Tutorial-Reference_Metric.ipynb

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    "\n",
    "# NRPy+'s Reference Metric Interface\n",
    "\n",
    "## Author: Zach Etienne\n",
    "### Formatting improvements courtesy Brandon Clark\n",
    "\n",
    "### NRPy+ Source Code for this module: [reference_metric.py](../edit/reference_metric.py)\n",
    "\n",
    "## This notebook expounds on NRPy+'s Reference Metric Interface, underlining its efficacy in reducing computational complexity when modeling geometrically specific problems. By utilizing appropriate coordinate systems—Spherical, Cylindrical, Cartesian, or Prolate Spheroidal—geometric entities are optimally defined, thereby mitigating the 'Curse of Dimensionality'.\n",
    "\n",
    "## Introduction:\n",
    "### Why use a reference metric? Benefits of choosing the best coordinate system for the problem\n",
    "\n",
    "When solving a partial differential equation on the computer, it is useful to first pick a coordinate system well-suited to the geometry of the problem. For example, if we are modeling a spherically-symmetric star, it would be hugely wasteful to model the star in 3-dimensional Cartesian coordinates ($x$,$y$,$z$). This is because, in Cartesian coordinates, we would need to choose high sampling in all three Cartesian directions. If instead, we chose to model the star in spherical coordinates  ($r$,$\\theta$,$\\phi$), so long as the star is centered at $r=0$, we would not need to model the star with more than one point in the $\\theta$ and $\\phi$ directions!\n",
    "\n",
    "A similar argument holds for stars that are *nearly* spherically symmetric. Such stars may exhibit density distributions that vary slowly in $\\theta$ and $\\phi$ directions (e.g., isolated neutron stars or black holes). In these cases, the number of points needed to sample the angular directions will still be much smaller than in the radial direction.\n",
    "\n",
    "Thus the choice of an appropriate reference metric may directly mitigate the [Curse of Dimensionality](https://en.wikipedia.org/wiki/Curse_of_dimensionality)."
   ]
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    "<a id='toc'></a>\n",
    "\n",
    "# Table of Contents\n",
    "$$\\label{toc}$$\n",
    "\n",
    "This notebook is organized as follow\n",
    "\n",
    "1. [Step 1](#define_ref_metric): Defining a reference metric, [`reference_metric.py`](../edit/reference_metric.py)\n",
    "1. [Step 2](#define_geometric): Defining geometric quantities, **`ref_metric__hatted_quantities()`**\n",
    "1. [Step 3](#prescribed_ref_metric): Prescribed reference metrics in [`reference_metric.py`](../edit/reference_metric.py)\n",
    "    1. [Step 3.a](#sphericallike): Spherical-like coordinate systems\n",
    "        1. [Step 3.a.i](#spherical): **`reference_metric::CoordSystem = \"Spherical\"`**\n",
    "        1. [Step 3.a.ii](#sinhspherical): **`reference_metric::CoordSystem = \"SinhSpherical\"`**\n",
    "        1. [Step 3.a.iii](#sinhsphericalv2): **`reference_metric::CoordSystem = \"SinhSphericalv2\"`**\n",
    "    1. [Step 3.b](#cylindricallike): Cylindrical-like coordinate systems\n",
    "        1. [Step 3.b.i](#cylindrical): **`reference_metric::CoordSystem = \"Cylindrical\"`**\n",
    "        1. [Step 3.b.ii](#sinhcylindrical): **`reference_metric::CoordSystem = \"SinhCylindrical\"`**\n",
    "        1. [Step 3.b.iii](#sinhcylindricalv2): **`reference_metric::CoordSystem = \"SinhCylindricalv2\"`**\n",
    "    1. [Step 3.c](#cartesianlike): Cartesian-like coordinate systems\n",
    "        1. [Step 3.c.i](#cartesian): **`reference_metric::CoordSystem = \"Cartesian\"`**\n",
    "        1. [Step 3.c.ii](#sinhcartesian): **`reference_metric::CoordSystem = \"SinhCartesian\"`**\n",
    "    1. [Step 3.d](#prolatespheroidal): Prolate spheroidal coordinates\n",
    "        1. [Step 3.d.i](#symtp): **`reference_metric::CoordSystem = \"SymTP\"`**\n",
    "        1. [Step 3.d.ii](#sinhsymtp): **`reference_metric::CoordSystem = \"SinhSymTP\"`**\n",
    "1. [Step 4](#latex_pdf_output): Output this notebook to $\\LaTeX$-formatted PDF file"
   ]
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   "source": [
    "<a id='define_ref_metric'></a>\n",
    "\n",
    "# Step 1: Defining a reference metric, [`reference_metric.py`](../edit/reference_metric.py) \\[Back to [top](#toc)\\]\n",
    "$$\\label{define_ref_metric}$$\n",
    "\n",
    "***Note that currently only orthogonal reference metrics of dimension 3 or fewer are supported. This can be extended if desired.***\n",
    "\n",
    "NRPy+ assumes all curvilinear coordinate systems map directly from a uniform, Cartesian numerical grid with coordinates $(x,y,z)$=(`xx[0]`,`xx[1]`,`xx[2]`). Thus, when defining reference metrics, all defined coordinate quantities must be in terms of the `xx[]` array. As we will see, this adds a great deal of flexibility\n",
    "\n",
    "For example,  [**reference_metric.py**](../edit/reference_metric.py) requires that the *orthogonal coordinate scale factors* be defined. As described [here](https://en.wikipedia.org/wiki/Curvilinear_coordinates), the $i$th scale factor is the positive root of the metric element $g_{ii}$. In ordinary spherical coordinates $(r,\\theta,\\phi)$, with line element $ds^2 = g_{ij} dx^i dx^j = dr^2+ r^2 d \\theta^2 + r^2 \\sin^2\\theta \\ d\\phi^2$, we would first define\n",
    "* $r = xx_0$\n",
    "* $\\theta = xx_1$\n",
    "* $\\phi = xx_2$,\n",
    "\n",
    "so that the scale factors are defined as\n",
    "* `scalefactor_orthog[0]` = $1$\n",
    "* `scalefactor_orthog[1]` = $r$\n",
    "* `scalefactor_orthog[2]` = $r \\sin \\theta$.\n",
    "\n",
    "Here is the corresponding code:"
   ]
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     "text": [
      "r*sin(th) = xx0*sin(xx1)\n"
     ]
    }
   ],
   "source": [
    "import sympy as sp               # SymPy: The Python computer algebra package upon which NRPy+ depends\n",
    "import NRPy_param_funcs as par   # NRPy+: parameter interface\n",
    "import reference_metric as rfm   # NRPy+: Reference metric support\n",
    "\n",
    "r = rfm.xx[0]\n",
    "th = rfm.xx[1]\n",
    "ph = rfm.xx[2]\n",
    "\n",
    "rfm.scalefactor_orthog[0] = 1\n",
    "rfm.scalefactor_orthog[1] = r\n",
    "rfm.scalefactor_orthog[2] = r*sp.sin(th)\n",
    "\n",
    "# Notice that the scale factor will be given\n",
    "#    in terms of the fundamental Cartesian\n",
    "#    grid variables, and not {r,th,ph}:\n",
    "print(\"r*sin(th) = \"+str(rfm.scalefactor_orthog[2]))"
   ]
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    "Next suppose we wish to modify our radial coordinate $r(xx_0)$ to be an exponentially increasing function so that our numerical grid $(xx_0,xx_1,xx_2)$ will map to a spherical grid with radial grid spacing ($\\Delta r$) that *increases* with $r$. Generally, we will find it useful to define $r(xx_0)$ to be an odd function, so let's choose\n",
    "\n",
    "$$r(xx_0) = a \\sinh(xx_0/s),$$\n",
    "\n",
    "where $a$ is an overall radial scaling factor, and $s$ denotes the scale (in units of $xx_0$) over which exponential growth will take place. In our implementation below, note that we use the relation\n",
    "\n",
    "$$\\sinh(x) = \\frac{e^x - e^{-x}}{2},$$\n",
    "\n",
    "as SymPy finds it easier to evaluate exponentials than hyperbolic trigonometric functions."
   ]
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a*(exp(xx0/s) - exp(-xx0/s))*sin(xx1)/2\n"
     ]
    }
   ],
   "source": [
    "a,s = sp.symbols('a s',positive=True)\n",
    "xx0_rescaled = rfm.xx[0] / s\n",
    "r = a*(sp.exp(xx0_rescaled) - sp.exp(-xx0_rescaled))/2\n",
    "\n",
    "# Must redefine the scalefactors since 'r' has been updated!\n",
    "rfm.scalefactor_orthog[0] = 1\n",
    "rfm.scalefactor_orthog[1] = r\n",
    "rfm.scalefactor_orthog[2] = r*sp.sin(th)\n",
    "\n",
    "print(rfm.scalefactor_orthog[2])"
   ]
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   "cell_type": "markdown",
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   "source": [
    "Often we will find it useful to also define the appropriate mappings from (`xx[0]`,`xx[1]`,`xx[2]`) to Cartesian coordinates (for plotting purposes) and ordinary spherical coordinates (e.g., in case of initial data when solving a PDE are naturally written in spherical coordinates). For this purpose, `reference_metric.py` also declares lists **`xx_to_Cart[]`** and **`xxSph[]`**, which in this case are defined as"
   ]
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     "name": "stdout",
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     "text": [
      "                        ⎛xx₀⎞\n",
      "a⋅sin(xx₁)⋅cos(xx₂)⋅sinh⎜───⎟\n",
      "                        ⎝ s ⎠\n"
     ]
    }
   ],
   "source": [
    "rfm.xxSph[0] = r\n",
    "rfm.xxSph[1] = th\n",
    "rfm.xxSph[2] = ph\n",
    "\n",
    "rfm.xx_to_Cart[0] = r*sp.sin(th)*sp.cos(ph)\n",
    "rfm.xx_to_Cart[1] = r*sp.sin(th)*sp.sin(ph)\n",
    "rfm.xx_to_Cart[2] = r*sp.cos(th)\n",
    "\n",
    "# Here we show off SymPy's pretty_print()\n",
    "#   and simplify() functions. Nice, no?\n",
    "sp.pretty_print(sp.simplify(rfm.xx_to_Cart[0]))"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "<a id='define_geometric'></a>\n",
    "\n",
    "# Step 2: Define geometric quantities, `ref_metric__hatted_quantities()` \\[Back to [top](#toc)\\]\n",
    "$$\\label{define_geometric}$$\n",
    "\n",
    "Once `scalefactor_orthog[]` has been defined, the function **`ref_metric__hatted_quantities()`** within [reference_metric.py](../edit/reference_metric.py) can be called to define a number of geometric quantities useful for solving PDEs in curvilinear coordinate systems. \n",
    "\n",
    "Adopting the notation of [Baumgarte, Montero, Cordero-Carrión, and Müller, PRD 87, 044026 (2012)](https://arxiv.org/abs/1211.6632), geometric quantities related to the reference metric are named \"hatted\" quantities. For example, the reference metric is defined as $\\hat{g}_{ij}$=`ghatDD[i][j]`:"
   ]
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     "text": [
      "⎡1           0                         0              ⎤\n",
      "⎢                                                     ⎥\n",
      "⎢                     2                               ⎥\n",
      "⎢      ⎛ xx₀    -xx₀ ⎞                                ⎥\n",
      "⎢      ⎜ ───    ─────⎟                                ⎥\n",
      "⎢    2 ⎜  s       s  ⎟                                ⎥\n",
      "⎢   a ⋅⎝ℯ    - ℯ     ⎠                                ⎥\n",
      "⎢0  ───────────────────                0              ⎥\n",
      "⎢            4                                        ⎥\n",
      "⎢                                                     ⎥\n",
      "⎢                                          2          ⎥\n",
      "⎢                           ⎛ xx₀    -xx₀ ⎞           ⎥\n",
      "⎢                           ⎜ ───    ─────⎟           ⎥\n",
      "⎢                         2 ⎜  s       s  ⎟     2     ⎥\n",
      "⎢                        a ⋅⎝ℯ    - ℯ     ⎠ ⋅sin (xx₁)⎥\n",
      "⎢0           0           ─────────────────────────────⎥\n",
      "⎣                                      4              ⎦\n"
     ]
    }
   ],
   "source": [
    "rfm.ref_metric__hatted_quantities()\n",
    "\n",
    "sp.pretty_print(sp.Matrix(rfm.ghatDD))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to $\\hat{g}_{ij}$, **`ref_metric__hatted_quantities()`** also provides the following. \n",
    "* The rescaling \"matrix\" `ReDD[i][j]` is used for separating singular (due to chosen coordinate system) pieces of smooth rank-2 tensor components from the smooth parts, so that the smooth parts can be used within temporal and spatial differential operators.\n",
    "* The inverse reference metric: $\\hat{g}^{ij}$=`ghatUU[i][j]`.\n",
    "* The reference metric determinant: $\\det\\left(\\hat{g}_{ij}\\right)$=`detgammahat`.\n",
    "* The first and second derivatives of the reference metric: $\\hat{g}_{ij,k}$=`ghatDD_dD[i][j][k]`; $\\hat{g}_{ij,kl}$=`ghatDD_dDD[i][j][k][l]`.\n",
    "* The Christoffel symbols associated with the reference metric, $\\hat{\\Gamma}^i_{jk}$ = `GammahatUDD[i][j][k]` and their first derivatives $\\hat{\\Gamma}^i_{jk,l}$ = `GammahatUDD_dD[i][j][k][l]`.\n",
    "\n",
    "For example, the Christoffel symbol $\\hat{\\Gamma}^{xx_1}_{xx_2 xx_2}=\\hat{\\Gamma}^1_{22}$ is given by `GammahatUDD[1][2][2]`:"
   ]
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-sin(2⋅xx₁) \n",
      "────────────\n",
      "     2      \n"
     ]
    }
   ],
   "source": [
    "sp.pretty_print(sp.simplify(rfm.GammahatUDD[1][2][2]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given the trigonometric identity $2\\sin(x)\\cos(x) = \\sin(2x)$, notice that the above expression is equivalent to Eq. 18 of [Baumgarte, Montero, Cordero-Carrión, and Müller, PRD 87, 044026 (2012)](https://arxiv.org/abs/1211.6632). This is expected since the sinh-radial spherical coordinate system is equivalent to ordinary spherical coordinates in the angular components."
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='prescribed_ref_metric'></a>\n",
    "\n",
    "# Step 3: Prescribed reference metrics in [`reference_metric.py`](../edit/reference_metric.py) \\[Back to [top](#toc)\\]\n",
    "$$\\label{prescribed_ref_metric}$$\n",
    "\n",
    "One need not manually define scale factors or other quantities for reference metrics, as a number of prescribed reference metrics are already defined in [reference_metric.py](../edit/reference_metric.py). These can be accessed by first setting the parameter **reference_metric::CoordSystem** to one of the following, and then calling the function **`rfm.reference_metric()`**."
   ]
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   "source": [
    "import indexedexp as ixp    # NRPy+: Symbolic indexed expression (e.g., tensors, vectors, etc.) support\n",
    "import grid as gri          # NRPy+: Functions having to do with numerical grids\n",
    "\n",
    "# Step 0a: Initialize parameters\n",
    "thismodule = __name__\n",
    "par.initialize_param(par.glb_param(\"char\", thismodule, \"CoordSystem\", \"Spherical\"))\n",
    "\n",
    "# Step 0b: Declare global variables\n",
    "xx = gri.xx\n",
    "xx_to_Cart = ixp.zerorank1(DIM=4) # Must be set in terms of xx[]s\n",
    "Cart_to_xx = ixp.zerorank1(DIM=4) # Must be set in terms of xx[]s\n",
    "Cartx,Carty,Cartz = sp.symbols(\"Cartx Carty Cartz\", real=True)\n",
    "Cart = [Cartx,Carty,Cartz]\n",
    "xxSph  = ixp.zerorank1(DIM=4) # Must be set in terms of xx[]s\n",
    "scalefactor_orthog = ixp.zerorank1(DIM=4) # Must be set in terms of xx[]s\n",
    "have_already_called_reference_metric_function = False\n",
    "\n",
    "\n",
    "\n",
    "CoordSystem = par.parval_from_str(\"reference_metric::CoordSystem\")\n",
    "M_PI,M_SQRT1_2 = par.Cparameters(\"#define\",thismodule,[\"M_PI\",\"M_SQRT1_2\"],\"\")\n",
    "\n",
    "UnitVectors = ixp.zerorank2(DIM=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will find the following plotting function useful for analyzing coordinate systems in which the radial coordinate is rescaled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   },
   "outputs": [],
   "source": [
    "def create_r_of_xx0_plots(CoordSystem, r_of_xx0,rprime_of_xx0):\n",
    "    import matplotlib.pyplot as plt  # matplotlib: Python module specializing in plotting capabilities\n",
    "    plt.clf()\n",
    "    Nr = 20\n",
    "    dxx0 = 1.0 / float(Nr)\n",
    "    xx0s    = []\n",
    "    rs      = []\n",
    "    deltars = []\n",
    "    rprimes = []\n",
    "    for i in range(Nr):\n",
    "        xx0 = (float(i) + 0.5)*dxx0\n",
    "        xx0s.append(xx0)\n",
    "        rs.append(     sp.sympify(str(r_of_xx0     ).replace(\"xx0\",str(xx0))))\n",
    "        rprimes.append(sp.sympify(str(rprime_of_xx0).replace(\"xx0\",str(xx0))))\n",
    "        if i>0:\n",
    "            deltars.append(sp.log(rs[i]-rs[i-1],10))\n",
    "        else:\n",
    "            deltars.append(sp.log(2*rs[0],10))\n",
    "\n",
    "    # fig, ax = plt.subplots()\n",
    "    fig = plt.figure(figsize=(12,12)) # 8 in x 8 in\n",
    "\n",
    "    ax = fig.add_subplot(221)\n",
    "    ax.set_title(r\"$r(xx_0)$ for \"+CoordSystem,fontsize='x-large')\n",
    "    ax.set_xlabel(r\"$xx_0$\",fontsize='x-large')\n",
    "    ax.set_ylabel(r\"$r(xx_0)$\",fontsize='x-large')\n",
    "    ax.plot(xx0s, rs, 'k.', label='Spacing between\\nadjacent gridpoints')\n",
    "    # legend = ax.legend(loc='lower right', shadow=True, fontsize='x-large')\n",
    "    # legend.get_frame().set_facecolor('C1')\n",
    "\n",
    "    ax = fig.add_subplot(222)\n",
    "    ax.set_title('Grid spacing for '+CoordSystem,fontsize='x-large')\n",
    "    ax.set_xlabel(r\"$xx_0$\",fontsize='x-large')\n",
    "    ax.set_ylabel(r\"$\\log_{10}(\\Delta r)$\",fontsize='x-large')\n",
    "    ax.plot(xx0s, deltars, 'k.', label='Spacing between\\nadjacent gridpoints\\nin $r(xx_0)$ plot')\n",
    "    legend = ax.legend(loc='lower right', shadow=True, fontsize='x-large')\n",
    "    legend.get_frame().set_facecolor('C1')\n",
    "\n",
    "    ax = fig.add_subplot(223)\n",
    "    ax.set_title(r\"$r'(xx_0)$ for \"+CoordSystem,fontsize='x-large')\n",
    "    ax.set_xlabel(r\"$xx_0$\",fontsize='x-large')\n",
    "    ax.set_ylabel(r\"$r'(xx_0)$\",fontsize='x-large')\n",
    "    ax.plot(xx0s, rprimes, 'k.', label='Nr=96')\n",
    "    # legend = ax.legend(loc='upper left', shadow=True, fontsize='x-large')\n",
    "    # legend.get_frame().set_facecolor('C1')\n",
    "\n",
    "    plt.tight_layout(pad=2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sphericallike'></a>\n",
    "\n",
    "## Step 3.a: Spherical-like coordinate systems \\[Back to [top](#toc)\\]\n",
