChQ1FQUHDJr7/00ksYMWKED05ERNT0sN2eiIiIiFTjcrmwd+9epKSkwGaz4ejRo2jVqhVM\nJhPMZjNiYmJgNBorBZmSJOG///0vkpOT0bt3bzz33HOXfM7lyAuh5ODU5XIBQKVlUN60TFPjI0mS\nUqEsVy3XNBwVQuD777/Hm2++iaioKMybNw+dOnVS+cRE/8N2eyIiVXAmKRERERHVPSEETp48CavV\nCpvNhl27dkGr1SImJgbx8fE4f/483n33XRQXF2PmzJl44IEHEBAQUOP7kxdCycGpPMvUMzhli37T\nI1cfO51O6PV6GI3GGl8HkiThiy++wNtvv42YmBg89dRTaN++vconJrrU4MGD8cYbbyA2NtbXRyEi\nasgYkhIRERGR7wkhUFxcjJdffhkffPABjEYj+vbti+bNm8NsNsNisSA6Otqr1ueq93e5hVBylakc\nmrLatHGSZ9u6XC4YDAYYDIYah6MulwuffvopVqxYgUGDBuHJJ59EeHi4yicmutTGjRsxc+ZMnDlz\nBs2bN0dMTAy+/vprXx+LiKihYkhKRERERL5VUlKCZcuWYdGiRejduzeefvppDBo0CEIIHDp0SGnR\nP3jwIJo3b67MNY2NjUVQUJAqQabcou8ZmkqSVKk9X6fTMTRt4FwuF+x2O9xuNwwGwzWNb6iO3W7H\nRx99hFWrVmHkyJF4/PHH0bx5c5VPTERERHWEISkRERER+UZ+fj4WLlyIFStWYNiwYZg7dy769OlT\n7ecLIVBUVKS06GdmZsLhcKBPnz5KcNquXTvVgkzPhVDy/7kQquGRq4blcNRoNMJgMNT49+3ChQv4\n4IMP8Omnn2L8+PGYPn06goKCVD41ERER1TGGpERERERU9z777DNMnToVDzzwAGbPno3IyMgafR+7\n3Y5du3bBarUiNTUVubm5uP7665XQtFevXtDr9aqc+UoLoeTQlAuh6g855Lbb7RBCwGg0Qq/X1/j3\n59y5c3j33Xfx9ddfY+rUqZg4cSKMRqPKpyYiIiIfYUhKRERERHWvuLgYLpdL9dmNkiQhJydHadHP\nzs6Gv78/4uLiYLFYkJCQgObNm6sWZHqGplUXQnlWm1LdEULA6XTCbrcDgNfhaGFhIZYsWYKUlBQ8\n9thjGD9+PHQ6nZpHJiIiIt9jSEpEREREjZcQAqWlpUhLS4PVakV6ejpKS0vRo0cPmEwmWCwWREVF\nqRZkyq3dnsGpRqOpFJyyRb92eIajGo0GRqPRqzmyeXl5WLRoEbKzszFr1iyMGjWKgTcREVHjxZCU\niIiIiJoWl8uF7Oxspdr02LFjiIiIgMlkgtlsRt++fb1a6OOpuoVQnu35XAjlHSEEHA4H7HY7/Pz8\nYDQavRp7cPToUSxYsAC//fYbnnrqKdx22238/SEiImr8GJISEREBgNvtRlxcHNq3b48tW7b4+jhE\nVIeEEMjLy1MWQu3evRtarRYxMTEwm80wmUwIDw9XtUVfrjL1XAglB6dyaMpg7sqEELDb7XA4HEo4\n6k0b/P79+5GUlISysjLMmzcPN998s4qnJSIionqOISkREREAJCcnY+fOnSgrK8PmzZt9fRwi8iEh\nBMrLy5GZmakshDpz5gy6dOmiVJtGR0fDz89PtfurGpoCXAhVHUmS4HA44HA4oNPplMrRmtq1axeS\nkpKg0+mQmJiIfv36qXhaIiIiaiAYkhIREeXm5mLSpEl49tlnkZyczEpSIrqEJEk4ePCg0qJ/6NAh\ntGjRAgkJCbBYLIiNjUVgYKBqLfryZnY5OJUk6ZLQtKnNx5QkCXa7HU6nE3q9Hkaj0aufQUpKChYu\nXIiWLVsiMTER3bt3V/G0RERE1MAwJCUiIrr77rvxzDPPoLS0FG+88QZDUiK6KiEEzpw5o7ToZ2Zm\nwul0ok+fPkq1abt27VSr/vQMTeXgVKvVVgpOG+tCKLfbDbvdDpfL5XU4KoTAt99+i7feegtdu3bF\n008/jaioKJVPTERERA1Qtf+IqvkwHyIiogbkiy++QKtWrRATE4P//Oc/vj4OETUQGo0G4eHhGD16\nNEaPHg0AqKiowK5du2Cz2TBv3jzk5eWhY8eOMJvNsFgs6NWrV41nZmo0Guj1euj1egD/Wwjlcrng\ncrlgt9shhKi0DKqht+h7hqMGgwHNmjWrcTgqSRI2b96Md955B3FxcVi9ejXatm2r8omJiIioMWIl\nKRERNQnPPPMMVq1aBZ1Oh4qKCpSWlmLs2LH497//7eujEVEDJ0kSjh07prTo7927FwEBAYiLi4PF\nYkF8fDyaN2+u+kIoz4pTOTSVg9OG0KIvh75utxtGoxEGg6HGPyOn04n169fj/fffx5/+9Cc88cQT\naNmypconJiIiokaA7fZERESy7du3s92eiGqNEAIlJSVIS0uD1WpFeno6zp8/jx49eigt+lFRUaoF\nmdUthJKrTOXQtD5Um8pnraiogCRJXoejFRUVWL16NT766COMHj0aM2bMQEhIiMqnJiIiokaE7fZE\nRESe6kNYQESNk0ajQYsWLTBs2DAMGzYMwO9Vkz///DOsViv+9a9/IScnBxERETCbzTCbzejbty+M\nRmON70+n0ykb4OUWfTk0dTgclyyE0ul0dfo8KM9alccFGI1G6PX6Gp/h/PnzeP/997Fx40ZMmDAB\nP/74IwIDA1U+NRERETUlrCQlIiIiIqpjQgjk5ubCZrPBarViz5498PPzQ0xMDMxmM0wmE1q2bFkr\nC6Hk/9fFQighBJxOJ+x2OwDA39/fq4C2uLgYy5Ytw7fffotp06bhoYcegsFgUPPIRERE1Lix3Z6I\niIiIqL4SQqC8vBwZGRmwWq1ITU1FUVERunTpooSm3bp1U7VFX14IJQenACqFpt4shPIMRzUaDYxG\no1fh6KlTp7BkyRKkpqZixowZuOeee2q8HIuIiIiaNIakREREREQNiSRJOHDgAKxWK6xWKw4fPozQ\n0FAkJCTAbDYjNjYWgYGBqi6E8lwG5bkQyrPa9EqEEHA4HLDb7fDz81PC0ZrKzc3FwoULsX//fjz5\n5JMYMWJEg1hKRURERPUWQ1IiIiIiooZMCIHCwkKlRX/Hjh1wuVzo06ePshCqbdu2qrboe7bnX2kh\nlBACdrsdDocDfn5+8Pf3h5+fX43v+9dff0VycjLy8/MxZ84cDBkyhLOkiYiISA0MSYmIiIiIGpuK\nigrs3LkTNpsNNpsNJ0+exPXXX68shOrVq5dqbelVF0K53W5IkqSEpHI46s397d27F0lJSbh48SIS\nExNhsVhUOTsRERHR/8eQlIiIiIiosZMkCUePHlVa9Pfu3YvAwEDEx8fDYrEgPj4eISEhXldlSpKk\nVI7KFaVytalWq61UbarRaK56f5mZmUhOTobRaMQzzzyDvn37enU+IiIiomowJCUiIiIiamqEECgp\nKUFaWhpSUlKQnp6OCxcuoGfPnkqLfmRk5DXP+Txz5gwCAwPhcrmg1+thNBorfa3cou9ZbfrYY4/B\n6XTCbDbDYrEgJiYGRqMRQgj89NNPWLhwIdq0aYPExERER0fX1o+CiEhVkiRBq9VCCMFxIEQNC0NS\nIiIiIiICXC4XsrKylGrT48ePo3Xr1jCbzTCZTOjbty+MRmOlr9m1axdef/117NmzB5mZmQgKCrqm\nUEAIgZycHFitVqSnpyM9PR3Hjh1Djx49UFRUhO7du+PFF19ETExMbT1cIqJac/bsWbRo0YIL5Yga\nFoakRERERER0KSEEcnNzldB0z5490PUbtGIAACAASURBVOl06NevH8LDw/Hdd99h//79mDFjBh5+\n+GEEBwfX6H7cbjc2bdqE999/H927d0dQUBCysrKQnp6O1q1bo3///rjpppvQv39/REdHM3QgonpD\nrhqVnTx5Ev/3f/+HHTt24O6770bnzp0xbty4Sz6PiOolhqRERERERHR1kiRhy5Yt+Mc//oHc3FwM\nHDgQp0+fxg033KBUm/6RENPpdGLt2rX44IMPcNttt+GJJ55AWFiYcrvb7ca+fftgtVphs9lgtVpx\n7tw5WCwWJTi96aabYDAYaushExFVa+vWrYiIiEBMTAxKSkrQvHlzvP766wgPD8ddd92Ff/7zn7DZ\nbNi+fTv8/f19fVwiujqGpEREREREVD1JkvD555/jpZdeQnl5ORITEzF+/HjodDq43W4cOHBAqTY9\nfPgwwsLCYDKZYDKZEBcXh4CAgEot+BcvXsS///1vrF27FmPHjsWjjz56zVWo+fn5sNlsyn9fffUV\nQkNDa+uhExFV4jlndP369ViyZAmCg4NhMBiwdu1a3Hbbbbj77rvx1VdfQZIkJCYmYsCAAT4+NRFd\nI4akRERERER0KbnS8+WXX0ZQUBCeffZZjBw58oqVokIIFBYWKqHpjh074Ha70adPH9x44404fvw4\ntm3bhgcffBBTp05FQEBAHT4iIqKaudwSpi+//BKTJk3C2LFjsXjxYuh0OkycOBEpKSnYsmULevTo\nAQDYu3cvevTowXZ7ovqv2pBUV5enICIiIiKi+kMIAbPZjJCQECxatAh/+tOfrmkhk0ajQatWrTBm\nzBiMGTMGAFBRUYGdO3di3bp1CAwMREpKCvR6fW0/BCIir8nhqPz898UXX+CHH37A5MmTMWTIELz8\n8svIyMhAeXk5AgMD8eCDD2L//v2IiIhAaWkpXnvtNZw5cwb//Oc/0aZNGx8/GiKqKVaSEhERERE1\nYXl5eWjXrp2vj0FEVOeqLlo6duwY5s+fj1OnTmHUqFGVgtJhw4Zh1qxZGDFiBABg7ty5OHnyJLKy\nsmAymfDss88iKirKVw+FiK4dK0mJiIiIiOhSDEiJqKmSA9Jvv/0Wa9euxcyZM/HII48gLi4OS5cu\nxfbt29GsWTOYTCbcdddd2Lx5M0JDQ7Fv3z689tprKCsrQ0VFBcLDwwFcvl2fiBoODssgIiIiIiIi\noibn3Llz6NatG7744gtMmDABffv2Re/evTFlyhQcPXoUH3/8MSoqKrBt2zZMmzYN7du3xxNPPIED\nBw7A6XQiKCgI4eHhcLvdkCSJASlRA8d2eyIiIvKJEydO4KGHHsLp06eh0Wgwffp0zJw509fHIiIi\nokbmchWecqv9LbfcgtDQUGzevBkAcPDgQYwaNQqHDh0CAPTr1w9dunTBG2+8gbZt28LtdsNgMNT5\nYyAi1XC7PREREdUvBQUFKCgoQN++fXH+/HnExsZi06ZN6N69u6+PRkRERI2A58xRl8sFne5/Ewfl\nj1NTU3H77bejtLRUuS06OhpjxozB8ePH4efnh+nTp+OWW25Rgla32w2NRsNN9kQNU7UhKf9EExER\nkU+0bt0affv2BQA0a9YM3bt3x8mTJ318KiIiUsPWrVvRrVs3dOnSBa+++qqvj0NNlFarRVlZGV5+\n+WU8+uijkCRJuU2n00GSJFgsFnTv3h3JycnKbevXrwcAWCwWrF69GgMGDKhUiern58eAlKgRYiUp\nERER+VxOTg4GDhyIffv2oVmzZr4+DhERecHtdiM6Ohrbtm1Du3btEB8fjzVr1rBTgGpd1bb6ffv2\nYfTo0Rg3bhwef/zxSxbVydWk33//PUaOHIkLFy5c9vu63W74+fnV6tmJqM6wkpSIiIjqp/Pnz2Pc\nuHFYtGgRA1IiokYgIyMDnTt3RmRkJPR6PcaPH4/PP//c18eiJkCj0SAnJwcZGRlwOBzo2rUrNBoN\n/P390a5dO9jt9kqfr9PpIITAkCFDcOeddyInJ6fS7ZIkQQjBgJSoiWBISkRERD7jdDoxduxYPPDA\nAxg9erSvj0NERCrIy8tDhw4dlI/bt2+PvLw8H56IGqOqXbEXLlzA7NmzMWTIEMyfPx+PPvooSkpK\n8MILL2Dr1q0AAKPReMn3cblcAH5vsY+MjKx0m1ar5cZ6oiaEISkRERH5hBACU6dORY8ePTBr1ixf\nH4eIiFTCUIlqkxyOytdZVlYWlixZgvT0dBw8eBBHjhzB+vXrERAQgOXLl2PAgAEICgrCpk2bAPwv\nFJUkCW63G3q9Xvne8m1E1DQxJCUiIiKfsFqtWL16NX788UfExMQgJiZGqfQgIqKGq127djhx4oTy\n8YkTJ9C+fXsfnogag6rhaE5ODu69914sX74cQUFBCAkJQUVFBYqKihAYGIg777wTeXl58PPzw733\n3ov58+cD+L3F3u12Q6vVws/PD+Xl5fj73/+Op556Cg6Hw2ePj4h8jyEpERER+cTNN98MSZKwZ88e\n7N69G7t378awYcN8fSwiIvJSXFwcfvnlF+Tk5MDhcGDdunUYOXKkr49FDVTVcDQ7OxujRo3C6dOn\n8emnnyI4OBiTJk2C0+lEbGws0tPTAQAJCQn46aeflJD0z3/+My5cuABJkuDn54czZ87gH//4B265\n5RYUFhbi0UcfRWBgoM8eJxH5ns7XByAiIiIiIqLGQ6fTYfHixbj99tvhdrsxdepUbranP0zeVO85\nvmHs2LEoLy/H/fffj4SEBMyfP19ZCtatWzfccMMN+Ne//oUWLVrgyy+/RHx8PIxGI5o1a6ZUkgK/\nz0QfM2YM+vXrhy1btqBt27Z1/viIqP7RVB12XMUVbyQiIiIiIiIiqi3Lli3DN998g1mzZmHz5s34\n5JNPcPToUfj5+UEIgbCwMPzwww+IiYmB3W7HRx99hO3bt8Pf3x8vvvgiwsPDle/lua3+4sWLCAgI\n8OEjIyIfqXZwNkNSIiIiIiIiIqpXnE4nXnvtNeTk5GDKlClYunQpOnTogNdeew3p6emIjY0FADz7\n7LNITU3FDz/8oHyty+WCTvd746wkSdBqOWmQiBTVhqRstyciIiIiIiKiekWSJBw7dgwPP/wwfvjh\nB9hsNrz33nswGAyYM2eOEoo+99xziI6ORnFxMUJDQwH8PvJBkiQAYEBKRNeMzxZEREREREREVK9I\nkoSzZ8/innvugV6vR1ZWFgYNGoSZM2di+/bt2LFjBwAgICAAx48fVwJSmVarZUBKRH8IK0mJiIiI\niIiIqF7x9/dHv3790KVLFzz11FMAgI8//hhGoxGJiYkoKipSPlej0VRqsSciqgnOJCUiIiIiIiKi\neufUqVOYPXs2ysvLUVRUBIfDgWeffRZ//vOffX00Imq4uLiJiIiIiIiIiBqW8vJyZGdno7i4GMOG\nDVN+nQuZiKiGGJISERERERERUcPGtnoi8hJDUiIiIiIiIiJqmIQQ0GiqzTaIiK5VtU8krE0nIiIi\nIiIionqNASkR1TaGpERERERERERERNSkMSQlIiIiIiIiIiKiJo0hKRERERERERERETVpDEmJiIiI\niIiIiIioSWNISkRERESVbN26Fd26dUOXLl3w6quv+vo4RERERES1TiOEuNLtV7yRiIiIiBoXt9uN\n6OhobNu2De3atUN8fDzWrFmD7t27+/poRERERETe0lR3AytJiYh8SJIkXx+BiKiSjIwMdO7cGZGR\nkdDr9Rg/fjw+//xzXx+LiIiIiKhWMSQlIvIhrfZ/T8NCCEiShKtU+BMR1aq8vDx06NBB+bh9+/bI\ny8vz4YmIiIiIiGofQ1IiIh9599138euvvyofazQaaLVaaDS/V/8zMCUiX5Cfg4iIiIiImhKGpERE\nPiCEQG5uLjZs2AAAKCwsxMqVK/H555/jxx9/RGlpaaXAVCZJElwuFwCgvLy8zs9NRI1fu3btcOLE\nCeXjEydOoH379j48ERERERFR7WNISkTkAxqNBm63G0VFRQCAzz77DF999RUcDgdWrlyJm2++GRMm\nTEBpaSkAoKKiAsDv7fk6nQ6lpaW4//774XA4AHC2KRGpJy4uDr/88gtycnLgcDiwbt06jBw50tfH\nIiIiIiKqVQxJiYh8xOl0onPnzjh37hy+/vprPPDAA7jrrrvw/PPP4+eff0Z4eDg2b94MAHjxxRcx\nePBg/OUvf8HGjRuh0+mwadMmGAwGAP+bbSqEYIs+EXlFp9Nh8eLFuP3229GjRw/ce++93GxPRERE\nRI2e5iovpvlKm4iolnz77bf4/vvvUVFRgfDwcPTv3x/r1q3Dnj17IIRAZmYmPvnkE4wdOxYxMTGI\ni4vDbbfdhh49euCNN95Ay5Yt8frrryMjIwOFhYVISEhAeHg4gN/DUrlVXwgBt9sNPz8/zhokIiIi\nIiKipqzaF8WsJCUi8pEOHTrg7bffRmpqKiZNmoTt27fDYDAgLS0N6enp6NixI7p3745z586hvLwc\nzz77LO6++2707NkThw4dwsCBAwEAp0+fxqeffoohQ4bgmWeeQVlZGTQaDU6fPg3g99Z+nU5XKSAV\nQnAxFBEREREREdH/p/P1AYiImiqj0Yhbb70VFosF7du3R9u2bbFv3z7k5eVh48aNsNvt6NKlC3bs\n2IHg4GBERkZCCAGXy4X8/HzEx8cDADp16oTExER07doVt956K/Lz8xEcHIzY2Fjccccd8PPzQ4cO\nHfDXv/4VwcHBSpXp5apKPStQiYiIiIiIiJoKhqRERD4ghMANN9yATZs2Kb82YMAA/PTTT5g9ezZy\ncnIQFxcHvV6PlJQUdO3aFcDvVaEZGRlo1aoVIiIisHXrVixatAh2ux2nTp1CQUEBAgIC4HQ6UVBQ\ngEGDBiEiIgL/+Mc/MGjQINx0003QaDRYu3YtjEYjEhIS0K5dO+UMckAqSZIy55SIiIiIiIiosWNI\nSkTkA/J2ewDw8/MDAHTr1g2rV68GAJSWliqb7cvKytC/f3/la7/88kv07t0bdrsdGzduxK233oo5\nc+bg+++/R3JyMlq0aAGr1Yr27dvj/vvvBwBYrVakpKQgLi4OTz/9NE6fPg1JkvDSSy9h0aJFuOmm\nm3Dy5EkUFxejZ8+eDEiJiIiIiIioSWFISkTkI3I4KpNDU61Wi5CQEISEhAAA5s+fX+nzdDodBg4c\nCKPRCKPRiF9++QV5eXlYtGgR9Ho9goOD8f333+Pmm28GAJw4cQIOhwOdOnVCSkoKbDYbfvzxRwQG\nBgIASkpKcOjQIbz//vvYu3cvCgoKMHHiRMycOfOK55dnmlZ9HEREREREREQNDUuFiIjqCT8/v8tu\noJckqdLH8+fPx4MPPggAmDBhAiRJwpw5c5Cfnw+LxQIA2LRpE2677TYAwLlz51BQUICYmBhs3boV\nt956KwIDA1FSUgLg90rVpKQk7Nu3D19++SWWL1+O48ePo6io6LLnlM+j1WorBaSSJMHtdl9yXiIi\nIiIiIqL6jpWkRET1XNXWd7fbrYSTJpMJJpMJAFBRUYGLFy8CANq2bYuhQ4cCAHJzc3H69Gm0adMG\nQggEBQUBAJo3bw4A2LdvH8rLy6HRaHDTTTehsLAQEREROHz4MCwWi7LMSb7ftWvX4oUXXsDkyZMR\nFhaGCRMmICAg4LIt+kIIZb4pF0IRERERERFRfcWQlIiogfGs3vRs0ff394e/vz8A4JtvvlE+p1On\nThg2bBhCQ0MxY8YMzJgxA8nJyRg4cCC6dOmCyMhIFBQUYNu2bQCA06dPIz8/H1FRUZXuVwihfO9m\nzZohMjISDocDmZmZ2LRpE6xWK+68805Mnz4drVu3BvD77FXP88qBq/x/IiIiIiIiovpAI7/orcYV\nbyQiovpHCAEhRLWVndu2bcOmTZtw8uRJvPTSS7j++usxadIkjBkzBrfffjvCwsLgdDqh1+srfa1c\nSdqhQwcsW7YMw4cPR1FREaZMmYLHHnsMAwYMwDPPPIObb74ZY8eOxYkTJ7Bx40ZotVqMHj0a7du3\nr/a8kiRxtikRERERERHVtmqrdRiSEhE1cpIkQaPRXLFyMyMjA//85z+Rm5uLzp0745VXXkF0dPQl\nn+dwONCyZUuUlpYCABYsWID33nsPOp0OCQkJOHz4MPr164fnn38e48aNQ9euXeFyuXD69GmEhYXh\nxRdfRGFhIYKDgxEZGam04lc9rxzystqUiIiIiIiIVFTti0wubiIiauSqho1utxsulwueb5IlJCTg\n66+/RnZ2NpYuXYrIyEilIlX+GgD48ccfERERAQCw2+3Q6XQYP348UlNTMWLECAwbNgy9e/fGDz/8\ngICAACxevBjvvPMOJElCWVkZWrVqhaVLl2Lt2rUoLS2FVqvFSy+9hLy8vErnrbrASq42JSIiqg1T\npkxBREQEevfu7eujEBERkY8wJCUiamL8/Pyg0+kuCU7lILRNmzYwGo1K9alnQHngwAHcfPPNAACj\n0YgWLVogPT0dAQEBGDFiBObNm4eJEyfit99+Q9++fQEAJSUl6N+/P7p06QLg9wVT3bt3R0hICADg\nueeeQ2BgIABgzZo1mD59OpKSknDy5EkA/6uElStO5bOcPHkSFRUVtfqzIiKipmHy5MnYunWrr49B\nREREPsSQlIiI4OfnV2kmaHJyMr788ksUFxdDo9Eo80lnzZqFlStXKp83atQoREREICYmBqNHj8aq\nVavgdrtx6tQpFBYWAgAKCgpw5MgRdO3aFbm5uXC5XGjVqhUAYMeOHejUqRNCQ0Px4YcfYseOHZg6\ndSrOnTuH5ORkAL9Xlq5atQrbtm1DWVmZEpa+8MILKCgoqPYxXWWcDBERkeKWW25BaGior49BRERE\nPsSQlIiILmEymbBr1y6MHj0aN998M6ZNm4ZTp04p1aaykJAQrFixAp999hnuuusutG3bFnq9Hnfe\neScOHz6M119/HW+99RZ2796N2NhYHDt2DAEBAQgPDwcAfPvtt4iPj8e5c+ewevVqbNq0CTabDS1b\ntkR2djb279+P1atX47PPPsPbb7+N2267Dd988w3WrFmDVatWoays7LLnF0JAo9Hgq6++gt1ur/Wf\nFxERERERETVsOl8fgIiI6p/+/fujf//++Pvf/w6Hw4Hc3FwEBQVdsoFeDiOjoqIQFRWl/LrFYsGz\nzz6L//znPwgODkbPnj3RokULhIaG4uzZsygoKEDr1q2xcuVK/P3vf8fRo0fRo0cPzJkzB0eOHEFK\nSgo6dOgASZJw4MABhIWF4b333kNFRQWcTic++OADGAwGTJ06FbGxsXj77beVswCARqOB2+3Gzp07\nMWDAABiNRrjdbmWEABdCERERERERkSdutyciIq/JS56qbqoHgOXLlyM7OxtvvvkmAOD/tXdvIVaX\nexyHv7PGGTygNZXHMiWzUiOJAtOwELLQbRQqkkknoiKriw5iFh1IOpgpFBFBZFaQQXWRinggiEiF\naposSlI6WFqaVpaYOGMz+0JmkZV7Ezud3O/z3MzM+q818665m8/8/u975513ZsWKFbnooovy6KOP\n5tNPP81xxx2X8ePHZ/HixdUp03Zr1qzJs88+m5NPPjnXXHNN+vTpk3vvvTctLS15+OGHs2vXrnTv\n3j2tra2pVCrVj5s2bUpzc3N1L9Q/8+uvv+aHH37IcccdJ5wCR6QZM2Zk6dKlqa+vz6BBg/Lcc8/l\nqKOO6uhlHZG+/PLLXHzxxfnoo486eikAwKHjdHsADp3fHqzUrq2tLT///HP27duXvn37Vh9/5JFH\n0tTUlFmzZmXx4sUZPHhwGhoaMmnSpEyZMiUzZ87M888/n2+//Tbff/99Ro0alSeffDLr16/P/fff\nnyRZvXp19QTi7t27HxBo2w92mjNnTu67774kydNPP5177rknS5YsyYYNG6pr+fLLL7Nw4cLs2bPH\nHqbAEenCCy/Mxx9/nHXr1uWUU07Jww8/3NFLAgA4IomkABwSNTU16dGjR2688cbceeedSfYHzH37\n9iVJjjrqqEyYMKG6z+mtt96a+++/P927d8/777+f2travPHGG7niiiuydOnSjB07tnpQ0xdffJEL\nLrjggJ/1+883bNiQSy65JMn+SLpu3bq89957GTt2bFatWpXm5uY88sgjefPNN7N3797qLfrt2tra\nqsEV4J9q7Nix1X8SjRgxIps3b+7gFR2Zpk6dmlGjRmXDhg3p37//AYcUAgBlsCcpAIdce7isVCrV\nP+bbJzfb9zmtra3N+eefn/PPP7/6ujFjxmTHjh1ZsmRJ6urq8sQTT2Tnzp059dRT09TUlAsuuOAP\n+6S2f/35559nxIgR+emnn7Jr167MmTMnQ4YMyd69e9PU1JRzzz03GzduzHfffZczzjgjL7zwQsaM\nGZPGxsb07ds3/fr1q4bT9u/ZHk3tawr8Ey1YsCBTp07t6GUckRYtWtTRSwAAOphICkCH+LPI2Nra\nmtbW1tTW1qampiY9e/bM9OnTM3369Opzmpubc+WVV2bmzJmZMmVK7rrrruo+pO2HN3300Ufp0aNH\nBg4cmDVr1qShoSFDhgzJnj17cswxx+TXX39N165d061bt7z88ss5/fTTU6lUMm/evGzevDnvvvtu\nOnXqlIULF2bgwIH59ttv07dv3z/dc7V93Qe7BvC/+u0k/W899NBDufjii5MkDz74YOrr63P55Zcf\n7uUBAPxfEEkB+Mf47aRpcuAt7+3TnPX19Zk6dWqmTp1anUZtv02+tbU1nTp1yuLFi9O7d+8kyTvv\nvJPTTjstSbJjx47s2LEjw4cPz5YtW/LLL7+ka9euqVQqeffddzN79uysWLEic+fOzcsvv5ylS5fm\n5ptvzuTJk3POOedk06ZNufzyy9OzZ8+MHj26+jN/u+b2tVQqFdOmwN9i1apV//H6woULs2zZsrzx\nxhuHaUUAAP9/jL0A8I9VU1OT2traP9xS39LSUr2eJHV1dalUKunUaf///kaPHp0ZM2YkSdauXZth\nw4Yl2X9Q0+7duzNs2LA0NjbmhBNOyIknnphk/2FQJ510UubNm5ezzz47s2fPztq1a7N79+40Nzen\nrq4uM2fOzL59+zJx4sTqWiqVSl577bUDtg9on4Rtf2z16tVZt26dPU6Bv93y5cszd+7cvP766+nc\nuXNHLwcA4IhlkhSAI05dXV1aWloyevToHH/88RkxYkRGjx6ds88+O3V1dTnvvPOqz33uueeq050t\nLS2pr69PQ0NDtm/fnvr6+qxfvz7Dhw/PunXrMm3atNx+++1JkvXr16dnz555++23M3DgwNx0003p\n379/+vbtmwkTJuTzzz/PgAED8sorr+SBBx7IpEmTMm/evKxduzYjR47MpZdemkGDBiVJlixZktra\n2gwdOtRt+cDf6pZbbklzc3PGjh2bJBk5cmSeeuqpDl4VAMCRp6Z9yuUg/uNFAOhIbW1t+e6779LY\n2Jhly5Zl48aNWbBgQfr06fOH6dPfv27nzp25++67s3z58qxcuTIbN27Mq6++muuvvz4jRoyo3oo/\na9asdOnSJbNmzUpdXV327NmTGTNmZOLEiencuXNeeuml/Otf/8q4cePy1Vdf5ccff8yiRYvS3Nyc\n+fPnZ+vWrZk/f36GDRuWq6666jD+dgAAAPidg+6JZpIUgCNWTU1NevfunfHjx2f8+PH/9fntBzvV\n1NSkoaHhgGmrQYMG5b333svMmTOzbdu2XHvttbnjjjvS2NiY6667LnV1dWltbU2XLl3yySef5LLL\nLsszzzyT008/PePGjcuWLVvy4osv5pdffkm3bt2ydevWfPrpp9m7d2/27NmT448//lD+KgAAAPgf\nuOcPgGL89iCl1tbW7Nu374Br99xzT9588800NTXl6quvTktLS4YMGZKhQ4cmSfVW+aFDh+aFF17I\n9u3bM23atCTJuHHj0qVLlwwYMCAffPBBvvnmmxx99NHZtGlTOnXqlP79+x/GdwoAAMBfYZIUgCJV\nKpUD9gdta2tLa2trampq0rlz5+oBKI8//vgfXjt8+PDccMMNWblyZfr06ZPdu3dn27Ztue2225Ls\nP+F+zZo1OfbYY/PZZ5+lR48e6dev3+F5YwAAAPxlIikAZP8k6e/3MW1ra0tbW9sfDlu67rrrMnny\n5Bx99NHVx6ZNm5azzjoro0aNyltvvZUJEyakUqlk27ZtGTBgQLp3735Y3gcAAAB/nUgKAAfRvn/p\n77W1taWhoaH6dbdu3fLYY49l9erV2bp1awYPHpxevXpl69at+frrr3PmmWcezmUDAADwFzndHgAO\nkb179+bDDz9Mr169MmDAgI5eDgAAQOkOerq9SAoAf5PW1tbq57+/RR8AAIAOJ5ICQEdoa2v701v2\nAQAAOOwO+seZMRcAOIQEUgAAgH8+kRQAAAAAKJpICgAAAAAUTSQFAAAAAIomkgIAAAAARRNJAQAA\nAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQFAAAAAIomkgIAAAAA\nRRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQFAAAAAIom\nkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQF\nAAAAAIomkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAA\nAAAUTSQFAAAAAIomkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAA\nKJpICgAAAAAUTSQFAAAAAIomkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0\nkRQAAAAAKJpICgAAAAAUTSQFAAAAAIomkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIp\nAAAAAFA0kRQAAAAAKJpICgAAdIM3EwAAATRJREFUAAAUTSQFAAAAAIomkgIAAAAARRNJAQAAAICi\niaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQFAAAAAIomkgIAAAAARRNJ\nAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQFAAAAAIomkgIA\nAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFA0kRQAAAAAKJpICgAAAAAUTSQFAAAA\nAIomkgIAAAAARRNJAQAAAICiiaQAAAAAQNFEUgAAAACgaCIpAAAAAFC0Tv/les1hWQUAAAAAQAcx\nSQoAAAAAFE0kBQAAAACKJpICAAAAAEUTSQEAAACAoomkAAAAAEDRRFIAAAAAoGj/BhY98e/GbnlU\nAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f930add3e50>"
+       "<matplotlib.figure.Figure at 0x7f6886e35e10>"
       ]
      },
      "metadata": {},
@@ -862,7 +939,7 @@
    ],
    "source": [
     "# custom number of clusters\n",
-    "num_clusters = 9\n",
+    "num_clusters = 6\n",
     "clusters = get_clustering_model(X, num_clusters)\n",
     "plot3([0,1,2], X, clusters, -1)"
    ]
@@ -883,7 +960,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 49,
    "metadata": {
     "code_folding": [],
     "collapsed": false
@@ -904,7 +981,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"5900bc1c-4c80-4ace-89aa-89708c98ce91\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -952,9 +1029,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2\");\n",
+       "    };var element = document.getElementById(\"5900bc1c-4c80-4ace-89aa-89708c98ce91\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '5900bc1c-4c80-4ace-89aa-89708c98ce91' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -963,8 +1040,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
-       "            var docs_json = {\"8b858ebf-6331-4918-bbb1-9f181e4874bb\":{\"roots\":{\"references\":[{\"attributes\":{\"axis_label\":\"IP 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+       "            var render_items = [{\"docid\":\"2ef40c30-3fec-4e91-add9-60425af850ef\",\"elementid\":\"5900bc1c-4c80-4ace-89aa-89708c98ce91\",\"modelid\":\"a10ff395-7821-41f8-8b3c-dc4c78b4afee\",\"notebook_comms_target\":\"5a79cd2d-949f-40ce-92c4-2313329eb961\"}];\n",
        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -1034,7 +1111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 99,
    "metadata": {
     "collapsed": false
    },
@@ -1043,10 +1120,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning: Setting a fixed font size value as a string '10pt' is deprecated, set with value('10pt') or ['10pt'] instead\n",
-      "  value = self.descriptor.prepare_value(obj.__class__, self.name, value)\n",
-      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning: Setting a fixed font size value as a string '14pt' is deprecated, set with value('14pt') or ['14pt'] instead\n",
-      "  value = self.descriptor.prepare_value(obj.__class__, self.name, value)\n"
+      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning:\n",
+      "\n",
+      "Setting a fixed font size value as a string '10pt' is deprecated, set with value('10pt') or ['10pt'] instead\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning:\n",
+      "\n",
+      "Setting a fixed font size value as a string '14pt' is deprecated, set with value('14pt') or ['14pt'] instead\n",
+      "\n"
      ]
     },
     {
@@ -1054,7 +1135,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"bb92ccdf-b43e-437f-8b58-3bc989711238\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -1102,9 +1183,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"bb92ccdf-b43e-437f-8b58-3bc989711238\");\n",
+       "    };var element = document.getElementById(\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'bb92ccdf-b43e-437f-8b58-3bc989711238' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '538b9546-3c95-4f1f-a6f7-ac63b1de4284' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -1113,8 +1194,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
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Application\",\"version\":\"0.11.1\"}};\n",
+       "            var render_items = [{\"docid\":\"22f9e79e-f48c-45ac-8357-778718d8476f\",\"elementid\":\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\",\"modelid\":\"65e48372-8f9a-455a-987f-a59d9cc84296\",\"notebook_comms_target\":\"68563ce1-606d-4a8c-aff0-c3f660810c72\"}];\n",
        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -1149,29 +1230,47 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning: Comm._comm_id_default is deprecated: use @default decorator instead.\n",
-      "  def _comm_id_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:29: DeprecationWarning: Comm._iopub_socket_default is deprecated: use @default decorator instead.\n",
-      "  def _iopub_socket_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning: Comm._kernel_default is deprecated: use @default decorator instead.\n",
-      "  def _kernel_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning: Comm._session_default is deprecated: use @default decorator instead.\n",
-      "  def _session_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
-      "  def _topic_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning: Comm._kernel_default is deprecated: use @default decorator instead.\n",
-      "  def _kernel_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning: Comm._comm_id_default is deprecated: use @default decorator instead.\n",
-      "  def _comm_id_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning: Comm._session_default is deprecated: use @default decorator instead.\n",
-      "  def _session_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
-      "  def _topic_default(self):\n"
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning:\n",
+      "\n",
+      "Comm._comm_id_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:29: DeprecationWarning:\n",
+      "\n",
+      "Comm._iopub_socket_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning:\n",
+      "\n",
+      "Comm._kernel_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning:\n",
+      "\n",
+      "Comm._session_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning:\n",
+      "\n",
+      "Comm._topic_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning:\n",
+      "\n",
+      "Comm._kernel_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning:\n",
+      "\n",
+      "Comm._comm_id_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning:\n",
+      "\n",
+      "Comm._session_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning:\n",
+      "\n",
+      "Comm._topic_default is deprecated: use @default decorator instead.\n",
+      "\n"
      ]
     }
    ],
    "source": [
-    "#num_clusters = 15\n",
+    "#num_clusters = 14\n",
     "#clusters = get_clustering_model(X, num_clusters)\n",
     "\n",
     "plot_countries(clusters, num_clusters, sessions, 8)"
@@ -1186,17 +1285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
-   "metadata": {
-    "code_folding": [],
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 158,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
@@ -1216,7 +1305,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"81ae9179-987c-46e1-8a7f-2ea4df9c21fe\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"a371810e-3345-462a-8c03-13ff7adddd24\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -1264,9 +1353,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"81ae9179-987c-46e1-8a7f-2ea4df9c21fe\");\n",
+       "    };var element = document.getElementById(\"a371810e-3345-462a-8c03-13ff7adddd24\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '81ae9179-987c-46e1-8a7f-2ea4df9c21fe' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a371810e-3345-462a-8c03-13ff7adddd24' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -1275,8 +1364,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
-       "            var docs_json = 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+       "            var render_items = [{\"docid\":\"226c40ad-5bb4-43e4-b24a-053c4fc9b6e0\",\"elementid\":\"a371810e-3345-462a-8c03-13ff7adddd24\",\"modelid\":\"0c39dcab-f4a6-4862-b1c9-fe77dce7091f\",\"notebook_comms_target\":\"a739f3c9-e01d-4042-b371-61f0701fb085\"}];\n",
        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -1307,14 +1396,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[4, 0, 0, 92]\n",
-      "[0.08, 0.0, 0.0, 5.18]\n"
-     ]
-    },
     {
      "name": "stderr",
      "output_type": "stream",
@@ -1338,6 +1419,14 @@
       "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
       "  def _topic_default(self):\n"
      ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[468, 0, 3]\n",
+      "[63.33, 0.0, 20.0]\n"
+     ]
     }
    ],
    "source": [
@@ -1388,6 +1477,84 @@
     "tools.save_selected_cluster(id_incident, selected_cluster)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "code_folding": [],
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function a(t,e){var r=e[0],n=e[1],a=e[2],o=e[3],s=i(r,n,a,o);s>1e-6?(t[0]=r/s,t[1]=n/s,t[2]=a/s,t[3]=o/s):(t[0]=t[1]=t[2]=0,t[3]=1)}function o(t,e,r){this.radius=l([r]),this.center=l(e),this.rotation=l(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),r=[].slice.call(r,0,4),a(r,r);var i=new o(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/lookAt\"),c=t(\"gl-mat4/fromQuat\"),f=t(\"gl-mat4/invert\"),h=t(\"./lib/quatFromFrame\"),p=o.prototype;p.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},p.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;a(e,e);var r=this.computedMatrix;c(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;3>l;++l){for(var u=0,f=0;3>f;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r},p.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},p.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},p.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=a[1],s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=a[2],v=a[6],m=a[10],y=g*o+v*s+m*l,b=g*c+v*f+m*h;g-=y*o+b*c,v-=y*s+b*f,m-=y*l+b*h;var x=n(g,v,m);g/=x,v/=x,m/=x;var _=c*e+o*r,w=f*e+s*r,k=h*e+l*r;this.center.move(t,_,w,k);var A=Math.exp(this.computedRadius[0]);A=Math.max(1e-4,A+i),this.radius.set(t,Math.log(A))},p.rotate=function(t,e,r,a){this.recalcMatrix(t),e=e||0,r=r||0;var o=this.computedMatrix,s=o[0],l=o[4],u=o[8],c=o[1],f=o[5],h=o[9],p=o[2],d=o[6],g=o[10],v=e*s+r*c,m=e*l+r*f,y=e*u+r*h,b=-(d*y-g*m),x=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(b,2)-Math.pow(x,2)-Math.pow(_,2))),k=i(b,x,_,w);k>1e-6?(b/=k,x/=k,_/=k,w/=k):(b=x=_=0,w=1);var A=this.computedRotation,M=A[0],T=A[1],E=A[2],L=A[3],S=M*w+L*b+T*_-E*x,C=T*w+L*x+E*b-M*_,P=E*w+L*_+M*x-T*b,z=L*w-M*b-T*x-E*_;if(a){b=p,x=d,_=g;var R=Math.sin(a)/n(b,x,_);b*=R,x*=R,_*=R,w=Math.cos(e),S=S*w+z*b+C*_-P*x,C=C*w+z*x+P*b-S*_,P=P*w+z*_+S*x-C*b,z=z*w-S*b-C*x-P*_}var O=i(S,C,P,z);O>1e-6?(S/=O,C/=O,P/=O,z/=O):(S=C=P=0,z=1),this.rotation.set(t,S,C,P,z)},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;u(i,e,r,n);var o=this.computedRotation;h(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),a(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var s=0,l=0;3>l;++l)s+=Math.pow(r[l]-e[l],2);this.radius.set(t,.5*Math.log(Math.max(s,1e-6))),this.center.set(t,r[0],r[1],r[2])},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e){var r=this.computedRotation;h(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),a(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;f(n,e);var i=n[15];if(Math.abs(i)>1e-6){var o=n[12]/i,s=n[13]/i,l=n[14]/i;this.recalcMatrix(t);var u=Math.exp(this.computedRadius[0]);this.center.set(t,o-n[2]*u,s-n[6]*u,l-n[10]*u),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},p.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var i=t.distance;i&&i>0&&this.radius.set(e,Math.log(i)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":16,\"filtered-vector\":17,\"gl-mat4/fromQuat\":183,\"gl-mat4/invert\":186,\"gl-mat4/lookAt\":187}],21:[function(t,e,r){arguments[4][17][0].apply(r,arguments)},{\"binary-search-bounds\":22,\"cubic-hermite\":23,dup:17}],22:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],23:[function(t,e,r){arguments[4][19][0].apply(r,arguments)},{dup:19}],24:[function(t,e,r){arguments[4][5][0].apply(r,arguments)},{dup:5}],25:[function(t,e,r){arguments[4][6][0].apply(r,arguments)},{dup:6}],26:[function(t,e,r){arguments[4][9][0].apply(r,arguments)},{dup:9}],27:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t){return Math.min(1,Math.max(-1,t))}function a(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),i=[0,0,0];e>Math.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,s=0;3>s;++s)a+=t[s]*t[s],o+=i[s]*t[s];for(var s=0;3>s;++s)i[s]-=o/a*t[s];return h(i,i),i}function o(t,e,r,n,i,a,o,s){this.center=l(r),this.up=l(n),this.right=l(i),this.radius=l([a]),this.angle=l([o,s]),this.angle.bounds=[[-(1/0),-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;16>u;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.up||[0,1,0],i=t.right||a(r),s=t.radius||1,l=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),h(r,r),i=[].slice.call(i,0,3),h(i,i),\"eye\"in t){var c=t.eye,d=[c[0]-e[0],c[1]-e[1],c[2]-e[2]];f(i,d,r),n(i[0],i[1],i[2])<1e-6?i=a(r):h(i,i),s=n(d[0],d[1],d[2]);var g=p(r,d)/s,v=p(i,d)/s;u=Math.acos(g),l=Math.acos(v)}return s=Math.log(s),new o(t.zoomMin,t.zoomMax,e,r,i,s,l,u)}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/invert\"),c=t(\"gl-mat4/rotate\"),f=t(\"gl-vec3/cross\"),h=t(\"gl-vec3/normalize\"),p=t(\"gl-vec3/dot\"),d=o.prototype;d.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},d.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},d.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,i=0,a=0,o=0;3>o;++o)a+=e[o]*r[o],i+=e[o]*e[o];for(var s=Math.sqrt(i),l=0,o=0;3>o;++o)r[o]-=e[o]*a/i,l+=r[o]*r[o],e[o]/=s;for(var u=Math.sqrt(l),o=0;3>o;++o)r[o]/=u;var c=this.computedToward;f(c,e,r),h(c,c);for(var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),b=Math.sin(g),x=this.computedCenter,_=v*y,w=m*y,k=b,A=-v*b,M=-m*b,T=y,E=this.computedEye,L=this.computedMatrix,o=0;3>o;++o){var S=_*r[o]+w*c[o]+k*e[o];L[4*o+1]=A*r[o]+M*c[o]+T*e[o],L[4*o+2]=S,L[4*o+3]=0}var C=L[1],P=L[5],z=L[9],R=L[2],O=L[6],I=L[10],j=P*I-z*O,N=z*R-C*I,F=C*O-P*R,D=n(j,N,F);j/=D,N/=D,F/=D,L[0]=j,L[4]=N,L[8]=F;for(var o=0;3>o;++o)E[o]=x[o]+L[2+4*o]*p;for(var o=0;3>o;++o){for(var l=0,B=0;3>B;++B)l+=L[o+4*B]*E[B];L[12+o]=-l}L[15]=1},d.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r};var g=[0,0,0];d.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;g[0]=i[2],g[1]=i[6],g[2]=i[10];for(var a=this.computedUp,o=this.computedRight,s=this.computedToward,l=0;3>l;++l)i[4*l]=a[l],i[4*l+1]=o[l],i[4*l+2]=s[l];c(i,i,n,g);for(var l=0;3>l;++l)a[l]=i[4*l],o[l]=i[4*l+1];this.up.set(t,a[0],a[1],a[2]),this.right.set(t,o[0],o[1],o[2])}},d.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=(Math.exp(this.computedRadius[0]),a[1]),s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=c*e+o*r,v=f*e+s*r,m=h*e+l*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+i),this.radius.set(t,Math.log(y))},d.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},d.setMatrix=function(t,e,r,a){var o=1;\"number\"==typeof r&&(o=0|r),(0>o||o>3)&&(o=1);var s=(o+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var l=e[o],c=e[o+4],f=e[o+8];if(a){var h=Math.abs(l),p=Math.abs(c),d=Math.abs(f),g=Math.max(h,p,d);h===g?(l=0>l?-1:1,c=f=0):d===g?(f=0>f?-1:1,l=c=0):(c=0>c?-1:1,l=f=0)}else{var v=n(l,c,f);l/=v,c/=v,f/=v}var m=e[s],y=e[s+4],b=e[s+8],x=m*l+y*c+b*f;m-=l*x,y-=c*x,b-=f*x;var _=n(m,y,b);m/=_,y/=_,b/=_;var w=c*b-f*y,k=f*m-l*b,A=l*y-c*m,M=n(w,k,A);w/=M,k/=M,A/=M,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,l,c,f),this.right.jump(t,m,y,b);var T,E;if(2===o){var L=e[1],S=e[5],C=e[9],P=L*m+S*y+C*b,z=L*w+S*k+C*A;T=0>j?-Math.PI/2:Math.PI/2,E=Math.atan2(z,P)}else{var R=e[2],O=e[6],I=e[10],j=R*l+O*c+I*f,N=R*m+O*y+I*b,F=R*w+O*k+I*A;T=Math.asin(i(j)),E=Math.atan2(F,N)}this.angle.jump(t,E,T),this.recalcMatrix(t);var D=e[2],B=e[6],U=e[10],V=this.computedMatrix;u(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,Y=V[14]/q,X=Math.exp(this.computedRadius[0]);this.center.jump(t,H-D*X,G-B*X,Y-U*X)},d.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},d.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},d.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},d.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},d.lookAt=function(t,e,r,a){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter,a=a||this.computedUp;var o=a[0],s=a[1],l=a[2],u=n(o,s,l);if(!(1e-6>u)){o/=u,s/=u,l/=u;var c=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=n(c,f,h);if(!(1e-6>p)){c/=p,f/=p,h/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=o*g+s*v+l*m;g-=y*o,v-=y*s,m-=y*l;var b=n(g,v,m);if(!(.01>b&&(g=s*h-l*f,v=l*c-o*h,m=o*f-s*c,b=n(g,v,m),1e-6>b))){g/=b,v/=b,m/=b,this.up.set(t,o,s,l),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var x=s*m-l*v,_=l*g-o*m,w=o*v-s*g,k=n(x,_,w);x/=k,_/=k,w/=k;var A=o*c+s*f+l*h,M=g*c+v*f+m*h,T=x*c+_*f+w*h,E=Math.asin(i(A)),L=Math.atan2(T,M),S=this.angle._state,C=S[S.length-1],P=S[S.length-2];C%=2*Math.PI;var z=Math.abs(C+2*Math.PI-L),R=Math.abs(C-L),O=Math.abs(C-2*Math.PI-L);R>z&&(C+=2*Math.PI),R>O&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,L,E)}}}}},{\"filtered-vector\":21,\"gl-mat4/invert\":186,\"gl-mat4/rotate\":190,\"gl-vec3/cross\":24,\"gl-vec3/dot\":25,\"gl-vec3/normalize\":26}],28:[function(t,e,r){\"use strict\";function n(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return t[e]}),this._mode=e,this._active=t[e],this._active||(this._mode=\"turntable\",this._active=t.turntable),this.modes=this._controllerNames,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}function i(t){t=t||{};var e=t.eye||[0,0,1],r=t.center||[0,0,0],i=t.up||[0,1,0],l=t.distanceLimits||[0,1/0],u=t.mode||\"turntable\",c=a(),f=o(),h=s();return c.setDistanceLimits(l[0],l[1]),c.lookAt(0,e,r,i),f.setDistanceLimits(l[0],l[1]),f.lookAt(0,e,r,i),h.setDistanceLimits(l[0],l[1]),h.lookAt(0,e,r,i),new n({turntable:c,orbit:f,matrix:h},u)}e.exports=i;var a=t(\"turntable-camera-controller\"),o=t(\"orbit-camera-controller\"),s=t(\"matrix-camera-controller\"),l=n.prototype,u=[[\"flush\",1],[\"idle\",1],[\"lookAt\",4],[\"rotate\",4],[\"pan\",4],[\"translate\",4],[\"setMatrix\",2],[\"setDistanceLimits\",2],[\"setDistance\",2]];u.forEach(function(t){for(var e=t[0],r=[],n=0;n<t[1];++n)r.push(\"a\"+n);var i=\"var cc=this._controllerList;for(var i=0;i<cc.length;++i){cc[i].\"+t[0]+\"(\"+r.join()+\")}\";l[e]=Function.apply(null,r.concat(i))}),l.recalcMatrix=function(t){this._active.recalcMatrix(t)},l.getDistance=function(t){return this._active.getDistance(t)},l.getDistanceLimits=function(t){return this._active.getDistanceLimits(t)},l.lastT=function(){return this._active.lastT()},l.setMode=function(t){if(t!==this._mode){var e=this._controllerNames.indexOf(t);if(!(0>e)){var r=this._active,n=this._controllerList[e],i=Math.max(r.lastT(),n.lastT());r.recalcMatrix(i),n.setMatrix(i,r.computedMatrix),this._active=n,this._mode=t,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}}},l.getMode=function(){return this._mode}},{\"matrix-camera-controller\":3,\"orbit-camera-controller\":20,\"turntable-camera-controller\":27}],29:[function(t,e,r){e.exports=function(t,e){e||(e=[0,\"\"]),t=String(t);var r=parseFloat(t,10);\n",
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i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);o>=s;s++){var l=n-s,u=this.words[l],c=t.words[s],f=u*c,h=67108863&f;i+=f/67108864|0,h+=a,a=67108863&h,i+=h>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var p=this.words[l]+i;this.words[l]=67108863&p,i=p>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var 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a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),0>t?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],\n",
+       "this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),0>t)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(-1===s),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var f=n.clone()._ishlnsubmul(a,1,u);f.sign||(n=f,l&&(l.words[u]=1));for(var h=u-1;h>=0;h--){var p=67108864*n.words[a.length+h]+n.words[a.length+h-1];for(p=Math.min(p/o|0,67108863),n._ishlnsubmul(a,p,h);n.sign;)p--,n.sign=!1,n._ishlnsubmul(a,1,h),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[h]=p)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return 0>a||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(67108863>=t);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(67108863>=t);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),f=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(f).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(f).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(0>i){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;n+1>a;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=0>t;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:t>n?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){i>n?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new h(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;n>i;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(f,s),f.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function y(t){if(m[t])return m[t];var y;if(\"k256\"===t)y=new l;else if(\"p224\"===t)y=new u;else if(\"p192\"===t)y=new c;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);y=new f}return m[t]=y,y},h.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},h.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},h.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},h.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},h.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},h.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},h.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},h.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},h.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},h.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},h.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},h.prototype.isqr=function(t){return this.imul(t,t)},h.prototype.sqr=function(t){return this.mul(t,t)},h.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),f=this.m.bitLength();for(f=new i(2*f*f).toRed(this);0!==this.pow(f,c).cmp(u);)f.redIAdd(u);for(var h=this.pow(f,o),a=this.pow(t,o.addn(1).ishrn(1)),p=this.pow(t,o),d=s;0!==p.cmp(l);){for(var g=p,v=0;0!==g.cmp(l);v++)g=g.redSqr();r(d>v);var m=this.pow(h,new i(1).ishln(d-v-1));a=a.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return a},h.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},h.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},h.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},h.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new p(t)},n(p,h),p.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},p.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},p.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},p.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).ishrn(this.shift),o=a;return a.cmp(this.m)>=0?o=a.isub(this.m):a.cmpn(0)<0&&(o=a.iadd(this.m)),o._forceRed(this)},p.prototype.invm=function(t){var e=this.imod(t._invmp(this.m).mul(this.r2));return e._forceRed(this)}}(\"undefined\"==typeof e||e,this)},{}],110:[function(t,e,r){(function(t){function r(t,e){return p[0]=t,p[1]=e,h[0]}function n(t){return h[0]=t,p[0]}function i(t){return h[0]=t,p[1]}function a(t,e){return p[1]=t,p[0]=e,h[0]}function o(t){return h[0]=t,p[1]}function s(t){return h[0]=t,p[0]}function l(t,e){return 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m=r.getExtension(\"WEBGL_depth_texture\");m?p?t.depth=s(r,u,c,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):d&&p?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):p&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var b=r.checkFramebufferStatus(r.FRAMEBUFFER);if(b!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(var v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(b)}i(r,e)}function c(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var l=0;i>l;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,f=[0|e,0|r];Object.defineProperties(f,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=f,u(this)}function f(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(0>e||e>s||0>r||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function h(t,e,r,n){d||(d=t.FRAMEBUFFER_UNSUPPORTED,g=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,v=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,m=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(0>e||e>o||0>r||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");n=n||{};var s=1;if(\"color\"in n){if(s=Math.max(0|n.color,0),0>s)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var f=!0;\"depth\"in n&&(f=!!n.depth);var h=!1;return\"stencil\"in n&&(h=!!n.stencil),new c(t,e,r,l,s,f,h,i)}var p=t(\"gl-texture2d\");e.exports=h;var d,g,v,m,y=null,b=c.prototype;Object.defineProperties(b,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return f(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t=0|t,f(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t=0|t,f(this,this._shape[0],t),t},enumerable:!1}}),b.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},b.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":179}],171:[function(t,e,r){arguments[4][34][0].apply(r,arguments)},{\"cwise-compiler\":172,dup:34}],172:[function(t,e,r){arguments[4][35][0].apply(r,arguments)},{\"./lib/thunk.js\":174,dup:35}],173:[function(t,e,r){arguments[4][36][0].apply(r,arguments)},{dup:36,uniq:175}],174:[function(t,e,r){arguments[4][37][0].apply(r,arguments)},{\"./compile.js\":173,dup:37}],175:[function(t,e,r){arguments[4][38][0].apply(r,arguments)},{dup:38}],176:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],177:[function(t,e,r){arguments[4][40][0].apply(r,arguments)},{dup:40}],178:[function(t,e,r){arguments[4][41][0].apply(r,arguments)},{\"bit-twiddle\":176,buffer:300,dup:41}],179:[function(t,e,r){\"use strict\";function 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l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}function o(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function s(t,e,r,n,i,a,s,l){var u=l.dtype,c=l.shape.slice();if(c.length<2||c.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var f=0,h=0,v=o(c,l.stride.slice());\"float32\"===u?f=t.FLOAT:\"float64\"===u?(f=t.FLOAT,v=!1,u=\"float32\"):\"uint8\"===u?f=t.UNSIGNED_BYTE:(f=t.UNSIGNED_BYTE,v=!1,u=\"uint8\");var m=1;if(2===c.length)h=t.LUMINANCE,c=[c[0],c[1],1],l=p(l.data,c,[l.stride[0],l.stride[1],1],l.offset);else{if(3!==c.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===c[2])h=t.ALPHA;else if(2===c[2])h=t.LUMINANCE_ALPHA;else if(3===c[2])h=t.RGB;else{if(4!==c[2])throw new Error(\"gl-texture2d: Invalid shape for pixel 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s=o(n,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,s=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,s=!1,r=\"uint8\");var c=0;if(2===n.length)c=t.LUMINANCE,n=[n[0],n[1],1],e=p(e.data,n,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==n.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===n[2])c=t.ALPHA;else if(2===n[2])c=t.LUMINANCE_ALPHA;else if(3===n[2])c=t.RGB;else{if(4!==n[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");c=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,s=!1);var f,h,v=e.size;if(s)f=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var m=[n[2],n[2]*n[0],1];h=g.malloc(v,r);var y=p(h,n,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?d.assign(y,e):b(y,e),f=h.subarray(0,v)}var x=l(t);return t.texImage2D(t.TEXTURE_2D,0,c,n[0],n[1],0,c,u,f),s||g.free(h),new a(t,x,n[0],n[1],c,u)}function 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this._wrapS},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;2>e;++e)if(y.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return i(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return t=0|t,i(this,t,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t=0|t,i(this,this._shape[0],t),t}}}),x.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},x.dispose=function(){this.gl.deleteTexture(this.handle)},x.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},x.setPixels=function(t,e,r,n){var i=this.gl;if(this.bind(),Array.isArray(e)?(n=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),n=n||0,t instanceof 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t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(c+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],185:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],186:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,k=i*u-a*l,A=c*g-f*d,M=c*v-h*d,T=c*m-p*d,E=f*v-h*g,L=f*m-p*g,S=h*m-p*v,C=y*S-b*L+x*E+_*T-w*M+k*A;return 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i=t(\"./identity\");e.exports=n},{\"./identity\":185}],188:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*f+w*g,t[1]=b*i+x*l+_*h+w*v,t[2]=b*a+x*u+_*p+w*m,t[3]=b*o+x*c+_*d+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*f+w*g,t[5]=b*i+x*l+_*h+w*v,t[6]=b*a+x*u+_*p+w*m,t[7]=b*o+x*c+_*d+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*f+w*g,t[9]=b*i+x*l+_*h+w*v,t[10]=b*a+x*u+_*p+w*m,t[11]=b*o+x*c+_*d+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*f+w*g,t[13]=b*i+x*l+_*h+w*v,t[14]=b*a+x*u+_*p+w*m,t[15]=b*o+x*c+_*d+w*y,t}e.exports=n},{}],189:[function(t,e,r){function n(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}e.exports=n},{}],190:[function(t,e,r){function n(t,e,r,n){var 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n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;3>r;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=h[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],f=n.prototype;f.isOpaque=function(){return this.opacity>=1},f.isTransparent=function(){return this.opacity<1},f.drawTransparent=f.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var f=0;3>f;++f)e.lineWidth(this.lineWidth[f]),r.capSize=this.capSize[f]*u,e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var h=function(){for(var t=new Array(3),e=0;3>e;++e){for(var r=[],n=1;2>=n;++n)for(var i=-1;1>=i;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();f.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;3>u;++u){this.lineOffset[u]=l;t:for(var c=0;s>c;++c){for(var f=r[c],h=0;3>h;++h)if(isNaN(f[h])||!isFinite(f[h]))continue t;var p=n[c],d=e[u];if(Array.isArray(d[0])&&(d=e[c]),3===d.length&&(d=[d[0],d[1],d[2],1]),!isNaN(p[0][u])&&!isNaN(p[1][u])){if(p[0][u]<0){var g=f.slice();g[u]+=p[0][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}if(p[1][u]>0){var g=f.slice();g[u]+=p[1][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},f.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":329,\"gl-buffer\":325,\"gl-vao\":420}],329:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":385}],330:[function(t,e,r){arguments[4][170][0].apply(r,arguments)},{dup:170,\"gl-texture2d\":416}],331:[function(t,e,r){r.lineVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  vec2 dir = (matrix * vec3(d, 0)).xy;\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = 0.5 * width *\\n    normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n}\\n\",r.lineFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\\n\",r.mitreVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 p;\\n\\nuniform mat3  matrix;\\nuniform vec2 screenShape;\\nuniform float radius;\\n\\nvoid main() {\\n  vec3 pp = matrix * vec3(p, 1);\\n  gl_Position  = vec4(pp.xy, 0, pp.z);\\n  gl_PointSize = radius;\\n}\\n\",r.mitreFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\nattribute vec4 pick0, pick1;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = width *\\n    normalize(screenShape.yx * vec2(d.y, -d.x)) / screenShape.xy;\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\\n\",r.fillVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 projectAxis;\\nuniform float projectValue;\\nuniform float depth;\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 p = base.xy / base.z;\\n  if(d.y < 0.0 || (d.y == 0.0 && d.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\\n\",r.fillFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"},{}],332:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.dashPattern=e,this.lineBuffer=r,this.pickBuffer=n,this.lineShader=i,this.mitreShader=a,this.fillShader=o,this.pickShader=s,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0,this.lodBuffer=[]}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=l(r,[1,1]),c=o(r,f.lineVertex,f.lineFragment),h=o(r,f.mitreVertex,f.mitreFragment),p=o(r,f.fillVertex,f.fillFragment),d=o(r,f.pickVertex,f.pickFragment),g=new n(t,u,i,a,c,h,p,d);return t.addObject(g),g.update(e),g}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),f=t(\"./lib/shaders\"),h=n.prototype;h.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[1,0],n=[-1,0],i=[0,1],a=[0,-1];return function(){var o=this.plot,s=this.color,l=this.width,u=(this.numPoints,this.bounds),c=this.vertCount,f=o.gl,h=o.viewBox,p=o.dataBox,d=o.pixelRatio,g=u[2]-u[0],v=u[3]-u[1],m=p[2]-p[0],y=p[3]-p[1],b=h[2]-h[0],x=h[3]-h[1];t[0]=2*g/m,t[4]=2*v/y,t[6]=2*(u[0]-p[0])/m-1,t[7]=2*(u[1]-p[1])/y-1,e[0]=b,e[1]=x;var _=this.lineBuffer;_.bind();var w=this.fill;if(w[0]||w[1]||w[2]||w[3]){var k=this.fillShader;k.bind();var A=k.uniforms;A.matrix=t,A.depth=o.nextDepthValue();var M=k.attributes;M.a.pointer(f.FLOAT,!1,16,0),M.d.pointer(f.FLOAT,!1,16,8),f.depthMask(!0),f.enable(f.DEPTH_TEST);var T=this.fillColor;w[0]&&(A.color=T[0],A.projectAxis=n,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[1]&&(A.color=T[1],A.projectAxis=a,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[2]&&(A.color=T[2],A.projectAxis=r,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[3]&&(A.color=T[3],A.projectAxis=i,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),f.depthMask(!1),f.disable(f.DEPTH_TEST)}var E=this.lineShader;E.bind();var L=E.uniforms;L.matrix=t,L.color=s,L.width=l*d,L.screenShape=e,L.dashPattern=this.dashPattern.bind(),L.dashLength=this.dashLength*d;var S=E.attributes;if(S.a.pointer(f.FLOAT,!1,16,0),S.d.pointer(f.FLOAT,!1,16,8),f.drawArrays(f.TRIANGLES,0,c),l>2&&!this.usingDashes){var C=this.mitreShader;C.bind();var P=C.uniforms;P.matrix=t,P.color=s,P.screenShape=e,P.radius=l*d,C.attributes.p.pointer(f.FLOAT,!1,48,0),f.drawArrays(f.POINTS,0,c/3|0)}}}(),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[0,0,0,0];return function(n){var i=this.plot,a=this.pickShader,o=this.lineBuffer,s=this.pickBuffer,l=this.width,u=this.numPoints,c=this.bounds,f=this.vertCount,h=i.gl,p=i.viewBox,d=i.dataBox,g=i.pickPixelRatio,v=c[2]-c[0],m=c[3]-c[1],y=d[2]-d[0],b=d[3]-d[1],x=p[2]-p[0],_=p[3]-p[1];\n",
+       "this.pickOffset=n,t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(c[0]-d[0])/y-1,t[7]=2*(c[1]-d[1])/b-1,e[0]=x,e[1]=_,r[0]=255&n,r[1]=n>>>8&255,r[2]=n>>>16&255,r[3]=n>>>24,a.bind();var w=a.uniforms;w.matrix=t,w.width=l*g,w.pickOffset=r,w.screenShape=e;var k=a.attributes;return o.bind(),k.a.pointer(h.FLOAT,!1,16,0),k.d.pointer(h.FLOAT,!1,16,8),s.bind(),k.pick0.pointer(h.UNSIGNED_BYTE,!1,8,0),k.pick1.pointer(h.UNSIGNED_BYTE,!1,8,4),h.drawArrays(h.TRIANGLES,0,f),n+u}}(),h.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},h.update=function(t){t=t||{};var e=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);for(var r=t.dashes||[1],n=0,a=0;a<r.length;++a)n+=r[a];for(var o=c.mallocUint8(n),s=0,f=255,a=0;a<r.length;++a){for(var h=0;h<r[a];++h)o[s++]=f;f^=255}this.dashPattern.dispose(),this.usingDashes=r.length>1,this.dashPattern=l(e,u(o,[n,1,4],[1,0,0])),this.dashPattern.minFilter=e.NEAREST,this.dashPattern.magFilter=e.NEAREST,this.dashLength=n,c.free(o);var p=t.positions;this.data=p;var d=this.bounds;d[0]=d[1]=1/0,d[2]=d[3]=-(1/0);var g=this.numPoints=p.length>>>1;if(0!==g){for(var a=0;g>a;++a){var v=p[2*a],m=p[2*a+1];d[0]=Math.min(d[0],v),d[1]=Math.min(d[1],m),d[2]=Math.max(d[2],v),d[3]=Math.max(d[3],m)}d[0]===d[2]&&(d[2]+=1),d[3]===d[1]&&(d[3]+=1);var y=c.mallocFloat32(24*(g-1)),b=c.mallocUint32(12*(g-1)),x=y.length,_=b.length,s=g;for(this.vertCount=6*(g-1);s>1;){var w=--s,v=p[2*s],m=p[2*s+1];v=(v-d[0])/(d[2]-d[0]),m=(m-d[1])/(d[3]-d[1]);var k=w-1,A=p[2*k],M=p[2*k+1];A=(A-d[0])/(d[2]-d[0]),M=(M-d[1])/(d[3]-d[1]);var T=A-v,E=M-m,L=w|1<<24,S=w-1,C=w,P=w-1|1<<24;y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S}this.lineBuffer.update(y),this.pickBuffer.update(b),c.free(y),c.free(b)}},h.dispose=function(){this.plot.removeObject(this),this.lineBuffer.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":331,\"gl-buffer\":325,\"gl-shader\":385,\"gl-texture2d\":416,ndarray:438,\"typedarray-pool\":463}],333:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":385}],334:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;3>n;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;3>r;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=v(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=p(new Array(1024),[256,1,4]),f=0;1024>f;++f)s.data[f]=255;var h=c(e,s);h.wrap=e.REPEAT;var d=new o(e,r,n,i,a,h);return d.update(t),d}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),f=t(\"glsl-read-float\"),h=t(\"binary-search-bounds\"),p=t(\"ndarray\"),d=t(\"./lib/shaders\"),g=d.createShader,v=d.createPickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){this.dirty=!0,\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var e=t.position||t.positions;if(e){var r=t.color||t.colors||[0,0,0,1],i=t.lineWidth||1,a=[],o=[],s=[],l=0,u=0,c=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];t:for(var f=1;f<e.length;++f){var d=e[f-1],g=e[f];o.push(l),s.push(d.slice());for(var v=0;3>v;++v){if(isNaN(d[v])||isNaN(g[v])||!isFinite(d[v])||!isFinite(g[v]))continue t;c[0][v]=Math.min(c[0][v],d[v],g[v]),c[1][v]=Math.max(c[1][v],d[v],g[v])}var m,y;Array.isArray(r[0])?(m=r[f-1],y=r[f]):m=y=r,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]);var b,x;Array.isArray(i)?(b=i[f-1],x=lineWidht[f]):b=x=i;var _=l;l+=n(d,g),a.push(d[0],d[1],d[2],g[0],g[1],g[2],_,b,m[0],m[1],m[2],m[3],d[0],d[1],d[2],g[0],g[1],g[2],_,-b,m[0],m[1],m[2],m[3],g[0],g[1],g[2],d[0],d[1],d[2],l,-b,y[0],y[1],y[2],y[3],g[0],g[1],g[2],d[0],d[1],d[2],l,b,y[0],y[1],y[2],y[3]),u+=4}if(this.buffer.update(a),o.push(l),s.push(e[e.length-1].slice()),this.bounds=c,this.vertexCount=u,this.points=s,this.arcLength=o,\"dashes\"in t){var w=t.dashes,k=w.slice();k.unshift(0);for(var f=1;f<k.length;++f)k[f]=k[f-1]+k[f];for(var A=p(new Array(1024),[256,1,4]),f=0;256>f;++f){for(var v=0;4>v;++v)A.set(f,0,v,0);1&h.le(k,k[k.length-1]*f/255)?A.set(f,0,0,0):A.set(f,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=f(t.value[0],t.value[1],t.value[2],0),r=h.le(this.arcLength,e);if(0>r)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;3>u;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(.5>o?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":333,\"binary-search-bounds\":335,\"gl-buffer\":325,\"gl-texture2d\":416,\"gl-vao\":420,\"glsl-read-float\":336,ndarray:438}],335:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],336:[function(t,e,r){function n(t,e,r,n){return i[0]=n,i[1]=r,i[2]=e,i[3]=t,a[0]}e.exports=n;var i=new Uint8Array(4),a=new Float32Array(i.buffer)},{}],337:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=c*o-s*u,h=-c*a+s*l,p=u*a-o*l,d=r*f+n*h+i*p;return d?(d=1/d,t[0]=f*d,t[1]=(-c*n+i*u)*d,t[2]=(s*n-i*o)*d,t[3]=h*d,t[4]=(c*r-i*l)*d,t[5]=(-s*r+i*a)*d,t[6]=p*d,t[7]=(-u*r+n*l)*d,t[8]=(o*r-n*a)*d,t):null}e.exports=n},{}],338:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{dup:180}],339:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],340:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{dup:182}],341:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{dup:183}],342:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],343:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],344:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{dup:186}],345:[function(t,e,r){arguments[4][187][0].apply(r,arguments)},{\"./identity\":343,dup:187}],346:[function(t,e,r){arguments[4][188][0].apply(r,arguments)},{dup:188}],347:[function(t,e,r){arguments[4][190][0].apply(r,arguments)},{dup:190}],348:[function(t,e,r){arguments[4][191][0].apply(r,arguments)},{dup:191}],349:[function(t,e,r){arguments[4][192][0].apply(r,arguments)},{dup:192}],350:[function(t,e,r){arguments[4][193][0].apply(r,arguments)},{dup:193}],351:[function(t,e,r){arguments[4][194][0].apply(r,arguments)},{dup:194}],352:[function(t,e,r){arguments[4][195][0].apply(r,arguments)},{dup:195}],353:[function(t,e,r){arguments[4][196][0].apply(r,arguments)},{dup:196}],354:[function(t,e,r){\"use strict\";function n(t,e){for(var r=[0,0,0,0],n=0;4>n;++n)for(var i=0;4>i;++i)r[i]+=t[4*n+i]*e[n];return r}function i(t,e,r,i,a){for(var o=n(i,n(r,n(e,[t[0],t[1],t[2],1]))),s=0;3>s;++s)o[s]/=o[3];return[.5*a[0]*(1+o[0]),.5*a[1]*(1-o[1])]}function a(t,e){if(2===t.length){for(var r=0,n=0,i=0;2>i;++i)r+=Math.pow(e[i]-t[0][i],2),n+=Math.pow(e[i]-t[1][i],2);return r=Math.sqrt(r),n=Math.sqrt(n),1e-6>r+n?[1,0]:[n/(r+n),r/(n+r)]}if(3===t.length){var a=[0,0];return u(t[0],t[1],t[2],e,a),l(t,a)}return[]}function o(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;3>o;++o)r[o]+=a*i[o];return r}function s(t,e,r,n,s,l){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),c=0;c<t.length;++c)u[c]=i(t[c],r,n,s,l);for(var f=0,h=1/0,c=0;c<u.length;++c){for(var p=0,d=0;2>d;++d)p+=Math.pow(u[c][d]-e[d],2);h>p&&(h=p,f=c)}for(var g=a(u,e),v=0,c=0;3>c;++c){if(g[c]<-.001||g[c]>1.0001)return null;v+=g[c]}return Math.abs(v-1)>.001?null:[f,o(t,g),g]}var l=t(\"barycentric\"),u=t(\"polytope-closest-point/lib/closest_point_2d.js\");e.exports=s},{barycentric:357,\"polytope-closest-point/lib/closest_point_2d.js\":359}],355:[function(t,e,r){var n=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution_2_0(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n  \\n  if(!gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = cookTorranceSpecular_1_1(L, V, N, roughness, fresnel);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5,0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\",c=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(f_position, clipBounds[0])) || \\n     any(greaterThan(f_position, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\",f=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\",h=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\",p=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\";r.meshShader={vertex:n,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:a,fragment:o,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:s,fragment:l,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:f,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:h,fragment:p,attributes:[{name:\"position\",type:\"vec3\"}]}},{}],356:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,g,v,m,y,b,x,_,w,k,A,M,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=v,this.edgeUVs=m,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=b,this.pointColors=_,this.pointUVs=w,this.pointSizes=k,this.pointIds=x,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this._model=R,this._view=R,this._projection=R,this._resolution=[1,1]}function i(t){for(var e=w({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;256>n;++n){for(var i=e[n],a=0;3>a;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return _(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;e>i;++i)n[i]=0;for(var a=t.length,i=0;a>i;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;e>n;++n)r[n]=t[n][2];return r}function s(t){var e=d(t,E);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=d(t,L);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=d(t,S);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function c(t){var e=d(t,C);return e.attributes.position.location=0,e.attributes.id.location=1,e}function f(t){var e=d(t,P);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function h(t){var e=d(t,z);return e.attributes.position.location=0,e}function p(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),p=f(e),d=h(e),y=m(e,_(new Uint8Array([255,255,255,255]),[1,1,4]));y.generateMipmap(),y.minFilter=e.LINEAR_MIPMAP_LINEAR,y.magFilter=e.LINEAR;var b=g(e),x=g(e),w=g(e),k=g(e),A=g(e),M=v(e,[{buffer:b,type:e.FLOAT,size:3},{buffer:A,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:x,type:e.FLOAT,size:4},{buffer:w,type:e.FLOAT,size:2},{buffer:k,type:e.FLOAT,size:3}]),T=g(e),E=g(e),L=g(e),S=g(e),C=v(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:S,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:E,type:e.FLOAT,size:4},{buffer:L,type:e.FLOAT,size:2}]),P=g(e),z=g(e),R=g(e),O=g(e),I=g(e),j=v(e,[{buffer:P,type:e.FLOAT,size:3},{buffer:I,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:e.FLOAT,size:4},{buffer:R,type:e.FLOAT,size:2},{buffer:O,type:e.FLOAT,size:1}]),N=g(e),F=v(e,[{buffer:N,type:e.FLOAT,size:3}]),D=new n(e,y,r,i,a,o,p,d,b,A,x,w,k,M,T,S,E,L,C,P,I,z,R,O,j,N,F);return D.update(t),D}var d=t(\"gl-shader\"),g=t(\"gl-buffer\"),v=t(\"gl-vao\"),m=t(\"gl-texture2d\"),y=t(\"normals\"),b=t(\"gl-mat4/multiply\"),x=t(\"gl-mat4/invert\"),_=t(\"ndarray\"),w=t(\"colormap\"),k=t(\"simplicial-complex-contour\"),A=t(\"typedarray-pool\"),M=t(\"./lib/shaders\"),T=t(\"./lib/closest-point\"),E=M.meshShader,L=M.wireShader,S=M.pointShader,C=M.pickShader,P=M.pointPickShader,z=M.contourShader,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=n.prototype;O.isOpaque=function(){return this.opacity>=1},O.isTransparent=function(){return this.opacity<1},O.pickSlots=1,O.setPickBase=function(t){this.pickId=t},O.highlight=function(t){if(!t||!this.contourEnable)return void(this.contourCount=0);for(var e=k(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=A.mallocFloat32(6*a),s=0,l=0;a>l;++l)for(var u=r[l],c=0;2>c;++c){var f=u[0];2===u.length&&(f=u[c]);for(var h=n[f][0],p=n[f][1],d=i[f],g=1-d,v=this.positions[h],m=this.positions[p],y=0;3>y;++y)o[s++]=d*v[y]+g*m[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),A.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"opacity\"in t&&(this.opacity=t.opacity),t.texture?(this.texture.dispose(),this.texture=m(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],f=[],h=[],p=[],d=[],g=[],v=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var k=t.vertexNormals,A=t.cellNormals;t.useFacetNormals&&!A&&(A=y.faceNormals(r,n)),A||k||(k=y.vertexNormals(r,n));var M=t.vertexColors,T=t.cellColors,E=t.meshColor||[1,1,1,1],L=t.vertexUVs,S=t.vertexIntensity,C=t.cellUVs,P=t.cellIntensity,z=1/0,R=-(1/0);if(!L&&!C)if(S)for(var O=0;O<S.length;++O){var I=S[O];z=Math.min(z,I),R=Math.max(R,I)}else if(P)for(var O=0;O<P.length;++O){var I=P[O];z=Math.min(z,I),R=Math.max(R,I)}else for(var O=0;O<n.length;++O){var I=n[O][2];z=Math.min(z,I),R=Math.max(R,I)}S?this.intensity=S:P?this.intensity=a(r,n.length,P):this.intensity=o(n);var j=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var O=0;O<n.length;++O)for(var F=n[O],D=0;3>D;++D)!isNaN(F[D])&&isFinite(F[D])&&(this.bounds[0][D]=Math.min(this.bounds[0][D],F[D]),this.bounds[1][D]=Math.max(this.bounds[1][D],F[D]));var B=0,U=0,V=0;t:for(var O=0;O<r.length;++O){var q=r[O];switch(q.length){case 1:for(var H=q[0],F=n[H],D=0;3>D;++D)if(isNaN(F[D])||!isFinite(F[D]))continue t;v.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?b.push(G[0],G[1],G[2],1):b.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],x.push(Y[0],Y[1]),j?_.push(j[H]):_.push(N),w.push(O),V+=1;break;case 2:for(var D=0;2>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;2>D;++D){var H=q[D],F=n[H];h.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?p.push(G[0],G[1],G[2],1):p.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],d.push(Y[0],Y[1]),g.push(O)}U+=1;break;case 3:for(var D=0;3>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;3>D;++D){var H=q[D],F=n[H];s.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?l.push(G[0],G[1],G[2],1):l.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],c.push(Y[0],Y[1]);var W;W=k?k[H]:A[O],u.push(W[0],W[1],W[2]),f.push(O)}B+=1}}this.pointCount=V,this.edgeCount=U,this.triangleCount=B,this.pointPositions.update(v),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(h),this.edgeColors.update(p),this.edgeUVs.update(d),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(f))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(var o=0;3>o;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;3>o;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;3>o;++o){for(var c=l[12+o],f=0;3>f;++f)c+=l[4*f+o]*this.lightPosition[f];s.lightPosition[o]=c/u}if(this.triangleCount>0){var h=this.triShader;h.bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var h=this.lineShader;h.bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var h=this.pointShader;h.bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var h=this.contourShader;h.bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=T(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=p},{\"./lib/closest-point\":354,\"./lib/shaders\":355,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-shader\":385,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,normals:358,\"simplicial-complex-contour\":360,\"typedarray-pool\":463}],357:[function(t,e,r){\"use strict\";function n(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];\n",
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s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,f=i.dataBox,h=i.screenBox,p=i.pixelRatio,d=i.tickEnable,g=i.tickPad,v=i.tickColor,m=i.tickAngle,y=(i.tickMarkLength,i.labelEnable),b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],k=this.labelCount[n],A=l.lt(o,f[n]),M=l.le(o,f[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(h[2+n]-h[n])-1;var T=2/h[2+(1^n)]-h[1^n];e[1^n]=T*c[1^n]-1,d[n]&&(e[1^n]-=T*p*g[n],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n],a.uniforms.angle=m[n],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n]&&(e[1^n]-=T*p*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,k)),e[1^n]=T*c[2+(1^n)]-1,d[n+2]&&(e[1^n]+=T*p*g[n+2],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n+2],a.uniforms.angle=m[n+2],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n+2]&&(e[1^n]+=T*p*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,k))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){for(var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,o=r.titleCenter,u=r.pixelRatio,c=0;2>c;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;2>u;++u){var c=a[u],f=a[u+2],h=f-c,p=.5*(o[u+2]+o[u]),d=o[u+2]-o[u],g=l[u],v=l[u+2],m=v-g,y=s[u],b=s[u+2],x=b-y;e[u]=2*h/d*m/x,t[u]=2*(c-p)/d*m/x}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){for(var e=[],r=t.ticks,n=t.bounds,i=0;2>i;++i){for(var a=[Math.floor(e.length/3)],o=[-(1/0)],l=r[i],u=0;u<l.length;++u){for(var c=l[u],f=c.x,h=c.text,p=c.font||\"sans-serif\",d=c.fontSize||12,g=s(p,h).data,v=1/(n[i+2]-n[i]),m=n[i],y=0;y<g.length;y+=2)e.push(g[y]*d,-g[y+1]*d,(f-m)*v);a.push(Math.floor(e.length/3)),o.push(f)}this.tickOffset[i]=a,this.tickX[i]=o}for(var i=0;2>i;++i){this.labelOffset[i]=Math.floor(e.length/3);for(var g=s(t.labelFont[i],t.labels[i]).data,d=t.labelSize[i],u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.labelCount[i]=Math.floor(e.length/3)-this.labelOffset[i]}this.titleOffset=Math.floor(e.length/3);for(var g=s(t.titleFont,t.title).data,d=t.titleSize,u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.titleCount=Math.floor(e.length/3)-this.titleOffset,this.vbo.update(e)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458}],370:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],371:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-(1/0),-(1/0)],this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}function i(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function a(t,e){return t.x-e.x}function o(t){var e=t.gl,r=s(e,[e.drawingBufferWidth,e.drawingBufferHeight]),i=new n(e,r);return i.grid=l(i),i.text=u(i),i.line=c(i),i.box=f(i),i.update(t),i}e.exports=o;var s=t(\"gl-select-static\"),l=t(\"./lib/grid\"),u=t(\"./lib/text\"),c=t(\"./lib/line\"),f=t(\"./lib/box\"),h=n.prototype;h.setDirty=function(){this.dirty=this.pickDirty=!0},h.setOverlayDirty=function(){this.dirty=!0},h.nextDepthValue=function(){return this._depthCounter++/65536},h.draw=function(){return function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT),t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;2>d;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(var d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind();for(var d=0;2>d;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();for(var b=this.overlays,d=0;d<b.length;++d)b[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),h.drawPick=function(){return function(){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}(),h.pick=function(){return function(t,e){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){\n",
