CH4-Characteristic_X_Rays.ipynb

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    "\n",
    "## Chapter 4 [Spectroscopy](Ch3-Spectroscopy.ipynb)\n",
    "\n",
    "\n",
    "<hr style=\"height:1px;border-top:4px solid #FF8200\" />\n",
    "\n",
    "# Generation of Characteristic X-Rays \n",
    "\n",
    "\n",
    "\n",
    "part of \n",
    "\n",
    "## [Analysis of Scanning Electron Microscope Data](_Analysis_of_Scanning_Electron_Microscope_Data.ipynb)\n",
    "\n",
    "\n",
    "\n",
    "by Gerd Duscher, 2019\n",
    "\n",
    "Microscopy Facilities<br>\n",
    "Joint Institute of Advanced Materials<br>\n",
    "The University of Tennessee, Knoxville\n",
    "\n",
    "Model based analysis and quantification of data acquired with scanning electron microscopes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First we import the essential libraries\n",
    "All we need here should come with the annaconda or any other package"
   ]
  },
  {
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   "execution_count": 14,
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "# import matplotlib and numpy\n",
    "%pylab --no-import-all notebook\n",
    "\n",
    "import pickle  ## we use this library to open the data file\n",
    "\n",
    "__notebook__ = 'CH4-Characteristic-X_Rays'\n",
    "__notebook_version__ = '2019_08_21'\n"
   ]
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    "## X-Ray Families\n",
    "The case is not always as simple as in the case of the carbon atom in the [Introduction](CH4-Introduction_X_Rays.ipynb#X-Rays)\n",
    "\n",
    "As the atomic number $Z$ increases the number of electrons in the respective energy states increases. With increasing complexity of the shell structure more options for relaxtions are available with different probabilities.\n",
    "\n",
    "For example a Na atom which has an M-shell The 1s state can be filled by an L- or an M-shell, producing two different characteristic X-rays:\n",
    "\n",
    "- K-L$_{2,3} ($K\\alpha$): $E_X = $E_K- E_L$ = 104 eV\n",
    "- K-M$_{2,3} ($K\\beta$): $E_X = $E_K- E_M$ = 1071 eV\n",
    "\n",
    "For heavier atoms than sodium more options exist:\n",
    "\n",
    "![Nomenclature](./images_SEM/Nomenclature.jpg)\n",
    "\n"
   ]
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    "## X-ray Nomenclature \n",
    "\n",
    "Two systems are in use for naming characteristic X-ray lines.\n",
    "\n",
    "The oldest one is the Siegbahn system in wich first the shell where the  ionization occured is listed and then a greek letter that suggests the order of their families by their **relative intensity** ($\\alpha>\\beta>\\gamma>\\eta>\\zeta$).\n",
    "\n",
    "For closely related memebers of a family additionally numebrs are attched such as $L \\beta_1$.\n",
    "\n",
    "While most commercial software still uses the Siegbahn system the International Union of Pure and Applied Chemistry (IUPAC) has officially changed the system to a protocol that first dentoes the subshell were the ionization occured and followed with the term that indicates from which subshell the relaxation originates.\n",
    "\n",
    "So $K\\alpha_1$ is replaced by $K-L_3$.\n",
    "\n",
    "![eds-lines](./images_SEM/eds-lines.jpg)\n",
    "\n",
    "|Siegbahn|  -----IUPAC-----   |Siegbahn| -----IUPAC-----  |Siegbahn|  -----IUPAC-----  |\n",
    "|--------| -------------- |--------| ------------ |--------| ------------- | \n",
    "| $K\\alpha_1$| $K-L_3$    |$L\\alpha_1$| $L_3-M_5$   |$M\\alpha_1$| $M_5-N_7$|\n",
    "| $K\\alpha_2$| $K-L_2$    |$L\\alpha_2$| $L_3-M_4$   |$M\\alpha_2$| $M_5-N_6$|\n",
    "| $K\\beta_1$| $K-M_3$     |$L\\beta_1$ | $L_2-M_4$   |$M\\beta$    | $M_4-N_6$|\n",
    "| $K\\beta_2$| $K-N_{2,3}$ |$L\\beta_2$ | $L_3-N_5$   |$M\\gamma$   | $M_3-N_5$|\n",
    "|           |             |$L\\beta_3$ | $L_1-M_3$   |$M\\zeta$     | $M_{4,5}-N_{2,3}$|\n",
    "|           |             |$L\\beta_4$ | $L_1-M_2$   |            | $M_3-N_1$|\n",
    "|           |             |$L\\gamma_1$| $L_2-N_4$   |            | $M_2-N_1$|\n",
    "|           |             |$L\\gamma_2$| $L_1-N_2$   |            | $M_3-N_{4,5}$|\n",
    "|           |             |$L\\gamma_3$| $L_1-N_3$   |            | $M_3-O_1$|\n",
    "|           |             |$L\\gamma_4$| $L_1-O_4$   |            | $M_3-O_{4,5}$|\n",
    "|           |             |$L\\zeta$   | $L_2-M_1$   |            | $M_2-N_4$|\n",
    "|           |             |$L\\iota$    | $L_3-M_1$   |            ||"
   ]
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    "## X-ray Weight of Lines\n",
    "\n",
    "Within the excitation probaility of the characteristic X-ray lines are not equal. \n",
    "\n",
    "For sodium (see above for energies), \n",
    "the ratio of $K-L_{2,3}$ to $K-M$ is approximatively 150: 1. \n",
    "\n",
    "This ratios between the lines are a strong function of the atomic number $Z$.\n",
    "\n",
    "We load the data of the X-Ray lines from data from [NIST](https://www.nist.gov/), the line weights are taken from the Program [DTSA-II](https://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html), which is the quasi-standard in EDS analysis.\n"
   ]
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       "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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BEYQHMPSaIAAAAAAAAD6yE1gBMExLI0GCAAAAAAAoI/cBEYQHMPSaIAAAAAAAAD6yE1gBMExLI0GCAAAAAAAoI/cBEYQHMPSaIAAAAAAAAD6yE1gBMExLI0GCAAAAAAAoI/cBEYQHMPSaICA96w6HCevjdkob46NlrVHr5i9HZ+UlpElIYsOyQuDV0mdkOUMBoPBYDAYDAbDJmP/hZtm/3UkT8hNYATBMSylbNmyqhEUFEQDBLxg7bErUrXXEgnu+eeo2muJzNsZY/a2fEpaRpZ0mLpN+RkxGAwGg8FgMBgM+4w952+Y/VeSPCE4hhEEx7AUgmPA+2LiU+Xp71ZoPhhV7bVEIrafN3t7PuFWepb8cwqhMYPBYDAYDAaDYddBcAw7IjiGpdEAAWPSMrLkzbHRbj8ghW87Z/Y2TZWaninvT95q+gdVBoPBYDAYDAaDYd4gOIYdERzD0miAgDG9Fxzw6EPSrC1nzd6qKVLTM6XdpC26P5PmP6yXf03fwWAwGAwGg8FgMGwwTl1NNvuvJ3lCbgIjCI5haTRAIO9+2XVBNxB9pPdS3T+fsfms2VsuUMm3M6XtBP3QuP2krZKanmn2FgEAAADALXITGEFwDEujAQJ5czg2UWr2XaYJRDv9vF12nYuXJwcs1w1Mp0WfMXvrBSIpLUPa/LRZ92fwwZStcis9y+wtAgAAAECuyE1gBMExLI0GCNy7hFsZ0mT4Wk0g2nDoGrmZmi4iIntjbsqTIfrh8ZSNp01+BfkrMS1D3g7bpPvaO0zdJmkZhMYAAAAArIHcBEYQHMPSaIDAvXE6nfLJzJ2aQLRG32Vy4EKCau7+CzeljovweOL6Uya9gvyVmJYh/xivHxp/OG07oTEAAAAASyE3gREEx7A0GiBwbyasP6UbikZsP687/+DFBHnq2xW6jwlbd7KAd5+/Em5lSOtx0bqvtdPPhMYAAAAArIfcBEYQHMPSaICA57acui7VemlD0e7z94nT6XT5uIMXE+Tp7/TD43FrThTgK8g/N1PT5c2x+qHxv6bvkNuZhMYAAAAArIfcBEYQHMPSaICAZ+IS06Ru6EpNKNpyzEaP7qQ9HJsoz7gIj8essnZ4fCMlXV7/caPua+s8YyehMQAAAADLIjeBEQTHsDQaIJC7jKxsafPTZk0o+mTIcjl3PcXjdY5eTpTnBmrD5+CeS+SHlcfd3rXsq+JT0qXlGP3Q+NNZOyU9M9vsLQIAAABAnpGbwAiCY1gaDRDI3cA/DusGoysPx93zWsfjknTvXA7uuURGLD9mqfD4evJteXX0Bt3X8tnsXZKRRWgMAAAAwNrITWAEwTEsjQYIuLdk/yXdYHRY1NE8r3kiLknqhq7SXXdo1FFLhMfXkm9Li1H6ofEX4bsJjQEAAAAUCuQmMILgGJZGAwRcO3klWWr3j9IEo+9P3iqZBoPRk1eS5flB+uFxv4UHfTp4PXIpUf42Yp3u3r+cu8fwzwYAAAAAfAW5CYwgOIal0QABfSm3M+XvP6zXBKMvDF4l15Jve+U5Tl9NlhcG64fHH0zZKjdT073yPN7idDpl7vbzUrPvMt09fxVBaAwAAACgcCE3gREEx7A0GiCg5XQ65T9z92iC0Ud7L5Vd5+K9+lxnr6XIi9+v1g1imw5fKyevJHn1+fIq+Xam/DdC+zO5M76et1eysn3/iA0AAAAAuBfkJjCC4BiWRgMEtGZsPqsbjv686Uy+PN+56ynScOga3ed8csByWXvsSr48r6cOxyZKMxdHUwT3XCI9f91PaAwAAACgUCI3gREEx7A0GiCgtuvcDaneZ6kmHO0yZ3e+fmnd9eTb0nbCFt1gtlqvJTJl4+kC/9I8p9Mpc7adlxoujqao2XeZzN1+3hJf5gcAAAAAeUFuAiMIjmEpZcuWVY2goCAaIPA/KbczpcEQ7Z2/zX9YLym3M/P9+dMzs6Xnr/td3tnbff4+uZ2Zle/7EPnzaAq94zrujGYj1smRS4kFshcAAAAAMAvBMYwgOIalEBwDroUsOqQJSB/vH1Wg5ww7nU75edMZqdZLP7Bt89Nmr305nyuHYxPlb26OpvhvxB5JLoAgHQAAAADMRnAMIwiOYWk0QOBPu87dkKo6Ye2ifbGm7GfD8avyZMhy3eC2wZA1cjjW+3f7Op1OCd92zu3RFBEcTQEAAADARshNYATBMSyNBgiI3M7MkuY/rNc919hMp64mu/xSusf6RUnUwctee66ktAz5kqMpAAAAAECF3ARGEBzD0miAgMgPK45pgtKnv1uR70dCeCIhNUM6TN3mMtAdu/qE4TuAD8UmuD2a4iuOpgAAAABgU+QmMILgGJZGA4TdHbmUKI/2XqoJS3/bfcHsrSkys7J1z1++M76cu0fSMjz70jyn0ylJaRly/nqq7I25KVM2nnZ7NEXkDo6mAAAAAGBf5CYwguAYlkYDhJ1lZmVLq3HRmsD0o2nbfTIsnbv9vG7IHdxzibw5NlpWH4mThXsuyrToMzJyxTHps+CAfB6+S9pN2iItRm2QeoNWSfU++o/XHE0xcp0cvczRFAAAAADsjdwERhAcw9JogLCzyRtOawLT2v2j5MKNVLO35tK209fl2YErPQp/8zq6Ru6VFI6mAAAAAAByExhCcAxLowHCrs5dT5Fa/bRHNMzYfNbsreUqJj5VWoza4PXAuGbfZTJvR4xP3m0NAAAAAGYgN4ERBMewNBog7MjpdEr7SVs1wWmbnzZLdrY1QtPk25nSecYOr4XGLUZt4GgKAAAAALgLuQmMIDiGpdEAYUcR289rgtMafZbJySvJZm/tnmRnO2Vo1FG3gXD1Pkvl+UGr5NXRG6T9pK3yRfhu6bvwgPyw4pj8vOmMLNxzUXafv8FdxgAAAACgg9wERhAcw9JogLCbuMQ0eTJkuSZgHbfmhNlby7ODFxNk9tZz8tvuC7L22BXZF3NTYuJTJfl2JoEwAAAAABhAbgIjCI5haTRA2InT6ZR/z9ypCY1fHb1BMrKyzd4eAAAAAMDHkJvACIJjWBoNEHay9MAlTWhcrdcS2X/hptlbAwAAAAD4IHITGEFwDEujAcIubqamS93QlZrg+PulR8zeGgAAAADAR5GbwAiCY1gaDRB20W3ePk1o3HT4WrmVnmX21gAAAAAAPorcBEYQHMPSaICwgw3Hr2pC4+CeS2TLqetmbw0AAAAA4MPITWAEwTEsjQaIwi7ldqY0GLJGExr3+u2A2VsDAAAAAPg4chMYQXAMS6MBorD7dvEhTWj8wuBVkpiWYfbWAAAAAAA+jtwERhAcw9JogCjMdp27IVV7aY+oWHk4zuytAQAAAAAsgNwERhAcw9JogCisbmdmSfMf1mtC4y5zdpu9NQAAAACARZCbwAiCY1gaDRC+KivbKWNWnZBGw9ZI/cGrpfkP6+WtsE3SYeo2+Tx8l/T4Zb8M/OOwjFp5XKZsPC2RO87Lkv2XZMPxq7L7/A0ZtOSwJjR++rsVci35ttkvDQAAAABgEeQmMILgGJZGA4QvSsvIkk9n7dQEv0bHb7svmP3SAAAAAAAWQm4CIwiOYWk0QPiahFsZ0nbCFq+Hxh9N2y5Op9PslwcAAAAAsBByExhBcAxLKVu2rGoEBQXRAOEzLiekSYtRG7weGj/eP0ou3Eg1++UBAAAAACyG4BhGEBzDUgiO4atOXkmSl75frRv8NhiyRl7/caM0HrZWnh24Uqr3WepxaFy11xL5ZRdHVAAAAAAA7h3BMYwgOIal0QDhC3aduyFPf7dCN/jtMHWbJN/O1DzmdmaWXEu+LWevpcjBiwmy5dR1WXHosvy2+4LM3HJWxq89KePWnJBd5+JNeEUAAAAAgMKA3ARGEBzD0miA9uJ0OiUr27fO+V19JE5q9VumGxr/N2KPpGdmm71FAAAAAIBNkZvACIJjWBoNsHDLznbK0cuJMmPzWfk8fJfUDV0pwT2XSP3Bq+X7ZUfkRFySqfubtyNGHumtf+xE6B+HJdvHQm4AAAAAgL2Qm8AIgmNYGg2wcMnKdsrBiwkyNfqM/HvmTnnGxfEPOUfrcdEya8tZuZmaXmD7dDqdMm7NCZd7mrzhdIHtBQAAAAAAV8hNYATBMSyNBmhtmVnZsv/CTZm84bR0nrFD6oQs9/hL4+4eNfosky/Cd8uao3GSmZV/x0NkZTul/+8HdffwaO+lsmAPX2QHAAAAAPAN5CYwguAYlkYDtJ6ktAyZvOG0dPx5uzwxIO9BsbtRb9AqGbz0iBy77N2jLNIysuTz8F26z/l4/yhZf/yqV58PAAAAAAAjyE1gBMExLI0GaC2JaRlSf/DqPAfCTYavlQ+nbZcaffS/jE5vvDk2WmZsPis3UowdZZGYliHtJm3RfY7nBq6UfTE3vfRTAgAAAADAO8hNYATBMSyNBmgt06LP3FNQ3GzkOun12wH5fe9FuZyQpqxzMzVdZm09J63Hb/J4rep9lsqns3bKsKijMnH9KZm7/bwsPXBJok9ckwMXEuTc9RS5mZouWTpfaBeXmCavjt6gu26jYWvkzLWUgvwxAgAAAADgEXITGEFwDEujAVrL15F73Ya7r4xaL/0WHpQ/9sfKlaS03BcUkZNXkmTIsqPy/KBVXjvq4skBy6XBkDXScsxGaTdpi8u7pF8bs9HjfQIAAAAAUNDITWAEwTEsjQZoLW+M3ag5Fzhk0SGJOnhJriffNrR2Zla2rDt2Rb6cu0dq9PX8KIu8jvcnb5WktAwv/WQAAAAAAPA+chMYQXAMS6MBWkd2tlNq9VMHuh2mbsuX50q4lSHh287J22GeH2VxL6PLnN1yOzMrX/YOAAAAAIC3kJvACIJjWBoN0Dpi4lM1Aey3iw/l+/Oeuposw6KOSoMha7wSGn+7+JBk65yDDAAAAACAryE3gREEx7A0GqB1rD4Spwlh524/X6B7SErLkIs3b8nh2ETZevq6LD90WebvjJEpG0/LDyuOSciiQ9I1cq/8a/oOafPTZnll1Hp5YfAqqdVvmdQfvFpmbTkrTiehMQAAAADAGshNYATBMSyNBmgdE9af0gTHO8/Gm70tAAAAAAAKLXITGEFwDEujAVrH1/P2aoLjhFS+XA4AAAAAgPxCbgIjCI5haTRA62g1LloVGj8/aJXZWwIAAAAAoFAjN4ERBMewNBqgNWRnO+Xx/lGq4PiDKVvN3hYAAAAAAIUauQmMIDiGpdEArSEmPlVzTEXIokNmbwsAAAAAgEKN3ARGEBzD0miA1rD26BVNcBy+7ZzZ2wIAAAAAoFAjN4ERBMewNBqgNUzacEoTHG8/E2/2tgAAAAAAKNTITWAEwTEsjQZoDd/M36cJjm+kpJu9LQAAAAAACjVyExhBcAxLowFaQ+vxm1Shcd3QVWZvCQAAAACAQo/cBEYQHMPSaIC+z+l0Su3+UarguP2krWZvCwAAAACAQo/cBEYQHMPSaIC+7+LNW5pjKvr/ftDsbQEAAAAAUOiRm8AIgmNYGg3Q9607dkUTHM/aes7sbQEAAAAAUOiRm8AIgmNYGg3Q903ZeFoTHG89fd3sbQEAAAAAUOiRm8AIgmNYGg3Q9/3fL/s0wfH15NtmbwsAAAAAgEKP3ARGEBzD0miAvu+tsE2q0Pi5gSvN3hIAAAAAALZAbgIjCI5haTRA3+Z0OuXJActVwfF7E7eYvS0AAAAAAGyB3ARGEBzD0miAvu1Swi3NMRV9Fx4we1sAAAAAANgCuQmMIDiGpdEAfduG41c1wfHMLWfN3hYAAAAAALZAbgIjCI5haTRA3zY1+owmON586prZ2wIAAAAAwBbITWAEwTEspWzZsqoRFBREA/RhPX/drwmOrybdNntbAAAAAADYAsExjCA4hqUQHFvLOz9tVoXGz3y3QpxOp9nbAgAAAADAFgiOYQTBMSyNBui7nE6n1AlZrgqO207YYva2AAAAAACwDXITGEFwDEujAfquuMQ0zTEVvRccMHtbAAAAAADYBrkJjCA4hqXRAH1X9IlrmuB4+qYzZm8LAAAAAADbIDeBEQTHsDQaoO/6edMZTXC86eQ1s7cFAAAAAIBtkJvACIJjWBoN0Hf1+u2AJji+kphm9rYAAAAAALANchMYQXAMS6MB+q53J2xWhcZPfbtCnE6n2dsCAAAAAMA2yE1gBMExLI0G6JucTqc89e0KVXDc5qfNZm8LAAAAAABbITeBEQTHsDQaoG+6kpSmOaai12/7zd4WAAAAAAC2Qm4CIwiOYWk0QN+0+eQ1TXA8LfqM2dsCAAAAAMBWyE1gBMExLI0G6JtmbD6rCY43nrhq9rYAAAAAALAVchMYQXAMS6MB+qY+Cw5oguPLCWlmbwsAAAAAAFshN4ERBMewNBqgb2o7cYsqNH4yZLk4nU6ztwUAAAAAgK2Qm8AIgmNYGg3QNz07cKUqOH47bJPZWwIAAAAAwHbITWAEwTEsjQboe64l39YcU9Hjl/1mbwsAAAAAANshN4ERBMewNBqg79ly6romOJ6y8bTZ2wIAAAAAwHbITWAEwTEsjQboe2ZtOasJjtcfv2r2tgAAAAAAsB1yExhBcAxLowH6nn4LD2qC49ibt8zeFgAAAAAAtkNuAiMIjmFpNEDf027SFlVo/MSA5eJ0Os3eFgAAAAAAtkNuAiMIjmFpNEDfUzd0pSo4/sf4TWZvCQAAAAAAWyI3gREEx7A0GqBviU9J1xxT0X3+PrO3BQAAAACALZGbwAiCY1gaDdC3bDt9XRMcT95w2uxtAQAAAABgS+QmMILgGJZGA/Qts7ee0wTHa49dMXtbAAAAAADYErkJjCA4hqXRAH3LgN8PaoLjCzdSzd4WAAAAAAC2RG4CIwiOYWk0QN/y/uStqtC4dv8ocTqdZm8LAAAAAABbIjeBEQTHsDQaoG+pN2iVKjhuPY73BAAAAAAAs5CbwAiCY1gaDdB33ExN1xxT0W3ePrO3BQAAAACAbZGbwAiCY1gaDdB37DgbrwmOJ64/Zfa2AAAAAACwLXITGEFwDEujAfqOOdvOa4LjNUfjzN4WAAAAAAC2RW4CIwiOYWk0QN8RsuiQJjiOiU81e1sAAAAAANgWuQmMIDiGpdEAfcc/p2xThcaP9YuS7Gyn2dsCAAAAAMC2yE1gBMExLI0G6DteGLxKFRy/OZb3AwAAAAAAM5GbwAiCY1gaDdA3JNzK0BxT8XXkXrO3BQAAAACArZGbwAiCY1gaDdA37DoXrwmOf1p3yuxtAQAAAABga+QmMILgGJZGA/QNEdvPa4LjVYfjzN4WAAAAAAC2Rm4CIwiOYWk0QN/w3eLDmuD43PUUs7cFAAAAAICtkZvACIJjWBoN0Dd0mLpNFRrX6rdMsrKdZm8LAAAAAABbIzeBEQTHsDQaoG948fvVquD49R83mr0lAAAAAABsj9wERhAcw9JogOZLTMvQHFPxVcQes7cFAAAAAIDtkZvACIJjWBoN0Hy7z9/QBMfj1540e1sAAAAAANgeuQmMIDiGpdEAzTdvR4wmOF5x6LLZ2wIAAAAAwPbITWAEwTEsjQZovtA/DmuC4zPXUszeFgAAAAAAtkduAiMIjmFpNEDzfTRtuyo0rtF3mWRlO83eFgAAAAAAtkduAiMIjuFVTqdTGjdurDSlgwcP5uvz0QDN12DIGlVw3HLMRrO3BAAAAAAAhNwExhAcw6vGjh0rDodD/Pz8CI5tIPl2puaYiv/M3WP2tgAAAAAAgJCbwBiCY3jNmTNnpGTJkvLaa69JcHAwwbEN7I25qQmOx605Yfa2AAAAAACAkJvAGIJjeIXT6ZTmzZtLqVKl5Pz58wTHNjF/Z4wmOI46eNnsbQEAAAAAACE3gTEEx/CKiRMnisPhkLFjx4qIEBzbxOClRzTB8amryWZvCwAAAAAACLkJjCE4zmdOp1NOnDghkZGR0qNHD2nevLmULVtW+T9tcHBwntZdtmyZtGvXTqpWrSrFixeXcuXKSb169SQ0NFSuXr3q3ReRi5iYGCldurS89NJLkp2dLSIEx3bR6eftqtC4Rp9lkpmVbfa2AAAAAACAkJvAGILjfNatWzfl/6B6416D49TUVGnTpo3bNR944AFZtmxZ/rwgHS1btpRixYrJ4cOHlT8jOLaHhkPXqILjV0dvMHtLAAAAAADgf8hNYATBcT776quvVKFuiRIl5Omnn85TcJydnS1vvPGG8tjy5ctL7969Zc6cOTJhwgRp0aKFcq148eKyadOm/Hth/zN9+nRxOBwSEhKi+nOC48Iv5Xam5piKLnN2m70tAAAAAADwP+QmMILgOJ9NmjRJunbtKrNmzZJDhw5JVlaWnD17Nk/B8ZQpU5TH1axZU2JjYzVzRo4cqcypUaOGZGRk6K714YcfSq1ate5pfPDBB6o1Ll26JH/5y1+kdu3akp6errpGcFz47b9wUxMcj1l1wuxtAQAAAACA/yE3gREExybIS3CcnZ0tlSpVUh63fft2l3Nfe+01Zd6UKVN05zRt2tTtcRd6o2HDhqo1WrduLUWKFJEtW7Zo1ic4Lvx+3XVBExwvO3DJ7G0BAAAAAID/ITeBEQTHJshLcLxu3TrlMY0aNXI7d/Xq1crcl19+2Qs71udwOKRkyZLStGlTzQgICBCHwyH16tWTpk2byvTp0/NlDzRA83y/7IgmOD55JcnsbQEAAAAAgP8hN4ERBMcmyEtw3KNHD+UxQ4YMcTs3MzNTSpUqJQ6HQ4oWLSopKSle2LXWvdytfPcZyN5CAzTPv6bvUIXG1fsslYysbLO3BQAAAAAA/ofcBEYQHJsgL8Fxy5YtlcesWbMm1/mNGjVS5u/YscPgju8dR1XkjdPpNHsLHms8bK0qOH5l1HqztwQAAAAAAHIobLkJChbBsQnyEhxXq1ZNecyZM2dynf/hhx8q82fPnm1wx/fOG8FxdHR0riMsLKxQNECn0ymztp6Tz8N3SXa274fHt9KzpGov9TEVX4TvNntbAAAAAAAgB4JjGEFwbIK8BMf333+/8pikpNzPkf3666+V+ePGjTO443vnjeD4Xr+8z6oNMDU9U7pG7lUC2LB1J83eUq4OXkzQnG88auVxs7cFAAAAAAByIDiGEQTHJshLcOzv7688JjMzM9f5ffr0UeZ///33Bnd87wiOPXMp4Za0GLVBFcBW67VENp+6ZvbW3Fqw54ImOF6y/5LZ2wIAAAAAADkQHMMIgmMT2CE49gY7HFWRlpElr/+4URPC1g1dKZcT0szenktDo45q9nw8Lvc74QEAAAAAQMEhOIYRBMcmsMNRFQWlMDTA89dTpU7Ick0Q2+anzZKRlW329nR1nrFTtddHey+V9Ezf3CsAAAAAAHZVGHITmIfg2AR2+HK8glJYGuCqw3Ga4Di45xIZ+Mdhs7emq+nwtap9Nv9hvdlbAgAAAAAAdyksuQnMQXBsgrwExy1btlQes2bNmlznN2rUSJm/Y8cOgzv2XYWpAQ7TOf4huOcSWXrAt84O3nzqmtaERkgAACAASURBVFTrpd7jZ7N3mb0tAAAAAABwl8KUm6DgERybIC/BcY8ePZTHDBkyxO3czMxMKVWqlDgcDilatKikpKR4Yde+qTA1wMysbHl/8lZNcFy7f5Scupps9vbk9NVkzREVd8YPK46ZvT0AAAAAAHCXwpSboOARHJsgL8Hx2rVrlcc0btzY7dzVq1crc5s1a+aFHfuuwtYAryXflhcGr9IEs6+MWi+p6bl/KWJ+uJmaLt8uPiSP9l6qGxoH91wia49dMWVvAAAAAADAtcKWm6BgERybIC/BcVZWljz00EPK47Zv3+5y7muvvabMmzx5spd27ZsKYwPceTZeN6TtGrlXnE5nge0jPTNbpkWfkae+XeEyMA7uuUT+NX2HZGUX3L4AAAAAAIBnCmNugoJDcGyCvATHIiKTJk1SHlerVi2JjY3VzBk5cqQyp3r16pKenu7FnZuvbNmyqhEUFFQoG+DU6DO6Ie2srefy/bmdTqesPBwnfxuxzm1g/MLgVfLLrguSTWgMAAAAAIBPIjiGEQTH+ezm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\" width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pkl_file = open('data/ffast.pkl', 'rb')\n",
