tsp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "1.7261607107863532"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "import pylab\n",
    "import operator\n",
    "import math\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "xsize=10\n",
    "ysize=10\n",
    "\n",
    "def makeCities(n=50):\n",
    "    cities=[]\n",
    "    for i in range(0,n):\n",
    "        cities.append((i,xsize*random.random(),ysize*random.random()))\n",
    "    return cities\n",
    "\n",
    "def plotCities(cities):\n",
    "    x=[city[1] for city in cities]\n",
    "    y=[city[2] for city in cities]\n",
    "    \n",
    "    plt.scatter(x,y)\n",
    "        \n",
    "def plotConnections(cities, connections):\n",
    "    x=[]\n",
    "    y=[]\n",
    "    for c in range(0,len(connections)):\n",
    "        i=connections[c]\n",
    "        j=connections[(c+1)%len(connections)]\n",
    "        x.append(cities[i][1])\n",
    "        x.append(cities[j][1])\n",
    "        y.append(cities[i][2])\n",
    "        y.append(cities[j][2])\n",
    "    plt.plot(x,y)\n",
    "    \n",
    "def connectCities(cities):\n",
    "    return list(range(0,len(cities)))\n",
    "    \n",
    "def pathLength(cities, connections):\n",
    "    length=0\n",
    "    for c in range(0,len(connections)):\n",
    "        i=connections[c]\n",
    "        j=connections[(c+1)%len(connections)]\n",
    "        x1=cities[i][1]\n",
    "        x2=cities[j][1]\n",
    "        y1=cities[i][2]\n",
    "        y2=cities[j][2]\n",
    "        length+=math.sqrt((x1-x2)**2+(y1-y2)**2)\n",
    "    return length\n",
    "\n",
    "def avgConnectionLength(cities, connections):\n",
    "    length = pathLength(cities, connections)\n",
    "    return length/len(cities)\n",
    "\n",
    "def optimizeStep(cities, connections, temperature, length):\n",
    "    newConns = list(connections)\n",
    "    for n in range(0,1):\n",
    "        i = random.randint(0,len(connections) - 1)\n",
    "        j = random.randint(0,len(connections) - 1)\n",
    "        newConns[i],newConns[j] = newConns[j],newConns[i]\n",
    "    newLength = pathLength(cities, newConns)\n",
    "    delta = (newLength - length) / length\n",
    "    if delta > temperature:\n",
    "        return (length, connections)\n",
    "    else:\n",
    "        return (newLength, newConns)\n",
    "\n",
    "def optimize(cities, connections, steps=100000, decay=1000):\n",
    "    length = pathLength(cities, connections)\n",
    "    for i in range(0, steps):\n",
    "        temperature = math.exp(-i/decay)\n",
    "        length, connections = optimizeStep(cities, connections, temperature, length)\n",
    "    return connections\n",
    "\n",
    "cities = makeCities()\n",
    "connections = connectCities(cities)\n",
    "\n",
    "connections = optimize(cities, connections)\n",
    "\n",
    "plt.ylim((0,ysize))\n",
    "plt.xlim((0,xsize))\n",
    "plt.axes().set_aspect('equal')\n",
    "plotCities(cities)\n",
    "plotConnections(cities,connections)\n",
    "plt.show()\n",
    "\n",
    "avgConnectionLength(cities, connections)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}