+       "var f=u[c].pick(a,o,l);if(f)return f}return null}}(),h.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},h.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},h.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},h.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;2>u;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.setDirty()},h.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},h.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},h.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},h.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},h.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":365,\"./lib/grid\":366,\"./lib/line\":367,\"./lib/text\":369,\"gl-select-static\":384}],372:[function(t,e,r){\"use strict\";e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",pickFragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],373:[function(t,e,r){\"use strict\";function n(t){if(t in h)return h[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var f=s[0]-o[0],h=s[1]-o[1],p=Math.sqrt(f*f+h*h);f/=p,h/=p,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(a[0],a[1]+1.4),n.push(h,-f),r.push(o[0],o[1]+1.4),n.push(h,-f)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;2>o;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return h[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.offsetBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,f.vertex,f.fragment),a=o(r,f.pickVertex,f.pickFragment),l=s(r),u=s(r),c=s(r),h=s(r),p=new i(t,n,a,l,u,c,h);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),f=t(\"./lib/shaders\"),h={},p=i.prototype;!function(){function t(){var t=this.plot,n=this.bounds,i=t.viewBox,a=t.dataBox,o=t.pixelRatio,s=n[2]-n[0],l=n[3]-n[1],u=a[2]-a[0],c=a[3]-a[1];e[0]=2*s/u,e[4]=2*l/c,e[6]=2*(n[0]-a[0])/u-1,e[7]=2*(n[1]-a[1])/c-1;var f=i[2]-i[0],h=i[3]-i[1];r[0]=2*o/f,r[1]=2*o/h}var e=[1,0,0,0,1,0,0,0,1],r=[1,1];p.draw=function(){var n=this.plot,i=this.shader,a=this.numVertices,o=n.gl;t.call(this),i.bind(),i.uniforms.pixelScale=r,i.uniforms.viewTransform=e,this.positionBuffer.bind(),i.attributes.position.pointer(),this.offsetBuffer.bind(),i.attributes.offset.pointer(),this.colorBuffer.bind(),i.attributes.color.pointer(o.UNSIGNED_BYTE,!0),o.drawArrays(o.TRIANGLES,0,a)};var n=[0,0,0,0];p.drawPick=function(i){var a=this.plot,o=this.pickShader,s=this.numVertices,l=a.gl;this.pickOffset=i;for(var u=0;4>u;++u)n[u]=i>>8*u&255;return t.call(this),o.bind(),o.uniforms.pixelScale=r,o.uniforms.viewTransform=e,o.uniforms.pickOffset=n,this.positionBuffer.bind(),o.attributes.position.pointer(),this.offsetBuffer.bind(),o.attributes.offset.pointer(),this.idBuffer.bind(),o.attributes.id.pointer(l.UNSIGNED_BYTE,!1),l.drawArrays(l.TRIANGLES,0,s),i+this.numPoints}}(),p.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},p.update=function(t){t=t||{};var e=t.positions||[],r=t.colors||[],i=t.glyphs||[],a=t.sizes||[],o=t.borderWidths||[],s=t.borderColors||[];this.points=e;for(var c=this.bounds=[1/0,1/0,-(1/0),-(1/0)],f=0,h=0;h<i.length;++h){f+=l(\"sans-serif\",i[h]).data.length+n(i[h]).coords.length>>1;for(var p=0;2>p;++p)c[p]=Math.min(c[p],e[2*h+p]),c[2+p]=Math.max(c[2+p],e[2*h+p])}c[0]===c[2]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);for(var d=1/(c[2]-c[0]),g=1/(c[3]-c[1]),v=c[0],m=c[1],y=u.mallocFloat32(2*f),b=u.mallocFloat32(2*f),x=u.mallocUint8(4*f),_=u.mallocUint32(f),w=0,h=0;h<i.length;++h){for(var k=l(\"sans-serif\",i[h]),A=n(i[h]),M=d*(e[2*h]-v),T=g*(e[2*h+1]-m),E=a[h],L=255*r[4*h],S=255*r[4*h+1],C=255*r[4*h+2],P=255*r[4*h+3],z=.5*(A.bounds[0]+A.bounds[2]),R=.5*(A.bounds[1]+A.bounds[3]),p=0;p<k.data.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-E*(k.data[p]-z),b[2*w+1]=-E*(k.data[p+1]-R),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1;var O=o[h];L=255*s[4*h],S=255*s[4*h+1],C=255*s[4*h+2],P=255*s[4*h+3];for(var p=0;p<A.coords.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-(E*(A.coords[p]-z)+O*A.normals[p]),b[2*w+1]=-(E*(A.coords[p+1]-R)+O*A.normals[p+1]),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1}this.numPoints=i.length,this.numVertices=f,this.positionBuffer.update(y),this.offsetBuffer.update(b),this.colorBuffer.update(x),this.idBuffer.update(_),u.free(y),u.free(b),u.free(x),u.free(_)},p.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":372,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458,\"typedarray-pool\":463,\"vectorize-text\":465}],374:[function(t,e,r){r.pointVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute float weight;\\n\\nuniform mat3 matrix;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\\n\",r.pointFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],375:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],376:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){4*h>=a?i(0,a-1,t,e,r,n):f(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;e>=o;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],f=a[o],h=o;h>t;){var p=r[h-1],d=n[2*(h-1)];if((p-s||l-d)>=0)break;r[h]=p,n[2*h]=d,n[2*h+1]=n[2*h-1],i[h]=i[h-1],a[h]=a[h-1],h-=1}r[h]=s,n[2*h]=l,n[2*h+1]=u,i[h]=c,a[h]=f}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],f=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=f}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0}function c(t,e,r,n,i,a,o,s){return(e-a[t]||o[2*t]-r||i-s[t])<0}function f(t,e,r,n,p,d){var g=(e-t+1)/6|0,v=t+g,m=e-g,y=t+e>>1,b=y-g,x=y+g,_=v,w=b,k=y,A=x,M=m,T=t+1,E=e-1,L=0;u(_,w,r,n,p,d)&&(L=_,_=w,w=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L),u(_,k,r,n,p,d)&&(L=_,_=k,k=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(_,A,r,n,p,d)&&(L=_,_=A,A=L),u(k,A,r,n,p,d)&&(L=k,k=A,A=L),u(w,M,r,n,p,d)&&(L=w,w=M,M=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L);var S=r[w],C=n[2*w],P=n[2*w+1],z=p[w],R=d[w],O=r[A],I=n[2*A],j=n[2*A+1],N=p[A],F=d[A],D=_,B=k,U=M,V=v,q=y,H=m,G=r[D],Y=r[B],X=r[U];r[V]=G,r[q]=Y,r[H]=X;for(var W=0;2>W;++W){var Z=n[2*D+W],$=n[2*B+W],K=n[2*U+W];n[2*V+W]=Z,n[2*q+W]=$,n[2*H+W]=K}var Q=p[D],J=p[B],tt=p[U];p[V]=Q,p[q]=J,p[H]=tt;var et=d[D],rt=d[B],nt=d[U];d[V]=et,d[q]=rt,d[H]=nt,o(b,t,r,n,p,d),o(x,e,r,n,p,d);for(var it=T;E>=it;++it)if(c(it,S,C,P,z,r,n,p))it!==T&&a(it,T,r,n,p,d),++T;else if(!c(it,O,I,j,N,r,n,p))for(;;){if(c(E,O,I,j,N,r,n,p)){c(E,S,C,P,z,r,n,p)?(s(it,T,E,r,n,p,d),++T,--E):(a(it,E,r,n,p,d),--E);break}if(--E<it)break}l(t,T-1,S,C,P,z,R,r,n,p,d),l(e,E+1,O,I,j,N,F,r,n,p,d),h>=T-2-t?i(t,T-2,r,n,p,d):f(t,T-2,r,n,p,d),h>=e-(E+2)?i(E+2,e,r,n,p,d):f(E+2,e,r,n,p,d),h>=E-T?i(T,E,r,n,p,d):f(T,E,r,n,p,d)}e.exports=n;var h=32},{}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;n>u;++u){var c=t[2*u],f=t[2*u+1],h=e[u];c>=i&&o>=c&&f>=a&&s>=f&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=f,e[l]=h,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var f=.5*o,h=s+1,p=u-s;r[_]=p,x[_++]=c;for(var d=0;2>d;++d)for(var g=0;2>g;++g){var v=i+d*f,m=a+g*f,y=n(t,e,h,u,v,m,v+f,m+f);if(y!==h){if(y-h>=Math.max(.9*p,32)){var b=u+s>>>1;l(v,m,f,h,b,c+1),h=b}l(v,m,f,h,y,c+1),h=y}}}var u=t.length>>>1;if(1>u)return[];for(var c=1/0,f=1/0,h=-(1/0),p=-(1/0),d=0;u>d;++d){var g=t[2*d],v=t[2*d+1];c=Math.min(c,g),h=Math.max(h,g),f=Math.min(f,v),p=Math.max(p,v),e[d]=d}c===h&&(h+=1+Math.abs(h)),f===p&&(p+=1+Math.abs(h));var m=1/(h-c),y=1/(p-f),b=Math.max(h-c,p-f);a=a||[0,0,0,0],a[0]=c,a[1]=f,a[2]=h,a[3]=p;var x=o.mallocInt32(u),_=0;l(c,f,b,0,u,0),s(x,t,e,r,u);for(var w=[],k=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*m,t[2*_+1]=(t[2*_+1]-f)*y;var M=x[_];M!==k&&(w.push(new i(b*Math.pow(.5,M),_+1,A-(_+1))),A=_+1,k=M)}return w.push(new i(b*Math.pow(.5,M+1),0,A)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":376,\"typedarray-pool\":463}],378:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.weightBuffer=n,this.shader=i,this.pickShader=a,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),h=new n(t,i,s,l,u,f);return h.update(e),t.addObject(h),h}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var f=n.prototype;f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},f.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords);var r=t.positions,n=u.mallocFloat32(r.length),i=u.mallocInt32(r.length>>>1);n.set(r);var a=u.mallocFloat32(r.length);this.points=r,this.scales=l(n,i,a,this.bounds),this.offsetBuffer.update(n),this.pickBuffer.update(i),this.weightBuffer.update(a);for(var o=u.mallocFloat32(r.length>>>1),s=0,c=0;s<r.length;s+=2,++c)o[c]=n[s];u.free(i),u.free(n),u.free(a),this.xCoords=o,this.pointCount=r.length>>>1,this.pickOffset=0},f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.scales,o=this.offsetBuffer,l=this.pickBuffer,u=this.bounds,c=this.size,f=this.borderSize,h=n.gl,p=n.pickPixelRatio,d=n.viewBox,g=n.dataBox;if(0===this.pointCount)return r;var v=u[2]-u[0],m=u[3]-u[1],y=g[2]-g[0],b=g[3]-g[1],x=(d[2]-d[0])*p/n.pixelRatio,_=(d[3]-d[1])*p/n.pixelRatio,w=Math.min(y/x,b/_);t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(u[0]-g[0])/y-1,t[7]=2*(u[1]-g[1])/b-1,this.pickOffset=r,e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,i.bind(),i.uniforms.matrix=t,i.uniforms.color=this.color,i.uniforms.borderColor=this.borderColor,i.uniforms.pointSize=p*(c+f),i.uniforms.pickOffset=e,0===this.borderSize?i.uniforms.centerFraction=2:i.uniforms.centerFraction=c/(c+f+1.25),o.bind(),i.attributes.position.pointer(),l.bind(),i.attributes.pickId.pointer(h.UNSIGNED_BYTE);for(var k=this.xCoords,A=(g[0]-u[0]-w*c*p)/v,M=(g[2]-u[0]+w*c*p)/v,T=a.length-1;T>=0;--T){var E=a[T];if(!(E.pixelSize<w&&T>1)){var L=E.offset,S=E.count+L,C=s.ge(k,A,L,S-1),P=s.lt(k,M,C,S-1)+1;h.drawArrays(h.POINTS,C,P-C)}}return r+this.pointCount}}(),f.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.scales,i=this.offsetBuffer,a=this.bounds,o=this.size,l=this.borderSize,u=e.gl,c=e.pixelRatio,f=e.viewBox,h=e.dataBox;if(0!==this.pointCount){var p=a[2]-a[0],d=a[3]-a[1],g=h[2]-h[0],v=h[3]-h[1],m=f[2]-f[0],y=f[3]-f[1],b=Math.min(g/m,v/y);t[0]=2*p/g,t[4]=2*d/v,t[6]=2*(a[0]-h[0])/g-1,t[7]=2*(a[1]-h[1])/v-1,r.bind(),r.uniforms.matrix=t,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointSize=c*(o+l),r.uniforms.useWeight=1,0===this.borderSize?r.uniforms.centerFraction=2:r.uniforms.centerFraction=o/(o+l+1.25),i.bind(),r.attributes.position.pointer(),this.weightBuffer.bind(),r.attributes.weight.pointer();for(var x=this.xCoords,_=(h[0]-a[0]-b*o*c)/p,w=(h[2]-a[0]+b*o*c)/p,k=!0,A=n.length-1;A>=0;--A){var M=n[A];if(!(M.pixelSize<b&&A>1)){var T=M.offset,E=M.count+T,L=s.ge(x,_,T,E-1),S=s.lt(x,w,L,E-1)+1;u.drawArrays(u.POINTS,L,S-L),k&&(k=!1,r.uniforms.useWeight=0)}}}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":374,\"binary-search-bounds\":375,\"gl-buffer\":325,\"gl-shader\":385,\"snap-points-2d\":377,\"typedarray-pool\":463}],379:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;2>c;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":465}],380:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},v={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,f)},r.createOrtho=function(t){return n(t,h)},r.createProject=function(t){return n(t,p)},r.createPickPerspective=function(t){return n(t,d)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,v)}},{\"gl-shader\":385}],381:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,f,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=f,this.pickProjectShader=h,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=S,r=0;2>r;++r)for(var n=0;3>n;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function f(t,e,r,n,a){var o,f=e.axesProject,h=e.gl,p=t.uniforms,d=r.model||x,g=r.view||x,v=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/h.drawingBufferWidth,w[1]=2/h.drawingBufferHeight,t.bind(),p.view=g,p.projection=v,p.screenSize=w,p.highlightId=e.highlightId,p.highlightScale=e.highlightScale,p.clipBounds=b,p.pickGroup=e.pickId/255,p.pixelRatio=e.pixelRatio;for(var _=0;3>_;++_)if(f[_]&&e.projectOpacity[_]<1===n){p.scale=e.projectScale[_],p.opacity=e.projectOpacity[_];for(var S=E,C=0;16>C;++C)S[C]=0;for(var C=0;4>C;++C)S[5*C]=1;S[5*_]=0,o[_]<0?S[12+_]=y[0][_]:S[12+_]=y[1][_],m(S,d,S),p.model=S;var P=(_+1)%3,z=(_+2)%3,R=s(k),O=s(A);R[P]=1,O[z]=1;var I=i(v,g,d,l(M,R)),j=i(v,g,d,l(T,O));if(Math.abs(I[1])>Math.abs(j[1])){var N=I;I=j,j=N,N=R,R=O,O=N;var F=P;P=z,z=F}I[0]<0&&(R[P]=-1),j[1]>0&&(O[z]=-1);for(var D=0,B=0,C=0;4>C;++C)D+=Math.pow(d[4*P+C],2),B+=Math.pow(d[4*z+C],2);R[P]/=Math.sqrt(D),O[z]/=Math.sqrt(B),p.axes[0]=R,p.axes[1]=O,p.fragClipBounds[0]=u(L,b[0],_,-1e8),p.fragClipBounds[1]=u(L,b[1],_,1e8),e.vao.draw(h.TRIANGLES,e.vertexCount),e.lineWidth>0&&(h.lineWidth(e.lineWidth),e.vao.draw(h.LINES,e.lineVertexCount,e.vertexCount))}}function h(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=z,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}f(e,r,n,i,a),r.vao.unbind()}function p(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=d(e),c=d(e),f=d(e),h=d(e),p=g(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:f,size:2,type:e.FLOAT},{buffer:h,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new o(e,r,n,i,u,c,f,h,p,a,s,l);return v.update(t),v}var d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"typedarray-pool\"),m=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=p;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],k=[0,0,0],A=[0,0,0],M=[0,0,0,1],T=[0,0,0,1],E=x.slice(),L=[0,0,0],S=[[0,0,0],[0,0,0]],C=[-1e8,-1e8,-1e8],P=[1e8,1e8,1e8],z=[C,P];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;h(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||0>e)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;3>i;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in t&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-(1/0),-(1/0),-(1/0)],l=t.glyph,u=t.color,c=t.size,f=t.angle,h=t.lineColor,p=0,d=0,g=0,m=n.length;t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_)if(isNaN(x[_])||!isFinite(x[_]))continue t;var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];d+=3*k.cells.length,g+=2*A.edges.length}var T=d+g,E=v.mallocFloat(3*T),L=v.mallocFloat(4*T),S=v.mallocFloat(2*T),C=v.mallocUint32(T),P=[0,a[1]],z=0,R=d,O=[0,0,0,1],I=[0,0,0,1],j=Array.isArray(u)&&Array.isArray(u[0]),N=Array.isArray(h)&&Array.isArray(h[0]);t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_){if(isNaN(x[_])||!isFinite(x[_])){p+=1;continue t}s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_])}var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];if(Array.isArray(u)){var F;if(F=j?u[y]:u,3===F.length){for(var _=0;3>_;++_)O[_]=F[_];O[3]=1}else if(4===F.length)for(var _=0;4>_;++_)O[_]=F[_];\n",
+       "}else O[0]=O[1]=O[2]=0,O[3]=1;if(Array.isArray(h)){var F;if(F=N?h[y]:h,3===F.length){for(var _=0;3>_;++_)I[_]=F[_];I[_]=1}else if(4===F.length)for(var _=0;4>_;++_)I[_]=F[_]}else I[0]=I[1]=I[2]=0,I[3]=1;var D=.5;Array.isArray(c)?D=+c[y]:c?D=+c:this.useOrtho&&(D=12);var B=0;Array.isArray(f)?B=+f[y]:f&&(B=+f);for(var U=Math.cos(B),V=Math.sin(B),x=n[y],_=0;3>_;++_)s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_]);a[0]<0?P[0]=a[0]*(1+M[1][0]):a[0]>0&&(P[0]=-a[0]*(1+M[0][0]));for(var q=k.cells,H=k.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;3>Y;++Y){for(var X=0;3>X;++X)E[3*z+X]=x[X];for(var X=0;4>X;++X)L[4*z+X]=O[X];C[z]=p;var W=H[G[Y]];S[2*z]=D*(U*W[0]-V*W[1]+P[0]),S[2*z+1]=D*(V*W[0]+U*W[1]+P[1]),z+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;2>Y;++Y){for(var X=0;3>X;++X)E[3*R+X]=x[X];for(var X=0;4>X;++X)L[4*R+X]=I[X];C[R]=p;var W=H[G[Y]];S[2*R]=D*(U*W[0]-V*W[1]+P[0]),S[2*R+1]=D*(V*W[0]+U*W[1]+P[1]),R+=1}p+=1}this.vertexCount=d,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(C)),v.free(E),v.free(L),v.free(S),v.free(C),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":379,\"./lib/shaders\":380,\"gl-buffer\":325,\"gl-mat4/multiply\":346,\"gl-vao\":420,\"typedarray-pool\":463}],382:[function(t,e,r){\"use strict\";r.boxVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(f>p||h>d)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*c;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":382,\"gl-buffer\":325,\"gl-shader\":385}],384:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(255>_inline_31_arg0_||255>_inline_31_arg1_||255>_inline_31_arg2_||255>_inline_31_arg3_){var 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l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],410:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\nattribute vec2 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  value = f.x;\\n  kill = f.y;\\n  planeCoordinate = uv.xy;\\n  \\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  float interpValue = (value - lowerBound.z) / (upperBound.z - lowerBound.z);\\n  vec4 surfaceColor = texture2D(colormap, vec2(interpValue, interpValue));\\n  vec4 litColor 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eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 || \\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e}},{\"gl-shader\":385}],411:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],412:[function(t,e,r){\"use strict\";function n(t){if(t in l)return l[t];for(var e=[],r=0;t>r;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");for(var n=[\"array\"],i=[\"junk\"],r=0;t>r;++r){n.push(\"array\"),i.push(\"out\"+r+\"s\");var a=o(t);a[r]=-1,n.push({array:0,offset:a.slice()}),a[r]=1,n.push({array:0,offset:a.slice()}),i.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return l[t]=s({args:n,pre:c,post:c,body:{body:e.join(\"\"),args:i.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}function i(t){function e(e){for(var r=a-e.length,n=[],i=[],s=[],l=0;a>l;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),n.push(\"1\"),i.push(\"s[\"+l+\"]-2\"));var u=\".lo(\"+n.join()+\").hi(\"+i.join()+\")\";if(0===n.length&&(u=\"\"),r>0){o.push(\"if(1\");for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\"&&s[\",l,\"]>2\");o.push(\"){grad\",r,\"(src.pick(\",s.join(),\")\",u);for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\",dst.pick(\",s.join(),\",\",l,\")\",u);o.push(\");\")}for(var l=0;l<e.length;++l){var c=Math.abs(e[l])-1,f=\"dst.pick(\"+s.join()+\",\"+c+\")\"+u;switch(t[c]){case\"clamp\":var h=s.slice(),p=s.slice();e[l]<0?h[c]=\"s[\"+c+\"]-2\":p[c]=\"1\",0===r?o.push(\"if(s[\",c,\"]>1){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",h.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>1){diff(\",f,\",src.pick(\",h.join(),\")\",u,\",src.pick(\",p.join(),\")\",u,\");}else{zero(\",f,\");};\");break;case\"mirror\":0===r?o.push(\"dst.set(\",s.join(),\",\",c,\",0);\"):o.push(\"zero(\",f,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[c]=\"s[\"+c+\"]-2\",g[c]=\"0\"):(d[c]=\"s[\"+c+\"]-1\",g[c]=\"1\"),0===r?o.push(\"if(s[\",c,\"]>2){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>2){diff(\",f,\",src.pick(\",d.join(),\")\",u,\",src.pick(\",g.join(),\")\",u,\");}else{zero(\",f,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}r>0&&o.push(\"};\")}var r=t.join(),i=u[r];if(i)return i;for(var a=t.length,o=[\"function gradient(dst,src){var s=src.shape.slice();\"],s=0;1<<a>s;++s){for(var c=[],p=0;a>p;++p)s&1<<p&&c.push(p+1);for(var d=0;d<1<<c.length;++d){for(var g=c.slice(),p=0;p<c.length;++p)d&1<<p&&(g[p]=-g[p]);e(g)}}o.push(\"return dst;};return gradient\");for(var v=[\"diff\",\"zero\"],m=[f,h],s=1;a>=s;++s)v.push(\"grad\"+s),m.push(n(s));v.push(o.join(\"\"));var y=Function.apply(void 0,v),i=y.apply(void 0,m);return l[r]=i,i}function a(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=\"string\"==typeof r?o(e.dimension,r):o(e.dimension,\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var n=0;n<e.dimension;++n)if(t.shape[n]!==e.shape[n])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;var a=i(r);return a(t,e)}e.exports=a;var o=t(\"dup\"),s=t(\"cwise-compiler\"),l={},u={},c={body:\"\",args:[],thisVars:[],localVars:[]},f=s({args:[\"array\",\"array\",\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),h=s({args:[\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"})},{\"cwise-compiler\":316,dup:322}],413:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],a=t,o=1;a instanceof Array;)r.push(a.length),o*=a.length,a=a[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),i(e,t),e)}},{\"./doConvert.js\":414,ndarray:438}],414:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":316}],415:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,f,h,p,d){this.gl=t,this.shape=e,this.bounds=r,this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=f,this._contourVAO=h,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=p,this._dynamicVAO=d,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.dirty=!0}function o(t,e){for(var r=e.axes&&e.axes.lastCubeProps.axis||F,n=e.showSurface,i=e.showContour,a=0;3>a;++a){n=n||e.surfaceProject[a];for(var o=0;3>o;++o)i=i||e.contourProject[a][o]}for(var a=0;3>a;++a){for(var s=D.projections[a],o=0;16>o;++o)s[o]=0;for(var o=0;4>o;++o)s[5*o]=1;s[5*a]=0,s[12+a]=e.axesBounds[+(r[a]>0)][a],k(s,t.model,s);for(var l=D.clipBounds[a],u=0;2>u;++u)for(var o=0;3>o;++o)l[u][o]=t.clipBounds[u][o];l[0][a]=-1e8,l[1][a]=1e8}return D.showSurface=n,D.showContour=i,D}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||R,n.view=t.view||R,n.projection=t.projection||R,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;2>i;++i)for(var a=n.clipBounds[i],s=0;3>s;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.shape=n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V;var l=U;k(l,n.view,n.model),k(l,n.projection,l),A(l,l);for(var i=0;3>i;++i)n.eyePosition[i]=l[12+i]/l[15];for(var u=l[15],i=0;3>i;++i)u+=this.lightPosition[i]*l[4*i+3];for(var i=0;3>i;++i){for(var c=l[12+i],s=0;3>s;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var f=o(n,this);if(f.showSurface&&e===this.opacity<1){this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vao.draw(r.TRIANGLES,this._vertexCount);for(var i=0;3>i;++i)this.surfaceProject[i]&&(this._shader.uniforms.model=f.projections[i],this._shader.uniforms.clipBounds=f.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(f.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var p=this._contourVAO;p.bind();for(var i=0;3>i;++i){h.uniforms.permutation=I[i],r.lineWidth(this.contourWidth[i]);for(var s=0;s<this.contourLevels[i].length;++s)s===this.highlightLevel[i]?(h.uniforms.contourColor=this.highlightColor[i],h.uniforms.contourTint=this.highlightTint[i]):(0===s||s-1===this.highlightLevel[i])&&(h.uniforms.contourColor=this.contourColor[i],h.uniforms.contourTint=this.contourTint[i]),h.uniforms.height=this.contourLevels[i][s],p.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s])}for(var i=0;3>i;++i){h.uniforms.model=f.projections[i],h.uniforms.clipBounds=f.clipBounds[i];for(var s=0;3>s;++s)if(this.contourProject[i][s]){h.uniforms.permutation=I[s],r.lineWidth(this.contourWidth[s]);for(var d=0;d<this.contourLevels[s].length;++d)d===this.highlightLevel[s]?(h.uniforms.contourColor=this.highlightColor[s],h.uniforms.contourTint=this.highlightTint[s]):(0===d||d-1===this.highlightLevel[s])&&(h.uniforms.contourColor=this.contourColor[s],h.uniforms.contourTint=this.contourTint[s]),h.uniforms.height=this.contourLevels[s][d],p.draw(r.LINES,this._contourCounts[s][d],this._contourOffsets[s][d])}}p=this._dynamicVAO,p.bind();for(var i=0;3>i;++i)if(0!==this._dynamicCounts[i]){h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=I[i],r.lineWidth(this.dynamicWidth[i]),h.uniforms.contourColor=this.dynamicColor[i],h.uniforms.contourTint=this.dynamicTint[i],h.uniforms.height=this.dynamicLevel[i],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]);for(var s=0;3>s;++s)this.contourProject[s][i]&&(h.uniforms.model=f.projections[s],h.uniforms.clipBounds=f.clipBounds[s],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]))}p.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function f(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function h(t){var e=t.gl,r=(t.field||t.coords&&t.coords[2]||_([],[0,0]),L(e)),n=C(e),i=S(e),o=P(e),s=d(e),l=g(e,[{buffer:s,size:4,stride:z,offset:0},{buffer:s,size:2,stride:z,offset:16},{buffer:s,size:3,stride:z,offset:24}]),u=d(e),c=g(e,[{buffer:u,size:4}]),f=d(e),h=g(e,[{buffer:f,size:2,type:e.FLOAT}]),p=v(e,1,j,e.RGBA,e.UNSIGNED_BYTE);p.minFilter=e.LINEAR,p.magFilter=e.LINEAR;var m=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,p,i,o,u,c,f,h),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",m.update(y),m}e.exports=h;var p=t(\"bit-twiddle\"),d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),m=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),k=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),M=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),_=t(\"ndarray\"),E=t(\"./lib/shaders\"),L=E.createShader,S=E.createContourShader,C=E.createPickShader,P=E.createPickContourShader,z=36,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],I=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;3>t;++t){var e=I[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var j=265,N=a.prototype;N.isTransparent=function(){return this.opacity<1},N.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},N.pickSlots=1,N.setPickBase=function(t){this.pickId=t};var F=[0,0,0],D={showSurface:!1,showContour:!1,projections:[R.slice(),R.slice(),R.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:R,view:R,projection:R,inverseModel:R.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1},U=R.slice(),V=[1,0,0,0,1,0,0,0,1];N.draw=function(t){return s.call(this,t,!1)},N.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:R,view:R,projection:R,inverseModel:R,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};N.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||R,r.view=t.view||R,r.projection=t.projection||R,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;2>n;++n)for(var i=r.clipBounds[n],a=0;3>a;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount);for(var n=0;3>n;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;u.bind();for(var a=0;3>a;++a){e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=I[a];for(var n=0;n<this.contourLevels[a].length;++n)l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n])}for(var n=0;3>n;++n){l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n];for(var a=0;3>a;++a)if(this.contourProject[n][a]){l.uniforms.permutation=I[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c])}}u.unbind()}},N.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;2>c;++c)for(var f=c?a:1-a,h=0;2>h;++h)for(var p=h?l:1-l,d=i+c,g=s+h,v=f*p,m=0;3>m;++m)u[m]+=this._field[m].get(d,g)*v;for(var y=this._pickResult.level,b=0;3>b;++b)if(y[b]=M.le(this.contourLevels[b],u[b]),y[b]<0)this.contourLevels[b].length>0&&(y[b]=0);else if(y[b]<this.contourLevels[b].length-1){var x=this.contourLevels[b][y[b]],_=this.contourLevels[b][y[b]+1];Math.abs(x-u[b])>Math.abs(_-u[b])&&(y[b]+=1)}r.index[0]=.5>a?i:i+1,r.index[1]=.5>l?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1];for(var m=0;3>m;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},N.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=f(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=f(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\n",
+       "\"colorBounds\"in t&&(this.colorBounds=t.colorBounds);var e=t.field||t.coords&&t.coords[2]||null;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var r=(e.shape[0]+2)*(e.shape[1]+2);r>this._field[2].data.length&&(m.freeFloat(this._field[2].data),this._field[2].data=m.mallocFloat(p.nextPow2(r))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var n=this.shape,a=0;2>a;++a)this._field[2].size>this._field[a].data.length&&(m.freeFloat(this._field[a].data),this._field[a].data=m.mallocFloat(this._field[2].size)),this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2]);if(t.coords){var o=t.coords;if(!Array.isArray(o)||3!==o.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(var a=0;2>a;++a){for(var s=o[a],c=0;2>c;++c)if(s.shape[c]!==n[c])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[a],s)}}else if(t.ticks){var h=t.ticks;if(!Array.isArray(h)||2!==h.length)throw new Error(\"gl-surface: invalid ticks\");for(var a=0;2>a;++a){var d=h[a];if((Array.isArray(d)||d.length)&&(d=_(d)),d.shape[0]!==n[a])throw new Error(\"gl-surface: invalid tick length\");var g=_(d.data,n);g.stride[a]=d.stride[0],g.stride[1^a]=0,l(this._field[a],g)}}else{for(var a=0;2>a;++a){var v=[0,0];v[a]=1,this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2],v,0)}this._field[0].set(0,0,0);for(var c=0;c<n[0];++c)this._field[0].set(c+1,0,c);this._field[0].set(n[0]+1,0,n[0]-1),this._field[1].set(0,0,0);for(var c=0;c<n[1];++c)this._field[1].set(0,c+1,c);this._field[1].set(0,n[1]+1,n[1]-1)}for(var y=this._field,b=(y[2].size,_(m.mallocFloat(3*y[2].size*2),[3,n[0]+2,n[1]+2,2])),a=0;3>a;++a)T(b.pick(a),y[a],\"mirror\");for(var x=_(m.mallocFloat(3*y[2].size),[n[0]+2,n[1]+2,3]),a=0;a<n[0]+2;++a)for(var c=0;c<n[1]+2;++c){var k=b.get(0,a,c,0),A=b.get(0,a,c,1),M=b.get(1,a,c,0),E=b.get(1,a,c,1),L=b.get(2,a,c,0),S=b.get(2,a,c,1),C=M*S-E*L,P=L*A-S*k,z=k*E-A*M,R=Math.sqrt(C*C+P*P+z*z);1e-8>R?(R=Math.max(Math.abs(C),Math.abs(P),Math.abs(z)),1e-8>R?(z=1,P=C=0,R=1):R=1/R):R=1/Math.sqrt(R),x.set(a,c,0,C*R),x.set(a,c,1,P*R),x.set(a,c,2,z*R)}m.free(b.data);for(var I=[1/0,1/0,1/0],j=[-(1/0),-(1/0),-(1/0)],N=(n[0]-1)*(n[1]-1)*6,F=m.mallocFloat(p.nextPow2(9*N)),D=0,B=0,a=0;a<n[0]-1;++a)t:for(var c=0;c<n[1]-1;++c){for(var U=0;2>U;++U)for(var V=0;2>V;++V)for(var q=0;3>q;++q){var H=this._field[q].get(1+a+U,1+c+V);if(isNaN(H)||!isFinite(H))continue t}for(var q=0;6>q;++q){var G=a+O[q][0],Y=c+O[q][1],X=this._field[0].get(G+1,Y+1),W=this._field[1].get(G+1,Y+1),H=this._field[2].get(G+1,Y+1),C=x.get(G+1,Y+1,0),P=x.get(G+1,Y+1,1),z=x.get(G+1,Y+1,2);F[D++]=G,F[D++]=Y,F[D++]=X,F[D++]=W,F[D++]=H,F[D++]=0,F[D++]=C,F[D++]=P,F[D++]=z,I[0]=Math.min(I[0],X),I[1]=Math.min(I[1],W),I[2]=Math.min(I[2],H),j[0]=Math.max(j[0],X),j[1]=Math.max(j[1],W),j[2]=Math.max(j[2],H),B+=1}}this._vertexCount=B,this._coordinateBuffer.update(F.subarray(0,D)),m.freeFloat(F),m.free(x.data),this.bounds=[I,j]}var Z=!1;if(\"levels\"in t){var $=t.levels;$=Array.isArray($[0])?$.slice():[[],[],$];for(var a=0;3>a;++a)$[a]=$[a].slice(),$.sort(function(t,e){return t-e});t:for(var a=0;3>a;++a){if($[a].length!==this.contourLevels[a].length){Z=!0;break}for(var c=0;c<$[a].length;++c)if($[a][c]!==this.contourLevels[a][c]){Z=!0;break t}}this.contourLevels=$}if(Z){for(var y=this._field,n=this.shape,K=[],Q=0;3>Q;++Q){for(var $=this.contourLevels[Q],J=[],tt=[],et=[0,0],a=0;a<$.length;++a){var rt=w(this._field[Q],$[a]);J.push(K.length/4|0);var B=0;t:for(var c=0;c<rt.cells.length;++c)for(var nt=rt.cells[c],q=0;2>q;++q){var it=rt.positions[nt[q]],at=it[0],ot=0|Math.floor(at),st=at-ot,lt=it[1],ut=0|Math.floor(lt),ct=lt-ut,ft=!1;e:for(var ht=0;2>ht;++ht){et[ht]=0;for(var pt=(Q+ht+1)%3,U=0;2>U;++U)for(var dt=U?st:1-st,G=0|Math.min(Math.max(ot+U,0),n[0]),V=0;2>V;++V){var gt=V?ct:1-ct,Y=0|Math.min(Math.max(ut+V,0),n[1]),H=this._field[pt].get(G,Y);if(!isFinite(H)||isNaN(H)){ft=!0;break e}var vt=dt*gt;et[ht]+=vt*H}}if(ft){if(q>0){for(var mt=0;4>mt;++mt)K.pop();B-=1}continue t}K.push(et[0],et[1],it[0],it[1]),B+=1}tt.push(B)}this._contourOffsets[Q]=J,this._contourCounts[Q]=tt}for(var yt=m.mallocFloat(K.length),a=0;a<K.length;++a)yt[a]=K[a];this._contourBuffer.update(yt),m.freeFloat(yt)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},N.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;3>t;++t)m.freeFloat(this._field[t].data)},N.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;3>e;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=m.mallocFloat(12*i[0]*i[1]),o=0;3>o;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],f=this._field[l],h=w(u,r[o]),p=h.cells,d=h.positions;this._dynamicOffsets[o]=n;for(var e=0;e<p.length;++e)for(var g=p[e],v=0;2>v;++v){var y=d[g[v]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),k=b-x,A=1-k,M=+y[1],T=0|M,E=0|Math.min(T+1,i[1]),L=M-T,S=1-L,C=A*S,P=A*L,z=k*S,R=k*L,O=C*c.get(x,T)+P*c.get(x,E)+z*c.get(_,T)+R*c.get(_,E),I=C*f.get(x,T)+P*f.get(x,E)+z*f.get(_,T)+R*f.get(_,E);if(isNaN(O)||isNaN(I)){v&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=I,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),m.freeFloat(a)}}},{\"./lib/shaders\":410,\"binary-search-bounds\":411,\"bit-twiddle\":299,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,\"ndarray-gradient\":412,\"ndarray-ops\":437,\"ndarray-pack\":413,\"surface-nets\":457,\"typedarray-pool\":463}],416:[function(t,e,r){arguments[4][179][0].apply(r,arguments)},{dup:179,ndarray:438,\"ndarray-ops\":437,\"typedarray-pool\":463}],417:[function(t,e,r){arguments[4][42][0].apply(r,arguments)},{dup:42}],418:[function(t,e,r){arguments[4][43][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:43}],419:[function(t,e,r){arguments[4][44][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:44}],420:[function(t,e,r){arguments[4][45][0].apply(r,arguments)},{\"./lib/vao-emulated.js\":418,\"./lib/vao-native.js\":419,dup:45}],421:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;t>=r;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var n=0;t>=n;++n)this.tuple[n]=this.vertices[n];var i=f[t];i||(i=f[t]=o(t)),this.orient=i}function l(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(i>=r)throw new Error(\"Must input at least d+1 points\");var a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),c=0;i>=c;++c)l[c]=c;0>o&&(l[0]=1,l[1]=0);for(var f=new n(l,new Array(i+1),!1),h=f.adjacent,p=new Array(i+2),c=0;i>=c;++c){for(var d=l.slice(),g=0;i>=g;++g)g===c&&(d[g]=-1);var v=d[0];d[0]=d[1],d[1]=v;var m=new n(d,new Array(i+1),!0);h[c]=m,p[c]=m}p[i+1]=f;for(var c=0;i>=c;++c)for(var d=h[c].vertices,y=h[c].adjacent,g=0;i>=g;++g){var b=d[g];if(0>b)y[g]=f;else for(var x=0;i>=x;++x)h[x].vertices.indexOf(b)<0&&(y[g]=h[x])}for(var _=new s(i,a,p),w=!!e,c=i+1;r>c;++c)_.insert(t[c],w);return _.boundary()}e.exports=l;var u=t(\"robust-orientation\"),c=t(\"simplicial-complex\").compareCells;n.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var f=[],h=s.prototype;h.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,i=this.tuple,a=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){t=o.pop();for(var s=(t.vertices,t.adjacent),l=0;r>=l;++l){var u=s[l];if(u.boundary&&!(u.lastVisited<=-n)){for(var c=u.vertices,f=0;r>=f;++f){var h=c[f];0>h?i[f]=e:i[f]=a[h]}var p=this.orient();if(p>0)return u;u.lastVisited=-n,0===p&&o.push(u)}}}return null},h.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,a=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,u=s.adjacent,c=0;n>=c;++c)a[c]=i[l[c]];s.lastVisited=r;for(var c=0;n>=c;++c){var f=u[c];if(!(f.lastVisited>=r)){var h=a[c];a[c]=t;var p=this.orient();if(a[c]=h,0>p){s=f;continue t}f.boundary?f.lastVisited=-r:f.lastVisited=r}}return}return s},h.addPeaks=function(t,e){var r=this.vertices.length-1,o=this.dimension,s=this.vertices,l=this.tuple,u=this.interior,c=this.simplices,f=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,u.push(e);for(var h=[];f.length>0;){var e=f.pop(),p=e.vertices,d=e.adjacent,g=p.indexOf(r);if(!(0>g))for(var v=0;o>=v;++v)if(v!==g){var m=d[v];if(m.boundary&&!(m.lastVisited>=r)){var y=m.vertices;if(m.lastVisited!==-r){for(var b=0,x=0;o>=x;++x)y[x]<0?(b=x,l[x]=t):l[x]=s[y[x]];var _=this.orient();if(_>0){y[b]=r,m.boundary=!1,u.push(m),f.push(m),m.lastVisited=r;continue}m.lastVisited=-r}var w=m.adjacent,k=p.slice(),A=d.slice(),M=new n(k,A,!0);c.push(M);var T=w.indexOf(e);if(!(0>T)){w[T]=M,A[g]=m,k[v]=-1,A[v]=e,d[v]=M,M.flip();for(var x=0;o>=x;++x){var E=k[x];if(!(0>E||E===r)){for(var L=new Array(o-1),S=0,C=0;o>=C;++C){var P=k[C];0>P||C===x||(L[S++]=P)}h.push(new i(L,M,x))}}}}}}h.sort(a);for(var v=0;v+1<h.length;v+=2){var z=h[v],R=h[v+1],O=z.index,I=R.index;0>O||0>I||(z.cell.adjacent[z.index]=R.cell,R.cell.adjacent[R.index]=z.cell)}},h.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var i=this.dimension,a=this.tuple,o=0;i>=o;++o){var s=n.vertices[o];0>s?a[o]=t:a[o]=r[s]}var l=this.orient(a);0>l||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},h.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,i=0;n>i;++i){var a=r[i];if(a.boundary){for(var o=new Array(t),s=a.vertices,l=0,u=0,c=0;t>=c;++c)s[c]>=0?o[l++]=s[c]:u=1&c;if(u===(1&t)){var f=o[0];o[0]=o[1],o[1]=f}e.push(o)}}return e}},{\"robust-orientation\":444,\"simplicial-complex\":424}],422:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],423:[function(t,e,r){arguments[4][130][0].apply(r,arguments)},{dup:130}],424:[function(t,e,r){arguments[4][151][0].apply(r,arguments)},{\"bit-twiddle\":422,dup:151,\"union-find\":423}],425:[function(t,e,r){arguments[4][248][0].apply(r,arguments)},{dup:248}],426:[function(t,e,r){arguments[4][245][0].apply(r,arguments)},{dup:245,\"mouse-event\":427}],427:[function(t,e,r){arguments[4][246][0].apply(r,arguments)},{dup:246}],428:[function(t,e,r){arguments[4][29][0].apply(r,arguments)},{dup:29}],429:[function(t,e,r){arguments[4][30][0].apply(r,arguments)},{dup:30,\"parse-unit\":428}],430:[function(t,e,r){arguments[4][31][0].apply(r,arguments)},{dup:31,\"to-px\":429}],431:[function(t,e,r){\"use strict\";var n=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{_inline_1_arg1_=_inline_1_arg2_.apply(void 0,_inline_1_arg0_)}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});e.exports=function(t,e){return n(t,e),t}},{\"cwise/lib/wrapper\":319}],432:[function(t,e,r){\"use strict\";function n(t,e){switch(e.length){case 0:break;case 1:t[0]=1/e[0];break;case 4:i(t,e);break;case 9:a(t,e);break;case 16:o(t,e);break;default:throw new Error(\"currently supports matrices up to 4x4\")}return t}e.exports=n;var i=t(\"gl-mat2/invert\"),a=t(\"gl-mat3/invert\"),o=t(\"gl-mat4/invert\")},{\"gl-mat2/invert\":433,\"gl-mat3/invert\":337,\"gl-mat4/invert\":344}],433:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],434:[function(t,e,r){\"use strict\";function n(t,e){var r=Math.floor(e),n=e-r,i=r>=0&&r<t.shape[0],a=r+1>=0&&r+1<t.shape[0],o=i?+t.get(r):0,s=a?+t.get(r+1):0;return(1-n)*o+n*s}function i(t,e,r){var n=Math.floor(e),i=e-n,a=n>=0&&n<t.shape[0],o=n+1>=0&&n+1<t.shape[0],s=Math.floor(r),l=r-s,u=s>=0&&s<t.shape[1],c=s+1>=0&&s+1<t.shape[1],f=a&&u?t.get(n,s):0,h=a&&c?t.get(n,s+1):0,p=o&&u?t.get(n+1,s):0,d=o&&c?t.get(n+1,s+1):0;return(1-l)*((1-i)*f+i*p)+l*((1-i)*h+i*d)}function a(t,e,r,n){var 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c=e[0].label,f=a.slice(),h=f.indexOf(c);-1===h?f.push(c):f.splice(h,1),o.relayout(t,\"hiddenlabels\",f)}else{if(\"\"===l)u=[s.index];else for(var p=0;p<i.length;p++)r=i[p],r.legendgroup===l&&u.push(r.index);n=s.visible===!0?\"legendonly\":!0,o.restyle(t,\"visible\",n,u)}}})}),c.repositionLegend(t,h),t._context.editable){var p,d,g,v,m,y;o.Fx.dragElement({element:l.node(),prepFn:function(){g=Number(l.attr(\"x\")),v=Number(l.attr(\"y\")),m=Number(l.attr(\"width\")),y=Number(l.attr(\"height\")),o.Fx.setCursor(l)},moveFn:function(e,n){var i=t._fullLayout._size;l.call(o.Drawing.setPosition,g+e,v+n),p=o.Fx.dragAlign(g+e,m,i.l,i.l+i.w,r.xanchor),d=o.Fx.dragAlign(v+n+y,-y,i.t+i.h,i.t,r.yanchor);var a=o.Fx.dragCursors(p,d,r.xanchor,r.yanchor);o.Fx.setCursor(l,a)},doneFn:function(e){o.Fx.setCursor(l),e&&void 0!==p&&void 0!==d&&o.relayout(t,{\"legend.x\":p,\"legend.y\":d})}})}}},c.repositionLegend=function(t,e){var r=t._fullLayout,n=r._size,a=r.legend,l=a.borderwidth,u=0,c=0;e.each(function(t){var 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d=\"top\";\"bottom\"===a.yanchor||\"auto\"===a.yanchor&&a.y<=1/3?(h-=c,d=\"bottom\"):(\"middle\"===a.yanchor||\"auto\"===a.yanchor&&a.y<2/3)&&(h-=c/2,d=\"middle\"),u=Math.ceil(u),c=Math.ceil(c),f=Math.round(f),h=Math.round(h),r._infolayer.selectAll(\"svg.legend\").call(o.Drawing.setRect,f,h,u,c),r._infolayer.selectAll(\"svg.legend .bg\").call(o.Drawing.setRect,l/2,l/2,u-l,c-l),o.Plots.autoMargin(t,\"legend\",{x:a.x,y:a.y,l:u*({right:1,center:.5}[p]||0),r:u*({left:1,center:.5}[p]||0),b:c*({top:1,middle:.5}[d]||0),t:c*({bottom:1,middle:.5}[d]||0)})}},{\"../../plotly\":595,\"../../traces/pie/style_one\":729,\"../../traces/scatter/subtypes\":749,\"./attributes\":554,d3:320}],556:[function(t,e,r){\"use strict\";function n(t,e){var r=e.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=t._fullLayout,o={};if(\"zoom\"===n)for(var 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r&&(\"setBackground\"===t&&\"opaque\"===e[t]?r[t]=i:r[t]=e[t])}),e.plot3dPixelRatio&&!r.plotGlPixelRatio&&(r.plotGlPixelRatio=r.plot3dPixelRatio)),r.staticPlot&&(r.editable=!1,r.autosizable=!1,r.scrollZoom=!1,r.doubleClick=!1,r.showTips=!1,r.showLink=!1,r.displayModeBar=!1)}function o(t,e,r){var n=L.select(t).selectAll(\".plot-container\").data([0]);n.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=n.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),P.micropolar.manager.fillLayout(t),\"initial\"===t._fullLayout.autosize&&t._context.autosizable&&(w(t,{}),t._fullLayout.autosize=r.autosize=!0),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=P.micropolar.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var a=t.framework.svg(),o=1,s=t._fullLayout.title;\"\"!==s&&s||(o=0);var l=\"Click to enter title\",u=function(){this.call(P.util.convertToTspans)},c=a.select(\".title-group text\").call(u);if(t._context.editable){c.attr({\"data-unformatted\":s}),s&&s!==l||(o=.2,c.attr({\"data-unformatted\":l}).text(l).style({opacity:o}).on(\"mouseover.opacity\",function(){L.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){L.select(this).transition().duration(1e3).style(\"opacity\",0)}));var f=function(){this.call(P.util.makeEditable).on(\"edit\",function(e){t.framework({layout:{title:e}}),this.attr({\"data-unformatted\":e}).text(e).call(u),this.call(f)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};c.call(f)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),I.addLinks(t),Promise.resolve()}function s(t){var e,r;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1);var n=P.Axes.list({_fullLayout:t});for(e=0;e<n.length;e++){var i=n[e];i.anchor&&\"free\"!==i.anchor&&(i.anchor=P.Axes.cleanId(i.anchor)),i.overlaying&&(i.overlaying=P.Axes.cleanId(i.overlaying)),i.type||(i.isdate?i.type=\"date\":i.islog?i.type=\"log\":i.isdate===!1&&i.islog===!1&&(i.type=\"linear\")),(\"withzero\"===i.autorange||\"tozero\"===i.autorange)&&(i.autorange=!0,i.rangemode=\"tozero\"),delete i.islog,delete i.isdate,delete i.categories,f(i,\"domain\")&&delete i.domain,void 0!==i.autotick&&(void 0===i.tickmode&&(i.tickmode=i.autotick?\"auto\":\"linear\"),delete i.autotick)}void 0===t.annotations||Array.isArray(t.annotations)||(console.log(\"annotations must be an array\"),delete t.annotations);var a=(t.annotations||[]).length;for(e=0;a>e;e++){var o=t.annotations[e];o.ref&&(\"paper\"===o.ref?(o.xref=\"paper\",o.yref=\"paper\"):\"data\"===o.ref&&(o.xref=\"x\",o.yref=\"y\"),delete o.ref),l(o,\"xref\"),l(o,\"yref\")}void 0===t.shapes||Array.isArray(t.shapes)||(console.log(\"shapes must be an array\"),delete t.shapes);var s=(t.shapes||[]).length;for(e=0;s>e;e++){var u=t.shapes[e];l(u,\"xref\"),l(u,\"yref\")}var c=t.legend;c&&(c.x>3?(c.x=1.02,c.xanchor=\"left\"):c.x<-2&&(c.x=-.02,c.xanchor=\"right\"),c.y>3?(c.y=1.02,c.yanchor=\"bottom\"):c.y<-2&&(c.y=-.02,c.yanchor=\"top\")),\"rotate\"===t.dragmode&&(t.dragmode=\"orbit\"),t.scene1&&(t.scene||(t.scene=t.scene1),delete t.scene1);var h,p,d,g,v,m,y,b=I.getSubplotIds(t,\"gl3d\");for(e=0;e<b.length;e++)if(h=t[b[e]],p=h.cameraposition,Array.isArray(p)&&4===p[0].length){for(d=p[0],v=p[1],g=p[2],m=S([],d),y=[],r=0;3>r;++r)y[r]=v[e]+g*m[2+4*r];h.camera={eye:{x:y[0],y:y[1],z:y[2]},center:{x:v[0],y:v[1],z:v[2]},up:{x:m[1],y:m[5],z:m[9]}},delete h.cameraposition}return z.markTime(\"finished rest of cleanLayout, starting color\"),N.clean(t),z.markTime(\"finished cleanLayout color.clean\"),t}function l(t,e){var r=t[e],n=e.charAt(0);r&&\"paper\"!==r&&(t[e]=P.Axes.cleanId(r,n))}function u(t,e){for(var r=[],n=(t.concat(Array.isArray(e)?e:[]).filter(function(t){return\"uid\"in t}).map(function(t){return t.uid})),i=0;i<t.length;i++){var a=t[i];if(!(\"uid\"in a)||-1!==r.indexOf(a.uid)){var o,s;for(s=0;100>s&&(o=z.randstr(n),-1!==r.indexOf(o));s++);a.uid=z.randstr(n),n.push(a.uid)}if(r.push(a.uid),\"histogramy\"===a.type&&\"xbins\"in a&&!(\"ybins\"in a)&&(a.ybins=a.xbins,delete a.xbins),a.error_y&&\"opacity\"in a.error_y){var l=N.defaults,u=a.error_y.color||(I.traceIs(a,\"bar\")?N.defaultLine:l[i%l.length]);a.error_y.color=N.addOpacity(N.rgb(u),N.opacity(u)*a.error_y.opacity),delete a.error_y.opacity}\"bardir\"in a&&(\"h\"!==a.bardir||!I.traceIs(a,\"bar\")&&\"histogram\"!==a.type.substr(0,9)||(a.orientation=\"h\",x(a)),delete a.bardir),\"histogramy\"===a.type&&x(a),(\"histogramx\"===a.type||\"histogramy\"===a.type)&&(a.type=\"histogram\"),\"scl\"in a&&(a.colorscale=a.scl,delete a.scl),\"reversescl\"in a&&(a.reversescale=a.reversescl,delete a.reversescl),a.xaxis&&(a.xaxis=P.Axes.cleanId(a.xaxis,\"x\")),a.yaxis&&(a.yaxis=P.Axes.cleanId(a.yaxis,\"y\")),I.traceIs(a,\"gl3d\")&&a.scene&&(a.scene=I.subplotsRegistry.gl3d.cleanId(a.scene)),I.traceIs(a,\"pie\")||(Array.isArray(a.textposition)?a.textposition=a.textposition.map(c):a.textposition&&(a.textposition=c(a.textposition))),f(a,\"line\")&&delete a.line,\"marker\"in a&&(f(a.marker,\"line\")&&delete a.marker.line,f(a,\"marker\")&&delete a.marker),z.markTime(\"finished rest of cleanData, starting color\"),N.clean(a),z.markTime(\"finished cleanData color.clean\")}}function c(t){var e=\"middle\",r=\"center\";return-1!==t.indexOf(\"top\")?e=\"top\":-1!==t.indexOf(\"bottom\")&&(e=\"bottom\"),-1!==t.indexOf(\"left\")?r=\"left\":-1!==t.indexOf(\"right\")&&(r=\"right\"),e+\" \"+r}function f(t,e){return e in t&&\"object\"==typeof t[e]&&0===Object.keys(t[e]).length}function h(t){var e,r,n,i,a=P.Axes.list(t),o=t._fullData,s=t._fullLayout,l=t.calcdata=new Array(o.length);for(t.firstscatter=!0,t.numboxes=0,t._hmpixcount=0,t._hmlumcount=0,s._piecolormap={},s._piedefaultcolorcount=0,e=0;e<a.length;e++)a[e]._categories=[];for(e=0;e<o.length;e++)r=o[e],n=r._module,i=[],n&&r.visible===!0&&n.calc&&(i=n.calc(t,r)),Array.isArray(i)&&i[0]||(i=[{x:!1,y:!1}]),i[0].t||(i[0].t={}),i[0].trace=r,z.markTime(\"done with calcdata for \"+e),l[e]=i}function p(t,e){var r,n,i=e+1,a=[];for(r=0;r<t.length;r++)n=t[r],0>n?a.push(i+n):a.push(n);return a}function d(t,e,r){var n,i;for(n=0;n<e.length;n++){if(i=e[n],i!==parseInt(i,10))throw new Error(\"all values in \"+r+\" must be integers\");if(i>=t.data.length||i<-t.data.length)throw new Error(r+\" must be valid indices for gd.data.\");if(e.indexOf(i,n+1)>-1||i>=0&&e.indexOf(-t.data.length+i)>-1||0>i&&e.indexOf(t.data.length+i)>-1)throw new Error(\"each index in \"+r+\" must be unique.\")}}function g(t,e,r){if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"currentIndices is a required argument.\");if(Array.isArray(e)||(e=[e]),d(t,e,\"currentIndices\"),\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&d(t,r,\"newIndices\"),\"undefined\"!=typeof r&&e.length!==r.length)throw new Error(\"current and new indices must be of equal length.\")}function v(t,e,r){var n,i;if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"traces must be defined.\");for(Array.isArray(e)||(e=[e]),n=0;n<e.length;n++)if(i=e[n],\"object\"!=typeof i||Array.isArray(i)||null===i)throw new Error(\"all values in traces array must be non-array objects\");if(\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&r.length!==e.length)throw new Error(\"if indices is specified, traces.length must equal indices.length\")}function m(t,e,r,n){var i=z.isPlainObject(n);if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array\");if(!z.isPlainObject(e))throw new Error(\"update must be a key:value object\");if(\"undefined\"==typeof r)throw new Error(\"indices must be an integer or array of integers\");d(t,r,\"indices\");for(var a in e){if(!Array.isArray(e[a])||e[a].length!==r.length)throw new Error(\"attribute \"+a+\" must be an array of length equal to indices array length\");if(i&&(!(a in n)||!Array.isArray(n[a])||n[a].length!==e[a].length))throw new Error(\"when maxPoints is set as a key:value object it must contain a 1:1 corrispondence with the keys and number of traces in the update object\")}}function y(t,e,r,n){var i,a,o,s,l,u=z.isPlainObject(n),c=[];Array.isArray(r)||(r=[r]),r=p(r,t.data.length-1);for(var f in e)for(var h=0;h<r.length;h++){if(i=t.data[r[h]],o=z.nestedProperty(i,f),a=o.get(),s=e[f][h],!Array.isArray(s))throw new Error(\"attribute: \"+f+\" index: \"+h+\" must be an 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i=t.hoverinfo.split(\"+\");for(e=0;e<i.length;e++)\"x\"===i[e]?i[e]=\"y\":\"y\"===i[e]&&(i[e]=\"x\");t.hoverinfo=i.join(\"+\")}}function _(t){var e,r={left:0,right:0,bottom:0,top:0};if(t)for(e in t)t.hasOwnProperty(e)&&(r.left+=t[e].left||0,r.right+=t[e].right||0,r.bottom+=t[e].bottom||0,r.top+=t[e].top||0);return r}function w(t,e){var r,n,i,a=t._fullLayout,o=t._context;if(t.emit(\"plotly_autosize\"),t._context.fillFrame)i=window.innerWidth,n=window.innerHeight,document.body.style.overflow=\"hidden\";else if(C(o.frameMargins)&&o.frameMargins>0){var s=_(t._boundingBoxMargins),l=s.left+s.right,u=s.bottom+s.top,c=a._container.node().getBoundingClientRect(),f=1-2*o.frameMargins;i=Math.round(f*(c.width-l)),n=Math.round(f*(c.height-u))}else r=window.getComputedStyle(t),n=parseFloat(r.height)||a.height,i=parseFloat(r.width)||a.width;return Math.abs(a.width-i)>1||Math.abs(a.height-n)>1?(a.height=t.layout.height=n,a.width=t.layout.width=i):\"initial\"!==a.autosize&&(delete e.autosize,a.autosize=t.layout.autosize=!0),I.sanitizeMargins(a),e}function k(t){var e=L.select(t),r=t._fullLayout;if(r._hasGL3D&&I.subplotsRegistry.gl3d.initAxes(t),r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),\"initial\"===r.autosize&&(w(t,{}),r.autosize=!0,t.layout.autosize=!0),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([0]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._geocontainer=r._paperdiv.selectAll(\".geo-container\").data([0]),r._geocontainer.enter().append(\"div\").classed(\"geo-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var n=[];L.selectAll(\"defs\").each(function(){this.id&&n.push(this.id.split(\"-\")[1]);\n",
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n,i,a=t._fullLayout._plots={},o=0;o<e.length;o++)n=e[o],i=a[n]={},i.id=n,i.x=r(n,\"x\"),i.y=r(n,\"y\"),i.xaxis=i.x(),i.yaxis=i.y()}function M(t,e){function r(t){t.append(\"g\").classed(\"imagelayer\",!0),t.append(\"g\").classed(\"maplayer\",!0),t.append(\"g\").classed(\"barlayer\",!0),t.append(\"g\").classed(\"errorlayer\",!0),t.append(\"g\").classed(\"boxlayer\",!0),t.append(\"g\").classed(\"scatterlayer\",!0)}var n=t._fullLayout,i=[];n._paper.selectAll(\"g.subplot\").data(e).enter().append(\"g\").classed(\"subplot\",!0).each(function(a){var o=n._plots[a],s=o.plotgroup=L.select(this).classed(a,!0),l=o.xaxis,u=o.yaxis;o.overlays=[];var c=P.Axes.getFromId(t,l.overlaying)||l;c!==l&&c.overlaying&&(c=l,l.overlaying=!1);var f=P.Axes.getFromId(t,u.overlaying)||u;f!==u&&f.overlaying&&(f=u,u.overlaying=!1);var h=c._id+f._id;h!==a&&-1!==e.indexOf(h)?(o.mainplot=h,i.push(o),l.domain=c.domain.slice(),u.domain=f.domain.slice()):(o.bg=s.append(\"rect\").style(\"stroke-width\",0),o.gridlayer=s.append(\"g\"),o.overgrid=s.append(\"g\"),o.zerolinelayer=s.append(\"g\"),o.overzero=s.append(\"g\"),o.plot=s.append(\"svg\").call(r),o.overplot=s.append(\"g\"),o.xlines=s.append(\"path\"),o.ylines=s.append(\"path\"),o.overlines=s.append(\"g\"),o.xaxislayer=s.append(\"g\"),o.yaxislayer=s.append(\"g\"),o.overaxes=s.append(\"g\")),o.draglayer=n._draggers.append(\"g\")}),i.forEach(function(t){var e=n._plots[t.mainplot];e.overlays.push(t),t.gridlayer=e.overgrid.append(\"g\"),t.zerolinelayer=e.overzero.append(\"g\"),t.plot=e.overplot.append(\"svg\").call(r),t.xlines=e.overlines.append(\"path\"),t.ylines=e.overlines.append(\"path\"),t.xaxislayer=e.overaxes.append(\"g\"),t.yaxislayer=e.overaxes.append(\"g\")}),e.forEach(function(t){var 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s=t.trace.hoverinfo;return\"all\"!==s&&(s=s.split(\"+\"),-1===s.indexOf(\"x\")&&(t.xLabel=void 0),-1===s.indexOf(\"y\")&&(t.yLabel=void 0),-1===s.indexOf(\"z\")&&(t.zLabel=void 0),-1===s.indexOf(\"text\")&&(t.text=void 0),-1===s.indexOf(\"name\")&&(t.name=void 0)),t}function l(t,e){var r,n,i=e.hovermode,a=e.rotateLabels,o=e.bgColor,s=e.container,l=e.outerContainer,u=t[0],c=u.xa,f=u.ya,h=\"y\"===i?\"yLabel\":\"xLabel\",p=u[h],d=(String(p)||\"\").split(\" \")[0],g=l.node().getBoundingClientRect(),v=g.top,m=g.width,y=g.height,b=u.distance<=T.MAXDIST&&(\"x\"===i||\"y\"===i);for(r=0;r<t.length;r++){n=t[r].trace.hoverinfo;var w=n.split(\"+\");if(-1===w.indexOf(\"all\")&&-1===w.indexOf(i)){b=!1;break}}var A=s.selectAll(\"g.axistext\").data(b?[0]:[]);A.enter().append(\"g\").classed(\"axistext\",!0),A.exit().remove(),A.each(function(){var e=x.select(this),r=e.selectAll(\"path\").data([0]),n=e.selectAll(\"text\").data([0]);r.enter().append(\"path\").style({fill:k.Color.defaultLine,\"stroke-width\":\"1px\",stroke:k.Color.background}),n.enter().append(\"text\").call(k.Drawing.font,j,I,k.Color.background).attr(\"data-notex\",1),n.text(p).call(k.util.convertToTspans).call(k.Drawing.setPosition,0,0).selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),e.attr(\"transform\",\"\");var a=n.node().getBoundingClientRect();if(\"x\"===i){n.attr(\"text-anchor\",\"middle\").call(k.Drawing.setPosition,0,\"top\"===c.side?v-a.bottom-R-O:v-a.top+R+O).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var o=\"top\"===c.side?\"-\":\"\";r.attr(\"d\",\"M0,0L\"+R+\",\"+o+R+\"H\"+(O+a.width/2)+\"v\"+o+(2*O+a.height)+\"H-\"+(O+a.width/2)+\"V\"+o+R+\"H-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(u.x0+u.x1)/2)+\",\"+(f._offset+(\"top\"===c.side?0:f._length))+\")\")}else{n.attr(\"text-anchor\",\"right\"===f.side?\"start\":\"end\").call(k.Drawing.setPosition,(\"right\"===f.side?1:-1)*(O+R),v-a.top-a.height/2).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var s=\"right\"===f.side?\"\":\"-\";r.attr(\"d\",\"M0,0L\"+s+R+\",\"+R+\"V\"+(O+a.height/2)+\"h\"+s+(2*O+a.width)+\"V-\"+(O+a.height/2)+\"H\"+s+R+\"V-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(\"right\"===f.side?c._length:0))+\",\"+(f._offset+(u.y0+u.y1)/2)+\")\")}t=t.filter(function(t){return void 0!==t.zLabelVal||(t[h]||\"\").split(\" \")[0]===d})});var M=s.selectAll(\"g.hovertext\").data(t,function(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr||\"\"].join(\",\")});return M.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var t=x.select(this);t.append(\"rect\").call(k.Color.fill,k.Color.addOpacity(o,.8)),t.append(\"text\").classed(\"name\",!0).call(k.Drawing.font,j,I),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(k.Drawing.font,j,I)}),M.exit().remove(),M.each(function(t){var e=x.select(this).attr(\"transform\",\"\"),r=\"\",n=\"\",s=k.Color.opacity(t.color)?t.color:k.Color.defaultLine,l=k.Color.combine(s,o),u=_(l).getBrightness()>128?\"#000\":k.Color.background;if(t.name&&void 0===t.zLabelVal){\n",
+       "var h=document.createElement(\"p\");h.innerHTML=t.name,r=h.textContent||\"\",r.length>15&&(r=r.substr(0,12)+\"...\")}void 0!==t.zLabel?(void 0!==t.xLabel&&(n+=\"x: \"+t.xLabel+\"<br>\"),void 0!==t.yLabel&&(n+=\"y: \"+t.yLabel+\"<br>\"),n+=(n?\"z: \":\"\")+t.zLabel):b&&t[i+\"Label\"]===p?n=t[(\"x\"===i?\"y\":\"x\")+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&(n=t.yLabel):n=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",t.text&&(n+=(n?\"<br>\":\"\")+t.text),\"\"===n&&(\"\"===r&&e.remove(),n=r);var d=e.select(\"text.nums\").style(\"fill\",u).call(k.Drawing.setPosition,0,0).text(n).attr(\"data-notex\",1).call(k.util.convertToTspans);d.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0);var g=e.select(\"text.name\"),w=0;r&&r!==n?(g.style(\"fill\",l).text(r).call(k.Drawing.setPosition,0,0).attr(\"data-notex\",1).call(k.util.convertToTspans),g.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),w=g.node().getBoundingClientRect().width+2*O):(g.remove(),e.select(\"rect\").remove()),e.select(\"path\").style({fill:l,stroke:u});var A,M,T=d.node().getBoundingClientRect(),E=c._offset+(t.x0+t.x1)/2,S=f._offset+(t.y0+t.y1)/2,C=Math.abs(t.x1-t.x0),P=Math.abs(t.y1-t.y0),z=T.width+R+O+w;t.ty0=v-T.top,t.bx=T.width+2*O,t.by=T.height+2*O,t.anchor=\"start\",t.txwidth=T.width,t.tx2width=w,t.offset=0,a?(t.pos=E,A=y>=S+P/2+z,M=S-P/2-z>=0,\"top\"!==t.idealAlign&&A||!M?A?(S+=P/2,t.anchor=\"start\"):t.anchor=\"middle\":(S-=P/2,t.anchor=\"end\")):(t.pos=S,A=m>=E+C/2+z,M=E-C/2-z>=0,\"left\"!==t.idealAlign&&A||!M?A?(E+=C/2,t.anchor=\"start\"):t.anchor=\"middle\":(E-=C/2,t.anchor=\"end\")),d.attr(\"text-anchor\",t.anchor),w&&g.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",\"translate(\"+E+\",\"+S+\")\"+(a?\"rotate(\"+L+\")\":\"\"))}),M}function u(t,e){function r(t){var e=t[0],r=t[t.length-1];if(i=f-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-h,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(.01>a)){if(-.01>i){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var u=0;for(o=0;o<t.length;o++)l=t[o],l.pos+l.dp+l.size>h&&u++;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos>h-1&&(l.del=!0,u--);for(o=0;o<t.length&&!(0>=u);o++)if(l=t[o],l.pos<f+1)for(l.del=!0,u--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos+l.dp+l.size>h&&(l.del=!0,u--)}}}for(var n,i,a,o,s,l,u,c=0,f=e._offset,h=e._offset+e._length,p=t.map(function(t,r){return[{i:r,dp:0,pos:t.pos,posref:t.posref,size:t.by*(\"x\"===e._id.charAt(0)?C:1)/2}]}).sort(function(t,e){return t[0].posref-e[0].posref});!n&&c<=t.length;){for(c++,n=!0,o=0;o<p.length-1;){var d=p[o],g=p[o+1],v=d[d.length-1],m=g[0];if(i=v.pos+v.dp+v.size-m.pos-m.dp+m.size,i>.01){for(s=g.length-1;s>=0;s--)g[s].dp+=i;for(d.push.apply(d,g),p.splice(o+1,1),u=0,s=d.length-1;s>=0;s--)u+=d[s].dp;for(a=u/d.length,s=d.length-1;s>=0;s--)d[s].dp-=a;n=!1}else o++}p.forEach(r)}for(o=p.length-1;o>=0;o--){var y=p[o];for(s=y.length-1;s>=0;s--){var b=y[s],x=t[b.i];x.offset=b.dp,x.del=b.del}}}function 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r=Math.max(0,Math.min(D,t+K)),n=Math.max(0,Math.min(B,e+Q)),i=Math.abs(r-K),a=Math.abs(n-Q),o=Math.floor(Math.min(a,i,V)/2);J.l=Math.min(K,r),J.r=Math.max(K,r),J.t=Math.min(Q,n),J.b=Math.max(Q,n),!G||a<Math.min(Math.max(.6*i,U),V)?U>i?(nt=\"\",J.r=J.l,J.t=J.b,at.attr(\"d\",\"M0,0Z\")):(J.t=0,J.b=B,nt=\"x\",at.attr(\"d\",\"M\"+(J.l-.5)+\",\"+(Q-V-.5)+\"h-3v\"+(2*V+1)+\"h3ZM\"+(J.r+.5)+\",\"+(Q-V-.5)+\"h3v\"+(2*V+1)+\"h-3Z\")):!H||i<Math.min(.6*a,V)?(J.l=0,J.r=D,nt=\"y\",at.attr(\"d\",\"M\"+(K-V-.5)+\",\"+(J.t-.5)+\"v-3h\"+(2*V+1)+\"v3ZM\"+(K-V-.5)+\",\"+(J.b+.5)+\"v3h\"+(2*V+1)+\"v-3Z\")):(nt=\"xy\",at.attr(\"d\",\"M\"+(J.l-3.5)+\",\"+(J.t-.5+o)+\"h3v\"+-o+\"h\"+o+\"v-3h-\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.t-.5+o)+\"h-3v\"+-o+\"h\"+-o+\"v-3h\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.b+.5-o)+\"h-3v\"+o+\"h\"+-o+\"v3h\"+(o+3)+\"ZM\"+(J.l-3.5)+\",\"+(J.b+.5-o)+\"h3v\"+o+\"h\"+o+\"v3h-\"+(o+3)+\"Z\")),J.w=J.r-J.l,J.h=J.b-J.t,it.attr(\"d\",et+\"M\"+J.l+\",\"+J.t+\"v\"+J.h+\"h\"+J.w+\"v-\"+J.h+\"h-\"+J.w+\"Z\"),rt||(it.transition().style(\"fill\",tt>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),at.transition().style(\"opacity\",1).duration(200),rt=!0)}function 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r=0,n=0,i=t.length;i>n;++n)r+=t[n]*e[n];return r}function b(t,e){return[t[1]*e[2]-t[2]*e[1],t[2]*e[0]-t[0]*e[2],t[0]*e[1]-t[1]*e[0]]}function x(t){for(var e=0,r=arguments.length,n=[];++e<r;)n.push(arguments[e]);var i=_.dispatch.apply(null,n);return i.of=function(e,r){return function(n){var a;try{a=n.sourceEvent=_.event,n.target=t,_.event=n,i[n.type].apply(e,r)}finally{_.event=a}}},i}var _=t(\"d3\"),w=Math.PI/180,k=180/Math.PI,A={cursor:\"pointer\"},M={cursor:\"auto\"};e.exports=n},{d3:320}],623:[function(t,e,r){\"use strict\";function n(t,e){var r=t.projection,n=t.zoom,a=function(){t.makeProjection(e),t.makePath(),n.scale(r.scale()),n.translate(r.translate()),i.loneUnhover(t.hoverContainer),t.render()};return a}var i=t(\"../cartesian/graph_interact\");e.exports=n},{\"../cartesian/graph_interact\":603}],624:[function(t,e,r){\"use strict\";function n(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxStart=[0,0],this.boxEnd=[0,0]}function i(t){var e=t.mouseContainer,r=t.glplot,i=new n(e,r);return i.mouseListener=a(e,function(e,n,a){function o(e,r,n){var a=Math.min(r,n),o=Math.max(r,n);a!==o?(e[0]=a,e[1]=o,i.dataBox=e):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}var s=t.xaxis.range,l=t.yaxis.range,u=r.viewBox,c=i.lastPos[0],f=i.lastPos[1];switch(n*=r.pixelRatio,a*=r.pixelRatio,a=u[3]-u[1]-a,t.fullLayout.dragmode){case\"zoom\":if(e){var h=n/(u[2]-u[0])*(s[1]-s[0])+s[0],p=a/(u[3]-u[1])*(l[1]-l[0])+l[0];i.boxEnabled||(i.boxStart[0]=h,i.boxStart[1]=p),i.boxEnd[0]=h,i.boxEnd[1]=p,i.boxEnabled=!0}else i.boxEnabled&&(o(s,i.boxStart[0],i.boxEnd[0]),o(l,i.boxStart[1],i.boxEnd[1]),i.boxEnabled=!1);break;case\"pan\":if(i.boxEnabled=!1,e){var d=(c-n)*(s[1]-s[0])/(r.viewBox[2]-r.viewBox[0]),g=(f-a)*(l[1]-l[0])/(r.viewBox[3]-r.viewBox[1]);s[0]+=d,s[1]+=d,l[0]+=g,l[1]+=g,i.lastInputTime=Date.now(),t.cameraChanged()}}i.lastPos[0]=n,i.lastPos[1]=a}),i.wheelListener=o(e,function(e,n){var a=t.xaxis.range,o=t.yaxis.range,s=r.viewBox,l=i.lastPos[0],u=i.lastPos[1];switch(t.fullLayout.dragmode){case\"zoom\":break;case\"pan\":var c=Math.exp(.1*n/(s[3]-s[1])),f=l/(s[2]-s[0])*(a[1]-a[0])+a[0],h=u/(s[3]-s[1])*(o[1]-o[0])+o[0];a[0]=(a[0]-f)*c+f,a[1]=(a[1]-f)*c+f,o[0]=(o[0]-h)*c+h,o[1]=(o[1]-h)*c+h,i.lastInputTime=Date.now(),t.cameraChanged()}return!0}),i}var a=t(\"mouse-change\"),o=t(\"mouse-wheel\");e.exports=i},{\"mouse-change\":426,\"mouse-wheel\":430}],625:[function(t,e,r){\"use strict\";function 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e=this.scene,r=a.Plots.getSubplotIds(e.fullLayout,\"gl2d\"),n=a.Axes.findSubplotsWithAxis(r,t);return 0!==n.indexOf(e.id)},l.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},l.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},l.getLabelPad=function(t,e){var r=1.5,n=e.titlefont.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?-10+n*(r+(i?1:0)):-10+n*(r+(i?.5:0)):\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},l.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},l.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":577,\"../../lib/str2rgbarray\":588,\"../../plotly\":595}],626:[function(t,e,r){\"use strict\";var 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n(t,e){this.container=t.container,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.updateAxes(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=d(this),this.traces={},this.spikes=f(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;2>r;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/plots\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),f=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),p=t(\"./convert\"),d=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),m=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o){a=document.createElement(\"canvas\");try{o=a.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0})}catch(t){throw new Error([\"Error creating static canvas/context for image server\"].join(\" \"))}}this.canvas=a,this.gl=o}else{var e,r=document.createElement(\"canvas\"),n={premultipliedAlpha:!0};try{e=r.getContext(\"webgl\",n)}catch(t){}if(!e)try{e=r.getContext(\"experimental-webgl\",n)}catch(t){}e||v(this),this.canvas=r,this.gl=e}var i=this.canvas,s=this.pixelRatio,l=this.fullLayout;i.width=0|Math.ceil(s*l.width),i.height=0|Math.ceil(s*l.height),i.style.width=\"100%\",i.style.height=\"100%\",i.style.position=\"absolute\",i.style.top=\"0px\",i.style.left=\"0px\",i.style[\"pointer-events\"]=\"none\";var u=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");u.style.position=\"absolute\",u.style.top=u.style.left=\"0px\",u.style.width=u.style.height=\"100%\",u.style[\"z-index\"]=20,u.style[\"pointer-events\"]=\"none\";var c=this.mouseContainer=document.createElement(\"div\");c.style.position=\"absolute\";var f=this.container;f.appendChild(i),f.appendChild(u),f.appendChild(c)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.glplot.setDirty(!0),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new 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o=e.width,u=e.height,c=0|Math.ceil(a*o),f=0|Math.ceil(a*u),h=this.canvas;(h.width!==c||h.height!==f)&&(h.width=c,h.height=f),t?Array.isArray(t)||(t=[t]):t=[];var p,d;for(r=0;r<t.length;++r){if(p=t[r],d=this.traces[p.uid])d.update(p);else{var g=s.getModule(p.type);d=g.plot(this,p)}this.traces[p.uid]=d}var v=Object.keys(this.traces);t:for(r=0;r<v.length;++r){for(n=0;n<t.length;++n)if(t[n].uid===v[r])continue t;d=this.traces[v[r]],d.dispose(),delete this.traces[v[r]]}var y=this.glplotOptions;y.merge(e),y.screenBox=[0,0,o,u];var b=e._size,x=this.xaxis.domain,_=this.yaxis.domain;y.viewBox=[b.l+x[0]*b.w,b.b+_[0]*b.h,o-b.r-(1-x[1])*b.w,u-b.t-(1-_[1])*b.h],this.mouseContainer.style.width=b.w*(x[1]-x[0])+\"px\",this.mouseContainer.style.height=b.h*(_[1]-_[0])+\"px\",this.mouseContainer.height=b.h*(_[1]-_[0]),this.mouseContainer.style.left=b.l+x[0]*b.w+\"px\",this.mouseContainer.style.top=b.t+(1-_[1])*b.h+\"px\";var 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o=n._size,s=this.xaxis.domain,l=this.yaxis.domain,c=t.pick(i/t.pixelRatio+o.l+s[0]*o.w,a/t.pixelRatio-(o.t+(1-l[1])*o.h));if(c&&n.hovermode){var f=c.object._trace.handlePick(c);if(f&&(!this.lastPickResult||this.lastPickResult.trace!==f.trace||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var h=this.lastPickResult=f;this.spikes.update({center:c.dataCoord}),h.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(c.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(c.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio];var p=h.hoverinfo;if(\"all\"!==p){var d=p.split(\"+\");-1===d.indexOf(\"x\")&&(h.traceCoord[0]=void 0),-1===d.indexOf(\"y\")&&(h.traceCoord[1]=void 0),-1===d.indexOf(\"text\")&&(h.textLabel=void 0),-1===d.indexOf(\"name\")&&(h.name=void 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i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":288,\"mouse-change\":426,\"mouse-wheel\":430,\"right-now\":440}],629:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"gl3d\",s),u=e[s]._scene;void 0===u&&(u=new n({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),e[s]._scene=u),u.plot(l,e,t.layout)}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\"),r.initAxes=function(t){var e=t._fullLayout;delete e.xaxis,delete e.yaxis;for(var r=i.getSubplotIds(e,\"gl3d\"),n=0;n<r.length;++n)for(var o=r[n],s=e[o],l=0;3>l;++l){var u=a[l],c=s[u];c._td=t}}},{\"../plots\":642,\"./layout/attributes\":630,\"./layout/defaults\":634,\"./layout/layout_attributes\":635,\"./scene\":639,\"./set_convert\":640}],630:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"sceneid\",dflt:\"scene\"}}},{}],631:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:\"rgb(0,0,0)\"},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},title:n.title,titlefont:n.titlefont,type:n.type,autorange:n.autorange,rangemode:n.rangemode,range:n.range,fixedrange:n.fixedrange,tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,mirror:n.mirror,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:n.tickfont,tickangle:n.tickangle,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:n.showline,linecolor:n.linecolor,linewidth:n.linewidth,showgrid:n.showgrid,gridcolor:i({},n.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:n.gridwidth,zeroline:n.zeroline,zerolinecolor:n.zerolinecolor,zerolinewidth:n.zerolinewidth}},{\"../../../lib/extend\":574,\"../../cartesian/layout_attributes\":605}],632:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"./axis_attributes\"),a=t(\"../../cartesian/axis_defaults\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=function(){};e.exports=function(t,e,r){function l(t,e){return n.coerce(u,c,i,t,e)}for(var u,c,f=0;f<o.length;f++){var h=o[f];u=t[h]||{},c={_id:h[0]+r.scene,_name:h},e[h]=c=a(u,c,l,{font:r.font,letter:h[0],data:r.data,showGrid:!0}),l(\"gridcolor\"),l(\"title\",h[0]),c.setScale=s,l(\"showspikes\")&&(l(\"spikesides\"),l(\"spikethickness\"),l(\"spikecolor\")),l(\"showbackground\")&&l(\"backgroundcolor\"),l(\"showaxeslabels\")}}},{\"../../../lib\":578,\"../../cartesian/axis_defaults\":599,\"./axis_attributes\":631}],633:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=l(this.tickPad),this._defaultLabelPad=l(this.labelPad),this._defaultLineTickLength=l(this.lineTickLength)}function i(t){var e=new n;return e.merge(t),e}var a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;3>r;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":577,\"../../../lib/str2rgbarray\":588,arraytools:298}],634:[function(t,e,r){\"use strict\";var n=t(\"../../../plotly\"),i=t(\"./layout_attributes\"),a=t(\"./axis_defaults\");e.exports=function(t,e,r){function o(t,e){return n.Lib.coerce(u,c,i,t,e)}if(e._hasGL3D){var s,l=n.Plots.getSubplotIdsInData(r,\"gl3d\");delete e.xaxis,delete e.yaxis;var u,c,f=l.length;for(s=0;f>s;++s){var h=l[s];void 0!==t[h]?u=t[h]:t[h]=u={},c=e[h]||{},o(\"bgcolor\");for(var p=Object.keys(i.camera),d=0;d<p.length;d++)o(\"camera.\"+p[d]+\".x\"),o(\"camera.\"+p[d]+\".y\"),o(\"camera.\"+p[d]+\".z\");o(\"domain.x\",[s/f,(s+1)/f]),o(\"domain.y\");var g=!!o(\"aspectratio.x\")&&!!o(\"aspectratio.y\")&&!!o(\"aspectratio.z\"),v=g?\"manual\":\"auto\",m=o(\"aspectmode\",v);g||(u.aspectratio=c.aspectratio={x:1,y:1,z:1},\"manual\"===m&&(c.aspectmode=\"auto\")),a(u,c,{font:e.font,scene:h,data:r}),e[h]=c}}}},{\"../../../plotly\":595,\"./axis_defaults\":632,\"./layout_attributes\":635}],635:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":574,\"./axis_attributes\":631}],636:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;3>e;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":588}],637:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;3>r;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,u=[[],[],[]],c=0;3>c;++c){var f=i[s[c]];if(f._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(f._length)===1/0)u[c]=[];else{f.range[0]=r[c].lo/t.dataScale[c],f.range[1]=r[c].hi/t.dataScale[c],f._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var h=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var 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i=t(\"../plotly\"),a=t(\"d3\"),o=t(\"../constants/xmlns_namespaces\");e.exports=function(t,e){var r,s,l=t._fullLayout,u=l._paper,c=l._size;u.insert(\"rect\",\":first-child\").call(i.Drawing.setRect,0,0,l.width,l.height).call(i.Color.fill,l.paper_bgcolor);var f,h=i.Plots.getSubplotIds(l,\"gl3d\");for(s=0;s<h.length;s++)f=l[h[s]],r=f.domain,n(l,f._scene,{x:c.l+c.w*r.x[0],y:c.t+c.h*(1-r.y[1]),width:c.w*(r.x[1]-r.x[0]),height:c.h*(r.y[1]-r.y[0])});var p,d=i.Plots.getSubplotIds(l,\"gl2d\");for(s=0;s<d.length;s++)p=l._plots[d[s]],n(l,p._scene2d,{x:c.l,y:c.t,width:c.w,height:c.h});var g,v,m=i.Plots.getSubplotIds(l,\"geo\");for(s=0;s<m.length;s++)g=l[m[s]],r=g.domain,v=g._geo.framework,v.attr(\"style\",null),v.attr({x:c.l+c.w*r.x[0]+g._marginX,y:c.t+c.h*(1-r.y[1])+g._marginY,width:g._width,height:g._height}),l._geoimages.node().appendChild(v.node());if(l._toppaper){var 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.supplyLayoutDefaults=t(\"./layout_defaults\"),n.layoutAttributes=t(\"./layout_attributes\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.style=t(\"./style\"),n.styleOne=t(\"./style_one\"),n.moduleType=\"trace\",n.name=\"pie\",n.basePlotModule=t(\"../../plots/cartesian\"),n.categories=[\"pie\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/cartesian\":604,\"./attributes\":720,\"./calc\":721,\"./defaults\":722,\"./layout_attributes\":725,\"./layout_defaults\":726,\"./plot\":727,\"./style\":728,\"./style_one\":729}],725:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\"}}},{}],726:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\")}},{\"../../lib\":578,\"./layout_attributes\":725}],727:[function(t,e,r){\"use strict\";function n(t,e,r){var n=Math.sqrt(t.width*t.width+t.height*t.height),a=t.width/t.height,o=Math.PI*Math.min(e.v/r.vTotal,.5),s=1-r.trace.hole,l=i(e,r),u={scale:l*r.r*2/n,rCenter:1-l,rotate:0};if(u.scale>=1)return u;var c=a+1/(2*Math.tan(o)),f=r.r*Math.min(1/(Math.sqrt(c*c+.5)+c),s/(Math.sqrt(a*a+s/2)+a)),h={scale:2*f/t.height,rCenter:Math.cos(f/r.r)-f*a/r.r,rotate:(180/Math.PI*e.midangle+720)%180-90},p=1/a,d=p+1/(2*Math.tan(o)),g=r.r*Math.min(1/(Math.sqrt(d*d+.5)+d),s/(Math.sqrt(p*p+s/2)+p)),v={scale:2*g/t.width,rCenter:Math.cos(g/r.r)-g/a/r.r,rotate:(180/Math.PI*e.midangle+810)%180-90},m=v.scale>h.scale?v:h;return u.scale<1&&m.scale>u.scale?m:u}function i(t,e){if(t.v===e.vTotal&&!e.trace.hole)return 1;var r=Math.PI*Math.min(t.v/e.vTotal,.5);return Math.min(1/(1+1/Math.sin(r)),(1-e.trace.hole)/2)}function a(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return 0>r&&(i*=-1),0>n&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function o(t,e){function 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r,n,i,a,o,s,l,u,c,f=t[0],h=f.trace,p=h.tilt,d=h.rotation*Math.PI/180,g=2*Math.PI/f.vTotal,v=\"px0\",m=\"px1\";if(\"counterclockwise\"===h.direction){for(l=0;l<t.length&&t[l].hidden;l++);if(l===t.length)return;d+=g*t[l].v,g*=-1,v=\"px1\",m=\"px0\"}for(p&&(a=p*Math.PI/180,r=h.tiltaxis*Math.PI/180,o=Math.sin(r)*Math.cos(r),s=1-Math.cos(a),n=Math.sin(r),i=Math.cos(r)),c=e(d),l=0;l<t.length;l++)u=t[l],u.hidden||(u[v]=c,d+=g*u.v/2,u.pxmid=e(d),u.midangle=d,d+=g*u.v/2,c=e(d),u[m]=c,u.largeArc=u.v>f.vTotal/2?1:0)}function u(t,e,r){if(!t)return 1;var n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var c=t(\"d3\"),f=t(\"../../plots/cartesian/graph_interact\"),h=t(\"../../components/color\"),p=t(\"../../components/drawing\"),d=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;s(e,r._size);var 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s=i(o,u),l=k+o.pxmid[0]*(1-s),c=A+o.pxmid[1]*(1-s),h=[];-1!==a.indexOf(\"label\")&&h.push(o.label),n.text&&n.text[o.i]&&-1!==a.indexOf(\"text\")&&h.push(n.text[o.i]),-1!==a.indexOf(\"value\")&&h.push(g.formatPieValue(o.v)),-1!==a.indexOf(\"percent\")&&h.push(g.formatPiePercent(o.v/u.vTotal)),f.loneHover({x0:l-s*u.r,x1:l+s*u.r,y:c,text:h.join(\"<br>\"),name:-1!==a.indexOf(\"name\")?n.name:void 0,color:o.color,idealAlign:o.pxmid[0]<0?\"left\":\"right\"},{container:r._hoverlayer.node(),outerContainer:r._paper.node()}),f.hover(t,e,\"pie\"),E=!0}}function h(){E&&(f.loneUnhover(r._hoverlayer.node()),E=!1)}function y(){t._hoverdata=[o],t._hoverdata.trace=e.trace,f.click(t,{target:!0})}function x(t,e,r,n){return\"a\"+n*u.r+\",\"+n*w+\" \"+b+\" \"+o.largeArc+(r?\" 1 \":\" 0 \")+n*(e[0]-t[0])+\",\"+n*(e[1]-t[1])}if(o.hidden)return void c.select(this).selectAll(\"path,g\").remove();l[o.pxmid[1]<0?0:1][o.pxmid[0]<0?0:1].push(o);var k=u.cx+_[0],A=u.cy+_[1],M=c.select(this),T=M.selectAll(\"path.surface\").data([o]),E=!1;if(T.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),M.select(\"path.textline\").remove(),M.on(\"mouseover\",s).on(\"mouseout\",h).on(\"click\",y),v.pull){var L=+(Array.isArray(v.pull)?v.pull[o.i]:v.pull)||0;L>0&&(k+=L*o.pxmid[0],A+=L*o.pxmid[1])}o.cxFinal=k,o.cyFinal=A;var S=v.hole;if(o.v===u.vTotal){var C=\"M\"+(k+o.px0[0])+\",\"+(A+o.px0[1])+x(o.px0,o.pxmid,!0,1)+x(o.pxmid,o.px0,!0,1)+\"Z\";S?T.attr(\"d\",\"M\"+(k+S*o.px0[0])+\",\"+(A+S*o.px0[1])+x(o.px0,o.pxmid,!1,S)+x(o.pxmid,o.px0,!1,S)+\"Z\"+C):T.attr(\"d\",C)}else{var P=x(o.px0,o.px1,!0,1);if(S){var z=1-S;T.attr(\"d\",\"M\"+(k+S*o.px1[0])+\",\"+(A+S*o.px1[1])+x(o.px1,o.px0,!1,S)+\"l\"+z*o.px0[0]+\",\"+z*o.px0[1]+P+\"Z\")}else T.attr(\"d\",\"M\"+k+\",\"+A+\"l\"+o.px0[0]+\",\"+o.px0[1]+P+\"Z\")}var R=Array.isArray(v.textposition)?v.textposition[o.i]:v.textposition,O=M.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==R?[0]:[]);O.enter().append(\"g\").classed(\"slicetext\",!0),O.exit().remove(),O.each(function(){var t=c.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(o.text).attr({\"class\":\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(p.font,\"outside\"===R?v.outsidetextfont:v.insidetextfont).call(d.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var e,r=p.bBox(t.node());\"outside\"===R?e=a(r,o):(e=n(r,o,u),\"auto\"===R&&e.scale<1&&(t.call(p.font,v.outsidetextfont),(v.outsidetextfont.family!==v.insidetextfont.family||v.outsidetextfont.size!==v.insidetextfont.size)&&(t.attr({\"data-bb\":\"\"}),r=p.bBox(t.node())),e=a(r,o)));var i=k+o.pxmid[0]*e.rCenter+(e.x||0),s=A+o.pxmid[1]*e.rCenter+(e.y||0);e.outside&&(o.yLabelMin=s-r.height/2,o.yLabelMid=s,o.yLabelMax=s+r.height/2,o.labelExtraX=0,o.labelExtraY=0,m=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+s+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+(e.rotate?\"rotate(\"+e.rotate+\")\":\"\")+\"translate(\"+-(r.left+r.right)/2+\",\"+-(r.top+r.bottom)/2+\")\")})}),m&&o(l,v),s.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=c.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],i=t.cyFinal+t.pxmid[1],a=\"M\"+n+\",\"+i,o=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var s=t.labelExtraX*t.pxmid[1]/t.pxmid[0],l=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);a+=Math.abs(s)>Math.abs(l)?\"l\"+l*t.pxmid[0]/t.pxmid[1]+\",\"+l+\"H\"+(n+t.labelExtraX+o):\"l\"+t.labelExtraX+\",\"+s+\"v\"+(l-s)+\"h\"+o}else a+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+o;e.append(\"path\").classed(\"textline\",!0).call(h.stroke,v.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,v.outsidetextfont.size/8),d:a,fill:\"none\"})}})})}),setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=c.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)}},{\"../../components/color\":529,\"../../components/drawing\":547,\"../../lib/svg_text_utils\":589,\"../../plots/cartesian/graph_interact\":603,\"./helpers\":723,d3:320}],728:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0],r=e.trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\".top path.surface\").each(function(t){n.select(this).call(i,t,r)})})}},{\"./style_one\":729,d3:320}],729:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r){var i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a,fill:e.color}).call(n.stroke,i)}},{\"../../components/color\":529}],730:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t){var e=t[0].trace,r=e.marker;if(n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.textposition,t,\"tp\"),e.textfont&&(n.mergeArray(e.textfont.size,t,\"ts\"),n.mergeArray(e.textfont.color,t,\"tc\"),n.mergeArray(e.textfont.family,t,\"tf\")),r&&r.line){var i=r.line;n.mergeArray(r.opacity,t,\"mo\"),n.mergeArray(r.symbol,t,\"mx\"),n.mergeArray(r.color,t,\"mc\"),n.mergeArray(i.color,t,\"mlc\"),n.mergeArray(i.width,t,\"mlw\")}}},{\"../../lib\":578}],731:[function(t,e,r){\"use strict\";var n=t(\"../../components/drawing\");t(\"./constants\");e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},dy:{valType:\"number\",dflt:1},text:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",\n",
