mdp/policy_agent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys ###dppolicyagent\n",
    "sys.path.append('../scripts/')\n",
    "from puddle_world import *\n",
    "import itertools\n",
    "import collections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PolicyAgent(PuddleIgnoreAgent): \n",
    "    def __init__(self, time_interval, estimator, goal, puddle_coef=100, widths=np.array([0.2, 0.2, math.pi/18]).T, \\\n",
    "                 lowerleft=np.array([-4, -4]).T, upperright=np.array([4, 4]).T, policyfile=\"../data/dp_policy.txt\"): \n",
    "        super().__init__(time_interval, estimator, goal, puddle_coef) \n",
    "        \n",
    "        ###座標関連の変数をDynamicProgrammingから持ってくる###\n",
    "        self.pose_min = np.r_[lowerleft, 0] \n",
    "        self.pose_max = np.r_[upperright, math.pi*2]\n",
    "        self.widths = widths\n",
    "        self.index_nums = ((self.pose_max - self.pose_min)/self.widths).astype(int)\n",
    "        \n",
    "        self.policyfile = policyfile\n",
    "        self.policy_data = self.init_policy(self.index_nums)\n",
    "        \n",
    "    def init_policy(self, index_nums):\n",
    "        tmp = np.zeros(np.r_[index_nums,2])\n",
    "        for line in open(self.policyfile, \"r\"):\n",
    "            d = line.split()\n",
    "            tmp[int(d[0]), int(d[1]), int(d[2])] = [float(d[3]), float(d[4])]\n",
    "            \n",
    "        return tmp\n",
    "    \n",
    "    def to_index(self, pose, pose_min, index_nums , widths): #姿勢をインデックスに変えて正規化\n",
    "        index = np.floor((pose - pose_min)/widths).astype(int)           #姿勢からインデックスに\n",
    "        \n",
    "        index[2] = (index[2] + index_nums[2]*1000)%index_nums[2] #角度の正規化\n",
    "        for i in [0,1]:                                                                                   #端の処理（内側の座標の方策を使う）\n",
    "            if index[i] < 0: index[i] = 0\n",
    "            elif index[i] >= index_nums[i]: index[i] = index_nums[i] - 1\n",
    "                \n",
    "        return tuple(index) #ベクトルのままだとインデックスに使えないのでタプルに\n",
    "    \n",
    "    def policy(self, pose, goal=None): #姿勢から離散状態のインデックスを作って方策を参照して返すだけ                \n",
    "        return self.policy_data[self.to_index(pose, self.pose_min, self.index_nums, self.widths)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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\", \"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>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"400\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def trial():  ###dppolicyagentrun\n",
    "    time_interval = 0.1\n",
    "    world = PuddleWorld(30, time_interval, debug=False) \n",
    "\n",
    "    ## 地図を生成して3つランドマークを追加 ##\n",
    "    m = Map()\n",
    "    for ln in [(-4,2), (2,-3), (4,4), (-4,-4)]: m.append_landmark(Landmark(*ln))\n",
    "    world.append(m)   \n",
    "\n",
    "    ##ゴールの追加##\n",
    "    goal = Goal(-3,-3)  #goalを変数に\n",
    "    world.append(goal)\n",
    "    \n",
    "    ##水たまりの追加##\n",
    "    world.append(Puddle((-2, 0), (0, 2), 0.1)) \n",
    "    world.append(Puddle((-0.5, -2), (2.5, 1), 0.1)) \n",
    "\n",
    "    ##4台のロボットを動かしてみる##   ##dppolicyagentrun\n",
    "    init_poses = []\n",
    "    for p in [[-3, 3, 0], [0.5, 1.5, 0], [3, 3, 0], [2, -1, 0]]:\n",
    "        init_pose = np.array(p).T\n",
    "    \n",
    "        kf = KalmanFilter(m, init_pose)\n",
    "        a = PolicyAgent(time_interval, kf, goal, policyfile=\"../data/dp_policy.txt\")\n",
    "        r = Robot(init_pose, sensor=Camera(m, distance_bias_rate_stddev=0, direction_bias_stddev=0), \n",
    "              agent=a, color=\"red\", bias_rate_stds=(0,0))\n",
    "\n",
    "        world.append(r)\n",
    "        \n",
    "    world.draw()\n",
    "    \n",
    "trial()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
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