From e2390ed8fd18f0dfe95a9ca0766c77de7775702c Mon Sep 17 00:00:00 2001
From: Lars Bogner <lars.bogner@outlook.de>
Date: Wed, 3 Sep 2025 10:03:01 +0200
Subject: [PATCH] Move to new version of the excercises for week 37

---
 doc/LectureNotes/exercisesweek36.html  |   11 +
 doc/LectureNotes/exercisesweek37.html  | 8395 ++++++++++++++++++++++++
 doc/LectureNotes/exercisesweek37.ipynb |  339 +-
 3 files changed, 8585 insertions(+), 160 deletions(-)
 create mode 100644 doc/LectureNotes/exercisesweek37.html
diff --git a/doc/LectureNotes/exercisesweek36.html b/doc/LectureNotes/exercisesweek36.html
index 477d5d6b8..334156f2f 100644
--- a/doc/LectureNotes/exercisesweek36.html
+++ b/doc/LectureNotes/exercisesweek36.html
@@ -7522,6 +7522,17 @@ a.anchor-link {
 </div>
 </div>
 </div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=6b5c366c">
+<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><strong>Python Code can be found at <a href="https://github.uio.no/larsbog/FYS-STK4155">https://github.uio.no/larsbog/FYS-STK4155</a></strong></p>
+</div>
+</div>
+</div>
+</div>
 <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=e5cc5739">
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diff --git a/doc/LectureNotes/exercisesweek37.html b/doc/LectureNotes/exercisesweek37.html
new file mode 100644
index 000000000..a2e4119de
--- /dev/null
+++ b/doc/LectureNotes/exercisesweek37.html
@@ -0,0 +1,8395 @@
+<!DOCTYPE html>
+
+<html lang="en">
+<head><meta charset="utf-8"/>
+<meta content="width=device-width, initial-scale=1.0" name="viewport"/>
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+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
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+  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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);
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+  --jp-icon-code-check: url(data:image/svg+xml;base64,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);
+  --jp-icon-code: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTExLjQgMTguNkw2LjggMTRMMTEuNCA5LjRMMTAgOEw0IDE0TDEwIDIwTDExLjQgMTguNlpNMTYuNiAxOC42TDIxLjIgMTRMMTYuNiA5LjRMMTggOEwyNCAxNEwxOCAyMEwxNi42IDE4LjZWMTguNloiLz4KCTwvZz4KPC9zdmc+Cg==);
+  --jp-icon-collapse-all: url(data:image/svg+xml;base64,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);
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+  --jp-icon-ellipses: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPGNpcmNsZSBjeD0iNSIgY3k9IjEyIiByPSIyIi8+CiAgICA8Y2lyY2xlIGN4PSIxMiIgY3k9IjEyIiByPSIyIi8+CiAgICA8Y2lyY2xlIGN4PSIxOSIgY3k9IjEyIiByPSIyIi8+CiAgPC9nPgo8L3N2Zz4K);
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+  --jp-icon-expand-all: url(data:image/svg+xml;base64,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);
+  --jp-icon-extension: url(data:image/svg+xml;base64,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);
+  --jp-icon-fast-forward: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTQgMThsOC41LTZMNCA2djEyem05LTEydjEybDguNS02TDEzIDZ6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
+  --jp-icon-file-upload: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTkgMTZoNnYtNmg0bC03LTctNyA3aDR6bS00IDJoMTR2Mkg1eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+  --jp-icon-file: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkuMyA4LjJsLTUuNS01LjVjLS4zLS4zLS43LS41LTEuMi0uNUgzLjljLS44LjEtMS42LjktMS42IDEuOHYxNC4xYzAgLjkuNyAxLjYgMS42IDEuNmgxNC4yYy45IDAgMS42LS43IDEuNi0xLjZWOS40Yy4xLS41LS4xLS45LS40LTEuMnptLTUuOC0zLjNsMy40IDMuNmgtMy40VjQuOXptMy45IDEyLjdINC43Yy0uMSAwLS4yIDAtLjItLjJWNC43YzAtLjIuMS0uMy4yLS4zaDcuMnY0LjRzMCAuOC4zIDEuMWMuMy4zIDEuMS4zIDEuMS4zaDQuM3Y3LjJzLS4xLjItLjIuMnoiLz4KPC9zdmc+Cg==);
+  --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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);
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+  --jp-icon-home: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjRweCIgdmlld0JveD0iMCAwIDI0IDI0IiB3aWR0aD0iMjRweCIgZmlsbD0iIzAwMDAwMCI+CiAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPjxwYXRoIGNsYXNzPSJqcC1pY29uMyBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xMCAyMHYtNmg0djZoNXYtOGgzTDEyIDMgMiAxMmgzdjh6Ii8+Cjwvc3ZnPgo=);
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+  --jp-icon-info: url(data:image/svg+xml;base64,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);
+  --jp-icon-inspector: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaW5zcGVjdG9yLWljb24tY29sb3IganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMjAgNEg0Yy0xLjEgMC0xLjk5LjktMS45OSAyTDIgMThjMCAxLjEuOSAyIDIgMmgxNmMxLjEgMCAyLS45IDItMlY2YzAtMS4xLS45LTItMi0yem0tNSAxNEg0di00aDExdjR6bTAtNUg0VjloMTF2NHptNSA1aC00VjloNHY5eiIvPgo8L3N2Zz4K);
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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,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);
+  --jp-icon-new-folder: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIwIDZoLThsLTItMkg0Yy0xLjExIDAtMS45OS44OS0xLjk5IDJMMiAxOGMwIDEuMTEuODkgMiAyIDJoMTZjMS4xMSAwIDItLjg5IDItMlY4YzAtMS4xMS0uODktMi0yLTJ6bS0xIDhoLTN2M2gtMnYtM2gtM3YtMmgzVjloMnYzaDN2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+  --jp-icon-not-trusted: url(data:image/svg+xml;base64,PHN2ZyBmaWxsPSJub25lIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI1IDI1Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgc3Ryb2tlPSIjMzMzMzMzIiBzdHJva2Utd2lkdGg9IjIiIHRyYW5zZm9ybT0idHJhbnNsYXRlKDMgMykiIGQ9Ik0xLjg2MDk0IDExLjQ0MDlDMC44MjY0NDggOC43NzAyNyAwLjg2Mzc3OSA2LjA1NzY0IDEuMjQ5MDcgNC4xOTkzMkMyLjQ4MjA2IDMuOTMzNDcgNC4wODA2OCAzLjQwMzQ3IDUuNjAxMDIgMi44NDQ5QzcuMjM1NDkgMi4yNDQ0IDguODU2NjYgMS41ODE1IDkuOTg3NiAxLjA5NTM5QzExLjA1OTcgMS41ODM0MSAxMi42MDk0IDIuMjQ0NCAxNC4yMTggMi44NDMzOUMxNS43NTAzIDMuNDEzOTQgMTcuMzk5NSAzLjk1MjU4IDE4Ljc1MzkgNC4yMTM4NUMxOS4xMzY0IDYuMDcxNzcgMTkuMTcwOSA4Ljc3NzIyIDE4LjEzOSAxMS40NDA5QzE3LjAzMDMgMTQuMzAzMiAxNC42NjY4IDE3LjE4NDQgOS45OTk5OSAxOC45MzU0QzUuMzMzMTkgMTcuMTg0NCAyLjk2OTY4IDE0LjMwMzIgMS44NjA5NCAxMS40NDA5WiIvPgogICAgPHBhdGggY2xhc3M9ImpwLWljb24yIiBzdHJva2U9IiMzMzMzMzMiIHN0cm9rZS13aWR0aD0iMiIgdHJhbnNmb3JtPSJ0cmFuc2xhdGUoOS4zMTU5MiA5LjMyMDMxKSIgZD0iTTcuMzY4NDIgMEwwIDcuMzY0NzkiLz4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgc3Ryb2tlPSIjMzMzMzMzIiBzdHJva2Utd2lkdGg9IjIiIHRyYW5zZm9ybT0idHJhbnNsYXRlKDkuMzE1OTIgMTYuNjgzNikgc2NhbGUoMSAtMSkiIGQ9Ik03LjM2ODQyIDBMMCA3LjM2NDc5Ii8+Cjwvc3ZnPgo=);
+  --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,PHN2ZyB2aWV3Qm94PSIwIDAgMTggMTgiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjEsMTAuOWgtMC43bC0wLjItMC4yYzAuOC0wLjksMS4zLTIuMiwxLjMtMy41YzAtMy0yLjQtNS40LTUuNC01LjRTMS44LDQuMiwxLjgsNy4xczIuNCw1LjQsNS40LDUuNCBjMS4zLDAsMi41LTAuNSwzLjUtMS4zbDAuMiwwLjJ2MC43bDQuMSw0LjFsMS4yLTEuMkwxMi4xLDEwLjl6IE03LjEsMTAuOWMtMi4xLDAtMy43LTEuNy0zLjctMy43czEuNy0zLjcsMy43LTMuN3MzLjcsMS43LDMuNywzLjcgUzkuMiwxMC45LDcuMSwxMC45eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+  --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,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0IiA+CiAgICA8cmVjdCBjbGFzcz0ianAtdGVybWluYWwtaWNvbi1iYWNrZ3JvdW5kLWNvbG9yIGpwLWljb24tc2VsZWN0YWJsZSIgd2lkdGg9IjIwIiBoZWlnaHQ9IjIwIiB0cmFuc2Zvcm09InRyYW5zbGF0ZSgyIDIpIiBmaWxsPSIjMzMzMzMzIi8+CiAgICA8cGF0aCBjbGFzcz0ianAtdGVybWluYWwtaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUtaW52ZXJzZSIgZD0iTTUuMDU2NjQgOC43NjE3MkM1LjA1NjY0IDguNTk3NjYgNS4wMzEyNSA4LjQ1MzEyIDQuOTgwNDcgOC4zMjgxMkM0LjkzMzU5IDguMTk5MjIgNC44NTU0NyA4LjA4MjAzIDQuNzQ2MDkgNy45NzY1NkM0LjY0MDYyIDcuODcxMDkgNC41IDcuNzc1MzkgNC4zMjQyMiA3LjY4OTQ1QzQuMTUyMzQgNy41OTk2MSAzLjk0MzM2IDcuNTExNzIgMy42OTcyNyA3LjQyNTc4QzMuMzAyNzMgNy4yODUxNiAyLjk0MzM2IDcuMTM2NzIgMi42MTkxNCA2Ljk4MDQ3QzIuMjk0OTIgNi44MjQyMiAyLjAxNzU4IDYuNjQyNTggMS43ODcxMSA2LjQzNTU1QzEuNTYwNTUgNi4yMjg1MiAxLjM4NDc3IDUuOTg4MjggMS4yNTk3NyA1LjcxNDg0QzEuMTM0NzcgNS40Mzc1IDEuMDcyMjcgNS4xMDkzOCAxLjA3MjI3IDQuNzMwNDdDMS4wNzIyNyA0LjM5ODQ0IDEuMTI4OTEgNC4wOTU3IDEuMjQyMTkgMy44MjIyN0MxLjM1NTQ3IDMuNTQ0OTIgMS41MTU2MiAzLjMwNDY5IDEuNzIyNjYgMy4xMDE1NkMxLjkyOTY5IDIuODk4NDQgMi4xNzk2OSAyLjczNDM3IDIuNDcyNjYgMi42MDkzOEMyLjc2NTYyIDIuNDg0MzggMy4wOTE4IDIuNDA0MyAzLjQ1MTE3IDIuMzY5MTRWMS4xMDkzOEg0LjM4ODY3VjIuMzgwODZDNC43NDAyMyAyLjQyNzczIDUuMDU2NjQgMi41MjM0NCA1LjMzNzg5IDIuNjY3OTdDNS42MTkxNCAyLjgxMjUgNS44NTc0MiAzLjAwMTk1IDYuMDUyNzMgMy4yMzYzM0M2LjI1MTk1IDMuNDY2OCA2LjQwNDMgMy43NDAyMyA2LjUwOTc3IDQuMDU2NjRDNi42MTkxNCA0LjM2OTE0IDYuNjczODMgNC43MjA3IDYuNjczODMgNS4xMTEzM0g1LjA0NDkyQzUuMDQ0OTIgNC42Mzg2NyA0LjkzNzUgNC4yODEyNSA0LjcyMjY2IDQuMDM5MDZDNC41MDc4MSAzLjc5Mjk3IDQuMjE2OCAzLjY2OTkyIDMuODQ5NjEgMy42Njk5MkMzLjY1MDM5IDMuNjY5OTIgMy40NzY1NiAzLjY5NzI3IDMuMzI4MTIgMy43NTE5NUMzLjE4MzU5IDMuODAyNzMgMy4wNjQ0NSAzLjg3Njk1IDIuOTcwNyAzLjk3NDYxQzIuODc2OTUgNC4wNjgzNiAyLjgwNjY0IDQuMTc5NjkgMi43NTk3NyA0LjMwODU5QzIuNzE2OCA0LjQzNzUgMi42OTUzMSA0LjU3ODEyIDIuNjk1MzEgNC43MzA0N0MyLjY5NTMxIDQuODgyODEgMi43MTY4IDUuMDE5NTMgMi43NTk3NyA1LjE0MDYyQzIuODA2NjQgNS4yNTc4MSAyLjg4MjgxIDUuMzY3MTkgMi45ODgyOCA1LjQ2ODc1QzMuMDk3NjYgNS41NzAzMSAzLjI0MDIzIDUuNjY3OTcgMy40MTYwMiA1Ljc2MTcyQzMuNTkxOCA1Ljg1MTU2IDMuODEwNTUgNS45NDMzNiA0LjA3MjI3IDYuMDM3MTFDNC40NjY4IDYuMTg1NTUgNC44MjQyMiA2LjMzOTg0IDUuMTQ0NTMgNi41QzUuNDY0ODQgNi42NTYyNSA1LjczODI4IDYuODM5ODQgNS45NjQ4NCA3LjA1MDc4QzYuMTk1MzEgNy4yNTc4MSA2LjM3MTA5IDcuNSA2LjQ5MjE5IDcuNzc3MzRDNi42MTcxOSA4LjA1MDc4IDYuNjc5NjkgOC4zNzUgNi42Nzk2OSA4Ljc1QzYuNjc5NjkgOS4wOTM3NSA2LjYyMzA1IDkuNDA0MyA2LjUwOTc3IDkuNjgxNjRDNi4zOTY0OCA5Ljk1NTA4IDYuMjM0MzggMTAuMTkxNCA2LjAyMzQ0IDEwLjM5MDZDNS44MTI1IDEwLjU4OTggNS41NTg1OSAxMC43NSA1LjI2MTcyIDEwLjg3MTFDNC45NjQ4NCAxMC45ODgzIDQuNjMyODEgMTEuMDY0NSA0LjI2NTYyIDExLjA5OTZWMTIuMjQ4SDMuMzMzOThWMTEuMDk5NkMzLjAwMTk1IDExLjA2ODQgMi42Nzk2OSAxMC45OTYxIDIuMzY3MTkgMTAuODgyOEMyLjA1NDY5IDEwLjc2NTYgMS43NzczNCAxMC41OTc3IDEuNTM1MTYgMTAuMzc4OUMxLjI5Njg4IDEwLjE2MDIgMS4xMDU0NyA5Ljg4NDc3IDAuOTYwOTM4IDkuNTUyNzNDMC44MTY0MDYgOS4yMTY4IDAuNzQ0MTQxIDguODE0NDUgMC43NDQxNDEgOC4zNDU3SDIuMzc4OTFDMi4zNzg5MSA4LjYyNjk1IDIuNDE5OTIgOC44NjMyOCAyLjUwMTk1IDkuMDU0NjlDMi41ODM5OCA5LjI0MjE5IDIuNjg5NDUgOS4zOTI1OCAyLjgxODM2IDkuNTA1ODZDMi45NTExNyA5LjYxNTIzIDMuMTAxNTYgOS42OTMzNiAzLjI2OTUzIDkuNzQwMjNDMy40Mzc1IDkuNzg3MTEgMy42MDkzOCA5LjgxMDU1IDMuNzg1MTYgOS44MTA1NUM0LjIwMzEyIDkuODEwNTUgNC41MTk1MyA5LjcxMjg5IDQuNzM0MzggOS41MTc1OEM0Ljk0OTIyIDkuMzIyMjcgNS4wNTY2NCA5LjA3MDMxIDUuMDU2NjQgOC43NjE3MlpNMTMuNDE4IDEyLjI3MTVIOC4wNzQyMlYxMUgxMy40MThWMTIuMjcxNVoiIHRyYW5zZm9ybT0idHJhbnNsYXRlKDMuOTUyNjQgNikiIGZpbGw9IndoaXRlIi8+Cjwvc3ZnPgo=);
+  --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==);
+  --jp-icon-toc: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik03LDVIMjFWN0g3VjVNNywxM1YxMUgyMVYxM0g3TTQsNC41QTEuNSwxLjUgMCAwLDEgNS41LDZBMS41LDEuNSAwIDAsMSA0LDcuNUExLjUsMS41IDAgMCwxIDIuNSw2QTEuNSwxLjUgMCAwLDEgNCw0LjVNNCwxMC41QTEuNSwxLjUgMCAwLDEgNS41LDEyQTEuNSwxLjUgMCAwLDEgNCwxMy41QTEuNSwxLjUgMCAwLDEgMi41LDEyQTEuNSwxLjUgMCAwLDEgNCwxMC41TTcsMTlWMTdIMjFWMTlIN000LDE2LjVBMS41LDEuNSAwIDAsMSA1LjUsMThBMS41LDEuNSAwIDAsMSA0LDE5LjVBMS41LDEuNSAwIDAsMSAyLjUsMThBMS41LDEuNSAwIDAsMSA0LDE2LjVaIiAvPgogIDwvZz4KPC9zdmc+Cg==);
+  --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,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);
+}
+
+/* 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;
+}
+
+.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',
+    'Segoe UI Emoji', 'Segoe UI Symbol';
+
+  /*
+   * Code Fonts
+   *
+   * Code font variables are used for typography of code and other monospaces content.
+   */
+
+  --jp-code-font-size: 13px;
+  --jp-code-line-height: 1.3077; /* 17px for 13px base */
+  --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */
+  --jp-code-font-family-default: menlo, consolas, 'DejaVu Sans Mono', monospace;
+  --jp-code-font-family: var(--jp-code-font-family-default);
+
+  /* This gives a magnification of about 125% in presentation mode over normal. */
+  --jp-code-presentation-font-size: 16px;
+
+  /* may need to tweak cursor width if you change font size */
+  --jp-code-cursor-width0: 1.4px;
+  --jp-code-cursor-width1: 2px;
+  --jp-code-cursor-width2: 4px;
+
+  /* Layout
+   *
+   * The following are the main layout colors use in JupyterLab. In a light
+   * theme these would go from light to dark.
+   */
+
+  --jp-layout-color0: white;
+  --jp-layout-color1: white;
+  --jp-layout-color2: var(--md-grey-200);
+  --jp-layout-color3: var(--md-grey-400);
+  --jp-layout-color4: var(--md-grey-600);
+
+  /* Inverse Layout
+   *
+   * The following are the inverse layout colors use in JupyterLab. In a light
+   * theme these would go from dark to light.
+   */
+
+  --jp-inverse-layout-color0: #111;
+  --jp-inverse-layout-color1: var(--md-grey-900);
+  --jp-inverse-layout-color2: var(--md-grey-800);
+  --jp-inverse-layout-color3: var(--md-grey-700);
+  --jp-inverse-layout-color4: var(--md-grey-600);
+
+  /* Brand/accent */
+
+  --jp-brand-color0: var(--md-blue-900);
+  --jp-brand-color1: var(--md-blue-700);
+  --jp-brand-color2: var(--md-blue-300);
+  --jp-brand-color3: var(--md-blue-100);
+  --jp-brand-color4: var(--md-blue-50);
+  --jp-accent-color0: var(--md-green-900);
+  --jp-accent-color1: var(--md-green-700);
+  --jp-accent-color2: var(--md-green-300);
+  --jp-accent-color3: var(--md-green-100);
+
+  /* State colors (warn, error, success, info) */
+
+  --jp-warn-color0: var(--md-orange-900);
+  --jp-warn-color1: var(--md-orange-700);
+  --jp-warn-color2: var(--md-orange-300);
+  --jp-warn-color3: var(--md-orange-100);
+  --jp-error-color0: var(--md-red-900);
+  --jp-error-color1: var(--md-red-700);
+  --jp-error-color2: var(--md-red-300);
+  --jp-error-color3: var(--md-red-100);
+  --jp-success-color0: var(--md-green-900);
+  --jp-success-color1: var(--md-green-700);
+  --jp-success-color2: var(--md-green-300);
+  --jp-success-color3: var(--md-green-100);
+  --jp-info-color0: var(--md-cyan-900);
+  --jp-info-color1: var(--md-cyan-700);
+  --jp-info-color2: var(--md-cyan-300);
+  --jp-info-color3: var(--md-cyan-100);
+
+  /* Cell specific styles */
+
+  --jp-cell-padding: 5px;
+  --jp-cell-collapser-width: 8px;
+  --jp-cell-collapser-min-height: 20px;
+  --jp-cell-collapser-not-active-hover-opacity: 0.6;
+  --jp-cell-editor-background: var(--md-grey-100);
+  --jp-cell-editor-border-color: var(--md-grey-300);
+  --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300);
+  --jp-cell-editor-active-background: var(--jp-layout-color0);
+  --jp-cell-editor-active-border-color: var(--jp-brand-color1);
+  --jp-cell-prompt-width: 64px;
+  --jp-cell-prompt-font-family: var(--jp-code-font-family-default);
+  --jp-cell-prompt-letter-spacing: 0;
+  --jp-cell-prompt-opacity: 1;
+  --jp-cell-prompt-not-active-opacity: 0.5;
+  --jp-cell-prompt-not-active-font-color: var(--md-grey-700);
+
+  /* A custom blend of MD grey and blue 600
+   * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */
+  --jp-cell-inprompt-font-color: #307fc1;
+
+  /* A custom blend of MD grey and orange 600
+   * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
+  --jp-cell-outprompt-font-color: #bf5b3d;
+
+  /* Notebook specific styles */
+
+  --jp-notebook-padding: 10px;
+  --jp-notebook-select-background: var(--jp-layout-color1);
+  --jp-notebook-multiselected-color: var(--md-blue-50);
+
+  /* The scroll padding is calculated to fill enough space at the bottom of the
+  notebook to show one single-line cell (with appropriate padding) at the top
+  when the notebook is scrolled all the way to the bottom. We also subtract one
+  pixel so that no scrollbar appears if we have just one single-line cell in the
+  notebook. This padding is to enable a 'scroll past end' feature in a notebook.
+  */
+  --jp-notebook-scroll-padding: calc(
+    100% - var(--jp-code-font-size) * var(--jp-code-line-height) -
+      var(--jp-code-padding) - var(--jp-cell-padding) - 1px
+  );
+
+  /* Rendermime styles */
+
+  --jp-rendermime-error-background: #fdd;
+  --jp-rendermime-table-row-background: var(--md-grey-100);
+  --jp-rendermime-table-row-hover-background: var(--md-light-blue-50);
+
+  /* Dialog specific styles */
+
+  --jp-dialog-background: rgba(0, 0, 0, 0.25);
+
+  /* Console specific styles */
+
+  --jp-console-padding: 10px;
+
+  /* Toolbar specific styles */
+
+  --jp-toolbar-border-color: var(--jp-border-color1);
+  --jp-toolbar-micro-height: 8px;
+  --jp-toolbar-background: var(--jp-layout-color1);
+  --jp-toolbar-box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.24);
+  --jp-toolbar-header-margin: 4px 4px 0 4px;
+  --jp-toolbar-active-background: var(--md-grey-300);
+
+  /* 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);
+  --jp-input-background: var(--md-grey-100);
+  --jp-input-border-color: var(--jp-inverse-border-color);
+  --jp-input-active-border-color: var(--jp-brand-color1);
+  --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3);
+
+  /* General editor styles */
+
+  --jp-editor-selected-background: #d9d9d9;
+  --jp-editor-selected-focused-background: #d7d4f0;
+  --jp-editor-cursor-color: var(--jp-ui-font-color0);
+
+  /* Code mirror specific styles */
+
+  --jp-mirror-editor-keyword-color: #008000;
+  --jp-mirror-editor-atom-color: #88f;
+  --jp-mirror-editor-number-color: #080;
+  --jp-mirror-editor-def-color: #00f;
+  --jp-mirror-editor-variable-color: var(--md-grey-900);
+  --jp-mirror-editor-variable-2-color: rgb(0, 54, 109);
+  --jp-mirror-editor-variable-3-color: #085;
+  --jp-mirror-editor-punctuation-color: #05a;
+  --jp-mirror-editor-property-color: #05a;
+  --jp-mirror-editor-operator-color: #a2f;
+  --jp-mirror-editor-comment-color: #408080;
+  --jp-mirror-editor-string-color: #ba2121;
+  --jp-mirror-editor-string-2-color: #708;
+  --jp-mirror-editor-meta-color: #a2f;
+  --jp-mirror-editor-qualifier-color: #555;
+  --jp-mirror-editor-builtin-color: #008000;
+  --jp-mirror-editor-bracket-color: #997;
+  --jp-mirror-editor-tag-color: #170;
+  --jp-mirror-editor-attribute-color: #00c;
+  --jp-mirror-editor-header-color: blue;
+  --jp-mirror-editor-quote-color: #090;
+  --jp-mirror-editor-link-color: #00c;
+  --jp-mirror-editor-error-color: #f00;
+  --jp-mirror-editor-hr-color: #999;
+
+  /*
+    RTC user specific colors.
+    These colors are used for the cursor, username in the editor,
+    and the icon of the user.