+       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i=t(\"../scatter/attributes\"),a=t(\"../../constants/gl_markers\"),o=t(\"../../lib/extend\").extendFlat,s=i.line,l=i.marker,u=l.line;e.exports={x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},text:o({},i.text,{}),mode:o({},i.mode,{dflt:\"lines+markers\"}),surfaceaxis:{valType:\"enumerated\",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:\"color\"},projection:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},line:{color:s.color,width:s.width,dash:s.dash},marker:{color:l.color,symbol:{valType:\"enumerated\",values:Object.keys(a),dflt:\"circle\",arrayOk:!0},size:o({},l.size,{dflt:8}),sizeref:l.sizeref,sizemin:l.sizemin,sizemode:l.sizemode,opacity:o({},l.opacity,{arrayOk:!1}),colorscale:l.colorscale,cauto:l.cauto,cmax:l.cmax,cmin:l.cmin,autocolorscale:l.autocolorscale,reversescale:l.reversescale,showscale:l.showscale,line:{color:u.color,width:o({},u.width,{arrayOk:!1}),colorscale:u.colorscale,cauto:u.cauto,cmax:u.cmax,cmin:u.cmin,autocolorscale:u.autocolorscale,reversescale:u.reversescale}},textposition:o({},i.textposition,{dflt:\"top 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e,r,n,a,o=this.scene.glplot.gl,s=w.solid;this.data=t;var l=c(this.scene,t);\"mode\"in l&&(this.mode=l.mode),\"lineDashes\"in l&&l.lineDashes in w&&(s=w[l.lineDashes]),this.color=f(l.scatterColor)||f(l.lineColor),this.dataPoints=l.position,e={gl:o,position:l.position,color:l.lineColor,lineWidth:l.lineWidth||1,dashes:s[0],dashScale:s[1],opacity:t.opacity},-1!==this.mode.indexOf(\"lines\")?this.linePlot?this.linePlot.update(e):(this.linePlot=p(e),this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var u=t.opacity;if(t.marker&&t.marker.opacity&&(u*=t.marker.opacity),r={gl:o,position:l.position,color:l.scatterColor,size:l.scatterSize,glyph:l.scatterMarker,opacity:u,orthographic:!0,lineWidth:l.scatterLineWidth,lineColor:l.scatterLineColor,project:l.project,projectScale:l.projectScale,projectOpacity:l.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=d(r),this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:o,position:l.position,glyph:l.text,color:l.textColor,size:l.textSize,angle:l.textAngle,alignment:l.textOffset,font:l.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=l.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=d(a),this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),n={gl:o,position:l.position,color:l.errorColor,error:l.errorBounds,lineWidth:l.errorLineWidth,capSize:l.errorCapSize,opacity:t.opacity},this.errorBars?l.errorBounds?this.errorBars.update(n):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):l.errorBounds&&(this.errorBars=g(n),this.scene.glplot.add(this.errorBars)),l.delaunayAxis>=0){var h=i(l.position,l.delaunayColor,l.delaunayAxis);this.delaunayMesh?this.delaunayMesh.update(h):(h.gl=o,this.delaunayMesh=v(h),this.scene.glplot.add(this.delaunayMesh))}else 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n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,f){function h(r,n){return i.coerce(t,e,c,r,n)}var p=n(t,e,h);if(!p)return void(e.visible=!1);h(\"text\"),h(\"mode\"),a.hasLines(e)&&s(t,e,r,h),a.hasMarkers(e)&&o(t,e,r,f,h),a.hasText(e)&&l(t,e,f,h);var d=(e.line||{}).color,g=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",d||g);for(var v=[\"x\",\"y\",\"z\"],m=0;3>m;++m){var y=\"projection.\"+v[m];h(y+\".show\")&&(h(y+\".opacity\"),h(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":752}],757:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":566,\"../../plots/gl3d\":629,\"../scatter/colorbar\":734,\"./attributes\":752,\"./calc\":753,\"./convert\":755,\"./defaults\":756}],758:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../lib/extend\").extendFlat,o=n.marker,s=n.line,l=o.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\").plot,n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":614,\"../scatter/colorbar\":734,\"./attributes\":758,\"./calc\":759,\"./defaults\":760,\"./plot\":762}],762:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t,n){h(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function i(t){for(var e=t.lon.length,r=new Array(e),n=0;e>n;n++)r[n]=[t.lon[n],t.lat[n]];return{type:\"LineString\",coordinates:r,trace:t}}function a(t,e){function r(e){var r=t.mockAxis;return u.tickText(r,r.c2l(e),\"hover\").text+\"\\xb0\"}var n=e.hoverinfo;if(\"none\"===n)return function(t){delete t.textLabel};var i=\"all\"===n?v.hoverinfo.flags:n.split(\"+\"),a=-1!==i.indexOf(\"location\")&&Array.isArray(e.locations),o=-1!==i.indexOf(\"lon\"),s=-1!==i.indexOf(\"lat\"),l=-1!==i.indexOf(\"text\");return function(t){var n=[];a?n.push(t.location):o&&s?n.push(\"(\"+r(t.lon)+\", \"+r(t.lat)+\")\"):o?n.push(\"lon: \"+r(t.lon)):s&&n.push(\"lat: \"+r(t.lat)),l&&n.push(t.tx||e.text),t.textLabel=n.join(\"<br>\")}}function o(t){var e=Array.isArray(t.locations);return function(r,n){return{points:[{data:t._input,fullData:t,curveNumber:t.index,pointNumber:n,lon:r.lon,lat:r.lat,location:e?r.location:null}]}}}var s=t(\"d3\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"../../plots/cartesian/axes\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,f=t(\"../../lib/geo_location_utils\").locationToFeature,h=t(\"../../lib/array_to_calc_item\"),p=t(\"../../components/color\"),d=t(\"../../components/drawing\"),g=t(\"../scatter/subtypes\"),v=t(\"./attributes\"),m=e.exports={};m.calcGeoJSON=function(t,e){var r,i,a,o,s=[],l=Array.isArray(t.locations);l?(o=t.locations,r=o.length,i=c(t,e),a=function(t,e){var r=f(t.locationmode,o[e],i);return void 0!==r?r.properties.ct:void 0}):(r=t.lon.length,a=function(t,e){return[t.lon[e],t.lat[e]]});for(var u=0;r>u;u++){var h=a(t,u);if(h){var p={lon:h[0],lat:h[1],location:l?t.locations[u]:null};n(t,p,u),s.push(p)}}return s.length>0&&(s[0].trace=t),s},m.plot=function(t,e){var r=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,function(t){return t.uid});r.enter().append(\"g\").attr(\"class\",\"trace 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}var d=o(t,e,p);return d?(p(\"text\"),p(\"mode\",d<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&l(t,e,r,p),a.hasMarkers(e)&&s(t,e,r,h,p),p(\"fill\"),\"none\"!==e.fill&&u(t,e,r,p),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/constants\":735,\"../scatter/fillcolor_defaults\":737,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/xy_defaults\":751,\"./attributes\":763}],766:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":626,\"../scatter/colorbar\":734,\"../scatter3d/calc\":753,\"./attributes\":763,\"./convert\":764,\"./defaults\":765}],767:[function(t,e,r){\"use strict\";function n(t){return{valType:\"boolean\",dflt:!1}}function i(t){return{show:{valType:\"boolean\",dflt:!1},project:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},color:{valType:\"color\",dflt:\"#000\"},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!1},highlightColor:{valType:\"color\",dflt:\"#000\"},highlightWidth:{valType:\"number\",min:1,max:16,dflt:2}}}var a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports={z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"data_array\"},zauto:a.zauto,zmin:a.zmin,zmax:a.zmax,colorscale:a.colorscale,autocolorscale:o({},a.autocolorscale,{dflt:!1}),reversescale:a.reversescale,showscale:a.showscale,contours:{x:i(\"x\"),y:i(\"y\"),z:i(\"z\")},hidesurface:{valType:\"boolean\",dflt:!1},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},_nestedModules:{colorbar:\"Colorbar\"}}},{\"../../components/colorscale/attributes\":535,\"../../lib/extend\":574}],768:[function(t,e,r){\"use strict\";var 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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/src/Clustering.ipynb b/src/Clustering.ipynb
index a49c828..5dc0b68 100644
--- a/src/Clustering.ipynb
+++ b/src/Clustering.ipynb
@@ -18,9 +18,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 159,
+   "execution_count": 10,
    "metadata": {
-    "code_folding": [],
+    "code_folding": [
+     332
+    ],
     "collapsed": false
    },
    "outputs": [
@@ -30,7 +32,7 @@
        "\n",
        "    <div class=\"bk-banner\">\n",
        "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
-       "        <span id=\"5b2bb606-0517-45bd-8b51-96192f3c4232\">Loading BokehJS ...</span>\n",
+       "        <span id=\"1cd13974-dfa2-437d-b526-37962420ef44\">Loading BokehJS ...</span>\n",
        "    </div>"
       ]
      },
@@ -96,7 +98,7 @@
        "    },\n",
        "    \n",
        "    function(Bokeh) {\n",
-       "      Bokeh.$(\"#5b2bb606-0517-45bd-8b51-96192f3c4232\").text(\"BokehJS successfully loaded\");\n",
+       "      Bokeh.$(\"#1cd13974-dfa2-437d-b526-37962420ef44\").text(\"BokehJS successfully loaded\");\n",
        "    },\n",
        "    function(Bokeh) {\n",
        "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.11.1.min.css\");\n",
@@ -131,23 +133,94 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
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-      "  def _config_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:340: DeprecationWarning: EnableNBExtensionApp._config_file_name_default is deprecated: use @default decorator instead.\n",
-      "  def _config_file_name_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:91: DeprecationWarning: JupyterApp._data_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _data_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:73: DeprecationWarning: JupyterApp._jupyter_path_default is deprecated: use @default decorator instead.\n",
-      "  def _jupyter_path_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:69: DeprecationWarning: JupyterApp._log_level_default is deprecated: use @default decorator instead.\n",
-      "  def _log_level_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:97: DeprecationWarning: JupyterApp._runtime_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _runtime_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning: ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _config_dir_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning: ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
-      "  def _config_dir_default(self):\n"
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:78: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/nbextensions.py:340: DeprecationWarning:\n",
+      "\n",
+      "EnableNBExtensionApp._config_file_name_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:91: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._data_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:73: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._jupyter_path_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:69: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._log_level_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/jupyter_core/application.py:97: DeprecationWarning:\n",
+      "\n",
+      "JupyterApp._runtime_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning:\n",
+      "\n",
+      "ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/notebook/services/config/manager.py:16: DeprecationWarning:\n",
+      "\n",
+      "ConfigManager._config_dir_default is deprecated: use @default decorator instead.\n",
+      "\n"
      ]
+    },
+    {
+     "data": {
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+       "* Licensed under the MIT license\n",
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o=t(\"./normalize\"),s=t(\"gl-mat4/create\"),l=t(\"gl-mat4/clone\"),u=t(\"gl-mat4/determinant\"),c=t(\"gl-mat4/invert\"),f=t(\"gl-mat4/transpose\"),h={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},p=s(),d=s(),g=[0,0,0,0],v=[[0,0,0],[0,0,0],[0,0,0]],m=[0,0,0];e.exports=function(t,e,r,s,y,b){if(e||(e=[0,0,0]),r||(r=[0,0,0]),s||(s=[0,0,0]),y||(y=[0,0,0,1]),b||(b=[0,0,0,1]),!o(p,t))return!1;if(l(d,p),d[3]=0,d[7]=0,d[11]=0,d[15]=1,Math.abs(u(d)<1e-8))return!1;var x=p[3],_=p[7],w=p[11],k=p[12],A=p[13],M=p[14],T=p[15];if(0!==x||0!==_||0!==w){g[0]=x,g[1]=_,g[2]=w,g[3]=T;var E=c(d,d);if(!E)return!1;f(d,d),n(y,g,d)}else 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b[0]=.5*Math.sqrt(Math.max(1+v[0][0]-v[1][1]-v[2][2],0)),b[1]=.5*Math.sqrt(Math.max(1-v[0][0]+v[1][1]-v[2][2],0)),b[2]=.5*Math.sqrt(Math.max(1-v[0][0]-v[1][1]+v[2][2],0)),b[3]=.5*Math.sqrt(Math.max(1+v[0][0]+v[1][1]+v[2][2],0)),v[2][1]>v[1][2]&&(b[0]=-b[0]),v[0][2]>v[2][0]&&(b[1]=-b[1]),v[1][0]>v[0][1]&&(b[2]=-b[2]),!0}},{\"./normalize\":12,\"gl-mat4/clone\":180,\"gl-mat4/create\":181,\"gl-mat4/determinant\":182,\"gl-mat4/invert\":186,\"gl-mat4/transpose\":196,\"gl-vec3/cross\":5,\"gl-vec3/dot\":6,\"gl-vec3/length\":7,\"gl-vec3/normalize\":9}],12:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;16>i;i++)t[i]=e[i]*n;return!0}},{}],13:[function(t,e,r){var n={identity:t(\"gl-mat4/identity\"),translate:t(\"gl-mat4/translate\"),multiply:t(\"gl-mat4/multiply\"),create:t(\"gl-mat4/create\"),scale:t(\"gl-mat4/scale\"),fromRotationTranslation:t(\"gl-mat4/fromRotationTranslation\")},i=(n.create(),n.create());e.exports=function(t,e,r,a,o,s){return 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h=Math.max(e,a,u),f=Math.sqrt(2*h-c+1);e>=h?(t[0]=.5*f,t[1]=.5*(i+r)/f,t[2]=.5*(s+n)/f,t[3]=.5*(o-l)/f):a>=h?(t[0]=.5*(r+i)/f,t[1]=.5*f,t[2]=.5*(l+o)/f,t[3]=.5*(s-n)/f):(t[0]=.5*(n+s)/f,t[1]=.5*(o+l)/f,t[2]=.5*f,t[3]=.5*(r-i)/f)}return t}e.exports=n},{}],17:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.min(e,Math.max(t,r))}function i(t,e,r){this.dimension=t.length,this.bounds=[new Array(this.dimension),new Array(this.dimension)];for(var n=0;n<this.dimension;++n)this.bounds[0][n]=-(1/0),this.bounds[1][n]=1/0;this._state=t.slice().reverse(),this._velocity=e.slice().reverse(),this._time=[r],this._scratch=[t.slice(),t.slice(),t.slice(),t.slice(),t.slice()]}function a(t){for(var e=new Array(t),r=0;t>r;++r)e[r]=0;return e}function o(t,e,r){switch(arguments.length){case 0:return new i([0],[0],0);case 1:if(\"number\"==typeof t){var n=a(t);return new i(n,n,0)}return new i(t,a(t.length),0);case 2:if(\"number\"==typeof e){var n=a(t.length);return new i(t,n,+e)}r=0;case 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a},u.dcurve=function(t){var e=this._time,r=e.length,n=l.le(e,t),i=this._scratch[0],a=this._state,o=this._velocity,u=this.dimension;if(n>=r-1)for(var c=a.length-1,f=(t-e[r-1],0);u>f;++f,--c)i[f]=o[c];else{for(var c=u*(n+1)-1,h=e[n],p=e[n+1],d=p-h||1,g=this._scratch[1],v=this._scratch[2],m=this._scratch[3],y=this._scratch[4],b=!0,f=0;u>f;++f,--c)g[f]=a[c],m[f]=o[c]*d,v[f]=a[c+u],y[f]=o[c+u]*d,b=b&&g[f]===v[f]&&m[f]===y[f]&&0===m[f];if(b)for(var f=0;u>f;++f)i[f]=0;else{s.derivative(g,m,v,y,(t-h)/d,i);for(var f=0;u>f;++f)i[f]/=d}}return i},u.lastT=function(){var t=this._time;return t[t.length-1]},u.stable=function(){for(var t=this._velocity,e=t.length,r=this.dimension-1;r>=0;--r)if(t[--e])return!1;return!0},u.jump=function(t){var e=this.lastT(),r=this.dimension;if(!(e>t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=this.bounds,l=s[0],u=s[1];this._time.push(e,t);for(var c=0;2>c;++c)for(var f=0;r>f;++f)i.push(i[o++]),a.push(0);this._time.push(t);for(var f=r;f>0;--f)i.push(n(l[f-1],u[f-1],arguments[f])),a.push(0)}},u.push=function(t){var e=this.lastT(),r=this.dimension;if(!(e>t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=t-e,l=this.bounds,u=l[0],c=l[1],f=s>1e-6?1/s:0;this._time.push(t);for(var h=r;h>0;--h){var p=n(u[h-1],c[h-1],arguments[h]);i.push(p),a.push((p-i[o++])*f)}}},u.set=function(t){var e=this.dimension;if(!(t<this.lastT()||arguments.length!==e+1)){var r=this._state,i=this._velocity,a=this.bounds,o=a[0],s=a[1];this._time.push(t);for(var l=e;l>0;--l)r.push(n(o[l-1],s[l-1],arguments[l])),i.push(0)}},u.move=function(t){var e=this.lastT(),r=this.dimension;if(!(e>=t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=this.bounds,l=s[0],u=s[1],c=t-e,f=c>1e-6?1/c:0;this._time.push(t);for(var h=r;h>0;--h){var 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l=t(\"filtered-vector\"),u=t(\"gl-mat4/lookAt\"),c=t(\"gl-mat4/fromQuat\"),f=t(\"gl-mat4/invert\"),h=t(\"./lib/quatFromFrame\"),p=o.prototype;p.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},p.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;a(e,e);var r=this.computedMatrix;c(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;3>l;++l){for(var u=0,f=0;3>f;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r},p.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},p.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},p.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=a[1],s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=a[2],v=a[6],m=a[10],y=g*o+v*s+m*l,b=g*c+v*f+m*h;g-=y*o+b*c,v-=y*s+b*f,m-=y*l+b*h;var x=n(g,v,m);g/=x,v/=x,m/=x;var _=c*e+o*r,w=f*e+s*r,k=h*e+l*r;this.center.move(t,_,w,k);var A=Math.exp(this.computedRadius[0]);A=Math.max(1e-4,A+i),this.radius.set(t,Math.log(A))},p.rotate=function(t,e,r,a){this.recalcMatrix(t),e=e||0,r=r||0;var o=this.computedMatrix,s=o[0],l=o[4],u=o[8],c=o[1],f=o[5],h=o[9],p=o[2],d=o[6],g=o[10],v=e*s+r*c,m=e*l+r*f,y=e*u+r*h,b=-(d*y-g*m),x=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(b,2)-Math.pow(x,2)-Math.pow(_,2))),k=i(b,x,_,w);k>1e-6?(b/=k,x/=k,_/=k,w/=k):(b=x=_=0,w=1);var A=this.computedRotation,M=A[0],T=A[1],E=A[2],L=A[3],S=M*w+L*b+T*_-E*x,C=T*w+L*x+E*b-M*_,P=E*w+L*_+M*x-T*b,z=L*w-M*b-T*x-E*_;if(a){b=p,x=d,_=g;var R=Math.sin(a)/n(b,x,_);b*=R,x*=R,_*=R,w=Math.cos(e),S=S*w+z*b+C*_-P*x,C=C*w+z*x+P*b-S*_,P=P*w+z*_+S*x-C*b,z=z*w-S*b-C*x-P*_}var O=i(S,C,P,z);O>1e-6?(S/=O,C/=O,P/=O,z/=O):(S=C=P=0,z=1),this.rotation.set(t,S,C,P,z)},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;u(i,e,r,n);var o=this.computedRotation;h(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),a(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var s=0,l=0;3>l;++l)s+=Math.pow(r[l]-e[l],2);this.radius.set(t,.5*Math.log(Math.max(s,1e-6))),this.center.set(t,r[0],r[1],r[2])},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e){var r=this.computedRotation;h(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),a(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;f(n,e);var i=n[15];if(Math.abs(i)>1e-6){var o=n[12]/i,s=n[13]/i,l=n[14]/i;this.recalcMatrix(t);var u=Math.exp(this.computedRadius[0]);this.center.set(t,o-n[2]*u,s-n[6]*u,l-n[10]*u),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},p.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var i=t.distance;i&&i>0&&this.radius.set(e,Math.log(i)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":16,\"filtered-vector\":17,\"gl-mat4/fromQuat\":183,\"gl-mat4/invert\":186,\"gl-mat4/lookAt\":187}],21:[function(t,e,r){arguments[4][17][0].apply(r,arguments)},{\"binary-search-bounds\":22,\"cubic-hermite\":23,dup:17}],22:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],23:[function(t,e,r){arguments[4][19][0].apply(r,arguments)},{dup:19}],24:[function(t,e,r){arguments[4][5][0].apply(r,arguments)},{dup:5}],25:[function(t,e,r){arguments[4][6][0].apply(r,arguments)},{dup:6}],26:[function(t,e,r){arguments[4][9][0].apply(r,arguments)},{dup:9}],27:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t){return Math.min(1,Math.max(-1,t))}function a(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),i=[0,0,0];e>Math.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,s=0;3>s;++s)a+=t[s]*t[s],o+=i[s]*t[s];for(var s=0;3>s;++s)i[s]-=o/a*t[s];return h(i,i),i}function o(t,e,r,n,i,a,o,s){this.center=l(r),this.up=l(n),this.right=l(i),this.radius=l([a]),this.angle=l([o,s]),this.angle.bounds=[[-(1/0),-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;16>u;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.up||[0,1,0],i=t.right||a(r),s=t.radius||1,l=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),h(r,r),i=[].slice.call(i,0,3),h(i,i),\"eye\"in t){var c=t.eye,d=[c[0]-e[0],c[1]-e[1],c[2]-e[2]];f(i,d,r),n(i[0],i[1],i[2])<1e-6?i=a(r):h(i,i),s=n(d[0],d[1],d[2]);var g=p(r,d)/s,v=p(i,d)/s;u=Math.acos(g),l=Math.acos(v)}return s=Math.log(s),new o(t.zoomMin,t.zoomMax,e,r,i,s,l,u)}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/invert\"),c=t(\"gl-mat4/rotate\"),f=t(\"gl-vec3/cross\"),h=t(\"gl-vec3/normalize\"),p=t(\"gl-vec3/dot\"),d=o.prototype;d.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},d.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},d.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,i=0,a=0,o=0;3>o;++o)a+=e[o]*r[o],i+=e[o]*e[o];for(var s=Math.sqrt(i),l=0,o=0;3>o;++o)r[o]-=e[o]*a/i,l+=r[o]*r[o],e[o]/=s;for(var u=Math.sqrt(l),o=0;3>o;++o)r[o]/=u;var c=this.computedToward;f(c,e,r),h(c,c);for(var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),b=Math.sin(g),x=this.computedCenter,_=v*y,w=m*y,k=b,A=-v*b,M=-m*b,T=y,E=this.computedEye,L=this.computedMatrix,o=0;3>o;++o){var S=_*r[o]+w*c[o]+k*e[o];L[4*o+1]=A*r[o]+M*c[o]+T*e[o],L[4*o+2]=S,L[4*o+3]=0}var C=L[1],P=L[5],z=L[9],R=L[2],O=L[6],I=L[10],j=P*I-z*O,N=z*R-C*I,F=C*O-P*R,D=n(j,N,F);j/=D,N/=D,F/=D,L[0]=j,L[4]=N,L[8]=F;for(var o=0;3>o;++o)E[o]=x[o]+L[2+4*o]*p;for(var o=0;3>o;++o){for(var l=0,B=0;3>B;++B)l+=L[o+4*B]*E[B];L[12+o]=-l}L[15]=1},d.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r};var g=[0,0,0];d.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;g[0]=i[2],g[1]=i[6],g[2]=i[10];for(var a=this.computedUp,o=this.computedRight,s=this.computedToward,l=0;3>l;++l)i[4*l]=a[l],i[4*l+1]=o[l],i[4*l+2]=s[l];c(i,i,n,g);for(var l=0;3>l;++l)a[l]=i[4*l],o[l]=i[4*l+1];this.up.set(t,a[0],a[1],a[2]),this.right.set(t,o[0],o[1],o[2])}},d.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=(Math.exp(this.computedRadius[0]),a[1]),s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=c*e+o*r,v=f*e+s*r,m=h*e+l*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+i),this.radius.set(t,Math.log(y))},d.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},d.setMatrix=function(t,e,r,a){var o=1;\"number\"==typeof r&&(o=0|r),(0>o||o>3)&&(o=1);var s=(o+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var l=e[o],c=e[o+4],f=e[o+8];if(a){var h=Math.abs(l),p=Math.abs(c),d=Math.abs(f),g=Math.max(h,p,d);h===g?(l=0>l?-1:1,c=f=0):d===g?(f=0>f?-1:1,l=c=0):(c=0>c?-1:1,l=f=0)}else{var v=n(l,c,f);l/=v,c/=v,f/=v}var m=e[s],y=e[s+4],b=e[s+8],x=m*l+y*c+b*f;m-=l*x,y-=c*x,b-=f*x;var _=n(m,y,b);m/=_,y/=_,b/=_;var w=c*b-f*y,k=f*m-l*b,A=l*y-c*m,M=n(w,k,A);w/=M,k/=M,A/=M,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,l,c,f),this.right.jump(t,m,y,b);var T,E;if(2===o){var L=e[1],S=e[5],C=e[9],P=L*m+S*y+C*b,z=L*w+S*k+C*A;T=0>j?-Math.PI/2:Math.PI/2,E=Math.atan2(z,P)}else{var R=e[2],O=e[6],I=e[10],j=R*l+O*c+I*f,N=R*m+O*y+I*b,F=R*w+O*k+I*A;T=Math.asin(i(j)),E=Math.atan2(F,N)}this.angle.jump(t,E,T),this.recalcMatrix(t);var D=e[2],B=e[6],U=e[10],V=this.computedMatrix;u(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,Y=V[14]/q,X=Math.exp(this.computedRadius[0]);this.center.jump(t,H-D*X,G-B*X,Y-U*X)},d.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},d.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},d.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},d.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},d.lookAt=function(t,e,r,a){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter,a=a||this.computedUp;var o=a[0],s=a[1],l=a[2],u=n(o,s,l);if(!(1e-6>u)){o/=u,s/=u,l/=u;var c=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=n(c,f,h);if(!(1e-6>p)){c/=p,f/=p,h/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=o*g+s*v+l*m;g-=y*o,v-=y*s,m-=y*l;var b=n(g,v,m);if(!(.01>b&&(g=s*h-l*f,v=l*c-o*h,m=o*f-s*c,b=n(g,v,m),1e-6>b))){g/=b,v/=b,m/=b,this.up.set(t,o,s,l),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var x=s*m-l*v,_=l*g-o*m,w=o*v-s*g,k=n(x,_,w);x/=k,_/=k,w/=k;var A=o*c+s*f+l*h,M=g*c+v*f+m*h,T=x*c+_*f+w*h,E=Math.asin(i(A)),L=Math.atan2(T,M),S=this.angle._state,C=S[S.length-1],P=S[S.length-2];C%=2*Math.PI;var z=Math.abs(C+2*Math.PI-L),R=Math.abs(C-L),O=Math.abs(C-2*Math.PI-L);R>z&&(C+=2*Math.PI),R>O&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,L,E)}}}}},{\"filtered-vector\":21,\"gl-mat4/invert\":186,\"gl-mat4/rotate\":190,\"gl-vec3/cross\":24,\"gl-vec3/dot\":25,\"gl-vec3/normalize\":26}],28:[function(t,e,r){\"use strict\";function n(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return t[e]}),this._mode=e,this._active=t[e],this._active||(this._mode=\"turntable\",this._active=t.turntable),this.modes=this._controllerNames,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}function i(t){t=t||{};var e=t.eye||[0,0,1],r=t.center||[0,0,0],i=t.up||[0,1,0],l=t.distanceLimits||[0,1/0],u=t.mode||\"turntable\",c=a(),f=o(),h=s();return c.setDistanceLimits(l[0],l[1]),c.lookAt(0,e,r,i),f.setDistanceLimits(l[0],l[1]),f.lookAt(0,e,r,i),h.setDistanceLimits(l[0],l[1]),h.lookAt(0,e,r,i),new n({turntable:c,orbit:f,matrix:h},u)}e.exports=i;var a=t(\"turntable-camera-controller\"),o=t(\"orbit-camera-controller\"),s=t(\"matrix-camera-controller\"),l=n.prototype,u=[[\"flush\",1],[\"idle\",1],[\"lookAt\",4],[\"rotate\",4],[\"pan\",4],[\"translate\",4],[\"setMatrix\",2],[\"setDistanceLimits\",2],[\"setDistance\",2]];u.forEach(function(t){for(var e=t[0],r=[],n=0;n<t[1];++n)r.push(\"a\"+n);var i=\"var cc=this._controllerList;for(var i=0;i<cc.length;++i){cc[i].\"+t[0]+\"(\"+r.join()+\")}\";l[e]=Function.apply(null,r.concat(i))}),l.recalcMatrix=function(t){this._active.recalcMatrix(t)},l.getDistance=function(t){return this._active.getDistance(t)},l.getDistanceLimits=function(t){return this._active.getDistanceLimits(t)},l.lastT=function(){return this._active.lastT()},l.setMode=function(t){if(t!==this._mode){var e=this._controllerNames.indexOf(t);if(!(0>e)){var r=this._active,n=this._controllerList[e],i=Math.max(r.lastT(),n.lastT());r.recalcMatrix(i),n.setMatrix(i,r.computedMatrix),this._active=n,this._mode=t,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}}},l.getMode=function(){return this._mode}},{\"matrix-camera-controller\":3,\"orbit-camera-controller\":20,\"turntable-camera-controller\":27}],29:[function(t,e,r){e.exports=function(t,e){e||(e=[0,\"\"]),t=String(t);var r=parseFloat(t,10);\n",
+       "return e[0]=r,e[1]=t.match(/[\\d.\\-\\+]*\\s*(.*)/)[1]||\"\",e}},{}],30:[function(t,e,r){\"use strict\";function n(t,e){var r=o(getComputedStyle(t).getPropertyValue(e));return r[0]*a(r[1],t)}function i(t,e){var r=document.createElement(\"div\");r.style[\"font-size\"]=\"128\"+t,e.appendChild(r);var i=n(r,\"font-size\")/128;return e.removeChild(r),i}function a(t,e){switch(e=e||document.body,t=(t||\"px\").trim().toLowerCase(),(e===window||e===document)&&(e=document.body),t){case\"%\":return e.clientHeight/100;case\"ch\":case\"ex\":return i(t,e);case\"em\":return n(e,\"font-size\");case\"rem\":return n(document.body,\"font-size\");case\"vw\":return window.innerWidth/100;case\"vh\":return window.innerHeight/100;case\"vmin\":return Math.min(window.innerWidth,window.innerHeight)/100;case\"vmax\":return Math.max(window.innerWidth,window.innerHeight)/100;case\"in\":return s;case\"cm\":return s/2.54;case\"mm\":return s/25.4;case\"pt\":return s/72;case\"pc\":return s/6}return 1}var 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i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);o>=s;s++){var l=n-s,u=this.words[l],c=t.words[s],f=u*c,h=67108863&f;i+=f/67108864|0,h+=a,a=67108863&h,i+=h>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var p=this.words[l]+i;this.words[l]=67108863&p,i=p>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var 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a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),0>t?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],\n",
+       "this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),0>t)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(-1===s),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var f=n.clone()._ishlnsubmul(a,1,u);f.sign||(n=f,l&&(l.words[u]=1));for(var h=u-1;h>=0;h--){var p=67108864*n.words[a.length+h]+n.words[a.length+h-1];for(p=Math.min(p/o|0,67108863),n._ishlnsubmul(a,p,h);n.sign;)p--,n.sign=!1,n._ishlnsubmul(a,1,h),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[h]=p)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return 0>a||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(67108863>=t);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(67108863>=t);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),f=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(f).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(f).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(0>i){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;n+1>a;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=0>t;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:t>n?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){i>n?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new h(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;n>i;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(f,s),f.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function y(t){if(m[t])return m[t];var y;if(\"k256\"===t)y=new l;else if(\"p224\"===t)y=new u;else if(\"p192\"===t)y=new c;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);y=new f}return m[t]=y,y},h.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},h.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},h.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},h.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},h.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},h.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},h.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},h.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},h.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},h.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},h.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},h.prototype.isqr=function(t){return this.imul(t,t)},h.prototype.sqr=function(t){return this.mul(t,t)},h.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),f=this.m.bitLength();for(f=new i(2*f*f).toRed(this);0!==this.pow(f,c).cmp(u);)f.redIAdd(u);for(var h=this.pow(f,o),a=this.pow(t,o.addn(1).ishrn(1)),p=this.pow(t,o),d=s;0!==p.cmp(l);){for(var g=p,v=0;0!==g.cmp(l);v++)g=g.redSqr();r(d>v);var m=this.pow(h,new i(1).ishln(d-v-1));a=a.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return a},h.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},h.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},h.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},h.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new p(t)},n(p,h),p.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},p.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},p.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},p.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).ishrn(this.shift),o=a;return a.cmp(this.m)>=0?o=a.isub(this.m):a.cmpn(0)<0&&(o=a.iadd(this.m)),o._forceRed(this)},p.prototype.invm=function(t){var e=this.imod(t._invmp(this.m).mul(this.r2));return e._forceRed(this)}}(\"undefined\"==typeof e||e,this)},{}],110:[function(t,e,r){(function(t){function r(t,e){return p[0]=t,p[1]=e,h[0]}function n(t){return h[0]=t,p[0]}function i(t){return h[0]=t,p[1]}function a(t,e){return p[1]=t,p[0]=e,h[0]}function o(t){return h[0]=t,p[1]}function s(t){return h[0]=t,p[0]}function l(t,e){return 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m=r.getExtension(\"WEBGL_depth_texture\");m?p?t.depth=s(r,u,c,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):d&&p?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):p&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var b=r.checkFramebufferStatus(r.FRAMEBUFFER);if(b!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(var v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(b)}i(r,e)}function c(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var l=0;i>l;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,f=[0|e,0|r];Object.defineProperties(f,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=f,u(this)}function f(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(0>e||e>s||0>r||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function h(t,e,r,n){d||(d=t.FRAMEBUFFER_UNSUPPORTED,g=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,v=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,m=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(0>e||e>o||0>r||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");n=n||{};var s=1;if(\"color\"in n){if(s=Math.max(0|n.color,0),0>s)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var f=!0;\"depth\"in n&&(f=!!n.depth);var h=!1;return\"stencil\"in n&&(h=!!n.stencil),new c(t,e,r,l,s,f,h,i)}var p=t(\"gl-texture2d\");e.exports=h;var d,g,v,m,y=null,b=c.prototype;Object.defineProperties(b,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return f(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t=0|t,f(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t=0|t,f(this,this._shape[0],t),t},enumerable:!1}}),b.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},b.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":179}],171:[function(t,e,r){arguments[4][34][0].apply(r,arguments)},{\"cwise-compiler\":172,dup:34}],172:[function(t,e,r){arguments[4][35][0].apply(r,arguments)},{\"./lib/thunk.js\":174,dup:35}],173:[function(t,e,r){arguments[4][36][0].apply(r,arguments)},{dup:36,uniq:175}],174:[function(t,e,r){arguments[4][37][0].apply(r,arguments)},{\"./compile.js\":173,dup:37}],175:[function(t,e,r){arguments[4][38][0].apply(r,arguments)},{dup:38}],176:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],177:[function(t,e,r){arguments[4][40][0].apply(r,arguments)},{dup:40}],178:[function(t,e,r){arguments[4][41][0].apply(r,arguments)},{\"bit-twiddle\":176,buffer:300,dup:41}],179:[function(t,e,r){\"use strict\";function 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l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}function o(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function s(t,e,r,n,i,a,s,l){var u=l.dtype,c=l.shape.slice();if(c.length<2||c.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var f=0,h=0,v=o(c,l.stride.slice());\"float32\"===u?f=t.FLOAT:\"float64\"===u?(f=t.FLOAT,v=!1,u=\"float32\"):\"uint8\"===u?f=t.UNSIGNED_BYTE:(f=t.UNSIGNED_BYTE,v=!1,u=\"uint8\");var m=1;if(2===c.length)h=t.LUMINANCE,c=[c[0],c[1],1],l=p(l.data,c,[l.stride[0],l.stride[1],1],l.offset);else{if(3!==c.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===c[2])h=t.ALPHA;else if(2===c[2])h=t.LUMINANCE_ALPHA;else if(3===c[2])h=t.RGB;else{if(4!==c[2])throw new Error(\"gl-texture2d: Invalid shape for pixel 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s=o(n,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,s=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,s=!1,r=\"uint8\");var c=0;if(2===n.length)c=t.LUMINANCE,n=[n[0],n[1],1],e=p(e.data,n,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==n.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===n[2])c=t.ALPHA;else if(2===n[2])c=t.LUMINANCE_ALPHA;else if(3===n[2])c=t.RGB;else{if(4!==n[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");c=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,s=!1);var f,h,v=e.size;if(s)f=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var m=[n[2],n[2]*n[0],1];h=g.malloc(v,r);var y=p(h,n,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?d.assign(y,e):b(y,e),f=h.subarray(0,v)}var x=l(t);return t.texImage2D(t.TEXTURE_2D,0,c,n[0],n[1],0,c,u,f),s||g.free(h),new a(t,x,n[0],n[1],c,u)}function 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this._wrapS},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;2>e;++e)if(y.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return i(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return t=0|t,i(this,t,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t=0|t,i(this,this._shape[0],t),t}}}),x.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},x.dispose=function(){this.gl.deleteTexture(this.handle)},x.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},x.setPixels=function(t,e,r,n){var i=this.gl;if(this.bind(),Array.isArray(e)?(n=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),n=n||0,t instanceof 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t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(c+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],185:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],186:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,k=i*u-a*l,A=c*g-f*d,M=c*v-h*d,T=c*m-p*d,E=f*v-h*g,L=f*m-p*g,S=h*m-p*v,C=y*S-b*L+x*E+_*T-w*M+k*A;return 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i=t(\"./identity\");e.exports=n},{\"./identity\":185}],188:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*f+w*g,t[1]=b*i+x*l+_*h+w*v,t[2]=b*a+x*u+_*p+w*m,t[3]=b*o+x*c+_*d+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*f+w*g,t[5]=b*i+x*l+_*h+w*v,t[6]=b*a+x*u+_*p+w*m,t[7]=b*o+x*c+_*d+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*f+w*g,t[9]=b*i+x*l+_*h+w*v,t[10]=b*a+x*u+_*p+w*m,t[11]=b*o+x*c+_*d+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*f+w*g,t[13]=b*i+x*l+_*h+w*v,t[14]=b*a+x*u+_*p+w*m,t[15]=b*o+x*c+_*d+w*y,t}e.exports=n},{}],189:[function(t,e,r){function n(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}e.exports=n},{}],190:[function(t,e,r){function n(t,e,r,n){var 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n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;3>r;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=h[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],f=n.prototype;f.isOpaque=function(){return this.opacity>=1},f.isTransparent=function(){return this.opacity<1},f.drawTransparent=f.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var f=0;3>f;++f)e.lineWidth(this.lineWidth[f]),r.capSize=this.capSize[f]*u,e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var h=function(){for(var t=new Array(3),e=0;3>e;++e){for(var r=[],n=1;2>=n;++n)for(var i=-1;1>=i;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();f.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;3>u;++u){this.lineOffset[u]=l;t:for(var c=0;s>c;++c){for(var f=r[c],h=0;3>h;++h)if(isNaN(f[h])||!isFinite(f[h]))continue t;var p=n[c],d=e[u];if(Array.isArray(d[0])&&(d=e[c]),3===d.length&&(d=[d[0],d[1],d[2],1]),!isNaN(p[0][u])&&!isNaN(p[1][u])){if(p[0][u]<0){var g=f.slice();g[u]+=p[0][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}if(p[1][u]>0){var g=f.slice();g[u]+=p[1][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},f.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":329,\"gl-buffer\":325,\"gl-vao\":420}],329:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":385}],330:[function(t,e,r){arguments[4][170][0].apply(r,arguments)},{dup:170,\"gl-texture2d\":416}],331:[function(t,e,r){r.lineVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  vec2 dir = (matrix * vec3(d, 0)).xy;\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = 0.5 * width *\\n    normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n}\\n\",r.lineFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\\n\",r.mitreVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 p;\\n\\nuniform mat3  matrix;\\nuniform vec2 screenShape;\\nuniform float radius;\\n\\nvoid main() {\\n  vec3 pp = matrix * vec3(p, 1);\\n  gl_Position  = vec4(pp.xy, 0, pp.z);\\n  gl_PointSize = radius;\\n}\\n\",r.mitreFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\nattribute vec4 pick0, pick1;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = width *\\n    normalize(screenShape.yx * vec2(d.y, -d.x)) / screenShape.xy;\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\\n\",r.fillVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 projectAxis;\\nuniform float projectValue;\\nuniform float depth;\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 p = base.xy / base.z;\\n  if(d.y < 0.0 || (d.y == 0.0 && d.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\\n\",r.fillFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"},{}],332:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.dashPattern=e,this.lineBuffer=r,this.pickBuffer=n,this.lineShader=i,this.mitreShader=a,this.fillShader=o,this.pickShader=s,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0,this.lodBuffer=[]}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=l(r,[1,1]),c=o(r,f.lineVertex,f.lineFragment),h=o(r,f.mitreVertex,f.mitreFragment),p=o(r,f.fillVertex,f.fillFragment),d=o(r,f.pickVertex,f.pickFragment),g=new n(t,u,i,a,c,h,p,d);return t.addObject(g),g.update(e),g}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),f=t(\"./lib/shaders\"),h=n.prototype;h.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[1,0],n=[-1,0],i=[0,1],a=[0,-1];return function(){var o=this.plot,s=this.color,l=this.width,u=(this.numPoints,this.bounds),c=this.vertCount,f=o.gl,h=o.viewBox,p=o.dataBox,d=o.pixelRatio,g=u[2]-u[0],v=u[3]-u[1],m=p[2]-p[0],y=p[3]-p[1],b=h[2]-h[0],x=h[3]-h[1];t[0]=2*g/m,t[4]=2*v/y,t[6]=2*(u[0]-p[0])/m-1,t[7]=2*(u[1]-p[1])/y-1,e[0]=b,e[1]=x;var _=this.lineBuffer;_.bind();var w=this.fill;if(w[0]||w[1]||w[2]||w[3]){var k=this.fillShader;k.bind();var A=k.uniforms;A.matrix=t,A.depth=o.nextDepthValue();var M=k.attributes;M.a.pointer(f.FLOAT,!1,16,0),M.d.pointer(f.FLOAT,!1,16,8),f.depthMask(!0),f.enable(f.DEPTH_TEST);var T=this.fillColor;w[0]&&(A.color=T[0],A.projectAxis=n,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[1]&&(A.color=T[1],A.projectAxis=a,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[2]&&(A.color=T[2],A.projectAxis=r,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[3]&&(A.color=T[3],A.projectAxis=i,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),f.depthMask(!1),f.disable(f.DEPTH_TEST)}var E=this.lineShader;E.bind();var L=E.uniforms;L.matrix=t,L.color=s,L.width=l*d,L.screenShape=e,L.dashPattern=this.dashPattern.bind(),L.dashLength=this.dashLength*d;var S=E.attributes;if(S.a.pointer(f.FLOAT,!1,16,0),S.d.pointer(f.FLOAT,!1,16,8),f.drawArrays(f.TRIANGLES,0,c),l>2&&!this.usingDashes){var C=this.mitreShader;C.bind();var P=C.uniforms;P.matrix=t,P.color=s,P.screenShape=e,P.radius=l*d,C.attributes.p.pointer(f.FLOAT,!1,48,0),f.drawArrays(f.POINTS,0,c/3|0)}}}(),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[0,0,0,0];return function(n){var i=this.plot,a=this.pickShader,o=this.lineBuffer,s=this.pickBuffer,l=this.width,u=this.numPoints,c=this.bounds,f=this.vertCount,h=i.gl,p=i.viewBox,d=i.dataBox,g=i.pickPixelRatio,v=c[2]-c[0],m=c[3]-c[1],y=d[2]-d[0],b=d[3]-d[1],x=p[2]-p[0],_=p[3]-p[1];\n",
+       "this.pickOffset=n,t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(c[0]-d[0])/y-1,t[7]=2*(c[1]-d[1])/b-1,e[0]=x,e[1]=_,r[0]=255&n,r[1]=n>>>8&255,r[2]=n>>>16&255,r[3]=n>>>24,a.bind();var w=a.uniforms;w.matrix=t,w.width=l*g,w.pickOffset=r,w.screenShape=e;var k=a.attributes;return o.bind(),k.a.pointer(h.FLOAT,!1,16,0),k.d.pointer(h.FLOAT,!1,16,8),s.bind(),k.pick0.pointer(h.UNSIGNED_BYTE,!1,8,0),k.pick1.pointer(h.UNSIGNED_BYTE,!1,8,4),h.drawArrays(h.TRIANGLES,0,f),n+u}}(),h.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},h.update=function(t){t=t||{};var e=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);for(var r=t.dashes||[1],n=0,a=0;a<r.length;++a)n+=r[a];for(var o=c.mallocUint8(n),s=0,f=255,a=0;a<r.length;++a){for(var h=0;h<r[a];++h)o[s++]=f;f^=255}this.dashPattern.dispose(),this.usingDashes=r.length>1,this.dashPattern=l(e,u(o,[n,1,4],[1,0,0])),this.dashPattern.minFilter=e.NEAREST,this.dashPattern.magFilter=e.NEAREST,this.dashLength=n,c.free(o);var p=t.positions;this.data=p;var d=this.bounds;d[0]=d[1]=1/0,d[2]=d[3]=-(1/0);var g=this.numPoints=p.length>>>1;if(0!==g){for(var a=0;g>a;++a){var v=p[2*a],m=p[2*a+1];d[0]=Math.min(d[0],v),d[1]=Math.min(d[1],m),d[2]=Math.max(d[2],v),d[3]=Math.max(d[3],m)}d[0]===d[2]&&(d[2]+=1),d[3]===d[1]&&(d[3]+=1);var y=c.mallocFloat32(24*(g-1)),b=c.mallocUint32(12*(g-1)),x=y.length,_=b.length,s=g;for(this.vertCount=6*(g-1);s>1;){var w=--s,v=p[2*s],m=p[2*s+1];v=(v-d[0])/(d[2]-d[0]),m=(m-d[1])/(d[3]-d[1]);var k=w-1,A=p[2*k],M=p[2*k+1];A=(A-d[0])/(d[2]-d[0]),M=(M-d[1])/(d[3]-d[1]);var T=A-v,E=M-m,L=w|1<<24,S=w-1,C=w,P=w-1|1<<24;y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S}this.lineBuffer.update(y),this.pickBuffer.update(b),c.free(y),c.free(b)}},h.dispose=function(){this.plot.removeObject(this),this.lineBuffer.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":331,\"gl-buffer\":325,\"gl-shader\":385,\"gl-texture2d\":416,ndarray:438,\"typedarray-pool\":463}],333:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":385}],334:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;3>n;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;3>r;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=v(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=p(new Array(1024),[256,1,4]),f=0;1024>f;++f)s.data[f]=255;var h=c(e,s);h.wrap=e.REPEAT;var d=new o(e,r,n,i,a,h);return d.update(t),d}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),f=t(\"glsl-read-float\"),h=t(\"binary-search-bounds\"),p=t(\"ndarray\"),d=t(\"./lib/shaders\"),g=d.createShader,v=d.createPickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){this.dirty=!0,\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var e=t.position||t.positions;if(e){var r=t.color||t.colors||[0,0,0,1],i=t.lineWidth||1,a=[],o=[],s=[],l=0,u=0,c=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];t:for(var f=1;f<e.length;++f){var d=e[f-1],g=e[f];o.push(l),s.push(d.slice());for(var v=0;3>v;++v){if(isNaN(d[v])||isNaN(g[v])||!isFinite(d[v])||!isFinite(g[v]))continue t;c[0][v]=Math.min(c[0][v],d[v],g[v]),c[1][v]=Math.max(c[1][v],d[v],g[v])}var m,y;Array.isArray(r[0])?(m=r[f-1],y=r[f]):m=y=r,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]);var b,x;Array.isArray(i)?(b=i[f-1],x=lineWidht[f]):b=x=i;var _=l;l+=n(d,g),a.push(d[0],d[1],d[2],g[0],g[1],g[2],_,b,m[0],m[1],m[2],m[3],d[0],d[1],d[2],g[0],g[1],g[2],_,-b,m[0],m[1],m[2],m[3],g[0],g[1],g[2],d[0],d[1],d[2],l,-b,y[0],y[1],y[2],y[3],g[0],g[1],g[2],d[0],d[1],d[2],l,b,y[0],y[1],y[2],y[3]),u+=4}if(this.buffer.update(a),o.push(l),s.push(e[e.length-1].slice()),this.bounds=c,this.vertexCount=u,this.points=s,this.arcLength=o,\"dashes\"in t){var w=t.dashes,k=w.slice();k.unshift(0);for(var f=1;f<k.length;++f)k[f]=k[f-1]+k[f];for(var A=p(new Array(1024),[256,1,4]),f=0;256>f;++f){for(var v=0;4>v;++v)A.set(f,0,v,0);1&h.le(k,k[k.length-1]*f/255)?A.set(f,0,0,0):A.set(f,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=f(t.value[0],t.value[1],t.value[2],0),r=h.le(this.arcLength,e);if(0>r)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;3>u;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(.5>o?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":333,\"binary-search-bounds\":335,\"gl-buffer\":325,\"gl-texture2d\":416,\"gl-vao\":420,\"glsl-read-float\":336,ndarray:438}],335:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],336:[function(t,e,r){function n(t,e,r,n){return i[0]=n,i[1]=r,i[2]=e,i[3]=t,a[0]}e.exports=n;var i=new Uint8Array(4),a=new Float32Array(i.buffer)},{}],337:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=c*o-s*u,h=-c*a+s*l,p=u*a-o*l,d=r*f+n*h+i*p;return d?(d=1/d,t[0]=f*d,t[1]=(-c*n+i*u)*d,t[2]=(s*n-i*o)*d,t[3]=h*d,t[4]=(c*r-i*l)*d,t[5]=(-s*r+i*a)*d,t[6]=p*d,t[7]=(-u*r+n*l)*d,t[8]=(o*r-n*a)*d,t):null}e.exports=n},{}],338:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{dup:180}],339:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],340:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{dup:182}],341:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{dup:183}],342:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],343:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],344:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{dup:186}],345:[function(t,e,r){arguments[4][187][0].apply(r,arguments)},{\"./identity\":343,dup:187}],346:[function(t,e,r){arguments[4][188][0].apply(r,arguments)},{dup:188}],347:[function(t,e,r){arguments[4][190][0].apply(r,arguments)},{dup:190}],348:[function(t,e,r){arguments[4][191][0].apply(r,arguments)},{dup:191}],349:[function(t,e,r){arguments[4][192][0].apply(r,arguments)},{dup:192}],350:[function(t,e,r){arguments[4][193][0].apply(r,arguments)},{dup:193}],351:[function(t,e,r){arguments[4][194][0].apply(r,arguments)},{dup:194}],352:[function(t,e,r){arguments[4][195][0].apply(r,arguments)},{dup:195}],353:[function(t,e,r){arguments[4][196][0].apply(r,arguments)},{dup:196}],354:[function(t,e,r){\"use strict\";function n(t,e){for(var r=[0,0,0,0],n=0;4>n;++n)for(var i=0;4>i;++i)r[i]+=t[4*n+i]*e[n];return r}function i(t,e,r,i,a){for(var o=n(i,n(r,n(e,[t[0],t[1],t[2],1]))),s=0;3>s;++s)o[s]/=o[3];return[.5*a[0]*(1+o[0]),.5*a[1]*(1-o[1])]}function a(t,e){if(2===t.length){for(var r=0,n=0,i=0;2>i;++i)r+=Math.pow(e[i]-t[0][i],2),n+=Math.pow(e[i]-t[1][i],2);return r=Math.sqrt(r),n=Math.sqrt(n),1e-6>r+n?[1,0]:[n/(r+n),r/(n+r)]}if(3===t.length){var a=[0,0];return u(t[0],t[1],t[2],e,a),l(t,a)}return[]}function o(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;3>o;++o)r[o]+=a*i[o];return r}function s(t,e,r,n,s,l){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),c=0;c<t.length;++c)u[c]=i(t[c],r,n,s,l);for(var f=0,h=1/0,c=0;c<u.length;++c){for(var p=0,d=0;2>d;++d)p+=Math.pow(u[c][d]-e[d],2);h>p&&(h=p,f=c)}for(var g=a(u,e),v=0,c=0;3>c;++c){if(g[c]<-.001||g[c]>1.0001)return null;v+=g[c]}return Math.abs(v-1)>.001?null:[f,o(t,g),g]}var l=t(\"barycentric\"),u=t(\"polytope-closest-point/lib/closest_point_2d.js\");e.exports=s},{barycentric:357,\"polytope-closest-point/lib/closest_point_2d.js\":359}],355:[function(t,e,r){var n=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution_2_0(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n  \\n  if(!gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = cookTorranceSpecular_1_1(L, V, N, roughness, fresnel);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5,0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\",c=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(f_position, clipBounds[0])) || \\n     any(greaterThan(f_position, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\",f=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\",h=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\",p=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\";r.meshShader={vertex:n,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:a,fragment:o,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:s,fragment:l,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:f,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:h,fragment:p,attributes:[{name:\"position\",type:\"vec3\"}]}},{}],356:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,g,v,m,y,b,x,_,w,k,A,M,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=v,this.edgeUVs=m,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=b,this.pointColors=_,this.pointUVs=w,this.pointSizes=k,this.pointIds=x,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this._model=R,this._view=R,this._projection=R,this._resolution=[1,1]}function i(t){for(var e=w({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;256>n;++n){for(var i=e[n],a=0;3>a;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return _(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;e>i;++i)n[i]=0;for(var a=t.length,i=0;a>i;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;e>n;++n)r[n]=t[n][2];return r}function s(t){var e=d(t,E);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=d(t,L);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=d(t,S);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function c(t){var e=d(t,C);return e.attributes.position.location=0,e.attributes.id.location=1,e}function f(t){var e=d(t,P);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function h(t){var e=d(t,z);return e.attributes.position.location=0,e}function p(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),p=f(e),d=h(e),y=m(e,_(new Uint8Array([255,255,255,255]),[1,1,4]));y.generateMipmap(),y.minFilter=e.LINEAR_MIPMAP_LINEAR,y.magFilter=e.LINEAR;var b=g(e),x=g(e),w=g(e),k=g(e),A=g(e),M=v(e,[{buffer:b,type:e.FLOAT,size:3},{buffer:A,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:x,type:e.FLOAT,size:4},{buffer:w,type:e.FLOAT,size:2},{buffer:k,type:e.FLOAT,size:3}]),T=g(e),E=g(e),L=g(e),S=g(e),C=v(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:S,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:E,type:e.FLOAT,size:4},{buffer:L,type:e.FLOAT,size:2}]),P=g(e),z=g(e),R=g(e),O=g(e),I=g(e),j=v(e,[{buffer:P,type:e.FLOAT,size:3},{buffer:I,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:e.FLOAT,size:4},{buffer:R,type:e.FLOAT,size:2},{buffer:O,type:e.FLOAT,size:1}]),N=g(e),F=v(e,[{buffer:N,type:e.FLOAT,size:3}]),D=new n(e,y,r,i,a,o,p,d,b,A,x,w,k,M,T,S,E,L,C,P,I,z,R,O,j,N,F);return D.update(t),D}var d=t(\"gl-shader\"),g=t(\"gl-buffer\"),v=t(\"gl-vao\"),m=t(\"gl-texture2d\"),y=t(\"normals\"),b=t(\"gl-mat4/multiply\"),x=t(\"gl-mat4/invert\"),_=t(\"ndarray\"),w=t(\"colormap\"),k=t(\"simplicial-complex-contour\"),A=t(\"typedarray-pool\"),M=t(\"./lib/shaders\"),T=t(\"./lib/closest-point\"),E=M.meshShader,L=M.wireShader,S=M.pointShader,C=M.pickShader,P=M.pointPickShader,z=M.contourShader,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=n.prototype;O.isOpaque=function(){return this.opacity>=1},O.isTransparent=function(){return this.opacity<1},O.pickSlots=1,O.setPickBase=function(t){this.pickId=t},O.highlight=function(t){if(!t||!this.contourEnable)return void(this.contourCount=0);for(var e=k(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=A.mallocFloat32(6*a),s=0,l=0;a>l;++l)for(var u=r[l],c=0;2>c;++c){var f=u[0];2===u.length&&(f=u[c]);for(var h=n[f][0],p=n[f][1],d=i[f],g=1-d,v=this.positions[h],m=this.positions[p],y=0;3>y;++y)o[s++]=d*v[y]+g*m[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),A.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"opacity\"in t&&(this.opacity=t.opacity),t.texture?(this.texture.dispose(),this.texture=m(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],f=[],h=[],p=[],d=[],g=[],v=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var k=t.vertexNormals,A=t.cellNormals;t.useFacetNormals&&!A&&(A=y.faceNormals(r,n)),A||k||(k=y.vertexNormals(r,n));var M=t.vertexColors,T=t.cellColors,E=t.meshColor||[1,1,1,1],L=t.vertexUVs,S=t.vertexIntensity,C=t.cellUVs,P=t.cellIntensity,z=1/0,R=-(1/0);if(!L&&!C)if(S)for(var O=0;O<S.length;++O){var I=S[O];z=Math.min(z,I),R=Math.max(R,I)}else if(P)for(var O=0;O<P.length;++O){var I=P[O];z=Math.min(z,I),R=Math.max(R,I)}else for(var O=0;O<n.length;++O){var I=n[O][2];z=Math.min(z,I),R=Math.max(R,I)}S?this.intensity=S:P?this.intensity=a(r,n.length,P):this.intensity=o(n);var j=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var O=0;O<n.length;++O)for(var F=n[O],D=0;3>D;++D)!isNaN(F[D])&&isFinite(F[D])&&(this.bounds[0][D]=Math.min(this.bounds[0][D],F[D]),this.bounds[1][D]=Math.max(this.bounds[1][D],F[D]));var B=0,U=0,V=0;t:for(var O=0;O<r.length;++O){var q=r[O];switch(q.length){case 1:for(var H=q[0],F=n[H],D=0;3>D;++D)if(isNaN(F[D])||!isFinite(F[D]))continue t;v.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?b.push(G[0],G[1],G[2],1):b.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],x.push(Y[0],Y[1]),j?_.push(j[H]):_.push(N),w.push(O),V+=1;break;case 2:for(var D=0;2>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;2>D;++D){var H=q[D],F=n[H];h.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?p.push(G[0],G[1],G[2],1):p.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],d.push(Y[0],Y[1]),g.push(O)}U+=1;break;case 3:for(var D=0;3>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;3>D;++D){var H=q[D],F=n[H];s.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?l.push(G[0],G[1],G[2],1):l.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],c.push(Y[0],Y[1]);var W;W=k?k[H]:A[O],u.push(W[0],W[1],W[2]),f.push(O)}B+=1}}this.pointCount=V,this.edgeCount=U,this.triangleCount=B,this.pointPositions.update(v),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(h),this.edgeColors.update(p),this.edgeUVs.update(d),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(f))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(var o=0;3>o;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;3>o;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;3>o;++o){for(var c=l[12+o],f=0;3>f;++f)c+=l[4*f+o]*this.lightPosition[f];s.lightPosition[o]=c/u}if(this.triangleCount>0){var h=this.triShader;h.bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var h=this.lineShader;h.bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var h=this.pointShader;h.bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var h=this.contourShader;h.bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=T(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=p},{\"./lib/closest-point\":354,\"./lib/shaders\":355,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-shader\":385,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,normals:358,\"simplicial-complex-contour\":360,\"typedarray-pool\":463}],357:[function(t,e,r){\"use strict\";function n(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];\n",
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s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,f=i.dataBox,h=i.screenBox,p=i.pixelRatio,d=i.tickEnable,g=i.tickPad,v=i.tickColor,m=i.tickAngle,y=(i.tickMarkLength,i.labelEnable),b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],k=this.labelCount[n],A=l.lt(o,f[n]),M=l.le(o,f[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(h[2+n]-h[n])-1;var T=2/h[2+(1^n)]-h[1^n];e[1^n]=T*c[1^n]-1,d[n]&&(e[1^n]-=T*p*g[n],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n],a.uniforms.angle=m[n],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n]&&(e[1^n]-=T*p*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,k)),e[1^n]=T*c[2+(1^n)]-1,d[n+2]&&(e[1^n]+=T*p*g[n+2],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n+2],a.uniforms.angle=m[n+2],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n+2]&&(e[1^n]+=T*p*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,k))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){for(var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,o=r.titleCenter,u=r.pixelRatio,c=0;2>c;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;2>u;++u){var c=a[u],f=a[u+2],h=f-c,p=.5*(o[u+2]+o[u]),d=o[u+2]-o[u],g=l[u],v=l[u+2],m=v-g,y=s[u],b=s[u+2],x=b-y;e[u]=2*h/d*m/x,t[u]=2*(c-p)/d*m/x}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){for(var e=[],r=t.ticks,n=t.bounds,i=0;2>i;++i){for(var a=[Math.floor(e.length/3)],o=[-(1/0)],l=r[i],u=0;u<l.length;++u){for(var c=l[u],f=c.x,h=c.text,p=c.font||\"sans-serif\",d=c.fontSize||12,g=s(p,h).data,v=1/(n[i+2]-n[i]),m=n[i],y=0;y<g.length;y+=2)e.push(g[y]*d,-g[y+1]*d,(f-m)*v);a.push(Math.floor(e.length/3)),o.push(f)}this.tickOffset[i]=a,this.tickX[i]=o}for(var i=0;2>i;++i){this.labelOffset[i]=Math.floor(e.length/3);for(var g=s(t.labelFont[i],t.labels[i]).data,d=t.labelSize[i],u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.labelCount[i]=Math.floor(e.length/3)-this.labelOffset[i]}this.titleOffset=Math.floor(e.length/3);for(var g=s(t.titleFont,t.title).data,d=t.titleSize,u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.titleCount=Math.floor(e.length/3)-this.titleOffset,this.vbo.update(e)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458}],370:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],371:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-(1/0),-(1/0)],this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}function i(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function a(t,e){return t.x-e.x}function o(t){var e=t.gl,r=s(e,[e.drawingBufferWidth,e.drawingBufferHeight]),i=new n(e,r);return i.grid=l(i),i.text=u(i),i.line=c(i),i.box=f(i),i.update(t),i}e.exports=o;var s=t(\"gl-select-static\"),l=t(\"./lib/grid\"),u=t(\"./lib/text\"),c=t(\"./lib/line\"),f=t(\"./lib/box\"),h=n.prototype;h.setDirty=function(){this.dirty=this.pickDirty=!0},h.setOverlayDirty=function(){this.dirty=!0},h.nextDepthValue=function(){return this._depthCounter++/65536},h.draw=function(){return function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT),t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;2>d;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(var d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind();for(var d=0;2>d;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();for(var b=this.overlays,d=0;d<b.length;++d)b[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),h.drawPick=function(){return function(){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}(),h.pick=function(){return function(t,e){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){\n",
