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ZGainsforth/Extract EDS tomo data.ipynb

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Quick and dirty way to read EDS info out from an EDS tilt series of Bruker stacks and place the maps into tilt stacks for tomographic reconstruction.
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Extract EDS tomo data.ipynb
{
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{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING:hyperspy_gui_traitsui:The nbAgg matplotlib backend is not supported by the installed traitsui version and the ETS toolkit has been set to null. To set the ETS toolkit independently from the matplotlib backend, set it before importing matplotlib.\n",
"WARNING:hyperspy_gui_traitsui:The traitsui GUI elements are not available.\n",
"/Users/Zack/Git/OtherLibs/tifffile.py:2170: UserWarning: failed to import _tifffile.decodepackbits\n",
" warnings.warn(\"failed to import %s\" % module_function)\n",
"/Users/Zack/Git/OtherLibs/tifffile.py:2170: UserWarning: failed to import _tifffile.decodelzw\n",
" warnings.warn(\"failed to import %s\" % module_function)\n",
"/Users/Zack/Git/OtherLibs/tifffile.py:2170: UserWarning: failed to import _tifffile.unpackints\n",
" warnings.warn(\"failed to import %s\" % module_function)\n"
]
}
],
"source": [
"# Written by Zack Gainsforth, 2018\n",
"\n",
"%pylab nbagg\n",
"import hyperspy.api as hs\n",
"import glob2 as glob\n",
"from serReader import serReader\n",
"from tifffile import imsave, imread\n",
"import os\n",
"import re\n",
"from scipy.ndimage.interpolation import shift"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Instructions on calling GenFire from python here: http://genfire-em.com/about/"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Step 1: Find all the Bruker files. \n",
"They should be named num.bcf where num is the stage tilt, e.g. 0, 10, 15, -5, -15, etc."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"Bcfs = glob.glob('*.bcf')\n",
"# print(Bcfs)\n",
"NewBcfs = []\n",
"for i in Bcfs:\n",
" if i[0] == 'n':\n",
" NewName = '-'+i[1:]\n",
" NewBcfs.append(NewName)\n",
" os.system('mv %s %s'%(i, NewName))\n",
" else:\n",
" NewBcfs.append(i)\n",
"Bcfs = NewBcfs\n",
"Nums = list(map(lambda s: float(s[:-4]), Bcfs))\n",
"Nums.sort()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Step 2: Read all the files into memory.\n",
"Loop through all the BCF files and extract EDS maps for each element we want. We will have a stack for each element, and each stack is a tilt sequence."
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-55.bcf\n",
"-50.bcf\n",
"-45.bcf\n",
"-40.bcf\n",
"-35.bcf\n",
"-30.bcf\n",
"-25.bcf\n",
"-20.bcf\n",
"-15.bcf\n",
"-10.bcf\n",
"-5.bcf\n",
"0.bcf\n",
"5.bcf\n",
"10.bcf\n",
"15.bcf\n",
"20.bcf\n",
"25.bcf\n",
"30.bcf\n",
"35.bcf\n",
"40.bcf\n",
"45.bcf\n",
"50.bcf\n",
"55.bcf\n",
"60.bcf\n",
"65.bcf\n",
"70.bcf\n"
]
}
],
"source": [
"# What size should the rebin be to.\n",
"# Usually we acquire EDS maps at too high a resolution and we want to downsample to get a better result.\n",
"rebinsize = 128\n",
"binning = 4\n",
"# Note rebinsize and binning must agree.\n",
"\n",
"# And write them to a tif.\n",
"SignalList = ['HAADF', 'Al', 'C', 'Ca', 'Cr', 'Fe', 'Ga', 'Mg', 'Na', 'Ni', 'O', 'P', 'Pt', 'S', 'Si']\n",
"for s in SignalList:\n",
" exec(s + ' = []')\n",
"\n",
"def WriteFile(n):\n",
" fname = n+'.bcf'\n",
" print(fname)\n",
" x = hs.load(fname)\n",
" HAADF.append(x[0].data) # The HAADF doesn't get rebinned.\n",
" El = x[1].get_lines_intensity(['Al_Ka', 'C_Ka', 'Ca_Ka', 'Cr_Ka', 'Fe_Ka', 'Ga_Ka', 'Mg_Ka', 'Na_Ka', 'Ni_Ka', 'O_Ka', 'P_Ka', 'Pt_La', 'S_Ka', 'Si_Ka'])\n",
" for i, s in enumerate(SignalList):\n",
" if s == 'HAADF':\n",
" continue\n",
" exec(s + '.append(El[%d-1].rebin((rebinsize,rebinsize)).data.copy().astype(\"int32\"))'%i)\n",
" \n",
"for n in Nums:\n",
" if n < 0:\n",
" # Filenames starting with a minus need an extra character.\n",
" WriteFile('%d'%(n))\n",
" else:\n",
" WriteFile('%d'%(n))"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [
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" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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6//xj3+E559/PnnHV77yleyowKK+VOEECBAgQIAAAQIECBAgQIAAgW4ICAB2A80jpSkQp+tm0s9//vPMYVF+//jHP86We+ihh2aPHRAgQIAAAQIECBAgQIAAAQIESk1AALDUekR9ui0wadKksN122yXP33nnneGUU07psKzXXnst/Pa3v22VZ/bs2WHWrFmtrscLS5YsCT/60Y9CLD+mvffeO3zhC19Ijv2HAAECBAgQIECAAAECBAgQIFCKAlVLAxpLSrFi6lR5AnFNvZdeeinb8Pr6+nDMMcck55tvvnk46KCDsvfiwf777593Hk/+/e9/h4033jjMmDEjuffZz342fPvb3w7rrrtuiGv1NTQ0hLh5x9133x3uv//+EKfv3nTTTXnlTJ06Ndn99xvf+EbYcccdw+qrrx5aWlrCv/71rzB58uTw2GOPJfnjlONYRu5uwHkFOSFAgAABAgQIECBAgAABAgQIlICAAGAJdIIqfCgQA3pXX311lznai12//vrrYY899ghPPvlkp2UdcMAB4YorrsjLFwOAcTRhR2nnnXdO6jpmzJiOsrlHgAABAgQIECBAgAABAgQIEOh3AbsA93sXqEBvC6y66qrh8ccfD7feemv43e9+lxzHnYEXLlyYjNabOHFi2HTTTcOuu+7a5vTdNddcM1x00UXhvvvuC88++2yyq/CiRYvCiiuuGDbbbLNk2u/222/f29VWHgECBAgQIECAAAECBAgQIECgKAJGABaFVaEECBAgQIAAAQIECBAgQIAAAQIESkPAJiCl0Q9qQYAAAQIECBAgQIAAAQIECBAgQKAoAgKARWFVKAECBAgQIECAAAECBAgQIECAAIHSEBAALI1+UAsCBAgQIECAAAECBAgQIECAAAECRREQACwKq0IJECBAgAABAgQIECBAgAABAgQIlIaAAGBp9INaECBAgAABAgQIECBAgAABAgQIECiKwKCilKpQAp0IzJ8/P0ybNi3JNXbs2DBokE+xEzK3CRAgQIAAAQIECBAgQIDAMgu0tLSE9957L3lu3XXXDcOGDVvmMjxQ/gKiLuXfh2XZghj822STTcqy7ipNgAABAgQIECBAgAABAgTKUeCJJ54IkyZNKseqq3MPBUwB7iGgxwkQIECAAAECBAgQIECAAAECBAiUsoARgKXcOymuW5z2m0nxXyBWWmmlzKnfBAgQIECAAAECBAgQIECAQC8JzJgxIzsDL/fv4r1UvGLKREAAsEw6Km3VzF3zLwb/xo0bl7Ymag8BAgQIECBAgAABAgQIECgpgdy/i5dUxVSm6AKmABed2AsIECBAgAABAgQIECBAgAABAgQI9J+AAGD/2XszAQIECBAgQIAAAQIECBAgQIAAgaILCAAWndgLCBAgQIAAAQIECBAgQIAAAQIECPSfgABg/9l7MwECBAgQIECAAAECBAgQIECAAIGiCwgAFp3YCwgQIECAAAECBAgQIECAAAECBAj0n4AAYP/ZezMBAgQIECBAgAABAgQIECBAgACBogsIABad2AsIECBAgAABAgQIECBAgAABAgQI9J+AAGD/2XszAQIECBAgQIAAAQIECBAgQIAAgaILCAAWndgLCBAgQIAAAQIECBAgQIAAAQIECPSfgABg/9l7MwECBAgQIECAAAECBAgQIECAAIGiCwwq+hu8gEARBebPnx9mzZoV5s6dGxYtWlTENymaAIFiCQwcODAMGTIkLLfccqGmpiYMGODfpoplrVwCBAgQIECAAAECBCpTQACwMvu97Fu9ZMmSMGPGjPDBBx+UfVs0gEClC7S0tIQFCxaEOXPmhKqqqvDxj388jBw5stJZtJ8AAQIECBAgQIAAAQK9JiAA2GuUCupLgYaGhlbBv0GDfM592QfeRaC3BOLo3RjUjyn+fuuttwQBewtXOQQIECBAgAABAgQIEFgqIGLiMyg7gebm5vDee+9l673CCiuEUaNGhTiNUCJAoPwEYtAvTuOfOXNmaGxszAYB11hjDdOBy6871ZgAAQIECBAgQIAAgRIUsNBSCXaKKnUsEAMEmVRbWxvij+BfRsRvAuUnEKf9VldXh3HjxiVrAMYWxKBg7p/18muVGhMgQIAAAQIECBAgQKB0BAQAS6cv1KSLAk1NTdmccdMAiQCBdAjEQOCYMWOyjZk9e3b22AEBAgQIECBAgAABAgQIdF9AALD7dp7sJ4E4BTimGCwYOnRoP9XCawkQKIbAiBEjkj/bsezMn/VivEeZBAgQIECAAAECBAgQqCQBAcBK6u2UtHXx4sVJS+K03xgElAgQSI9A/DOdmdIfNweRCBAgQIAAAQIECBAgQKDnAgKAPTdUAgECBAgQIECAAAECBAgQIECAAIGSFRAALNmuUTECBAgQIECAAAECBAgQIECAAAECPRcQAOy5oRIIECBAgAABAgQIECBAgAABAgQIlKyAAGDJdo2KESBAgAABAgQIECBAgAABAgQIEOi5gABgzw2VQIAAAQL/EXjttdeSzXniZh5XXXUVFwIECBAgQIAAAQIECBAoAQEBwBLoBFUgUMoC+++/fzagE4M7XUkTJkxInom/i5FiYCkGmDI/xx9/fKev2XLLLYtap04rIAMBAgQIECBAgAABAgQIEOgnAQHAfoL3WgIEek/goosuCu+++27vFagkAgQIECBAgAABAgQIECCQIgEBwBR1pqYQqFSBpqamcNZZZ1Vq87WbAAECBAgQIECAAAECBAh0KCAA2CGPmwQIlLpAXV1dUsVLLrkkzJgxo9Srq34ECBAgQIAAAQIECBAgQKDPBQQA+5zcCwkQ6E2BY489Nilu/vz54YwzzujNopVFgAABAgQIECBAgAABAgRSISAAmIpu1AgC5SEwZcqU7MYd8TimG2+8MWyzzTZh7NixYfjw4WHNNdcMMag3c+bM5H5n/5k0aVLYZZddkmyXXXZZmD59emePdHg/bnRy5JFHhk996lNh5MiRYcSIEWHixInhkEMOCdOmTevw2cymJKeeemqS7/777w977LFHGD9+fBg8eHDI3RQl5snkj5lnz54d4rV111031NTUhI997GNhxx13DH/729+SsjL/iWsdnnjiiUn9qqurQ21tbdhtt93C3//+90yWDn//7//+b/h//+//Jc8vv/zyifnqq68eDjjggPD00093+Gy8uWjRovDLX/4yfPaznw3LLbdciGVsuOGG4dxzzw0LFizo9HkZCBAgQIAAAQIECJSrwOLFS8I1j74W7pw2Izz+SkN46d3GsHDR4nJtjnpXmMCgCmuv5hIgUCICMZC01157heuvvz6vRv/3f/8XzjnnnPDHP/4xPPTQQ2HFFVfMu9/WyU9+8pNw++23h+bm5vDTn/40/OpXv2orW6fXfvOb34SDDz64VSDrpZdeCvHn8ssvD6effno44YQTOi3rxz/+cZdHJMag5Ze+9KUQ255JcV3Du+66K/z5z38Ov/3tb5NA4jPPPJMEBd96661MtjB37txw2223hXvuuSfceeedYeutt87eKzyIdY9WLS0tebdeffXVEH+uvvrqcNJJJ4XTTjst737mZM6cOWGHHXYIjzzySOZS8jsGH+PPDTfcEH7961/n3XNCgAABAgQIECBAIC0Cs+cvDCfd+q+85jx6wtZhpeWH511zQqAUBYwALMVeUScCFSBw8sknJ8G/r3zlK+Hmm28OTz31VBLA2mmnnZLWx4BbHInXlbT++uuH3XffPcl65ZVXJsGsrjyXm+eOO+4I+++/fxL8iyPwTjnllCQA+eijj4Zf/OIXIa41GIOWP/rRj0Jcb7CjFIOXcTpyHM13xRVXhCeeeCI8+OCD4Yc//GGbj8VRgm+++WYSWIz5nnzyyXD++ecnI+ziOw888MCkTTvvvHOYN29e+NnPfhYefvjh8PjjjyfBuiFDhiT1jqP4YhC0rRS9408M/m222WZh8uTJIbZt6tSp4brrrgubbrppWLJkSRIgvPDCC9sqIgnYZoJ/m2yySRKYjM9Hu9iG2IdxpKREgAABAgQIECBAII0C9Y2tZ7yMqR6SxqZqUwoFjABMYadqUghxaPb7c9sOhKTVZ/SIIWHAgKqyaV6c2hpH68WRcrnpy1/+cog/ceTbTTfdFC644IJkenBunraO46i1W265JSxcuDAZpRcDb11N8ZkYuIoBsBj8iyMPY1Axkz73uc+Fr33ta0mQLG40cvTRRycBr8wGJJl8md9xpF6c1hwDY0OHDs1cDl/84hezx7kH//jHP5IAYZxWm0kbb7xxWGONNUIMiMaRd/FerF8MJn7iE5/IZAsxEBfrcdhhh4U33ngjeWcmGJrJFAOKMWgYU5w+HEcC5qaNNtoo7LnnnmG//fYL1157bdIn++yzTxg1alQ225/+9KcQf2KKU5NvvfXWMGjQR/8nJF6Lowtj4FQiQIAAAQIECBAgkEaB+sb8v2OOHDYoDB00MI1N1aYUCnz0t7cUNk6TKlcgBv82+ul9FQXw1IlfCrU1HwWbSr3xMegUR9MVprguXhwpFwOAcbRaHKW26667FmZrdf7pT386Ccr97ne/C3Eqb5ymG9fu60qKI/Yy02pjQDI3+Jd5ftVVV02mJu+9997JtNs40vCYY47J3M77PWDAgGSEXW7wLy9DwckRRxyRBPgKLieBtvje119/Pbz33nvh0ksvzQv+ZfLHkX9HHXVUiBuhxOBlYQDw7LPPXhoUXxyieQzStZVinePIv9///vdJwDEGXw866KBs1syox9imOM03N/iXyRSDi/H5Z599NnPJbwIECBAgQIAAAQKpEWgoCADWldHfv1LTCRrSbQFTgLtN50ECBHoi8F//9V/JJhhtlREDVZn0yiuvZA47/R030Rg4cGAyVbe9dezaKuS++z4MFsfg47e//e22siTX4jTXuOlFTJlnkpOC/2y++eZ5G34U3G51GkfftZc+85nPJLdi3b7xjW+0mS1unpIJdhZ6xdGNcS3BmL7+9a+3ax7vxxF/cdpyTDHwmkkxEBunJse03XbbhZVXXjlzK+93DCLGUYQSAQIECBAgQIAAgTQKNDTlTwGuNf03jd2c2jYJAKa2azWMQGkLrLXWWu1WcMyYMdl7cfprV1MsMwYWY4obZzz//PNdejQzYm3ChAlhhRVWaPeZuNbeBhtskNzPPNNW5kzQrq17bV2LU33bS5lpuHGa7+jRo9vLlp2uW+j13HPPJSMW44NxVGRm5+H2fsc1/WJ6++23k9/xPy+//HK2jLjrckcpTkmWCBAgQIAAAQIECKRRoHAKcG2N9f/S2M9pbZMAYFp7VrsI9JJADBQta4pr1cXU0bMjRoxot9g4kiyT4iYYy5LiGnRxemqc8hpHBHYlzZw5M8n2sY99rNPsmV2JM8+09UBHgbq28nfFoqM8scyMWaHXu+++29YrO70WdxfOpPfffz9z2GGANGbqimG2MAcECBAgQIAAAQIEykigoWATkHJagqmMmFW1SALWACwSrGL7VyBuiBHXxKukFNtcjBSnl2ZSblAoc62t301NTcnl6urqtm4X9VrcIGPfffdNdt+N69HFNf26OiKvo4BlptKZ4GbmvK3fcRpyqaTcgOA555yTbLDSlbrl9l1umzszys3blffIQ4AAAQIECBAgQKBcBFqtAWgKcLl0nXouFRAA9BmkUiDuhutfY3qna3On48Zpoeuss06HBS9YsCDMmjUryZP7bIcP9fLNk046KVxzzTXJjsBxRGDc5KOjlKln7rTX9vK/8847ya3MM+3lK5XrtbW12arE9QDjZinLmnLbmml/e2V0d8Rhe+W5ToAAAQIECBAgQKBUBFqtAWgTkFLpGvXogsBH8+y6kFkWAgQqTyB39NzTTz/dKcA///nPZBOOmDH32U4f7MUMcS2/Aw88MCnxlltuCZ3VOxMUe+2110JHAawYQPv73/+elJt5pherXZSiPvWpT4W4dmFMcWfl7qQ4qjIzBfnJJ5/ssIjO7nf4sJsECBAgQIAAAQIESligcASgNQBLuLNUrZWAAGArEhcIEMgV+OIXv5isqRevxY01Opviee2112Yf32abbbLHfX0Qp/4OHTo0ee3JJ5/c4eu/9KUPp4vHtl1xxRXt5r3pppvCBx98kNzPPNNu5hK5EQN3mX6YMmVKeOKJJ5a5ZnFNxS222CJ5LgYRZ8yY0WYZcd3Fq6++us17LhIgQIAAAQIECBAod4H6wjUAqz/8+0a5t0v9K0NAALBM+vnYY4/N270z/kW+u2n27NnhhhtuCN/5znfChhtumOweGkcIjR07Nmy55Zbh3HPPzU7h7O47PJcegbjpxde//vWkQXEk3VlnndVu4+6///5w6aWXJvdXXXXVsMsuu7Sbt9g3xo0bFw4++ODkNXfccUf417/+1e4rd99997Dyyisn988444wQRzEWpunTp4ejjz46uRyDagcccEBhlpI9j8HQzNp9e+65Z7Krb3uVjWsGXn/99eHNN9/My/K9730vOY9TvA855JDsKM/cTGeeeWaYNm1a7iXHBAgQIECAAAECBFIh0NyyOMye35LXljq7AOd5OCltAQHA0u6fpHYxGHH++ef3Sk3vuuuuZBfPb33rW2Hy5MnJdMY4oilObayvrw8PPvhgOOaYY8Jaa60VHnjggV55p0LKX+C8887L7v76ox/9KGy//fbJGnuPP/54eOqpp8Ktt94aDjrooOR6/JbijrRXXnllduRgfwnEumY2MYnfd3tp8ODB4bLLLkuCZHPmzAmf//znw09+8pPwyCOPhNjG+Odv4403Dv/+97+TImKQvK6urr3iSu765ptvHjKjIF999dWw/vrrhyOOOCLceeedyf8GPPbYY8k/CvzgBz8Iq6yySthrr71a/SNADOZmArp/+tOfQizzd7/7XTK9+u677w4xsHjiiSeGSZMmlVz7VYgAAQIECBAgQIBATwVmNjW3KsK6861IXChhAZuAlHDnxKrFKXVxpF5LS0sSgOlofbKuNKWhoSHEETwxQLPtttsmO4Kut956ySjAOOLnuuuuS/5SHxf633nnnZMASAwWSJUtsNJKK4W//vWvIY6Ue/7555O15NpbT27UqFEhTgPeaqut+h0tjl489NBDwy9+8YtO67LTTjslQcs4uq2xsTHEzUPiT26Ku/uefvrpITMaLvdeqR+feuqpyZ/z448/Pmnf//zP/4T401aKI4KHDRvW6lb834cddtghGxiNQb/cFEcU/+pXv0pGFuded0yAAAECBAgQIECg3AUKp/8u3XcyjBo+uNybpf4VJGAEYIl39gUXXBDiovpxRF5mU4OeVDmOdIoBjjgKKI7aiaOAYqBmgw02SEb3xKnB8Z0xzZ07Nxx11FE9eZ1nUySw5pprhmeeeSYJ7sUpwXGKb5wKG4NFMdAW15k755xzQtxIIwbTSiUdd9xxobq6ukvV2W+//cILL7wQ4ki4tddeO3kujiCMm2DEQHzcAOSEE07oUlmlmCn+eX/55ZdD3CX5c5/7XDKKMa7vF33WWGON8LWvfS2Zwv3WW2+FT37yk62aMHLkyDBl6fIDF154YTLSr6amJsRr8R8J4vTfOGJy9OjRrZ5zgQABAgQIECBAgEC5CzQUjAAcs3T9vwExCigRKBOBqqWL3i8pk7pWXDXjmmPrrLNOMlonTseNf/E+7bTTEod4HtfrK1aK0/imTp2ajBSMow5ra2t79VVxtOH48eOTMmM743ptXU0vvvhiMiIyBi4mTpzY1cfkI0CgTAT8GS+TjlJNAgQIECBAgEAFCdz89Jvhhzd+tFb4WiuODHcf8cWyEOjJ37/LooEq2SUBIwC7xNQ/meLUxTgVMY5KKmawr63WZd4XpyDH0YISAQIECBAgQIAAAQIECBCoVIGGxvw1AGttAFKpn0LZtlsAsES77sYbbwy33357GDNmTDKtsq+rGdcJzKS4XqBEgAABAgQIECBAgAABAgQqVaC+6aO/I0eD2qVTgCUC5SQgslOCvTVr1qxkDbJYtbPPPjuMHTu2z2sZdwOOKU6zbWstsD6vkBcSIECAAAECBAgQIECAAIF+EjACsJ/gvbbXBOwC3GuUvVfQscceG95+++2w2Wab9crGH8taszvuuCPZ7CE+t/3224fllltuWYsIcY2BjtKMGTM6uu0eAQIECBAgQIAAAQIECBAoGYGGxvwRgHU1RgCWTOeoSJcEBAC7xNR3mR5++OEwefLkZOTdpZdeGqqq+nZXoZkzZ4bDDjssafDAgQPD6aef3q3GZzb46NbDHiJAgAABAgQIECBAgAABAiUkULgLcG31kBKqnaoQ6FzAFODOjfosR3Nzczj44IND3Jj5yCOPDOuuu26fvTu+aNGiRWGvvfYKr7/+evLeE088MWywwQZ9WgcvI0CAAAECBAgQIECAAAECpSbQegqwEYCl1kfq07GAEYAd+/Tp3TPOOCM8//zzYZVVVgmnnHJKn747vizuOnz33Xcn791pp53CSSed1O06TJ8+vcNn4xTgTTbZpMM8bhIgQIAAAQIECBAgQIAAgf4WiIN06gumANsFuL97xfuXVUAAcFnFipT/hRdeCGeeeWZS+oUXXhiqq6uL9Ka2iz3hhBPCZZddltz8/Oc/H37/+9+HOAW4u2ncuHHdfdRzBAgQIECAAAECBAgQIECgZASamheFBS2L8+pTZxfgPA8npS8gAFgifXT++eeHOAV49dVXD3Pnzg033HBDq5o9++yz2Wv3339/slFIvLDLLrv0KGAYdxo+66yzkrI33HDDcPvtt4fhw4dn3+WAAAECBAgQIECAAAECBAhUqkDhBiDRwQjASv0ayrfdAoAl0ncLFny4o9Arr7wSvvWtb3Vaq9zNOV599dVuBwAvvvjicPzxxyfvW3vttcM999wTll9++U7fLwMBAgQIECBAgAABAgQIEKgEgfrG5rxmDhs8IIwY0v0Zc3mFOSHQRwI2Aekj6FJ8zTXXXBMOP/zwpGpx5OF9990X6urqSrGq6kSAAAECBAgQIECAAAECBPpFoHAEYO3S6b9VVVX9UhcvJdBdAQHA7sr18nNXXXVVsvtvXFy0vZ/cjUEeeOCBbL4JEyYsc21uvvnmcMABByRlxPX6/vKXv4SVV155mcvxAAECBAgQIECAAAECBAgQSLNAQ1P+CMC6miFpbq62pVRAADBlHRsDifFfIuLPqaee2mbr/vznPyfTjBctWhRWWGGFZORfd4KIbRbuIgECBAgQIECAAAECBAgQSJFAqxGANUNT1DpNqRQBawBWSk//p52PPfZY2H333ZMNRwYPHhzi5iMLFy4MuRuMFJLEEYKjRo0qvOycAAECBAgQIECAAAECBAikXqBwDcDaaiMAU9/pKWygAGAKO7WjJt19993JLsMxTwz87bXXXh1lT+5deeWVYf/99+80nwwECBAgQIAAAQIECBAgQCBtAoVTgGuNAExbF1dEe0wBrohu1kgCBAgQIECAAAECBAgQIECgOwKFU4CtAdgdRc/0t0DV0g0nlvR3Jby/8gTefPPNMH78+KTh06dPD3GacVfTiy++GFpaWsKgQYPCxIkTu/qYfAQIlImAP+Nl0lGqSYAAAQIECBCoEIHtz/9r+N935mRbe/431wu7b9D1v8NmH+yng578/bufquy1RRAwArAIqIokQIAAAQIECBAgQIAAAQIE0iHQ0LQgryG11TYByQNxUhYCAoBl0U0qSYAAAQIECBAgQIAAAQIECPS1wKLFS8LMpua819bW2AQkD8RJWQgIAJZFN6kkAQIE2haoqqoK8efUU09tO4OrBAgQIECAAAECBAh0W2DW3OawNAaYl+psApLn4aQ8BAQAy6Of1JJAvwpMmTIlCTJlgk177rlnp/WJO0dn8neaWQYCBAgQIECAAAECBAiUoEDhDsCxiqNHGAFYgl2lSp0ICAB2AuQ2AQKtBW688cYwbdq01jdcIUCAAAECBAgQIECAQIoE6hvz1/9bfvjgMGSQUEqKurhimuKrrZiu1lACvScQNw8/5ZRTeq9AJREgQIAAAQIECBAgQKAEBRoarf9Xgt2iSt0QEADsBppHCFSyQF1dXdL8P/7xj+Hpp5+uZAptJ0CAAAECBAgQIEAg5QINBSMA6+wAnPIeT2/zBADT27daRqAoAj/4wQ/C0KEfbntvFGBRiBVKgAABAgQIECBAgECJCBSuAWgH4BLpGNVYZgEBwGUm8wCByhYYN25cOPjggxOE22+/PTz++OPdBnnvvffCiSeeGDbYYIMwatSoMGzYsDBhwoSwzz77hIcffrjDcmO+uMlI3Gwkpqeeeio5Xm211ZIAZbyXSVdddVV2Q5LXXnstNDc3h/POOy9svPHGYfnllw9jxowJW265ZbjjjjsyjyS/58yZE37+858n9VtuueWSOm677bbhL3/5S16+9k7efPPNcMIJJ4QNN9wwjB49OmnfKqusEr75zW+GBx54oL3H8q5fd911Sd3i8zU1NeHTn/50Mv161qxZefmcECBAgAABAgQIECDQ+wL1pgD3PqoS+0VgUL+81UsJEChrgRjUmjx5cpg3b144+eSTwz333LPM7fnzn/8c9thjjzB79uy8Z19//fUQf6699tpw2GGHhQsuuCAMGNDxv1Vceuml4fvf/35oaWnJK6utk/i+uItxYeDywQcfDPHnF7/4RfjhD38Y3njjjbDjjjuGf/3rX3nF3HfffUkA8De/+U3Ye++98+7lnlx++eVJnaJRbpo+fXqIP3EjlQMPPDDEug8a1Pp/imNbYj3/8Ic/5D6e1CfWKQYG77333rx7TggQIECAAAECBAgQ6F2BwinAtaYA9y6w0vpMoOO/VfdZNbyIAIFyElhppZXC9773vaTKMZDX2Wi9wrb94x//CLvssksS/Bs8eHA44ogjkhFxTzzxRPjVr34V4ii+mH75y18mI+gKn889f/LJJ8Phhx8e4sjEiy66KDz66KNJfc4888zcbNnjOHoxjhY89NBDkwDa1KlTk2BmbFNMxxxzTHj22WfDV7/61fDKK6+E448/PkyZMiXE9/z3f/93MmIwboISn3/33Xez5eYeXHHFFeGggw5KAqRxxN6FF16Y1CmumRgDejGwGFMMEh533HG5j2aPjzzyyGzwb80110zyxjrEAOQhhxwSXn311WQkYfYBBwQIECBAgAABAgQI9LpA4RTgupohvf4OBRLoC4HWw0764q3eQaDYAosXhzBvZrHfUlrlDx8Tlg6V67M6xcBYDNY1NTUlowDvv//+Lr87BuHiNNyBAweGOI14u+22yz47adKkZGTg5z//+fDcc8+Fc889N+y7777hU5/6VDZP7kHMs+6664a//vWvyRTdzL3NN988c5j3OwYZb7755vCVr3wle32jjTYKm2yySTLVd9GiRWHrrbdOgpNxROBnP/vZbL44ZXjixIlhp512CnF6cByFFwN1uSmO7oujEWPab7/9kuBi7gi/ON05Bhd//OMfhzPOOCMJKsaA3hprrJEt5plnngkXX3xxch6nD8d6xOm/mbTNNtuEzTbbLCk/c81vAgQIECBAgAABAgR6X6BwBGBdzYfroff+m5RIoLgCAoDF9VV6fwnE4N85n+ivt/fPe495OYTqD3fo7YsKjB07Nhl5d/bZZyej9+KadltttVWnr44BuDiSLaY4Si43+Jd5OK53d9lll4UYBFy8NJgbg2FxNGB7Kd6Lawh2JX3jG9/IC/5lnolBxPi+GGyLaxPGAGdu8C+TL47eW3XVVZNpyg899FCrAOD//M//hLlz54aVV1653em9sazTTjstXH311eGtt94KcTrxT3/608wrkudiu2OKDrnBv0ymGBS94YYbwl133ZW55DcBAgQIECBAgAABAr0s0NBqDUABwF4mVlwfCfTdcKE+apDXECDQdwJxuuzIkSOTF5500kldenGcwppJcQ289lIcwbf22msnt3OfKcw/fvz48IUvfKHwcrvncV299tJnPvOZ7K24UUd7KZMvThEuTLfeemtyKU5xjpuatJfiqMBNN900uR2nLeemTHtjUDKOTmwvffvb327vlusECBAgQIAAAQIECPRQYP7CRWHOgvx1xu0C3ENUj/ebgABgv9F7MYHyF6itrU3W74steeSRR7q0GUhcXy+mIUOGJFNuk5N2/pMZgffiiy8mU4bbypYJxrV1r61ruVNtC+/njiLsSr44DTg3ffDBB+Gll15KLsXp0XEn4o5+brrppiTv22+/nS1m/vz52TLidOiOUpy2LBEgQIAAAQIECBAgUByBmU3NrQquswlIKxMXykNAALA8+kktCZSsQNwxNxM4izsCd5ZmzvxwbcYxY8a0uftt7vMrrrhicho33Xj//fdzb2WP43ThZUkjRoxoN3vubsNdyRfXC8xN7W0KkpunreM4ZTiTZs2aFWJ7Y1phhRUyl9v8/bGPfazN6y4SIECAAAECBAgQINBzgcLpv4MGVIXlhltJreeySugPAV9uf6h7Z/EF4oYYcU28Skqxzf2QYvAvBgFj8C+u7xc39dh55507rUkcGddZygTCOsoXNxIplZQbEIw7G3c0xTm3znE0ZCbltrkrRpnn/CZAgAABAgQIECBAoHcF6psW5BUYp//6/9HzSJyUkYAAYBl1lqoug0DcDbcPN8RYhpqlMmsMdsXNLxoaGpJAYNwlt70UR/7FFPO2tLR0OArwnXfeSfLG/yO7rCP9kgf7+D9xSnQmxVF9n/70pzOnXf6d285M+9t7uLP77T3nOgECBAgQIECAAAECnQsUjgCsNf23czQ5SlbAFOCS7RoVI1A+AnEjkLghSEx///vfwy233NJu5TNBsebm5iRvuxmX3ogjCmOaOHFismZgclLC/4k7I3/84x9Pahg38sgdzdfVaseNQ2J7Y8rsltzes53db+851wkQIECAAAECBAgQ6FygobH1CMDOn5KDQGkKCACWZr+oFYGyEzj88MOza9adcsop7Qa/vvSlL2Xbdvnll2ePCw/izrjPPfdccjn3mcJ8pXa+6667JlWKOwRnNvlY1jpm2jtt2rQOg6RXXHHFshYtPwECBAgQIECAAAECXRRoKNgEpK5maBeflI1A6QkIAJZen6gRgbIUqK6uDscdd1xS9xi4uvPOO9tsR9y5NrO77eTJk8O9997bKl/cTfeQQw5JrseNOb73ve+1ylOqF+JIyKFDP/x/DL773e+GqVOndljV6PTMM8/k5Yltz6wtcvDBB4empqa8+/Hkuuuua9e4VWYXCBAgQIAAAQIECBBYZoH6whGA1R+t3b3MhXmAQD8LCAD2cwd4PYE0CcRA3UorrZQ0qb6+vt2mXXbZZcmU3rhpRlwv8KijjgpTpkxJgmW//vWvw4YbbhhiEDGmo48+ultr6bX78iLfWG211cKll16avCXueLz55puHgw46KJkW/fTTTyfTmm+++eZw/PHHh09+8pNJ+9944428Wq233nrhsMMOS67FAOLGG28crrrqqvDUU0+F+++/PwmI7rvvvsn1vAedECBAgAABAgQIECDQawKt1gA0ArDXbBXU9wI2Ael7c28kkFqB4cOHhx/96Efh+9//fodtXH/99cOf/vSnsMcee4TZs2eH8847L/kpfCgGwc4888zCyyV/vv/++4doEUfvxfbFqc7tTXeOIxzj6MnCFE3+/e9/hxgsfOGFF8IBBxyQlyUGGm+88caw+uqr5113QoAAAQIECBAgQIBA7wg0tLELcO+UrBQCfS9gBGDfm3sjgVQLfOc73wnjx4/vtI3bbbddeOmll5KAYQwILrfccsnU2VVWWSXstdde4aGHHgoXXXRRiAGyckzf/OY3w2uvvRbOOuussOWWWybrIw4ePDiMGDEiCdrtsssuSdAz5tlqq61aNTHm/cMf/hCuueaa8IUvfCEsv/zyybNrr712YhZHA8YgoESAAAECBAgQIECAQHEECkcA1tWYAlwcaaX2hUDV0l0ql/TFi7yDQK7Am2++mQ0STZ8+PYwbNy73dofHL774YmhpaQmDBg3K7pba4QNuEiBQVgL+jJdVd6ksAQIECBAgQCCVAjFUsuaJd4fmRYuz7bv1sM3DeuNHZc/L5aAnf/8ulzaqZ+cC5Tm0pvN2yUGAAAECBAgQIECAAAECBAgQ6JbAnAUtecG/WEitEYDdsvRQaQgIAJZGP6gFAQIECBAgQIAAAQIECBAgUCIChdN/Y7Vqq4eWSO1Ug8CyCwgALruZJwgQIECAAAECBAgQIECAAIEUC9Q3LshrXfWQgWH40h+JQLkKCACWa8+pNwECBAgQIECAAAECBAgQIFAUgYaCAGBtjdF/RYFWaJ8JCAD2GbUXESBAgAABAgQIECBAgAABAuUgUN/YnFdN6//lcTgpQwEBwDLsNFUmQIAAAQIECBAgQIAAAQIEiidQuAag9f+KZ63kvhEQAOwbZ28hQIAAAQIECBAgQIAAAQIEykSgoSl/DcA6OwCXSc+pZnsCAoDtybhOgAABAgQIECBAgAABAgQIVKRAqxGAAoAV+R2kqdECgGnqTW0hQIAAAQIECBAgQIAAAQIEeixQuAuwKcA9JlVAPwsIAPZzB3g9AQIECBAgQIAAAQIECBAgUFoCDU02ASmtHlGbngoIAPZU0PMECBAgQIAAAQIECBAgQIBAqgQaGgvXAByaqvZpTOUJCABWXp9rMQECBEpaYMmSJSVdP5UjQIAAAQIECBBIt0DLosXh/bkL8xpZaw3APA8n5ScgAFh+fVbxNR44cGBisGjRorB48eKK9wBAIE0C8c91/Ikp82c9Te3TFgIECBAgQIAAgdIXmDk3f/pvrLE1AEu/39SwYwEBwI593C1BgWHDhiW1iqOEGhsbS7CGqkSAQHcFZs2alX10xIgR2WMHBAgQIECAAAECBPpKoHAH4KqqEEaPGNxXr/ceAkUREAAsCqtCiymw3HLLZYt/++23w+zZs40EzIo4IFB+AjGYP3/+/PDuu+8mP5kWjB49OnPoNwECBAgQIECAAIE+EygMAI4eMSQMGih80mcd4EVFERhUlFIVSqCIAtXV1WH48OFh3rx5yVTBt956K1Qt/ScZ0wWLiK5oAkUUiFN+C9f9W3755cPQoRZaLiK7ogkQIECAAAECBNoRaGjK3wCktnpIOzldJlA+AgKA5dNXavofgRjsW2WVVcIbb7yRBAHj5Rg8aGlpYUSAQAoExo4dG2pra1PQEk0gQIAAAQIECBAoR4H6xvw1AG0AUo69qM6FAgKAhSLOy0JgwIABYdVVVw1NTU1hzpw52dGAZVF5lSRAIE8g/nkeMmRIiKN7a2pqkuO8DE4IECBAgAABAgQI9KFAQ2PBCMAaM1P6kN+riiQgAFgkWMUWXyCOBIzBgvgjESBAgAABAgQIECBAgACB3hAoXAOwzhTg3mBVRj8LWMWynzvA6wkQIECAAAECBAgQIECAAIHSEWi1BqARgKXTOWrSbQEBwG7TeZAAAQIECBAgQIAAAQIECBBIm4A1ANPWo9oTBQQAfQcECBAgQIAAAQIECBAgQIAAgf8ItBoBWG0NQB9H+QsIAJZ/H2oBAQIECBAgQIAAAQIECBAg0EsCrdYArBnSSyUrhkD/CQgA9p+9NxMgQIAAAQIECBAgQIAAAQIlJDC3uSXMbV6UV6NaawDmeTgpTwEBwPLsN7UmQIAAAQIECBAgQIAAAQIEelmgcPRfLL7WCMBeVlZcfwgIAPaHuncSIECAAAECBAgQIECAAAECJSfQ0NScV6chAweEkUMH5V1zQqAcBQQAy7HX1JkAAQIECBAgQIAAAQIECBDodYGGxgV5ZcbRf1VVVXnXnBAoRwEBwHLsNXUmQIAAAQIECBAgQIAAAQIEel2gcAqw6b+9TqzAfhIQAOwneK8lQIAAAQIECBAgQIAAAQIESkugvqlgBGD10NKqoNoQ6KaAAGA34TxGgAABAgQIECBAgAABAgQIpEvACMB09afWfCQgAPiRhSMCBAgQIECAAAECBAgQIECgggUK1wCsqzECsII/h1Q1XQAwVd2pMQQIECBAgAABAgQIECBAgEB3BQp3Aa6tHtLdojxHoKQEBABLqjtUhgABAgQIECBAgAABAgQIEOgvgfrG5rxX1xoBmOfhpHwFBADLt+/UnAABAgQIECBAgAABAgQIEOhFgcIpwHYB7kVcRfWrgABgv/J7OQECBAgQIECAAAECBAgQIFAKAosXLwkzm/JHANbZBbgUukYdekFAALAXEBVBgAABAgQIECBAgAABAgQIlLfA7PkLQ8vSIGBuMgIwV8NxOQsIAJZz76k7AQIECBAgQIAAAQIECBAg0CsChev/xULH2ASkV2wV0v8CAoD93wdqQIAAAQIECBAgQIAAAQIECPSzQOH6fyOHDQrDBg/s51p5PYHeERAA7B1HpRAgQIAAAQIECBAgQIAAAQJlLNBQuP6fHYDLuDdVvVBAALBQxDkBAgQIECBAgAABAgQIECBQcQKFIwBrTf+tuG8gzQ0WAExz72obAQIECBAgQIAAAQIECBAg0CWBwjUAbQDSJTaZykRAALBMOko1CRAgQIAAAQIECBAgQIAAgeIJNDQtyCu81hTgPA8n5S0gAFje/af2BAgQIECAAAECBAgQIECAQC8INDQ255VSZwpwnoeT8hYQACzv/lN7AgQIECBAgAABAgQIECBAoBcECgOARgD2AqoiSkZAALBkukJFCBAgQIAAAQIECBAgQIAAgf4SqG81BXhIf1XFewn0uoAAYK+TKpAAAQIECBAgQIAAAQIECBAoN4FWIwCrh5ZbE9SXQLsCAoDt0rhBgAABAgQIECBAgAABAgQIVIJAc8vi8MG8hXlNrasxAjAPxElZCwgAlnX3qTwBAgQIECBAgAABAgQIECDQU4H35+ZvABLLswZgT1U9X0oCAoCl1BvqQoAAAQIECBAgQIAAAQIECPS5QH3jgrx3DqgKYdTwwezca9IAAEAASURBVHnXnBAoZwEBwHLuPXUnQIAAAQIECBAgQIAAAQIEeixQuP7fmKXr/w2IUUCJQEoEBABT0pGaQYAAAQIECBAgQIAAAQIECHRPoKFgB2Dr/3XP0VOlKyAAWLp9o2YECBAgQIAAAQIECBAgQIBAHwgUjgCstQFIH6h7RV8KCAD2pbZ3ESBAgAABAgQIECBAgAABAiUnUN+YvwlI7dIpwBKBNAkIAKapN7WFAAECBAgQIECAAAECBAgQWGaBhoJNQIwAXGZCD5S4gABgiXeQ6hEgQIAAAQIECBAgQIAAAQLFFWhoyh8BWFdjBGBxxZXe1wICgH0t7n0ECBAgQIAAAQIECBAgQIBASQm0GgFYPaSk6qcyBHoqIADYU0HPEyBAgAABAgQIECBAgAABAmUt0GoNQCMAy7o/Vb61gABgaxNXCBAgQIAAAQIECBAgQIAAgQoRWLJkSWhoWpDXWmsA5nE4SYGAAGAKOlETCBAgQIAAAQIECBAgQIAAge4JzG1eFOYvXJz3cJ1dgPM8nJS/gABg+fehFhAgQIAAAQIECBAgQIAAAQLdFGhozN8AJBZjBGA3MT1WsgICgCXbNfkVO/bYY0NVVVX2Z8qUKfkZunl2ww03hO233z6stNJKYdiwYWHChAlhn332CY899lg3S/QYAQIECBAgQIAAAQIECBAoH4H3GvOn/w4bPCCMGDKwfBqgpgS6IDCoC3lk6WeBf/7zn+H888/v1VrMnz8/7LHHHuH222/PK/f1118P8ef6668Pp556ajjppJPy7jshQIAAAQIECBAgQIAAAQJpEmi9A/DQZPBNmtqoLQSMACzxb2Dx4sXhO9/5TmhpaQkrrLBCr9X2wAMPzAb/ttpqq3DLLbeEJ554Ilx++eXhE5/4RIjvPfnkk8PkyZN77Z0KIkCAAAECBAgQIECAAAECpSbQ0JQ/BbiuZkipVVF9CPRYQACwx4TFLeCCCy4ITz75ZFhrrbVCDNr1RnrwwQeTEX6xrF122SXce++9YbfddguTJk0K3/72t5Ppv6usskryqjj1eNasWb3xWmUQIECAAAECBAgQIECAAIGSE2g1ArBmaMnVUYUI9FRAALCngkV8fvr06dkpuJdcckkYMqR3/hXi5z//eVLrgQMHhosvvjjE37mprq4unH322cml999/PxkVmHvfMQECBAgQIECAAAECBAgQSItAfcEmILXVvfN377T4aEc6BAQAS7gfDz300NDY2Bj222+/sOWWW/ZKTWN5f/nLX5Kytt122zBu3Lg2y/3qV78alltuueTezTff3GYeFwkQIECAAAECBAgQIECAQLkLFE4BrjUCsNy7VP3bEBAAbAOlFC7deOONyRp9Y8aMCeecc06vVSmu87dgwYc7HG2xxRbtlhtHG37uc59L7sdnFi5c2G5eNwgQIECAAAECBAgQIECAQLkKFE4BtgZgufakenckIADYkU4/3Ytr7v3gBz9I3h6n4o4dO7bXavL8889ny4rrCnaUMvfjBiQvvvhiR1ndI0CAAAECBAgQIECAAAECZSnQUDgF2CYgZdmPKt2xwKCOb7vbHwJx44233347bLbZZr228UemHXFdwUxqb/pv5v748eMzhyE+t84662TPOzt48803O8wyY8aMDu+7SYAAAQIECBAgQIAAAQIE+kKgoenDWXKZd9VW2wQkY+F3egQEAEusLx9++OEwefLkMGjQoHDppZeGqqqqXq3hnDlzsuXV1NRkj9s6qK6uzl6OawcuS8oNHi7Lc/ISIECAAAECBAgQIECAAIG+Eli0eEmY2dSc97paIwDzPJykQ8AU4BLqx+bm5nDwwQeHJUuWhCOPPDKsu+66vV67+fPnZ8vsbFfhoUM/+lePefPmZZ9zQIAAAQIECBAgQIAAAQIE0iAwa25zWBoDzEt1NgHJ83CSDgEjAEuoH88444wQ1+hbZZVVwimnnFKUmg0bNixbbgw4dpQym4XEPMOHD+8oa6t7uVONW91ceiFOAd5kk03auuUaAQIECBAgQIAAAQIECBDoE4HCHYDjS0ePGNIn7/YSAn0pIADYl9odvOuFF14IZ555ZpLjwgsvDLnTbzt4bJlvjRw5MvtMZ9N6m5qasnk7my6czfifg87WFyzM75wAAQIECBAgQIAAAQIECPS1QH1j/vp/yw8fHIYMMlmyr/vB+4ovIABYfOMuveH8888PcUTe6quvHubOnRtuuOGGVs89++yz2Wv3339/slFIvLDLLrt0OWCYG5iLG3VsvPHG2TILD3JH8VnTr1DHOQECBAgQIECAAAECBAiUu4AdgMu9B9W/qwICgF2VKnK+zHTbV155JXzrW9/q9G2nn356Ns+rr77a5QBg7k6+cdRhRylzP25I8slPfrKjrO4RIECAAAECBAgQIECAAIGyE2goGAFYZwfgsutDFe6agHGtXXNKTa5JkyaFzOYfDz74YLvtiqMRH3vsseR+7jPtPuAGAQIECBAgQIAAAQIECBAoM4HCNQDtAFxmHai6XRYQAOwyVXEzXnXVVcnuv3EH4PZ+cjcGeeCBB7L5JkyY0OXKxTUAt9lmmyT/fffdF+I04LbSzTffHGbPnp3c2n333dvK4hoBAgQIECBAgAABAgQIEChrgfrG/M0xBQDLujtVvgMBAcAOcMrxVgwkVlVVJT+nnnpqm004+uijk+stLS3hsMMOC4sWLcrLV19fH4477rjk2qhRo8JBBx2Ud98JAQIECBAgQIAAAQIECBBIg0DhFOBaU4DT0K3a0IaAAGAbKGm/tPXWW4c999wzaeZtt90Wtt122xB/T506NVx55ZXhc5/7XHjjjTeS+2eddVYYPXp02km0jwABAgQIECBAgAABAgQqUKBwCnBdzZAKVNDkShAYVAmN1MbWAldccUUyxffOO+8McTpx/MlNAwYMCCeddFI45JBDci87JkCAAAECBAgQIECAAAECqRFoNQKwZmhq2qYhBHIFjADM1aig4+HDh4c77rgjXHfddckIwBVWWCHZHGT8+PHhv/7rv8LDDz8c2ptCXEFMmkqAAAECBAgQIECAAAECKRZoKFwDsNoIwBR3d0U3rWrphhNLKlpA4/tFIG4+EoONMU2fPj2MGzeuX+rhpQQIECBAgAABAgQIECBQmQLzFy4Ka510d17j7/vhFuGTK9TkXSv3E3//Lvce7J36GwHYO45KIUCAAAECBAgQIECAAAECBMpIYGZT/g7AserWACyjDlTVZRIQAFwmLpkJECBAgAABAgQIECBAgACBNAgUTv8dNKAqLDdscBqapg0EWgkIALYicYEAAQIECBAgQIAAAQIECBBIu0B904K8Jo5Zuv7fgKVBQIlAGgUEANPYq9pEgAABAgQIECBAgAABAgQIdChQOAKw1g7AHXq5Wd4CAoDl3X9qT4AAAQIECBAgQIAAAQIECHRDoKExfwSg9f+6geiRshEQACybrlJRAgQIECBAgAABAgQIECBAoLcEGgo2AaldOgVYIpBWAQHAtPasdhEgQIAAAQIECBAgQIAAAQLtCtS3GgE4tN28bhAodwEBwHLvQfUnQIAAAQIECBAgQIAAAQIEllnAGoDLTOaBMhYQACzjzlN1AgQIECBAgAABAgQIECBAoHsCDQW7ANfWmALcPUlPlYOAAGA59JI6EiBAgAABAgQIECBAgAABAr0qUDgC0CYgvcqrsBITEAAssQ5RHQIECBAgQIAAAQIECBAgQKC4AkuWLAmFAcDaamsAFldd6f0pIADYn/reTYAAAQIECBAgQIAAAQIECPS5wJwFLaF50eK895oCnMfhJGUCAoAp61DNIUCAAAECBAgQIECAAAECBDoWKBz9F3MbAdixmbvlLSAAWN79p/YECBAgQIAAAQIECBAgQIDAMgo0NC7Ie6J6yMAwfOmPRCCtAgKAae1Z7SJAgAABAgQIECBAgAABAgTaFKhvbM67Xltj/b88ECepExAATF2XahABAgQIECBAgAABAgQIECDQkUBDU/4IQOv/daTlXhoEBADT0IvaQIAAAQIECBAgQIAAAQIECHRZoHANQOv/dZlOxjIVEAAs045TbQIECBAgQIAAAQIECBAgQKB7AoVrANbVDOleQZ4iUCYCAoBl0lGqSYAAAQIECBAgQIAAAQIECPSOQH1T4RqAAoC9I6uUUhUQACzVnlEvAgQIECBAgAABAgQIECBAoCgChSMATQEuCrNCS0hAALCEOkNVCBAgQIAAAQIECBAgQIAAgeILtFoD0BTg4qN7Q78KCAD2K7+XEyBAgAABAgQIECBAgAABAn0t0FAwBbiuZmhfV8H7CPSpgABgn3J7GQECBAgQIECAAAECBAgQINCfAi2LFof351oDsD/7wLv7XkAAsO/NvZEAAQIECBAgQIAAAQIECBDoJ4H35y4MS5bkv9wagPkeztInIACYvj7VIgIECBAgQIAAAQIECBAgQKAdgYamBXl3qqpCGD1icN41JwTSJiAAmLYe1R4CBAgQIECAAAECBAgQIECgXYHCDUBGjxgSBg0UHmkXzI1UCPjCU9GNGkGAAAECBAgQIECAAAECBAh0RaC+MX8EYG31kK48Jg+BshYQACzr7lN5AgQIECBAgAABAgQIECBAYFkECkcA1tYIAC6Ln7zlKSAAWJ79ptYECBAgQIAAAQIECBAgQIBANwQK1wCsrRnajVI8QqC8BAQAy6u/1JYAAQIECBAgQIAAAQIECBDogUDhCMA6U4B7oOnRchEQACyXnlJPAgQIECBAgAABAgQIECBAoMcC9Y3NeWUYAZjH4SSlAgKAKe1YzSJAgAABAgQIECBAgAABAgRaC7SeAmwNwNZKrqRNQAAwbT2qPQQIECBAgAABAgQIECBAgEC7AoVTgGurrQHYLpYbqREQAExNV2oIAQIECBAgQIAAAQIECBAg0JlAQ+OCvCx1dgHO83CSTgEBwHT2q1YRIECAAAECBAgQIECAAAECBQLzmheFpqU/uckagLkajtMqIACY1p7VLgIECBAgQIAAAQIECBAgQCBPoHD9v3iz1gjAPCMn6RQQAExnv2oVAQIECBAgQIAAAQIECBAgUCBQuP7fkIEDwsihgwpyOSWQPgEBwPT1qRYRIECAAAECBAgQIECAAAECbQjUF6z/F0f/VVVVtZHTJQLpEhAATFd/ag0BAgQIECBAgAABAgQIECDQjkDhCEDTf9uBcjl1AgKAqetSDSJAgAABAgQIECBAgAABAgTaEqhvyt8BuLZ6aFvZXCOQOgEBwNR1qQYRIECAAAECBAgQIECAAAECbQkYAdiWimuVICAAWAm9rI0ECBAgQIAAAQIECBAgQIBAaChYA7CuxghAn0VlCAgAVkY/ayUBAgQIECBAgAABAgQIEKh4gYam5jyD2uoheedOCKRVQAAwrT2rXQQIECBAgAABAgQIECBAgECeQH1jQQDQCMA8HyfpFRAATG/fahkBAgQIECBAgAABAgQIECCQI1A4BdguwDk4DlMtIACY6u7VOAIECBAgQIAAAQIECBAgQCAKLF68JMwsmAJcZxdgH0eFCAgAVkhHayYBAgQIECBAgAABAgQIEKhkgdnzF4aWpUHA3GQEYK6G4zQLCACmuXe1jQABAgQIECBAgAABAgQIEEgECtf/ixfH2ATE11EhAgKAFdLRmkmAAAECBAgQIECAAAECBCpZoHD9v5FDB4VhgwdWMom2V5CAAGAFdbamEiBAgAABAgQIECBAgACBShVoKFj/z/TfSv0SKrPdAoCV2e9aTYAAAQIECBAgQIAAAQIEKkqgcARgbc3Qimq/xla2gABgZfe/1hMgQIAAAQIECBAgQIAAgYoQKFwDsNb6fxXR7xr5oYAAoC+BAAECBAgQIECAAAECBAgQSL1AQ9OCvDYaAZjH4STlAgKAKe9gzSNAgAABAgQIECBAgAABAgRCaGhszmOoqxmSd+6EQJoFBADT3LvaRoAAAQIECBAgQIAAAQIECCQChQFAU4B9GJUkIABYSb2trQQIECBAgAABAgQIECBAoEIF6k0BrtCe1+woIADoOyBAgAABAgQIECBAgAABAgRSL9BqBKApwKnvcw38SEAA8CMLRwQIECBAgAABAgQIECBAgEAKBZpbFocP5i3Ma9nYmqF5504IpFlAADDNvattBAgQIECAAAECBAgQIECAQHh/bv4GIJHELsA+jEoSEACspN7WVgIECBAgQIAAAQIECBAgUIEC9Y0L8lo9oCqEUcMH511zQiDNAgKAae5dbSNAgAABAgQIECBAgAABAgRC4fp/Y6qHhgExCigRqBABAcAK6WjNJECAAAECBAgQIECAAAEClSrQULADcJ0NQCr1U6jYdgsAVmzXazgBAgQIECBAgAABAgQIEKgMgcIRgLUCgJXR8VqZFRAAzFI4IECAAAECBAgQIECAAAECBNIoUN+YvwlI7dIpwBKBShIQAKyk3tZWAgQIECBAgAABAgQIECBQgQINBZuAGAFYgR9BhTdZALDCPwDNJ0CAAAECBAgQIECAAAECaRdoaMofAVhXYwRg2vtc+/IFBADzPZwRIECAAAECBAgQIECAAAECKRNoNQKwekjKWqg5BDoWEADs2MddAgQIECBAgAABAgQIECBAoMwFWq0BaARgmfeo6i+rgADgsorJT4AAAQIECBAgQIAAAQIECJSNwJIlS0JD04K8+loDMI/DSQUICABWQCdrIgECBAgQIECAAAECBAgQqFSBuc2LwvyFi/OaX2cX4DwPJ+kXEABMfx9rIQECBAgQIECAAAECBAgQqFiBhsb8DUAihBGAFfs5VGzDBQArtus1nAABAgQIECBAgAABAgQIpF+gvmD677DBA8KIIQPT33AtJJAjIACYg+GQAAECBAgQIECAAAECBAgQSJdA4QjA2qXTf6uqqtLVSK0h0ImAAGAnQG4TIECAAAECBAgQIECAAAEC5SvQ0Ji/AUhdzZDybYyaE+imgABgN+E8RoAAAQIECBAgQIAAAQIECJS+QENT/hqAtTVDS7/SakiglwUEAHsZVHEECBAgQIAAAQIECBAgQIBA6QjUF4wArK02ArB0ekdN+kpAALCvpL2HAAECBAgQIECAAAECBAgQ6HOBVmsAGgHY533ghf0vIADY/32gBgQIECBAgAABAgQIECBAgECRBBoKdgG2BmCRoBVb0gICgCXdPSpHgAABAgQIECBAgAABAgQI9ESg9QhAU4B74unZ8hQQACzPflNrAgQIECBAgAABAgQIECBAoAsC9Y0Fm4BU2wSkC2yypExAADBlHao5BAgQIECAAAECBAgQIECAwIcCixcvCTMLpgDX1hgB6PuoPAEBwMrrcy0mQIAAAQIECBAgQIAAAQIVITBr3sKwNAaYl+psApLn4aQyBAQAK6OftZIAAQIECBAgQIAAAQIECFScQEPjglZtHj3CCMBWKC6kXkAAMPVdrIEECBAgQIAAAQIECBAgQKAyBQrX/1t++OAwZJBQSGV+DZXd6kGV3fzSaf3s2bPDnXfeGZ588skwderU8NZbb4X33nsvzJs3L4waNSqss846YccddwwHHnhgqK2t7XHFX3/99XDJJZeEe++9N7z88suhqakpjBw5Mqy11lphhx12CN/97nfD2LFje/weBRAgQIAAAQIECBAgQIAAgf4SaLD+X3/Re2+JCVQtWZpKrE4VWZ377rsvbLvttp22va6uLlx77bVh++237zRvexmuv/768J3vfCfMnTu3vSxJkPHGG28MW2+9dbt5enLjzTffDOPHj0+KmD59ehg3blxPivMsAQIECBAgQIAAAQIECBBoJXD1314Lp9z2r+z1TSaMCTd+d9PseSUc+Pt3JfRy5200ArBzoz7LEQNiW221Vdhoo42S4NhKK60UFi9eHOIf1ptuuincfPPNob6+Puy6667JSMHPfOYzy1y3Rx99NOy7775h0aJFYcCAAWG//fYLu+22W1h55ZXDG2+8Ea6++urwpz/9KTQ0NCTvefbZZ8OECROW+T0eIECAAAECBAgQIECAAAEC/S1QuAagHYD7u0e8v78EBAD7S77gvTHwFwNw7aVvfOMb4ZZbbgm77757aG5uDqeddlr4wx/+0F72dq+fccYZSfAvZrjwwgvDoYcems07adKk8LWvfS0cddRR4bzzzkumBcffF1xwQTaPAwIECBAgQIAAAQIECBAgUC4C9U3NeVUVAMzjcFJBAla+LJHOHjhwYKc1+cpXvpKs0Rcz/vWvf+00f1sZHnnkkeRyXEcwN/iXm/fkk0/Onv7tb3/LHjsgQIAAAQIECBAgQIAAAQLlJNBqBGD10HKqvroS6DUBAcCllA888EAyLXbixInJRhiDBg0Kzz33XB7yQw89FC6++OJk/b28G318Ul1dnbxx/vz53XpzHD0Y02qrrdbu88svv3yIaw3GtGBB6y3T233QDQIECBAgQIAAAQIECBAgUEICDY35IwDraoaUUO1UhUDfCVT0FOC4CUZcAy+urRdTZj+UqqqqVj0QR+gdfvjhId777Gc/G2KwsK/T888/H/7xj38kr4279XYnrbHGGuHvf/97ePXVV9t9PO5IHNcajCnmlwgQIECAAAECBAgQIECAQDkKNLSaAmwEYDn2ozr3XKCiRwB+85vfTIJ/MfAX1787+uij2xXdbLPNwrrrrpvc787ae+0W3MmNGKR88cUXkzX54jqBcfOOmH7wgx908mTbtw855JDkRtzk49JLL20z0+mnn569nsmfveCAAAECBAgQIECAAAECBAiUiUB9Y/6sttpqIwDLpOtUs5cFKnYE4B//+Mdwxx13JCP6LrvssnDQQQcltOeee267xF/96lfDtGnTwoMPPhiOP/74dvP19MZVV10VDjjggHaLiYHKvfbaq937Hd2I7YzTma+77rpw2GGHhaeeeirZ7TfuOBw3Ibn22mtDtInpuOOOC9ttt11HxbV7L+5c3FGaMWNGR7fdI0CAAAECBAgQIECAAAECPRJY0LIozJnfkldGbY0RgHkgTipGoGIDgFdffXXSyXvvvXc2+NdZr2+00UZJljgVtz/S+uuvn4zai1OQu5viVOYY5Nt1113DWWedFSZPnpz85JYXRxrGAGd3g3+xrPHjx+cW6ZgAAQIECBAgQIAAAQIECPSpwMyC6b/x5dYA7NMu8LISEqjYKcBPPvlkMvovTgPuaoqj5GJ67733uvpIt/LF3X7jSMP488QTT4Tf/va3Yffdd0/