+  */
+
+  --jp-collaborator-color1: #ffad8e;
+  --jp-collaborator-color2: #dac83d;
+  --jp-collaborator-color3: #72dd76;
+  --jp-collaborator-color4: #00e4d0;
+  --jp-collaborator-color5: #45d4ff;
+  --jp-collaborator-color6: #e2b1ff;
+  --jp-collaborator-color7: #ff9de6;
+
+  /* Vega extension styles */
+
+  --jp-vega-background: white;
+
+  /* Sidebar-related styles */
+
+  --jp-sidebar-min-width: 250px;
+
+  /* Search-related styles */
+
+  --jp-search-toggle-off-opacity: 0.5;
+  --jp-search-toggle-hover-opacity: 0.8;
+  --jp-search-toggle-on-opacity: 1;
+  --jp-search-selected-match-background-color: rgb(245, 200, 0);
+  --jp-search-selected-match-color: black;
+  --jp-search-unselected-match-background-color: var(
+    --jp-inverse-layout-color0
+  );
+  --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);
+
+  /* Icon colors that work well with light or dark backgrounds */
+  --jp-icon-contrast-color0: var(--md-purple-600);
+  --jp-icon-contrast-color1: var(--md-green-600);
+  --jp-icon-contrast-color2: var(--md-pink-600);
+  --jp-icon-contrast-color3: var(--md-blue-600);
+
+  /* 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);
+  --jp-reject-color-active: var(--md-grey-800);
+
+  /* File or activity icons and switch semantic variables */
+  --jp-jupyter-icon-color: #f37626;
+  --jp-notebook-icon-color: #f37626;
+  --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 */
+* {
+  -webkit-print-color-adjust: exact;
+}
+
+/* Misc */
+a.anchor-link {
+  display: none;
+}
+
+/* Input area styling */
+.jp-InputArea {
+  overflow: hidden;
+}
+
+.jp-InputArea-editor {
+  overflow: hidden;
+}
+
+.cm-editor.cm-s-jupyter .highlight pre {
+/* weird, but --jp-code-padding defined to be 5px but 4px horizontal padding is hardcoded for pre.cm-line */
+  padding: var(--jp-code-padding) 4px;
+  margin: 0;
+
+  font-family: inherit;
+  font-size: inherit;
+  line-height: inherit;
+  color: inherit;
+
+}
+
+.jp-OutputArea-output pre {
+  line-height: inherit;
+  font-family: inherit;
+}
+
+.jp-RenderedText pre {
+  color: var(--jp-content-font-color1);
+  font-size: var(--jp-code-font-size);
+}
+
+/* Hiding the collapser by default */
+.jp-Collapser {
+  display: none;
+}
+
+@page {
+    margin: 0.5in; /* Margin for each printed piece of paper */
+}
+
+@media print {
+  .jp-Cell-inputWrapper,
+  .jp-Cell-outputWrapper {
+    display: block;
+  }
+}
+</style>
+<!-- Load mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/latest.js?config=TeX-AMS_CHTML-full,Safe"> </script>
+<!-- MathJax configuration -->
+<script type="text/x-mathjax-config">
+    init_mathjax = function() {
+        if (window.MathJax) {
+        // MathJax loaded
+            MathJax.Hub.Config({
+                TeX: {
+                    equationNumbers: {
+                    autoNumber: "AMS",
+                    useLabelIds: true
+                    }
+                },
+                tex2jax: {
+                    inlineMath: [ ['$','$'], ["\\(","\\)"] ],
+                    displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
+                    processEscapes: true,
+                    processEnvironments: true
+                },
+                displayAlign: 'center',
+                messageStyle: 'none',
+                CommonHTML: {
+                    linebreaks: {
+                    automatic: true
+                    }
+                }
+            });
+
+            MathJax.Hub.Queue(["Typeset", MathJax.Hub]);
+        }
+    }
+    init_mathjax();
+    </script>
+<!-- End of mathjax configuration --><script type="module">
+  document.addEventListener("DOMContentLoaded", async () => {
+    const diagrams = document.querySelectorAll(".jp-Mermaid > pre.mermaid");
+    // do not load mermaidjs if not needed
+    if (!diagrams.length) {
+      return;
+    }
+    const mermaid = (await import("https://cdnjs.cloudflare.com/ajax/libs/mermaid/10.7.0/mermaid.esm.min.mjs")).default;
+    const parser = new DOMParser();
+
+    mermaid.initialize({
+      maxTextSize: 100000,
+      maxEdges: 100000,
+      startOnLoad: false,
+      fontFamily: window
+        .getComputedStyle(document.body)
+        .getPropertyValue("--jp-ui-font-family"),
+      theme: document.querySelector("body[data-jp-theme-light='true']")
+        ? "default"
+        : "dark",
+    });
+
+    let _nextMermaidId = 0;
+
+    function makeMermaidImage(svg) {
+      const img = document.createElement("img");
+      const doc = parser.parseFromString(svg, "image/svg+xml");
+      const svgEl = doc.querySelector("svg");
+      const { maxWidth } = svgEl?.style || {};
+      const firstTitle = doc.querySelector("title");
+      const firstDesc = doc.querySelector("desc");
+
+      img.setAttribute("src", `data:image/svg+xml,${encodeURIComponent(svg)}`);
+      if (maxWidth) {
+        img.width = parseInt(maxWidth);
+      }
+      if (firstTitle) {
+        img.setAttribute("alt", firstTitle.textContent);
+      }
+      if (firstDesc) {
+        const caption = document.createElement("figcaption");
+        caption.className = "sr-only";
+        caption.textContent = firstDesc.textContent;
+        return [img, caption];
+      }
+      return [img];
+    }
+
+    async function makeMermaidError(text) {
+      let errorMessage = "";
+      try {
+        await mermaid.parse(text);
+      } catch (err) {
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+<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" id="cell-id=1b638450">
+<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">
+<!-- HTML file automatically generated from DocOnce source (https://github.com/doconce/doconce/)
+doconce format html exercisesweek37.do.txt  -->
+<!-- dom:TITLE: Exercises week 37 -->
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=60060788">
+<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="Exercises-week-37">Exercises week 37<a class="anchor-link" href="#Exercises-week-37">¶</a></h1><p><strong>Implementing gradient descent for Ridge and ordinary Least Squares Regression</strong></p>
+<p>Date: <strong>September 8-12, 2025</strong></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=b5bb413f">
+<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><strong>Python Code can be found at <a href="https://github.uio.no/larsbog/FYS-STK4155">https://github.uio.no/larsbog/FYS-STK4155</a></strong></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=7cdd88e4">
+<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="Learning-goals">Learning goals<a class="anchor-link" href="#Learning-goals">¶</a></h2><p>After having completed these exercises you will have:</p>
+<ol>
+<li><p>Your own code for the implementation of the simplest gradient descent approach applied to ordinary least squares (OLS) and Ridge regression</p>
+</li>
+<li><p>Be able to compare the analytical expressions for OLS and Rudge regression with the gradient descent approach</p>
+</li>
+<li><p>Explore the role of the learning rate in the gradient descent approach and the hyperparameter $\lambda$ in Ridge regression</p>
+</li>
+<li><p>Scale the data properly</p>
+</li>
+</ol>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=0328fa2a">
+<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="Simple-one-dimensional-second-order-polynomial">Simple one-dimensional second-order polynomial<a class="anchor-link" href="#Simple-one-dimensional-second-order-polynomial">¶</a></h2><p>We start with a very simple function</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ac760265">
+<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>$$
+f(x)= 2-x+5x^2,
+$$</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=8d4b0753">
+<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>defined for $x\in [-2,2]$. You can add noise if you wish.</p>
+<p>We are going to fit this function with a polynomial ansatz. The easiest thing is to set up a second-order polynomial and see if you can fit the above function.
+Feel free to play around with higher-order polynomials.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4517d311">
+<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="Exercise-1,-scale-your-data">Exercise 1, scale your data<a class="anchor-link" href="#Exercise-1,-scale-your-data">¶</a></h2><p>Before fitting a regression model, it is good practice to normalize or
+standardize the features. This ensures all features are on a
+comparable scale, which is especially important when using
+regularization. Here we will perform standardization, scaling each
+feature to have mean 0 and standard deviation 1.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=da1834a9">
+<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="1a)">1a)<a class="anchor-link" href="#1a)">¶</a></h3><p>Compute the mean and standard deviation of each column (feature) in your design/feature matrix $\boldsymbol{X}$.
+Subtract the mean and divide by the standard deviation for each feature.</p>
+<p>We will also center the target $\boldsymbol{y}$ to mean $0$. Centering $\boldsymbol{y}$
+(and each feature) means the model does not require a separate intercept
+term, the data is shifted such that the intercept is effectively 0
+. (In practice, one could include an intercept in the model and not
+penalize it, but here we simplify by centering.)
+Choose $n=100$ data points and set up $\boldsymbol{x}, $\boldsymbol{y}$ and the design matrix $\boldsymbol{X}$.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=2fb97177">
+<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 [1]:</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="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
+
+
+<span class="k">def</span><span class="w"> </span><span class="nf">polynomial_features</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">intercept</span><span class="o">=</span><span class="kc">False</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">x</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">intercept</span><span class="p">:</span>
+        <span class="n">P</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">p</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">P</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">p</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span>
+    <span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="n">x</span><span class="p">[:,</span> <span class="n">np</span><span class="o">.</span><span class="n">newaxis</span><span class="p">],</span> <span class="n">P</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">X</span>
+
+
+<span class="n">theta_true</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="o">-</span><span class="mf">2.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">])</span>
+<span class="n">X</span> <span class="o">=</span> <span class="n">polynomial_features</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">100</span><span class="p">),</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
+<span class="n">y</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">theta_true</span><span class="nd">@X</span><span class="o">.</span><span class="n">T</span> <span class="o">+</span> <span class="mf">0.1</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">100</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=590b2fb0">
+<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 [2]:</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"># Standardize features (zero mean, unit variance for each feature)</span>
+<span class="n">X_mean</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+<span class="n">X_std</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+<span class="n">X_std</span><span class="p">[</span><span class="n">X_std</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>  <span class="c1"># safeguard to avoid division by zero for constant features</span>
+<span class="n">X_norm</span> <span class="o">=</span> <span class="p">(</span><span class="n">X</span> <span class="o">-</span> <span class="n">X_mean</span><span class="p">)</span> <span class="o">/</span> <span class="n">X_std</span>
+
+<span class="c1"># Center the target to zero mean (optional, to simplify intercept handling)</span>
+<span class="n">y_mean</span> <span class="o">=</span> <span class="n">y</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+<span class="n">y_centered</span> <span class="o">=</span> <span class="n">y</span> <span class="o">-</span> <span class="n">y_mean</span>
+
+<span class="n">n_features</span> <span class="o">=</span> <span class="n">X_norm</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">theta_true</span> <span class="o">*=</span> <span class="n">X_std</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=cf63b06e">
+<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 [3]:</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">theta_true</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 jp-OutputArea-executeResult">
+<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[3]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>array([-0.58315293,  1.50663026])</pre>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=bab1bb8d">
+<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 [4]:</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">X_std</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 jp-OutputArea-executeResult">
+<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[4]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>array([0.29157647, 0.30132605])</pre>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3b714989">
+<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 [5]:</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="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">X_norm</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">y_centered</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="s2">"Feature 1"</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="s2">"Target"</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 jp-OutputArea-executeResult">
+<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[5]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>Text(0, 0.5, 'Target')</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">
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=24dd92fc">
+<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>Fill in the necessary details.</p>
+<p>After this preprocessing, each column of $\boldsymbol{X}_{\mathrm{norm}}$ has mean zero and standard deviation $1$
+and $\boldsymbol{y}_{\mathrm{centered}}$ has mean 0. This makes the optimization landscape
+nicer and ensures the regularization penalty $\lambda \sum_j
+\theta_j^2$ in Ridge regression treats each coefficient fairly (since features are on the
+same scale).</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4ba80e16">
+<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="Exercise-2,-calculate-the-gradients">Exercise 2, calculate the gradients<a class="anchor-link" href="#Exercise-2,-calculate-the-gradients">¶</a></h2><p>Find the gradients for OLS and Ridge regression using the mean-squared error as cost/loss function.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=5e5da080">
+<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 class="alert alert-block alert-success">
+The gradients can be calculated as
+
+<p>$$
+\nabla_\theta C_{OLS} = \nabla_\theta (X\cdot\theta - y)^2 = 2 X (X\cdot \theta - y)
+$$</p>
+<p>The gradient of the Ridge cost function then directly follows as</p>
+<p>$$
+\nabla_\theta C_\mathrm{Ridge} = \nabla_\theta C_{OLS} + \nabla_\theta \lambda \theta^2 = 2 X (X\cdot \theta - y) + 2 \lambda \theta
+$$</p>
+<p>Because the factors of 2 are somewhat tedious, I will from here on use $\tilde C = \frac{C}{2}$.</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=be65f56f">
+<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="Exercise-3,-use-the-analytical-formulae-for-OLS-and-Ridge-regression-to-find-the-optimal-paramters-$%5Cboldsymbol%7B%5Ctheta%7D$">Exercise 3, use the analytical formulae for OLS and Ridge regression to find the optimal paramters $\boldsymbol{\theta}$<a class="anchor-link" href="#Exercise-3,-use-the-analytical-formulae-for-OLS-and-Ridge-regression-to-find-the-optimal-paramters-$%5Cboldsymbol%7B%5Ctheta%7D$">¶</a></h2>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=a616cdee">
+<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 [6]:</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="w"> </span><span class="nf">Ridge_parameters</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">lam</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">):</span>
+    <span class="c1"># Assumes X is scaled and has no intercept column</span>
+    <span class="k">return</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">X</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="n">X</span> <span class="o">+</span> <span class="n">lam</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="n">X</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="o">@</span> <span class="n">X</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="n">y</span>
+<span class="k">def</span><span class="w"> </span><span class="nf">OLS_parameters</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">Ridge_parameters</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">lam</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=a7256776">
+<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="c1"># Set regularization parameter, either a single value or a vector of values</span>
+<span class="n">lambda_</span> <span class="o">=</span> <span class="mf">0.1</span>
+
+<span class="c1"># Analytical form for OLS and Ridge solution: theta_Ridge = (X^T X + lambda * I)^{-1} X^T y and theta_OLS = (X^T X)^{-1} X^T y</span>
+<span class="n">I</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="n">n_features</span><span class="p">)</span>
+<span class="n">theta_closed_formRidge</span> <span class="o">=</span> <span class="n">Ridge_parameters</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">lam</span><span class="o">=</span><span class="n">lambda_</span><span class="p">)</span>
+<span class="n">theta_closed_formOLS</span> <span class="o">=</span> <span class="n">OLS_parameters</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Closed-form Ridge coefficients:"</span><span class="p">,</span> <span class="n">theta_closed_formRidge</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Closed-form OLS coefficients:"</span><span class="p">,</span> <span class="n">theta_closed_formOLS</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>Closed-form Ridge coefficients: [-0.4835408   1.41698898]
+Closed-form OLS coefficients: [-0.51267301  1.44659558]
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=b989efb9">
+<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>This computes the Ridge and OLS regression coefficients directly. The identity
+matrix $I$ has the same size as $X^T X$. It adds $\lambda$ to the diagonal of $X^T X$ for Ridge regression. We
+then invert this matrix and multiply by $X^T y$. The result
+for $\boldsymbol{\theta}$  is a NumPy array of shape (n$\_$features,) containing the
+fitted parameters $\boldsymbol{\theta}$.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=17b08af7">
+<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="3a)">3a)<a class="anchor-link" href="#3a)">¶</a></h3><p>Finalize, in the above code, the OLS and Ridge regression determination of the optimal parameters $\boldsymbol{\theta}$.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=6acd4708">
+<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="3b)">3b)<a class="anchor-link" href="#3b)">¶</a></h3><p>Explore the results as function of different values of the hyperparameter $\lambda$. See for example exercise 4 from week 36.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3edc1a2c">
+<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 [8]:</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="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
+
+<span class="n">n_lam</span> <span class="o">=</span> <span class="mi">8</span>
+<span class="n">thetas</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">n_features</span><span class="p">,</span> <span class="n">n_lam</span><span class="p">))</span>
+<span class="n">lambdas</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([[</span><span class="mi">0</span><span class="p">],</span> <span class="n">np</span><span class="o">.</span><span class="n">logspace</span><span class="p">(</span><span class="o">-</span><span class="mi">5</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">n_lam</span><span class="o">-</span><span class="mi">1</span><span class="p">)])</span>
+
+
+<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">lam</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">lambdas</span><span class="p">):</span>
+    <span class="n">thetas</span><span class="p">[:,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">Ridge_parameters</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">lam</span><span class="o">=</span><span class="n">lam</span><span class="p">)</span>
+
+<span class="n">avg_thetas</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">thetas</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+<span class="n">norm_thetas</span> <span class="o">=</span> <span class="n">thetas</span> <span class="o">-</span> <span class="n">avg_thetas</span><span class="p">[:,</span> <span class="n">np</span><span class="o">.</span><span class="n">newaxis</span><span class="p">]</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="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
+<span class="c1"># Annotation</span>
+<span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">norm_thetas</span><span class="p">,</span> <span class="n">aspect</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">'viridis'</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="n">n_features</span><span class="p">):</span>
+    <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_lam</span><span class="p">):</span>
+        <span class="n">text</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">j</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">norm_thetas</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="w"> </span><span class="n">j</span><span class="p">]</span><span class="si">:</span><span class="s2">.2e</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+                       <span class="n">ha</span><span class="o">=</span><span class="s2">"center"</span><span class="p">,</span> <span class="n">va</span><span class="o">=</span><span class="s2">"center"</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"w"</span> <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">norm_thetas</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mf">0.5</span> <span class="k">else</span> <span class="s2">"black"</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">n_features</span><span class="p">))</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">n_lam</span><span class="p">))</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">l</span><span class="si">:</span><span class="s2">.2e</span><span class="si">}</span><span class="s2">"</span> <span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">lambdas</span><span class="p">],</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">45</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Features"</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="s2">"Regularization Parameter (lambda)"</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="sa">r</span><span class="s2">"Feature Coefficients ($\theta^\lambda_i - \bar{\theta}_i$)"</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 jp-OutputArea-executeResult">
+<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[8]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>Text(0.5, 1.0, 'Feature Coefficients ($\\theta^\\lambda_i - \\bar{\\theta}_i$)')</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" id="cell-id=50579422">
+<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="Exercise-4,-Implementing-the-simplest-form-for-gradient-descent">Exercise 4, Implementing the simplest form for gradient descent<a class="anchor-link" href="#Exercise-4,-Implementing-the-simplest-form-for-gradient-descent">¶</a></h2><p>Alternatively, we can fit the ridge regression model using gradient
+descent. This is useful to visualize the iterative convergence and is
+necessary if $n$ and $p$ are so large that the closed-form might be
+too slow or memory-intensive. We derive the gradients from the cost
+functions defined above. Use the gradients of the Ridge and OLS cost functions with respect to
+the parameters  $\boldsymbol{\theta}$ and set up (using the template below) your own gradient descent code for OLS and Ridge regression.</p>
+<p>Below is a template code for gradient descent implementation of ridge:</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=392b0bb7">
+<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 [9]:</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="w"> </span><span class="nf">gradient_descent</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">cost_func</span><span class="p">,</span> <span class="n">grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+    <span class="c1"># Initialize weights</span>
+    <span class="n">theta</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">X</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="c1"># Store cost history</span>
+    <span class="n">cost_history</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">num_iters</span><span class="p">)</span>
+    <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_iters</span><span class="p">):</span>
+        <span class="c1"># Compute cost</span>
+        <span class="n">cost_history</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">=</span> <span class="n">cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="c1"># Compute gradient</span>
+        <span class="n">grad</span> <span class="o">=</span> <span class="n">grad_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="c1"># Update weights</span>
+        <span class="n">theta</span> <span class="o">-=</span> <span class="n">eta</span> <span class="o">*</span> <span class="n">grad</span>
+    <span class="k">return</span> <span class="n">theta</span><span class="p">,</span> <span class="n">cost_history</span>
+
+<span class="k">def</span><span class="w"> </span><span class="nf">OLS_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">):</span>
+    <span class="n">error</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span> <span class="o">-</span> <span class="n">y</span>
+    <span class="k">return</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">error</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
+
+<span class="k">def</span><span class="w"> </span><span class="nf">OLS_grad_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">):</span>
+    <span class="n">error</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span> <span class="o">-</span> <span class="n">y</span>
+    <span class="k">return</span> <span class="n">X</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">error</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
+
+<span class="k">def</span><span class="w"> </span><span class="nf">Ridge_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="n">lam</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">OLS_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">)</span> <span class="o">+</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">lam</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">theta</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
+
+<span class="k">def</span><span class="w"> </span><span class="nf">Ridge_grad_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="n">lam</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">OLS_grad_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">)</span> <span class="o">+</span> <span class="n">lam</span> <span class="o">*</span> <span class="n">theta</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=be6ebfa8">
+<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">eta</span> <span class="o">=</span> <span class="mf">0.1</span>
+<span class="n">num_iters</span> <span class="o">=</span> <span class="mi">1000</span>
+<span class="n">lam</span> <span class="o">=</span> <span class="mf">1e-3</span>
+
+<span class="n">theta_gdOLS</span><span class="p">,</span> <span class="n">history_gdOLS</span> <span class="o">=</span> <span class="n">gradient_descent</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">OLS_cost_func</span><span class="p">,</span> <span class="n">OLS_grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="n">eta</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="n">num_iters</span><span class="p">)</span>
+<span class="n">theta_gdRidge</span><span class="p">,</span> <span class="n">history_gdRidge</span> <span class="o">=</span> <span class="n">gradient_descent</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">Ridge_cost_func</span><span class="p">,</span> <span class="n">Ridge_grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="n">eta</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="n">num_iters</span><span class="p">,</span> <span class="n">lam</span><span class="o">=</span><span class="n">lam</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Gradient Descent OLS coefficients:"</span><span class="p">,</span> <span class="n">theta_gdOLS</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Gradient Descent Ridge coefficients:"</span><span class="p">,</span> <span class="n">theta_gdRidge</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>Gradient Descent OLS coefficients: [-0.47433764  1.40826022]
+Gradient Descent Ridge coefficients: [-0.44990454  1.38335272]
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=32a7e3a3">
+<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 [11]:</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="w"> </span><span class="nf">theta_error</span><span class="p">(</span><span class="n">theta_est</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">theta_est</span> <span class="o">-</span> <span class="n">theta_true</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">((</span><span class="n">theta_est</span> <span class="o">-</span> <span class="n">theta_true</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Gradient Descent OLS error: </span><span class="si">{</span><span class="n">theta_error</span><span class="p">(</span><span class="n">theta_gdOLS</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Gradient Descent Ridge error: </span><span class="si">{</span><span class="n">theta_error</span><span class="p">(</span><span class="n">theta_gdRidge</span><span class="p">)</span><span class="si">}</span><span class="s2">"</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>Gradient Descent OLS error: (array([ 0.10881529, -0.09837005]), np.float64(0.010758716397832158))
+Gradient Descent Ridge error: (array([ 0.13324839, -0.12327754]), np.float64(0.016476242667611243))
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=e2654903">
+<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="4a)">4a)<a class="anchor-link" href="#4a)">¶</a></h3><p>Discuss the results as function of the learning rate parameters and the number of iterations.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=006ce51b">
+<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 [12]:</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">etas</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logspace</span><span class="p">(</span><span class="o">-</span><span class="mi">4</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
+<span class="n">max_iterations</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
+<span class="n">theta_errors</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">etas</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">max_iterations</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
+
+<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">eta</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">etas</span><span class="p">):</span>
+    <span class="k">for</span> <span class="n">j</span><span class="p">,</span> <span class="n">max_iter</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">max_iterations</span><span class="p">):</span>
+        <span class="c1"># print(f"Running GD with eta={eta}, max_iter={max_iter}")</span>
+        <span class="n">theta_gdOLS</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">gradient_descent</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">OLS_cost_func</span><span class="p">,</span> <span class="n">OLS_grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="n">eta</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="n">max_iter</span><span class="p">)</span>
+        <span class="n">theta_gdRidge</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">gradient_descent</span><span class="p">(</span><span class="n">X_norm</span><span class="p">,</span> <span class="n">y_centered</span><span class="p">,</span> <span class="n">Ridge_cost_func</span><span class="p">,</span> <span class="n">Ridge_grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="n">eta</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="n">max_iter</span><span class="p">,</span> <span class="n">lam</span><span class="o">=</span><span class="n">lam</span><span class="p">)</span>
+
+        <span class="n">theta_errors</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">theta_error</span><span class="p">(</span><span class="n">theta_gdOLS</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
+        <span class="n">theta_errors</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">theta_error</span><span class="p">(</span><span class="n">theta_gdRidge</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=b06f0bc6">
+<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 [13]:</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="w"> </span><span class="nn">matplotlib.cm</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">mcm</span>
+<span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.colors</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">mcolors</span>
+
+<span class="n">fig</span><span class="p">,</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">)</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">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="c1"># Log Colormap</span>
+<span class="n">cm</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">'viridis'</span><span class="p">)</span>
+<span class="c1"># Create LogNorm between min and max of theta_errors</span>
+<span class="n">norm</span> <span class="o">=</span> <span class="n">mcolors</span><span class="o">.</span><span class="n">LogNorm</span><span class="p">(</span><span class="n">vmin</span><span class="o">=</span><span class="n">theta_errors</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">vmax</span><span class="o">=</span><span class="n">theta_errors</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
+
+
+<span class="n">im1</span> <span class="o">=</span> <span class="n">ax1</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">theta_errors</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">aspect</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="s1">'nearest'</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">cm</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="n">norm</span><span class="p">)</span>
+<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Gradient Descent OLS Error'</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">im1</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax1</span><span class="p">)</span>
+
+<span class="n">im2</span> <span class="o">=</span> <span class="n">ax2</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">theta_errors</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">aspect</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="s1">'nearest'</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">cm</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="n">norm</span><span class="p">)</span>
+<span class="n">ax2</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Gradient Descent Ridge Error'</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">im2</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax2</span><span class="p">)</span>
+
+<span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</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">'Max Iterations'</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'Learning Rate'</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">max_iterations</span><span class="p">)))</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">etas</span><span class="p">)))</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">max_iterations</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">45</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_yticklabels</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">etas</span><span class="p">,</span> <span class="mi">4</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>
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+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div class="alert alert-block alert-success">
+In this simple example (well converging function) the gradient descent converges for all learning rates given enough iterations. The Error on the paramters approaches 10^-3 and stays at this plateau indicating the parameters have converged
+
+</div>
+</div>
+</div>
+</div>
+</div>
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+<h3 id="4b)">4b)<a class="anchor-link" href="#4b)">¶</a></h3><p>Try to add a stopping parameter as function of the number iterations. How would you define a stopping criterion?</p>
+<div class="alert alert-block alert-success">
+We define the stopping criterion via the decrease in the cost function. If the decrease gets too small we stop. This will be implemented using a custom stopping_criterion function so it can easily be replaced.
+
+</div>
+</div>
+</div>
+</div>
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+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [14]:</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="w"> </span><span class="nf">gradient_descent</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">cost_func</span><span class="p">,</span> <span class="n">grad_cost_func</span><span class="p">,</span> <span class="n">eta</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">stopping_criterion</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+    <span class="c1"># Initialize weights</span>
+    <span class="n">theta</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">X</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="c1"># Store cost history</span>
+    <span class="n">cost_history</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">num_iters</span><span class="p">)</span>
+    <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_iters</span><span class="p">):</span>
+        <span class="c1"># Compute cost</span>
+        <span class="n">cost_history</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">=</span> <span class="n">cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="c1"># Compute gradient</span>
+        <span class="n">grad</span> <span class="o">=</span> <span class="n">grad_cost_func</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="c1"># Update weights</span>
+        <span class="n">theta</span> <span class="o">-=</span> <span class="n">eta</span> <span class="o">*</span> <span class="n">grad</span>
+        <span class="k">if</span> <span class="n">stopping_criterion</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">stopping_criterion</span><span class="p">(</span><span class="n">cost_history</span><span class="p">[:</span><span class="n">t</span><span class="o">+</span><span class="mi">1</span><span class="p">]):</span>
+            <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Converged at iteration </span><span class="si">{</span><span class="n">t</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+            <span class="k">break</span>
+    <span class="k">return</span> <span class="n">theta</span><span class="p">,</span> <span class="n">cost_history</span>
+
+<span class="k">def</span><span class="w"> </span><span class="nf">stopping_criterion</span><span class="p">(</span><span class="n">cost_history</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1e-5</span><span class="p">):</span>
+    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">cost_history</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mi">2</span><span class="p">:</span>
+        <span class="k">return</span> <span class="kc">False</span>
+    <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">cost_history</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">cost_history</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">])</span> <span class="o">&lt;</span> <span class="n">tol</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=75542708">
+<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="Exercise-5,-Ridge-regression-and-a-new-Synthetic-Dataset">Exercise 5, Ridge regression and a new Synthetic Dataset<a class="anchor-link" href="#Exercise-5,-Ridge-regression-and-a-new-Synthetic-Dataset">¶</a></h2><p>We create a synthetic linear regression dataset with a sparse
+underlying relationship. This means we have many features but only a
+few of them actually contribute to the target. In our example, we’ll
+use 10 features with only 3 non-zero weights in the true model. This
+way, the target is generated as a linear combination of a few features
+(with known coefficients) plus some random noise. The steps we include are:</p>
+<p>Decide on the number of samples and features (e.g. 100 samples, 10 features).
+Define the <strong>true</strong> coefficient vector with mostly zeros (for sparsity). For example, we set $\hat{\boldsymbol{\theta}} = [5.0, -3.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0]$, meaning only features 0, 1, and 6 have a real effect on y.</p>
+<p>Then we sample feature values for $\boldsymbol{X}$ randomly (e.g. from a normal distribution). We use a normal distribution so features are roughly centered around 0.
+Then we compute the target values $y$ using the linear combination $\boldsymbol{X}\hat{\boldsymbol{\theta}}$ and add some noise (to simulate measurement error or unexplained variance).</p>
+<p>Below is the code to generate the dataset:</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=06077986">
+<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 [15]:</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="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
+
+<span class="c1"># Set random seed for reproducibility</span>
+<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
+
+<span class="c1"># Define dataset size</span>
+<span class="n">n_samples</span> <span class="o">=</span> <span class="mi">100</span>
+<span class="n">n_features</span> <span class="o">=</span> <span class="mi">10</span>
+
+<span class="c1"># Define true coefficients (sparse linear relationship)</span>
+<span class="n">theta_true</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="mf">5.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">3.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">])</span>
+
+<span class="c1"># Generate feature matrix X (n_samples x n_features) with random values</span>
+<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">n_samples</span><span class="p">,</span> <span class="n">n_features</span><span class="p">)</span>  <span class="c1"># standard normal distribution</span>
+
+<span class="c1"># Generate target values y with a linear combination of X and theta_true, plus noise</span>
+<span class="n">noise</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">n_samples</span><span class="p">)</span>    <span class="c1"># Gaussian noise</span>
+<span class="n">y</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">theta_true</span><span class="p">)</span> <span class="o">+</span> <span class="n">noise</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=86d46505">
+<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>This code produces a dataset where only features 0, 1, and 6
+significantly influence $\boldsymbol{y}$. The rest of the features have zero true
+coefficient. For example, feature 0 has
+a true weight of 5.0, feature 1 has -3.0, and feature 6 has 2.0, so
+the expected relationship is:</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f1d2f848">
+<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>$$
+y \approx 5 \times x_0 \;-\; 3 \times x_1 \;+\; 2 \times x_6 \;+\; \text{noise}.
