index.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, (ax_peso, ax_talla) = plt.subplots(nrows=2, ncols=1, figsize=(12, 8), sharex=True)\n",
    "\n",
    "# peso\n",
    "percentiles_peso = pd.read_csv('wtageinf.csv', index_col='Agemos')\n",
    "\n",
    "pesadas = pd.read_csv('pesadas.txt', index_col='fecha', parse_dates=True, dayfirst=True)\n",
    "pesadas['meses'] = (pesadas.index - pesadas.index[0]).days / 30\n",
    "\n",
    "percentiles_peso.query('Sex==1')[['P3', 'P5', 'P10', 'P25', 'P50', 'P75', 'P90', 'P95', 'P97']].plot(ax=ax_peso, cmap='jet', legend=None, linewidth=5, alpha=0.5)\n",
    "pesadas.plot.scatter(ax=ax_peso, x='meses', y='peso', color='black', marker='x')\n",
    "\n",
    "ax_peso.legend(ncol=3, loc='lower right', fontsize=10, framealpha=0.15)\n",
    "\n",
    "ax_peso.set_xlim([0, 12])\n",
    "ax_peso.set_ylim([2, 9])\n",
    "\n",
    "ax_peso.grid(True)\n",
    "\n",
    "# talla\n",
    "percentiles_talla = pd.read_csv('lenageinf.csv', index_col='Agemos', skiprows=[38])\n",
    "\n",
    "talladas = pd.read_csv('talladas.txt', index_col='fecha', parse_dates=True, dayfirst=True)\n",
    "talladas['meses'] = (talladas.index - talladas.index[0]).days / 30\n",
    "\n",
    "percentiles_talla.query('Sex==1')[['P3', 'P5', 'P10', 'P25', 'P50', 'P75', 'P90', 'P95', 'P97']].plot(ax=ax_talla, cmap='jet', legend=None, linewidth=5, alpha=0.5)\n",
    "talladas.plot.scatter(ax=ax_talla, x='meses', y='talla', color='black', marker='x')\n",
    "\n",
    "ax_talla.legend(ncol=3, loc='lower right', fontsize=10, framealpha=0.15)\n",
    "\n",
    "ax_talla.set_xlim([0, 12])\n",
    "ax_talla.set_ylim([45, 70])\n",
    "\n",
    "ax_talla.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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