    "ffast = pickle.load(pkl_file)\n",
    "pkl_file.close()\n",
    "\n",
    "K_M5 = []\n",
    "ele_K_M5 = []\n",
    "L3_M1 = []\n",
    "ele_M3_M1 = []\n",
    "L1_N3 = []\n",
    "ele_L1_N3 = []\n",
    "L3_N5 =[]\n",
    "ele_L3_N5 = []\n",
    "L2_M4 = []\n",
    "ele_L2_M4 = []\n",
    "for element in range(1,93):\n",
    "    if 'K-M5' in ffast[element]['lines']:\n",
    "        K_M5.append(ffast[element]['lines']['K-M5']['weight']/ffast[element]['lines']['K-L3']['weight'])\n",
    "        ele_K_M5.append(element)\n",
    "    if 'L3-M5' in ffast[element]['lines']:\n",
    "    \n",
    "        if 'L3-M1' in ffast[element]['lines']:\n",
    "            L3_M1.append(ffast[element]['lines']['L3-M1']['weight']/ffast[element]['lines']['L3-M5']['weight'])\n",
    "            ele_M3_M1.append(element)\n",
    "        \n",
    "        if 'L1-N3' in ffast[element]['lines']:\n",
    "            L1_N3.append(ffast[element]['lines']['L1-N3']['weight']/ffast[element]['lines']['L3-M5']['weight'])\n",
    "            ele_L1_N3.append(element)\n",
    "        \n",
    "        if 'L3-N5' in ffast[element]['lines']:\n",
    "            L3_N5.append(ffast[element]['lines']['L3-N5']['weight']/ffast[element]['lines']['L3-M5']['weight'])\n",
    "            ele_L3_N5.append(element)\n",
    "        \n",
    "        if 'L2-M4' in ffast[element]['lines']:\n",
    "            L2_M4.append(ffast[element]['lines']['L2-M4']['weight']/ffast[element]['lines']['L3-M5']['weight'])\n",
    "            ele_L2_M4.append(element)\n",
    "    \n",
    "ele = np.linspace(1,94,94)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(ele_K_M5 ,K_M5, label = 'K-M$_3$ / K-L$_3$')\n",
    "plt.plot(ele_M3_M1,L3_M1, label = 'L$_3$-M$_1$ / L$_3$-M$_5$')\n",
    "plt.plot(ele_L1_N3,L1_N3, label = 'L$_1$-N$_3$ / L$_3$-M$_5$')\n",
    "plt.plot(ele_L3_N5,L3_N5, label = 'L$_3$-N$_5$ / L$_3$-M$_5$')\n",
    "plt.plot(ele_L2_M4,L2_M4, label = 'L$_2$-M$_4$ / L$_3$-M$_5$')\n",
    "plt.ylabel('')\n",
    "plt.gca().set_yscale('log')\n",
    "plt.xlabel('atomic number')\n",
    "plt.ylabel('relative weights of lines')\n",
    "\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'K-L3': {'weight': 1.0, 'position': 7478.100000000001}, 'K-L2': {'weight': 0.514, 'position': 7460.9000000000015}, 'K-M3': {'weight': 0.14, 'position': 8264.7}, 'K-M2': {'weight': 0.078, 'position': 8264.7}, 'K-M5': {'weight': 0.00027, 'position': 8329.2}, 'L3-M5': {'weight': 1.0, 'position': 851.1}, 'L3-M4': {'weight': 0.0963, 'position': 851.1}, 'L3-M1': {'weight': 0.0904, 'position': 742.9000000000001}, 'L2-M4': {'weight': 0.029, 'position': 868.3}, 'L2-M3': {'weight': 0.000597, 'position': 803.8}, 'L2-M1': {'weight': 0.015, 'position': 760.1}, 'L1-M3': {'weight': 0.00122, 'position': 940.0}, 'L1-M2': {'weight': 0.00758, 'position': 940.0}}\n"
     ]
    }
   ],
   "source": [
    "print(ffast[28]['lines'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Characteristic X-ray Intensity\n",
    "\n",
    "The cross section $Q_I$ (probability of excitation expressed as area) of an isolated atom ejecting an electron bound with energy $E_c$ (keV) by an electron with energy $E$ (keV) is:\n",
    "\n",
    "$$Q_I \\left(\\frac{ionizations}{e^- (atoms/cm^2)} \\right) =  6.51 \\times 10^{-20} \\left[ \\frac{n_s b_s}{E E_c}\\right]\\log_e (c_s E / E_c) $$\n",
    "\n",
    "where:\n",
    "- $n_s$: number of electrons in shell or subshell $s$\n",
    "- $b_s$, $c_s$: constants for a given shell $s$\n",
    "- $E$: energy of the exciting electron\n",
    "- $E_𝑐$: Critical ionization energy\n",
    "\n",
    "For example for a K shell (Powell 1979): $n_K = 2$, $b_K = 0.35$, and $c_k = 1$\n",
    "\n",
    "For silion the characteristic energy or binding energy for the K shell: $E_c = 1.838$ keV$\n",
    "\n",
    "The relationship between energy of the exciting electron and critical energy is important and is expressed as **overvoltage** $U$:\n",
    "$$U =\\frac{E}{E_c}$$\n",
    "\n",
    "\n",
    "\n",
    "The overvoltage of the primary electron with energy $E_0$ is expressed as:\n",
    "$$ U_0 =\\frac{E_0}{E_c}$$\n",
    "\n",
    "We can express the cross section with the overvoltage:\n",
    "\n",
    "$$Q_I  =  6.51 \\times 10^{-20} \\left[ \\frac{n_s b_s}{U E_c^2}\\right]\\log_e (c_s U) $$\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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AAAIOz/88IOuv/56n2Fm586ddeHCBbdtjBo1ytRr2rSp0tLS3NYbPXq0qXfTTTd5rHf69Gk9+uijfoWsM2bMcLk/2MFxWlqa4uLi/LqvY8eOSk1NdelTXgfHBw8e1I033uiz7W7duunSpUse23F+737//Xfdc889XtsbNWqUx7ZyauLEiUpISPD6vPj4eM2aNctjG87B8b59+/TSSy95be/RRx91++WDs8OHD6tly5Y+39tWrVrpt99+c9vGlcHxqlWrbAeweQp9HQ6Hevfu7fW5bdq00blz5zy2kZGRoRo1asiyLBUvXlynTp3y+bN48sknTXtLlizxWd+d9PR0lSpVSpZlqV69ej7r+xMcjxkzRkWLFjXB7JYtW9zWO3XqlB588EGfP7Mbb7xRBw8edNtGamqqSpYsaeru2rXL52t47rnnTP1XXnnFa12Hw2Ha9+f9AQAABRvBMQAACCvffPONCXayQ98333xTs2fP1ty5czVo0CDVrl3bXL///vs9rtB84IEHTL2+ffu6XL9yZfJPP/3ktp3Tp0+bPVEty1JsbKyeeOIJTZw4UfPnz9eMGTPUv39/3XbbbSpSpIjb7R48BccHDx7UokWL9MILL5j2X3jhBS1atMilnD9/3tx38eJFWZalChUq6PHHH9fw4cM1c+ZMLVy4UNOmTdOLL76oihUrmjY7d+7s0qfcPtuf4PjYsWOqWrWqqVepUiW99tprmj17tmbMmKFnn33WrNC0LEvt2rXz+HPMfu+qVq2qVq1aybIs3XLLLRo5cqTmzZunKVOm2FaNFy1aNCgrjwcNGmTaLFasmDp16qTx48dr/vz5mjZtmnr06GEL71NSUty24xwcZ692rV69ugYMGKDZs2dr1qxZeu6552zvx/Dhwz3265dffrG9t/Xq1dPAgQOVnJysefPmafjw4WrcuLEtiLx48aJLO87BcfPmzc2/uw4dOmj8+PGaN2+exo4dq4EDB9ru69Onj+297ty5s6ZMmaKUlBQNHTpUdevWlWVZevzxxz0Gx5I0bNgwc/29997z+rP47bffzPtTs2ZNORwOr/U9Wbdune0LC1+8BceZmZnq16+fuX7ttdd6/OuGM2fO2OaQ6tWrq1+/fpoxY4bmz5+vpKQk3XHHHeZ6zZo1dfLkSbdtPfvss6beP/7xD6/9v3jxoq6++uocBc3OX8zs3bvXZ30AAFBwERwDAICwceHCBdWpU0eWZSk6OlrTpk1zW+/SpUvq0qWLCTemTJnitt5vv/2matWqmXqLFy82186cOWOeZVmW5syZ47FfjzzyiKl3ww036MCBAx7r7tq1Szt27HD5756C42w53Wc4IyNDn332mdcALTU11bbCccOGDUF5tj/BsfNzW7ZsqdOnT7vU2bFjhy3cHjt2rNu2st+77DJy5Ei39d58801T58EHH/T5OrxZsWKFihQpIsuy1KBBA/34449u6+3cudMcKHbVVVe5Dfucg2PLyloB7m6l/Jo1axQVFWVWrrpb/Z6ZmanmzZubtoYOHep2DDgcDr3yyium3pXhr2QPji3LUlxcnJYuXer1fdm4caN5X+Lj491uhXLp0iV16tTJ1ra74Pj48ePmi5tGjRp5fe4777xj2nrrrbe81vVm5MiRpp0JEyb4rO8pOE5LS7PNQbfccotOnDjhsR3n9+P555/3+JcN7777rqmXvX3Ilf7v//7P1KlYsaLX1emzZs2yfTngj4EDB5p7vK2kBwAABR/BMQAACBvjxo0zgcW//vUvr3XT0tJUq1YtWZal+vXre6y3bt06E8aVLVtWP//8sySpc+fO5ll//etfPd6/detWU69ChQo6fvx4rl5bsINjf50+fVrx8fGyLEs9e/YMyrN9Bcfff/+9uV6mTBmvgdqKFStM3WrVqnndHzp7xa4nGRkZZiVu8eLFfW734M3NN99s2tm3b5/Xup9//rnXlcLOwXHdunXdrv7N5jwu3a2aXrx4sbneu3dvn68jO2QuVaqUy3YgVwbHngJ5Zw8//LCp721LkAsXLph/n56CY0m2Vcnr1q1zWyczM9OsYo6JidGxY8d89tOT7BXflmV53f87m7vg+PTp07r77rvNf2/fvr1tRf6Vtm/fbur6szdzdsgcHR3tcf9s5xXl3vayzl6hb1mWPvzwQ5/Pluxhc2Jiol/3AACAgongGAAAhI2mTZualYzu9uS9Uv/+/U3A4W0VsPNK1JYtW2rixInmfzdq1Mhr6OO8jcOIESNy9bqk0AXHknTbbbfJsixdf/31QXm2r+B4yJAh5vqrr77qs73skNayLK1fv97lunNwvH37dq9tOQeDu3fv9vlsd3bs2OFz1eeVKleuLMuydPfdd7tccw6OR48e7bUd58PPJk+e7HK9Y8eO5vqVhyW68/7775v6X375pe2ac3AcFxens2fPem3r0qVLtgPgfP0bdV7d6yk4dj7w7sknn3RbZ+XKlabOY4895vWZvrRo0cLvsSS5Bsc///yzbf/1nj17ej3MTrJv7eFufF/ps88+87nid8yYMaZOhw4d3NbZu3evWR1esmRJv+ZUKevAxWC93wAAILIRHAMAgLBw5swZc8BUnTp13O6ze2VxPqBr2bJlHtt2OBxuD1QrXry4vv/+e6/9atKkianvabsCf+RVcHz06FG98847atOmjapXr64SJUq4vM7scvXVVwfl2b6C43bt2pnrq1ev9tneP//5T1P/nXfecbme/d7Fx8d73Ac522uvvWba+uqrr3w+253x48fbgkF/xmK9evVkWVlbB1zJOTjevHmz12cvX77c6+rl7MPrSpYs6Ve/3njjDdPepEmTbG05B8fNmjXz+b5s3rzZ1G/durXP+l9//bXP4Fj6499YbGys24P8nA+l9Gc8edOwYUPT1qFDh3zWdw6Od+zYYdv6ZvDgwX4984YbbjD3zJs3z+fPbOzYsaa+uy1GJOnkyZMmxPe0Mtl5y4levXr51Vcp5z9nAABQcBEcAwCAsOC8vUFuiq+9OI8cOaLy5cvb7vG0N7KzMmXKmHAmEHkRHE+ZMkUJCQl+v0dFixYNyrN9BcfOQdnhw4d9tpecnGzqv/TSSy7Xs9+76tWr+2zL+UC7NWvW+KzvjvOBZzkt7saJc3Ds67Axb+9tampqQP9Ghg0bZmvPOTju1KmTz/dl0aJFOQoiT58+7VdwPHnyZFMvKSnJdu3YsWOKiYmRZXnfksZf11xzjXnWqVOnfNZ3Do6zDw+MiorS1KlT/X6m8+F0OS3etiNx3mP5yq19HA6HLeT29YWFs127dpn7/PlCAQAAFFwExwAAICxs2LAhoFDMV+B58eJF25+Yx8fH+7VXanR0tAmNAhHs4HjBggW213/rrbcqMTFRkyZN0ty5c20rGK+77jpTLxjP9hUcOx866O5QvCs5B5LPPvusy3Vf752zYATHzz77bEBj8UrOwbGv7SW8vbe//PJLQP26sj3n4NifLTmcA/6+ffv6rJ+enu5XcJyamqqrrrpKlmWpXr16tlXlb731lmnD257K/nJecXzw4EGf9Z2D4+zV/EWKFPF4kKM72dtF5KZ423/deQuPK0N15+0mGjdu7HdfJfvhe6w4BgCgcCM4BgAAYeGbb74xYUWbNm2C3v5zzz3nEsrcd999Prc+CNcVx9mHhUVFRWnRokVe6zrvIRyMZ4dqxXF+Bcd9+/Y1bcydOzdXbTgLVnDsvII3GKtvcxoc59WKY0l6/vnnTd3sQ+scDoc5YC8uLk6///67Py/LK+c9jv/73//6rO8cHG/YsMEE3JblflsVd7L/KiAhISHQ7ttkZmbaVlA775/svBf2mDFjctSu8x7L7HEMAEDhRnAMAADCwq+//mrCiqpVqwa17X//+9+m7Vq1atmCVHf7yDpzDkHDZY/jffv2mbqPPPKIz2dn74ubX8Gx8x7H/oS3/u5xnF/BcVJSkmnD0x6zORGs4FiSSpYsKcuyVKxYMa+HOvojp8FxXu1xLEk//PCDqZu9bYZzgOnvIYW+OB+euHLlSp/1rzwcb/PmzSpdurT5b0OHDvXZRoMGDfz++efUsGHDTNs9evSQlDWXFitWTJaVtW/0yZMnc9Sm8xc5iYmJQe0vAACILATHAAAgbDhvJZHbg82udODAAbPHaHR0tL766ivt3bvXrBzM/m+evPjii6ZPV+4jmhO+ws+PPvrIPOfDDz/02tamTZtM3VdffdVrXeewz1NwnJNnS77DzSFDhpjrr732ms/2brnlFrerJrPld3C8bds200bDhg19rkr3JZjB8QMPPBC01dA5DY4vXbpkAskSJUr4DK5Hjhzpd3AsSa1atZJlWYqJidGxY8fUoUOHoM8HI0aMMG36s93ElcGxJG3fvt32Zczrr7/utQ3nQzz9XaXsr8OHDysqKsr8TM6dO6dRo0aZ53Xp0iXHbfbv39/c72vveAAAULARHAMAgLDhvNKzZcuWSk9PD6i99PR03XHHHW6D33nz5tlWIXs6KMs5RKxQoYKOHz+eq774Cj+dV0X7CrS+/fZbv1YcZ2Zmqk2bNj6D45w8W/Idbu7cudNcL1u2rH777TePbX3xxRembrVq1dz+zPM7OM7MzNSf/vQn087kyZNz1U62YAbHCxcuNNfr1auns2fP5rpfOQ2OJenhhx8293jbc/jChQtmmwl/g2Pnfbv//ve/m0C0SZMmfr4i39auXWue8cQTT/is7y44lrIO86xUqZK51q9fP49tOO8ZXL58eR09ejTg1+HM+cuEqVOn2r6A++KLL3LcXnaAb1m+D3MEAAAFG8ExAAAIGxcuXLAdrPbwww97DHSlrD1Qly9f7vHPxV999VXT1p///GeXlaO9evUy1zt27OjxOY8++qipd+ONN+rAgQMe6/7444/asWOHy3/3FX5u377d7xDv8uXLZsuC6OhobdiwwaVOenq6/v73v9tCY0/BcU6eLfkONyXpL3/5i6lz991368yZMy51du7cqcqVK5t648aNc9tWfgfHkrR8+XJzqFmxYsU0ZcoUr/V///13jRo1ym1QF8zgODMzU82bNzd1WrRooV9++cVrmxs3bnQbbOYmON6wYYN5X+Lj47V69WqXOmlpaerUqZNt3PkTHKenp6tq1aouYzbQ4N7Z5cuXzV8bXHPNNT7rewqOpax/6879feGFFzyuTn/sscdMveuvv167d+/2+txvvvlGvXv39us1ffzxx6btKlWqmP+7du3aOV4t73A4zNxSt27dHN0LAAAKHoJjAAAQVn744QeVLVvWhB9XXXWVnnnmGU2ePFkLFixQcnKy3nnnHT355JOqUKGCLMv9fqsrVqwwAVelSpXcrhS+cOGCbXXexIkT3fbp9OnTatSokakXGxurJ554QhMnTtSCBQs0c+ZMvf7662revLmKFCnidp9gX+Fnenq6WcEYHR2tl19+WQsXLtSyZctMuXDhgqn/2muvmf5ER0frmWee0QcffKC5c+dqyJAhqlevnizLUuPGjX0ejpfTZ/sTHB87dswWqlWuXFkDBgzQnDlz9NFHH6lXr16KjY0119u1a+cx5ApFcCzZtzWwLEvXXXedBg4cqJkzZ2rBggWaNm2aBgwYoHvvvVcxMTGyLEvJycku7QQzOJako0ePqnbt2rbx+Pjjj2vcuHGaP3++Zs+erdGjR+uZZ55RjRo1ZFmW6tSp49JOboJjSerTp4+5r2jRourcubOmTp2qlJQUDRs2zBzc2KVLF1OvVatWfrU9ePBg23tesmRJnTt3zu+++ePJJ5807R86dMhrXW/BsSTt3bvXjE/LstSzZ0+34/jcuXO66aabTL2oqCg99NBDGj16tFJSUjR37lyNGzdOvXv3Nv92Y2Nj/Xo96enpti9gsos/+y9facuWLeZ+f7aZAQAABRvBMQAACDsHDhxQixYtXIIQT+XK0Ovo0aOqWLGiCba8/bn2zp07FR8fL8uyFBcXp++++85tvVOnTtlW0XorH330kcv9/oSf06dPN2G3u+IcOqalpal9+/Ze+3HDDTfowIEDPsOvnD7bn3BTyvo53njjjT7fr65du+rSpUse2wlVcCxJKSkptv1svZXY2FgtW7bMpY1gB8eS9Ntvv/k9Hi3L/Yrf3AbHDofDtlrfXWnTpo1OnTpl/veDDz7oV9tHjhxRdHS0uc/fVbc54bw9yujRo73W9effzsGDB3Xttdfa3kuHw+FS7/z58+rRo4eKFi3q18/MXdjvifMXSdnB9M8//+z3/dkSExNNG7t27crx/QAAoGAhOAYAAGFr9erV6t27txo3bqwyZcooKipKCQkJqlu3rh588EGNGDFCO3futN3jcDh07733mvCjf//+Pp8zbdo0U79hw4ZeD/3auHGjevfurUaNGqlUqVKKiopSqVKldOONN6p3795avny529DI3/BzzZo16tSpk2rXrq3ixYt7DG+lrG0LPvroI7Vq1UqlS5dWTEyMKleurFatWmnSpElKS0uT5F/4lZNn+xtuSlk/jzlz5ujhhx9W9erVFRsbq4SEBNWrV0/PPvusNm3a5PV+KbTBsZQV+E2aNEkPPfSQatasqRIlSig6OlplypRR06ZN9cwzzyg5Odnjtip5ERxn27Ztm/r27aumTZuqXLlyio6OVnx8vGrVqqW2bdtqyJAh2rJli9t7cxscZ1u1apUeffRRValSRcWKFVOlSpV07733Kjk5WZmZmTp69Khpv0ePHn636/xlwzfffJPjfvmSmZlp/oLA1/7J/v7bOXLkiBo2bGjqdunSxeMe7bt379Zrr72m22+/XRUqVFBMTIyKFy+uatWqqXXr1howYIDWrl2bo20m9uzZY/vi5/777/f73mwZGRlmqwt3f8UBAAAKH4JjAAAAAEHnvPfumDFj/Lpn7969JgC944478qxv06dPN33buHFjnj0nkjgfkrlixYpQdwcAAIQBgmMAAAAAQde6dWsTRHraAuZK/fr1M/e42y86WDIyMtSgQYMcbaNR0N16662yLEt33nlnqLsCAADCBMExAAAAAL8dPHhQe/fu9Xg9PT3ddoBey5Yt/Wr3559/VkJCgizLUpUqVcxWK3nl008/lWVZKlKkiLZt25anzwp3S5cuNe/F5s2bQ90dAAAQJgiOAQAAAPht8eLFKlq0qO644w71799f06dP18KFCzVjxgz169fP7EltWZaKFy/usg+5s2XLlumzzz7T+PHjdc0115j7Jk+enC+vpUOHDrIsS3fffXe+PC8cORwONW7cWJZlqVevXqHuDgAACCMExwAAAAD8tnjxYtvBiZ5K5cqVfe4f7O6+tm3b5uhgOAAAAOQNgmMAAAAAfktNTdWCBQvUs2dPNWnSRFWrVlVcXJzi4uJUtWpVtW/fXhMmTNCFCxd8tpUdFsfHx+v666/XyJEjdfHixXx4FQAAAPCF4BgAAAAAAAAAYENwDAAAAAAAAACwITgGAAAAAAAAANgQHAMAAAAAAAAAbAiOAQAAAAAAAAA2BMcAAAAAAAAAABuCYwAAAAAAAACADcExAAAAAAAAAMCG4BgAAAAAAAAAYENwDAAAAAAAAACwITgGAAAAAAAARrsG4wAAAKFJREFUANgQHAMAAAAAAAAAbAiOAQAAAAAAAAA2BMcAAAAAAAAAABuCYwAAAAAAAACADcExAAAAAAAAAMCG4BgAAAAAAAAAYENwDAAAAAAAAACwITgGAAAAAAAAANgQHAMAAAAAAAAAbAiOAQAAAAAAAAA2BMcAAAAAAAAAABuCYwAAAAAAAACADcExAAAAAAAAAMCG4BgAAAAAAAAAYPP/AJReweV28DW+AAAAAElFTkSuQmCC\" width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_K = 2.0\n",
    "b_K = 0.35\n",
    "c_K = 1.0\n",
    "\n",
    "# Silicon\n",
    "E_c_Si = 1.838 \n",
    "# Iron\n",
    "E_c_Fe = 6.401\n",
    "\n",
    "E = np.linspace(0,30,2048)+0.05\n",
    "U = E/E_c_Si\n",
    "\n",
    "Q_Si = 6.51*1e-20*n_K*b_K/(U * E_c_Si**2)* np.log(c_K * U)\n",
    "U = E/E_c_Fe\n",
    "Q_Fe = 6.51*1e-20*n_K*b_K/(U * E_c_Fe**2)* np.log(c_K * U)\n",
    "plt.figure()\n",
    "plt.plot(E,Q_Si, label ='Si')\n",
    "plt.plot(E,Q_Fe, label ='Fe')\n",
    "\n",
    "plt.ylim(0.,Q_Si.max()*1.1)\n",
    "plt.xlabel('excitation energy (keV)')\n",
    "plt.ylabel('Q (inizations/[e$^-$ (atoms /cm$^2$)])')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[C.J. Powell,\"Cross sections for inelastic electron scattering in solids\", Ultramicroscopy **28** pp 24-31 (1989)](https://doi.org/10.1016/0304-3991(89)90264-7)\n",
    "\n",
    "[E. Casnati, A. Tartari, and C. Baraldi; J. Phys. B: At. Mol. Phys..li (1982) 155-167: *An empirical approach to K-shell ionisation cross section by electrons*](https://doi.org/10.1088/0022-3700/15/1/022)\n",
    "\n",
    "\n",
