CH4-Analysis_Spectrum_Images-CL2.ipynb

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   "source": [
    "## Chapter 4: [Spectroscopy](CH4-Spectroscopy.ipynb)\n",
    "\n",
    "<hr style=\"height:1px;border-top:4px solid #FF8200\" />\n",
    "\n",
    "# Analysis of Spectrum Images - Core-Loss\n",
    "\n",
    "\n",
    "part of \n",
    "\n",
    "## [Analysis of Transmission Electron Microscope Data](_Analysis_of_Transmission_Electron_Microscope_Data.ipynb)\n",
    "\n",
    "\n",
    "\n",
    "by Gerd Duscher, 2019\n",
    "\n",
    "Microscopy Facilities<br>\n",
    "Joint Institute of Advanced Materials<br>\n",
    "The University of Tennessee, Knoxville\n",
    "\n",
    "Model based analysis and quantification of data acquired with transmission electron microscopes\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Content\n",
    "\n",
    "Plotting, Interacting and Quantifying Spectrum Image data\n",
    "\n",
    "Please cite for core-loss quantification:\n",
    "\n",
    "[M. Tian et  al. *Measuring the areal density of nanomaterials by electron energy-loss spectroscopy*\n",
    "Ultramicroscopy Volume 196, 2019, pages 154-160](https://doi.org/10.1016/j.ultramic.2018.10.009)\n",
    "\n",
    "as a reference of this quantification method."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First we import the relevant packages"
   ]
  },
  {
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "windows\n",
      "pyTEM version:  0.10.2019.1\n"
     ]
    }
   ],
   "source": [
    "# import matplotlib and numpy\n",
    "#                       use \"inline\" instead of \"notebook\" for non-interactive plots\n",
    "%pylab --no-import-all notebook\n",
    "%gui qt\n",
    "\n",
    "from scipy.ndimage.filters import gaussian_filter\n",
    "\n",
    "# import pyTEMlib packages\n",
    "import pyTEMlib\n",
    "import pyTEMlib.file_tools  as ft     # File input/ output library\n",
    "import pyTEMlib.EELS_tools  as eels \n",
    "\n",
    "# For archiving reasons it is a good idea to print the version numbers out at this point\n",
    "print('pyTEM version: ',pyTEMlib.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load and plot a spectrum\n",
    "\n",
    "As an example we load the spectrum **1EELS Acquire (high-loss).dm3** from the *example data* folder.\n",
    "\n",
    "Please see [Working with Spectrum Images](CH4-Working_with_Spectrum_Images.ipynb) for details on storage and plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Channel_000 :  3-EELS Spectrum Image\n"
     ]
    },
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       "             * 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",
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       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
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       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
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       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# If a file is open, close it\n",
    "try:\n",
    "    h5_file.close()\n",
    "except:\n",
    "    pass\n",
    "# Load new file\n",
    "h5_file = ft.h5open_file()#os.path.join(current_directory,filename))\n",
    "current_channel = h5_file['Measurement_000/Channel_000']\n",
    "measurement_group = h5_file['Measurement_000']\n",
    "\n",
    "\n",
    "for key in list(measurement_group.keys()):\n",
    "    if 'title' in measurement_group[key].keys(): \n",
    "        print(key,': ',measurement_group[key]['title'][()])\n",
    "    else:\n",
    "        print(key,': ')    \n",
    "        \n",
    "if current_channel['data_type'][()] == 'spectrum_image':\n",
    "    SI_plot= eels.interactive_spectrum_image(current_channel, horizontal = True)\n",
    "    \n",
    "else:\n",
    "    print('NOT what we want here, please select a spectrum image ')\n",
    "    ft.h5_plot(current_channel)\n",
    "   \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add survey image to file\n",
    "If you have not done so before, add the survey image to the dataset (measurement group)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Channel_000 :  3-EELS Spectrum Image\n",
      "Channel_001 :  3SI Survey Image\n"
     ]
    }
   ],
   "source": [
