NeuroDiffeq_LogisticEquation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With solve (OLD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from neurodiffeq import diff\n",
    "from neurodiffeq.ode import solve\n",
    "from neurodiffeq.conditions import IVP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\arazs\\.conda\\envs\\tensorenviron\\lib\\site-packages\\neurodiffeq\\ode.py:262: FutureWarning: The `solve_system` function is deprecated, use a `neurodiffeq.solvers.Solver1D` instance instead\n",
      "  FutureWarning,\n"
     ]
    }
   ],
   "source": [
    "pop_eq = lambda u, t: diff(u, t) - 0.1*u*(1-u)\n",
    "initial_vals = IVP(t_0 = 0, u_0 = 0.9)\n",
    "\n",
    "\n",
    "#solving my ODE\n",
    "\n",
    "solution_fun, loss_stats = solve(\n",
    "ode = pop_eq, condition = initial_vals, t_min = 0.0, t_max = 100.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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       "        } 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",
       "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.one(\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",
       "\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",
       "    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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Testing Solved function with analytical equivalent function\n",
    "\n",
    "ts = np.linspace(0, 100.0, 100)\n",
    "u_neuro = solution_fun(ts, to_numpy = True)\n",
    "u_ana = 1/(1 + np.exp(-(0.1*ts + np.log(9))))\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(ts, u_neuro, label = 'Solution with NeuroDiffeq')\n",
    "plt.plot(ts, u_ana, label = 'Analytical Solution')\n",
    "plt.ylabel('u')\n",
    "plt.xlabel('t')\n",
    "plt.title('Comparing the Solutions')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "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.one(\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",
       "\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",
       "    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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(loss_stats['train_loss'], label='training loss')\n",
    "plt.plot(loss_stats['valid_loss'], label='validation loss')\n",
    "plt.yscale('log')\n",
    "plt.title('loss during training')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With 1-D Solver (NEW)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from neurodiffeq.solvers import Solver1D\n",
    "from neurodiffeq.callbacks import MonitorCallback"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### t_0 = 0 and u_0 = 0.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pop_eq = lambda u, t: [diff(u, t) - 0.1*u*(1-u)]\n",
    "initial_vals = [IVP(t_0 = 0, u_0 = 0.9)]\n",
    "\n",
    "solver = Solver1D(\n",
    "ode_system = pop_eq, conditions = initial_vals, t_min = -0, t_max = 10.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver.fit(max_epochs = 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "sol_1d = solver.get_solution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "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.one(\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",
       "\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",
       "    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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts = np.linspace(0, 10.0, 100)\n",
    "u_neuro = sol_1d(ts, to_numpy = True)\n",
    "u_ana = 1/(1 + np.exp(-(0.1*ts + np.log(9))))\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(ts, u_neuro, label = 'Solution with NeuroDiffeq')\n",
    "plt.plot(ts, u_ana, label = 'Analytical Solution')\n",
    "plt.ylabel('u')\n",
    "plt.xlabel('t')\n",
    "plt.title('Comparing the Solutions')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### t_0 = 0 and u_0 = 0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "pop_eq = lambda u, t: [diff(u, t) - 0.1*u*(1-u)]\n",
    "initial_vals = [IVP(t_0 = 0, u_0 = 0.8)]\n",
    "\n",
    "solver = Solver1D(\n",
    "ode_system = pop_eq, conditions = initial_vals, t_min = -0, t_max = 10.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver.fit(max_epochs = 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sol_1d = solver.get_solution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "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.one(\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",
       "\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",
       "    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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts = np.linspace(0, 10.0, 100)\n",
    "u_neuro = sol_1d(ts, to_numpy = True)\n",
    "u_ana = 1/(1 + np.exp(-(0.1*ts + np.log(4))))\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(ts, u_neuro, label = 'Solution with NeuroDiffeq')\n",
    "plt.plot(ts, u_ana, label = 'Analytical Solution')\n",
    "plt.ylabel('u')\n",
    "plt.xlabel('t')\n",
    "plt.title('Comparing the Solutions')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trying to save Pytorch Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'metrics': {},\n",
       " 'n_batches': {'train': 1, 'valid': 4},\n",
       " 'best_nets': [FCNN(\n",
       "    (NN): Sequential(\n",
       "      (0): Linear(in_features=1, out_features=32, bias=True)\n",
       "      (1): Tanh()\n",
       "      (2): Linear(in_features=32, out_features=32, bias=True)\n",
       "      (3): Tanh()\n",
       "      (4): Linear(in_features=32, out_features=1, bias=True)\n",
       "    )\n",
       "  )],\n",
       " 'criterion': <function neurodiffeq.solvers.BaseSolver.__init__.<locals>.<lambda>(r)>,\n",
       " 'conditions': [<neurodiffeq.conditions.IVP at 0x1c195bdccc8>],\n",
       " 'global_epoch': 1000,\n",
       " 'lowest_loss': 4.802509823238725e-08,\n",
       " 'n_funcs': 1,\n",
       " 'nets': [FCNN(\n",
       "    (NN): Sequential(\n",
       "      (0): Linear(in_features=1, out_features=32, bias=True)\n",
       "      (1): Tanh()\n",
       "      (2): Linear(in_features=32, out_features=32, bias=True)\n",
       "      (3): Tanh()\n",
       "      (4): Linear(in_features=32, out_features=1, bias=True)\n",
       "    )\n",
       "  )],\n",
       " 'optimizer': Adam (\n",
       " Parameter Group 0\n",
       "     amsgrad: False\n",
       "     betas: (0.9, 0.999)\n",
       "     eps: 1e-08\n",
       "     lr: 0.001\n",
       "     weight_decay: 0\n",
       " ),\n",
       " 'diff_eqs': <function __main__.<lambda>(u, t)>,\n",
       " 'generator': {'train': <neurodiffeq.generators.SamplerGenerator at 0x1c195b95c88>,\n",
       "  'valid': <neurodiffeq.generators.SamplerGenerator at 0x1c195be02c8>},\n",
       " 'train_generator': <neurodiffeq.generators.SamplerGenerator at 0x1c195b95c88>,\n",
       " 'valid_generator': <neurodiffeq.generators.SamplerGenerator at 0x1c195be02c8>,\n",
       " 't_min': 0,\n",
       " 't_max': 10.0}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solver.get_internals()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "torch.save(solver.nets, 'test_model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[FCNN(\n",
       "   (NN): Sequential(\n",
       "     (0): Linear(in_features=1, out_features=32, bias=True)\n",
       "     (1): Tanh()\n",
       "     (2): Linear(in_features=32, out_features=32, bias=True)\n",
       "     (3): Tanh()\n",
       "     (4): Linear(in_features=32, out_features=1, bias=True)\n",
       "   )\n",
       " )]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.load('test_model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}