    "$$\\label{sphericallike}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='spherical'></a>\n",
    "\n",
    "### Step 3.a.i: **`reference_metric::CoordSystem = \"Spherical\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{spherical}$$\n",
    "\n",
    "Standard spherical coordinates, with $(r,\\theta,\\phi)=(xx_0,xx_1,xx_2)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:25.174692Z",
     "iopub.status.busy": "2021-08-29T17:43:25.174084Z",
     "iopub.status.idle": "2021-08-29T17:43:25.176224Z",
     "shell.execute_reply": "2021-08-29T17:43:25.175582Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"Spherical\":\n",
    "    # Adding assumption real=True can help simplify expressions involving xx[0] & xx[1] below.\n",
    "    xx[0] = sp.symbols(\"xx0\", real=True)\n",
    "    xx[1] = sp.symbols(\"xx1\", real=True)\n",
    "\n",
    "    RMAX = par.Cparameters(\"REAL\", thismodule, [\"RMAX\"],10.0)\n",
    "    xxmin = [sp.sympify(0), sp.sympify(0), -M_PI]\n",
    "    xxmax = [         RMAX,          M_PI,  M_PI]\n",
    "\n",
    "    r  = xx[0]\n",
    "    th = xx[1]\n",
    "    ph = xx[2]\n",
    "\n",
    "    Cart_to_xx[0] = sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2)\n",
    "    Cart_to_xx[1] = sp.acos(Cartz / Cart_to_xx[0])\n",
    "    Cart_to_xx[2] = sp.atan2(Carty, Cartx)\n",
    "\n",
    "    xxSph[0] = r\n",
    "    xxSph[1] = th\n",
    "    xxSph[2] = ph\n",
    "\n",
    "    # Now define xCart, yCart, and zCart in terms of x0,xx[1],xx[2].\n",
    "    # Note that the relation between r and x0 is not necessarily trivial in SinhSpherical coordinates. See above.\n",
    "    xx_to_Cart[0] = xxSph[0]*sp.sin(xxSph[1])*sp.cos(xxSph[2])\n",
    "    xx_to_Cart[1] = xxSph[0]*sp.sin(xxSph[1])*sp.sin(xxSph[2])\n",
    "    xx_to_Cart[2] = xxSph[0]*sp.cos(xxSph[1])\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(xxSph[0],xx[0])\n",
    "    scalefactor_orthog[1] = xxSph[0]\n",
    "    scalefactor_orthog[2] = xxSph[0]*sp.sin(xxSph[1])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.sin(xxSph[1])*sp.cos(xxSph[2]), sp.sin(xxSph[1])*sp.sin(xxSph[2]),  sp.cos(xxSph[1])],\n",
    "                   [ sp.cos(xxSph[1])*sp.cos(xxSph[2]), sp.cos(xxSph[1])*sp.sin(xxSph[2]), -sp.sin(xxSph[1])],\n",
    "                   [                 -sp.sin(xxSph[2]),                  sp.cos(xxSph[2]),  sp.sympify(0)   ]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's analyze $r(xx_0)$ for **\"Spherical\"** coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:25.182737Z",
     "iopub.status.busy": "2021-08-29T17:43:25.182127Z",
     "iopub.status.idle": "2021-08-29T17:43:26.187428Z",
     "shell.execute_reply": "2021-08-29T17:43:26.187924Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "CoordSystem = \"Spherical\"\n",
    "par.set_parval_from_str(\"reference_metric::CoordSystem\",CoordSystem)\n",
    "rfm.reference_metric()\n",
    "\n",
    "RMAX     = 10.0\n",
    "r_of_xx0      = sp.sympify(str(rfm.xxSph[0]                   ).replace(\"RMAX\",str(RMAX)))\n",
    "rprime_of_xx0 = sp.sympify(str(sp.diff(rfm.xxSph[0],rfm.xx[0])).replace(\"RMAX\",str(RMAX)))\n",
    "\n",
    "create_r_of_xx0_plots(CoordSystem, r_of_xx0,rprime_of_xx0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhspherical'></a>\n",
    "\n",
    "### Step 3.a.ii: **`reference_metric::CoordSystem = \"SinhSpherical\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhspherical}$$\n",
    "\n",
    "Spherical coordinates, but with $$r(xx_0) = \\text{AMPL} \\frac{\\sinh\\left(\\frac{xx_0}{\\text{SINHW}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHW}}\\right)}.$$\n",
    "\n",
    "SinhSpherical uses two parameters: `AMPL` and `SINHW`. `AMPL` sets the outer boundary distance; and `SINHW` sets the focusing of the coordinate points near $r=0$, where a small `SINHW` ($\\sim 0.125$) will greatly focus the points near $r=0$ and a large `SINHW` will look more like an ordinary spherical polar coordinate system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:26.197316Z",
     "iopub.status.busy": "2021-08-29T17:43:26.196345Z",
     "iopub.status.idle": "2021-08-29T17:43:26.198654Z",
     "shell.execute_reply": "2021-08-29T17:43:26.198140Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhSpherical\":\n",
    "    xxmin = [sp.sympify(0), sp.sympify(0), -M_PI]\n",
    "    xxmax = [sp.sympify(1),          M_PI,  M_PI]\n",
    "\n",
    "    AMPL, SINHW = par.Cparameters(\"REAL\",thismodule,[\"AMPL\",\"SINHW\"],[10.0,0.2])\n",
    "    # Set SinhSpherical radial coordinate by default; overwrite later if CoordSystem == \"SinhSphericalv2\".\n",
    "    r = AMPL * (sp.exp(xx[0] / SINHW) - sp.exp(-xx[0] / SINHW)) / \\\n",
    "               (sp.exp(1 / SINHW) - sp.exp(-1 / SINHW))\n",
    "    th = xx[1]\n",
    "    ph = xx[2]\n",
    "\n",
    "    Cart_to_xx[0] = SINHW*sp.asinh(sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2)*sp.sinh(1/SINHW)/AMPL)\n",
    "    Cart_to_xx[1] = sp.acos(Cartz / sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2))\n",
    "    Cart_to_xx[2] = sp.atan2(Carty, Cartx)\n",
    "\n",
    "    xxSph[0] = r\n",
    "    xxSph[1] = th\n",
    "    xxSph[2] = ph\n",
    "\n",
    "    # Now define xCart, yCart, and zCart in terms of x0,xx[1],xx[2].\n",
    "    # Note that the relation between r and x0 is not necessarily trivial in SinhSpherical coordinates. See above.\n",
    "    xx_to_Cart[0] = xxSph[0]*sp.sin(xxSph[1])*sp.cos(xxSph[2])\n",
    "    xx_to_Cart[1] = xxSph[0]*sp.sin(xxSph[1])*sp.sin(xxSph[2])\n",
    "    xx_to_Cart[2] = xxSph[0]*sp.cos(xxSph[1])\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(xxSph[0],xx[0])\n",
    "    scalefactor_orthog[1] = xxSph[0]\n",
    "    scalefactor_orthog[2] = xxSph[0]*sp.sin(xxSph[1])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.sin(xxSph[1])*sp.cos(xxSph[2]), sp.sin(xxSph[1])*sp.sin(xxSph[2]),  sp.cos(xxSph[1])],\n",
    "                   [ sp.cos(xxSph[1])*sp.cos(xxSph[2]), sp.cos(xxSph[1])*sp.sin(xxSph[2]), -sp.sin(xxSph[1])],\n",
    "                   [                 -sp.sin(xxSph[2]),                  sp.cos(xxSph[2]),  sp.sympify(0)   ]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we explore $r(xx_0)$ for `SinhSpherical` assuming `AMPL=10.0` and `SINHW=0.2`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:26.238146Z",
     "iopub.status.busy": "2021-08-29T17:43:26.206462Z",
     "iopub.status.idle": "2021-08-29T17:43:27.286965Z",
     "shell.execute_reply": "2021-08-29T17:43:27.286459Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+Xgdszm8XdUSmoVITJyIeT3EA2CczJ+Rsfqc5+08UF0leTfGl8KbM/EVn/rMpvjwOHGfXrdLphNbLM/Nl3a5FkmaazpDLn83MGXFSOSLeAbwmM0caLEIdHhsFthRpgmXmzztj6+9Nce3JRKyzHREnUDS9zwG+vjYQdcylaA0xEEmSSiki5lAM8nA2xYX8h1K0vA0fZU3SCAxFmnCZeeokrPPHFIM7jDTvSyNNlySpRJLi+trXU3T9u4riutL/7GJN0oxh9zlJkiRJpeaQ3JIkSZJKzVAkSZIkqdRmxTVFO+20Uy5evLjbZUhSaVx44YW3ZOaiTS+p0XjskqSptbFj16wIRYsXL2bZsmXdLkOSSiMirul2DTOdxy5JmlobO3bZfU6SJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSSqbZbLJ06VKazWa3S5EkaUwm+9jVOylrlSRNS81mk76+PlqtFtVqlf7+fmq1WrfLkiRpVFNx7LKlSJJKpNFo0Gq1aLfbtFotGo1Gt0uSJGmjpuLYZSiSpBKp1+tUq1UqlQrVapV6vd7tkiRJ2qipOHbZfU6SSqRWq9Hf30+j0aBer9t1TpI07U3FsctQJEklU6vVDEMjiIgjgY8BFeCzmXnysPn/DrwMGACWA/8vM6/pzGsDv+8sem1mPm3KCpekEpjsY5ehSJJUehFRAU4BjgCuBy6IiLMy89Ihi10MLMnMFRHxL8AHged05q3MzAOnsmZJ0sTxmiJJkuBg4PLMvDIzW8BXgaOHLpCZ52Xmis7LXwO7TXGNkqRJYiiSJAl2Ba4b8vr6zrTRHAf8YMjreRGxLCJ+HRHHTEJ9kqRJZPc5SZLGISJeCCwBnjBk8p6ZeUNE7A2cGxG/z8wrRnjv8cDxAHvssceU1CtJ2jRbiiRJghuA3Ye83q0zbQMRcTjwVuBpmbl67fTMvKHz55VAA3j4SBvJzFMzc0lmLlm0aNHEVS9J2iKGIkmS4AJg34jYKyKqwHOBs4YuEBEPBz5DEYhuHjJ9+4iY23m+E/BYYOgADZKkac7uc5Kk0svMgYh4NfAjiiG5P5+Zf4yI9wDLMvMs4D+BhcA3IgLWD729P/CZiBikONl48rBR6yRJ05yhSJIkIDPPBs4eNu0dQ54fPsr7fgU8ZHKrkyRNJrvPSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkSdNsNlm6dCnNZrPbpYzKIbklSZIkTYpms0lfXx+tVotqtUp/fz+1Wq3bZd2LLUWSJEmSJkWj0aDVatFut2m1WjQajW6XNCJDkSRJkqRJUa/XqVarVCoVqtUq9Xq92yWNyO5zkiRJkiZFrVajv7+fRqNBvV6fll3nwFAkSZIkaRLVarVpG4bWsvucJEmSpFIzFEmSJEkqNUORJEmSpFKblqEoIv4tIv4YEX+IiP+LiHndrkmSJEnS7DTtQlFE7Aq8BliSmQ8GKsBzu1uVJEmSpNlq2oWijl5gfkT0AguAG7tcjyRJkqRZatqFosy8AfgQcC1wE3BHZv54+HIRcXxELIuIZcuXL5/qMiVJkiTNEtMuFEXE9sDRwF7A/YCtIuKFw5fLzFMzc0lmLlm0aNFUlylJkiRplph2oQg4HLgqM5dn5hrg28BjulyTJEmSpFlqOoaia4FHR8SCiAigD7isyzVJkiRJmqWmXSjKzPOBbwIXAb+nqPHUrhYlSZIkadbq7XYBI8nMdwLv7HYdkiRJkma/addSJEmSJElTyVAkSZIkaUTNZpOlS5fSbDa7Xcqkmpbd5yRJkiR1V7PZpK+vj1arRbVapb+/n1qt1u2yJoUtRZIkSZLupdFo0Gq1aLfbtFotGo1Gt0uaNIYiSZIkSfdSr9epVqtUKhWq1Sr1er3bJU0au89JkiRJupdarUZ/fz+NRoN6vT5ru86BoUiSJEnSKGq12qwOQ2vZfU6SJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSpI6IODIi/hwRl0fEm0eYPzcivtaZf35ELB4y78TO9D9HxJOmtHBJ0hYxFEmSBEREBTgFeDLwIOB5EfGgYYsdB9yemfsAHwE+0Hnvg4DnAgcARwKf7KxPkjQDGIokSSocDFyemVdmZgv4KnD0sGWOBk7vPP8m0BcR0Zn+1cxcnZlXAZd31idJmgEMRZIkFXYFrhvy+vrOtBGXycwB4A5gxzG+V5I0TRmKJEmaIhFxfEQsi4hly5cv73Y5kqQOQ5EkSYUbgN2HvN6tM23EZSKiF9gWuHWM7yUzT83MJZm5ZNGiRRNYuiRpSxiKJEkqXADsGxF7RUSVYuCEs4Ytcxbwks7zZwLnZmZ2pj+3MzrdXsC+wG+mqG5J0hbq7XYBkiRNB5k5EBGvBn4EVIDPZ+YfI+I9wLLMPAv4HPCliLgcuI0iONFZ7uvApcAAcEJmtrvyQSRJ42YokiSpIzPPBs4eNu0dQ56vAp41ynvfB7xvUguUpHFqNps0Gg3q9Tq1Wq3b5UxbhiJJkiRpFmo2m/T19dFqtahWq/T39xuMRuE1RZIkSdIs1Gg0aLVatNttWq0WjUaj2yVNW4YiSZIkaRaq1+tUq1UqlQrVapV6vd7tkqYtu89JkiRJs1CtVqO/v99risbAUCRJkiTNUrVazTA0BnafkyRJklRqhiJJkiRJpWYokiRJklRqhiJJkiRJpWYokiRJklRqhiJJkiRJpWYokqQZpNlssnTpUprNZrdLkSRp1vA+RZI0QzSbTfr6+mi1WlSrVfr7+733hCRJE8CWIkmaIRqNBq1Wi3a7TavVotFodLskSZJmBUORJM0Q9XqdarVKpVKhWq1Sr9e7XZIkSbOC3eckaYao1Wr09/fTaDSo1+t2nZMkaYIYiiRpBqnVaoYhSZImmN3nJEmSJJWaoUiSJEmahrwNw9Sx+5wkSZI0zXgbhqllS5EkSZI0zXgbhqllKJIkSZKmGW/DMLXsPidJkiRNM96GYWoZiiRJkqRpyNswTB27z0mSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSSi8idoiIn0TEXzt/bj/CMgdGRDMi/hgRv4uI5wyZd1pEXBURl3QeB07pB5AkbRFDkSRJ8GagPzP3Bfo7r4dbAbw4Mw8AjgQ+GhHbDZn/H5l5YOdxyWQXLEmaOIYiSZLgaOD0zvPTgWOGL5CZf8nMv3ae3wjcDCyaqgIlzSzNZpOlS5fSbDa7XYrGoLfbBUiSNA3snJk3dZ7/Ddh5YwtHxMFAFbhiyOT3RcQ76LQ0ZebqEd53PHA8wB577DERdUuahprNJn19fbRaLarVKv39/dRqtW6XpY2Yli1FEbFdRHwzIv4UEZdFhP+KJElbJCLOiYg/jPA4euhymZlAbmQ9uwBfAl6amYOdyScCDwQOAnYA3jTSezPz1MxckplLFi2ykUmarRqNBq1Wi3a7TavVotFodLskbcJ0bSn6GPDDzHxmRFSBBd0uSJI0s2Xm4aPNi4i/R8QumXlTJ/TcPMpy2wDfB96amb8esu61rUyrI+ILwBsmsHRJM0y9Xqdara5rKarX690uSZsw7UJRRGwLHAIcC5CZLaDVzZokSbPeWcBLgJM7f545fIHOSbozgC9m5jeHzVsbqILieqQ/THrFkqatWq1Gf38/jUaDer1u17kZYNqFImAvYDnwhYh4GHAh8NrMvKe7ZUmSZrGTga9HxHHANcCzASJiCfDKzHxZZ9ohwI4RcWznfcd2Rpr734hYBARwCfDKKa1e0rRTq9UMQzPIdAxFvcAjgH/NzPMj4mMUQ6O+fehCXqwqSZoomXkr0DfC9GXAyzrPvwx8eZT3HzapBUqSJtV0HGjheuD6zDy/8/qbFCFpA16sKkmSJGkiTLtQlJl/A66LiP06k/qAS7tYkiRJkqRZbDp2nwP4V4r+2VXgSuClXa5HkiRJ0iw1LUNR56LVJd2uQ5IkSdLsN+26z0mSJEnSVDIUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZI0TLPZZOnSpTSbzW6XoinQ2+0CJEmSpOmk2WzS19dHq9WiWq3S399PrVbrdlmaRLYUSZIkSUM0Gg1arRbtdptWq0Wj0eh2SZpkhiJJkiRpiHq9TrVapVKpUK1Wqdfr3S5Jk8zuc5IkSdIQtVqN/v5+Go0G9XrdrnMlYCiSJEmShqnVaoahErH7nCRJkqRSMxRJkiRJKjVDkSRNIe97IUnS9OM1RZI0RbzvhSRJ05MtRZI0RbzvhSRJ05OhSJKmiPe9kCRperL7nCRNEe97IUnS9GQokqQp5H0vxici9gP2BuYDy4GLM/Pu7lYlSZptDEWSpGklIhYDrwJeAOwybPZARPwC+DTwjczMKS5PkjQLeU2RJGnaiIgPAX8A9gPeChwAbAvMpQhIRwG/Ak4GLomIR3SpVEnSLGIokiRNJwuBBwD/TBGI/pGZd2Xmmsz8e2aek5lvy8y9gfcC+3ezWEnS7GD3OUnStJGZr1z7PCJeCXxiI8t+Y0qKkiTNerYUSZKmq3OBg7pdhCRp9jMUSZKmqzOAkyLi4d0uRJI0u9l9TpI0XX0OCOD8iPg5RcvRhcCFmbm8q5VJmtaazab3hNO4GIokSdPVdsCBwCOAhwPPAd4JVCLixszcvXulSZqums0mfX19tFotqtUq/f39BiNtkqFIkjQtZeZdwM87DwAiYi7wMIqwJEn30mg0aLVatNttWq0WjUbDUKRN8poiSdKMkZmrgb8Bu3W7FknTU71ep1qtUqlUqFar1Ov1bpekGcCWIknStBcRPcA/AccDT6K41ugdE7j+HYCvAYuBq4FnZ+btIyzXBn7feXltZj6tM30v4KvAjhTXPb0oM1sTVZ+ksavVavT393tNkcZlQluKImK/iHhyRDwjIh4fEQsncv2SpHKJiD0i4j3AtcDXgTXAWydhU28G+jNzX6C/83okKzPzwM7jaUOmfwD4SGbuA9wOHDcJNUoao1qtxoknnmgg0phtcSiKiMUR8cGIuAG4FPg+8E3gp8BtEXFuRDw7ImJLtyVJmv0ioicijo6Is4ErgSOBk4H7ZeYxwPcmYbNHA6d3np8OHDPWN3aOb4dRHPvG/X5JUvdtUSiKiA8BfwD2ozhz92BgW2AusAtwFPArioPZJRHxiC2qVpJUBtcCHwMuAg7IzIMz8xOZeeskbnPnzLyp8/xvwM6jLDcvIpZFxK8j4pjOtB2Bf2TmQOf19cCuI705Io7vvH/Z8uWOKi5J08WWXlO0EHhAZt44wry/dx7nAG+LiGcB+1Mc5CRJGs19Ke5JdClwzUStNCLO6ax7uA2642VmRkSOspo9M/OGiNgbODcifg/cMdYaMvNU4FSAJUuWjLYNSdIU26JQlJmvHMey39iSbUmSSmMPimty3g98KiK+BZyWmT/bkpVm5uGjzYuIv0fELpl5U0TsAtw8yjpu6Px5ZUQ0KO6f9C1gu4jo7bQW7QbcsCW1SpKmlkNyS5Kmlcy8MTNPAvYCng/sAPRHxFWdQRf2nYTNngW8pPP8JcCZwxeIiO0790kiInYCHgtcmpkJnAc8c2PvlyRNX5MyJHdEPBp4Buv7VN8AfCczfzUZ25MkzT6dsPF94PsRcT/gZcD/A94GTHTXs5OBr0fEcRRd9p4NEBFLgFdm5ssouoB/JiIGKU4qnpyZl3be/ybgqxHxXuBi4HMTXJ8kaRJNeCiKiJOAQ4EvUvQJh6IrxAcjopGZb5vobUqSZrfOtavv6RxjjgJePsHrvxXoG2H6MoowRufE3kNGef+VwMETWZMkaepMRkvRc4D9Omf41omIzwF/ojjDJ0nSuA1tPep2LZKk2WMyrikaAPYcYfoenXmSJI0oIh45jmXnRsT+k1mPJKkcJqOl6DXAjyLiSuC6zrQ9KC6YPWEStidJmj3OjIgLgE8DP8nMweELRMSuwIuBVwHvBi6b2hIlSbPNhIWiiFiSmcsy85zOmbuDKIYlheJGdheMdHCTJGmI/YA3A1+muFHqxRSD9ayiGIXuAIqTbA3geZn5iy7VKUmaRSaypejciDg6M8/rhJ/zOw8iYoGBSJK0KZl5D/D2zihuTwYOoQhB2wPLgVOAH2Tmn7pXpSRptpnIUPTvwHcj4sWZ+W2AiOgBjgfeCewygduSJM1imbka+E7nIUnSpJqwUJSZn42I5cCXI2JH4FZgKUUY+uhEbUeSJEmzV7PZpNFoUK/XqdVq3S5HJTGhAy1k5pmdu41/BlgDfAJYmpm3TOR2JEmSNPs0m036+vpotVpUq1X6+/sNRpoSEzYkd0Q8NCK+S9E6dCawGrjZQCRJkqSxaDQatFot2u02rVaLRqPR7ZJUEhPZUnQxxWhAj8rMCyPiIOD7EbEoM98wgduRJJVMRDwaeAawa2fSDcB3MvNX3atK0kSr1+tUq9V1LUX1er3bJakkJjIUPTUzf7D2RWZeEBGHUNyzaKfMPHYCtyVJKomIOAk4FPgicG5n8h7AByOikZlv61pxkiZUrVajv7/fa4o05SZyoIUfjDDtTxHxOOCHE7UdSVLpPAfYLzNz6MSI+BzwJ8BQJM0itVrNMKQpN5HXFC0ZaXpmXgc8fqK2I0kqnQFgzxGm79GZJ0nSFpmUm7eOMG/VBG5HklQur6Hoin0lcF1n2h4UN3V9ddeqkiTNGlNx89ZXAO/Am7dKkjZDZp4TEfsDBwG7dSZfD1yQmYPdq0ySNFt481ZJ0rTXCT/ndx7rRMQrM/PT3alKkjRbTNg1RVDcvBVYe/PW/wO+B+ydme+YyO1IktTxlm4XIEma+SaspSgiHgq8D3gyxc1b+/DmrZJmkWaz6TCxXRARvxttFrDzVNYiSZqdvHmrJI1Bs9mkr69v3Q0F+/v7DUZTZ2fgScDtw6YH4M1bJUlbbCK7zz01M/sy80Iobt4KHAI8KyJOm8DtSNKUazQatFot2u02rVaLRqPR7ZLK5AfA1pl5zbDH1cAvulybJGkW8OatkjQG9XqdarW6rqWoXq93u6TSyMxjNzLv2VNYiiRplprI7nMjyszrIsKbt0qa0Wq1Gv39/V5TJEnSLLRFoSgiHrm2u9zGZOZtETGXYiS6y8a47gqwDLghM5+6JXVK0kSo1WqGIUmSZqEtvabozIg4IyKe1LlR671ExK4R8WbgcuCx41j3a4ExBShJ0uwTEX+NiL+M8PhzRPw2Ir4REUd0u05J0sy3paFoP+APwJeBOyLiZxHxfxHxhYg4MyIuB64FjgCel5mfHctKI2I34CnAmJaXJM1K3wDuQ3Ez8O91Hrd0pp0L7AD8MCL+qWsVSpJmhS3qPpeZ9wBvj4gPUgzJfTmwfeexHDgF+EFm/mmcq/4o8EZg69EWiIjjgeMB9thjj3HXLkma9rYFPpmZG9ygNSLeC2yXmX0R8QHgbcB3u1GgpA15PzfNVBMy0EJm3hUR9wXenZnXbMm6IuKpFDd9vTAi6hvZ5qnAqQBLlizJLdmmJGlaei7w6BGmnw6cD7wa+BLwyqksStLIvJ+bZrKJvE9RP7BkAtbzWOBpEXE18FXgsIj48gSsV5I0s1SAB4ww/QGsP36tBganrCJJo/J+bprJJjIUnQG8NyIeviUrycwTM3O3zFxMcZbw3Mx84UQUKEmaUb4OfDYijo2I/SPigRHxUopeAl/tLFMDxttFW9IkWHs/t0ql4v3cNONM5H2KPgcEcH5E/JziItgLgQszc/kEbkeSVA6vAVYBnwbmUBxjWsBnKK47BbgIeFlXqpO0Ae/nppksMifmcpyI2Bo4EHgE8PDOnw+k6P5wY2buPiEbGsGSJUty2bJlk7V6SdIwEXFhZk5El+mxbGsBsE/n5eWZuWIqtjvZPHZJ0tTa2LFrwlqKMvMu4Oedx9oNzwUeRhGWJEkat04I+l2365AkzV4TeU3RvWTm6sz8TWekOEmSxiUiDo2IcyLips7jJxsbmVSSpM0xqaFIkqTNFRHPA84B7gRO7jzuBs6JiOd0szZJ0uwykQMtSJI0kd4GvC0zlw6Z9rGIeAvwduBr3SlLkjTb2FIkSZqu9gG+McL0b7B+4IUJERE7dLrm/bXz5/YjLHNoRFwy5LEqIo7pzDstIq4aMu/AiaxPkjS5DEWSpOlqOfDQEaY/rDNvIr0Z6M/MfSluRv7m4Qtk5nmZeWBmHggcBqwAfjxkkf9YOz8zL5ng+iRJk8juc5Kk6erLwGciYhHrRzY9BDgJ+J8J3tbRQL3z/HSgAbxpI8s/E/jBbBkeXJLKzlAkSZqu3kZxr7uPAdXOtNXAfwPvmOBt7ZyZN3We/w3YeRPLPxf4r2HT3hcR76DT0pSZqye4RknSJDEUSZKmpcwcAP6jEzSG3rx15easLyLOAe47wqy3DttuRsSodzaPiF2AhwA/GjL5RIowVQVOpWhles8I7z0eOB5gjz32GOcnkCRNFkORJGnaiIgfj2EZADLzieNZd2YevpF1/j0idsnMmzqh5+aNrOrZwBmZuWbIute2Mq2OiC8AbxilhlMpQhNLliwZNXhJkqaWoUiSNJ3c0KXtngW8hOJeSC8BztzIss+jaBlaZ0igCuAY4A+TVKckaRIYiiRJ00ZmvrRLmz4Z+HpEHAdcQ9EaREQsAV6ZmS/rvF4M7A78dNj7/7czIEQAlwCvnJqyJUkTwVAkSSq9zLwV6Bth+jLgZUNeXw3sOsJyh01mfZKkyeV9iiRJkgRAs9lk6dKlNJvNbpciTSlbiiRJkkSz2aSvr49Wq0W1WqW/v59ardbtsqQpYUuRJEmSaDQatFot2u02rVaLRqPR7ZKkKWMokiRJEvV6nWq1SqVSoVqtUq/Xu12SNGXsPidJkiRqtRr9/f00Gg3q9bpd51QqhiJJkiQBRTAyDKmM7D4nqRQcUUmSJI3GliJJs54jKkmSpI2xpUjSrOeISpIkaWMMRZJmPUdUkiRJG2P3OUmzniMqSZKkjTEUSSoFR1SSJEmjsfucJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJM0CzWaTpUuX0mw2u12KNON481ZJkqQZrtls0tfXR6vVolqt0t/f7w2rpXGwpUiSJGmGazQatFot2u02rVaLRqPR7ZKkGcVQJEmSNMPV63Wq1SqVSoVqtUq9Xu92SdKMYvc5SZKkGa5Wq9Hf30+j0aBer9t1ThonQ5EkSdIsUKvVDEPSZrL7nCRJkqRSMxRJkiRJKjVDkSRJkqRSMxRJkiRJKjVDkSRJkqRSMxRJkiRJKjVDkSRJkqRSMxRJmvaazSZLly6l2Wx2uxRJkjQLefNWSdNas9mkr6+PVqtFtVqlv7/fmxNKkqQJZUuRpGmt0WjQarVot9u0Wi0ajUa3S5IkSbOMoUjStFav16lWq1QqFarVKvV6vdslSZKkWcZQJGlaq9Vq9Pf3c9JJJ9l1TpMmIp4VEX+MiMGIWLKR5Y6MiD9HxOUR8eYh0/eKiPM7078WEdWpqVySNBG8pkjStFer1QxDmmx/AJ4BfGa0BSKiApwCHAFcD1wQEWdl5qXAB4CPZOZXI+LTwHHApya/bEnSRLClSJJUepl5WWb+eROLHQxcnplXZmYL+CpwdEQEcBjwzc5ypwPHTFqxmpUcZVPqLluKJEkam12B64a8vh54FLAj8I/MHBgyfdcprk0zmKNsSt1nS5EkqRQi4pyI+MMIj6OnsIbjI2JZRCxbvnz5VG1W05yjbErdZ0uRJKkUMvPwLVzFDcDuQ17v1pl2K7BdRPR2WovWTh+phlOBUwGWLFmSW1iPZom1o2yubSlylE1p6hmKJEkamwuAfSNiL4rQ81zg+ZmZEXEe8EyK64xeApzZvTI106wdZbPRaFCv1+06J3WBoUiSVHoR8XTg48Ai4PsRcUlmPiki7gd8NjOPysyBiHg18COgAnw+M//YWcWbgK9GxHuBi4HPdeFjaAZzlE2puwxFkqTSy8wzgDNGmH4jcNSQ12cDZ4+w3JUUo9NJkmYgB1qQJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGrTLhRFxO4RcV5EXBoRf4yI13a7JkmSJEmz13QcknsAeH1mXhQRWwMXRsRPMvPSbhcmSZIkafaZdi1FmXlTZl7UeX4XcBmwa3erkrQlms0mS5cupdlsdrsUSZKke5mOLUXrRMRi4OHA+SPMOx44HmCPPfaY2sIkjVmz2aSvr49Wq0W1WqW/v9+7tkuSpGll2rUUrRURC4FvAa/LzDuHz8/MUzNzSWYuWbRo0dQXKGlMGo0GrVaLdrtNq9Wi0Wh0uyRJkqQNTMtQFBFzKALR/2bmt7tdj6TNV6/XqVarVCoVqtUq9Xq92yVJkiRtYNp1n4uIAD4HXJaZ/9XteiRtmVqtRn9/P41Gg3q9btc5SbNOs9n0O06a4aZdKAIeC7wI+H1EXNKZ9pbMPLt7JUnaErVazR8KkmYlr5uUZodpF4oy8xdAdLsOSZKkTRnpuklDkTTzTMtriiRJkmYCr5uUZodp11IkSZI0U3jdpDQ7GIokSZK2gNdNSjOf3eckSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokbVSz2WTp0qU0m81ulyJJkjQpvE+RpFE1m036+vpotVpUq1X6+/u9F4ckSZp1DEWSRtVoNGi1WrTbbVqtFo1Gw1AkSTPAbbfeyg1X/5VW9kJEt8uRJlcm1Rhg18X7ssOOO27WKgxFkkZVr9epVqvrWorq9Xq3S5IkbcJtt97KdVdcyv2bb2LBP/5MTw50uyRpUg1GLyu2248r2h8AHrRZwchQJGlUtVqN/v5+Go0G9XrdViJJmgFuuPqv3L/5Jhbe/sdulyJNiZ4cYOHtf+T+zTfxl/ZStn/0IcQ4W0gNRZI2qlarGYYkzWrNZnNWnfxpZS8L/vHnbpchTbkF//gzg3MWcP45Z/HoI44e13sNRZIkqbRm5YAyEXaZUyn15AARPfzmvO9x0GFPpVKpjP29k1iXJEnStDbSgDKSZrbMZNWKu8f1HkORJEkqrbUDylQqFQeUkWaJ8V5PBIYiSZJUYmsHlDnppJNmR9c5TZjFH72L9/5s9ZRsK959J1/+XWtKtqWReU2RJEkqNQeUmT5Wrkne//PVfPWPA1x/5yDze+H+O/TwoofO4TWPmjultVzw8q1YMGfm3OPp+jsH2f0jd3PeSxZQX+xP/PFyj0mSJGla+Jfvr+K8qwf42JHzeNjOFe5cnVz8tzbX3pFTXsuirexQVSaGImkWm23DzEqSZrfv/GkN7z1sHsc8cM66aQ+774YjiB37nZVcf+cgT9m3