EmptyTanks.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modelica.Fluid.Examples.Tanks.EmptyTanks を実行する\n",
    "\n",
    "モデルをコンパイルしてFMUを作成します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pymodelica import compile_fmu\n",
    "fmu_name = compile_fmu(\"Modelica.Fluid.Examples.Tanks.EmptyTanks\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FMUをロードします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyfmi import load_fmu\n",
    "model = load_fmu(fmu_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "オプションでソルバーを LSODAR に変えてシミュレーションを実行します。\n",
    "オプションの詳細は help(opts) で確認できます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final Run Statistics: --- \n",
      "\n",
      " Number of steps                       : 74\n",
      " Number of function evaluations        : 203\n",
      " Number of Jacobian evaluations        : 10\n",
      " Number of state function evaluations  : 145\n",
      " Number of state events                : 3\n",
      "\n",
      "Solver options:\n",
      "\n",
      " Solver                  : LSODAR \n",
      " Absolute tolerances     : [  1.00000000e-06   3.00000000e-04   1.00000000e-06   3.00000000e-04]\n",
      " Relative tolerances     : 0.0001\n",
      " Starter                 : classical\n",
      "\n",
      "Simulation interval    : 0.0 - 50.0 seconds.\n",
      "Elapsed simulation time: 0.0151219367981 seconds.\n"
     ]
    }
   ],
   "source": [
    "opts = model.simulate_options()\n",
    "opts['solver'] = \"LSODAR\"\n",
    "res = model.simulate(options=opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "シミュレーション結果を取得します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "level1 = res['tank1.level']\n",
    "level2 = res['tank2.level']\n",
    "mflow = res['pipe.port_a.m_flow']\n",
    "t = res['time']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "プロットします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(1)\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(t, level1, t, level2)\n",
    "plt.ylabel('Tank Level (m)')\n",
    "plt.legend(['Tank1 Level','Tank2 Level'])\n",
    "plt.subplot(2,1,2)\n",
    "plt.plot(t,mflow)\n",
    "plt.ylabel('mass flow rate (kg/s)')\n",
    "plt.legend(['Pipe Mass Flow Rate'])\n",
    "plt.xlabel('Time (s)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.17"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}

JModelica.org 使い方メモ