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solarPOT/Tilted_irradiance/Merge_tilted_irrad.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"from scipy.spatial.distance import cdist\n",
"\n",
"from pvlib.solarposition import get_solarposition\n",
"\n",
"import time\n",
"import util\n",
"\n",
"import matplotlib\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Aims:\n",
"- Combine parallelised .csv files and find an efficient method to load/store the data\n",
"\n",
"--> Saving as netcdf requires 350MB instead of 1.2GB for each file, and can be opened in mf_dataset!\n",
"--> NOTE: conversion to xarray takes MUCH longer when dealing with timestamps instead of strings - change afterwards to timestamps!!!"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"path = '/scratch/walch/workspace_tilted_irrad/files'\n",
"file_base = 'tilted_irradiance_interp'"
]
},
{
"cell_type": "markdown",
"metadata": {
"scrolled": true
},
"source": [
"N_BATCHES = 97\n",
"for file_id in range(52, N_BATCHES):\n",
" print('\\n\\nCurrent batch: %i out of %i\\n' %(file_id + 1, N_BATCHES))\n",
"\n",
" tt = time.time()\n",
" file = pd.read_csv( os.path.join( path, '%s_%d.csv' %(file_base, file_id)), index_col = 0 )\n",
" print('Loaded data in %.2f seconds' %(time.time() - tt))\n",
" \n",
" tt = time.time()\n",
" indexed_data = file.set_index(['DF_UID', 'timestamp'])\n",
" print('Indexed data in %.2f seconds' %(time.time() - tt))\n",
" \n",
" tt = time.time()\n",
" data_xr = indexed_data.to_xarray()\n",
" print('Coverted to xarray in %.2f seconds' %(time.time() - tt))\n",
" \n",
" # change type of \"timestamp\"\n",
" timestamp_str = data_xr.timestamp\n",
" data_dt = data_xr.assign_coords( timestamp = pd.to_datetime(timestamp_str) )\n",
" \n",
" tt = time.time()\n",
" data_dt.to_netcdf( os.path.join( path, '%s_%d.nc' %(file_base, file_id)) )\n",
" print('Saved data in %.2f seconds' %(time.time() - tt))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"all_data = xr.open_mfdataset( os.path.join( path, file_base + '_*.nc' ) )"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 148)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
" * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
"Data variables:\n",
" poa_direct (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>\n",
" poa_sky_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>\n",
" poa_ground_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Clean tilted irradiance"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 148)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
" * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
"Data variables:\n",
" poa_direct (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>\n",
" poa_sky_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>\n",
" poa_ground_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>\n",
" poa_global (DF_UID, timestamp) float64 dask.array<shape=(9639231, 148), chunksize=(100000, 148)>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all_data['poa_global'] = all_data.poa_direct + all_data.poa_sky_diffuse + all_data.poa_ground_diffuse\n",
"all_data"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/walch/.local/lib/python3.6/site-packages/dask/core.py:137: RuntimeWarning: invalid value encountered in greater\n",
" return func(*args2)\n"
]
},
{
"data": {
"text/plain": [
"<xarray.DataArray 'timestamp' (timestamp: 5)>\n",
"array(['2001-01-15T16:00:00.000000000', '2001-05-15T04:00:00.000000000',\n",
" '2001-07-15T04:00:00.000000000', '2001-09-15T05:00:00.000000000',\n",
" '2001-12-15T07:00:00.000000000'], dtype='datetime64[ns]')\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T16:00:00 ... 2001-12-15T07:00:00"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"outliers = all_data.where(all_data.poa_global > 5000, drop = True)\n",
"outliers.timestamp"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"good_timestamps = all_data.timestamp[np.logical_not(all_data.timestamp.isin(outliers.timestamp))]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
" * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
"Data variables:\n",
" poa_direct (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_sky_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_ground_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_global (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_global_yearly (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(100000,)>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"poa_irrad_clean = all_data.sel(timestamp = good_timestamps)\n",
"poa_irrad_clean['poa_global_yearly'] = util.get_yearly_sum(poa_irrad_clean, 'poa_global') / 1000\n",
"poa_irrad_clean"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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"\n",
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"\n",
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"\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",
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"\n",
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"\n",
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" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
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"\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",
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"\n",
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"\n",
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"\n",
"mpl.figure.prototype._init_header = function() {\n",
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" '<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",
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" mouse_event_fn(event);\n",
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"\n",
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" 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",
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" function toolbar_mouse_event(event) {\n",
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" }\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",
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"\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",
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" 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",
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"\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",
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" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
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"<img src=\"data:image/png;base64,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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"poa_irrad_clean.poa_global_yearly.plot.hist(bins = 50, density = True)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"poa_irrad_clean.poa_global_yearly.plot.hist(bins = 50, density = True)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"poa_irrad_cleaned = poa_irrad_clean.drop(['poa_global', 'poa_global_yearly'])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
" * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
"Data variables:\n",
" poa_direct (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_sky_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_ground_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"poa_irrad_cleaned"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"poa_irrad_cleaned.to_netcdf( '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_interp_clean.nc')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get yearly dataframe"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"global_yearly = poa_irrad_clean.poa_global_yearly.to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>poa_global_yearly</th>\n",
" </tr>\n",
" <tr>\n",
" <th>DF_UID</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1466.928074</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>647.329211</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1230.609135</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1235.111256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1073.956770</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" poa_global_yearly\n",
"DF_UID \n",
"1 1466.928074\n",
"2 647.329211\n",
"3 1230.609135\n",
"4 1235.111256\n",
"5 1073.956770"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"global_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"global_yearly.to_csv('/scratch/walch/workspace_tilted_irrad/tilted_irradiance_interp_clean_yearly.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Validate results"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# to check old tilted irradiance\n",
"poa_irrad_clean = xr.open_mfdataset( '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_clean.nc', chunks = {'DF_UID' : 100000} )\n",
"poa_irrad_clean['poa_global'] = poa_irrad_clean.poa_direct + poa_irrad_clean.poa_sky_diffuse + poa_irrad_clean.poa_ground_diffuse"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
" * DF_UID (DF_UID) int64 1 2 3 4 ... 9890021 9890022 9890023\n",
"Data variables:\n",
" poa_direct (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_sky_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_ground_diffuse (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>\n",
" poa_global (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(100000, 143)>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"poa_irrad_clean"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"poa_mean = poa_irrad_clean.mean(dim = 'DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"poa_mean_df = poa_mean.poa_global.to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"poa_mean_df.to_csv('/scratch/walch/workspace_tilted_irrad/tilted_irradiance_interp_clean_mean.csv')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"poa_mean_df['hour_index'] = (poa_mean_df.index.month - 1)*18 + (poa_mean_df.index.hour - 3)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>poa_global</th>\n",
" <th>hour_index</th>\n",
" </tr>\n",
" <tr>\n",
" <th>timestamp</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2001-01-15 08:00:00</th>\n",
" <td>142.926207</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2001-01-15 09:00:00</th>\n",
" <td>180.189816</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2001-01-15 10:00:00</th>\n",
" <td>215.262471</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2001-01-15 11:00:00</th>\n",
" <td>228.916739</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2001-01-15 12:00:00</th>\n",
" <td>213.281537</td>\n",
" <td>9</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" poa_global hour_index\n",
"timestamp \n",
"2001-01-15 08:00:00 142.926207 5\n",
"2001-01-15 09:00:00 180.189816 6\n",
"2001-01-15 10:00:00 215.262471 7\n",
"2001-01-15 11:00:00 228.916739 8\n",
"2001-01-15 12:00:00 213.281537 9"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"poa_mean_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"LAT = 46.818188\n",
"LON = 8.227512\n",
"solpos = get_solarposition(poa_mean_df.index, LAT, LON)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"plot_array = np.zeros((12*18))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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"\n",
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" 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",
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"\n",
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"\n",
" this.image_mode = 'full';\n",
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" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
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"\n",
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"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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"\n",
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"\n",
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" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
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" 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",
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" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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"\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",
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" rubberband.mousedown('button_press', mouse_event_fn);\n",
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" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
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"\n",
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" } else {\n",
" event.step = -1;\n",
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" 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",
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"\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",
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" cursor = 'move';\n",
" break;\n",
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" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" 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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{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fb83a447828>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"\n",
"plot_array[poa_mean_df.hour_index.values] = poa_mean_df.poa_global\n",
"plt.plot(plot_array, '-o', label = 'mean $G_t$')\n",
"\n",
"# plt.scatter(poa_mean_df.hour_index, poa_mean_df.poa_global, c = 'C0')\n",
"\n",
"plot_array[poa_mean_df.hour_index.values] = 10 * solpos.apparent_elevation\n",
"plt.plot(plot_array, '--o', markersize = 3, label = 'sun altitude')\n",
"\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcd6c35a0f0>"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"\n",
"plot_array[poa_mean_df.hour_index.values] = poa_mean_df.poa_global\n",
"plt.plot(plot_array, '-o', label = 'mean $G_t$')\n",
"\n",
"# plt.scatter(poa_mean_df.hour_index, poa_mean_df.poa_global, c = 'C0')\n",
"\n",
"plot_array[poa_mean_df.hour_index.values] = 10 * solpos.apparent_elevation\n",
"plt.plot(plot_array, '--o', markersize = 3, label = 'sun altitude')\n",
"\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"all_data_mean = all_data.mean(dim = 'DF_UID').to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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xpwjvkpuV0e4IpaDOKGTFwmogwAFkAIoW4kUQFmCjCcBEtAlgTE7vTHnKAVQl42rg6QogBRA2TKmAMoSZDwJkIAuCYza4YV5x/yU3LyGV0ccR3td5smktEmAAkgBlK1cCqAsQcaTAAnoksDI7V6Yf9wkgJeHVUc8JwqgLhtao0lRACmAsqVLAZQlyHgSIAFdEhi+zQsL3UwC6Dm0GpxjOegyTyalTQIUQAqgbOVSAGUJMp4ESECXBIZuvYLFJ24puXkMqYYEsSmAumxojSZFAaQAypYuBVCWIONJgAR0ScBaAC8OroqEcRx1mSeT0iYBCiAFULZyKYCyBBlPAiSgSwKDt1zG0pO3ldzcB1VForgUQF02tEaTogBSAGVLlwIoS5DxJEACuiQwaPNlLDtlEsDzA12QJJ6TLvNkUtokQAGkAMpWLgVQliDjSYAEdElgwCZPrDh9R8nt7AAXJHOmAOqyoTWaFAWQAihbuhRAWYKMJwES0CWBfhs9seqMSQDPDKiC5M6xdJknk9ImAQogBVC2cimAsgQZTwIkoEsC/TZewqozd5XcTvevghTxKYC6bGiNJkUBpADKli4FUJYg40mABHRJoM/6S1hzziSAJ/tVRqoEsXWZJ5PSJgEKIAVQtnIpgLIEGU8CJKBLAr3Xe2DtuXtKbm59KyNNQgqgLhtao0lRACmAsqVLAZQlyHgSIAFdEui5zgPrz5sE8HifSkibKI4u82RS2iRAAaQAylYuBVCWIONJgAR0SaDH2ovYeOG+ktux3pWQLjEFUJcNrdGkKIAUQNnSpQDKEmQ8CZCALgn0WHMRG91NAnikV0VkSBJXl3kyKW0SoABSAGUrlwIoS5DxJEACuiTQbbU7Nl98oOR2uGdFZExKAdRlQ2s0KQogBVC2dCmAsgQZTwIkoEsCf6xyx1YPkwAe/LMCMieLp8s8mZQ2CVAAKYCylUsBlCXIeBIgAV0S6LLKHdvMAri/RwVkTU4B1GVDazQpCiAFULZ0KYCyBBlPAiSgSwKdV17AjksPldz29yiPrMmddZknk9ImAQogBVC2cimAsgQZTwIkoEsCnVdcwA5PkwDu7V4e2VNQAHXZ0BpNigJIAZQtXQqgLEHGkwAJ6JLAb8vPY9flR0puu7uVQ86U4uuSFwmogwAFkAIoW4kUQFmCjCcBEtAlgV+XncOeK4+V3HZ1LYdcqSiAumxojSZFAaQAypYuBVCWIONJgAR0SaDD0nPY62USwB1/lEWe1Al0mSeT0iYBCiAFULZyKYCyBBlPAiSgSwLtlpzDfm+TAG7vUhZ501AAddnQGk2KAkgBlC1dCqAsQcaTAAnokkC7JWex3/uJktvW38sgf9qEusyTSWmTAAWQAihbuRRAWYKMJwES0CWBXxafxcGrJgHc0rkMCqSjAOqyoTWaFAWQAihbuhRAWYKMJwES0CWB1ovO4LDPUyW3TZ1Ko1D6RLrMk0lpkwAFkAIoW7kUQFmCjCcBEtAlgVYLz+DINZMAbvitNIpkoADqsqE1mhQFkAIoW7oUQFmCjCcBEtAlgRYLTuPY9WdmASyFIhkS6zJPJqVNAhRACqBs5VIAZQkyngRIQJcErAVwXcdSKJaRAqjLhtZoUhRACqBs6VIAZQkyngRIQJcEfp5/Cm43niu5relQEiUyJ9FlnkxKmwQogBRA2cqlAMoSZDwJkIAuCfw09xRO+poEcHWHkihJAdRlO2s1KQogBVC2dimAsgQZTwIkoEsCTeeexCnfF0puK9uXQOksSXWZJ5PSJgEKIAVQtnIpgLIEGU8CJKBLAk3mnMQZP5MArmhXAmWyUgB12dAaTYoCSAGULV0KoCxBxpMACeiSQOPZJ3D21kslt2Vti6NctmS6zJNJaZMABZACKFu5FEBZgownARLQJYFGs07g3G2TAC79pTjKZ6cA6rKhNZoUBZACKFu6FEBZgownARLQJYEGM91w4c4rJbfFbYqhYo7kusyTSWmTAAWQAihbuRRAWYKMJwES0CWB+jPd4G4WwEWti6FSTgqgLhtao0lRACmAsqVLAZQlyHgSIAFdEqg7ww0ed009gAtbF0XlnCl0mSeT0iYBCiAFULZyKYCyBBlPAiSgSwI/TD+OS/f8ldzmtywKl9wUQF02tEaTogBSAGVLlwIoS5DxJEACuiRQ5+/j8LxvEsC5LYqgWp6UusyTSWmTAAWQAihbuRRAWYKMJwES0CWBWtOO4cqD10puc1oUQXUKoC7bWatJUQApgLK1SwGUJch4EiABXRKo+dcxeD00CeDs5oXhmjeVLvNkUtokQAGkAMpWLgVQliDjSYAEdEnAdepRXH30Rslt5s+FUTMfBVCXDa3RpCiAFEDZ0qUAyhJkPAmQgC4JVJ9yFD6PTQI4o1lh1MpPAdRlQ2s0KQogBVC2dCmAsgQZTwIkoEsC1aYcwbXHb5Xc/v6pEOoUSK3LPJmUNglQACmAspVLAZQlyHgSIAFdEnCZfAQ3npgE8K+mBVG3YBpd5smktEmAAkgBlK1cCqAsQcaTAAnokkCVSYdx8+k7JbepPxZEvUIUQF02tEaTogBSAGVLlwIoS5DxJEACuiRQeeJh+D4zCeCUHwugfqG0usyTSWmTAAWQAihbuRRAWYKMJwES0CWBihMO4dbz90pukxoXQMMiFEBdNrRGk6IAUgBlS5cCKEuQ8SRAArokUGHCIdw2C+CERvnRuGg6XebJpLRJgAJIAZStXAqgLEHGkwAJ6JJAufEHcffFByW38Y3yowkFUJftrNWkKIAUQNnapQDKEmQ8CZCALgmUGXsQ91+ZBHBcw3z4sVh6XebJpLRJgAJIAZStXAqgLEHGkwAJ6JKAtQCOaZAPPxWnAOqyoTWaFAWQAihbuhRAWYKMJwES0CWBUmMO4KH/RyW30fXzoVkJCqAuG1qjSVEAKYCypUsBlCXIeBIgAV0SKDn6AB69NgngyHp50bxkBl3myaS0SYACSAGUrVwKoCxBxpMACeiSQPFR+/HkTYCS24i6edCiVEZd5smktEmAAqheASwPoBeAIgDECeL1AWy2KrPFAFpFKrs9AFyt/lticQQlgDoAQgFsANAVgOlsItOVX5xTDqAYgKfm14//D+WsfQEMDQFunwDePgbipQAylAZs7f4DAr6UBEiABD4nUHTkfjx7axLA4XXzoCUFkGWiIgIUQPUKYA0AZQBcMIvblwQwBYA2VvUkvmleWv37LrM8/grAAcAiAGcBNDO/RsjbNQD7AYwBkA/AQgDdAMz9yjrVtgB6bQV29wFeP4hIN35qwHUckPuHr0TAl5EACZDAlwRwH569DVR+MLRObrQuk4mYSEA1BCiA6hVA6yIJ+4cewIQA6v1DNeUC4GXu2Ttnfo3oHdwJQGxHL4znNwCjAKQEYPqWAsaa75nzK6tUuwIo5G9tSwACr/VlY/qXJkspgV9ZBHwZCZDA5wQKj9iHF+9MX62Da+fGL2UpgKwT9RCgAGpbAIX8iW8X0et3EMBAAM/N5fWLOH0IQCKrcrMHIGYkNwawCcBSAELgrCWykvleYvjYujcx/DZOAMT/wi9nAPf8/f0RP764lUYuMew7Na+l588/LC7i4T3sbMJl0AYQPYHdPDkcrJEm5WOSgNoIFBq+Fy/fBymPNbBWLrQrl1ltj8jnMTABCqB2BbApAHHIpB+ALGKXAfPcvlIAQgD0N88RzBGpvp8AGAJgFoC95ngxRBx+5QZwBYD4f+8vfDaGmuM/+ZHmBNDvGLCktpLDk7CEKBcwFRVsPTDXccqnKbfaDmQqZ+CvCKZOAiQQVQIFhu2F/wcKYFT5MS56CVAAtSuAkStD/Gl5E4ALgAP/RwDFQo9BAGb/gwDmAXAZgBhCvvqF8tNHD6DnemBDWyW9M6E50CRwCDLaPMJhpx6fptxwAZCvUfR+Cnl3EiABXRLIN3QP3nwMVnLrXzMnOpQXf6