CH4-Detector.ipynb

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    "## Chapter 4 [Spectroscopy](Ch4-Spectroscopy.ipynb)\n",
    "\n",
    "\n",
    "<hr style=\"height:1px;border-top:4px solid #FF8200\" />\n",
    "\n",
    "# EDS Detector Efficiency \n",
    "\n",
    "\n",
    "part of \n",
    "\n",
    "## [Analysis of Scanning Electron Microscope Data](_Analysis_of_Scanning_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 scanning electron microscopes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First we import the essential libraries\n",
    "All we need here should come with the annaconda or any other package"
   ]
  },
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     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "#import matplotlib and numpy with a magic comand\n",
    "%pylab --no-import-all notebook\n",
    "\n",
    "import pickle ## to read photoabsorption data"
   ]
  },
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   "source": [
    "## Bremsstrahlung and EDS Background\n",
    "\n",
    "At low energies,  the [Bremsstrahlung](Ch4-Bremsstrahlung.ipynb) above does not look anything like the background we obtain in the EDS spectrum.\n",
    "\n",
    "This is due to the  response of the EDS detector system\n",
    "\n",
    "![X-Ray_Auger](./images_SEM/DetectorEfficiency.png).\n"
   ]
  },
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    "## Detector Response\n",
    "\n",
    "The detector response depends on the material. The detected X-ray photons need to be absorbed in the Si detector. This absorption is then dependent on the silicon aborption coefficients (per energy).\n",
    "Everything that absorbs X-ray photons before it reaches the detector crystal will weken the signal according to the photoabsorption in that material layers. Obviously we want to keep the thicknesses of those layers as thin as possible.\n",
    "\n",
    "Let's look at the design of a detector:\n",
    "\n",
    "![detector overview](images_SEM/Bruker3b.jpg)\n",
    "\n",
    "![detector details](images_SEM/Bruker.jpg)\n",
    "\n",
    "For the detector there is actually only one type common anymore (the liquid notrogen cooled Si(Li) detectors are phased out) and that is the Silicon droft detector (SDD):\n",
    "\n",
    "![detector crystal](images_SEM/SDD2.jpg)\n",
    "\n",
    "In front of the detector is usually a window. Only high vacuum system can have a window-less system otherwise ice would build up on the Peltier-cooled detector crystal.\n",
    "This window is rather fragile and relative expensive to replace so be carfull with handling the detector system on that end.\n",
    "\n",
    "\n",
    "![detector window](images_SEM/Window2.jpg)"
   ]
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    "## Signal - Photoelectric absorption of X-ray photon.\n",
    "\n",
    "Whole energy of X-ray photon is transferred to inner shell electron of a silicon atom.\n",
    "\n",
    "This ejected electron has now the kinetic energy of the X-ray photon minus its binding energy in the atom (K: 1838 eV, L: 98 eV)\n",
    "\n",
    "The ejected electron undergoes inelastic scattering and creates electron hole pairs (valence to conduction band) in the process (besides other effects)\n",
    "\n",
    "Charge generation process requires about 3.6 eV per electron hole pair\n",
    "\n",
    "So the number of created charge carriers $𝑛$ is proportional to the original photon energy $𝐸_𝑝$:\n",