    "[D. Bote  and F. Salvat \"Calculations of inner-shell ionization by electron impact with the distorted-wave and plane-wave Born approximations\",Phys. Rev. A 77, 042701](https://doi.org/10.1103/PhysRevA.77.042701)\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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FBT4uoklGrkJzCA4hl+jAwQAAAAAoPiKXXtQNzTuNnO75OUTGnsbuQnMIDiGX6MDBAAAAACgeFq845huaPzC5M1yJSfP1827LpCbwAyCY/g1OkAAAAAAAIqfzb+fkXqDVtqFxq3GbpBzmdm+bt51g9wEZhAcw6/RAQIAAAAAULz8ln5BGo9YYxcaNxn1rRw9e8nXzbuukJvADIJj+DU6QAAAAAAAio//XbgiD0el2YXGDYaukl1Hz/u6edcdchOYQXAMv0YHCAAAAABA8XApO1faT9pkFxrXHvi1fLP3lK+bd10iN4EZBMfwa3SAAAAAAAD4Xl5+gbw3c7vuYnjJmw75unnXLXITmEFwDL9GBwgAAAAAgO998dU+3dB4xPK9vm7adY3cBGYQHMOv0QECAAAAAOBbqT8c0g2N352xXfLyC3zdvOsauQnMIDiGX6MDBAAAAADAd9buS5c6A+1D4/aTNsml7FxfN++6R24CMwiO4dfoAAEAAAAA8I3dxzKk4dDVdqHxw1Fp8r8LV3zdPAi5CcwhOIZfowMEAAAAAODaO3bukjQN/9YuNG48Yo0cTL/g6+bh/5GbwAyCY/g1OkAAAAAAAK6tf67kSOvY7+xC43qDVsoPv5/xdfOgQW4CMwiO4dfoAAEAAAAAuHayc/Olc9KPuovhLdp+1NfNgw1yE5hBcAy/RgcIAAAAAMC1UVBQIJ8s2qUbGo/75ldfNw//x96dR9lRkAn/514IsoQd1JkRCbsgi8qgjLwzjIA4DuIyiOi8RkFHthdBhIFsEMKigAkiiAZIZIshbGaMZCOELJDEYIAkQBIgOySBLGRPJ9197/P7wx93iF3d6XR1d3V1fz7n1B/erlv1NIc85+TL9VYC3YQ0hGNyzQIEAACA1nHnM28kRuPLH3kpyuVy1uORQDchDeGYXLMAAQAAoOUNfentxGh8Tv/JsbmmNuvxqIduQhrCMblmAQIAAEDL+vO8lXF4jxF1ovEX+o6L1Ru3ZD0eDdBNSEM4JtcsQAAAAGg5c5evj+OuH10nGn/mhqdj0cqNWY/HNugmpCEck2sWIAAAALSMles3xz/f+mydaHxEzxHx4qL3sh6PRtBNSEM4JtcsQAAAAGh+VdW18fW7n68Tjbt0eypGzFya9Xg0km5CGsIxuWYBAgAAQPMqlcpx0cPTEh+Gd++EeVmPx3bQTUhDOCbXLEAAAABoXj8bPisxGvccOjPK5XLW47EddBPSEI7JNQsQAAAAms9DUxYmRuPzfjc1ampLWY/HdtJNSEM4JtcsQAAAAGgez85+Nw7uVjca//uvJsaGzTVZj0cT6CakIRyTaxYgAAAApPfK22viqGtH1onGJ/3smXhnbVXW49FEuglpCMfkmgUIAAAA6Sxdsyk+e/OYOtH4k9eNillL12Y9HinoJqQhHJNrFiAAAAA03bqq6vjSLyfUicaHdB8eE15fnvV4pKSbkIZwTK5ZgAAAANA01bWl6DpwauLD8AZPXZT1eDQD3YQ0hGNyzQIEAACA7Vcul6PbkzMSo/EtI2dnPR7NRDchDeGYXLMAAQAAYPv9ZtzcxGj8/37/YpRK5azHo5noJqQhHJNrFiAAAABsnz/NWJIYjc/+zaSoqq7NejyakW5CGsIxuWYBAgAAQOP9ZcGqOLzniDrR+JTbno1VG7ZkPR7NTDchDeGYXLMAAQAAoHEWrNgQn+ozuk40/lSf0TF/xYasx6MF6CakIRyTaxYgAAAAbNuqDVvilNuerROND+85Iv6yYFXW49FCdBPSEI7JNQsQAAAAGlZVXRtn/2ZS4vcaD5u+JOvxaEG6CWkIx+SaBQgAAAD1K5XKcenglxKj8d3j3sx6PFqYbkIawjG5ZgECAABA/W4dOTsxGnd7ckaUy+Wsx6OF6SakIRyTaxYgAAAAJHtk6qLEaPzdAX+O6tpS1uPRCnQT0hCOyTULEAAAAOqa8PryOKT78DrR+Eu/nBDrqqqzHo9WopuQhnBMrlmAAAAAsLXZy9bGJ68bVScaf/bmMbFk9aasx6MV6SakIRyTaxYgAAAA/K931lbFST97pk40PurakfHK22uyHo9WppuQhnBMrlmAAAAA8FcbNtfEv/9qYp1ofHC3p+LZ2e9mPR4Z0E1IQzgm1yxAAAAAiKipLcX597+Q+DC8h6YszHo8MqKbkIZwTK5ZgAAAAHR05XI5eg19JTEa3zx8VtbjkSHdhDSEY3LNAgQAAKCju2/ivMRofNHD06JUKmc9HhnSTUhDOCbXLEAAAAA6shEzl0aXbnWj8dfvfj6qqmuzHo+M6SakIRyTaxYgAAAAHdVLi96LI3qOqBON//nWZ2PF+s1Zj0cboJuQhnBMrlmAAAAAdESLVm6Mz9zwdJ1ofNz1o2Pu8vVZj0cboZuQhnBMrlmAAAAAdDSrN26JL/QdVycaH95jRPx53sqsx6MN0U1IQzgm1yxAAAAAOpLNNbXxrf6TEx+GN/Slt7MejzZGNyEN4TjHXnjhhfj1r38d5513Xpx44onRpUuX6Ny5c3Tq1Cn233//OPnkk6N79+4xZ86cZr/3/Pnzo1u3bnHcccfF3nvvHbvttlscdthh8cMf/jAmTZrU7PerjwUIAABAR1Eul+MnQ15OjMZ3PvNG1uPRBukmpCEc59juu+9e+cPf0LHjjjvGT3/606itbZ6nqQ4cOLDBexcKhfjxj38cpVKpWe7XEAsQAACAjqLf068nRuMrH5se5XI56/Fog3QT0hCOc2z33XeP/fbbL/793/89rr766rj99ttj8ODB8cgjj8Rtt90WX/ziF7cKuj/84Q9T3/ORRx6JQqFQCcTnnHNODBgwIB5++OG47LLLonPnzpX7XXrppc3wWzbMAgQAAKAjeGjKwsRo/J/3TYktNS3/wS3ySTchDeE4x2bOnLnN/6I4atSo+NCHPlRZEi+88EKT77dy5crYa6+9KtH4scceq3POrFmz4oADDqjcb/z48U2+X2NYgAAAALR3//Py29GlW91ofHq/8bFmU3XW49GG6SakIRx3AJdeemllSVx33XVNvk63bt0q17n44ovrPe/RRx+tnHfyySc3+X6NYQECAADQno2d/U4c2n14nWj8jzeNibfe25j1eLRxuglpCMcdQP/+/StL4oILLmjydbp06VK5zty5c+s9r1Qqxcc//vHKuYsWLWryPbfFAgQAAKC9mjJvZRzRc0SdaHzMdaPilbfXZD0eOaCbkIZw3AFcddVVqT9xPGvWrMo1jjzyyG2ef8EFF1TO79+/f5Pu2RgWIAAAAO3RzLfWxCevG1UnGh/Za0S8sGBV1uORE7oJaQjH7dyUKVNi9913r3wv8YwZM5p0nSFDhlQWTdeuXbd5/oABAyrnX3LJJU26Z2NYgAAAALQ3b767Pj59w9N1ovGh3YfHs3PezXo8ckQ3IQ3huJ2YNGlSDB06NIYOHRqPPvpo3HHHHfH1r389isViJRrfcsstTb5+nz59tutTy2PHjq2cf9pppzX5vttiAQIAANCevPXexjjpZ8/UicZduj0Vw6YvyXo8ckY3IQ3huJ047bTTKovgb4/Pfe5z8ac//SnV9a+44orK9e68885tnj9jxozK+SeccEKT7vncc89t87j77rstQAAAANqF5es2xym3PVsnGh90zVMxeGrLPT+I9ks4Jg3huJ2oLxwfcMABce2118a8efNSXf9HP/pR5Zr33XffNs9/4403KucfccQRTbpnfSG8vsMCBAAAIK/WbKyOf7tjYmI0/u34+h9QDw0RjklDOG6HNm7cGK+99lr07ds3PvKRj8QOO+wQu+22WwwZMqTJ1xSOAQAAoGVs3FIT37j7+cRofMvI2VmPR44Jx6QhHLdzK1asiKOPPrryPcdPP/10k67jqyoAAACg+W2uqY3vDvhzYjTu8YeZUS6Xsx6RHBOOSUM47gDGjx9fWRInnXRSk67h4XgAAADQvGpL5bh40LTEaHzp4JeitiQak45uQhrCcQdQLpejc+fOscMOO0SxWIyNGzdu9zWGDBlSWTRdu3bd5vkDBgyonH/JJZc0ZexGsQABAADIo3K5HFc/PiMxGp/3u6lRXVvKekTaAd2ENITjDuKjH/1oZVEsXbp0u98/a9asyvuPPPLIbZ5/wQUXVM7v379/U0ZuFAsQAACAvCmXy3HTU68lRuNzfjs5Nm2pzXpE2gndhDSE4w5gzZo1seOOO1a+53jLli1Nus5BBx1UWTZz59b/RNdSqbTVuQsXLmzq6NtkAQIAAJA3d419IzEan3nnxFhbVZ31eLQjuglpCMcdwG233VZZEp/97GebfJ1rrrmmcp2LL7643vMeffTRynmf//znm3y/xrAAAQAAyJMHJy9IjMan9h0XK9dvzno82hndhDSE45z6zW9+E2PHjt3m01UHDBgQnTp1qiyJhx9+uM45CxYsqPx8hx3q/1dixYoVseeee1Y+ufz444/XOWf27Nnx4Q9/uHKtsWPHbv8vtx0sQAAAAPJi6EtvJ0bjz/98bCxZvSnr8WiHdBPSEI5z6vvf/37ssMMO8bGPfSzOO++8uP3222PQoEHxxBNPxMCBA+Oqq66KT3ziE1sF4e9+97uJ12psOI6IGDRoUBQKhUo8/ta3vhUDBw6MQYMGxeWXXx577LFHoz6V3FwsQAAAAPJgzGvvxCHdh9eJxifc+HTMX7Eh6/Fop3QT0hCOc+r9cNyYY9ddd42bbropSqXkJ7JuTziOiLj33ntjt912a/Cel1xySdTWtvyX+VuAAAAAtHWT566Mw3uOqBONj+k9Kl5bsjbr8WjHdBPSEI5zav369TF69Ojo0aNHnHrqqXHkkUfGPvvsEzvuuGPsueeecdhhh8U3vvGNuOuuu2L58uUNXmt7w3FExLx58+Lqq6+OY445Jvbaa6/Ydddd49BDD43zzz8/nn/++eb4FRvFAgQAAKAtm/HW6jj62pF1ovGRvUbEXxasyno82jndhDSEY3LNAgQAAKCteuOddfGpPqPrROPDegyP8a83/CEvaA66CWkIx+SaBQgAAEBbtHjVxvjczc/UicYHd3sqnpqxNOvx6CB0E9IQjsk1CxAAAIC25t11VfEvtz1bJxofdM1T8cjURVmPRweim5CGcEyuWYAAAAC0JWs2VseXfjkhMRrfM2Fu1uPRwegmpCEck2sWIAAAAG3Fxi018Y27n0+MxreNmp31eHRAuglpCMfkmgUIAABAW7C5pja+O+DPidG419BXolwuZz0iHZBuQhrCMblmAQIAAJC1mtpSXPTwtMRofNkjL0WpJBqTDd2ENIRjcs0CBAAAIEvlcjn++/HpidH4B/e/ENW1paxHpAPTTUhDOCbXLEAAAACyUi6X44Y/vZYYjb/Vf3JUVddmPSIdnG5CGsIxuWYBAgAAkJVfPfNGYjT+yp3Pxbqq6qzHA92EVIRjcs0CBAAAIAv3Pz8/MRqf2ndcrNqwJevxICJ0E9IRjsk1CxAAAIDW9uSLbyVG48//fGwsXbMp6/GgQjchDeGYXLMAAQAAaE2jX10Wh3QfXican3DjmFiwYkPW48FWdBPSEI7JNQsQAACA1jJp7oo4vOeIOtH42N6jYtbStVmPB3XoJqQhHJNrFiAAAACt4eXFq+Poa0fWicaf6DUypi18L+vxIJFuQhrCMblmAQIAANDSXn9nXRzfZ3SdaHxYj+Ex8Y3lWY8H9dJNSEM4JtcsQAAAAFrS4lUb47M3j6kTjQ/u9lSMmLk06/GgQboJaQjH5JoFCAAAQEt5d21V/POtz9aJxgdd81Q8+sLirMeDbdJNSEM4JtcsQAAAAFrC6o1b4ozbJyRG4/smzst6PGgU3YQ0hGNyzQIEAACguW3YXBNf+/XzidG47+g5WY8HjaabkIZwTK5ZgAAAADSnzTW18Z/3TUmMxtf9zytRLpezHhEaTTchDeGYXLMAAQAAaC41taW44KG/JEbjnwx5OUol0Zh80U1IQzgm1yxAAAAAmkOpVI4rH5ueGI1/+MALUV1bynpE2G66CWkIx+SaBQgAAEBa5XI5+gx7LTEan3vP5Kiqrs16RGgS3YQ0hGNyzQIEAAAgrTvGvJEYjc+667lYv7km6/GgyXQT0hCOyTULEAAAgDR+9/z8xGh8er/xsWrDlqzHg1R0E9IQjsk1CxAAAICmemLaW4nR+ORbxsayNVVZjwep6SakIRyTaxYgAAAATTH61WVxSPfhdaLxP940Jhas2JD1eNAsdBPSEI7JNQsQAACA7fX8myvi8B4j6kTj464fHbOXrc16PGg2uglpCMfkmgUIAADA9pg6f1V8otfIOtH4qGtHxouL3st6PGhWuglpCMfkmgUIAABAY01b+F4cfW3daHx4jxHx3Bsrsh4Pmp1uQhrCMblmAQIAANAYM95aHcdcN6pOND6421Mx8pWlWY8HLUI3IQ3hmFyzAAEAANiWV5esieOuH10nGnfp9lQMfentrMeDFqObkIZwTK5ZgAAAADRkzrJ18ekbnq4TjQ+65ql49IXFWY8HLUo3IQ3hmFyzAAEAAKjPm++ujxNuTI7GD09ZmPV40OJ0E9IQjsk1CxAAAIAkC1ZsiBNvGpMYjX/3/Pysx4NWoZuQhnBMrlmAAAAA/K3FqzbGP/3smcRofM+EuVmPB61GNyEN4ZhcswABAAD4oCWrN8XJt4xNjMZ3jX0j6/GgVekmpCEck2sWIAAAAO97Z21V/MttzyZG436j52Q9HrQ63YQ0hGNyzQIEAAAgImL5us1xat9xidH45yNmR7lcznpEaHW6CWkIx+SaBQgAAMCqDVvijNsnJEbjPsNeE43psHQT0hCOyTULEAAAoGNbvXFLfPmOiYnRuNfQV0RjOjTdhDSEY3LNAgQAAOi41lZVx1l3PZcYja95YkaUSqIxHZtuQhrCMblmAQIAAHRM6zfXxNfvfj4xGl/x6MuiMYRuQjrCMblmAQIAAHQ8G7fUxDm/nZwYjS8d/FLUisYQEboJ6QjH5JoFCAAA0LFUVdfGd+6dkhiNL3xoWlTXlrIeEdoM3YQ0hGNyzQIEAADoOKqqa6PrwKmJ0fiHD7wQW2pEY/gg3YQ0hGNyzQIEAADoGLbUlOIH97+QGI27Dpwam2tqsx4R2hzdhDSEY3LNAgQAAGj/qmtLceFD0xKj8XfunRJV1aIxJNFNSEM4JtcsQAAAgPatprYUlw5+KTEan/PbybFxS03WI0KbpZuQhnBMrlmAAAAA7VdtqRxXDHk5MRp/4+7nY/1m0RgaopuQhnBMrlmAAAAA7VOpVI6rH5+RGI3Puuu5WFtVnfWI0ObpJqQhHJNrFiAAAED7Uy6Xo+fQmYnR+Mt3TIzVG7dkPSLkgm5CGsIxuWYBAgAAtC/lcjmuH/ZqYjQ+4/YJsWqDaAyNpZuQhnBMrlmAAAAA7Ue5XI6fjZiVGI1P7Tsulq/bnPWIkCu6CWkIx+SaBQgAANB+9Bs9JzEan3Lbs/HO2qqsx4Pc0U1IQzgm1yxAAACA9uGusW8kRuP/c+vYWLJ6U9bjQS7pJqQhHJNrFiAAAED+9R8/NzEa/9PPnonFqzZmPR7klm5CGsIxuWYBAgAA5NvA5+YnRuPP3jwmFqzYkPV4kGu6CWkIx+SaBQgAAJBfD09ZmBiNT7hxTLz57vqsx4Pc001IQzgm1yxAAACAfHr0hcWJ0fhTfUbHnGXrsh4P2gXdhDSEY3LNAgQAAMifP7z0VnTpVjcaH3f96Hh1yZqsx4N2QzchDeGYXLMAAQAA8uVPM5bEwQnR+JjrRsWMt1ZnPR60K7oJaQjH5JoFCAAAkB8jX1kWh3QfXicaH33tyHhx0XtZjwftjm5CGsIxuWYBAgAA5MMzs96Jw3rUjcaf6DUyps5flfV40C7pJqQhHJNrFiDImooIAAAgAElEQVQAAEDbN+H15XF4jxF1ovERPUfEpDdXZD0etFu6CWkIx+SaBQgAANC2TXpzRRzRs240PrzHiBj/+vKsx4N2TTchDeGYXLMAAQAA2q6p81fFJ3qNrBOND+sxPJ6Z9U7W40G7p5uQhnBMrlmAAAAAbdOLi96Lo6+tG40P6T48Rr6yLOvxoEPQTUhDOCbXLEAAAIC2Z+Zba+KY3qPqROODuz0Vw6YvyXo86DB0E9IQjsk1CxAAAKBteW3J2jju+tF1onGXbk/Fky++lfV40KHoJqQhHJNrFiAAAEDbMWfZuvj0DU/XicYHXfNUPPrC4qzHgw5HNyEN4ZhcswABAADahrnL18cJN45JjMYPTVmY9XjQIekmpCEck2sWIAAAQPYWrNgQn705ORoPfG5+1uNBh6WbkIZwTK5ZgAAAANlavGpj/NPPnkmMxv3Hz816POjQdBPSEI7JNQsQAAAgO0tWb4r/c+vYxGh85zNvZD0edHi6CWkIx+SaBQgAAJCNpWs2xT/f+mxiNO47ek7W4wGhm5COcEyuWYAAAACtb9maqviX25Kj8c+Gz4pyuZz1iEDoJqQjHJNrFiAAAEDrWramKv71F+MSo/H1w14VjaEN0U1IQzgm1yxAAACA1vPO2qr4Qj3R+Lr/eUU0hjZGNyEN4ZhcswABAABax7sNRONeQ0VjaIt0E9IQjsk1CxAAAKDlvbuuKr7QNzka9xw6UzSGNko3IQ3hmFyzAAEAAFrW8nWb49R6onH3P8yMUkk0hrZKNyEN4ZhcswABAABazvJ1m+P0fuMTo3G3J2eIxtDG6SakIRzn1Pr162Po0KFx2WWXxcknnxwHHHBAdOrUKTp37hyHHnponHvuufHEE09ETU1Ns9xv3LhxlUXTmOOUU05plvtuiwUIAADQMlas3xxfvD05Gl/9uGgMeaCbkIZwnEP9+vWLXXbZpVEB9/jjj49XX3019T2FYwAAgI5j5frNccbtExKj8VWPTReNISd0E9IQjnPowgsvrPyh/7u/+7vo2rVr/OpXv4ohQ4bEQw89FJdffnnsu+++lXP233//eP3111Pd84Ph+Nxzz42hQ4c2eLTWMrIAAQAAmteqDVviS79MjsZXisaQK7oJaQjHOXTRRRfF6aefHiNHjoza2trEc5YvXx4nnXRSZTmcdtppqe75wXDcu3fvVNdqThYgAABA83mvgWh8xaMvR61oDLmim5CGcJxDq1atatR5S5YsiV133bWyIBYuXNjkewrHAAAA7dt7G7bEl++YmBiNfzJENIY80k1IQzhu584444zKghg2bFiTryMcAwAAtF+rN26Jf/9VcjS+7JGXRGPIKd2ENITjdu6cc86pLIghQ4Y0+TrCMQAAQPu0ZmN1nHlncjT+8eCXoqa2lPWIQBPpJqQhHLdzRx11VGVBTJ48ucnX+WA4PuaYY+L444+PPffcM3beeef46Ec/GqeeemrcdNNN8c477zTj9NtmAQIAADTdmk3V8ZU7n0uMxv/v9y+KxpBzuglpCMft2Adj7/7771/vg/S291oNHR/60Ieib9++US63zv+NyQIEAABomjWbquOrdyVH40sGicbQHugmpCEct1MbN26MI488srIc+vXrl+p674fjz3zmM/HTn/407r333nj88cfjgQceiP/+7/+OQw45ZKuAfNlll6X+HZ577rltHnfffbcFCAAAsJ3WVlXHV3/9fGI0vnjQtKgWjaFdEI5JQzhuh8rlcpx99tmVxXDSSSdFdXV1qmsuXbo0Xn/99Xp/XltbGz//+c+jUChU7vvkk0+mumdjPuH8wcMCBAAA2LZ1VdXxtXqi8YUPicbQngjHpCEct0NXXHFFZSl85CMficWLF7favXv27LnVdyGnIRwDAAA0r3VV1fGNu5Oj8QUP/UU0hnZGOCYN4bid6dGjR2Uh7LfffjFz5sxWvf/GjRtjjz32qMwwf/78Jl/LV1UAAAA0n/Wba+I/fjMpMRr/14N/iS01ojG0N8IxaQjH7cgHP+277777xssvv5zJHF/84hcrcwwfPrxF72UBAgAAbNv6zTVxdj3R+IcPvCAaQzulm5CGcNxOdO/evbII9tlnn3jxxRczm+U///M/K7P8/ve/b9F7WYAAAAAN27C5Js757eTEaPyD+1+IzTW1WY8ItBDdhDSE43bg6quvbjPROCLijDPOqMwzYsSIFr2XBQgAAFC/jVtq4pz+ydH4vN9NFY2hndNNSEM4zrkrr7yyTUXjqqqq2HPPPSszzZs3r0XvZwECAAAk27ilJs69Jzkaf/93U6OqWjSG9k43IQ3hOMd+8pOfbPWdxllH44iI3r17V2Y66qijWvx+FiAAAEBdm7bUxrfvmZIYjbsOFI2ho9BNSEM4zqnLL7+8WR6Et2DBgsp1dtgh+V+HN998M2655ZZYs2ZNvdcplUpx2223RaFQqFxryJAhTZppe1iAAAAAW9u0pTa+c29yNP7ugD+LxtCB6CakIRznUK9evbaKvb17946hQ4du85g9e3adazUmHL/88suxww47xM477xxf+tKXolevXvG73/0uHn/88XjwwQejW7ducdhhh211nYsuuqil/zFEhAUIAADwQVXVtfF/7/tzYjT+v/eJxtDR6CakIRzn0CmnnLJVpG3s0bt37zrX2p5w3Jhjl112idtuuy1KpVIL/1P4KwsQAADgr6qqa+O7A5Kj8X/eNyU2bRGNoaPRTUhDOM6h1g7HmzdvjtGjR0efPn3izDPPjKOPPjo+8pGPRKdOnWL33XePAw88MM4888zo169frFixooV/+61ZgAAAAH+Nxl0HTk2Mxt++RzSGjko3IQ3hmFyzAAEAgI6uqro2vldPND73nsmxcUtN1iMCGdFNSEM4JtcsQAAAoCPbXFMb5/0uORqf0180ho5ONyEN4ZhcswABAICOanNNbZx//wvJ0fi3k2PDZtEYOjrdhDSEY3LNAgQAADqiLTWl+OEDydH4m7+dJBoDEaGbkI5wTK5ZgAAAQEezpaYU//XgXxKj8X/8ZlKsF42B/59uQhrCMblmAQIAAB1JdW0pflRPNP7G3c/HuqrqrEcE2hDdhDSEY3LNAgQAADqK6tpSXPjQtMRo/HXRGEigm5CGcEyuWYAAAEBHUF1bioseTo7GX/v187FWNAYS6CakIRyTaxYgAADQ3tXUluKSQS8mRuOvisZAA3QT0hCOyTULEAAAaM9qakvx/36fHI3Puuu5WLNJNAbqp5uQhnBMrlmAAABAe1VTW4pLB7+UGI2/cudzsWajaAw0TDchDeGYXLMAAQCA9qi2VI7LHkmOxmfeOVE0BhpFNyEN4ZhcswABAID2prZUjp8MeTkxGn/5jomxeuOWrEcEckI3IQ3hmFyzAAEAgPaktlSOK+qJxv92x8R4b4NoDDSebkIawjG5ZgECAADtRW2pHD99dHpiNP7SLyfEKtEY2E66CWkIx+SaBQgAALQHpVI5rnpMNAaal25CGsIxuWYBAgAAeVcqlePqx2ckRuMzbp8QK9dvznpEIKd0E9IQjsk1CxAAAMizUqkc1zyRHI1P7zc+VojGQAq6CWkIx+SaBQgAAORVqVSObk/OTIzGp/UbH8vXicZAOroJaQjH5JoFCAAA5FG5XI4ef0iOxqf2HRfvrqvKekSgHdBNSEM4JtcsQAAAIG/K5XL0GvpKYjT+wi/GxbtrRWOgeegmpCEck2sWIAAAkCflcjl6//HVxGj8r78YF++IxkAz0k1IQzgm1yxAAAAgL8rlclw/LDkan3Lbs7FsjWgMNC/dhDSEY3LNAgQAAPKgXC5Hn2GvJUbjf7nt2Vi6ZlPWIwLtkG5CGsIxuWYBAgAAbV25XI4b/5Qcjf/51mdjyWrRGGgZuglpCMfkmgUIAAC0ZeVyOW4ePisxGv+fW8fG26Ix0IJ0E9IQjsk1CxAAAGiryuVy/GxEcjQ++Zax8dZ7G7MeEWjndBPSEI7JNQsQAABoi8rlctwycnZiNP78z8fG4lWiMdDydBPSEI7JNQsQAABoa8rlcvxi1JzEaPxPP3tGNAZajW5CGsIxuWYBAgAAbU2/p19PjMYn/eyZWLRSNAZaj25CGsIxuWYBAgAAbckvxyRH48/d/EwsXLkh6/GADkY3IQ3hmFyzAAEAgLbijjFvJEbjz948JhasEI2B1qebkIZwTK5ZgAAAQFtw5zPJ0fjEm8bEfNEYyIhuQhrCMblmAQIAAFn79bNv1huN5y5fn/V4QAemm5CGcEyuWYAAAECW7h6XHI3/8aYx8ea7ojGQLd2ENIRjcs0CBAAAstJ//NzEaHzCjWPizXfXZT0egG5CKsIxuWYBAgAAWbh3wrzEaPyZG56ON94RjYG2QTchDeGYXLMAAQCA1nbfxPqj8ZxlojHQdugmpCEck2sWIAAA0JoGPjc/MRp/+oanY/aytVmPB7AV3YQ0hGNyzQIEAABay/3PJ0fjT/UZHbOWisZA26ObkIZwTK5ZgAAAQGt4cPKCxGh8fJ/R8doS0Rhom3QT0hCOyTULEAAAaGkP1RONj7t+dLy6ZE3W4wHUSzchDeGYXLMAAQCAljTozwsTo/GxvUfFK2+LxkDbppuQhnBMrlmAAABASxk8dVG90XjmW6Ix0PbpJqQhHJNrFiAAANAShryQHI2P6T0qpi9enfV4AI2im5CGcEyuWYAAAEBze/SFxdGlW0I0vm5UvCwaAzmim5CGcEyuWYAAAEBzeuwvydH4k9eNipcWvZf1eADbRTchDeGYXLMAAQCA5vLEtLfqjcbTForGQP7oJqQhHJNrFiAAANAc/vBScjQ++tqRMW3hqqzHA2gS3YQ0hGNyzQIEAADSGvrS23FwQjQ+6tqR8ZcFojGQX7oJaQjH5JoFCAAApPE/L9cfjafOF42BfNNNSEM4JtcsQAAAoKmGTV+SGI0/0WtkTJm3MuvxAFLTTUhDOCbXLEAAAKApnpqxNA7pPrxOND6y14iYPFc0BtoH3YQ0hGNyzQIEAAC214iZ9UfjSW+uyHo8gGajm5CGcEyuWYAAAMD2GPnK0jg0IRof0XNEPC8aA+2MbkIawjG5ZgECAACNNerVZfVG4+feEI2B9kc3IQ3hmFyzAAEAgMYYXU80PrzniJjw+vKsxwNoEboJaQjH5JoFCAAAbMuY196Jw3okROMeI2LcnHezHg+gxegmpCEck2sWIAAA0JCxs9+Jw3uMSIzGz84WjYH2TTchDeGYXLMAAQCA+jw7593EaHxYj+ExdvY7WY8H0OJ0E9IQjsk1CxAAAEgybs67cXjP5Gg85jXRGOgYdBPSEI7JNQsQAAD4Ww1F46dFY6AD0U1IQzgm1yxAAADgg56Zlfydxod2Hx6jXl2W9XgArUo3IQ3hmFyzAAEAgPeNenVZHNZjeGI0HvmKaAx0PLoJaQjH5JoFCAAAREQMn7k0Du2eHI1HzFya9XgAmdBNSEM4JtcsQAAAYNj0JXFIQjQ+rIevpwA6Nt2ENIRjcs0CBACAju0PL70VB3d7qk40PrzHiHhmlgfhAR2bbkIawjG5ZgECAEDH9fi0t6JLUjTuOSKenfNu1uMBZE43IQ3hmFyzAAEAoGMa8sKixGh8RM8RMeH15VmPB9Am6CakIRyTaxYgAAB0PA9PWVgnGB90zVPxiV4jY9KbK7IeD6DN0E1IQzgm1yxAAADoWB6YtCAxGh917cj487yVWY8H0KboJqQhHJNrFiAAAHQc902clxiNP3ndqPjLglVZjwfQ5ugmpCEck2sWIAAAdAy/HT83MRofc92oeHHRe1mPB9Am6SakIRyTaxYgAAC0f3eNfSMxGh/be1TMeGt11uMBtFm6CWkIx+SaBQgAAO1XuVyOX455PTEaH99ndLzy9pqsRwRo03QT0hCOI2LChAmtdqxa5Xu3mpMFCAAA7VO5XI5fjJqTGI0/fcPT8dqStVmPCNDm6SakIRxHRKFQiGKx2CrHH//4x6x/3XbFAgQAgPanXC7Hz0bMSozGJ9z4dMxZti7rEQFyQTchDeE4/jccFwqFFj2E4+ZnAQIAQPtSLpfjhj+9lhiN//GmMfHmu6IxQGPpJqQhHMf/huNvf/vbcf3117fIIRy3DAsQAADaj3K5HL3/+GpiNP7szWNi7vL1WY8IkCu6CWkIxxGtEnWF45ZhAQIAQPtQKpWj59CZidH4n372TCxYsSHrEQFyRzchDeE4hOM8swABACD/SqVyXPPEjMRo/Pmfj43FqzZmPSJALukmpCEcR1S+g7ilw3FL36MjsgABACDfakvluPKx6YnR+J9vfTbeek80Bmgq3YQ0hOOIWLhwYSxcuDA2bdqU63t0RBYgAADkV01tKX4y5OXEaHzKbc/GktX+/gSQhm5CGsIxuWYBAgBAPtXUluLSwS8lRuMv/GJcLFtTlfWIALmnm5CGcEyuWYAAAJA/1bWluOjhaYnR+LR+4+PddaIxQHPQTUhDOM6p9evXx9ChQ+Oyyy6Lk08+OQ444IDo1KlTdO7cOQ499NA499xz44knnoiamppmv/f8+fOjW7ducdxxx8Xee+8du+22Wxx22GHxwx/+MCZNmtTs92uIBQgAAPmypaYUP3rwL4nR+IzbJ8SK9ZuzHhGg3dBNSEM4bgYLFy6M3//+9/Hggw/GzJkzW/x+/fr1i1122aXyB7+h4/jjj49XX3212e49cODA2H333eu9X6FQiB//+MdRKpWa7Z4NsQABACA/NtfUxg/ufyExGv/bHRNj1YYtWY8I0K7oJqQhHDdg5cqV0adPn+jTp0+98bVbt26x0047RbFYrBxf//rXY+PGlnvy74UXXlj5Q/93f/d30bVr1/jVr34VQ4YMiYceeiguv/zy2HfffSvn7L///vH666+nvu8jjzwShUKhEojPOeecGDBgQDz88MNx2WWXRefOnSv3vPTSS5vhN902CxAAAPKhqro2vjdwamI0PvPOibF6o2gM0Nx0E9IQjhvw8MMPR6FQiF122SXee++9Oj9/4IEHolAoRLFYjEKhUDmKxWJ885vfbLG5Lrroojj99NNj5MiRUVtbm3jO8uXL46STTqosh9NOOy3VPVeuXBl77bVXJRo/9thjdc6ZNWtWHHDAAZV7jh8/PtU9G8MCBACAtm/Tltr47oA/J0bjr971XKzZWJ31iADtkm5CGsJxA7p27RqFQiFOP/30xJ8ffPDBlVh89tlnx3//939Hly5dKvF44sSJLTLXqlWrGnXekiVLYtddd60siIULFzb5nt26datc5+KLL673vEcffbRy3sknn9zk+zWWBQgAAG3bxi018e17piRG42/c/XysrRKNAVqKbkIawnEDjj/++CgWi9GrV686P5syZUolEN98882V15cvXx777rtvFIvFuOCCC1pz3ERnnHFGZUEMGzasydfp0qVL5Tpz586t97xSqRQf//jHK+cuWrSoyfdsDAsQAADarvWba+Kc/pMTo/E3fzsp1m9u/od5A/C/dBPSEI4b8LGPfSyKxWI8+OCDdX524403Vr7GYv369Vv97OKLL45CoRDHHXdca41ar3POOaeyIIYMGdKka8yaNatyjSOPPHKb519wwQWV8/v379+kezaWBQgAAG3Tuqrq+I/fTEqMxt/qPzk2iMYALU43IQ3huAG77rprFIvF+MMf/lDnZ1/+8pfr/RqLe+65JwqFQuy9996tMWaDjjrqqMqCmDx5cpOuMWTIkMo1unbtus3zBwwYUDn/kksuadI9G8sCBACAtmfNpur42q+fT4zG37l3SmzcIhoDtAbdhDSE4wa8H44HDx5c52f77LNPFIvFuP766+v87IknnohCoRCdOnVqjTHrNW7cuMpy2H///et9kN629OnTp3Kd6667bpvnjx07tlkeyvfcc89t87j77rstQAAAaENWb9wSZ931XGI0/u6AP0dVddP+XgLA9hOOSUM4bsCBBx4YxWIxbrjhhq1enzZtWuX7jUePHl3nfQ8++GAUCoXYY489WmvUOjZu3BhHHnlkZTn069evyde64oorKte58847t3n+jBkzKuefcMIJTb7v+9do7GEBAgBAtt7bsCW+fMfExGh83u+misYArUw4Jg3huAFf+cpXKt9VXC6XK69ffvnlUSgUYuedd67z/cYRf/2EbqFQiMMPP7w1x60ol8tx9tlnVxbDSSedFNXVTX9S8Y9+9KPKte67775tnv/GG29Uzj/iiCOafF/hGAAA8mPl+s3xpV9OSIzGP3zgL7G5RjQGaG3CMWkIxw0YMGBA5ZPF5557bowcOTJuuumm6NSpUxSLxTjrrLMS33fmmWdGoVCIr371q6088V998BPCH/nIR2Lx4sWprpdVOPZVFQAAkA/L122OL94+PjEaX/jQtNhSU8p6RIAOSTgmDeG4ATU1NXH00UdX4vH7R6FQiJ122immTp1a5z0bNmyofDdy3759W33mHj16VBbCfvvtFzNnzkx9zay+qqIxLEAAAMjWu2ur4tS+4xKj8SWDXozqWtEYICu6CWkIx9uwePHiOPHEE6NQKFSOzp07x/333594/gc/pTxt2rRWnbVnz56VZbDvvvvGyy+/3CzXzerheI1hAQIAQHaWramKf/1FcjT+8eCXokY0BsiUbkIawnEjvfjiizFkyJD405/+FKtXr673vEGDBsX1118fN9xww1bfi9zSunfvXlkE++yzT7z44ovNdu0hQ4ZUrt21a9dtnj9gwIDK+ZdcckmzzZHEAgQAgGy8vXpT/MttzyZG4yuGvBy1pdb7+xAAyXQT0hCO24Grr766xaJxRMSsWbMq1z/yyCO3ef4FF1xQOb9///7NOsvfsgABAKD1LV61MU6+ZWxiNL7qsemiMUAboZuQhnCcc1deeWWLRuP3HXTQQZX7zJ07t97zSqXSVucuXLiwReZ5nwUIAACta+HKDfH5nydH425PzoySaAzQZugmpCEc59hPfvKTrb7TuKWicUTENddcU7nXxRdfXO95jz76aOW8z3/+8y02z/ssQAAAaD3zV2yIz938TGI07jX0FdEYoI3RTUhDON4OpVIp3njjjZg6dWpMmDChUUdLufzyy5vlQXgLFiyoXGeHHer/12HFihWx5557xg477BCFQiEef/zxOufMnj07PvzhD1euNXbs2CbNtD0sQAAAaB1vvrs+TrxpTGI0vn7Yq636jBcAGkc3IQ3huBGmTJkSX//612P33XePYrHY6GPHHXdskXl69eq1Vezt3bt3DB06dJvH7Nmz61yrseE44q8P/isUCpV4/K1vfSsGDhwYgwYNissvvzz22GOPRn0quTlZgAAA0PJef2ddnHBjcjS+efgs0RigjdJNSEM43oY77rgjdtpppygWi1EoFLbrKBaLLTLTKaecslXsbezRu3fvOtfannAcEXHvvffGbrvt1uB9LrnkkqitrW2B37wuCxAAAFrW7GVr4zM3PJ0YjW8dOVs0BmjDdBPSEI4bMHny5EoALhQK8bGPfSy6du0a3bt3j+uvv75RR0vIMhxHRMybNy+uvvrqOOaYY2KvvfaKXXfdNQ499NA4//zz4/nnn2/m37ZhFiAAALSc6YtXx/F9RidG436j54jGAG2cbkIawnEDvvWtb1XC8Y033hilUinrkfgbFiAAALSMyXNXxtHXjkyMxneMeSPr8QBoBN2ENITjBvzDP/xDFIvF+NrXvpb1KNTDAgQAgOY3dvY7cUTPEYnR+NfPvpn1eAA0km5CGsJxAz70oQ9FsViMgQMHZj0K9bAAAQCgeQ2bviQO7T48MRrfN3Fe1uMBsB10E9IQjhvw0Y9+NIrFYjz++ONZj0I9LEAAAGg+g6cuii7d6gbjLt2eikemLsp6PAC2k25CGsJxA04//fQoFovRt2/frEehHhYgAAA0j3snzEv8lPGh3YfHsOlLsh4PgCbQTUhDOG7Aww8/HIVCIU466aSsR6EeFiAAAKRTLpej3+g5idH4iJ4jYuzsd7IeEYAm0k1IQzhuQLlcjlNPPTWKxWL069cv63FIYAECAEDTlUrl6P3HVxOj8dHXjowp81ZmPSIAKegmpCEcb8Pq1asr8fj73/9+zJgxI+uR+AALEAAAmqamthRXPjY9MRof32d0TF+8OusRAUhJNyEN4bgBBx98cBx88MFx4IEHRqFQiGKxGMViMTp37hwHHXRQ5ef1HYccckjWv0K7ZwECAMD221xTGxc9PC0xGp9405iYs2xd1iMC0Ax0E9IQjhvwwVhcLBajUChs11EsFrP+Fdo9CxAAALbPpi210XXg1MRofPItY2Phyg1ZjwhAM9FNSEM4bsBBBx0UXbp0SXXQsixAAABovLVV1fHN305KjMan9Rsfy9ZUZT0iAM1INyEN4ZhcswABAKBxVq7fHGfeOTExGp9558RYuX5z1iMC0Mx0E9IQjsk1CxAAALZt2ZqqOLXvuMRo/M3fToq1VdVZjwhAC9BNSEM4bsCECRNiwoQJ8fLLL2c9CvWwAAEAoGELV26Ik28ZmxiNvzdwamzaUpv1iAC0EN2ENITjBrz/gLurrroq61GohwUIAAD1m7NsXZx405jEaHzxoGmxpaaU9YgAtCDdhDSE4wbsuuuuUSwWY9CgQVmPQj0sQAAASDZ98eo4vs/oxGh81WPTo6ZWNAZo73QT0hCOG3DwwQdHsViM3//+91mPQj0sQAAAqGvy3JVx9LUjE6Px9cNejVKpnPWIALQC3YQ0hOMGnHvuuVEsFqNHjx5Zj0I9LEAAANja2NnvxBE9RyRG435Pvx7lsmgM0FHoJqQhHDfgT3/6UxQKhTjwwANj06ZNWY9DAgsQAAD+17DpS+LQ7sMTo/F9E+dlPR4ArUw3IQ3heBvOPffcKBQKcdZZZ8X69euzHoe/YQECAMBfDZ66KLp0qxuMu3R7Kh6Zuijr8QDIgG5CGsJxAxYtWhRvvvlmfOUrX6t5UP4AACAASURBVIlCoRB///d/H9dee20888wzMWfOnFi0aNE2D1qWBQgAABH3TpiX+CnjQ7sPj2HTl2Q9HgAZ0U1IQzhuQKFQiGKxWDn+9n9v69hxxx2z/hXaPQsQAICOrFwuR7/RcxKj8RE9R8TY2e9kPSIAGdJNSEM4bkChUEh1FIvFrH+Fds8CBACgoyqVytH7j68mRuOjrx0ZU+atzHpEADKmm5CGcNyA8847L/VBy7IAAQDoiGpqS3HlY9MTo/HxfUbH9MWrsx4RgDZANyEN4ZhcswABAOhoNtfUxkUPT0uMxifeNCbmLFuX9YgAtBG6CWkIx+SaBQgAQEeyaUttdB04NTEan3zL2Fi4ckPWIwLQhugmpCEck2sWIAAAHcXaqur45m8nJUbj0/qNj2VrqrIeEYA2RjchDeGYXLMAAQDoCFau3xxn3jkxMRqfeefEWLl+c9YjAtAG6SakIRyTaxYgAADt3bI1VXFq33GJ0fibv50Ua6uqsx4RgDZKNyEN4biR3nrrrfj5z38eX/3qV+Mzn/lMHHbYYXHwwQc3eBxyyCFZj93uWYAAALRnC1duiJNvGZsYjb83cGps2lKb9YgAtGG6CWkIx9tQLpeje/fu0alTpygWi1EsFqNQKGx1NPQ6LcsCBACgvZqzbF2ceNOYxGh88aBpsaWmlPWIALRxuglpCMfb8OMf/3irKPzRj360EoU//OEPxwEHHBA77rjjVrH4wAMPjC5dukSXLl2yHr/dswABAGiPpi9eHcf3GZ0Yja96bHrU1IrGAGybbkIawnEDXnzxxUoMPumkk2Lu3LkREZXX/vjHP0ZExLp16+LRRx+N4447LgqFQnzpS1+KNWvWZDl6h2EBAgDQ3kyeuzKOvnZkYjS+ftirUSqVsx4RgJzQTUhDOG7ARRddFIVCIfbZZ59YuXJl5fW/Dcfv27JlS3zjG9+IYrEYX/ziF1t73A7JAgQAoD0ZO/udOKLniMRo3O/p16NcFo0BaDzdhDSE4wYcc8wxUSwW48ILL9zq9frCcUTEpk2b4h/+4R+iWCzGI4880lqjdlgWIAAA7cWw6Uvi0O7DE6PxfRPnZT0eADmkm5CGcNyAffbZJ4rFYtx3331bvf5+OH7ssccS39ejR48oFApx1llntcaYHZoFCABAezB46qLo0q1uMO7S7al4ZOqirMcDIKd0E9IQjhvQqVOnKBaL8eSTT271+m677RbFYjEGDBiQ+L7BgwdHoVCIj3/8460xZodmAQIAkHf3TpiX+CnjQ7sPj2HTl2Q9HgA5ppuQhnDcgPc/cTx48OCtXv/7v//7KBaLce211ya+7/77749CoRC77LJLa4zZoVmAAADkVblcjn6j5yRG4yN6joixs9/JekQAck43IQ3huAGf+tSnolgsxu23377V66eeemoUCoU47bTTEt93+eWXR6FQiL333rs1xuzQLEAAAPKoVCpH7z++mhiNj752ZEyZt3LbFwGAbdBNSEM4bsB5550XhUIhzj///K1e79OnTxQKhdhxxx3jhRde2Opnb775Zuy+++5RLBbj5JNPbs1xOyQLEACAvKmpLcWVj01PjMbH9xkd0xevznpEANoJ3YQ0hOMGPPDAA1EoFKJLly5bvT5//vzYeeedo1gsxp577hlXXXVV3HPPPXHVVVfF3nvvXXl43l133ZXR5B2HBQgAQJ5srqmNix6elhiNT7xpTMxZti7rEQFoR3QT0hCOG7By5crYaaedolgs1vnDdcMNN1QC8d8ehUIhPve5z0VNTU1Gk3ccFiAAAHmxcUtNfG/g1MRofPItY2Phyg1ZjwhAO6ObkIZwvA3z58+POXPmxHvvvVfnZ3379o0999wzCoVC5SgWi/Gd73wn1qxZk8G0HY8FCABAHixZvSm+fMfExGh8Wr/xsWxNVdYjAtAO6SakIRyntHnz5hg3blw88sgjMWzYsFi2bFnWI3UoFiAAAG3dy4tXxz/eNCYxGp9558RYuX5z1iMC0E7pJqQhHJNrFiAAAG3ZsOlL4oieIxKj8Td/OynWVlVnPSIA7ZhuQhrCMblmAQIA0BaVy+W4/enXE4PxQdc8FRc+NC02banNekwA2jndhDSEY3LNAgQAoK2pqq6NS37/Yr3R+LZRs6NUKmc9JgAdgG5CGsLxdhg9enT813/9Vxx77LGx3377xc477xz77bdfHHvssfGjH/0oRo8enfWIHY4FCABAW/Lu2qr46l3PJQbjw3uMiD+89FbWIwLQgegmpCEcN8KMGTPi05/+dBSLxcpRKBQqxwdfP+GEE+KVV17JeuQOwwIEAKCteOXtNfG5m59JjMYn3Ph0TFv4XtYjAtDB6CakIRxvw/jx46Nz5851YnGnTp1i7733jk6dOm31eqFQiM6dO8eECROyHr1DsAABAGgLRr6yLD7Ra2RiNP7SLyfEW+9tzHpEADog3YQ0hOMGrFy5Mvbff/9KED7qqKPi3nvvjQULFmx13sKFC+Pee++NT37yk5Vz999//1i5cmU2g3cgFiAAAFkql8vx62ffrPf7jH9w/wuxfnNN1mMC0EHpJqQhHDegR48ela+iOO+886K6urrB82tqauL888+vvKdnz56tNGnHZQECAJCVzTW1ccWQl+uNxjcPnxW1HoIHQIZ0E9IQjhtw7LHHRqFQiE9+8pNRW1vbqPfU1tZWPnl8zDHHtPCEWIAAAGRhxfrN8R+/mZQYjA/rMTwefWFx1iMCgG5CKsJxA/bYY48oFotx6623btf7br311sp3HdOyLEAAAFrb7GVr4/M/H5sYjT/VZ3RMmecr6wBoG3QT0hCOG7DXXntFsViMxx57bLve99hjj0WhUIi99tqrhSbjfRYgAACt6ZlZ78TR1yY/BO+0fuNj4coNWY8IABW6CWkIxw049thjo1gsRv/+/bfrfffcc08UCoU47rjjWmgy3mcBAgDQGsrlctw3cV506Zb8fcZdB06NtVUNPxMFAFqbbkIawnED3n843plnnrld7zvzzDM9HK+VWIAAALS0LTWluPrxGfU+BK/3H1+NmtpS1mMCQB26CWkIxw1YunRp7L///lEsFmPQoEGNes/gwYOjUCjEhz/84Vi2bFkLT4gFCABAS3pvw5b4Vv/JicH4kO7D46EpC7MeEQDqpZuQhnC8DRMmTIj99tsvdtppp/jpT38aS5cuTTxv6dKlceWVV0anTp1i//3394exlViAAAC0lDffXR//ctuzidH42N6j4rk3VmQ9IgA0SDchDeE4Is4///wGj1NPPTUKhUIUi8XYaaed4rjjjouzzz47vve978XZZ58dxx13XOy0005RLBajWCzGaaedFueff3784Ac/yPpXa/csQAAAWsKE15fHMb1HJUbjf/3FuJi7fH3WIwLANukmpCEcR1SicGOO+s6t73ValgUIAEBze2DSgjik+/DEaPzte6bE6o1bsh4RABpFNyEN4Tj+Go5b4hCOW54FCABAc6muLUWvoa/U+xC8bk/OjGoPwQMgR3QT0hCOI2LhwoUtdtCyLEAAAJrDmo3V8X/v+3NiMD6421Mx8Ln5US6Xsx4TALaLbkIawjG5ZgECAJDW/BUb4gt9xyVG4/+PvTuP0qsgE/xPYiu4QY9L60wfhwCJEY2ioI0gNiLDYsdxmW6ktZuZcVx+iqLCjJA9BEjCEhCRQFgNq4kRQU1V9n2BLBAg+77veyWV2t73fX5/qNUsdauS3Kq6das+n3Pev+rWvc97DvUcz9ebez82YHxMXbEz6xEB4LjoJqQhHJNrFiAAAGnMWbM7PnHjhAaj8QW3TYmVOyqyHhEAjptuQhrCMblmAQIAcLyenrcxzkh4Cd6/3D8n9hyqznpEAEhFNyEN4ZhcswABADhWhWIpBv1xaeJL8P7vb1+O6rpC1mMCQGq6CWkIxxGxcePG2LhxY1RVVeX6Gh2RBQgAwLGoqKqN//3ovAaDcZdeY2PE9DVeggdAu6GbkIZwHBGdOnWKt7zlLfGHP/wh19foiCxAAACO1qa9lXHJXdMbjMZn9h8XE5Zsz3pEAGhWuglpCMfx56jbuXPnFg/HLX2NjsgCBADgaMxfvzc+ddPEBqPxeUMmx9KtB7MeEQCanW5CGsJxCMd5ZgECANCUMQs3R7c+5Q1G46/eOzt2VnicHADtk25CGsJx/EfU/eY3vxmDBg1qkY9w3DIsQAAAkhSLpRhavjzxJXg/+c1LUVXrJXgAtF+6CWkIx/Ef4bglP8Jxy7AAAQBoyOHquvjeYwsSo/E9k1d5CR4A7Z5uQhrCcfw5HLfWRzhuXhYgAABvtHX/kbj87pkNBuPu/cqj7NVtWY8IAK1CNyEN4Tgipk+f3mqfPXv2ZP112xULEACA13pp47445+ZJDUbjfxg8KV7ZvD/rEQGg1egmpCEck2sWIAAAf/Xcoi3RrW/DL8Hrec/M2H7AS/AA6Fh0E9IQjsk1CxAAgGKxFHdOXJn4POMfPrkwjtR4CR4AHY9uQhrCMblmAQIAdGxHagpx9VMvJkbjYRNWRLHoJXgAdEy6CWkIx+SaBQgA0HHtOFgV//1XsxoMxt36lsdzi7ZkPSIAZEo3IQ3hmFyzAAEAOqZXNx+IcwdPbjAan3PzxFi4YV/WIwJA5nQT0hCOyTULEACgYymVSjFyzvro1qfhl+Bd9osZsXlfZdZjAkCboJuQhnBMrlmAAAAdx/7KmvjeYwsSn2f8nZEL4nB1XdZjAkCboZuQhnBMrlmAAAAdw8INe+P8oVMSo/GQsmVR8BI8AHgd3YQ0hGNyzQIEAGjfisVS3Dt1dZzeu6zBYNy9X3mMWbg56zEBoE3STUhDOM6xUqkUq1atilGjRsX1118fF198cbznPe+pXwinnnpqs15v2rRp9ec+ms+FF17YrNdviAUIANB+7ayoin976IXEu4wvvWtGrNpRkfWYANBm6SakIRzn2HXXXddouBWOAQDIqxkrd8U5N09MjMa9f/9qVNUWsh4TANo03YQ0hOMc++lPf/q6UPuOd7wjzjrrrFYJx1deeWU8++yzjX5aYyFZgAAA7UttoRi3jlueGIx7DBgfY1/ZlvWYAJALuglpCMc59sADD8TPfvazePzxx2PJkiVRKBRi/fr1rRKOBw4c2KznPl4WIABA+7F5X2V8ffjsxGj8lXtnx6a9lVmPCQC5oZuQhnB8FFavXh2PPvpo3HjjjXHNNdfED37wg7jhhhtixIgRMX/+/KzHex3hGACAPBq3eFt8fOD4xGg8uGxZ1NQVsx4TAHJFNyEN4ThBdXV1DB8+PM4444zo3Llzo5+///u/j0GDBsXBgwezHls4BgAgV6pqC9H/ucWJwfhTN02MqSt2Zj0mAOSSbkIawnEDFi9eHN27d68Pw506dWry07lz5/jgBz8YEydOTDzvli1bWnx24RgAgLxYs+tQXH73zMRo/K8PPB87DlZlPSYA5JZuQhrC8RvMmDEj3vnOd74pGHfp0iUuv/zy+Nd//de48sor4/LLL48uXbq8Lhx36tQp3vrWt8aoUaPedN4bb7wxbrrpphafv7XCcY8ePeKss86Kk08+Od72trfFBz/4wfjiF78Yt9xyS+zYsaNZr9sYCxAAIJ/GLNwcZ/Yf12AwPq3X2Pjl5FVRKJayHhMAck03IQ3h+DXWrFkT733ve+tj8N/93d/F4MGDY+vWrYm/s23bthg8eHB84AMfqP+9E088MRYtWlR/zPXXXx+dO3eOQYMGtfh3aK1w3NjnxBNPjGHDhkWplO5/6M+aNavJz/Dhwy1AAIAcOVxdF9eOWpR4l/G5gyfHvHV7sx4TANoF4Zg0hOPX+MpXvlJ/9/CXvvSl2L1791H/7p49e6Jnz5718fjss8+OiIhrrrmm/pztJRyfffbZcd1118WDDz4YY8aMiZEjR8bPf/7zOP30018XkH/yk5+kut7RROrXfixAAIC2bcnWA/GFO6YlRuPvjJwf+w7XZD0mALQbwjFpCMd/sXDhwvrAe/HFF0dtbe0xn6O2tjYuvvji+vOcd9559Y+wOOWUU2LevHktMPnrtWQ43rZtW6xcuTLx54VCIYYOHRqdOnWqn+GZZ5457usJxwAA7UOpVIqRc9ZHtz7lDQbjrn3K4pFZ61L/izUA4PWEY9IQjv+iX79+0alTp3j7298e69evP+7zrF+/Pt7+9re/7sV673vf+2LBggXNN2wT12+pcHy0+vbt+7pnIR8vj6oAAMi//ZU18b3HFiTeZfyPt0+NVzcfyHpMAGiXhGPSEI7/4vzzz4/OnTvH1772tdTn+vrXv17/yIr//J//cyxevLgZJjw6bSEcV1ZWxrvf/e76OdatW9di17IAAQDaroUb9sb5Q6ckRuNrnn4pKqqO/V/6AQBHRzchDeH4Lz70oQ9F586d4+677059rl/+8pf1j6tYvXp1M0x39NpCOI6IuOSSS+rnKCsra7HrWIAAAG1PsViKe6eujtN7lzUYjLv3K4/R8zd5NAUAtDDdhDSE47846aSTonPnzjF69OjU5xo9enR9OG5tbSUcf+tb36qf46mnnmqx61iAAABty86Kqvi3h15IvMv40rtmxKodFVmPCQAdgm5CGsLxX/zt3/5tdO7cOUaOHJn6XCNHjqx/IV5rayvh+NJLL62fo7y8vMWuYwECALQdM1buinNunpgYjXv//tWoqi1kPSYAdBi6CWkIx3/RrVu36Ny5c/Tv3z/1ufr37x+dOnWKrl27NsNkx6YthOOqqqo4+eST6+dYu3Zti13LAgQAyF5toRi3jlueGIx7DBgfY1/ZlvWYANDh6CakIRz/xV9faHfWWWelPtcnP/nJ6Ny5c3z1q19thsmOTVsIxwMHDqyf4cwzz2zRa1mAAADZ2ryvMr4+fHZiNP7KvbNj097KrMcEgA5JNyEN4fgvRowYUf9c4t/97nfHfZ7f//739ee57777mnHCo3M84fi1v3PCCQ3/J7F69eq49dZb48CBA4nnKRaLcfvtt0enTp3qzzVq1Kjj+RpHzQIEAMjOuMXb4uMDxydG4yFly6Kmrpj1mADQYekmpCEc/8WePXvi5JNPjs6dO8f73ve+WLJkyTGfY8mSJfG+970vOnXqFCeffHLs2bOnBSb9D/v374++ffu+7vPjH/+4fiGccsopb/r5sGHD3nSeownHixYtihNOOCHe9ra3xWWXXRb9+vWLRx99NMaMGROPPfZY9OrVK7p27fq68/zgBz9o0e8fYQECAGShqrYQ/Z5dnBiMP3XTxJi6YmfWYwJAh6ebkIZw/Bo33nhjdOrUKTp16hTvec974oknnjjq333yySfjve99b/3dxgMGDGjBSf/sjcH3aD4N3YV8LOH4aD4nnXRS3H777VEstvzdJRYgAEDrWrPrUFx+98zEaPyvDzwfOw5WZT0mABC6CekIx69RV1cXX/jCF+rjcefOneMjH/lIDB06NGbOnBk7d+6MmpqaqKmpiZ07d8bMmTNj6NChceaZZ0bnzp3rf+/CCy+Murq6Fp+3NcNxdXV1TJgwIQYNGhQ9e/aMj370o/GBD3wg3vrWt8Y73/nO+NCHPhQ9e/aMO++8M3bv3t3C3/w/WIAAAK1nzMLNcWb/cQ0G49N6jY1fTl4VhWIp6zEBgL/QTUhDOH6D/fv3x/nnn18fjo/289dofN5558W+ffuy/hodhgUIANDyDlfXxbWjFiXeZfzZIZNj3rq9WY8JALyBbkIawnED6urq4vrrr4+TTjqpPgg39TnppJPi//2//9cqdxrzHyxAAICWtWTrgfjCHdMSo/F3Rs6PfYdrsh4TAGiAbkIawnEjtm/fHv369YvPfOYz8Td/8zdvisV/8zd/E5/5zGeiX79+sW3btqzH7ZAsQACAllEqlWLknPXRrU95g8G4a5+yeGTWuiiVPJoCANoq3YQ0hOOjVFlZGWvWrIl58+bFvHnzYs2aNVFZWZn1WB2eBQgA0Pz2V9bE9x5bkHiX8T/ePjVe3Xwg6zEBgCboJqQhHJNrFiAAQPNasH5vnD90SmI0/slvXoqKqtqsxwQAjoJuQhrCMblmAQIANI9isRT3Tl0dp/cuazAYd+9XHqPnb/JoCgDIEd2ENIRjcs0CBABIb2dFVfzbQy8k3mV86V0zYvXOiqzHBACOkW5CGsIxuWYBAgCkM3PVrjjn5omJ0bjP71+NqtpC1mMCAMdBNyEN4ZhcswABAI5PXaEYd4xfEV16NRyMewwYH2Nf2Zb1mABACroJaQjH5JoFCABw7LYdOBJX3D838S7jr9w7Ozbtrcx6TAAgJd2ENIRjcs0CBAA4NlOX74xPDpqQGI2HlC2L2kIx6zEBgGagm5CGcEyuWYAAAEentlCMIWXLEoPxp26aGFNX7Mx6TACgGekmpCEck2sWIABA0zbvq4yvDZ+dGI2vuH9ubD9QlfWYAEAz001IQzgm1yxAAIDGjV+yPT4+cHyDwbhLr7ExbMKKqPNoCgBol3QT0hCOyTULEACgYdV1hbjxj0sS7zI+5+ZJMWvV7qzHBABakG5CGsIxuWYBAgC82YY9h+PL98xKjMbffPD52Fnh0RQA0N7pJqQhHJNrFiAAwOuNfWVb9BjQ8KMpTus1Nn45eVUUiqWsxwQAWoFuQhrCMblmAQIA/FlVbSH6Pvtq4l3G/zB4Ujy/dk/WYwIArUg3IQ3hmFyzAAEAItbuOhSX3z0zMRr/z0fmxZ5D1VmPCQC0Mt2ENIRjcs0CBAA6umdf2hJn9h/XYDA+vXdZ3DdtTRQ9mgIAOiTdhDSEY3LNAgQAOqojNYW4fswriXcZnzdkcizcsDfrMQGADOkmpCEck2sWIADQEa3aURGX3DU9MRp/Z+T82He4JusxAYCM6SakIRyTaxYgANCRlEqlGL1gU3TvV95gMO7apywemrk2SiWPpgAAdBPSEY7JNQsQAOgoDlfXxbWjFiXeZfy5W6fEok37sx4TAGhDdBPSEI7JNQsQAOgIlm07GBcNm5YYjf+/xxfGgSO1WY8JALQxuglpCMfkmgUIALRnpVIpnnxhQ3Tr2/CjKbr1KY/H5q73aAoAoEG6CWkIx+SaBQgAtFcVVbXxo6deTLzL+MLbp8biLQeyHhMAaMN0E9IQjsk1CxAAaI8WbzkQ/3j71MRo/OOnX4qKKo+mAAAap5uQhnBMrlmAAEB7UiqV4tez10W3Pg0/muLDfcvj6XkbPZoCADgquglpCMfkmgUIALQXBypr4/uPL0i8y/iLw6bF8u0Hsx4TAMgR3YQ0hGNyzQIEANqDlzbui8/dOiUxGl87elEcrq7LekwAIGd0E9IQjsk1CxAAyLNSqRQPzlgbZ/QuazAYf6TfuBizcHPWYwIAOaWbkIZwTK5ZgABAXu07XBP/59fzE+8yvvSuGbFqR0XWYwIAOaabkIZwTK5ZgABAHi1Yvzc+O2RyYjS+4XevxJGaQtZjAgA5p5uQhnBMrlmAAECeFIuluHfq6jg94dEUH+0/Lp5btCXrMQGAdkI3IQ3hmFyzAAGAvNh9qDr+/eEXEu8y/tLdM2PtrkNZjwkAtCO6CWkIx+SaBQgA5MHcNXviM7dMSozG/Z5dHFW1Hk0BADQv3YQ0hGNyzQIEANqyQrEUv5i0Mk7r1XAw7jFgfJS9ui3rMQGAdko3IQ3hmFyzAAGAtmrnwar45oPPJ95l/N9/NSs27qnMekwAoB3TTUhDOCbXLEAAoC2auWpXnHPzxMRoPOiPS6Omrpj1mABAO6ebkIZwTK5ZgABAW1JXKMYd41dEl4RHU3zixgkxcemOrMcEADoI3YQ0hGNyzQIEANqKrfuPxL/cPyfxLuOvD58dm/d5NAUA0Hp0E9IQjsk1CxAAaAvGL9ken7hxQmI0HlK+LGoLHk0BALQu3YQ0hGNyzQIEALJUVVuIfs8uTgzGn7ppYkxdsTPrMQGADko3IQ3hmFyzAAGArKzeWRGX/WJGYjS+4v65sf1AVdZjAgAdmG5CGsIxuWYBAgCtrVQqxW/mbYzu/cobDMan9Robd01cGXUeTQEAZEw3IQ3hmFyzAAGA1nSwqjZ+9NSLiXcZnzt4cjy/dk/WYwIARIRuQjrCMblmAQIAreWljfvigtumJEbj74ycH/sO12Q9JgBAPd2ENIRjcs0CBABaWrFYivumrYkzepc1GIy79SmPX89eF6VSKetRAQBeRzchDeGYXLMAAYCWtLOiKv794RcS7zK+aNi0WLL1QNZjAgA0SDchDeGYXLMAAYCWMmPlrjjn5omJ0fj//vblOFxdl/WYAACJdBPSEI7JNQsQAGhuNXXFGFK2LDEYf2zA+Hhu0ZasxwQAaJJuQhrCMblmAQIAzWnjnsr4yq9mJUbj//6rWbFhz+GsxwQAOCq6CWkIx+SaBQgANJfnFm2Jjw0YnxiNB5cti5q6YtZjAgAcNd2ENIRjcs0CBADSqqypi5+PeTkxGJ9908SYtmJn1mMCABwz3YQ0hGNyzQIEANJYuvVgfHHYtMRo/G8PvRA7D1ZlPSYAwHHRTUhDOCbXLEAA4HiUSqUYOWd9dOtb3mAwPr13WQyftjqKxVLWowIAHDfdhDSEY3LNAgQAjtW+wzXx3ccWJN5l/Llbp8SLG/dlPSYAQGq6CWkIx+SaBQgAHIsX1u6Jzw6ZnBiNr37yxThwpDbrMQEAmoVuQhrCMblmAQIAR6NQLMUvJq2M03o1HIy79yuPp+dtjFLJoykAgPZDNyEN4ZhcswABgKZsO3AkrhgxN/Eu40vvmhGrdlRkPSYAQLPTTUhDOCbXLEAAoDETl+6IswZNSIzGfZ99NapqC1mPCQDQInQT0hCOyTULEABoSFVtIQb+YUliMP74wPExbvG2rMcEAGhRuglpCMfkmgUIALzRml2H4vK7ZyZG43++b05s3leZ9ZgAAC1ONyEN4ZhcswABgL8qlUoxesGm+Ei/cQ0G4y69xsawCSuirlDMVkOjygAAIABJREFUelQAgFahm5CGcEyuWYAAQERERVVtXPP0S4l3Gf/D4EkxZ83urMcEAGhVuglpCMfkmgUIALy8aX98/rapidH427+eH3sOVWc9JgBAq9NNSEM4JtcsQADouIrFUjwwY02c0buswWDcrU95PDJrXZRKpaxHBQDIhG5CGsIxuWYBAkDHtKuiOq56ZF7iXcZfuGNaLN5yIOsxAQAypZuQhnBMrlmAANDxzFy1K865eVJiNL529KI4VF2X9ZgAAJnTTUhDOCbXLEAA6DhqC8UYWr48uvRqOBh/tP+4+P1Lm7MeEwCgzdBNSEM4JtcsQADoGDbtrYyv3js78S7jnvfMjHW7D2c9JgBAm6KbkIZwTK5ZgADQ/v3x5a3RY8D4xGh805+WRnVdIesxAQDaHN2ENIRjcs0CBID260hNIW743SuJwfhTN02Mqct3Zj0mAECbpZuQhnBMrlmAANA+Ldt2MC6+c3piNP7XB56PHQersh4TAKBN001IQzgm1yxAAGhfisVSPDRzbXTrU95gMD69d1ncO3V1FIqlrEcFAGjzdBPSEI7JNQsQANqPHQer4t8eeiHxLuPzh06JhRv2Zj0mAEBu6CakIRyTaxYgALQP4xZvj7MGTUiMxj94YmEcqKzNekwAgFzRTUhDOCbXLEAAyLfD1XWNvgCve7/yeOqFjVEqeTQFAMCx0k1IQzgm1yxAAMivlzftjy/cMS0xGn/5nlmxZtehrMcEAMgt3YQ0hGNyzQIEgPwpFEtx79TVcUbvsgaDcZdeY+PWccujpq6Y9agAALmmm5CGcEyuWYAAkC+b91XGFSPmJt5lfN6QyTF3zZ6sxwQAaBd0E9IQjsk1CxAA8uO5RVuix8DxidH4R0+96AV4AADNSDchDeGYXLMAAaDtO1hVGz8btSgxGH9