vzIgF1EKAA6kcARUUJuRPDwHMARNcQcOTK1eYcQKsewJMhufBT0CCkt3mMo07d2QOoju8mPgUJaJ5AviF78CbAJIB9a+RExwoUQM03qo4SoADqRwDFwo475vl8W809eGIRSFEA5801Ww3A7i8sAhGriU3jFKah5AYA9L0IxDIH8CFOhORCs6CBSIOncIsldskRF+cA6uh7jqmQwHchkGfwbrwLFDNygD6uOfFbRQrgd2kIvukXCVAA1SuA8QBkNbeaOwAxNnkIwAvz/8Q8PrGv3yPzHECxd59YkCG2cjFtPAWIbWCE3HW02gZGrAgO3wYmAQAf81DwOAB5zdvAiG4w/W8DY14FfCwkL1oE9UNqPMOJWH+Y5E9cXAXMr00SIAEJArkG7caHIJMA9qqeA50rhX+lS9yUoSTwjQhQANUrgBXNwhe5qZeYt28Rm0IXAiC2ghFbuogFHWJu32OrALGSd3qkjaCF4VhvBF3A/BqxEfQz80bQQga/9tLmEHB4dl5bcWTLArTy74CUeI5TsboA8dMArmO5BczXVgBfRwIk8EUCOQftwscgsQc/0LNadvxeORtJkYBqCFAA1SuAqimSf3kQbQugsGzvR2iz5DySxQrD2VYJeBKIViqPz0kCKieQfeAuBAabBPDPqtnRpQoFUOVNZqjHowBSAGULXvMCeMD7MdouOYek8RxxbmBVWR6MJwESIAGFQPYBuxAYYhLA7i7Z0dWFAsjSUA8BCiAFULYaNS+Ae688Qodl55E4riMuDKIAyhYE40mABEwEsvbfieBQ0+byXatkQ/eq2YmGBFRDgAJIAZQtRs0L4O7Lj9Bx+XkkiO0AjyFioTQvEiABEpAnkLnfDpj9D39UyYYeFEB5qLzDNyNAAaQAyhaT5gVwl+dD/LbiApxj2cNzaHVZHownARIgAYVApn47EGY+XbJL5az4s1rkg5kIigS+HwEKIAVQtvo0L4DbLz3A7yvdEc/JHpeHUQBlC4LxJEACJgIZ++6woOhcKQt6Vf/a7VVJkASinwAFkAIoW2WaF8CtHg/wxyp3xHawg/cIV1kejCcBEiABhIWFIVO/nRYSYhNosRk0LxJQCwEKIAVQthY1L4Cb3e+j25qLcLK3hc/IGrI8GE8CJEACCAkNQ5b+EQIojoETx8HxIgG1EKAAUgBla1HzArjxwj30WOsBRztbXBtFAZQtCMaTAAkAQSGhyDZAHMZkun4tnxn9auYiGhJQDQEKIAVQthg1L4Drzt1Fr/WXYG9rgxuja8ryYDwJkAAJKBtAi42gw6/25TJhQK3cJEMCqiFAAaQAyhaj5gVw7dm76L3hEmxsAL8xtWR5MJ4ESIAE8DEoBDkH7baQaFc2EwbWpgCyNNRDgAJIAZStRs0L4Kozd9Bvo6fCwW9MTdgIE+RFAiRAAhIEIgvgL2UyYXAdCqAEUoZ+YwIUQAqgbElpXgBXnL6NAZsuKxx8R9eErS0FULYoGE8CRifwPjAYuQfvsWBoXTojhv6Qx+hYmL+KCFAAKYCy5ah5AVx28hYGbbmicLg+qgYc7GxlmTCeBEjA4ATeBgQj7xAKoMHLQNXpUwApgLIFqnkBXHLiFoZsNQmgz0hXONnbyTJhPAmQgMEJvPkYhHxD91ootCyVAcPr5jU4FaavJgIUQAqgbD1qXgAXuflh2DYvhcPVEa6I5UABlC0KxpOA0Qn4fwhCgWERAti8ZHqMrJfP6FiYv4oIUAApgLLlqHkBnH/MFyN3eCscrgyrjrhO9rJMGE8CJGBwAq/eB6Lg8H0WCs1KpMfo+hRAg5eFqtKnAFIAZQtS8wI476gvRu00CaDn0GpwjuUgy4TxJEACBifw8l0gCo2IEMCfiqfHmAYUQIOXharSpwBSAGULUvMCOPvITYzddVXh4DGkGhLEpgDKFgXjScDoBJ6/DUCRkfstGJoWS4exDfMbHQvzVxEBCiAFULYcNS+AMw/fwPjdPgqHi4OrImEcR1kmjCcBEjA4gWdvA1DUSgCbFE2L8Y0KGJwK01cTAQogBVC2HjUvgNMPXsfEvdcUDucHunEK5t4AACAASURBVCBJPCdZJownARIwOIEnbz6i+KgDFgqNi6TFhMYUQIOXharSpwBSAGULUvMCOO3AdUzeZxLAswNckMyZAihbFIwnAaMTePz6I0qMjhDAhoXTYlITCqDR60JN+VMAKYCy9ah5AZyy7xr+OnBd4XCmfxUkjx9LlgnjSYAEDE7gkf9HlBwTIYANCqXB5B8LGpwK01cTAQogBVC2HjUvgJP3+mDawRsKh5P9KiNVgtiyTBhPAiRgcAIPXn1A6bEHLRTqF0qDKRRAg1eFutKnAFIAZStS8wI4Yc9VzDh0U+Hg1rcy0iSkAMoWBeNJwOgE7r/6gDJWAli3YGr81bSQ0bEwfxURoABSAGXLUfMCOG73Vcw6bBLAY70rIV3iOLJMGE8CJGBwAndfvEe58YcsFOoUSI2/f6IAGrwsVJU+BZACKFuQmhfAMbu8MeeIr8LhSK+KyJAkriwTxpMACRicwJ3n71F+QoQA1s6fCtObFTY4FaavJgIUQAqgbD1qXgBH7fDCvGN+CodDPSsiU1IKoGxRMJ4EjE7g9vN3qDDhsAVDrXypMONnCqDR60JN+VMAKYCy9ah5ARyx3QsLjpsE8MCfFZAlWTxZJownARIwOAG/Z+9QaWKEANbImxKzmhcxOBWmryYCFEAKoGw9al4Ah269gsUnbikc9nUvj2wpnGWZMJ4ESMDgBHyfvkXlSUcsFKrnSYE5LYoanArTVxMBCiAFULYeNS+AQ7ZcxpKTtxUOe7qVR46UFEDZomA8CRidwI0nb+EyOUIAq+VOgbktKYBGrws15U8BpADK1qPmBXDgZk8sP3VH4bCraznkSiVS4kUCJEACUSdw/fEbVJ1y1HIDl1wpML8VBTDqRBn5rQlQACmAsjWleQHsv8kTK0+bBHDHH2WRJ3UCWSaMJwESMDiBa4/foJqVAFbJmRwLWhczOBWmryYCFEAKoGw9al4A+264hNVn7yoctv1eFvnSUgBli4LxJGB0AlcfvYbr1GMWDJVzJsdCCqDRy0JV+VMAKYCyBal5Aey93gNrz91TOGzpXAYF0iWUZcJ4EiABgxPwevAaNadFCGDFHMmwuE1xg1Nh+moiQAGkAMrWo+YF8M+1HthwwSSAmzqVRqH0iWSZMJ4ESMDgBK488EetacctFMpnT4alv1AADV4WqkqfAkgBlC1IzQtgjzUXsdH9vsJhw2+lUCRDYlkmjCcBEjA4gcv3/VH77wgBLJctKZa1LWFwKkxfTQQogBRA2XrUvAB2Xe2OLRcfKBzWdSyFYhkpgLJFwXgSMDoBz3v+qDM9QgDLZk2K5e0ogEavCzXlTwGkAMrWo+YFsMsqd2zzMAngmg4lUSJzElkmjCcBEjA4AY+7r1B3hpuFQuksSbCyfUmDU2H6aiJAAaQAytaj5gWw88oL2HHpocJhZfsSKJ0lqSwTxpMACRicgPudl6g/84SFQqnMSbCqAwXQ4GWhqvQpgBRA2YLUvAD+tvw8dl1+pHBY0a4EymSlAMoWBeNJwOgELtx5iQZWAlgiU2Ks+bWU0bEwfxURoABSAGXLUfMC+Ouyc9hz5bHCYVnb4iiXLZksE8aTAAkYnMD52y/QcNZJC4XiGRNjbUcKoMHLQlXpUwApgLIFqXkBbLfkHPZ7mwRwcZtiqJgjuSwTxpMACRicwLlbL9BodoQAFs2QCOt/K21wKkxfTQQogBRA2XrUvAC2XXwWB64+UTgsal0MlXJSAGWLgvEkYHQCZ/xeoMmcCAEskiERNlAAjV4WqsqfAkgBlC1IzQtg60VncNjnqcJhQauiqJIrhSwTxpMACRicwCnf52g695SFQqH0CbGpUxmDU2H6aiJAAaQAytaj5gWw5cIzOHrNJIDzWhZF1dwUQNmiYDwJGJ3AyZvP8dO8CAEUR0yKoyZ5kYBaCFAAKYCytah5AWw+/zSO33imcJjdvAhc86aUZcJ4EiABgxM4ceMZms0/baFQIG0CbPm9rMGpMH01EaAAUgBl61HzAths3imcuPlc4TDr58KokS+VLBPGkwAJGJyA241n+NlKAPOlSYBtXSiABi8LVaVPAaQAyhak5gXwxzkncdrvhcJhRrPCqJWfAihbFIwnAaMTOHb9KVosOGPBkCd1fOz4o5zRsTB/FRGgAFIAZctR8wLYZPZJnLllEsBpPxXCDwVSyzJhPAmQgMEJHLn2FK0WRghg7lTxsbMrBdDgZaGq9CmAFEDZgtS8ADaadQLnbr9UOPzVtCDqFkwjy4TxJEACBidw2OcJWi86a6GQM6Uzdncrb3AqTF9NBCiAFEDZetS8ANaf6Qb3O68UDlN+LID6hdLKMmE8CZCAwQkcuvoEbRZHCGCOFM7Y050CaPCyUFX6FEAKoGxBal4A685wg8ddkwBObFwAjYpQAGWLgvEkYHQCB7wfo+2ScxYM2VPEw97uFYyOhfmriAAFkAIoW46aF8A6fx+H531/hcP4RvnRpGg6WSaMJwESMDiB/V6P0W5phABmTR4P+3tQAA1eFqpKnwJIAZQtSM0LYK1px3DlwWuFw7iG+fBjsfSyTBhPAiRgcAJ7rzxCh2XnLRQyJ4uLg39WNDgVpq8mAhRACqBsPWpeAF2nHsXVR28UDqPr50OzEhRA2aJgPAkYncCeK4/wq5UAZkoaF4d6UgCNXhdqyp8CSAGUrUfNC2D1KUfh89gkgCPr5UXzkhlkmTCeBEjA4AR2X36IjssvwMYGCAsDMiaJg8O9KhmcCtNXEwEKIAVQth41L4Auk4/gxpO3CocRdfOgRamMskwYTwIkYHACOz0fotOKC7C3tUFwaBjSJ46Do70pgAYvC1WlTwGkAMoWpOYFsPKkw/B9+k7hMOyHPGhVmgIoWxSMJwGjE9hx6SE6r7wAJ3tbBASHIm2i2Djep7LRsTB/FRGgAFIAZctR8wJYccIh3Hr+XuEwuHZu/FI2kywTxpMACRicwDaPB+iyyh1xHO3wPjAEaRLGhltfCqDBy0JV6VMAKYCyBal5ASw//hDuvDAJ4MBaudCuXGZZJownARIwOIGtHg/wxyp3ODvZ401AMFIniIUT/aoYnArTVxMBCiAFULYeNS+AZccdxL2XHxQOA2rmQvvyFEDZomA8CRidwJaL99F19UUkiO0A/w9BSBk/Fk71pwAavS7UlD8FkAIoW4+aF8DSYw7ggf9HhUPfGjnRsUIWWSaMJwESMDiBTe730H2NB5LEdcTzd4FIEd8Jp/u7GJwK01cTAQogBVC2HjUvgCVHH8Cj1yYB7O2aA50qZpVlwngSIAGDE9h44R56rPVAMmcnPH0ToPz/2QEUQIOXharSpwBSAGULUvMCWGzUfuULWly9qudA50oUQNmiYDwJGJ3A+vP30HOdhzL0K/7ATBrPEecGVjU6FuavIgIUQAqgbDlqXgCLjtyHZ28DFQ49qmbHH1WyyTJhPAmQgMEJrDt3F73WX1JW/95/9UEZCj4/iAJo8LJQVfoUQAqgbEFqXgALDd+Ll++DFA7dXLKhm0t2WSaMJwESMDiBtWfvoveGS8oG0GKXgURxHOA+uJrBqTB9NRGgAFIAZetR8wJYYNheZZWeuETvn+gF5EUCJEACMgRWn7mDvhs9Ic4A9nv2TlkN7DGEAijDlLHflgAFUL0CWF5MSQNQBEAqAPUBbLZqfhtxcAWA9gASAnAD8BuA61avSQzgbwB1AIQC2ACgKwDTuWemKz+AGQCKAXhqfv34/1BmmhfAfEP2KPt0iev3SlnRs3qO/5A+X0oCJEACnxNYdeYO+m30RNbk8ZSjJp1j2cNzaHWiIgHVEKAAqlcAawAoA+CCWdwiC2AfAP0AtAbgK46xBZAPQG4ApiWtwC6zPP4KwAHAIgBnATQz/1zI2zUA+wGMMccvFCOhAOZ+ZZVqXgDzDN6Nd4EhSrqdKmZBb9ecX5k6X0YCJEACXyaw4vRtDNh0GTlSOMPn8RtlQ2jPYRRA1ot6CFAA1SuA1lUSFqkHUPT+PQAwCcBE8wsTAHhsFsLVAHIB8DL37J0zv8YVwE4Aac3xosdwFICUAEyrIICxAOoB+FoL0rwA5hy0Cx+DRAcplD0AxV6AvEiABEhAhsCyU7cxaPNl5EoVH94PXyOuox2uDBdfwbxIQB0EKIDaFEBxVMVNAIUAXLQqpSPmfxfDvL+YBTGR1c/tzb2DjQFsArAUgBA4IXzhVyUABwGI4eOXXyhTJwDif+GXM4B7/v7+iB9f3Ep7V/aBuxAYbBLAX8tnRr+awp15kQAJkEDUCSw7eQuDtlxBvjQJ4HnfH7Ed7OA9ggIYdaKM/NYEKIDaFMDS5jl/qQE8tCqKtQBEb+GPAPoDaAUg8oS2JwCGAJgFYC8AP+E9VvcQQ8hXzEPJ3l8ouKHm+E9+pGUBzNp/J4JDBTagXdlMGFhbIOBFAiRAAlEnsOTELQzZegUF0iWEx91XiOVgi6sjxMweXiSgDgIUQH0J4DoAYjJb0/8jgGKhxyAAs/9BAPMAuGweQr76hTLVXQ9g5n47YPY//FImEwbXoQCq4+uJT0EC2iWw2M0PQ7d5oXD6hLhw5xUc7W1xbSQFULstqr8npwBqUwC/5xBw5E+B5ucAZuy7w5JT69IZMfQH4cC8SIAESCDqBBYe98Pw7V4oljERzt56CQc7G1wfVTPqN2QkCXxjAhRAbQpg+CIQsQBELAQRlxAxMbwrVgVbLwIpCuC8+TViE6rdX1gEkgKAaSM8YDSABkZZBBIaGobM/cW6GNPVslQGDK+b9xt/zHg7EiABoxGYf8wXI3d4o2TmxDjl+wL2tja4MZoCaLQ6UHO+FED1CmA8AOGH0rqLU8oAHALwAsAdAGIbmL7meX5iHp/YBkbs6Rd5Gxghdx2ttoERK4LDt4ERK4d9zEPB4wAI8xHbwHQ3yjYwwSGhyDpA7JZjupqXTI+R9cRuOrxIgARIIOoEwgWwTNYkcLvxHLY2gO+YWlG/ISNJ4BsToACqVwArmoUvcpMvMffyhW8E3cG8EfRxsY2deV+/8Bixknd6pI2g/4i0EXQB82vERtDPzBtBCxn82kvTQ8ABwSHIMVB0ipquZiXSY3R9CuDXNj5fRwIk8GUCc4/exOidV1EuW1Icuy6+WoFbYymArBf1EKAAqlcA1VMl//9JNC2AH4NCkHNQhAA2LZYOYxuKjlReJEACJBB1AnOO3MSYXVdRKUcyHPIRa+8AvzE1YWMj/nbnRQLfnwAFkAIoW4WaFsB3AcHIM2SPhUGTomkxvpHoFOVFAiRAAlEnMOvwTYzbfRUuuZJjv7eYng34jq4JWzEWzIsEVECAAkgBlC1DTQvgm49ByDdUbIdouhoVSYuJjSmAskXBeBIwOoEZh25gwh4fVMudAnu9xCFNwI1RNWBvZ2t0NMxfJQQogBRA2VLUtAD6vw9CgeERAtigUBpM/rGgLBPGkwAJGJxAuADWzJcSOz0fKTTEPoBiP0BeJKAGAhRACqBsHWpaAF++C0ShEfssDOoVTI2pTcUJe7xIgARIIOoE/j5wHZP2XUPt/Kmw/ZLpwCafka5wsreL+k0ZSQLfkAAFkAIoW06aFsBnbwNQdOR+C4MfCqTGtJ8ogLJFwXgSMDqBaQeuY/K+a6hbMDW2XHyg4Lg6whWxHCiARq8NteRPAaQAytaipgXwyZuPKD7qgIWB+Gt9erPCskwYTwIkYHACU/dfw9T919GgcBpsvHBfoeE1vDriONobnAzTVwsBCiAFULYWNS2Aj19/RInREQIo5uvM/LmILBPGkwAJGJyA6P0TvYCNi6TFuvP3FBpXhlVHXCcKoMFLQzXpUwApgLLFqGkBfPDqA0qPPWhh4JonJWa3oADKFgXjScDoBCbv9cG0gzcg9hZdffaugsNzaDU4x3IwOhrmrxICFEAKoGwpaloA7718j7LjxAl7pkts2TC3pTg+mRcJkAAJRJ3AxD0+mH7ohnK60MrT4vROwGNINSSITQGMOlVGfksCFEAKoGw9aVoA7zx/j/ITIgRQbNo6v5U4FY8XCZAACUSdwPjdVzHz8E20LJUBS0/eNgng4GpIEIcCGHWqjPyWBCiAFEDZetK0AN569g4VJx62MKicMzkWtqYAyhYF40nA6ATEKSDiNJDWpTNi8YlbCg73QVWRKK6j0dEwf5UQoABSAGVLUdMCePPpW1SZdMTCoGKOZFjcprgsE8aTAAkYnMCYXd6Yc8QXbctmwoLjfgqN8wNdkCSek8HJMH21EKAAUgBla1HTAnjjyRu4TD5qYVAuW1Isa1tClgnjSYAEDE5gzE5vzDnqiw7lM2PuUV+FxtkBLkjmTAE0eGmoJn0KIAVQthg1LYA+j96g+tQIASybNSmWt6MAyhYF40nA6ARG7fDCvGN++LWCSQDDwoAzA6oguXMso6Nh/iohQAGkAMqWoqYF0Pvha9T465iFQeksSbCyfUlZJownARIwOIER272Uod+OFbJg3jFfhISG4XT/KkgRnwJo8NJQTfoUQAqgbDFqWgAv3/dH7b+PWxiUzJwYqzuUkmXCeBIgAYMTGL7NCwvd/NCpokkAg0LCcLJfZaRKENvgZJi+WghQACmAsrWoaQH0vOePOtMjBLB4xsRY25ECKFsUjCcBoxMYuvWKsvq3cyUhgH4IDA7Fib6VkTohBdDotaGW/CmAFEDZWtS0AF68+wr1ZrhZGBTNkAjrfysty4TxJEACBicQLoBdKmdV5gAGBIfieJ9KSJsojsHJMH21EKAAUgBla1HTAnjhzks0mHnCwqBw+oTY2KmMLBPGkwAJGJzA4C2XlQ2g/6iSDfOO+uJDUAiO9a6EdIkpgAYvDdWkTwGkAMoWo6YF8PztF2g466SFQYF0CbGlMwVQtigYTwJGJzBwsyeWn7qDrlWyYf4xX7wLDMHRXpWQPgkF0Oi1oZb8KYAUQNla1LQAnvF7gSZzIgQwf9oE2Pp7WVkmjCcBEjA4gQGbPLHi9B10d8muLAJ5GxCMwz0rImPSuAYnw/TVQoACSAGUrUVNC+Ap3+doOveUhUHeNPGxvUs5WSaMJwESMDiBfhs9serMHfSoahLANx+DcfDPCsicLJ7ByTB9tRCgAFIAZWtR0wJ44sYzNJt/2sIgV6r42NWVAihbFIwnAaMT6LfxEladuYue1YQA+sH/QxAO/FkBWSiARi8N1eRPAaQAyhajpgXw+PVnaL4gQgBzpnTG7m7lZZkwngRIwOAE+qy/hDXn7qJX9RxKD+Cr90HY36M8siZ3NjgZpq8WAhRACqBsLWpaAI9ce4pWC89YGGRPEQ97u1eQZcJ4EiABgxPotc4D687fQ2/XHJh/zA8v3gVib/fyyJ6CAmjw0lBN+hRACqBsMWpaAA/5PEGbRWctDLIki4sDf1aUZcJ4EiABgxPouc4D68/fQ98aOZVVwM/eBmJ3t3LImVJ8ZfIige9PgAJIAZStQk0L4AHvx2i75JyFQeakcXGwJwVQtigYTwJGJ9Bj7UVsvHAf/WvmxNyjfnj2NkCZXyzmGfMiATUQoABSAGXrUNMCuM/rMdovjRDAjEni4HCvSrJMGE8CJGBwAt3XXMQm9/sYUDOXMgfwyZsA7PijLPKkTmBwMkxfLQQogBRA2VrUtADuvvwIHZefh60NEBoGpE8cB0d7UwBli4LxJGB0At1Wu2PzxQcYWCuXMgfw0euP2N6lLPKmoQAavTbUkj8FkAIoW4uaFsBdng/x24oLcLS3VQ5rT5MwNtz6VpZlwngSIAGDE/hjlTu2ejzAoNq5seCYLx74f8S238siX1oKoMFLQzXpUwApgLLFqGkB3HHpITqvvIC4jnbKUU2pE8TCiX5VZJkwngRIwOAEuqxyxzaPBxhSJ7fSA3j/1QflmElx3CQvElADAQogBVC2DjUtgOIvdPGXevxY9nj9MRgp48fCqf4UQNmiYDwJGJ2A+MNS/IE57Ic8yhzAey8/YFOn0iiUPpHR0TB/lRCgAFIAZUtR0wK45eJ9dF19EUniOuL5u0Akc3bC2QEuskwYTwIkYHACnVacx07PRxheN4/SA3jnxXts7FQahSmABq8M9aRPAaQAylajpgVw44V76LHWAyniO+Hx6wAkjeeIcwOryjJhPAmQgMEJ/Lb8PHZdfoQR9fIq+wDefv4eG34rhSIZEhucDNNXCwEKIAVQthY1LYBio1axYatY/CHm6CSO64gLgyiAskXBeBIwOoFfl53DniuPMbJeXiw47ge/Z++wrmMpFMtIATR6baglfwogBVC2FjUtgGvP3kXvDZeQIUkc5S/0BLEd4DGkmiwTxpMACRicQIel57DX6zFG18+H+cd94fv0Hdb+WgrFM1EADV4aqkmfAkgBlC1GTQvg6jN30HejJ8QRcDefvoNzLHt4Dq0uy4TxJEACBifQbsk57Pd+jLEN8imLQMT3y+oOJVEycxKDk2H6aiFAAaQAytaipgVwxenbGLDpMnKmdMbVR28Qz8kel4dRAGWLgvEkYHQCbRefxYGrTzCuYT5lEcj1J2+xsn0JlM6S1OhomL9KCFAAKYCypahpAVx26jYGbb6MvGni4/L914jtYAfvEa6yTBhPAiRgcAK/LD6Lg1efYHyj/FhwzA8+j99gRbsSKJOVAqjp0ggNAW6fAN4+BuKlADKUBmztNJkSBZACKFu4mhbAJSduYcjWK8rmrB53X8HJ3hY+I2vIMmE8CZCAwQm0XnQGh32eYmLjAsoqYDHCsLxtCZTNRgHUbGl4bQV29wFeP4hIIX5qwHUckPsHzaVFAaQAyhatpgVwkZsfhm3zQtEMiXDu9ks42tni2igKoGxRMJ4EjE6g1cIzOHLtKSYJATzuB++Hr7H0l+Ionz2Z0dFoM38hf2tbAgiL9Pw2pn9vslRzEkgBpADKfhg1LYBie4YR271QMnNinPJ9AXtbG9wYXVOWCeNJgAQMTqDFgtM4dv0ZpvwoegD9cOXBayxuUwwVcyQ3OBkNpi+GfafmtfT8vQ9zwvMwZ6SzfWZOxgYQPYHdPDU1HEwBpADKfho1LYDzjvpi1E5vlMuWVPmytrEB/MbUkmXCeBIgAYMTaD7/NI7feIapPxZU9gH0vO+PRW2KoRIFUHuV4XcMWFLb8twtAvvCLTQvjjp1Q1qbcAkE0Go7kKmcZvKjAFIAZYtV0wI458hNjNl1FZVyJMMhn6cKC78xNWEjTJAXCZAACUSRwM/zT8HtxnP81dQkgJfu+WNh66KonDNFFO/IsO9GwHM9sKGt5e3LBkzFvbDkWO04HCVtr0Y8VsMFQL5G3+0x/+sbUwApgP+1ZiK/XtMCOPPwDYzf7QOXXCmUPbvE5Tu6JmxtKYCyhcF4EjAygZ/mnsJJ3+f4+6dCyhxAschsfsuicMlNAdRcXUTqASz58W88QhIscxiNcnaXI9JhD6Dmmpa/6eWaTNMCOOPQDUzY44MaeVMq53aK6/qoGnCws5WjwmgSIAFDE/hxzkmc9nuB6c0KKT2A7ndeYV7LoqhKAdReXVjmAD5UFoEU/TgLz5AACx3Go7LdRSj9SJwDqL12NbUcLwkCmhbAaQeuY/K+a6hTIDW2eZiW9vuMdIWTvTb3dZJoR4aSAAl8QwJN5pzEGb8XmPlzYWUbmAt3XmFOiyKoniflN3wX3irGCFhWAQMFPs6BP+JhjsNkVLc7b3oErgKOsab4lm9EAZSjqWkBnLr/Gqbuv44GhdJgo/t9hcTVEa6I5UABlCsLRsc4AbVuUKvW54rmBmo8+wTO3nqJWT8XVnoAxTZTs5sXhmveVNH8zrx9tBEw7wOY58kIvENsTHf4C7UT3QNcx2puCxjBiHMA2QMo+1nRtABO3uuDaQdvoEnRtFh77p7C4sqw6ojrZC/LhfEkEHME1LpBrVqfKwZaptGsE2bpK4KFx/1w5papN7BmPgpgDOCPvrcIDUH2QbsRGAJMqRQL9atW1NTWL9ZgKIAUQNkPiqYFcOIeH0w/dAPNSqTHytN3FBaeQ6vBOZaDLBfGk0DMEPjHDWrNb99oCZC3Xsw8i/W7qPW5YohEg5luyrDv3BZFlEUgYjh4RrPCqJWfAhhDTRBtb5O53w6EhgHjG+ZHk2Lpou19ovvGFEAKoGyNaVoAx+2+ilmHb6JlqQxYevK2wsJjSDUkiE0BlC0MxscAgUgb1H7xHW1sgUaLgDwxKIFqfa4YaJLwt6g3ww0X75oWfiw47qtsNC9WBIv5xry0SyA0NAyZ++9UEhhZLy+al8yg2WQogBRA2eLVtACO2eWNOUd80aZMRixyu6WwcB9UFYniOspyYTwJRD+BSNtTLAt2weOwROhivwlONsGfvn+TZTE3T8nqud6GxcLgoDbIYPsIv9tthp1NpKO0YvK5or9FLO9Qd4absvXLglZCAP1w4qZpT8C6BdPE4FPwrb41gYDgEOQYuFu57dA6udG6TKZv/RYxdj8KIAVQttg0LYCjdnhh3jE/dCifGXOP+ioszg90QZJ4TrJcGE8C0U9gdz/g1EzlfdxC8uDnoAHKP1e0vYjZDlMQyyYo4hnip4m5o6qsnmtSUGP8HVJfeQ4X23OY5jADcWwCvs9zRX+LWN7hh+nHLZs/CwEM3xSaAhiDjRANb/UuIBh5huxR7jygZi60L585Gt4lZm5JAaQAylaapgVQnAMsvpw7VsiCOUdvIiwMODvABcmcKYCyhcH4aCagzLFrobxJQJg9agSOhW9YxPBiBduLWOgw4dMet5jYqNbquR6HJUSFgCn4CCfYIQQhsENp28tY6Tj6Uzgx8VzR3ByRb1/n7+OW49/EIpDwc4HrF0obw0/Ct/uWBF69D0TB4fuUW/aqngOdK2X9lreP0XtRACmAsgWnaQEctu2KMvTbuVIWzD7ii5DQMJzpXwXJ48eS5cJ4vRJQw7YmkebYzQiuiwnBPyIpXmG0wwJ0DeqMD4iFRQ7jUMnOI6IlovuoqkjP1SeoPdaEVEIRGx/0BAjBPwAAIABJREFUd1iJpoGDEAR7HHTsgcy2po3XlSu6n+s71GKtacdw5cFrLPmluPJH5tFrTzGpcQE0LEIB/A7N8c3e8umbABQbtV+5XzeXbOjmkv2b3Tumb0QBpADK1pymBXDIlstYcvI2ulTOitlHbiIoJAwn+1VGqgSxZbkwXo8E1LKtidUcu3dhTigaMEsRvqkOM1DPzg39g37ByhAXtLTbi+EOiyNaIrp72qye62ZoKlQNnIBQ2GKD4xAUsb2O5oH9cDw0HwbaL0c7e9NEeuWK7uf6DrVY469j8H74Gkt/KY6Fbn447PMUExsXQCMK4HdojW/3lg/9P6DUmIPKDUXHQa/qOb/dzWP4ThRACqBsyWlaAAdtvoxlp26ja5VsigAGBIfCrW9lpElIAZQtDN3F/+O2Jua95GPyJACrw+mPh+RF86D+SIOnOO7UFTY2wP6QwmgX1BNpbZ7gmGM32Ij/GBNHVVk914JgV4wIbomytp5Y7jhGKYeFwa4YHtwSJW2vYLXjKFOJOKcGul/W7F5q/1TnrlOP4uqjN1jetoSyCviQz1OMb5QfTYpqd9sQ3X2mo5DQ3RfvUW78ISXy1/KZ0a9mrijcRR0hFEAKoGwlaloA+2/yVPb/6+6SXRHAD0EhONa7EtIljiPLhfF6IvA125rEpMhY9bRNCWqIv0Iaop7tcUx1NC0IeR/mhIIBcxAIR+x37Imstg+AmNgP0Oq5Ogd2wY7QUuhlvwad7bcoz3U7NDkqBE5V5gNecPoVCWzeA7ETA3X+irkVyjFUl9WnHIXP4zdY2U4IoB8OXH2CcQ3z4cdi6WPoCfg20UHA9+lbVJ50RLm12D1iSJ080fE2MXJPCiAFULbQNC2A/TZewqozd9GzWnZlP8B3gSE40qsiMiSJK8uF8d+CgBrm24k8Do8DDkcsXNgWUhJbQspggP0KZLKey1axP1Cxz7fI/P/fw+pw+p8D+8EtNC9G2C9EC3vT3CRxtQzsg6OhBdDffgU62O8w9QC6jote0bJ6rtIf/8IDJMVKh5EobedleS6XgPG4EZYW0xz+xg92JyOOY4/JHlTxNNFcW9WmHMG1x2+xsn0JLDx+C/u9H2Nsg3xoWpwCGP0fkOh7h2uP36DalKPKGzQvmR4j6+WLvjeL5jtTACmAsiWmaQHsvd5DOQJOrOYSPYBvPgbjUM+KyJSUAihbGNLxaplvZ7WqVeR0KTQTGgYOUxYzZLG5j82Og+Fs8yEi3Zja185rK4LXtEb+gHl4j1jY7dgHOW3vWp5jUXB1DAtuhVK2V7BKGW6NoaFqr614tKYrSgZMhy1C4enUFnGttn0ZE9QUc0J++KTHUnm2mBiiDqfzpdqKnRAo0Qko3/ObDEe7TD6CG0/eYnWHkkoP4D6vxxhdP59y6hAv7RK48sAftaYdVxL4sWg6jGuUX7PJUAApgLLFq2kB7LnOA+vP30PfGjmVHkD/D0E48GcFZEkWT5YL42UIqOUYsUhDv2JT49qBo3ErLKUlu2q2ZzHbYSpswzc4jqn99kJD4LltOuqczApnvIOHUwfTM4iTP8JCcSs0BSoGToE9gpXh1viKpMaMaO3atRW/HbFDLptb2OXU/5NKOBOaA00ChyAB3irP9cnG0DGxGOTfausbDUlXnnQYvk/fYU2HksoikD1XHmv+5AiZj7ReYsXm3mKTb3E1KJQGk38sqNnUKIAUQNni1bQA9lhzERvd76N/TZMAvnwfhH3dyyNbCmdZLoyPKoGvmW8XU8ebRTppI3x1bWo8wxiH+Wgf9CcC4YBJDrPQ0O5YRMbRLTLmHqyFL/Iriyoq2bpjUYJ5QPZagMcKy3NUDpio7A04z2EiqtpdiJnnCw3B6NUHMfdSIJplfIPRpW2Bp9eAYxOU9w8Os0X+gPlKr6VlfmL4k0X3djCRaisozA4ONiFfqFQbQHJIuvLEw/B99g7rOpaC2Adw1+VHGFE3D1qUyhjVTwbjVEDg/O0XaDhLTF0AaudPhenNCqvgqaL2CBRACmDUKiciStMC2G21OzZffICBtXIpQ8DP3gZiT7fyyJGSAihbGFGOt5KuJ2EJIfa4q2V3CsVtfT6/ZXQPt1qtag0Js0HBgHl4gzhY6jAG5e08MTmoEaaFNIDoBZzrOCXi+aJTZKx6sDoH/oEdoSXNCy22Avj0mLUegR2xMbQ8utuvQ1f7TdH/fGYxbfS0Pc6F5cBEh1lolOgmULj1J3MoGwQMxYWw7PjL4W/UVeYBmq/oFmffI8DSH5Q32xtSBJ2CuqKkrTcG2y9Fdtv7n9aXZE9uxQmHcOv5e2z4rZQyBLzT8xGG182DlhTAKH81qCHwlO9zNJ17SnkU1zwpMbtFETU8VpSegQJIAYxS4VgFaVoAu6xyxzaPBxhcOzdmHbkJscnnrq7lkCuVSIvXdyFwaS2wsb3y1uErSR0QjPEOc1DfzjT0Yrkkf0n/a35WMno5NKMy/OuM97jo1F4ZuhTzAX8IHKX8NzGcaelNii6RserBEqfWlAiYgSdIhDWOw1HC9upn6cwPromRwc1Rw/Y0Zjn+Fb2iZRbTwDBb5AtYgAA44oDjn8iiLJIJM632/fBS+ecBQb9gRYgLOtptRV+H1TEzNC2eb1sX4MMrCJkXexSGn5wiViWPtZ+Hxvamyf2WS6Idy48/hDsvhACWVoaAd1x6qPmzY//182KAFxy//gzNF5xWMq2SMzkWtC6m2awpgBRA2eLVtAB2XnnB8sUsBPDx6wBs71IWedMkkOXC+KgQEL+kt3cD3j/HjdDUqBo4HmGwtdxpvP0cNLE3bcHwLX5J/+sjWq1qnR9cQ5GpyrYXsNBxohIaGmaDIgGz8RLOWOc4DMVEL2WcpEAPb8De8V9v/59fYCWkd0OTolzgNAg5FgstPjn313zj8D0CM9o8wmGnHtEnWlZi6hGaGXUDRypz/C46dVD2JVS+ZmMnMgsgsDy4MgYGt4U4rm6Jo2loWHbI9f+yjDTvb3tICfwe1FV5RtFm+0OLWO2ZaHUniZ7ccuMP4u6LD9jUSQjgLcsfmr+UzfSfm50B6iFw6OoTtFl8VnmgctmSYlnbEup5uP/4JBRACuB/LJnPXq5pAey04rwyNCPm5og5gA/8P2Lb72WRLy0FULYw/nN8pF/S4cOXLrbnkdbmKRaHuCKrzT3sd+r96a0lfkl/1TOan6tdYA9FFPrZr8Sv9tstoV0Cf8e20NLoYrcJfzqsM/336NpyxWpI+lBIAbQJ6oOcNnew26nvF1KxwbMwZxQNmA0bhOKyUzvTalzJuW1fZGYlpsuCXTAo+Bez3I3/9OVim5wLi3HhVRw0CByOZHiJs8lHA65jo297mkjz/oS01wwcg6th6dHNfj1+tduOQgFzlPOKdzn2QS6rldQyJ5SUGXsQ9199wObOZZQ5gFs9HmBQ7dxoSwH8qo+dWl+098ojdFh2Xnm8kpkTY3WHUmp91H99LgqgdgVwKIAhkVpYTJIKP5dGHGY7CUBTAE4A9gDoBOCxVYzYj2AWgEoA3gJYAqCfmKf9r5UT8QJNC+Cvy85ZVucJARRf2Fs6l0GBdAn/AwK+VJpApF/Sd0KTo1LgJITADlscByKjzWPll7Q4Vuyk0+9IZfMi4i0lhum+6rlDQxByZCIK7c2M12FxlOcpYOtrWW27Lrg8egV3RAGbm9jiNMh8y2jacsVKtMJP1fhseFc8gVm08PoBin2cgadIhE2JpqFQnc7RI1pWYjo8qDkWhtREe7vtGOCw8nNZz1Mf72+4Ic/C1wiDDc71r4Sk8aNx4/VIC3nCT0mJh/fKySkJbd7BJPdFP50rKbmxd7gAbv3dJIDhc43blcv8VWXHF6mTwE7Ph+i0wrSgqkiGRMoQv1YvCqC2BbARABer4hPi9sz870LsagFoDcAfwHQxYgWgjPnndgAuAhATdHoBSAVgKYB5AD7dt+H/V7emBbD90nPK/lxjGuTDzMM3LEM2hdIn0upnWpvPHemXdPheceVsL2GZ41glp7oBw+ERlhUT7Geb52rFwJYm5kUNV145oFbgGAhpuJiwN+xLdgRK/wFMzYvH74JRImCm0st2wakjEtmIv6XEFQ3PZzUkPTCoNZaHVEUnuy3o7bDm8/cU/+X2CbTY+hLHHtphdL08aFYymlagWrVf28CeOBBaGCPtF6C5/YFP69FK1itPPATfZ++xrHIAymVLBmQo/U323/vsA2Alp+Jn3QI7YXNoWbSz24GBDqYV02uDK6B38K/Ia+OH7U4DTLeQ3A6m1JgDeOj/UZlSIgQwfLeBDuWzaPMzyqdWCGy5eB9dV4tfnUCBtAmw5feymiVDAdS2ANYD8KVNiMT45VMAzQCsN1en6Bn0BiD6q8USphoAxDhWaqtewY4AxgFIBiDwK6ta0wLYdvFZyxFNMw/fxG3zqr0iGRJ/Zfp82TchEOmXdOOAwTgbltNK9oCJQY0xPaQ+6tq64S/HGaa3jc7jzayGpMN72yraXsTi8DlrFftZVrZWDxgLn7D0+NthGurYmVYIWq5v3UNpfq7wE0A+EWLxppGGeMfs8MKcY35omT0Ywysljh7RshLTygGmxRUrHEahjN2Vz8XU1g7w2orOay5jR0CBiCH16Bo2j/THRYWAybgdlhJLHMaigt0l5fmehzmjWMAspYfZzakL0tg8l944u8To/ZY5xYvcbmHDhXvoVyMnfq3wfwQwmk8n+SafVYPfZMP5e/hznYdCQSwWFIsGtXpRALUtgKLnTvTufQQg9lIQw7d3AFQGIP70Ft1Yr6yK8zaAqQDEfhXDAYj9EKwFUsxO9gUgNjZy/8qi1rQAtll0RjmkfUKj/MocwPB9u4plpAB+Zft/m5dZ/ZIW+8TlDVigzMmy3ifuVGhONA0cjKTwxxmnTqZNj6NLGiINSXcI7I69ocXQx34VfrPfZl7UkNCyqGFk0M+YH1ILze32YaTDok+ZRMccRa+tKL38NR6EJsIGxyEoYnsdECuiI8+l89qKTZvXoPvrZihu4421TiOij5n5ZJJcAYuUU1KOO/2BtDZiQCLScLhZYKcH/4CJwT9anQgSTcPmVnL6PCweigTMUdrHw6k9Eti8s7RVk4BBOBOWC0PtF6O1/d4vi+t/qPbio/bjyZsA7PyjnLIKWGw438c1J36r+A8CqJaTb/5DjkZ86Zqzd9Bng6eSetbk8bC/RwXNYqAAalcARQ+eOK5CzPsTw7diPmAaAHkB1AEgfguJuX/W1xkAhwCIw0rnAsgAoLrVC8REHPGNWBPArn+oanFP6/uKDfPu+fv7I3587W2d0nLhGRy99hSTGhdQhoBvmnfuL5E5iWY/1Jp8cKtf0l6h6VAzcKwy3HrJqb3lhI3AMDtlHz6xgfBOx77IbSv+1okmaYjUa1Tk4yw8RwJsdByMwrY3PkO8JaQUugZ1QREbH2xwGvbpz791DyCAD4EhyDV4t/I+7o0+IFGSFJ/37JlFyzs0LWoEjlNOCxE8bUzLcqNlMcjd01tRbpMdHBGIq05tzJJuJaZWYn0wpCB+CeqNHDZ3sMeyiCUahs1FrmYWB0IKoW1QT+UIvwNO4u/niGtecE2MCm6OsraeWO44RroNi47cj2dvA7C7WzllCDj8yMnOlbJ+/hH9t9NJorOnW5NfGN/voZefuo2Bmy8rD5AhSRwc6SWm0GvzogBqVwAjV5xYtSB6+MReD+LMpy8JoFi7LnoGxZLB/yeAQi5Nv10+v760+ARaFcAWC07j2PVnmPpjQcw4dAPXn5gOby+dJak2P9FafmrzL8FVwZXQL7gdSttexkrH0Z9k1CawFw6FFkJ/+xXoYL/D/LNokAarIemXYfFQKEB8XAAvpzaIY3WurWlrk1e4rmxZMwFx8QGeTu3M0hoNz2XO2OvBa9ScdgwJ4zjg4uBqn7e6lWgJcc7zpV65aDh7V/wxJf6oyprQFvtrvQPiRRJTK7F+GJYYpQKmQ+zBd8Xpl0+3sYkGaRYSOHH9IUx/74JGdkcw0WHOJ1vTeIWmV/7wEHs6XnJqZ96+xow2Cr24RUfus2wsv8jND6vP3lXOHP9MANV08o2Wvz9i6NkXu/lh6DYv5d1SJ4iFE/2qxNA7f/u3oQDqRwBFdQjB2w9gXzQOAeuqB7DZvFM4cfM5/mpaUBkCvvroDVa0K4EyWSmA3/7r5ivu6LUVfdeexeqPJfGb3Rb0EYsbxL56701rmxYEu2JEcEtYLw6x3PVbSoOVqJwPzYaGgcMgjn87EeuPT5MQq20Pj1GON8sdsACBcMQRx27IYCum4EZPL5u4rdhUWOxhWSh9QmzqFL6uy+rRIvVgugaIbU8yYL7DRLhE45Fwy07ewqAtV+CSKwXmtyr6eYNbibXYyFqs7H4FZ6se3agL1/+tLvPcup83v4TbYzuMKhaAnwsnU85MDj8ZxFqUjzl2RbrwNhQ3jkJtFR6xDy/eBSpHS4oh4FVn7uLPqtnRpUq2Tx81UlvtCSmKFSFV0Ml+C0pG3tw7uk+++YqPqNFfMv+YL0buENPpgWTOTjg7wHodprboUAD1I4BiOFiMiYkeOrGdi/gN9BOADeaSzG4eLo68CEQMHz8xv6YDALEra3IAAV9ZypqeA9h07kmc8n2B6c0KYcahm/B++BrL2hY3rUo00qWGyefmZ6ix5iW8X9lhdrmPcM2dHHjz0HIyiGdoJtQJHIVEeKOcvBE+mqk0VRR6af6xia2GpNcGl1dWiH4qnVa9e1d3ALv7oPbTzrgclgmzHSbDNdHDaN3bbvrB65i49xoaFk6LSU0K/F/REj/sGtgZW0LLWM1hjB7RGr7NS5GddmUzYWDt3J8/VyTZqR8wDO5h2TDTYSpq2okZKuYrCsL1j21pnlsX4v8QBQLm4S3iYFfiSchVuxuQs5aykhuvHyonlNQMGA2vsIyY4zAZ1e3OSa3kLjh8L169D8L+HkIAb2Hl6Tvo7pIdXV0iCaCVFH8Ic0SZgGl4gfjKqvJOdlvRw36dcuqMckX3yTdG+s6LYq6io2DcbtOpO//YAx/Fe8d0GAVQuwIojiIQs9HFsK9YySsmHokFHeJbV8if2AZGzOUT28C8BvC3ubjCNy0K3wbmAQCxs25KAMsAzDfSNjBNZp/EmVsvMPPnwsoQ8JUHr7G4TTFUzCEc2CDXlyafx04IlOgElO8ZPVtzREZrfob3/s+RL2C+sv/fqSTDkbLWANMw3ZLaSoT4BZk7YKFyOshZp45IZiNKOxqkQdzSPCRt2pKmDlrZ7cEwB/G31Rfm0IWGoNeSA1jnE4SuRRzRvWHl6OMWGoIeiw5g4/Ug9CrmhM71K33+XpFEa0pQQ/wV0hA/2R3EGAfxEY8eZuGr6kfWy4vmJcUU40iXlVgL4eoR+Bs2hpZDL/vV6GwvzjL+xsPmVnPrfELTonrgeMTBR2WYXpEqsWJaXGtbKv/3Z2AHbAitgK52G9DdYaPpZ1HcOLvAsL3w/xCEA39WgBgCXn7qDrpWyYbuVcXf4lbX4XGW1eThm2jHQoCyCEpcI+wXooW9GNiJnjb7vJH4X/4fgb8PXMekfdeUl8R1tMOV4a6aBUYB1K4AigM0ywMQqxWE8B0HIDawummuxvCNoEUvoPVG0GLfv/BLfEMLUaxoXvwhfruJ+YGG2Qi60awTOHf7JWY3LwyxDcyle/5Y1LoYKuU0iAD+2+Rzyb3Qvuqb0eoZzobmQOPAIUiBFzgdq4spvNFiYG8/Sy9NxYDJuBWWEisdRqK0nZiL842lwfqhvbai3Wpv7A/Mi+H2i9DSft+XV9uK4enjfhix3QvVcqf4H3tXGR+10nfPenF3h4u7uxd3d3d3t+Je3N0vDsWttEBxhxZ316KlK8m+v5lNutl02012lwt9n50v99LNTCaTycyZv5yD5W3tuD8lDYaDizigXP9DN1znLWeJXgLVp9sSPIuA1m6mNAYYe6GEMhj/aif/njFjGVSacRSPv7DYWCs2ypQuZx8ER7xvYL6pPnxNTdBEFYCZGkJB6jzgijRyoti6f00VMNzUFSWVwdgiHgPOirvqcz4aYlBFeRkrkm51yYqb1+cIvoebcHJwBZoEsuH8M/StnBUDhQCQjkUb2nUSRlDR4IsX5uR0rn00J8B8pmHkcAd3WrrdMSf/x9rwPXYf8088oE+tVSlxfzIJmY+ZxQMAYy4A/FtmXIx2ATdcHISrz79geZvCWBTwCDdefMGqdkVQOWeKv2V8f18/pASf07srnLaCOOy8qA8rTTWp3m5V5SUs1xK2Ig7cVZsCbCfGbKCroT+lZBmnXocOPF2Hk1Yah/0jnEqzAig90MZKepSJhrD47KOPaLniAtLHV+BUnbDICRBSbhbdNRxwMpvN1JX5DXE46bKX9oGTAGhdYzOjgWEiUuETzvFxjO4csxA/MIeGI8eHqVYKmATayMCUfz4OyPqFZkBfYx8UVdzF9mSrXAJckYZOZAUdbuyMf5lKIuJsQXwfy+DcuVNosS8MaeMpcGZENZesuHnGHcEPvQkBgytQC+C6c8/Qp9I/GFQ1u6Wrorm/jymBPsa+SIxvCNL1xUtzMppYRDKqb+i6IpaCo2Z1p3vc1Tn5P1ifuH+JG5gvT6bWtGbWx7Dx8ABADwB0dcrGaABYb1EQBX0r2xbBooCHuMaBwaq5iUf8/3kRbJDEtTrU2BW/oEMuxTNUU11CbiWJLuDK74o9Em3SfKzaEPVW9FLvtd6fbHq/Qmms3exPpbGAaWBxZyY55F7QIHrlRoZFzjGHYWLNODeiElIliBXlpAi96oeC20hkBXBL1wnxFL/cx7knAAufzfFQiOOyu6trx2XPRmEF5YBW6NdvEZnMd5ONgFeNSe6ThOOA5gs2Kcoa5kELI+7o2kPFecqjdKGyDG5dPo06u34iaSwFLo9xDXBFejEicvFG+nG4Ys4emaxbYFH7GmZE/gkWDsAbTX4hQWI79DoSl4XcYw/jp4HBqSEVaVzk2rNP0atiFgypxql1iuY+z0M4QL0d/dS7QZJkSDzgayTFGs10VFTdsCREDbwDqLUSe+G5zN0jMPlACFacfhLR7IPJNaBRKd19m/+kPQ8A9ABAVydajAaAdReeiXD7khhAizu4MKrn+R8AgIINcrOpEkaaOkfMhQT4gQu6Xr+fmkO0SdfVT8RNcxYs18xGVZVFcJ0WfpNmGfidCETfE79QKIUKu/pVcclK42jyP3z/A96+gYhNYn3GV4v6pM+BoBLh8/EWSbBD64MiShIn5CbOPalZyfasQywD89Mg5F/7Dd8MChztVxrZUrlJ61oATE8zedDGOBL/KF7iuI6EFZMSvXv+e7gReX0sgOuWT1XE89I4eiXSf4+Cy3G/dgTyCA83wjEL8UPpjd/wik2ErdoJKE6ycJ0kGycHh19GBqeHWgAgUQPpWSELhlbnAKBg7uvNauSlWeQaLovckpfHWy07qA5hnIaEaJNEkNRRW1alj47nSidHwMcvmIJ5vtyZUB2xtJaDX0wrHgDoAYCuztkYDQBrzT8dkfix+OQjmhCypFUh1MhLkqP/nxfBBsnr7NZSnscFNgc+IqElm5VmQnLld8QeCfpALB759CvwHXFwVDsE2ZSvrPcWbNL33n5HtbmnEE+nxk2fqr/P/cIyOBoYiK5HfiFPUiX2D6xqH2wKQBDPU2gbuO+GGEUBWNjDlEZ/m3g+wTyN5h3xhx0S7uA2C7fg/fEJDN7KK1ipnW378UTjtuT58ohmbp40RMXSTUUQB/nVHAv59Zbkl9u6joirIOJJovfCgfjOhoE4zhbmQgyOOA3ic4w5hHAjizPDKlLwR2JEu5fPguE1IlsAr7L/oKFhApLgKy7rekRktx9kiqGnsb+IuNpNhwo3DfP/WjOj99yiCT18uTGuKhLEcuPB5T8cUA8A9ABAV6dbjAaANeadjqB+Wej/EBeefMailoVQK9//AAC8vQfY2QH3mNQ0O1INE87remO5qTaWM7VRW3kOC7V88rhzXGgOJ5dgk/5sjivJtWkwscg11uKWPVs/HKlTJHe/vi3nOl3yuTCmm1qgrjII85Putm95EYCgGcZmWMzUQwvVCUzVrJIMghyOk+Aei0z1MNPUDA2Vp+CrXSr5Hn22XMO+G68xqmZOdCmX2eEtJV0gAKaTjS2xgqmNjqqDGKvZaFs9GmDKJ2ItaFEQdfITQgM3Fg7U3WAzo55hIpIjFBe9ekUGdQIQ72tsTJMvmqpOYgafmOJEolG20YdA5urZ4ZVoDCBxG3Yrlxkjaua0PKBg7q8yVaPJJ2Lw/NUch3Il2moUk8puOFS4cZj/l5oavvMmJfXmy+XR3kgaVyy6FTNGxAMAPQDQ1ZkaowFgtTmncO+dhfyZuIAJKfT8FgVR190bkauj7O76gszbCcbWWM3URHXlRSzVzsVNNhPqGiYjFsJxRdfDonyhUAKN1wC567u7JxF0KxYriJBwOQpLR4gfqm76gPtMSmtslDvdYoKxGWLsiu1MBVjisvZYnl2cPGHHOldcEYKtukmSQZDDQRWAhZHGDtjMeKOvahcGanZwVR0DgtlH72GB/0O0LJ4eUxrkdXhLSRcIgGkvQx8cYEtitHoDOqtFSpLRWAAHb79BdXLtkiRL6oSDi0L8sGfPv+j/rZVAD1mkmyx4jkNMUfQwDkAexRPs1xFiBUGRkYCRddRBGBlL7OjaoKdYduoxupbLjJE8ACTNcnOtt6E39rMlESn2lUQ/cLGLU9Qr0VLt73R/3DGUnjaAQdtuYOdVLvEKcBgb/DePmQcAegCgq/MzRgPAKr6BVP5tS5cSFACeefiRqoLUK0Bklf+fFoG1g8QeldAvQijiYY1mBiqqrtPg8woGXzwzpxQFzP/GbOAQP+zavRUDv7e00nSQxJPq02yTFUQb5gj1ZnRT73faTRfpDYsyMxvqfXDVnE0wDnaAlgA8WCxNkwSWJufAg92Zxz17O8NQBLL5MV2j9p3lAAAgAElEQVS9HM3UAZKffScBWdtvoPQ/SbCpcwn3TG4BMG2oH0fHypbU2TEwXeR/HzOPPkDDTCb4Vk3sfmsugDlH72Ke/yM0z2LCNG879xCA+CdsSkrHooMBd3g9Y360ZIRB/DPyILVSXxhZmcYALgt8HJkgm4zfqVkofTQVXrFJrNRGVGIwlN6Vt0hGyNcJ35yM/rjnhXta6ffvNey9TuhzLYUk+aRPEjtGDowHAHoAoKsTN0YDwEqzA/D4w09s7VoCC08+pLrAc5rlR4OCaV0dl7+3vgCw+DMF0NE4FCnxiVJP8IoDM41NsYipL6BjIY/jeDN35aF9j97FfP9HaPGPCVMr29mkBeBsvqkB5Y+zdYO6oX+imMQopcqEliC5sWauDFKIH7w3fcRDJgU2aqagjOp2lLyE4ttcefIRjZZdQJo4LIJaJ3Qf0OKAacnw+XiDJNitHYOCSkKTISFWLcQPB/ZsQq9vbVFIcR+7dD6/Jcmh75Zr8LvxmsbfkTi8SEXw3o1mFXLo11Iy8rO63kit+Gy9XIYFMPOIA2DNwMVRlWkMIKEO6Vg6E8bW4RRSuDCD91/DUEy/mCp/3Eo4CHFLdALSl4iQqDvMFEV34wDkUzyCn26Mbddl9MeVaeepax2BXpuu4sAtohxjKYToO0syIsQV84oHAHoAoKuzNkYDwIqzAvDk40/s6F6SAsCAex8wq0l+NC78/xgACqwdvsZGmM80gti6cJdNh+qG6ZE5yMhs+U2bDn+yHlEjB7o52KQPM0XQ3TgQeRWPsU832n2bomBsvppjRyQOhOg6WFzhfBFbXgSce0XCF+MjEmC/dqQ129RNnHuEAzDX2CM0u9S/Tjgyp5YY/xjih48HJ6LIRx8KNO7q2kOXILnbsklNt/2QbSNpWYkLup5IofjiGJhyYxbMpkctw1TKf3fVq7s04Chz1eITYJa1KYxq9iieRMTZ7iAbzzTiALWmE63YtWefUKnJDqUzYlyd3BGuX6KGQrR/uxkHIofiOQ7rRlieTEB+/phNgUoGXxB1kBBdRyipLJwbDjsyx9BzuWUEuq6/jKMh7yKG43D/ssiRkmyDMa94AKAHALo6a2M0ACw34ySefw7Dzh6lqAvY/+57zGicD02LpHN1XP7e+gJrR0fDYPizhTBevRbteFJloopqBorpF+EDEmGXdiwKKR9GDX7c9KT1Fp7BjZdfo6bhEYCzR2wqVDbMpnGKZFN0myawYGxC2PSoaZgmACaCB7UHgjmLTuMPXXCZ55tL9MKtPIWhPw0oOPEY7cjdidXhpZFAPyEgkCYye0QL97h2MP5RclYMN4DT119+odQ0f6iVwL1mv6CK74A/T2DN/WnWIbd+DX2mG7rOSKAIcyvAIaA5n89RfNebcHRAOWRLEc/+jBWA+PaGIQhgC2CyeiVaqU9arpcxTuSemUYcpNWujPamFkBywGxfKiN8aufg9IctbsTpxmZYQhOHeJk+W/JzxqxATv1qGKDlKGKI8JO8/rjpE/U0A6Dj2kt0n+DLvt5lkDetG7PX/8NR9gBADwB0dbrFaABYZro/Xob+wu6eFgB4/M57TG+UF82Kpnd1XP7e+gJrR7HwhXiPRNipHYfCSou8EV/aG4bSTfC/0iLltVOjPFELwJmBuunWUYvTRV0PJFd8tXbcFQulYGyOMQXRxThYlAzgwPIi0AQeWESHvg3t6PS6MDNuv/qK2gvO0KxDkn3osIhiGmvpJyPYnAkrNbPgrbrqNqB15dlnNFpyDmkSxkLQ8EoOuwURR1+x8EV0Hu7VjkZ+5WP3vEvSCsvg490zKLL+B3VI3xlfBV66aEiUORA//lNlrGFqoItqP0YlCZQN4lnWjMwjLQDw6pgqWBv0BPP9H6JtyQyYkC80Qtua/N7cMArn2dyYoV6GpupA22fnyM9rfehF39syjS+qJXojuz+OX4jnCqkj0GbVBRoqxBdiPCicIZHU6n/VdR4A6AGArk7IGA0AS009gddfw+HXuzTNkDwW8o5mSJJMyf/XJcQP77f2pVY+JVjc1nWydXEC4OMAm6v8MU1DONR+k9uJZfDlXhAKrPtOh/yOTxXE8rKzSYvcdGX1c6lu6nbteBRV3nNf/zhL0DpTFYwztUc15UUs086V7JpcHPAQMw7fQ4OCaTCnWQG3TqPDt9+i+8YryJ8uIfb2Ku24bRHQsmbqbkRntQWg0OIKaAYovQyhmSmaMRG2dy/luF8iAvAm+rG4ZM4RrUqH40ZFV3Bg7tKXeFRfOg0+ICj5dMdub5bB+gMBGBsUDu8Maqzs5i2bbJxhzcjCAcDrY6tQC+C8Ew/QukR6TMpyD9jZiXbWwn25Et8RG4e1w5BDaaUXEZKfD1x7ArvuGzGoqA59Grj3UCF7XP/HKzRffg7nH1vjQv/tWgIlMieJkaPiAYAeAOjqxI3RALDElBN4+y0chISW8AAeDn6LSfXzoHWJDK6Oy19f3/+oHzr6q5BV8RLHeOWGWImBX2RxU+AQU4TSYVji7LjgcxluMEkDwG3S177Eolq1JBnlfPKp0WvIbmtLm25tGI4zbF7MVC9FE/Vpy+3c1b8QP0zZcRrLwyogQoXBXlaynYc8fPsNum+8Kh2kSRooy0WETHji/hDUzJsSi1sVdlxTBLR4d2M71RGM16yz1ncxm3T5qUeYcvAupU8iNEoOiwiYDjT0wC62LIaqt6Cnep+1urPAVEDls81UHkNN3VBWeRMbtNMlzZNT9z+g7eqL+Cd5XBwfWN7h44gvIBKCWUdZqHAIUTDhAZx7/AFaFU+PyQW+RFgA35sT0gQQcggj8nk6hcnusy8LfISph+6idr5UWNiykOz+eCq4bwR43kq+xY2diqNM1qTuu8F/2JIHAHoAoKvTLUYDwGKTj+P9dz0O9i2LhScf4OCtt5hYLzfalMzo6rj83fVZBvN2ncScy3o0TPsDvuUUQLxUlszQuweo5u7zLyaUM8yl2q7ByUZDU2OK+/RjyegINmle3cLCnzc5+k2aA42jPlXHJsYbvVW7MTjJWbe7xXptuoIDt95idCEDOhdNKjlrllcqie+lppu/wiZA0bVpQcAfAYFdymbCqFpcNml0TYqAFi/5V0l5Fau1s1wHWlwLvDxWt/KZMaIGR3QcXb9E1lw+GclKoO2CtVnk9uZBbxvVUUzUrJVkKX7xOQxlZ5yEVqXEnYnVoVLywsbS3h8hgCZE0KQQtRrCA+h77D5aFEuPqfVzcTGAb3CezY7mhrHIoHiLQN1ArvHIz37y3nt0WHMJWRMpcazmTyCu8xrF0p5AdBUZ02dngR/v/vt7O9Xh31eJ14/n77CmfVFUzJH8993wN7bsAYAeAOjq9IrRAJCXoSJxZ8QFfODmG4yvmxvtSv0/BoAcgOrysTmOsUUwRr0enRLftLW6cfqx+dZ8w3ejAgf7lEKuNG6McxFt0nNNDTHX1BjNVCcxnaovOI61W+F3EpPP61EnixoLOsl30zma+PUXBeH6iy9Y2roQqueRrgwTbmSQY8xh2vyVRr+QJKn7NuvuG65QK7VPnVxoXzqTo0ewUZsgGae8Xq/V6usC0BLcvduGyzgS/E7etyNIuthuKoshpu6yrHRRPrwI9PYw9MMhtjjGqtejo9ryXmiJxrpIXLhEy9fAsFTLN11ieTxvwjlwe3w1GgM46+h9NC+aDtMa5Ys4/Gw2VaQa3BWV17BGOzPKMIPXl/xQaqeKqvUE6zpaLIXuJD+PbiZx6wW+WbnvECshULwnUG6wbPe440n7d1/By4fyvYwys/zvfgzaOw8A9ABAV6dpjAaAhSYew+efBhwbUI4CQMIVNrZ2LnQsI2FzdXXk/kR9gdWtZPgCytu2TTsexZT3Lb0RuVCbLTuLC09CMbOEAU3yS7eCOXw00Sbd39ATe9gyGKbegh4SXYBHg9+i64YryJc2Afx6l3F4S7kX8NZhEh+aL21C6dVD/FB64ze8YgXJNe7YrFkGdXyP4tZHFiuqxUKV8uWlbb4CoPWUTY4Khjlc9nQnS/a0G9zmPM3KirZFUCVXClljRazN57/Ep5awjIq3CEg22zVrrsjtXVM/BSHmjFilmYnKqmvWvjlwe1eeHYBHH35iQ6diKJs1mfRnAvDLwCDnWAvYDCYA8OxTzDxyD82KpMP0xvksbYX4YdL2M1j5q7xVPi8K8nPz1rbIp19OdbKtsYISeBZl9drOxYL1wm5TJGSkzjz3egZc7fNvrs+rR/G3WdiyIGrnc7OE4W9+Br55DwD0AEBXp1qMBoB85imJ81no/wB7rr/G6Fo50bmsm7RSXR1dd9YXWN0+muOjiH6phXxW1xlxFeGRrW4hfpi4/QxW/SqP9qrD8NGsd5/VQbRJN9CPxzVzVpGKBNHBWgXkbWx3FO6/+46qc04hnpcaN93satWbGGQfzVnxRnsjiVStT27DtI1PPCU5gSTK181ZYQq9H4vPiI8D2hHIndDoOKGBb5Crb/j6Dtn162CGEpeSjkeymqPdsnkXmXQcH3/oaSxtnjQyKTFYBi9vn0GZzT+gUQJ3J1SDSq12fuaLDhf5w5fjK+LiiHYosiutEl6OEl86r72I43c/YGJRA9oUknf4CTOYKF8jKXcmVMeas09oYlCTwmkxs0n+iGfruOYi/O99wKSiBrS2dw/BN9tYP47SC83TLEA91TmuDfdYcO0OtshKH/UL+Y0KQc7Pgt9WkxcP0KqVVOs5JgsHeACgBwC6+qHEaACY1+cIvoebcHJwBSw48QC7rr3CqJo50aXc/0MAKNgYA5h8aG8cjsyK1/DXDbadA8Q1RugntrXFLqY0Bhp7oqjiLrbrJrgOZPg7RUED4qcdhXzKJ9b+ROOmE7rZro2pgkRxoqH3kDnLn336ifIzA+ClUdINXFIcn2DDHGNsjw1MVfRU7cVQzVbXNmsOVP4ya5BTT2LYCF9eF44vT4YFj4vjKrnhC96EKbG7RwkUzOBi9iLLQP84CNlXWjK4r46qhMTxYskcbYC4XLOPPkSl084Or4TUCeW3EXFTQXzhD7MOefSr6U+3dR3tH3Ts9daudS61ZMD9Q29CnnEWAEj4GokFcNqhu2hUKC1mN7UCQJ6IfnOX4iiVxU4igeA7GWnsSDWgbecU13lnk2Wie1Oib3S9qQoem1Ohk+oQ0ik5LkK+PrFc9r8lzSIte3b8XRV47tiEsTX4EmbEjEb50LRozOSN9QBADwB09euK0QAw99jD+GlgEDikAnUBE1H6KOWiXB0pUp8Ppv7+Bvj5AYiTzJp8oZRA6utKHwRWt2Wm2phqaonaynNYqF1g22rDFcDxcSAxP/fYtKhmmIE4+EUthW5TIRBs0nqzCtn162kfLuu6I6nim+MYQK7HfBb3nl6lUSCdDDetg3E8+/AjWq68gMzJ4sB/UAVpoy7YMFebqmOCqS2qKy9iKaWQERQ5m7UAVD5kU8PbMAtxEUbfhSW3RL4FqOnSc7j49DPN1iVZu04Xzqr47IsJ5Q1zqXbu3WQjoagx3SmrIr+xElnG4q7SanCg2TJ/pyMhvuO6VzdpBxiu7kZTJYw2dYI1YUa6y/VbuJGST5Nyb1J1rDv7lGZJNyyUBr5NLdRAxHpE3MQE/BK94BTxvSK/CsE3u9ZUFT6m9qiivIwVWl/ba13M4rY7BwT3DmYzULUWUkhSWGfVQQxRb7UlYJczr52edH++Ik8dljqBF6UQm9wgD1oVj5msER4A6AGArn5RMRoAkkBvIqtFAr0X+D/AtssvMbR6dvSs8I+r4xK5vr1gav4qd8SIOeqxAKCMMHbCFqYy+qp2YaBmh23NalOAIyPp30xmJXLrV0MPLQK0A5BRaZVAcuRCc9QdPgv4GZsc5Q1zqNTVHV0Hq7VNQmwaH6M4r5QB9fLKc9NF179tl19g6I6bKJs1KTZ0Ku7wUegFgg3zJFMAHYxDkUPxzCrvxbciZ7MWvLNAJh/aGYcju+I5juiGOw0qB267jl1XX2FItezoVdHJeS6IDTvH5EQL4xhkUrzBSd6aLOHdiQe11crzCHr4yX1SjCF+OLF3LTp97YTciic4oBvlWJ5OALiDmNxoZRwlspJLA9xffxlBwktIeTC5Bs0Cnnzwjg035MP3P+DtG4g4WhVIoohdK7Od959N8QJHdcOcfv/SJjOAgOlAwBR6eTdDfxxhi1Eg/QUWJZU1mumoqLphbU7OvJbcib/vwqKTj+PDdz09HBIdeckJWX/fo3iSQKxHwr/w7cSMLsVoAEioGshJnKgXEBfwv5deuLYxRvXOHAVT03q/OZZGYHVraRiBs2wezNYsQSMVx6HHW5O8fYBdXSKepIZ+Cu6YM2K1ZgYqqa67d8EP8cNZvxVo+aW7daOVyLdHAOSwbZexNbw4Bqi3o596t3tiFFkGc3eexNwrejTPocG0tpWlubYEmzUvVRcb4TRr04YJRo6lRAAqt5gqYoSpiyBjVDDZZGy+c47dp6TELYqlw9SGXEKCnLVGFBu2iylDwwRKKW9js5YABmkgSXzL4Ttv0u+vv3dW9PfOJqdHUV67Pugxxu67g6ppGSyvlcgxlY/gHb4yJ0Fp/QKaeUu0k9UK1nofB+/wS5gBBSZYJPseTalJeQAnHbiDegVSY17zgtQTcDQwEF2P/EKepErsH1jV/hwTfLPP2GQRllZyUHKbNd7e6NH1qg39hZdEJPHCR7XDsIqpgX+ZSmiqOokZNGOfK3LmtVve7p9ppOCEowgNMyJPmvi4/epbjA4Z8lgAPRZAV7+iGA0As446CCNjxrkRlagLePOF5xhYJRv6Vs7q6rhY69sJpv5h9sINNgvUCgbFlXe5a53bOGV1lAOipcLn4TWSCiTgBO6tWIlspKp6GfriAFsCo9Ub0Flt4TajxU0L/vZLzzBk522UTclgQz0JmzTdlcgG1RaLTHUw09QcDZWn4atdIs3FF92AcVbaIZ9qYztTAYPU29An8UVpsV8itzaJ17OVqnPi/QoAia+xMeYzDdFSdRxTNJa4NmfeBQlzGLz9Bsr8kxQbO0u0bgrvJYoNW2Sqh5mmZmikDMRs7TKn+kQqESlGkikrjpOTNb9FF089eAfLTj1Gx9KZMLaOBN5EAeBmzQrk0K+hGryntf1s494cAG6hZvPjKTVpDOCE/SEWouz8LyjP5tLPhTDN1BJ1lUGYn3S3Q/JzYo0n/TFBjXO63kilCLU8rRPW1mjHVLRedTf0x2G2WES4yFkmF1oaRyMRvuOSrocFGMdLDQy4Le2g5MoL/Qvq5h13hOpKF8uYmIZSuGRJ/8PP4wGAHgDo6hSM0QAw84gDYM3AxZGVMd//ATaef+5WCwQd3EiqB90p5QkBB6T8q52AEhEg0H3AKqoXG37TDzk2W+INr+i6IYniu61rTETSO8vYBAuZBmilOo7JFHg4AWSimWVzj9+nKgkRHGmOZqRggzrAFEcvYz8UVtzDTt14rqaT/RNYaVsZRiIowkJ6RvpGK6BcKR0+F6+QDDu0PijC6yzL3awF72KwsSt2MOVp7FUv9V6nn/X8409ovvw8MiSJjcAhFR2NduTfRRnco4wdKSF3H9VuDNJst14vwypJKu299gL9tt5EseQMtjWQeBBw0Ptem67iwK03GFM7FzpJoXYSfauV9TPxyJwGGzVTUEZ1WzK4/fRDj8KTjls+/6kWADh+XwhqZ2Sx8C2xrJkxzNgFW5mK6KfaiQGaXdHPMe5gUuHDYDw1p8QWzUSUTPTNNbqcqMZOMAYfzPFRVL+UXnlUOwTZlK9oWEhR/RKEIh42ayahlCoE+B+ig8kx5hDCjSzKZ0uGwPsf3L9fyP8ina7hAYAeAOj05OEqxmgAmHH4AfoYl0Z50xjA9eeeUesfsQK6rQg2TN6dQtom7sEweKG08jY2UdcZV0r0BKpbAq5/R3nw7juqEPoULXCz8S8o4tkhKhYAmZ1MGQwy9uBcfFy/5AKZaB5kyPYb2H7lJQZVyYY+Uiyvgg3qNpsBtQ1TkRRfcdmrh+1d5FgoRVaPCnpfutFawbkMUMlt1q0+treCyESPnd+suXfBu+19NYvRUEVAqfSkBOHAvPryC6Wn+UOjUuDuxBqyVS7EB5qOhsHwZwthinolWqr9JYMkm5cV4oer+xahYWhfpMZHnPXq6xZ3Pq/asLR1YVTPk9Lx5yQ6/HQwDMFJtqDg2aTNAxIjRmLFSHk6rRZNAhnnF4xauhtYpLDI0fH6x1ZaF8fk5+2WHEPgCwbTynmhefUKv8fiJliv/JiS6Gvsg1yKpzios8QFk8KDVxt1FfKDG9cFxy/rz1xBNJ5J4k6NPClx6PZb9K74DwZXy/5nOuPiXT0A0AMAXZxCiLEA0Gw2I9OIg/T5r46pgvknHtCTuts/aAFgmWhsjVVMTZodOlqzEQRoEJfObu0YFFQ+sr6LphucyqSU8jJ5AmUSw7K/T9moq3BA5uqX2GhomIBU+IRzyac5D2SiuBMf/D+7SX40KpzW8SMINqjv5ljIq19F61hpPrgm5FigBO8oWtefVFDJMhix4QS23DGibyEtBjau5NpmHeKHips+4wmTzGL9Ud1xnNAQxUiSzYtYMUjow9n64UidIrnj2DhhWyKQVF0/FXfNGQRJAdJAUkSTHMD9YI5HrU0k1uyerh20fMydC6DCKX5CweHHx9gGa5nq6KbywwiezkdCf95/D0exySdAFOQeT62FDeeeYszeYNRQXsAS7Tz66IXDl+ATEmC/diTyKJ9aRziaOTZu722sO/cM3ctnoWwFv6XYSRbrpDqIMZqNEbc7yeRHB+MwJEcozut6/954xN/ykM41KtwzSEY3SabqVi4zRtSUIH/o3C1/ay0PAPQAQFcnWIwFgCaGxT+cYPv1sQQAPsTqoCfoWSELhlZ34+J6ew+wswOMrAIl9Avpos+rEgwxdqWxZt7KK1ipnc29C5kbqMw3uOLUY5qRKElYnmXw5V4QCqyz8LyF+HgjtpdO5h2jv7zCzJN4+ikM/3YtgRJS6D9EbroC4ctoZqJVIYG7n1SwRi4XgMr35gQopl8CJQdENArG+gAyQOXSwEeU+y0i8N+FUSMbD5GX05tYBNYNR4ZUMkGb8N4hfii/KRTPmKTYqp1giUGVm4UuAEn5w5cJiJZfWe4kASTR6wSWV7MZyKVfjV/wEmScO/8tCHkiyfedMLYMnkju8LP6cz5K50OBW9Idkg8/776Fo/iUE1ArFXg4pSY2nH+GMXtuR9ACOXtwWX3mCY0lJNanJa0LuzCjoqkqAPgV9bPwxJwKKzWz4K26GlHJYFahsH4pVSbZqR2HwnyIA7lCznf3e57gt7Uq1HhuXSI9DRnqUDojxtXJ/dvu+Tsb9gBADwB0dX7FWAAoFmyff/wBVp554t7TtSCu7ChTGF2Ng5AUX+ipmQRPP2ZTUm43Eg/Ix9hEvJDftJCO2n0Lmy48l2Xp5DPfDvQtg9ypZSo9RLfXUGuUTM1VkQWqrn4ibpqzYLlmNqqqrjgXoygAldfYLGhgmGixeHr1se29jHdy+PYbdN94FfnTJcTeXqVd+s6IXCGRLSSF8Mrp1E5yRoqUSmZplqAxzQJ3wp0c4oewQ2OQ64MlfOGmrhPiJ0gsGSTRSiIwX0U/Aw/MabFBMwVlZcTc2RvcRx9+oPJsBzQr0b0VlsGJU4HodPgXciVR4uCgKDJ17bTx9ms4Skw9Qd3sDybXxKYLzzBq921UVV7Ccu2ciMzaxPiGq17dJc8x/7vv0HHtZeRMFR+H+kVjvXdpthH9uj14s20ASuoX0oPQdV0XxFf8smmVp4YZpd6ILmqLJ4UWGYckV7v5X9cXKrx0LZcZy089BgGCk+rn/a+74pb7eQCgBwC6OpFiLAAUC7YTFzD5oN1m0hfFlXU1DMBRtii6qvZjpGZzxLjzMVTD1ZvRXb3/ty+kvMt1ZuN8aFJEGoN9w8VBuPr8C9yteyl0ld2bVAMalSUxxmERWKB6GfrQLOUx6vXopLaoL0i2QPE3EoDKA0wxtySWhLz+hprzTyNRbA2uja3q8JGiu+D2q6+oveAMksbV4vLoKs61JZiPI4ydsYWpxCUg7OTak29te/j2K7znnkFctRm3OyWQ50omdxUllEQZTygXVLAMTp05hbYHw5AtkRJHh0gHb8LBffj+O7x9TyGeTo2bPlWlKcIAeP3lF0pN8weRC7s/qQa2XHyOEbtuwVt7GyuVU3GEKYxuxoHIr3iEvboxksefB7WxtSqqMSxJoUbubOGsn7tCM1N6H9s+WhtbaKqHWaZmqKcMwjztIusPMg5Jcrv2p68X8jv2q5yV0inZ6Dv/6Q7KvL8HAHoAoMwpE+nyGAsAxXqd5GMmbrvOZTJhdG0JlBGORk5g3SAun4L6ZTTeT2zpW2mqgUmmNpH53X7HQsoyKD3lCF79MGNHvdgoUrycpNi0QdtuYOdVGYkajsaG+/3a81A0WHwWqRJ44dyIyhJrcZdxG9XUT+WwjKlr0StOckKeBUp4Rw5ULjfVxBRTKws9B93YnLCOAfipNyE3Jwd2Y1xVJIilkfd8gquPhbxDl/WXkTdNAuzrU8a5dgTzkaduaag8BV+tJcszosiYd6cffECbVReRNXlcHBtYXn6/RBbAccZ2WMdUQw/VXgyLkNCT6Vbk5sWWz9kpbyJV8ki6WRqVj+gJhIdEEiecWKLc4MvQMJSZfhI6tRLkYPPvxecYTgBgWjNWfmyNlabq9JuvpTyPRdr5kucY0agm5PWUuaDhLyRPZieBS/5bsNYQeCz48BRL/OO/lmsIRdSvLzSLmY8DzKJ4hRO6Ic5Z3l3p6x+oK8zuJjGYJMRDqO7yB7rk0i09ANADAF2aQEDMTQL5Hm5EXk6uieh1Egvg4oBH0jnDHI2cwLpxhsmD1saRSKd4j9O6/jY1b7GZUMcwGfEQRl0tKoI3SEyWu7U1Q/ygPzQSOT5MhRlKXNJ1R7IEcelU3p0AACAASURBVCVtjIv872Pm0QdomMkE36qJ5Vt67I0Vy2C/fyB6H/+FIilV2NG3iiQwatMUy2DjoQCMPh0O7wxqrOzmLb8NEQj02X4Wa3+VRXeVH4aTjU8qMbWdZ+STEPb1LoO8aZ13na8/9xRj9wajaq4UWN62iKOZZ/93wXzcy5REP2MfFFPcwTbdRNvrZVjbtl16gaE7b6JctmRY37GY/H6J3PkrTTUxydRaIFEo0yopADAzjU2xiKkPS6bqOkvfpMYmCp6Elxvc3bMUCqZPJOkZX3wOQ9kZJxFLo8KdidXBj1OlHMmxutgb8HMsAlxJnWMhfiiz8StesomxXTseRZX35MdvRvUEIo9FGf1cvDQnx1rNNFRQ3bQAPAoALfyDwqSd27rOiKPQOzW+kgb0L7mIj+0kyT2EWohQ+9TJnxoLWhT8S3oorxseAOgBgPJmTOSrY6wFUCzXNO/4Ayw8+RDtS2WET103BPUKrBu8u8RqVbIOJGNWoIB+Bb4jNvZpRyEvyQh0YqOK9kVyG+NDNhWNOSTavrd1naTJroX44dCejejxrR0KKB5gj26c65sOZ6VZ/rmg1doWHRluNA9HuLjarb6IbCni4ugAJ6xQorY7r7uE43feY2JRA9oUck1ervGSIFx+9gULShtQJ4/zbU09dAfLAh+7NjcF8/Eq+w/N7I6gXBGOgQwLoGwOR3vvUeDOP8wURnfqGn2IvWSeyQFtIgDT39CT8m1aQytkgkmur02XncPFJ58xr3kB1CuQRtJ6+fxTGMrNPEll3oInVMf2yy8wZMdNVMieDGs7FEOntRdx4u4HTCpqQGupc4wbpzaGYTjN5sNM9VI0UZ+SbD102PEoVFBu6LpYwB1fKowErq6lWuHFwxfiHRJjR8JFKFK3+29jLoiy77y2+o93QFw3W0Pt3JS37BLX/tjauTCaJPbkTomlbX5TQo7Dl+baBR4A6AGArs2gGGwBFLL1E7km4gImVsC2JTNgQr08ro6LIMPxDToZBuEEWwjj1OvQgY9TI3dQKAEzC55vbHSsnehcPjtQbrBrlixh7wUb43GmEDobB4t4vaLZGLlN5y6bFtUN0xEfP0E2hIjYI2eAqsBKY+vy2yZvw+ee8fGHH6g0O5BaW0ImuB4XVXPeaYS8+YbV7YugUo4Uzs+DED8M3HYNu8KLWMmb5Wbbcnfvu+Ua/G68xsiaOdC1XBbn+iSwtkWmXCGZzvIB0rAdN7H18gsM8M6Gft4uqOdwB4LbXzSU1zEJvuJK8kny3PkidzLPs7dAMx91VOetYyYD4JJKPE+lHIWgZ59+ovzMAMTVqanO707Cc7n9BiUPXtexGKrOCcT9dz/o/5O/OSyCb3i0sQM2MlXQW7UbgyOIt+W/u0j3FFiIjzBFaIxihIay8GJiIc7dAHh2Fp32h+LEKxV8audE+zKZHT6GWy/g5gwBohElVkKgeE/3rp+CTj/9+BMVZgVQYE8yf4n1u3KO5FjVvqhbH+2/aswDAD0A0NW5FmMtgGK2fgIAiSKFW7O6Qvxg3toWhfVL8BnxsUc7BgUo3x8XV9Z4LfDxHpYGPsC0Xw1QRXkZK7S+rlvYhG9VsDHy8YbW2CPBheKNUbDphJs1yKG3uNGu6rohMVEPcQIwCGk/SFudDYNwnC2MSepVaK0+4VSbJC6KZBITGpHLo72RNK5rNDX5xx8FsQ4f6V8O2VNahO9lFw7kzjfVh6+pCZqoAjBTs9xpa02TpWdx6WkodTURl5PTheuXhXJllYBy5b1T4LvNqgs4/eAjZjTOh6YSE4qi7DvL4Ov9IORfa6EcCh7njTixZLxLUUJJqfD5VO4wEsemDBc36ceC4/cx+/gDNM5swqwq0sIfnnz8iYqzAhDPS41bPtWw6+pLDNx2A2WzJqWuchIbGmZg4D+oPDIni+v4ddp8w2I3eTTfsOOWrVcI7jHH2AjzmEZorArELI1A3o9cLVgnfI/exXz/R7LGRk6XorxWcIi0e81vUibhk4JIPK9P3VwYsNXyTjd0ckJS0S0D4VojHgDoAYCuzaC/1QLIuwa+vwF+fgDiJAPipbKJXeMzUBUKItdUi1r/fI/dR8vi6TGlgZvS+lkGzw7PR/lT2aCFEbd0naBTmKxxZWT0t7XFNTYzpR5JiO+4qutOCWRpccbCJn6jgo1xrLE91jNVrfFtwmvFG6PIolI6fJ5A2uy+taYci4qozRr6Kbhjzog1mhmoqLruXJsASk49gTdfwyEnTsvexP+hNyEPl7hxy6cq4nk5kbghAM57mVLoZ+wtirWTb60hyh1EwWNnj5IonCGxa98sZzmp8qG/lXIlUag8axvXA2/fQDx8/wMbOxVHmaxJXesXVzufzxF8CzfJB+CCuWU0q5Bdv06kxczdQM58DfHD3j1b0O9ba+s7lGDF5bN1CVAgCUB7rr1C/63Xqf4ycSXzMnGSKX0E3/AxphC6GAcjr+Ix9ulG2465THBrU1lgIe5q6E8ZCyyZ9Ye5y0TzNsQPR/euR9evHZBD8QyHdSPce3CNajaJXP3P2eSIpwhDIsUPUQ2Fe9ZPQat33nxDjXmn6SFzXJ1c6LPlGkpkTox/u5Z0y9z/rxvxAEAPAHR1zv19FkB7rgH+KQWLNx/Qq1IqQFzAvBi9ZE1aRyPH9WNPaCb0N/ZCQcUD7E44x+qiIPXn5qGxNGTDyq9fQaXhDmmHIafyhVPWMLtdEmyM7Q1DEcAWwFT1CrRQn7S9XLwxiiwqtvq4hDuOK3I2HVGb+cJX4BviROZAlNMmwclLz1Fh9vktCqKuCxay++++o+qcU4jvRWg/qjl6w/Z/F4z3dTYL6hsmIiU+4byTnIKMyYTsY4/AxAJnW8VF6txlXA8PYBl0WHocJ5+bMKWsF1rWkC8rRsipeUvWiUHlkUWKJUvCiNaafxrBr79hZdsi8M4lwwUvADAv2KQoa5gHLQy4q+vgnFIFZ2W6zmam7zAFPuOCV29JVlwCigk4Thhbg+tjq2Lv9Vfo9+91lMqShJLM118UhBTxdbgw0lvCiNjyJT5g06CKYSbi4Sdu0nAMQRNywK29O3PPXEY/hyaARKjOiDPhuevemBNRrkAVGATrOsKLHG5JccfBNaqRCZgOBFi4Jy+x2dHCMAoamNBZdQhd1fsRT8hXSJJr3JhMd+vlV9RZeIayFhAXcPeNV1AkQyLs6FFK2nv8y67yAEAPAHR1Sv5dANCRa4A+reVk+CZNFZSc6g+tSon7k2tgccBDzDh8D02LpMWMxvldGxc7cW4dVQcxVrPJukCSjLp1tSPu08YwnAZ3T1SvRhu1RUeUFlcXdcHGWEk/E4/NqbFJMxmlVcHcDaKwSImsdSONHbGZ8UZf1S4M1Oxwrn8iapwoZdxkPvPArdew69prDMlvRK8SSZzOUj559z06rL3kGtGuAOSGmuOioJ64foG7unbwUhit4yYF5Ib44d2BySj+aSwl5L2vawt1gpSSMrcdTeCxe29T7WtnlW++hhmRf8JReps7E6ojltZJcmpRR7tvuILDwW/hUycX2pfO5OgxbH/nvrtzTE60MI5GJsUbnNQNkgTabBoSWJnsv8Porbi83jahjSH0MSR+k8RxlsychHoYiOVIFnAQfMPhZjVy6tfQTH6XwjGiGNmv1/2Q/1/LuyTxvgkUP20z4UXqLUX0Fkm7vdrRyK987L6Dq73+0ffbhv5C1EhqG6bgvtnKZUpiFvdpR3OA303rp6AfV56FotGSs0iXOBbG181NSbnzp02Avb2dpGaSN7vdfrUHAHoAoKuT6u8BgCLXQNQPZlm8X7a7iDIzAyO4unjprsaF02JWExcAoKgfvFKFNRid2zy8fYBdXSK6OcPYDIuZemihOoGpGou+LS1SgIKjtxjiB3ZrO+TQr4EBGpzW9kM65YfoN0YRRccyU21MNbW05ceTS1cjaPMemwbVDDOQAD9ww6sr9wTy3aMI8cOcHScwL6wqmqv8MU2z0mlX1Mbzz2hmn3fO5FjZzsnAbgHIJbF2xLJr18rpCORyYIYPD7AqkzjHSyieIrwkoFM0FiyDO1dPo8aOn0jkpcC1sdVct0pyHZx8IAQrTj9BpzKZKNWG7BLih+27t2PI9+Yoq7yJDdpp8ql8RO8wH83St2OpjuId3nv7HdXmnkKSOFpcGVMF+2++Ru/N11A8U2KUz56MHjQbFEyDOc0KSH88QbZ0qfB5NL5xl3YsCvEa4m6yul14/AnNlp9HmrgKBNULi5xdKzoYtjUMwyk2PyarV6KV2t/6PI7mt/Qnt1wpWleXmOpguqkFiJoK0VUn4S0/EFtgtXTj+sk1xY9N5qRxML5ebsqB+dtVWeSOk4zrPQDQAwBlTBe7l/49AFC0MJ1nc2CFqTZemZMiDDrM0Sy20ax8UW83ym79BcKqHzKhOvgNsWHBNPCVszCLh0XQD5I8kUe/ihJAn9H1RVrFR+vV1aYAR0ZG/HsfUwJ9jH0trmKeAoP86qaF9O1lP5TYoaLumnu6dlSKziHHnV2KDqJeMNbSb2c2Ha5Nf6YAOhqHCDKSnQA2XFs7mDIYbOyB0srb2KQl7iEn2gIw/fBdLAl4hHYlM2C8s5ngIuBcRz8Jt8yZ5UnVCTa7A0xxqkxSSHEfu3Q+zgNl0TzlpeoKpEuIPXKk6rjQBv/Q5OhoHGp5f8kWusUqSbroDs7DucfuYe6Jh2iexYRp3tISN2yGRxSqUEs/GcHmTJE0caM6nN19+w3V51pixUhi0sFbb9Bz01UUy5gIWWL9wJY7RvQtpMXAxpXkAWdu7Ft87IBzbG74ahajYaInTsVv2l3NWQZrDwTAJygaXk3R2Ew2tsQKpraFiF2z3tqsOw6uwk4K1tU35sSoqJ+NcOjAyxny6jbWhCuuspvWT9Ja0MOPaLXyAqWcIkwRzZefxz/J4+K4mAT9P6ancXYT9wBADwB0du7w9f4eAChYmEhMXQW9L01a4AsJmvbTjo6ImXmqzYYK33wiqBpWnn6MSQfuoH6B1Jjb3AViT0E/eF3ZpPiKS7oetvE6DVcAx8cB395QZv2HbGrK0Rcb4ZSjjyaCyLWwRfM2CZcZ4TRLH1+BU3XsnOyjqsttOne/qCgVDLXYJR/v2qYT4ocNu/ZizI+GgsznNPLaFICkC2wONDOMRXrFO5zSDXAOJLEM+q0+jr0PTRhRXIdu9SrK25yF4ycAzr0NvbGfLYnR6o3orD4kDTjbyfqspTyHRdoFtm/Jhc3NKXk5QWjDRlNljDZ1grfyClaSzHVnDwSieecONzxP3TKoSjb0qewEPY3oMNnT0A8H2eKipIioD2e8DGDyeDpcHOWNQ7feoMemqyiqeQwv5gcN9ZihXoamiR/IB84sgxHrT2DLXSdBpIPvfOinWtjGVLSEeiQ5G7l/orHZZiqPoaZuKKO8hY3aqdbWXZibdrsoWFd56x85LO/SjqPrKokHbGIYRzlOL+t6IJbCYKHZarwGyF3f1X2O1g+49x7t11xCrlTxMbF+bjRacg4ZksRG4JCK1vb/AD2Nsw/nAYAeAOjs3Pn7AKAgOHgHU5ZahJLiC6ZoVmGAsSd+IhaWaOaghuoS7ftjNiUqGXwRX2vGzQm1sfrME0zYH0KTCEgygdNFsED+a6qA4aaukRdH0jhZIAmr/ra29FYmswK59auhhxYntQORSfnOOQtbFB3fceUlBm+/QTMRN3aWSVvAMgh7GIRcqy0UHddHV0LCuLGcHiJScdrBECw99QTts5vgU8EJK41gnF+bE6MUF4weYd3keydlI+IW7cYfuuCyOTsWauahdqIX8jdnMQg8PAwzP5WhihStVccwKclRaSBXsNnxXIk2klz8fVywsgiJ0Al/YmytOvr3KXLB2SptrHVb7BevLxxPY8bNDvGhyFhaNhBvueI8zj76hDnN8qNBwbTy56nIijvN2BxLmbpopzqC8VRVJPpQheDXX1Fr/pmIRI/Dh/3QPUCFwop7NF7uqTkl56q86xRw5sNV6hVIjXmuHFb5kREAe95ibVkrL0fun2hseFJxmyQZNx5cI16e4Huvrx+P6+asAvooUBqocoa5eGFOjnmahainOstVdV828PGQd+i83hL3N7F+HtRdGIQ0CWMhaHgly70cxaD/Jnoa+RPcUsMDAD0A0Nm583cBQEFwMFHWIFlyJNmBVwHwNTbGfKYhiG7lUe1QqBRWi1tCxU9cn9wI686/wDi/YNTOlwoLWxZyflwEC6SPsQ3WMtXRWXUAo/kEEPHmITgxRiy+8dejRv1WbmXWJxQ3hOqmRbF0mNown1PPV3zKcbz7pqcuQ+I6dKWQQPh9N15jVM2c6FLOCRJZAUgi7zynfq0ovpHrnSOQJFi0bbnjSEC7k25ufmBYBtuOBGBoYDjKplVhQ0+JcneCza6jYTD82UKRY6zIPaSA22heUl6fI/gebsLRWuHIljZ59MkzIsvPQEMP7GLLYqh6C3qq91nv4kqfQvwQfmgUcnyYRtsj0ogJEySQDcTLzTiJ55/DsK1bSRTL5CRtjsCKu8VUgeoKV1Bex1rtTIfzgreuUo3rYRVwdHozSpdCFE5CzBlhtAkJkR/3yrvv86dLiL1y3Pf25oIA2JvMSuTSr4YBWgRq+yODkvBD2umfYGy+mb2QT2+JWbYkjYS59eAa0WWun+++hqG4fjH98wVdT6RQEG1iS+H5C8spb2C9djr3V/njG9Unw4974QyJMKl+HkoJkyyeDpdGeQMmA+CbEwizhPk8ZVMgteIjtApCsi4s7gOkrqy/pK4HAHoAoKtz6M+7gEWWiUNMUfQwDqCqFUG6vpQW4Js5Fsrp5+IL4lniZlRncJ9Ng6qGmRbVgW7psOFtOozZG4yaeVNicSsXpX24BbK5YRTOs7kcyzZxMSNDj3/Gtkdq9K2YBQOr5XD13djUH7D1OnZfe4Wh1bOjZ4V/nGrbGVmsqG7UcHEQrj7/gsWtCqFm3lTy+yMCJJX1M/HInAbrNVNRTnVLGiARzB1b7rieSE43Ftc3Dz5wPH3i2Dg1VOAqiu6JBYeIKvrplK/P9rlc7xexVtTc/BYhpjRYrZmBSoSHMTqOO1HsV1P9GFw05xRZW1xIWhIA8aLhi/ABiazSiGSsJMabsqwZ2cccgpExU8sMsdA4XbjD2dnQhGhpHI3MitfwTzbHoRX35ssv1DqUOoEXzjbX4tjqsZS7j1jJiHSaGibc1bW3xOHyRQZw5vnoeJoZp5+PVBR8R/yaSNyot3Sdo8+mFRxcS4QvwFskwc5EC1G4Tg+3Hlwjno3cb19fbPheGGNMHSPHSgN4xiZHecNcmjFPMqTJ4d6Z8Y1qPMmBlRxcSTLP5AZ5rVQ/jcOB/f2BsE+0Kk+4TzxQLVQn0UW9H/F/Iz2Ns+/fAwA9ANDZucPX+/MAUAQEGunH4Yo5O/qodmNQhFQSsMBUH7NNTVFReQ1rtDNxh02HGobp1E18uZUOG38Wdau2oznYD4U2hiPUHIfbyJ44TLpYc+YRxu+/C++0DFbWSuQ0nYm9l9p4yVlcfhaKhS0LonY+59Qkhu64gW2XX7ou/QWgxJQTePst3HlrosgVxauKWGl0JIAkwdyxcMfNp4TdZHNWKsxu2Tzefg1HiaknQPgm706sDo1KKe2b41RkeMUOS1jAW6cTXGxuyoGtboZ+OMIWw3j1WrRTE0qXaJJnRN8Zby3dqR1nk1zllFVSdIhrqPfBVXM2LNbMRU3VRVlAXDje9yZWh1rqeEf1VlgGL26fQdnNP6BVEsqbalCpo3eX33jxBfUWce7BWp9xYttCdDIOibhDBsVbBOoG2t7RkaVacHWYwYRcY4/Qv1wfWwUJY2ulzSl7VwmAvR9TEn2NfUQJR1wle/3jDq5t9obi9FsVZjTMg6bFMjjfl6hqCg4HPF3WMPUW9BBanrm6lfSzqPdnpWYWvFVXrS3KGN+ourH72kuq/kHCaIhYANV7VpsRrG5N47hJIbHcNQ1TqBWVLxbL8QzbZmUAfvcPqKVFDwD0AEBX59afB4CCBeyjOT6K6hdTjqzzul5IqQiNeL57bFpKO+IFPa7ruuKROTVqGaYiOUJxsVsGbH6fASN330LVXCmwvG0RV8cF77+Fo9iUEzSZI6TpL3gldCBWHuKHc37L0eJLD6RVvMcZXX+n6Uzsdb7Y5ON4/10Pv96lkS+tc+5bniy7YaE08G0qg8JC1CGDiaVWGhK3Q9wnxI3iVBG4oiYZW2IlUwuR+BZz1Y26acHcsXDHjUFGxVsEuLA5i29GLFK5xh1GuJFFwOAKyJg0juRH/XDFD0W3q6AAS0GpjYpMdM8V3R0EYGuSsRUds2hDFPi2BIBbb1Yhh34t/c4u6bojmeKbLJAWqXsicNnP0At72dIRIRwR10vYNK88+0yD89MmioUzw7jYLMkjbv9ChjUjhwyr4rXnoWiw2MIXd7qJBidXj0YH49CIxm1dlNyfJTybsHf897y3ejjyZ3Dgvo/u+QVjP9vYBAuYBmih8sdUQqckLNH0b/y+YKwJeoouZTNhVC0nqHskztev5tgorF9KWRX8tQORmR6IbAufDdxVtR8jNZutP8ocX3td2nb5BYbuuImK2ZNRC2Cpaf7QwoT7XpY4bhKKQhJRyOGlvPI6GqtOUSUgFkoc1A5HLuVza7MlegLVBUkzLs5RZ6p7AKAHADozb4R1/jwAFCxgfPKHPRFzAjZK6i2uCuJOI9JBdQyTkUr5BecmNcfWK68wbOct1zjgBCNz6v4HtF19EYQzyn9whejHmQMyZIEjvHGk3NR1QnxFuKWeRPeX3ZuwDH49DEJONyRwHLjxCr22XEfhpAx2NnLeQvn8Uxg9PWvVShArjcJGzkDmlORcURs/56RZqZWUV7E66RaHbjp6FzsJO2ThXufm03pV30Dcf/8D6yrqUT5bMsmW3avPQ9Fw8VmkiqPAufoyMrclbvjrTFUxztQeVZWXsFw7x/GGz83TJ2wKVDT4IhbCEaLraH1/zs5TkXuZj+WK4HXkeybBisOrbhA33dZu7pPoItq+RON3c5fiKJUletk7/r1Rt//gcgiY3gjtv1o5P9uojmKihiTOkCLBUi1+nyF+aLrlGS4aM2OeZgHqqc45f1i0IwE3Vr0eHaOSgLMztzaff4qRe4JRITWDtXWcXxfsTlvBN8pbKP9RvMRxnRVQC+vtYspgoLEnCigeYA+l03JifKP4fjZfeE6NBFVypaAWwKKTj9PD2WNda5qJvMlUCaNMnREXYTiqG4rUis/obehDWQAaKk/BV7vUtuWmG36Pu1ziEuoBgB4AKHGqRHnZnweAAosGT9cQSa2CW2iHGTtjK1MRnVQHUVd1FvUMk5AmjhlBY2qDP91VypEcq9s7SQLMDxPLYIXfSUw+r0fNzGos7uwddSajyP3Fu9a2a8ejqPKeawsYB44efLEkxlD5qGTjoKgxXf7CE+KH2/vmoXboQBBam8tePZzedM4++oiWKy4gU9I4OOkIHEuZoSyDoKBTaHUgDJkTKOE/rKq0zFHB5jfd2BRLmHpoqzqKCa5sznY26y7/3sExQx5MUK9BW/UxyePGgxmSyEASGtxSBGArkMmHdsbhyKp4iWPiDTUqsBXih8C9q9Dua1dkU7zAUd0wh6ENDvstsgDa11CWkPTCMli05yRmXtSjYTYNfNtXljYPHHYQaLf6IgLvf8C0hnnRvFj6aGvwVsiMSWIjYEhFBB7zQ7sTVqUUCyXQQefc+RwIH2Lsgu1MBQxUb0df9W7n2uKfgmuzon4WnphTYaNmCsqobktrM8QPl/yWoMmX3kiDDwjy6id5fksYdkAwX3k1IluLtbAVBV6wSWgoB4mzJFJ5sRV6oPE6II/rVDA8RyWJE5/aIF+EEs5DXWsaz1lPPxE3zFkwSr0RXej7BW6wmek+Q+TqCBesNWnFfcBU0jjaucgDAD0A0Nm5w9f78wCQCw42hH1DYf0yfEds7NaOQUHKkM/FNJXqA9zegYOhadHT2B/kBDlDsxwNDROQTvkJp1snxI5fhShNSoXsybC2QzHnx4UDXYM+1sFOtjwGqLejX+ILUWcyijY/PuszAizwPZHrwhDEzZxgCtIYJItllBOQl2Ot4dr6bvYCL992S9cJ8ZyxULIMdhwNwOCAcJRJo8LGXhIzYx28kVdffqH0NH+ouVg7h7FfPFnrvYPA+cWIzPXmHJm0TTe5cePd0+TgMUazUdrGCkToUzcqlBazm7qgTiPslGC+vTQnRRm9Je4xRNdBclLCxnNPMHpvCCqnYbCqthssPqJ4zptsJtQ1TEYyhOKSVy9phyDuuxv5qbpVstAej52TX/aYPbex4bw06bxLTz+jydJzEQec0w8+UNUIvizXzEZV1RX5wFlwWFxkqouZpuYiy5LzoCL8lh9ybSL2LCUu6nogueKr4/5x85vEOfOSh8G6DohDOPhIkbPGRPVeBPO1in4GTYhapvFFNZ6ihq9XYSRwdS3MX1+jtH4+VUqJkLyMLrlJxnzguWIJVdi0Rnkj4jDv6NrjgzkhpaEhCSgkO9kSFsENA5cw1UO1F8M0W23vKHddl9FfR5d6AKAHADqaI45+/7MAUAByzjK5aKYeyeq9pOtpCeIX8i4F78HXbT1QSL8MDFTUddLP2AeWgOxB2F1kAwacUaJs1qTY0EkmT57oJE0CgmvrJ+O2OROWanxRnSz2US2IIvcXLwnXUnUcUzSrreMvwf0VcbHIqrjGVA3jTe1QXXkRS7VzpW2ofGOitgqHW7Q/92tHII/ymby2uE163ufimGNqgmaqk5ie5IBsmg97k5LE2uUYexgkvvDUkIpInyR21HPXDllrLf0UBJszYpVmJiqrrjne/Bx9GYJx22DyppmL3srLVtJkCa6pYTtuYuvlF+jvnRX9vbM5uqO03wVgizWD0n4QRYUA7QBkJNyTEvo19eAdLDv1GO1LZYRP3dzS7uvobep3pAAAIABJREFUqiioRUg2KsnkjxZMCNYBXpqMEi2rT7kNiKw89RCTDt5DrfQmLKoRPW8lT7qeOVkc+A+qEKEgwQ+BJNode+MlAEO8QgzhFtypG+8yqOC5CxPqFLjWKAyKeA5ilkXrQpHwxfiIhPDTjkI+5RNJ88jRlKC/c/cJ/fodBfXL6J+sGsjkXwLQe2cfsL0d+BjSfqqdGKDZKfnA5ag/PP8iiYGe3igfso6yELvf0HXGJqYyZphaCNSIrK0dZoqgu3EgzQI/r+ttKwggZ1131EGZv3sAoAcAypwykS7/cwBQtADxAe2NlIGYrbUsFIiXGhhAXBkA5uYBvr1GY/04SvbbQHkau9myFmoH3RDs1dZEv2+tnCNKFixU5B5CPi2HG2sk91dJCkyLKO5hh3Bhl3NSFLU53tgGa5gacCowWtQWn6FJyZJVF6wTwlH/BJv0UGMXqjZAraPqPW7bpKv4BuIBibXrWMwSa2evCPrB/0ziQ/PqV1It0eNFr+CfQhUlx+lF+QEJxu0UkxdtjSPsu1qjGTee0Hh2k/xoVNgJQuOoOicAWzX0k3EnAvhel/Quem66goO33lKtXqLZ67YiAOY8oNiXaC7y1ukTdciCaB3g6YAirD8SAK3D/of44eje9ZTLjygK7SNW9GisSucff7KRCTv78CNarrR+KyQb3EtjdQk7vD9/geCwGMxmoElsCfEd13TdXAYVe669Qv+t11EsY2Js6y4h3EC0LrQwjKLydLM1S9BIdVr6uiDl4cn4b5mHrsaB1Htjjf8TWOlz1IpY4/lYvFLK29hMpSFJcd46yndxof8DzDp6H82KpMO0nE+RaYPlHV7WdUdbw3DK8ThVvQIt1CdtnopIghbQL6cHrcPaYcihfOHe8ZEyhnau8QBADwB0cupEVPtzAFC0APHp/1bqCK6PZIMlZV1t+h+eDoZYCokli5BDn9ANAR9gXCpLEmzuUkL+uAj6w8u6kSD5YCrrFg2liMj9dZdNRyXXaLyeroslwF4us77IqshTJ0RanKScPkVt8eDNerrmhiq6tkSbdGvDCJxh80boeLpjcSa96LL+Mo6FvMP4urnRrlTGyO9Q1A/+gk/meDR8gDjA7iQbBa8B11yPHROM23M2OXUPaWHAHV0HSkQeUaIZt7Iz/PHi8y/XCI2jmskc2Or9sRENUh+p3oSuia9LSp6pveA0br/6hhVti9CAeLcWzjXfdFcoLn5QYV6zfKhXMF3UtxB8d6xZEWHRtBIZC9aBTGXld5UDy/fYNJRFgPCL3vQiCR1Rhwice/QJLVacR9bkcXFsYHnw/yY3TxFfhwsjveX3g9QQPCsBFbn0a2xdtnyrjg5j4ruzDKZv88eS6wa0zqXBpNYSYidF68JYY3usZ6qim2ofRmi2SJrfkgeBZTB5+UaseJoULVQnMFVjIZ620TIXjM0DNg2NeSaMDzd1nW3JmOWOjaCTc47dx7wTD9CqWDpMftoMWd9Po6TemzWTqPeJ6KwT71NiBVFMUgKxEgC/CJ+oGR0MQ3CSLYgR6s3opiZ7khPruuQBk3ahBwB6AKC0mRL1VX8OAAoWoPfmhCimX0w3cELxQtno+UI2WFJ2dqL/4TUj+Z/5QHbepeJ09qAdPi3C/L9XN9Z29Oxt+AKLjIGy8a+hVAdndX1oJpnsWBoROOatKXu0Y1CAxkbK2BRFbfEkpzWUF7BEO09aW6I2iJA7CTbfopmIkqo70tqQMFOnHAjG8tNPo5aXE/SDkINPNrUGyTQlcU+NDOOtQewubBIR3YwCmESir7B3L5aB6UkQsq/8Rqklzg+rgJSJpNPHSBgqyyUsA98d/ph/1YDmOTSY1lbCxg8g//ijIFJyh/uXRY6UZAlwf+Hd3/0qZ8WAKtG4vwXf3Qs2Gcoa5tmPaZRy2BE/huDA8MuspWozpFCFEkoybH8T5y1+2VPEw5EB5cCTgZO6ki1s9oZUdFgkeudEVs4layd3EOj8sQWOs4UtiUqJgx2HZYi+6c2mShhp6oxIFDeufktc/+p/6Ebl3+ZoFqFB3GCgeE+g3GDrQU0wD4hFn4T6hCIeIq15zswD7l3MPHIXi04+Qvs8Wvg8bIxc4asRBi80VZ2kHo1Iz07iEgMsVC9rTVXgY2oPG6ukm5JTnP36PADQAwCdnTt8vT8HAO3QA9ijf6HEtKRwFkBycs6nX0llw0jJoXiOw7rh4BVEnF6gBf2ZYmyJ5Uxt2NI9OABdAvcXH+y8JsFKVKzXQX7GrmCj+GiOhyL6pRQcE2skzYqTc/oUbTq8O9PiOh8srS3B4mxxj69xTrYtutka4ofNu3dh5PcmnGTXjMhuOkE/+Li8/IpHaKc+QqkjSiqDsUU7GXBhk4joomjcbGNCicZqFBYAbh68+GLgiKkNuJtsFJQ1psmfBxK+bj7TuGjGRNjevZTDGkIN4eDx1RBH50BD2GGL9i/g460canMLvruTTAHKt8d/0zYtOwNERCCnWPgivEciQZKZ/W/6zIOPaL3qAnKkjIfD/cuBjwkkVzcpnBYzm7iQ0CM4LHYxDMAxtgjGqdehAyXylpl4IQiHKKefg+fmFNI1ikXzm9cElpW442hucP0LM2uRT7+CHopJJm1ahUVxw+ZgLHpXvMXNR70W7fmxIXWcmQdcP/nY1845jBj9tB3yhy/HV8RFInynYHOaejmaqwOsT0XWEZUWODwMT76wlDqJZAOTA0Qcsg67KTnF0TBG9bsHAHoAoLNz588DQMECNMrYAZsYb44EmGRZkiLYYMk/aQzgG2qOb6Ifi0tmi9RaLsVTHNSNwmFdVXT/2g5FMiTCjh6ON8JIAyfoT3PDSJxnc8MSiB4YuT/KKOJ/OPdXr0OfceC5GiOqZ0c3J2XbeGHyICY3WhlHCgiOnchuFWw678wJqBYncXcQQOmlMDq2UNpxz0iSm5I6O7n+nWVyUleMlcxZ9KyCfvDJNuQWxK20halsJcB1YZOw6bJg3AYaulPt3EHqbeij3mt/s7aT1MTHqMre3CWOHa9bmziOFlfHVIm+Fsvg9pXTqL3zJ5J4KXBlbDXXXeVR3PFI8Ft023AFedMkwL4+ZaLul+C7W26qiSmmVqilPIdF2gXSv7uoWhe5OfnQBbsbfd7GEa3wWb85U8XHoX5lcfnJRzReZokBHFxUh94NKro2btwhYeanMljE1AdNGEtyRJL7PqKTAutmmFmH3PpVlNj7iq4bklAXpgQXpWB+E5DGt3FZ1wNJSRasK1nAgv7xCX6p8RFnvfraf68iQDrP1IAmmtVXnsFcLdEOlvA8Dr6ZCftCsDroCboX0GL43cbgPSt8tSBdH6ThwSn5I7+OBO+BeVs7lDdYQLZVpcSJtVjidy3lMg8A9ABAKfMkumv+nAWQ9Cp4D8368tbPwEMbegA7H5ZgseI530gTeRRPsF83CseKr0eXQDUKpU+IXT1LOzcuIX5gt7ZDfv1ySkdzSDsMOWnAr7wPfcGJB5h97D5cVdwgIHDlrv2Y9KOeNQM4fhp5GwU/EtymQ2gWSEAzOfkeTOSLXHX6ObZMCRbnvUwJmuRSSHEfu3Q+rm/Sgo3itTkxSukXUg4wEmunoULs9g8Cg41dsYMpT+9PYoVIgDaVl0p0xZI4FBVIlzszuHFb8rkwpptaoI7yLBYk3R35HYjiE7eZymOoqZvAreT6Bmav60JZsWuNfyFRkiiyP7nnOBSahmptU6LdZMscuwrljhd3/YN331FlzinE1QC3mvyKPiuV+7Yt8akV0F+9A/3Vu2R/d5G6KrIqTTa2xAqmNtqrDsNHs956uejAQPgCCW9g7tTxccA7FFf2LUaj0D70+vmaBaib6Jnr48Yy2Hs8EP38f6FoShW295VJpyR4Np52J4LfUzgQjg5DAs8FH9qxMeFylKnbyfG6EN3cEPRvrqkh5poao54yCPO0i2xrCfsnWOMDmbyU49JyGBxkqeMKIAUwdu9trD/3zKLVHtwAJd+PwBskoU1nUrzBSf4+dtec1+DjJF0mAnfymxJX8wBADwB0dSr9OQDILTwfvv5AUb2FYf2aritV+LAJDhY+IVfHPzQ5OnLSTMQFuFc3Bid0ldHpayfkT5cQe3s5CQBJnPZ5P1Tco4IOBgTrOlq41WSCLt76kTupEgeq/QTiOqBkiOYtDt52HTuuvkL/vEb0L5XEtexWzkLZZFcoLn1QYW7TfKhfKJoAffHYb2uL6cZmWMLUtVgtKM2NPHAc3SZNkgBy6tdADy2s2rlcDX6j4DaJNoZhOM3ms2luiWYOasR9BNSZ59rmJe4ky+DEqUB0OvwLORIrcXiwHaJqEdiYZWyChUwDtFIdx2QhHZCjDVnuFx3ih1Ibv+E1mwgRur5i15TAMrncVIta2SiQ5TdjFzdWe13W3/JDjk0KapWy8tKljho4hfihweYXuGbKiIgMdZnfXaR+iKxKO/+vvfMAj6Lq+vg/u5sNIEWqFEEFpLdAEEQ6CAFRUBSUT0GKgIAIKCC9CghIVwQBAUGpAgERJJBXeu8EREF6JySUkN1s+Z4zO5PMTjbZmd1Jg3Of532eFzNz98zvlvnPueeea6+DL+I/xSsBp7EiaEyyXqWIv2+h408HUCGPExtiP8QRR3G8baXrgXXmoagspEnxX5BEXruP5jN2IFfWQOFMYE0n6si8m7/aGmCQ7RP3+DQJhppwCHFe6PHHPWy8ZMSQZqXxSb2SWnui+/Uy+9pahmKfsxzGmeahnWmb+3VK+8Q5PiYmJuFUpSP5RiB38+F+j+lBv53Ar/svod/rpdC74CnUXRIlePSoJI7T5FcdpHysxQJuYntQ3+SFrH/kVN/NApAFoOrOksyF6SMAZS8kafOGW9xPSsG1Qj7AHgmTg3RkkBQ/VCmvE2H9XTuGfSlSTFVwASPWvP7QJ/F2YW8Y6q81uu8a1RovIk7KLVZG42SUAT/8XzBCKxb25ZGS3DNkzQks3XcJPeqXwIBQ11K6qhIZho+XncX/rGUxxrQAH5nCNYvjJL+jWKZ7yzIGx50lEo/I8vQiiwxD6NIbOGMv4lad67xOMUWDzqLmclQs6kyMgNlowKnRTRFoNCT7wqM/dLZ+ia2OqkgSw6TmhayqMQApTEASw4khC57Ta1C1Q+M7Yon9dfQ0rkX/wBW6LK0lMVcc33UsU3HZWQDLzaNRw3AmxY8Fp9OJSqP+xIM4GzY1j0OZon6cjys3SOZVinQURXPrBGEn8LGgrq7UKx76ScSZW+i48AAqmS4jzDQQRx0l0EoUgMeCPkGuFDaQqG06ui4u3o5ywzeB8jnuH9wIBXJmUX+77INDOq4s0XMqq0bDB8eMrf9gCq1cBBfBlLa+nxUu/LponzxmO8lHHV2XzCYqXNyNhr9E4/wDA36qF4cGZfzvD/1XHsPKQ1cwINiBHlcHoNHtvjjndM0hCdknlB8dsvnpkTNIeO9QLOMO8+coaridCFrPca2yF7AAZAGosqske1naC0DFUpnkVu9g3IxRgYtSfiHJ7m1qmYC/ncUSliKlY7EqmK5gw+guvi0BUrqCZdvw43Er2pcPxOj/U7er0o1uZBjsyzsI8TS0LJm4a1SDp0z8CrbF3EB5ywLBI/a/POPxYosBfn8Fk62Ld53H8PWn0biIHfM0ngRRc1w4bty3YNXrFoQUV38ubrI9MJmch+5HuileFA47qg5ZhShndmG5mCZkKieDOiG7cLqJ/sutlKi6wsjNiLXaEd6vLkoWyOH+SMlsOEjwyklXa3ghpzi4ZWNhZHx7LLSHKlJ4iAxazQYWv5VQlZRoOUkcXCrY5fm3PLfNzftxqDFuKwwBwOkxoQgy+ZBnLzlg4niyxNwSxpOwQz/vWBR+Y5DH8bT19E10XnQQUhaAk44X0cI6DrnwEMeydHX/FT+5NZwcgfN3YrGkoQW1X9YwnsT2d8TcQIjle0QhJ1aZRyLEcFa0T/sYoBRMlIpJ8HI382/lQkoAvftebrSLH4KCuIs9QZ/J8h16sS8yDP1WHMFvcSHobVyNfpQQWutHtKI/9F1+FGuOXMUQ01J8YvodoZbxOON8Qdhgdziou2v1Sel8UIxrKQ/tN6a5aCvfMOJnP/DlRc4CkAWgL/1Gfk/aC0DFgJKEnMf8f8q8X7J7JU9G9YAzWBk0GjvsFfBR/GCUDbiAP7pWArTmDBNfEm1vdxKWKwRvSp5/tMX6yF7Kb1rG4oSzOH4InIpQ4wH1k7LMO+qej7CLKx+hv56tyDDsCZuLD6I/RdGAW9gR1Ef1xHrvkRXBY7YIz3JiZBPkyOLaie1XUSzTSR5hoR2DBnsUc9Z/t6PUPAp0B5ob9mGjowbyIRoHs/TQ9eWsfK6Ws3bi2JUYfF/HgublFC9r2XNIG23oWCkKI8gqHK2l/YWcIlfZWFhsex3DbR0VJ5WId9fpD+yYJPzjgTMralpm4RGyJi4XSz+ilwdDZpckTDsZN2K4cISerMhfmLKzoF/KZUCE2rOgtXQ80aMeujwaZ6INmN++KhqVK+SxhvDIm+iy+KArTjJohJAYvm98D+Fsb+EsaHnxh1tkGLotj8RmS0UMNy1GJ9Mm1WNRMOHUWpxaPlxIKE2bsiiFVkLcLP1d41xxZX8Yav9mFHa60pFwZorB9VV0Ee/tkzF5yz9CKAQl7p9qnp04D6ZknzgHLrY1Fvp1YnoWDR/RHlq219JD2HDihrjrejOk1QYpjtzjGFXMT1PiW2OGvTXeMuzCDCGEQudxraFPswBkAaihu3i8NO0FoMylTrvXKKUIlQNB3d3OX/SYykN2ryQUGhoOY4F5Mly7ZYe4Uki0yw/IdvV5hSROOLQUQ+kK6EQJV8b3K65b1U6kspffF9ZuwlnCmpZlFN7RDfYa6BX/ecKLyO/JRnzOu87sQuJkKnSGbDY1Z3867Ni9ezvabYhF0RwB2DFIxx2kHnYpk3iiZTpPx4hd3bsar63NIryoFgVOEHYOux/TJra4Py9nZaeJDMOXKw5jVVz1xDZNJtYu3B6MLvFfQspR6XecpKcOLBsLex1l8L51uOejqsq2BE67di1LqXMoeXq4ub/76RN6eTBkdq21v4Y+8T0hxel6FE7ih9fCqApCnrXXDQfxY75l2j68vA7wxAv6LDuMtUevo3/lePSs6Tmm9s9TN9D150OKjU7J/Iiv3MQ+/238u5hpfztxB7vamFqR29yoYCGms5HhMOabJ7uM9CV2MjIMzuXtUUnYAPeMzxvgXJNKmJA6hU5Vam0ZgUPO0nDzmKVkn2wOlDa3kOeVxK2wZO+H4Or2w2ZsvmBLCF+RTkXqZgzDoMBliQ2sbFPZ/LTXUVoYa/TBSUmjBZvSKR8gC0AWgBqmvgwiAGUi6aTjBbSwjkce3MfhLN3dDfQ0scrupQS7y+wN8KohEsUNNyClGhBeul3Lq/cAyiacc45CaGT9VthVejKos2sDiJYJR/byk4Lt3zDsxXfmGe7PlpwwSWYjwQfGbRgfOC/5CUpNL1CISykFgiuo/XzKzylO6AuiKmG0rT2aGA5gbr7l+r6kZS+NOpZpQuzY4uwzUbd2A/eEsXSW6N4IvLM2NiHx8zFHcRQNuC1m8JfB8PXl7EH8YUV7JKYpkdrU8271qau2YnpsEyQca+jLC9lbmypOlZByY3qMs6LkSU4g1OoKm3Dlndss/oLOHgyZXdKubko5RLFzruV5sVDbPL4H4kqpnSSP/qfGdRgoxCZq+PDyxkr6e2QY5qz+A+MftUhMNePBw7Xp5A10X3II1QL/w2rjUMG+pMUPbrKxKJ1g5H4msPflUYmbtMw+zLQYncmDSEWrIJHZ08YyDPudZTEl8Hu8Y9ypvY/IVjDkMXPbzX1QzHALoOTK8gTQSrCy/mN1GlHBMh9WmGWhNLL+o3GVp/PMMGy9akzI9zdQ2HVeD2vMI9wT7CeX7H/TQFAYAcUBUnjPn+b+KGW46ruXVG2/TeY6FoAsAP3sQkh7D6DMpb7eXgOfxfeG6slP4Y6XP/w+Rxm0tQ5HCeNNbB3TQX0MoGzCWWd3neMbHPAP1gSN8C5IU5i8ttmrCDuVNSW1VWyI6GLth3BHiD4bCRTisp11MHY7KihyHXoIypZN6P3ju2Klvb4Yk0NpOnR+SYvLRn23xWKN9ZVkY382nbiG7kuPeG4nwSg/Xs7KNpW9HCPsldExfqDiTGBFmpqLu9F5fRS2XjNhZDULPg7RENelZTQrxoL04nbbaRlgAJz0EZN4gg4db0gH2ieethOg3sOtxj6FXZKYJ09tPePxxLbpfRSYUVnwElGRdoomCg8d25B+QOzHUnoR6QhJT97ZTSevo/uSw6hewImV9z8Un1ouAv1bipQfCZf06EgZ5OQ2SIjnolucpgQxstk8AKWFFQsfuMnmhhHxHbDI3hSfGDdgSOAv2uZAxUemFJddBLexM+hzdcdiKubAVpZRwgkiSc4u98G7337WJmy/Yk84wpKW9u8gFwoG3FP3nGLaMulozsQPKT/7g5px5eEaFoAsAH3sOgm3pb0AlE3GM2ytMMX2Ht41/oXJgbQkqWIgydzx8i9z6Yi44jmd2DZYwy5g2YTjSnHSMmnqDrJZzYQje/lddORHvSTnx3qZnBUirbZlGq44C2CZeTRqCrsoxeKLZ0sxsY6K/wg/2Zspkm8rnlMxoSeNa/ThZZNSjxXbdomtIYbaOsvSWrj3i8V7LmD4ulNoajiAOeZpCg+Nij6kZdTI2uSqMy9es8wUNp7Q0rkQIyUV8mwcXigImupx3+E2cmN17pmo9mYPXTbueDRZNhamxr+D6fbWsvQu7l6rz609sc7xmnB03gS5N5nsrj9QCxHv18rs+sLaVQiFSNx1LHqonsmbcLoPVRgSN1t4GYeZh6CSlGaF/uBLX09BxN9y5sIrltmgEANqQyERukI0bTxxHT2WHsYrL+XBijq3E5YzE2dNH3NxShXIxiJ5uRKPjuzlOjpSKp7mHFl/3GMviw/ih7kvR/oyR8jsWWarj69sXVHbcAJLzK5j0FK0R/53xfwlzacJnnA1tinq+Cq+C5bZG6K38Tf0C1zl1xzYbu4e7D4fhemB36GlcZeHfpzCfCabC2fb3hRygrqHneg8F3ofZWAByAJQRTdJ8ZL0EYBkUmQYhF1ZlmoYYPoVPUzr1ceuyJYLpac7lLUWWt/rhRfzZsP/+jdQz0U24UjHDyWkOJHXovZFJL78aIm6rGWBsHzhOtheTBmQUjyhTEDed2ZBJYvrHGRvZ5eqeljFxColKk44Ps3T5Cy7h76WE3Ykm/viRcNNvybjJDbLJljJK5INccJh8Mql+Mlb/sWsiH/RvrQDo+8NSPAiCXXqvdyqOKNUSqK9wTwYFQwXkjzGTeezwkkrrg0gnV0bQNTGkKpqSMVF4ljYG51TiE2io7z2PzsUAS/VTYj9o75IS8S0+UPPs1VTNFe0a0XUy0JC7JCAv7EqaJTrFlp2LdcK2EsnPAB3nDkTjjuk0AvhmC2pqPnw8sZN1o9pKTzEMht3UxCbvx+/jp6/HEbCueLiBhI8vOlTWqgk5iWzEW5B4EQ0NB5NeVzJ+qOUYDlxQ4Lsl7Rwk9lD4RQtrWPhU1JpxUfmB9Yh2OMo7/mIteRitBUe5Pm2UIyxtUdTw37xY893odXmhz3YfyEK3wVOxxvG/do+HGWMpNjEHIgV5mYjbc7zNH9665d+/p0FIAtAP7tQOiwByyyWdlX+UMeCUOWuSm9PppiUjxjK4e3Ze1E0T1bsGNDQ292Jf5dNOK/GzRAyw/ubTkEKgg69/ZmQZmB+4CQ0yn1L3QkeooA86CiFd60jUIjSJ2ShUwj89GwpJlYptcWzeIAjQd08L8/IJnQpXpMmPYrnEnYkp9JLmhJCu05jecajR6j/wZxCPq8vm5RCr/rFQTnDdHs5K3uO4mX9f9bB2OWogPGmH/GBKSJJPwu3V026AYQET58T6sMS1Pde15UOO+IivkWlLaWEM5rDzV+ipMG1tErlrKMImlgngQT1iaDOaffCOrUWF5f3FzzhtGGHfjvB4yaLq5MS7JYMuILwoAHuT6/2wyslZgphIi3hJfnQE0XT+mPX8NmvR/Bq8bz4tWtNra3h/XrFWJS8s/1Ny9DTFJbyMq6HD9ZRpoXoID8vlyzQwk1mz2NnoPCh55An8Fa7rKwQ2rShjsbw7+ZBKG+4qF4kyTzIO+3l8WH8YPGkDjq73Pewk7e/34Ujl6Ixt74dTSJdm1QSircPR1kfkn9QuTYLirlHqTItwtt7T0nxChaALAD97ELpJwDliV8396mL0gUVedU0Ptmxy9Fo+d0uFHk2K3Z9pUEA0u9EhiFmefeE5NLHgzojZ8Bj/0SXw45e88Ox4ZwNg2oEoVtLDeeHRobh59/WYtjD1qhvOIqF5on6eLZkE2uc0yRM9HYYhfxchWjpSempkk3o0g7SOobj+Nk8IdVf0pI3dqhpCbqYNib+Xuv56HCgGOi4ronvVkKbEJUnmWjsTwmXK17W4+Pfxxy3k1DcK54a31pYin3HsB1TzK4TboSi5YWs1VaxXT+wDhY8LmNN8/GhaWtCLSttddHf1l12Agb9yXdPiirzRG509CClnrmJPPglcCxqGSMTbxdiFJ2YEv+OkFrDfalQR/sUIl7ynLmnJklsIykZ/Gsl82Jpl1QQgOKc49rIAcy2tRCWFF2ePJdXNFmvcQLX60L+P/JkrjEPQ7DhnMjVR26yuaGhZRLOOwsLO+zrGU+kbI+8M8jGygVHAdS3ThWS4ZMnPMmxjt6OahQ9yLdiHiUu2ecfgizNxvocUvHmzJ04cTUGP31cHQ1K5dX24ZhMDHWSD8HUHOeKgccCkAWgqrk4hYvSbQn4zkMLQsaGC9voT48ORZZA/xK/nrgSgzdn7UThXFmwe1AjzVz2RYSh7WZjws5SoQJvX4VefmXqlrOYvvUftAl5HhPfrazJpqFrjmPJvsvoXi4eX9VPrKTlAAAY4UlEQVTx8wg4+S/Lls+bWL7BWWdRLMg1Hw1bfpx0YpVN6H2t3bHGUQefG1ejLyVlFYqPLxtPJBQT7BxbC4y3tUNjwyHMM3+beEeHDQhd58SZGw+wsGN11C9dQBNXny6WvRw32F8RUvNUCjiHsKDhSXaISptrknhlUsszIFs6n257G1Nt7yXucBUfdlj8x/jZ3kQW2O+nN1kNRFl79rb2RJjjNUXfkTWpdSD+clROPF3GX2+30j6FiN9ur4j28YOQeKSXez+WBGDtkvmwpEsNNU/r2zXiWIy4l1/YXCRkMMg/w/tKQWQYLi/rhzrW6R48q757yKSVi553WuN3x6v4yvQLuuc54t0e5fyyoj3C7DXRO/4zWQogH/qcww7nhV2ouug+7lkCsKFXLVR4PrdvrAGETtsuzBs/d34FdSjptpai6EOT4tvgO3srtDFGYGLgj/rOhSrtYgHIAlBlV0n2snQTgPv/i0KbOXvwfO6s2DlQo8fOw+OcuhaDN2bsRMGcWbB3sHYBuGj3BYwIO4XGL5gwr/YDXWJ9pKWkqsWexW89tJ1P/O7s3Th48R6mv18FLau4H3nmb6MLWfov7sbnm6Ow7oIJ/Zu8jJ4NS3muVhQ/9Szf4qKzoOgVEHdz0h16xbcpJtjEOJtHQg4wI70/xKXUal9vw91HVmzsXQflClMXToMivqwvRtvEzT3xOJl/GMzVPgT+N04w4L4zK6pa5ggnTbjiPm+5CVfNycnVPJZMaO13lEYb6wjQsj7lKHN5XZCQ8HZm4Ay8adzr94eNGrPg4axal2ge5na7s0YPBG8PRrRTttzv54eXR/tkIp7iaymVB51TfCDoU1f+UVk/XnPkCvouP4Y6L+fDz51TUQCSoQ47bkTuRM0lD4U+HjmqCYLM3hOsb9i4Hr22G1Ax4DzWB1GqGv8/WIU6HHZ8tyYCkw5Y0LKkCdM7NdYeuhAZhnGrdmBubH18aNyCsYE/+dXn6D1B74spbSrjnarPq+p+ni5qPOUv/HvrIX79pCZeLZFXez2yPiTl+nw54Aq2BImbqPSaC1VaxgKQBaDKrpLxBODyA5cwcPUJ3SbZ09fvo9n0HcifIwgHhjTWzEU6KLxngxLo31TD+bgp/JJkU84sJhwb0UT1Ye+0PF5x5J94aLFBj+Xx5Ez84a9zmPDHGbxRqRC+a1c12Se5cygMIStdHtpjQV1cKURS+SVtcwYgWIgDzIYN5iGuDRdtFsNaqgVKDf1DsOXQ0MbImz1Ic1v7fIPokai88D7uWwPwe69aKE8CVEjLcR2SdzAxxQj9ko5eUk+Gy4QWbdR51TJT2IEsxJ0aj4BShVSwLEA8TNj+VhyKFfL/TFVV/GTClDZ5vGL5XogrUwrji63CUG/ZQ5gNwMk2j2HO9RzwQi3tokONUTLvd6hlAs44i2FOroVo2vIjN+/3b4evoN+KY6hbKj8Wd3pFTc1+XUPjnU7YiY6Nx++9a6N84Vxe6xu38TTmbj+PD8sFYmzwfV0+WKUflY7CK/1cDmzuW9erLZ4u+GDuHuw5H4VvaljRtko+v9p02NqT+HnvRXSrVxyDmpX1yR66qf6kCFy4G4tV3V9FyIt5fKtH7EN3Yx4kJNM/lm8YcjUf6fPStG+GgHcBJwZp+YrwibivJ4D+AArS+xkA7RigLU5qSrp5AMf/cRpz/jqPj2u9iJFvlVdja4rX/H3jAZpO24582c04OPR1zfVJAcIzPwjGm5ULa77f0w102HvZ4ZuEJLz7hzRCgRzqDnu/HBWLOhMjEGgMQOToUAQaDbrYo6yE4ug6LNiP4vmfwbYv6if7G9LJCC/nNmBLcz/PCPX2JLKXdCfrl9jmqIqh2dejyzvNhQn2WvRj1JqwDSZDAM6ObQYDHR6bxqXdj3ux+9xdfNO6ItpWL5aQY66ftTt+c9RBV+MGDBZyqPmw7KX1WRRL52PiP8R8e3O0MOzBLPNMSLs6c2cJwOERzVR/hGg1I8n1Co/uh9ZB2OmoiP6m5ehpopNJXMJ4XYPN+Hz5cVQp+izW9tTmJffJRtH7PXhrFH7514RudV7CoDfKuVW1ijYYrTyG+qXzY2HH1BeA9ONt5+zBvv+i8O17ldG6mncvl+QVm/RuJbyncxysfIydGt1U87nMdG525dF/4kGcTbWgTaktSfyRCGxYpgAWfFzdp2anm16bsA1Xox8L/Yz6m89F7EP1lkbj4kMDFncMQd3Sz/lcna83sgeQPYBtASwGQMdo7APQB8B7AEoDkK0/JdvF0k0Adl18EH9G3sSot8qjQ60XfR0DCff9e+sBGk/ZjjzPmHF4mDYBSBNWhZGbEWu1I7xfXZQs4N+GFPnD1J0YgUtRsZqWHaSzSMsUzIFNfXz7AlcD9PYDC6p/7YrDPDWqKbKZTR5vIy8heQvbhhTFN+9WUlO1f9eIE+yPB+7i68OBaFwmP+Z97HoRH70cjVbf7fI51tM/w1x3j994GnPI+1KzGMa2qij8N/vJMIQsjcM95zOJeRtTw0uqfACF0DrheAlvWr9GEKw4GPQp1tprY5itI+qVyodFnVJ5OVNpm2zJbJmtnpBfrkzARWwSznh2hQ+MPlcSC3b9p9uHoNr2XX3oCr5YeQwhL+TGqk9rud224uBlDFh13G/BodYWum5k2Cks3H0BXesWx+DmKXu5bHaHsELwON6OP/vWRann9JuvyBbySFYZvQUxj+Ox4bPaqFDEu0dS/qz/3XmEBpP/B7PJIMwr/n7ASuFCPm3wkxlWY1w4bt63+PRMntqyz7IjWHv0Gvo2LoXPG7+spbl1uZYFIAtAEn0HAPQSexS5imhP+kwAiq2aHvtcuglAKR7Dp4BcD49y7vZDNPr2L+TKGigst2opl+7Gou6kCGHCihzVFCYdPW6dFh7AtjO3MKZVBXxU8wVVZs3a9g8m/3kWbwcXwdS2VVTd4+tFtBGHNuSs6VELwcU8B1hL3oYEj5evP6bxPmljT44sJhwd3gRGQwA2n7qBbj8fQuWiz2JdWniMPNgsxXbKbTh0MQqtZ+9BTjNwqPVjBOZMxaXMFIQWvbwbWyfhnLMIJpnmYJ+zDFbZ66F3w5Lo14S+C9O4iB7d6JgYIf8exUeG55mIki2+EDy6rWfvxqGL9zC1bWW8Hezd86WX9XKRcmJkEzcv14oDlzFg9XE0KlMA8/3wOGmxddn+S/jqN3UhMWdu3EfotB14xmzE8ZFNhXGhd3l/7h7sPR8FXzyMYceuofevR3Qbo9GxVkGQUqG2ypHFe4ykJx5Vx2xB1COrbmE1Utx4WnqK5c/FAvDpFoBmALGUVx/AWlnHWASA/NstPQwCCpiSB03Rp+OVmJgY5MypXzA9HaVE52mmVDYcvw6bw4mdAxvg+dzZ/J6/pAmdlgZbVCqkqb7bDy3Y9e9dIZ7r9951NN3r7WIpVqfUc9lRrpA6xkcuR+Pi3VgMalYG3eqV8PYTfv39o/n7sOOfO4InhDbkeCobT96A1ebQ3TvqzXC7gzwRrqWkJuWeQzazERejYoVcXvTvue1DvFWRKn+/cOcR6pOHw2hA84oUeQGcu/1ISDFB4QMURpDmRbZ0PsvWEpNtbVHMcBePzHlwNy4A89qHoHG5tF+mEjiIHt2O6+8h4poRVYrmwot5nxH+JPWtbV/UQ/H82dMMGwnlamPDBUHQuGwBZA9K9H5TnBh5mhuXfQ7zOqRNH5M822QH2ZNSuRYTJ2yKqFk8D5Z1fTVVmEkeSVqFoP9pKX/ffAiKf5Z7yLXc7+naV74Ox60HFsErSzHVvpTfT1xHvN2JrV/UQwkd+trxK9F4a9YuYV6i+SilElqhIEIraHsveXtGFoBPtwCkQLWrAGj9Yo+ss0wEUA+Ap/WekQAUh9wCegvAaeFnMS38H2/9F89mC8Thoa/rEsdFE3nI2C1weDq33aslrgva1SiGcW+7lvT0KtLXsC/1LetaEzWL+7BbTcOPTdlyFjO2em+rfNmDsH9wI13aSoN5+HTJIfzh4WPC34BwLTYoryXxUP3rrYLnVFlmtQtGi0r6xJBqtlEUWpdv3EL9sCywi2OBPopoZzy1YXoWKb2K0ob06ls9lx4GiYLkii/pm3zlG2u1odqYcGFZV235rGFJfJFKXt3k2kqtbXTdtLZV0CpYnwwGXRYdRPhp2elDWgyRXUveUtokSKFC/pZ4uwPVxmzB/Tib16r6NH4ZfRonk2nB692eL2AByALQkwCcBIDcWJ4ymKaJB5CWdI5cUhyw7aEPk7jRGl+S0ljZ9e8d4cvTlxIUaMQbFQvpMjHIf5/idUgEkkDVUgrlyip4lwIoQC8VC+00piXNR5aUJ7FaJfKlXcoV2fPeuh8nCECabKWS1WwURBYt96dXibx2H7vP3XH7+bzZzWhZuUiai2RPDHb/eweR4ligXaU+pb3QGS7F2q47dhV3H7qPhXTrWw/i8McJ974lPTKFgzSrUEjIKpBWRe28SfZQvO5bVQq7eS71tNPXeUuyIXc2M1pWKaxbOM2NmDjQyhKtGvlTyhbKiddK5vOnCrd7KUxl3393vdZH4TXVXvA9h6GnH2AB+HQLQF+WgJX9KN1iAL2OGL6ACTABJsAEmAAT8EiABeDTLQCpU9AmEEr5QqlfqNAmkEsAZmX0TSA8ppkAE2ACTIAJMAHfCLAAZAEopYHpKgpBSgPTBgBlMlYTMMEeQN/GHt/FBJgAE2ACTCDdCLAAZAFInY9SwEiJoI8C6C16BtV0TBaAaijxNUyACTABJsAEMhABFoAsAP3tjiwA/SXI9zMBJsAEmAATSGMCLABZAPrb5VgA+kuQ72cCTIAJMAEmkMYEWACyAPS3y7EA9Jcg388EmAATYAJMII0JsABkAehvl2MB6C9Bvp8JMAEmwASYQBoTYAHIAtDfLscC0F+CfD8TYAJMgAkwgTQmwAKQBaC/XY4FoL8E+X4mwASYABNgAmlMgAUgC0B/uxwLQH8J8v1MgAkwASbABNKYAAtAFoD+djkWgP4S5PuZABNgAkyACaQxARaALAD97XIsAP0lyPczASbABJgAE0hjAiwAWQD62+VYAPpLkO9nAkyACTABJpDGBFgAsgD0t8sJAvDy5cvImZP+LxcmwASYABNgAkwgoxMgAVi0aFEyMxeA+xnd3tSwLyA1Kn2K6iwC4MpT9Lz8qEyACTABJsAEniQCzwO4+iQ9kNpnYQGolpTn64hfYQAP/KvG4905RHFJnTM16k8Fk5+qKrl9Mn5zcxtxG2V8Ahnfwid5HNGzXQPgzPjNoL+FLAD1Z6pXjcLy8tPsntYLZCrVw+2TSmB1rJbbSEeYqVQVt1EqgdWxWm4jHWFmpKpYAGak1nC3hQddxm0bsozbJ2O3D7dRxm8fbiNuo8xB4Am1kgVgxm1YFhgZt234xZWx20ayjsdQxm8nbiNuo4xP4Am1kAVgxm3YIACDAIwHYMm4Zj61lnH7ZPym5zbiNsr4BDK+hTyOMn4b+WQhC0CfsPFNTIAJMAEmwASYABPIvARYAGbetmPLmQATYAJMgAkwASbgEwEWgD5h45uYABNgAkyACTABJpB5CbAAzLxtx5YzASbABJgAE2ACTMAnAiwAfcLGNzEBJsAEmAATYAJMIPMSYAGYMduuJ4D+AAoCOAbgMwD7M6apT7xVIwGMUDzl3wDKiP8tC4BvAbwPgHbLbQbQA8DNJ55M+j1gXXF8VANQCMDbANbKzKF5bRSATwA8C2AXgE8B/CO7Jg+AmQDeBOAAsBrA5wAept9jPVG/7K2NFgLooHhiGjuh3EZp0g8ow8Q74jz2GMBuAAMB0NwmFTVzWzEAswE0EMfOIjF7hS1NnoJ/xC8CLAD9wpcqN7cFsBhAdwD7APQB8B6A0gBupcovcqUpESAB+C6AxrKLaHK7I/6bJr83AHwsntwySxQUrzHWVCPQDADxPSwKN6UApBcZveCoTc4DGAOgIoByAOJEq/4QxWM3AIEAfgJwAEC7VLP66arYWxuRAHwOQEcZFkp3dU/2b26j1OszmwAsE/u8CcA4ABXEMfJI5dxmBHAUwA3xg4w+xujd9SOAwalnOtesFwEWgHqR1K8eEn30IuolVmkAcFn0VkzQ72e4JpUESAC2AlDFw/W5ANwWRcMq8e/kGTwN4FUAe1X+Bl/mOwE6w1MuAGlOo7M9ySs7WayW2ok8siQI6aVXFkAkgOoADorXkOdpIwA6e5vu56IfAWUbUc0kAMk7S2PLU+E20o+/mpryiw6GegC2i0eQepvbSORvAFBYtuJBjotvAFB9VjU/zNekHwEWgOnH3tMvmwHEih4n+ZIWudVpsmyZscx9KqwhAUjL8XQuM3mP9ojepUsAGgLYCiA3gGgZjYsApgGY+lQQSt+HVIqL4gDOAQgWvROSdX+J/6Zl3k6iQKR2kwp5Qah9ydu+Jn0f6Yn79eQEIIk/Egnk9dsGYCiAu+LTcxulbTcoKYZIkKf8pMq5bTSAtxQfxy+JXveqAI6k7SPwr2klwAJQK7HUvZ6+pK4CqCUKDenXJgKgL7MaqfvzXLsHAvSVm12MjaElDooHLCIul1D8GC0dUuyfvFC8ZoQYU8NQU5eAUlzQ2KGYPxpL12U/vQIAXUshFrQ8RfFnFFYhLxRiQe1Ly/pc9CPgSQBSzCx97P4HoIS4BEnxl+Q5t3Mb6QdfRU20yhQmOhlqi9dTKIS3uW0ugBcANJX9RjYAtITcHAAt4XPJwARYAGasxklOAE4CUAdAzYxl7lNpDXliycPXDwAFT3uaJGkJnzyDXz2VhNL2odUKwJWisCDhkZwApCWvYQB+SNtHeOJ/zZMAVD605LmlWFsaO9xGadct6IOHPnRJ/F3xIgDlc1tKApDqozhDLhmYAAvAjNU4vAScsdojOWtoEgwHsIWXgNO9wXgJON2bwKsBagQgVUICnJaB5/AyvVemel1Am9YotIh2bZM3Vipqwlt4CVivVkinelgAphP4FH6WNoHQEiKlfqFC7nmKN6OByptA0r+9aDmY2oNiAyk2k15aH4i7Ucm6UuJyMW8CSZu2Sm4TCG0AoY0gVHKKAe7KTSAhAA6J1zQRPRa8CUT/dlMjAIk7jSuKC6TlSGkTCLeR/u1BNdK7n9Ig0Qaq+ooUSfR3aYNbSnObtAmEQmOkDBVdAdCKVQEAtKubSwYmwAIw4zWOlAaGBhIJQUoD00bM18S55dK+vUhIrBeXfWmJnvLL0Y5gSilC4o+WTyjehcTFfXFSJSspFo1L6hAgEU5B61Qo0JyW4ynmMkoUEZQGhpbfKc6PvBqUBqaShzQwlIaEdi1KaWBoRzCngdGnzVJqI2onirWk3IuUQoRiACnOOYeYrkcSDhRDxm2kT3soa/le7Ovk/ZPn/qPNbhTaQsXb3CalgaFd8wPEvLU/A5jHaWBSp9H0rpUFoN5E9amPUsBIiaApz1JvMSegPrVzLVoIUNoQWh7JKwq+nQCGiDtNqR4pWSp9KcsTQdOLjUvqECCPBQk+ZSGPLAlxKRE0fURRzCa1GSXnPiu7gRJBk1ddngiaxhkngtanzVJqI0rKTVkOaKc2tQ8JiD/F+Ev5Ry63kT5t4akW8sp6KpSXkVL0qJ3baBMICUVqb9r8QWOQPr44EXTqtZ1uNbMA1A0lV8QEmAATYAJMgAkwgcxBgAVg5mgntpIJMAEmwASYABNgAroRYAGoG0quiAkwASbABJgAE2ACmYMAC8DM0U5sJRNgAkyACTABJsAEdCPAAlA3lFwRE2ACTIAJMAEmwAQyBwEWgJmjndhKJsAEmAATYAJMgAnoRoAFoG4ouSImwASYABNgAkyACWQOAiwAM0c7sZVMgAkwASbABJgAE9CNAAtA3VByRUyACTABJsAEmAATyBwEWABmjnZiK5kAE2ACTIAJMAEmoBsBFoC6oeSKmAATYAJMgAkwASaQOQiwAMwc7cRWMgEmwASYABNgAkxANwIsAHVDyRUxASbABJgAE2ACTCBzEGABmDnaia1kAkyACTABJsAEmIBuBFgA6oaSK2ICTIAJMAEmwASYQOYgwAIwc7QTW8kEmAATYAJMgAkwAd0IsADUDSVXxASYABNgAkyACTCBzEGABWDmaCe2kgkwASbABJgAE2ACuhFgAagbSq6ICTABJsAEmAATYAKZgwALwMzRTmwlE2ACTIAJMAEmwAR0I8ACUDeUXBETYAJMgAkwASbABDIHARaAmaOd2EomwASYABNgAkyACehGgAWgbii5IibABJgAE2ACTIAJZA4CLAAzRzuxlUyACTABJsAEmAAT0I0AC0DdUHJFTIAJMAEmwASYABPIHARYAGaOdmIrmQATYAJMgAkwASagGwEWgLqh5IqYABNgAkyACTABJpA5CLAAzBztxFYyASbABJgAE2ACTEA3AiwAdUPJFTEBJsAEmAATYAJMIHMQYAGYOdqJrWQCTIAJMAEmwASYgG4EWADqhpIrYgJMgAkwASbABJhA5iDAAjBztBNbyQSYABNgAkyACTAB3Qj8P84le1Qe/YLvAAAAAElFTkSuQmCC\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fcd907d4b70>"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all_data_mean['hour_index'] = (all_data_mean.index.month - 1)*18 + (all_data_mean.index.hour - 3)\n",
"plot_array = np.zeros((12*18))\n",
"plot_array[all_data_mean.hour_index.values] = all_data_mean.poa_global\n",
"\n",
"plt.figure()\n",
"plt.plot(plot_array)\n",
"plt.scatter(all_data_mean.hour_index, all_data_mean.poa_global, c = 'C1')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Read Sonnendach"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"DF_UIDs = pd.read_csv('/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt', usecols = ['DF_UID'])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"9639231"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(DF_UIDs)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compare no Albedo and with Albedo"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"withALB = '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_clean.nc'\n",
"noALB = '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_noALB_clean.nc'"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"withALB = xr.open_mfdataset(withALB, chunks = {'DF_UID' : 10000})\n",
"noALB = xr.open_mfdataset(noALB , chunks = {'DF_UID' : 10000})"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"withALB['poa_global'] = withALB.poa_direct + withALB.poa_sky_diffuse + withALB.poa_ground_diffuse\n",
"noALB[ 'poa_global'] = noALB.poa_direct + noALB.poa_sky_diffuse + noALB.poa_ground_diffuse"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"withALB['poa_global_yearly'] = util.get_yearly_sum(withALB, 'poa_global') / 1000\n",
"noALB[ 'poa_global_yearly'] = util.get_yearly_sum(noALB, 'poa_global') / 1000"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"withALB_yearly = withALB.poa_global_yearly.to_pandas()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"noALB_yearly = noALB.poa_global_yearly.to_pandas()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID\n",
"1 1435.760226\n",
"2 668.646172\n",
"3 1284.928051\n",
"4 1352.075574\n",
"5 949.123793\n",
"dtype: float64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"withALB_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID\n",
"1 1433.768987\n",
"2 665.870799\n",
"3 1284.716919\n",
"4 1350.480231\n",
"5 947.335436\n",
"dtype: float64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"noALB_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"diffALB = withALB_yearly - noALB_yearly"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean absolute difference: 2.338 kWh/a\n",
"Mean difference: 1.962 kWh/a\n",
"Percentage difference: 0.180 percent\n"
]
}
],
"source": [
"print('Mean absolute difference: %.3f kWh/a' %(abs(diffALB).mean()))\n",
"print('Mean difference: %.3f kWh/a' %(diffALB.mean()))\n",
"print('Percentage difference: %.3f percent' %((diffALB/withALB_yearly).mean()*100))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
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]
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},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"withALB_yearly.plot.hist(bins = 50, density = True, label = 'with ALB', range = (300, 2000),\n",
" facecolor = 'None', edgecolor = 'C0')\n",
"noALB_yearly.plot.hist( bins = 50, density = True, label = 'without ALB', range = (300, 2000),\n",
" facecolor = 'None', edgecolor = 'C1')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Spielwiese"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"data = []\n",
"for idx in incomplete_files: # range(97):\n",
" data.append( xr.open_dataset( os.path.join( path, '%s_%i.nc' %(file_base, idx)) ) )"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 100000\n",
"1 100000\n",
"2 100000\n",
"3 100000\n",
"4 100000\n",
"5 100000\n",
"6 100000\n",
"7 100000\n",
"8 100000\n",
"9 100000\n",
"10 100000\n",
"11 100000\n",
"12 100000\n",
"13 100000\n",
"14 100000\n",
"15 100000\n",
"16 100000\n",
"17 100000\n",
"18 100000\n",
"19 100000\n",
"20 100000\n",
"21 100000\n",
"22 100000\n",
"23 100000\n",
"24 100000\n",
"25 100000\n",
"26 100000\n",
"27 100000\n",
"28 100000\n",
"29 100000\n",
"30 100000\n",
"31 100000\n",
"32 100000\n",
"33 100000\n"
]
}
],
"source": [
"incomplete_files = []\n",
"for i,d in enumerate(data):\n",
" print(i, len(d.DF_UID))"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[28 29 30 36 37 39 40 43 44 45 47 48 49 50 51 52 53 54 55 56 57 64 65 66 67\n",
" 72 74 76 77 79 81 82 88 93]\n"
]
},
{
"data": {
"text/plain": [
"34"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(np.asarray(incomplete_files) + 1)\n",
"len(incomplete_files)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Fix issue with rooftop linking (linking to pixels outside CH!)\n",
"- Some rooftop coordinates lie slightly outside CH - should be linked to pixels inside\n",
"- Logic: 1. get pixels that lie outside CH ([x_idx, y_idx] not in the existing combinations)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"roofs = pd.read_csv('/scratch/walch/workspace_tilted_irrad/rooftops_tmp.csv', index_col = 0)\n",
"meteo = xr.open_dataset('/scratch/walch/workspace_tilted_irrad/meteo_tmp.nc')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def link_rooftops_with_pixels( rooftop_frame, meteo_xarray, \n",
" rooftop_coords = ['XCOORD', 'YCOORD'], \n",
" meteo_coords = ['x', 'y'], \n",
" new_columns = ['x_idx', 'y_idx']):\n",
" # creates columns 'x_idx' and 'y_idx' on rooftop_frame, giving the index for the x- and y- coordinate of each\n",
"\n",
" x_link = pd.DataFrame(data = meteo_xarray[meteo_coords[0]].values, columns = [meteo_coords[0]]).reset_index()\n",
" y_link = pd.DataFrame(data = meteo_xarray[meteo_coords[1]].values, columns = [meteo_coords[1]]).reset_index()\n",
" \n",
" for roof_coord, meteo_coord, new_column,link in zip(rooftop_coords, meteo_coords, new_columns, [x_link, y_link]):\n",
" \n",
" # merge on one coordinate (first on x, then on y):q\n",
" rooftop_frame = pd.merge_asof(rooftop_frame.sort_values( roof_coord ), link.sort_values( meteo_coord ), \n",
" left_on= roof_coord , right_on= meteo_coord , \n",
" direction = 'nearest' )\n",
"\n",
" rooftop_frame.drop(meteo_coord, axis=1, inplace=True)\n",
" rooftop_frame.rename(index=str, columns={\"index\": new_column}, inplace = True)\n",
" \n",
" ## CHECK FOR COORDINATES THAT ARE OUTSIDE CH AND ASSIGN TO CLOSEST PIXEL IN CH\n",
" # create a pandas dataframe with a list of all coordinates that are in CH\n",
" index_mask = create_mask( meteo_xarray )\n",
" idx_CH = util.to_pandas( index_mask )\n",
" \n",
" # merge that information to the linked dataframe, so there is a column \"CH\" that is [0, 1]\n",
" check_CH = rooftop_frame.merge(idx_CH, left_on = ['x_idx', 'y_idx'], right_on = ['x', 'y'], how = 'left')\n",
" check_CH.CH.fillna(0, inplace = True)\n",
" \n",
" # get points outside CH and coordinates of CH\n",
" outside_CH = check_CH.loc[ check_CH.CH == 0 ]\n",
" CH_coords = idx_CH.drop('CH', axis = 1)\n",
" \n",
" # calcualte distances and get index for coordinates of closest pixels\n",
" distance_matrix = cdist( outside_CH.loc[:,['x_idx', 'y_idx']], CH_coords )\n",
" min_distances = np.argmin( distance_matrix, axis = 1 )\n",
" \n",
" # fill data in linked dataframe and drop unnecessary columns\n",
" check_CH.loc[ check_CH.CH == 0, ['x_idx', 'y_idx'] ] = CH_coords.loc[ min_distances, : ].values\n",
" corrected_frame = check_CH.drop( columns = ['x', 'y', 'CH'])\n",
" \n",
" return corrected_frame\n",
"\n",
"def create_mask( meteo_xr, var = 'SIS', sum_dim = 'timestamp' ):\n",
"# create a mask boolean mask indicating all sums greater than 0 (i.e. values inside CH) summed over multiple timesteps\n",
"# NOTE: xarray dataframe spatial coordinates must be labelled \"x\" and \"y\"\n",
" \n",
" mask = meteo_xr[ var ].sum( dim = sum_dim ).where(meteo_xr[ var ].sum( dim = sum_dim ) > 0) * 0 + 1\n",
" mask = mask.rename('CH')\n",
" mask_idx = mask.assign_coords( x = range(len( mask.x )) )\n",
" mask_idx = mask_idx.assign_coords( y = range(len( mask.y )) )\n",
" \n",
" return mask_idx.to_dataset()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"linked = link_rooftops_with_pixels( roofs, meteo )"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
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" XCOORD YCOORD DF_UID FLAECHE NEIGUNG AUSRICHTUNG \\\n",
"83283 612514.648039 116294.773446 9336881 19.795029 19 156 \n",
"83260 612515.801416 116292.143741 9336882 20.223975 21 -24 \n",
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"\n",
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"83283 280 92 \n",
