Kite_Investigation/surrogate/nn_kite_modell.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "45a82489",
   "metadata": {},
   "source": [
    "# Neural network system model for towing Kite\n",
    "\n",
    "In this Jupyter Notebook we train the neural network system model for the towing kite."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "84d9b784",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "sys.path.append('../../../do-mpc/')\n",
    "import do_mpc\n",
    "import pandas as pd\n",
    "import scipy.io as sio\n",
    "import pathlib\n",
    "\n",
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from nn_tools import get_keras_model, NNPredictModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c6696b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d85189ad",
   "metadata": {},
   "source": [
    "## Load prepared training / test and validation data\n",
    "\n",
    "See Jupyter Notebook ``train_test_val_data_prep.ipynb`` for details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bb2bd2de",
   "metadata": {},
   "outputs": [],
   "source": [
    "load_name = 'S01_Prep_01'\n",
    "load_path = './data_prep/'\n",
    "\n",
    "data = do_mpc.tools.load_pickle(load_path + load_name + '.pkl')\n",
    "\n",
    "nn_in_train_scaled = data['in_train_scaled']\n",
    "nn_in_test_scaled = data['in_test_scaled']\n",
    "nn_out_train_scaled = data['out_train_scaled']\n",
    "nn_out_test_scaled = data['out_test_scaled']\n",
    "\n",
    "# preprocessing.StandardScaler() objects:\n",
    "in_scaler = data['in_scaler']\n",
    "out_scaler = data['out_scaler']\n",
    "\n",
    "# Test sequences:\n",
    "test_res = data['test_res']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "707a32a1",
   "metadata": {},
   "source": [
    "## Create and train neural network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e976904",
   "metadata": {},
   "source": [
    "Get the keras NN model for prediction ``model`` and the ``activation_model`` for the computation of the BLL covariance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f672c186",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-12-01 14:34:06.002552: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-12-01 14:34:06.002747: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(99)\n",
    "tf.random.set_seed(99)\n",
    "\n",
    "architecture = [nn_in_train_scaled.shape[1], 20,20, nn_out_train_scaled.shape[1]]\n",
    "\n",
    "nn_model, activation_model = get_keras_model(architecture, 'tanh')\n",
    "\n",
    "nn_model.compile(\n",
    "    optimizer=tf.keras.optimizers.Adam(learning_rate=0.001),\n",
    "    loss=tf.keras.losses.MSE,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3562fcca",
   "metadata": {},
   "source": [
    "Train the neural network. We capture the output to better display the results on Github."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6d973b72",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-12-01 14:34:09.422074: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n"
     ]
    }
   ],
   "source": [
    "%%capture\n",
    "history = nn_model.fit(\n",
    "    nn_in_train_scaled, \n",
    "    nn_out_train_scaled,\n",
    "    validation_data = (nn_in_test_scaled, nn_out_test_scaled),\n",
    "    epochs=1000,\n",
    "    batch_size=200,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7af5ed3",
   "metadata": {},
   "source": [
    "Plot the training progression (training loss and validation loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b8b6b3f8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb9c2005e20>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.semilogy(history.history['loss'], label='training loss')\n",
    "ax.semilogy(history.history['val_loss'], label='validation loss')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8edfb3b8",
   "metadata": {},
   "source": [
    "## Open-loop predictions\n",
    "\n",
    "Compute an open-loop prediction for one of the test cases. Choose the case with ``case = ...``.\n",
    "The open-loop predictions are computed through the class ``NNPredictModel``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6edd41f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "case = 0\n",
    "\n",
    "x0 = (test_res[case]['states'][0]).reshape(-1,1)\n",
    "a_train = activation_model.predict(nn_in_train_scaled)\n",
    "\n",