+       "var f=u[c].pick(a,o,l);if(f)return f}return null}}(),h.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},h.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},h.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},h.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;2>u;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.setDirty()},h.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},h.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},h.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},h.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},h.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":365,\"./lib/grid\":366,\"./lib/line\":367,\"./lib/text\":369,\"gl-select-static\":384}],372:[function(t,e,r){\"use strict\";e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",pickFragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],373:[function(t,e,r){\"use strict\";function n(t){if(t in h)return h[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var f=s[0]-o[0],h=s[1]-o[1],p=Math.sqrt(f*f+h*h);f/=p,h/=p,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(a[0],a[1]+1.4),n.push(h,-f),r.push(o[0],o[1]+1.4),n.push(h,-f)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;2>o;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return h[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.offsetBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,f.vertex,f.fragment),a=o(r,f.pickVertex,f.pickFragment),l=s(r),u=s(r),c=s(r),h=s(r),p=new i(t,n,a,l,u,c,h);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),f=t(\"./lib/shaders\"),h={},p=i.prototype;!function(){function t(){var t=this.plot,n=this.bounds,i=t.viewBox,a=t.dataBox,o=t.pixelRatio,s=n[2]-n[0],l=n[3]-n[1],u=a[2]-a[0],c=a[3]-a[1];e[0]=2*s/u,e[4]=2*l/c,e[6]=2*(n[0]-a[0])/u-1,e[7]=2*(n[1]-a[1])/c-1;var f=i[2]-i[0],h=i[3]-i[1];r[0]=2*o/f,r[1]=2*o/h}var e=[1,0,0,0,1,0,0,0,1],r=[1,1];p.draw=function(){var n=this.plot,i=this.shader,a=this.numVertices,o=n.gl;t.call(this),i.bind(),i.uniforms.pixelScale=r,i.uniforms.viewTransform=e,this.positionBuffer.bind(),i.attributes.position.pointer(),this.offsetBuffer.bind(),i.attributes.offset.pointer(),this.colorBuffer.bind(),i.attributes.color.pointer(o.UNSIGNED_BYTE,!0),o.drawArrays(o.TRIANGLES,0,a)};var n=[0,0,0,0];p.drawPick=function(i){var a=this.plot,o=this.pickShader,s=this.numVertices,l=a.gl;this.pickOffset=i;for(var u=0;4>u;++u)n[u]=i>>8*u&255;return t.call(this),o.bind(),o.uniforms.pixelScale=r,o.uniforms.viewTransform=e,o.uniforms.pickOffset=n,this.positionBuffer.bind(),o.attributes.position.pointer(),this.offsetBuffer.bind(),o.attributes.offset.pointer(),this.idBuffer.bind(),o.attributes.id.pointer(l.UNSIGNED_BYTE,!1),l.drawArrays(l.TRIANGLES,0,s),i+this.numPoints}}(),p.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},p.update=function(t){t=t||{};var e=t.positions||[],r=t.colors||[],i=t.glyphs||[],a=t.sizes||[],o=t.borderWidths||[],s=t.borderColors||[];this.points=e;for(var c=this.bounds=[1/0,1/0,-(1/0),-(1/0)],f=0,h=0;h<i.length;++h){f+=l(\"sans-serif\",i[h]).data.length+n(i[h]).coords.length>>1;for(var p=0;2>p;++p)c[p]=Math.min(c[p],e[2*h+p]),c[2+p]=Math.max(c[2+p],e[2*h+p])}c[0]===c[2]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);for(var d=1/(c[2]-c[0]),g=1/(c[3]-c[1]),v=c[0],m=c[1],y=u.mallocFloat32(2*f),b=u.mallocFloat32(2*f),x=u.mallocUint8(4*f),_=u.mallocUint32(f),w=0,h=0;h<i.length;++h){for(var k=l(\"sans-serif\",i[h]),A=n(i[h]),M=d*(e[2*h]-v),T=g*(e[2*h+1]-m),E=a[h],L=255*r[4*h],S=255*r[4*h+1],C=255*r[4*h+2],P=255*r[4*h+3],z=.5*(A.bounds[0]+A.bounds[2]),R=.5*(A.bounds[1]+A.bounds[3]),p=0;p<k.data.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-E*(k.data[p]-z),b[2*w+1]=-E*(k.data[p+1]-R),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1;var O=o[h];L=255*s[4*h],S=255*s[4*h+1],C=255*s[4*h+2],P=255*s[4*h+3];for(var p=0;p<A.coords.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-(E*(A.coords[p]-z)+O*A.normals[p]),b[2*w+1]=-(E*(A.coords[p+1]-R)+O*A.normals[p+1]),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1}this.numPoints=i.length,this.numVertices=f,this.positionBuffer.update(y),this.offsetBuffer.update(b),this.colorBuffer.update(x),this.idBuffer.update(_),u.free(y),u.free(b),u.free(x),u.free(_)},p.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":372,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458,\"typedarray-pool\":463,\"vectorize-text\":465}],374:[function(t,e,r){r.pointVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute float weight;\\n\\nuniform mat3 matrix;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\\n\",r.pointFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],375:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],376:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){4*h>=a?i(0,a-1,t,e,r,n):f(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;e>=o;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],f=a[o],h=o;h>t;){var p=r[h-1],d=n[2*(h-1)];if((p-s||l-d)>=0)break;r[h]=p,n[2*h]=d,n[2*h+1]=n[2*h-1],i[h]=i[h-1],a[h]=a[h-1],h-=1}r[h]=s,n[2*h]=l,n[2*h+1]=u,i[h]=c,a[h]=f}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],f=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=f}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0}function c(t,e,r,n,i,a,o,s){return(e-a[t]||o[2*t]-r||i-s[t])<0}function f(t,e,r,n,p,d){var g=(e-t+1)/6|0,v=t+g,m=e-g,y=t+e>>1,b=y-g,x=y+g,_=v,w=b,k=y,A=x,M=m,T=t+1,E=e-1,L=0;u(_,w,r,n,p,d)&&(L=_,_=w,w=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L),u(_,k,r,n,p,d)&&(L=_,_=k,k=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(_,A,r,n,p,d)&&(L=_,_=A,A=L),u(k,A,r,n,p,d)&&(L=k,k=A,A=L),u(w,M,r,n,p,d)&&(L=w,w=M,M=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L);var S=r[w],C=n[2*w],P=n[2*w+1],z=p[w],R=d[w],O=r[A],I=n[2*A],j=n[2*A+1],N=p[A],F=d[A],D=_,B=k,U=M,V=v,q=y,H=m,G=r[D],Y=r[B],X=r[U];r[V]=G,r[q]=Y,r[H]=X;for(var W=0;2>W;++W){var Z=n[2*D+W],$=n[2*B+W],K=n[2*U+W];n[2*V+W]=Z,n[2*q+W]=$,n[2*H+W]=K}var Q=p[D],J=p[B],tt=p[U];p[V]=Q,p[q]=J,p[H]=tt;var et=d[D],rt=d[B],nt=d[U];d[V]=et,d[q]=rt,d[H]=nt,o(b,t,r,n,p,d),o(x,e,r,n,p,d);for(var it=T;E>=it;++it)if(c(it,S,C,P,z,r,n,p))it!==T&&a(it,T,r,n,p,d),++T;else if(!c(it,O,I,j,N,r,n,p))for(;;){if(c(E,O,I,j,N,r,n,p)){c(E,S,C,P,z,r,n,p)?(s(it,T,E,r,n,p,d),++T,--E):(a(it,E,r,n,p,d),--E);break}if(--E<it)break}l(t,T-1,S,C,P,z,R,r,n,p,d),l(e,E+1,O,I,j,N,F,r,n,p,d),h>=T-2-t?i(t,T-2,r,n,p,d):f(t,T-2,r,n,p,d),h>=e-(E+2)?i(E+2,e,r,n,p,d):f(E+2,e,r,n,p,d),h>=E-T?i(T,E,r,n,p,d):f(T,E,r,n,p,d)}e.exports=n;var h=32},{}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;n>u;++u){var c=t[2*u],f=t[2*u+1],h=e[u];c>=i&&o>=c&&f>=a&&s>=f&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=f,e[l]=h,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var f=.5*o,h=s+1,p=u-s;r[_]=p,x[_++]=c;for(var d=0;2>d;++d)for(var g=0;2>g;++g){var v=i+d*f,m=a+g*f,y=n(t,e,h,u,v,m,v+f,m+f);if(y!==h){if(y-h>=Math.max(.9*p,32)){var b=u+s>>>1;l(v,m,f,h,b,c+1),h=b}l(v,m,f,h,y,c+1),h=y}}}var u=t.length>>>1;if(1>u)return[];for(var c=1/0,f=1/0,h=-(1/0),p=-(1/0),d=0;u>d;++d){var g=t[2*d],v=t[2*d+1];c=Math.min(c,g),h=Math.max(h,g),f=Math.min(f,v),p=Math.max(p,v),e[d]=d}c===h&&(h+=1+Math.abs(h)),f===p&&(p+=1+Math.abs(h));var m=1/(h-c),y=1/(p-f),b=Math.max(h-c,p-f);a=a||[0,0,0,0],a[0]=c,a[1]=f,a[2]=h,a[3]=p;var x=o.mallocInt32(u),_=0;l(c,f,b,0,u,0),s(x,t,e,r,u);for(var w=[],k=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*m,t[2*_+1]=(t[2*_+1]-f)*y;var M=x[_];M!==k&&(w.push(new i(b*Math.pow(.5,M),_+1,A-(_+1))),A=_+1,k=M)}return w.push(new i(b*Math.pow(.5,M+1),0,A)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":376,\"typedarray-pool\":463}],378:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.weightBuffer=n,this.shader=i,this.pickShader=a,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),h=new n(t,i,s,l,u,f);return h.update(e),t.addObject(h),h}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var f=n.prototype;f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},f.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords);var r=t.positions,n=u.mallocFloat32(r.length),i=u.mallocInt32(r.length>>>1);n.set(r);var a=u.mallocFloat32(r.length);this.points=r,this.scales=l(n,i,a,this.bounds),this.offsetBuffer.update(n),this.pickBuffer.update(i),this.weightBuffer.update(a);for(var o=u.mallocFloat32(r.length>>>1),s=0,c=0;s<r.length;s+=2,++c)o[c]=n[s];u.free(i),u.free(n),u.free(a),this.xCoords=o,this.pointCount=r.length>>>1,this.pickOffset=0},f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.scales,o=this.offsetBuffer,l=this.pickBuffer,u=this.bounds,c=this.size,f=this.borderSize,h=n.gl,p=n.pickPixelRatio,d=n.viewBox,g=n.dataBox;if(0===this.pointCount)return r;var v=u[2]-u[0],m=u[3]-u[1],y=g[2]-g[0],b=g[3]-g[1],x=(d[2]-d[0])*p/n.pixelRatio,_=(d[3]-d[1])*p/n.pixelRatio,w=Math.min(y/x,b/_);t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(u[0]-g[0])/y-1,t[7]=2*(u[1]-g[1])/b-1,this.pickOffset=r,e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,i.bind(),i.uniforms.matrix=t,i.uniforms.color=this.color,i.uniforms.borderColor=this.borderColor,i.uniforms.pointSize=p*(c+f),i.uniforms.pickOffset=e,0===this.borderSize?i.uniforms.centerFraction=2:i.uniforms.centerFraction=c/(c+f+1.25),o.bind(),i.attributes.position.pointer(),l.bind(),i.attributes.pickId.pointer(h.UNSIGNED_BYTE);for(var k=this.xCoords,A=(g[0]-u[0]-w*c*p)/v,M=(g[2]-u[0]+w*c*p)/v,T=a.length-1;T>=0;--T){var E=a[T];if(!(E.pixelSize<w&&T>1)){var L=E.offset,S=E.count+L,C=s.ge(k,A,L,S-1),P=s.lt(k,M,C,S-1)+1;h.drawArrays(h.POINTS,C,P-C)}}return r+this.pointCount}}(),f.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.scales,i=this.offsetBuffer,a=this.bounds,o=this.size,l=this.borderSize,u=e.gl,c=e.pixelRatio,f=e.viewBox,h=e.dataBox;if(0!==this.pointCount){var p=a[2]-a[0],d=a[3]-a[1],g=h[2]-h[0],v=h[3]-h[1],m=f[2]-f[0],y=f[3]-f[1],b=Math.min(g/m,v/y);t[0]=2*p/g,t[4]=2*d/v,t[6]=2*(a[0]-h[0])/g-1,t[7]=2*(a[1]-h[1])/v-1,r.bind(),r.uniforms.matrix=t,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointSize=c*(o+l),r.uniforms.useWeight=1,0===this.borderSize?r.uniforms.centerFraction=2:r.uniforms.centerFraction=o/(o+l+1.25),i.bind(),r.attributes.position.pointer(),this.weightBuffer.bind(),r.attributes.weight.pointer();for(var x=this.xCoords,_=(h[0]-a[0]-b*o*c)/p,w=(h[2]-a[0]+b*o*c)/p,k=!0,A=n.length-1;A>=0;--A){var M=n[A];if(!(M.pixelSize<b&&A>1)){var T=M.offset,E=M.count+T,L=s.ge(x,_,T,E-1),S=s.lt(x,w,L,E-1)+1;u.drawArrays(u.POINTS,L,S-L),k&&(k=!1,r.uniforms.useWeight=0)}}}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":374,\"binary-search-bounds\":375,\"gl-buffer\":325,\"gl-shader\":385,\"snap-points-2d\":377,\"typedarray-pool\":463}],379:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;2>c;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":465}],380:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},v={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,f)},r.createOrtho=function(t){return n(t,h)},r.createProject=function(t){return n(t,p)},r.createPickPerspective=function(t){return n(t,d)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,v)}},{\"gl-shader\":385}],381:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,f,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=f,this.pickProjectShader=h,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=S,r=0;2>r;++r)for(var n=0;3>n;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function f(t,e,r,n,a){var o,f=e.axesProject,h=e.gl,p=t.uniforms,d=r.model||x,g=r.view||x,v=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/h.drawingBufferWidth,w[1]=2/h.drawingBufferHeight,t.bind(),p.view=g,p.projection=v,p.screenSize=w,p.highlightId=e.highlightId,p.highlightScale=e.highlightScale,p.clipBounds=b,p.pickGroup=e.pickId/255,p.pixelRatio=e.pixelRatio;for(var _=0;3>_;++_)if(f[_]&&e.projectOpacity[_]<1===n){p.scale=e.projectScale[_],p.opacity=e.projectOpacity[_];for(var S=E,C=0;16>C;++C)S[C]=0;for(var C=0;4>C;++C)S[5*C]=1;S[5*_]=0,o[_]<0?S[12+_]=y[0][_]:S[12+_]=y[1][_],m(S,d,S),p.model=S;var P=(_+1)%3,z=(_+2)%3,R=s(k),O=s(A);R[P]=1,O[z]=1;var I=i(v,g,d,l(M,R)),j=i(v,g,d,l(T,O));if(Math.abs(I[1])>Math.abs(j[1])){var N=I;I=j,j=N,N=R,R=O,O=N;var F=P;P=z,z=F}I[0]<0&&(R[P]=-1),j[1]>0&&(O[z]=-1);for(var D=0,B=0,C=0;4>C;++C)D+=Math.pow(d[4*P+C],2),B+=Math.pow(d[4*z+C],2);R[P]/=Math.sqrt(D),O[z]/=Math.sqrt(B),p.axes[0]=R,p.axes[1]=O,p.fragClipBounds[0]=u(L,b[0],_,-1e8),p.fragClipBounds[1]=u(L,b[1],_,1e8),e.vao.draw(h.TRIANGLES,e.vertexCount),e.lineWidth>0&&(h.lineWidth(e.lineWidth),e.vao.draw(h.LINES,e.lineVertexCount,e.vertexCount))}}function h(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=z,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}f(e,r,n,i,a),r.vao.unbind()}function p(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=d(e),c=d(e),f=d(e),h=d(e),p=g(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:f,size:2,type:e.FLOAT},{buffer:h,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new o(e,r,n,i,u,c,f,h,p,a,s,l);return v.update(t),v}var d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"typedarray-pool\"),m=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=p;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],k=[0,0,0],A=[0,0,0],M=[0,0,0,1],T=[0,0,0,1],E=x.slice(),L=[0,0,0],S=[[0,0,0],[0,0,0]],C=[-1e8,-1e8,-1e8],P=[1e8,1e8,1e8],z=[C,P];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;h(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||0>e)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;3>i;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in t&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-(1/0),-(1/0),-(1/0)],l=t.glyph,u=t.color,c=t.size,f=t.angle,h=t.lineColor,p=0,d=0,g=0,m=n.length;t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_)if(isNaN(x[_])||!isFinite(x[_]))continue t;var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];d+=3*k.cells.length,g+=2*A.edges.length}var T=d+g,E=v.mallocFloat(3*T),L=v.mallocFloat(4*T),S=v.mallocFloat(2*T),C=v.mallocUint32(T),P=[0,a[1]],z=0,R=d,O=[0,0,0,1],I=[0,0,0,1],j=Array.isArray(u)&&Array.isArray(u[0]),N=Array.isArray(h)&&Array.isArray(h[0]);t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_){if(isNaN(x[_])||!isFinite(x[_])){p+=1;continue t}s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_])}var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];if(Array.isArray(u)){var F;if(F=j?u[y]:u,3===F.length){for(var _=0;3>_;++_)O[_]=F[_];O[3]=1}else if(4===F.length)for(var _=0;4>_;++_)O[_]=F[_];\n",
+       "}else O[0]=O[1]=O[2]=0,O[3]=1;if(Array.isArray(h)){var F;if(F=N?h[y]:h,3===F.length){for(var _=0;3>_;++_)I[_]=F[_];I[_]=1}else if(4===F.length)for(var _=0;4>_;++_)I[_]=F[_]}else I[0]=I[1]=I[2]=0,I[3]=1;var D=.5;Array.isArray(c)?D=+c[y]:c?D=+c:this.useOrtho&&(D=12);var B=0;Array.isArray(f)?B=+f[y]:f&&(B=+f);for(var U=Math.cos(B),V=Math.sin(B),x=n[y],_=0;3>_;++_)s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_]);a[0]<0?P[0]=a[0]*(1+M[1][0]):a[0]>0&&(P[0]=-a[0]*(1+M[0][0]));for(var q=k.cells,H=k.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;3>Y;++Y){for(var X=0;3>X;++X)E[3*z+X]=x[X];for(var X=0;4>X;++X)L[4*z+X]=O[X];C[z]=p;var W=H[G[Y]];S[2*z]=D*(U*W[0]-V*W[1]+P[0]),S[2*z+1]=D*(V*W[0]+U*W[1]+P[1]),z+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;2>Y;++Y){for(var X=0;3>X;++X)E[3*R+X]=x[X];for(var X=0;4>X;++X)L[4*R+X]=I[X];C[R]=p;var W=H[G[Y]];S[2*R]=D*(U*W[0]-V*W[1]+P[0]),S[2*R+1]=D*(V*W[0]+U*W[1]+P[1]),R+=1}p+=1}this.vertexCount=d,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(C)),v.free(E),v.free(L),v.free(S),v.free(C),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":379,\"./lib/shaders\":380,\"gl-buffer\":325,\"gl-mat4/multiply\":346,\"gl-vao\":420,\"typedarray-pool\":463}],382:[function(t,e,r){\"use strict\";r.boxVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(f>p||h>d)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*c;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":382,\"gl-buffer\":325,\"gl-shader\":385}],384:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(255>_inline_31_arg0_||255>_inline_31_arg1_||255>_inline_31_arg2_||255>_inline_31_arg3_){var 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l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],410:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\nattribute vec2 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  value = f.x;\\n  kill = f.y;\\n  planeCoordinate = uv.xy;\\n  \\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  float interpValue = (value - lowerBound.z) / (upperBound.z - lowerBound.z);\\n  vec4 surfaceColor = texture2D(colormap, vec2(interpValue, interpValue));\\n  vec4 litColor 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eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 || \\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e}},{\"gl-shader\":385}],411:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],412:[function(t,e,r){\"use strict\";function n(t){if(t in l)return l[t];for(var e=[],r=0;t>r;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");for(var n=[\"array\"],i=[\"junk\"],r=0;t>r;++r){n.push(\"array\"),i.push(\"out\"+r+\"s\");var a=o(t);a[r]=-1,n.push({array:0,offset:a.slice()}),a[r]=1,n.push({array:0,offset:a.slice()}),i.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return l[t]=s({args:n,pre:c,post:c,body:{body:e.join(\"\"),args:i.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}function i(t){function e(e){for(var r=a-e.length,n=[],i=[],s=[],l=0;a>l;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),n.push(\"1\"),i.push(\"s[\"+l+\"]-2\"));var u=\".lo(\"+n.join()+\").hi(\"+i.join()+\")\";if(0===n.length&&(u=\"\"),r>0){o.push(\"if(1\");for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\"&&s[\",l,\"]>2\");o.push(\"){grad\",r,\"(src.pick(\",s.join(),\")\",u);for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\",dst.pick(\",s.join(),\",\",l,\")\",u);o.push(\");\")}for(var l=0;l<e.length;++l){var c=Math.abs(e[l])-1,f=\"dst.pick(\"+s.join()+\",\"+c+\")\"+u;switch(t[c]){case\"clamp\":var h=s.slice(),p=s.slice();e[l]<0?h[c]=\"s[\"+c+\"]-2\":p[c]=\"1\",0===r?o.push(\"if(s[\",c,\"]>1){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",h.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>1){diff(\",f,\",src.pick(\",h.join(),\")\",u,\",src.pick(\",p.join(),\")\",u,\");}else{zero(\",f,\");};\");break;case\"mirror\":0===r?o.push(\"dst.set(\",s.join(),\",\",c,\",0);\"):o.push(\"zero(\",f,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[c]=\"s[\"+c+\"]-2\",g[c]=\"0\"):(d[c]=\"s[\"+c+\"]-1\",g[c]=\"1\"),0===r?o.push(\"if(s[\",c,\"]>2){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>2){diff(\",f,\",src.pick(\",d.join(),\")\",u,\",src.pick(\",g.join(),\")\",u,\");}else{zero(\",f,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}r>0&&o.push(\"};\")}var r=t.join(),i=u[r];if(i)return i;for(var a=t.length,o=[\"function gradient(dst,src){var s=src.shape.slice();\"],s=0;1<<a>s;++s){for(var c=[],p=0;a>p;++p)s&1<<p&&c.push(p+1);for(var d=0;d<1<<c.length;++d){for(var g=c.slice(),p=0;p<c.length;++p)d&1<<p&&(g[p]=-g[p]);e(g)}}o.push(\"return dst;};return gradient\");for(var v=[\"diff\",\"zero\"],m=[f,h],s=1;a>=s;++s)v.push(\"grad\"+s),m.push(n(s));v.push(o.join(\"\"));var y=Function.apply(void 0,v),i=y.apply(void 0,m);return l[r]=i,i}function a(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=\"string\"==typeof r?o(e.dimension,r):o(e.dimension,\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var n=0;n<e.dimension;++n)if(t.shape[n]!==e.shape[n])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;var a=i(r);return a(t,e)}e.exports=a;var o=t(\"dup\"),s=t(\"cwise-compiler\"),l={},u={},c={body:\"\",args:[],thisVars:[],localVars:[]},f=s({args:[\"array\",\"array\",\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),h=s({args:[\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"})},{\"cwise-compiler\":316,dup:322}],413:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],a=t,o=1;a instanceof Array;)r.push(a.length),o*=a.length,a=a[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),i(e,t),e)}},{\"./doConvert.js\":414,ndarray:438}],414:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":316}],415:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,f,h,p,d){this.gl=t,this.shape=e,this.bounds=r,this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=f,this._contourVAO=h,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=p,this._dynamicVAO=d,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.dirty=!0}function o(t,e){for(var r=e.axes&&e.axes.lastCubeProps.axis||F,n=e.showSurface,i=e.showContour,a=0;3>a;++a){n=n||e.surfaceProject[a];for(var o=0;3>o;++o)i=i||e.contourProject[a][o]}for(var a=0;3>a;++a){for(var s=D.projections[a],o=0;16>o;++o)s[o]=0;for(var o=0;4>o;++o)s[5*o]=1;s[5*a]=0,s[12+a]=e.axesBounds[+(r[a]>0)][a],k(s,t.model,s);for(var l=D.clipBounds[a],u=0;2>u;++u)for(var o=0;3>o;++o)l[u][o]=t.clipBounds[u][o];l[0][a]=-1e8,l[1][a]=1e8}return D.showSurface=n,D.showContour=i,D}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||R,n.view=t.view||R,n.projection=t.projection||R,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;2>i;++i)for(var a=n.clipBounds[i],s=0;3>s;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.shape=n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V;var l=U;k(l,n.view,n.model),k(l,n.projection,l),A(l,l);for(var i=0;3>i;++i)n.eyePosition[i]=l[12+i]/l[15];for(var u=l[15],i=0;3>i;++i)u+=this.lightPosition[i]*l[4*i+3];for(var i=0;3>i;++i){for(var c=l[12+i],s=0;3>s;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var f=o(n,this);if(f.showSurface&&e===this.opacity<1){this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vao.draw(r.TRIANGLES,this._vertexCount);for(var i=0;3>i;++i)this.surfaceProject[i]&&(this._shader.uniforms.model=f.projections[i],this._shader.uniforms.clipBounds=f.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(f.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var p=this._contourVAO;p.bind();for(var i=0;3>i;++i){h.uniforms.permutation=I[i],r.lineWidth(this.contourWidth[i]);for(var s=0;s<this.contourLevels[i].length;++s)s===this.highlightLevel[i]?(h.uniforms.contourColor=this.highlightColor[i],h.uniforms.contourTint=this.highlightTint[i]):(0===s||s-1===this.highlightLevel[i])&&(h.uniforms.contourColor=this.contourColor[i],h.uniforms.contourTint=this.contourTint[i]),h.uniforms.height=this.contourLevels[i][s],p.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s])}for(var i=0;3>i;++i){h.uniforms.model=f.projections[i],h.uniforms.clipBounds=f.clipBounds[i];for(var s=0;3>s;++s)if(this.contourProject[i][s]){h.uniforms.permutation=I[s],r.lineWidth(this.contourWidth[s]);for(var d=0;d<this.contourLevels[s].length;++d)d===this.highlightLevel[s]?(h.uniforms.contourColor=this.highlightColor[s],h.uniforms.contourTint=this.highlightTint[s]):(0===d||d-1===this.highlightLevel[s])&&(h.uniforms.contourColor=this.contourColor[s],h.uniforms.contourTint=this.contourTint[s]),h.uniforms.height=this.contourLevels[s][d],p.draw(r.LINES,this._contourCounts[s][d],this._contourOffsets[s][d])}}p=this._dynamicVAO,p.bind();for(var i=0;3>i;++i)if(0!==this._dynamicCounts[i]){h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=I[i],r.lineWidth(this.dynamicWidth[i]),h.uniforms.contourColor=this.dynamicColor[i],h.uniforms.contourTint=this.dynamicTint[i],h.uniforms.height=this.dynamicLevel[i],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]);for(var s=0;3>s;++s)this.contourProject[s][i]&&(h.uniforms.model=f.projections[s],h.uniforms.clipBounds=f.clipBounds[s],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]))}p.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function f(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function h(t){var e=t.gl,r=(t.field||t.coords&&t.coords[2]||_([],[0,0]),L(e)),n=C(e),i=S(e),o=P(e),s=d(e),l=g(e,[{buffer:s,size:4,stride:z,offset:0},{buffer:s,size:2,stride:z,offset:16},{buffer:s,size:3,stride:z,offset:24}]),u=d(e),c=g(e,[{buffer:u,size:4}]),f=d(e),h=g(e,[{buffer:f,size:2,type:e.FLOAT}]),p=v(e,1,j,e.RGBA,e.UNSIGNED_BYTE);p.minFilter=e.LINEAR,p.magFilter=e.LINEAR;var m=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,p,i,o,u,c,f,h),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",m.update(y),m}e.exports=h;var p=t(\"bit-twiddle\"),d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),m=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),k=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),M=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),_=t(\"ndarray\"),E=t(\"./lib/shaders\"),L=E.createShader,S=E.createContourShader,C=E.createPickShader,P=E.createPickContourShader,z=36,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],I=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;3>t;++t){var e=I[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var j=265,N=a.prototype;N.isTransparent=function(){return this.opacity<1},N.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},N.pickSlots=1,N.setPickBase=function(t){this.pickId=t};var F=[0,0,0],D={showSurface:!1,showContour:!1,projections:[R.slice(),R.slice(),R.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:R,view:R,projection:R,inverseModel:R.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1},U=R.slice(),V=[1,0,0,0,1,0,0,0,1];N.draw=function(t){return s.call(this,t,!1)},N.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:R,view:R,projection:R,inverseModel:R,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};N.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||R,r.view=t.view||R,r.projection=t.projection||R,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;2>n;++n)for(var i=r.clipBounds[n],a=0;3>a;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount);for(var n=0;3>n;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;u.bind();for(var a=0;3>a;++a){e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=I[a];for(var n=0;n<this.contourLevels[a].length;++n)l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n])}for(var n=0;3>n;++n){l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n];for(var a=0;3>a;++a)if(this.contourProject[n][a]){l.uniforms.permutation=I[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c])}}u.unbind()}},N.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;2>c;++c)for(var f=c?a:1-a,h=0;2>h;++h)for(var p=h?l:1-l,d=i+c,g=s+h,v=f*p,m=0;3>m;++m)u[m]+=this._field[m].get(d,g)*v;for(var y=this._pickResult.level,b=0;3>b;++b)if(y[b]=M.le(this.contourLevels[b],u[b]),y[b]<0)this.contourLevels[b].length>0&&(y[b]=0);else if(y[b]<this.contourLevels[b].length-1){var x=this.contourLevels[b][y[b]],_=this.contourLevels[b][y[b]+1];Math.abs(x-u[b])>Math.abs(_-u[b])&&(y[b]+=1)}r.index[0]=.5>a?i:i+1,r.index[1]=.5>l?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1];for(var m=0;3>m;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},N.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=f(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=f(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\n",
+       "\"colorBounds\"in t&&(this.colorBounds=t.colorBounds);var e=t.field||t.coords&&t.coords[2]||null;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var r=(e.shape[0]+2)*(e.shape[1]+2);r>this._field[2].data.length&&(m.freeFloat(this._field[2].data),this._field[2].data=m.mallocFloat(p.nextPow2(r))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var n=this.shape,a=0;2>a;++a)this._field[2].size>this._field[a].data.length&&(m.freeFloat(this._field[a].data),this._field[a].data=m.mallocFloat(this._field[2].size)),this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2]);if(t.coords){var o=t.coords;if(!Array.isArray(o)||3!==o.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(var a=0;2>a;++a){for(var s=o[a],c=0;2>c;++c)if(s.shape[c]!==n[c])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[a],s)}}else if(t.ticks){var h=t.ticks;if(!Array.isArray(h)||2!==h.length)throw new Error(\"gl-surface: invalid ticks\");for(var a=0;2>a;++a){var d=h[a];if((Array.isArray(d)||d.length)&&(d=_(d)),d.shape[0]!==n[a])throw new Error(\"gl-surface: invalid tick length\");var g=_(d.data,n);g.stride[a]=d.stride[0],g.stride[1^a]=0,l(this._field[a],g)}}else{for(var a=0;2>a;++a){var v=[0,0];v[a]=1,this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2],v,0)}this._field[0].set(0,0,0);for(var c=0;c<n[0];++c)this._field[0].set(c+1,0,c);this._field[0].set(n[0]+1,0,n[0]-1),this._field[1].set(0,0,0);for(var c=0;c<n[1];++c)this._field[1].set(0,c+1,c);this._field[1].set(0,n[1]+1,n[1]-1)}for(var y=this._field,b=(y[2].size,_(m.mallocFloat(3*y[2].size*2),[3,n[0]+2,n[1]+2,2])),a=0;3>a;++a)T(b.pick(a),y[a],\"mirror\");for(var x=_(m.mallocFloat(3*y[2].size),[n[0]+2,n[1]+2,3]),a=0;a<n[0]+2;++a)for(var c=0;c<n[1]+2;++c){var k=b.get(0,a,c,0),A=b.get(0,a,c,1),M=b.get(1,a,c,0),E=b.get(1,a,c,1),L=b.get(2,a,c,0),S=b.get(2,a,c,1),C=M*S-E*L,P=L*A-S*k,z=k*E-A*M,R=Math.sqrt(C*C+P*P+z*z);1e-8>R?(R=Math.max(Math.abs(C),Math.abs(P),Math.abs(z)),1e-8>R?(z=1,P=C=0,R=1):R=1/R):R=1/Math.sqrt(R),x.set(a,c,0,C*R),x.set(a,c,1,P*R),x.set(a,c,2,z*R)}m.free(b.data);for(var I=[1/0,1/0,1/0],j=[-(1/0),-(1/0),-(1/0)],N=(n[0]-1)*(n[1]-1)*6,F=m.mallocFloat(p.nextPow2(9*N)),D=0,B=0,a=0;a<n[0]-1;++a)t:for(var c=0;c<n[1]-1;++c){for(var U=0;2>U;++U)for(var V=0;2>V;++V)for(var q=0;3>q;++q){var H=this._field[q].get(1+a+U,1+c+V);if(isNaN(H)||!isFinite(H))continue t}for(var q=0;6>q;++q){var G=a+O[q][0],Y=c+O[q][1],X=this._field[0].get(G+1,Y+1),W=this._field[1].get(G+1,Y+1),H=this._field[2].get(G+1,Y+1),C=x.get(G+1,Y+1,0),P=x.get(G+1,Y+1,1),z=x.get(G+1,Y+1,2);F[D++]=G,F[D++]=Y,F[D++]=X,F[D++]=W,F[D++]=H,F[D++]=0,F[D++]=C,F[D++]=P,F[D++]=z,I[0]=Math.min(I[0],X),I[1]=Math.min(I[1],W),I[2]=Math.min(I[2],H),j[0]=Math.max(j[0],X),j[1]=Math.max(j[1],W),j[2]=Math.max(j[2],H),B+=1}}this._vertexCount=B,this._coordinateBuffer.update(F.subarray(0,D)),m.freeFloat(F),m.free(x.data),this.bounds=[I,j]}var Z=!1;if(\"levels\"in t){var $=t.levels;$=Array.isArray($[0])?$.slice():[[],[],$];for(var a=0;3>a;++a)$[a]=$[a].slice(),$.sort(function(t,e){return t-e});t:for(var a=0;3>a;++a){if($[a].length!==this.contourLevels[a].length){Z=!0;break}for(var c=0;c<$[a].length;++c)if($[a][c]!==this.contourLevels[a][c]){Z=!0;break t}}this.contourLevels=$}if(Z){for(var y=this._field,n=this.shape,K=[],Q=0;3>Q;++Q){for(var $=this.contourLevels[Q],J=[],tt=[],et=[0,0],a=0;a<$.length;++a){var rt=w(this._field[Q],$[a]);J.push(K.length/4|0);var B=0;t:for(var c=0;c<rt.cells.length;++c)for(var nt=rt.cells[c],q=0;2>q;++q){var it=rt.positions[nt[q]],at=it[0],ot=0|Math.floor(at),st=at-ot,lt=it[1],ut=0|Math.floor(lt),ct=lt-ut,ft=!1;e:for(var ht=0;2>ht;++ht){et[ht]=0;for(var pt=(Q+ht+1)%3,U=0;2>U;++U)for(var dt=U?st:1-st,G=0|Math.min(Math.max(ot+U,0),n[0]),V=0;2>V;++V){var gt=V?ct:1-ct,Y=0|Math.min(Math.max(ut+V,0),n[1]),H=this._field[pt].get(G,Y);if(!isFinite(H)||isNaN(H)){ft=!0;break e}var vt=dt*gt;et[ht]+=vt*H}}if(ft){if(q>0){for(var mt=0;4>mt;++mt)K.pop();B-=1}continue t}K.push(et[0],et[1],it[0],it[1]),B+=1}tt.push(B)}this._contourOffsets[Q]=J,this._contourCounts[Q]=tt}for(var yt=m.mallocFloat(K.length),a=0;a<K.length;++a)yt[a]=K[a];this._contourBuffer.update(yt),m.freeFloat(yt)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},N.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;3>t;++t)m.freeFloat(this._field[t].data)},N.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;3>e;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=m.mallocFloat(12*i[0]*i[1]),o=0;3>o;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],f=this._field[l],h=w(u,r[o]),p=h.cells,d=h.positions;this._dynamicOffsets[o]=n;for(var e=0;e<p.length;++e)for(var g=p[e],v=0;2>v;++v){var y=d[g[v]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),k=b-x,A=1-k,M=+y[1],T=0|M,E=0|Math.min(T+1,i[1]),L=M-T,S=1-L,C=A*S,P=A*L,z=k*S,R=k*L,O=C*c.get(x,T)+P*c.get(x,E)+z*c.get(_,T)+R*c.get(_,E),I=C*f.get(x,T)+P*f.get(x,E)+z*f.get(_,T)+R*f.get(_,E);if(isNaN(O)||isNaN(I)){v&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=I,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),m.freeFloat(a)}}},{\"./lib/shaders\":410,\"binary-search-bounds\":411,\"bit-twiddle\":299,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,\"ndarray-gradient\":412,\"ndarray-ops\":437,\"ndarray-pack\":413,\"surface-nets\":457,\"typedarray-pool\":463}],416:[function(t,e,r){arguments[4][179][0].apply(r,arguments)},{dup:179,ndarray:438,\"ndarray-ops\":437,\"typedarray-pool\":463}],417:[function(t,e,r){arguments[4][42][0].apply(r,arguments)},{dup:42}],418:[function(t,e,r){arguments[4][43][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:43}],419:[function(t,e,r){arguments[4][44][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:44}],420:[function(t,e,r){arguments[4][45][0].apply(r,arguments)},{\"./lib/vao-emulated.js\":418,\"./lib/vao-native.js\":419,dup:45}],421:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;t>=r;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var n=0;t>=n;++n)this.tuple[n]=this.vertices[n];var i=f[t];i||(i=f[t]=o(t)),this.orient=i}function l(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(i>=r)throw new Error(\"Must input at least d+1 points\");var a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),c=0;i>=c;++c)l[c]=c;0>o&&(l[0]=1,l[1]=0);for(var f=new n(l,new Array(i+1),!1),h=f.adjacent,p=new Array(i+2),c=0;i>=c;++c){for(var d=l.slice(),g=0;i>=g;++g)g===c&&(d[g]=-1);var v=d[0];d[0]=d[1],d[1]=v;var m=new n(d,new Array(i+1),!0);h[c]=m,p[c]=m}p[i+1]=f;for(var c=0;i>=c;++c)for(var d=h[c].vertices,y=h[c].adjacent,g=0;i>=g;++g){var b=d[g];if(0>b)y[g]=f;else for(var x=0;i>=x;++x)h[x].vertices.indexOf(b)<0&&(y[g]=h[x])}for(var _=new s(i,a,p),w=!!e,c=i+1;r>c;++c)_.insert(t[c],w);return _.boundary()}e.exports=l;var u=t(\"robust-orientation\"),c=t(\"simplicial-complex\").compareCells;n.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var f=[],h=s.prototype;h.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,i=this.tuple,a=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){t=o.pop();for(var s=(t.vertices,t.adjacent),l=0;r>=l;++l){var u=s[l];if(u.boundary&&!(u.lastVisited<=-n)){for(var c=u.vertices,f=0;r>=f;++f){var h=c[f];0>h?i[f]=e:i[f]=a[h]}var p=this.orient();if(p>0)return u;u.lastVisited=-n,0===p&&o.push(u)}}}return null},h.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,a=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,u=s.adjacent,c=0;n>=c;++c)a[c]=i[l[c]];s.lastVisited=r;for(var c=0;n>=c;++c){var f=u[c];if(!(f.lastVisited>=r)){var h=a[c];a[c]=t;var p=this.orient();if(a[c]=h,0>p){s=f;continue t}f.boundary?f.lastVisited=-r:f.lastVisited=r}}return}return s},h.addPeaks=function(t,e){var r=this.vertices.length-1,o=this.dimension,s=this.vertices,l=this.tuple,u=this.interior,c=this.simplices,f=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,u.push(e);for(var h=[];f.length>0;){var e=f.pop(),p=e.vertices,d=e.adjacent,g=p.indexOf(r);if(!(0>g))for(var v=0;o>=v;++v)if(v!==g){var m=d[v];if(m.boundary&&!(m.lastVisited>=r)){var y=m.vertices;if(m.lastVisited!==-r){for(var b=0,x=0;o>=x;++x)y[x]<0?(b=x,l[x]=t):l[x]=s[y[x]];var _=this.orient();if(_>0){y[b]=r,m.boundary=!1,u.push(m),f.push(m),m.lastVisited=r;continue}m.lastVisited=-r}var w=m.adjacent,k=p.slice(),A=d.slice(),M=new n(k,A,!0);c.push(M);var T=w.indexOf(e);if(!(0>T)){w[T]=M,A[g]=m,k[v]=-1,A[v]=e,d[v]=M,M.flip();for(var x=0;o>=x;++x){var E=k[x];if(!(0>E||E===r)){for(var L=new Array(o-1),S=0,C=0;o>=C;++C){var P=k[C];0>P||C===x||(L[S++]=P)}h.push(new i(L,M,x))}}}}}}h.sort(a);for(var v=0;v+1<h.length;v+=2){var z=h[v],R=h[v+1],O=z.index,I=R.index;0>O||0>I||(z.cell.adjacent[z.index]=R.cell,R.cell.adjacent[R.index]=z.cell)}},h.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var i=this.dimension,a=this.tuple,o=0;i>=o;++o){var s=n.vertices[o];0>s?a[o]=t:a[o]=r[s]}var l=this.orient(a);0>l||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},h.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,i=0;n>i;++i){var a=r[i];if(a.boundary){for(var o=new Array(t),s=a.vertices,l=0,u=0,c=0;t>=c;++c)s[c]>=0?o[l++]=s[c]:u=1&c;if(u===(1&t)){var f=o[0];o[0]=o[1],o[1]=f}e.push(o)}}return e}},{\"robust-orientation\":444,\"simplicial-complex\":424}],422:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],423:[function(t,e,r){arguments[4][130][0].apply(r,arguments)},{dup:130}],424:[function(t,e,r){arguments[4][151][0].apply(r,arguments)},{\"bit-twiddle\":422,dup:151,\"union-find\":423}],425:[function(t,e,r){arguments[4][248][0].apply(r,arguments)},{dup:248}],426:[function(t,e,r){arguments[4][245][0].apply(r,arguments)},{dup:245,\"mouse-event\":427}],427:[function(t,e,r){arguments[4][246][0].apply(r,arguments)},{dup:246}],428:[function(t,e,r){arguments[4][29][0].apply(r,arguments)},{dup:29}],429:[function(t,e,r){arguments[4][30][0].apply(r,arguments)},{dup:30,\"parse-unit\":428}],430:[function(t,e,r){arguments[4][31][0].apply(r,arguments)},{dup:31,\"to-px\":429}],431:[function(t,e,r){\"use strict\";var n=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{_inline_1_arg1_=_inline_1_arg2_.apply(void 0,_inline_1_arg0_)}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});e.exports=function(t,e){return n(t,e),t}},{\"cwise/lib/wrapper\":319}],432:[function(t,e,r){\"use strict\";function n(t,e){switch(e.length){case 0:break;case 1:t[0]=1/e[0];break;case 4:i(t,e);break;case 9:a(t,e);break;case 16:o(t,e);break;default:throw new Error(\"currently supports matrices up to 4x4\")}return t}e.exports=n;var i=t(\"gl-mat2/invert\"),a=t(\"gl-mat3/invert\"),o=t(\"gl-mat4/invert\")},{\"gl-mat2/invert\":433,\"gl-mat3/invert\":337,\"gl-mat4/invert\":344}],433:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],434:[function(t,e,r){\"use strict\";function n(t,e){var r=Math.floor(e),n=e-r,i=r>=0&&r<t.shape[0],a=r+1>=0&&r+1<t.shape[0],o=i?+t.get(r):0,s=a?+t.get(r+1):0;return(1-n)*o+n*s}function i(t,e,r){var n=Math.floor(e),i=e-n,a=n>=0&&n<t.shape[0],o=n+1>=0&&n+1<t.shape[0],s=Math.floor(r),l=r-s,u=s>=0&&s<t.shape[1],c=s+1>=0&&s+1<t.shape[1],f=a&&u?t.get(n,s):0,h=a&&c?t.get(n,s+1):0,p=o&&u?t.get(n+1,s):0,d=o&&c?t.get(n+1,s+1):0;return(1-l)*((1-i)*f+i*p)+l*((1-i)*h+i*d)}function a(t,e,r,n){var 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c=e[0].label,f=a.slice(),h=f.indexOf(c);-1===h?f.push(c):f.splice(h,1),o.relayout(t,\"hiddenlabels\",f)}else{if(\"\"===l)u=[s.index];else for(var p=0;p<i.length;p++)r=i[p],r.legendgroup===l&&u.push(r.index);n=s.visible===!0?\"legendonly\":!0,o.restyle(t,\"visible\",n,u)}}})}),c.repositionLegend(t,h),t._context.editable){var p,d,g,v,m,y;o.Fx.dragElement({element:l.node(),prepFn:function(){g=Number(l.attr(\"x\")),v=Number(l.attr(\"y\")),m=Number(l.attr(\"width\")),y=Number(l.attr(\"height\")),o.Fx.setCursor(l)},moveFn:function(e,n){var i=t._fullLayout._size;l.call(o.Drawing.setPosition,g+e,v+n),p=o.Fx.dragAlign(g+e,m,i.l,i.l+i.w,r.xanchor),d=o.Fx.dragAlign(v+n+y,-y,i.t+i.h,i.t,r.yanchor);var a=o.Fx.dragCursors(p,d,r.xanchor,r.yanchor);o.Fx.setCursor(l,a)},doneFn:function(e){o.Fx.setCursor(l),e&&void 0!==p&&void 0!==d&&o.relayout(t,{\"legend.x\":p,\"legend.y\":d})}})}}},c.repositionLegend=function(t,e){var r=t._fullLayout,n=r._size,a=r.legend,l=a.borderwidth,u=0,c=0;e.each(function(t){var 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d=\"top\";\"bottom\"===a.yanchor||\"auto\"===a.yanchor&&a.y<=1/3?(h-=c,d=\"bottom\"):(\"middle\"===a.yanchor||\"auto\"===a.yanchor&&a.y<2/3)&&(h-=c/2,d=\"middle\"),u=Math.ceil(u),c=Math.ceil(c),f=Math.round(f),h=Math.round(h),r._infolayer.selectAll(\"svg.legend\").call(o.Drawing.setRect,f,h,u,c),r._infolayer.selectAll(\"svg.legend .bg\").call(o.Drawing.setRect,l/2,l/2,u-l,c-l),o.Plots.autoMargin(t,\"legend\",{x:a.x,y:a.y,l:u*({right:1,center:.5}[p]||0),r:u*({left:1,center:.5}[p]||0),b:c*({top:1,middle:.5}[d]||0),t:c*({bottom:1,middle:.5}[d]||0)})}},{\"../../plotly\":595,\"../../traces/pie/style_one\":729,\"../../traces/scatter/subtypes\":749,\"./attributes\":554,d3:320}],556:[function(t,e,r){\"use strict\";function n(t,e){var r=e.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=t._fullLayout,o={};if(\"zoom\"===n)for(var 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r&&(\"setBackground\"===t&&\"opaque\"===e[t]?r[t]=i:r[t]=e[t])}),e.plot3dPixelRatio&&!r.plotGlPixelRatio&&(r.plotGlPixelRatio=r.plot3dPixelRatio)),r.staticPlot&&(r.editable=!1,r.autosizable=!1,r.scrollZoom=!1,r.doubleClick=!1,r.showTips=!1,r.showLink=!1,r.displayModeBar=!1)}function o(t,e,r){var n=L.select(t).selectAll(\".plot-container\").data([0]);n.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=n.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),P.micropolar.manager.fillLayout(t),\"initial\"===t._fullLayout.autosize&&t._context.autosizable&&(w(t,{}),t._fullLayout.autosize=r.autosize=!0),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=P.micropolar.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var a=t.framework.svg(),o=1,s=t._fullLayout.title;\"\"!==s&&s||(o=0);var l=\"Click to enter title\",u=function(){this.call(P.util.convertToTspans)},c=a.select(\".title-group text\").call(u);if(t._context.editable){c.attr({\"data-unformatted\":s}),s&&s!==l||(o=.2,c.attr({\"data-unformatted\":l}).text(l).style({opacity:o}).on(\"mouseover.opacity\",function(){L.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){L.select(this).transition().duration(1e3).style(\"opacity\",0)}));var f=function(){this.call(P.util.makeEditable).on(\"edit\",function(e){t.framework({layout:{title:e}}),this.attr({\"data-unformatted\":e}).text(e).call(u),this.call(f)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};c.call(f)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),I.addLinks(t),Promise.resolve()}function s(t){var e,r;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1);var n=P.Axes.list({_fullLayout:t});for(e=0;e<n.length;e++){var i=n[e];i.anchor&&\"free\"!==i.anchor&&(i.anchor=P.Axes.cleanId(i.anchor)),i.overlaying&&(i.overlaying=P.Axes.cleanId(i.overlaying)),i.type||(i.isdate?i.type=\"date\":i.islog?i.type=\"log\":i.isdate===!1&&i.islog===!1&&(i.type=\"linear\")),(\"withzero\"===i.autorange||\"tozero\"===i.autorange)&&(i.autorange=!0,i.rangemode=\"tozero\"),delete i.islog,delete i.isdate,delete i.categories,f(i,\"domain\")&&delete i.domain,void 0!==i.autotick&&(void 0===i.tickmode&&(i.tickmode=i.autotick?\"auto\":\"linear\"),delete i.autotick)}void 0===t.annotations||Array.isArray(t.annotations)||(console.log(\"annotations must be an array\"),delete t.annotations);var a=(t.annotations||[]).length;for(e=0;a>e;e++){var o=t.annotations[e];o.ref&&(\"paper\"===o.ref?(o.xref=\"paper\",o.yref=\"paper\"):\"data\"===o.ref&&(o.xref=\"x\",o.yref=\"y\"),delete o.ref),l(o,\"xref\"),l(o,\"yref\")}void 0===t.shapes||Array.isArray(t.shapes)||(console.log(\"shapes must be an array\"),delete t.shapes);var s=(t.shapes||[]).length;for(e=0;s>e;e++){var u=t.shapes[e];l(u,\"xref\"),l(u,\"yref\")}var c=t.legend;c&&(c.x>3?(c.x=1.02,c.xanchor=\"left\"):c.x<-2&&(c.x=-.02,c.xanchor=\"right\"),c.y>3?(c.y=1.02,c.yanchor=\"bottom\"):c.y<-2&&(c.y=-.02,c.yanchor=\"top\")),\"rotate\"===t.dragmode&&(t.dragmode=\"orbit\"),t.scene1&&(t.scene||(t.scene=t.scene1),delete t.scene1);var h,p,d,g,v,m,y,b=I.getSubplotIds(t,\"gl3d\");for(e=0;e<b.length;e++)if(h=t[b[e]],p=h.cameraposition,Array.isArray(p)&&4===p[0].length){for(d=p[0],v=p[1],g=p[2],m=S([],d),y=[],r=0;3>r;++r)y[r]=v[e]+g*m[2+4*r];h.camera={eye:{x:y[0],y:y[1],z:y[2]},center:{x:v[0],y:v[1],z:v[2]},up:{x:m[1],y:m[5],z:m[9]}},delete h.cameraposition}return z.markTime(\"finished rest of cleanLayout, starting color\"),N.clean(t),z.markTime(\"finished cleanLayout color.clean\"),t}function l(t,e){var r=t[e],n=e.charAt(0);r&&\"paper\"!==r&&(t[e]=P.Axes.cleanId(r,n))}function u(t,e){for(var r=[],n=(t.concat(Array.isArray(e)?e:[]).filter(function(t){return\"uid\"in t}).map(function(t){return t.uid})),i=0;i<t.length;i++){var a=t[i];if(!(\"uid\"in a)||-1!==r.indexOf(a.uid)){var o,s;for(s=0;100>s&&(o=z.randstr(n),-1!==r.indexOf(o));s++);a.uid=z.randstr(n),n.push(a.uid)}if(r.push(a.uid),\"histogramy\"===a.type&&\"xbins\"in a&&!(\"ybins\"in a)&&(a.ybins=a.xbins,delete a.xbins),a.error_y&&\"opacity\"in a.error_y){var l=N.defaults,u=a.error_y.color||(I.traceIs(a,\"bar\")?N.defaultLine:l[i%l.length]);a.error_y.color=N.addOpacity(N.rgb(u),N.opacity(u)*a.error_y.opacity),delete a.error_y.opacity}\"bardir\"in a&&(\"h\"!==a.bardir||!I.traceIs(a,\"bar\")&&\"histogram\"!==a.type.substr(0,9)||(a.orientation=\"h\",x(a)),delete a.bardir),\"histogramy\"===a.type&&x(a),(\"histogramx\"===a.type||\"histogramy\"===a.type)&&(a.type=\"histogram\"),\"scl\"in a&&(a.colorscale=a.scl,delete a.scl),\"reversescl\"in a&&(a.reversescale=a.reversescl,delete a.reversescl),a.xaxis&&(a.xaxis=P.Axes.cleanId(a.xaxis,\"x\")),a.yaxis&&(a.yaxis=P.Axes.cleanId(a.yaxis,\"y\")),I.traceIs(a,\"gl3d\")&&a.scene&&(a.scene=I.subplotsRegistry.gl3d.cleanId(a.scene)),I.traceIs(a,\"pie\")||(Array.isArray(a.textposition)?a.textposition=a.textposition.map(c):a.textposition&&(a.textposition=c(a.textposition))),f(a,\"line\")&&delete a.line,\"marker\"in a&&(f(a.marker,\"line\")&&delete a.marker.line,f(a,\"marker\")&&delete a.marker),z.markTime(\"finished rest of cleanData, starting color\"),N.clean(a),z.markTime(\"finished cleanData color.clean\")}}function c(t){var e=\"middle\",r=\"center\";return-1!==t.indexOf(\"top\")?e=\"top\":-1!==t.indexOf(\"bottom\")&&(e=\"bottom\"),-1!==t.indexOf(\"left\")?r=\"left\":-1!==t.indexOf(\"right\")&&(r=\"right\"),e+\" \"+r}function f(t,e){return e in t&&\"object\"==typeof t[e]&&0===Object.keys(t[e]).length}function h(t){var e,r,n,i,a=P.Axes.list(t),o=t._fullData,s=t._fullLayout,l=t.calcdata=new Array(o.length);for(t.firstscatter=!0,t.numboxes=0,t._hmpixcount=0,t._hmlumcount=0,s._piecolormap={},s._piedefaultcolorcount=0,e=0;e<a.length;e++)a[e]._categories=[];for(e=0;e<o.length;e++)r=o[e],n=r._module,i=[],n&&r.visible===!0&&n.calc&&(i=n.calc(t,r)),Array.isArray(i)&&i[0]||(i=[{x:!1,y:!1}]),i[0].t||(i[0].t={}),i[0].trace=r,z.markTime(\"done with calcdata for \"+e),l[e]=i}function p(t,e){var r,n,i=e+1,a=[];for(r=0;r<t.length;r++)n=t[r],0>n?a.push(i+n):a.push(n);return a}function d(t,e,r){var n,i;for(n=0;n<e.length;n++){if(i=e[n],i!==parseInt(i,10))throw new Error(\"all values in \"+r+\" must be integers\");if(i>=t.data.length||i<-t.data.length)throw new Error(r+\" must be valid indices for gd.data.\");if(e.indexOf(i,n+1)>-1||i>=0&&e.indexOf(-t.data.length+i)>-1||0>i&&e.indexOf(t.data.length+i)>-1)throw new Error(\"each index in \"+r+\" must be unique.\")}}function g(t,e,r){if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"currentIndices is a required argument.\");if(Array.isArray(e)||(e=[e]),d(t,e,\"currentIndices\"),\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&d(t,r,\"newIndices\"),\"undefined\"!=typeof r&&e.length!==r.length)throw new Error(\"current and new indices must be of equal length.\")}function v(t,e,r){var n,i;if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"traces must be defined.\");for(Array.isArray(e)||(e=[e]),n=0;n<e.length;n++)if(i=e[n],\"object\"!=typeof i||Array.isArray(i)||null===i)throw new Error(\"all values in traces array must be non-array objects\");if(\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&r.length!==e.length)throw new Error(\"if indices is specified, traces.length must equal indices.length\")}function m(t,e,r,n){var i=z.isPlainObject(n);if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array\");if(!z.isPlainObject(e))throw new Error(\"update must be a key:value object\");if(\"undefined\"==typeof r)throw new Error(\"indices must be an integer or array of integers\");d(t,r,\"indices\");for(var a in e){if(!Array.isArray(e[a])||e[a].length!==r.length)throw new Error(\"attribute \"+a+\" must be an array of length equal to indices array length\");if(i&&(!(a in n)||!Array.isArray(n[a])||n[a].length!==e[a].length))throw new Error(\"when maxPoints is set as a key:value object it must contain a 1:1 corrispondence with the keys and number of traces in the update object\")}}function y(t,e,r,n){var i,a,o,s,l,u=z.isPlainObject(n),c=[];Array.isArray(r)||(r=[r]),r=p(r,t.data.length-1);for(var f in e)for(var h=0;h<r.length;h++){if(i=t.data[r[h]],o=z.nestedProperty(i,f),a=o.get(),s=e[f][h],!Array.isArray(s))throw new Error(\"attribute: \"+f+\" index: \"+h+\" must be an 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i=t.hoverinfo.split(\"+\");for(e=0;e<i.length;e++)\"x\"===i[e]?i[e]=\"y\":\"y\"===i[e]&&(i[e]=\"x\");t.hoverinfo=i.join(\"+\")}}function _(t){var e,r={left:0,right:0,bottom:0,top:0};if(t)for(e in t)t.hasOwnProperty(e)&&(r.left+=t[e].left||0,r.right+=t[e].right||0,r.bottom+=t[e].bottom||0,r.top+=t[e].top||0);return r}function w(t,e){var r,n,i,a=t._fullLayout,o=t._context;if(t.emit(\"plotly_autosize\"),t._context.fillFrame)i=window.innerWidth,n=window.innerHeight,document.body.style.overflow=\"hidden\";else if(C(o.frameMargins)&&o.frameMargins>0){var s=_(t._boundingBoxMargins),l=s.left+s.right,u=s.bottom+s.top,c=a._container.node().getBoundingClientRect(),f=1-2*o.frameMargins;i=Math.round(f*(c.width-l)),n=Math.round(f*(c.height-u))}else r=window.getComputedStyle(t),n=parseFloat(r.height)||a.height,i=parseFloat(r.width)||a.width;return Math.abs(a.width-i)>1||Math.abs(a.height-n)>1?(a.height=t.layout.height=n,a.width=t.layout.width=i):\"initial\"!==a.autosize&&(delete e.autosize,a.autosize=t.layout.autosize=!0),I.sanitizeMargins(a),e}function k(t){var e=L.select(t),r=t._fullLayout;if(r._hasGL3D&&I.subplotsRegistry.gl3d.initAxes(t),r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),\"initial\"===r.autosize&&(w(t,{}),r.autosize=!0,t.layout.autosize=!0),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([0]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._geocontainer=r._paperdiv.selectAll(\".geo-container\").data([0]),r._geocontainer.enter().append(\"div\").classed(\"geo-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var n=[];L.selectAll(\"defs\").each(function(){this.id&&n.push(this.id.split(\"-\")[1]);\n",
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n,i,a=t._fullLayout._plots={},o=0;o<e.length;o++)n=e[o],i=a[n]={},i.id=n,i.x=r(n,\"x\"),i.y=r(n,\"y\"),i.xaxis=i.x(),i.yaxis=i.y()}function M(t,e){function r(t){t.append(\"g\").classed(\"imagelayer\",!0),t.append(\"g\").classed(\"maplayer\",!0),t.append(\"g\").classed(\"barlayer\",!0),t.append(\"g\").classed(\"errorlayer\",!0),t.append(\"g\").classed(\"boxlayer\",!0),t.append(\"g\").classed(\"scatterlayer\",!0)}var n=t._fullLayout,i=[];n._paper.selectAll(\"g.subplot\").data(e).enter().append(\"g\").classed(\"subplot\",!0).each(function(a){var o=n._plots[a],s=o.plotgroup=L.select(this).classed(a,!0),l=o.xaxis,u=o.yaxis;o.overlays=[];var c=P.Axes.getFromId(t,l.overlaying)||l;c!==l&&c.overlaying&&(c=l,l.overlaying=!1);var f=P.Axes.getFromId(t,u.overlaying)||u;f!==u&&f.overlaying&&(f=u,u.overlaying=!1);var h=c._id+f._id;h!==a&&-1!==e.indexOf(h)?(o.mainplot=h,i.push(o),l.domain=c.domain.slice(),u.domain=f.domain.slice()):(o.bg=s.append(\"rect\").style(\"stroke-width\",0),o.gridlayer=s.append(\"g\"),o.overgrid=s.append(\"g\"),o.zerolinelayer=s.append(\"g\"),o.overzero=s.append(\"g\"),o.plot=s.append(\"svg\").call(r),o.overplot=s.append(\"g\"),o.xlines=s.append(\"path\"),o.ylines=s.append(\"path\"),o.overlines=s.append(\"g\"),o.xaxislayer=s.append(\"g\"),o.yaxislayer=s.append(\"g\"),o.overaxes=s.append(\"g\")),o.draglayer=n._draggers.append(\"g\")}),i.forEach(function(t){var e=n._plots[t.mainplot];e.overlays.push(t),t.gridlayer=e.overgrid.append(\"g\"),t.zerolinelayer=e.overzero.append(\"g\"),t.plot=e.overplot.append(\"svg\").call(r),t.xlines=e.overlines.append(\"path\"),t.ylines=e.overlines.append(\"path\"),t.xaxislayer=e.overaxes.append(\"g\"),t.yaxislayer=e.overaxes.append(\"g\")}),e.forEach(function(t){var 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s=t.trace.hoverinfo;return\"all\"!==s&&(s=s.split(\"+\"),-1===s.indexOf(\"x\")&&(t.xLabel=void 0),-1===s.indexOf(\"y\")&&(t.yLabel=void 0),-1===s.indexOf(\"z\")&&(t.zLabel=void 0),-1===s.indexOf(\"text\")&&(t.text=void 0),-1===s.indexOf(\"name\")&&(t.name=void 0)),t}function l(t,e){var r,n,i=e.hovermode,a=e.rotateLabels,o=e.bgColor,s=e.container,l=e.outerContainer,u=t[0],c=u.xa,f=u.ya,h=\"y\"===i?\"yLabel\":\"xLabel\",p=u[h],d=(String(p)||\"\").split(\" \")[0],g=l.node().getBoundingClientRect(),v=g.top,m=g.width,y=g.height,b=u.distance<=T.MAXDIST&&(\"x\"===i||\"y\"===i);for(r=0;r<t.length;r++){n=t[r].trace.hoverinfo;var w=n.split(\"+\");if(-1===w.indexOf(\"all\")&&-1===w.indexOf(i)){b=!1;break}}var A=s.selectAll(\"g.axistext\").data(b?[0]:[]);A.enter().append(\"g\").classed(\"axistext\",!0),A.exit().remove(),A.each(function(){var e=x.select(this),r=e.selectAll(\"path\").data([0]),n=e.selectAll(\"text\").data([0]);r.enter().append(\"path\").style({fill:k.Color.defaultLine,\"stroke-width\":\"1px\",stroke:k.Color.background}),n.enter().append(\"text\").call(k.Drawing.font,j,I,k.Color.background).attr(\"data-notex\",1),n.text(p).call(k.util.convertToTspans).call(k.Drawing.setPosition,0,0).selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),e.attr(\"transform\",\"\");var a=n.node().getBoundingClientRect();if(\"x\"===i){n.attr(\"text-anchor\",\"middle\").call(k.Drawing.setPosition,0,\"top\"===c.side?v-a.bottom-R-O:v-a.top+R+O).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var o=\"top\"===c.side?\"-\":\"\";r.attr(\"d\",\"M0,0L\"+R+\",\"+o+R+\"H\"+(O+a.width/2)+\"v\"+o+(2*O+a.height)+\"H-\"+(O+a.width/2)+\"V\"+o+R+\"H-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(u.x0+u.x1)/2)+\",\"+(f._offset+(\"top\"===c.side?0:f._length))+\")\")}else{n.attr(\"text-anchor\",\"right\"===f.side?\"start\":\"end\").call(k.Drawing.setPosition,(\"right\"===f.side?1:-1)*(O+R),v-a.top-a.height/2).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var s=\"right\"===f.side?\"\":\"-\";r.attr(\"d\",\"M0,0L\"+s+R+\",\"+R+\"V\"+(O+a.height/2)+\"h\"+s+(2*O+a.width)+\"V-\"+(O+a.height/2)+\"H\"+s+R+\"V-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(\"right\"===f.side?c._length:0))+\",\"+(f._offset+(u.y0+u.y1)/2)+\")\")}t=t.filter(function(t){return void 0!==t.zLabelVal||(t[h]||\"\").split(\" \")[0]===d})});var M=s.selectAll(\"g.hovertext\").data(t,function(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr||\"\"].join(\",\")});return M.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var t=x.select(this);t.append(\"rect\").call(k.Color.fill,k.Color.addOpacity(o,.8)),t.append(\"text\").classed(\"name\",!0).call(k.Drawing.font,j,I),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(k.Drawing.font,j,I)}),M.exit().remove(),M.each(function(t){var e=x.select(this).attr(\"transform\",\"\"),r=\"\",n=\"\",s=k.Color.opacity(t.color)?t.color:k.Color.defaultLine,l=k.Color.combine(s,o),u=_(l).getBrightness()>128?\"#000\":k.Color.background;if(t.name&&void 0===t.zLabelVal){\n",
+       "var h=document.createElement(\"p\");h.innerHTML=t.name,r=h.textContent||\"\",r.length>15&&(r=r.substr(0,12)+\"...\")}void 0!==t.zLabel?(void 0!==t.xLabel&&(n+=\"x: \"+t.xLabel+\"<br>\"),void 0!==t.yLabel&&(n+=\"y: \"+t.yLabel+\"<br>\"),n+=(n?\"z: \":\"\")+t.zLabel):b&&t[i+\"Label\"]===p?n=t[(\"x\"===i?\"y\":\"x\")+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&(n=t.yLabel):n=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",t.text&&(n+=(n?\"<br>\":\"\")+t.text),\"\"===n&&(\"\"===r&&e.remove(),n=r);var d=e.select(\"text.nums\").style(\"fill\",u).call(k.Drawing.setPosition,0,0).text(n).attr(\"data-notex\",1).call(k.util.convertToTspans);d.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0);var g=e.select(\"text.name\"),w=0;r&&r!==n?(g.style(\"fill\",l).text(r).call(k.Drawing.setPosition,0,0).attr(\"data-notex\",1).call(k.util.convertToTspans),g.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),w=g.node().getBoundingClientRect().width+2*O):(g.remove(),e.select(\"rect\").remove()),e.select(\"path\").style({fill:l,stroke:u});var A,M,T=d.node().getBoundingClientRect(),E=c._offset+(t.x0+t.x1)/2,S=f._offset+(t.y0+t.y1)/2,C=Math.abs(t.x1-t.x0),P=Math.abs(t.y1-t.y0),z=T.width+R+O+w;t.ty0=v-T.top,t.bx=T.width+2*O,t.by=T.height+2*O,t.anchor=\"start\",t.txwidth=T.width,t.tx2width=w,t.offset=0,a?(t.pos=E,A=y>=S+P/2+z,M=S-P/2-z>=0,\"top\"!==t.idealAlign&&A||!M?A?(S+=P/2,t.anchor=\"start\"):t.anchor=\"middle\":(S-=P/2,t.anchor=\"end\")):(t.pos=S,A=m>=E+C/2+z,M=E-C/2-z>=0,\"left\"!==t.idealAlign&&A||!M?A?(E+=C/2,t.anchor=\"start\"):t.anchor=\"middle\":(E-=C/2,t.anchor=\"end\")),d.attr(\"text-anchor\",t.anchor),w&&g.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",\"translate(\"+E+\",\"+S+\")\"+(a?\"rotate(\"+L+\")\":\"\"))}),M}function u(t,e){function r(t){var e=t[0],r=t[t.length-1];if(i=f-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-h,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(.01>a)){if(-.01>i){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var u=0;for(o=0;o<t.length;o++)l=t[o],l.pos+l.dp+l.size>h&&u++;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos>h-1&&(l.del=!0,u--);for(o=0;o<t.length&&!(0>=u);o++)if(l=t[o],l.pos<f+1)for(l.del=!0,u--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos+l.dp+l.size>h&&(l.del=!0,u--)}}}for(var n,i,a,o,s,l,u,c=0,f=e._offset,h=e._offset+e._length,p=t.map(function(t,r){return[{i:r,dp:0,pos:t.pos,posref:t.posref,size:t.by*(\"x\"===e._id.charAt(0)?C:1)/2}]}).sort(function(t,e){return t[0].posref-e[0].posref});!n&&c<=t.length;){for(c++,n=!0,o=0;o<p.length-1;){var d=p[o],g=p[o+1],v=d[d.length-1],m=g[0];if(i=v.pos+v.dp+v.size-m.pos-m.dp+m.size,i>.01){for(s=g.length-1;s>=0;s--)g[s].dp+=i;for(d.push.apply(d,g),p.splice(o+1,1),u=0,s=d.length-1;s>=0;s--)u+=d[s].dp;for(a=u/d.length,s=d.length-1;s>=0;s--)d[s].dp-=a;n=!1}else o++}p.forEach(r)}for(o=p.length-1;o>=0;o--){var y=p[o];for(s=y.length-1;s>=0;s--){var b=y[s],x=t[b.i];x.offset=b.dp,x.del=b.del}}}function 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r=Math.max(0,Math.min(D,t+K)),n=Math.max(0,Math.min(B,e+Q)),i=Math.abs(r-K),a=Math.abs(n-Q),o=Math.floor(Math.min(a,i,V)/2);J.l=Math.min(K,r),J.r=Math.max(K,r),J.t=Math.min(Q,n),J.b=Math.max(Q,n),!G||a<Math.min(Math.max(.6*i,U),V)?U>i?(nt=\"\",J.r=J.l,J.t=J.b,at.attr(\"d\",\"M0,0Z\")):(J.t=0,J.b=B,nt=\"x\",at.attr(\"d\",\"M\"+(J.l-.5)+\",\"+(Q-V-.5)+\"h-3v\"+(2*V+1)+\"h3ZM\"+(J.r+.5)+\",\"+(Q-V-.5)+\"h3v\"+(2*V+1)+\"h-3Z\")):!H||i<Math.min(.6*a,V)?(J.l=0,J.r=D,nt=\"y\",at.attr(\"d\",\"M\"+(K-V-.5)+\",\"+(J.t-.5)+\"v-3h\"+(2*V+1)+\"v3ZM\"+(K-V-.5)+\",\"+(J.b+.5)+\"v3h\"+(2*V+1)+\"v-3Z\")):(nt=\"xy\",at.attr(\"d\",\"M\"+(J.l-3.5)+\",\"+(J.t-.5+o)+\"h3v\"+-o+\"h\"+o+\"v-3h-\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.t-.5+o)+\"h-3v\"+-o+\"h\"+-o+\"v-3h\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.b+.5-o)+\"h-3v\"+o+\"h\"+-o+\"v3h\"+(o+3)+\"ZM\"+(J.l-3.5)+\",\"+(J.b+.5-o)+\"h3v\"+o+\"h\"+o+\"v3h-\"+(o+3)+\"Z\")),J.w=J.r-J.l,J.h=J.b-J.t,it.attr(\"d\",et+\"M\"+J.l+\",\"+J.t+\"v\"+J.h+\"h\"+J.w+\"v-\"+J.h+\"h-\"+J.w+\"Z\"),rt||(it.transition().style(\"fill\",tt>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),at.transition().style(\"opacity\",1).duration(200),rt=!0)}function 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r=0,n=0,i=t.length;i>n;++n)r+=t[n]*e[n];return r}function b(t,e){return[t[1]*e[2]-t[2]*e[1],t[2]*e[0]-t[0]*e[2],t[0]*e[1]-t[1]*e[0]]}function x(t){for(var e=0,r=arguments.length,n=[];++e<r;)n.push(arguments[e]);var i=_.dispatch.apply(null,n);return i.of=function(e,r){return function(n){var a;try{a=n.sourceEvent=_.event,n.target=t,_.event=n,i[n.type].apply(e,r)}finally{_.event=a}}},i}var _=t(\"d3\"),w=Math.PI/180,k=180/Math.PI,A={cursor:\"pointer\"},M={cursor:\"auto\"};e.exports=n},{d3:320}],623:[function(t,e,r){\"use strict\";function n(t,e){var r=t.projection,n=t.zoom,a=function(){t.makeProjection(e),t.makePath(),n.scale(r.scale()),n.translate(r.translate()),i.loneUnhover(t.hoverContainer),t.render()};return a}var i=t(\"../cartesian/graph_interact\");e.exports=n},{\"../cartesian/graph_interact\":603}],624:[function(t,e,r){\"use strict\";function n(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxStart=[0,0],this.boxEnd=[0,0]}function i(t){var e=t.mouseContainer,r=t.glplot,i=new n(e,r);return i.mouseListener=a(e,function(e,n,a){function o(e,r,n){var a=Math.min(r,n),o=Math.max(r,n);a!==o?(e[0]=a,e[1]=o,i.dataBox=e):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}var s=t.xaxis.range,l=t.yaxis.range,u=r.viewBox,c=i.lastPos[0],f=i.lastPos[1];switch(n*=r.pixelRatio,a*=r.pixelRatio,a=u[3]-u[1]-a,t.fullLayout.dragmode){case\"zoom\":if(e){var h=n/(u[2]-u[0])*(s[1]-s[0])+s[0],p=a/(u[3]-u[1])*(l[1]-l[0])+l[0];i.boxEnabled||(i.boxStart[0]=h,i.boxStart[1]=p),i.boxEnd[0]=h,i.boxEnd[1]=p,i.boxEnabled=!0}else i.boxEnabled&&(o(s,i.boxStart[0],i.boxEnd[0]),o(l,i.boxStart[1],i.boxEnd[1]),i.boxEnabled=!1);break;case\"pan\":if(i.boxEnabled=!1,e){var d=(c-n)*(s[1]-s[0])/(r.viewBox[2]-r.viewBox[0]),g=(f-a)*(l[1]-l[0])/(r.viewBox[3]-r.viewBox[1]);s[0]+=d,s[1]+=d,l[0]+=g,l[1]+=g,i.lastInputTime=Date.now(),t.cameraChanged()}}i.lastPos[0]=n,i.lastPos[1]=a}),i.wheelListener=o(e,function(e,n){var a=t.xaxis.range,o=t.yaxis.range,s=r.viewBox,l=i.lastPos[0],u=i.lastPos[1];switch(t.fullLayout.dragmode){case\"zoom\":break;case\"pan\":var c=Math.exp(.1*n/(s[3]-s[1])),f=l/(s[2]-s[0])*(a[1]-a[0])+a[0],h=u/(s[3]-s[1])*(o[1]-o[0])+o[0];a[0]=(a[0]-f)*c+f,a[1]=(a[1]-f)*c+f,o[0]=(o[0]-h)*c+h,o[1]=(o[1]-h)*c+h,i.lastInputTime=Date.now(),t.cameraChanged()}return!0}),i}var a=t(\"mouse-change\"),o=t(\"mouse-wheel\");e.exports=i},{\"mouse-change\":426,\"mouse-wheel\":430}],625:[function(t,e,r){\"use strict\";function 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e=this.scene,r=a.Plots.getSubplotIds(e.fullLayout,\"gl2d\"),n=a.Axes.findSubplotsWithAxis(r,t);return 0!==n.indexOf(e.id)},l.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},l.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},l.getLabelPad=function(t,e){var r=1.5,n=e.titlefont.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?-10+n*(r+(i?1:0)):-10+n*(r+(i?.5:0)):\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},l.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},l.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":577,\"../../lib/str2rgbarray\":588,\"../../plotly\":595}],626:[function(t,e,r){\"use strict\";var 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n(t,e){this.container=t.container,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.updateAxes(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=d(this),this.traces={},this.spikes=f(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;2>r;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/plots\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),f=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),p=t(\"./convert\"),d=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),m=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o){a=document.createElement(\"canvas\");try{o=a.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0})}catch(t){throw new Error([\"Error creating static canvas/context for image server\"].join(\" \"))}}this.canvas=a,this.gl=o}else{var e,r=document.createElement(\"canvas\"),n={premultipliedAlpha:!0};try{e=r.getContext(\"webgl\",n)}catch(t){}if(!e)try{e=r.getContext(\"experimental-webgl\",n)}catch(t){}e||v(this),this.canvas=r,this.gl=e}var i=this.canvas,s=this.pixelRatio,l=this.fullLayout;i.width=0|Math.ceil(s*l.width),i.height=0|Math.ceil(s*l.height),i.style.width=\"100%\",i.style.height=\"100%\",i.style.position=\"absolute\",i.style.top=\"0px\",i.style.left=\"0px\",i.style[\"pointer-events\"]=\"none\";var u=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");u.style.position=\"absolute\",u.style.top=u.style.left=\"0px\",u.style.width=u.style.height=\"100%\",u.style[\"z-index\"]=20,u.style[\"pointer-events\"]=\"none\";var c=this.mouseContainer=document.createElement(\"div\");c.style.position=\"absolute\";var f=this.container;f.appendChild(i),f.appendChild(u),f.appendChild(c)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.glplot.setDirty(!0),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new 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o=e.width,u=e.height,c=0|Math.ceil(a*o),f=0|Math.ceil(a*u),h=this.canvas;(h.width!==c||h.height!==f)&&(h.width=c,h.height=f),t?Array.isArray(t)||(t=[t]):t=[];var p,d;for(r=0;r<t.length;++r){if(p=t[r],d=this.traces[p.uid])d.update(p);else{var g=s.getModule(p.type);d=g.plot(this,p)}this.traces[p.uid]=d}var v=Object.keys(this.traces);t:for(r=0;r<v.length;++r){for(n=0;n<t.length;++n)if(t[n].uid===v[r])continue t;d=this.traces[v[r]],d.dispose(),delete this.traces[v[r]]}var y=this.glplotOptions;y.merge(e),y.screenBox=[0,0,o,u];var b=e._size,x=this.xaxis.domain,_=this.yaxis.domain;y.viewBox=[b.l+x[0]*b.w,b.b+_[0]*b.h,o-b.r-(1-x[1])*b.w,u-b.t-(1-_[1])*b.h],this.mouseContainer.style.width=b.w*(x[1]-x[0])+\"px\",this.mouseContainer.style.height=b.h*(_[1]-_[0])+\"px\",this.mouseContainer.height=b.h*(_[1]-_[0]),this.mouseContainer.style.left=b.l+x[0]*b.w+\"px\",this.mouseContainer.style.top=b.t+(1-_[1])*b.h+\"px\";var 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o=n._size,s=this.xaxis.domain,l=this.yaxis.domain,c=t.pick(i/t.pixelRatio+o.l+s[0]*o.w,a/t.pixelRatio-(o.t+(1-l[1])*o.h));if(c&&n.hovermode){var f=c.object._trace.handlePick(c);if(f&&(!this.lastPickResult||this.lastPickResult.trace!==f.trace||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var h=this.lastPickResult=f;this.spikes.update({center:c.dataCoord}),h.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(c.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(c.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio];var p=h.hoverinfo;if(\"all\"!==p){var d=p.split(\"+\");-1===d.indexOf(\"x\")&&(h.traceCoord[0]=void 0),-1===d.indexOf(\"y\")&&(h.traceCoord[1]=void 0),-1===d.indexOf(\"text\")&&(h.textLabel=void 0),-1===d.indexOf(\"name\")&&(h.name=void 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i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":288,\"mouse-change\":426,\"mouse-wheel\":430,\"right-now\":440}],629:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"gl3d\",s),u=e[s]._scene;void 0===u&&(u=new n({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),e[s]._scene=u),u.plot(l,e,t.layout)}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\"),r.initAxes=function(t){var e=t._fullLayout;delete e.xaxis,delete e.yaxis;for(var r=i.getSubplotIds(e,\"gl3d\"),n=0;n<r.length;++n)for(var o=r[n],s=e[o],l=0;3>l;++l){var u=a[l],c=s[u];c._td=t}}},{\"../plots\":642,\"./layout/attributes\":630,\"./layout/defaults\":634,\"./layout/layout_attributes\":635,\"./scene\":639,\"./set_convert\":640}],630:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"sceneid\",dflt:\"scene\"}}},{}],631:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:\"rgb(0,0,0)\"},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},title:n.title,titlefont:n.titlefont,type:n.type,autorange:n.autorange,rangemode:n.rangemode,range:n.range,fixedrange:n.fixedrange,tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,mirror:n.mirror,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:n.tickfont,tickangle:n.tickangle,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:n.showline,linecolor:n.linecolor,linewidth:n.linewidth,showgrid:n.showgrid,gridcolor:i({},n.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:n.gridwidth,zeroline:n.zeroline,zerolinecolor:n.zerolinecolor,zerolinewidth:n.zerolinewidth}},{\"../../../lib/extend\":574,\"../../cartesian/layout_attributes\":605}],632:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"./axis_attributes\"),a=t(\"../../cartesian/axis_defaults\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=function(){};e.exports=function(t,e,r){function l(t,e){return n.coerce(u,c,i,t,e)}for(var u,c,f=0;f<o.length;f++){var h=o[f];u=t[h]||{},c={_id:h[0]+r.scene,_name:h},e[h]=c=a(u,c,l,{font:r.font,letter:h[0],data:r.data,showGrid:!0}),l(\"gridcolor\"),l(\"title\",h[0]),c.setScale=s,l(\"showspikes\")&&(l(\"spikesides\"),l(\"spikethickness\"),l(\"spikecolor\")),l(\"showbackground\")&&l(\"backgroundcolor\"),l(\"showaxeslabels\")}}},{\"../../../lib\":578,\"../../cartesian/axis_defaults\":599,\"./axis_attributes\":631}],633:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=l(this.tickPad),this._defaultLabelPad=l(this.labelPad),this._defaultLineTickLength=l(this.lineTickLength)}function i(t){var e=new n;return e.merge(t),e}var a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;3>r;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":577,\"../../../lib/str2rgbarray\":588,arraytools:298}],634:[function(t,e,r){\"use strict\";var n=t(\"../../../plotly\"),i=t(\"./layout_attributes\"),a=t(\"./axis_defaults\");e.exports=function(t,e,r){function o(t,e){return n.Lib.coerce(u,c,i,t,e)}if(e._hasGL3D){var s,l=n.Plots.getSubplotIdsInData(r,\"gl3d\");delete e.xaxis,delete e.yaxis;var u,c,f=l.length;for(s=0;f>s;++s){var h=l[s];void 0!==t[h]?u=t[h]:t[h]=u={},c=e[h]||{},o(\"bgcolor\");for(var p=Object.keys(i.camera),d=0;d<p.length;d++)o(\"camera.\"+p[d]+\".x\"),o(\"camera.\"+p[d]+\".y\"),o(\"camera.\"+p[d]+\".z\");o(\"domain.x\",[s/f,(s+1)/f]),o(\"domain.y\");var g=!!o(\"aspectratio.x\")&&!!o(\"aspectratio.y\")&&!!o(\"aspectratio.z\"),v=g?\"manual\":\"auto\",m=o(\"aspectmode\",v);g||(u.aspectratio=c.aspectratio={x:1,y:1,z:1},\"manual\"===m&&(c.aspectmode=\"auto\")),a(u,c,{font:e.font,scene:h,data:r}),e[h]=c}}}},{\"../../../plotly\":595,\"./axis_defaults\":632,\"./layout_attributes\":635}],635:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":574,\"./axis_attributes\":631}],636:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;3>e;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":588}],637:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;3>r;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,u=[[],[],[]],c=0;3>c;++c){var f=i[s[c]];if(f._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(f._length)===1/0)u[c]=[];else{f.range[0]=r[c].lo/t.dataScale[c],f.range[1]=r[c].hi/t.dataScale[c],f._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var h=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var 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i=t(\"../plotly\"),a=t(\"d3\"),o=t(\"../constants/xmlns_namespaces\");e.exports=function(t,e){var r,s,l=t._fullLayout,u=l._paper,c=l._size;u.insert(\"rect\",\":first-child\").call(i.Drawing.setRect,0,0,l.width,l.height).call(i.Color.fill,l.paper_bgcolor);var f,h=i.Plots.getSubplotIds(l,\"gl3d\");for(s=0;s<h.length;s++)f=l[h[s]],r=f.domain,n(l,f._scene,{x:c.l+c.w*r.x[0],y:c.t+c.h*(1-r.y[1]),width:c.w*(r.x[1]-r.x[0]),height:c.h*(r.y[1]-r.y[0])});var p,d=i.Plots.getSubplotIds(l,\"gl2d\");for(s=0;s<d.length;s++)p=l._plots[d[s]],n(l,p._scene2d,{x:c.l,y:c.t,width:c.w,height:c.h});var g,v,m=i.Plots.getSubplotIds(l,\"geo\");for(s=0;s<m.length;s++)g=l[m[s]],r=g.domain,v=g._geo.framework,v.attr(\"style\",null),v.attr({x:c.l+c.w*r.x[0]+g._marginX,y:c.t+c.h*(1-r.y[1])+g._marginY,width:g._width,height:g._height}),l._geoimages.node().appendChild(v.node());if(l._toppaper){var 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.supplyLayoutDefaults=t(\"./layout_defaults\"),n.layoutAttributes=t(\"./layout_attributes\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.style=t(\"./style\"),n.styleOne=t(\"./style_one\"),n.moduleType=\"trace\",n.name=\"pie\",n.basePlotModule=t(\"../../plots/cartesian\"),n.categories=[\"pie\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/cartesian\":604,\"./attributes\":720,\"./calc\":721,\"./defaults\":722,\"./layout_attributes\":725,\"./layout_defaults\":726,\"./plot\":727,\"./style\":728,\"./style_one\":729}],725:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\"}}},{}],726:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\")}},{\"../../lib\":578,\"./layout_attributes\":725}],727:[function(t,e,r){\"use strict\";function n(t,e,r){var n=Math.sqrt(t.width*t.width+t.height*t.height),a=t.width/t.height,o=Math.PI*Math.min(e.v/r.vTotal,.5),s=1-r.trace.hole,l=i(e,r),u={scale:l*r.r*2/n,rCenter:1-l,rotate:0};if(u.scale>=1)return u;var c=a+1/(2*Math.tan(o)),f=r.r*Math.min(1/(Math.sqrt(c*c+.5)+c),s/(Math.sqrt(a*a+s/2)+a)),h={scale:2*f/t.height,rCenter:Math.cos(f/r.r)-f*a/r.r,rotate:(180/Math.PI*e.midangle+720)%180-90},p=1/a,d=p+1/(2*Math.tan(o)),g=r.r*Math.min(1/(Math.sqrt(d*d+.5)+d),s/(Math.sqrt(p*p+s/2)+p)),v={scale:2*g/t.width,rCenter:Math.cos(g/r.r)-g/a/r.r,rotate:(180/Math.PI*e.midangle+810)%180-90},m=v.scale>h.scale?v:h;return u.scale<1&&m.scale>u.scale?m:u}function i(t,e){if(t.v===e.vTotal&&!e.trace.hole)return 1;var r=Math.PI*Math.min(t.v/e.vTotal,.5);return Math.min(1/(1+1/Math.sin(r)),(1-e.trace.hole)/2)}function a(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return 0>r&&(i*=-1),0>n&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function o(t,e){function 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r,n,i,a,o,s,l,u,c,f=t[0],h=f.trace,p=h.tilt,d=h.rotation*Math.PI/180,g=2*Math.PI/f.vTotal,v=\"px0\",m=\"px1\";if(\"counterclockwise\"===h.direction){for(l=0;l<t.length&&t[l].hidden;l++);if(l===t.length)return;d+=g*t[l].v,g*=-1,v=\"px1\",m=\"px0\"}for(p&&(a=p*Math.PI/180,r=h.tiltaxis*Math.PI/180,o=Math.sin(r)*Math.cos(r),s=1-Math.cos(a),n=Math.sin(r),i=Math.cos(r)),c=e(d),l=0;l<t.length;l++)u=t[l],u.hidden||(u[v]=c,d+=g*u.v/2,u.pxmid=e(d),u.midangle=d,d+=g*u.v/2,c=e(d),u[m]=c,u.largeArc=u.v>f.vTotal/2?1:0)}function u(t,e,r){if(!t)return 1;var n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var c=t(\"d3\"),f=t(\"../../plots/cartesian/graph_interact\"),h=t(\"../../components/color\"),p=t(\"../../components/drawing\"),d=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;s(e,r._size);var 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s=i(o,u),l=k+o.pxmid[0]*(1-s),c=A+o.pxmid[1]*(1-s),h=[];-1!==a.indexOf(\"label\")&&h.push(o.label),n.text&&n.text[o.i]&&-1!==a.indexOf(\"text\")&&h.push(n.text[o.i]),-1!==a.indexOf(\"value\")&&h.push(g.formatPieValue(o.v)),-1!==a.indexOf(\"percent\")&&h.push(g.formatPiePercent(o.v/u.vTotal)),f.loneHover({x0:l-s*u.r,x1:l+s*u.r,y:c,text:h.join(\"<br>\"),name:-1!==a.indexOf(\"name\")?n.name:void 0,color:o.color,idealAlign:o.pxmid[0]<0?\"left\":\"right\"},{container:r._hoverlayer.node(),outerContainer:r._paper.node()}),f.hover(t,e,\"pie\"),E=!0}}function h(){E&&(f.loneUnhover(r._hoverlayer.node()),E=!1)}function y(){t._hoverdata=[o],t._hoverdata.trace=e.trace,f.click(t,{target:!0})}function x(t,e,r,n){return\"a\"+n*u.r+\",\"+n*w+\" \"+b+\" \"+o.largeArc+(r?\" 1 \":\" 0 \")+n*(e[0]-t[0])+\",\"+n*(e[1]-t[1])}if(o.hidden)return void c.select(this).selectAll(\"path,g\").remove();l[o.pxmid[1]<0?0:1][o.pxmid[0]<0?0:1].push(o);var k=u.cx+_[0],A=u.cy+_[1],M=c.select(this),T=M.selectAll(\"path.surface\").data([o]),E=!1;if(T.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),M.select(\"path.textline\").remove(),M.on(\"mouseover\",s).on(\"mouseout\",h).on(\"click\",y),v.pull){var L=+(Array.isArray(v.pull)?v.pull[o.i]:v.pull)||0;L>0&&(k+=L*o.pxmid[0],A+=L*o.pxmid[1])}o.cxFinal=k,o.cyFinal=A;var S=v.hole;if(o.v===u.vTotal){var C=\"M\"+(k+o.px0[0])+\",\"+(A+o.px0[1])+x(o.px0,o.pxmid,!0,1)+x(o.pxmid,o.px0,!0,1)+\"Z\";S?T.attr(\"d\",\"M\"+(k+S*o.px0[0])+\",\"+(A+S*o.px0[1])+x(o.px0,o.pxmid,!1,S)+x(o.pxmid,o.px0,!1,S)+\"Z\"+C):T.attr(\"d\",C)}else{var P=x(o.px0,o.px1,!0,1);if(S){var z=1-S;T.attr(\"d\",\"M\"+(k+S*o.px1[0])+\",\"+(A+S*o.px1[1])+x(o.px1,o.px0,!1,S)+\"l\"+z*o.px0[0]+\",\"+z*o.px0[1]+P+\"Z\")}else T.attr(\"d\",\"M\"+k+\",\"+A+\"l\"+o.px0[0]+\",\"+o.px0[1]+P+\"Z\")}var R=Array.isArray(v.textposition)?v.textposition[o.i]:v.textposition,O=M.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==R?[0]:[]);O.enter().append(\"g\").classed(\"slicetext\",!0),O.exit().remove(),O.each(function(){var t=c.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(o.text).attr({\"class\":\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(p.font,\"outside\"===R?v.outsidetextfont:v.insidetextfont).call(d.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var e,r=p.bBox(t.node());\"outside\"===R?e=a(r,o):(e=n(r,o,u),\"auto\"===R&&e.scale<1&&(t.call(p.font,v.outsidetextfont),(v.outsidetextfont.family!==v.insidetextfont.family||v.outsidetextfont.size!==v.insidetextfont.size)&&(t.attr({\"data-bb\":\"\"}),r=p.bBox(t.node())),e=a(r,o)));var i=k+o.pxmid[0]*e.rCenter+(e.x||0),s=A+o.pxmid[1]*e.rCenter+(e.y||0);e.outside&&(o.yLabelMin=s-r.height/2,o.yLabelMid=s,o.yLabelMax=s+r.height/2,o.labelExtraX=0,o.labelExtraY=0,m=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+s+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+(e.rotate?\"rotate(\"+e.rotate+\")\":\"\")+\"translate(\"+-(r.left+r.right)/2+\",\"+-(r.top+r.bottom)/2+\")\")})}),m&&o(l,v),s.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=c.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],i=t.cyFinal+t.pxmid[1],a=\"M\"+n+\",\"+i,o=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var s=t.labelExtraX*t.pxmid[1]/t.pxmid[0],l=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);a+=Math.abs(s)>Math.abs(l)?\"l\"+l*t.pxmid[0]/t.pxmid[1]+\",\"+l+\"H\"+(n+t.labelExtraX+o):\"l\"+t.labelExtraX+\",\"+s+\"v\"+(l-s)+\"h\"+o}else a+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+o;e.append(\"path\").classed(\"textline\",!0).call(h.stroke,v.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,v.outsidetextfont.size/8),d:a,fill:\"none\"})}})})}),setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=c.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)}},{\"../../components/color\":529,\"../../components/drawing\":547,\"../../lib/svg_text_utils\":589,\"../../plots/cartesian/graph_interact\":603,\"./helpers\":723,d3:320}],728:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0],r=e.trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\".top path.surface\").each(function(t){n.select(this).call(i,t,r)})})}},{\"./style_one\":729,d3:320}],729:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r){var i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a,fill:e.color}).call(n.stroke,i)}},{\"../../components/color\":529}],730:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t){var e=t[0].trace,r=e.marker;if(n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.textposition,t,\"tp\"),e.textfont&&(n.mergeArray(e.textfont.size,t,\"ts\"),n.mergeArray(e.textfont.color,t,\"tc\"),n.mergeArray(e.textfont.family,t,\"tf\")),r&&r.line){var i=r.line;n.mergeArray(r.opacity,t,\"mo\"),n.mergeArray(r.symbol,t,\"mx\"),n.mergeArray(r.color,t,\"mc\"),n.mergeArray(i.color,t,\"mlc\"),n.mergeArray(i.width,t,\"mlw\")}}},{\"../../lib\":578}],731:[function(t,e,r){\"use strict\";var n=t(\"../../components/drawing\");t(\"./constants\");e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},dy:{valType:\"number\",dflt:1},text:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",\n",