    "\n",
    "$$ n =  \\frac{E_p} {3.6 eV} $$\n",
    "\n",
    "    \n",
    "    "
   ]
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    "## Detector Efficiency\n",
    "### Photoabsorption \n",
    "If we only look at the crystal we see that we have a contact and the Silicon crystal. However there is also a thin deadlayer on the top of the crystal that will absorb X-rays without detecting it.\n",
    "We will talk more about detectors in the [EDS resolution section]()\n",
    "\n",
    "Detection and wekening of the signal through absorption are both governed by photoabsorption cross section.\n",
    "\n",
    "The mass absorption coefficiencts  $ \\mu/ \\rho$ (a function of energy) are taken from the [Mass Absorption Coefficients from NIST](https://physics.nist.gov/PhysRefData/FFast/html/form.html)\n",
    "\n",
    "Select the element and as *Type of Data* select **Mass Photoabsorption Coefficient (cm^2/g)**\n",
    "\n",
    "I collected all the data in a pickled dictionary which we open below and then test the content.\n"
   ]
  },
  {
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     "text": [
      "Edges of Si:\n",
      "K  : 1.839 keV\n",
      "L-1: 0.149 keV\n",
      "L-2: 0.099 keV\n",
      "L-3: 0.099 keV\n",
      "M-1: 0.011 keV\n",
      "M-2: 0.005 keV\n"
     ]
    },
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       "            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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wV28eHHZtGmTR2/Ddvy8Do6nTJmiqq1Ro4bLs7BSU1Nl1qxZMmLECIfbY2NjVeM98sgjcvToUU1denq69O/fX1Xbpk0bpz/TtA+Ocz4IDRs2zOFPeU+fPi0PPfSQUh8SEiJXrlxxul/uMhMc7927V7O/9mwDyZx9LFu2rLI0h70lS5aofpKtFxrZBpwWi0W6devmMBw8f/68tGjRQlX72WefOR03N2scjxw5UhMKnj9/XlOXmpqq+VLi3//+t8uxGzZsKGPGjJGzZ886rcnKypJJkyapjuMrr7ziclxH91NwcLDT5298fLwqqKhcubLTJVoqV66s1D311FO6P6n/+eef5c0333S63VvH19HZe0FBQTJ16lRD6247ej43a9bM4dzOnz+vWZJm5syZTsfOzRrHRoPjxMRE1WOmYsWKsnv3bk1ddna2TJw4UTX3OnXqyJ07d5yO7ejY/Pvf/3Z4JuLVq1elUaNGqj4HDx50a5+dsQ8BV61a5ZFxHXF0tni7du0MnUHtrfvCk89F29CzZs2aul/oHjx4UN566y25ceOGyzqjrl27pgprg4ODZenSpR4ZO8eqVatUx7Zhw4byxx9/OKzdu3evaumG2rVru3xO2H4xlROQ/v77707rL1++LOPHj5cZM2Y43G52jWN3/r7Kq/fbAgUKSJEiRZxeg2Pz5s3KF3MWy98XeQaAvEZwDAAIaI0bN9Z8oG3VqpVER0fL4cOHc31BKdtx8zI4vnjxourDRJUqVRyGNkalp6erzn4rX768nDt3zmUf+yUtnJ0JYx8cWyyOLy5n64cfflDVz58/3/S+2TMTHH/wwQeqPsOGDdPU2F9ALzg42GEAYuu1115T6kNCQpz+zNX+4kitWrVyeVZTamqq1K5dW6kPDQ11GpyYDY4vXryoWp6gTp06LoOSjIwMzfIYSUlJTutdBRH2Ro0apYxZqFAhl4GV/f1ksVhk+vTpLse3Xy/d0a8XkpOTVTUHDhwwPH9HvHl8HQXHY8eONTw3+74PPfSQy7Mrr127JlWrVlXqS5cu7fT+zYvguGHDhkpd4cKFdcPaYcOGqfZ31qxZTmvtj03Xrl1djn3kyBFVKOjotcWMp59+WjUPV78KyS374LhevXqGn7/euC88+VxMT09X3T/ffvut6bFy46WXXtI8th5//HGZMmWKHDhwIFcXrL1z547q/b9WrVq6vwjZv3+/6vVpwYIFDusOHDigmnOjRo1yfe0CbwfHefl+a7HoLz1i+/5msVh0lwcDAE8jOAYABLS9e/cqSzQ4aqVKlZK2bdvKsGHDZN26dW6fIWQ7Vl4Gx59++qmqLrdnUickJKjGmzdvnm6fS5cuqZaV6Nixo8M6++A4LCxMbt++rTt+tWrVlD59+/Z1e5+ccTc4Xrt2reqMU4vFInv37tXU2QeSRn5OvG3bNlWf7du3O6x75513lJoCBQoYupL7+vXrVWNHREQ4rDMbHNuf/edqCYccv//+u+qnt576+fytW7ekePHiyrgJCQlOa+3vp7p16+qGLllZWaqfyj/88MOamp07d6rGNfIYd8Wbx9f+daZChQpuXcjL/nXU1fHOYb9O6+eff+6wztvB8c8//6yax9ChQ3XHvXv3rmpsR2uc57AdOzg42OUZ8zls17Bu27atbr0Rtj+zL1CgQK6/JHXFPjheu3atoX7eui88+Vw8d+6caiwjr73ecOrUKSlXrpzTv2WKFSsmzZs3l8GDB8vq1avlr7/+Mjy2/bJezt6H7Nn+8ugf//iHw5rXX39d9XzwxPHzdnCcl++3//znP3XHPnPmjKqPp882BwA9BMcAgIC3bds2l1fEtm2hoaHSvXt32bVrl6GxbfvmZXBsG2I1aNDA0Fxdsf1ZZvHixQ1fRKl3795Kv0KFCsndu3c1NfbBsdH1GW3PaG7atKlb++OKXnBstVrl+vXrsn37dnnnnXc0awx269bN4bj2gaSRx9CdO3dU48fExDisq1ixolLTunVrw/tqG763aNHCYY3Z4Nh2+YFq1aoZ7te6dWulX+XKlQ330/PMM88o4w4ePNhpnf39FBUVZWj8yZMnq/odPnxYtf3XX39Vbf/xxx9ztT/ePL72rzOujpcjtn1Lly4tGRkZun0yMjJU6xe//PLLDuu8HRzbLv8RFBRk+Exc+4ujnThxwmGdu6GQiMjw4cOVPhUqVDDUR4/tsS5VqpRHxnTG9riXK1fO8Nmv3rovPPlcvHbtmmqsuLg402Pl1m+//aY6s9VVK1iwoHTq1MnQF062X1w0atTI8Hx2796tuk37JaWysrJUXy4/99xzbu+zI94OjvPy/XbFihWGxn7wwQeVPs6WGwMAbyE4BgDcE9LS0iQ8PFz1c2m91qdPH92f29rW51Vw/Ndff6nWhHS1np5RDz/8sDJep06dDPf78ssvVfP9+eefNTX2wbGr42RryJAhSp969eoZnpMe++DYnfb44487PSvdNvAqVKiQoTBNRKRs2bJKv8mTJ2u225/xFhkZaXhfbc8IK1q0qMNAx0xwnJmZqTqT/7333jM8p6ioKNXt5WaJFVu9evXSDSVFtMGxq+UybNn/5Nr+rK87d+6olo+pVKmS0/Wt9Xj7+Nq/zri7/q1t3xdeeMFwv+eff17pV716dYc13g6O27Vrp9TUrVvX8Nj265w7O8vatsZoqGV7IbdixYoZnpMrtr+SqFixokfGdMb2uHfu3NlwP2/dF558LoqI6u+GkiVLyurVq716Brcr6enpMmfOHM3FAl21f/3rX3L16lWH42VmZkqxYsWUWvsLYbqSkZGhXOjWYrHI+vXrVdv37dunmseiRYtyte85vBkc5/X7rd562Tls10J///33Dc8JADyB4BgAcE+xWq3yyy+/yMSJE6VLly6qM0sctdatW7tc285oIOrJ4Hj79u2qmu+//96NI6CVnZ2tOuvVyM+Fcxw9elQ1l8WLF2tq7INj+w+XztgGSFWrVjU8Jz1mguOiRYvKkCFDXH6RYDvf+++/3/B8bD8EO/oSwP4xYeQMshwLFixQ9T19+rSmxkxwbH+fGlnaJMemTZtUfbdu3eqy/vTp0xIRESHPPfec1KhRQ0qVKqVac9RRc3Wmp+39VLBgQcNLNNivdTpy5EhNje1PnHNa7dq15T//+Y+sXbtWrl+/bui2vH187R9T//vf/wyPL6J+3Rs1apThfvZrdTp6bfV2cGxb06NHD8Nj2/86YMyYMQ7rbPcvOjra0Ni5uUClM7ZnHJcuXdojYzpje0wHDhxoqp+n7wtPPRdFtMvGWCx/n83fv39/+eqrr+TSpUuGx/KkpKQkmTZtmrz00ktSrVo11RfK9q1evXoOv/Q8fPiwqs7ZRdqcuf/++5W+9r+YWbp0qWrs3377LVf7m8ObwXFev98aXQvcdv16vQvLAoCnERwDAO55Fy9elJUrV0q3bt00a9laLK4vGmVbl1fB8TfffKOqcbTerjuuXr2qGm/q1KmG+16/fl3V19FFxuxDMKNnfuUmQHLFPjiuXr26qtWoUUMaNmworVq1kn79+kl8fLyhkMHsfPU+BK9evdp0yGf/WNm/f7+mxkxo9b///U/VZ/Xq1YbnZH/hoW+++cZh3Y0bN6Rfv36apUKMtFatWjm9fdv7qUyZMobnLSISFham9HV01teNGzekSZMmTudVoEABadKkiYwfP17OnDnj9Ha8fXztX2eOHTtmeHwR9eueqwvF2Zs5c6aqr6MLSHk7OL7vvvuUGndCThGRUqVKKX0HDRrksMboe4ItbwTHtmscFyxYMM/WOHbnZ/TevC889VwU+fus3C5dujgdKygoSOrXry9Dhw7VLGFj66uvvtK83zhqX331lVvHIse1a9dkzZo10rt3b4fXdujTp4+mz44dO9x+fXXW7M/Otb+oqDvrLrvizeDYH99vRdTB8RtvvGG4HwB4AsExAAA2Dh8+LI8++qjqD/uSJUs6PSvEaEjgyeDY/iyeP/74w829VDt79qxqPHfObszMzFT1HT9+vKbG34NjT/FWcJyb+3vz5s2qvjt27NDUmPkga3/WuztnZR07dkzV19FF0m7evClPPvmkw3CiYMGCUr58ealcubIqbLFdS9PVc8z2fnL3J/y2v1Bw9uH9zp07Mn78eNUSJI5aoUKFZODAgQ5fW7x9fI2u9emMbd/Y2FjD/WJjY3Vv19vBse1Z4+78ukJEpEKFCkrfN99802GN0fcEW94Ijp9++mnVmHrhaG6YDfK8fV944rmYIzs7W+bMmSOVKlVyOVZQUJD07NnT4dIQ9vezs2b0cePKuXPnpFWrVprXTvvHwffff29oTkaa/S9mxo0bp9ru6BoIZngzOPbH91sRgmMAvkVwDACAnQsXLqjOZrJYLJKYmOiw1uiHPX8+49j+4j/32hnHnuKt4Pjrr79WzdcfzoCyv/iUp8+I/fjjj1U1DRo0kNjYWDl+/LjTC2+9/vrrhp5j3jzj2FZ6erqsXbtWPvzwQ2nUqJHT5TVatGihWS7D28fXk8FxfjvjuGTJkkpNIJ9xPGjQINWYZs9iNcJskOft+yJHbp6L9rKzs2XLli0yfPhwadasmYSEhDgcq3bt2nLt2jVV37wMjkVEbt26JTVq1FCNbf9Fz48//qjabv+FnDttxowZqrHz4xnH/vh+K0JwDMC3CI4BAHDA9iInFotFZs+e7bDO6Ie9QF3j2P7sRiNrHBMcq+l9CP7vf/+rmq87Z5/GxMSo+npqjeNTp06p+rhzlrr9WVn2a/Cmp6erzh5+5plnDK1D/Oyzzxp6jtmvcWz0IoZG1jh2JTU1VVavXi3du3fXLIlj/4WLN4+viGeD4/y2xrHthc7cWVf37t27bq9x7Mvg+KuvvlKN6c0LapkN8rx9XzjjznNRz+3bt2XDhg3Sp08fzfIQeoF2XrC/WOaQIUNU25OSklTbt23b5rHbzo9rHPvj+60IwTEA3yI4BgDAgejoaNUf9xMmTHBY54vg+MqVK6qL4Di6oJq7Hn74YWW8Tp06Ge5nH078/PPPmhqCY9f0PgTn5irvAwYMUPoVK1bM0FXejcjMzJSiRYsqfd577z3Dc5oyZYrq9s6fP6/abr/m5q5duwyNW79+fbeDY4vFIklJSYbGP3DggKrf0qVLDfVzZM+eParj16RJE9V2bx5fEc8Gxy+88ILhfs8//7zSr3r16g5rvB0ct2vXTqmpW7eu4bH37dun2u+EhASHdf4SHF+7dk31GCpVqpTcvn3bI2PbMxvkefu+MELvueiO5ORk1cXi3LlIqresX79edazeeust1fabN29KoUKFlO3ufEmlx36t9kWLFnlkXG8Gx/74fitCcAzAtwiOAQBwYNq0aao/7qOjox3W+SI4FhGpV6+eUtOwYUM39syxV199VRmvePHihgOGPn36KP1CQkIcrmFIcOyakQ/BtmvrtmnTxvDYthfIatGihcOazz//XHU8srOzDY3drFkz3RDQkTZt2ij9KleurNm+cuVK1XyMXHX+0qVLqjMQ3QmOo6KiDM178uTJqn65XVvcdimBEiVKaLZ76/iKeDY4DgsLM3TWdkZGhpQuXVrp5+wM0/Hjxys1lSpVcmteRp5LI0eOVGqCgoIcnhXoyNixY1X7feLECYd1/hIci4i8//77qnEjIiI8NrYts0Get+8Lo/Sei+6wX57hypUruRovt+yXXvjkk080NbbrYXfu3Nljt52dna26AGLXrl09Mq7t8hvu/OLB6OueN99vCY4B5EcExwAAOPDSSy+p/rjfvHmzwzpfBcdjxoxR1W3atMmNvdP64osvVOPFxMTo9rl8+bLqQ6GzM5UJjl0zErq8++67Sk2BAgUMhZYbN25U7aezM6fs12V0dFEnRyIiIgw9R2wdPnxYFfA6OpPW/rFov06oI5999pmqjzvBcb169XTD8uzsbNWXNTVr1tSdk565c+cq4xUpUkSz3VvHV8SzwbHFYpEvvvhCt8+KFStUfZYtW+awzjZ4u++++9yal2k3qJEAACAASURBVJHn0i+//KKax4gRI3THvXv3rjz00EOqx4wz/hQcnzhxQrUGb2hoqOEz7O3dvXtXFi5c6HCb2eDY2/eFUXrPRXesW7dOtU8XL17M9fxyY8iQIbrv7bbPuQIFCph+jDjSu3dvZezg4GA5dOhQrsds2LChMqY7a2Mbfd3z5vstwTGA/IjgGAAQsL755huZNm2aoTMWbf3000+qtUxLlCjh9GrgvgqOL126pFpPsWrVqnLhwgU39lItIyND9RPbBx54QHe81157TTVXZ2stExy7ZiR0sV8moW3btk4vEicikpaWJnXq1FEFRs4uTGR/MTWja1xeunRJFUrVq1dPbt686bQ+MzNTWrdurbqtgwcPaup+/vlnVc3nn3/uch5JSUlSuHBh08GxxaJ/gTf7i7pNmjRJU3P+/HmnrxOO9OvXTxmvdu3amu3eOr4ing+Oq1WrJtevX3daf/36dalWrZpSX7p0aaevy/ZfZJw5c8bwvIwGmI899pgqKNQLs2zPjLVYnK95L+JfwbGI9rFbvnx5ty74JSJy/PhxadKkidPnldngWMQ794Unn4tXrlyRGzduGB5r0qRJylhFixY1/AsOV3bt2iWjR492+RxzJDk5WbVefFBQkPz555+aulu3bkm5cuWUukceecTt23L2fE5KSlItrdWoUSNJS0tza2x7Xbt2VcZz54xgo6973ny/JTgGkB8RHAMAAlbOhUoeeOABGT58uO5ZI1arVZYvX6660rvF4vqnkL4KjkW0y2k8/PDDDtcYzpGWliZz5851elGvhQsXqsZr2LChJCcna+rS09Plgw8+UNW2adNGrFarw3EJjl0zGrrYB/U9e/Z0+AH8woUL0qpVK1Wtq4tHZWRkqMKF1q1bG/4Swv5iZ23btnV4ht2NGzeke/fuqtrevXs7HDMzM1O1pMH999/v9KJKP/zwgxJ4mFmqIqdPcHCwLFmyxGH9kiVLVBfQqly5ssMANz4+Xh588EGZOHGi7k/uV61apRrT0c/HRbxzfEU8GxznHMMWLVo4fNxcuHBBWrRooeozc+ZMp2OnpKSo7ssePXoYDrGMPpcSExNVYVaVKlUchqlWq1Vz5nedOnVcfhnpb8GxiMjLL7+sGr9IkSIyfPhw3eN68uRJ6d+/v7IGrjeCY2/cF558Lm7ZskVKly4tw4cPl8OHD7sca9u2bapf4bz88ssGjoC+nAtelipVSgYOHCj79u3T7bNx40apUKGC6ni99tprTutXrVqlqq1Vq5bs2LHD5W1kZWXJ1q1b5fXXX5dnn33WaZ393wtNmjRx+QXBlStXZOLEiU5fJ2zD+QIFCsiKFSuc/v1hy53XPW+93xIcA8iPCI4BAAHL/grXFsvfa4W++uqrMn78eJk3b57Ex8fLtGnT5O2331Z9+M1pTz75pMv1fo2GBN4IjkVEExYFBQVJs2bNZPTo0bJgwQJZsGCBjB07Vp577jkpVqyY7oeOF198URMw9OrVS2bMmCELFiyQTz75RKpWraqqKV++vJw6dcrpmATHrhkNXa5du6ZaQ9Fi+ftLkQ8++EDmzZsnc+bMkbfeekvzxUfTpk0lMzPT5Rzee+89TRj40EMPyaOPPioNGjSQBg0aSMeOHTX9MjIy5Mknn1T1LVWqlLz99tsye/ZsmTdvngwcOFB1NrvF8vdSD65CK9t1bi2Wv8/g6tmzp8yaNUvi4uJk/PjxqjDy0UcflW7duhl6jtnfT7YBwVNPPSXh4eGycOFCCQ8Pl6eeeko1j4IFC8qGDRscjmsbCAQFBcljjz0m/fr1kylTpkhcXJzExMTIyJEj5YknntA8f5ydneat4+vJ4Pijjz5Sfv1QqlQpeeedd2Tu3Lkyd+5ceeedd6RUqVKq+pYtW+qehdmpUydVn+DgYKlRo4byWGzQoIH07dtX08+dAPOjjz7S3EbXrl1l6tSpEhsbK59++qlqeRKL5e8LXu3Zs8fwsfGX4DgzM1N1Vm1OCwkJkTZt2siIESNkxowZEhcXJxEREfLBBx/Io48+qqn3RnAs4vn7wpPPRfvnSp06daR3794SGRkpsbGxEhsbK2PHjpU2bdqoAvAiRYrI0aNH3T4WjuQEx7atYsWK0q1bNxkzZozMmTNHFi1aJDNnzpT+/furzn7NaQ8//LDushn2X1RZLBb5xz/+IR999JHMnj1b4uPjZdasWTJy5Ejp0qWLlC1bVqnr0KGD03HT09NVa7bn3Mft27eX8ePHS2xsrMybN09GjRolHTp0UH5p4eyxdPbsWQkNDVWNV7JkSalXr57qNeLbb79V9XPndc9b77cExwDyI4JjAEDAWrZsmeZDkDuta9eukpqa6vI2jIYE3gqOs7KyNBdA0muuPnRkZGTIK6+8YnisypUr657JTXDsmjuhS0pKitSvX9/w/fPMM88Y+lnw9evX5fHHH3c5lrN9unHjhmaJBFetQYMGumc0Z2ZmSseOHQ2N9/DDD0tycrLh55j9/ZSWlqa6OJSzVrBgQVm8eLHTce0DASPt//7v/+TAgQMuj4U3jq8ng+P4+HhZvny5alkNZ61Ro0aGzh4+ffq0amkLR83RfexugGm//qurVrp0adm5c6fbx8YIbwfHOWJjY+WBBx5w+3FqsVikY8eOTs/8z21wLOLZ+8KTz0X754qRdt9990liYqKp4+DI9u3bVWfhu9uaN28u586dM3RbCxYs0ISyRpqzaxzkuH37trzwwgtujenqsRQfH6+cCe+s2T//3H3d88b7LcExgPyI4BgAENBOnDghU6ZMkQ4dOqh+QuqshYaGyvPPPy8bN240NL7RkMBbwXGOHTt2SJs2bVRrM9u3kiVLSq9evQz9zHX16