    "SI_channel = ft.h5add_channels(h5_file,current_channel,'survey image')\n",
    "    \n",
    "measurement_group = h5_file[current_channel.name.split('/')[1]]\n",
    "    \n",
    "for key in list(measurement_group.keys()):\n",
    "    if 'title' in measurement_group[key].keys(): \n",
    "        print(key,': ',measurement_group[key]['title'][()])\n",
    "    else:\n",
    "        print(key,': ')   \n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Z-contrast image\n",
    "If you have not done so before, add the survey image to the dataset (measurement group)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Channel_000 :  3-EELS Spectrum Image\n",
      "Channel_001 :  3SI Survey Image\n",
      "Channel_002 :  3Analog\n"
     ]
    }
   ],
   "source": [
    "Z_channel = ft.h5add_channels(h5_file,current_channel,'Z-contrast image')\n",
    "    \n",
    "measurement_group = h5_file[current_channel.name.split('/')[1]]\n",
    "    \n",
    "for key in list(measurement_group.keys()):\n",
    "    if 'title' in measurement_group[key].keys(): \n",
    "        print(key,': ',measurement_group[key]['title'][()])\n",
    "    else:\n",
    "        print(key,': ') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Ronchigram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "original_metadata.root.ImageList.1.ImageTags.DataBar.Exposure Time (s) 0.5\n",
      "(4194304, 1)\n",
      "Counts/seconds:  32939792374.0\n",
      "Channel_000 :  3-EELS Spectrum Image\n",
      "Channel_001 :  3SI Survey Image\n",
      "Channel_002 :  3Analog\n",
      "Channel_003 :  Ronchigram\n"
     ]
    }
   ],
   "source": [
    "Ronchi_channel = ft.h5_add_channels(h5_file,current_channel,'Ronchigram')\n",
    "    \n",
    "measurement_group = h5_file[current_channel.name.split('/')[1]]\n",
    "for key in Ronchi_channel.attrs.keys():\n",
    "    if 'Exposure Time (s)' in key:\n",
    "        print(key, Ronchi_channel.attrs[key])\n",
    "        if 'exposure_time_s' in Ronchi_channel:\n",
    "            Ronchi_channel['exposure_time_s'][()] = Ronchi_channel.attrs[key]\n",
    "        else:\n",
    "            Ronchi_channel['exposure_time_s'] = Ronchi_channel.attrs[key]\n",
    "print(Ronchi_channel['Raw_Data'][()].shape)\n",
    "ronchi = np.array(Ronchi_channel['Raw_Data'][()], dtype= float)\n",
    "print ('Counts/seconds: ', ronchi.sum()/Ronchi_channel['exposure_time_s'])\n",
    "if 'counts_per_s' in Ronchi_channel:\n",
    "    Ronchi_channel['counts_per_s'][()] = ronchi.sum()/Ronchi_channel['exposure_time_s']\n",
    "else:\n",
    "    Ronchi_channel['counts_per_s'] = ronchi.sum()/Ronchi_channel['exposure_time_s']\n",
    "    \n",
    "if 'incident_current_counts_per_s' in current_channel:\n",
    "    current_channel['incident_current_counts_per_s'][()] = Ronchi_channel['counts_per_s']\n",
    "else:\n",
    "    current_channel['incident_current_counts_per_s'] = Ronchi_channel['counts_per_s']\n",
    "Ronchi_channel['file_name']= Ronchi_channel['title'][()] \n",
    "Ronchi_channel['title'][()] = 'Ronchigram'      \n",
    "\n",
    "for key in list(measurement_group.keys()):\n",
    "    if 'title' in measurement_group[key].keys(): \n",
    "        print(key,': ',measurement_group[key]['title'][()])\n",
    "    else:\n",
    "        print(key,': ') \n",
    "        \n",
    "      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [],
   "source": [
    "del h5_file['Measurement_000/Channel_003']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Survey Image to plot above\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "SI_plot.set_Survey_image(h5_file['Measurement_000']['Channel_001'])\n",
    "SI_plot.overlay_data() \n",
    "\n",
    "## set view port \n",
    "#SI_plot.ax1.set_xlim(0,90)\n",
    "#SI_plot.ax1.set_ylim(60,20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overlay Z-contrast image on survey image at plot above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "SI_plot.set_Survey_image(h5_file['Measurement_000']['Channel_001'])\n",
    "SI_plot.overlay_Zcontrast_image(h5_file['Measurement_000']['Channel_002'])\n",
    "\n",
    "\n",
    "## set view port \n",
    "#SI_plot.ax1.set_xlim(0,90)\n",
