fast-approx-ML.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pickle as pk\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np\n",
    "from numpy.linalg import norm\n",
    "from math import sqrt, exp\n",
    "%matplotlib nbagg\n",
    "from PyKEP import *\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from matplotlib import rc\n",
    "rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n",
    "## for Palatino and other serif fonts use:\n",
    "#rc('font',**{'family':'serif','serif':['Palatino']})\n",
    "rc('text', usetex=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We load the data file obtained from the optimization (in low-thrust) of many legs (GTOC7): \n",
    "\n",
    "ast1, ast2, $t_1$, $t_2$, $m^*$, $m_i$, $\\Delta V^*$, $\\Delta V$, $\\Delta V_L$, $\\Delta V_D$, $m^*_L$, $m^*_D$\n",
    "\n",
    "We want to learn $\\Delta V$ (i.e. the final mass) from the rest (known quickly using a Lambert solver and Damon model). The ast1 and ast2 ids can be used with the gtoc7 asteroids to know the orbitalparameters.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DATA =  [[ 11830.          10256.          10962.60236546 ...,   4906.74618359\n",
      "    2544.20354737   1476.60103897]\n",
      " [  6846.           6073.          11098.51009776 ...,   6586.44735414\n",
      "    1251.97554234    775.87757295]\n",
      " [ 15646.           8853.          10472.90296903 ...,   4091.14474818\n",
      "    2968.07001635   1992.14286758]\n",
      " ..., \n",
      " [  4952.          14339.          10326.68381981 ...,   4057.38011553\n",
      "    2788.37388882   1485.32852058]\n",
      " [ 12662.          11131.           9791.69375163 ...,   4885.57653231\n",
      "    2874.03260757   2312.48314192]\n",
      " [ 14007.           7294.          10253.04425878 ...,   4728.99722101\n",
      "    2062.81669447   1294.33686228]]\n",
      "ONE ROW =  [ 11830.          10256.          10962.60236546  11220.6581701\n",
      "   1427.64964893   1352.56164444   4894.91224655   4225.21779204\n",
      "   2629.03746956   4906.74618359   2544.20354737   1476.60103897]\n"
     ]
    }
   ],
   "source": [
    "a = pk.load(open(\"learn.pkl\",\"rb\"))\n",
    "print(\"DATA = \", a)\n",
    "print(\"ONE ROW = \", a[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Visualizing the data\n",
    "\n",
    "We plot the data with a high alpha as to show the data density. The plots are a result of knowledge in the domain, thus manual feature engineering ...\n",
    "\n",
    "First we plot the starting mass (fraction w.r.t the maximual allowed $m^*$) vs the $\\Delta V$ (fraction w.r.t. $\\Delta V^*$). This last fraction is, essentially ,the duration of the coast arc. 1 -> no coast, 0-> full coast. \n",
    "We observe that no trajectory has a $\\Delta V$ higher than the one relative to maxmum mass (obvious as that correspond to no coast arc), you thus cannot thrust for longer. A strange feature that should be discussed / checked is that many trajectories show no coast arc even if they are very light."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f0d8093bc50>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "skip=10\n",
    "plt.subplot(1,3,1)\n",
    "plt.scatter(  a[::skip,5]/a[::skip,4], a[::skip,7] / a[::skip,6], marker='o', color = 'k', alpha=0.05)\n",
    "#plt.hexbin(  a[:,5]/a[:,4], a[:,7] / a[:,6], bins='log')\n",
    "plt.xlabel(\"$ m_i / m^*$\")\n",
    "plt.ylabel(\"$ \\Delta V / \\Delta V^*$\")\n",
