From 8e9961fbf9e12daaac2490ed5a8a2250cad12875 Mon Sep 17 00:00:00 2001
From: Robert Lanzafame <R.C.Lanzafame@tudelft.nl>
Date: Wed, 4 Dec 2024 14:56:26 +0100
Subject: [PATCH] WS 2.4 finished
---
content/Week_2_4/WS_2_4_solution.ipynb | 80 +-
src/students/Week_2_4/WS_2_4_solution.html | 8670 ++++++++++++++++++++
2 files changed, 8718 insertions(+), 32 deletions(-)
create mode 100644 src/students/Week_2_4/WS_2_4_solution.html
diff --git a/content/Week_2_4/WS_2_4_solution.ipynb b/content/Week_2_4/WS_2_4_solution.ipynb
index e4290d78..181ca576 100644
--- a/content/Week_2_4/WS_2_4_solution.ipynb
+++ b/content/Week_2_4/WS_2_4_solution.ipynb
@@ -530,7 +530,9 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "<div style=\"background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p>If you want to compute the $\\theta_i$ you can use the <code>np.arctan2</code> function. This function is a version of the arctan function that returns the angle in the correct quadrant. Using the <code>np.arctan</code> function will not give you the correct angle!</p></div>"
+ "<div style=\"background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p>\n",
+ "\n",
+ "If you want to compute the $\\theta_i$ you can use the <code>np.arctan2</code> function. This function is a version of the arctan function that returns the angle in the correct quadrant. Using the <code>np.arctan</code> function will not give you the correct angle!</p></div>"
]
},
{
@@ -593,6 +595,50 @@
" print(f'A_{i} = {A_i:.3f}, theta_{i} = {theta_i:.3f}, f_{i} = {f:.3f}')"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "<div style=\"background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p>Task 4.2 was moved here, since it made more sense to interpret the parameters earlier.</p></div>"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "\n",
+ "<div style=\"background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p> <b>Task 4.2:</b> \n",
+ "<p>\n",
+ "\n",
+ "- What can you say about the parameters, do the parameters make sense? \n",
+ "\n",
+ "- What time of the day is the pressure highest (on average)?\n",
+ " \n",
+ "- What has the highest impact on the pressure, the daily or the yearly periodic signal?\n",
+ "\n",
+ "</p>\n",
+ "</div>"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "_Your answer here._"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p> <b>Solution:</b> \n",
+ "<p>\n",
+ "Yes, the parameters make sense. The average pressure is about 1013 hPa (the intercept); the slope is 0, so there is no increasing/decreasing trend. Looking at the periodic signals we can see that the daily parameter for theta is 1.6, which is around half of pi, or one-quarter of the daily period; therefore the pressure is highest around 6:00-7:00 AM. Looking at the amplitude parameters we can see that the yearly periodic signal has the highest impact on the pressure.\n",
+ "</p>\n",
+ "</div>"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -939,37 +985,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "\n",
- "\n",
- "<div style=\"background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p> <b>Task 4.2:</b> \n",
- "<p>\n",
- "\n",
- "- What can you say about the parameters, do the parameters make sense? \n",
- "\n",
- "- What time of the day is the pressure highest (on average)?\n",
- " \n",
- "- What has the highest impact on the pressure, the daily or the yearly periodic signal?\n",
- "\n",
- "</p>\n",
- "</div>"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "_Your answer here._"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p> <b>Solution:</b> \n",
- "<p>\n",
- "parameters make sense. The average pressure is about 1013 hPa. The pressure is highest at 6:00/7:00. The yearly periodic signal has the highest impact on the pressure.\n",
- "</p>\n",
- "</div>"
+ "<div style=\"background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%\"> <p>Task 4.2 was moved above in the notebook, since it made more sense to interpret the parameters earlier.</p></div>"
]
},
{
diff --git a/src/students/Week_2_4/WS_2_4_solution.html b/src/students/Week_2_4/WS_2_4_solution.html
new file mode 100644
index 00000000..964d8949
--- /dev/null
+++ b/src/students/Week_2_4/WS_2_4_solution.html
@@ -0,0 +1,8670 @@
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+}
+
+.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle:after {
+ top: 50%;
+ min-height: 8px;
+ transform: translateY(-50%);
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabBar {
+ display: flex;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] {
+ flex-direction: row;
+ align-items: flex-end;
+}
+
+.lm-TabBar[data-orientation='vertical'] {
+ flex-direction: column;
+ align-items: flex-end;
+}
+
+.lm-TabBar-content {
+ margin: 0;
+ padding: 0;
+ display: flex;
+ flex: 1 1 auto;
+ list-style-type: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] > .lm-TabBar-content {
+ flex-direction: row;
+}
+
+.lm-TabBar[data-orientation='vertical'] > .lm-TabBar-content {
+ flex-direction: column;
+}
+
+.lm-TabBar-tab {
+ display: flex;
+ flex-direction: row;
+ box-sizing: border-box;
+ overflow: hidden;
+ touch-action: none; /* Disable native Drag/Drop */
+}
+
+.lm-TabBar-tabIcon,
+.lm-TabBar-tabCloseIcon {
+ flex: 0 0 auto;
+}
+
+.lm-TabBar-tabLabel {
+ flex: 1 1 auto;
+ overflow: hidden;
+ white-space: nowrap;
+}
+
+.lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+}
+
+.lm-TabBar-tab.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar-addButton.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab {
+ position: relative;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab {
+ left: 0;
+ transition: left 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab {
+ top: 0;
+ transition: top 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging {
+ transition: none;
+}
+
+.lm-TabBar-tabLabel .lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+ background: inherit;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabPanel-tabBar {
+ z-index: 1;
+}
+
+.lm-TabPanel-stackedPanel {
+ z-index: 0;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Collapse {
+ display: flex;
+ flex-direction: column;
+ align-items: stretch;
+}
+
+.jp-Collapse-header {
+ padding: 1px 12px;
+ background-color: var(--jp-layout-color1);
+ border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
+ color: var(--jp-ui-font-color1);
+ cursor: pointer;
+ display: flex;
+ align-items: center;
+ font-size: var(--jp-ui-font-size0);
+ font-weight: 600;
+ text-transform: uppercase;
+ user-select: none;
+}
+
+.jp-Collapser-icon {
+ height: 16px;
+}
+
+.jp-Collapse-header-collapsed .jp-Collapser-icon {
+ transform: rotate(-90deg);
+ margin: auto 0;
+}
+
+.jp-Collapser-title {
+ line-height: 25px;
+}
+
+.jp-Collapse-contents {
+ padding: 0 12px;
+ background-color: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ overflow: auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/* This file was auto-generated by ensureUiComponents() in @jupyterlab/buildutils */
+
+/**
+ * (DEPRECATED) Support for consuming icons as CSS background images
+ */
+
+/* Icons urls */
+
+:root {
+ --jp-icon-add-above: url(data:image/svg+xml;base64,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);
+ --jp-icon-add-below: url(data:image/svg+xml;base64,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);
+ --jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-bell: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug: url(data:image/svg+xml;base64,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);
+ --jp-icon-build: url(data:image/svg+xml;base64,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);
+ --jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-caret-right: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik03LjIsNS4yTDEwLjksOWwtMy44LDMuOFY1LjJINy4yeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-caret-up-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iMTUuNCwxMy4zIDkuOSw3LjcgNC40LDEzLjIgMy42LDEyLjUgOS45LDYuMyAxNi4xLDEyLjYgIi8+Cgk8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-caret-up: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik01LjIsMTAuNUw5LDYuOGwzLjgsMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-case-sensitive: url(data:image/svg+xml;base64,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);
+ --jp-icon-check: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik05IDE2LjE3TDQuODMgMTJsLTEuNDIgMS40MUw5IDE5IDIxIDdsLTEuNDEtMS40MXoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-circle-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDJDNi40NyAyIDIgNi40NyAyIDEyczQuNDcgMTAgMTAgMTAgMTAtNC40NyAxMC0xMFMxNy41MyAyIDEyIDJ6bTAgMThjLTQuNDEgMC04LTMuNTktOC04czMuNTktOCA4LTggOCAzLjU5IDggOC0zLjU5IDgtOCA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-circle: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMTggMTgiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPGNpcmNsZSBjeD0iOSIgY3k9IjkiIHI9IjgiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-clear: url(data:image/svg+xml;base64,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);
+ --jp-icon-close: url(data:image/svg+xml;base64,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);
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+ --jp-icon-file-upload: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTkgMTZoNnYtNmg0bC03LTctNyA3aDR6bS00IDJoMTR2Mkg1eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-file: url(data:image/svg+xml;base64,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);
+ --jp-icon-filter-dot: url(data:image/svg+xml;base64,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);
+ --jp-icon-filter-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEwIDE4aDR2LTJoLTR2MnpNMyA2djJoMThWNkgzem0zIDdoMTJ2LTJINnYyeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-filter: url(data:image/svg+xml;base64,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);
+ --jp-icon-folder-favorite: url(data:image/svg+xml;base64,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);
+ --jp-icon-folder: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTAgNEg0Yy0xLjEgMC0xLjk5LjktMS45OSAyTDIgMThjMCAxLjEuOSAyIDIgMmgxNmMxLjEgMCAyLS45IDItMlY4YzAtMS4xLS45LTItMi0yaC04bC0yLTJ6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-home: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjRweCIgdmlld0JveD0iMCAwIDI0IDI0IiB3aWR0aD0iMjRweCIgZmlsbD0iIzAwMDAwMCI+CiAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPjxwYXRoIGNsYXNzPSJqcC1pY29uMyBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xMCAyMHYtNmg0djZoNXYtOGgzTDEyIDMgMiAxMmgzdjh6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-html5: url(data:image/svg+xml;base64,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);
+ --jp-icon-image: url(data:image/svg+xml;base64,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);
+ --jp-icon-info: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDUwLjk3OCA1MC45NzgiPgoJPGcgY2xhc3M9ImpwLWljb24zIiBmaWxsPSIjNjE2MTYxIj4KCQk8cGF0aCBkPSJNNDMuNTIsNy40NThDMzguNzExLDIuNjQ4LDMyLjMwNywwLDI1LjQ4OSwwQzE4LjY3LDAsMTIuMjY2LDIuNjQ4LDcuNDU4LDcuNDU4CgkJCWMtOS45NDMsOS45NDEtOS45NDMsMjYuMTE5LDAsMzYuMDYyYzQuODA5LDQuODA5LDExLjIxMiw3LjQ1NiwxOC4wMzEsNy40NThjMCwwLDAuMDAxLDAsMC4wMDIsMAoJCQljNi44MTYsMCwxMy4yMjEtMi42NDgsMTguMDI5LTcuNDU4YzQuODA5LTQuODA5LDcuNDU3LTExLjIxMiw3LjQ1Ny0xOC4wM0M1MC45NzcsMTguNjcsNDguMzI4LDEyLjI2Niw0My41Miw3LjQ1OHoKCQkJIE00Mi4xMDYsNDIuMTA1Yy00LjQzMiw0LjQzMS0xMC4zMzIsNi44NzItMTYuNjE1LDYuODcyaC0wLjAwMmMtNi4yODUtMC4wMDEtMTIuMTg3LTIuNDQxLTE2LjYxNy02Ljg3MgoJCQljLTkuMTYyLTkuMTYzLTkuMTYyLTI0LjA3MSwwLTMzLjIzM0MxMy4zMDMsNC40NCwxOS4yMDQsMiwyNS40ODksMmM2LjI4NCwwLDEyLjE4NiwyLjQ0LDE2LjYxNyw2Ljg3MgoJCQljNC40MzEsNC40MzEsNi44NzEsMTAuMzMyLDYuODcxLDE2LjYxN0M0OC45NzcsMzEuNzcyLDQ2LjUzNiwzNy42NzUsNDIuMTA2LDQyLjEwNXoiLz4KCQk8cGF0aCBkPSJNMjMuNTc4LDMyLjIxOGMtMC4wMjMtMS43MzQsMC4xNDMtMy4wNTksMC40OTYtMy45NzJjMC4zNTMtMC45MTMsMS4xMS0xLjk5NywyLjI3Mi0zLjI1MwoJCQljMC40NjgtMC41MzYsMC45MjMtMS4wNjIsMS4zNjctMS41NzVjMC42MjYtMC43NTMsMS4xMDQtMS40NzgsMS40MzYtMi4xNzVjMC4zMzEtMC43MDcsMC40OTUtMS41NDEsMC40OTUtMi41CgkJCWMwLTEuMDk2LTAuMjYtMi4wODgtMC43NzktMi45NzljLTAuNTY1LTAuODc5LTEuNTAxLTEuMzM2LTIuODA2LTEuMzY5Yy0xLjgwMiwwLjA1Ny0yLjk4NSwwLjY2Ny0zLjU1LDEuODMyCgkJCWMtMC4zMDEsMC41MzUtMC41MDMsMS4xNDEtMC42MDcsMS44MTRjLTAuMTM5LDAuNzA3LTAuMjA3LDEuNDMyLTAuMjA3LDIuMTc0aC0yLjkzN2MtMC4wOTEtMi4yMDgsMC40MDctNC4xMTQsMS40OTMtNS43MTkKCQkJYzEuMDYyLTEuNjQsMi44NTUtMi40ODEsNS4zNzgtMi41MjdjMi4xNiwwLjAyMywzLjg3NCwwLjYwOCw1LjE0MSwxLjc1OGMxLjI3OCwxLjE2LDEuOTI5LDIuNzY0LDEuOTUsNC44MTEKCQkJYzAsMS4xNDItMC4xMzcsMi4xMTEtMC40MSwyLjkxMWMtMC4zMDksMC44NDUtMC43MzEsMS41OTMtMS4yNjgsMi4yNDNjLTAuNDkyLDAuNjUtMS4wNjgsMS4zMTgtMS43MywyLjAwMgoJCQljLTAuNjUsMC42OTctMS4zMTMsMS40NzktMS45ODcsMi4zNDZjLTAuMjM5LDAuMzc3LTAuNDI5LDAuNzc3LTAuNTY1LDEuMTk5Yy0wLjE2LDAuOTU5LTAuMjE3LDEuOTUxLTAuMTcxLDIuOTc5CgkJCUMyNi41ODksMzIuMjE4LDIzLjU3OCwzMi4yMTgsMjMuNTc4LDMyLjIxOHogTTIzLjU3OCwzOC4yMnYtMy40ODRoMy4wNzZ2My40ODRIMjMuNTc4eiIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-inspector: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaW5zcGVjdG9yLWljb24tY29sb3IganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMjAgNEg0Yy0xLjEgMC0xLjk5LjktMS45OSAyTDIgMThjMCAxLjEuOSAyIDIgMmgxNmMxLjEgMCAyLS45IDItMlY2YzAtMS4xLS45LTItMi0yem0tNSAxNEg0di00aDExdjR6bTAtNUg0VjloMTF2NHptNSA1aC00VjloNHY5eiIvPgo8L3N2Zz4K);
+ --jp-icon-json: url(data:image/svg+xml;base64,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);
+ --jp-icon-julia: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDMyNSAzMDAiPgogIDxnIGNsYXNzPSJqcC1icmFuZDAganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjY2IzYzMzIj4KICAgIDxwYXRoIGQ9Ik0gMTUwLjg5ODQzOCAyMjUgQyAxNTAuODk4NDM4IDI2Ni40MjE4NzUgMTE3LjMyMDMxMiAzMDAgNzUuODk4NDM4IDMwMCBDIDM0LjQ3NjU2MiAzMDAgMC44OTg0MzggMjY2LjQyMTg3NSAwLjg5ODQzOCAyMjUgQyAwLjg5ODQzOCAxODMuNTc4MTI1IDM0LjQ3NjU2MiAxNTAgNzUuODk4NDM4IDE1MCBDIDExNy4zMjAzMTIgMTUwIDE1MC44OTg0MzggMTgzLjU3ODEyNSAxNTAuODk4NDM4IDIyNSIvPgogIDwvZz4KICA8ZyBjbGFzcz0ianAtYnJhbmQwIGpwLWljb24tc2VsZWN0YWJsZSIgZmlsbD0iIzM4OTgyNiI+CiAgICA8cGF0aCBkPSJNIDIzNy41IDc1IEMgMjM3LjUgMTE2LjQyMTg3NSAyMDMuOTIxODc1IDE1MCAxNjIuNSAxNTAgQyAxMjEuMDc4MTI1IDE1MCA4Ny41IDExNi40MjE4NzUgODcuNSA3NSBDIDg3LjUgMzMuNTc4MTI1IDEyMS4wNzgxMjUgMCAxNjIuNSAwIEMgMjAzLjkyMTg3NSAwIDIzNy41IDMzLjU3ODEyNSAyMzcuNSA3NSIvPgogIDwvZz4KICA8ZyBjbGFzcz0ianAtYnJhbmQwIGpwLWljb24tc2VsZWN0YWJsZSIgZmlsbD0iIzk1NThiMiI+CiAgICA8cGF0aCBkPSJNIDMyNC4xMDE1NjIgMjI1IEMgMzI0LjEwMTU2MiAyNjYuNDIxODc1IDI5MC41MjM0MzggMzAwIDI0OS4xMDE1NjIgMzAwIEMgMjA3LjY3OTY4OCAzMDAgMTc0LjEwMTU2MiAyNjYuNDIxODc1IDE3NC4xMDE1NjIgMjI1IEMgMTc0LjEwMTU2MiAxODMuNTc4MTI1IDIwNy42Nzk2ODggMTUwIDI0OS4xMDE1NjIgMTUwIEMgMjkwLjUyMzQzOCAxNTAgMzI0LjEwMTU2MiAxODMuNTc4MTI1IDMyNC4xMDE1NjIgMjI1Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-jupyter-favicon: url(data:image/svg+xml;base64,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);
+ --jp-icon-jupyter: url(data:image/svg+xml;base64,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);
+ --jp-icon-jupyterlab-wordmark: 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+ --jp-icon-kernel: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzYxNjE2MSIgZD0iTTE1IDlIOXY2aDZWOXptLTIgNGgtMnYtMmgydjJ6bTgtMlY5aC0yVjdjMC0xLjEtLjktMi0yLTJoLTJWM2gtMnYyaC0yVjNIOXYySDdjLTEuMSAwLTIgLjktMiAydjJIM3YyaDJ2MkgzdjJoMnYyYzAgMS4xLjkgMiAyIDJoMnYyaDJ2LTJoMnYyaDJ2LTJoMmMxLjEgMCAyLS45IDItMnYtMmgydi0yaC0ydi0yaDJ6bS00IDZIN1Y3aDEwdjEweiIvPgo8L3N2Zz4K);
+ --jp-icon-keyboard: url(data:image/svg+xml;base64,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);
+ --jp-icon-launch: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMzIgMzIiIHdpZHRoPSIzMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yNiwyOEg2YTIuMDAyNywyLjAwMjcsMCwwLDEtMi0yVjZBMi4wMDI3LDIuMDAyNywwLDAsMSw2LDRIMTZWNkg2VjI2SDI2VjE2aDJWMjZBMi4wMDI3LDIuMDAyNywwLDAsMSwyNiwyOFoiLz4KICAgIDxwb2x5Z29uIHBvaW50cz0iMjAgMiAyMCA0IDI2LjU4NiA0IDE4IDEyLjU4NiAxOS40MTQgMTQgMjggNS40MTQgMjggMTIgMzAgMTIgMzAgMiAyMCAyIi8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-launcher: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkgMTlINVY1aDdWM0g1YTIgMiAwIDAwLTIgMnYxNGEyIDIgMCAwMDIgMmgxNGMxLjEgMCAyLS45IDItMnYtN2gtMnY3ek0xNCAzdjJoMy41OWwtOS44MyA5LjgzIDEuNDEgMS40MUwxOSA2LjQxVjEwaDJWM2gtN3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-line-form: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGZpbGw9IndoaXRlIiBkPSJNNS44OCA0LjEyTDEzLjc2IDEybC03Ljg4IDcuODhMOCAyMmwxMC0xMEw4IDJ6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-link: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTMuOSAxMmMwLTEuNzEgMS4zOS0zLjEgMy4xLTMuMWg0VjdIN2MtMi43NiAwLTUgMi4yNC01IDVzMi4yNCA1IDUgNWg0di0xLjlIN2MtMS43MSAwLTMuMS0xLjM5LTMuMS0zLjF6TTggMTNoOHYtMkg4djJ6bTktNmgtNHYxLjloNGMxLjcxIDAgMy4xIDEuMzkgMy4xIDMuMXMtMS4zOSAzLjEtMy4xIDMuMWgtNFYxN2g0YzIuNzYgMCA1LTIuMjQgNS01cy0yLjI0LTUtNS01eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xOSA1djE0SDVWNWgxNG0xLjEtMkgzLjljLS41IDAtLjkuNC0uOS45djE2LjJjMCAuNC40LjkuOS45aDE2LjJjLjQgMCAuOS0uNS45LS45VjMuOWMwLS41LS41LS45LS45LS45ek0xMSA3aDZ2MmgtNlY3em0wIDRoNnYyaC02di0yem0wIDRoNnYyaC02ek03IDdoMnYySDd6bTAgNGgydjJIN3ptMCA0aDJ2Mkg3eiIvPgo8L3N2Zz4K);
+ --jp-icon-markdown: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-down: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-up: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTQiIGhlaWdodD0iMTQiIHZpZXdCb3g9IjAgMCAxNCAxNCIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggY2xhc3M9ImpwLWljb24zIiBkPSJNMS41Mjg5OSA2LjQ3MTAxQzEuMjM2ODQgNi43NjMxNiAxLjIzNjg0IDcuMjM2ODQgMS41Mjg5OSA3LjUyODk5VjcuNTI4OTlDMS44MjA5NSA3LjgyMDk1IDIuMjk0MjYgNy44MjExNiAyLjU4NjQ5IDcuNTI5NDZMNi4yNSAzLjg3MjVWMTIuMjVDNi4yNSAxMi42NjQyIDYuNTg1NzkgMTMgNyAxM1YxM0M3LjQxNDIxIDEzIDcuNzUgMTIuNjY0MiA3Ljc1IDEyLjI1VjMuODcyNUwxMS40MDI3IDcuNTMxNzhDMTEuNjk2NiA3LjgyNjE5IDEyLjE3MzYgNy44MjY0MSAxMi40Njc3IDcuNTMyMjZWNy41MzIyNkMxMi43NjE3IDcuMjM4MyAxMi43NjE3IDYuNzYxNyAxMi40Njc3IDYuNDY3NzRMNy43MDcxMSAxLjcwNzExQzcuMzE2NTggMS4zMTY1OCA2LjY4MzQyIDEuMzE2NTggNi4yOTI4OSAxLjcwNzExTDEuNTI4OTkgNi40NzEwMVoiIGZpbGw9IiM2MTYxNjEiLz4KPC9zdmc+Cg==);
+ --jp-icon-new-folder: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIwIDZoLThsLTItMkg0Yy0xLjExIDAtMS45OS44OS0xLjk5IDJMMiAxOGMwIDEuMTEuODkgMiAyIDJoMTZjMS4xMSAwIDItLjg5IDItMlY4YzAtMS4xMS0uODktMi0yLTJ6bS0xIDhoLTN2M2gtMnYtM2gtM3YtMmgzVjloMnYzaDN2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-not-trusted: url(data:image/svg+xml;base64,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);
+ --jp-icon-notebook: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtbm90ZWJvb2staWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiNFRjZDMDAiPgogICAgPHBhdGggZD0iTTE4LjcgMy4zdjE1LjRIMy4zVjMuM2gxNS40bTEuNS0xLjVIMS44djE4LjNoMTguM2wuMS0xOC4zeiIvPgogICAgPHBhdGggZD0iTTE2LjUgMTYuNWwtNS40LTQuMy01LjYgNC4zdi0xMWgxMXoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-numbering: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTQgMTlINlYxOS41SDVWMjAuNUg2VjIxSDRWMjJIN1YxOEg0VjE5Wk01IDEwSDZWNkg0VjdINVYxMFpNNCAxM0g1LjhMNCAxNS4xVjE2SDdWMTVINS4yTDcgMTIuOVYxMkg0VjEzWk05IDdWOUgyM1Y3SDlaTTkgMjFIMjNWMTlIOVYyMVpNOSAxNUgyM1YxM0g5VjE1WiIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-offline-bolt: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDIuMDJjLTUuNTEgMC05Ljk4IDQuNDctOS45OCA5Ljk4czQuNDcgOS45OCA5Ljk4IDkuOTggOS45OC00LjQ3IDkuOTgtOS45OFMxNy41MSAyLjAyIDEyIDIuMDJ6TTExLjQ4IDIwdi02LjI2SDhMMTMgNHY2LjI2aDMuMzVMMTEuNDggMjB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-palette: url(data:image/svg+xml;base64,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);
+ --jp-icon-paste: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE5IDJoLTQuMThDMTQuNC44NCAxMy4zIDAgMTIgMGMtMS4zIDAtMi40Ljg0LTIuODIgMkg1Yy0xLjEgMC0yIC45LTIgMnYxNmMwIDEuMS45IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjRjMC0xLjEtLjktMi0yLTJ6bS03IDBjLjU1IDAgMSAuNDUgMSAxcy0uNDUgMS0xIDEtMS0uNDUtMS0xIC40NS0xIDEtMXptNyAxOEg1VjRoMnYzaDEwVjRoMnYxNnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-pdf: url(data:image/svg+xml;base64,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);
+ --jp-icon-python: url(data:image/svg+xml;base64,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);
+ --jp-icon-r-kernel: url(data:image/svg+xml;base64,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);
+ --jp-icon-react: url(data:image/svg+xml;base64,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);
+ --jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-regex: url(data:image/svg+xml;base64,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);
+ --jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-running: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDUxMiA1MTIiPgogIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICA8cGF0aCBkPSJNMjU2IDhDMTE5IDggOCAxMTkgOCAyNTZzMTExIDI0OCAyNDggMjQ4IDI0OC0xMTEgMjQ4LTI0OFMzOTMgOCAyNTYgOHptOTYgMzI4YzAgOC44LTcuMiAxNi0xNiAxNkgxNzZjLTguOCAwLTE2LTcuMi0xNi0xNlYxNzZjMC04LjggNy4yLTE2IDE2LTE2aDE2MGM4LjggMCAxNiA3LjIgMTYgMTZ2MTYweiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-search: url(data:image/svg+xml;base64,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);
+ --jp-icon-settings: url(data:image/svg+xml;base64,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);
+ --jp-icon-share: url(data:image/svg+xml;base64,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);
+ --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-table-rows: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMSw4SDNWNGgxOFY4eiBNMjEsMTBIM3Y0aDE4VjEweiBNMjEsMTZIM3Y0aDE4VjE2eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-tag: url(data:image/svg+xml;base64,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);
+ --jp-icon-terminal: url(data:image/svg+xml;base64,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);
+ --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-toc: url(data:image/svg+xml;base64,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);
+ --jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-trusted: url(data:image/svg+xml;base64,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);
+ --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-users: url(data:image/svg+xml;base64,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);
+ --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-word: url(data:image/svg+xml;base64,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);
+ --jp-icon-yaml: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbi1jb250cmFzdDIganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjRDgxQjYwIj4KICAgIDxwYXRoIGQ9Ik03LjIgMTguNnYtNS40TDMgNS42aDMuM2wxLjQgMy4xYy4zLjkuNiAxLjYgMSAyLjUuMy0uOC42LTEuNiAxLTIuNWwxLjQtMy4xaDMuNGwtNC40IDcuNnY1LjVsLTIuOS0uMXoiLz4KICAgIDxjaXJjbGUgY2xhc3M9InN0MCIgY3g9IjE3LjYiIGN5PSIxNi41IiByPSIyLjEiLz4KICAgIDxjaXJjbGUgY2xhc3M9InN0MCIgY3g9IjE3LjYiIGN5PSIxMSIgcj0iMi4xIi8+CiAgPC9nPgo8L3N2Zz4K);
+}
+
+/* Icon CSS class declarations */
+
+.jp-AddAboveIcon {
+ background-image: var(--jp-icon-add-above);
+}
+
+.jp-AddBelowIcon {
+ background-image: var(--jp-icon-add-below);
+}
+
+.jp-AddIcon {
+ background-image: var(--jp-icon-add);
+}
+
+.jp-BellIcon {
+ background-image: var(--jp-icon-bell);
+}
+
+.jp-BugDotIcon {
+ background-image: var(--jp-icon-bug-dot);
+}
+
+.jp-BugIcon {
+ background-image: var(--jp-icon-bug);
+}
+
+.jp-BuildIcon {
+ background-image: var(--jp-icon-build);
+}
+
+.jp-CaretDownEmptyIcon {
+ background-image: var(--jp-icon-caret-down-empty);
+}
+
+.jp-CaretDownEmptyThinIcon {
+ background-image: var(--jp-icon-caret-down-empty-thin);
+}
+
+.jp-CaretDownIcon {
+ background-image: var(--jp-icon-caret-down);
+}
+
+.jp-CaretLeftIcon {
+ background-image: var(--jp-icon-caret-left);
+}
+
+.jp-CaretRightIcon {
+ background-image: var(--jp-icon-caret-right);
+}
+
+.jp-CaretUpEmptyThinIcon {
+ background-image: var(--jp-icon-caret-up-empty-thin);
+}
+
+.jp-CaretUpIcon {
+ background-image: var(--jp-icon-caret-up);
+}
+
+.jp-CaseSensitiveIcon {
+ background-image: var(--jp-icon-case-sensitive);
+}
+
+.jp-CheckIcon {
+ background-image: var(--jp-icon-check);
+}
+
+.jp-CircleEmptyIcon {
+ background-image: var(--jp-icon-circle-empty);
+}
+
+.jp-CircleIcon {
+ background-image: var(--jp-icon-circle);
+}
+
+.jp-ClearIcon {
+ background-image: var(--jp-icon-clear);
+}
+
+.jp-CloseIcon {
+ background-image: var(--jp-icon-close);
+}
+
+.jp-CodeCheckIcon {
+ background-image: var(--jp-icon-code-check);
+}
+
+.jp-CodeIcon {
+ background-image: var(--jp-icon-code);
+}
+
+.jp-CollapseAllIcon {
+ background-image: var(--jp-icon-collapse-all);
+}
+
+.jp-ConsoleIcon {
+ background-image: var(--jp-icon-console);
+}
+
+.jp-CopyIcon {
+ background-image: var(--jp-icon-copy);
+}
+
+.jp-CopyrightIcon {
+ background-image: var(--jp-icon-copyright);
+}
+
+.jp-CutIcon {
+ background-image: var(--jp-icon-cut);
+}
+
+.jp-DeleteIcon {
+ background-image: var(--jp-icon-delete);
+}
+
+.jp-DownloadIcon {
+ background-image: var(--jp-icon-download);
+}
+
+.jp-DuplicateIcon {
+ background-image: var(--jp-icon-duplicate);
+}
+
+.jp-EditIcon {
+ background-image: var(--jp-icon-edit);
+}
+
+.jp-EllipsesIcon {
+ background-image: var(--jp-icon-ellipses);
+}
+
+.jp-ErrorIcon {
+ background-image: var(--jp-icon-error);
+}
+
+.jp-ExpandAllIcon {
+ background-image: var(--jp-icon-expand-all);
+}
+
+.jp-ExtensionIcon {
+ background-image: var(--jp-icon-extension);
+}
+
+.jp-FastForwardIcon {
+ background-image: var(--jp-icon-fast-forward);
+}
+
+.jp-FileIcon {
+ background-image: var(--jp-icon-file);
+}
+
+.jp-FileUploadIcon {
+ background-image: var(--jp-icon-file-upload);
+}
+
+.jp-FilterDotIcon {
+ background-image: var(--jp-icon-filter-dot);
+}
+
+.jp-FilterIcon {
+ background-image: var(--jp-icon-filter);
+}
+
+.jp-FilterListIcon {
+ background-image: var(--jp-icon-filter-list);
+}
+
+.jp-FolderFavoriteIcon {
+ background-image: var(--jp-icon-folder-favorite);
+}
+
+.jp-FolderIcon {
+ background-image: var(--jp-icon-folder);
+}
+
+.jp-HomeIcon {
+ background-image: var(--jp-icon-home);
+}
+
+.jp-Html5Icon {
+ background-image: var(--jp-icon-html5);
+}
+
+.jp-ImageIcon {
+ background-image: var(--jp-icon-image);
+}
+
+.jp-InfoIcon {
+ background-image: var(--jp-icon-info);
+}
+
+.jp-InspectorIcon {
+ background-image: var(--jp-icon-inspector);
+}
+
+.jp-JsonIcon {
+ background-image: var(--jp-icon-json);
+}
+
+.jp-JuliaIcon {
+ background-image: var(--jp-icon-julia);
+}
+
+.jp-JupyterFaviconIcon {
+ background-image: var(--jp-icon-jupyter-favicon);
+}
+
+.jp-JupyterIcon {
+ background-image: var(--jp-icon-jupyter);
+}
+
+.jp-JupyterlabWordmarkIcon {
+ background-image: var(--jp-icon-jupyterlab-wordmark);
+}
+
+.jp-KernelIcon {
+ background-image: var(--jp-icon-kernel);
+}
+
+.jp-KeyboardIcon {
+ background-image: var(--jp-icon-keyboard);
+}
+
+.jp-LaunchIcon {
+ background-image: var(--jp-icon-launch);
+}
+
+.jp-LauncherIcon {
+ background-image: var(--jp-icon-launcher);
+}
+
+.jp-LineFormIcon {
+ background-image: var(--jp-icon-line-form);
+}
+
+.jp-LinkIcon {
+ background-image: var(--jp-icon-link);
+}
+
+.jp-ListIcon {
+ background-image: var(--jp-icon-list);
+}
+
+.jp-MarkdownIcon {
+ background-image: var(--jp-icon-markdown);
+}
+
+.jp-MoveDownIcon {
+ background-image: var(--jp-icon-move-down);
+}
+
+.jp-MoveUpIcon {
+ background-image: var(--jp-icon-move-up);
+}
+
+.jp-NewFolderIcon {
+ background-image: var(--jp-icon-new-folder);
+}
+
+.jp-NotTrustedIcon {
+ background-image: var(--jp-icon-not-trusted);
+}
+
+.jp-NotebookIcon {
+ background-image: var(--jp-icon-notebook);
+}
+
+.jp-NumberingIcon {
+ background-image: var(--jp-icon-numbering);
+}
+
+.jp-OfflineBoltIcon {
+ background-image: var(--jp-icon-offline-bolt);
+}
+
+.jp-PaletteIcon {
+ background-image: var(--jp-icon-palette);
+}
+
+.jp-PasteIcon {
+ background-image: var(--jp-icon-paste);
+}
+
+.jp-PdfIcon {
+ background-image: var(--jp-icon-pdf);
+}
+
+.jp-PythonIcon {
+ background-image: var(--jp-icon-python);
+}
+
+.jp-RKernelIcon {
+ background-image: var(--jp-icon-r-kernel);
+}
+
+.jp-ReactIcon {
+ background-image: var(--jp-icon-react);
+}
+
+.jp-RedoIcon {
+ background-image: var(--jp-icon-redo);
+}
+
+.jp-RefreshIcon {
+ background-image: var(--jp-icon-refresh);
+}
+
+.jp-RegexIcon {
+ background-image: var(--jp-icon-regex);
+}
+
+.jp-RunIcon {
+ background-image: var(--jp-icon-run);
+}
+
+.jp-RunningIcon {
+ background-image: var(--jp-icon-running);
+}
+
+.jp-SaveIcon {
+ background-image: var(--jp-icon-save);
+}
+
+.jp-SearchIcon {
+ background-image: var(--jp-icon-search);
+}
+
+.jp-SettingsIcon {
+ background-image: var(--jp-icon-settings);
+}
+
+.jp-ShareIcon {
+ background-image: var(--jp-icon-share);
+}
+
+.jp-SpreadsheetIcon {
+ background-image: var(--jp-icon-spreadsheet);
+}
+
+.jp-StopIcon {
+ background-image: var(--jp-icon-stop);
+}
+
+.jp-TabIcon {
+ background-image: var(--jp-icon-tab);
+}
+
+.jp-TableRowsIcon {
+ background-image: var(--jp-icon-table-rows);
+}
+
+.jp-TagIcon {
+ background-image: var(--jp-icon-tag);
+}
+
+.jp-TerminalIcon {
+ background-image: var(--jp-icon-terminal);
+}
+
+.jp-TextEditorIcon {
+ background-image: var(--jp-icon-text-editor);
+}
+
+.jp-TocIcon {
+ background-image: var(--jp-icon-toc);
+}
+
+.jp-TreeViewIcon {
+ background-image: var(--jp-icon-tree-view);
+}
+
+.jp-TrustedIcon {
+ background-image: var(--jp-icon-trusted);
+}
+
+.jp-UndoIcon {
+ background-image: var(--jp-icon-undo);
+}
+
+.jp-UserIcon {
+ background-image: var(--jp-icon-user);
+}
+
+.jp-UsersIcon {
+ background-image: var(--jp-icon-users);
+}
+
+.jp-VegaIcon {
+ background-image: var(--jp-icon-vega);
+}
+
+.jp-WordIcon {
+ background-image: var(--jp-icon-word);
+}
+
+.jp-YamlIcon {
+ background-image: var(--jp-icon-yaml);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/**
+ * (DEPRECATED) Support for consuming icons as CSS background images
+ */
+
+.jp-Icon,
+.jp-MaterialIcon {
+ background-position: center;
+ background-repeat: no-repeat;
+ background-size: 16px;
+ min-width: 16px;
+ min-height: 16px;
+}
+
+.jp-Icon-cover {
+ background-position: center;
+ background-repeat: no-repeat;
+ background-size: cover;
+}
+
+/**
+ * (DEPRECATED) Support for specific CSS icon sizes
+ */
+
+.jp-Icon-16 {
+ background-size: 16px;
+ min-width: 16px;
+ min-height: 16px;
+}
+
+.jp-Icon-18 {
+ background-size: 18px;
+ min-width: 18px;
+ min-height: 18px;
+}
+
+.jp-Icon-20 {
+ background-size: 20px;
+ min-width: 20px;
+ min-height: 20px;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.lm-TabBar .lm-TabBar-addButton {
+ align-items: center;
+ display: flex;
+ padding: 4px;
+ padding-bottom: 5px;
+ margin-right: 1px;
+ background-color: var(--jp-layout-color2);
+}
+
+.lm-TabBar .lm-TabBar-addButton:hover {
+ background-color: var(--jp-layout-color1);
+}
+
+.lm-DockPanel-tabBar .lm-TabBar-tab {
+ width: var(--jp-private-horizontal-tab-width);
+}
+
+.lm-DockPanel-tabBar .lm-TabBar-content {
+ flex: unset;
+}
+
+.lm-DockPanel-tabBar[data-orientation='horizontal'] {
+ flex: 1 1 auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/**
+ * Support for icons as inline SVG HTMLElements
+ */
+
+/* recolor the primary elements of an icon */
+.jp-icon0[fill] {
+ fill: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon1[fill] {
+ fill: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon2[fill] {
+ fill: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon3[fill] {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon4[fill] {
+ fill: var(--jp-inverse-layout-color4);
+}
+
+.jp-icon0[stroke] {
+ stroke: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon1[stroke] {
+ stroke: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon2[stroke] {
+ stroke: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon3[stroke] {
+ stroke: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon4[stroke] {
+ stroke: var(--jp-inverse-layout-color4);
+}
+
+/* recolor the accent elements of an icon */
+.jp-icon-accent0[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.jp-icon-accent1[fill] {
+ fill: var(--jp-layout-color1);
+}
+
+.jp-icon-accent2[fill] {
+ fill: var(--jp-layout-color2);
+}
+
+.jp-icon-accent3[fill] {
+ fill: var(--jp-layout-color3);
+}
+
+.jp-icon-accent4[fill] {
+ fill: var(--jp-layout-color4);
+}
+
+.jp-icon-accent0[stroke] {
+ stroke: var(--jp-layout-color0);
+}
+
+.jp-icon-accent1[stroke] {
+ stroke: var(--jp-layout-color1);
+}
+
+.jp-icon-accent2[stroke] {
+ stroke: var(--jp-layout-color2);
+}
+
+.jp-icon-accent3[stroke] {
+ stroke: var(--jp-layout-color3);
+}
+
+.jp-icon-accent4[stroke] {
+ stroke: var(--jp-layout-color4);
+}
+
+/* set the color of an icon to transparent */
+.jp-icon-none[fill] {
+ fill: none;
+}
+
+.jp-icon-none[stroke] {
+ stroke: none;
+}
+
+/* brand icon colors. Same for light and dark */
+.jp-icon-brand0[fill] {
+ fill: var(--jp-brand-color0);
+}
+
+.jp-icon-brand1[fill] {
+ fill: var(--jp-brand-color1);
+}
+
+.jp-icon-brand2[fill] {
+ fill: var(--jp-brand-color2);
+}
+
+.jp-icon-brand3[fill] {
+ fill: var(--jp-brand-color3);
+}
+
+.jp-icon-brand4[fill] {
+ fill: var(--jp-brand-color4);
+}
+
+.jp-icon-brand0[stroke] {
+ stroke: var(--jp-brand-color0);
+}
+
+.jp-icon-brand1[stroke] {
+ stroke: var(--jp-brand-color1);
+}
+
+.jp-icon-brand2[stroke] {
+ stroke: var(--jp-brand-color2);
+}
+
+.jp-icon-brand3[stroke] {
+ stroke: var(--jp-brand-color3);
+}
+
+.jp-icon-brand4[stroke] {
+ stroke: var(--jp-brand-color4);
+}
+
+/* warn icon colors. Same for light and dark */
+.jp-icon-warn0[fill] {
+ fill: var(--jp-warn-color0);
+}
+
+.jp-icon-warn1[fill] {
+ fill: var(--jp-warn-color1);
+}
+
+.jp-icon-warn2[fill] {
+ fill: var(--jp-warn-color2);
+}
+
+.jp-icon-warn3[fill] {
+ fill: var(--jp-warn-color3);
+}
+
+.jp-icon-warn0[stroke] {
+ stroke: var(--jp-warn-color0);
+}
+
+.jp-icon-warn1[stroke] {
+ stroke: var(--jp-warn-color1);
+}
+
+.jp-icon-warn2[stroke] {
+ stroke: var(--jp-warn-color2);
+}
+
+.jp-icon-warn3[stroke] {
+ stroke: var(--jp-warn-color3);
+}
+
+/* icon colors that contrast well with each other and most backgrounds */
+.jp-icon-contrast0[fill] {
+ fill: var(--jp-icon-contrast-color0);
+}
+
+.jp-icon-contrast1[fill] {
+ fill: var(--jp-icon-contrast-color1);
+}
+
+.jp-icon-contrast2[fill] {
+ fill: var(--jp-icon-contrast-color2);
+}
+
+.jp-icon-contrast3[fill] {
+ fill: var(--jp-icon-contrast-color3);
+}
+
+.jp-icon-contrast0[stroke] {
+ stroke: var(--jp-icon-contrast-color0);
+}
+
+.jp-icon-contrast1[stroke] {
+ stroke: var(--jp-icon-contrast-color1);
+}
+
+.jp-icon-contrast2[stroke] {
+ stroke: var(--jp-icon-contrast-color2);
+}
+
+.jp-icon-contrast3[stroke] {
+ stroke: var(--jp-icon-contrast-color3);
+}
+
+.jp-icon-dot[fill] {
+ fill: var(--jp-warn-color0);
+}
+
+.jp-jupyter-icon-color[fill] {
+ fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
+}
+
+.jp-notebook-icon-color[fill] {
+ fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
+}
+
+.jp-json-icon-color[fill] {
+ fill: var(--jp-json-icon-color, var(--jp-warn-color1));
+}
+
+.jp-console-icon-color[fill] {
+ fill: var(--jp-console-icon-color, white);
+}
+
+.jp-console-icon-background-color[fill] {
+ fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
+}
+
+.jp-terminal-icon-color[fill] {
+ fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
+}
+
+.jp-terminal-icon-background-color[fill] {
+ fill: var(
+ --jp-terminal-icon-background-color,
+ var(--jp-inverse-layout-color2)
+ );
+}
+
+.jp-text-editor-icon-color[fill] {
+ fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
+}
+
+.jp-inspector-icon-color[fill] {
+ fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
+}
+
+/* CSS for icons in selected filebrowser listing items */
+.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
+ fill: #fff;
+}
+
+.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
+ fill: var(--jp-brand-color1);
+}
+
+/* stylelint-disable selector-max-class, selector-max-compound-selectors */
+
+/**
+* TODO: come up with non css-hack solution for showing the busy icon on top
+* of the close icon
+* CSS for complex behavior of close icon of tabs in the main area tabbar
+*/
+.lm-DockPanel-tabBar
+ .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
+ > .lm-TabBar-tabCloseIcon
+ > :not(:hover)
+ > .jp-icon3[fill] {
+ fill: none;
+}
+
+.lm-DockPanel-tabBar
+ .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
+ > .lm-TabBar-tabCloseIcon
+ > :not(:hover)
+ > .jp-icon-busy[fill] {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+/* stylelint-enable selector-max-class, selector-max-compound-selectors */
+
+/* CSS for icons in status bar */
+#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
+ fill: #fff;
+}
+
+#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
+ fill: var(--jp-brand-color1);
+}
+
+/* special handling for splash icon CSS. While the theme CSS reloads during
+ splash, the splash icon can loose theming. To prevent that, we set a
+ default for its color variable */
+:root {
+ --jp-warn-color0: var(--md-orange-700);
+}
+
+/* not sure what to do with this one, used in filebrowser listing */
+.jp-DragIcon {
+ margin-right: 4px;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/**
+ * Support for alt colors for icons as inline SVG HTMLElements
+ */
+
+/* alt recolor the primary elements of an icon */
+.jp-icon-alt .jp-icon0[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.jp-icon-alt .jp-icon1[fill] {
+ fill: var(--jp-layout-color1);
+}
+
+.jp-icon-alt .jp-icon2[fill] {
+ fill: var(--jp-layout-color2);
+}
+
+.jp-icon-alt .jp-icon3[fill] {
+ fill: var(--jp-layout-color3);
+}
+
+.jp-icon-alt .jp-icon4[fill] {
+ fill: var(--jp-layout-color4);
+}
+
+.jp-icon-alt .jp-icon0[stroke] {
+ stroke: var(--jp-layout-color0);
+}
+
+.jp-icon-alt .jp-icon1[stroke] {
+ stroke: var(--jp-layout-color1);
+}
+
+.jp-icon-alt .jp-icon2[stroke] {
+ stroke: var(--jp-layout-color2);
+}
+
+.jp-icon-alt .jp-icon3[stroke] {
+ stroke: var(--jp-layout-color3);
+}
+
+.jp-icon-alt .jp-icon4[stroke] {
+ stroke: var(--jp-layout-color4);
+}
+
+/* alt recolor the accent elements of an icon */
+.jp-icon-alt .jp-icon-accent0[fill] {
+ fill: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-alt .jp-icon-accent1[fill] {
+ fill: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-alt .jp-icon-accent2[fill] {
+ fill: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-alt .jp-icon-accent3[fill] {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-alt .jp-icon-accent4[fill] {
+ fill: var(--jp-inverse-layout-color4);
+}
+
+.jp-icon-alt .jp-icon-accent0[stroke] {
+ stroke: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-alt .jp-icon-accent1[stroke] {
+ stroke: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-alt .jp-icon-accent2[stroke] {
+ stroke: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-alt .jp-icon-accent3[stroke] {
+ stroke: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-alt .jp-icon-accent4[stroke] {
+ stroke: var(--jp-inverse-layout-color4);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
+ display: none !important;
+}
+
+/**
+ * Support for hover colors for icons as inline SVG HTMLElements
+ */
+
+/**
+ * regular colors
+ */
+
+/* recolor the primary elements of an icon */
+.jp-icon-hover :hover .jp-icon0-hover[fill] {
+ fill: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-hover :hover .jp-icon1-hover[fill] {
+ fill: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-hover :hover .jp-icon2-hover[fill] {
+ fill: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-hover :hover .jp-icon3-hover[fill] {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-hover :hover .jp-icon4-hover[fill] {
+ fill: var(--jp-inverse-layout-color4);
+}
+
+.jp-icon-hover :hover .jp-icon0-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-hover :hover .jp-icon1-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-hover :hover .jp-icon2-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-hover :hover .jp-icon3-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-hover :hover .jp-icon4-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color4);
+}
+
+/* recolor the accent elements of an icon */
+.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
+ fill: var(--jp-layout-color1);
+}
+
+.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
+ fill: var(--jp-layout-color2);
+}
+
+.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
+ fill: var(--jp-layout-color3);
+}
+
+.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
+ fill: var(--jp-layout-color4);
+}
+
+.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
+ stroke: var(--jp-layout-color0);
+}
+
+.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
+ stroke: var(--jp-layout-color1);
+}
+
+.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
+ stroke: var(--jp-layout-color2);
+}
+
+.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
+ stroke: var(--jp-layout-color3);
+}
+
+.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
+ stroke: var(--jp-layout-color4);
+}
+
+/* set the color of an icon to transparent */
+.jp-icon-hover :hover .jp-icon-none-hover[fill] {
+ fill: none;
+}
+
+.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
+ stroke: none;
+}
+
+/**
+ * inverse colors
+ */
+
+/* inverse recolor the primary elements of an icon */
+.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
+ fill: var(--jp-layout-color1);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
+ fill: var(--jp-layout-color2);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
+ fill: var(--jp-layout-color3);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
+ fill: var(--jp-layout-color4);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
+ stroke: var(--jp-layout-color0);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
+ stroke: var(--jp-layout-color1);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
+ stroke: var(--jp-layout-color2);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
+ stroke: var(--jp-layout-color3);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
+ stroke: var(--jp-layout-color4);
+}
+
+/* inverse recolor the accent elements of an icon */
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
+ fill: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
+ fill: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
+ fill: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
+ fill: var(--jp-inverse-layout-color4);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color0);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color1);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color2);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color3);
+}
+
+.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
+ stroke: var(--jp-inverse-layout-color4);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-IFrame {
+ width: 100%;
+ height: 100%;
+}
+
+.jp-IFrame > iframe {
+ border: none;
+}
+
+/*
+When drag events occur, `lm-mod-override-cursor` is added to the body.
+Because iframes steal all cursor events, the following two rules are necessary
+to suppress pointer events while resize drags are occurring. There may be a
+better solution to this problem.
+*/
+body.lm-mod-override-cursor .jp-IFrame {
+ position: relative;
+}
+
+body.lm-mod-override-cursor .jp-IFrame::before {
+ content: '';
+ position: absolute;
+ top: 0;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ background: transparent;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2016, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-HoverBox {
+ position: fixed;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-FormGroup-content fieldset {
+ border: none;
+ padding: 0;
+ min-width: 0;
+ width: 100%;
+}
+
+/* stylelint-disable selector-max-type */
+
+.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
+.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
+.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
+ font-size: var(--jp-content-font-size2);
+ border-color: var(--jp-input-border-color);
+ border-style: solid;
+ border-radius: var(--jp-border-radius);
+ border-width: 1px;
+ padding: 6px 8px;
+ background: none;
+ color: var(--jp-ui-font-color0);
+ height: inherit;
+}
+
+.jp-FormGroup-content fieldset input[type='checkbox'] {
+ position: relative;
+ top: 2px;
+ margin-left: 0;
+}
+
+.jp-FormGroup-content button.jp-mod-styled {
+ cursor: pointer;
+}
+
+.jp-FormGroup-content .checkbox label {
+ cursor: pointer;
+ font-size: var(--jp-content-font-size1);
+}
+
+.jp-FormGroup-content .jp-root > fieldset > legend {
+ display: none;
+}
+
+.jp-FormGroup-content .jp-root > fieldset > p {
+ display: none;
+}
+
+/** copy of `input.jp-mod-styled:focus` style */
+.jp-FormGroup-content fieldset input:focus,
+.jp-FormGroup-content fieldset select:focus {
+ -moz-outline-radius: unset;
+ outline: var(--jp-border-width) solid var(--md-blue-500);
+ outline-offset: -1px;
+ box-shadow: inset 0 0 4px var(--md-blue-300);
+}
+
+.jp-FormGroup-content fieldset input:hover:not(:focus),
+.jp-FormGroup-content fieldset select:hover:not(:focus) {
+ background-color: var(--jp-border-color2);
+}
+
+/* stylelint-enable selector-max-type */
+
+.jp-FormGroup-content .checkbox .field-description {
+ /* Disable default description field for checkbox:
+ because other widgets do not have description fields,
+ we add descriptions to each widget on the field level.