swPh45sXNXoAHANDMdBPSEI5zrFQqxapVq2LUqFFx/fXXx8UXXxzvec976hfCqaee2mLXXrduXfTq1Ss+8YlPxN/+7d/GO97xjujatWt85zvfiTlz5rTYdd/IAgSAtm3B+r3xuVunJEbjrw+fHRv3VGY9JgBAu6SbkIZwnGPXXXdd/R9/Q5+WCsePPPJIvPOd70y8bqdOneKaa66JYrHlX2hjAQJA21RXKMadE1fGab0aDsan9y6LX0xaGXUFL8ADAGgpuglpCMc59tOf/vR1wfYd73hHnHXWWS0ajn/zm99Ep06d6gPxFVdcEQ8//HA88cQT8ZOf/CTe9a531V//xz/+cbNf/40sQABoezbsORxfvXd24l3GF9w2JRZu2Jf1mAAA7Z5uQhrCcY498MAD8bOf/Swef/zxWLJkSRQKhVi/fn2LheM9e/bEKaecUh+Nf/vb377pmGXLlsX73//++hmmT5/erDO8kQUIAG1HqVSK3y7YFB/tPy4xGl83+uWoqPICPACA1qCbkIZw3M60ZDju1atX/bl/+MMfJh43evTo+uM+97nPNesMb2QBAkDbsL+yJq5+8sXEYPzxgePjT69szXpMAIAORTchDeG4nWnJcNylS5f6c69ZsybxuGKxGP/1v/7X+mM3btzYrHO8lgUIANmbs2Z3nDt4cmI0/saIubF1/5GsxwQA6HB0E9IQjtuZlgrHy5Ytqz9v9+7dmzz++9//fv3xI0aMaLY53sgCBIDs1NQVY0jZsuiS8AK8M3qXxX3T1kShWMp6VACADkk3IQ3huJ1pqXA8atSo+vNeddVVTR7/8MMP1x9/9dVXN9scb2QBAkA2Vu88FP/0y5mJdxlfNGxavLr5QNZjAgB0aLoJaQjH7UxLheNBgwbVn3fAgAFNHj9lypT64y+++OJmm+ONLEAAaF2lUimeeH5DdO9XnhiNe//+1aisqct6VACADk83IQ3huJ1pqXB87bXX1p/3nnvuafL4V155pf74c84557iuOWvWrCY/w4cPtwABoJXsPlQd3xk5PzEYf+qmiTFhyfasxwQA4C+EY9IQjtuZlgrH3/ve9+rP+9BDDzV5/KpVq+qP//CHP3xc1/zr7x/txwIEgJYzbcXOOOfmSYnR+KpH5sXOg1VZjwkAwGsIx6QhHLczwjEA0Jyqagsx8A9LEoNxt77l8ejsdVH0AjwAgDZHOCYN4bid8agKAKC5LNt2MC65a3piNL70rhmxfPvBrMcEACCBcEwawnE74+V4AEBaxWIpHp61Lrr1SX4B3o1/XBJVtYWsRwUAoBG6CWkIx+1MS4XjUaNG1Z/3qquuavL4hx9+uP74q6++utnmeCMLEACa146DVfHvD7+QGIw/fcukmL5yV9ZjAgBwFHQT0hCO25mWCsfLli2rP2/37t2bPP773/9+/fEjRoxotjneyAIEgOYzfsn2+OSgCYnR+DsjF8SeQ9VZjwkAwFHSTUhDOG5nWiocR0Sceuqp9edes2ZN4nHFYvF1x27YsKFZ53gtCxAA0qusqYtez7yaGIy79yuPJ1/YEKWSF+ABAOSJbkIawnE705Lh+IYbbqg/9w9/+MPE40aPHl1/3Pnnn9+sM7yRBQgA6byyeX9cdMe0xGjc856ZsXrnoazHBADgOOgmpCEctzPHE45f+zsnnJD8n8Tu3bvj5JNPjhNOOCE6deoUY8aMedMxy5cvj7/7u7+rP9eUKVOO96scFQsQAI5PoViK4dNWxxm9yxoMxl16jY2h5cujpq6Y9agAABwn3YQ0hOMc279/f/Tt2/d1nx//+Mf1C+GUU05508+HDRv2pvMcbTiOiHjyySejU6dO9fH4G9/4RjzyyCPx5JNPxk9/+tN497vffVR3JTcXCxAAjt2W/UfiGyPmJt5l/Nkhk2Pumj1ZjwkAQEq6CWkIxzn2xuB7NJ+G7kI+lnAcEfHggw/GO97xjkavc/XVV0ehUGiBb/16FiAAHJs/vrw1egwcnxiNr37yxThQWZv1mAAANAPdhDSE4xzLKhxHRKxduzauv/766NGjR5xyyinx9re/Pc4444z49re/HbNnz27mb5rMAgSAo1NRVRvXjl6UGIw/2n9cjFm42QvwAADaEd2ENIRjcs0CBICmLVi/Ny64bUpiNP7a8NmxYc/hrMcEAKCZ6SakIRyTaxYgACQ7WFUbfZ99Nbr0ajgYn9ZrbNw1cWXUFbwADwCgPdJNSEM4JtcsQAB4s1KpFGNf2RafvmVS4l3GF9w2JRZu2Jv1qAAAtCDdhDSEY3LNAgSA19u0tzK+/ev5icH41BvGxrWjF0VFlRfgAQC0d7oJaQjH5JoFCAB/VlcoxgMz1sRH+o1LDMafHDQh/vjy1qxHBQCglegmpCEck2sWIABEvLxpf3zp7pmN3mV83eiXY+/hmqxHBQCgFekmpCEck2sWIAAdWUVVbQz8w5LEl9+desPY+MId02LO6t1ZjwoAQAZ0E9IQjsk1CxCAjmrc4u1x7uDJicG4a5+yuHPCiqiqLWQ9KgAAGdFNSEM4JtcsQAA6mq37j8R3H1vQ6GMprrh/bqzeWZH1qAAAZEw3IQ3hmFyzAAHoKArFUjw8a12c2T/55XefuHFCjJq/MYrFUtbjAgDQBugmpCEck2sWIAAdweItB+LL98xq9C7jn/7mpdh9qDrrUQEAaEN0E9IQjsk1CxCA9uxwdV3c9KelcVojL7/7/G1TY8bKXVmPCgBAG6SbkIZwTK5ZgAC0V5OW7ojzhiS//O6M3mVx27jlXn4HAEAi3YQ0hGNyzQIEoL3ZfqAq/r/HFzb6WIr/cd+cWLHdy+8AAGicbkIawjG5ZgEC0F4UiqUYOWd9fGzA+MRg3GPg+HjyhQ1efgcAwFHRTUhDOCbXLEAA2oMlWw/EV+6d3ehdxj966sXYWVGV9agAAOSIbkIawjG5ZgECkGeVNXUxuGxZnN67LDEYnz90SkxdsTPrUQEAyCHdhDSEY3LNAgQgr6Yu3xnnD52SGIxP710WQ8qXRWVNXdajAgCQU7oJaQjH5JoFCEDe7DxYFVc/9WKjj6X4yr2zY+nWg1mPCgBAzukmpCEck2sWIAB5USyW4onnN0SPgckvv/vYgPHx2Nz1UfDyOwAAmoFuQhrCMblmAQKQB8u3H4yvD2/85Xc/eGJhbD/g5XcAADQf3YQ0hGNyzQIEoC07UlOIW8ctjzMaefndeUMmx6SlO7IeFQCAdkg3IQ3hmFyzAAFoq6av3BWfv21qYjA+rdfYuOlPS+NwtZffAQDQMnQT0hCOyTULEIC2ZldFdVzz9EuNPpbiy/fMisVbDmQ9KgAA7ZxuQhrCMblmAQLQVhSLpXh63sb4eCMvv/to/3HxyKx1Xn4HAECr0E1IQzgm1yxAANqCVTsq4l/un9PoXcbffWxBbN1/JOtRAQDoQHQT0hCOyTULEIAsVdUWYtiEFdG1T/LL784dPDnGL9me9agAAHRAuglpCMfkmgUIQFZmr94dF96e/PK7Lr3GxsA/LImKqtqsRwUAoIPSTUhDOCbXLEAAWtueQ9Vx7ahFjT6W4kt3z4yXN+3PelQAADo43YQ0hGNyzQIEoLWUSqV4btGWOGvQhMRg/JF+4+LBGWujrlDMelwAANBNSEU4JtcsQABaw97DNfHDJxc2epfxt389Pzbvq8x6VAAAqKebkIZwTK5ZgAC0tMnLdsQ5N09KDMafuWVSlL26LUqlUtajAgDA6+gmpCEck2sWIAAtpaKqNn4+5uVGX37X79nFcdDL7wAAaKN0E9IQjsk1CxCAljBnze44f+iUxGh84e1TY+GGvVmPCQAAjdJNSEM4JtcsQACaU1VtIW7845JGn2Xc/7nFUVlTl/WoAADQJN2ENIRjcs0CBKC5LNq0Py4aNi0xGJ87eHLMXLUr6zEBAOCo6SakIRyTaxYgAGnV1BXjzgkr4vTeZYnR+NpRi+LAEc8yBgAgX3QT0hCOyTULEIA0VmyviH/65czEYHz2TRNj3OJtWY8JAADHRTchDeGYXLMAATgehWIpRkxfE936lCdG4+89tiB2H6rOelQAADhuuglpCMfkmgUIwLHauKcy/uX+OYnBuMeA8fG7hZujVCplPSoAAKSim5CGcEyuWYAAHK1SqRRPvrAhzuw/LjEaf+uh52PL/iNZjwoAAM1CNyEN4ZhcswABOBrbD1TF/3xkXmIw7t6vPEbOWR/ForuMAQBoP3QT0hCOyTULEIDGlEqleG7RlvjEjRMSo/HXhs+OtbsOZT0qAAA0O92ENIRjcs0CBCDJ3sM1cfWTLyYG4659yuLeqaujrlDMelQAAGgRuglpCMfkmgUIQEMmL9sR59w8KTEaX/aLGbF068GsxwQAgBalm5CGcEyuWYAAvFZFVW38fMzLicH4tF5j49Zxy6O6rpD1qAAA0OJ0E9IQjsk1CxCAv5q7Zk+cP3RKYjS+8PapsXDD3qzHBACAVqObkIZwTK5ZgABU1RZi0B+XJgbjU28YG/2fWxyVNXVZjwoAAK1KNyEN4ZhcswABOraXN+2PLw6blhiMzx08OWau2pX1mAAAkAndhDSEY3LNAgTomGoLxbhzwoo4vXdZYjS+dtSiOHCkNutRAQAgM7oJaQjH5JoFCNDxrNxRET3vmZkYjD9108QYt3hb1mMCAEDmdBPSEI7JNQsQoOMoFEvxwIw10a1veWI0/u5jC2JXRXXWowIAQJugm5CGcEyuWYAAHcPGPZVxxf1zE4NxjwHjY8zCzVEqlbIeFQAA2gzdhDSEY3LNAgRo30qlUjz1wsY4s/+4xGj8rYeejy37j2Q9KgAAtDm6CWkIx+SaBQjQfu04WBX/69F5icG4e7/yGDlnfRSL7jIGAICG6CakIRyTaxYgQPtTKpXiuUVb4hM3TkiMxl8bPjvW7jqU9agAANCm6SakIRyTaxYgQPuy93BNXP3ki4nBuGufsrh36uqoKxSzHhUAANo83YQ0hGNyzQIEaD8mL9sR59w8KTEaX/aLGbF068GsxwQAgNzQTUhDOCbXLECA/Kuoqo3rx7ySGIxP6zU2bh23PKrrClmPCgAAuaKbkIZwTK5ZgAD5NnfNnjh/6JTEaPyPt0+NhRv2Zj0mAADkkm5CGsIxuWYBAuTToeq6uPGPSxKD8ak3jI1+zy6Oypq6rEcFAIDc0k1IQzgm1yxAgHwplUoxbvH2+OyQyYnB+NzBk2PGyl1ZjwoAALmnm5CGcEyuWYAA+bFpb2X8n1/Pb/Qu42tHLYoDlbVZjwoAAO2CbkIawjG5ZgECtH21hWLcN21NdO9XnhiMP3XTxBi3eFvWowIAQLuim5CGcEyuWYAAbdv89XvjkrumN3qX8dVPvRi7KqqzHhUAANod3YQ0hGNyzQIEaJv2Ha6J68e80mgw/sfbp8Z0zzIGAIAWo5uQhnBMrlmAAG1LqVSK3y7YFJ8cNCExGHftUxZ3TlgRVbWFrMcFAIB2TTchDeGYXLMAAdqOVTsq4ooRcxu9y/jKB+bG6p2Hsh4VAAA6BN2ENIRjcs0CBMjekZpC3DZueZzRuywxGJ9908R45sXNUSqVsh4XAAA6DN2ENIRjcs0CBMjW1OU744LbpjR6l3GvZ16N/ZU1WY8KAAAdjm5CGsIxuWYBAmRj+4Gq+OGTCxsNxpf9YkYs3LA361EBAKDD0k1IQzgm1yxAgNZVVyjGI7PWxUf7j0sMxh/pNy4enLE2agvFrMcFAIAOTTchDeGYXLMAAVrPok37459+ObPRu4y/99iC2LL/SNajAgAAoZuQjnBMrlmAAC3vwJHa6Pfs4ujSKzkYnzdkckxcuiPrUQEAgNfQTUhDOCbXLECAllMqleIPL2+NT98yKTEYn967LIaULYvD1XVZjwsAALyBbkIawjG5ZgECtIx1uw/Hvz/8QqOPpfgf982J5dsPZj0qAACQQDchDeGYXLMAAZpXdV0h7p60Krr1LU8Mxp+4cUL8Zt7GKBZLWY8LAAA0QjchDeGYXLMAAZrP7NW746I7pjV6l/G1oxfF7kPVWY8KAAAcBd2ENIRjcs0CBEhvV0V1/PQ3LzUajC8aNi3mrtmT9agAAMAx0E1IQzgm1yxAgONXLJbiiec3xMcHjk8Mxh/uWx6/mrIqqusKWY8LAAAcI92ENIRjcs0CBDg+S7cejK/eO7vRu4yvemRebNhzOOtRAQCA46SbkIZwTK5ZgADH5lB1Xdz8p6Vxeu+yxGD8mVsmxdhXtkWp5OV3AACQZ7oJaQjH5JoFCHB0SqVSjFu8PT47ZHJiMD6t19gY+IclUVFVm/W4AABAM9BNSEM4JtcsQICmbdpbGf/n1/MbfSzFl++ZFa9s3p/1qAAAQDPSTUhDOCbXLECAZLWFYtw3bU1071eeGIw/NmB8jJyzPgpFj6UAAID2RjchDeG4HSgvL48rr7wyunTpEieddFK8973vjU9/+tNx8803x65du5rtOtOmTatfNkfzufDCC5vt2kksQICGzV+/Ny65a3qjdxn/6KkXY8fBqqxHBQAAWohuQhrCcY5VVlbGP//zPzcab9/3vvdFeXl5s1xPOAZo+/Ydronrx7zSaDD+/G1TY/rK5vs/FgEAgLZJNyEN4TinisVi9OzZs/6P//3vf3/07t07nnrqqbj//vvj0ksvrf/ZSSedFLNnz059zdeG4yuvvDKeffbZRj+tsZAsQIA/K5VK8dsFm+KTgyYkBuOufcpi2IQVUVVbyHpcAACgFegmpCEc59RDDz1U/4f/4Q9/OLZu3fqmY4YNG1Z/TLdu3aK2tjbVNV8bjgcOHJjqXM3FAgSIWL3zUFwxYm6jdxlf+cDcWL3zUNajAgAArUg3IQ3hOIeKxWL8/d//ff0f/rx58xKP/dKXvlR/3EMPPZTqusIxQNtSWyjGvVNXR7c+yS+/O/umifHMi5ujVPLyOwAA6Gh0E9IQjnPotQH3ggsuaPTYyZMn1x/7xS9+sdmuKxwDZOvVzQfi8rtnNnqXca9nXo39lTVZjwoAAGRENyEN4TiHrr/++vo/+qFDhzZ6bF1dXbzrXe+KE044Id7ylrfE4cOHj/u6wjFA9qpqCzGkfFmc3rssMRhf9osZsXDD3qxHBQAAMqabkIZwnEOXX355/R/9lClTmjz+ggsuqD9+/vz5x33d14bjHj16xFlnnRUnn3xyvO1tb4sPfvCD8cUvfjFuueWW2LFjx3Ff41hZgEBH8vzaPfGFO6YlBuPu/cpjxPQ1UVsoZj0qAADQBugmpCEc59Bpp51W/0e/bt26Jo+/6qqr6o9/4oknjvu6rw3HjX1OPPHEGDZsWOrnac6aNavJz/Dhwy1AoN2rqKqNPr9/tcmX363fffz/qgQAAGh/hGPSEI5z6D/9p/9U/0dfUVHR5PHXXntt/fG/+tWvjvu6fw3HZ599dlx33XXx4IMPxpgxY2LkyJHx85//PE4//fTXBeSf/OQnx32tiDiqSP3ajwUItEeTl+2IcwdPTgzGPQaMj6fnbfTyOwAA4E2EY9IQjnPorW99a/0ffV1dXZPH9+nTp/74IUOGHPd1t23bFitXrkz8eaFQiKFDh0anTp3qr/fMM88c9/WEY6Aj23OoOq55+qVG7zL+zsgFsf1AVdajAgAAbZRwTBrCcQ5lFY6PVt++fV/3LOTj5VEVQEdUKpXiuUVb4pODJiQG47Nvmhh/emWru4wBAIBGCcekIRznUFaPqjhalZWV8e53v/uYnsN8vCxAoD3Zuv9IfPvX8xu9y/jaUYti3+GarEcFAAByQDchDeE4h7J6Od6xuOSSS+qvWVZW1mLXsQCB9qBYLMUTz2+Ijw0YnxiMzx86Jaat2Jn1qAAAQI7oJqQhHOfQ5ZdfXv9HP2XKlCaPv+CCC+qPnz9/fitMGPGtb32r/ppPPfVUi13HAgTybu2uQ3HFiLmN3mU84LnFcai66UcTAQAAvJZuQhrCcQ5df/319X/0Q4cObfTYurq6eNe73hUnnHBCvOUtb4nDhw+3yoyXXnpp/Yzl5eUtdh0LEMirukIx7p++Jj7ctzwxGF80bFrMX78361EBAICc0k1IQzjOoalTp9b/0X/+859v9NjJkyfXH3vRRRe1ynxVVVVx8skn11937dq1LXYtCxDIoyVbD0TPe2YmBuPTe5fF7eOXR1VtIetRAQCAHNNNSEM4zqFCoRD/5b/8l/o//Hnz5iUe+6Uvfan+uAcffLBV5hs4cGD9Nc8888wWvZYFCORJVW0hbh+/PE7vXZYYjf/plzNjydYDWY8KAAC0A7oJaQjHOfXAAw/U/+F37949tm7d+qZjhg0bVn9M165do6ampsFzrV+/vv64E05o+D+J1atXx6233hoHDiTHjGKxGLfffnt06tSp/lyjRo06vi94lCxAIC8WrN8bFw2blhiMu/Utj/umrYm6QjHrUQEAgHZCNyEN4TinCoXC616S9/73vz/69OkTTz/9dIwYMSIuu+yy+p+deOKJMWPGjMRzHU04XrRoUZxwwgnxtre9LS677LLo169fPProozFmzJh47LHHolevXtG1a9fXnecHP/hBS339ehYg0NYdqq6LAc8tji69kl9+d8X9c2PtrkNZjwoAALQzuglpCMc5dvjw4fja1772ulj7xs973/veGDt2bKPnOZZwfDSfk046KW6//fYoFlv+rjkLEGjLpq3YGecPnZIYjD82YHw8/vyGKBZLWY8KAAC0Q7oJaQjH7cDYsWPjG9/4Rpx66qlx4oknxnve854455xzYtCgQbFz584mf/9ownF1dXVMmDAhBg0aFD179oyPfvSj8YEPfCDe+ta3xjvf+c740Ic+FD179ow777wzdu/e3dxfMZEFCLRF+w7XxLWjFyUG41NvGBv/+9F5sXX/kaxHBQAA2jHdhDSEY3LNAgTaklKpFGNf2Rbn3DwxMRh/ctCEeG7RliiV3GUMAAC0LN2ENIRjcs0CBNqKHQer4ruPLWj0LuNrnn4p9hyqznpUAACgg9BNSEM4JtcsQCBrpVIpfjNvY/QYOD4xGJ87eHJMWroj61EBAIAORjchDeGYXLMAgSxt2HM4vvng843eZdzn96/GwararEcFAAA6IN2ENIRjcs0CBLJQKJbioZlro3u/8sRgfOHtU+P5tXuyHhUAAOjAdBPSEI7JNQsQaG0rtlfEV+6dnRiMT+s1NoaUL4uq2kLWowIAAB2cbkIawjG5ZgECraW6rhB3TVwZXfuUJUbjy34xI17ZvD/rUQEAACJCNyEd4ZhcswCB1vDSxn1xyV3TE4Nxtz7l8aspq6K2UMx6VAAAgHq6CWkIx+SaBQi0pMqaurjpT0ujS6/kl9/9j/vmxOqdFVmPCgAA8Ca6CWkIx+SaBQi0lFmrdscFt01JDMZn9h8XI+esj2KxlPWoAAAADdJNSEM4JtcsQKC5HaisjZ+PeTkxGJ96w9i46pF5sXlfZdajAgAANEo3IQ3hmFyzAIHmUiyWYvT8TXHOzZMSg/EnbpwQv1u4OUoldxkDAABtn25CGsIxuWYBAs1h/vq90fOemY3eZXz1ky/GrorqrEcFAAA4aroJaQjH5JoFCKSxZf+R+NFTLzYajD99y6QYt3h71qMCAAAcM92ENIRjcs0CBI5HZU1d3DlxZXy4b3mj0fj6Ma/EgcrarMcFAAA4LroJaQjH5JoFCByLUqkUz760Jc4dPLnRYNzznpkxb93erMcFAABIRTchDeGYXLMAgaP18qb98fXhsxsNxufcPDFGz98UhaKX3wEAAPmnm5CGcEyuWYBAU3YcrIrrRr/caDDu2qcshpQvi4oqj6UAAADaD92ENIRjcs0CBJJU1Rbi3qmr48z+4xqNxt99bEGs330463EBAACanW5CGsIxuWYBAm9UKpWi/NVt8blbpzQajC+5a3rMWrU763EBAABajG5CGsIxuWYBAq+1dOvBuPKBuY0G47MGTYjH566PukIx63EBAABalG5CGsIxuWYBAhERew5VR69nXo3TeiUH49N7l8XAPyyJ/ZU1WY8LAADQKnQT0hCOyTXSN7dqAAAgAElEQVQLEDq2mrpiPDRzbfQYOL7Ru4yvemRerNpRkfW4AAAArUo3IQ3hmFyzAKFjKpVKMWX5jrjojmmNBuOL7pgWU5bviFKplPXIAAAArU43IQ3hmFyzAKHjWb2zIq56ZF6jwbjHwPHx0My1UVPnOcYAAEDHpZuQhnBMrlmA0HHsr6yJgX9YEqf3LksMxl16jY3ev3819hyqznpcAACAzOkmpCEck2sWILR/dYViPD53fZw1aEKjdxlf+cDcWLr1YNbjAgAAtBm6CWkIx+SaBQjt26xVu+PSu2Y0Gow/d+uUKH91m+cYAwAAvIFuQhrCMblmAUL7tH734fjuYwsaDcZn9h8X905dHVW1hazHBQAAaJN0E9IQjsk1CxDal4qq2hhSviy69kl+jvGpN4yN60a/HDsOVmU9LgAAQJumm5CGcEyuWYDQPhSKpRg1f2Occ/OkRoPx14fPjkWb9mc9LgAAQC7oJqQhHJNrFiDk37x1e6PnPTMbDcbnDp4czy3a4jnGAAAAx0A3IQ3hmFyzACG/tuw/Ej966sVGg/GH+5bHnRNXRmVNXdbjAgAA5I5uQhrCMblmAUL+VNbUxZ0TVsSH+5Y3Go1/9NSLsXlfZdbjAgAA5JZuQhrCMblmAUJ+lEqlePalLXHu4MmNBuOe98yMeev2Zj0uAABA7ukmpCEck2sWIOTDok3742vDZzcajM+5eWKMnr8pCkXPMQYAAGgOuglpCMfkmgUIbduOg1Vx7ehFjQbjrn3KYkj5sqioqs16XAAAgHZFNyEN4ZhcswChbTpQWRt3TlgRZ/Yf12g0/u5jC2L97sNZjwsAANAu6SakIRyTaxYgtC0Hq2rjF5NWRo+B4xsNxpfeNSNmr96d9bgAAADtmm5CGsIxuWYBQttwqLoufjVlVXy8iWB81qAJ8fjc9VFXKGY9MgAAQLunm5CGcEyuWYCQrcPVdTF82uo4a9CERoPx6b3LYuAflsT+ypqsRwYAAOgwdBPSEI7JNQsQsnGkphAPzFgTn7ppYqPB+NQbxsYPnlgYq3dWZD0yAABAh6ObkIZwTK5ZgNC6qmoL8dDMtXHOzU0H4+89tiCWbj2Y9cgAAAAdlm5CGsIxuWYBQuuoqi3Eo7PXxadvmdRkMP7OyPmxeMuBrEcGAADo8HQT0hCOyTULEFpWdV0hHp+7Ps4dPLnJYPy/Hp0XL2/an/XIAAAA/IVuQhrCMblmAULLqKkrxpMvbIjzhjQdjP/94RfixY37sh4ZAACAN9BNSEM4JtcsQGhetYVijJq/Mc4fOqXJYPzNB5+P+ev3Zj0yAAAACXQT0hCOyTULEJpHXaEYv12wKT5/29Qmg/EVI+bG82v3ZD0yAAAATdBNSEM4JtcsQEinUCzF71/aHBfe3nQw/uf75sSc1bujVCplPTYAAABHQTchDeGYXLMA4fgUiqV4btGWuGjYtCaD8deGz46Zq3YJxgAAADmjm5CGcEyuWYBwbIrFUox9ZVv8tzunNxmMv/KrWTF1xU7BGAAAIKd0E9IQjsk1CxCOTrFYinGLt8Vlv5jRZDD+p1/OjMnLdgjGAAAAOaebkIZwTK5ZgNC4UqkUE5Zsjy/dPbPJYHz53TNj/JLtgjEAAEA7oZuQhnBMrlmA0LBSqRRTlu+IL98zq8lgfMld06P81W1RLArGAAAA7YluQhrCMblmAcLrlUqlmLZiZ3zl3tlNBuOL75wef3plq2AMAADQTukmpCEck2sWIPxZqVSKWat2x9eHNx2ML7pjWjy3aEsUBGMAAIB2TTchDeGYXLMAIWLumj1xxf1zmwzG/3j71Hjmxc1RVyhmPTIAAACtQDchDeGYXLMA6cheWLsnrnyg6WB8wW1T4rcLNgnGAAAAHYxuQhrCMblmAdIRLdywN7710PNNBuPzh06J38zbGLWCMQAAQIekm5CGcEyuWYB0JC9t3BdXPTKvyWD82SGT44nnN0RNnWAMAADQkekmpCEck2sWIO3d/sqaGDV/Y3zzwabvMP6HwZPisbnro7qukPXYAAAAtAG6CWkIx+SaBUh7VFFVG8+8uDm+/ev50bVPWZPB+NO3TIpHZ6+LqlrBGAAAgP+gm5CGcEyuWYC0F5U1dfHHl7fG9x9fEN36ljcZi0+9YWycc/PEeGjm2jhSIxgDAADwZroJaQjH5JoFSJ5V1RZi3OLtcfVTL8ZH+o07qlh86g1j45ODJsSI6WuisqYu668AAABAG6abkIZwTK5ZgORNTV0xJi/bET8btSg+NmD8UcfiU28YG//tzulx//Q1cahaMAYAAKBpuglpCMfkmgVIHtQVijFj5a74+ZiX4xM3TjimWPyFO6bFsAkrYsX2iqy/BgAAADmjm5CGcEyuWYC0VYViKeau2RO9f/9qfOqmiccUi88fOiWGlC+LxVsORKlUyvqrAAAAkFO6CWkIx+SaBUhbUiyWYuGGvTHwD0vi07dMOqZYfO7gyXHTn5bGSxv3icUAAAA0C92ENIRjcs0CJGulUile3rQ/bhm7NM4bMvmYYvE5N0+M/s8tjnnr9kaxKBYDAADQvHQT0hCOyTULkCyUSqVYuvVg3DZueXz+tqnHFIvPGjQhej3zSsxZvTsKYjEAAAAtSDchDeGYXLMAaU2rdlTEnRNXxkXDph1TLO4xcHz839++HNNW7IzaQjHrrwEAAEAHoZuQhnBMrlmAtLT1uw/Hr6asist+MeOYYvFH+4+Ln/zmpZi4dEdU1xWy/hoAAAB0QLoJaQjH5JoFSEvYvK8yRkxfE1++Z9YxxeLu/crjh08ujPJXt0VVrVgMAABAtnQT0hCOyTULkOay42BVPDJrXXxt+OxjisXd+pTHdx9bEM8t2hKHq+uy/hoAAABQTzchDeGYXLMASWP3oep4fO76uGLE3OjS6+hj8Rm9y+J/PTovxizcHAeO1Gb9NQAAAKBBuglpCMfkmgXIsaiuK8SSrQfiyRc2xL899EKcdgyx+LReY+NbDz0fT8/bGPsO12T9VQAAAKBJuglpCMfkmgVIkl0V1TFj5a4YMX1N/PQ3L8Wld82IM3qXHdNjKLr0GhtXjJgbj89dH7sqqrP+SsD/396dB1dR5W0c7xBCFhKQLfDKEhAE1MEaBWQJAYHB0RkZcRDBEggOaqmjgowiywhCEBQQkBhkFZCQBR0ZEAmKCAiMsimoIDoswxIIxIVAAMn2vH9Y6UqTuyV9k9ybfD9Vp4qif/ec7pucPqknnXMBAAAAlAi5CewgOIZf4waInLx8fXcmS+9/eVKvfHhQgxd/ofZxG0sUEF/b+iVs1+JtR3Xm/JWKvjwAAAAAAEqN3AR2EBzDr3EDrFp+yr6q7f/N1KLPjmhU6j7dM+cz3Thuva2QuLD9ee5nemvLYZ346VJFXyYAAAAAAF5BbgI7CI7h17gBVk65efn6IeOC1uxL16tp3yn27Z264xV7TxE7anfN2qr4TT/oaGZ2RV8yAAAAAABeR24COwiO4de4Afq/85dy9PmRH/X29qN64d19unfuNrUe752niIu2zlM/0SNLd2n6hu/0wf50HSMsBgAAAABUcuQmsIPgGH6NG6D/yMsv0JFzF7Vu/2nN2HBIf1u6S12nbfJ6QHzj+PX689zP9I9V+7R421HtOJypn7OvVvTlAwAAAABQ7shNYAfBMfwaN0DfdOFKjnYd+0nL/3NMY/71te57c7va/jPN6yFxxykbNWTJTk1df1D//uqUvs+4oJy8/Iq+fAAAAAAAfAK5CewgOIZf4wZYsfLzC3T8x0tK++aMZn38vR5bvlvdXvP+U8Stxn2oP87equdSvtLCrUe07YdMZV78taIvHwAAAAAAn0ZuAjsIjiuB9evXa+DAgWrevLlCQkJUr149dejQQXFxcTp37lyZjHn06FGNGTNGt956q6677jqFhYWpVatWGj58uHbs2FEmYzrCDbDsXbqaq+/OZOmjb89o0WdH9NK/v1Hs2zvVc+Zm3TjO+3sR3z75Yz286AtNWXdA7+05qQPpWbqay1PEAAAAAACUFLkJ7CA49mOXLl1S//79zRuAo1a/fn2tX7/eq+MuWbJENWvWdDpmQECAnnnmGeXnl33Yxw3Qvvz8AmVkXdHOoz/p3T0n9frH32tE8pe6P2G72sdt9HowXNhuGPuh+szaomeSvtS8zYe1+dBZnc26ooKCgop+SwAAAAAAqBTITWAHwbGfys/P15///Gdz8jdo0EBjx47VypUr9dZbb+muu+4yj4WEhGj79u1eGTc5OVkBAQFmQDxgwAAtXrxYK1as0LPPPqvw8HBz3Kef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width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
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    }
   ],
   "source": [
    " \"\"\"        \n",
    " (Casnati's equation) was found to fit cross-section data to\n",
    " typically better than +-10% over the range 1<=Uk<=20 and 6<=Z<=79.\"\n",
    " \n",
    " Note: This result is for K shell. L & M are much less well characterized.\n",
    " C. Powell indicated in conversation that he believed that Casnati's\n",
    " expression was the best available for L & M also.\n",
    "\"\"\"\n",
    "shell_occupancy={'K':2,'L-1':2,'L-2':2,'L-3':4,'M-1':2,'M-1':2,'M-2':2,'M-3':4,'M-4':4,'M-5':6}\n",