W/4sj/26//fZulZt56IUXXgjXX399Un7mWu7vRx99NPzmN78JRunlqjgmQIAAAQIECBAgQIAAgXISKNwAZNCAqrDcsMHl1AR1JdBrAhUbAIxr4MX08Y9/fJkxFy9evMzPLMsDo0aNCp/+9KeTn7g24Z577pmsVRiDcq+88krYbbfdQpwm3J0Up/9uuumm4dZbb03afs0114S33347xN2Bp0+fHn75y1+G4cOHJ1OEN9lkk9Dd0Y6xrI5+YmBTIkCAAAECBAgQIECAAAECxRIoXP9vzNL1/wYsDQJKBCpRoGKnAI8cOTLMnDkzxB1vu5pefvnlJGttbW1XH+nVfPvss08y+u/GG29MdiSOgcDRo0d3+R0LFiwI3/rWt8KsWbPCiiuuGB577LHkd6aAcePGhUMPPTRsscUWYeONNw5xHb999903xNGSy5piWRIBAgQIECBAgAABAgQIEOgvgfrG5rxXW/8vj8NJhQlU7AjAiRMnJl29LCPRMrv/rrfeev32mcSgX0xNTU3hrrvuWqZ63H333eGtt95Knvn+97+fF/zLLehTn/pUiGsjxjR16tTwz3/+M/e2YwIECBAgQIAAAQIECBAgUPICDQU7AFv/r+S7TAWLKFCxAcAdd9wxLFmyJFx88cVh/vz5nRLH4FkMAFZVVYWdd9650/zFyjB27Nhs0a+//nr2uCsHudN5N9xwww4fyWx4EjPFNQMlAgQIECBAgAABAgQIECBQTgINBZuA1C6dAiwRqFSBig0AHn744SGutffaa6+Fr371qyGzJmDhhxCDg7/4xS+SPHHtvzh19oADDijM1mfnmRF88YU1NTXL9N5Bgz6a8d3Skr8VemFBCxcuzF7KfS570QEBAgQIECBAgAABAgQIEChhgcI1AE0BLuHOUrWiC1RsADAG/6699tqlC4AOCPfcc09YZZVVQhwVmEmnn3562GGHHcIKK6wQjj322GSU4ODBg5PNMYYNG5bJ1ue/f//732ffue6662aPu3Kw2mqrZbPFzUA6Sg8++GD2du5z2YsOCBAgQIAAAQIECBAgQIBACQsU7gJcW2MEYAl3l6oVWaBiA4DRNQb87rzzzhCn1c6bNy/Eab5xim9McaONP//5z6GxsTGZKlxXV5fk3XLLLZP7vf2fuKtvZ1ORzz///KQO8d0TJkwIn//85/OqMWXKlKT+sQ37779/3r14ss0224QRI0Yk1y+55JIwbdq0Vnnihbi24B//+MfkXtwlef31128zn4sECBAgQIAAAQIECBAgQKBUBRqaFuRVra56aN65EwKVJPDRnNBKanVOW/8/e/cBHlWVNnD8TQ9JaEkglITeRHoVEFBU1BVd0V0UFLGuHVDcb131s6zu6qKroliQVVgL+okigoorICiggqggHaR3SEJJb+Q75+KMuXdmUifT7v8+z5Bbzr333N8ZAvPOOee94IILZMeOHTJjxgz5+OOPjaQXOkuuXnSwrGfPnnLZZZfJbbfdJjpzcG0tjz76qEyaNEmuvPJKI7DXtm1bY4hvVlaWEah75513ZMWKFcbto6OjZfr06VLVobm61+P9998vDz/8sOjrDhw4UHQyEG2gswkfPnzYMNDX1sOd9fLUU08ZvSSNDf5AAAEEEEAAAQQQQAABBBBAIEgE6AEYJA1FNX0iYPsAoFbWgb4777zTeOltPT9eSUmJxMT49tuBzMxMI7CnA3CeltTUVHnjjTfk/PPP91Sk3P0PPfSQ6PtMmTLF6N345JNPin5ZFz3c+R//+IczG7D1ONsIIIAAAggggAACCCCAAAIIBKqATvrpGgD07Wf8QLWhXvYUIADopt11z7qq9q5zc5kq7Vq8eLEsWrRIlixZIjpbr+6NpxOT6PkGU1JSjGG4OvvwqFGjnMN4q3SDXwvr4cF6KPG1114r//73v2X58uWiswnn5uYaPQ7btWsnQ4cOlVtvvVU6dOhQnVtwDgIIIIAAAggggAACCCCAAAJ+FcgqKJbCktMj2xwVIQuwQ4KfdhQgABggra6H/OqXDrxVd9HzE+pvOSqz9O7dW/SLBQEEEEAAAQQQQAABBBBAAIFQE7D2/tPPRxKQUGtlnqcqArZOAlIVKMoigAACCCCAAAIIIIAAAggggEBwCGRkmxOAxEVHSFw0faCCo/WoZW0I2D4AqIfb3nPPPdKnTx9JTEwUPfddREREuS9fDw+ujYbnmggggAACCCCAAAIIIIAAAgiEqkB6dqHp0ej9Z+Jgw4YCtg5/6wy3OiOuTvhR2aGzNnyP8MgIIIAAAggggAACCCCAAAIIBJVARo65B2ByAglAgqoBqazXBWwbAJw9e7Y88MADBmh4eLgMHjxYunfvLg0aNBC9zYIAAggggAACCCCAAAIIIIAAAsEpYJ0DMCmeAGBwtiS19paAbQOAU6ZMMQybN28un332mXTt2tVbplwHAQQQQAABBBBAAAEEEEAAAQT8KGCdAzA5IdqPteHWCPhfwLZd3X7++WcJCwuTxx9/nOCf/9+H1AABBBBAAAEEEEAAAQQQQAABrwmk5zAHoNcwuVBICNg2AKiTfeilR48eIdGQPAQCCCCAAAIIIIAAAggggAACCJwWsPYAZAgw7wy7C9g2ANihQwej7TMyMuz+HuD5EUAAAQQQQAABBBBAAAEEEAgpAZc5ABkCHFLty8NUXcC2AcBx48YZmX/nzp1bdTXOQAABBBBAAAEEEEAAAQQQQACBgBXIsAwBJgtwwDYVFfORgG0DgDfddJOR+fe1116T+fPn+4ib2yCAAAIIIIAAAggggAACCCCAQG0KFJeckmO5zAFYm8ZcO/gEbJsFWM8B+PHHH4vuCThy5Ei5+uqrZdSoUaKHBsfFxVXYki1atKiwDAUQQAABBBBAAAEEEEAAAQQQQMC3Asdyi9SIP/M9mQPQ7MGW/QRsGwDUTd2gQQMZP368fPfdd/Luu+8ar8q8BXT24OLi4soUpQwCCCCAAAIIIIAAAggggAACCPhQICOnwHQ39RFeGsadTgRqOsAGAjYSsO0QYN3GEydOlOHDh0t6eroxH2Cp+oqgsi8bvUd4VAQQQAABBBBAAAEEEEAAAQSCRsCaAKRhXLRERtg6/BE0bUdFa0/Atj0A3377bXnhhRcM2Xr16hnDgLt162b0CgwP5xdD7b3luDICCCCAAAIIIIAAAggggAACtSeQnm3uAZgUH117N+PKCASJgG0DgC+++KLRRJ06dZIlS5ZISkpKkDQZ1UQAAQQQQAABBBBAAAEEEEAAAU8C1h6ASQkEAD1Zsd8+Arbt6rZ582bRc/k9+uijBP/s837nSRFAAAEEEEAAAQQQQAABBEJcwDoHYFJCTIg/MY+HQMUCtg0A6izAetFZf1kQQAABBBBAAAEEEEAAAQQQQCA0BKw9AJMZAhwaDctT1EjAtgFAPfRXL4cOHaoRICcjgAACCCCAAAIIIIAAAggggEDgCKRnF5oqQw9AEwcbNhWwbQDwhhtuMDL+vvvuuzZteh4bAQQQQAABBBBAAAEEEEAAgdATcB0CzByAodfKPFFVBWwbALzppptkxIgRorMBT506tapulEcAAQQQQAABBBBAAAEEEEAAgQAUsA4BTopnDsAAbCaq5GMB22YB/vrrr2X8+PFy9OhRmTBhgsyaNUuuvvpqY07AuLi4CpthyJAhFZahAAIIIIAAAggggAACCCCAAAII+FYgI7vAdMNksgCbPNiwp4BtA4DnnHOOkQXY0ewrV64U/arMorMHFxcXV6YoZRBAAAEEEEAAAQQQQAABBBBAwEcCeYUlkqNeZRfmACyrwbpdBWwbANQNXlpaatd257kRQAABBBBAAAEEEEAAAQQQCDkB6/x/+gGT6AEYcu3MA1VdwLYBwCVLllRdizMQQAABBBBAAAEEEEAAAQQQQCBgBazz/0VHhEvdGNuGPgK2naiY7wVs+7dg6NChvtfmjggggAACCCCAAAIIIIAAAgggUGsC1h6AuvefnsaLBQG7C9g2C7DdG57nRwABBBBAAAEEEEAAAQQQQCDUBNKzC02PxPBfEwcbNhYgAGjjxufREUAAAQQQQAABBBBAAAEEEAglAesQ4KT4mFB6PJ4FgWoLEACsNh0nIoAAAggggAACCCCAAAIIIIBAIAlkZBeYqkMPQBMHGzYWsO0cgGXbfPv27TJv3jxZu3atpKenS15eXrkZgvX8AYsXLy57CdYRQAABBBBAAAEEEEAAAQQQQMDPAhk55iHAyQn0APRzk3D7ABGwdQAwNzdX7rzzTnnrrbdcAn6lpaUuE4XqfXphAtEAefdSDQQQQAABBBBAAAEEEEAAAQTKCKRbewDGR5c5yioC9hWwbQBQB/NGjhwpixYtMoJ/ycnJkpqaKmvWrDECfIMHD5Zjx47Jli1bpKioyNjXsWNHadKkiX3fLTw5AggggAACCCCAAAIIIIAAAgEs4DIHID0AA7i1qJovBWw7B+Ds2bNl4cKFhvUjjzwihw4dkjfffNNp/9VXX8nPP/8smZmZ8txzz0l8fLyx/vjjj8uSJUuc5VhBAAEEEEAAAQQQQAABBBBAAIHAEMjIYQ7AwGgJahFoArYNAM6aNctoiwEDBogOAIaHh7sd2qsDfxMmTDDm/MvKypIrrrhCDhw4EGjtSH0QQAABBBBAAAEEEEAAAQQQsLWAHuln7QGYTBZgW78nePjfBGwbAFy9erUR8Lvlllt+0yhnrW/fvnL77bcbSUJeeOGFckpyCAEEEEAAAQQQQAABBBBAAAEEfC1wMq9Yik+dnrvfcW+yADsk+Gl3AdsGAHW2X720adPG+R6IiopyrutMwNblkksuMXZ98skn1kNsI4AAAggggAACCCCAAAIIIICAHwXSLcN/dVUSSQLixxbh1oEkYNsAYGTk6fwndevWdbZH2XU9J6B1qV+/vrFr79691kNsI4AAAggggAACCCCAAAIIIICAHwWsw3/rxkRKbFSEH2vErREIHAHbBgCbNWtmtMLRo0edraEz/NapU8fY/vHHH537HSu//PKLsVpcXOzYxU8EEEAAAQQQQAABBBBAAAEEEAgAgYxsEoAEQDNQhQAVsG0AsHv37kaTrFu3ztk0YWFh0r9/f2P75Zdfdu7XKzrop7MB66V9+/bGT/5AAAEEEEAAAQQQQAABBBBAAIHAEEjPKTRVJCkhxrTNBgJ2FrBtAHDYsGGiMwR9/vnnpva/8cYbjf1Lly6VoUOHyksvvSRPP/20ERhctWqVkThk1KhRpnPYQAABBBBAAAEEEEAAAQQQQAAB/wq49ABk/j//Ngh3DygB2wYAR44caQTzlixZIjt27HA2yrXXXisXXXSREQRcvny5jB8/Xu6//35Zs2aNUaZHjx5y7733OsuzggACCCCAAAIIIIAAAggggAAC/hewzgFID0D/twk1CBwB2wYA9Xx/RUVFkp+fb8oErJvmo48+kgcffFBSUlKMQKDuKagTgNx5552iA4axsbGB04LUBAEEEEAAAQQQQAABBBBAAAEEJMOSBTg5IRoVBBD4VeB0KlybcoSHu49/xsTEyOOPP268MjMzjfn/GjVqZPQYtCkVj40AAggggAACCCCAAAIIIIBAQAukZ1vmAGQIcEC3F5XzrYBtA4B79uwxpBMSEiQxMdGjennHPJ7EAQQQQAABBBBAAAEEEEAAAQQQ8KmAyxyAJAHxqT83C2wB913gArvOXqldq1atpHXr1vLee+955XpcBAEEEEAAAQQQQAABBBBAAAEE/CeQ4ZIFmCHA/msN7hxoArYNANapU8doi759+wZam1AfBBBAAAEEEEAAAQQQQAABBBCogkBRySk5nltkOiOZHoAmDzbsLWDbAGDz5s2Nli8pKbH3O4CnRwABBBBAAAEEEEAAAQQQQCDIBY5Zev/px0liDsAgb1Wq700B2wYAhw8fbjguX77cm55cCwEEEEAAAQQQQAABBBBAAAEEfCxgTQASHibSII4hwD5uBm4XwAK2DQBOmDBB9DDgZ555Rvbv3x/ATUTVEEAAAQQQQAABBBBAAAEEEECgPIGMnALT4UTV+y9CRwFZEEDAELBtALB9+/Yya9Ysyc3NlbPOOstYLyw0pwznPYIAAggggAACCCCAAAIIIIAAAoEvkJ5tDgAmxccEfqWpIQI+FIj04b0C6lbDhg0z6tOoUSPZuXOnjB07Vm666SbRgcGGDRtKRESEx/qGhYXJ4sWLPR7nAAIIIIAAAggggAACCCCAAAII+E4gI9vcoScpgeG/vtPnTsEgYNsA4NKlS0UH8hxLaWmpFBQUyPr16x27XH7q8rpc2fNcCrEDAQQQQAABBBBAAAEEEEAAAQR8KmCdAzCJDMA+9edmgS9g2wDgkCFDCOQF/vuTGiKAAAIIIIAAAggggAACCCBQoUCGyxBgegBWiEYBWwnYNgCoewCyIIAAAggggAACCCCAAAIIIIBA8Atk5JiHACczBDj4G5Un8KpAyAcA582bZ4Cdd955Eh8f71U8LoYAAggggAACCCCAAAIIIIAAAv4XsPYATGYIsP8bhRoElEDIZwG+/PLL5YorrpDdu3eb4G+88UbRr4MHD5r2s4EAAggggAACCCCAAAIIIIAAAsElwByAwdVe1Nb3AiEfANSkOnGHdZk5c6b85z//kWPHjlkPsY0AAggggAACCCCAAAIIIIAAAkEioD/zZ+QUmGpLFmATBxsISMgHAGNiYoxmzs7OprkRQAABBBBAAAEEEEAAAQQQQCDEBHILSyS/6JTpqZLjT8cCTDvZQMDGAiEfAGzevLnRvMuWLbNxM/PoCCCAAAIIIIAAAggggAACCISmQEa2OQGIfkp6AIZmW/NU1RcI+SQgOvnH9OnT5YEHHpBVq1ZJhw4dJCoqyin28ssvS+PGjZ3blV15+OGHK1uUcggggAACCCCAAAIIIIAAAgggUEsC6Zbhv7FR4RIXHVFLd+OyCASnQJgaK+86QV5wPovbWu/du1d69eolGRkZEhYW5izjeOyy+5wHK7FSUlJSiVIU8SSwb98+SUtLMw7rNkpNTfVUlP0IIIAAAggggAACCCCAAAIIeBRYuPGw3PLmaufx5g3qyIr7hzm37b7C52+7vwNOP3/IDwHWQaYff/xRbr75ZmnVqpXR+08H/xyBP71enRdvHwQQQAABBBBAAAEEEEAAAQQQ8L9ARrY5AUhyQrT/K0UNEAgwgZAfAqy9dRDwtddeM9GHh4cbQcB169ZJ586dTcfYQAABBBBAAAEEEEAAAQQQQACB4BDIyDHPAZiUQAKQ4Gg5aulLgZDvAehLTO6FAAIIIIAAAggggAACCCCAAAK+FUi39ABMiqcHoG9bgLsFg4AtegC6a4gZM2YYu5l7zp0O+xBAAAEEEEAAAQQQQAABBBAIDgFrFmB6AAZHu1FL3wrYNgA4btw430pzNwQQQAABBBBAAAEEEEAAAQQQ8LpAhiULMHMAep2YC4aAAEOAQ6AReQQEEEAAAQQQQAABBBBAAAEE7Crg2gOQIcB2fS/w3J4FCAB6tuEIAggggAACCCCAAAIIIIAAAggEuEB6tiUJSDxJQAK8yaieHwQIAPoBnVsigAACCCCAAAIIIIAAAggggEDNBU6dKpVMyxDgpAR6ANZcliuEmgABwFBrUZ4HAQQQQAABBBBAAAEEEEAAAZsIHM8rEhUDNC3JCfQANIGwgYASIADI2wABBBBAAAEEEEAAAQQQQAABBIJSICO7wKXeDePoAeiCwg7bCxAAtP1bAAAEEEAAAQQQQAABBBBAAAEEglPAOv9f/TpREh1JqCM4W5Na16YAfytqU5drI4AAAggggAACCCCAAAIIIIBArQlkMP9frdly4dASIAAYWu3J0yCAAAIIIIAAAggggAACCCBgG4EMSwbgZDIA26btedCqCRAArJoXpRFAAAEEEEAAAQQQQAABBBBAIEAErHMAkgE4QBqGagScAAHAgGsSKoQAAggggAACCCCAAAIIIIAAApURSM8pNBUjAGjiYAMBp0Ckc82mK8XFxfLpp5/KsmXLZMeOHZKVlSUlJSXlaoSFhcnixYvLLcNBBBBAAAEEEEAAAQQQQAABBBCoXQGXHoAMAa5dcK4etAK2DgAuX75cxo4dK3v27HE2YGlpqXPduqIDf/q4/smCAAIIIIAAAggggAACCCCAAAL+FXCZAzAh2r8V4u4IBKiAbQOAmzdvlosuukjy8vKMoF50dLS0b99eEhMTJTyckdEB+n6lWggggAACCCCAAAIIIIAAAgg4BTJchgDHOI+xggACvwnYNgD4j3/8Q3JzcyUiIkIee+wxGT9+vCQkJPwmwxoCCCCAAAIIIIAAAggggAACCAS0QHp2gal+SfH0ADSBsIHArwK2DQB++eWXxlDeCRMmyAMPPMAbAgEEEEAAAQQQQAABBBBAAAEEgkigoLhEsvKLTTVOSqAHoAmEDQR+FbDtWNf09HSDYOTIkbwZEEAAAQQQQAABBBBAAAEEEEAgyAQyLcN/dfWTmQMwyFqR6vpKwLYBwEaNGhnGderU8ZU190EAAQQQQAABBBBAAAEEEEAAAS8JWBOARIaHSb3YKC9dncsgEFoCtg0Ann322UZLrl+/PrRalKdBAAEEEEAAAQQQQAABBBBAwAYC1vn/EtX8f+EqCMiCAAKuArYNAN57771GApApU6ZIcbF5zgBXJvYggAACCCCAAAIIIIAAAggggEAgCVh7ADL/XyC1DnUJNAHbBgD79u0rzz77rKxZs0auuOIKccwJ6K8GOnnypLz33nsyadIkGTp0qLRr107q168v0dHR0rhxYznnnHNk8uTJkpGR4dUqrlq1Su644w4544wzpF69ekYm5LZt28oll1xi+Bw9etSr9+NiCCCAAAIIIIAAAggggAACCHhDICPHnAGY+f+8oco1QlXAtlmA//a3vxlt2r9/f/nkk0+kZcuWcsEFF0inTp0kLi6uwvZ++OGHKyxTlQI6EDd69Gi3p+gg3FdffWW8nn76aXn77bflwgsvdFu2sjsLCgrkrrvuktdff11KS0tNp+3YsUP067PPPpM2bdrI5ZdfbjrOBgIIIIAAAggggAACCCCAAAL+FnDpAaiGALMggIB7AdsGAB999FEJCzs9N4D+mZeXJ/Pnzzde7qnMe70dANRXT0tLk3PPPVd69+5trDdt2lROnTol+/btkw8++EDmzJlj9FS87LLL5Pvvv5du3bqZK1XJrcLCQtHZjxcsWGCcMXjwYLnuuuuMXoCRkZGye/duWbt2rcyePbuSV6QYAggggAACCCCAAAIIIIAAAr4VSM8uNN2QIcAmDjYQMAnYNgCoFaw936zbJqla3tCBvz179ni8y6hRo2Tu3LlG4E4H8B577DH58MMPPZYv78ATTzzhDP4988wzxrDjsuV1r0h9v7///e9SVFRU9hDrCCCAAAIIIIAAAggggAACCASEgHUIcFICPQADomGoREAK2HYOQN2zriYvb7dmREREhZfUQ3H1EGW9fP311xWWd1dAD+196qmnjEPXX3+9S/DPek5UFCnUrSZsI4AAAggggAACCCCAAAII+F/AOgQ4OT7G/5WiBggEqIBtA4AB2h4VVis+Pt4ok5+fX2FZdwVee+01o1efHvZcG8OY3d2TfQgggAACCCCAAAIIIIAAAgh4WyAj25wEhB6A3hbmeqEkYOshwMHWkJs2bTKyFut6O3oCVvUZHPP69enTR1q3bm2crntCHjhwwAgMNmnSROrUqVPVy1IeAQQQQAABBBBAAAEEEEAAAZ8J6Cm80nOYA9Bn4Nwo6AXoARjgTZibmyvbtm2TZ5991kgQUlJSYtR4woQJVa65ziashwDrZcCAAXLy5EmZOHGiJCcnG0lHdMbfevXqydChQ+XTTz+t8vU5AQEEEEAAAQQQQAABBBBAAAFfCGQXFEth8SnTrZLIAmzyYAOBsgL0ACyrESDrM2fOlBtuuMFjbe677z655pprPB73dGDjxo3OQ7qXX69evWT79u3OfXqluLjYmF9QzzF4zz33GIFHU4FKbujMxeUtBw8eLO8wxxBAAAEEEEAAAQQQQAABBBDwKGCd/08XZAiwRy4OICAhHwDUvdr0oue8KxvscuyvznvAeq3qXKM65/To0UNeffVV0Vl6q7NkZmY6T3v++eeloKBABg4cKE8++aT07dtX9LyCCxYsEB1g1AG65557Tjp06CC33Xab87zKrqSlpVW2KOUQQAABBBBAAAEEEEAAAQQQqJKANQNwXHSExEWHfIijSkYURqCsQMj/7di1a5fxvDpoV3Zx7C+7r7Lr1mtV9rzKltPZfvUcfXrJy8szApfvv/++fPTRR0bPPx28GzFiRGUv5yyXk5PjXNfBv969e8vixYslNjbW2K97BY4ZM8YIBvbs2VN0eZ0oZNy4ccwL6JRjBQEEEEAAAQQQQAABBBBAwN8C6dnW+f+i/V0l7o9AQAuEfABQB6/cLZ72uyvr630NGjQQ/XIsunfe1VdfLW+99ZYRjPv9738vr7/+ulx//fWOIpX66Qj0OQr//e9/dwb/HPv0z/bt28vtt98uzzzzjOh5AxctWiSXXnpp2SIVru/du7fcMrqHYb9+/cotw0EEEEAAAQQQQAABBBBAAAEE3AlYhwAnxce4K8Y+BBD4VSDkA4AzZsxw29ie9rstHCA7x44dK5988ono3oB33XWX6EBgw4YNK127unXrOstGR0cbSUWcOywrF154oREA1Lu///77KgcAU1NTLVdkEwEEEEAAAQQQQAABBBBAAAHvCGRkF5gulJxAD0ATCBsIWATIAmwBCfRNHfTTix6eq+frq8pSdl6+lJQU0UFAT0vZskeOHPFUjP0IIIAAAggggAACCCCAAAII+FwgI8cyBJgegD5vA24YXAIEAIOrvaRRo0bOGu/evdu5XpkVPbQ3KirKKFpSUlLuKWWPR0aGfEfRci04iAACCCCAAAIIIIAAAgggEFgC6ZYegGQADqz2oTaBJ0AAMPDapNwa7d+/33k8ISHBuV6ZFR38GzBggFH08OHDRi9CT+eVzZjcvHlzT8XYjwACCCCAAAIIIIAAAggggIDPBVzmAExgDkCfNwI3DCoBAoBB1Vwis2fPdta4a9euzvXKrlx55ZVGUd3D7+OPP/Z42pw5c5zHBg8e7FxnBQEEEEAAAQQQQAABBBBAAAF/C2TkMAegv9uA+weXAAHAAGmvmTNnSn5+frm1ee655+Szzz4zyrRq1UrOPvtsU/mlS5dKWFiY8fKUIfjGG2+Uxo0bG+c98MADonsCWhd9HZ1xWC9dunSRQYMGWYuwjQACCCCAAAIIIIAAAggggIDfBFx6ADIHoN/aghsHhwCTuwVIOz366KMyadIk0T30dGCvbdu2oof4ZmVlybp16+Sdd96RFStWGLXVyTumT58u1ZmbT1/zhRdekNGjR4ueQ7Bv375y//33S79+/YwApE4sogONuoegvv6rr75qBBQDhIlqIIAAAggggAACCCCAAAII2Fyg5FSpZOZakoCQBdjm7woevyIBAoAVCfnweGZmphHY08E9T0tqaqq88cYbcv7553sqUuH+q666StLT0+Xee++VvXv3yp133ulyjg4Uvv322/T+c5FhBwIIIIAAAggggAACCCCAgD8FjqngX2mpuQYkATF7sIWAVYAAoFXET9uLFy+WRYsWyZIlS2TTpk3G0NyMjAyJjY2VlJQU6dGjh4wYMUJGjRolcXFxNa6lDvqdc8458tJLL8nChQtFJxeJiIiQNm3ayEUXXSQTJ06Upk2b1vg+XAABBBBAAAEEEEAAAQQQQAABbwpYh/+qmbAkMS7am7fgWgiEnAABwABpUj3kV79uvfXWatdIB/RKrV+DlHO1M888U15++eVySnAIAQQQQAABBBBAAAEEEEAAgcASyMg2JwBpqIJ/kRGkOAisVqI2gSbA35BAaxHqgwACCCCAAAIIIIAAAggggAACHgXScyzz/8XT+88jFgcQ+FWAACBvBQQQQAABBBBAAAEEEEAAAQQQCBqB9CxzD0Dm/wuapqOifhRgCHA5+IcPH5ZPPvnESJjRunVrufTSS6VOnTrlnMEhBBBAAAEEEEAAAQQQQAABBBCoTYGMHGsAMKY2b8e1EQgJAdsGAHWijUceeUTC1Gyh06ZNkwYNGpgadN68eTJmzBjJy8tz7k9LSxO9v1u3bs59rCCAAAIIIIAAAggggAACCCCAgO8ErElAkhkC7Dt87hS0ArYdAjx37lz54IMPjGy71uDfkSNH5Nprr5Xc3FwjqYZOrKFfe/bsMXoB5uTkBG2DU3EEEEAAAQQQQAABBBBAAAEEglkgPdsyB2ACPQCDuT2pu28EbBsAXLx4sdH7b8SIES7SOjNudna2REZGyrPPPitr166VyZMnS3h4uOzbt0+mT5/ucg47EEAAAQQQQAABBBBAAAEEEECg9gVchwCTBKT21blDsAvYNgCoe/PppXv37i5tOGfOHCM4eN1118nEiROla9euct9998lNN91k9ATUw4BZEEAAAQQQQAABBBBAAAEEEEDA9wLWIcBJ8fQA9H0rcMdgE7BtAPDo0aNGWzVq1MjUZunp6bJhwwZjn54DsOxy2WWXGZuO42VSHhkqAABAAElEQVSPsY4AAggggAACCCCAAAIIIIAAArUvkJFtTgKSnEAPwNpX5w7BLmDbAKCe308v+fn5pjZcvny50csvOjpaBg0aZDrWtGlTY/v48eOm/WwggAACCCCAAAIIIIAAAggggEDtC+QVlkiOepVdkpgDsCwH6wi4FbBtADAxMdEAcQwFdujouQH10qdPH4mJMXcjLi4uNo4lJCQYP/kDAQQQQAABBBBAAAEEEEAAAQR8J2Cd/0/fOYkegL5rAO4UtAK2DQA65v6bNWuWs/Hy8vJk9uzZxvx/w4YNc+53rOzevdtYTUlJceziJwIIIIAAAggggAACCCCAAAII+EjAOv9fdES41I2J9NHduQ0CwStg2wDg1VdfbQz1nT9/vuj1qVOnyvDhw+XIkSNGAHD06NEurbpy5UpjX5s2bVyOsQMBBBBAAAEEEEAAAQQQQAABBGpXwNoDUPf+CwsLq92bcnUEQkDAtgFAneH37LPPNoKAutffhAkT5JtvvjGa9IYbbpBOnTq5NK8jO7C73oEuhdmBAAIIIIAAAggggAACCCCAAAJeFUjPLjRdj+G/Jg42EPAoYNsAYHh4uCxYsEDuvfdeSU1NlcjISElLS5P//d//lVdeecUFTPcU3LVrl7H/ggsucDnODgQQQAABBBBAAAEEEEAAAQQQqF0B6xDgpHjz3P21e3eujkDwCth6oHx8fLw888wzxquiJtS9BXfu3GkUa9myZUXFOY4AAggggAACCCCAAAIIIIAAAl4WyMguMF2RHoAmDjYQ8Chg6wCgRxU3Bxo2bCj6xYIAAggggAACCCCAAAIIIIAAAv4RyMgxDwFOTqAHoH9agrsGm4BthwDrefzOO+88cWT2rUzDHThwQBznVaY8ZRBAAAEEEEAAAQQQQAABBBBAwHsC6dYegPHR3rs4V0IghAVs2wNw6dKlRqagnJycSjdvXl6eOM6r9EkURAABBBBAAAEEEEAAAQQQQAABrwi4zAFID0CvuHKR0BewbQ/A0G9anhABBBBAAAEEEEAAAQQQQACB0BLIyGEOwNBqUZ7GVwIEAKsg7egtGBsbW4WzKIoAAggggAACCCCAAAIIIIAAAjUVKC0tFWsPwGSyANeUlfNtIkAAsAoNvWDBAqN0ampqFc6iKAIIIIAAAggggAACCCCAAAII1FTgZF6xFJ8qNV2GLMAmDjYQ8ChgmzkAb7zxRrcIDz30kDRo0MDtMcfOgoIC2b59u3z//ffGvIFDhw51HOInAggggAACCCCAAAIIIIAAAgj4QCDdMvxX3zKRJCA+kOcWoSBgmwDgzJkzjeBd2UbT3Yc//vjjsrs8ruuyeklMTJS//vWvHstxAAEEEEAAAQQQQAABBBBAAAEEvC9gHf5bNyZSYqMivH8jrohACArYJgDYokULUwBw9+7dxnbTpk0lKirKY9OGhYWJnvNPlxs4cKDcfvvt0qxZM4/lOYAAAggggAACCCCAAAIIIIAAAt4XyMgmAYj3VbmiXQRsEwDctWuXqU3Dw09Pf/jFF19I586dTcfYQAABBBBAAAEEEEAAAQQQQACBwBJIzyk0VSgpIca0zQYCCHgWsE0A0EowZMgQowdgfHy89RDbCCCAAAIIIIAAAggggAACCCAQYAIuPQCZ/y/AWojqBLKAbQOAS5cuDeR2oW4IIIAAAggggAACCCCAAAIIIFBGwDoHID0Ay+CwikAFAqfHwVZQiMMIIIAAAggggAACCCCAAAIIIICAPwUyLFmAkxOi/Vkd7o1AUAnYtgegu1Y6efKkZGVlSUlJibvDpn06qQgLAggggAACCCCAAAIIIIAAAgj4RiA92zIHIEOAfQPPXUJCwPYBwIULF8rLL78sy5Ytk2PHjlWqUXVm4OLi4kqVpRACCCCAAAIIIIAAAggggAACCNRcwGUOQJKA1ByVK9hGwNYBwPHjx8tLL71kNHZpaaltGp0HRQABBBBAAAEEEEAAAQQQQCDYBDJcsgAzBDjY2pD6+k/AtgHAWbNmydSpUw352NhYufzyy6V3796SmJgo4eFMjei/tyR3RgABBBBAAAEEEEAAAQQQQMAsUFRySo7nFpl2JtMD0OTBBgLlCdg2ADht2jTDJS0tTb788ktp27ZteU4cQwABBBBAAAEEEEAAAQQQQAABPwkcs/T+09VIYg5AP7UGtw1GAdt2dfv5559Fz+X3yCOPEPwLxncudUYAAQQQQAABBBBAAAEEELCNgDUBSHiYSIM4hgDb5g3Ag9ZYwLYBwKKi012He/bsWWNELoAAAggggAACCCCAAAIIIIAAArUnkJFTYLp4our9F6GjgCwIIFApAdsGAFu1amUAZWdnVwqKQggggAACCCCAAAIIIIAAAggg4B+BjOxC042T4mNM22wggED5ArYNAF5xxRWGzOLFi8sX4igCCCCAAAIIIIAAAggggAACCPhVID3b3AMwKYHhv35tEG4edAK2DQBOmjRJWrRoIc8//7xs3rw56BqOCiOAAAIIIIAAAggggAACCCBgF4EMSxKQJDIA26XpeU4vCdg2AFi/fn35/PPPJSUlRQYNGiQvv/yyHDt2zEusXAYBBBBAAAEEEEAAAQQQQAABBLwlkGHtAUgGYG/Rch2bCETa5DldHrNNmzbGvtzcXCPwd/fdd8v48eMlOTlZ4uLiXMqX3aGzB2/fvr3sLtYRQAABBBBAAAEEEEAAAQQQQKCWBKxzACYzBLiWpLlsqArYNgC4a9cuU5uWlpaKfh05csS0392GDgCyIIAAAggggAACCCCAAAIIIICAbwTSGQLsG2juErICtg0Ajhs3LmQblQdDAAEEEEAAAQQQQAABBBBAIJQEGAIcSq3Js/hDwLYBwBkzZvjDm3sigAACCCCAAAIIIIAAAggggEAVBaxDgEkCUkVAittewLZJQGzf8gAggAACCCCAAAIIIIAAAgggEAQCuYXFkldUYqopcwCaONhAoEIBAoAVElEAAQQQQAABBBBAAAEEEEAAAQT8JWDt/afrQQ9Af7UG9w1WAQKAwdpy1BsBBBBAAAEEEEAAAQQQQAABGwikZxeYnjImMlzioyNM+9hAAIHyBWw7B+Cbb75ZvkwFR6+77roKSnAYAQQQQAABBBBAAAEEEEAAAQRqKmDtAZicECNhYWE1vSznI2ArAdsGAK+//vpq/8LQv2gIANrq7wkPiwACCCCAAAIIIIAAAggg4CeBjBxzD8CkhGg/1YTbIhC8ArYNAOomKy0tDd6Wo+YIIIAAAggggAACCCCAAAII2EAgPbvQ9JRJ8QQATSBsIFAJAdsGAHfu3FkhT05OjmzZskXeeecdmTNnjgwcOFBee+01iY+Pr/BcCiCAAAIIIIAAAggggAACCCCAQM0F3A0BrvlVuQIC9hKwbQCwZcuWlWrpzp07y8iRI+Xdd9+VsWPHyt133y2LFi2q1LkUQgABBBBAAAEEEEAAAQQQQACBmgm4DgGOqdkFORsBGwqQBbiSjT569Ghj3r+lS5fKtGnTKnkWxRBAAAEEEEAAAQQQQAABBBBAoCYCrj0AGQJcE0/OtacAAcAqtPuoUaOMeQNnzpxZhbMoigACCCCAAAIIIIAAAggggAAC1RVIzyYJSHXtOA8BhwABQIdEJX42adLEKKXnBWRBAAEEEEAAAQQQQAABBBBAAIHaF8jIsSYBYQhw7atzh1ATIABYhRbds2ePUbqoqKgKZ1EUAQQQQAABBBBAAAEEEEAAAQSqI3DqVKlkWgOACQwBro4l59hbgABgJdtfB/0mT55slG7Xrl0lz6IYAggggAACCCCAAAIIIIAAAghUV+BEXpGUqCBg2SU5gR6AZT1YR6AyArbNAuzozVce0qlTp+TYsWOyevVqmTp1qqxfv17CwsLk6quvLu80jiGAAAIIIIAAAggggAACCCCAgBcErBmA9SUbxtED0Au0XMJmArYNALZu3brKTV1aWioDBgyQe+65p8rncgICCCCAAAIIIIAAAggggAACCFRNID3bPP9f/TpREh3JYMaqKVIaARHb/q3RwbyqvBo2bCj333+/LFq0SGJi6G7MXx4EEEAAAQQQQAABBBBAAAEEalsgwxIATGL+v9om5/ohKmDbHoAzZsyosEnDw8Olbt26onsLdunSRSIiIio8hwIIIIAAAggggAACCCCAAAIIIOAdAesQ4OR4OuR4R5ar2E3AtgHAcePG2a2teV4EEEAAAQQQQAABBBBAAAEEgkogPavAVF96AJo42ECg0gK2HQJcaSEKIoAAAggggAACCCCAAAIIIICAXwTSc8xzABIA9EszcNMQECAAGAKNyCMggAACCCCAAAIIIIAAAgggEIoCGdmWHoAMAQ7FZuaZfCBg2yHAVtsffvjBSPCxfv16yczMNA4nJiYac/+df/750rt3b+spbCOAAAIIIIAAAggggAACCCCAQC0KWJOAJJMEpBa1uXQoC9g+ALhu3Tr505/+JKtWrfLYzg888ID0799fpk2bJl27dvVYjgMIIIAAAggggAACCCCAAAIIIOA9gQyXIcAkAfGeLleyk4CthwAvWrRI+vXrZwT/SktLRb8iIyMlJSVFGjdubKw79n/33XdG2cWLF9vp/cGzIoAAAggggAACCCCAAAIIIOA3gXSXIcDRfqsLN0YgmAVsGwBMT0+XP/7xj1JQUCBhYWFy8803y8qVKyUnJ0cOHDggBw8elNzcXCM4eMstt0hERIRRVp+TkZERzG1O3RFAAAEEEEAAAQQQQAABBBAIeIGC4hLJyi821TMpgR6AJhA2EKikgG0DgFOmTJETJ05IdHS0fPrpp/Laa69J3759jV5/Djsd9OvTp48x9FeXiYqKMs7R57IggAACCCCAAAIIIIAAAggggEDtCWRahv/qOzEHYO15c+XQFrBtAFAH9HTPv7vuuksuvPDCClt5+PDhcvfddxvDhPW5LAgggAACCCCAAAIIIIAAAgggUHsC1gQgkeFhUi82qvZuyJURCGEB2wYAd+7caTTrZZddVunmdZTdsWNHpc+hIAIIIIAAAggggAACCCCAAAIIVF1g25Es00mN6sZIuAoCsiCAQNUFbBsAzM/PN7Ti4+MrrRYXF2eU1fMGsiCAAAIIIIAAAggggAACCCCAQO0JrNlz3HTxM5vVN22zgQAClRewbQCwSZMmhtJPP/1UaS1HWZ0lmAUBBBBAAAEEEEAAAQQQQAABBGpPYM1ecwCwZ4sGtXczroxAiAvYNgA4ePBgYz6/p556Sk6ePFlhM+sy//znP415A/W5LAgggAACCCCAAAIIIIAAAgggUDsCOgPwxoPmz+o90ggA1o42V7WDgG0DgLfeeqvRvnouwCFDhsj333/vsb1XrVpllHHM/ec41+MJHEAAAQQQQAABBBBAAAEEEEAAgWoLbDxwUopKSp3nqxye0jWVIcBOEFYQqKJAZBXLh0zxQYMGyR133CEvv/yyrFu3Ts466yzp3Lmz9O/fX/QQX50h+NChQ7Jy5UrZuHGj87n1OfpcFgQQQAABBBBAAAEEEEAAAQQQqB0B6/Dfto0SyABcO9Rc1SYCtg0A6vZ98cUXRSf2ePbZZ+XUqVOyYcMGU7BPlyktPf2NQ3h4uNx3332ihwyzIIAAAggggAACCCCAAAIIIIBA7QlYA4AM/609a65sDwHbDgHWzat7+U2ePFnWrFkjt99+u7Rv394I+Omgn+Ol9+ljuoxjDkB7vDV4SgQQQAABBBBAAAEEEEAAAQT8I0AA0D/u3DV0BWzdA9DRrF26dJGXXnrJ2CwsLJRjx44Z6w0bNpTo6GhHMX4igAACCCCAAAIIIIAAAggggEAtC2TmFMrujFzTXegBaOJgA4EqCxAAtJDpgJ+eA5AFAQQQQAABBBBAAAEEEEAAAQR8L7B273HTTWOjwqVTk7qmfWwggEDVBGw9BLhqVJRGAAEEEEAAAQQQQAABBBBAAIHaFvjJEgDs2ry+REYQvqhtd64f2gK2+Ru0YMEC6dWrl/GaNWtWlVr1nXfecZ67aNGiKp1LYQQQQAABBBBAAAEEEEAAAQQQqLwA8/9V3oqSCFRWwBYBQJ3Q45577pG1a9dKUlKSjBkzprI+RjldXp+nE4FMmjSpSudSGAEEEEAAAQQQQAABBBBAAAEEKiegP79bhwD3SGtYuZMphQACHgVsEQD88ssvZevWrRIeHi7PP/+8RwxPB3S24ClTpkhERISsX79eli5d6qko+xFAAAEEQkRgyZYj8tc56+TNb3dJbmFxiDwVj4EAAggggAACCAS2wC6V/ONEXpGpkj1aNDBts4EAAlUXsEUA8MMPPzRkLrjgAjnzzDOrrqTO6Ny5s1x44YXGuY7rVetCnIQAAgggENAChcWn5KG56+SGGd/Lu6v2yMMfb5Bznl4q76zcLUUlpwK67lQOAQQQQAABBBAIdoE1e4+ZHiE5IUaa1Y817WMDAQSqLmCLAOCqVatE9+K79NJLqy5U5owRI0aI7o783XffldnrndWTJ0/Ke++9ZwwxHjp0qLRr107q168vOitx48aN5ZxzzpHJkydLRkaGd25ouUpubq60adPGcNJWrVq1spRgEwEEEAh9gSMn82X09O/k7e/2mB72SFaBPPjRernwua9lwbqDxr8FpgJsIIAAAggggAACCHhFYM0ecwbgHmkNjM+pXrk4F0HAxgKRdnj23bt3G4/ZsWPHGj1uhw4djPN37dpVo+u4O1kHKUePHu3ukBw9elS++uor4/X000/L22+/7eyN6PaEaux8+OGHZefOndU4k1MQQACB0BD4YXem3P72j6KDfZ6WHek5cvs7P0p39R/Rv1zUUQa2TfZUlP0IIIAAAggggAAC1RCwJgDpyfDfaihyCgKuArYIAJ44ccJ48sTERFeBKuxxnK9769XGkpaWJueee6707t1b9HrTpk3l1KlTsm/fPvnggw9kzpw5kp6eLpdddpl8//330q1bN69U46effjLmRoyNjZWoqCjJysryynW5CAIIIBAMArpn9zsr98hj8zeoIb6lpipHhIdJySnzPl1AT0w9ZvpKGdqhkfyPCgSe2ay+6Tw2EEAAAQQQQAABBKoukF9UIhsPmj9v6x6ALAggUHMBWwQA69WrJ8eOHZPjx81diavK5zi/bt26VT21wvI68Ldnj3nIWdmTRo0aJXPnzpWRI0dKYWGhPPbYY+KNuQhLSkrklltuEf3zkUcekddff50AYFl41hFAIKQF9H8yH/54vby/ep/Lc6Y2rCOvXttbTqpJqJ/6fLP8vO/0l0llC361VfXQVq/LezSTScM7SlpiXNnDrCOAAAIIIIAAAghUQUAH/8p+Iatmp5JuqXzRWgVCiiLgUcAWcwDqOfT0snHjRo8QlTmwadMmo5jjepU5p7JldIbhipbLL79cOnXqZBT7+uuvKypeqeM6u/EPP/wgenj0X/7yl0qdQyEEEEAgFAQOHM+Tq6Z96zb4d3a7ZJl/19nSpXl9GajWP75zkLw0ppe0To53++hz1xyQYf9aKo/O2yDp2Z6HELs9mZ0IIIAAAggggAAChoB1/r92jRKkbmwUOggg4AUBWwQA+/XrZ0zYPm/evBqRffzxx8bko3379q3RdWpycnz86Q+f+fn5NbmMca6eG1HP/aeXV155xUg4YmzwBwIIIBDiAt/tyJBLX1wua9306rttaFv5z439pGF8tFNBJ0e6pFtT+eKeIfL3kV2kUd0Y5zHHiv62euY3u2To5CXy/KKtkl1Q7DjETwQQQAABBBBAAIFKCFjn/2P4byXQKIJAJQVsEQC8+OKLDY6FCxdKdXvO6fO++OIL4zqO61XS2GvFdA/ENWvWGNdz9ASsycXvuOMOycnJkbFjxxpzD9bkWpyLAAIIBIOAnu9vxoqdcs2/V0pGTqGpynHRETJ1TE+5/+JOouf+c7dERYTLNf1byld/Pkf+fGFHqRvjOpNGTmGJCgBuMwKB/1EBwcLiU+4uxT4EEEAAAQQQQAABi4BLAJAEIBYhNhGovoDrJ5fqXytgz7zyyiulTZs2smPHDtFz6emMulXJCLx161bjPN0DpFWrVvKHP/zBZ8+am5sr+/fvl/nz58vkyZONufr0zSdMmFCjOrz33nvy2WefScOGDeWZZ56p0bU4GQEEEAgGgTwVmHvgo3Xy0U/7XarbMilOXhvbRzo2qdwcr3HRkXLnue1kTL8W8tKSX+TNb3dLYYk50KcDjI+oIcGvL9+p5gfsIJd2aybhHgKLLhViR5UEcguLZZ4ahr1o02E5oeZsVHFeY3Gkb9GBX738tm1sOrcdJ7ge//W8Xw94uu7pq6nrO8r9dmX1nqonN5/d2sgc7SjHTwQQQAABBBBwFchU/3fak5lrOkAPQBMHGwjUSMAWAcDIyEj517/+JVdccYUcPXpU+vTpI3/729+M5BcJCQkeAbOzs+Xf//63MUxWr+sAoL6Ovl5tLjNnzpQbbrjB4y3uu+8+ueaaazwer+iATogyceJEo9hTTz0ltTGnoc5cXN5y8ODB8g5zDAEEEPCqwF71n8lb3/rBJaucvsm5HRvJ81f1lPpxVZ9fRg8TfmhEZ7l+UCt5buE2mfPTPmcQyPEA+j+yE95bI699vUNlDO4kQ9onG/+eOI7zs/oCvxzJVhmcd8sHP+yTrPzAHHK99XC2fPrzAbl+YGsjEBzvptdo9QU4EwEEEEAAgdARWLvXnLQzNipcOqZU7svZ0FHgSRCoPYHajWTVXr2rfOXf//738sQTT8iDDz4ouledDqLprLeDBw+WXr16SUpKiuj59fSQ2MOHD8uPP/4oy5YtM7YdPQd05l2diMNfS48ePeTVV1+V/v3716gKf/7zn41nHDBggBEErdHFPJyclpbm4Qi7EUAAAd8KLNt2VO5+9yc5nlvkcuPxw9rJxPM71LhnXmrDOPnXqO5yy5DW8vTnW2Tx5iMu99pw4KSMe2OVDGybJH9RgcDuaQ1cyrCjYoEi1dNy0cbD8tZ3u+Wb7RkVnxAAJU6pnoFvqKHn/91wSJ64vIuc2+l0crIAqBpVQAABBBBAIGAEfrIEALuqZGyRavoVFgQQ8I5AmApu/TpgxTsXDPSrvPXWW+KY+07XVffq87Q4aOLi4mTq1Kly/fXXeyrq1f3Hjx8XRw+6vLw82b59u7z//vvy0UcfSdu2beX555+XESNGVOueei7Dc845R3TWYZ39t1u3bqbr6CHOOjlIy5YtZdeuXaZjVdkoz9V6nb1790pqaqp1N9sIIIBAjQT07/Bpqtfd5M83iw7AlF0SVC8sHbC78MwmZXd7bf37XZny1ILN8sPuYx6veUnXpkaPsDYqux1LxQKHTuTLu6v2GK8jWcGdafnS7s3kYdVz1F0ymYolKIEAAggggEBoClynvij9eutR58PdMri1PHhJZ+c2K9UX0PEFRycdPn9X3zHYz7RdAFA3mB5++uyzz8qbb75pDAn21IjJyclG0E8Pl23WrJmnYj7br4OX48aNM4KWr7/+epUDkgUFBdK9e3fZsmWLTJo0ye3cf94KADoCmJ5wdBvo7Mx64ReQJyX2I4BAdQVyVAbe//nwZzX00nW6gTaN4o35/to1rt3Amw5ALlQ91Z7+7xbZpoaqult0spGr+qbJxPPaS+N6se6K2HqfNtS9/N5ScywuVPP7lVgjuWV09Pd5Qzs0UkO6GzuTuDi+4wuT01/2/batvwA8fbLj2K9FHD+cXxD+Wuy38pbzHNdxVMXxBZgupocov/LVdreJYOrFRqoPNWfIqD5pzns5rsFPBBBAAAEE7Cag/83v8beFxly+jmd/aUwvuaRbU8cmP2sgQACwBnghdKotA4Bl22/jxo2ydu1aSU9Pl6ysLKlbt67owJ8OlHXuHHjfNlx11VVGb0A9XFkHznQSj8ouDz/8sDz++ONG5F8/t7v5D1u18k4PwIrqxC+gioQ4jgAC1RXYlZ5jzPe35XCWyyWGd04xev7Vja36fH8uF6vkDh20+vDHfWqOwK1yUPVic7fUiYqQG89uJbcObSv1fFg3d3UJhH0n1HDtD5SZnt9vx9GccqvUUM3dOEoFUa/p11JaqGQugbbsVO/HB+ask293uB+ufFabRPnHyK5CT9BAaznqgwACCCDgS4EdR7Nl2L++Mt1yxf3DpHmDOqZ9bFRPgM/f1XMLtbNsHwAMtgadNWuWMwHIO++8I2PGjKn0I8TExEhhYaGRYGT48OFuz7v77ruNYKgOgr744otGGZ0kZNiwYW7LV3cnv4CqK8d5CCBQnsASNffehPd+kpOWhBC6l9a9aq4/nbnXX5l484tKVLbgXSpr8HbTt9tln6eBCmbdpep47VktJVYFBe22rNt3Qt5Wc/t9vHa/5BeZsypbLXq1aCBjB7SUi7s0DXgr3athtkpU8vdPN7lt++jIcNHzUf5pSFvR6ywIIIAAAgjYTWCO+uLv3vfXOh9bT5Ox6oHz6CXvFKnZCp+/a+YXKmfbJglIqDRYo0aNnI+i5+qryqKDf3qZMWOG8SrvXN0jcvTo0UaRoUOHej0AWN69OYYAAghUVeCU6mX30pJf5NlFW12y8NZVQy1fuLqn3xMv6ICeDvBc1beFvKqGhc5QSSGsQS6dqOQJFSSasWKX3HNBBxnZs7lzOGtVTYKlvA6MfqKGauukHtbsf9Zn0D0lL1cm157VQs5sVt96OGC39bBgPdR3mEr+8bf5G2Xe2gOmuhYWn5Jnvtgq89celCev7Cq9WlS+d7/pQmwggAACCCAQpAJrLAlAeqhkaY5pNYL0kag2AgEnQAAw4Jqk/Art37/fWcDdEF7nQVYQQAABmwhk5RfJJPWN8Rdqvj3r0jGlrkwb21taJcdbD/ltu36dKCML8LgBrWTK4q3y/up9LnPb7T+eJ/fNXivTVRKT/7mooxE4CrX/BOuh2nqIr+4Z5y5Dc9kG0vM1Xtu/hVzROzWoh0gnJ8TIC6N7yshezeWhj9aLbueyix62fuUr38hY1QP0zxd2FF8OVS9bD9YRQAABBBDwtYC7AKCv68D9EAh1AQKAQdbCs2fPdta4a9euzvXKrOghSBUtvpoDsKJ6cBwBBBCojIBOsnDrW6tlu5t54nSW3cl/6CbxKuNvIC5N6sfKk1d0k5vObiPPqEQhn2845FJNHRC66T+rpW+rhnL/xZ2kd8tElzLBtKO45JR8qYZp695+y7all1v1SJUg5cIuTVTgr6XoefJCKQCqE5V8cc8QY17IN1RP0LK5TfQ/1W+qpCdfbDgsf/v9mTK8ljJVl4vPQQQQQAABBHwooEcDbDp40nTHnqoHIAsCCHhXgIlmvOtZ7avNnDlT8vPdTw7vuOhzzz0nn332mbGpA3Vnn32245Dxc+nSpcYHJP0h6frrrzcdYwMBBBAINYEvVMDs8pdWuAT/VNxI/qqCZVPH9AzY4F/ZttC9215VvRQ/umOg9G/tPsD3/a5jqmfYt3LLm6vlW5UV95BKJqKHPQfLciQrX15cvE2GTF4if3rrh3KDf01VYPReNfz5GzXxt87+N6BtUkgF/xxtpgPTD43oLHPvHCSdm9Zz7Hb+PHQy37C6/e0f5LBaZ0EAAQQQQCBUBTaq4F9RyW//r1EfZ6VravBM9RGq7cJzhZ5AYHaLCD3nCp/o0UcflUmTJsmVV15pBPbatm1rZOnVmYnXrVsnOuHHihUrjOtER0fL9OnTJTKS5qsQlgIIIBByAjrw9bya6++FL39xeTadRONFNcRycPvf5kt1KRSgO3qqed/e+9NZsnTrUfnngs2y+ZBrFuOFapizfuklKiJMmqnMeDo7XmpD/TPu9E+1rreb1IuVyAj/fc+ne52v3JlpJPX4fP0hKa4gYDm4fbKR/OQ8NU+eP+vt67dHt9QGMu+uQfL68p3ynHpfW+eFXKDslv+SbvQAHa3mj/RXEhtfu3A/BBBAAAH7CKzZc9z0sO0aJTANhkmEDQS8I0AEyTuOXrlKZmamEdjTwT1PS2pqqrzxxhty/vnneyrCfgQQQCBkBU7kFclEleV3yZajLs+oe1Hp+f7SEuNcjgXLDt2DWw8PHaoCmDoT7r9UYoh9x8zzxDmeRX9Tvjsj13g59pX9GaG6QuogoBEcNIKCKkDoCBaq7ab169RKxtmTak7Gj37cbwT+tqkh2uUtej7EP6p5/a5Rc961DqB5Gsurc20c0wHPW4e2NTIaPzh3nUsPySyV1fpBNWfg3J/2q2HjXaVd47q1UQ2uiQACCCCAgF8EmP/PL+zc1IYCBAADpNEXL14sixYtkiVLlsimTZvk8OHDkpGRIbGxsZKSkiI9evSQESNGyKhRoyQuLng/3AYIN9VAAIEgFNiiesTp+f52qaCXddHZcv8xsqvUiY6wHgrKbd3La2TPVPmdmsdw1so98qLq7ZiZczqTe2UfqET1uNNJJoxEEztdz9LDa1Lqlg0QmnsR6p6FOnNxZZeNB07K2yqphw5S5RaWlHtadzWs51oV9Lu0e7Mq3aPci4bAwRZJcfLmjf1k7pr98vgnm1zaXA8Fv3jKMrnjnHZyx7ltJSay8u0TAjw8AgIIIIBAiAq4BABbMP9fiDY1j+VngTA1ROe3wfZ+rgy3t4/Avn37JC0tzXjgvXv3iu7ZyIIAAgh4Evj054Py5w/WugSWdC+3hy45Q64f2Cok54lzeOhMx3qIqHbYnZkrhcWnHIdq9WejujG/DTF204tQ+y9Yd8hI6vHD7mPl1iU2KlwuUwE/HfjTw15ZyhfQAd8nPt0oc1RvSndL20bx8tSV3VSCGPfzRro7h30IIIAAAggEmkBGdoH0fmKRqVqfjj9bzmzGHIAmlBpu8Pm7hoAhcjoBwBBpyGB7DH4BBVuLUV8E/COge7FN/u9mmfbVDpcKJMVHy0vX9FIZYpNcjoXyDj0HYnpOgTE0eL8aHqyHCO8/nmv8NNbVdp7KpueLJVoNXS1UmX3LW9qoob16iO8feqVKfTVHI0vVBJZtO2oM/92jAr/uljH9W8hfLuokejg1CwIIIIAAAsEm8OXmw3LjzNXOatdRow/WPTrcVvMBOx++Flf4/F2LuEF0aYYAB1FjUVUEEEDATgLHVA+o8Wq+v2Xb0l0eWw8hfeXa3kYSDJeDIb5DDw9urIbu6lcvlTjEuuiO/br3mB766wgI7juW69zW+7ILiq2nVWvbU/BP9wy84IwUGTugpQwM0Sy+1QKrxkk6oc1/Jw6RKSqL8vRlO0QHxcsueoj4oo2H5bHLzpSLujQJ6Z6wZZ/bW+s6w7LOrL1CJVpZtStTilTv2j/0SZObB7eWerEEVb3lzHUQQAABTwLWBCBdm9cn+OcJi/0I1FCAAGANATkdAQQQQMD7AhsOnFDz/f1gBLCsVx/VJ1X+9vsuzB1nhfl1WycSSUqIMV7uhtrqAOHJvGLZ92uvQWsvQh04PJ5b5OHq5e9urIYMj+7Xwng1qR9bfmGOVlpAz215/8Wd1JyJTeWvc9bJz/tOmM49klUgt7/zo5yvgq6PX36mkeDFVIANp4D+YuG7HRnyjQr6fbM9XbYfzXEec6y8oIKt//lml9ymErOMG9hS4qL577LDhp8IIICAtwV+2mvOANyD+f+8Tcz1EHAK8D8aJwUrCCCAAAKBIKCTSNw/52fJLzIPLY2KCJNHLj1TrlFDHnWQi6V6AtpOD8WtH1ff4/w6uofg6cDgbz0Hy26nZ5sTkuhefmPVMN/zO6dIlBoWzFI7Ano+pI/uGCQzVXDqX19scZkTc9Gmw0Zw688XdjTmWtQ9Me2+6Pkzv1c9+7755XTQb9Ohk6Ji4BUuOuP4Pz/fbMy9eZdKuDJa/d4h6UqFbBRAAAEEqiSgpzVZaw0ApjFPcJUQKYxAFQSYA7AKWBT1ngBzEHjPkishECoCRWouuSc/2yxvrHBNWauTUbx6bS/p3ZKEB4HQ3nkqy6/uKXhU9TzTmWt1xmAW3wroYd0PzV0vS7ccdXvjnqoHxZNXdJVOTeq5PR6qO/PV/Jc/qoQ0jh5+a1VvSeuw6eo8u36Pjz+vnVyp5rKMJMhdHULOQQABBFwEdhzNlmH/+sq0/5v7h9lyihcTQi1s8Pm7FlCD8JIEAIOw0UKhyvwCCoVW5BkQ8J6AziD7j882ibtMsr1bNpRXVLKPxvUYUuo9ca4UCgJ6OPcnKjP0Y/M3iLVXpn6+SNUDUA9jvWtYu5AdMq+/OPh533FnD78f9hyrcpbsurGRRjKh/q0TZfWuY/L5hkMe3x6tVVKbiee3l0u7NRM9HycLAggggED1Beb8uE/ufX+t8wL6C99VD5zHSA+niPdW+PztPctgvhJDgIO59ag7AgggEOQC+oP7swu3euzFdO1ZLeThEWdKdCTDSoO8qal+LQjo4dyXdm8mg9snGwH091fvM92lWA2tmrrkF/l03UH5x8iuMkAN1Q72RQ8X23jwpJG4Q8/ht2pnpuSoHqlVWWKjwqVvq0QZ1C7ZSFKjh1Y7hkvfPFhkneo1+IwaYv3VVtfelTvTc2TCe2vklaXbZdLwjmrexcZ8UK0KPmURQACBMgJr3Az/ZZqXMkCsIuBlAXoAehmUy1VOgG8gKudEKQRCVWCT+gCvA38LVfZSd0u0GmL3xOVdZFTfNHeH2YcAAm4EdEDswY/Wiw5SuVt0Ap0HfneGNIiLdnc4IPfpXo7b1RAxY0ivmsfvu50ZVU5So+cP7akyZuu5Kge2TZYean6pynypoIOLz/x3i5Ed2BNOd3WtP6tA4KB2SQQCPSGxHwEEEPAgcNnU5abEVnoO2zvPbeehNLtrIsDn75rohc65BABDpy2D6kn4BRRUzUVlEfCawLbDWfL8om1GjyRPF9Vzbb2khvzqD+ksCCBQNQE9B97UL3+RV7/aLroHoHWJVxmFdYbmenWipF6seqmf9etEOtf1vvr6WJl9elsPk/VVgpe9mbnOHn468KezHFdl0SNzuzavLwN/7eHXR80dqjMpV2fRAcivt6UbgcB1+83Zl8te76w2iaI/uDJPaVkV1hFAAAHPAvrfq66P/leKSn77t2rWzf2N392ez+JIdQX4/F1dudA6jyHAodWePA0CCCAQkAK6R9KURVvl47UHPGbgTE6IltvPaWdk+Y2Nqt6H9YB8eCqFgA8F9N+d+1QgakT3pnL/h+vEOrxKD5fdftR9D8GKqhmngming4aRp4OEvwYQ66ng4OmgoSOoqAKKvwYYjf2qnA4gepoz78jJfPl2h8rSqzP17kiXvZl5FVXF5XinJnWNIc66h18/NZefvq83Fj0UbWiHRjJEDbP+74bDqufyFtl6ONvl0t/tyJQrX/lWzu3YyBga3EUFIFkQQAABBDwLbDhw0hT8U79upWsqvzs9i3EEgZoLEACsuSFXQAABBBDwIKB78ryweJvM+Wm/x0ycDeOi5FaVqOC6AS0lLpp/ljxQshuBKgno7L8f3j5Q3v5ut0z+fHOV58lzd7NcFTzUr0Mn3R0tf5/+YJcQ81tPQ93rsK4KDOovB3454hpQK/9qIq1U9mlHD7+z2iRJckJMRafU6LgOBF7UpYlc0DlF5qsvMp5TX2jszsh1ueYSlZVZv37XtYnce0EHade4rksZdiCAAAIIiMsXVO0bJxj/LmCDAAK1J8Anrdqz5coIIICAbQUOHM8zkg+8//1et8MQNYzuNXTL4DZyw9mtjcCAbbF4cARqSUAnthg3sJURtHpk3gaPc27W0u1Nl1UjaSUrv9h47Ve/H6q6NFFZwAeqefZ0Dz+dzERPFeCPRZte3rO5XNKtqXzwwz7jC46DJ/JdqvLZukPy+fpDMrJnqpE1OC0xzqUMOxBAAAE7C1h7qDP1i53fDTy7rwQIAPpKmvsggAACNhDQQ/leVtkxZ63cI4Ulp9w+se4FdOOgVnKTCv55a5ie2xuxEwEEDIFmKlg2/bo+amhtruzKyJETeUVyMq9YTubrn0Wnt1VwTq/rfc7jatvT3+Papk2Mj5YBqmefI+ine/wFUmZIPR/i6H4tVICvubyjft+9rLItZ+QUmlj0FIwf/rhP5q3dL1ephEZ3D2svKSqQyYIAAgggoHsAHjMx9EhraNpmAwEEvC9AAND7plwRAQQQsJ1ARnaBkXTgLTXcML/IfeCvjpqbTPdGunVIG2moPtyzIICAbwV0L7Sq9kTTk7T/Fhj8LWh4et/poKERMDSCiaePnw4g6mBisceh/9Ynr6u+GOivEmkMUD38dLbejil1Pc4ZaD3Xn9t6zsWbVC/mq1WAb+Y3u2SaSr6in7vsoie4f/u7PTJ79T5jqgM916kOcLIggAACdhXQ/2+0zvdKD0C7vht4bl8KEAD0pTb3QgABBEJM4Hhuobz29Q7jg6+eG8zdEhMZLtee1VJuU/P8Napbu/N0ubs/+xBAoPoCOsClX42r0XNNZ9DVvxdMAUJnj8PTPQ3j1byffVXSji7N6kmk6lUXrEu8CmDeeW4743fddPU78Y0VO41nL/s8BcWnZPqynUYPad0D+ubBrY2kKmXLsI4AAgjYQWDtvuOmx9RfEndISTDtYwMBBLwvQADQ+6ZcEQEEEAh5AT1M8HX1QfaN5Tslq8Dc28Xx8FERYcYQOf2hmGFvDhV+ImAfAT1kVwfG9KuZ+GfOPl9r62kNdBbm69U0B6+o6RB0r+hCFfgru+hMzDo50n9Uj0H9xci4gSRAKuvDOgIIhL7Amj3mAGBXlTk9mL8ECv0W4wlDRYAAYKi0JM+BAAII+EAgRwX79DA33etP9+pxt0SqSfL/2CdV7lLzXflron539WIfAggg4CsBnZX4f0d0Nnr5vbD4FzX81zUhkv4d+k+Vofl19UXKXee2ldH9W0hMZISvqsh9EEAAAb8J/LTXHADs0aKB3+rCjRGwkwABQDu1Ns+KAAIIVFMgT/VYeeu7XWqevx2SaZno3nFJFfczMl5OOK+9tFAT9rMggAACdhdoWr+OPHlFV9XTr408v2ibzF2zX3RG5LJLupoL69H5G43hwePPaydX9kqlJ0xZINYRQCCkBE6pDElrrQHANAKAIdXIPEzAChAADNimoWIIIICA/wV0AoB3V6kMl2oo29GsArcVUqP85NJuzWTC+e2lbSPmb3GLxE4EELC1QMukeHnuqh5y+zlt5dkvtsrnGw65eOw/nid/+XCd8UXLRPX7VP9eDdffrLAggAACISSwU2WjtyZLIgFICDUwjxLQAgQAA7p5qBwCCCDgHwE9Z9X7asjaS0t+kYMn8j1W4uIuTWTi+R2kY5O6HstwAAEEEEDgtEAHld341bG95Wc1Af4zKhD49dajLjQ703NkwntrjDkEJw3vKOef0Vj0fIosCCCAQCgIWOf/a6wSxDWtHxsKj8YzIBDwAgQAA76JqCACCCDgO4HiklMy58f98sKX22TfsTyPN9YfSHXgr4uatJkFAQQQQKBqAt1SG8ibN/aTVTsz5Zn/bpFVuzJdLrD5UJbc8uZq+V3XJvLC1T0ZFuwixA4EEAhGgTVuhv/yJUcwtiR1DkYBAoDB2GrUGQEEEPCyQImaj2Xe2v0yRc1RtSsj1+PVh3RoJPde0EEYquGRiAMIIIBApQX6tU6U/7v1LPl6W7oRCFy3/4TLuZ+tOyRN6m2Why/t7HKMHQgggECwCbgEAEkAEmxNSH2DWIAAYBA3HlVHAAEEaiqgJ2L+bP1BY3L6X45ke7zcgDZJMml4B+nTKtFjGQ4ggAACCFRdQPd8Gaq+XBnSPln+u+GwPLtwi2w9bP59/MaKndK5WT35Q+/Uqt+AMxBAAIEAEdBzS286eNJUG75UNnGwgUCtChAArFVeLo4AAggErsDiTYflaTX0TA8z87T0adlQ7lWBv4Ftkz0VYT8CCCCAgBcEdCDwIjWv6gWdU2TuT/vlr3PWSaGalsGxPPDROpVoKV56tmjo2MVPBBBAIKgENhw4KcXqy2fHoqc31VMisCCAgG8ECAD6xpm7IIAAAgEjoLP5PjJvvehhZZ6W7qn1VeCvo9EjhXlZPCmxHwEEEPC+QITK/Hul6ulXUloq//PBz84b6ORMt771g8y/+2xJqceE+U4YVhBAIGgErMN/2zdOkIQYQhJB04BUNOgF+NsW9E3IAyCAAAKVEyhVHybnrT0gj87bIMdyi9ye1LlpPWOOv/PIOunWh50IIICArwRG9UmTjaq3zMxvdjlveUR9gaODgO/96SyJjYpw7mcFAQQQCAYBawCQ4b/B0GrUMZQECACGUmvyLAgggIAHgcMn8+VBNXxs0aYjbkt0SEmQe1RW3wvPbCLhqvcJCwIIIICA/wUevOQMNR9glnyzPcNZGf0B+qG56+XpP3QTemg7WVhBAIEgEFiz95iplj3SmNLABMIGArUsQACwloG5PAIIIOBPAd3rb/YP++TxTzZKVn6xS1UaxkXJQ5d0lst7Nhc97IwFAQQQQCBwBKIiwmXqmF5y2dTlsu9YnrNiH6jf62eqpCA3DGrt3McKAgggEMgCGdkFsjfzt99juq70AAzkFqNuoSgQHooPxTMhgAACCIjsP54n42Z8b8wh5S74d0nXpvLFPUONuaYI/vGOQQABBAJTIDE+WqZf10fqWIb8PvHpJvnml/TArDS1QgABBCwC1uG/+neaHoHCggACvhMgAOg7a+4UAgJLNh+R47mFIfAkPEIoC5xS2dXeWblbLnzua/l661GXR01OiJZXruklL6lXo7oxLsfZgQACCCAQWAJnqPlZnx3V3VSpEvW7/o5ZP6oeNbmm/WwggAACgShgDQB2VQnnIlUvZxYEEPCdAH/jfGfNnYJcYMOBE8bE27+bskxW7cwM8qeh+qEqsCcjV67590o13996yS5wHfI7Ug31Xah6/V2sev+xIIAAAggEj4D+vT1+WDtThY+rhE63vLlactz8vjcVZAMBBBDws4A1ANgzrYGfa8TtEbCfAAFA+7U5T1wNgdzCYrn73Z+ksOSUHDiRL1e/9q1MWbRN9LfvLAgEgoDu9TdjxU658Pmv5dsdv00W76hbSr0YeX1cH3nuqh7SUA0nY0EAAQQQCD6BiSpZ0/lnpJgqvvlQltw3e63ofwdYEEAAgUAU0L+frAFA5v8LxJaiTqEuQAAw1FuY5/OKwOTPt8iOoznOa+n/Yz+3aKuMmf6dHFIBQRYE/Cmw42i2jJr2rTw2f6PkFZW4VOWqPmnGXH/nWT40uhRkBwIIIIBAQAvoLO3PXdVd2jc2z5u1YP0hmbrkl4CuO5VDAAH7CuzMyHFJRtejBT0A7fuO4Mn9JUAA0F/y3DeoBG4/p60MaJPkUueVaijwxVO+lsWbDrscYwcCtS1QrHqkTvtqu3oPLpPVu4+53K55gzry5o395J9/6Cb160S5HGcHAggggEDwCdSNjTKSgtSLjTRV/tmFW+WLDYdM+9hAAAEEAkFgzZ7jpmrokSlN69cx7WMDAQRqX4AAYO0bc4cQEEipFytv39xf7hveQazZUo+p+Xdu+s9q1ftqgxQUu/a+CoHH5xECUGDr4Sy58pVv5MkFm9X77pRLDa89q4X8954hMqRDI5dj7EAAAQQQCG6BVsnxMnVML1EdAk3LPf+3RvS/DywIIIBAIAlYh/92T6X3XyC1D3WxjwABQPu0NU9aQwEd+LtrWHv5vz+dJbpnlXWZsWKXXPHyN2qocLb1ENsIeE2gSPX6e3HxNrnkhWWydt8Jl+u2SIyTd285S564vKskxJh7h7gUZgcCCCCAQNAK6C94/nrxGab65xSWGElBjucWmvazgQACCPhTwBoAZPivP1uDe9tZgACgnVufZ6+WQJ9WifLZ+MFy0ZlNXM7fcOCkjHhxuXz4wz6XY+xAoKYCOhP176eukH+pYV5FJebJ3sNUL5AbB7WWzycOlgFtXYer1/TenI8AAgggEHgCNw9uLTq7e9llt8oGrxOX6WkiWBBAAAF/C+Sr+ak3HTxpqgYJQEwcbCDgMwECgD6j5kahJFA/LkpeubaX6mXVRaIjzX+NctW375NUNj49DCe7oDiUHptn8ZOAHlr+7BdbjODfRst/oHSV2qihYLNvHSAPX9pZ4qLp9eenZuK2CCCAgM8FwtS3P09e0VW6pdY33XvZtnT55+ebTfvYQAABBPwhoL/ALi6TpVx/ad2NIcD+aAruiYCYIxeAIIBApQX0f7qvPaulzLtrkLSzZOPTF/nop/0yQg3TXOdmmGalb0JB2wus3XtcLlW9Sl/48hfTf540jJ776bahbeWzCYNF90xlQQABBBCwn0BsVIRMG9tbkhNiTA8/fdlOmfMjIxJMKGwggIDPBX6yJADp0Lgu09T4vBW4IQKnBQgA8k5AoIYCnZrUk/l3nS2j+6W5XGmXGoZzxSsr5PXlO6W01Dxk06UwOxAoI6CHSzy5YJOMfHmFmtDddV7Jjil15aM7Bsn9F3cS/eGPBQEEEEDAvgI6m+a0sb0kKsKcFeT+OetEf5HEggACCPhLwGX+vzQSgPirLbgvAgQAeQ8g4AWBOtERaghON3lxdE+pa0m8oOdqe/yTjUam4IzsAi/cjUuEusDqXZnyO9V7dNpXO6TMiAnjsSNVt7/x57WXeXcPku78ByrU3wo8HwIIIFBpgd4tE42pScqeUKiyxN/61g9yJCu/7G7WEUAAAZ8JuAQAWxAA9Bk+N0LAIkAA0ALCJgI1Ebi0ezNjOKa7iW2/3HxELp6yTL7Znl6TW3BuCAvkFhbLY/M3yB+nfauySee4POmZzerJx2rI+b0XdJCYSHr9uQCxAwEEELC5wFV9W8i4AS1NCodO5svtb/8oej5ZFgQQQMCXAumq88O+Y3mmW7r7nGQqwAYCCNSaAAHAWqPlwnYVSEuMk9m3DTDmZrMaHMkqkGv+vVL+pRI6kJ3PqmPvbR0Yvuj5ZTJjxS41XNxsER0RLvcN7yBz7xwkZzYzT/RuLskWAggggIDdBR4a0VnOamOeF/aH3cfk4bkbmI7E7m8Onh8BHwtYpyCIU6OmOqhpbFgQQMA/AgQA/ePOXUNcIEoFbPTcbG/e2E9Nyh1telod3HlRJXS4+rXvZP9x8zdipoJs2EJAZ4p+8KN1Mmb6StmTmevyzHqY7yfjz5a7hrVXczvxK9sFiB0IIIAAAiYB/W/FS2N6SfMGdUz7/2/1Xnnru92mfWwggAACtSlgHf7bpXl9idBZ7FgQQMAvAnya9As7N7WLwJAOjWTBhCEyuH2yyyOvVt/G/04NCf58/SGXY+ywh8BXW4/Khc99Le+s3OPywDGR4fLA7zrJh6o3Kd+UuvCwAwEEEECgHIEklRH4tet6Sx1LkqjH5m+Ub7dnlHMmhxBAAAHvCVgDgD2Zv9p7uFwJgWoIEACsBhqnIFAVgUZ1Y+Q/N/QzegTqBA5llxN5RXLb2z/I/85dLzrrK4s9BHS7/88Ha2XcG6vc9gLt07KhChwPlj8NaSuR9Pqzx5uCp0QAAQS8LKCnjHjmj91NVy1RmaX+n737gI+yyBs4/ocUQoCE3gNI7wSloyJ2BRuKYqH4qljOcp56XtEDvbPfWV8VOxYE64uCYMEGBwrSOwJSAoQOIbRAwr4zD+7yzGY3yaZsnufZ33w+mGfmaTPfedwyO+W2cfMkI0SPc+NAIggggEAJBY6p15vgBkDm/yshKqcjUEIBGgBLCMjpCBRFoKJq+LulXwtrbsC0muaQHH2+HpJz6YszZc327KJcjmNcLPDtim1y7jM/yodzN+Urhe6pMeqi9vLhzb2leZ2q+faTgAACCCCAQCQCAzo3kNv7tzRO2XPwqIxUKwPrhacICCCAQFkJ/LbzgGQfNl9n0lkBuKy4uS4CRRKgAbBITByEQOkIdG1SQ7648zQZqD6QB4eVW7Plohdmyge/bGSS7mAcD8SP5B6TP324UG54e65s25eTr0S9m9eSr/54ulzf9yTRw47XhQAAQABJREFUDcYEBBBAAAEESkNArxx/dru6xqVWZO6T+z5azOcNQ4UIAgiUpkBw7796KZWkQWr+jhCleU+uhQACBQvQAFiwD3sRKHWBlKQEeeHqrvLE5Z0kKcH8X/CQGgZ8/ydL5I7xC2Tf4aOlfm8uWH4Cj05ZIZ/O35wvA1Urxcsjl3WUcTf2lCa1kvPtJwEBBBBAAIGSCOgflZ65Kl1a1jV7ln+xJFNe+mFtSS7NuQgggEBYgYUZe4x9DP81OIggUC4CZutDuWSBmyIQewIVKlSQq7o3kUm3nypt61fLBzB5caYMeH5Gvnkz8h1IgisEdE+Ld35any+vepGYr+4+Xa7t2ZRef/l0SEAAAQQQKC2BaurHx9eGdZOUpHjjkv/+epVMW77NSCOCAAIIlIZAcA/A9LQapXFZroEAAiUQoAGwBHicikBJBVrVqyYT/9BXhvZqmu9SGbsPyRUvz5JXflwrehJdgjsFfD6fPDRpmdirUK/w+9QVndXiMN2lUXWGQrizZsk1Aggg4C6Bk2pXkefVCAT7LBPqLUr++MFC5iB2V1WSWwQcL6AXN1yZac5tTg9Ax1cbGYwBARoAY6CSKaKzBZLUwg//vLSjjLnulHy/zOeqVqPHpq6UEWN/kR3Z+eeNc3bJyJ0WmLJkq/z8224D49YzWsjgbmmie4ISEEAAAQQQiJbAGW3qyv3ntzVutz8nV256Z57oFeoJCCCAQGkILNuSJfp7jD/oHx46N071R/mLAALlJEADYDnBc1sEggXO71hfpqpFILo1zd89fvqvO+SC52bIjNU7gk8j7mCBQ0fyRM/9Zw+6x59eEZqAAAIIIIBAeQiMPL25XJLe0Lj1OrVa551q/uE82xd24wAiCCCAQAQCCzbuNY5urUY9VVHzXhMQQKB8BWgALF9/7o6AIaAbhyaM7CV3nNlS9Q4zdsnO/Tky9I058rjqEXg075i5k5gjBV6ZvlY27z1k5O3vA9qpxV/ijDQiCCCAAAIIREtA9z5/4vLO0rFRinHLH9WPjU9+tdJII4IAAggURyB4/r8ujasX5zKcgwACpSxAA2Apg3I5BEoqEB9XUe45t421Kmy9lEr5LjdGzQk4eMxPkrH7YL59JDhHYNOeg/Jy0OqKvZrXlAtUT08CAggggAAC5Smgf4h6dWg3qV010cjGKz/+Jp8tzL9ivXEQEQQQQKAQgeAGwPQmNAAWQsZuBKIiQANgVJi5CQKRC/RpUVum3HmanNm2br6T9ZvqhWpI8OTFW/LtI8EZAo9NWSk5uSd6auq5T0Zf3IF5/5xRPeQCAQQQiHmBhmrUwctq/uGEOHPIwZ8/XixLNmXFvA8ACCBQPAE9amnTHnMEDAuAFM+SsxAobQEaAEtblOshUIoCtapWkjeGd5MHB7bP9wE9W03affv7C+QvnyyWmWt2ytLNWdZw0wMqXa88Syg/gVlrd8oXSzKNDFynVnpuW98cbmUcQAQBBBBAAIEoC3RvVlMevqSjcVf949XId+ey+JihQgQBBIoqsDBo/r/kxDjRcwASEECg/AWYibP864AcIFCggJ6r54ZTT5Ie6kP6HePny/pd5tDfCb9kiP5nD/rX/NTKiVIjOUGqq3/27erJiSqeoPYl/r7v+DE6rt+gWZnWLhn5dq6an/HhScuNE3Ud/Omc1kYaEQQQQAABBJwgcHWPJrJ8yz559+cNgexkZh2WW9+bJ+/f1EsS4+kvEIBhAwEEChUIHv7bqVGqxOmhMAQEECh3ARoAy70KyAACRRPo1DhVJqshwf+YuFQ+XVDw/DxH83zWoiG6C34kIVTDoW68Ot6QeLzh8Hj8xLZuUKxCw2GAefycjbJya3Ygrjf0nI7aiYAAAggggIATBf5xUXtZtS1b5qzbHcje3A17ZNTny+SxQZ0CaWwggAAChQkENwAy/19hYuxHIHoCNABGz5o7IVBigaqV4uXpq9Klb8va8uBnS+XgkbwSX9N+gZI2HOrGwQapSfI/fU+S/iHmLrTfy4vbew4ckX9//atRtLb1q8k1qncFAQEEEEAAAacKJKgFyF669mS55H9nGqvX6x+1OjRMET2NBQEBBBAoTODYMZ8sUnOV20PXNBYAsXuwjUB5CtCnvzz1uTcCxRS4/JTGMvmOU+UK9bd57SpSs0qilGfPen/D4Zrt+2XG6p1yw9u/GL0IillM15329De/Staho0a+9cIfDHswSIgggAACCDhQoLaad/iVoadIUoL59WC06gU4+7ddDswxWUIAAacJ/LbzgOh5yu0hPa2GPco2AgiUowA9AMsRn1sjUBKB5nWqyr8HdwlcQv/itv9Iruw9cFT2Hjoiew/qv+rfwd+3rbh/W/1V+7J+PyZPnVuaQV/ujxMWyNS7TpdU1SswFsKKzH0ybvaJ+ZN0mQd0biC9mteKheJTRgQQQAABDwh0VHN1PXVFFzXn8IJAaXLVm/pt4+bLZ7f3lcY1kgPpbCCAAALBAsHDf+unJEl9NTqIgAACzhCgAdAZ9UAuECixQEXVBTAlKcH610SK/gHd33BoNQaqBsE9usHQahw8orZ1A+LxBkW9/8S+442LBTUcblETiP/l08XWkCKvLyyiV13WPSTs7ai6B8XfLmxX4nrlAggggAACCERT4KIuDUX/qPXSD2sDt92lprgY+c48+eTWPlJZzftLQAABBEIJLMzYYySnM/zX8CCCQHkL0ABY3jXA/REoZwF7w2FazaJnRjd66S7+/oZD3evwhe/WGEN/py7daq1QrFcY9HKYsmSrzLZNnK7Lemu/ltKoemUvF5uyIYAAAgh4VEAvXqUXtPpu5fZACZerRsH7Pl4kL1zdVbz+w16g0GwggEBEAsE9ALvQABiRHwcjUNYC5iQfZX03ro8AAp4R0B/+dY/DtJrJolcoPq1VHXl+SFe12q055PehSctkzXZzVVzPIKiCHFILsTw6ZYVRJN3wd3O/5kYaEQQQQAABBNwioOeufXZIujSvU8XI8uTFmUbPQGMnEQQQiGmBw0fzZGWm+ZmfHoAx/UhQeAcK0ADowEohSwi4VUDP8fHk5Z2N7B8+ekxuf3+B6A8FXgxjflxrrJioy/j3Ae3UJOoMkfJifVMmBBBAIFYE9I98rw3rJtWSzAFDT321Sp7+epXokQAEBBBAwC+wdHOW6DlD/UEvUNhZdRIgIICAcwRoAHROXZATBDwhcG6H+jKsd1OjLHoY0eNTVxppXohs2nNQdAOgPfRWi35c0LG+PYltBBBAAAEEXCnQQi04pnv3q07/RnheTfnxxw8WSk6uN3/cMwpLBAEEiiQQPPy3db1qUqWS+QNCkS7EQQggUGYCNACWGS0XRiB2BfTiF23Um749jJ21Xr5dsc2e5Prtx6asVF9+jgXKoX/pHHVxe+ZGCoiwgQACCCDgdoH+bevKXy9om68Yny3cIte9Plt2qwVCCAgggMCCjL0GAsN/DQ4iCDhCgAZAR1QDmUDAWwJ6+OsL13SVSvHmS8x9Hy+WbfsOe6Kws9bulC+WZBplua5XU2lbP8VII4IAAggggIDbBUae3kL+eUkH0T902cMv6/fIoJdmyrqdB+zJbCOAQAwKLNxIA2AMVjtFdpmA+e3cZZknuwgg4FwB3e3/wYHtjQzqXgJ/+nChHLPND2Ic4JJIbt4xeXjSciO3evGTP53T2kgjggACCCCAgFcEhvZuJm8M7y5VEs05btfvOiiXqUbAOet2e6WolAMBBCIU2JGdk29O7PQm1SO8CocjgEBZC9AAWNbCXB+BGBa4tmcTOa9DPUNg5ppd8sr034w0t0Xen7NR9LyG9nDPuW3UCsiJ9iS2EUAAAQQQ8JSAHg780S19pH5KklGuvQePWsOBJy7YbKQTQQCB2BBYFDT8V/9Q0KquOR1QbEhQSgScLUADoLPrh9wh4GqBCmrW8CfUqsAN1OrA9vAftXpg8ETB9v1O3t6jejH+5+tfjSy2rV9NrunRxEgjggACCCCAgBcF2jdMkYl/6CvtG5hTXhxRveP1wiDPf7uaFYK9WPGUCYECBII/13dSq//GBc8ZUMD57EIAgegI0AAYHWfugkDMCuhecc9clW6sIJirhgDfOX6BZB8+6jqXp7/5VbIOmfkefXEHPuS4ribJMAIIIIBAcQXqqx/2Prqlt5ypegQGB/0+ec9Hi+SIbZGs4GOII4CAtwSCGwC7pDH811s1TGm8IkADoFdqknIg4GCBXs1ryR39Wxo53Lj7oDw4camR5vTI8i37ZNzsDUY2B3RuILp8BAQQQAABBGJJoEqleHltWDcZ0adZvmJ/On+zDHtztuw9yArB+XBIQMBjAnpu7+AhwF1pAPRYLVMcrwjQAOiVmqQcCDhc4M6zWskpTWsYuZy4cIt8On+TkebUiM/nk4cmLRP7+iVJCRXlbxe2c2qWyRcCCCCAAAJlKqCH+Ole8KMuap9vheCff9stg16eJRt2sUJwmVYCF0egnAV+27lfsnNyjVykp5mf+Y2dRBBAoNwEaAAsN3pujEBsCcTHVZRn1VDgaknxRsF1L8D1O53/5WDKkq0yO2iFw1v7tZRG1Ssb5SGCAAIIIIBArAlc3/ckeXVoN6mcYK4Q/NuOA2qF4FkybwMrBMfaM0F5Y0dgwca9RmH1IkF6mgACAgg4T4AGQOfVCTlCwLMCaTWT5bFBnYzyHTiSJ3dOWODouYIOqTw+8sVyI9+64e/mfs2NNCIIIIAAAgjEqsDZ7evJhzf3lrrVKhkEu9XiWVe/NlsmLdpipBNBAAFvCATP/5fO8F9vVCyl8KQADYCerFYKhYBzBQZ2bihXdUszMrh4U5b855tVRpqTImN+XCtbsg4bWXpgQDtJCurpYBxABAEEEEAAgRgT0Ct/6hWC29avZpRcLwhyh1r868Xv17BCsCFDBAH3C+RrAGzCAiDur1VK4FUBGgC9WrOUCwEHC4y6uL00r1PFyOErP/4mM1bvMNKcENm056DoBkB76K0W/Ti/Y317EtsIIIAAAgggoAQaqh7yeoXgfq3r5PN46qtVcv8ni+Vo3rF8+0hAAAH3CehRMiu3ZhsZpwegwUEEAUcJ0ADoqOogMwjEhkByYrw8P6SrJKp5Ae3hTx8ukp37c+xJ5b796JQVkqN6LviDmu9cdANmhQpqg4AAAggggAAC+QSqJSXIG8O7ybU9m+Tb9+HcTTLirTmSdehovn0kIICAuwSWbcmSPNsKefpzcqdGqe4qBLlFIIYEzG/fMVRwiooAAuUr0FF9OLj/grZGJnZk58h9Hy1yzPCgWWt3il78wx6G9mqqhjal2JPYRgABBBBAAIEgAb34178u7Sh6yozg38xmrtklV6gVgjN2Hww6iygCCLhJIHj4b+t61aRKJXPBPzeVh7wi4HUBGgC9XsOUDwEHC/xP32bSv405ROj7VTvkrZnryz3XuWp40sOTzIU/aiQnyN3ntC73vJEBBBBAAAEE3CCge8vfeFpzefnaU9S8uebXjtXb96sVgmdKcAOCG8pFHhFA4LjAggxzBeCuzP/Ho4GAowXMd2JHZ5XMIYCA1wT0F4OnBneR2lXNFQMfn7pSlm7OKtfivj9nY745Tf50bhupnpxYrvni5ggggAACCLhNQM+b+8HI3vne73fuPyJXvfKTTF2S6bYikV8EEFACCzeaDYBdGrMACA8GAk4WoAHQybVD3hCIAQHd+Pf0lV2Mkh5Rve/unLBADh7JNdKjFdlz4Ij85+tfjdu1a5Ai1/TIP5eRcRARBBBAAAEEEAgp0CWtulohuI+0rlfV2K/n2b3t/fny6vS1jpkCxMggEQQQCCmgp+7ZvPeQsS+dHoCGBxEEnCZAA6BDamTfvn0yYcIEueeee6Rfv37SsmVLSU1NlcTERKlbt66cccYZ8uSTT8quXbtKlOPDhw/LZ599JnfccYf07NlTatasKQkJCdbf3r17y+jRoyUzk19hS4TMyRELnK5WCrz59ObGeb/tOCAPfW4OwTUOKMPIf75ZlW9y8tEXtZc4PbMxAQEEEEAAAQSKJdC4RrJ8fGsfOa1VbeN8n0/k0Skr5e8Tl4qegoOAAALOFwgevl8lMU5a1a3m/IyTQwRiWKCCT4UYLr9jij5t2jQ555xzCs1P7dq15b333pPzzjuv0GODD1i8eLGceuqpkp1tLtUefFy1atXk9ddflyuvvDJ4V6nFN23aJGlpadb1MjIypHHjxqV2bS7kToEjqgfAFWNmyeJN5tDf/72mqwzs3DBqhVq+ZZ8MfGGG2BY0kwGdG8iL15wctTxwIwQQQAABBLwscFQ18j2oGvsm/JKRr5j6R8EX1Xu/XkmYgAACzhV46quV8uL3awMZ7NW8pkxQQ/0JzhTg+7cz6yXauaIHYLTFC7ifbhAbNmyYPPfcc/Lpp5/KTz/9JDNnzpQPPvhABg8eLHFxcbJz5065+OKLRTfmRRp0L0N/41/fvn3lsccek2+++Ubmz58vX331ldx8883WPfQx11xzjUydOjXSW3A8AsUWSIyvKM8N6Sr610N7+OunS6K2SqD+PeShScuMxj89afnfLmxnzxLbCCCAAAIIIFACgQS1QvBjgzrJ/ee3zXeV6b/ukMFjfso3tDDfgSQggEC5CgT3AExPq1Gu+eHmCCBQuAA9AAs3isoReXl5VuNbQTebOHGiXHbZZdYhgwYNkk8++aSgw/PtmzVrltW4OGrUKGnfvn2+/TpBDw/W99ANIS1atJDVq1eLXqihtAO/QJS2qHeu98m8TXLPR4uMAp3StIaaPLyXxKsvDGUZJi/eIre/v8C4xd1nt5a7zm5lpBFBAAEEEEAAgdIR+GJxptz94ULRIwHsoU61SvLm8O7SqXGqPZltBBBwgMAxNVSmy0NfS3bOifm6x1x3iugFfwjOFOD7tzPrJdq5Kttv09EujYvvp3v3FRYuvfRSadv2+C+l06dPL+zwfPv79Olj9SYM1/inT7jkkktENy7qsHbtWlm4cKG1zX8QiJbAoJMbyaXp5pDfeRv2yPPfrSnTLBw6kiePfrHCuEej6pXl5n7NjTQiCCCAAAIIIFB6AnqajfE39ZJaVRKNi+oFBq5UKwR/s3ybkU4EAQTKX+C3nfuNxj+do64sAFL+FUMOEChEgAbAQoCctrtKlSpWlvRiHmUV+vfvH7i0bgQkIBBNAd3j9J+XdpQmNZON2/7vd6tl9m8lWwTHuGBQZMyPa2VLlvn/1QMD2klSQuGN80GXIooAAggggAACEQjonv7/d1tfaVHn+Odc/6mHjubJyHfnypv/XccKwX4U/iLgAIEFG/cauWiQmiT1UpKMNCIIIOA8ARoAnVcnYXO0YsWKQI88f0/AsAeXYEdOTk7g7IoVeUQCGGxETUBP/P3ckHSJt626qxfl+OMHC2XvwSOlno9New6KbgC0h97NazGMwQ7CNgIIIIAAAmUo0KRWsnx6a1/R77/2oJcrfHjychn9+TJWCLbDsI1AOQrkn/+vejnmhlsjgEBRBWjdKapUOR138OBBax6+p59+WnTPPD1XoA533XVXmeXoxx9/DFy7LBsaAzdhA4EQAl2b1JA/ndva2JOpeujd/8niUu8F8OiUFZJjm3soTjU8jrq4fZnMf2kUiAgCCCCAAAIIBARSkxPk7f/pIVec0jiQ5t94+6cNctM7c2W/bc4x/z7+IoBAdAWCGwC7pNEAGN0a4G4IFE8gvnincVZZCowdO1auv/76sLe499575dprrw27vyQ7Fi1aJF988YV1iQ4dOoRdLKSwe+hJRgsKmZmZBe1mHwKWwC2nt5CZa3aqfyeG/n61bJu8P2ejXNuzaakozVq7U6Ys2Wpc67qeTaRt/RQjjQgCCCCAAAIIlL1AYnxFeeqKztJM9Qj899e/Gjf8ftUOuVKtEPzmiO5SXw05JCCAQPQF9LzZK7dmGzdOpwHQ8CCCgFMFaAB0as2EyFd6erqMGTNGevbsGWJvyZP00N8bb7wx0Mvw0UcfLfZF09LSin0uJyLgF6ioeuI9fWW6nP/sdNlz8Kg/WR6etFy6N6spretVC6QVZyM375g89Ply49QaqvfB3eeYPQ+NA4gggAACCCCAQJkK6PmAbz+zlaSp+YDv+2ixHFHv1/6wPHOfXPriTHljRDfp0JAVgv0u/EUgWgJLt2RJnp6b5/egZ+zp1Ij/F/0e/EXAyQIMAXZg7ejVfpcsWWL9mzNnjowfP14uu+wya/4/3fNv8uTJZZLr22+/XebOnWtde/jw4XLxxReXyX24KAKRCOgJhf89uItxih6ue+f4BXJYTQ5ekqB7Eq7aZv6Cec+5baR6srkSYUnuwbkIIIAAAgggUDyBS9Ibybibeor+cc4etu47LINVT8DvVrJCsN2FbQSiIbAwaAEQ/YN8lUr0K4qGPfdAoKQCFXwqlPQinB8dgXfffVd0w5z+VfSNN96QESNGlNqNH3vsMfnb3/5mXe+UU04RPQ+gf8Xh4tykKEOAe/ToYV06IyNDGjfOP9dLce7LOd4V0JN/j5213ijgsN5N5eFLOhppRY3sOXBEzvj3D5J16ETPwnYNUmTyHaeKngOQgAACCCCAAALOEFi384D8z9hfRP+1B/12PbxPM+nXuo50UyMDqtIIYedhG4EyEfjDuPnyxZIT0zld3SNNHhvUuUzuxUVLT0B/P/eP0uP7d+m5uu1KNAC6rMauuuoq+fDDD63GOf0/bo0aNUpcgldeeUVuueUW6zpt2rSRGTNmSJ06dUp83YIuwAtQQTrsCyWge/vpIT/Bc468NqybnNO+XqhTCkx7YOISee/njcYxH4zsJT2DVh80DiCCAAIIIIAAAuUioH+4u/ndeTJn/e6Q99c/3ulhiL3U+3iv5jVpEAypRCICJRfo+/h3snnvocCFnri8k1zVvUkgzoYzBfj+7cx6iXauGAIcbfES3u+SSy6xrnDgwAGZOnVqCa8m1vDi2267zbpO06ZNZdq0aWXe+FfiTHOBmBRISoiTF67uKkkJ5svWfR8vkq1qdeBIwvIt++T92Wbj38DODWj8iwSRYxFAAAEEEIiiQI0qifLujT3k0vSGIe+q5yTTK5OO+XGtjHjrF+ny0NfWD4ePT10pP6zazurBIdVIRCAyge3Zh43GP312elrJO6RElguORgCB4gowWL+4cuV0nr1n3oYNG0qUi88//1yGDRsmx44dkwYNGsi3337LUNwSiXJyWQu0UnOM/GNgB/nb/y0J3GqvWhzk7g8Wyns39izS0F0968HoScvENnex1aj4twvbBa7JBgIIIIAAAgg4T6BSfJw8c1W6NK1VRZ77dnWBGfQ3CPobBekhWCAXOxEoksCijCzjuCqJcdKyblUjjQgCCDhXgAZA59ZNyJxt3rw5kF61avFfbHVj35VXXim5ublSq1Yt+eabb6RFixaBa7OBgFMF9DwjM1bvkKlLtway+NNvu6xf/P/Qv2UgLdyGnrNkzjpz+NCt/VpKw+qVw51COgIIIIAAAgg4REDPhX33Oa3lvA711WeBTPlZfQbQjXxH8wqe1pwGQYdUINlwtcDCjD1G/js3rl6kH+CNk4gggEC5CdAAWG70xbvxRx99FDixU6dOge1INmbNmiV6KHFOTo6kpKTIV199JR06dIjkEhyLQLkJ6A/+j6uJhhepD/tbbEN/n/7mV+ndopac3CT8MIRDR/Lk0S9WGHlvpBr+bu7X3EgjggACCCCAAALOFmjfMEX0Px30+/v8jXusxkAaBJ1db+TO3QK6sd0e0ptUt0fZRgABhwvQAOiQCho7dqwMGTJEkpKSwubomWeekSlTplj7mzVrJqeeeqpx7A8//CD9+/e30vRqwfqawWHhwoUyYMAA0XMI6lV+9fX0qr8EBNwkkJqcIM8O6SpDXv0pMJRX/7J/14QF8sWdp0lKUkLI4rys5gWyNxrqgx4Y0E4NAY4LeTyJCCCAAAIIIOB8gcpqGGLflrWtfzq3NAg6v87IofsEjqnP2ouDhgB3UT0ACQgg4B4BGgAdUlejR4+We+65Ry6//HKrYU8Px9VDfLOzs2XJkiUybtw4mTlzppXbxMREee211yQ+PrLqW7t2rZx33nmyd+/xX27+9a9/SWpqqixdujSsQt26dUX/IyDgNIEeJ9WUO85sZcwBlLH7kDzwf0vluSHponsK2sOmPQflFdUAaA99VI/B8zvWtyexjQACCCCAAAIuFwhuEDx4JFfmb9gb6CG4aBNDhl1exWS/HATW7tgv2Tm5xp270gPQ8CCCgNMFImtBcnppXJ6/3bt3Ww17unEvXGjcuLG8+eabcvbZZ4c7JGz6jBkzZPv27YH9d999d2A73MaoUaNEN04SEHCiwB1ntpRZa3fKL+tPzEfy+aItcnrrOnLFKY2NLD86ZYXk5B4LpOnJwEdd1CFfQ2HgADYQQAABBBBAwBMCyYnxcmqr2tY/XaDSahDs3DhVejWvZf3r1rSGVKnEVytPPDAUIqTAgqDhvw1Sk6ReSvjRayEvQiICCJSrAO9S5cp/4uZ6UY5p06bJ999/LytWrJBt27bJrl27rCHB9erVk/T0dBk4cKC1cEdycvKJE9lCIIYF4uMqWkOBL3h2uuw7fOIXyX98tlTNBVhdmtc5vlCObiScsuTEoiGa7LqeTaRN/WoxrEfREUAAAQQQiE2B0moQXLBxr+h/L/+w1loIQTcI3q4WJDurXb3YhKXUnhbIN/9fGsN/PV3hFM6TAhV8KniyZBTK0QKbNm2StLQ0K48ZGRmiezYSECiuwBS1su9t4+Ybp3dslCKf3tpXVEc/GfD8f2XVtuzA/hpqDsHv7z1DqicnBtLYQAABBBBAAAEEtEBxegja5R4b1Emu7tHEnsQ2Aq4XuPC5GbI8c1+gHH+9oK1aSK9FIM6GswX4/u3s+olW7ugBGC1p7oMAAmUmcGGnBuqDdpqMn5MRuMfSzfvkqa9WSlrNZKPxTx9wz7ltaPwLSLGBAAIIIIAAAnaBkvYQ1CMRWterJqeoYcEEBLwgoBfWsf+YrsuUTg9AL1QtZYgxARoAY6zCKS4CXhX4x8AO1lyAa7bvDxTxtRnrJFmtDGgP7Rqk8Ku8HYRtBBBAAAEEEChQINIGwaN5Prn1vXky6Y5TmSOtQFl2ukVg6ZYsyVOrAPuDnku7kxryTkAAAXcJVHRXdsktAgggEFpAr/j3/JCukqjmBbSHg+oXS3sYfVF7a54eexrbCCCAAAIIIIBAUQX8DYL3ntdGPr61jywada6M6NPMOH17do7VCHjEtgCZcQARBFwksFDNdWkPuoer/v+AgAAC7hIwvym7K+/kFgEEEDAE2jdMkb9e2NZIs0cGdm4gPdVqfQQEEEAAAQQQQKC0BHRDyAMD2knfluZnjPmq0WT0pGWldRuug0C5CbAASLnRc2MESlWABsBS5eRiCCBQ3gL6F/gz29bNl42khIrytwvb5UsnAQEEEEAAAQQQKKlAvBqB8MLVJ0uj6pWNS70/e6Oao3ijkUYEAbcJ5G8AZPiv2+qQ/CKgBWgA5DlAAAFPCVSoUEGeuqKz1K1WySjXbWe0lIZBH8qNA4gggAACCCCAAAIlEKhZJVFeHXaK6B8d7UEvCjJvwx57EtsIuEZge/Zh2bz3kJHf9DQWuDFAiCDgEgHz3cklmSabCCCAQEECtapWkleGniINU5Oswy7oWF9Gnt68oFPYhwACCCCAAAIIlFigQ8NUeeLyzsZ1/IuCbNt32EgngoAbBILn/6ui5t1uWbeqG7JOHhFAIEiAmTuDQIgigIA3BLo2qSHf3XuG5Bw9JtWS4qWiWq2MgAACCCCAAAIIlLXAJemNZOnmLHltxrrArfyLgowf2UsqxccF0tlAwOkCwcN/OzeuzoJ6Tq808odAGAF6AIaBIRkBBNwvkJQQJ6nJCTT+ub8qKQECCCCAAAKuErj//LahFwX5fLmrykFmEQhuAExvUh0UBBBwqQANgC6tOLKNAAIIIIAAAggggAACzhTQi4L8r1oUpHENc1EQvSCIXhiEgIAbBPKO+WTxpiwjq+lpNAAaIEQQcJEADYAuqiyyigACCCCAAAIIIIAAAu4QqKEXBRnaLd+iIKM+14uC7HZHIchlTAv8tmO/7M/JNQy60gBoeBBBwE0CNAC6qbbIKwIIIIAAAggggAACCLhGoH3DFHnyii5GfvWiILe8N19YFMRgIeJAgQUZe41c6QX26qYcX2TP2EEEAQRcIUADoCuqiUwigAACCCCAAAIIIICAGwUu7tJQRp7e3Mj6juwc1Qg4T3Jy84x0Igg4SYD5/5xUG+QFgZIL0ABYckOugAACCCCAAAIIIIAAAgiEFfjzeW3k1Ja1jf0LNu6V0Z8vM9KIIOAkgYXqGbUH5v+za7CNgPsEaAB0X52RYwQQQAABBBBAAAEEEHCRgF4U5IWru0pazeBFQTJk3OwNLioJWY0VgUNH8mTVtmyjuF0aswCIAUIEAZcJ0ADosgojuwgggAACCCCAAAIIIOA+Ab0oyCvX5V8URPcCnLueRUHcV6PezvGSzVmiVwH2h7iKFaRT41R/lL8IIOBCARoAXVhpZBkBBBBAAAEEEEAAAQTcJxBuUZBbx7EoiPtq09s5Xpixxyhg63rVJDkx3kgjggAC7hKgAdBd9UVuEUAAAQQQQAABBBBAwMUCelGQm1kUxMU1GBtZz7cASBrDf2Oj5imllwVoAPRy7VI2BBBAAAEEEEAAAQQQcJzAn89vK6e1YlEQx1UMGQoIBC8A0pUGwIANGwi4VYAGQLfWHPlGAAEEEEAAAQQQQAABVwro+dRYFMSVVRcTmd6+77BsyTpslDW9CT0ADRAiCLhQgAZAF1YaWUYAAQQQQAABBBBAAAF3C1RPTpRXh3aTyglxRkFYFMTgIFIOAsHDf6tWipcWdaqWQ064JQIIlKYADYClqcm1EEAAAQQQQAABBBBAAIEiCrRrkCJPDe5sHH00zycsCmKQEImyQHADYGe1+q/utUpAAAF3C9AA6O76I/cIIIAAAggggAACCCDgYoGBndWiIP2aGyXYkZ0jt7w3T3Jy84x0IghEQyC4ATCd+f+iwc49EChzARoAy5yYGyCAAAIIIIAAAggggAAC4QX+fF7oRUFGfbZMfD5f+BPZg0ApC+Qd88niTVnGVbvQAGh4EEHArQI0ALq15sg3AggggAACCCCAAAIIeEIg3KIgE37JkHGzN3qijBTCHQJrtu+X/Tm5RmZZAdjgIIKAawVoAHRt1ZFxBBBAAAEEEEAAAQQQ8IpAuEVBHpq0TOau3+2VYlIOhwtMXLjZyGHD1CSpm5JkpBFBAAF3CtAA6M56I9cIIIAAAggggAACCCDgMYFwi4Lc8t582Zp12GOlpThOEzh8NE/GzzF7nJ7Tvp7Tskl+EECgmAI0ABYTjtMQQAABBBBAAAEEEEAAgdIWCLUoyM79LApS2s5cL7/A5wu3yN6DR40dQ3s3M+JEEEDAvQI0ALq37sg5AggggAACCCCAAAIIeFAg1KIgemXWf0xkURAPVrcjiqQXm3lr1nojL6e1qi0t61Y10ogggIB7BWgAdG/dkXMEEEAAAQQQQAABBBDwoIB/UZAmNZON0n0wN0PeY1EQw4RI6Qj8sn6PrMjcZ1zs+r7NjDgRBBBwtwANgO6uP3KPAAIIIIAAAggggAACHhSwFgUZdopUTogzSvfQ58vkFxYFMUyIlFxg7Kx1xkWa1kqWM1rXNdKIIICAuwVoAHR3/ZF7BBBAAAEEEEAAAQQQ8KhA2/op8tTgzkbpco/55Fa1KEhm1iEjnQgCxRXYsveQfLVsm3H6MDX3X8WKFYw0Iggg4G4BGgDdXX/kHgEEEEAAAQQQQAABBDwsoBcFuaVfC6OExxcFmS961VYCAiUVeO/nDZKnGpb9ITkxTgZ3a+yP8hcBBDwiQAOgRyqSYiCAAAIIIIAAAggggIA3Be47r42c3rqOUbhFelGQz5aKXryBgEBxBXQj8vg5G43TLz+5saQkJRhpRBBAwP0CNAC6vw4pAQIIIIAAAggggAACCHhYQC8K8vyQdAleFOTDuZtYFMTD9R6Non2+aIvsOXjUuNXwPk2NOBEEEPCGAA2A3qhHSoEAAggggAACCCCAAAIeFvAvCqKHZ9oDi4LYNdiORED3Hn171nrjlNNa1ZaWdasZaUQQQMAbAjQAeqMeKQUCCCCAAAIIIIAAAgh4XMBaFOSKLkYpWRTE4CASgcDcDXtk2ZZ9xhnD1eIfBAQQ8KYADYDerFdKhQACCCCAAAIIIIAAAh4UGNC5gdx6BouCeLBqo16ksUG9//QQ8/5t60Y9H9wQAQSiI0ADYHScuQsCCCCAAAIIIIAAAgggUCoC957bRvo5fFGQo3nHZMOuAzJj9Q4ZN3uDvPLjWlmwcU+plJ+LlFwgM+uQfLl0q3GhYb2bip5vkoAAAt4UiPdmsSgVAggggAACCCCAAAIIIOBNgeOLgnSVi1/8r2pkOxgopF4UpFOjVBkapWGc+w4flY3q/ht3H7Tyof9m6O3dB2TL3sOSd8xcoTheNS69OuwUObNtvUCe2SgfgXE/bzTqp3JCnAzullY+meGuCCAQFQEaAKPCzE0QQAABBBBAAAEEEEAAgdITSE1OkFeHdpPLXpopB4/kBS780KTl0qZ+ivQ4qWYgrbgbugFP9xTTDXv+hj5rW8fVv71Bq8cWdh89X+GDE5dJ7z/VlspBi5kUdi77S0/g8NE8eX/ORuOCg05uJKmVE4w0Iggg4C0BGgC9VZ+UBgEEEEAAAQQQQAABBGJEoE39avLvwV3ktnHzAyXWjWy3jZsnk+44VRqkVg6kh9s4kJMb6MGne+/phr0N6p/e3rTnoBzNM3vxhbtOUdM37z0kr07/Te46u1VRT+G4UhaYvDhTdh84Ylx1eJ9mRpwIAgh4T4AGQO/VKSVCAAEEEEAAAQQQQACBGBG4sFMDuU0tCvLSD2sDJd65/4jc8u48+eDm3pIYV1G2Z+dY8/Hpxr3jQ3SPN/TpbX1sWYZqleIlPq6C7LH1Fnz5xzVquGljaVi98AbKssxbLF7b5/PJ2FnrjKL3bVlLWterZqQRQQAB7wnQAOi9OqVECCCAAAIIIIAAAgggEEMC96hFQZZn7pMfVu0IlHrRpiw5/cnvJevQUcnJPRZIL+0NvWaE7mmoV5C1/tX6/a+KN1XbeljpisxsGfjCDPFPCXj46DF54suV8tyQrqWdHa5XiMB8tRDL0s37jKOGR2nOSOOmRBBAIOoCNABGnZwbIoAAAggggAACCCCAAAKlJ6AXBXnuqvyLguief6URktV8ff4GPt2op7fTrAa+KtJI9eJLjK9Y4G3aN0yRq3s0UasBn5h37rOFW2Ror6bSrVnJ5yos8ObsNATemrneiDeuUVnOaseiLAYKEQQ8KkADoEcrlmIhgAACCCCAAAIIIIBA7AiEWxSkqAL1U5KMHny6oU838unGvlpVEqVCBdXVrwThT+e0ls8XbZHsw7mBq+gFSz77Q1+pqLsREspcYGvWYfly6VbjPsN6NxXdgExAAAHvC9AA6P06poQIIIAAAggggAACCCAQAwJ6UZCnr+wit7+/QPRiIPaQlFAx0IvP6r2nG/d+783XuEayJCXE2Q8v9e1aVSvJH89uLf+cvDxw7SWbs+ST+ZvUfIBpgTQ2yk5g3OwNxnNRWdX5Vd2alN0NuTICCDhKgAZAR1UHmUEAAQQQQAABBBBAAAEEii9wfscG8tntyTJn3W5JSUqw5uHTvfjqVKtU4l58xc/V8TN1b7P3VSPU2h0HApd64stVcn7H+lJN5ZVQdgI5uXkyfs6JIdj6Tpd2bSS65ygBAQRiQ6DgyRpiw4BSIoAAAggggAACCCCAAAKeEejQMFWu73uSXH5KY2uOvbpqeG9Jh/CWBk6CWpH4gYHtjUvt3J8jL35/YgVjYyeRUhP4YnFmvhWfR/RpVmrX50IIIOB8ARoAnV9H5BABBBBAAAEEEEAAAQQQ8IRA/zZ1pX+bOkZZ3vzvOtmw60SvQGMnkRIL+Hw+GTtrvXGd3s1riR4yTkAAgdgRoAEwduqakiKAAAIIIIAAAggggAAC5S6gewHG2xaeOJJ3TB75YkW558urGViQsVcWb8oyijeibzMjTgQBBLwvQAOg9+uYEiKAAAIIIIAAAggggAACjhFoUaeqDA8afvr18m0yc81Ox+TRSxkZO3O9UZxG1SvL2e3qGWlEEEDA+wI0AHq/jikhAggggAACCCCAAAIIIOAogTvPaiU1qyQaeXp40nLJVb0BCaUnsG3fYZmyJNO4oF6MJc7WA9PYSQQBBDwrQAOgZ6uWgiGAAAIIIIAAAggggAACzhRIrZwg95zb2sjcqm3Z+VaqNQ4gErHAuNkbJfeYL3BeUkJFuap7WiDOBgIIxI4ADYCxU9eUFAEEEEAAAQQQQAABBBBwjMCQ7k2kbdBCFP/55lfZe/CIY/Lo5ozk5ObJ+6oB0B4u69pIqiebPS/t+9lGAAHvCtAA6N26pWQIIIAAAggggAACCCCAgGMF9DDUURd1MPK39+BReXbaaiONSPEE9NDfnftzjJOD5140dhJBAAFPC9AA6OnqpXAIIIAAAggggAACCCCAgHMFereoJRd0rG9k8N2fN8hqNRyYUDKBsbM2GBfo1bym6nGZYqQRQQCB2BGgATB26pqSIoAAAggggAACCCCAAAKOE/jbhe0kMf7EV9M8NWfdw5OXi893Yu46x2Xa4RlasHGPLMrYa+RyRNDKy8ZOIggg4HmBE6+yni8qBUQAAQQQQAABBBBAAAEEEHCaQFrNZBl5WnMjWzNW75TvVm430ogUXeDtWeuNgxtVryxnt6tnpBFBAIHYEqABMLbqm9IigAACCCCAAAIIIIAAAo4TuPWMFlK3WiUjX//6YoUcyT1mpBEpXGB79mH5Qs3/Zw/X9Woq8XF8/bebsI1ArAnwChBrNU55EUAAAQQQQAABBBBAAAGHCVSpFC9/uaCtkat1Ow9IcE824wAiIQX0yr9H804Mn66khlcP6Z4W8lgSEUAgdgRoAIyduqakCCCAAAIIIIAAAggggIBjBS5NbyTpadWN/D3/7WrZkW2uZGscQMQQ0D0mx6kGQHvQrjWqJNqT2EYAgRgUoAEwBiudIiOAAAIIIIAAAggggAACThOoWLGCjLqovZGt7Jxc+c/Xq4w0IuEFpi7NzNdgOpzFP8KDsQeBGBKgATCGKpuiIoAAAggggAACCCCAAAJOFujapIYM6trIyOIHczNk6eYsI41IaIG3Zq43dvQ4qaa0b5hipBFBAIHYFKABMDbrnVIjgAACCCCAAAIIIIAAAo4U+PP5bSU5MS6QN5+azu7hScvFpzcIYQUWZuwV/c8eRtD7z87BNgIxLUADYExXP4VHAAEEEEAAAQQQQAABBJwlUD81SW5TqwLbw5z1u/OtbGvfz7bkWzClgXI8t309aBBAAAFLgAZAHgQEEEAAAQQQQAABBBBAAAFHCdx4WnNpXKOykafHpqyUw0fzjDQixwW2Zx+WyYu3GBzX9Woq8XF85TdQiCAQwwK8GsRw5VN0BBBAAAEEEEAAAQQQQMCJAkkJcfL3C9sZWdu895C8Ov03I43IcYHxszPkaN6JIdKJ8RXl6h5N4EEAAQQCAjQABijYQAABBBBAAAEEEEAAAQQQcIrA+R3rS0+1iIU9vPzDWsnMOmRPivntI7nHZNzsDYbDJV0aSs0qiUYaEQQQiG0BGgBju/4pPQIIIIAAAggggAACCCDgSIEKFSrIPy5qLxUrnMjeITUE+ImpK08ksCVTl2bK9uwcQ2I4i38YHkQQQECEBkCeAgQQQAABBBBAAAEEEEAAAUcKdGiYKkOChrJOXLhF5m3Y7cj8lkem3p613rht92Y1pGOjVCONCAIIIEADIM8AAggggAACCCCAAAIIIICAYwXuOae1VEuKN/L30KTlcuzYiTnvjJ0xFFm8aa/M37jXKPGIPicZcSIIIICAFqABkOcAAQQQQAABBBBAAAEEEEDAsQK1qlaSu85qZeRv8aYs+XTBZiMtFiNjg3r/1U9JknM71ItFCsqMAAKFCNAAWAgQuxFAAAEEEEAAAQQQQAABBMpXYFjvZtK8ThUjE098uVL25+QaabEU2bk/RyYvyjSKPLR3U0mI42u+gUIEAQQsAV4ZeBAQQAABBBBAAAEEEEAAAQQcLZAYX1EeHNDeyOMOtfDFi9+vMdJiKTJ+9kY5kncsUGRtNKR7WiDOBgIIIGAXoAHQrsE2AggggAACCCCAAAIIIICAIwX6t60rZ7SpY+TtjRnrZOOug0ZaLESOqoa/92ZvMIp6cZeGoodLExBAAIFQAjQAhlIhDQEEEEAAAQQQQAABBBBAwHECD6hegPEVKwTypXvAPTJleSAeKxtfLt0q2/blGMUd0aeZESeCAAII2AVoALRrsI0AAggggAACCCCAAAIIIOBYgZZ1q4qeD9Aevlq2TWat2WlP8vz220GLf3RrWkM6Nkr1fLkpIAIIFF+ABsDi23EmAggggAACCCCAAAIIIIBAlAX0isA1qyQad3148nLJtc2HZ+z0WGTp5iyZu2GPUarh9P4zPIgggEB+ARoA85uQggACCCCAAAIIIIAAAggg4FCB1OQEuefc1kbuVm7NlvG/ZBhpXo2MDer9Vy+lkpzfsb5Xi0u5EECglARoACwlSC6DAAIIIIAAAggggAACCCAQHYEh3ZtI2/rVjJs9/fUqyTp41EjzWmTX/hz5fNEWo1jX9WwqCXF8tTdQiCCAQD4BXiXykZCAAAIIIIAAAggggAACCCDgZIE4tRDIPy5qb2Rxj2r8e/bbX400r0UmqF6OR3KPBYqVqBr+ru7ZJBBnAwEEEAgnQANgOBnSEUAAAQQQQAABBBBAAAEEHCvQp0VtuSBo6Os7P22QNduzHZvnkmTsqJrj8F1VPnsY2KWB1K5ayZ7ENgIIIBBSgAbAkCwkIoAAAggggAACCCCAAAIIOF3gbxe2k8T4E19r84755OHJK8Tn8zk96xHn72u12vHWfYeN867vc5IRJ4IAAgiEEzjxShnuCNIRQAABBBBAAAEEEEAAAQQQcKBAWs1kuek0sxFs+q875PtV2x2Y25JlaeysdcYFTm5SXTo1TjXSiCCAAALhBGgADCcT5fR9+/bJhAkT5J577pF+/fpJy5YtJTU1VRITE6Vu3bpyxhlnyJNPPim7du0qtZx9+eWXMmjQIGncuLFUqlTJ+qvjOp2AAAIIIIAAAggggAACCLhB4LYzWkrdauYw2H+qXoD2ufLcUI6C8rh0c5b8sn6PccjwPs2MOBEEEECgIIEKqmu09/pGF1Rih+6bNm2anHPOOYXmrnbt2vLee+/JeeedV+ix4Q7QVX7LLbfIq6++Gu4QGTlypIwZM0YqVKgQ9piS7Ni0aZOkpaVZl8jIyLAaH0tyPc5FAAEEEEAAAQQQQACB2BX4ZN4mueejRQbAAwPayY2nNTfS3Bq5T5XtI1VGf9ANnv+9/0xj+LN/H38RCBbg+3ewSGzG6QHooHrXDWLDhg2T5557Tj799FP56aefZObMmfLBBx/I4MGDJS4uTnbu3CkXX3yxLF68uNg5f+CBBwKNf127dpXx48fLnDlzrL86roNuHHzwwQeLfQ9ORAABBBBAAAEEEEAAAQSiJXBZ10bSJa26cbvnpq2WnftzjDQ3RnYfOCKfLdpiZP3ank1p/DNEiCCAQGEC9AAsTChK+/Py8qwGvoJuN3HiRLnsssusQ/RQ3U8++aSgw0PuW7NmjbRr105yc3OlW7duMn36dKlcuXLg2IMHD1pDkOfOnSvx8fGycuVKadGiRWB/aW3wC0RpSXIdBBBAAAEEEEAAAQQQ0ALzN+6RQS/NMjCu7pEmjw3qbKS5LfLi92vkqa9WBbKdEFdBZv3lLKkTNOw5cAAbCAQJ8P07CCRGo/QAdEjF6959hYVLL71U2rZtax2mG+6KE5555hmr8U+f+8ILLxiNfzotOTnZStfbupHw2Wef1ZsEBBBAAAEEEEAAAQQQQMDRAic3qSG6J6A9TPglQ5ZtybInuWo7N++YvPfzBiPPAzs3pPHPECGCAAJFEaABsChKDjqmSpUqVm4OHzaXfy9KFvXcf5999pl1qG5I7NWrV8jTdHqbNm2sfbrXIdNEhmQiEQEEEEAAAQQQQAABBBwmcP/5baVywonOFXrG+4cmLXftd5qvl2+TzCzzu98IFv9w2FNHdhBwhwANgO6oJyuXK1askIULF1rb/p6AkWR/3bp1snnzZusUvdJwQcG/X3cVXr9+fUGHsg8BBBBAAAEEEEAAAQQQcIRA/dQk+UN/cwqjOet2y5QlWx2Rv0gzMXbWeuOUdDXPYfBch8YBRBBAAIEwAjQAhoFxSrKek2/16tXy9NNPS//+/UXPFajDXXfdFXEWdQOiPxTWgGjfbz/Pfz5/EUAAAQQQQAABBBBAAAEnCuiVfxtVPzHPuc7jo1NWyOGjx79LOTHPofK0fMs+0Y2X9nB932b2KNsIIIBAkQXii3wkB0ZNYOzYsXL99deHvd+9994r1157bdj94XZkZGQEdjVu3DiwHWpDr0jsD/bz/GmF/dU9BwsKmZmZBe1mHwIIIIAAAggggAACCCBQLIEkNQT47wPayW3j5gfO37z3kLw2/Te546xWgTSnb7wd1PtPL/pxQccGTs82+UMAAYcK0ADo0IoJla309HQZM2aM9OzZM9TuQtOys7MDx1StWjWwHWrDP9eg3rd///5QhxSYZm9ALPBAdiKAAAIIIIAAAggggAACpSxwQcf60vOkmjLb1oPupR/WyuBuaaKHCTs97DlwRCYuPD59kz+v1/ZsIonxDOLze/AXAQQiE+DVIzKvqBytV/tdsmSJ9W/OnDkyfvx4ueyyy6z5/3TPv8mTJxcrH/aFQxITEwu8RqVKlQL7Dx06FNhmAwEEEEAAAQQQQAABBBBwukCFChXkHxe1F/UnEA6pIcBPfLkyEHfyhl69OCf3WCCLCXEV5BrVAEhAAAEEiitAD8DiypXhedWrVxf9zx+6d+8uQ4YMkXfffVeGDx8ul1xyibzxxhsyYsQI/yFF+puUdOKXriNHjhR4Tk5OTmB/5crm/BmBHQVsFDZsWA8B7tGjRwFXYBcCCCCAAAIIIIAAAgggUHyBDg1TZUj3JjJ+zsbARf5vwWYZ2rupnNykRiDNaRu5ecfkvZ83GNka0KmB1K124vucsZMIAgggUAQBegAWAckphwwdOlQGDx4sx44dk9tvv1327NkTUdaqVasWOL6wYb0HDhwIHFvYcOHAgbYNPcdgQf8aNGDuChsXmwgggAACCCCAAAIIIFAGAvee21qqJZn9Xh6atFx9p/KVwd1K55LTVmwTPWehPQzv08weZRsBBBCIWIAGwIjJyvcE3ftPB91AN3Xq1IgyY1/4o7BFOuw9+JjPLyJmDkYAAQQQQAABBBBAAAGHCNSqWknuClr4Y1HGXtE9AZ0axgYt/tElrbp0dXCPRac6ki8EEDAFaAA0PRwfq1OnTiCPGzaY3cIDO8JstG/fPrBn5cqC576w72/Xrl3gPDYQQAABBBBAAAEEEEAAATcJDOvdTJrXrmJkWc8FeCAn10hzQmRF5j75+bfdRlZG9GlqxIkggAACxRGgAbA4auV4zubNJ36pinRo7kknnSQNGza0cv/jjz8WWIrp06db+xs1aiTNmjUr8Fh2IoAAAggggAACCCCAAAJOFdAr5z448ERnCJ3P7dk58tIPaxyX5Xd+Wm/kqbbqwXihmv+PgAACCJRUgAbAkgpG+fyPPvoocMdOnToFtouyoVfC8g8h1j38fv7555Cn6XR/D0B9vD6PgAACCCCAAAIIIIAAAgi4VaB/27rSr/WJ0VS6HIg3s64AAC+fSURBVK9NXye3vjdPnv92tUxbfnzePZ+v/OYG3HvwSL6hyXrl30rxcW5lJ98IIOAgARoAHVIZY8eOlcOHDxeYm2eeeUamTJliHaN75Z166qnG8T/88IPVWKcb7MKtEPzHP/5R4uOPT4J7xx13yKFD5uSyOq7TddDH6eMJCCCAAAIIIIAAAggggIDbBR4c2E7iK57o3HBErbY7delWefqbX+XGd+ZK38e/k/SHv5GrX/1ZHlYLhXw8b5Ms25IlR3KPRaXoH/ySIYePnriXzut1qgGQgAACCJSGgLkcUmlckWsUS2D06NFyzz33yOWXX2417LVo0UL0EN/s7GxZsmSJjBs3TmbOnGldOzExUV577bVAQ14kN2zdurXce++98vjjj8vcuepNrm9fuf/++0Xfb+3atfLEE0/IggULrEved9990qpVq0guz7EIIIAAAggggAACCCCAgCMFWtatJno+wDdnrgubv6xDR+Wn33ZZ//wHJcRVkBZ1qkr7hinSvsHxf+3U3xpVEv2HlPhvnlqV+J2fNhjX0UN/66YkGWlEEEAAgeIK0ABYXLkyOG/37t1Ww55u3AsX9Eq+b775ppx99tnhDik0/ZFHHpHt27db19GNfUOGDMl3zg033CD/+te/8qWTgAACCCCAAAIIIIAAAgi4VeDuc1rJgow9smDj3iIX4WieT1Zuzbb+fSon5mRvkJpkNQjqxkDdOKj/Nq2ZLBVtvQyLepNpK44PQbYfP6JvM3uUbQQQQKBEAjQAloiv9E7+9ttvZdq0afL999/LihUrZNu2bbJr1y5JSkqSevXqSXp6ugwcOFCuvPJKSU5OLtGNK1asKG+88YbV2/DVV1+VX375RXbu3Cm1a9eW7t27y8033ywXXHBBie7ByQgggAACCCCAAAIIIICA0wSqJSXIp7f2UUN798ly/U+tuqv/6dV3sw9HtipwZtZh0f++Xbk9UMzkxDhpW79aoEFQ9xhsWz9FKqv0gsLYmeuN3Z0bp0rXtOpGGhEEEECgJAIV1CSn5TfLaUlyzrmuFti0aZOkpaVZZcjIyBDds5GAAAIIIIAAAggggAACCJSHgP5avGnPoUBjoG4cXLF1n2TsNudML07e9JqKJ9WuYvUQ9A8h1j0G61arZM3hvkr1Ljzv2enGpZ++sosMOpnvSAYKkWIL8P272HSeOpEegJ6qTgpTpgKrvynTy3NxBBBAAAEEEEAAAQQQKB8BvTSI7p6Qpqb1O6+p2tD/VDh4pKLVCLhx94Hf/x6UTXsPSq4aFhxR2CVyQP37Zan69/uJ1ZLiJa1Gshw6midnVDwQuFyKSr8oWfUYXL0ikMaGgwVanePgzJE1BE4I0AB4woItBAoWGDdY7Y/wjb7gK7IXAQQQQAABBBBAAAEEHCygJ19q8/u/QDb1aN6CR/QGDi1wQy/4qxoFrWBfT0SnT/g9nT8OF1BNx6OLPp+kwwtD9jwuUNHj5aN4CCCAAAIIIIAAAggggAACCCCAAAIIxLQADYAxXf0UHgEEEEAAAQQQQAABBBBAAAEEEEDA6wIMAfZ6DVO+0hNIVZPwsmZO6XlyJQQQQAABBBBAAAEEYlBATyqUd+yYHFXzCB7N03+PiZ5SMCGugqRWTpCKomckJLhCQK/wQkDAJQI0ALqkosimAwTuVjP2EhBAAAEEEEAAAQQQQACBEgjoJiP9RVz/q1yC63AqAgggEIkAQ4Aj0eJYBBBAAAEEEEAAAQQQQAABBBBAAAEEXCZAA6DLKozsIoAAAggggAACCCCAAAIIIIAAAgggEIkADYCRaHEsAggggAACCCCAAAIIIIAAAggggAACLhOgAdBlFUZ2EUAAAQQQQAABBBBAAAEEEEAAAQQQiESABsBItDgWAQQQQAABBBBAAAEEEEAAAQQQQAABlwnQAOiyCiO7CCCAAAIIIIAAAggggAACCCCAAAIIRCJAA2AkWhyLAAIIIIAAAggggAACCCCAAAIIIICAywRoAHRZhZFdBBBAAAEEEEAAAQQQQAABBBBAAAEEIhGgATASLY5FAAEEEEAAAQQQQAABBBBAAAEEEEDAZQI0ALqswsguAggggAACCCCAAAIIIIAAAggggAACkQjQABiJFscigAACCCCAAAIIIIAAAggggAACCCDgMgEaAF1WYWQXAQQQQAABBBBAAAEEEEAAAQQQQACBSARoAIxEi2MRQAABBBBAAAEEEEAAAQQQQAABBBBwmQANgC6rMLKLAAIIIIAAAggggAACCCCAAAIIIIBAJAI0AEaixbEIIIAAAggggAACCCCAAAIIIIAAAgi4TIAGQJdVGNlFAAEEEEAAAQQQQAABBBBAAAEEEEAgEgEaACPR4lgEEEAAAQQQQAABBBBAAAEEEEAAAQRcJkADoMsqjOwigAACCCCAAAIIIIAAAggggAACCCAQiQANgJFocSwCCCCAAAIIIIAAAggggAACCCCAAAIuE6AB0GUVRnYRQAABBBBAAAEEEEAAAQQQQAABBBCIRIAGwEi0OBYBBBBAAAEEEEAAAQQQQAABBBBAAAGXCdAA6LIKI7sIIIAAAggggAACCCCAAAIIIIAAAghEIkADYCRaHIsAAggggAACCCCAAAIIIIAAAggggIDLBGgAdFmFkV0EEEAAAQQQQAABBBBAAAEEEEAAAQQiEaABMBItjkUAAQQQQAABBBBAAAEEEEAAAQQQQMBlAjQAuqzCyC4CCCCAAAIIIIAAAggggAACCCCAAAKRCNAAGIkWxyKAAAIIIIAAAggggAACCCCAAAIIIOAyARoAXVZhZBcBBBBAAAEEEEAAAQQQQAABBBBAAIFIBOIjOZhjESgtgdzc3MClMjMzA9tsIIAAAggggAACCCCAAAIIIIBA6QnYv3Pbv4uX3h24khsEaAB0Qy15MI87duwIlKpHjx6BbTYQQAABBBBAAAEEEEAAAQQQQKBsBPR38WbNmpXNxbmqowUYAuzo6iFzCCCAAAIIIIAAAggggAACCCCAAAIIlEyggk+Fkl2CsxGIXODw4cOyZMkS68Q6depIfHz+zqi6m7K/d+CcOXOkQYMGkd+IM2JWgOcnZqu+1ArOM1RqlDF5IZ6fmKz2Uis0z0+pUcbkhXh+YrLaS7XQPEOlyumIi+lhv/5ReJ06dZKkpCRH5ItMRFcgf6tLdO/P3WJUQL/gdO/evcil141/jRs3LvLxHIiAXYDnx67BdnEEeIaKo8Y5fgGeH78Ef4sjwPNTHDXO8Qvw/Pgl+FtcAZ6h4so57zyG/TqvTqKdI4YAR1uc+yGAAAIIIIAAAggggAACCCCAAAIIIBBFARoAo4jNrRBAAAEEEEAAAQQQQAABBBBAAAEEEIi2AA2A0RbnfggggAACCCCAAAIIIIAAAggggAACCERRgAbAKGJzKwQQQAABBBBAAAEEEEAAAQQQQAABBKItQANgtMW5HwIIIIAAAggggAACCCCAAAIIIIAAAlEUoAEwitjcCgEEEEAAAQQQQAABBBBAAAEEEEAAgWgL0AAYbXHuhwACCCCAAAIIIIAAAggggAACCCCAQBQFKvhUiOL9uBUCCCCAAAIIIIAAAggggAACCCCAAAIIRFGAHoBRxOZWCCCAAAIIIIAAAggggAACCCCAAAIIRFuABsBoi3M/BBBAAAEEEEAAAQQQQAABBBBAAAEEoihAA2AUsbkVAggggAACCCCAAAIIIIAAAggggAAC0RagATDa4twPAQQQQAABBBBAAAEEEEAAAQQQQACBKArQABhFbG6FAAIIIIAAAggggAACCCCAAAIIIIBAtAVoAIy2OPdDAAEEEEAAAQQQQAABBBBAAAEEEEAgigI0AEYRm1shgAACCCCAAAIIIIAAAggggAACCCAQbQEaAKMtzv0QQAABBBBAAAEEEEAAAQQQQAABBBCIogANgFHE5lYIIIAAAggggAACCCCAAAIIIIAAAghEW4AGwGiLcz8EEEAAAQQQQAABBBBAAAEEEEAAAQSiKEADYBSxuVXxBI4ePSpjx46VAQMGSJMmTaRSpUpSu3Zt6dSpk9x4443y0UcfFXrhjRs3yr333ivt2rWTKlWqSM2aNaVHjx7y73//Ww4ePFjo+RzgDYGpU6dKhQoVAv9Gjx5dpIItW7ZMbrnlFmnZsqVUrlxZ6tSpI6effrq88sorkpubW6RrcJB7BPTrxcsvvyxXXXWVtGnTxnrNSEpKksaNG8sll1wi48ePj6jeeX7cU/ellVPec0pL0hvXmT9/vjz66KNywQUXSFpamvU5pmrVqtK6dWsZMWKEzJgxI6KCfvnllzJo0CDrNUl/JtKvTTqu0wmxJfDnP/858JlGf7754YcfCgXg+SmUyNMH7Ny5U5588knp27ev1K9f33o9atiwofTs2VPuu+8++emnnwotvz5m6NCh0qxZM9Gfjxo0aCDnn3++TJgwodBzOQABBMpZwEdAwMECixYt8nXs2NGn/jcJ+y81NbXAEkyePNmnjwl3DfUF37d27doCr8FO9wvs37/f17RpU+M5GDVqVKEFe/31133qC5Zxnv1Z6tWrl099mCr0OhzgDoEHH3zQp75Eha1vf91369bNt2HDhkILxfNTKJHnDuA9x3NVWqICqR+LCn090a8r6su0Lycnp8B7HTt2zDdy5MgCr6f36+MI3hdYuHChLz4+3ngevv/++7AF5/kJSxMzOz788ENfrVq1jGfG/7nG/1f90Fmgx0MPPeSrWLFi2GtcdNFFvkOHDhV4DXYigED5CdADUL3aEZwpsHjxYunfv78sXbpUEhMT5eabb5aJEyfK3LlzZdq0afLGG2/INddcIykpKWELoBoQ5corr5SsrCzRv7Y/8sgjMmvWLPn222/lpptuss5btWqV1btQNRCFvQ473C+gGnZENdhI3bp1i1yYr776StSXKVFfyqRevXry/PPPy+zZs0X3JNS9LXT4+eefrW31wbrI1+VA5wps2bJF1Fuy1evvuuuuk7feekv++9//Wq877777rnTv3t3KvH4dOvvss6Wg1w2eH+fWc1nljPecspJ173U3b95sZV73sLnrrrvk448/ljlz5li9bJ5++mlp1KiRtV+/vujegAWFBx54QF599VXrkK5du1q9kfW1dK9kHddB79fvdwRvC+jPHPpzrB6FUNTPNTw/3n4mCivdO++8I0OGDJFdu3ZZz4z6EVy++eYbmTdvnnzxxRfWZ9xzzjlHEhISwl5K/agp+jz9/LVo0cL6LqZfg/T3M/2dTYdJkyZZI7TCXoQdCCBQvgLl1/bInREIL6B/OVJDY6xfl1S3ct+SJUvCHlzQL+ZnnHGGdQ39C6lq+Mt3DdUFPvALlv5Fi+BNAfXhxhcXF2f15FNfjgJ1XlAPQDX03KeG/FrHqkZm35o1a/Lh3HbbbYFrvf322/n2k+A+ATWcyvfEE0/49u3bFzLz6suWT/2oEKj3hx9+OORxPD8hWTyfyHuO56s44gKq6Ut8H3zwgU+/doQKO3bsCHzeUd8IfNOnTw91mG/16tWB3l66B7KavsQ47sCBAz6drq+hP/OEes8yTiDiaoFnnnnGquu2bdv6/vrXvwbek8L1AOT5cXV1lzjzy5cvD4xmOe2003x79+4Ne81w36v27Nnjq169uvWsqSmZfPq1yx70a5zu/adfg/S/H3/80b6bbQQQcIiA7ulAQMBxAv/85z8DbyDhPswUlmn1i1TgGqr3YMjD8/LyfGpeQOu4GjVq+I4cORLyOBLdK6A/kJx88slWHetGXv08+T+cFNQAqIdJ+I977LHHQgLoL1z6udHH6aHqhNgQ0EO+Va9kq947d+4cstA8PyFZPJ3Ie46nq7dMC6d6zATeb+68886Q97L/4KTm3wp5jE73v2/dfvvtIY8h0f0Cao5RnxrVYtW1/kyjP8v4613HQwWen1AqsZN21llnWc+ImkM9X8NdURXsnSZUr+OQp2VkZFg/uOvnceDAgSGPIREBBMpXgCHA6hWK4CwB1SgnY8aMsTKlelOI/lecoLuj+8P111/v3zT+qjksZNiwYVaa+mWrSJMnGxcg4ngB9Su56AnY9WTr999/f5Hza39+wg3LSk5OtoaY64vqoerqF/YiX58D3Sug5s8R1fBnFUDNHxqyIDw/IVk8nWivc95zPF3VpV44++ecUK8p6quCfPbZZ9Z9VY8vUXPPhsyDTtcLF+mgn0d9HsF7Aqoxz5p+Yvjw4UX6jMzz471nIJISrVy50pr6SJ+jfhiwFlKM5Hz/sf73OD31kn8aHP8+/1+9IJGeHkUHPby4oGlS/OfwFwEEoitAA2B0vblbEQT0HH3+OXMGDx4cOEOv1quGtEhmZqY190RgR5gN/6p6etXfU045JcxRIv369Qvs03N9EbwjsH79emuuEl2il156yVrprKil8z8/+suUXiUtXOD5CSfj7XQ9L6QO+keEUIHnJ5SKt9P8dc57jrfruSxKp0YfBC4b6jVl3bp1gc9F9vecwEm2Df/+TZs2iX4PJHhLQPUuF7XQkNSsWVOeeuqpIhWO56dITJ496KOPPgqUzf69Snd80D9c6zkBCwv6NUrP9adD7969rbnZw53jfw3Sn5N++eWXcIeRjgAC5SQQ+ptLOWWG2yKgBfSiCv6g32T0G855550n1apVk1atWomeSLtOnTrWBLN6UYdwYcWKFdYuNY+bqPlwwh0m+td0f/Cf44/z190Ct956q+iG42uvvVbU8IciF0b/Yqm/POlgfz5CXcC+n+cnlJD30rZv3y7+urbXv7+kPD9+idj6638meM+JrXovjdKqubIClwn1muJ/tvRBofYHTg7abz/Pfgzb7hRQ87ZZC8no3Ku5aq3PwkUpif054Pkpipi3jvF/r0pNTRU17ZGMGzdOunTpYjUi69ExaliwNG/eXNQ0OWF77OmGQjWljgXDM+St54PSxJ4ADYCxV+eOL7GaqDaQR/2m1bdvX/n666+NXn+7d++2Vp5KT08XNWF24Hj/xuHDh0XN02VFdXf0goKaw81a8VMfo+auKOhQ9rlI4P3335cvv/xS1ITF8p///CeinOvGP//QqcKen7S0tMC1eX4CFJ7e0L0u/B+E9SrjwYHnJ1jE+3Hec7xfx2VVQr2a5uOPPx64fKjXFPt7C+9JAaqY21CLVMnWrVulT58+csMNNxS5/Dw/Raby5IH+71XNmjWTO+64Q6677jpZvHixUVbdS3T06NFW774tW7YY+3SEZygfCQkIuFaABkDXVp13M64b9/zh7rvvFj0noP7Qo+fF0d3J9TDge++9VypUqCD611A9D4V/yLD/vOzsbP+mqImSA9vhNvSQLR2YqyKckLvS9TOknx0d1AIeUq9evYgKEMnz43929A14fiJiduXBs2fPlmeffdbKu/4irudiCg48P8Ei3o9HUudaw/+6wWuG95+Nwkqo56n1D6277LLLRK3km++USJ4v/7OlL8LzlY/StQl6iprXX3/dGtGi58nWn4GLGnh+iirlzeP836v0XIAvvvii9cO4fob0aAb945UepnvBBRdYhdfzWethwvqHCXvgGbJrsI2AuwVoAHR3/Xky92pl1UC5dIOfWnXKGuqgu6erlTelRYsW1rwnjzzyiHWcnrtCN/LYg35D8wd9TmGhUqVK1iGHDh0q7FD2u0BANxDrDzY9e/aUkSNHRpzjSJ4f/7Ojb8LzEzG1q07Ytm2bXHHFFVbvP/3l6+233xa9EExw4PkJFvF+PJI61xr+1w1eM7z/bBRUQj309y9/+Yt1SN26deXll18OeXgkz5f/2dIX4vkKyem6RD3/mv4so0cm6B83O3XqFFEZeH4i4vLcwf7vVfo7VVxcnEydOlVuvvlmawi5fr3QPzroeSX9jYB6LvZPP/3UcOAZMjiIIOBqARoAXV195Zt5PQROfwku6b+xY8caBUlKSgrEdQ8bf0+uQOLvG/fdd580aNDAik2YMCEwZFMn2K9hn1z791Pz/dFvijpUrlw53z4SykagrJ6fH374Qd566y3rQ47+hTPUhOqFlSiS58f/7Ohr8vwUJlt6+8vq+QmXQ/3r94ABAwJzQz766KNy5plnhjyc5ycki6cTI6lzDeF/3eA1w9OPRYGFW7Zsmegef/q1TH8J14s7hOutHsnz5X+29M15vgqsAtfs1O83eh6/Jk2aBBY2iyTzPD+RaHnvWHv96959oVYR15+V7YvKjB8/3oCwX6Ow71W8Bhl0RBBwnAANgI6rEjKkF/vwh3POOcdqyPHH7X/1wh7+L+C6F6Cev8If7NcoyhAY/69jRRku7L8Hf50noD906F81dbjzzjtFzxFZnBDJ8+N/dvR9eH6Ko+38c/Qv35dcconMmzfPyuyf/vSnQK+dULnn+Qml4u20SOpcS/hfN3jN8PZzEa50+vPKueeeK3oVTt0jR3/Z9q+cGeqcSJ4v/7Olr8PzFUrTXWl62KZ/lMsLL7wQmD4gklLw/ESi5b1j7fXv7+UXqpQdOnSQRo0aWbuCV++1X6Ow71W8BoXSJQ0B5wiEXxrVOXkkJw4V0A1w9pXFiptNfy8+//n2RRUimexaD/nUw4R10L9U6VWt9EIg/tVc/dcP/qs/gPvfrOz3Dj6OeOkKlMXzo4cs/Prrr9YcOe3btxfdMzQ4+CdD1ul6rhP/MXq48EknnWQdbn/uCnt+7BMj8/wEa5ddvCyen1C51b1z9KT833//vbX7xhtvLHRRGZ6fUJLeTuM9x9v1W5ql0xPsn3322aL/6hEUb775ptUTsKB78JpSkI639+k5InWPK/359uDBg4HPLPZS688y/vDdd99ZC4Xo+EUXXWQ1GPL8+HVi86/+bKoXj9HB/iyE0tDH6nnV9Xcqe7Cfx+diuwzbCLhPgAZA99WZo3Jc2FLwxcms/gXKH/QCIAUF+37dIGAPeqn7GTNmWIuG6C/xwfv9x+pfV/1Bn0OInkBpPz/+YQe6vm+66aZCC/LJJ5+I/qeDHjbsbwDUvSb0hyDduGd/PkJd0L6f5yeUUNmllfbzE5xTPQn20KFDZdKkSdauq666Sl555ZXgw/LFeX7ykcREAu85MVHNJSqk/lFSj2z47bffrOvoHl3Dhg0r9Jr6By1/sL/n+NPsf+37eU+yy7hz2/+5Rj8zV199daGF+Oc//xk4Rvc01YvC8PwESGJyQ3+v8vfos39vCoXh3x/8nal169ZWb2W93/4aE+oa9v28BoUSIg2B8hVgCHD5+nP3EAKnn356IFWv/FtQsO/3d1v3H3/qqadam7p3n3/onn+f/a+ehNsf+vbt69/kb4wL+J+fVatWBX45DUXC8xNKxRtpeji5v4fowIED5d133y3ynJI8P954BiIphb/Oec+JRC12js3KypLzzjtP/L3QH3/8cfnDH/5QJAD941TDhg2tY+3vOaFOnj59upWsPxM1a9Ys1CGkxZgAz0+MVXhQcSP5XuX/cSL4O5VeULFHjx7WlX/66SerV2rQbQJR/2uUf4GRwA42EEDAEQI0ADqiGsiEXUB/UOnatauV9NVXX1lDHuz7/dt6Uv5vvvnGiuqVgYOHEl966aX+Q63eXYGIbUP38HnnnXeslOrVq0v//v1te9l0m8CIESOsxWD0Snnh/vmHcuqyjRo1KnCcPtce7M9P8EI1/uP0cBw9cbsO+hd2/QspwRsCep6/119/3SrMWWedJR9//LEkJCQUuXA8P0Wm8syB9jrXPYpDBd5zQql4P02/V+hFhObPn28V9u9//7vcf//9RS64Hiqs5yHVQfeu+fnnn0Oeq9P9vW/08fo8grsF9OePcJ9n/On6s4w/6M84/nR/AzDPj18nNv9efPHFgc8vwav72kV0w52eU12H0047zb7L2va/x+3bty/fKsH+g/Xw4GnTpllR/dnJPneg/xj+IoBAOQuoNwkCAo4T+OCDD3zqfw3r3y233BIyfzfccEPgGLVyVchj1BuYdYzqyu5Ty9rnO+bJJ58MXEN9gMq3nwTvCagPx0WqczXnjk81LFvHpqSk+NasWZMP47bbbgtcS33hz7efBHcK6NcC/+tPnz59fGrC64gLwvMTMZknTuA9xxPVWKqFUEM4fWrBj8Bryl133VWs66ve6D79WUa/NnXr1s2nGhWN6+i4Ttf79XFqPlxjPxHvCtjfs/RnnFCB5yeUSuyk3XrrrYHXILXoUL6Cq0Y9n1o4L3DMnDlz8h2jGgd9qamp1jFNmzb1qSkNjGPU9Ds+Ne9k4BpqPkpjPxEEEHCGgP6ViICAIwUuvPDCwJuI+uXc99lnn/nUr+e+iRMn+s4///zAPtVb0Hfo0KGQZdDHV65c2TpWzcvle/TRR32q67pPvymNHDkycA3Vc8un3/wI3hcoagOglvjiiy98FStWtJ6TevXq+dR8Tb7Zs2f7vvzyS9/ll18eeH7U0D+f/uBDcL/A888/H6hXNQTG99///te3ZMmSAv/pxr5QgecnlIq303jP8Xb9Fqd0gwYNCrymnHnmmb7FixcX+HqiG2rChb/85S+Ba+nPPmqKAp+a28v6q+P+Hy7++te/hrsE6R4UKEoDoC42z48HK7+IRVKLeviaNGlivUboHwhuv/1267vQ3LlzffoHbDWncuD1QzcWhgtjxowJHKd/JFeLGFmvQfo7mhpFFdin5qsMdwnSEUCgnAVoACznCuD24QXUEF/jV3P/B1v73+7du/syMzPDX0Tt+fzzz326B5f9PPu2bvxbvXp1gddgp3cEImkA1KV+9dVXfWruk7DPj5oTxbdjxw7vAMV4Sfr16xe2ru2vG/ZtNdF6WDWen7A0nt3Be45nq7ZYBbO/VhRlW/esCRf+v707D9Gq+hsA/rUETZPKtcWUxMLUghbSIEnoj8j6Q22zLCLLiiQpgiKyRUrSNipCixKy1CKLFKEg21NbRVsoTCmJwjRLs0VF09+cA3feGX2eccand3we53Ngus+955x7z/ncYZy+c5a6Bfh3jRs3rsmfUWl2RContR2B5gYAff+0ne+JUj2tW390V//+/Zv8+ZF+vpT7o2Zxz7vvvntX3bTysvdJAzjKDcwo7uFIgMD+E7AGYN1vY1J1CqSdNNMagHVD1aNuxF8ceeSReQ2LHj165F306v7qFGkh2nS9qVQ3HD3q/uIet9xyS16jrVOnTpHW+6ubKhPTpk2L5cuXR90/iE3dQl4bFki7CadNZNKxX79+0bFjx+jWrVukBf9nzJgRS5Ysie7du7dhIV1vSsD3T1M6B2aef3MOzPdaDb2qG5EeM2fOjLrRxXlNwLQxSFqcPx3Tmn+vv/56Xrs0lZMI7C7g+2d3kbZ1nnbkXbFiRdQtmxRDhgyJrl275p8fvXv3jksvvTTqZkflny97W+948uTJUTc7Ii6//PI49thj8z169uyZ/99s7ty5+edT+l1ZIkCgOgXapdhjdTZNqwgQIECAAAECBAgQIECAAAECBAgQqFTAnwgrFVSfAAECBAgQIECAAAECBAgQIECAQBULCABW8cvRNAIECBAgQIAAAQIECBAgQIAAAQKVCggAViqoPgECBAgQIECAAAECBAgQIECAAIEqFhAArOKXo2kECBAgQIAAAQIECBAgQIAAAQIEKhUQAKxUUH0CBAgQIECAAAECBAgQIECAAAECVSwgAFjFL0fTCBAgQIAAAQIECBAgQIAAAQIECFQqIABYqaD6BAgQIECAAAECBAgQIECAAAECBKpYQACwil+OphEgQIAAAQIECBAgQIAAAQIECBCoVEAAsFJB9QkQIECAAAECBAgQIECAAAECBAhUsYAAYBW/HE0jQIAAAQIECBAgQIAAAQIECBAgUKmAAGClguoTIECAAAECBAgQIECAAAECBAgQqGIBAcAqfjmaRoAAAQIECBAgQIAAAQIECBAgQKBSAQHASgXVJ0CAAAECBAgQIECAAAECBAgQIFDFAgKAVfxyNI0AAQIECBAgQIAAAQIECBAgQIBApQICgJUKqk+AAAECBAgQIECAAAECBAgQIECgigUEAKv45WgaAQIECBAgQIAAAQIECBAgQIAAgUoFBAArFVSfAAECBAgQIECgRQJr1qyJdu3a5a/nnnuuRXUVJkCAAAECBAgQaLmAAGDLzdQgQIAAAQIECOxXgcWLF9cH0FIg7YMPPtiv7fFwAgQIECBAgACB6hYQAKzu96N1BAgQIECAAIE9BJ5//vlG13Y/b5TphAABAgQIECBAoM0LCAC2+W8BAAQIECBAgEAtCWzbti3mzZuXm3zooYfmYzrfsmVLLXVDWwkQIECAAAECBFpRQACwFbE9igABAgQIECBQqcCCBQti06ZN+TaPP/54Pm7evDnSdYkAAQIECBAgQIBAKQEBwFIqrhEgQIAAAQIEqlRg1qxZuWUDBw6McePGRTqmZBpwZvAfAgQIECBAgACBEgICgCVQXCJAgAABAgQIVKPA+vXr480338xNu+KKK/Jx7Nix+Ziur1u3rmyz77333vqNQ1KhrVu3xkMPPRSnnnpqdOnSJX+dccYZ8eSTT8aOHTvK3qfI+PDDD2P06NHRq1ev6NixY/Tr1y9uuOGGWL16dS4yfPjw/Lx0rCR9+umnMX78+DjhhBMiTXnu3LlzDBgwICZMmBCrVq2q5NbqEiBAgAABAgTajIAAYJt51TpKgAABAgQI1LrAnDlzcnAu7fxbBP7SMZ3/+++/kfKbk1KgcOjQoXHbbbfF8uXL46+//spfn332Wdx00005sLdz586yt5oyZUqcffbZ8dprr0UKSqZ1CX/44Yd4+umnc0CxCFKWvUEzMlIQ8sYbb4whQ4bEs88+m4N9f//9d/zzzz+xcuXKmD59egwaNCieeeaZZtxNEQIECBAgQIBA2xYQAGzb71/vCRAgQIAAgRoSKKb/Dhs2LPr06ZNb3rdv3zjrrLPy5+ZOA04j97799tuYOHFiLFq0KJYtWxZz586NE088Md9n4cKFZQNrL774YkyaNCl27doVRxxxREydOjWWLl2av6ZNmxbt27ePMWPGxNq1ayuSveaaa2LGjBn5Huedd17Mnj070mjAFKRMQb8U/Nu+fXtcd911kdorESBAgAABAgQIlBdoXz5LDgECBAgQIECAQLUIfPXVV/HFF1/k5hTTf4u2pfM0JTflp3InnXRSkVXymIJoaZRew+m5aSrwueeem9cUTCME0wi766+/vlH9NNLv5ptvzte6du0aH330UZ6aWxQ688wzY+TIkZGO3333XXG5xcdXX321fk3DFOy79tprG93j9NNPj9Tn888/P955550cyExBwhR8lAgQIECAAAECBPYUMAJwTxNXCBAgQIAAAQJVJ1CM/uvQoUNcfPHFjdp3ySWXRLqeUlGuUYHdTtI034bBvyI7BfWuvvrqfPrll1/GH3/8UWTlYzHlN53cc889jYJ/RcG0Vl/KqyQ98MADufqoUaP2CP4V903rDqb1ClNas2ZNvPfee/mz/xAgQIAAAQIECOwpIAC4p4krBAgQIECAAIGqEkjr+6UpuimlUW+HH354o/al8xEjRuRrqVwq31Qq1g8sVea0006rv5zW9WuY3n777Xx60EEHxZVXXtkwq9HnNDovrUu4L+nnn3/OU5JT3RTYbCqlKcvdu3fPRdJoRIkAAQIECBAgQKC0gABgaRdXCRAgQIAAAQJVI5Cm6xZr6u0+/bdoZHE9lXvrrbeKyyWPaRfdcimNAizSn3/+WXzMx6+//jofjzvuuLz+X6PMBifpHmlX4H1Jn3/+eX21yy67rH7n4hRQLPW1YcOGXP6XX36pr+cDAQIECBAgQIBAYwEBwMYezggQIECAAAECVSdQbO6RRvqlEYClUsORgUX5UuXStU6dOpXLijS6r0i7jyTcuHFjzurZs2dRpOyxR48eZfOayki7Cu9LSrsDSwQIECBAgAABAqUFrJRc2sVVAgQIECBAgEBVCGzevDkWLFiQ27Jp06b6tf6aatz8+fMjjd7r0qVLU8WqMq9h0HHOnDlx8sknN6udaUdiiQABAgQIECBAoLSAAGBpF1cJECBAgAABAlUh8PLLL8eWLVta1JY0Gu6VV16p39CjRZWbKFwE2ZozSu/XX39t4k7ls7p161afmab8Dh48uP7cBwIECBAgQIAAgX0TEADcNze1CBAgQIAAAQKtIlBM5z3qqKPi0Ucf3eszb7/99vjxxx8j1St29N1rpWYWGDRoUHz88ceRNgf5/fffo+F6gQ1vkfK+//77hpea/fmUU06pL5vWPkzrAEoECBAgQIAAAQKVCQgAVuanNgECBAgQIEDg/00gBdoWL16c73/hhRfGmDFj9vqstInGI488Eu+//34OBPbp02evdZpb4JxzzomZM2fGzp07Y/bs2TFx4sSSVVPerl27Subt7WL//v1j4MCB8c0338RLL70UkydPjv+yD3t7vnwCBAgQIECAwIEo8H+rPB+IvdMnAgQIECBAgEANC7zwwgv1gbSLLrqoWT0pyqUAXKr/X6ZRo0ZFsQFICsytWrVqj9unaymvkjRp0qRcfevWrTF69Ohoajrxtm3bYvr06ZHKSgQIECBAgAABAqUFBABLu7hKgAABAgQIENjvAkUALwXdhg0b1qz2DBkyJHr37p3LFvWbVbEZhTp27BiPPfZYLpmm+aZnPfjgg3lacJoanD4PHTo0jxA8/vjjc7m0jl9LU5r2e9VVV+Vqy5YtyyMCU1Bw0aJFsWLFiliyZEme4jx+/Pg4+uijY8KECbFjx46WPkZ5AgQIECBAgECbETAFuM28ah0lQIAAAQIEakkgBblWr16dm5xG3h10UPP+bpsCbmnU3BNPPBErV66MTz75JAfq/qu+p+BcWt/vrrvuio0bN0Zac7Bh6tSpU8ybNy+mTp2aRwimoOG+pDTVuFevXnk684YNG2LKlCn5q9S9OnfuHAcffHCpLNcIECBAgAABAgTqBJr3myQqAgQIECBAgACBVhUoNv9ID03r/7UkNSzf8D4tuUdTZe+88868xuDIkSPzlOAOHTpE3759Y9y4cZHWIBwxYkRs3rw53+Kwww5r6lZl81JAb9q0aXktwFtvvTXS5iBpF+J0vUuXLpE2JBk7dmzMmjUr1q5dG4ccckjZe8kgQIAAAQIECLR1gXZ168Ps2wrNbV1O/wkQIECAAAECBEoKbN++PVLgb8uWLZGm7t53330ly7lIgAABAgQIECDQOgJGALaOs6cQIECAAAECBNqMwPz583PwL3U4rQkoESBAgAABAgQI7F8BIwD3r7+nEyBAgAABAgRqTiCtTdi/f/+S7V6zZk3esOSnn37Ka/ilY/v2lp0uieUiAQIECBAgQKCVBPw21krQHkOAAAECBAgQOFAEBgwYkNf5u+CCC/JafGkTjvXr18e7774bTz31VGzatCl39eGHHxb8O1Beun4QIECAAAECNS1gBGBNvz6NJ0CAAAECBAi0vkDaabiplHYsvv/+++OOO+5oqpg8AgQIECBAgACBVhIwArCVoD2GAAECBAgQIHCgCCxcuDDeeOONWLp0aaxbty5+++23SDsBH3PMMTF8+PCYMGFCDB48+EDprn4QIECAAAECBGpewAjAmn+FOkCAAAECBAgQIECAAAECBAgQIECgvIBdgMvbyCFAgAABAgQIECBAgAABAgQIECBQ8wICgDX/CnWAAAECBAgQIECAAAECBAgQIECAQHkBAcDyNnIIECBAgAABAgQIECBAgAABAgQI1LyAAGDNv0IdIECAAAECBAgQIECAAAECBAgQIFBeQACwvI0cAgQIECBAgAABAgQIECBAgAABAjUvIABY869QBwgQIECAAAECBAgQIECAAAECBAiUFxAALG8jhwABAgQIECBAgAABAgQIECBAgEDNCwgA1vwr1AECBAgQIECAAAECBAgQIECAAAEC5QUEAMvbyCFAgAABAgQIECBAgAABAgQIECBQ8wICgDX/CnWAAAECBAgQIECAAAECBAgQIECAQHkBAcDyNnIIECBAgAABAgQIECBAgAABAgQI1LyAAGDNv0IdIECAAAECBAgQIECAAAECBAgQIFBeQACwvI0cAgQIECBAgAABAgQIECBAgAABAjUvIABY869QBwgQIECAAAECBAgQIECAAAECBAiUFxAALG8jhwABAgQIECBAgAABAgQIECBAgEDNCwgA1vwr1AECBAgQIECAAAECBAgQIECAAAEC5QUEAMvbyCFAgAABAgQIECBAgAABAgQIECBQ8wICgDX/CnWAAAECBAgQIECAAAECBAgQIECAQHmB/wFpJbGlPgjWjwAAAABJRU5ErkJggg==\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0,0.5,'Counts in frame')"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Normalize all the stacks to correct for tilt.\n",
"# Option 1, just normalize in the simplest fashion. This will only work if the stack has an isolated object.\n",
"# Option 2, not implemented, use a cos approximation to correct for the detector shadowing at 18 degrees.\n",
"\n",
"def NormalizeStack(Stack):\n",
" # Get the index of the stack with the least tilt. This will have the best\n",
" # quantification for the element intensity. So we want to normalize to that\n",
" # so we preserve count rates for quantification.\n",
" MinTilt = np.argmin(np.array(Nums)**2)\n",
" #print(f'MinTiltIndex: {MinTilt}')\n",
" # Now sum up the minimum tilt frame (usually zero tilt.)\n",
" NormIntensity = np.sum(Stack[MinTilt,:,:])\n",
" #print(f'NormIntensity: {NormIntensity}')\n",
" \n",
" # Convert to float\n",
" Stack = Stack.astype(float)\n",
" \n",
" for i in range(Stack.shape[0]):\n",
" # Normalize to 1.\n",
" Stack[i,:,:] = Stack[i,:,:] / np.sum(Stack[i,:,:])\n",
" # Now normalize to the actual count rate.\n",
" Stack[i,:,:] = Stack[i,:,:] * NormIntensity\n",
" \n",
" # Things need to fit in 16 bits.\n",
" if np.max(Stack) > 2**16-1:\n",
" Stack /= np.max(Stack)\n",
" Stack *= 2**16-1\n",
" \n",
" Stack2 = Stack.round().astype(uint16)\n",
" return Stack2\n",
" \n",
"# Test that the function normalizes correctly.\n",
"WhichStack = HAADF.copy()\n",
"I = list(map(np.sum, WhichStack))\n",
"plot(Nums,I)\n",
"StackNorm = NormalizeStack(np.array(WhichStack))\n",
"I = list(map(np.sum, StackNorm))\n",
"plot(Nums,I)\n",
"legend(['UnNormed', 'Normed'])\n",
"xlabel('Angle')\n",
"ylabel('Counts in frame')\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {},
"outputs": [],
"source": [
"# Write out all the stacks as tiff files.\n",
"for i, s in enumerate(SignalList):\n",
" npStack = np.array(eval(s))\n",
" StackNorm = NormalizeStack(npStack)\n",
" if not os.path.exists('Element Stacks'):\n",
" os.mkdir('Element Stacks')\n",
" imsave(os.path.join('Element Stacks',s+'.tif'), StackNorm)\n",
" \n",
"# Make a tilts file\n",
"with open(os.path.join('Element Stacks','tilts.txt'), 'w') as f:\n",
" for n in Nums:\n",
" f.write(f'0.0 {n:0.1f} 0.0\\n')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# HALT!!!! \n",
"At this point we have to align the stacks. Since they all are aligned the same, we first align the HAADF and then apply the same alignment to all the EDS stacks. In order for that to work, we need to align the HAADF in such a way as we have an output file of all the offsets.\n",
"\n",
"<b>Method 1:</b> do a MultiStackReg on HAADF.tif in ImageJ and save it as HAADFAligned.tif and the transformations as TransformationMatrices.txt. This will only work if all the images are aligned to the first one.\n"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [],
"source": [
"# Read in the translations file written by ImageJ.\n",
"with open(os.path.join('Element Stacks', 'TransformationMatrices.txt'), 'r') as f:\n",
" s = f.read()\n",
" \n",
"translations = re.findall(pattern='([\\d\\.]*)\\t([\\d\\.]*)', string=s)\n",
"\n",
"# There are 6 lines in each translation from the output file. \n",
"# The zeroth is the new position, the third is the original position.\n",
"# The other lines are for rotations which we are not using.\n",
"# Example:\n",
