example-analysis-cgm.ipynb

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    "# This is an examples of how to perform a CGM analysis using the rb_spec.py pipeline\n",
    "\n",
    "\n",
    "## Written By: Rongmon Bordoloi\n",
    "----------------\n",
    "\n",
    "The goal of this notebook is to show a running example analysing absorption line spectra. We will read in a fits file of a HST/COS quasar, pick one absorption line, continuum normalize it locally and then compute the EW and AOD column density of that line. \n",
    "\n",
    "This pipeline allows one to do a batch mode continuum normalization or an interactive local continuum normalization\n",
    "\n",
    "\n",
    "-----------------\n",
    "Example Created: Feb 11, 2021\n",
    "\n",
    "Tested on Python 3.7\n",
    "https://github.com/rongmon/rbcodes\n",
    "\n",
    "-------------------\n",
    "## Requirements: \n",
    "\n",
    "astropy, numpy, scipy, matplotlib,linetools\n",
    "\n",
    "\n",
    "\n",
    "linetools for input output of fits files, and for COS LSF\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "from GUIs.rb_spec import rb_spec as r\n",
    "from IGM import rb_setline as setline\n",
    "from linetools.spectra.xspectrum1d import XSpectrum1D  \n",
    "from importlib import reload\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read in the data that you want to measure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalizing spectrum using given continuum...\n"
     ]
    }
   ],
   "source": [
    "filename='example-data/test.fits'\n",
    "s=r.from_file(filename,filetype='xfits')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The transition of the absorber and it's redshift"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Redshift of the absorber you are trying to fit\n",
    "zabs=0.348\n",
    "transition=1025.6 # HI 1025 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shift spectrum to the rest frame of the absorber"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.shift_spec(zabs);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a small slice of the spectrum that you want to analyze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'wave': 1025.7223, 'fval': 0.07912, 'name': 'HI 1025'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlim=[-600,600]\n",
    "s.slice_spec(transition,xlim[0],xlim[1],use_vel=True);\n",
    "# Showing the atomic tranistion and its line properties\n",
    "str1=setline.rb_setline(transition,'closest',linelist='LLS')\n",
    "str1"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Fit continuum \n",
    "\n",
    "## First we will fit in a non-interactive mode, a Legendre polinomial fit with part of the spectrum masked off\n",
    "\n",
    "Note: Use only the continuum fitting routine you want. You don't need to use both methods. I am commenting out the non-interactive mode below. But it is presented for psterity.\n",
    "\n",
    "<p> We mask the part of spectrum that we don't want to fit. </p>\n",
    "<p>Mask is created to have multiple low vel, high vel ranges.</p>\n",
    "<p>e.g. mask = [-300.,-250.,100.,120.] will exclude -300,-250 and 100,120 km/s parts of the spectrum in the fit\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Model is linear in parameters; consider using linear fitting methods. [astropy.modeling.fitting]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Both statistical and continuum fitting error included.\n"
     ]
    },
    {
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       "    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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-600.0, 600.0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.fit_continuum(mask=[-560,-500,-330,-230,-170,120.,140.,290.],domain=xlim,Legendre=3)\n",
    "\n",
    "\n",
    "\n",
    "# Show the fits\n",
    "plt.subplot(2,1,1)\n",
    "plt.step(s.velo,s.flux_slice)\n",
    "plt.step(s.velo,s.flux_slice/s.fnorm)\n",
    "plt.step(s.velo,s.cont,'k-')\n",
    "plt.step(s.velo,s.cont+s.cont_err,'k--')\n",
    "plt.step(s.velo,s.cont-s.cont_err,'k--')\n",
    "plt.step(s.velo,s.error_slice)\n",
    "plt.xlim(xlim)\n",
    "plt.subplot(2,1,2)\n",
    "plt.step(s.velo,s.fnorm)\n",
    "plt.step(s.velo,s.enorm)\n",
    "\n",
    "\n",
    "plt.plot([-600,600],[1,1],'--')\n",
    "plt.xlim(xlim)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## An alternate method to fit local continuum. \n",
    "\n",
    "## Interactive Continuum Fitting.\n",
    "\n",
    "## ***********************************\n",
    "\n",
    "\n",
    "<p>The required keystrikes are:</p>\n",
    "\n",
    "\n",
    "\n",
    "<p>         This calls an interactive continuum fitter for 1D spectrum.\n",
    "            We will create a spline continuum fit from selected points.\n",
    "    \n",
    "            Program sequence is important. First you select the continuum positions using either left mouse button or keystroke b. Right clock will deselect any continuum point. \n",
    "    \n",
    "    Then press 'enter' to fit the continuum. Then press 'n' to show the normalized spectrum.\n",
    "    \n",
    "    \n",
    "            Useful Keystrokes:\n",
    "    \n",
    "                Mouse Clicks:\n",
    "                \n",
    "                    Left Click  : Select the median flux value within +/- 5 pixel from the x-coordinate.\n",
    "                                  These points are used for the continuum fit.\n",
    "                    Right Click : Delete the nearest continuum point.\n",
    "    \n",
    "                Keystrokes:\n",
    "                  \n",
    "                  b     :    Select a point for continuum fit at that exact (x,y) coordinate.\n",
    "                  enter :    Perform a spline fit to data to create a continuum.\n",
    "                  n     :    Show the normalized spectrum.\n",
    "                  w     :    Only after pressing n: This will ourput the continuum. \n",
    "                  h     :    This Help screen.\n",
    "                  r     :    Reset fit.\n",
    "                  q     :    Quit Program.\n",
    "             ---------------------------------------------------------------------------\n",