    "#plt.xlim(0.3,1)\n",
    "#plt.ylim(0.5,1.02)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Second, we plot the starting mass (fraction w.r.t the maximual allowed $m^*$) vs the $\\Delta V$ (fraction w.r.t. $\\Delta V^L$). \n",
    "We observe a few low-thrust trajectories with a $\\Delta V$ which is improving w.r.t Lambert. These are not extremely frequent, but correspond to cases where a two impulse orbital transfer is not optimal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.5, 2.3)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.subplot(1,3,2)\n",
    "plt.scatter(  a[::skip,5]/a[::skip,4], a[::skip,7] / a[::skip,8], marker='o', alpha=0.05, edgecolor=\"none\", color = 'k')\n",
    "#plt.hexbin(  a[:,5]/a[:,4], a[:,7] / a[:,8], bins='log')\n",
    "plt.xlabel(\"$ {m_i} / {m^*}$\")\n",
    "plt.ylabel(\"$ {\\Delta V} / {\\Delta V_L}$\")\n",
    "plt.xlim(0.3,1)\n",
    "plt.ylim(0.5,2.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Third, we plot the starting mass (fraction w.r.t the maximual allowed $m^*$) vs $\\Delta V - \\Delta V_L$ (fraction w.r.t. $\\Delta V^*$). This third plot shows the highes correlation between variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.subplot(133)\n",
    "plt.scatter(  a[::skip,5]/a[::skip,4], (a[::skip,7]-a[::skip,8]) / (a[::skip,6]), marker='o', alpha=0.05,edgecolor=\"none\", color = 'k')\n",
    "#plt.hexbin(  a[:,5]/a[:,4], (a[:,7]-a[:,8]) / (a[:,6]), bins='log')\n",
    "plt.xlim(0.3,1)\n",
    "plt.ylim(-1,0.6)\n",
    "plt.xlabel(\"$ {m_i} / {m^*}$\")\n",
    "plt.ylabel(\"$ {(\\Delta V - \\Delta V_L} ) / {\\Delta V^*}$\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.tight_layout(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f0d80800e10>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.scatter(  a[:,5]/a[:,4],  ( 1. - np.exp(-a[:,7] / 3000 / 9.80665)), marker='o', alpha=0.02,edgecolor=\"none\", c=np.array([a[:,5]  / max(a[:,8])]*3).transpose())\n",
    "plt.xlim(0.3,1)\n",
    "#plt.ylim(-2,1)\n",
    "plt.xlabel(\"$ ({m_i} / {m^*}) $\")\n",
    "plt.ylabel(\"$ (m_i - m_f ) / m_i $\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Now we do some machine learning\n",
    "\n",
    "From each line ast1, ast2, $t_1$, $t_2$, $m^*$, $m_i$, $\\Delta V^*$, $\\Delta V$, $\\Delta V_L$, $\\Delta V_D$, $m^*_L$, $m^*_D$\n",
    "\n",
    "As attributes we use $t_2-t_1$, $m^*_D$, $m_i$, $\\Delta V^*_D$, $\\Delta V_L$, $m^*_L$, as these are the ones we can compute at the cost of one lambert problem solution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X = list()\n",
    "#X_queries = list()\n",
    "y = list()\n",
    "for row in a:\n",
    "    a1 = planet.gtoc7(int(row[0])).osculating_elements(epoch(0))[0] \n",
    "    a2 = planet.gtoc7(int(row[1])).osculating_elements(epoch(0))[0]\n",
    "    n1 = sqrt(MU_SUN/a1**3)\n",
    "    n2 = sqrt(MU_SUN/a2**3)\n",
    "    #e1 = planet.gtoc7(int(row[0])).osculating_elements(epoch(0))[1] \n",
    "    #e2 = planet.gtoc7(int(row[1])).osculating_elements(epoch(0))[1]\n",
    "    r1,v1 = planet.gtoc7(int(row[0])).eph(row[2]) # MJD2000 assumed in data\n",
    "    r2,v2 = planet.gtoc7(int(row[1])).eph(row[3])\n",
    "    h1 = np.cross(r1,v1)\n",
    "    h2 = np.cross(r2,v2)\n",
    "    cost = np.dot(h1,h2) / norm(h1) / norm(h2)\n",
    "    X.append(np.array((row[3] - row[2], row[5], row[11], row[10], cost, n1, n2, norm([a-b for a,b in zip(r1,r2)]),norm([a-b for a,b in zip(v1,v2)]))))\n",
