Building Pitch Control.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pitch Control\n",
    "\n",
    "Pitch control at a given location is the probability that a player (or team) will gain control of the ball if it moves directly in that location.\\\n",
    "Pitch control tries to answer the question:\"What options are available to the player with the ball?\"\\\n",
    "Pitch control models enables one to qauntify the passing options directly\\\n",
    " \n",
    "### Building a pitch control model\n",
    "For a given position on the pitch:\n",
    "\n",
    "1. How long will it take for the ball to arrive?\n",
    "2. How long will it take for each player to arrive?\n",
    "3. What is the total probability that each team will control the ball after it has arrived?\n",
    "\n",
    "Repeat calculation for all locations on the pitch\n",
    "\n",
    "### Player time to arrival\n",
    "Given their initial positions and velocity how fast can a player get to any other position on the pitch?\\\n",
    "  \n",
    "Key assumptions:\n",
    "1. Players have a maximum speed: 5 m/s\n",
    "2. Players have a maximum acceleration: 7m/s/s\n",
    "3. Players take the fastest possible path\n",
    "\n",
    "### Simple approximation for arrival time\n",
    "Two step process\n",
    "1. There is an initial \"reaction time\" of 0.7 seconds. During this time each player continues along with their current trajectory\n",
    "2. After 0.7 seconds, the player runs directly towards the target location at their maximum speed of 5 m/s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Dependencies and Read in Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import nbimporter\n",
    "import matplotlib.pyplot as plt\n",
    "import Analyzing_Player_Motion as APM\n",
    "import Football_Analytics as FA\n",
    "import Pitch_Control_Model as MPC\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading team: home\n",
      "Reading team: away\n"
     ]
    }
   ],
   "source": [
    "DATADIR2 = r\"C:\\Users\\MustaphaM\\Desktop\\sample-data-master\\data\\Sample_Game_2\\Sample_Game_2_RawEventsData.csv\"\n",
    "\n",
    "#read in the events data\n",
    "events = pd.read_csv(DATADIR2)\n",
    "\n",
    "#read in the tracking data\n",
    "DataDir= r\"C:\\Users\\MustaphaM\\Desktop\\sample-data-master\\data\"\n",
    "tracking_Hom = APM.tracking_data(DataDir, 2, \"Home\")\n",
    "tracking_Awa = APM.tracking_data(DataDir,2,\"Away\")\n",
    "\n",
    "#Convert positions from metrica units to meters\n",
    "tracking_HomeConv = tracking_Hom.copy()\n",
    "tracking_AwayConv = tracking_Awa.copy()\n",
    "\n",
    "tracking_home = APM.to_metric_coordinates(tracking_HomeConv)\n",
    "tracking_away = APM.to_metric_coordinates(tracking_AwayConv)\n",
    "events = APM.to_metric_coordinates(events)\n",
    "\n",
    "#reverse direction of play in the second half so that home team is always attacking from right -> left\n",
    "tracking_home, tracking_away, events = APM.to_single_playing_direction(tracking_home, tracking_away, events)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Player Velocities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "tracking_home = APM.calc_player_velocities(tracking_home, smoothing = True)\n",
    "tracking_away = APM.calc_player_velocities(tracking_away, smoothing = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Taking a Look at the Passes Leading up to the Second Goal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Type</th>\n",
       "      <th>Subtype</th>\n",
       "      <th>Period</th>\n",
       "      <th>Start Frame</th>\n",
       "      <th>Start Time [s]</th>\n",
       "      <th>End Frame</th>\n",
       "      <th>End Time [s]</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Start X</th>\n",
       "      <th>Start Y</th>\n",
       "      <th>End X</th>\n",
       "      <th>End Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>Home</td>\n",
       "      <td>SHOT</td>\n",
       "      <td>ON TARGET-GOAL</td>\n",
       "      <td>1</td>\n",
       "      <td>12202</td>\n",
       "      <td>488.08</td>\n",
       "      <td>12212</td>\n",
       "      <td>488.48</td>\n",
       "      <td>Player10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-47.70</td>\n",
       "      <td>-3.40</td>\n",
       "      <td>-54.06</td>\n",
       "      <td>-2.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>823</th>\n",
       "      <td>Away</td>\n",
       "      <td>SHOT</td>\n",
       "      <td>ON TARGET-GOAL</td>\n",
       "      <td>1</td>\n",
       "      <td>53049</td>\n",
       "      <td>2121.96</td>\n",
       "      <td>53075</td>\n",
       "      <td>2123.00</td>\n",
       "      <td>Player24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.52</td>\n",
       "      <td>2.72</td>\n",
       "      <td>54.06</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1118</th>\n",
       "      <td>Home</td>\n",
       "      <td>SHOT</td>\n",
       "      <td>HEAD-ON TARGET-GOAL</td>\n",
       "      <td>2</td>\n",
       "      <td>73983</td>\n",
       "      <td>2959.32</td>\n",
       "      <td>73995</td>\n",
       "      <td>2959.80</td>\n",
