{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# A Marte con Python usando poliastro\n",
    "\n",
    "<img src=\"http://poliastro.github.io/_images/logo_text.svg\" width=\"70%\" />\n",
    "\n",
    "## Juan Luis Cano Rodríguez <juanlu@pybonacci.org>\n",
    "## 2016-04-09 PyData Madrid 2016"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### ...en 5 minutos :)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## *Warning*: This *is* rocket science!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# ¿Qué es la Astrodinámica?\n",
    "\n",
    "> Una rama de la Mecánica (a su vez una rama de la Física) que estudia problemas prácticos acerca del movimiento de cohetes y otros vehículos en el espacio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "![Rosetta's mission](rosetta.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# ¿Qué es poliastro?\n",
    "\n",
    "> Una biblioteca de puro Python para Astrodinámica\n",
    "\n",
    "http://poliastro.github.io/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# ¡Vamos a Marte!\n",
    "\n",
    "![TGO](tgo.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "import astropy.units as u\n",
    "from astropy import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File de421.bsp already exists under /home/juanlu/.poliastro\n"
     ]
    }
   ],
   "source": [
    "from poliastro import iod\n",
    "from poliastro.plotting import plot\n",
    "from poliastro.bodies import Sun, Earth\n",
    "from poliastro.twobody import State\n",
    "from poliastro import ephem\n",
    "\n",
    "from jplephem.spk import SPK\n",
    "ephem.download_kernel(\"de421\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Primero: definir la órbita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "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": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = [-6045, -3490, 2500] * u.km\n",
    "v = [-3.457, 6.618, 2.533] * u.km / u.s\n",
    "\n",
    "ss = State.from_vectors(Earth, r, v)\n",
    "\n",
    "with plt.style.context('pybonacci'):\n",
    "    plot(ss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Segundo: localiza los planetas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "epoch = time.Time(\"2015-06-21 16:35\")\n",
    "\n",
    "r_, v_ = ephem.planet_ephem(ephem.EARTH, epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$[-61689.755,~-1.394555 \\times 10^{8},~-60480590] \\; \\mathrm{km}$"
      ],
      "text/plain": [
       "<Quantity [ -6.16897551e+04, -1.39455502e+08, -6.04805903e+07] km>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$[29.308324,~-0.19527688,~-0.084878762] \\; \\mathrm{\\frac{km}{s}}$"
      ],
      "text/plain": [
       "<Quantity [ 29.30832407, -0.19527688, -0.08487876] km / s>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v_.to(u.km / u.s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Tercero: Calcula la trayectoria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "date_launch = time.Time('2011-11-26 15:02', scale='utc')\n",
    "date_arrival = time.Time('2012-08-06 05:17', scale='utc')\n",
    "tof = date_arrival - date_launch\n",
    "r0, _ = ephem.planet_ephem(ephem.EARTH, date_launch)\n",
    "r, _ = ephem.planet_ephem(ephem.MARS, date_arrival)\n",
    "\n",
    "(v0, v), = iod.lambert(Sun.k, r0, r, tof)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$[-29.29151,~14.533265,~5.4169134] \\; \\mathrm{\\frac{km}{s}}$"
      ],
      "text/plain": [
       "<Quantity [-29.29150991, 14.53326535,  5.41691338] km / s>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$[17.615499,~-10.998307,~-4.2079605] \\; \\mathrm{\\frac{km}{s}}$"
      ],
      "text/plain": [
       "<Quantity [ 17.6154993 ,-10.99830709, -4.20796052] km / s>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### ...y es Python puro!\n",
    "\n",
    "Truco: **numba**\n",
    "\n",
    "![Fortran and Python](benchmark.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Cuarto: ¡vamos a Marte!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def go_to_mars(offset=500., tof_=6000.):\n",
    "    # Initial data\n",
    "    N = 50\n",
    "\n",
    "    date_launch = time.Time('2016-03-14 09:31', scale='utc') + ((offset - 500.) * u.day)\n",
    "    date_arrival = time.Time('2016-10-19 16:00', scale='utc') + ((offset - 500.) * u.day)\n",
    "    tof = tof_ * u.h\n",
    "\n",
    "    # Calculate vector of times from launch and arrival Julian days\n",
    "    jd_launch = date_launch.jd\n",
    "    jd_arrival = jd_launch + tof.to(u.day).value\n",
    "    jd_vec = np.linspace(jd_launch, jd_arrival, num=N)\n",
    "\n",
    "    times_vector = time.Time(jd_vec, format='jd')\n",
    "    rr_earth, vv_earth = ephem.planet_ephem(ephem.EARTH, times_vector)\n",
    "    rr_mars, vv_mars = ephem.planet_ephem(ephem.MARS, times_vector)\n",
