IK_CCD_AngleLimit

IK_CCD-angleLimit2.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Inverse Kinematics: CCD + Angle Limit"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-04-30T21:01:26.589551Z",
          "end_time": "2021-04-30T21:01:28.239675Z"
        },
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          "iopub.status.idle": "2021-03-09T19:28:06.867Z",
          "shell.execute_reply": "2021-03-09T19:28:07.034Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%matplotlib notebook\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom math import tau, pi, sin, cos",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-04-30T21:01:28.242642Z",
          "end_time": "2021-04-30T21:01:28.292915Z"
        },
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          "iopub.status.busy": "2021-03-09T19:28:06.898Z",
          "iopub.status.idle": "2021-03-09T19:28:06.936Z",
          "shell.execute_reply": "2021-03-09T19:28:07.040Z"
        },
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      "cell_type": "code",
      "source": "class Arm:\n    def __init__(self, ax, ay, length, angle, minAngle=-pi/2, maxAngle=pi/2):\n        self.ax = ax\n        self.ay = ay\n        self.length = length\n        self.angle = convTheta(angle)\n        self.bx = self.ax + self.length * cos(self.angle)\n        self.by = self.ay + self.length * sin(self.angle)\n        self.minAngle = convTheta(minAngle)\n        self.maxAngle = convTheta(maxAngle)\n    \n    def angleLimit(self, prevTheta, newTheta):\n        theta = convTheta(newTheta - prevTheta)\n        if theta < self.minAngle:\n            theta = self.minAngle\n        elif theta > self.maxAngle:\n            theta = self.maxAngle\n        self.angle = theta + prevTheta\n        self.bx = self.ax + self.length * cos(self.angle)\n        self.by = self.ay + self.length * sin(self.angle)\n\ndef convTheta(theta): # convert to Angle range between -180 and 180 degrees\n    theta = theta % tau\n    if theta > pi:\n        theta = theta - tau\n    return theta ",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-04-30T21:01:28.299547Z",
          "end_time": "2021-04-30T21:01:28.407901Z"
        },
        "code_folding": [
          18
        ],
        "trusted": true
      },
      "cell_type": "code",
      "source": "N  = 4 # the number of links\nOX = 0 # offset x\nOY = 0 # offset y\n\nccd, ccd2 = [], []\nlinkLength = 1\ninitTheta = pi / 2\n\nfor i in range(N):\n    if i == 0:\n        ccd.append(Arm(OX, OY, linkLength, initTheta))\n        ccd2.append(Arm(OX, OY, linkLength, initTheta, 0, pi))\n    else:\n        ccd.append(Arm(ccd[i-1].bx, ccd[i-1].by, linkLength, initTheta))\n        ccd2.append(Arm(ccd2[i-1].bx, ccd2[i-1].by, linkLength, initTheta, -pi/2, pi/2))\n    \nCX, CY = [], []        \nLX, LY = [], []\nfor i in range(N):\n    CX.append([ccd[i].ax, ccd[i].bx])\n    CY.append([ccd[i].ay, ccd[i].by])\n    LX.append([ccd2[i].ax, ccd2[i].bx])\n    LY.append([ccd2[i].ay, ccd2[i].by])\n        \nfig = plt.figure(figsize=(5,5))\nax = fig.add_subplot(111, alpha=0.6)\nax.axis([-1,N+1,-1,N+1])\nax.grid()\nax.plot(CX, CY, color='tab:blue', alpha=0.6)\nax.scatter(CX, CY, color='tab:blue', alpha=0.6)\nax.plot(LX, LY, color='magenta', alpha=0.6)\nax.scatter(LX, LY, color='magenta', alpha=0.6)",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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    fig.cell_info[0].output_area.element.one(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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 / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
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\" width=\"500\">"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "<matplotlib.collections.PathCollection at 0x7f943d437d60>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-17T19:09:02.040245Z",
          "start_time": "2021-04-17T19:09:02.031562Z"
        }
      },
      "cell_type": "markdown",
      "source": "<img width=\"70%\" align=\"left\" alt=\"ccd\" src=\"https://user-images.githubusercontent.com/26479204/116737642-671a6c80-aa2c-11eb-898f-0dbf50bddcc9.png\">"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-04-30T21:01:28.415983Z",
          "end_time": "2021-04-30T21:01:28.552473Z"
        },
        "code_folding": [
          0
        ],
        "trusted": true
      },
      "cell_type": "code",
      "source": "def CCD(arm, tx, ty):\n    for i in reversed(range(N)):\n        targetTheta = np.arctan2(ty - arm[i].ay, tx - arm[i].ax)\n        tipTheta = np.arctan2(arm[-1].by - arm[i].ay, arm[-1].bx - arm[i].ax)\n        theta = targetTheta - tipTheta;\n        for j in range(i, N):\n            linkTheta = np.arctan2(arm[j].by - arm[i].ay, arm[j].bx - arm[i].ax)\n            linkDist = ((arm[j].bx - arm[i].ax)**2 + (arm[j].by - arm[i].ay)**2)**0.5\n            arm[j].bx = arm[i].ax + linkDist * np.cos(theta + linkTheta)\n            arm[j].by = arm[i].ay + linkDist * np.sin(theta + linkTheta)\n            if j < N - 1:\n                arm[j+1].ax = arm[j].bx\n                arm[j+1].ay = arm[j].by\n    \n    PX, PY = [], []\n    for i in range(N):\n        PX.append(arm[i].ax)\n        PY.append(arm[i].ay)\n    PX.append(arm[N-1].bx)\n    PY.append(arm[N-1].by)\n    \n    return PX, PY\n\n\ndef CCD2(arm, tx, ty):\n    for i in reversed(range(N)):\n        targetTheta = np.arctan2(ty - arm[i].ay, tx - arm[i].ax)\n        tipTheta = np.arctan2(arm[-1].by - arm[i].ay, arm[-1].bx - arm[i].ax)\n        dTheta = convTheta(targetTheta - tipTheta)\n        for j in range(i, N):\n            if j == 0:\n                arm[j].angleLimit(0, arm[j].angle + dTheta)\n            else:\n                arm[j].ax = arm[j-1].bx\n                arm[j].ay = arm[j-1].by\n                linkTheta = np.arctan2(arm[j].by - arm[i].ay, arm[j].bx - arm[i].ax)\n                linkDist = ((arm[j].bx - arm[i].ax)**2 + (arm[j].by - arm[i].ay)**2)**0.5\n                arm[j].bx = arm[i].ax + linkDist * cos(linkTheta + dTheta)\n                arm[j].by = arm[i].ay + linkDist * sin(linkTheta + dTheta)\n                \n                newTheta = np.arctan2(arm[j].by - arm[j].ay, arm[j].bx - arm[j].ax)\n                arm[j].angleLimit(arm[j-1].angle, newTheta)\n\n                \n    PX, PY = [], []\n    for i in range(N):\n        PX.append(arm[i].ax)\n        PY.append(arm[i].ay)\n    PX.append(arm[N-1].bx)\n    PY.append(arm[N-1].by)\n    \n    return PX, PY\n\ntx, ty = N*0.7, N*0.5\nCX, CY = CCD(ccd, tx, ty)\nLX, LY = CCD2(ccd2, tx, ty)\n\nfig = plt.figure(figsize=(5,5))\nax = fig.add_subplot(111)\nax.axis([-1,N+1,-1,N+1])\nax.grid()\nax.plot(CX, CY, color='tab:blue', alpha=0.6)\nax.scatter(CX, CY, color='tab:blue', alpha=0.6)\nax.plot(LX, LY, color='magenta', alpha=0.6)\nax.scatter(LX, LY, color='magenta', alpha=0.6)\nax.plot([tx], [ty], marker='x', ms=30, color='red')",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<IPython.core.display.Javascript object>",
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\nmpl.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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(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 (fig.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n    if (this.ratio !== 1) {\n        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n    }\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    var resizeObserver = new ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    resizeObserver.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\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\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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    fig.cell_info[0].output_area.element.one(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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 / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
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\" width=\"500\">"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x7f943d4b8a60>]"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Interactive mode: Arm follows Mouse"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2021-04-30T21:01:28.560358Z",
          "end_time": "2021-04-30T21:01:28.680817Z"
        },
        "code_folding": [],
        "trusted": true
      },
      "cell_type": "code",
      "source": "def motion(event):\n    mx = event.xdata\n    my = event.ydata\n    Mouse.set_data(mx, my)\n    \n    CX, CY = CCD(ccd, mx, my)\n    CLine.set_data(CX, CY)\n    CDot.set_data(CX, CY)\n    \n    LX, LY = CCD2(ccd2, mx, my)\n    LLine.set_data(LX, LY)\n    LDot.set_data(LX, LY)\n    \n    plt.draw()\n\nfig = plt.figure(figsize=(5,5))\nax = fig.add_subplot(111)\nax.axis([-1,N+1,-1,N+1])\nax.grid()\n\nCLine, = ax.plot([],[], linestyle='-', color='tab:blue', alpha=0.6, label='CCD')\nCDot, = ax.plot([],[], marker='o', color='tab:blue', alpha=0.6)\nLLine, = ax.plot([],[], linestyle='-', color='magenta', alpha=0.6, label='CCD_AL')\nLDot, = ax.plot([],[], marker='o', color='magenta', alpha=0.6)\nMouse, = ax.plot([],[], marker='x', ms=20, color='red')\n\nplt.connect('motion_notify_event', motion)\nplt.legend(loc='lower right')\nplt.show()",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<IPython.core.display.Javascript object>",
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\nmpl.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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(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 (fig.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n    if (this.ratio !== 1) {\n        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n    }\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    var resizeObserver = new ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    resizeObserver.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\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\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                evt.data\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.which === this._key) {\n            return;\n        } else {\n            this._key = event.which;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.which !== 17) {\n        value += 'ctrl+';\n    }\n    if (event.altKey && event.which !== 18) {\n        value += 'alt+';\n    }\n    if (event.shiftKey && event.which !== 16) {\n        value += 'shift+';\n    }\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, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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    fig.cell_info[0].output_area.element.one(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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 / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.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\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
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\" 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          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "_draft": {
      "nbviewer_url": "https://gist.github.com/9812d63557b813f1dd5ae3bbb01ff460"
    },
    "gist": {
      "id": "9812d63557b813f1dd5ae3bbb01ff460",
      "data": {
        "description": "IK_CCD_AngleLimit",
        "public": true
      }
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
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      "version": "3.8.5",
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      "codemirror_mode": {
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      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
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    "nteract": {
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  "nbformat": 4,
  "nbformat_minor": 4
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