lw81W9y+MnnKA3r5zFPns8P8omXnopvavPXcVVx44yAr1iT7L+rhpEPnceQ+63/6Dgwm7/tZiy/+rsX1dyY7LQie8cBePn7UfKDoPveyR1R52yFz171+8cPmcMcq+NLvWsypBM9/8Bz+84lz6e0ptrtyTfLaH67ia39cQ0/A8x48h23nBt+4dA2Xv2brjX72W1ck//z1Ffzw8gG2mxe88TFVXvvo9a1jd7eSt/av5puXreH2lcl+O/Xw9kPm8oz9i321+0eKgQUOPX0FAHtuG1x2wkK2+8BdfO95Czji/sVnf8Jp9/Dr69vc/qatWTAnWLEm2e7ku/ju8xbwpM7++fj5LU65oMXV/xhk9217OPZhc3jT46rrPueadvK+n6/m9N+u4aa7kvvv0MNrDq7yiiXVdfXGu+/klKPm0by+zXf+tIZt5wYnHFTlxMdPbYvfWBmBpVlq7TCzb3/72+nr66PZbHa7JGlaiohnRcQfI2IwIpaMsszuEXFeRFzaWfa1Q+a9KyJuiIhLOo+jpq56aXbZZesefnj5ALet3HjL0G9uaHPe1W1++IIFnP2CBVzyt0GOO2vluvl3rk6ec8AcznvJAi56xVY86f69PO3/VvCXW9vrljnurFWcckGLdz1hLpe+aiHfevZ89t5+4z+NP/6bFrtsHZz/sq34+JPn8YkLWpx+yZp18990zmrO/PMAX3r6fH593FZsOzf45LKxXSv07p+upr5nLxe/Yive+Jgqr//xas78U7HuzOSf/m8Fv/17m689cz5/eNVC/mVJled+cyX9VxbDr190/FYAfOvZ87np9Qu54OVbMX9O8KhdK5x7VbHMyjXJr69vs+3c4BfXFvvi59cUfz5+zyJ8vquxig81V7O0by6XnbCQjx05l89c2OLdjfXXV738u6v49mUDfOap87nshIW845C5vOmcVXzuog0/67t/uppD9qhwySsWcuLj5vKWc1evq3e6saVImqVGGmbW1iJpRH8AngF8ZiPLDACvz8yLImJr4MKI+ElmXtqZ/5HM/NBkFyrNdp/9p3k8/9srWfSfd3HAoh4evVuFo/bt5ej9ejcYUWww4UtPn8+284pppxw1jyd9eQWX3zbIPjv03OuamvceVuG7fxngG38c4K2HVLj8tkG++Ns1fONZ83nmg4qWlvvv0MOjd9v4T+PH79HLmx9XtHTsu2OFL1zS4pyrBjjuEVXuaSWfubDFJ4+ax9P2K9a59PAK513d5pYVg5v87E95wBz+9VFFS8sDdqxw/g1tPtRscfQD5/DTa9o0r2vz9zdsve4zH//IKr++vs3Hf9Oib+9eFm1VTN9hfnDfhevD3WF7VTj7r0UQ+cW1bXbbJnjS/Xs596oBntj581G7Vda1Gn3wly2+/ZwF61rV9tq+h/celrzmB6s46bB5XHV7se8uPWErHrhTZd0yf751kI//psVxj1jfWvScA+bw8kcWr084uMonLmhxzpUD9O09/SLI9KtI0oRYO8zs2hsSOsysNLLMvAw2PoRrZt4E3NR5fldEXAbsClw66pskjdtj9+jlitcs5Dc3FCHgZ9e2eebXV/LkfXs567nz1/0/fdCinnXhAOCxuxc/zi9d3mafHXpYfs8g72ys5tyr2vzt7kEGBmHVAFyzaxFOLrqpaB154v3H91P4wPtu2JJ0v4U9XPWPYp2X3zZIqw2P3m3D7n613Sp89y+bDkW1Ye977O69vP28VQBccEObVht2/a+7Nlim1YZ9d9x469ahi3t5789a3LEqOfeqAfr26uXQxb3856+Klp9zrx7gqE4A+uPNg6wcgH/++gqGfiO2s9h/y+8ZZNmNbRJYcuo9G2xnYBAqw0q51/7aOvj7PVN/fdhYGIqkWWrtMLNeUyRNrIhYDDwcOH/I5FdHxIuBZRQtSrd3ozZpNujtCR6zey+P2b2X1z8Gvvy7Fi86YxU/u6bNE8Y4qtqxZ67i2jsG+eARc9lrux7mzwme+80VtNqbfu/GVCsbnjyJKFqthk+baIMJ286DC16+cISaNv7e2u4VqhVoXD3AuVcP8G+Pnsuhe1V4/rcHueYfg1x80yAfOqK3s53iw3zjWfN5wI73XvEO82Pd5/3VcfcenW/4Rx9eW3Dv/TVdGIqkWcxhZqVCRJwD3HeEWW/NzDPHsZ6FwLeA12XmnZ3JnwJOArLz54eB/zfK+48HjgfYY489xly/VGb7d7po3TykheGyWwa5c3WyzdziZ/ivrivSzoMWFcv+7JoBPnj4+m5s97SSK28f5MH3KeY/Ypfizx9fMbCu+9yW2meHHqoVaF7XXlcHwK9vGFsS+/X1bV510PrXv7p+YN16ltyvwj9WwaqBXPcZhlsbQNqDw6cHj9m9whl/GuCimwY5bK8KOy3o4UGLenjPT1dTrRTBCeCA+1SY1wtX3p4cte/ILVCPvF+x7LV3DPLUB0zMvpsODEWSpFkvMw/f0nVExByKQPS/mfntIev++5Bl/gf43kbqOBU4FWDJkiXT9Hyp1D1POO0envfgOSy5X4VFC4LLbxvkLeeuYrt5cOhe68NAAC8+YyXvPWwut61MTjh7FU/br5d9dih+yO+3Yw//+/s1PG6PCu2Ed5y3mvaQ/3H77NDDCx4yh1d9fxWrBpLabr3ctjL51XUDG4z4Nh5bVYNXPLLK285bzc4Lgwfs2MPpl6zhsuXtMQ3v/b2/rOETv6nwpPtX+OHlbb72hwG+8axiJLzD9qpw+N4VnvG1lXzwiLk8dOcKt69MfnVdm3m98PJHVtlpQbCwWgS9A+7Tw9xKsH1nNL7D9urlnY3VPHCnHu7TqeWwxb184oIW9cWVdS1gC6vBWx43l7f0ryKAw/euMDAIv795kItvavOBI+axzw49/L8D5/Dy767ig4cntd17uaeVXHhTm+X3JG963PQcXW5TDEWSJG1CFBcyfA64LDP/a9i8XTrXHAE8nWLgBkmb4cn79PK/v1/DO85bzZ2rk/tsFRyyZy9fOHo+Oy1YHywO3rXC4/aocMSXVnDHquTJ+/Zy6lPnrZv/haPn84rvreLgz97DzlsFb3zsXFas2fA8xBeOnsd7frqat527mhvvWsV9tootbjX6wOFzWTWQPP9bK+kJeP5D5nDsgVX6r9r0iGvveMJczrlygDf+ZBXbzgs+eMRcnt4ZbjsiOOu5C3j3T1fzbz9axQ13JjvMDw68bw9vfGwRQnoiOOWoebyzsZoPN1vstk1w9euKYcAPXVzhrYNFEFrrsL0qfPT8DacBvP0Jc9ll6+ATv2nx+h8PMn8OPGDHHo592PoBFE79p3l8uNnifT9vceXtq9hmbnDAfXp49UFVZqrInPknqpYsWZLLli3rdhmSVBoRcWFmjjh89UwTEU8HPg4sAv4BXJKZT4qI+wGfzcyjIuJxwM+B3wNrO6e8JTPPjogvAQdSdJ+7GnjFkJA0Ko9dE8P7sd3bhRdeyCO/e1i3y5g0a+9TdM6Lt+p2KWNy2On3sP384FvPXtDtUkrhwn86l19+69Mcd+KH2GrrbTeYt7Fjly1FkqRSy8wzgDNGmH4jcFTn+S+49zXEa5d70aQWqFGtvR/b2lE2+/v7DUbqqt//vc1FN7Wp7V6h1YYv/XYN513d5gcvMBBNd968VZqmms0mS5cu9aarkjSKke7HJnVTBHxq2RoO+p97qH3uHs69eoAznjN/3T1/NH35NyRNQ579lKRN835s5XTaMfO7XcKoHnyfCr9+2czo1qcNGYqkaWiks5+GIknakPdjkzRR7D4nTUNrz35WKhXPfkrSRtRqNU488UQDUcnVT7uHl521ctTXZTOWz/+uxir2+e+7urLt6ciWImka8uynJEmb79vPWUDvNDz1f/2dg+z+kbs57yULqC+evJ/h3fz8m7Ptl521kstvG6RxbPe6HhqKpGmqVqsZhiRJ2gw7zB9xsMhZr9VOqpXo6uefqfveUCRJkqRp4SdXDPC+n6/md39v00448L4V/vOIeRy8a2XdMtf8Y5BXfG8lP72mzU4Lgjc+Zu691lM/7R722aGHzz5t/pjXe3credu5q/nWZWu4+Z5kl4XB8Y+s8pbHF+v/+92DvOmc1Xz/rwOsGkgeunOFpX1zOWTP4ud04+oBDj19BT9+4QJO+tlqlt3YZvF2PXz4iXN58r7FTVh3/8jdABx6+goA9tx2/Q1Wh7t1xSCv/P4qzv7rAAurwfGPmMO1dyY3DLlHU/20e7j/9j3cb+vgsxevIRP+9oat7/X5Vw0k//bDVXzlD2voCXjuAXPYbt6G4WXt/Z+esm8vH2q2uH1l8pQH9PKZp85fF3Qykw83W3zyghbX35nsvm3wrwdXed2j1/8dDN/22td7btvDKRe0aLWTpz5gDp98yjwWVoN3NVbxuYvXABDvvhMobqx77IFVPntRiw83W1x1+yAL5hQDWXzln+ez2zYT3wxmKJImiTcUlCRpfO5uJa86qMrDdu5hYBA+8usWR375Hv76rwvZcUEPmcnTv7aCSg80XrKAub3Bf/xkFRfd1GafHUb/oTyW9T71Kyu49o5BPv7keTx05wrX3znIn28p7tW8ck1y6Okr2H9RDz94wQK2mxd87Q9rOOJLK7jkFVux/6L14eoNP1nFBw6fx/23D97/ixbP+eZKrnldL9vPDy46fiseceo9fOvZ83nM7hUqG2lUeemZq/jTLYN873kLuM9WwYeaLb7zpzUcdL/KBst9/dI1vOAhc+h/8QLagyOv68RzVvOtywb44jHz2W+nHj570RpOuaDFfbbasIDf3NBmwZzghy9YwK0rk5d/dxXHnbWSM55T3Gfpkxes4e3nreZjR87j0MUV+q9q87ofrmLranDcI6qjfpZvXrqGlx5YpXHsAq69I3nuN1ew57bBSYfN4w2PmctfbxvkqtuTbz+nCFLbzg0uvLHNK7+3is8fPY8n7NnLnauT829oj77DtpChSJoEDqktSdL4PX3/ORu8PvWf5vGty9bww8vbvOChPfRf1ebivw3y51dvxQN2LMLBV54xnz0+evcWrffcq9r89Jo2F7x8K5Z0Qsfe2/dwyJ7F8l/74xruXJ187Znz6e0pgsRbD5lL/1UDfObCNXz0yPVB5Z1PmLvuvkQn983ltEvW8Jsb2jxpn14WdULIDvOD+y4cPcT99dY23/3LAOe8aAGH7lWs69SnzuOcKwfutewuC3v45FPm0RMjJ6x7WsmnlrX4+JPncfQDi/3woSdWaFw9wD9W5QbLDiZ86enz2bbTinTKUfN40pdXcPltg+yzQw8n/3I1/3pwleMfWQSgfXes8OdbBnnfz1dvNBTtuV0PHzlyHgAP3Amec8AczrmqzUnAwmowvzeoVnKDfXLtHYNsVYVjHjiHbeYW9Txk58pIq58QhiJpEjiktiRJ43fV7YO8o7Ga5nUD3HxPMpiwYg1cc0fRBHLp8qLL3NpABLBoqx7223Hj3ak2td4Lb2qz/TzWBaLhLrihzd/uTrY7ecPR2la3Yf6cDcPIgfddv46dF/ZQCfj7PaM04Yzi0uXF8o/ebf265lSCJfercNfqDYPMI+/XM2ogArji9kFWt+Exu2/42R63Ry/f+8uaDaY9aFHPukAE8NjOey5d3uY+WwXX35kcsueG63nC4gofO7/FijXJgjkj1/GwYWHmflv38KMr7h3whjri/r3svX0Pe33sbo7Yu8Jhe/XyjP172WnB5IwgYSiSJoE3FJQkzRbN6wZoXN2mvrhCbffJ/en41P9bwU4LglOOms/u2wbVSvC4z99Dq52bfvMkrncwYf9FPeu6kQ21YMNGKKoj5KrBzSx/I1lnna1GCSLTyfB9ErHpfbKwGix7+Vb88ro251w5wKeXtXjjT1bR/+KteOQo4XVLTMPBCqWZb+2Q2ieddJJd5yRJM1bzugH6vriCt5+3mr4vrqB53cbP7m+JW1cMcunyQd782CpP2qeXBy2qMK8Xbr5n/a/nBy2qcMuK5K+3rr+25JYVg/z51tFbYsay3kfuUuH2VbDsxpGvWVlyvwpX3j7INnNhnx16Nnjcb+ux/5xeGw5Gu/Zn/ecs1tm8bn09A4PJhaPUtzH3376HagV+dd2G7/3lCH+Xl90yyJ1DWqLWvudBiypsMzfYbZvgZ9dsuJ6fXt1mr+1j1FaisahWYKR8WukJDtmzl/ccOo8Lj9+KXbbu4Su/X3PvBSeALUXSJHFIbUnaOAekmf4aV7dptYsfrK128XqyWou2nx8sWhD8z0VruP8OPdy6InnjOauZP6Qlpm+vCg/buYcXnrGSjz95PtUKvOmcVczZSC4Zy3oP26vC4/eo8JxvruC/nlgMtHDjXYNcdssgL3tElRc8dA4f+XWLp3xlBe87bB4P2LGHv989yLlXtdl/UQ/HPHDO6AUMsdOCYGEVfnzFAAfcp4e5lWD7EYaw3nfHCv/0gF5OOHsVn3nqPBZtFXz4Vy3uXJ1jaj0aaqtq8MpHVnnbeavZeWGw3449fO7iNfz5lsF7DbQQwIvPWMl7D5vLbSuTE85exdP26103iMWJj5vL63+8in136KG+uMK5V7X51LIWpxw1b3xFDbPXdj1849IB/nhzm50XBltXgx9ePsCVtw9yyJ7FtVgX3tjmujsG1wXGiWYokkbggVqSJpcD0swM9cUVqpUiEFUrxevJ0hPBN541n9f8cBUP/dQ97LldD+8/bC5vOmfVumUigu88dwHHf3clh3zhHnZaEPzHY6qs3kgD1ljX+/3nL+At/at45fdXceuKZNdtgld0BhSY1xv89NgFvO3c1bz0zJUsvydZtFVw8K6VdYMqjPUznnLUPN7ZWM2Hmy1222b0Ibm/cPQ8XvG9VTz5f1ewsBq8cskcjrh/L6s2o7Hu5MPnsmogedEZK4FioIMTDqryjUs3bHU5eNcKj9ujwhFfWsEdq5In79vLqU9dH3j+Zckc7mkl7//Fal51drL7NsHJh8/d6CALY3HcI6qcd3Wbx3z+Hu5cXXz2vbfv4bvnD/D+X7S4a3Wy+7Y9vO2QLd/WaCJzy/poTgdLlizJZcuWdbsMzRIeqKVNi4gLM3NJt+uYycp+7Fq6dClvf/vbabfbVCoVTjrpJE488cRulzUrXHjhhTzyu4dN2Pqm8pqiiVL73D08atcKHz1yy1owppP2YPLAU+7haQ/o5cNPmvjPtfY+RWvvgTRTXfhP5/LLb32a4078EFttve0G8zZ27JoZ/7KlKeTIcZI0+RyQZuao7d47Y8LQyjXJH24e5I83t3n5I8bWpW26+tk1xUh5D79vhbtayUd+3eLqfwxy7IEz+3NNVzPjX7g0hTxQS9LkWzsgjV2VNZG+9sc1vPaHq/in/Xp5wUNmdnhoD8J7f7aay28bZE4FHnyfCue9ZMGk3qunzAxFmnW29HogD9SSNDUckEYT7dgDqxx74ORcczLVDt2rl0teuXDKtnfaMfOnbFvTkaFIs8pEXQ/kgVqSJKk8vE+RZpWRrgeSJEmSNsZQpFll7fVAlUrF64EkSZI0JoYiTSvNZpOlS5fSbDY36/1rrwc66aSTHEpbkqQZ6NjvrOTwL94zaeu/u5Xs+l93ccEN7UnbxnCv+O5KXv+jVZtecAwme/+UldcUadrweiBJkvSxI+cxOIm30fzAL1az5H4VDtp16kZxe8cT5vKAT9zNCQdX2Xv7qW+TOPyL97DbNj2lH0xhY2wp0rTh9UCSNHNsacu+NJpt5wXbz48JX++adrJqIPnUsjW84pFTO1z3rtv00LdXL5+8oDWl29XY2VKkCbUlw2F7fyBJmhkmqmVfGsmx31nJ9XcOcs6Lt6J+2j3ss0MPe27bwykXtGi1k6c+YA6ffMo8FlZHD053rk62O/kuPve0eZzxpwH6rxrglY+s8vg9K6wcSJ54/w1/Ap/91zU89SsruegVW3HgfYsWpM9e1OLffrSK/hdvxS0rBjc6/+AxtDo9/YG9vOXc1XzoifNGXaZ+2j3svX0P99kq+OxFa2i1k+c+eA7//eR5zOsd+fOuaSdvP281X/rdGpbfk+yzQw9vO2Quz+/cp+nY76yk/6o20Ob0364B4LyXLKC+2BgwlHtDE2ZLD5LeH0iSZoaRWvb9ztZk+eala3jpgVUaxy7g2juS535zBXtuG5x02Ojh4pK/tUng5F+2OOnQuXzsyHlUK/ChX7V4+H0r9PZsGDCO2ncOT1jc4q3nrub7z1/AmX9aw2t+sIqznregE3gqm5i/aY/arcLf7k4uW95m/0Wjv+ebl67hOQfM4ecvXcDltw1y3Fmr2GrOaj5y5Mif9y39q/n8JWv49FPm8bD79vDNSwd44bdXsvNWQd/evXzsyHlcefsgu2wdfKyzjh0moSVupjMUaZ0tvenpRBwkvR5IkqY/W/Y1lfbcrmddIHjgTvCcA+ZwzlVtTtrIey66qU0l4H+fMZ8l91sfQK76xyC7bjNyIPjPI+Zx8P/cwwd/uZr3/HQ1px8zn8P37h3z/HOuHOBff7CKNe3kOQfM4X19G4aY3bYprlq58vbBjYaiHeYHn37qPCo9wf6LKrz3sOQ1P1jFew+by1bDWsdWrEn++zctPvKkeTzrgKJl6C2Pr3DBjW3e9/PV9O3dy7bzgmoF5vcG913olTOjMRQJmJiuEB4kJakcbNnXVHrYzhsGiPtt3cOPrhjY6Hsu/tsgj9+zskEgAlg5kGw7b+RgsOR+FZ62Xy9vOmc1n3rK+pAxlvntweRV31/FD16wgMXbBYectoJfXTfAY3Zf/1N7Xu/aGjb+eQ/etUJlSEvWY3evsLoNV9w+yEOH7YvLbxuk1YZD9txw+hP2rLD0F16/NB6GolliurTyeJCUpHKwZV9TpTqsUSWCTY5Od9FNbZ79oHsPprBoQQ+3rRz5zRfc0Kb/qgF6e2CnBfduTdrY/AtubLPX9sH9dygC14sfOodvX7ZhKFq73UUjrFvdZyiaBaZTK48HSUmS1E2rBpI/3TLII+937xahR+zSwyd+c+8WlD/d0uaor6zgxMfNZfk9yVv6V3PMA3vXXXu0qfnX35nsvs367e2xbdC4ZnCDbfz+74NUAh6+y8avQbrgxjbtwVzXWvSr69rMrcD9RxjKe58dephbgZ9d0+bB91m/3p9e0+bB91m/fLUStCdxmPPZwI6F08CWDms6EUNZe9NTSSoXh9TWbPW7vw8yMAiPHCF8PHmfXq76R3LdHesDy3V3DPLEL63ghQ+Zw1seP5e3PL7KTXcPcuqFa8Y0f6waVw/wuD0qbDN34y1Ft65ITjh7FZctb/P9v6zh7eet5hWPrN7reiKABXOC1zyqytvPW803/riGv9za5v0/X82ZfxrgLY+bu265vbYLLryxzRW3DXLLikHWmJDuZVq2FEXEkcDHgArw2cw8ucslbdSWdF2zlUeSNNUcUluz2cU3tbnf1sHOIwwqsP+iCvXFFb70uzW85fFzuXXFIE/68gqesLiX/3pSESIWbdXD6x5V5d0/Xc1T9u3lyf87+vwXP2wOC6vBbtsE1925Pmhde0ey69brt5+ZfOUPa3j/RkbMW+uZD5rD1tXgcV9YQaszaMPJh88ddfn3HTaXnoDX/WjVuiG5v/yM+fQNGQTi9Y+Zy+9vXsnDPn0396xxSO6RTLu9EREV4BTgCOB64IKIOCszL52M7W3ptThbemDxWh5J0nhNh+tIpcly2jHz1z1vHLvVvea/7ZC5vO2Q0UPCK5ZUecWS6qjz31Ofy3O/tZJ/e3SVHRf0cOkJC++1zEmHzVs35Pem5gMcdL8KV96eXHHbIIu3C774uzV8YEiQ+calAyysBs8+YNM/vXsC/vOJ8/jPUe5nNHT/AMypBCcfPo+TDx89cO29fQ8/e+m996XWm3ahCDgYuDwzrwSIiK8CRwMTHoom4kzZlh5YbOWRJI3HdOphIM1Ej9+zl3c+YS5X3j7IAffZ+PU9Y1XpCU45ah5P+coK1gwmz37QHB63x/qf2asHki8cPX+DUeU0vUzHULQrcN2Q19cDj5qMDU3EmbItPbDYyiNJGg97GEhb7vhHjt6StLmeeP9e/vTqe7cqAbzoYRO/PU2s6RiKxiQijgeOB9hjjz02ax0TcaZsIg4stvJIksbKHgbS7DVSd0FNjekYim4Adh/yerfOtA1k5qnAqQBLlizZrCE0JupMmQcWSZrZIuJZwLuA/YGDM3PZKMtdDdwFtIGBzFzSmb4D8DVgMXA18OzMvH0yarWVR5Im3nQMRRcA+0bEXhRh6LnA8ydrYwYaSRLwB+AZwGfGsOyhmXnLsGlvBvoz8+SIeHPn9ZsmuMZ1PHZJ0sSadvcpyswB4NXAj4DLgK9n5h+7W5UkaTbLzMsy889bsIqjgdM7z08HjtnioiRJU2Y6thSRmWcDZ3e7DkmShkngxxGRwGc6XbkBds7MmzrP/wbsPNKbJ+J6WEnSxJuWoUiSpIkWEecA9x1h1lsz88wxruZxmXlDRNwH+ElE/CkzfzZ0gczMTmi6l4m4HlbapEwGo5eeHOh2JdKUGoxeyMFNLzgCQ5EkqRQy8/AJWMcNnT9vjogzKO6t9zPg7xGxS2beFBG7ADdv6bakzVWNAVZstx8Lb/fqA5XLiu32Y3DVnWSO/5zTtLumSJKk6SgitoqIrdc+B55IMUADwFnASzrPXwKMteVJmnC7Lt6XK2of4O7tDyjOnEuz3GD0cvf2B/CXg97LTddcAcDceQvGtQ7/p0iSSi8ing58HFgEfD8iLsnMJ0XE/YDPZuZRFNcJnRERUBw/v5KZP+ys4mTg6xFxHHAN8Owp/xBSxw477gg8iD8PvI+sLiTCc+Ca5XKQwVV3ctNVl3Pl737Nfgc+it45c8a1CkORJKn0MvMM4IwRpt8IHNV5fiXwsFHefyvQN5k1SuOxw447ss1Bj+PH3/gcf/ndBfRUKkS3i5ImUQKD7Tb7PmQJRzzz/437/YYiSZKkWah3zhyOfO7xPO7Jz2LlPXd1uxxp0s3famsWbrs9PT3jbx01FEmSJM1SPT09bLP9jmyz/Y7dLkWa1uxkKkmSJKnUDEWSJEmSSs1QJEmSJKnUYnNubjTdRMRyiiFQR7MTcMsUlTPduS/Wc18U3A/ruS/W29S+2DMzF01VMbORx65xcV8U3A/ruS/Wc1+st9nHrlkRijYlIpZl5pJu1zEduC/Wc18U3A/ruS/Wc190n38H67kvCu6H9dwX67kv1tuSfWH3OUmSJEmlZiiSJEmSVGplCUWndruAacR9sZ77ouB+WM99sZ77ovv8O1jPfVFwP6znvljPfbHeZu+LUlxTJEmSJEmjKUtLkSRJkiSNaNaEoog4MiL+HBGXR8SbR5g/NyK+1pl/fkQs7kKZU2IM++LfI+LSiPhdRPRHxJ7dqHMqbGpfDFnunyMiI2LWjt4yln0REc/u/Nv4Y0R8ZaprnCpj+D+yR0ScFxEXd/6fHNWNOqdCRHw+Im6OiD+MMj8i4r87++p3EfGIqa5xNvPYtZ7HrvU8dq3nsWs9j12FSTtuZeaMfwAV4Apgb6AK/BZ40LBlXgV8uvP8ucDXul13F/fFocCCzvN/KfO+6Cy3NfAz4NfAkm7X3cV/F/sCFwPbd17fp9t1d3FfnAr8S+f5g4Cru133JO6PQ4BHAH8YZf5RwA+AAB4NnN/tmmfLw2PXuPeFx64Nl/PYlR67hi1TimPXZB23ZktL0cHA5Zl5ZWa2gK8CRw9b5mjg9M7zbwJ9ERFTWONU2eS+yMzzMnNF5+Wvgd2muMapMpZ/FwAnAR8AVk1lcVNsLPvi5cApmXk7QGbePMU1TpWx7IsEtuk83xa4cQrrm1KZ+TPgto0scjTwxSz8GtguInaZmupmPY9d63nsWs9j13oeu9bz2NUxWcet2RKKdgWuG/L6+s60EZfJzAHgDmDHKaluao1lXwx1HEWano02uS86Taq7Z+b3p7KwLhjLv4sHAA+IiF9GxK8j4sgpq25qjWVfvAt4YURcD5wN/OvUlDYtjfc7RWPnsWs9j13reexaz2PXeh67xm6zjlu9k1aOpr2IeCGwBHhCt2vphojoAf4LOLbLpUwXvRTdEOoUZ2B/FhEPycx/dLOoLnkecFpmfjgiasCXIuLBmTnY7cKksvPY5bFrGI9d63ns2gKzpaXoBmD3Ia9360wbcZmI6KVoVrx1SqqbWmPZF0TE4cBbgadl5uopqm2qbWpfbA08GGhExNUU/U7PmqUXrI7l38X1wFmZuSYzrwL+QnGgmW3Gsi+OA74OkJlNYB6w05RUN/2M6TtFm8Vj13oeu9bz2LWex671PHaN3WYdt2ZLKLoA2Dci9oqIKsXFqGcNW+Ys4CWd588Ezs3O1VizzCb3RUQ8HPgMxUFltva9hU3si8y8IzN3yszFmbmYoo/60zJzWXfKnVRj+T/yHYozbUTEThRdEq6cwhqnylj2xbVAH0BE7E9xYFk+pVVOH2cBL+6M5vNo4I7MvKnbRc0SHrvW89i1nseu9Tx2reexa+w267g1K7rPZeZARLwa+BHF6Byfz8w/RsR7gGWZeRbwOYpmxMspLs56bvcqnjxj3Bf/CSwEvtG5XvfazHxa14qeJGPcF6Uwxn3xI+CJEXEp0Ab+IzNn3RnpMe6L1wP/ExH/RnHh6rGz9IcoEfF/FD8odur0Q38nMAcgMz9N0S/9KOByYAXw0u5UOvt47FrPY9d6HrvW89i1nseu9SbruBWzcF9JkiRJ0pjNlu5zkiRJkrRZDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEXSBIuIoyJiMCIOHDLtZRFxV0QcvKn53ahZklRuHrtUdt68VZoEEXEesCIznxIRRwP/BzwtM88Zy3xJkqaaxy6VmS1F0uT4D+DJEfFG4H+Blww7aGx0fkQcHhGXRcTlEfG+Ka1cklRWHrtUWrYUSZMkIr4DHA38S2Z+eqzzI6ICXAY8Gbga+BnwH5n5q8mvWpJUZh67VFa2FEmTICIOAvqAAeCWcc4/CLgqM6/IzDbwReAZk1uxJKnsPHapzAxF0gSLiAcCZwNLgU8A74+I3rHOB3YDrhvy+lpg18muW5JUXh67VHaGImkCRcTuwI+BL2fm+4H3A7sAx49lviRJU81jl2QokiZMROwI/Aj4KfDvAJm5HPgo8M6I2HMT8xd2VnU9sPuQVe8B3DD5n0CSVDYeu6SCAy1I00znYtU/AUey/mLVN2XmL7pZlyRJo/HYpZmud9OLSJpKmdmOiBOA7wNzgK97UJEkTWceuzTT2VIkSZIkqdS8pkiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiTIiIWRsQNEXHQFG7zMxHx4TEuuzQi/h4RGRHHTnJpI23/tIg4ZzPe14iIz05GTVO9rc3dB1O1PkmSVB6GIk2IiHhTRLx3yKQ3Acsy84IpLOM9wCsjYu+NLRQRjwLeDBwP7AJ8bSKLiIj5EXFSRPw1IlZGxG0RcUFEvGbIYq8FnjWR2x3n9qeDSdsHkiRJ49Hb7QI080XEHOCZFEGIiJgH/Avw4qmsIzNviIh+4FXAGzay6L7AYGaeuSXbi4hqZrZGmPUp4FCKH/2/BbYBHg7sMaTWO7Zk25uwye1309r9Nsn7QJIkacxsKdK4RMQ2ETEYES+NiLMi4h7gVKA3M8/tLHYkMB/48bD3HtV574FDpr0sIu6KiIM3NX+MJZ4BvGAj9Z8GfAno6XSdy870ORFxcqfLXysiLo2I5w97byMiPtdphbkJuHaUzRwD/Gdmficzr8rM32bmaZn5nqF1DO3qtbarWkS8PSL+1mnd+WJELBzlc2xsubFsvxERn+985lsi4s6IOLUTaMezLSLiXyPiTxGxqtM69daI6B22rXvtt5G6u0XECZ19vzoibo6Ibw2Zd0RnXbdFxB0R8dNx/LuQJEkalaFI43UgEBTdz74MPBg4B/j4kGWeAFycmQND35iZZwM/Bd4HEBFHA/8NPD0zf7Op+WOs73zgvhGx/yjzXwu8DmhTdJ3bpTP9/cDLO/Me3PlsX46IvmHvfzawCOgDjhhlGzcBR0bEDmOsea1nAjsAdeC5wFPptL6Nc7mxbv+ZwI7A4ymC5DHA0vFsKyLeRdEqdyKwP8X+fQXwzmHr2eR+i4h3Ax8APgk8hCJcXzRkkYWdeTXgMcBfgR9GxI6b+JySJEkbl5k+fIz5QREaBoAlQ6a9G5g35PV3gK+N8v4lwCDwRuBu4FnjmT+G+rYBEnjKRpY5FhgY8noBsBp41bDlzgDOHfK6AfwF6NlEDY8FrqEIXr+jaEk7Boghy5wGnDNs3b8dtp5PAc1h0za53Bi33wCuBipDph0PrAK2Gsu2OvttBXDksGVeDPxjU/tt6D4AtgJWAm8Yx991D3A78IKR9qkPHz58+PDhw8dYH7YUabweDvw8M5etnZCZ78zMVUOWmU/x4/peOu87i6JF4A2Z+Y3xzI+IwyPisoi4PCLeN8Im1m53/jg+0z5AFfjZsOk/BQ4YNu3CzBzc2Moy85fA/SlaYE4Hdga+CZwVEbGRt/522OsbO+8d13Lj2P5vMrM95PUvgbmd945lWwdQ7OdvRcTdax/AZ4BtI2LRkPdtar8dAMxjWJfLoSJir4j4Uufv/k7gTmBbYM+NrFeSJGmTHGhB4/UI4OubWGY5RZere4liiO4+itamW8YzPyIqFN2nnkzRyvGziHhMZv5qyGJrt7t8Ux9kM90zloWy6Dr4q87jwxHxQoprmQ6hCFsjGT5oQzJyF9dNLreZ2x9vTWv/fBZFS9Bwtw15Pqb9tgnfo/g3cQJwXae2X1AEWkmSpM1mS5HGrHMR/gOBCzex6EXcu4WFiHggcDbFdSufAN4/7IL8jc4HDgKuyswrOi0cXwSeMWwzD6HoNnbxOD7a5RTd5w4ZNv0JwB/GsZ6Nuazz530maH0Tsf2DOkFzrcdQ7IcrxrjOP1K0zO2dmZeP8GhvagVDXNpZ1xNHmtm5buhBwMmZ+aPMXLt8t/anJEmaRWwp0ng8lOLfzKZC0Q8oWid2z8zrACJid4quUV/OzPd3ula9jOI6lk9uan5nvbtRtBCsdS3FAABD1YFfZOadY/1QmbkiIv4bOCkillN0GXsmcDSjD6Ywqoj4KfB/wDKKFqt9KAZy+Adw3njXN4nb3xE4JSI+BuwNnAR8JjPH2hp2d0S8nyK8JsWAG70UwfThmTnSIBEbW9eHgXdFxErgJxRd847KzKUU1w4tB14eEVd0av8gxXVIkiRJW8SWIo3Hw4EbM/PvG1soMy+juLj+RbDuLP+PKLpt/XtnmeXAR4F3RsSem5g/4rDUw3Wul3k+xTUt4/VW4H862/wD8ELghZnZvxnr+gHFaG5nA38GvkAxUtpjM/NeXQYnwVi3/03gLoouaF+l6J725vFsKDNPovg7ezlFmPwF8G8U3RvH6+0Ufw+vofg7+DFFd0061yM9i+J6p99RDKrwUYqR9iRJkrZIZGa3a9AsFBGPp/ihvU9mTsjZ/Ih4NPDuzHxS5/UrgH0z8w2d18+m+GF94Di7bpVORDSAyzPzZd2uRZIkqdtsKdKkyMyfUwzVvfcErvYCYO+IuH/nWpgXUwz/vdZc4KUGIkmSJI2H1xRp0mTmqRO8vnZEnAB8H5gDfD0zfzFk/pcmcnuSJEkqB7vPSZIkSSo1u89JkiRJKjVDkSRJkqRSmxXXFO200065ePHibpchSaVx4YUX3pKZi7pdhyRJE2FWhKLFixezbNmybpchSaUREdd0uwZJkiaK3eckSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokqWSazSZLly6l2Wx2uxRJkqaF3m4XIEmaOs1mk76+PlqtFtVqlf7+fmq1WrfLkiSpq2wpkqQSaTQatFot2u02rVaLRqPR7ZIkSeo6Q5EklUi9XqdarVKpVKhWq9Tr9W6XJElS19l9TpJKpFar0d/fT6PRoF6v23VOkiQMRZJUOrVazTAkSdIQdp+TJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEmlZiiSJEmSVGqGIkmSJEml1vVQFBGViLg4Ir7Xeb1XRJwfEZdHxNciotrtGiVJkiTNXl0PRcBrgcuGvP4A8JHM3Ae4HTiuK1VJkiRJKoWuhqKI2A14CvDZzusADgO+2VnkdOCYrhQnSZIkqRS63VL0UeCNwGDn9Y7APzJzoPP6emDXLtQlSZIkqSS6Fooi4qnAzZl54Wa+//iIWBYRy5YvXz7B1UmSJEkqi262FD0WeFpEXA18laLb3MeA7SKit7PMbsANI705M0/NzCWZuWTRokVTUa8kSZKkWahroSgzT8zM3TJzMfBc4NzMfAFwHvDMzmIvAc7sUomSJEmSSqDb1xSN5E3Av0fE5RTXGH2uy/VIkiRJmsV6N73I5MvMBtDoPL8SOLib9UiSJEkqj+nYUiRJkiRJU8ZQJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSNIM0m02WLl1Ks9nsdimSJM0avd0uQJI0Ns1mk76+PlqtFtVqlf7+fmq1WrfLkiRpxrOlSJJmiEajQavVot1u02q1aDQa3S5JkqRZwVAkSTNEvV6nWq1SqVSoVqvU6/VulyRJ0qxg9zlJmiFqtRr9/f00Gg3q9bpd5yRJmiCGIkmaQWq1mmFIkqQJZvc5SZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUaoYiSZIkSaVmKJIkSZJUal0LRRExLyJ+ExG/jYg/RsS7O9P3iojzI+LyiPhaRFS7VaMkSZKk2a+bLUWrgcMy82HAgcCREfFo4APARzJzH+B24LjulShJkiRptutaKMrC3Z2XczqPBA4DvtmZfjpwzNRXJ0mSJKksunpNUURUIuIS4GbgJ8AVwD8yc6CzyPXArl0qT5IkSVIJdDUUZWY7Mw8EdgMOBh441vdGxPERsSwili1fvnyySpQkSZI0y02L0ecy8x/AeUAN2C4iejuzdgNuGOU9p2bmksxcsmjRoqkpVJIkSdKs083R5xZFxHad5/OBI4DLKMLRMzuLvQQ4sysFSpIkSSqF3k0vMml2AU6PiApFOPt6Zn4vIi4FvhoR7wUuBj7XxRolSZIkzXJdC0WZ+Tvg4SNMv5Li+iJJkiRJmnTT4poiSZIkSeoWQ5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSZIkSSo1Q5EkSZKkUjMUSdIUajabLF26lGaz2e1SJElSR2+3C5Cksmg2m/T19dFqtahWq/T391Or1bpdliRJpWdLkSRNkUajQavVot1u02q1aDQa3S5JkiRhKJKkKVOv16lWq1QqFarVKvV6vdslSZIk7D4nSVOmVqvR399Po9GgXq/bdU6SpGnCUCRJU6hWqxmGJEmaZuw+J0mSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUDEWSJEmSSs1QJEmSJKnUxn2foojYD9gbmA8sBy7OzLsnujBJkiRJmgpjCkURsRh4FfAC4L5ADJk9EBG/AD4NfCMzc6KLlCRJkqTJssnucxHxIeAPwH7AW4EHA9sCc4FdgKOAXwEnA5dExCMmrVpJkiRJmmBjaSlaCDwgM28cYd7fO49zgLdFxLOA/YGLJq5ESZIkSZo8mwxFmfnKsa4sM7+xZeVIkiRJ0tRy9DlJkiRJpTbu0eeGiohHA88Adu1MugH4Tmb+aksLkyRJkqSpsNmhKCJOAg4Fvgic25m8B/DBiGhk5tsmoD5JkiRJmlRb0lL0HGC/4UNwR8TngD8BhiJJkiRJ096WXFM0AOw5wvQ9OvMkSZIkadrbkpai1wA/iogrges60/YA9gJO2NLCJEmSJGkqbHYoysxzImJ/4CBgt87k64