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"83304 280 92 \n",
"83235 281 92 "
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"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"linked.sort_values('DF_UID').head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (timestamp: 159, x: 494, y: 122)\n",
"Coordinates:\n",
" * x (x) float64 5.565e+05 5.567e+05 ... 6.549e+05 6.551e+05\n",
" * y (y) float64 9.789e+04 9.809e+04 ... 1.219e+05 1.221e+05\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
"Data variables:\n",
" SIS (x, y, timestamp) float64 nan nan nan nan ... nan nan nan\n",
" SISDIR (x, y, timestamp) float64 ...\n",
" apparent_zenith (x, y, timestamp) float64 ...\n",
" azimuth (x, y, timestamp) float64 ...\n",
" DHI (x, y, timestamp) float64 ...\n",
" DNI (x, y, timestamp) float64 ...\n",
" rel_airmass (x, y, timestamp) float64 ...\n",
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"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"meteo"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# create boolean mask of CH\n",
"mask = meteo.SIS.sum(dim = 'timestamp').where(meteo.SIS.sum(dim = 'timestamp') > 0) * 0 + 1\n",
"mask = mask.rename('CH')\n",
"mask_idx = mask.assign_coords( x = range(len( mask.x )) )\n",
"mask_idx = mask_idx.assign_coords( y = range(len( mask.y )) )\n",
"mask_idx.to_dataset()"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"idx_CH = util.to_pandas(mask_idx.to_dataset())"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {},
"outputs": [],
"source": [
"check_CH = linked.merge(idx_CH, left_on = ['x_idx', 'y_idx'], right_on = ['x', 'y'], how = 'left')\n",
"check_CH.CH.fillna(0, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [
{
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"text/plain": [
" XCOORD YCOORD DF_UID FLAECHE NEIGUNG \\\n",
"83342 655019.166405 116304.698060 9362000 70.225513 0 \n",
"83360 655002.186185 116307.886175 9362001 119.907529 0 \n",
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"83444 654999.654431 116328.291700 9361994 170.446780 16 \n",
"\n",
" AUSRICHTUNG x_idx y_idx x y CH \n",
"83342 -180 493 92 NaN NaN 0.0 \n",
"83360 -180 493 92 NaN NaN 0.0 \n",
"83424 11 493 92 NaN NaN 0.0 \n",
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"source": [
"check_CH[ check_CH.CH == 0 ]"
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {},
"outputs": [],
"source": [
"# get coordinates that distances should be calculated for\n",
"outside_CH = check_CH.loc[ check_CH.CH == 0 ]\n",
"CH_coords = idx_CH.drop('CH', axis = 1)"
]
},
{
"cell_type": "code",
"execution_count": 115,
"metadata": {},
"outputs": [],
"source": [
"# calcualte distances and get index for coordinates of closest pixels\n",
"distance_matrix = cdist( outside_coords.loc[:,['x_idx', 'y_idx']], CH_coords )\n",
"min_distances = np.argmin( distance_matrix, axis = 1 )"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {},
"outputs": [],
"source": [
"# fill data in linked dataframe\n",
"check_CH.loc[ check_CH.CH == 0, ['x_idx', 'y_idx'] ] = CH_coords.loc[ min_distances, : ].values"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {},
"outputs": [
{
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"text/plain": [
" XCOORD YCOORD DF_UID FLAECHE NEIGUNG \\\n",
"83342 655019.166405 116304.698060 9362000 70.225513 0 \n",
"83360 655002.186185 116307.886175 9362001 119.907529 0 \n",
"83424 654999.689638 116322.288723 9361993 210.977038 15 \n",
"83444 654999.654431 116328.291700 9361994 170.446780 16 \n",
"\n",
" AUSRICHTUNG x_idx y_idx x y CH \n",
"83342 -180 492 92 NaN NaN 0.0 \n",
"83360 -180 492 92 NaN NaN 0.0 \n",
"83424 11 492 92 NaN NaN 0.0 \n",
"83444 -169 492 92 NaN NaN 0.0 "
]
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"execution_count": 117,
"metadata": {},
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}
],
"source": [
"# check that it is now filled with a different ID\n",
"check_CH[ check_CH.CH == 0 ]"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {},
"outputs": [],
"source": [
"corrected_CH = check_CH.drop( columns = ['x', 'y', 'CH'])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
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" 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"1000\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize = (10, 4))\n",
"meteo.SIS.sum(dim = 'timestamp').plot(x = 'x', y = 'y', cmap = 'binary')\n",
"plt.scatter(linked.XCOORD, linked.YCOORD, c = linked.y_idx, s = 1)\n",
"plt.axis('equal')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the 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",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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VWfA9iUggcoIOINeGXobloAEuiCQg6D//e9/LyXoCy+8cDeCvjywG7AkMDuwHnDWKChXBA4DFgEeAPYHTup4517g3SPU8X1g+/T7lwErDCvzQ2CbLtJoUQmUIqCgl8KW9UsKetbps/MSkMBYCCjoY6HnuxKQwKAI5CDoN998cylBX2SR8GZmBJ4twHN1YFngOuDMAoI+L/A34AfAccDKwBHAmsBFqb1ZgSk72l4U+C3wcSDEPJ7439uBb3aUe6FgnwuEZREJTJqAgt6+0aGgty/nRiwBCSQCCrpDQQISyIGAgj5ill4vIOgHJxkP6R56TgNmAlabRO5D4NcC4oL2aGNI0G8Ads5hvNjHZhFQ0JuVzyLRKOhFKFlGAhJoJAEFvZFpNSgJNI5ADoL+t7/9rdQM+qKLTnTnojPonbktIuiXp9n2TrHeMs2iR5vDn6mAh9OS+AM6PowZ9JjqD1d6FDgH2A+IWXQfCfSVgILeV7y1rFxBr2Va7JQEJDAIAgr6ICjbhgQkMFYCOQj6X//611KCvthiiwWeuYDnOji9DMSvyT1FBD2WpZ8IHNhR0RrAecC0wIvDGtgQOBV4VxL1oY+3Bu5Lv/d+IGbmrwY+Pdbc+r4ERiOgoI9GqHmfK+jNy6kRSUACBQko6AVBWUwCEqiUQA6CftNNN5US9Pe/P3z3Dc8EYN8+CXrsPz8XmAZ4aVgbsS/9FWDtUdpeCbgEWAC4q9LBYeONJ6CgNz7FbwhQQW9fzo1YAhJIBBR0h4IEJJADgRwE/cYbbywl6IsvvnikoF8z6N0scY+T3O9Os+JnjzIupgOeT/vYhw6by2Eo2ccMCSjoGSZtjF1W0McI0NclIIF8CSjo+ebOnkugTQRyEPQbbrihlKB/4AMfiFT2aw96LEWPJe0T19GnJ5awzzLCIXExY/9lYG7g1VHGV5wkfwUQ3y7c1KaxaKyDJ6CgD5551S0q6FVnwPYlIIHKCCjolaG3YQlIoAsCCvr/wZo+LSuP37ge2BW4FHgKuD/tNZ8T+Hx6I65Zuxk4GjgBiKXpRw67Zi2KTgHcA/wMGD8sNfMDmwLnA08CsSb/cODBEe5G7yKrFpVAMQIKejFOTSqloDcpm8YiAQl0RUBB7wqXhSUggYoI5CDo119/fakZ9A9+8INBtegM+opJyIdn4mRgC+AkYB4gyg09cZ/5YcDCSarj9PUo1/l8Mt2LvmC677zzs5hRPwWI4+ZjafsDwK+A/b0HvaI/EC1rVkFvWcIBBb19OTdiCUggEVDQHQoSkEAOBHIQ9Ouuu66UoC+xxBLdCHoO6bKPEugpAQW9pzizqExBzyJNdlICEugHAQW9H1StUwIS6DWBXAR9+uljBXrx5/nnn0dBL87Lku0koKC3L+8KevtybsQSkEAioKA7FCQggRwI5CDo1157LWUEfckll4wUFF3inkO67KMEekpAQe8pziwqU9CzSJOdlIAE+kFAQe8HVeuUgAR6TSAHQf/LX/5SStA/9KEPKei9HjDW1ygCCnqj0lkoGAW9ECYLSUACTSSgoDcxq8YkgeYRUNCbl1MjkkBRAgp6UVLNKaegNyeXRiIBCXRJQEHvEpjFJSCBSgjkIOjXXHNNqRn0D3/4w86gVzKqbDQXAgp6/TI1AxDXQawHvCPd+bgTcM0IXf0hsDWwC3BEwVAU9IKgLCYBCTSPgILevJwakQSaSCAHQb/66qtLCfpHPvIRBb2Jg9aYekZAQe8Zyp5VdHq6d3Fb4GFgsyTgcZfjQx2trAvsC8wKHKKg94y/FUlAAg0moKA3OLmGJoEGEchB0K+66qpSgr7UUksp6A0aq4bSewIKeu+ZjqXGaYDngHWA8zoquha4APh6+r05gauAVVO5mD13Bn0s5H1XAhJoBQEFvRVpNkgJZE8gB0H/85//XErQl156aQU9+xFqAP0koKD3k273dcfy9meBVYBLOl6/AngVWBGYArgYOBv4LnBvknMFvXveviEBCbSMgILesoQbrgQyJZCDoP/pT38qJegf/ehHFfRMx6XdHgwBBX0wnLtp5UrgFWBT4DFgE+Bk4E5gQWBP4ONp9vz1AoI+DohfQ098CfDg+PHjGTeu87e76aJlJSABCeRJQEHPM2/2WgJtI6Cgty3jxiuB/09AQa/faJgfOAFYHngNuA64HVgC+Fxa0h7/P/anxzPaDHrsU99neJgKev0Sb48kIIH+E1DQ+8/YFiQggbETyEHQr7zyylIz6Msss0wAmjGtGh07LGuQQMMIKOj1Teh0QJy4/ggQB8dND/wWOAz4T0e3p0z//QAwzwjhOINe3xzbMwlIYMAEFPQBA7c5CUigFIEcBP2Pf/xjKUFfdtllFfRSo8KX2kJAQa9/pmcG7gF2B84EZh/W5YuAnwAnArcVCMdr1gpAsogEJNBMAgp6M/NqVBJoGoEcBP2KK64oJejLLbecgt60AWs8PSWgoPcUZ08qi5PZIy8h2wukK9ReBuKn2b9HaGG0Je7DX1HQe5ImK5GABHIkoKDnmDX7LIH2EchB0P/whz+UEvSPfexjCnr7hrQRd0FAQe8C1oCKbggcCMwFPJVmzfcGnplE+wr6gBJjMxKQQP4EFPT8c2gEEmgDgRwE/fLLLy8l6MsvH8csuQe9DePYGMsRUNDLccv5LWfQc86efZeABMZEQEEfEz5floAEBkRAQR8QaJuRQA0JKOg1TEqfu6Sg9xmw1UtAAvUloKDXNzf2TAIS+P8EchD03//+96Vm0FdYYQVn0B3sEpgMAQW9fcNDQW9fzo1YAhJIBBR0h4IEJJADgRwE/bLLLisl6CuuuKKCnsMgtI+VEVDQK0NfWcMKemXobVgCEqiagIJedQZsXwISKEIgB0G/9NJLSwn6xz/+cQW9yCCwTGsJKOjtS72C3r6cG7EEJOAMumNAAhLIiEAOgv673/2ulKCvtNJKCnpGY9GuDp6Agj545lW3qKBXnQHbl4AEKiPgDHpl6G1YAhLogkAOgn7JJZeUEvSVV15ZQe9iLFi0fQQU9PblXEFvX86NWAIScAbdMSABCWREQEHPKFl2VQI9JqCg9xhoBtUp6BkkyS5KQAL9IeAMen+4WqsEJNBbArkI+nTTTddV4P/6179wBr0rZBZuIQEFvX1JV9Dbl3MjloAEnEF3DEhAAhkRyEHQL774YsoI+iqrrBKZmBF4NqOU2FUJDIyAgj4w1LVpSEGvTSrsiAQkMGgCzqAPmrjtSUACZQjkIOi//e1vSwn6Jz7xCQW9zKDwndYQUNBbk+r/C1RBb1/OjVgCEnAG3TEgAQlkRCAHQf/Nb35TStA/+clPKugZjUW7OngCCvrgmVfdooJedQZsXwISqIyAM+iVobdhCUigCwI5CPpFF11UStBXXXVVBb2LsWDR9hFQ0NuXcwW9fTk3YglIwBl0x4AEJJARAQX9/5K1PLAbsCQwO7AecNYoqVwROAxYBHgA2B84qeOdfYF9htVxG7BQx+9NDRwKbAyMAy4CtgMey2gY2dVMCSjomSZuDN1W0McAz1clIIG8CTiDnnf+7L0E2kIgB0G/8MILS82gr7baapHGoofErQ4sC1wHnFlA0OcF/gb8ADgOiEvXjwDWTJIdbYegrw9MPK0uPa8C/+j472PSO1sAzwBHA/9JfWnLMDTOiggo6BWBr7BZBb1C+DYtAQlUS0BBr5a/rUtAAsUI5CDoF1xwQSlBX331cO7Cgt4J7PUCgn5wEutFO148DZgJmPjNQBL0dYEPTCIb8eXBE8CmwC9SmZhdvwX4KPDnYlm0lATKEVDQy3HL+S0FPefs2XcJSGBMBBT0MeHzZQlIYEAEchD0888/v5Sgr7HGGv0U9MvTbPvOHanaMs2ih3gPCXosm4+Z8ZeAPwF7Avenz1cCLgFmBp7uqOe+VM/hAxoGNtNSAgp6+xKvoLcv50YsAQkM/ats31jZ6CMBCUig3gRyEPTzzjuvlKCvuWasNmcu4LmOLLwMxK/JPUVm0G8HTgQO7KgovhE4D5gWeBGIKfzpgdh3HvvaYz/6nEDMukefYuY86oi9553P1cClwB71Hj32LncCCnruGey+/wp698x8QwISaAgBZ9AbkkjDkEDDCeQg6Oeee24pQV9rrbVGyt6EtPS8H4Ie3wicC0yTZsyHtxHL32N2fFfg+MkI+jVpZn18w4ef4VVMQEGvOAEVNK+gVwDdJiUggXoQUNDrkQd7IQEJTJ5ACwS9XzPoRZa4jwQ/5PvitNTdJe7+Aa2UgIJeKf5KGlfQK8FuoxKQQB0IKOh1yIJ9kIAERiOQg6Cfc845pWbQ11577Qi/6CnunaiKLHGPQ+JiSftiHS+eCszScUjccPyx3D32n8ceqCNT3+KQuE3SyfFR/r1pSbyHxI02eP18zAQU9DEjzK4CBT27lNlhCUigVwQU9F6RtB4JSKCfBHIQ9F//+telBP1Tn/pUN4Ie8rxAYn19WoYe+8CfSlIde81j//jnU5m4Zu3mdC3aCUDMhod0d16z9h3gnLSsfQ4gltfHie4Lp9Pbo6q4Zi1EP65ZexY4KtW/TD/zbt0SCAIKevvGgYLevpwbsQQkkAgo6A4FCUggBwI5CPrZZ59dStDXWWedbgR9xXQw2/C0nZzk+SRgHiDKDT0fBw5Lwv0gsB8Q5YaeuHZteeBtScivAPYG7uooMzVwaJpFj8PiLgK2Ax7NYfzYx7wJKOh5569M7xX0MtR8RwISaAQBBb0RaTQICTSeQA6CftZZZ5US9HXXjSvISy1xb3zeDVACQUBBb984UNDbl3MjloAEEgEF3aEgAQnkQEBBzyFL9lEC/SGgoPeHa51rVdDrnB37JgEJ9JWAgt5XvFYuAQn0iEAOgv6rX/2q1Az6euut5wx6j8aJ1TSTgILezLxOLioFvX05N2IJSMAZdMeABCSQEYEcBP2Xv/xlKUH/9Kc/raBnNBbt6uAJKOiDZ151iwp61RmwfQlIoDICzqBXht6GJSCBLgjkIOhnnnlmKUH/zGc+o6B3MRYs2j4CCnr7cq6gty/nRiwBCTiD7hiQgAQyIpCDoP/iF78oJejrr7++gp7RWLSrgyegoA+eedUtKuhVZ8D2JSCBygg4g14ZehuWgAS6IJCLoE877bRdRAUvvPACCnpXyCzcQgIKevuSrqC3L+dGLAEJOIPuGJCABDIioKBnlCy7KoEeE1DQeww0g+oU9AySZBclIIH+EHAGvT9crVUCEugtgRwE/ec//zllZtA32GCDgDUj8GxvqVmbBJpBQEFvRh67iUJB74aWZSUggUYRUNAblU6DkUBjCeQg6GeccUYpQd9www0V9MaOXAPrBQEFvRcU86pDQc8rX/ZWAhLoIQEFvYcwrUoCEugbgRwE/fTTTy8l6BtttJGC3reRY8VNIKCgNyGL3cWgoHfHy9ISkECDCCjoDUqmoUigwQRyEPTTTjutlKBvvPHGCnqDx66hjZ2Agj52hrnVoKDnljH7KwEJ9IyAgt4zlFYkAQn0kUAOgv6zn/2slKBvsskmCnofx45V509AQc8/h91GoKB3S8zyEpBAYwgo6I1JpYFIoNEEFPRGp9fgJDBZAgp6+waIgt6+nBuxBCSQCCjoDgUJSCAHAjkI+qmnnlpqBn3TTTd1Bj2HQWgfKyOgoFeGfpINzwDsB6wHvAO4HtgJuGbo35dAbN6ZG3gFuBbYG7iqYCgKekFQFpOABJpHQEFvXk6NSAJNJJCDoP/0pz8tJeif/exnFfQmDlpj6hkBBb1nKHtW0enAosC2wMPAZsAuwMLAQ0B87fg4cDcwTfosLpRcAHiiQC8U9AKQLCIBCTSTgILezLwalQSaRiAHQT/llFNKCfpmm8U/bb0HvWlj1nh6R0BB7x3LXtQUwv0csA5wXkeFMUt+AfD1ERqZKNzAKsAlBTqhoBeAZBEJSKCZBBT0ZubVqCTQNAI5CPpPfvKTUoL+uc99TkFv2oA1np4SUNB7inPMlcXy9mdHkO0rgFeBFYe1MBWwYxL3mEH/R1keib8AACAASURBVIEeKOgFIFlEAhJoJgEFvZl5NSoJNI1ADoL+4x//uJSgf/7zn1fQmzZgjaenBBT0nuLsSWVXpr3lsZT9MSDuojgZuBNYMLWwFnAaMC3wCLBuxx714Z0YB8SvoSe+BHhw/PjxjBvX+ds96XttK9nt4IOZ9qWXeGHqqTlkjz1q2087JgEJ9JeAgt5fvtYuAQn0hoCC3huO1iKBHAko6PXL2vzACcDywGvAdcDtwBJpH3r0eDpgduDtwFbASsBSaW/68Ij2BfYZ/pttE/R9JkwgBvvrwIR93oCjfqPAHklAAn0hoKD3BauVSkACPSaQg6CffPLJpWbQN99886A1Y1o12mNyVieB/Ako6PXNYUh4LEePGfI4OG56YM1JdPeOJPUHjvC5M+iAM+j1Hej2TAKDJKCgD5K2bUlAAmUJ5CDoJ510UilB32KLLRT0sgPD91pBQEGvf5pnBu4Bdgd+NInu3gX8BIjZ8tEe96CPRsjPJSCBxhJQ0BubWgOTQKMI5CDoJ554YilB33LLLRX0Ro1Wg+k1AQW910THXt+qMHE19m3p6rRDgJeB5YA4FC7uPP91mlmPJe7bp6vXlgRuLtC8gl4AkkUkIIFmElDQm5lXo5JA0wjkIOgnnHBCKUH/whe+oKA3bcAaT08JKOg9xdmTyjYEYqn6XMBTwJlJyuMqtamBU9N+85DzJ9PhcPtP5pC44Z1S0HuSJiuRgARyJKCg55g1+yyB9hHIQdCPP/74UoL+xS9+UUFv35A24i4IKOhdwGpIUQW9IYk0DAlIoHsCCnr3zHxDAhIYPAEFffDMbVECdSGgoNclE4Prh4I+ONa2JAEJ1IyAgl6zhNgdCUhgRAI5CPpxxx1Xagb9S1/6kjPojnsJTIaAgt6+4aGgty/nRiwBCSQCCrpDQQISyIFADoJ+7LHHlhL0rbaKG4K9Zi2HcWgfqyGgoFfDvcpWFfQq6du2BCRQKQEFvVL8Ni4BCRQkkIOg/+hHPyol6FtvvbWCXnAcWKydBBT09uVdQW9fzo1YAhJwBt0xIAEJZEQgF0GfZpppuqL64osv0qWgLw/sBsRtRbMD6wFnjdLoisBhwCLAA0AcpnxSxzt7Ap8GFgJeBK4E9kg3KA0VuwxYYVg7PwS26SpgC0ugBAEFvQS0zF9R0DNPoN2XgATKE3AGvTw735SABAZHIAdB/+EPf0gZQf/yl78cIGcEni1AdHVgWeC6dLPRaII+L/A34AfAccDKwBHAmsBFqb0LgdPSDUhvBg4AFgUWBv6VyoSg3w58s6OPLxTsc4GwLCKBSRNQ0Ns3OhT09uXciCUggURAQXcoSEACORBQ0EfM0usFZtAPTjIewj30hIzPBKw2idzPCjyeZswv7xD0G4Cdcxgv9rFZBBT0ZuWzSDQKehFKlpGABBpJQEFvZFoNSgKNI5CDoP/gBz8oNYO+zTYTV4kXnUHvzG0RQQ/Bjtn2TrHeMs2iR5sjPQsAdwCLpdn3KBMz6LFEPlzpUeAcYD8gZtF9JNBXAgp6X/HWsnIFvZZpsVMSkMAgCCjog6BsGxKQwFgJ5CDoxxxzTClB33bbbQPPXMBzHZxeBuLX5J4igh7L0k8EDuyoaA3gPGDatOe8s40pgF+nGfblOj6Ik+zuAx4G3g/EzPzVae/6WNPr+xKYLAEFvX0DREFvX86NWAISSAQUdIeCBCSQA4EcBP373/9+KUHfbrvtRkrBBGDfPgl67D8/F4gT7V4a1sYxQOxzDzl/cDLtrwRcAsRs+105jCH7mC8BBT3f3JXtuYJelpzvSUAC2RNQ0LNPoQFIoBUEchD0733ve6UEffvtt48c9msGvZsl7kcD6wBxUvw9owys6YDn0z72ocPmWjEWDXLwBBT0wTOvukUFveoM2L4EJFAZAQW9MvQ2LAEJdEEgB0E/+uijSwn6V77ylSDRrz3osRQ9lrTHfvKh51Rglo5D4sJ/jkoHzsWVbLH/fLQnTpK/AlgcuGm0wn4ugbEQUNDHQi/PdxX0PPNmryUggR4QUNB7ANEqJCCBvhNQ0P8P8fRpWXn8xvXArsClwFPA/Wmv+ZzA59Mbcc3azUDMjp8AxNL0I4dds/Z9YNM0e35bRzKfSXvU50+fnw88mfagH56WwA+/G73vY8EG2kdAQW9fzhX09uXciCUggURAQXcoSEACORDIQdCPOuqoUjPoO+ywQ6Sg6Ax6zHCHkA9/Tga2AE4C5gGi3NDzceCwdK957CuP09ej3NATh82N9MRp71FubuCUdDd6LG1/APgVsL/3oOfwpyf/Piro+eew2wgU9G6JWV4CEmgMAQW9Mak0EAk0mkAOgn7kkUeWEvQdd9yxG0FvdJ4NTgIjEVDQ2zcuFPT25dyIJSCBREBBdyhIQAI5EMhB0L/73e+WEvSddtpJQc9hENrHyggo6JWhr6xhBb0y9DYsAQlUTUBBrzoDti8BCRQhkIOgH3HEEaUEfeedd1bQiwwCy7SWgILevtQr6O3LuRFLQALOoDsGJCCBjAjkIOiHH354KUHfZZddFPSMxqJdHTwBBX3wzKtuUUGvOgO2LwEJVEbAGfTK0NuwBCTQBQEFvQtYFpVAwwgo6A1LaIFwFPQCkCwiAQk0k4CC3sy8GpUEmkYgB0E/7LDDSs2g77pr3JRW+BT3pqXWeCQwKgEFfVREjSugoDcupQYkAQkUJaCgFyVlOQlIoEoCOQj6oYceWkrQv/rVryroVQ4u2649AQW99inqeQcV9J4jtUIJSCAXAgp6LpmynxJoN4EcBP073/lOKUH/2te+pqC3e3gb/SgEFPT2DREFvX05N2IJSCARUNAdChKQQA4EchD0Qw45pJSg77bbbgp6DoPQPlZGQEGvDH1lDSvolaG3YQlIoGoCCnrVGbB9CUigCIEcBP3b3/52KUHffffdFfQig8AyrSWgoLcv9Qp6+3JuxBKQgDPojgEJSCAjAgp6RsmyqxLoMQEFvcdAM6hOQc8gSXZRAhLoDwFn0PvD1VolIIHeEshB0A8++OBSM+h77LGHM+i9HS7W1jACCnrDElogHAW9ACSLSEACzSSgoDczr0YlgaYRyEXQp5566q7Qv/TSSyjoXSGzcAsJKOjtS7qC3r6cG7EEJJAIKOgOBQlIIAcCOQj6QQcdRBlBHz9+vDPoOQxC+1gZAQW9MvSVNaygV4behiUggaoJKOhVZ8D2JSCBIgRyEPQDDzywlKDvueeeCnqRQWCZ1hJQ0NuXegW9fTk3YglIwBl0x4AEJJARgRwE/YADDigl6HvttZeCntFYtKuDJ6CgD5551S0q6FVnwPYlIIHKCDiDXhl6G5aABLogoKB3AcuiEmgYAQW9YQktEI6CXgCSRSQggWYSUNCbmVejkkDTCOQg6N/61rdKzaDvvffezqA3bcAaT08JKOg9xZlFZQp6FmmykxKQQD8IKOj9oGqdEpBArwnkIOj7779/KUH/+te/rqD3esBYX6MIKOiNSmehYBT0QpgsJAEJNJGAgt7ErBqTBJpHIAdB32+//UoJ+je+8Q0FvXlD1oh6SEBB7yHMTKpS0DNJlN2UgAR6T0BB7z1Ta5SABHpPIAdB/5//+Z9Sgv7Nb35TQe/9kLHGBhFQ0BuUzIKhKOgFQVlMAhJoHgEFvXk5NSIJNJFADoI+YcKEUoK+zz77KOhNHLTG1DMCCnrPUGZTkYKeTarsqAQk0GsCCnqviVqfBCTQDwIKej+oWqcE8iCgoNcvTzMA+wHrAe8Argd2Aq4B3gLsD6wBzAc8A1wMjAceLhiKgl4QlMUkIIHmEVDQm5dTI5JAEwnkIOjx83TqqafuCv9LL71E+jk8I/BsVy9bWAItIaCg1y/RpwOLAtsm6d4M2AVYGHge+AVwLHAjMDPwXWBK4EMFQ1HQC4KymAQk0DwCCnrzcmpEEmgigRwEPZaqlxH0WBoPKOhNHLjG1BMCCnpPMPaskmmA54B1gPM6ar0WuACYeC/FsOfDwNXAu4H7C/REQS8AySISkEAzCSjozcyrUUmgaQRyEPQ47K2MoMfhcgp600as8fSSgILeS5pjryuWt8dyn1WASzqquwJ4FVhxhCai7G+AmQouFVLQx54na5CABDIloKBnmji7LYGWEchB0OO6tDKCHtezNVzQY3vq6wWG7BIFylikhQQU9Pol/UrgFWBT4DFgE+Bk4E5gwWHdjY0/fwRuBT47iVDGAfFr6IkvAR4cP34848Z1/nb9QNij/yXwzQkTiD+o8ZP+f/735NNsnpz7ng3kYR3d7eCDmfall3hh6qk5ZI89sgpjEONFQc9qSNhZCbSWQA6C/vWvf72UoO+/fxyn1Ogl7p3/WIt/wu0J/AB4atiAnrjW30cCwwko6PUbE/MDJwDLA68B1wG3A/EtW+xDH3riwLgzgbnSzPqkDtrYF3iD1Sno9Uv8pHq0T4egT8hM0HPuez4j5L97mjPzQfRdQc91ZNtvCbSLgILeqHzH9tXFgbsbFZXB9I2Agt43tGOueDoglqM/AsTBcdMDa6ZaQ87PSCe5rwQ8OZnWnEEfcyqqrWAQs4r9ijDnvveLSb/rdQZ98oQV9H6PQOuXgAR6QSAHQd97771LzaB/61vfCkRFD4mLCavdgCWB2dMtR2eNwji2hB4GLAI8kG5AOmnYO9unemdLBy/vkM50GioWq1QPBTZOK1EvArZLq1u7TbGC3i2xlpdX0Mc+AOIPfMx4Xz72qkasIU5qvwfYHfhRumot5Pw9wMeBJ7ps1z3oXQKzuAQk0BwCCnpzcmkkEmgygRwEfa+99iol6AcccEA3gr46sGxaURorR+Ma4skJ+rzA39KS8uOAlYEj0iRXSHY8GwE/BrYBrgJ2BjZIW0kfT2WOSe9ska41Phr4T+pLt0NPQe+WWMvLK+hjHwBnA6ulE9RPTPvFHxpDtavCxC3HtwELAIcALwPLpW3I8cMplruvNexbvNjXEnvXR3sU9NEI+bkEJNBYAgp6Y1NrYBJoFIEcBH3PPfcsJegHHnhgN4Lemdc4jmc0QT84iXVcWTz0nJYOU45/r8cTUn4N8JX031OkmfajgIPS7H5MgMV5UHG9cTwLAbcAHwX+3OVgU9C7BNb24gp6b0bArMDngM3TPvGLgeOBkPd/d9nEhkD85Iq95SHdIeR7p2/v5kmz6SNVGbPplxVoS0EvAMkiEpBAMwko6M3Mq1FJoGkEchD0OM+ozCnuBx0UDjzx37khrkNPTEbFr8k9RQQ9VrTG+U0xKz70bJlm0WNZ/VTAC8D6w2bi40DmuBEprjqO7aNxm1KsYn26o577Uj2Hj9LPHYd9Hl8axITbP4b9/pFNG7fG0xsCCnpvOHbWErPb8YPgS8DzwCnA94E7et9UqRoV9FLYfEkCEmgCAQW9CVk0Bgk0n0Augt7tjUAvv/wySdCHJzFONI+Djccq6HGwcqxonThNn541gPOAaZN0x0rXZYA/dZT5NrACsFSaOY86hl93dDVwKTDaFSmxNXW0J75smG+0Qn7eTgIKem/zHodXfB74AjBnmv2O/40/8LGHfLRv3Hrbm5FrU9AHQdk2JCCBWhJQ0GuZFjslAQkMI9ACQe/XDPpIgh6HLJ8LTAPMAowk6DHD/TFg6ckIeiyLj5n18Q5YCfSTgII+drpxovqn0qz5J4GbgDiU4qcdS3fiLvOYRY+lMlU/CnrVGbB9CUigMgIKemXobVgCEuiCQA6Cvscee1BmBv3gg2PFd+FT3Dup5bLEPZbIx6FyIfvDr0GOZfZXpgPq/tDFkLBoiwgo6GNPduwnicMlfgYcC9wwQpUh5rEfJk6WrPpR0KvOgO1LQAKVEVDQK0NvwxKQQBcEchD03XffvZSgf/vbsZq8b4Ie9h9L2hfrwH1qmjnvPCQulqvH1WrxxL/j709S3XlIXEywxVlQ8bw3HeBc5JC4X6el8JNaORt71OPsqDjwzkcCbyCgoI99UMThcD8HXhp7VQOpQUEfCGYbkYAE6khAQa9jVuyTBCQwnEAOgr7bbruVEvRDDonV5IUFffp0q1G8cz2wa5LfOEg5pDr2msd20thiGk9Mht2cZDuuQY7Z7DiMLZa5D79mbet093kcKBeHNMdJ7Y+leuKatRD9uGYtZsHjhPd4Yu/6aE8cJhdfBsSp7yM90c5vgHeNVpGft5OAgt6+vCvo7cu5EUtAAomAgu5QkIAEciCQg6B/7WtfKyXo3/nOd7oR9BWTkA9PW5y6HvJ8EhC3HEW5oSdmpw9LNys9COyXynXWEVes7QbMlla/xqx2XL829EwNHArELHocFhdyvx3waIHxE5N2cc3bnZMoG9co/zXtiS9QnUXaRkBBb1vGQUFvX86NWAISUNAdAxKQQEYEFPSMkvXGrt4FfA341SSi+DQQ31J4invWae5f5xX0/rGta80Kel0zY78kIIG+E3AGve+IbUACEugBgRwE/atf/WqpGfRDD42J6cJL3HtAc+BVxHL4mNH/8AhbYOMk+aHr2obflz7wjtpgPQko6PXMSz97paD3k651S0ACtSagoNc6PXZOAhJIBHIQ9F133bWUoB92WKw+b7SgvzMdDv1a2gt/GxAn0L8P2B6YEliiY7+7414C/0VAQW/fgFDQ25dzI5aABBIBBd2hIAEJ5EAgB0HfZZddSgn64YdPPNw8rhsbfgVZDqkp2sd3A3HQ3KrAkG+FpA/tZb+3aEWWax8BBb19OVfQ25dzI5aABBR0x4AEJJARgRwEfeeddy4l6EcccUQbBH1otMVVy3EoXDjXHcA/MxqGdrUiAgp6ReArbFZBrxC+TUtAAtUScAa9Wv62LgEJFCOQg6DvtNNOpQT9u9/9bpsEvVjCLSWBDgIKevuGg4LevpwbsQQk4Ay6Y0ACEsiIgIKeUbLsqgR6TEBB7zHQDKpT0DNIkl2UgAT6Q8AZ9P5wtVYJSKC3BHIQ9B133LHUDPqRRx7pDHpvh4u1NYyAgt6whBYIR0EvAMkiEpBAMwko6M3Mq1FJoGkEchD0HXbYoZSgH3VU3ELW+EPimjYkjWeABBT0AcKuSVMKek0SYTckIIHBE1DQB8/cFiUgge4J5CDoX/nKV0oJ+tFHH62gdz8kfKNFBBT0FiU7haqgty/nRiwBCSQCCrpDQQISyIFADoK+/fbblxL0733vewp6DoPQPlZGQEGvDH1lDSvolaG3YQlIQALlCfjlQnl2vimB3AjkIOjbbbddKUH//ve/r6DnNiDt70AJKOgDxV2LxhT0WqTBTkhAAhLojoCC3h0vS0sgZwIKes7Zs+8SGBsBBX1s/HJ8W0HPMWv2WQISaD0BBb31Q0AALSKQg6Bvu+22pWbQjznmGGfQWzSWDbV7Agp698xyf0NBzz2D9l8CEmglAQW9lWk36JYSyEHQt9lmm1KC/oMf/EBBb+m4NuxiBBT0YpyaVEpBb1I2jUUCEmgNAQW9Nak2UAmQg6B/+ctfLiXoP/zhDxV0x7gEJkNAQW/f8FDQ25dzI5aABBpAQEFvQBINQQIFCeQi6FNNNVXBiP632CuvvIKC3hUyC7eQgILevqQr6O3LuRFLQAINIKCgNyCJhiCBggRyEPStt96aMoL+ox/9yBn0guPAYu0koKC3L+8KevtybsQSkEADCCjoDUiiIUigIAEFvSAoi0mggQQU9AYmdZSQFPT25dyIJSCBBhBQ0BuQREOQQEECOQj6VlttVWoG/dhjj3UGveA4sFg7CSjo7cu7gt6+nBuxBCTQAAIKegOSaAgSKEggB0H/0pe+VErQjzvuOAW94DiwWDsJKOjty7uC3r6cG7EEJNAAAgp6A5JoCBIoSCAHQf/iF79YStCPP/54Bb3gOLBYOwko6O3Lu4LevpwbsQQk0AACCnoDkmgIEihIIAdB/8IXvlBK0E844QQFveA4sFg7CSjo7cu7gt6+nBuxBCTQAAIKegOSaAgSKEggB0HfcsstSwn6iSeeqKAXHAcWaycBBb19eVfQ25dzI5aABBpAQEFvQBINQQIFCSjoBUFZTAINJKCgNzCpo4SkoLcv50YsAQk0gICC3oAkGoIEChLIQdC32GKLUjPoJ510kjPoBceBxdpJQEFvX94V9Pbl3IglIIEGEFDQG5BEQ5BAQQI5CPrmm29eStBPPvlkBb3gOLBYOwko6O3Lu4LevpwbsQQk0AACCnoDkmgIEihIIAdB//znP19K0H/84x8r6AXHgcXaSUBBb1/eFfT25dyIJSCBBhBQ0BuQREOQQEECOQj65z73uVKC/pOf/KSMoG8P7AbMBtwI7ABcPQmcbwH2BDYH5gRuA/YALuwofy/w7hHe/z4QbcVzGbDCsDI/BLYpmEaLSaAUAQW9FLasX1LQs06fnZeABNpKQEFva+aNu40EchD0zTbbrJSgn3LKKd0K+kZATLuHGF8F7AxsACwIPD7C+DgY2AzYCrgVWBU4DFgGuD6VnxWYsuPdRYHfAh9PYj4k6LcD3+wo9wLwbBvHpDEPjoCCPjjWdWlJQa9LJuyHBCQggS4IKOhdwLKoBDInoKD/VwJDyq8BvpJ+dwrgAeAo4KARUv0w8C3gex2fnQm8mMR9pNFxBLAW8B7g9VQgZtBvSF8IZD6i7H5OBBT0emVrBmA/YD3gHelbvp3SD6Xo6aeBLwNLAm8DPph+cHQThYLeDS3LSkACEqgJAQW9JomwGxIYAIEcBP2zn/1sqRn0n/70p0FwxoIz0VMBMWu9PnBWB/o4aW4mYJ0R0vEksDtwfMdnMW2/HDDPCOWjjZD6mGU/oOPzEPRFgPClR4Fz0r/Toz8+EugbAQW9b2hLVXw6EEtstk0/KGJ5zi7AwsBDwOeAedNnxyropRj7kgQkIIEsCSjoWabNTkugFIEcBH3TTTctJeinnnpqMJkLeK4DzstA/Br+zJH+DRzL0//U8eG30/7wpUZ4JxpYHFgXuAtYGTg7LWkfN0L5DYF4513p39hDRbYG7ku/934gls7HvveYMPORQN8IKOh9Q9t1xdOkH1TxTeB5HW9fC1wAfL3j9+Lbv3sU9K4Z+4IEJCCBbAko6Nmmzo5LoGsCOQj6JptsUkrQf/azn43EYwKwbxeCfgjwMWDpEd6J/eUxkbV2Wq4ekn4xsCUw7QjlLwJeSeUnl6uVgEuABZL4d51XX5BAEQIKehFKgykTy9vj0IlV0h/+oVavAF4FViwp6PFNYee3hdHOg+PHj2fcuJG+RBxMsLYiAQlIQALdEVDQu+NlaQnkTCAHQd94441LCfppp50WqSk6g15miftQ6qdOW0Jj+XrsVY895rFkvfOJk9zvTrPiMcs+uWc64HlgNSCk3kcCfSGgoPcFa+lKr0zf4G0KPAZsAsQemzvTSZVDFXczgx7fRu4zvEcKeukc+aIEJCCBSggo6JVgt1EJVEIgB0HfaKONSgn66afHjs7Ce9CjbBwSF0vL42q1eOKQuPuBoydxSNzwnMW1a7cAZwB7Dfsw/p0c5zvNnSbEJpfvZYGYOIvl8zdVMjBstBUEFPR6pXl+4ARgeeA14DogrndYIu1DLyPozqDXK8f2RgISkEApAgp6KWy+JIEsCSjo/5W2oWvWYk94iHpcsxb7xhdKE1pxBVuc1RR3n8cT+9Lj/vM4gT3+NyQ8znCKf08/3VFziH5sGY019+OHDZT4N3lMmJ0PxKFzsQf98FiFOsLd6FmOMTtdXwIKej1zE0to4rT1R4D4mnF6YM2OrnYzgz48Qk9xr2fO7ZUEJCCByRJQ0B0gEmgPgRwEfcMNNyw1g37GGTGR3dUMepSPK9Z2A2ZL4r1jmlmPz+K09XuBLdIIWQE4BpgvLUkPyQ4Bj6Xunc8n01L1uE89JsQ6n5hRj5Pf4/Dm+Hd5XOv2K2D/gqfPt2ewGmnPCSjoPUfa0wpnTt/sxVURP1LQe8rWyiQgAQlkRUBBzypddlYCYyKQi6C/5S2xerz48+9//5uSgl68EUtKIHMCCnq9ErhqumvxtnRCZJxQGVdOxL2N/wZmSVdAxJUTcdL7xkCUjbsZ41eRxxn0IpQsIwEJSKBmBBT0miXE7kigjwRyEPQNNtiAMoL+85//PMgVvQe9j5StWgL1JKCg1ysvsZ/mwHSy5VPAmcDewDOpm7F058QRujypqylGik5Br1fO7Y0EJCCBQgQU9EKYLCSBRhDIQdDXX3/9UoL+i1/8QkFvxCg1iH4RUND7Rba+9Sro9c2NPZOABCQwSQIKuoNDAu0hkIOgf+Yznykl6GeeGfNPzqC3ZzQbabcEFPRuieVfXkHPP4dGIAEJtJCAgt7CpBtyawko6K1NvYFLAAW9fYNAQW9fzo1YAhJoAAEFvQFJNAQJFCSQg6B/+tOfLjWD/stf/tIZ9ILjwGLtJKCgty/vCnr7cm7EEpBAAwgo6A1IoiFIoCCBHAR9vfXWKyXov/pV3FbmEveCQ8FiLSSgoLcv6Qp6+3JuxBKQQAMIKOgNSKIhSKAggRwEfd111y0l6GeddZaCXnAcWKydBBT09uVdQW9fzo1YAhJoAAEFvQFJNAQJFCSQg6Cvs846pQT97LPPVtALjgOLtZOAgt6+vCvo7cu5EUtAAg0goKA3IImGIIGCBHIQ9E996lOlBP3Xv/61gl5wHFisnQQU9PblXUFvX86NWAISaAABBb0BSTQECRQkoKAXBGUxCTSQgILewKSOEpKC3r6cG7EEJNAAAgp6A5JoCBIoSCAHQV977bVLzaCfc845zqAXHAcWaycBBb19eVfQ25dzI5aABBpAQEFvQBINQQIFCeQg6GuttVYpQT/33HMV9ILjwGLtJKCgty/vCnr7cm7EEpBAAwgo6A1IoiFIoCCBHAR9zTXXLCXo5513noJecBxYrJ0EFPT25V1Bb1/OjVgCEmgAAQW9AUk0BAkUJJCDoK+xxhqlBP38889X0AuOA4u1k4CC3r68K+jty7kRS0ACDSCgoDcgiYYggYIE1oQ1hAAAIABJREFUchD01VdfvZSgX3DBBQp6wXFgsXYSUNDbl3cFvX05N2IJSKABBBT0BiTRECRQkICCXhCUxSTQQAIKegOTOkpICnr7cm7EEpBAAwgo6A1IoiFIoCCBHAR9tdVWKzWDfuGFFzqDXnAcWKydBBT09uVdQW9fzo1YAhJoAAEFvQFJNAQJFCSQg6CvuuqqpQT9oosuUtALjgOLtZOAgt6+vCvo7cu5EUtAAg0goKA3IImGIIGCBHIQ9E9+8pOlBP03v/mNgl5wHFisnQQU9PblXUFvX86NWAISaAABBb0BSTQECRQkkIOgf+ITnygl6L/97W8V9ILjwGLtJKCgty/vCnr7cm7EEpBAAwgo6A1IoiFIoCCBHAR9lVVWKSXoF198sYJecBxYrJ0EFPT25V1Bb1/OjVgCEmgAAQW9AUk0BAkUJKCgFwRlMQk0kICC3sCkjhKSgt6+nBuxBCTQAAIKegOSaAgSKEggF0F/85vfXDCi/y326quv4gx6V8gs3EICCnr7kq6gty/nRiwBCTSAgILegCQaggQKEshB0FdeeWXKCPoll1wSFGYEni2Iw2ISaBUBBb1V6Z4YrILevpwbsQQk0AACCnoDkmgIEihIIAdBX2mllUoJ+u9+9zsFveA4sFg7CSjo7cu7gt6+nBuxBCTQAAIKegOSaAgSKEggB0H/+Mc/XkrQL730UgW94DiwWDsJKOjty7uC3r6cG7EEJNAAAgp6A5JoCBIoSCAHQV9xxRVLCfpll12moBccBxZrJwEFvX15V9Dbl3MjloAEGkBAQW9AEg1BAgUJKOgFQVlMAg0koKA3MKmjhKSgty/nRiwBCTSAgILegCQaggQKEshB0FdYYYVSM+i///3vy8ygbw/sBswG3AjsAFw9CZxvAfYENgfmBG4D9gAu7Ci/L7DPsPej3EIdvzc1cCiwMTAOuAjYDnisYBotJoFSBBT0UtiyfklBzzp9dl4CEmgrAQW9rZk37jYSyEHQl19++VKCfvnll3cr6BsBPwa2Aa4CdgY2ABYEHh9hfBwMbAZsBdwKrAocBiwDXJ/Kh6CvD6zS8f6rwD86/vsYYE1gC+AZ4GjgP8CybRyTxjw4Agr64FjXpSUFvS6ZsB8SkIAEuiCgoHcBy6ISyJxADoL+sY99rJSg/+EPf+hW0EPKrwG+ktI6BfAAcBRw0Aipfhj4FvC9js/OBF5M4h6/HYK+LvCBSQyVuAbuCWBT4BepTMyu3wJ8FPhz5kPM7teYgIJe4+T0qWsKep/AWq0EJCCBfhJQ0PtJ17olUC8COQj6csstV0rQr7jiioA9F/BcB/WXgfg1/JkKeCHNdp/V8eHJwEzAOiO88ySwO3B8x2enAMsB86TfC0GPJfMxM/4S8Ke0LP7+9PlKQFzYPjPwdEc99wFHAIfXa8TYmyYRUNCblM1isSjoxThZSgISkECtCCjotUqHnZFAXwnkIOjLLrtsKUH/4x//OBK7CWlWe/hncwAPpeXpIdFDz7eBFYClRqjsVGDxNEN+F7AycDYwZdpLHq+sDkyf9qfPnvajx371RdMXBzFzfmJH+aFmYt973BMXe9p9JNAXAgp6X7DWulIFvdbpsXMSkIAERiagoDsyJNAeAi0Q9KIz6JMS9EOAjwFLjzAqZgWOBdYGXgdC0i8GtgSmncQoitn4mB3fNc28T0rQY6l9zKyPb89oNNJBE1DQB028+vYU9OpzYA8kIAEJdE1AQe8amS9IIFsCOQj6MsssU2oG/corr4y8xB7vZwskqMwS96Fq4xT2twGxJz32qq8FLDKZNkO+Q+TjBHiXuBdIjkX6Q0BB7w/XOteqoNc5O/ZNAhKQwCQIKOgODQm0h0AOgv7Rj360lKD/6U8TV6oXFfQoG4fExdLyuFotnjgkLvaKx6nqIx0SN3ygxLVrcbjbGcBekxhFsdw96oy96Uem/sUhcZsAccBcPO9NS+I9JK49fxQriVRBrwR7pY0q6JXit3EJSEAC5Qgo6OW4+ZYEciSQg6AvvfTSpQT9z3+eeAB6N4I+dM3a1knU45q1DdOd5XEneVzBFvvUY+Y7ntiXHvvJb0j/G9I9L7BEx4Fv3wHOScvaYxl97IGPE90XTqe3Rz1xzdoa6Zq1mO2PU+PjievafCTQNwIKet/Q1rZiBb22qbFjEpCABCZNQEF3dEigPQRyEPSlllqqlKBfdVVMiHcl6FE+rliLU9dnS+K9Y5pZj88uA+5NIh3/HYfHhVzPBzwPnJ/2jMdS96HnNGD5tAQ+ZsrjaPm90371oTKxRP7QNIs+DrgI2A54tD0j0UirIKCgV0G92jYV9Gr527oEJCCBUgQU9FLYfEkCWRJQ0LNMm52WQE8IKOg9wdjTSmYA9gPWA94BXA/sBMTBFfFEzmIZzlbp/se4q2Jb4I6CvVDQC4KymAQkIIE6EVDQ65QN+yKB/hLIQdA/8pGPlJpBv/rq2E7e9Qx6f4FbuwRqREBBr1EyUldOT3cwhnTHUpzNgF3SnpjYXxP3LsYemy2Au5PML5Y+f6lAOAp6AUgWkYAEJFA3Agp63TJifyTQPwI5CPqHP/zhUoJ+zTUT55y62YPeP9DWLIEaElDQ65WUaYDngHWA8zq6di1wAfCNJO2xHyYOtxj6ARcHZISwx36a0R4FfTRCfi4BCUighgQU9BomxS5JoE8EchD0D33oQ6UE/S9/+YuC3qdxY7XNIKCg1yuPsbw9TolcBbiko2txcMWrwBfS4RUfTAdkDBX5ffrvWAo//IlDLeLX0BNtPDh+/HjGjev87XqBsDf/n8BORxzBTM88w9Mzzsh3d46DS30kIIE2ElDQ25h1Y24rgRwEfckllywl6NdeG/NOzqC3dWwb9+gEFPTRGQ26xJXAK8CmQMyMx/2LJwN3AlsCsec8roN4pKNjca/j60BcQzH8iasl9hn+mwr6oNNavr19JkyYePBAJHjCPm9IZfmKfVMCEsiKgIKeVbrsrATGRCAXQZ9yyim7ivO1115DQe8KmYVbSEBBr1/S5wdOSFc/vAZcB9ye7m780iQE/edAlN14hHCcQa9fjrvqkTPoXeGysAQaS0BBb2xqDUwCbyCgoDsoJNBeAgp6fXM/HRD7xWOmPA6Omx7YocQS9+ERuge9vjm3ZxKQgAQmSUBBd3BIoD0EchD0JZZYgjIz6NddF3NPLnFvz2g20m4JKOjdEht8+ZmBe4DdgWPTIXFxQFwcFBdPCPfjHhI3+MTYogQkIIFBElDQB0nbtiRQLYEcBP2DH/xgKUG//vq4QVhBr3aE2XqdCSjo9cvOqumu89uABYBDgJeB5YB/p2vWxgObJ3GPO9Pf7zVr9UukPZKABCTQSwIKei9pWpcE6k0gB0H/wAc+UErQb7jhBgW93sPP3lVMQEGvOAEjNL8hcCAwF/AUcCawN/BMKhs5mwBsDcwExAnv26V96kWicYl7EUqWkYAEJFAzAgp6zRJidyTQRwI5CPriiy9eStBvvPFGBb2PY8eq8yegoOefw24jUNC7JWZ5CUhAAjUgoKDXIAl2QQIDIpCDoL///e8vJeg33XSTgj6gcWQzeRJQ0PPM21h6raCPhZ7vSkACEqiIgIJeEXiblUAFBBT0CqDbpARqQkBBr0kiBtgNBX2AsG1KAhKQQK8IKOi9Imk9Eqg/gRwEfbHFFis1g/7Xv/7VGfT6D0F7WCEBBb1C+BU1raBXBN5mJSABCYyFgII+Fnq+K4G8COQg6IsuumgpQf/b3/6moOc1HO3tgAko6AMGXoPmFPQaJMEuSEACEuiWgILeLTHLSyBfAjkI+iKLLFJK0G+++WYFPd+hac8HQEBBHwDkmjWhoNcsIXZHAhKQQBECCnoRSpaRQDMI5CDoCy+8cClB//vf/66gN2OYGkWfCCjofQJb42oV9Bonx65JQAISmBQBBd2xIYH2EMhB0N/3vveVEvRbbrlFQW/PUDbSEgQU9BLQMn9FQc88gXZfAhJoJwEFvZ15N+p2ElDQ25l3o5ZAEFDQ2zcOFPT25dyIJSCBBhBQ0BuQREOQQEECOQj6QgstVGoG/dZbb3UGveA4sFg7CSjo7cu7gt6+nBuxBCTQAAIKegOSaAgSKEggB0FfcMEFSwn6bbfdpqAXHAcWaycBBb19eVfQ25dzI5aABBpAQEFvQBINQQIFCeQg6O9973tLCfrtt9+uoBccBxZrJwEFvX15V9Dbl3MjloAEGkBAQW9AEg1BAgUJ5CDo73nPe0oJ+h133KGgFxwHFmsnAQW9fXlX0NuXcyOWgAQaQEBBb0ASDUECBQnkIOgLLLBAKUG/8847FfSC48Bi7SSgoLcv7wp6+3JuxBKQQAMIKOgNSKIhSKAgAQW9ICiLSaCBBBT0BiZ1lJAU9Pbl3IglIIEGEFDQG5BEQ5BAQQI5CPr8889fagb9rrvucga94DiwWDsJKOjty7uC3r6cG7EEJNAAAgp6A5JoCBIoSCAHQZ9vvvlKCfrdd9+toBccBxZrJwEFvX15V9Dbl3MjloAEGkBAQW9AEg1BAgUJ5CLoU0wxRcGI/rfYf/7zHxT0rpBZuIUEFPT2JV1Bb1/OjVgCEmgAAQW9AUk0BAkUJJCDoM8777yUEfR77rmnzAz69sBuwGzAjcAOwNWTwPkWYE9gc2BOIC5e3wO4sKN8fP5pYCHgReDKVGbiJe3puQxYYVgbPwS2KZhGi0mgFAEFvRS2rF9S0LNOn52XgATaSkBBb2vmjbuNBHIQ9HnmmaeUoN97773dCvpGwI+TGF8F7AxsACwIPD7C+DgY2AzYCrgVWBU4DFgGuD6VD1k/DbgGeDNwALAosDDwrw5Bj0vbv9nRxgvAs20ck8Y8OAIK+uBY16UlBb0umbAfEpCABLogoKB3AcuiEsicgIL+XwkMKQ+R/kr63VhX/wBwFHDQCKl+GPgW8L2Oz85MM+Uh7iM9sybZjxnzyzsE/Yb0hUDmI8ru50RAQc8pW73pq4LeG47WIgEJSGCgBBT0geK2MQlUSiAHQX/3u99dagb9vvvuC7YzFpyJngqIWev1gbM6knIyMBOwzgiJehLYHTi+47NTgOWAeSaR2AWAO4DFgL91CPoiQPjSo8A5wH6pP5WODxtvNgEFvdn5HSk6Bb19OTdiCUigAQQU9AYk0RAkUJBADoL+rne9q5Sg33///UFhLuC5DhwvA/Fr+DMH8FBanv6njg+/nfaHLzXCO6cCiwPrAnGn28rA2cCUwLgRyseM/K+T8IfEDz1bA/FtQszIvx+IpfOx7z32rvtIoG8EFPS+oa1txQp6bVNjxyQgAQlMmoCC7uiQQHsI5CDoc889dylBf+CBWJ3+hmcCsG8Xgn4I8DFg6RHeieXqxwJrA68nSb8Y2BKYdoTyxwCrpxn2ByczylYCLgFitn3iZe4+EugHAQW9H1TrXaeCXu/82DsJSEACIxJQ0B0YEmgPgRwEfa655iol6A8+ONGBi86gl1niPjRQpgbelmbAY6/6WkAsWe98jk7L5JcHJh4vP5lnOuB5YDXgovaMRiMdNAEFfdDEq29PQa8+B/ZAAhKQQNcEFPSukfmCBLIlkIOgzznnnKUE/aGHYsV64T3oUTYOiYul5XG1WjyxJD3WyYdcj3RI3PC8x7VrtwBnAHulD8OB4pC59YAV0/7z0cbLssAVafn8TaMV9nMJlCWgoJcll+97Cnq+ubPnEpBAiwko6C1OvqG3joCC/l8pH7pmLfaEh6jHNWsbpjvMH0tXsIX1x93m8cS+9Lj/PE5gj/+NpfPzAksAT6cy3wc2TbPnnXefP5NOe58/fX4+EIfOxR70w4GY/h9+N3rrxqcB95eAgt5fvnWsXUGvY1bskwQkIIFRCCjoDhEJtIdADoI+xxxzlJpBf/jhOHOtqxn0KB9XrO0GzJbEe8c0sx6fXQbE5epbpBESAh37yudLS9JDssenpe5Dgyj2po/0xD71k4C5gTj5Pe5Gj6XtsXH+V8D+BU+fb89gNdKeE1DQe4609hUq6LVPkR2UgAQk8EYCCrqjQgLtIZCDoM8+++ylBP2RRx4pI+jtSb6Rtp6Agt6+IaCgty/nRiwBCTSAgILegCQaggQKEshB0GebbbZSgv7oo3GleNcz6AXJWUwC+RNQ0PPPYbcRKOjdErO8BCQggRoQUNBrkAS7IIEBEchB0N/5zneWEvTHHott4wr6gIaSzWRIQEHPMGlj7LKCPkaAvi4BCUigCgIKehXUbVMC1RDIQdDf8Y53lBL0xx9/XEGvZljZaiYEFPRMEtXDbiroPYRpVRKQgAQGRUBBHxRp25FA9QQU9OpzYA8kUBUBBb0q8tW1q6BXx96WJSABCZQmoKCXRueLEsiOQA6CPuuss5aaQX/iiSecQc9uRNrhQRJQ0AdJux5tKej1yIO9kIAEJNAVAQW9K1wWlkDWBHIQ9Le//e2lBP0f//iHgp716LTz/SagoPebcP3qV9DrlxN7JAEJSGBUAgr6qIgsIIHGEMhB0N/2treVEvQnn3xSQW/MSDWQfhBQ0PtBtd51Kuj1zo+9k4AEJDAiAQXdgSGB9hDIQdBnmWWWUoL+1FNPKejtGcpGWoKAgl4CWuavKOiZJ9DuS0AC7SSgoLcz70bdTgI5CPrMM89cStD/+c9/KujtHNZGXZCAgl4Q1ICKTQnsC2wGzAY8DJwE7A+8nvrwTuBg4JPATMDlwA7AHQX7qKAXBGUxCUhAAnUioKDXKRv2RQL9JaCg95evtUugzgQU9HplZy9gV2Bz4GbgQ8CJwN7AkUDk60rg38BXgWdT+dWAhYF/FQhHQS8AySISkIAE6kZAQa9bRuyPBPpHIBdBf9ObulOJ119/HWfQ+zdurLkZBLr7U9WMmOscxbnAY8AXOzp5JvBimlV/L3AbsGgS+Cg2BfAoEHJ/XIHgFPQCkCwiAQlIoG4EFPS6ZcT+SKB/BHIQ9Jlmmokygv70008HuBnTRFP/IFqzBDIloKDXK3Eh2Vun5eu3A4sDv0mz5D8FFgNuAhYA7uro+gPAJcAWI4QzDohfQ88MwIPjx49n3LjO364XCHvTDALfnDBh4rKP2J/xP/vsk01QH/rLX1juiiu4Yrnl+MuHYiGLjwSqJ6CgV58DeyCBQRHIQdBnnHHGUoL+zDPPKOiDGki2kyUBBb1eaYvZ8AOA3YHXgNiTHsvbD0zdfEvaa3418OW0pH0X4KAk8quOEE7saX+DGSno9Up8U3uzT4egT8hI0Hc+4ghmeuYZnp5xRo7Yeeempse4MiOgoGeWMLsrgTEQyEHQ3/rWt5YS9IjNGfQxDA5fbTwBBb1eKd4YOATYLS1h/wBwRJpBPzl1dUng+DS7HhJ/MfCf9NkaI4TjDHq9ctyq3jiD3qp0G2yfCSjofQZs9RKoEYEcBH2GGWYoJejPPfecgl6jsWZX6kdAQa9XTmKpesyGf6+jW19P+88XGtbV2LszFfAEcBXwF2D7AuG4B70AJItIQAISqBsBBb1uGbE/EugfAQW9f2ytWQJ1J6Cg1ytDTwIh5Md0dGtPYEsgDogb6XkPcCuwelrmPlpECvpohPxcAhKQQA0JKOg1TIpdkkCfCOQg6NNPP32pGfTnn38+qHlIXJ/GjtXmT0BBr1cO487zVdL+8rhm7YPAj4ATgD1SVzdIs+b3p0PjvgtcC3ymYCgKekFQFpOABCRQJwIKep2yYV8k0F8COQj6dNNNV0rQ//WvibcCK+j9HULWnjEBBb1eyYsT1vcD1gPeATwM/CwOwAZeSV3dMe1RfyfwCPDj9M7Q56NFpKCPRsjPJSABCdSQgIJew6TYJQn0iUAOgj7ttNOWEvQXXnhBQe/TuLHaZhBQ0JuRx26iUNC7oWVZCUhAAjUhoKDXJBF2QwIDIJCDoE8zzTSlBP3FF19U0AcwhmwiXwIKer65K9tzBb0sOd+TgAQkUCEBBb1C+DYtgQETyEHQp5566lKC/tJLLynoAx5PNpcXAQU9r3z1orcKei8oWocEJCCBARNQ0AcM3OYkUCEBBb1C+DYtgYoJKOgVJ6CC5hX0CqDbpAQkIIGxElDQx0rQ9yWQD4EcBH3cuHGlZtBffvllZ9DzGYr2tAICCnoF0CtuUkGvOAE2LwEJSKAMAQW9DDXfkUCeBHIQ9KmmmqqUoL/yysRzjT3FPc+haa8HQEBBHwDkmjWhoNcsIXZHAhKQQBECCnoRSpaRQDMI5CDob3nLW0oJ+r///W8FvRnD1Cj6REBB7xPYGleroNc4OXZNAhKQwKQIKOiODQm0h0AOgv7mN7+5lKC/+uqrCnp7hrKRliCgoJeAlvkrCnrmCbT7EpBAOwko6O3Mu1G3k0AOgj7llFOWEvTXXntNQW/nsDbqggQU9IKgGlRMQW9QMg1FAhJoDwEFvT25NlIJKOiOAQm0l4CC3r7cK+jty7kRS0ACDSCgoDcgiYYggYIEchD0KaaYotQM+n/+858yM+jbA7sBswE3AjsAV08C51uAPYHNgTmB24A9gAuHlR+tzqmBQ4GNgXHARcB2wGMF02gxCZQioKCXwpb1Swp61umz8xKQQFsJKOhtzbxxt5FADoL+pje9qZSgv/76690K+kbAj4FtgKuAnYENgAWBx0cYHwcDmwFbAbcCqwKHAcsA16fyReo8BlgT2AJ4BjgaiG8Xlm3jmDTmwRFQ0AfHui4tKeh1yYT9kIAEJNAFAQW9C1gWlUDmBHIQ9EAckt7Nk+S8W0EPKb8G+EpqawrgAeAo4KAR2n8Y+BbwvY7PzgReTOIevz1anXEN3BPApsAvUj0LAbcAHwX+3E3clpVANwS6+1PVTc2WrSuBiYK+yy67MG5crNbxkYAEJCCBHAjsuWes2PSRgATaQCAEfe655+5WZAeFZuK/JcfY2FzAcx11vAzEr+HPVMALwPrAWR0fngzMBKwzwjtPArsDx3d8dgqwHDAPUKTOlYBLgJmBpzvquQ84Ajh8jPH7ugQmSUBBb9/giL04D7YvbCOWgAQkIAEJSEAC2REIkX2oZr2Ovdn3pP3gZbr2PDD9sBcnAPuOUNkcKf5Ynv6njs+/DawALDXCO6cCiwPrAncBKwNnA1OmveRF6oyZ8xNT+c4mYt/7pWlPe5nYfUcCoxJQ0EdF1LgCkfP4wdT5rWXRIGdIcj/8W8+i71uuHAG5l+M2lrdkPhZ65d+Ve3l2Y3lT7mOhV/5duZdnN5Y3c+IefY3l2hM3bdfsCUmPmehePZOaQZ+UTB8CfAxYeoQOzAocC6yd2IWkXwxsCUyb/h0cX3oMl/7OOicl6LHUPmbWx/cqcOuRwHACCrpjohsCQ0uaYl/Os928aNkxEZD7mPCVelnmpbCN+SW5jxlhqQrkXgrbmF+S+5gRlqpA7qWwVfZSkeXok+pcfInwtvQlR+xVXwtYxCXuleXShgsSUNALgrLYRAL+pVbNQJD74LnLfPDM/RlTDXO5y706AtW07M/3ariPpdU40C2WlsfVavHEIXH3p1PVRzokbnhbce1aHO52BrBX+nC0OocOidsEiAPm4nlvurLNQ+LGkk3fHZWAgj4qIgt0EPAvtWqGg9wHz13mg2euKFbDXO5yr45ANS37870a7mNpdehKtK2TqMc1axsCcap63EkeV7DFkvWhkzRjX3qcuXRD+t/Y2z4vsETHgW+j1Rn9jWvW1kjXrMXK0Tg1Pp5YGu8jgb4RUND7hraRFcex7/HD78BJnLTZyKBrEJTcB58EmQ+eebQod7lXQ6CaVh3vcq+GQJ6txhVru6WD6UK8d0xXpUU0lwH3JpGO/47D40Ku5wPiQLrz057x2M/f+UyuzigXS+QPBWIWPf68XgRsBzyaJ0J7nQsBBT2XTNlPCUhAAhKQgAQkIAEJSEACEmg0AQW90ek1OAlIQAISkIAEJCABCUhAAhLIhYCCnkum7KcEJCABCUhAAhKQgAQkIAEJNJqAgt7o9BqcBCQgAQlIQAISkIAEJCABCeRCQEHPJVP2UwISkIAEJCABCUhAAhKQgAQaTUBBb3R6uw4uTmg/APguEFdYxDMbcAjwCWCGdP/jtzruhBxqZE3gm8D7gZeA3wPrdt2Ddr5Qlnvcxxm5WRaYCrgJ+Ho6zbSdJLuLeiTu8wPfAZZLJ7ZemO5djWtchp5Z0lUrawP/SX8WdkonxXbXg3aWLsN9HuAbwErpZ1KcxHsKED+LXmknxq6jLsO9s5E4wTjuDV4c+GC6vqjrTrTwhbFw9+/VcgOmLHP/Ti3H27ckIIEeE1DQeww04+o+DJwBxD2Pl3YI+m+AmYC4iuIfwKbABOBDwPUp3s8AxwJ7Ab8D3gwsmurLGMlAuj4W7rcDd6Sr715MOdsCCMn0CpDJp28k7tOlLzluBPZJr+8HzAEsnWQ8fvsCYHbgy8BbgBOBa9KfjYEMmowbKct9NSDurP0ZcGf6+RI/c34CfC1jHoPqelnunf2LL27fA6yuoBdO21i4+/dqYcz/VXAszP07tRxz35KABHpMQEHvMdBMq5seuC7d7RgzsHG/5NAMetwfuW36h/BQeE8CewDHJRmPuydDaI7PNP6quj0W7m8HngCWB/6QAogVDvEFS6x2uLiqoDJod1LcP5nke+bEMUKZEfgnEJ8F0/cBfwfiH4F/SbGGPMYdq3MBw+9YzQDHwLo4Fu4jdTLuw42fTXHPrc+kCfSCe0j5YUBI480KeqHhNhbu8SW3f68WwvxfhcbC3L9Tu+ftGxKQQJ8IKOh9AptZtScDTwG7pOXRnYIeM+ixhPTzwNPAhknEY5ljzGR9JC17/AKwY1p+Gu/HrFb8Q85n0gTGwj3+7N6S5Dy+THk5fakS0rJQkkrZj0xgUtxjyfqvgJhJD57xxLLefwH7A/sCMc4PBULih574x3Rs69ggvS/33nMfqcbISXw5Eqt5fLr/OVNkvEet7wSuTVuWYhXVPQp6oeE2lp8z/r1aCPEbCo2FuX+nlmPpKNr9AAAHBElEQVTuWxKQQB8IKOh9gJpZlRsDe6cZwZCMy4bNoMfy9tPTDOKrwAtJRELc44n3Y9np/cCu6Vv/r6bysZ8rxN/njQTGyj1qjBnbs4Al0vLrx4HYszi09UDu3XGfNX3pFEvWY7tG/Hw8KG3v+FFa0h6/vzmw4LCqg32sIjlG6CMSmNx4L8J9eKULJGmMLwJjqbvPyATGyj3+DMTqkD+mL6niLAAFffTRNlbu/r06OuPhJcbK3L9Tu2fuGxKQQJ8IKOj/r727B5WjCsMA/IIopLEQrCT+tIpYiEVEwaCNEgQhpRaCimillbWFIgqKP6idjWVAsRKxEFKIWChJkZSCIJaCjYUoL8zCZr3kzu7MvXfXfU4TyJ2ZPfPs2Z395nznmyOC3ZHDnh7SdJu+23W3basB+gfDLHkDk86etPBbZ9ofTnJpWHf7+RC8NIhp66zjr0PBsk93xOI4uzmHez+7Dc67BrqFsroG/bkkTw43W347zhPakdca497PQoPsu4abHr35dPeQJfLSELgfFKB3uUGLmH2yIxbH2c053Jf7e9tQhLLfVR3z2sECc7g3K6pr/7uU5u8kAvTDR9sc7q314rp6uPViiznMXVPHe9uSAIEjFhCgHzHwlh++wXZTevvDa9FuSPLPEJx0lnBRkGk5Xb1rcfv/LyY5OxSGa8B+cek4rfbb7To7r10rMIf7o0maxbC8Xrqv0qJxrQXQmV9tPffeWFp8FroesRkjXdbRgntNa2/FfCnu64+qw8b7GPfFq7ZgXwPz75O0IGKr6GsHC8zh3puATYXvNWH5GtHPSQPI3qzS5v+ecV1db1TNMdZdU9cztzUBAkcoIEA/QtwdOHSLit2x0s+m915J8taQ4ttHd3UGseudF+3rJL8keSHJzUma3vvyUpG4zup2Br0ziotZ9R3gOLYuzuHeH8398dwiZi3kt2hXk3QdXh+Xp10rcJj75QPA+livRXG42i6KxHXdc9fltnXWvY9jUyTu4BE3h3uP3JnzPmGi7k+v3Fg01v8rMIf77cN3/OLovUHS7//zQ1ZJv+e1+b9nXFfXG1VzjHXX1PXMbU2AwBEKCNCPEHdHD72c4t5AuxWrmy7dtZ6t3t471Z1JPDesTexpvjf8YOvsYgP3FirrxU6xsvGDYF33zvD2RkqfN//6kOL+fJI+j7sVxhdLFsb3YD+3XF3S8exwM6op62eS9NFSnyVpXYVF62PWWjirGSSLx6y1onvTUrVxAuu6NzDsWG+tixasXM768UjBcebdal331SNLcR9vvbzlJu6uq5tZL/Za19w1dZq3vQkQmFFAgD4j5v/kUKsXtT73tunSDyXpI0ya2v7OymPXGqS8meSZJKeGmZVWFlfFffyg2MS9s7hdf95/+x7Uu8F6A0htnMCqe8d6U6dvGQoedk35uyspvv3bh8NNqKZYXxieYLCcyTDu1fd3q3Xd+540u+eg5jo2fhyt6y5AH297vS03cXddnWa/iblr6jRzexMgMJOAHzYzQToMAQIECBAgQIAAAQIECBCYIiBAn6JnXwIECBAgQIAAAQIECBAgMJOAAH0mSIchQIAAAQIECBAgQIAAAQJTBAToU/TsS4AAAQIECBAgQIAAAQIEZhIQoM8E6TAECBAgQIAAAQIECBAgQGCKgAB9ip59CRAgQIAAAQIECBAgQIDATAIC9JkgHYYAAQIECBAgQIAAAQIECEwREKBP0bMvAQIECBAgQIAAAQIECBCYSUCAPhOkwxAgQIAAAQIECBAgQIAAgSkCAvQpevYlQIAAAQIECBAgQIAAAQIzCQjQZ4J0GAIECBAgQIAAAQIECBAgMEVAgD5Fz74ECBAgcFICtya5lOT9JG8MnTiT5Lskjyf59qQ65nUJECBAgAABApsKCNA3lbMfAQIECJy0wBNJvkjyYJIrSX5O8mWSV0+6Y16fAAECBAgQILCJgAB9EzX7ECBAgMC2CHyU5LEkPya5N8kDSf7als7pBwECBAgQIEBgHQEB+jpatiVAgACBbRM4leRyktNJ7h/S3retj/pDgAABAgQIEBglIEAfxWQjAgQIENhSgXuG2fMbkzyV5Kst7aduESBAgAABAgQOFRCgH0pkAwIECBDYUoGbkvyQ5KckV5O8MqS5/76l/dUtAgQIECBAgMB1BQToBggBAgQI7KrA20nOJ7kvyZ9DBfc/kpzb1RPSbwIECBAgQGC/BQTo+/3+O3sCBAjsqsAjSb5JcjbJxeEk7hwqub+W5ONdPTH9JkCAAAECBPZXQIC+v++9MydAgAABAgQIECBAgACBLRIQoG/Rm6ErBAgQIECAAAECBAgQILC/AgL0/X3vnTkBAgQIECBAgAABAgQIbJGAAH2L3gxdIUCAAAECBAgQIECAAIH9FfgX66l0RBdSmn4AAAAASUVORK5CYII=\" width=\"1000\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize = (10, 4))\n",
"mask_idx.plot(x = 'x', y = 'y', cmap = 'gray')\n",
"plt.scatter(linked.x_idx, linked.y_idx, c = 'r', s = 1)\n",
"# plt.scatter(corrected_CH.x_idx, corrected_CH.y_idx, c = 'g', s = 1)\n",
"plt.axis('equal')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Aims:\n",
"- Check that tilted_irradiance.py works as expected and with (subsets of) the existing data structures\n",
"- Save as netCDF in order to save space"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Load data"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"N_SAMPLES = 1000"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"meteo_path = '/work/hyenergy/output/solar_potential/physical_potential/results'\n",
"meteo_file = 'physical_potential_dhm25_200_CH_ELM50_1000.nc'\n",
"albedo_file = 'ALB_dhm25_200_CH_ELM30_1000_CPU_prediction.nc'\n",
"rooftop_fp = '/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt'\n",
"\n",
"save_path = '/scratch/walch/workspace_tilted_irradiance'"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"meteo = xr.open_dataset(os.path.join(meteo_path, meteo_file ))\n",
"albedo = xr.open_dataset(os.path.join(meteo_path, albedo_file))\n",
"\n",
"roofs = pd.read_csv( rooftop_fp, nrows = N_SAMPLES, index_col = 0 )"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (timestamp: 159, x: 1742, y: 1103)\n",
"Coordinates:\n",
" * x (x) float64 4.855e+05 4.857e+05 ... 8.335e+05 8.337e+05\n",
" * y (y) float64 7.529e+04 7.549e+04 ... 2.955e+05 2.957e+05\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
"Data variables:\n",
" SIS (x, y, timestamp) float64 ...\n",
" SISDIR (x, y, timestamp) float64 ...\n",
" apparent_zenith (x, y, timestamp) float64 ...\n",
" azimuth (x, y, timestamp) float64 ...\n",
" DHI (x, y, timestamp) float64 ...\n",
" DNI (x, y, timestamp) float64 ...\n",
" rel_airmass (x, y, timestamp) float64 ...\n",
" DNI_extra (timestamp) float64 ..."
