diff --git a/src/students/GA_1_8/GA_1_8_solution_HT.html b/src/students/GA_1_8/GA_1_8_solution_HT.html
new file mode 100644
index 0000000000000000000000000000000000000000..eb7a0c33432c14be9ef0365b59d57695eec4179e
--- /dev/null
+++ b/src/students/GA_1_8/GA_1_8_solution_HT.html
@@ -0,0 +1,8732 @@
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+
+.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,PHN2ZyB3aWR0aD0iMTQiIGhlaWdodD0iMTQiIHZpZXdCb3g9IjAgMCAxNCAxNCIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPGcgY2xpcC1wYXRoPSJ1cmwoI2NsaXAwXzEzN18xOTQ5MikiPgo8cGF0aCBjbGFzcz0ianAtaWNvbjMiIGQ9Ik00Ljc1IDQuOTMwNjZINi42MjVWNi44MDU2NkM2LjYyNSA3LjAxMTkxIDYuNzkzNzUgNy4xODA2NiA3IDcuMTgwNjZDNy4yMDYyNSA3LjE4MDY2IDcuMzc1IDcuMDExOTEgNy4zNzUgNi44MDU2NlY0LjkzMDY2SDkuMjVDOS40NTYyNSA0LjkzMDY2IDkuNjI1IDQuNzYxOTEgOS42MjUgNC41NTU2NkM5LjYyNSA0LjM0OTQxIDkuNDU2MjUgNC4xODA2NiA5LjI1IDQuMTgwNjZINy4zNzVWMi4zMDU2NkM3LjM3NSAyLjA5OTQxIDcuMjA2MjUgMS45MzA2NiA3IDEuOTMwNjZDNi43OTM3NSAxLjkzMDY2IDYuNjI1IDIuMDk5NDEgNi42MjUgMi4zMDU2NlY0LjE4MDY2SDQuNzVDNC41NDM3NSA0LjE4MDY2IDQuMzc1IDQuMzQ5NDEgNC4zNzUgNC41NTU2NkM0LjM3NSA0Ljc2MTkxIDQuNTQzNzUgNC45MzA2NiA0Ljc1IDQuOTMwNjZaIiBmaWxsPSIjNjE2MTYxIiBzdHJva2U9IiM2MTYxNjEiIHN0cm9rZS13aWR0aD0iMC43Ii8+CjwvZz4KPHBhdGggY2xhc3M9ImpwLWljb24zIiBmaWxsLXJ1bGU9ImV2ZW5vZGQiIGNsaXAtcnVsZT0iZXZlbm9kZCIgZD0iTTExLjUgOS41VjExLjVMMi41IDExLjVWOS41TDExLjUgOS41Wk0xMiA4QzEyLjU1MjMgOCAxMyA4LjQ0NzcyIDEzIDlWMTJDMTMgMTIuNTUyMyAxMi41NTIzIDEzIDEyIDEzTDIgMTNDMS40NDc3MiAxMyAxIDEyLjU1MjMgMSAxMlY5QzEgOC40NDc3MiAxLjQ0NzcxIDggMiA4TDEyIDhaIiBmaWxsPSIjNjE2MTYxIi8+CjxkZWZzPgo8Y2xpcFBhdGggaWQ9ImNsaXAwXzEzN18xOTQ5MiI+CjxyZWN0IGNsYXNzPSJqcC1pY29uMyIgd2lkdGg9IjYiIGhlaWdodD0iNiIgZmlsbD0id2hpdGUiIHRyYW5zZm9ybT0ibWF0cml4KC0xIDAgMCAxIDEwIDEuNTU1NjYpIi8+CjwvY2xpcFBhdGg+CjwvZGVmcz4KPC9zdmc+Cg==);
+ --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,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE2IDE2IiB2ZXJzaW9uPSIxLjEiPgogICA8cGF0aCBjbGFzcz0ianAtaWNvbjIganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMzMzMzMzIgogICAgICBkPSJtOCAwLjI5Yy0xLjQgMC0yLjcgMC43My0zLjYgMS44LTEuMiAxLjUtMS40IDMuNC0xLjUgNS4yLTAuMTggMi4yLTAuNDQgNC0yLjMgNS4zbDAuMjggMS4zaDVjMC4wMjYgMC42NiAwLjMyIDEuMSAwLjcxIDEuNSAwLjg0IDAuNjEgMiAwLjYxIDIuOCAwIDAuNTItMC40IDAuNi0xIDAuNzEtMS41aDVsMC4yOC0xLjNjLTEuOS0wLjk3LTIuMi0zLjMtMi4zLTUuMy0wLjEzLTEuOC0wLjI2LTMuNy0xLjUtNS4yLTAuODUtMS0yLjItMS44LTMuNi0xLjh6bTAgMS40YzAuODggMCAxLjkgMC41NSAyLjUgMS4zIDAuODggMS4xIDEuMSAyLjcgMS4yIDQuNCAwLjEzIDEuNyAwLjIzIDMuNiAxLjMgNS4yaC0xMGMxLjEtMS42IDEuMi0zLjQgMS4zLTUuMiAwLjEzLTEuNyAwLjMtMy4zIDEuMi00LjQgMC41OS0wLjcyIDEuNi0xLjMgMi41LTEuM3ptLTAuNzQgMTJoMS41Yy0wLjAwMTUgMC4yOCAwLjAxNSAwLjc5LTAuNzQgMC43OS0wLjczIDAuMDAxNi0wLjcyLTAuNTMtMC43NC0wLjc5eiIgLz4KPC9zdmc+Cg==);
+ --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==);
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+ --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-image: url(data:image/svg+xml;base64,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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);
+ --jp-icon-json: url(data:image/svg+xml;base64,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);
+ --jp-icon-julia: url(data:image/svg+xml;base64,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);
+ --jp-icon-jupyter-favicon: url(data:image/svg+xml;base64,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);
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+ --jp-icon-jupyterlab-wordmark: 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+ --jp-icon-kernel: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzYxNjE2MSIgZD0iTTE1IDlIOXY2aDZWOXptLTIgNGgtMnYtMmgydjJ6bTgtMlY5aC0yVjdjMC0xLjEtLjktMi0yLTJoLTJWM2gtMnYyaC0yVjNIOXYySDdjLTEuMSAwLTIgLjktMiAydjJIM3YyaDJ2MkgzdjJoMnYyYzAgMS4xLjkgMiAyIDJoMnYyaDJ2LTJoMnYyaDJ2LTJoMmMxLjEgMCAyLS45IDItMnYtMmgydi0yaC0ydi0yaDJ6bS00IDZIN1Y3aDEwdjEweiIvPgo8L3N2Zz4K);
+ --jp-icon-keyboard: url(data:image/svg+xml;base64,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);
+ --jp-icon-launch: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMzIgMzIiIHdpZHRoPSIzMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yNiwyOEg2YTIuMDAyNywyLjAwMjcsMCwwLDEtMi0yVjZBMi4wMDI3LDIuMDAyNywwLDAsMSw2LDRIMTZWNkg2VjI2SDI2VjE2aDJWMjZBMi4wMDI3LDIuMDAyNywwLDAsMSwyNiwyOFoiLz4KICAgIDxwb2x5Z29uIHBvaW50cz0iMjAgMiAyMCA0IDI2LjU4NiA0IDE4IDEyLjU4NiAxOS40MTQgMTQgMjggNS40MTQgMjggMTIgMzAgMTIgMzAgMiAyMCAyIi8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-launcher: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkgMTlINVY1aDdWM0g1YTIgMiAwIDAwLTIgMnYxNGEyIDIgMCAwMDIgMmgxNGMxLjEgMCAyLS45IDItMnYtN2gtMnY3ek0xNCAzdjJoMy41OWwtOS44MyA5LjgzIDEuNDEgMS40MUwxOSA2LjQxVjEwaDJWM2gtN3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-line-form: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGZpbGw9IndoaXRlIiBkPSJNNS44OCA0LjEyTDEzLjc2IDEybC03Ljg4IDcuODhMOCAyMmwxMC0xMEw4IDJ6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-link: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTMuOSAxMmMwLTEuNzEgMS4zOS0zLjEgMy4xLTMuMWg0VjdIN2MtMi43NiAwLTUgMi4yNC01IDVzMi4yNCA1IDUgNWg0di0xLjlIN2MtMS43MSAwLTMuMS0xLjM5LTMuMS0zLjF6TTggMTNoOHYtMkg4djJ6bTktNmgtNHYxLjloNGMxLjcxIDAgMy4xIDEuMzkgMy4xIDMuMXMtMS4zOSAzLjEtMy4xIDMuMWgtNFYxN2g0YzIuNzYgMCA1LTIuMjQgNS01cy0yLjI0LTUtNS01eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xOSA1djE0SDVWNWgxNG0xLjEtMkgzLjljLS41IDAtLjkuNC0uOS45djE2LjJjMCAuNC40LjkuOS45aDE2LjJjLjQgMCAuOS0uNS45LS45VjMuOWMwLS41LS41LS45LS45LS45ek0xMSA3aDZ2MmgtNlY3em0wIDRoNnYyaC02di0yem0wIDRoNnYyaC02ek03IDdoMnYySDd6bTAgNGgydjJIN3ptMCA0aDJ2Mkg3eiIvPgo8L3N2Zz4K);
+ --jp-icon-markdown: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-down: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-up: url(data:image/svg+xml;base64,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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,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);
+ --jp-icon-settings: url(data:image/svg+xml;base64,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);
+ --jp-icon-share: url(data:image/svg+xml;base64,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);
+ --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-table-rows: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMSw4SDNWNGgxOFY4eiBNMjEsMTBIM3Y0aDE4VjEweiBNMjEsMTZIM3Y0aDE4VjE2eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-tag: url(data:image/svg+xml;base64,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);
+ --jp-icon-terminal: url(data:image/svg+xml;base64,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);
+ --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-toc: url(data:image/svg+xml;base64,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);
+ --jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-trusted: url(data:image/svg+xml;base64,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);
+ --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-users: url(data:image/svg+xml;base64,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);
+ --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-word: url(data:image/svg+xml;base64,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);
+ --jp-icon-yaml: url(data:image/svg+xml;base64,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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;
+}
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+.jp-RenderedText pre .ansi-yellow-fg {
+ color: #ddb62b;
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+.jp-RenderedText pre .ansi-blue-fg {
+ color: #208ffb;
+}
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+ color: #d160c4;
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+.jp-RenderedText pre .ansi-cyan-fg {
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+
+.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;
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+ --jp-inverse-layout-color4: var(--md-grey-600);
+
+ /* Brand/accent */
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+ * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
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+
+ /*
+ RTC user specific colors.