tUOzzjLaWFhYTJ8+HBDoSTBsWvuhi7p6ekSGRkp//d//+f0/qlevbrExcUZ+vmu7bhxcXHy7LPPStWqVaVYsWKan5A7k52dLbGxsS7DvgcffFCioqIkIyPD0HwyMzNl9OjRTp+39913n7z//vvKY9BscCzy9xcmH3/8sebssZzWuHFj2b17t8v5pqSkyMSJE6VZs2a6IWrZsmVlyJAhhpdg8PTx9XRwLPL3Oqz2Z3DmtBIlSsiwYcPcWnf2xo0bMnPmTOnQoYNUqFBBtaa7s/vYTIC5detWefrpp1WPddtWvHhxeffdd+XSpUuGxjP6nmArr4Jjkb/Xs42KipImTZrohpFly5aVfv366T72PREci3juvvDkc/H69esyffp0eeaZZ6Ro0aIuxypRooS89dZbhkNad5w/f17mzp0rzz33nJQpU8blPCyWv7/oat++vaELV9o7e/asvPfee6olg5zdH507d5b4+HjD6xZ/99130qRJE6f3scVikXLlykm/fv10z9j+/fffZdCgQdK4cWMJCwvTBMm5DY5FPP9+S3AMID8iOAYA3DOysrLkjz/+kDVr1sjcuXNl0qRJMn78eJkxY4YsWbJE9u7d6/aF9PzN1atX5dtvv5W5c+fK+PHjZfLkybJ48WLZs2eP7nIFjiQnJ8uyZctk6tSpMnHiRImNjZXt27e7vFAM8obVapU9e/ZIfHy8REREyOTJk2XJkiVOzwrMKwcPHpQlS5bI5MmTJSIiQuLj42XPnj1uhdi2bt68KevXr5fp06fLhAkTJCYmRjZs2OCV5+rt27dl3bp1MnfuXJk4caLExcXJ77//7vY4d+/eld27dyvPnXHjxsnkyZMlLi5O9uzZYzg8d8TTx9cMV+HMoUOH5PPPP5fIyEiZMWOGrFmzxuVyP/4iJSVFvvjiC5kxY4aEh4fL/PnzZfPmzW6F3fnN1atXZcOGDbJ48WKZMmWKTJgwQebMmSOrVq2S48eP+2xenrwvPPlczMzMlF9//VVWrlwp06ZNk3HjxklERIQsWLBAdu7cmWd/P1itVklOTpb169fLvHnzJCIiQsaNGyfTpk2T+Ph4+emnn1xeSNOo7Oxs2b17t/L4GD9+vEyfPl1WrFghBw4c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width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pkl_file = open('data/ffast.pkl', 'rb')\n",
    "ffast = pickle.load(pkl_file)\n",
    "pkl_file.close()\n",
    "\n",
    "Z = 14\n",
    "print(f\"Edges of {ffast[Z]['element']}:\")\n",
    "for key in ffast[Z]['edges']:\n",
    "      print(f\"{key:3s}: {ffast[Z]['edges'][key]/1e3:.3f} keV\")\n",
    "plt.figure()\n",
    "plt.plot(ffast[Z]['E']/1000., ffast[Z]['photoabsorption']*0.1)\n",
    "plt.xlim(0,3)\n",
    "plt.ylim(0,1.2e4)\n",
    "            \n",
    "plt.xlabel('energy [keV]')\n",
    "plt.ylabel('$\\mu$ [m$^2$/kg]')\n",
    "plt.title('Silicon Photoabsorption Cross-Section')\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detector Efficiency\n",
    "### Absorption\n",
    "Absorption probability $P(E)$ is related t the mass aborption coefficient  with:\n",
    "\n",
    "$$ P(E) = I/I_0 =\\exp\\left[ -(\\mu/\\rho) * \\rho * t\\right] = \\exp\\left[ -\\mu* t\\right]$$\n",
    "\n",
    "with\n",
    "- $I_0$: initial intensity of X-rays\n",
    "- $I$:  intensity of X-rays after going through thickness $t$\n",
    "- $\\rho$: density of material \n",
    " \n",
    "### Detector \n",
    "\n",
    "The detector response $P_D$ is given by Small et al. as:\n",
    "Here, we assume the contact to be Al and the dead layer is of course Si like the detector crystal:\n",
    "\n",
    "$$ \\Large \n",
    "\\begin{align}\n",
    "P_D = &(\\exp(\\mu_{Al}(E) *t_{Al} *\\rho_{Al})) * (\\exp(\\mu_{Si}(E) *t_{dead layer} *\\varrho_{Si} )) \\\\\n",
    "&\\times (1- \\exp(\\mu_{Si}(E) *t_{detector} *\\varrho_{Si} ))\n",
    "\\end{align} $$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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   ],
   "source": [
    "from scipy.interpolate import interp1d\n",
    "import scipy.constants as const\n",
    "\n",
    "\n",
    "## layer thicknesses of commen materials in EDS detectors in m\n",
    "nickelLayer = 0.* 1e-9 # in m\n",
    "alLayer = 30 *1e-9    # in m\n",
    "goldLayer = 0.* 1e-9   # in m\n",
    "deadLayer = 100 *1e-9  # in m\n",
    "detector_thickness = 45 * 1e-3  # in m\n",
    "\n",
    "area = 30 * 1e-6 #in m2\n",
    "oo4pi = 1.0 / (4.0 * np.pi)* np.radians(10)*2\n",
    "\n",
    "#We make a linear energy scale \n",