    "    # Compute the transfer orbit!\n",
    "    r0 = rr_earth[:, 0]\n",
    "    rf = rr_mars[:, -1]\n",
    "\n",
    "    (va, vb), = iod.lambert(Sun.k, r0, rf, tof)\n",
    "\n",
    "    ss0_trans = State.from_vectors(Sun, r0, va, date_launch)\n",
    "    ssf_trans = State.from_vectors(Sun, rf, vb, date_arrival)\n",
    "    # Extract whole orbit of Earth, Mars and transfer (for plotting)\n",
    "    rr_trans = np.zeros_like(rr_earth)\n",
    "    rr_trans[:, 0] = r0\n",
    "    for ii in range(1, len(jd_vec)):\n",
    "        tof = (jd_vec[ii] - jd_vec[0]) * u.day\n",
    "        rr_trans[:, ii] = ss0_trans.propagate(tof).r\n",
    "\n",
    "    # Better compute backwards\n",
    "    jd_init = (date_arrival - 1 * u.year).jd\n",
    "    jd_vec_rest = np.linspace(jd_init, jd_launch, num=N)\n",
    "\n",
    "    times_rest = time.Time(jd_vec_rest, format='jd')\n",
    "    rr_earth_rest, _ = ephem.planet_ephem(ephem.EARTH, times_rest)\n",
    "    rr_mars_rest, _ = ephem.planet_ephem(ephem.MARS, times_rest)\n",
    "    # Plot figure\n",
    "    # To add arrows:\n",
    "    # https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/streamplot.py#L140\n",
    "    fig = plt.figure(figsize=(10, 10))\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "    def plot_body(ax, r, color, size, border=False, **kwargs):\n",
    "        \"\"\"Plots body in axes object.\n",
    "\n",
    "        \"\"\"\n",
    "        return ax.plot(*r[:, None], marker='o', color=color, ms=size, mew=int(border), **kwargs)\n",
    "\n",
    "    # I like color\n",
    "    color_earth0 = '#3d4cd5'\n",
    "    color_earthf = '#525fd5'\n",
    "    color_mars0 = '#ec3941'\n",
    "    color_marsf = '#ec1f28'\n",
    "    color_sun = '#ffcc00'\n",
    "    color_orbit = '#888888'\n",
    "    color_trans = '#444444'\n",
    "\n",
    "    # Plotting orbits is easy!\n",
    "    ax.plot(*rr_earth.to(u.km).value, color=color_earth0)\n",
    "    ax.plot(*rr_mars.to(u.km).value, color=color_mars0)\n",
    "    ax.plot(*rr_trans.to(u.km).value, color=color_trans)\n",
    "\n",
    "    ax.plot(*rr_earth_rest.to(u.km).value, ls='--', color=color_orbit)\n",
    "    ax.plot(*rr_mars_rest.to(u.km).value, ls='--', color=color_orbit)\n",
    "\n",
    "    # But plotting planets feels even magical!\n",
    "    plot_body(ax, np.zeros(3), color_sun, 16)\n",
    "\n",
    "    plot_body(ax, r0.to(u.km).value, color_earth0, 8)\n",
    "    plot_body(ax, rr_earth[:, -1].to(u.km).value, color_earthf, 8)\n",
    "\n",
    "    plot_body(ax, rr_mars[:, 0].to(u.km).value, color_mars0, 8)\n",
    "    plot_body(ax, rf.to(u.km).value, color_marsf, 8)\n",
    "\n",
    "    # Add some text\n",
    "    ax.text(-0.75e8, -3.5e8, -1.5e8, \"ExoMars mission:\\nfrom Earth to Mars\",\n",
    "            size=20, ha='center', va='center', bbox={\"pad\": 30, \"lw\": 0, \"fc\": \"w\"})\n",
    "    ax.text(r0[0].to(u.km).value * 2.4, r0[1].to(u.km).value * 0.4, r0[2].to(u.km).value * 1.25,\n",
    "            \"Earth at launch\\n({})\".format(date_launch.to_datetime().strftime(\"%d %b\")),\n",
    "            ha=\"left\", va=\"bottom\", backgroundcolor='#ffffff')\n",
    "    ax.text(rf[0].to(u.km).value * 1.1, rf[1].to(u.km).value * 1.1, rf[2].to(u.km).value,\n",
    "            \"Mars at arrival\\n({})\".format(date_arrival.to_datetime().strftime(\"%d %b\")),\n",
    "            ha=\"left\", va=\"top\", backgroundcolor='#ffffff')\n",
    "    ax.text(-1.9e8, 8e7, 1e8, \"Transfer\\norbit\", ha=\"right\", va=\"center\", backgroundcolor='#ffffff')\n",
    "\n",
    "    # Tune axes\n",
    "    ax.set_xlim(-3e8, 3e8)\n",
    "    ax.set_ylim(-3e8, 3e8)\n",
    "    ax.set_zlim(-3e8, 3e8)\n",
    "\n",
    "    # And finally!\n",
    "    ax.view_init(30, 260)\n",
    "    plt.show()\n",
    "    #fig.savefig(\"trans_30_260.png\", bbox_inches='tight')\n",
    "    #return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "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": {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "go_to_mars()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Quinto: ¡¡Hagámoslo interactivo!!!1!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KgQMHVtU5tTdiwFPD7r77bjz77LMYPHiw+RMOh7Hvvvtizz33xJ577mmmVePx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\n8yjgIYQQQojN+39EkpMmeokVSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f766bda1198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from ipywidgets import interactive\n",
    "from IPython.display import display\n",
    "\n",
    "w = interactive(go_to_mars, offset=(0., 1000.), tof_=(100., 12000.))\n",
    "display(w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "### http://poliastro.github.io\n",
    "\n",
    "## ¡Mil gracias!\n",
    "\n",
    "![Rocket](rocket.png)"
   ]
  }
 ],
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