+$$</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f1c91e84">
+<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>You can remove the noise if you wish to.</p>
+<p>Try to fit the above data set using OLS and Ridge regression with the analytical expressions and your own gradient descent codes.</p>
+<p>If everything worked correctly, the learned coefficients should be
+close to the true values [5.0, -3.0, 0.0, …, 2.0, …] that we used to
+generate the data. Keep in mind that due to regularization and noise,
+the learned values will not exactly equal the true ones, but they
+should be in the same ballpark.  Which method (OLS or Ridge) gives the best results?</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=1aaa2666">
+<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 [16]:</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">res</span> <span class="o">=</span> <span class="n">gradient_descent</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">OLS_cost_func</span><span class="p">,</span> <span class="n">OLS_grad_cost_func</span><span class="p">,</span> <span class="n">num_iters</span><span class="o">=</span><span class="mi">100000</span><span class="p">,</span> <span class="n">stopping_criterion</span><span class="o">=</span><span class="n">stopping_criterion</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Terminated with error on theta of </span><span class="si">{</span><span class="n">theta_error</span><span class="p">(</span><span class="n">res</span><span class="p">[</span><span class="mi">0</span><span class="p">])[</span><span class="mi">1</span><span class="p">]</span><span class="si">:</span><span class="s2">.3e</span><span class="si">}</span><span class="s2">"</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>Converged at iteration 85
+Terminated with error on theta of 3.750e-03
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+</main>
+</body>
+</html>
diff --git a/doc/LectureNotes/exercisesweek37.ipynb b/doc/LectureNotes/exercisesweek37.ipynb
index 62c74edd0..9a4cbe900 100644
--- a/doc/LectureNotes/exercisesweek37.ipynb
+++ b/doc/LectureNotes/exercisesweek37.ipynb
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1f66bb2f",
+   "id": "b5bb413f",
    "metadata": {},
    "source": [
     "**Python Code can be found at https://github.uio.no/larsbog/FYS-STK4155**"
@@ -63,98 +63,7 @@
    "source": [
     "## Simple one-dimensional second-order polynomial\n",
     "\n",
-    "We create a synthetic linear regression dataset with a sparse\n",
-    "underlying relationship. This means we have many features but only a\n",
-    "few of them actually contribute to the target. In our example, we will\n",
-    "use 10 features with only 3 non-zero weights in the true model. This\n",
-    "way, the target is generated as a linear combination of a few features\n",
-    "(with known coefficients) plus some random noise. The steps we include are:\n",
-    "\n",
-    "Decide on the number of samples and features (e.g. 100 samples, 10 features).\n",
-    "Define the **true** coefficient vector with mostly zeros (for sparsity). For example, we set $\\hat{\\boldsymbol{\\theta}} = [5.0, -3.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0]$, meaning only features 0, 1, and 6 have a real effect on y.\n",
-    "\n",
-    "Then we sample feature values for $\\boldsymbol{X}$ randomly (e.g. from a normal distribution). We use a normal distribution so features are roughly centered around 0.\n",
-    "Then we compute the target values $y$ using the linear combination $\\boldsymbol{X}\\hat{\\boldsymbol{\\theta}}$ and add some noise (to simulate measurement error or unexplained variance).\n",
-    "\n",
-    "Below is the code to generate the dataset:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "9e6acfef",
-   "metadata": {
-    "collapsed": false,
-    "editable": true,
-    "jupyter": {
-     "outputs_hidden": false
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "# Set random seed for reproducibility\n",
-    "np.random.seed(0)\n",
-    "\n",
-    "# Define dataset size\n",
-    "n_samples = 100\n",
-    "n_features = 10\n",
-    "\n",
-    "# Define true coefficients (sparse linear relationship)\n",
-    "theta_true = np.array([5.0, -3.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0])\n",
-    "\n",
-    "# Generate feature matrix X (n_samples x n_features) with random values\n",
-    "X = np.random.randn(n_samples, n_features)  # standard normal distribution\n",
-    "\n",
-    "# Generate target values y with a linear combination of X and theta_true, plus noise\n",
-    "noise = 0.5 * np.random.randn(n_samples)    # Gaussian noise\n",
-    "y = X @ theta_true + noise"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "de370995",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  9.79794828,  -0.20820758, -14.84544524,   2.15318795,\n",
-       "        -3.37427507,  -5.40426588,  -5.27365266,   0.60787097,\n",
-       "        -6.19533156,  -5.5427031 ,  12.13162753,   9.35115762,\n",
-       "         4.39080256,  -3.53244394, -10.99536903,  -3.68161441,\n",
-       "       -10.167063  ,   1.20194765,   0.25360044,  -5.67324644,\n",
-       "        -0.66859127,   3.91571974,  -3.63750527,  -3.20012413,\n",
-       "         1.16544606,   2.48543602,  -3.89882746,  10.75806552,\n",
-       "        -5.1450755 ,  -1.76135661, -14.55239547,  -3.91723721,\n",
-       "        -1.57784936,   3.45194764,   6.35031305,  -2.66082655,\n",
-       "         3.59232485,   6.05166812, -11.42207923,   4.33238054,\n",
-       "         2.81808632,  -8.74092274,   5.09102217,   4.11714319,\n",
-       "         3.1336241 ,  -8.4624152 ,  -1.35434132,  -6.12500763,\n",
-       "         3.8119143 ,  -5.84403289,  -1.60885033,   0.90200251,\n",
-       "         3.42168223, -12.40126176,   8.4350032 ,  -4.10291902,\n",
-       "        10.22537853,   6.77936945,  -8.3636364 ,   0.12906052,\n",
-       "        -9.12015726,  -4.9746779 ,   5.00624051,  -4.96426885,\n",
-       "        -2.44764182,   8.45246218,  -0.88759959,   1.05540356,\n",
-       "        -1.95453159,  -1.67965422,  -2.23592179,  -7.8858097 ,\n",
-       "        -2.29987312,   0.33223236,  -2.40309155,  10.6587834 ,\n",
-       "        -2.95341782,  -3.20039517,   6.51082782,  -3.32577856,\n",
-       "         5.49390475,  -6.09136851,   0.86829871,  -3.55729026,\n",
-       "         3.61818052, -13.1381039 ,   4.5022915 ,   6.42751502,\n",
-       "        11.73765566,  -6.33983703,  -6.74108381,  -0.10967951,\n",
-       "       -11.69392899,   6.35925176,  -0.43824325,  -3.78885595,\n",
-       "        -4.25173964,  -7.04162883,   1.59342361,   1.60361719])"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "y"
+    "We start with a very simple function"
    ]
   },
   {
@@ -220,8 +129,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "a140aac7",
+   "execution_count": 1,
+   "id": "2fb97177",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "\n",
+    "def polynomial_features(x, p, intercept=False):\n",
+    "    n = len(x)\n",
+    "    if intercept:\n",
+    "        P = np.arange(p+1)\n",
+    "    else:\n",
+    "        P = np.arange(1, p+1)\n",
+    "    X = np.power(x[:, np.newaxis], P)\n",
+    "    return X\n",
+    "\n",
+    "\n",
+    "theta_true = np.array([-2.0, 5.0])\n",
+    "X = polynomial_features(np.linspace(0, 1, 100), p=2)\n",
+    "y = 2 + theta_true@X.T + 0.1 * np.random.randn(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "590b2fb0",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -235,8 +169,88 @@
     "X_norm = (X - X_mean) / X_std\n",
     "\n",
     "# Center the target to zero mean (optional, to simplify intercept handling)\n",
-    "y_mean = y.mean()\n",
-    "y_centered = y - y_mean"
+    "y_mean = y.mean(axis=0)\n",
+    "y_centered = y - y_mean\n",
+    "\n",
+    "n_features = X_norm.shape[1]\n",
+    "theta_true *= X_std"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cf63b06e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([-0.58315293,  1.50663026])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "theta_true"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bab1bb8d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.29157647, 0.30132605])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_std"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "3b714989",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Target')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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AkLIIhAAAQMoiEAIAACmLgooAAJzU6DaoGp1iCIQAAJC0cnu1ypbvULWr3nssz56pOWMK6SOWxFgaAwCkvJXbqzX52S3NgiBJcrrqNfnZLVq5vTpmY0NkJVQg9Oabb2rMmDHq0aOHbDabli5dGvSadevWafDgwcrIyFCfPn20ePHiqIwVAJAYGt2GypbvkOHjd55jZct3qNHt6wwkuoQKhOrq6jRw4EAtXLjQ1PlVVVUaPXq0Lr/8clVUVGjKlCn60Y9+pNdffz3iYwUAJIZNVYdazQQ1ZUiqdtVrU9WhqI4L0ZFQOUJXXXWVrrrqKtPnL1q0SAUFBXrggQckSf3799f69ev10EMPaeTIkREcKQAgUXx2xH8QFMp5SCwJNSNkVXl5uUpLS5sdGzlypMrLy/1e09DQoJqammY/AIDk1b1TZljPQ2JJ6kDI6XQqNze32bHc3FzV1NTo2LFjPq+ZN2+e7Ha79yc/Pz9KowUAxMLQghzl2TMVaJN8TlY7OWvqVV55kFyhJJPUgVAoZs6cKZfL5f35+OOPYz0kAEAEpafZNGdMoST5DYYO1Z3Q1BcrNP7xt3Xx/LXsIksiSR0IORwOHThwoNmxAwcOKDs7Wx06dPB5TUZGhrKzs5v9AACS26iiPD12/WA57MGXv9hSn1wSKlnaqpKSEr322mvNjq1atUolJSUxGxMAID6NKsrTiEKHNlUdktN1THNX7NShuuOtzjNOzhyVLd+hEYUOKk8nuISaEaqtrVVFRYUqKiqkk9vjKyoqtG/fPunkstYNN9zgPf+WW27Rhx9+qDvuuEO7du3S7373O/35z3/W1KlTY/YeAADxKz3NppLeXeSwd/AZBHmwpT55JNSM0LvvvqvLL7/c+3jatGmSpAkTJmjx4sWqrq72BkWSVFBQoBUrVmjq1Kn67W9/qzPOOENPPPEEW+cBAAG1dUs9PcsSR0IFQpdddpkMw3+2vq+q0Zdddpm2bt0a4ZEBAJJJW7bU07MssSTU0hgAANEQbEu97WRwM7Qgp9lxepYlHgIhAABaCLSl3vN4zpjCZstd9CxLTARCAICU1eg2VF55UMsq9rcqluhvS73DnqnHrh/capmLnmWJKaFyhAAACBczuTxNt9QHS3ymZ1liIhACAKQcTy5Py0UqTy5P0xkfz5b6YOhZlphYGgMApJRI5fKEmmCN2CIQAgCklEjl8oSSYI3YIxACAKSUSObyWE2wRuyRIwQASCmRzuWxkmCN2CMQAgCkFE8uj9NV7zNPyHZyBqctuTxmE6wReyyNAQBSCrk8aIpACACQcsjlgQdLYwCAlEQuD0QgBABIZeTygKUxAACQspgRAgAkpUa3wbIXgrIcCPXq1UvvvPOOunRpPpX4xRdfaPDgwfrwww/DOT4AACwz01AVUChLY3v37lVjY2Or4w0NDdq/f3+4xgUAQEg8DVVbttHwNFRdub06ZmND/DE9I/S3v/3N+79ff/112e127+PGxkatWbNGPXv2DP8IAQAwKVhDVdvJhqojCh0sk0GyEgiNGzdOkmSz2TRhwoRmv2vXrp169uypBx54IPwjBADAJCsNVdktBlkJhNxutySpoKBA77zzjrp27RrJcQEAYJonMfrvJpe9Nuz5L8nTkCTZDMPwNYNoSn19vTIzQ2tKlyhqampkt9vlcrmUnZ0d6+EAAFrwlRhtBsnTyc3s97flZGm32625c+fq9NNP16mnnurdJTZr1iw9+eSTbRs1AAAW+EuMNoPkaSiUQOiee+7R4sWLdd9996l9+/be40VFRXriiSfCPT4AAHwKlBhthue6suU71OgOeXEECc5yIPT000/rD3/4g6677jqlp6d7jw8cOFC7du0K9/gAAEmi0W2ovPKgllXsV3nlwTYHH8ESo81omjyN1GS5oOL+/fvVp0+fVsfdbrdOnDgRrnEBAJJIJAocfnakbUFQpJ4LicXyjFBhYaH+9a9/tTr+l7/8RYMGDQrXuAAASSJSBQ67dwrfZp1wPhcSi+UZodmzZ2vChAnav3+/3G63Xn75Ze3evVtPP/20Xn311ciMEgCQkCJZ4HBoQY7y7Jlyuup9Pr9NUm52hiSbDtT4P8dh/6oPGVKT5RmhsWPHavny5Vq9erWysrI0e/Zs7dy5U8uXL9eIESMiM0oAQEKyUuDQLE+u0avvfaprLzhTOhnQNOV5fNe3z9Vd3y4MeM6cMYXUE0phIXWf/8Y3vqFVq1aFfzQAgKRiNvcm0HlNu8jv/fyont+0T86ar8/v3LGdJOmLo1/nqTpa5B89dv3gVjlKLc9BagopEAIAwAyzuTee85oGPd07Zepw3XHNXRG4WKLr6AkZkqaW9lXPrlnq3imzVdXoUUV5GlHoaPbcVJaGQgmETjvtNNlsrT84NptNmZmZ6tOnjyZOnKgbb7wxXGMEACQoM3k8nhydUCtEe3KNXnjnY62/8wq/wU16mo3+YmjFco7Q7NmzlZaWptGjR6usrExlZWUaPXq00tLSdOutt+rss8/W5MmT9fjjj0dmxACAhJGeZtOcMcFzdFbtcIZcIVrUA0IbWJ4RWr9+ve655x7dcsstzY7//ve/1z/+8Q/99a9/1YABA/Twww9r0qRJ4RwrACABjSrKC5ijM6LQoYvnrw25QnRT1AOCVZabrp566qmqqKhoVVRxz549Ki4uVm1trSorKzVgwADV1dWFe7xRR9NVAAiPlvk/nhyd8sqDGv/422F5jecnXcjyF6RINl3NycnR8uXLWx1fvny5cnK+qsNQV1enTp06WX1qAEAS8+TojC0+XSW9u3hzecIxi2M7WamaekCwyvLS2KxZszR58mS98cYbGjp0qCTpnXfe0WuvvaZFixZJklatWqVLL700/KMFACSVRrehz480tOk5qAeEtrC8NCZJGzZs0KOPPqrdu3dLkvr166ef/vSnGj58eCTGGFMsjQFAZIS6S6yltvYsQ3Iy+/1taUboxIkT+vGPf6xZs2bp+eefD8c4AQApyNN/LJQEaUd2hsYPPdNvzSDACkuBULt27fTXv/5Vs2bNityIAABJLVD/sZby7JmaNbq/TsvKoBAiIsJyjtC4ceO0dOlSTZ06NTIjAgAktWD9xzxmje6viRcVEPQgoiwHQn379tXdd9+tDRs2aMiQIcrKymr2+5/97GfhHF8rCxcu1G9+8xs5nU4NHDhQjzzyiDdpu6XFixe3qnCdkZGh+nrqTABArJjdJda1UwZBECLOciD05JNPqnPnztq8ebM2b97c7Hc2my2igdCLL76oadOmadGiRRo2bJgWLFigkSNHavfu3erevbvPa7Kzs71J3Z4xAgBix2r/MSCSLAdCVVVVkRmJCQ8++KAmTZrkneVZtGiRVqxYoT/+8Y+aMWOGz2tsNpscDkeURwoA8MdK/zEg0iwXVIyV48ePa/PmzSotLfUeS0tLU2lpqcrLy/1eV1tbq7POOkv5+fkaO3as3n///YCv09DQoJqammY/AIDwMdt/jGUxRIPlGSFJ+uSTT/S3v/1N+/bt0/Hjx5v97sEHHwzX2Jr5/PPP1djYqNzc3GbHc3NztWvXLp/X9OvXT3/84x81YMAAuVwu3X///Ro+fLjef/99nXHGGT6vmTdvnsrKyiLyHgAAXwnWf4yaQIgWy4HQmjVr9O1vf1u9evXSrl27VFRUpL1798owDA0ePDgyowxRSUmJSkpKvI+HDx+u/v376/e//73mzp3r85qZM2dq2rRp3sc1NTXKz8+PyngBIJWMKsrTiEKHz/5jQLRYDoRmzpypn//85yorK1OnTp3017/+Vd27d9d1112nUaNGRWaUkrp27ar09HQdOHCg2fEDBw6YzgFq166dBg0apD179vg9JyMjQxkZGW0eLwAgOE//MSBWLOcI7dy5UzfccIMk6ZRTTtGxY8d06qmn6u6779b8+fMjMUZJUvv27TVkyBCtWbPGe8ztdmvNmjXNZn0CaWxs1LZt25SXx5QrAAAIIRDKysry5gXl5eWpsrLS+7vPP/88vKNrYdq0aXr88cf1pz/9STt37tTkyZNVV1fn3UV2ww03aObMmd7z7777bv3jH//Qhx9+qC1btuj666/XRx99pB/96EcRHScAAEgMppfG7r77bk2fPl0XXnih1q9fr/79++vqq6/W9OnTtW3bNr388su68MILIzrYa665Rv/97381e/ZsOZ1OFRcXa+XKld4E6n379ikt7evY7vDhw5o0aZKcTqdOO+00DRkyRG+99ZYKCwsjOk4AAJAYTHefT09PV3V1tWpra1VbW6sBAwaorq5O06dP11tvvaW+ffvqwQcf1FlnnRX5UUcR3ecBAEg8Ye8+74mXevXq5T2WlZWlRYsWtXWsAAAAMWFp1xjtKQAAZjW6DbbGI+5ZCoTOPvvsoMHQoUOH2jomAECcCxbkrNxe3apYYh7FEhGHLAVCZWVlstvtkRsNACDuBQtyVm6v1uRnt7TqI+Z01Wvys1v02PWDCYYQN0wnS6elpcnpdPrt8p6sSJYGgK/5C3I8c0ELfzBIc1fsbBYktTzPYc/U+juvYJkMEWX2+9t0HSHygwAgtTW6DZUt3+GzY7zn2C+XbfcbBHnOq3bVa1MVaRSID5Z3jQEAkleg3J9NVYeCBjmH6k6Yep3Pjvh/HiCaTAdCbrc7siMBAMSUv9yfWaP767SsDP19e3XYXqt7p8ywPRfQFpabrgIAko+/3J9qV71+smSrpefKyWqvw3XHfS6heXKEhhbktGm8QLhY7jUGAEgugXJ/rLCdnEG6Z2yR93HL30vSnDGFJEojbhAIAUCKC5b7Y5Yh6eoih07Laq+FPxgsh7358pfDnsnWecQdlsYAIMWFI3E5zSa5DenJDXv15Ia9zXKLqCyNeMaMEACkuLYkLl96djdJXwVBTTld9bp1yVa5jh3X2OLTVdK7C0EQ4hKBEACkuKEFOcqzZ7bK6TFj236Xz+OeuKhs+Q41toySgDhCIAQAKS49zaY5YwolHwnO/tgk5WS106G6437PoXgiEgGBEABAo4ry9Nj1rROcffEES98pPt3Uc1M8EfGMZGkAgHQyGBpR6GhWWfpw3XHNXdG8yKLjZINVe4f2enLD3qDPS/FExDMCIQCAV3qaTSW9uzQ7NrLI4bPtRqPbUJ49U05XPcUTkbAIhAAAAfkKjtQkt2jys1tka5IgLYonIoGQIwQACJm/3CKKJyJRMCMEAGgTX7lFFE9EoiAQAgC0mb/lMyDesTQGAABSFoEQAABIWQRCAAAgZREIAQCAlEUgBAAAUhaBEAAASFkEQgAAIGVRRwgA4lyj26BYIRAhBEIAEMdWbq9W2fLm3d/zTnZ/p30F0HYsjQFAnFq5vVqTn93SLAiSJKerXpOf3aKV26tjNjYgWRAIAUAcanQbKlu+o1lHdw/PsbLlO9To9nUGALMIhAAgDm2qOtRqJqgpQ1K1q16bqg5FdVxAsiEQAoA49NkR/0FQKOcB8I1ACADiUPdOmWE9D4BvBEIAEIeGFuQoz54pf5vkbSd3jw0tyInyyIDkQiAEAHEoPc2mOWMKpZNBT1Oex3PGFFJPCGgjAiEAiFOjivL02PWD5bA3X/5y2DP