+ These colors are used for the cursor, username in the editor,
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+ */
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+ --jp-collaborator-color1: #ffad8e;
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+
+ /* 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;
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+ --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);
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+ --jp-terminal-icon-background-color: var(--md-grey-800);
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+ --jp-text-editor-icon-color: var(--md-grey-700);
+ --jp-inspector-icon-color: var(--md-grey-700);
+ --jp-switch-color: var(--md-grey-400);
+ --jp-switch-true-position-color: var(--md-orange-900);
+}
+</style>
+<style type="text/css">
+/* Force rendering true colors when outputing to pdf */
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+/* Input area styling */
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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=24fdc979">
+<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="GA-1.8:-Multivariate-Distributions">GA 1.8: Multivariate Distributions<a class="anchor-link" href="#GA-1.8:-Multivariate-Distributions">¶</a></h1><h1 style="position: absolute; display: flex; flex-grow: 0; flex-shrink: 0; flex-direction: row-reverse; top: 60px;right: 30px; margin: 0; border: 0">
+<style>
+ .markdown {width:100%; position: relative}
+ article { position: relative }
+ </style>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/tu-logo/TU_P1_full-color.png" style="width:100px; height: auto; margin: 0"/>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/mude-logo/MUDE_Logo-small.png" style="width:100px; height: auto; margin: 0"/>
+</h1>
+<h2 style="height: 10px">
+</h2>
+<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 1.8, Friday Oct 25, 2024.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8b5d241">
+<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="Objective">Objective<a class="anchor-link" href="#Objective">¶</a></h2><p>This notebook is structured in an identical way to WS 1.8. In particular, we have 3 main tasks:</p>
+<ol>
+<li>Build a multivariate distribution $F_{X_1,X_2}(x_1,x_2)$</li>
+<li>Use the distribution by comparing empirical probabilities to values computed with $F_{X_1,X_2}(x_1,x_2)$ for the AND, OR and function of random variable cases</li>
+<li>Validate the distribution using the distribution of the function of random variables, $Z(X_1,X_2)$.</li>
+</ol>
+<h3 id="Multivariate-Distribution-(Task-1)">Multivariate Distribution (Task 1)<a class="anchor-link" href="#Multivariate-Distribution-(Task-1)">¶</a></h3><p>As with WS 1.8, we will build a multivariate distribution, but this time we will include non-Gaussian marginal distributions using a Gaussian Copula:</p>
+<p>$$
+F_{X_1,X_2}(x_1,x_2) = C[F_{X_1}(x_1)F_{X_2}(x_2)]
+$$</p>
+<p>In this case, the Copula requires one parameter: the Pearson correlation coefficient, $\rho$.</p>
+<p>This distribution has been implemented in the class <code>Bivariate</code> within <code>helper.py</code>. You can define an instance of the class using:</p>
+<pre><code>my_bivariate_dist = Bivariate(marginal_1, marginal_2, rho)
+</code></pre>
+<p>where the arguments are the marginal distributions for your random variables and are instances of the class <code>rv_continuous</code> from <code>scipy.stats</code>. In fact, the <code>Bivariate</code> class has been created with similar methods to <code>multivariate_normal</code>; in other words, you can use the methods <code>pdf</code>, <code>cdf</code> and <code>rvs</code> in the same way as <code>multivariate_normal</code> in WS 1.8.</p>
+<p>Note that the function <code>plot_contours</code> will also work, but due to the way <code>Bivariate</code> is implemented, it is slow to make the plots, so you may want to use small sample sizes.</p>
+<h4 id="Python-Package:-pyvinecopulib">Python Package: <code>pyvinecopulib</code><a class="anchor-link" href="#Python-Package:-pyvinecopulib">¶</a></h4><p>A package <code>pyvinecopulib</code> is required for the Bivariate class. It is only available on PyPI, so it has to be installed using <code>pip</code>. Fortunately you should already have done this as part of PA 1.8, so all you need to do is remember to use your environment <code>mude-week-8</code>.</p>
+<h3 id="Probability-Calculations-for-3-Cases-(Task-2)">Probability Calculations for 3 Cases (Task 2)<a class="anchor-link" href="#Probability-Calculations-for-3-Cases-(Task-2)">¶</a></h3><p>For each data set, we will use the 90th percentile of each random variable to evaluate the AND, OR and function of random variable cases. In other words:</p>
+<p>$$
+x_{1,90} = F_{X_1}^{-1}(0.90) \;\;\textrm{and}\;\; x_{2,90} = F_{X_2}^{-1}(0.90)
+$$</p>
+<p>Since there were three data sets to choose from last week, each with different functions and variables, this notebook uses the notation $Z(X_1,X_2)$ to represent the function of random variables for your particular case. As we did in WS 1.8, we would like to evaluate $Z$ for a threshold condition (in WS 1.8 it was $Z<0$ for the Thingamajig). For this assignment, consider the threshold case to be all combinations of $x_1$ and $x_2$ such that:</p>
+<p>$$
+Z>Z(x_{1,90},z_{2,90})
+$$</p>
+<h3 id="Propagating-Uncertainty-(Task-3)">Propagating Uncertainty (Task 3)<a class="anchor-link" href="#Propagating-Uncertainty-(Task-3)">¶</a></h3><p>This proceeds as in WS 1.8 as well, where you will use the samples generated in Task 2 to evaluate the distribution of $Z$ and compare to the empirical data set.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=55bd0e2d">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below allows you to edit the contents of helper and incorporate the changes in the notebook without restarting the kernel.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=91463787">
+<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="o">%</span><span class="k">load_ext</span> autoreload
+<span class="o">%</span><span class="k">autoreload</span> 2
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=7eeb37e0-aca0-4759-866f-f5ad09ea8d0b">
+<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="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
+
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">plot_contour</span>
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">Bivariate</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=d0113213">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below is only for the solution.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=b4a22fde">
+<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">data_set</span> <span class="o">=</span> <span class="s1">'dataset_HT'</span>
+<span class="n">N_factor_MCS</span> <span class="o">=</span> <span class="mi">100</span>
+<span class="n">make_figs</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="n">save_figs</span> <span class="o">=</span> <span class="kc">False</span>
+
+<span class="n">bivariate_lim</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">25</span><span class="p">]</span>
+
+<span class="n">plot_x2</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">z90</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">z90</span><span class="o">/</span><span class="p">(</span><span class="mf">255.4</span><span class="o">*</span><span class="n">x1</span> <span class="o">-</span> <span class="mf">490.4</span><span class="p">))</span>
+<span class="n">Z</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">:</span> <span class="mf">255.4</span><span class="o">*</span><span class="n">x1</span><span class="o">*</span><span class="n">x2</span><span class="o">**</span><span class="mi">2</span> <span class="o">-</span> <span class="mf">490.4</span><span class="o">*</span><span class="n">x2</span><span class="o">**</span><span class="mi">2</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4d11b3b2-5d82-4e67-a151-0e7025ab175a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-1:-Creating-a-Bivariate-Distribution">Part 1: Creating a Bivariate Distribution<a class="anchor-link" href="#Part-1:-Creating-a-Bivariate-Distribution">¶</a></h2><p>We need to represent our two dependent random variables with marginal distributions and use the correlation coefficient to model dependence, as found previously in GA 1.7.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=fbd5f10c-2c28-4dde-b5c4-e2781058997f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.1:</b>
+<p>Import your data set from last week and define the marginal distributions as frozen scipy stats objects.</p>
+<p><em>The cell below illustrates how to create a frozen Gaussian distribution</em></p>
+</p>
+