       "      <td>Player9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-47.70</td>\n",
       "      <td>1.36</td>\n",
       "      <td>-54.06</td>\n",
       "      <td>2.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1671</th>\n",
       "      <td>Away</td>\n",
       "      <td>SHOT</td>\n",
       "      <td>ON TARGET-GOAL</td>\n",
       "      <td>2</td>\n",
       "      <td>115009</td>\n",
       "      <td>4600.36</td>\n",
       "      <td>115024</td>\n",
       "      <td>4600.96</td>\n",
       "      <td>Player20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.28</td>\n",
       "      <td>1.36</td>\n",
       "      <td>55.12</td>\n",
       "      <td>2.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1723</th>\n",
       "      <td>Home</td>\n",
       "      <td>SHOT</td>\n",
       "      <td>ON TARGET-GOAL</td>\n",
       "      <td>2</td>\n",
       "      <td>121027</td>\n",
       "      <td>4841.08</td>\n",
       "      <td>121055</td>\n",
       "      <td>4842.20</td>\n",
       "      <td>Player12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-30.74</td>\n",
       "      <td>5.44</td>\n",
       "      <td>-54.06</td>\n",
       "      <td>2.72</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Team  Type              Subtype  Period  Start Frame  Start Time [s]  \\\n",
       "198   Home  SHOT       ON TARGET-GOAL       1        12202          488.08   \n",
       "823   Away  SHOT       ON TARGET-GOAL       1        53049         2121.96   \n",
       "1118  Home  SHOT  HEAD-ON TARGET-GOAL       2        73983         2959.32   \n",
       "1671  Away  SHOT       ON TARGET-GOAL       2       115009         4600.36   \n",
       "1723  Home  SHOT       ON TARGET-GOAL       2       121027         4841.08   \n",
       "\n",
       "      End Frame  End Time [s]      From   To  Start X  Start Y  End X  End Y  \n",
       "198       12212        488.48  Player10  NaN   -47.70    -3.40 -54.06  -2.04  \n",
       "823       53075       2123.00  Player24  NaN    44.52     2.72  54.06   1.36  \n",
       "1118      73995       2959.80   Player9  NaN   -47.70     1.36 -54.06   2.04  \n",
       "1671     115024       4600.96  Player20  NaN    40.28     1.36  55.12   2.72  \n",
       "1723     121055       4842.20  Player12  NaN   -30.74     5.44 -54.06   2.72  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shots = events[events[\"Type\"]== \"SHOT\"]\n",
    "goals = shots[shots[\"Subtype\"].str.contains(\"-GOAL\")].copy()\n",
    "goals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 864x576 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0xf1c0624d88>)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_events(events.loc[820:823], color =\"k\", indicators = [\"Marker\", \"Arrow\"], annotate = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pitch Control for Passes leading up to Goal 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_player_accel': 7.0,\n",
       " 'max_player_speed': 5.0,\n",
       " 'reaction_time': 0.7,\n",
       " 'tti_sigma': 0.45,\n",
       " 'kappa_def': 1.0,\n",
       " 'lambda_att': 4.3,\n",
       " 'lambda_def': 4.3,\n",
       " 'lambda_gk': 12.899999999999999,\n",
       " 'average_ball_speed': 15.0,\n",
       " 'int_dt': 0.04,\n",
       " 'max_int_time': 10,\n",
       " 'model_converge_tol': 0.01,\n",
       " 'time_to_control_att': 3.3202550055547313,\n",
       " 'time_to_control_def': 3.3202550055547313}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#first get model parameters\n",
    "params = MPC.default_model_params(3)\n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_frame( hometeam, awayteam, figax=None, team_colors=('r','b'), field_dimen = (106.0,68.0), include_player_velocities=False, PlayerMarkerSize=10, PlayerAlpha=0.7, annotate=False ):\n",
    "    \"\"\" plot_frame( hometeam, awayteam )\n",
    "    \n",
    "    Plots a frame of Metrica tracking data (player positions and the ball) on a football pitch. All distances should be in meters.\n",
    "    \n",
    "    Parameters\n",
    "    -----------\n",
    "        hometeam: row (i.e. instant) of the home team tracking data frame\n",
    "        awayteam: row of the away team tracking data frame\n",
    "        fig,ax: Can be used to pass in the (fig,ax) objects of a previously generated pitch. Set to (fig,ax) to use an existing figure, or None (the default) to generate a new pitch plot, \n",
    "        team_colors: Tuple containing the team colors of the home & away team. Default is 'r' (red, home team) and 'b' (blue away team)\n",
    "        field_dimen: tuple containing the length and width of the pitch in meters. Default is (106,68)\n",
    "        include_player_velocities: Boolean variable that determines whether player velocities are also plotted (as quivers). Default is False\n",
    "        PlayerMarkerSize: size of the individual player marlers. Default is 10\n",
    "        PlayerAlpha: alpha (transparency) of player markers. Defaault is 0.7\n",
    "        annotate: Boolean variable that determines with player jersey numbers are added to the plot (default is False)\n",
    "        \n",
    "    Returrns\n",