+ */
+ display: none;
+}
+
+.jp-FormGroup-content #root__description {
+ display: none;
+}
+
+.jp-FormGroup-content .jp-modifiedIndicator {
+ width: 5px;
+ background-color: var(--jp-brand-color2);
+ margin-top: 0;
+ margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
+ flex-shrink: 0;
+}
+
+.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
+ background-color: var(--jp-error-color0);
+ margin-right: 0.5em;
+}
+
+/* RJSF ARRAY style */
+
+.jp-arrayFieldWrapper legend {
+ font-size: var(--jp-content-font-size2);
+ color: var(--jp-ui-font-color0);
+ flex-basis: 100%;
+ padding: 4px 0;
+ font-weight: var(--jp-content-heading-font-weight);
+ border-bottom: 1px solid var(--jp-border-color2);
+}
+
+.jp-arrayFieldWrapper .field-description {
+ padding: 4px 0;
+ white-space: pre-wrap;
+}
+
+.jp-arrayFieldWrapper .array-item {
+ width: 100%;
+ border: 1px solid var(--jp-border-color2);
+ border-radius: 4px;
+ margin: 4px;
+}
+
+.jp-ArrayOperations {
+ display: flex;
+ margin-left: 8px;
+}
+
+.jp-ArrayOperationsButton {
+ margin: 2px;
+}
+
+.jp-ArrayOperationsButton .jp-icon3[fill] {
+ fill: var(--jp-ui-font-color0);
+}
+
+button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
+ cursor: not-allowed;
+ opacity: 0.5;
+}
+
+/* RJSF form validation error */
+
+.jp-FormGroup-content .validationErrors {
+ color: var(--jp-error-color0);
+}
+
+/* Hide panel level error as duplicated the field level error */
+.jp-FormGroup-content .panel.errors {
+ display: none;
+}
+
+/* RJSF normal content (settings-editor) */
+
+.jp-FormGroup-contentNormal {
+ display: flex;
+ align-items: center;
+ flex-wrap: wrap;
+}
+
+.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
+ margin-left: 7px;
+ color: var(--jp-ui-font-color0);
+}
+
+.jp-FormGroup-contentNormal .jp-FormGroup-description {
+ flex-basis: 100%;
+ padding: 4px 7px;
+}
+
+.jp-FormGroup-contentNormal .jp-FormGroup-default {
+ flex-basis: 100%;
+ padding: 4px 7px;
+}
+
+.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
+ font-size: var(--jp-content-font-size1);
+ font-weight: normal;
+ min-width: 120px;
+}
+
+.jp-FormGroup-contentNormal fieldset:not(:first-child) {
+ margin-left: 7px;
+}
+
+.jp-FormGroup-contentNormal .field-array-of-string .array-item {
+ /* Display `jp-ArrayOperations` buttons side-by-side with content except
+ for small screens where flex-wrap will place them one below the other.
+ */
+ display: flex;
+ align-items: center;
+ flex-wrap: wrap;
+}
+
+.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
+ padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
+ margin-top: 2px;
+}
+
+/* RJSF compact content (metadata-form) */
+
+.jp-FormGroup-content.jp-FormGroup-contentCompact {
+ width: 100%;
+}
+
+.jp-FormGroup-contentCompact .form-group {
+ display: flex;
+ padding: 0.5em 0.2em 0.5em 0;
+}
+
+.jp-FormGroup-contentCompact
+ .jp-FormGroup-compactTitle
+ .jp-FormGroup-description {
+ font-size: var(--jp-ui-font-size1);
+ color: var(--jp-ui-font-color2);
+}
+
+.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
+ padding-bottom: 0.3em;
+}
+
+.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
+ width: 100%;
+ box-sizing: border-box;
+}
+
+.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
+ padding-bottom: 7px;
+}
+
+.jp-FormGroup-contentCompact
+ .jp-objectFieldWrapper
+ .jp-objectFieldWrapper
+ .form-group {
+ padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
+ margin-top: 2px;
+}
+
+.jp-FormGroup-contentCompact ul.error-detail {
+ margin-block-start: 0.5em;
+ margin-block-end: 0.5em;
+ padding-inline-start: 1em;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.jp-SidePanel {
+ display: flex;
+ flex-direction: column;
+ min-width: var(--jp-sidebar-min-width);
+ overflow-y: auto;
+ color: var(--jp-ui-font-color1);
+ background: var(--jp-layout-color1);
+ font-size: var(--jp-ui-font-size1);
+}
+
+.jp-SidePanel-header {
+ flex: 0 0 auto;
+ display: flex;
+ border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
+ font-size: var(--jp-ui-font-size0);
+ font-weight: 600;
+ letter-spacing: 1px;
+ margin: 0;
+ padding: 2px;
+ text-transform: uppercase;
+}
+
+.jp-SidePanel-toolbar {
+ flex: 0 0 auto;
+}
+
+.jp-SidePanel-content {
+ flex: 1 1 auto;
+}
+
+.jp-SidePanel-toolbar,
+.jp-AccordionPanel-toolbar {
+ height: var(--jp-private-toolbar-height);
+}
+
+.jp-SidePanel-toolbar.jp-Toolbar-micro {
+ display: none;
+}
+
+.lm-AccordionPanel .jp-AccordionPanel-title {
+ box-sizing: border-box;
+ line-height: 25px;
+ margin: 0;
+ display: flex;
+ align-items: center;
+ background: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
+ box-shadow: var(--jp-toolbar-box-shadow);
+ font-size: var(--jp-ui-font-size0);
+}
+
+.jp-AccordionPanel-title {
+ cursor: pointer;
+ user-select: none;
+ -moz-user-select: none;
+ -webkit-user-select: none;
+ text-transform: uppercase;
+}
+
+.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
+ /* Title is rotated for horizontal accordion panel using CSS */
+ display: block;
+ transform-origin: top left;
+ transform: rotate(-90deg) translate(-100%);
+}
+
+.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
+ user-select: none;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+ overflow: hidden;
+}
+
+.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
+ transform: rotate(-90deg);
+ margin: auto 0;
+ height: 16px;
+}
+
+.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
+ transform: rotate(0deg);
+}
+
+.lm-AccordionPanel .jp-AccordionPanel-toolbar {
+ background: none;
+ box-shadow: none;
+ border: none;
+ margin-left: auto;
+}
+
+.lm-AccordionPanel .lm-SplitPanel-handle:hover {
+ background: var(--jp-layout-color3);
+}
+
+.jp-text-truncated {
+ overflow: hidden;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2017, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Spinner {
+ position: absolute;
+ display: flex;
+ justify-content: center;
+ align-items: center;
+ z-index: 10;
+ left: 0;
+ top: 0;
+ width: 100%;
+ height: 100%;
+ background: var(--jp-layout-color0);
+ outline: none;
+}
+
+.jp-SpinnerContent {
+ font-size: 10px;
+ margin: 50px auto;
+ text-indent: -9999em;
+ width: 3em;
+ height: 3em;
+ border-radius: 50%;
+ background: var(--jp-brand-color3);
+ background: linear-gradient(
+ to right,
+ #f37626 10%,
+ rgba(255, 255, 255, 0) 42%
+ );
+ position: relative;
+ animation: load3 1s infinite linear, fadeIn 1s;
+}
+
+.jp-SpinnerContent::before {
+ width: 50%;
+ height: 50%;
+ background: #f37626;
+ border-radius: 100% 0 0;
+ position: absolute;
+ top: 0;
+ left: 0;
+ content: '';
+}
+
+.jp-SpinnerContent::after {
+ background: var(--jp-layout-color0);
+ width: 75%;
+ height: 75%;
+ border-radius: 50%;
+ content: '';
+ margin: auto;
+ position: absolute;
+ top: 0;
+ left: 0;
+ bottom: 0;
+ right: 0;
+}
+
+@keyframes fadeIn {
+ 0% {
+ opacity: 0;
+ }
+
+ 100% {
+ opacity: 1;
+ }
+}
+
+@keyframes load3 {
+ 0% {
+ transform: rotate(0deg);
+ }
+
+ 100% {
+ transform: rotate(360deg);
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2017, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+button.jp-mod-styled {
+ font-size: var(--jp-ui-font-size1);
+ color: var(--jp-ui-font-color0);
+ border: none;
+ box-sizing: border-box;
+ text-align: center;
+ line-height: 32px;
+ height: 32px;
+ padding: 0 12px;
+ letter-spacing: 0.8px;
+ outline: none;
+ appearance: none;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+}
+
+input.jp-mod-styled {
+ background: var(--jp-input-background);
+ height: 28px;
+ box-sizing: border-box;
+ border: var(--jp-border-width) solid var(--jp-border-color1);
+ padding-left: 7px;
+ padding-right: 7px;
+ font-size: var(--jp-ui-font-size2);
+ color: var(--jp-ui-font-color0);
+ outline: none;
+ appearance: none;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+}
+
+input[type='checkbox'].jp-mod-styled {
+ appearance: checkbox;
+ -webkit-appearance: checkbox;
+ -moz-appearance: checkbox;
+ height: auto;
+}
+
+input.jp-mod-styled:focus {
+ border: var(--jp-border-width) solid var(--md-blue-500);
+ box-shadow: inset 0 0 4px var(--md-blue-300);
+}
+
+.jp-select-wrapper {
+ display: flex;
+ position: relative;
+ flex-direction: column;
+ padding: 1px;
+ background-color: var(--jp-layout-color1);
+ box-sizing: border-box;
+ margin-bottom: 12px;
+}
+
+.jp-select-wrapper:not(.multiple) {
+ height: 28px;
+}
+
+.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
+ border: var(--jp-border-width) solid var(--jp-input-active-border-color);
+ box-shadow: var(--jp-input-box-shadow);
+ background-color: var(--jp-input-active-background);
+}
+
+select.jp-mod-styled:hover {
+ cursor: pointer;
+ color: var(--jp-ui-font-color0);
+ background-color: var(--jp-input-hover-background);
+ box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
+}
+
+select.jp-mod-styled {
+ flex: 1 1 auto;
+ width: 100%;
+ font-size: var(--jp-ui-font-size2);
+ background: var(--jp-input-background);
+ color: var(--jp-ui-font-color0);
+ padding: 0 25px 0 8px;
+ border: var(--jp-border-width) solid var(--jp-input-border-color);
+ border-radius: 0;
+ outline: none;
+ appearance: none;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+}
+
+select.jp-mod-styled:not([multiple]) {
+ height: 32px;
+}
+
+select.jp-mod-styled[multiple] {
+ max-height: 200px;
+ overflow-y: auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-switch {
+ display: flex;
+ align-items: center;
+ padding-left: 4px;
+ padding-right: 4px;
+ font-size: var(--jp-ui-font-size1);
+ background-color: transparent;
+ color: var(--jp-ui-font-color1);
+ border: none;
+ height: 20px;
+}
+
+.jp-switch:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-switch-label {
+ margin-right: 5px;
+ font-family: var(--jp-ui-font-family);
+}
+
+.jp-switch-track {
+ cursor: pointer;
+ background-color: var(--jp-switch-color, var(--jp-border-color1));
+ -webkit-transition: 0.4s;
+ transition: 0.4s;
+ border-radius: 34px;
+ height: 16px;
+ width: 35px;
+ position: relative;
+}
+
+.jp-switch-track::before {
+ content: '';
+ position: absolute;
+ height: 10px;
+ width: 10px;
+ margin: 3px;
+ left: 0;
+ background-color: var(--jp-ui-inverse-font-color1);
+ -webkit-transition: 0.4s;
+ transition: 0.4s;
+ border-radius: 50%;
+}
+
+.jp-switch[aria-checked='true'] .jp-switch-track {
+ background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
+}
+
+.jp-switch[aria-checked='true'] .jp-switch-track::before {
+ /* track width (35) - margins (3 + 3) - thumb width (10) */
+ left: 19px;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2016, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-private-toolbar-height: calc(
+ 28px + var(--jp-border-width)
+ ); /* leave 28px for content */
+}
+
+.jp-Toolbar {
+ color: var(--jp-ui-font-color1);
+ flex: 0 0 auto;
+ display: flex;
+ flex-direction: row;
+ border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
+ box-shadow: var(--jp-toolbar-box-shadow);
+ background: var(--jp-toolbar-background);
+ min-height: var(--jp-toolbar-micro-height);
+ padding: 2px;
+ z-index: 8;
+ overflow-x: hidden;
+}
+
+/* Toolbar items */
+
+.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
+ flex-grow: 1;
+ flex-shrink: 1;
+}
+
+.jp-Toolbar-item.jp-Toolbar-kernelStatus {
+ display: inline-block;
+ width: 32px;
+ background-repeat: no-repeat;
+ background-position: center;
+ background-size: 16px;
+}
+
+.jp-Toolbar > .jp-Toolbar-item {
+ flex: 0 0 auto;
+ display: flex;
+ padding-left: 1px;
+ padding-right: 1px;
+ font-size: var(--jp-ui-font-size1);
+ line-height: var(--jp-private-toolbar-height);
+ height: 100%;
+}
+
+/* Toolbar buttons */
+
+/* This is the div we use to wrap the react component into a Widget */
+div.jp-ToolbarButton {
+ color: transparent;
+ border: none;
+ box-sizing: border-box;
+ outline: none;
+ appearance: none;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ padding: 0;
+ margin: 0;
+}
+
+button.jp-ToolbarButtonComponent {
+ background: var(--jp-layout-color1);
+ border: none;
+ box-sizing: border-box;
+ outline: none;
+ appearance: none;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ padding: 0 6px;
+ margin: 0;
+ height: 24px;
+ border-radius: var(--jp-border-radius);
+ display: flex;
+ align-items: center;
+ text-align: center;
+ font-size: 14px;
+ min-width: unset;
+ min-height: unset;
+}
+
+button.jp-ToolbarButtonComponent:disabled {
+ opacity: 0.4;
+}
+
+button.jp-ToolbarButtonComponent > span {
+ padding: 0;
+ flex: 0 0 auto;
+}
+
+button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
+ font-size: var(--jp-ui-font-size1);
+ line-height: 100%;
+ padding-left: 2px;
+ color: var(--jp-ui-font-color1);
+ font-family: var(--jp-ui-font-family);
+}
+
+#jp-main-dock-panel[data-mode='single-document']
+ .jp-MainAreaWidget
+ > .jp-Toolbar.jp-Toolbar-micro {
+ padding: 0;
+ min-height: 0;
+}
+
+#jp-main-dock-panel[data-mode='single-document']
+ .jp-MainAreaWidget
+ > .jp-Toolbar {
+ border: none;
+ box-shadow: none;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.jp-WindowedPanel-outer {
+ position: relative;
+ overflow-y: auto;
+}
+
+.jp-WindowedPanel-inner {
+ position: relative;
+}
+
+.jp-WindowedPanel-window {
+ position: absolute;
+ left: 0;
+ right: 0;
+ overflow: visible;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/* Sibling imports */
+
+body {
+ color: var(--jp-ui-font-color1);
+ font-size: var(--jp-ui-font-size1);
+}
+
+/* Disable native link decoration styles everywhere outside of dialog boxes */
+a {
+ text-decoration: unset;
+ color: unset;
+}
+
+a:hover {
+ text-decoration: unset;
+ color: unset;
+}
+
+/* Accessibility for links inside dialog box text */
+.jp-Dialog-content a {
+ text-decoration: revert;
+ color: var(--jp-content-link-color);
+}
+
+.jp-Dialog-content a:hover {
+ text-decoration: revert;
+}
+
+/* Styles for ui-components */
+.jp-Button {
+ color: var(--jp-ui-font-color2);
+ border-radius: var(--jp-border-radius);
+ padding: 0 12px;
+ font-size: var(--jp-ui-font-size1);
+
+ /* Copy from blueprint 3 */
+ display: inline-flex;
+ flex-direction: row;
+ border: none;
+ cursor: pointer;
+ align-items: center;
+ justify-content: center;
+ text-align: left;
+ vertical-align: middle;
+ min-height: 30px;
+ min-width: 30px;
+}
+
+.jp-Button:disabled {
+ cursor: not-allowed;
+}
+
+.jp-Button:empty {
+ padding: 0 !important;
+}
+
+.jp-Button.jp-mod-small {
+ min-height: 24px;
+ min-width: 24px;
+ font-size: 12px;
+ padding: 0 7px;
+}
+
+/* Use our own theme for hover styles */
+.jp-Button.jp-mod-minimal:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-Button.jp-mod-minimal {
+ background: none;
+}
+
+.jp-InputGroup {
+ display: block;
+ position: relative;
+}
+
+.jp-InputGroup input {
+ box-sizing: border-box;
+ border: none;
+ border-radius: 0;
+ background-color: transparent;
+ color: var(--jp-ui-font-color0);
+ box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
+ padding-bottom: 0;
+ padding-top: 0;
+ padding-left: 10px;
+ padding-right: 28px;
+ position: relative;
+ width: 100%;
+ -webkit-appearance: none;
+ -moz-appearance: none;
+ appearance: none;
+ font-size: 14px;
+ font-weight: 400;
+ height: 30px;
+ line-height: 30px;
+ outline: none;
+ vertical-align: middle;
+}
+
+.jp-InputGroup input:focus {
+ box-shadow: inset 0 0 0 var(--jp-border-width)
+ var(--jp-input-active-box-shadow-color),
+ inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
+}
+
+.jp-InputGroup input:disabled {
+ cursor: not-allowed;
+ resize: block;
+ background-color: var(--jp-layout-color2);
+ color: var(--jp-ui-font-color2);
+}
+
+.jp-InputGroup input:disabled ~ span {
+ cursor: not-allowed;
+ color: var(--jp-ui-font-color2);
+}
+
+.jp-InputGroup input::placeholder,
+input::placeholder {
+ color: var(--jp-ui-font-color2);
+}
+
+.jp-InputGroupAction {
+ position: absolute;
+ bottom: 1px;
+ right: 0;
+ padding: 6px;
+}
+
+.jp-HTMLSelect.jp-DefaultStyle select {
+ background-color: initial;
+ border: none;
+ border-radius: 0;
+ box-shadow: none;
+ color: var(--jp-ui-font-color0);
+ display: block;
+ font-size: var(--jp-ui-font-size1);
+ font-family: var(--jp-ui-font-family);
+ height: 24px;
+ line-height: 14px;
+ padding: 0 25px 0 10px;
+ text-align: left;
+ -moz-appearance: none;
+ -webkit-appearance: none;
+}
+
+.jp-HTMLSelect.jp-DefaultStyle select:disabled {
+ background-color: var(--jp-layout-color2);
+ color: var(--jp-ui-font-color2);
+ cursor: not-allowed;
+ resize: block;
+}
+
+.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
+ cursor: not-allowed;
+}
+
+/* Use our own theme for hover and option styles */
+/* stylelint-disable-next-line selector-max-type */
+.jp-HTMLSelect.jp-DefaultStyle select:hover,
+.jp-HTMLSelect.jp-DefaultStyle select > option {
+ background-color: var(--jp-layout-color2);
+ color: var(--jp-ui-font-color0);
+}
+
+select {
+ box-sizing: border-box;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Styles
+|----------------------------------------------------------------------------*/
+
+.jp-StatusBar-Widget {
+ display: flex;
+ align-items: center;
+ background: var(--jp-layout-color2);
+ min-height: var(--jp-statusbar-height);
+ justify-content: space-between;
+ padding: 0 10px;
+}
+
+.jp-StatusBar-Left {
+ display: flex;
+ align-items: center;
+ flex-direction: row;
+}
+
+.jp-StatusBar-Middle {
+ display: flex;
+ align-items: center;
+}
+
+.jp-StatusBar-Right {
+ display: flex;
+ align-items: center;
+ flex-direction: row-reverse;
+}
+
+.jp-StatusBar-Item {
+ max-height: var(--jp-statusbar-height);
+ margin: 0 2px;
+ height: var(--jp-statusbar-height);
+ white-space: nowrap;
+ text-overflow: ellipsis;
+ color: var(--jp-ui-font-color1);
+ padding: 0 6px;
+}
+
+.jp-mod-highlighted:hover {
+ background-color: var(--jp-layout-color3);
+}
+
+.jp-mod-clicked {
+ background-color: var(--jp-brand-color1);
+}
+
+.jp-mod-clicked:hover {
+ background-color: var(--jp-brand-color0);
+}
+
+.jp-mod-clicked .jp-StatusBar-TextItem {
+ color: var(--jp-ui-inverse-font-color1);
+}
+
+.jp-StatusBar-HoverItem {
+ box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
+}
+
+.jp-StatusBar-TextItem {
+ font-size: var(--jp-ui-font-size1);
+ font-family: var(--jp-ui-font-family);
+ line-height: 24px;
+ color: var(--jp-ui-font-color1);
+}
+
+.jp-StatusBar-GroupItem {
+ display: flex;
+ align-items: center;
+ flex-direction: row;
+}
+
+.jp-Statusbar-ProgressCircle svg {
+ display: block;
+ margin: 0 auto;
+ width: 16px;
+ height: 24px;
+ align-self: normal;
+}
+
+.jp-Statusbar-ProgressCircle path {
+ fill: var(--jp-inverse-layout-color3);
+}
+
+.jp-Statusbar-ProgressBar-progress-bar {
+ height: 10px;
+ width: 100px;
+ border: solid 0.25px var(--jp-brand-color2);
+ border-radius: 3px;
+ overflow: hidden;
+ align-self: center;
+}
+
+.jp-Statusbar-ProgressBar-progress-bar > div {
+ background-color: var(--jp-brand-color2);
+ background-image: linear-gradient(
+ -45deg,
+ rgba(255, 255, 255, 0.2) 25%,
+ transparent 25%,
+ transparent 50%,
+ rgba(255, 255, 255, 0.2) 50%,
+ rgba(255, 255, 255, 0.2) 75%,
+ transparent 75%,
+ transparent
+ );
+ background-size: 40px 40px;
+ float: left;
+ width: 0%;
+ height: 100%;
+ font-size: 12px;
+ line-height: 14px;
+ color: #fff;
+ text-align: center;
+ animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
+}
+
+.jp-Statusbar-ProgressBar-progress-bar p {
+ color: var(--jp-ui-font-color1);
+ font-family: var(--jp-ui-font-family);
+ font-size: var(--jp-ui-font-size1);
+ line-height: 10px;
+ width: 100px;
+}
+
+@keyframes jp-Statusbar-ExecutionTime-progress-bar {
+ 0% {
+ background-position: 0 0;
+ }
+
+ 100% {
+ background-position: 40px 40px;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Variables
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-private-commandpalette-search-height: 28px;
+}
+
+/*-----------------------------------------------------------------------------
+| Overall styles
+|----------------------------------------------------------------------------*/
+
+.lm-CommandPalette {
+ padding-bottom: 0;
+ color: var(--jp-ui-font-color1);
+ background: var(--jp-layout-color1);
+
+ /* This is needed so that all font sizing of children done in ems is
+ * relative to this base size */
+ font-size: var(--jp-ui-font-size1);
+}
+
+/*-----------------------------------------------------------------------------
+| Modal variant
+|----------------------------------------------------------------------------*/
+
+.jp-ModalCommandPalette {
+ position: absolute;
+ z-index: 10000;
+ top: 38px;
+ left: 30%;
+ margin: 0;
+ padding: 4px;
+ width: 40%;
+ box-shadow: var(--jp-elevation-z4);
+ border-radius: 4px;
+ background: var(--jp-layout-color0);
+}
+
+.jp-ModalCommandPalette .lm-CommandPalette {
+ max-height: 40vh;
+}
+
+.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
+ display: none;
+}
+
+.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
+ display: none;
+}
+
+.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
+ margin-left: 4px;
+ margin-right: 4px;
+}
+
+.jp-ModalCommandPalette
+ .lm-CommandPalette
+ .lm-CommandPalette-item.lm-mod-disabled {
+ display: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Search
+|----------------------------------------------------------------------------*/
+
+.lm-CommandPalette-search {
+ padding: 4px;
+ background-color: var(--jp-layout-color1);
+ z-index: 2;
+}
+
+.lm-CommandPalette-wrapper {
+ overflow: overlay;
+ padding: 0 9px;
+ background-color: var(--jp-input-active-background);
+ height: 30px;
+ box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
+}
+
+.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
+ box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
+ inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
+}
+
+.jp-SearchIconGroup {
+ color: white;
+ background-color: var(--jp-brand-color1);
+ position: absolute;
+ top: 4px;
+ right: 4px;
+ padding: 5px 5px 1px;
+}
+
+.jp-SearchIconGroup svg {
+ height: 20px;
+ width: 20px;
+}
+
+.jp-SearchIconGroup .jp-icon3[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.lm-CommandPalette-input {
+ background: transparent;
+ width: calc(100% - 18px);
+ float: left;
+ border: none;
+ outline: none;
+ font-size: var(--jp-ui-font-size1);
+ color: var(--jp-ui-font-color0);
+ line-height: var(--jp-private-commandpalette-search-height);
+}
+
+.lm-CommandPalette-input::-webkit-input-placeholder,
+.lm-CommandPalette-input::-moz-placeholder,
+.lm-CommandPalette-input:-ms-input-placeholder {
+ color: var(--jp-ui-font-color2);
+ font-size: var(--jp-ui-font-size1);
+}
+
+/*-----------------------------------------------------------------------------
+| Results
+|----------------------------------------------------------------------------*/
+
+.lm-CommandPalette-header:first-child {
+ margin-top: 0;
+}
+
+.lm-CommandPalette-header {
+ border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
+ color: var(--jp-ui-font-color1);
+ cursor: pointer;
+ display: flex;
+ font-size: var(--jp-ui-font-size0);
+ font-weight: 600;
+ letter-spacing: 1px;
+ margin-top: 8px;
+ padding: 8px 0 8px 12px;
+ text-transform: uppercase;
+}
+
+.lm-CommandPalette-header.lm-mod-active {
+ background: var(--jp-layout-color2);
+}
+
+.lm-CommandPalette-header > mark {
+ background-color: transparent;
+ font-weight: bold;
+ color: var(--jp-ui-font-color1);
+}
+
+.lm-CommandPalette-item {
+ padding: 4px 12px 4px 4px;
+ color: var(--jp-ui-font-color1);
+ font-size: var(--jp-ui-font-size1);
+ font-weight: 400;
+ display: flex;
+}
+
+.lm-CommandPalette-item.lm-mod-disabled {
+ color: var(--jp-ui-font-color2);
+}
+
+.lm-CommandPalette-item.lm-mod-active {
+ color: var(--jp-ui-inverse-font-color1);
+ background: var(--jp-brand-color1);
+}
+
+.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
+ color: var(--jp-ui-inverse-font-color0);
+}
+
+.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
+ fill: var(--jp-layout-color0);
+}
+
+.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
+ color: var(--jp-ui-inverse-font-color1);
+ background: var(--jp-brand-color1);
+}
+
+.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
+ background: var(--jp-layout-color2);
+}
+
+.lm-CommandPalette-itemContent {
+ overflow: hidden;
+}
+
+.lm-CommandPalette-itemLabel > mark {
+ color: var(--jp-ui-font-color0);
+ background-color: transparent;
+ font-weight: bold;
+}
+
+.lm-CommandPalette-item.lm-mod-disabled mark {
+ color: var(--jp-ui-font-color2);
+}
+
+.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
+ margin: 0 4px 0 0;
+ position: relative;
+ width: 16px;
+ top: 2px;
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
+ opacity: 0.6;
+}
+
+.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-itemCaption {
+ display: none;
+}
+
+.lm-CommandPalette-content {
+ background-color: var(--jp-layout-color1);
+}
+
+.lm-CommandPalette-content:empty::after {
+ content: 'No results';
+ margin: auto;
+ margin-top: 20px;
+ width: 100px;
+ display: block;
+ font-size: var(--jp-ui-font-size2);
+ font-family: var(--jp-ui-font-family);
+ font-weight: lighter;
+}
+
+.lm-CommandPalette-emptyMessage {
+ text-align: center;
+ margin-top: 24px;
+ line-height: 1.32;
+ padding: 0 8px;
+ color: var(--jp-content-font-color3);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2017, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Dialog {
+ position: absolute;
+ z-index: 10000;
+ display: flex;
+ flex-direction: column;
+ align-items: center;
+ justify-content: center;
+ top: 0;
+ left: 0;
+ margin: 0;
+ padding: 0;
+ width: 100%;
+ height: 100%;
+ background: var(--jp-dialog-background);
+}
+
+.jp-Dialog-content {
+ display: flex;
+ flex-direction: column;
+ margin-left: auto;
+ margin-right: auto;
+ background: var(--jp-layout-color1);
+ padding: 24px 24px 12px;
+ min-width: 300px;
+ min-height: 150px;
+ max-width: 1000px;
+ max-height: 500px;
+ box-sizing: border-box;
+ box-shadow: var(--jp-elevation-z20);
+ word-wrap: break-word;
+ border-radius: var(--jp-border-radius);
+
+ /* This is needed so that all font sizing of children done in ems is
+ * relative to this base size */
+ font-size: var(--jp-ui-font-size1);
+ color: var(--jp-ui-font-color1);
+ resize: both;
+}
+
+.jp-Dialog-content.jp-Dialog-content-small {
+ max-width: 500px;
+}
+
+.jp-Dialog-button {
+ overflow: visible;
+}
+
+button.jp-Dialog-button:focus {
+ outline: 1px solid var(--jp-brand-color1);
+ outline-offset: 4px;
+ -moz-outline-radius: 0;
+}
+
+button.jp-Dialog-button:focus::-moz-focus-inner {
+ border: 0;
+}
+
+button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
+button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
+button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
+ outline-offset: 4px;
+ -moz-outline-radius: 0;
+}
+
+button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
+ outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
+}
+
+button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
+ outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
+}
+
+button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
+ outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
+}
+
+button.jp-Dialog-close-button {
+ padding: 0;
+ height: 100%;
+ min-width: unset;
+ min-height: unset;
+}
+
+.jp-Dialog-header {
+ display: flex;
+ justify-content: space-between;
+ flex: 0 0 auto;
+ padding-bottom: 12px;
+ font-size: var(--jp-ui-font-size3);
+ font-weight: 400;
+ color: var(--jp-ui-font-color1);
+}
+
+.jp-Dialog-body {
+ display: flex;
+ flex-direction: column;
+ flex: 1 1 auto;
+ font-size: var(--jp-ui-font-size1);
+ background: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ overflow: auto;
+}
+
+.jp-Dialog-footer {
+ display: flex;
+ flex-direction: row;
+ justify-content: flex-end;
+ align-items: center;
+ flex: 0 0 auto;
+ margin-left: -12px;
+ margin-right: -12px;
+ padding: 12px;
+}
+
+.jp-Dialog-checkbox {
+ padding-right: 5px;
+}
+
+.jp-Dialog-checkbox > input:focus-visible {
+ outline: 1px solid var(--jp-input-active-border-color);
+ outline-offset: 1px;
+}
+
+.jp-Dialog-spacer {
+ flex: 1 1 auto;
+}
+
+.jp-Dialog-title {
+ overflow: hidden;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+}
+
+.jp-Dialog-body > .jp-select-wrapper {
+ width: 100%;
+}
+
+.jp-Dialog-body > button {
+ padding: 0 16px;
+}
+
+.jp-Dialog-body > label {
+ line-height: 1.4;
+ color: var(--jp-ui-font-color0);
+}
+
+.jp-Dialog-button.jp-mod-styled:not(:last-child) {
+ margin-right: 12px;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.jp-Input-Boolean-Dialog {
+ flex-direction: row-reverse;
+ align-items: end;
+ width: 100%;
+}
+
+.jp-Input-Boolean-Dialog > label {
+ flex: 1 1 auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2016, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-MainAreaWidget > :focus {
+ outline: none;
+}
+
+.jp-MainAreaWidget .jp-MainAreaWidget-error {
+ padding: 6px;
+}
+
+.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
+ width: auto;
+ padding: 10px;
+ background: var(--jp-error-color3);
+ border: var(--jp-border-width) solid var(--jp-error-color1);
+ border-radius: var(--jp-border-radius);
+ color: var(--jp-ui-font-color1);
+ font-size: var(--jp-ui-font-size1);
+ white-space: pre-wrap;
+ word-wrap: break-word;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/**
+ * google-material-color v1.2.6
+ * https://github.com/danlevan/google-material-color
+ */
+:root {
+ --md-red-50: #ffebee;
+ --md-red-100: #ffcdd2;
+ --md-red-200: #ef9a9a;
+ --md-red-300: #e57373;
+ --md-red-400: #ef5350;
+ --md-red-500: #f44336;
+ --md-red-600: #e53935;
+ --md-red-700: #d32f2f;
+ --md-red-800: #c62828;
+ --md-red-900: #b71c1c;
+ --md-red-A100: #ff8a80;
+ --md-red-A200: #ff5252;
+ --md-red-A400: #ff1744;
+ --md-red-A700: #d50000;
+ --md-pink-50: #fce4ec;
+ --md-pink-100: #f8bbd0;
+ --md-pink-200: #f48fb1;
+ --md-pink-300: #f06292;
+ --md-pink-400: #ec407a;
+ --md-pink-500: #e91e63;
+ --md-pink-600: #d81b60;
+ --md-pink-700: #c2185b;
+ --md-pink-800: #ad1457;
+ --md-pink-900: #880e4f;
+ --md-pink-A100: #ff80ab;
+ --md-pink-A200: #ff4081;
+ --md-pink-A400: #f50057;
+ --md-pink-A700: #c51162;
+ --md-purple-50: #f3e5f5;
+ --md-purple-100: #e1bee7;
+ --md-purple-200: #ce93d8;
+ --md-purple-300: #ba68c8;
+ --md-purple-400: #ab47bc;
+ --md-purple-500: #9c27b0;
+ --md-purple-600: #8e24aa;
+ --md-purple-700: #7b1fa2;
+ --md-purple-800: #6a1b9a;
+ --md-purple-900: #4a148c;
+ --md-purple-A100: #ea80fc;
+ --md-purple-A200: #e040fb;
+ --md-purple-A400: #d500f9;
+ --md-purple-A700: #a0f;
+ --md-deep-purple-50: #ede7f6;
+ --md-deep-purple-100: #d1c4e9;
+ --md-deep-purple-200: #b39ddb;
+ --md-deep-purple-300: #9575cd;
+ --md-deep-purple-400: #7e57c2;
+ --md-deep-purple-500: #673ab7;
+ --md-deep-purple-600: #5e35b1;
+ --md-deep-purple-700: #512da8;
+ --md-deep-purple-800: #4527a0;
+ --md-deep-purple-900: #311b92;
+ --md-deep-purple-A100: #b388ff;
+ --md-deep-purple-A200: #7c4dff;
+ --md-deep-purple-A400: #651fff;
+ --md-deep-purple-A700: #6200ea;
+ --md-indigo-50: #e8eaf6;
+ --md-indigo-100: #c5cae9;
+ --md-indigo-200: #9fa8da;
+ --md-indigo-300: #7986cb;
+ --md-indigo-400: #5c6bc0;
+ --md-indigo-500: #3f51b5;
+ --md-indigo-600: #3949ab;
+ --md-indigo-700: #303f9f;
+ --md-indigo-800: #283593;
+ --md-indigo-900: #1a237e;
+ --md-indigo-A100: #8c9eff;
+ --md-indigo-A200: #536dfe;
+ --md-indigo-A400: #3d5afe;
+ --md-indigo-A700: #304ffe;
+ --md-blue-50: #e3f2fd;
+ --md-blue-100: #bbdefb;
+ --md-blue-200: #90caf9;
+ --md-blue-300: #64b5f6;
+ --md-blue-400: #42a5f5;
+ --md-blue-500: #2196f3;
+ --md-blue-600: #1e88e5;
+ --md-blue-700: #1976d2;
+ --md-blue-800: #1565c0;
+ --md-blue-900: #0d47a1;
+ --md-blue-A100: #82b1ff;
+ --md-blue-A200: #448aff;
+ --md-blue-A400: #2979ff;
+ --md-blue-A700: #2962ff;
+ --md-light-blue-50: #e1f5fe;
+ --md-light-blue-100: #b3e5fc;
+ --md-light-blue-200: #81d4fa;
+ --md-light-blue-300: #4fc3f7;
+ --md-light-blue-400: #29b6f6;
+ --md-light-blue-500: #03a9f4;
+ --md-light-blue-600: #039be5;
+ --md-light-blue-700: #0288d1;
+ --md-light-blue-800: #0277bd;
+ --md-light-blue-900: #01579b;
+ --md-light-blue-A100: #80d8ff;
+ --md-light-blue-A200: #40c4ff;
+ --md-light-blue-A400: #00b0ff;
+ --md-light-blue-A700: #0091ea;
+ --md-cyan-50: #e0f7fa;
+ --md-cyan-100: #b2ebf2;
+ --md-cyan-200: #80deea;
+ --md-cyan-300: #4dd0e1;
+ --md-cyan-400: #26c6da;
+ --md-cyan-500: #00bcd4;
+ --md-cyan-600: #00acc1;
+ --md-cyan-700: #0097a7;
+ --md-cyan-800: #00838f;
+ --md-cyan-900: #006064;
+ --md-cyan-A100: #84ffff;
+ --md-cyan-A200: #18ffff;
+ --md-cyan-A400: #00e5ff;
+ --md-cyan-A700: #00b8d4;
+ --md-teal-50: #e0f2f1;
+ --md-teal-100: #b2dfdb;
+ --md-teal-200: #80cbc4;
+ --md-teal-300: #4db6ac;
+ --md-teal-400: #26a69a;
+ --md-teal-500: #009688;
+ --md-teal-600: #00897b;
+ --md-teal-700: #00796b;
+ --md-teal-800: #00695c;
+ --md-teal-900: #004d40;
+ --md-teal-A100: #a7ffeb;
+ --md-teal-A200: #64ffda;
+ --md-teal-A400: #1de9b6;
+ --md-teal-A700: #00bfa5;
+ --md-green-50: #e8f5e9;
+ --md-green-100: #c8e6c9;
+ --md-green-200: #a5d6a7;
+ --md-green-300: #81c784;
+ --md-green-400: #66bb6a;
+ --md-green-500: #4caf50;
+ --md-green-600: #43a047;
+ --md-green-700: #388e3c;
+ --md-green-800: #2e7d32;
+ --md-green-900: #1b5e20;
+ --md-green-A100: #b9f6ca;
+ --md-green-A200: #69f0ae;
+ --md-green-A400: #00e676;
+ --md-green-A700: #00c853;
+ --md-light-green-50: #f1f8e9;
+ --md-light-green-100: #dcedc8;
+ --md-light-green-200: #c5e1a5;
+ --md-light-green-300: #aed581;
+ --md-light-green-400: #9ccc65;
+ --md-light-green-500: #8bc34a;
+ --md-light-green-600: #7cb342;
+ --md-light-green-700: #689f38;
+ --md-light-green-800: #558b2f;
+ --md-light-green-900: #33691e;
+ --md-light-green-A100: #ccff90;
+ --md-light-green-A200: #b2ff59;
+ --md-light-green-A400: #76ff03;
+ --md-light-green-A700: #64dd17;
+ --md-lime-50: #f9fbe7;
+ --md-lime-100: #f0f4c3;
+ --md-lime-200: #e6ee9c;
+ --md-lime-300: #dce775;
+ --md-lime-400: #d4e157;
+ --md-lime-500: #cddc39;
+ --md-lime-600: #c0ca33;
+ --md-lime-700: #afb42b;
+ --md-lime-800: #9e9d24;
+ --md-lime-900: #827717;
+ --md-lime-A100: #f4ff81;
+ --md-lime-A200: #eeff41;
+ --md-lime-A400: #c6ff00;
+ --md-lime-A700: #aeea00;
+ --md-yellow-50: #fffde7;
+ --md-yellow-100: #fff9c4;
+ --md-yellow-200: #fff59d;
+ --md-yellow-300: #fff176;
+ --md-yellow-400: #ffee58;
+ --md-yellow-500: #ffeb3b;
+ --md-yellow-600: #fdd835;
+ --md-yellow-700: #fbc02d;
+ --md-yellow-800: #f9a825;
+ --md-yellow-900: #f57f17;
+ --md-yellow-A100: #ffff8d;
+ --md-yellow-A200: #ff0;
+ --md-yellow-A400: #ffea00;
+ --md-yellow-A700: #ffd600;
+ --md-amber-50: #fff8e1;
+ --md-amber-100: #ffecb3;
+ --md-amber-200: #ffe082;
+ --md-amber-300: #ffd54f;
+ --md-amber-400: #ffca28;
+ --md-amber-500: #ffc107;
+ --md-amber-600: #ffb300;
+ --md-amber-700: #ffa000;
+ --md-amber-800: #ff8f00;
+ --md-amber-900: #ff6f00;
+ --md-amber-A100: #ffe57f;
+ --md-amber-A200: #ffd740;
+ --md-amber-A400: #ffc400;
+ --md-amber-A700: #ffab00;
+ --md-orange-50: #fff3e0;
+ --md-orange-100: #ffe0b2;
+ --md-orange-200: #ffcc80;
+ --md-orange-300: #ffb74d;
+ --md-orange-400: #ffa726;
+ --md-orange-500: #ff9800;
+ --md-orange-600: #fb8c00;
+ --md-orange-700: #f57c00;
+ --md-orange-800: #ef6c00;
+ --md-orange-900: #e65100;
+ --md-orange-A100: #ffd180;
+ --md-orange-A200: #ffab40;
+ --md-orange-A400: #ff9100;
+ --md-orange-A700: #ff6d00;
+ --md-deep-orange-50: #fbe9e7;
+ --md-deep-orange-100: #ffccbc;
+ --md-deep-orange-200: #ffab91;
+ --md-deep-orange-300: #ff8a65;
+ --md-deep-orange-400: #ff7043;
+ --md-deep-orange-500: #ff5722;
+ --md-deep-orange-600: #f4511e;
+ --md-deep-orange-700: #e64a19;
+ --md-deep-orange-800: #d84315;
+ --md-deep-orange-900: #bf360c;
+ --md-deep-orange-A100: #ff9e80;
+ --md-deep-orange-A200: #ff6e40;
+ --md-deep-orange-A400: #ff3d00;
+ --md-deep-orange-A700: #dd2c00;
+ --md-brown-50: #efebe9;
+ --md-brown-100: #d7ccc8;
+ --md-brown-200: #bcaaa4;
+ --md-brown-300: #a1887f;
+ --md-brown-400: #8d6e63;
+ --md-brown-500: #795548;
+ --md-brown-600: #6d4c41;
+ --md-brown-700: #5d4037;
+ --md-brown-800: #4e342e;
+ --md-brown-900: #3e2723;
+ --md-grey-50: #fafafa;
+ --md-grey-100: #f5f5f5;
+ --md-grey-200: #eee;
+ --md-grey-300: #e0e0e0;
+ --md-grey-400: #bdbdbd;
+ --md-grey-500: #9e9e9e;
+ --md-grey-600: #757575;
+ --md-grey-700: #616161;
+ --md-grey-800: #424242;
+ --md-grey-900: #212121;
+ --md-blue-grey-50: #eceff1;
+ --md-blue-grey-100: #cfd8dc;
+ --md-blue-grey-200: #b0bec5;
+ --md-blue-grey-300: #90a4ae;
+ --md-blue-grey-400: #78909c;
+ --md-blue-grey-500: #607d8b;
+ --md-blue-grey-600: #546e7a;
+ --md-blue-grey-700: #455a64;
+ --md-blue-grey-800: #37474f;
+ --md-blue-grey-900: #263238;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2017, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| RenderedText
+|----------------------------------------------------------------------------*/
+
+:root {
+ /* This is the padding value to fill the gaps between lines containing spans with background color. */
+ --jp-private-code-span-padding: calc(
+ (var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
+ );
+}
+
+.jp-RenderedText {
+ text-align: left;
+ padding-left: var(--jp-code-padding);
+ line-height: var(--jp-code-line-height);
+ font-family: var(--jp-code-font-family);
+}
+
+.jp-RenderedText pre,
+.jp-RenderedJavaScript pre,
+.jp-RenderedHTMLCommon pre {
+ color: var(--jp-content-font-color1);
+ font-size: var(--jp-code-font-size);
+ border: none;
+ margin: 0;
+ padding: 0;
+}
+
+.jp-RenderedText pre a:link {
+ text-decoration: none;
+ color: var(--jp-content-link-color);
+}
+
+.jp-RenderedText pre a:hover {
+ text-decoration: underline;
+ color: var(--jp-content-link-color);
+}
+
+.jp-RenderedText pre a:visited {
+ text-decoration: none;
+ color: var(--jp-content-link-color);
+}
+
+/* console foregrounds and backgrounds */
+.jp-RenderedText pre .ansi-black-fg {
+ color: #3e424d;
+}
+
+.jp-RenderedText pre .ansi-red-fg {
+ color: #e75c58;
+}
+
+.jp-RenderedText pre .ansi-green-fg {
+ color: #00a250;
+}
+
+.jp-RenderedText pre .ansi-yellow-fg {
+ color: #ddb62b;
+}
+
+.jp-RenderedText pre .ansi-blue-fg {
+ color: #208ffb;
+}
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+.jp-RenderedText pre .ansi-magenta-fg {
+ color: #d160c4;
+}
+
+.jp-RenderedText pre .ansi-cyan-fg {
+ color: #60c6c8;
+}
+
+.jp-RenderedText pre .ansi-white-fg {
+ color: #c5c1b4;
+}
+
+.jp-RenderedText pre .ansi-black-bg {
+ background-color: #3e424d;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-red-bg {
+ background-color: #e75c58;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-green-bg {
+ background-color: #00a250;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-yellow-bg {
+ background-color: #ddb62b;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-blue-bg {
+ background-color: #208ffb;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-magenta-bg {
+ background-color: #d160c4;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-cyan-bg {
+ background-color: #60c6c8;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-white-bg {
+ background-color: #c5c1b4;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-black-intense-fg {
+ color: #282c36;
+}
+
+.jp-RenderedText pre .ansi-red-intense-fg {
+ color: #b22b31;
+}
+
+.jp-RenderedText pre .ansi-green-intense-fg {
+ color: #007427;
+}
+
+.jp-RenderedText pre .ansi-yellow-intense-fg {
+ color: #b27d12;
+}
+
+.jp-RenderedText pre .ansi-blue-intense-fg {
+ color: #0065ca;
+}
+
+.jp-RenderedText pre .ansi-magenta-intense-fg {
+ color: #a03196;
+}
+
+.jp-RenderedText pre .ansi-cyan-intense-fg {
+ color: #258f8f;
+}
+
+.jp-RenderedText pre .ansi-white-intense-fg {
+ color: #a1a6b2;
+}
+
+.jp-RenderedText pre .ansi-black-intense-bg {
+ background-color: #282c36;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-red-intense-bg {
+ background-color: #b22b31;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-green-intense-bg {
+ background-color: #007427;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-yellow-intense-bg {
+ background-color: #b27d12;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-blue-intense-bg {
+ background-color: #0065ca;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-magenta-intense-bg {
+ background-color: #a03196;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-cyan-intense-bg {
+ background-color: #258f8f;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-white-intense-bg {
+ background-color: #a1a6b2;
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-default-inverse-fg {
+ color: var(--jp-ui-inverse-font-color0);
+}
+
+.jp-RenderedText pre .ansi-default-inverse-bg {
+ background-color: var(--jp-inverse-layout-color0);
+ padding: var(--jp-private-code-span-padding) 0;
+}
+
+.jp-RenderedText pre .ansi-bold {
+ font-weight: bold;
+}
+
+.jp-RenderedText pre .ansi-underline {
+ text-decoration: underline;
+}
+
+.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
+ background: var(--jp-rendermime-error-background);
+ padding-top: var(--jp-code-padding);
+}
+
+/*-----------------------------------------------------------------------------
+| RenderedLatex
+|----------------------------------------------------------------------------*/
+
+.jp-RenderedLatex {
+ color: var(--jp-content-font-color1);
+ font-size: var(--jp-content-font-size1);
+ line-height: var(--jp-content-line-height);
+}
+
+/* Left-justify outputs.*/
+.jp-OutputArea-output.jp-RenderedLatex {
+ padding: var(--jp-code-padding);
+ text-align: left;
+}
+
+/*-----------------------------------------------------------------------------
+| RenderedHTML
+|----------------------------------------------------------------------------*/
+
+.jp-RenderedHTMLCommon {
+ color: var(--jp-content-font-color1);
+ font-family: var(--jp-content-font-family);
+ font-size: var(--jp-content-font-size1);
+ line-height: var(--jp-content-line-height);
+
+ /* Give a bit more R padding on Markdown text to keep line lengths reasonable */
+ padding-right: 20px;
+}
+
+.jp-RenderedHTMLCommon em {
+ font-style: italic;
+}
+
+.jp-RenderedHTMLCommon strong {
+ font-weight: bold;
+}
+
+.jp-RenderedHTMLCommon u {
+ text-decoration: underline;
+}
+
+.jp-RenderedHTMLCommon a:link {
+ text-decoration: none;
+ color: var(--jp-content-link-color);
+}
+
+.jp-RenderedHTMLCommon a:hover {
+ text-decoration: underline;
+ color: var(--jp-content-link-color);
+}
+
+.jp-RenderedHTMLCommon a:visited {
+ text-decoration: none;
+ color: var(--jp-content-link-color);
+}
+
+/* Headings */
+
+.jp-RenderedHTMLCommon h1,
+.jp-RenderedHTMLCommon h2,
+.jp-RenderedHTMLCommon h3,
+.jp-RenderedHTMLCommon h4,
+.jp-RenderedHTMLCommon h5,
+.jp-RenderedHTMLCommon h6 {
+ line-height: var(--jp-content-heading-line-height);
+ font-weight: var(--jp-content-heading-font-weight);
+ font-style: normal;
+ margin: var(--jp-content-heading-margin-top) 0
+ var(--jp-content-heading-margin-bottom) 0;
+}
+
+.jp-RenderedHTMLCommon h1:first-child,
+.jp-RenderedHTMLCommon h2:first-child,
+.jp-RenderedHTMLCommon h3:first-child,
+.jp-RenderedHTMLCommon h4:first-child,
+.jp-RenderedHTMLCommon h5:first-child,
+.jp-RenderedHTMLCommon h6:first-child {
+ margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
+}
+
+.jp-RenderedHTMLCommon h1:last-child,
+.jp-RenderedHTMLCommon h2:last-child,
+.jp-RenderedHTMLCommon h3:last-child,
+.jp-RenderedHTMLCommon h4:last-child,
+.jp-RenderedHTMLCommon h5:last-child,
+.jp-RenderedHTMLCommon h6:last-child {
+ margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
+}
+
+.jp-RenderedHTMLCommon h1 {
+ font-size: var(--jp-content-font-size5);
+}
+
+.jp-RenderedHTMLCommon h2 {
+ font-size: var(--jp-content-font-size4);
+}
+
+.jp-RenderedHTMLCommon h3 {
+ font-size: var(--jp-content-font-size3);
+}
+
+.jp-RenderedHTMLCommon h4 {
+ font-size: var(--jp-content-font-size2);
+}
+
+.jp-RenderedHTMLCommon h5 {
+ font-size: var(--jp-content-font-size1);
+}
+
+.jp-RenderedHTMLCommon h6 {
+ font-size: var(--jp-content-font-size0);
+}
+
+/* Lists */
+
+/* stylelint-disable selector-max-type, selector-max-compound-selectors */
+
+.jp-RenderedHTMLCommon ul:not(.list-inline),
+.jp-RenderedHTMLCommon ol:not(.list-inline) {
+ padding-left: 2em;
+}
+
+.jp-RenderedHTMLCommon ul {
+ list-style: disc;
+}
+
+.jp-RenderedHTMLCommon ul ul {
+ list-style: square;
+}
+
+.jp-RenderedHTMLCommon ul ul ul {
+ list-style: circle;
+}
+
+.jp-RenderedHTMLCommon ol {
+ list-style: decimal;
+}
+
+.jp-RenderedHTMLCommon ol ol {
+ list-style: upper-alpha;
+}
+
+.jp-RenderedHTMLCommon ol ol ol {
+ list-style: lower-alpha;
+}
+
+.jp-RenderedHTMLCommon ol ol ol ol {
+ list-style: lower-roman;
+}
+
+.jp-RenderedHTMLCommon ol ol ol ol ol {
+ list-style: decimal;
+}
+
+.jp-RenderedHTMLCommon ol,
+.jp-RenderedHTMLCommon ul {
+ margin-bottom: 1em;
+}
+
+.jp-RenderedHTMLCommon ul ul,
+.jp-RenderedHTMLCommon ul ol,
+.jp-RenderedHTMLCommon ol ul,
+.jp-RenderedHTMLCommon ol ol {
+ margin-bottom: 0;
+}
+
+/* stylelint-enable selector-max-type, selector-max-compound-selectors */
+
+.jp-RenderedHTMLCommon hr {
+ color: var(--jp-border-color2);
+ background-color: var(--jp-border-color1);
+ margin-top: 1em;
+ margin-bottom: 1em;
+}
+
+.jp-RenderedHTMLCommon > pre {
+ margin: 1.5em 2em;
+}
+
+.jp-RenderedHTMLCommon pre,
+.jp-RenderedHTMLCommon code {
+ border: 0;
+ background-color: var(--jp-layout-color0);
+ color: var(--jp-content-font-color1);
+ font-family: var(--jp-code-font-family);
+ font-size: inherit;
+ line-height: var(--jp-code-line-height);
+ padding: 0;
+ white-space: pre-wrap;
+}
+
+.jp-RenderedHTMLCommon :not(pre) > code {
+ background-color: var(--jp-layout-color2);
+ padding: 1px 5px;
+}
+
+/* Tables */
+
+.jp-RenderedHTMLCommon table {
+ border-collapse: collapse;
+ border-spacing: 0;
+ border: none;
+ color: var(--jp-ui-font-color1);
+ font-size: var(--jp-ui-font-size1);
+ table-layout: fixed;
+ margin-left: auto;
+ margin-bottom: 1em;
+ margin-right: auto;
+}
+
+.jp-RenderedHTMLCommon thead {
+ border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
+ vertical-align: bottom;
+}
+
+.jp-RenderedHTMLCommon td,
+.jp-RenderedHTMLCommon th,
+.jp-RenderedHTMLCommon tr {
+ vertical-align: middle;
+ padding: 0.5em;
+ line-height: normal;
+ white-space: normal;
+ max-width: none;
+ border: none;
+}
+
+.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
+.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
+ max-width: none;
+}
+
+:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
+:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
+:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
+ text-align: right;
+}
+
+.jp-RenderedHTMLCommon th {
+ font-weight: bold;
+}
+
+.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
+ background: var(--jp-layout-color0);
+}
+
+.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
+ background: var(--jp-rendermime-table-row-background);
+}
+
+.jp-RenderedHTMLCommon tbody tr:hover {
+ background: var(--jp-rendermime-table-row-hover-background);
+}
+
+.jp-RenderedHTMLCommon p {
+ text-align: left;
+ margin: 0;
+ margin-bottom: 1em;
+}
+
+.jp-RenderedHTMLCommon img {
+ -moz-force-broken-image-icon: 1;
+}
+
+/* Restrict to direct children as other images could be nested in other content. */
+.jp-RenderedHTMLCommon > img {
+ display: block;
+ margin-left: 0;
+ margin-right: 0;
+ margin-bottom: 1em;
+}
+
+/* Change color behind transparent images if they need it... */
+[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
+ background-color: var(--jp-inverse-layout-color1);
+}
+
+[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
+ background-color: var(--jp-inverse-layout-color1);
+}
+
+.jp-RenderedHTMLCommon img,
+.jp-RenderedImage img,
+.jp-RenderedHTMLCommon svg,
+.jp-RenderedSVG svg {
+ max-width: 100%;
+ height: auto;
+}
+
+.jp-RenderedHTMLCommon img.jp-mod-unconfined,
+.jp-RenderedImage img.jp-mod-unconfined,
+.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
+.jp-RenderedSVG svg.jp-mod-unconfined {
+ max-width: none;
+}
+
+.jp-RenderedHTMLCommon .alert {
+ padding: var(--jp-notebook-padding);
+ border: var(--jp-border-width) solid transparent;
+ border-radius: var(--jp-border-radius);
+ margin-bottom: 1em;
+}
+
+.jp-RenderedHTMLCommon .alert-info {
+ color: var(--jp-info-color0);
+ background-color: var(--jp-info-color3);
+ border-color: var(--jp-info-color2);
+}
+
+.jp-RenderedHTMLCommon .alert-info hr {
+ border-color: var(--jp-info-color3);
+}
+
+.jp-RenderedHTMLCommon .alert-info > p:last-child,
+.jp-RenderedHTMLCommon .alert-info > ul:last-child {
+ margin-bottom: 0;
+}
+
+.jp-RenderedHTMLCommon .alert-warning {
+ color: var(--jp-warn-color0);
+ background-color: var(--jp-warn-color3);
+ border-color: var(--jp-warn-color2);
+}
+
+.jp-RenderedHTMLCommon .alert-warning hr {
+ border-color: var(--jp-warn-color3);
+}
+
+.jp-RenderedHTMLCommon .alert-warning > p:last-child,
+.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
+ margin-bottom: 0;
+}
+
+.jp-RenderedHTMLCommon .alert-success {
+ color: var(--jp-success-color0);
+ background-color: var(--jp-success-color3);
+ border-color: var(--jp-success-color2);
+}
+
+.jp-RenderedHTMLCommon .alert-success hr {
+ border-color: var(--jp-success-color3);
+}
+
+.jp-RenderedHTMLCommon .alert-success > p:last-child,
+.jp-RenderedHTMLCommon .alert-success > ul:last-child {
+ margin-bottom: 0;
+}
+
+.jp-RenderedHTMLCommon .alert-danger {
+ color: var(--jp-error-color0);
+ background-color: var(--jp-error-color3);
+ border-color: var(--jp-error-color2);
+}
+
+.jp-RenderedHTMLCommon .alert-danger hr {
+ border-color: var(--jp-error-color3);
+}
+
+.jp-RenderedHTMLCommon .alert-danger > p:last-child,
+.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
+ margin-bottom: 0;
+}
+
+.jp-RenderedHTMLCommon blockquote {
+ margin: 1em 2em;
+ padding: 0 1em;
+ border-left: 5px solid var(--jp-border-color2);
+}
+
+a.jp-InternalAnchorLink {
+ visibility: hidden;
+ margin-left: 8px;
+ color: var(--md-blue-800);
+}
+
+h1:hover .jp-InternalAnchorLink,
+h2:hover .jp-InternalAnchorLink,
+h3:hover .jp-InternalAnchorLink,
+h4:hover .jp-InternalAnchorLink,
+h5:hover .jp-InternalAnchorLink,
+h6:hover .jp-InternalAnchorLink {
+ visibility: visible;
+}
+
+.jp-RenderedHTMLCommon kbd {
+ background-color: var(--jp-rendermime-table-row-background);
+ border: 1px solid var(--jp-border-color0);
+ border-bottom-color: var(--jp-border-color2);
+ border-radius: 3px;
+ box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
+ display: inline-block;
+ font-size: var(--jp-ui-font-size0);
+ line-height: 1em;
+ padding: 0.2em 0.5em;
+}
+
+/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
+ * At the bottom of cells this is a bit too much as there is also spacing
+ * between cells. Going all the way to 0 gets too tight between markdown and
+ * code cells.