    "energy_scale = np.linspace(.1,60,1199)\n",
    "\n",
    "\n",
    "## interpolate mass absorption coefficient to our energy scale\n",
    "lin = interp1d(ffast[14]['E']/1000.,ffast[14]['photoabsorption'],kind='linear') \n",
    "mu_Si = lin(energy_scale) * ffast[14]['nominal_density']*100. #1/cm -> 1/m\n",
    "\n",
    "## interpolate mass absorption coefficient to our energy scale\n",
    "lin = interp1d(ffast[13]['E']/1000.,ffast[13]['photoabsorption'],kind='linear') \n",
    "mu_Al = lin(energy_scale) * ffast[13]['nominal_density'] *100. #1/cm -> 1/m\n",
    " \n",
    "detector_Efficiency1 = np.exp(-mu_Al * alLayer)* np.exp(-mu_Si * deadLayer)  * oo4pi\n",
    "detector_Efficiency2 = (1.0 - np.exp(-mu_Si * detector_thickness)) * oo4pi;\n",
    "detector_Efficiency =detector_Efficiency1 * detector_Efficiency2/  oo4pi;\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(energy_scale,detector_Efficiency*100, label = 'detector efficieny', color = 'red')\n",
    "plt.plot(energy_scale,detector_Efficiency1*100, '--', label = 'deadlayer and contacts', color = 'blue')\n",
    "plt.plot(energy_scale,detector_Efficiency2*100, '--',label = 'crystal efficiency' , color = 'orange')\n",
    "plt.xlabel('energy [keV]')\n",
    "plt.ylabel('efficiency [%]')\n",
    "plt.title('SDD Detector Efficiency')\n",
    "#plt.ylim(60,105)\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the detector efficiency drops off after our maximum acceleration voltage of 30 keV in the SEM.\n",
    "\n",
    "The background Bremsstrahlung will be absorbed at low energies as we expected.\n",
    "\n",
    "Play around with the thickness values of the contact and deadlayer. \n",
    "\n",
    "What has the biggest impact?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effective Background\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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"
      ],
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width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Z = 26\n",
    "E_0 = 30 # keV\n",
    "\n",
    "Z2 = 26\n",
    "E_02 = 10\n",
    "\n",
    "\n",
    "K = -4000\n",
    "I = 1\n",
    "E = energy_scale #= np.linspace(.1,30,2048) #in keV\n",
    "\n",
    "N_E = I*K*Z*(E-E_0)/E\n",
    "N_E2 = I*K*Z2*(E-E_02)/E\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(energy_scale, N_E, '--', color = 'blue');\n",
    "plt.plot(energy_scale, N_E*detector_Efficiency , color = 'blue', label = f'Z = {Z} and E$_0$ = {E_0} keV');\n",
    "plt.plot(energy_scale, N_E2, '--', color = 'red', label = f'Z = {Z2} and E$_0$ = {E_02} keV');\n",
    "plt.plot(energy_scale, N_E2*detector_Efficiency,  color = 'red');\n",
    "plt.axhline(y=0., color='gray', linestyle='-', linewidth = 0.5);\n",
    "plt.xlim(0,3)\n",
    "plt.legend();\n",
    "\n",
    "plt.ylabel('intensity [a.u.]')\n",
    "plt.xlabel('energy [keV]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the curve above the change at the lower energiers is now as we expect it.\n",
    "\n",
    "Please check the slope at about 1.8 keV which is caused by the Si-K edge absorption fo the deadlayer.\n",
    "\n",
    "Change the values of *Z2* and the acceleration voltage *E_02* of the second curve to see the effects."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effect of Window\n",
    "\n",