    "    -----------\n",
    "       fig,ax : figure and aixs objects (so that other data can be plotted onto the pitch)\n",
    "    \"\"\"\n",
    "    if figax is None: # create new pitch \n",
    "        fig,ax = plot_pitch( field_dimen = field_dimen )\n",
    "    else: # overlay on a previously generated pitch\n",
    "        fig,ax = figax # unpack tuple\n",
    "    # plot home & away teams in order\n",
    "    for team,color in zip( [hometeam,awayteam], team_colors) :\n",
    "        x_columns = [c for c in team.keys() if c[-2:].lower()=='_x' and c!='ball_x'] # column header for player x positions\n",
    "        y_columns = [c for c in team.keys() if c[-2:].lower()=='_y' and c!='ball_y'] # column header for player y positions\n",
    "        ax.plot( team[x_columns], team[y_columns], color+'o', MarkerSize=PlayerMarkerSize, alpha=PlayerAlpha ) # plot player positions\n",
    "        if include_player_velocities:\n",
    "            vx_columns = ['{}_vx'.format(c[:-2]) for c in x_columns] # column header for player x positions\n",
    "            vy_columns = ['{}_vy'.format(c[:-2]) for c in y_columns] # column header for player y positions\n",
    "            ax.quiver( team[x_columns], team[y_columns], team[vx_columns], team[vy_columns], color=color, scale_units='inches', scale=10.,width=0.0015,headlength=5,headwidth=3,alpha=PlayerAlpha)\n",
    "        if annotate:\n",
    "            [ ax.text( team[x]+0.5, team[y]+0.5, x.split('_')[1], fontsize=10, color=color  ) for x,y in zip(x_columns,y_columns) if not ( np.isnan(team[x]) or np.isnan(team[y]) ) ] \n",
    "    # plot ball\n",
    "    ax.plot( hometeam['ball_x'], hometeam['ball_y'], 'ko', MarkerSize=6, alpha=1.0, LineWidth=0)\n",
    "    return fig,ax\n",
    "\n",
    "def plot_pitchcontrol_for_event( event_id, events,  tracking_home, tracking_away, PPCF, alpha = 0.7, include_player_velocities=True, annotate=False, field_dimen = (106.0,68)):\n",
    "    \"\"\" plot_pitchcontrol_for_event( event_id, events,  tracking_home, tracking_away, PPCF )\n",
    "    \n",
    "    Plots the pitch control surface at the instant of the event given by the event_id. Player and ball positions are overlaid.\n",
    "    \n",
    "    Parameters\n",
    "    -----------\n",
    "        event_id: Index (not row) of the event that describes the instant at which the pitch control surface should be calculated\n",
    "        events: Dataframe containing the event data\n",
    "        tracking_home: (entire) tracking DataFrame for the Home team\n",
    "        tracking_away: (entire) tracking DataFrame for the Away team\n",
    "        PPCF: Pitch control surface (dimen (n_grid_cells_x,n_grid_cells_y) ) containing pitch control probability for the attcking team (as returned by the generate_pitch_control_for_event in Metrica_PitchControl)\n",
    "        alpha: alpha (transparency) of player markers. Default is 0.7\n",
    "        include_player_velocities: Boolean variable that determines whether player velocities are also plotted (as quivers). Default is False\n",
    "        annotate: Boolean variable that determines with player jersey numbers are added to the plot (default is False)\n",
    "        field_dimen: tuple containing the length and width of the pitch in meters. Default is (106,68)\n",
    "        \n",
    "    NB: this function no longer requires xgrid and ygrid as an input\n",
    "        \n",
    "    Returrns\n",
    "    -----------\n",
    "       fig,ax : figure and aixs objects (so that other data can be plotted onto the pitch)\n",
    "    \"\"\"    \n",
    "\n",
    "    # pick a pass at which to generate the pitch control surface\n",
    "    pass_frame = events.loc[event_id]['Start Frame']\n",
    "    pass_team = events.loc[event_id].Team\n",
    "    \n",
    "    # plot frame and event\n",
    "    fig,ax = plot_pitch(field_color='white', field_dimen = field_dimen)\n",
    "    plot_frame( tracking_home.loc[pass_frame], tracking_away.loc[pass_frame], figax=(fig,ax), PlayerAlpha=alpha, include_player_velocities=include_player_velocities, annotate=annotate )\n",
    "    plot_events( events.loc[event_id:event_id], figax = (fig,ax), indicators = ['Marker','Arrow'], annotate=False, color= 'k', alpha=1 )\n",
    "    \n",
    "    # plot pitch control surface\n",
    "    if pass_team=='Home':\n",
    "        cmap = 'bwr'\n",
    "    else:\n",
    "        cmap = 'bwr_r'\n",
    "    ax.imshow(np.flipud(PPCF), extent=(-field_dimen[0]/2., field_dimen[0]/2., -field_dimen[1]/2., field_dimen[1]/2.),interpolation='spline36',vmin=0.0,vmax=1.0,cmap=cmap,alpha=0.5)\n",
    "\n",
    "    return fig,ax\n",
    "def find_goalkeeper(team):\n",
    "    '''\n",
    "    Find the goalkeeper in team, identifying him/her as the player closest to goal at kick off\n",
    "    ''' \n",
    "    x_columns = [c for c in team.columns if c[-2:].lower()=='_x' and c[:4] in ['Home','Away']]\n",
    "    GK_col = team.iloc[0][x_columns].abs().idxmax(axis=1)\n",
    "    return GK_col.split('_')[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['savefig.dpi'] = 80\n",
