CH2-Atomic_Form_Factor.ipynb

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   "source": [
    "<font size = \"5\"> **Chapter 2: [Diffraction](Ch2-Diffraction.ipynb)** </font>\n",
    "\n",
    "\n",
    "<hr style=\"height:1px;border-top:4px solid #FF8200\" />\n",
    "\n",
    "\n",
    "# Atomic Form Factor\n",
    "\n",
    "part of \n",
    "\n",
    "\n",
    "<font size = \"5\"> **[Analysis of Transmission Electron Microscope Data](_Analysis_of_Transmission_Electron_Microscope_Data.ipynb)**</font>\n",
    "\n",
    "\n",
    "by Gerd Duscher, 2019\n",
    "\n",
    "Microscopy Facilities<br>\n",
    "Joint Institute of Advanced Materials<br>\n",
    "The University of Tennessee, Knoxville\n",
    "\n",
    "Model based analysis and quantification of data acquired with transmission electron microscopes"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Import numerical and plotting python packages"
   ]
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      "Populating the interactive namespace from numpy and matplotlib\n",
      "Using KinsCat library version  0.5  by G.Duscher\n",
      "spglib not installed; Symmetry functions of spglib disabled\n",
      "windows\n"
     ]
    }
   ],
   "source": [
    "# import matplotlib and numpy\n",
    "#                       use \"inline\" instead of \"notebook\" for non-interactive plots\n",
    "%pylab --no-import-all notebook\n",
    "\n",
    "# additional package \n",
    "import scipy.constants as const\n",
    "\n",
    "# Import libraries from the book\n",
    "import pyTEMlib.KinsCat as ks         # Kinematic sCattering Library\n",
    "                             # with Atomic form factors from Kirklands book"
   ]
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    "## Coulomb Force\n",
    "\n",
    "The electron scatters at the Coulomb force of the screened nucleus of an atom. This force is:\n",
    "\n",
    "$\\mathbf{F} = \\frac{1}{4\\pi\\varepsilon_0}\\frac{Qq}{r^2}\\mathbf{\\hat{e}}_r \n",
    "=  k_\\text{e}\\frac{Qq}{r^2}\\mathbf{\\hat{e}}_r $\n",
    "\n",
    "$k_\\text{e} = \\frac{1}{4\\pi\\varepsilon_0}= 8.987\\,551\\,787\\,368\\,1764\\times 10^9~\\mathrm{N\\ m^2\\ C^{-2}}$\n"
   ]
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     "text": [
      " k_e   = 8987551787.4 N m²C⁻²\n",
      " F_r_m = 20007.8 N m² kg⁻¹ = 20007.8 m³s⁻²\n"
     ]
    }
   ],
   "source": [
    "Z = 79 # gold\n",
    "\n",
    "k_e = 1/(4* const.pi * const.epsilon_0)\n",
    "F_r_m = k_e * Z* const.e**2 /const.m_e\n",
    "print(f\" k_e   = {k_e:.1f} N m\\u00b2C\\u207B\\u00b2\")\n",
    "print(f\" F_r_m = {F_r_m:.1f} N m\\u00b2 kg\\u207B\\u00B9 = {F_r_m:.1f} m\\u00b3s\\u207B\\u00B2\")"
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       "        var msg = JSON.parse(evt.data);\n",
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       "\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def coulomb_plot(impact_param = 1.0, Z = 79, v_c = 0.5):\n",
    "    # all length are in m\n",
    "    #time interval for each iteration. Should be chosen small enough so that\n",
    "    #the velocity change and position change in this interval is relatively\n",
    "    #small. If too small this calculation will take a while\n",
    "    dt = 1e-20 # s\n",
    "    \n",
    "    x = -50.0*1e-9 # starting x in m\n",
    "    y = impact_param*1e-9  #in m\n",
    "    #starting y\n",
    "    x_coords=[x] #array for the x coordinates of the plot\n",
    "    y_coords=[y] #array for the y coordinates of the plot\n",
    "    vx = v_c * const.c #initial x velocity in m/s\n",
    "    vy = 0.0 #initial y velocity\n",
    "    \n",
    "    r = np.sqrt(x*x + y*y)\n",
    "    rold = r*2 # an arbitrary value more than r\n",
    "\n",
    "    k_e = 1/(4* const.pi * const.epsilon_0) #[N m^2 C^-2]\n",
    "    F_r_m = -k_e * Z* const.e**2/const.m_e # [ N m^2 / kg]\n",
    "    \n",
    "    # The plot coordinates are generated as long as the incident particle\n",
    "    # is going towards the origin( which means that r < rold )\n",
    "    # or\n",
    "    # if it is coming out, as long as r < 50.0 nm. You can choose this to be\n",
    "    # something else.\n",
    "    while (r < rold) or ( r < 50.0*1e-9) :\n",
    "        rold = r # old r is changed to the current r\n",
    "        x = x + vx*dt# calculate new x\n",
    "        y = y + vy*dt# calculate new y\n",
    "        # add x and y to the plotting coordinates for x and y\n",
    "        x_coords.append(x)\n",
    "        y_coords.append(y)\n",
    "        r = np.sqrt(x*x + y*y)\n",
    "        \n",
    "        #vx = vx + x-acceleration*dt = vx + Fx/m*dt \n",