12PWDqSMEhAEFFQEgjo0qytOIQgeVpYEIIRACgDiXnmZTSe8usR4GkJQSbmls4cKF6tmzpzIzMzVs2DBt2rQp4PkvvfSSzjnnHGVmZuq8887Ta6+9FrWxAkC0NLoNlVce1LKK/SqvPEihRcCkhJoRevHFFzVt2jQtWrRIw4YN04IFCzRy5Ejt3r1b3bt3b3X+W2+9pfHjx2vevHn61re+pSVLlmjcuHHasmWLioqKYvIeACDc/PUjmzW6v07LymBJDQjAZhhGwvyzYdiwYbrgggv06KOPSpLcbrfy8/P105/+VDNmzGh1/jXXXKO6ujq9+uqr3mMXXnihiouLtWjRIp+v0dDQoIaGBu/jmpoa5efny+VyKTs7OyLvCwBC5elHZuY/5DRrRSqpqamR3W4P+v2dMEtjx48f1+bNm1VaWuo9lpaWptLSUpWXl/u8pry8vNn5kjRy5Ei/50vSvHnzZLfbvT/5+flhfBcAED6B+pH5QrNWoLWECYQ+//xzNTY2Kjc3t9nx3NxcOZ1On9c4nU5L50vSzJkz5XK5vD8ff/xxmN4BAIRXsH5kLdGsFWgtoXKEoiEjI0MZGRmxHgYABBVKn7GmzVrZiQYk0IxQ165dlZ6ergMHDjQ7fuDAATkcDp/XOBwOS+cDQCJpS58xmrUCX0mYQKh9+/YaMmSI1qxZ4z3mdru1Zs0alZSU+LympKSk2fmStGrVKr/nA0AiCdaPLJDPjzSwPAYkUiAkSdOmTdPjjz+uP/3pT9q5c6cmT56suro63XjjjZKkG264QTNnzvSef/vtt2vlypV64IEHtGvXLt1111169913ddttt8XwXQBAeATqRxbM3BU7dfH8tSROI+UlVCB0zTXX6P7779fs2bNVXFysiooKrVy50psQvW/fPlVXf/1/6uHDh2vJkiX6wx/+oIEDB+ovf/mLli5dSg0hAEnDXz8yM9hFBiRYHaFYMFuHAABiqdFtNOtHdrjuuOau2BF0V5ntZBPX9XdeQbFFJBWz39/sGgOAJOCrH9nIIocWb6jS3BU7/V7n2UX20Kr/6KI+Xak+jZSTUEtjAADz0tNs6trJXDmQR9/Yo/GPv03eEFIOgRAAJDGrW+zJG0KqIRACgCRmdYs91aeRagiEACCGGt2GyisPalnFfpVXHgx78BHKFvum1aeBZEeyNADEyMrt1Spb3nxnV549U7NG99dpWRneHWBtTWD2bLFv+VrBUH0aqYBACABiYOX2ak1+dkurzvHVrnr9ZMnWZsfy7JmaM6ZQo4ryQn69UUV5GlHo0KaqQ9qw57969I3KoNe0pYUHkChYGgOAKGt0GypbvqNVEORPuBKYPVvsp47oFzBvyHYy+BpakNOm1wMSAYEQAETZpqpDlpaowp3AHChvyPN4zphC6gkhJRAIAUCUhZJ7E+4EZn+tORz2TD12/eA2LcMBiYQcIQCIkJZtLzxJz23JvQlnAnPTvKFwJWYDiYZACAAiwN+OsDljCjWi0KE8e6acrnrTeUIeniDKX5Blla/WHEAqIRACgDDztyPM6arXLc9u0dTSvrqqyKE/btgrW5McoEA8zVGHFuQEDLJY0gKsoft8EHSfB2BFo9vQxfPXmk6GTrNJwfKfPfM8j10/WJJ8BllNzyEYAsx/f5MsDQBhZHVHmCcIuuminnp+0oX63Q8GK89PAvOIQoffbfe0xgBCw9IYgJQSrtwaf0JJZrZJem27U/83+qst6yOLfCcwl1ceDBhkNd1ZRt4PYA6BEICUEY3cmlB2hLUMYPwlMJsNsmiNAZjH0hiAlOBJYG45oxKuqs0eVru9NxUsgDEbZNEaAzCPQAhA0gvU0iKaVZuDCRbABAuyaI0BWEcgBCDpBUtgjlbVZn/MBjC0xgDCjxwhAAnJStKz1dyacCRUt6zavPfzo1qw+j9Si7pBVgMYT5DVMtfJQR0hICQEQgASjtWkZyu5NeFMqG6Z9NzPcWpYAhhaYwDhQ0HFICioCMQXf1WbAxUU9BQ59NfSwlO1edboQt26JLLFCiO9fR/AVyioCCDphJr0bCa3Ztbo/pq7IvIJ1Z5ZorHFp3u3ygOIHQIhAAmjLUnP/hKYPVWbT8vKiGpCNYD4QI4QgITR1oKCgXJrllXsD+sYACQGAiEACSMcBQX9VW2mWCGQmlgaA5AwIllQ0OpzN7oNlVce1LKK/SqvPEijUyBBMSMEIGF4kp4nP7tFtjbW4/Fouovr2gvO1ILV/wn63NHoWQYgOtg+HwTb54H4E65AxNfzdO7YTpL0xdETPp87lO37AKLP7Pc3M0IAEk44Cgr6C2hcR0/IkDS1tK96ds1q9tzBtu/bTm6xH1HoYFs8kCAIhAAkJH9Jz2aYCWheeOdjrb/zCm8AVF55UBv2/Nf0FvtQxwYgugiEAKQcK/WIXMeOt1o+C4Yt9kDiIBACkHLMBiqrdjj11Ia9PmeOAvn8SIMa3QbLY0ACYPs8gJRjthbQ0opPLQdBkjR3xU5dPH+tVm6vDuFqANFEIAQg5ZipGZST1U6H6o6H/BpOV70mP7uFYAiIcwRCAFKOmSas3yk+vU2vEc5GrQAih0AIQEzFqkJzsCaspYWONr8GjVqB+EeyNICYiXWF5kD1iBrdhvLsmXK66n3mCdkk2Tu00xfHTvj4bXPsIgPiFzNCAGLCU9Cw5bb0tuTWhDK75KlHNLb4dJX07uLd6WVm+ezGi3qaGheNWoH4lTCB0KFDh3TdddcpOztbnTt31k033aTa2tqA11x22WWy2WzNfm655ZaojRmAb8EKGiqE3JqV26t18fy1Gv/427r9hQqNf/xtXfTrNfrt6v+EvOwWbPnstiv6RqwJLIDoSJilseuuu07V1dVatWqVTpw4oRtvvFE333yzlixZEvC6SZMm6e677/Y+7tixYxRGCyAQKwUNzVRo9tcuw1nToIdWf+B9HMqyW7B2HuFuAgsguhJiRmjnzp1auXKlnnjiCQ0bNkwXX3yxHnnkEb3wwgv69NNPA17bsWNHORwO7w+NU4HYM5szY+a8QLNLLYW67OZv+UwmZo1owArEt4SYESovL1fnzp11/vnne4+VlpYqLS1NGzdu1He+8x2/1z733HN69tln5XA4NGbMGM2aNSvgrFBDQ4MaGhq8j2tqasL4TgDIQs6MmfOCzS41FanGqOFoAgsgNhIiEHI6nerevXuzY6eccopycnLkdDr9XveDH/xAZ511lnr06KH33ntPd955p3bv3q2XX37Z7zXz5s1TWVlZWMcPJINGtxG2L3pPQcNAO7IcJnNrrO7IilRj1LY0gQUQOzENhGbMmKH58+cHPGfnzp0hP//NN9/s/d/nnXee8vLydOWVV6qyslK9e/f2ec3MmTM1bdo07+Oamhrl5+eHPAYgGYR7m7tnR1Y4cmtC3ZHFlnYAinUgNH36dE2cODHgOb169ZLD4dBnn33W7PiXX36pQ4cOyeEwX/Rs2LBhkqQ9e/b4DYQyMjKUkZFh+jmBZOc3Eflkvk2oeTCe3JqWAZbDYoAVbHbJH7a0A1CsA6Fu3bqpW7duQc8rKSnRF198oc2bN2vIkCGSpLVr18rtdnuDGzMqKiokSXl5JC8CHoGWvIJtc29rvk04cmsCzS75YmXZDUDyS4gcof79+2vUqFGaNGmSFi1apBMnTui2227Ttddeqx49ekiS9u/fryuvvFJPP/20hg4dqsrKSi1ZskRXX321unTpovfee09Tp07VJZdcogEDBsT6LUVVOHM7kFyCLXmFe5u7L+HIrfE3u9QSW9oBtJQQgZBO7v667bbbdOWVVyotLU3f+9739PDDD3t/f+LECe3evVtHjx6VJLVv316rV6/WggULVFdXp/z8fH3ve9/TL3/5yxi+i8hrGfQcrjuuuSti18IA8cvMklfDl25Tz2Ul3yZSgXnL2aW9nx/V85v2yVkT+rIbgORnMwyDtsgB1NTUyG63y+VyxX0NIl//uvfF85VDjZPU1eg2dPH8tX4/K57lo/v/Z6Cue2Jj0Od7ftKFpgsfRrO3GLOhQOoy+/2dMDNCCMzfv+59iVQtFSQOs0teMhS2be5tSboONaBhSzuAYAiEkoCVyroekaqlgsRgdinr87qGsGxzb0vSdaw71ANIbgnRYgOBWams2xK1VFKTlcrOVlpI+Ov+biXpuqlIdKgHgKaYEUoCbQlmqKWSmqxWdjazzT3QzE0oSdeR3roPAGJGKDmEEszYTn5JUUslNXlq76jJEpeHvyWvQI1Hg83c7P28ztS4mn6WQ51FAgArCISSgOdf92b/TUwtFSiMXdODzdxI0vOb9smR7f8z6iswD2eHegDwh6WxJGC1sm4y11Jhu7Q14ajsbGbmxlnToKmlZ2vB6v+YTroOZ4d6APCHQChJ+Kusm2fP1KzR/XVaVkbSBwfsLgpNW7eYm52R6dm1o6XeYuHsUA8A/hAIJZFw/Os+UUWqMSiCszJzU9K7i+nPaDg71AOAPwRCSSYVC8iZyVH5v1e26dgJtxzZqRMcRovVmRsrn9FwdagHAH8IhJDwzNRROlR3QlNfrJBYLgubpvlY115wpqX8HytSeaYTQOQRCCU4koOt7xpiuaztfOVjde7YTpL0xdET3mO52RkaP/RMNXzpVnnlwZA/n6k40wkgOgiEElioycHJFjxZ3TWUzMX4ovG39ZeP5Tp6QoakqaV91bNrlrf7+0OrP/CeY3Y2Ltk+owDiF93ng4jX7vP+voyCdZZPxp1Vnk7q/nJUAjHbNT0RRONva7Zr/azRhbp1ifXPZ7TeB4DkZ/b7m4KKCchMcnDZ8h3ePk8eydq3KVCV5GCSpRhftP62Zqs9/3LZdsufTyXxZxRA/CIQSkChtB4INXhKFP6qJAeTSMX4/DU0jebf1mzgeKjuuN/f+WuNkeyfUQDxiRyhBBRK6wErwVOiLhU13V3kdB3T3BU7dbjueEjF+OItRyXQcpG9Q3tLf9u2vLdwBo4tP8ep8BkFEH8IhBJQKK0HUqVvU9PdRR3ap4dUjM9sjkq0gqVgxSL/30U9TT3PZ0fq2/zezNQMOi2rnQ7VnfDx2+Zafo5T5TMKIL4QCMVAW79AQ2k9kIp9m0Ipxhco6Ljl2S2tdkQ5ayKb0Btsucgm6ZWK/aaea+/nR7Vg9X+CVt8OFiwFq/Z8z9gizV2x03JrjFT8jAKIPQKhKPP3JWOlH1gorQdStW+TlWJ8ZnJUmm4FbykS9YnMLBcdqjuhnKz2fpcBJcmeeYr+VL43YEBVtnyH3G753O3V8r0FCzDT0myWZ+NS9TMKILbYPh9EOLfP+5tt8MVMcGR1m7Hn9eXnyynVCwyWVx7U+MffbtNzeL6s1995RViWyZZV7NftL1QEPe//XdRTT23YK7X421qVk9Xeb6Jzy/cWbGYzlG3wfEYBhIvZ728CoSDCFQgFq79iRjjyVKjR4p/ZoMOMcNUnMhucPT/pQrmOHW/1t40EK+8tlGVgPqMAwsHs9zdLY1Fiph9WML6WXqy2HqBvk3/hzD35+8l6N229t1aWi9LTbBpR6NDblQd165It+uJY8ITlUFhJVg6lNQafUQDRRCAUJeHY6RKu1hCh9m2Kty3l4RYs6LDi6fKP9HT5R22eyQiUD6aTj68u+ipo8Pw90tJsloOgtuz2igR6iwGIFgoqRkm4vjz8FaOLtJXbq3Xx/LUa//jbuv2FCo1//G1dPH9t0lT69QR5VxU5vAFnOJitiNyyWOLxk01Kl1Xsl71Dey38QetikZ4Y9MkNe5v9PawG3U13e+XZM/2+d9vJJSqSlQEkE2aEoiScsw2Kci2VYHVsEj2B1VdOis0mhSN7zswsnq/XT7NJTQsoN02eX7XDqT9u2KuWBZY9f48ppX0tjbGtu70AIJExIxQlbemH5Uu0aqkke9sDf72tPG/npot6amrp2bK14e8WaBYv2Ot7OF31unXJVh2ua9Dftzv9vo4kPb9pnxzZ/md2JCknq50euqZYz0+6UOvvvMIbyPprVeKwZyZ8wAsAvjAjFEX+6q9YEalaKv7yf5K57UGgIE8n7/Vr251af+cV6uc4tXXdnOwMjR96pg7WHdfT5R8Ffb2Ws3jBXr8pz8zSL5dtD5jHY0hy1jRoaunZWrD6P35ndn71nfP8BjUkKwNIJQRCUebrS+Zw3XHNXRE8OIrU8kSg7coNX7pNPYfnSz6aCdVtfS0rQV6g4KC88qCpQKjlLJ7VnYSe4olm9Oza0XJV7aZIVgaQKgiEYsDXl8zIouDBkdkvMSuC5f+YzTfp3ikzqvVfwvFaVntb+QsOQq2IHMk8r+6dMlXSuwszOwAQBIFQnDATHIX7S8xMHytPvsmBmsBf8ofrjptqzdDW8W6qOuRNFm7J6muFq7dVKC1PrLx+S4HaabQMupjZAYDASJaOY54vsbHFp6ukd5ew/0vezNKQs6ZB44eeKflIFvY8njW6v+auiGxCddPt+76CoFBeyzOTE47t4laSjD1b5Z2uY8rJam86CdsznnvGFnkft/y92NkFAJYwI5TCzC7NBMo3mTW6v6pd9aZybR5a9R9d1Kerz5mtQPk+Vnq0WUneDnUmxx8zSca+lvTMaDqeUUV5eiwt9PwfAMDXCIRSmJWlIV/5JmaTvD0efWOPHn1jT6tcnkD5PiMKHaZ3VjVlNsgz00ndikBLUVYCupZ1hFqOh51dABAeBEIpzGqSb9Mv+ZXbq33mBJnRNJdHUtBk7VBKDQQK8lrOPo0odEQsqPC8ltN1THNX7Ax4v3Ky2mnWt86VIztTQ846TZs/OhxwPOT/AEDbEQilsFCXhqzUv/HFk4h919/el2QLmKz9lJ98IH+C1VmK9c62QA7VnZAjO9Mb3BDkAEDkkSyd4kKpJGy1/o0vnkRsZ03g3CIrzUOD5fX4q+Jsth+YFf5eK5hotk4BADAjhBDyTaL9ZX1qRrrqGhqDzkAFyusxUyogUD8wK9oyYxat1ikAgK8QCEGymG8S7S/r2obGgL+/6aKeKi10BAzeotkqJJQZs0i1TgEABEYgBMvMJFnnZmdIsgUsxBjsnGCs5PZYrSLdFlafg/o/ABA7BEKwzEyS9V3fPlc6uSMslHP8abqzysrOrnBVkY7Ec1D/BwBiJ2GSpe+9914NHz5cHTt2VOfOnU1dYxiGZs+erby8PHXo0EGlpaX64IMPIj7WSPFUJF5WsV/llQfbVKm5rcwkWbflHH+a7qyyMnsSzirSbX0tnQzoHrqmWM9PulDr77yCIAgAYsRmGEbsvk0tmDNnjjp37qxPPvlETz75pL744oug18yfP1/z5s3Tn/70JxUUFGjWrFnatm2bduzYocxMc1+8NTU1stvtcrlcys7ODsM7CU00t33LQmd3M+eZPeehVf/Ro2/sCTq2315brLHFp1t+T56dXPIzQxWOfmixeC0AQGtmv78TJhDyWLx4saZMmRI0EDIMQz169ND06dP185//XJLkcrmUm5urxYsX69prrzX1evEQCPmrSBypL9VoB10e5ZUHNf7xt4Oe9/ykC0NOaI51HaFo3EcAgPnv76TNEaqqqpLT6VRpaan3mN1u17Bhw1ReXu43EGpoaFBDQ4P3cU1NTVTG6080t30rQNAViS7yLWeIrFa6DkU0W1PQBgMA4l/SBkJOp1OSlJub2+x4bm6u93e+zJs3T2VlZREfn1nR3PYdjaAr2CxJOJug+hPN1hS0wQCA+BbTZOkZM2bIZrMF/Nm1a1dUxzRz5ky5XC7vz8cffxzV128pmtu+rQRdoTBT2TmUStcAAIQqpjNC06dP18SJEwOe06tXr5Ce2+FwSJIOHDigvLyvvzwPHDig4uJiv9dlZGQoIyMjpNeMhGhu+45k0GVltoklJQBAtMQ0EOrWrZu6desWkecuKCiQw+HQmjVrvIFPTU2NNm7cqMmTJ0fkNSMhGnkzHpEMuqwu8bGkBACIhoSpI7Rv3z5VVFRo3759amxsVEVFhSoqKlRbW+s955xzztErr7wiSbLZbJoyZYruuece/e1vf9O2bdt0ww03qEePHho3blwM34k1nuKFapIn4xHuisSRrLUTzSU+AADMSphAaPbs2Ro0aJDmzJmj2tpaDRo0SIMGDdK7777rPWf37t1yuVzex3fccYd++tOf6uabb9YFF1yg2tparVy50nQNoXgRrbyZSAZd0VziAwDArISrIxRt8VBHyMNskcO2ikT9m0a3oYvnrw26xLf+zivIBQIAtFnSFlSMtngKhKIpEkEX1ZYBANFCIBQmqRoIRQrVlgEA0ZDylaURn9gaDwCIJwRCiDq2xgMA4kXC7BoDAAAINwIhAACQsgiEAABAyiIQAgAAKYtACAAApCwCIQAAkLIIhAAAQMoiEAIAACmLQAgAAKQsKksH4WnFVlNTE+uhAAAAkzzf28FaqhIIBXHkyBFJUn5+fqyHAgAALDpy5Ijsdrvf39N9Pgi3261PP/1UnTp1ks2W2I1Ba2pqlJ+fr48//jhgJ95kxj34CvfhK9yHr3AfuAceyXQfDMPQkSNH1KNHD6Wl+c8EYkYoiLS0NJ1xxhmxHkZYZWdnJ/wHvK24B1/hPnyF+/AV7gP3wCNZ7kOgmSAPkqUBAEDKIhACAAApi0AohWRkZGjOnDnKyMiI9VBihnvwFe7DV7gPX+E+cA88UvE+kCwNAABSFjNCAAAgZREIAQCAlEUgBAAAUhaBEAAASFkEQkns3nvv1fDhw9WxY0d17tzZ1DUTJ06UzWZr9jNq1KiIjzWSQrkPhmFo9uzZysvLU4cOHVRaWqoPPvgg4mONpEOHDum6665Tdna2OnfurJtuukm1tbUBr7nssstafR5uueWWqI05HBYuXKiePXsqMzNTw4YN06ZNmwKe/9JLL+mcc85RZmamzjvvPL322mtRG2skWbkPixcvbvV3z8zMjOp4w+3NN9/UmDFj1KNHD9lsNi1dujToNevWrdPgwYOVkZGhPn36aPHixVEZayRZvQ/r1q1r9Vmw2WxyOp1RG3OkEQglsePHj+t//ud/NHnyZEvXjRo1StXV1d6f559/PmJjjIZQ7sN9992nhx9+WIsWLdLGjRuVlZWlkSNHqr6+PqJjjaTrrrtO77//vlatWqVXX31Vb775pm6++eag102aNKnZ5+G+++6LynjD4cUXX9S0adM0Z84cbdmyRQMHDtTIkSP12Wef+Tz/rbfe0vjx43XTTTdp69atGjdunMaNG6ft27dHfezhZPU+6GRl4aZ/948++iiqYw63uro6DRw4UAsXLjR1flVVlUaPHq3LL79cFRUVmjJlin70ox/p9ddfj/hYI8nqffDYvXt3s89D9+7dIzbGqDOQ9J566inDbrebOnfChAnG2LFjIz6mWDB7H9xut+FwOIzf/OY33mNffPGFkZGRYTz//PMRHmVk7Nixw5BkvPPOO95jf//73w2bzWbs37/f73WXXnqpcfvtt0dplOE3dOhQ49Zbb/U+bmxsNHr06GHMmzfP5/n/+7//a4wePbrZsWHDhhk//vGPIz7WSLJ6H6z8NyMRSTJeeeWVgOfccccdxrnnntvs2DXXXGOMHDkywqOLHjP34Y033jAkGYcPH47auKKNGSG0sm7dOnXv3l39+vXT5MmTdfDgwVgPKaqqqqrkdDpVWlrqPWa32zVs2DCVl5fHdGyhKi8vV+fOnXX++ed7j5WWliotLU0bN24MeO1zzz2nrl27qqioSDNnztTRo0ejMOK2O378uDZv3tzs75iWlqbS0lK/f8fy8vJm50vSyJEjE/bvrhDvgyTV1tbqrLPOUn5+vsaOHav3338/SiOOD8n4WWiL4uJi5eXlacSIEdqwYUOshxNWNF1FM6NGjdJ3v/tdFRQUqLKyUv/3f/+nq666SuXl5UpPT4/18KLCs/adm5vb7Hhubm7Cros7nc5WU9mnnHKKcnJyAr6nH/zgBzrrrLPUo0cPvffee7rzzju1e/duvfzyy1EYddt8/vnnamxs9Pl33LVrl89rnE5nUv3dFeJ96Nevn/74xz9qwIABcrlcuv/++zV8+HC9//77SdeE2h9/n4WamhodO3ZMHTp0iNnYoikvL0+LFi3S+eefr4aGBj3xxBO67LLLtHHjRg0ePDjWwwsLAqEEM2PGDM2fPz/gOTt37tQ555wT0vNfe+213v993nnnacCAAerdu7fWrVunK6+8MqTnjIRI34dEYfY+hKppDtF5552nvLw8XXnllaqsrFTv3r1Dfl7Et5KSEpWUlHgfDx8+XP3799fvf/97zZ07N6ZjQ3T169dP/fr18z4ePny4Kisr9dBDD+mZZ56J6djChUAowUyfPl0TJ04MeE6vXr3C9nq9evVS165dtWfPnrgKhCJ5HxwOhyTpwIEDysvL8x4/cOCAiouLQ3rOSDF7HxwOR6vE2C+//FKHDh3yvl8zhg0bJknas2dP3AdCXbt2VXp6ug4cONDs+IEDB/y+Z4fDYen8RBDKfWipXbt2GjRokPbs2ROhUcYff5+F7OzslJkN8mfo0KFav359rIcRNgRCCaZbt27q1q1b1F7vk08+0cGDB5sFBPEgkvehoKBADodDa9as8QY+NTU12rhxo+UdeJFm9j6UlJToiy++0ObNmzVkyBBJ0tq1a+V2u73BjRkVFRXSyenyeNe+fXsNGTJEa9as0bhx4yRJbrdba9as0W233ebzmpKSEq1Zs0ZTpkzxHlu1alWz2ZFEE8p9aKmxsVHbtm3T1VdfHeHRxo+SkpJWpRMS/bMQLhUVFQnx3wDTYp2tjcj56KOPjK1btxplZWXGqaeeamzdutXYunWrceTIEe85/fr1M15++WXDMAzjyJEjxs9//nOjvLzcqKqqMlavXm0MHjzY6Nu3r1FfXx/Dd9I2Vu+DYRjGr3/9a6Nz587GsmXLjPfee88YO3asUVBQYBw7dixG76LtRo0aZQwaNMjYuHGjsX79eqNv377G+PHjvb//5JNPjH79+hkbN240DMMw9uzZY9x9993Gu+++a1RVVRnLli0zevXqZVxyySUxfBfWvPDCC0ZGRoaxePFiY8eOHcbNN99sdO7c2XA6nYZhGMYPf/hDY8aMGd7zN2zYYJxyyinG/fffb+zcudOYM2eO0a5dO2Pbtm0xfBdtZ/U+lJWVGa+//rpRWVlpbN682bj22muNzMxM4/3334/hu2ibI0eOeP+/L8l48MEHja1btxofffSRYRiGMWPGDOOHP/yh9/wPP/zQ6Nixo/GLX/zC2Llzp7Fw4UIjPT3dWLlyZQzfRdtZvQ8PPfSQsXTpUuODDz4wtm3bZtx+++1GWlqasXr16hi+i/AiEEpiEyZMMCS1+nnjjTe850gynnrqKcMwDOPo0aPGN7/5TaNbt25Gu3btjLPOOsuYNGmS9z+WicrqfTBObqGfNWuWkZuba2RkZBhXXnmlsXv37hi9g/A4ePCgMX78eOPUU081srOzjRtvvLFZMFhVVdXsvuzbt8+45JJLjJycHCMjI8Po06eP8Ytf/MJwuVwxfBfWPfLII8aZZ55ptG/f3hg6dKjx9ttve3936aWXGhMmTGh2/p///Gfj7LPPNtq3b2+ce+65xooVK2Iw6vCzch+mTJniPTc3N9e4+uqrjS1btsRo5OHh2Qbe8sfzvidMmGBceumlra4pLi422rdvb/Tq1avZfyMSldX7MH/+fKN3795GZmamkZOTY1x22WXG2rVrY/gOws9mfPUlAAAAkHKoIwQAAFIWgRAAAEhZBEIAACBlEQgBAICURSAEAABSFoEQAABIWQRCAAAgZREIAQCAlEUgBAAAUhaBEICYmjhxomw2W6ufcHU6X7x4sTp37hyW5wrVm2++qTFjxqhHjx6y2WxaunRpTMcD4GsEQgBibtSoUaqurm72U1BQEOthtXLixImQrqurq9PAgQO1cOHCsI8JQNsQCAGIuYyMDDkcjmY/6enpkqRly5Zp8ODByszMVK9evVRWVqYvv/zSe+2DDz6o8847T1lZWcrPz9dPfvIT1dbWSpLWrVunG2+8US6XyzvTdNddd0mSz5mZzp07a/HixZKkvXv3ymaz6cUXX9Sll16qzMxMPffcc5KkJ554Qv3791dmZqbOOecc/e53vwv4/q666irdc889+s53vhPmOwegrU6J9QAAwJ9//etfuuGGG/Twww/rG9/4hiorK3XzzTdLkubMmSNJSktL08MPP6yCggJ9+OGH+slPfqI77rhDv/vd7zR8+HAtWLBAs2fP1u7duyVJp556qqUxzJgxQw888IAGDRrkDYZmz56tRx99VIMGDdLWrVs1adIkZWVlacKECRG4CwAiKnaN7wHAMCZMmGCkp6cbWVlZ3p/vf//7hmEYxpVXXmn86le/anb+M888Y+Tl5fl9vpdeesno0qWL9/FTTz1l2O32VudJMl555ZVmx+x2u/HUU08ZhmEYVVVVhiRjwYIFzc7p3bu3sWTJkmbH5s6da5SUlJh6v75eF0DsMCMEIOYuv/xyPfbYY97HWVlZkqR///vf2rBhg+69917v7xobG1VfX6+jR4+qY8eOWr16tebNm6ddu3appqZGX375ZbPft9X555/v/d91dXWqrKzUTTfdpEmTJnmPf/nll7Lb7W1+LQDRRyAEIOaysrLUp0+fVsdra2tVVlam7373u61+l5mZqb179+pb3/qWJk+erHvvvVc5OTlav369brrpJh0/fjxgIGSz2fTVBM3XfCVDe4Iyz3gk6fHHH9ewYcOanefJaQKQWAiEAMStwYMHa/fu3T6DJEnavHmz3G63HnjgAaWlfbX3489//nOzc9q3b6/GxsZW13br1k3V1dXexx988IGOHj0acDy5ubnq0aOHPvzwQ1133XUhvisA8YRACEDcmj17tr71rW/pzDPP1Pe//32lpaXp3//+t7Zv36577rlHffr00YkTJ/TII49ozJgx2rBhgxYtWtTsOXr27Kna2lqtWbNGAwcOVMeOHdWxY0ddccUVevTRR1VSUqLGxkbdeeedateuXdAxlZWV6Wc/+5nsdrtGjRqlhoYGvfvuuzp8+LCmTZvm85ra2tpmdZGqqqpUUVGhnJwcnXnmmWG4UwBCFuskJQCpbcKECcbYsWP9/n7lypXG8OHDjQ4dOhjZ2dnG0KFDjT/84Q/e3z/44INGXl6e0aFDB2PkyJHG008/bUgyDh8+7D3nlltuMbp06WJIMubMmWMYhmHs37/f+OY3v2lkZWUZffv2NV577TWfydJbt25tNabnnnvOKC4uNtq3b2+cdtppxiWXXGK8/PLLft/DG2+8YUhq9TNhwoSQ7xuA8LAZLRfJAQAAUgQFFQEAQMoiEAIAACmLQAgAAKQsAiEAAJCyCIQAAEDKIhACAAApi0AIAACkLAIhAACQsgiEAABAyiIQAgAAKYtACAAApKz/D3G7DYY0sjs8AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.scatter(X_norm[:, 0], y_centered)\n",
+    "plt.xlabel(\"Feature 1\")\n",
+    "plt.ylabel(\"Target\")"
    ]
   },
   {
@@ -269,7 +283,30 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d5dc7708",
+   "id": "5e5da080",
+   "metadata": {},
+   "source": [
+    "<div class=\"alert alert-block alert-success\">\n",
+    "The gradients can be calculated as\n",
+    "\n",
+    "$$\n",
+    "\\nabla_\\theta C_{OLS} = \\nabla_\\theta (X\\cdot\\theta - y)^2 = 2 X (X\\cdot \\theta - y)\n",
+    "$$\n",
+    "\n",
+    "The gradient of the Ridge cost function then directly follows as\n",
+    "\n",
+    "$$\n",
+    "\\nabla_\\theta C_\\mathrm{Ridge} = \\nabla_\\theta C_{OLS} + \\nabla_\\theta \\lambda \\theta^2 = 2 X (X\\cdot \\theta - y) + 2 \\lambda \\theta\n",