    "            Written By:  Rongmon Bordoloi                                   July 13 2017.\n",
    "    \n",
    "\n",
    "\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
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       "\n",
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       "            /* 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",
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       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
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       "        button.appendChild(icon_img);\n",
       "\n",
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       "    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",
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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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b52d4a4335d64c2c8ab51ada3dea9d66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value='')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from GUIs import interactive_cont_jn as ft\n",
    "reload(ft)\n",
    "cont=ft.interactive_cont(s.wave_slice,s.flux_slice,error=s.error_slice)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add the handfitted continuum into the rb_spec object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using prefitted continuum...\n"
     ]
    }
   ],
   "source": [
    "s.fit_continuum(prefit_cont=cont.cont);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Third option for automatic continuum fitting using RANSAC fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing RANSAC continuum fitter\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/bordoloi/opt/anaconda3/envs/zgui/lib/python3.9/site-packages/scipy/signal/_signaltools.py:1545: UserWarning: kernel_size exceeds volume extent: the volume will be zero-padded.\n",
      "  warnings.warn('kernel_size exceeds volume extent: the volume will be '\n",
      "/Users/bordoloi/opt/anaconda3/envs/zgui/lib/python3.9/site-packages/scipy/signal/_signaltools.py:1545: UserWarning: kernel_size exceeds volume extent: the volume will be zero-padded.\n",
      "  warnings.warn('kernel_size exceeds volume extent: the volume will be '\n",
      "/Users/bordoloi/WORK/python/linetools/linetools/spectra/xspectrum1d.py:107: UserWarning: Assuming wavelength unit is Angstroms\n",
      "  warnings.warn(\"Assuming wavelength unit is Angstroms\")\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#s.fit_continuum(mask=[-100,300],domain=xlim,Legendre=3)\n",
    "s.fit_continuum_ransac(window=199,mednorm=False)\n",
    "plt.subplot(2,1,1)\n",
    "plt.step(s.velo,s.flux_slice)\n",
    "plt.step(s.velo,s.flux_slice/s.fnorm)\n",
    "plt.xlim(xlim)\n",
    "plt.subplot(2,1,2)\n",
    "plt.step(s.velo,s.fnorm)\n",
    "plt.plot([-600,600],[1,1],'--')\n",
    "plt.xlim(xlim)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute Equivalent Width and column density for the line profile within a velocity range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W_lambda = 0.418 +/- 0.036  \\AA   over [-200.0 to 305.0]  km/s\n",
      "Direct N = 14.953 +/- 0.040 cm^-2\n"
     ]
    },
    {
     "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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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": [
    "\n",
    "# Setting plot False will hide the plot below\n",
    "s.compute_EW(transition,vmin=-200.,vmax=305.,plot=True);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-11.913295560786768 61.45310172970429\n"
     ]
    }
   ],
   "source": [
    "print(s.vel_centroid,s.vel_disp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save all the information produced above. \n",
    "\n",
    "See rb_spec.py file for details of what is saved.\n",
    "\n",
    "All entries are saved as a python dictionary in a pickle file. The entries for the saved dictionary are:\n",
    "\n",
    "<p>zabs= Absorber redshift</p>\n",
    "<p>wave_slice= sliced observed wavelength vector</p>\n",
    "<p>flux_slice= sliced observed flux vector</p>\n",
    "<p>error_slice= sliced velocity spectra </p>\n",
    "<p>linelist=. LineList used</p>\n",
    "<p>velo=  sliced velocity vector</p>\n",
    "<p>cont = Fitted continuum</p>\n",
    "<p>fnorm= Normalized flux</p>\n",
    "<p>enorm= Normalized error</p>\n",
    "<p>trans=  Name of the Transition</p>\n",
    "<p>fval= fvalue of transition</p>\n",
    "<p>trans_wave= rest frame wavelength of transition</p>\n",
    "<p>vmin=     velocity minimum used for equivalent width calculation</p>\n",
    "<p>vmax=    velocity maximum used for equivalent width calculation</p>\n",
    "<p>W=    Rest Frame equivalenth width</p>\n",
    "<p>W_e=  uncertainty on rest frame equivalent width</p>\n",
    "<p>logN=  AOD column density</p>\n",
    "<p>logN_e= AOD column density uncertainty</p>\n",
    "<p>Tau= Apparant optical depth as a function of velocity</p>\n",
    "<p>vel_centroid= EW weighted velocity centroid</p>\n",
    "<p>vel_disp= 1 sigma velocity dispersion</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Option 1: save as pickle file [default]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.save_slice('outfile.p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Option 2: Save as json file\n",
    "\n",
    "Experimental. DO NOT USE RIGHT NOW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.save_slice('outfile.json',file_format='json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read saved rb_spec object from json file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from GUIs.rb_spec import load_rb_spec_object as r_load\n",
    "f='outfile.json'\n",
    "sp_test=r_load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the loaded spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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": [
    "sp_test.plot_slice()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read saved rb_spec object from pickle file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('outfile.p', 'rb') as f:\n",
    "    sp_test = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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": [
    "#Plot the loaded spe\n",
    "sp_test.plot_slice()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}