+       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i=t(\"../scatter/attributes\"),a=t(\"../../constants/gl_markers\"),o=t(\"../../lib/extend\").extendFlat,s=i.line,l=i.marker,u=l.line;e.exports={x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},text:o({},i.text,{}),mode:o({},i.mode,{dflt:\"lines+markers\"}),surfaceaxis:{valType:\"enumerated\",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:\"color\"},projection:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},line:{color:s.color,width:s.width,dash:s.dash},marker:{color:l.color,symbol:{valType:\"enumerated\",values:Object.keys(a),dflt:\"circle\",arrayOk:!0},size:o({},l.size,{dflt:8}),sizeref:l.sizeref,sizemin:l.sizemin,sizemode:l.sizemode,opacity:o({},l.opacity,{arrayOk:!1}),colorscale:l.colorscale,cauto:l.cauto,cmax:l.cmax,cmin:l.cmin,autocolorscale:l.autocolorscale,reversescale:l.reversescale,showscale:l.showscale,line:{color:u.color,width:o({},u.width,{arrayOk:!1}),colorscale:u.colorscale,cauto:u.cauto,cmax:u.cmax,cmin:u.cmin,autocolorscale:u.autocolorscale,reversescale:u.reversescale}},textposition:o({},i.textposition,{dflt:\"top 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e,r,n,a,o=this.scene.glplot.gl,s=w.solid;this.data=t;var l=c(this.scene,t);\"mode\"in l&&(this.mode=l.mode),\"lineDashes\"in l&&l.lineDashes in w&&(s=w[l.lineDashes]),this.color=f(l.scatterColor)||f(l.lineColor),this.dataPoints=l.position,e={gl:o,position:l.position,color:l.lineColor,lineWidth:l.lineWidth||1,dashes:s[0],dashScale:s[1],opacity:t.opacity},-1!==this.mode.indexOf(\"lines\")?this.linePlot?this.linePlot.update(e):(this.linePlot=p(e),this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var u=t.opacity;if(t.marker&&t.marker.opacity&&(u*=t.marker.opacity),r={gl:o,position:l.position,color:l.scatterColor,size:l.scatterSize,glyph:l.scatterMarker,opacity:u,orthographic:!0,lineWidth:l.scatterLineWidth,lineColor:l.scatterLineColor,project:l.project,projectScale:l.projectScale,projectOpacity:l.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=d(r),this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:o,position:l.position,glyph:l.text,color:l.textColor,size:l.textSize,angle:l.textAngle,alignment:l.textOffset,font:l.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=l.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=d(a),this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),n={gl:o,position:l.position,color:l.errorColor,error:l.errorBounds,lineWidth:l.errorLineWidth,capSize:l.errorCapSize,opacity:t.opacity},this.errorBars?l.errorBounds?this.errorBars.update(n):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):l.errorBounds&&(this.errorBars=g(n),this.scene.glplot.add(this.errorBars)),l.delaunayAxis>=0){var h=i(l.position,l.delaunayColor,l.delaunayAxis);this.delaunayMesh?this.delaunayMesh.update(h):(h.gl=o,this.delaunayMesh=v(h),this.scene.glplot.add(this.delaunayMesh))}else 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n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,f){function h(r,n){return i.coerce(t,e,c,r,n)}var p=n(t,e,h);if(!p)return void(e.visible=!1);h(\"text\"),h(\"mode\"),a.hasLines(e)&&s(t,e,r,h),a.hasMarkers(e)&&o(t,e,r,f,h),a.hasText(e)&&l(t,e,f,h);var d=(e.line||{}).color,g=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",d||g);for(var v=[\"x\",\"y\",\"z\"],m=0;3>m;++m){var y=\"projection.\"+v[m];h(y+\".show\")&&(h(y+\".opacity\"),h(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":752}],757:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":566,\"../../plots/gl3d\":629,\"../scatter/colorbar\":734,\"./attributes\":752,\"./calc\":753,\"./convert\":755,\"./defaults\":756}],758:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../lib/extend\").extendFlat,o=n.marker,s=n.line,l=o.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\").plot,n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":614,\"../scatter/colorbar\":734,\"./attributes\":758,\"./calc\":759,\"./defaults\":760,\"./plot\":762}],762:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t,n){h(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function i(t){for(var e=t.lon.length,r=new Array(e),n=0;e>n;n++)r[n]=[t.lon[n],t.lat[n]];return{type:\"LineString\",coordinates:r,trace:t}}function a(t,e){function r(e){var r=t.mockAxis;return u.tickText(r,r.c2l(e),\"hover\").text+\"\\xb0\"}var n=e.hoverinfo;if(\"none\"===n)return function(t){delete t.textLabel};var i=\"all\"===n?v.hoverinfo.flags:n.split(\"+\"),a=-1!==i.indexOf(\"location\")&&Array.isArray(e.locations),o=-1!==i.indexOf(\"lon\"),s=-1!==i.indexOf(\"lat\"),l=-1!==i.indexOf(\"text\");return function(t){var n=[];a?n.push(t.location):o&&s?n.push(\"(\"+r(t.lon)+\", \"+r(t.lat)+\")\"):o?n.push(\"lon: \"+r(t.lon)):s&&n.push(\"lat: \"+r(t.lat)),l&&n.push(t.tx||e.text),t.textLabel=n.join(\"<br>\")}}function o(t){var e=Array.isArray(t.locations);return function(r,n){return{points:[{data:t._input,fullData:t,curveNumber:t.index,pointNumber:n,lon:r.lon,lat:r.lat,location:e?r.location:null}]}}}var s=t(\"d3\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"../../plots/cartesian/axes\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,f=t(\"../../lib/geo_location_utils\").locationToFeature,h=t(\"../../lib/array_to_calc_item\"),p=t(\"../../components/color\"),d=t(\"../../components/drawing\"),g=t(\"../scatter/subtypes\"),v=t(\"./attributes\"),m=e.exports={};m.calcGeoJSON=function(t,e){var r,i,a,o,s=[],l=Array.isArray(t.locations);l?(o=t.locations,r=o.length,i=c(t,e),a=function(t,e){var r=f(t.locationmode,o[e],i);return void 0!==r?r.properties.ct:void 0}):(r=t.lon.length,a=function(t,e){return[t.lon[e],t.lat[e]]});for(var u=0;r>u;u++){var h=a(t,u);if(h){var p={lon:h[0],lat:h[1],location:l?t.locations[u]:null};n(t,p,u),s.push(p)}}return s.length>0&&(s[0].trace=t),s},m.plot=function(t,e){var r=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,function(t){return t.uid});r.enter().append(\"g\").attr(\"class\",\"trace 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}var d=o(t,e,p);return d?(p(\"text\"),p(\"mode\",d<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&l(t,e,r,p),a.hasMarkers(e)&&s(t,e,r,h,p),p(\"fill\"),\"none\"!==e.fill&&u(t,e,r,p),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/constants\":735,\"../scatter/fillcolor_defaults\":737,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/xy_defaults\":751,\"./attributes\":763}],766:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":626,\"../scatter/colorbar\":734,\"../scatter3d/calc\":753,\"./attributes\":763,\"./convert\":764,\"./defaults\":765}],767:[function(t,e,r){\"use strict\";function n(t){return{valType:\"boolean\",dflt:!1}}function i(t){return{show:{valType:\"boolean\",dflt:!1},project:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},color:{valType:\"color\",dflt:\"#000\"},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!1},highlightColor:{valType:\"color\",dflt:\"#000\"},highlightWidth:{valType:\"number\",min:1,max:16,dflt:2}}}var a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports={z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"data_array\"},zauto:a.zauto,zmin:a.zmin,zmax:a.zmax,colorscale:a.colorscale,autocolorscale:o({},a.autocolorscale,{dflt:!1}),reversescale:a.reversescale,showscale:a.showscale,contours:{x:i(\"x\"),y:i(\"y\"),z:i(\"z\")},hidesurface:{valType:\"boolean\",dflt:!1},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},_nestedModules:{colorbar:\"Colorbar\"}}},{\"../../components/colorscale/attributes\":535,\"../../lib/extend\":574}],768:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){n(e,e.z,\"\",\"z\")}},{\"../../components/colorscale/calc\":536}],769:[function(t,e,r){\"use strict\";function n(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.dataScale=1}function i(t,e){return void 0===e&&(e=1),t.map(function(t){var r=t[0],n=p(t[1]),i=n.toRgb();return{index:r,rgb:[i.r,i.g,i.b,e]}})}function a(t){var e=t.shape,r=[e[0]+2,e[1]+2],n=u(new Float32Array(r[0]*r[1]),r);return h.assign(n.lo(1,1).hi(e[0],e[1]),t),h.assign(n.lo(1).hi(e[0],1),t.hi(e[0],1)),h.assign(n.lo(1,r[1]-1).hi(e[0],1),t.lo(0,e[1]-1).hi(e[0],1)),h.assign(n.lo(0,1).hi(1,e[1]),t.hi(1)),h.assign(n.lo(r[0]-1,1).hi(1,e[1]),t.lo(e[0]-1)),n.set(0,0,t.get(0,0)),n.set(0,r[1]-1,t.get(0,e[1]-1)),n.set(r[0]-1,0,t.get(e[0]-1,0)),n.set(r[0]-1,r[1]-1,t.get(e[0]-1,e[1]-1)),n}function o(t){var e=Math.max(t[0].shape[0],t[0].shape[1]);if(g>e){for(var r=g/e,n=[0|Math.floor(t[0].shape[0]*r+1),0|Math.floor(t[0].shape[1]*r+1)],i=n[0]*n[1],o=0;3>o;++o){var s=a(t[o]),l=u(new Float32Array(i),n);c(l,s,[r,0,0,0,r,0,0,0,1]),t[o]=l}return r}return 1}function s(t,e){var r=t.glplot.gl,i=l({gl:r}),a=new n(t,i,e.uid);return a.update(e),t.glplot.add(i),a}var l=t(\"gl-surface3d\"),u=t(\"ndarray\"),c=t(\"ndarray-homography\"),f=t(\"ndarray-fill\"),h=t(\"ndarray-ops\"),p=t(\"tinycolor2\"),d=t(\"../../lib/str2rgbarray\"),g=128,v=n.prototype;v.handlePick=function(t){if(t.object===this.surface){var e=[Math.min(0|Math.round(t.data.index[0]/this.dataScale-1),this.data.z[0].length-1),Math.min(0|Math.round(t.data.index[1]/this.dataScale-1),this.data.z.length-1)],r=[0,0,0];Array.isArray(this.data.x[0])?r[0]=this.data.x[e[1]][e[0]]:r[0]=this.data.x[e[0]],Array.isArray(this.data.y[0])?r[1]=this.data.y[e[1]][e[0]]:r[1]=this.data.y[e[1]],r[2]=this.data.z[e[1]][e[0]],t.traceCoordinate=r;var n=this.scene.fullSceneLayout;t.dataCoordinate=[n.xaxis.d2l(r[0])*this.scene.dataScale[0],n.yaxis.d2l(r[1])*this.scene.dataScale[1],n.zaxis.d2l(r[2])*this.scene.dataScale[2]];var i=this.data.text;return i&&i[e[1]]&&void 0!==i[e[1]][e[0]]?t.textLabel=i[e[1]][e[0]]:t.textLabel=\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}},v.setContourLevels=function(){for(var t=[[],[],[]],e=!1,r=0;3>r;++r)this.showContour[r]&&(e=!0,t[r]=this.scene.contourLevels[r]);e&&this.surface.update({levels:t})},v.update=function(t){var e,r=this.scene,n=r.fullSceneLayout,a=this.surface,s=t.opacity,l=i(t.colorscale,s),c=t.z,h=t.x,p=t.y,g=n.xaxis,v=n.yaxis,m=n.zaxis,y=r.dataScale,b=c[0].length,x=c.length,_=[u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x])],w=_[0],k=_[1],A=r.contourLevels;this.data=t,f(_[2],function(t,e){return m.d2l(c[e][t])*y[2]}),Array.isArray(h[0])?f(w,function(t,e){return g.d2l(h[e][t])*y[0]}):f(w,function(t){return g.d2l(h[t])*y[0]}),Array.isArray(p[0])?f(k,function(t,e){return v.d2l(p[e][t])*y[1]}):f(k,function(t,e){return v.d2l(p[e])*y[1]}),this.dataScale=o(_);var M={colormap:l,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacity:1,colorBounds:[t.zmin*y[2],t.zmax*y[2]]};\"opacity\"in t&&t.opacity<1&&(M.opacity=.25*t.opacity);var T=[!0,!0,!0],E=[!0,!0,!0],L=[\"x\",\"y\",\"z\"];for(e=0;3>e;++e){var S=t.contours[L[e]];T[e]=S.highlight,E[e]=S.show,M.showContour[e]=S.show||S.highlight,M.showContour[e]&&(M.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,M.levels[e]=A[e],a.highlightColor[e]=M.contourColor[e]=d(S.color),S.usecolormap?a.highlightTint[e]=M.contourTint[e]=0:a.highlightTint[e]=M.contourTint[e]=1,M.contourWidth[e]=S.width):this.showContour[e]=!1,S.highlight&&(M.dynamicColor[e]=d(S.highlightColor),M.dynamicWidth[e]=S.highlightWidth))}M.coords=_,a.update(M),a.highlightEnable=T,a.contourEnable=E,a.visible=t.visible,a.snapToData=!0,\"lighting\"in t&&(a.ambientLight=t.lighting.ambient,a.diffuseLight=t.lighting.diffuse,a.specularLight=t.lighting.specular,a.roughness=t.lighting.roughness,a.fresnel=t.lighting.fresnel),s&&1>s&&(a.supportsTransparency=!0)},v.dispose=function(){this.glplot.remove(this.surface),this.surface.dispose()},e.exports=s},{\"../../lib/str2rgbarray\":588,\"gl-surface3d\":415,ndarray:438,\"ndarray-fill\":431,\"ndarray-homography\":436,\"ndarray-ops\":437,tinycolor2:459}],770:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/defaults\"),a=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}var l,u,c=s(\"z\");if(!c)return void(e.visible=!1);var f=c[0].length,h=c.length;if(s(\"x\"),s(\"y\"),!Array.isArray(e.x))for(e.x=[],l=0;f>l;++l)e.x[l]=l;if(s(\"text\"),!Array.isArray(e.y))for(e.y=[],l=0;h>l;++l)e.y[l]=l;s(\"lighting.ambient\"),s(\"lighting.diffuse\"),s(\"lighting.specular\"),s(\"lighting.roughness\"),s(\"lighting.fresnel\"),s(\"hidesurface\"),s(\"opacity\"),s(\"colorscale\");var p=[\"x\",\"y\",\"z\"];for(l=0;3>l;++l){var d=\"contours.\"+p[l],g=s(d+\".show\"),v=s(d+\".highlight\");if(g||v)for(u=0;3>u;++u)s(d+\".project.\"+p[u]);g&&(s(d+\".color\"),s(d+\".width\"),s(d+\".usecolormap\")),v&&(s(d+\".highlightColor\"),s(d+\".highlightWidth\"))}i(t,e,o,s,{prefix:\"\",cLetter:\"z\"})}},{\"../../components/colorscale/defaults\":538,\"../../lib\":578,\"./attributes\":767}],771:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../heatmap/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"surface\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"noOpacity\"],n.meta={},e.exports=n},{\"../../plots/gl3d\":629,\"../heatmap/colorbar\":690,\"./attributes\":767,\"./calc\":768,\"./convert\":769,\"./defaults\":770}]},{},[262])(262)});\n",
+       "</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -193,13 +266,18 @@
     "    [255, 128, 0],    #Orange\n",
     "]\n",
     "\n",
+    "stram = open(\"../conf/bothound.yaml\", \"r\")\n",
+    "conf = yaml.load(stram)\n",
+    "tools = BothoundTools(conf)\n",
+    "tools.connect_to_db()\n",
+    "\n",
     "def get_palette(N=5):\n",
     "    result = []\n",
     "    for x in range(N):\n",
     "        s = color_set[x % len(color_set)]\n",
     "        result.append([s[0]/255.0,s[1]/255.0,s[2]/255.0,1])\n",
     "    return result\n",
-    "palette = get_palette(30)\n",
+    "palette = get_palette(80)\n",
     "\n",
     "def plot_costs(costs, num_clusters, title):\n",
     "    KK = range(1,len(costs)+1)\n",
@@ -233,7 +311,7 @@
     "    left = [] \n",
     "    for i in range(len(sizes)):\n",
     "        left.append(i-0.5)\n",
-    "    fig = plt.figure()\n",
+    "    fig = plt.figure(figsize=(12,8))\n",
     "    plt.title(title)\n",
     "    ax = fig.add_subplot(111)\n",
     "    ax.bar(left,sizes, color = palette)            \n",
@@ -244,7 +322,7 @@
     "    model.fit(X)\n",
     "    \n",
     "    clusters = model.predict(X)\n",
-    "    plot_clusters(X, clusters, num_clusters)\n",
+    "    plot_clusters(clusters, num_clusters)\n",
     "    return clusters\n",
     "\n",
     "def get_best_clustering_model(X, max_number_of_clusters, title):\n",
@@ -268,14 +346,15 @@
     "\n",
     "    # calculate first derivative\n",
     "    derivative1 = [cost[i+1]-cost[i] for i in range(len(cost)-1)]\n",
-    "    #print derivative1\n",
+    "    #print \"d1\", derivative1\n",
     "\n",
     "    # calculate second derivative\n",
     "    derivative2 = [derivative1[i+1]-derivative1[i] for i in range(len(derivative1)-1)]\n",
-    "    #print derivative2\n",
+    "    #print \"d2\", derivative2\n",
     "\n",
     "    max2 = argrelextrema(np.argsort(derivative2), np.less) \n",
     "    num_clusters = 4 \n",
+    "    #print \"max2\", max2\n",
     "    if(len(max2[0]) > 0):\n",
     "        num_clusters = max2[0][0] + 3\n",
     "    else:\n",
@@ -296,7 +375,73 @@
     "    plot_clusters(clusters, model.n_clusters, title)\n",
     "    return clusters, model.n_clusters, cost\n",
     "\n",
+    "\n",
+    "import plotly\n",
+    "plotly.offline.init_notebook_mode() # run at the start of every notebook\n",
+    "\n",
+    "from plotly.plotly import iplot\n",
+    "from plotly.graph_objs import Scatter3d, Data, Marker\n",
+    "import plotly.graph_objs as go\n",
+    "\n",
     "def plot3(feature_indexes, X, clusters, selected_cluster):\n",
+    "    clusters_plot = []\n",
+    "    num_clusters = max(clusters)+1\n",
+    "    for i in range(0, num_clusters):\n",
+    "        d = X[clusters == i,: ]\n",
+    "        cluster = Scatter3d(\n",
+    "            x=d[:,feature_indexes[0]],\n",
+    "            y=d[:,feature_indexes[1]],\n",
+    "            z=d[:,feature_indexes[2]],\n",
+    "            mode='markers',\n",
+    "            name = \"Cluster {}\".format(i),\n",
+    "            marker=dict(\n",
+    "                color='rgb({}, {}, {})'.format(palette[i][0]*255,palette[i][1]*255,palette[i][2]*255 ),\n",
+    "                size=6,\n",
+    "                line=dict(\n",
+    "                    color='rgb(204, 204, 204)',\n",
+    "                    width=0.0\n",
+    "                ),\n",
+    "                opacity=0.5\n",
+    "            )\n",
+    "        )\n",
+    "        clusters_plot.append(cluster)\n",
+    "\n",
+    "    data = Data(clusters_plot)\n",
+    "    bk_color = \"rgb(224, 224, 224)\"\n",
+    "    layout = go.Layout(\n",
+    "        margin=dict(l=0, r=0, b=0,t=60),\n",
+    "        title='Clusters', \n",
+    "        height = 1000,\n",
+    "        width = 1000,\n",
+    "        scene=go.Scene(\n",
+    "            xaxis=dict(\n",
+    "                title = features[feature_indexes[0]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "           ),\n",
+    "            yaxis=dict(\n",
+    "                 title = features[feature_indexes[1]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "            ),\n",
+    "            zaxis=dict(\n",
+    "                 title = features[feature_indexes[2]],\n",
+    "    showbackground=True, # (!) show axis background\n",
+    "    backgroundcolor=bk_color, # set background color to grey\n",
+    "    gridcolor=\"rgb(255, 255, 255)\",       # set grid line color\n",
+    "    zerolinecolor=\"rgb(255, 255, 255)\",   # set zero grid line color\n",
+    "            )\n",
+    "        ),\n",
+    "    )\n",
+    "    fig = go.Figure(data=data, layout=layout)\n",
+    "    plotly.offline.iplot(fig)\n",
+    "\n",
+    "\n",
+    "def plot3_old(feature_indexes, X, clusters, selected_cluster):\n",
     "    if(selected_cluster >= 0):\n",
     "        X_plot = X[clusters == selected_cluster,: ]\n",
     "        labels_plot = clusters[clusters == selected_cluster]\n",
@@ -427,7 +572,10 @@
     "        cluster_total = bans[clusters_np == cluster]\n",
     "        cluster_banned = cluster_total[cluster_total==1]\n",
     "        banned.append(cluster_banned.shape[0])\n",
-    "        p = float(\"{0:.2f}\".format(cluster_banned.shape[0]*100.0/cluster_total.shape[0]))\n",
+    "        if (cluster_total.shape[0] == 0):\n",
+    "            p = 0\n",
+    "        else:\n",
+    "            p = float(\"{0:.2f}\".format(cluster_banned.shape[0]*100.0/cluster_total.shape[0]))\n",
     "        percentage.append(p)\n",
     "        d[\"data\"].append(cluster_total.shape[0]-cluster_banned.shape[0])\n",
     "          \n",
@@ -454,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {
     "code_folding": [],
     "collapsed": false
@@ -462,27 +610,32 @@
    "outputs": [],
    "source": [
     "#Report Configuration\n",
-    "id_incident = 20\n",
+    "id_incident = 21\n",
     "\n",
     "features = [\n",
-    "    \"request_interval\", #1\n",
+    "    #\"request_interval\", #1\n",
     "    #\"ua_change_rate\",#2\n",
-    "    \"html2image_ratio\",#3\n",
+    "    #\"html2image_ratio\",#3\n",
     "    \"variance_request_interval\",#4\n",
-    "    \"payload_average\",#5\n",
-    "    #\"error_rate\",#6\n",
+    "    #\"payload_average\",#5\n",
+    "    \"error_rate\",#6\n",
     "    #\"request_depth\",#7\n",
-    "    #\"request_depth_std\",#8\n",
+    "    \"request_depth_std\",#8\n",
     "    \"session_length\",#9\n",
     "    #\"percentage_cons_requests\",#10\n",
     "]\n",
     "\n",
-    "max_number_of_clusters = 8\n",
-    "\n",
-    "stram = open(\"../conf/bothound.yaml\", \"r\")\n",
-    "conf = yaml.load(stram)\n",
-    "tools = BothoundTools(conf)\n",
-    "tools.connect_to_db()"
+    "max_number_of_clusters = 15\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## For incident 19: \n",
+    "* features: 3,4,6,8,9  \n",
+    "* no PCA  \n",
+    "* DBSCAN - eps=0.3, min_samples=10"
    ]
   },
   {
@@ -494,9 +647,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
-    "code_folding": [],
+    "code_folding": [
+     0
+    ],
     "collapsed": false,
     "scrolled": true
    },
@@ -505,10 +660,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Incident 20 loaded:\n",
-      "Start: 2016-02-10 07:00:00\n",
-      "Stop : 2016-02-10 07:10:00\n",
-      "(13068, 5)\n"
+      "Incident 21 loaded:\n",
+      "Start: 2016-03-01 14:30:00\n",
+      "Stop : 2016-03-01 19:25:00\n",
+      "(6241, 4)\n"
      ]
     }
    ],
@@ -544,66 +699,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# PCA Clustering"
+    "# PCA Transform"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 84,
    "metadata": {
     "code_folding": [
      0
     ],
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[900]\n",
-      "[228, 672]\n",
-      "[671, 228, 1]\n",
-      "[671, 227, 1, 1]\n",
-      "[641, 225, 1, 32, 1]\n",
-      "[219, 308, 1, 31, 1, 340]\n",
-      "[339, 219, 1, 1, 308, 1, 31]\n",
-      "[339, 219, 1, 1, 30, 308, 1, 1]\n",
-      "[671, 227, 1, 1]\n",
-      "('Num clusters(PCA):', 4)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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wPTBOUnczu1JSJ+AvZvZuhWO6AocRJr5ZXD6GVjXvsdxf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\nP7Tpz17tMGEUAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe839a14ed0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe83ab80510>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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AcAe3tdC3rbqy3kKfNkCnuaKj0ah19+cY+rSEqun6/lysWiRVn7VZP4bNB6hpSVxRFGZt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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe833802550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# perform PCA dimensionality reduction\n",
     "\n",
@@ -612,10 +720,10 @@
     "X = pca.transform(X)\n",
     "\n",
     "# elbow methos fpr PCA\n",
-    "clusters, num_clusters, costs_pca = get_best_clustering_model(X, max_number_of_clusters, \"PCA\")\n",
-    "print (\"Num clusters(PCA):\", num_clusters)\n",
+    "#clusters, num_clusters, costs_pca = get_best_clustering_model(X, max_number_of_clusters, \"PCA\")\n",
+    "#print (\"Num clusters(PCA):\", num_clusters)\n",
     "\n",
-    "plot3([0,1,2], X, clusters, -1)"
+    "#plot3([0,1,2], X, clusters, -1)"
    ]
   },
   {
@@ -627,11 +735,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 13,
    "metadata": {
-    "code_folding": [
-     0
-    ],
+    "code_folding": [],
     "collapsed": false
    },
    "outputs": [
@@ -639,15 +745,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[3610, 6421, 484, 21, 136, 27, 65, 33, 20, 23, 31]\n",
-      "Estimated number of clusters: 11\n"
+      "[4811, 496, 373, 29, 48, 140, 11, 15, 15]\n",
+      "Estimated number of clusters: 9\n"
      ]
     },
     {
      "data": {
-      "image/png": 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WLZKqz9qsH8PmA1SLpPbjPoukIsxBBYB9EJICwAbqVVmpYjRpY/VVfZbeZDKJ6XQ6W7h0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SPTxMnv99cKWDqOQzKZJBwOI7ZvR6xZgxw/vsFtywMOIPaf/yALCoDU8UcIUe93qZTKTNdPnw+l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//40aNMhkuh6C6DXXYC1fjt+nDzI/H//005GbN0NqKv6YMbXyTZ3/+Z96txH629+wliyBcBix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OP+gSu1tbXU1tZi23bJ3I9iEAWnyWSSVCpFJpOhqqoK27YxDCMfQjc3N9PS0kIu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\n4gscRYQkjHa6bsPoGpUFhCy0gdELALuTWsMwqq9Dvl4WB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2mE7vpLwiFfvcM6u4gLzp36\nqOJoJpNxfchXLBbx4x//GD/60Y9wxhln4NFHH8WECRMCuGJCwkO877aEhAjZXBYKhdBkjUqYOkDX\nKGkfdmMoSFHCzvkj80EEtuHhYZYaRwjdecyS+mDQSybrObWjNnf0RjpxcmyR1qA7tnRhq7Oz09d8\nUxI/dLNB0jNrax3Wqc0IJY6JjaF2Iwcx6l7TzZ5s165duOuuu/DAAw/gS1/6Ev7nf/4HPT09AVwx\nIeGD3e1J6CkWi7Asq+6DzjAM7Nq1C+PHj2/hlTkjqA71bq/Fsizs2LGjKhSJkNDsA1QWJnLKLR3q\nk7ggIe7Qy6HD1GG8XkdwfQNL2oc+hqRDNGkf9Tobh3HuqBtK9T5EiFP0MZTL5VyN70ZdwdWGamF4\nThL/0IWtsHSqjwqN5k4ShFM1Tzybzbrea27btg233norHnvsMZx33nk499xzkcvlArhiQtpOzQlC\nkZSEniiKpHauUdm8t0sclUWD/Fv9nFPXj10THS7kSDNEeQypc0Zcpyz5aj1RHkNJRZ877S7Tt+sQ\nnc1mOXeJY1o1hlSntj532Nwm2ui5x7wP+YuaDRznuSP3Ia9j6P3338dNN92EpUuX4qKLLsKXvvSl\n2Ec8kMRDkZRElyiJpGF0jTbKGq3lmNM3ruVyGeVyGZ2dnXSNkqZRyxDjMobUckmZP0lqbNNq3Dbz\nIuFDLzVWD+yCLDXWm6AwloE0S7u7jEvEhS7+8MAuOrR7DCWZegd2URJO1UMay7I8jaGNGzfihhtu\nwDPPPIMrrrgCn/3sZ0P/+gnxCYqkJLo4EUkrlQp27NjRliDpsLtGpZS+mQeeiKblchmGYVR/juQ4\nxr1khfiDXSOmuJey1nMuxKWxTauRMVQul6uu0TiPoaQSZJm+mvOnxsMQ4hQ9s7ad6zyddh06kOZQ\n89fFSMGDvvZS69BB9jxhO3RQ95yAN4H9z3/+M6677jps2LABV199NT7xiU+E4jUS0kIokpLoIiWV\nYRNJ7Vyj7Sr5tHONymLYbdao6vhTu7LKQgLAGMccH64E2D0exSUhcyOpLgm9sY18JCknyw16Sb2M\nIbobkkUt14+TzateyspYBuIGNX89SrnHzDcND3YCOw9pwku9Q4d2ubVV97FXgf2FF17AwoULsX37\ndlx77bU48cQTA7hiQiIBRVISXcIkkqrlDdIoJJ/Ph8I1allW1THqpkO9nvGXyWTqbgT0MmO6FpKN\nbMjUrqxhasQUJtTNq8wfgIcOwNjNZBxiGYh/OHHMdXR0VO9FAKriKMcQcUpcBXYnpca83/qHGjOU\nTqcjI7CTsdRr5hnkgbceEeNlz7l27VosXLgQnZ2dmD9/Pk444QTfrpOQiEKRlEQXKdWttzg1TRPb\ntm3DXnvtFcg1hMk1CmDUAteLa1TP+POSz6a7Fug2TQZ0/PlDrUMHJw3Voo4qsLPDOGkWtVSyXC7D\nNE0AqAqnzAYmTlGfZ5ZlxV5gZ75pMKid6sV9zPtP/Gjk1vYinKriqFf38dKlS3Hddddh0qRJ+M53\nvoNjjjnG1c8hJIZQJCXRpV0iaRhdo3KK6dU12qqcyEZuU3EscPEdPexiGehA8Y9ai2+9zDjKGy+9\neUXcBQkSDCJIqJm1qVRqzKFdWDPmSPvR3VpJzorU3dqGYbTEMRd17NzH7WrcStqH3aGDZVm2zx67\nsaGaV7y4jy3Lwn//93/jxhtvxJFHHol58+bhsMMO8+MlEhInKJKS6CLNgxqJpFu3bsXEiRM9/76w\nuUbV8o6wuEbdUq/MmE1two+dwE6HROvQN6664yedTkdi48qSeuIV9RBTImLqPadrlelT+Ek2ejk0\nG3rZ47SpWhIPvfUu4zzsIzpOYi5SqRTK5bLnaAbTNPHLX/4S3//+99Hf34+rr74aBxxwgN8viZC4\nQJGURBcnIqllWdiyZYtrkZSu0fbgpKkN3abtJwwCOxmLKvzIHLJrzBEGEVt32YTtXkSigd4d2u+I\nGDvHTxjmD/EXlkN7J+n5pn420iHJQo+5KJfLED1GjYhpZg9aLpdx//3344477sApp5yCyy+/HJMm\nTQryZRASByiSkugSpEgadteoOEaj6Bp1C92m4cCuERObDoQfu0MHwFk38KCuhyX1xCutcvzpwg/L\n9OODfmgs6z3+Lf0hKfmmdlmRUX9NpPWoBzWyR5PP600J33jjDfzhD39Af38/jj/+eHR1dVV/TqFQ\nwD333IMf//jH+OxnP4uLL74Y48aNa9fLIiRq1Lxxs6aExArLshouVOxcoz09PW07AbZzjUrZbDOo\nGwB56Pb09ERO1JINqZSb6G5TaRCkuxXoAvEH1akF7Ba1urq6uAGICKlUCplMprrg1suMa80fv93a\nqqjV2dmJfD5Plw1pCjv3cW9vb6D3ejmUbGb+sEw/3OgHNblcDt3d3fx7+Yx6sB/H+aNnRUZxfU3a\nj+w/Jbe2r69v1NhXx5TMH9M08dxzz+GHP/whXnvtNRx55JE4/vjjYZomnnnmGXz961/H73//e3R3\nd7fjJRESS+gkJaHHiZMUADZv3oy99tqr5kIrzq5R6cYKJMOpZedWANrnlosDbMSUHOq5tVXHtptu\nrCypJ14Ju/vYrkwfgK3wQ9oHs4/DSdTyTe0qaji3STPoayMvLva3334bN998M9avX49t27bh/fff\nx8aNGzF9+nTMmjWr+jFlypRQzB9CQg7L7Ul08SKS2rlG25kb5GfWqL5wEzEiiQ/FRt1Yw5TNGCaa\nbX5C4kmtbGBxtTdy+9i5j8MkapFoEGVRq1FTNR7ctQ51beSlAQppHY3yTd0e3HlBd/xxbUSaRW/q\nlcvlXEefvffee7jpppuwbNkyXHzxxfjiF79YjZzZtm0b1qxZg1WrVlU/tm/fjv7+/qpoeuaZZ3L8\nEjIWiqQkujQjkk6YMAEdHR2hdY2apgkAdI22ALpNaxPlzFrSGpw0teno6BjlPmY2G3GDOGzilH3c\n6OAuSmXGUYGiVnxoV76pfnDM3FriBruID7dr7L/85S9YtGgRXnjhBXzrW9/CGWec4ei+9t5772H1\n6tVYtWoVXnrpJfz4xz/mOCZkLBRJSXSRzn9ORNLe3t4xZTHtdI3Kgss0TbpG20zS3ab6OJJNZNTF\nCNI65LCnXC6jUqmM6cYq2cC8L5FGJNHF3ijmgmX6zaM7tXhwHF+CPHjwU9QiyUUdR2LQcbsHfe21\n17Bw4UJs3LgR11xzDU499VSOR0L8hyIpiS6NRFJxjY6MjKCjowP5fD4WrlG7EtZMJsMNlI/oJcZ6\nJ+M4iD4shSZ+oI8jWfzrc8guW473LCKo4yiVSiXexc4yfXfo46idB+KkfTjNN631DFI71Xd0dHAc\nEVeo48hrVc26deuwYMECjIyM4Nprr8VHP/rRAK6YEPI3KJKS6CLuN3WRY5c1Wi6X0dfXV81oaSV+\nuUYBVDvU0zXaelSngmxYoyr6yLyRTqwshSZu0Bt6NRpHdtmmAGMuko4cZjKaoT71nkFq1UNYmtq0\nGj23VkQtQgQn+aapVKoaXcVxRNxiWRaKxaIv42j16tVYuHAhstksvvOd72D69Ok+Xy0hxAaKpCS6\nqCKpLJALhQIAjHKNbt26FX19fS0tH/bTNSolGmrJWBTEuLhj5zZVnT5hcpvKOCqVSokpYSX+I2O+\nVCp5zvdzUiKZZNEnzugdfdkZ2h1OyvTj7n6TcWQYxqjDY0IaoTYmlA89KoaHd6QZ1MMaL83hLMvC\n//7v/+L666/Hhz70IcyfPx9HHXVUAFdMCKkBRVISXQzDwMjISMOs0VaJpLprNJVKuXYX6i6tKHXz\nTSphdJvqjZhYMkbc0KpS6FpN1fQ5xPEbTdTDGuZEBoP+DNLL9MN0eOcWPw9rSLKxE9nl87Uc22ys\nRnTUiggvh36WZeG3v/0tbrzxRhxzzDGYN28eDjnkEP8vmBDSCIqkJLoYhoEtW7Y0XCBv27YNPT09\ngZXM+O0apdsvPtTLlVMbQgXRhVU2kHTXELeohzXpdLrlER+q00ctkezo6Bhz8MANa3jhYU37iFOZ\nPpvoED/QneyNOtXr+abiOI1i3BLxF11kdyuOVioVPPTQQ1iyZAnmzJmDK6+8Evvvv38AV0wIcQhF\nUhJd7DJJ7QhCJKVrlLhBNqx6Qxt1oe32b89GTMQPwu7SstuwAskqMY4KsoFU3TU8rGk/9RzbqvAT\nljmkNz/hGom4Qe1ZYFmWJ5HdSb5pmOYQ8RdVHPWyRiqXy/jpT3+Ku+66C5/4xCdw+eWXY+LEiQFc\nMSGkSSiSkujSDpGUrlHiN17dproQwYZexA16N98odRevV2IclGOb2BN2kZ2MRRzbYSvTV0tYveT7\nkWSjOpBTqVQgTvZ6VQ96qT6fQ9FFRHYnDuR6jIyM4Ec/+hHuvfdenHXWWbjooovQ19cXwBUTQlxC\nkZREF6ci6fbt29HV1YVMJuPq94hrVBY94hoF0PTGj65R0gjdbao75WSzKkIERXbiBbknlUqlqsge\n9W6+tRzbLI8MDt3JzlLoaFNvDulOOb//xvJs8+rSIsnGrsN4q+NiGkVd8AAv/Mj+r1AowDRNT+Lo\njh07cPvtt+Phhx/GV7/6VZx//vno6uoK4KoJIR6hSEqiS9AiqZ+uUTl9NE2TGZGkaWShXS6XbTuw\nxqEZB2kd+j0pCUKEXh5pGAZdPj6guv3aIUSQ1hFkmb5+T/IiRJBkE2YHcq18U/Xwjgd44cDPeIbN\nmzfj+9//Pp544gn88z//M77yla9Um4QRQkIJRVISXWQh5KdI6qdrVG9WEaXyVRIe7BoxyViulcvI\nPCxiB+9Je2jk8lHL9MlYVLefl4YVJLo0KjF2EnWhOpBTqVSi70nEG3410Wk19fJNVfGUc6I16A3i\n8vm864q/d955B4sXL8bKlStx6aWX4vOf/3xoBHtCSF0okpLo4lQk3bFjR9WVUO9nqYsTr65RdhYn\nXjFNc0yOVr3NY61cRnYBJ2yg44x6TjluVkdnaVuWxeZwZAxOy/QBVMVROpCJF9ScyDhURTDftD34\nmV27YcMGLFq0CC+99BKuvPJKnH766fxbERItKJKS6OJVJKVrlIQNGY+SW+ulEVOjLuB0m8YbNofz\nTq3NatIy5fTnWxCNT0h8UeeQ/C+w+zBaKiP4LCLNkLR4BuabBofatFIObNzmsr/88stYuHAh3nvv\nPVxzzTU4+eST+fcgJJpQJCXRxa1IGoRrVG0wQIcWaRZd0BLXqN+Clu7w0QUfET64qIsuFLSCRT18\nUAWfOB4+6E296EAmbpA5I24/EUb1MuNmyvRJMtFLoZPcII75pt7QG3vl83nXz7dnn30WCxYsQLlc\nxrXXXovBwUGfr5YQ0mIokpLo4lQk3blzJ9LpNDKZzCjXqCzAvbhGnZRBE1IL1TXa2dlZ7Szeyu6r\ntQQflhdHCzmwYUl966kVdRFFwUePjKEDmbilGUFLF3yYEUxUVLcfD/9qw3zTxqh7OK+NvVasWIGF\nCxeit7cX8+fPx7Rp03y+WkJIm6BISqKLE5HUNE3s3LkTADydrNYqg3ZbkkGSi11ubVgaDDgpL6bb\nNDy0yoFMmqOW4BNmh4/aQAdItkOLeMMvQYuCD9EFLa67m0Mt06+Vb5pOpyNziOcF2TOqB8lunsGW\nZeHJJ5/E9ddfj4MOOgjz58/HEUccEcAVk6hzzTXX4JFHHkE2m8Xhhx+OO++8E+PHj2/3ZRFnUCQl\n0aWeSKpvTvUFttOySGmeIxtHNqogbolqbi3dpuGDJfXRQ30OyTwKw0ZVHUtsoEO8oIoQXh1adjQS\nfKLm2ia10QUtRln5R6PmanHLN5WoD8MwPIujjz76KBYvXoypU6di3rx5mDx5cgBXTOLC448/jlNO\nOQUdHR249tprAQD/+Z//2earIg6hSEqiiy6SmqZZffBbllXNGVUfhnZlkXYuOb+a55BkY+dAjnoZ\ntL5RNQyDZZEtQB9LzECONo0acQQ9j9Q8bYoQxAv6WGplZUS9Mn31EI/Po2igClqM+mgdjRp9RnEe\n+TWWKpUKfvGLX+DWW2/FiSeeiCuvvBL77bdfAFdM4syDDz6In//857jnnnvafSnEGTUFH9YykNAj\ngqX6YG+UNSqiaSaTATB6YVAulzEyMlL92nQ6je7ubjq0SNPopavZbBZdXV2xGEepVKq6YBZkHqkx\nAgDGlBfH4fW3GrWk3rKsWI2lJKPOI2kqqEZdBDGP7OIZOJaIG+y6i7djLKVSKaTT6VEl2OohnjqP\nWP0QTvTGXrwvtZ44zSO5L3kdS6VSCffeey/uvvtufPrTn8YjjzyCvfbaK4ArJkngjjvuwJe//OV2\nXwbxAYqkJNTIZu9f/uVfMH36dAwMDODAAw90fcopAo80eJJFW6FQGONKoGhKaqE3Ysrn84kYL/oC\nW3ebiihDt6lz7MqgkzCWkkwqlap2/gYazyOnGcFsekL8Qm3GlEqlQhkbY3cYrs6jcrlcLdPX3aZh\neh1xRz8AzOVy6O7u5t8gJDQzj9odG2N3aON2LI2MjODuu+/Gfffdhy984Qt44okn0NvbG8BVkzhw\n2mmn4Z133hnz+e9+97s444wzAAD/8R//gWw2i3POOafVl0cCgOX2JNTIA3H58uVYvnw5li1bhrff\nfhuHHnooBgcHMTg4iI985CM1A963b9+On/zkJ5gyZQoGBgaqC3070UZ19+hZcszAIvrijCVi9qhu\nUzUjWD18SPo8UkvqWQZN7KiXEaxnbauHNkFkRJLkELfsWpbptw+10iaVSvHQJsK0O99UXX+L0O72\n0Gb79u247bbb8Ktf/QrnnnsuzjvvPOTzed+vmSSLu+66Cz/4wQ/wu9/9juMpWjCTlMQH0zTx6quv\nYmhoCENDQ3jhhRfQ09ODWbNmYc6cOZg1axZefvll3H777Xj44Ydx4okn4pprrkF/f39TD1R9UaBm\n94S5BIX4S1QbMYWFepmMSdukqu4sgA3iiHMsyxp1kKceQAAY1RGa44k0iwjtpVIpFpna9dCbQhmG\nUa2SYGyMdyzLQrFYHFMdQeJFo4M8P9Z2uqPdi9D+wQcf4Oabb8aTTz6Jb3zjGzjnnHOq7llCvPCb\n3/wGV111Ff7whz9g0qRJ7b4c0hwUSUl8sSwLW7ZswZNPPonbb78df/zjH9HV1YWPfexjOOmkk3Dy\nySfjwx/+sC8ijH6SqjaEYmlxfGDznGDRxR7DMEJRyhUUujuLYhZxi7pplOxaYM+zybKsUWIPxxmp\nhZ4RmdTqCL28WD5Ypt8caqd6OtqTid08AprP2/YzOubtt9/GjTfeiDVr1uCyyy7DWWedxXFJfOWI\nI45AqVTCxIkTAQBz5szBzTff3OarIg6hSEriy7p167BkyRL85Cc/wd/93d9h7ty5OOWUU/Dss89i\n2bJlGBoawoYNG3DAAQdgcHAQAwMDmD59enVz6QW70mK1UUfcxJ64Y9eIiU6/4Imj21QXIFhST7zg\ntAxa3aTqsTF8JhHAvkkcn3OjsesCrh9ARO2ZFBRqd3FxIfN9IUD9Awi7Z5Iqjnp1Ib/55ptYtGgR\nXn31VVx11VX41Kc+xXscIUSHIimJF4VCAffffz+WLFmC119/Heeffz4uuOACTJ482fbrLcvChg0b\nqiX6zzzzDDKZDGbOnFkVTidOnOj5AVpL7KGzJ9yopYaqA4J/p/YRVbGHJfXETwzD8JRdWy9LLqoH\nEMQdbOzlDZbpj0btLp7NZpHL5RLz2ol7aj2TRCT12sDypZdewoIFC7B582bMmzcPJ510EsclIaQW\nFElJfCiVSjj88MPxkY98BHPnzsXpp5/edK6MZVnYuXMnVq5ciaVLl+Kpp57Cli1bcNRRR1VF0yOP\nPNK3En07sUdtZNOoazHxH9VNw0ZM4afWwjosBxBqqWEcGp6Q9mHXwddPob1WtmlSxZ64o5dBS9wH\n8YbukjMMo6XNbNqB3kCHh4DEC3JvkgqJzs7O6pwCRuebjoyMYNy4cTV/1p/+9CcsWLAAlmVh/vz5\nmDVrVqteBiEkulAkJfHigw8+wN577+3rz6xUKnj++eerbtNXXnkFkyZNwsDAAAYGBjBz5kx0dXX5\n4jatFXbOhlDBozdiopsmutRzm6oZwUH9bWXDWCqVqiX1LDUkbmmX08+J2MPDvOjBMujWY1emD/jb\nzKYd+NlAhxD14KbWvUl3bp900knYuXMnZsyYgZkzZ2LWrFk44YQTsG7dOlx33XUYP3485s+fj+OO\nO65Nr4oQEkEokhLSLJZl4Z133qnmmq5ZswamaWL69OkYHBzEnDlzsN9++/kimqrOHnWDynJIf7AT\ns5gPGT9a5TbVs2tzuRwymQw3jMQVapO4sDj97PK2AR7mhZ2gXcikeRpFx4R5LtllRIb1Wkn4UQ9u\nmq3eqlQqeOWVV7By5UqsWbMGK1euxMsvv4yuri6ceuqpOPXUUzF79mwcd9xxbX9+EkIiA0VSQrxi\nWRYKhQJWr16NoaEhLF++HO+88w4OPfRQDA4OYnBwEMcee6wvD+d63b9b4ZCLC2zERPx0m6piFjeM\nxAtR6yyuH+axA3i40LOQeXATXqJQpq9W3LBTPfFKpVJBoVDwnF9rmiZ+/etf4+abb8b06dNx2WWX\nYcuWLVi5cmX1Y8OGDZg+fTpmz55d/Tj00EN5LySE2EGRlJAgME0Tr776KpYuXYqhoSG88MIL6O3t\nxezZszE4OIhZs2ahr6/Pt4ZQqtsUwCh3HMWaPYj4IKU84hrl+0MalUPqc0l3IYddzCLhJk5ilpPS\nYpbkBosqZvHgJrrUi2FqZZm+ehDIiAbiFbW5lxdXu2EYeOCBB3DbbbfhpJNOwre+9S3su+++tl+7\nbdu2qtNUPgqFAv7t3/4Nl156qdeXRAiJFxRJCWkFlmVhy5YtWL58OZYuXVp9OB933HEYGBjA4OAg\nJk+e7GtDKNXZo29Ok7S4ZSMm4ha7uSQuHtM0AYBlq8QTupglJfVxG0+15hKrIPxFj2ig0y9+tLJM\nX+9Uz7UTcYve3MvLQWCxWMRPfvIT/OhHP8Lpp5+OSy65BBMmTGj652zcuBGVSgWTJ09u+nsJIbGG\nIikh7aJcLuPpp5/G0NAQli1bhg0bNuDAAw/E4OAgBgYGcPzxxyObzXr+PbWcCLIxFdE0bpvTpIgP\npDWoLmRdKKVzmzSLOp5EfEiSmFUrJ5iZ280TtYgG4i9qmb7MJy9l+syvJX4i46lQKADwViUxPDyM\nu+66C/fffz/OPvtszJ07Fz09PX5fMiGEUCQlJCxYloU333wTQ0NDGBoawjPPPINsNov+/n4MDAxg\nYGAAEydO9K1E325BrQqnUVwQsxET8RMnJfW1HHL6XIrifCL+Yic+ZDIZill/Q+9arGZuh72RTTvQ\nnVnM1iaCkzJ9fZ0Xp8gP0n7U8ZRKpZDL5VzvLbZt24Zbb70Vjz76KM477zx87WtfQy6XC+CqCSEE\nAEVSQsKLZVnYsWMHVq5ciaVLl+Kpp57C1q1bcfTRR1dL9I844ghfNthq4w2vTWzagWma1ZJ6gIt7\n4g21sVcqlUI2m3U8nuptTtn9O5monaA7OjqaGk9JppFDTn02JQl9PHkRH0hyqBd5IWvAjo4O5PN5\njifiGv3+lM/nXa95Nm3ahJtuugl//OMf8c1vfhNf/vKX2aGeENIKKJISEiUqlQqef/55LF26FMuW\nLcOrr76KSZMmVZ2mM2fORD6fD7QhVJiEHnH5sRET8QPJ8yuVStXx5HVBXqv7t52jh+M2X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arZZDTUgRzl62NpsNKpVKnvhc088t12o45zXGatOq5Rq8S5LESfW1yK0e+lVVixlA+eD9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\nuLhYHghFRESkNEEQEBUVhaFDh3p6KUREROQBqjv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+      "image/png": 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MAACDQAYAgEEgAwDAIJABAGAQyAAAMAhkAAAYBDIAAAwCGQAABoEMAACDQAYAgEEgAwDA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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe8338b57d0>"
+       "<matplotlib.figure.Figure at 0x7ff7150b6b90>"
       ]
      },
      "metadata": {},
@@ -665,12 +773,12 @@
     }
    ],
    "source": [
-    "# DBSCAN clusterint\n",
+    "# DBSCAN clustering\n",
     "from sklearn.cluster import DBSCAN\n",
     "from sklearn import metrics\n",
     "\n",
     "# Compute DBSCAN\n",
-    "db = DBSCAN(eps=0.1, min_samples=20).fit(X)\n",
+    "db = DBSCAN(eps=0.3, min_samples=10).fit(X)\n",
     "\n",
     "core_samples_mask = np.zeros_like(db.labels_, dtype=bool)\n",
     "core_samples_mask[db.core_sample_indices_] = True\n",
@@ -686,6 +794,28 @@
     "plot3([0,1,2], X, clusters, -1)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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AbXEeSZUNskiqWIWaz0BN03RNgFr8df6zN8OHFgyLkBQqql8LfcTkLlxqNpsx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\nIDZvFlBSwrF+vYjNm0XcfHMQRUUcP/yhgmCQ4Y47gl2tQO6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3lQfbtgl46ikZo0YZuPnm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NAfSBVBoLbrJgtWw48u8IcmGL5mVyXgiqhEcDGBKD8qKCEbf60bkWpc4xrLQqpbBTSCNdpo2yyt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\nm82qWrWqBgwYo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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f68859f6350>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot3([3,0,1], X, clusters, -1)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -695,33 +825,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 45,
    "metadata": {
     "code_folding": [],
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[13068]\n",
-      "[2046, 11022]\n",
-      "[6918, 1949, 4201]\n",
-      "[4951, 2140, 4201, 1776]\n",
-      "[2140, 4195, 4952, 1776, 5]\n",
-      "[2111, 4195, 1342, 635, 5, 4780]\n",
-      "[4761, 3623, 1337, 2109, 632, 5, 601]\n",
-      "[3623, 4592, 833, 2009, 5, 422, 601, 983]\n",
-      "[4951, 2140, 4201, 1776]\n",
-      "('Num clusters:', 4)\n"
+      "[902]\n",
+      "[842, 60]\n",
+      "[805, 38, 59]\n",
+      "[325, 482, 36, 59]\n",
+      "[465, 34, 318, 26, 59]\n",
+      "[462, 34, 318, 40, 26, 22]\n",
+      "[397, 142, 22, 34, 26, 241, 40]\n",
+      "[40, 393, 141, 25, 29, 240, 12, 22]\n",
+      "[40, 239, 393, 11, 22, 9, 27, 20, 141]\n",
+      "[394, 141, 40, 4, 20, 23, 22, 236, 13, 9]\n",
+      "[331, 40, 23, 128, 20, 132, 22, 182, 4, 11, 9]\n",
+      "[301, 135, 23, 40, 12, 22, 9, 9, 182, 11, 154, 4]\n",
+      "[130, 316, 40, 23, 9, 127, 11, 20, 180, 11, 4, 10, 21]\n",
+      "[293, 182, 40, 9, 133, 23, 19, 11, 5, 12, 4, 145, 22, 4]\n",
+      "[162, 40, 4, 293, 12, 23, 22, 96, 139, 9, 11, 19, 4, 5, 63]\n",
+      "[40, 239, 393, 11, 22, 9, 27, 20, 141]\n",
+      "('Num clusters:', 9)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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WWc+zdKn47LM13HzzAHr2PDLtaM65PFpvd5akQ+PXbpJOKPmovogui/2qkqhf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\naML9jcplaw+cUpE3VPBzuDrEi4irLVY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xxk/Ze++p9O3rvybnXP5lUlV1K3Cjmc2um0i5a0hVVePGTWDMmAf4+utuLFhw\nOdtscylNmrzJ4MH9OPvskwodzzmXELlUVVV7xSFpTjTbGDhN0ofAt9E6M7Ndcovp4nDWWQNo02YT\nhg6dCYgvvqjgttsG+VWHcy7vamrjOCqaehMGVDosbd1R+Y9WP8VV7ykJSSxZsoqttx7CkiUr+eqr\nsC4OSamf9Zzx8pzxSULGXFVbcJhZuZmVA5en5tPX1VVAV72ysnmMH384ZWXXcNxxvbnppnmFjuSc\nawAyaeOYZWa7pi2vB8w2sx3zHS5bDamNo7IVK2CHHeDee6FHj0Kncc4lRdxdjlwiaRnQVdKy1AR8\nRhgb3BWR5s1Dr7mDBsGaNYVO45yrz2qqqrrCzFoCV5tZy7SpjZkNq8OM9Uo+6z379oW2beGmm9b9\nWEmpn/Wc8fKc8UlCxlzVdMWxfTT7oKTdKk+ZHFzSnZIWpd2hhaQRkuZLmhVNvdNeGy6pTNI7kg5L\nW7+7pDnRazfk8D4bBAnGjIHLLw9dkjjnXD5U28Yh6TYzO1PSdKoej+PAWg8u7U940vweM+sarbsM\nWGZm11badkfgfmAPYHPgWaCLmZmkEmCQmZVIegoYY2aTqzhfg23jSPeHP8Bnn8FddxU6iXOu2MX6\nHIeZnRn97JlrIDN7XlKnKl6qKuTRwEQzWw2US3oP2EvSR0BLMyuJtrsHOAb4ScHhgj/+MTSUv/QS\n7LtvodM45+qbWvuqkvSCpL9JOlxSy5jOe76kNyXdIal1tK49MD9tm/mEK4/K6xdE6xOpLuo9W7aE\nq66C886D77/P7RhJqZ/1nPHynPFJQsZcZdJX1SnA/oQecq+WtAp4wcz+L8dzjgVSPev+FbgGOCPH\nY/3EwIED6dSpEwCtW7eme/fu9IzGWE39Igu5XFpaWifn69cPrrxyOkOHwvXXF8/7j3u5rj7PhrLs\nn2d8y6WlpUWVJ7Wcmi8vLydXGY3HIak9YWCnA4ADgY8z7fgwqqp6PNXGUd1rkoYBmNmo6LXJwGXA\nR8A0M9shWt8f6GFm51RxPG/jSPPWW3DQQfD22/CznxU6jXOuGOWlW3VJ7wP/BDYD7gB2WpfeciW1\nS1s8FkjdcfUY0E9SE0lbEbo5KTGzhcBSSXsp9KdxMvBorudvSHbeGQYMgEsuKXQS51x9ksl4HGOA\neUB/YDAwUNI2mRxc0kTgJWA7SfMknQ5cKWm2pDeBHsDvAcxsLjAJmAs8DZybdvlwLnA7UAa8V9Ud\nVUmRfrmPesGQAAAcBElEQVRYF0aMgCefhJKSWjf9kbrOmSvPGS/PGZ8kZMxVrW0cZnYDcIOkFsBp\nwAhC43TjDPbtX8XqO2vY/grgiirWvw78pKrL1W6jjWDUqNBQ/sor0LjW35pzztUsk76qriE0jrcg\nXD08T2gcfz//8bLjbRxVM4P994dTT4Uzzyx0GudcMcnXmOPHAzPNrOifRfaCo3qlpdCrF/z3v9Cm\nTaHTOOeKRV4ax83swSQUGklRqHrP7t3h+OPh0ksz2z4p9bOeM16eMz5JyJirTBrHXT3x17/CI4/A\nG28UOolzLskyeo4jKbyqqnZ33AG33w4vvgiN/GuDcw1eXqqqogPvL+m0aP5n0XMWLoFOOw0qKuCe\newqdxDmXVJk8ADgC+AMwPFrVBJiQx0z1WqHrPRs1CuN1DB8OS5ZUv12hc2bKc8bLc8YnCRlzlckV\nx7GEnmtXAJjZAiCuzg5dAfziF9CnD/zpT4VO4pxLokxuxy0xsz1TY49Lag68bGa71E3EzHkbR+a+\n/DJ0vf7ss7BL0f0mnXN1JV9tHA9KGge0lnQW8Byh+w+XYJtsAn/5S3ii3Mta51w2MnmO4yrg4Wja\nFvijmY3Jd7D6qpjqPc88E775Bu6776evFVPOmnjOeHnO+CQhY64yGY8DM5sKTM1zFlfHGjcODeV9\n+4Y2j1atCp3IOZcEmbRxLKti9dfAq8BQM/sgH8Fy4W0cuTn9dNh4Y7jmmkIncc7VtXz1VXU5oVv1\nidGqfsDWwCzgnHUZkzxuXnDk5rPPYKedYPr08NM513Dkq3G8j5mNM7Ol0XQr0MvMHgA2zilpA1aM\n9Z4//3m4Nff889c2lBdjzqp4znh5zvgkIWOuMik4vpF0oqRG0XQCsCp6zb/e1xO/+124RXfSpEIn\ncc4Vu0yqqrYGbgD2jla9AvwfsADY3cxeyGvCLHhV1bp54QXo3z90vd6iRaHTOOfqQl7aOJLEC451\nd/LJ0L69IV3FyJEXEYZ5d87VV3lp45DUTNIgSTdLujM15R6zYSv2es/Ro+Hmm6dwww0lPPJI8d+B\nXeyfZ4rnjFcSciYhY64yaeO4F9gMOByYAXQElmdy8KiQWSRpTtq6NpKekfSupKmSWqe9NlxSmaR3\nJB2Wtn53SXOi127I9M257IwbN4FDDjmSZs2eZ9Wq8xg2bCY77XQk48Z5n5bOubUyaeMoNbPukmab\n2S6S1ieMOb5XrQeX9icUMveYWddo3WjgCzMbLeliYGMzGyZpR+B+YA9gc+BZoIuZmaQSYJCZlUh6\nChhjZpOrOJ9XVa0DM+OhhyYzdOhM5s0byYYbDueuu3rw61/38ior5+qpfN2O+13082tJXYHWwM8y\nObiZPQ98VWl1H+DuaP5u4Jho/mhgopmtNrNy4D1gL0ntgJZmVhJtd0/aPi5GkpDEkiWr2H77Iaxa\ntZJ//ENeaDjnfiSTguNWSW2AS4HHgLnA6HU452ZpY5gvIlSDAbQH5qdtN59w5VF5/YJofSIVe71n\nWdk8xo8/nJtvPorbb+/NtGnzuO22QqeqXrF/nimeM15JyJmEjLmqsa8qSY2AZWa2mNC+EevIf1E1\nVKx1SwMHDqRTp04AtG7dmu7du9OzZ09g7S+ykMulpaVFlafy8j77dKFnz55Mnz6drbbagOuv34aL\nLoKOHaFp08Lnq7xc7J9n0pb984xvubS0tKjypJZT8+Xl5eQqkzaO181s95xPIHUCHk9r43gH6Glm\nC6NqqGlmtr2kYQBmNirabjJwGfBRtM0O0fr+QA8zO6eKc3kbRx689BIccwxMnQrduxc6jXMuTvlq\n43hG0oWSOkZ3RLWJqq5y9RhwajR/KvBo2vp+kppEY5p3AUrMbCGwVNJeCpXtJ6ft4+rAvvuGXnSP\nOgrmzSt0GudcoWVScPQDzgNmAq+nTbWSNBF4CdhO0jxJpwGjgEMlvQscFC1jZnOBSYQ2lKeBc9Mu\nH84lDB5VBrxX1R1VSZF+uVjMKuc8/ni44AL41a/g668Lk6kqSf08i5XnjE8SMuaq1vE4zKxTrgc3\ns/7VvHRINdtfAVxRxfrXga655nDxGDoUysvh17+Gp56C9dcvdCLnXCFk0sbRHBgCbGFmZ0rqAmxn\nZk/URcBseBtH/n3/PRx7bBh69s47we/UdS7Z8tXGMZ7wLMe+0fInwN+yzObqicaNYeJEeOst+Otf\nC53GOVcImRQcW5vZlUQPAprZivxGqt+SUu9ZU87mzeHxx2H8eLj77mo3qxP14fMsJp4zPknImKtM\nxhz/VlKz1ELUzfq3+YvkkqBt29DO0bMndOgABx9c6ETOubqSSRvHYcD/A3YEngH2Awaa2bT8x8uO\nt3HUvRkzwh1X//437LxzodM457KVt/E4JG3K2oGc/mNmn+eQL++84CiM+++H4cPh5ZehfftCp3HO\nZSNf43E8DhxGeHr7iWItNJIiKfWe2eT8zW/g7LPhyCNh2bL8ZapKffw8C8lzxicJGXOVSeP4NcD+\nwFxJD0n6taSmec7lEmb4cPjFL+CEE2DNmkKncc7lU8ZDx0paDzgQOBM43Mxa5TNYLryqqrDWrAnd\nkmyxBdxyiz/j4VwS5Os5DqK7qvoC5xAGWirwTZiuGK23HkyaBCUlcOWVhU7jnMuXTNo4JgHvEPqV\nupHwXMf5+Q5WXyWl3jPXnC1bwpNPwtix4UHBfKvvn2dd85zxSULGXGXyHMedQH8z+x7CcLCS+pnZ\nefmN5pKqfXt44onwbMfmm8MBBxQ6kXMuTpnejrsb0B84AfgQeNjM/p7nbFnzNo7i8txz4Y6rGTNg\n++0LncY5V5VY2zgkbSdphKT/AtcDHxMKmp7FWGi44nPwwTB6dOiKfeFCY9iw0XjB7lzy1dTG8V9g\nN6CXmR0QFRbf102s+isp9Z5x5Tz1VDjlFPjlL6dw882f8sgjU2M5bkpD+zzzzXPGJwkZc1VTwXEc\nsBKYKekWSQcDfoOly8q4cRN48MEj+eyz51m27FrOOmsmnTsfyS23TCh0NOdcjjLpq6oFcDShjeNA\n4B7gn2YW71fHGHgbR/ExMx56aDJDh85k3ryRtGw5nI026sGqVb044ghxxBFw2GGw0UaFTupcw5SX\n5zjMbLmZ3WdmRwIdgVnAsBwzugZGEpJYsmQVO+44BFjJ9deLV18Ve+wRumbv0AEOPBCuuQbeeQe8\n7HeuuGX0AGCKmS02s1vN7KB1PbGkckmzJc2SVBKtayPpGUnvSpoqqXXa9sMllUl6J+qxN5GSUu8Z\nZ86ysnmMH384b711DePH96asbB6dOsF554Wu2RcuhCFDoKwMDjkEttkmjG8+dSp8W0sH/g3x88wn\nzxmfJGTMVSbPceSLAT3NbHHaumHAM2Y2WtLF0fIwSTsCJxK6dt8ceFbStmZWUeepXdaGDz/zh/m+\nfXv95PXmzUNXJUcdFa42Zs8ODxH++c9hpMEDD4QjjghTeu+7Zsatt06kR48eyPs3ca7OZNxXVewn\nlj4EfmFmX6atewfoYWaLJLUFppvZ9pKGAxXRSIRImgyMMLNXKh3T2zjqmS++gMmTQ0EyZQp06hQK\nkCOPhI8/nswZZ0xh/PjDqyy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9uAbKCw6XNKsJT1//vvILlb+ZS1oe/ewpaYakRyW9L2mU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\n5f8DumuCLHMqTb8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f333dd9ae10>"
+       "<matplotlib.figure.Figure at 0x7f6886ca3750>"
       ]
      },
      "metadata": {},
@@ -729,9 +866,9 @@
     },
     {
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3337b99450>"
+       "<matplotlib.figure.Figure at 0x7f68847b8a50>"
       ]
      },
      "metadata": {},
@@ -739,9 +876,9 @@
     },
     {
      "data": {
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PYjQaxeuvvx6/+7u/G+95z3tOfEvrqbfhgtHVJNTYphb64q+n8Pbbb8d73vOe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\nORt4m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4QrJsR22G5PiFswyxqtq6tDLBYry03YzDUqnEi5vk4ikegjbDmxlcysdVp+4DO2\ns1ZSNlu5MU6Idns7q1mbobH1C3D/RtwpmOXVOq2lvhhkqjU5YgBgrWXDjVPGi4Km9cvRBMxbWmUx\ny1hrVob1BH72M1S9+CISvb1Qr722OO+nhAjXXyKRQHDwYNRUiPPYbsz2avI9VIiHoia90rFhdkBT\nU1Pj6vfkZMThoVmkkqg1Ob7LDfEj8n2sqqoKNTU1eRlVdF3HK6+8grvuuguHHXYY7rrrLhxxxBFF\nuGJCSg9FUkIcQras0Xg8jizOb1uvpViuUbcJW5ke+syy2cRmnG5TexCHBiKXLBgMor6+3pPCVi45\nuqw164gDGiFssZ21/7omBAbhNmWt9cXoPM73odITfPYZwiecAH3UKMRWrMj65ekym+UDoUyREOr5\n5wM9PUjOnFnsd1Y05GgY4frz6n2sXFgRs7LVmpPxwkA4r5AtSzddrZVbOJUjzgrJrNU0Dc8//zzu\nu+8+NDQ0YMmSJRg1alQRrpiQ8sF2e+J4rLTbJxIJ9Pb2YsCAAaW6LFvIZUJ9T08PFEVBdXV10a7H\nrqxRs3boQCDg2QeCdO2ssnuhIt1GBWAcxFSxji0DmVqnORSqL7Jjy2mxHm7Aapu+V2vNTNhiOyug\nfPIJwk1N0A86CNE33rDlNbPVmlvjRyhsOQ8rteakAyG6192LU2rNONBLRHvkiqqqeOqpp/DAAw/g\npJNOws0334yDDjqoCFdMSMlgJilxL14USc1co6FQKON7LJZIKlyj4gYuTkgB5PQwmC5r1E2uUTsx\n5k3SlZUd44TxShqCUgjGbDZVVR3lXiglZi31FLbsI90AMqut026AwlZ2lH/9C3pNDTBoUNG+h9kA\nMsAdmZO6riP+xR7PV1VFYcvhpMvSLeeUc6Prj4d83iDbEDI7hVNZHC1koFcsFsNjjz2GRx55BGee\neSauu+46DCri2k9ICaFIStyLV0RS8XAZjUazukbN6O3tha7rqKmpseV66BotLVbcpk594Cs2XhjE\n5CQqcSiU0XnMlvrSYGzTl4fdue1ASK6hqqqqlCjh9OuuJDIdPjrhQCglSnR1YcjFF8NXVYX4s88C\nwWBZrofkT7kGQ6UzGxDvYpx9kEwmCxLpRQeEeNbM96B4//79WLJkCZ566il85zvfwQ9+8APU1tbm\n8xYJcSoc3ETci6IoWbM4rXxNuciWNVrqa7HDNQr0HaLj9/sRDof5QJkBswwjeRMuWjrdmJWVL8Z2\naLfl1TqVbIN6jEOh3OwANNZQvhlbJD/EQ1tQEoGMD3zC1evUSAj5gZI15GxyyTc11lox1zZjDdWF\nQvDv23dguJWqUiR1IZkGQ8lT5e0S6Y3CViUMFSQHyJRHbzbwLp1IL+eJi9zjfGpx3759uP/++7Fs\n2TJcfvnl+Nvf/pa6LkIqBTpJieOJxWLQdT3jQq+qKvbv34+BAweW8MrSk841WogIUYiTVL7ZAoW5\nRo1DdNjKah+VkDfJGnIGmRyApRQX8oE15D4yubLKIdKbTYime90bZGpntbN1OmsN7doFKAowdKhN\n74w4DaNIn6uT3ph7zHWIpEMW6Y33UZ/Pl6pFK/Ft6fjss89wzz33oLW1FT/84Q/xne98hxEPxOuw\n3Z64FzeJpPlkjVpFnA5abXUohms0kUiwDbHEZMubdIvbVM5GYg05k3TiglMiITjMyztkEheKKdIb\nh6AwlqEyyNY6LWrOSh0ws5ZkwkrmpM/nS+2rAdYQyR15HRKt+aL2jO5m+fnPjG3btuGuu+7CP/7x\nD9x0000455xzeOhMKgWKpMS9WBFJk8kkurq6yhIkXQzXqBlWRVK6Rr2NLC4IF6BT3aYcxOR+smUA\nlkKkFzWUSCRS6xBryHtYdQDms7bJB30cgkKyZematU4bM2uLsc8j3sQYdyNmAYhDIdlxSkgm5GdO\noL/AbnYAeeWVV2Lz5s2YOnUqpk2bhsbGRkyePBnbt2/HHXfcgY8++gg/+tGPcNppp3E9I5UGRVLi\nXoRI5zSR1Mw1WkwRMZNIauYaFcIFXaPex/iwV263qaZpqRNu8XeDLglvkEmkN7YXFvp95EMaUUN8\niKws0jkAje5mK62sPOgjmUi3tol6Ea76XAZuEgKYC+zCTWqHu5l4H9k5KvbVVp/NYrEYNm7ciHXr\n1qGjowPr16/H1tbz2aUAACAASURBVK1bEQwGcfLJJ+OMM85AU1MTjjnmGK5tpNKgSErci5NEUjmD\nSgwKCYfDJdnICKdqXV1d6v/JD5C6rqcco3a4RgOBAN1aLqVUQpbxe6abyspNvreRXTKF5k1ywjjJ\nhJU2fWMrqxBHWUPEKmJNE4fTYv2yMjyFEIEcMyQE9nT76nzczcT7GCNiCnnm7OjowPz581FVVYWb\nbroJPp8Pa9euTf365JNPMGXKFDQ2NqKpqQlNTU048sgjub4RL0ORlLgX0aqbaZHWNA379u3D4MGD\ni3INpXaNmiE2WnV1dX02UIW4Ro0Zf8xn8y5mm2/AmiMr2+vS8Udkch0KJQvsYjo0W+qJVdjKSuxC\nvp/pum4qsJvlhIvp1BSyCNB3Un0gEEg5R3PFeCikqmrK3ez0AYukMGRxVLiP83V5tra24o477sCw\nYcNw++23Y+LEiaZf19nZifXr12Pt2rVYt24d1q5di927d+PHP/4xbr311kLeDiFOhSIpcS/lEknL\n6Ro1IxqNIh6PIxAIAEBBrlHmRJJ0m2+rblPGMpBcMOZNqqoKACmRFEAqz5k1RHJBCBJyZq1w/VHI\nIlYwurVyaWUtdMI58QZm8R7FuJ9ZGQzFenMvsnklm/s4E7qu489//jPuvvtujB8/HnPmzMHhhx+e\n8+t89tlniEajGD16dM5/lhAXQJGUuJdEIpHKWEyHpmnYu3cvhgwZUvD3c4Jr1Hg9wiEj3A1i451L\nZhFdoyQb6dqm5Yc84bQRAnu+DglSuYi1SAgSoq7KMRSKuBP5ENPKYMF0QhaFhcrG2A5t10CvbEKW\nvHdjvbkbeS1K5z4uxTWki7xhLIQ7yCWaIdvr/OlPf8JvfvMbNDY24kc/+hEOOeSQIlwxIZ6AIilx\nL1ZEUl3XsWfPnrxFUqe5RjVNS4mjxqxRY9aksY1VuB+EQ4uuUZIvQlgQNcQ2VpIvRpeN2Vok15vd\n082JNxCOv3g8DkVRCjrsM3M367rez23KevMedrVD54IVIYvdGO6hkEE6pSDd0Lt8ssJJ8ZDF0ULW\nokQigSeffBIPPvggTj31VNx4440YNmxYEa6YEE9BkZS4l2KKpE51jYqsUZEzmu29yw95YiOkKEoq\nu4iDK0iumA1ikiey2jGkh3gf+UESyH2ITrGydIm7KJbjz+z7sE3fmxgPjcV+r1w/S5HdbHbozUE9\nzsUsK9INP6NssRCst9IiH9Rk64TIRDQaxaOPPorHHnsM55xzDq699loMGDCgCFdMiCehSErcSy4i\n6eDBg7Pe3M1co+U8Ac7kGs0F+X2JNkLZeVrMyebEO8hOLSC7qJUt29TobiaVgSxq2ZlZy3qrHMzc\nx6WO97BSb2zTdzbGgxoxXNCJPy/Wm3OxKyvSScj1JoR61ltxkZ/TCsmt7e7uxkMPPYSnn34aF110\nEa666irU1NQU4YoJ8TQUSYl7sSKSAsDu3bsziqRecI2mex2RVwqYi1rZsiZ5ekzsHMSUzt1Mt6m3\nsdJSX8zva1Zvxvw/4nwKdR8Xm3RDyJj/5yxkUcvNwwXTxUIwhqQ0pOuo8SpWBkPxIDI3jHujQlzs\ne/fuxW9+8xv8+c9/xpVXXolLL70UwWCwCFdNSEVAkZS4l0JEUi+7Ro0bNyFG5DONVXYrcNNdOeQ6\n/KSQ72PWNs1NtzfI1X1cCtJlN3PatHNxs6hlvJ+yjbV8yHsjrzj+jDBvsvgYHX/lNFWUm3SxNzwY\nyoxxqFchLvZPP/0U99xzD9rb23Httdfi29/+dlEiZwipMCiSEveSi0g6aNCgVIu5E12jYvBNMV2j\n+WLcBInPnJOmvYcsRojM2lK3H9Jt6n6MLfVOzmbjUCjnIhw28kGm20Uttk2XnkoWtazkTXIPlx3j\nwXG5c2udDPOb02NnxMcnn3yCBQsW4O2338bNN9+MM888s2LWNUJKAEVS4l5UVUUikbAkktbV1fVr\niymna1RsuMQApXK4RvMlU1aR2AS5xeVD+teReIh0ihiRzm3q8/n6iVisufJhHH7i5vZDs4c8uv9K\nQ6lc7E4iWyyEE4R65cMPETrjDCRPOgmJu+8u23VYxejUcoKL3SlkOhhiB0df3JRb61Q4GKpvHQmD\nTr7PSe+//z7mz5+Pbdu24dZbb8XXv/51z35uhJQRiqTEvWQTSYWbqbe3Fz6fD+Fw2BOuUbMW1kAg\nUNYHqEwthWxhdSZObIW2CrMmnYOxjrz4EMmhUMVHriNFUcriYncSTmvT961ejdDMmdAmT0astbUk\n39MKvrVroR1+ODB0KID+dVTOA3E34QahvpTIk+p9Ph/ryGasCPVeeG6Q66jQrpqNGzdi3rx56O3t\nxdy5c3H88ccX4YoJIV9AkZS4F+F+kzdtZlmjiUQC9fX1Zcloscs1CiDl0iqlazRfzDZAYqAARazy\nIv7eGCexuv1nkS5rkm7T4mAc6OWVOrJKuqF3jIXIDTdFM5QTK9Omiy3UKxs2QB85Ehg+vCivnyu+\nFSsQ+t73oEUi6H3yyT65tULUIvnjNKG+FBjzj1lHpSPbYCj5ucHpNafrOmKxmC11tG7dOsyfPx/B\nYBC33347pk6davPVEkJMSLvI8I5AXIXY2ESjUQBAOBxGTU0NfD4f9u7dW/IbqplrVOQ+5YLcoiFa\nxurr6x1/mq8oSmpjI5Af8KLRKEWsEiLqKB6Pp1pY3VBHuSAOHwKBAID+zhixNlCozx9jS30wGERd\nXZ2n6sgqYk0XDz7GWIhEIsE1Lg3Gib6BQKBi68gq8j1VTCyW17hEItFvjbM7+kZvaLDldexCP/RQ\naKNHIzp5Mrq7uxEIBFBbW+uYqBi3Y3ZPlYVTL61x8mGN3+9nHZUB4z0V6CvUi30H4FyHsyyyF1JH\nuq7jb3/7G+6880585StfwS9/+UscddRRRbhiQkiu0ElKHI+qqujt7c2aNbp3717U19cXfcNjdI2K\nh5p8bt5Gl5abpvlaxXhqrKoqAIpYdmIcxFTpLWN0m+YHW6Hzw2yN03W93wALpzzgFRv5sIY5kcUh\n3RrnpSE9Zoc1Xs+tdSpud/+JwxpVVV2do10piMNIpzmcZZG9kDrSdR0vv/wy7r77bkycOBFz5szB\n2LFj7b9gQkg22G5P3IuqqtizZ0/WDfK+fftQW1tbtJYZO7NGjW6/Stv4mz3gMfcvN8wG6DhpEJOT\nyCbUV/oQMvmwxu/3Ozriwy1ka2H1gohlhIc15cMJbfp2oes6EvE4Yh7OP/YCZkN6AOccgBud7JxU\n726sDIYq1n3VLpE9mUzimWeewaJFizBjxgzccsstOPjgg229VkJITlAkJe7FLJPUjGKIpHSNloZM\nwwSY+9cXNw9ichKZnFiVMISMLq3Skk3EkmvObYgHSNldw8Oa8pMpT9cJIpYRcW8Lz5qF4KpV2P/c\nc6gaN84x10cyI7v/0jmcS7GXk2cW6LpOkd3DZHM4F9o5JIujheyREokEHn/8cSxZsgSnnXYabrzx\nRgwZMiTn1yGE2A4zSQnJBbuzRmXXKDPZ+iNnFIVCoX65f+Lz84KgkC9GIaK6utpRD7huI10Om6qq\nqQcsTdP6iPReONQwTvMNBoOoqalx/ftyOpmyJmWxGnDH4ZCZyO61/GO3ky5P1ywzvJwOZ2NOZOCz\nz+Dbvx+Bnh7oDqx9Yo5wKafLNxXrRbGmm8vZ/oqi0MleAZjlm5rl1IuBssbIpXSIPaBwIFdXV+dV\nR729vXjkkUewdOlSnHvuufjzn/+M+vr6vN4rIaS00ElKHI9VJ2lnZyeqq6tTm7NcEa5RcXMVD7UA\ncn7wo2vUftK5YsSmx4vtq4xmKC+ZWqbd5jYVa1I8Hk9FM3Car7NI105YDEGhkGuUnex0abkb+XCo\n1FmTQjTr59Lq6oKyZw/0MWNs/X7EGViJv8nlENxswrhTD5dIecgWDSF+aZqGaDQKTdMKimfo6urC\n4sWL8eyzz+KSSy7BFVdcgerqarvfFiGkcNhuT9xLsUVSO7NGZQcaMyKLS6b2VaunxU5FzvajyO4c\n0gkKTh3QY1yTKLK7D6fk6cpuPwoR3qaYbfrGNYk5kQToL2KpqppyCaZr0zc6kBnzQaxidNXLz4Bi\njctnndu9ezd+85vfYMWKFfjBD36Aiy++ONU5QghxJBRJiXsRGyE7RVI7XaPGYRWcCF0+5BZ9sfkp\ndyuhVTiIyZ04cUAP1yRvU8o8Xdntx6nQlYkx/iafmpMdyIqicE0iGck0pMfn86X274FAAOFwmGsS\nyRk5ngFA6t5mrDuxzi1fvhyHHnoojjnmmH7PmTt27MDChQuxZs0aXH/99fjWt77FvTsh7oAiKXEv\nVkXSrq6ulCsh02vJzohCXaMUtJxNOrepk3ImNU3rl6PFh0f3kql9tdgOZw7QqUzsrjk55kPXdQ6H\nI/2w2qYPoE9XBB3IJF/EPkkIVwD65ZuK/Rzri6Qjl+xa2Uwze/ZstLa2Ytu2bTj22GPR0NCA8ePH\nY+3atdi+fTtmz56NM844g7VHiLugSErcS6EiKV2jRMYJOZOiHkVurSyys5a8h1kroV1uU+bWEjPM\nnH8Asravyvc3Dj4huSDXnPgncOAwOhAIIBAI8B5HciJbPEO2aAinReCQ8iEPrRQHNvnksu/btw8v\nvfQSXnjhBbz33nvYsWMHEokEGhsbMX36dDQ1NWH69Ok4+OCDi/AuCCE2Q5GUuJd8RdJiuEblAQN0\naHkDoyPGmPlXSP6a2feSBS3hGuUGvrKwI0+XghbJBWP7qshgE3Umfs/v9yMcDvP+RnLG98QTUA89\nFL3HHpvqsAkEAmnbV902/I6UDrNWaCuGBDlrMl0EjtkBEfEuxsFehdzf3njjDcybNw+JRAJz585F\nc3MzAGDnzp1Yu3Yt1qxZk/pndXV1SjBtampCU1MTBg4caOdbI4QUDkVS4l6siqTd3d3w+/0IBAJ9\nXKNiA16Ia5Rt0JVFusw/o4BltRZk1ygHMREzrObpGh3IbKkn+SAf2Ij1TewHi3FARLyLruvQVq5E\n3f/5P9AGD0bXpk1p90rGQWTp2vR5cFiZyG4/uw7/Mh0QGd2mXOu8g/wMV+hgr9WrV2P+/Pmoq6tD\nS0sLJk+enPHrdV3H1q1b+4im3/3ud3H11Vfn9f0JIUWDIilxL1ZEUk3T0N3dDQD9Nj25kK4NOp+W\nDOIdMk2YloVTeYNtllvLoSfEKka3qaqqfUQs4dJiPZFckAfoAP0dWqUcCkXcjSxoBTs6MPiss4C6\nOvT+6185vY7ZgB4g8/2VeAujoFXsfXcmsb7Y2eGkuIhnRvkgOZ+fo67rePXVV3HnnXdi1KhRaGlp\nwZFHHlmEKyZu5sknn8RPfvITbNq0CWvXrsVxxx1X7ksiuZF2Y0Hlh7gaeYNTVVWVEjiB3NwwYniO\n+LPBYBDV1dXclBMAB6Ia/H5/n0273KKfSCRSNSgcWaqqplyjNTU1rCWSE2L4hKgzkYGsKEpKxBKt\niJlyJgkB+ooQVVVVqK6uNq0VEUkjpvfKcSRyNiDFhMpF0zT4brwRwRUrEF2+HLUHH4yq446DNnMm\ntPHjc369dDUn9nbi/kqx3nsYBa3a2tqSdEak29OJmhOH2wCd9W5BDK5UVRWBQAB1dXV5i6Mvvvgi\nFi5ciEmTJuGBBx7AmDFjinDFxAtMmjQJf/zjHzFr1qxyXwqxGTpJieMxOkk1TUs9tOm6ntpgyzdD\nMzeM2QRMDs8hdiAPFxAxDwK6YUguGN3smTKQs7URsnWVyHna8j2uELINIuNa5y2UtWsRuvJKxK67\nDvu/+12oqooRXwwlSX71q4i//HLRr4HOP28hC1pOHTYo8k2NA/DsGrpI7MGuWkomk3j66adx//33\n46tf/SpuueUWjBgxoghXTLzIySefjHnz5tFJ6j7oJCXuRWw+5E1KtqxRM2eC7Ero7e1Nfa3f70dN\nTQ0zIknOGFtXg8EgamtroShKPwFLDGuigEXMkDMidV235GZXFCVVT/LrCOFKdsPQbVo5mA2Is7Mz\nIpvzz7jWyQeTrDt3oes6grfcAmXLFoRaWhC99FJUV1dDHzkSyr/+BfXKK0tyHbk6/3gw6TzEvUkc\nJtu9LtmNWK/EMFig/6BPs7WOLufSIBsTCqmleDyOpUuX4uGHH8bpp5+O559/HoMHDy7CFRNC3ARF\nUuJoxMPef/7nf2Lq1KmIRCIYOXJk3sKSEA/EgCexaYtGo/1cCRRNSTqMg5jC4XC/eslHwKIrofIw\ntkEXOqjCKCZQrK8cijH0xArZ1rpEIoFoNAqAApZbkKeLV3d0AACU3l6EQiEAQHTz5nJeHoDc2vTz\nHbpICsd4ABgKhVwbQZRprRM1J691hcxIIP2Ru7bEAWC+tdTb24uHH34Yv//973H++edjxYoVqKur\nK8JVE7czc+ZM7Nixo9////nPf44zzzyzDFdESgFFUuJ4FEXBOeecg5UrV2LOnDnYvn07DjvsMDQ3\nN6O5uRnHHHNM2oD3zs5O/O53v8O4ceMQiUQQDAYRDodNNytyW00sFkNPTw8zsEgK4+YsGAzmnHmU\nScASwilbCL2P3FIv2qCLlcWWi1hPAcudyIc2fr+/ZLl+mTBb6+R7LAUsh7F/P/z33w/11FMRHT++\nT3Zt8ogj4H//fcDhP5dsAhYzdUuL3GmjKErJDm1KjbzWiUME48Gkqqqpr2NHR+7I+28htMsDB3Oh\ns7MTDzzwAJ577jlcdtlleO211xAOh4tw1cQrLF++vNyXQMoARVLiaBRFQSAQwNe+9jV87WtfA3Bg\n87Flyxa0tbVh8eLFePvtt1FbW4umpibMmDEDTU1N2Lx5MxYvXoxnn30WX/3qVzFt2jTU1dVlbV0V\nE6OB/gMr6ISpTGSnnxiek+/mzIj8UCdaumQhQWyuKdZ7A9mdBZRvQFyublO2SzsPsU4IkTufQ5tS\nkq51VRawotEodF3vJyQ49T15Cd/jjyPwk59Af/llaE8/3UdoT7zxBtQ33oA+YUKZrzJ3rLTpU8Cy\nF13XEYvF+gjtxZxU70TocrYHec9UqND++eef495778Wrr76Kq6++Gq2tramfDyF2kGXOD3EZHNxE\nXI+u69izZw9effVVLF68GK+//jqqq6txwgkn4MQTT8Qpp5yCQw891JYHLTmLyDgQim2r3iGX4Tml\nuBZj3Wma1mdj7UV3hpcwttQHg0HH/8yMAhbdps7AKLQX4qhxIsZBZByUUjx0XUfVPffA98wz6Pzx\nj1H/0EPQzjsP+llnlfvSSopRwJIH9FDAso48qV64KsvtaHcymYaRyffZSjyctDM6Zvv27bj77rux\nfv163HDDDTj33HNZl8Q2/vjHP+KGG27Arl27MHDgQDQ0NGDZsmXlvixinbSLCkVS4no2btyIRYsW\n4Xe/+x3+7d/+DbNmzcKpp56KN954A+3t7Whra8NHH32EQw45BM3NzYhEIpg6dWofR0u+yG2r8lAp\nPtC5E7NBTMFg0HE/v0xCAt2mzsA4pMKuyeLlIt2kX7pNS4NZdm0liNTGSJJ0QgIPJ60jZ0QOnToV\nvu3bkbjlFqj//d/lvjTHYBSwVFWlyzkN8nTxQCCAUCjEzyVPzO6xAEzvs15EFkfljPZ8+PDDD7Fg\nwQJs2bIFs2fPxje/+U3Pfm6EkLyhSEq8RTQaxZNPPolFixZh69atuOKKK3DllVdizJgxpl+v6zo+\n+ugjtLW1oa2tDf/4xz8QCAQwbdq0lHA6ZMiQgm+g6R7o6PpzNsI1Go/H+zgg3PJzMrpNVVUFAFNH\nAikuZi31ThTa7YBu0+IjWuqFAOFmod0uzA4nAdZdNszcWTXXXAP/448jfv/9SF50Ubkv0dEY3aaV\n3qYvTxcPBoMIhUIV895LhTicNK53srveC3UnHwIW6kJ+9913MW/ePOzevRtz5szBiSee6OrPhhBS\nVCiSEu8Qj8dxxBFH4JhjjsGsWbNwxhln5Jwro+s6uru7sWbNGrS2tmLVqlXYs2cPjjrqqJRoOn78\neNta9M1cf/JEc7qvSo/sphGDmILBoGccEEaxnnVXXORWw0py+smkc5uybTU3zCb4elVot4N07dJm\n06Ur8TM0tkGLuA8AQDIJ5ZNPoB96aHkv0oUY605V1X5Zzl6rO+MAHS8fAjqVbO56N9WdnRENf//7\n3zFv3jzouo6WlhY0NTXZfLWEEA9CkZR4i88//xxDhw619TWTySTeeuutlNv0vffew7BhwxCJRBCJ\nRDBt2jRbhqzQfVVejIOYvDpx1Qjrzn6Mw3PYatifTHVHl3Nf7Mxhq3TM2qWBymlbBdgGXQ6s1J0b\n2/TtHKBD7Mdt8RCyOFro2rRy5UrccccdGDhwIFpaWnDsscfafLWEEA9DkZSQXNF1HTt27Ejlmq5f\nvx6apmHq1Klobm7GjBkzMGLECFtEU9l9JbsRjO4rkh9mYlalt61azZhk3fXHmF3rteE5xSaby9kt\nLhi7kIfE9XP6EdtIV3deynKWnX61t9+OwLZtSDz8MJS6unJfWsWSbRiZkw8ozTIinXqtpC9m7nqg\nvAfj8sFNId1buq7jL3/5C+68806MHTsWc+fOxbhx44pwxYQQj0ORlJBC0XUd0WgU69atQ1tbG1au\nXIkdO3bgsMMOQ3NzM5qbm3H00Ufb8nBrFK9UVfXcw1wpcMsgJqeQzvVXqZlrRmQxiw+M9pHNfeVF\nt6lxsJfX4j7cgDHLWW5bddsBpTELORQKYeDo0VC6u9G7bh30iRPLfIVE4IY2fTszIokzSBdLUopn\ni2QyiWg0WnB+raZpeOGFF3Dvvfdi6tSpuPXWWzFq1Chbr5UQUlFQJCWkGGiahi1btqC1tRVtbW14\n++23UVdXh+nTp6O5uRlNTU2or6+3bSAUB/NYQ4gPopVHuEb5+eRGtoe5SpgsbXQhU8wqDV51m5qJ\nWXQhO4d006WdelAki1nGgxtfRwfw6afQvvGNcl8myUK2WJJSCfbyQSAjGrxPpoMiYyxJPmuePNyr\nkGxtVVXx1FNP4YEHHsCJJ56Im2++GcOHD8/5dQghxABFUkJKga7r2LNnD1auXInW1lasWbMG0WgU\nxx57LCKRCJqbmzFmzBhbB0LJm5tKbpX2+iAmp2CctCq7nOW6c4qIkC9sqXcWbs+YNIpZoqXeqddL\nDmDF9VeOIXjGiAY6/bxHKdv0jZPquXeqXIx7vFwFe+Nwr0L2TrFYDL/73e/wyCOP4IwzzsB1112H\nQYMGFfT+CCFEgiIpIeUikUhgw4YNaGtrQ3t7Oz766COMHDkSzc3NiEQimDJlCoLBYMHfJ1urtFfE\nKyMUH8pLpkmrbmtZBczzIZ3kHCNf4oaMSdnVLsQHilnuplzDyBjRUNnYPdVcFrM0TSvI6Ue8jRXB\n3ufzpdrqgcIOlnt6erBkyRI8+eSTuOCCCzBr1izU1tba/bYIIYQiKSFOQdd1fPjhh2hra0NbWxv+\n8Y9/IBgMorGxEZFIBJFIBEOGDLGtRT+TeOVWMZGDmJyNcRCZE8UrGbbUe4N0rYOyWF+KNc9MfAgE\nAqwnjyKG4BVLsDc6s5itTQRW2vSNax4jP0ihGJ8vVFWF0BP8fn/qV65r3r59+3D//ffjxRdfxOWX\nX47vfe97CIVCxXobhBBCkZQQp6LrOrq6urBmzRq0trZi1apV2Lt3LyZMmJBq0T/yyCNtecB2m3hl\nRNO0VEs9wM29W3CKeGV2XcKFrCgKgsEg68ljZHLA2L3myZOgfT4f66mCMcZDmK152Rz2xnoKhUKu\nPdgkpSOTw17sAX0+H8LhMOuJ5I3Z+gT0vefKxoxXXnkFU6ZMMR20tGvXLtxzzz14/fXXcc011+DC\nCy+0ZQguIYRkgSIpIW4imUzirbfeQmtrK9rb27FlyxYMGzYs5TSdNm0awuFwUQdCyQ9z5d5EC5cf\nBzF5h3TiVSkG84iW+ng8nqonbsgrAyuCfa7xEGYRDawnYsQ4WdqY5yx+yYc3YhgT64nkixz5Ie6n\nuq6XPVeXuBNZHM22Pok1r6enB5dddhnWr1+PYDCIhoYGNDY2Yvz48Xj99dfxzjvv4KabbsI555zD\njgtCSCmhSEqIm9F1HTt27Ei16K9fvx4AMHXqVEQiEcyYMQMjRoywZYNrFBDkgVClnGZuHMTEllVv\nk20wT6E5f8YWaLbUE0G2vDWztkHmQ5JCSReJA6CfE5niFckVTdNS4qhxuJeV4Tx0mRIZOf8/32Fx\nmqbhgw8+wIoVK/DKK6/grbfewvbt23HYYYdh+vTpiEQimD59OiZNmmTLrAZCCMkCRVJCvISu6+jt\n7cW6devQ1taGlStXYufOnTj88MNTounRRx9tS0an2WZaUZSiTTOXXVkcxFTZpGsbNGbqZqoNEdHA\nFmhilXRuU7HmAUi5spgPSQrBLF/b7/f3OTACnNfdQZyLOLxRVRWBQAChUCjr4U22XF0vD/8kmckk\ntufK22+/jfnz56OzsxO33XYbTjjhBKiqio0bN2LNmjWpX++//z4mT57cRzg94ogjWHuEELuhSEqI\n19E0De+9916qRf/tt99GfX09pk+fjubmZjQ1NaGurq5oA6EKyZc0e1C0srEnlUWmIRVGAUFuMRT1\nxMFeJF/E1F5VVaEoCnRdp4BA8sbq8BwhXhm7O0oVTULcgdHZbsek+myHRWzT9zayOFronnzDhg34\n9a9/jaqqKrS0tGDatGkZv767uxvr16/vI5zefvvtmDVrVl7fnziXl156CTfddBOSySSuvPJK3Hbb\nbeW+JFJZUCQlpNLQdR27d+/GypUr0dbWhjVr1iAajWLSpEmYPn06ZsyYgTFjxtjWop8pXzLdRlpu\n36HLj+SKUUBQVTXVrgog5Xpgnh/JF1lsF65RkRtpdlhkFOx50ENk5Htevp0SZtEkuq4XlKtL3Ikc\nI6PretGHWWZr0y80FoeUH9mJXGiMTFtbG+644w4MHToULS0tOProo/O+Lk3TuKZ5jGQyiaOOOgor\nVqzAyJEjoPa5MAAAIABJREFU0dTUhKVLl2LixInlvjRSOVAkJYQcaBHt6OhIteh/9NFHGDVqFJqb\nmxGJRDB58mRbcoAyOf7EBlpV1T7tYHT5kXyRhQdFURAIBACgz0OcUUDgQxxJR775tUbHn3EwD92m\nlYtxuJfd97x8cnWJe5GdyIqipA4DS/3zzeR0Zu25C3HPExnboVAor5+ZrutYvnw57rrrLhx55JG4\n7bbbcPjhhxfhionbWblyJX7605/ipZdeAgD84he/AADMnTu3nJdFKou0ixztNYRUEIFAAJFIBJFI\nBMCBzcyHH36I1tZWPP7442hpaUEoFMK0adNSwungwYNz3igpigK/3596GBSuq1gslmovBJByu2ia\nBkVReEpMcsLYUl9bW9tPeJAdf0KooOOPmCFPFRd5o7m4soRAL0R6o9tUrr1SD8Ij5cEoPNTV1RXl\n5+3z+eDz+Vh7HkfXdcRisZQTubq6uqyHfqJDSD5cN7bpp6s9tumXH7OYhpqamrx+Lpqm4bnnnsN9\n992HadOm4ZFHHsHIkSOLcNXEK2zbtg2jR49O/feoUaOwevXqMl4RIV9CkZSQCkZRFIwdOxZjx47F\nxRdfDF3X0dXVhdWrV6OtrQ2//e1vsXfvXkycOBGRSATNzc0YN25cTg9WqqoikUikBjHV1NSk2p/l\nTbTsupIf4LiJJjLCQSMevEKhEMLhcNqalIeMya+RrvbofKk8jIMp7BIe5NoTIoKx9uh09h5GJ3Ih\nwkO+pKs9WTTlUCj3YFyjzA4EnYKVey7b9MuLWUxDvmuUqqp44okn8OCDD+KUU07B008/jWHDhhXh\nqonX4N934mQokhJCUiiKggEDBmDmzJmYOXMmgANuvY0bN6K1tRW/+tWvsGXLFhx00EEp0fS4445D\nOBzuc7NLJBL405/+hPvvvx8XXXQRLrjgAlMHjZnrSrThR6NRANxEkwMY82sLaS/MxfFnzNUl3sDo\noAkEAkVz+clkqr1Mris6/pyP0YlcrhbodMgdHkD/2kskEkgmk33Eeh5WlhfjpPpSrFHFwGzdk4XT\naDTap02fB+XFwerAOCvEYjE8+uijePTRR3H22Wdj2bJlGDhwoN2XTDzMyJEj8fHHH6f+++OPP8ao\nUaPKeEWEfAkzSQkhOaHrOrZv3462tja0t7dj/fr1AICGhgaMHz8e//znP7F06VKMGTMGV111Fc49\n91yEQqG8vpdxMIrxAU44/oh3EaKlcXBOscmU8ccHOPdifEgUNeWkn2O64Sh0mzoT4zAmNw+LMxsK\nBaDffZe1V1yMMQ2FDM9xC8bak4fh8cCoMOzMsN2/fz8efPBBPP3007joootw1VVXoaampghXTbyO\nqqo46qij8Morr+CQQw7B9OnTObiJlBoObiKEFAdN07B8+XL88pe/xKpVqzBt2jRUV1dj2LBhiEQi\nmDFjBiZOnGiLsJVuIJTs9qNw5X7klnpd1x0hZBlz1pLJJHRdp9PZJdgxVbxcGB1/qqpSPHAARpdf\nqQ5wSo3ZYSUPjOzHLKah3Pe9ciOve/KBESMirCHc7bFYLHWAk+/ntXfvXixatAgvv/wyrrjiClx2\n2WW2DHollc2yZctw0003IZlM4oorrkBLS0u5L4lUFhRJCSH20tnZiUcffRT33nsvNE3DD3/4Q1xy\nySUYOHAgNE3D5s2b0draivb2drzzzjuor6/H9OnTMWPGDDQ2NqKurq7gja2xTVp2HrBN2n24TchK\nJx4YB0I59forAeNwL7unipeLdG5TigfFxRjTUCkuPxmzAyMOw8sfO1ugvY7xwIiivTnGAV+FuNs/\n/fRT3HPPPWhra8O1116LCy64wLVOeUIIMUCRlBBiDxs3bsS9996Lxx9/HKeeeiquvfZanHjiiRk3\npLquY/fu3Whvb0dbWxvWrFmDWCyGyZMnp4TT0aNH27KplXOu2CbtfIToIAYoudmRla1VlW7T0mB0\nZFWCkJXNbSofGLH+codCVmbSOf4YEZEe2eVXaM52JZOpTb/SRHv5oNnv9xd0KLht2zYsWLAAGzdu\nxM0334yzzjqrIj5DQkhFQZGUEFI4yWQSzc3NOOOMM3DVVVfhkEMOyfu14vE4Ojo60N7ejvb2dnz8\n8ccYPXp0aiDU5MmTUyH/hWB0vcjCFR1X5cMN2ZB2YCVXl8KVPRgH5wSDwYoWstLFk3Dtsw6FrPyg\naJ8eL2XYOpVKa9PXNK1fx0S+gub777+PO+64A9u2bcOPfvQjfP3rX/fM50QIIQYokhJCnI2u6/jg\ngw/Q1taGtrY2vPHGGwiFQmhsbERzczMikQgGDRpky2bN2CooC1fM9ysubmuptxsKV/YjPyAWmrvm\nZYwTpSnap0euqUIdWeQAmda+SnDaG4Ust3ZMuJFMbfpujscx5iIXIo6+9dZbmDdvHnp6ejB37lwc\nf/zxNl8tIYQ4DoqkhBB3oes6urq6sGrVKrS1tWHVqlXo7OzExIkTUy36RxxxhC1iplm+n6IofR7e\n3LZ5dhLGHD8+IH6JUbjiUB5rmNVUIQ+IlQpF+76oqton+oM1VTzE2uf1oVCykFUJ0R9uwc1t+nbW\n1Lp16zB//nwEAgHcfvvtaGhosPlqCSHEsVAkJYS4H1VVsXHjxpTb9J///CcOOuigVIv+cccdh1Ao\nVLSBUPLGuZLcj/lSKS31dpNuKA/z/b6sqXg8Dl3XWVM2k85t6nbHVSY4Vdw5pBOujGufE4UrGeMh\nDmvKHRjdpqqqQlEUx9x7xTpVaE3puo7XX38dCxYswIgRI9DS0oIJEyYU4YoJIcTRUCQlhHgPXdfx\nr3/9KzUQqqOjAwDQ0NCA5uZmNDc3Y/jw4ba16BsdV7JwwDbVL2H7s72kE+3d4HixCzmmgdmQpcWr\nbdLMsHUHZsKVcJs6QbiSMR7icMCXu3FCm75Yf6PRaMGHOLqu4+WXX8bChQsxYcIEzJkzB2PHjrX/\nogkhxB1QJCWEeB9d19Hb24s1a9agvb0dK1euxKeffopx48YhEolgxowZmDBhgi1t3mxT7Qvbn0uL\n0e1nFA68EhEhakoeSMGYhvJjNpDMLW5Ts8E5lbRWu51Mh0ZG0b5UP1Oj4M5DHO9idDurqgpd1213\nO8sO90IF92QyiWeffRaLFi1CJBLB7NmzcfDBBxd0fYQQ4gEokhJCKhNN0/Duu++mWvQ3bdqEAQMG\npHJNGxsbUVtba0uLfrpsSS+7/eSHQwB0zpQJL0VEiL9H8XgcyWSSOX4uwEw4AJzlNpUFd1FTFNy9\nQbqIkmIfWuq6jlgsxkn1FY6dbfrGmKJwOJz3vTuRSOD3v/89HnroIcycORM33ngjhg4dmvPrEEKI\nR6FISgghwIEN6Oeff55q0V+7di1isRgmT56ccpuOGjXKloepTG4/tw+lSCaTiMfjbKl3MOkiIpxa\nfxTcvYUT3KZGhzsF98qg2Nm6cqSM3++nw530wdimbxzIaFZ/sjhaqBs5Go3if//3f7F06VKce+65\nuOaaazBgwAC73yYhhLgdiqSEEJKOWCyGjo4OtLe3o729HZ988gnGjBmTcptOmjQJgUCg4O8jNs6y\n2xRwltsqE3T4uRun1h8zbCuDbG5TO93ORjcWBXdipf6ydXvIU8UZKUNyIV2bvhDXk8kkqqqqUs7R\nfOju7sbixYvxzDPP4OKLL8aVV16J6upqO98GIYR4CYqkhBBiFU3T8MEHH6Ra9N98802EQiE0NjZi\nxowZmD59OgYNGmTrQCjZ8WIUDcr9EEaHn3cpp9tPCO4UHCqXdPWXr9tZrFWxWIwDvkhWMrnt5fuv\n0Y0cCoVYU6QgdF1HNBpN5diKOstnKNnu3buxaNEirFixAldddRUuvvhiBIPBEr0TQghxLRRJCSEk\nX3RdR2dnJ1avXo3W1lasXr0anZ2dmDhxYqpF//DDD7dF4Ek3EEoIBqUcyCO31Pv9/lSGHx8OvUsm\nt5Ud2X7G6c/CjcyaIkB/t7PVbF22PxM7MGY7C7cfcGANDAaDjji4JO5FHhxnXKvM2vR37dqFSy65\nBI2NjWhsbMT06dMxbtw4+Hw+7Ny5EwsXLsTq1atx3XXX4fzzz+e6Rwgh1qFISgghdqKqKt58882U\n23Tr1q0YPnw4IpEImpub0dDQYIvbJNMkX1k4tUtkYks9MWIUrczcztkmScsPhnT4kVzI5PYT7itV\nVVMOP65VpBCMUQ3i/ievfwDyGspDKhf5ICeXzolYLIbVq1djzZo1WLduHdavX4/e3l6MHj0a+/bt\nw2WXXYbrr78ew4YNK8G7IIQQT0GRlBBCiomu69i2bVtqINSGDRugKAoaGhrQ3NyM5uZmHHTQQbYP\nhLJrII/cUq8oCoLBIFvqiSnp3M5mblPhRo7H46kHQzpdSCFompYSsXRdh6Io0HW9n2hFsZTkghzV\nkCkb2ej2Mzs4ctpQPFI+7Myxfe+99zB//nzs3bsX06dPR1dXV0o8HTFiBCKRSOrX1KlT2XJPCCGZ\noUhKCCGlRNd19PT0YO3atWhra8PKlSvx2WefYdy4cSnRdMKECbYIRpkG8mRrkWZLPSmUdJN8BaKl\nMN9hFIQAmYcxWc2W5LpGjGRqf7ZKpoMju4eSEXcgi6OFduS8+eabmDdvHmKxGFpaWtDc3Nzve73z\nzjtYvXp16teWLVswadIkRCIRfP/738fUqVPteFvEgVx++eV44YUXMHz4cLz55pvlvhxC3ARFUkII\nKTeapuHdd99Fa2sr2trasGnTJgwcODCVazpt2jTU1tbaNhAqU4s0AMTjcWiaxpZ6YguyG1nX9ZSA\nZdaiStGKWEUWsTI5/GTSZZsaD4645lUussu9GFENdg8lI+5AVdXUkK9QKFRQ5vaaNWswf/581NTU\noKWlBVOmTLH8Z7u7u7F+/XqsXr0aJ554IiKRSF7XQJzP66+/jrq6Olx66aUUSQnJDYqkhBDiNHRd\nx65du1It+mvXrkUikcDkyZNT2aajRo2yrUU/kUggkUiknKaKolC0IgVjRcSykq1L0YrI2B3VYGyR\nVlWVbtMKRBaxSnlASOHeu4gIpFgsBk3TChJHdV3Hq6++ijvvvBMjR45ES0sLxo8fX4SrJl7igw8+\nwJlnnkmRlJDcoEhKCCFuIBaLoaOjI9Wi/8knn2DMmDEp0XTSpEkIBAI5vaZo+xIDA0RLvZlolW2K\nNCECMeBLZK2JurKKnK1rFK3otKpMRNtyKUQsCveVg50ilp2YCffy4SWHQjkbua50Xe8TAZLPay1b\ntgwLFy7Escceizlz5mDMmDFFuGriRSiSEpIXFEkJIcSNaJqGrVu3oq2tDW1tbdi4cSPC4TAaGxsx\nY8YMTJ8+HQMHDuy3KU8kEnj22WexePFi3HPPPTjkkEOyig3pcv1kt2m2KebE2whHsohqsFNsSOe0\nonDvfeS60nU9JY6W+medSbin29R9ZMqxdSLp8p3Nsk2d+h4qAbmuFEVJZW7n8zNJJpP44x//iPvv\nvx/HH388Zs+ejREjRhThqomXoUhKSF5QJCWEEC+g6zr27duH1atXo7W1FatXr0ZXVxeOPvpoRCIR\nHHXUUVi+fDkeeughjB49GrNmzcJ//Md/5DXlNJcp5sTbyJOffT5fQQ+FuZBpIA/dpu6nXHVllUxu\nU2MNEufg9LrKhWxDoUQNuvG9uQ076yoej2Pp0qV4+OGH8c1vfhPXX389hgwZUoSrJpUARVJC8oIi\nKSGEeBVVVfHEE0/grrvuwoYNG9Dc3Izhw4ejoaEBkUgEDQ0NCIVCBT9E6brex2klu1zYnupNRC5k\nIpHIe/KznRjdpiJfl4KBu9A0LRUB4vf7EQwG4ff7y31ZljC6TY1DyXh4VD7M8pHdUldWEfdhDoUq\nHbI4Wmhd9fb24uGHH8bvf/97fOtb38LVV1+N+vp6m6+YVBoUSQnJC4qkhBDiNRKJBP7whz/g7rvv\nxscff4xrr70WV155JYYMGYJt27ahra0N7e3t2LBhA3w+HxoaGtDc3IxIJIKDDjrIthZp5kp6C/Ez\njcfjJR9ukg/ppkgzJsJ5iLxRkWNr90TxcpCtRZpu0+JjFN3LfZhTamS3abqoEtZg7ui6jlgshng8\nXnBddXZ24oEHHsBzzz2Hyy67DJdffjnC4bDNV0wqkQsvvBCvvfYaPv/8cwwfPhw/+9nP8P3vf7/c\nl0WIG6BISgghXmHnzp1YtGgRFi1ahPHjx+P666/HWWedldbZoOs6enp6sHbtWrS2tmLlypX4/PPP\nMW7cODQ3N6O5uRlHHXWULQ+VdPq5F7fl96WDMRHOwqlDc4qJmdMPoNvUbrwoutuF2VAoOV+XNZge\nO0X3zz//HPfddx/++te/YtasWfjud7+b8/BNQgghRYEiKSGEeIFt27Zh0qRJOP/883Hddddh0qRJ\neb2OpmnYtGkTWltb0d7ejk2bNmHQoEGIRCJobm5GY2MjampqbHmAMnP6GQdR8MG2fJi1qHrp4dkY\nE8EaLA1eEd3tgG5T+xACdCwWQzKZrAjR3Q6s5utWsuteFkcLFd23b9+OhQsXYu3atbjhhhtw3nnn\nVZS7mRBCXABFUkII8QpdXV22Z1jpuo5du3alWvTXrl2LRCKBKVOmpITTkSNH2taib+b0k9uj2aJf\nfIwurGAwWDEPcdlqkC6r/PG66G4X6dymdDybIzuSdV2vaNHdLliDB5DvhYXGy3z44YdYsGAB3nvv\nPcyePRunn3665z8/QghxKRRJCSGE5EY0GkVHRwfa2tqwcuVKbNu2DWPGjEm16B977LG2tI1lcrgY\ncyVJYVRi67MV6PQrHKcN+XIbxhpM53iuNKef7EhWFMXVk+qdTjrXvZzx7KWc8WQyiWg0msreLmTA\n5bvvvov58+dj165dmDNnDk466SRPfEaEEOJhKJISQggpDE3TsHXr1lSL/ptvvonq6mo0NTWhubkZ\n06dPx8CBA20fCCX+yYFQ+SNP5/X5fBQaLGB0WRkz/eh47t/67PQhX26jkvN1zSaKe/W9OhnjUChj\nzrgbh0KJg0I74hr+/ve/Y968edA0DS0tLZg+fbrNV0sIIaRIUCQlhBBiL7quY9++fVi1ahXa2tqw\nevVqdHd34+ijj0616B922GG2PDxlGgjldbGgEIzuvmAwmHbAF8mMFcez28SCfDG2PgtxlH//iovV\nfF03u00rfVK9GzC67uVDTKceINkd17Bq1SrMnz8fAwYMQEtLS9758IQQQsoGRVJSOj7++GNceuml\n+PTTT6EoCn7wgx/ghhtu6Pd1N9xwA5YtW4aamhosWbIEDQ0NZbhaQoidqKqKN954I+U23bp1K77y\nla+gubkZkUgEDQ0NCIVCtnwvWTQ1igWV3B5Nd1/pyCQWeNHxTEey8/CK25ST6t2L1aFQ5fh5CnE0\nGo0CKGyAnK7r+Mtf/oI777wTY8eOxdy5czFu3Di7L5kQQkhpoEhKSseOHTuwY8cOTJ06Fd3d3Zg2\nbRqeeeYZTJw4MfU1L774IhYuXIgXX3wRq1evxo033ohVq1aV8aoJIcVA13V88sknqYFQGzZsQFVV\nFY477riU23TYsGG2DoSShVNFURztbrETThMvP0bHsxALZLHKjaKi2TAmOpKdidtyJeXWZx7oeAez\nGgRKNxzPzixbTdPw4osv4p577sGUKVNw6623YvTo0UW4akIIISWEIikpH+eccw6uv/56nHrqqan/\nd/XVV+Pkk0/GBRdcAACYMGECXnvtNYwYMaJcl0kIKQG6rqOnp+f/s3ff4VGX6f7H3zOZZEIKhCCh\nlwAS6QRIMkGxHBcVlaKyAjYsICoeBQUXXH67R49dqgiIugi4NqyLGlBRQTOTQhEEaQJSpUoNIVO/\nvz+4Zs4kEMBk0j+v6+LSkCnPJA+TzGfu577Jzc0NDIT6448/uPjiiwPVpklJSSE5XllcdUtVD6yK\nKhpg+Y/UV/XHVV0UV21aGQOrolTdVz2cr6+kfy+W1x7UALma50IGk4XiubBotXtkZGSJ97bH4+Hj\njz/mzTff5PLLL2f06NEkJCSUeG0iIlKpFPuDQWUAUqa2b9/OTz/9RFpaWqG/37NnT6F3YZs2bcru\n3bsVkopUcyaTiejoaK666iquuuoq4HSItGHDBjIzM5k+fTqbNm2ibt26gUrT7t27ExUV9adf5ARX\nkUZERATuy//izOl0kp+fXyiwqkr9/PyPwe12ExERQXR0tHr3VUJmsxmz2Ux4eDhw5vFo/zHQigqs\nivIHWC6XK1DdFxMTo3C0CjOZTFgslkLVv8FvIPknfJd1eK9q95or+OexX/BzodvtLtVzYdFBX1FR\nUSWudne5XLz77rvMnz+fG264gS+//JK4uLgS3ZaIiFQ9CkmlzOTl5TFw4ECmTZtGTEzMGZ8vWsWs\