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f00a23b6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+Remember there is a <a href="https://mude.citg.tudelft.nl/2024/book/probability/python.html" target="_blank">new page on scipy stats in the book</a> in case you need a reference.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=2b3477a8-002c-42a8-bd30-6c24890156c2">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+<span class="c1"># parameters1 = st.norm.fit_loc_scale(data_x1)</span>
+<span class="c1"># dist_x1 = st.norm(*parameters1)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3aad6608-743f-4f49-bcab-440ab5b3d093">
+<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="n">data_path</span> <span class="o">=</span> <span class="s2">"data/dataset_HT.csv"</span>
+<span class="c1"># data_path = "data/dataset_traffic.csv"</span>
+
+<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">genfromtxt</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span>
+ <span class="n">delimiter</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span>
+ <span class="n">unpack</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">skip_header</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="c1"># first is ?, then H, then T</span>
+<span class="n">data_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">,:])</span>
+<span class="n">data_x2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">2</span><span class="p">,:])</span>
+
+<span class="n">parameters1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">expon</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="n">dist_x1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">expon</span><span class="p">(</span><span class="o">*</span><span class="n">parameters1</span><span class="p">)</span>
+
+<span class="n">parameters2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x2</span><span class="p">)</span>
+<span class="n">dist_x2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="p">(</span><span class="o">*</span><span class="n">parameters2</span><span class="p">)</span>
+
+<span class="n">N</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data: </span><span class="si">{</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'mean and std of X1 and X2: '</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x1</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x2</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x2</span><span class="o">.</span><span class="n">std</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>shape of data: (3, 582755)
+shape of data_x1: (582755,)
+min/max of data_x1: 0.04, 9.19
+shape of data_x2: (582755,)
+min/max of data_x2: 2.02, 16.71
+
+
+mean and std of X1 and X2:
+1.296410395449203 0.8151654687505836
+6.861141165669963 2.1703304220642203
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=9b6d08ec-5e23-4efb-a9fc-d96776812429">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.2:</b>
+Compute the covariance and correlation coefficient between the two random variables. Print the results.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=c8a5e3ec-d87d-4d2d-b51d-85351bdd586d">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5c13ea7e-65b8-46ee-804e-f62fb4e68afd">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Covariance of two random variables X1 and X2 (numpy arrays).</span>
+<span class="sd"> '''</span>
+ <span class="n">mean_x1</span> <span class="o">=</span> <span class="n">X1</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">mean_x2</span> <span class="o">=</span> <span class="n">X2</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">diff_x1</span> <span class="o">=</span> <span class="n">X1</span> <span class="o">-</span> <span class="n">mean_x1</span>
+ <span class="n">diff_x2</span> <span class="o">=</span> <span class="n">X2</span> <span class="o">-</span> <span class="n">mean_x2</span>
+ <span class="n">product</span> <span class="o">=</span> <span class="n">diff_x1</span> <span class="o">*</span> <span class="n">diff_x2</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">product</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="k">return</span> <span class="n">covariance</span>
+
+<span class="k">def</span> <span class="nf">pearson_correlation</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">)</span>
+ <span class="n">correl_coeff</span> <span class="o">=</span> <span class="n">covariance</span><span class="o">/</span><span class="p">(</span><span class="n">X1</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="o">*</span><span class="n">X2</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+ <span class="k">return</span> <span class="n">correl_coeff</span>
+
+<span class="n">cov_x12</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The covariance of X1 and X2 is </span><span class="si">{</span><span class="n">cov_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="n">rho_x12</span> <span class="o">=</span> <span class="n">pearson_correlation</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The correlation coefficient of X1 and X2 is </span><span class="si">{</span><span class="n">rho_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>The covariance of X1 and X2 is 0.80639
+The correlation coefficient of X1 and X2 is 0.45580
+The correlation coefficient of X1 and X2 is 0.45580
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=23e4d105-dc2f-4aa8-902f-1872d517e547">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.3:</b>
+Build the bivariate distribution by instantiating the <code>Bivariate</code> class in <code>helper.py</code> (and described above). To validate the result, create a plot that shows contours of the joint PDF, compared with the data (see note below). Include the data in your plot and write a few comments on the quality of the fit for use in your Report.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f9ee9c39-6e6a-4257-9746-fdf118eef8aa">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Use the helper function <code>plot_contour</code> in <code>helper.py</code>; it works exactle the same as in WS 1.8.</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=896fd1c2">
+<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="c1"># plot_contour? # uncomment and run to read docstring</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5cd6a070">
+<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="c1"># bivar_dist = Bivariate(YOUR_CODE_HERE, YOUR_CODE_HERE, YOUR_CODE_HERE)</span>
+
+<span class="c1"># plot_contour(YOUR_CODE_HERE, YOUR_CODE_HERE, data=data)</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">bivar_dist</span> <span class="o">=</span> <span class="n">Bivariate</span><span class="p">(</span><span class="n">dist_x1</span><span class="p">,</span> <span class="n">dist_x2</span><span class="p">,</span> <span class="n">rho_x12</span><span class="p">)</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</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[9]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='$X_1$', ylabel='$X_2$'>)</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=c7336c15-ffd9-4548-8bd6-6a156e184037">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-2:-Using-the-Bivariate-Distribution">Part 2: Using the Bivariate Distribution<a class="anchor-link" href="#Part-2:-Using-the-Bivariate-Distribution">¶</a></h2><p>Now that we have the distribution, we will use it compute probabilities related to the three cases, presented above, as follows:</p>
+<ol>
+<li>$P[X_1>x_{1,90} \;\cup\; X_2>x_{2,90}$</li>
+<li>$P[X_1>x_{1,90} \;\cap\; X_2>x_{2,90}]$</li>
+<li>$P[X_1,X_2:\; Z>Z(x_{1,90},x_{2,90})]$</li>
+</ol>
+<p>Note that the "critical" Z value in this case is that where your Z function is evaluated at the 90th percentile values of each random variable.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f544418c">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 2:</b>
+<p>For each of the three cases, do the following:</p>
+<ul>
+<li>Compute the requested probability using the empirical distribution.</li>
+<li>Compute the requested probability using the bivariate distribution.</li>
+<li>Create a bivariate plot that includes PDF contours <em>and</em> the region of interest.</li>
+<li>Repeat the calculations for additional cases of correlation coefficient (for example change $\rho$ to: +0.9, 0.0, then -0.9) to see how the answer changes (you can simply regenerate the plot, you don't need to make multiple versions). <em>You can save this sub-task for later if you are running out of time. It is more important to get through Task 3 during the in-class session.</em></li>
+<li>Write two or three sentences that summarize the results and explains the quantitative impact of correlation coefficient. Make a particular note about whether or not one case may or be affected more or less than the others.</li>
+</ul>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=bdab1a35-4e2f-42a2-804c-17f7f0917b6a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note that the optional arguments in the helper function <code>plot_contour</code> will be useful here.