    "import scipy.constants as const\n",
    "res = 0.0;\n",
    "beamE = 30\n",
    "rel = []\n",
    "Z= []\n",
    "shell = 'M-4'\n",
    "for element in range(25,56):\n",
    "    ee = ffast[element]['edges'][shell] #getEdgeEnergy();\n",
    "    u =  ee/beamE;\n",
    "    #print(u)\n",
    "    if(u > 1.0):\n",
    "        u2 = u * u;\n",
    "        phi = 10.57 * np.exp((-1.736 / u) + (0.317 / u2));\n",
    "        #psi = Math.pow(ee / PhysicalConstants.RydbergEnergy, -0.0318 + (0.3160 / u) + (-0.1135 / u2));\n",
    "        psi = np.power(ee / const.Rydberg, -0.0318 + (0.3160 / u) + (-0.1135 / u2));\n",
    "\n",
    "        i = ee / const.electron_mass# PhysicalConstants.ElectronRestMass;\n",
    "        t = beamE / const.electron_mass#PhysicalConstants.ElectronRestMass;\n",
    "        f = ((2.0 + i) / (2.0 + t)) * np.sqrt((1.0 + t) / (1.0 + i)) * np.power(((i + t) * (2.0 + t) * np.sqrt(1.0 + i))/ ((t * (2.0 + t) * np.sqrt(1.0 + i)) + (i * (2.0 + i))), 1.5);\n",
    "        getGroundStateOccupancy = shell_occupancy[shell]\n",
    "        res = ((getGroundStateOccupancy * np.sqrt((const.value('Bohr radius') * const.Rydberg) / ee) * f * psi * phi * np.log(u)) / u);\n",
    "        \n",
    "        rel.append(res)\n",
    "        Z.append(element)\n",
    "    #print(res)\n",
    "    \n",
    "plt.figure()\n",
    "plt.title(f\"Casnati's cross section for beam energy {beamE:.0f} keV\")\n",
    "plt.plot(Z,rel)\n",
    "\n",
    "plt.xlabel('atomic number Z')\n",
    "plt.ylabel('Q [barns]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even though the cross section raises fast with overvoltage $U$, \n",
    "too low overvoltage leads to a small cross section, which results in poor excitation of the X-ray line.\n",
    "\n",
    "We can also see that the intial overvoltage $U_0$ varies with atomic number $Z$, which will affect the relative generation of X-rays from different elements.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## X-ray Production in a Thin Foil\n",
    "\n",
    "Now we have all the ingeedients to look at the total generation of X-rays.\n",
    "\n",
    "The number of photons $n_X$ produced in a thin foil of thickness $t$ is :\n",
    "$$ n_x  = Q_I(E) \\ \\omega   N_A  \\frac{1}{A} \\rho \\ t $$\n",
    "\n",
    "- $n_X$ [photons/e^-]\n",
    "- $Q_I(E)$ [ ionizations/e$^-$ (atoms / cm$^2$)): ionization cross section\n",
    "- $\\omega$ [X-rays/ ionization]: fluorescent yield = number of X-rays generated per ionization\n",
    "- $ N_A$  [atoms per mol]: Avogadro’s number \n",
    "- $A$ [g/moles]: atomic weight\n",
    "- $\\rho$ [g/cm$^3$]: density of sample\n",
    "- $t$ [cm]: thickness of sample\n",
    "\n",
    "The number of X-rays increase linearly with the number of atoms per unit area ($N_A  \\frac{1}{A} \\rho \\ t $).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## X-ray Production in a Thick Solid Sample\n",
    "\n",
    "If the sample is sufficient thick so that all electrons interact ( several micrometers) thr X-ray intensity is found to follow an expression fo the form:\n",
    "\n",
    "$$I \\approx i_p \\left[ (E_0-E_c)/E_0\\right]^n \\approx i_p [U_0-1]^n$$\n",
    "\n",
    "where:\n",
    "- $i_p$: beam current \n",
    "- $n$: exponent $n$ depends on particular element and shell (Lifshin et al. 1980) \n",
    "\n",
    "The exponent $n$ is ususally between 1.5 and 2. See what changes in the plot below if you change this exponent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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",
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       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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IiLic5/7XNeQPPbYY4WfEY4BAACAvfWb51YURuP/74dTYuO2nWWf1xB0E1IIx0RExDnnnNM1JCNGjCj8jHAMAAAA7I3JL62JIweMronGpwydGK9v2lH2eQ1DNyGFcExERBx77LFdQzJ9+vTCz7z56+9973vj9NNPj3e+851xwAEHxCGHHBInnXRSXHzxxfHCCy/06t0GEAAAAPqWWUs3xjGDx9RE449cOS5eXr217PMaim5CCuGYmDJlSteIHHLIIbv8QXpvfmZP7xvf+EY0Nzf3yu0GEAAAAPqORau3xkeuHFcTjY8ZPCZmLd1Y9nkNRzchhXDc4LZv3x7HHHNM14gMGzZsl5/t169fHHbYYfFP//RPcfvtt8fDDz8c999/f1x77bVx6qmnVsXjU045JXbsSPu/nkybNm2Pb/jw4QYQAAAA+oDlG7bHJ66bUBONjxgwOiYvXFP2eQ1JOCaFcNzAKpVKfPWrX62KvW1tbbv8/JQpU3b7faNGjYp3vOMdXd/3ve99L+m+vf0vnA0gAAAAlGvt1tY488bJhT8M7z9nryj7vIYlHJNCOG5gl1xySdd4vOc974nly5cnf+eECRO6vvOAAw6IVatW7fd3CccAAADQ921paYsv3jK1MBrfPXVJ2ec1NOGYFMJxgxo4cGDXcLzzne/s1h9qd9ZZZ3V9989+9rP9/h7/VAUAAAD0bS1tHXHOndMLo/GNYxeWfV7DE45JIRw3oEGDBnWNxsEHHxxz5szp1u+/7rrrur7/3//937v1u/+QAQQAAIBytHd0xrd+8WxhNB7wmxeiUqmUfWLD001IIRw3mAEDBnQNxkEHHRSzZ8/u9j/jrrvu6vozvv3tb3f79/8+AwgAAAC9r7OzEpc8PKcwGn/3/tnR0Ska9wW6CSmE4wZy6aWX9ng0jogYOnRo159z6aWX9sif8SYDCAAAAL2rUqnEVY/NL4zG5/306Wht7yj7RP5/ugkphOMG8f3vf79XonFExGc/+9muP+uee+7psT8nwgACAABAb7tj8iuF0fgrdzwZ21rbyz6P36ObkEI4bgAXX3xx1b9p3JPRePLkyV1/1lve8pZYuXJlj/1ZEQYQAAAAetMvZywtjMZnD3s8Nm7bWfZ5/AHdhBTCcZ276KKLuuUH4V122WWxZMmS3X5m7NixcdBBB3X9eRdccMF+/Vn7wgACAABA7/jd3JVxWP/aaHzq9ZNi1eaWss+jgG5CCuG4jg0ePLhrHPr16xdDhgyJkSNH7vEtXLiw5rv+7M/+LPr16xcnn3xyXHzxxXHnnXfGww8/HA8++GAMHTo0Tj/99Ko/6+STT47m5uYe/zsaQAAAAOh5TyxaG0cNHF0TjT9+9fhYsrbn//c/+0c3IYVwXMfOPPPMqpi7t2/IkCE13/VmON6b981vfjO2bNnSK39HAwgAAAA9a/ayjfGhwU010fj4K8bGi69vLvs8dkM3IYVwXMe6Mxw/88wz8aMf/SjOPffc+OhHPxp/+Zd/GW9729viwAMPjPe+971x+umnx4ABA+Kll17q1b+jAQQAAICes2j11vjIleNqovHRg8bEjCXryz6PPdBNSCEckzUDCAAAAD1j+Ybt8YnrJtRE4yMGjI7x81eXfR57QTchhXBM1gwgAAAAdL+1W1vjzBsn10TjQy8bFY/MWlH2eewl3YQUwjFZM4AAAADQvba0tMUXb5laGI3vnrqk7PPYB7oJKYRjsmYAAQAAoPu0tHXEOXdOL4zGN45dWPZ57CPdhBTCMVkzgAAAANA92js641u/eLYwGg/4zQtRqVTKPpF9pJuQQjgmawYQAAAA0nV2VuKSh+cURuPv3j87OjpF4xzpJqQQjsmaAQQAAIA0lUolrnpsfmE0Pu+nT0dre0fZJ7KfdBNSCMdkzQACAABAmjsmv1IYjb9yx5OxrbW97PNIoJuQQjgmawYQAAAA9t8vZywtjMZnD3s8Nm7bWfZ5JNJNSCEckzUDCAAAAPvnd3NXxmH9a6PxqddPilWbW8o+j26gm5BCOCZrBhAAAAD23ROL1sZRA0fXROOPXz0+lqxtLvs8uoluQgrhmKwZQAAAANg3s5dtjA8NbqqJxsdfMTZefH1z2efRjXQTUgjHZM0AAgAAwN57adXW+MiV42qi8dGDxsSMJevLPo9uppuQQjgmawYQAAAA9s7S9dvi5Gsn1ETjIwaMjvHzV5d9Hj1ANyGFcEzWDCAAAADs2eotLfHpGybVRONDLxsVv561ouzz6CG6CSmEY7JmAAEAAGD3Nm7bGWcPe7wwGt89dUnZ59GDdBNSCMdkzQACAADArjW3tsf/un1aYTQeNn5R2efRw3QTUgjHZM0AAgAAQLGWto742k+mF0bjIY/Oi0qlUvaJ9DDdhBTCMVkzgAAAAFCrraMzvvWLZwuj8SUPz4nOTtG4EegmpBCOyZoBBAAAgGqdnZW4eMScwmj87XtnRntHZ9kn0kt0E1IIx2TNAAIAAMB/q1QqcflvXyyMxl+/a0a0tHWUfSK9SDchhXBM1gwgAAAA/Lebxr5UGI2/cseT0dzaXvZ59DLdhBTCMVkzgAAAAPBf7npiSWE0/tzNT8Sm7TvLPo8S6CakEI7JmgEEAACAiIeeWVYYjU+/YXKs2dJS9nmURDchhXBM1gwgAAAAjW7U3DfisP610fgT102I5Ru2l30eJdJNSCEckzUDCAAAQCOb8tKaOGrg6JpofOJV42LR6q1ln0fJdBNSCMdkzQACAADQqJ59bUMcM3hMTTQ+7vKmeH75prLPow/QTUghHJM1AwgAAEAjmrdycxw/ZGxNND560JiYvnh92efRR+gmpBCOyZoBBAAAoNEsWdscH796fE00PmLA6Jgwf3XZ59GH6CakEI7JmgEEAACgkby+aUd8aujEmmh8WP9RMfK518s+jz5GNyGFcEzWDCAAAACNYl1za3zmpik10fjQy0bFfdNfK/s8+iDdhBTCMVkzgAAAADSCzTva4ou3TC2MxndMfqXs8+ijdBNSCMdkzQACAABQ73bs7Ii/+/FThdH4utELolKplH0ifZRuQgrhmKwZQAAAAOrZzvbO+MY9zxRG48semSsas1u6CSmEY7JmAAEAAKhXHZ2V+O4Dswuj8XcfmB0dnaIxu6ebkEI4JmsGEAAAgHpUqVTiskfmFkbjb9zzTOxs7yz7RDKgm5BCOCZrBhAAAIB6U6lUYujoBYXR+O9+/FTs2NlR9olkQjchhXBM1gwgAAAA9eaOya8URuMv3jI1Nu9oK/s8MqKbkEI4JmsGEAAAgHrysydfLYzGn7lpSqxrbi37PDKjm5BCOCZrBhAAAIB68fDM5YXR+FNDJ8brm3aUfR4Z0k1IIRyTNQMIAABAPRg19404vH9tND7pmvGxeG1z2eeRKd2EFMIxWTOAAAAA5G7ywjVx5IDRNdH4hCFjY/7KLWWfR8Z0E1IIx2TNAAIAAJCz6YvXxwcHjamJxsde3hTPLdtY9nlkTjchhXBM1gwgAAAAuXpu2cY47vKmmmj8wUFj4qnF68o+jzqgm5BCOCZrBhAAAIAcLXhjS3zkynE10fjIAaNj0sLVZZ9HndBNSCEckzUDCAAAQG6WrG2Ok64ZXxOND+8/Kn43d2XZ51FHdBNSCMdkzQACAACQkxUbt8enhk6sicaHXjYqHn52ednnUWd0E1IIx2TNAAIAAJCLNVta4owbJxdG4589+WrZ51GHdBNSCMdkzQACAACQg43bdsZnb368MBrfPunlss+jTukmpBCOyZoBBAAAoK/b2tIWX759WmE0HjpmQVQqlbJPpE7pJqQQjsmaAQQAAKAv27GzI8758fTCaDxo5AuiMT1KNyGFcEzWDCAAAAB9VWt7R5x/zzOF0fiSEXOis1M0pmfpJqQQjsmaAQQAAKAvau/ojO/cN6swGv/zfTOjvaOz7BNpALoJKYRjsmYAAQAA6Gs6OytxyYg5hdH4/Hueidb2jrJPpEHoJqQQjsmaAQQAAKAvqVQqMXjki4XR+JwfT48dO0Vjeo9uQgrhmKwZQAAAAPqKSqUS149ZWBiNv3TbtNjS0lb2iTQY3YQUwjFZM4AAAAD0FXdMfqUwGn/25sdj47adZZ9HA9JNSCEckzUDCAAAQF/wsydfLYzGZ9w4OdZsaSn7PBqUbkIK4ZisGUAAAADK9vDM5YXR+JShE2P5hu1ln0cD001IIRyTNQMIAABAmUbNfSMO718bjU+6ZnwsXttc9nk0ON2EFMIxWTOAAAAAlGXywjVx5IDRNdH4hCFjY/7KLWWfB7oJSYRjsmYAAQAAKMP0xevjg4PG1ETjYy9vitnLNpZ9HkSEbkIa4ZisGUAAAAB62+xlG+O4y5tqovHRg8bEU4vXlX0edNFNSCEckzUDCAAAQG968fXNcfyQsTXR+MgBo2PSwtVlnwdVdBNSCMdkzQACAADQWxat3hofvWpcTTQ+vP+o+N3clWWfBzV0E1IIx2TNAAIAANAblqxtjpOumVATjQ+9bFQ8PHN52edBId2EFMIxWTOAAAAA9LTlG7bHKUMnFkbje6e/VvZ5sEu6CSmEY7JmAAEAAOhJqza3xOk3TC6Mxj95YnHZ58Fu6SakEI7JmgEEAACgp6zd2hqf+eGUwmh8y4SXyz4P9kg3IYVwTNYMIAAAAD1h0/ad8fkfPVEYjYeOWRCVSqXsE2GPdBNSCMdkzQACAADQ3ba0tMWXb59WGI2v+O2LojHZ0E1IIRyTNQMIAABAd9q+sz2++h9PFUbjS389Nzo7RWPyoZuQQjgmawYQAACA7tLS1hF/f/eMwmh84UPPRYdoTGZ0E1IIx2TNAAIAANAddrZ3xj/+/NnCaPzP982Mto7Osk+EfaabkEI4JmsGEAAAgFTtHZ1xwS9nFUbjb/7smWht7yj7RNgvugkphGOyZgABAABI0dlZiYtHzCmMxuf+ZEa0tInG5Es3IYVwTNYMIAAAAPurUqlE//+cWxiN/2b4k7Gttb3sEyGJbkIK4ZisGUAAAAD2R6VSiSGPziuMxl+6bVpsaWkr+0RIppuQQjgmawYQAACA/XFD08LCaPy5m5+Ijdt2ln0edAvdhBTCMVkzgAAAAOyr2ye9XBiNP3PTlFi7tbXs86Db6CakEI7JmgEEAABgX9w9dUlhNP70DZPijc07yj4PupVuQgrhmKwZQAAAAPbWfTOWFkbjT143MZZv2F72edDtdBNSCMdkzQACAACwN349a0VhND7pmvGxeG1z2edBj9BNSCEckzUDCAAAwJ78bu7KOLx/bTQ+8apxsXDVlrLPgx6jm5BCOCZrBhAAAIDdGT9/dRw5YHRNND7+irHxworNZZ8HPUo3IYVwTNYMIAAAALvyxKK1cfTAMTXR+NjLm2LW0g1lnwc9TjchhXBM1gwgAAAARWYsWR/HDK6Nxh8cNCaeemVd2edBr9BNSCEckzUDCAAAwB+a+dqGOPbypppofNTA0TH5pTVlnwe9RjchhXBM1gwgAAAAv++5ZRvjw1eMrYnGRwwYHU0vrir7POhVugkphGOyZgABAAB404uvb47jh9RG48P7j4rfznm97POg1+kmpBCOyZoBBAAAICJiwRtb4sSrxtVE48P6j4pfz1pR9nlQCt2EFMIxWTOAAAAAvLx6a3z86vE10fjQy0bFg88sK/s8KI1uQgrhmKwZQAAAgMa2ZG1znHzthMJofO/018o+D0qlm5BCOCZrBhAAAKBxLVu/PT553cTCaHz31CVlnwel001IIRyTNQMIAADQmFZs3B6nXj+pMBrfMfmVss+DPkE3IYVwTNYMIAAAQONZtbklTr9hcmE0vnn8orLPgz5DNyGFcEzWDCAAAEBjWbO1JT5z05TCaPyDpoVRqVTKPhH6DN2EFMIxWTOAAAAAjWN9c2ucPezxwmh89e/mi8bwB3QTUgjHZM0AAgAANIZN23fGF26ZWhiNL//ti6IxFNBNSCEckzUDCAAAUP8272iLL902rTAaX/bI3OjsFI2hiG5CCl8rxNwAACAASURBVOGYrBlAAACA+tbc2h7/e/iThdH4kofniMawG7oJKYRjsmYAAQAA6tf2ne3xdz9+qjAa/9uDz0WHaAy7pZuQQjgmawYQAACgPrW0dcTX75pRGI2/c9+saOvoLPtE6PN0E1IIx2TNAAIAANSflraOOO+nTxdG42/94tnY2S4aw97QTUghHJM1AwgAAFBfdrZ3xj/+/NnCaHz+Pc9Ea3tH2SdCNnQTUgjHZM0AAgAA1I+2js745/tmFkbjr981I1raRGPYF7oJKYRjsmYAAQAA6kN7R2f86wOzC6PxOT+eHtt3tpd9ImRHNyGFcEzWDCAAAED+OjorccmIOYXR+H8PfzKaW0Vj2B+6CSmEY7JmAAEAAPLW2VmJS389tzAaf+m2abF5R1vZJ0K2dBNSCMdkzQACAADkq1KpxOCRLxZG4y/cMjU2bd9Z9omQNd2EFMIxWTOAAAAAeapUKjHk0XmF0fizNz8e65tbyz4RsqebkEI4JmsGEAAAID+VSiWuemx+YTT+zA+nxJqtLWWfCHVBNyGFcEzWDCAAAEBeKpVKXDd6QWE0PuPGybFqs2gM3UU3IYVwTNYMIAAAQD4qlUr8oGlhYTT+9A2TYuWmHWWfCHVFNyGFcEzWDCAAAEAeKpVK3DT2pcJofOr1k2LFxu1lnwh1RzchhXBM1gwgAABAHm4ev6gwGn9q6MRYvkE0hp6gm5BCOCZrBhAAAKDvu3Xiy4XR+JShE2Pp+m1lnwd1SzchhXBc55qbm2PkyJFx4YUXxmmnnRbvete74oADDoi3v/3tceSRR8bXvva1eOSRR6K9vX2fvvPmm2+O0047Ld797nfHgQceGO9///vjy1/+cowYMSIqlUoP/o2qGUAAAIC+7Y7JrxRG409cNyFeXScaQ0/STUghHNexYcOGxVvf+taugdjdO/HEE2PevHl7/M5nnnkmDj300N1+11/91V/FunXreuFvaAABAAD6sjsfX1wYjU++dkIsXttc9nlQ93QTUgjHdew73/lO1zi8733vi/PPPz9uvfXWGDFiRNx3331x0UUXxcEHH9z1mUMOOSQWLVq0y+9bsGBBHHTQQV2f/+QnPxm33nprPPTQQ3H11VfHBz7wga5f+8QnPhE7dvT8T8M1gAAAAH3T3VOXFEbjk66ZEK+sEY2hN+gmpBCO69gFF1wQZ599djQ1NUVHR0fhZ9auXRunnHJK14icddZZu/y+T3/6012f+973vlfzT1Js3rw5TjvttK7PXHnlld369yliAAEAAPqee6a9WhiNP371+Hh59dayz4OGoZuQQjiuYxs2bNirz61cuTLe9ra3dQ3J0qVLaz4zduzYrl8/4YQTdvlvIi9btiwOPPDA6NevX/zpn/5pbN68OenvsCcGEAAAoG+5d/prhdH4Y1ePj5dWicbQm3QTUgjHRETE5z73ua4heeyxx2p+/Zvf/GbXr//0pz/d7Xedd955XZ+97777eurkiDCAAAAAfckvZywtjMYnXjUu5q/cUvZ50HB0E1IIx0RExDnnnNM1JCNGjKj59Xe/+91dv75q1ardfteDDz7Y9dlzzz23p06OCAMIAADQVzz4zLLCaPyRK8fFi6/37P8bFSimm5BCOCYiIo499tiuIZk+fXrVr61evbrr197//vfv8bsWL17c9fnjjjuup06OCAMIAADQFzz87PLCaHz8kLHxwgrRGMqim5BCOCamTJnSNSKHHHJIzQ/Se+KJJ7p+/Ywzztjj97W1tcVb3vKW6NevXxxwwAE1P0Rvb02bNm2Pb/jw4QYQAACgRL+etSIO618Qja8YG88v31T2edDQhGNSCMcNbvv27XHMMcd0jciwYcNqPvPoo492/frf/u3f7tX3HnTQQV2/p7m5eb9ue/P37+0zgAAAAL3rN88VR+MPXzE2Zi/bWPZ50PCEY1IIxw2sUqnEV7/61a4BOeWUU6Ktra3mcw888EDXZ/7hH/5hr777z//8z7t+zxtvvLFf9wnHAAAAfdejz6+Mwwui8XGXN8WspRvKPg8I4Zg0wnEDu+SSS7rG4z3veU8sX7688HNlhWP/VAUAAEDfNGruG3HEgNE10fjYy5vi2ddEY+grhGNSCMcNauDAgV3D8c53vjNeeOGFXX62rH+qYm8YQAAAgN415oXiaPyhwU0xY8n6ss8Dfo9uQgrhuAENGjSoazQOPvjgmDNnzm4/n/LD8f7oj/5ov3843t4wgAAAAL1n7LxVcWRBND5m8Jh4avG6ss8D/oBuQgrhuMEMGDCgazAOOuigmD179h5/z+rVq7t+z/vf//49fn7x4sVdnz/uuOO64+xdMoAAAAC9Y8L81XHUwNpo/MFBY2Lay6Ix9EW6CSmE4wZy6aWX7nM0ftO73/3urt+7atWq3X72wQcf7Prsueeem3r2bhlAAACAnjd54Zo4euCYmmh89KAx8cSitWWfB+yCbkIK4bhBfP/739/vaBwR8Y1vfKPr999zzz27/ex5553X9dl777035ew9MoAAAAA9a5fReOCYmPzSmrLPA3ZDNyGFcNwALr744qp/03hfo3FERFNTU9d3nHDCCdHe3l74ueXLl8eBBx4Y/fr1iz/5kz+JTZs2pZ6/WwYQAACg5+wqGh81cHRMXLC67POAPdBNSCEc17mLLrpon34Q3u6ceuqpXd910UUX1fzQuy1btsRpp53W9Zkrrrgi9fw9MoAAAAA9Y1fR+MgBo2PcvN3/E4ZA36CbkEI4rmODBw/uGod+/frFkCFDYuTIkXt8CxcuLPy++fPnxzve8Y6u7zvllFPitttui4ceeiiuueaaOPTQQ7t+7eSTT47t27f3+N/RAAIAAHS/3UXjsaIxZEM3IYVwXMfOPPPMqnC8t2/IkCG7/M7p06fHBz7wgd3+/jPOOCPWrOmdf+fKAAIAAHQv0Rjqh25CCuG4jvVEOI6I2Lp1a/zwhz+MU089Nd71rnfFH//xH8df/MVfxJe+9KV48MEHa/4Ji55kAAEAALqPaAz1RTchhXBM1gwgAABA9xCNof7oJqQQjsmaAQQAAEgnGkN90k1IIRyTNQMIAACQRjSG+qWbkEI4JmsGEAAAYP+JxlDfdBNSCMdkzQACAADsH9EY6p9uQgrhmKwZQAAAgH0nGkNj0E1IIRyTNQMIAACwb0RjaBy6CSmEY7JmAAEAAPaeaAyNRTchhXBM1gwgAADA3tldNG56UTSGeqSbkEI4JmsGEAAAYM9EY2hMugkphGOyZgABAAB2TzSGxqWbkEI4JmsGEAAAYNdEY2hsugkphGOyZgABAACKicaAbkIK4ZisGUAAAIBaojEQoZuQRjgmawYQAACgmmgMvEk3IYVwTNYMIAAAwH8TjYHfp5uQQjgmawYQAADgv0xcsFo0BqroJqQQjsmaAQQAAIgYP391HDVwtGgMVNFNSCEckzUDCAAANLqmF1fFkQNEY6CWbkIK4ZisGUAAAKCRjX7hDdEY2CXdhBTCMVkzgAAAQKN67PmVcURBND5q4OgYP3912ecBfYBuQgrhmKwZQAAAoBH9ds7rcXj/UTXR+OiBY2LSQtEY+C+6CSmEY7JmAAEAgEbzn7NXFEfjQWNiyktryj4P6EN0E1IIx2TNAAIAAI3kVzOXx2EF0fiDg8bEE4vWln0e0MfoJqQQjsmaAQQAABrFiGeXFUbjYwaPiSdfWVf2eUAfpJuQQjgmawYQAABoBA88vawmGB962aj40OCmeGqxaAwU001IIRyTNQMIAADUu/umv1YYjY+9vCmeXrK+7POAPkw3IYVwTNYMIAAAUM9+/uSrhdH4uMubYuZrG8o+D+jjdBNSCMdkzQACAAD16qfTiqPxh68YG7OWbiz7PCADugkphGOyZgABAIB6dNcTSwqj8fFDxsZzy0RjYO/oJqQQjsmaAQQAAOrNf0xZXBiNTxgyNuau2FT2eUBGdBNSCMdkzQACAAD15PZJLxdG449cOS5efH1z2ecBmdFNSCEckzUDCAAA1ItbJhRH449eNS7mrRSNgX2nm5BCOCZrBhAAAMhdpVKJYeMXFUbjj109Pha8saXsE4FM6SakEI7JmgEEAAByVqlU4qaxLxVG45OuGR8vrdpa9olAxnQTUgjHZM0AAgAAuapUKnH9mIW7iMYT4uXVojGQRjchhXBM1gwgAACQo0qlEteOml8Yjf/HtRPilTXNZZ8I1AHdhBTCMVkzgAAAQG4qlUpc9VhxNP7kdRPj1XXbyj4RqBO6CSmEY7JmAAEAgJx0dlZi8MgXC6PxKUMnxmuiMdCNdBNSCMdkzQACAAC56OisxGWPzC2MxqdePymWrd9e9olAndFNSCEckzUDCAAA5KC9ozMuGTGnMBqf9oNJsXyDaAx0P92EFMIxWTOAAABAX9fW0Rn/+sDswmh8xo2T4/VNO8o+EahTugkphGOyZgABAIC+bGd7Z/zzfTMLo/FnfjglVm9pKftEoI7pJqQQjsmaAQQAAPqqlraO+MefP1sYjT938xOxdmtr2ScCdU43IYVwTNYMIAAA0Bft2NkR5/306cJo/MVbpsaGbTvLPhFoALoJKYRjsmYAAQCAvmZba3uc+5MZhdH4y7dPi03bRWOgd+gmpBCOyZoBBAAA+pKtLW3x1f94qjAa/83wJ2NLS1vZJwINRDchhXBM1gwgAADQV2ze0RZfuePJwmh8zp3To7m1vewTgQajm5BCOCZrBhAAAOgLNm7bGX9929TCaPz3d8+I7TtFY6D36SakEI7JmgEEAADKtq65NT7/oycKo/E3f/ZMtLR1lH0i0KB0E1IIx2TNAAIAAGVas6Ulzhr2eGE0/qd7Z0Zru2gMlEc3IYVwTNYMIAAAUJY3Nu+Iv7ppSmE0/pf7Z0VbR2fZJwINTjchhXBM1gwgAABQhuUbtsenb5hUGI0vfOi5aBeNgT5ANyGFcEzWDCAAANDblq7fFqdeXxyNv/+r56Ojs1L2iQARoZuQRjgmawYQAADoTYvXNscnrptQGI0H/OaF6BSNgT5ENyGFcEzWDCAAANBbXlq1NU66pjgaD3l0XlQqojHQt+gmpBCOyZoBBAAAesP8lVviY1ePL4zGQ0cvEI2BPkk3IYVwTNYMIAAA0NPmrtgUH7lyXGE0/uG4l0RjoM/STUghHJM1AwgAAPSkWUs3xvFXjC2MxrdNfLns8wB2SzchhXBM1gwgAADQU2YsWR/HXd5UGI3vfHxx2ecB7JFuQgrhmKwZQAAAoCc8vmhtfHDQmMJofM+0V8s+D2Cv6CakEI7JmgEEAAC627h5q+LogcXR+JczlpZ9HsBe001IIRyTNQMIAAB0p0efXxlHDBhdE4wP6z8qHp65vOzzAPaJbkIK4ZisGUAAAKC7PDxzeRzWv/a/Mj5iwOj47ZzXyz4PYJ/pJqQQjsmaAQQAALrDvdNfK/ynKY4eOCbGzVtV9nkA+0U3IYVwTNYMIAAAkOrHjy8ujMYfHDQmHl+0tuzzAPabbkIK4ZisGUAAAGB/VSqVuHn8osJofNzlTTFjyfqyTwRIopuQQjgmawYQAADYH5VKJa4bvaAwGp8wZGzMXrax7BMBkukmpBCOyZoBBAAA9lVnZyUGj3yxMBp/7Orx8eLrm8s+EaBb6CakEI7JmgEEAAD2RUdnJb7/q+cLo/H/uHZCvLx6a9knAnQb3YQUwjFZM4AAAMDeauvojH99YHZhND71+knx2rptZZ8I0K10E1IIx2TNAAIAAHujpa0jvvWLmYXR+IwbJ8eKjdvLPhGg2+kmpBCOyZoBBAAA9mTHzo4476dPF0bjs4c9Hmu2tJR9IkCP0E1IIRyTNQMIAADsTnNre5xz5/TCaPzFW6bG+ubWsk8E6DG6CSmEY7JmAAEAgF3ZvL0t/tcdTxZG46/c8WRs3t5W9okAPUo3IYVwTNYMIAAAUGR9c2t88ZaphdH4/9w5PZpb28s+EaDH6SakEI7JmgEEAAD+0OotLXHWsMcLo/H59zwTO3Z2lH0iQK/QTUghHJM1AwgAAPy+FRu3xxk3Ti6Mxt++d2a0tovGQOPQTUghHJM1AwgAALzp1XXb4lNDJxZG43978Llo6+gs+0SAXqWbkEI4JmsGEAAAiIhYtHprnHzthMJo/O+/fj46OitlnwjQ63QTUgjHZM0AAgAAL6zYHB+9alxhNL7ity9Gp2gMNCjdhBTCMVkzgAAA0NieXrI+PnzF2MJoPHTMgqhURGOgcekmpBCOyZoBBACAxjXlpTXxwUFjCqPxrRNfFo2BhqebkEI4JmsGEAAAGtPoF96IowaOLozGd09dUvZ5AH2CbkIK4ZisGUAAAGg8v5q5PA7vXxuMD+s/Kh58ZlnZ5wH0GboJKYRjsmYAAQCgsfz8yVcL/yvjIweMjkefX1n2eQB9im5CCuGYrBlAAABoDJVKJW6f9HJhND560JiYuGB12ScC9Dm6CSmEY7JmAAEAoP5VKpUYOnpBYTQ+7vKmeGrxurJPBOiTdBNSCMdkzQACAEB96+ysxMDfvFAYjT9y5bh4btnGsk8E6LN0E1IIx2TNAAIAQP1q6+iMCx96rjAan3TNhFjwxpayTwTo03QTUgjHZM0AAgBAfWpp64hv/WJmYTT+1NCJsWRtc9knAvR5ugkphGOyZgABAKD+bGttj7+/e0ZhNP6rm6bE65t2lH0iQBZ0E1IIx2TNAAIAQH3ZvL0t/mb4k4XR+PM/eiLWbm0t+0SAbOgmpBCOyZoBBACA+rGuuTW+cMvUwmj8lTuejM3b28o+ESArugkphGOyZgABAKA+rNy0Iz5z05TCaHzuT2ZEc2t72ScCZEc3IYVwTNYMIAAA5O+1ddvi1Ov/H3t3HmVnQef5nwQZupFupafbcezRhFVAUBDsRjSI0i497dLaOsP8pImjbdsqCvYoZCGsMQKGRVZRlhB2cSFalcq+kAVCQhKyELKTfV+rktrufb6/P6apAXNvJZWnqp567n29zrmnT5/cqnzzz+d0v8/luRNLRuOvP/xiNLYUsj4RIJd0E9IQjsk1AwgAAPm2ZNOeOHfo+JLR+LIn5kZLoZj1iQC5pZuQhnBMrhlAAADIr3lrd8X7rxtbMhoP+M3LUSgmWZ8IkGu6CWkIx+SaAQQAgHyauWJ7nD6krmQ0HlqzOJJENAZISzchDeGYXDOAAACQP5OWbIlTBo8uGY1/NmGZaAzQSXQT0hCOyTUDCAAA+TJq/oY4cWBtyWj8wLRVWZ8HUFF0E9IQjsk1AwgAAPkx8vnXou+AA4Nx3wE18dSLa7I+D6Di6CakIRyTawYQAAB6viRJ4u5Jy0t+yvjEgbXxh5c3ZH0iQEXSTUhDOCbXDCAAAPRsSZLE0JrFJaPxKYNHx6QlW7I+EaBi6SakIRyTawYQAAB6rtZCMX70zPyS0fiMa8bErFU7sj4RoKLpJqQhHJNrBhAAAHqmptZCfGvknJLR+IM3jIuF63dnfSJAxdNNSEM4JtcMIAAA9DwNTa3x1V++UDIan/+TibFya33WJwJUBd2ENIRjcs0AAgBAz7JrX3N84e7pJaPxJ4ZPjg279md9IkDV0E1IQzgm1wwgAAD0HJv3NMYnb5tSMhp/9s5psb2+KesTAaqKbkIawjG5ZgABAKBneG17Q3z05oklo/H/+PnM2NvYkvWJAFVHNyEN4ZhcM4AAAJC9VzbuiXOHji8Zjb8x4sVobClkfSJAVdJNSEM4JtcMIAAAZGvOazvjzGvHlIzGP3hqXrQUilmfCFC1dBPSEI7JNQMIAADZmbp0a5x6dV3JaHztqEVRLCZZnwhQ1XQT0hCOyTUDCAAA2ah5eWOcNKi2ZDS+ffzSSBLRGCBruglpCMfkmgEEAIDu9+SsNXH8gAODcZ+rauKh6auyPg+A/6CbkIZwTK4ZQAAA6F4/n7KiZDA+YWBt/OaldVmfB8Ab6CakIRxXuCRJYtmyZfHUU0/FlVdeGRdddFH8xV/8Rdto9OnT55B/1+s/c6iv7mAAAQCgeyRJEjfVLSkZjU8ePDrGLd6c9YkA/BHdhDSE4wr37//+7+3GXeEYAAA4mEIxiQG/WVAyGp8+pC5mrNiW9YkAlKCbkIZwXOEuv/zyN8XcY445Jj7wgQ+kCsfve9/74ne/+91BX93BAAIAQNdqbi3Gdx5/qWQ0Puv6sfHyul1ZnwhAGboJaQjHFe7++++PK664IkaOHBmLFi2KQqEQq1evThWOP/axj3XZvR1lAAEAoOvsa26NSx+cVTIanzdsQizfsjfrEwFoh25CGsJxFRKOAQCAg9m1rzn+8Z7pJaPxhT+dHOt27sv6RAAOQjchDeG4CgnHAABAezbu3h9/d+uUktH47+94Lrbubcr6RAAOgW5CGsJxFRKOAQCAclZsrY/zfzKxZDT+8n0zYk9jS9YnAnCIdBPSEI6rUNpw/M53vjP69esX//k//+c46qij4i//8i/jnHPOiSuuuCIWLFjQdYeXYAABAKDzzF+7K86+YVzJaPz1h1+M/c2FrE8EoAN0E9IQjqtQ2nB8sNell14a9fX1XfcPeAMDCAAAnWPasm1x2pC6ktH4B0/Pi5ZCMesTAegg3YQ0hOMqlCYc9+3bN/7lX/4l7rrrrnj66afjsccei6FDh8b555//pnh83nnnxf79+1PdOW3atIO+7rnnHgMIAAAp/eHlDXHSoNqS0XhozeIoFpOsTwTgMAjHpCEcV6HDDceTJ09u989ramri7W9/e9vv/t73vpfqzkP9hLMBBACAwzfy+dei74ADg3Gfq2rivikrsj4PgBSEY9IQjqvQ4YbjQzF+/Pi2333UUUfFpk2bDvt3CccAANB1kiSJ28cvLRmMjx9QE0+/uDbrEwFISTgmDeG4Ax555JFue61bt67L/h1dGY4jIi666KK23//QQw8d9u/xqAoAAOgaxWISQ55dWDIanzx4dIxddPgfAAGg5xCOSUM47oBevXpF7969u+U1atSoLvt3dHU4/vGPf9z2+3/0ox91+u9/IwMIAAAd09xajO8+/lLJaHzGNWPihZXbsz4RgE6im5CGcNwBr4fjXr16dekr7+H4F7/4Rdvv/+Y3v9npv/+NDCAAABy6hqbWuOSBF0pG43NuHB+LNuzO+kQAOpFuQhrCcQe8HnW///3vx4gRI7rkVQnheNiwYW2//8orr+z03/9GBhAAAA7Njobm+Pzd00tG4343T4rXtjdkfSIAnUw3IQ3huAO6I+pWQjj+5Cc/2fb7H3zwwU7//W9kAAEA4ODW79ofnxg+uWQ0/swdz8WWPY1ZnwhAF9BNSEM47gDh+OAmTZrU9ruPPPLI2LBhQ6f+/j9mAAEAoH3Lt+yN84ZNKBmNv/LzmbF7f0vWJwLQRXQT0hCOO+D1ZxB3dTju6r/jcMLxVVddFStXrmz3PWPGjInjjjuu7Xf/27/9Wydc2z4DCAAA5c1dszM+cP3YktH4GyNmR2NLIesTAehCuglpCMcVbteuXTF48OA3vS677LK20Xjb2952wJ8PHz78gN/ztre9LY444og499xz44orroif//zn8fTTT8cTTzwRw4YNi379+rX9ztffV19f3+X/PgMIAAClTVm6NU69uq5kNP7hr+ZHa6GY9YkAdDHdhDSE4wr3xk8XH+qr1KeQXw/Hh/Lq379/7Nmzp1v+fQYQAAAONGr+hjhpUG3JaDxs9CuRJEnWJwLQDXQT0hCOK1xnheNZs2bF7bffHhdffHGcddZZ8d/+23+LP/3TP42jjz463vnOd0a/fv1i4MCB8eqrr3brv88AAgDAm42YsTr6DjgwGPe5qibun7oi6/MA6Ea6CWkIxxmbPHlyfPWrX836jNwygAAA8H8lSRK3jltaMhifMLA2npmzLusTAehmuglpCMcZ2LRpUwwbNixOOumk6N27d/Tu3Tvrk3LLAAIAQEShmMSA3ywoGY1PGTw6xi/enPWJAGRANyEN4bibFIvFGDVqVHz+85+Po446qi0Y9+rVSzhOwQACAFDtGlsK8c1HZpeMxmdcOyZeXL0j6xMByIhuQhrCcRdbvnx5DBw4MN71rne9KRa//jrhhBPiuuuuy/rM3DKAAABUs937WuLL980oGY0/NHR8vLKxe760GoCeSTchDeG4CzQ1NcVjjz0WF154YclY/Od//ufx9a9/PZ577rmsT809AwgAQLXasGt/fPK2KSWj8YU/nRxrd+zL+kQAMqabkIZw3Inmzp0b3/3ud+O4444rGYx79+4d/fv3j/3792d9asUwgAAAVKNlm/fGecMmlIzGn79rWmyvb8r6RAB6AN2ENITjlPbs2RP33ntvfPCDHywZi48//vi47rrr2sLx9ddfn/XJFcUAAgBQbWav3hHvv25syWj8zw/Oioam1qxPBKCH0E1IQzg+TFOnTo1//ud/jmOOOeaAYHzsscfGpZdeGpMnT257v3DcNQwgAADVZNzizXHK4NElo/EPnpoXLYVi1icC0IPoJqQhHHfQTTfdFKecckrJTxf369cvHnrooWhoaDjg54TjrmEAAQCoFk/OWhPHDzgwGPe5qiaG1b4SxWKS9YkA9DC6CWkIxx30egB+PRb36dMnhgwZEitXrjyknxOOO5cBBACg0iVJEj+bsKxkMO5zVU388rn2/38RAKqXbkIawnEHvR6Ae/fuHV//+tcP+YvuhOOuYQABAKhkhWISg3+3oGQwPmlQbYyavyHrEwHowXQT0hCOO+iN4bh3797x9re/Pb71rW/FzJkzD+nnhOPOZQABAKhUjS2F+NbIOSWj8elD6mLasm1ZnwhAD6ebkIZw3EEjRoyIfv36venZxq9H5Pe+973xk5/8JNavX3/AzwnHXcMAAgBQiXbvb4mv/HxmyWh8zo3jYuH63VmfCEAO6CakIRwfpqVLl8YPf/jD+C//5b8cEJDf8pa3xKc+9al44oknoqmpKSKE465iAAEAqDSbdjfGp2+fWjIaZN/oqAAAIABJREFUX3DLpHht+4Ffxg0ApegmpCEcp9Ta2hq//vWv4+///u/jyCOPPCAiv/3tb49//dd/FY67iAEEAKCSLN9SH+f/ZGLJaPzZO6fFtvqmrE8EIEd0E9IQjjvRunXr4rrrrou+ffse8CiL1//n5z73uVizZk3Wp1YMAwgAQKV4ac3O+MD1Y0tG40seeCHqm1qzPhGAnNFNSEM47gJJksTYsWPjK1/5Shx99NEHfKHekUceGRdeeGE88sgj0dDgPzNLwwACAFAJJryyOd579eiS0fj7T86N5tZi1icCkEO6CWkIx11s+/btMXz48Dj99NNLfqHescceG/3798/6zNwygAAA5N3TL66NEwbWlozGN/5hcRSLSdYnApBTuglpCMfdaMaMGfG1r30tjj322AMiMofHAAIAkFdJksRdE5eVDMZ9rqqJX0xdmfWJAOScbkIawnEG6uvr4+c//3l86EMfEo5TMoAAAORRoZjEkGcXlgzGJw6sjd/OXZf1iQBUAN2ENITjjL388svx/e9/P+szcssAAgCQN40thfjXkbNLRuPThtTFlKVbsz4RgAqhm5CGcEyuGUAAAPJkZ0NzfOneGSWj8QdvGBfz1+7K+kQAKohuQhrCMblmAAEAyIu1O/bFx4dPLhmNP3rzxFi1rSHrEwGoMLoJaQjH5JoBBAAgDxau3x3n3Di+ZDT+7J3TYuvepqxPBKAC6SakIRx3omKxGM8++2x861vfivPPPz9OO+20OP744w/6OuGEE7I+PbcMIAAAPd2UpVvj9CF1JaNx/4dmRUNTa9YnAlChdBPSEI47yauvvhrvf//7o3fv3m969erV66Cv3r17Z31+bhlAAAB6smfmrIsTB9aWjMY//NX8aCkUsz4RgAqmm5CGcNwJtm/fHu9617veFIqPOuqo+K//9b9G3759D+nF4TGAAAD0REmSxF0Tl5UMxn2uqonbxi2NJEmyPhOACqebkIZw3AkGDBjQ9snhs88+O8aMGRPNzc1Zn1UVDCAAAD1Na6EYA3+7oGQwPmFgbTw5a03WJwJQJXQT0hCOO8EZZ5wRvXr1ipNPPjkaGnwTcncygAAA9CT7mwvxjREvlozGp15dFxOXbM76RACqiG5CGsJxJzj22GOjd+/eccstt2R9StUxgAAA9BTb65viC3dPLxmNP3jDuJi/dlfWJwJQZXQT0hCOO8Gf//mfR+/evePXv/511qdUHQMIAEBP8Nr2hvjYLZNKRuOP3TIpXtvuv0wEoPvpJqQhHHeCM888M3r37h0PPvhg1qdUHQMIAEDW5q/dFefcOK5kNP783dNje31T1icCUKV0E9IQjjvB1VdfHb169Yr+/ftnfUrVMYAAAGRp0pItcerVdSWj8dcffjH2NbdmfSIAVUw3IQ3huBNs3rw5/vIv/zKOPvroWLhwYdbnVBUDCABAVp56cU2cMLC2ZDQe8JsF0VooZn0iAFVONyEN4biTTJw4MY499tj467/+65g8eXLW51QNAwgAQHdLkiRuG7e0ZDDuc1VN3DlhWSRJkvWZAKCbkIpw3Amuv/76uP766+OLX/xi9OrVK3r37h1nnXVWfPe7341rr7227c/be3F4DCAAAN2ptVCMK595uWQwPnFgbfxq9tqsTwSANroJaQjHneD1WPz664//90N5cXgMIAAA3aWhqTW+9tCsktH4tCF1MWXp1qxPBIA30U1IQzjuBL169Ur1Eo4PnwEEAKA7bN3bFJ+7a1rJaHzOjeNj4frdWZ8IAAfQTUhDOO4EU6ZMSf3i8BhAAAC62vIt9fHRmyeWjMYfHz451u7Yl/WJAFCSbkIawjG5ZgABAOhKL6zcHu+/bmzJaPzFe6bHzobmrE8EgLJ0E9IQjsk1AwgAQFcZNX9DnDxodMlo/M1HZkdjSyHrEwGgXboJaQjH5JoBBACgsyVJEvdOXlEyGPe5qiauHbUoCsUk6zMB4KB0E9IQjsk1AwgAQGdqLRRj4G8XlAzGfQfUxC+fWxlJIhoDkA+6CWkIx+SaAQQAoLM0NLXG1x6aVTIanzJ4dIxesDHrEwGgQ3QT0hCOO6BXr15x5JFHxqhRo3L9d1QSAwgAQGfYsqcx/uHO50pG47OuHxtzXtuZ9YkA0GG6CWkIxx3Qq1ev6N27d5eH467+OyqJAQQAIK2lm/fG+T+ZWDIaf+yWSbFqW0PWJwLAYdFNSEM47gDhuOcxgAAApDFj+bY449oxJaPxF++ZHtvrm7I+EQAOm25CGsJxB7wedS+//PJ45JFHuuQlHHeMAQQA4HD95qV1cdKg2pLR+N8enRONLYWsTwSAVHQT0hCOO+D1qNuVL+G4YwwgAAAdlSRJ/GzCspLBuM9VNXHjHxZHsZhkfSYApKabkIZw3AG9evXqlpdwfOgMIAAAHdFSKMaPnplfMhj3HVATD09flfWJANBpdBPSEI47YMSIEd32WrduXdb/3FwwgAAAHKq9jS1xyQMvlIzG7716dIxdtCnrEwGgU+kmpCEck2sGEACAQ7Fx9/749O1TS0bjD94wLuat3ZX1iQDQ6XQT0hCOyTUDCADAwSzesCf+9scTSkbjjw+fHGu278v6RADoEroJaQjH5JoBBACgPVOXbo33XTOmZDT+8n0zYte+5qxPBIAuo5uQhnBMrhlAAADKefrFtXHiwNqS0fi7j78UjS2FrE8EgC6lm5CGcEyuGUAAAP5YsZjET8e8WjIY97mqJoaNfiWKxSTrMwGgy+kmpCEck2sGEACAN2psKcRlT8wtGYyPH1ATI59/LesTAaDb6CakIRyTawYQAIDXba9vii/dO6NkND716rqY8MrmrE8EgG6lm5CGcEyuGUAAACIiVmytj343TyoZjc8dOj5eXrcr6xMBoNvpJqQhHJNrBhAAgJkrtsf7rxtbMhp/6rapsX7X/qxPBIBM6CakIRyTawYQAKC6/XrOujhpUG3JaHzJAy/E3saWrE8EgMzoJqQhHJNrBhAAoDolSRK3jn21ZDDuc1VNDPztgmgtFLM+EwAypZuQhnDcQUuWLMn6BN7AAAIAVJ/GlkJ8/8m5JYNx3wE18YupKyNJkqzPBIDM6SakIRx3UK9eveLP/uzPol+/fnHFFVfEo48+Gq+88or/wzQjBhAAoLrsaGiOL983o2Q0fu/Vo6Nu4aasTwSAHkM3IQ3huIN69eoVvXv3PuB17LHHxkc/+tG4/PLLY+TIkbF48WIxuRsYQACA6rFya31ccMukktH4nBvHx/y1u7I+EQB6FN2ENITjDnr3u98dvXr1Kvn645j81re+Nc4///z43ve+FyNGjIiFCxdGseg5a53JAAIAVIcXVm6P9183tmQ0/uRtU2Ldzn1ZnwgAPY5uQhrC8WHYtm1bjBkzJn784x/Hl770pejTp88hx+RjjjkmPvzhD8dll10WDz/8cCxYsEBMTsEAAgBUvt+8tC5OGlRbMhpf8sALsaexJesTAaBH0k1IQzjuJNu3b4+xY8fGsGHD4p/+6Z86HJM5PAYQAKByJUkSt41bWjIY97mqJgb8ZkG0FHwIAwDK0U1IQzjuQn8ck/v27Vs2JHN4DCAAQGVqai3EFU/NKxuN75+6wneKAMBB6CakIRx3sx07dsS4cePiJz/5SXz5y1+O448/XjhOwQACAFSenQ3N8ZX7ZpYMxqcMHh2jF2zM+kQAyAXdhDSE4x5g586dWZ+QWwYQAKCyrNrWEBf+dHLJaHzOjeNi7hr/tzMAHCrdhDSEY3LNAAIAVI5Zq3bEB64fWzIa/92tU2Ltjn1ZnwgAuaKbkIZwTK4ZQACAyvDbuevi5EGjS0bjr/7yhdi9vyXrEwEgd3QT0hCOyTUDCACQb8ViEj8d82rZL8G76tcvR0uhmPWZAJBLuglpCMfkmgEEAMiv/c2F+PZjc8pG4/umrIgkSbI+EwBySzchDeGYXDOAAAD5tGVPY3zurmklg/Epg0dH7YKNWZ8IALmnm5CGcEyuGUAAgPxZtGF3nDdsQslofM6N42Pe2l1ZnwgAFUE3IQ3hmFwzgAAA+TJu8eY4bUhdyWj8mTuei/W79md9IgBUDN2ENIRjcs0AAgDkQ5Ikcf/UFdF3QOnnGX9jxIvR0NSa9ZkAUFF0E9IQjsk1AwgA0PM1txbjymdeLvsleENrFkeh6EvwAKCz6SakIRyTawYQAKBn27WvOf7n/TNLBuMTB9bGk7PWZH0iAFQs3YQ0hGNyzQACAPRcK7fWx4U/nVwyGr//urExY8W2rE8EgIqmm5CGcEyuGUAAgJ5pxvJt8f7rxpaMxhf+dHKs3Fqf9YkAUPF0E9IQjsk1AwgA0PM8OWtNnDiwtmQ0vvj+52PXvuasTwSAqqCbkIZwTK4ZQACAnqNQTGJozeKyX4J35TMvR3NrMeszAaBq6CakIRyTawYQAKBnaGhqjW+MeLFkMO47oCZ+MXVlJEmS9ZkAUFV0E9IQjsk1AwgAkL31u/bHZ+54rmQ0Pm1IXYxbvDnrEwGgKukmpCEck2sGEAAgW/PW7opzbhxfMhqfN2xCLNqwO+sTAaBq6SakIRyTawYQACA7f3h5Q5wyeHTJaPz5u6bFlj2NWZ8IAFVNNyEN4ZhcM4AAAN2vWEzitnFLy34J3nceeyn2NxeyPhMAqp5uQhrCMblmAAEAutf+5kJ8+7E5ZaPx8LGvRrHoS/AAoCfQTUhDOCbXDCAAQPfZuHt//MOdpb8E7+RBo+O3c9dlfSIA8Aa6CWkIx+SaAQQA6B5z1+yMc4eW/hK8c24cF7NX78j6RADgj+gmpCEck2sGEACg6/127ro4ucyX4H369qmxbue+rE8EAErQTUhDOCbXDCAAQNcpFpO4qW5J2ecZf/OR2dHQ1Jr1mQBAGboJaQjH5JoBBADoGvVNrfGNEbPLRuOfjvEleADQ0+kmpCEck2sGEACg863dsS8+ffvU0l+CN3h0PDtvfdYnAgCHQDchDeGYXDOAAACd68XVO+LsG8aVjMYfGjo+5q3dlfWJAMAh0k1IQzgm1wwgAEDnefrFtXHSoNqS0fizd06LTbsbsz4RAOgA3YQ0hGNyzQACAKRXKCZx4x8Wl32e8Xcefyn2NxeyPhMA6CDdhDSEY3LNAAIApLOnsSX6PzSrbDT+2YRlkSS+BA8A8kg3IQ3hmFwzgAAAh2/1toa46NYpJYPxe68eHbULNmZ9IgCQgm5CGsIxuWYAAQAOz4wV2+ID148tGY3PGzYhFq7fnfWJAEBKuglpCMfkmgEEAOi4R59/LU4cWPpL8P7xnumxZa8vwQOASqCbkIZwTK4ZQACAQ9daKMaQZxeWfZ7xFU/Ni8YWX4IHAJVCNyEN4ZhcM4AAAIdmZ0Nz/K9fPF8yGPcdUBP3Tl7hS/AAoMLoJqQhHJNrBhAA4OCWbNoTH715YslofPqQuhi3eHPWJwIAXUA3IQ3hmFwzgAAA7atbuClOG1JXMhp/5KaJsWTTnqxPBAC6iG5CGsIxuWYAAQBKKxaTuGP8srLPM/7KfTNje31T1mcCAF1INyEN4ZhcM4AAAAdqaGqNb42cUzYaD/ztgmhuLWZ9JgDQxXQT0hCOyTUDCADwZmt37ItP3z61ZDA+cWBtPPr8a1mfCAB0E92ENIRjcs0AAgD8PzOWb4uzrh9bMhqffcO4eGHl9qxPBAC6kW5CGsIxuWYAAQAikiSJETNWxwkDa0tG48/c8Vys27kv6zMBgG6mm5CGcEyuGUAAoNo1tRbiymdeLvs84+88/lLsa27N+kwAIAO6CWkIx+SaAQQAqtnWvU3xpXtnlAzGfQfUxN2TlkeSJFmfCQBkRDchDeGYXDOAAEC1enndrjhv2ISS0fh914yJ8Ys3Z30iAJAx3YQ0hOMKlyRJLFu2LJ566qm48sor46KLLoq/+Iu/aBuNPn36dPh31tfXx2233RYf+chH4h3veEccffTR8e53vzs+97nPxVNPPdWtn2oxgABANXp23vo4ZfDoktH4Y7dMimWb92Z9IgDQA+gmpCEcV7h///d/bxuIUq+OhuNZs2ZFnz592v2dF154YWzbtq1r/kF/xAACANWkUExi2OhXyj7P+JIHXojd+1qyPhMA6CF0E9IQjivc5Zdf/qaoe8wxx8QHPvCBwwrHr7zyShx33HFtP/u3f/u38bOf/SyefPLJuOGGG+I973lP25/9zd/8Tezfv7/r/mH/wQACANVi9/6W6P/QrLLR+MY/LI7WQjHrMwGAHkQ3IQ3huMLdf//9ccUVV8TIkSNj0aJFUSgUYvXq1YcVjj/60Y+2/dz3vve9Ax5JsXv37vjIRz7S9p7rrruuk/81BzKAAEA1WLG1Pj7+08klg/HJg0fHr+esy/pEAKAH0k1IQziuQocTjseMGdP2M2eeeWa0traWfN+aNWvi6KOPjiOOOCLe+ta3xu7duzvx8gMZQACg0k1asiXOuGZMyWj8oaHjY97aXVmfCAD0ULoJaQjHVehwwnH//v3bfuaBBx5o972XXHJJ23tHjhzZCReXZwABgEqVJEncNXFZ9B1Q+tEUX7h7emze05j1mQBAD6abkIZwXIUOJxy/4x3vaPuZTZs2tfveJ554ou29F198cSdcXJ4BBAAqUX1Ta3xr5JyyzzP+P7+aH40thazPBAB6ON2ENITjKtTRcLx58+a297/73e8+6PtXrFjR9v7TTz+9Ey4uzwACAJVm1baG+Ltbp5QMxscPqIkHpq064LsmAABK0U1IQziuQh0Nx1OnTm17/wUXXHDQ97e0tMSRRx4ZRxxxRBx11FFd+v/YGEAAoJJMXLI5zri29POMz7p+bExbti3rEwGAHNFNSEM4rkIdDcejRo1qe/+XvvSlQ/o7jjvuuLafqa+vP6w7p02bdtDXPffcYwABgNwrFpO4c0L55xn//R3Pxdod+7I+EwDIGeGYNITjKtTRcPz444+3vf+rX/3qIf0d73rXu9p+ZuPGjYd15+s/f6gvAwgA5FF9U2v868jZZZ9n/L0n5sb+Zs8zBgA6TjgmDeG4CgnHAAA9w8qt9XFRO88z/uVzKz3PGAA4bMIxaQjHVcijKgAAsnew5xlPX+55xgBAOsIxaQjHVag7vxzvLW95iy/HAwB4g2IxiZ95njEA0A10E9IQjqtQR8Px5s2b297/7ne/+6DvX7FiRdv7Tz/99E64uDwDCADkSX1Ta3zzkfLPM/7+k55nDAB0Ht2ENITjKtTRcBwR8Y53vKPtZzZt2tTue5944om291588cWdcHF5BhAAyAvPMwYAuptuQhrCcRU6nHB86aWXtv3Mgw8+2O57L7nkkrb3PvLII51wcXkGEADIgwmvbI4zrin/POMZnmcMAHQB3YQ0hOMqdDjhuK6uru1nzjzzzGhtbS35vrVr18bRRx8dRxxxRBxzzDGxa9euTrz8QAYQAOjJPM8YAMiSbkIawnEVOpxwHBFx/vnnt/3c5ZdffsB/Srlnz574yEc+0vaea665ppMvP5ABBAB6qr2NLe0+z/hyzzMGALqYbkIawnGF27VrVwwePPhNr8suu6xtNN72trcd8OfDhw8v+bsWL14cb3/729t+9rzzzos777wznnzyybjxxhujT58+bX927rnnxr59Xf/pGQMIAPREK7bWxyeGTy4ZjE8YWOt5xgBAt9BNSEM4rnBv/HTxob7a+xTyzJkz4z3veU+7P3/BBRfEli1buuXfZwABgJ5mzKJN8T7PMwYAegDdhDSE4wrX2eE4ImLv3r0xfPjwOP/88+Ov/uqv4j/9p/8Uf/3Xfx2f/exn44knnujWT88YQACgpygUk7i5bknZR1P89589F+t2ep4xANB9dBPSEI7JNQMIAPQEOxqa45IHXvA8YwCgR9FNSEM4JtcMIACQtQXrdsf5P5lY9nnGD0xb5XnGAEAmdBPSEI7JNQMIAGTp6RfXxsmDR5eMxufcOD5eWLk96xMBgCqmm5CGcEyuGUAAIAtNrYUY8JsFZR9N8cV7psfmPY1ZnwkAVDndhDSEY3LNAAIA3W3Drv3x+bumlY3GQ55dGM2txazPBADQTUhFOCbXDCAA0J1mLN8WZ98wrmQwPmXw6PjNS+uyPhEAoI1uQhrCMblmAAGA7pAkSdw3ZUUcP6D0p4z73TwpFm3YnfWZAABvopuQhnBMrhlAAKCr1Te1xr89Oqfsoym+9tCs2L2vJeszAQAOoJuQhnBMrhlAAKArLd+yNz4xfHLZaHzbuKVRLCZZnwkAUJJuQhrCMblmAAGArjJ6wcY4fUhdyWB85rVjYuKSzVmfCADQLt2ENIRjcs0AAgCdrbVQjGG1r5T9lPGnb58ar21vyPpMAICD0k1IQzgm1wwgANCZttc3xf/6xfNlo/HlT86N/c2FrM8EADgkuglpCMfkmgEEADrL3DU748PDJpQMxicOrI0RM1ZHknieMQCQH7oJaQjH5JoBBADSSpIkRsxYHScNqi0ZjT80dHzMXr0j6zMBADpMNyEN4ZhcM4AAQBoNTa1x2RNzyz6a4sv3zYgtexqzPhMA4LDoJqQhHJNrBhAAOFzLt+yNi26dUjYaX/f7RdFSKGZ9JgDAYdNNSEM4JtcMIABwOEbN3xCnDakrGYxPG1IXo+ZvyPpEAIDUdBPSEI7JNQMIAHREc2sxrnl2YdlPGV9065RYvmVv1mcCAHQK3YQ0hGNyzQACAIdqw6798YW7p5eNxpc9MTcamlqzPhMAoNPoJqQhHJNrBhAAOBRTl26Ns64fWzIYnzSoNkbMWB1JkmR9JgBAp9JNSEM4JtcMIADQnmIxiTvGL4u+A0p/yvjDwybES2t2Zn0mAECX0E1IQzgm1wwgAFDOjobm+OcHZ5V9NMUlD7wQOxqasz4TAKDL6CakIRyTawYQAChl3tpd8eFhE0oG474DauK2cUujUPRoCgCgsukmpCEck2sGEAB4oyRJYuTM1XHSoNqS0fgD14+Nya9uyfpMAIBuoZuQhnBMrhlAAOB1DU2t8f0n55Z9NMXn75oW63buy/pMAIBuo5uQhnBMrhlAACAiYvmW+vi7W6eUjcZX/25hNLUWsj4TAKBb6SakIRyTawYQAPj9/A1x+pC6ksH41Kvr4tl567M+EQAgE7oJaQjH5JoBBIDq1dRaiKt/t7Dsp4w/PnxyLN28N+szAQAyo5uQhnBMrhlAAKhOr21viH+487my0fg7j78U9U2tWZ8JAJAp3YQ0hGNyzQACQPWpW7gxzrhmTMlgfOLA2nhw2qpIkiTrMwEAMqebkIZwTK4ZQACoHs2txbju94vKfsr4