+ */
+.jp-RenderedHTMLCommon > *:last-child {
+ margin-bottom: 0.5em;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-cursor-backdrop {
+ position: fixed;
+ width: 200px;
+ height: 200px;
+ margin-top: -100px;
+ margin-left: -100px;
+ will-change: transform;
+ z-index: 100;
+}
+
+.lm-mod-drag-image {
+ will-change: transform;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.jp-lineFormSearch {
+ padding: 4px 12px;
+ background-color: var(--jp-layout-color2);
+ box-shadow: var(--jp-toolbar-box-shadow);
+ z-index: 2;
+ font-size: var(--jp-ui-font-size1);
+}
+
+.jp-lineFormCaption {
+ font-size: var(--jp-ui-font-size0);
+ line-height: var(--jp-ui-font-size1);
+ margin-top: 4px;
+ color: var(--jp-ui-font-color0);
+}
+
+.jp-baseLineForm {
+ border: none;
+ border-radius: 0;
+ position: absolute;
+ background-size: 16px;
+ background-repeat: no-repeat;
+ background-position: center;
+ outline: none;
+}
+
+.jp-lineFormButtonContainer {
+ top: 4px;
+ right: 8px;
+ height: 24px;
+ padding: 0 12px;
+ width: 12px;
+}
+
+.jp-lineFormButtonIcon {
+ top: 0;
+ right: 0;
+ background-color: var(--jp-brand-color1);
+ height: 100%;
+ width: 100%;
+ box-sizing: border-box;
+ padding: 4px 6px;
+}
+
+.jp-lineFormButton {
+ top: 0;
+ right: 0;
+ background-color: transparent;
+ height: 100%;
+ width: 100%;
+ box-sizing: border-box;
+}
+
+.jp-lineFormWrapper {
+ overflow: hidden;
+ padding: 0 8px;
+ border: 1px solid var(--jp-border-color0);
+ background-color: var(--jp-input-active-background);
+ height: 22px;
+}
+
+.jp-lineFormWrapperFocusWithin {
+ border: var(--jp-border-width) solid var(--md-blue-500);
+ box-shadow: inset 0 0 4px var(--md-blue-300);
+}
+
+.jp-lineFormInput {
+ background: transparent;
+ width: 200px;
+ height: 100%;
+ border: none;
+ outline: none;
+ color: var(--jp-ui-font-color0);
+ line-height: 28px;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) 2014-2016, Jupyter Development Team.
+|
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-JSONEditor {
+ display: flex;
+ flex-direction: column;
+ width: 100%;
+}
+
+.jp-JSONEditor-host {
+ flex: 1 1 auto;
+ border: var(--jp-border-width) solid var(--jp-input-border-color);
+ border-radius: 0;
+ background: var(--jp-layout-color0);
+ min-height: 50px;
+ padding: 1px;
+}
+
+.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
+ border-color: red;
+ outline-color: red;
+}
+
+.jp-JSONEditor-header {
+ display: flex;
+ flex: 1 0 auto;
+ padding: 0 0 0 12px;
+}
+
+.jp-JSONEditor-header label {
+ flex: 0 0 auto;
+}
+
+.jp-JSONEditor-commitButton {
+ height: 16px;
+ width: 16px;
+ background-size: 18px;
+ background-repeat: no-repeat;
+ background-position: center;
+}
+
+.jp-JSONEditor-host.jp-mod-focused {
+ background-color: var(--jp-input-active-background);
+ border: 1px solid var(--jp-input-active-border-color);
+ box-shadow: var(--jp-input-box-shadow);
+}
+
+.jp-Editor.jp-mod-dropTarget {
+ border: var(--jp-border-width) solid var(--jp-input-active-border-color);
+ box-shadow: var(--jp-input-box-shadow);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+.jp-DocumentSearch-input {
+ border: none;
+ outline: none;
+ color: var(--jp-ui-font-color0);
+ font-size: var(--jp-ui-font-size1);
+ background-color: var(--jp-layout-color0);
+ font-family: var(--jp-ui-font-family);
+ padding: 2px 1px;
+ resize: none;
+}
+
+.jp-DocumentSearch-overlay {
+ position: absolute;
+ background-color: var(--jp-toolbar-background);
+ border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
+ border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
+ top: 0;
+ right: 0;
+ z-index: 7;
+ min-width: 405px;
+ padding: 2px;
+ font-size: var(--jp-ui-font-size1);
+
+ --jp-private-document-search-button-height: 20px;
+}
+
+.jp-DocumentSearch-overlay button {
+ background-color: var(--jp-toolbar-background);
+ outline: 0;
+}
+
+.jp-DocumentSearch-overlay button:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-DocumentSearch-overlay button:active {
+ background-color: var(--jp-layout-color3);
+}
+
+.jp-DocumentSearch-overlay-row {
+ display: flex;
+ align-items: center;
+ margin-bottom: 2px;
+}
+
+.jp-DocumentSearch-button-content {
+ display: inline-block;
+ cursor: pointer;
+ box-sizing: border-box;
+ width: 100%;
+ height: 100%;
+}
+
+.jp-DocumentSearch-button-content svg {
+ width: 100%;
+ height: 100%;
+}
+
+.jp-DocumentSearch-input-wrapper {
+ border: var(--jp-border-width) solid var(--jp-border-color0);
+ display: flex;
+ background-color: var(--jp-layout-color0);
+ margin: 2px;
+}
+
+.jp-DocumentSearch-input-wrapper:focus-within {
+ border-color: var(--jp-cell-editor-active-border-color);
+}
+
+.jp-DocumentSearch-toggle-wrapper,
+.jp-DocumentSearch-button-wrapper {
+ all: initial;
+ overflow: hidden;
+ display: inline-block;
+ border: none;
+ box-sizing: border-box;
+}
+
+.jp-DocumentSearch-toggle-wrapper {
+ width: 14px;
+ height: 14px;
+}
+
+.jp-DocumentSearch-button-wrapper {
+ width: var(--jp-private-document-search-button-height);
+ height: var(--jp-private-document-search-button-height);
+}
+
+.jp-DocumentSearch-toggle-wrapper:focus,
+.jp-DocumentSearch-button-wrapper:focus {
+ outline: var(--jp-border-width) solid
+ var(--jp-cell-editor-active-border-color);
+ outline-offset: -1px;
+}
+
+.jp-DocumentSearch-toggle-wrapper,
+.jp-DocumentSearch-button-wrapper,
+.jp-DocumentSearch-button-content:focus {
+ outline: none;
+}
+
+.jp-DocumentSearch-toggle-placeholder {
+ width: 5px;
+}
+
+.jp-DocumentSearch-input-button::before {
+ display: block;
+ padding-top: 100%;
+}
+
+.jp-DocumentSearch-input-button-off {
+ opacity: var(--jp-search-toggle-off-opacity);
+}
+
+.jp-DocumentSearch-input-button-off:hover {
+ opacity: var(--jp-search-toggle-hover-opacity);
+}
+
+.jp-DocumentSearch-input-button-on {
+ opacity: var(--jp-search-toggle-on-opacity);
+}
+
+.jp-DocumentSearch-index-counter {
+ padding-left: 10px;
+ padding-right: 10px;
+ user-select: none;
+ min-width: 35px;
+ display: inline-block;
+}
+
+.jp-DocumentSearch-up-down-wrapper {
+ display: inline-block;
+ padding-right: 2px;
+ margin-left: auto;
+ white-space: nowrap;
+}
+
+.jp-DocumentSearch-spacer {
+ margin-left: auto;
+}
+
+.jp-DocumentSearch-up-down-wrapper button {
+ outline: 0;
+ border: none;
+ width: var(--jp-private-document-search-button-height);
+ height: var(--jp-private-document-search-button-height);
+ vertical-align: middle;
+ margin: 1px 5px 2px;
+}
+
+.jp-DocumentSearch-up-down-button:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-DocumentSearch-up-down-button:active {
+ background-color: var(--jp-layout-color3);
+}
+
+.jp-DocumentSearch-filter-button {
+ border-radius: var(--jp-border-radius);
+}
+
+.jp-DocumentSearch-filter-button:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-DocumentSearch-filter-button-enabled {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-DocumentSearch-filter-button-enabled:hover {
+ background-color: var(--jp-layout-color3);
+}
+
+.jp-DocumentSearch-search-options {
+ padding: 0 8px;
+ margin-left: 3px;
+ width: 100%;
+ display: grid;
+ justify-content: start;
+ grid-template-columns: 1fr 1fr;
+ align-items: center;
+ justify-items: stretch;
+}
+
+.jp-DocumentSearch-search-filter-disabled {
+ color: var(--jp-ui-font-color2);
+}
+
+.jp-DocumentSearch-search-filter {
+ display: flex;
+ align-items: center;
+ user-select: none;
+}
+
+.jp-DocumentSearch-regex-error {
+ color: var(--jp-error-color0);
+}
+
+.jp-DocumentSearch-replace-button-wrapper {
+ overflow: hidden;
+ display: inline-block;
+ box-sizing: border-box;
+ border: var(--jp-border-width) solid var(--jp-border-color0);
+ margin: auto 2px;
+ padding: 1px 4px;
+ height: calc(var(--jp-private-document-search-button-height) + 2px);
+}
+
+.jp-DocumentSearch-replace-button-wrapper:focus {
+ border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
+}
+
+.jp-DocumentSearch-replace-button {
+ display: inline-block;
+ text-align: center;
+ cursor: pointer;
+ box-sizing: border-box;
+ color: var(--jp-ui-font-color1);
+
+ /* height - 2 * (padding of wrapper) */
+ line-height: calc(var(--jp-private-document-search-button-height) - 2px);
+ width: 100%;
+ height: 100%;
+}
+
+.jp-DocumentSearch-replace-button:focus {
+ outline: none;
+}
+
+.jp-DocumentSearch-replace-wrapper-class {
+ margin-left: 14px;
+ display: flex;
+}
+
+.jp-DocumentSearch-replace-toggle {
+ border: none;
+ background-color: var(--jp-toolbar-background);
+ border-radius: var(--jp-border-radius);
+}
+
+.jp-DocumentSearch-replace-toggle:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.cm-editor {
+ line-height: var(--jp-code-line-height);
+ font-size: var(--jp-code-font-size);
+ font-family: var(--jp-code-font-family);
+ border: 0;
+ border-radius: 0;
+ height: auto;
+
+ /* Changed to auto to autogrow */
+}
+
+.cm-editor pre {
+ padding: 0 var(--jp-code-padding);
+}
+
+.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
+ background-color: var(--jp-layout-color0);
+ color: var(--jp-content-font-color1);
+}
+
+.jp-CodeMirrorEditor {
+ cursor: text;
+}
+
+/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
+@media screen and (min-width: 2138px) and (max-width: 4319px) {
+ .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
+ border-left: var(--jp-code-cursor-width1) solid
+ var(--jp-editor-cursor-color);
+ }
+}
+
+/* When zoomed out less than 33% */
+@media screen and (min-width: 4320px) {
+ .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
+ border-left: var(--jp-code-cursor-width2) solid
+ var(--jp-editor-cursor-color);
+ }
+}
+
+.cm-editor.jp-mod-readOnly .cm-cursor {
+ display: none;
+}
+
+.jp-CollaboratorCursor {
+ border-left: 5px solid transparent;
+ border-right: 5px solid transparent;
+ border-top: none;
+ border-bottom: 3px solid;
+ background-clip: content-box;
+ margin-left: -5px;
+ margin-right: -5px;
+}
+
+.cm-searching,
+.cm-searching span {
+ /* `.cm-searching span`: we need to override syntax highlighting */
+ background-color: var(--jp-search-unselected-match-background-color);
+ color: var(--jp-search-unselected-match-color);
+}
+
+.cm-searching::selection,
+.cm-searching span::selection {
+ background-color: var(--jp-search-unselected-match-background-color);
+ color: var(--jp-search-unselected-match-color);
+}
+
+.jp-current-match > .cm-searching,
+.jp-current-match > .cm-searching span,
+.cm-searching > .jp-current-match,
+.cm-searching > .jp-current-match span {
+ background-color: var(--jp-search-selected-match-background-color);
+ color: var(--jp-search-selected-match-color);
+}
+
+.jp-current-match > .cm-searching::selection,
+.cm-searching > .jp-current-match::selection,
+.jp-current-match > .cm-searching span::selection {
+ background-color: var(--jp-search-selected-match-background-color);
+ color: var(--jp-search-selected-match-color);
+}
+
+.cm-trailingspace {
+ background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
+ background-position: center left;
+ background-repeat: repeat-x;
+}
+
+.jp-CollaboratorCursor-hover {
+ position: absolute;
+ z-index: 1;
+ transform: translateX(-50%);
+ color: white;
+ border-radius: 3px;
+ padding-left: 4px;
+ padding-right: 4px;
+ padding-top: 1px;
+ padding-bottom: 1px;
+ text-align: center;
+ font-size: var(--jp-ui-font-size1);
+ white-space: nowrap;
+}
+
+.jp-CodeMirror-ruler {
+ border-left: 1px dashed var(--jp-border-color2);
+}
+
+/* Styles for shared cursors (remote cursor locations and selected ranges) */
+.jp-CodeMirrorEditor .cm-ySelectionCaret {
+ position: relative;
+ border-left: 1px solid black;
+ margin-left: -1px;
+ margin-right: -1px;
+ box-sizing: border-box;
+}
+
+.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
+ white-space: nowrap;
+ position: absolute;
+ top: -1.15em;
+ padding-bottom: 0.05em;
+ left: -1px;
+ font-size: 0.95em;
+ font-family: var(--jp-ui-font-family);
+ font-weight: bold;
+ line-height: normal;
+ user-select: none;
+ color: white;
+ padding-left: 2px;
+ padding-right: 2px;
+ z-index: 101;
+ transition: opacity 0.3s ease-in-out;
+}
+
+.jp-CodeMirrorEditor .cm-ySelectionInfo {
+ transition-delay: 0.7s;
+ opacity: 0;
+}
+
+.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
+ opacity: 1;
+ transition-delay: 0s;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-MimeDocument {
+ outline: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Variables
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-private-filebrowser-button-height: 28px;
+ --jp-private-filebrowser-button-width: 48px;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-FileBrowser .jp-SidePanel-content {
+ display: flex;
+ flex-direction: column;
+}
+
+.jp-FileBrowser-toolbar.jp-Toolbar {
+ flex-wrap: wrap;
+ row-gap: 12px;
+ border-bottom: none;
+ height: auto;
+ margin: 8px 12px 0;
+ box-shadow: none;
+ padding: 0;
+ justify-content: flex-start;
+}
+
+.jp-FileBrowser-Panel {
+ flex: 1 1 auto;
+ display: flex;
+ flex-direction: column;
+}
+
+.jp-BreadCrumbs {
+ flex: 0 0 auto;
+ margin: 8px 12px;
+}
+
+.jp-BreadCrumbs-item {
+ margin: 0 2px;
+ padding: 0 2px;
+ border-radius: var(--jp-border-radius);
+ cursor: pointer;
+}
+
+.jp-BreadCrumbs-item:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-BreadCrumbs-item:first-child {
+ margin-left: 0;
+}
+
+.jp-BreadCrumbs-item.jp-mod-dropTarget {
+ background-color: var(--jp-brand-color2);
+ opacity: 0.7;
+}
+
+/*-----------------------------------------------------------------------------
+| Buttons
+|----------------------------------------------------------------------------*/
+
+.jp-FileBrowser-toolbar > .jp-Toolbar-item {
+ flex: 0 0 auto;
+ padding-left: 0;
+ padding-right: 2px;
+ align-items: center;
+ height: unset;
+}
+
+.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
+ width: 40px;
+}
+
+/*-----------------------------------------------------------------------------
+| Other styles
+|----------------------------------------------------------------------------*/
+
+.jp-FileDialog.jp-mod-conflict input {
+ color: var(--jp-error-color1);
+}
+
+.jp-FileDialog .jp-new-name-title {
+ margin-top: 12px;
+}
+
+.jp-LastModified-hidden {
+ display: none;
+}
+
+.jp-FileSize-hidden {
+ display: none;
+}
+
+.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
+ display: none;
+}
+
+/*-----------------------------------------------------------------------------
+| DirListing
+|----------------------------------------------------------------------------*/
+
+.jp-DirListing {
+ flex: 1 1 auto;
+ display: flex;
+ flex-direction: column;
+ outline: 0;
+}
+
+.jp-DirListing-header {
+ flex: 0 0 auto;
+ display: flex;
+ flex-direction: row;
+ align-items: center;
+ overflow: hidden;
+ border-top: var(--jp-border-width) solid var(--jp-border-color2);
+ border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
+ box-shadow: var(--jp-toolbar-box-shadow);
+ z-index: 2;
+}
+
+.jp-DirListing-headerItem {
+ padding: 4px 12px 2px;
+ font-weight: 500;
+}
+
+.jp-DirListing-headerItem:hover {
+ background: var(--jp-layout-color2);
+}
+
+.jp-DirListing-headerItem.jp-id-name {
+ flex: 1 0 84px;
+}
+
+.jp-DirListing-headerItem.jp-id-modified {
+ flex: 0 0 112px;
+ border-left: var(--jp-border-width) solid var(--jp-border-color2);
+ text-align: right;
+}
+
+.jp-DirListing-headerItem.jp-id-filesize {
+ flex: 0 0 75px;
+ border-left: var(--jp-border-width) solid var(--jp-border-color2);
+ text-align: right;
+}
+
+.jp-id-narrow {
+ display: none;
+ flex: 0 0 5px;
+ padding: 4px;
+ border-left: var(--jp-border-width) solid var(--jp-border-color2);
+ text-align: right;
+ color: var(--jp-border-color2);
+}
+
+.jp-DirListing-narrow .jp-id-narrow {
+ display: block;
+}
+
+.jp-DirListing-narrow .jp-id-modified,
+.jp-DirListing-narrow .jp-DirListing-itemModified {
+ display: none;
+}
+
+.jp-DirListing-headerItem.jp-mod-selected {
+ font-weight: 600;
+}
+
+/* increase specificity to override bundled default */
+.jp-DirListing-content {
+ flex: 1 1 auto;
+ margin: 0;
+ padding: 0;
+ list-style-type: none;
+ overflow: auto;
+ background-color: var(--jp-layout-color1);
+}
+
+.jp-DirListing-content mark {
+ color: var(--jp-ui-font-color0);
+ background-color: transparent;
+ font-weight: bold;
+}
+
+.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
+ color: var(--jp-ui-inverse-font-color0);
+}
+
+/* Style the directory listing content when a user drops a file to upload */
+.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
+ outline: 5px dashed rgba(128, 128, 128, 0.5);
+ outline-offset: -10px;
+ cursor: copy;
+}
+
+.jp-DirListing-item {
+ display: flex;
+ flex-direction: row;
+ align-items: center;
+ padding: 4px 12px;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.jp-DirListing-checkboxWrapper {
+ /* Increases hit area of checkbox. */
+ padding: 4px;
+}
+
+.jp-DirListing-header
+ .jp-DirListing-checkboxWrapper
+ + .jp-DirListing-headerItem {
+ padding-left: 4px;
+}
+
+.jp-DirListing-content .jp-DirListing-checkboxWrapper {
+ position: relative;
+ left: -4px;
+ margin: -4px 0 -4px -8px;
+}
+
+.jp-DirListing-checkboxWrapper.jp-mod-visible {
+ visibility: visible;
+}
+
+/* For devices that support hovering, hide checkboxes until hovered, selected...
+*/
+@media (hover: hover) {
+ .jp-DirListing-checkboxWrapper {
+ visibility: hidden;
+ }
+
+ .jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
+ .jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
+ visibility: visible;
+ }
+}
+
+.jp-DirListing-item[data-is-dot] {
+ opacity: 75%;
+}
+
+.jp-DirListing-item.jp-mod-selected {
+ color: var(--jp-ui-inverse-font-color1);
+ background: var(--jp-brand-color1);
+}
+
+.jp-DirListing-item.jp-mod-dropTarget {
+ background: var(--jp-brand-color3);
+}
+
+.jp-DirListing-item:hover:not(.jp-mod-selected) {
+ background: var(--jp-layout-color2);
+}
+
+.jp-DirListing-itemIcon {
+ flex: 0 0 20px;
+ margin-right: 4px;
+}
+
+.jp-DirListing-itemText {
+ flex: 1 0 64px;
+ white-space: nowrap;
+ overflow: hidden;
+ text-overflow: ellipsis;
+ user-select: none;
+}
+
+.jp-DirListing-itemText:focus {
+ outline-width: 2px;
+ outline-color: var(--jp-inverse-layout-color1);
+ outline-style: solid;
+ outline-offset: 1px;
+}
+
+.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
+ outline-color: var(--jp-layout-color1);
+}
+
+.jp-DirListing-itemModified {
+ flex: 0 0 125px;
+ text-align: right;
+}
+
+.jp-DirListing-itemFileSize {
+ flex: 0 0 90px;
+ text-align: right;
+}
+
+.jp-DirListing-editor {
+ flex: 1 0 64px;
+ outline: none;
+ border: none;
+ color: var(--jp-ui-font-color1);
+ background-color: var(--jp-layout-color1);
+}
+
+.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
+ color: var(--jp-success-color1);
+ content: '\25CF';
+ font-size: 8px;
+ position: absolute;
+ left: -8px;
+}
+
+.jp-DirListing-item.jp-mod-running.jp-mod-selected
+ .jp-DirListing-itemIcon::before {
+ color: var(--jp-ui-inverse-font-color1);
+}
+
+.jp-DirListing-item.lm-mod-drag-image,
+.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
+ font-size: var(--jp-ui-font-size1);
+ padding-left: 4px;
+ margin-left: 4px;
+ width: 160px;
+ background-color: var(--jp-ui-inverse-font-color2);
+ box-shadow: var(--jp-elevation-z2);
+ border-radius: 0;
+ color: var(--jp-ui-font-color1);
+ transform: translateX(-40%) translateY(-58%);
+}
+
+.jp-Document {
+ min-width: 120px;
+ min-height: 120px;
+ outline: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Main OutputArea
+| OutputArea has a list of Outputs
+|----------------------------------------------------------------------------*/
+
+.jp-OutputArea {
+ overflow-y: auto;
+}
+
+.jp-OutputArea-child {
+ display: table;
+ table-layout: fixed;
+ width: 100%;
+ overflow: hidden;
+}
+
+.jp-OutputPrompt {
+ width: var(--jp-cell-prompt-width);
+ color: var(--jp-cell-outprompt-font-color);
+ font-family: var(--jp-cell-prompt-font-family);
+ padding: var(--jp-code-padding);
+ letter-spacing: var(--jp-cell-prompt-letter-spacing);
+ line-height: var(--jp-code-line-height);
+ font-size: var(--jp-code-font-size);
+ border: var(--jp-border-width) solid transparent;
+ opacity: var(--jp-cell-prompt-opacity);
+
+ /* Right align prompt text, don't wrap to handle large prompt numbers */
+ text-align: right;
+ white-space: nowrap;
+ overflow: hidden;
+ text-overflow: ellipsis;
+
+ /* Disable text selection */
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.jp-OutputArea-prompt {
+ display: table-cell;
+ vertical-align: top;
+}
+
+.jp-OutputArea-output {
+ display: table-cell;
+ width: 100%;
+ height: auto;
+ overflow: auto;
+ user-select: text;
+ -moz-user-select: text;
+ -webkit-user-select: text;
+ -ms-user-select: text;
+}
+
+.jp-OutputArea .jp-RenderedText {
+ padding-left: 1ch;
+}
+
+/**
+ * Prompt overlay.
+ */
+
+.jp-OutputArea-promptOverlay {
+ position: absolute;
+ top: 0;
+ width: var(--jp-cell-prompt-width);
+ height: 100%;
+ opacity: 0.5;
+}
+
+.jp-OutputArea-promptOverlay:hover {
+ background: var(--jp-layout-color2);
+ box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
+ cursor: zoom-out;
+}
+
+.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
+ cursor: zoom-in;
+}
+
+/**
+ * Isolated output.
+ */
+.jp-OutputArea-output.jp-mod-isolated {
+ width: 100%;
+ display: block;
+}
+
+/*
+When drag events occur, `lm-mod-override-cursor` is added to the body.
+Because iframes steal all cursor events, the following two rules are necessary
+to suppress pointer events while resize drags are occurring. There may be a
+better solution to this problem.
+*/
+body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
+ position: relative;
+}
+
+body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
+ content: '';
+ position: absolute;
+ top: 0;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ background: transparent;
+}
+
+/* pre */
+
+.jp-OutputArea-output pre {
+ border: none;
+ margin: 0;
+ padding: 0;
+ overflow-x: auto;
+ overflow-y: auto;
+ word-break: break-all;
+ word-wrap: break-word;
+ white-space: pre-wrap;
+}
+
+/* tables */
+
+.jp-OutputArea-output.jp-RenderedHTMLCommon table {
+ margin-left: 0;
+ margin-right: 0;
+}
+
+/* description lists */
+
+.jp-OutputArea-output dl,
+.jp-OutputArea-output dt,
+.jp-OutputArea-output dd {
+ display: block;
+}
+
+.jp-OutputArea-output dl {
+ width: 100%;
+ overflow: hidden;
+ padding: 0;
+ margin: 0;
+}
+
+.jp-OutputArea-output dt {
+ font-weight: bold;
+ float: left;
+ width: 20%;
+ padding: 0;
+ margin: 0;
+}
+
+.jp-OutputArea-output dd {
+ float: left;
+ width: 80%;
+ padding: 0;
+ margin: 0;
+}
+
+.jp-TrimmedOutputs pre {
+ background: var(--jp-layout-color3);
+ font-size: calc(var(--jp-code-font-size) * 1.4);
+ text-align: center;
+ text-transform: uppercase;
+}
+
+/* Hide the gutter in case of
+ * - nested output areas (e.g. in the case of output widgets)
+ * - mirrored output areas
+ */
+.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
+ display: none;
+}
+
+/* Hide empty lines in the output area, for instance due to cleared widgets */
+.jp-OutputArea-prompt:empty {
+ padding: 0;
+ border: 0;
+}
+
+/*-----------------------------------------------------------------------------
+| executeResult is added to any Output-result for the display of the object
+| returned by a cell
+|----------------------------------------------------------------------------*/
+
+.jp-OutputArea-output.jp-OutputArea-executeResult {
+ margin-left: 0;
+ width: 100%;
+}
+
+/* Text output with the Out[] prompt needs a top padding to match the
+ * alignment of the Out[] prompt itself.
+ */
+.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
+ padding-top: var(--jp-code-padding);
+ border-top: var(--jp-border-width) solid transparent;
+}
+
+/*-----------------------------------------------------------------------------
+| The Stdin output
+|----------------------------------------------------------------------------*/
+
+.jp-Stdin-prompt {
+ color: var(--jp-content-font-color0);
+ padding-right: var(--jp-code-padding);
+ vertical-align: baseline;
+ flex: 0 0 auto;
+}
+
+.jp-Stdin-input {
+ font-family: var(--jp-code-font-family);
+ font-size: inherit;
+ color: inherit;
+ background-color: inherit;
+ width: 42%;
+ min-width: 200px;
+
+ /* make sure input baseline aligns with prompt */
+ vertical-align: baseline;
+
+ /* padding + margin = 0.5em between prompt and cursor */
+ padding: 0 0.25em;
+ margin: 0 0.25em;
+ flex: 0 0 70%;
+}
+
+.jp-Stdin-input::placeholder {
+ opacity: 0;
+}
+
+.jp-Stdin-input:focus {
+ box-shadow: none;
+}
+
+.jp-Stdin-input:focus::placeholder {
+ opacity: 1;
+}
+
+/*-----------------------------------------------------------------------------
+| Output Area View
+|----------------------------------------------------------------------------*/
+
+.jp-LinkedOutputView .jp-OutputArea {
+ height: 100%;
+ display: block;
+}
+
+.jp-LinkedOutputView .jp-OutputArea-output:only-child {
+ height: 100%;
+}
+
+/*-----------------------------------------------------------------------------
+| Printing
+|----------------------------------------------------------------------------*/
+
+@media print {
+ .jp-OutputArea-child {
+ break-inside: avoid-page;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Mobile
+|----------------------------------------------------------------------------*/
+@media only screen and (max-width: 760px) {
+ .jp-OutputPrompt {
+ display: table-row;
+ text-align: left;
+ }
+
+ .jp-OutputArea-child .jp-OutputArea-output {
+ display: table-row;
+ margin-left: var(--jp-notebook-padding);
+ }
+}
+
+/* Trimmed outputs warning */
+.jp-TrimmedOutputs > a {
+ margin: 10px;
+ text-decoration: none;
+ cursor: pointer;
+}
+
+.jp-TrimmedOutputs > a:hover {
+ text-decoration: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Table of Contents
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-private-toc-active-width: 4px;
+}
+
+.jp-TableOfContents {
+ display: flex;
+ flex-direction: column;
+ background: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ font-size: var(--jp-ui-font-size1);
+ height: 100%;
+}
+
+.jp-TableOfContents-placeholder {
+ text-align: center;
+}
+
+.jp-TableOfContents-placeholderContent {
+ color: var(--jp-content-font-color2);
+ padding: 8px;
+}
+
+.jp-TableOfContents-placeholderContent > h3 {
+ margin-bottom: var(--jp-content-heading-margin-bottom);
+}
+
+.jp-TableOfContents .jp-SidePanel-content {
+ overflow-y: auto;
+}
+
+.jp-TableOfContents-tree {
+ margin: 4px;
+}
+
+.jp-TableOfContents ol {
+ list-style-type: none;
+}
+
+/* stylelint-disable-next-line selector-max-type */
+.jp-TableOfContents li > ol {
+ /* Align left border with triangle icon center */
+ padding-left: 11px;
+}
+
+.jp-TableOfContents-content {
+ /* left margin for the active heading indicator */
+ margin: 0 0 0 var(--jp-private-toc-active-width);
+ padding: 0;
+ background-color: var(--jp-layout-color1);
+}
+
+.jp-tocItem {
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.jp-tocItem-heading {
+ display: flex;
+ cursor: pointer;
+}
+
+.jp-tocItem-heading:hover {
+ background-color: var(--jp-layout-color2);
+}
+
+.jp-tocItem-content {
+ display: block;
+ padding: 4px 0;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+ overflow-x: hidden;
+}
+
+.jp-tocItem-collapser {
+ height: 20px;
+ margin: 2px 2px 0;
+ padding: 0;
+ background: none;
+ border: none;
+ cursor: pointer;
+}
+
+.jp-tocItem-collapser:hover {
+ background-color: var(--jp-layout-color3);
+}
+
+/* Active heading indicator */
+
+.jp-tocItem-heading::before {
+ content: ' ';
+ background: transparent;
+ width: var(--jp-private-toc-active-width);
+ height: 24px;
+ position: absolute;
+ left: 0;
+ border-radius: var(--jp-border-radius);
+}
+
+.jp-tocItem-heading.jp-tocItem-active::before {
+ background-color: var(--jp-brand-color1);
+}
+
+.jp-tocItem-heading:hover.jp-tocItem-active::before {
+ background: var(--jp-brand-color0);
+ opacity: 1;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Collapser {
+ flex: 0 0 var(--jp-cell-collapser-width);
+ padding: 0;
+ margin: 0;
+ border: none;
+ outline: none;
+ background: transparent;
+ border-radius: var(--jp-border-radius);
+ opacity: 1;
+}
+
+.jp-Collapser-child {
+ display: block;
+ width: 100%;
+ box-sizing: border-box;
+
+ /* height: 100% doesn't work because the height of its parent is computed from content */
+ position: absolute;
+ top: 0;
+ bottom: 0;
+}
+
+/*-----------------------------------------------------------------------------
+| Printing
+|----------------------------------------------------------------------------*/
+
+/*
+Hiding collapsers in print mode.
+
+Note: input and output wrappers have "display: block" propery in print mode.
+*/
+
+@media print {
+ .jp-Collapser {
+ display: none;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Header/Footer
+|----------------------------------------------------------------------------*/
+
+/* Hidden by zero height by default */
+.jp-CellHeader,
+.jp-CellFooter {
+ height: 0;
+ width: 100%;
+ padding: 0;
+ margin: 0;
+ border: none;
+ outline: none;
+ background: transparent;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Input
+|----------------------------------------------------------------------------*/
+
+/* All input areas */
+.jp-InputArea {
+ display: table;
+ table-layout: fixed;
+ width: 100%;
+ overflow: hidden;
+}
+
+.jp-InputArea-editor {
+ display: table-cell;
+ overflow: hidden;
+ vertical-align: top;
+
+ /* This is the non-active, default styling */
+ border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
+ border-radius: 0;
+ background: var(--jp-cell-editor-background);
+}
+
+.jp-InputPrompt {
+ display: table-cell;
+ vertical-align: top;
+ width: var(--jp-cell-prompt-width);
+ color: var(--jp-cell-inprompt-font-color);
+ font-family: var(--jp-cell-prompt-font-family);
+ padding: var(--jp-code-padding);
+ letter-spacing: var(--jp-cell-prompt-letter-spacing);
+ opacity: var(--jp-cell-prompt-opacity);
+ line-height: var(--jp-code-line-height);
+ font-size: var(--jp-code-font-size);
+ border: var(--jp-border-width) solid transparent;
+
+ /* Right align prompt text, don't wrap to handle large prompt numbers */
+ text-align: right;
+ white-space: nowrap;
+ overflow: hidden;
+ text-overflow: ellipsis;
+
+ /* Disable text selection */
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Mobile
+|----------------------------------------------------------------------------*/
+@media only screen and (max-width: 760px) {
+ .jp-InputArea-editor {
+ display: table-row;
+ margin-left: var(--jp-notebook-padding);
+ }
+
+ .jp-InputPrompt {
+ display: table-row;
+ text-align: left;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Placeholder
+|----------------------------------------------------------------------------*/
+
+.jp-Placeholder {
+ display: table;
+ table-layout: fixed;
+ width: 100%;
+}
+
+.jp-Placeholder-prompt {
+ display: table-cell;
+ box-sizing: border-box;
+}
+
+.jp-Placeholder-content {
+ display: table-cell;
+ padding: 4px 6px;
+ border: 1px solid transparent;
+ border-radius: 0;
+ background: none;
+ box-sizing: border-box;
+ cursor: pointer;
+}
+
+.jp-Placeholder-contentContainer {
+ display: flex;
+}
+
+.jp-Placeholder-content:hover,
+.jp-InputPlaceholder > .jp-Placeholder-content:hover {
+ border-color: var(--jp-layout-color3);
+}
+
+.jp-Placeholder-content .jp-MoreHorizIcon {
+ width: 32px;
+ height: 16px;
+ border: 1px solid transparent;
+ border-radius: var(--jp-border-radius);
+}
+
+.jp-Placeholder-content .jp-MoreHorizIcon:hover {
+ border: 1px solid var(--jp-border-color1);
+ box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
+ background-color: var(--jp-layout-color0);
+}
+
+.jp-PlaceholderText {
+ white-space: nowrap;
+ overflow-x: hidden;
+ color: var(--jp-inverse-layout-color3);
+ font-family: var(--jp-code-font-family);
+}
+
+.jp-InputPlaceholder > .jp-Placeholder-content {
+ border-color: var(--jp-cell-editor-border-color);
+ background: var(--jp-cell-editor-background);
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Private CSS variables
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-private-cell-scrolling-output-offset: 5px;
+}
+
+/*-----------------------------------------------------------------------------
+| Cell
+|----------------------------------------------------------------------------*/
+
+.jp-Cell {
+ padding: var(--jp-cell-padding);
+ margin: 0;
+ border: none;
+ outline: none;
+ background: transparent;
+}
+
+/*-----------------------------------------------------------------------------
+| Common input/output
+|----------------------------------------------------------------------------*/
+
+.jp-Cell-inputWrapper,
+.jp-Cell-outputWrapper {
+ display: flex;
+ flex-direction: row;
+ padding: 0;
+ margin: 0;
+
+ /* Added to reveal the box-shadow on the input and output collapsers. */
+ overflow: visible;
+}
+
+/* Only input/output areas inside cells */
+.jp-Cell-inputArea,
+.jp-Cell-outputArea {
+ flex: 1 1 auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Collapser
+|----------------------------------------------------------------------------*/
+
+/* Make the output collapser disappear when there is not output, but do so
+ * in a manner that leaves it in the layout and preserves its width.
+ */
+.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
+ border: none !important;
+ background: transparent !important;
+}
+
+.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
+ min-height: var(--jp-cell-collapser-min-height);
+}
+
+/*-----------------------------------------------------------------------------
+| Output
+|----------------------------------------------------------------------------*/
+
+/* Put a space between input and output when there IS output */
+.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
+ margin-top: 5px;
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
+ overflow-y: auto;
+ max-height: 24em;
+ margin-left: var(--jp-private-cell-scrolling-output-offset);
+ resize: vertical;
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
+ max-height: unset;
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
+ content: ' ';
+ box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
+ width: 100%;
+ height: 100%;
+ position: sticky;
+ bottom: 0;
+ top: 0;
+ margin-top: -50%;
+ float: left;
+ display: block;
+ pointer-events: none;
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
+ padding-top: 6px;
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
+ width: calc(
+ var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
+ );
+}
+
+.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
+ left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
+}
+
+/*-----------------------------------------------------------------------------
+| CodeCell
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| MarkdownCell
+|----------------------------------------------------------------------------*/
+
+.jp-MarkdownOutput {
+ display: table-cell;
+ width: 100%;
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-left: var(--jp-code-padding);
+}
+
+.jp-MarkdownOutput.jp-RenderedHTMLCommon {
+ overflow: auto;
+}
+
+/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
+.jp-collapseHeadingButton {
+ display: flex;
+ min-height: var(--jp-cell-collapser-min-height);
+ font-size: var(--jp-code-font-size);
+ position: absolute;
+ background-color: transparent;
+ background-size: 25px;
+ background-repeat: no-repeat;
+ background-position-x: center;
+ background-position-y: top;
+ background-image: var(--jp-icon-caret-down);
+ right: 0;
+ top: 0;
+ bottom: 0;
+}
+
+.jp-collapseHeadingButton.jp-mod-collapsed {
+ background-image: var(--jp-icon-caret-right);
+}
+
+/*
+ set the container font size to match that of content
+ so that the nested collapse buttons have the right size
+*/
+.jp-MarkdownCell .jp-InputPrompt {
+ font-size: var(--jp-content-font-size1);
+}
+
+/*
+ Align collapseHeadingButton with cell top header
+ The font sizes are identical to the ones in packages/rendermime/style/base.css
+*/
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
+ font-size: var(--jp-content-font-size5);
+ background-position-y: calc(0.3 * var(--jp-content-font-size5));
+}
+
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
+ font-size: var(--jp-content-font-size4);
+ background-position-y: calc(0.3 * var(--jp-content-font-size4));
+}
+
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
+ font-size: var(--jp-content-font-size3);
+ background-position-y: calc(0.3 * var(--jp-content-font-size3));
+}
+
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
+ font-size: var(--jp-content-font-size2);
+ background-position-y: calc(0.3 * var(--jp-content-font-size2));
+}
+
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
+ font-size: var(--jp-content-font-size1);
+ background-position-y: top;
+}
+
+.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
+ font-size: var(--jp-content-font-size0);
+ background-position-y: top;
+}
+
+/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
+.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
+ display: none;
+}
+
+.jp-Notebook.jp-mod-showHiddenCellsButton
+ :is(.jp-MarkdownCell:hover, .jp-mod-active)
+ .jp-collapseHeadingButton {
+ display: flex;
+}
+
+/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
+is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
+.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
+ margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
+ margin-top: var(--jp-code-padding);
+ border: 1px solid var(--jp-border-color2);
+ background-color: var(--jp-border-color3) !important;
+ color: var(--jp-content-font-color0) !important;
+ display: flex;
+}
+
+.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
+ background-color: var(--jp-border-color2) !important;
+}
+
+.jp-showHiddenCellsButton {
+ display: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Printing
+|----------------------------------------------------------------------------*/
+
+/*
+Using block instead of flex to allow the use of the break-inside CSS property for
+cell outputs.