+
+<p>Here is an example code that shows you what it can do (the values are meaningless)</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=adb079f6">
+<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">region_example</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="mi">0</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">18</span><span class="p">,</span> <span class="mi">19</span><span class="p">,</span> <span class="mi">12</span><span class="p">]])</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="mi">23</span><span class="p">,</span> <span class="mi">13</span><span class="p">],</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_example</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8974e1b">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.1 and 2.2:</b> create cells below to carry out the OR and AND calculations.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=0999c23c">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a07bc27f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.3:</b> create cells below to carry out the Case 3 calculations.</p>
+<p>Note that in this case you need to make the plot to visualize the region over which we want to integrate. We need to define the boundary of the region of interest by solving the equation $Z(X_1,X_2)$ for $X_2$ when $Z=Z(x_{1,90},x_{2,90})$.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=0bea4cff">
+<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>The equation can be defined as follows:</p>
+<p>$$
+\textrm{WRITE THE EQUATION HERE}
+$$</p>
+<p>which is then defined in Python and included in the <code>plot_contours</code> function as an array for the keyword argument <code>region</code>.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=cf2e5192">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=da352934-c7b3-4dd2-a913-271f9ad38d26">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Start of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=096a378a-2256-489e-a99c-9458924b6e1a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: order of the tasks in this solution is not important.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=364b7689-2034-437f-b7cf-d59042ea93a8">
+<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="Case-1-and-2">Case 1 and 2<a class="anchor-link" href="#Case-1-and-2">¶</a></h3><p>First we will compute the probabilities from the distribution.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=74874fef-e398-45b6-8858-bebd1017e095">
+<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="n">x90_1</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+<span class="n">x90_2</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+
+<span class="n">region_or</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">]]])</span>
+<span class="n">region_and</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">]])</span>
+
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">cdf</span><span class="p">([</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_2</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="c1"># Case 1 and 2 empirical probabilities</span>
+<span class="n">N</span> <span class="o">=</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">size</span>
+
+<span class="n">number_of_points_lower_left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">((</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">&</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">))</span>
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">number_of_points_lower_left</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 empirical probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_or</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_2.svg'</span><span class="p">))</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_and</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_3.svg'</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>Case 1 and 2 probabilities
+ lower left: 0.82977
+ left side: 0.90000
+ bottom side: 0.90000
+=============================
+Case 1, Union: 0.17023
+Case 2, Intersection: 0.02977
+
+
+Case 1 and 2 empirical probabilities
+ lower left: 0.82112
+ left side: 0.90200
+ bottom side: 0.88094
+=============================
+Case 1, Union: 0.17888
+Case 2, Intersection: 0.03818
+
+
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ee7d5b8c-1cee-4799-bd44-d01ae4266fc3">
+<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="Case-3">Case 3<a class="anchor-link" href="#Case-3">¶</a></h3><p>The Z function is defined at the top of this notebook in a solution code cell.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=cfe4b8df-e9e4-4086-a265-a67100f28fe0">
+<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 [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="n">z_90</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">)</span>
+
+<span class="n">plot_Z_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">bivariate_lim</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">plot_Z_x2</span> <span class="o">=</span> <span class="n">plot_x2</span><span class="p">(</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">z_90</span><span class="p">)</span>
+<span class="n">region_Z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">plot_Z_x2</span><span class="p">])</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_Z</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_4.svg'</span><span class="p">))</span>
+
+<span class="n">sample_N</span> <span class="o">=</span> <span class="n">N_factor_MCS</span><span class="o">*</span><span class="n">N</span>
+<span class="n">sample</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">rvs</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">sample_N</span><span class="p">)</span>
+<span class="n">sample_X1</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">sample_X2</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span>
+
+<span class="n">sample_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">sample_X1</span><span class="p">,</span> <span class="n">sample_X2</span><span class="p">)</span>
+<span class="n">Z_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90</span> <span class="o">=</span> <span class="n">Z_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">sample_N</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="s1">'Z case MCS'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">sample_N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of samples of Z < 0 is: </span><span class="si">{</span><span class="n">Z_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The MCS probability is </span><span class="si">{</span><span class="n">p_Z90</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">sample_N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="n">empirical_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="n">Z_data_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">empirical_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90_data</span> <span class="o">=</span> <span class="n">Z_data_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">N</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="s1">'Z case empirical'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of data where Z < 0 is: </span><span class="si">{</span><span class="n">Z_data_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The empirical probability is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90_data</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</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="application/vnd.jupyter.stderr" tabindex="0">
+<pre>C:\Users\rlanzafame\AppData\Local\Temp\ipykernel_12520\3263440411.py:8: RuntimeWarning: invalid value encountered in sqrt
+ plot_x2 = lambda x1, z90: np.sqrt(z90/(255.4*x1 - 490.4))
+</pre>
+</div>
+</div>
+<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>Z case MCS
+N = 58275500
+The number of samples of Z < 0 is: 4466776
+This is 7.665% of all samples.
+The MCS probability is 0.077.
+The c.o.v. is of p is 0.000.
+
+
+Z case empirical
+N = 582755
+The number of data where Z < 0 is: 46473
+This is 7.975% of all samples.
+The empirical probability is 0.080.
+The c.o.v. is of p is 0.005.
+
+
+</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=b95860c6-8cbb-47e1-89ab-4d4d56a6f1be">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: the bivariate figures are an important concept for the exam, so if using the code is too difficult for you to use when studying on your own, try sketching it on paper.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=839cec7d-2167-4572-9585-b1318ca41803">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>End of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2421b1e1-8adb-4dee-8095-5a54b02e6d44">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">Part 3: Validate Bivariate with Monte Carlo Simulation<a class="anchor-link" href="#Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">¶</a></h2><p>Now that we have seen how the different cases give different values of probability, let's focus on the function of random variables. This is a more interesting case because we can use the samples of $Z$ to approximate the distribution $f_Z(z)$ and use the empirical distribution of $Z$ to help validate the bivariate model.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=6d2196f5-c480-4810-81e4-d692819d648f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p>$\textbf{Task 3:}$</p>
+<p>Do the following:</p>
+<ul>
+<li>Use Monte Carlo Simulation to create a sample of $Z(X_1,X_2)$ and compare this distribution to the empirical distribution.</li>
+<li>Write 2-3 sentences assessing the quality of the distribution from MCS, and whether the bivariate distribution is acceptable for this problem. Use qualitative and quantitative measures from last week to support your arguments.</li>
+</ul>
+</p>
+<p>
+<em>Note: it would be interesting to fit a parametric distribution to the MCS sample, but it is not required for this assignment.</em>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=99ee3a19">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.1:</b> Plot histograms of $Z$ based on the Monte Carlo samples, and based on the data. Note that you probably already computed the samples in Part 2.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=446b73fe-5277-48ff-8187-e4eabcd21354">
+<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="c1"># plot_values = np.linspace(sample_Z.min(), sample_Z.max(), 30)</span>
+<span class="c1"># fig, ax = plt.subplots(1)</span>
+<span class="c1"># ax.hist([YOUR_CODE_HERE, YOUR_CODE_HERE],</span>
+<span class="c1"># bins=plot_values,</span>
+<span class="c1"># density=True,</span>
+<span class="c1"># edgecolor='black');</span>
+<span class="c1"># ax.legend(['Data', 'MCS Sample'])</span>
+<span class="c1"># ax.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># ax.set_xlabel('Empirical Density [--]')</span>
+<span class="c1"># ax.set_title('Comparison of Distributions of $Z$');</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">plot_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">sample_Z</span><span class="o">.</span><span class="n">max</span><span class="p">(),</span> <span class="mi">30</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="mi">1</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">([</span><span class="n">empirical_Z</span><span class="p">,</span> <span class="n">sample_Z</span><span class="p">],</span>
+ <span class="n">bins</span><span class="o">=</span><span class="n">plot_values</span><span class="p">,</span>
+ <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">edgecolor</span><span class="o">=</span><span class="s1">'black'</span><span class="p">);</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s1">'Data'</span><span class="p">,</span> <span class="s1">'MCS Sample'</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">'$Z(X_1,X_2)$'</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">'Empirical Density [--]'</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="s1">'Comparison of Distributions of $Z$'</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