    "pm = NNPredictModel(nn_model, activation_model, \n",
    "                    a_train, in_scaler, out_scaler, x0,\n",
    "                   sig_e=1, sig_w=1e3)\n",
    "\n",
    "for k in range(test_res[case]['states'].shape[0]):\n",
    "    u0 = test_res[case]['input'][k]\n",
    "    p = test_res[case]['wind'][k]\n",
    "    pm.make_step(u0,p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bf24bf15",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fb9c27f59d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(3,1, sharex=True, figsize=(10,5))\n",
    "\n",
    "ax[0].plot(pm.aux[:,0],label='true')\n",
    "ax[0].plot(test_res[case]['T_F'], label='pred')\n",
    "ax[0].set_ylabel('tether force')\n",
    "ax[0].legend()\n",
    "\n",
    "ax[1].plot(pm.aux[:,1])\n",
    "ax[1].plot(test_res[case]['height'])\n",
    "ax[1].set_ylabel('Kite height')\n",
    "\n",
    "ax[2].plot(pm.v, label='BLL covariance')\n",
    "ax[2].set_ylabel('uncertainty')\n",
    "\n",
    "trust_threshold = 0.02\n",
    "ax[2].axhline(trust_threshold, label='trust threshold', color='k')\n",
    "ax[2].legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b1a3fb9",
   "metadata": {},
   "source": [
    "Compute open-loop predictions for all test cases:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60d5b1fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "nn_traj = []\n",
    "nn_trust = []\n",
    "n_eval = min(20,len(test_res))\n",
    "\n",
    "for i, res_i in enumerate(test_res[:n_eval]):\n",
    "    x0 = (res_i['states'][0]).reshape(-1,1)\n",
    "    pm.reset(x0)\n",
    "\n",
    "    for k in range(res_i['states'].shape[0]):\n",
    "        u0 = res_i['input'][k]\n",
    "        p = res_i['wind'][k]\n",
    "        pm.make_step(u0,p)\n",
    "    \n",
    "    nn_traj.append(pm.x)\n",
    "    nn_trust.append(pm.v)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d693cd05",
   "metadata": {},
   "source": [
    "Plot all test cases ($\\phi$, $\\theta$ diagram) and flag points with trust violations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fc403548",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_row = int(np.ceil(np.sqrt(n_eval)))\n",
    "n_col = int(np.ceil(n_eval/n_row))\n",
    "\n",
    "trust_threshold = 0.02\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(n_row, n_col, sharex=True, sharey=True, figsize=(8,8))\n",
    "for i, res_i in enumerate(test_res[:n_eval]):\n",
    "    ax[i//n_col, np.mod(i,n_col)].plot(res_i['states'][:,1],res_i['states'][:,0], label='true')\n",
    "    ax[i//n_col, np.mod(i,n_col)].plot(nn_traj[i][:,1], nn_traj[i][:,0], label='prediction')\n",
    "    \n",
    "    viol_ind = (nn_trust[i]>= trust_threshold).flatten()\n",
    "    ax[i//n_col, np.mod(i,n_col)].plot(nn_traj[i][1:,:][viol_ind,1], nn_traj[i][1:,:][viol_ind,0],\n",
    "                                      'x', color='red', label='trust violation')\n",
    "    \n",
    "    \n",
    "for i in range(ax.size):\n",
    "    ax[i//n_col, np.mod(i,n_col)].axis('off')\n",
    "\n",
    "ax[0,0].legend()\n",
    "ax[0,0].set_xlim(-np.pi/2,np.pi/2)\n",
    "ax[0,0].set_ylim(0,np.pi/2)\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d67c354",
   "metadata": {},
   "source": [
    "## Export model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "84c75bcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "export_bool = False\n",
    "\n",
    "if export_bool:\n",
    "    export_name = 'S01_NN_M01'\n",
    "    export_path = './nn_models/{}/'\n",
    "    pathlib.Path(export_path.format(export_name)).mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "    export_dict = {'a_train': a_train, 'in_scaler': in_scaler, 'out_scaler': out_scaler, 'C': pm.C}\n",
    "\n",
    "    do_mpc.tools.save_pickle(export_path.format(export_name) + export_name + '_aux.pkl', export_dict)\n",
    "\n",
    "    nn_model.save(export_path.format(export_name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5af63762",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-171.2210149152047"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checksum\n",
    "np.sum(nn_traj)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e98f66b8",
   "metadata": {},
   "source": [
    "Ensure that the trained model produces this result for the checksum:\n",
    "\n",
    "S01_NN_M01: -171.2210149152047"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}