ELMnNwIoqTJEmSpMk2rlAUEUsyc9na153wc37nIUmSJEkzznivKTo3Ig4daUZELJiAeiRJkiRpSo03FP078N2IeMbaCRHRExH/AlwxoZVJkiRJ0hQYV/e5zPxsRCwHvhwROwK3AkuBXYCPTnx5kiRJkjS5xj3QQmaeGRHvAT4DrAE+ASzNzFsmujhJkiRJmmzj6j4XEQ+NiO9StA6dCawGbjYQSZIkSZqpxttSdDHQAB6VmRdGxEHA9yNiUWa+YcKrkyRJkqRJNt5Q9NTM/MHaF5l5QUQcQnET150y89gJrU6SJEmSJtl4R59bPnxCZv4JeBzFTVwlSZIkaUaZkPsUZeZ1wJETU5IkSZIkTZ2JvE/Rbya0MkmSJEmaAt6nSJIkSVKpeZ8iSZIkSaXmfYokSZIklZr3KZIkSZJUat6nSJIkSVKpjav73NBANGSa9ymSJEmSNGONd0juEXXuU/T4iViXJEmSJE2lTYaiiHjkWFaUmbdFxNyI2H/Ly5Kk6afZbLJ06VKazWa3S5EkSRNoLNcUnRkRFwCfBn6SmYPDF4iIXYEXAScA7wYum9AqJanLms0mfX19tFotqtUq/f391Gq1bpclSZImwFhC0X7Am4EvA/Mi4mLgBmAVsANwALAXxah0z8vMX0xOqZLUPY1Gg1arRbvdptVq0Wg0DEWSJM0Sm+w+l5n3ZObbgd0oWoOWAfOAXYA7gVOAAzKzz0Akabaq1+tUq1UqlQrVapV6vd7tkiRJ0gQZ85Dcmbka+E7nIUmlUqvV6O/vp9FoUK/XbSWSJGkWGVMoioj3AOdmZmOiNhwRuwNfBHYGEjg1Mz8WETsAXwMWA1cDz87M2ydqu5K0uWq1mmFIkqRZaKxDct8NfDAiLoyIYyOiOgHbHgBen5kPAh4NnBARD6K4fqk/M/cF+juvJUmSJGlSjCkUZeYHgccCvwVawIlbuuHMvCkzL+o8v4tixLpdgaOB0zuLnQ4cs6XbkiRJkqTRjPnmrZm5BngW8MvMfPdEFhERi4GHA+cDO2fmTZ1Zf6PoXjfSe46PiGURsWz58uUTWY4kSZKkEhlzKOo4FzhoIguIiIXAt4DXZeadQ+dlZlJcb3QvmXlqZi7JzCWLFi2ayJIkSZIklch4Q9EZwEkR8fCJ2HhEzKEIRP+bmd/uTP57ROzSmb8LcPNEbEuSJEmSRjLeUPQ5ipu5nh8R/RHx1og4MiLG3VQTEdFZ32WZ+V9DZp0FvKTz/CXAmeNdtyRJkiSN1ZjvU9SxHXAg8AiKa4CeA7wTqETEjZm5+zjW9ViKm8H+PiIu6Ux7C3Ay8PWIOA64Bnj2OGuUJEmSpDEbVyjqjBL3884DgIiYCzyMIiyNZ12/AGKU2X3jWZckSZIkba7xthTdS2auBn7TeUiSJEnSjDLea4okSZIkaVYxFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEkqhWazydKlS2k2m90uRZIkTTO93S5AkiZbs9mkr6+PVqtFtVqlv7+fWq3W7bIkSdI0YUuRpFmv0WjQarVot9u0Wi0ajUa3S5IkSdOIoUjSrFev16lWq1QqFarVKvV6vdslSZKkacTuc5JmvVqtRn9/P41Gg3q9btc5SZK0AUORpFKo1WqGIUmSNCK7z0mSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEma9prNJkuXLqXZbHa7FEmSNAv1drsASdqYZrNJX18frVaLarVKf38/tVqt22VJkqRZxJYiSdNao9Gg1WrRbrdptVo0Go1ulyRJkmYZQ5Gkaa1er1OtVqlUKlSrVer1erdLkiRJs4zd5yRNa7Vajf7+fhqNBvV63a5zkiRpwhmKJE17tVrNMCRJkiaN3eckSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklZqhSJIkSVKpGYokSZIklVpXQ1FEfD4ibo6IPwyZtkNE/CQi/tr5c/tu1ihJkiRpdut2S9FpwJHDpr0Z6M/MfYH+zmtJkiRJmhRdDUWZ+TPgtmGTjwZO7zw/HThmKmuSJEmSVC7dbikayc6ZeVPn+d+AnbtZjKQt12w2Wbp0Kc1ms9ulSJIk3UtvtwvYmMzMiMiR5kXE8cDxAHvssceU1iVp7JrNJn19fbRaLarVKv39/dRqtW6XJUmStM50bCn6e0TsAtD58+aRFsrMUzNzSWYuWbRo0ZQWKGnsGo0GrVaLdrtNq9Wi0Wh0uyRJkqQNTMdQdBbwks7zlwBndrEWSVuoXq9TrVapVCpUq1Xq9Xq3S5IkSdpAV7vPRcT/AXVgp4i4HngncDLw9Yg4DrgGeHb3KpS0pWq1Gv39/TQaDer1ul3nJEnStBOZI16yM6MsWbIkly1b1u0yJKk0IuLCzFzS7TokSZoI07H7nCRJkiRNGUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEmSJEkqNUORJEmSpFIzFEnaqGazydKlS2k2m90uRZIkaVL0drsASdNXs9mkr6+PVqtFtVqlv7+fWq3W7bIkSZImlC1FkkbVaDRotVq0221arRaNRqPbJUmSJE04Q5GkUdXrdarVKpVKhWq1Sr1e73ZJkiRJE87uc5JGVavV6O/vp9FoUK/X7TonSZJmJUORpI2q1WqGIUmSNKvZfU6SJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiSJElSqRmKJEmSJJWaoUiaxZrNJkuXLqXZbHa7FEmSpGnL+xRJs1Sz2aSvr49Wq0W1WqW/v9/7DUmSJI3AliJplmo0GrRaLdrtNq1Wi0aj0e2SJEmSpiVDkTRL1et1qtUqlUqFarVKvV7vdkmSJEnTkt3npFmqVqvR399Po9GgXq/bdU6SJGkUhiJpFqvVaoYhSZKkTbD7nCRJkqRSMxRJkiRJKjVDkSRJkqRSMxRJkiRJKjVDkTRNNZtNli5dSrPZ7HYpkiRJs5qjz0nTULPZpK+vj1arRbVapb+/31HkJEmSJoktRdI01Gg0aLVatNttWq0WjUaj2yVJkiTNWoYiaRqq1+tUq1UqlQrVapV6vd7tkiRJkmYtu89J01CtVqO/v59Go0G9XrfrnCRJ0iQyFEnTVK1WMwxJkiRNAbvPSZIkSSo1Q5E0SRxSW5IkaWaw+5w0CRxSW5IkaeawpUiaBA6pLUmSNHMYiqRJ4JDakiRJM4fd56RJ4JDakiRJM4ehSJokDqktSZI0M9h9ThqBI8dJkiSVhy1F0jCOHCdJklQuthRJwzhynCRJUrkYiqRhHDlOkiSpXOw+p1mn2Wxu0ahvjhwnSZJULoYizSoTdT2QI8dJkiSVh93nNKt4PZAkSZLGy1CkWcXrgSRJkjRedp/TtOL1QJIkSZpqhiJNG14PJEmSpG6w+5wmVLPZZOnSpTSbzXG/1+uBJEmS1A22FGnCbGlLz9rrgda+3+uBJEmSNBVsKdI6W9LKA1ve0rP2eqCTTjpps7vOSZIkSeNlS5GAibmeZyJaerweSJIkSVPNlqJZotutPGBLjyRJkmYmW4omwJYOIz0R758OrTxgS48kSZJmntKHom4HkokINCO18ox3Hd7fR5IkSWVV6lA0HQLJRAQaW3kkSZKkzVfqUDQdAslEDU5gK48kSZK0eaZlKIqII4GP/f/27j/U7rqO4/jz1ab1h1bg/EPcnEKTMouMqxj9UaCFM9igIjaQNCwhMirDflBgFNkv+kFkmdUw+6GZf8gFF4tqJf1QvCFIasmaprPAWSbB6Mf03R/nwL2Obferu+fzPTvf5wMG53u+39372ptz7uW1z/f7PcAq4NtV9dlJfJ9pKCQrVWhc5ZEkSZKem1RV3xmeIckq4AHgDcAe4C5ga1Xdd6i/Mzc3VwsLC8/p+x3pNUWSNERJfl9Vc33nkCRpJUzjStE5wK6q2g2Q5CZgM3DIUnQkXGGRJEmShm0aP6foZOCRJdt7xs9JkiRJ0oqbxlLUSZLLkiwkWdi7d2/fcSRJkiQdpaaxFD0KrFuyvXb83DNU1XVVNVdVcyeeeGKzcJIkSZJmyzSWoruADUlOS3IssAWY7zmTJEmSpBk1dTdaqKr9SS4HdjC6Jfe2qrq351iSJEmSZtTUlSKAqtoObO87hyRJkqTZN42nz0mSJElSM5YiSZIkSYNmKZIkSZI0aJYiSZIkSYNmKZIkSZI0aKmqvjMcsSR7gb8c5pA1wOON4kw7Z7HIWYw4h0XOYtFys1hfVX5ytiRpJsxEKVpOkoWqmus7xzRwFoucxYhzWOQsFjkLSdKQePqcJEmSpEGzFEmSJEkatKGUouv6DjBFnMUiZzHiHBY5i0XOQpI0GIO4pkiSJEmSDmUoK0WSJEmSdFCWIkmSJEmDNjOlKMkFSf6UZFeSjxxk//OT/Gi8/84kp/YQs4kOs7giyX1J7kny8yTr+8jZwnKzWHLcW5JUkpm9BXGXWSR52/i1cW+SH7bO2EqH98gpSXYmuXv8Prmwj5wtJNmW5LEkfzjE/iT56nhW9yR5deuMkiRN2kyUoiSrgGuAjcAZwNYkZxxw2KXAE1X1EuDLwOfapmyj4yzuBuaq6pXALcDn26Zso+MsSHI88D7gzrYJ2+kyiyQbgI8Cr62qlwPvb52zhY6vi48DN1fVWcAW4OttUzZ1PXDBYfZvBDaM/1wGfKNBJkmSmpqJUgScA+yqqt1V9V/gJmDzAcdsBr47fnwLcF6SNMzYyrKzqKqdVbVvvHkHsLZxxla6vC4APsWoJP+7ZbjGusziXcA1VfUEQFU91jhjK11mUcALx49fBPy1Yb6mqup24B+HOWQzcEON3AG8OMlJbdJJktTGrJSik4FHlmzvGT930GOqaj/wJHBCk3RtdZnFUpcCP5loov4sO4vxqUDrquq2lsF60OV1cTpwepLfJLkjyeFWD45mXWbxCeCiJHuA7cB720SbSs/2Z4okSUed1X0HUH+SXATMAa/rO0sfkjwP+BJwSc9RpsVqRqdIvZ7R6uHtSV5RVf/sM1RPtgLXV9UXk7wG+F6SM6vq6b6DSZKklTcrK0WPAuuWbK8dP3fQY5KsZnRKzN+bpGuryyxIcj7wMWBTVf2nUbbWlpvF8cCZwC+TPAScC8zP6M0Wurwu9gDzVfW/qnoQeIBRSZo1XWZxKXAzQFX9DngBsKZJuunT6WeKJElHs1kpRXcBG5KcluRYRhdGzx9wzDxw8fjxW4Ff1Gx+cu2ys0hyFvBNRoVoVq8bgWVmUVVPVtWaqjq1qk5ldH3Vpqpa6CfuRHV5j9zKaJWIJGsYnU63u2HGVrrM4mHgPIAkL2NUivY2TTk95oG3j+9Cdy7wZFX9re9QkiStpJk4fa6q9ie5HNgBrAK2VdW9ST4JLFTVPPAdRqfA7GJ0UfGW/hJPTsdZfAE4Dvjx+F4TD1fVpt5CT0jHWQxCx1nsAN6Y5D7gKeDKqpq51dSOs/gg8K0kH2B004VLZvQ/UUhyI6MyvGZ8DdVVwDEAVXUto2uqLgR2AfuAd/STVJKkycmM/p6XJEmSpE5m5fQ5SZIkSXpOLEWSJEmSBs1SJEmSJGnQLEWSJEmSBs1SJEmSJGnQLEWSJEmSBs1SJK2wJBcmeTrJq5Y8984k/0pyznL7+8gsSZI0ZH5OkTQBSXYC+6rqTUk2AzcCm6rqZ132S5IkqR1XiqTJuBLYmORDwA+Aiw8oPIfdn+T8JPcn2ZXk002TS5IkDYwrRdKEJLkV2Ay8u6qu7bo/ySrgfmAj8BBwO3BlVf128qklSZKGx5UiaQKSnA2cB+wHHn+W+88GHqyqP1fVU8ANwJsnm1iSJGm4LEXSCkvyUmA78Bnga8DVSVZ33Q+sBR5Zsv0wcPKkc0uSJA2VpUhaQUnWAT8Fvl9VVwNXAycBl3XZL0mSpPYsRdIKSXICsAP4FXAFQFXtBb4CXJVk/TL7jxt/qT3AuiVf+hTg0cn/CyRJkobJGy1IU2Z8o4U/AheweKOFD1fVr/vMJUmSNKtWL3+IpJaq6qkk7wFuA44BbrYQSZIkTY4rRZIkSZIGzWuKJEmSJA2apUiSJEnSoFmKJEmSJA2apUiSJEnSoFmKJEmSJA2apUiSJEnSoFmKJEmSJA2apUiSJEnSoFmKJEmSJA3a/wGaJjGzHz7WdgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x864 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "CoordSystem = \"SinhSpherical\"\n",
    "par.set_parval_from_str(\"reference_metric::CoordSystem\",CoordSystem)\n",
    "rfm.reference_metric()\n",
    "\n",
    "AMPL     = 10.0\n",
    "SINHW    = 0.2\n",
    "r_of_xx0      = sp.sympify(str(rfm.xxSph[0]                   ).replace(\"AMPL\",str(AMPL)).replace(\"SINHW\",str(SINHW)))\n",
    "rprime_of_xx0 = sp.sympify(str(sp.diff(rfm.xxSph[0],rfm.xx[0])).replace(\"AMPL\",str(AMPL)).replace(\"SINHW\",str(SINHW)))\n",
    "\n",
    "create_r_of_xx0_plots(CoordSystem, r_of_xx0,rprime_of_xx0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhsphericalv2'></a>\n",
    "\n",
    "### Step 3.a.iii: **`reference_metric::CoordSystem = \"SinhSphericalv2\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhsphericalv2}$$\n",
    "\n",
    "The same as SinhSpherical coordinates, but with an additional `AMPL*const_dr*xx_0` term:\n",
    "$$r(xx_0) = \\text{AMPL} \\left[\\text{const_dr}\\ xx_0 + \\frac{\\sinh\\left(\\frac{xx_0}{\\text{SINHW}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHW}}\\right)}\\right].$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:27.295510Z",
     "iopub.status.busy": "2021-08-29T17:43:27.294823Z",
     "iopub.status.idle": "2021-08-29T17:43:27.296999Z",
     "shell.execute_reply": "2021-08-29T17:43:27.296342Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhSphericalv2\":\n",
    "    # SinhSphericalv2 adds the parameter \"const_dr\", which allows for a region near xx[0]=0 to have\n",
    "    # constant radial resolution of const_dr, provided the sinh() term does not dominate near xx[0]=0.\n",
    "    xxmin = [sp.sympify(0), sp.sympify(0), -M_PI]\n",
    "    xxmax = [sp.sympify(1),          M_PI,  M_PI]\n",
    "\n",
    "    AMPL, SINHW = par.Cparameters(\"REAL\",thismodule,[\"AMPL\",\"SINHW\"],[10.0,0.2])\n",
    "    const_dr = par.Cparameters(\"REAL\",thismodule,[\"const_dr\"],0.0625)\n",
    "\n",
    "    r = AMPL*( const_dr*xx[0] + (sp.exp(xx[0] / SINHW) - sp.exp(-xx[0] / SINHW)) /\n",
    "               (sp.exp(1 / SINHW) - sp.exp(-1 / SINHW)) )\n",
    "    th = xx[1]\n",
    "    ph = xx[2]\n",
    "\n",
    "    # NO CLOSED-FORM EXPRESSION FOR RADIAL INVERSION.\n",
    "    # Cart_to_xx[0] = \"NewtonRaphson\"\n",
    "    # Cart_to_xx[1] = sp.acos(Cartz / sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2))\n",
    "    # Cart_to_xx[2] = sp.atan2(Carty, Cartx)\n",
    "\n",
    "    xxSph[0] = r\n",
    "    xxSph[1] = th\n",
    "    xxSph[2] = ph\n",
    "\n",
    "    # Now define xCart, yCart, and zCart in terms of x0,xx[1],xx[2].\n",
    "    # Note that the relation between r and x0 is not necessarily trivial in SinhSpherical coordinates. See above.\n",
    "    xx_to_Cart[0] = xxSph[0]*sp.sin(xxSph[1])*sp.cos(xxSph[2])\n",
    "    xx_to_Cart[1] = xxSph[0]*sp.sin(xxSph[1])*sp.sin(xxSph[2])\n",
    "    xx_to_Cart[2] = xxSph[0]*sp.cos(xxSph[1])\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(xxSph[0],xx[0])\n",
    "    scalefactor_orthog[1] = xxSph[0]\n",
    "    scalefactor_orthog[2] = xxSph[0]*sp.sin(xxSph[1])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.sin(xxSph[1])*sp.cos(xxSph[2]), sp.sin(xxSph[1])*sp.sin(xxSph[2]),  sp.cos(xxSph[1])],\n",
    "                   [ sp.cos(xxSph[1])*sp.cos(xxSph[2]), sp.cos(xxSph[1])*sp.sin(xxSph[2]), -sp.sin(xxSph[1])],\n",
    "                   [                 -sp.sin(xxSph[2]),                  sp.cos(xxSph[2]),  sp.sympify(0)   ]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we explore $r(xx_0)$ for `SinhSphericalv2` assuming `AMPL=10.0`, `SINHW=0.2`, and `const_dr=0.05`. Notice that the `const_dr` term significantly increases the grid spacing near $xx_0=0$ relative to `SinhSpherical` coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:27.321214Z",
     "iopub.status.busy": "2021-08-29T17:43:27.315572Z",
     "iopub.status.idle": "2021-08-29T17:43:28.942535Z",
     "shell.execute_reply": "2021-08-29T17:43:28.941905Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "CoordSystem = \"SinhSphericalv2\"\n",
    "par.set_parval_from_str(\"reference_metric::CoordSystem\",CoordSystem)\n",
    "rfm.reference_metric()\n",
    "\n",
    "AMPL     = 10.0\n",
    "SINHW    = 0.2\n",
    "const_dr = 0.05\n",
    "r_of_xx0      = sp.sympify(str(rfm.xxSph[0]                   ).replace(\"AMPL\",str(AMPL)).replace(\"SINHW\",str(SINHW)).replace(\"const_dr\",str(const_dr)))\n",
    "rprime_of_xx0 = sp.sympify(str(sp.diff(rfm.xxSph[0],rfm.xx[0])).replace(\"AMPL\",str(AMPL)).replace(\"SINHW\",str(SINHW)).replace(\"const_dr\",str(const_dr)))\n",
    "\n",
    "create_r_of_xx0_plots(CoordSystem, r_of_xx0,rprime_of_xx0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='cylindricallike'></a>\n",
    "\n",
    "## Step 3.b: Cylindrical-like coordinate systems \\[Back to [top](#toc)\\]\n",
    "$$\\label{cylindricallike}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='cylindrical'></a>\n",
    "\n",
    "### Step 3.b.i: **`reference_metric::CoordSystem = \"Cylindrical\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{cylindrical}$$\n",
    "\n",
    "Standard cylindrical coordinates, with $(\\rho,\\phi,z)=(xx_0,xx_1,xx_2)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:28.950831Z",
     "iopub.status.busy": "2021-08-29T17:43:28.950166Z",
     "iopub.status.idle": "2021-08-29T17:43:28.952076Z",
     "shell.execute_reply": "2021-08-29T17:43:28.951523Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"Cylindrical\":\n",
    "    # Assuming the cylindrical radial coordinate\n",
    "    #   is positive makes nice simplifications of\n",
    "    #   unit vectors possible.\n",
    "    xx[0] = sp.symbols(\"xx0\", real=True)\n",
    "\n",
    "    RHOMAX,ZMIN,ZMAX = par.Cparameters(\"REAL\",thismodule,[\"RHOMAX\",\"ZMIN\",\"ZMAX\"],[10.0,-10.0,10.0])\n",
    "    xxmin = [sp.sympify(0), -M_PI, ZMIN]\n",
    "    xxmax = [       RHOMAX,  M_PI, ZMAX]\n",
    "\n",
    "    RHOCYL = xx[0]\n",
    "    PHICYL = xx[1]\n",
    "    ZCYL   = xx[2]\n",
    "\n",
    "    Cart_to_xx[0] = sp.sqrt(Cartx ** 2 + Carty ** 2)\n",
    "    Cart_to_xx[1] = sp.atan2(Carty, Cartx)\n",
    "    Cart_to_xx[2] = Cartz\n",
    "\n",
    "    xx_to_Cart[0] = RHOCYL*sp.cos(PHICYL)\n",
    "    xx_to_Cart[1] = RHOCYL*sp.sin(PHICYL)\n",
    "    xx_to_Cart[2] = ZCYL\n",
    "\n",
    "    xxSph[0] = sp.sqrt(RHOCYL**2 + ZCYL**2)\n",
    "    xxSph[1] = sp.acos(ZCYL / xxSph[0])\n",
    "    xxSph[2] = PHICYL\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(RHOCYL,xx[0])\n",
    "    scalefactor_orthog[1] = RHOCYL\n",
    "    scalefactor_orthog[2] = sp.diff(ZCYL,xx[2])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.cos(PHICYL), sp.sin(PHICYL), sp.sympify(0)],\n",
    "                   [-sp.sin(PHICYL), sp.cos(PHICYL), sp.sympify(0)],\n",
    "                   [ sp.sympify(0),  sp.sympify(0),  sp.sympify(1)]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next let's plot **\"Cylindrical\"** coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:29.108296Z",
     "iopub.status.busy": "2021-08-29T17:43:29.017750Z",
     "iopub.status.idle": "2021-08-29T17:43:29.454197Z",
     "shell.execute_reply": "2021-08-29T17:43:29.453473Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x864 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np                  # NumPy: A numerical methods module for Python\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D  # Needed for projection=3d below.\n",
    "\n",
    "R = np.linspace(0, 2, 24)\n",
    "h = 2\n",
    "u = np.linspace(0,  2*np.pi, 24)\n",
    "\n",
    "x = np.outer(R, np.cos(u))\n",
    "y = np.outer(R, np.sin(u))\n",
    "z = h * np.outer(np.ones(np.size(u)), np.ones(np.size(u)))\n",
    "\n",
    "r = np.arange(0,2,0.25)\n",
    "theta = 2*np.pi*r*0\n",
    "\n",
    "fig = plt.figure(figsize=(12,12)) # 8 in x 8 in\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
    "\n",
    "ax1 = plt.axes(projection='polar')\n",
    "\n",
    "ax1.set_rmax(2)\n",
    "\n",
    "ax1.set_rgrids(r,labels=[])\n",
    "\n",
    "thetas = np.linspace(0,360,24, endpoint=True)\n",
    "ax1.set_thetagrids(thetas,labels=[])\n",
    "\n",
    "# ax.grid(True)\n",
    "ax1.grid(True,linewidth='1.0')\n",
    "ax1.set_title(\"Top Down View\")\n",
    "plt.show()\n",
    "\n",
    "ax2 = plt.axes(projection='3d', xticklabels=[], yticklabels=[], zticklabels=[])\n",
    "#ax2.plot_surface(x,y,z, alpha=.75, cmap = 'viridis') # z in case of disk which is parallel to XY plane is constant and you can directly use h\n",
    "\n",
    "x=np.linspace(-2, 2, 100)\n",
    "z=np.linspace(-2, 2, 100)\n",
    "Xc, Zc=np.meshgrid(x, z)\n",
    "Yc = np.sqrt(4-Xc**2)\n",
    "\n",
    "rstride = 10\n",
    "cstride = 10\n",
    "ax2.plot_surface(Xc, Yc, Zc, alpha=1.0, rstride=rstride, cstride=cstride, cmap = 'viridis')\n",
    "ax2.plot_surface(Xc, -Yc, Zc, alpha=1.0, rstride=rstride, cstride=cstride, cmap = 'viridis')\n",
    "ax2.set_title(\"Standard Cylindrical Grid in 3D\")\n",
    "ax2.grid(False)\n",
    "plt.axis('off')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhcylindrical'></a>\n",
    "\n",
    "### Step 3.b.ii\" **`reference_metric::CoordSystem = \"SinhCylindrical\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhcylindrical}$$\n",
    "\n",
    "Cylindrical coordinates, but with\n",
    "$$\\rho(xx_0) = \\text{AMPLRHO} \\frac{\\sinh\\left(\\frac{xx_0}{\\text{SINHWRHO}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWRHO}}\\right)}$$\n",
    "and \n",
    "$$z(xx_2) = \\text{AMPLZ} \\frac{\\sinh\\left(\\frac{xx_2}{\\text{SINHWZ}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWZ}}\\right)}.$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:29.461980Z",
     "iopub.status.busy": "2021-08-29T17:43:29.461364Z",
     "iopub.status.idle": "2021-08-29T17:43:29.463759Z",
     "shell.execute_reply": "2021-08-29T17:43:29.462949Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhCylindrical\":\n",
    "    # Assuming the cylindrical radial coordinate\n",
    "    #   is positive makes nice simplifications of\n",
    "    #   unit vectors possible.\n",
    "    xx[0] = sp.symbols(\"xx0\", real=True)\n",
    "\n",
    "    xxmin = [sp.sympify(0), -M_PI, sp.sympify(-1)]\n",
    "    xxmax = [sp.sympify(1),  M_PI, sp.sympify(+1)]\n",
    "\n",
    "    AMPLRHO, SINHWRHO, AMPLZ, SINHWZ = par.Cparameters(\"REAL\",thismodule,\n",
    "                                                       [\"AMPLRHO\",\"SINHWRHO\",\"AMPLZ\",\"SINHWZ\"],\n",
    "                                                       [     10.0,       0.2,   10.0,    0.2])\n",
    "\n",
    "    # Set SinhCylindrical radial & z coordinates by default; overwrite later if CoordSystem == \"SinhCylindricalv2\".\n",
    "    RHOCYL = AMPLRHO * (sp.exp(xx[0] / SINHWRHO) - sp.exp(-xx[0] / SINHWRHO)) / (sp.exp(1 / SINHWRHO) - sp.exp(-1 / SINHWRHO))\n",
    "    # phi coordinate remains unchanged.\n",
    "    PHICYL = xx[1]\n",
    "    ZCYL   = AMPLZ   * (sp.exp(xx[2] / SINHWZ)   - sp.exp(-xx[2] / SINHWZ))   / (sp.exp(1 / SINHWZ)   - sp.exp(-1 / SINHWZ))\n",
    "    Cart_to_xx[0] = SINHWRHO*sp.asinh(sp.sqrt(Cartx ** 2 + Carty ** 2)*sp.sinh(1/SINHWRHO)/AMPLRHO)\n",
    "    Cart_to_xx[1] = sp.atan2(Carty, Cartx)\n",
    "    Cart_to_xx[2] = SINHWZ*sp.asinh(Cartz*sp.sinh(1/SINHWZ)/AMPLZ)\n",
    "\n",
    "    xx_to_Cart[0] = RHOCYL*sp.cos(PHICYL)\n",
    "    xx_to_Cart[1] = RHOCYL*sp.sin(PHICYL)\n",
    "    xx_to_Cart[2] = ZCYL\n",
    "\n",
    "    xxSph[0] = sp.sqrt(RHOCYL**2 + ZCYL**2)\n",
    "    xxSph[1] = sp.acos(ZCYL / xxSph[0])\n",