    "mpl.rcParams['figure.dpi'] = 80"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // 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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\" width=\"815.1666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 960x640 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0xf1c14e1448>)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GK_numbers = [find_goalkeeper(tracking_home),find_goalkeeper(tracking_away)] #find goal keepers for offside calculations\n",
    "PPCF,xgrid,ygrid = MPC.generate_pitch_control_for_event(820, events, tracking_home, tracking_away, params, GK_numbers, field_dimen = (106.,68.,), n_grid_cells_x = 50)\n",
    "\n",
    "plot_pitchcontrol_for_event( 820, events,  tracking_home, tracking_away, PPCF, annotate=True )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Player 21 makes the long pass out to the right wing. It was a pass to the blue region meaning the blue team were likely to retain the ball.\\\n",
    "Also there is about 60.8% chance that the pass will be successful. If the had passed the ball to the blue portion, it will be about 100 percent certain for them to retain control, however, if they had passed it to the red portion, then, it will be next to impossible for them to retain the possession."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // 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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"829.6833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 960x640 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0xf1c1dd6dc8>)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#second pass\n",
    "PPCF,xgrid,ygrid = MPC.generate_pitch_control_for_event(821, events, tracking_home, tracking_away, params, GK_numbers, field_dimen = (106.,68.,), n_grid_cells_x = 50)\n",
    "plot_pitchcontrol_for_event( 821, events,  tracking_home, tracking_away, PPCF, annotate=True )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The probability that the pass is successful is about 75.8 percent, hence there is nearly about 4/5 that control will be retained. The opportunity to pass there was made possible by the run made by player 23"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // 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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"959.2166666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 960x640 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0xf1c58a5488>)"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#third pass\n",
    "PPCF,xgrid,ygrid = MPC.generate_pitch_control_for_event(822, events, tracking_home, tracking_away, params, GK_numbers, field_dimen = (106.,68.,), n_grid_cells_x = 50)\n",
    "plot_pitchcontrol_for_event( 822, events,  tracking_home, tracking_away, PPCF, annotate=True )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The probability that the pass is successful is about 60%. The pass provides a clear shot-on-goal for player 24"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating the Probability for Every Home Team Successful Pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(543, 14)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calculates the probability of success for every home team successful pass at moment the pass was made\n",
    "#we are only considering the complete passes\n",
    "home_passes = events[ (events['Type'].isin(['PASS'])) & (events['Team']=='Home') ]\n",
    "home_passes.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 543 such passes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Storing Pass Success Probabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "pass_success_probability = []\n",
    "\n",
    "for i,row in home_passes.iterrows():\n",
    "    pass_start_pos = np.array([row['Start X'],row['Start Y']])\n",
    "    pass_target_pos = np.array([row['End X'],row['End Y']])\n",
    "    pass_frame = row['Start Frame']\n",
    "    \n",
    "    attacking_players = MPC.initialise_players(tracking_home.loc[pass_frame],'Home',params, GK_numbers[0])\n",
    "    defending_players = MPC.initialise_players(tracking_away.loc[pass_frame],'Away',params, GK_numbers[1])\n",
    "    Patt,Pdef = MPC.calculate_pitch_control_at_target(pass_target_pos, attacking_players, defending_players, pass_start_pos, params)\n",
    "\n",
    "    pass_success_probability.append( (i,Patt) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making a Histogram for the Pass Sucesss Probability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // 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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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7W9/W6+99lo6b+KwuDgYADDZjiSh9DEXBwMAJtuRJJRp8MgjjyRctrg4GAAw2Y4koUyDiy++WKeeeqqmTZumadOmqX///rr00kt1/fXXW/27lC4OBgBMtiNJKNPgO9/5jhobG723GxsbNX78+HTexGFxcTAAYLIdSUKZBmeeeab27Nnjvd3W1qYzzzwznTdxWFwcDACYbEeSUKbB3LlzFYvFdMcdd2j+/Pk666yzNG/evHTexGFxcTAAYLIdSUKZJqtXr9b999+v+++/X6tXr0734Q+Li4MBAJPtSBLKNHn99de9Z7hu375d77//frpv4pC5OBgAMNmOJKFMg7lz52r8+PE644wzJEkfffSRzjnnnHTexGFxcTAAYLIdSUKZBtFoVPF4XAUFBd77wuFwOm/isLg4GAAw2Y4koUyDoqIiSVJhYaGkjj/kTCgBID1sR5JQpsHChQt19dVXa+DAgfr973+vYcOG6cEHH0znTRwWFwcDACbbkSSUafLSSy9p9uzZmjVrll566aV0H/6wuDgYADDZjiShTNG+ffs0duzYQ/66K6+8Un379lU0GvXed9ttt6l///6KRqOKRqOqqanxPnbnnXcqNzdXgUBAf/3rX5O6DRcHAwAm25EklGkwfvx47dy585C+ZsWKFVqzZk2XUN53331dPnfDhg0qLCxUW1ub6uvrlZeXp/b29m5vw8XBAIDJdiQJZRp897vfVU5OjqZPn64bbrjBW92pr69PKpR33nmnFixY4L09btw4vf76690e38XBAIDJdiQJZRo8/PDDB13dOVgoc3JyFA6HNXXqVDU1NUmSrrnmGj3xxBPe502fPl1PPfVUt8d3cTAAYLIdSUKZgo8//jilrzdD+cknn6i9vV379u3TLbfcoqlTp0qSKioquoTyz3/+80GPWVVVpVgsplgspqysrJTODwAyge1IEsoU7P+9Sanj4ddDZYbyQB9++KHy8/Ml8dArgCOb7UgSyhQc+Eo8B/47WWYoGxoavH8/8MADuuSSSyRJ69ev957Ms2XLFuXm5vJkHgBHDNuRJJQpOPA7ygP/nYzJkyfrlFNO0THHHKMBAwZo6dKlmjx5skKhkMLhsCZMmNApnPPnz9fAgQMVCAT0wgsvJHUbLg4GAEy2I0koU3D00UfrxBNP1AknnKD/+7//04knnui9feKJJ6bjJlLi4mAAwGQ7koTSx1wcDACYbEeSUPqYi4MBAJPtSBJKH3NxMABgsh1JQuljLg4GAEy2I0kofczFwQCAyXYkCaWPuTgYADDZjiSh9DEXBwMAJtuRJJQ+5uJgAMBkO5KE0sdcHAwAmGxHklD6mIuDAQCT7UgSSh9zcTAAYLIdSULpYy4OBgBMtiNJKH3MxcEAgMl2JAmlj7k4GAAw2Y4kofQxFwcDACbbkSSUPubiYADAZDuShNLHXBwMAJhsR5JQ+piLgwEAk+1IEkofc3EwAGCyHUlC6WMuDgYATLYjSSh9zMXBAIDJdiQJpY+5OBgAMNmOJKH0MRcHAwAm25EklD7m4mAAwGQ7koTSx1wcDACYbEeSUPqYi4MBAJPtSBJKH3NxMABgsh1JQuljLg4GAEy2I0koLbryyivVt29fRaNR732NjY0aM2aM8vLyNGbMGDU1NUmS4vG4rrvuOuXm5iocDmvNmjXdHt/FwQCAyXYkCaVFK1as0Jo1azqFcs6cOVqwYIEkacGCBbrxxhslSTU1NSotLZUk1dXVaejQod0e38XBAIDJdiQJpWX19fWdQhkIBLR161ZJ0tatWxUIBCRJ06dPV3V1tfd5wWBQDQ0NCY/t4mAAwGQ7koTSMjOUJ510UqeP9+nTR5JUWlqqlStXeu8vKSnRqlWrEh7bxcEAgMl2JAmlZWYo94fRfHvcuHFdQrl69eoux6uqqlIsFlMsFlNWVlYPnTUA9B7bkSSUlvHQKwAkZjuShNIyM5SzZ8/u9GSeOXPmSJKWL1+u8ePHS+p4Mk9RUVG3x3ZxMABgsh1JQmnR5MmTdcopp+iYY47RgAEDtHTpUm3fvl2jRo1SXl6eRo0apcbGRkkdvx5SUVGhgQMHKhQKdfvzScnNwQCAyXYkCaWPuTgYADDZjiSh9DEXBwMAJtuRJJQ+5uJgAMBkO5KE0sdcHAwAmGxHklD6mIuDAQCT7UgSSh9zcTAAYLIdSULpYy4OBgBMtiNJKH3MxcEAgMl2JAmlj7k4GAAw2Y4kofQxFwcDACbbkSSUPubiYADAZDuShNLHXBwMAJhsR5JQ+piLgwEAk+1IEkofc3EwADKP7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4HxNKAEiS7UhlwkqVi/sxoQSAJNmOVCasVLm4H2d8KLOzsxUKhRSNRr0L3NjYqDFjxigvL09jxoxRU1NTwmO4OBgAmcd2pDJhpcrF/diJUH722Wed3jdnzhwtWLBAkrRgwQLdeOONCY/h4mAAZB7bkcqElSoX92MnQxkIBLR161ZJ0tatWxUIBBIew8XBAMg8tiOVCStVLu7HGR/KnJwcFRYWasiQIaqqqpIknXTSSZ0+p0+fPgmP4eJgAGQe25HKhJUqF/fjjA/lRx99JKnjO8fCwkL94x//6BLGg4WyqqpKsVhMsVhMWVlZvXKuAPzNdqQyYaWKUPawO+64QwsXLuShVwBW2I5UJqxUubgfZ3Qov/jiC33++eeSpObmZn3rW9/Siy++qNmzZ3d6Ms+cOXMSHsfFwQDoynYkWIQy42zatEmRSESRSETBYFDz58+XJG3fvl2jRo1SXl6eRo0apcbGxoTHcXEwALqyHQkWofQtFwcDoCvbkWARSt9ycTAAurIdCRah9C0XBwOgK9uRYBFK33JxMAC6sh0JFqH0LRcHA2Qa2xs0KzNWqlzcjwklgKTY3qBZmbFS5eJ+TCgBJMX2Bs3KjJUqF/djQgkgKbY3aFZmrFS5uB8TSgBJsb1BszJjpcrF/ZhQAkiK7Q2alRkrVS7ux4QSQFJsb9CszFipcnE/JpQAkmJ7g2ZlxkqVi/sxoQSQFNsbNCszVqpc3I8JJYCk2N6gWZmxUuXifkwoASTF9gbNyoyVKhf3Y0IJICm2N2hWZqxUubgfE0oASbG9QbMyY6XKxf2YUAJIiu0NmpUZK1Uu7seEEnCE7Q2SxcquJJS+5eJgAJPtDZLFyq4klL7l4mAAk+0NksXKriSUvuXiYACT7Q2SxcquJJS+5eJgAJPtDZLFyq4klL7l4mAAk+0NksXKriSUvuXiYJB5bG9QLFYmrFS5uB8TSiBJtjcoFisTVqpc3I8JJZAk2xsUi5UJK1Uu7seEEkiS7Q2KxcqElSoX92NnQ/niiy8qEAgoNzdXd911V8LPdXEwyDy2NygWKxNWqlzcj50MZXt7u/Ly8lRfX6+2tjYVFhZqw4YNX/n5Lg4GndneHFgsVsdKlYv7sZOhfP311zVu3Djv7QULFujOO+/8ys93cTDozPbmwGKxOlaqXNyPnQzlU089pRkzZnhvP/7447rmmmu+8vNdHIzJ9n8cLBaLlV1JKJ1RXV3dJZTXXnttp8+pqqpSLBZTLBbTcccd5/37cFZWVlZKX++HxTXgGhzp959rkJ5r0KdPn95ORsqcDOWhPvSaqljMvf8HlG5cA67BkX7/Ja6BdGReAydDuXfvXuXm5mrLli3ek3nWr1/fY7d3JP4Pw8Q14Boc6fdf4hpIR+Y1cDKUklRTU6NAIKCBAwdq/vz5PXpbVVVVPXp8F3ANuAZH+v2XuAbSkXkNnA0lAAC9gVACAJAAoQQAIAFCeYDuXhavtbVV5eXlysvLU3Fxserr63v/JHtYd9dg7ty5GjRokCKRiC644AJ99tlnFs6y5yT70ojPPfecjjrqKK1du7YXz653JHMN/vSnPykYDCoYDOp73/teL59hz+vuGrz//vsaMWKECgoKFIlE9OKLL1o4y55z5ZVXqm/fvopGowf9eDwe13XXXafc3FyFw2GtWbOml8+wdxHKLyXzsniLFi1SRUWFpI7f5SwvL7dxqj0mmWvw8ssvq62tTZL0s5/9TD/5yU9snGqPSPalEZubmzVixAgNHTrUd6FM5hps3LhRhYWFampqkiR9+umnNk61xyRzDa666iotXrxYkrRhwwbl5ubaONUes2LFCq1Zs+YrQ1lTU6PS0lJJUl1dnYYOHdqbp9frCOWXkvndzJKSEtXV1Unq+I+pX79+isfjvXqePelQfz/16aef1ve///3eOLVekez9v+mmm/TMM89o+PDhvgtlMtdgzpw5+t3vftfbp9ZrkrkGV199te655x7v84cNG9ar59gb6uvrvzKU06dPV3V1tfd2MBhUQ0NDb51aryOUX0rmZfHy8/P18ccfe28HAgFt27at186xpx3qSwOWlpbqscce641T6xXJ3P///ve/mjBhgiT5MpTJXIMLLrhAlZWVOuecc1RcXOy7hx2TuQYNDQ0KhUIaMGCATjjhBP373//u7dPscYlCWVpaqpUrV3pvl5SUaNWqVb11ar2OUH4pmZfFCwaDXUK5ffv2XjvHnpbMNdjvnnvu0YQJE3z1HXUy9//888/X//73P0n+DGUy16C0tFQXXnih9uzZo/r6ep122mm++ll1Mtfg3nvv1f333y9Jqq2tVWFhYa+eY29IFMpx48Z1CeXq1at769R6HaH8Eg+9Jv/QY3V1tWKxmHbt2tWbp9fjkrn/J510krKzs5Wdna2vf/3rOvXUU3313UQy12DGjBlaunSp9/aB/134QTLXwHyosV+/fmptbe21c+wNPPT6/xHKLyXzsngPPfRQpyfzTJo0ycap9phkrsGKFSt05plndvrO2i8O9aUR/fgdZTLX4MUXX/R+Nr19+3ZlZ2f76pGVZK7B2LFj9eijj0qS1q1b57sn80iJQ7l8+XKNHz9eUseTeYqKinrz1HodoTzAwV4W75ZbbtFzzz0nSWppaVFZWZlyc3NVVFSkTZs22TzdHtHdNYjFYurfv7+i0aii0Winh6j8oLv7fyA/hlLq/hrE43HdcMMNGjx4sMLhsJ544gmbp9sjursGGzZs0Nlnn61IJKLCwkK9+uqrNk837SZPnqxTTjlFxxxzjAYMGKClS5dqyZIlWrJkiaSO/w1UVFRo4MCBCoVCvv75pEQoAQBIiFACAJAAoQQAIAFCCQBAAoQSAIAECCUAAAkQSjjt6KOPVjQaVX5+vsrKytTc3Gz7lJyWnZ19SK+yc9ttt+m+++7r8v5Vq1bp+uuv7/I5V1xxhffKRon+OguQSQglnHb88cd7/7700kt17733WjwbN7S3t3/lx9IVymQ+58DZAZmMUMJpB262S5Ys0dVXXy2p44W7hwwZomAwqKqqKkkdgZgyZYoGDx6sUCikX/7yl5KkBx54QIFAQJFIRJdcckmX21i/fr1isZii0ajC4bA2btzY5VVLDozBu+++q9GjRysSiWjIkCH64IMP1N7erpkzZyo/P1/hcNg7p7/97W86++yzVVhYqLKyMu9lASsrKxUIBBQOhzVr1ixJHa8GNXjwYEUiEZ177rldzrO2tlYjRozQBRdcoGAwqIqKCu8lFo8//nj97Gc/U1FRkd544w29/PLLKigoUCgU0tSpU72XX8vOzlZlZaWKioo0dOhQ70U1nn/+eQ0dOlQFBQUaPXq0PvnkE+9+f//739eIESN0xhlneH9VpLa2VhdccEGXa7P/RRoqKyu9RwMuv/xy3