+    "$$\n",
+    "\n",
+    "Because the factors of 2 are somewhat tedious, I will from here on use $\\tilde C = \\frac{C}{2}$.\n",
+    "\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be65f56f",
    "metadata": {
     "editable": true
    },
@@ -279,8 +316,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "77c59cc4",
+   "execution_count": 6,
+   "id": "a616cdee",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -293,23 +330,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "97ac6cb6",
-   "metadata": {
-    "collapsed": false,
-    "editable": true
-   },
+   "execution_count": 7,
+   "id": "a7256776",
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Closed-form Ridge coefficients: [ 5.02716096e+00 -2.88896347e+00 -1.55169486e-02  1.52287662e-01\n",
-      " -6.93302234e-02 -4.47229113e-02  1.76836298e+00  4.62139092e-03\n",
-      "  4.41380481e-02 -4.96664608e-02]\n",
-      "Closed-form OLS coefficients: [ 5.03241281e+00 -2.89258175e+00 -1.55189951e-02  1.51795012e-01\n",
-      " -6.83299260e-02 -4.40147965e-02  1.76999871e+00  4.37643569e-03\n",
-      "  4.52550260e-02 -4.97610000e-02]\n"
+      "Closed-form Ridge coefficients: [-0.4835408   1.41698898]\n",
+      "Closed-form OLS coefficients: [-0.51267301  1.44659558]\n"
      ]
     }
    ],
@@ -366,8 +396,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "id": "99dc481e",
+   "execution_count": 8,
+   "id": "3edc1a2c",
    "metadata": {},
    "outputs": [
     {
@@ -376,13 +406,13 @@
        "Text(0.5, 1.0, 'Feature Coefficients ($\\\\theta^\\\\lambda_i - \\\\bar{\\\\theta}_i$)')"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -441,8 +471,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "c8fb3f01",
+   "execution_count": 9,
+   "id": "392b0bb7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -477,23 +507,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "a67af634",
-   "metadata": {
-    "collapsed": false,
-    "editable": true
-   },
+   "execution_count": 10,
+   "id": "be6ebfa8",
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Gradient Descent OLS coefficients: [ 5.03241281e+00 -2.89258175e+00 -1.55189951e-02  1.51795012e-01\n",
-      " -6.83299260e-02 -4.40147965e-02  1.76999871e+00  4.37643569e-03\n",
-      "  4.52550260e-02 -4.97610000e-02]\n",
-      "Gradient Descent Ridge coefficients: [ 5.02716096e+00 -2.88896347e+00 -1.55169486e-02  1.52287662e-01\n",
-      " -6.93302234e-02 -4.47229113e-02  1.76836298e+00  4.62139092e-03\n",
-      "  4.41380481e-02 -4.96664608e-02]\n"
+      "Gradient Descent OLS coefficients: [-0.47433764  1.40826022]\n",
+      "Gradient Descent Ridge coefficients: [-0.44990454  1.38335272]\n"
      ]
     }
    ],
@@ -511,18 +534,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "2bbb16b9",
+   "execution_count": 11,
+   "id": "32a7e3a3",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Gradient Descent OLS error: (array([ 0.03241281,  0.10741825, -0.015519  ,  0.15179501, -0.06832993,\n",
-      "       -0.0440148 , -0.23000129,  0.00437644,  0.04525503, -0.049761  ]), np.float64(0.009992203674399302))\n",
-      "Gradient Descent Ridge error: (array([ 0.02716096,  0.11103653, -0.01551695,  0.15228766, -0.06933022,\n",
-      "       -0.04472291, -0.23163702,  0.00462139,  0.04413805, -0.04966646]), np.float64(0.010139794608820855))\n"
+      "Gradient Descent OLS error: (array([ 0.10881529, -0.09837005]), np.float64(0.010758716397832158))\n",
+      "Gradient Descent Ridge error: (array([ 0.13324839, -0.12327754]), np.float64(0.016476242667611243))\n"
      ]
     }
    ],
@@ -549,8 +570,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "0871c0a5",
+   "execution_count": 12,
+   "id": "006ce51b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -570,13 +591,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "49a2cb11",
+   "execution_count": 13,
+   "id": "b06f0bc6",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Mu4F0v/r160sXHUVq1qz5yEtNFb3uogsnOWXtMHiQu7s7Pv30U/znP//BqVOnsGnTJsyePRsxMTFwd3fHG2+88dBztG7dukyTBZa0soDcY+fOnYNWqy228oCbmxtq1Kgh/e6X5dxERGXFPGeeF1E6z+8XFxeHJ598EtnZ2Vi6dCl+++036bWU5ty5c2jcuHGxuh68Ha7o9+nBDLW1tS0218OpU6dw/Phx2X9AP/i7UxIbGxuEhYU9tB1Kyet69eoVm9jv3Llz8PHxKTYxZ7NmzaTHy3JuorJgRwA9EmdnZ7i7u+PIkSPFHiu6x7Do/q8H6XS6Yh9wer0eL7zwAjIzM/F///d/aNq0KRwdHXHp0iUMHjwYBoOhwjUXneP111+XvT/8qaeeMvpZbhmYsn5z/CiK3tOiMDMYDKhbty6+/vrrEtsXBZlGo8G3336LP/74Az/99BM2bdqEIUOGYP78+fjjjz/KfK+jwWCARqPBL7/8UuLrf/A8Sr9HRb9bD7vwOHToEOrVq1fsXryy0mg0ePLJJ/Hkk0+iW7du8PHxwddff12mjoCyKm0Wf7nHHrzYeZRzExGVFfOceV7ElO/R/R3oERERaNeuHV577TWcPHmyQnMxPAqDwYCWLVvKLu14/6SYSpDLayVynNcCVBHsCKBH1q1bN3zxxRfYs2cPWrduXaFzHT58GH/++SdWrFiBgQMHSvu3bNli1K5o/eJTp04VO8fJkydLfY46deqgevXq0Ov1Ze7FLYuy/sOtLG7cuIHvv/8enp6eUu9vo0aN8L///Q/PPPNMmT7w27RpgzZt2uD999/HqlWr0L9/f6xevRpvvPEGGjVqhE2bNiEzM1P2W4RGjRpBCAFvb288+eSTiryu8r5H3bt3x+eff46dO3dKM+rfb8eOHTh79ixGjBihSH0NGzZEzZo18ffffytyvkfRoEEDGAwGnDp1Svp/j7sTYmVlZam2djcRWT7m+R3M84dT4j2ysbFBbGwsOnTogEWLFmHKlCmybRs0aIAjR45ACGH03A/+jhT9Pp0+fRodOnSQ9hcWFuLs2bNGHUONGjXCwYMH0bFjR0X/nyuhQYMGOHToEAwGg1En24kTJ6THiZTCOQLokU2ePBlVq1bFkCFDkJ6eXuzx8vQgF/VC33+MEAIff/yxUTt3d3f4+/tjxYoV0vBC3L3AeNiSKTY2NujZsyfWrVtX4jcfGRkZZa73fo6Ojka1PKq8vDwMGDAAmZmZmDZtmhROvXv3hl6vx7vvvlvsmMLCQmRlZQF3hzc++J77+/sDd5fJwd17yYQQePvtt4udq+jYV155BTY2Nnj77beLnU8IgWvXrpX7tRWtmVtU68NMmjQJDg4OGDFiRLHny8zMxJtvvomqVati0qRJ5apj9+7dRjP2FtmzZw+uXbum6sz7Xbt2BQAsWLDAaH/RNxbdunVTpS4isnzM8zuY5w9X3jyXExoaitatW2PBggW4deuWbLuuXbvi8uXL+Pbbb6V9RcsL3y8wMBC1atXC559/jsLCQmn/119/Xez2j969e+PSpUv4/PPPiz1fXl5eidcJlaVr165IS0vDmjVrpH2FhYX45JNPUK1aNbRv31612sjycEQAPTIfHx+sWrUK/fr1Q5MmTdC/f3/4+flBCIHU1FSsWrUKWq22TMsANW3aFI0aNcLEiRNx6dIlODk5Yd26dSXeuxcbG4tu3bqhXbt2GDJkCDIzM/HJJ5+gefPmJd7jeL8PPvgAv/76K4KDgzFs2DD4+voiMzMT+/fvx//+9z9kZmaW+30ICAjAmjVrEBUVhaCgIFSrVg0vvvhiqcdcunQJX331FXD3W4Njx45h7dq1SEtLw4QJE4y+6W7fvj1GjBiB2NhYpKSkoFOnTqhSpQpOnTqFtWvX4uOPP8arr76KFStW4D//+Q969OiBRo0a4fr16/j888/h5OQk/SOzQ4cOGDBgABYuXIhTp06hc+fOMBgM2LFjBzp06IBRo0ahUaNGeO+99xAdHS0tvVO9enWkpqbi+++/x/DhwzFx4sRyvUeNGjVCjRo1EB8fj+rVq8PR0RHBwcGy97b5+PhgxYoV6N+/P1q2bImhQ4fC29sbZ8+exZIlS3D16lX897//RaNGjYodu3TpUiQkJBTbP3bsWKxcuRJff/01evTogYCAANjZ2eH48eNYunQp7O3tpTV8H+aXX36Reufv17ZtWzRs2LBM53iQn58fBg0ahMWLFyMrKwvt27fHnj17sGLFCkRERBh9w0FEpCTm+R3M84crb56XZtKkSejVqxeWL19ebALdIsOGDcOiRYswcOBA7Nu3D+7u7li5cqW0VGUROzs7zJo1C6NHj8bzzz+P3r174+zZs1i+fDkaNWpk9M3/gAED8M033+DNN9/Er7/+imeeeQZ6vR4nTpzAN998g02bNj10HqDCwkLp//uDevToIXWYlNfw4cPx2WefYfDgwdi3bx+8vLzw7bffYteuXViwYEG550UiKpXayxbQ4+/06dPirbfeEo0bNxb29vbCwcFBWpotJSXFqO2gQYOEo6Njiec5duyYCAsLE9WqVRO1a9cWw4YNEwcPHixxmZp169aJZs2aCZ1OJ3x9fcV3330nBg0a9NDlhoQQIj09XYwcOVJ4enqKKlWqCDc3N9GxY0exePFiqU3RckNr1641OrZouZb767lx44Z47bXXRI0aNUpc8uhBRUu/ARAajUY4OTmJ5s2bi2HDhondu3fLHrd48WIREBAgHBwcRPXq1UXLli3F5MmTxeXLl4UQQuzfv1/069dPPPHEE0Kn04m6deuK7t27i7179xqdp7CwUMydO1c0bdpU2NnZiTp16oguXbqIffv2FXuP27VrJxwdHYWjo6No2rSpGDlypDh58qTUpn379qJ58+bFai3p/8UPP/wgfH19ha2tbZmXHjp06JDo16+fcHd3l/5f9evXz2i5pyKlLe0HQFy4cEEcOnRITJo0STz99NPCxcVF2NraCnd3d9GrVy+xf//+h9bzsOcoek1Fvydz584tdo6i5QMzMjKKPXb79m3x9ttvC29vb1GlShXh6ekpoqOjxa1bt4zaPWzJKiKiR8E8Z54/qKJ5XtrSvnq9XjRq1Eg0atRIWl7vweUDhRDi3Llz4qWXXhJVq1YVtWvXFmPHjpWWXCxaPrDIwoULRYMGDYROpxOtW7cWu3btEgEBAaJz585G7QoKCsTs2bNF8+bNhU6nEzVr1hQBAQHi7bffFtnZ2bKvRzxk+UAAIjU19aGvXe79Fnd/ryMjI0Xt2rWFnZ2daNmyZbH3uLTrDKKy0ghTzpJCRERERESkAoPBgDp16uCVV14p8VYAImvGOQKIiIiIiOixduvWrWJzIXz55ZfIzMxEaGioanURmSuOCCAiIiIiosfatm3bMH78ePTq1Qu1atXC/v37sWTJEjRr1gz79u2DnZ2d2iUSmRVOFkhERERERI81Ly8veHp6YuHChdKyigMHDsQHH3zATgCiEnBEABEREREREZEV4RwBRERERERERFaEHQFEREREREREVoRzBJiQwWDA5cuXUb16dWg0GrXLISJ67AghcP36dXh4eECrVa7v+tatWygoKFDkXHZ2drC3t1fkXPT4YdYTEVUMs14d7AgwocuXL8PT01PtMoiIHnsXLlxA/fr1FTnXrVu34N2gGtKu6BU5n5ubG1JTUy3uAoHKhllPRKQMZn3lYkeACVWvXh0AcG6/F5yq8S4Mc6IXBrVLQL4oVLsEAMAVvTI9pRW165aX2iUAAD462lHtEgAA9eLN4+NZ+/shVZ+/ELexExulz1MlFBQUIO2KHqn7GsCpesU+m3OuG+AdcA4FBQUWdXFAZcesN1/M+nuY9caY9ca0SYdVff5CcRs78TOzvpKZx2+fhSoaIuhUTVvhX0BSlt4M1srIF+bxO5GnN486HGzN4+PIpqp5fMDbmsn7odVUUbeAu39XTTHk2qk6P5up4pj15otZfw+z3hiz3pjqWY87ec+sr1zm8dtHRERUyfTCUOF/KJjDN45ERERUMma9PHYEEBGRVTJAwICKXR1U9HgiIiIyHWa9PI6TICIiIiIiIrIiHBFARERWyQADKjrYr+JnICIiIlNh1stjRwAREVklvRDQi4oN96vo8URERGQ6zHp5vDWAiIiIiIiIyIpwRAAREVklTiBERERk2Zj18tgRQEREVskAAT0vDoiIiCwWs14ebw0gIiIiIiIisiIcEUBERFaJwwWJiIgsG7NeHjsCiIjIKnEmYSIiIsvGrJfHWwOIiIiIiIiIrIhZdATExcXBy8sL9vb2CA4Oxp49e0ptv3btWjRt2hT29vZo2bIlNm7caPS4EAIxMTFwd3eHg4MDwsLCcOrUKaM2mZmZ6N+/P5ycnFCjRg0MHToUN27ckB6/desWBg8ejJYtW8LW1hYREREKv2oiIlKTQaENAIKCguDr64u4uDiVX5X5YtYTEVFlY9bLU70jYM2aNYiKisLMmTOxf/9++Pn5ITw8HFeuXCmx/e+//45+/fph6NChOHDgACIiIhAREYEjR45IbebMmYOFCxciPj4eu3fvhqOjI8LDw3Hr1i2pTf/+/XH06FFs2bIFGzZswG+//Ybhw4dLj+v1ejg4OGDMmDEICwsz8btARESVTX93JuGKbgCQnJyMY8eOYeTIkWq/LLPErCciIjUw6+VphFD3pofg4GAEBQVh0aJFAACDwQBPT0+MHj0aU6ZMKda+T58+yM3NxYYNG6R9bdq0gb+/P+Lj4yGEgIeHByZMmICJEycCALKzs+Hq6orly5ejb9++OH78OHx9fZGcnIzAwEAAQEJCArp27YqLFy/Cw8PD6DkHDx6MrKwsrF+/vlyvLScnB87Ozvjnz4Zwqq56nwvdRy8MZWhlWvmiUO0SAADp+gK1SwAAbM9rqHYJAIDZh8PVLgEAUH+heUzhot1xQNXnLxS3sQ0/IDs7G05OToqcs+iz+ejxuqhewc/m69cNaN7siqL1WSJmPamBWX8Ps94Ys96YdmeKqs9fKG5jm1jPrK9kqiZWQUEB9u3bZ9QLr9VqERYWhqSkpBKPSUpKKtZrHx4eLrVPTU1FWlqaURtnZ2cEBwdLbZKSklCjRg3pwgAAwsLCoNVqsXv37kd+Pfn5+cjJyTHaiIjIPOmFMhuVjllPRERqYdbLU7Uj4OrVq9Dr9XB1dTXa7+rqirS0tBKPSUtLK7V90Z8Pa1O3bl2jx21tbeHi4iL7vGURGxsLZ2dnafP09HzkcxERkWkped8gyWPWExGRWpj18jiGTUHR0dHIzs6WtgsXLqhdEhERESmIWU9ERJZA1RtTateuDRsbG6SnpxvtT09Ph5ubW4nHuLm5ldq+6M/09HS4u7sbtfH395faPDhBUWFhITIzM2Wftyx0Oh10Ot0jH09ERJXHAA300FT4HFQ6Zj0REamFWS9P1REBdnZ2CAgIQGJiorTPYDAgMTERISEhJR4TEhJi1B4AtmzZIrX39vaGm5ubUZucnBzs3r1bahMSEoKsrCzs27dParN161YYDAYEBwcr/jqJiMj8GIQyG5WOWU9ERGph1stTfarKqKgoDBo0CIGBgWjdujUWLFiA3NxcREZGAgAGDhyIevXqITY2FgAwduxYtG/fHvPnz0e3bt2wevVq7N27F4sXLwYAaDQajBs3Du+99x58fHzg7e2NGTNmwMPDQ1ofuFmzZujcuTOGDRuG+Ph43L59G6NGjULfvn2NZhE+duwYCgoKkJmZievXryMl5c6MmkXfNhAREdHDMeuJiIjMi+odAX369EFGRgZiYmKQlpYGf39/JCQkSBMAnT9/HlrtvYELbdu2xapVqzB9+nRMnToVPj4+WL9+PVq0aCG1mTx5MnJzczF8+HBkZWWhXbt2SEhIgL29vdTm66+/xqhRo9CxY0dotVr07NkTCxcuNKqta9euOHfunPRzq1atAAAqr7hIREQK0CswXLCix1sLZj0REamBWS9PI5h0JsO1hc0X1xa+h2sLG+Pawsa0Ow6o+vyF4ja24QeTrC38+1F3VKvgZ/ON6wa0bf63xa0tTGXHrDdfzPp7mPXGmPXGtDtTVH3+QnEb28R6Zn0lY2IRERERERERWRHz6IYiIiKqZAahgUFUcCbhCh5PREREpsOsl8eOACIiskq8b5CIiMiyMevl8dYAIiIiIiIiIivCEQFERGSV9NBCX8H+cL1i1RAREZHSmPXy2BFARERWSShw36Cw0PsGiYiILAGzXh5vDSAiIiIiIiKyIhwRQEREVokTCBEREVk2Zr08dgQQEZFV0gst9KKC9w0KxcohIiIihTHr5fHWACIiIiIiIiIrwhEBRERklQzQwFDB/nADLPRrAiIiIgvArJfHjgAiIrJKvG+QiIjIsjHr5bEjgCqVXhjULgEAkC8K1S4B6foCtUsAAGzPa6h2CQCA2YfD1S4BAFB/oXl8LGp3HFC7BCKiR8Ksv4dZb4xZb0y7M0XtEu4QKn/jrfbzWynz+FtARERUyZSZQIgXL0REROaKWS+PHQFERGSV7tw3WLHhfhU9noiIiEyHWS+PqwYQERFVUFBQEHx9fREXF6d2KURERGQClpb1HBFARERWyQAt9ArNJJycnAwnJyeFKiMiIiIlMOvlsSOAiIisEu8bJCIismzMenm8NYCIiIiIiIjIinBEABERWSUDtDAoNFyQiIiIzA+zXh47AoiIyCrphQZ6UbGZgCt6PBEREZkOs14ebw0gIiIiIiIisiIcEUBERFZJr8BMwnoLHS5IRERkCZj18tgRQEREVskgtDBUcCZhg4XOJExERGQJmPXyeGsAERERERERkRXhiAAiIrJKHC5IRERk2Zj18tgRQEREVsmgwEzABsWqISIiIqUx6+Xx1gAiIiIiIiIiK2IWHQFxcXHw8vKCvb09goODsWfPnlLbr127Fk2bNoW9vT1atmyJjRs3Gj0uhEBMTAzc3d3h4OCAsLAwnDp1yqhNZmYm+vfvDycnJ9SoUQNDhw7FjRs3pMdPnjyJDh06wNXVFfb29mjYsCGmT5+O27dvK/zqiYhIDQZoFdmobJj1RERU2Zj18lR/VWvWrEFUVBRmzpyJ/fv3w8/PD+Hh4bhy5UqJ7X///Xf069cPQ4cOxYEDBxAREYGIiAgcOXJEajNnzhwsXLgQ8fHx2L17NxwdHREeHo5bt25Jbfr374+jR49iy5Yt2LBhA3777TcMHz5cerxKlSoYOHAgNm/ejJMnT2LBggX4/PPPMXPmTBO/I0REVBn0QqvIRg/HrCciIjUw6+VphFB3PYTg4GAEBQVh0aJFAACDwQBPT0+MHj0aU6ZMKda+T58+yM3NxYYNG6R9bdq0gb+/P+Lj4yGEgIeHByZMmICJEycCALKzs+Hq6orly5ejb9++OH78OHx9fZGcnIzAwEAAQEJCArp27YqLFy/Cw8OjxFqjoqKQnJyMHTt2lPh4fn4+8vPzpZ9zcnLg6emJf/5sCKfqlvkLVF56YR532eSLQrVLQLq+QO0SAADb8xqqXQIAYPbhcLVLAADUX2geU6dodxxQuwSzUChuYxt+QHZ2NpycnBQ5Z05ODpydnbFoXzAcqlXs/3fejUKMCtitaH2WiFlvXZj19zDrjTHrjWl3pqhdwh0qL4/HrFeHqolVUFCAffv2ISws7F5BWi3CwsKQlJRU4jFJSUlG7QEgPDxcap+amoq0tDSjNs7OzggODpbaJCUloUaNGtKFAQCEhYVBq9Vi9+7dJT7v6dOnkZCQgPbt28u+ntjYWDg7O0ubp6dnmd8LIiKqXAZoFNmodMx6IiJSC7NenqodAVevXoVer4erq6vRfldXV6SlpZV4TFpaWqnti/58WJu6desaPW5rawsXF5diz9u2bVvY29vDx8cHzz77LN555x3Z1xMdHY3s7Gxpu3DhQhneBSIiUgOHC1YOZj0REamFWS/PMl+VgtasWYP9+/dj1apV+PnnnzFv3jzZtjqdDk5OTkYbERERmTdmPRERWRtVb5CpXbs2bGxskJ6ebrQ/PT0dbm5uJR7j5uZWavuiP9PT0+Hu7m7Uxt/fX2rz4ARFhYWFyMzMLPa8RUP+fH19odfrMXz4cEyYMAE2NjYVeOVERKQ2PbTQV7A/vKLHWwNmPRERqYVZL0/VV2VnZ4eAgAAkJiZK+wwGAxITExESElLiMSEhIUbtAWDLli1Se29vb7i5uRm1ycnJwe7du6U2ISEhyMrKwr59+6Q2W7duhcFgQHBwsGy9BoMBt2/fhsFgHpPgEBHRozMIjSIblY5ZT0REamHWy1N9ysyoqCgMGjQIgYGBaN26NRYsWIDc3FxERkYCAAYOHIh69eohNjYWADB27Fi0b98e8+fPR7du3bB69Wrs3bsXixcvBgBoNBqMGzcO7733Hnx8fODt7Y0ZM2bAw8MDERERAIBmzZqhc+fOGDZsGOLj43H79m2MGjUKffv2lWYR/vrrr1GlShW0bNkSOp0Oe/fuRXR0NPr06YMqVaqo9n4RERE9bpj1RERE5kX1joA+ffogIyMDMTExSEtLg7+/PxISEqQJgM6fPw+t9t7AhbZt22LVqlWYPn06pk6dCh8fH6xfvx4tWrSQ2kyePBm5ubkYPnw4srKy0K5dOyQkJMDe3l5q8/XXX2PUqFHo2LEjtFotevbsiYULF0qP29raYvbs2fjzzz8hhECDBg0watQojB8/vtLeGyIiMh2DAsMFDRY6XFBpzHoiIlIDs16eRgiVF460YEXrV3Jt4Xu4tvA9XFvYGNcWNqbdcUDtEsyCKdcW/veeDrCv4NrCt24UYmrrXy1ubWEqO2Z9ccz6e5j1xpj1xrQ7U9Qu4Q6V/znIrFcHE4uIiIiIiIjIiphHdxgREVEl00MDPSo2AVBFjyciIiLTYdbLY0cAERFZJYPQwiAqeN9gBY8nIiIi02HWy7PMV0VEREREREREJeKIACIiskp6BYb76RWrhoiIiJTGrJfHjgAiIrJKHC5IRERk2Zj18izzVRERERERERFRiTgigIiIrJJeaKGvYC9/RY8nIiIi02HWy2NHABERWSUBDQwVvG9QWOiSQkRERJaAWS/PMrs3iIiIiIiIiKhEHBFARERWicMFiYiILBuzXh47AqyEXhjULgEAkC8K1S4BAJCuL1C7BGzPa6h2CQCA2YfD1S4BAFB/oXl8HGl3HFC7BKokBqGBQVRsuF9FjydSErPeGLP+Hma9Me3OFLVLuEMItSuweMx6eZbZvUFEREREREREJTKPbjkiIqJKpocW+gr2h1f0eCIiIjIdZr08dgQQEZFV4nBBIiIiy8asl2eZ3RtEREREREREVCJ2BBARkVUyQKvIpoYNGzagSZMm8PHxwRdffKFKDUREROaOWS+PtwYQEZFV0gsN9BUc7lfR4x9FYWEhoqKi8Ouvv8LZ2RkBAQHo0aMHatWqVem1EBERmTNmvTyOCCAiInqM7NmzB82bN0e9evVQrVo1dOnSBZs3b1a7LCIiIlJIZWQ9OwKIiMgqFU0gVNGtvH777Te8+OKL8PDwgEajwfr164u1iYuLg5eXF+zt7REcHIw9e/ZIj12+fBn16tWTfq5Xrx4uXbpUgXeCiIjIMjHr5bEjgIiIrJIQWhgquAlxJ0ZzcnKMtvz8fNnnzc3NhZ+fH+Li4kp8fM2aNYiKisLMmTOxf/9++Pn5ITw8HFeuXDHZe0FERGSJmPXy2BFARERUQZ6ennB2dpa22NhY2bZdunTBe++9hx49epT4+Icffohhw4YhMjISvr6+iI+PR9WqVbF06VIAgIeHh9G3ApcuXYKHh4cJXhUREREVsbSs52SBRERklfTQQI8KTiB09/gLFy7AyclJ2q/T6R7pfAUFBdi3bx+io6OlfVqtFmFhYUhKSgIAtG7dGkeOHMGlS5fg7OyMX375BTNmzKjQ6yAiIrJEzHp57AggIiKrZBB4pPv+HjwHADg5ORldHDyqq1evQq/Xw9XV1Wi/q6srTpw4AQCwtbXF/Pnz0aFDBxgMBkyePJkrBhAREZWAWS+PHQFERESPmZdeegkvvfSS2mUQERGRiZg669kRQEREVqloEqCKnkNJtWvXho2NDdLT0432p6enw83NTdHnIiIisnTMenmcLJCIiKySARpFNiXZ2dkhICAAiYmJ9+o0GJCYmIiQkBBFn4uIiMjSMevlmUVHQGlrKJZk7dq1aNq0Kezt7dGyZUts3LjR6HEhBGJiYuDu7g4HBweEhYXh1KlTRm0yMzPRv39/ODk5oUaNGhg6dChu3Lhh1GbTpk1o06YNqlevjjp16qBnz544e/asgq+ciIiszY0bN5CSkoKUlBQAQGpqKlJSUnD+/HkAQFRUFD7//HOsWLECx48fx1tvvYXc3FxERkaqXHnFMOuJiMhaPA5Zr3pHQHnXUPz999/Rr18/DB06FAcOHEBERAQiIiJw5MgRqc2cOXOwcOFCxMfHY/fu3XB0dER4eDhu3boltenfvz+OHj2KLVu2YMOGDfjtt98wfPhw6fHU1FS8/PLLeP7555GSkoJNmzbh6tWreOWVV0z8jhARUWXQC40iGwAEBQXB19dXdr3g++3duxetWrVCq1atgLsXA61atUJMTAwAoE+fPpg3bx5iYmLg7++PlJQUJCQkFJtU6HHCrCciIjUw6+VphBCi0p6tBMHBwQgKCsKiRYuAu8MiPD09MXr0aEyZMqVY+z59+iA3NxcbNmyQ9rVp0wb+/v6Ij4+HEAIeHh6YMGECJk6cCADIzs6Gq6srli9fjr59++L48ePw9fVFcnIyAgMDAQAJCQno2rUrLl68CA8PD3z77bfo168f8vPzodXe6S/56aef8PLLLyM/Px9VqlR56GvLycmBs7Mz/vmzIZyqq9vnohcGVZ+/SL4oVLsEAEC6vkDtErA9r6HaJQAAZh8OV7sEAED9heYxZYl2xwG1S6D7FIrb2IYfkJ2drchMvbjvs7lv4uuwq2ZXoXMV3CjA6o5fKVqfJWLWVw5mvTFm/T3MemPanSlql3CHuv8MMxvMenWomlhFayiGhYXdK+iBNRQflJSUZNQeAMLDw6X2qampSEtLM2rj7OyM4OBgqU1SUhJq1KghXRgAQFhYGLRaLXbv3g0ACAgIgFarxbJly6DX65GdnY2VK1ciLCxM9sIgPz8fOTk5RhsREZE1Y9YTERGZH1U7AkpbQzEtLa3EY9LS0kptX/Tnw9rUrVvX6HFbW1u4uLhIbby9vbF582ZMnToVOp0ONWrUwMWLF/HNN9/Ivp7Y2Fg4OztLm6enZzneDSIiqkwGaGAQFdwUnkDIEjHriYhILcx6earPEWCu0tLSMGzYMAwaNAjJycnYvn077Ozs8Oqrr0Luboro6GhkZ2dL24ULFyq9biIiKhuhwCzCwkIvDqwFs56IyLIx6+WpeqPOo6yh6ObmVmr7oj/T09Ph7u5u1Mbf319q8+AERYWFhcjMzJSOj4uLg7OzM+bMmSO1+eqrr+Dp6Yndu3ejTZs2xWrT6XTQ6XTlfh+IiIgsFbOeiIjI/Kg6IuBR1lAMCQkxag8AW7Zskdp7e3vDzc3NqE1OTg52794ttQkJCUFWVhb27dsntdm6dSsMBgOCg4MBADdv3pQmDipiY2Mj1UhERI+3Cg8VvLtR6Zj1RESkFma9PNVvDXjYGooDBw5EdHS01H7s2LFISEjA/PnzceLECcyaNQt79+7FqFGjAAAajQbjxo3De++9hx9//BGHDx/GwIED4eHhgYiICABAs2bN0LlzZwwbNgx79uzBrl27MGrUKPTt2xceHh4AgG7duiE5ORnvvPMOTp06hf379yMyMhINGjSQloEgIqLHl0FoFdlQziWFrBGznoiI1MCsl6f6Gh59+vRBRkYGYmJikJaWBn9/f6M1FM+fP2/UW9+2bVusWrUK06dPx9SpU+Hj44P169ejRYsWUpvJkycjNzcXw4cPR1ZWFtq1a4eEhATY29tLbb7++muMGjUKHTt2hFarRc+ePbFw4ULp8eeffx6rVq3CnDlzMGfOHFStWhUhISFISEiAg4NDpb0/RERk/pKTky1qSSGlMeuJiOhxZ2lZrxFys+FQhXFt4eK4tvA9XFvYmNmsLbzjgNol0H1Mubbwy5uHoIpjxdYWvp1bgB86LbW4tYWp7Jj1xTHr72HWGzObrN+ZonYJd/CfYQCzXjXm8beRiIiokhXNBlzRcxAREZF5YtbLU32OACIiIiIiIiKqPBwRQEREVkmJmYAtdSZhIiIiS8Csl8eOACIiskq8OCAiIrJszHp5vDWAiIiIiIiIyIpwRAAREVklfktARERk2Zj18jgigIiIrFLRxUFFNwAICgqCr68v4uLi1H5ZREREdBezXh5HBBAREVVQcnKyRa0tTERERMYsLevZEUBERFZJKLA2sFCsGiIiIlIas14eOwKIiMgq8b5BIiIiy8asl8c5AoiIiIiIiIisCEcEEBGRVeK3BERERJaNWS+PHQGVQC8M0Kt8c0m+KFS3gLvS9QVqlwAA2J7XUO0SMPtwuNolAADqLzSPjwHtjgNql0BWhhcHpCRm/T3M+nuY9ca0O1PULuEOYal3fdODmPXyeGsAERERERERkRUxj+5BIiKiSsZvCYiIiCwbs14eOwKIiMgqCaGBqGC4V/R4IiIiMh1mvTzeGkBERFRBQUFB8PX1RVxcnNqlEBERkQlYWtZzRAAREVklAzQwoILDBe8en5ycDCcnJ4UqIyIiIiUw6+WxI4CIiKwS7xskIiKybMx6ebw1gIiIiIiIiMiKcEQAERFZJU4gREREZNmY9fLYEUBERFaJwwWJiIgsG7NeHm8NICIiIiIiIrIiHBFARERWicMFiYiILBuzXh47AoiIyCoJBYYLWurFARERkSVg1svjrQFEREREREREVoQjAoiIyCoJAEJU/BxERERknpj18tgRQEREVskADTSo4EzCFTyeiIiITIdZL88sbg2Ii4uDl5cX7O3tERwcjD179pTafu3atWjatCns7e3RsmVLbNy40ehxIQRiYmLg7u4OBwcHhIWF4dSpU9LjZ8+exdChQ+Ht7Q0HBwc0atQIM2fOREFBgdRm27ZtePnll+Hu7g5HR0f4+/vj66+/NsGrJyKix11QUBB8fX0RFxendilmi1lPRESPM0vLetU7AtasWYOoqCjMnDkT+/fvh5+fH8LDw3HlypUS2//+++/o168fhg4digMHDiAiIgIRERE4cuSI1GbOnDlYuHAh4uPjsXv3bjg6OiI8PBy3bt0CAJw4cQIGgwGfffYZjh49io8++gjx8fGYOnWq0fM89dRTWLduHQ4dOoTIyEgMHDgQGzZsqIR3hYiITK1oJuGKbgCQnJyMY8eOYeTIkWq/LLPErCciIjUw6+VphKjoXRMVExwcjKCgICxatAgAYDAY4OnpidGjR2PKlCnF2vfp0we5ublGId2mTRv4+/sjPj4eQgh4eHhgwoQJmDhxIgAgOzsbrq6uWL58Ofr27VtiHXPnzsWnn36Kv/76S7bWbt26wdXVFUuXLi3x8fz8fOTn50s/5+TkwNPTE1dPesGpurp9LvmiUNXnL5KuLyhDK9PbntdQ7RIw+3C42iUAAOovNI87hLQ7DqhdApmhQnEb2/ADsrOz4eTkpMg5c3Jy4OzsjBbfTIJNVV2FzqW/mY8jvecqWp8lYtZXDma9MWb9PWaT9TtT1C7hDnX/+UMPYNarQ9XEKigowL59+xAWFnavIK0WYWFhSEpKKvGYpKQko/YAEB4eLrVPTU1FWlqaURtnZ2cEBwfLnhN3LyBcXFxKrfdhbWJjY+Hs7Cxtnp6epZ6PiIjI0jHriYiIzI+qHQFXr16FXq+Hq6ur0X5XV1ekpaWVeExaWlqp7Yv+LM85T58+jU8++QQjRoyQrfWbb75BcnIyIiMjZdtER0cjOztb2i5cuCDbloiI1CWEMhuVjllPRERqYdbLM49xQiq6dOkSOnfujF69emHYsGEltvn1118RGRmJzz//HM2bN5c9l06ng05XsaEnRERUOe6/768i5yDzx6wnIrJOzHp5qo4IqF27NmxsbJCenm60Pz09HW5ubiUe4+bmVmr7oj/Lcs7Lly+jQ4cOaNu2LRYvXlzi823fvh0vvvgiPvroIwwcOPARXiUREZH1YtYTERGZH1U7Auzs7BAQEIDExERpn8FgQGJiIkJCQko8JiQkxKg9AGzZskVq7+3tDTc3N6M2OTk52L17t9E5L126hNDQUAQEBGDZsmXQaou/Fdu2bUO3bt0we/ZsDB8+XJHXTERE5kHJmYRJHrOeiIjUwqyXp/qtAVFRURg0aBACAwPRunVrLFiwALm5udL9eQMHDkS9evUQGxsLABg7dizat2+P+fPno1u3bli9ejX27t0r9fJrNBqMGzcO7733Hnx8fODt7Y0ZM2bAw8MDERERwH0XBg0aNMC8efOQkZEh1VP0TcKvv/6K7t27Y+zYsejZs6d0z6Gdnd1DJxoiIiLzZxAaaCoY7gYLvThQGrOeiIjUwKyXp3pHQJ8+fZCRkYGYmBikpaXB398fCQkJ0gRA58+fN+rBb9u2LVatWoXp06dj6tSp8PHxwfr169GiRQupzeTJk5Gbm4vhw4cjKysL7dq1Q0JCAuzt7YG73yqcPn0ap0+fRv369Y3qKVpNccWKFbh58yZiY2OlCxMAaN++PbZt22by94WIiMhSMOuJiIjMi0YIS50HUX1F61dybeF7uLbwPVxb2Jh2xwG1SyAzZMq1hZ/8eooiawv/2f8Di1tbmMqOWV8cs/4eZr0x7c4UtUu4g//8MSvMenWYx6cCERFRJbuzJFBFZxJWrBwiIiJSGLNenrpd10RERERERERUqTgigIiIrBLXFiYiIrJszHp5FRoRcOvWLeUqISIiqkRCoQ0AgoKC4Ovri7i4OJVflfKY9URE9Lhi1ssrd0eAwWDAu+++i3r16qFatWr466+/AAAzZszAkiVLTFEjERGRWUtOTsaxY8cwcuRItUtRBLOeiIjImKVlfbk7At577z0sX74cc+bMgZ2dnbS/RYsW+OKLL5Suj4iIyCSKhgtWdLNEzHoiIrIEzHp55e4I+PLLL7F48WL0798fNjY20n4/Pz+cOHFC6fqIiIhMQ8nxghaGWU9ERBaBWS+r3B0Bly5dQuPGjYvtNxgMuH37tlJ1ERERkUqY9URERJat3B0Bvr6+2LFjR7H93377LVq1aqVUXURERKalxFBBCx0uyKwnIiKLwKyXVe7lA2NiYjBo0CBcunQJBoMB3333HU6ePIkvv/wSGzZsME2VREREVGmY9URERJat3CMCXn75Zfz000/43//+B0dHR8TExOD48eP46aef8MILL5imSiIiIoUJocxmiZj1RERkCZj18so9IgAAnn32WWzZskX5aixUvihEvih3n4ui0vUFqj5/ke15DdUuAQAw+3C42iWg/sJH+uunOO2OA2qXQKQKJWYCttSZhMGsLzdm/T3M+nvMJut3pqhdwh2W+i8qMlvMennlTqyGDRvi2rVrxfZnZWWhYUPz+OAnIiKiR8esJyIismzl7qY8e/Ys9Hp9sf35+fm4dOmSUnURERGZlhITAFnotwTMeiIisgjMelll7gj48ccfpf/etGkTnJ2dpZ/1ej0SExPh5eWlfIVEREQmoMR9f5Y2ypVZT0REloRZL6/MHQEREREAAI1Gg0GDBhk9VqVKFXh5eWH+/PnKV0hERESVgllPRERkHcrcEWAwGAAA3t7eSE5ORu3atU1ZFxERkWmJu1tFz2FBmPVERGRRmPWyyj1HQGpqqmkqISIiqkScSVges56IiCwBs17eI61pkpubi+3bt+P8+fMoKDBeqmbMmDFK1UZEREQqYdYTERFZrnJ3BBw4cABdu3bFzZs3kZubCxcXF1y9ehVVq1ZF3bp1eXFARESPDwsd7ldRzHoiIrIYzPoSact7wPjx4/Hiiy/in3/+gYODA/744w+cO3cOAQEBmDdvnmmqJCIiUljRcMGKbpaIWU9ERJaAWS+v3B0BKSkpmDBhArRaLWxsbJCfnw9PT0/MmTMHU6dONU2VREREVGmY9URERJat3B0BVapUgVZ757C6devi/PnzAABnZ2dcuHBB+QqJiIhMQSi0AQgKCoKvry/i4uLUflWKYNYTEZFFYNbLKvccAa1atUJycjJ8fHzQvn17xMTE4OrVq1i5ciVatGhhmiqJiIgUp7m7VfQcQHJyMpycnBSpyhww64mIyDIw6+WUe0TAv//9b7i7uwMA3n//fdSsWRNvvfUWMjIy8Nlnn5miRiIiIqpEzHoiIiLLVu4RAYGBgdJ/161bFwkJCUrXREREZHr3Dfer0DksELOeiIgsArNeVrlHBMjZv38/unfvrtTpiIiITEvB+watBbOeiIgeK8x6WeXqCNi0aRMmTpyIqVOn4q+//gIAnDhxAhEREQgKCoLBYDBJkXFxcfDy8oK9vT2Cg4OxZ8+eUtuvXbsWTZs2hb29PVq2bImNGzcaPS6EQExMDNzd3eHg4ICwsDCcOnWq2Hl+/vlnBAcHw8HBATVr1kRERITir42IiMicqJX1YN4TERFVmjJ3BCxZsgRdunTB8uXLMXv2bLRp0wZfffUVQkJC4ObmhiNHjhQLYCWsWbMGUVFRmDlzJvbv3w8/Pz+Eh4fjypUrJbb//fff0a9fPwwdOhQHDhxAREQEIiIicOTIEanNnDlzsHDhQsTHx2P37t1wdHREeHg4bt26JbVZt24dBgwYgMjISBw8eBC7du3Ca6+9pvjrIyIilQiNMpsFUSvrwbwnIiJTYNbL0gghyjTY4amnnsKAAQMwadIkrFu3Dr169UKbNm3wzTffoH79+iYrMDg4GEFBQVi0aBEAwGAwwNPTE6NHj8aUKVOKte/Tpw9yc3OxYcMGaV+bNm3g7++P+Ph4CCHg4eGBCRMmYOLEiQCA7OxsuLq6Yvny5ejbty8KCwvh5eWFt99+G0OHDn3k2nNycuDs7IxLJ+rDqbpid2E8knR9garPX2R7XkO1SwAAzD4crnYJqL+w3FN0mIR2xwG1SyCSVShuYxt+QHZ2tmIz9RZ9Ntdf9Da0DvYVOpch7xYujpqpaH1qUivr8RjnPbO+OGb9PWaT9TtT1C7hjrL9s4OsDLNeHWVOrDNnzqBXr14AgFdeeQW2traYO3euSS8MCgoKsG/fPoSFhUn7tFotwsLCkJSUVOIxSUlJRu0BIDw8XGqfmpqKtLQ0ozbOzs4IDg6W2uzfvx+XLl2CVqtFq1at4O7uji5duhh9y1CS/Px85OTkGG1ERESPCzWyHo9Z3jPriYjIEpS5IyAvLw9Vq1YFAGg0Guh0OmlpIVO5evUq9Ho9XF1djfa7uroiLS2txGPS0tJKbV/0Z2ltiu6JnDVrFqZPn44NGzagZs2aCA0NRWZmpmy9sbGxcHZ2ljZPT89Het1ERFQJOIFQMWpkPR6zvGfWExE9Rpj1sso1XumLL75AtWrVAACFhYVYvnw5ateubdRmzJgxylaogqKJkKZNm4aePXsCAJYtW4b69etj7dq1GDFiRInHRUdHIyoqSvo5JyeHFwhEROZKifv+LPC+QWvJejxi3jPriYgeI8x6WWXuCHjiiSfw+eefSz+7ublh5cqVRm00Go2iFwe1a9eGjY0N0tPTjfanp6fDzc2txGPc3NxKbV/0Z3p6utG3HOnp6fD39wcAab+vr6/0uE6nQ8OGDXH+/HnZenU6HXQ63SO8UiIiIvWpkfV4zPKeWU9ERJagzLcGnD17FqmpqaVuRUPslGJnZ4eAgAAkJiZK+wwGAxITExESElLiMSEhIUbtAWDLli1Se29vb7i5uRm1ycnJwe7du6U2AQEB0Ol0OHnypNTm9u3bOHv2LBo0aKDoayQiInVohDKbJVEj68G8JyIiE2HWyzOPqUxLERUVhUGDBiEwMBCtW7fGggULkJubi8jISADAwIEDUa9ePcTGxgIAxo4di/bt22P+/Pno1q0bVq9ejb1792Lx4sXA3W8yxo0bh/feew8+Pj7w9vbGjBkz4OHhIa0b7OTkhDfffBMzZ86Ep6cnGjRogLlz5wKANIkSERE95pS4789CLw7UwLwnIiLFMetlmX1HQJ8+fZCRkYGYmBikpaXB398fCQkJ0uQ/58+fh1Z7b2BD27ZtsWrVKkyfPh1Tp06Fj48P1q9fjxYtWkhtJk+ejNzcXAwfPhxZWVlo164dEhISYG9/b2mJuXPnwtbWFgMGDEBeXh6Cg4OxdetW1KxZs5LfASIiIsvHvCciIqo8GiG4oKepcG3h4ri28D1ms7bwjgNql0Aky5RrC3t+9K4iawtfGD/D4tYWprJj1hfHrL/HbLJ+Z4raJdzBf3ZQCZj16jCPTyciIqLKxuGCRERElo1ZL0vdrmsiIiIiIiIiqlTlHhGQk5NT4n6NRgOdTgc7Ozsl6iIiIjItfksgi1lPREQWgVkvq9wdATVq1IBGo5F9vH79+hg8eDBmzpxpNKkPERGRWeHFgSxmPRERWQRmvaxydwQsX74c06ZNw+DBg9G6dWsAwJ49e7BixQpMnz4dGRkZmDdvHnQ6HaZOnWqKmomIiMiEmPVERESWrdwdAStWrMD8+fPRu3dvad+LL76Ili1b4rPPPkNiYiKeeOIJvP/++7w4ICIi8yU0d7aKnsMCMeuJiMgiMOtllXs83++//45WrVoV29+qVSskJSUBANq1a4fz588rUyEREZEJaIQymyVi1hMRkSVg1ssrd0eAp6cnlixZUmz/kiVL4OnpCQC4du0aatasqUyFREREVKmY9URERJat3LcGzJs3D7169cIvv/yCoKAgAMDevXtx4sQJfPvttwCA5ORk9OnTR/lqiYiIlMIJhGQx64mIyCIw62WVuyPgpZdewokTJ/DZZ5/hzz//BAB06dIF69evh5eXFwDgrbfeUr5SIiIiqhTMeiIiIstW7o4AAPD29sYHH3ygfDVERESPoaCgINjY2GDkyJEYOXKk2uUogllPRER0j6Vl/SN1BGRlZWHPnj24cuUKDAaD0WMDBw5UqjYiIiKT0aDiEwAVzSOcnJwMJycnJcoyG8x6IiJ63DHr5ZW7I+Cnn35C//79cePGDTg5OUGjubecgkaj4cVBCa7oC5CnL/e8jIrakeel6vMXmX04XO0SAAD1P7ZRuwRodx5QuwQi68YlhWQx68uPWX+P2WT9wkf6vktR2p0papdwh7DQm5yJHoZZL6vciTVhwgQMGTIEN27cQFZWFv755x9py8zMNE2VREREVGmY9URERJat3F2lly5dwpgxY1C1alXTVERERFQZOJOwLGY9ERFZBGa9rHKPCAgPD8fevXtNUw0REVFlEQptFohZT0REFoFZL6vcIwK6deuGSZMm4dixY2jZsiWqVKli9PhLL72kZH1ERERUyZj1RERElq3cHQHDhg0DALzzzjvFHtNoNNDr9cpURkREZEIaocBMwhb6LQGznoiILAGzXl65OwIeXEKIiIjoscT7BmUx64mIyCIw62Wpu84NEREREREREVWqMo0IWLhwIYYPHw57e3ssXLiw1LZjxoxRqjYiIiLT4bcERpj1RERkcZj1ssrUEfDRRx+hf//+sLe3x0cffSTbTqPR8OKAiIgeC7xv0BiznoiILA2zXl6ZOgJSU1NL/G8iIiKyDMx6IiIi61HuyQKJiIgsgtDc2Sp6DiIiIjJPzHpZ5e4I0Ov1WL58ORITE3HlypViMwtv3bpVyfqIiIhMg/cNymLWExGRRWDWyyp3R8DYsWOxfPlydOvWDS1atIBGY5k9JERERNaKWU9ERGTZyt0RsHr1anzzzTfo2rWraSoiIiKqBJxASB6znoiILAGzXl65OwLs7OzQuHFj01RDRERUWThcUBaznoiILAKzXpa2vAdMmDABH3/8MYRQ5h2Ji4uDl5cX7O3tERwcjD179pTafu3atWjatCns7e3RsmVLbNy40ejx7777Dp06dUKtWrWg0WiQkpJS4nmSkpLw/PPPw9HREU5OTnjuueeQl5cHANi2bRs0Gk2JW3JysiKvm4iIyFwpnfVg3hMREZmVco8I2LlzJ3799Vf88ssvaN68OapUqWL0+HfffVfmc61ZswZRUVGIj49HcHAwFixYgPDwcJw8eRJ169Yt1v73339Hv379EBsbi+7du2PVqlWIiIjA/v370aJFCwBAbm4u2rVrh969e2PYsGElPm9SUhI6d+6M6OhofPLJJ7C1tcXBgweh1d7pF2nbti3+/vtvo2NmzJiBxMREBAYGlvn1ERGRGVNguKClfkugZNaDeU9ERGph1ssqd0dAjRo10KNHD0We/MMPP8SwYcMQGRkJAIiPj8fPP/+MpUuXYsqUKcXaf/zxx+jcuTMmTZoEAHj33XexZcsWLFq0CPHx8QCAAQMGAADOnj0r+7zjx4/HmDFjjJ6jSZMm0n/b2dnBzc1N+vn27dv44YcfMHr06FInTMrPz0d+fr70c05OTpnfCyIiqmQcLihLyayHheU9s56I6DHCrJdVro6AwsJCdOjQAZ06dTIKzkdRUFCAffv2ITo6Wtqn1WoRFhaGpKSkEo9JSkpCVFSU0b7w8HCsX7++zM975coV7N69G/3790fbtm1x5swZNG3aFO+//z7atWtX4jE//vgjrl27Jl3AyImNjcXbb79d5lqIiIjMjZJZDwvMe2Y9ERFZgnLNEWBra4s333zTqCf8UV29ehV6vR6urq5G+11dXZGWllbiMWlpaeVqX5K//voLADBr1iwMGzYMCQkJePrpp9GxY0ecOnWqxGOWLFmC8PBw1K9fv9RzR0dHIzs7W9ouXLhQ5rqIiKiSCYU2C6Nk1sMC855ZT0T0GGHWyyr3rQGtW7fGgQMH0KBBA9NUZGIGgwEAMGLECKnHv1WrVkhMTMTSpUsRGxtr1P7ixYvYtGkTvvnmm4eeW6fTQafTmahyIiJSEpcUkve4Zz1MmPfMeiKixwezXl65OwL+9a9/YcKECbh48SICAgLg6Oho9PhTTz1VpvPUrl0bNjY2SE9PN9qfnp4uOxTRzc2tXO1L4u7uDgDw9fU12t+sWTOcP3++WPtly5ahVq1aeOmll8r8HERERI8zpbIezHsiIiKzVO7lA/v27YvU1FSMGTMGzzzzDPz9/dGqVSvpz7Kys7NDQEAAEhMTpX0GgwGJiYkICQkp8ZiQkBCj9gCwZcsW2fYl8fLygoeHB06ePGm0/88//yz2zYcQAsuWLcPAgQOLzZhMRERkqZTKejDviYiIzFK5RwSkpqYq9uRRUVEYNGgQAgMD0bp1ayxYsAC5ubnSEL6BAweiXr160vC9sWPHon379pg/fz66deuG1atXY+/evVi8eLF0zszMTJw/fx6XL18GAOkCwM3NDW5ubtBoNJg0aRJmzpwJPz8/+Pv7Y8WKFThx4gS+/fZbo/q2bt2K1NRUvPHGG4q9ZiIiMhOcSViWklkP5j0REamFWS+r3B0BSt4v2KdPH2RkZCAmJgZpaWnw9/dHQkKCNEHQ+fPnpbV+cXe931WrVmH69OmYOnUqfHx8sH79emlNYdyd8ff+2X779u0LAJg5cyZmzZoFABg3bhxu3bqF8ePHIzMzE35+ftiyZQsaNWpkVN+SJUvQtm1bNG3aVLHXTEREZO6UnhuAeU9ERGReNEKIR+rjOHbsGM6fP4+CggKj/by37p6cnBw4OzvjwNG6qF693HdhKGpHnpeqz18k9nAXtUsAANT/2EbtEqDdmaJ2CURmr1Dcxjb8gOzsbDg5OSlyzqLP5sZT/g0be/sKnUt/6xZOfzBV0frMCbP+4Zj1xZlN1i8s9/ddijObrH+0y32iSsGsV0e5PyH/+usv9OjRA4cPH4ZGo0FRP4JGowEA6PV65askIiIyBV4bl4hZT0REFoNZX6Jyd12PHTsW3t7euHLlCqpWrYqjR4/it99+Q2BgILZt22aaKomIiKjSMOuJiIgsW7lHBCQlJWHr1q2oXbs2tFottFot2rVrh9jYWIwZMwYHDhwwTaVERERK4gRCspj1RERkEZj1sso9IkCv16N69erA3bWBi2brbdCgQbEleoiIiMyVRiizWSJmPRERWQJmvbxyjwho0aIFDh48CG9vbwQHB2POnDmws7PD4sWL0bBhQ9NUSURERJWGWU9ERGTZyt0RMH36dOTm5gIA3nnnHXTv3h3PPvssatWqhTVr1piiRiIiIuVxuKAsZj0REVkEZr2scncEhIeHS//duHFjnDhxApmZmahZs6Y0mzAREZG5U2K4n6UOF2TWExGRJWDWy3vkBW9Pnz6NTZs2IS8vDy4uLspWRURERKpj1hMREVmmcncEXLt2DR07dsSTTz6Jrl274u+//wYADB06FBMmTDBFjURERMoTCm0WiFlPREQWgVkvq9wdAePHj0eVKlVw/vx5VK1aVdrfp08fJCQkKF0fERGRafDiQBaznoiILAKzXla55wjYvHkzNm3ahPr16xvt9/Hxwblz55SsjYiIiFTArCciIrJs5R4RkJuba/TtQJHMzEzodDql6iIiIjIpS15buEePHqhZsyZeffXVRzqeWU9ERJaAWS+v3CMCnn32WXz55Zd49913AQAajQYGgwFz5sxBhw4dHqkIS/dbXkM42JT7rVbU/KNhqj5/kfof26hdAgBAuzNF7RKISG0WvKTQ2LFjMWTIEKxYseKRjmfWlx+z/h6zyfpdZpD1wkw/JIisBbNeVrkTa86cOejYsSP27t2LgoICTJ48GUePHkVmZiZ27dr1SEUQERGRckJDQ7Ft27ZHPp5ZT0REZN4qmvXlvjWgRYsW+PPPP9GuXTu8/PLLyM3NxSuvvIIDBw6gUaNGj1wIERFRpVJpAqHffvsNL774Ijw8PKDRaLB+/fpibeLi4uDl5QV7e3sEBwdjz549yrzmMmLWExGRRWDWy3qkMWzOzs6YNm2a0b6LFy9i+PDhWLx4sVK1ERERmYwS9/0VHZ+Tk2O0X6fTyd5Ln5ubCz8/PwwZMgSvvPJKscfXrFmDqKgoxMfHIzg4GAsWLEB4eDhOnjyJunXrAgD8/f1RWFhY7NjNmzfDw8OjYi/qLmY9ERE97pj18hS7me3atWtYsmQJLw6IiMjqeHp6Gv08c+ZMzJo1q8S2Xbp0QZcuXWTP9eGHH2LYsGGIjIwEAMTHx+Pnn3/G0qVLMWXKFABASoo69z4z64mIyFpZWtarO6sNERGRWhScQOjChQtwcnKSdj/qzPoFBQXYt28foqOjpX1arRZhYWFISkqqYLFERERWhlkvix0BRERklZQcLujk5GR0cfCorl69Cr1eD1dXV6P9rq6uOHHiRJnPExYWhoMHDyI3Nxf169fH2rVrERISUuH6iIiIHifMennsCCAiIrIw//vf/9QugYiIiEyoollf5o6AkiY5uF9WVlaFCiEiIqpUZri2cO3atWFjY4P09HSj/enp6XBzc1P2yUrArCciIovCrJdV5uUDnZ2dS90aNGiAgQMHmrZaIiIipai0pFBp7OzsEBAQgMTERGmfwWBAYmJipQztZ9YTEZFFYdbLKvOIgGXLlpm2EiIiIitw48YNnD59Wvo5NTUVKSkpcHFxwRNPPIGoqCgMGjQIgYGBaN26NRYsWIDc3FxpZmFTYtYTERFVnDlnfRHOEUBERFZJc3er6DkAICgoCDY2Nhg5ciRGjhxZ6jF79+5Fhw4dpJ+joqIAAIMGDcLy5cvRp08fZGRkICYmBmlpafD390dCQkKxSYWIiIiodMx6eewIICIi66TgfYPJycllnkk4NDQUQpT+xKNGjcKoUaMqWBwREZGVY9bLKvMcAURERERERET0+OOIACIiskpKri1MRERE5odZL88sRgTExcXBy8sL9vb2CA4Oxp49e0ptv3btWjRt2hT29vZo2bIlNm7cKNv2zTffhEajwYIFC4o99vPPPyM4OBgODg6oWbMmIiIiSjzHtWvXUL9+fWg0Gi6dRERkKcxwJmFLxqwnIqJKx6yXpXpHwJo1axAVFYWZM2di//798PPzQ3h4OK5cuVJi+99//x39+vXD0KFDceDAAURERCAiIgJHjhwp1vb777/HH3/8AQ8Pj2KPrVu3DgMGDEBkZCQOHjyIXbt24bXXXivxOYcOHYqnnnpKgVdLRERkfZj1RERE5kX1joAPP/wQw4YNQ2RkJHx9fREfH4+qVati6dKlJbb/+OOP0blzZ0yaNAnNmjXDu+++i6effhqLFi0yanfp0iWMHj0aX3/9NapUqWL0WGFhIcaOHYu5c+fizTffxJNPPglfX1/07t272PN9+umnyMrKwsSJExV+5UREpDp+Q1ApmPVERKQaZn2JVO0IKCgowL59+xAWFnavIK0WYWFhSEpKKvGYpKQko/YAEB4ebtTeYDBgwIABmDRpEpo3b17sHPv378elS5eg1WrRqlUruLu7o0uXLsW+aTh27BjeeecdfPnll9BqH/5W5efnIycnx2gjIiLzVHTfYEU3Kh2znoiI1MKsl6dqR8DVq1eh1+uLrZfo6uqKtLS0Eo9JS0t7aPvZs2fD1tYWY8aMKfEcf/31FwBg1qxZmD59OjZs2ICaNWsiNDQUmZmZwN2g79evH+bOnYsnnniiTK8nNjYWzs7O0ubp6Vmm44iI6PEWFBQEX19fxMXFqV2K2WHWExGRJbC0rLe4VQP27duHjz/+GPv374dGoymxjcFgAABMmzYNPXv2BAAsW7YM9evXx9q1azFixAhER0ejWbNmeP3118v83NHR0YiKipJ+zsnJ4QUCEZG5UmltYao4Zj0REZUJs16WqiMCateuDRsbG6SnpxvtT09Ph5ubW4nHuLm5ldp+x44duHLlCp544gnY2trC1tYW586dw4QJE+Dl5QUAcHd3BwD4+vpK59DpdGjYsCHOnz8PANi6dSvWrl0rnaNjx45SzTNnziyxNp1OBycnJ6ONiIjME4cLVg5mPRERqYVZL0/VjgA7OzsEBAQgMTFR2mcwGJCYmIiQkJASjwkJCTFqDwBbtmyR2g8YMACHDh1CSkqKtHl4eGDSpEnYtGkTACAgIAA6nQ4nT56UznH79m2cPXsWDRo0AO7ONHzw4EHpHF988QVw9+Jj5MiRJng3iIiILA+znoiIyPyofmtAVFQUBg0ahMDAQLRu3RoLFixAbm4uIiMjAQADBw5EvXr1EBsbCwAYO3Ys2rdvj/nz56Nbt25YvXo19u7di8WLFwMAatWqhVq1ahk9R5UqVeDm5oYmTZoAAJycnPDmm29i5syZ8PT0RIMGDTB37lwAQK9evQAAjRo1MjrH1atXAQDNmjVDjRo1TP6+EBGRiSk4XJBKx6wnIiJVMOtlqd4R0KdPH2RkZCAmJgZpaWnw9/dHQkKCNEnQ+fPnjWbxbdu2LVatWoXp06dj6tSp8PHxwfr169GiRYtyPe/cuXNha2uLAQMGIC8vD8HBwdi6dStq1qyp+GskIiLzo8RwP0sdLqg0Zj0REamBWS9PI4Sw0JemvpycHDg7O+PjvW3gUE3dPpf5R8PK0Mr06i1Qve8JAKDdmaJ2CURUBoXiNrbhB2RnZyt2L3bRZ/NTQ/4NGzv7Cp1LX3ALh5ZOVbQ+erww64szm6zfdVDtEgBeZhM9FLNeHebxSU1ERFTZOFyQiIjIsjHrZak6WSAREZFqhEKbBa4tTEREZBGY9bI4IoCIiKiCLG1tYSIiIjJmaVnPjgAiIrJKnECIiIjIsjHr5bEjgIiIrBPvGyQiIrJszHpZnCOAiIiIiIiIyIpwRAAREVkljRDQVHBpr4oeT0RERKbDrJfHjgAiIrJOHC5IRERk2Zj1snhrABEREREREZEV4YgAIiKySpxJmIiIyLIx6+WxI4CIiKwThwsSERFZNma9LN4aQEREVEFBQUHw9fVFXFyc2qUQERGRCVha1nNEQCX46GAYtFXtVa3B20x+XzW7UtQugYgIUHi4YHJyMpycnBSpix5P5pD1Xv9R9ekl2l0H1S7hDgud6ZuIyo5ZL48dAUREZJ04XJCIiMiyMetl8dYAIiIiIiIiIivCEQFERGSVOJMwERGRZWPWy2NHABERWScOFyQiIrJszHpZvDWAiIiIiIiIyIpwRAAREVktSx3uR0RERHcw60vGjgAiIrJOQlR8eTEuT0ZERGS+mPWyeGsAERERERERkRXhiAAiIrJKnEmYiIjIsjHr5bEjgIiIrBNnEiYiIrJszHpZvDWAiIiogoKCguDr64u4uDi1SyEiIiITsLSs54gAIiKyShrDna2i5wCA5ORkODk5KVIXERERKYNZL48dAUREZJ04XJCIiMiyMetl8dYAIiIiIiIiIivCEQFERGSVOJMwERGRZWPWy1N9REBcXBy8vLxgb2+P4OBg7NmzR7bt0aNH0bNnT3h5eUGj0WDBggXF2sTGxiIoKAjVq1dH3bp1ERERgZMnTxq1OXPmDHr06IE6derAyckJvXv3Rnp6uvT42bNnMXToUHh7e8PBwQGNGjXCzJkzUVBQoPCrJyIi1QihzEZlwrwnIqJKx6yXpWpHwJo1axAVFYWZM2di//798PPzQ3h4OK5cuVJi+5s3b6Jhw4b44IMP4ObmVmKb7du3Y+TIkfjjjz+wZcsW3L59G506dUJubi4AIDc3F506dYJGo8HWrVuxa9cuFBQU4MUXX4TBcGcmiBMnTsBgMOCzzz7D0aNH8dFHHyE+Ph5Tp0414btBRERkmZj3RERE5kUjhHpdHMHBwQgKCsKiRYsAAAaDAZ6enhg9ejSmTJlS6rFeXl4YN24cxo0bV2q7jIwM1K1bF9u3b8dzzz2HzZs3o0uXLvjnn3+kWR+zs7NRs2ZNbN68GWFhYSWeZ+7cufj000/x119/yT5Xfn4+8vPzpZ9zcnLg6ekJryXToa1qX2qdpuZtJqtcaHalqF0CET1GCsVtbMMPyM7OVmym3pycHDg7OyP4xXdhW6Vin82Ft29h908zFK3PEllS3ptz1nv9R9Wnl2h3HVS7hDss9Fs8IkvDrFeHaiMCCgoKsG/fPqMg1mq1CAsLQ1JSkmLPk52dDQBwcXEB7ga4RqOBTqeT2tjb20Or1WLnzp2lnqfoHHJiY2Ph7OwsbZ6enoq9DiIiUphQaKNSWVreM+uJiB4jzHpZqnUEXL16FXq9Hq6urkb7XV1dkZaWpshzGAwGjBs3Ds888wxatGgBAGjTpg0cHR3xf//3f7h58yZyc3MxceJE6PV6/P333yWe5/Tp0/jkk08wYsSIUp8vOjoa2dnZ0nbhwgVFXgcREdHjytLynllPRESWQPXJAk1p5MiROHLkCFavXi3tq1OnDtauXYuffvoJ1apVg7OzM7KysvD0009Dqy3+dly6dAmdO3dGr169MGzYsFKfT6fTwcnJyWgjIiLzVDSTcEU3Ul9l5j2znojo8cGsl6fa8oG1a9eGjY2N0ey9AJCeni47MVB5jBo1Chs2bMBvv/2G+vXrGz3WqVMnnDlzBlevXoWtrS1q1KgBNzc3NGzY0Kjd5cuX0aFDB7Rt2xaLFy+ucE1ERGRGlJgJmPcgPxTznoiIVMOsl6XaiAA7OzsEBAQgMTFR2mcwGJCYmIiQkJBHPq8QAqNGjcL333+PrVu3wtvbW7Zt7dq1UaNGDWzduhVXrlzBSy+9JD126dIlhIaGIiAgAMuWLSvx2wMiIiIqHfOeiIjI/Kg2IgAAoqKiMGjQIAQGBqJ169ZYsGABcnNzERkZCQAYOHAg6tWrh9jYWODuhEPHjh2T/vvSpUtISUlBtWrV0LhxY+Du8MBVq1bhhx9+QPXq1aX7D52dneHg4AAAWLZsGZo1a4Y6deogKSkJY8eOxfjx49GkSRPgvouCBg0aYN68ecjIyJBqVuLbCyIiUp8Sw/0sdbig0pj3RESkBma9PFU7Avr06YOMjAzExMQgLS0N/v7+SEhIkCYUOn/+vFHP/OXLl9GqVSvp53nz5mHevHlo3749tm3bBgD49NNPAQChoaFGz7Vs2TIMHjwYAHDy5ElER0cjMzMTXl5emDZtGsaPHy+13bJlC06fPo3Tp08XG2ao4mqLRESkJCVmAmYklAnznoiIVMGsl6URTDqTKVq/0hzWFvaOU/XpJZpdKWqXQESPEVOuLRzS+R1F1hZOSojBk08+CRsbG4wcORIjR45UpE56PJhT1nv9R9Wnl2h3HVS7hDt4iUv0WGDWq0PVEQFERERqUXK4YHJyMmePJyIiMjPMennsCCAiIutkEHe2ip6DiIiIzBOzXhanxiUiIiIiIiKyIhwRQERE1okTCBEREVk2Zr0sdgQQEZFV0iiwJJBGqWKIiIhIccx6ebw1gIiIiIiIiMiKcEQAERFZJyEqvrwYlycjIiIyX8x6WewIICIiq6TkkkJERERkfpj18nhrABEREREREZEV4YgAIiKyTpxJmIiIyLIx62WxI4CIiKySRghoKnjfX0WPJyIiItNh1svjrQFEREREREREVoQjAipBw/n5sLVRtwbDkRPqFkBEZG4Md7eKnoMIQMOPzCDrDzHriYiMMOtlsSOAiIisEocLEhERWTZmvTzeGkBERERERERkRTgigIiIrBNnEiYiIrJszHpZ7AggIiLrJMSdraLnICIiIvPErJfFWwOIiIgqKCgoCL6+voiLi1O7FCIiIjIBS8t6jgggIiKrpBF3toqeAwCSk5Ph5OSkSF1ERESkDGa9PHYEEBGRdeJwQSIiIsvGrJfFWwOIiIiIiIiIrAhHBBARkVXSGO5sFT0HERERmSdmvTx2BBARkXXicEEiIiLLxqyXxVsDiIiIiIiIiKwIRwQQEZF1Ene3ip6DiIiIzBOzXhY7AoiIyCpphICmgsP9Kno8ERERmQ6zXh5vDSAiIiIiIiKyImbRERAXFwcvLy/Y29sjODgYe/bskW373XffITAwEDVq1ICjoyP8/f2xcuVKozaDBw+GRqMx2jp37mzUZv/+/XjhhRdQo0YN1KpVC8OHD8eNGzdKfM5r166hfv360Gg0yMrKUuhVExGRqoomEKroRmXCrCciokrHrJelekfAmjVrEBUVhZkzZ2L//v3w8/NDeHg4rly5UmJ7FxcXTJs2DUlJSTh06BAiIyMRGRmJTZs2GbXr3Lkz/v77b2n773//Kz12+fJlhIWFoXHjxti9ezcSEhJw9OhRDB48uMTnHDp0KJ566imFXzkREalKADBUcLPMawPFMeuJiEgVzHpZqncEfPjhhxg2bBgiIyPh6+uL+Ph4VK1aFUuXLi2xfWhoKHr06IFmzZqhUaNGGDt2LJ566ins3LnTqJ1Op4Obm5u01axZU3psw4YNqFKlCuLi4tCkSRMEBQUhPj4e69atw+nTp43O8+mnnyIrKwsTJ0400TtARERk2Zj1RERE5kXVjoCCggLs27cPYWFh9wrSahEWFoakpKSHHi+EQGJiIk6ePInnnnvO6LFt27ahbt26aNKkCd566y1cu3ZNeiw/Px92dnbQau+9fAcHBwAwusg4duwY3nnnHXz55ZdGbeXk5+cjJyfHaCMiIvNUNIFQRTcqHbOeiIjUwqyXp2pHwNWrV6HX6+Hq6mq039XVFWlpabLHZWdno1q1arCzs0O3bt3wySef4IUXXpAe79y5M7788kskJiZi9uzZ2L59O7p06QK9Xg8AeP7555GWloa5c+eioKAA//zzD6ZMmQIA+Pvvv4G7Qd+vXz/MnTsXTzzxRJleT2xsLJydnaXN09Pzkd4XIiKqBEKJewfVfhHmj1lPRESqYdbLUv3WgEdRvXp1pKSkIDk5Ge+//z6ioqKwbds26fG+ffvipZdeQsuWLREREYENGzYgOTlZatO8eXOsWLEC8+fPR9WqVeHm5gZvb2+4urpK3wZER0ejWbNmeP3118tcV3R0NLKzs6XtwoULJnj1RERElo9ZT0REZDqqdgTUrl0bNjY2SE9PN9qfnp4ONzc32eO0Wi0aN24Mf39/TJgwAa+++ipiY2Nl2zds2BC1a9c2uifwtddeQ1paGi5duoRr165h1qxZyMjIQMOGDQEAW7duxdq1a2FrawtbW1t07NhRqnnmzJklPo9Op4OTk5PRRkREZoozCVcKZj0REamGWS/LVs0nt7OzQ0BAABITExEREQEAMBgMSExMxKhRo8p8HoPBgPz8fNnHL168iGvXrsHd3b3YY0VDFZcuXQp7e3tp2OG6deuQl5cntUtOTsaQIUOwY8cONGrUqFyvk4iIzJABgEaBc1CpmPVERKQaZr0sVTsCACAqKgqDBg1CYGAgWrdujQULFiA3NxeRkZEAgIEDB6JevXrStwCxsbEIDAxEo0aNkJ+fj40bN2LlypX49NNPAQA3btzA22+/jZ49e8LNzQ1nzpzB5MmT0bhxY4SHh0vPu2jRIrRt2xbVqlXDli1bMGnSJHzwwQeoUaMGABS7ALh69SoAoFmzZlIbIiIiejhmPRERkXlRvSOgT58+yMjIQExMDNLS0uDv74+EhASp9/78+fNGs/jm5ubiX//6Fy5evAgHBwc0bdoUX331Ffr06QMAsLGxwaFDh7BixQpkZWXBw8MDnTp1wrvvvgudTiedZ8+ePZg5cyZu3LiBpk2b4rPPPsOAAQNUeAeIiEgNSswEbKkzCSuNWU9ERGpg1svTCGGhr8wM5OTkwNnZGc/7ToKtja4MR5iO4cgJVZ+fiOhRFIrb2IYfkJ2drdi92EWfzR2bV/yzuVCfj8SjcxWtjx4vUta3MIOsP8SsJ6LHD7NeHY/lqgFERERERERE9GhUvzWAiIhIFUrMBMxBdUREROaLWS+LHQFERGSdeHFARERk2Zj1snhrABEREREREZEV4YgAIiKyTlxbmIiIyLIx62WxI4CIiKwSlxQiIiKybMx6ebw1gIiIqIKCgoLg6+uLuLg4tUshIiIiE7C0rOeIACIisk4KTiCUnJxsUWsLExERWQRmvSyOCCAiIiIiIiKyIhwRQERE1skgAE0FvyUwWOZ9g0RERBaBWS+LHQFERGSduLYwERGRZWPWy+KtAURERERERERWhCMCKoHh2J8waKqoXQYRERlR4FsCWOa3BFR+hiPMeiIi88Osl8OOACIisk4cLkhERGTZmPWyeGsAERERERERkRXhiAAiIrJOBlHx4X4WOpMwERGRRWDWy2JHABERWSdhuLNV9BxERERknpj1snhrABEREREREZEV4YgAIiKyTpxAiIiIyLIx62WxI4CIiKwT7xskIiKybMx6Wbw1gIiIiIiIiMiKcEQAERFZJw4XJCIismzMelnsCCAiIuskFAh3y7w2ICIisgzMelm8NYCIiIiIiIjIinBEABERWScOFyQiIrJszHpZ7AggIiLrZDAAMChwDiIiIjJLzHpZvDWAiIiIiIiIyIpwRAAREVknDhckIiKybMx6WVYxIuC3337Diy++CA8PD2g0Gqxfv/6hx2zbtg1PP/00dDodGjdujOXLl1dKrUREVEmKLg4qupHZYN4TEZERZr0sq+gIyM3NhZ+fH+Li4srUPjU1Fd26dUOHDh2QkpKCcePG4Y033sCmTZtMXisRERE9GuY9ERFR2VjFrQFdunRBly5dytw+Pj4e3t7emD9/PgCgWbNm2LlzJz766COEh4fLHpefn4/8/Hzp55ycnApWTkREJmMQFV8c2GCZ3xI8rioj75n1RESPEWa9LKsYEVBeSUlJCAsLM9oXHh6OpKSkUo+LjY2Fs7OztHl6epq4UiIielRCGBTZ6PH1KHnPrCcienww6+WxI6AEaWlpcHV1Ndrn6uqKnJwc5OXlyR4XHR2N7Oxsabtw4UIlVEtERESP4lHynllPRESWwCpuDagsOp0OOp1O7TKIiKgshKj4cD8LnUCI5DHriYgeI8x6WewIKIGbmxvS09ON9qWnp8PJyQkODg6q1UVERAoSCtw3aKEXB9aCeU9EZOGY9bJ4a0AJQkJCkJiYaLRvy5YtCAkJUa0mIiIiUhbznoiIrJVVdATcuHEDKSkpSElJAe4uF5SSkoLz588Dd+/3GzhwoNT+zTffxF9//YXJkyfjxIkT+M9//oNvvvkG48ePV+01EBGRwgwGZTYyG8x7IiIywqyXZRW3BuzduxcdOnSQfo6KigIADBo0CMuXL8fff/8tXSQAgLe3N37++WeMHz8eH3/8MerXr48vvvii1KUDiYjoMcPhghaHeU9EREaY9bKsoiMgNDQUopT/gcuXLy/xmAMHDpi4MiIiIlIK856IiKhsrKIjgIiI6EHCYIDQVGy4n6WuLUxERGQJmPXy2BFARETWicMFiYiILBuzXpZVTBZIRERERERERHdwRAAREVkngwA0/JaAiIjIYjHrZbEjgIiIrJMQACp435+FXhwQERFZBGa9LN4aQERERERERGRF2BFARERWSRiEIpu5uXDhAkJDQ+Hr64unnnoKa9euVbskIiIiVTDr5fHWACIisk7CoMBwQfNbUsjW1hYLFiyAv78/0tLSEBAQgK5du8LR0VHt0oiIiCoXs17+HCatkIiIiCqVu7s73N3dAQBubm6oXbs2MjMz2RFARERkIZTIet4aQEREVkmt4YK//fYbXnzxRXh4eECj0WD9+vXF2sTFxcHLywv29vYIDg7Gnj17Huk17tu3D3q9Hp6eno90PBER0eOMWS+PIwKIiMg6qTRcMDc3F35+fhgyZAheeeWVYo+vWbMGUVFRiI+PR3BwMBYsWIDw8HCcPHkSdevWBQD4+/ujsLCw2LGbN2+Gh4cHACAzMxMDBw7E559//kgvjYiI6LHHrJfFjgATEneXmijEbcD85pggIjJ7hbgN3Pd5qvi5K3jaovpycnKM9ut0Ouh0uhKP6dKlC7p06SJ7zg8//BDDhg1DZGQkACA+Ph4///wzli5diilTpgAAUlJSSq0rPz8fERERmDJlCtq2bVvu10Vlx6wnIqoYZr06Wc+OABO6fv06AGAnNqpdChHRY+369etwdnZW5Fx2dnZwc3PDzjRlPpurVatWbDjezJkzMWvWrHKfq6CgAPv27UN0dLS0T6vVIiwsDElJSWU6hxACgwcPxvPPP48BAwaUuwYqH2Y9EZEymPWVm/XsCDAhDw8PXLhwAdWrV4dGo3mkc+Tk5MDT0xMXLlyAk5OT4jU+LjWwDtZh7jWwDtPUIYTA9evXpSFwSrC3t0dqaioKCgoUOZ8QothnvNw3BA9z9epV6PV6uLq6Gu13dXXFiRMnynSOXbt2Yc2aNXjqqaekexJXrlyJli1bPlJNVDpLyXpzqcMcamAdrONxqMMcalCqDmb9HZWd9ewIMCGtVov69esrci4nJydV/5KbSw2sg3WYew2sQ/k6lPp24H729vawt7dX/LzmoF27djAYzG+pI0tlaVlvLnWYQw2sg3U8DnWYQw1K1MGsLx8lsp6rBhAREZmJ2rVrw8bGBunp6Ub709PT4ebmplpdREREpAxzyXp2BBAREZkJOzs7BAQEIDExUdpnMBiQmJiIkJAQVWsjIiKiijOXrOetAWZOp9Nh5syZj3wPiqXUwDpYh7nXwDrMtw5zc+PGDZw+fVr6OTU1FSkpKXBxccETTzyBqKgoDBo0CIGBgWjdujUWLFiA3NxcaWZhsjzm8nfFHOowhxpYB+t4HOowhxrMqQ5z8zhkvUaYYp0GIiIiKtG2bdvQoUOHYvsHDRqE5cuXAwAWLVqEuXPnIi0tDf7+/li4cCGCg4NVqJaIiIjK63HIenYEEBEREREREVkRzhFAREREREREZEXYEUBERERERERkRdgRQERERERERGRF2BFAZcbpJIiIiCwbs56IyDqwI4DK5Ny5c9i0aRNwd51LteTn56v23HIuX76MP//8U+0yiIiIKoRZL49ZT0SWhh0Bj6HK7q0/cuQIGjdujEmTJgEAtFp1fm1OnjyJadOm4fbt26o8f0kOHDiAp556yiwuDoQQ/CanFOb03mRlZaGgoEDtMoyoedFPRMUx65n1cpj38szpfTHHrAfznu5jq3YBJO/PP//EkiVLcOXKFfj7+6Nr167w8fGBRqOBEAIajcbkNaSkpKBdu3YIDw/HiRMnsHLlSgwYMMDkz/ugQ4cOITg4GPn5+ejQoQO6detW6TU86ODBg3j22WcxbNgwdO/evdjjlfX/KD8/HzqdDrdv34adnZ3Jn68szp49i61bt+LixYvo378/GjZsWCnvxYMuXryI9PR0BAQEqPL8Jdm/fz+6dOmCzZs3w8/PT5Uazp49ix9++AF6vR5PPvkkunfvrtpF//3OnTuHlJQUpKeno1u3bnBxcYGDg4PaZRGZFLP+HmZ96Zj3JWPWyzPHvGfWmxFBZuno0aPC2dlZdO7cWfTs2VM4OzuLsLAw8fnnn0ttDAaDSWtISUkRVatWFTNmzBAFBQWiTZs2YsCAASZ9Trk6HBwcxMiRI0Xfvn1F//79RW5urslff2mOHj0qqlevLiZNmiSEEKKwsFDs2LFDbNy4UWzfvr1S6+jZs6fo1q2bCA0NFRs3bhTZ2dmV9vwlOXTokKhXr5547rnnhKurq6hXr564ePFipddx4sQJ4erqKoKCgsSOHTsq/flLkpKSIqpXry7GjBmjWg2HDh0S7u7uIjQ0VDRr1kz4+fmJxMRE1eopcvDgQVG3bl3h5+cn6tSpI+rUqSOmTZsm/vzzTyEq4fOOSA3MeuM6mPWl18K8L45ZL88c855Zb17YEWCG8vPzxeuvvy6GDRsm7Tt16pTo06ePaNOmjfj4449NXsOpU6eERqMR06ZNk/atXbtW6HQ68euvv5r8+Yvs27dPVK9eXapjwYIFwsnJSZw6dUoIlT4wCgsLRVhYmHBychLHjx8Xer1edOvWTTz99NPCxcVFODg4iLfeeksUFhaatI7jx48LFxcXMWrUKPHhhx+KESNGCI1GI6KiosTx48dN+txyLl68KBo3bizeffddkZubK4QQolGjRuLrr7+u1Dr+/vtvERoaKp555hnRpUsX0alTJ/Hbb79Vag0POnjwoHBycpIuKA0Ggzh79qw4dOiQuHTpktTOlL/Tly5dEt7e3mLKlClCCCGOHDki/P39xQ8//GDUTq/Xm6yGkmRlZYng4GAxadIkkZmZKYQQ4u233xZt2rQRvXv3FseOHavUeogqA7P+HmZ96Zj3JWPWyzPHvGfWmx92BJipF154QQwfPlyI+z4szp07JwYPHiyeffZZ8eOPP5r0+S9cuCA+++wz6WeDwSAuXrwonnnmGTF+/HghKuHDIzs7Wzg6OkrPJ4QQBQUFIjAwUAwcOFDVXsPTp0+LgIAA8cILLwh/f38RHh4u9u3bJ44fPy5++OEH4ejoKIWAKRQWForIyEgxePBgo/2dO3cW1apVE6NHjxbnzp0z2fPL2bRpk3j66aeNvhF48cUXxXvvvSdGjRolNm7cKNLT001eR3JysujYsaPYtWuX+OWXX1S/QMjLyxPNmzcXderUEeLu352IiAgRFBQkbG1tRevWrcW8efNMXsdPP/0kgoKCxPXr16V9PXr0EBMnThQxMTHiiy++kPZX5sXB33//Lby9vcX69euN9i9btky0a9dOREZGGl1AEVkKZj2z/mGY9/KY9fLMMe+Z9eaHHQFmprCwUBQUFIjIyEjx6quvilu3bgmDwSD9JT1z5owICQkRffr0UaW+mJgYUbNmTXH16lUhTNijeeHCBXH48GFx8uRJaZ/BYBCFhYVi6tSponnz5uLKlSsmrUFOUe//mTNnRPPmzUXbtm3F+fPnjdp8+OGHwsvLS1y4cMEk9RUWFornn39evPPOO0IIIX3QT5w4UbzwwgvCyclJfPrpp0JU8vvz5ZdfiurVq4tDhw4JIYSYN2+eqFKlinj99dfFM888Ixo3bizmzJlTKd+gpKSkSP/9888/SxcI9w/nLPp7VRkhuGXLFlGzZk0xaNAgERYWJjp16iR++eUX8fPPP4vo6GhRp04dsXjxYpPW8Msvv4gaNWpIIfzee+8JjUYj+vbtKyIiIoStra2YOnWqSWsoSVpamvDz8xPx8fFCCCFu374tPfbpp5+KJ598UqxatUoIFUYrEJkCs/4OZn3Z6mDey2PWl8wc855Zb37YEWAmHvyg3LZtm7CxsTEaGljUZtu2bUKr1YojR44oWsONGzdETk5OifecFYVLRkaGaNasmZgyZYrJAufw4cPC09NTREVFCXHf6y56vvT0dFG9enUpFCtDUQ1FH0xFP1+6dEmsXr1aFBQUGLX/6KOPxFNPPSVu3rxpspoGDBggWrVqJdV0+fJlUatWLbFnzx4RExMjXF1dpaFXpnT/B7kQQgQFBQkXFxcRHh4u7OzsxObNm6XHxo8fL7y9vU1S140bN0p9fOPGjaJz584iPDxc+rZg7Nix4o8//lC8FjmJiYmiatWqIjAwUKSlpUn709PTRb9+/USvXr3ErVu3TPb8J06cEH369BFOTk6iW7duQqPRGPXMx8XFiQYNGkj36lWm1157TTRu3Fj8/fffQjzwe9W3b18REBBQ6TURKY1Zfw+zvuyY9/cw68vGXPOeWW9e2BFgBk6ePCnmzZsnLl++bLR/3rx5QqvVGk0aJO7eS9esWTORmpqqWA1Hjx4VnTp1Eq1atRIeHh7iq6++EqKE3uXbt2+LyMhIERISUiwQlVA0aZG3t7dwc3MrNqysKJQnTpwo2rZtWynD4Q4fPixCQ0OlbwLK0rM8evRo0bt3b5NeHGzbtk20bt1auLm5iYEDBwpHR0fpXtODBw8KT09PceLECZM9v7j7ezNgwIBikwNt3LhRrFy5UoSGhoobN25I78PGjRtF06ZNxYULFxSt49ixY6JJkyZi7dq1xR67/3e4aOhg586dRUREhNBoNGL//v2K1vKgBy+c9u7dK1avXl1s/1tvvSXatm2raC94ZmamSE1NNfo9+PPPP8WOHTvEl19+KTp27Gj0fGvWrBFNmjSRAtpUrly5Ig4ePCgOHz4sXSTm5eUJX19f0bp162L/QFm8eLFo06aNST5ziCoLs/4eZn35MO/vYNbLM8e8Z9abP3YEqOzUqVPCxcVFaDQaER0dLTIyMqTHcnNzxdtvvy00Go2YPn262L9/v7h27ZqYMmWKaNy4sTRcrqKOHj0qatWqJcaPHy++/vprERUVJapUqSIOHDhg1K7oQ/avv/4SGo3G6L5CJRTNGDx16lSRkZEhmjdvLt577z1hMBiKXaRs3rxZVK9eXXz//feK1vCg1NRU0bhxY6HRaISPj48UaHIf4H/99ZeYNm2aqFGjhjh8+LBidZw6dUp88MEHYtKkSWLp0qUiKytLiLuhGBUVJcaPH290Ebl9+3bx5JNPirNnzypWw4MOHTokXFxcxODBg6VvrO5/X5YvXy6eeuopo2PGjRsn2rVrp/hMx1OmTBEajUa4uLiUeIFwfxD/9NNPombNmqJGjRpGQwqVdPz4cTFs2DCRk5MjRAnfAt7/PhX9bg8aNEiMGTNGsYuDw4cPi7Zt2wofHx/RvHlzMWHCBKPHN23aJAIDA40usKOjo0X79u3FP//8o0gNJTl06JDw9vYWzZs3FzY2NqJbt27SvYpHjhwRjRs3Fv7+/iIlJUUaAjtixAjRsWNHkZeXZ7K6iEyJWX8Ps750zHt5zPqSmWPeM+sfD+wIUNGNGzfEkCFDxODBg0VcXJzQaDRi0qRJRqGv1+vFihUrhJubm6hXr55o2rSp8PDwEPv27VOkhmvXrolOnToVW+IkNDRUjB49WogHeln1er3IyckRo0ePVnQ40cGDB4VOp5PuV9Lr9eLVV18VQUFBUpsHLxC6dOkinn32WaHX600ydDEvL09Mnz5d9OjRQyQmJornnntONGjQQPYCISUlRbz22mviiSeeKHZhVRGHDx8WLi4uomvXruLVV18VOp1OPPvss2LDhg1Smwd7T8ePHy/atm0rXUAoLTMzUzz99NNi1KhR0r4bN24YDYG7ePGicHFxEV26dBGLFi0SI0aMEC4uLuLgwYOK1/Ptt9+KcePGiXfffVfY2dmJNWvWSI8V/W7o9Xqh1+vFuHHjRPXq1RW/eCty+vRpUa9ePWFvby969uwpe4FQJDMzU0yfPl3UrVtXsRlzjx49KmrWrCkmTZoktmzZImbNmiX8/PyMvpn5/fffhY+Pj3jjjTfE22+/LUaPHi1q1Khhkv8/RdLT00WDBg3E+PHjxZkzZ8TGjRtFZGSkqF+/voiNjRVCCHH27FnRpk0b8cQTTwg/Pz/RpUsXUb16dZNdyBGZGrP+HmZ96Zj3pWPWF2eOec+sf3ywI0BFN2/eFHFxcWL16tVC3B2mU9IFgrjbW719+3bxyy+/KLpGa1pammjdurV0H1VR4EVGRor+/fvLHqf0vU179uwRM2bMMKrhxIkTwtnZWfznP/8p8Zjvv/9enD59WtE6HrR69WopaM6ePSueffZZ2QuE7OxssXnzZkWHcWZlZYm2bduK6Ohoad/x48eFra2taNWqlVi2bJlR+61bt4oxY8aY/MP03LlzIiQkRFy9elXo9XrRs2dP8cwzzwhHR0fxr