csiborgtools/scripts/plot_concentration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a38ed25",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-05T19:13:52.330907Z",
     "start_time": "2022-11-05T19:13:48.488980Z"
    }
   },
   "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\n",
    "from glob import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "267eb013",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-05T19:47:57.931968Z",
     "start_time": "2022-11-05T19:47:51.411225Z"
    }
   },
   "outputs": [],
   "source": [
    "Nsim = 9844\n",
    "simpath = csiborgtools.io.get_sim_path(Nsim)\n",
    "Nsnap = 1016\n",
    "\n",
    "outfname = join(utils.dumpdir, \"ramses_out_{}_{}.npy\".format(str(Nsim).zfill(5), str(Nsnap).zfill(5)))\n",
    "\n",
    "mmain = csiborgtools.io.read_mmain(Nsim, \"/mnt/zfsusers/hdesmond/Mmain\")\n",
    "\n",
    "data = np.load(outfname)\n",
    "data = csiborgtools.io.merge_mmain_to_clumps(data, mmain)\n",
    "\n",
    "data = data[(data[\"npart\"] > 100) & np.isfinite(data[\"m200\"])]\n",
    "\n",
    "boxunits = csiborgtools.units.BoxUnits(Nsnap, simpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "ddb244c0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-05T20:16:08.055506Z",
     "start_time": "2022-11-05T20:16:07.116399Z"
    }
   },
   "outputs": [
    {
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       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
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       "    this.header = titletext;\n",
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       "\n",
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       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
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       "    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",
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       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
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       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
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       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
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       "\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",
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       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
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       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
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       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
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       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
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       "                // Chrome 84 implements new version of spec.\n",
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       "    });\n",
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       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
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       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
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       "};\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",
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       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
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       "        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",
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       "    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",
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       "        var fmt = mpl.extensions[ind];\n",
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       "        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": [
    "m200 = boxunits.box2solarmass(data[\"m200\"])\n",
    "m500 = boxunits.box2solarmass(data[\"m500\"])\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "plt.scatter(m200, m500, s=1, rasterized=True)\n",
    "t = np.linspace(1e11, 1e15)\n",
    "plt.plot(t,t,c=\"red\", ls=\"--\")\n",
    "plt.yscale(\"log\")\n",
    "plt.xscale(\"log\")\n",
    "\n",
    "plt.xlabel(r\"$M_{\\rm 200c}$\")\n",
    "plt.ylabel(r\"$M_{\\rm 500c}$\")\n",
    "plt.savefig(\"../plots/masses.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "6eb8ba93",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-05T20:12:58.775164Z",
     "start_time": "2022-11-05T20:12:57.143437Z"
    },
    "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(boxunits.box2solarmass(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()"
   ]
  }
 ],
 "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
}