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"meteo"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (month: 12, x: 1742, y: 1103)\n",
"Coordinates:\n",
" * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
" * x (x) float64 4.855e+05 4.857e+05 4.859e+05 ... 8.335e+05 8.337e+05\n",
" * y (y) float64 7.529e+04 7.549e+04 7.569e+04 ... 2.955e+05 2.957e+05\n",
"Data variables:\n",
" z (month, x, y) float64 ...\n",
" ALB (month, x, y) float64 ..."
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"albedo"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Select subset of data according to rooftops:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Range of X: from 621669.342 to 637075.097\n",
"Range of Y: from 253991.833 to 254270.418\n"
]
}
],
"source": [
"print('Range of X: from %.3f to %.3f' %(roofs.XCOORD.min(),roofs.XCOORD.max()))\n",
"print('Range of Y: from %.3f to %.3f' %(roofs.YCOORD.min(),roofs.YCOORD.max()))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (month: 12, x: 351, y: 62)\n",
"Coordinates:\n",
" * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
" * x (x) float64 6.201e+05 6.203e+05 6.205e+05 ... 6.899e+05 6.901e+05\n",
" * y (y) float64 2.539e+05 2.541e+05 2.543e+05 ... 2.659e+05 2.661e+05\n",
"Data variables:\n",
" z (month, x, y) float64 ...\n",
" ALB (month, x, y) float64 ..."
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"meteo_select = meteo.sel( x = slice( roofs.XCOORD.min()-200, roofs.XCOORD.max()+200), y = slice( roofs.YCOORD.min()-200, roofs.YCOORD.max()+200) )\n",
"albedo_select = albedo.sel( x = slice( roofs.XCOORD.min()-200, roofs.XCOORD.max()+200), y = slice( roofs.YCOORD.min()-200, roofs.YCOORD.max()+200) )\n",
"\n",
"albedo_select"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Save samples on scratch"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"meteo_tmp = os.path.join( save_path, 'meteo_subset_1000roofs.nc' )\n",
"albedo_tmp = os.path.join( save_path, 'albedo_subset_1000roofs.nc' )\n",
"roofs_tmp = os.path.join( save_path, 'SONNENDACH_subset_1000roofs.csv')\n",
"result_tmp = os.path.join( save_path, 'tilted_irr_subset_1000roofs.csv' )"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"meteo_select.to_netcdf( meteo_tmp )\n",
"albedo_select.to_netcdf( albedo_tmp )\n",
"roofs.to_csv( roofs_tmp, index = False )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Test run of file"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/scratch/walch/workspace_tilted_irradiance/meteo_subset_1000roofs.nc\n",
"/scratch/walch/workspace_tilted_irradiance/albedo_subset_1000roofs.nc\n",
"/scratch/walch/workspace_tilted_irradiance/SONNENDACH_subset_1000roofs.csv\n",
"/scratch/walch/workspace_tilted_irradiance/tilted_irr_subset_1000roofs.csv\n"
]
}
],
"source": [
"print(meteo_tmp)\n",
"print(albedo_tmp)\n",
"print(roofs_tmp)\n",
"print(result_tmp)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/work/hyenergy/output/solar_potential/physical_potential/results/physical_potential_dhm25_200_CH_ELM50_1000.nc\n",
"/work/hyenergy/output/solar_potential/physical_potential/results/ALB_dhm25_200_CH_ELM30_1000_CPU_prediction.nc\n",
"/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt\n"
]
}
],
"source": [
"print(os.path.join(meteo_path, meteo_file ))\n",
"print(os.path.join(meteo_path, albedo_file ))\n",
"print(rooftop_fp)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" XCOORD YCOORD DF_UID FLAECHE NEIGUNG AUSRICHTUNG\n",
"0 683482.130379 253957.757634 9889792 12.194088 0 -180\n",
"1 683305.481435 253965.590119 9889793 280.868991 0 -180\n",
"2 683469.481349 253907.323720 9889794 184.241492 4 159\n",
"3 683498.213679 253898.875688 9889795 293.661442 0 -180\n",
"4 683498.012043 253898.746946 9889796 5.256826 0 -111\n",
"5 683296.764879 253983.097301 9889797 270.246719 0 -180\n",
"6 683297.710151 253984.740580 9889798 7.582342 0 -180\n",
"7 683393.966716 253866.479971 9889799 135.030977 22 69\n",
"8 683400.387855 253868.861565 9889800 134.601280 22 -111\n",
"9 683354.186520 253959.293627 9889801 10.035644 0 -180\n",
"10 683315.207392 253844.665737 9889802 80.864057 0 -180\n",
"11 683364.516816 253768.626689 9889803 5.467228 0 -180\n",
"12 683360.021767 253761.354028 9889804 200.559661 0 -180\n",
"13 683449.856116 253989.574914 9889805 34.678996 15 69\n",
"14 683453.088294 253990.810354 9889806 36.779475 14 -111\n",
"15 683300.658716 253923.590100 9889807 258.718983 0 -180\n",
"16 683300.827173 253925.389782 9889808 5.732134 0 -180\n",
"17 683307.607778 253929.398958 9889809 0.779147 0 -180\n",
"18 683292.559788 253919.867469 9889810 1.174222 0 -180\n",
"19 683452.768862 253931.143509 9889811 30.644242 3 -68\n",
"20 683478.468068 253997.386001 9889812 43.128305 12 -21\n",
"21 683476.877851 254001.506662 9889813 43.192307 12 159\n",
"22 683365.077659 253838.672417 9889814 282.400035 0 -180\n",
"23 683356.601360 253834.027535 9889815 1.220804 0 -180\n",
"24 683364.705183 253840.819033 9889816 1.174428 0 -180\n",
"25 683412.152885 253995.528044 9889817 59.545737 22 70\n",
"26 683417.293700 253997.407781 9889818 59.022761 22 -110\n",
"27 683478.885892 253966.976201 9889819 63.274385 12 159\n",
"28 683480.700445 253962.323693 9889820 65.900155 11 -21\n",
"29 683422.699906 253797.494062 9889821 3.977896 0 -180\n",
".. ... ... ... ... ... ...\n",
"202 683806.599770 253949.998246 9889994 10.427635 0 -180\n",
"203 683790.710893 253950.274145 9889995 7.403436 0 -180\n",
"204 683795.366549 253951.987280 9889996 92.962710 0 -180\n",
"205 684254.231280 253836.436535 9889997 52.693563 42 9\n",
"206 684255.204785 253842.340407 9889998 44.335771 35 -171\n",
"207 684244.087173 253838.156182 9889999 117.077544 42 9\n",
"208 684245.791408 253846.344335 9890000 185.820748 35 -171\n",
"209 684234.067839 253842.082515 9890001 68.913247 27 99\n",
"210 684219.249721 253840.300209 9890002 11.937935 0 -180\n",
"211 684217.306617 253848.180900 9890003 133.700300 27 100\n",
"212 684224.340946 253846.995681 9890004 71.773829 36 -80\n",
"213 684255.945260 253785.494932 9890005 35.454973 43 162\n",
"214 684260.179296 253783.414922 9890006 34.791863 44 -108\n",
"215 684258.122952 253779.207104 9890007 19.437468 45 -18\n",
"216 684253.794967 253781.289568 9890008 34.592246 44 72\n",
"217 684257.033069 253779.351511 9890009 5.810284 46 72\n",
"218 684258.261015 253778.220522 9890010 4.185050 45 -18\n",
"219 684258.601043 253779.871319 9890011 5.503249 49 -108\n",
"220 684262.231649 253814.019311 9890012 45.432721 22 160\n",
"221 684263.730692 253809.917455 9890013 43.138027 23 -20\n",
"222 680673.292625 241922.194535 9890014 90.230932 35 168\n",
"223 680674.727769 241915.634872 9890015 94.386422 33 -12\n",
"224 680647.364382 241983.401620 9890016 102.246055 33 167\n",
"225 680648.558053 241978.175130 9890017 96.772988 35 -13\n",
"226 680656.228606 241909.403208 9890018 320.192257 31 -12\n",
"227 680654.154856 241918.883711 9890019 307.089850 33 168\n",
"228 680639.156908 241978.555776 9890020 25.457102 4 77\n",
"229 681267.596269 241974.071131 9890021 20.216029 7 -174\n",
"230 681252.144233 241972.021141 9890022 264.665365 7 -174\n",
"231 681272.758490 241968.440592 9890023 138.787180 9 -174\n",
"\n",
"[232 rows x 6 columns]\n",
"<xarray.Dataset>\n",
"Dimensions: (timestamp: 159, x: 20, y: 62)\n",
"Coordinates:\n",
" * x (x) float64 6.805e+05 6.807e+05 ... 6.841e+05 6.843e+05\n",
" * y (y) float64 2.419e+05 2.421e+05 ... 2.539e+05 2.541e+05\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
"Data variables:\n",
" SIS (x, y, timestamp) float64 ...\n",
" SISDIR (x, y, timestamp) float64 ...\n",
" apparent_zenith (x, y, timestamp) float64 ...\n",
" azimuth (x, y, timestamp) float64 ...\n",
" DHI (x, y, timestamp) float64 ...\n",
" DNI (x, y, timestamp) float64 ...\n",
" rel_airmass (x, y, timestamp) float64 ...\n",
" DNI_extra (timestamp) float64 ...\n",
"<xarray.Dataset>\n",
"Dimensions: (month: 12, x: 20, y: 62)\n",
"Coordinates:\n",
" * month (month) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0\n",
" * x (x) float64 6.805e+05 6.807e+05 6.809e+05 ... 6.841e+05 6.843e+05\n",
" * y (y) float64 2.419e+05 2.421e+05 2.423e+05 ... 2.539e+05 2.541e+05\n",
"Data variables:\n",
" z (month, x, y) float64 ...\n",
" ALB (month, x, y) float64 ...\n",
"\n",
"Merged meteo data on rooftop dataset\n",
"CPU time: 0.03 seconds\n",
"Wall clock time: 0.05 seconds\n",
"\n",
"Computed irradiance components\n",
"CPU time: 0.04 seconds\n",
"Wall clock time: 0.10 seconds\n",
"\n",
"Added columns for unique identification to dataframe\n",
"CPU time: 0.01 seconds\n",
"Wall clock time: 0.01 seconds\n",
"\n",
"Saved file as /scratch/walch/workspace_tilted_irradiance/tilted_irr_subset_1000roofs.csv\n",
"CPU time: 0.27 seconds\n",
"Wall clock time: 0.33 seconds\n"
]
}
],
"source": [
"%run '../tilted_irradiance.py' '/work/hyenergy/output/solar_potential/physical_potential/results/physical_potential_dhm25_200_CH_ELM50_1000.nc' '/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt' '/scratch/walch/workspace_tilted_irradiance/tilted_irr_subset_1000roofs.csv' '/work/hyenergy/output/solar_potential/physical_potential/results/ALB_dhm25_200_CH_ELM30_1000_CPU_prediction.nc' 9639000 1000 "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Verify results"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>timestamp</th>\n",
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" <td>2001-01-15 12:00:00</td>\n",
" <td>49.900486</td>\n",
" <td>81.753697</td>\n",
" <td>0.287374</td>\n",
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" <td>19.081494</td>\n",
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" <td>0.144279</td>\n",
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" <td>44.570550</td>\n",
" <td>0.114169</td>\n",
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" <td>77.852443</td>\n",
" <td>0.246367</td>\n",
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" <th>11</th>\n",
" <td>277556</td>\n",
" <td>2001-02-15 09:00:00</td>\n",
" <td>72.691185</td>\n",
" <td>107.417003</td>\n",
" <td>0.357375</td>\n",
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" <th>12</th>\n",
" <td>277556</td>\n",
" <td>2001-02-15 10:00:00</td>\n",
" <td>100.482348</td>\n",
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" <td>0.389452</td>\n",
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" <td>78.258006</td>\n",
" <td>0.282694</td>\n",
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" <td>29.772479</td>\n",
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" <td>0.154500</td>\n",
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" <td>2001-02-15 16:00:00</td>\n",
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" <td>0.029362</td>\n",
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" <td>94.036467</td>\n",
" <td>0.234351</td>\n",
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" <th>21</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 08:00:00</td>\n",
" <td>120.606670</td>\n",
" <td>135.242820</td>\n",
" <td>0.375789</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 09:00:00</td>\n",
" <td>166.455139</td>\n",
" <td>162.098684</td>\n",
" <td>0.482765</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 10:00:00</td>\n",
" <td>197.676098</td>\n",
" <td>177.218020</td>\n",
" <td>0.551136</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 11:00:00</td>\n",
" <td>213.082669</td>\n",
" <td>181.826292</td>\n",
" <td>0.580314</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 12:00:00</td>\n",
" <td>206.075323</td>\n",
" <td>175.486872</td>\n",
" <td>0.559265</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 13:00:00</td>\n",
" <td>176.103703</td>\n",
" <td>158.838608</td>\n",
" <td>0.488301</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 14:00:00</td>\n",
" <td>129.792933</td>\n",
" <td>131.721016</td>\n",
" <td>0.378074</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 15:00:00</td>\n",
" <td>76.129529</td>\n",
" <td>94.746856</td>\n",
" <td>0.242820</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>277556</td>\n",
" <td>2001-03-15 16:00:00</td>\n",
" <td>28.415949</td>\n",
" <td>49.641530</td>\n",
" <td>0.108874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584341</th>\n",
" <td>266782</td>\n",
" <td>2001-09-15 16:00:00</td>\n",
" <td>121.016520</td>\n",
" <td>68.142443</td>\n",
" <td>2.357418</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584342</th>\n",
" <td>266782</td>\n",
" <td>2001-09-15 17:00:00</td>\n",
" <td>9.496472</td>\n",
" <td>9.616746</td>\n",
" <td>0.269298</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584343</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 06:00:00</td>\n",
" <td>0.000000</td>\n",
" <td>27.855027</td>\n",
" <td>1.368103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584344</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 07:00:00</td>\n",
" <td>0.000000</td>\n",
" <td>61.149796</td>\n",
" <td>3.517255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584345</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 08:00:00</td>\n",
" <td>10.783403</td>\n",
" <td>95.046551</td>\n",
" <td>5.628829</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584346</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 09:00:00</td>\n",
" <td>66.838590</td>\n",
" <td>126.591016</td>\n",
" <td>7.487039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584347</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 10:00:00</td>\n",
" <td>139.897738</td>\n",
" <td>147.984409</td>\n",
" <td>8.999720</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584348</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 11:00:00</td>\n",
" <td>208.025440</td>\n",
" <td>170.407381</td>\n",
" <td>9.630354</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584349</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 12:00:00</td>\n",
" <td>248.691871</td>\n",
" <td>168.521585</td>\n",
" <td>9.069536</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584350</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 13:00:00</td>\n",
" <td>248.289917</td>\n",
" <td>150.872273</td>\n",
" <td>7.419509</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584351</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 14:00:00</td>\n",
" <td>197.275492</td>\n",
" <td>120.921911</td>\n",
" <td>4.965573</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584352</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 15:00:00</td>\n",
" <td>109.611330</td>\n",
" <td>62.683926</td>\n",
" <td>2.347676</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584353</th>\n",
" <td>266782</td>\n",
" <td>2001-10-15 16:00:00</td>\n",
" <td>12.634373</td>\n",
" <td>9.199459</td>\n",
" <td>0.303141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584354</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 07:00:00</td>\n",
" <td>0.000000</td>\n",
" <td>32.142300</td>\n",
" <td>2.017311</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584355</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 08:00:00</td>\n",
" <td>0.572969</td>\n",
" <td>55.636007</td>\n",
" <td>3.875714</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584356</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 09:00:00</td>\n",
" <td>43.066052</td>\n",
" <td>87.057153</td>\n",
" <td>5.306170</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584357</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 10:00:00</td>\n",
" <td>88.265316</td>\n",
" <td>110.898954</td>\n",
" <td>6.442656</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584358</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 11:00:00</td>\n",
" <td>129.279010</td>\n",
" <td>122.438269</td>\n",
" <td>6.854062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584359</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 12:00:00</td>\n",
" <td>147.719507</td>\n",
" <td>117.342110</td>\n",
" <td>6.174163</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584360</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 13:00:00</td>\n",
" <td>135.626147</td>\n",
" <td>99.207230</td>\n",
" <td>4.655356</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584361</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 14:00:00</td>\n",
" <td>99.424242</td>\n",
" <td>67.505822</td>\n",
" <td>2.671690</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584362</th>\n",
" <td>266782</td>\n",
" <td>2001-11-15 15:00:00</td>\n",
" <td>26.237605</td>\n",
" <td>21.494864</td>\n",
" <td>0.552659</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584363</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 08:00:00</td>\n",
" <td>0.000000</td>\n",
" <td>39.733698</td>\n",
" <td>3.052643</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584364</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 09:00:00</td>\n",
" <td>27.862882</td>\n",
" <td>67.759070</td>\n",
" <td>4.565005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584365</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 10:00:00</td>\n",
" <td>64.466725</td>\n",
" <td>90.967376</td>\n",
" <td>5.669832</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584366</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 11:00:00</td>\n",
" <td>93.078785</td>\n",
" <td>102.576708</td>\n",
" <td>5.983329</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584367</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 12:00:00</td>\n",
" <td>105.625690</td>\n",
" <td>99.798670</td>\n",
" <td>5.367904</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584368</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 13:00:00</td>\n",
" <td>97.246016</td>\n",
" <td>83.497182</td>\n",
" <td>3.983382</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584369</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 14:00:00</td>\n",
" <td>63.925913</td>\n",
" <td>54.742542</td>\n",
" <td>2.097014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14584370</th>\n",
" <td>266782</td>\n",
" <td>2001-12-15 15:00:00</td>\n",
" <td>2.559927</td>\n",
" <td>4.167915</td>\n",
" <td>0.196697</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>14584371 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" DF_UID timestamp poa_direct poa_sky_diffuse \\\n",
"0 277556 2001-01-15 08:00:00 2.744178 43.169190 \n",
"1 277556 2001-01-15 09:00:00 24.452941 68.011805 \n",
"2 277556 2001-01-15 10:00:00 41.489234 82.969924 \n",
"3 277556 2001-01-15 11:00:00 51.911583 87.511378 \n",
"4 277556 2001-01-15 12:00:00 49.900486 81.753697 \n",
"5 277556 2001-01-15 13:00:00 37.429682 68.469641 \n",
"6 277556 2001-01-15 14:00:00 19.081494 45.826261 \n",
"7 277556 2001-01-15 15:00:00 3.088669 17.680890 \n",
"8 277556 2001-01-15 16:00:00 0.000000 1.002305 \n",
"9 277556 2001-02-15 07:00:00 0.682631 44.570550 \n",
"10 277556 2001-02-15 08:00:00 39.637057 77.852443 \n",
"11 277556 2001-02-15 09:00:00 72.691185 107.417003 \n",
"12 277556 2001-02-15 10:00:00 100.482348 118.292971 \n",
"13 277556 2001-02-15 11:00:00 118.056879 120.337102 \n",
"14 277556 2001-02-15 12:00:00 117.463994 113.293882 \n",
"15 277556 2001-02-15 13:00:00 97.948815 99.921133 \n",
"16 277556 2001-02-15 14:00:00 65.325666 78.258006 \n",
"17 277556 2001-02-15 15:00:00 29.772479 49.451868 \n",
"18 277556 2001-02-15 16:00:00 2.883752 12.011673 \n",
"19 277556 2001-03-15 06:00:00 13.537968 47.443845 \n",
"20 277556 2001-03-15 07:00:00 64.807421 94.036467 \n",
"21 277556 2001-03-15 08:00:00 120.606670 135.242820 \n",
"22 277556 2001-03-15 09:00:00 166.455139 162.098684 \n",
"23 277556 2001-03-15 10:00:00 197.676098 177.218020 \n",
"24 277556 2001-03-15 11:00:00 213.082669 181.826292 \n",
"25 277556 2001-03-15 12:00:00 206.075323 175.486872 \n",
"26 277556 2001-03-15 13:00:00 176.103703 158.838608 \n",
"27 277556 2001-03-15 14:00:00 129.792933 131.721016 \n",
"28 277556 2001-03-15 15:00:00 76.129529 94.746856 \n",
"29 277556 2001-03-15 16:00:00 28.415949 49.641530 \n",
"... ... ... ... ... \n",
"14584341 266782 2001-09-15 16:00:00 121.016520 68.142443 \n",
"14584342 266782 2001-09-15 17:00:00 9.496472 9.616746 \n",
"14584343 266782 2001-10-15 06:00:00 0.000000 27.855027 \n",
"14584344 266782 2001-10-15 07:00:00 0.000000 61.149796 \n",
"14584345 266782 2001-10-15 08:00:00 10.783403 95.046551 \n",
"14584346 266782 2001-10-15 09:00:00 66.838590 126.591016 \n",
"14584347 266782 2001-10-15 10:00:00 139.897738 147.984409 \n",
"14584348 266782 2001-10-15 11:00:00 208.025440 170.407381 \n",
"14584349 266782 2001-10-15 12:00:00 248.691871 168.521585 \n",
"14584350 266782 2001-10-15 13:00:00 248.289917 150.872273 \n",
"14584351 266782 2001-10-15 14:00:00 197.275492 120.921911 \n",
"14584352 266782 2001-10-15 15:00:00 109.611330 62.683926 \n",
"14584353 266782 2001-10-15 16:00:00 12.634373 9.199459 \n",
"14584354 266782 2001-11-15 07:00:00 0.000000 32.142300 \n",
"14584355 266782 2001-11-15 08:00:00 0.572969 55.636007 \n",
"14584356 266782 2001-11-15 09:00:00 43.066052 87.057153 \n",
"14584357 266782 2001-11-15 10:00:00 88.265316 110.898954 \n",
"14584358 266782 2001-11-15 11:00:00 129.279010 122.438269 \n",
"14584359 266782 2001-11-15 12:00:00 147.719507 117.342110 \n",
"14584360 266782 2001-11-15 13:00:00 135.626147 99.207230 \n",
"14584361 266782 2001-11-15 14:00:00 99.424242 67.505822 \n",
"14584362 266782 2001-11-15 15:00:00 26.237605 21.494864 \n",
"14584363 266782 2001-12-15 08:00:00 0.000000 39.733698 \n",
"14584364 266782 2001-12-15 09:00:00 27.862882 67.759070 \n",
"14584365 266782 2001-12-15 10:00:00 64.466725 90.967376 \n",
"14584366 266782 2001-12-15 11:00:00 93.078785 102.576708 \n",
"14584367 266782 2001-12-15 12:00:00 105.625690 99.798670 \n",
"14584368 266782 2001-12-15 13:00:00 97.246016 83.497182 \n",
"14584369 266782 2001-12-15 14:00:00 63.925913 54.742542 \n",
"14584370 266782 2001-12-15 15:00:00 2.559927 4.167915 \n",
"\n",
" poa_ground_diffuse \n",
"0 0.141408 \n",
"1 0.215859 \n",
"2 0.276918 \n",
"3 0.305856 \n",
"4 0.287374 \n",
"5 0.231563 \n",
"6 0.144279 \n",
"7 0.048825 \n",
"8 0.002802 \n",
"9 0.114169 \n",
"10 0.246367 \n",
"11 0.357375 \n",
"12 0.433739 \n",
"13 0.470947 \n",
"14 0.455027 \n",
"15 0.389452 \n",
"16 0.282694 \n",
"17 0.154500 \n",
"18 0.029362 \n",
"19 0.094109 \n",
"20 0.234351 \n",
"21 0.375789 \n",
"22 0.482765 \n",
"23 0.551136 \n",
"24 0.580314 \n",
"25 0.559265 \n",
"26 0.488301 \n",
"27 0.378074 \n",
"28 0.242820 \n",
"29 0.108874 \n",
"... ... \n",
"14584341 2.357418 \n",
"14584342 0.269298 \n",
"14584343 1.368103 \n",
"14584344 3.517255 \n",
"14584345 5.628829 \n",
"14584346 7.487039 \n",
"14584347 8.999720 \n",
"14584348 9.630354 \n",
"14584349 9.069536 \n",
"14584350 7.419509 \n",
"14584351 4.965573 \n",
"14584352 2.347676 \n",
"14584353 0.303141 \n",
"14584354 2.017311 \n",
"14584355 3.875714 \n",
"14584356 5.306170 \n",
"14584357 6.442656 \n",
"14584358 6.854062 \n",
"14584359 6.174163 \n",
"14584360 4.655356 \n",
"14584361 2.671690 \n",
"14584362 0.552659 \n",
"14584363 3.052643 \n",
"14584364 4.565005 \n",
"14584365 5.669832 \n",
"14584366 5.983329 \n",
"14584367 5.367904 \n",
"14584368 3.983382 \n",
"14584369 2.097014 \n",
"14584370 0.196697 \n",
"\n",
"[14584371 rows x 5 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.read_csv( '/scratch/walch/workspace_tilted_irrad/tilted_irradiance_2.csv', index_col = 0 )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
c4science · Help