    "#SI_plot.ax1.set_ylim(60,20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "SI_plot.set_Zcontrast_image(h5_file['Measurement_000']['Channel_002'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['spectrum', 'energy_scale', 'intensity_scale', 'edges', 'do_All', 'intentsity_scale'])\n"
     ]
    }
   ],
   "source": [
    "print(tags['spectra']['0-0'].keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare Quantification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7cca8c879b3c48af857e60c11ca0a663",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Box(children=(ToggleButton(value=False, description='fix_energy'), ToggleButton(value=False, description='fit_…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if 'incident_current_counts_per_s' in current_channel:\n",
    "    SI_plot.tags['intentsity_scale_ppm'] =  1./(current_channel['incident_current_counts_per_s'][()]*SI_plot.tags['exposure_spectrum']) *1e6\n",
    "for key in SI_plot.tags['spectra']:\n",
    "    SI_plot.tags['spectra'][key]['intensity_scale']= SI_plot.tags['intentsity_scale_ppm'] \n",
    "    \n",
    "tags = SI_plot.tags.copy()\n",
    "SI_plot2= eels.interactive_spectrum_image(tags, horizontal = False)\n",
    "\n",
    "# Set edges to be fitted\n",
    "edges_present = ['B-K','C-K', 'N-K1']\n",
    "SI_plot2.tags['edges_present'] = edges_present\n",
    "\n",
    "## ACTIVATE THE FITTING\n",
    "#SI_plot.analysis= 'fit_quantification'\n",
    "#SI_plot2.set_legend(False)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Activate the regions selection tool."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [],
   "source": [
    "## define the fitting regions\n",
    "edges = eels.make_edges(edges_present, tags['energy_scale'], tags['acceleration_voltage'], tags['collection_angle'])\n",
    "\n",
    "regions = eels.Region_Selector(SI_plot2.ax2)\n",
    "for key in edges:\n",
    "    regions.set_regions(str(key),edges[key]['onset']-edges[key]['start_exclude'], edges[key]['start_exclude']+edges[key]['end_exclude'])                               \n",
    "regions.set_regions('fit region',tags['energy_scale'][100], tags['energy_scale'][-1]-tags['energy_scale'][100])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## After adjusting the regions, remove the selector and make legend visible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "SI_plot2.set_legend(True)\n",
    "region_tags = regions.get_regions()\n",
    "SI_plot2.tags['region_tags'] = region_tags\n",
    "tags2 = SI_plot2.tags.copy()\n",
    "try:\n",
    "    regions.disconnect()\n",
    "    del regions\n",
    "except:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## You can  adjust the previous selections "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    region_tags = regions.get_regions()\n",
    "    regions.disconnect()\n",
    "    del regions\n",
    "except:\n",
    "    pass\n",
    "\n",
    "regions = eels.Region_Selector(SI_plot2.ax2)\n",
    "print(region_tags['1'].keys())\n",
    "for key in region_tags:\n",
    "    regions.set_regions(str(key),region_tags[key]['start_x'], region_tags[key]['width_x'])                               \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result of the selected spectrum can be seen here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "spectrum  7 10\n",
      "B : 90.9 atoms = 5.0 monolayer\n",
      "C : 0.0 atoms = 0.0 monolayer\n",
      "N : 0.9 atoms = 0.1 monolayer\n"
     ]
    }
   ],
   "source": [
    "x = SI_plot2.x\n",
    "y = SI_plot2.y\n",
    "\n",
    "print('spectrum ', x,y)\n",
    "if 'edges' not in SI_plot2.tags['spectra'][f'{x}-{y}']:\n",
    "    SI_plot2.fit_quatification()\n",
    "spectrum_dictionary = SI_plot2.tags['spectra'][f'{x}-{y}']['edges']\n",
    "for key in  spectrum_dictionary: \n",
    "    if key.isdigit():  # only edges have numbers in that dictionary\n",
    "        \n",
    "        element = SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['element']\n",
    "        areal_density = SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['areal_density']\n",
    "        areal_density = areal_density * SI_plot2.tags['spectra'][f'{x}-{y}']['intensity_scale']/1e2\n",
    "        monolayer = 18.2\n",
    "        print(f'{element:2}: {areal_density:.1f} atoms = {areal_density/monolayer:.1f} monolayer')\n",