+*/
+
+@media print {
+ .jp-Cell-inputWrapper,
+ .jp-Cell-outputWrapper {
+ display: block;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Variables
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-notebook-toolbar-padding: 2px 5px 2px 2px;
+}
+
+/*-----------------------------------------------------------------------------
+
+/*-----------------------------------------------------------------------------
+| Styles
+|----------------------------------------------------------------------------*/
+
+.jp-NotebookPanel-toolbar {
+ padding: var(--jp-notebook-toolbar-padding);
+
+ /* disable paint containment from lumino 2.0 default strict CSS containment */
+ contain: style size !important;
+}
+
+.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
+ border: none;
+ box-shadow: none;
+}
+
+.jp-Notebook-toolbarCellTypeDropdown select {
+ height: 24px;
+ font-size: var(--jp-ui-font-size1);
+ line-height: 14px;
+ border-radius: 0;
+ display: block;
+}
+
+.jp-Notebook-toolbarCellTypeDropdown span {
+ top: 5px !important;
+}
+
+.jp-Toolbar-responsive-popup {
+ position: absolute;
+ height: fit-content;
+ display: flex;
+ flex-direction: row;
+ flex-wrap: wrap;
+ justify-content: flex-end;
+ border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
+ box-shadow: var(--jp-toolbar-box-shadow);
+ background: var(--jp-toolbar-background);
+ min-height: var(--jp-toolbar-micro-height);
+ padding: var(--jp-notebook-toolbar-padding);
+ z-index: 1;
+ right: 0;
+ top: 0;
+}
+
+.jp-Toolbar > .jp-Toolbar-responsive-opener {
+ margin-left: auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Variables
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+
+/*-----------------------------------------------------------------------------
+| Styles
+|----------------------------------------------------------------------------*/
+
+.jp-Notebook-ExecutionIndicator {
+ position: relative;
+ display: inline-block;
+ height: 100%;
+ z-index: 9997;
+}
+
+.jp-Notebook-ExecutionIndicator-tooltip {
+ visibility: hidden;
+ height: auto;
+ width: max-content;
+ width: -moz-max-content;
+ background-color: var(--jp-layout-color2);
+ color: var(--jp-ui-font-color1);
+ text-align: justify;
+ border-radius: 6px;
+ padding: 0 5px;
+ position: fixed;
+ display: table;
+}
+
+.jp-Notebook-ExecutionIndicator-tooltip.up {
+ transform: translateX(-50%) translateY(-100%) translateY(-32px);
+}
+
+.jp-Notebook-ExecutionIndicator-tooltip.down {
+ transform: translateX(calc(-100% + 16px)) translateY(5px);
+}
+
+.jp-Notebook-ExecutionIndicator-tooltip.hidden {
+ display: none;
+}
+
+.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
+ visibility: visible;
+}
+
+.jp-Notebook-ExecutionIndicator span {
+ font-size: var(--jp-ui-font-size1);
+ font-family: var(--jp-ui-font-family);
+ color: var(--jp-ui-font-color1);
+ line-height: 24px;
+ display: block;
+}
+
+.jp-Notebook-ExecutionIndicator-progress-bar {
+ display: flex;
+ justify-content: center;
+ height: 100%;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*
+ * Execution indicator
+ */
+.jp-tocItem-content::after {
+ content: '';
+
+ /* Must be identical to form a circle */
+ width: 12px;
+ height: 12px;
+ background: none;
+ border: none;
+ position: absolute;
+ right: 0;
+}
+
+.jp-tocItem-content[data-running='0']::after {
+ border-radius: 50%;
+ border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
+ background: none;
+}
+
+.jp-tocItem-content[data-running='1']::after {
+ border-radius: 50%;
+ border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
+ background-color: var(--jp-inverse-layout-color3);
+}
+
+.jp-tocItem-content[data-running='0'],
+.jp-tocItem-content[data-running='1'] {
+ margin-right: 12px;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.jp-Notebook-footer {
+ height: 27px;
+ margin-left: calc(
+ var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
+ var(--jp-cell-padding)
+ );
+ width: calc(
+ 100% -
+ (
+ var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
+ var(--jp-cell-padding) + var(--jp-cell-padding)
+ )
+ );
+ border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
+ color: var(--jp-ui-font-color3);
+ margin-top: 6px;
+ background: none;
+ cursor: pointer;
+}
+
+.jp-Notebook-footer:focus {
+ border-color: var(--jp-cell-editor-active-border-color);
+}
+
+/* For devices that support hovering, hide footer until hover */
+@media (hover: hover) {
+ .jp-Notebook-footer {
+ opacity: 0;
+ }
+
+ .jp-Notebook-footer:focus,
+ .jp-Notebook-footer:hover {
+ opacity: 1;
+ }
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Imports
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| CSS variables
+|----------------------------------------------------------------------------*/
+
+:root {
+ --jp-side-by-side-output-size: 1fr;
+ --jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
+ --jp-private-notebook-dragImage-width: 304px;
+ --jp-private-notebook-dragImage-height: 36px;
+ --jp-private-notebook-selected-color: var(--md-blue-400);
+ --jp-private-notebook-active-color: var(--md-green-400);
+}
+
+/*-----------------------------------------------------------------------------
+| Notebook
+|----------------------------------------------------------------------------*/
+
+/* stylelint-disable selector-max-class */
+
+.jp-NotebookPanel {
+ display: block;
+ height: 100%;
+}
+
+.jp-NotebookPanel.jp-Document {
+ min-width: 240px;
+ min-height: 120px;
+}
+
+.jp-Notebook {
+ padding: var(--jp-notebook-padding);
+ outline: none;
+ overflow: auto;
+ background: var(--jp-layout-color0);
+}
+
+.jp-Notebook.jp-mod-scrollPastEnd::after {
+ display: block;
+ content: '';
+ min-height: var(--jp-notebook-scroll-padding);
+}
+
+.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
+ contain: strict;
+}
+
+.jp-Notebook .jp-Cell {
+ overflow: visible;
+}
+
+.jp-Notebook .jp-Cell .jp-InputPrompt {
+ cursor: move;
+}
+
+/*-----------------------------------------------------------------------------
+| Notebook state related styling
+|
+| The notebook and cells each have states, here are the possibilities:
+|
+| - Notebook
+| - Command
+| - Edit
+| - Cell
+| - None
+| - Active (only one can be active)
+| - Selected (the cells actions are applied to)
+| - Multiselected (when multiple selected, the cursor)
+| - No outputs
+|----------------------------------------------------------------------------*/
+
+/* Command or edit modes */
+
+.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
+ opacity: var(--jp-cell-prompt-not-active-opacity);
+ color: var(--jp-cell-prompt-not-active-font-color);
+}
+
+.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
+ opacity: var(--jp-cell-prompt-not-active-opacity);
+ color: var(--jp-cell-prompt-not-active-font-color);
+}
+
+/* cell is active */
+.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
+ background: var(--jp-brand-color1);
+}
+
+/* cell is dirty */
+.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
+ color: var(--jp-warn-color1);
+}
+
+.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
+ color: var(--jp-warn-color1);
+ content: '•';
+}
+
+.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
+ background: var(--jp-warn-color1);
+}
+
+/* collapser is hovered */
+.jp-Notebook .jp-Cell .jp-Collapser:hover {
+ box-shadow: var(--jp-elevation-z2);
+ background: var(--jp-brand-color1);
+ opacity: var(--jp-cell-collapser-not-active-hover-opacity);
+}
+
+/* cell is active and collapser is hovered */
+.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
+ background: var(--jp-brand-color0);
+ opacity: 1;
+}
+
+/* Command mode */
+
+.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
+ background: var(--jp-notebook-multiselected-color);
+}
+
+.jp-Notebook.jp-mod-commandMode
+ .jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
+ background: transparent;
+}
+
+/* Edit mode */
+
+.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
+ border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
+ box-shadow: var(--jp-input-box-shadow);
+ background-color: var(--jp-cell-editor-active-background);
+}
+
+/*-----------------------------------------------------------------------------
+| Notebook drag and drop
+|----------------------------------------------------------------------------*/
+
+.jp-Notebook-cell.jp-mod-dropSource {
+ opacity: 0.5;
+}
+
+.jp-Notebook-cell.jp-mod-dropTarget,
+.jp-Notebook.jp-mod-commandMode
+ .jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
+ border-top-color: var(--jp-private-notebook-selected-color);
+ border-top-style: solid;
+ border-top-width: 2px;
+}
+
+.jp-dragImage {
+ display: block;
+ flex-direction: row;
+ width: var(--jp-private-notebook-dragImage-width);
+ height: var(--jp-private-notebook-dragImage-height);
+ border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
+ background: var(--jp-cell-editor-background);
+ overflow: visible;
+}
+
+.jp-dragImage-singlePrompt {
+ box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
+}
+
+.jp-dragImage .jp-dragImage-content {
+ flex: 1 1 auto;
+ z-index: 2;
+ font-size: var(--jp-code-font-size);
+ font-family: var(--jp-code-font-family);
+ line-height: var(--jp-code-line-height);
+ padding: var(--jp-code-padding);
+ border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
+ background: var(--jp-cell-editor-background-color);
+ color: var(--jp-content-font-color3);
+ text-align: left;
+ margin: 4px 4px 4px 0;
+}
+
+.jp-dragImage .jp-dragImage-prompt {
+ flex: 0 0 auto;
+ min-width: 36px;
+ color: var(--jp-cell-inprompt-font-color);
+ padding: var(--jp-code-padding);
+ padding-left: 12px;
+ font-family: var(--jp-cell-prompt-font-family);
+ letter-spacing: var(--jp-cell-prompt-letter-spacing);
+ line-height: 1.9;
+ font-size: var(--jp-code-font-size);
+ border: var(--jp-border-width) solid transparent;
+}
+
+.jp-dragImage-multipleBack {
+ z-index: -1;
+ position: absolute;
+ height: 32px;
+ width: 300px;
+ top: 8px;
+ left: 8px;
+ background: var(--jp-layout-color2);
+ border: var(--jp-border-width) solid var(--jp-input-border-color);
+ box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
+}
+
+/*-----------------------------------------------------------------------------
+| Cell toolbar
+|----------------------------------------------------------------------------*/
+
+.jp-NotebookTools {
+ display: block;
+ min-width: var(--jp-sidebar-min-width);
+ color: var(--jp-ui-font-color1);
+ background: var(--jp-layout-color1);
+
+ /* This is needed so that all font sizing of children done in ems is
+ * relative to this base size */
+ font-size: var(--jp-ui-font-size1);
+ overflow: auto;
+}
+
+.jp-ActiveCellTool {
+ padding: 12px 0;
+ display: flex;
+}
+
+.jp-ActiveCellTool-Content {
+ flex: 1 1 auto;
+}
+
+.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
+ background: var(--jp-cell-editor-background);
+ border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
+ border-radius: 0;
+ min-height: 29px;
+}
+
+.jp-ActiveCellTool .jp-InputPrompt {
+ min-width: calc(var(--jp-cell-prompt-width) * 0.75);
+}
+
+.jp-ActiveCellTool-CellContent > pre {
+ padding: 5px 4px;
+ margin: 0;
+ white-space: normal;
+}
+
+.jp-MetadataEditorTool {
+ flex-direction: column;
+ padding: 12px 0;
+}
+
+.jp-RankedPanel > :not(:first-child) {
+ margin-top: 12px;
+}
+
+.jp-KeySelector select.jp-mod-styled {
+ font-size: var(--jp-ui-font-size1);
+ color: var(--jp-ui-font-color0);
+ border: var(--jp-border-width) solid var(--jp-border-color1);
+}
+
+.jp-KeySelector label,
+.jp-MetadataEditorTool label,
+.jp-NumberSetter label {
+ line-height: 1.4;
+}
+
+.jp-NotebookTools .jp-select-wrapper {
+ margin-top: 4px;
+ margin-bottom: 0;
+}
+
+.jp-NumberSetter input {
+ width: 100%;
+ margin-top: 4px;
+}
+
+.jp-NotebookTools .jp-Collapse {
+ margin-top: 16px;
+}
+
+/*-----------------------------------------------------------------------------
+| Presentation Mode (.jp-mod-presentationMode)
+|----------------------------------------------------------------------------*/
+
+.jp-mod-presentationMode .jp-Notebook {
+ --jp-content-font-size1: var(--jp-content-presentation-font-size1);
+ --jp-code-font-size: var(--jp-code-presentation-font-size);
+}
+
+.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
+.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
+ flex: 0 0 110px;
+}
+
+/*-----------------------------------------------------------------------------
+| Side-by-side Mode (.jp-mod-sideBySide)
+|----------------------------------------------------------------------------*/
+.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
+ margin-top: 3em;
+ margin-bottom: 3em;
+ margin-left: 5%;
+ margin-right: 5%;
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
+ display: grid;
+ grid-template-columns: minmax(0, 1fr) min-content minmax(
+ 0,
+ var(--jp-side-by-side-output-size)
+ );
+ grid-template-rows: auto minmax(0, 1fr) auto;
+ grid-template-areas:
+ 'header header header'
+ 'input handle output'
+ 'footer footer footer';
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
+ grid-template-columns: minmax(0, 1fr) min-content minmax(
+ 0,
+ var(--jp-side-by-side-resized-cell)
+ );
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
+ grid-area: header;
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
+ grid-area: input;
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
+ /* overwrite the default margin (no vertical separation needed in side by side move */
+ margin-top: 0;
+ grid-area: output;
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
+ grid-area: footer;
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
+ grid-area: handle;
+ user-select: none;
+ display: block;
+ height: 100%;
+ cursor: ew-resize;
+ padding: 0 var(--jp-cell-padding);
+}
+
+.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
+ content: '';
+ display: block;
+ background: var(--jp-border-color2);
+ height: 100%;
+ width: 5px;
+}
+
+.jp-mod-sideBySide.jp-Notebook
+ .jp-CodeCell.jp-mod-resizedCell
+ .jp-CellResizeHandle::after {
+ background: var(--jp-border-color0);
+}
+
+.jp-CellResizeHandle {
+ display: none;
+}
+
+/*-----------------------------------------------------------------------------
+| Placeholder
+|----------------------------------------------------------------------------*/
+
+.jp-Cell-Placeholder {
+ padding-left: 55px;
+}
+
+.jp-Cell-Placeholder-wrapper {
+ background: #fff;
+ border: 1px solid;
+ border-color: #e5e6e9 #dfe0e4 #d0d1d5;
+ border-radius: 4px;
+ -webkit-border-radius: 4px;
+ margin: 10px 15px;
+}
+
+.jp-Cell-Placeholder-wrapper-inner {
+ padding: 15px;
+ position: relative;
+}
+
+.jp-Cell-Placeholder-wrapper-body {
+ background-repeat: repeat;
+ background-size: 50% auto;
+}
+
+.jp-Cell-Placeholder-wrapper-body div {
+ background: #f6f7f8;
+ background-image: -webkit-linear-gradient(
+ left,
+ #f6f7f8 0%,
+ #edeef1 20%,
+ #f6f7f8 40%,
+ #f6f7f8 100%
+ );
+ background-repeat: no-repeat;
+ background-size: 800px 104px;
+ height: 104px;
+ position: absolute;
+ right: 15px;
+ left: 15px;
+ top: 15px;
+}
+
+div.jp-Cell-Placeholder-h1 {
+ top: 20px;
+ height: 20px;
+ left: 15px;
+ width: 150px;
+}
+
+div.jp-Cell-Placeholder-h2 {
+ left: 15px;
+ top: 50px;
+ height: 10px;
+ width: 100px;
+}
+
+div.jp-Cell-Placeholder-content-1,
+div.jp-Cell-Placeholder-content-2,
+div.jp-Cell-Placeholder-content-3 {
+ left: 15px;
+ right: 15px;
+ height: 10px;
+}
+
+div.jp-Cell-Placeholder-content-1 {
+ top: 100px;
+}
+
+div.jp-Cell-Placeholder-content-2 {
+ top: 120px;
+}
+
+div.jp-Cell-Placeholder-content-3 {
+ top: 140px;
+}
+
+</style>
+<style type="text/css">
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*
+The following CSS variables define the main, public API for styling JupyterLab.
+These variables should be used by all plugins wherever possible. In other
+words, plugins should not define custom colors, sizes, etc unless absolutely
+necessary. This enables users to change the visual theme of JupyterLab
+by changing these variables.
+
+Many variables appear in an ordered sequence (0,1,2,3). These sequences
+are designed to work well together, so for example, `--jp-border-color1` should
+be used with `--jp-layout-color1`. The numbers have the following meanings:
+
+* 0: super-primary, reserved for special emphasis
+* 1: primary, most important under normal situations
+* 2: secondary, next most important under normal situations
+* 3: tertiary, next most important under normal situations
+
+Throughout JupyterLab, we are mostly following principles from Google's
+Material Design when selecting colors. We are not, however, following
+all of MD as it is not optimized for dense, information rich UIs.
+*/
+
+:root {
+ /* Elevation
+ *
+ * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
+ *
+ * https://github.com/material-components/material-components-web
+ * https://material-components-web.appspot.com/elevation.html
+ */
+
+ --jp-shadow-base-lightness: 0;
+ --jp-shadow-umbra-color: rgba(
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ 0.2
+ );
+ --jp-shadow-penumbra-color: rgba(
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ 0.14
+ );
+ --jp-shadow-ambient-color: rgba(
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ var(--jp-shadow-base-lightness),
+ 0.12
+ );
+ --jp-elevation-z0: none;
+ --jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
+ 0 1px 1px 0 var(--jp-shadow-penumbra-color),
+ 0 1px 3px 0 var(--jp-shadow-ambient-color);
+ --jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
+ 0 2px 2px 0 var(--jp-shadow-penumbra-color),
+ 0 1px 5px 0 var(--jp-shadow-ambient-color);
+ --jp-elevation-z4: 0 2px 4px -1px var(--jp-shadow-umbra-color),
+ 0 4px 5px 0 var(--jp-shadow-penumbra-color),
+ 0 1px 10px 0 var(--jp-shadow-ambient-color);
+ --jp-elevation-z6: 0 3px 5px -1px var(--jp-shadow-umbra-color),
+ 0 6px 10px 0 var(--jp-shadow-penumbra-color),
+ 0 1px 18px 0 var(--jp-shadow-ambient-color);
+ --jp-elevation-z8: 0 5px 5px -3px var(--jp-shadow-umbra-color),
+ 0 8px 10px 1px var(--jp-shadow-penumbra-color),
+ 0 3px 14px 2px var(--jp-shadow-ambient-color);
+ --jp-elevation-z12: 0 7px 8px -4px var(--jp-shadow-umbra-color),
+ 0 12px 17px 2px var(--jp-shadow-penumbra-color),
+ 0 5px 22px 4px var(--jp-shadow-ambient-color);
+ --jp-elevation-z16: 0 8px 10px -5px var(--jp-shadow-umbra-color),
+ 0 16px 24px 2px var(--jp-shadow-penumbra-color),
+ 0 6px 30px 5px var(--jp-shadow-ambient-color);
+ --jp-elevation-z20: 0 10px 13px -6px var(--jp-shadow-umbra-color),
+ 0 20px 31px 3px var(--jp-shadow-penumbra-color),
+ 0 8px 38px 7px var(--jp-shadow-ambient-color);
+ --jp-elevation-z24: 0 11px 15px -7px var(--jp-shadow-umbra-color),
+ 0 24px 38px 3px var(--jp-shadow-penumbra-color),
+ 0 9px 46px 8px var(--jp-shadow-ambient-color);
+
+ /* Borders
+ *
+ * The following variables, specify the visual styling of borders in JupyterLab.
+ */
+
+ --jp-border-width: 1px;
+ --jp-border-color0: var(--md-grey-400);
+ --jp-border-color1: var(--md-grey-400);
+ --jp-border-color2: var(--md-grey-300);
+ --jp-border-color3: var(--md-grey-200);
+ --jp-inverse-border-color: var(--md-grey-600);
+ --jp-border-radius: 2px;
+
+ /* UI Fonts
+ *
+ * The UI font CSS variables are used for the typography all of the JupyterLab
+ * user interface elements that are not directly user generated content.
+ *
+ * The font sizing here is done assuming that the body font size of --jp-ui-font-size1
+ * is applied to a parent element. When children elements, such as headings, are sized
+ * in em all things will be computed relative to that body size.
+ */
+
+ --jp-ui-font-scale-factor: 1.2;
+ --jp-ui-font-size0: 0.83333em;
+ --jp-ui-font-size1: 13px; /* Base font size */
+ --jp-ui-font-size2: 1.2em;
+ --jp-ui-font-size3: 1.44em;
+ --jp-ui-font-family: system-ui, -apple-system, blinkmacsystemfont, 'Segoe UI',
+ helvetica, arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji',
+ 'Segoe UI Symbol';
+
+ /*
+ * Use these font colors against the corresponding main layout colors.
+ * In a light theme, these go from dark to light.
+ */
+
+ /* Defaults use Material Design specification */
+ --jp-ui-font-color0: rgba(0, 0, 0, 1);
+ --jp-ui-font-color1: rgba(0, 0, 0, 0.87);
+ --jp-ui-font-color2: rgba(0, 0, 0, 0.54);
+ --jp-ui-font-color3: rgba(0, 0, 0, 0.38);
+
+ /*
+ * Use these against the brand/accent/warn/error colors.
+ * These will typically go from light to darker, in both a dark and light theme.
+ */
+
+ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1);
+ --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1);
+ --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7);
+ --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5);
+
+ /* Content Fonts
+ *
+ * Content font variables are used for typography of user generated content.
+ *
+ * The font sizing here is done assuming that the body font size of --jp-content-font-size1
+ * is applied to a parent element. When children elements, such as headings, are sized
+ * in em all things will be computed relative to that body size.
+ */
+
+ --jp-content-line-height: 1.6;
+ --jp-content-font-scale-factor: 1.2;
+ --jp-content-font-size0: 0.83333em;
+ --jp-content-font-size1: 14px; /* Base font size */
+ --jp-content-font-size2: 1.2em;
+ --jp-content-font-size3: 1.44em;
+ --jp-content-font-size4: 1.728em;
+ --jp-content-font-size5: 2.0736em;
+
+ /* This gives a magnification of about 125% in presentation mode over normal. */
+ --jp-content-presentation-font-size1: 17px;
+ --jp-content-heading-line-height: 1;
+ --jp-content-heading-margin-top: 1.2em;
+ --jp-content-heading-margin-bottom: 0.8em;
+ --jp-content-heading-font-weight: 500;
+
+ /* Defaults use Material Design specification */
+ --jp-content-font-color0: rgba(0, 0, 0, 1);
+ --jp-content-font-color1: rgba(0, 0, 0, 0.87);
+ --jp-content-font-color2: rgba(0, 0, 0, 0.54);
+ --jp-content-font-color3: rgba(0, 0, 0, 0.38);
+ --jp-content-link-color: var(--md-blue-900);
+ --jp-content-font-family: system-ui, -apple-system, blinkmacsystemfont,
+ 'Segoe UI', helvetica, arial, sans-serif, 'Apple Color Emoji',
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+ *
+ * Code font variables are used for typography of code and other monospaces content.
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+
+ --jp-code-font-size: 13px;
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+ * The following are the main layout colors use in JupyterLab. In a light
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+
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+
+ /* Statusbar specific styles */
+
+ --jp-statusbar-height: 24px;
+
+ /* Input field styles */
+
+ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300);
+ --jp-input-active-background: var(--jp-layout-color1);
+ --jp-input-hover-background: var(--jp-layout-color1);
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+ --jp-input-border-color: var(--jp-inverse-border-color);
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+
+ --jp-editor-selected-background: #d9d9d9;
+ --jp-editor-selected-focused-background: #d7d4f0;
+ --jp-editor-cursor-color: var(--jp-ui-font-color0);
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+ /* Code mirror specific styles */
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+ --jp-mirror-editor-keyword-color: #008000;
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+ These colors are used for the cursor, username in the editor,
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+ --jp-sidebar-min-width: 250px;
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+
+ /* Icon colors that work well with light or dark backgrounds */
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+
+ /* Button colors */
+ --jp-accept-color-normal: var(--md-blue-700);
+ --jp-accept-color-hover: var(--md-blue-800);
+ --jp-accept-color-active: var(--md-blue-900);
+ --jp-warn-color-normal: var(--md-red-700);
+ --jp-warn-color-hover: var(--md-red-800);
+ --jp-warn-color-active: var(--md-red-900);
+ --jp-reject-color-normal: var(--md-grey-600);
+ --jp-reject-color-hover: var(--md-grey-700);
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+ --jp-json-icon-color: var(--md-orange-700);
+ --jp-console-icon-background-color: var(--md-blue-700);
+ --jp-console-icon-color: white;
+ --jp-terminal-icon-background-color: var(--md-grey-800);
+ --jp-terminal-icon-color: var(--md-grey-200);
+ --jp-text-editor-icon-color: var(--md-grey-700);
+ --jp-inspector-icon-color: var(--md-grey-700);
+ --jp-switch-color: var(--md-grey-400);
+ --jp-switch-true-position-color: var(--md-orange-900);
+}
+</style>
+<style type="text/css">
+/* Force rendering true colors when outputing to pdf */
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+ -webkit-print-color-adjust: exact;
+}
+
+/* Misc */
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+}
+
+/* Input area styling */
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+ overflow: hidden;
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+.cm-editor.cm-s-jupyter .highlight pre {
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+<!-- End of mermaid configuration --></head>
+<body class="jp-Notebook" data-jp-theme-light="true" data-jp-theme-name="JupyterLab Light">
+<main>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h1 id="WS-2.4:-Atmospheric-Pressure">WS 2.4: Atmospheric Pressure<a class="anchor-link" href="#WS-2.4:-Atmospheric-Pressure">¶</a></h1><h1 style="position: absolute; display: flex; flex-grow: 0; flex-shrink: 0; flex-direction: row-reverse; top: 60px;right: 30px; margin: 0; border: 0">
+<style>
+ .markdown {width:100%; position: relative}
+ article { position: relative }
+ </style>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/tu-logo/TU_P1_full-color.png" style="width:100px"/>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/mude-logo/MUDE_Logo-small.png" style="width:100px"/>
+</h1>
+<h2 style="height: 10px">
+</h2>
+<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 2.4, Time series analysis. For: December 4, 2024.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p>In this workshop we will analyze Atmospheric pressure data. The data is a time series of atmospheric pressure measurements over a period of 2 years, with measurements taken every 4 hours. The first column is the time in days, the second column is the atmospheric pressure in hPa.</p>
+<p>In this workshop we will analyze the time series. We will first fit a functional model to the data in order to stationarize the data. Then we will address the remaining noise and establish a stochastic model by fitting an AR(1) model to the residuals.</p>
+<p>We begin by loading the data and plotting it.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-0.1:-Load-the-data-and-plot-it">Part 0.1: Load the data and plot it<a class="anchor-link" href="#Part-0.1:-Load-the-data-and-plot-it">¶</a></h2><p>This week we are using a new library called <code>statsmodels</code>. This library is very useful for time series analysis. If you don't have it installed, you can install it by running <code>!pip install statsmodels</code> in a code cell. You can also install it by running <code>pip install statsmodels</code> in a terminal of your choice (make sure you are in the right environment activated!).</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">from</span> <span class="nn">statsmodels.graphics.tsaplots</span> <span class="kn">import</span> <span class="n">plot_acf</span>
+<span class="kn">from</span> <span class="nn">scipy.stats</span> <span class="kn">import</span> <span class="n">chi2</span>
+<span class="kn">from</span> <span class="nn">scipy.signal</span> <span class="kn">import</span> <span class="n">periodogram</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">loadtxt</span><span class="p">(</span><span class="s1">'atm_data.txt'</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s1">','</span><span class="p">)</span>
+<span class="n">time</span> <span class="o">=</span> <span class="n">data</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span>
+
+<span class="c1"># dt = YOUR_CODE_HERE # Time step</span>
+<span class="c1"># fs = YOUR_CODE_HERE # Sampling frequency</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">dt</span> <span class="o">=</span> <span class="n">time</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">time</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">fs</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">dt</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [days]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Atmospheric Pressure [hPa]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'2 year of atmospheric pressure data'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-1:-Finding-frequencies-of-periodic-patterns">Part 1: Finding frequencies of periodic patterns<a class="anchor-link" href="#Part-1:-Finding-frequencies-of-periodic-patterns">¶</a></h2><p>We clearly see that the data contains a seasonal pattern. We will start by fitting a functional model to the data in order to make the data stationary. To find the frequency of the seasonal pattern we will use the power spectrum of the data.</p>
+<p>The time series may be influenced by multiple periodic signals at different frequencies; therefore we will apply a method to find the dominant frequency, and then iteratively remove the corresponding signal from the data.</p>
+<p>We will create a function <code>find_frequency</code> that will take the data and an $\mathrm{A}$-matrix as input and return the frequency of the most dominant periodic signal. Note that we cannot have an empty A-matrix when running the function for the first time. Therefore, we first define an A matrix for a linear model that accounts for an intercept and slope, with which <code>find_frequency</code> will then de-trend the time series.</p>
+<p>The function will look like this:</p>
+<ol>
+<li>Using the $\mathrm{A}$-matrix we will fit a model to the data using the least squares method.</li>
+<li>We will calculate the PSD of the residuals of the model.</li>
+<li>We will find the frequency of the most dominant periodic signal in the PSD.</li>
+<li>Optional: we can plot the power spectrum of the data with the highest peak.</li>
+</ol>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h3 id="Create-the-necessary-functions">Create the necessary functions<a class="anchor-link" href="#Create-the-necessary-functions">¶</a></h3>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%">
+<p>
+<b>Task 1.1:</b>
+<p>Read the code in the next Python cell study the contents until you understand what the functions are doing. Then complete the missing parts of the code.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%">
+<p>
+<b>Tip:</b>
+We will write functions that return multiple parameters, but if we are not interested in defining a particular parameter we can use `_` to ignore it. For example, if we write <code>_, b = function(a)</code>, we only define the second output of the function; the first output is not stored in a variable.</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">fit_model</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">plot</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Function to find the least squares solution of the data</span>
+<span class="sd"> data: input data</span>
+<span class="sd"> time: time vector</span>
+<span class="sd"> A: A-matrix to fit the data</span>
+<span class="sd"> plot: boolean to plot the results or not</span>
+<span class="sd"> '''</span>
+
+ <span class="c1"># x_hat = YOUR_CODE_HERE # least squares solution</span>
+ <span class="c1"># y_hat = YOUR_CODE_HERE # model prediction</span>
+ <span class="c1"># e_hat = YOUR_CODE_HERE # residuals</span>
+
+ <span class="c1"># SOLUTION</span>
+ <span class="n">x_hat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">solve</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="n">A</span><span class="p">,</span> <span class="n">A</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="n">data</span><span class="p">)</span>
+ <span class="n">y_hat</span> <span class="o">=</span> <span class="n">A</span> <span class="o">@</span> <span class="n">x_hat</span>
+ <span class="n">e_hat</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="n">y_hat</span>
+ <span class="c1"># END SOLUTION BLOCK</span>
+
+ <span class="k">if</span> <span class="n">plot</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">211</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Estimated data'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [days]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Atmospheric Pressure [hPa]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Data vs Estimated data'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">212</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">e_hat</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [days]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Atmospheric Pressure [hPa]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
+
+ <span class="k">return</span> <span class="n">x_hat</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">e_hat</span>
+
+<span class="k">def</span> <span class="nf">find_frequency</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">fs</span><span class="p">,</span> <span class="n">plot</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Function to find the dominant frequency of the signal</span>
+<span class="sd"> data: input data</span>
+<span class="sd"> time: time vector</span>
+<span class="sd"> A: A-matrix to detrend the data (prior to spectral analysis)</span>
+<span class="sd"> fs: sampling frequency</span>
+<span class="sd"> plot: boolean to plot the psd or not</span>
+<span class="sd"> '''</span>
+ <span class="c1"># Detrending the data</span>
+ <span class="n">_</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">e_hat</span><span class="o">=</span> <span class="n">fit_model</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">)</span>
+
+ <span class="n">N</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+
+ <span class="c1"># Finding the dominant frequency in e_hat</span>
+ <span class="c1"># freqs, pxx = periodogram(YOUR_CODE_HERE, fs=YOUR_CODE_HERE, window='boxcar',</span>
+ <span class="c1"># nfft=N, return_onesided=False,</span>
+ <span class="c1"># scaling='density')</span>
+
+ <span class="c1"># SOLUTION</span>
+ <span class="c1"># Finding the dominant frequency in e_hat</span>
+ <span class="n">freqs</span><span class="p">,</span> <span class="n">pxx</span> <span class="o">=</span> <span class="n">periodogram</span><span class="p">(</span><span class="n">e_hat</span><span class="p">,</span> <span class="n">fs</span><span class="o">=</span><span class="n">fs</span><span class="p">,</span> <span class="n">window</span><span class="o">=</span><span class="s1">'boxcar'</span><span class="p">,</span>
+ <span class="n">nfft</span><span class="o">=</span><span class="n">N</span><span class="p">,</span> <span class="n">return_onesided</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
+ <span class="n">scaling</span><span class="o">=</span><span class="s1">'density'</span><span class="p">)</span>
+ <span class="c1"># END SOLUTION BLOCK</span>
+
+ <span class="c1"># finding the dominant frequency and amplitude</span>
+ <span class="c1"># Note: there are many ways to do this</span>
+ <span class="c1"># amplitude = YOUR_CODE_HERE # Amplitude of the dominant frequency</span>
+ <span class="c1"># dominant_frequency = YOUR_CODE_HERE # Dominant frequency</span>
+
+ <span class="c1"># SOLUTION</span>
+ <span class="c1"># finding the dominant frequency and amplitude</span>
+ <span class="n">dominant_frequency</span><span class="p">,</span> <span class="n">amplitude</span> <span class="o">=</span> <span class="n">freqs</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">pxx</span><span class="p">)],</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">pxx</span><span class="p">)</span>
+ <span class="c1"># END SOLUTION BLOCK</span>
+
+ <span class="c1"># Plotting the PSD</span>
+ <span class="k">if</span> <span class="n">plot</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">211</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">e_hat</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Atmospheric Pressure [hPa]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">212</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">freqs</span><span class="p">[</span><span class="n">freqs</span><span class="o">></span><span class="mi">0</span><span class="p">],</span> <span class="n">pxx</span><span class="p">[</span><span class="n">freqs</span><span class="o">></span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">'PSD of residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Frequency'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'PSD'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Power Spectral Density'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">dominant_frequency</span><span class="p">,</span> <span class="n">amplitude</span><span class="p">,</span> <span class="s1">'ro'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Dominant Frequency'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">xscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
+
+ <span class="k">return</span> <span class="n">dominant_frequency</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%">
+<p>
+<b>Task 1.2:</b>
+<p>How can we use the <code>find_frequency</code> function to find the frequency of all periodic pattern in the data? In other words, how can we iteratively detect the frequencies in the data?</p>
+<p>Write your answer in a bulleted list that describes the procedure in the Markdown cell below.</p>
+<p><em>Hint: we should try to remove frequencies from the data once we have detected them.</em></p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here:</em></p>
+<ul>
+<li>Step 1:</li>
+<li>Step 2:</li>
+<li>Step ...:</li>
+<li>Step n:</li>
+</ul>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%">
+<p>
+<b>Solution:</b>
+<ul>
+<li>Step 1: Run the function</li>
+<li>Step 2: Find dominant frequency</li>
+<li>Step 3: Add the new parameters to the A matrix</li>
+<li>Step 4: Repeat</li>
+</ul>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h3 id="Find-the-first-dominant-frequency">Find the first dominant frequency<a class="anchor-link" href="#Find-the-first-dominant-frequency">¶</a></h3><p>Now we will run <code>find_frequency</code> repeatedly to find the frequencies in the data. For the first iteration we will use an $\mathrm{A}$-matrix that will remove a linear trend from the data. When we have found a frequency we will also remove the corresponding signal from the data in the next iteration.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%">
+<p>
+<b>Task 1.3:</b>
+<p>Set up the $\mathrm{A}$-matrix for a linear trend, remove it from the data, then find the most dominant frequency and print the result.</p>
+<p>The default units of frequency are cumbersome to interpret, so you should convert the result to a better unit.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># A = YOUR_CODE_HERE # A-matrix for linear trend (intercept and slope)</span>
+<span class="c1"># dom_f = find_frequency(YOUR_CODE_HERE)</span>
+<span class="c1"># print(f'Dominant Frequency: {YOUR_CODE_HERE} [YOUR_CODE_HERE]')</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">A</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)),</span> <span class="n">time</span><span class="p">))</span>
+<span class="n">dom_f</span> <span class="o">=</span> <span class="n">find_frequency</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">fs</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Dominant Frequency: </span><span class="si">{</span><span class="n">dom_f</span><span class="o">*</span><span class="mi">365</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> cycle/year'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Dominant Frequency: 1.000 cycle/year
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 1.4:</b>
+<p>
+Look back at the plot of the original time series and confirm whether or not you can see the presence of the signal with the frequency found in the previous task. Write your answer in one sentence in the Markdown cell below.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Solution:</b>
+<p>
+yes there is a clear yearly pattern in the data
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 1.5:</b>
+<p>
+Find a second frequency by repeating the process. Before using <code>find_frequency</code> again, the linear trend and first periodic component should be accounted for.
+<p>Repeat this step until you have removed all dominant signals (you will have to determine when to stop).</p>
+<p>Print the frequencies of all periodic signals found in the data.</p>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># YOUR_CODE_HERE # may be more than one line or more than one cell</span>
+
+<span class="n">A2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span><span class="n">A</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f</span><span class="o">*</span><span class="n">time</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f</span><span class="o">*</span><span class="n">time</span><span class="p">)))</span>
+<span class="n">dom_f2</span> <span class="o">=</span> <span class="n">find_frequency</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A2</span><span class="p">,</span> <span class="n">fs</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Dominant Frequency: </span><span class="si">{</span><span class="n">dom_f2</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> cycle/day'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Dominant Frequency: 1.000
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># third model and third frequency</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">A3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span><span class="n">A2</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f2</span><span class="o">*</span><span class="n">time</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f2</span><span class="o">*</span><span class="n">time</span><span class="p">)))</span>
+<span class="n">dom_f3</span> <span class="o">=</span> <span class="n">find_frequency</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A3</span><span class="p">,</span> <span class="n">fs</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Dominant Frequency: </span><span class="si">{</span><span class="n">dom_f3</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> cycle/day'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Dominant Frequency: 0.073
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 1.6:</b>
+<p>
+Describe the number of steps taken in the previous task and explain in your own words how the dominant frequencies were determined (print them, if you did not already do so).
+<p>How did you decide when to stop?</p>
+<p>Is the final (detrended) time series (residuals) stationary? Explain.</p>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Solution:</b>
+<p>
+<ul>
+<li>First run: we fit a linear model to the data and find the dominant frequency of 1 cycle per year. PSD of the residuals are not stationary, so we need to do this again.</li>
+<li>Second run: we fit a model with a linear trend and a yearly cycle. We find a dominant frequency of 1 cycle per day.</li>
+<li>Third run: the highest PSD is a signal with frequency 0.07 cycle/day, which is about 3 orders of magnitude less than the previous run (comparing the order of magnitude on the y-axis between the previous two plots). Therefore, the third frequency is not necessary.</li>
+<li>The previous point illustrates that the detrended series is indeed stationary.</li>
+</ul>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-2:-Fitting-the-functional-model">Part 2: Fitting the functional model<a class="anchor-link" href="#Part-2:-Fitting-the-functional-model">¶</a></h2><p>In the next cell we will fit the model to generate stationary residuals. Above we have used for each dominant frequency $f_i$ ($i=1,2$) the model:</p>
+$$a_i \cos(2\pi f_i t) + b_i \sin(2\pi f_i t)$$<p>However, to report the periodic signals we would like to have the amplitude, phase shift and the frequency of those signals, which can be recovered from:
+$$A_i \cos(2\pi f_i t + \theta_i)$$
+Where the amplitude $A_i = \sqrt{a_i^2 + b_i^2}$ and $\theta_i = \arctan(-b_i/a_i)$</p>
+<p>Note: in Section 4.1 book this was shown where the angular frequency $\omega = 2\pi f$ was used.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 2:</b>
+<p>
+<p>Complete the missing parts of the code cell below to create the functional model.</p>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p>
+<p>If you want to compute the $\theta_i$ you can use the <code>np.arctan2</code> function. This function is a version of the arctan function that returns the angle in the correct quadrant. Using the <code>np.arctan</code> function will not give you the correct angle!</p></p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">rewrite_seasonal_comp</span><span class="p">(</span><span class="n">ak</span><span class="p">,</span> <span class="n">bk</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Function to rewrite the seasonal component in terms of sin and cos</span>
+<span class="sd"> ak: seasonal component coefficient for cos</span>
+<span class="sd"> bk: seasonal component coefficient for sin</span>
+<span class="sd"> '''</span>
+ <span class="n">Ak</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">ak</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="n">bk</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
+ <span class="n">theta_k</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arctan2</span><span class="p">(</span><span class="o">-</span><span class="n">bk</span><span class="p">,</span> <span class="n">ak</span><span class="p">)</span>
+ <span class="k">return</span> <span class="n">Ak</span><span class="p">,</span> <span class="n">theta_k</span>
+
+<span class="c1"># creating the A matrix of the functional model</span>
+<span class="n">A</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)),</span> <span class="n">time</span><span class="p">,</span>
+ <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f</span><span class="o">*</span><span class="n">time</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f</span><span class="o">*</span><span class="n">time</span><span class="p">),</span>
+ <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f2</span><span class="o">*</span><span class="n">time</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">dom_f2</span><span class="o">*</span><span class="n">time</span><span class="p">)))</span>
+
+<span class="c1"># Finding the Best Linear Unbiased Estimator</span>
+<span class="n">x_hat</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">e_hat</span> <span class="o">=</span> <span class="n">fit_model</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">)</span>
+
+<span class="c1"># Extracting the seasonal component coefficients from the estimated parameters</span>
+<span class="n">a_i</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x_hat</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">x_hat</span><span class="p">[</span><span class="mi">4</span><span class="p">]])</span>
+<span class="n">b_i</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x_hat</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">x_hat</span><span class="p">[</span><span class="mi">5</span><span class="p">]])</span>
+<span class="n">freqs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">dom_f</span><span class="p">,</span> <span class="n">dom_f2</span><span class="p">])</span>
+
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Estimated Parameters:'</span><span class="p">)</span>
+<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x_hat</span><span class="p">)):</span>
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'x</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">x_hat</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="si">:</span><span class="s1">.2f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">The seasonal component is rewritten as:'</span><span class="p">)</span>
+<span class="n">i</span> <span class="o">=</span> <span class="mi">0</span>
+<span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">a_i</span><span class="p">,</span> <span class="n">b_i</span><span class="p">,</span> <span class="n">freqs</span><span class="p">):</span>
+ <span class="n">A_i</span><span class="p">,</span> <span class="n">theta_i</span> <span class="o">=</span> <span class="n">rewrite_seasonal_comp</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
+ <span class="n">i</span> <span class="o">=</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span>
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'A_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">A_i</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">, theta_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">theta_i</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">, f_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">f</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Estimated Parameters:
+x0 = 1012.92
+x1 = 0.00
+x2 = -2.99
+x3 = 0.04
+x4 = -0.07
+x5 = -0.96
+
+The seasonal component is rewritten as:
+A_1 = 2.990, theta_1 = -3.128, f_1 = 0.003
+A_2 = 0.959, theta_2 = 1.642, f_2 = 1.000
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p>Task 4.2 was moved here, since it made more sense to interpret the parameters earlier.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 4.2:</b>
+<p>
+<ul>
+<li><p>What can you say about the parameters, do the parameters make sense?</p>
+</li>
+<li><p>What time of the day is the pressure highest (on average)?</p>
+</li>
+<li><p>What has the highest impact on the pressure, the daily or the yearly periodic signal?</p>
+</li>
+</ul>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Solution:</b>
+<p>
+Yes, the parameters make sense. The average pressure is about 1013 hPa (the intercept); the slope is 0, so there is no increasing/decreasing trend. Looking at the periodic signals we can see that the daily parameter for theta is 1.6, which is around half of pi, or one-quarter of the daily period; therefore the pressure is highest around 6:00-7:00 AM. Looking at the amplitude parameters we can see that the yearly periodic signal has the highest impact on the pressure.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-3:-Analyzing-the-residuals">Part 3: Analyzing the residuals<a class="anchor-link" href="#Part-3:-Analyzing-the-residuals">¶</a></h2><p>Now that we have our residuals we can fit an AR model to the residuals. We will start by plotting the ACF of the residuals. We will then fit an AR model to the residuals and report the parameters of the AR model..</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h3 id="Part-3.1:-Plot-the-ACF-of-the-residuals">Part 3.1: Plot the ACF of the residuals<a class="anchor-link" href="#Part-3.1:-Plot-the-ACF-of-the-residuals">¶</a></h3>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 3.1:</b>
+<p>
+<p>Use the <code>plot_acf</code> function to plot the ACF of the residuals.</p>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+<span class="n">plot_acf</span><span class="p">(</span><span class="n">e_hat</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">lags</span><span class="o">=</span><span class="mi">20</span><span class="p">);</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Lags [days]'</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 3.2:</b>
+<p>
+What can you conclude from this ACF?