nX5JFaiaz2UyHDh3o0KEDI0aMwDAMDh48iN1u59tvv+XFF1/E7XbTtWtXUlNTSU9Pp3HjxiV6zjhX\nYFX0RVpl7Od3tgqsyMhIBVhVSEkCq/II788WYJXkzQmpGsozvD9bdZ+q3SX4udDfq7y458Li+jwH\nn6SwWCylerMwPz+fuXPn8uGHHzJo0CCWLFly1tcvIiJSvem4vZQJt9vNjTfeSJ8+fRg1atQZn3/g\ngQe48sorGTx4MKDj9iJybgUFBaxcuRKHw4HD4eD333+nRYsW2Gw2bDYbHTt2DEmPxKL9/DweT6WY\nYF40ZIiIiFAFVjVWnsN4DMPA6XSqXYOcoWi7kj9bbapetlJaxfV5DgsLC3zOYrEEjtWXxLFjx3jj\njTf48ssvueeee7jnnntCNmBSREQqLfUklfJjGAZDhw6lXr16TJky5ayXCR7clJ2dzahRozS4SUQu\nmM/nY9u2bWRmZuJwOFi3bh1RUVGkpKRgs9lITU2ldu3aIQuRgl+geTyecptg7vV6cblcuN1uLBZL\nIMCSmqW4YTylmR7t8/kC7Rr8lVxq1yDncr7epv696A/e3W434eHhREREaG9JSPh8PgoKCnC73YGf\nu/4hjX92KNShQ4eYOXMmy5Yt48EHH+S2227Tz1cRkZpDIamUn8zMTC6//HI6d+4c+AXlueeeY+fO\nnQCMGDECgIcffpjFixcTHR3NW2+9Rbdu3SpszSJStRmGwbFjx8jKysJut5OTk8PJkyfp0KFD4Ih+\ny5YtQ1IBWrSyJdRDUPxBhCY+y7n490lwcArnnx6taeISSsHVpv7KeyBwlD88PLzSDiaTqiN4iFzR\n562iQ6E8Hg+bNm1i9OjRpKSkBN48bdGiBWazmb179zJt2jRWr17No48+yk033aTnQBGRmkchqYiI\n1Cwej4c1a9Zgt9ux2+3s2LGDhg0bYrPZSEtLo2vXriE7Une2Y6lFq6vO9yKsaE9I/wtBhQtyIc4W\nFPiPpfqr+DweD4ZhaJq4hMzZ3tSxWCyFKk79R6KDnw+19+RCFH1Tx2q1XtDeOXXqFDk5OeTm5rJ8\n+XJWrFiBYRg0btyYvLw8hg0bxsiRI4mNjS2HRyEiIpWQQlIREanZDMNg9+7dgdD0p59+wmKx0L17\nd9LS0rDZbNSrVy9kR/TP1lMyeBCPv7qqaN8+9YSUUPEfTfWHo0ChY6nB+1DkzwgeIucP3ovrk1w0\nvD/fMB6p2YoG76V9U2fDhg1MnDgRp9NJcnIyR44cITs7mzVr1tCmTZtAb3ObzUZSUpKqSkVEagaF\npCIiIsEMw+DkyZPk5uZit9vJysri8OHDtG3bNhCahuoFU3CVnz8k8Pl8mEwmDMMI9IRUPzQJhbMN\nzPFXk55tH1b0YDKpOvxD5FwuFyaTKfC89WcCrHMN49E+rLn+TPB+IX766ScmTZqEyWRi/Pjx9OjR\no9DnXS4Xa9asITs7O/Dnjz/+IDU1FZvNxpAhQ2jXrl0oHppUYrt27eKuu+7iwIEDmEwm7r//fh55\n5JGKXpaIlD2FpCIiIufj9XrZsGFDoNp08+bNxMfHk5aWRlpaGj169KBWrVql6jcafHzQX8kXPDla\n1VVSUsF9+y50YI6q/ORC+IcxldWk+nPtQ1U9V29FW82UNhy12+1MmTKF+Ph4xo8fT4cOHS74ugcP\nHiQnJ4fs7GyuvfZaevXqVaI1SNWxb98+9u3bR9euXcnLy6N79+589tlnCshFqj+FpCIiIn+WYRgc\nPHgwEJquWLECr9dLly5dSEtLIz09nUaNGp33xdzx48fZtm0brVu3xmQyERERccaLwHMNhAqurlJI\nIMFCPeiruCq/4CP62oc1h8/nC0yq91e8l8ek+uKq71VtWn0Eh6MlrUoOvq0lS5bwyiuv0Lp1a8aN\nG0erVq3KYNVS3Q0YMID//u//5uqrr67opYhI2VJIKiIiEgoFBQWsWLECh8OBw+Fg7969tGzZMhCa\ndujQIVBhtW3bNmbOnMn777/PHXfcwTPPPPOnAqaiYVXwQKjgKj+peUJdfXUuZxtMZjabzwirFJxW\nH0Wrkq1Wa4U/1wRXm/r3o6pNqx5/ywan01moHUhJvm8+n4/PP/+cWbNm0b17d8aMGUOTJk3KYNVS\nE2zfvp0rrriCX375hZiYmIpejoiULYWkIiIiZcHn87F169ZAtem6detwuVyEh4ezefNmBg8ezMiR\nI0lMTCz1ffmrBoPDKpPJpJCgBgkOGMxmc6mqr0qzhqJhFXBGgK99WPUUnSZemqrksqZq06ollC0b\nPB4PH374If/617+46qqrGDVqFPXr1w/xiqUmycvL48orr2TChAkMGDCgopcjImVPIamIiEhZcrlc\nLFiwgKlTp3Ls2DH69OlDTEwMy5cv5+TJk3Ts2JHU1FTS09Np0aJFmQ6ECg4IyjtAk7JRUceeL9TZ\nqk39ezB4H2ovVj5FB+b4w9Gq+L3yPxZVm1YewYPkSvvc5XQ6eeedd/j3v/9Nv379GDlyJHXq1Anx\niqWmcbvd3HjjjfTp04dRo0ZV9HJEpHwoJBURESkLBw8eZPbs2cycOZMOHTowatQo+vTpUygEdbvd\nrF60+hO+AAAgAElEQVS9GofDgd1uZ8eOHTRu3Ji0tDRsNhtdunTBarWGZD3FDUAJ7impsKrq8Hg8\nuFyuSnXs+UIEV5v69yGox25lUp4tGyrKuapN1bakbAW/sXOhg+SKc/LkSd566y0+/vhjhgwZwv33\n309UVFSIVyw1kWEYDB06lHr16jFlypSKXo6IlB+FpCIiIqG0adMmXn75ZT7++GMGDhzIo48+SseO\nHS/ouoZhsGvXrsAR/TVr1mCxWOjevTtpaWmkpaVRr169kIQVCquqnuDKPp/Ph9VqrbKVfX6GYRSq\n8vN4PAqrKkgoe0JWRWdrWwIUej6sSV+PUPN6vbhcrkA4Wpo3do4ePcrrr7/O4sWLuffeexk6dGjI\n3lAUAcjMzOTyyy+nc+fOgX/zzz//PNddd10Fr0xEyphCUhERkVD6/PPPWbNmDSNGjCh1LzTDMDh5\n8iS5ublkZmaSlZXFkSNHSEpKClSbtm3bNmRH9IsLq9THr2L5wyuXy4XJZCIiIqLaVfYFU1hVvkJ5\n7Lk6Ca42VYBfcsHDvkrbz/bgwYO8+uqrOBwOHnroIQYNGlTi/qUiIiJnoZBURESkKvF6vaxfvz5Q\nbfrrr78SHx8fCE27d+9OrVq1QlZtWlwfv+CAQGFV2QgOr2piZZ+fBvGUjVBW9tUUCvAvXPCwr9JW\nve/Zs4dp06axdu1aRo0aRf/+/bVXRUSkLCgkFRERqcoMw+DAgQOB0HTlypV4vV66dOmCzWbDZrPR\nqFGjkIWmPp+vULUpaHp5qPkrr9xud6DySpV9hWkQT8lVpUn1ld35qk2D92JN4A+RCwoKQtISZOvW\nrUyZMoXdu3czZswYevfurX/TIiJSlhSSioiIVCeGYVBQUMDKlSux2+1kZWWxd+9eEhMTSUtLIz09\nnfbt24fsiOKFTC+vKQFBafjDBYVXJVNctWlwhZ9/OFlNVB372VZWxVWbVud+z8H7yzCMUg/7+uWX\nX5g8eTJ5eXmMGzeOSy+9NMQrFhEROSuFpCI1wb333suXX35JQkICa9euPePzS5cupX///rRq1QqA\nW265hQkTJpT3MkWkjPh8PrZs2RKoNl2/fj3R0dGkpKSQnp5OSkoKsbGxZToQyh8OqMKvsJowSbyi\nFK3w83q9Na5dhPZXxStabVrcm0kmk6nKfV+K7q/IyMhSvRmxcuVKJk+eTHh4OOPHjyc5OTmUyxUR\nETkfhaQiNcGPP/5ITEwMd911V7Eh6eTJk1m4cGEFrE5EypthGBw5coTs7GwyMzPJzc0lPz+fjh07\nBqpNmzdvHrKBUOfrJ1kTK/yCJ4mbzWasVmuN/DqUp5rULkL7q3Ir7s2kqlJtGhyOmkymUu0vwzDI\nzMxk6tSp1K9fn/Hjx9OuXbsyWLWIiMh5FfuDTGMCRaqRXr16sX379nNe5jxvjIhINWIymYiPj+f6\n66/n+uuvB8DtdrN69Wrsdjv/8z//w86dO2ncuHFgIFSXLl2IiIgo0X35X/D7rx/cT9LpdJKfn19j\nKvx8Pl+g36jFYiE6Olr9RstJ8F70Cw7wCwoKAtWmRQdCVZW9WHTYV1RUlKZ/V0ImkwmLxYLFYsFq\ntWIYRqHnRbfbXSmrTYPD97CwMGrVqlXiMNcwDL766iteffVVkpKSmDlzJomJiWWwahERkdJTJalI\nNbN9+3b69u171krSZcuWcfPNN9O0aVOaNGnCxIkTad++fQWsUkQqC8Mw2LlzJ3a7HYfDwZo1a7BY\nLHTv3h2bzUZaWhrx8fFlPhCqKlRVXQh/IOzxeDRJvBILrvCrSnuxaPhutVoVvldx56o2Le/KZ8Mw\ncDqdgfDdXzlaEl6vl4ULF/Laa6+RmprKmDFjaNSoUYhXLCIiUiI6bi9SU5wrJD1x4kSg4mTRokU8\n+uijbN68uQJWKSKVlWEY5OXlkZubS2ZmJtnZ2Rw9epSkpKRAtenFF18csuAvODQt2sMvuNq0MtOw\nnOrhXHuxoiv8FL7XHEWrTf1/yrLyObgyubThu9vt5oMPPuCtt96id+/ePProo9SrVy8k6xQREQkR\nhaQiNcW5QtKiEhMTWblyJfHx8eWwMhGpqrxeL+vXryczMxOHw8Gvv/5KvXr1AqFp9+7diYyMDOlA\nqOCAIPj4dGUaCKVhOdVbRfeT9N+/0+nE6/USERGB1WrV/qqBzlX5XJpq0+DK5NKG7wUFBbz99tu8\n++673HTTTTz00EPUrl27RLclIiJSxhSSitQU5wpJ9+/fT0JCAiaTidzcXG699dbz9jAVESnKMAz2\n79+P3W7HbrezcuVKDMOgS5cu2Gw20tPTadCgQUiP6BcdCBUcUpX3oJqi/SD9VVcKr6q3otPLPR5P\nYDhZKCufgyuTDcNQ+C5nVfR58c9Um4ayMjkvL485c+bw6aefcvvttzNs2DCioqJK+/BERETKkkJS\nkZpgyJAhLFu2jEOHDtGgQQOeeuop3G43ACNGjGDGjBnMmjULi8VCVFQUkydPxmazVfCqRaSqMwyD\ngoICVqxYgd1uJysri3379pGYmIjNZsNms9G+ffuQDZYpGlQVDQfK6li01+sNhKP+YEH9IGu2s1U+\nA4X24oVWPodykrjUPBdSbQrgcrnweDxEREQQERFR4nD0yJEjvPbaa3zzzTcMHz6cO++8s0RD/0RE\nRCqAQlIREREpPz6fjy1btgSO6K9fv56YmBhSUlJIT0+nR48exMbGhvSIflkciz7bkefSBAtSvRVX\n+Vx0Lwbvn6KTxFWZLKHi34tutzvwprnJZMJisRSqfP4ze23//v3MmDGDrKwsHn74YW699Va9WSQi\nIlWNQlIRERGpOIZhcOTIEbKysrDb7eTm5nLq1Ck6duwY6G3avHnzkISPRQefBB+LLi6oOtttuN1u\nXC4XhmEEwlEFV/JnFR3C4/F4MJvNmM3mQAhvsViIjIxU2CQh499bBQUFgYFy4eHhZ1Tiw+k3lA4e\nPMimTZtIS0sjLi7ujNvbtWsXU6dOZcOGDTz22GP07dtXz4ciIlJVKSQVERGRysXtdvPTTz9ht9tx\nOBzs3LmTJk2aBI7od+7cOWTHN4sLqs7WS9Jf1Wc2m3XkWULO32/Uvwf9oX5F9tmV6uPP9rT1h6a5\nubn885//ZM2aNTRr1owePXqQlpZG8+bN+eSTT9i3bx9jx47l6quv1t4UEZGqTiGpiIiIVG6GYbBj\nx45AaLpmzRoiIiLo3r07NpuN1NRU4uPjQzoQKrja1P87kdlsVuWohJw/uDpb24bi+uwWDfG1H6U4\nwT1tASIjI0sUtrtcLtauXctXX31FZmYmP//8M263m549e5Keno7NZiMtLY26deuWxcMQEREpDwpJ\nRUREpGoxDIO8vDxycnKw2+1kZ2dz9OhRkpKSAi/UL7744lId0Q+e8uwPo4IDK39lX/AQHpELFVzV\n5z/yfCHh+9lCfCg8hEd9SwVCP/Br+fLlTJ48mcjISJ588km6dOnCgQMHyM7OJjs7m6ysLFasWEHT\npk1JT08PBKft27dXu4gapqCggCuuuAKn04nL5aJ///48//zzFb0sEZELoZBUREREqj6v18svv/wS\nGAi1ZcsWLrrookBf027duhEZGXnOgMDn8/Htt9+SmpoaCBXOFlwVNxCqJJPLpWYpWtV3viPPF6Lo\nQCh/tWnwfjSZTNqPNcTZBn75J9iX5LaWLVvGtGnTaNy4MePGjSMpKanYy3s8HtatW0dWVlYgON2/\nfz9vv/02/fr1K+lDkiooPz+fqKgoPB4Pl112GRMnTuSyyy6r6GWJiJyPQlIRERGpfgzDYN++fYEj\n+itXrsQwDLp27RrobdqgQQNMJhMFBQW89957TJ8+nbCwMD744AMSExMvOFS6kMnl6iVZswUHV2Xd\n07a4EL/ogDLtx+rFMIxA5Z7FYsFqtZa4gtMwDBYvXsz06dPp0KEDTzzxBC1atCjRbR06dIjw8HDq\n1KlToutL1Zafn88VV1zBvHnzaN++fUUvR0TkfBSSioiISPVnGAYFBQUsX74ch8OBw+Fg9+7dmM1m\ndu3aRVJSEqNHj6Z3794hOTofPBBKvSRrLp/Ph8vlwuVylbqqr6T8A6CCK03VMqL6CN5jpQ1HvV4v\nn376Ka+//jo9e/bkscceo2HDhiFesdQEPp+Pbt26sXXrVh588EFeeumlil6SiMiFUEgqIiIiNcvW\nrVuZMmUK7777LldddRU2m42NGzeyfv16YmNjSU1NxWazkZKSQkxMTJkNhAJV91VXPp8Pp9OJ2+0m\nPDyciIiIStWX0V9tGhycAoX2ovZj5VZ0j1mt1hIH3W63m/fee4+5c+dy3XXX8cgjjxAfHx/iFUtN\ndOzYMa699lpeeOEFrrzyyopejojI+RT7i0/5vsUtIiIiUsYcDgeTJk3ihx9+4P777+eXX36hUaNG\ngc8bhsHhw4fJysrCbrczZcoUCgoK6NSpU6C3afPmzUsUHJlMpkDw5Bccmrrd7kLVfcHVplJ1BA/8\nioiIICYmplJ+D00mExaLJVDVGtwywuv14nK5Ai0jtB8rl1DusVOnTjF//nzef/99brnlFr755hti\nY2NDvGKpyerUqcMNN9zAihUrFJKKSJWmSlIRERGp8gzD4JNPPmHixIkcOHCA0aNHc8899xAdHX1B\n13e73axatSpwRH/nzp00bdoUm81GWloanTt3JiIiImRrLVrdFxyuaiBU5eT/vjmdTrxe7wVPqq/s\niu5Hj8cTaBmh/Vj+ioajVqu1xF/7EydO8Oabb7Jw4ULuuusu7r33XmrVqhXiFUtNdejQISwWC3Fx\ncZw6dYprr72Wf/7zn1x99dUVvTQRkfPRcXsRERGpvgzDYPjw4Vx//fX079+/1EeeDcNgx44dZGZm\n4nA4WLNmDVarle7duweC07p164b0iH7RgVDBR6I1EKri+Pt8Op1ODMMIyaT6yuxCBpSp2jT0/Hss\nFAH8H3/8wWuvvcZ3333H/fffzx133EF4eHiIVyw13dq1axk6dCg+nw+fz8edd97J2LFjK3pZIiIX\nQiGpiIiISEkZhsGJEyfIycnBbreTnZ3NsWPHuOSSSwJH9Nu0aROy4Cj4SHTwQCh/SOUPTatrUFcZ\n+CfVu1wuTCZTmU6qr+yK248aUFY6oQ7g9+3bx/Tp01m+fDmPPPIIt9xyS6XqkSsiIlJJKCQVERER\nCSWv18u6deuw2+3Y7Xa2bt3KRRddFKg07datG5GRkSGrNi0aUoEGQpUFwzBwOp2FJtXra1tY0QFl\nqn7+c0Idju7cuZOpU6eyefNmHnvsMW644QZ97UVERIqnkFRERESkLBmGwd69e7Hb7TgcDlatWoVh\nGCQnJweqTRs0aBCy0NQftPiDUx2JLp3gKeIWiyUQjsqFOV/1s6pNT/+7dbvdOJ3OkFQnb968mUmT\nJnHo0CHGjh3LVVddVaO/viIiIhdIIamISHm49957+fLLL0lISGDt2rVnvcwjjzzCokWLiIqKYu7c\nuSQnJ5fzKkWkPBiGwalTp1i+fDkOh4OsrCwOHDhAq1atsNls2Gw22rVrF7IgLjg0LTqAR0eiixc8\nKCc8PByr1apwOQSCq5/9+xEoVGlaUyp0/a0bnE4nZrOZyMjIUj32NWvWMGnSJLxeL+PGjSMtLS3E\nKxYREanWFJKKiJSHH3/8kZiYGO66666zhqQZGRm8+uqrZGRkkJOTw6OPPkp2dnYFrFREKoLP52Pz\n5s2BI/obNmygdu3apKamYrPZSElJITo6OqQDoYKrTaFmhlRnEzwoJyIigoiICIWjZazoQKjq3ms3\nOBz1t26wWCwlvr3s7GwmT55M7dq1GT9+PJ06dQrhakVERGoMhaQiIuVl+/bt9O3b96wh6QMPPMBV\nV13FoEGDALjkkktYtmwZDRo0KO9likglYBgGhw8fJisri8zMTHJzc3E6nXTu3JnU1FTS09Np1qxZ\nyEKjs4VU/tDUH1JV56CwaC9IfzhaXUK5qqa69tr1+XyBoV+lbd1gGAbff/8906ZNo3nz5owbN46L\nL744xCsWERGpUYr9xaLkb2WKiMiftmfPHpo1axb4uGnTpuzevVshqUgNZTKZqFevHjfeeCM33ngj\nAC6Xi1WrVuFwOJgwYQK7du2iWbNmgYFQnTt3Jjw8vET3ZzabMZvNgesHh1Rut5uCggKAQpV91eGI\nfnAvSKDUg3IkNEwmExaLJRAkFu2163a7CwX5wW0jKqOifW2jo6NLHI76fD4yMjKYMWMGnTt3Zs6c\nOYV+fxAREZHQU0gqIlLOilbw60W6iASLiIgI9Cx97LHHMAyD7du3Y7fbeffddxk3bhxWq5UePXoE\ngtO4uLgSPZecLaQKrjZ1uVxnDISqSlPLix53rlWrVpWsTKwp/EftIyIiAn/nD/L9+9FfbRpcaVrR\n39PgcDQ8PJyYmJgSB7ler5ePP/6YN954g169evHhhx+SkJAQ4hWLiIjI2SgkFREpR02aNGHXrl2B\nj3fv3k2TJk0qcEUiUtmZTCYSExNJTEzkjjvuwDAMTpw4QU5ODpmZmbz++uscO3aMdu3aBY7ot27d\nukQhjclkCoRO/qAquLLP6XSSn59f6QdCFT3uXJqKPqlYwUE+UCjI93q9hYL88q42DR76FRERUapw\n1OVy8d577zFv3jyuv/56vvjiC+rWrRviFYuIiMi5KCQVESlH/fr149VXX2Xw4MFkZ2cTFxeno/Yi\n8qeYTCZq165N79696d27N3A6rFm7di12u50XX3yRbdu2Ub9+/UClabdu3bBarSWuNg0PDy90RN8/\nEMrj8QSO6FeGPpL+0MzlchEREaFwtBoKDvL9goN8l8uFx+MJBPll0TbC6/VSUFAQGPoVGxtb4tvO\nz89n3rx5LFiwgFtvvZUlS5YQExMTknWKiIjIn6PBTSIiITRkyBCWLVvGoUOHaNCgAU899RRutxuA\nESNGAPDwww+zePFioqOjeeutt+jWrVtFLllEqiHDMPj9999xOBzY7XZWrVqFyWQiOTmZtLQ0bDYb\nCQkJIR0IFTwMqrz7SBat6NOk+pqtaNsIr9d7RtuIkuxJ/9Avr9eL1Wot1dCv48eP88Ybb/DFF19w\n9913c8899xAZGVmi2xIREZE/RdPtRURERGoqwzA4deoUy5cvx263k5WVxcGDB2ndujVpaWmkp6dz\nySWXhKzqMriPpD80Da4ADEVlX/Ckep/PV+rQSqq34CP6/n15IW0jgveZYRilHvp16NAhZs6cybJl\ny3jwwQcZMmRIiQexiYiISIkoJBURERGR/+Pz+di8eTOZmZnY7XY2btxInTp1SE1NxWaz0aNHD6Kj\no0MSOhZX2Rdc1XehA6E0qV5CIbhthD88LbonDcMI2T7bu3cvr7zyCqtWreLRRx/l5ptvVrWziIhI\nxVBIKiIiIiLFMwyDP/74I3BEf/ny5bhcLjp37hwYCNW0adOQHtE/W2WfP6Tyh6b++wueVG82m7Fa\nrRccrIpcCH9o6na78Xg8QOHBUSUZUrZ9+3amTp3K1q1befzxx+nTp4/2rIiISMVSSCoiIiIif47T\n6eSnn34KHNHftWsXzZs3D4SmnTp1CtlRYf8R/eDQFAhU9Pn7nEZGRgYmnYuEStEQPjIyErPZfEaY\nD6f35K+//srRo0dJSUkhOjr6jNvbuHEjkyZN4ujRozzxxBNcccUV5f2QRERE5OwUkoqIiIhI6fh8\nPnbs2BE4or927VoiIyPp0aMHNpuN1NRU4uLiQlIp5x/G5Ha7A8eSQzF8RyRYcDgaFhYWqFAujj80\n/fTTT5k+fTobNmygbdu2pKamkpqaSnx8PG+//TZms5lx48aRkpJSjo9GRERELoBCUhEREREJLcMw\nOH78ODk5OWRmZpKTk8OJEydo165doNq0VatWfyrIdLvdgePO4eHhWK3WwPX9Q3SCK/suZPiOSFE+\nnw+Xy4XL5cJisWC1Wks0uCw/P59Vq1aRkZFBbm4uP//8M1FRUVx++eX07NmT9PR0unXrhtVqLYNH\nISIiIiWgkFREREREyp7H42HdunVkZmbicDjYtm0bCQkJpKWlYbPZSE5Oxmq1FgoyfT4fP/74I5Mn\nT6ZTp05MmDDhjMucTdHhO8HHoYODU4Wm4ufz+QIVyqUJR+H0/vv222955ZVXSExMZNy4cbRq1Yrt\n27fjcDhwOBxkZWWxadMmunTpEghNe/bsSaNGjUL8yKSq8Xq99OjRg6ZNm/L5559X9HJERGoShaQi\nIiIiUv4Mw+D333/HbrfjcDhYtWoVZrOZ5ORkUlJSyMvL4/XXX+fIkSM88sgj3HHHHdSqVavE9+c/\nDh1cceoPTf3BqY7o1zxerxeXy4Xb7T6jQvnP8vl8fPHFF8yaNYvk5GTGjBlD06ZNi718Xl4ey5cv\nD4SmWVlZxMbG8v7772Oz2Ur6kKSKmzx5MitXruTEiRMsXLiwopcjIlKTKCQVERERkYpnGAZHjhzh\n+eefZ+7cuVitVrp27UqdOnWw2Wykp6eTlJRU4uq+s93f2QZC+atM/aGpqk2rJ39vW4/HQ0REBBER\nESUORz0eDx999BFvvvkmV155JaNHj6Z+/fp/+nYMw2Dz5s00atSI2rVrl2gtUrXt3r2bu+++m7//\n/e9MnjxZlaQiIuWr2F/6NBpURERERMrFsWPHmD17NtOmTaNTp04sWLCAK6+8EsMw2LRpE5mZmcyY\nMYONGzdSp06dQF/T7t27Ex0dXaIg02QyYbFYAker/Uf0/aGpy+U6YyCUxWJRaFrFeTwenE4nXq+X\niIgIYmNjS/w9dTqdvPPOO7z99tv069ePRYsWUadOnRKvzWQykZSUVOLrS9U3evRoXn75ZY4fP17R\nSxERkSAKSUVERESkTO3du5epU6fy5ptvct1115GRkUGXLl0CnzeZTLRr14527doxfPhwDMPgjz/+\nwG63s3TpUl5++WVcLhddunQJBKdNmjQpcWjqP3ofEREBFB4I5XQ6yc/P10CoKshfNewPR61WK1FR\nUSX+vp08eZK5c+fy0UcfMXjwYL777juio6NDvGqpab744gsSEhJITk5m6dKlFb0cEREJouP2IiIi\nIlJmPvnkE+677z7uuOMOHn/8cVq2bFmi23E6naxatQq73U5WVha7d++mRYsWgdC0Y8eOhIeHh2TN\n5xoI5Q9NNRCq8vCH3E6nE8MwsFqthIeHl/j7c/ToUV5//XUWLVrEfffdx9ChQzWdXkLmySef5O23\n38ZisVBQUMDx48e55ZZbmD9/fkUvTUSkplBPUhEREREpf0eOHMHj8ZSod+O5+Hw+tm/fTmZmJg6H\ng7Vr1xIZGUmPHj1IT08nNTWVOnXqhCzIDA5Niw6ECq42lfJjGAZutxun0wlQ6nD04MGDzJgxg8zM\nTB566CEGDx6MxaKDd1J2li1bxsSJE9WTVESkfCkkFREREZHqyzAMjh8/TnZ2Nna7nZycHI4fP077\n9u1JS0sjPT2dxMTEkAWZ/qPdwcFp8FF+DYQqO8HhqMlkwmq1lqqP7J49e5g2bRpr165l1KhR9O/f\nX4G3lItly5YxadIkTbcXESlfCklFREREpGbxeDysXbs2UG3622+/0aBBA9LS0rDZbHTt2hWr1RqS\nILPoQCiv14vP5yt0PF8DoUrHMAxcLhdOp5OwsDCsVmup2h5s27aNKVOmsHPnTsaMGcM111yj74+I\niEj1p5BURERqnsWLFzNq1Ci8Xi/Dhg3jb3/7W6HPL126lP79+9OqVSsAbrnlFiZMmFARSxWRcmAY\nBnv27MFut+NwOPjpp58wm80kJydjs9lIS0ujfv36IT2i768y9QenZrM5EJz6Q1MFc+dmGAZOpxOX\nyxUIR0tzDH79+vVMmjSJEydOMG7cOC677LIQrlZEREQqOYWkIiJSs3i9XpKSkliyZAlNmjQhJSWF\n9957j3bt2gUus3TpUiZPnqxjbiI1lGEY5Ofns3z58sBAqEOHDnHxxRcHqk2TkpIICwsL2f0VDU1B\nA6GK4/P5cLlcuFwuLBZLoHK0pFatWsWkSZOwWCyMHz+ebt26hXC1IiIiUkUU+4uWOpGLiEi1lJub\nS5s2bQKTtAcPHsx//vOfQiEpnA4tRKRmMplMREdHc+WVV3LllVcCp4O5jRs3kpmZyauvvsqmTZuI\ni4sjNTWV9PR0unfvTlRUVImCTJPJhMViCQR+hmEEJrN7vV5cLhc+n++M0LSm9cf0+Xw4nU7cbjfh\n4eHExMSU6muQmZnJ1KlTueiii3juuefO+DkgIiIiAgpJRUSkmtqzZw/NmjULfNy0aVNycnIKXcZk\nMuFwOOjSpQtNmjRh4sSJtG/fvryXKiKViNlspn379rRv3577778fwzA4dOgQdrud7777jhdffBG3\n202XLl0C1aZNmjQpcWhqMpmIiIgI/F3R0NTj8WA2mwsFp9V1IJTX68XpdOLxeEodjhqGwddff830\n6dNp27YtM2bMIDExMcQrFhERkepEIamIiFRLFxIgdOvWjV27dhEVFcWiRYsYMGAAmzdvLofViUhV\nYTKZqF+/PgMGDGDAgAEAFBQUsGrVKhwOB+PGjWPPnj00b94cm81Geno6HTt2LHHPTJPJRHh4OOHh\n4cD/DYTyeDx4PB6cTieGYRQaBlXVj+gHh6MRERGlCkd9Ph8LFy7ktddeo0ePHvz73/+mcePGIV6x\niIiIVEcKSUVEpFpq0qQJu3btCny8a9cumjZtWugysbGxgf/v06cPDz30EIcPHyY+Pr7c1ikiVU9k\nZCQ9e/akZ8+ewOlg7rfffiMzM5N58+axbt06atWqRY8ePUhPTyclJYU6deqUuNrUH4j6+QdCeTwe\nCgoK8Hq9gcv4g9OqcETfH/p6vV6sViu1atUqcdjrdrtZsGABc+bM4S9/+QuffPIJF110UYhXLCIi\nItWZBjeJiEi15PF4SEpK4ttvv6Vx48akpqaeMbhp//79JCQkYDKZyM3N5dZbb2X79u0Vt2gRqS7q\nFYAAACAASURBVBYMw+DYsWNkZ2djt9vJyckhLy+P9u3bB47oJyYmhizILG4glL/K1B+aVoZqU/9a\nCwoK8Pl8WK1WIiIiSry2goIC/v3vf/POO+8wYMAARo4cSe3atUO8ahEREalGNN1eRERqnkWLFjFq\n1Ci8Xi/33Xcf48ePZ/bs2QCMGDGCGTNmMGvWLCwWC1FRUUyePBmbzVbBqxaR6sjj8fDzzz9jt9ux\n2+1s376dBg0aYLPZsNlsdO3aFavVGpL78h/RDw5Niw6Eslgs5Rqa+nut+tsFWK1WwsPDS7yGvLw8\n5syZw6effsrtt9/OsGHDiIqKCvGqRUTKnv80gIiUG4WkIiIiIiKVhWEY7N69G4fDgd1uZ/Xq1YSF\nhZGcnIzNZiMtLY2LLrooZEFm8EAo/3/LYyCUYRi43W6cTidwulVBaQLaI0eOMHv2bL7++muGDRvG\nXXfdVWjwlYhIVXX8+HFVwouUD4WkIiIiIiKVlWEY5Ofnk5ubi91uJysriz/++IOLL744EJpecskl\nIT2i7x8I5Q9OgUKhaWkGQgWHoyaTCavVWqpwdP/+/cyYMYOsrCxGjhzJrbfeWuLhWCIiFeXEiRMs\nXbqU1NRUGjRoAMDixYuZNWsWVquVoUOHcsUVVxATE1PBKxWp1hSSioiIiIhUJT6fjw0bNgSO6G/e\nvJm6deuSmpqKzWaje/fuREVFhaz6Mzg09f8JHgblrzY9F8MwcLlcOJ1OwsLCAuFoSe3evZupU6ey\nfv16Ro8eTd++favEUCoRkWD+59Nt27axbds2rr76akwmE3v37uXuu+/m4Ycf5tixY3zzzTd06tSJ\nMWPGVPSSRaozhaQiIiIiIlWZYRgcPHgwcER/xYoVeDweunTpEhgI1bhx45Ae0Q8+nn+ugVCGYeB0\nOnG5XISFhREZGVmqHntbtmxh8uTJ7N27l7FjxwYCBRGRqsTn87F27VqsViuXXHIJANu3b2fx4sUM\nHDiQH374gWnTprFs2TLcbjcrVqzgueeeY968ecTHx1fw6kWqrWJ/odAZFRERERGRKsBkMpGQkMCA\nAQMYMGAAcHq6+8qVK3E4HDzxxBP8/vvvtGjRIjAQqmPHjiWu5DSZTFgslsD1iw6Ecrlc+Hy+QEga\nFhZGVFRUqSpH161bx6RJkzh16hTjx48nPT29xLclIlJRDMPAZDJhNptZu3YtmzZtwmKxYLVaufTS\nS1m0aBHt2rUjOTkZk8nEzp07ad68OTExMdSpU4d9+/YpJBWpAApJRURERESqqMjISC699FIuvfRS\n4HTV0rZt27Db7cydO5d169YRFRVFSkoK6enppKSkULt27RJVZZpMpkLH74MrR81mM16vl5MnT2I2\nmwtVm5pMpvPe3/Lly5k8eTJWq5Unn3ySrl27lujrISJSkfxvJgVX0kdHRzNp0iS6d+/OSy+9RHp6\nOhkZGdjtdho2bMill17K008/zZtvvsnBgwc5deoUSUlJFfgoRGouHbcXEREREammDMPg2LFjZGdn\nk5mZSU5ODidPnqRDhw6BI/otW7a84D6fhw4dIioqCo/HQ3h4OFartdB1/Uf0g4/pP/TQQ7jdbmw2\nG+np6SQnJ2O1WjEMgx9++IGpU6fSqFEjxo8fr2BARKokf+WoX0FBAZ9//jk33HADR48eZdKkSSQk\nJDBy5EhiYmJwOBzMnj2bYcOG0bZtWwYOHEjdunXZunUrf//737ntttvOuE0RCRn1JBUREREREfB4\nPKxZsyYwEGrHjh00bNgQm81GWloaXbt2xWq1FrrOqlWrePnll1m9ejXLly8nOjr6gl68G4bB9u3b\nsdvt5OTkkJOTw2+//Ub79u35448/aNeuHc888wzJycll9XBFRMqMv+WI//nQ6XQydepU5s2bR9eu\nXWnRogU333wzDRs25IknnuCOO+7ghhtuAGDs2LHUqlWLJ554gsjISNatW6cqepHyoZBURERERETO\nZBgGu3fvDoSmq1evxmKx0K1bN+rXr88333zD+vXrGTlyJMOHDyc2NrZE9+P1evnss8+YM2cO7dq1\nIzo6mjVr1pCTkxM4ctqzZ08uvfRSkpKSNMVeCmnZsiW1a9cmLCyM8PBwcnNzK3pJIgGHDh3is88+\no3nz5vz+++/cdddd5OTkMGLECFJSUpg9ezbPPvssFouFBx54AJPJRE5ODt9//z1jxowhISEhcFse\nj4ewsDBVkYqUHYWkIiIiIiJyfj6fj88//5x//OMf7N69myuuuIIDBw7QqlWrQLXpnwkx3W4377//\nPnPnzuWaa67h0UcfLTSQxOv18ssvv2C323E4HNjtdo4ePUp6enogOO3ZsycRERFl9ZClCkhMTGTl\nypUaZiOVhmEY5OXlMXHiRI4ePcpFF13E2LFjAfh//+//8cMPP3DLLbewfv16hgwZQps2bXjllVdY\nuHAhHTp04N1336V27doV/ChEaiSFpCIiIiIiUjyfz8d//vMfnnvuOfLz8xk/fjyDBw/GYrHg9XrZ\nsGFDoNp08+bNxMfHk5aWRlpaGj169KBWrVqFKp9OnTrF/Pnzef/997nlllt48MEHL7gKde/evTgc\njsCfjIwM6tatW1YPXaqAxMREVqxYQb169Sp6KSKFNGzYkD59+vDWW28BsHHjRiZMmMBHH30EQK9e\nvWjUqBHz58/H6XSyefNmUlJSAtf3+XyqnBcpXwpJRURERETkTP5Kz+eff57o6Gj+/ve/069fv3O+\naDcMg4MHDwZC0xUrVuD1eunSpQudO3dmx44dLFmyhDvvvJP77ruPWrVqleMjkuqoVatW1KlTh7Cw\nMEaMGMHw4cMreklSA3i9XsLCws46RMnj8WCxWJg6dSoZGRl8/fXXABw/fpy4uDhWrVrFqlWrWLJk\nCV26dOHee++lfv36Z9y2iJQ7haQiIiIiIlKYYRj06NGD2rVr8+STT/KXv/ylxH3wCgoKWLlyJR98\n8AFRUVH87//+L+Hh4SFesdRUe/fupVGjRhw8eJDevXszffp0evXqVdHLkmqqaCjqcrkCLT/8n/P/\n1+12065dO9555x3S0tIAmDVrFl999RV5eXlMmzaNDh06VMjjEJGzUkgqIiIiIiJn2rNnD02aNKno\nZYhcsKeeeoqYmBgef/zxil6KVHMLFy5kzpw5tG/fnhtvvJGePXsW+ry/mvSf//wn69ev58MPPwRO\nB6n5+flER0cHPjYMQ8fqRSqHYkNS/QsVEREREanBFJBKZZefn8+JEycAOHnyJF9//TWdOnWq4FVJ\ndWEYBl6v94y//+6775g7dy5PPvkkjRs3ZsKECfz888+FLuM/Lv/444+Tk5PD7t27ATCZTERHRwdu\n22QyKSAVqQIsFb0AERERERERkeLs37+fm266CThduXf77bdzzTXXVPCqpLowmUyBsPPbb78lNjaW\n1NRUfvjhB6655ho2bdrEa6+9xoABA2jVqtUZ1/V6vdSuXZtffvnljOF0wbctIpWfQlIREREpF4sX\nL2bUqFF4vV6GDRvG3/72tzMu88gjj7Bo0SKioqKYO3cuycnJFbBSERGpTBITE1m9enVFL0OqibMN\nYXrttddYsmQJq1at4pJLLiEjI4P4+HjGjh3LQw89xNdff03jxo05deoUJ06cIDY2FsMwCk2mj42N\n1TAmkSpO9d4iIiJS5rxeLw8//DCLFy9m/fr1vPfee2zYsKHQZTIyMtiyZQu//vorr7/+Og8++GAF\nrVZERESqG5/PFzj6Huz7779n7ty5PPfcc8yfP5/169fjcDho3749/fr1Y9CgQTRu3Jjly5czbtw4\nduzYEQhaw8LCMJlMZGdnM2/ePE6ePFlBj05EQkEhqYiIiJS53Nxc2rRpQ8uWLQkPD2fw4MH85z//\nKXSZhQsXMnToUADS0tI4evQo+/fvr4jlioiISDVjNpsJCwvj5MmTfPLJJ4E+t7t27aJnz560bduW\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xmrSx+qo+S68sy3jnnXeWLfTT6VTbJ3RUPTzdtkgqVcSn4106BlokdTz7zkFNVtv3zUEF\ngN0ISQHgHpuqRdsYikbESy30aeHSYDCIJ0+exHjs9OBY2vZeob/SvMxtAerqsXF1kdQ+AapK7Pvt\nMgc1tfCvqledmoMKAHe5CgKAFfWFS11ooa8vXEoLXbIsizzP4+rqavn1zGYzF8mP5PmjD1KAus7q\nDNR0/FkNUDe18ae/n/0cYg5q+pFGrLT1hiAAPJSQFIDe62IL/aaFS9fX1xYuAUezyyKpehVqunFT\nluWd41L971HleBi7zkGdz+cxm81iMpnc+T3moALQdUJSAHqpay306cI2/RgMBsuFS6mV/j6DwUCr\nK3A0uwSos9nsTpi6ukhqUwt/247ZTVMPUFOFab1aeNc5qOkmnDmoALSRkBSAXqi30KdwNGlrC326\nWJ3P57FYLCxcAlqrHqBWVRUXFxfLX6tXOdZvbq0GqJta+B0LH2/XOaibAlRzUAFoAyEpAJ20Ohdv\nsVgsf62tlUebFi5dXl7GeDxu3dcDsIt0bLtvkVRq468vkXrsIinut+8c1PRn6uFp+mdbP6cBaDch\nKQCd0bUW+l0XLgH0WWrv3hagrn4+rC6SEqAex65zUNNn9urvq4enqy38Xh8ADk1ICkBr3ddC37aL\nKAuXWMecWNjf6mzNutWOg3RjajVA3dTGz+NsC1Aj3g+40+fiaohqkRQAhyYkBaBV6qHo8+fPYzwe\nt7o17xALlwB4uF0WSdWrUFNQV5blnT+7GqSmv5vHOcQc1NUAVcANwDZCUgAabVMLfUTEixcv4vr6\nulVt56sLl8qyXFaLTqfTjRVP9FPaNA2c1i4Bav3zKYWo9UVSm1r4hXSPZw4qAMcgJAWgUeoXnqli\nNFm9gGnLhYyFSwDdUf8cWr2xVZ+zWV8klapQq6ra2sLfhM+Dtt+Yecwc1PrrYg4qQP8ISQE4u3QR\nWf9nRDvnika0e+FS2y+OAc6pHp7uskiqvkSqSYuk2va5uytzUAHYRkgKwMnVFy6tttBvam9ssq4s\nXGrDY+wCQTT0132LpOoB6mqIapHU8d03B7U+MmeVOagA7SckBeDoHtJC3xYWLgFwSPcFqPXwNHUs\n1APUengqQD28XRZJpTmo6/7spirU9OsAnJ+QFICj2LRwqa2hqIVLAJzLLouk6lWoqVW8LMuXAtT6\nv6e/m8cxBxWgG4SkABxEvYU+haPJMVvoj9m6bOES+9BOD5zSLgFq/cZlClHT5/RqeFr/Mz7nHu8x\nc1DT63BxcWEOKsAJCEkB2MvqRddisVj+2qmqRQ/997d54RLN4IIVaJL6Z/Fqx0O9wjFVodZnhb/7\n7rtbZ6A63h3GtucydbCMRiNzUAFOQEgKwM662ELfhYVLAPBQ9fC0HqCmYG4ymdxp4U+f+6uLpNYF\nqT47D2dblXDEfnNQvT4A6wlJAdjovhb6Nl4IWbgEAPd77CKpbVWoPN6+c1CrqnqpAtUcVID3CEkB\nWKpXJdQvfCLaG4pauAQAh7XrIqlNAeq2KlQe7yEBavq5+u/dVoHqNQK6TEgK0HObWugjjrtw6Zgs\nXNqfpUPAOTkGtd+uAeq6Nv6IlxdJpR/p7+ZxdlkkVb/BXP/5+muyqQoVoM2EpAA906UW+sFgsPx6\nLFx6vLa87gAczzG32u8SoK7evE1VqBHrA9S2nbs03bbncpc5qPXw1BxUoG2EpAA9sBqKdqGFPm3g\nffbs2Z0WeguXANrN8buf6ucj60bhrLbwpwA1BavbZqB6Tx3GLm38KUA1BxVoIyEpQAfVq0W70kK/\nbuFSRESe5zGdTp1cA0CHpSrFbQHquhb+1TbxdVWoTdWm8RP7LpJKzEEFmkBICtAB9fa0VDGatLla\n9L6FS++8844ZowDQcylAXWeXRVLbqlDPrQmP4bH2nYOa1APU9Fo36TUCukNICtBSmxYutTkUrVeL\nWrgEADzWQxdJrQao26pQOYxd5qBuC1BXW/m9RsC+hKQALXHfwqU2ttBbuAQAnMtDA9R6G3/E+kVS\n6e8S0B3GoeegWvYFbCMkBWiorrbQp0ULqVr0MQuX0nZ7AIBD2iVAXe3qSVWoEesD1LaevzXVY+eg\nroan5qACQlKABulaC33E+oVLWZbFZDKJLMta+TUBAP1VPyfbtkgqVaGmADUFq9tmoDovOoxd5qDW\nw+1V6xZJmYMK3SckBTijrrbQ37dwiWZSmQsAj5eWC20LUNe18NcXSQ2Hwzu/T4B6WPvOQV0sFsuZ\n+eagQvcISQFOaF1rVtLWatHVhUvz+TxGo5GFSwAAK1KAus7qeWL67+fPn98JUDdVoXIY26pQi6JY\nBqWrc1DTnzEHFdpLSApwZJta6CO238VusrIs71SLWrgE71ONC8A+1s1BraoqLi4u1i6SSudg9UrT\nTbNQOZxts2ojdp+DmmbxG7UAzSEkBTiw1Rb629vbWCwWMZlMWnsX+dALl6CrfB8Abbcu2OH8dlkk\ntamNP8IiqVN46BzU1e+1dXNQBahwWkJSgANYnStaX7iUTojaVl3ZhoVLZmgCAH23S4C62tmU5sZH\nhEVSJ3LfHNT6XP9V6bVZDVBVCsNhCUkB9lCvFl3XQl8/SW3LiYuFS3B86XigUguAU6gHc9sWSaWb\n/OmmfzrXFaCexi6LpBaLhTmocGRCUoAd1O/Ap5PH5L4TkKZWO1q4BADQb2mR1LYAdV0Lf32R1KY2\nfg5jWxv/fXNQ66+LOahwPyEpwAabFi61+a7s6sKliIgsy+Li4sLCJQAAllKAus5qC39VVctOpHqA\nuqkKta1SdW1TmIMKhyUkBfhfD2mhb4t1C5eyLFvOFm37iSqH18SqZwCgWR66SCoFdGVZ3vmz64JU\nDsccVHgYISnQW49poW+y1Rb64XAY4/E4ptNpJ1vohXqH07X3Rld4jwP0U1uP/w9dJJXOXeuLpDa1\n8DtXOZyHzEFd92c3VaGmX4c2EpICvdLFFvp1C5dStWjXFy618fWCh/AeB+i3rn0ObFskVZ+vWT9f\nXw1QLZI6PnNQ6SshKdBp9Rb6dLKVnKqF/tCLm9YtXEpb6K+urpYnIgAA0Bb18HTbIqnUxp/O79P5\nvkVSp/GQANUcVNpGSAp0ymr7zmKxWP5am6tFLVwCoA9WL6YBkrRIaluAunodsLpI6rEBqmPUdrss\nklo3B3X1NUoB6moVKhybkBRovU0t9BHbZ+00mYVLAPSVzzfgoVKAus5qEUVVVcsW/no4t6mNn8N5\n7BzUenhqkRTHICQFWue+Fvq2BqPrFi6luaJdXLgEADSPSjm6ZpdFUvUq1NQiXpblnT87HA7vBK2+\nTw5rlzb+FKDWn/+qqmI4HEZVVZFlmTmoPIqQFGiF1VC0TQuXNs0k3bZw6fLyUgv9jtq6+RUAgPPa\nJUCtV6FGRMzn85jNZhERW1v4m3x90ja7BKjPnz/fGF6bg8quhKRAI93XQt/GANHCpcM79FIsOAXf\n5wDQfPUALbXyp6KG+n/XF0mlKtRU3biphd+5wOGsLoVavU7cNAc1IuJXfuVX4vOf//xJHiftICQF\nGqF+lzZVjCZtvhubQtGyLOOtt96KCAuXaDah8+N5DgE4hBS00Tz18HSXRVL1JVKHXCTF+zZVkW57\nTr/5zW8e+2HRMkJS4GzSHdf6PyPaHYquttAvFosYj9871D558sRgcRrNexMAYLNdZ5Het0iqHqCu\nhqgC1NNxY5tVQlLgZOoLl7rSQh8RL22hTwuXLi8vYzwex2KxiKdPn248UQIAAPrhvgC1Hp5WVbXs\nSqsHqJva+IHHEZICR9PVFvp0spJ+pE2KeZ6vbaFv49cI7Mf3OwCwr10WSdWrUNO1SFmWd/7sapCa\n/m7u8pywSkgKHNSmhUttD0VXq0XTwqXr62sLl85oMBjcCd8BAKCLdglQ69di9d0IEbG1hb/t1zLa\n5jkUISnwKPUW+vRhnLS5hX51C/1gMIgsy2IymcR4PG7t1wUAAHRLPehcbeVPAWK9hT8VgKRruW0t\n/G0KUB/6WNv0tXEaQlLgQVbvUC4Wi+WvtflO5LqFS1mWRZZlMZ1OzfkBAABapx6erpuFutrCX18i\nZZEUfSMkBe7VxRb6iPsXLh3q6xoMBlpAAAB4kF03qXM6XXxN7lskVQ9QV0NUi6ToGiEp8JL7Wujb\nGow+dOES9JFAH6DfUustwH0Baj08Tdda9QC1Hp4KUGkDISkQEfFSKNqFalELl+BhVD0DALCLXRZJ\n1atQU5FKWZYvBaj1f09/90N0scKX8xCSQk+tfljVdXXhUpZlPjw7RqgHAADNskuAWq9CTddwqYNx\n2wzUQ13PuYZgHSEp9ET9gyhVjEZEvPvuu5HneeR53soAsQ0LlwR5AAAAcSfo3LZIKlWhps7AdD27\nLjxNf+4h5vN5ZFn2+C+IThGSQoelD5X6PyPuttCnD5VzB4kPcaqFSwAAAIm27uNLc1C3Baj14p/0\n7xHvFQBtq0KtE5KyjpAUOqS+cKkeika0u4XewiUAAIB+27RIarFYxIsXL2I6na5dJPWXf/mX8du/\n/dvxPd/zPcsf3/3d3x0REc+ePYvLy8tTfykn85u/+ZvxJ3/yJzEcDuMHf/AH43Of+1xcXFyc+2E1\nlpAUWmxTC33E7guXmtgKbuESAAB917RzdGiy1eVPdZ/5zGfi05/+dHzta1+Lr3/96/H1r389/vZv\n/za+9KUvxQc/+MH40Ic+FK+//nq89tpr8frrry9/vPbaa/GBD3zgDF/NYXzjG9+IP/zDP4x/+Zd/\niYuLi/jZn/3Z+PznPx8///M/f+6H1lhCUmiZ+oyWTS30bdSHhUvacwBgO6EQ3OXcER4vz/P4+Mc/\nHh//+MeXP/df//Vf8eu//uvxZ3/2Z/Gf//mf8dWvfjW++tWvxte+9rX4i7/4i+W/T6fTeP311+OP\n//iP7/z5Nri5uYksy+LZs2cxGo3i2bNnywpa1hOSQsPVW+hTOJq0vYW+vnCpLMtlteh0Ol3bRtFW\nTm6Pp4mV0OA9CY/jcxOAY5vP5zEej2M0GsWrr74ar776avz4j//4nd9TVVX893//d3z1q1+N7/qu\n7zrTI93fBz/4wfi1X/u1ePXVV2M6ncZP/uRPxk/8xE+c+2E1WjvTFeiwVClaFEXMZrN48eJF3N7e\nRlEUy0rE1U1+h/h/nkKaFfPOO+/Et7/97Xj27FlERFxeXsYrr7wST548iclk0qmAFNpGwAcA8DLn\nSM21z2uzy+KmwWAQH/nIR+LTn/50XF1d7fvwzuZrX/ta/M7v/E584xvfiG9+85vx9OnT+NM//dNz\nP6xGU0kKDXDOFvpj/t0WLkG7qN56PM8hAHSbz/pmeujrUhRF5Hl+pEfTDP/4j/8YP/ZjPxYf+tCH\nIiLip3/6p+Pv/u7v4jOf+cyZH1lzSSjgDFIoOp/P4/b2Nl68eBGz2SyKooiI99vo2zZjNLXQP3/+\nPN5+++34n//5n3jx4kUMh8O4vr6OV155Ja6vr+Pi4kJACgDQQGaoA32wSyVp233f931f/P3f/308\nf/48qqqKL37xi/H93//9535YjaaSFE4gVYbW54pauNQvaXam5wMAAOC80kzSLvvEJz4RP/dzPxc/\n8iM/EsPhMH7oh34ofvmXf/ncD6vRuv2OgDPa1EIf0ayFSw9dfNOnhUsAAAB0Tx8qSSMiPvvZz8Zn\nP/vZcz+M1hCSwoHct4W+zdWii8ViGYoWRRHD4TCyLIvLy8sYj8et/bpoP9vt6QPvcYB+0oUEu9nn\ne6UPM0l5OCEpPMJqKNqVFnoLlwCaoa2fIwDQNULrbulLJSkPIySFB6hXiza5hf6hyrK800JfFMWy\nhf76+jpGo5ETggNQDQYAAHB+QlLWEZLCFikUTXNFu9RCnxYuzWazWCwWURSFhUtH5PkEAABohlQY\nBHXeEbBi08KltoeimxYuDYfDGI1GcX19fe6HCJyZGa8AALTNPuevqUgI6oSk9N59C5fa2kIfsdvC\npRcvXsRisTj3Q4W9CfUAAKDfHlrMpN2edYSk9E6XW+j3Wbikcow2a+v3KgAAcD5CUtYRktILXW6h\nX60WtXCpmYTRAEAbOF9pDtvUm8Xr0S1CUtYRktJJXW6hTwuX0o/BYGDhEkCLOE4DTec4BXRdURQx\nnU7P/TDwLC08AAAgAElEQVRoGCEpnVBvoU/VokkXqkXXLVzKsiym02mMRqNH/f0qHAEAAGirfap8\nVZKyjpCU1trUQh8RrQ9FV6tFR6PRSwuXAAAAgIez3Z51hKS0xn0t9G0PRh+6cIn2UbF7HJ5XmsZ7\nEgCg2VSSso6QlEZbDUUtXKKtvJ7H4Xk9PAHf43hPAkA3OUfqFiEp6whJaZR6tei6Fvo2V1Q2deGS\nmaRAIuADzs05CdBkzpWaaZ+ZpNrtWUdIylnVFy6litGnT5/GdDpdzt5s6wfRsRcuAQAA3eSGATzM\nPiHpeCwS4y7vCE5u08KlFIimu0BtC0ctXOI+TnYB4H7Ol+B9vh/gOLTbs46QlJMpiiKKouhcC329\nWrStC5eEd8fnBBcAAKAZtNuzjpCUk0mt9W2sEk26uHCpbY8X6szUpY28ZwEAzkslKesISTm5+0K5\npoUeTV24BEB7lGUZs9ls+VkSETEcDl/60eYbiQDQZfssB+I09nlthKSsIySFFRYuAfBYqfMgBaNl\nWS7HsdQ/R+rzrMuyXJ7kp9C0vuBQgAqcgiAI6APt9qwjJKX3+r5wqWmVu13leYbuq6pqGXZ++9vf\njsFgEHmev/RZ8vz5840zueuhaP3H8+fPo6qqOxWnqxWoAADsRiUp6whJaZxThEmrC5ciIrIsi4uL\ni1YtXAI4NGH+w9TnVKebbIPBIG5ubvbqPEjVoulzqCiKiIiYTqcvhafp/12vMtW+DwBwPyEp6whJ\n6YV1C5eyLFvOFlWFA2CR2y7WjWSp32Srqireeeedo4xmGQwGMRqNXvq769Wn97Xv16tQBagAzWXs\nAexun5v82u1ZR0hKZ6220A+Hw+Vc0a630D+ENnDazPuXU0ht9Gm+aPo8WTeSZbFYnPzxrVaf1q22\n7y8Wi2V4qn0fAHYnuG42i5s4BCEpJ7PrQWvf0GNTdU+6kNVCzzkJ86BdUvfBbDaLoihiPB5Hnuet\nW+B3X4CqfR8A6CMhKesISWmtdQuX0hb6q6ur5Vw4ALjPphttk8kksizr5OeJ9n0AoK/STXCo847g\nZB5y4bSp4s7CJQAOZdNYlr7faNO+DwB0nZmkrCMkpXHqF1IWLh2fNnCgTxaLxXK2aP0z5ZBt9F0+\npmrfBwCaZp95sdrtWUdISuOklsenT59auATAo9Tb6GezWVRVFXmeH62Nvs+fUdr3AYA2cZ7BKiEp\nZ5e2BqeqnsViEaPRKCaTiYVLdIaK3eNIJza2jR5OF96n69ro8zyP6+vrVrbRt/010b4P7eIztRna\nfuzvIt8b0H1CUk5uXQt9feHS7e1tDIfDuLi4OPdD7RUf+kBbjwEpZFvXRt/Em21tfZ6PQfs+wGaO\nZwCnJSTlpJ49exZFUURELOeKjsfjOxdHs9nsXA+vl5x8AW2U2uhTMBoRnd9G3zfa9wGAXSj44VCE\npJxUmi26rVVOWzIA66QwbDabRVEUrW+j30UXv6bH0r4PAMAxCEk5mcFgEFmWNa7tEU5B+A8PVx/P\nMpvNoizLGI/Hked5XF1d+TzhJYdq30+/V/UpAEB/CEmBZYDnQhA4t/oyv3ob/eXlZYzHY8cp9vaQ\n9v2IiNvbW+37Z+CGIgBwLkJSTmqXi4nBYLC8QAG4j5C//Vbb6EejUWRZFk+ePNEKzdGtqz4tiiKm\n0+ny+KJ9/7Q8f0ATpeM+zbLvzTWfNawjJOWkBBkArGujz7JMGz2Nc6j2/Xp46jwIAA7P5yuHICQF\nzMs8Ec8xfVZvo5/NZss51droaauHtO+n8FT7PrArxSUApyckpXEEdnSRk1za4pDH37IsYzabLcPR\n8XgcWZbFzc3NS8ESdMV91afa9wEAmklICgBExOPD/NRGn4JRbfS01bFu1mrfBwBoLiEpALC31Eaf\ngtHBYBB5nmujp/VO/d7Vvk8TpBsE3jvwMiMQmmmf10XnKpsISTmZXQ9c2u1Pz3NOm3n/nl6qcKu3\n0ed5HtPpVBs9HJj2fQA4rKIoYjwWh/Ey7wqAExDk0WZVVUVRFMtQNLXRX1xcxPX1tcBlhe91TkX7\nPgA83Hw+jyzLzv0waCAhKQDwktU2+uFwaBv9DjwvNIX2fQBYL3VCwSrvChpHxd3pec6BiPfa6Kuq\nirfffjuKoogsyyLLMm300CHa96EdzL+E4ymKIvI8P/fDoIGEpADQU/U2+tlstgxCJpNJZFnm4gx6\nRvs+AG2zzw0F7fZsIiSlkVQ10jWqdY/Hc/swqbU2/Uht9NfX1xER8fTpU3fWgZdo3wf6TnVvd2i3\nZxPvChrHBw/A4aTQIs0WrbfRX15e3qkYS6EGwK4O3b7vGATAsakkZRMhKSfnDlzzqMSDbklt9CkY\nraoq8jzXRg+c1D7t+xERz549e6l1X/UpAIeyWCyEpKwlJOVkHnJSK7ADeJh1bfR5nsf19XWMRiPB\nAtAom9r3nz59GpPJJCJC+z4A9zKTlEMSktI4TnDpKuE/h1RV1bLyaj6fx2KxiPF4HHmev9RGD9AW\n9RB01T7t++m/ASARkrKJkJSTcpLaTNrtj897n0NYbaOPiMiyTBs90Av7tO+XZXnnz2nf385YrOZw\nbt48vj+6w+ImNvGuoHEEdsBDdfmYkVpNZ7NZFEURo9FouY1eGz3Aeza179erT7Xv0zbeg3AcRVFE\nnufnfhg0kJAUgFbr2gVEvY1+NptFWZbLNvqrqytt9AAPcF/1qfZ9gP7Rbs8mQlIAOLOqqu4sXYp4\nr43+8vIyxuOxC3KgN07Zzqp9H6D9LG7ikISkNI52+9PznB+f55hVZVkuZ4umuUhZlsWTJ0/OWqnk\nfQqgfR+gy4SkbCIkBYATWNdGn2VZo9roXcADbKd9H6D9iqIQkrKWkBQAjqTeRj+bzWIwGESe59ro\nATpI+z50m+323aGSlE2EpDSWD6HT0QpOmzXt/ZsufOtt9Hmex83NzUttmwD0g/Z9gOMwk5RDEpJy\nUruEGU746KomBXkcTmqjT/NFm9hGz+mkzzA3+oBdaN9nE58jcDxFUcR4LA7jZd4VACfgJLdbUht9\nCkaHw6Ft9OzsodXPbrBAP2nfBziOoiji6urq3A+DBhKS0kjpAtKJHNAU9aVL6e5znucxnU610XM0\nPgeBdbTvA+xPuz2bCEmBxs10hCaoqiqKoljOFk1t9JPJJLIsczEJQOM8tn0/nROmLgnt+/Ae10rN\ntc9rIyRlEyEpJyWMA5osVdykH6mN/urqKkajkQtFAFprl/b9oihisVho34cNvOeb6aGvS1EUQlLW\nEpLSSMJUusZ7+nge+9yuttFnWRZZlvWyjd7SIYB+Su37Ee99Lk4mk4jQvg90k0pSNhGScnIuvptn\nMBhEWZbnfhhwEvU2+tlsFlVVRZ7n2ugBYMVj2/frwan2faApVJKyiZAUgM7b1EZ/fX2tjR4A9rBL\n+349QNW+/zAKS+B4VJKyiZCUk9r1g15rMvAY6eJsNpvFfD6/00Z/eXm59oIOADiM1L6/OrZG+/7D\n9PFrhodKlesPISRlEyEpwAkI/o8vtdGnYDQibKMHgAbRvk9bqeztFu32bCIkpbEESqcjwKOt0kXU\nYrGIZ8+exXA4jDzPtdHTeI65AHdp3wdORSUpmwhJaSQnNMA6VVUtL4zm83ksFosYDAYxHo/jyZMn\n2ugBoIO07wOHpJKUTYSkADRaVVV3li5FvNdGP51OYzwex7Nnz2I0GglIAaBntO8D+4xCKIoixmNx\nGC/zrqCxtCKejnb70zHPaDepEmQ2m0VRFDEajWyjBwB2pn0f2ES7PZsISWkkJyB0jff0dvU2+tls\nFmVZRpZlked5XF1dqRI9oXTTxHsWoH/6cvzXvg/9JiRlEyEpJ+XkAUjqbfSz2SwGg0FkWRaXl5cx\nHo8dLwB6yvGfc2lS+35fAuu28Hp0i5CUTYSkNJL2b+imsixjNpstw9HxeBxZlsXNzc2jLySgSVxM\nwcM5ltNk2vehOyxuYhMhKSflRKCZhNIcS2qjT8HoMdroHVdoGu9JgH45Rvs+sJt9bkyrJGUTISnA\nifRl1uO6Nvo8z7XRAwC98tD2/Xqgmn7PYrE4SPs+8D4hKZsISWkklY3QLqmtrN5Gn+d53NzcvFRV\nAQDQd/cFqM+fP4/RaBSDwUD7PhyYdns2EZICQmkebFMb/cXFhW30AACPkALP0WgU4/H7l+yp+rRe\ngbpr+74A9XH60A3WJypJ2URICsBOUht9CkaHw6Ft9AAAJ1IPO7fNP13Xvr8anGrfpyv2DbC991lH\nSEojqWyki9r4vk7tXbPZbNmWkmVZTKfTRrXRt+15bTrPJwCc10M/i+9r30/haeoGShWoEbG2dV+A\nSpc512UTISkAS1VVRVEUy9miqY1+MplElmWNPFluY/jcZE18jQGgjw71mZxa9zdVn+7Svr/6784X\ngC4SkgJCpp5LJ8TpR2qjv7q6Wi4MAACgWx7Svp9a+Ovt+5sWSEHTeZ+yiZCUk9r1YCS0g+OqL11q\nchs9AHA6ltOQaN8H+khICtAD9Tb62WwWVVVFnueNbqMHAKB5+ti+7wZCc3ltOCQhKaBy90RO/Tyv\na6PP8zyur6+10QMAcFDa94G2E5LSSIPBYNmuAewmnXiua6O/vLxc2y7VBY4XAADNpn2fJvHeYRMh\nKUCLpTb6FIxGROO30QMAsF2furz62L4PNJOQFNBu3zLpBHE2m0VRFNroAQA6qO/ndNr3uY9rWA5N\nSEojCe3oon3f1/W2o9lsFmVZxng8jjzP4+rqqrNt9JyH4+9hHPI59HoAwF2nbt+3HKjZvDYcipAU\noIGqqrqzdCkilrNFx+OxEwFosEN+f/peB4CHOUb7PtAPQlJO6iEfMCpn6JvVNvrRaBRZlsWTJ0+c\noEGH+F4GgNN7TPt+/bNb+367pdca1hGS0kg+bE4rPd/aSE5rXRt9lmXa6B9IezgAAI9xX/v+7e3t\n8lrpEO37nM9isYjxWBTGet4ZACdUluVyE/1sNovBYBB5nmujB6D33PBqBucicFcKPauqijzPlz//\nmPZ932eHsU+Rz3w+jyzLjvSIaDshKY3lRJmuSMHoYrGId999N8bjcWRZFjc3Ny+1+gBAnwkOzsv5\nN+zuMe37q8Gp9v3Tmc/nKknZyDuDRvLhQJulNvpUMZra6IfDYUwmk7i4uDj3QwQAoMGMwWqWh74e\n97Xvp+C0Pn5L+/5pzOfzOxXBUCckBSLi/bmOPnz3k7bRp2B0XRv9O++84/kFAIAeGwwGMRqNNlaf\nat8/rqIotNuzkZCUxtLuQ9Olu77px3g8jjzPYzqdaqOn1Rx/AQBOS/v+w+07k1S7PZt4Z3AW9x3M\nun4wp52qqoqiKJahaGqjv7i4iOvr63vft7awH4fn9bAcfwEAmkX7/uFY3MQ2QlJOqq8H4jYQNK23\n2kY/HA4jyzLb6AEAgLPTvv8wRVGYScpGQlIaSWDHOaW7r7PZbDmzJssybfQAAEAraN9fTyUp2whJ\nObkuHFjplnob/Ww2i6qqIs/zmEwmkWWZ9ywAAPRYCg67oivt+/sUVglJ2UZICkRE/6p3U7tJ+pHa\n6K+vr2M0Gh3lQ75vzzEAAA/nfJFzalv7vsVNHJJ3Bo0kTOIYFovFcrZovY3+8vKyU3eGAQBoP91M\nNElX2vcXi4VKUjYSkgKdldroUzCqjb6b3FQBgMPweQrso03t+9rt2UZICnTKujb6PM+P2kYPsErQ\nALSVcyXgkJrWvi8kZRshKY2kMuz02vqc1+9GzufzWCwWMR6PI8/zRrbRt/E5pn+8Tx9HwAAA3ZJC\nOw7nEO376fcuFoudq0+FpGwjJAVaZ7WNPiIiy7LGt9E39XFBnfcpAADntGv7flEUUVVV3N7erm3f\nf/PNN6Oqqnj99ddjOp1GRCx3U3TZt7/97fjFX/zF+Od//ucYDAbxR3/0R/GjP/qj535YrSAk5eQe\nUrHojh1Jar+YzWZRFEWMRqOjb6MHAACgOVbb9xeLRUwmk7Xt+3/9138df/7nfx7/8R//ER/+8Ifj\ntddeiw9/+MNRlmV84QtfiDfeeCM+9rGPNa778LH+z//5P/FTP/VT8Vd/9VdRFEW8++67535IrTG4\nJ6zSb8fB3d7e7hR+futb34rv+I7vEH6dyNtvvx2TySTyPD/3Q4mIu230s9ksyrJcttFnWdbKD7Jn\nz57FYDBY3sXkMObzeTx79iw+8IEPnPuhdMI777wTFxcXjTkWtNFbb70VV1dXMR6vvxc9m81isVi8\n1Fq2TlVV8e6778b19fWhHyZbPH36NK6urpyDnFhZlvH8+fO4uro690Pprdvb2xgMBj4Dzsyxv3me\nP38eWZZt/GznPNK4tclkcu/v+/d///d4880342/+5m/iy1/+cmRZFm+++WZ861vfitdffz3eeOON\n+N7v/d544403lv/+wQ9+8ERfyeG89dZb8clPfjK+/vWvn/uhNNnGEzzf4UBENKPFtqqqO0uXIt5r\no7+8vIzxeNyIx0jzeF8AAF2imw52s2uHapZl8frrr8frr7++DBF/6Zd+KSLeuzH6r//6r/Hmm2/G\nV77ylfjCF74Qf/AHfxBf+cpX4tVXX40vf/nLx/wSDu7f/u3f4ju/8zvjF37hF+Kf/umf4od/+Ifj\nd3/3d+Py8vLcD60VhKTAWZVluZwtOp/PYzweR5Zl8eTJk52Hb7dFW5djAQAANNFDrxeLorgTGF5f\nX8cnP/nJ+OQnP3nn91VVFW+99dZBHuMpFUURX/rSl+L3f//341Of+lT86q/+avzWb/1W/MZv/Ma5\nH1ortK9fld4QKHVTWrr0/PnzeOutt+Ktt96Koigiz/N45ZVX4ubmJqbTqTmjAABAI6ju7Y75fL7T\nSJHBYBCvvPLKCR7RYX30ox+Nj370o/GpT30qIiJ+5md+Jr70pS+d+VG1h0pSTk742UzHfF3qbfSz\n2Ww560obPQCQOD8E4Njm83mnt9t/5CMfiY997GPx5ptvxhtvvBFf/OIX4wd+4AfO/bBaQ0hKozlZ\nbq+0dKneRp/nedzc3Oy0rAQA6B83TgE4psVi0emQNCLi937v9+Izn/lMzGazeO211+Jzn/vcuR9S\nawhJOYtd2hWcJLdL2kaf5ouWZRlZlkWe53F1ddXKbfTHIPg/Ds/r4aj2B+ivqqqcswGtsc8YhFTA\n02Wf+MQn4h/+4R/O/TBaqdvvDBpJ+NlM+wQjqY0+BaPD4dA2+i08H8fheQUAAHbR9XZ7HkdISqOp\nZmqe1EY/m82iKIplG31atgQAAOzPkqDm8Zp0R1EUQlI2EpLSWD6EmiFto0+zRVMb/WQyiSzLvE4A\nAAC0gkpSthGSAi8py/LO0qXURn91dRWj0UgwCgAAwFntU+GrkpRthKQ0mnb706nPF00fHFmWaaM/\nIAtxgGTXY0E68dfmBwDwsn0WNwlJ2URISmO5GDyuehv9bDaLsixjNBrFdDrVRk+rCJ9pIu9JAIDm\nEZKyjZAUemRTG/319XXc3t7GcDiMPM/P/TABOs1NKACA89BuzzZCUhpLddjjVVUVZVnGbDaL+Xx+\np43+8vIyhsPh8vfOZjPPN+DYewBCUADoFmNvukMlKdsISTk5Hy7HldroUzAaETttoxeMHJ/nGACA\n+zhfhN3sE14LSdlGSAodsK6NPs/zuL6+to0eAABaxvk7HIeQlG2EpJzcrh/4qu42q6oqFovFMhRd\nLBYxHo8jz/OX2ugBAGAXWoqBrkvXzrCOdwa0RFVVd6pFI95ro59OpzEejx99QjsYDKIsy0M8VDgp\nN1Rom7IsoyxLYQQAwImpJGUbISk0WGqjn81mURRFjEaj5TZ6bfTtJMyD/qlX/89ms+UNqdlsFoPB\nIIbD4Us/HN8BoBmcvzeXmaQcmpCUxupjddi6C+ksyyLP87i6utJG33JCD+iP+hK92WwWEe9V/19e\nXi5/bTQaRVVVy8rSdPwvyzIGg8EyQI2I5e9PPw8AnJbP324oikJIykZCUjizeht9qipKF9KHaKPf\nVR9DaYBDSuHnYrGId999NwaDwdolemlkymoQWv976uFp+jOz2SyqqtpYeeriDQBgO5WkbCMkhTMo\nyzJms9kyHB2Px5FlWdzc3GizBGiRdKMrHdPTMXwymcRkMtnr71wNT2ezWUyn0+XNrBSeppEsab5p\n+n9r3QcAWC+dM8E6QlIaq0uVjamNPl1Ea6MHmqwrx95jqarqzo2u0WgUeZ7HdDqN0WgUb7/9doxG\no6P8vweDQYxGo5f+/tXwtCiK5c+ZewrQLhb7AZyHkBSOZF0bfZ7nJ2+jpzm6FPw3SfpeckFxGJ7D\n9eqL9FKbVhqN0oQbXdvC021zT+uBqdZ9zs1nJAAP4fyfQxOScnIPOYi17WQ5XXzW2+jzPI+bm5uj\nVRUdigAP4K40GmU2m8VisVge09vUAbDr3NN69am5pwDwPkEc9IeQlMZqQ2i3qY3+4uKiVRfRALwn\nHdNns9nymD6ZTCLLsk5dIG0KTyNebt1fnXu6bvZpl54bzst7CQA4FyEpPNC6JR3n2EYPwOOtu9l1\niNEoTb/Jt81D5p6m8NTcUwCgDdp8jsbxCUlptKYcwFIb/Ww2i6IolrPo0pKOLmhD5W7beY6hGaqq\niqIolsf1iDAzegePnXtar0DVug/NpK0YaBPHLA5NSEpjnfNgV7+ArrfRd7HlEqAP0nE9tdKnLoDr\n6+sYjUaO64+w69zTxWKx/PeIMPcUADg5I/HYRkgK/yvNXUs/0gX01dWVC2houFSl6/uUunXjUU6x\nTM/78D2PnXu6rvoUoA+c0zSL1wP6Q0hKox27Nbk+h66rbfQAD9XmsRApcEvjUUaj0bKVXuVAc+w6\n97Qenpp7CgDAMQlJaaxjXPSszqGrqiryPNdGH+ZlnornmKZr47GgLMtlG3264ZXneVxdXQlGW+a+\n8DT9c9vcU+EpAHRf285XaQchKSd36ouWdW30eZ6bQ8fJea/B4dQ7ARaLRavmRjf98TVRCk9XbVsa\nFWHuKQB0nc90DklISmPtW82ULpbqF8/j8TiyLNNuCdBSVVUtA7DZbBZlWeoEYKelUemf2+aeCk8B\noPtUn3IfISmdUN9aPJ/PIyJaVVXUBG1ssQW6LQWjqZU+IpY3vMbjsWM7G+27NKr+Z4qi0LoPAB2y\nWCzsHmErISmttbqcQxs99JeQvzvW3fRybOeQdlkatVgsoiiK5c+ZewrQX7bbd8d8Po8sy879MGgw\nISmNtRp61Fst6230lnPQFoI8WK+qquVNr/rs6CdPnrjbz8nUw9Pb29uYTCbL4/amuaf1ilWt+8Ch\nOF+E++0TXs/n8xiPxWBs5t1Bo1VVtbxorrfRT6dTrZYALbZ6fB+NRpHneUynU8EojbLL3NPUrm/u\nKXAojhVwePP5PPI8P/fDoMGEpDROaqO/vb2NxWIRL168iCzL4smTJ1rbjkiVI3Bs9TEpqd3JUj3a\nat+5p+lcRus+TaStGOiyxWKh3Z6thKScTToJW7exOMuyGI/HUZZl3NzcnPuhAvTGYDCIsiwP9veV\nZblcvGRMyvuEEN22y9zTsizNPQWAE0rdS7CJkJSTS8HofD5fLucYDAaR5/mdjcVFUSxb7KFLVGkc\nnkroZqlvpE83viaTSWRZ5r2/J8eNbtgWnm6be1oPTLXuA8B+s3stbuI+QlLO4vb2NoqiiCzL4ubm\nxt2cBhAyHZ+LWboqdQSkNvqyLF+68cX+PH/dt+vc03r1qbmnAKfhRmVz7bO4yUxSthGSchbT6TQi\nth/UhHYAzVVV1bLifzabRUQIRuHAHjP3dFP1KQD0VSrUgk2EpADATlIwmlrph8NhZFkW19fXMRqN\nBDA1bvJxbLvOPV0sFsvw1NxTAPpMuz33EZICd2gnAerSDOnUSj8cDiPPc6NStnAM5ZweO/e0Xn16\n6tZ9NxfgPakiHDis+Xwe47EYjM28O2gs7fan5aL+NNL72vNNk1VVFbe3tzGbzaIoihiNRstWehdt\n0E67zj1NladlWUZEnHzuqc9HAHaxzzVVURRmkrKVkBSATnBT5XHKsozZbBYvXrxYtubmeR5XV1eC\nUeiw+8LTeoC6ae7pavUpQJcocOgO7fbcR0gKQOs5cd1ParedzWaxWCwiy7JlC9L19fWZH123CfVp\nunq16H1zT+vhqbmnADSVkJT7CElpLO32p6cVHLotBRtp8VJZlpHneUwmk8iyLAaDQdze3sZ8Pj/3\nQwUa7L6lUemf2+aeCk8BODUhKfcRknIWAlD6ynufU6uqKhaLxTIYjYjIsiwuLy9jPB4LKICDSeHp\nqm1LoyLen3ta/32nXhrFe9wsB9pin2uqoiiEpGwlJKXxnKwBPExVVVEUxXIjfUREnudxfX0do9HI\nMRU4qV2WRlVVFfP5PKqqiufPn6+de3rspVEAtMs+i5tst2cb7w4aywkwwO5SwJBmjA6Hw8jzPJ48\neaKlFWikdeHpYrGIyWRi7im9pusIjkO7PfcRkgJLWsFpq76+d6uqWlaLzufzGI1Gked53NzcrG15\nBWiL++aermvdF57SJd63zaGzsTuEpNxHSErj+VCia/oY5nE4qaIqhaNZli1njK62sgJ0zbbwdNPc\n03rFqtZ9gP4qiiImk8m5HwYNJiTlLHat+nLiStd4T7OP+kb6xWIR4/E48jyPq6srwShA7Db3tB6g\nptZ9c08B2mmfYqr5fB43NzdHekR0gZAUWOpryzI0UX0jfVmWkWVZTCaTyLLMxTucgO+zbtgUnka8\n3Lpfn3taD0y17gN0g3Z77iMk5Wx2ufMjtAP6oqqqZTCaLtTzPI/Ly8sYj8cnuzB33AX6Yte5p0VR\nLH/O3FOA9iqKQkjKVkJSzsKJJMB7F+JFUSxnjEbEWYJRAN6379zTddWnWveh/VJ1Oe2nkpT7CEkB\nTkiV3nG06XlNwWhqpR8Oh5FlWVxfX8doNHIxzXGUZYz/5V+i+sAHYvHRj5770UArPWTuaVEUUZZl\nRNVCXEAAACAASURBVIS5pwBHsM+5v5CU+whJabQ2BR9d4PmG46iq6s5G+uFwGHmex83NzUuVSnRD\n046lw//3/yL7v/834uIingtJ4aAeO/d0XfXpOTTtuNVn+yykgT566PeJdnvuIyQFgCNIF8Oz2SyK\noojRaLRspdey1W1NvLAtP/jBKP4/e/ceJFtZ3/v/s9bqtbqnu/fsDRvcXBSR+2aziRiNRk6kRC1O\nPIImmPIk8rOsSsyppBIS/R2xKgK5VCKxQmLUJJb+Ei2NsYh3waiUHDUSiRrFkHBROeAFspEtuK9z\n6XV7fn+wn0VPT89MT093r9v7VbUL2TMta7rXrH7Wp7/P93vuuUp37Mj7UAqPoAiTNGrf0yRJsvA0\n776nRbyGAcAkUEmKjRCSAgAwIWmaZtWidhEWBIE6nQ7BKPLleYqe+cy8jwLAMVvte9pffcrWfQAY\nTZIkajSIwbA2zg4UGtu/Z4vne/p4jqvH3sCGYagkSbJgtNvtctMKANiUUfue2spT+p4CwOioJMVG\nCEkBANikJEmywUtpmsr3fbVaLfm+zw0pAGDiNgpP+wPUtfqeEp4C46FHbDHZa9xmEJJiI4SkAIDS\nm3aFrjFmRTAqSb7vq91uq9FosHAGgAlgp8Xm9QeeG/U97Q9Ph/U95b0MQNUxuAkbISRFLkZdhLE1\nGUBejDGK4zjrMSop20bveV6lbya57gLIS5WvrbO20dAo+8/+vqeStLS0RIAKoJKoJMVGCEkBZAil\nUXfGmGzoUhiGcl1XQRBo27ZttblJrMPPmDeeYwB5suHpoDRNtbi4KN/3h4anbN2fHdbjwHQQkmIj\nhKTIBYsp1BVBdPHYYNRWjHqepyAIND8/P/QmEgCAKrLr88HJz4M9T+37Jn1Pp4vnD1jfOL1iCUmx\nEUJSFBqBEoBpsL3ZbDDq+37WY3SzDeABAKiytYZGSev3PbVhKVv3UXbcj1YHPUmxEUJSABlCaZTZ\nRudumqbZ4KUkSdRoNBQEgTqdDsEoCo9rM4Ai2qjvqf3Tv3V/WHBKeIqi4/ysBipJsRFCUgBA6a21\ncO2fSJ+mqXzfV6vVku/7LHZRGpyrAMpmvfC0P0AdDE/XqjzlOghgEghJsRFCUhQalY2oGs7p6TLG\nZMGovekKgkDtdluNRoObLAAA1jBOf7/NWmvr/mB4mqap4jjO/p6+pwAmge322AghKQCg1Ppvqnq9\nniQRjAIAUCJb6Xs6rPcp7/1A9Y3zwU4cx6uG0wH9ODtQeFTdzQ5VjigLY4ziOM620kuS53nqdrvy\nPI+boy3iOgAAKIpR+57aytMq9D3lfRiYjjRNV11LgH6EpCi0sixkAEyfMWbFRHrXdRUEgebn59Xr\n9eQ4Dp8MTwDX3cngBhcApmvcvqfDqk+LuHW/aMdTZ7NoRQGgGLibRC54k0GdEZ6Mzm6rC8NQcRzL\n87xsK/2wfmYAAKDeNtv3NE1TSSpG39Mokrdvn5xOR+p0ZvffBQBIIiRFCRB8zA7b7aePDwg2lqZp\nVi1qJ1AGQaBOpzO0V5nEuQsAANa31b6ngxWo01jTef/1X2r84Adqzs9LO3dO/P8fqBIqfDENhKQo\nNIIPoB7sVrgwDJUkSRaMdrtdFj8oHc5ZACiXUfue9oen0+h7mu7apWRxUdGOHaJrIgDMHiEpACAX\nSZJkg5fSNJXv+2q1WvJ9n5AJAADkbqt9Twe37W+0vjFzc4rPP1/J0aPT/LEAAGsgJEWhOY6T9QnC\nbFC5i2kxxqwIRo0xWX/RRqNBMAoAAEph1L6n/eGpVJC+pwCANRGSAsiwQJu+urWQMMYojuOsx6ik\nbBu953mccwAAoDJGCU/tP9fre2ofwzqpGHgtgPogJAUATJQxJhu6FIahXNedSTBap/AZAIBJIwia\nns0OjZKkxcXFqfQ9BapinGsWvzvYCCEpcjHqxaluVXdAWdlg1FaMep4n3/c1Pz+/qo/XNLDgmRyu\nuwAAzM5g31NjjBYWFtTpdLLg1LYsWq/vKeEpAGwdISmADOEINsNWO9hgtNFoZD1Gh1VKAAAAYDTj\nDI2S6HsKAFtBSAoAM1T2YWRpmmaDl5IkyYLRTqdDMAoA2BI+qAU2NurQKLvLZ62+p4SnALAaISkK\njcpGIH92In0URUqSRL7vq9Vqyfd9FtYAAAAFsNm+p/3h6bDt+6zxnsC9aDHxumBaCEkBZAilIWlF\n36swDJWmqYIgIBgFAEwd7zHA5K23db8/PKXv6drq+nMX3WZelyRJ2PmGDRGSAgCyYNRupZck3/fV\nbrfVaDQKvzAk4AcAANiccfqe2vB0MERl6z6KLooi+b6f92Gg4AhJUWgEH6iiopzTxhjFcZwFo67r\nyvd9dbtdeZ7HQhcAAGDGirBOHLXvaZqmiuM4+3v6nqLICEkxCkJSAJihvBeJtom/7THquq6CIND8\n/PyqKgIAAADMXt7rxbVspe/pWtWnwKwQkmIUhKTIhX1DNMbw5lggVO5WkzEmC0WjKJLneQqCQHNz\ncwSjwJRwLQUA1MmofU/jOM7CU/qeYlzj5AhxHBOSYkOEpCg0QjtgPGmarghGfd9XEARqt9s0LMe6\nuO4CAIBJ2Urf08Hq0zy27lPUUx1RFKnRIALD+jhDkBvebIDJ6p9InyRJFox2u11+34AZImgGUEZc\ntzBLm+17mqapJNH3FGNjuz1GQUgKYAUWyNM16fCkfyJ9mqbyfV+tVku+79dqsUgoBQDA1tVp7YBi\n2mrf08EKVM5pWFEUKQiCvA8DBUdIikIj+JgtFhHFZ4xZEYwaY7Jt9I1Gg9cQAAAAlTRq39P+8JS+\np9VET1JMCyEpABScMUZxHGc9RiVl2+g9z2ORBwAAgNraKDy1/1yr7+ngtn3W1tUUxzE9SbEhzhAU\nHpWkqCNjTDZ0KQxDua5LMAoAAFBxDAqaHBueDlpvaJS0su9p/2N4XcqNwU0YBWcICo03otmivcFs\nrPUc22DUVox6niff9zU/Pz90gQcAAABgc0YZGtVffWqM0cLCAkOjSo6epBgFISkAzNDgIsr2TQrD\nUHEcy/O8rMfosIb1AAAAACZvWHiaJIl6vZ7m5uboe1og4xT20JMUoyAkRaFR2YgqMsZoeXk5C0Z9\n31cQBOp0OgSjY+JaMTk8l8XEawIAQH5GGRplB6yu1/eU8HRyNvs8RlFESIoNEZIiN9yIFw+vyfTY\nifS9Xk9pmiqOY7VaLfm+z0IJqBl+5wEAqIb1wtO1+p72V6yydX92CEkxCkJSAJiC/k+SwzBUmqYK\ngkDNZlO9Xk/dbjfvQwRQEtwwAQBQLqP0PbXVp/1b9+l7Oj1st8coCElRCkwTRBnYYDQMQ4VhKEny\nfV/tdluNRkOO4yiO4+xrAAAAAIpr0veha4Wn9r+1Vt9TG5aydX98VJJiFISkKDQu+ig6Y0wWfIZh\nKMdxFASBut2uPM/jHAYAAKVAUUIx0Pqqvkbpe2rbdtm/q2vf03GuV4SkGAUhKXJD/8vi4TUZjd0W\nE4ahoiiS67oKgkDz8/OrFjWYHc5dAABQBVUPuLA54/Y9HVZ9Wuet+4SkGAUhKQrPBnd1vZijGIwx\nWSgaRZE8z1MQBJqbmyMYLQCuDwBQfnZLKQBgY6P2Pe2vPq1z31M7OBdYDyEpAKzB9gKy4ajv+wqC\nQO12e+ybOKp1gXrg9xwAAORhK31P16o+rQIGN2EUhKTIFRWixVTn16V/In2SJFkw2u12a/ucAAAA\nACi/zfQ9teFpEfue0pMU00JIityMelGj8m526hoC9k+kT9NUvu+r1WrJ9/3aPieoL3vO1/nDkq3i\neQMAoBrqsh7aSt/TwQrUom7dp5IUoyAkBVA7xpgsGLVv8nYbfaPRKOSbOgAAAADM0qh9T5Mkyf63\npEL2PaWSFKMgJAVQC8YYxXGcBaOSFASBOp2OPM+b6Rs2ldHTwfMKAAAATN9W+54Oqz6dNkJSjIKQ\nFIXHdvvZss93FaopjTHZNPowDOW6btZfdNbBqFWF57WIeF4BAEAVVGUdjvoate9pf3g6i76nbLfH\nKAhJAVSKDUZtxajnefJ9X/Pz86veqAEAAAAA07dReGr/uV7fU/uHwU2YFkJSAKVnP4m0wWij0ch6\njA7bAgIAAAAAG6Gyd/pseDpovaFR9nFpmo7c95RKUoyCkBSFx3b72SrL852maTaR3r7h2R6jBKMA\nAACbQxgEoEjWGxrV6/UkSZ7nDe17euONNyoIAp177rk677zzdOaZZ9amkjRJEj372c/WU5/6VN1y\nyy15H07pEJICKI3+ifRJksj3fbVaLfm+X5pFfVlCaAAAAAAoGhueOo6zKvS0lafnnnuu7rrrLn3w\ngx/U/fffr0ceeUQnnXSS7r33Xj3vec/T7t27tXv3bp177rnqdDo5/STT8fa3v13nn3++jhw5kveh\nlBIhKXKzmVCLUKmejDHZtoowDJWmqYIgKF0wiukjfAYAAADqwVaMDrJb91/1qlfpVa96Vfb3S0tL\neuMb36gLL7xQR44c0c0336y3vvWtuv/++7Vr164sNLV/9uzZo+OOO26WP9JEPPzww/rMZz6jN7/5\nzfqLv/iLvA+nlAhJUXgEYfVig1G7lV6SfN9Xu91Wo9HgfABmwIbO/L4BAACg7Obm5uS6rq644gqd\nffbZ2d8nSaLvfe97uu+++3Tffffpjjvu0N/93d/pkksu0Vvf+tYcj3g8r3/96/Vnf/ZnOnz4cN6H\nUlqEpMgNN9/FlEdFnjFGcRxnwajjOAqCQN1uV57nca4AAACgFviQEpgOO+C3n+d5Ouuss3TWWWfp\n8ssvz+nIJuPTn/60nvKUp+iiiy7Sl770pbwPp7QISVEKbKOtHmPMion0rusqCALNz88PnW5YNSyA\nAQAAgGJjzV4dVR/cdMcdd+jmm2/WZz7zGS0vL+vw4cN6zWteow984AN5H1qpMAIahcebUnXYSYRH\njx7VwYMHtby8rEajofn5eW3fvl1zc3OVD0g5nwEAAABgtuI4rnRI+pa3vEUPPfSQvve97+mmm27S\npZdeSkA6BipJAaww6e32aZquqBj1fT/rMTqs2TYAAAAAAGsZp8K36pWkgyjOGQ8hKQqPqdXl0z+R\nPkkSNRoNBUGgTqdDMIqp4DoBAAAAYC11CkkvueQSXXLJJXkfRikRkgKYiP6J9Gmayvd9tVot+b7P\np1gAamej0J5QHwAAYHaqvt0ek0FICmAsxpgsGI2iSGmaKggCtdttNRoNgtF12KpHniOgmvjdBgCg\nGowx7ISriDpVkmJ8hKTIzWZuIqm4mZ31ti0bYxTHcbaVXlK2jd7zPIIBoCJoXwAgD3yAmC+e/2Lg\n/RfY2DjXqzRNKz8kGFtHSIrCY7GWL2OMoijKglHXdRUEgbrdLsEoAAAAMGGsrwEgH4SkyBULgGIy\nxmT9RaMokud58n1f8/PzfPoGAFuUJInSNFWSJHJdl/dCAAAAoAAISZGrUcrk2fY5G2maKoqibDu9\nnUjfbrfpwzNhnNOTZ68jbBVEUQ0Ot3McJwtLHceR67qr/nAu18e3P/pRHXzgAf3M//7fcvkwEgCA\nieP+C6MgJAVqLE3T7KbdTvtzXVfNZlOtVivvwwOAUrPX2F6vt2K4neu66vV6ajQaMsbIGKM0TbPq\nUjsMz4an9u/tvxOeVs//ef3rFR45oqdfeqlOfs5z8j4cAACAWiIkBWqmfyJ9kiTyfV+tVku+78tx\nHB09epQbcAAYk63Kj6JIhw4dku/7mpuby66x9nssx3Gy8LNff3ja6/WUJIniOM6m7A6rOuXaXV4v\nfOtbdeD//l/tuuiikR/z9l27dNyZZ+o1d9wxxSMDgHpjl1IxjfO68DpiFISkKDzHcVbcUGJzjDFZ\nZZLd5hkEwYpgFAAwvv6qfNtn1PM8bdu2bexrbH94Gsdx1hu6v+rUBrJpmhKeltz5v/Irm/r+9150\nkZKlJT12991TOiIAAID6ISQFKsgGo/amXZJ831e73Vaj0Vj3hpl+mdPHcwyUnw0o+9uV2A+fbLX+\nNMJJx3Hked6qIXqEp/Xy/Ouu02de+1o59AwHAACYGEJS5Iabs8kyxiiO4+zmXJKCIFC325XneTzf\nALBFxpgVfZztgLtut5v7NXYz4WmSJJKUBaae5zEsqmTO+8Vf1Hm/+It5HwaAKbAfbgGYLNY4GAUh\nKQqPqru1GWOySqYoiuS6roIg0LZt21bdKANVZ68VLIC2juvuk4ocjI5irfC0PzgdNixqWOUpAABA\nEbDmx7QQkgIlY2/Y7WAQz/MUBIHm5uYmEowSjgCou8EPoGww2ul0JlLdU4RFvQ0/+/UPiyI8BQCA\nMA6oG0JSoAT6e99FUSTf97Meo2zHAYCtGwxG7QdQdbrO9g+L6kd4CtQD27wBAHVHSIrCq2tl4+C0\n5ElXMiE/dT2ngaIhGB3NKOFpkiSK45hhUQAAACgtQlKgQPon0qdpumJaMjeWALB1/UPuwjCcWjBa\nhw9C+sPTRuPJJeWwYVGEpwAAYBLGWWMlScIH4BgJISlKoao3m8aYLBi1N5H2Zr3RaORy00iVI4Cq\nGQxG7ZC7+fn5qQy5q3vgt9awKMJTAAAwKZtZI9iWdcBGCEmRu42aYVftBsnerNstnpJyD0aBKiDg\nR79ZB6PY2GbC0yRJJD05YMrzPPqdAqgFBgUBkxfH8YpdL8BaOEuQmzq9+Q+7Wfd9X91uV57n1eq5\nAGEeMC391flhGMpxHILREhgWnjIsCgBQBITW1UAlKUZFSIpSKGOgNDgQpCxVTI7jKE3TvA8DQM7K\nct0dDEalJ6rzu90uFQMlNsqwKMJTAAAwijiOCUkxEu4ekKtRblzKdHNjtwmGYag4jpmUDKCUynDd\nTZJEvV5vVTBKdX61EZ4CAFBv41T3UkmKURGSAluUpmlWLWovvkEQqNPpEIwCwAT1V4waYwhGkRkl\nPE2SRHEcbzgsCgAAVEsURewwwkg4S1AKRdv2aStUwjBUkiTyfV/NZlPdbpcbLIykaOd0VfC8Vk9/\nMJqmKYPusCn94Wn/zdGwYVH94amkrIe4DU8536aPazgAYBqiKFIQBHkfBkqAkBSFV4SbEnszNXij\n3mq15Pt+IY5xUhgqNH1VOl+KhOe1OghGMW3DhkVJT/a4XV5eznqLb1R5yjk5WTyfAIqEwU3VQE9S\njIqQFFjDsGEgvu9zow4AU9D/QVSSJJUPRvkwqphseCpJzWYz+/thladJkkiSXNeV53ls20fpEQYV\nA+8PwPrG+R2hJylGRUiKwptlZaMxRnEcZz1GJYaBAMC0DAajvu9XskIf5Tes8pRhUQCmhWsFsL5x\nBjfRkxSj4CxB7dntdLbHqOu6CoJA27ZtW7UNrw7Ybg9gmghGURWjDIsiPAUAIH/0JMWoCElRS8aY\nFRPpPc9TEASan5+vZTCK2SKIRt3Y7clhGCqOYzUaDYJRVBbhKQAAxUJPUoyKkBS5GiUsmlSg1H+T\nbnuS2B6jgzcyAMqJ8HkyJnHdtR9G9Qejtn0JwQ/qaJTwNEkSxXFcrGFRxij413+VkkThz/6sxHZF\nAEDJ2LUosBHOElTa4LZOe5Pe6XQIRoGKIXjLn21f0uv1VgSjXHOBtfWHp/03cMOGReUSnqap3EOH\npDSVkoSQFEBt2A+MWWMWyzhD5hjchFGxykHl9E+kT9OUfnebxFZwAJthg1Fbpe95nprNJsEosEXD\nhkVJOYSnnqfeJZc8EZI2m1v8qQAAmD1CUoyKkBSFZxf2a31iZIzJglF7oxAEgdrtthqNBsEoCokg\nGmU2LBi1112C0SfwO45p2Ux4miSJJMl1XXmeN3a/U9NuT/RnAABgluhJilERkiJX41YtGmMUx3F2\nky6JYBSlwfmJMrLX3V6vRzAKFNCw8JRhUUD5jLOVGMD6qCTFqAhJURr2Bt1upXddV77vq9vtyvM8\nFhMTwnZ7ANaw624QBJqbm1tVxYYn8X6EohhlWBThKQCgTOhJimkiJEXu1rvI2S2dknTo0KHsBn1+\nfp4bdAArEPBPhg1Oer2eFhYWuO4CFUR4imF4DwVQVXEcKwiCvA8DJUBIisKxfbTCMFQcx9lN+bZt\n21ZMfQXKjBsRFInt7Wy30qdpKs/zCEaBmhklPE2SRHEcT3dYFHLD6wY8idYH1RFFkbrdbt6HgRIg\ncUKu7JtOmqbZABBbCh8EQTYd+cCBA/S8Q2VQ8Ygi6B9619/bedu2bVpcXFQQBASkACStDE/7P7Ae\nNiyK8BQAUDRst8eoCEmRqyRJdOTIEaVpmgWj3W531QKaUGl2eK6B6lorGB3s7cx1oHh4PVBEw4ZF\nSYSnAIBiYbo9RkVIily5rqtWq6UgCFgcA8CU2GC01+tJGh6Morh4jarlsfvu08EHH9RZ/+N/5H0o\nUzNqeBqGodI0lfTEmjBNU8VxnP075z4AYBCDmzBNhKTIleM48n1/pIscVTQAMLr+itE0TbMWJo1G\ng+AByNHNv/zLOvzQQ/qlf/onnfq85+V9ODM1LDzt73fa6/VW/JNhUagj+mACk0clKUZFSIpSYKEw\nO2yznT7HcbLKGUwO5+7wYLTdbhOMAgVy3i/9kn70zW/q+HPOyftQCqG/32kYhlk/5P7w1A6Mstv2\nCU8BzAKBdXXEccwQaIyEswQAgBKzW1Zt5RXBKFBsz3/zm/M+hFLoD0/7EZ4CADaL7fYYFSEpSqPu\nFWIAYNlgNAxDJUki3/c1Nzc3cvsSACiiUdZ6G4WnSZJkvU0ZFgUA1TNOhS/b7TEqQlKUAotYAHU3\nLBhttVoEowAqZdzr2Xrhaf+wKFt1SngKAPVBJSlGRUiKXLEILR76Ok4fzzFGZW/owzDMPgEnGAWA\n0Q0bFiURngJAnRCSYlSEpCgNQiUAdWCMySpGbZP5IAjU7XZndoNOkA+g6kYNT+0gPElyXVee51W6\n32nVfh4AkNhuj9ERkiJXoy7EWLAB2EiZg70iBKOYrPXORfuaMjUXKJ5h4WldhkWV9T20SngNioX3\n6eqgkhSjIiQFsAI378BsGGOyrfRRFGXBaKfTWdVTDwCQn42GRVU9PMXscZ4Aa7NtUTaDkBSjIiRF\nKZS5QgwArMFg1PM8BUGgdrtNMAoAJUN4CgDlQEiKURGSAsCMEfrXC8Fo/RB2APW2UXiaJInSNFUc\nxwyLAoAZoCcpRkVICgDAhBljFMdx1mfUdV01m02CUQCosfXC0/5hUbbqlPAUACaDSlKMipAUpUDl\n3WzZ55sFOMomz+vEsGA0CALNz8+vmp4MAIA1bFiURHgK5I37oWIa53Wxg1GBjXCWAAAqIY9FLMEo\nAGBaRg1PwzBUmqaSJNd15Xke/U4BoA+VpBgVISlyxaINdURldLnZfnI2GJWkZrNJMAoAmIlh4SnD\nogBgbfQkxagISVEKhEqzxfMNrDQsGA2CQN1uV57nVe5Gk2sAAJTLRsOiRglP7fciP2zvBqYjSRKK\nGTASQlIAANaQJIl6vV4tglEAQPVsJjyVpKWlJSpPARTauB/mcA3DKAhJAQDo018xaoyR7/sEo5g4\nziUAeRoWnh49elTtdlvSE++FaZoqjmOGRQEoHK47mBZCUpQCWz9RNZzP0zHu89ofjKZpqiAI1G63\n1Wg0WIQBAGpjvcrT/mFRdss+4SmqjPYHQP0QkgJYhVB6ulhsTcdmz1uCUQAARjNsWJREeAoAKKY4\njvX444/L9301Gg01Gk/En57nqdVq+ZISY0w6+DhCUpQGoR2ArUrTNAtGkyQhGAUAYAtGDU/tB5KS\n5LquPM+j3ykAYGq+//3v6/d+7/e0c+dOLS0tKUkSdTodmyu9T9Kdkv7CcRy3PywlJEUpsHACMK7B\nYNT3fbVaLfm+z7UFAIApGBaeDhsWZStPGRYFYFS0QcAojjvuOF111VU6ePCgPvGJT2h+fl4vfvGL\n9e1vf1uSniHpq8MeR0iKXHFxKya226Ps7Ja/Xq9HMAoAQAGs1++U8PQJrL+B6eB3q3527typK664\nQrfddpuCIND73//+7GvXXXfd9ZJ+TdJfSVrxhkJICgAzRgg9HcYYJUmiI0eOKI5jNRoNgtEt4BwF\nMGtcd+qJ8HSlKvwMVcE1qTr4vaqfNE3luq6iKNLBgwd18OBBua6rTqcjSWdJsm86hKQoH0IlAMMY\nY7Kt9FEUyXVdzc3NqdvtshjaAq65W8fzV168dvni2g1ro/A0SRKlaao4jhkWhanh3KkGXsf6se8d\nl1xyie644w4997nP1Yte9CLdc889kvQ/JV197FuT/scRkgIYiptEFJUxJttKbytGgyBQo9FQmqZq\nNpt5HyKAkuNmCiiu9cLT/mFRtuqU8BSoFu5TsRmu6+rNb36zfuM3fkPf+MY39LrXvU7PetazLpMU\nSZIZOKEISVEaXAxnhwUjisYGo7Zi1PM8NZtNdTqd7CZpeXk556MEnsA1FABmb9iwKInwFKgifkex\nEbvd/pOf/KS+/OUv62/+5m90xRVX2C9fKel5kn7HcRzPGJNVkxKSohS4CKJK2Mo8mmHBaBAEarfb\nq6pHgKrjmgEA4xk1PA3DUGmaSnqi8sjzvMr1OwWAulhaWtKhQ4d099136/HHH9f+/fv16KOP6ilP\neYoknasn81B6kgIAiskYoziOsz6jBKMAAEyf/SCmTkHgsPC0rsOigCqzv7+olx//+Md6y1veoptv\nvlmNRkOXXnqp4jhWkiSStFvSW499Kz1JUTzGmA0vXFTRzA6VjtiKH//4x3r88cd1zjnnjBRsDgaj\nrusqCALNz8+vqvoAAACYlo2GRRGe1ottyYByi6JIvu/nfRiYsdNPP13vec979MY3vlH79+/XxRdf\n3P/lV9n/MdiTlN945GrUxQOLDKA8vva1r+nOO+/Uvn371vweu5V+YWFBBw8e1OLiolzX1fz8vLZv\n3665ublNB6SE+6gq3gMBIF82CLXDIlutltrttjqdjubm5uT7vhzHUZIk6vV6WlhY0MLCgpaWXpas\ndAAAIABJREFUltTr9RRFkZIk2XCdMkrhCFBn41S9E5LWk22f8pOf/EQHDx6UJP3Lv/yLXvayl8lx\nnD92HOe4YY8jJAWAHFQ5zNu9e7dOP/10nXjiiSv+3laMLi4u6tChQxMJRgEAAPKyUXjaaDyxcTOO\nYy0vL2thYUGLi4taXl5WGIaK4zgbIgVgOghJ68leVz/72c/q61//uiTpH/7hH/S85z1PkpqSflOS\nHMdZcQPKdnvkbpRPgagQmy2e7+mqeoXAmWeeqTPPPFPSE29OSZJkW+klKQgCdbvd7MYBxeM4Tvbp\nKwAA2Jz1tu33D4uyW/b7t3XbD5Xtlv2qrxuBaYvjmJC0xjzPU7PZ1Be/+EU1m01dc801uu666x6V\n1B72/dyhAgAmrr/HqPRkMOp5Hot9ACi7JJF/zz1KTjhB6Smn5H00QGkMGxYlPRme2m35g+HpsH6n\nrKeA0VBJWk/2Gnn++efrYx/7mD7ykY/ola98pYIgkKSdkn4y7HGEpACAieivGDXGEIwCQEV5P/qR\n/P/4DzW6XS294hV5Hw5QejY8tQOi5ubmJK2uPA3DMNvp4bquPM9jWBRqZZzdjnEcs4OthlzXlTFG\nV155pfbs2aMjR47oWc96li3i+aSk/ce+te04zqIxJpEISVESbP8Giqk/GE3TVEEQqN1uq9FosFAH\ngIpKdu1SfO65SgZ6TwOYrGGVpzZItcFpf+Wp3eI/rPIUm8cgrWLa7GsSRREhaU3ZHOm8887L/u7Y\nB1Jf6+tFep2kD0n6d4mQFMAQhNLTZd/Yy7rwKmowWsfz9rHHHtO+fft0xhlnqNvt5n04AOqi0VD4\nnOfkfRRALa3X75TwFFgtjmO7xRo1NMJ1zpcU238hJAUAbMhu8QrDUEmSFCYYrbsDBw5oYWFBhw8f\nJiQFAKDktvJhL+EpMBw9SbEBQlKUTx0rxIC8DQajvu+r1WrJ930WzwVx+umn67jjjtPxxx+f96EA\nAIAJmPQaa73wtL/faRzHDItCJbHdHhsgJEWxEIAWE69JPRGMlovv+zrhhBPyPgwAQMmVtQUQxjes\n36m0Ojy1VaeEpyiCca5VVJJiAw1JSf+/AMAKBNezUZQbErsADsNQcRwTjAITwDUU2CRj5PR6UqeT\n95EAtUZ4+qSirNWxNfQkrbckSfTjH/9Yjz32WBaY7927d6+k70k6Kun1x/4piZAUJUFoh6rJe8Fl\njMkqRuM4VqPRUBAE6na7uR8b8sc1d2v4HQI2r/Htb2vbQw/JXHSRzIkn5n04AAaMGp7awZ6S5Lqu\nPM+j3ylyRSVpPSVJIs/zdPPNN+v666/X0tKSjjvuOPvlWyX9T0lflnTUGJPaLxCSAkBNVD0YJdgD\ngBLzPBlJGuibCKDYhoWnDItCkRCS1pPtw/zud79bN9xwg172spf1f/kU+z/6A1KJkBQlw5aH2XAc\nJ/sEGOVmjMm20tum5UEQqNPprGrgDwBAXuJzztHRXbvUmZ8XKz2g3NYbFkV4iq0YpyCCkLSeDh8+\nrO3bt+u0005TFEVKkkS9Xk+NRkPNZtM3xkTDHkdIityNUv3FmyMwusFg1PM8BUGgdrtNMAoAKCRj\njOR5rPmACiM8xSRs9rW3MxdQLx/+8If1wAMPaPv27brhhhv0uc99Tqeffro9f37fcZx3GWP+a/Bx\nhKQAkINJbw0nGAUAACi3uu6aWy887e93Gsdx5YdFYfKoJK2n448/XkeOHFGaprrqqqsUx7HiOLZf\n9iQNvRknJEUh1HVBUFT0diwHY4ziOM76jLquq2azSTAKAACA0ht1WJStOp10eMo9ajXYWQyolyuv\nvFKS9JGPfESXXXaZ5ufns6+96U1v+ldJbLdHMY36xmODO96oUGfDgtEgCDQ/P79qAVlHhPsAAADV\nlnd4inKhkrSejhw5om3btunGG2/USSedpOc///k6cuSIduzYIUlvlPSbkn7sOI5j+m4iCUkBoOCM\nMVmjaYLRtbHIBQAAqK9Rw9MwDLMhta7ryvM8+p2WxDhFU3Ecq9PpTOmIUFR33XWXbrnlFj3wwAN6\nxzveoZtuuinrdyypI+nwsMcRkqJUqBJDVWzU0sAGo7ZiVJKazSbBKGaClhvTxw0YAACzMSw8HWVY\nlN3BZUNU3rvLiUrSejrttNN0+eWX6+tf/7pe9rKXaefOnVpcXNTc3Jze+973vsQY87gkmYGbHkJS\nlAZvSrNDQJKPYcFoEATqdrvymPgLAMjJY/feqwdvvVV7X/Maze3cmffhYApoaYW6WW9YlA1PkyRR\nkiTZwCj7/cO27aO4mG5fT6eddppOO+00ffGLX9T+/fv1wAMPaMeOHTr77LMl6cBajyMkBYCc9W+l\nlwhGAQDF8h/ve58e/pd/UfvEE3XBVVflfTgAMDWD4Wmr1coKSDaqPCU8LSYqSevJfvj3yU9+Um96\n05u0a9cudbtd3XnnnZL0647j/H/GmGTwcYSkKA2qG1Elxhj1ej0tLCwoTVOCUQBAYe197WvVPekk\nnfnzP5/3oQCVRkVvca1Xedrf79RWnTIsajrG+R0hJK0ne65cc801uuWWW3TuuedKyiqLXy/p45L2\nDz6OkBTAUATSk9e/ld4upNrtthqNBoulCeG8BYDJO3HPHp24Z0/ehwEAhTPqsChbdUp4Ontst68n\n+/v09Kc/XZ7nKY5jxXGsVqslST+WFA97HCEpgFV4g56cNE2zrfS2YrTdbmtxcVGtVos37AnivAUA\nAEAREJ4WB5Wk9WR/b/bu3atXv/rVeuUrX6nt27frox/9qCR9R9JljuOkkj5mjMkCU0JS5G7Uiz7b\n7VEWaZpmFaNJksj3/VUVoyx2AAAAgHoZNTy1BRaS5LquPM+j3+mYqCSttyAI9MIXvlD79u3Tgw8+\nqHPOOUef//znY0kvktSU9In+7yckBYAJGBaM2kpRFjFA/fChHqYpTRJ9//Of18nPeQ7T5gGgAoaF\npwyLmgwqSevtT//0T7W4uCjXde1We/3VX/3V/1rr+921vgDMChfy4qFqdzR2K/3hw4d16NChrMfJ\njh071O12FQQB5zdQQ/zeY9ru/vu/1y1XXaX/84Y35H0oAFBJ9l4oz/d0G4Q2Gg0FQaBWq6V2u61O\np6O5ubmsGCNJkmwg7MLCgpaWltTr9RRFkZIkqdR93TiDm+I4VqNBfWBdfeUrX9Hll1+uM844Q0mS\n6O6775bjOH/iOM7QPJQzBaVBcIcisL2DwjDM3nDHqRjlfEaRcX4CxdbZtUuNuTm1Tzwx70MBAMyY\n7VPquiszHipPh2O7fb1dffXVuummm/TLv/zL8jxPF1xwgST9ojHmzcO+n5AUADZgjMm20ttgNAgC\ndbvdWiwsyoJgD2UzajWE4zhZXzJAkg7/4AeKl5Z05OGH8z4UABM0TpUcYK0Xnvb3O43juFbDothu\nX19Jksh1XZ199tnZWjqKIknqrfUYQlIAqxA2PbGYiKJIvV5vRTDa6XRWLTwAAJilPa9+tZIw1Bn/\n/b/nfSgAJqxK4RSKYdRhUbbqtGrhKSFpfaVpqrPPPltf/vKXtby8rMOHD+umm26SpAfXegwhKUqD\n4A7TZoPRMAwVRZE8zyMYBQAUTrBtm5599dV5HwYqhApGoH7KGJ7aY9gMQtL68n1fb3vb2/Ta175W\nR44c0d69e7Vnzx5J+vW1HkNICqDW1gpG2+32VINRQn8AAAAARTNqeBqGYbaF2XVdeZ5XyH6n9CSt\np4MHD8rzPG3btk2f/exnFYahHMexs0QOrPU4QlIAtWOMURzHWZ/RWQWjAAAAAIqP6urVhoWnZRgW\nRSVp/SwvL+stb3mL2u220jTV4uKiut2uXNe1PUl/S9Lbhz2WkBSlQeXd7FTxuR4MRl3XVRAEmp+f\nX/UpKQAAmK2qrTsAoA7WGxZVlPCUkLSeTj31VBlj9IUvfEH79+/X5ZdfrgMHDujTn/60JJ0jSY7j\nOGZgAUJIitzxCR2mhWC0XqoY7gNAnbAmBIBqKFJ4SkhaP61WS7/zO7+jAwcO6BOf+IS++tWvZl97\nwxveoFNPPfW8Y//qSCIkBVBdxhglSZIFo47jEIwCYyBwBgAAwCStF5729zuN43josKg0TeW67qba\nIdCTtH7s+XH48GEdOXJEBw4cUKPR0NzcnPbt2ydJ82s9lpAUpUGV2OyU7bkeDEYlKQgCdbtdNRrF\nvMyV7TlGvVDNBQDA7NEHE3U16rAoOzDK7hIc/CNpVQAbx3Gli2UeeughveY1r9H+/fvlOI5+/dd/\nXVdffXXeh5Urex3dtWuXXvGKV+hFL3qRXv7yl+vRRx+1VaVvO/atq27Ii5keAMAI+rfSS08Go57n\nscAEABTW49/+tprbt6t78sl5HwoAYAgC62IYDE/TNJXv+/I8b0VwGkWRFhYWdNFFF+mss87S7t27\ntXv3bp1//vkKgiDnn2K6fN/X2972Nj3zmc/U0aNH9dM//dN6yUteot27d+d9aLlrtVq6/vrr9Qu/\n8Au6/fbbdeaZZ+raa6/VKaec8qFj3+I6jtM2xhyxjyEkRalQeYf+ilFjDMEoAKBUDjzwgD506aVq\nn3CCfvU//iPvwwEAoHSGVZ7Ozc3p3//933Xvvffq3nvv1X333adPf/rTuuuuu3TiiSfqggsu0AUX\nXKA9e/Zk/zz++ONz/Ckm46STTtJJJ50kSep2u9q9e7f27dtHSHqMMUZ79+7V3r17s79zHMc1xqSS\ndkv6zWN/JBGSokTYnjx7RfkEtT8YTdNUQRCo3W6r0WgU4vgAABhVa8cO7XjGM7TjjDPyPhQAAEpl\no/vTnTt36ud+7uf0cz/3c9nfvfSlL9VHPvIR3XPPPbr77rt155136gMf+IDuuecebdu2LQtNL7jg\nAl122WU69dRTZ/GjTMX3v/99fetb39Jzn/vcvA+lMNY4X2yw5EuK+r9ASApglSIEj1UPRgn9J8+e\nF0UJ94H1cI7W19zOnfp/vvKVvA8DAIBacBwnq7Z80YtelP29MUYPPfSQ7r77bt19993653/+Z513\n3nmlDUmPHj2qV77ylXr729+ubreb9+GUhS8p7P8LQlKUCqFStfU34k6SpHLBKIB6IbAHUBZcrwDU\njeM4Ou2003TaaafppS99ad6HsyVRFOnKK6/UVVddpVe84hV5H07hmSeDJV9Sr/9rhKTI3agLMhZu\n1TQYjPq+r1arJd/3ec0BlBLXLgAAAMyCMUa/+qu/qvPPP1+/+7u/m/fhFEqv11Ov19P8/Hz2d2ma\nyvM83xgTach2e3fGxwigJKa5HTxNUy0vL+vw4cM6dOiQ4jhWq9XSjh071O12FQQBIQOAyjLGKI5j\nJUmiNE3ZJQEAkMSuuSKhuhpl8ZWvfEUf/OAH9cUvflEXXXSRLrroIn3uc5/L+7AK4a677tK11167\n4u++/vWvS9KfHvvXr0q6sf/rVJKiNOjhWG5pmiqKIoVhqDiOqRgVC2EUF9fbyTPGZNfAKIqy614Y\nhjLGyHVdeZ4n13WzP3W9NgJAnXHtB9Y2Tnhd9d+p//bf/pvSNM37MAql1+tpcXFR3/jGN/Tggw8q\niiL96Ec/0sknn6wHHnhAkp527FtjY8xy/2MJSQFMjTEm20ofx7EajYaCIFC32638m9VGCKGA6jPG\nKEkS9Xo9hWEoz/OyXsth+ESPeNd1laZp9idJEkVRpDRN5TiOPM+TMUbGmOzv6n79BAAAANby2GOP\n6dprr9WHP/xhBUGgpz71qdlg6DPOOEOS/v7Yt65KlwlJAUwUwSjyZMNnzjXkKUkSSdLhw4clSc1m\nU/Pz8/I8b+j328rRfjYUTdNUcRzLGKOlpSWqTgEAAIB1nHrqqXrf+96n3//939c3v/lNXXnllYPf\ncoskGWMISVFeVN7N1mae78FtpJ7nqdlsqtPprLrxB4AqskPoer1etuWp0+mo0WiMFWDaKlIbrCZJ\nolarlVWnDqs6HQxPqToFAABA3diimTRNdcIJJ0iSvvvd7+pd73qXTjnlFF1zzTVdY8zRYY8lJAUw\nlmHBqN1GSjAKoA4GK+d939fc3Jx839eBAwfGDkjX4ziOGo2Vyze7Hd+GpzY4tVWnw8JTAACwNnYm\nFROvC0ZxbIK9br31Vn3zm9/UJZdcove///360Y9+ZLOK35P0e47jeMaYpP+xhKQoDC54xUcwOjn2\nky0A5WIn0/d6vRWV83m2FLEVo8O27K9XddofnlJ1CmCrDv3gB3r83nt1+kteIrfBbSaA/LETtd4c\nx9HOnTt1zz336MCBA3rHO96hz3/+85LUXesxvHshd6PelLHdfrbs820DAVst5bqums0mwSiAWum/\nDjqOU4oPiKg6BTBL33znO/WT735XjXZbp11ySd6HAwCKoki+7+d9GJgxu3495ZRTdPvtt+u6667T\n05/+dJ144ol69NFHJSlc67GEpABWsTfRS0tLiuNYrusqCIJ1B48AQNWkaZpNpjfGZEPoBoPHMlmv\n6tRWnBa56tQ5ckStz35WyamnKrz44lyOAaiiSezoesZll6k5P68TL7hgQkdVP+ysAyaLkLSe7Dr3\niiuu0Mknn6z7779fP//zP680TfVTP/VTknTTsW9lcBOKicVA/mxlUX8g4Ps+wShKhYpzbJXtM9rr\n9ZQkiXzfV7vdnkp/0SIZHBQlPfmB2eB2/f6q08HwdOrHubgo98gRmccem/p/C8DmPOMlL9EzXvKS\nvA8DQEWNs8aPoqjUH25j6572tKdp3759euihh3TcccfpwgsvlKR7JckMOak4W1AahB+TZ4NRu4VU\nUlYxevToUTWbTQLSKeF8RpHV7fwc7LfcaDTUarXk+36lg9GN9Fed9t9g2ODUhqdxHK+qOrXh6aSr\nTtNdu7T08pcr7XQm9v+JYqCCDgAwis28V8RxrCAIpng0KKI0TeW6rr72ta/pr//6r/XJT35S119/\nvS688EL98R//sST9L0lvY3ATgDWD0W63m93QSvULSQDUy2D1PIPoRtdfdWq3sA1WndoeroNVp/3h\n6bjSE06Y1I8CAMBQfHBTDWy3ryebY3z0ox/VZZddphe/+MX63ve+J0nqdruSNLfWYwlJgZroDwOk\n4cEoAFSd/ZCo1+tJkprNJm1FJqCIVacAAKDe2G5fb51OR2ma6pFHHskqio8cOSJJy2s9hrMFpUFl\n4+b1V4ymaUowCqCW0jTNroVJknAtnKGNqk7TNJ1q1SkAAKgvKknrye4Ke8ELXqDbb79dt912m37m\nZ35Gf/AHf6CHH35Ykr5w7FsZ3ARU3bBgdJyhI4TS08fzOx08r5Ce7DPa6/UUx7F83595n9FJbtWr\n0nndX3Xarz84tcH2sKpT+4fwFACA+hhnXUVP0npyHEdJkujSSy/VM57xDLmuq+985zvavn273vnO\nd+pjH/vYvzuO4zC4CagoezPZ6/W2FIxidnhdpoPntd6MMVlVou0z2mw21e12Z35uTPK/V5fzur/q\n1BqsOrUfBA6rOrV/AKCs6IMJTBaVpPXleZ4effRReZ6n3/7t31YQBHJdV3Eca9jAJouQFIUwStUi\nlY0rDW4f9X1fc3NztZ/GDKB++oNRx3EUBIG2b99OYFYBVJ0CAPJAYF0N9CStpyRJ5Hme/vIv/1J/\n+7d/q+OPPz7ri39su/3LJX2c6fZAyQ0LRme9fRQAiiBN02wYXZqmWcUoC+F6mETVadkGRRlj9K13\nvUvdk0/WOb/wC3kfDgAAhRfHMWvDGrLrwxtuuEE33HBD9kH67bffrltuuUU33njj/ce+lZ6kKLc6\nVpKmaZr11ZtlMErlLlBfRf39N8ZkrUXs9ZDWIrBGrTqNokhJkqxZdVpUj3/727r9D/5AbqOhs1/x\nCs55AECt0JMUm2XvZxzHURzHesELXqB3v/vdknS2pP+U5EhacdNDSIrSqNPNgA0CwjDMPv1qNpsK\ngqBWz0OVFTWEAorGDmAKwzDbMsX1EJsxatVpFEVZpYF9Hy5S1enx55yjZ//Wb6l76qlTOxZncVHN\nz39e6QknKLz44qn8N1BMrEkAVBE9SevJBupf+9rX9Mgjj2hubk5BEGj//v164IEHJOnQWo8lJAUK\nYlgwGgRBLgNHgDLjRq/8jDFKkiTbTu+6rprNptrtdqEr/VAe61WdJkmi5eXlLKBP01TGGHmel2uv\nU9fzdPH110/3P7K8LPfoUYl1Ry2x3gRQNYSk9WRD0ttuu01f+tKX1O12lSSJut2ubrjhBl166aVf\nOPZ9bLdHMW2mqq5KTbSHVUgFQaBOp5N7EEClI8qoKteGurI9JHu9niQpCALNz8+vqAAEpskGp47j\nqNlsStq46nQwPC1C1em4zPHHa+mlL5VarbwPBQCALSMkrSebpVx77bW69tprV3wtTVNJco7lHasC\nD0JSlEZZbzgGDQajnucpCAIqpADU0uBAOvtBEX1GURSb6XVqq05d1x0anpaBOe64vA8BqCWKE4rF\nXstRbnEcE5LWUJqmcl1X733ve3XnnXfquOOOk+/7iuPYfgj+/0rqOo7zHmPMf/U/lpAUhVGlCtFB\nBKMYhsUw6speE3u9XrZ4ncVAOmCShvU6lbQiOB2sOh0MT8tcdQpgOrgmAMONkxdQSVpvP/zhD/Wl\nL31JL3zhC/W0pz1Nn/rUp9TtdiWpLWnoRC9CUhTCqBc7uwW8DIsHY4ziOM4qpAhG0a8M5zAwScOu\nic1msxDtRYBJsgFov6pWnQIAUGSEpPVki5H+7d/+Tf/4j/+oPXv2SJKuueYavfzlL5ekjxtj/tMZ\nsuAiJAUmaDAEcF23tD316EkKYBL6BzA5jlPaayKwFWtVndpBUVSdAgAweYSk9RaGob773e/qrLPO\nUhiG6na72r9/vyStWaFBSApsUZWCUaDsCPeLwfYZ7fV6StNUzWZT3W5XnucR8hzDuQrpifOg0Vi5\nHLeDomx4Olh1Oiw8BQAAq8VxrE6nk/dhYMbsjp7Xv/71+qM/+iPdeuutOvXUU/WpT31Kl1xyib76\n1a8+KInBTSi/otxU2psXG4xSHQWgSmzospn2JsaY7Jpo+4y2220GMAGbtNGgqCRJhlad9oenVJ0C\nwNZxHS0WepJiVDY3eulLX6rnPOc5+qd/+ictLCzoPe95j571rGfpz//8z4+s9VhCUmBEg8GoJAVB\noG63u6oKpAqKEkhXFc8vqmBwKF2j0ciui9xYAJM1bMu+rTod3K7fX3U6GJ4CADbGOr0akiSp5L06\nNuY4jpaXl/Wtb31Ljz32mK6++mqFYaj//M//1IUXXugbY6Jhj+NsATbQv5VeejIYZdsogDqyHxjZ\nPqOu66rZbDKUDshBf9Vp/01gf3CapqniOKbqFABQO1SS1pOtOv6TP/kTff/739fnPvc5/cqv/IpO\nOukkve51r5OkEyQ9MuyxhKQolVlV3/VXjBpjCEYB1J69LvZ6PUmixcgIqEJBXspYdcrvS77seYD8\njLOVGMD6CEnryV5PP/7xj+uee+7RC1/4wmydE0WRJKVrPZaQFDimPxhN01RBENS+nx43LEC92aEx\nYRgqSRIFQaBOp1Pr6+KoeH5QNBtVndrwdFjVqQ1Pp111yu8NAGCSbJ981ItdTzztaU/Tvn37tLCw\noDRNs2IPSUO32kuEpCiIvBbFBKNrq/vPP230JJ0Ontets31GJenQoUPyfV+tVku+73NdACqov+rU\n3kj2V53a7fp2d01/cNofngIAME0MbsKo7Hly8cUX6w//8A/12GOP6UMf+pA+9rGP6dWvfrXuvPPO\nQ2s9lpAUpTKJACRN0ywYtZVRBKMA6swYs6L/st2iu337drbTAzXUX3Xarz84teupYVWn9g/rKgBl\nRfuDaqCStN4+/vGP653vfKcuuOACPf7447rxxht18cUX6w1veEOy1mMISVEI034DGgxGqYwCAK0Y\nwCRJzWYz6zP6k5/8hP50AFbYqNdp/5Aoqk4BAHmjkrTezj//fD388MO66qqr1Gw2laapFhYW1Ol0\n1nwMISkqi2B0a9i2DFSTvTb2ej2laapms8lgOqBEDj74oD792tfqrJe9TM+75pq8D2diVacAAEwa\nIWm9/fCHP9Sv/dqvadeuXWq323IcR3Ec67777nONMUOHNxGSolQ2Cu76h4zEcaxGo0EwikIihMYs\nGWOyD43stqON2ozYc5Rr5/RwDcA4fnL//frJd76jh7ZvL0RIupZRqk5tb/j+a00YhoSnAIBVxlmX\nst2+3m699Va5rqs4jpUkSbb2OOGEE5huj+oavPlvNBoKgkDdbpebewC1ZfuM9no9RVHEtRGoiDMu\nu0yv+MhHtPPcc/M+lE1br+o0iiJFUZT97yRJ6HWKWuGDSWDyqCStt3a7venHEJKilOwCutfrrQhG\nO50OVQdAjdW9QtcYk1Vm9Xo9ua6rZrOpdrvNtRGokNNe8IK8D2Gi+sPQZrMpaXjVaRRFStN0zeCU\ngAkA0I+QFJtFSIrSsIvlpaUlLSwsyPM8NZtNgtEpqXvYBJSJDUbtttUgCLIBTABQRqP2OrVVp5Lk\neR5VpwAmgsreamC7PTaLkBSFZitGwzBUFEWSJN/3tW3bNoJRALVmw4Fer6ckSRQEwYZ9RgGgjNI4\n1m2/+7syxuglb3+7vEZjw16nVJ0CAOyuU2BUnC0onMFg1PO87OZ/cXFRjUaDgBSlZ2/O+JS6HpaW\nlnTgwAGdfPLJW3q9h7UaYTgdgKqLl5b0X3fc8UQf+qNH1dqxY8XXN1N1mqapjDFUnQ5gPQKg6Iwx\nm84B2G6PzSIkRSE4jqM4jrNw1HVdBUGgubm5FZUCLN5mh+32wOTcfvvtevTRR/WCF7xAT3/60zf1\nWDuAyW6ntx8c0WoEQF0E27bp8g9+UMaYVQHpehzHked5q1qP9Aen/VWn9vupOgWAaiAkxWYRkqIw\n7M0/ffQAbEURw/2TTz5ZvV5POzZxc58kiXq9nsIwlCQ1m02ujwBq64Tzz5/Y/5cNQPtt5jo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RiSElHb0X1GPc9DEASwLAuu66JUKvHNlyiGlc5EyXjl/vtx87nnonvuXLzvT39KejlE1AQMgSgr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x00034aGHHkKpVMJHP/pRnHjiiTjppJNw0EEHBfLyqIam8iMOW3YpWHbDc1jplz1BVZvq1Vmm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\nnts3EA0tERsAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f333fc5d850>"
+       "<matplotlib.figure.Figure at 0x7f6886ca3290>"
       ]
      },
      "metadata": {},
@@ -764,7 +901,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": 31,
    "metadata": {
     "code_folding": [
      0
@@ -776,14 +913,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[58, 311, 180, 36, 1, 313, 1]\n"
+      "[22, 319, 34, 461, 40, 26]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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wOeCCFotHs5F9fX2vDddqNWq1WncVm5mNEfV6nXq9PqBlFNE0c7fNIO0KfBO4MyI+32T6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\nf6C3ao90c6mwAAAAAElFTkSuQmCC\n",
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f930823b750>"
+       "<matplotlib.figure.Figure at 0x7f6887295490>"
       ]
      },
      "metadata": {},
@@ -791,9 +928,9 @@
     },
     {
      "data": {
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FgH0QkgLAHTSrslLFaHKf6qtjB2rNWXrT6TRms9mihf7s7GxnbZ/N8QLA8TXD002LpFJF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6VpyuAmrI09BrVyXvjJiR9Sd1sz1HX/dwcw2Yt7+owCANAcFCBUz1aNus7rdeoOidpV1SnQVHY1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\nz+crVb150UUX8dhjj/Gf//yH3Nxc2rRpQ2xsLJ9++ikDBw4kIyODkSNHAvD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xmrSx+qo+S68sy3jnnXeWLfTT6VTbJ3RUPTzdtkgqVcSn4106BlokdTz7zkFNVtv3zUEF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\nAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f930add3e50>"
+       "<matplotlib.figure.Figure at 0x7f6886e35e10>"
       ]
      },
      "metadata": {},
@@ -802,7 +939,7 @@
    ],
    "source": [
     "# custom number of clusters\n",
-    "num_clusters = 9\n",
+    "num_clusters = 6\n",
     "clusters = get_clustering_model(X, num_clusters)\n",
     "plot3([0,1,2], X, clusters, -1)"
    ]
@@ -823,7 +960,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 49,
    "metadata": {
     "code_folding": [],
     "collapsed": false
@@ -844,7 +981,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"5900bc1c-4c80-4ace-89aa-89708c98ce91\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -892,9 +1029,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2\");\n",
+       "    };var element = document.getElementById(\"5900bc1c-4c80-4ace-89aa-89708c98ce91\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a94769e1-ba8f-4a8b-8b6b-ffc54f4189f2' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '5900bc1c-4c80-4ace-89aa-89708c98ce91' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -903,8 +1040,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
-       "            var docs_json = {\"8b858ebf-6331-4918-bbb1-9f181e4874bb\":{\"roots\":{\"references\":[{\"attributes\":{\"axis_label\":\"IP 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+       "            var render_items = [{\"docid\":\"2ef40c30-3fec-4e91-add9-60425af850ef\",\"elementid\":\"5900bc1c-4c80-4ace-89aa-89708c98ce91\",\"modelid\":\"a10ff395-7821-41f8-8b3c-dc4c78b4afee\",\"notebook_comms_target\":\"5a79cd2d-949f-40ce-92c4-2313329eb961\"}];\n",
        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -974,7 +1111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 99,
    "metadata": {
     "collapsed": false
    },
@@ -983,10 +1120,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning: Setting a fixed font size value as a string '10pt' is deprecated, set with value('10pt') or ['10pt'] instead\n",
-      "  value = self.descriptor.prepare_value(obj.__class__, self.name, value)\n",
-      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning: Setting a fixed font size value as a string '14pt' is deprecated, set with value('14pt') or ['14pt'] instead\n",
-      "  value = self.descriptor.prepare_value(obj.__class__, self.name, value)\n"
+      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning:\n",
+      "\n",
+      "Setting a fixed font size value as a string '10pt' is deprecated, set with value('10pt') or ['10pt'] instead\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/bokeh/core/properties.py:453: DeprecationWarning:\n",
+      "\n",
+      "Setting a fixed font size value as a string '14pt' is deprecated, set with value('14pt') or ['14pt'] instead\n",
+      "\n"
      ]
     },
     {
@@ -994,7 +1135,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"bb92ccdf-b43e-437f-8b58-3bc989711238\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -1042,9 +1183,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"bb92ccdf-b43e-437f-8b58-3bc989711238\");\n",
+       "    };var element = document.getElementById(\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'bb92ccdf-b43e-437f-8b58-3bc989711238' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '538b9546-3c95-4f1f-a6f7-ac63b1de4284' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -1053,8 +1194,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
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Application\",\"version\":\"0.11.1\"}};\n",
+       "            var render_items = [{\"docid\":\"22f9e79e-f48c-45ac-8357-778718d8476f\",\"elementid\":\"538b9546-3c95-4f1f-a6f7-ac63b1de4284\",\"modelid\":\"65e48372-8f9a-455a-987f-a59d9cc84296\",\"notebook_comms_target\":\"68563ce1-606d-4a8c-aff0-c3f660810c72\"}];\n",
        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -1089,29 +1230,47 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning: Comm._comm_id_default is deprecated: use @default decorator instead.\n",
-      "  def _comm_id_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:29: DeprecationWarning: Comm._iopub_socket_default is deprecated: use @default decorator instead.\n",
-      "  def _iopub_socket_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning: Comm._kernel_default is deprecated: use @default decorator instead.\n",
-      "  def _kernel_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning: Comm._session_default is deprecated: use @default decorator instead.\n",
-      "  def _session_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
-      "  def _topic_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning: Comm._kernel_default is deprecated: use @default decorator instead.\n",
-      "  def _kernel_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning: Comm._comm_id_default is deprecated: use @default decorator instead.\n",
-      "  def _comm_id_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning: Comm._session_default is deprecated: use @default decorator instead.\n",
-      "  def _session_default(self):\n",
-      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
-      "  def _topic_default(self):\n"
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning:\n",
+      "\n",
+      "Comm._comm_id_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:29: DeprecationWarning:\n",
+      "\n",
+      "Comm._iopub_socket_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning:\n",
+      "\n",
+      "Comm._kernel_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning:\n",
+      "\n",
+      "Comm._session_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning:\n",
+      "\n",
+      "Comm._topic_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:24: DeprecationWarning:\n",
+      "\n",
+      "Comm._kernel_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:52: DeprecationWarning:\n",
+      "\n",
+      "Comm._comm_id_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:32: DeprecationWarning:\n",
+      "\n",
+      "Comm._session_default is deprecated: use @default decorator instead.\n",
+      "\n",
+      "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning:\n",
+      "\n",
+      "Comm._topic_default is deprecated: use @default decorator instead.\n",
+      "\n"
      ]
     }
    ],
    "source": [
-    "#num_clusters = 15\n",
+    "#num_clusters = 14\n",
     "#clusters = get_clustering_model(X, num_clusters)\n",
     "\n",
     "plot_countries(clusters, num_clusters, sessions, 8)"
@@ -1126,7 +1285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 160,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
@@ -1146,7 +1305,7 @@
       "text/html": [
        "\n",
        "\n",
-       "    <div class=\"plotdiv\" id=\"e216567b-f330-48c2-be9b-55be4b867d2b\"></div>\n",
+       "    <div class=\"plotdiv\" id=\"a371810e-3345-462a-8c03-13ff7adddd24\"></div>\n",
        "<script type=\"text/javascript\">\n",
        "  \n",
        "  (function(global) {\n",
@@ -1194,9 +1353,9 @@
        "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "      }\n",
-       "    };var element = document.getElementById(\"e216567b-f330-48c2-be9b-55be4b867d2b\");\n",
+       "    };var element = document.getElementById(\"a371810e-3345-462a-8c03-13ff7adddd24\");\n",
        "    if (element == null) {\n",
-       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e216567b-f330-48c2-be9b-55be4b867d2b' but no matching script tag was found. \")\n",
+       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a371810e-3345-462a-8c03-13ff7adddd24' but no matching script tag was found. \")\n",
        "      return false;\n",
        "    }\n",
        "  \n",
@@ -1205,8 +1364,8 @@
        "    var inline_js = [\n",
        "      function(Bokeh) {\n",
        "        Bokeh.$(function() {\n",
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        "            \n",
        "            Bokeh.embed.embed_items(docs_json, render_items);\n",
        "        });\n",
@@ -1237,14 +1396,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[4, 0, 0, 92]\n",
-      "[0.08, 0.0, 0.0, 5.18]\n"
-     ]
-    },
     {
      "name": "stderr",
      "output_type": "stream",
@@ -1268,6 +1419,14 @@
       "/usr/local/lib/python2.7/dist-packages/ipykernel/comm/comm.py:41: DeprecationWarning: Comm._topic_default is deprecated: use @default decorator instead.\n",
       "  def _topic_default(self):\n"
      ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[468, 0, 3]\n",
+      "[63.33, 0.0, 20.0]\n"
+     ]
     }
    ],
    "source": [
@@ -1318,6 +1477,84 @@
     "tools.save_selected_cluster(id_incident, selected_cluster)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "code_folding": [],