    "        #Fx = x component of Coulomb force = (magnitude of F)*cos(theta) =\n",
    "        #(magnitude of F)*x/r = \n",
    "        #vx = vx + (F_r/m/r^2)*x/r = F_r_m * x/r^3,\n",
    "        vx = vx + F_r_m*x/r**3*dt\n",
    "        #as for vx\n",
    "        vy = vy + F_r_m*y/r**3*dt\n",
    "        \n",
    "    return np.array(x_coords), np.array(y_coords)\n",
    "\n",
    "\n",
    "#plotting trajectories for 4 impact parameters\n",
    "plt.figure()\n",
    "for b in [-1e-5, -0.001, -0.1, -1.0, -2.0, -4.0, -6.0]:\n",
    "    xc, yc = coulomb_plot(b, Z= 79, v_c = 0.7)\n",
    "    plt.plot(xc*1e9,yc*1e9, label = str(b))\n",
    "\n",
    "plt.xlabel('distance [nm]')\n",
    "plt.ylabel('impact parameter [nm]')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above graph was calulated for 200keV electrons.\n",
    "What changes if you change the v_c = v/c parameter to higher or lower speeds?\n",
    "\n",
    "|E (keV)|$\\lambda$ (pm) | M/m$_0$ | v/c|\n",
    "--------|---------------|---------|----|\n",
    "|10 |  12.2 | 1.0796 | 0.1950 |\n",
    "|30 | 6.02 | 1.129 | 0.3284 |\n",
    "|100 | 3.70 | 1.1957 | 0.5482|\n",
    "|200 | 2.51 | 1.3914 |  0.6953|\n",
    "|400 | 1.64 | 1.7828 | 0.8275 |\n",
    "|1000 | 0.87 | 2.9569 | 0.9411|\n",
    "\n",
    "You can also change the atom number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting trajectories for 7 impact parameters\n",
    "plt.figure()\n",
    "for b in [-1e-5, -0.001, -0.1, -1.0, -2.0, -4.0, -6.0]:\n",
    "    xc, yc = coulomb_plot(b, Z= 6, v_c = 0.7)\n",
    "    plt.plot(xc*1e9,yc*1e9, label = str(b))\n",
    "\n",
    "plt.xlabel('distance [nm]')\n",
    "plt.ylabel('impact parameter [nm]')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we look at the scattering power of a single atom that deflects an electron:\n",
    "    \n",
    "![Ewald Sphere](images/scattering_single_atom.jpg)\n",
    "\n",
    "The scattering power is dependent on the so-called atomic form factor $f_e$ ( the subscript $_e$ means this is for electrons).\n",
    "\n",
    "99\n",
    "Since an electron scatters through the coulomb force of the (screend) nucleus, the form factor is the inner potential.\n",
    "We can 9\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tabulated Atomic Form Factors\n",
    "The calculated form factors are tabulated and can be plotted according to the momentum transfer.\n",
    "\n",
    "Here we use the values from Appendix C of Kirkland, \"Advanced Computing in Electron Microscopy\", 2nd ed.\n",
    "\n",
    "The calculation of electron form factor for specific $q$ perfommed by the KinsCat function *feq* using equation Kirkland C.17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# recreating figure 5.8 of Kirkland, \"Advanced Computing in Electron Microscopy\" 2nd ed.   \n",
    "x = []\n",
    "ySi = []\n",
    "yC = []\n",
    "yCu =[]\n",
    "yAu =[]\n",
    "yU = []\n",
    "for i in range(100):\n",
    "    x.append(i/5)\n",
    "    ySi.append(ks.feq('Si', i/5))\n",
    "    yC.append(ks.feq('C', i/5))\n",
    "    yCu.append(ks.feq('Cu', i/5))\n",
    "    yAu.append(ks.feq('Au', i/5))\n",
    "    yU.append(ks.feq('U', i/5))\n",
    "fig = plt.figure()\n",
    "plt.plot(x,ySi,label='Si')\n",
    "plt.plot(x,yC,label='C')\n",
    "plt.plot(x,yCu,label='Cu')\n",
    "plt.plot(x,yAu,label='Au')\n",
    "plt.plot(x,yU,label='U')\n",
    "plt.legend()\n",
    "plt.ylabel('scattering factor (in Ang.)')\n",
    "plt.xlabel('scattering angle q (in 1/nm)')\n",
    "plt.show()\n"
   ]
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    "Adding atoms in a row makes the atom just look heavier:\n",
    "\n",
    "![Structure Factor](images/form_factor.jpg)\n",
    "\n",
    "Similar effects appear if atoms are periodically arranged. That is discussed in more detail in the \n",
    "[Structure Factors](CH2-Structure_Factors.ipynb) notebook."
   ]
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    "## Conclusion\n",
    "The scattering power of an atom is given by the tabulated scattering factors. As long as there are no dynamic effects the scattering factors can be combined linearly.\n",
    "\n",
    "Next we need to transfer out knowledge into a  diffraction pattern."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Navigation\n",
    "## Back: [The Electron](CH2-Electron.ipynb)\n",
    "## Next: [Basic Crystallography](CH2-Basic_Crystallography.ipynb)\n",
    "## Chapter 2: [Diffraction](CH2-_Diffraction.ipynb)\n",
    "## List of Content: [Front](_Analysis_of_Transmission_Electron_Microscope_Data.ipynb)\n"
   ]
  }
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