"# [('236.81374221505683', '288.85170101351565'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('256.0', '256.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('246.23227371186195', '229.14170151652533'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('256.0', '256.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('264.2877416986045', '281.32142526192746'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('256.0', '256.0'),\n",
"# ('0.0', '0.0'),\n",
"# ('0.0', '0.0'),\n",
"# ...\n",
" \n",
"\n",
"# There should be as many translations as there are images-1 because we are registering to the first image.\n",
"assert(len(translations)/6 == len(Nums)-1)\n",
"\n",
"offsets = []\n",
"offsets.append(np.array((0,0))) # MultiStackReg will ignore the first image since others are registered relative to it.\n",
"# Loop through all the translation info, image by image (6 lines at a time).\n",
"for i in range(0, len(translations), 6):\n",
" NewPos = translations[i] # Image shifted to here\n",
" OrigPos = translations[i+3] # Image started here\n",
" # How much to shift:\n",
" offset = -np.array((float(NewPos[1]) - float(OrigPos[1]), float(NewPos[0]) - float(OrigPos[0])))\n",
" if len(offsets) > 0:\n",
" offset += offsets[-1]\n",
" offsets.append(offset)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<b>Method 2:</b> Align the images using a manual alignment in Tomviz. For this to work, it has to be the only data source, and the tomviz file needs to be saved as HAADF_Alignment.tvsm. There need to be the following exact sequence:\n",
"1. Assign tilt angles.\n",
"2. Manual translation align.\n",
"3. Manual Shift/rotate. Only adjust the y-axis of the shift. (If you need to adjust the rotation then write some code! :-).\n",
"\n",
"Like this:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src=\"Screen Shot 2018-04-20 at 4.48.11 PM.png\"/>"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: 'Element Stacks/HAADF_alignment.tvsm'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-31-8545ebb63609>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Read in the tvsm file (which is XML) into a python dictionary structure. So cool!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mxmltodict\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Element Stacks'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'HAADF_alignment.tvsm'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mtvsm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mxmltodict\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'Element Stacks/HAADF_alignment.tvsm'"
]
}
],
"source": [
"# Read in the tvsm file (which is XML) into a python dictionary structure. So cool!\n",
"import xmltodict\n",
"with open(os.path.join('Element Stacks', 'HAADF_alignment.tvsm')) as f:\n",
" tvsm = xmltodict.parse(f.read())\n",
" \n",
"# We just go to the first DataSource, second operator and check that it is TranslateAlign.\n",
"OperatorType = tvsm['tomvizState']['DataSource']['Operator'][1]['@operator_type']\n",
"if OperatorType != 'TranslateAlign':\n",
" print(\"Error! Expecting second operator to be TranslateAlign. Check the XML in HAADF_alignment.tvsm.\")\n",
" \n",
"# Find out how many frames.\n",
"NumOffsets = int(tvsm['tomvizState']['DataSource']['Operator'][1]['@number_of_offsets'])\n",
"print(f'Number of frames is: {NumOffsets}')\n",
"\n",
"# For each frame get the offset.\n",
"Offsets = tvsm['tomvizState']['DataSource']['Operator'][1]['offset']\n",
"if len(Offsets) != NumOffsets:\n",
" print('NumOffsets != the number of frames. Brwooop! Brwooop!')\n",
"\n",
"# And get the shift to move the axis to the center.\n",
"# This will be added to the offset.\n",
"AxisShift = int(tvsm['tomvizState']['DataSource']['Operator'][2]['arguments']['variant']['variant'][1]['@value'])\n",
"print(f'Axis shift is: {AxisShift}')\n",
"\n",
"offsets = []\n",
"for OneOffset in Offsets:\n",
" x = int(OneOffset['@y_offset']) + AxisShift\n",
" y = int(OneOffset['@x_offset'])\n",
" offsets.append(np.array((x,y)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Alignment done, continue\n",
"Now you can just apply the alignment."
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Aligning HAADF\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Al\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning C\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Ca\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Cr\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Fe\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Ga\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Mg\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Na\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Ni\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning O\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning P\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Aligning Pt\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning S\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n",
"Aligning Si\n",
"[0 0]\n",
"[-10.56531347 -0.76869794]\n",
"[-7.57585307 1.17490137]\n",
"[-21.22083041 0.10797676]\n",
"[-21.07241449 4.71735066]\n",
"[-14.58672978 -1.65171027]\n",
"[ -9.28610747 18.72658437]\n",
"[-10.81448485 21.45125873]\n",
"[ -9.91957505 19.41443962]\n",
"[-10.43070641 19.75927847]\n",
"[-14.41914219 22.82609869]\n",
"[-12.74124184 21.63501793]\n",
"[-12.39666614 21.17229003]\n",
"[-10.7498741 19.94298267]\n",
"[-14.59067358 19.84496354]\n",
"[-13.93458427 17.88619463]\n",
"[-17.02988091 17.34388515]\n",
"[-12.85265235 18.13929351]\n",
"[-10.75320571 16.87528888]\n",
"[-13.02779107 21.09715628]\n",
"[-14.20805326 22.70445981]\n",
"[-12.7085064 21.66274809]\n",
"[-27.2881577 8.96019932]\n",
"[-18.07827049 0.86247128]\n",
"[-5.73898499 -8.53676851]\n",
"[ 1.27623452 -2.70714799]\n"
]
}
],
"source": [
"# Apply the shifts to all the images.\n",
"\n",
"doall = open(os.path.join('Element Stacks','runall.sh'), 'w')\n",
"\n",
"for s in SignalList:\n",
" print('Aligning', s)\n",
" Sig = eval(s)\n",
" SigAlign = []\n",
" #SigAlign.append(Sig[0])\n",
"\n",
" # Apply the shifts to every image in this signal stack.\n",
" for i in range(len(offsets)):\n",
" print(offsets[i])\n",
" if s == 'HAADF':\n",
" SigAlign.append(shift(Sig[i], offsets[i]))\n",
" else:\n",
" SigAlign.append(shift(Sig[i], offsets[i]/binning))\n",
" \n",
" # Save the result as a tif for easy viewing.\n",
" imsave(os.path.join('Element Stacks',s+'_aligned.tif'), np.array(SigAlign))\n",
" \n",
" # Swap the numpy axes to be how GENFire expects it and save npy files.\n",
" SigAlign = np.array(SigAlign)\n",
" SigAlign = np.swapaxes(np.swapaxes(SigAlign, 0,1), 1,2)\n",
" np.save(os.path.join('Element Stacks',s+'_aligned.npy'), np.array(SigAlign))\n",
" \n",
" # HAADF images are usually too big to do the full genfire. We have avoid using oversampling so they fit in memory.\n",
" if s == 'HAADF':\n",
" osetting = '-o 1'\n",
" else:\n",
" osetting = ''\n",
" \n",
" slurmscript = '#!/bin/bash -l\\n'\\\n",
" '# Job name:\\n'\\\n",
" '#SBATCH --job-name=GENFIRE_%s\\n'\\\n",
" '#\\n'\\\n",
" '# Partition:\\n'\\\n",
" '#SBATCH --partition=vulcan\\n'\\\n",
" '#\\n'\\\n",
" '# Account:\\n'\\\n",
" '#SBATCH --account=vulcan\\n'\\\n",
" '#\\n'\\\n",
" '# Wall clock limit:\\n'\\\n",
" '#SBATCH --time=2:00:00\\n'\\\n",
" '#\\n'\\\n",
" '# Processors\\n'\\\n",
" '#SBATCH --ntasks=8\\n'\\\n",
" '#\\n'\\\n",
" '# Mail type:\\n'\\\n",
" '#SBATCH --mail-type=all\\n'\\\n",
" '#\\n'\\\n",
" '# Mail user:\\n'\\\n",
" '#SBATCH --mail-user=zgainsforth@lbl.gov\\n'\\\n",
" '#\\n'\\\n",
" '## Run command\\n'\\\n",
" '\\n'\\\n",
" 'cd $SLURM_SUBMIT_DIR;\\n'\\\n",
" 'module load python\\n'\\\n",
" 'source activate conda36\\n'\\\n",
" 'python DoGenfire.py %s %s\\n' % (s, s, osetting)\n",
" with open(os.path.join('Element Stacks',s+'_slurm.sh'), 'w') as f:\n",
" f.write(slurmscript)\n",
" \n",
" doall.write('sbatch %s_slurm.sh\\n'%s)\n",
" doall.write('sleep 3\\n')\n",
"\n",
"doall.close()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# At this point all the EDS stacks are aligned and you can fire up GENFires for them."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Some other registration approaches I've played with in the past."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
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"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
},
{
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"\n",
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"\n",
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" }\n",
"\n",
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" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
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"\n",
" this.canvas = canvas[0];\n",
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"\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",
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" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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"\n",
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" pass_mouse_events = false;\n",
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" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
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" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
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" } else {\n",
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"\n",
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"\n",
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" // 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",
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"\n",
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" }\n",
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" }\n",
"\n",
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" 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",
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"\n",
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" // 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",
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"\n",
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" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
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" icon_img.addClass('ui-corner-all');\n",
"\n",
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" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
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"\n",
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"\n",
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"\n",
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" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
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"\n",
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"\n",
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" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
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"\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",
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" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
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" 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",
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" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
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"}\n",
"\n",
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" {\n",
" case 0:\n",
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" case 1:\n",
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" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
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" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
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"}\n",
"\n",
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" fig.send_draw_message();\n",
"}\n",
"\n",
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"}\n",
"\n",
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" this.send_message(\"ack\", {});\n",
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" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" 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",
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" fig.waiting = false;\n",
" return;\n",
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"\n",
" var msg = JSON.parse(evt.data);\n",
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"\n",
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" var callback = fig[\"handle_\" + msg_type];\n",
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" return;\n",
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"\n",
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" 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 overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
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{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"StackAlign = hs.signals.Signal2D(HAADF)\n",
"S2 = StackAlign.align2D()\n",
"StackAlign.plot()"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'tvec': array([-33.8393811 , 19.03266518]), 'success': 0.096294723611813057, 'angle': 0}\n",
"[-33.8393811 19.03266518]\n",
"[ 28.01530697 10.7978632 ]\n",
"[-25.11391821 -7.86684622]\n",
"[ 23.0702638 -6.98664801]\n",
"[ -5.88981896 19.12638869]\n",
"[-31.81820052 -9.00642787]\n",
"[ 40.9368323 -13.50696723]\n",
"[-0.08009547 0.02131036]\n",
"[-15.97333975 -12.18822169]\n",
"[-28.25592078 26.07145559]\n",
"[ 4.9024495 -3.18818693]\n",
"[ 47.21118656 -32.06886613]\n",
"[-15.18781038 26.16505911]\n",
"[ 0.31897419 0.34951543]\n"
]
}
],
"source": [
"import imreg_dft\n",
"\n",
"print(imreg_dft.translation(HAADF[0], HAADF[1]))\n",
"HAADFReg = []\n",
"HAADFReg.append(HAADF[0])\n",
"for i in range(1, len(HAADF)):\n",
" tvec = imreg_dft.translation(HAADF[i-1], HAADF[i])\n",
" print(tvec['tvec'])\n",
" HAADFReg.append(imreg_dft.transform_img(HAADF[i], tvec=tvec['tvec']))\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(array([-32., 18.]), 0.29716657447141293, 6.9623500950971265e-16)\n",
"[-32. 18.]\n",
"[ 26. 8.]\n",
"[-25. -7.]\n",
"[ 23. -6.]\n",
"[ -6. 18.]\n",
"[-31. -8.]\n",
"[ 39. -15.]\n",
"[-4. 5.]\n",
"[-15. -12.]\n",
"[-27. 26.]\n",
"[ 5. -3.]\n",
"[ 47. -32.]\n",
"[-16. 23.]\n",
"[ 4. 2.]\n"
]
}
],
"source": [
"from skimage.feature import register_translation\n",
"from skimage.transform import EuclideanTransform, warp\n",
"\n",
"print(register_translation(HAADF[0], HAADF[1]))\n",
"HAADFReg = []\n",
"HAADFReg.append(HAADF[0])\n",
"for i in range(1, len(HAADF)):\n",
" shift, error, diffphase = register_translation(HAADF[i-1], HAADF[i])\n",
" print(shift)\n",
" HAADFReg.append(warp(HAADF[i], EuclideanTransform(translation=shift)))\n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 75,
"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",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/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",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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