    "So far we have ignored the effect of the window in front of the X-ray detector. This window consists mostly of carbon being manufactured from polymer in a modern detector system. The exact composition is necessary to determine the effective background in an EDS spectrum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>"
      ]
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     "output_type": "display_data"
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width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "C_window = .3* 1e-6   # in m\n",
    "\n",
    "## interpolate mass absorption coefficient to our energy scale\n",
    "lin = interp1d(ffast[6]['E']/1000.,ffast[6]['photoabsorption'],kind='linear') \n",
    "mu_C = lin(energy_scale) * ffast[6]['nominal_density']*100. #1/cm -> 1/m\n",
    "\n",
    "\n",
    "window_Absorption = np.exp(-mu_C * C_window)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(energy_scale, N_E, '--', color = 'blue');\n",
    "plt.plot(energy_scale, N_E*detector_Efficiency , color = 'blue', label = f'Detector');\n",
    "plt.plot(energy_scale, N_E*detector_Efficiency * window_Absorption, color = 'red', label = f'Detector and Window');\n",
    "\n",
    "plt.axhline(y=0., color='gray', linestyle='-', linewidth = 0.5);\n",
    "plt.xlim(0,3)\n",
    "plt.legend();\n",
    "\n",
    "plt.ylabel('intensity [a.u.]')\n",
    "plt.xlabel('energy [keV]');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background Slope at High Energies\n",
    "While Kramers law gives the approximate shape of the background, the exact slopes is not reproduced.\n",
    "Several authors intorduced a parametrized function of the Bremsstrahlung efficiency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "E = energy_scale\n",
    "Z = 26\n",
    "E_0 = 30\n",
    "a = [0, -73.9,1,2446,36.502,148.5, 0.1293,-0.006624,0.0002906]\n",
    "g  = np.sqrt(Z)* (E_0-E)/E *(a[1]+a[2]*E+a[3]*np.log(Z)+a[4]*E**a[5]/Z)*(1+(a[6]+a[7]*E_0)*Z/E)\n",
    "plt.figure()\n",
    "\n",
    "a = [0,54.86,1.072, 0.2835, 30.4,875,-0.08]\n",
    "g2 = np.sqrt(Z)* (E_0-E)/E *(a[1]+a[2]+a[3]*E_0 +a[4]*np.log(Z)+a[5]*E_0**a[6]/Z**2)\n",
    "b = [2000,-.6]\n",
    "f = (b[0]+b[1]*E_0)*Z/E\n",
    "\n",
    "plt.plot(E,g2, label = 'parametrized')\n",
    "plt.plot(E,N_E/100, label = 'Kramer')\n",
    "plt.plot(E,g2*detector_Efficiency,label = 'parametrized with Detector')\n",
    "plt.xlim(0,5)\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fitting Background\n",
    "\n",
    "Neither Kramer's Law nor any of the parametrized versions of the Bremsstrahlung are usefull for fitting.\n",
    "\n",
    "The following expression is used for fitting purposes:\n",
    "\n",
    "$$ N(E) = \\epsilon(E) A(E) \\left[ p_0+ p_1 \\frac{E_0-E}{E} + p_2 \\frac{(E_0-E)^2}{E}  \\right]$$\n",
    "\n",
    "in which we have the fitting parameters ($p_0, p_1, p_2$) of a polynomial of the overvoltage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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"
    },
    {
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\" width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0, 4)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = [10, 26, 10]\n",
    "E = E\n",
    "N = detector_Efficiency * (p[0] + p[1]*(E_0-E)/E + p[2]*(E_0-E)**2/E)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(E,N_E/200*detector_Efficiency)\n",
    "plt.plot(E,N)\n",
    "\n",
    "plt.xlim(0,4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now we put all of that together\n",
    "\n",