3/9S1qndvPmzeLpp58WrVq1Et27dzdZIG/btk20aNFC5OXliX/961/C3t5ebN68WUycOFHExcVJ7Q4fPizq1asn9u7da5I6rl+/Lvr37y9effVVsWDBAtGmTRvx8ssvy14g/O9//xODBw8Wbm5uig1bLJqM5/6ZrM+cOSM6dOgg9u7da/R7sXTpUtGpUyfRsmVL0aNHD2nSJ1PZu3evaNGihdEFyrlz58S7774rXFxcxPz5841qe/fdd8W///1vo4nEiB43zPp7mPXymPcPx6w3Zq55z6x/fLAjQGUPTnqyevVqodFoxMSJE6Whg7dv3zbp/XH39/YX9TRPnz5dDBgwwKjd/UuQmJrBYBBZWVkiIiJC9O7dWxQWFqq6hFBRTWfOnJG+LSi6SMvLyxP79+83yVCmjIwM8fTTT4tff/1VGAwGkZubKwoLC8Vzzz0n/P39RceOHY0mktq0aVOl/IPu4MGDwsPDQxw/fly88sorIjw8XPz4449i0aJFokOHDqJz585SDQaDQeTk5Ch+D2XR70PRcletW7eWQjg6OlrY2NhI6z/fT+nbEh4UGxsrVq5cKQoLC8XKlSuLXSDcf0F5+PBhERcXJ62VrYRz586Jt99+2+gibNasWaJatWqiQYMG4sknnzSajOfq1asiLy9PWgfalIqGBG/atMlof1pampgxY4Zo0aJFsceILAGzvmTM+nuY9yVj1ssz17xn1j8+2BFgJu4Pv//+97/StwWXLl0S48ePF6+88oq4ceOGSQPy/g+tadOmifDwcOnnf//732L+/PnFJj0xtXXr1gmNRiN27txZKc8nN5vy/e/N6dOnpQuEv/76S4wcOVIEBgYqep9VUW/y6dOnhYODg/jvf/8rPXbu3DnRunVr8d///le4uLiImJgYo2Mr4x9058+fFy1atBD/+c9/RO/evcXRo0elx7Zt2yZ8fX2LTXyllCtXrpT496Bdu3ZS7/+AAQNE9erVhZ2dXbH1ak31d6ikvxv5+fniyy+/LHaBcPPmTel3TOmllQoLC43uP46Pjxc1atQQa9asEUePHhV79+4Vnp6elbZG+P3+/vtv0bFjRzFy5MhiExSdOHFCBAQEiLlz5wrxwMUfkaVg1pfMWrNeMO9lMesfzlzznln/+GBHgBm5fw3h1atXiypVqogmTZoIW1tbxe9DK60GcffioEuXLkIIIWbMmCE0Go0q9+3k5+eLTp06if79+5t8Vt6yzqYs7g69Cg0NFRqNRjg6Ooo9e/YoVseBAwdE9+7dpW+Q/u///k/Y2dmJadOmiY8//lg4OzuL4cOHC3F3DeO2bduKGzdumPTC7dSpU+K7774T+fn50r4JEyYIjUYj7OzsRHJyslH7l19+WfTu3VvxOg4fPiyaNGki4uLipL8rRa+7W7du4ocffhBjxowR7u7uIiUlRUyePLnYkjlKKxo6e/97I+77xu327dtixYoV0gXC1atXxYgRI0SnTp0U+39WdJ6iP+8P+23bthldXBcWFoqwsDBpxmlTys7OFmlpaeLatWvSvs8++0w4OTmJ2bNnF1tWql+/fqJr165cP5gsGrO+OGvMesG8l8Wsl2eOec+sf3zZgsyGRqMBAAgh0KdPHyxevBgpKSnYv38/WrZsWSk1CCGg0Whga2sLT09PzJs3D3PmzMHevXvh5+dXKTXcz87ODh06dEBsbCyys7Ph4OBgkuc5duwYnnvuOQwcOBCBgYHYt28fIiMj0bx5c/j7+xdrX79+fbi5uaFmzZrYsWMHfH19Fanj4MGDaNu2LUaPHg1HR0cAwOjRo1GtWjUsW7YMdevWxYQJEzBjxgwAwLVr1yCEkNqawqFDhxAWFoaIiAgEBwfD3d0dGo0G7733HrKzs7FkyRIkJibCx8cHzs7OAICqVauiSZMmitZx4sQJPPfcc4iMjET37t2h1WoBALa2dz7G2rVrh169eqFu3brYsGED/Pz84OfnB1tbW8VrKXLs2DHExMTg1q1byM3NxeTJk/HMM8/AyckJVapUgV6vh62tLV577TVoNBrEx8ejadOmyMvLQ2JiolR7RRw/fhzz58/HjRs3YGdnh6ioKKPf2fbt2xu1F0LA2dkZTz75pPRz0WePkg4fPow333wTaWlpqFWrFnx9fbF06VIMHz4c165dw7Rp01BQUIB+/fqhUaNGUi2NGjUyST1E5oJZX5y1ZT2Y97KY9fLMMe+Z9Y85tXsiqLjCwkIxfvx4odFoTDqDd2nee+89odFohLOzc7He38pS1DufmZkpAgICFJ+Yp8ijzKb8ySefCBsbG0UnfTl48KBwdHSUJn0pes6i3uabN28WmxV4+PDhYujQoaKgoMAkw6rOnTsnnnjiCaOJaO6XkZEhXnvtNWFraytGjRolZs+eLcaPHy9cXFwUnRVXr9eL4cOHi8jISOnn3377TSxbtkycPHlS3Lx5U+zevVv06tWr0r5RO378uHBxcRGjRo0SH374oRgxYoTQaDQiKirK6F7Foh7vGzduiHbt2omaNWsqNolS0WzBI0aMEFFRUeKVV14RdnZ2YuHChcXW5S4yY8YM4enpadLJt86ePSvq1KkjJkyYINatWyfmzJkjfHx8hK+vrzhz5owQQoi5c+cKLy8vERoaKgYMGCAGDBggnJycTDahJJG5YdbfYW1ZL5j3spj18swx75n1jz92BJihwsJC8cUXX1Tah1xJkpOThUajMboXTC0Gg6HYREtKepTZlH/88UdFl1T6+++/hZubm3SvZmFhoRg3bpzo2rWraNKkifjwww/FiRMnpPZ//vmnmDx5snBycjKaPEhpP/30k+jatasQdy9Qpk2bJiIiIsTQoUPFypUrpXazZ88W4eHhwt/fX3Tv3l3xoaWFhYWiXbt2YsWKFUIIIdq3by8CAgKEs7OzaNiwoXjrrbeKDT0zpcLCQhEZGSkGDx5stL9z586iWrVqYvTo0UaTft2+fVtMnz5d2NvbK/be5Ofni1dffVW89dZb0r68vDzh7+8vnJycRGxsrNH9o7///rt48803Ra1atRS/qH3QunXrRGBgoNH9t2fOnBHBwcHCx8dHuqfx559/Fu+//77o1KmTeOutt3hhQFaFWW/MGrJeMO9LxawvmbnmPbP+8adVe0QCFWdjY4MhQ4aUOEytsgQGBuL69euKDoN7VBqNxqRD4VxdXfHVV1/h2WefBQDo9XoAQL169aQhaUWuX78OAHjxxRfh4+OjaB0hISG4du0afvjhB3Tv3h3/396dR0V1nn8A/95BBgQZUECCgooixYUoKDlqPDaKC25RxAQ3UNG6NcWgYHCJxC7GGGtNqm2xWokbmFRyTixGowkSa1NBFAwmCiqLChaDwQgi2zy/P35yCwGNjTMyYb6fczxH7n1n7sOIfO9573uf++WXX6JXr14YOXIk/vjHP+Ltt99GYWEhysrKsGfPHqSkpCA1NRV9+vQxaB0NnT17Frdv3wYAjBs3DqdOnULXrl1RWFiITZs2YeXKlQCAFStW4ODBgzh9+jTef/99gy8ttbCwQMeOHVFWVoa1a9fCysoKBw4cwDfffIOIiAicPXsWW7duxYPJTYMe+2EKCgrQvXt3AEB5eTkAoG/fvhg8eDDee+89HD58GHiwBK5NmzawsbHB6dOnDfbZ1NbWIj8/X/09cf/+fVhbW8Pf3x/+/v54/fXXkZKSAgC4c+cOLly4gHv37iE1NRW+vr4GqeFhiouLkZ+fD51OBwDQ6/Xo3r07PvzwQ9jY2GDixInAg5+pVatW4ciRI9i6dSv69u1r1LqITAmzvjFzyXow7x+KWd88U817Zn0r0NIzEUSmpCW7KRcVFUlYWJi0bdtWRo0aJd988426b9++feLg4CDJycnq2IctBTOkY8eOyYgRI2THjh0yatQo9TFKZWVlsm7dOhk0aJD62CBDN30pKipqdJVq4cKF0r9/f5k5c6bExcU1GhsVFSW9evVSl1U+DaGhoeLr66t+30VFReLo6ChpaWmydu1acXFxMfqVi/Hjx0tQUJBaw/Xr18XZ2VnS0tIkPDxcfHx81KsEFRUVRr3aJg2WtxYUFEjnzp3lzTffVPfV13jq1Cnx9PRUO2OzUzARPW0t/eQE5v1/MesfjynlPbO+9eCKAKIGNBpNo1nm+qsEa9euxerVqxEQEGCwpi/f5+rqijfffBOvvvoqYmJi4OjoqNYyY8YMODk5qTO+rq6u6Nixo8FrqL9CUs/NzQ0XL17E5s2bISLo3LkzAMDe3h5z587F+fPnkZ2dDTT4rAzhxo0b8PHxwZo1a5CWlgYA2Lx5M/R6Pfbv34+CgoJG40ePHg2tVouKigqD1fBD5syZAysrK3Tu3BmzZ89Gz549MWXKFPj7+yM4OBharRYlJSUGPWZhYSEuXryofh0cHIybN29iwIABiImJgbe3NyZPngx/f38EBQWhsrJS/UxsbGyMdrWtqqoKeHDVAgAcHBzw0ksv4fDhw0hISAAa/Hz07dsXGo0GV69eBRo0TiMielpaMuvBvFcx6x/OFPOeWd/6cCKA6Hvqw7gluil36tQJMTExGDp0KPDgF6eIoLS0FM7OzkZd4pWTk4MtW7aguLhY3ebt7Y3t27cjJycH58+fxxdffKHuc3FxwaBBg9ChQweD15Kbm4s7d+7gzp072LZtG9LS0mBjY4Pt27fD29sbe/bswdGjR9XQO3r0KBwcHKDVag1eCwDk5eXhD3/4A5YvX47ExETgQXfeP/3pTwgNDYWjoyO2bNmC7du3AwDKysrQtm1bWFtbG6yGc+fOYeDAgeqJGACEhoYiJiYG/fr1w7Vr17B+/Xq1Br1eD0tLS4NO0DTnwoULmD59OkaNGoWJEyciNTUVOp0OkZGR0Ol0iIuLw65du9TxOp0O3bt3h5WVFdDg/xsR0dPUklkP5j3ArH8oU8x7Zn0r1dJLEohMlSl0U663du1a6dmzp+Tn5xvl/XNzc6VDhw6iKIqsXLlSbfBSLyEhQTQajYwZM0YSEhIkNzdXYmJipFOnTlJYWGjwekpLS+XFF1+UuLg48fPzk5kzZ6pdibOysuSFF14Qd3d36devn0ycOFEcHByM9uzr8+fPi5ubmwQEBMiQIUNEo9E0WgYnzSyTjIyMlCFDhjTp+vxjZWZmiq2trURGRj50TP0zjustWbJERo4c2aiBkKHl5OSITqeTBQsWSHR0tEydOlUURZE1a9ZIRUWF5OXlycsvvyw+Pj4ya9Ys2bNnjyxatEh0Op3BG3AREf0YppT1YmZ5z6xvyhTznlnfenEigOghTKGbckJCgixYsEDat29vtM6v5eXlEh4eLnPmzJFt27aJoigSHR3d5OTg+PHjMnjwYHFxcRFvb2/x8vIySk21tbVSUlIiXl5ecv36dUlKShJ/f3+ZP3++DBkyREJDQ0VE5C9/+YusXbtWNmzYIJcuXTJ4HfLg0Tienp6yYsUK9QRg586d4uLiIjk5OU3uefvss88kIiJC7OzsDHay8vXXX4uNjY2sWrVK5EFX4hMnTsiHH34oqampTcYfO3ZMIiIixN7e3uiPJFuzZo2MHj260bZ3331XOnToIFFRUVJdXS1FRUWyY8cO8fPzE39/fxk+fLjRTuSIiP5XppD1YoZ5z6xvylTznlnfehnvBiiin7j6bsrG7GL8Q3r37o29e/fi5MmTRusWrNFoMGDAADg6OiIkJAROTk6YNm0a8KA7sJOTEwAgICAA/fv3x+3bt1FRUQE3Nzd1n6HrcXZ2hr+/P7KzsxEUFAQrKyvMnj0b9+/fx9y5cwEACxcuNPixG9Lr9UhMTISnpydWrVqlLrnz9/eHpaUl9Hp9k3veqqurce3aNZw6dQo+Pj5PXENNTQ1WrVoFW1tbvPjiiwCAKVOmoLCwEDdv3sTt27exYMECxMbGwtnZGXjQ7fr06dP4/PPP8eyzzz5xDY9SWVmp/r22thZt2rTBr371K2i1WixbtgweHh5YsmQJ5s2bh3nz5uH+/fsAYPBllEREP5YpZD3MMO+Z9Y2Zct4z61uxlp6JIKJHq6qqMvoxvt9dNjExURRFkaioKLWbcU1NjeTl5Rm9lnphYWESExMjIiLz5s2T9u3bS+/evSU8PFz+/e9/q+OM2Yk2NTVVraFeXV2ddOvWTVJSUpp9jaGX5mVkZMiYMWNk9OjR4u3tLYGBgXL27FkpKCiQ5ORk0Wq1snLlykav+e677wxaw8O88847YmdnJzdu3BD53s/qunXrxNbWttEzlomI6OHMMe+Z9f9lqnnPrG+9OBFARKra2lo1bBMSEtRlgzdu3JDIyEiZMmWKlJeXGzWQ6987Pj5eYmNjZfHixeLq6ipXr16VpKQk6dGjhyxatKjJPXKGUltb+8i66urqxMPDQz755BN13/Hjx+XmzZsGq6G0tFS++uoruXjxosiD5YLPP/+8jBo1qsnJ2datW8XJyUmuXbv20NqNpaqqSoYNGyaDBg1STyArKytFRKS4uFjc3d0lKSnpqdZEREQ/rKXznln//34Kec+sb714awARqSwsLCAi0Ov1mDZtGhRFQWhoKD766CNcuXIF6enpRl8+Wb8Ez8PDA3PnzoWLiwv+8Y9/wMPDAx4eHlAUBf369VM70RpSTk4ODh06hBkzZsDV1RV40OlWURQoioLa2lpUVVXBwsICOp0OALBq1Sps2LAB169fN0gN2dnZCAsLQ21tLS5evIjVq1cjNjYWO3fuRHZ2tvpIp/q68ODxUk5OTrCwsDBIDc3JycnBzp07UVJSgv79+2PcuHHo2bMnYmNjsXLlSoSEhOD9999Xu0pbWVnB1tYWlpaWRquJiIh+nJbOe3PPepho3jPrzUxLz0QQkenR6/XqrPiIESOkQ4cOcv78+adaQ3V1tezcuVNtgGPMVQjyGJ2U5cEVgsrKSunRo4ecOXNGfv3rX4utra2kpaUZpIYLFy6Io6OjREVFyYULF2TTpk2iKIraPfr7HYtFRJYuXSrBwcFGfTrAhQsXxN7eXgIDAyU4OFjs7e1lxIgRsnv3bhEROXTokDz33HPi4eEhR48elc8++0zWrFkjzzzzDJcLEhGZsJbOe3PMejHRvGfWmx9OBBBRs2prayUyMlIURTF69/mHaS4IjeFxOynX8/X1FX9/f9FqtQZ73NStW7dk2LBhsnTpUnWbXq+XwMBAOXXqlHqfYL3Lly/L66+/Lg4ODpKdnW2QGppTVVUls2bNkl/84hfqttzcXAkJCRF/f3+Ji4sTEZGvvvpKpk+fLs7OzuLl5SV9+vSRjIwMo9VFRESG0dJ5b05ZLyaa98x688RbA4joofr06YOzZ88avfv8w9R3730ax3mcTsp1dXW4c+cOrl69ivLycpw7d85gHYMVRUFgYCCmTp2qbvvtb3+Lo0eP4ubNmygtLUXv3r3x+uuv45lnnsHy5cuRlZWFlJQUo3WYBgCtVov//Oc/8PDwAB4sUfT09MTGjRsRGxuL3bt3w93dHWPHjsX+/ftx8eJF6HQ6aLVaozxVgoiIDK8l896csh4mmvfMevOkiIi0dBFEZJoa3pfW2lVUVDS6H/LAgQOYPn06li9fjpiYGDg6OqK2thZlZWXIyMiAm5ubwQP57t27sLOzAwAkJiZixowZSExMxMiRI5GdnY2oqChMmDABK1euxD//+U94eHigW7duBq2hobq6Ouj1eixcuBB3797F3r17odVqISLQaDS4evUqZs2aBXd3dxw4cAAws58ZIqLWwlx+d5tC1sPE8p5Zb744EUBE1EBdXR00Gg0URVHDOSoqCq+++io2bdqE/Px87N27FzY2Nkato6CgAKWlpfDz81O3TZgwARqNBh999JFRj11XV9eoEVFqaioCAgKwefNmRERENBqTmpqKESNG4Pz580ZdmUBERGQoppL1aMG8Z9YTbw0gImrgUZ2UL1++jDNnzjyVE4OuXbuia9euAAC9Xo/q6mq0a9fO6Ms2m+um/POf/xxvvfUWIiMjYWNjg/nz56snD3Z2dvjZz35m9KdJEBERGYqpZD1aKO+Z9QROBBARNVW/3E1EEBISgu3btyMzM9Pg9wk+Lo1Gg/Xr1+OLL77Ab37zG6Md5/Llyxg8eDC+/fZblJaWYtmyZeq9f4sXL0ZFRQUWLFiAgoICTJkyBV27dsUHH3yAmpoanhwQEdFPiqllPZ5S3jPrqR5vDSAieoi6ujpER0djy5YtyMzMbJEmSh988AFSU1ORmJiIY8eOwdfX1yjHqaioQEREBPR6Pfz9/fHKK68gKioK0dHRcHZ2Bh5cqdi7dy9ee+01WFhYwM7ODt999x0OHTrUaEkjERHRT4UpZD2eUt4z66khrgggInqEln5yQu/evfH3v/8dJ0+eRK9evYx2nEd1U64/QdBoNAgLC8OwYcNQWFiIe/fuwcfHB507dzZaXURERMbW0lmPp5T3zHpqiCsCiIgewRQ649bU1MDS0tLox3lUN+XXXnsNTk5OqK2tRVFREbp06WL0eoiIiJ4GU8h6PKW8Z9ZTPa4IICJ6BFM4MXgakwAA1BOD+m7KISEhEBHMmDEDiqKo3ZQLCgqwe/du2NjYmMTnQ0RE9CRMJcueRt4z66keVwQQEVETIqI+Q/jAgQMIDQ1F9+7dceXKFaSnp6N///4tXSIRERE9AWa9eeNEABERNas+HhRFQUBAADIzM3HixIkW66ZMREREhsWsN1+8NYCIiJqlKIraTTklJQWZmZk8MSAiImpFmPXmS9PSBRARkWkzhW7KREREZDzMevPDWwOIiOiRTKWbMhERERkHs978cCKAiIiIiIiIyIzw1gAiIiIiIiIiM8KJACIiIiIiIiIzwokAIiIiIiIiIjPCiQAiIiIiIiIiM8KJACIiIiIiIiIzwokAIiIiIiIiIjPCiQAiMoo5c+Zg8uTJLV0GERERGQmznuinixMBRE9gzpw5UBQFixYtarLvl7/8JRRFwZw5c4xaQ3x8PBwcHNSv33jjDfTv39+ox2woPz8fiqIgMzOz0fZ33nkH8fHxT60OIiIiY2DWM+uJWiNOBBA9IXd3dyQmJqKyslLddv/+fezfvx9dunRp0dqeRHV19RO93t7evtFJCxER0U8Vs755zHqiny5OBBA9IT8/P7i7uyMpKUndlpSUhC5dusDX17fR2CNHjmDo0KFwcHCAo6MjJkyYgCtXrqj7d+/ejXbt2iE3N1fdtmTJEnh7e+PevXs/WEt8fDzWrVuHrKwsKIoCRVHUmfqysjLMnz8fzs7O0Ol0GDFiBLKystTX1l9d2LFjBzw8PGBtbf1YNXt4eAAAfH19oSgKXnjhBaCZ5YJVVVWIiIhAx44dYW1tjaFDhyI9PV3df+LECSiKgk8//RQDBw6EjY0NhgwZgkuXLqljsrKyMHz4cNjZ2UGn02HAgAE4c+bMY/wrERER/XjMemY9UWvDiQAiAwgPD8euXbvUr//2t79h7ty5TcZVVFRg2bJlOHPmDD799FNoNBoEBQVBr9cDAMLCwjBu3DjMnDkTtbW1SE5Oxo4dO7Bv3z7Y2Nj8YB0hISFYvnw5+vTpg+LiYhQXFyMkJAQA8NJLL6GkpAQff/wxMjIy4Ofnh4CAANy+fVt9/eXLl3Hw4EEkJSWpy/9+qOa0tDQAwPHjx1FcXNzoJKmhFStW4ODBg3jvvfdw9uxZeHp6YsyYMY2ODwCrV6/G73//e5w5cwZt2rRBeHi4um/mzJlwc3NDeno6MjIyEBMTA0tLyx/8XIiIiJ4Us55ZT9SqCBH9aLNnz5ZJkyZJSUmJWFlZSX5+vuTn54u1tbXcunVLJk2aJLNnz37o62/duiUA5Msvv1S33b59W9zc3GTx4sXi4uIiv/vd7x5Zw65du8Te3l79OjY2Vvr169dozMmTJ0Wn08n9+/cbbe/Ro4fExcWpr7O0tJSSkpJHHu/7Nefl5QkAOXfuXLOfjYhIeXm5WFpayr59+9T91dXV0qlTJ9m4caOIiKSkpAgAOX78uDomOTlZAEhlZaWIiNjZ2Ul8fPwj6yMiIjIkZj2znqg14ooAIgNwdnbG+PHjER8fj127dmH8+PFwcnJqMi43NxfTp09H9+7dodPp0K1bNwBAYWGhOqZ9+/bYuXMn/vznP6NHjx6IiYl54vqysrJQXl4OR0dHtGvXTv2Tl5fXaOlf165d4ezs/D/X/EOuXLmCmpoaPP/88+o2S0tLPPfcc/j6668bjX322WfVv7u6ugIASkpKAADLli3D/PnzMXLkSGzYsKFR7URERMbErH80Zj3RT0ubli6AqLUIDw/HK6+8AgDYtm1bs2MmTpyIrl274q9//Ss6deoEvV6Pvn37NmnW8/nnn8PCwgLFxcWoqKiAnZ3dE9VWXl4OV1dXnDhxosm+hk1+bG1tf3TNhtJw+Z+iKACgLk184403MGPGDCQnJ+Pjjz9GbGwsEhMTERQUZJRaiIiIGmLWGwaznqjlcUUAkYEEBgaiuroaNTU1GDNmTJP9paWluHTpEtasWYOAgAD06tUL3377bZNx//rXv/DWW2/h0KFDaNeunXrC8bi0Wi3q6uoabfPz88PNmzfRpk0beHp6NvrT3NWM/6VmrVYLAE2O2VCPHj2g1Wpx6tQpdVtNTQ3S09PRu3fv/+n78/LyQmRkJD755BNMmTKl0f2aRERExsSsZ9YTtRZcEUBkIBYWFurSNwsLiyb727dvD0dHR2zfvh2urq4oLCxsshTw7t27CA0NRUREBMaOHQs3Nzf4+/tj4sSJmDp16mPV0a1bN+Tl5SEzMxNubm6ws7PDyJEjMXjwYEyePBkbN26El5cXioqKkJycjKCgIAwcOLDZ93qcmjt27Ii2bdviyJEjcHNzg7W1Nezt7RuNsbW1xeLFixEdHY0OHTqgS5cu2LhxI+7du4d58+Y91vdVWVmJ6OhoTJ06FR4eHrh+/TrS09MRHBz8WK8nIiJ6Usx6Zj1Ra8EVAUQGpNPpoNPpmt2n0WiQmJiIjIwM9O3bF5GRkXj77bcbjVm6dClsbW2xfv16AICPjw/Wr1+PhQsX4saNG49VQ3BwMAIDAzF8+HA4OzsjISEBiqLg8OHDGDZsGObOnQsvLy9MmzYNBQUFcHFxeeh7PU7Nbdq0wbvvvou4uDh06tQJkyZNava9NmzYgODgYISGhsLPzw+XL1/G0aNH0b59+8f6viwsLFBaWoqwsDB4eXnh5ZdfxtixY7Fu3brHej0REZEhMOuZ9UStgSIi0tJFEBEREREREdHTwRUBRERERERERGaEEwFEREREREREZoQTAURERERERERmhBMBRERERERERGaEEwFEREREREREZoQTAURERERERERmhBMBRERERERERGaEEwFEREREREREZoQTAURERERERERmhBMBRERERERERGaEEwFEREREREREZuT/AJbwbY95cdWDAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 1200x500 with 4 Axes>"
       ]
@@ -616,10 +637,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2f2b970c",
+   "id": "adc1a742",
    "metadata": {},
    "source": [
-    "In this simple example (well converging function) the gradient descent converges for all learning rates given enough iterations. The Error on the paramters approaches 10^-2 indicating the converging."
+    "<div class=\"alert alert-block alert-success\">\n",
+    "In this simple example (well converging function) the gradient descent converges for all learning rates given enough iterations. The Error on the paramters approaches 10^-3 and stays at this plateau indicating the parameters have converged\n",
+    "\n",
+    "</div>"
    ]
   },
   {
@@ -634,13 +658,16 @@
     "Try to add a stopping parameter as function of the number iterations. How would you define a stopping criterion?\n",
     "\n",
     "\n",
-    "We define the stopping criterion via the decrease in the cost function. If the decrease gets too small we stop. This will be implemented using a custom stopping_criterion function so it can easily be replaced."
+    "<div class=\"alert alert-block alert-success\">\n",
+    "We define the stopping criterion via the decrease in the cost function. If the decrease gets too small we stop. This will be implemented using a custom stopping_criterion function so it can easily be replaced.\n",
+    "\n",
+    "</div>"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "4258b4f3",
+   "execution_count": 14,
+   "id": "e214e0be",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -694,8 +721,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "8be1cebe",
+   "execution_count": 15,
+   "id": "06077986",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -718,8 +745,8 @@
     "X = np.random.randn(n_samples, n_features)  # standard normal distribution\n",
     "\n",
     "# Generate target values y with a linear combination of X and theta_true, plus noise\n",
-    "noise = 0.5 * np.random.randn(n_samples)  # Gaussian noise\n",
-    "y = X.dot @ theta_true + noise"
+    "noise = 0.5 * np.random.randn(n_samples)    # Gaussian noise\n",
+    "y = X.dot(theta_true) + noise"
    ]
   },
   {
@@ -768,8 +795,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "3e466f75",
+   "execution_count": 16,
+   "id": "1aaa2666",
    "metadata": {},
    "outputs": [
     {
@@ -785,14 +812,6 @@
     "res = gradient_descent(X, y, OLS_cost_func, OLS_grad_cost_func, num_iters=100000, stopping_criterion=stopping_criterion)\n",
     "print(f\"Terminated with error on theta of {theta_error(res[0])[1]:.3e}\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "244364a3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