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kDmiKeeekrbt29XSkqKateurQ4dOmj69Olq1qxZSWwOAABQMcLI9u3b9fbbbys2NlaJiYk2123YEx0drQULFmjfvn1KT09X8+bNNWXKFPXo0eNG+w4AACoAh58z4uhTULdv367u3btrw4YNio2NVdeuXRUaGqq4uDiHOwsAACqeGzpN8+c7WoqqefPm1vvzAQDAra3ML2DNycnRxYsX8/yWSGFtzp49q6pVq5bKw64AAEDJMwxDFy9elJ+fnypVyv9kTJmHkblz5+ry5cs2TzH8s/T0dJvfezhz5gwXjQIAUE6dOnWqwKdVl2kYWbFihaZMmaIvvvhCderUybferFmzNHXq1Dzlp06dUrVq1UqziwAAoISkpaXJ39+/0J9lKLMwsnLlSg0bNkyrVq3SAw88UGDd8PBwjRs3zvo6d2OqVatGGAEAoJwp7BKLMgkjK1as0NChQ7VixQr16dOn0Pqurq55fh0VAABUTA6HkYKeglqvXj2Fh4frzJkz+vjjjyVdDyIDBw7Uu+++qw4dOigpKUmS5O7ururVq5fQZgAAgPLK4eeM7NmzR23atFGbNm0kSePGjVObNm2st+kmJiYqISHBWv/DDz9UVlaWRo4cKV9fX+v00ksvldAmAACA8qxcPA4+LS1N1atX14ULF7hmBABMkp2drczMTLO7gZtI5cqV5eTklO/8on5+l6sfygMAlD3DMJSUlKTff//d7K7gJlSjRg35+Pjc0HPACCMAgALlBpE6deqoSpUqPHwSkq6H1CtXrig5OVmS5OvrW+xlEUYAAPnKzs62BpFatWqZ3R3cZNzd3SVJycnJqlOnToGnbAri8AWsAIBbR+41IlWqVDG5J7hZ5e4bN3I9EWEEAFAoTs0gPyWxbxBGAACAqbhmBADgsISEBKWkpJTZ+ry8vFSvXr0yWx/KFmEEAOCQhIQENQlsqmtXr5TZOt3cq+jwoXiHAsngwYO1bNkySZKzs7Nq1qypli1b6umnn9bgwYML/En7P4qKitKYMWO4tbkUEUYAAA5JSUnRtatXVOvB8apcy7/U15eZekqpX81VSkqKw0dHevbsqaVLlyo7O1vnzp3Txo0b9dJLL2n16tX68ssv5ezMx+DNgHcBAFAslWv5y9WnodndKJCrq6t8fHwkSbfffrvatm2rDh066P7771dUVJSGDx+uefPmaenSpTp27Jhq1qyp0NBQvfXWW/L09NTWrVs1ZMgQSf+7UPONN97QlClTtHz5ckVEROjw4cPy8PBQt27dFBERoTp16pi2veUVF7DepBISErR379480x9/9wcA4Lhu3bqpVatWio6OliRVqlRJ8+fP188//6xly5Zp8+bNeuWVVyRJHTt2VEREhKpVq6bExEQlJiZqwoQJkqSMjAxNnz5d+/fv17p163T8+HENHjzYrM0q1zgyYjJ7F4ElJibqicf76uq19Dz1q7i7Kf7QYS7kAoAbEBgYqB9//FGSNGbMGGt5QECApk+frhdeeEGRkZFycXFR9erVZbFYrEdYcg0dOtT67zvuuEPz589X+/btdenSJXl6epbJdlQUhBETFXYR2PJH3dW09v8OXsX/lqNn114t1nlTAMD/GIZhPe2yZcsWzZw5UwcPHlRaWpqysrJ07do1Xb58WR4eHvkuIy4uTlOmTNG+fft0/vx55eTkSLr+t71Zs2Zlsh0VBWHERPldBHb12B5d2LFcTWtXUlvf4j1aFwCQv/j4eAUEBOjkyZPq3bu3RowYoenTp6tmzZr65ptvNGzYsAKfKHr58mWFhIQoJCREy5cvV+3atZWQkKAePXooIyOjDLekYiCM3AT+fBFYZuopE3sDABXb5s2b9dNPP2ns2LHas2ePsrKyNHfuXOutvp9//rlNfRcXF2VnZ9uUHTp0SCkpKfr73/8uf//rXyb37NlTNhtQAXEBKwCgwkpPT1dSUpLOnDmjvXv3aubMmXr44Yf14IMPauDAgbrzzjuVlZWl9957T8eOHdM///lPLVy40GYZDRo00KVLl/Sf//xHKSkpunLliurVqycXFxdruy+//FLTp083aSvLP46MAACKpayO4t7IejZu3ChfX185OzvrtttuU6tWrTR//nwNGjRIlSpVUuvWrTVv3jzNnj1b4eHhuvfeezVr1iwNHDjQuoyOHTtqxIgRevLJJ5Wammq9tTcqKkqvv/665s+fr7Zt22rOnDl66KGHSmKTbzkWwzAMsztRmLS0NFWvXl0XLlxQtWrVzO5Oidm7d6+CgoLkMyjC5jTNpQNblPrVXMX+1cPmmpG9idkK+uiyYmNj1bZtWzO6DOAWc+3aNR0/flwBAQFyc3OTVH6ewIqyYW8fyVXUz2+OjAAAHFKvXj0dPhTPb9OgxBBGAAAOq1evHuEAJYYLWAEAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApuI5IwAAhyUkJPDQswrgxIkTCggIUFxcnFq3bm1aPwgjAACHJCQkqGlgE125eq3M1lnF3U3xhw4XOZAMHjxYy5Yt0/PPP5/nh+/CwsK0YMECDRo0SFFRUdbypKQkvfnmm/rXv/6lM2fOqE6dOmrdurXGjBmj+++/X5IUFxenSZMm6fvvv1daWpp8fHx0991364MPPpCXl5fdvhw7dkwTJ07Utm3bdP78eXl5eSkoKEhvv/22GjduXLwBqWAIIwAAh6SkpOjK1Wta/qi7mtYu/bP98b/l6Nm1V5WSkuLQ0RF/f3999tlneuedd+Tu7i7p+u+orFixIs9yTpw4oU6dOqlGjRp666231LJlS2VmZurrr7/WyJEjdejQISUnJ+uBBx5QaGiovv76a9WoUUPHjx/Xl19+qStX7P9OT0ZGhrp3767AwEBFR0fL19dXp0+f1oYNG3ThwoXiD0oFQxgBABRL09qVbH7M82bTtm1bHTt2TNHR0XrmmWckSdHR0fL399cdd9xhUzcsLEwWi0Xff/+9PDw8rOXNmzfX0KFDJUm7du1SWlqaFi1aJGfn6x+fAQEB6tatW759OHjwoI4dO6bNmzerfv36kqT69eurU6dONvVeffVVrV27VqdPn5aPj4+eeeYZTZ48WZUrV5YkTZkyRevWrdPo0aM1ZcoUnT9/XgMGDND777+vuXPnat68ecrJydFLL72kiRMnWpdrsVgUGRmpL7/8Ulu3bpWPj4/eeustPfHEEwX2ecKECdq+fbs8PDwUEhKid955J98jPyWBC1gBABXWkCFDtHTpUuvrJUuWWMNFrvPnz2vjxo0aOXKkTRDJVaNGDUmSj4+PsrKytHbtWhX1B+9r166tSpUqafXq1crOzs63XtWqVRUVFaWDBw/q3Xff1T/+8Q+98847NnWOHj2q//u//9PGjRu1YsUKLVmyRH369NHp06e1bds2zZ49W3/729/07bff2rSbNGmS+vbtq/379+vZZ5/V008/rfj4eLv9SExMVJcuXdS6dWvt2bNHGzdu1Llz59SvX78ibW9xEUYAABXWgAED9M033+jEiRM6efKkdu7cqWeffdamzq+//irDMBQYGFjgsjp06KDXX39d/fv3l5eXl3r16qW3335b586dy7fN7bffrvnz52vy5Mm67bbb1K1bN02fPl3Hjh2zqfe3v/1NHTt2VIMGDRQaGqrx48fr888/t6mTk5OjJUuWqFmzZgoNDVXXrl11+PBhRUREqEmTJhoyZIiaNGmirVu32rR74oknNHz4cDVu3FjTp09Xu3bt9N5779nt74IFC9S2bVvNnDlTgYGBatOmjZYsWaItW7bol19+KXB8bgRhBABQYXl5ealPnz5atmyZli5dqj59+uQ53ZB7lMNisRS6vDfffFNJSUlauHChmjVrpoULFyowMFA//fRTvm1GjhyppKQkLV++XMHBwVq1apWaN2+umJgYa53Vq1frnnvukY+Pjzw9PTVp0iQlJCTYLKdBgwaqWrWq9bW3t7eaNWumSpUq2ZQlJyfbtAsODs7zOr8jI7GxsdqyZYs8PT2tU25IO3r0aCGjU3yEEQBAhTZ06FBFRUVp2bJleU7RSFKjRo1ksVjy/YD+s1q1aumJJ57Q3LlzFR8fLz8/P82ZM6fANlWrVtVDDz2kN998U/v371fnzp01Y8YMSdK3336rp556Sr169dJXX32luLg4TZw4URkZGTbLyL1+JJfFYrFblpOTU+g25Be8cnJyFBoaqn379tlMR44c0b333lvocouLMAIAqNB69uypjIwMZWRkqEePHnnm16xZUz169NAHH3ygy5cv55n/+++/57tsFxcX3XnnnXbb5cdisSgwMNDaZufOnapfv74mTpyodu3aqVGjRjp58mSRl1eYP19D8u233+Z7Sqpt27Y6cOCAGjRooIYNG9pM9q6nKSmEEQBAhebk5KT4+HjFx8fLycn+3T+RkZHKzs5W+/bttWbNGh05ckTx8fGaP3++9TTHV199pWeffVZfffWVfvnlFx0+fFhz5szRhg0b9PDDD9td7r59+/Twww9r9erVOnjwoH799VctXrxYS5YssbZp2LChEhIS9Nlnn+no0aOaP3++1q5dW2Lbv2rVKi1ZskS//PKL3njjDX3//fcaNWqU3bojR47U+fPn9fTTT+v777/XsWPHtGnTJg0dOrTAC3BvFLf2AgCKJf63wk8H3CzrqVatWoHzAwICtHfvXr355psaP368EhMTVbt2bQUFBWnBggWSpGbNmqlKlSoaP368Tp06JVdXVzVq1EiLFi3SgAED7C63bt26atCggaZOnaoTJ07IYrFYX48dO1aS9PDDD2vs2LEaNWqU0tPT1adPH02aNElTpky54e2WpKlTp+qzzz5TWFiYfHx89Mknn6hZs2Z26/r5+Wnnzp169dVX1aNHD6Wnp6t+/frq2bOnzbUpJc1iFPX+JBOlpaWpevXqunDhQqE7VHmyd+9eBQUFyWdQhFx9GlrLLx3YotSv5ir2rx429/DvTcxW0EeXFRsbq7Zt25rRZQC3mGvXrun48eMKCAiQm5ubpPLxBFZcZ7FYtHbtWj3yyCOltg57+0iuon5+c2QEAOCQevXqKf7QYX6bBiWGMAIAcFi9evUIBygxhBEAACqocnAlhiTupgEAACYjjAAAClVevmGj7JXEvkEYAQDkK/cJn1euXDG5J7hZ5e4bf34arCO4ZgQAkC8nJyfVqFHD+nsnVapUKdJvuKDiMwxDV65cUXJysmrUqJHvA+WKgjACACiQj4+PJOX5ATZAkmrUqGHdR4qLMAIAKJDFYpGvr6/q1KmjzMxMs7uDm0jlypVv6IhILsIIAKBInJycSuSDB/gzLmAFAACmIowAAABTORxGtm/frtDQUPn5+clisWjdunWFttm2bZuCgoLk5uamO+64QwsXLixOXwEAQAXkcBi5fPmyWrVqpffff79I9Y8fP67evXurc+fOiouL0+uvv67Ro0drzZo1DncWAABUPA5fwNqrVy/16tWryPUXLlyoevXqKSIiQpLUtGlT7dmzR3PmzFHfvn0dXT0AAKhgSv2akd27dyskJMSmrEePHtqzZ0++t4ilp6crLS3NZgIAABVTqYeRpKQkeXt725R5e3srKytLKSkpdtvMmjVL1atXt07+/v6l3U0AAGCSMrmb5s+PDs79UZ38HikcHh6uCxcuWKdTp06Veh8BAIA5Sv2hZz4+PkpKSrIpS05OlrOzs2rVqmW3jaurq1xdXUu7awAA4CZQ6kdGgoODFRMTY1O2adMmtWvX7oZ+4Q8AAFQMDoeRS5cuad++fdq3b5+k67fu7tu3TwkJCZKun2IZOHCgtf6IESN08uRJjRs3TvHx8VqyZIkWL16sCRMmlMwWAACAcs3h0zR79uxR165dra/HjRsnSRo0aJCioqKUmJhoDSaSFBAQoA0bNmjs2LH64IMP5Ofnp/nz53NbLwAAkFSMMHLfffdZL0C1JyoqKk9Zly5dtHfvXkdXBQAAbgH8Ng0AADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiqWGEkMjJSAQEBcnNzU1BQkHbs2FFg/U8++UStWrVSlSpV5OvrqyFDhig1NbVYHQYAABWLw2Fk5cqVGjNmjCZOnKi4uDh17txZvXr1UkJCgt3633zzjQYOHKhhw4bpwIEDWrVqlX744QcNHz78hjsPAADKP4fDyLx58zRs2DANHz5cTZs2VUREhPz9/bVgwQK79b/99ls1aNBAo0ePVkBAgO655x49//zz2rNnzw13HgAAlH8OhZGMjAzFxsYqJCTEpjwkJES7du2y26Zjx446ffq0NmzYIMMwdO7cOa1evVp9+vQpfq8BAECF4VAYSUlJUXZ2try9vW3Kvb29lZSUZLdNx44d9cknn+jJJ5+Ui4uLfHx8VKNGDb333nv5ric9PV1paWk2EwAAqJiKdQGrxWKxeW0YRp6yXAcPHtTo0aM1efJkxcbGauPGjTp+/LhGjBiR7/JnzZql6tWrWyd/f//idBMAAJQDDoURLy8vOTk55TkKkpycnOdoSa5Zs2apU6dOevnll9WyZUv16NFDkZGRWrJkiRITE+22CQ8P14ULF6zTqVOnHOkmAAAoRxwKIy4uLgoKClJMTIxNeUxMjDp27Gi3zZUrV1Spku1qnJycJF0/omKPq6urqlWrZjMBAICKyeHTNOPGjdOiRYu0ZMkSxcfHa+zYsUpISLCedgkPD9fAgQOt9UNDQxUdHa0FCxbo2LFj2rlzp0aPHq327dvLz8+v5LYEAACUS86ONnjyySeVmpqqadOmKTExUS1atNCGDRtUv359SVJiYqLNM0cGDx6sixcv6v3339f48eNVo0YNdevWTbNnzy65rQAAAOWWw2FEksLCwhQWFmZ3XlRUVJ6yF198US+++GJxVgUAACo4fpsGAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmKlYYiYyMVEBAgNzc3BQUFKQdO3YUWD89PV0TJ05U/fr15erqqjvvvFNLliwpVocBAEDF4uxog5UrV2rMmDGKjIxUp06d9OGHH6pXr146ePCg6tWrZ7dNv379dO7cOS1evFgNGzZUcnKysrKybrjzAACg/HM4jMybN0/Dhg3T8OHDJUkRERH6+uuvtWDBAs2aNStP/Y0bN2rbtm06duyYatasKUlq0KDBjfUaAABUGA6dpsnIyFBsbKxCQkJsykNCQrRr1y67bb788ku1a9dOb731lm6//XY1btxYEyZM0NWrV/NdT3p6utLS0mwmAABQMTl0ZCQlJUXZ2dny9va2Kff29lZSUpLdNseOHdM333wjNzc3rV27VikpKQoLC9P58+fzvW5k1qxZmjp1qiNdAwAA5VSxLmC1WCw2rw3DyFOWKycnRxaLRZ988onat2+v3r17a968eYqKisr36Eh4eLguXLhgnU6dOlWcbgIAgHLAoSMjXl5ecnJyynMUJDk5Oc/Rkly+vr66/fbbVb16dWtZ06ZNZRiGTp8+rUaNGuVp4+rqKldXV0e6BgAAyimHjoy4uLgoKChIMTExNuUxMTHq2LGj3TadOnXS2bNndenSJWvZL7/8okqVKqlu3brF6DIAAKhIHD5NM27cOC1atEhLlixRfHy8xo4dq4SEBI0YMULS9VMsAwcOtNbv37+/atWqpSFDhujgwYPavn27Xn75ZQ0dOlTu7u4ltyUAAKBccvjW3ieffFKpqamaNm2aEhMT1aJFC23YsEH169eXJCUmJiohIcFa39PTUzExMXrxxRfVrl071apVS/369dOMGTNKbisAAEC55XAYkaSwsDCFhYXZnRcVFZWnLDAwMM+pHQAAAInfpgEAACYjjAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMVK4xERkYqICBAbm5uCgoK0o4dO4rUbufOnXJ2dlbr1q2Ls1oAAFABORxGVq5cqTFjxmjixImKi4tT586d1atXLyUkJBTY7sKFCxo4cKDuv//+YncWAABUPA6HkXnz5mnYsGEaPny4mjZtqoiICPn7+2vBggUFtnv++efVv39/BQcHF7uzAACg4nEojGRkZCg2NlYhISE25SEhIdq1a1e+7ZYuXaqjR4/qjTfeKF4vAQBAheXsSOWUlBRlZ2fL29vbptzb21tJSUl22xw5ckSvvfaaduzYIWfnoq0uPT1d6enp1tdpaWmOdBMAAJQjxbqA1WKx2Lw2DCNPmSRlZ2erf//+mjp1qho3blzk5c+aNUvVq1e3Tv7+/sXpJgAAKAccCiNeXl5ycnLKcxQkOTk5z9ESSbp48aL27NmjUaNGydnZWc7Ozpo2bZr2798vZ2dnbd682e56wsPDdeHCBet06tQpR7oJAADKEYdO07i4uCgoKEgxMTF69NFHreUxMTF6+OGH89SvVq2afvrpJ5uyyMhIbd68WatXr1ZAQIDd9bi6usrV1dWRrgEAgHLKoTAiSePGjdOAAQPUrl07BQcH66OPPlJCQoJGjBgh6fpRjTNnzujjjz9WpUqV1KJFC5v2derUkZubW55yAABwa3I4jDz55JNKTU3VtGnTlJiYqBYtWmjDhg2qX7++JCkxMbHQZ44AAADkcjiMSFJYWJjCwsLszouKiiqw7ZQpUzRlypTirBYAAFRA/DYNAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMVawwEhkZqYCAALm5uSkoKEg7duzIt250dLS6d++u2rVrq1q1agoODtbXX39d7A4DAICKxeEwsnLlSo0ZM0YTJ05UXFycOnfurF69eikhIcFu/e3bt6t79+7asGGDYmNj1bVrV4WGhiouLu6GOw8AAMo/h8PIvHnzNGzYMA0fPlxNmzZVRESE/P39tWDBArv1IyIi9Morr+gvf/mLGjVqpJkzZ6pRo0Zav379DXceAACUfw6FkYyMDMXGxiokJMSmPCQkRLt27SrSMnJycnTx4kXVrFkz3zrp6elKS0uzmQAAQMXkUBhJSUlRdna2vL29bcq9vb2VlJRUpGXMnTtXly9fVr9+/fKtM2vWLFWvXt06+fv7O9JNAABQjhTrAlaLxWLz2jCMPGX2rFixQlOmTNHKlStVp06dfOuFh4frwoUL1unUqVPF6SYAACgHnB2p7OXlJScnpzxHQZKTk/McLfmzlStXatiwYVq1apUeeOCBAuu6urrK1dXVka4BAIByyqEjIy4uLgoKClJMTIxNeUxMjDp27JhvuxUrVmjw4MH69NNP1adPn+L1FAAAVEgOHRmRpHHjxmnAgAFq166dgoOD9dFHHykhIUEjRoyQdP0Uy5kzZ/Txxx9Luh5EBg4cqHfffVcdOnSwHlVxd3dX9erVS3BTAABAeeRwGHnyySeVmpqqadOmKTExUS1atNCGDRtUv359SVJiYqLNM0c+/PBDZWVlaeTIkRo5cqS1fNCgQYqKirrxLQAAAOWaw2FEksLCwhQWFmZ33p8DxtatW4uzCgAAcIvgt2kAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpnM3uAIovISFBKSkpduelp6fL1dU1T7mXl5fq1atX2l0DAKDIihVGIiMj9fbbbysxMVHNmzdXRESEOnfunG/9bdu2ady4cTpw4ID8/Pz0yiuvaMSIEcXu9M0kv0BQ2h/6CQkJahLYVNeuXrE7v5JFyjHylldxd1P8ocMEEgDATcPhMLJy5UqNGTNGkZGR6tSpkz788EP16tVLBw8etPsBd/z4cfXu3VvPPfecli9frp07dyosLEy1a9dW3759S2QjzFJQIHB1ddOaNavl6+ubZ15JBJWUlBRdu3pFtR4cr8q1/G3mXT22Rxd2LNfyR93VtPb/zsTF/5ajZ9deVUpKCmEEAHDTcDiMzJs3T8OGDdPw4cMlSREREfr666+1YMECzZo1K0/9hQsXql69eoqIiJAkNW3aVHv27NGcOXPKfRjJLxBcO31AaZv/oQcffNBuu9yjEyWhci1/ufo0tCnLTD0lSWpau5La+jqVyHoAACgtDoWRjIwMxcbG6rXXXrMpDwkJ0a5du+y22b17t0JCQmzKevToocWLFyszM1OVK1d2sMs3nz8HgszUU8oxlOfIhGR7dMJs+Z1iyu96E4lrTgAAJc+hMJKSkqLs7Gx5e3vblHt7eyspKclum6SkJLv1s7KylJKSYvc0Rnp6utLT062vL1y4IElKS0tzpLtFkpSUlG/fK1WqpJycnDzlPj4+8vHx0aVLl673N+lX5WRcs87PPTJxJdPQpQzbCzeuZF5/ndu2oPaxZ7Nt2h9OySm0bVHbHzhwQEHt/qL0a1fzbJ9Fkp3LTSRJ7m6u+mFPrPz9/fMdu8LGTbqxcS+ofX5tb7S9mX3/Y1v6XrH6Xhb7a3nuO38nzNtnSkru57Zh5Pep8v8ZDjhz5owhydi1a5dN+YwZM4wmTZrYbdOoUSNj5syZNmXffPONIclITEy02+aNN94wdP3zkImJiYmJiamcT6dOnSowXzh0ZMTLy0tOTk550lZycnKeox+5fHx87NZ3dnZWrVq17LYJDw/XuHHjrK9zcnJ0/vx51apVSxaLxZEulytpaWny9/fXqVOnVK1aNbO7U+Ex3mWL8S47jHXZYrzzZxiGLl68KD8/vwLrORRGXFxcFBQUpJiYGD366KPW8piYGD388MN22wQHB2v9+vU2ZZs2bVK7du3yvV7E1dU1zzULNWrUcKSr5Vq1atXYocsQ4122GO+yw1iXLcbbvurVqxdax+EnsI4bN06LFi3SkiVLFB8fr7FjxyohIcH63JDw8HANHDjQWn/EiBE6efKkxo0bp/j4eC1ZskSLFy/WhAkTHF01AACogBy+tffJJ59Uamqqpk2bpsTERLVo0UIbNmxQ/fr1JUmJiYlKSEiw1g8ICNCGDRs0duxYffDBB/Lz89P8+fPL/W29AACgZBTrCaxhYWEKCwuzOy8qKipPWZcuXbR3797irOqW4urqqjfeeCPf22pRshjvssV4lx3Gumwx3jfOYhiF3W8DAABQevjVXgAAYCrCCAAAMBVhBAAAmIowAgAATEUYKWORkZEKCAiQm5ubgoKCtGPHjgLrb9u2TUFBQXJzc9Mdd9yhhQsXllFPKwZHxnvr1q2yWCx5pkOHDpVhj8un7du3KzQ0VH5+frJYLFq3bl2hbdi3i8/R8WbfLr5Zs2bpL3/5i6pWrao6derokUce0eHDhf/qOvu3YwgjZWjlypUaM2aMJk6cqLi4OHXu3Fm9evWyeS7LHx0/fly9e/dW586dFRcXp9dff12jR4/WmjVryrjn5ZOj453r8OHDSkxMtE6NGjUqox6XX5cvX1arVq30/vvvF6k++/aNcXS8c7FvO27btm0aOXKkvv32W8XExCgrK0shISG6fPlyvm3Yv4uhqD+ShxvXvn17Y8SIETZlgYGBxmuvvWa3/iuvvGIEBgbalD3//PNGhw4dSq2PFYmj471lyxZDkvHf//63DHpXcUky1q5dW2Ad9u2SU5TxZt8uOcnJyYYkY9u2bfnWYf92HEdGykhGRoZiY2MVEhJiUx4SEqJdu3bZbbN79+489Xv06KE9e/YoMzOz1PpaERRnvHO1adNGvr6+uv/++7Vly5bS7OYti33bHOzbN+7ChQuSpJo1a+Zbh/3bcYSRMpKSkqLs7Ow8v27s7e2d51eNcyUlJdmtn5WVpZSUlFLra0VQnPH29fXVRx99pDVr1ig6OlpNmjTR/fffr+3bt5dFl28p7Ntli327ZBiGoXHjxumee+5RixYt8q3H/u24Yj0OHsVnsVhsXhuGkaessPr2ymGfI+PdpEkTNWnSxPo6ODhYp06d0pw5c3TvvfeWaj9vRezbZYd9u2SMGjVKP/74o7755ptC67J/O4YjI2XEy8tLTk5Oeb6VJycn50nQuXx8fOzWd3Z2Vq1atUqtrxVBccbbng4dOujIkSMl3b1bHvu2+di3HfPiiy/qyy+/1JYtW1S3bt0C67J/O44wUkZcXFwUFBSkmJgYm/KYmBh17NjRbpvg4OA89Tdt2qR27dqpcuXKpdbXiqA4421PXFycfH19S7p7tzz2bfOxbxeNYRgaNWqUoqOjtXnzZgUEBBTahv27GEy8ePaW89lnnxmVK