Xzzzd5rp0rSzJkz9etf/zqp/w0APY1Qwmn7Q7l3715NnDjR+xuBjY2NkjpeTSkSicRzmpwAAAVRSURBVGj79u1avXp1p5fa2v+d0wknnKCdO3d2et+Brr32Wj300EOSpLa2Nu3evTthKIcOHarnn39ekrR7927t3r1bixcvVnl5uffdXGNjo7Zt26bhw4d7Dxfffffdmj9/vhobG3Xqqadq7969nc4pFAp5L6V2sPOsra3Vscceq/r6eu3bt09jx47V008/LUk66qijvH+3tLTotNNO0zvvvCNJmjp1qnfu2dnZuvvuuyVJjz32mPeXUpqamrzoLl26VDNnzvTud0FBgVpaWryXs2toaOg2lAfOTpI2b96sIUOGeLPMycnRjh07utxHwAZCCaft/64kGo3q2muv9f6o9G233aZIJKJIJKJvfvObWrlypZqampSdna2rrrpKNTU12rdvn6SOvwgyfvx4PfLII/r888+73MZjjz2mvLw8/fznP/d+vvZVofz888+VnZ3d5RgXX3yx/v73v3d637Jly3TyySd75z948GD98Ic/1N69exUKhTR58mQ99dRT3nd7M2bM0LnnnqslS5Yc9M+71dbWauTIkd7bjzzyiPdzwq997Wte6NatW6cRI0Z4n/fqq6/qoosuktQRyvfff19Sx3fgJ598siTprbfe0re//W2FQiEFAgGdf/753v2eN2+ed6ypU6fq2WefPeRQStLo0aO1bt06Pffcc7r00ku73D/AFkIJpx3s51y1tbU677zztHv3bkkdG3Btba0kadeuXfrzn/+siRMnasqUKZI6glBbW6uZM2cqLy/P+07uQO+9954efPBBDRw4UC+//LI+/PBDhcNh7+M33XST7rvvPu3cufOgobzooou8c9jv+eef1+TJkw96v1pbW1VTU6Mf/OAHGj58uPf+N954Q7feeqsGDBjQ5YXIa2trNWrUKO/tA0N54HVau3Ztp6Caofzggw8kSfv27VPfvn0ldQSupqZGkvTaa69553Tbbbfp9ttv946VSigff/xx3XDDDbrooov00ksvHfS6ADYQSjjtYKF89tlndeGFF0qSNm7cqGOPPVa1tbXatm2b9xDr22+/rWg0qn379qm+vl5Sx0N+p556apeHNTdt2uR9NzZr1izdd9992rNnj/r27aumpibt3r1bBQUFXgyKi4u7PPS6ZMmSLg+9bt26VVlZWd7PAb/44gtt3LhRu3bt0qeffipJ2rFjh/r06SOpI9b7nXXWWV1ekL22tlbf+MY3tGXLFu3bt0/jxo3TX/7yly7XqaWlRVlZWXr33XcldTwTdf/PB7Ozs7Vw4UJJ0hNPPKGJEydKkgoKCrzbu+KKKzqFcsiQIWptbVVjY6NycnKSfui1T58+2rNnj3dera2tOuOMM5Sbm+t9tw9kAkIJpx0slK2trRo7dqwikYjKyso0atQo1dbWat26dSosLFQ0GlVBQYFeeOEF7dmzR8OGDVMoFFJ+fv5Bf2XhzjvvVDAYVEFBgc4//3zv55/333+/cnNzNXbsWF122WVeDDZu3KgRI0YoHA4rFovpww8/1N69e72/uBGJRPSb3/xGkvTKK6+oqKhI4XBY4XBYy5cvV0NDg/e+UCikhx9+WFLHd6WhUEihUEg/+tGPuvwt1NraWo0ZM0ZlZWUaPHiwrr766k5P5jlQoifzzJs3r8uTeZ599lmdfvrpOvfcc1VZWdkplDNmzNDIkSMP6ck8knTjjTfqzDPP1OWXX+6d1xVXXKGbb765+8EDvYhQAj5xYJxctG/fPhUUFPjyz9fBbYQS8AmXQ/nWW2/p9NNP934VBsgkhBIAgAQIJQAACRBKAAASIJQAACRAKAEASIBQAgCQAKEEACCB/wcbdAxPJtQUDwAAAABJRU5ErkJggg==\" width=\"511.43333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Frequency')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "ax.hist( [p[1] for p in pass_success_probability], np.arange(0,1.1,0.1))    \n",
    "ax.set_xlabel('Pass success probability')\n",
    "ax.set_ylabel('Frequency') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the passes made by the home team were more than 90 percent likely to be successful.\\\n",
    "20 - 30 passes had less than 50 percent success probability"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Looking at the Risky Passes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Type</th>\n",
       "      <th>Subtype</th>\n",
       "      <th>Period</th>\n",
       "      <th>Start Frame</th>\n",
       "      <th>Start Time [s]</th>\n",
       "      <th>End Frame</th>\n",
       "      <th>End Time [s]</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Start X</th>\n",
       "      <th>Start Y</th>\n",
       "      <th>End X</th>\n",
       "      <th>End Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1489</td>\n",
       "      <td>59.56</td>\n",
       "      <td>1578</td>\n",
       "      <td>63.12</td>\n",
       "      <td>Player11</td>\n",
       "      <td>Player9</td>\n",
       "      <td>53.00</td>\n",
       "      <td>10.20</td>\n",
       "      <td>9.54</td>\n",
       "      <td>24.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>5372</td>\n",
       "      <td>214.88</td>\n",
       "      <td>5400</td>\n",
       "      <td>216.00</td>\n",
       "      <td>Player4</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-1.06</td>\n",
       "      <td>-20.40</td>\n",
       "      <td>-23.32</td>\n",
       "      <td>-9.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>CROSS</td>\n",
       "      <td>1</td>\n",
       "      <td>12180</td>\n",
       "      <td>487.20</td>\n",
       "      <td>12202</td>\n",
       "      <td>488.08</td>\n",
       "      <td>Player1</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-40.28</td>\n",
       "      <td>19.72</td>\n",
       "      <td>-47.70</td>\n",
       "      <td>-3.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>16388</td>\n",
       "      <td>655.52</td>\n",
       "      <td>16435</td>\n",
       "      <td>657.40</td>\n",
       "      <td>Player9</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-13.78</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-33.92</td>\n",
       "      <td>11.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>DEEP BALL</td>\n",
       "      <td>1</td>\n",
       "      <td>20940</td>\n",
       "      <td>837.60</td>\n",
       "      <td>21022</td>\n",
       "      <td>840.88</td>\n",
       "      <td>Player4</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-1.06</td>\n",
       "      <td>-13.60</td>\n",
       "      <td>-42.40</td>\n",
       "      <td>-17.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>33376</td>\n",
       "      <td>1335.04</td>\n",
       "      <td>33427</td>\n",
       "      <td>1337.08</td>\n",
       "      <td>Player4</td>\n",
       "      <td>Player7</td>\n",
       "      <td>16.96</td>\n",
       "      <td>-19.72</td>\n",
       "      <td>-18.02</td>\n",