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function a(t,e){var r=e[0],n=e[1],a=e[2],o=e[3],s=i(r,n,a,o);s>1e-6?(t[0]=r/s,t[1]=n/s,t[2]=a/s,t[3]=o/s):(t[0]=t[1]=t[2]=0,t[3]=1)}function o(t,e,r){this.radius=l([r]),this.center=l(e),this.rotation=l(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),r=[].slice.call(r,0,4),a(r,r);var i=new o(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/lookAt\"),c=t(\"gl-mat4/fromQuat\"),f=t(\"gl-mat4/invert\"),h=t(\"./lib/quatFromFrame\"),p=o.prototype;p.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},p.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;a(e,e);var r=this.computedMatrix;c(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;3>l;++l){for(var u=0,f=0;3>f;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r},p.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},p.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},p.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=a[1],s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=a[2],v=a[6],m=a[10],y=g*o+v*s+m*l,b=g*c+v*f+m*h;g-=y*o+b*c,v-=y*s+b*f,m-=y*l+b*h;var x=n(g,v,m);g/=x,v/=x,m/=x;var _=c*e+o*r,w=f*e+s*r,k=h*e+l*r;this.center.move(t,_,w,k);var A=Math.exp(this.computedRadius[0]);A=Math.max(1e-4,A+i),this.radius.set(t,Math.log(A))},p.rotate=function(t,e,r,a){this.recalcMatrix(t),e=e||0,r=r||0;var o=this.computedMatrix,s=o[0],l=o[4],u=o[8],c=o[1],f=o[5],h=o[9],p=o[2],d=o[6],g=o[10],v=e*s+r*c,m=e*l+r*f,y=e*u+r*h,b=-(d*y-g*m),x=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(b,2)-Math.pow(x,2)-Math.pow(_,2))),k=i(b,x,_,w);k>1e-6?(b/=k,x/=k,_/=k,w/=k):(b=x=_=0,w=1);var A=this.computedRotation,M=A[0],T=A[1],E=A[2],L=A[3],S=M*w+L*b+T*_-E*x,C=T*w+L*x+E*b-M*_,P=E*w+L*_+M*x-T*b,z=L*w-M*b-T*x-E*_;if(a){b=p,x=d,_=g;var R=Math.sin(a)/n(b,x,_);b*=R,x*=R,_*=R,w=Math.cos(e),S=S*w+z*b+C*_-P*x,C=C*w+z*x+P*b-S*_,P=P*w+z*_+S*x-C*b,z=z*w-S*b-C*x-P*_}var O=i(S,C,P,z);O>1e-6?(S/=O,C/=O,P/=O,z/=O):(S=C=P=0,z=1),this.rotation.set(t,S,C,P,z)},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;u(i,e,r,n);var o=this.computedRotation;h(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),a(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var s=0,l=0;3>l;++l)s+=Math.pow(r[l]-e[l],2);this.radius.set(t,.5*Math.log(Math.max(s,1e-6))),this.center.set(t,r[0],r[1],r[2])},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e){var r=this.computedRotation;h(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),a(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;f(n,e);var i=n[15];if(Math.abs(i)>1e-6){var o=n[12]/i,s=n[13]/i,l=n[14]/i;this.recalcMatrix(t);var u=Math.exp(this.computedRadius[0]);this.center.set(t,o-n[2]*u,s-n[6]*u,l-n[10]*u),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},p.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var i=t.distance;i&&i>0&&this.radius.set(e,Math.log(i)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":16,\"filtered-vector\":17,\"gl-mat4/fromQuat\":183,\"gl-mat4/invert\":186,\"gl-mat4/lookAt\":187}],21:[function(t,e,r){arguments[4][17][0].apply(r,arguments)},{\"binary-search-bounds\":22,\"cubic-hermite\":23,dup:17}],22:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],23:[function(t,e,r){arguments[4][19][0].apply(r,arguments)},{dup:19}],24:[function(t,e,r){arguments[4][5][0].apply(r,arguments)},{dup:5}],25:[function(t,e,r){arguments[4][6][0].apply(r,arguments)},{dup:6}],26:[function(t,e,r){arguments[4][9][0].apply(r,arguments)},{dup:9}],27:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t){return Math.min(1,Math.max(-1,t))}function a(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),i=[0,0,0];e>Math.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,s=0;3>s;++s)a+=t[s]*t[s],o+=i[s]*t[s];for(var s=0;3>s;++s)i[s]-=o/a*t[s];return h(i,i),i}function o(t,e,r,n,i,a,o,s){this.center=l(r),this.up=l(n),this.right=l(i),this.radius=l([a]),this.angle=l([o,s]),this.angle.bounds=[[-(1/0),-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;16>u;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.up||[0,1,0],i=t.right||a(r),s=t.radius||1,l=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),h(r,r),i=[].slice.call(i,0,3),h(i,i),\"eye\"in t){var c=t.eye,d=[c[0]-e[0],c[1]-e[1],c[2]-e[2]];f(i,d,r),n(i[0],i[1],i[2])<1e-6?i=a(r):h(i,i),s=n(d[0],d[1],d[2]);var g=p(r,d)/s,v=p(i,d)/s;u=Math.acos(g),l=Math.acos(v)}return s=Math.log(s),new o(t.zoomMin,t.zoomMax,e,r,i,s,l,u)}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/invert\"),c=t(\"gl-mat4/rotate\"),f=t(\"gl-vec3/cross\"),h=t(\"gl-vec3/normalize\"),p=t(\"gl-vec3/dot\"),d=o.prototype;d.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},d.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},d.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,i=0,a=0,o=0;3>o;++o)a+=e[o]*r[o],i+=e[o]*e[o];for(var s=Math.sqrt(i),l=0,o=0;3>o;++o)r[o]-=e[o]*a/i,l+=r[o]*r[o],e[o]/=s;for(var u=Math.sqrt(l),o=0;3>o;++o)r[o]/=u;var c=this.computedToward;f(c,e,r),h(c,c);for(var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),b=Math.sin(g),x=this.computedCenter,_=v*y,w=m*y,k=b,A=-v*b,M=-m*b,T=y,E=this.computedEye,L=this.computedMatrix,o=0;3>o;++o){var S=_*r[o]+w*c[o]+k*e[o];L[4*o+1]=A*r[o]+M*c[o]+T*e[o],L[4*o+2]=S,L[4*o+3]=0}var C=L[1],P=L[5],z=L[9],R=L[2],O=L[6],I=L[10],j=P*I-z*O,N=z*R-C*I,F=C*O-P*R,D=n(j,N,F);j/=D,N/=D,F/=D,L[0]=j,L[4]=N,L[8]=F;for(var o=0;3>o;++o)E[o]=x[o]+L[2+4*o]*p;for(var o=0;3>o;++o){for(var l=0,B=0;3>B;++B)l+=L[o+4*B]*E[B];L[12+o]=-l}L[15]=1},d.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r};var g=[0,0,0];d.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;g[0]=i[2],g[1]=i[6],g[2]=i[10];for(var a=this.computedUp,o=this.computedRight,s=this.computedToward,l=0;3>l;++l)i[4*l]=a[l],i[4*l+1]=o[l],i[4*l+2]=s[l];c(i,i,n,g);for(var l=0;3>l;++l)a[l]=i[4*l],o[l]=i[4*l+1];this.up.set(t,a[0],a[1],a[2]),this.right.set(t,o[0],o[1],o[2])}},d.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=(Math.exp(this.computedRadius[0]),a[1]),s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=c*e+o*r,v=f*e+s*r,m=h*e+l*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+i),this.radius.set(t,Math.log(y))},d.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},d.setMatrix=function(t,e,r,a){var o=1;\"number\"==typeof r&&(o=0|r),(0>o||o>3)&&(o=1);var s=(o+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var l=e[o],c=e[o+4],f=e[o+8];if(a){var h=Math.abs(l),p=Math.abs(c),d=Math.abs(f),g=Math.max(h,p,d);h===g?(l=0>l?-1:1,c=f=0):d===g?(f=0>f?-1:1,l=c=0):(c=0>c?-1:1,l=f=0)}else{var v=n(l,c,f);l/=v,c/=v,f/=v}var m=e[s],y=e[s+4],b=e[s+8],x=m*l+y*c+b*f;m-=l*x,y-=c*x,b-=f*x;var _=n(m,y,b);m/=_,y/=_,b/=_;var w=c*b-f*y,k=f*m-l*b,A=l*y-c*m,M=n(w,k,A);w/=M,k/=M,A/=M,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,l,c,f),this.right.jump(t,m,y,b);var T,E;if(2===o){var L=e[1],S=e[5],C=e[9],P=L*m+S*y+C*b,z=L*w+S*k+C*A;T=0>j?-Math.PI/2:Math.PI/2,E=Math.atan2(z,P)}else{var R=e[2],O=e[6],I=e[10],j=R*l+O*c+I*f,N=R*m+O*y+I*b,F=R*w+O*k+I*A;T=Math.asin(i(j)),E=Math.atan2(F,N)}this.angle.jump(t,E,T),this.recalcMatrix(t);var D=e[2],B=e[6],U=e[10],V=this.computedMatrix;u(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,Y=V[14]/q,X=Math.exp(this.computedRadius[0]);this.center.jump(t,H-D*X,G-B*X,Y-U*X)},d.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},d.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},d.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},d.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},d.lookAt=function(t,e,r,a){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter,a=a||this.computedUp;var o=a[0],s=a[1],l=a[2],u=n(o,s,l);if(!(1e-6>u)){o/=u,s/=u,l/=u;var c=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=n(c,f,h);if(!(1e-6>p)){c/=p,f/=p,h/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=o*g+s*v+l*m;g-=y*o,v-=y*s,m-=y*l;var b=n(g,v,m);if(!(.01>b&&(g=s*h-l*f,v=l*c-o*h,m=o*f-s*c,b=n(g,v,m),1e-6>b))){g/=b,v/=b,m/=b,this.up.set(t,o,s,l),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var x=s*m-l*v,_=l*g-o*m,w=o*v-s*g,k=n(x,_,w);x/=k,_/=k,w/=k;var A=o*c+s*f+l*h,M=g*c+v*f+m*h,T=x*c+_*f+w*h,E=Math.asin(i(A)),L=Math.atan2(T,M),S=this.angle._state,C=S[S.length-1],P=S[S.length-2];C%=2*Math.PI;var z=Math.abs(C+2*Math.PI-L),R=Math.abs(C-L),O=Math.abs(C-2*Math.PI-L);R>z&&(C+=2*Math.PI),R>O&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,L,E)}}}}},{\"filtered-vector\":21,\"gl-mat4/invert\":186,\"gl-mat4/rotate\":190,\"gl-vec3/cross\":24,\"gl-vec3/dot\":25,\"gl-vec3/normalize\":26}],28:[function(t,e,r){\"use strict\";function n(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return t[e]}),this._mode=e,this._active=t[e],this._active||(this._mode=\"turntable\",this._active=t.turntable),this.modes=this._controllerNames,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}function i(t){t=t||{};var e=t.eye||[0,0,1],r=t.center||[0,0,0],i=t.up||[0,1,0],l=t.distanceLimits||[0,1/0],u=t.mode||\"turntable\",c=a(),f=o(),h=s();return c.setDistanceLimits(l[0],l[1]),c.lookAt(0,e,r,i),f.setDistanceLimits(l[0],l[1]),f.lookAt(0,e,r,i),h.setDistanceLimits(l[0],l[1]),h.lookAt(0,e,r,i),new n({turntable:c,orbit:f,matrix:h},u)}e.exports=i;var a=t(\"turntable-camera-controller\"),o=t(\"orbit-camera-controller\"),s=t(\"matrix-camera-controller\"),l=n.prototype,u=[[\"flush\",1],[\"idle\",1],[\"lookAt\",4],[\"rotate\",4],[\"pan\",4],[\"translate\",4],[\"setMatrix\",2],[\"setDistanceLimits\",2],[\"setDistance\",2]];u.forEach(function(t){for(var e=t[0],r=[],n=0;n<t[1];++n)r.push(\"a\"+n);var i=\"var cc=this._controllerList;for(var i=0;i<cc.length;++i){cc[i].\"+t[0]+\"(\"+r.join()+\")}\";l[e]=Function.apply(null,r.concat(i))}),l.recalcMatrix=function(t){this._active.recalcMatrix(t)},l.getDistance=function(t){return this._active.getDistance(t)},l.getDistanceLimits=function(t){return this._active.getDistanceLimits(t)},l.lastT=function(){return this._active.lastT()},l.setMode=function(t){if(t!==this._mode){var e=this._controllerNames.indexOf(t);if(!(0>e)){var r=this._active,n=this._controllerList[e],i=Math.max(r.lastT(),n.lastT());r.recalcMatrix(i),n.setMatrix(i,r.computedMatrix),this._active=n,this._mode=t,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}}},l.getMode=function(){return this._mode}},{\"matrix-camera-controller\":3,\"orbit-camera-controller\":20,\"turntable-camera-controller\":27}],29:[function(t,e,r){e.exports=function(t,e){e||(e=[0,\"\"]),t=String(t);var r=parseFloat(t,10);\n",
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i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);o>=s;s++){var l=n-s,u=this.words[l],c=t.words[s],f=u*c,h=67108863&f;i+=f/67108864|0,h+=a,a=67108863&h,i+=h>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var p=this.words[l]+i;this.words[l]=67108863&p,i=p>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var 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a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),0>t?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],\n",
+       "this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),0>t)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(-1===s),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var f=n.clone()._ishlnsubmul(a,1,u);f.sign||(n=f,l&&(l.words[u]=1));for(var h=u-1;h>=0;h--){var p=67108864*n.words[a.length+h]+n.words[a.length+h-1];for(p=Math.min(p/o|0,67108863),n._ishlnsubmul(a,p,h);n.sign;)p--,n.sign=!1,n._ishlnsubmul(a,1,h),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[h]=p)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return 0>a||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(67108863>=t);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(67108863>=t);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),f=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(f).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(f).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(0>i){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;n+1>a;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=0>t;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:t>n?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){i>n?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new h(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;n>i;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(f,s),f.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function y(t){if(m[t])return m[t];var y;if(\"k256\"===t)y=new l;else if(\"p224\"===t)y=new u;else if(\"p192\"===t)y=new c;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);y=new f}return m[t]=y,y},h.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},h.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},h.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},h.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},h.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},h.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},h.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},h.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},h.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},h.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},h.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},h.prototype.isqr=function(t){return this.imul(t,t)},h.prototype.sqr=function(t){return this.mul(t,t)},h.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),f=this.m.bitLength();for(f=new i(2*f*f).toRed(this);0!==this.pow(f,c).cmp(u);)f.redIAdd(u);for(var h=this.pow(f,o),a=this.pow(t,o.addn(1).ishrn(1)),p=this.pow(t,o),d=s;0!==p.cmp(l);){for(var g=p,v=0;0!==g.cmp(l);v++)g=g.redSqr();r(d>v);var m=this.pow(h,new i(1).ishln(d-v-1));a=a.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return a},h.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},h.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},h.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},h.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new p(t)},n(p,h),p.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},p.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},p.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},p.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).ishrn(this.shift),o=a;return a.cmp(this.m)>=0?o=a.isub(this.m):a.cmpn(0)<0&&(o=a.iadd(this.m)),o._forceRed(this)},p.prototype.invm=function(t){var e=this.imod(t._invmp(this.m).mul(this.r2));return e._forceRed(this)}}(\"undefined\"==typeof e||e,this)},{}],110:[function(t,e,r){(function(t){function r(t,e){return p[0]=t,p[1]=e,h[0]}function n(t){return h[0]=t,p[0]}function i(t){return h[0]=t,p[1]}function a(t,e){return p[1]=t,p[0]=e,h[0]}function o(t){return h[0]=t,p[1]}function s(t){return h[0]=t,p[0]}function l(t,e){return 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m=r.getExtension(\"WEBGL_depth_texture\");m?p?t.depth=s(r,u,c,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):d&&p?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):d?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):p&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var b=r.checkFramebufferStatus(r.FRAMEBUFFER);if(b!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(var v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(b)}i(r,e)}function c(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var l=0;i>l;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,f=[0|e,0|r];Object.defineProperties(f,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=f,u(this)}function f(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(0>e||e>s||0>r||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function h(t,e,r,n){d||(d=t.FRAMEBUFFER_UNSUPPORTED,g=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,v=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,m=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(0>e||e>o||0>r||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");n=n||{};var s=1;if(\"color\"in n){if(s=Math.max(0|n.color,0),0>s)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var f=!0;\"depth\"in n&&(f=!!n.depth);var h=!1;return\"stencil\"in n&&(h=!!n.stencil),new c(t,e,r,l,s,f,h,i)}var p=t(\"gl-texture2d\");e.exports=h;var d,g,v,m,y=null,b=c.prototype;Object.defineProperties(b,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return f(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t=0|t,f(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t=0|t,f(this,this._shape[0],t),t},enumerable:!1}}),b.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},b.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":179}],171:[function(t,e,r){arguments[4][34][0].apply(r,arguments)},{\"cwise-compiler\":172,dup:34}],172:[function(t,e,r){arguments[4][35][0].apply(r,arguments)},{\"./lib/thunk.js\":174,dup:35}],173:[function(t,e,r){arguments[4][36][0].apply(r,arguments)},{dup:36,uniq:175}],174:[function(t,e,r){arguments[4][37][0].apply(r,arguments)},{\"./compile.js\":173,dup:37}],175:[function(t,e,r){arguments[4][38][0].apply(r,arguments)},{dup:38}],176:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],177:[function(t,e,r){arguments[4][40][0].apply(r,arguments)},{dup:40}],178:[function(t,e,r){arguments[4][41][0].apply(r,arguments)},{\"bit-twiddle\":176,buffer:300,dup:41}],179:[function(t,e,r){\"use strict\";function 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l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}function o(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function s(t,e,r,n,i,a,s,l){var u=l.dtype,c=l.shape.slice();if(c.length<2||c.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var f=0,h=0,v=o(c,l.stride.slice());\"float32\"===u?f=t.FLOAT:\"float64\"===u?(f=t.FLOAT,v=!1,u=\"float32\"):\"uint8\"===u?f=t.UNSIGNED_BYTE:(f=t.UNSIGNED_BYTE,v=!1,u=\"uint8\");var m=1;if(2===c.length)h=t.LUMINANCE,c=[c[0],c[1],1],l=p(l.data,c,[l.stride[0],l.stride[1],1],l.offset);else{if(3!==c.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===c[2])h=t.ALPHA;else if(2===c[2])h=t.LUMINANCE_ALPHA;else if(3===c[2])h=t.RGB;else{if(4!==c[2])throw new Error(\"gl-texture2d: Invalid shape for pixel 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s=o(n,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,s=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,s=!1,r=\"uint8\");var c=0;if(2===n.length)c=t.LUMINANCE,n=[n[0],n[1],1],e=p(e.data,n,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==n.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===n[2])c=t.ALPHA;else if(2===n[2])c=t.LUMINANCE_ALPHA;else if(3===n[2])c=t.RGB;else{if(4!==n[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");c=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,s=!1);var f,h,v=e.size;if(s)f=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var m=[n[2],n[2]*n[0],1];h=g.malloc(v,r);var y=p(h,n,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?d.assign(y,e):b(y,e),f=h.subarray(0,v)}var x=l(t);return t.texImage2D(t.TEXTURE_2D,0,c,n[0],n[1],0,c,u,f),s||g.free(h),new a(t,x,n[0],n[1],c,u)}function 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this._wrapS},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;2>e;++e)if(y.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return i(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return t=0|t,i(this,t,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t=0|t,i(this,this._shape[0],t),t}}}),x.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},x.dispose=function(){this.gl.deleteTexture(this.handle)},x.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},x.setPixels=function(t,e,r,n){var i=this.gl;if(this.bind(),Array.isArray(e)?(n=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),n=n||0,t instanceof 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t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(c+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],185:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],186:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,k=i*u-a*l,A=c*g-f*d,M=c*v-h*d,T=c*m-p*d,E=f*v-h*g,L=f*m-p*g,S=h*m-p*v,C=y*S-b*L+x*E+_*T-w*M+k*A;return 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i=t(\"./identity\");e.exports=n},{\"./identity\":185}],188:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*f+w*g,t[1]=b*i+x*l+_*h+w*v,t[2]=b*a+x*u+_*p+w*m,t[3]=b*o+x*c+_*d+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*f+w*g,t[5]=b*i+x*l+_*h+w*v,t[6]=b*a+x*u+_*p+w*m,t[7]=b*o+x*c+_*d+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*f+w*g,t[9]=b*i+x*l+_*h+w*v,t[10]=b*a+x*u+_*p+w*m,t[11]=b*o+x*c+_*d+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*f+w*g,t[13]=b*i+x*l+_*h+w*v,t[14]=b*a+x*u+_*p+w*m,t[15]=b*o+x*c+_*d+w*y,t}e.exports=n},{}],189:[function(t,e,r){function n(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}e.exports=n},{}],190:[function(t,e,r){function n(t,e,r,n){var 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n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;3>r;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=h[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],f=n.prototype;f.isOpaque=function(){return this.opacity>=1},f.isTransparent=function(){return this.opacity<1},f.drawTransparent=f.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var f=0;3>f;++f)e.lineWidth(this.lineWidth[f]),r.capSize=this.capSize[f]*u,e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var h=function(){for(var t=new Array(3),e=0;3>e;++e){for(var r=[],n=1;2>=n;++n)for(var i=-1;1>=i;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();f.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;3>u;++u){this.lineOffset[u]=l;t:for(var c=0;s>c;++c){for(var f=r[c],h=0;3>h;++h)if(isNaN(f[h])||!isFinite(f[h]))continue t;var p=n[c],d=e[u];if(Array.isArray(d[0])&&(d=e[c]),3===d.length&&(d=[d[0],d[1],d[2],1]),!isNaN(p[0][u])&&!isNaN(p[1][u])){if(p[0][u]<0){var g=f.slice();g[u]+=p[0][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}if(p[1][u]>0){var g=f.slice();g[u]+=p[1][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},f.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":329,\"gl-buffer\":325,\"gl-vao\":420}],329:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":385}],330:[function(t,e,r){arguments[4][170][0].apply(r,arguments)},{dup:170,\"gl-texture2d\":416}],331:[function(t,e,r){r.lineVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  vec2 dir = (matrix * vec3(d, 0)).xy;\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = 0.5 * width *\\n    normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n}\\n\",r.lineFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\\n\",r.mitreVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 p;\\n\\nuniform mat3  matrix;\\nuniform vec2 screenShape;\\nuniform float radius;\\n\\nvoid main() {\\n  vec3 pp = matrix * vec3(p, 1);\\n  gl_Position  = vec4(pp.xy, 0, pp.z);\\n  gl_PointSize = radius;\\n}\\n\",r.mitreFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\nattribute vec4 pick0, pick1;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = width *\\n    normalize(screenShape.yx * vec2(d.y, -d.x)) / screenShape.xy;\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\\n\",r.fillVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 projectAxis;\\nuniform float projectValue;\\nuniform float depth;\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 p = base.xy / base.z;\\n  if(d.y < 0.0 || (d.y == 0.0 && d.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\\n\",r.fillFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"},{}],332:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.dashPattern=e,this.lineBuffer=r,this.pickBuffer=n,this.lineShader=i,this.mitreShader=a,this.fillShader=o,this.pickShader=s,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0,this.lodBuffer=[]}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=l(r,[1,1]),c=o(r,f.lineVertex,f.lineFragment),h=o(r,f.mitreVertex,f.mitreFragment),p=o(r,f.fillVertex,f.fillFragment),d=o(r,f.pickVertex,f.pickFragment),g=new n(t,u,i,a,c,h,p,d);return t.addObject(g),g.update(e),g}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),f=t(\"./lib/shaders\"),h=n.prototype;h.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[1,0],n=[-1,0],i=[0,1],a=[0,-1];return function(){var o=this.plot,s=this.color,l=this.width,u=(this.numPoints,this.bounds),c=this.vertCount,f=o.gl,h=o.viewBox,p=o.dataBox,d=o.pixelRatio,g=u[2]-u[0],v=u[3]-u[1],m=p[2]-p[0],y=p[3]-p[1],b=h[2]-h[0],x=h[3]-h[1];t[0]=2*g/m,t[4]=2*v/y,t[6]=2*(u[0]-p[0])/m-1,t[7]=2*(u[1]-p[1])/y-1,e[0]=b,e[1]=x;var _=this.lineBuffer;_.bind();var w=this.fill;if(w[0]||w[1]||w[2]||w[3]){var k=this.fillShader;k.bind();var A=k.uniforms;A.matrix=t,A.depth=o.nextDepthValue();var M=k.attributes;M.a.pointer(f.FLOAT,!1,16,0),M.d.pointer(f.FLOAT,!1,16,8),f.depthMask(!0),f.enable(f.DEPTH_TEST);var T=this.fillColor;w[0]&&(A.color=T[0],A.projectAxis=n,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[1]&&(A.color=T[1],A.projectAxis=a,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[2]&&(A.color=T[2],A.projectAxis=r,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[3]&&(A.color=T[3],A.projectAxis=i,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),f.depthMask(!1),f.disable(f.DEPTH_TEST)}var E=this.lineShader;E.bind();var L=E.uniforms;L.matrix=t,L.color=s,L.width=l*d,L.screenShape=e,L.dashPattern=this.dashPattern.bind(),L.dashLength=this.dashLength*d;var S=E.attributes;if(S.a.pointer(f.FLOAT,!1,16,0),S.d.pointer(f.FLOAT,!1,16,8),f.drawArrays(f.TRIANGLES,0,c),l>2&&!this.usingDashes){var C=this.mitreShader;C.bind();var P=C.uniforms;P.matrix=t,P.color=s,P.screenShape=e,P.radius=l*d,C.attributes.p.pointer(f.FLOAT,!1,48,0),f.drawArrays(f.POINTS,0,c/3|0)}}}(),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[0,0,0,0];return function(n){var i=this.plot,a=this.pickShader,o=this.lineBuffer,s=this.pickBuffer,l=this.width,u=this.numPoints,c=this.bounds,f=this.vertCount,h=i.gl,p=i.viewBox,d=i.dataBox,g=i.pickPixelRatio,v=c[2]-c[0],m=c[3]-c[1],y=d[2]-d[0],b=d[3]-d[1],x=p[2]-p[0],_=p[3]-p[1];\n",
+       "this.pickOffset=n,t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(c[0]-d[0])/y-1,t[7]=2*(c[1]-d[1])/b-1,e[0]=x,e[1]=_,r[0]=255&n,r[1]=n>>>8&255,r[2]=n>>>16&255,r[3]=n>>>24,a.bind();var w=a.uniforms;w.matrix=t,w.width=l*g,w.pickOffset=r,w.screenShape=e;var k=a.attributes;return o.bind(),k.a.pointer(h.FLOAT,!1,16,0),k.d.pointer(h.FLOAT,!1,16,8),s.bind(),k.pick0.pointer(h.UNSIGNED_BYTE,!1,8,0),k.pick1.pointer(h.UNSIGNED_BYTE,!1,8,4),h.drawArrays(h.TRIANGLES,0,f),n+u}}(),h.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},h.update=function(t){t=t||{};var e=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);for(var r=t.dashes||[1],n=0,a=0;a<r.length;++a)n+=r[a];for(var o=c.mallocUint8(n),s=0,f=255,a=0;a<r.length;++a){for(var h=0;h<r[a];++h)o[s++]=f;f^=255}this.dashPattern.dispose(),this.usingDashes=r.length>1,this.dashPattern=l(e,u(o,[n,1,4],[1,0,0])),this.dashPattern.minFilter=e.NEAREST,this.dashPattern.magFilter=e.NEAREST,this.dashLength=n,c.free(o);var p=t.positions;this.data=p;var d=this.bounds;d[0]=d[1]=1/0,d[2]=d[3]=-(1/0);var g=this.numPoints=p.length>>>1;if(0!==g){for(var a=0;g>a;++a){var v=p[2*a],m=p[2*a+1];d[0]=Math.min(d[0],v),d[1]=Math.min(d[1],m),d[2]=Math.max(d[2],v),d[3]=Math.max(d[3],m)}d[0]===d[2]&&(d[2]+=1),d[3]===d[1]&&(d[3]+=1);var y=c.mallocFloat32(24*(g-1)),b=c.mallocUint32(12*(g-1)),x=y.length,_=b.length,s=g;for(this.vertCount=6*(g-1);s>1;){var w=--s,v=p[2*s],m=p[2*s+1];v=(v-d[0])/(d[2]-d[0]),m=(m-d[1])/(d[3]-d[1]);var k=w-1,A=p[2*k],M=p[2*k+1];A=(A-d[0])/(d[2]-d[0]),M=(M-d[1])/(d[3]-d[1]);var T=A-v,E=M-m,L=w|1<<24,S=w-1,C=w,P=w-1|1<<24;y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S}this.lineBuffer.update(y),this.pickBuffer.update(b),c.free(y),c.free(b)}},h.dispose=function(){this.plot.removeObject(this),this.lineBuffer.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":331,\"gl-buffer\":325,\"gl-shader\":385,\"gl-texture2d\":416,ndarray:438,\"typedarray-pool\":463}],333:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":385}],334:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;3>n;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;3>r;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=v(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=p(new Array(1024),[256,1,4]),f=0;1024>f;++f)s.data[f]=255;var h=c(e,s);h.wrap=e.REPEAT;var d=new o(e,r,n,i,a,h);return d.update(t),d}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),f=t(\"glsl-read-float\"),h=t(\"binary-search-bounds\"),p=t(\"ndarray\"),d=t(\"./lib/shaders\"),g=d.createShader,v=d.createPickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){this.dirty=!0,\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var e=t.position||t.positions;if(e){var r=t.color||t.colors||[0,0,0,1],i=t.lineWidth||1,a=[],o=[],s=[],l=0,u=0,c=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];t:for(var f=1;f<e.length;++f){var d=e[f-1],g=e[f];o.push(l),s.push(d.slice());for(var v=0;3>v;++v){if(isNaN(d[v])||isNaN(g[v])||!isFinite(d[v])||!isFinite(g[v]))continue t;c[0][v]=Math.min(c[0][v],d[v],g[v]),c[1][v]=Math.max(c[1][v],d[v],g[v])}var m,y;Array.isArray(r[0])?(m=r[f-1],y=r[f]):m=y=r,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]);var b,x;Array.isArray(i)?(b=i[f-1],x=lineWidht[f]):b=x=i;var _=l;l+=n(d,g),a.push(d[0],d[1],d[2],g[0],g[1],g[2],_,b,m[0],m[1],m[2],m[3],d[0],d[1],d[2],g[0],g[1],g[2],_,-b,m[0],m[1],m[2],m[3],g[0],g[1],g[2],d[0],d[1],d[2],l,-b,y[0],y[1],y[2],y[3],g[0],g[1],g[2],d[0],d[1],d[2],l,b,y[0],y[1],y[2],y[3]),u+=4}if(this.buffer.update(a),o.push(l),s.push(e[e.length-1].slice()),this.bounds=c,this.vertexCount=u,this.points=s,this.arcLength=o,\"dashes\"in t){var w=t.dashes,k=w.slice();k.unshift(0);for(var f=1;f<k.length;++f)k[f]=k[f-1]+k[f];for(var A=p(new Array(1024),[256,1,4]),f=0;256>f;++f){for(var v=0;4>v;++v)A.set(f,0,v,0);1&h.le(k,k[k.length-1]*f/255)?A.set(f,0,0,0):A.set(f,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=f(t.value[0],t.value[1],t.value[2],0),r=h.le(this.arcLength,e);if(0>r)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;3>u;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(.5>o?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":333,\"binary-search-bounds\":335,\"gl-buffer\":325,\"gl-texture2d\":416,\"gl-vao\":420,\"glsl-read-float\":336,ndarray:438}],335:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],336:[function(t,e,r){function n(t,e,r,n){return i[0]=n,i[1]=r,i[2]=e,i[3]=t,a[0]}e.exports=n;var i=new Uint8Array(4),a=new Float32Array(i.buffer)},{}],337:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=c*o-s*u,h=-c*a+s*l,p=u*a-o*l,d=r*f+n*h+i*p;return d?(d=1/d,t[0]=f*d,t[1]=(-c*n+i*u)*d,t[2]=(s*n-i*o)*d,t[3]=h*d,t[4]=(c*r-i*l)*d,t[5]=(-s*r+i*a)*d,t[6]=p*d,t[7]=(-u*r+n*l)*d,t[8]=(o*r-n*a)*d,t):null}e.exports=n},{}],338:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{dup:180}],339:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],340:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{dup:182}],341:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{dup:183}],342:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],343:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],344:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{dup:186}],345:[function(t,e,r){arguments[4][187][0].apply(r,arguments)},{\"./identity\":343,dup:187}],346:[function(t,e,r){arguments[4][188][0].apply(r,arguments)},{dup:188}],347:[function(t,e,r){arguments[4][190][0].apply(r,arguments)},{dup:190}],348:[function(t,e,r){arguments[4][191][0].apply(r,arguments)},{dup:191}],349:[function(t,e,r){arguments[4][192][0].apply(r,arguments)},{dup:192}],350:[function(t,e,r){arguments[4][193][0].apply(r,arguments)},{dup:193}],351:[function(t,e,r){arguments[4][194][0].apply(r,arguments)},{dup:194}],352:[function(t,e,r){arguments[4][195][0].apply(r,arguments)},{dup:195}],353:[function(t,e,r){arguments[4][196][0].apply(r,arguments)},{dup:196}],354:[function(t,e,r){\"use strict\";function n(t,e){for(var r=[0,0,0,0],n=0;4>n;++n)for(var i=0;4>i;++i)r[i]+=t[4*n+i]*e[n];return r}function i(t,e,r,i,a){for(var o=n(i,n(r,n(e,[t[0],t[1],t[2],1]))),s=0;3>s;++s)o[s]/=o[3];return[.5*a[0]*(1+o[0]),.5*a[1]*(1-o[1])]}function a(t,e){if(2===t.length){for(var r=0,n=0,i=0;2>i;++i)r+=Math.pow(e[i]-t[0][i],2),n+=Math.pow(e[i]-t[1][i],2);return r=Math.sqrt(r),n=Math.sqrt(n),1e-6>r+n?[1,0]:[n/(r+n),r/(n+r)]}if(3===t.length){var a=[0,0];return u(t[0],t[1],t[2],e,a),l(t,a)}return[]}function o(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;3>o;++o)r[o]+=a*i[o];return r}function s(t,e,r,n,s,l){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),c=0;c<t.length;++c)u[c]=i(t[c],r,n,s,l);for(var f=0,h=1/0,c=0;c<u.length;++c){for(var p=0,d=0;2>d;++d)p+=Math.pow(u[c][d]-e[d],2);h>p&&(h=p,f=c)}for(var g=a(u,e),v=0,c=0;3>c;++c){if(g[c]<-.001||g[c]>1.0001)return null;v+=g[c]}return Math.abs(v-1)>.001?null:[f,o(t,g),g]}var l=t(\"barycentric\"),u=t(\"polytope-closest-point/lib/closest_point_2d.js\");e.exports=s},{barycentric:357,\"polytope-closest-point/lib/closest_point_2d.js\":359}],355:[function(t,e,r){var n=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution_2_0(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n  \\n  if(!gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = cookTorranceSpecular_1_1(L, V, N, roughness, fresnel);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5,0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\",c=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(f_position, clipBounds[0])) || \\n     any(greaterThan(f_position, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\",f=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\",h=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\",p=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\";r.meshShader={vertex:n,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:a,fragment:o,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:s,fragment:l,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:f,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:h,fragment:p,attributes:[{name:\"position\",type:\"vec3\"}]}},{}],356:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,g,v,m,y,b,x,_,w,k,A,M,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=v,this.edgeUVs=m,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=b,this.pointColors=_,this.pointUVs=w,this.pointSizes=k,this.pointIds=x,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this._model=R,this._view=R,this._projection=R,this._resolution=[1,1]}function i(t){for(var e=w({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;256>n;++n){for(var i=e[n],a=0;3>a;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return _(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;e>i;++i)n[i]=0;for(var a=t.length,i=0;a>i;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;e>n;++n)r[n]=t[n][2];return r}function s(t){var e=d(t,E);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=d(t,L);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=d(t,S);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function c(t){var e=d(t,C);return e.attributes.position.location=0,e.attributes.id.location=1,e}function f(t){var e=d(t,P);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function h(t){var e=d(t,z);return e.attributes.position.location=0,e}function p(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),p=f(e),d=h(e),y=m(e,_(new Uint8Array([255,255,255,255]),[1,1,4]));y.generateMipmap(),y.minFilter=e.LINEAR_MIPMAP_LINEAR,y.magFilter=e.LINEAR;var b=g(e),x=g(e),w=g(e),k=g(e),A=g(e),M=v(e,[{buffer:b,type:e.FLOAT,size:3},{buffer:A,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:x,type:e.FLOAT,size:4},{buffer:w,type:e.FLOAT,size:2},{buffer:k,type:e.FLOAT,size:3}]),T=g(e),E=g(e),L=g(e),S=g(e),C=v(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:S,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:E,type:e.FLOAT,size:4},{buffer:L,type:e.FLOAT,size:2}]),P=g(e),z=g(e),R=g(e),O=g(e),I=g(e),j=v(e,[{buffer:P,type:e.FLOAT,size:3},{buffer:I,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:e.FLOAT,size:4},{buffer:R,type:e.FLOAT,size:2},{buffer:O,type:e.FLOAT,size:1}]),N=g(e),F=v(e,[{buffer:N,type:e.FLOAT,size:3}]),D=new n(e,y,r,i,a,o,p,d,b,A,x,w,k,M,T,S,E,L,C,P,I,z,R,O,j,N,F);return D.update(t),D}var d=t(\"gl-shader\"),g=t(\"gl-buffer\"),v=t(\"gl-vao\"),m=t(\"gl-texture2d\"),y=t(\"normals\"),b=t(\"gl-mat4/multiply\"),x=t(\"gl-mat4/invert\"),_=t(\"ndarray\"),w=t(\"colormap\"),k=t(\"simplicial-complex-contour\"),A=t(\"typedarray-pool\"),M=t(\"./lib/shaders\"),T=t(\"./lib/closest-point\"),E=M.meshShader,L=M.wireShader,S=M.pointShader,C=M.pickShader,P=M.pointPickShader,z=M.contourShader,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=n.prototype;O.isOpaque=function(){return this.opacity>=1},O.isTransparent=function(){return this.opacity<1},O.pickSlots=1,O.setPickBase=function(t){this.pickId=t},O.highlight=function(t){if(!t||!this.contourEnable)return void(this.contourCount=0);for(var e=k(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=A.mallocFloat32(6*a),s=0,l=0;a>l;++l)for(var u=r[l],c=0;2>c;++c){var f=u[0];2===u.length&&(f=u[c]);for(var h=n[f][0],p=n[f][1],d=i[f],g=1-d,v=this.positions[h],m=this.positions[p],y=0;3>y;++y)o[s++]=d*v[y]+g*m[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),A.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"opacity\"in t&&(this.opacity=t.opacity),t.texture?(this.texture.dispose(),this.texture=m(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],f=[],h=[],p=[],d=[],g=[],v=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var k=t.vertexNormals,A=t.cellNormals;t.useFacetNormals&&!A&&(A=y.faceNormals(r,n)),A||k||(k=y.vertexNormals(r,n));var M=t.vertexColors,T=t.cellColors,E=t.meshColor||[1,1,1,1],L=t.vertexUVs,S=t.vertexIntensity,C=t.cellUVs,P=t.cellIntensity,z=1/0,R=-(1/0);if(!L&&!C)if(S)for(var O=0;O<S.length;++O){var I=S[O];z=Math.min(z,I),R=Math.max(R,I)}else if(P)for(var O=0;O<P.length;++O){var I=P[O];z=Math.min(z,I),R=Math.max(R,I)}else for(var O=0;O<n.length;++O){var I=n[O][2];z=Math.min(z,I),R=Math.max(R,I)}S?this.intensity=S:P?this.intensity=a(r,n.length,P):this.intensity=o(n);var j=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var O=0;O<n.length;++O)for(var F=n[O],D=0;3>D;++D)!isNaN(F[D])&&isFinite(F[D])&&(this.bounds[0][D]=Math.min(this.bounds[0][D],F[D]),this.bounds[1][D]=Math.max(this.bounds[1][D],F[D]));var B=0,U=0,V=0;t:for(var O=0;O<r.length;++O){var q=r[O];switch(q.length){case 1:for(var H=q[0],F=n[H],D=0;3>D;++D)if(isNaN(F[D])||!isFinite(F[D]))continue t;v.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?b.push(G[0],G[1],G[2],1):b.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],x.push(Y[0],Y[1]),j?_.push(j[H]):_.push(N),w.push(O),V+=1;break;case 2:for(var D=0;2>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;2>D;++D){var H=q[D],F=n[H];h.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?p.push(G[0],G[1],G[2],1):p.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],d.push(Y[0],Y[1]),g.push(O)}U+=1;break;case 3:for(var D=0;3>D;++D)for(var H=q[D],F=n[H],X=0;3>X;++X)if(isNaN(F[X])||!isFinite(F[X]))continue t;for(var D=0;3>D;++D){var H=q[D],F=n[H];s.push(F[0],F[1],F[2]);var G;G=M?M[H]:T?T[O]:E,3===G.length?l.push(G[0],G[1],G[2],1):l.push(G[0],G[1],G[2],G[3]);var Y;Y=L?L[H]:S?[(S[H]-z)/(R-z),0]:C?C[O]:P?[(P[O]-z)/(R-z),0]:[(F[2]-z)/(R-z),0],c.push(Y[0],Y[1]);var W;W=k?k[H]:A[O],u.push(W[0],W[1],W[2]),f.push(O)}B+=1}}this.pointCount=V,this.edgeCount=U,this.triangleCount=B,this.pointPositions.update(v),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(h),this.edgeColors.update(p),this.edgeUVs.update(d),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(f))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(var o=0;3>o;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;3>o;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;3>o;++o){for(var c=l[12+o],f=0;3>f;++f)c+=l[4*f+o]*this.lightPosition[f];s.lightPosition[o]=c/u}if(this.triangleCount>0){var h=this.triShader;h.bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var h=this.lineShader;h.bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var h=this.pointShader;h.bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var h=this.contourShader;h.bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=T(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=p},{\"./lib/closest-point\":354,\"./lib/shaders\":355,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-shader\":385,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,normals:358,\"simplicial-complex-contour\":360,\"typedarray-pool\":463}],357:[function(t,e,r){\"use strict\";function n(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];\n",
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s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,f=i.dataBox,h=i.screenBox,p=i.pixelRatio,d=i.tickEnable,g=i.tickPad,v=i.tickColor,m=i.tickAngle,y=(i.tickMarkLength,i.labelEnable),b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],k=this.labelCount[n],A=l.lt(o,f[n]),M=l.le(o,f[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(h[2+n]-h[n])-1;var T=2/h[2+(1^n)]-h[1^n];e[1^n]=T*c[1^n]-1,d[n]&&(e[1^n]-=T*p*g[n],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n],a.uniforms.angle=m[n],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n]&&(e[1^n]-=T*p*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,k)),e[1^n]=T*c[2+(1^n)]-1,d[n+2]&&(e[1^n]+=T*p*g[n+2],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n+2],a.uniforms.angle=m[n+2],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n+2]&&(e[1^n]+=T*p*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,k))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){for(var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,o=r.titleCenter,u=r.pixelRatio,c=0;2>c;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;2>u;++u){var c=a[u],f=a[u+2],h=f-c,p=.5*(o[u+2]+o[u]),d=o[u+2]-o[u],g=l[u],v=l[u+2],m=v-g,y=s[u],b=s[u+2],x=b-y;e[u]=2*h/d*m/x,t[u]=2*(c-p)/d*m/x}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){for(var e=[],r=t.ticks,n=t.bounds,i=0;2>i;++i){for(var a=[Math.floor(e.length/3)],o=[-(1/0)],l=r[i],u=0;u<l.length;++u){for(var c=l[u],f=c.x,h=c.text,p=c.font||\"sans-serif\",d=c.fontSize||12,g=s(p,h).data,v=1/(n[i+2]-n[i]),m=n[i],y=0;y<g.length;y+=2)e.push(g[y]*d,-g[y+1]*d,(f-m)*v);a.push(Math.floor(e.length/3)),o.push(f)}this.tickOffset[i]=a,this.tickX[i]=o}for(var i=0;2>i;++i){this.labelOffset[i]=Math.floor(e.length/3);for(var g=s(t.labelFont[i],t.labels[i]).data,d=t.labelSize[i],u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.labelCount[i]=Math.floor(e.length/3)-this.labelOffset[i]}this.titleOffset=Math.floor(e.length/3);for(var g=s(t.titleFont,t.title).data,d=t.titleSize,u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.titleCount=Math.floor(e.length/3)-this.titleOffset,this.vbo.update(e)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458}],370:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],371:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-(1/0),-(1/0)],this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}function i(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function a(t,e){return t.x-e.x}function o(t){var e=t.gl,r=s(e,[e.drawingBufferWidth,e.drawingBufferHeight]),i=new n(e,r);return i.grid=l(i),i.text=u(i),i.line=c(i),i.box=f(i),i.update(t),i}e.exports=o;var s=t(\"gl-select-static\"),l=t(\"./lib/grid\"),u=t(\"./lib/text\"),c=t(\"./lib/line\"),f=t(\"./lib/box\"),h=n.prototype;h.setDirty=function(){this.dirty=this.pickDirty=!0},h.setOverlayDirty=function(){this.dirty=!0},h.nextDepthValue=function(){return this._depthCounter++/65536},h.draw=function(){return function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT),t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;2>d;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(var d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind();for(var d=0;2>d;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();for(var b=this.overlays,d=0;d<b.length;++d)b[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),h.drawPick=function(){return function(){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}(),h.pick=function(){return function(t,e){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){\n",
+       "var f=u[c].pick(a,o,l);if(f)return f}return null}}(),h.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},h.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},h.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},h.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;2>u;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.setDirty()},h.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},h.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},h.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},h.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},h.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":365,\"./lib/grid\":366,\"./lib/line\":367,\"./lib/text\":369,\"gl-select-static\":384}],372:[function(t,e,r){\"use strict\";e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",pickFragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],373:[function(t,e,r){\"use strict\";function n(t){if(t in h)return h[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var f=s[0]-o[0],h=s[1]-o[1],p=Math.sqrt(f*f+h*h);f/=p,h/=p,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(a[0],a[1]+1.4),n.push(h,-f),r.push(o[0],o[1]+1.4),n.push(h,-f)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;2>o;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return h[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.offsetBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,f.vertex,f.fragment),a=o(r,f.pickVertex,f.pickFragment),l=s(r),u=s(r),c=s(r),h=s(r),p=new i(t,n,a,l,u,c,h);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),f=t(\"./lib/shaders\"),h={},p=i.prototype;!function(){function t(){var t=this.plot,n=this.bounds,i=t.viewBox,a=t.dataBox,o=t.pixelRatio,s=n[2]-n[0],l=n[3]-n[1],u=a[2]-a[0],c=a[3]-a[1];e[0]=2*s/u,e[4]=2*l/c,e[6]=2*(n[0]-a[0])/u-1,e[7]=2*(n[1]-a[1])/c-1;var f=i[2]-i[0],h=i[3]-i[1];r[0]=2*o/f,r[1]=2*o/h}var e=[1,0,0,0,1,0,0,0,1],r=[1,1];p.draw=function(){var n=this.plot,i=this.shader,a=this.numVertices,o=n.gl;t.call(this),i.bind(),i.uniforms.pixelScale=r,i.uniforms.viewTransform=e,this.positionBuffer.bind(),i.attributes.position.pointer(),this.offsetBuffer.bind(),i.attributes.offset.pointer(),this.colorBuffer.bind(),i.attributes.color.pointer(o.UNSIGNED_BYTE,!0),o.drawArrays(o.TRIANGLES,0,a)};var n=[0,0,0,0];p.drawPick=function(i){var a=this.plot,o=this.pickShader,s=this.numVertices,l=a.gl;this.pickOffset=i;for(var u=0;4>u;++u)n[u]=i>>8*u&255;return t.call(this),o.bind(),o.uniforms.pixelScale=r,o.uniforms.viewTransform=e,o.uniforms.pickOffset=n,this.positionBuffer.bind(),o.attributes.position.pointer(),this.offsetBuffer.bind(),o.attributes.offset.pointer(),this.idBuffer.bind(),o.attributes.id.pointer(l.UNSIGNED_BYTE,!1),l.drawArrays(l.TRIANGLES,0,s),i+this.numPoints}}(),p.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},p.update=function(t){t=t||{};var e=t.positions||[],r=t.colors||[],i=t.glyphs||[],a=t.sizes||[],o=t.borderWidths||[],s=t.borderColors||[];this.points=e;for(var c=this.bounds=[1/0,1/0,-(1/0),-(1/0)],f=0,h=0;h<i.length;++h){f+=l(\"sans-serif\",i[h]).data.length+n(i[h]).coords.length>>1;for(var p=0;2>p;++p)c[p]=Math.min(c[p],e[2*h+p]),c[2+p]=Math.max(c[2+p],e[2*h+p])}c[0]===c[2]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);for(var d=1/(c[2]-c[0]),g=1/(c[3]-c[1]),v=c[0],m=c[1],y=u.mallocFloat32(2*f),b=u.mallocFloat32(2*f),x=u.mallocUint8(4*f),_=u.mallocUint32(f),w=0,h=0;h<i.length;++h){for(var k=l(\"sans-serif\",i[h]),A=n(i[h]),M=d*(e[2*h]-v),T=g*(e[2*h+1]-m),E=a[h],L=255*r[4*h],S=255*r[4*h+1],C=255*r[4*h+2],P=255*r[4*h+3],z=.5*(A.bounds[0]+A.bounds[2]),R=.5*(A.bounds[1]+A.bounds[3]),p=0;p<k.data.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-E*(k.data[p]-z),b[2*w+1]=-E*(k.data[p+1]-R),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1;var O=o[h];L=255*s[4*h],S=255*s[4*h+1],C=255*s[4*h+2],P=255*s[4*h+3];for(var p=0;p<A.coords.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-(E*(A.coords[p]-z)+O*A.normals[p]),b[2*w+1]=-(E*(A.coords[p+1]-R)+O*A.normals[p+1]),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1}this.numPoints=i.length,this.numVertices=f,this.positionBuffer.update(y),this.offsetBuffer.update(b),this.colorBuffer.update(x),this.idBuffer.update(_),u.free(y),u.free(b),u.free(x),u.free(_)},p.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":372,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458,\"typedarray-pool\":463,\"vectorize-text\":465}],374:[function(t,e,r){r.pointVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute float weight;\\n\\nuniform mat3 matrix;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\\n\",r.pointFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],375:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],376:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){4*h>=a?i(0,a-1,t,e,r,n):f(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;e>=o;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],f=a[o],h=o;h>t;){var p=r[h-1],d=n[2*(h-1)];if((p-s||l-d)>=0)break;r[h]=p,n[2*h]=d,n[2*h+1]=n[2*h-1],i[h]=i[h-1],a[h]=a[h-1],h-=1}r[h]=s,n[2*h]=l,n[2*h+1]=u,i[h]=c,a[h]=f}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],f=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=f}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0}function c(t,e,r,n,i,a,o,s){return(e-a[t]||o[2*t]-r||i-s[t])<0}function f(t,e,r,n,p,d){var g=(e-t+1)/6|0,v=t+g,m=e-g,y=t+e>>1,b=y-g,x=y+g,_=v,w=b,k=y,A=x,M=m,T=t+1,E=e-1,L=0;u(_,w,r,n,p,d)&&(L=_,_=w,w=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L),u(_,k,r,n,p,d)&&(L=_,_=k,k=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(_,A,r,n,p,d)&&(L=_,_=A,A=L),u(k,A,r,n,p,d)&&(L=k,k=A,A=L),u(w,M,r,n,p,d)&&(L=w,w=M,M=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L);var S=r[w],C=n[2*w],P=n[2*w+1],z=p[w],R=d[w],O=r[A],I=n[2*A],j=n[2*A+1],N=p[A],F=d[A],D=_,B=k,U=M,V=v,q=y,H=m,G=r[D],Y=r[B],X=r[U];r[V]=G,r[q]=Y,r[H]=X;for(var W=0;2>W;++W){var Z=n[2*D+W],$=n[2*B+W],K=n[2*U+W];n[2*V+W]=Z,n[2*q+W]=$,n[2*H+W]=K}var Q=p[D],J=p[B],tt=p[U];p[V]=Q,p[q]=J,p[H]=tt;var et=d[D],rt=d[B],nt=d[U];d[V]=et,d[q]=rt,d[H]=nt,o(b,t,r,n,p,d),o(x,e,r,n,p,d);for(var it=T;E>=it;++it)if(c(it,S,C,P,z,r,n,p))it!==T&&a(it,T,r,n,p,d),++T;else if(!c(it,O,I,j,N,r,n,p))for(;;){if(c(E,O,I,j,N,r,n,p)){c(E,S,C,P,z,r,n,p)?(s(it,T,E,r,n,p,d),++T,--E):(a(it,E,r,n,p,d),--E);break}if(--E<it)break}l(t,T-1,S,C,P,z,R,r,n,p,d),l(e,E+1,O,I,j,N,F,r,n,p,d),h>=T-2-t?i(t,T-2,r,n,p,d):f(t,T-2,r,n,p,d),h>=e-(E+2)?i(E+2,e,r,n,p,d):f(E+2,e,r,n,p,d),h>=E-T?i(T,E,r,n,p,d):f(T,E,r,n,p,d)}e.exports=n;var h=32},{}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;n>u;++u){var c=t[2*u],f=t[2*u+1],h=e[u];c>=i&&o>=c&&f>=a&&s>=f&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=f,e[l]=h,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var f=.5*o,h=s+1,p=u-s;r[_]=p,x[_++]=c;for(var d=0;2>d;++d)for(var g=0;2>g;++g){var v=i+d*f,m=a+g*f,y=n(t,e,h,u,v,m,v+f,m+f);if(y!==h){if(y-h>=Math.max(.9*p,32)){var b=u+s>>>1;l(v,m,f,h,b,c+1),h=b}l(v,m,f,h,y,c+1),h=y}}}var u=t.length>>>1;if(1>u)return[];for(var c=1/0,f=1/0,h=-(1/0),p=-(1/0),d=0;u>d;++d){var g=t[2*d],v=t[2*d+1];c=Math.min(c,g),h=Math.max(h,g),f=Math.min(f,v),p=Math.max(p,v),e[d]=d}c===h&&(h+=1+Math.abs(h)),f===p&&(p+=1+Math.abs(h));var m=1/(h-c),y=1/(p-f),b=Math.max(h-c,p-f);a=a||[0,0,0,0],a[0]=c,a[1]=f,a[2]=h,a[3]=p;var x=o.mallocInt32(u),_=0;l(c,f,b,0,u,0),s(x,t,e,r,u);for(var w=[],k=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*m,t[2*_+1]=(t[2*_+1]-f)*y;var M=x[_];M!==k&&(w.push(new i(b*Math.pow(.5,M),_+1,A-(_+1))),A=_+1,k=M)}return w.push(new i(b*Math.pow(.5,M+1),0,A)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":376,\"typedarray-pool\":463}],378:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.weightBuffer=n,this.shader=i,this.pickShader=a,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),h=new n(t,i,s,l,u,f);return h.update(e),t.addObject(h),h}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var f=n.prototype;f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},f.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords);var r=t.positions,n=u.mallocFloat32(r.length),i=u.mallocInt32(r.length>>>1);n.set(r);var a=u.mallocFloat32(r.length);this.points=r,this.scales=l(n,i,a,this.bounds),this.offsetBuffer.update(n),this.pickBuffer.update(i),this.weightBuffer.update(a);for(var o=u.mallocFloat32(r.length>>>1),s=0,c=0;s<r.length;s+=2,++c)o[c]=n[s];u.free(i),u.free(n),u.free(a),this.xCoords=o,this.pointCount=r.length>>>1,this.pickOffset=0},f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.scales,o=this.offsetBuffer,l=this.pickBuffer,u=this.bounds,c=this.size,f=this.borderSize,h=n.gl,p=n.pickPixelRatio,d=n.viewBox,g=n.dataBox;if(0===this.pointCount)return r;var v=u[2]-u[0],m=u[3]-u[1],y=g[2]-g[0],b=g[3]-g[1],x=(d[2]-d[0])*p/n.pixelRatio,_=(d[3]-d[1])*p/n.pixelRatio,w=Math.min(y/x,b/_);t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(u[0]-g[0])/y-1,t[7]=2*(u[1]-g[1])/b-1,this.pickOffset=r,e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,i.bind(),i.uniforms.matrix=t,i.uniforms.color=this.color,i.uniforms.borderColor=this.borderColor,i.uniforms.pointSize=p*(c+f),i.uniforms.pickOffset=e,0===this.borderSize?i.uniforms.centerFraction=2:i.uniforms.centerFraction=c/(c+f+1.25),o.bind(),i.attributes.position.pointer(),l.bind(),i.attributes.pickId.pointer(h.UNSIGNED_BYTE);for(var k=this.xCoords,A=(g[0]-u[0]-w*c*p)/v,M=(g[2]-u[0]+w*c*p)/v,T=a.length-1;T>=0;--T){var E=a[T];if(!(E.pixelSize<w&&T>1)){var L=E.offset,S=E.count+L,C=s.ge(k,A,L,S-1),P=s.lt(k,M,C,S-1)+1;h.drawArrays(h.POINTS,C,P-C)}}return r+this.pointCount}}(),f.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.scales,i=this.offsetBuffer,a=this.bounds,o=this.size,l=this.borderSize,u=e.gl,c=e.pixelRatio,f=e.viewBox,h=e.dataBox;if(0!==this.pointCount){var p=a[2]-a[0],d=a[3]-a[1],g=h[2]-h[0],v=h[3]-h[1],m=f[2]-f[0],y=f[3]-f[1],b=Math.min(g/m,v/y);t[0]=2*p/g,t[4]=2*d/v,t[6]=2*(a[0]-h[0])/g-1,t[7]=2*(a[1]-h[1])/v-1,r.bind(),r.uniforms.matrix=t,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointSize=c*(o+l),r.uniforms.useWeight=1,0===this.borderSize?r.uniforms.centerFraction=2:r.uniforms.centerFraction=o/(o+l+1.25),i.bind(),r.attributes.position.pointer(),this.weightBuffer.bind(),r.attributes.weight.pointer();for(var x=this.xCoords,_=(h[0]-a[0]-b*o*c)/p,w=(h[2]-a[0]+b*o*c)/p,k=!0,A=n.length-1;A>=0;--A){var M=n[A];if(!(M.pixelSize<b&&A>1)){var T=M.offset,E=M.count+T,L=s.ge(x,_,T,E-1),S=s.lt(x,w,L,E-1)+1;u.drawArrays(u.POINTS,L,S-L),k&&(k=!1,r.uniforms.useWeight=0)}}}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":374,\"binary-search-bounds\":375,\"gl-buffer\":325,\"gl-shader\":385,\"snap-points-2d\":377,\"typedarray-pool\":463}],379:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;2>c;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":465}],380:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},v={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,f)},r.createOrtho=function(t){return n(t,h)},r.createProject=function(t){return n(t,p)},r.createPickPerspective=function(t){return n(t,d)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,v)}},{\"gl-shader\":385}],381:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,f,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=f,this.pickProjectShader=h,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=S,r=0;2>r;++r)for(var n=0;3>n;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function f(t,e,r,n,a){var o,f=e.axesProject,h=e.gl,p=t.uniforms,d=r.model||x,g=r.view||x,v=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/h.drawingBufferWidth,w[1]=2/h.drawingBufferHeight,t.bind(),p.view=g,p.projection=v,p.screenSize=w,p.highlightId=e.highlightId,p.highlightScale=e.highlightScale,p.clipBounds=b,p.pickGroup=e.pickId/255,p.pixelRatio=e.pixelRatio;for(var _=0;3>_;++_)if(f[_]&&e.projectOpacity[_]<1===n){p.scale=e.projectScale[_],p.opacity=e.projectOpacity[_];for(var S=E,C=0;16>C;++C)S[C]=0;for(var C=0;4>C;++C)S[5*C]=1;S[5*_]=0,o[_]<0?S[12+_]=y[0][_]:S[12+_]=y[1][_],m(S,d,S),p.model=S;var P=(_+1)%3,z=(_+2)%3,R=s(k),O=s(A);R[P]=1,O[z]=1;var I=i(v,g,d,l(M,R)),j=i(v,g,d,l(T,O));if(Math.abs(I[1])>Math.abs(j[1])){var N=I;I=j,j=N,N=R,R=O,O=N;var F=P;P=z,z=F}I[0]<0&&(R[P]=-1),j[1]>0&&(O[z]=-1);for(var D=0,B=0,C=0;4>C;++C)D+=Math.pow(d[4*P+C],2),B+=Math.pow(d[4*z+C],2);R[P]/=Math.sqrt(D),O[z]/=Math.sqrt(B),p.axes[0]=R,p.axes[1]=O,p.fragClipBounds[0]=u(L,b[0],_,-1e8),p.fragClipBounds[1]=u(L,b[1],_,1e8),e.vao.draw(h.TRIANGLES,e.vertexCount),e.lineWidth>0&&(h.lineWidth(e.lineWidth),e.vao.draw(h.LINES,e.lineVertexCount,e.vertexCount))}}function h(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=z,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}f(e,r,n,i,a),r.vao.unbind()}function p(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=d(e),c=d(e),f=d(e),h=d(e),p=g(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:f,size:2,type:e.FLOAT},{buffer:h,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new o(e,r,n,i,u,c,f,h,p,a,s,l);return v.update(t),v}var d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"typedarray-pool\"),m=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=p;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],k=[0,0,0],A=[0,0,0],M=[0,0,0,1],T=[0,0,0,1],E=x.slice(),L=[0,0,0],S=[[0,0,0],[0,0,0]],C=[-1e8,-1e8,-1e8],P=[1e8,1e8,1e8],z=[C,P];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;h(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||0>e)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;3>i;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in t&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-(1/0),-(1/0),-(1/0)],l=t.glyph,u=t.color,c=t.size,f=t.angle,h=t.lineColor,p=0,d=0,g=0,m=n.length;t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_)if(isNaN(x[_])||!isFinite(x[_]))continue t;var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];d+=3*k.cells.length,g+=2*A.edges.length}var T=d+g,E=v.mallocFloat(3*T),L=v.mallocFloat(4*T),S=v.mallocFloat(2*T),C=v.mallocUint32(T),P=[0,a[1]],z=0,R=d,O=[0,0,0,1],I=[0,0,0,1],j=Array.isArray(u)&&Array.isArray(u[0]),N=Array.isArray(h)&&Array.isArray(h[0]);t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_){if(isNaN(x[_])||!isFinite(x[_])){p+=1;continue t}s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_])}var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];if(Array.isArray(u)){var F;if(F=j?u[y]:u,3===F.length){for(var _=0;3>_;++_)O[_]=F[_];O[3]=1}else if(4===F.length)for(var _=0;4>_;++_)O[_]=F[_];\n",
+       "}else O[0]=O[1]=O[2]=0,O[3]=1;if(Array.isArray(h)){var F;if(F=N?h[y]:h,3===F.length){for(var _=0;3>_;++_)I[_]=F[_];I[_]=1}else if(4===F.length)for(var _=0;4>_;++_)I[_]=F[_]}else I[0]=I[1]=I[2]=0,I[3]=1;var D=.5;Array.isArray(c)?D=+c[y]:c?D=+c:this.useOrtho&&(D=12);var B=0;Array.isArray(f)?B=+f[y]:f&&(B=+f);for(var U=Math.cos(B),V=Math.sin(B),x=n[y],_=0;3>_;++_)s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_]);a[0]<0?P[0]=a[0]*(1+M[1][0]):a[0]>0&&(P[0]=-a[0]*(1+M[0][0]));for(var q=k.cells,H=k.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;3>Y;++Y){for(var X=0;3>X;++X)E[3*z+X]=x[X];for(var X=0;4>X;++X)L[4*z+X]=O[X];C[z]=p;var W=H[G[Y]];S[2*z]=D*(U*W[0]-V*W[1]+P[0]),S[2*z+1]=D*(V*W[0]+U*W[1]+P[1]),z+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;2>Y;++Y){for(var X=0;3>X;++X)E[3*R+X]=x[X];for(var X=0;4>X;++X)L[4*R+X]=I[X];C[R]=p;var W=H[G[Y]];S[2*R]=D*(U*W[0]-V*W[1]+P[0]),S[2*R+1]=D*(V*W[0]+U*W[1]+P[1]),R+=1}p+=1}this.vertexCount=d,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(C)),v.free(E),v.free(L),v.free(S),v.free(C),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":379,\"./lib/shaders\":380,\"gl-buffer\":325,\"gl-mat4/multiply\":346,\"gl-vao\":420,\"typedarray-pool\":463}],382:[function(t,e,r){\"use strict\";r.boxVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(f>p||h>d)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*c;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":382,\"gl-buffer\":325,\"gl-shader\":385}],384:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(255>_inline_31_arg0_||255>_inline_31_arg1_||255>_inline_31_arg2_||255>_inline_31_arg3_){var 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l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],410:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\nattribute vec2 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  value = f.x;\\n  kill = f.y;\\n  planeCoordinate = uv.xy;\\n  \\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  float interpValue = (value - lowerBound.z) / (upperBound.z - lowerBound.z);\\n  vec4 surfaceColor = texture2D(colormap, vec2(interpValue, interpValue));\\n  vec4 litColor 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eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 || \\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e}},{\"gl-shader\":385}],411:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],412:[function(t,e,r){\"use strict\";function n(t){if(t in l)return l[t];for(var e=[],r=0;t>r;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");for(var n=[\"array\"],i=[\"junk\"],r=0;t>r;++r){n.push(\"array\"),i.push(\"out\"+r+\"s\");var a=o(t);a[r]=-1,n.push({array:0,offset:a.slice()}),a[r]=1,n.push({array:0,offset:a.slice()}),i.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return l[t]=s({args:n,pre:c,post:c,body:{body:e.join(\"\"),args:i.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}function i(t){function e(e){for(var r=a-e.length,n=[],i=[],s=[],l=0;a>l;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),n.push(\"1\"),i.push(\"s[\"+l+\"]-2\"));var u=\".lo(\"+n.join()+\").hi(\"+i.join()+\")\";if(0===n.length&&(u=\"\"),r>0){o.push(\"if(1\");for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\"&&s[\",l,\"]>2\");o.push(\"){grad\",r,\"(src.pick(\",s.join(),\")\",u);for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\",dst.pick(\",s.join(),\",\",l,\")\",u);o.push(\");\")}for(var l=0;l<e.length;++l){var c=Math.abs(e[l])-1,f=\"dst.pick(\"+s.join()+\",\"+c+\")\"+u;switch(t[c]){case\"clamp\":var h=s.slice(),p=s.slice();e[l]<0?h[c]=\"s[\"+c+\"]-2\":p[c]=\"1\",0===r?o.push(\"if(s[\",c,\"]>1){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",h.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>1){diff(\",f,\",src.pick(\",h.join(),\")\",u,\",src.pick(\",p.join(),\")\",u,\");}else{zero(\",f,\");};\");break;case\"mirror\":0===r?o.push(\"dst.set(\",s.join(),\",\",c,\",0);\"):o.push(\"zero(\",f,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[c]=\"s[\"+c+\"]-2\",g[c]=\"0\"):(d[c]=\"s[\"+c+\"]-1\",g[c]=\"1\"),0===r?o.push(\"if(s[\",c,\"]>2){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>2){diff(\",f,\",src.pick(\",d.join(),\")\",u,\",src.pick(\",g.join(),\")\",u,\");}else{zero(\",f,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}r>0&&o.push(\"};\")}var r=t.join(),i=u[r];if(i)return i;for(var a=t.length,o=[\"function gradient(dst,src){var s=src.shape.slice();\"],s=0;1<<a>s;++s){for(var c=[],p=0;a>p;++p)s&1<<p&&c.push(p+1);for(var d=0;d<1<<c.length;++d){for(var g=c.slice(),p=0;p<c.length;++p)d&1<<p&&(g[p]=-g[p]);e(g)}}o.push(\"return dst;};return gradient\");for(var v=[\"diff\",\"zero\"],m=[f,h],s=1;a>=s;++s)v.push(\"grad\"+s),m.push(n(s));v.push(o.join(\"\"));var y=Function.apply(void 0,v),i=y.apply(void 0,m);return l[r]=i,i}function a(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=\"string\"==typeof r?o(e.dimension,r):o(e.dimension,\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var n=0;n<e.dimension;++n)if(t.shape[n]!==e.shape[n])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;var a=i(r);return a(t,e)}e.exports=a;var o=t(\"dup\"),s=t(\"cwise-compiler\"),l={},u={},c={body:\"\",args:[],thisVars:[],localVars:[]},f=s({args:[\"array\",\"array\",\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),h=s({args:[\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"})},{\"cwise-compiler\":316,dup:322}],413:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],a=t,o=1;a instanceof Array;)r.push(a.length),o*=a.length,a=a[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),i(e,t),e)}},{\"./doConvert.js\":414,ndarray:438}],414:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":316}],415:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,f,h,p,d){this.gl=t,this.shape=e,this.bounds=r,this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=f,this._contourVAO=h,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=p,this._dynamicVAO=d,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.dirty=!0}function o(t,e){for(var r=e.axes&&e.axes.lastCubeProps.axis||F,n=e.showSurface,i=e.showContour,a=0;3>a;++a){n=n||e.surfaceProject[a];for(var o=0;3>o;++o)i=i||e.contourProject[a][o]}for(var a=0;3>a;++a){for(var s=D.projections[a],o=0;16>o;++o)s[o]=0;for(var o=0;4>o;++o)s[5*o]=1;s[5*a]=0,s[12+a]=e.axesBounds[+(r[a]>0)][a],k(s,t.model,s);for(var l=D.clipBounds[a],u=0;2>u;++u)for(var o=0;3>o;++o)l[u][o]=t.clipBounds[u][o];l[0][a]=-1e8,l[1][a]=1e8}return D.showSurface=n,D.showContour=i,D}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||R,n.view=t.view||R,n.projection=t.projection||R,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;2>i;++i)for(var a=n.clipBounds[i],s=0;3>s;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.shape=n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V;var l=U;k(l,n.view,n.model),k(l,n.projection,l),A(l,l);for(var i=0;3>i;++i)n.eyePosition[i]=l[12+i]/l[15];for(var u=l[15],i=0;3>i;++i)u+=this.lightPosition[i]*l[4*i+3];for(var i=0;3>i;++i){for(var c=l[12+i],s=0;3>s;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var f=o(n,this);if(f.showSurface&&e===this.opacity<1){this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vao.draw(r.TRIANGLES,this._vertexCount);for(var i=0;3>i;++i)this.surfaceProject[i]&&(this._shader.uniforms.model=f.projections[i],this._shader.uniforms.clipBounds=f.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(f.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var p=this._contourVAO;p.bind();for(var i=0;3>i;++i){h.uniforms.permutation=I[i],r.lineWidth(this.contourWidth[i]);for(var s=0;s<this.contourLevels[i].length;++s)s===this.highlightLevel[i]?(h.uniforms.contourColor=this.highlightColor[i],h.uniforms.contourTint=this.highlightTint[i]):(0===s||s-1===this.highlightLevel[i])&&(h.uniforms.contourColor=this.contourColor[i],h.uniforms.contourTint=this.contourTint[i]),h.uniforms.height=this.contourLevels[i][s],p.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s])}for(var i=0;3>i;++i){h.uniforms.model=f.projections[i],h.uniforms.clipBounds=f.clipBounds[i];for(var s=0;3>s;++s)if(this.contourProject[i][s]){h.uniforms.permutation=I[s],r.lineWidth(this.contourWidth[s]);for(var d=0;d<this.contourLevels[s].length;++d)d===this.highlightLevel[s]?(h.uniforms.contourColor=this.highlightColor[s],h.uniforms.contourTint=this.highlightTint[s]):(0===d||d-1===this.highlightLevel[s])&&(h.uniforms.contourColor=this.contourColor[s],h.uniforms.contourTint=this.contourTint[s]),h.uniforms.height=this.contourLevels[s][d],p.draw(r.LINES,this._contourCounts[s][d],this._contourOffsets[s][d])}}p=this._dynamicVAO,p.bind();for(var i=0;3>i;++i)if(0!==this._dynamicCounts[i]){h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=I[i],r.lineWidth(this.dynamicWidth[i]),h.uniforms.contourColor=this.dynamicColor[i],h.uniforms.contourTint=this.dynamicTint[i],h.uniforms.height=this.dynamicLevel[i],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]);for(var s=0;3>s;++s)this.contourProject[s][i]&&(h.uniforms.model=f.projections[s],h.uniforms.clipBounds=f.clipBounds[s],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]))}p.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function f(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function h(t){var e=t.gl,r=(t.field||t.coords&&t.coords[2]||_([],[0,0]),L(e)),n=C(e),i=S(e),o=P(e),s=d(e),l=g(e,[{buffer:s,size:4,stride:z,offset:0},{buffer:s,size:2,stride:z,offset:16},{buffer:s,size:3,stride:z,offset:24}]),u=d(e),c=g(e,[{buffer:u,size:4}]),f=d(e),h=g(e,[{buffer:f,size:2,type:e.FLOAT}]),p=v(e,1,j,e.RGBA,e.UNSIGNED_BYTE);p.minFilter=e.LINEAR,p.magFilter=e.LINEAR;var m=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,p,i,o,u,c,f,h),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",m.update(y),m}e.exports=h;var p=t(\"bit-twiddle\"),d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),m=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),k=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),M=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),_=t(\"ndarray\"),E=t(\"./lib/shaders\"),L=E.createShader,S=E.createContourShader,C=E.createPickShader,P=E.createPickContourShader,z=36,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],I=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;3>t;++t){var e=I[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var j=265,N=a.prototype;N.isTransparent=function(){return this.opacity<1},N.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},N.pickSlots=1,N.setPickBase=function(t){this.pickId=t};var F=[0,0,0],D={showSurface:!1,showContour:!1,projections:[R.slice(),R.slice(),R.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:R,view:R,projection:R,inverseModel:R.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1},U=R.slice(),V=[1,0,0,0,1,0,0,0,1];N.draw=function(t){return s.call(this,t,!1)},N.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:R,view:R,projection:R,inverseModel:R,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};N.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||R,r.view=t.view||R,r.projection=t.projection||R,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;2>n;++n)for(var i=r.clipBounds[n],a=0;3>a;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount);for(var n=0;3>n;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;u.bind();for(var a=0;3>a;++a){e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=I[a];for(var n=0;n<this.contourLevels[a].length;++n)l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n])}for(var n=0;3>n;++n){l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n];for(var a=0;3>a;++a)if(this.contourProject[n][a]){l.uniforms.permutation=I[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c])}}u.unbind()}},N.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;2>c;++c)for(var f=c?a:1-a,h=0;2>h;++h)for(var p=h?l:1-l,d=i+c,g=s+h,v=f*p,m=0;3>m;++m)u[m]+=this._field[m].get(d,g)*v;for(var y=this._pickResult.level,b=0;3>b;++b)if(y[b]=M.le(this.contourLevels[b],u[b]),y[b]<0)this.contourLevels[b].length>0&&(y[b]=0);else if(y[b]<this.contourLevels[b].length-1){var x=this.contourLevels[b][y[b]],_=this.contourLevels[b][y[b]+1];Math.abs(x-u[b])>Math.abs(_-u[b])&&(y[b]+=1)}r.index[0]=.5>a?i:i+1,r.index[1]=.5>l?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1];for(var m=0;3>m;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},N.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=f(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=f(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\n",