    "    #X_queries.append(np.array((row[3] - row[2], row[11], row[5], row[9], row[8], row[10])))\n",
    "    y.append(row[5] * ( 1 - np.exp(-row[7] / 3000 / 9.80665)) )\n",
    "X = np.array(X)\n",
    "y = np.array(y)\n",
    "#X_queries = np.array(X_queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  2.58055805e+02   1.35256164e+03   1.47660104e+03   2.54420355e+03\n",
      "   9.99065966e-01   4.81712020e-08   5.12879740e-08   3.54455760e+11\n",
      "   1.45237988e+04]\n",
      "180.946956378\n"
     ]
    }
   ],
   "source": [
    "print(X[0])\n",
    "print(y[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Split data in train and test data\n",
    "# A random permutation, to split the data randomly\n",
    "N = 30000\n",
    "np.random.seed(23)\n",
    "indices = np.random.permutation(len(X))\n",
    "traj_X_train = X[indices[:-N]]\n",
    "traj_y_train = y[indices[:-N]]\n",
    "traj_X_test  = X[indices[-N:]]\n",
    "traj_y_test  = y[indices[-N:]]\n",
    "#traj_X_query_test = X_queries[indices[-N:]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Decision trees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE 19.213834191121016\n",
      "EVS 0.918086862323\n"
     ]
    }
   ],
   "source": [
    "#from sklearn import linear_model\n",
    "#regr = linear_model.LinearRegression()\n",
    "from sklearn import tree\n",
    "regr = tree.DecisionTreeRegressor()\n",
    "regr.fit(traj_X_train, traj_y_train)\n",
    "\n",
    "# The mean square error\n",
    "print(\"RMSE\", sqrt(np.mean((regr.predict(traj_X_test)-traj_y_test)**2)))\n",
    "#print(\"RMSE (queries)\", sqrt(np.mean((regr.predict(traj_X_query_test)-traj_y_test)**2)))\n",
    "\n",
    "\n",
    "# Explained variance score: 1 is perfect prediction\n",
    "# and 0 means that there is no linear relationship\n",
    "# between X and Y.\n",
    "print(\"EVS\", regr.score(traj_X_test, traj_y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ensemble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE 7.5079551643\n",
      "RMSE 12.189544692481228\n",
      "Max 145.609473384\n"
     ]
    }
   ],
   "source": [
    "#from sklearn import linear_model\n",
    "#regr = linear_model.LinearRegression()\n",
    "from sklearn import ensemble\n",
    "regr = ensemble.GradientBoostingRegressor(max_depth=8)\n",
    "regr.fit(traj_X_train, traj_y_train)\n",
    "\n",
    "# The mean square error\n",
    "print(\"MAE\", np.mean(np.abs((regr.predict(traj_X_test)-traj_y_test))))\n",
    "#print(\"MAX\", sqrt(np.mean((lambert_prediction-traj_y_test)**2)))\n",
    "print(\"RMSE\", sqrt(np.mean((regr.predict(traj_X_test)-traj_y_test)**2)))\n",
    "print(\"Max\", max(np.abs(regr.predict(traj_X_test)-traj_y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0d807dd438>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "h = plt.hist(regr.predict(traj_X_test)-traj_y_test, 100)\n",
    "#plt.xlabel(\"error (Kg) on the test set\")\n",
    "plt.axes()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets see what would happen if, instead we predict the final mass as:\n",
    "\n",
    "$$\n",
    "m_f = m_i * exp(\\frac{-\\Delta V_L}{I_{sp}g_0)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE 31.4457383414\n",
      "RMSE 42.776498713068996\n",
      "Max 639.826315194\n"
     ]
    }
   ],
   "source": [
    "lambert_prediction = a[indices[-N:], 5] * (1 - np.exp( - a[indices[-N:], 8] / 3000 / 9.80665) )\n",
    "# The mean square error\n",