    "    xxSph[2] = PHICYL\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(RHOCYL,xx[0])\n",
    "    scalefactor_orthog[1] = RHOCYL\n",
    "    scalefactor_orthog[2] = sp.diff(ZCYL,xx[2])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.cos(PHICYL), sp.sin(PHICYL), sp.sympify(0)],\n",
    "                   [-sp.sin(PHICYL), sp.cos(PHICYL), sp.sympify(0)],\n",
    "                   [ sp.sympify(0),  sp.sympify(0),  sp.sympify(1)]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next let's plot **\"SinhCylindrical\"** coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:29.557048Z",
     "iopub.status.busy": "2021-08-29T17:43:29.515810Z",
     "iopub.status.idle": "2021-08-29T17:43:29.762610Z",
     "shell.execute_reply": "2021-08-29T17:43:29.762032Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oqpu2tjZcvHgRhBB0d3djbGwMTqfz0PvdbjeWlpbi3tfHCpPJhOHhYTz//PPUk08+eUEmk/3sUVMTPVIXQ1EUXyKR9P/e7/1e+Ze//GW2QqFAdXU1HhZBCwoKkJaWBqXyV7lrh8OB0dFR9PX1QSQS4YknnkBVVVVMwYxHXcoXqyooPT0d9fX1ePLJJ8Hn89HV1YWZmRl4PB7mPXNzc5DJZMcipD8Ik8mEoaEhtLa2QiQS4Xvf+x730qVL75LJZP/+UJZpIfDIkJOiKK5UKr378Y9/vPZrX/sas9x+mASlUyuLi4vY2dnB1NQUuru7kZqaimvXrqGsrCwumdmjTM5ESPbomtkrV67A5/Oho6MDi4uLMJvN0Ov1qKqqSuAVR4a9xKRz5fQetK2t7f0ymewfj/2iQuCRIadMJvvxe9/73ub//t//+6Go7MMkaGpqKtLT09Hd3Q1CCK5evcrYZsQLkUgEs9kMv/+R2uoAAHZ3d0EIQUZG/LLU1NRUNDU14cKFC7Barejt7YVIJIrrwRYLghGTBpvNxr/927/xampqPpqfn/+lY72wEHgkyJmfn/8HlZWVH/j2t7/NDbWqeBgENRgM6OzsZGRyCoUCKSmJs1DlcrkQCATY2tpK2JiJAp0GSuQqLyMjA0VFRUhLS4PL5cKdO3dgtVoTNn44hCMmDS6Xi5/85Ce8/Pz8/5vH4105lgsLg4dOTjabfUEoFP7Pl156iXfUk/S4COr1ejE+Po7x8XE0Nzfj9OnTqK6uxvT0dMItTR7VpW0yqlD8fj9mZmbQ3NyM9vZ2lJSUoK+vDwsLC0ktQI+EmDSysrLwn//5n3yxWPwqRVHHk3wNgYdKToqiFBKJ5PpLL73EjzTKmWyCGgwGdHV1gRCCK1euID8/HwBQXFwMj8cDnU6X0PM9iuQMBAIwmUwJJ+fy8jJycnIgFApBURQUCgUuX76Mra0t3LlzJymR62iISaOqqgrf+9730iUSSR9FUccfsXqAh0bOB+qfvu985zsZkdpR0EgGQb1eLyYmJjA+Po6mpqZDAgI6ODQzM5PQPWJubi52d3f3RTIfNiwWC1MNkyg4nU6srKygrq5u37+npqbizJkzKCkpQW9vb0Jn0ViISeOpp57C5z//eZFUKr31sFIsD+WkFEWxZDLZm5/5zGcK3vve98Y0RiIJurW1he7ubgQCAVy5ciVkUlwkEiErKwsrKytxnW8vWCwWcnNzYTKZEjZmvEjGknZ2djakKGHvLGo2m3Hnzh3s7sbXoT4eYtL44he/yL569eoJiUTy/8V1MTHioZCzqKjo+QsXLrT+8R//cVzhukQQVK1WY2BgAA0NDWHldjTq6uqwsrISNLEeK/Lz8x+ppS0dDEoUtra2YDKZUFFREfZ9qampOHv2LORyOXp6emJ2jEgEMYH7D42///u/58rl8udycnJ+I+aBYsSxkzMrK+sjUqn00z/84Q9DRmajQawEDQQCmJqawtLSEs6fPx9xrWJ6ejoUCkVC3eIfJesSr9cLi8WSMFd3QgimpqZQW1sbkd6WoiiUlpbi1KlTGB0dxcrKSlRBuEQRkwafz8fPfvYznlAo/P5xu/odq7aWoihFcXHxP/7sZz/jJXI/Q4vH+/r60N7efqTqxOPxYHh4GABw8eLFfdUikaCyshIdHR3Y2tpKyE2cmZkJv98Pu92O9PTgtquEEHg8HsbNwOl0Mq4Ge61KAGB0dBQsFgtsNjuogwKXyw2ZIjGbzcjJyYmISJFgfX0dFEVBKpVGdZxQKMSFCxcwODgIm82GxsbGI/OiiSYmjYKCAvz7v/97yvvf//5bFEXJCSH2hA0eBsdGToqiKJlMduOv//qvU4qKihI+fqQEtdlsGBwchFgsRm1tbUzVEBwOBzU1NZiamsLFixfjzgXudYNPT09HIBCAzWZjnAksFgtsNts+stFES09PB5vNBovFAkVR0Gg0yMvLAyEEPp8PLpcLVqt1nz0JcD9lQDsvZGVlITMzExRFJXS/6fV6MTs7i7a2tpi+o/T0dJw/f56RS7a2tobMMyeLmDROnTqF5557TvDDH/7whwA+kvATBMGx2ZTk5+d/4cqVK//jxRdf5CVTvqhWqzE/Px+UoJubmxgdHUVtbW3cpVqEENy5cwelpaX7ennEOtb8/Dw2NjbA4XCws7ODtLS0fZ4+WVlZEc1mkdiUeDyefX5FVqsVLpcL2dnZ2NnZQUNDAyQSSdwPndnZWbhcLpw8eTKucejvZ319HW1tbYc8hpJNTBo+nw9nz551j46OvtPv999O2oke4FjISVFUcUlJyezQ0FBqXl5e0s8XjKBarRZTU1M4ffp0wvZTW1tbGBoawrVr16JeBvp8PhiNRuj1emxuboLL5cLhcODs2bPIzs6OeVkZrYcQDa/XC71ej/HxcfD5fFAUBbFYDLFYHFPzIrvdjjt37uDy5csJc3sI9hseFzFpTE1N4d3vfve2RqORJXt5m/RlLUVRlFQqvf43f/M3KcdBTODwEtdisWBmZibhzm60W/zi4mJErQMIITCZTFCr1djc3GQsUSorK5Geno7Ozk6w2eyE7feiAZfLBSEEYrEYp06dws7ODnQ6Hebm5rC7uwuJRAKFQhFxSdz09HTCbVgkEgnYbDYGBgZw+vRpEEKOlZgA0NDQgOeeey7zBz/4QdKXt0m/C4RC4RfOnTtX9oEPfOBYS3Fogt65cwdsNhvt7e0QCAQJP09tbS26u7uhUChCBnO8Xi/W1tagVCrBYrGgUCjQ2Nh4KBBF7ztzcnISfp2RYG/LBYFAAIFAgKqqKjidTqytrWFwcBB8Ph8lJSUMUYLBYDDAZrPh1KlTCb9GsViMlpYWDAwMgBCCtra2YyMmja997Wuc11577X1sNvuy3+/vTtZ5kppKoSiqJDMz8//+27/926TuM8OcHxRFJdVtIJxbvNPpxOTkJG7evInt7W2cPHkSV65cQVlZWdAI8cOU8oUrEUtNTUVVVRWefPJJVFVVQaPR4ObNm5ifn4fX6933Xtp6pK6uLmlVJywWi4lMP4z7is1m44c//CG/sLDw5WS6ySeNnBRFsaRS6Y3/9b/+V8pxdULeC61Wi9nZWVy4cAG1tbVJFcuXl5czNpLA/YDLzMwMurq6wGazceXKFZw6dQq5ublhb6a8vDxsb28fS8ezg9jZ2QGbzQ45+wNg9qHt7e1ob2+Hw+FAR0cHlpeXGUmjWq0Gn89PiGt7MNB7zLa2NrS2tmJwcPChVPXU19fjU5/6lEAul/9Tss6RNHKKRKIvnj9/vuR973vfsT/adDodpqamcPbsWWRmZiZdLM9ms1FXV4epqSksLi6io6MDXq8XV65cQV1dXcT7Li6Xi6ysrIdys0WbQhEIBDh58iTa29thNpvR0dGB1dVVzM3NhWx4Gy8OBn/y8/Nx4sQJDAwMHFvp2V589atfZYvF4vew2eykGO4mhZwUReWmpqb+2Xe+851jX85arVaMj48fCrknk6B0TtFut0Or1eL8+fNobm6OKRjysKR8sUr2BAIB2tra0NLSgsXFRQBgcqmJRKiorFgsRmNjIwYGBpJy3nBgs9n4h3/4B15RUdGLFEUlfA2fFHKWlJR8+7d/+7fTIo3sJQputxuDg4NoaGgIGlRJBkGdTicGBgawsrKC5uZmuN3uuKo5Hsa+MxAIwGw2xxVY4XK5CAQCaGhoYGphD+5HY8VR6RKJRAKZTIahoaFjd5WoqqrC+fPnc3Nycn430WMnnJwURUlZLNYHn3jiCaqrqwubm5uJPkVQBAIBDA0NQSKRhJWKJYqghBCsra2hu7sb2dnZuHTpEmQyGQoLC7GwsBDzuNnZ2bDb7XC73TGPES22traQkZERtYyRBu3aXlVVBZlMhitX7psIdHV1xa0ZjjSPWV1dDR6Ph8nJyYQXxAcD/ft3dHTgd37nd9hpaWn/g6KoxNlkIAnkVCgUf/9Hf/RHvAsXLjD7sP7+/rhLgI7C1NQUuFwuampqIrnGuAi6d7Zsb29HdXU1k6Svrq6GRqOJmfgsFgtCofBYZ894JXubm5twOp2MazuXy0VzczOam5sxPj6OiYmJmGbRaAQGFEWhpaUFFotln1tiMkAXh6tUKrS1teGJJ57AM888k5afn/+VhJ6IFkwn4gWgpqGhwenz+QgNv99PlpaWyPXr18nU1BTxeDwk0VhdXSUdHR1Rj61Sqcjrr79ObDZbxMcYDAZy48YNMjc3R/x+f9D3LC8vk76+PhIIBKK6HhorKytkdHQ0pmN//vOfR33M7du3icFgiOl8Pp+P3Lx5k2xubgb9u8fjIaOjo+TmzZtRfc9Go5Fcv36dGI3GqK5nd3eX3LhxI+T1xAOHw0GGh4fJ66+/TtbW1vb9vmazmchksl0AWSRBfErozCmXy//5m9/8Zsre/BaLxUJ5eTmuXLkCr9eLjo4OqFSqhC09TCYTFhYW0NbWFrUjXjQzKCEESqUSIyMjaGlp2TdbHkRJSQkcDkfMS3p635mo7ygcvF4vbDZbzJLG1dVVZGRkhAwmcblcnDhxApWVlejp6YFerz9yzHgkeenp6Uy5WaJWa36/HwsLC+jq6mIMxGUy2b6IdG5uLn7nd34nRSKR/D8JOSkSqK2lKOrM2bNnu3t7e/nhIrQWi4XpxVhfXx9XEIJuuHry5Mm4ioPDieWBX9V+ms1mtLW1hc0F0tjc3MTU1BSuXr0atS6VEII333wT586d22dNSRMpWLdr8qCz9fb2NqOFDdbFWiAQ7BMH6HQ6KJVKtLe3R3WNwP2obFdXFy5cuBCRhSatRS4tLUV5eXnQdEuitLKrq6tYW1vDxYsXY+7DQgjBxsYGZmZmkJOTg9ra2rC/vdPpRF1dnVOpVJYRQuI2m0oIOR+Ugy3++Mc/Lr906dKR7z/4oevq6sL21AiFkZER8Hi8hHRcDkVQt9uNoaEhcLlcnDx5MqrZub+/H0KhEOXl5VFfz+joKHg8HlJSUpjqEZfLBYFAgLS0tH1lY3w+HywWCywWC3fv3sW5c+fg9/sPdbG22+1MzShd6WI2m5GdnX2kS0EwjI2NgcfjHfIFCgd6v56ZmYnm5uZ9D4pEitgJIbh37x7y8vJiMq+me5J6vV40NDREfD3f+c53An/1V3/1ilqt/mDUJz2AhJCTy+W++4knnnj5+vXrYWfNg/D5fFheXsbq6ipKSkpQUVERsehbp9NhZmYGly9fTphQ/CBBHQ4H+vr6UFRUhJqamqgT6zs7O+jp6cHVq1cjSq/srVTZ2NgAAMhkMqb9XkZGxpGzwFFVKX6/n6kVtVgsWF9fB5/PR1FRUVQVKBaLBf39/bh27VrU2wmfz4fx8XE4nU6cOXMGXC43KdUlDocDt2/fxrlz5yLWVbvdbszNzUGv16O6uhoKhSKq393n86GxsdE1NzfXQAhZjvXagQSQ88GsqXnttdeKGhsbYxrD6XRiZmYGZrMZdXV1R9YS0svZ1tZWJLrShSZoc3MzJiYmUFZWhrKyspjHm56ehs/nC9lOnRACs9kMtVoNvV7PVKrk5uair68PTz31VFTLsmhKxhwOB7q7u9He3o7NzU3o9XrY7XZIpVIoFIqQFTyEEPT09EAul8dcF0sIweTkJCwWC6qqqjA2NpaU6hK1Wg2lUnnk8jYQCGB1dRVLS0uQyWSoqqqK2dX/3//938lXv/rV20qlMi5j6kRMOedramryYiUmcF9YferUKZjNZkxNTUGpVKK+vj5kdcbk5CQkEknCiQncDxK53W709/ejqqoqLmIC95PUHR0dsFgs+8qtfD4f1tfXsbq6yrjPNTQ07Ms1pqWlJdTP5yBoVRA9M1dVVcHhcGBtbQ0DAwOMqL+wsHDfja3VauH3+yGXy2M+N0VRaGxsxNDQEAYHB3H69OmkVJfI5XJsbGxgaWkp6PKWEILNzU1MT08zzgvxNld69tlnqW9+85ttFEUVxrP3jDtaW1JS8r/+8A//MCGGQHl5ebh06RLkcjkGBgYwOjp6SJK1sbEBi8USUT4zFjgcDqhUKkilUqjV6riVRFwud59bvN/vx8rKCm7dusU0pg1VqZJstVCw/GZaWhqqq6vxxBNPoKysDEqlEp2dndBoNIxMcXZ2NiH6WbPZDJPJBLFYjIWFhYQpivaCoig0NzdjdXX1kP52Z2cH/f39mJmZQUNDA6PFjhdsNhv/7b/9N75EIvlaPOPEtaylKEpRX18/Pzk5mZJoDa3X68Xi4iLW1tZQXl6O0tJS+P3+pC1ngfvRx7t376K0tBRlZWVHRnEjBSEEXV1dEAqF2NzcRGZmJmpqao4s/DYYDFhcXMT58+cjPleky1pCCF5//XVcunTpyGCc0WjE7OwsCCHIzMxEIBBAa2trxNcUDHv3mHl5eZicnITNZkN7e3tSSs32Lm99Ph8WFhag0WhQWVmJkpKShHfWttlsqK+v311fXxcRQmIS/cZ1RTKZ7M+fe+65pIjbuVwu6urqcOHCBWxtbaGrqwujo6MoLCxMCjH9fj8GBwchk8mYpWyipH4WiwWBQABqtRpNTU04c+ZMRI4Mubm5sFgsSZlRrFYruFxuRFFykUiEixcvQqFQQKPRMJHfWHEw+EMvcVNTUzE+Pp6U/K5cLgeXy8Xo6Cg6OzsRCARw9epVlJWVJaXlvUAgwLvf/W5+Zmbmb8U6RsxXRVFUKoAPP/fcc0kt2M7IyEBbWxsqKyuxubkJm82W8J4ahBBMTEwwRcV7EQ9B/X4/ZmdnMTAwgOrqahQUFGB7ezvi4zkcDnJycmA2m6M6bySItgqFoiiYzWZUVlZCLBbjzp07UCqVURMpVFSWXn7u7OxgeTmuIGfI8zqdTuh0Opw+fRpNTU0JbTcRDF/60pe42dnZ34z1+JiJlZaW9utPPfUUL5EeMeFgNBpRWVkJiUSC3t5eTE5OJqy/CL0fOXHiRNB9VCwEtVgsuH37NnZ2dnD58mVIpVLU19djdXU1Krf4ZO07o9XTms1mbG1toaKiAhUVFTh//jzW19fR19cHh8MR0RhHpUs4HA7a2tqwurqasIIJu92OwcFBjI2Noba2FmKx+NhaXzzYjmVTFNUSy/Exk1MkEv3ZZz/72fg7yEYA2mWA3nteu3YNAJgC33ga3xgMBiwtLaGtrS1svjQagiqVSvT396OyshKnT59mvFbT0tJQXFwclVt8Msjp9/uxtbUVcXSUBHFtz8zMxPnz55Gfn4/bt28fSaZI85ipqalobW3F6OhoXFsJOnB1+/ZtZGVl4dq1a0y+emVl5dgaRz333HMpJSUlfx7LsTGRk6Ko6oKCgoL6+vpYDo8ac3NzqKioYPJOPB4PjY2NOHfuHHQ6Hbq7u2MqTbLb7RgdHUVra2tEe6+jCBoIBDAxMQGlUokLFy5AKpUemokrKipgMpkidjvIzs6Gy+U6NNsSQuB0OmEymWAwGKDT6aDRaADcF2gYDAaYzeagpWdbW1sQCAQR5/HW1tbAZrMhkUj2/TuLxUJFRQXa2towPj6O5eXloMvcaAUGubm5qKurw8DAQNT7bUII1tfX0dHRAafTiStXrqCqqooJMmVkZKCwsBBLS0tRjRsrPvzhD8Pv91+NxWsopjynXC7/6ic+8Ymo1ECxwmw2Y2dnJ2h0UCAQoL29HXq9HhMTExAIBKirq4tI50kIwdjYGMrLy6MKMIVylqdlfhwOBxcuXAh543M4HNTW1kbsFk9RFPLy8qDVapGenr7PCJo8aAvPZrMZ13fgPpn8fj98Ph92dnbA5XL3GVRvbm5GvKT1er2Ym5vDmTNnQl5rbm4uLl68yNiF7JXlxar8kcvlMJvNmJ2dRVNTU0THbG1tMSmr1tbWkPnhqqoqdHV1obS0NKHWncHA4/Hw3ve+l/vP//zPvwHg76I5NupUCkVRbKlUapmfn8+IRAAeDwghuHv3LkpKSo50Vff7/VhdXcXy8jLkcjkqKyvDzgyrq6uMpUgsD5m9aRY2mx2VzI/+XMXFxSET+YFAAAaDAevr6zAYDAgEAhAKhYxgIDs7GykpKYfOdTCVQgiB3W7f19rBZDKBz+ejoKAAcrk8rPHYzMwMPB4PTpw4uocPLctzuVxoa2uD1WqNS5Ln9XrR1dWF5ubmsMErp9OJ2dlZmEwm1NTUHKoYCYbZ2Vm43e6IPle8mJubw1NPPbWmUqmiklPFMnO2NTc3c5JNTOB+0MLn80XUBIfNZqOiogIymQxzc3Po6OhATU0N5HL5oR/KbrdjYWEBFy5ciDmRTs+gPT09TFlcpGoiiqLQ0NCAgYEBFBYW7nuIOBwOKJVKrK+vIy0tDXK5HKWlpRgcHAw7e4U7V0ZGBjIyMiCVSuHxePDmm28ykj06dUFL8fZGMHd3d7G2tsY4GxwFDoeDlpYWTE5O4s6dO3C73XEpf+ii7fHxcVy5cuXQw5YWdKysrEChUODq1asRL9UrKipw8+ZNVFVVxVR0EQ2qq6uRnp4uoihKRAiJOIAQNTllMtnvPP300wm1YwiF1dVVlJWVRXVDpqSk4MSJE9je3makgA0NDczSlV7OVlRURLT8DQeRSMSoZqItWcvJyUF+fj4WFxdRV1eH7e1trKyswGAwQC6X49y5c/uED3QPlXiNsY1GI4RCIWMaXV5eju3tbajVanR0dEAikaCsrAwZGRmYmZlBeXl5yOZBwUBRFIqKirC2toa0tLS4Hfbz8/MhEokwMzPD6JMJIUzhQ1ZWFi5evBhRGd9ecLlcyOVyKJXKqKpqYgFFUXjiiSe4Kysr7wXww0iPizogRAh5/wc/GHc1zJHY3d3F9vZ21K3jaOTk5ODChQsoLy/H8PAwhoeH4XQ6mdxcvJpZl8uFvr4+VFVVob6+PqY8aG1tLdRqNfr6+jA0NIScnBw8+eSTqK+vP6RISlTU9mAKhaIo5Obm4sSJE7h69Sp4PB7u3r2L/v5+2Gw2lJaWRjW+yWTC8PAwzpw5A6FQiIGBgbhNt+rr62EwGGAwGGC1WtHX18cUJ5w+fTpqYtIoKSnB2trasfgEf+hDH+JIpdLPRHNMVOSkKKpcIpEcSzMipVIJhUIRl5SL7gt57do1ZGRkoLOzE7Ozs6ivr49LF0qriehZJpY8KHngsB4IBOBwOBgta6hlWSLISZ8zVDAoJSUFNTU1uHr1KsxmM5NyiRR7gz8ikQiNjY3g8/lxq35ob6jh4WFmb3/58uW4WxWmp6cjNzcX6+vrcY0TCdrb2+H1eqspiopY+RAVOYVC4a+/+93vTq6sAr+q2KANo+IFh8NBdXU1pFIp+Hw+hoaGoNVqY7phaDVRSkoKqqurmX+PhqAulwuDg4NYWlrC2bNnmQZH4SASiWA2m+PK6TocDgQCgSN1wlqtFjk5OWhubsbo6CgmJiaOnF2CRWUpisKJEyews7ODlZWVmK45EAhgZWUFU1NTYLFYqKqqSqgWtrS0NKG2OaHAZrNx9uxZNoDLkR4T1SfMyMj4nWeffTbpreo3NjaQm5ub0DC30+lkorMnT57E0tISenp6YLFYohqHVhOdPHny0Ox7FEHpHFx3dzcEAgEuXbqEvLw81NfXY3p6OizxeDweMjIy4nKDNxgMTKOiUHC73VhYWEB9fT3EYjGuXLkCv9+Prq6ukA+QcOkSWvWzvLwctepnc3MTtL3q+fPn0drauq/1QyIgFArh8/mivg9iwQc+8AF+aWnp70f6/ohTKRRF5VRXV2tnZ2dTk53fvHv3LsrLyxPab2N8fJwR0wO/8h2dm5tDQUEBampqjgx80Pupixcvho3wBatm8fv9GBsbg81mw4kTJ/bVqhJC0NfXh8LCwrB7vNnZWVAUhZqaGgQCAezs7DD2JX6/n0knVVRUMH1PsrOzkZ6eDoqiMDg4iMLCwrBpqYmJCUaIvhd0Llkul6O6upoheKR5zK2tLQwMDERUBbO7u4vp6Wns7u6ivr4eBQUFzPkGBgYgFArjjhnsxeLiIhwOR8iC+ETBbrejqqpqR6vVZpEIiBfxLMjn899z7tw53u7ublKXADabDXa7HQUFBQkbk+41udcnhy5wpm02urq6sLy8HHL28vl8GBsbQ3Nz85E318EZ1OfzYWBgAIFAAJcuXTpURE6nVhYWFkLKyjweDwghUKvVuHPnDq5fv47h4WGYTCYEAgFwOBxmpcFms+H3+7GxsYG+vj5cv34dPT092NzcZMQJwWCz2bCxsbFvuU5DLBbj8uXLMBgMjHFzNAKD3NxclJeXY2xsLOT94/V6MT09jbt370IoFOLq1asQi8X7ZvqamhosLS0ltFKHLshORvUPDUIIvF4vKisrUwBEpKqIOJUil8v/4OLFi+y+vj5QFAWRSMS8Eqnu1+l0kEgkCS3jWVhYCNl2j8vlor6+HgqFAjMzM1CpVIee1sD9WSs3NxdisTiic9J50N7eXqSkpEAgEKC5uTnk5xIIBCgqKsL8/Dwza9EBHLVazSxJaUFAbm5u0ODRzMzMocoat9vNGF3rdDrMzs6iqKgICoWCeVDQ+tmqqqqQzu98Ph/t7e0YHBxEX18frFZrVHnMsrIybGxsQKVS7Ysn0A+d+fl5ZikdahUjEAiQn5+P1dXVmIy7giElJQU5OTkwGo0oKipKyJjA/T2+0WiEwWCAyWQCj8fDhQsXOIuLix8H8Pmjjo+InBRFsWUyWfXHPvYxsNls7O7uwmg0QqvVYmJiAmlpaUw+Kjc3Ny7DLZ1Oh0Rqdp1OJ+M4EA6ZmZk4c+YMY1mxurqK+vp6CAQCmEwm6HS6iJPxNCQSCRYXF7G7u4uTJ08e+cCpqalBR0cH5HI5bDYblpeXQVEUSkpK0NzcDC6Xi76+PgQCgaj8bfh8Pvx+P6RSKRoaGuB0OrG+vo6hoSGkpaWhvLwcgUAAbrcbxcXFYcficrkoLy/HwMAA8vLyopI+slgsnDx5Ej09PcjPz0d6ejpMJhOmp6fBZrNx5syZiDpnl5eXo6+vD+Xl5QkrzBaLxdDpdHGR0+PxwGQywWg0MgIakUiEgoIC1NfX0yWJ1I9+9KNnkShyAqgqLy9n7a1IyMzMRGlpKQKBACwWC4xGIxYXF2GxWJCTk8PMqtnZ2RGnLZxOJxwOR0I9c1ZXVyGTySK+mQsKCiASiaBUKtHb2wuJRAK9Xo+mpqaoeonQ6RahUIicnBzcu3fvSEcFHo8HuVyOnp4e5OTkoL6+/lAAJz8/HwaDIer9OF3VA9yv/KisrER5eTkzk9rtdpw4ceLIB4jJZMLo6CgT5JmcnERjY2PEv3FmZibKy8sxOjoKPp8Pi8WCuro6FBUVRTwGLaDQarVx+RjtRUFBAebn5xEIBCJetfn9fmxvbzOz4+7uLnJzcyESiVBcXAyBQHDoM0kkEnC53GyKoviEkLANcSKdOVuam5uD3pksFgu5ubnIzc1FVVUVvF4vzGYzjEYjxsbG4HK59i2BwyWMNzc3UVBQkLAlrd/vx9raGi5cuBDVcSwWC2VlZZBKpRgYGIDb7YbT6Yz4hyOEYGRkhJGf0R22D4rl9yIQCDC2LFwuFyUlJUFVRyKRCCqVKqrP4/P5GLPpg59TIpFgd3cXGo2GMfsOJnkEDgd/aIfA+fn5iD2dfD4fvF4vtra2IJPJcPXq1ZhWWqWlpVhYWEgYOdPS0pCamhr0e6JBCMHOzg4MBgOMRiPTAEokEqGurg45OTlHzuQURaGyshIrKysNAIbDvTeib6WkpOS9bW1tEa0fuFwuxGIxszdzOp3MND8/Pw82mw2RSIT8/HwIhcJ9s5Ferz9S4B4NdDodsrKyYpbpsVgsOBwOnDx5EiqVipECHpX8VqlUcDqd+0T1oapZgPv1qqOjo0hNTcXly5exs7ODyclJFBQUHPqxBQIBvF4vHA5HxJpQ2jg6GAlcLhdWV1dx4cIFBAIBjI6OYmNj41B/0WDBHy6XizNnzqC7uxsikSjs3pMQAq1Wi5mZGeTl5aGxsRFqtTrmZWlBQQEmJydhtVrjlgjSEIvF0Ov1+8i59/41Go3gcDgQiURQKBRoaWmJqTPbyZMn+R0dHa1IBDn9fv/ZWOz6gftLKLlcDrlczjx5jEYj1tbWMDY2xjx5cnNzYTab0dISU9F4UKjV6iP3UOGwsrICkUgEiUSCoqIi6HQ6jI+PIysrC3V1dUFXAQ6HA/Pz8zh37tyhGy8YQekZq66ujqmmSE1NRWZmJpMW2QuKoiAUCpkSMqvVCqvVCo/Hw0Sa7969Cz6fz5SI6XS6kA+U2dlZyOVy5gF28eJFLC0t4fbt24z5VrioLJ/PR1NTE8bGxnDlypWgD4Dt7W1MT0/D7/fj1KlTyMvLY1JZGxsbh+pEIwFFUZDL5VCpVBGXlB2FgoICjIyMIC8vj5kdPR4PhEIhRCIRLWCP+zxtbW0smUz2XgDfDfe+I/OcFEWxFQqFTalUpiU6vxkIBLC1tcUEl+x2OzOrikSioGv2SEG7fb/zne+MaZnsdrvR0dGBy5cv75uhDlZC7C0Cp/OV+fn5Ydsb0JFJhUIBtVqNs2fPHhK07+7u4u7du0zkkhACi8WCtbU1aDQaBAIBiEQihoA8Hg9sNhu3b9/G+fPn4XK5mNpPukSMfkjSRNze3sbAwEBQ13aDwYCRkRGUl5djeXn5yHTJ6OgoOBzOvvyoy+XC7OwsDAZD0Aoho9GIiYmJmPrJAPdnta6uLrzrXe+KeStE95eh943b29vIzs5GYWEh8vPzkZWVFbcF6EGYTCacPHnSsLa2FjZfGMnMWVlSUkIlQ3hA96IUCoVwuVzMjWM0GqFSqeDz+ZinVn5+flSKIb1eH9f+ValUoqio6NDSkc1mo7KykilN6+zsZGoIVSoV/H7/kb1RFAoFTCYTFhcX0dbWFrTSJCMjA3K5HLOzsxCLxVheXobb7YZcLkdbWxsGBwfR1tYW9Mahl2USiQQulwsdHR1oa2uDVqtFT08PsrOzUVZWhrm5OdTW1gYNluXn56OqqoqxJzkqXdLQ0IDOzk4UFhYiNzd3X21tqJYNIpEIKSkpTPosWqSmpiI9PR1mszlinS0hhMk2GI1GmEwmpKenMzOjVqtlglbJQl5eHrhcbgZFUTxCSEi/lCPJ+SAYlHSvoO3tbZSUlCA7O5sJZ9N5Ito3lcfjMYEloVAYNgKr1+tjXtL6/X6oVKqwnbdSU1Nx8uRJpvp+eXkZTqczIneD9fV1mEwmVFdXY3x8PGSQSCqV4vbt29je3kZNTQ0KCwuZsXk8Hmw225H7LZPJxESMc3JyUFNTA41Gg+HhYRBCQoo96NaKtDgiNzc3bNqEy+WiqakJIyMjYLPZEAgEEXUfKy0txcrKSkzkBH61TwxHTpfLxdi5GI1GJk8vkUjQ3Ny8L0/vdrsjalMYDx4EhajV1dV6AKOh3nckOYuLi9/T2tqamE5BIeDz+eBwOA7NIGlpaVAoFFAoFCCEMEZfdJ9MOiEtEomQk5PDzJJerxfb29s4ffp0TNej0+mQmZkZUe1kbm4uzp8/j66uLgD3pWC1tbUhZ/mtrS3MzMygvb0dAoEAfD7/UJCIEAKVSsUk5V0u1z5iAr9KqURiTL036kt7Ac3NzUEoFKK7uxtNTU37xBUH95gZGRkYGhrCpUuXQn4um82GlZUV+P1+ZGdno62t7cjvDrhPrunp6ZgDO2KxGIODg/sqjXw+H5MxMBqNcDqdyMvLQ35+PiorKxk5YzBkZ2djfn4+6uuIFidOnOB3dnaeRjzkDAQC7efOnUvohR2E1WpFZmZm2CUoRVGMPUdFRQVTzmQwGDA1NQW73Y68vDymADoeMUS0gSSj0QgWi4V3vOMdWF5eRldXF8rKyg4lyX0+H0ZHR9HY2MgQ/2CQKCUlBcPDw/B4PDh//jwyMjJw+/ZtaLXafbWtIpEIq6urjPG03W5nBOFTU1PIzMxEVlYWDAYDKisr913v0tISRCIRWlpaYDKZMDY2hs3NTTQ0NDA9NPfuMfPz81FSUoLx8fFDbgwejwfz8/PQarWoqqrCqVOn0NnZybQaPAosFgtyuRxqtfqQnjcSCAQCJhJMr7TofaNIJEJTUxOys7Mj3t5kZGTA7XbD4/HEFImNFHuCQiF9hcIGhCiKYsnl8h2VSpXwYNBerKysYGdnJy7hsdvtZtQZGo0GFEWhsLCQWQZHWs1PB5Le8Y53RBzm7+3thVwuZ9JAdrsdMzMzsFqtqKurY2a96elpuFwunDp16tAYarUac3Nz4PP5yMnJQWNjI3NDmc1mjIyM4OrVqyCEQKPRQK1Ww2q17msPyOFwMD4+jrq6Ouzs7MBsNjNBNrlcjqKiIrhcLty+fRuXL19mZkGfz4fBwUEEAgHYbLagkrxAIIA7d+6gpKQECoUCgUAAKpUKCwsLkEgkqK6uZm7m2dlZuhVexN95d3d3xIEdQggcDgezTN3c3ASHw4FUKkV+fj7y8vLiUqndvXsXVVVVcTVkPgpGoxGnTp3aVKvVIfWgR32CooPLqWTAarXGrQri8/n7Uh6nT5+GzWaDTqfD1NQUUlJSmMBSuB+PDiRFSkx61tq7Z0pPT8fp06dhMpkwNTXFqJQ0Gk1ICWBRUREWFhZgt9vR0tKy7ybNy8tDTk4O+vv7sbOzg7y8PNTU1GB+fh61tbX79lvj4+NMMGN1dRXb29soKCiAWq3GzMwM+Hw+SkpK9i1PORwOysvL0d/fzwhKDoKW3vX29oLFYmFpaQl8Pj9o78vS0lJ0dnbuI2w4pKWlHRnY8Xg8+/KNfr8f+fn5KCwsRFFREVQqVUKaKAP3l7ZWqzWp5HzQhiJsYe1R5CwsKChIuv+lxWKJ2g4jFJxOJ2MnmZeXh5KSEiYNYTQasby8jKGhIWbZQ0sMaTJEG0haWVlBaWlp0Ce+UCjE5cuXoVQqMTExETLiSQjB4OAgCgoKkJWVdUjqt729DavVCofDgXPnzjGBGToNFeqGNhqNkEgkkEqlkEqlUKlUmJycBIfD2bfsNJlMGBkZwZkzZ7C8vIypqamguUMWiwUej4fx8XG0tLQc2gfTSElJQWFhIVQq1aEldSgcDOzs3bYYjcZ925bS0lJkZmYy5/Z4PIzbQiImkuzs7GMJCj3Y+6YTQoI2njmSnGKx+FiCQYlovQbgUB9M4P4XQUcrKysr9wUMJiYmmIBBXl4etra2Iu6g5fV6odfrwwr1KYqC3+9HQUEB0tLS0NnZeaizFd0bhNao7pX66fV6rKysoL6+Hjs7O1AqlQw5RSIRJiYmkJGRAavVypSCzczMQCAQwGg0MiQjhECpVOLkyZNwOp24c+cOoxc+KMnr6uqCXq9ngkR7O76VlZVBo9GAxWKFJYJCocDo6CgqKioiIkxBQQEGBgbA5/MZ022BQACRSISGhoZ9Ab+D4PF44PP52N3dTch9lJWVhYWFhbjHOQoPHtaFAII2hwlLPC6XKyksLEwqOW02G2OMnAgEI+dBcDgcFBQUMGkEl8vFlGbR7foiKYnTarVHlszRHZPpzmLFxcWYnp5mStPS0tKwvLyMS5cu7ZP6EUJw+/ZtpKSkMFFSn8+Hzs5O6HQ6WK1WqNVquFwu6PV65OTkgMfjYW1tDRwOB2q1GoFAAL29vcxKgMvlMl3D8/Pz0dvbi0AgwJhx0d/NiRMnMDIygpycHOj1eqYgnRZE0NccrnwuJycHFEVha2srZApmb6rMYDDA5/PBZrOhpKQEra2tUVXeZGdnw2KxJIScmZmZcLlc8Hq9MXe3jgQFBQUsxErOgoKCOolEktRlrcPhSIgkiobVao3aeyglJQUymYzZn4nF4n0lcXSSWiQSIS8vj3mQrK+vh1UCAYBGo2Eip8D9H/7s2bPY3NxkmjGVlZUdEjt4PB5wuVz4fD5mRqR1yUNDQ5DL5Th79ixmZ2chkUiYPe/4+DiqqqpACGGULsvLy8wMTz8A6MJiFot1qMCbzot2dHQwXd72FogXFRVhdnYW29vbIbuP0/K6tbU1hpxer3ffvtHr9TLfa21tLRYWFphrjhY0OROhzaYoCmlpaXA4HAnT7QbDg4kvZI1aWHKmpKRUJFKIHgxutzsqX9RwoPeWsX6hFosFRUVFh0riaHnXwsICrFYrcnJymBTGUcoUtVodVG1SUFCAsrIyrK6uYnV1FT6fD1VVVeByuTCZTFAqlbh06RI2NzfR19eH1tZWzM/Pw+v1IjMzEzk5ORAIBMjLy8P6+jqcTifTF2V1dRU6nQ41NTXIy8uDTqdDQUEBVldXsbOzg6KiIoyMjOD06dNMjWhWVhbS09PhdDoxMzODra0tUBSF2traQwRksVgoLi6GWq0OSU76M66srGBubg5GoxE2mw25ubnIz88PWlJFEywWZGVlJawzGXD/gR2sz0wiIZFIOBkZGSFd4MOSkxAiSzY5XS5XwpwUXC4XIxyPFnQa4SCxWSwWsx+trq5mSuLUajUA4M0339wnMdw7A+7u7oa0XCGEYHV1FSdOnEBGRgbjUl9RUYHV1VU0NTUhJSUFCoUCPp8PPT09kEgkOHPmDGw2G+7du4etrS1sbGwgEAgwJU/A/YeMzWbD+Pg4CgsLodVqce3aNaZtxNra2r6lLG0fkpeXx7gUNDc3Q6PRYHl5OWggSyaToaurC/X19Uzke29hAy2No21RampqkJubG3b7kp2dzXyv0YKOsCYqKMTn8+FyxdSQOmJIJBKIRKKQjtZhyenxeISJqpcLBZfLlbBgkNPpjNlaf3d3FykpKUfuMeiSOLvdjpSUFFRWVu4riaNLikQiEba3t0NarmxuboLL5TJ9Spqbm2GxWBgT5r03vE6ng1AohNFoxO7uLhP8sdlsuHr1Km7fvg2ZTAYOh4PZ2Vnk5+fD6XSiqakJvb29AO4v91ksFnZ3d5GdnY2NjQ3k5+eDEILU1FRsbW3B5/PtM+CSyWSYn5/H7u7uIRleamoqsrOzsb6+DjabzXwH9NJbLpfj5MmTGBoaYgrYj4JAIMDu7i78fn/UMQg6ZePz+RKyT0xJSUk6OaVSKTgcTsg0RVhyUhSVkuyeKC6XK2HL2nhm4UgCSQffLxQKg5bEGQwGqNVqGI1GpKamgs1mIz8/f18xLq1C2vuUp+1EamtrMTo6ipycHEZqdvbsWcbci8/n48yZMxgaGoJKpWICP/TMOTo6ipSUFKjVarBYLDQ3N2N4eJgJ/mRnZ6OrqwsrKyvY2NiA3+9HY2MjFhYW9v0WbDYbUqkUa2trqK2tBYB9xfRWqxVmsxlisThkSVVWVhYsFktEOUPaMdBms4VdLocCPdslipx2e9AMR8LwYFUUUlQckpwURbFLS0s5iTTaCoZEkzPWsaINTFkslkN7SYqiGAuNsrIyvP7666itrYXNZsPMzAxjY5Gbmwuj0Xiow5VKpYJUKkVxcTFkMhlmZ2extLSEkpIS+P1+xjvI7/fD6/UyxlgKhQJbW1soLS3F8PAwUlJSUFxczJCNDiixWCwEAgH4fD5kZmZienoaDQ0NKCkpAUVR0Gq12NjY2CcTlEgkGBwcZGbHvTY0lZWV0Ol0YVNP9CwdKdLT0+FwOGIiJz3bJWIllpKSArPZHPc44SAWi+H1erND/T3czCnMyclJrg02EhsQioecbrc74iZBXq8XTqcz7E1AL4mKioogkUhQU1PDGECtr6+DEILOzs59VTbr6+uMYJy2tywtLYXH48HNmzfh9/tx6dIlaDQaDA0Noba2FsvLy1hbW4PH42FWDXRPmIyMDOTk5GB4eBinTp0Ch8PB8PD94nu6tnLvHk2hUGBtbQ1ZWVmH1DhutxuVlZX7NMtutxvz8/Nh93nZ2dlRdfKOZzmZyKXocQSE+Hw+2Gx2SAlVOHKmJbs1Gm2EnKhcksvlisoN7uCxkcq1bDbbkUJ9epm896bl8XgoKiqCw+FAamoqysvLYTAYGMc/n88HtVrNqJboQE5KSgp6enpgt9sxMjICp9PJzIxcLpfxNqId2Xk8HjweD/x+P+x2OxQKBUMQNpsNsViM+vp6mM1mjI+PQyKRwGQyYXNzE0ajEb29vSgoKIBEImHKwAoKCg59P3w+H1wuF3a7PWRpWHp6Orxeb8RC8nhIkWhyJnvPSVEUWCxWyOhVOHJy2Gx2UnOcPp8PHA4nYdrdeGbhaParu7u7R86y4fawVqsVQqEQaWlpKC4uRnFxMeNwkJqaCqVSCbPZDBaLBZVKBYFAAJvNhieffBIjIyPY3d2FxWIBl8tlcpRsNpv5HuliBjqwsr29DZfLhdLSUsbdr6CgACaTCXa7Hbdu3doXxGppadm3rKRTHMGizvTfQpGToihkZmYymuCjQCt9YkEiCcXhcI6l+1jYawj3Nw6Hk9RlbSAQSKioniZ7LIiG2JGcJ5xrfbD9qtVqhUgkQkVFBSoqKjA7OwuHwwG/38/MqiMjIzCbzWhsbGRc11ksFnw+3z6n+r0CA7/fD4/Hg6qqKqjValgsFng8HszNzaGoqAi5ublQKBRM8p7ugL2XnFlZWSH3jRkZGUcGTugleiSIh2CJJBS9Pz8GUBRFUcHaMxxFzqTOnPTNlcjxYiV7NOH7SCwyw43ndrsP5WJ3dnb2LRt3dnYgk8lQVFQEv98PHo/HyOFmZmYQCATAZrPDtsagZ1OXywWVSgWXy8X0hMnNzWWUVDabjTlGIBAcasKUmpoacqkZCfHYbHbEN3o07z0Ieg+dCCRyrHB4cI+wABz6EsPdYZxE6V1DIVEJYxrxzMTRXEskRKbJE+pvB8m9N7cJ3CcwvcymZWS0Iqi0tBRSqRSBQCAsMei9HovFYqpz0tLSmJpQ+j1arZY5xul0HqrI8Pl8Ibub0X484WA2m2G1WsO+h4bH44k5Smq32xOmEqILFpKN5eXlVABBl2whi60pijr55JNPDn/mM59JesnYYzzGf1W8//3vB4AsQojt4N/CLWt9bDbb9b73vS9xTTIPwOFwoKenB+94xzsSMt7t27fR0NAQU+H2jRs3cPXq1YiCQouLi/B6vUw7wWAYGBhglqUHcf36dTzxxBP7ope9vb2oqKhglrb37t1DSUkJxGIxxsbGkJWVBTabjYWFBXA4HOzs7NDRvpBPeDonGggEGC3wuXPnoNFomB4pS0tLcLvdTNnbysoK7Hb7PhcDs9mM2dnZoM75CwsLjHAi3Hchl8sjErSbTCbMz8/j/PnzR773INRqNcxmM06ePBn1sQfh8/nw+uuv4z3veU/cY4VDRUWFc2lpyRHsb2HJmexoFUVRCd10s1ismPcJ0QQA2Gz2keH+cHsnLpcLt9u9j5zp6enY3d1lyEk3UHK73bBardBoNEyaobS0lDGhCrcU37tUzs3Nxc7ODgYHB5lqELr9wN7Sr2BSPbfbHTLdFW75vvc6ErmfD4VExjASveUKhQccC/p0DUvOZK+5E73pjiYqeBB8Pj9ooCbW86SmpoaMYmZlZTGmZjSys7NhMpmQmpoKo9GIjY0NeDweFBUVobCwEE6nE9euXcPw8DCWl5fB4XDA4/Gws7MDDocDQghzTXQgiL7RA4EA1tfXUVJSguLiYnR2djLVLJubm9jZ2cHOzg6TStmrEAIQ1hnPbrcfmR/2+/0Rk2bvXjtaRHOeo5DoTEI4hGqkG+6TeH0+X1LDVRwOB36/P2EEjaeSIJoQflpa2pG5uHDlT/TfAoEAzGYz5ufnsbq6Cq1WC6VSyXjistlsNDU1oaqqCunp6ejp6WEE6hUVFUzlPyFk3wxGE5PH48Hr9TIt/pRKJQYHB1FUVISKigrU1tYiJSUFTU1NYLPZmJubg9Vqxfz8PJaWlmCxWJgyvFA526M0ybSJc6TSyHhUXomUgsYivo8F4Tpch5s53cmWL9FLrkehkiAaYkdSnpSVlYWZmZl9/0YL4x0OBzY2NqBWq5lC7traWoyNjaGpqYm5kfPz86FWq+H3+7GzswNCCK5cuQKNRoPp6WnU19djaWmJGVsul0OpVDIzSEpKCsRiMWZnZxlngf7+fjgcDqjVamxvb0OhUDCu+zk5OZifn0dpaSmMRiNGRkbgdrvh9/shFAoPNU/yer1wuVxhjaNpT6dISeNyuWIq+aOPTVSFUyKJHgqEkJjJadze3k76vE4T6mFXEkRDbB6PBx6PF9azhpat2Ww2xgybdhvPy8tDIBDAtWvX9t2IEokEa2trqKmpYZwMZmZmmJbvKpUKw8PDsNvtqK6uxtzcHDgcDqqrq7G2tsYsB7lcLurq6jAxMQGHw4HKykpMTk6CzWajsbERWVlZGBsbw87Ozj7RulqtZgI3dPDGZDJhYGAAFosFy8vL4HK5jJqIxWJBIBBELWMMB5fLFZPonT72UdBpRwqv1wu/3x+y131IchJCvMXFxf5kb4wTXUkQKh93FOiaxkgRbN8I/Mpt3GAwgBCCO3fuMK70e93Ge3t7sb29vY+cJSUljLRudnYWXq8XhYWFTClVfn4+VlZWkJWVBalUCqVSidzcXMbvll5G0y3k6bpOuuzL7XYjNzcX6enpjJnz1NQUtFotiouLYTabD1XKmM1myGQyNDY2ghACm83G+C0ZjUbweDzMzc0xneIOEjVaJ3dadxwLHpUiikhhMBjAZrN3Qv09rAbN7/e7HQ5HRjJrOhOp/o9nz5mVlQWlUhnx++l9Y1FREWO7ubekSigUorCwEGlpaUEby8pkMqjV6n2pFh6PBw6Hg76+PtTX10OhUMDv96O7uxtTU1PQaDQ4e/YsDAYDurq6IBAIcOrUKXR0dKCyshJcLhd6vR5lZWXY3t7GyZMn0dnZidu3b6O2thYsFgu9vb0QiURMbxO/34+lpSX09fUxhd806DZ9tAk2RVHIyspCVlYW03o+IyMDhBCmJI62rxSJRMjMzITFYonYajQQCGBnZyfi6qCDSKSrRiKJHgpra2vg8Xgh6+nCkpPH421ptdq8SL1HY0EixcqpqalwOp0xHSsQCJiWBuECAYQQ2O12uFwuaLVarK2tITU1ldHF7jWstlgsGBoaQnV1ddD247Ozs4z7oFKpxOLiIgoLC5mmvxRFMcvWkZERlJaWQiQSIS0tjelu/cYbb8Dn88Hv9zM3JiEEBoMBN2/eZOR4crkcbDYbGxsb0Gq1TGNfDoeDjIwMpKeng8/no7OzE7W1tZBIJNDpdIwD/UHQ5W8nTpxgUkL0vxmNRsYXyefzQSQSwel0Hjkj7uzsIDU1NaYtDv0dJKqFgsvlitvo/Cisr6/D7/eHnBHCkpPFYmnW1tYqkknORHq1pKWlRVWetBdsNpvxfz34o9CtHmiDY7oXi8/nwxNPPBHypqOFA2az+ZAPD5vNRklJCSYnJ+FyuZCeno7z588jMzMTQqEQY2NjuHjxIiwWC6amptDS0oL5+Xl4PB4mAltVVYWFhQXo9XrYbDYYDAYA90mSkpKC+vp6xsxrZmaG0czW1dVhaGgI7e3t4HA4mJmZYRwSzGYz41Lv9XpDtpPXarXIz8/f9z3TJXH0asBsNqO/vx9bW1tYXFxkXPdpF8ODJIzWjWIvrFZrXP1cDyKRs3AoaLVabG9vhyx2DUtOr9e7rNFogvcPSBBSUlIi1l0eBXrZFaktxkHQ+8isrKx9Xarsdjtj4lVeXo6MjAxQFMU07AlFToqioFAooFKpDpGT7mWytbWFyspKVFdXM3+TSCRMXaXdbmd6l4jFYoyOjsJgMCAvL48JOJWUlID2enrllVfQ2NgINpvNuN3xeDymS3ZNTQ0zY/b29jKtGGhS5OXl4dKlSxgaGoLFYoFer0dubu6+JR7dBS2cQgq4L6jPz89Ha2vrPtf9lZUVDA8PIysri9mP0xHweJwTYyV2MBzHnlOr1fq3t7dXQ/09LDk3NzdntFotAZC0iFBqaiocjqDqpZhA7wWjISfdXtDn82F+fh4zMzPIyso60m1cLpdjfX09bGNZuVyOxcVFJg3h9XoxPz8PjUaDyspKxvmutLSUmYUoioJUKsW9e/eYztXAfRWT3W5HTU0NLBYL3nzzTfj9fqSmpkKv1zMz0cbGBpxOJzY3N7G6ugqJRILS0lLY7XZmZikoKMD8/DxcLteh0jb6wUG7LnR1daG8vBylpaWMXQkh5EjTrvX1dVRVVTGf6aDrPt1Ogo4qA/fdGHZ2dpgHYKSgPZ0SAUJIRMvweKHT6XwAYttzulyuda1W6wOQNNvrrKws2Gy2hMmlsrKyIupzsbdLlclkAo/HQ25uLvx+P5544omInppSqRSdnZ1oaGgIWd/J5XIhl8uxtLSErKwspufmXh1vYWEhs3QF7qcvhoeHcfbsWWg0Gty5cwcnTpyAxWIBj8dDeXk5KIqC0WjE6OgoKIqCUqlk6jjX19eRmZmJQCDALLv9fj86OjpgMpng8/kwMTGBkpIS8Hi8ff1BA4EAxsbGUF1dzQR/FAoFZmZmoFarUVtbC6VSyVxDKND53FAE5nA4yM/PR35+Purq6rC1tYV79+7B4/Hg3r17ABCR6z4Nq9WKsrKy8D9YhHA4HGCz2Ulf1m5ubgYA6EL9/ajKZJ1er/cjieTkcrlISUmJK0q3F6Gan+4NVhiNRiZQUVBQgPr6euYpubu7C5vNFhE56bpIrVbL9NkMhtzcXAwNDTFu7weXbrW1tbh9+zaTJtnbu0QoFEKr1aK/vx9+vx/t7e0MKSwWCwoLC/ctL1955RXGh4hugEQ7AFZWVmJwcBBcLhctLS3MTEP3Zjl79ixWV1fB4/H2RVhp13eDwYCxsbEjRf/A/ZypTCaLWE5H24g2Nzfvaw1Pu+6npaUx3sAHe6+Gar4cKxK9RA4Fo9FIEA85H7A7qaD3iYn4cjMyMuDxeOB0OmG325nZkXa+E4lEQd3GaRQUFECv10e8LC4tLcX09DRjmLUXDocDMzMz2N7eRmlpKTY3N4OqaTgcDtrb23H79m34fL59hs/0Epee4QcGBlBcXAy5XA6DwRC2O5tIJILBYEBqaipUKhW0Wi3YbDZKS0v3LQHp3ix37txhAlPBvht6Zi0pKcG9e/cO9eWk4fV6sba2hsuXL0f0HQL3u7vRn4W2Ntnruk/vVxcXF/c5AIpEIvj9/iM9naJBPF0DosGDAN2hUjEaR5FTq9Ppkq7Qp4MB8WBvgpzFYuHWrVtMl6q6urp9nrHhIBaLce/ePTQ0NET0mUUiESiKgsFgYPZuPp8PS0tLUCqVKCsrY3SyTqcTc3NzQbuS2e12BAIBcDgcxmOIxs7ODvR6Pa5evQqPxwOlUok7d+4wjnt0lzb6821ubsJms8FkMsFkMkGv10Mmk+Hq1atwuVzo7++HXC5n9qj0npsW/wdTbBFCmKVwdXU1KioqMD8/j46ODlRVVaG4uJghh1qtPuR+Hw4ejydsawsWi8VYilZVVe3zzh0bG2OCciqVCiKRKO7eO1arNWEtKUPBZrPB5/M5Y5XvgRDilcvlO0ajMS2ZjURDLUWPgtPp3GfhSLut0x2c6eVdNBAIBODz+TAajRHNnhRFoby8HMvLyxCJRNBqtZidnYVQKMSVK1f2BRUaGxvR1dXFePfQMJlMGBoawunTp5Geno6+vj5YLBY0NDSAy+VienoalZWV4PP54PP5aGxsRH5+Pubm5iAUCmG1WqHX65kStZWVFWRmZkIqlcJiseD8+fMMUWi97cLCAurr62G32zE+Pg4AuHz5MjY2NvbtQWmsr6/D5XIx/TZ5PB4aGxtRXFyMqakppmtaXl4eVldXI26jSI8tFosj9n+iXffpUrdbt25BIpEwRQS06zz9iiatdpTQP1Ho7+9HSkrKVLj3HPlt8Hi84b6+vl97ULGdFNApjKNmaPqJSS9VPR4Pk+LY6zbudrvR0dERc22gQqFgnv6RQCKRYH5+Hp2dneByuWhtbQ2awKaJNTIyggsXLiAlJYUhJr3HBIBLly5hbm4OXV1dkMvlcDgchzqnmc1mFBYWHlLfvPLKK2hvb2f+e3NzEyaTCXvbatTU1KCjowNsNhsqlQrl5eVMgIfeO+8lKG2K3d7efuj7FAgETB/RiYkJUBTF+OVGAtoYO9IW9Qdht9vh8/kYocfefi3r6+sYHx9HRkYGQ9Sj+rU4nU6maCCZGBgYIJubm6+Fe8+R5FxbW/vFwMDAU+9///uTZv0eqvnp3g5ftP1/Tk4O8vPz0dLSwqhoDoLP5yMjIwMmkymmfKdUKsXc3FxE4XR6qUo74J07dy7sMUVFRUwjopqaGoyNje0jJnB/D9rQ0MAssXNzcw/ZcRqNxojarItEIhiNRoacdLCFx+NBqVTiwoULh/TBewna3NyM8fFxNDQ0hNyHURSFwsJC8Hg8JuI6MzPDSArDwWQygRASs9+wXq9HQUEBcx8cdN0PBAJMymZubm5fpzORSHQo9nBcwaCRkRH3zs7OvXDvOZKcXq93aGxszA0gqUmfnJwcxthpb5cquqSqqqpqX2/Mo0C3MY+FnFwuFzKZDEqlMqT9ht/vx8rKClZWVqBQKPDEE09geXkZk5OTOH36dNgVQFVVFWw2GwYHBxmBQTDQdpm5ublMmz65XI7c3FzY7faIZieRSMQoi+gyNa/Xi9LSUqysrITsKq5QKOB2uzEwMIDKyspDBdjBvo+JiQk0NzdDKBQyXdNqamqCBstorK6uoqysLOaYxt5AUjCwWCwm6l1TUwOv18uovVQq1b4eofn5+dja2oq5KiYazM3NBQCMh3tPJIv8maWlpaQFheiu0k6nE1NTU+Dz+RCJRJBKpWhubo451yQWi9Hf3x9xYOcgSktLcefOHZSXl+/bs9Bdv2ihwsWLF5nldGVlJW7fvg2NRhO2iavZbIbJZIJYLMbc3Byys7MPLaPcbjeWlpYYSV95eTk2NjagUqkwNjYGFouF2dlZZGdnIysrC3w+n1ly0kEdi8UCi8UCr9eLN998E/n5+aiqqmJmmrS0NExPTzPlX3ths9mgVCohkUigVqshkUjCVg4tLCwgPT2d6Zx94sQJbG9vY2pqCkqlEo2NjYeW+larlTGxjgVHBZKCgcvl7iuJ29tde28lEN3ZLRmdrXd2duB0Ol2EkLDqm5Due3uhUCj0w8PDBdF8CaFAl1TRX4jT6WQKfRcWFvCud70rZmPovaDbttfW1sY0ewLAxMQE2Gw2E121Wq2Ynp6G2+1GQ0ND0JvCYrGgv78fly9fDrpv2bvHzMvLw8LCAtbX19HS0rLv5h0fHweHwwka2R0eHgaHw0FaWhpjAv2gNpBxQODxeMjOzmbsT7Kzsxm1zt7vqL+/H/n5+fsS+BsbG5icnERdXR1TPTM/P38oSERje3sbAwMDQT8zIQRarRYzMzPIy8tDXV0ds+y/d+8eCgoKYo6MrqyswGKxxEzug9jZ2UFPTw/KyspgMpmwtbXFRPzpLnGJSNd0dHTg937v9+4sLS1dCve+iFjA5XJH7t279+6nn3466guho18GgwEmkwnb29vIzs6GSCRCU1MTsrOzmQ9MBy/2Gk7FCjq4EU1g5yAqKyvR1dUFqVQKtVoNnU6HqqoqKBSKkD9SdnY2FAoFJiYmDi1vgwV/qqurIRAIMDg4CKlUipqaGiZ1cu3atUPjE0KwtbWFs2fPBiXKK6+8gqeeemrfv6WmpgZtSktRFOrr69HT08MsW6empmCxWHD69GnmYREsSETD7/djbGwM9fX1QR9GdJ5WLBZjaWkJ3d3dKC0tRXZ2NnZ3d3H69Omg3+NRiDeQFAx6vR5FRUWorKxEZWUl/H4/s1+dmpqC3W4/VBIXy6rs3r17xGAw/PKo90VEzvX19VcHBgbe9fTTTx/52KBLqvbuG+lqhPLy8n0lVQchFouxubmZEHIC9wM7s7OzMYuY+Xw+srKycPfuXRQXF+Pq1asRheUrKyvR09ODubk5Zs8ajJg0ioqKkJeXh6mpKXR3d4PFYqG6ujroksput4MQEtYa5CDoKpdg5XB0ymVkZAQ2mw1SqRRXrlw59L5gBA0EAhgZGYFAIIBEErLNJID7Qa6amhooFApMT09jYWFhX240WmxtbSEQCMQcSAqGzc1NVFRUMP+9NyVTW1vLVCfRJXF+v5+ZVUUiUcT32OjoqNtms/Ud9b6IyOnxeAZHR0dDBoU8Hs+hlnH5+fkoLCxEY2NjxBctFovR29uLxsbGhOxvuVwuJBIJVCrVvqqPSGAwGJg9MN1ENtJ8GZvNxtmzZ9HT0wMOh8PI94IRkwafz8epU6eYPZrVaj3k2QPcD5bRwodIwePxkJGRge3t7UPnt1qtsNvtMJlMaG5uRrhO5nsJevbsWSwvL8Pv9+PUqVMRX09aWhoKCwths9lgNpvR29uL+vr6qCOkq6urTF/RRIC2IA0nnufz+ZBIJJBIJCCEMPpsnU6HqampfSVxQqEw5CQ0OztLcEQwCIiQnACm5+fnmbyh3+8/VFJFT/elpaUxT/cZGRngcDiMPCsRKC0tRV9fHyoqKiKK9O7u7mJ6ehq7u7uor69HQUEBtFotxsbGcOnSpYijxTweD2fPnsXt27exuLi4T5IXCn6/n2lGu7W1hdu3b0MoFKKkpAR5eXmM2D0Sc+aDoFMqQqEQgUAAm5ubUCqV2NnZYYq419bWIJPJwv52e6V+GRkZOH/+fFSzn8vlYupHs7KyoFar0d/fD7FYjJqamogCgLT4pLm5OeLzHoXNzU2IRKKIf1+KopCeno6SkhKm1cXBkjh6+0aXxLFYLGxtbcHhcDgIIUe2UouInIQQT3l5+dovf/nLqry8PGajnJ+fH7akKhbQS9tEkZPOeWk0mrDidK/XywRnKioq0NrayvxQEokEGxsbWFhYCOtsfhC0JI/L5WJra+tIci4vLyMnJ4eJJlZWVmJtbQ2Tk5Pw+/2QSCQwGAxRrwIIIRAIBEw+VqvVIiMjAwqFAhKJhDHjXltbg06nC+pST4POPdNF8kc1ET54HRMTE1AoFMxMWVxcDIlEgoWFBXR2dqKiogKlpaVh76eVlRXIZLKERlLj3U4FK4mjJ7CJiQk4nU7k5eWht7cXLBbryP0mEPnMCaPR+J033njj//3a175G0TaLyUBhYSFGR0dRVVWVsCVLdXU1hoeHIZVKDz0Z6Ztybm4OBQUFuHLlyqFlOEVRaGxsRHd3NwoLCyN6cByU5N27dw9erxe1tbVBP5fT6cTq6iouXfpVAI/L5aKsrAylpaWwWq1YWVkBAPT09IDNZjPR2LS0NLDZbOazbWxsMHaaVqsVFosFFEXB4/GAzWbj/Pnzh/asdHBofHwcBQUFQWcQv9+PkZER+Hw+XLlyBVqtNmiQKBQ0Gg3sdjvjSbT3c9KeSTMzM4wUcK+4YO/3tLa2hitXEucB4PV6YTAYEhpc4nA4KCgoYPTWLpcLJpMJt27d8qnV6h9EMkZEqRQAoCiqqKmpaXl8fDypYgRCCLq6utDY2Jiw4lngfr+OvLy8fX0xaUsONpuNhoaGI/c9Wq0Wc3NzuHTpUtiHU7DgD12nSJs4H3wAjIyMhDQDo7GwsMCUazkcDiaP6XQ6mTSKwWDY59hHF2unpKSgv78fCoUi7Mw4ODiIrKysQ2kXm82GsbExpKamoqWlhSHvUWkWGru7u+jp6WHsUMKB7vSdlpaG+vr6feOOjY2Bz+dHtYI5CkqlEiaTKSo9cCzweDwoKyuzazSabELI0b1OHhjbRvSSy+W69fV1kmwsLy+T4eHhhI5ptVrJjRs3iMfjIXa7nQwNDZE33niDaDQaEggEIh5ncnKS9PX1hTzGaDSS69evE6PReOhvfr+fzM7OkuvXr5O1tTVmDLPZTF5//XXi9XrDnvvu3btEr9eHfc/Pf/7zkH9bWloi4+PjYY/f3d0lv/zlL8n9bdH9a15YWCDXr18nSqUy6OdWqVTk9ddfJzabLeiYHo+H3Lp1iyiVyrDn3gu/30+Wl5fJ9evXyeTkJHG73cRms5Hr168Tj8cT8TiRoKuri2xubiZ0zGC4fv06KSsr6yYR8i2qjaLX6/3Xl156KekdRWUyGfR6PdNSPRGgk8n9/f3o7u5GRkYGrl69yihaIkVdXR1jBXkQ4dIlwH0pWU1NDc6ePYulpSUMDg4yyqja2tqw4gufzweLxRJX6oAOCoVDeno6iouLGWfAu3fvwmg04tKlSyguLg76XSkUClRXV6Ovr+9Q411CCEZGRiAUCiO2yATuf1dlZWW4evUqAoEAOjs7MTw8jLKysoRuqWgFVSIENkfh5Zdf9q6urv6fSN8fFTl1Ot2/vPrqq4mxygsDHo8HsViMtbW1hIxHHjSLNRqN2N7eRnt7O6qrq2NSIrFYLJw6dQp6vX7f9R1FzL3Izs7GpUuXIBAI0NnZCY/Hc2Se0Gw2Izs7Oy71lEAgYFwDwqG8vBx6vR53796FXC5He3v7kbWZoQg6OzsLv98fkUg/GPh8PpqamlBbW4vd3V3md0wUlEolFApF0psWEULQ3d3tI4S8Eekx0YZYJxYWFryxtjyIBqWlpVhdXY27ReD29jZ6enqwvLyM1tZWlJeXY3FxMa7mSTweD6dPn8bs7Cz0en1UxKTBZrP3+fDcu3cPm5ubIa+Lzm/GA4qiws6edDey3t5epKamIjU1NeRsGQwHCbqysgKdTodTp07FFc0PBAJYWVlBU1MTqqurMT4+jsHBwZhbb9Bwu93Q6XRRzeix4kHEXUMICenwfhBRfWOEEMLn8ztfey1sGVpCkJOTw7jKxQKXy4WxsTGmceulS5eQl5eHqqoq7OzsYGMjpOlZRBAIBGhra8Po6CgGBgaiIiaNxcVFiMViXLt2DXK5HLOzs+jq6oJarcbB3qgGgyFmGeJe0NYle0GL7G/evIm1tTXU1tbi8uXL4HA4WF9fj2p8mqB37tzB8vIyzp07F7dR1uLiIlJTU5lmxFevXkV2djbu3LmD2dnZQ99VpFCpVCgqKkqYEXU4/PSnPw2Yzea/i+aYqB9nq6urf/ezn/0sue3HHoAua4pmlqPbC3R1dYHH4+HatWv7li1sNhsnT57E1NRU3GbWdPtCiqKivkHsdjtDBBaLBZlMhsuXL6O+vh46nQ5vvPEGRkdHYTKZ4HQ64XK5ElJnKBKJYDKZGMHDwMAAbt26BZvNhra2Npw7dw4FBQVgsVior6/H3Nwc4+oXKXw+H9MXNN4GzBaLBUqlEk1NTft+w8rKSly+fBkulwsdHR1YW1uL+j5RqVRJtyOhcePGDbfNZnspmmNi2cB037t3z+/z+RJSPRIOhYWFmJ+fj8gyhBACvV6PmZkZZGZm4sKFCyH1pzk5OZDJZJicnERra2tM+w16KdvW1gY2m42BgQHU1taGlb/txfT0NMrKyvalVCiKYuwiXS4XNBoNJicnYbfbGWd2OjUSja8r3YOETr34fD5cv34d2dnZkMvlOHnyZNAgS25uLoRCIZaWliJKXRBCMD8/D61Wi0uXLsFoNEaVBw123WNjY/sqWfaC7mO6tbXFyB4bGhoiaqOgUqmQnZ2dMMe+cHiwT94lhEQVRImaXYQQd0lJyd2XX375nc8++2y0h0cFOro5OzsbVk9qs9kwPT0Nl8vF+Oscherqaty+fRtarfbIQuKDCLbHbG9vx+DgIGw2GzMbhoLBYIDNZjuUjN+LlJQUxj5kaGgIfD4fPB4Per2eKZ7OyspCRkYG2Gw2WCwWk3ucmZmB3++H3++HzWZjepDQooWCggIIBIKIlEa1tbXo7u6GQqEIa5zl8/kwOjoKt9uN8+fPIyUlJWw1SyRYWFhglrPhkJubi4sXL0Kj0WBoaAhCoRC1tbUhHSm8Xi+Wlpb22bkkE9/73vf8Tqcz4igtjYhFCPsOoqi2a9eudd+6dSu5RisAo+MsKys7RCKPx8M8qQ86wEUCug4xmGImFMIFfzweD4aGhpiIbrDZKBAIoLu7GzU1NRFpZAkhePPNN3Hu3Ll910gXGjscDoaIgUCAkRiyWCymSVFWVta+VY5Op4NSqYz45qTtKEOVdzkcDgwMDCA7O5tpBbEXkQoV9oJu3nvp0qWonNdp50N6yVpeXn7oemgLmpMnT0Y8bqzw+/2ora11Li4uygkhpqgOjjQhuvcFgJJKpYZoksrxwGAwkDfffJP4/X5CyP0E9crKCrlx4waZmJggbrc75rGVSiW5detWRIntcAIDGn6/n0xOTpKbN2+Sra2tQ39fWVkhPT09EQsfrFYrefPNNyN+fzgRAg2Px0NeffVV4vP5IhrT5/ORN998kxgMhkN/0+l05MaNG2R5eTnsNR4lVNiL3d1dcuPGjbDfcyRjDAwMkDfffJNotVrm2pxOJ/nlL39J7HZ7zGNHgxs3bpCSkpJ7JAaexRTfJoQQu93+N9/97nf9sRwfLUQiETIyMqBSqWAwGNDd3Q2dTof29nY0NjbGFW0rLi6GSCTC8PBw2IBCpOkSFouFhoYG1NTUYGBggMnzAfdnu8XFxaisU2IpETsKXC6XadYUCdhsNurq6jA9Pc2ktjweD0ZGRjA9PY3W1tYjfYDCCRX2wuv1YmBgAFVVVXHJN9PT03H69Gk0NzdjYWEBvb29sFqtWFhYgFwuj9hTN1787d/+rVupVP5pLMfGnHza3t7+/ksvveSJNxoXKYqLizEzM4Px8XHU1NSgvb09YZv5+vp6BAIBzM4G78YWSx5TIpHg8uXL2N3dxe3bt7G9vY35+XkUFhZGdd2JyG8GQyRqob2g3fXUajX0ej0TDb98+XLEqqWjCEoeqIny8vIOWYHGCpFIhMuXL0MqlaKvrw9ra2thq5MSic3NTYyOjjoBdMVyfMzkJIRsBwKB2z/5yU9iHSIieL1ehpQZGRmQyWQoLCxM6EzCYrHQ2tqKjY2NQ6qkWIhJIyUlBa2traisrMS9e/egVqujSngHAoGgvT0TgWjJSVEUiouLMT09zTRdCtfAKRTCEZQuaYtVTRQK9LXn5eUhKysLPT09WFlZiVvgchReeOEFv9vt/l+EkJhOFFcRpkql+sq3v/1tV7jlYKwgDzxiOjo64PF4cOXKFZw+fRoqlSrssihW8Hg8tLW1MaofID5i0qAoChKJBAKBgKnnm56ejkg3vL29zXScTjRycnJgt9vhdh+dsrbb7RgZGcHU1BQT7Y3ngRGMoCsrK9jY2EBra2vCaoP3YnNzExaLBe3t7Th//jwMBgO6urqwubmZ8HMB95f9L774osdkMn071jHiSlQSQqaKi4u1Q0NDZbEaNQUDXcrFYrHQ1ta2r36yqqoKY2NjuHDhQsL1kLTqp7+/n2mxEA8xadAi/suXL8Pj8WBhYQEdHR1QKBQoKSkJGY1M1pIW+JWfq8lkCqnrtdlsWF1dxcbGBkpLS9HY2MiI0OlmULFib5pFLpdDo9EkRE0UDF6vl/HU5XA4yMzMxJkzZ7C5ucnkR+vq6mLKxYbCP//zPxNCyHVCiCXWMeJ+RGk0mi89//zzCSkfcTqdGB4exvDwMMrLy3HhwoVDhc0lJSVgs9lM4XGikZOTg6qqKszOzqK8vDxuYvr9fszMzKC+vp6x+W9qasLFixfh9/vR1dWFwcFBGAyGQwGpZJITuG/8dXBp6/f7odVq0dvbi76+PqSmpuLatWuM4Rifz0dlZSWmp6fj0icD9wkqFAqxuLiIpqampAVppqenUVBQsC//TVEU0ydVKBSip6cH09PTUauhgoEQgu9+97tutVr9tXjGiVvi4/f7X+3t7bWr1WperBttn8+HlZUVxrSJfsIFA0VRaG5uxp07d1BQUJDQpx1wfym7sLCAhoYGLCwsIDMzMy77itXVVWRmZh4SRqSnp6OhoQHV1dXQaDSYnZ2F2+2GWCxmgkZWqzWh7nIHkZ+fj5WVFXi9XhiNRuh0OhgMBggEAigUCqZo+yBKSkqgUqnitvZYWVmB2Wxm2lLEqiQKB9puNVQ7QhaLhfLycshkMsalvrq6Oq5Klc7OTpjN5hVCyEIclx6bCOEgBALBc08//fT/+Zd/+ZeochqEEGxsbGBmZgY5OTmoq6uL+Om5uroKjUaT0OXtwT0mLVKIRpa3Fy6XC11dXWGlhHtB+9Xq9XpYrVaw2WxUVVUxru6RmE+98soreN/73hf2PV6vl3Fbn5+fB0VRyMvLYzp3RZL0p5eEV69ejXqPSAjBwsICNBoNU44Wi1DhKHi9XnR2duLkyZMRr0AsFgszgzY0NES9ciKE4OzZs+6BgYGLhJDBWK6bRkLISVEUWyKR6F5//XVRMIfyYLBYLJiamoLf70d9fX1MX0JfXx8KCgr2WY/EilDBH7qnSWFhYUj/n1AYGxsDj8c7sgt0qGN9Ph+4XC4sFgt2d3cZ25G0tDSkpKQgJSUFfD4fKSkpYLFYoCgKN27cwLve9S74/X64XC64XC6mPYPdbofFYoHL5YJAIEB2djZsNhvEYnFM32F/fz+EQmFUx9IyP5fLhdOnT+/TFieaoHTbiqampqiOi2fSeOmll/ClL31pQKVSnYnlmvciIeQEAC6X+/Q73/nOn7722mthZ0+Xy4X5+Xno9fq4lw92ux137tzBuXPn4gpOHBWVjUSWdxB0W4Zr167FVLnf0dGBlpYWphJlr2GXw+FgCEeTLxAIgBACr9cLHo8HNpvNEJd+0fravdal6+vr0Ol0MTmv7+7u4u7du0FN0YKBlvllZWWhqakp6EogUQTV6/WYmprClStXYi7Q8Pv9WF5exurqKoqLi1FRURF2LL/fj6amJtfMzExzvEtaALHJ94K9AFAymUzZ09MTVMbk9/vJ0tISuX79OpmamkqYD8za2hq5efNmzBK+SCR5hNy//omJCXLr1i2ys7MT9r2BQIDcuXOHqFSqmK7J4XCQ69evR+VtRCMS+d5e0HK2WM5FCCFTU1NkbGzsyPeZTKaIZH6ERCf1Cwbaa8hsNsd0/EE4HA4yPDxMXn/99X3eTwfxd3/3d36FQvEqSRSnEjUQuU/Qc+fPn3ftvfhAIEB0Oh25efMmuXfvXsxfeDhMT0+Tnp4eRnsbKSIl5l4olUpy48YNsr6+HvJHWl9fJ11dXTHf8CqVigwNDcV0bLTkJISQzs7OmG9kj8dDbty4Qba3t4P+PRAIkKWlJXLjxo2oTLRiJajb7SY3b96M+cEYDmazmXR3d5Pbt28f0k27XC5SVlbmACAhCeJTQrO9hJDe9fX1OdopYWdnB/39/ZiZmUFDQwPOnDmT8GgcAKYKY3p6OuJjYhUYFBcXo62tDYuLixgaGjpUsO3z+TA7Oxtz60Eg+SmUg4hWLbQXXC4X1dXVmJqaOpRa2dnZwd27d6HX63HhwoWonBwi1eLuRSAQwPDwMAoKCpIi0aNL04qLizE4OMjsnQHg+eef93s8nn8jhGgTdb6ESzHUavVvfv3rX3dPTEygp6cH+fn5uHLlCmOumwxQFIVTp07BaDRCpVId+f54lT85OTm4dOkSMjIy0N3dDa1Wy9yYy8vLyM3NjTkFQgiByWR6y5ATuE8kv9/PWL8QQrC8vMx0Lzt37lzYWtBw40ZDUNoRMZYAXKSgKApyuRxXr15FSkoKurq6MDY2hu9973vu9fX1LyfyXAknJyFk2m63D928eZNcvXoVZWVlSZFjHQSXy0VbWxvm5uZgMoUum0uEJA+4X6lRW1uLtrY2zM/PY2hoCNvb22G7YUcCm83G9N48LuTl5TEOCbGAdoufmZlhDNX0ej0uXryI0tLSuFJdkRJUrVZjc3MzbjOxSMHlclFbW4uLFy/ie9/7HiGE/B9CyHYiz5GUT7G8vPwb3//+94/FZ2gvMjIy0NLSguHh4aD2j4ki5l7k5OTg8uXLyMjIwN27d5GRkRGXr+pxL2mB+60DsrOzIy4hC4b09HRQFIXe3l5IJJKYZ8tgOIqgW1tbmJ2dRVtb27GYde2F1WrFa6+9tru+vv7NRI+dFHISQtR2u/0fv/a1rx1PPdke5Ofno6KiAn19ffv2g8kgJg02m42CggLweDykpaXh1q1bTHu8aPEwyAnEvrT1eDyYmZlBV1cX8vPzQVFUwquGgNAEtVqtGBwcxMmTJ5MSzwgHQgg+9alPeex2++fJES3kY0HS5n+tVvuFF1980dzf35+sU4REWVkZZDIZent7mYanySImcP9HmpqaQn19PVpaWnDu3DmYzWZ0dHRArVZHTFK6teLDIudBy8xw8Hq9WFxcREdHB7xeL65cuYKmpiaUlpYGdcNPBA4S1Gaz4d69e2hoaEhqTCMU/umf/ikwMTExabFY/jEZ4yfNPo8Q4qYo6tc++clP9o6MjPCTUW0QDlVVVQgEArhz5w68Xi9Onz6dFGICwNraGthsNlPdQVe3bG1tYX5+HnNzcyguLkZxcXHYZD3dWjFZHdzCIScnhxE1hLvG3d1dRjqZn5+P8+fP75uxKioq0NHRAbPZnBRdMB2F7enpAXC/UP4ot/xkQKfT4c/+7M+c6+vr7yUHw9QJQlJ3zoSQEYvF8sM/+ZM/OfblLXC/6sLlcoHL5SZtyeP1ejE3Nxc0dZKbm4v29na0t7cz/qpDQ0NBK1CAh7ekBe4HdYJVqQD3UxR0u7+7d++Cw+HgypUrOHXq1KHvlcPhoK6uLmhqJVHIyckBIQSBQCAhXr7RghCC5557zmO1Wj9LCInN9TwCJD2spdVqv/CTn/zEfO/evWSfah9MJhOGh4dx5swZSKVS9PT0xG0iHQyLi4soKCgIe5MIBAI0NzfjHe94B4RCIWZnZ3Hz5k1MTk7CYDAwy96HSU5g/77T6/ViY2MDo6OjeOONN6BSqSCXy/GOd7wjrO0kAKYhb6J63eyF1WpFX18fGhoaUF9fH1UeNFH40Y9+FJicnBy3Wq3/lMzzJNcVGr9a3j733HPHtrw9uMcUiURgsVjo6emJqClPpNjd3Y2qkSuXy0VJSQmKi4uZCpT5+Xns7OxAKBTCZrMlLMIZCzIzMzE7O4t79+5ha2sLOTk5EIvFqK6ujuo7oygKDQ0NGBgYQFFRUcKW6XSVUENDw76lbDzG1dFiY2MDf/7nf+5cX19/X7KWszSSTk7g/vJWKpX+4I//+I8/9b//9/9O6jlDBX+qqqrA4XBw584dtLa2JmQ/NDMzg/Ly8ohE33tBURQEAgEEAgEqKyvhdrsxPz8PLpeLzs5O8Hg8xtmdfiUyRUAIgcvlgsViYTpfWywWRjYmEokiFviHQk5ODvLz87G4uJgQUcD6+jqmp6dx4sSJfTWk8RpXRwNCCD75yU96rFbrp5O5nKVxLOQEAK1W+4c//elPn/nQhz4kPnfuXFLOcVRUtqysDJmZmRgcHERNTU1c3aUMBgN2dnbCurZHCno1UVFRgdLSUuzu