neuromathmod_simple.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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": [
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     },
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     "output_type": "display_data"
    },
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width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import neuromathmod_test\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}