       "      <td>-20.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>38287</td>\n",
       "      <td>1531.48</td>\n",
       "      <td>38318</td>\n",
       "      <td>1532.72</td>\n",
       "      <td>Player4</td>\n",
       "      <td>Player7</td>\n",
       "      <td>28.62</td>\n",
       "      <td>-34.00</td>\n",
       "      <td>14.84</td>\n",
       "      <td>-30.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>737</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>HEAD</td>\n",
       "      <td>1</td>\n",
       "      <td>49065</td>\n",
       "      <td>1962.60</td>\n",
       "      <td>49105</td>\n",
       "      <td>1964.20</td>\n",
       "      <td>Player3</td>\n",
       "      <td>Player6</td>\n",
       "      <td>28.62</td>\n",
       "      <td>-16.32</td>\n",
       "      <td>21.20</td>\n",
       "      <td>-10.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>51510</td>\n",
       "      <td>2060.40</td>\n",
       "      <td>51526</td>\n",
       "      <td>2061.04</td>\n",
       "      <td>Player9</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-33.92</td>\n",
       "      <td>-13.60</td>\n",
       "      <td>-36.04</td>\n",
       "      <td>-7.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>813</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>52620</td>\n",
       "      <td>2104.80</td>\n",
       "      <td>52692</td>\n",
       "      <td>2107.68</td>\n",
       "      <td>Player4</td>\n",
       "      <td>Player10</td>\n",
       "      <td>31.80</td>\n",
       "      <td>-18.36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>903</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>59884</td>\n",
       "      <td>2395.36</td>\n",
       "      <td>59944</td>\n",
       "      <td>2397.76</td>\n",
       "      <td>Player9</td>\n",
       "      <td>Player1</td>\n",
       "      <td>-26.50</td>\n",
       "      <td>23.12</td>\n",
       "      <td>-49.82</td>\n",
       "      <td>16.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1116</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>CROSS</td>\n",
       "      <td>2</td>\n",
       "      <td>73955</td>\n",
       "      <td>2958.20</td>\n",
       "      <td>73983</td>\n",
       "      <td>2959.32</td>\n",
       "      <td>Player8</td>\n",
       "      <td>Player9</td>\n",
       "      <td>-46.64</td>\n",
       "      <td>-19.72</td>\n",
       "      <td>-47.70</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1164</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>78565</td>\n",
       "      <td>3142.60</td>\n",
       "      <td>78643</td>\n",
       "      <td>3145.72</td>\n",
       "      <td>Player11</td>\n",
       "      <td>Player10</td>\n",
       "      <td>43.46</td>\n",
       "      <td>10.88</td>\n",
       "      <td>-2.12</td>\n",
       "      <td>-10.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1405</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>93804</td>\n",
       "      <td>3752.16</td>\n",
       "      <td>93811</td>\n",
       "      <td>3752.44</td>\n",
       "      <td>Player2</td>\n",
       "      <td>Player5</td>\n",
       "      <td>-1.06</td>\n",
       "      <td>33.32</td>\n",
       "      <td>-5.30</td>\n",
       "      <td>30.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>CROSS</td>\n",
       "      <td>2</td>\n",
       "      <td>98866</td>\n",
       "      <td>3954.64</td>\n",
       "      <td>98880</td>\n",
       "      <td>3955.20</td>\n",
       "      <td>Player9</td>\n",
       "      <td>Player10</td>\n",
       "      <td>-45.58</td>\n",
       "      <td>-22.44</td>\n",
       "      <td>-48.76</td>\n",
       "      <td>-4.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1553</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>103191</td>\n",
       "      <td>4127.64</td>\n",
       "      <td>103210</td>\n",
       "      <td>4128.40</td>\n",
       "      <td>Player7</td>\n",
       "      <td>Player10</td>\n",
       "      <td>42.40</td>\n",
       "      <td>-34.00</td>\n",
       "      <td>25.44</td>\n",
       "      <td>-32.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1680</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>CROSS</td>\n",
       "      <td>2</td>\n",
       "      <td>117206</td>\n",
       "      <td>4688.24</td>\n",
       "      <td>117218</td>\n",
       "      <td>4688.72</td>\n",
       "      <td>Player1</td>\n",
       "      <td>Player9</td>\n",
       "      <td>-39.22</td>\n",
       "      <td>30.60</td>\n",
       "      <td>-41.34</td>\n",
       "      <td>7.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1753</th>\n",
       "      <td>Home</td>\n",
       "      <td>PASS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>124311</td>\n",
       "      <td>4972.44</td>\n",
       "      <td>124336</td>\n",
       "      <td>4973.44</td>\n",
       "      <td>Player10</td>\n",
       "      <td>Player9</td>\n",
       "      <td>-54.06</td>\n",
       "      <td>-14.28</td>\n",
       "      <td>-45.58</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Team  Type    Subtype  Period  Start Frame  Start Time [s]  End Frame  \\\n",