    "and make a function:\n",
    "\n",
    "The input is in the form of a dictionary.\n",
    "\n",
    "We note that we have several layers that reduce the efficiency and that the detector crystal itself is not really that importantfor the acceleration voltages in an SEM.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0, 4)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tags = {}\n",
    "\n",
    "tags['acceleration_voltage_V'] = 30000\n",
    "\n",
    "tags['detector'] ={}\n",
    "tags['detector']['layers'] ={}\n",
    "\n",
    "## layer thicknesses of commen materials in EDS detectors in m\n",
    "tags['detector']['layers']['alLayer'] = {}\n",
    "tags['detector']['layers']['alLayer']['thickness'] = 30 *1e-9    # in m\n",
    "tags['detector']['layers']['alLayer']['Z'] = 13\n",
    "\n",
    "tags['detector']['layers']['deadLayer'] = {}\n",
    "tags['detector']['layers']['deadLayer']['thickness'] =  100 *1e-9  # in m\n",
    "tags['detector']['layers']['deadLayer']['Z'] = 14\n",
    "\n",
    "tags['detector']['layers']['window'] = {}\n",
    "tags['detector']['layers']['window']['thickness'] =  100 *1e-9  # in m\n",
    "tags['detector']['layers']['window']['Z'] = 6\n",
    "\n",
    "tags['detector']['detector'] = {}\n",
    "tags['detector']['detector']['thickness'] = 45 * 1e-3  # in m\n",
    "tags['detector']['detector']['Z'] = 14\n",
    "tags['detector']['detector']['area'] = 30 * 1e-6 #in m2\n",
    "## interpolate mass absorption coefficient to our energy scale\n",
    "\n",
    "\n",
    "def detector_response(detector_definition,energy_scale):\n",
    "    response = np.ones(len(energy_scale))\n",
    "    for key in detector_definition['layers']:\n",
    "        Z = detector_definition['layers'][key]['Z']\n",
    "        t = detector_definition['layers'][key]['thickness']\n",
    "        \n",
    "        lin = interp1d(ffast[Z]['E']/1000.,ffast[Z]['photoabsorption'],kind='linear') \n",
    "        mu = lin(energy_scale) * ffast[Z]['nominal_density']*100. #1/cm -> 1/m\n",
    "        absorption = np.exp(-mu * t)\n",
    "        response = response*absorption\n",
    "    Z = detector_definition['detector']['Z']\n",
    "    t = detector_definition['detector']['thickness']    \n",
    "    lin = interp1d(ffast[Z]['E']/1000.,ffast[Z]['photoabsorption'],kind='linear') \n",
    "    mu = lin(energy_scale) * ffast[Z]['nominal_density']*100. #1/cm -> 1/m\n",
    "    response = response*(1.0 - np.exp(-mu * t))# * oo4pi;\n",
    "    return(response)\n",
    "\n",
    "\n",
    "p = [10, 26, 10]\n",
    "\n",
    "def EDS_Background(p,tags,energy_scale):\n",
    "    E_0= tags['acceleration_voltage_V']/1000\n",
    "\n",
    "    detector_efficiency = detector_response(tags['detector'],energy_scale)\n",
    "    E = energy_scale\n",
    "    N = detector_efficiency * (p[0] + p[1]*(E_0-E)/E + p[2]*(E_0-E)**2/E)\n",
    "    return N\n",
    "\n",
    "background = EDS_Background(p,tags,energy_scale)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(energy_scale, background)\n",
    "plt.xlim(0,4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Back: [Characteristic X-Rays](CH4-Characteristic_X_Rays.ipynb)\n",
    "## Next: [Analyze Spectrum](CH4-Analyze_Spectrum.ipynb)\n",
    "## List of Content: [Front](_Analysis_of_Scanning_Electron_Microscope_Data.ipynb#Content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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