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Solution:</b>
+<p>
+The data is autocreated since lags are significant correlated (up to lag 3)
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h3 id="Fit-an-AR(1)-model-to-the-residuals">Fit an AR(1) model to the residuals<a class="anchor-link" href="#Fit-an-AR(1)-model-to-the-residuals">¶</a></h3><p>First we write a function <code>AR1</code> that will take the stationary residuals as input and return the parameters of the AR1 model. Then we will fit this model to the residuals and report the parameters.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 3.3:</b>
+<p>
+Complete the missing parts of the code cell below.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">AR1</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">plot</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Function to find the AR(1) model of the given data</span>
+<span class="sd"> s: input data</span>
+<span class="sd"> return: x_hat, e_hat</span>
+<span class="sd"> '''</span>
+ <span class="n">y</span> <span class="o">=</span> <span class="n">s</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span>
+ <span class="n">y_lag_1</span> <span class="o">=</span> <span class="n">s</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+ <span class="n">A</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">atleast_2d</span><span class="p">(</span><span class="n">y_lag_1</span><span class="p">)</span><span class="o">.</span><span class="n">T</span>
+ <span class="n">x_hat</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">e_hat</span> <span class="o">=</span> <span class="n">fit_model</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">A</span><span class="p">)</span>
+ <span class="k">if</span> <span class="n">plot</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Original Residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">time</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Estimated Residuals'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [days]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Atmospheric Pressure [hPa]'</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Original Data vs Estimated Data'</span><span class="p">)</span>
+ <span class="c1"># plt.xlim([0, 100]) # uncomment this line to zoom in, for better visualization</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Estimated Parameters:'</span><span class="p">)</span>
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'phi = </span><span class="si">{</span><span class="n">x_hat</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s1">.4f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+
+ <span class="k">return</span> <span class="n">x_hat</span><span class="p">,</span> <span class="n">e_hat</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h3 id="Fit-an-AR1-model-to-the-residuals">Fit an AR1 model to the residuals<a class="anchor-link" href="#Fit-an-AR1-model-to-the-residuals">¶</a></h3><p>Fit an AR(1) model to the residuals of the functional model (found in Part 2), then report the parameters. We will need to check if the AR(1) model is a good fit to the residuals, although there are many ways to check whether this is the case. We can use a testing procedure to compare different AR models, an example of this can be found in the book.</p>
+<p>Today is your lucky day: we will use a more simple method. If the AR(1) model is a good fit to the residuals, the residuals of the AR(1) model (output by the <code>AR1</code> function) should be white noise. We will plot the ACF of the residuals of the AR(1) model to check if this is the case.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 3.4:</b>
+<p>
+Complete the missing parts of the code cell below.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [10]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="n">_</span><span class="p">,</span> <span class="n">e_hat2</span> <span class="o">=</span> <span class="n">AR1</span><span class="p">(</span><span class="n">e_hat</span><span class="p">,</span> <span class="n">time</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span>
+
+<span class="c1"># Lets start with the ACF plot</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+<span class="n">plot_acf</span><span class="p">(</span><span class="n">e_hat2</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">lags</span><span class="o">=</span><span class="mi">20</span><span class="p">);</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Estimated Parameters:
+phi = 0.4908
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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23atMHixYttaTt27AidToc+ffpg5MiRyMrKwqJFi5CUlOSQb926dbF582YsWrQIjRo1spm5ueM5XnnlFTRr1gxTpkxBXFwc/vzzT975HTt2YOHChXjnnXdQrVo1sCyLzZs3Izk5GR07dnSav9lstpWJkNdeew16vR7du3fHq6++isaNG6NMmTKIiYlBcHAwKleujJdeeslWBgAwd+5cfPrpp9BqtahZsyYCAgIUP6tSmjdvjhIlSuCrr77CuHHjoNVqsWbNGly8eNEhrVWuadOm2VZW69WrhxYtWmDgwIHo168fwsPD0bp1a/j7++PBgwc4ceIE6tati6+//holSpTA999/j8mTJ2PAgAF4//33ERcXh/Hjx6syyUtOTraVc3p6Om7cuIF169bh+PHj6N27N29zXTX1xrq6uH79elSrVg0+Pj6oW7cuunXrhs2bN2PQoEG2yH6TJk1C+fLlcevWLbVFTiAQnhe8FGyCQCAQ8p3Q0FC2V69ebLly5ViNRsOWLVuWfffdd9mQkBCHtNZIeI8fP5Y8xyUrK4sdPnw4W7ZsWdbHx4dt2rQpGxoayhYrVowdNmyYLZ1UlDx/f39F91m2bBlbs2ZNVq/Xs9WqVWOnTJnCLl261CESm5ooeeBEgfP392erVavG9urVi924cSMvWpuV7du3s/Xr12d9fHzYF154gf3hhx9s0fS4z5WYmMj26tWLLV68OEtRFO9ZlD6HHH/++ScLgPX19XWIFHf9+nW2T58+bPXq1VlfX1+2WLFi7BtvvMGuWLHCab5yUfIAsLdu3WJZlmVnzZrFNm/enC1dujSr0+nYSpUqsf3792ejo6N5+Y0ZM4atUKECS9M0r4ykouTNmDGDd721zmzcuJF3fPny5SwA9syZM7ZjISEhbLNmzVg/Pz+2TJky7IABA9hz586xANjly5fb0mVnZ7MDBgxgy5QpY3s33HJftmwZ26RJE9bf35/19fVlq1evzvbt25cNDw+3pTGbzeyUKVPYihUrsjqdjq1Xrx67fft2xXWvcuXKtjKlKIotUqQIW7NmTfaTTz5h9+7dK3qN0noTHR3NdurUiQ0ICGAB8KI1Tp06la1SpQqr1+vZWrVqsUuWLBH91ggEAsEKxbIe2O2QQCAQCAgJCUGLFi2wZs0afPTRR94Wh0AgEAgEggsQhYlAIBDcwP79+xEaGopGjRrB19cXFy9exNSpU1GsWDFcunTJIQIegUAgEAiEwgHxYSIQCAQ3ULRoUezbtw/BwcF4+vQpSpcujS5dumDKlClEWSIQCAQCoRBDVpgIBAKBQCAQCAQCQQISVpxAIBAIBAKBQCAQJCAKE4FAIBAIBAKBQCBIQBQmAoFAIBAIBAKBQJDguQr6YDabcf/+fQQEBPB2+SYQCAQCgUAgEAjPFyzL4unTp6hQoYLsJvPPlcJ0//59VKxY0dtiEAgEAoFAIBAIhAJCXFwcXnzxRcnzz5XCFBAQAMBSKEWLFvWqLAaDAfv27UOnTp2g1Wq9KsvzCCl/70Pegfch78C7kPL3PuQdeBdS/t7neX8HqampqFixok1HkOK5UpisZnhFixYtEAqTn58fihYt+lxWUG9Dyt/7kHfgfcg78C6k/L0PeQfehZS/9yHvwIIzVx0S9IFAIBAIBAKBQCAQJCAKE4FAIBAIBAKBQCBIQBQmAoFAIBAIBAKBQJDgufJhUgLLsjAajTCZTB69j8FggEajQVZWlsfvRXCkIJQ/wzDQaDQkxD2BQCAQCARCAYYoTBxycnLw4MEDZGRkePxeLMsiMDAQcXFxZMDsBQpK+fv5+aF8+fLQ6XRek4FAIBAIBAKBIA1RmHIxm82IiooCwzCoUKECdDqdRwfSZrMZaWlpKFKkiOxGWQTP4O3yZ1kWOTk5ePz4MaKiovDSSy+RekAgEAgEAoFQACEKUy45OTkwm82oWLEi/Pz8PH4/s9mMnJwc+Pj4kIGyFygI5e/r6wutVouYmBibLAQ7v+6MAMsCP3er7W1RCAQCgUAgPMeQkboAorwQ8hNS38RJzTJgyfEo/HUiCknpOd4Wh0AgEAgEwnMMGa0RCIQCh9HE2v82szIpCQQCgUAgEDwLUZgIBEKBhsREIRAIBAKB4E2IwvScEx0dDYqicOHCBcXXrFixAsWLF/e6HAQCgUAgEAgEgqchCtMzQFxcHPr372+L7le5cmUMHToUCQkJTq+tWLEiHjx4gFdffVXx/T744APcvHkzLyK7RNu2bUFRFCiKgl6vxwsvvIDu3btj8+bNqvOaMGECWrVq5QEpCe6AZYkZHoFAIBAIhIIBUZgKOXfu3EHjxo1x8+ZN/PPPP7h9+zYWL16MgwcPolmzZkhMTJS8NicnBwzDIDAwEBqN8oCJvr6+KFu2rDvEV80XX3yBBw8e4Pbt2/j3339Ru3ZtfPjhhxg4cKBX5CF4HmKRRyAQCAQCwZsQhUkClmWRkWP06L/MHJPocTWz64MHD4ZOp8O+ffvQpk0bVKpUCV26dMGBAwdw7949/PTTT7a0VapUweTJk/HZZ5+hWLFi+OKLL0RN4bZt24aXXnoJvr6+aNeuHVauXAmKopCcnAzA0SRv/PjxaNCgAf7++29UqVIFxYoVw4cffoinT5/a0uzZswctW7ZE8eLFUapUKXTr1g2RkZGq34ufnx8CAwNRsWJFNG3aFNOmTcMff/yBJUuW4MCBA7Z0o0aNwssvvww/Pz9Uq1YNY8eOhcFgsMk/ceJEXLlyBQzDgKIorFixAgAwe/Zs1K1bF/7+/qhYsSIGDRqEtLQ01XISCAQCgUAgEJ4NyD5MEmQaTKj9y16v3DtiYmf46Zy/msTEROzduxe//vorfH19eecCAwPx8ccfY/369Vi4cKFtE94ZM2Zg7Nix+Pnnn0XzjI6ORq9evTB06FAMGDAA58+fx/fff+9UlsjISGzduhU7duxAUlISevfujalTp+LXX38FAKSnp2P48OGoW7cu0tPT8csvv6Bnz564cOFCnkNrf/rppxgxYgQ2b96MDh06AAACAgKwYsUKVKhQAZcvX8YXX3yBgIAAjBw5Eh988AEuX76MXbt24eDBg6BpGsWKFQNgCfM9b948VKlSBVFRURg0aBBGjhyJhQsX5klGAoFAIBAIBELhhChMhZhbt26BZVnUqlVL9HytWrWQlJSEx48f20zo3nzzTZ4CFB0dzbtm8eLFqFmzJmbMmAEAqFmzJq5cuWJTfKQwm81YsWIFAgICAACffPIJDh48aLvuvffe46VfunQpypYti4iICFX+U2LQNI2XX36Z9yxchbBKlSoYMWIE1q9fj5EjR8LX1xdFihSBRqNBYGAgT2H77rvvbH9XrVoVkyZNwtdff00UpnyGeDARCAQCgUAoKBCFSQJfLYOIiZ09lr/ZbMbT1KcIKBrgsMLiq2Xccg+raR/FicvcuHFj2Wtu3LiB119/nXfsjTfecHqvKlWq2JQlAChfvjwePXpk+x0ZGYmxY8fi1KlTePLkCcxmMwAgNjY2zwoTYHlW7nNu2rQJwcHBuH37NtLS0mA0GlG0aFGn+Rw+fBi//fYbIiIikJqaCqPRiKysLKSnp8Pf3z/PchIIBAKBQCAQChfEh0kCiqLgp9N49J+vjhE9TinceKZGjRqgKAoRERGi569fv44SJUqgdOnStmPOBv1CxcN6zBlarZb3m6Iom1IEAN27d0dCQgKWLFmCsLAwhIWFAbAEnsgrJpMJt27dQtWqVQEAp06dwocffoguXbpgx44dOH/+PH766Sen94qJiUFQUBBeffVV/Pvvvzh79iwWLFgAADb/J0L+wK1ySr8HAoFAIBAIBE9AVpgKMaVKlULHjh2xcOFCDBs2jOfHFB8fjzVr1qBv376qBpyvvPIKdu3axTsWHh6eJzkTEhJw7do1/PHHH7ZQ3idOnMhTnlxWrlyJpKQkm9nfyZMnUblyZV7Ai5iYGN41Op0OJpOJdyw8PBxGoxGzZs2yrfpt2LDBbXISXIOEGCcQCAQCgeBNFClM27ZtU51xx44dHQIRENzP/Pnz0bx5c3Tu3BmTJ09G1apVcfXqVfzwww944YUXnPoeCfnyyy8xe/ZsjBo1Cv3798eFCxdsEeRcnekvUaIESpUqhT///BPly5dHbGwsRo8e7VJeGRkZiI+Ph9FoxL1797B582bMmTMHX3/9Ndq1awfAsvIWGxuLdevW4fXXX8fOnTuxZcsWXj6VK1dGbGwsLly4gEqVKiEgIADVq1eH0WjE77//ju7du+PkyZNYvHixS3IS8gbL8WIi6hKBQCAQCARvokhheuedd1RlSlEUbt26hWrVqrkiE0EFL730EsLDwzF+/Hh88MEHSEhIQGBgIN555x2MGzcOJUuWVJVf1apVsWnTJowYMQJz585Fs2bN8NNPP+Hrr7+GXq93SUaaprFu3ToMGTIEr776KmrWrIl58+ahbdu2qvNasmQJlixZAp1Oh1KlSqFRo0ZYv349evbsaUvz9ttvY9iwYfjmm2+QnZ2Nrl27YuzYsRg/frwtzXvvvYeNGzeiffv2SE5OxvLly/HZZ59h9uzZmDZtGsaMGYPWrVtjypQp6Nu3r0vPTcgDHC2JLDARCAQCgUDwJhSrwN6FpmnEx8cr3qw0ICAAFy9eLHAKU2pqKooVK4aUlBSHAABZWVmIiopC1apV4ePj43FZzGYzUlNTUbRo0TyH1fY0v/76KxYvXoy4uDhvi+I2Ckr553e9K0gYDAbs2rULQUFBDj5wD1Oz0OS3gwCA0z+1R9mA56ts8gu5d0DwPKT8vQ95B96FlL/3ed7fgZxuwEXRCtOnn36qyrzuf//7n6KIZISCycKFC/H666+jVKlSOHnyJGbMmIFvvvnG22IRniPIqhKBQCAQCISCgiKFafny5aoyXbRokUvCEAoGt27dwuTJk5GYmIhKlSphxIgRGDNmjLfFIjxHmLkaE1GeCAQCgUAgeBESJY/gwJw5czBnzhxvi0F4jmEl/iYQCAQCgUDIb1xSmM6cOYONGzciNjbWYW+bzZs3u0UwAoHw/MJ1rSTmeQQCgUAgELyJam/3devWoUWLFoiIiMCWLVtgMBgQERGBQ4cOoVixYp6QUZQpU6aAoih89913+XZPAoGQP/At8ojGRCAQCAQCwXuoVph+++03zJkzBzt27IBOp8PcuXNx7do19O7dG5UqVfKEjA6cOXMGf/75J+rVq5cv9yMQCN6DrDARCAQCgUDwJqoVpsjISHTt2hUAoNfrkZ6eDoqiMGzYMPz5559uF1BIWloaPv74YyxZsgQlSpTw+P0IBEL+Q5QkAoFAIBAIBQXVPkwlS5bE06dPAQAvvPACrly5grp16yI5ORkZGRluF1DI4MGD0bVrV3To0AGTJ0+WTZudnY3s7Gzb79TUVACWmPMGg4GX1mAwgGVZmM1mmM1m9wsuwOqjYb0nIX8pKOVvNpvBsiwMBgMYhvGaHN7A+g0Kv0UAyOEcs3yvJD6NJ5B7BwTPQ8rf+5B34F1I+Xuf5/0dKH1u1aOQVq1aYf/+/ahbty569+6NoUOH4tChQ9i/fz/at2+vWlA1rFu3DufOncOZM2cUpZ8yZQomTJjgcHzfvn3w8/PjHdNoNAgMDERaWppDIAtPYlU+Cd7B2+Wfk5ODzMxMHDt2DEaj0auyeIv9+/c7HHuUCVibp0OHD6OkPn9let4QewcEabJNwN10oGoAQFN5z4+Uv/ch78C7kPL3Ps/rO1C62EOxrDrjl8TERGRlZaFChQowm82YOXMmTpw4gRo1amDs2LEeM5OLi4tD48aNsW/fPtSvXx8A0LZtWzRo0ADBwcGi14itMFWsWBFPnjxx2Fg3KysLcXFxqFKlCnx8fDzyDFxYlsXTp08REBAAinJDj+tGVqxYgeHDhyMxMdHboihGrcwFpfyzsrIQHR2NihUr5ku9K0gYDAbs378fHTt2dNhdPOpJOjrNPQkAODy8FV4soXzjbIJy5N4BQZref4bhfFwKfuxSE/2aV3Y5H1L+3oe8A+9Cyt/7PO/vIDU1FaVLl0ZKSoqDbsBF1QpTTEwM9u3bB4PBgDZt2qBOnToYOXIkRo4cmWeBnXH27Fk8evQIjRo1sh0zmUw4duwY5s+fj+zsbAeTJr1eD73ecWpaq9U6VAqTyQSKokDTNGhatWuXaqxmYNZ7uspnn32GlStXOhzv3Lkz9uzZ4/T6KlWq4LvvvuNFG+zTpw+6devm8XJYsWIFvvvuOyQnJ+c5L6uscjJzFSM/Pz8EBgaiZcuWGDJkCK9eKcGZsq4UmqZBUZRonXxeEHt2RmNvmjQazXNbNvnF81z/XOF8XAoA4N9z9zGwTY0850fK3/uQd+BdSPl7n+f1HSh9ZsUK07FjxxAUFGRbutJoNFi5ciX69OnjmoQqad++PS5fvsw71q9fP7zyyisYNWrUc+f/weWtt97C8uXLecfEFEWl+Pr6wtf32ZzRX758Od566y1kZGTgwoULWLNmDZo0aYJly5ahb9++3haPkAsJ+kAgEAgEAqGgoHgJYezYsWjXrh3u3r2LhIQEfP755/mysmQlICAAr776Ku+fv78/SpUqhVdffdX9N2RZICfds/8MGeLHVY4W9Xo9AgMDef+4ppHjx49HpUqVoNfrUaFCBQwZMgSAZZUkJiYGw4YNA0VRthWYFStWoHjx4rzrGzRogGXLlqFSpUooUqQIvv76a5hMJkyfPh2BgYEoW7Ysfv31V55cs2fPRt26deHv74+KFSti0KBBSEtLAwAcOXIE/fr1Q0pKiu3e48ePB2Dx6xk5ciReeOEF+Pv7o0mTJjhy5Agv7xUrVqBSpUrw8/NDz549kZCQoKisihcvjsDAQFSpUgVvvvkmNm7ciI8//hjffPMNkpKSAAAJCQno06cPXnzxRfj5+aFu3br4559/bHl89tlnOHr0KObOnWuTPTo6GiaTCf3790fVqlXh6+uLmjVrYu7cuYrkIgghG9cSCAQCgUAoGCheYbp8+TKOHTuGChUqAABmzZqFJUuWICkp6dkM723IAH6r4LHsaQDFpU7+eB/Q+bvlPps2bcKcOXOwbt061KlTB/Hx8bh48SIAYPPmzahfvz4GDhyIL774QjafyMhI7N69G3v27EFkZCR69eqFqKgovPzyyzh69ChCQkLw+eefo3379mjatKnlGWka8+bNQ5UqVRAVFYVBgwZh5MiRWLhwIZo3b47g4GD88ssvuHHjBgCgSJEiACwrh9HR0Vi3bh0qVKiALVu24K233sLly5fx0ksvISwsDJ9//jl+++03vPvuu9izZw/GjRvnchkNGzYMq1atwv79+9G7d29kZWWhUaNGGDVqFIoWLYqdO3fik08+QbVq1dCkSRPMnTsXN2/exKuvvoqJEycCAMqUKQOz2YwXX3wRGzZsQOnSpRESEoKBAweifPny6N27t8vyPY+QjWsJhQFSNwkEAuH5QLHClJycjLJly9p++/v7w8/PD8nJyV5TmISrDs8rO3bssCkbVkaNGoWxY8ciNjYWgYGB6NChA7RaLSpVqoQ33ngDgCVEPMMwCAgIQGBgoOw9zGYzli1bhoCAANSuXRvt2rXDjRs3sGvXLtA0jZo1a2LatGk4cuSITWHi+kVVrVoVkyZNwtdff42FCxdCp9OhWLFioCiKd+/IyEj8888/uHv3rk05//7777Fnzx4sX74cv/32G+bOnYvOnTtj9OjRAICXX34ZISEhiny2xHjllVcAANHR0QAs4fK///572/lvv/0We/bswcaNG9GkSRMUK1YMOp3O5gdlhWEYXlTGqlWrIiQkBBs2bCAKk0rMXIWJjEkJBRRSNwkEAuH5QFXQh4iICMTHx9t+syyLa9eu8UIz16tXz33SeROtn2Wlx0OYzWakPn2KogEBjoEKtH7iF0nQrl07LFq0iHesZMmSAID3338fwcHBqFatGt566y0EBQWhe/fu0GjURZSvUqUKAgICbL/LlSsHhmF4spcrVw6PHj2y/T58+DB+++03REREIDU1FUajEVlZWUhPT4e/v/gK2rlz58CyLF5++WXe8ezsbJQqVQoAcO3aNfTs2ZN3vlmzZi4rTNZAkVaTRJPJhKlTp2L9+vW4d++eLdqilMxcFi9ejL/++gsxMTHIzMxETk4OGjRo4JJczzPcmXsyJiUQCAQCoXDz+Gk2Zu69gY+aVEL9isW9LY5qVI2a27dvD2EU8m7duoGiKLAsC4qiYDKZ3Cqg16Aot5nFiWI2A1qT5R55jEbn7++PGjXEIzVVrFgRN27cwP79+3HgwAEMGjQIM2bMwNGjR1VFQxGmtUZ2Ex6zRv+LiYlBUFAQvvrqK0yaNAklS5bEiRMn0L9/f9lNwsxmMxiGwdmzZx0CeVhX0VRGwnfKtWvXAFhWhACLuemcOXMQHBxs88H67rvvnO7PtWHDBgwbNgyzZs1Cs2bNEBAQgBkzZiAsLMyt8j4P8EzyyDQ+gUAgEAiFmh+3XMb+iIdYHx6H6KldvS2OahQrTFFRUZ6Ug+BBfH190aNHD/To0QODBw/GK6+8gsuXL6Nhw4bQ6XQeUXLDw8NhNBoxa9Ys2yrUhg0beGnE7v3aa6/BZDLh0aNHaNWqlWjetWvXxqlTp3jHhL/VEBwcjKJFi6JDhw4AgOPHj+Ptt9/G//73PwAWJe7WrVuoVauWrOzHjx9H8+bNMWjQINuxyMhIl+V6niE6EoFAIBAIzw6Rj9K8LUKeUKwwVa7s+uZ8BM+SnZ3NM5UELGHfS5cujRUrVsBkMqFJkybw8/PD33//DV9fX9v7rFKlCo4dO4YPP/wQer0epUuXdotM1atXh9FoxO+//47u3bvj5MmTWLx4MS9NlSpVkJaWhoMHD6J+/frw8/PDyy+/jI8//hh9+/bFrFmz8Nprr+HJkyc4dOgQ6tati6CgIAwZMgTNmzfH9OnT8c4772Dfvn2KzfGSk5MRHx+PzMxMXLhwAatXr8Z///2HVatW2SID1qhRA//++y9CQkJQokQJzJ49G/Hx8TyFqUqVKggLC0N0dDSKFCmCkiVLokaNGli1ahX27t2LqlWr4u+//8aZM2dsK1cE5RCTPEJhgNRNAoFAeD5wyRYsOTkZ+/btw+rVq7Fq1SreP0L+s2fPHpQvX573r2XLlgAsYbSXLFmCFi1aoF69ejh48CC2b99u8weaOHEioqOjUb16dZQpU8ZtMjVo0ACzZ8/GtGnT8Oqrr2LNmjWYMmUKL03z5s3x1Vdf4YMPPkCZMmUwffp0AJa9kvr27YsRI0agZs2a6NGjB8LCwlCxYkUAQNOmTfHXX3/h999/R4MGDbBv3z78/PPPiuTq168fypcvj9q1a2PEiBEoUqQITp8+jY8++siWZuzYsWjYsCE6d+6Mtm3bIjAwEO+88w4vn++//x4Mw6B27dooU6YMYmNj8dVXX+Hdd9/FBx98gCZNmiAhIYG32kRQDkuCPhAIBAKBQCggUKxKB4Ht27fj448/Rnp6OgICAmyO8oDFhyUxMdHtQrqL1NRUFCtWDCkpKShatCjvXFZWFqKiolC1alX4+Ph4XBaz2YzU1FQULVrUMegDweMUlPLP73rnLowmM2ISM1CttD+vDVCDwWDArl27EBQU5OAPd+VeCrr9fgIAcGB4a9QoGyCWBSGPyL0DgjRVRu8EANQoWwQHhrdxOR9S/t6HvAPvQsrf++TXO2g38wiinqQDQIHyYZLTDbioHimOGDECn3/+OZ4+fYrk5GQkJSXZ/hVkZYlAILiPb/85j/azjmJDeJxH8jezZONaAoFAIBCeFQp7ACfVCtO9e/cwZMgQ+PmpC31NIBCeHXZfsfjMLT56xyP5F/J2lUAgEAgEwjOEaoWpc+fOCA8P94QsBAKBAIDvTJ8X3amwz2gRCjakfhEIBMLzgaIoedu2bbP93bVrV/zwww+IiIhA3bp1Hewde/To4V4JCQRCgcU17yXnsG4wycsxmvH2gpOoWa4Igj98zU2SEQgEAoFAeN5QpDAJI4QBluhqQp6FjWvJjCEhPyns9c1T0vNXmFy7y6k7Cbj2IBXXHqQShYlAIBAIBILLKFKYzGazp+XwOtaVsoyMDPj6+npZGsLzQkZGBgCQ6EAC3BFW3MXgfQQCgUAgEAg8FG9c+6zDMAyKFy+OR48eAQD8/PxcDpesBLPZjJycHGRlZZGw4l7A2+XPsiwyMjLw6NEjFC9eHAzD5LsM7sBTK2TuMMljiMZEeE7IMphw+V4KGlYqAYYm9Z5AIBQ8Crc9jUKFad68eRg4cKDifWIWL16Mjz/+GAEBhWvvlMDAQACwKU2ehGVZZGZmwtfX16OKGUGcglL+xYsXt9U7gh13NKw0Z+DIsiz5zghup6AMAL5efRaHbzzG8I4vY0j7l7wtDiEfmHvgFs7HJWFJ38bQMtKTfgciHuKlckVQuZR/PkpHIDx7KFKYhg0bhj59+ihWmEaOHIlOnToVOoWJoiiUL18eZcuWhcFg8Oi9DAYDjh07htatWxdqcyyDySzbWBdUCkL5a7XaQruy5Gl4JnkuDku5M+1mFmA8pC8V1m+A8Oxw+MZjAMCq0BiiMD0nzDlwEwBw4tYTtHulrGiaYzcfY8AqS1TjgrRRKIFQGFGkMLEsi/bt20OjUWbBl5mZmSehvA3DMB4fyDIMA6PRCB8fn0KrMB258QgD/z6LiT3q4MM3KuXLPY0mMzRuGJw+C+VfEPBY0Ac3mOTRnBUlo9kMhnb/N7378gN8veYcZr1fH+81etHt+RMKOAVliSkXDTHHey7IMdr9yvUa6f7wXGxSfohT6ElMz4GZZVG6iN7bohAKMIo0oHHjxqnK9O2330bJkiVdEohQePhs+RkAwOjNl/NFYQqNTMDnK87gh8418XnLqh6/H8F7uGMcyh08msyeGdl+veYcAGDExotEYSJ4HeK/JA/Lshj17yVUKO6L7zq87G1xXCYzxx6N2FdHrBTygsnMouGk/QCA65Pego+WlCdBHI8oTASCJ1gTFoNMgwkTd0QUCIVp1r4b8NEyGNyuhrdFeeZwR5Q8Jh8UJgKhIPE8Kkxq/BOv3k/FhvC7AFCoFSalZsqUx3bKe3bINNiVz8T0HFQoTqIkE8QhhveEQsPdpIJj6hmfkoXfD93GjL03kG0s3HuPFURc9VviwjXJIwpT/vAoNQujNl3ClXspHrsHy7LIyDHm6fqnWZ71UVUKy7IuTwiI8byZ5P0dGo0GE/fj0t1kRemzDM9GW8338SQQCPkBUZgIhQalHcO/Z++i6W8HPTpo4ypJhXzv2QKJO4I+cKPFG4nClC+M2HgR68Pj0O33Ex67R/+V4aj9y17EJmS4dP3ITZdQd/w+nI1JzLMsealVOUYzuvwegmU33dcN08+gwhQenYg+f57CjfinDufG/ncVKZkGTNoRoSivZzFQZmHf/NzbkPLLPwp7UROFifDMMWLjRcSnZuG79Rfy5X6FvRHwBNsu3sfvB2+5fL07TPK415EVpvzhusigVi0hkU9w4tYTyfOHrlu2fVh3Jtal/DeetZhkzT9026Xr3cWZ6EREPk7HpUT3dcPP4gpTr8WhCL2TgH7LT0um8dfzvQtCIxOw9ETUMzsY5j7VM/qIXuFZVKgJ7oNsXEtAlsEEDU25JfpcQULpIDkl04AjNx6hY+1y8NOJfxK7Lj9AxP1UjOj0MiiK4tmGu8N8rLAi1VkP+ec8AKDlS6XxWqUS6vPllKmrpcuVzUxGFflCXgeoWQYTPloSBgC4PL4TAnw8F8EyNcsIs5n12qqMJ+76LPswxadmSZ7z0fAd9fssOQUAqFbGH+1qckNuPxvlw4siKpOOKACEgkRhHyu5PELOycnBjRs3YDS6bktO8D4ZOUa8Om4vOs055m1RvMaXf4dj6LoL+HnrFck0g9acw/zDt3Ekd78TLmQsLk1CWo7DsZQMA9aExSA5Q9qPhL/C5FoBF/bGuTCS14U8bvSv9Gx5f5O8vt2zMUn4VGbVojDyLCtMrrzvuES+2eazqEC42v+cjUnEoesP3StMISfifirenHkEuy8/8LYohAKIaoUpIyMD/fv3h5+fH+rUqYPYWItZxJAhQzB16lS3C0jwLJfupsBoZnHnSbq3RXGOhzSTU3csvgybz91zmvbx02yHY2RYLo3Yys63687jpy1X8O26C5LXsRJ/K7qnmcXcA7d4Zl2FTalNzTLgQMRD3n4rhYG8ruStD49zkyTKOC5j+udxPDB4f5YVpmeVbKMJiemOE0ty8E3yXPvm3lsUis9XhONecsEJpuQNuKU3aM053HmSbtsugkDgolphGjNmDC5evIgjR47Ax8fHdrxDhw5Yv369W4UjeJ7CNiBTgyeGDmKrFs+zuZezVRyxFYdjNy2rdKeipDdVzItp164rDzDnwE1M2X3dnp/LuXmHvktPY8CqcMzaf8PboqjCnMclpn1X490kSf5Q0HxknkUfJivuLuqC8u5aTz+MhpP245GMyaEQvrlx3u6v5r7PIixnCJT9DI+HTGYWx289lo0QGvUkHZ3mHMV/F5xPHj+PqFaYtm7divnz56Nly5a8vQ9q166NyMhItwr3vJFjNCMqn1d6nmWFyROI9bEsKUIZXDWn4/ytMgux8PMFZXCklAtxyQCUrXoWJOSKeW1YLP46fidf7pUX4lOykJZdOE3Nn6UVpuvxqbiY+x2IkcRZlVFifnshLhlTd3EmUQpIk/Aw1WK1EHonQfE1PB9PmQeRqg3ciY3waOmJKynuJ2ciJNKLq7Nu5Hkx3V5y/A4+WXra5t8nxo9br+LmwzQMlbH+eJ5RHfTh8ePHKFu2rMPx9PR0xZvHEcT5ZGkYwqISsaRvY3SsXS5f7pljIqP9vPK8NLiu4OrsZ+SjNM6v57d8C8qgTilSq60mM4sft1wGAHSvXwHlivqIpvP24z5MzULTKQehY2jc/LWLR+6RkWPEzYdpzhO6gIZ+NgL3sCyLt4KPS56/+fCpIr9b7ojknQUneefMLAu6AAWBoF0cP7nSxnK3Wfh11zV80bqaquubTz0EANjwZTO8UbWkegEKEPnVxiZn5ODwjUfoXCdQMriUJ/k3NzrolXupkmmc+Y3mlcLWnwlR3bq+/vrr2Llzp+23VUlasmQJmjVr5j7JnkPCoiy+NGvDYvLtnoZnWWHyUF/IsiySM+2zm4U1YnW20YRUD2/g6UoDybIsJu+85nIeYq+9IDXULMs+MxtoCpH6FrgRKzNy3PPsnpioOBtjmW1XM5GUrnI16oM/TuGdBSexKXcA406elRUmZ9/rRoGvG+VCY1+AmgQAKhWmPEYANZpd7/e5q1NnovO+l5m3ya960G/FGQxbfxG//Hc1n+5IcDeqFaYpU6bgp59+wtdffw2j0Yi5c+eiY8eOWLFiBX799VdPyEjwIIXJJE+qYYt8nIbdlx84mCZ4xocJGPvfFfSYb5+tdIcPk8Fkxo9bLmPUpkv5NphuMfUQ6o3fh5RMzylNrpSNcNCtNge1E7UmM5uvJnvDN1zEK2P3uLzxakEmr9+CqlfngVemVt+ITshAnXF7sfmccuXncu6G2p4wt3xWfJicvVp3WLMUpEkUQF3d44rumsLk+sN7I7Lk+G1XMXz9BY+0066UX2aOCWO3XpHdL07I+dhkAMC2C/dV3y+/IEZi8qhWmJo3b46QkBBkZGSgevXq2LdvH8qVK4fQ0FA0atTIEzI+d+SnaWN+dBpZBhMm74hAuIdmo9rPOoqv15zD0ZuOIb+FGE3mPPknsCyw+lSsw7G8suXcPawNi8X68DhM2XXN+QVu4EluyO9Ld5NdzsPZs+dlAD2I+Q9/a38DZXKMTCiH2GyzlBjZRhNaTz+MT5bm3yBgy3nLQHlFSLTTtKkeVGY9gVQ5c5u0bRfu45OlYTwfFNv1HpJLKa62vcM3XMzTfd01EPTWnlLuxm2BdGTep5p7GE1mzD1wC6ejPLei4mrdc2UfJpPJ9fI9zos+6vkv1mxmsSIkGpvP30OMYJLpyr0UDFwVjtuPXN8w25VH+PPYHfx9Kgb/Wxqm+lpvBYnytjKUkmEQ9S8uTKhSmAwGA/r16wc/Pz+sXLkSV65cQUREBFavXo26det6Ssbnjmejy7Pz685r+OtEFHotDnXp+piEdNnILlYuxqU4TdPt9xN4ddxePElTNwi3ImYG5I5O49FTe6SinSr3gEhKz0HwgZsOe44UVqzlOVK7Hq2YKyh5Z7tkWrGobGo6hvDoJNxLzsSJ2wXTgTnHZMbh64+8LQaPpSeiJGVSMhiYc+Amjt96ghn7HCMAqvmUPDHsYLw0qnDXGOqZWWFyUh7Cp/S0H+mG8LuYc+Amev/hWh+mBDXmlHndpy4vK0z5DVfSUf9e4pn39lx4EvsiHqJvHia8XKk7d5Nc72sLcsl7svlrNHm/5zLPJ1QpTFqtFlu2bPGULAQPEPUkXTZsaH4ELMjLrFz0k3S0mXEEb/x60Gla4bOIzdhdj7fMRB296b4BspK+5/ajp/hoySmESURCCvDRcn6pa7VG/XsJwQduOTg1FwTcMZtGGcVnpSZsv4omUw4iQYHyK1XPXekfYhLSLR11PoXAnrbnuvNE+cTZmERM2hGBfivOiJ6Xetti1eBRaham77mOidsjOOnU15e/T8Xggz9C3WJa6q2YCe6adVYy6DabWd6gsyDirDzcZZLXb/lpDFp7wWnaO489E6SDC6Oi7nHbsxO3Emz7A2bmmHibP0uRFx8mnhz5UI24bUJYVCL2XLG3u4bclbL7KXkIje7CM2gY1+uf11aY8nkqPiYhHetOx9r85AuTki6F6u6hZ8+e2Lp1qwdEIbibx0+z0W7mEbzxm7SyUdDsuIWERVkUjEwFfj1qnsXV/lY0rLiCFveLVWcREpmAD/4UD+mp07g+UrOGo01Qufmhlbw0pE5N8lzol4VZsiLyrTsdi+Uno/H4aTZWhvKDpIgNpiTldOHRf9h4CedjkzHw77PqL+bKpLCn1uehbrgbawhkKaQGA2LPmpppxMIjkVh2Mgr3Xdg80zqQGrv1CsKiEjHv4C3VeQhxdSAuvMxkZp2uYnOvcVcz7ExhYlkW7/8Rio5zjsJYiAP+uGMm/H5KJg7feIz91x4hy0sxWLjKgKt1b9nJKLSafggZOUY0m3oQ3eefsOUrzHPnpQeYuD0CBqN7apw3hg+JGa71c1K48gyuRjQECvaYS8lYIDQyAd9vvIhkJ++hzYwjGL35MpadiHKXeF5HdWzDGjVqYNKkSQgJCUGjRo3g7+/POz9kyBC3CUfIG5EKZsXy49vNS+fmo2VsfztraNQEfXBVSRATQcnESbyKGTBv2xq7E1fql/A9CxWmO4/TMHrzZdtvYXGJRslzQQ4puBES8wO9hnGeyA0kpueguK9W1g/G2UBBzWAgy2gfpVpnIfPynmISHPewi7ifin0R8fiydXX46pyXo6sDIeFV//srDKF3ErB7aCvUKl/U6fVqB1GxCRkoW1TPax/F5BC7jzUSYNSTdLxULkDdjfOJ/JiF5/UXzkwAPdQmc/sONXVPWDxZBjNORyUiOcOA5AwDDCYWOo1jfoPXngMAlCqic0leZ3J4AqW3YFnWJaXTlbqWF4XJWygR+cp96ZDjVqz7ODEUhWm96jlNfzoqEV+2qe785oUA1QrTX3/9heLFi+Ps2bM4e5Y/w0pRFFGYVJCUDSw8cgefNK+Kkv72Bsxd3+KzYM/OU5g4TefG8Di837giL62w2ZMrR3cWjZgfjRA171S1aE5uv+9qPLQMjXavOO6f5g4yc0z4YdNFdK4TiO71K/DOuWfgw8/DGqzCSl6+F1cUZ7WdZWxCBoIP3sSXraujZqB9gKr03nlZfVTK5XspeHdxGFq/XAarPn9DMp2rbYpYNeBG6LSe59YXtebC2SIRP4PmWfbyyTKYMbrLK07zcFe7YF313XL+nqTCRMFes9WYIoZHJ6LX4lDUKFsEB4a34Z1zqtBy/pZrtmITMvDhn6Ho36oa+resqlg2d6HWh0nqW6IAnLz9BA9EJqzUWSQ4rxj/nI6FjqHxXqMXFefLNY3j1j2jyQyaoiQnL5yJbjCZZduNBynucb5X840aTWZo1NgdwrJ6XMxXyzsm9SZY1rW+wFk9uHQ3GctORGHkW6+gQnFfAM9O+P68cD4uSVG6QqhbSqJaYYqKenaW17zN/KsMnmTfRnhsMv7u38Tt+XM/apOZVfWRX7mXggAfDSqX8nee2INwFSauGcEPmy45KEyqcKdNnpLbuXY3RchJlJyRYzMduzm5i2gnmtcGbdnJKOy49AA7Lj1wUJhc8Ulx7IT5AgrlFQ6WxJ5HSo78aMw/X3kGtx+lYffleFyb9Jbq67V5sJdXyuowy742x5xEmnTnQOHRU7vJmlVR4ppwOl9RVn6vq/edB4QB+AqH2cwqjjonNaAu4Sc9k89K/O2MrRcsURZvP0rDvIO38DlXoXEiLvc7kPNjmrwzAvdTsjBpR4R3FCYn54XFLTVwj03MwM9br7h0DzU8ScvGmNxV7x4NKkCrUDHg1ndrwBGjyYw3Zx2Fn47B7qGtJEyMHaXn3jPHaIa/Xvq+rprkuRrgaPKOCPx9Kgb7hrVWPKa4/SgNf59Svielq+/T2XXWLUTuJmVi09fNARCFCYCKzbefnbIqOMbxzyFPsi0V6biKWP5q4O76vvZ0rGgUNbH2Lz4lC91+P4E2M454RC41aDkNkzNHVTVtuVh7p2TwLG6S5167BHcO4rkh1D21SXGijO+UaxvXCn4LFSJBekcFSiRPkWPbL97HjXj14WjVmn3cfmTpWIR+eEpnZwtS58xVIPIaHZJbb6xjd/4KiHz+wrNy6VnWsr3BdCcBNLivVs13LfWG5PzPuNeouRc36ez9NzFtt/KgIErL19sbmjsrD6WrvFFPHM00ld5DDRnZ9m9bTUANk4gPU1xSJmITM3A9/qmqDZS5JeLs/bnyfq/cS0GjyQd4x5QW4V8nopBtNGPB4duK76d2P0JX36fSduwOpy7lZ5sck5Bu2xzbaDJj+IYL2MDZuPlRahZ2XnpQqH0SCwuqV5g+//xz2fPLli1zWRg5pkyZgs2bN+P69evw9fVF8+bNMW3aNNSsWdMj9/MuefsYrba83EguY7degYamcPu3IKfXcSMCDd9wAVPfrZcvZkGicB2jnQUYcMMAxxlit1DSP6oZZKs1E5Nr8HmrjFKrLKru5ohc32FmgTn7b4JlWQzvlD/fqpKgDyG3n+Dbf84L0iizgS9A+ovbUFo9NYJVa6XRopx9mhEPUlGjbBFeXRZes+nsXaw/Eyt53hnzD93GwiORsmm4A3ETyyruIF2JAEVRlO0h8hJO/Vys3TTGmSJhlilfuXvkN2pN8lzJpyA433OVK+unxV1RNphY6EUqodhegtzHcaZoqVHErAzfcEF2ciy/kKrirr5PV67LDx+mK/dSsOX8PSw9EYXSRfQI/7kD/rtwH5vP3cPmc/fQO9fCpnPwMSRlGPBz11oY0Kqax+VSy7Nkkqd6FJyUlMT79+jRIxw6dAibN29GcnKyB0S0cPToUQwePBinTp3C/v37YTQa0alTJ6SnS88gPY9M3hGBplMOIjE9x2EWxFmnbm04uKk2n7uH9ZzZjLwiDHm6/kwsftpyWdIPiKs8qJ1xllM83Lk5sJIZqrzc7XRUIob8c563V5NSuA0766EJKLnOIyXTgLkHb2HeoduiG5UqwWGFycmKkrg4/HcU8cDRuVVpx5nfHYA7BnZK/OyUwH3X7gwTO0SgvIrx/caLOBMtbTfvrJyuK1hN5LaZ7oi8rLSuqClJuedUEvTBirMVOW+SHxuiqvJhcnbexZVJZ6Z1BqMZLMti4ZHbOH7Lbi77VvBxkbzsf+eI+PNxcWWFSTxCrIUnadn478I9ZBvlV4XSc0w4F5ukaPN4qW9Hql93fYVJ/TVKLC5vPnyKcf9dcanfBix7Ri7NjTBnjbiZLLJ1QlKG5dihArZfn5VnSF9Sv8Iktg+T2WzGoEGDUK2a57TbPXv28H4vX74cZcuWxdmzZ9G6dWvRa7Kzs5GdbbeTT021DJIMBgMMhrzv2ZEXhPfn/WbNLsv3V+4HtuTYbXSvV97pfY0mI+8cTVMwGvmN2ZPUTKfyGAwGZBtM0GsdI1FxO4U64/bg6rgONufPUf9a7L5bVS+J9rXsQQmyDCZM2XMDRTn7EwkbRIPBgH0RD+3nTfxyY1lWUm6z2QQGTt6DCCaTY4eQYzA6vY4ruVhabr4s+HJbN0vMyDZg0cevyd5HmLeZ836zcnLgpxVeYbm3q/WNZVmwHE3MoTw5dSk+OR0/bLzgVOYcgVJtMvPfq1HQKZsF580i78ggeEfi79GgzNRCooNVUoY8Oc3KvnNzHtoDAFgffhdT9tzA0k8aolHlEqLysBzlR+5erNleblnZOWBkuhBuPjkG5wMkg8HAU+xynLTTZrNJcXmazWZIjRGl6k52Tg40lPIuUuq7VvLucnIMMBiU3ctsFtZ/e5k5qysGjpmTXPnKfdP5QY7EPa2ymAXarNks3tYL08ndQ+45TWb58jBx2tnsHAO0lLJReI6gTTIYDDBx2syM7ByERT7G9D2WTZ5vTeoknZfRnldWtuXdcusz/1tx7Eud4/hM5lyZ3114ErGJmfiqdVWM6PiSZA47Lz3AzksP8HLZItj5bXPevR3GJkbxNkPqmzIYDGCgXhHklpswPz6s4vaSZVl0mnMMgCVa8fJPGznJ2zkGg4HXbwnzkBvv5CaQvFbsugsxCahTQT7Cp5LnkJLL22NwLkplUa0wiUHTNIYNG4a2bdti5MiR7sjSKSkpFifekiVLSqaZMmUKJkyY4HB837598PPz85hsyrEX/65du2y/Hz58mPvb9Txv3IpEseRbEL5iYb6X4ykAFiVn1+7doCngRrL9GADcvHkTuzJvyMr/0/Ld2HCHwacvmdCwNL9hffqUgXWewcwCM9buRWwahS4VzbY8Tpw+i+wo+3X77lLYGcdXvtLTM8Cdr9i1axeGhtpluB0ZiV277M/8NO2pSDlazl2+dAkNSgH79++3PwfLypS7Jc3Vq1fBLRvAsvp5w0l1MhntZSB2j8sP7WWelZUlSJN779hH2LlzF84nUKhUhEVpH8tZg0zeaQb79fsPHEAAT2GyHD8ZGobE62qn2SzXZmZm4s6dO7AuVtvvbzl/6+YN23P9/M8JnH3iODVneQd2LPqS/b1GRUXhBue5op7yz9+8eQO7Mux+HFfj+fUXAI4dO4abnHd07b5jml27diuaOUxJsZc3/3r5umNPY/kdHR2NXbvuOL3m0aNHeWgPgJ9zv5GBK09jUmPxGeB79+7B+g537NwlaXbILfvde/fBz6EHET6rhWzBOxVj165dSOW0FUeOHLHVcWHeABAVZS0/y/EnCQmS3/vjJ0+gpQExowruNdGc59uzdx98JUV2PLFz5y7OrLjl/LWICOxKuip6LWs2w/qshw4fFilLcWJjaXCfIyU11ZbPvbt3sWtXrPiF4H9bJ0NCcF8iqvijR/Z75KXuuQq33eJileV2HP/7ffgwXrTNfPjoIaQMaU6cOGFLl5wDbN21H/4iE0oAEBXjWB7bYmjcSwcG1jIjJcd+zz2i34U46ZznPHUqFPFXwctr7/6DuJrE6aMF7SuX06fP2NIdPX4Mt/yAG/eE11rHGPHglgu/7oqT9tSx3bt16zZ2Zd9EbKIl382n76CWQWw/NL68Nx+lOdQrYT9wL93xOgC4cuUydj2+5JDv7j17oXdhB4bHmeL3EZZ1TnaO7VhkrPz3EZdmv+5c9BNe2VuvyTYBt1MpvFyMzW2b7Fh0G8ex27UH0nUhIeGJ7LfKbVuVfNPvLDqFuc3ElFbxNl4qnf3blB+LepOMDEf/fjHcojABQGRkpOSMgLthWRbDhw9Hy5Yt8eqrr0qmGzNmDIYPH277nZqaiooVK6JTp04oWtT53hiexGAwAKGHbb+DgoIwNHQfACAwMBBBQQ1cyteaR6XKVdCq0QuYejGUdz4oiO/DlHQ6DhujrgEAunTpAoamUCwyAQuv2UPGv/TSywh60zGOvvVeALDhjuUjXnmLwc99+bNgi+6E4H6G3S9q2U1L2hYNawOwDHQb1K+PoAb2CGsh/10F4u7x8vHx9QWy7cvb3DIDgKrVqiGo88u2Y8UCAhAU1FxU5vr16wF3L6Jjx47290BRDuUjvK5W7dpANF95bNWqNV4qV0T0Oitjzx9CZu4spNg9Us/cxfo7EZbn9PFBUFAbh3sXDQiA6cWqWHnKsipnnW0cc/agbVVGmHdieg5+Cj8CAGj3ZnuUDbCHTrLmu/g6IztzKYb1Wh9fX7xUozwO3Ivi3d96vmbNV7A91tKB6ouWBp4kOuTVsWNHaLX2kUpGjhE/nD5k+12lajXU6GR/rvOxyQi+ctr2u2bNmghqY1/dTubUaSvCd/QwJAZbY/jvsfNbbyny1Vsaewpx6Y4mfc7qjjWN9XeVKlUQFCQe6pp7TdmyZREU1NCpXFJY8zJRGgQFdeadMxgM2L9/P1588QWEPX4AAEgq9So+aVoJD1KyUMpfxyuT83H2sn+zfQfedghCubnlkZ5txEjOOxUjKCgIv98+CWRazKzbtGmLyqXsWi43bwCoUtVSftbjJUuWQlDQ66LylC5d2mKGJGI2zpXz4t0UzLkSBgDo0LGjQ0hjK3+e+gMTtCsx1fAhwlnLO+zSpYstKIb1vrXr1EFQ00qiMlE0bXOAbNu2LUoXVTaJd2LrVeCRvW0sUiQAyG1fK1WsiKCgOpLXcr+tJk2bobFgxdHKxsdngRRLaPSar7dB9TLKIpv9d/EBUjMN8NEyWHcmDgs+aoDAoj7OL+SQYzQj5E4CEO5opml9V7cO3gbu2icbypWz9JlPs4y4EJcMhFr2GypbtiyuJokHVWrRoiVmXrbsKTPlYu4Ej0Q7eGXvTRy8H22TIctgwtCJlg3hA15qhEZli2DCOYuZXIcOHVFcbClfhMT0HCC3fW7StClGbb6Ku0n2kN8tW7cBbifg3+jrvOcXfgsA8Prrr2PxNctzt2rZCjUDAxB3LAo7cttfbttzO00LwD55wq27Uiy8E4IHmfzIaNVr1EBQhxq2fP39/REU1NLhWjF5rc9ibYOE/cDgfy4AcDQzq1u3LoIav+iQb6dOneAv5vDlhKgn6cCFk5LyWe+h0+sQFNQOgKX+7b13h5eOy4W4ZOCypZ3UaLQICurs0DZ+teY8Dl5/jA8av4jJ3Wrzrh+4+hwAfr0NCgrC49AYbMkdfwjlK126NIKCGks+56KoUNzPeCoqs/UdSJUBF6k2XiqddTwrrANy1+Y3VuszZ6iuXVwFBLAoLw8ePMDOnTvx6aefqs3OJb755htcunQpd4ZIGr1eD73eMbamVqvlfZgFAa48FEWpki8mIR0nbj/B+43sYbbNoMBoHF+vMF+GsU/JaDQaaBiadwwAaIZWJY9DWompq0dp9mXQtWfu4p2GFW2mehTlOHAV2hoL70PTAjllylGr0cAokgf3d/STdFyIS8bbHEWOph2nsGgNY7tOSShiMZm4ZU5LyE1RFMJj7eGRtVot9lx5gAyOCZvwOo2Gs88Hw0iXh4vfw9MsIzQc2YX5UJxIjUJfJABIzHb8HjVmfjrhe9Vo+fWaETyXsP4CAKPR8NLQtGP9sqSxX5uaZcDMvTfwdoMKaFS5pOy1gLIyFMqg5BqKUvf9SZGeY+LlE3YnASX9GJssVtaF30XjqqXQY/5J1KlQFDuHtLLLz2lTNIIyFSL3TqXScz9x4TsTouZ7D73jqKiLyanj1C2aEb9/XGIG1uh+Q3EqHZv0E1Elay0AQKPVOph0MjLvmJvS2bPyrhO0p9wyc1anGM57YCSeT3iP0zHJeKVCcUWyfb/pMu/30pOxGN9DWoETY/im89h+8b7oOau884/wV2Zp2vLuByw5jXOxyfbjIv2IFUZkQ2itVos7j9MQn5KF5jVK2/PhLj3TDBr+ah9csqCh03HaH867TErPweKjkXiv0Yt4WWSTYK2WGyWP4SlLAMBSDLQa6faVC7dvssrAlZs/KcVfaRaru475i7SZgrGBmrGLWN/LPbYvQtwnR9jeW9FotdBq1StMYuMkMfko2J+NlunzAEvbaIVlxZ/14HWLT9r68LuY1qs+7/zhG45Kvlarle1raSf9BPebVvqONBoN77qFR/hRDpXkI9UGCvP2JkrLQ3XQh/Pnz/P+XbpkWRqdNWsWgoOD1Wanmm+//Rbbtm3D4cOH8eKLyjeIe1bYezUenywN4zkStplxBD9tuYIlx+2diMFkRmyCsmVGK9am2yGss4f8b/119o//XGwy1oRJm5IAzqPRqXEUVhKJru3MI/hu/QXbvieScuXqJInpOXj91wP4cctl2fTOkH8M+8njtx7jq9XnHFI8zTJg8dFIhzDyasLdKiUt24jfD0mHiuXt+yLyYBPOaRCfKuYUy4r8ZcFpWHE3tcEz9tzAqtAYvLeIv0rryTb+SVo2DnD88jzF7UdP8cGfp9Ax2DKzyn0kmqLw79m7AICrgp3fWYm/3QUvf2dBXjwgALddELt/Qlo2Wk0/jOKUY7AhMadzuQEB95SqKHmCtNz7OhuAKN2HiYtO5WajXFyJJialLCmBqywBlgkdKaQe/81ZR/HRX2G8LQe49eLx02wYTNJlfjoqwfb3T1sv449jd9A5+JjovZzWcSiL3GlNa0VtAAQl6UW3axCOFVTd1ZoHi5MPKYd3pxa5Zzh84xGGrb+A1CwxfyNl+XNfA7cslp+MclkuteS3gsFtI8KjE22+dGqQEtmdQYPyC9Xq+OHDh50n8gAsy+Lbb7/Fli1bcOTIEVStWtUrcuQH1gp2NiYJE3dEYFz32mhYyWI68WXuJqQTt0dg/kd8M53TUfZZ1Bwja9uwVBYvhkPy1fGr38W7yba/xcN3520AxfIGFk7FsxHGmZ0Wu4W1o1obFoOE9BysDYvFbz3r8tKoaeik9udhWX7krkt3U0TTjdt2FZvP3cPio5E4MNxu2sffFNRz710qNLRUpLbzscmoWMo++8oCoGQUJiFC5VdskKZkz6OUXFMiK9b9kxzv5z6ux6fiQXIW2r1iCXjSbd4JCQXSvQgjxnGLjKYoRfVVyfdmzUdxfWNF/1R9rarLJMLJi2Unt1mjuMKkXAalCFNyPytn95NTSDNyjFgbFouOtcvx3q3SLSVEI75pvDuDfDpaemVRTF7uvk3X41NRM9BxVUgsSic3q69Wn0P01K4ALG0bcs+zLIu/T8WgdvmiaFzF0fdarHlkWeVKJ1cG69+8KLMyA1Ql1U/RPoUu9CsnIhOw4Q6DDXdO28rNFeRu3W/5GQBASX8dxgrM35Q3HPYC4JbFhO0RyDaa8VUbR7cFQNm2I0pwFunUE7qU0czCusDJ3WhcDdw6SMOMQcx/OG1+BVmGToo3eC4oqJY2MzOT5yAVExOD4OBg7NvnaKPqTgYPHozVq1dj7dq1CAgIQHx8POLj45GZmen84gLIjksPnKZ5b1EILsYlo9eiEIdzYvsh8GYsXRg9iIUVF3L4xiPM2nfDLWGKNSo3tHG6wiT4LRwEKRlY3E/ORGhkAu8Yd88KsQ7BVm4y8ond735ypuSgXAols1Uhty3yJ2cYeDKZJBQZK9lGE3ZeemAL/30/ORMDVp5ByG3XN1bm3kZqHyjhTDfLsvxoR6x8PRFuCKtoJlREFKWbKrpzD463go+j34oziMhdyckPZQkQewb7b7mVB96gzEkbM/pfdSutmTkmxfsEieHqTK5Z4pnEwyg7LxvexIxCGdRILrvCpOJa4WuesfcGJu+8hg6zj/KeU7nCJHZQ0aWKcec+QGKiffBHqMhRfvsdNNcxpLdU3eOuRB25+Ri//HcVvRbb78G9SiyPPVfiFQ+EnfWPUu2v1L2FiMkh/B5ced3RT+zjybMxSc7lkDiuRFkTa19dGcoIJ+mmymwe7a4VJhZ5U4qEl/66MwITtgsD0vDh9gWik9gqC+895hi+127EBv0kZDsJfV8QUa0wvf3221i1ahUAIDk5GW+88QZmzZqFt99+G4sWLXK7gFYWLVqElJQUtG3bFuXLl7f9W79+vcfu6UmGbVQ+mFBaJ135lrhZT9tzHUaT2aHh4f7qt/wMfj90G9svKTebcGUZWWxgklcTHSWmK82nHkKfJacQzpmZNJrkM3a1QWw+9RA6zD6qahAg1+k5vZazxCSWy6x9NzF47Tn8b6nF6X3kpks4cO0RPvorTNV9pPZ6kWpcxQboNFdCwbsSvrt5B2/xVledySSFda8LZ3hiJu/mQ+d7BHGxhHN3vS7IzVXcePgUK0Kipe7MkUH+Htz928Zsdt7e1fplD6I5ZsTOv3f3DESkvl/xNkhOHudppPJSZZInkIvfrjmmT80yYPKOCFy6m8wrM+FzW1fSDSaWN9BXapLnTtMjKRpO2o85+286HN979SG+Xq3AooKDmLhKZtGt+95Y4ew/7AC3zb3zWH7PSLEs5h68hT1X4p3KBAAbON+bbYWJUx/yapKtxIzdlSrAbYveE5kcVoqr1c+V69T0Ae76LFhWzAtYOVyZn2YZsOR4FJafjEaCTL/nbOyjaDzCuW81yr5QkGUQj9hakFGtMJ07dw6tWlmcgDdt2oTAwEDExMRg1apVmDdvntsFtGIdIAj/ffbZZx67p7dQ0jCJfbDcgaSSPAD+x7z0RBT+PXdX0SzRveS8r+zJNToumeQJJBdmz73e2eIWd6ZrmxObeiUrc3K3E/oaSd4HrKLGl1sOJ27bNzs0OTHJ23Le4qt19X4qjCYzYgVyxadk4XyspVwaULdxQPc92tAXRe5vh9tHX5QwIfz+3yu4et9+joXQJE/+vQLAzL1222qxerU/4iGMnAIQS5OWrawBV/ptqUF+E1HBANnM4t1FIfhk6WneuSyDCZGPla1YctuKNbdpPBWx7ReXRfxvZyhZUXe4l4I0jzgzxq6OSyRXtcRWmOQUptwLeO9SppHjTSao05j4+XC+a7G6OXX3dfx1Igo95p/EfxfsbZlZUHe4mzlzvxUNo9SHRhnZRhMOX3+E9Gwjgg/cxBerwlUN5uceFAtbDexWqFhYcadZspTfqpE3Qy+vgEtNKDmbDLKyn+P7aK2L3DcnV8ZK6p9Yn+now6S+TB2CmDiRxcSyWHYiyrYqb0XsGX7dGYFRmy7ZfotaH7gis4q0VqWC67PtCiwg256omZjmKkJySo+RN8nqmE7JdysllbPNlQsiqn2YMjIyEBBgsevdt28f3n33XdA0jaZNmyImJsbtAj6PuGMG25VGAADuJWWirIIwsN5wfXIe9IH/W1iOvHGMk+s1ErOqrihyYnA7R2F0Imt2K05G4YZg5UFtJz9svV2h4S2vi6TlDpJORyU6NIZNp1jC6O4c0hKrdFNQlMrESt00W5QwMZTKO2jNORz9oV3uNeCZ5LFOTPKEcAeNL1KP4YtszDkA+GhpfJlrZy4mllGws6nkNyTlxGoyIzEjB2UDpL+f5Azx1UQ1k7/3kjNtvhFZBjN8czviD/4IxcW7KVj5+Rto83IZ2Ty4j3D6MQ08VhZogq9PeLYRcOojBeDDJac46V2TR+oyscNyz5xlMMNHo7xUnOhmiq4D5FeYdl56gLWcYDrjttlNcLjX/X6Ir4S4shgh2g6KfCvj/ruKdWfieMeO3XqMdjXL5sn8Vy3uqr1Ps4w4fktcbm4b6szJXaofcWU8IJaV3MBYmQ+TMj8/tQizNbOAnI6+7nQcLt9znHwTymIys1hyPEr23tlGk2tBH0TkyzKYbD6wi49G8uQArGMK11dVWNa5orY/4iGO3HiEcd3rOJjScgP4cH375CYAufVXrPrmJXCDF4aQeUb1ClONGjWwdetWxMXFYe/evejUybJvwaNHj7y+txFBPYoGGSJpIlX63ojh8Jmyon/ayKvJB/f6oRsuYXuMdPXXSrTYx249djhmbTO44gn9YYSdjYEzcyPlEzN+ewT+Oc03s1DSPkkPACVm0nPhNn5hUYmSq4jnYpJQlJJeYZQz+5EiXbC6Q3MVJkFNES0uSvzvE/qh2K8fiZJIxd6r8jPQigcmEo/00V9heOPXg5Y9OHK5IujYG0x03OsCUFe3uQo2dxBkXcHbIBiMiuFqtCVXV5hcupeCLpVr5mRNnW004bdd1xQPvlmJdkd8ckQ6n4aT9uPDP0953iRPuOIo48M0eK1jFE3bdZz5AaHvCD9P9dYK9oOOh4TKkkUWFqlZBtXmv3khJUPZqiogP1CVGzRyB5xifi7O2mThvZX6jIhPiElfuy/C+eqcqA+TcIXJhTZB2P85G5OIKUuAYxtqMMmvYIzdegU1f96j2hx63sFbmLnP0SyUWw/2XpWfgLql8p6Asj7ii1XhWBMWizVh/MWLw9f5Idq5bgByXYH1mZLSczB11zWH8yYnJnuW/LmWT3a8MemeV1QrTL/88gu+//57VKlSBU2aNEGzZs0AWFabXnvtNbcLSLCgRLHhjxldHBDZ/iPP5vPyobZdvXdGjiUMrNLOl3faSRlx+5r0bBMO3Jeu/hqJvXbEZhKv3k9x6Mhm7L3BGywL3wa389IwFOYfEjczEaKk0ZRKwR8Yyi+vC81euAMqMwuYZVZ9uDmfi0mWE5UjG2svQ1bgw+QGqlDxTpWEvJraWU1n1p+xz+gPWBmu7GKZxxWe4gZLEa6KAcDOyw+QkmlA9JN0vL3AcUNGwLlJqqQsrpqRuXQvdeetv1eFxODPY3cUD76XnriDEyLftdg3cuia/EDodHSiqiAMtnupKEvHmXSgCDLQn9mJYgbxvWvEkFtx4EXgVPgQeakOGoZGaqZyBcYdDFgl/20qDuct8+BqTA2l3gdXDm6aAGSgHhUJscaDK5MGRtAw88yrhHAtEaRwlzmbFWvbJWyLXF60EFwnVvbcsvz7lEWpmC+zLYYYs0V86ADn3zC3On2pJIKxkzwcznH+Fga3EE7gcstGLoiRdZzyw6ZLuJ/iGDCDWx8v303BoDVnEZPA99UTqMP2vwqhxqTaJK9Xr15o2bIlHjx4gPr169uOt2/fHj179nSrcM8TzkJeH7nx2BZ6WAp3mPL9fug2XijuqzA1i7foM7hkrob7KO08ucPVfLacv4ct5+/h+Mh2oumdORg6+/zUDPCU2u0DwC//XUVattGh80iRGQBwFSaGpkQbIzG4j3DspuNqlzCNknzEZBLCdcZlWflukpt36J0E6YQcEtJz0HDyfqwf2Azliur5K0zCoA8iXfeF2GR8sSocP3etJdoB6CkDuG9DSUevpBxpmNGJDsc580t4hBIA+DP3Sn2D1JjLcDt9q3P+oiORvDQLj9zG+dhkXOSsdgEWu3Gdhna5rXC2AuNOXM0/OkHeuV6IdbY4empXXjssdv+VoerMzhWHFVeRp6OiyOJX7TK8zYQg8eZhAI4zwWJwJ3nkJguUL7y6XiG0jLJQ9t5Crb+tYnirjFIKk/1vk5mFdeeDzbpxeIm+h09zRuGouT7vGmtODGtAqP4bJLEBMJk75EFQZQqkmrJIyTSgVBG9yEbMrhWo8CpnAQvEc3C9Djq7GzdnubGBZP5sHifCOYj5c8u5Gxy9KT4Rw1XCu88/AcCyHce+YW1sx6WqTeFTl1xYYQKAwMBAvPbaa6BpGqmpqdi6dSsCAgLwyiuvuFu+54aQSPmB5WNFEbzUf0wXBAMqwDGgg1TF7sMcwmJdMP7RTVZ9X0DavGD5yWjRRrMUm4g9ulEYrflH9DpnPkxqQmAqCXleHE9RNTfqyx9H78im5e/bcBUxifZBHePQYUjDbejCFDoDK4FlWdkZSL4Mbrstj+QMA8b+dwUAf4WJZS0hp+U6mRyTGfsjHopu5AsAWhhx7UGq6DkrwvrCDVcuFdHnf8x+LNYF44D+B9sxl3zaFFxjNJkRdieBJ4v1nU3bwzf3eZplFJ2xt27c6A6TPC7LT0ZhwMozLuUpeS+VXao1tbvG3a5W891X7AEulA5whO8/y2DC4qORuP3I0XRHbPDTkbbMWJfMUR69lGtCJDexobSu5KVd0DK0y6ueahnMbMUMzWK4a8gm9+2q8fFQkpS7MvASbbHyeJN2bPOsIhXLiEYZKhUv0/dgzKOTvejrcUMRCt+7qwqog0mewv6MBTBJswwn9EMRAGUBmETzcXI7qZVCpeRlRV+ojIspk2K5t515BDsvPeBFzeQitornLBqklfyIquluVCtMvXv3xvz58wFY9mRq3LgxevfujXr16uHff/91u4DPCx87MR9xx75HYmy94Pqu6u8xlv0oKtPyZiBS/aDUIyWmZ4t+vW8iHK/QcfhKs10iP8tFPshGEH0Kfmb+h6vGPEIq6AOXCz5f4rB+BCpSD8WjFkr8Wn4ymve+8zK7LJFK9bVK/aOkc7fmw+ZpppnKlYVvksei3oS9qD9hH9KyjbID4ruJGZzOwZ6HFkak59gVDSfm7QAsSocVqT0j2tPnAQBFKXtHy9/vS1pYrtmTkvc67+AtfPDnKQxZd952zGBU966tx13dS0rK52LC9ggcuPYIPsjG79p56EaL72ej6l65+d9PzsSvOyNsxwORgD7MQTDmLPELnFACqfiYOYCicOzY+StortVjJeZNVl6l7qA5fcVB9LkHb2Hq7uvoMPsY73iWwYTtgqidWQYz9FC/P5HSAUtezAoTFG6ZoKEpyTpJw4xm9FX4wXEVvjF1HYd0w9GWvqBQSuAH7Qa8rzmGhpQyM2hn5KVr5l4q9T5oJwPtTOid5GzBaMpbGGd37j8H2CUU5ns3KdOp/5FofoJHluvvuYFQAOATzQG8SD1BL+ao5DUU5MdhckrQ3AO3eH5DySr856xcjEvGKdmJDeV5iUUGlRJfzg9SieLFdxWRX8Ev6KhWmI4dO2YLK75lyxawLIvk5GTMmzcPkye7ttJAcE5e9t9Rhvr8qTxOL6mdYSiicPZnvGYlFurm4een/PooV4YlkQpuGQhXmHyQjVpUDMTKqRF1y2G3d4imtMMdjCstB1ZFWvHrpRsrNflalCLx1pllLf8606cxXzsP/lAXfp6iLM9J8zaute8LoyTYiE0p4ClM/MGCcEVGPB/79Wo2hVY60Ob6hSm5Znnu3kjWCHmA9CyqVH5i4YZVwXL/tPzgDkwGMjvRnTmF+brfAYAXLl4pnenTGKNZY5uy7b8ynBftapt+LKZol6LD/T9FRXO2qrNUNxO/apdhtnYh5L5SdzS5zgYxO/Q/Y63uN9Bp/LDr5yQ28Jy0I8LhWKbBBIZSL6x6kyU+tx89xWfLT9u2GhAbS246e1fR/mYMLf3WBjI78I/uV6zSTXXMXz8R1eh4zNfytzRpRl/FLO1CFIe0c70fpWzfNUC+TuVlgmj1KbuJ5zdrz4um4dYhsQG7mL+nPRnH39FodEinCrGgD8LfLnw0wmw7zD6K3hIbCMuhJuiDVBh4Z+TI5CnXh845IO73ZCVJwcTCR3+FyW5xItfUiK1KC8+5UovFlFJhHZCaNHwuVphSUlJQsmRJAMCePXvw3nvvwc/PD127dsWtW+6ZsXneEWuczWbWLVG+DCYzuv1+HMM3XLAdW6Sdg726UdBAvEGVnK3Oo5O87IqHyvTca3rnzhLVM/IbRakV+s70aZzz+QqTNMttx4QK00bdBOzWj0EX+rRoHnmxv1caaej2o7S8RcnjHI9L4iuf7lrlsp76QxeMbswpDNb855CmKNIwRbMEb1COvhbW2Ua+wiS/4a7w/ixYVMATBMJussjLTwLhO+StFAH478I9hAlm+MQmDVxx+v/j2B2HPZSsSrw1N2vIWi4Gk1lUKfFUX8SfEbf8n9tplqP4A/2u806ovsMfumB8qdmJgKhdAOBgSlmWSgYA1HzK3+RS6TM3pC0O0B2Y81iineVSHu5G8/Quop6k45/TsZbNwznn2s44jAcpmbifnIk1gpnxvKB0Eu5JWjbWhsUiPZvfPwxYGY4jNx6j58Lc9yCRnZJ9hFgWkh/LB8xhAEBjWnrQWYTirz79o/sV7zEnMEbCfBvI+4SfFbE2+ejNx4qir/2eG3BAqu8F+IqtmImfWNtmfbXcsYTJxL/Hm/Q5TNQsh1bm3lyUtGUsgPDoRPRddtqlPeGscCeFlKJmhUmK4lQadunGoD+zU/S8nBJmNrMuWwK1nnHYpeucYTaz2H35Ae4m8ScuxfZkdEV0sfqo2FKl8OlL6oM+VKxYEaGhoShZsiT27NmDdevWAQCSkpLg4+N8/x6CPD4Qn/UymVleZBUxpUpJg3bqTgKu3EvFlXupmN27AQAWXRiL70E96g7OsS87XCM1g+asvlvNR6R2T1c/Myef3vr8tMRsq9QAYaRmPQDLsvxY4+cAgGHrL/DS1KWjAQC9mGPYbW4iuK9FdZSTTl6fUl4OSRL7+HCRmrnhHu00h2/qo2qFCdIrTDsu3Ue20Yzeub+FA2gAGK35B300h9FHc9hhDyeKsjTgvFlTrsLEsk6VU9qQgRCfIcoeRgZumdyIf4qh6y4AAN6oUlL2Olf6gbtJmWg/y24O8h59DLN0i7HQ2AOn8C0Ayz5SDvdigQ//POVwfM/VeBT300oK5+rsHvcya0fL/Y4ZmX1GSiAVFahEXGWrSKZpy9kIWZPuJOKbw4pu7uqZirmLjsw5WKOBmMws/jkdCwYm0FC2SbS7YFkW7WYeAeDoLxedkIGVITEoIfY+84DSwd3wDZZ3Eh6TmNtnWBD6uu68LL45cbbRuSmYmWUd+jQNjCiKDMm2Rq6uWXmRsgfG0cCIupR9pVKNwiQf9MExn0+XiU+siTFK8w8+Z/YgKOc3RLIvOJxP4yiqYu+MEVWY7OutVoyC97BMNxMA8BS+mGH8UFbGqCfpiHrCNWFlUQYpos/ea7FldeiLVeE4NKKtbL6A6xE7hZhZFiYza9t2QczvRjTSH+cZvma2QUeZUJuOAbDQIa2ULw8ArD0di2UnorDi8zdUy861OFEKy7KyK14AsPXCPdv3y8CEHzQbcMpcCyazfZzHfaIiyMB63STsMzXGXNN7TmVQ4vcs9XoLo8KkeoXpu+++w8cff4wXX3wR5cuXR9u2bQFYTPXq1q3rbvmeK/7H7Md1n3544+leh3PC71RM2VAyUBC2t74cBS0D6hReZytMM/fewA+bLkmaZMh96852RRdDMhoLyyLycRoMEn4oYh0n19+Fi3U2Twe+DXJCeg7mCUJxUxJ/O8rncEQybUyCc7PEJAn76P0R8fhxy2XOAIa1+T6oabxYVlrCoesuYCRnZ3WxQU1VSjo0M5X7Njox9pC/lMqW1Sfbtc0vK5XkR4fk3jY20V7uzhR93jcm8eKdDfbGaVcCAAZptsFkNuNiXDK0In51LCve2aZkGkTryltzjyM8OtHluXWeWSdHBisaSvqjDtd/jZ36H3NDIYvDVbCdyeiuFQLrnf49dxebzsbhsG44wvVfgTVl525sKX8fudUBsdf/IvUI4zQreYN57qOERyc5PPzio5GYIrKPjxghkcrqv1o/kf2CvWWEG25LmTllGZzfh4Vj+71NNxbnfL5CNdrRskIHA0L13zrNl8tkzTJs0Y+z/XbWXSodx7uykvHJ0jBbWO2vNduhpwwYrtno9DqxGX2x78D2bXIeYs2pKId0ADBYs03UP8yKwWRGu5lHeBOfwdoFOOMzCDWSjvPvyxHlQbJ85Nd7uase7oqO+M6Ck2g9/bCtXqsxdbeio+TbZbl3HXzgFlKzjPhWwrSyLJIwS7sI9Sl1YcylGLHhImr+vMf2W/g9AsAJzl507zLH8ZVmO1bopvMUv8dPs9F+znHsu0ejD3MIdegYDNMqi0egqIgp0T9tW8gUJlQrTIMGDUJoaCiWLVuGkydPgs7dr6ZatWrEhymPTNZaTMI+jXe01RbOLJ28nYBQJ5H1lFCE42OSBfEZTFdnAvZz9iypScWiHPimGSaJ2QmKEh8KSQ2Q3qCuYa52PvwN4qYfS09Eof2so/gld5d7Vxyk7TIAQfQp3PT51OU8hFheLYv1uomI9vkItdjbkoO0HAWztVIsOByJtWGxWH3KYtYzXfMnbvh8hqrUA3UKk4p7is5+yqS39p3jtas4R/kmec58VMwi563K/W0RH6jW9EW8Q59AmSL8CQP+nkMS8joxyROjL7MXEfp+oiaJ3JytnLydgLcXnBSNPvSbyGaCciSm51j8A1z8pvkrTI7n5RRBq59NEBOGHvRJydV0W/7OpRGVTe3wy1pHL91NBg0WlejHKEZlICHuBmr+vAcjNjgGceDuQ3bbpy8GMuKBaKxcvpuCoevOIyEtG6u0U9FPsxcrtfZ23mzm1vG8KYIfLQlDeLRzM7gMiUkhKYRScfeq++u4dJTQbIkIk1yGrjvv8N1YZvnFeZWKsplmysHN8UPNEd45tQr3S9RdvADpjcvVcPzWE4c9/YwKDH7EBuxiPkxi3+bOi3cl8y1PSY8lhAFvBjLb8Q5jMcNsdX8Z/74qyvTzFRbLFiUrTMM0m7BbN9rBj1kDIzrTZ1ACqUjKMOBeciZuPbS08Q8UbtWhFIt/reX5aJjxp3YWhilQcq1M0/6J95jj+E//i1vkEe6FKaYwcevBi5S9vvH2XDxwC7GJmdh/j4ZOoXmmFam+Ttwck0Upym4+/sGfp5CswGKmIOFSWPHGjRuja9euuHfvns2RsGvXrmjRooVbhSPYETMn+2QpP7Ke2EDSF1koCnvlvSCwDVb7gXBxtsJkFbkhdRN79aOxNNcEwIpUyFVhrp8ye/EJs88h3Tu5m3Ju0E/C20wIut+d5ZAGACbvtAwqj918jPGaFbjh8xlepewdvBpfLBpmLNTxHYyVdLw0zOhBh+BFytHMiAWLqlQ8mtCWGeS/TaMlFRix2biiSMdK7VT0pI+LXOHIw9xN7XprLCZg/Zldqky01KQVV5iky5uiKNF9ZsSoTMXjK8ZxdlRuU90Os4/irsB/a5VuGoJ1CxGQwfcP4VZPs0BT6EGfRA3qrvi7d1I8E7UroaeMmK1bJJ8wl965PhxicGcQlWLZeNhFkzwAP2rWYIpmieh70Sgwk/pKswPzdAswSbMc1aj76EC7tomjtaKUQTI+ZA5BY1buxM/FKjNNUbz3+eMmy0zx5vP3wLIsz1RO+OQ/asV9Zayfa/f5J/Dfhfv4aEmYbcWkOm03Ycsy2Nthywpu3pSm07IKE+sQNVIJwvfNHaBZ21gxMgwmbLt43xbSXoy4xEzFm1wDytts+XQsXqNu4V36mEwaC345idivH4mTPkMdzrnqt9JvBT8MvxGOPopCxBSmclSSTZHQwAgN7HsCcvsLuX5K7pxwHM6t68LreM2kkzpsjaCoZIVpqGYzatGxuOIzABVgb/O+ZHbgD90cbNXZlRDrfcXMIvO8mJX7SE3pCHRizmKoZoviS6tR4iarVp5mGfDfhXs8E0w1iClMYsEdAP7Yi2syq7YmS3Uj7WcdBQMT6lJ3QOea1M/WLsJ7DN+n9dB15RttFwRUK0wZGRno378//Pz8UKdOHcTGWgYZQ4YMwdSpjisjBPcgNsARKhxijcFp/WBc8hlo219AGK2F5pjQiM1UuYM2jMVE69VcPyArch2N9XF9kYUJ2pWYpF2BYhR/1kK4h1SpbOkZNCufaSyK11DNZtsx95n2SNPNfATzdPNxQv+dwzmWBQyC2UVJPySR44M1W9GGuYQ5CgfgouaOiq60Xq98wCI2gJZdYYJjR8vyfJgs54drNuCofjhGa9c57MtlpuSbteAD4sFp/HP4ygdXDm5da5wdhnm6BTigHymaj9KgD3L1jntmunaJTC6uIfbp+SNT1LzMyDHdYk1GDNTsRB/NYWhSoi3HOHmJKchSvK85hkP67/GXbhaa0o7R35zrdJYE87TzMVX7F77O+AMAfwCmRw5a0ZccTGi5WCeNKPDfCXe17NPlZ/DK2D3CSyV5ibqLXzSroBeYh96QCAQwfrv9+a2RJuUoijTRlfIc1jLolmtbZ2kX4bK+P6in8kGELM9vz0eoYCnZqw4Apu+5gSH/nMfgNdLhiQFlvk5WxFaRXWGLfhxm6xajISUfxaxEVpzkOXdFsDWwChQmkXt1ZsJxQT8QAIs1ut9wSv8NmGzHesbAjHfoE9ih+5FvDgr571b+8ViZX9br5ctHrQ/TL9q/bX93Yyz+m5XpR05XrN2B9UnUtHNWnCnEwzdcxNB1F/DDRuXbEnChecqx5W+pZoDbR3HdPWrQzreZaUpHYI9uFBpT12Xrxq+apdiu/xlBjy3917uMYwAgV8xZvYlqhWnMmDG4ePEijhw5wgvy0KFDB6xfv96twj3rVKbisUE3Ae1oR5vXidv5AwhXZ7ECKIvJ3at0lOh5rpLEHSwUx1OUh2WZXu2dx269ggYT99lmZKWul9vUz3qGKx/XBGO8ZoXDNZSzneM4mHOr/rozzpUs3j3EfMck0qZyfEsaslck82RzTfK4XL0vvsmqWANVkhM6947IUviXzHYs0s6RNJdiQbmw4mB/ahpmbNBNwEztYodUSqLT8XIVK0ye6aZFziGarbYjr9N83w5n9WDTWYl3LriOWz25+3ZUM9gVLh3lqGAIy7I8ErBHNwofMQdl5eKJ4qYBoRQRgvpVFOm46tMfh3QjHNLW+Gk3R2G0lxFlcPSRcnXSpb6oX5OyvJoxlrbyrRzHVejp2j/xt24qJoi0F1asSqJwppsbiv7YTf4A09n72a8fic81e1DvWrBsOlcoinRc8hmIi/ov0Ja+wBsomnIHZXJO5O8xJ+BDGcCeXSmZpggycEo/2CFcN3cjXbEZbTmEJmh5waxi6PINswXRPh85HOdKX5WSVx7l3rf1ex+m2YRV2imyPm1ymDgD6vb0WQwQidQmNQ7QUGYURxqa0NdRmkqFz9MonLz9BIuP2r8rBmYE6xbiVToakzR8Uzq575Z7RjjxIPQv5f60Dtr7LDmFylQ8Rmg2oAQc+zU5E+spmiXYqvuZd0zK36oN7VzR+O/CffwrbP+dNDN1qGgc1I1Aa3MYcnLNE7kTnMI+ThgMxYqzOrs/wuLCsPuKfF2UgjuBYZ3s4++3ZD/PtbLgbggvptQIWaebjFfoOGzST7TlL2wfAbsJ7JtP1rq8p11BQ7XCtHXrVsyfPx8tW7bkdTC1a9dGZKS0My/BkenaP/EGfQPLdTMczi07yVdwlERRsb4OX5EGZYV2ukOoTJZlJWdKLvh8iVCfb/EFswOMhKmLVCfy96kYJGcYJKPjWVEyM8dVUIpy7JetK0X8tMoH56bcqj92m+PMtlJ5nPHV6rOi0YqEsGAdOqy3c80NhYgpNtxx3pucSGtWxmj/QRfmDDrRlkAKDiZvcDSDk0PYadenIvEGfQO9GEfTFg3MqEXFIIh2jOQmBgVgyi6+AsQKFBlH+e3NWFq2EbceiiubQiZpluFnjX228vI9fnhuqcEJdwXrDfqG43nuoIGiMEa7Fq/QcfhNu1SRXIDnFSbhSnPj3OeoRDt2fAAw+t/cQB5c5dVk+b7zaj4GAJVETFWFlEES+jO77AcUVNq3c30t+mgOQwsj1mod/Wytq6AUxf9KXR34cglIj1aUjreho5MSrUdbzIl9KANW6KbzJiqsKy9/HJP2KbLCyDi4v8WcQRkqFd0Yvtn3xnD7YNMV8ybu4CwvKF1hYkHhe624n4mSyZy4xAxLdDiZh7VWw6GazWjNXLa1s2oxctqxpbpZ+Fm7xsHP0TrJKDb5peE8D23IwMd/hUlOiJah+G0dBRaTd0Q4RGgE7H1OeSQ4+O7K9bnWWnzqTiL+043Ft5qtmKn9g5cmIS0bu2W2S+mjOYwGtFxddlzNj3USGGmEyhWcP3SzUZ1+gBnG6RiV2w7msHaFyUehT7RJ5XA7ABloRl/FMM1GTrvHYpV2CpZoZ8L67HWoKKzUTsWNi457V3EVFW6fsuuyvcwvCix1VJHbBwijCguJFPG/LYyoVpgeP36MsmXLOhxPT093W7ST54XiULZPAQCnygdg+QiGMJtxzedzvJTGb7T1lAFjtWt4x1iW34iKKQM/adeixV3xgR4r8BURbv4qxo+aNbZG1mRi0Y/ZjRP6IXzfntzQ0u3o86hP82fIhJRBkv0yNX44Lg5I1V41a59lYCo3AGZZ+c67KR2BUP03eJM+J+p3oFSJK0pZOpJkwaCFBWwzZ0qQN6nj58PAhN36MViom4fXqevoRofidZn9VK7eT8UWgTMrd2AsFtZV+C53XbrnkEZIWSThE80BDNDsth2LfJSKBE5ERymF3tlMoXA2zTcfTEXkKINk/KhZg6oyNvSKFTSu8mp0HCiIRuxS8F1+rHFcfRNGV1uj+w1jtas591K3etmZPoPmjOMEiXUliQLfh0ku4p9YeVUUif5oppTt3MFTmJwUl7Ct4Co1alZetDDh8dNsB2sGoTy8aziRGl0xelDTzsih9Dnl/XbkYQG0mn4Y7WYeQSanLnLrnQZGh/qtdAAtxCRislWZfgiAxQJtMIK182Eys7gR/xR/aWc6pKV5ClNa7jGuian9vFBGCiz+OhGFiSIbI1sf7yORb9R6siYVi7XayajHivuyFacsA+b2zHnM0CzGh8whAJYQ5NsvubaiIsT6rn/gRGl1B9zAWCG5gbZy4Fxh+prZhmifj9CZtviqqVWY1ukm4R/drxiq2YKx2tXQwIjySERr5jI6Mudscv2rG482zCWs1f3qkAd3fkvt51qTcr7nG2u09G0JTjbeHbjKtUmEgoZqhen111/Hzp32lQqrkrRkyRI0a9bMfZI9w2TmDnqFfitySJmvCUMzDtduAgC8Fz8Lzj4Rs2C/G6ll+erJ4qsdXDrS4Tjn8xV+FSz1A3zFaqBmJ2ZrF+GIbhjKpF/HOO3feJF64uCHUjrnLpbrZmCNbgpHPsfO9l/deNvfagZQagYWXMTKiJLY9wkA5h+2hBB1pjDJ2USv001GeSoRy3QzQcGM+dq5+F6j3vzVukGh0CTtU81+vPHbAcX57Lz0gO9Ayuno5YKIvMOcxHzd79BT0rPMog6vnEF6nyWOK1VChUmJWZiYKR0APEmzN/wmiT03nNUd4afqio+cOw0YJmuXYaBmJ3boflR0v7q5AVHKIglFYRnoXI9/ivcXh+BGvH31zmywrGQ7G+AvPxmtWFZuWQmjQL1MSyvSvDwkPrXKEuHsrSstlhUmcR8mJbxMiZh6KpxE5N53X8RDXhh7x7TSqJkIYmDCiI0XHawZAP43VAr21QidxlL3j958jMcik3hVqQfoQoehPBLwnWYT71rlsKhDOcokJR8XBiY0puwr1EoDHQzQ7MJYzd/gfgncKK7JmfZ2gYZlO4Z52t9xXf8ZAtL50fyk9gF0BgsKHelw/KSxTwr4IwtlkIKuzGm8w4Tgx3+Oo3PwMbRjHFdJuH0IlTvzz1OiOH+XFqwwWctzbVgstl28j6a/HcSRG4+sggEQb/esZbhcNx3NmQgsM/HN5zaccfT9el9zDFO1fwGAYG8nPq9IDNj5faljUAu1QROcvS1nZvhSgW5GaS17lP6hmwPA0YfpBTzGKu0UtBYxJaxL3UEdQZRIoSmiVQaf3P60BMfHO9ugLrS6GHv1ox0iGwuhjMoiEUYniL/nwmaop3rUOGXKFPz000/4+uuvYTQaMXfuXHTs2BErVqzAr786argER6x9qJKoOELH3jJIwiBmK0rndkQmM4umdAR26sagASe+v86c5XRm+0laDr+RtUbWUah4cCu71dZdbKZYSE/mJKrQD9E1ZrrtWDcmjNdJljE4Oh+KKUxcEyI1A1Mlsz1t6fP4T/czXqbsjb6ccgQAA5idor4qrJxJh8Uozqk8APAGdQPdmDB8o/kPAIs52gV4jxFGx2PRmT7jEJFPLoJZVTh39rQidFzvytiVGL3Qxp3zXGIrHAu1wbaAJADfcdUKz6yAFTcp5KLWb4p7HXcjPj2biQO67/GLZhUvXVySfCch7KTUrEragxS4b4+KWpSl4/Wn+O3BWM3fmKb5E5Yv2S7lVt1YFMdTnPYZjEs+X9iOn4lOwrwDdhPEnZcsdea9RSG2Y2ITA2Kz1krIdBLFTc4HUowftBtEj2sk6otW4nv5itkGrYg5m2h4Z4VvX5hKTBmx30e6fnMHtWLmVVz8NNLmONx7jORMzmgYCveTMyU3Zj2sH4FFurkI9fkW32k2Y4xE9EAxrJ9Nf2Y3dup/kk27QjdN9PgwzSZs0k+0/S5FSZvnctumWnQs+mt2ow4Vg7fpE/hHOxl/7bav3BX11dn+ZmDGCf1Q9GBCoaHMeD2WP0nIHeiXQCoO6kbgW2YznEGBxRLdbHyhsZud+iKHV4fuPhEPGgLw3xmb245xn5Eb4Mm64iN27ZB/ziM+NQufLbesjFjbM6noo6lZBlSgxAfWI/9VttrTkLrJG78AwB79aNG0Ut8U9+jOS/y+pgyS8DmzmxcxOC9wy6sPc0iR+a5Q4Zym/ROtmctYlVuXuT5I2/V8xRMAiiCLNyEiN05bERKN24/SeJN3rph5v0LzFd752rm835TRufWEmaVEV6NfEptgKuCoVpiaN2+OkJAQZGRkoHr16ti3bx/KlSuH0NBQNGrUyBMyPpMUx1M0oOV9vl6jbuGGz2f4QbPOdmy5bgZGajdgUe6sBQvLCkQdOgb/6Oz2+RpjJn7SrBFmyWNNWAzvw7d+Tg4DCE5lr4An6MMchF7QkOslZuzlEDYgS3SzcuWgRGePGSdKBcWKRGRTaVZVFOloQV8GDTNW6GagPn0Hi7TB9nvIyFAOifhZuwa/aZeKDGocG6sSSEUD6nauSZ6ywZ8vZR+sV6IeoSfjuPr3Fn0Gf+jmOETk08o06pblfRYt6cu2WSUKZvRnduE1yjGqHPfdf6XZYftbqDDx7i9SR4KY0xiqsW+SJ77CJD/wq0LFg1tJxcpSSfm2oi9j8g67SUlX9hhq0PfxuYYfHc2Zss33YZK/5/vMEWzVjUUZJAOwbK75t24qilDKZu6UkA5fh2MMTOiv2Y0PNEdQkXrEe58MxeINQSANK9xyPBdjqSfX48UHcdxw6EomYcogmWf+4gzJfdxUDgysK0lLT0QJvm/xOjNau070uFQdk1N+XEFeYbI/+7aL3EkQR9l0lJnXPvojEzt0P2IIs5n3LCU5SoeOoXE3Sfk7kt9rjI91X6gBHIVBSDXqPvTIcfDBASyBKgYw/Gtr0dLR7cRqSV36DubqFqIZE4H/Zdj9Gw9cs0/M/axZzbu/UI/gmvl+qdmB6vQDjNBuAsBiiXYmFnL6E748ju+oA3OWNxiXW/XkKkTWVXkpkzzHe0tjzUGs3aNYMxYcui2qTCnZsBiwrJxs1o/HVv0vaEWrNacTdykYvJYfkXGN7jf8ov3bwYfKkoWTcYXIMW65DtP+i2VaRz90IUZB+ZUT7CPmbALIj8ritdPO+rQOs49KRp58uVwRNKGuoR+zG3LrPNwJewpmB59GKFCYpHKvQsUXuiUmVQqTwWBAv3794Ofnh5UrV+LKlSuIiIjA6tWrUbduXU/J+MxBUxQvNKYU1l3JB2u22To2a2huqx8I91v3pTirUazJ5vDMuzdXQaIo3u89+tGoQ0U7NMpPs3Iwc+8NsCyLPfpRmKJdim81WxTXdamZDSOl4/3mBnUQG2DRMj4FgLgPk3RYTXGZNugmYo1uCj5h9tuOcfdLkVOYilD2gYRwUCNmKnNCPxRb9b/A736IZOMnVHK4yqzUihE3RLPVpMqSl3RnS4FFe/ocVuumIMznG2hhxNt0CMZqV9vqYTGkoSV9WXbwKxe+Wcp3aYBmN6pT0n5HrOAlCl3ii1EZGMHZQFBsYNCRCRcNhsLlK80OhN6xb+DY4IUiounU+jDJMUP7JxrQkTbzjfc1zveEAYC36RO5Zqz2e+mRg9ep6w7fr9j3x60732k2owT4Ss+fuRMyQoTvXvis3F/ccOgztH+K5sfljM8g/Mzxs3S26mo1jcorGt6kEXcApg5R/y1Q6DTHMRCLkmulkBsocdsZ6wrdC3iME/qhiPb5iBdJjIGRl9Nq3RS8SkdjuHYTT540jsKt09AwmJQNhC3yiJlxmfEWfRqVqXg0oG5juGYD9MjBj1suA5APr31I/z026CaKnrviM8BmnqQMx3KcpFlu+7s4x8SJu8lvX81+3jXXHqRJRmjj9mmBSERH5hyCmNMOG7BK0Yi+hR+09hU+uYnJ4/phtr8pm8KkbNsQWSXcusIk2u6xeJyWnadxrz+nXf5bNxXVKHlrBxZAO/q8zXTYitjzNaUjMIjZajPnbU87hrZ3xSJB+L22Zi6LSMknmQ2QzcMZDMy8tlzqeu7zSAULY01GrNdPwjjt32gjo6RyJ0BFFW6T84k9qfGfkj37ChqqFCatVostW7Z4SpbnBooCqjtpFIRIfloy35yYWQ93gMFQlEMjM0u7yOHDMJhYzD98GyGRCSiaqxT0Z3a7tMTLRXg9rwEQXWFyojCJnJ+x1zGKGWDZv6E/4ziTaV2C5pqZcZFz6OXK34/ZY2u4bsQ/Fd/3JtdEKuDecdFnG69ZgVs+fXnHlOz/wJVjtGat7W+5BooC0J4T3n6IZjOCdQt5af7TjcVq3RT0kdlI1ZlSK8UuGf8aOAzSHVN8ywkzLlZG7zAhgrDnzjsrvVZ84CZV71+nrmO5dhrKGuzKnw+bjfaMvVy5YZq576kY1EURmqtbiK8023md3RTtX9ion4hxHBPCokgX/S64ZfQec9zhXUvBbS9MZjMvdL4cYhEUneFsQEGBxQ8CX76h684jOSMHb9Mn0JyWDuXPhbvfEPfNig+kpGUapPkPIzWC1SeKRlKG80G8mnDs8iGg7V36/eRMfMgcwkmfoXiRsoT0XskxZePWgcbUdbxG202iuM+ew2ptf5+NScK2C+r6LiE96RNYrAvGUf1wbNX/giGarfiM2QsAGKNZIxmp0Up92ahpyqki4tMmVbLyYcX55cqF6685V7dAUX5CuJt9yk1I8chdlef7KEu3zW1EfKJsWdl8mBxlpsDCZGZd9gkGHFeuXpKZPAMsIeCX62aImK05vr11uskYyTHF5Zb7q9QdzNfOQwWz/IayQhpSN/GLdpXDca5J4WhhOwAgkaMw6ZGjaM8jLnSu8b4VMYubz5g9uKbvh0aUZdxjndzQwMiLFtktxz72Ee7JxcW+R50ZnzIikYkFgX/EJrCk/CrNoBwmPws6qmt5z549sXXrVg+I8vwg5qfhjPLZUaLHT9wW39uCBSVqgsWdTWVox873FTqON/gE7AMXbiQU3mqWiwg/FX8qG0u1M1DM+NjpIE8MsQEWdx8KLr5UDsZqV6MGdVf0uixWJ3IVUE9kP6uZ2j/Qmr7IaxZ+0q7F+4xlZrlz8DFk5HDKXaC4mBk9xoqsOIqFTude24UW9yPgylGT5oQBdjLDqOe8U2EdiPb5CFVoywCjGx0q2eEL31FL5qrkPbnoKQPmaueLrzQ5OC2JP8cPmnWoRt2XXAHrytjLy9lgnGVZhHFWm5SwUT8R7ZiLGJIwyXbsf9jBS9NNQhFXG2DASrlc34EG1G3bHhp9NfvRlbbsfXLJ5wueWVLZ3KiSamb3KIlZagpA/QnWOsqiGNLyPInCxZkSQcES/prLfxfu4+KF05irW4i1ut8U3Wen/qfcVQu+L6HYk3BXMoXUo6MwSLMNlTl7+igdDojXR/Gr5eoud3Dyx7E7Nud6MTSs0XaLuoJ2baJ2pagU/124j/Xh0mZuzmDBIkho1gPYyuxLjePeQ55CzL+KO/BXWpfl0nEVnCYcM1dXvxPFvo2sdQJA3lTZylCN9ES4dVArZYpsUZjUP4+1rRfm6ywvaz9kwfmKixQ79D+jG3MKk7OmiJ6/dDc518ePn+9m/XjRUOc1OEFpvtJsdzhv4shqnSBQA52rYlgR6+fGa1dBTxlsk4PW/Rx7CvZXqpFjn0iWK++X6ThoYcRHzCFehFKbDJygDy3oy7jh8xkGMVt5aViJelMYY2orD9OWS40aNTBp0iSEhISgUaNG8Pf3550fMmSI24R7VqHg+HG/zxyRvebtx3/iLziW7eC159DVR+QCiEfr4dpDUxSFrzXbHNIIP3ZrQyvcp1B5hyLOg9Qc1BBM4rdnzqNG3FjsKtbHIb2zQaWajWutlJBwAs2EXlU+q3TT0DF7Ou9YHSra9je3DCL0/TDP+K7tt5nWoSmtzNafq/CKObEzMAkaVc7fTgJWKA2HS1PS80Ku7IBu5W0mBE3oa2iavYB3nDWb0Yc5iM50OL42DJWclRqs2Yb+zG58kDNW5i4sAApFnfjKhEXxnZjrU7dxka2h5DFQ2mjv0CtBPDIbAJTN9VsClCkwpZGCZbrp2GBqaztmNZnYqv+Fl3a8dgXWmDo45FGfjsR+c2NVChMDs83+npbosCdrluF/ogFfLOXtCtYZcT1y0I/Z43CeAmuJwCnIvryEA7ocb9A3UB6JeMoxPxMbgAknEsTg+pIqHxjz71UEGditG4Oj5nr42difl+5dhyAvdtSELqZhst11nIyJuNwzFEUaUuEPqXdcJTcstu08Kx5kI0tle+spuCZ9zr3ZnJ/rLjFBYq9b9qut2z7IoXiFyexokudq22xfYRKPkmdmWRX13E4zOgKRphccvrNX6ShcYysplY4ji5LUllQ1OAEHKrPiwQd6zLf4B19WWDXlFLbhmg3oyNjNAR1WohXwMnWXZ26v5n0Kt7AxmYywxhyTWx38UrMTjehbSGX9xBOY7D5MUzSWyZmR2g1YaHrHdtwTYwVvoVph+uuvv1C8eHGcPXsWZ8+e5Z2jKIooTAoQW2ByZuOvgVF0nw+1aGDCF8wOlKFSYKQmojOjPD6+WmdqC3LmI+L5lc+KBIqJKXvyH5ir0dHEkIuuJIVcgykMkMFVdsy0+GqWGM6UxmJI58nRkGNmwy3tF8BfhqfAygZs4CJXzjRYl1dLACCQSnI4RrEmTMnd9LWfeS/AtpW83ocyyM6kFkM6UlAE6yX8IKw8TM3ilWNNOg5F2QxFQQloTpAKucEUd5+f1sxlVDPKm2h8qdmOenQUb5XTBzmi/hAMzA77pFnkoXLPq1WYLFASAzBxZQn4Xfs7vjW41idY3+M3mq0Sior4zLarRh4UWIFC6FpO/IhhytpMGizKIBlBTBi2mFqiJ3MCFenH+B99EMWpNEw3fohYthxO6b8R/UasqBm4Kt2Y15fKxifMPuwzNcZDlLQdr0dFYpt+LLaZmmGI4VtIlfxb9BnsMb+RK5/4fbOgvA30BrLbQoica0Jd463YC7HWM+sgE4BItFNHFCtMcAz64Gr/KGeSR+ea5HHLoBRS8K1mC9aZ3sR1BYqPsL0eqtkiu+LFhR9g3Pn3ak2xQjddNh3/HsraAS1MqENF4QZb0eHcEEH7xQgmLydplmGs8XPZ/OfoFvHzUPg+O9FneOa2lmvt7b+zFb3G9E0cNtUXPUdxfJikJmukFDJLHyV76wKHaoUpKkrcNIygHFc2+GVYA/7SzuId08GAHGglrhBHAzN+0lr8Wg5SAxVdYws3rlLskkjFDv2PkiFH5e4o7sMkP8iT7tQsAQ2umKuKnBGnsczmqlII/SmUyQaYaeWfYQfmrOx5LYxoIeG78TIVhx81a7DQ2APHBRH0KLCKG2Ch8ymXedrfUYFSZ8rmDG5VKEplgHWykig3MLDWZbVR6Myg8bduKgDgD2NX2bQUa8KCw7cxuF0NVQPYQ/rvJc91p0NElfhS1FPReleSSkM/jeOqzEztYnyZMxyxrOPm41Jw64WSfdu4dGdO5VlhEoYb5p4XV5hcNHeiDNivs6/UUbCEvs2EHnfZMi7lyZVFrr1mYMYq3VTUomPRhL6GM+aatnPdmDB0Y8Jw0PSarLIEAOWQhPeZI/jP1MJp36BhTYoClLzDhOAdJgRfanagZbbdB88aza4HE4qhhsH4TiMeOrsnc8KmMK0KjcZHtONGpWUFEcMKGvKTYY6s108SOWpnpnYxhhkGoY9G2h9UDB1lVDQjYG0juVYmvZkjqu5lxcyyGKlZh0Ei1igUWBy58RgsY6/nU7VL0JE5h880+1Ala63DNVZq5m7X4erEhPDaDzWH0YU9jW8N3yIbOsgVlNWnz518q9mC8lQi/jW1VH3tJ5oDThUmIa2ZS+hKi69gWnmJuisawIc7+WxmaUzULEcMW04yn1a0MKiFhYTkp7j2wNIvSSlGUm+hES3uX16QUaUwhYWFYdu2bTAajWjfvj06derkKbkIAhjWgOo0f+n4D+1s9DOMUpUPd7fuIoyy2Sr7/kx8uFHhxPhcs1tWWZL6wEwsi4cpjrPmNQXPP0/7O+93lpHFP0cj8aXgujXa39CCuYo01tF20Z0+F9wldyGyszgqplla0PI+QTRYVKXFVyK75Pp7VKCeOJhrUlBuOCUXoEAujK/L8MKKs04dReUG8gf0P6BrtrhvS5j5FWkROKs1pSjpvVAAy+B3xt4bGNxOmQmfEn7XzRc9/pVmOxJZ8Wh+wr1WrMfW6yehZXaw4ntLK0yeNalIg4StcS5amETbEFe/6Tfo67xQv0M1m1E7d/PIellLUNeFYAPW0lqinYmOzDn8Zewimq4OHY1atGX/ns70GYRzFCYr3OAhUmgpE2Zo/8SL1BPMMfaSTas0UpsV4SAzmxMMYoJmpUP0OCslqVR8wuzDCXNdLDgM/ODjOKHSizmGlcaCO55QE5RDCZ2ZcEQw6gbIgPIVJusWG1yF4lOJ9+MMFhBVlgAgx2BEttEMM0dhqpMbydcZViUhLz0wd0xg9RH7n/kAlpqCbD7EXNzZ3wuxmgK/J/AXUooeOfiAOYzD5gaK0lutLuSoJrL3IcCffH6NviVpIWBFIxHMadOZaGwLs6yMctvixVq7kiY1zvtUsx+h97YDGCx774KEYoPnLVu2oEWLFpg7dy7++OMPdOnSBcHBwR4U7fmmLX2Bf8Dk2FCK7fZtRaph4Jq2mFVu/ChcGWtIi8/8fsgcQrTPR6gk2DjVUUZxzKzFJMoZPZhQ/nWgMGW34/4xLXIDD4itKrgSvUsplTkmlLIrTCLnhLt6W3E2a1zPyd5eAFCPchz4UQKHdzl8qByPdjw+wg2XOStKFFinvmo+MqYwpalUhPl8I3ruKcvfr4hbHrN0i4XJJeFuaurJcrJSkhL3w5NDrA5IcdlnABpSlhVXpU7k7iALOuy4JG2mqIPBreUrzMuqLAHARt0ErNGJO4fLY8nTOpnC3aOHC3d1hqFYycAlSvmcEb8PlybUVdVvkOv7kc1pi6SUJcCyncAk7Qoc1o+A3Kz/ex5si13BXh/k20adyCbGnkKvNOiDmUVlKh4zxPYdksCh3QWQnm3E8PUXJK/JyY3CJvcdtqflrSLyYsItRoncCS0xNwc9ZcQXzA7JbUXE4L57d2xjIMXXmm2YqF3JCw+fV6TKlhs8pInEnnvK8re8f19k4SVO0AtuMJ4AKlNycq3SA8fAVgUZxQrTb7/9hs8++wzJyclITk7GhAkTMHnyZOcXEkQp6WSWWmhj65/zBEbW9dCdYpgVrmyoNcmzRmYSKjRqcGWZ3pVIPWpNItTQhrmE/zHOZ/XEXkOEj/jsozPTlT90wU7vJxa2twodj+ZOVq+sqNlc1BXO6/lrhNzNbGtTMQ77MgmZrVUWIltIB+Y8SsG+IaWkgafCqrn4aGSBtdFeqJvnPBGHzfrxeIWK5YVJVmrCWQbyZmRS1KDu4Zu15yUHYzoY3WqSJ4dwdVsprsqSV2U0wMnqv5VibCp+0jhGv5Jimm1vLdeerKPM4Dk/JhfU8qNmDY7ohouu1lpx94BfjgrUE9SjnE+KXX+QjDW631SZnl336Yf/MftBwYzXqesoggwsOHzbIQAOF2s/LVVbNTBiqW6WxFmgNX1RcgLLVb7R/Cd7/iftWtGAWEo4KGM2nVcaUerdAJwh5ffN3TeKq+iozj93smC3boxsuqmaJRJnCmgHKYHiEfiNGzcwcuRIaDQWK74ffvgBycnJePLE/bagzwNqbWhL4CmMkN7QT4giB0iFUeWkTPLyitSAi3UxvISre0FY90PyBJO1ywHIy/YkzXOzVkqZrl3CWxmRoziVrnhA5grCkPUX4+wddivmCpw1smVcCNhhZXqxf21/i4XlB5RvLjt19/VC1h3Is0c/Gks4fpTWEOlfMDukLgEAnPFxzeTCWYhpmmJtG1JyEQt2oYSqlKNvTZ5xwV8VgM3PNC9wlX8p+lE78IXGcT86KXxzZ9jX6SbjYydmPGIEuhDB0Ft0Y8IwULMTVeiH+ERkDxor+Rnta5z2b2zTy0UBtXD5bpJLfjqTtcsR5fM/bNRPxCbdBMSnyFt6WMYGrG1/RoCv+K7XyftyrZLYvyqv9GfcF56e+wV7wvfJSlUR3z7X83qI3sxh1cp8qsDKwhnWiZ0qEm4AVnprJDbvLqgzihIoHmGmpaWhePHitt96vR6+vr5ITXV9cEJQjp4ywqDC5UyJU7tPmrJZ06r0Q0zV/AnGoN70Rw6dxK7lLCiX/CPEBkplFcxue97hWN7rZtsldRvnPW8IZ9tzDJ6b0W2ffcD2tysrls863M0WrWYX7hjcu4uXKNdWggBpP428wAJ4l/aOqdnPIvumCKnEqts8MwcaFEWa4m0Q1NBPo35vmvyig4z/WF4sKTyFO/wLX6HjEPFAfnxHg0UTim/SxZ2sbUTfyrMcrjBWu8ZteeUlKIUa3K2MTdcusbkjKMVZJGIhhTE0eF5QFfRh7969KFasmO232WzGwYMHceWKPSpXjx493CcdgYdY2MavGNc7eTUrMh9qjiDqmmumTlK8SklHXHRlqJot4t9z2sXZbXfiLBQwQR5hh7Xw8C009fA9WRboLeI0rJZsI+tCLNLCwx6duqAznma/fiRizMojAHqamw/TMFuF/5s76cmcdJpGaWhxKw3oSFzyURZdVYoMVg8/D67qE9znX3g9Xt51gAJr8xmyoiYqromlHEJsFxRa0pdRm4rON4XJE6j10VYett5C3hXzwlW2qrryTz/91OHYl1/a/Q0oioLJlH/2vM8bYjbeo7XqN0CzojLmA65GXEVV5VaBTpFaBZO3ipZGbYj1/MKZssSCQjxbgihVEjCCunA2JhFOAqjliTGbL2Pj6Tu47eO6bXdlKh4xbGCB9MtwJ694IipiHqlMywebIdhRO6OcV/yRpWpzXYJreDogixUjGNWDbC6W9rFgDppXuxTkpXAjFQ1PMj1MHg2EUdBQ3HKZzWan/4iy5FlKuBANSw7WrG52Mb86uqJUpkv28bXpGEzSLPOARJ4nSSI0NAEQdqienvH753Rsnk0NjuqHAyioQ4HCQzkUHp+Xwkh+BiwALBN8nvR/JFhwp8JUnZKeOHqBSsA83QKX8yZmz4Wb8dpVuKzv7/L1hW317hk2FiE448aDZDRTkT4/GzdXQ11+ojngPFEBg4bZadTE55mvNPygAvk1e5pXxmr+9rYIhR53R9DKfwr2gFBpoBdC4WJUHixPuFTAExzU/+CWvMR41lfgnwfyFFb/WQ36QHj2uByrbvbW1Sh0BHkma5fzNswkyFNDZsazINFfszsfAooQCjIt6cvOE3kRTwRvIDw7rPBQFDsreonATwRCQYSsMD3HMCpnBt5jjntIEgJBORt0Ez2Wd6yuBr40bMenborY1YmR37SR8GwjDJFPIBQmxML2Ewjug6wweZSFCxeiatWq8PHxQaNGjXD8eCEcxJsLRijG/gp2gycQChpqHVPVQLMmjNH+oyrSE4FAIBAIhGebQqUwrV+/Ht999x1++uknnD9/Hq1atUKXLl0QGxvrbdHUYXY9qow7cXX3egLhWYXOZyd4AoFAIBAIBR/VCtOZM2cQFhbmcDwsLAzh4eFuEUqK2bNno3///hgwYABq1aqF4OBgVKxYEYsWLfLofd2Oyuh0BAIhf6BZojARCAQCgeBxClnQB9U+TIMHD8bIkSPRpEkT3vF79+5h2rRposqUO8jJycHZs2cxevRo3vFOnTohJCRE9Jrs7GxkZ9s3yEtNtexabTAYYDB4cZXHTBXQHYMIhOcbii0Y5rIEAoHgSVJQBMXg3q1KCAQ1sCzr3bF4LkplUK0wRUREoGHDhg7HX3vtNURERKjNTjFPnjyByWRCuXLleMfLlSuH+Ph40WumTJmCCRMmOBzft28f/Pz8PCKnUt726t0JBIIoJuKkTyAQnn3usmVRzM17OxIIakhPe4pdu3Z5WwxkZGQoSqdaYdLr9Xj48CGqVavGO/7gwQNoNJ4PukdR/Lj9LMs6HLMyZswYDB8+3PY7NTUVFStWRKdOnVC0aFGPyumU8969vbv4zvgNgjXzvS0GgeAWNDSQxz1rCQSCG0hn9fCnsp0nJLgExTCkrSN4Ff8iRRAUFORtMWzWZ85Q7cPUsWNHjBkzBikpKbZjycnJ+PHHH9GxY0e12SmmdOnSYBjGYTXp0aNHDqtOVvR6PYoWLcr7BwBardbr/yYYPvFYWeUnfT7s620RCIQ8c9anKQCglDnBy5IQCAQAOGx+zdsiFBpGGwaoviaD8o6VzZ+mbl65L6HgcfJJEa+Pxa3/lKBaYZo1axbi4uJQuXJltGvXDu3atUPVqlURHx+PWbNmqS4wpeh0OjRq1Aj79+/nHd+/fz+aN2/usft6imPmet4WwT0wxBuL4Bkumqs5T+Qm9pcmiv8lc1Vvi0Ag2LhiruJtEQoNW00tVF+zzP8LmFkKBpbxgETSVK/l6NJBeD7ZX/pjb4ugCtUK0wsvvIBLly5h+vTpqF27Nho1aoS5c+fi8uXLqFixoidktDF8+HD89ddfWLZsGa5du4Zhw4YhNjYWX331lUfv6wnKVamDR2xx2+/jpleRxBbxnkAuQtFk72OCZ8jP+Dk5Gv98vJtnGJgzDIuNrs/empC/Aycpvjd86W0RCAUAM8RN7fPKXOO7HsnXm5wc3V5V+tezFuKxX3XUzl6GmtkrPSSVI4dN9ZGlLZ5v9yMUbGb0auBtEVTh0j5M/v7+GDhwIBYsWICZM2eib9++ipe08sIHH3yA4OBgTJw4EQ0aNMCxY8ewa9cuVK5c2eP3djeNqpTEuzn2gBRRbHmMNnzhRYlcgyoAK0w/G/p5WwRCASfKLG62CwBXzZVRKsC7QWDcQSrypvQV9dO7SRLXecCWxC3zC94WAwAw30hC83iTBpVKeiTfJUbXfSaS2QI6sULRGJLzjaKkZpbCYxSHj5ZBFvQw5+N2nPfZ0oCHFGFv8oBVX1fDzS97QJLCRXF/7/c5alD0pWzbts0Wdm/btm2y/zzNoEGDEB0djezsbJw9exatW7f2+D09AU1RMLP2hsME2mMzas64YK7u8rUU7f1Z6dUmz/nOSbHVVPjMQAsf7vke7rGlJHP6LOcH9Mn5GbVe8MzgTAnuGoSZWQp0HtblpILn5AcNsxZjpbEj+uWMhKmA7Kc+0/iBt0V4rinuIQU+LwrCDdazVjSuwlI0tpmb46pZ+eRxp9rSk0ieggXAPmP60ixDLwzMGe48oYAfDf1Vpd9raqz6HgUeqmC09UpRZE/1zjvvID4+HmXLlsU777wjmY6iKJhMZONHJTA0BZYzjDNA4zWFiWv8tN/UEB2Zc4qvpBnvK0z5QdWs1Yjy+Z/t9yjDQGwxtUIP5iTeY054UbJnGfcY5U0z9MH3mvWi547kOpZTlPfq8VRjH0zV/pXnfPo0rYqEM65vHi7W+kwwfIJx2r9dF0ohiSiKcUbLSnEdKtrj9wOAtcZ2+EhzOF/uVRhomz0LR/QjvC2GDYr2zGDK1VZliTEIJ8x10UR33a3yuIXcgaeSCROaYjH3wwboXq8CShfRo4iPBljjaQEtVC/th4RCNkiW4wFbEr+b3kUg1AcLMqowgU5jfbDH9Do6M6637wWSQubSoajmms1mlC1b1va31D+iLCmnc+1yMHD01ZfLFeUpUFLcZUu7XZYiyLL9rXb2jc6nFaaz5pdEj8uZWrkTVlAu2dDhqLk+slldvtyf4DqZ0Dn9sljGew13Nuses9bWL5eFj8a9ky7rTO3cmp8z6lcsjqD6njfJe8IWxY9G5ybQMwy9PS5LQcHAFrDBi4cG1tN6NxI97iz4wa/G/yGdlV71ijGXzZNceYHNXbahFKqDbzd4ATRNoUvd8qhUMv/MkauX9gWlcIzxYc7PHpYmb8wy9ML7OeMAgDeWU4pBRGF6zIpvd1OEyhI9Xuh5FhUmKwaDAe3atcPNmzc9Jc9zQ7Uy/uhc1d74lvU1453XXnR6ndkD69k16Pu2v+PYMqqupVWIM8fwHg6ZGqjKHwAizJXxi4Sf0iOUUJ2fO/HeqmDh573scbLn97nJBOH1quKTDLxvyUXF3x2DpCy4SemmGdkZ5ptOfIPEanJ++jcAgNFkRvWyxTx+HyWTUwAQr9I3wVSI7Y0KiimkFSUmokaWxjWzOjO5NrXEv4ORhoFOr61YKkDynDfLT6+ztF+MCxsrUfnYh8W/1EfxCt9D1rt9uzN+N72Lu7njJVcUJqPIBIWcH7tSZViOoTmD8pyHFKfNNdVfVMhWG1VJq9VqceXKFa/auj9LFNHbZ5a1pgxFlWe1qYPTNP+aWqmWpWnW72iTPVv14I2WqAvXRTqxuaZ3cdMFG3AW0p3RcuNbGPJmDdV5uov8HlAWVrgRIN/JnoiqWatxlpVvYN21X4eZBShKvrNxNdrjafMrefIBBIBsuGeFiaJp0BIDpmxWg5Wmzk4ycDzkbBB4zVwJn+SMViqiU1KzDGDzoX9RMrj9um111RMiRhcGTmp5wJbEQ06EVXdRUKIk2lBQD17L/hNfGL53S7ZPIK2op7KWVRitVvr9erP8ivpoMemdVyW/fzkoCmiUtQjts2d4QDI7b2QtQFrpevA1pjhPDEsgrLnGnm67f4ipttvyEkJrfVRfI2aSJ1eH8toq9sye4L7JOREyZVZfJXmWV5gAoG/fvli6dKknZHmuoQBFCtMSU1enaVzZvyIepRDDBsIHOaquk+p8RhjEQr1TMLqoYEgNcI6a66FnQ+crc2r5xfCponT5Gfo6P5hpeN9jeVfP+htvZC3ABbaGzcRRbsbLXYNPM8Rn51gAxXy1+Lv/G3kMXpK3WqB2oHWPLQXAcVKCojSSs5Bm0NhiaukkZ8eP2ZlikQE9LpjzPmFRws+iNNZ/sXi+bFWgxH+gy6uBqhUmMTMbd9MpezraZ890e77uUtzdhgK/QgMY3GXLIFhFqHCpSb5MgXn1WmM73GdL4oDpNZt5GCXTRydA3JzK09w2VwAAfNK0skurECwLJKAYIlnPmsI+QnGABXwMSYqvmWN0X3/0j+nNPEVIlKNeZfWuEj++7bgxs1R7K6ybrsCCUryyLscRU318nDPG4bhLK6wFIGiYGlQ/YU5ODhYtWoRGjRrhyy+/xPDhw3n/CMrhVl2KosAqUJiEvjRi/J2HqHEa2P3QNpmcRyDkLudzTZykPkxXZ+GkPkYzaFVmgUq5zNk0tVHWIhTRiw/i8mOFaYGxB/7f3nmHR1V0f/x7t6T3hDSSkBAgBBIIEHovoYRqAQREuqIiRURRVFBUsP/EXhD05VV8FQv64iuI0lQEkY4i0puA0ku23fn9sdnduXXv3exmQzKf5+Ehe8vMuXPnzsyZOXPOvdbKiTX2isN/M3o0HAgcMEpMKL/gvQ3ifWOBfZD7bwIFcwaOw7ZHS9Cxfi2fB+kcV/GZv9RYz+ykN7M5APiZz0fDskXobX0ab9j7e04YlL3knUMUriIMN1rm6JLNW3vDy5TsHdZpmtK2E0/ayyd1wOTu9fH4wIIKm2nMsN3u1XQ5Gle9psMTbZvoafRs5PbGi7abMN4qdMKwj6+NS4gISLtjgRmrHPL7ewLJm3aFSUANK0y+DAA5QBAD0YV49v0h+wS0s7yC8bYZ2EOynfmpDPBmaDDp8yd9LU+iQdl76Gl9xn3MFy+ZpNKm/ZxtBUeCM83IB8gT8du3FaNzwzTd98VESxVspfpchhD8mdhZdx7CtP0zXvkbsfiBL8RKUVtBjx01E0RnS76gu/R27dqF5s2bIyYmBn/88Qe2bt3q/rdt27YAiFiNEWpMmjoIb6x2NBPMzG/l62Gu7Vb8264tsF10iKdKaIkTQDsyukDFgVH6MOlBklY4KCtMNpgUZwz9xT+Ixbr7hZvfHyptiJgwfYPsX/gGeMPeH5eJZ4CsZVP5s/Zb8ClfNdznKw1E9/B18IzoWUZb73f/rWbjfav1QZzwIY6FGhcoE8BODVIU66PbvFjnTNcyRwecJVH4P/tNFbYtb52j79kJgDI4zR/oFQ2OM4JTMMkZb3WaLal2mNR3dImEK8Y3o1cFeRgknfwlhKvK74KePMlMiMC9JQ2QEBlSYYXpY0cXr9fEcloUJhJUhWkfqY1veeGgxCWNP/bL/McuHICtuq9E9x5WMQVl+r09XiLyTgfUVnNcuOrzBR2u+TlOWn5b+XqCflOpnUuMkje9utM6BUdJxRwQ6XfoxMEKs+Cb/ppvpTvfytRfeEJg4PSbDerhD742hlgekRwPxB6ztNgwlDRKQUSI57unzc9VkYlhqSRjuAlITa74fll/KIwpOAtAqtx1Mu7Un1h1N8n7/vvvFf999913gZCxRsBx3pdLFWfiKMRt30USgYWOUvylcQNlfIS+CkyvMMVzl91/K32Yvn6uaitMgdCXxBtOxVnc3ikX2x7tqSvNyyQc8+3DsIvkuI+95hig+f4nbCN05RcIVvCtZY9zIHjNMQgWaiPrGr7I/beaScEGvhDP+dkbGV3/ctJTcVFmQCX43nQ23C/YBqOF5Q0cI7UqrDDRe0K1zZgL47e5jxpNsgP8mbbx7hnyi/AMTsVxPRyc5x29Yh+EJY4SvDaiuSQ9elWQgJN862pK2UY+3/23knmuL+aRax1NAABDZQZK3RTM14a3zsKHdmUvgJnxEboHd3oG7t5Qc8LhD9OaVxyDBL+zkjQO9FS4DP0e1xTrCzUbp+RMw1X3PnBomxAEnCZ59DdbankKN1gfUx1MhpgMeKi0IRrVlu9H/TEYP8DrW6WQa3VetN9cYTkCwYVypZgQgCOBVZh6Wp/FJpIvOU7AqTrF2OnDVgaXsmk2GtC+7CX0tDyNq9C2l0du3KLkMdVAeBDi3DPqK3JttcUHz5guj31+MT8OUOiAQOGztH/++Se++eYbXLt2DQBAgrTMej0j/l4Ip25D/qmjI/JSlL30AFITGlfHqtbB/shRtrRUY6ZltlRJWRHn59oYb+LsXtOUw67g8rVZVpzfnZDMtI3HCSRhnHW625ObXBYGA6e4ybZMpuFzdapGaulai4mlix/5xpqv9Se0edtCex/Za1wDEKUZ+atQ3xTrb52XhwGzbaOw2N4TjoxWuCybvydXgw8Nt+vdVVR2OmcrNcutVNb0t0V/Fxxn8LoicoCk40XbTXjYNgabRV6NHAZPnf2TOPdFFKQLN8KLV0R5wuEawgT7JtXM4aZY7/bkp9S++KAwPWcfgryyxfhZZqB0oPxZxDx1QyHm2EcpBvusFR2qeYVppm089vG1MTd8hmaZv3K0UT0vp4i79ob6Y6bY4cNqP81Xjja4yzpZ8fzPfENN6ShOrlErTGcV9ge57rXo3MxOl61zMoETKD28qMHv0qAWbu+Uq1g307l/0KmB99U5JbfRgH4lWO56qw/70AI9cutieR7tLQsAOFeYKsskr3XZKwKHPA4ot4+jrffja4f8ZKAaXRs6V30MHHActfAHydS9D5zGqmCJwRHnuGmMVXv7IoaAk+wLvqzRGoAmHBYAvnkGHG+djktEf55VBd0t5j///IPu3bujQYMGKC0txcmTJwEA48ePx/TpVSfo3XUHx+FstDTWkGvmFHB+8I1rq28sFTcHxP2/cmN8nEv1XE81Zl862mI7tZdHDqVUxXI8a3cOtEwyCoaVGL162rqkMHN5W9s6ft/DtNTRDQCwmm/h9uRGr6T9HOaZYdeTtUdhEpbBJOs9sBATno59FO/ZPfvPLMSECVQEcV8aN39wnniUdKVZJdeGcbECOd92CxyEwyzbWNU8xF7sHlBxr6oFBwx4z9ELc+yjYTDIr96SCihMAqXFj6YedCekFHuMHm/QSgdnMGIzpEq1+NlfctyEJY4SyTdqN4TiJstszLaNwmreubJEjxtfst+AV0WrEq4B6wRqr43abPspJOAJ2wg8ZBunMkMp/1W9aLtJMV0eBt2DZsA50F7HN1E8X5ylzcX5V442KLE+i4OGbM15T7JNRpOyt9Hf8oTsefHg7hIJx+7y1Wl/rDBpWRW5qGAuBzjlX8G3UZylPkfUJ/dcbCdKXiY5vGcvwSE+BUvs8t5h9ZbDdr5u+QqTelridB28613Il9kBkqapHxpkmYuisjc1yXpWq2mXH7kYgMHsIZLmXnl07ifVtsI0sbOzXlxQqYNqnEKCYE8eD052EsIpF6eorCjxxKACPNzXOUFDbwvQanEgpzcqKbyufvUvJApM+vUijrV2ygdTeFc5WX2IH7iDr4uXqQnY6w3dPf20adNgNptx5MgRRER4KvLQoUPxv//9z6/CVXeMVAPLgYPdJG0gn7R7zLAcMAoG7v91SO2Vlcwb1D7ht0zDPdfxnsbMghAMtD6hOlOotLhjAMFiu9NkbYr1LvzAFwIQrq64sMGE9XwT9LbMl92UHh5iwvS+UtMgwNno+HMP0xFeYZaQk//xp8LstZxESgrTV3xbNLIswi/hbTHbPhrNy95AdtkHyLO8j1W8x2zqCEnBfNstWh5DwL+owYYWRx5qKA1QXAqTUaT4vOEYgHzLYq8uxOlO5hSJw0cVDJhKy6m0AklLqrcK0R6x5Mz9tLDM0QEP28aAo0Za9CBZqayVlDViMOC/0B9SwMXvcZ2wheSVux935sFxwHDrQ1jm6IDFdqlb8hPl+y7oVQJvG4vfcfTFB47uKisL8q3VfoVvDZAO/vXMYaut1oSHaRucuJ5Zr+J9EZE4q1GxoJ/RAQPWOwp05SVNz6OwjrPKT3YOtz7k/ltpJU7Ju57WiYSf+MayXrfAGTDbPgZdrC/gHKR94x6+DvRMWY2xzsAt1ofLHbVIa0hemrJybHcpTAorTDv4upokOY5aOA/59y3+3v/tJYSIP5RmQDhJ2sGyAKWWpxSv1RrIWdHtPVFWmMSBg11tspIZnZz52pO24YLfVyjLAl5kkkeb4/LgkMJp994HALe2qYPIcmdQBoP29k+JbXwuBveWf+cG4hk3VWR1OSs5TvD7MNG3L+oMicF95avcixy9dedPKjXql//R/WZXrlyJp59+GhkZQlfO9evXx+HDh/0mWE3AbPA0VBzHgeOEG3E7Wl4UfBwO0X4duQ9TaaCgZvp11UB3RtLGiV7lEKM0GDWCxxz7aOSVLXbveXjqhkJ8ZOwvmbV0zar/TrLwK5E6mogIMSIq3IzNfANJQ0yIf8y5HreNxGzbKHfkbjGCcqd+6LGddw1Q5LzJeJRhTtH8BHAqIHrYzDcQDMIXiOJa3Gmdonr/BRKBlTy910XBi4/KHiWlWbPXhhXJHqfrdUfLi9jMN9C0f4+GHlxqmfnV04y3LHvVvZoxtDjT55W/6ba7sMRRIqhbESjDr3w92IgRP/DyA2KhwuQZZBgMRhDOgKZlb4muBwq8rEzfZn0AuxOlHaCB4/AjX4DptrtwjqqXo6wP4CtHazxlHy6RSWuHrtQm0YMDF/v42vgvtX+OXnnXk6e8HMr32g3a9iO41x98WO5WHmAR0XV02hxG2mSUDB3QCs0ZmQHuMZIkKJth1ocx0ToVH9s7CYJOX1Go/3o8orom1Gg8JnmcpA251fogBlrnak7/AonA93wzXEOY20hdTPt69GSZwgqTQn/nD+dD9PudYr0Lr9sHYKJ1quL1gTBsu4hI7CHZ7tAFYl51DMIXjnaK979tL8Wt1gfxuO022fMRIUacjJMPSH5Y5DTDVRpKCpPcitARURpChcmAzobt7t8P2se7/ybgyhVw36A/e62KrHiFaZD1cWQkyE++cRom0rzmB6AoW6gguSYmxat4BWXvoLDsHYy13oc51LvsbXnaHUvzd5KFtmUvC+6zKmydoGWPKN8DdT2iW2G6cuWKYGXJxd9//43QUB8CV9VgzHTpcxw4cIJN2UdJimggInxd8puCOfRuTJnYlV+lZnbSOD0G9ZKjMLAoXbCHycVFRCnanSp9uq4lZNpMZnjrLNgiU9Dc8obgWq22sIOts9HBskDwAQPaIsJ74wrC8J6jF05BfomazoEe6CnHCpJ2Z65BvGJwQR8fQ2k2b7ZtFMZb7xOs6ok7lM0yq4euwehDtnFoYXlDoOCKn+oV+0A4CIen7cNUZUynXGff2SUX/xrXCnERnkEQ3SG4Bg5j2mfjKEnBYOsczLPrc3ghWGFSMsWg6o2ece4ZyjV6z8YpgpR98RJ26oLF/fdj9ttwk3UOCiwLcRHynSedn11kkkcIwQXRbDwBh+zESGQnitttz0Ov45vKDvaVPq21fFNMsk3BVWOsOw8XtLJ6gE9V7ESVlByrWTrT/7L9BsF3945DGE9F76Z7+rtVG4BYTZ534Fr9vkJCFTdf+zJoVpJdXGel11Ws3RNMKpTnRZdFV8sLgusvIhL/41thhn2iYMXY5V74vGiltaKmqvTKq1VkSnSGxMIGE965TX7wLUZgfqtgkkfvmRK3FjaHs80mCm6QrTDr6oeGWWdhraMJRlkfAOCMrUbL+AXfAVcRhl945ZV5f60wZSdGollWHNrW9ShJas4j1CYn9pJMbOALZZWZW9tkoVVOAk7HNZW9VzyR6Fq9OUjknWHI7bEWvze63vAwiGJl0SaYwG+kIgqT/ITRMkdHPGUb5jXUgdOpCadah1zP5qsnzs/u6gDe4BmP7eNrYw1fhOHWh9DT8ozg2suIwCVE4Du+uWSVjuasaLV0jn20qgwXEAmHF6WqKqO7RevUqRPef/9992+O48DzPJ599ll07VoxM5qahkRhkvlWhBu8DV6bSAIO8ZEhgt8AsJtko5dlvmT2GQBW7jmFVdM64aVbmgG8Nvtij9jUaou9m/vvcAU9wsBJNx5e9RIhOtp6xmUgBBtMWOLogS8c7fCgbRxCzf6Jw+QtQjr9nBa79zKSc3Lgamzk9nH5wg4+B5Otd6OfggnF5472uIAomFQ8fcl1fhNs09HHMg8fOLrBDpNix2wnBjxnH4p8y2LsLvfCpgS9IbpT/VroWF9o+ihUSJ2/Hunre2R2MzzORZRMcIR7mHyctSPCdC4jAssdbXWlcfaKZ5PwD3whiJf9OHR+ydx5999qbpidK9jqzyg32PemAEwtqY+nbypUNMm7jHAs59vL3qtUr2ymSAywCFcPxPX0IonAbeWDTddvLWm7OBri2TcjN1PvGpQcjm2NTXwelti741fSAAMsc9HR8hJKrU+hcZkngLvrfWlVmHjBYE3BNFH0W6uDmF81BhKmV4Bc7d8BanBqgwnXNHj8mmcfjqdswyQrPt7k3ctnCGIXSUy/qfosnlRzlVmPRim4u6vSHigPdIwljpNfteAFCpNQdtcKk9JqoA1GcJxzz6YWs+ef+MYYZZuJtXxTtC17Gd0sz8vWQ7VVJK2eb71hMHD49M52WDy2pSdflcG90h6dzxzt8amjo+I1TwwqLPcGLF+GoZxN8Ht0u2wUZcbhTtsU2WeVk6IWd0F0jSev/kUZisG7eRhwTaXNpffpbeYboHXZK4LzdPdB15HptjvxlqM/PnZ0QUPLYsX0XfWZ44B/vJjo+mryZzBw4ClX5m85nFYbP/IFihPFSnK6oBVjiyECHzi6o13ZAsl9+WXvonHZQthgwmJHT2xwNMb9FdynHAx0l/yzzz6LN998E3369IHVasX999+PgoICrFu3Dk8//XQgZKy20AqTw+z8SMTNlNgkb0z7HOqs/CDQqjCg30uyJLPPLtyDKZ0uP2l5DxLPytbzN8ubE8kNKMTKhXhTY4RdaFtshwlTbJPwoaM7ejVOhYHjFN3OasXb3XSDeL7Me4C2Mdb7BTPrZ0kUni+PWr6Gd86wiT0m6X0CO4xYzrfHGcTJnucVVrRKLU9hL5+BkdaZsrPbVpjLZ9ukxity5mC0ucw+lcCr93Srh76Fae64Q3TsCoHc5e/SVyUGEM5Wcpy89z66M62Y0i28ebLtHuzgcxSulfJ7eFP8yadjhcyeRDnoJ2nK7ff8MBgUlSK5o5KBusxF3oqFc6/fURMKEK4cKjnFUpqk4AnBDpEjANeA+WHbGLxp74vtJBc7qTL+B9qcM1CCqeJSJrYcu4Qh1tl42D4OALCD5OIsYkBgwBWEo0XZ6ygqe5Paw6StIo00zHf/rTRj7yqfB2wTcJGEu81n5w4qwKP9lCcTNvLaJhrkvv2ljq54yX4jBlseBeD0MPimva/q3skyhOItR38cptp/wHt8n17WZwQxs8RmgRy1H8zOCQezdH27r6fyKsyd1ik4ytfC7ZRZOccpuJdWWWFyuB5GcVKCg4Fzmky79nho5SQSYUGIrOKstppzUaEvp5lrG4EDfKrX67hyCxctyLWl91gnYZrtbk2D+XV//iN7nPYu96JxDCJDTVh6exscJqm4U8Y0Uc5kea3IkobeL9WqTizio4WroKscLbCfT8MvfJ5qSIBQyrvvz3y+RMHgFFaYaNQ8GNLvfld5u2YnBrxh7wcA+Dbtdvf35OsKE5dUHzz1HamZ0SvJJq6jdB96zeQcz5xAEjpYXsI6h8fM9hrC3Ka7FxGFW22z8J8K7lMOBroVpkaNGmHHjh1o1aoVSkpKcOXKFdx4443YunUrcnO9z/QwPBg4Z3TwHxyNsb/hRNnBjtgkLzPBYxr3j4yLUgIOZXbabbVOFBQmpXRokbdSM5shoUrBCKXHfi+3iXVxs3UO9muMSWE2Ovd13WR9TPGa1+zCfT9P2EZghu12QTBf8YxYvybC/Dl4bxBdWIgJ20g9weZeZ8wep/3wc/YhmGkbL1kZ0mvN483lsWtAJDZ12EOy0cv6DNbzTSQN4NyBUi9rdCdIXy9ndqG0ARwApvfMw6sjmrsHlY3SotEuxVnf6PLfK6oPvkCbIRo4TrasHBwtv7ActLpEBuS/DW8bto9SzkV4Qwh6WJ/FXbapGnP0yErPnNPPeJj32KoTOFevb2srNDkRyy27OuKlTrr0A16hXhhAFAdRkZC3ZZcbaFvK01ziKCk3z+RwDjEYZ52OYdZZFYpgLzdQdX073laT/0Gs4Ds3ahDjI3sX7DV4+kq67Oh2z8Q56/BHjq5oannbbQZ3S8tM1EtWHiwrtU95ZYsxzDoL+/jamGO7TbDC5FIgHDDiRfvN2Ew89X+efYTuvZOAL26yhZgc19x/2w3K7QrHcagjMTd18jXfGh2tL0kUcFllnTK3o7+F2HAznhzkHPwRSmGiB4SAsI9QdB6kE7oMN/MN3I4+tDpf2MnX1ewan/785eKPuVbO5VaPvuSV9zWJ2XPiguxx2oHSR8b+ApnklI1ZtnGSY9fKrVVSY5yTrmHUqpWp7KzETHSC7V70sD4LG0w4j2i8bu+Pr7y4F5f7vuj6omriS02iGg30PeX/E+A+20QssvdCH+t8zLcPQ2fLC1iTPNJ9rS8xvxqXLQQXEgFi9LTNZRq9itKrjQQc5t1YiE2z5PZue647RmrhpyCFQQkkPvUyqampeOyxx/DVV19hxYoVeOKJJ5CWpi/oGsNZvT52dMEI2yzwoc4Z0u/Lg326zNToxs4OIwwchzus07DS0QIvlK9Y0JwgSRjY1NPw6LZz1hkjwcBx6GR5EaOsD+BXNMR82y14314CPkV+hUlOmsdEe5J+J1nobn1eswwcx2EbqScw0aF5zy4MMPuOoy8+dnTBLLunwRV3ArXjPIrp2PY54DjPIPpDyvRQDm+rGRaEYKmjm+ZlcCXkPA7SeN0zBWnjO7JttuQaovC3nM23nsac4zjcnCNVmHzxvqOaD+Q9M9kphUm8MPCobbTm9OUG6x85uqCfgrvo7pZn0dPqWY03chxcX8bgFhmy99A0yYzHkOIMfHtvJxjM1GqsKdzt8arE+qz7sKPclHeUzLulkVsc8WZiRonuJiXOo0AYQBSHa7+Wu00/LfoO5JogpX2Oq/kWsh2zmuMUJ5zC305cZsMhWjQgCi0meeLHo+sP7RX1KrXS7mo/7uqSC7NRfQicw50U/L7RMgfty16CBSH4iW+MEuuzWOzoLbuHyZ/o7XvE31Gt0z+5/3ZITPIqhtwKE60McRywenpnbJrVHVsfKUGjdFd98lwz2z4aS+zdZT0MDrfNcv+t3Q20+oTpLNs4TLBNxxDLI3jdMQBfTuqA0e2ysXCU8j4uorR/00vurlg7NDNsdwAA/iY6V3PFMsmIM9l6N36SWRl1fU9lMgqT3B5P1+qL3ESOgdhlHJEITQSftg/DJNsURacXgLypKd1MqO1Vcu0lP0kSBKvRdJpnEIfH7KOwj2QA4HCYpAr3iOqMn2YhJlxBuHP7DOXERuvecbGFSVJUKJKjpXWaiNq+igZ0r4r4pDCdP38eK1euxJIlS/D+++8L/jG0I5zRcbr33MAX4kbLHHSwvOS8RrAZ3rma8g3fErfbpkvM65Y5OuCD0CHo2Vh9CX6kdSbWOwrwrG0I+lqeFJwjVEeSlaAt/sERkoK1fFOEmY14wzEAj9rHwKww0BAPKC6SCEU3qy7shlDV/ReudkepIT+FBEHwVTnEHzf969H+zoZ8uHUW2pS9jF+I+uqDKy29zYWSSUSLOvGYf6PUi5S3vVCuAYjadVq8i4mX5PtZnsAyR0dBEFK5a7XAif4HnDbVFaVxmmfArLTCxEM4o/yjw/mep1nvxF6iPaK6/HvmsIvIxzDbT2rjGmWGSnecWgbcMeFmPHNzU9RLjsbfEZ48uIg4999WmPGevQR7+Qys4FuD4zgYDBxu76QcV02u/mkzyRPWseeHt8Z3jiIAwLuO3op1bLptIl6zD8DtJqFiyZePqFY7mnmeR0fMjwkdczDGej+283UFbrEFclMiyb0/lzIRYgqEwiS8hlYU/iCZGGmdidft/dHz5vFYMVnoJt5tOa0ysXVZtJ/rV9IAxyFd8aDfi5Ir94ogTrGo7E2cLje7G00F4GyYGi2RB3AOcF3YDcomeYB+c2b5SSS6nTMit1YUkqPDhANbahXKQsx42D4Oq3mn04veBZ5+9xhJRlHZmygqe1PzJJL8HiahqWsZQrGJ5IOHAY3SYzBnQGN0z0+RudOTpvYVJk9eUTKrv659ei/ab8b/HC0l55XklpNJzHK+vaycru9JzXKBxqUwyY0XOOLAT8aWsBKjVwuC/bxyCAM5+YUmecrv+z7bRLxouwmDrY+WT5QppynO07Wq7KtJHiAMTq69Xmq1rhGfq34Kk+5QvV9++SVGjBiBK1euIDo6WlBROI7DbbfJu5NkSBHMcVLlSLvWpgfyDhgUO+RNfB6m2+7C0wOEA+vfZQZ+6/kmWK/gNc9AdcR1a0XiyNmr6s9AiRNqMuCq1bnqYdKqMCkEpKX5LblU9byr7NQaqj94dTMvb50KxznNVf6C8syT+9rytHyJhC3Hsjud5g4zP90pOO5thcnjZMKueI0WBUesMO0idTHddqfstSdJAoqwX/acHBV12FFqeQorQqWD4lpR1D4aTn62i97kbeA4jLA9hFCbDWUaNrrTVNRbFd1xagrjQ13/ZeRN+Of8BXzraIGPRHLMto/x3CL6H5DK7fMKE4CrdJmFROIO273IsZ/EHyQDRSb5+nAG8XjGfgtqccLydr2p8bbpOGi8FQBwREe8kJl98pG7/iAGWuVX+Mol9+QnMyPsKB8Y619h0nV5uSSewbudGLCeONvnVbUTUT9FIWaPSnPl0FwfqXpXLkN6bBhOXPCP219x/TqPaPSwPIO63F/YJhOsVlIfaYWJUx8w6/WUKrvCRP1tN4TIGiwRhT1M744uRkqMcNbd20SgGPkwId4nCiXpEA4GzuP10Bdl+AtHO9xv/sj9+yQV4PQiIjHRNg2HjMPlbvWKWNn/u3xrgTAGnfNv1zNaFPbb3GOdhKHG79HBuBuAR5mQm+gw8DZcRCQKLQt1B6kVyu/NJE+Z84jGSw5nAG6hSZ56/SWEYHL3enhj7X78QTKQi5Oq139s74TBpnWS4zylMIkVr5HWmXjB/BoeoByxiGVTV4QrNolxPaB7hWn69OkYO3YsLl26hPPnz+PcuXPuf2fPng2EjNUWiT4u86UZRAqTclrCm/tbnsAC+yBcbTUFU7rXF5iYqcuktBohrf4/OBoLOqows+cDNBnlPxdxvyZ2FysH8TKjIrf8LuYbviU28w3whr2/4PgH9q44QRLc3n3ceYpehp44Pa7grVdEphgj29RB5wbKtu169zDJxXOicdWXWO6K4jVa9n7QDeFNzeWdOozvkIPODWrhUdtofO9oiomOB5BbS1tA1zs75WhavreI6sp6RwH2UN756Ng8dFlyHId/ZFYfaTMIjnP+1qssJUWHalKYXLbr063SDeFqStLN5ZvvhXjys3FheNZ+C7aS+qqDdfeqs2BlRdTB0TPMoSbc3ztPtk4uGi2dXb6KMAy2PIobLXNgMIfDBlN5vA4OP/P5yoJBpt0jrv8M6GOZhyGWRzSbr3asnyQYiCjB8/TgTHo9rzJTrYb2FSbKxIZq32jFU35LGVeehtr3ok3mVGqA7w+TvNpx4RjdLtv9+yhJlsTsuYgobCP1BDK6ylj8Hq7E1Hf/LdxvWHHUPIcCwpl4AQofa3pcuF5rdglyt9N9WpPacYJzSnWTHifomcyhrzyOWigsewe3W6dhD18Ho633K94ndicPeAJay8GLHtQ1sSi36ud6xjMipy7P2ZzbEb7k2wlCWriUgBuaSfupy3X7ggDlDjb0DX1phVFunGHUuMIkuEdWYZKvRDwPRIS4HN+MxVJ7FwyyPK6Y9gy7guMR6jviRaZ96/kmaGl5Hd/xzQXHxSb5V63yE7BShan6rTDpVpiOHz+OyZMny8ZiYuhDMKiDfCdINyJqK0yedJznd5K6eME+BJkpSZhW0gAx4dqWtOlBuLcOYKZ9vOAToRUms0LHIm7kNa1waHSHrJaWDSYMts7BfFG8oIfsE9DesgCXRCtd4mdXE0HJZlnskjcvNRrvjRV6QhvXIUc5YQW28c7ZWSUXqf+Q6HKTA6dcLttwsVc+QN1zjwu6XCNC5QcuMeFmvDe2Fc4gHmNsD2B7RGv8lzInUlKgAeDekvpolOrd41N363N42OZZNRHPEn/Ft6GEFr7AWbax2MjnYzy130C8Z0EPb9zaArNK81GUGYcyDeZiHzi6o0nZ21jGS10OC2YnRfVO3vyTHmxSRxUe4uG++ejVWNlsR06OLya1x11d6smm2bWhcLXHdc1m0hC/kgaSslzOt8Xd1snoaHlRIWfhQ/NUIfxG6mATUVe4aIrraFOsHFSWcs3cXlOeylllaPOt10WTM578OHdcH8AZ+PUR22g8ahsl8nwmY1ZUfkitbdY6SJ7d37NnxB9DG0IIbm2ThTus0/CmvS8WOvrgaw2eH13SitvRYw0oaxWRAlPRVd1zRNjeTGzoEMR9Envl8yCfr1q/XBFJ9T5ny+x4yYB+g0ObibP4ES4hAiv5lii1zlM1UZYbGO8m2Zhhux3DrLMk58STka7gvEoBal25dLc8i7MkCqsczfGKY5D7jFE0Rlo8piXGd8yRyMZHJGpWal8uD/D+K18Pc223CgLayylEjdM9favWd0YrTK53ptSG023iP4jFTPvt5RMPyiwrHx+8Sm1HoOv4USI3eSvNX+x47FKZvMJkE72+6qgw6Z626dWrF3755RfUratsC8/QhpbPip75u6VVtuLAjpP8oT8vAIgml2WPy85+EaECF0otgyvN8roOnyGxqMVdwPd8ETo3qIW1f5xRlIlw6vGnXPmKO4pVjhbYqMHbmZbZJrUOsbXlVeQaTmBpiNAEaL59GJaGPIHF5U4n5JJ4sE9DLNxwUPG8HCOtD6KFYS828NJ9TQBQapmH05Sr8Vftg3CCJGGNo6m2DEQIXNsr9GnijsjAccIVR022ZuocI8lY4ijBE+ZFAACjaJZYraM6jlq4xfqI4vV6A47S+xX+7eiBAcafJN4YxSgFoqW/FYd4+lUOgRk0dRjy32mrnAR3R0yvlEaEGAU30Eqtqzy8FYu22E0c/ksrsyLEdUdLESgRKxMAbtmd7YBFIokUvFqVWJ7Bzca1WJ9wKzrKyOYNg+h9yEEAXLMJV4f/5egpuU7NaaGrjJ60Dccs8weYY7sNc8zvu9PXAsc5V9gbGI5rdkWuBoHzO/+Gb4lvePU9LmI5nPeLJtPMHquICyG14LjKuVfvxdfO6JWH9f8pQEfjLk15jrI+gKfMC/GkfQR+eqAzNq1bjQtUmnsTu0O5xpbLTZW0P2IBenMrriXgxzujWoLMF9btufaR2EcyMMv0b7epnhy+BoCXcxABQOAynoaW4G7rZGwvH/h7W+XcT2qjjeVVySSfcGWKQ5e8ZNk9fgbO28qsh82kIZqUvVXeZosneaXER4Zg86weCA8x4sSTM2SukEK3+5fLXW4r9UO+NIn32+7Au/ZS7KGUXQ5AP8sTiOWu4ASUVwGFCGWyKQ0CJE4fqh+aFKbly5e7/+7bty9mzJiBPXv2oLCwEGazsPIOGKDf/WhNha5QHCffOdMN5sP9CxQ/KG+BV9UYWOTZ4LiXy0Ez8rum+1xOKFzQAy4lhcn1jDdYH0cPwxZ85OiCdl56G28KjVJDP8Em9V6klQaivQNqEp5BHM7wcYJj7XIT8eP+RigseweXVBpDeq+XN7O/jvWTsH7f37iECKzhmylex4FAziufr9AdeaP0WABS01tvHZFZZYXJlYJexHX+TyoGlJbZLWEcJql8gyyPo8Bw0K2gKbGb5KCJ5R1VUww1ZU5gziEj9iY+D60Me6kj8mkpjXfoZ6M/tYTIUICaHwkR1EXpvUp5iq9Qu2dgUTq+2HZCNU2tgxqaOf0bYfPhcxjWWjgTnpMUiYx4qTmyS8QmGbEgJz3y7iMZmGcfgWJznG4ZAOezXyLhiOauYSOfj0LHAbQv31/hgoBDYmQITlZgr5BrQPi2ox8+cXTCOcRQCpP2ocpDdv8Gj/RlzO2654ooHh8xeIYnDnMMOltfxIbQqQCk+0N7NkpBO9udmE4+xlDTGq957iC56Gd9CpEhRiRFOS0BrCbPqtMPGRNkFSbe6JHxb8pMzFdlg8ZbrddiFh4bbsZVkUneFYRjoaMUo43fIJNTnpj0FS17dWlTTRDINmG/aXC0I2cRcVomDqH8++AUJ0A+ntgWi384hP/u9OwNUopzpTQeqRXtrEeaTfI4DmOt9+FB04eYarvLeUzhVt4He08HjJKA8hwHpzMiHcmJveS5FCajgRNN8IkVphq6wjRo0CDJsccfl9pPchwHh8N7UE+GE/E3LVe9/iAZWOtogtMkDgM5702mZG6Xk8+LpkM9z0zDq9wwnLRG4Cu+DWgHx0qzX/TRXccvKuYxtYfTHt314R8jtbC43H20t2CPShttA0W73ETc1CID565a0ao8yKru/UXlLR9t6lfRWcjmWfFYv+9vr9f9VUF35WJeGd4c+NT5d0H9XMgqTF5MGJWcgFQElynGQMvjqMOdFpgoJEeHIsRoQEqs8p4k2tRT7v1uI/WwzVHPq8IEeO8k1ToPTkGhWTiqGOPe+wVDrY9gd+g4RHAWibD0F6g0aKMVmHEdcvDpr8cxsCgdZM964XUy3vrEKTbLihM9FyQxcNQWE8UTEYC03fNlL8jNxZkYLQjq7UpLXX34YEIbvPb4e5LjrgkfvaI0z4pHt/3Po7HhENbyTZDFnZJVmBI0KExyctcuV/5ouc6JXKhrVZj8McjPiA/HsXPOeEmE6Nvr6cJV1752tMIY0zfu44TabxFqNmAfScZb9r6IwlUcE5kTcRyH04jHA/bbNSlMchDOiLyyxQCAsQZ5kzzCGVFY9g4M4N1e4+hnUEhZW/5yJpg+DDrpSVbx/hN/MtI6E3NNiyROAsTseqwXoihTbuEQ2/NrmaMjIlGGX/g8aAwRBMBpeXCHdSrOEWHbsua+LvjwjfVw+TxSmpQGgMLasZqDTnvzLKv1+8tLjcZ3fHN8Z/XsGeJEfZJLXtf/79xWjPHv/yJJ61e+Hpob/vSap15LCkBsksfBVm7PbOQ4OOi3KRqnyTkbeaRfI8z9ao9uGaoKmkYxPM9r+seUJX2Iq67cx0xgwCjbTMywT4SBUx64u9xgijtB1y+174TO9woXgZccN2E/kd/cT8NDZnpZlK+LphlxznsUlsrVIKKVLC28Yh+o7waKN0a2gNHA4Y7OuWiWFQ9AWK7zZFx8i5Gf3/I+W6+GWof3H3tnACgPbOjnxXDOgAGWuRhieQRcpLwyJpZN/CxmLy+Z82GU7Fph2k7qYbkocKLZaMCOOT3x/fQuivdfM3hM5LQqszbiu0tXJQRmXNTfbeo6PTISGHBNMIJQV/Qk6VOtfGJUKH56sBseLJXuC6JXAcPMBkn6zw1uik8mCsuZ4zgUZycI9kip1XM5ecXmM0ous9Xeker7UzkXFWpCYpR0dOZSmLTO7K6e3hn/N7QIfQpTcQZxWMMXgcCAzxwdcYrE4ROHZ+8agbPNfXxgYzRKU/akJqfQ3NzC6e1TfQ+TNiraSuyY0xOrp3cWpkklOqxVlsI+CXk5NpGGuKN8Pwsg9GIZXm7e+5R9hOyqmK/PIhigwrkab1EZrRMQXEKEJKSHUWMHlVsrEvER8nseXy/vs1x1pX/TdMFEjN2g3/GFVg9nvrCeb4Iu1hfxs5c9hlGifa9K3zeBAe85emE3ydakeDenJm++4VtJ9jpmJ0UKnF1xKnkDgDcjCFcw8FXlbuSV0BKqA5D35EfXI4Hb8XK5ezSS34tqISGa+qaKKkwEHKzlwbzFE2Pi+rWZz4OYcR1yJJNu1xOVO3XPECCuuwmR6pvHDRwn6UQHWR7HEnt3PGF3ut/1pUmkTWDoBqV5ubKgfJ9BsWETP5vrt5zJkdHAyZrwubzvHEzspGmFgraBFnvD00pSVAhiwtTfQ7jZe8Mku//Ay8tJjZEGgxta7HGHrtbYP2ofjTutU3CXbapX2XxhB8nFJpKv+L7FAwbxdXER6lOG4pnU8RqcYZyVcWJBpxdmNsrWm3usk/AHXxv/Tp3puV5jR1JqnafpOjFyQX5dGGVWdsR/053RX3VU6rZMFRF3kp5nFR4PNxsxrUcD3NUlF8nldZG+NyHSLPlOXadvaeUxp1FTXka0roM6iRGCeFCSFSaFe18Z3lzhjBclTeacjfL6IOe0xb3CpFH7yK0VhUHNakvK+hIi0NbyCu6zebxWkfLaflvbbHxxV1sMy9U20Xhj89pU+SsL5ssKU3qs1uCqHmLCzAg1edpCsSllqMmA3SQH91onYojlEfHttCCuP/ADFYPNbPIMtGO9OC3yw2JZhbDYld+hK67cGRKLRaNb4ZeHS2Sv202y0ajsXdxXHiA2NtwEC0Lwhr0f3rOX4KzRu/IJCN8/rbBqHcgHGrqW6Al0Loaue0rQzT/HcYr7Iw0c53WFqaf1GbQqexUHiHKMJqBi5UzXY7ot8bav08g5NE2UaPEgKoZOlwcHO19ukqc0yCvnB74Qo633u2OKutO7ji31fPLVuXr1arz44ov47bffwHEcGjZsiKlTp6JHjx7+lq9aQ1cvjnO6JhXTu3Eq/rf7L/c1YraRethmV/eW4g36Y6T/ntilLqLCTIpLqERBJkA6AC2oHVuevtwKE4ev7umAPi8JTYQ6WV5EJvc3esU2QwOve2CEe1p8De7mr49ZdoVJobAWjWmJj385igdL85EUHYqPfzmKeTc2gdEAtMv1mEuqyVaGUHzNt66g1N5Ret9iL3iu6+YOKsDavacxvLU3+3TPw93RuS4e7KM8azndOhE3G9fhEcpjnlp6Yr7k2+FLazv0D/V0fFpm3rbxdcujr2un1PIUWhl+x8eOzorXiM0w5P6mn+ZSorz7dADo2CAJK3b+JTim2EeKbjYZOUzpUV9wjHbkcu6KTZqEjIBqZRkbbsaa+7qA4zi8te6A81ax0weF0YFa/Vd7fXLnrlgpb6ByplDlN+ltDuTyEptrHhe5XI5W0AXESal5U6TxZSXBZXosOZ6dgE2HtIcLoZ/fNTj7VMYzJE2n+knYfvQ8AOAyItC27GVYYcLboSbMHdgYPAF2n7jgJV9tzyzYSwNxH+w9DSXFPC0uHAfPyIdveMA2ATv4HKwJ6YwViereha9CqrjOtzvjHXn3N+hEyVzzJElEDk5pTCVwEAK8Zy9BM8OfWM0rT4J4Q+51ids6I7UMoub0geO8rxJaEILTGmwFK7KSZ1DoC7ytdJvg0JSvVrNDGnqPGgEHe/lkkzQtadpr+CLd+VVldKv3r7zyCnr37o3o6GhMmTIFkydPRkxMDEpLS/HKK68EQsZqi7h6RYtWNmLDzWib6wmUKm7Q/29okTRNJQVG5WMqUVjmDTUZ3W6vleIqaBlozunfyL2xVu67Nxo45KfF4O3bivHlJI+r7IuIcm9alFu+lshCuxD1ceZKywBJS98s1/kqtVVd85Lx2ogWSIgMwQO9G2LzrB4oaZSCbg1TBJ7mxrTPdpejHjrW97y7Z26SD1hcUSQrD+X/j2xTB++Mail4Dq9peSngZXwnDLM9jONQiWmlOTcn/vByJcceko3Fjt6K9bG4TjyUap3w21JQqkRPOu8G6ftV+kbPGJO9XsdxHFpmx8Ns5NAlT6a83YoF7TFMvTAloQXEJnkK96kNGlQVJplj3kyVfK0Oau3saOv9eN9egvccvTTlJZnApf6OClOf61xR7s773/buitfQ6U3uXl/2mpY56lYGNIQo78dTY3L3+rijs2fF8SQS8Q9iwQEY2TYbo9pl+zQzLubNkS3wSD9t3gD1TpyJzc5oLiAKrzkG4SSnPfgyoNFjpg5m2ifgOEnE0xiteM3mWT2w4YGufs1XDAHBbPsYDLA+qRjWQovjF7lv/rURQgWM7ks4FacPBk7eysUXyvRswJKRw4XShJkcRvCaFCaTD8/o8uBXLhUalpsRh4rHZMFe5q0EdI8q582bhxdffBEffvghJk+ejMmTJ+ODDz7Aiy++iKeeeioQMlZbxAOf+slCu+jk6FBVMyw9Zl9qdZkehCvld5dtMtY6muBu62TPtV4sje/qkou2dRMxoo3HHElu0ONq1EoapaAwI1ZyHgBCjBrsc6lmxdcVpqwEffHF6EZjkvUeWIhZEOtHIJ/GBkVppjMxKhQ/P6Q8AJKjdlw4Dv3jmfmUW8X0Bv3KFFeYJKZa+hpPf3nUcZSbV11Ma68zfy3yOq+J9jJY1crq6Z3xwQShLy6ecvxnEHSY8vKJizlWZn+EUr37NaQlnrENxSjrAwCAesnyXqGW3t4Wvz5SgkQZZV02ZZ39planD2o1ROn9OVfBpecEG8RVZqr1DjDUqv0avgiP2sdIBolac6DT7lAvCSMUVm0JOEy13Y0Zttvxf/YbFdOj9yCkyJgD64VAvB9P25OZjQZM7iavsLmQq8NKSp4c/Zumo1fjVOmgmJP90ydPjf5GHGy+osPRIyQF7S0v4wOur+I1taJDkREv3wc2z4rD2hldKiiF8vft2jepFbk6kVtL2IbRVnscJ2xDppc08JwDsPO4+iqmVh60jccxkoQHbPo8UD57cxPB92PQoDG59i1t4RtoUpjEk5FK3msTIj1K30XiqQ9P3lCAgU2d+9vfHFksuEdvMODrEd1PePHiRfTu3VtyvGfPnrh4UdlLGkOKuKpGhpoQGeL5wl8Z3rzSm225/L6c1AGHSBpG2WZikyiukVqfeH/vhvjw9jYwU4bEcTK26Fo61vAQDfuGKJM8vXbEr49ojr5N0vDysGbe86HkfXOkZwPoV3xb5FsW4Vu+hezsqj8mYPROEBFCYKEiypWJ4r80SInCUzZnMN+X+KFe01MamEoUJn1iKvaiz97sXDGJU9goLaal5XX0tzyBK7WKvF4rNMfRlDwA6FZalcitFVW+curJ3M7Lr9ScIfITCXJ8epfQMYOSwsRxHF5zDMRavileHdYUjdPl8zAaOMnqd0T59+jysEm/Pt2TmGKTPJm6kJUQgexEZY+T3vJcbO8JCzHhcdtI/ORohEdso6ns5VaDncf0zjprvVowMaXRKkA4+8zhyRvknc8QcLDCjI8dXXAGyitEQg+L3mXe8EBXdC8PWjx3YGPJeQcvnELTU3Lyk3+eg+L3sOuxXriXGvB6I1znYNwX/KlkTeycK+v10R+oTcKqwROgTmKk+9uX493RxXjj1uYY0FR5n49S9lodZ7iQGzeID4n7JTrv9pTlBccBu0/4Z/y6n9RGB8sCfORQXqlrUUf4XfZqnILBxZmCek5LrrS63sP6LJ60Dcez9iGaxjxiMzq5/dr1k6Pwy6we+Pmh7njm5iaIy2mONY6mWOboiBGt67jTaFEnHguo8ZLWWuVr/asK6G5FBgwYgM8++0xy/IsvvkD//r5ttK+pyLUP8ZRmn5eq7EHJeb+cKYl4pt91XCMydVlp1YfI5OeNF4YWCaJiA9pmcZtlxqFbw2T0VDAfBIAroqVjPRRlxeHV4c2RqWGFiU65kehZPKZXco15xTUmvWkUZcUJTDvEDfX4jnXxlqM/WpW9ijchnY0e1ioT4SFUfB6F7I1i5wo6H1Xp8sHFmdj9WC/NSspZxGAnqau7nLTYdhNwiAkzISLEPytMctSOD0e73ET0LUwTyHSP7R5s4vMw0jrT6zeXkygMkKulKNS+Kzk2zeqB9fd3RXaSNBhvReu5XH+6ZJxwf554dlMtTw7AHPtoNLa8i3cdfTDM9jD+gsfU+SInbWddZe/PFSY1+bSkpTVtX4YjcnVqdLtswfGM+AgsHN0S22f3xMi22ZLry2wOoYw6ykIuf7WkJOZAFMOss/AXicfM0Fmq6auKqFSIfpj00sLMPg0RFWrCPd182Z+sLqSvw1XXfWrj3eToMPQuSFOdaOjWUME00Q99hrgdoBdQOA74+7InyK7QcoLDtB7aFXB/46qfnGhSxIWSwnSYpOJtRz9cQ5i2FSbRZ1NamAYAqB3nWWGODjPBYOCQEhOGIcWZCDGbMNr2AKbb7vTyENpeoMXue8zQYKO758/Pz8eTTz6JNWvWoG3btgCAjRs34ocffsD06dOxYMEC97WTJ09WSoahEdWNznLHJBYHnPwJ3yXyLoQKubWi8Nld7dHg4a/dx7QMVg0GDu+OdkaP7/niWvxx6rLkmoMkDc/bbsZZKHtPU0KP4qfkycYbgdono8SdXXJxe8e66P7CWo8MCitBpxGPcNGrndK9PqaVNMDq305Jrgecg0nXioh4AHNAYQO0MsoVPVJlf4ASWspa+B69X680g8dxnu/0pVuKMGXpNu+JKeXBE4mZHgAcIOkYYp0NABgryNv7LKsvG329ERVqUty3QefWtzBNEAxSDqmXPGldoMsYgGTSRVHpgKc87FR316aux8nBt6YuaODYgh95z6qJ2ySPGmHkpURj76lLis+hLok/8HPaosGkmDkDGuO5b/ZKjit5rCuzOXyWUOmde/7WvoL9E98YbSyvIjsqAsBVHyXSTyAmzum4ZZU5L98jPxnf/nZaeLD8ASu6knZX11y3IysavS6vZa04xNcoeCB1InwOuQDX/qBldjw2HzonOCZWgFyi0f0oLa2/6pa4DB4qzUeD1Gh0rpeATs+tk71H6wTYuVDvoWgAqZXL9YTukcjChQsRHx+PPXv2YM8ej/e0uLg4LFy40P2b4zimMOlBoU76EuFZjn6Fadh+9DyyEyNw6B/lTsRbbhfhmVG+gnC/KAF604hXcVH9skPZZl8NPW21NrMTeW+AgaBurUhZBeWB3k7zSUEd0lCdXINT2lmE55znGbrkJaNurUhsPPCPqgmGFjZGdMHQc2/iR4e2Tdne0FvUWhRmC9FmFlgRbmun7H7cDSf7pyJ6TV18QWmfW0HtWHz3+2lcU+kkxSYadRLlVq2EVVdsFqTu9EF6slMDjwMLB2fCVNsk2XvoFabeBanYe+oS0mLDkB4Xji2HhYMgb3Ioy6fxOs0rTNou1DJDr4foMLPPOp1JJtqxmsmgv9pSJQ+Vgebnh7pj71+XcLHMhkkfbEXXvFr4fu8ZyXVVyXhJiyxahitKDpz0jgPk6oD42IGEjsDBp/EHXxvRXtIXe3pVQ8t+q4gQI7bP7gmTgcOSn49g0YaDOPC3s59W8gQqmAiixNHi/0OLSR79nb19WzHCQ4wY2aYObDapB1QZMSQQQjDE8ghuMX2PPzPuxW3ZcXj/p8Oy17av51zVr1ErTAcPHgyEHDUeV6UMlHnn2A45qJcchaLMODSbu0rxOm/2pRaEoLPlBbedPN3hDCpKx+fbTniVRdzOmTXEWKLp2yQNPx88q9tBg6pMeq71cYXJ3/3xsFaZMHAcJnbORcdnvle8jm6cpTNbHqlcM4ebZ/XAkbNX3XG4lPanGA3OGSp/cN6UhPyyd1GGEHhZ+NeI99Kmr9DSWVtE9Z1Ox1VEiZH6vRjSJEdXfPO9WMbKWNmka5VBpk5pvRdwmgfOKs3Hkyt+E6RJ1924iBA0zYxzu6NWGugTQLYqCAfjMgOv8iYphzI5vLtrPeQmR6Ft3UTUig7F2+sOCGRUyEpeLvqhFW6SKgka09aqMPlJQ1h6exs88d89mDuwQDSZ5D19l2MDuUG0WjsbCOVGS5Jq16TFqX+7dHmnxIS5HW0UpMciIz4c9WZ9rXSrEx/GBnWTIt2D9IqkA3jqrNIQobB2rMREXQ6leqHUl3asn4T1+/6WpiP3XYuOXQ1JRpOyt3EFYfgBHJplxWHrkfMApM8hp7TL0bcwDTP7NPR6HQfP2GZkmzoY2aYOsmf+FwDgUFhhEgdSdqFt34/3GkwPtZQsBPRWj00kH5ts+RgTEo/H+jXCmPY56PrcGsE1+57s45586pKXjA83HfHr+K2yqLAxvsPhwM6dO1GnTh3Ex8f7QyZGBVDqBI0GDl2VbIcptHwsh0mqJz/qeNPMOG0Kk+i3kqcWJZzBLyPRVGFvlU/42AErNfJySqC/O/mcpEjc3inX63V0W2sUx0uSuT4pKlToOZG+XmUjdkW5JhODxFd0rzBpuMGiwV1s+3qJuLNLLl5fs1+fADqgJZULmCnd+yL/bJUxo+50Ne39GhqO4zChU12BMiI2yQOAIcUZboVJDW/5q6203N6pLv65bEGPRikIMRkEK6kdyldgQ4wGyX16KLMryCUxQ9OWttYBD52akthaHqdN3UR8dU9HAMI9It4Y3S4bYynHBgZOeSZd4txOg2BarlFqwnzRKZKjw7DszraICDFJYgqqIbcP0F90yUvGgb/9M8ntbfJj+aT2Gt+LvuNv31aMW9/5Gb+IVnTl8hK7Yuc4j1UMxwGRIXRMIW35A0BiZAj+uWIFAIztkK1pr7Naadkd3muYcDLTO1quoccresddcogD0nMch3SZiQN6PPRw33w0To/RvW+2KqDb6cPUqVPdpncOhwOdOnVC8+bNkZmZiTVr1vhbvhqP3hWnin4CuvMTrDj4lrvJywqTuBE0Gjh0blBL8rFWBL3OK6gbZcmSCVCodyXNX9Az8zFhZvf+jbu6CJUtvWXgTxNDfy+s6pVMS9Xdzcuby4k36rpMIbWi5nXKGxsPSIOKih+lMlaY6G9Ur8dELatQRgOHuqKB5TWrNlt4Xx7fZcYYZjbisYEF6FhfGoMqPy0Gq6Z1wuZZnoDtWvNybbbWg1a3y/lp2iaSBHuEyiV/bnBTcBzc8YpcXhC1omd1cc6AxrLtpLysFavEtaLlV371puutpraok4D8NP17aBXzo9puujzzUpQdQu3iswE4QyyYTdLn09bWytznWmGSuXp8hxzNZal0lVL/E2Y2ollWnKZ0aHfY4ms4qK9aqo196MDOWp9TLT2JpYeskyjl6+XYyeeUX6ssHz1G8zbukpNDTCfa02D5M4SajHhxaFPFeyJDTbi1TR0k+yGUQWWjewT3ySefoGlTZ2F8+eWXOHToEH7//XdMnToVs2bN8nK3bxw6dAjjxo1DTk4OwsPDkZubi9mzZ8NqtQYkv6qEWqcTCOu9imzo1KowiRscb4rEJ1uO+SyTVvTtYfKg9Mj3iOKKtKmbgM4NhIOupCj/KXxqiN/o0tvb4ve5vXG/aGCv9937e4XJn2ibXVY3y3IxyPI4FtgH4U1Hf3kzEJ8k9DCpaz00zYzD4zKumuXQ7QFQaYXJj0aidIcuCWLsB8XaZDAgPjIE62Z0xaZZ3cuP+Ud+OfG0Jl0/JVoQ+0rLow4pzsBdXeVXhm/v5Ang6kpqVmk+GqZG464u2jympcRqG4jI7RFqm5uIP57o4w5Y3rpuIj6Z2FagFKqnSaGzK1Ezu/O1CrnCRUzsIl/eVbgJk0CPmWmnJWKm2u7Gv+w90Mc6HyPbyE/yaMhNOX+Z9/qwxoDAgPK7pNuQV4YLA9DKtSFy4wbJJKpwVkBQx5plxqFj/SQMV4hnRkPfp3WiUK0/lQQlVuhXXIrxoCLvDhWm2e7C+/YS9LHOk5yLL2+jaCcY/mg/lfYA3tAsA0WZcRVOv6qh2yTv77//Rmqq0yRrxYoVGDx4MBo0aIBx48YJPOT5k99//x08z+PNN99EvXr1sGvXLkyYMAFXrlzBc889F5A8KxulwIEVWfHxBb35Ccy9fMzcLPpwxXbXx89f8yldPeiR3NsepgFN0wX2wdGhJiy9va3798cT2+LZ/+3FnAHaBshKaH1XcrNTYWbtqxpK9tOV4UzAV7T0BXTnIb68VnQozlxymhdtI/Wwze4crMrNh1e0GOIjQ/DF3foC7aohrpOB8JInho4fJTAl0VBJtay8upQwekViaMssrPrtFHrkq5t2+KKw+arkaVFCexekCp6ZLiHaTMYlwoROdTGBUqR8leG76Z3R7fm17rRFY0lKBuH7KM5WHpxL8qYS0jv1JjElpaTydTW7T2Ea+qiu5unTyoLZ4imZRos5jXg8Ynf60owOlTqq8TUOTqAdUNBKREtRnZN7//d0r+fVA+fWIx4zPgPHCQPDGjj8iwpXkKNiGvnzwX/cf2utA+orTMLfdJpj2mdj0Q+H8GCffPRtkoZ9py9r2n5wBvF41D5Gcrxzg1rueJF0n63dyYVvtb4qOSzxF7pXmFJSUrBnzx44HA7873//Q48ezpmnq1evwmj03bREjd69e2PRokXo2bMn6tatiwEDBuC+++7Dp59+GpD8KpO3RzbDkzcUKC7jq1U6uYZP0lnqrOt6Kzk9m6x1EC4WySza8PvFpPb4UMa1shqrpnVSPHdziwzB782zemDPnB7okOLx1qJvgCQ/q+LCWxm2zE7Afya21bRBVg0tnnO8XVeRwb6/No0HAi0DVzWF79t7O1cof9qEQ44GKVGq5yuC2MV7ZbwmJa9PhHhvgkI0KExys6HhIUb8e3wbjFEJ8Kklfzl8LTNf7qObca3ftByHeKfieLJ2L9nzdWtFYc19XdCnIFWioPvrW6a/u4oGqFRS6LTL4h2DQh5aZG/oJU6ivyms7Rk0a82b89kKXFp6ft0zrBPx9187Lhy1orw72PnztCf8iNMkT7lWNEqPwdyBjXFrG+mK07mrHi9y2leYlLHzQk9xtFyP9muEjQ92x5CWmYgMNaEoM65C32dsuNk9NjMJVpjkK4d0T6m2fCSXXccBapXQvcI0ZswYDBkyBGlpaeA4DiUlJQCAn3/+GQ0b6rPdrwgXLlxAQoL6oMRiscBi8WxCvXjRGcnZZrOpulGsDFz5t8+Jg9lsdv+mG2qbzQY7talbLHNmnLTBcDjsgut4h8Prs9Lnxfl7wwge95XUh9XBozDdMwhUu1fcGbWqEyu4PswIFKQJZ3u8yZKdEIbWOfH4+aDU1S8vapziwgyw2Wzoncljwylno2G12WCzaWsZ6DJ1yGy653leWKYa5PcFh5d3q1SnxGm4IEReTvoa+jwHoil/b+dtNpvgHSVEmCpcXuLvQB7Pe7LZReVil7+Xg/pzuc69cksTfLP7NB5ZvkdwvnlWHEa0ykSHeok+P6PSs9HHPprQCkPf3gQAsNvssMnMZfDEU+YVLW+rzeO5gE7L7nAIBg5y+ZiNnNf8icMOm01/B0wIgV3mXQq+HblkiXrdVsJuV/DgoJC3zWYTZG/iPL/sdi112EMv69NI5s5hWkw+gJ0AgMbp0Wifm4iejVJgs9lQOzYEC4Y2ASDc/2az2cD7YSWSLussL3FtvD2bg3p+QoRtuJZyIRreIf090+2cw8F7bQtvbp6OJ1bsRUeZb1nOgYUWeVy4rqP7/6nd6mJAkxRsPnQOg5qmakrLbpOvj17bZoe0X7u/Z73y+ir9YMTp0e25+JxNRqbiJB7nuVBcLPeAIr6Hg1jBkH8G8TF6EcVutwsG8XL331LsNH1bsvGI4LiBA1wloq1vUX/fDofwnHjMkBhh9NuYgU6b56n3SoTtkJLcROVd0hDCS9LRcl9VQKt8uhWmOXPmoKCgAEePHsXgwYMRGuoctBuNRsycOVNvcj6xf/9+vPzyy3j++edVr5s3bx4ee+wxyfGVK1ciIqJquDRctUro4jvZZMAJGMCBYMWKFdh7nAPgHO2sWLECADCtADhr4XB0+w8Qv8KtW7eCHCHu4zt27ED4X9tFuQrvcaULADxvhGuugD6uVFVWrFiBzPK/d23ci9sbcogyEdG9QpzfkTO9GDPB0e0/4KhIRBsvzFMtPRcZhMPPkI4MDeePAtRxV1r08GD1t98iymuYHac8J3//BSsOOY/YRXICwIkTJ7BixTH3cZvdpkl+7TjT/e3337Hi8m+CYzSuPB2K7xTYfsZTv3iHQ1bOHWfFddCZ1/FjR7FixWFZ2eTyUmLVqlU4fdoA14J36KndWLFit8yV2purH37YgMMCnVt679GjHvmv2ITXrFy5SvYeq9UqeS6lbyZGJt+rF87CdPxvbDyu9UmkMmzetBmX/iCS83Te5yyec6tWrkSYTNGdO+uRW9wO6WXrafk6sm/fH3DYDVBrU+yWMoW6Qr+Pb6DPqZPz3qtXr2LlNyshLse9ez3fzqVLnnJwceL4MaxYIRw0aeEsVe5KbN78C67+SW/m9+SdeukP9/1fr/oOKV5jaXrysiAER0kKtm/bBte7uHbpIhrbz+H4jj9xfIfwzn0XPO/s66+/9st+nmt2j0xH/9gJyLTHANCrNi9554QXvod169djf/k3fOCIp30AlNoWYblfuXJFpQ1yXltmKXPX/d9++80t74GDB7FihdTT5Q6qniee3Y0pjYGMyFOSfKYVAM/vFMpjk2k7lOR3Xbf9b09+a1evBACkAvjmf3vEN8um8+0qad232e1e2+aTp4Tl3SiOx/rvnOXk4KXfizi948c994vP/XVVKCMAjKzPY962y1Dqp/Yf85QDAJRdvYpV366WpCO+r+yaR9bV336LM6eV5RIiTNepADrTkfYt8vfyvLSOu85duXZN0E6edI8ZtKBv2H7ypCft/Rc9969fuwa7BXPuzuPnz58XyH3qlLcyc9538IDwmzl3XnncUdW4elVbgGuf3IrffPPNkmOjRo3Snc6cOXNkFRqazZs3o7i42P37xIkT6N27NwYPHozx48er3vvggw/i3nvvdf++ePEiMjMz0bNnT8TE+M+TjS/YbDasWrUKJSUlMJs9I/W2Xax4Z8Mh3FCUjnrJUTi67iC+PLIPAFBaWipJZ8pPKwW/B/fqiPrJUe7jTZo0QWnz2or3PDWoEUopk7X7Nq2Co9zlJZ2fOB8XYpmkEsozdaMzvY55aSgtbSI5b7HzuO/nbxXzkePvjUew7NDvkuNzR/XCJ3OEadlsNny2wjNI7N69OxK9LPE3bXcN567YUFDbU3esdh7TKTkBIC0tDaWlTd1lZjKZUFoqbybjC6506zfIQ2mXuoJjNK4ym7ZxpeSYW/5tJ7Dkz10AgOTYcJSWSk0bzXtOY+Hebe7779u0CjYHwYhuzdCrsXD/CC2Ht3dGfwOfnNmB3y847cRvGSR/n9wzyrmbBoAOHTqgEWXmKndvTp06KC2PI3XuqhUP/bIGADC4RW307dMQMzevltwTEhKC0tKugmMzNn8LR3kwPvEzi/NNS01GaalwQ7MacnK3atUKHcqDAE7duNL9/HTef10sw5xfnZHbe/bqKRtzY8nJzdh/ybkiK26H9HL5l2PA/j1uOVxy16vfABvOHMY1h10i42b+Nyz5+Shm31CE3o2l+5DoZ+9X2keXWYrr3sZZSejduwgzNgnfZcOGDVHa0WnK9+r+H3Hy2mXB+azMTJSW6t9jeOL8NTz2q7pL6VYti90OYGw2G375wNN+DB7QB7N+cbZLg/vJvzcaufrRvFkzvLfPqR3Fx8ejtLSV7L0/HzyLV/b8AgDoq7N8lbhUZsfMzd8BcD7nW79vdZ9bd18ndHrOWScHd2shcYIzY/O3rhkoAEDbdh3cbe2+1X/im+MH3Oe09IVRUZEoLe0gK6fr2ojwcJSUtMWqVauQn58PHPwDAFA3JwelffIk95VtPY4P9jsnc/r1VW/fiorPIj0uDN1f3AAACAmVth1K8ruez779JLBvp+CYN+h0evXqifs3fSc4bzQavfZH/z65GbjgsdaoVcvTbv33wjas3HNacL1Ytu8+2Ylf/j4pe+7P05cxb/uPkjwjIiOBa1dl7zmy9gBWHP3T/TsyMhLdu7fEI1vWqsrx0r4N+NviTLOkpATfX9mNnedOy15LI65LJqPR3cZ37NAR+WnKJpGueznOICnnQxEH8OLqP/HskObomlfLfW16errsOEiLbN6g09565DwW7HZaHvTs0R3J5d4jbTYb8NP3AIC4uDiUlnr2dn11fptqmbnkyambg9Lenm/mnSMbcfTKRcX7qhIu6zNv+KQwrV27Fs899xx+++03cByH/Px8zJgxAx07dtSVzqRJk3DLLbeoXpOdne3++8SJE+jatSvatm2Lt956y2v6oaGh7hUwGrPZXKHBgT8Ry5Ica8ZDfT0dNUfZmarJPKxVJkoL09CodrzguNFolNz3ycS2+PngWUzsnCvxaEUPPrWUUUXLMTREKh8A8Jxn6fiuLrma8jEq2OSGh4WipFEKVu05BUBeZoPJ5DWP7FpmZIu8C3MGadRqjjMI0uLABaa+cerpus7xKu/UZPLM2sVFhMimZ6SuMZvN+OGBbvj9r0voWD9JdZCl9ZnNZrPAUFpPWRk4ThIEEADMJu/fuMnoeU8JUZ5nfOrGJlIvRuVwGstc8bzM96gXk8mThpHjYC9/fjrdjAQT+hSkIsRkQHyU/DIFJyrzishFOPl2qqB2HDjuiOy5uYMKMa0kz+tEBeBUVPXw2V3t8K+Nh/FA74bydZp6D3JOMeTaTS2Yzd5N8oyitoauaSEhIdj2aAksdh7xUb653TWZPN26Wn2lr9NbvkqE8J6yNJqEw4usJM8gMzUuUiKX5C0YPN8n3U4BGtsIL98q4Gw/5PIwGAwK9cbzTN7S7pgnnATQ0w/IyeRLfQyVfa/e5bCJ4xkZPPc8O7gIbX89hse+9KxyidMzqIxbzGZhvbilZQaAQ6BrgPieENE9BgMnqV9y99FjgpAQMyZ0ysWq306jR36yrvKkuzmz2ftYAXB+1+LrppTk4fbO9RAuCiVhNMrXN39A12UTVY7hofL9vbjNEPcTSojbTK33VQW0yqdbYVqyZAnGjBmDG2+8EZMnTwYhBD/++CO6d++OxYsXY/jw4ZrTSkpKQlKStjgPx48fR9euXdGiRQssWrRI8EEygHrJ0bKxQuQozk5Q9HxU2dv0Qk3yJhv05uGWXjbQu9DtlUnn9XJo2QBa0c3PSlRkg7gexOInx4RVmRgKg4pqY9mvUlMGLZPldINuMhqwY05PAE4vYQ5ePsaPXLJ66pF2z0TK0N/Gfb3yMP/r3yXugzmOw+u3tvCSjv8Qe2JcMbkjdp24gBKV4IQcx6kqSwuGNcPkD7cqnlejWVY8mmU5J4/KbNriNdH4ap6mqd6Jfou/r4rGl/N5k7YfUHKi4OKNW5vj2LlrKKAcGLivF90g8Lzog7Ra7lAqK60xaqo68k6JvHccNodwIpCuo7HhZoxpnyNQmPyBWj8pDVXgjCnoDfo+jnM649k8qwcSI/V9Y7RoWr8vpecRK0uVCS2SUl8kV9Za8NauVQd0K0xPPvkknnnmGUybNs19bMqUKXjhhRcwd+5cXQqTVk6cOIEuXbogKysLzz33HM6cOeM+53JxXl3ROthWuq4qezIDpB69XHhz3S2Hqjc4bzf7+HFr6ZDkVkD8gb8VsSpeVSR0blAL9/VqIKswaakz4kvoDjhQZWHTEOFdD3d0qouSRinISVQ1qpfFn5KIXVE3So9xe4H0tSzTNMYT8oYv+fvqxtqXgb10jbpi0OMdtXccCHfz3p6/d4Gyi2/xvXbqWwmUZ3y54L0AoKQvXWdNpM+x1ka0roMHP93p/h0ZqjzIHyzyQqtFKuVf8oi95Bk4DuEhRqyY3BEvrf4D3+w+JXsfPfh3+Q1RCmKsht2H2Uk9d/i7Xi0e0xKjF212yiEQxPNDXKZD6jqw9kwE5t1YKJLNN42pIjE9qyq6p1EOHDiA/v37S44PGDAABw8e9ItQYlauXIk///wT3333HTIyMpCWlub+V93xdUwcUq6ItNa4OuPJr3IreYiCwkSjtTFRkz1KZte7PwbFcgqpWAx/D5JdaIn+XdnULY9lUT85cG6zXfRqnKoYw0fLu/V1UOxLXi6uWfWvdqjlx3EccmtFVUqsJTVuaFYbLbPjcW9JA7+l2SIrHqWFqbinm7aArUp46/DlvmFfgzLrXdkE/DMTWzuONrukBokqiQeixlQsTIHwN+16OVATGEptgJJ5d2VT0brha7NwS8tMfHWPZ/9XVoLyhIy/3o3ao4aKQpZcKnN6NWuUHoP6ycr7iWilQOzKWw9KJtpq6Hl3eia225fvX+1TIL9YkFsrEl3ykmXP0Y8hdivePoVg/YxOaJDim7t8fwZCr6robhUyMzOxerV0M/Tq1auRmZkpc0fFGT16NAghsv+qO74+4a+PlGDDA12RmaDPG6Ce/IYU651ZkqLUYdFH/dEgz+zTEM2z4vDc4KbuY2FGICUmFElRoZr2UfiKL42tFvxR/bU1ctozem9sK4zrkINFY1r6LpRGCIigDOh3q8kcx4c8K1oXBzXzHrGdZunt+uKR6cGf3VuY2YiPJ7bD5O71JeciQ3zaKguDgcNrI1pgek/p5ns9VObKKZ2VN4cNLvzROtBjH63BYwNdLhW1bqBXmAIVfFipn5GL+1VRgrGCr2VCT+m+gtqxePbmJuiSVwuTVCYt/DVQVpNrUJGw3aRNkNVWMmLCPVYD0RpM+LQQbMXg9VtbYMGwZpKVIBfi0hC0B/R+ZhmTvKpukRRsdPdk06dPx+TJk7Ft2za0a9cOHMdhw4YNWLx4MV566aVAyFij8XVQHBVq0txh+5rf4wMLdKcvRun7pD9cfzRQydFh+PQuYbBGAwesubcjTGazzzPKclSWHu8PU78MKlaKP8o5MyECj/RrpPs+LY/StzBNENmdJ8IZ9MZUIGBxvYoIMeKq1YHaceE4fv6abvnU0FJu79xWjPhIM5qX76vRilz0+eutS3tzZAtM+uBXPNC78uL00XgrL7nzPq8+Ure9fVsxhr290estWVEV/45pef21cuoLtKJRPzkKA4vS8cW2E5ruFcvdmPJGGqhnUkrXH3sNqwIV7dYGF2dicLH6RLhcEY5pn43Pth5Hj3z5lQ451CwmwkOMiA414ZLF6VRlYudc6j7lNOn6qMWaRYlnbmqC+5c5PU8GoirqSTImzIwBTdMl+8y0QJexv5UjcXLVcT1D94j6zjvvRGpqKp5//nn85z//AQDk5+fjo48+wsCBA/0uIKPqEmau+OZFpU/WlxUmXz5Qk9GgaNblK5VluxulMnPfI195sz2NkvOPqsgrw5thvqUQhXPK3aoSYUkLlV5hpVl2Zzu8/N0+3FuShx4vrAUQmD0cSkSEGtGijv6yDmSnU1nj6oLasVgzo2vlZCaDLwMDn50+UPVO6+bujEhgydhiZCX6ZgoDCAf+tOjq9cf/FcBkNOCDCa0BAqTHeQ0ipSpNcrRnD1vA6qpCusYqMtNe0b5EdoWpQilqo0lGHLY9WoLYcLlVHY8EISYD7uxcF1t/OORVrvv7NMQjn+/CLS0zBU45AtFGDinOwH9+OYbSwlQ8N7gpCIFHYfJ/dj6hWEdF5VE3yWMeH0irCvFlTGEq54YbbsANN9zgb1kYMlTHjXM0vniVUiJYZTW5Wz0cP1/mdj4Q6IbiqRsK8fWukxjTIUf2/NZHShBN7dl66ZYizPhkB14drj3+D01lNHxa3h3HcQKvis4VJs95gYcuUaXJT4vBayOEXuP81fFd88ELW4WoKj32dYJccSlNyBg4Z73q2ECbx1FJugInAtrlaZ2TUCHXu3Td17r9JlDzBe1ytXm+1YMv+zW1PB49oKev96fFgYfgfLhTutfHS6v3eQ74uT1XejVavD1uebgHwozANS8fqAAAIsBJREFUVrWEyrm1dRaa1I5FXqpwYiEQWzMeH1iA3gWpaFs3CeEhRly1esIFBESX9iFNb/rSJxPbYtVvp3BH57rucy3qxKNpRizq1vL/HuMqMscQUHwzLi/n8uXL5RGQPQQ7IGx1Q2tbcL1q80rmTIKPz8cVpl6NU3BLyyzfBNPBveV7LMTe2vo3TceX20+gf9N0v+Y3vHUWhrdWfq54kcvUgUW10bcwrVq4yhV4ACNEoGjRG7UD13ZLU360XyM8/tUezOhVsb02clT3CZOqxsaHumP/6Stom5vo0/107VDcn+nHyhkdZsKlMju65iVj/5mD5TJoy6CwdiwKascgPVbfSlDAUBE7Ltw/caJcvHFrc7z6/X48T+17pBE7GfAP6t+yXBBuf5hJTytpgDHts1H0+CrvF/uAftMwzzM5FVPnQ3tr6TiOQ9PMOMnxQDg/CjMb0a2hx0oj0PuWfHKb76UhkQsfYzIa8MUk+WDOyvnoFg1A5YeoqQx0K0wHDx7EpEmTsGbNGpSVlbmPE0LAcRwcjkqeba3mVMdKBwAts+Ox+dA53NBcfhM83RhotV+nyyohMgRvjiyuiIg+45LjmZuaYEDTdLdXm2CiRVnSuMIfVOi6wBOh/TptoqBpw7da0F0dXrLGtM9Gz8YpIk9lorx87HADapJXQ5aq9HT4ydFhAlMwvdD1szKU3W/v7YxNB8+iWVYc3tlQ7qVWo9MHk9GALyd1qDIbvdWkuLF5bby0+g+cumhRvEbP/sTeBWluF+c2m9PjGl0MNzeXd2gUyKLyqA4e/FWHKhrbSw2LD3tpXHDUU/va1lXGZLHwvfu/EvhzLtPv4UZqSD+hBd0K04gRIwAA7777LlJSUqpMY1tt0RqHqUoNa73z4YQ2uFRml6yGyKHZJI/QfwevPFxZh4cYVQN3MvRD7zsiEL5nLeZQNGpNl8HAYfvsnnDwBM3nrlK9h+M4ZMSre6P09fuMi5CJxM46MF1466P82YXRXrkul9llr/Hn+0uJCUP/puk4ddEzeanHQcL10n+HmY14qDQfU5ZuU7zm44ltsXz7Ccz/+nef8sij3Ckr7T9TmxTxTtUoa3+PFaz2CihMGpV7NSq7p/fnJzOjVx7+vfEwpvkxHEOwRj7idq06erHWrTDt2LEDW7ZsQV6e/81PGFIqu8q5vBqNalvH+8UVwGQ0aFKWAO2d+vWmNDI8+NK2EkLcqwEGzukJz31Ow/3ealVsuFnS6Ff2kCcixIT/Tu6Avgs2VHLODF8wGjiMbpeN7cfOozg7Ae1yE/Hj/n8Cnq+iBXM1GrSEezGTS48Lx8TOuW6FSe/AtklGLBaOKlYNxdG6biLm9G+Eeiqxf3yFk7PJuw6oiMJEc0fHbMz56nf0LdQXX/PmFhlYuOEgiuvES875qzT1TsZp5e6u9XBXl9wKT1w0yYjFjmMX/CSVb1wncy8VQrfC1LJlSxw9epQpTJXEqHbZ+NfGw+jfxL/7YJR4+qYmGFqcWaW8pwXSS15gqDKC6EKpmCvF6YNPCpPTy9Lux3rBwHG6O25fgowGg8bpsYLfVUAkhgpzBjR2/y1XrwO9afx6rR+tchLx7W+nFM93a5iMno1S0CQjVvGaitJdg3fR0e3lne1cL/irPZ/cvT7eXLsfM/v4Hi6Ao+wQh7fKRIcGychOVA6SK0d+Wgy2PNwjoGaH9OqJ/91xVzy9IcWZboXJ7/21j17yqiO6FaZ33nkHEydOxPHjx1FQUCDx7NOkSRO/CccAkqJCseXhkgB57ZESZjaiXT3/ezmqCL48eTBVlmAqbvWS/e/9pkteLcSGmwM6UPEF14piZHm8MStlS6/FHKCmm7ZdrwNrfxPIelBZq970Mwj3UV0/PNw3X1VhMhkNeOu24OxL9Qe+fG9VZxJQyr0lDTC5Wz3dzoTUYi/6unIXyMDz1wN0f8csbQKHboXpzJkz2L9/P8aMGeM+xnEcc/oQQLQoS1W5Ya0ovnQ04sjglUlwlTX/5x4ZasIvD/cQBAH0N7408uKAhXrFu14VhutU7BrJTc0zsPHAWTROj8HuExcBBOb9BcpkqDLJToqUusCuAFVtQsRb09yvSRq+2HYi4BNT/uwhKup5taq9IyXoviVSY3y1yiSQYw7Nb0jUoVbHMaluhWns2LFo1qwZPvzwQ+b0oQrhbdP59Y3GPUzUF1oRM4HrkZl9GmL+17/jqRsKA5K+v4P7+gNxg6x3Zt2Xlqs4W2onz7i+CWQXdnOLDNRLjkKDlGg0nv1NwPJRcuIV7EFLvybOPbFZKvuCaKrjRnGtPHlDIdrnJqEH5SiIjjtXHaFN8qoyJqMBT95QgDIbj+QY371oBgoHNXvo70/I1zH+vJsKMeSNn/BA7+ozFtOtMB0+fBjLly9HvXr1AiEPQydLxrXG1iPn0KcgNdiiBAyzUdsHS684hAUkjoY2gtHpT+yci3EdcqqkYhMoxPE3tLbrfQpS8fWuvzC0lb4YXWYjFzCFVA/RYb4HOKWpyXNdlbUiw3EcmmWJlOwAZFhVJy575Cfjy0kdkFNL274U2stgRamiRaJIVKgJQ1pmCo71bJyCjvWTpHXoOoZutq8TfQkAMKJ1YB1hVQR67BOsOQfx59Y8Kx6/z+1dLeI/utCtMHXr1g3bt29nClMVoUP9JHSoX7X2HPmLUW3r4MSFMhTW1maiUFUmJ4MlRoWVpSCOMHx5d2JFWqs75ddGNIfFzutWqqeVNPB5Y3FOkr6NzGo0SmfBwRlChF7yqo6mwHEcCnWYmN3apg42HzqL7g2rTziGgtox2HX8IgYW6XfcZDYa8K9xrf0qTyACvfpKoCWpQo8aUKrCyqxc91udlCXAB4Wpf//+mDZtGnbu3InCwkKJ04cBAwb4TThGzeaxgQXBFoFRBelTkIpdJy5gaEt9K0QuOI6rtBXINfd1wcUyG9JiKxK/xUN0mO4mm+GNSp4oCIRCoxx0OvgDKT2EmY1BCzgeKJaMa40f9/+Dbg2TKzXfWtHyjhCCPbbOiPe0hUaOA9v1XnECqQRXkr+x6wLdve/EiRMBAI8//rjkHHP6wAgmVWVwEOwOqbrz2ojmAKRmSII9TFXkHWT7cWUJwPVjv8JQJBBKr9Dtsd+TZ1SAuIgQlOqMLeQPqmo1CDMbse1Rp+dfg4EDGzJWHKFJnn87Ca2WK1VpZTtQ6G65ed4/QcoYDH8j9poWLKqIGLoJZnOnp8yU9msEeqBYEzoERuCYO6gAJ85fQ4FGE2N/4K+goozrD3GbOrFzLt5Yux+3BTgovRYCGTOpJhLIFSbNClMN6B51Gxi+//77sFgskuNWqxXvv/++X4RiMK5nqoI98XWHH4pMuIeper4Dfz5VZQ7cqzKV1c+PbFMncB6jRA/hMv8a2Sb4g2NG1WBGrzwsn9Qej/ZrFGxRGH6GHnL4u+cLNWldYar+6FaYxowZgwsXLkiOX7p0SRCbiVG9WDCsGVJiQnFzi4xgi6JMkBUVV7ysdrnV0wlHVacmNNj+ZGr3BpjcNRf3N7EHWxRGBRF7/Xt1eHN8MKE1hldhz16Bpqp6DgwWRgOHJhlx1W4jflVjaLHT02FlruQJAtf6eRik1UtxTUC3SZ4rQK2YY8eOITaWzVhWVwY0TceApulYsvEwPtlyLNjiyBLsNYU193XBTwf+wQ3Nghc0tyJc7+MLjgNaZsfj/FUbcpKigi1OlSc8xIh7uuVixYq9wRYlqFzv9R6QThaEhxjZxE0Nhxk6BGdMMHdQAQYXZ6BpZlyl5ZmfFjjPqcwkz4NmhalZs2bgOA4cx6F79+4wmTy3OhwOHDx4EL179w6IkIyqQ1Vug4PdQWQmRCBTY4DGqkiyglelysAfDjs4jsN/7mgLQgBDNXXtw8w9K0bdWpE4/M9V3NCsCq+U+wBbTWEwqgYhJgOKsxMqJa//Te2I305eFHhg9Lfzqz4FaXhtzX6kxARvfFBV0KwwDRo0CACwbds29OrVC1FRnhnckJAQZGdn46abbvK7gAyGVqqKl7zrjUVjWmLJT4cxtxq4cXdO6gQq7cCkywg8S8a1xqmLZbixeW1YHTxCTcELbB0IBHGYWEVlMGoEDVNj0DBVuLrk7zm1woxYfDe9M1JiwlSvqwntjmaFafbs2QCA7OxsDB06FGFh0sLbtm0bioqK/CYcg6EHNvnuG13zktE1r3JjhDD0MaV7fby0eh+evKEw2KJcl9DBvcXKUnXo5gV7mKrDA1WAOokROPzPVZQWpAZblKBS0+sBw3/UrcVM3AEf9jCNGjVK8PvChQv497//jXfeeQfbt29ncZiqO1VYK4kMZUE9GdWTaSUNMLZDDmLDzd4vZtQ4mMt7D5/d1R6bDp5F9/yaPQlUhbtqRgBhrz1w+Owu5bvvvsOtt96KtLQ0vPzyyygtLcUvv/ziT9kYDF2MbpeNtnUT8diAxsEWhaET1rl7hylLgeHJGwoRHWbCw33zgy2Kz4i95NVkEiJD0LsgVfNmdQajOhGsvrQmrGjqmpI/duwYFi9ejHfffRdXrlzBkCFDYLPZsGzZMjRqxHz7M4JLZKgJH97eJthiMHzgetCXakB/UCPJT4vB9kd7VltHIQxGTYU5yak8jDVAY9I8BVNaWopGjRphz549ePnll3HixAm8/PLLgZSNUQVhzQ8jEKTFqm8orQqw+CXVl+qkLNWAcQuDoYm4iJBgixAEKneUdkfnuqibFIlhrbMqNd9goHmFaeXKlZg8eTLuvPNO1K9fP5AyMaow3fNT8OgXu5GTFBlsURjViDkDGsPBEwyvwo2uqRoNqhnVC6YkMRhSHumbj1MXyzCyTc0J4FzZi2oP9snHg32uX3NmPWhWmNavX493330XxcXFaNiwIUaOHImhQ4cGUjZGFaR2XDh+faQEUczBAsOPJEWF4vVbWwRbDFWMTGFiVFGY0wcGQ0pyTBj+c0fbYIvBqCZotjFp27Yt3n77bZw8eRJ33HEHli5ditq1a4PneaxatQqXLl0KpJyMKkRCZAhCTMw8iVGzYCtMjKqKcIWJ1VMGo6bCtk0EDt2j3oiICIwdOxYbNmzAzp07MX36dMyfPx/JyckYMGBAIGRkMBiMoMNWmBhVFVYzGVLY0LkmwhxdBI4KLRPk5eXhmWeewbFjx/Dhhx/6SyYGg8GocpiMbFjKqJpwbBMTg8FgBBS/2FUZjUYMGjQIy5cv90dyDAaDUeUwsEEpo4pC10xWTRmMmgtbXwocbCMKg8FgaCDcbAy2CAyGLExJYkhhlaImUhPiIQULpjAxGAyGCnd3zUWnBrXQrWFysEVhMGRhJnkMF88PboqEyBC8ObJqex1l+Jf/G1qExMgQvHUbe++BgvmGZjAYDBVm9GoYbBEYDM0w1almc1OLDNzYvDZTomsYg5rVxsCidPbeAwhbYWIwGAwGg8GoJrBBc82EvffAwhQmBoPBYDCqCWzQxGAwGP7nulOYLBYLioqKwHEctm3bFmxxGAwGg8GoMjB1icFgMPzPdacw3X///UhPTw+2GAwGg8FgVDmykyKDLQKDwWBUO64rpw9ff/01Vq5ciWXLluHrr78OtjgMBoPBYFQJtj1aAoudR2y4OdiiMBgMRrXjulGYTp06hQkTJuDzzz9HRESEpnssFgssFov798WLFwEANpsNNpstIHJqxZV/sOWoqbDyDz7sHQQf9g6Ciz/LP9LMIdJsZO9SJ+wbCC6s/INPTX8HWp+bI4RU+cDAhBCUlpaiffv2ePjhh3Ho0CHk5ORg69atKCoqUrxvzpw5eOyxxyTHP/jgA81KF4PBYDAYDAaDwah+XL16FcOHD8eFCxcQExOjeF1QFSYlhYZm8+bN+PHHH/HRRx9h3bp1MBqNmhUmuRWmzMxM/P3336qFUhnYbDasWrUKJSUlMJuZCUVlw8o/+LB3EHzYOwgurPyDD3sHwYWVf/Cp6e/g4sWLSEpK8qowBdUkb9KkSbjllltUr8nOzsYTTzyBjRs3IjQ0VHCuuLgYI0aMwHvvvSd7b2hoqOQeADCbzVWmUlQlWWoirPyDD3sHwYe9g+DCyj/4sHcQXFj5B5+a+g60PnNQFaakpCQkJSV5vW7BggV44okn3L9PnDiBXr164aOPPkLr1q0DKSKDwWAwGAwGg8GowVwXTh+ysrIEv6OiogAAubm5yMjICIZIDAaDwWAwGAwGowZw3cVhYjAYDAaDwWAwGIzK4rpYYRKTnZ2N68C5H4PBYDAYDAaDwbjOuS4VJl9xKVmueEzBxGaz4erVq7h48WKN3GQXbFj5Bx/2DoIPewfBhZV/8GHvILiw8g8+Nf0duHQCbwsxNUphunTpEgAgMzMzyJIwGAwGg8FgMBiMqsClS5cQGxureP66CFzrL3iex4kTJxAdHQ2O44Iqiysm1NGjR4MeE6omwso/+LB3EHzYOwgurPyDD3sHwYWVf/Cp6e+AEIJLly4hPT0dBoOya4catcJkMBiqnFe9mJiYGllBqwqs/IMPewfBh72D4MLKP/iwdxBcWPkHn5r8DtRWllwwL3kMBoPBYDAYDAaDoQBTmBgMBoPBYDAYDAZDAaYwBYnQ0FDMnj0boaGhwRalRsLKP/iwdxB82DsILqz8gw97B8GFlX/wYe9AGzXK6QODwWAwGAwGg8Fg6IGtMDEYDAaDwWAwGAyGAkxhYjAYDAaDwWAwGAwFmMLEYDAYDAaDwWAwGAowhYnBYDAYDAaDwWAwFGAKUxB47bXXkJOTg7CwMLRo0QLr168PtkjVhnXr1qF///5IT08Hx3H4/PPPBecJIZgzZw7S09MRHh6OLl26YPfu3YJrLBYL7rnnHiQlJSEyMhIDBgzAsWPHKvEprl/mzZuHli1bIjo6GsnJyRg0aBD27t0ruIa9g8Dx+uuvo0mTJu4AhG3btsXXX3/tPs/KvnKZN28eOI7D1KlT3cfYOwgsc+bMAcdxgn+pqanu86z8K4fjx4/j1ltvRWJiIiIiIlBUVIQtW7a4z7P3EFiys7Ml3wHHcbj77rsBsPL3CcKoVJYuXUrMZjN5++23yZ49e8iUKVNIZGQkOXz4cLBFqxasWLGCzJo1iyxbtowAIJ999png/Pz580l0dDRZtmwZ2blzJxk6dChJS0sjFy9edF8zceJEUrt2bbJq1Sry66+/kq5du5KmTZsSu91eyU9z/dGrVy+yaNEismvXLrJt2zbSt29fkpWVRS5fvuy+hr2DwLF8+XLy3//+l+zdu5fs3buXPPTQQ8RsNpNdu3YRQljZVyabNm0i2dnZpEmTJmTKlCnu4+wdBJbZs2eTxo0bk5MnT7r/nT592n2elX/gOXv2LKlTpw4ZPXo0+fnnn8nBgwfJt99+S/7880/3New9BJbTp08LvoFVq1YRAOT7778nhLDy9wWmMFUyrVq1IhMnThQca9iwIZk5c2aQJKq+iBUmnudJamoqmT9/vvtYWVkZiY2NJW+88QYhhJDz588Ts9lMli5d6r7m+PHjxGAwkP/973+VJnt14fTp0wQAWbt2LSGEvYNgEB8fT9555x1W9pXIpUuXSP369cmqVatI586d3QoTeweBZ/bs2aRp06ay51j5Vw4PPPAA6dChg+J59h4qnylTppDc3FzC8zwrfx9hJnmViNVqxZYtW9CzZ0/B8Z49e+LHH38MklQ1h4MHD+Kvv/4SlH9oaCg6d+7sLv8tW7bAZrMJrklPT0dBQQF7Rz5w4cIFAEBCQgIA9g4qE4fDgaVLl+LKlSto27YtK/tK5O6770bfvn3Ro0cPwXH2DiqHffv2IT09HTk5Objllltw4MABAKz8K4vly5ejuLgYgwcPRnJyMpo1a4a3337bfZ69h8rFarViyZIlGDt2LDiOY+XvI0xhqkT+/vtvOBwOpKSkCI6npKTgr7/+CpJUNQdXGauV/19//YWQkBDEx8crXsPQBiEE9957Lzp06ICCggIA7B1UBjt37kRUVBRCQ0MxceJEfPbZZ2jUqBEr+0pi6dKl+PXXXzFv3jzJOfYOAk/r1q3x/vvv45tvvsHbb7+Nv/76C+3atcM///zDyr+SOHDgAF5//XXUr18f33zzDSZOnIjJkyfj/fffB8C+g8rm888/x/nz5zF69GgArPx9xRRsAWoiHMcJfhNCJMcYgcOX8mfvSD+TJk3Cjh07sGHDBsk59g4CR15eHrZt24bz589j2bJlGDVqFNauXes+z8o+cBw9ehRTpkzBypUrERYWpngdeweBo0+fPu6/CwsL0bZtW+Tm5uK9995DmzZtALDyDzQ8z6O4uBhPPfUUAKBZs2bYvXs3Xn/9ddx2223u69h7qBwWLlyIPn36ID09XXCclb8+2ApTJZKUlASj0SjRzk+fPi3R9Bn+x+UpSa38U1NTYbVace7cOcVrGN655557sHz5cnz//ffIyMhwH2fvIPCEhISgXr16KC4uxrx589C0aVO89NJLrOwrgS1btuD06dNo0aIFTCYTTCYT1q5diwULFsBkMrnLkL2DyiMyMhKFhYXYt28f+wYqibS0NDRq1EhwLD8/H0eOHAHA+oHK5PDhw/j2228xfvx49zFW/r7BFKZKJCQkBC1atMCqVasEx1etWoV27doFSaqaQ05ODlJTUwXlb7VasXbtWnf5t2jRAmazWXDNyZMnsWvXLvaONEAIwaRJk/Dpp5/iu+++Q05OjuA8eweVDyEEFouFlX0l0L17d+zcuRPbtm1z/ysuLsaIESOwbds21K1bl72DSsZiseC3335DWloa+wYqifbt20vCSfzxxx+oU6cOANYPVCaLFi1CcnIy+vbt6z7Gyt9HKtvLRE3H5VZ84cKFZM+ePWTq1KkkMjKSHDp0KNiiVQsuXbpEtm7dSrZu3UoAkBdeeIFs3brV7bZ9/vz5JDY2lnz66adk586dZNiwYbKuNDMyMsi3335Lfv31V9KtW7ca7UpTD3feeSeJjY0la9asEbg0vXr1qvsa9g4Cx4MPPkjWrVtHDh48SHbs2EEeeughYjAYyMqVKwkhrOyDAe0ljxD2DgLN9OnTyZo1a8iBAwfIxo0bSb9+/Uh0dLS7j2XlH3g2bdpETCYTefLJJ8m+ffvIv//9bxIREUGWLFnivoa9h8DjcDhIVlYWeeCBByTnWPnrhylMQeDVV18lderUISEhIaR58+Zul8uMivP9998TAJJ/o0aNIoQ43ZnOnj2bpKamktDQUNKpUyeyc+dOQRrXrl0jkyZNIgkJCSQ8PJz069ePHDlyJAhPc/0hV/YAyKJFi9zXsHcQOMaOHetuW2rVqkW6d+/uVpYIYWUfDMQKE3sHgcUVT8ZsNpP09HRy4403kt27d7vPs/KvHL788ktSUFBAQkNDScOGDclbb70lOM/eQ+D55ptvCACyd+9eyTlW/vrhCCEkKEtbDAaDwWAwGAwGg1HFYXuYGAwGg8FgMBgMBkMBpjAxGAwGg8FgMBgMhgJMYWIwGAwGg8FgMBgMBZjCxGAwGAwGg8FgMBgKMIWJwWAwGAwGg8FgMBRgChODwWAwGAwGg8FgKMAUJgaDwWAwGAwGg8FQgClMDAaDwWAwGAwGg6EAU5gYDAaDUenMmTMHRUVFlZ7vmjVrwHEcOI7DoEGDVK/t0qULpk6dWilyufJzybZt27ZKy5fBYDAY6piCLQCDwWAwqhccx6meHzVqFF555RXcc889lSSRlL179yI5OTlo+cvx6aefYv/+/WjVqlWwRWEwGAwGBVOYGAwGg+FXTp486f77o48+wqOPPoq9e/e6j4WHhyMqKgpRUVHBEA8AkJycjLi4uKDlL0dCQgIuXrwYbDEYDAaDIYKZ5DEYDAbDr6Smprr/xcbGguM4yTGxSd7o0aMxaNAgPPXUU0hJSUFcXBwee+wx2O12zJgxAwkJCcjIyMC7774ryOv48eMYOnQo4uPjkZiYiIEDB+LQoUO6Zb5y5Qpuu+02REVFIS0tDc8//7zkmiVLlqC4uBjR0dFITU3F8OHDcfr0aQAAIQT16tXDc889J7hn165dMBgM2L9/PwCnKWJWVhZCQ0ORnp6OyZMn65aVwWAwGJULU5gYDAaDUSX47rvvcOLECaxbtw4vvPAC5syZg379+iE+Ph4///wzJk6ciIkTJ+Lo0aMAgKtXr6Jr166IiorCunXrsGHDBkRFRaF3796wWq268p4xYwa+//57fPbZZ1i5ciXWrFmDLVu2CK6xWq2YO3cutm/fjs8//xwHDx7E6NGjATjNEMeOHYtFixYJ7nn33XfRsWNH5Obm4pNPPsGLL76IN998E/v27cPnn3+OwsJC3wuMwWAwGJUCU5gYDAaDUSVISEjAggULkJeXh7FjxyIvLw9Xr17FQw89hPr16+PBBx9ESEgIfvjhBwDA0qVLYTAY8M4776CwsBD5+flYtGgRjhw5gjVr1mjO9/Lly1i4cCGee+45lJSUoLCwEO+99x4cDofgurFjx6JPnz6oW7cu2rRpgwULFuDrr7/G5cuXAQBjxozB3r17sWnTJgCAzWbDkiVLMHbsWADAkSNHkJqaih49eiArKwutWrXChAkT/FByDAaDwQgkTGFiMBgMRpWgcePGMBg83VJKSopgBcZoNCIxMdFtBrdlyxb8+eefiI6Odu+JSkhIQFlZmdsETgv79++H1WpF27Zt3ccSEhKQl5cnuG7r1q0YOHAg6tSpg+joaHTp0gWAUxECgLS0NPTt29dtNvjVV1+hrKwMgwcPBgAMHjwY165dQ926dTFhwgR89tlnsNvtOkqIwWAwGMGAKUwMBoPBqBKYzWbBb47jZI/xPA8A4HkeLVq0wLZt2wT//vjjDwwfPlxzvoQQr9dcuXIFPXv2RFRUFJYsWYLNmzfjs88+AwCB+d/48eOxdOlSXLt2DYsWLcLQoUMREREBAMjMzMTevXvx6quvIjw8HHfddRc6deoEm82mWVYGg8FgVD7MSx6DwWAwrkuaN2+Ojz76CMnJyYiJifE5nXr16sFsNmPjxo3IysoCAJw7dw5//PEHOnfuDAD4/fff8ffff2P+/PnIzMwEAPzyyy+StEpLSxEZGYnXX38dX3/9NdatWyc4Hx4ejgEDBmDAgAG4++670bBhQ+zcuRPNmzf3WX4Gg8FgBBa2wsRgMBiM65IRI0YgKSkJAwcOxPr163Hw4EGsXbsWU6ZMwbFjxzSnExUVhXHjxmHGjBlYvXo1du3ahdGjRwvMA7OyshASEoKXX34ZBw4cwPLlyzF37lxJWkajEaNHj8aDDz6IevXqCcz8Fi9ejIULF2LXrl04cOAA/vWvfyE8PBx16tSpWEEwGAwGI6AwhYnBYDAY1yURERFYt24dsrKycOONNyI/Px9jx47FtWvXdK84Pfvss+jUqRMGDBiAHj16oEOHDmjRooX7fK1atbB48WJ8/PHHaNSoEebPny9xIe5i3LhxsFqtbmcPLuLi4vD222+jffv2aNKkCVavXo0vv/wSiYmJ+h+ewWAwGJUGR7QYbzMYDAaDUQ1Ys2YNunbtinPnzgUscO0PP/yALl264NixY0hJSdF176FDh5CTk4OtW7cK4lQxGAwGI3iwFSYGg8Fg1DgyMjIwbNgwv6ZpsVjw559/4pFHHsGQIUN0K0t9+vRB48aN/SoTg8FgMCoOW2FiMBgMRo3h2rVrOH78OADn3qXU1FS/pb148WKMGzcORUVFWL58OWrXrq3r/uPHj+PatWsAPHumGAwGgxF8mMLEYDAYDAaDwWAwGAowkzwGg8FgMBgMBoPBUIApTAwGg8FgMBgMBoOhAFOYGAwGg8FgMBgMBkMBpjAxGAwGg8FgMBgMhgJMYWIwGAwGg8FgMBgMBZjCxGAwGAwGg8FgMBgKMIWJwWAwGAwGg8FgMBRgChODwWAwGAwGg8FgKPD/Y2aK+KE/vhkAAAAASUVORK5CYII="/>
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 3.5:</b>
+<p>
+<ul>
+<li><p>What can you conclude from this ACF?</p>
+</li>
+<li><p>Is the AR(1) model a good fit to the residuals?</p>
+</li>
+<li><p>What would you do if the AR(1) model is not a good fit to the residuals?</p>
+</li>
+</ul>
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<p><em>Your answer here.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Solution:</b>
+<p>
+No autocorrelation in the residuals of the AR(1) model, so the AR(1) model is a good fit to the residuals. If the AR(1) model is not a good fit to the residuals we could try a higher order AR model.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-4:-Report-the-results">Part 4: Report the results<a class="anchor-link" href="#Part-4:-Report-the-results">¶</a></h2><p><em>This part is optional because it is not part of the book, and is not part of the exam material. However, it is a nice exercise to see how the uncertainty in our model parameters can be computed for situations where the observations are <strong>not</strong> independent. This is different from Q1 when we studied observation theory models with an assumption of independent observations. Maybe we will also (optionally) use this on Friday...</em></p>
+<p>Now that we have found the periodic signals in the data and fitted an AR model to the residuals, we can report the results. By combining including the AR (noise) process, we get residuals that are white noise. When the model hat white noise residuals, we can also report the confidence intervals of the model.</p>
+<p>We will use the unbiased estimate of the variance of the residuals to calculate the confidence intervals. The unbiased estimate of the variance is given by:</p>
+$$\hat{\sigma}^2 = \frac{1}{n-p} \sum_{t=1}^{n} \hat{e}_t^2$$<p>Where $n$ is the number of observations and $p$ is the number of parameters in the model.</p>
+<p>The covariance matrix of the parameters is given by:</p>
+$$\hat{\Sigma} = \hat{\sigma}^2 (\mathbf{A}^T \mathbf{A})^{-1}$$<p>Where $\mathbf{A}$ is the design matrix of the model.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p> <b>Task 4.1:</b>
+<p>
+Complete the missing parts of the code cell below.
+</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># combine ar1 and seasonal model</span>
+
+<span class="n">A_final</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span><span class="n">A</span><span class="p">[</span><span class="mi">1</span><span class="p">:,:],</span> <span class="n">e_hat</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
+<span class="n">x_hat</span><span class="p">,</span> <span class="n">y_hat</span><span class="p">,</span> <span class="n">e_hat_final</span> <span class="o">=</span> <span class="n">fit_model</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">time</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">A_final</span><span class="p">,</span> <span class="n">plot</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+
+<span class="c1"># compute the standard errors</span>
+<span class="n">N</span> <span class="o">=</span> <span class="n">A_final</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">p</span> <span class="o">=</span> <span class="n">A_final</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
+<span class="n">sigma2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">e_hat_final</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">N</span> <span class="o">-</span> <span class="n">p</span><span class="p">)</span>
+<span class="n">Cov</span> <span class="o">=</span> <span class="n">sigma2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">inv</span><span class="p">(</span><span class="n">A_final</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="n">A_final</span><span class="p">)</span>
+<span class="n">se</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diag</span><span class="p">(</span><span class="n">Cov</span><span class="p">))</span>
+
+<span class="c1"># Extracting the seasonal component coefficients from the estimated parameters</span>
+<span class="n">a_i</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x_hat</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">x_hat</span><span class="p">[</span><span class="mi">4</span><span class="p">]])</span>
+<span class="n">b_i</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x_hat</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">x_hat</span><span class="p">[</span><span class="mi">5</span><span class="p">]])</span>
+<span class="n">freqs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">dom_f</span><span class="p">,</span> <span class="n">dom_f2</span><span class="p">])</span>
+
+<span class="c1"># Check if the number of coefficients match the number of frequencies</span>
+<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">a_i</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">b_i</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">freqs</span><span class="p">),</span> <span class="s1">'The number of coefficients do not match'</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Estimated Parameters (standard deviation):'</span><span class="p">)</span>
+<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x_hat</span><span class="p">)):</span>
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'x</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">x_hat</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="se">\t\t</span><span class="s1"> (</span><span class="si">{</span><span class="n">se</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">)'</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">The seasonal component is rewritten as:'</span><span class="p">)</span>
+<span class="n">i</span> <span class="o">=</span> <span class="mi">0</span>
+<span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">a_i</span><span class="p">,</span> <span class="n">b_i</span><span class="p">,</span> <span class="n">freqs</span><span class="p">):</span>
+ <span class="n">A_i</span><span class="p">,</span> <span class="n">theta_i</span> <span class="o">=</span> <span class="n">rewrite_seasonal_comp</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
+ <span class="n">i</span> <span class="o">=</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span>
+ <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'A_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">A_i</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">, theta_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">theta_i</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">, f_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1"> = </span><span class="si">{</span><span class="n">f</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>Estimated Parameters (standard deviation):
+x0 = 1012.918 (0.032)
+x1 = 0.000 (0.000)
+x2 = -2.990 (0.021)
+x3 = 0.041 (0.023)
+x4 = -0.068 (0.021)
+x5 = -0.957 (0.021)
+x6 = 0.491 (0.013)
+
+The seasonal component is rewritten as:
+A_1 = 2.990, theta_1 = -3.128, f_1 = 0.003
+A_2 = 0.959, theta_2 = 1.642, f_2 = 1.000
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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+</div>
+</div>
+</div>
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+<div style="background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"> <p>Task 4.2 was moved above in the notebook, since it made more sense to interpret the parameters earlier.</p></div>
+</div>
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+<p><strong>End of notebook.</strong></p>
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+</h3>
+<span style="font-size: 75%">
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