    "       "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Whole Spectrum Image Analysis\n",
    "\n",
    "Now we do the all the spectra, with the same setting as selected above. \n",
    "Set the verbose variable to **True** to see the progress."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "SI_plot2.do_All(verbose = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the results:\n",
    "\n",
    "The results are in the individual spectrum dictionary: \n",
    "\n",
    "*SI_plot2.tags['spectra'][f'{x}-{y}']*\n",
    "\n",
    "The compositional results are in the edge dictionary. Each edge has its own sub-dictionary. The areal_density is the result of the compositional fit. \n",
    "\n",
    "So we collect the areal densities of the different edges in numpy arrays.\n",
    "\n",
    "The arrays are stored in a dictionary *results_dictionary* and then we plot those arrays.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_dictionary = {}\n",
    "\n",
    "# we are only after the edges so it does not matter which spectrum we use\n",
    "for key in  SI_plot2.tags['spectra']['0-0']['edges']: \n",
    "    \n",
    "    if key.isdigit():  # only edges have numbers in that dictionary\n",
    "        x = y = 0\n",
    "        results_dictionary[key] = {} # make new dictionary\n",
    "        # store the additional data like element and what edge\n",
    "        results_dictionary[key]['element'] =SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['element']\n",
    "        results_dictionary[key]['Z'] =SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['Z']\n",
    "        results_dictionary[key]['onset'] =SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['onset']\n",
    "        results_dictionary[key]['symmetry'] =SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['symmetry']\n",
    "        \n",
    "        # intitalize data array\n",
    "        results_dictionary[key]['data'] = np.empty(SI_plot.tags['cube'].shape[0:2])\n",
    "        # go through all spectra and fill data array pixel.\n",
    "        for x in range(results_dictionary[key]['data'].shape[1]):\n",
    "            for y in range(results_dictionary[key]['data'].shape[0]):\n",
    "                \n",
    "                results_dictionary[key]['data'][y,x] = SI_plot2.tags['spectra'][f'{x}-{y}']['edges'][key]['areal_density']\n",
    "\n",
    "## plot\n",
    "ax = []; im= [];color_bar = []\n",
    "fig = plt.figure()\n",
    "titles = ['Ti [counts]', 'V [counts]', 'O [counts]', 'O/(Ti+V)  [rel.]',]\n",
    "for key in results_dictionary:        \n",
    "    ax.append(plt.subplot(2, 2, int(key)))\n",
    "    im.append(ax[-1].imshow(results_dictionary[key]['data'], origin= 'upper'));\n",
    "    color_bar.append(fig.colorbar(im[-1], ax=ax[-1]))\n",
    "    color_bar[-1].set_label(results_dictionary[key]['element']+' [counts]')\n",
    "#im[3].set_clim(vmax=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## With scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['Z', 'symmetry', 'element', 'chemcial_shift', 'original_onset', 'onset', 'start_exclude', 'end_exclude', 'data', 'areal_density'])\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scale =  SI_plot2.tags['spectra'][f'{x}-{y}']['intensity_scale']/1e2 /monolayer\n",
    "\n",
    "print(SI_plot2.tags['spectra'][f'{x}-{y}']['edges']['1'].keys())\n",
    "## plot\n",
    "ax = []; im= [];color_bar = []\n",
    "fig = plt.figure()\n",
    "titles = ['Ti [counts]', 'V [counts]', 'O [counts]', 'O/(Ti+V)  [rel.]',]\n",
    "for key in results_dictionary:        \n",
    "    ax.append(plt.subplot(2, 2, int(key)))\n",
    "    im.append(ax[-1].imshow(results_dictionary[key]['data']*scale, origin= 'upper'));\n",
    "    color_bar.append(fig.colorbar(im[-1], ax=ax[-1]))\n",
    "    color_bar[-1].set_label(results_dictionary[key]['element']+' [counts]')\n",
    "#im[0].set_clim(vmax=3)    \n",
    "#im[2].set_clim(vmax=3)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dictionary for Log of Fitting Results: Needs to be finished"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "out_tags = {}\n",
    "for key1 in edges:\n",
    "    if key1.isdigit():\n",
    "        for key2 in edges[key1]:\n",
    "            if key2 == 'data':\n",
