Ellipse Animation 5B.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (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": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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   "source": [
    "# Ellipse Animation 5A\n",
    "# revision 5 introduces the Kepler Equation, M = E-ε sin E, where ε is eccentricity,\n",
    "# M is Mean anomaly and E is Eccentric anomaly, from \n",
    "# https://en.wikipedia.org/wiki/Kepler%27s_laws_of_planetary_motion#Position_as_a_function_of_time\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.animation import FuncAnimation, FFMpegWriter\n",
    "\n",
    "from math import floor\n",
    "%matplotlib notebook\n",
    "# set up figure size and DPI for screen demo\n",
    "# plt.rcParams['figure.figsize'] = (7, 7)\n",
    "# plt.rcParams['figure.dpi'] = 100\n",
    "\n",
    "TWOPI = 2*np.pi # numpy doesn't have tau (2π)\n",
    "\n",
    "# fig = plt.figure(figsize=(5, 10))\n",
    "# fig = plt.figure(figsize=(7, 7), dpi=100)\n",
    "fig = plt.figure()\n",
    "ax = plt.subplot(1,1,1,projection='polar') # subplot(nrows, ncols, index, **kwargs)\n",
    "\n",
    "# fig, ax = plt.subplots(projection='polar')\n",
    "\n",
    "# h&k are offsets from the origin for later use when setting a star at a focus\n",
    "# h = k = 0.0 # for now, the center of the ellipse is the origin\n",
    "# a = 1.2     # a is the semimajor axis\n",
    "# b = 0.8     # b is the semiminor axis (assuming a>b)\n",
    "\n",
    "e = 0.0 # eccentricity of the ellipse. e = |cs|/a, where |cs| is the distance from the center to a focus (=h, assuming no tilt) and a is the semimajor axis\n",
    "\n",
    "datastepsize = TWOPI/120\n",
    "theta = np.arange(0.0, TWOPI, datastepsize) # θ values from 0 to 2π in increments of datastepsize\n",
    "\n",
    "# cartesian:\n",
    "# x = h + a*np.cos(theta)    # x values from -1 to 1\n",
    "# y = h + b*np.sin(theta)    # y values from -1 to 1\n",
    "# l = plt.plot(x, y,         # x,y ellipse plot\n",
    "#              'b. ',        # made of blue dots--a visual check if the data points are\n",
    "#             )              # evenly spaced (they shouldn't be for orbits)\n",
    "# ax = plt.axis([-2,2,-2,2]) # plt.axis([xmin, xmax, ymin, ymax])\n",
    "#                            # equivalent to ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))\n",
    "\n",
    "# redDot, = plt.plot([x[0]], [y[0]], 'ro')\n",
    "\n",
    "# polar:\n",
    "\n",
    "# r = np.arange(1.0, 1.0, datastepsize) # !!!!! don't think this is right\n",
    "# r = np.full(floor(TWOPI/datastepsize), 1.0) # fill an nparray of the same size as theta with all 1.0's\n",
    "r = theta\n",
    "# x = h + a*np.cos(theta)    # x values from -1 to 1\n",
    "# y = h + b*np.sin(theta)    # y values from -1 to 1\n",
    "# l = plt.plot(x, y,         # x,y ellipse plot\n",
    "#              'b. ',        # made of blue dots--a visual check if the data points are\n",
    "#             )              # evenly spaced (they shouldn't be for orbits)\n",
    "\n",
    "plt.plot(theta, r, 'b. ')\n",
    "# ax = plt.axis([-2,2,-2,2]) # plt.axis([xmin, xmax, ymin, ymax])\n",
    "#                            # equivalent to ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))\n",
    "\n",
    "redDot, = plt.plot([theta[0]], r[0], 'ro')\n",
    "\n",
    "# plt.plot\n",
    "\n",
    "\"\"\"\n",
    "Note that the value at x[-1] yields the last value in the numpy ndarray x.\n",
    "\n",
    "It's the same value as x[floor(1000*TWOPI)], so when we want to reference various\n",
    "values of x and y based on the iterator i with values from 0 to 2π the index of the\n",
    "array x or y is the floor of 1000*i. It's times 1000 because we initially used a step\n",
    "size of 1/1000 or 0.001. In the general case, it would be x[floor(i/datastepsize)].\n",
    "\"\"\"\n",
    "\n",
    "def animate(i):\n",
    "#     redDot.set_data(np.cos(i), np.sin(i))\n",
    "#    redDot.set_data(x[floor(i/datastepsize)], y[floor(i/datastepsize)])\n",
    "#     redDot.set_data(x[floor(i/0.001)], y[floor(i/0.001)])\n",
    "#     redDot.set_data(x[floor(i*1000)], y[floor(i*1000)])\n",
    "    redDot.set_data(theta[floor(i/datastepsize)], r[floor(i/datastepsize)])\n",
    "    plt.title('radians: {:^2.1f}'.format(i))\n",
    "    return redDot,\n",
    "\n",
    "# create animation using the animate() function\n",
    "\n",
    "# disabling progress_callback lambda function during mybinder.org development on iPad :)\n",
    "\n",
    "# progress_callback = lambda i, n: print(f'Saving frame {i+1} of {n}')\n",
    "animation = FuncAnimation(fig, animate, frames=np.arange(0.0, TWOPI, 0.01),\n",
    "                          interval=5, blit=True, repeat=False)\n",
    "\n",
    "# animation = FuncAnimation(plt.gcf(), #get current figure or gcf\n",
    "#                           update, #the function to update\n",
    "#                           frames=frames, #overrides the default frames behavior of counting up i in integers from 0\n",
    "#                           interval=interval,\n",
    "#                           #repeat = False, #option to stop animation after one iteration\n",
    "#                           repeat_delay = 2e3, #optional delay in ms; 1e3 = 1000 ms = 1 s\n",
    "#                           #progress_callback=progress_callback\n",
    "#                           )\n",
    "\n",
    "# disabling saving .mp4 during mybinder.org development on iPad :)\n",
    "\n",
    "# # from matplotlib.animation import FFMpegWriter\n",
    "# writer = FFMpegWriter(fps=15, metadata=dict(artist='Stephen Shadle'), bitrate=1800)\n",
    "# #ani.save(\"/home/pi/Documents/Thonny/dynamic_image.mp4\", writer=writer) #explicit directory\n",
    "# animation.save(\"animate_ellipse.mp4\", writer=writer, progress_callback=progress_callback) #current directory\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "120"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(theta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "120"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05235987755982988"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TWOPI/120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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