+       "\"colorBounds\"in t&&(this.colorBounds=t.colorBounds);var e=t.field||t.coords&&t.coords[2]||null;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var r=(e.shape[0]+2)*(e.shape[1]+2);r>this._field[2].data.length&&(m.freeFloat(this._field[2].data),this._field[2].data=m.mallocFloat(p.nextPow2(r))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var n=this.shape,a=0;2>a;++a)this._field[2].size>this._field[a].data.length&&(m.freeFloat(this._field[a].data),this._field[a].data=m.mallocFloat(this._field[2].size)),this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2]);if(t.coords){var o=t.coords;if(!Array.isArray(o)||3!==o.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(var a=0;2>a;++a){for(var s=o[a],c=0;2>c;++c)if(s.shape[c]!==n[c])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[a],s)}}else if(t.ticks){var h=t.ticks;if(!Array.isArray(h)||2!==h.length)throw new Error(\"gl-surface: invalid ticks\");for(var a=0;2>a;++a){var d=h[a];if((Array.isArray(d)||d.length)&&(d=_(d)),d.shape[0]!==n[a])throw new Error(\"gl-surface: invalid tick length\");var g=_(d.data,n);g.stride[a]=d.stride[0],g.stride[1^a]=0,l(this._field[a],g)}}else{for(var a=0;2>a;++a){var v=[0,0];v[a]=1,this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2],v,0)}this._field[0].set(0,0,0);for(var c=0;c<n[0];++c)this._field[0].set(c+1,0,c);this._field[0].set(n[0]+1,0,n[0]-1),this._field[1].set(0,0,0);for(var c=0;c<n[1];++c)this._field[1].set(0,c+1,c);this._field[1].set(0,n[1]+1,n[1]-1)}for(var y=this._field,b=(y[2].size,_(m.mallocFloat(3*y[2].size*2),[3,n[0]+2,n[1]+2,2])),a=0;3>a;++a)T(b.pick(a),y[a],\"mirror\");for(var x=_(m.mallocFloat(3*y[2].size),[n[0]+2,n[1]+2,3]),a=0;a<n[0]+2;++a)for(var c=0;c<n[1]+2;++c){var k=b.get(0,a,c,0),A=b.get(0,a,c,1),M=b.get(1,a,c,0),E=b.get(1,a,c,1),L=b.get(2,a,c,0),S=b.get(2,a,c,1),C=M*S-E*L,P=L*A-S*k,z=k*E-A*M,R=Math.sqrt(C*C+P*P+z*z);1e-8>R?(R=Math.max(Math.abs(C),Math.abs(P),Math.abs(z)),1e-8>R?(z=1,P=C=0,R=1):R=1/R):R=1/Math.sqrt(R),x.set(a,c,0,C*R),x.set(a,c,1,P*R),x.set(a,c,2,z*R)}m.free(b.data);for(var I=[1/0,1/0,1/0],j=[-(1/0),-(1/0),-(1/0)],N=(n[0]-1)*(n[1]-1)*6,F=m.mallocFloat(p.nextPow2(9*N)),D=0,B=0,a=0;a<n[0]-1;++a)t:for(var c=0;c<n[1]-1;++c){for(var U=0;2>U;++U)for(var V=0;2>V;++V)for(var q=0;3>q;++q){var H=this._field[q].get(1+a+U,1+c+V);if(isNaN(H)||!isFinite(H))continue t}for(var q=0;6>q;++q){var G=a+O[q][0],Y=c+O[q][1],X=this._field[0].get(G+1,Y+1),W=this._field[1].get(G+1,Y+1),H=this._field[2].get(G+1,Y+1),C=x.get(G+1,Y+1,0),P=x.get(G+1,Y+1,1),z=x.get(G+1,Y+1,2);F[D++]=G,F[D++]=Y,F[D++]=X,F[D++]=W,F[D++]=H,F[D++]=0,F[D++]=C,F[D++]=P,F[D++]=z,I[0]=Math.min(I[0],X),I[1]=Math.min(I[1],W),I[2]=Math.min(I[2],H),j[0]=Math.max(j[0],X),j[1]=Math.max(j[1],W),j[2]=Math.max(j[2],H),B+=1}}this._vertexCount=B,this._coordinateBuffer.update(F.subarray(0,D)),m.freeFloat(F),m.free(x.data),this.bounds=[I,j]}var Z=!1;if(\"levels\"in t){var $=t.levels;$=Array.isArray($[0])?$.slice():[[],[],$];for(var a=0;3>a;++a)$[a]=$[a].slice(),$.sort(function(t,e){return t-e});t:for(var a=0;3>a;++a){if($[a].length!==this.contourLevels[a].length){Z=!0;break}for(var c=0;c<$[a].length;++c)if($[a][c]!==this.contourLevels[a][c]){Z=!0;break t}}this.contourLevels=$}if(Z){for(var y=this._field,n=this.shape,K=[],Q=0;3>Q;++Q){for(var $=this.contourLevels[Q],J=[],tt=[],et=[0,0],a=0;a<$.length;++a){var rt=w(this._field[Q],$[a]);J.push(K.length/4|0);var B=0;t:for(var c=0;c<rt.cells.length;++c)for(var nt=rt.cells[c],q=0;2>q;++q){var it=rt.positions[nt[q]],at=it[0],ot=0|Math.floor(at),st=at-ot,lt=it[1],ut=0|Math.floor(lt),ct=lt-ut,ft=!1;e:for(var ht=0;2>ht;++ht){et[ht]=0;for(var pt=(Q+ht+1)%3,U=0;2>U;++U)for(var dt=U?st:1-st,G=0|Math.min(Math.max(ot+U,0),n[0]),V=0;2>V;++V){var gt=V?ct:1-ct,Y=0|Math.min(Math.max(ut+V,0),n[1]),H=this._field[pt].get(G,Y);if(!isFinite(H)||isNaN(H)){ft=!0;break e}var vt=dt*gt;et[ht]+=vt*H}}if(ft){if(q>0){for(var mt=0;4>mt;++mt)K.pop();B-=1}continue t}K.push(et[0],et[1],it[0],it[1]),B+=1}tt.push(B)}this._contourOffsets[Q]=J,this._contourCounts[Q]=tt}for(var yt=m.mallocFloat(K.length),a=0;a<K.length;++a)yt[a]=K[a];this._contourBuffer.update(yt),m.freeFloat(yt)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},N.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;3>t;++t)m.freeFloat(this._field[t].data)},N.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;3>e;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=m.mallocFloat(12*i[0]*i[1]),o=0;3>o;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],f=this._field[l],h=w(u,r[o]),p=h.cells,d=h.positions;this._dynamicOffsets[o]=n;for(var e=0;e<p.length;++e)for(var g=p[e],v=0;2>v;++v){var y=d[g[v]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),k=b-x,A=1-k,M=+y[1],T=0|M,E=0|Math.min(T+1,i[1]),L=M-T,S=1-L,C=A*S,P=A*L,z=k*S,R=k*L,O=C*c.get(x,T)+P*c.get(x,E)+z*c.get(_,T)+R*c.get(_,E),I=C*f.get(x,T)+P*f.get(x,E)+z*f.get(_,T)+R*f.get(_,E);if(isNaN(O)||isNaN(I)){v&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=I,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),m.freeFloat(a)}}},{\"./lib/shaders\":410,\"binary-search-bounds\":411,\"bit-twiddle\":299,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,\"ndarray-gradient\":412,\"ndarray-ops\":437,\"ndarray-pack\":413,\"surface-nets\":457,\"typedarray-pool\":463}],416:[function(t,e,r){arguments[4][179][0].apply(r,arguments)},{dup:179,ndarray:438,\"ndarray-ops\":437,\"typedarray-pool\":463}],417:[function(t,e,r){arguments[4][42][0].apply(r,arguments)},{dup:42}],418:[function(t,e,r){arguments[4][43][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:43}],419:[function(t,e,r){arguments[4][44][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:44}],420:[function(t,e,r){arguments[4][45][0].apply(r,arguments)},{\"./lib/vao-emulated.js\":418,\"./lib/vao-native.js\":419,dup:45}],421:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;t>=r;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var n=0;t>=n;++n)this.tuple[n]=this.vertices[n];var i=f[t];i||(i=f[t]=o(t)),this.orient=i}function l(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(i>=r)throw new Error(\"Must input at least d+1 points\");var a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),c=0;i>=c;++c)l[c]=c;0>o&&(l[0]=1,l[1]=0);for(var f=new n(l,new Array(i+1),!1),h=f.adjacent,p=new Array(i+2),c=0;i>=c;++c){for(var d=l.slice(),g=0;i>=g;++g)g===c&&(d[g]=-1);var v=d[0];d[0]=d[1],d[1]=v;var m=new n(d,new Array(i+1),!0);h[c]=m,p[c]=m}p[i+1]=f;for(var c=0;i>=c;++c)for(var d=h[c].vertices,y=h[c].adjacent,g=0;i>=g;++g){var b=d[g];if(0>b)y[g]=f;else for(var x=0;i>=x;++x)h[x].vertices.indexOf(b)<0&&(y[g]=h[x])}for(var _=new s(i,a,p),w=!!e,c=i+1;r>c;++c)_.insert(t[c],w);return _.boundary()}e.exports=l;var u=t(\"robust-orientation\"),c=t(\"simplicial-complex\").compareCells;n.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var f=[],h=s.prototype;h.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,i=this.tuple,a=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){t=o.pop();for(var s=(t.vertices,t.adjacent),l=0;r>=l;++l){var u=s[l];if(u.boundary&&!(u.lastVisited<=-n)){for(var c=u.vertices,f=0;r>=f;++f){var h=c[f];0>h?i[f]=e:i[f]=a[h]}var p=this.orient();if(p>0)return u;u.lastVisited=-n,0===p&&o.push(u)}}}return null},h.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,a=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,u=s.adjacent,c=0;n>=c;++c)a[c]=i[l[c]];s.lastVisited=r;for(var c=0;n>=c;++c){var f=u[c];if(!(f.lastVisited>=r)){var h=a[c];a[c]=t;var p=this.orient();if(a[c]=h,0>p){s=f;continue t}f.boundary?f.lastVisited=-r:f.lastVisited=r}}return}return s},h.addPeaks=function(t,e){var r=this.vertices.length-1,o=this.dimension,s=this.vertices,l=this.tuple,u=this.interior,c=this.simplices,f=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,u.push(e);for(var h=[];f.length>0;){var e=f.pop(),p=e.vertices,d=e.adjacent,g=p.indexOf(r);if(!(0>g))for(var v=0;o>=v;++v)if(v!==g){var m=d[v];if(m.boundary&&!(m.lastVisited>=r)){var y=m.vertices;if(m.lastVisited!==-r){for(var b=0,x=0;o>=x;++x)y[x]<0?(b=x,l[x]=t):l[x]=s[y[x]];var _=this.orient();if(_>0){y[b]=r,m.boundary=!1,u.push(m),f.push(m),m.lastVisited=r;continue}m.lastVisited=-r}var w=m.adjacent,k=p.slice(),A=d.slice(),M=new n(k,A,!0);c.push(M);var T=w.indexOf(e);if(!(0>T)){w[T]=M,A[g]=m,k[v]=-1,A[v]=e,d[v]=M,M.flip();for(var x=0;o>=x;++x){var E=k[x];if(!(0>E||E===r)){for(var L=new Array(o-1),S=0,C=0;o>=C;++C){var P=k[C];0>P||C===x||(L[S++]=P)}h.push(new i(L,M,x))}}}}}}h.sort(a);for(var v=0;v+1<h.length;v+=2){var z=h[v],R=h[v+1],O=z.index,I=R.index;0>O||0>I||(z.cell.adjacent[z.index]=R.cell,R.cell.adjacent[R.index]=z.cell)}},h.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var i=this.dimension,a=this.tuple,o=0;i>=o;++o){var s=n.vertices[o];0>s?a[o]=t:a[o]=r[s]}var l=this.orient(a);0>l||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},h.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,i=0;n>i;++i){var a=r[i];if(a.boundary){for(var o=new Array(t),s=a.vertices,l=0,u=0,c=0;t>=c;++c)s[c]>=0?o[l++]=s[c]:u=1&c;if(u===(1&t)){var f=o[0];o[0]=o[1],o[1]=f}e.push(o)}}return e}},{\"robust-orientation\":444,\"simplicial-complex\":424}],422:[function(t,e,r){arguments[4][39][0].apply(r,arguments)},{dup:39}],423:[function(t,e,r){arguments[4][130][0].apply(r,arguments)},{dup:130}],424:[function(t,e,r){arguments[4][151][0].apply(r,arguments)},{\"bit-twiddle\":422,dup:151,\"union-find\":423}],425:[function(t,e,r){arguments[4][248][0].apply(r,arguments)},{dup:248}],426:[function(t,e,r){arguments[4][245][0].apply(r,arguments)},{dup:245,\"mouse-event\":427}],427:[function(t,e,r){arguments[4][246][0].apply(r,arguments)},{dup:246}],428:[function(t,e,r){arguments[4][29][0].apply(r,arguments)},{dup:29}],429:[function(t,e,r){arguments[4][30][0].apply(r,arguments)},{dup:30,\"parse-unit\":428}],430:[function(t,e,r){arguments[4][31][0].apply(r,arguments)},{dup:31,\"to-px\":429}],431:[function(t,e,r){\"use strict\";var n=t(\"cwise/lib/wrapper\")({args:[\"index\",\"array\",\"scalar\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{_inline_1_arg1_=_inline_1_arg2_.apply(void 0,_inline_1_arg0_)}\",args:[{name:\"_inline_1_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg1_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:1}],thisVars:[],localVars:[]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});e.exports=function(t,e){return n(t,e),t}},{\"cwise/lib/wrapper\":319}],432:[function(t,e,r){\"use strict\";function n(t,e){switch(e.length){case 0:break;case 1:t[0]=1/e[0];break;case 4:i(t,e);break;case 9:a(t,e);break;case 16:o(t,e);break;default:throw new Error(\"currently supports matrices up to 4x4\")}return t}e.exports=n;var i=t(\"gl-mat2/invert\"),a=t(\"gl-mat3/invert\"),o=t(\"gl-mat4/invert\")},{\"gl-mat2/invert\":433,\"gl-mat3/invert\":337,\"gl-mat4/invert\":344}],433:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],434:[function(t,e,r){\"use strict\";function n(t,e){var r=Math.floor(e),n=e-r,i=r>=0&&r<t.shape[0],a=r+1>=0&&r+1<t.shape[0],o=i?+t.get(r):0,s=a?+t.get(r+1):0;return(1-n)*o+n*s}function i(t,e,r){var n=Math.floor(e),i=e-n,a=n>=0&&n<t.shape[0],o=n+1>=0&&n+1<t.shape[0],s=Math.floor(r),l=r-s,u=s>=0&&s<t.shape[1],c=s+1>=0&&s+1<t.shape[1],f=a&&u?t.get(n,s):0,h=a&&c?t.get(n,s+1):0,p=o&&u?t.get(n+1,s):0,d=o&&c?t.get(n+1,s+1):0;return(1-l)*((1-i)*f+i*p)+l*((1-i)*h+i*d)}function a(t,e,r,n){var 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c=e[0].label,f=a.slice(),h=f.indexOf(c);-1===h?f.push(c):f.splice(h,1),o.relayout(t,\"hiddenlabels\",f)}else{if(\"\"===l)u=[s.index];else for(var p=0;p<i.length;p++)r=i[p],r.legendgroup===l&&u.push(r.index);n=s.visible===!0?\"legendonly\":!0,o.restyle(t,\"visible\",n,u)}}})}),c.repositionLegend(t,h),t._context.editable){var p,d,g,v,m,y;o.Fx.dragElement({element:l.node(),prepFn:function(){g=Number(l.attr(\"x\")),v=Number(l.attr(\"y\")),m=Number(l.attr(\"width\")),y=Number(l.attr(\"height\")),o.Fx.setCursor(l)},moveFn:function(e,n){var i=t._fullLayout._size;l.call(o.Drawing.setPosition,g+e,v+n),p=o.Fx.dragAlign(g+e,m,i.l,i.l+i.w,r.xanchor),d=o.Fx.dragAlign(v+n+y,-y,i.t+i.h,i.t,r.yanchor);var a=o.Fx.dragCursors(p,d,r.xanchor,r.yanchor);o.Fx.setCursor(l,a)},doneFn:function(e){o.Fx.setCursor(l),e&&void 0!==p&&void 0!==d&&o.relayout(t,{\"legend.x\":p,\"legend.y\":d})}})}}},c.repositionLegend=function(t,e){var r=t._fullLayout,n=r._size,a=r.legend,l=a.borderwidth,u=0,c=0;e.each(function(t){var 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d=\"top\";\"bottom\"===a.yanchor||\"auto\"===a.yanchor&&a.y<=1/3?(h-=c,d=\"bottom\"):(\"middle\"===a.yanchor||\"auto\"===a.yanchor&&a.y<2/3)&&(h-=c/2,d=\"middle\"),u=Math.ceil(u),c=Math.ceil(c),f=Math.round(f),h=Math.round(h),r._infolayer.selectAll(\"svg.legend\").call(o.Drawing.setRect,f,h,u,c),r._infolayer.selectAll(\"svg.legend .bg\").call(o.Drawing.setRect,l/2,l/2,u-l,c-l),o.Plots.autoMargin(t,\"legend\",{x:a.x,y:a.y,l:u*({right:1,center:.5}[p]||0),r:u*({left:1,center:.5}[p]||0),b:c*({top:1,middle:.5}[d]||0),t:c*({bottom:1,middle:.5}[d]||0)})}},{\"../../plotly\":595,\"../../traces/pie/style_one\":729,\"../../traces/scatter/subtypes\":749,\"./attributes\":554,d3:320}],556:[function(t,e,r){\"use strict\";function n(t,e){var r=e.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=t._fullLayout,o={};if(\"zoom\"===n)for(var 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r&&(\"setBackground\"===t&&\"opaque\"===e[t]?r[t]=i:r[t]=e[t])}),e.plot3dPixelRatio&&!r.plotGlPixelRatio&&(r.plotGlPixelRatio=r.plot3dPixelRatio)),r.staticPlot&&(r.editable=!1,r.autosizable=!1,r.scrollZoom=!1,r.doubleClick=!1,r.showTips=!1,r.showLink=!1,r.displayModeBar=!1)}function o(t,e,r){var n=L.select(t).selectAll(\".plot-container\").data([0]);n.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=n.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),P.micropolar.manager.fillLayout(t),\"initial\"===t._fullLayout.autosize&&t._context.autosizable&&(w(t,{}),t._fullLayout.autosize=r.autosize=!0),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=P.micropolar.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var a=t.framework.svg(),o=1,s=t._fullLayout.title;\"\"!==s&&s||(o=0);var l=\"Click to enter title\",u=function(){this.call(P.util.convertToTspans)},c=a.select(\".title-group text\").call(u);if(t._context.editable){c.attr({\"data-unformatted\":s}),s&&s!==l||(o=.2,c.attr({\"data-unformatted\":l}).text(l).style({opacity:o}).on(\"mouseover.opacity\",function(){L.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){L.select(this).transition().duration(1e3).style(\"opacity\",0)}));var f=function(){this.call(P.util.makeEditable).on(\"edit\",function(e){t.framework({layout:{title:e}}),this.attr({\"data-unformatted\":e}).text(e).call(u),this.call(f)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};c.call(f)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),I.addLinks(t),Promise.resolve()}function s(t){var e,r;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1);var n=P.Axes.list({_fullLayout:t});for(e=0;e<n.length;e++){var i=n[e];i.anchor&&\"free\"!==i.anchor&&(i.anchor=P.Axes.cleanId(i.anchor)),i.overlaying&&(i.overlaying=P.Axes.cleanId(i.overlaying)),i.type||(i.isdate?i.type=\"date\":i.islog?i.type=\"log\":i.isdate===!1&&i.islog===!1&&(i.type=\"linear\")),(\"withzero\"===i.autorange||\"tozero\"===i.autorange)&&(i.autorange=!0,i.rangemode=\"tozero\"),delete i.islog,delete i.isdate,delete i.categories,f(i,\"domain\")&&delete i.domain,void 0!==i.autotick&&(void 0===i.tickmode&&(i.tickmode=i.autotick?\"auto\":\"linear\"),delete i.autotick)}void 0===t.annotations||Array.isArray(t.annotations)||(console.log(\"annotations must be an array\"),delete t.annotations);var a=(t.annotations||[]).length;for(e=0;a>e;e++){var o=t.annotations[e];o.ref&&(\"paper\"===o.ref?(o.xref=\"paper\",o.yref=\"paper\"):\"data\"===o.ref&&(o.xref=\"x\",o.yref=\"y\"),delete o.ref),l(o,\"xref\"),l(o,\"yref\")}void 0===t.shapes||Array.isArray(t.shapes)||(console.log(\"shapes must be an array\"),delete t.shapes);var s=(t.shapes||[]).length;for(e=0;s>e;e++){var u=t.shapes[e];l(u,\"xref\"),l(u,\"yref\")}var c=t.legend;c&&(c.x>3?(c.x=1.02,c.xanchor=\"left\"):c.x<-2&&(c.x=-.02,c.xanchor=\"right\"),c.y>3?(c.y=1.02,c.yanchor=\"bottom\"):c.y<-2&&(c.y=-.02,c.yanchor=\"top\")),\"rotate\"===t.dragmode&&(t.dragmode=\"orbit\"),t.scene1&&(t.scene||(t.scene=t.scene1),delete t.scene1);var h,p,d,g,v,m,y,b=I.getSubplotIds(t,\"gl3d\");for(e=0;e<b.length;e++)if(h=t[b[e]],p=h.cameraposition,Array.isArray(p)&&4===p[0].length){for(d=p[0],v=p[1],g=p[2],m=S([],d),y=[],r=0;3>r;++r)y[r]=v[e]+g*m[2+4*r];h.camera={eye:{x:y[0],y:y[1],z:y[2]},center:{x:v[0],y:v[1],z:v[2]},up:{x:m[1],y:m[5],z:m[9]}},delete h.cameraposition}return z.markTime(\"finished rest of cleanLayout, starting color\"),N.clean(t),z.markTime(\"finished cleanLayout color.clean\"),t}function l(t,e){var r=t[e],n=e.charAt(0);r&&\"paper\"!==r&&(t[e]=P.Axes.cleanId(r,n))}function u(t,e){for(var r=[],n=(t.concat(Array.isArray(e)?e:[]).filter(function(t){return\"uid\"in t}).map(function(t){return t.uid})),i=0;i<t.length;i++){var a=t[i];if(!(\"uid\"in a)||-1!==r.indexOf(a.uid)){var o,s;for(s=0;100>s&&(o=z.randstr(n),-1!==r.indexOf(o));s++);a.uid=z.randstr(n),n.push(a.uid)}if(r.push(a.uid),\"histogramy\"===a.type&&\"xbins\"in a&&!(\"ybins\"in a)&&(a.ybins=a.xbins,delete a.xbins),a.error_y&&\"opacity\"in a.error_y){var l=N.defaults,u=a.error_y.color||(I.traceIs(a,\"bar\")?N.defaultLine:l[i%l.length]);a.error_y.color=N.addOpacity(N.rgb(u),N.opacity(u)*a.error_y.opacity),delete a.error_y.opacity}\"bardir\"in a&&(\"h\"!==a.bardir||!I.traceIs(a,\"bar\")&&\"histogram\"!==a.type.substr(0,9)||(a.orientation=\"h\",x(a)),delete a.bardir),\"histogramy\"===a.type&&x(a),(\"histogramx\"===a.type||\"histogramy\"===a.type)&&(a.type=\"histogram\"),\"scl\"in a&&(a.colorscale=a.scl,delete a.scl),\"reversescl\"in a&&(a.reversescale=a.reversescl,delete a.reversescl),a.xaxis&&(a.xaxis=P.Axes.cleanId(a.xaxis,\"x\")),a.yaxis&&(a.yaxis=P.Axes.cleanId(a.yaxis,\"y\")),I.traceIs(a,\"gl3d\")&&a.scene&&(a.scene=I.subplotsRegistry.gl3d.cleanId(a.scene)),I.traceIs(a,\"pie\")||(Array.isArray(a.textposition)?a.textposition=a.textposition.map(c):a.textposition&&(a.textposition=c(a.textposition))),f(a,\"line\")&&delete a.line,\"marker\"in a&&(f(a.marker,\"line\")&&delete a.marker.line,f(a,\"marker\")&&delete a.marker),z.markTime(\"finished rest of cleanData, starting color\"),N.clean(a),z.markTime(\"finished cleanData color.clean\")}}function c(t){var e=\"middle\",r=\"center\";return-1!==t.indexOf(\"top\")?e=\"top\":-1!==t.indexOf(\"bottom\")&&(e=\"bottom\"),-1!==t.indexOf(\"left\")?r=\"left\":-1!==t.indexOf(\"right\")&&(r=\"right\"),e+\" \"+r}function f(t,e){return e in t&&\"object\"==typeof t[e]&&0===Object.keys(t[e]).length}function h(t){var e,r,n,i,a=P.Axes.list(t),o=t._fullData,s=t._fullLayout,l=t.calcdata=new Array(o.length);for(t.firstscatter=!0,t.numboxes=0,t._hmpixcount=0,t._hmlumcount=0,s._piecolormap={},s._piedefaultcolorcount=0,e=0;e<a.length;e++)a[e]._categories=[];for(e=0;e<o.length;e++)r=o[e],n=r._module,i=[],n&&r.visible===!0&&n.calc&&(i=n.calc(t,r)),Array.isArray(i)&&i[0]||(i=[{x:!1,y:!1}]),i[0].t||(i[0].t={}),i[0].trace=r,z.markTime(\"done with calcdata for \"+e),l[e]=i}function p(t,e){var r,n,i=e+1,a=[];for(r=0;r<t.length;r++)n=t[r],0>n?a.push(i+n):a.push(n);return a}function d(t,e,r){var n,i;for(n=0;n<e.length;n++){if(i=e[n],i!==parseInt(i,10))throw new Error(\"all values in \"+r+\" must be integers\");if(i>=t.data.length||i<-t.data.length)throw new Error(r+\" must be valid indices for gd.data.\");if(e.indexOf(i,n+1)>-1||i>=0&&e.indexOf(-t.data.length+i)>-1||0>i&&e.indexOf(t.data.length+i)>-1)throw new Error(\"each index in \"+r+\" must be unique.\")}}function g(t,e,r){if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"currentIndices is a required argument.\");if(Array.isArray(e)||(e=[e]),d(t,e,\"currentIndices\"),\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&d(t,r,\"newIndices\"),\"undefined\"!=typeof r&&e.length!==r.length)throw new Error(\"current and new indices must be of equal length.\")}function v(t,e,r){var n,i;if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array.\");if(\"undefined\"==typeof e)throw new Error(\"traces must be defined.\");for(Array.isArray(e)||(e=[e]),n=0;n<e.length;n++)if(i=e[n],\"object\"!=typeof i||Array.isArray(i)||null===i)throw new Error(\"all values in traces array must be non-array objects\");if(\"undefined\"==typeof r||Array.isArray(r)||(r=[r]),\"undefined\"!=typeof r&&r.length!==e.length)throw new Error(\"if indices is specified, traces.length must equal indices.length\")}function m(t,e,r,n){var i=z.isPlainObject(n);if(!Array.isArray(t.data))throw new Error(\"gd.data must be an array\");if(!z.isPlainObject(e))throw new Error(\"update must be a key:value object\");if(\"undefined\"==typeof r)throw new Error(\"indices must be an integer or array of integers\");d(t,r,\"indices\");for(var a in e){if(!Array.isArray(e[a])||e[a].length!==r.length)throw new Error(\"attribute \"+a+\" must be an array of length equal to indices array length\");if(i&&(!(a in n)||!Array.isArray(n[a])||n[a].length!==e[a].length))throw new Error(\"when maxPoints is set as a key:value object it must contain a 1:1 corrispondence with the keys and number of traces in the update object\")}}function y(t,e,r,n){var i,a,o,s,l,u=z.isPlainObject(n),c=[];Array.isArray(r)||(r=[r]),r=p(r,t.data.length-1);for(var f in e)for(var h=0;h<r.length;h++){if(i=t.data[r[h]],o=z.nestedProperty(i,f),a=o.get(),s=e[f][h],!Array.isArray(s))throw new Error(\"attribute: \"+f+\" index: \"+h+\" must be an 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i=t.hoverinfo.split(\"+\");for(e=0;e<i.length;e++)\"x\"===i[e]?i[e]=\"y\":\"y\"===i[e]&&(i[e]=\"x\");t.hoverinfo=i.join(\"+\")}}function _(t){var e,r={left:0,right:0,bottom:0,top:0};if(t)for(e in t)t.hasOwnProperty(e)&&(r.left+=t[e].left||0,r.right+=t[e].right||0,r.bottom+=t[e].bottom||0,r.top+=t[e].top||0);return r}function w(t,e){var r,n,i,a=t._fullLayout,o=t._context;if(t.emit(\"plotly_autosize\"),t._context.fillFrame)i=window.innerWidth,n=window.innerHeight,document.body.style.overflow=\"hidden\";else if(C(o.frameMargins)&&o.frameMargins>0){var s=_(t._boundingBoxMargins),l=s.left+s.right,u=s.bottom+s.top,c=a._container.node().getBoundingClientRect(),f=1-2*o.frameMargins;i=Math.round(f*(c.width-l)),n=Math.round(f*(c.height-u))}else r=window.getComputedStyle(t),n=parseFloat(r.height)||a.height,i=parseFloat(r.width)||a.width;return Math.abs(a.width-i)>1||Math.abs(a.height-n)>1?(a.height=t.layout.height=n,a.width=t.layout.width=i):\"initial\"!==a.autosize&&(delete e.autosize,a.autosize=t.layout.autosize=!0),I.sanitizeMargins(a),e}function k(t){var e=L.select(t),r=t._fullLayout;if(r._hasGL3D&&I.subplotsRegistry.gl3d.initAxes(t),r._container=e.selectAll(\".plot-container\").data([0]),r._container.enter().insert(\"div\",\":first-child\").classed(\"plot-container\",!0).classed(\"plotly\",!0),r._paperdiv=r._container.selectAll(\".svg-container\").data([0]),r._paperdiv.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),\"initial\"===r.autosize&&(w(t,{}),r.autosize=!0,t.layout.autosize=!0),r._glcontainer=r._paperdiv.selectAll(\".gl-container\").data([0]),r._glcontainer.enter().append(\"div\").classed(\"gl-container\",!0),r._geocontainer=r._paperdiv.selectAll(\".geo-container\").data([0]),r._geocontainer.enter().append(\"div\").classed(\"geo-container\",!0),r._paperdiv.selectAll(\".main-svg\").remove(),r._paper=r._paperdiv.insert(\"svg\",\":first-child\").classed(\"main-svg\",!0),r._toppaper=r._paperdiv.append(\"svg\").classed(\"main-svg\",!0),!r._uid){var n=[];L.selectAll(\"defs\").each(function(){this.id&&n.push(this.id.split(\"-\")[1]);\n",
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n,i,a=t._fullLayout._plots={},o=0;o<e.length;o++)n=e[o],i=a[n]={},i.id=n,i.x=r(n,\"x\"),i.y=r(n,\"y\"),i.xaxis=i.x(),i.yaxis=i.y()}function M(t,e){function r(t){t.append(\"g\").classed(\"imagelayer\",!0),t.append(\"g\").classed(\"maplayer\",!0),t.append(\"g\").classed(\"barlayer\",!0),t.append(\"g\").classed(\"errorlayer\",!0),t.append(\"g\").classed(\"boxlayer\",!0),t.append(\"g\").classed(\"scatterlayer\",!0)}var n=t._fullLayout,i=[];n._paper.selectAll(\"g.subplot\").data(e).enter().append(\"g\").classed(\"subplot\",!0).each(function(a){var o=n._plots[a],s=o.plotgroup=L.select(this).classed(a,!0),l=o.xaxis,u=o.yaxis;o.overlays=[];var c=P.Axes.getFromId(t,l.overlaying)||l;c!==l&&c.overlaying&&(c=l,l.overlaying=!1);var f=P.Axes.getFromId(t,u.overlaying)||u;f!==u&&f.overlaying&&(f=u,u.overlaying=!1);var h=c._id+f._id;h!==a&&-1!==e.indexOf(h)?(o.mainplot=h,i.push(o),l.domain=c.domain.slice(),u.domain=f.domain.slice()):(o.bg=s.append(\"rect\").style(\"stroke-width\",0),o.gridlayer=s.append(\"g\"),o.overgrid=s.append(\"g\"),o.zerolinelayer=s.append(\"g\"),o.overzero=s.append(\"g\"),o.plot=s.append(\"svg\").call(r),o.overplot=s.append(\"g\"),o.xlines=s.append(\"path\"),o.ylines=s.append(\"path\"),o.overlines=s.append(\"g\"),o.xaxislayer=s.append(\"g\"),o.yaxislayer=s.append(\"g\"),o.overaxes=s.append(\"g\")),o.draglayer=n._draggers.append(\"g\")}),i.forEach(function(t){var e=n._plots[t.mainplot];e.overlays.push(t),t.gridlayer=e.overgrid.append(\"g\"),t.zerolinelayer=e.overzero.append(\"g\"),t.plot=e.overplot.append(\"svg\").call(r),t.xlines=e.overlines.append(\"path\"),t.ylines=e.overlines.append(\"path\"),t.xaxislayer=e.overaxes.append(\"g\"),t.yaxislayer=e.overaxes.append(\"g\")}),e.forEach(function(t){var 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s=t.trace.hoverinfo;return\"all\"!==s&&(s=s.split(\"+\"),-1===s.indexOf(\"x\")&&(t.xLabel=void 0),-1===s.indexOf(\"y\")&&(t.yLabel=void 0),-1===s.indexOf(\"z\")&&(t.zLabel=void 0),-1===s.indexOf(\"text\")&&(t.text=void 0),-1===s.indexOf(\"name\")&&(t.name=void 0)),t}function l(t,e){var r,n,i=e.hovermode,a=e.rotateLabels,o=e.bgColor,s=e.container,l=e.outerContainer,u=t[0],c=u.xa,f=u.ya,h=\"y\"===i?\"yLabel\":\"xLabel\",p=u[h],d=(String(p)||\"\").split(\" \")[0],g=l.node().getBoundingClientRect(),v=g.top,m=g.width,y=g.height,b=u.distance<=T.MAXDIST&&(\"x\"===i||\"y\"===i);for(r=0;r<t.length;r++){n=t[r].trace.hoverinfo;var w=n.split(\"+\");if(-1===w.indexOf(\"all\")&&-1===w.indexOf(i)){b=!1;break}}var A=s.selectAll(\"g.axistext\").data(b?[0]:[]);A.enter().append(\"g\").classed(\"axistext\",!0),A.exit().remove(),A.each(function(){var e=x.select(this),r=e.selectAll(\"path\").data([0]),n=e.selectAll(\"text\").data([0]);r.enter().append(\"path\").style({fill:k.Color.defaultLine,\"stroke-width\":\"1px\",stroke:k.Color.background}),n.enter().append(\"text\").call(k.Drawing.font,j,I,k.Color.background).attr(\"data-notex\",1),n.text(p).call(k.util.convertToTspans).call(k.Drawing.setPosition,0,0).selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),e.attr(\"transform\",\"\");var a=n.node().getBoundingClientRect();if(\"x\"===i){n.attr(\"text-anchor\",\"middle\").call(k.Drawing.setPosition,0,\"top\"===c.side?v-a.bottom-R-O:v-a.top+R+O).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var o=\"top\"===c.side?\"-\":\"\";r.attr(\"d\",\"M0,0L\"+R+\",\"+o+R+\"H\"+(O+a.width/2)+\"v\"+o+(2*O+a.height)+\"H-\"+(O+a.width/2)+\"V\"+o+R+\"H-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(u.x0+u.x1)/2)+\",\"+(f._offset+(\"top\"===c.side?0:f._length))+\")\")}else{n.attr(\"text-anchor\",\"right\"===f.side?\"start\":\"end\").call(k.Drawing.setPosition,(\"right\"===f.side?1:-1)*(O+R),v-a.top-a.height/2).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var s=\"right\"===f.side?\"\":\"-\";r.attr(\"d\",\"M0,0L\"+s+R+\",\"+R+\"V\"+(O+a.height/2)+\"h\"+s+(2*O+a.width)+\"V-\"+(O+a.height/2)+\"H\"+s+R+\"V-\"+R+\"Z\"),e.attr(\"transform\",\"translate(\"+(c._offset+(\"right\"===f.side?c._length:0))+\",\"+(f._offset+(u.y0+u.y1)/2)+\")\")}t=t.filter(function(t){return void 0!==t.zLabelVal||(t[h]||\"\").split(\" \")[0]===d})});var M=s.selectAll(\"g.hovertext\").data(t,function(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr||\"\"].join(\",\")});return M.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var t=x.select(this);t.append(\"rect\").call(k.Color.fill,k.Color.addOpacity(o,.8)),t.append(\"text\").classed(\"name\",!0).call(k.Drawing.font,j,I),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(k.Drawing.font,j,I)}),M.exit().remove(),M.each(function(t){var e=x.select(this).attr(\"transform\",\"\"),r=\"\",n=\"\",s=k.Color.opacity(t.color)?t.color:k.Color.defaultLine,l=k.Color.combine(s,o),u=_(l).getBrightness()>128?\"#000\":k.Color.background;if(t.name&&void 0===t.zLabelVal){\n",
+       "var h=document.createElement(\"p\");h.innerHTML=t.name,r=h.textContent||\"\",r.length>15&&(r=r.substr(0,12)+\"...\")}void 0!==t.zLabel?(void 0!==t.xLabel&&(n+=\"x: \"+t.xLabel+\"<br>\"),void 0!==t.yLabel&&(n+=\"y: \"+t.yLabel+\"<br>\"),n+=(n?\"z: \":\"\")+t.zLabel):b&&t[i+\"Label\"]===p?n=t[(\"x\"===i?\"y\":\"x\")+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&(n=t.yLabel):n=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",t.text&&(n+=(n?\"<br>\":\"\")+t.text),\"\"===n&&(\"\"===r&&e.remove(),n=r);var d=e.select(\"text.nums\").style(\"fill\",u).call(k.Drawing.setPosition,0,0).text(n).attr(\"data-notex\",1).call(k.util.convertToTspans);d.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0);var g=e.select(\"text.name\"),w=0;r&&r!==n?(g.style(\"fill\",l).text(r).call(k.Drawing.setPosition,0,0).attr(\"data-notex\",1).call(k.util.convertToTspans),g.selectAll(\"tspan.line\").call(k.Drawing.setPosition,0,0),w=g.node().getBoundingClientRect().width+2*O):(g.remove(),e.select(\"rect\").remove()),e.select(\"path\").style({fill:l,stroke:u});var A,M,T=d.node().getBoundingClientRect(),E=c._offset+(t.x0+t.x1)/2,S=f._offset+(t.y0+t.y1)/2,C=Math.abs(t.x1-t.x0),P=Math.abs(t.y1-t.y0),z=T.width+R+O+w;t.ty0=v-T.top,t.bx=T.width+2*O,t.by=T.height+2*O,t.anchor=\"start\",t.txwidth=T.width,t.tx2width=w,t.offset=0,a?(t.pos=E,A=y>=S+P/2+z,M=S-P/2-z>=0,\"top\"!==t.idealAlign&&A||!M?A?(S+=P/2,t.anchor=\"start\"):t.anchor=\"middle\":(S-=P/2,t.anchor=\"end\")):(t.pos=S,A=m>=E+C/2+z,M=E-C/2-z>=0,\"left\"!==t.idealAlign&&A||!M?A?(E+=C/2,t.anchor=\"start\"):t.anchor=\"middle\":(E-=C/2,t.anchor=\"end\")),d.attr(\"text-anchor\",t.anchor),w&&g.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",\"translate(\"+E+\",\"+S+\")\"+(a?\"rotate(\"+L+\")\":\"\"))}),M}function u(t,e){function r(t){var e=t[0],r=t[t.length-1];if(i=f-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-h,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(.01>a)){if(-.01>i){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var u=0;for(o=0;o<t.length;o++)l=t[o],l.pos+l.dp+l.size>h&&u++;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos>h-1&&(l.del=!0,u--);for(o=0;o<t.length&&!(0>=u);o++)if(l=t[o],l.pos<f+1)for(l.del=!0,u--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(0>=u);o--)l=t[o],l.pos+l.dp+l.size>h&&(l.del=!0,u--)}}}for(var n,i,a,o,s,l,u,c=0,f=e._offset,h=e._offset+e._length,p=t.map(function(t,r){return[{i:r,dp:0,pos:t.pos,posref:t.posref,size:t.by*(\"x\"===e._id.charAt(0)?C:1)/2}]}).sort(function(t,e){return t[0].posref-e[0].posref});!n&&c<=t.length;){for(c++,n=!0,o=0;o<p.length-1;){var d=p[o],g=p[o+1],v=d[d.length-1],m=g[0];if(i=v.pos+v.dp+v.size-m.pos-m.dp+m.size,i>.01){for(s=g.length-1;s>=0;s--)g[s].dp+=i;for(d.push.apply(d,g),p.splice(o+1,1),u=0,s=d.length-1;s>=0;s--)u+=d[s].dp;for(a=u/d.length,s=d.length-1;s>=0;s--)d[s].dp-=a;n=!1}else o++}p.forEach(r)}for(o=p.length-1;o>=0;o--){var y=p[o];for(s=y.length-1;s>=0;s--){var b=y[s],x=t[b.i];x.offset=b.dp,x.del=b.del}}}function 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r=Math.max(0,Math.min(D,t+K)),n=Math.max(0,Math.min(B,e+Q)),i=Math.abs(r-K),a=Math.abs(n-Q),o=Math.floor(Math.min(a,i,V)/2);J.l=Math.min(K,r),J.r=Math.max(K,r),J.t=Math.min(Q,n),J.b=Math.max(Q,n),!G||a<Math.min(Math.max(.6*i,U),V)?U>i?(nt=\"\",J.r=J.l,J.t=J.b,at.attr(\"d\",\"M0,0Z\")):(J.t=0,J.b=B,nt=\"x\",at.attr(\"d\",\"M\"+(J.l-.5)+\",\"+(Q-V-.5)+\"h-3v\"+(2*V+1)+\"h3ZM\"+(J.r+.5)+\",\"+(Q-V-.5)+\"h3v\"+(2*V+1)+\"h-3Z\")):!H||i<Math.min(.6*a,V)?(J.l=0,J.r=D,nt=\"y\",at.attr(\"d\",\"M\"+(K-V-.5)+\",\"+(J.t-.5)+\"v-3h\"+(2*V+1)+\"v3ZM\"+(K-V-.5)+\",\"+(J.b+.5)+\"v3h\"+(2*V+1)+\"v-3Z\")):(nt=\"xy\",at.attr(\"d\",\"M\"+(J.l-3.5)+\",\"+(J.t-.5+o)+\"h3v\"+-o+\"h\"+o+\"v-3h-\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.t-.5+o)+\"h-3v\"+-o+\"h\"+-o+\"v-3h\"+(o+3)+\"ZM\"+(J.r+3.5)+\",\"+(J.b+.5-o)+\"h-3v\"+o+\"h\"+-o+\"v3h\"+(o+3)+\"ZM\"+(J.l-3.5)+\",\"+(J.b+.5-o)+\"h3v\"+o+\"h\"+o+\"v3h-\"+(o+3)+\"Z\")),J.w=J.r-J.l,J.h=J.b-J.t,it.attr(\"d\",et+\"M\"+J.l+\",\"+J.t+\"v\"+J.h+\"h\"+J.w+\"v-\"+J.h+\"h-\"+J.w+\"Z\"),rt||(it.transition().style(\"fill\",tt>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),at.transition().style(\"opacity\",1).duration(200),rt=!0)}function 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r=0,n=0,i=t.length;i>n;++n)r+=t[n]*e[n];return r}function b(t,e){return[t[1]*e[2]-t[2]*e[1],t[2]*e[0]-t[0]*e[2],t[0]*e[1]-t[1]*e[0]]}function x(t){for(var e=0,r=arguments.length,n=[];++e<r;)n.push(arguments[e]);var i=_.dispatch.apply(null,n);return i.of=function(e,r){return function(n){var a;try{a=n.sourceEvent=_.event,n.target=t,_.event=n,i[n.type].apply(e,r)}finally{_.event=a}}},i}var _=t(\"d3\"),w=Math.PI/180,k=180/Math.PI,A={cursor:\"pointer\"},M={cursor:\"auto\"};e.exports=n},{d3:320}],623:[function(t,e,r){\"use strict\";function n(t,e){var r=t.projection,n=t.zoom,a=function(){t.makeProjection(e),t.makePath(),n.scale(r.scale()),n.translate(r.translate()),i.loneUnhover(t.hoverContainer),t.render()};return a}var i=t(\"../cartesian/graph_interact\");e.exports=n},{\"../cartesian/graph_interact\":603}],624:[function(t,e,r){\"use strict\";function n(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxStart=[0,0],this.boxEnd=[0,0]}function i(t){var e=t.mouseContainer,r=t.glplot,i=new n(e,r);return i.mouseListener=a(e,function(e,n,a){function o(e,r,n){var a=Math.min(r,n),o=Math.max(r,n);a!==o?(e[0]=a,e[1]=o,i.dataBox=e):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}var s=t.xaxis.range,l=t.yaxis.range,u=r.viewBox,c=i.lastPos[0],f=i.lastPos[1];switch(n*=r.pixelRatio,a*=r.pixelRatio,a=u[3]-u[1]-a,t.fullLayout.dragmode){case\"zoom\":if(e){var h=n/(u[2]-u[0])*(s[1]-s[0])+s[0],p=a/(u[3]-u[1])*(l[1]-l[0])+l[0];i.boxEnabled||(i.boxStart[0]=h,i.boxStart[1]=p),i.boxEnd[0]=h,i.boxEnd[1]=p,i.boxEnabled=!0}else i.boxEnabled&&(o(s,i.boxStart[0],i.boxEnd[0]),o(l,i.boxStart[1],i.boxEnd[1]),i.boxEnabled=!1);break;case\"pan\":if(i.boxEnabled=!1,e){var d=(c-n)*(s[1]-s[0])/(r.viewBox[2]-r.viewBox[0]),g=(f-a)*(l[1]-l[0])/(r.viewBox[3]-r.viewBox[1]);s[0]+=d,s[1]+=d,l[0]+=g,l[1]+=g,i.lastInputTime=Date.now(),t.cameraChanged()}}i.lastPos[0]=n,i.lastPos[1]=a}),i.wheelListener=o(e,function(e,n){var a=t.xaxis.range,o=t.yaxis.range,s=r.viewBox,l=i.lastPos[0],u=i.lastPos[1];switch(t.fullLayout.dragmode){case\"zoom\":break;case\"pan\":var c=Math.exp(.1*n/(s[3]-s[1])),f=l/(s[2]-s[0])*(a[1]-a[0])+a[0],h=u/(s[3]-s[1])*(o[1]-o[0])+o[0];a[0]=(a[0]-f)*c+f,a[1]=(a[1]-f)*c+f,o[0]=(o[0]-h)*c+h,o[1]=(o[1]-h)*c+h,i.lastInputTime=Date.now(),t.cameraChanged()}return!0}),i}var a=t(\"mouse-change\"),o=t(\"mouse-wheel\");e.exports=i},{\"mouse-change\":426,\"mouse-wheel\":430}],625:[function(t,e,r){\"use strict\";function 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e=this.scene,r=a.Plots.getSubplotIds(e.fullLayout,\"gl2d\"),n=a.Axes.findSubplotsWithAxis(r,t);return 0!==n.indexOf(e.id)},l.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},l.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},l.getLabelPad=function(t,e){var r=1.5,n=e.titlefont.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?-10+n*(r+(i?1:0)):-10+n*(r+(i?.5:0)):\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},l.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},l.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":577,\"../../lib/str2rgbarray\":588,\"../../plotly\":595}],626:[function(t,e,r){\"use strict\";var 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n(t,e){this.container=t.container,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.updateAxes(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=d(this),this.traces={},this.spikes=f(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;2>r;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/plots\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),f=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),p=t(\"./convert\"),d=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),m=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o){a=document.createElement(\"canvas\");try{o=a.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0})}catch(t){throw new Error([\"Error creating static canvas/context for image server\"].join(\" \"))}}this.canvas=a,this.gl=o}else{var e,r=document.createElement(\"canvas\"),n={premultipliedAlpha:!0};try{e=r.getContext(\"webgl\",n)}catch(t){}if(!e)try{e=r.getContext(\"experimental-webgl\",n)}catch(t){}e||v(this),this.canvas=r,this.gl=e}var i=this.canvas,s=this.pixelRatio,l=this.fullLayout;i.width=0|Math.ceil(s*l.width),i.height=0|Math.ceil(s*l.height),i.style.width=\"100%\",i.style.height=\"100%\",i.style.position=\"absolute\",i.style.top=\"0px\",i.style.left=\"0px\",i.style[\"pointer-events\"]=\"none\";var u=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");u.style.position=\"absolute\",u.style.top=u.style.left=\"0px\",u.style.width=u.style.height=\"100%\",u.style[\"z-index\"]=20,u.style[\"pointer-events\"]=\"none\";var c=this.mouseContainer=document.createElement(\"div\");c.style.position=\"absolute\";var f=this.container;f.appendChild(i),f.appendChild(u),f.appendChild(c)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.glplot.setDirty(!0),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new 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o=e.width,u=e.height,c=0|Math.ceil(a*o),f=0|Math.ceil(a*u),h=this.canvas;(h.width!==c||h.height!==f)&&(h.width=c,h.height=f),t?Array.isArray(t)||(t=[t]):t=[];var p,d;for(r=0;r<t.length;++r){if(p=t[r],d=this.traces[p.uid])d.update(p);else{var g=s.getModule(p.type);d=g.plot(this,p)}this.traces[p.uid]=d}var v=Object.keys(this.traces);t:for(r=0;r<v.length;++r){for(n=0;n<t.length;++n)if(t[n].uid===v[r])continue t;d=this.traces[v[r]],d.dispose(),delete this.traces[v[r]]}var y=this.glplotOptions;y.merge(e),y.screenBox=[0,0,o,u];var b=e._size,x=this.xaxis.domain,_=this.yaxis.domain;y.viewBox=[b.l+x[0]*b.w,b.b+_[0]*b.h,o-b.r-(1-x[1])*b.w,u-b.t-(1-_[1])*b.h],this.mouseContainer.style.width=b.w*(x[1]-x[0])+\"px\",this.mouseContainer.style.height=b.h*(_[1]-_[0])+\"px\",this.mouseContainer.height=b.h*(_[1]-_[0]),this.mouseContainer.style.left=b.l+x[0]*b.w+\"px\",this.mouseContainer.style.top=b.t+(1-_[1])*b.h+\"px\";var 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o=n._size,s=this.xaxis.domain,l=this.yaxis.domain,c=t.pick(i/t.pixelRatio+o.l+s[0]*o.w,a/t.pixelRatio-(o.t+(1-l[1])*o.h));if(c&&n.hovermode){var f=c.object._trace.handlePick(c);if(f&&(!this.lastPickResult||this.lastPickResult.trace!==f.trace||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var h=this.lastPickResult=f;this.spikes.update({center:c.dataCoord}),h.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(c.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(c.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio];var p=h.hoverinfo;if(\"all\"!==p){var d=p.split(\"+\");-1===d.indexOf(\"x\")&&(h.traceCoord[0]=void 0),-1===d.indexOf(\"y\")&&(h.traceCoord[1]=void 0),-1===d.indexOf(\"text\")&&(h.textLabel=void 0),-1===d.indexOf(\"name\")&&(h.name=void 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i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":288,\"mouse-change\":426,\"mouse-wheel\":430,\"right-now\":440}],629:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"gl3d\",s),u=e[s]._scene;void 0===u&&(u=new n({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),e[s]._scene=u),u.plot(l,e,t.layout)}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\"),r.initAxes=function(t){var e=t._fullLayout;delete e.xaxis,delete e.yaxis;for(var r=i.getSubplotIds(e,\"gl3d\"),n=0;n<r.length;++n)for(var o=r[n],s=e[o],l=0;3>l;++l){var u=a[l],c=s[u];c._td=t}}},{\"../plots\":642,\"./layout/attributes\":630,\"./layout/defaults\":634,\"./layout/layout_attributes\":635,\"./scene\":639,\"./set_convert\":640}],630:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"sceneid\",dflt:\"scene\"}}},{}],631:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:\"rgb(0,0,0)\"},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},title:n.title,titlefont:n.titlefont,type:n.type,autorange:n.autorange,rangemode:n.rangemode,range:n.range,fixedrange:n.fixedrange,tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,mirror:n.mirror,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:n.tickfont,tickangle:n.tickangle,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:n.showline,linecolor:n.linecolor,linewidth:n.linewidth,showgrid:n.showgrid,gridcolor:i({},n.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:n.gridwidth,zeroline:n.zeroline,zerolinecolor:n.zerolinecolor,zerolinewidth:n.zerolinewidth}},{\"../../../lib/extend\":574,\"../../cartesian/layout_attributes\":605}],632:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"./axis_attributes\"),a=t(\"../../cartesian/axis_defaults\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=function(){};e.exports=function(t,e,r){function l(t,e){return n.coerce(u,c,i,t,e)}for(var u,c,f=0;f<o.length;f++){var h=o[f];u=t[h]||{},c={_id:h[0]+r.scene,_name:h},e[h]=c=a(u,c,l,{font:r.font,letter:h[0],data:r.data,showGrid:!0}),l(\"gridcolor\"),l(\"title\",h[0]),c.setScale=s,l(\"showspikes\")&&(l(\"spikesides\"),l(\"spikethickness\"),l(\"spikecolor\")),l(\"showbackground\")&&l(\"backgroundcolor\"),l(\"showaxeslabels\")}}},{\"../../../lib\":578,\"../../cartesian/axis_defaults\":599,\"./axis_attributes\":631}],633:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=l(this.tickPad),this._defaultLabelPad=l(this.labelPad),this._defaultLineTickLength=l(this.lineTickLength)}function i(t){var e=new n;return e.merge(t),e}var a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;3>r;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":577,\"../../../lib/str2rgbarray\":588,arraytools:298}],634:[function(t,e,r){\"use strict\";var n=t(\"../../../plotly\"),i=t(\"./layout_attributes\"),a=t(\"./axis_defaults\");e.exports=function(t,e,r){function o(t,e){return n.Lib.coerce(u,c,i,t,e)}if(e._hasGL3D){var s,l=n.Plots.getSubplotIdsInData(r,\"gl3d\");delete e.xaxis,delete e.yaxis;var u,c,f=l.length;for(s=0;f>s;++s){var h=l[s];void 0!==t[h]?u=t[h]:t[h]=u={},c=e[h]||{},o(\"bgcolor\");for(var p=Object.keys(i.camera),d=0;d<p.length;d++)o(\"camera.\"+p[d]+\".x\"),o(\"camera.\"+p[d]+\".y\"),o(\"camera.\"+p[d]+\".z\");o(\"domain.x\",[s/f,(s+1)/f]),o(\"domain.y\");var g=!!o(\"aspectratio.x\")&&!!o(\"aspectratio.y\")&&!!o(\"aspectratio.z\"),v=g?\"manual\":\"auto\",m=o(\"aspectmode\",v);g||(u.aspectratio=c.aspectratio={x:1,y:1,z:1},\"manual\"===m&&(c.aspectmode=\"auto\")),a(u,c,{font:e.font,scene:h,data:r}),e[h]=c}}}},{\"../../../plotly\":595,\"./axis_defaults\":632,\"./layout_attributes\":635}],635:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":574,\"./axis_attributes\":631}],636:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;3>e;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":588}],637:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;3>r;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,u=[[],[],[]],c=0;3>c;++c){var f=i[s[c]];if(f._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(f._length)===1/0)u[c]=[];else{f.range[0]=r[c].lo/t.dataScale[c],f.range[1]=r[c].hi/t.dataScale[c],f._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var h=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var 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i=t(\"../plotly\"),a=t(\"d3\"),o=t(\"../constants/xmlns_namespaces\");e.exports=function(t,e){var r,s,l=t._fullLayout,u=l._paper,c=l._size;u.insert(\"rect\",\":first-child\").call(i.Drawing.setRect,0,0,l.width,l.height).call(i.Color.fill,l.paper_bgcolor);var f,h=i.Plots.getSubplotIds(l,\"gl3d\");for(s=0;s<h.length;s++)f=l[h[s]],r=f.domain,n(l,f._scene,{x:c.l+c.w*r.x[0],y:c.t+c.h*(1-r.y[1]),width:c.w*(r.x[1]-r.x[0]),height:c.h*(r.y[1]-r.y[0])});var p,d=i.Plots.getSubplotIds(l,\"gl2d\");for(s=0;s<d.length;s++)p=l._plots[d[s]],n(l,p._scene2d,{x:c.l,y:c.t,width:c.w,height:c.h});var g,v,m=i.Plots.getSubplotIds(l,\"geo\");for(s=0;s<m.length;s++)g=l[m[s]],r=g.domain,v=g._geo.framework,v.attr(\"style\",null),v.attr({x:c.l+c.w*r.x[0]+g._marginX,y:c.t+c.h*(1-r.y[1])+g._marginY,width:g._width,height:g._height}),l._geoimages.node().appendChild(v.node());if(l._toppaper){var 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.supplyLayoutDefaults=t(\"./layout_defaults\"),n.layoutAttributes=t(\"./layout_attributes\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.style=t(\"./style\"),n.styleOne=t(\"./style_one\"),n.moduleType=\"trace\",n.name=\"pie\",n.basePlotModule=t(\"../../plots/cartesian\"),n.categories=[\"pie\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/cartesian\":604,\"./attributes\":720,\"./calc\":721,\"./defaults\":722,\"./layout_attributes\":725,\"./layout_defaults\":726,\"./plot\":727,\"./style\":728,\"./style_one\":729}],725:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\"}}},{}],726:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\")}},{\"../../lib\":578,\"./layout_attributes\":725}],727:[function(t,e,r){\"use strict\";function n(t,e,r){var n=Math.sqrt(t.width*t.width+t.height*t.height),a=t.width/t.height,o=Math.PI*Math.min(e.v/r.vTotal,.5),s=1-r.trace.hole,l=i(e,r),u={scale:l*r.r*2/n,rCenter:1-l,rotate:0};if(u.scale>=1)return u;var c=a+1/(2*Math.tan(o)),f=r.r*Math.min(1/(Math.sqrt(c*c+.5)+c),s/(Math.sqrt(a*a+s/2)+a)),h={scale:2*f/t.height,rCenter:Math.cos(f/r.r)-f*a/r.r,rotate:(180/Math.PI*e.midangle+720)%180-90},p=1/a,d=p+1/(2*Math.tan(o)),g=r.r*Math.min(1/(Math.sqrt(d*d+.5)+d),s/(Math.sqrt(p*p+s/2)+p)),v={scale:2*g/t.width,rCenter:Math.cos(g/r.r)-g/a/r.r,rotate:(180/Math.PI*e.midangle+810)%180-90},m=v.scale>h.scale?v:h;return u.scale<1&&m.scale>u.scale?m:u}function i(t,e){if(t.v===e.vTotal&&!e.trace.hole)return 1;var r=Math.PI*Math.min(t.v/e.vTotal,.5);return Math.min(1/(1+1/Math.sin(r)),(1-e.trace.hole)/2)}function a(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return 0>r&&(i*=-1),0>n&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function o(t,e){function 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r,n,i,a,o,s,l,u,c,f=t[0],h=f.trace,p=h.tilt,d=h.rotation*Math.PI/180,g=2*Math.PI/f.vTotal,v=\"px0\",m=\"px1\";if(\"counterclockwise\"===h.direction){for(l=0;l<t.length&&t[l].hidden;l++);if(l===t.length)return;d+=g*t[l].v,g*=-1,v=\"px1\",m=\"px0\"}for(p&&(a=p*Math.PI/180,r=h.tiltaxis*Math.PI/180,o=Math.sin(r)*Math.cos(r),s=1-Math.cos(a),n=Math.sin(r),i=Math.cos(r)),c=e(d),l=0;l<t.length;l++)u=t[l],u.hidden||(u[v]=c,d+=g*u.v/2,u.pxmid=e(d),u.midangle=d,d+=g*u.v/2,c=e(d),u[m]=c,u.largeArc=u.v>f.vTotal/2?1:0)}function u(t,e,r){if(!t)return 1;var n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var c=t(\"d3\"),f=t(\"../../plots/cartesian/graph_interact\"),h=t(\"../../components/color\"),p=t(\"../../components/drawing\"),d=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;s(e,r._size);var 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s=i(o,u),l=k+o.pxmid[0]*(1-s),c=A+o.pxmid[1]*(1-s),h=[];-1!==a.indexOf(\"label\")&&h.push(o.label),n.text&&n.text[o.i]&&-1!==a.indexOf(\"text\")&&h.push(n.text[o.i]),-1!==a.indexOf(\"value\")&&h.push(g.formatPieValue(o.v)),-1!==a.indexOf(\"percent\")&&h.push(g.formatPiePercent(o.v/u.vTotal)),f.loneHover({x0:l-s*u.r,x1:l+s*u.r,y:c,text:h.join(\"<br>\"),name:-1!==a.indexOf(\"name\")?n.name:void 0,color:o.color,idealAlign:o.pxmid[0]<0?\"left\":\"right\"},{container:r._hoverlayer.node(),outerContainer:r._paper.node()}),f.hover(t,e,\"pie\"),E=!0}}function h(){E&&(f.loneUnhover(r._hoverlayer.node()),E=!1)}function y(){t._hoverdata=[o],t._hoverdata.trace=e.trace,f.click(t,{target:!0})}function x(t,e,r,n){return\"a\"+n*u.r+\",\"+n*w+\" \"+b+\" \"+o.largeArc+(r?\" 1 \":\" 0 \")+n*(e[0]-t[0])+\",\"+n*(e[1]-t[1])}if(o.hidden)return void c.select(this).selectAll(\"path,g\").remove();l[o.pxmid[1]<0?0:1][o.pxmid[0]<0?0:1].push(o);var k=u.cx+_[0],A=u.cy+_[1],M=c.select(this),T=M.selectAll(\"path.surface\").data([o]),E=!1;if(T.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),M.select(\"path.textline\").remove(),M.on(\"mouseover\",s).on(\"mouseout\",h).on(\"click\",y),v.pull){var L=+(Array.isArray(v.pull)?v.pull[o.i]:v.pull)||0;L>0&&(k+=L*o.pxmid[0],A+=L*o.pxmid[1])}o.cxFinal=k,o.cyFinal=A;var S=v.hole;if(o.v===u.vTotal){var C=\"M\"+(k+o.px0[0])+\",\"+(A+o.px0[1])+x(o.px0,o.pxmid,!0,1)+x(o.pxmid,o.px0,!0,1)+\"Z\";S?T.attr(\"d\",\"M\"+(k+S*o.px0[0])+\",\"+(A+S*o.px0[1])+x(o.px0,o.pxmid,!1,S)+x(o.pxmid,o.px0,!1,S)+\"Z\"+C):T.attr(\"d\",C)}else{var P=x(o.px0,o.px1,!0,1);if(S){var z=1-S;T.attr(\"d\",\"M\"+(k+S*o.px1[0])+\",\"+(A+S*o.px1[1])+x(o.px1,o.px0,!1,S)+\"l\"+z*o.px0[0]+\",\"+z*o.px0[1]+P+\"Z\")}else T.attr(\"d\",\"M\"+k+\",\"+A+\"l\"+o.px0[0]+\",\"+o.px0[1]+P+\"Z\")}var R=Array.isArray(v.textposition)?v.textposition[o.i]:v.textposition,O=M.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==R?[0]:[]);O.enter().append(\"g\").classed(\"slicetext\",!0),O.exit().remove(),O.each(function(){var t=c.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(o.text).attr({\"class\":\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(p.font,\"outside\"===R?v.outsidetextfont:v.insidetextfont).call(d.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var e,r=p.bBox(t.node());\"outside\"===R?e=a(r,o):(e=n(r,o,u),\"auto\"===R&&e.scale<1&&(t.call(p.font,v.outsidetextfont),(v.outsidetextfont.family!==v.insidetextfont.family||v.outsidetextfont.size!==v.insidetextfont.size)&&(t.attr({\"data-bb\":\"\"}),r=p.bBox(t.node())),e=a(r,o)));var i=k+o.pxmid[0]*e.rCenter+(e.x||0),s=A+o.pxmid[1]*e.rCenter+(e.y||0);e.outside&&(o.yLabelMin=s-r.height/2,o.yLabelMid=s,o.yLabelMax=s+r.height/2,o.labelExtraX=0,o.labelExtraY=0,m=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+s+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+(e.rotate?\"rotate(\"+e.rotate+\")\":\"\")+\"translate(\"+-(r.left+r.right)/2+\",\"+-(r.top+r.bottom)/2+\")\")})}),m&&o(l,v),s.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=c.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],i=t.cyFinal+t.pxmid[1],a=\"M\"+n+\",\"+i,o=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var s=t.labelExtraX*t.pxmid[1]/t.pxmid[0],l=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);a+=Math.abs(s)>Math.abs(l)?\"l\"+l*t.pxmid[0]/t.pxmid[1]+\",\"+l+\"H\"+(n+t.labelExtraX+o):\"l\"+t.labelExtraX+\",\"+s+\"v\"+(l-s)+\"h\"+o}else a+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+o;e.append(\"path\").classed(\"textline\",!0).call(h.stroke,v.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,v.outsidetextfont.size/8),d:a,fill:\"none\"})}})})}),setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=c.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)}},{\"../../components/color\":529,\"../../components/drawing\":547,\"../../lib/svg_text_utils\":589,\"../../plots/cartesian/graph_interact\":603,\"./helpers\":723,d3:320}],728:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0],r=e.trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\".top path.surface\").each(function(t){n.select(this).call(i,t,r)})})}},{\"./style_one\":729,d3:320}],729:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r){var i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a,fill:e.color}).call(n.stroke,i)}},{\"../../components/color\":529}],730:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t){var e=t[0].trace,r=e.marker;if(n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.textposition,t,\"tp\"),e.textfont&&(n.mergeArray(e.textfont.size,t,\"ts\"),n.mergeArray(e.textfont.color,t,\"tc\"),n.mergeArray(e.textfont.family,t,\"tf\")),r&&r.line){var i=r.line;n.mergeArray(r.opacity,t,\"mo\"),n.mergeArray(r.symbol,t,\"mx\"),n.mergeArray(r.color,t,\"mc\"),n.mergeArray(i.color,t,\"mlc\"),n.mergeArray(i.width,t,\"mlw\")}}},{\"../../lib\":578}],731:[function(t,e,r){\"use strict\";var n=t(\"../../components/drawing\");t(\"./constants\");e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},dy:{valType:\"number\",dflt:1},text:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",\n",
+       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i=t(\"../scatter/attributes\"),a=t(\"../../constants/gl_markers\"),o=t(\"../../lib/extend\").extendFlat,s=i.line,l=i.marker,u=l.line;e.exports={x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},text:o({},i.text,{}),mode:o({},i.mode,{dflt:\"lines+markers\"}),surfaceaxis:{valType:\"enumerated\",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:\"color\"},projection:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},line:{color:s.color,width:s.width,dash:s.dash},marker:{color:l.color,symbol:{valType:\"enumerated\",values:Object.keys(a),dflt:\"circle\",arrayOk:!0},size:o({},l.size,{dflt:8}),sizeref:l.sizeref,sizemin:l.sizemin,sizemode:l.sizemode,opacity:o({},l.opacity,{arrayOk:!1}),colorscale:l.colorscale,cauto:l.cauto,cmax:l.cmax,cmin:l.cmin,autocolorscale:l.autocolorscale,reversescale:l.reversescale,showscale:l.showscale,line:{color:u.color,width:o({},u.width,{arrayOk:!1}),colorscale:u.colorscale,cauto:u.cauto,cmax:u.cmax,cmin:u.cmin,autocolorscale:u.autocolorscale,reversescale:u.reversescale}},textposition:o({},i.textposition,{dflt:\"top 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e,r,n,a,o=this.scene.glplot.gl,s=w.solid;this.data=t;var l=c(this.scene,t);\"mode\"in l&&(this.mode=l.mode),\"lineDashes\"in l&&l.lineDashes in w&&(s=w[l.lineDashes]),this.color=f(l.scatterColor)||f(l.lineColor),this.dataPoints=l.position,e={gl:o,position:l.position,color:l.lineColor,lineWidth:l.lineWidth||1,dashes:s[0],dashScale:s[1],opacity:t.opacity},-1!==this.mode.indexOf(\"lines\")?this.linePlot?this.linePlot.update(e):(this.linePlot=p(e),this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var u=t.opacity;if(t.marker&&t.marker.opacity&&(u*=t.marker.opacity),r={gl:o,position:l.position,color:l.scatterColor,size:l.scatterSize,glyph:l.scatterMarker,opacity:u,orthographic:!0,lineWidth:l.scatterLineWidth,lineColor:l.scatterLineColor,project:l.project,projectScale:l.projectScale,projectOpacity:l.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=d(r),this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:o,position:l.position,glyph:l.text,color:l.textColor,size:l.textSize,angle:l.textAngle,alignment:l.textOffset,font:l.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=l.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=d(a),this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),n={gl:o,position:l.position,color:l.errorColor,error:l.errorBounds,lineWidth:l.errorLineWidth,capSize:l.errorCapSize,opacity:t.opacity},this.errorBars?l.errorBounds?this.errorBars.update(n):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):l.errorBounds&&(this.errorBars=g(n),this.scene.glplot.add(this.errorBars)),l.delaunayAxis>=0){var h=i(l.position,l.delaunayColor,l.delaunayAxis);this.delaunayMesh?this.delaunayMesh.update(h):(h.gl=o,this.delaunayMesh=v(h),this.scene.glplot.add(this.delaunayMesh))}else 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n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,f){function h(r,n){return i.coerce(t,e,c,r,n)}var p=n(t,e,h);if(!p)return void(e.visible=!1);h(\"text\"),h(\"mode\"),a.hasLines(e)&&s(t,e,r,h),a.hasMarkers(e)&&o(t,e,r,f,h),a.hasText(e)&&l(t,e,f,h);var d=(e.line||{}).color,g=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",d||g);for(var v=[\"x\",\"y\",\"z\"],m=0;3>m;++m){var y=\"projection.\"+v[m];h(y+\".show\")&&(h(y+\".opacity\"),h(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":752}],757:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":566,\"../../plots/gl3d\":629,\"../scatter/colorbar\":734,\"./attributes\":752,\"./calc\":753,\"./convert\":755,\"./defaults\":756}],758:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../lib/extend\").extendFlat,o=n.marker,s=n.line,l=o.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\").plot,n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":614,\"../scatter/colorbar\":734,\"./attributes\":758,\"./calc\":759,\"./defaults\":760,\"./plot\":762}],762:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t,n){h(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function i(t){for(var e=t.lon.length,r=new Array(e),n=0;e>n;n++)r[n]=[t.lon[n],t.lat[n]];return{type:\"LineString\",coordinates:r,trace:t}}function a(t,e){function r(e){var r=t.mockAxis;return u.tickText(r,r.c2l(e),\"hover\").text+\"\\xb0\"}var n=e.hoverinfo;if(\"none\"===n)return function(t){delete t.textLabel};var i=\"all\"===n?v.hoverinfo.flags:n.split(\"+\"),a=-1!==i.indexOf(\"location\")&&Array.isArray(e.locations),o=-1!==i.indexOf(\"lon\"),s=-1!==i.indexOf(\"lat\"),l=-1!==i.indexOf(\"text\");return function(t){var n=[];a?n.push(t.location):o&&s?n.push(\"(\"+r(t.lon)+\", \"+r(t.lat)+\")\"):o?n.push(\"lon: \"+r(t.lon)):s&&n.push(\"lat: \"+r(t.lat)),l&&n.push(t.tx||e.text),t.textLabel=n.join(\"<br>\")}}function o(t){var e=Array.isArray(t.locations);return function(r,n){return{points:[{data:t._input,fullData:t,curveNumber:t.index,pointNumber:n,lon:r.lon,lat:r.lat,location:e?r.location:null}]}}}var s=t(\"d3\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"../../plots/cartesian/axes\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,f=t(\"../../lib/geo_location_utils\").locationToFeature,h=t(\"../../lib/array_to_calc_item\"),p=t(\"../../components/color\"),d=t(\"../../components/drawing\"),g=t(\"../scatter/subtypes\"),v=t(\"./attributes\"),m=e.exports={};m.calcGeoJSON=function(t,e){var r,i,a,o,s=[],l=Array.isArray(t.locations);l?(o=t.locations,r=o.length,i=c(t,e),a=function(t,e){var r=f(t.locationmode,o[e],i);return void 0!==r?r.properties.ct:void 0}):(r=t.lon.length,a=function(t,e){return[t.lon[e],t.lat[e]]});for(var u=0;r>u;u++){var h=a(t,u);if(h){var p={lon:h[0],lat:h[1],location:l?t.locations[u]:null};n(t,p,u),s.push(p)}}return s.length>0&&(s[0].trace=t),s},m.plot=function(t,e){var r=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,function(t){return t.uid});r.enter().append(\"g\").attr(\"class\",\"trace 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}var d=o(t,e,p);return d?(p(\"text\"),p(\"mode\",d<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&l(t,e,r,p),a.hasMarkers(e)&&s(t,e,r,h,p),p(\"fill\"),\"none\"!==e.fill&&u(t,e,r,p),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/constants\":735,\"../scatter/fillcolor_defaults\":737,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/xy_defaults\":751,\"./attributes\":763}],766:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":626,\"../scatter/colorbar\":734,\"../scatter3d/calc\":753,\"./attributes\":763,\"./convert\":764,\"./defaults\":765}],767:[function(t,e,r){\"use strict\";function n(t){return{valType:\"boolean\",dflt:!1}}function i(t){return{show:{valType:\"boolean\",dflt:!1},project:{x:n(\"x\"),y:n(\"y\"),z:n(\"z\")},color:{valType:\"color\",dflt:\"#000\"},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!1},highlightColor:{valType:\"color\",dflt:\"#000\"},highlightWidth:{valType:\"number\",min:1,max:16,dflt:2}}}var a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports={z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"data_array\"},zauto:a.zauto,zmin:a.zmin,zmax:a.zmax,colorscale:a.colorscale,autocolorscale:o({},a.autocolorscale,{dflt:!1}),reversescale:a.reversescale,showscale:a.showscale,contours:{x:i(\"x\"),y:i(\"y\"),z:i(\"z\")},hidesurface:{valType:\"boolean\",dflt:!1},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},_nestedModules:{colorbar:\"Colorbar\"}}},{\"../../components/colorscale/attributes\":535,\"../../lib/extend\":574}],768:[function(t,e,r){\"use strict\";var 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-0.01663500656888118, -0.01663500656888118, -0.01663500656888118, -0.01663500656888118], \"type\": \"scatter3d\"}], {\"width\": 1000, \"title\": \"Clusters\", \"margin\": {\"r\": 0, \"b\": 0, \"t\": 60, \"l\": 0}, \"scene\": {\"zaxis\": {\"zerolinecolor\": \"rgb(255, 255, 255)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"backgroundcolor\": \"rgb(234, 234, 234)\", \"title\": \"request_depth_std\"}, \"xaxis\": {\"zerolinecolor\": \"rgb(255, 255, 255)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"backgroundcolor\": \"rgb(234, 234, 234)\", \"title\": \"variance_request_interval\"}, \"yaxis\": {\"zerolinecolor\": \"rgb(255, 255, 255)\", \"gridcolor\": \"rgb(255, 255, 255)\", \"showbackground\": true, \"backgroundcolor\": \"rgb(234, 234, 234)\", \"title\": \"error_rate\"}}, \"height\": 1000}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/src/bothound_tools.py b/src/bothound_tools.py
index efc2870..47834d8 100644
--- a/src/bothound_tools.py
+++ b/src/bothound_tools.py
@@ -22,7 +22,8 @@ def connect_to_db(self):
         learn2bantools instance and will be used to save data back to the db
         """
         self.db = MySQLdb.connect(host = self.db_host, user = self.db_user, 
-            passwd = self.db_password,port = self.db_port)
+            passwd = self.db_password,port = self.db_port, charset='utf8',
+            use_unicode=True)
 
         #Create cursor object to allow query execution
         self.cur = self.db.cursor(MySQLdb.cursors.DictCursor)
@@ -209,7 +210,7 @@ def factorize_countries(self, ip_feature_db):
                 
                 country_name = ""
                 if (c is not None):
-                    country_name = c.name
+                    country_name = c.name.encode('ascii','ignore')
                 self.cur.execute("insert into countries(code, name) values ('{}', '{}')".format(country_code, country_name))
                 ids[country_code] = self.cur.lastrowid
                 features[feature_index] = self.cur.lastrowid
diff --git a/src/session_computer.py b/src/session_computer.py
index d77fb77..c54ede7 100644
--- a/src/session_computer.py
+++ b/src/session_computer.py
@@ -124,7 +124,7 @@ def process_incident(self, incident):
         #print ip_feature_db
         self.bothound_tools.add_sessions(incident['id'], ip_feature_db, banned_ips)
         self.bothound_tools.set_incident_process(incident['id'], False)
-
+        print "Incident {} processed.".format(incident['id'])
         return ip_feature_db
 
     def extract(self):
diff --git a/src/util/es_handler.py b/src/util/es_handler.py
index 36e7e53..a3fdebc 100644
--- a/src/util/es_handler.py
+++ b/src/util/es_handler.py
@@ -99,53 +99,57 @@ def get(self, start, stop, target):
         print >>f1, indexes
         print >>f1, ts_start
         print >>f1, ts_stop
-        """   
-        #pdb.set_trace()
-        page = self.es.search(index=indexes, 
-            scroll = '5m',
-            #search_type = 'scan',
-            size = 10000,
-            body = es_body
-            #add index between the quotation marks
-            )
+        """  
         result = []
-        sid = page['_scroll_id']
-        page_index = 0
-        scroll_size = page['hits']['total'] 
-        print "total # of hits : ", scroll_size
-        # Start scrolling
-
-        num_processed = 0
-        while (scroll_size > 0):
-            print "Scrolling...", page_index
-            # Do something with the obtained page
-            json_result = page['hits']['hits']
+        try: 
             #pdb.set_trace()
+            page = self.es.search(index=indexes, 
+                scroll = '5m',
+                #search_type = 'scan',
+                size = 10000,
+                body = es_body
+                #add index between the quotation marks
+                )
 
-            for log in json_result:
-                #print log['_source']['@timestamp']
-                cur_rec_dict = util.es_log_muncher.parse_es_json_object(log)
-                if cur_rec_dict:
-                    cur_ats_rec = ATSRecord(cur_rec_dict);
-                    #print cur_ats_rec.payload['time']
-                    result.append(cur_ats_rec);
-                    num_processed = num_processed +  1
-                        
-            print "num_processed: " + str(num_processed)
-            if(num_processed > 5000000):
-                break
+            sid = page['_scroll_id']
+            page_index = 0
+            scroll_size = page['hits']['total'] 
+            print "total # of hits : ", scroll_size
+            # Start scrolling
 
-            page_index = page_index + 1
-            tStart = datetime.datetime.now()
-            page = self.es.scroll(scroll_id = sid, scroll = '5m')
-            print "scroll time ,sec:", (datetime.datetime.now() - tStart).total_seconds()
+            num_processed = 0
+            while (scroll_size > 0):
+                print "Scrolling...", page_index
+                # Do something with the obtained page
+                json_result = page['hits']['hits']
+                #pdb.set_trace()
 
-            # Update the scroll ID
-            sid = page['_scroll_id']
-            # Get the number of results that we returned in the last scroll
-            scroll_size = len(page['hits']['hits'])
-            #print "scroll size: " + str(scroll_size)
-  
+                for log in json_result:
+                    #print log['_source']['@timestamp']
+                    cur_rec_dict = util.es_log_muncher.parse_es_json_object(log)
+                    if cur_rec_dict:
+                        cur_ats_rec = ATSRecord(cur_rec_dict);
+                        #print cur_ats_rec.payload['time']
+                        result.append(cur_ats_rec);
+                        num_processed = num_processed +  1
+                            
+                print "num_processed: " + str(num_processed)
+                if(num_processed > 5000000):
+                    break
+
+                page_index = page_index + 1
+                tStart = datetime.datetime.now()
+                page = self.es.scroll(scroll_id = sid, scroll = '5m')
+                print "scroll time ,sec:", (datetime.datetime.now() - tStart).total_seconds()
+
+                # Update the scroll ID
+                sid = page['_scroll_id']
+                # Get the number of results that we returned in the last scroll
+                scroll_size = len(page['hits']['hits'])
+                #print "scroll size: " + str(scroll_size)
+        except Exception as ex:
+            print ex
+ 
         return result
 
     def get_banjax(self, start, stop, target):
@@ -164,7 +168,7 @@ def get_banjax(self, start, stop, target):
         #indexes = [start.strftime('deflect.log-%Y.%m.*')]
         #if(start.month != stop.month):
             #indexes.append(stop.strftime('deflect.log-%Y.%m.*'))
-        print "es.search() start..."
+        print "es.search() start banjax..."
         if (target is not None) :
             es_body = {
             "from" : 0, "size" : 10000,
@@ -224,53 +228,57 @@ def get_banjax(self, start, stop, target):
         print >>f1, ts_start
         print >>f1, ts_stop
         """   
-        #pdb.set_trace()
-        page = self.es.search(index=indexes, 
-            scroll = '5m',
-            #search_type = 'scan',
-            size = 10000,
-            body = es_body
-            #add index between the quotation marks
-            )
-        result = []
-        sid = page['_scroll_id']
-        page_index = 0
-        total_size = page['hits']['total'] 
-        print "total # of Banjax hits : ", total_size
-        # Start scrolling
-        #pdb.set_trace()
-        num_processed = 0
-        scroll_size = total_size
         result = {}
-        while (scroll_size > 0):
-            print "Scrolling...", page_index
+        try:
+            #pdb.set_trace()
+            page = self.es.search(index=indexes, 
+                scroll = '5m',
+                #search_type = 'scan',
+                size = 10000,
+                body = es_body
+                #add index between the quotation marks
+                )
+            result = []
+            sid = page['_scroll_id']
+            page_index = 0
+            total_size = page['hits']['total'] 
+            print "total # of Banjax hits : ", total_size
+            # Start scrolling
+            #pdb.set_trace()
+            num_processed = 0
+            scroll_size = total_size
+            
+            while (scroll_size > 0):
+                print "Scrolling banjax...", page_index
 
-            json_result = page['hits']['hits']
-            for log in json_result:
-                src = log["_source"]
-                if "client_ip" not in src:
-                    continue
-                v = {}
-                if "rule_type" in src:
-                    v['rule'] = src['rule_type']
-                
-                result[src['client_ip']] = v  
+                json_result = page['hits']['hits']
+                for log in json_result:
+                    src = log["_source"]
+                    if "client_ip" not in src:
+                        continue
+                    v = {}
+                    if "rule_type" in src:
+                        v['rule'] = src['rule_type']
+                    
+                    result[src['client_ip']] = v  
 
-            print "num_processed: " + str(num_processed)
-            if(num_processed > 5000000):
-                break
+                print "num_processed: " + str(num_processed)
+                if(num_processed > 5000000):
+                    break
 
-            page_index = page_index + 1
-            tStart = datetime.datetime.now()
-            page = self.es.scroll(scroll_id = sid, scroll = '2m')
-            print "scroll time ,sec:", (datetime.datetime.now() - tStart).total_seconds()
+                page_index = page_index + 1
+                tStart = datetime.datetime.now()
+                page = self.es.scroll(scroll_id = sid, scroll = '2m')
+                print "scroll time ,sec:", (datetime.datetime.now() - tStart).total_seconds()
+
+                # Update the scroll ID
+                sid = page['_scroll_id']
+                # Get the number of results that we returned in the last scroll
+                scroll_size = len(page['hits']['hits'])
+                print "scroll size: " + str(scroll_size)
+        except Exception as ex:
+            print ex
 
-            # Update the scroll ID
-            sid = page['_scroll_id']
-            # Get the number of results that we returned in the last scroll
-            scroll_size = len(page['hits']['hits'])
-            print "scroll size: " + str(scroll_size)
-    
         return result