    "                out_tags[f\"edge_{key1}_Xsection\"] = edges[key1][key2]\n",
    "            else:\n",
    "                out_tags[f\"edge_{key1}_{key2}\"] = edges[key1][key2]\n",
    "    else:\n",
    "        print(key1)\n",
    "        for key2 in edges[key1]:\n",
    "            out_tags[f\"{key1}_{key2}\"] = edges[key1][key2]\n",
    "\n",
    "out_tags['monolayer']= 18.2 #atoms/nm^2\n",
    "out_tags['X_section_unit'] = 'atoms/nm$^2$'\n",
    "\n",
    "for key in results_dictionary:\n",
    "    name = results_dictionary[key]['element']+'_'+results_dictionary[key]['symmetry']\n",
    "    out_tags[name+'_areal_density'] = results_dictionary[key]['data']\n",
    "    out_tags[name+'_onset'] = results_dictionary[key]['onset']\n",
    "\n",
    "    \n",
    "for key in  SI_plot2.tags:\n",
    "    if isinstance(SI_plot2.tags[key],dict):\n",
    "        if key == 'spectra':\n",
    "            name = 'spectrum'\n",
    "            for key1 in SI_plot2.tags[key]:\n",
    "                name1= name+'_'+key1\n",
    "                for key2 in SI_plot2.tags[key][key1]:\n",
    "                    \n",
    "                    name2 = name1+'_'+key2\n",
    "                    if key2 in ['edges']:\n",
    "                        \n",
    "                        for key3 in SI_plot2.tags[key][key1][key2]:\n",
    "                            for key4 in SI_plot2.tags[key][key1][key2][key3]:\n",
    "                                name3 = name2+'_'+key3+'_'+key4\n",
    "                                out_tags[name3]= SI_plot2.tags[key][key1][key2][key3][key4]\n",
    "                        \n",
    "                        \n",
    "                        \n",
    "                    else:\n",
    "                        out_tags[name2] = SI_plot2.tags[key][key1][key2]\n",
    "        \n",
    "        elif key =='region_':\n",
    "                print('region')\n",
    "        else:\n",
    "            for key1 in SI_plot2.tags[key]:\n",
    "                #print(key1)\n",
    "                if isinstance(SI_plot2.tags[key][key1],dict):\n",
    "                    #print('dict', key, key1, SI_plot2.tags[key][key1])\n",
    "                    for key2 in SI_plot2.tags[key][key1]:\n",
    "                        out_tags[key+'_'+key1+'_'+key2] = SI_plot2.tags[key][key1][key2]\n",
    "                else:\n",
    "                    print(' - ', key, key1, SI_plot2.tags[key][key1])\n",
    "    else:\n",
    "        #\n",
    "        if key not in ['timestamp', 'title']:\n",
    "            #out_tags[key]=SI_plot2.tags[key]\n",
    "            #print(key)\n",
    "            pass\n",
    "        if 'edges_present' in SI_plot2.tags:\n",
    "            #out_tags['edges_present']=SI_plot2.tags['edges_present']\n",
    "            pass\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Log Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<HDF5 group \"/Measurement_000/Channel_000/Log_000\" (3 members)>\n"
     ]
    }
   ],
   "source": [
    "log_group = ft.h5_add_Log(current_channel, name='Xsection_fit')\n",
    "print (log_group)\n",
    "ft.h5_add_Data2Log(log_group,  out_tags)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "for key in  out_tags:\n",
    "    if isinstance(out_tags[key],dict):\n",
    "        print(key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check on File Content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "title\n"
     ]
    }
   ],
   "source": [
    "import pyUSID as usid \n",
    "#usid.hdf_utils.print_tree(h5_file)\n",
    "for key in dict(current_channel['Log_004']).keys():\n",
    "    if key in SI_plot2.tags:\n",
    "        print(key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Close File\n",
    "File needs to be closed to be used with other notebooks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [],
   "source": [
    "h5_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Back: [Calculating Dielectric Function II: Silicon](DielectricDFT2.ipynb)\n",
    "## Next:  [ELNES](ELNES.ipynb)\n",
    "\n",
    "## Chapter 4: [Spectroscopy](Spectroscopy.ipynb)\n",
    "## Index: [Index](Analysis_of_Transmission_Electron_Microscope_Data.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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