       "29    Home  PASS        NaN       1         1489           59.56       1578   \n",
       "93    Home  PASS        NaN       1         5372          214.88       5400   \n",
       "197   Home  PASS      CROSS       1        12180          487.20      12202   \n",
       "251   Home  PASS        NaN       1        16388          655.52      16435   \n",
       "332   Home  PASS  DEEP BALL       1        20940          837.60      21022   \n",
       "512   Home  PASS        NaN       1        33376         1335.04      33427   \n",
       "566   Home  PASS        NaN       1        38287         1531.48      38318   \n",
       "737   Home  PASS       HEAD       1        49065         1962.60      49105   \n",
       "797   Home  PASS        NaN       1        51510         2060.40      51526   \n",
       "813   Home  PASS        NaN       1        52620         2104.80      52692   \n",
       "903   Home  PASS        NaN       1        59884         2395.36      59944   \n",
       "1116  Home  PASS      CROSS       2        73955         2958.20      73983   \n",
       "1164  Home  PASS        NaN       2        78565         3142.60      78643   \n",
       "1405  Home  PASS        NaN       2        93804         3752.16      93811   \n",
       "1478  Home  PASS      CROSS       2        98866         3954.64      98880   \n",
       "1553  Home  PASS        NaN       2       103191         4127.64     103210   \n",
       "1680  Home  PASS      CROSS       2       117206         4688.24     117218   \n",
       "1753  Home  PASS        NaN       2       124311         4972.44     124336   \n",
       "\n",
       "      End Time [s]      From        To  Start X  Start Y  End X  End Y  \n",
       "29           63.12  Player11   Player9    53.00    10.20   9.54  24.48  \n",
       "93          216.00   Player4  Player10    -1.06   -20.40 -23.32  -9.52  \n",
       "197         488.08   Player1  Player10   -40.28    19.72 -47.70  -3.40  \n",
       "251         657.40   Player9  Player10   -13.78     0.68 -33.92  11.56  \n",
       "332         840.88   Player4  Player10    -1.06   -13.60 -42.40 -17.00  \n",
       "512        1337.08   Player4   Player7    16.96   -19.72 -18.02 -20.40  \n",
       "566        1532.72   Player4   Player7    28.62   -34.00  14.84 -30.60  \n",
       "737        1964.20   Player3   Player6    28.62   -16.32  21.20 -10.20  \n",
       "797        2061.04   Player9  Player10   -33.92   -13.60 -36.04  -7.48  \n",
       "813        2107.68   Player4  Player10    31.80   -18.36   0.00   6.80  \n",
       "903        2397.76   Player9   Player1   -26.50    23.12 -49.82  16.32  \n",
       "1116       2959.32   Player8   Player9   -46.64   -19.72 -47.70   1.36  \n",
       "1164       3145.72  Player11  Player10    43.46    10.88  -2.12 -10.88  \n",
       "1405       3752.44   Player2   Player5    -1.06    33.32  -5.30  30.60  \n",
       "1478       3955.20   Player9  Player10   -45.58   -22.44 -48.76  -4.08  \n",
       "1553       4128.40   Player7  Player10    42.40   -34.00  25.44 -32.64  \n",
       "1680       4688.72   Player1   Player9   -39.22    30.60 -41.34   7.48  \n",
       "1753       4973.44  Player10   Player9   -54.06   -14.28 -45.58   0.00  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risky_passes = events.loc[[p[0] for p in pass_success_probability if p[1]<0.5]]\n",
    "risky_passes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // 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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"959.2166666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 960x640 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0xf1c0950208>)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#plot the risky passes\n",
    "FA.plot_events(risky_passes, color ='k', indicators = [\"Marker\", \"Arrow\"], annotate = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observations: 1. Very long passes had lower probability of success\n",
    "              2. Also, passes into crowded locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Event following a risky (completed) pass\n",
      "0.9761786746948964 PASS\n",
      "0.31160841865474626 CHALLENGE\n",
      "0.7518055328493835 BALL LOST\n",
      "0.6643544450943134 PASS\n",
      "0.9336350554716212 PASS\n",
      "0.9901257167861145 PASS\n",
      "0.9714052407449258 PASS\n",
      "0.9751056048813957 PASS\n",
      "0.9836812077003456 PASS\n",
      "0.5147228904616257 PASS\n",
      "0.9096298019133129 BALL LOST\n",
      "1.0 PASS\n",
      "0.9904149555663557 PASS\n",
      "0.9760395733280377 PASS\n",
      "0.6407971367135854 PASS\n",
      "0.9245990067088163 PASS\n",
      "0.7757401155735683 PASS\n",
      "0.9914749443239345 PASS\n",
      "0.9823808029823321 PASS\n",
      "0.7731927881262496 PASS\n"
     ]
    }
   ],
   "source": [
    "#What happened following the risky passes?\n",
    "\n",
    "print(\"Event following a risky (completed) pass\")\n",
    "for p in pass_success_probability[:20]:\n",
    "    outcome = events.loc[ p[0]+1 ].Type\n",
    "    print( p[1], outcome )\n",
    "\n"
   ]
  },
  {
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}