vGETYs5rO7I+EwCgx9BNSEM4JtcMIABUh7U79sXn755eNhr3f2hW7GhozvpMAIAeRTchDeGYXDOAAFD5xi3eHGdeW/rRFCcMrI17Ji+PYtGjKQAA/phuQhrCMblmAAGgcrUUivHj2lfKfsr4Q0PHxwsrt2d9JgBAj6WbkIZwTK4ZQACoTBt27Y8v3TujbDS+5IEXYlt9U9ZnAgD0aLoJaQjH5JoBBIDKM+nVLXHW9WNLBuO+A2riZxOWRcGjKQAADko3IQ3hmFwzgABQOVoLxbipbknZTxmfc+P4mLF8W9ZnAgDkhm5CGsIxuWYAAaAybN7TGF/5+cyy0fji+5+PLXsbsz4TACBXdBPSEI7JNQMIAPn33LKt8cEbxpV9NMWtY1/1aAoAgMOgm5CGcEyuGUAAyK9CMYlbx74afQeU/pTxB28YF1OXbs36TACA3NJNSEM4JtcMIADk05Y9jXHx/c+XfTTFV+6bGZt2ezQFAEAauglpCMfkmgEEgPyZsrT8oyn6XFUTN9UtidZCMeszAQByTzchDeGYXDOAAJAfLYVi/GT0krLB+APXj41JS7ZkfSYAQMXQTUhDOCbXDCAA5MO6nfvii/dMLxuNv3jP9Fi/a3/WZwIAVBTdhDSEY3LNAAJAzzdm0aY489oxZaPxsNpXosWjKQAAOp1uQhrCMblmAAGg52psKcQ1zy4sG4zPvmFcTHrVoykAALqKbkIawjG5ZgABoGdata0h/vvPnisbjf/n/TNj857GrM8EAKhouglpCMfkmgEEgJ7n2Xnr4/QhdSWD8fEDauKO8cuiUEyyPhMAoOLpJqQhHJNrBhAAeo59za3xo2fml/2U8d/8eHw8v3J71mcCAFQN3YQ0hGNyzQACQM/w6qa98Xe3Tikbjfs/NCu21zdlfSYAQFXRTUhDOCbXDCAAZCtJknhi1po4ZfDoksH4xIG1cf/UFVH0aAoAgG6nm5CGcEyuGUAAyM7expb47uMvlf2U8Udumhhz1+zM+kwAgKqlm5CGcEyuGUAAyMbL63ZFv5snlY3G335sTuze35L1mQAAVU03IQ3hmFwzgADQvZIkiQemrYqTBtWWDMYnDx4dI59/LZLEoykAALKmm5CGcEyuGUAA6D7b65vifz/8YtlPGX/8p5Nj8YY9WZ8JAMB/0E1IQzgm1wwgAHSPacu2xblDx5eNxj94el40NLVmfSYAAG+gm5CGcEyuGUAA6FrNrcUYNvqV6DugdDA+9eq6eGbOuqzPBACgBN2ENIRjcs0AAkDXeW17Q3z+rmllP2X8mTuei+Vb6rM+EwCAMnQT0hCOyTUDCABd47dz18XpQ+rKRuNrRy2KxpZC1mcCANAO3YQ0hGNyzQACQOfa29gSVzw1r2wwPvuGcTFxyeaszwQA4BDoJqQhHJNrBhAAOs/8tbviglsmlY3G/98vn48texqzPhMAgEOkm5CGcEyuGUAASK9YTOK+KSvixIG1JYPxiQNr497JK6JYTLI+FQCADtBNSEM4JtcMIACks2VPY3z1ly+U/ZTxBbdMinlrd2V9JgAAh0E3IQ3hmFwzgABw+CYu2Rxn3zCubDS+4ql5sbexJeszAQA4TLoJaQjH5JoBBICOa2otxHW/X1Q2GJ8+pC5+89K6rM8EACAl3YQ0hGNyzQACQMcs37I3PnPHc2VoeSqUAAAgAElEQVSj8efvmhartzVkfSYAAJ1ANyEN4ZhcM4AAcGiSJIknZq2JU6+uKxuNh41+JZpbi1mfCgBAJ9FNSEM4JtcMIAAc3I6G5vjmI7PLBuNzh46P55ZtzfpMAAA6mW5CGsIxuWYAAaB9U5dujQ8NHV82Gn/toVmxvb4p6zMBAOgCuglpCMfkmgEEgNIaWwpx/e8Xlw3GJw8aHQ9OWxVJkmR9KgAAXUQ3IQ3hmFwzgABwoFc37Y1P3z61bDS+6NYpsWjD7qzPBACgi+kmpCEck2sGEAD+nyRJ4uHpq+LkwaPLRuNrnl0YjS2FrE8FAKAb6CakIRyTawYQAP6vLXsb49IHZ5UNxufcOC4mLdmS9ZkAAHQj3YQ0hGNyzQACQMT4xZvj7BvGlY3G//vhF2ObL8ADAKg6uglpCMfkmgEEoJrtby7EoN8uKBuMTxk8OkY+/5ovwAMAqFK6CWkIx+SaAQSgWi1cvzs+Pnxy2Wj893c8F8u37M36TAAAMqSbkIZwTK4ZQACqTaGYxH1TVsRJg2pLBuO+A2piWO0r0dTqC/AAAKqdbkIawjG5ZgABqCYbdu2P/3n/zLKfMv7bH0+IGcu3ZX0mAAA9hG5CGsIxuWYAAagWf3h5Q5x57Ziy0fjbj82JXfuasz4TAIAeRDchDeGYXDOAAFS6PY0t8YOn5pUNxqcPqYtfzV7rC/AAADiAbkIawjG5ZgABqGQzVmyLDw+bUDYaf+Hu6fHa9oaszwQAoIfSTUhDOCbXDCAAlaixpRA3/GFx2WB8/ICauHXc0mgpFLM+FQCAHkw3IQ3hmFwzgABUmoXrd8ff3TqlbDT+yE0TY/bqHVmfCQBADugmpCEck2sGEIBKUSgmcfek5XHSoNqy0fjKZ16O+qbWrE8FACAndBPSEI7JNQMIQCV4bXtDfOneGWWD8QdvGBdjF23K+kwAAHJGNyEN4ZhcM4AA5FmSJPHErDVx2pC6stH4GyNmx7b6pqxPBQAgh3QT0hCOyTUDCEBebd3bFF9/+MWywfj0IXXx1ItrIkmSrE8FACCndBPSEI7JNQMIQB6NWbQpzr5hXNlo/E/3zog12/dlfSYAADmnm5CGcEyuGUAA8mRvY0v88FfzywbjkwbVxj2Tl0eh6FPGAACkp5uQhnBMrhlAAPLihZXb4yM3TSwbjT9525RYtGF31mcCAFBBdBPSEI7JNQMIQE/X1FqIYaNfib4DSgfjvgNqYmjN4mhsKWR9KgAAFUY3IQ3hmFwzgAD0ZAvX745P3Ta17KeMz//JxJi5YnvWZwIAUKF0E9IQjsk1AwhAT9RSKMYd45fFiQNry0bjHzw9L/Y0tmR9KgAAFUw3IQ3hmFwzgAD0NEs3743P3jmtbDA+6/qxMXrBxqzPBACgCugmpCEck2sGEICeolBM4udTVsTJg0aXjcZfe2hWbNnTmPWpAABUCd2ENIRjcs0AAtATrNrWEF+6d0bZYPy+a8bEUy+uiSRJsj4VAIAqopuQhnBMrhlAALJULCbx8PRV8d6ry3/K+H/94vlYt3Nf1qcCAFCFdBPSEI7JNQMIQFbW7tgXF9//fNlg/N6rR8eIGaujWPQpYwAAsqGbkIZwTK4ZQAC6W5Ik8eSsNXH6kLqy0fhL986IVdsasj4VAIAqp5uQhnBMrhlAALrT5j2N0f+hWWWD8cmDRsf9U1dEwaeMAQDoAXQT0hCOyTUDCEB3SJIkfjd3fZx57Ziy0fizd06LpZv3Zn0qAAC00U1IQzgm1wwgAF1tW31T/OvI2WWD8YkDa+OO8cuipVDM+lQAAHgT3YQ0hGNyzQAC0JVGL9gYZ98wrmw0/tRtU2Ph+t1ZnwkAACXpJqQhHJNrBhCArrCtvim+89hLZYPx8QNq4qa6JdHUWsj6VAAAKEs3IQ3hmFwzgAB0piRJ4vfzN7T7KeOP/3RyvLRmZ9anAgDAQekmpCEck2sGEIDOsmVvY7vPMu5zVU1c//vFsb/Zp4wBAMgH3YQ0hGNyzQACkFaSJPG7uevjA9ePLRuM+908KZ5fuT3rUwEAoEN0E9IQjsk1AwhAGlv2NMY3RpT/lHHfATVx3e8Xxb7m1qxPBQCADtNNSEM4JtcMIACHI0mS+PWcdXHmtWPKRuMLfzo5Xly9I+tTAQDgsOkmpCEck2sGEICO2rS7Mf73wy+2+ynjG//gWcYAAOSfbkIawjG5ZgABOFRJksTTs9fGGe18yvjjwyfHnNd8yhgAgMqgm5CGcEyuGUAADsWGXfvjnx+cVTYYHz+gJobVvhKNLT5lDABA5dBNSEM4JtcMIADtSZIknpi1Jt53TflPGV9065SYu2Zn1qcCAECn001IQzgm1wwgAOWs3bEvLnnghXY/ZXxT3RKfMgYAoGLpJqQhHJNrBhCAP1YoJvHgtFVx6tV1ZaPxJ2+bEvPX7sr6VAAA6FK6CWkIx+SaAQTgjZZt3hv/eM/0ssH4hIG1MXzsq9HU6lPGAABUPt2ENIRjcs0AAhAR0dxajDvGL4uTBtWWjcafvn1qLFy/O+tTAQCg2+gmpCEc0yH9+/dvG5xDeT388MNdeo8BBGDe2l3xqdumlg3GJw2qjdvGLY3m1mLWpwIAQLfSTUhDOKZDhGMAeop9za1xwx8Wx/EDSgfjPlfVxBfunh5LN+/N+lQAAMiEbkIawjEd8sZwfP/998fvfve7dl9r1qzp0nsMIEB1mr58W3z05ollg/GpV9fFA9NWRaGYZH0qAABkRjchDeGYDnljOF69enXW5xhAgCqze19L/OiZ+WWDcZ+rauKrv3wh1u7Yl/WpAACQOd2ENIRjOkQ4BiArdQs3xrlDx5cNxmdeOyZ+NXttJIlPGQMAQIRuQjrCMR0iHAPQ3bbsbYx/e3ROu58y/vZjc2LL3sasTwUAgB5FNyEN4ZgOEY4B6C5JksTTs9fGmdeOKRuMzx06PuoWbsr6VAAA6JF0E9IQjumQN4bjT37yk/Ge97wnjj766PizP/uzOPHEE+Piiy+Op556KgqFQrfcYwABKtPqbQ3x1V++0O6njK985uXYva8l61MBAKDH0k1IQzimQ94Yjtt7nXLKKTFnzpxUf9e0adMO+rrnnnsMIEAFaSkU4+5Jy+OUwaPLBuN+N0+K6cu3ZX0qAAD0eMIxaQjHdEj//v3jrW99a3zuc5+LG2+8MR599NH41a9+Fffcc09ccskl8ad/+qdtg/Qnf/InMWPGjMP+uw4lUL/xZQAB8m3OazvjU7dNLRuMjx9QE0NrFsf+5u75r1oAACDvhGPSEI7pkNmzZ0d9fX3ZP9+4cWN87GMfaxuld77zndHQ0HBYf5dwDFAd9jS2xNW/Wxh9B5R/LMWnbpsa89buyvpUAADIFeGYNIRjOl1DQ0O8973vbRum4cOHH9bv8agKgMqWJEnULdwYf/Pj8WWD8cmDR8ddE5dFc2sx63MBACB3hGPSEI7pEo8++mjbMF1wwQVd9vcYQIB82rBrf3xjxOx2v/zu4vufj1XbDu+/WgEAAHQT0hGO6RIbNmxoG6a/+qu/6rK/xwAC5EuhmMRD01fF6UPqygbjs64fG8/MWRdJkmR9LgAA5JpuQhrCMV2ipaWlbZiOOuqoLvt7DCBAfizesCc+f9e0dj9l/IOn5sX2+qasTwUAgIqgm5CGcEyX2LhxY9swveMd7+iyv8cAAvR8+5sLMaz2lThhYG3ZYHzBLZNi2rJtWZ8KAAAVRTchDeGYLvH444+3DVO/fv267O8xgAA925SlW+OjN08sG4xPHFgbN9cticaWQtanAgBAxdFNSEM4ptPt27cvTjvttLZhuvnmm7vs7zKAAD3Tlr2N8b0n5rb7WIp/vGd6LNm0J+tTAQCgYukmpCEcc8hGjBgRo0ePjmKxWPY9mzdvjk984hNvekzF3r17u+wmAwjQsxSKSTwyc3Wcce2YssH4jGvGxMiZq6NY9OV3AADQlXQT0hCOOWSXX355HHHEEfHOd74zLr300hg+fHg89thj8cwzz8R9990Xl156aRxzzDFtg3T00UfHlClTuvQmAwjQcyxYtzs+d5Avv/vWyDmxaXdj1qcCAEBV0E1IQzjmkL0ejg/ldeqpp8asWbO6/CYDCJC9PY0tcc2zC+P4AeWD8XnDJsS4xZuzPhUAAKqKbkIawjGHbP369fHYY4/FZZddFueff36ceOKJ8ba3vS3e8pa3xHHHHRfve9/74mtf+1qMGjUqCoXu+ZIjAwiQnSRJYtT8DXHu0PFlg/HxA2riut8vivqm1qzPBQCAqqObkIZwTK4ZQIBsrNrWEF/95QvtPpbiC3dPj4Xrd2d9KgAAVC3dhDSEY3LNAAJ0r8aWQtw6bmmcPGh02WB85rVj4rEXXvPldwAAkDHdhDSEY3LNAAJ0n6lLt8bHbpnU7qeMf/DUvNhW35T1qQAAQOgmpCMck2sGEKDrbd7TGN95/KV2g/Enhk+OmSu2Z30qAADwBroJaQjH5JoBBOg6rYViPDR9VbzvmjFlg/Epg0fH3ZOWR3NrMetzAQCAP6KbkIZwTK4ZQICuMee1nfHff/Zcu58y/tpDs2Ltjn1ZnwoAAJShm5CGcEyuGUCAzrWtvil++Kv57Qbj84ZNiLqFGyNJfPkdAAD0ZLoJaQjH5JoBBOgcrYVijJixOs68tvxjKU4YWBtDaxZHQ1Nr1ucCAACHQDchDeGYXDOAAOnNXr0jPnNH+4+l+OI90+OVjXuyPhUAAOgA3YQ0hGNyzQACHL6te5viB0/PazcYn33DuHjqxTVRLHosBQAA5I1uQhrCMblmAAE6rrVQjIemr4ozrin/WIrjB9TE1b9bGLv2NWd9LgAAcJh0E9IQjsk1AwjQMS+s3B6fvn3qQR9LsXD97qxPBQAAUtJNSEM4JtcMIMCh2bKnMS5/cm67wfiDN4yLX81e67EUAABQIXQT0hCOyTUDCNC+lkIxfvncynjfQR5Lce2oRbF7f0vW5wIAAJ1INyEN4ZhcM4AA5c1csT0+eduUdj9l/E/3zohFGzyWAgAAKpFuQhrCMblmAAEOtG7nvvj2Y3PaDcbn3Dg+fj1nXSSJx1IAAECl0k1IQzgm1wwgwP+zv7kQt459NU4ZPLpsMD5hYG1c9/tFsafRYykAAKDS6SakIRyTawYQICJJkhg1f0OcN2xCu58y/sp9M+OVjXuyPhcAAOgmuglpCMfkmgEEqt3C9bvjK/fNbDcYf2jo+PjtXI+lAACAaqObkIZwTK4ZQKBaba9vigG/WRB9B5QPxicPGh031S2J+qbWrM8FAAAyoJuQhnBMrhlAoNq0FIrxwLRVcca1Y9r9lPG/PDI7Vm9ryPpcAAAgQ7oJaQjH5JoBBKrJ1KVb46Jbp7QbjC+6dUo8t2xr1qcCAAA9gG5CGsIxuWYAgWrw2vaG+MaI2e0G4zOuHRMPTlsVLYVi1ucCAAA9hG5CGsIxuWYAgUpW39QaN9UtiZMHjS4bjPsOqImBv10Q2+ubsj4XAADoYXQT0hCOyTUDCFSiQjGJJ2etiXNuHN/up4y/ct/MWLRhd9bnAgAAPZRuQhrCMblmAIFKM335tvj07VPbDcYfHjYhfj9/QyRJkvW5AABAD6abkIZwTK4ZQKBSrNhaH19/+MV2g/Epg0fHreOWxv7mQtbnAgAAOaCbkIZwTK4ZQCDvdjY0x7WjFsWJA2vbjcbffmxOrNu5L+tzAQCAHNFNSEM4JtcMIJBXza3FeGDaqnj/dWPbDcafu2tavLh6R9bnAgAAOaSbkIZwTK4ZQCBvkiSJsYs2xYU/ndxuMP7bH0+I37y0LopFzzEGAAAOj25CGsIxuWYAgTxZtGF3XHz/8+0G41Ovros7xi/zHGMAACA13YQ0hGNyzQACebBlT2P86Jn50XdA+WDcd0BN/J9fzY/NexqzPhcAAKgQuglpCMfkmgEEerKGpta4Y/yyOG1IXbufMv4fP58ZC9fvzvpcAACgwugmpCEck2sGEOiJWgvFePyFNXHu0PHtBuMLbpkUdQs3RZJ4jjEAAND5dBPSEI7JNQMI9CRJksT4xZvjoluntBuMz7h2TPzyuZXR3FrM+mT+//buPD6q8tD/+GENOyIEKgghxa0iokALCtgiiGirAl6LG2Btba2tiOBlhwgoqATZGlZRZIcKqA0EJBBZBFksS1hkN8Gwh5BAAllmvr8/uJxfhkwyk5xJTk7yeb9ez+t1L/OcmedMep6mH4YzAAAAQAlGN4EVhGM4GhsggOJiV3ySnpu+Jc9g/MvBKzXiy1glXkm3e7kAAAAASgG6CawgHMPR2AAB2O2nC1f0jwU/5BmMQwZG6s9zdujI2RS7lwsAAACgFKGbwArCMRyNDRCAXRKvpOvdr/fpjiEr8wzGT0/ZpK3HLti9XAAAAAClEN0EVhCO4WhsgACK2tWMLEXEHNF9I1bnGYzbf7he/9mTwBffAQAAALAN3QRWEI7haGyAAIpKlsutf+88qTZjovMMxg+MXKNPNx/ni+8AAAAA2I5uAisIx3A0NkAAhc3tdmv9wbPqMnFjnsH4rqGr9EHUQV1Ky7B7yQAAAAAgiW4CawjHcDQ2QACFaceJRD03bUuewbjxoEj1X7pbCUlpdi8XAAAAADzQTWAF4RiOxgYIoDAcPJ2sP8/ZnmcwDhkYqZ6zt2l/QrLdywUAAAAAr+gmsIJwDEdjAwQQSPGJqXp7yS41HpR3MH5i4kZtPHzO7uUCAAAAQJ7oJrCCcAxHYwMEEAjnUq4p7Kt9umPIyjyDcdsP1mnZDyflcrntXjIAAAAA+EQ3gRWEYzgaGyAAK1KuZmj8mh/1q+FReQbjlqO/0ZzvTuhaZpbdSwYAAAAAv9FNYAXhGI7GBgigIK5mZGnWxmN6YOSaPINx0xGrNTn6sK5cy7R7yQAAAACQb3QTWEE4hqOxAQLIj8wsl5Zsj9dDY6LzDMZ3Dl2l9yL3K/FKut1LBgAAAIACo5vACsIxHI0NEIA/XC63vt6doEfDY/IMxqGDIjXg33uUkJRm95IBAAAAwDK6CawgHMPR2AAB5MXtdmv1vtN6fMKGPINxyMBIvT5vp46cTbF7yQAAAAAQMHQTWEE4hqOxAQLwxu12a/2PZ/WHyZt8BuMXZm7Vrvgku5cMAAAAAAFHN4EVhGM4GhsggJt9d+S8ukVs9hmM/zB5kzYdPm/3cgEAAACg0NBNYAXhGI7GBgjghu0nEtVjxhafwbjT+G+1cu8pud1uu5cMAAAAAIWKbgIrCMdwNDZAALvjk9Rz9jafwfh342L05a6fleUiGAMAAAAoHegmsIJwDEdjAwRKr/0JyfrznB0+g3HbD9ZpyY54ZWa57F4yAAAAABQpugmsIBzD0dgAgdLnx9MpemP+Dz6Dcev3ozVv609KzyQYAwAAACid6CawgnAMR2MDBEqPA6eS9fq8nT6DccvRazV703Fdzciye8kAAAAAYCu6CawgHMPR2ACBkm9fwiX9da7vW1I0H7lG0749qtT0TLuXDAAAAADFAt0EVhCO4WhsgEDJFfvzJb32ue9gfN+I1ZoUfVgpVzPsXjIAAAAAFCt0E1hBOIajsQECJc/ek5f8+tK7piNWa9zqH3UplWAMAAAAAN7QTWAF4RiOxgYIlBx7Tibp1c+2+/UJ4/FrflRSarrdSwYAAACAYo1uAisIx3A0NkDA+XbFJ+mVT7f5DsZhq/XxN4f4hDEAAAAA+IluAisIx3A0NkDAuXacSFSv2b6DcbOw1Zqw9pAupRGMAQAAACA/6CawgnAMR2MDBJzF7XZrw6Fzem76Fp/B+P5312hS9GEl86V3AAAAAFAgdBNYQTiGo7EBAs7gcrkVFXtaT03Z5DMYNx+5RlPWHVYKwRgAAAAALKGbwArCMRyNDRAo3jKzXFr2w0l1HP+tz2D8wMg1+tf6I7p8LdPuZQMAAABAiUA3gRWEYzgaGyBQPF3NyNK8rT+p3YfrfAbjFqO+0dSYowRjAAAAAAgwugmsIBzD0dgAgeLlyrVMzdxwTL9+b63PYPzQmGjN+e6E0tKz7F42AAAAAJRIdBNYQTiGo7EBAsXDpdQMTVx7WM1HrvEZjH83LkZLdsQrPdNl97IBAAAAoESjm8AKwjEcjQ0QsFdCUppG/2e/7h0e5TMYd5m4Uf/Zk6Asl9vuZQMAAABAqUA3gRWEYzgaGyBgj4Onk/X24l1qMnilz2DcLWKz1h08I7ebYAwAAAAARYluAisIx3A0NkCg6Ljdbm05ekG9P93mMxaHDIzUy598ry1HLxCMAQAAAMAmdBNYQTiGo7EBAoUvy+XWyr2n9PSUTX4F49c+36Fd8Ul2LxsAAAAASj26CawgHMPR2ACBwnM1I0tzt/6kRz5a7zMW3zFkpfov3a1DZ1LsXjYAAAAA4P/QTWAF4RiOxgYIBN7FK+maFH1YLUZ94zMYNx2xWu+vPKBTl9LsXjYAAAAA4CZ0E1hBOIajsQECgXPs3GUNWxGre4ZF+QzGrd5bq6kxR3UpLcPuZQMAAAAAckE3gRWEYzgaGyBgjdvt1ndHzuvVz7b7df/iR8NjtHh7nK5lZtm9dAAAAACAD3QTWEE4hqOxAQIFcy0zS0t3xKvLxI1+BeNnp36nb/afkcvltnvpAAAAAAA/0U1gBeEYjsYGCOTPhcvXNCn6sFqOXutXMP7L5zu040Si3csGAAAAABQA3QRWEI7haGyAgH8On0nRoGV7dNfQVT5j8V1DV2nQsr06cjbF7mUDAAAAACygm8AKwjEcjQ0QyJ3b7da3h86p5+xtfn26+NfvrdWUdYeVeCXd7qUDAAAAAAKAbgIrCMdwNDZAIKeUqxn6bPNxdQiP8SsYPzlpo5b9cFLpmS67lw4AAAAACCC6CawgHMPR2ACB/+/I2csa/mWs7h0e5TMWNx4UqT/P2aEtRy/I7eYL7wAAAACgJKKbwArCMRyNDRClXZbLrTX7TuulWd/79eniXw2P0ogvY3X8/BW7lw4AAAAAKGR0E1hBOIajsQGitLp4JV3Tvj2qh8eu8ysYtxkTrWnfHtWl1Ay7lw4AAAAAKCJ0E1hBOIajsQGitIn9+ZL+99+7ddfQVX4F4+emb1HknlPKyOL+xQAAAABQ2tBNYAXhGI7GBojS4GpGlpb9cFLdp37nVyy+e9gqDVq2R/sTku1eOgAAAADARnQTWEE4hqOxAaIkO3ruskb9Z7+aj1zjVzBu9+E6zdxwTEmp6XYvHQAAAABQDNBNYAXhGI7GBoiSJj3Tpa93J+j5GVv9isUhAyP18iffK/rAGWW53HYvHwAAAABQjNBNYAXhGI7GBoiSIu5CqsauOqiWo7/xKxY3HbFaYV/t09Fzl+1eOgAAAACgmKKbwArCMRyNDRBOlpnlUlTsafWcvc3vTxd3/niDPt9yQpevZdq9fAAAAABAMUc3gRWEYzgaGyCc6MT5K/ow6qB+8/5av2LxnUNX6e3Fu7TjRKLcbm5HAQAAAADwD90EVhCO4WhsgHCKtPQsfbHzpP44fYvfny7uMC5GszYe08UrfNkdAAAAACD/6CawgnAMR2MDRHHmdru1Kz5Jg5fv1X0jVvsVi+8YslJvLPhB3x09z6eLAQAAAACW0E1gBeEYjsYGiOIo8Uq6Ptl0XJ0/3uD3p4vbfbhOETFHdC7lmt3LBwAAAACUEHQTWEE4hqOxAaK4yHK5FfPjWf19/k7dMWSl358ufn3eTsX8eFYuF58uBgAAAAAEFt0EVhCO4WhsgLDbgVPJen/lAf36Pf++6C5kYKQ6jf9WszYe04XLfLoYAAAAAFB46CawgnAMR2MDhB3OplzVrI3H1GXiRr9jcdMRqzVo2R79N+4i9y4GAAAAABQJugmsIBzD0dgAUVTS0rP05a6f1Wv2NoUO8i8WhwyM1HPTt+jfO08qNT3T7lMAAAAAAJQydBNYQTiGo7EBojC5XG59d/S8+i/drXuHR/kdi3/93lp9EHVQx89fsfsUAAAAAAClGN0EVhCO4WhsgAg0t9ut2J8v6f2VB/TQmGi/Y/GdQ1fpHwt+0LqDZ5SZ5bL7NAAAAAAAoJvAEsIxHI0NEIFy5GyKxn9zSB3Gxfgdi2/cimLx9jglX82w+xQAAAAAAPBAN4EVhGM4GhsgrIhPTFVEzBE9PmFDvmLx78bFaHL0YcUnptp9CgAAAAAA5IpuAisIx3A0NkDk19nkq5q96bi6RmzOVyxuPnKNhq2I1X/jLsrtdtt9GgAAAAAA+EQ3gRWEYzgaGyD8kZCUptmbjuu5aVvUeJD/sfiuoav0+rydWr3vtNIzuW8xAAAAAMBZ6CawgnAMR2MDRG7iLqRq+rdH9cy/8vfJ4iaDV+pPn23X8v+eVAr3LQYAAAAAOBjdBFYQjuFobIDI7sjZFE2OPqwnJm7MVyxuPChSz8/YqoXb4nTxSrrdpwEAAAAAQEDQTWAF4RiOxgZYurlcbu05maTwNT+q0/hv8xWLQwZGqmvEZs3edFxnk6/afSoAAAAAAAQc3QRWEI7haGyApc/VjCytO3hGg5bt1W/eX5vvWPz0lE2aGnNU8Ympdp8KAAAAAACFim4CKwjHcDQ2wNLhXMo1Ldker9c+36F7hkXl+zYU/zPtO32y6bh+Tkqz+1QAAAAAACgydBNYQTiGo7EBlkxut1s/nk5RRMwRdYvYrMaD8vep4tBBkXph5lbN3XKC21AAAAAAAEotugmsIBzD0dgAS45LaRlaufeUBvx7j1q/H53vW1DcMWSles3epsXb45TIF9wBAAAAAEA3gSWEYzgaG6BzuVxu7Y5P0uTow3p26nf65eCV+Y7FzUeuUd/FuxS555RSrmbYfUoAAAAAABQrdBNYQTiGo7EBOsvpS1f1xc6T6rPov3pw1Df5DsUhAyP1u3Exei9yv74/dkGZWS67TwkAAAAAgGKLbgIrCMdwNDbA4u3C5WuK3HNKQ5bvVYdxMQUKxaH/9+V20789qo4pfZQAACAASURBVKPnLtt9SgAAAAAAOAbdBFYQjuFobIDFS/LVDK3df0Yjv96vxydsKFAoDhkYqRajvlHfxbu04r8/c79iAAAAAAAKiG4CKwjHKLBVq1apR48eaty4sSpVqqTatWurVatWGj16tM6dO1cka2ADtNfZlKtatfeURn69X09P2aTQQQULxb8cvFLPTduif60/otifL8nlctt9agAAAAAAOB7dBFYQjpFvqampevbZZ82Nx9uoU6eOVq1aVehrYQMsOm63W0fOXtaibXHqv3S3fvvR+gJ/ojhkYKQeGhOtQcv2KCr2lJL5YjsAAAAAAAKObgIrCMfIF5fLpd///vfmphMcHKzBgwdrwYIFmjZtmjp37mw+VqlSJW3evLlQ18MGWHiSUtO14dA5TY4+rD/P2VHgL7O7Me5/d43+NnenPt9yQkfOpsjt5lPFAAAAAAAUJroJrCAcI19mzZplbjh33XWXEhIScswJDw8359x5553KyCi8T5OyAQZGanqmtp9I1KyNx/TPhf/VIxY/TRwyMFL3Do/SK59u08wNx7j9BAAAAAAANqCbwArCMfzmcrnUoEEDc8PZtm1brnOfeOIJc96sWbMKbU1sgPnjdrt1JvmqYn48q6kxR9Vn0X/12MffFvjexNnHr4ZH6cVZWzVl3WHt/OmiMrJcdp8uAAAAAAClGt0EVhCO4beYmBhzs2nXrl2ec6Ojo825jz76aKGtiQ3QO7fbrQuXr2nb8UQt2hanUf/ZrxdmbrV8u4ns49fvrdUb83/Qp5uPK/bnS8okFAMAAAAAUKzQTWAF4Rh+GzBggLnZjB07Ns+5mZmZqlatmgzDULly5XTlypVCWVNp3gBvxOE9J5O0cu8p/Wv9EfVbsltdIzbr/nfXBCwQhwyMVONBkeo0/lsNWrZXy344qfjEVO5RDAAAAABAMVeauwmsIxzDb126dDE3m3Xr1vmc365dO3P+9u3bC2VNJW0DzMxyKflqhs4kX9WRs5e19dgFRe45pc+3nND4bw5p0LK96jl7mx4Nj9E9w6ICGoezj7YfrNMb83/Q9G+PauuxC7p8LdPutwYAAAAAAORTSesmKFqEY/gtNDTU3GyOHz/uc37Pnj3N+fPmzcv3623atMnniIiIcPwGODXmqJqPXKM7h6wqtBCc13h47Dq9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width=\"639.9\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 1.5\n",
    "\n",
    "U_0 = np.linspace(1,10, 2048)\n",
    "i_p = 1.0 # in nA\n",
    "I = i_p * (U_0-1.0)**n\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(U_0,I)\n",
    "plt.axhline(y=0., color='gray', linewidth=0.5)\n",
    "plt.xlabel('overvoltage $U_0$ []')\n",
    "plt.ylabel('$I$ [nA]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the graph above, we can see the importance of the overvoltage $U$ by how the intensity increase with increasing $U_0$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz\n",
    "Why is the overvoltage increasing so much while the cross section remains rather constant above the threshold? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Back: [Bremsstrahlung](CH4-Bremsstrahlung.ipynb)\n",
    "## Next: [Detector Response](CH4-Detector.ipynb)\n",
    "## List of Content: [Front](_Analysis_of_Scanning_Electron_Microscope_Data.ipynb#Content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
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 },
 "nbformat": 4,
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}