csiborgtools/scripts/playground.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a38ed25",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-06T10:20:02.405259Z",
     "start_time": "2022-11-06T10:19:59.114936Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "try:\n",
    "    import csiborgtools\n",
    "except ModuleNotFoundError:\n",
    "    import sys\n",
    "    sys.path.append(\"../\")\n",
    "    import csiborgtools\n",
    "import utils\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import joblib\n",
    "from os.path import join"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "267eb013",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-06T10:20:27.266576Z",
     "start_time": "2022-11-06T10:20:24.523404Z"
    }
   },
   "outputs": [],
   "source": [
    "Nsim = 9844\n",
    "Nsnap = 1016\n",
    "\n",
    "data = utils.load_processed(Nsim, Nsnap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f8c6d928",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-06T10:24:20.697506Z",
     "start_time": "2022-11-06T10:24:19.631208Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\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",
       "\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 = 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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = 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",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.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",
       "\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.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",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\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",
       "\n",
       "mpl.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",
       "\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.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",
       "\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.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",
       "\n",
       "mpl.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",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       "    }\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",
       " * https://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",
       "        }\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",
       "        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",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = 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.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.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",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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",
       "\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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(11.8, 15.4, 0.2)\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "x, mu, std = csiborgtools.match.number_density(data, \"m200\", bins, 200, True)\n",
    "plt.errorbar(x, mu, std, capsize=4, label=r\"$M_{200c}$\")\n",
    "\n",
    "x, mu, std = csiborgtools.match.number_density(data, \"m500\", bins, 200, True)\n",
    "plt.errorbar(x, mu, std, capsize=4, label=r\"$M_{500c}$\")\n",
    "\n",
    "x, mu, std = csiborgtools.match.number_density(data, \"totpartmass\", bins, 200, True)\n",
    "plt.errorbar(x, mu, std, capsize=4, label=r\"$M_{\\rm tot}$\")\n",
    "\n",
    "x, mu, std = csiborgtools.match.number_density(data, \"mass_mmain\", bins, 200, True)\n",
    "plt.errorbar(x, mu, std, capsize=4, label=r\"$M_{\\rm mmain}$\")\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.yscale(\"log\")\n",
    "plt.xscale(\"log\")\n",
    "\n",
    "plt.ylabel(r\"$\\phi / (\\mathrm{Mpc}^{-3})~\\mathrm{dex}$\")\n",
    "plt.xlabel(r\"$M_{\\rm x}$\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"../plots/HMF.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "985d46c9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-06T10:20:46.078113Z",
     "start_time": "2022-11-06T10:20:44.524929Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\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",
       "\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 = 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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = 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",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.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",
       "\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.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",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\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",
       "\n",
       "mpl.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",
       "\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.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",
       "\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.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",
       "\n",
       "mpl.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",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       "    }\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",
       " * https://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",
       "        }\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",
       "        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",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = 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.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.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",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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",
       "\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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nfw = csiborgtools.fits.NFWProfile()\n",
    "m200_nfw = nfw.enclosed_mass(data[\"r200\"], data[\"Rs\"], data[\"rho0\"])\n",
    "\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.scatter(data[\"m200\"], m200_nfw, s=1)\n",
    "t = np.linspace(1e11, 1e15)\n",
    "plt.plot(t, t, c=\"red\", ls=\"--\", lw=1.5)\n",
    "plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "\n",
    "plt.xlabel(r\"$M_{200c}$\")\n",
    "plt.ylabel(r\"$M_{\\mathrm{NFW}, 200c}$\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"../plots/enclosed_vs_nfw.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8923ca86",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6eb8ba93",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-06T10:22:19.498275Z",
     "start_time": "2022-11-06T10:22:17.953025Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\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",
       "\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 = 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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = 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",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.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",
       "\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",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.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 (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.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",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\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",
       "\n",
       "mpl.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",
       "\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.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",
       "\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.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",
       "\n",
       "mpl.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",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       "    }\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",
       " * https://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",
       "        }\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",
       "        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",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = 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.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.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",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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",
       "\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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "logm200 = np.log10(data[\"m200\"])\n",
    "conc = data[\"conc\"]\n",
    "\n",
    "N = 10\n",
    "bins = np.linspace(logm200.min(), logm200.max(), N)\n",
    "x = [0.5*(bins[i] + bins[i + 1]) for i in range(N-1)]\n",
    "y = np.full((N - 1, 3), np.nan)\n",
    "for i in range(N - 1):\n",
    "    mask = (logm200 >= bins[i]) & (logm200 < bins[i + 1]) & np.isfinite(conc)\n",
    "    y[i, :] = np.percentile(conc[mask], [14, 50, 84])\n",
    "\n",
    "\n",
    "    \n",
    "    \n",
    "fig, axs = plt.subplots(nrows=2, sharex=True, figsize=(6.4, 6.4 * 1))\n",
    "fig.subplots_adjust(hspace=0)\n",
    "axs[0].plot(x, y[:, 1], c=\"red\", marker=\"o\")\n",
    "axs[0].fill_between(x, y[:, 0], y[:, 2], color=\"red\", alpha=0.25)\n",
    "axs[1].hist(logm200, bins=\"auto\", log=True)\n",
    "\n",
    "for b in bins:\n",
    "    for i in range(2):\n",
    "        axs[i].axvline(b, c=\"orange\", lw=0.5)\n",
    "\n",
    "axs[0].set_ylim(2, 10)\n",
    "axs[1].set_xlabel(r\"$M_{200c}$\")\n",
    "axs[0].set_ylabel(r\"$c_{200c}$\")\n",
    "axs[1].set_ylabel(r\"Counts\")\n",
    "\n",
    "plt.tight_layout(h_pad=0)\n",
    "plt.savefig(\"../plots/mass_concentration.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be26cbcc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv_galomatch",
   "language": "python",
   "name": "venv_galomatch"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  },
  "vscode": {
   "interpreter": {
    "hash": "f29d02a8350410abc2a9fb79641689d10bf7ab64afc03ec87ca3cf6ed2daa499"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}