    "print(\"MAE\", np.mean(np.abs((lambert_prediction-traj_y_test))))\n",
    "#print(\"MAX\", sqrt(np.mean((lambert_prediction-traj_y_test)**2)))\n",
    "print(\"RMSE\", sqrt(np.mean((lambert_prediction-traj_y_test)**2)))\n",
    "print(\"Max\", max(np.abs(lambert_prediction-traj_y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-200, 200)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "h = plt.hist(regr.predict(traj_X_test)-traj_y_test, 100, alpha=0.8,normed=False, log=False)\n",
    "h = plt.hist(lambert_prediction-traj_y_test, 100, alpha=0.5, normed=False, log=False)\n",
    "plt.xlabel(\"Error (Kg)\")\n",
    "plt.ylabel(\"N. instances\")\n",
    "plt.xlim(-200,200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.tight_layout(1)\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# We try them all :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'sklearn.ensemble.weight_boosting.AdaBoostRegressor'>\n",
      "MAE 24.7813340118\n",
      "RMSE 30.47651669718731\n",
      "Max 127.180459974\n",
      "EVS 0.79391036946\n",
      "cpu time 6.184276342391968\n"
     ]
    }
   ],
   "source": [
    "from sklearn import ensemble, neighbors, tree, svm\n",
    "import time\n",
    "\n",
    "regressors = [\n",
    "             ensemble.RandomForestRegressor(),\n",
    "             ensemble.AdaBoostRegressor(),\n",
    "             ensemble.BaggingRegressor(),\n",
    "             ensemble.BaggingRegressor(ensemble.ExtraTreesRegressor()),\n",
    "             ensemble.ExtraTreesRegressor(),\n",
    "             ensemble.GradientBoostingRegressor(max_depth=7),\n",
    "             tree.DecisionTreeRegressor(),\n",
    "             tree.ExtraTreeRegressor(),\n",
    "             #svm.LinearSVR(), \n",
    "             #svm.NuSVR(), \n",
    "             #svm.SVR() \n",
    "             ]\n",
    "\n",
    "regressors = [ensemble.AdaBoostRegressor(loss='square', n_estimators=100, learning_rate=1.5)]\n",
    "    \n",
    "for regr in regressors:\n",
    "    tstart = time.time()\n",
    "    regr.fit(traj_X_train, traj_y_train)\n",
    "    tend = time.time()\n",
    "\n",
    "    print(type(regr))\n",
    "    # The mean square error\n",
    "    print(\"MAE\", np.mean(np.abs((regr.predict(traj_X_test)-traj_y_test))))\n",
    "    #print(\"MAX\", sqrt(np.mean((lambert_prediction-traj_y_test)**2)))\n",
    "    print(\"RMSE\", sqrt(np.mean((regr.predict(traj_X_test)-traj_y_test)**2)))\n",
    "    print(\"Max\", max(np.abs(regr.predict(traj_X_test)-traj_y_test)))\n",
    "\n",
    "\n",
    "    # Explained variance score: 1 is perfect prediction\n",
    "    # and 0 means that there is no linear relationship\n",
    "    # between X and Y.\n",
    "    print(\"EVS\", regr.score(traj_X_test, traj_y_test))\n",
    "    print(\"cpu time\", tend-tstart)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'KNeighborsRegressor' object has no attribute 'name'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-479-7186718883c6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mregressors\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: 'KNeighborsRegressor' object has no attribute 'name'"
     ]
    }
   ],
   "source": [
    "regressors[0].name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sklearn.ensemble.forest.RandomForestRegressor"
      ]
     },
     "execution_count": 456,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(regressors[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}