7jKkWVxchNVqBZfLRWpq6qFKk5SUFLDZbFAUxex5t7a2mAqVvdUr9MvpdIIQwhBfLpejsbERqampmJiYAEVRCZntamtr0dXVBYVCEbFp90EQQjA7O4uNjY2Q1UfHRdAf/vCHgZmZmTGr1frjpJzgABJWMhbRySjqRG1t7b3BwUF+opdv0aRLdnd3MTAwAJFIxNiHRINAIICuri7U1dXF5QSwFzdv3kRbW1vQm48QAofDcYhkdLkY3VApEAjAarUiJycHFEWBw+EcqvukS8dSUlKC5iK1Wi3W19dx5kzc5YgAgKWlJWxtbaGtrS3qY71eL0ZGRuDz+dDa2nqkv1AyCrb3jn3x4kX72tpaGSEkOa5gB5EoBX2kr8LCwj97+umn3dFWkIRDLNUlHo+H9PX1kZ6enqjLzVZWVkhvb2/MVScHQTucJ2K8WKpS9sLlcpHXXnst6gqfUKDd4qNt676zs0Nu3bpFxsfHo7qWeMvNgsFut5MTJ0640tLS3kuOkSvJFyEegE6n+4vx8fGub3zjGwlJr8QqMOByuThz5gzT59Fms0V0nNvtxsLCAurr6xOmgkmGq3us4PP5SE9Px/Z2YmSibDYb9fX1+9zij4LBYEBPTw9KS0vR1NQU1comlmqWcCCE4Ld+67e8BoPhebvd/mrcA0aBYycnIYSsra2970c/+pHmxRdfjGtNHa/yh6Io1NXVoaqqCr29vVhaWjoyNzc/P8/40CYKDzuFchDxVqkchFgsBp/PP7JiyOfzYWpqCmNjYzh16lTMru+JJOif//mf+wYHB+9otdqYWirEg2MnJ3A/vaLVas9++ctf3hkdHY1pjERK8mQyGS5evAiDwYC7d++G/EFtNht0Ol1ErfMiBSHkbU9OOrWysLAQ0kzbbDaju7ubMRCP9zdNBEFfeukl8g//8A8b6+vr7yFHPbWTgIdCTgAghOg1Gs3Vj3zkI65oNJ1AckTs6enpaG9vh0wmQ09PD5aXl/fNouSBfraqqiqhaQ2LxQI+nx9Vm7tkIy8vD1arNSEerjQEAgEkEgnm5+f3/Ts9Ww4NDaGurg4tLS0J+37jIejExAS+8IUv7Gi12rOEkMSrVyLAQyMncD//aTabf++DH/ygJ9IbIZkidoqiUFJSgosXL2Jzc3PfLKrX6+F2uxNeYR9J1+7jBpvNRm5ubti62FhQXV0NrVbL7O/3zpZXr16NqF9ptIiFoCaTCR/+8IddGo3mSULIRsIvKkI8VHICwNbW1j+p1eoffepTn/IetXJIdnUJDXoWpWV/c3NzmJqaQkNDQ8ILeR+1JS2NRC9tgfv9aKqqqjAxMYGJiYmkzJbBEA1BvV4vPvjBD3rMZvPnSJy+s/HioZMTADQaze/fvHlz8oUXXghZW3VcxKRBURRKS0tx8eJFZtbc2dlJaGcqn8+H7e3tpLq6x4pkkNPr9cLlcmFrawtOpzNps2UwREJQQgg+/elPe5VK5b+azeYfHMuFhcEjQU5CSECj0Vx9/vnndf/4j/946O4/bmLuBYvFgsvlQmtrKzY3N9HR0QGNRpOQioutrS1kZWU9lBKxo5CVlQWPxwOn0xn3WH6/HysrK+jo6IDL5cKJEyewu7sbkYN9IhGOoIQQfPWrX/W9/vrroxqN5rljvbAQODb53lEghNgoimr++te/PsXn88Uf+9jHKODhEhO43zNSoVAwrQpMJhNmZmawvLyMmpoapvo/FjyqS1rgVyVkBoMh5n02IQTr6+uYn5+HQCDY1/BYp9NhdXUVFRUVibzsIxFM6kcIwV/8xV/4/uVf/mVao9FcIoQcS8f2o/DIkBMACCFmiqKav/KVr0zz+XzhpUuXqIdJzO3tbRgMBly7do35N6FQiIsXL0Kn02F6eho8Hg9lZWUQi8VR70eNRiMaGxsTfdkJQ35+PkwmU9Tk9Pl80Gg0WF1dBZfLRUtLy6Gle11dHe7evQuZTBZ14UC8OEjQv/3bv/X/4Ac/WNRoNGcJIcfufRUKjxQ5AYAQYqAoqvkP/uAPpr/whS/k/PZv//ZDISadOqmtrT207KQoCkVFRRCLxdDpdFhZWcH09DRKSkqgUCgiCm643W7Y7faHUiwcKUQiEebm5kAIiWh14HQ6oVQqoVarkZubi/r6+pDKp4yMDMjlcszNzeHEiRPJuPywoAn6l3/5l+Rf//VfVRqN5vTDSpmEwiNHTgAghGxQFNX0wgsvTBQXF2c/88wzx65ro/eVMpks5HtYLBYkEgkkEgm2t7exurqKmzdvQiwWQ6FQIC8vL+RNbTQaIRQKj8XGMVakpaWBw+HAZrMhKysr6HsCgQA2NzehVquxtbUFmUwWcVe1yspKdHR0YHt7+1Af1mSDEIL/+I//8P/bv/3bmkajOUEIsR/rBUSAR5KcAEAIWacoqv4P/uAPxt1ut5Degx4HaNf21tbWiPeTOTk5aGlpgcfjwfr6OiYnJxEIBCCRSCAWi5Gdnb1vrEd5v7kXdNR2LzkDgQDMZjP0ej20Wi3S09OhUChw6tSpqJoGcblc1NTUYGpqKimdykOB3mM+WMqefhSJCTzC5ASYGbT+K1/5yrjb7S74xCc+cSzTzNLSEoRCIXJzc6M+lt6DlpaWYnt7GzqdDqOjo/B6vUxQifbqSUTrwmRDJBJBrVZDoVBgc3MTer0eBoMB6enpEIvF+4I8sUAul0OpVEKr1UIqlSbwyoODEIKvfe1rvh//+MczD/aY8Yejk4RHmpwAswdt+PrXvz5usVgKP//5z7OT+YR1OBxQKpURW4+EAkVRyM3NRW5uLurq6rC7uwu9Xo/l5WUMDw+DEAKz2QxCyL6WfI8KAoEAbDYbdnd3YTQa8eabbzINduvq6hImN6R1t8PDwxCLxTG364sEfr8fn/vc57yvvvrqmEajufgoBX+C4ViLreMBRVECqVTa8cQTTzT9/d//PTdZucGhoSEIBAJUVVUlZXzgvimYwWBASkoK08yWtiWh/zcjIyOm/Wgkna0Pwu/3w2az7bMs2d3dRVpaGiPjq6+vT1hheTAMDw8jIyMjoUUFe7G9vY0PfehDnqWlpZfX19d/kxDyUBwho8EjP3PSeJAHbbt169bfXrly5RMvv/wyL9GaVJPJhO3tbZw8eTKh4x7E9vY2iouLmWWc1+tlSGEwGLC4uMh0n6a7WAezJ+FwOEfOuIQQeDyeoHYldMR4b9ds2rZEIBAws9jc3By2traSSs7a2lp0d3dDLpcnvE/M7OwsnnnmGbfJZPqy0Wj8dkIHTyLeMjPnXuTm5n48Ly/vuy+++GJKS0tLQsYkhKC7uxuVlZVJNSkOBAK4ceMGrl27Fja/5/V6YbVa4XQ6gxKLtvmk/YPotvMOhwMpKSlMNb3P5wObzQ5J8NTU1H1EDAZaeHHp0qWEfx97QTsRtra2JmzMX/ziF+Szn/2sXavVPuX3+3sSNvBx4DhtFxL5AtAilUqt//7v/54QrxClUknu3r2bMOuRUDCbzaSzszMhY3m9XuJyuYjD4SB2u53s7u6Sn//858ThcBCn00lcLhfx+Xxxn8fn85HXXnst5u7hkcLr9ZI33ngjKruZUAgEAuQv//IvfRKJRANATh6Bezba16ObZDsChJARjUZT9aUvfUn1ta99zRePIN3r9WJ+fj6h1iOhkMgUCofDYWpB09LSGM9b2sCLz+cnRL+arBKyg+BwOKitrcX09HRc2mWXy4WPfexj3u9+97v9Wq22ihCSeHfrY8BblpzA/YJtrVZb8+Mf//jWBz7wAY/dHlu6amFhgclFJhuPYv1mJMjPz094lUowSCQSsNnsmN3itVotLl686Ll79+63NRrNBfKI5jAjwVuanMB9y5P19fV3Dw0Nfev06dPuvr6+qI7f2dnB+vo6ampqknSFvwId+Iklf/qwEW0XslhBp1bm5uaicmIghOCnP/0pOX/+vGNhYeE3NRrNF0k80+8jgLc8OYH7pmEbGxvfnJ2dPfvss8/qP//5z/vc7shSWDMzM6ioqDjSEzURMJvNyMnJSWouL1nIzMyE3+9HrKuTaJCdnY2CggIsLCxE9H6z2YyPfOQjni9+8YuzKpWqxmq1/iTJl3gseFuQkwYhZEyr1Speeuml77W0tLiPap60ubmJ3d1dlJaWHsv1vVUke8FAUVRSCrBDoaamBuvr69jd3Q35HkIIXnrpJXLq1Clnd3f3H62vrze8VfeXwfC2IicAEEI8Go3mszMzM+0f/vCHN7/whS8EnUUDgQCmp6djcnyPFW9lcgLJcUcIhZSUFJSXl2N6ejro381mM37913/d84d/+IfzKpWqxmAwvPBWX8YexNuOnDQIIaNarVb+05/+9O9bWlrcBztsK5VKpKWlHVtHZKfTCZfL9UiXiB0FmpzHxQG6b8zm5q+6HxBC8J//+Z/k1KlTzq6urj9eX1+vI4Soj+WCjhlvW3ICzCz6mZmZmXMf+tCHNr/4xS/63G433G43FhcXjyV1QoMuEXvUNLTRgG6kZLFYjuV8B93it7a28NGPftTz+c9/fl6lUtUaDIb//XabLffibU1OGoSQEa1Wq/iP//iP7zc0NDi//e1vk6KiomPp50jjrZpCOYjjSqnQKCgoAJfLxZ/92Z8FTpw4Ye/o6PiqRqOpI4Soju0iHhYetgriuF8AFOXl5Xebmpqcv/jFL5KuCCLkvlrlxo0bZHd3N+nnireR0VHQ6XSkp6cnqeeg4fP5yPe+9z1/WVmZs7S09F8A5JJH4B46rtd/iZlzLwgh6qWlpQsTExOtn/vc58YuXLjg7u3tTeo5d3Z2wGazH2rX6kQhLy8P29vb8PmSV9RBCMHLL7+M5uZm17e+9a3XV1ZWKlZWVn6DELKVtJM+gnjrJdwSBELINICTFEWd++hHP/ovDQ0NRf/zf/5PXn19fcLP9VaP0u4Fl8tFVlYWtra2Er5MJ4Tg9u3b+JM/+RO3TqebVKvVv0UImT/6yLcn/suSkwYhpJeiqFKdTveeycnJH1y8eDHnW9/6FjeRbReMRmNYL6K3GuiobSLJOT4+jj/6oz/yzM3Nra2vr/8GIWQgYYO/RfFfblkbDIQQ4vV6X9VoNEWvvfbap8+dO7f97LPPegYGBuh9asyg/XbeLjMnkLigECEE169fxzve8Q73008/vXHr1q33ra+vVz4m5n38l58594LcNxP+AUVR//jyyy+/Z3Bw8HmxWCz53Oc+l/KRj3wkJtnd1tYW0tPTk9oL5LiRnZ0Nu90Ot9sdk+zR4XDg+9//Pvn+97/vdjgck0ql8osAekm8T8K3GR6TMwgekPQVAK9QFNWwubn5P77xjW9ceeaZZ3if/vSn2cXFxRGP9XZJoewFi8ViTMoiNeUi5L4P8Le//W3vG2+84QHwH+vr698kbyO5XcLxsMPFb5UXgJycnJwvy2SyzatXrzpffPFF4vV6yVG4ffs2MRgMR74vUUh2KoXGysoKGR0dPfJ9u7u75Dvf+U6gtbXVqVAolGlpab8NIJU8Ar/po/56PHNGCELINoC/pijqb9bX11uVSuVffOUrX7lw5swZzgc+8AHee9/73kOpEq/XC5vN9pYsETsKIpGIaTB8UPVkMpnw8ssv4xe/+IVrYmLCx2KxXl5bW/sWISSyMpPHAPB4WRs1CCEEwCCAd1EUxV9bW7s0NDT0qS996UtPVFVVcd/znvekPPPMM5RcLofJZEJubu6xd9M6DmRkZIAQArvdjvT0dMzPz+MnP/mJ//r16x6dTucA8LP19fUfAhgkj0hjoLcaHpMzDpD7vqdvAniToihKq9U2zs3N/cYLL7zwGzk5OVnnz59Peec730kFAoFHuu1CLPD7/dDpdPj85z/v7+np8bjdbr3NZvvB1tbWfxBCVh729b0d8JZ033srgKKoIoFA8IxQKPz9QCCgqK6upk6cOMFva2tjtbe3J00EH4tv7VEghGBtbQ337t3DwMCAb3x83LuyshJISUmZXV1dfcHv9994sOx/jATiMTmPARRF8QDU8Xi80zKZ7L1er/cUh8PJLC8v30fYeHp90oiXnIFAAGtra+jr68Pg4KBvfHzcq1QqCUVRZhaL1adSqV4jhIwAWHy8XE0uHpPzIYGiKC6AOi6X2yqXy9/r9Xpb2Wy2QCwWUw9e7MLCQo5EIqFkMhnkcjmkUinS0tLCEjgcOQOBAHZ3d7G2toa1tTVoNBpsbGwQrVbr3dzc9G9ubhK9Xo8HROxRqVS/3EPE2O0NHyMmPCbnI4QHhC0CUAigMCUlRZafn1/H5/PL/X6/1Ov15rFYLD6Xy2Xn5OSQB9aXFIfDAf1yu918Npvt9vl88Pl8xO/3w+l0Ymtri/L7/T5CiIvH4xkpilpzuVxLGxsbM4FAYAOAjn49JuKjgcfkfAviAYmFAPgAuLgf2OM8+P8BAL4DLycA0+Nl6FsLj8n5GI/xiOLtFd9/jMd4G+ExOR/jMR5RPCbnYzzGI4rH5HyMx3hE8Zicj/EYjyj+fzBnw5JuY6ZvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "\n",
    "\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax = plt.subplot(1,1,1, projection='polar')\n",
    "\n",
    "ax.set_rmax(2)\n",
    "\n",
    "Nr = 20\n",
    "xx0s = np.linspace(0,2,Nr, endpoint=True) + 1.0/(2.0*Nr)\n",
    "\n",
    "rs = []\n",
    "AMPLRHO = 1.0\n",
    "SINHW = 0.4\n",
    "for i in range(Nr):\n",
    "    rs.append(AMPLRHO * (np.exp(xx0s[i] / SINHW) - np.exp(-xx0s[i] / SINHW)) / \\\n",
    "                        (np.exp(1.0 / SINHW) - np.exp(-1.0 / SINHW)))\n",
    "\n",
    "ax.set_rgrids(rs,labels=[])\n",
    "\n",
    "thetas = np.linspace(0,360,25, endpoint=True)\n",
    "ax.set_thetagrids(thetas,labels=[])\n",
    "\n",
    "# ax.grid(True)\n",
    "ax.grid(True,linewidth='1.0')\n",
    "\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhcylindricalv2'></a>\n",
    "\n",
    "### Step 3.b.iii: **`reference_metric::CoordSystem = \"SinhCylindricalv2\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhcylindricalv2}$$\n",
    "\n",
    "Cylindrical coordinates, but with\n",
    "$$\\rho(xx_0) = \\text{AMPLRHO} \\left[\\text{const_drho}\\ xx_0 + \\frac{\\sinh\\left(\\frac{xx_0}{\\text{SINHWRHO}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWRHO}}\\right)}\\right]$$\n",
    "and \n",
    "$$z(xx_2) = \\text{AMPLZ} \\left[\\text{const_dz}\\ xx_2 + \\frac{\\sinh\\left(\\frac{xx_2}{\\text{SINHWZ}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWZ}}\\right)}\\right].$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:29.771387Z",
     "iopub.status.busy": "2021-08-29T17:43:29.770753Z",
     "iopub.status.idle": "2021-08-29T17:43:29.773164Z",
     "shell.execute_reply": "2021-08-29T17:43:29.772576Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhCylindricalv2\":\n",
    "    # Assuming the cylindrical radial coordinate\n",
    "    #   is positive makes nice simplifications of\n",
    "    #   unit vectors possible.\n",
    "    xx[0] = sp.symbols(\"xx0\", real=True)\n",
    "\n",
    "    # SinhCylindricalv2 adds the parameters \"const_drho\", \"const_dz\", which allows for regions near xx[0]=0\n",
    "    # and xx[2]=0 to have constant rho and z resolution of const_drho and const_dz, provided the sinh() terms\n",
    "    # do not dominate near xx[0]=0 and xx[2]=0.\n",
    "    xxmin = [sp.sympify(0), -M_PI, sp.sympify(-1)]\n",
    "    xxmax = [sp.sympify(1),  M_PI, sp.sympify(+1)]\n",
    "    AMPLRHO, SINHWRHO, AMPLZ, SINHWZ = par.Cparameters(\"REAL\",thismodule,\n",
    "                                                       [\"AMPLRHO\",\"SINHWRHO\",\"AMPLZ\",\"SINHWZ\"],\n",
    "                                                       [     10.0,       0.2,   10.0,    0.2])\n",
    "    const_drho, const_dz = par.Cparameters(\"REAL\",thismodule,[\"const_drho\",\"const_dz\"],[0.0625,0.0625])\n",
    "\n",
    "    RHOCYL = AMPLRHO * ( const_drho*xx[0] + (sp.exp(xx[0] / SINHWRHO) - sp.exp(-xx[0] / SINHWRHO)) / (sp.exp(1 / SINHWRHO) - sp.exp(-1 / SINHWRHO)) )\n",
    "    PHICYL = xx[1]\n",
    "    ZCYL   = AMPLZ   * ( const_dz  *xx[2] + (sp.exp(xx[2] / SINHWZ  ) - sp.exp(-xx[2] / SINHWZ  )) / (sp.exp(1 / SINHWZ  ) - sp.exp(-1 / SINHWZ  )) )\n",
    "\n",
    "    # NO CLOSED-FORM EXPRESSION FOR RADIAL OR Z INVERSION.\n",
    "    # Cart_to_xx[0] = \"NewtonRaphson\"\n",
    "    # Cart_to_xx[1] = sp.atan2(Carty, Cartx)\n",
    "    # Cart_to_xx[2] = \"NewtonRaphson\"\n",
    "\n",
    "    xx_to_Cart[0] = RHOCYL*sp.cos(PHICYL)\n",
    "    xx_to_Cart[1] = RHOCYL*sp.sin(PHICYL)\n",
    "    xx_to_Cart[2] = ZCYL\n",
    "\n",
    "    xxSph[0] = sp.sqrt(RHOCYL**2 + ZCYL**2)\n",
    "    xxSph[1] = sp.acos(ZCYL / xxSph[0])\n",
    "    xxSph[2] = PHICYL\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(RHOCYL,xx[0])\n",
    "    scalefactor_orthog[1] = RHOCYL\n",
    "    scalefactor_orthog[2] = sp.diff(ZCYL,xx[2])\n",
    "\n",
    "    # Set the unit vectors\n",
    "    UnitVectors = [[ sp.cos(PHICYL), sp.sin(PHICYL), sp.sympify(0)],\n",
    "                   [-sp.sin(PHICYL), sp.cos(PHICYL), sp.sympify(0)],\n",
    "                   [ sp.sympify(0),  sp.sympify(0),  sp.sympify(1)]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, let's set up **`SinhCylindricalv2`** coordinates and output the Christoffel symbol $\\hat{\\Gamma}^{xx_2}_{xx_2 xx_2}$, or more simply $\\hat{\\Gamma}^2_{22}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:29.837803Z",
     "iopub.status.busy": "2021-08-29T17:43:29.801784Z",
     "iopub.status.idle": "2021-08-29T17:43:30.910671Z",
     "shell.execute_reply": "2021-08-29T17:43:30.910056Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                         ⎛ 2⋅xx₂     ⎞    1                             \n",
      "                         ⎜ ──────    ⎟  ──────                          \n",
      "                         ⎜ SINHWZ    ⎟  SINHWZ                          \n",
      "                        -⎝ℯ       - 1⎠⋅ℯ                                \n",
      "────────────────────────────────────────────────────────────────────────\n",
      "       ⎛                  ⎛   2       ⎞   xx₂     ⎛ 2⋅xx₂     ⎞    1   ⎞\n",
      "       ⎜                  ⎜ ──────    ⎟  ──────   ⎜ ──────    ⎟  ──────⎟\n",
      "       ⎜                  ⎜ SINHWZ    ⎟  SINHWZ   ⎜ SINHWZ    ⎟  SINHWZ⎟\n",
      "SINHWZ⋅⎝- SINHWZ⋅const_dz⋅⎝ℯ       - 1⎠⋅ℯ       - ⎝ℯ       + 1⎠⋅ℯ      ⎠\n"
     ]
    }
   ],
   "source": [
    "par.set_parval_from_str(\"reference_metric::CoordSystem\",\"SinhCylindricalv2\")\n",
    "\n",
    "rfm.reference_metric()\n",
    "\n",
    "sp.pretty_print(sp.simplify(rfm.GammahatUDD[2][2][2]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we will soon see, defining these \"hatted\" quantities will be quite useful when expressing hyperbolic ([wave-equation](https://en.wikipedia.org/wiki/Wave_equation)-like) PDEs in non-Cartesian coordinate systems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='cartesianlike'></a>\n",
    "\n",
    "## Step 3.c: Cartesian-like coordinate systems \\[Back to [top](#toc)\\]\n",
    "$$\\label{cartesianlike}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='cartesian'></a>\n",
    "\n",
    "### Step 3.c.i: **`reference_metric::CoordSystem = \"Cartesian\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{cartesian}$$\n",
    "\n",
    "Standard Cartesian coordinates, with $(x,y,z)=$ `(xx0,xx1,xx2)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:30.918339Z",
     "iopub.status.busy": "2021-08-29T17:43:30.917732Z",
     "iopub.status.idle": "2021-08-29T17:43:30.919908Z",
     "shell.execute_reply": "2021-08-29T17:43:30.919368Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"Cartesian\":\n",
    "    xmin, xmax, ymin, ymax, zmin, zmax = par.Cparameters(\"REAL\",thismodule,\n",
    "                                                         [\"xmin\",\"xmax\",\"ymin\",\"ymax\",\"zmin\",\"zmax\"],\n",
    "                                                         [ -10.0,  10.0, -10.0,  10.0, -10.0,  10.0])\n",
    "    xxmin = [\"xmin\", \"ymin\", \"zmin\"]\n",
    "    xxmax = [\"xmax\", \"ymax\", \"zmax\"]\n",
    "\n",
    "    xx_to_Cart[0] = xx[0]\n",
    "    xx_to_Cart[1] = xx[1]\n",
    "    xx_to_Cart[2] = xx[2]\n",
    "\n",
    "    xxSph[0] = sp.sqrt(xx[0] ** 2 + xx[1] ** 2 + xx[2] ** 2)\n",
    "    xxSph[1] = sp.acos(xx[2] / xxSph[0])\n",
    "    xxSph[2] = sp.atan2(xx[1], xx[0])\n",
    "\n",
    "    Cart_to_xx[0] = Cartx\n",
    "    Cart_to_xx[1] = Carty\n",
    "    Cart_to_xx[2] = Cartz\n",
    "\n",
    "    scalefactor_orthog[0] = sp.sympify(1)\n",
    "    scalefactor_orthog[1] = sp.sympify(1)\n",
    "    scalefactor_orthog[2] = sp.sympify(1)\n",
    "\n",
    "    # Set the transpose of the matrix of unit vectors\n",
    "    UnitVectors = [[sp.sympify(1), sp.sympify(0), sp.sympify(0)],\n",
    "                   [sp.sympify(0), sp.sympify(1), sp.sympify(0)],\n",
    "                   [sp.sympify(0), sp.sympify(0), sp.sympify(1)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:30.964793Z",
     "iopub.status.busy": "2021-08-29T17:43:30.935236Z",
     "iopub.status.idle": "2021-08-29T17:43:31.041772Z",
     "shell.execute_reply": "2021-08-29T17:43:31.041134Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np               # NumPy: A numerical methods module for Python\n",
    "import matplotlib.pyplot as plt  # matplotlib: Python module specializing in plotting capabilities\n",
    "\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "Nx = 16\n",
    "ax.set_xticks(np.arange(0, 1., 1./Nx))\n",
    "ax.set_yticks(np.arange(0, 1., 1./Nx))\n",
    "\n",
    "for tick in ax.get_xticklabels():\n",
    "    tick.set_rotation(60)\n",
    "\n",
    "# plt.scatter(x, y)\n",
    "ax.set_aspect('equal')\n",
    "\n",
    "plt.grid()\n",
    "\n",
    "# plt.savefig(\"Cartgrid.png\",dpi=300)\n",
    "plt.show()\n",
    "# plt.close(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhcartesian'></a>\n",
    "\n",
    "### Step 3.c.ii: **`reference_metric::CoordSystem = \"SinhCartesian\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhcartesian}$$\n",
    "\n",
    "In this coordinate system, all three coordinates behave like the $z$-coordinate in SinhCylindrical coordinates, i.e.\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "x(xx_0) &= \\text{AMPLXYZ} \\left[\\frac{\\sinh\\left(\\frac{xx_0}{\\text{SINHWXYZ}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWXYZ}}\\right)}\\right]\\ ,\\\\\n",
    "y(xx_1) &= \\text{AMPLXYZ} \\left[\\frac{\\sinh\\left(\\frac{xx_1}{\\text{SINHWXYZ}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWXYZ}}\\right)}\\right]\\ ,\\\\\n",
    "z(xx_2) &= \\text{AMPLXYZ} \\left[\\frac{\\sinh\\left(\\frac{xx_2}{\\text{SINHWXYZ}}\\right)}{\\sinh\\left(\\frac{1}{\\text{SINHWXYZ}}\\right)}\\right].\n",
    "\\end{align}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:31.050239Z",
     "iopub.status.busy": "2021-08-29T17:43:31.049599Z",
     "iopub.status.idle": "2021-08-29T17:43:31.052110Z",
     "shell.execute_reply": "2021-08-29T17:43:31.051335Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhCartesian\":\n",
    "    # SinhCartesian coordinates allows us to push the outer boundary of the\n",
    "    # computational domain a lot further away, while keeping reasonably high\n",
    "    # resolution towards the center of the computational grid.\n",
    "\n",
    "    # Set default values for min and max (x,y,z)\n",
    "    xxmin = [sp.sympify(-1), sp.sympify(-1), sp.sympify(-1)]\n",
    "    xxmax = [sp.sympify(+1), sp.sympify(+1), sp.sympify(+1)]\n",
    "\n",
    "    # Declare basic parameters of the coordinate system and their default values\n",
    "    AMPLXYZ, SINHWXYZ = par.Cparameters(\"REAL\", thismodule,\n",
    "                                        [\"AMPLXYZ\", \"SINHWXYZ\"],\n",
    "                                        [     10.0,        0.2])\n",
    "\n",
    "    # Compute (xx_to_Cart0,xx_to_Cart1,xx_to_Cart2) from (xx0,xx1,xx2)\n",
    "    for ii in [0, 1, 2]:\n",
    "        xx_to_Cart[ii] = AMPLXYZ*(sp.exp(xx[ii]/SINHWXYZ) - sp.exp(-xx[ii]/SINHWXYZ))/(sp.exp(1/SINHWXYZ) - sp.exp(-1/SINHWXYZ))\n",
    "\n",
    "    # Compute (r,th,ph) from (xx_to_Cart2,xx_to_Cart1,xx_to_Cart2)\n",
    "    xxSph[0] = sp.sqrt(xx_to_Cart[0] ** 2 + xx_to_Cart[1] ** 2 + xx_to_Cart[2] ** 2)\n",
    "    xxSph[1] = sp.acos(xx_to_Cart[2] / xxSph[0])\n",
    "    xxSph[2] = sp.atan2(xx_to_Cart[1], xx_to_Cart[0])\n",
    "\n",
    "    # Compute (xx0,xx1,xx2) from (Cartx,Carty,Cartz)\n",
    "    Cart_to_xx[0] = SINHWXYZ*sp.asinh(Cartx*sp.sinh(1/SINHWXYZ)/AMPLXYZ)\n",
    "    Cart_to_xx[1] = SINHWXYZ*sp.asinh(Carty*sp.sinh(1/SINHWXYZ)/AMPLXYZ)\n",
    "    Cart_to_xx[2] = SINHWXYZ*sp.asinh(Cartz*sp.sinh(1/SINHWXYZ)/AMPLXYZ)\n",
    "\n",
    "    # Compute scale factors\n",
    "    scalefactor_orthog[0] = sp.diff(xx_to_Cart[0], xx[0])\n",
    "    scalefactor_orthog[1] = sp.diff(xx_to_Cart[1], xx[1])\n",
    "    scalefactor_orthog[2] = sp.diff(xx_to_Cart[2], xx[2])\n",
    "\n",
    "    # Set the transpose of the matrix of unit vectors\n",
    "    UnitVectors = [[sp.sympify(1), sp.sympify(0), sp.sympify(0)],\n",
    "                   [sp.sympify(0), sp.sympify(1), sp.sympify(0)],\n",
    "                   [sp.sympify(0), sp.sympify(0), sp.sympify(1)]]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:31.072092Z",
     "iopub.status.busy": "2021-08-29T17:43:31.071445Z",
     "iopub.status.idle": "2021-08-29T17:43:31.195468Z",
     "shell.execute_reply": "2021-08-29T17:43:31.194853Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np               # NumPy: A numerical methods module for Python\n",
    "import matplotlib.pyplot as plt  # matplotlib: Python module specializing in plotting capabilities\n",
    "\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure(dpi=160)\n",
    "ax = fig.gca()\n",
    "\n",
    "# Set plot title\n",
    "ax.set_title(r\"$z=0$ slice of the 3D grid\")\n",
    "\n",
    "# Set SINH parameters. Here we assume:\n",
    "#\n",
    "# AMPLX  = AMPLY  = SINHA\n",
    "# SINHWX = SINHWY = SINHW\n",
    "SINHA = 10.0\n",
    "SINHW = 0.45\n",
    "\n",
    "# Set number of points. We assume the same point\n",
    "# distribution along the (x,y)-directions\n",
    "Nxxs = 24\n",
    "xxis = np.linspace(-1,1,Nxxs, endpoint=True)\n",
    "\n",
    "# Compute axis ticks by evaluating x and y using SinhCartesian coordinates\n",
    "axis_ticks = []\n",
    "for i in range(Nxxs):\n",
    "    axis_ticks.append(SINHA * (np.exp(xxis[i] / SINHW) - np.exp(-xxis[i] / SINHW)) / \\\n",
    "                        (np.exp(1.0 / SINHW) - np.exp(-1.0 / SINHW)))\n",
    "\n",
    "# Set the axis ticks\n",
    "ax.set_xticks(axis_ticks)\n",
    "ax.set_yticks(axis_ticks)\n",
    "\n",
    "# Set x and y labels. Initialize array with empty strings\n",
    "labelsx = [\"\" for i in range(Nxxs)]\n",
    "labelsy = [\"\" for i in range(Nxxs)]\n",
    "\n",
    "# Set x_min and x_max tick label\n",
    "labelsx[0] = r\"-AMPLX\"\n",
    "labelsx[-1] = r\"AMPLX\"\n",
    "\n",
    "# Set y_min and y_max tick label\n",
    "labelsy[0] = r\"-AMPLY\"\n",
    "labelsy[-1] = r\"AMPLY\"\n",
    "\n",
    "# Set tick labels\n",
    "ax.set_xticklabels(labelsx)\n",
    "ax.set_yticklabels(labelsy)\n",
    "\n",
    "# Rotate x labels by 60 degrees\n",
    "for tick in ax.get_xticklabels():\n",
    "    tick.set_rotation(60)\n",
    "\n",
    "# Draw the x=0 and y=0 ticklabel\n",
    "ax.text(0,-11,\"0\",ha=\"center\",va=\"center\")\n",
    "ax.text(-11,0,\"0\",ha=\"center\",va=\"center\")\n",
    "\n",
    "# plt.scatter(x, y)\n",
    "ax.set_aspect('equal')\n",
    "\n",
    "plt.grid(color='black',linewidth=0.3)\n",
    "\n",
    "plt.show()\n",
    "# plt.savefig(\"Cartgrid.png\",dpi=400)\n",
    "# plt.close(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='prolatespheroidal'></a>\n",
    "\n",
    "## Step 3.d: [Prolate spheroidal](https://en.wikipedia.org/wiki/Prolate_spheroidal_coordinates)-like coordinate systems \\[Back to [top](#toc)\\]\n",
    "$$\\label{prolatespheroidal}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='symtp'></a>\n",
    "\n",
    "### Step 3.d.i: **`reference_metric::CoordSystem = \"SymTP\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{symtp}$$\n",
    "\n",
    "The Symmetric TwoPuncture (SymTP) coordinate system is obtained by slightly modifying [prolate spheroidal coordinates](https://en.wikipedia.org/wiki/Prolate_spheroidal_coordinates) (PSC). Standard PSC are related to Cartesian coordinates $(x,y,z)$ via\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "x &= a\\sinh\\mu\\sin\\nu\\cos\\varphi,\\\\\n",
    "y &= a\\sinh\\mu\\sin\\nu\\sin\\varphi,\\\\\n",
    "z &= a\\cosh\\mu\\cos\\nu = \\left(a^{2}\\sinh^{2}\\mu + a^{2}\\right)^{1/2}\\cos\\nu,\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "where $\\mu\\in[0,\\infty)$, $\\nu\\in[0,\\pi]$, and $\\varphi\\in[0,2\\pi]$, and we have used the [identity](https://en.wikipedia.org/wiki/Hyperbolic_functions)\n",
    "\n",
    "$$\n",
    "\\cosh^{2}\\mu - \\sinh^{2}\\mu = 1.\n",
    "$$\n",
    "\n",
    "PSC have two foci located at $z=\\pm a$, where the grid lines get more dense and the grid resolution increases. However, note that the parameter $a$ controls both the foci position *and* the grid scaling, which is not a particularly interesting property.\n",
    "\n",
    "In order to remedy this, we introduce new coordinates $(xx_{0},xx_{1},xx_{2})$, such that\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "xx_{0} &= \\frac{1}{a}\\sinh\\mu,\\\\\n",
    "xx_{1} &= \\nu,\\\\\n",
    "xx_{2} &= \\varphi,\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "and change $a\\to \\text{bScale}$, so that we obtain\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "x &= xx_{0}\\sin(xx_{1})\\cos(xx_{2}),\\\\\n",
    "y &= xx_{0}\\sin(xx_{1})\\sin(xx_{2}),\\\\\n",
    "z &= \\left(xx_{0}^{2}+\\text{bScale}^{2}\\right)\\cos(xx_{1}),\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "Note that, for numerical convenience, we change the range of $xx_{2}$ to $[-\\pi,\\pi]$. Comparing SymTP coordinates with Cylindrical coordinates, we find that $(\\rho,\\phi,z)=(xx_{0}\\sin(xx_{1}), xx_{2}, \\sqrt{xx_{0}^2 + \\text{bScale}^2}\\cos(xx_{1}))$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:31.204621Z",
     "iopub.status.busy": "2021-08-29T17:43:31.203911Z",
     "iopub.status.idle": "2021-08-29T17:43:31.206836Z",
     "shell.execute_reply": "2021-08-29T17:43:31.206297Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SymTP\":\n",
    "\n",
    "    var1, var2= sp.symbols('var1 var2',real=True)\n",
    "    bScale, AW, AMAX, RHOMAX, ZMIN, ZMAX = par.Cparameters(\"REAL\",thismodule,\n",
    "                                                           [\"bScale\",\"AW\",\"AMAX\",\"RHOMAX\",\"ZMIN\",\"ZMAX\"],\n",
    "                                                           [0.5,     0.2,   10.0,    10.0, -10.0,  10.0])\n",
    "\n",
    "    # Assuming xx0, xx1, and bScale\n",
    "    #   are positive makes nice simplifications of\n",
    "    #   unit vectors possible.\n",
    "    xx[0],xx[1] = sp.symbols(\"xx0 xx1\", real=True)\n",
    "\n",
    "    xxmin = [sp.sympify(0), sp.sympify(0),-M_PI]\n",
    "    xxmax = [         AMAX,          M_PI, M_PI]\n",
    "\n",
    "    AA = xx[0]\n",
    "\n",
    "    var1 = sp.sqrt(AA**2 + (bScale * sp.sin(xx[1]))**2)\n",
    "    var2 = sp.sqrt(AA**2 + bScale**2)\n",
    "\n",
    "    RHOSYMTP = AA*sp.sin(xx[1])\n",
    "    PHSYMTP = xx[2]\n",
    "    ZSYMTP = var2*sp.cos(xx[1])\n",
    "\n",
    "    xx_to_Cart[0] = AA  *sp.sin(xx[1])*sp.cos(xx[2])\n",
    "    xx_to_Cart[1] = AA  *sp.sin(xx[1])*sp.sin(xx[2])\n",
    "    xx_to_Cart[2] = ZSYMTP\n",
    "\n",
    "    xxSph[0] = sp.sqrt(RHOSYMTP**2 + ZSYMTP**2)\n",
    "    xxSph[1] = sp.acos(ZSYMTP / xxSph[0])\n",
    "    xxSph[2] = PHSYMTP\n",
    "\n",
    "    rSph  = sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2)\n",
    "    thSph = sp.acos(Cartz / rSph)\n",
    "    phSph = sp.atan2(Carty, Cartx)\n",
    "\n",
    "    # Mathematica script to compute Cart_to_xx[]\n",
    "    #             AA = x1;\n",
    "    #             var2 = Sqrt[AA^2 + bScale^2];\n",
    "    #             RHOSYMTP = AA*Sin[x2];\n",
    "    #             ZSYMTP = var2*Cos[x2];\n",
    "    #             Solve[{rSph == Sqrt[RHOSYMTP^2 + ZSYMTP^2],\n",
    "    #                    thSph == ArcCos[ZSYMTP/Sqrt[RHOSYMTP^2 + ZSYMTP^2]],\n",
    "    #                    phSph == x3},\n",
    "    #                   {x1, x2, x3}]\n",
    "    Cart_to_xx[0] = sp.sqrt(-bScale**2 + rSph**2 +\n",
    "                            sp.sqrt(bScale**4 + 2*bScale**2*rSph**2 + rSph**4 -\n",
    "                                    4*bScale**2*rSph**2*sp.cos(thSph)**2))*M_SQRT1_2 # M_SQRT1_2 = 1/sqrt(2); define this way for UnitTesting\n",
    "\n",
    "    # The sign() function in the following expression ensures the correct root is taken.\n",
    "    Cart_to_xx[1] = sp.acos(sp.sign(Cartz)*(\n",
    "                              sp.sqrt(1 + rSph**2/bScale**2 -\n",
    "                                      sp.sqrt(bScale**4 + 2*bScale**2*rSph**2 + rSph**4 -\n",
    "                                              4*bScale**2*rSph**2*sp.cos(thSph)**2)/bScale**2)*M_SQRT1_2)) # M_SQRT1_2 = 1/sqrt(2); define this way for UnitTesting\n",
    "\n",
    "    Cart_to_xx[2] = phSph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "Nxxs   = 24\n",
    "xx0    = np.linspace(-2,2,Nxxs,endpoint=True)\n",
    "xx1    = np.linspace(0,np.pi,Nxxs,endpoint=True)\n",
    "xx2    = 0\n",
    "bScale = 1\n",
    "\n",
    "def x(xx0,xx1):\n",
    "    return xx0 * np.sin(xx1)\n",
    "def z(xx0,xx1,bScale):\n",
    "    return np.sqrt(xx0**2 + bScale**2) * np.cos(xx1)\n",
    "\n",
    "import numpy as np               # NumPy: A numerical methods module for Python\n",
    "import matplotlib.pyplot as plt  # matplotlib: Python module specializing in plotting capabilities\n",
    "\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure(dpi=160)\n",
    "ax = fig.gca()\n",
    "\n",
    "# Set plot title\n",
    "ax.set_title(r\"\"\"SymTP Coordinates: zx-plane ($xx_{2}$=0 and $xx_{2}=\\pi$)\n",
    "Blue (red) lines have constant $xx_{0}$ ($xx_{1}$)\"\"\")\n",
    "\n",
    "ax.set_xlim(-2.5,2.5)\n",
    "ax.set_ylim(-2.5,2.5)\n",
    "ax.set_aspect('equal')\n",
    "ax.axis('off')\n",
    "\n",
    "for i0 in range(Nxxs):\n",
    "    plt.plot(x(xx0[i0],xx1),z(xx0[i0],xx1,bScale),'b',lw=0.75)\n",
    "\n",
    "for i1 in range(Nxxs):\n",
    "    plt.plot(x(xx0,xx1[i1]),z(xx0,xx1[i1],bScale),'r',lw=0.75)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sinhsymtp'></a>\n",
    "\n",
    "### Step 3.d.ii: **`reference_metric::CoordSystem = \"SinhSymTP\"`** \\[Back to [top](#toc)\\]\n",
    "$$\\label{sinhsymtp}$$\n",
    "\n",
    "SinhSymTP coordinates are obtained from SymTP coordinates by making the substitution\n",
    "\n",
    "$$\n",
    "xx0 \\to \\mathcal{A}\\frac{\\sinh(xx_{0}/w)}{\\sinh(1/w)},\n",
    "$$\n",
    "\n",
    "with the further modification that $xx_{0}\\in[0,1]$. The parameter $\\mathcal{A}$ controls the scale of the grid, while the parameter $w$ controls how densily sampled the region around the foci are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:31.216338Z",
     "iopub.status.busy": "2021-08-29T17:43:31.215635Z",
     "iopub.status.idle": "2021-08-29T17:43:31.218456Z",
     "shell.execute_reply": "2021-08-29T17:43:31.217832Z"
    }
   },
   "outputs": [],
   "source": [
    "if CoordSystem == \"SinhSymTP\":\n",
    "\n",
    "    var1, var2= sp.symbols('var1 var2',real=True)\n",
    "    bScale, AW, AMAX, RHOMAX, ZMIN, ZMAX = par.Cparameters(\"REAL\",thismodule,\n",
    "                                                           [\"bScale\",\"AW\",\"AMAX\",\"RHOMAX\",\"ZMIN\",\"ZMAX\"],\n",
    "                                                           [0.5,     0.2,   10.0,    10.0, -10.0,  10.0])\n",
    "\n",
    "    # Assuming xx0, xx1, and bScale\n",
    "    #   are positive makes nice simplifications of\n",
    "    #   unit vectors possible.\n",
    "    xx[0],xx[1] = sp.symbols(\"xx0 xx1\", real=True)\n",
    "\n",
    "    xxmin = [sp.sympify(0), sp.sympify(0),-M_PI]\n",
    "    xxmax = [sp.sympify(1),          M_PI, M_PI]\n",
    "\n",
    "    AA = AMAX * (sp.exp(xx[0]/SINHWAA) - sp.exp(-xx[0]/SINHWAA)) / (sp.exp(1/SINHWAA) - sp.exp(-1/SINHWAA))\n",
    "\n",
    "    var1 = sp.sqrt(AA**2 + (bScale * sp.sin(xx[1]))**2)\n",
    "    var2 = sp.sqrt(AA**2 + bScale**2)\n",
    "\n",
    "    RHOSYMTP = AA*sp.sin(xx[1])\n",
    "    PHSYMTP = xx[2]\n",
    "    ZSYMTP = var2*sp.cos(xx[1])\n",
    "\n",
    "    xx_to_Cart[0] = AA*sp.sin(xx[1])*sp.cos(xx[2])\n",
    "    xx_to_Cart[1] = AA*sp.sin(xx[1])*sp.sin(xx[2])\n",
    "    xx_to_Cart[2] = ZSYMTP\n",
    "\n",
    "    xxSph[0] = sp.sqrt(RHOSYMTP**2 + ZSYMTP**2)\n",
    "    xxSph[1] = sp.acos(ZSYMTP / xxSph[0])\n",
    "    xxSph[2] = PHSYMTP\n",
    "\n",
    "    rSph  = sp.sqrt(Cartx ** 2 + Carty ** 2 + Cartz ** 2)\n",
    "    thSph = sp.acos(Cartz / rSph)\n",
    "    phSph = sp.atan2(Carty, Cartx)\n",
    "\n",
    "    # Mathematica script to compute Cart_to_xx[]\n",
    "    #             AA = x1;\n",
    "    #             var2 = Sqrt[AA^2 + bScale^2];\n",
    "    #             RHOSYMTP = AA*Sin[x2];\n",
    "    #             ZSYMTP = var2*Cos[x2];\n",
    "    #             Solve[{rSph == Sqrt[RHOSYMTP^2 + ZSYMTP^2],\n",
    "    #                    thSph == ArcCos[ZSYMTP/Sqrt[RHOSYMTP^2 + ZSYMTP^2]],\n",
    "    #                    phSph == x3},\n",
    "    #                   {x1, x2, x3}]\n",
    "    Cart_to_xx[0] = sp.sqrt(-bScale**2 + rSph**2 +\n",
    "                            sp.sqrt(bScale**4 + 2*bScale**2*rSph**2 + rSph**4 -\n",
    "                                    4*bScale**2*rSph**2*sp.cos(thSph)**2))*M_SQRT1_2 # M_SQRT1_2 = 1/sqrt(2); define this way for UnitTesting\n",
    "\n",
    "    # The sign() function in the following expression ensures the correct root is taken.\n",
    "    Cart_to_xx[1] = sp.acos(sp.sign(Cartz)*(\n",
    "                              sp.sqrt(1 + rSph**2/bScale**2 -\n",
    "                                      sp.sqrt(bScale**4 + 2*bScale**2*rSph**2 + rSph**4 -\n",
    "                                              4*bScale**2*rSph**2*sp.cos(thSph)**2)/bScale**2)*M_SQRT1_2)) # M_SQRT1_2 = 1/sqrt(2); define this way for UnitTesting\n",
    "\n",
    "    Cart_to_xx[2] = phSph\n",
    "\n",
    "    scalefactor_orthog[0] = sp.diff(AA,xx[0]) * var1 / var2\n",
    "    scalefactor_orthog[1] = var1\n",
    "    scalefactor_orthog[2] = AA * sp.sin(xx[1])\n",
    "\n",
    "    # Set the transpose of the matrix of unit vectors\n",
    "    UnitVectors = [[sp.sin(xx[1]) * sp.cos(xx[2]) * var2 / var1,\n",
    "                    sp.sin(xx[1]) * sp.sin(xx[2]) * var2 / var1,\n",
    "                    AA * sp.cos(xx[1]) / var1],\n",
    "                   [AA * sp.cos(xx[1]) * sp.cos(xx[2]) / var1,\n",
    "                    AA * sp.cos(xx[1]) * sp.sin(xx[2]) / var1,\n",
    "                        -sp.sin(xx[1]) * var2 / var1],\n",
    "                   [-sp.sin(xx[2]), sp.cos(xx[2]), sp.sympify(0)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np               # NumPy: A numerical methods module for Python\n",
    "import matplotlib.pyplot as plt  # matplotlib: Python module specializing in plotting capabilities\n",
    "\n",
    "Nxx0   = 12\n",
    "Nxx1   = 24\n",
    "xx0    = np.linspace(0,1,Nxx0,endpoint=True)\n",
    "xx1    = np.linspace(0,np.pi,Nxx1,endpoint=True)\n",
    "xx2    = 0\n",
    "bScale = 1\n",
    "sinhA  = 2.2\n",
    "sinhW  = 0.3\n",
    "\n",
    "def rtilde(xx0,sinhA,sinhW):\n",
    "    return sinhA * np.sinh(xx0/sinhW) / np.sinh(1.0/sinhW)\n",
    "def x(xx0,xx1,sinhA,sinhW):\n",
    "    return rtilde(xx0,sinhA,sinhW) * np.sin(xx1)\n",
    "def z(xx0,xx1,bScale,sinhA,sinhW):\n",
    "    return np.sqrt(rtilde(xx0,sinhA,sinhW)**2 + bScale**2) * np.cos(xx1)\n",
    "\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure(dpi=160)\n",
    "ax = fig.gca()\n",
    "\n",
    "# Set plot title\n",
    "ax.set_title(r\"\"\"SinhSymTP Coordinates: zx-plane ($xx_{2}$=0 and $xx_{2}=\\pi$)\n",
    "Blue (red) lines have constant $xx_{0}$ ($xx_{1}$)\"\"\")\n",
    "\n",
    "ax.set_xlim(-2.5,2.5)\n",
    "ax.set_ylim(-2.5,2.5)\n",
    "ax.set_aspect('equal')\n",
    "ax.axis('off')\n",
    "\n",
    "for i0 in range(Nxx0):\n",
    "    plt.plot(x(xx0[i0],xx1,sinhA,sinhW),z(xx0[i0],xx1,bScale,sinhA,sinhW),'b',lw=0.75)\n",
    "    plt.plot(-x(xx0[i0],xx1,sinhA,sinhW),z(xx0[i0],xx1,bScale,sinhA,sinhW),'b',lw=0.75)\n",
    "\n",
    "for i1 in range(Nxx1):\n",
    "    plt.plot(x(xx0,xx1[i1],sinhA,sinhW),z(xx0,xx1[i1],bScale,sinhA,sinhW),'r',lw=0.75)\n",
    "    plt.plot(-x(xx0,xx1[i1],sinhA,sinhW),z(xx0,xx1[i1],bScale,sinhA,sinhW),'r',lw=0.75)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='latex_pdf_output'></a>\n",
    "\n",
    "# Step 4: Output this notebook to $\\LaTeX$-formatted PDF file \\[Back to [top](#toc)\\]\n",
    "$$\\label{latex_pdf_output}$$\n",
    "\n",
    "The following code cell converts this Jupyter notebook into a proper, clickable $\\LaTeX$-formatted PDF file. After the cell is successfully run, the generated PDF may be found in the root NRPy+ tutorial directory, with filename\n",
    "[Tutorial-Reference_Metric.pdf](Tutorial-Reference_Metric.pdf). (Note that clicking on this link may not work; you may need to open the PDF file through another means.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-29T17:43:31.223012Z",
     "iopub.status.busy": "2021-08-29T17:43:31.222416Z",
     "iopub.status.idle": "2021-08-29T17:43:38.463277Z",
     "shell.execute_reply": "2021-08-29T17:43:38.463991Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created Tutorial-Reference_Metric.tex, and compiled LaTeX file to PDF file\n",
      "    Tutorial-Reference_Metric.pdf\n"
     ]
    }
   ],
   "source": [
    "import cmdline_helper as cmd    # NRPy+: Multi-platform Python command-line interface\n",
    "cmd.output_Jupyter_notebook_to_LaTeXed_PDF(\"Tutorial-Reference_Metric\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}