1c2Fi9ebBw8eNAYM2aM4eHhYZw4ccIwDMN47bXXjAEDBljrHzt2zKhSpYoxduxY4+DBg8bixYuNypUrG6tXrzZrE8oVR8f7nXfeMdauXWv88ssvxs8//2y89tprhiRjzZo1Zm1CuXHx4kUjLi7OiIuLMyQZ8+bNM+Li4oyTJ08ahsG+XdIcHW/27eJ74YUXjOrVqxtbt241EhMTrdOVK1esddi/bxxhpIx98MEHRv369Q0XFxejbdu2NreHDRo0yOjSpYtN/a1btxpt2rQxXFxcjAYNGhgLFiwo4x6Xb46M9+zZs40777zTcHNzM2677TbjnnvuMf71r3+Z0OvyJ/fW0T9PgwYNMgyDfbukOTre7NvFZ2+cJRlLly611mH/vnEWw/j/V9UAAACYgGtGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAFdjgwYP1yCOPFFrPYrFo3bp1JbbeBg0aKCIiosSWV5qmTJmi1q1bl8pyLRaLLBaLw2Nx4sQJa9vS6BuQa/v27QoNDZWfn1+x/w4YhqE5c+aocePGcnV1lb+/v2bOnOnQMggjQCkbPHiw9YPlj1PPnj1Lfd3vvvuuoqKiCq2XmJioXr16lXp/cv3xg9rZ2VleXl669957FRERofT09DLrhyRNmDBB//nPf6yvixrgiqJ58+ZKTEzUX//6V4fa+fv7KzExUePHjy+RfgD5uXz5slq1aqX333+/2Mt46aWXtGjRIs2ZM0eHDh3S+vXr1b59e4eW4VzstQMosp49e2rp0qU2Za6urqW+3urVqxc4PyMjQy4uLvLx8Sn1vvxZ8+bN9e9//1s5OTlKTU3V1q1bNWPGDP3zn//U1q1bVbVq1TLph6enpzw9PUtl2c7OzsUaWycnJ/n4+JRav4BcvXr1KvCLSEZGhv72t7/pk08+0e+//64WLVpo9uzZuu+++yRJ8fHxWrBggX7++Wc1adKk2P3gyAhQBlxdXeXj42Mz3Xbbbdb5FotFH374oR588EFVqVJFTZs21e7du/Xrr7/qvvvuk4eHh4KDg3X06FFrm9zTCx9++KH8/f1VpUoVPfHEE/r999+tdf78Lf++++7TqFGjNG7cOHl5eal79+7W9f/x8Ozp06f11FNPqWbNmvLw8FC7du303XffSZKOHj2qhx9+WN7e3vL09NRf/vIX/fvf/3Z4THI/qP38/HTXXXfpxRdf1LZt2/Tzzz9r9uzZ1noZGRl65ZVXdPvtt8vDw0N33323tm7dap0fFRWlGjVq6Ouvv1bTpk3l6empnj17KjEx0Vpn69atat++vTw8PFSjRg116tRJJ0+etBnH3H8vW7ZMX3zxhfXIzdatW9WtWzeNGjXKpv+pqalydXXV5s2bHd52oLwYMmSIdu7cqc8++0w//vijnnjiCfXs2VNHjhyRJK1fv1533HGHvvrqKwUEBKhBgwYaPny4zp8/79B6CCPATWL69OkaOHCg9u3bp8DAQPXv31/PP/+8wsPDtWfPHknK84H466+/6vPPP9f69eu1ceNG7du3TyNHjixwPcuWLZOzs7N27typDz/8MM/8S5cuqUuXLjp79qy+/PJL7d+/X6+88opycnKs83v37q1///vfiouLU48ePRQaGqqEhIQbHoPAwED16tVL0dHR1rLC/hhK0pUrVzRnzhz985//1Pbt25WQkKAJEyZIkrKysvTII4+oS5cu+vHHH7V792799a9/lcViybP+CRMmqF+/ftYwk5iYqI4dO2r48OH69NNPbU4hffLJJ/Lz81PXrl1veLuBm9HRo0e1YsUKrVq1Sp07d9add96pCRMm6J577rEe6T127JhOnjypVatW6eOPP1ZUVJRiY2P1+OOPO7QuTtMAZeCrr77Kc8j91Vdf1aRJk6yvhwwZon79+lnnBQcHa9KkSerRo4ek6+dlhwwZYrOMa9euadmyZapbt64k6b333lOfPn00d+7cfE8PNGzYUG+99Va+ff3000/122+/6YcfflDNmjWtbXK1atVKrVq1sr6eMWOG1q5dqy+//DJPWCqOwMBAbdq0SdL//hiePn1afn5+kq4Hho0bN2rp0qXWi+QyMzO1cOFC3XnnnZKuh7Zp06ZJktLS0nThwgU9+OCD1vlNmza1u25PT0+5u7srPT3dZvz69u2rF198UV988YX1PVq6dKn1eiCgItq7d68Mw1Djxo1tytPT01WrVi1JUk5OjtLT0/Xxxx9b6y1evFhBQUE6fPhwkU/dEEaAMtC1a1ctWLDApiz3gz5Xy5Ytrf/29vaWJN111102ZdeuXVNaWpqqVasmSapXr541iEhScHCwcnJydPjw4XzDSLt27Qrs6759+9SmTZs8/ct1+fJlTZ06VV999ZXOnj2rrKwsXb16tUSOjEjXr8zP/YAvyh9DSapSpYo1aEiSr6+vkpOTJV0f58GDB6tHjx7q3r27HnjgAfXr10++vr5F7pOrq6ueffZZLVmyRP369dO+ffu0f/9+h+88GDFihJYvX259fenSJfXq1Us7duyQJNWvX18HDhxwaJlAacnJyZGTk5NiY2Pl5ORkMy/3y5Wvr6+cnZ1t/o/mhv2EhATCCHAz8fDwsDm6YE/lypWt/879MLZXlnu6xJ7cOgV9W/fw8CiwH+7u7gXOf/nll/X1119rzpw5atiwodzd3fX4448rIyOjwHZFFR8fr4CAAElF+2Mo2Y6TdH37DcOwvl66dKlGjx6tjRs3auXKlfrb3/6mmJgYdejQocj9Gj58uFq3bq3Tp09ryZIluv/++1W/fn2Htm3atGnW00e5Fi1apKtXr9rdDsBMbdq0UXZ2tpKTk9W5c2e7dTp16qSsrCwdPXrU+oXgl19+kSSH/n8QRoByLCEhQWfPnrWewti9e7cqVaqU50iCI1q2bKlFixbp/Pnzdo+O7NixQ4MHD9ajjz4q6fq3+xMnThR7fX906NAhbdy4UeHh4ZKK9sewqNq0aaM2bdooPDxcwcHB+vTTT+2GERcXF2VnZ+cpv+uuu9SuXTv94x//0Keffqr33nvP4T7UqVNHderUsSm7/fbbHV4OUFIuXbqkX3/91fr6+PHj2rdvn2rWrKnGjRvrmWee0cCBAzV37ly1adNGKSkp2rx5s+666y717t1bDzzwgNq2bauhQ4cqIiJCOTk5GjlypLp37+7Q3yEuYAXKQHp6upKSkmymlJSUG16um5ubBg0apP3792vHjh0aPXq0+vXrd0O36j799NPy8fHRI488op07d+rYsWNas2aNdu/eLen69SPR0dHWUxX9+/cv8GhNfrKyspSUlKSzZ8/qp59+0nvvvacuXbqodevWevnllyXJ5o9hdHS0jh8/rh9++EGzZ8/Whg0birSe48ePKzw8XLt379bJkye1adMm/fLLL/leN9KgQQP9+OOPOnz4sFJSUpSZmWmdN3z4cP39739Xdna2NYwB5dmePXusQV2Sxo0bpzZt2mjy5MmSrh9VHDhwoMaPH68mTZrooYce0nfffSd/f39JUqVKlbR+/Xrrs4L69Omjpk2b6rPPPnOoHxwZAcrAxo0b81yj0KRJEx06dOiGltuwYUM99thj6t27t86fP6/evXsrMjLyhpbp4uKiTZs2afz48erdu7eysrLUrFkzffDBB5Kkd955R0OHDlXHjh3l5eWlV199VWlpaQ6v58CBA/L19ZWTk5OqV6+uZs2aKTw8XC+88ILNM1iWLl2qGTNmaPz48Tpz5oxq1aql4OBg9e7du0jrqVKlig4dOqRly5YpNTVVvr6+GjVqlJ5//nm79Z977jlt3bpV7dq106VLl7RlyxbrMxWefvppjRkzRv3795ebm5vD2wzcbO677z6bU5p/VrlyZU2dOlVTp07Nt46fn5/WrFlzQ/2wGAX1AsBNa8qUKVq3bp327dtndlduGadOnVKDBg30ww8/qG3btgXWLYn3h/cYtwpO0wBAITIzM5WQkKBXX31VHTp0KDSI5Prpp5/k6enp8NGqhIQEeXp6Ovz7HkB5xWkaACjEzp071bVrVzVu3FirV68uUpvRo0fr2WeflSTVrl3bofX5+flZj4aUxc8GAGbjNA0AADAVp2kAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKn+H17llEE/q6pvAAAAAElFTkSuQmCC"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ebc6a6a6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.2:</b> Define a function to compute the ecdf.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=5804f940-23e1-480b-adf1-17c3f41fb5c1">
+<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="c1"># def ecdf(var):</span>
+<span class="c1"># x = YOUR_CODE_HERE # sort the values from small to large</span>
+<span class="c1"># n = YOUR_CODE_HERE # determine the number of datapoints</span>
+<span class="c1"># y = YOUR_CODE_HERE</span>
+<span class="c1"># return [y, x]</span>
+
+<span class="c1"># SOLUTION:</span>
+<span class="k">def</span> <span class="nf">ecdf</span><span class="p">(</span><span class="n">var</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">sort</span><span class="p">(</span><span class="n">var</span><span class="p">)</span> <span class="c1"># sort the values from small to large</span>
+ <span class="n">n</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span> <span class="c1"># determine the number of datapoints</span>
+ <span class="n">y</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">n</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+ <span class="k">return</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2efb02a2">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.3:</b> Create a semi-log plot of the non-exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3c0da378-d6b8-4bdf-9a24-ac7f38862b4d">
+<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 [17]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('CDF, $\mathrm{P}[Z < z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands lower tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'CDF, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z < z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands lower tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
+<pre>c:\Users\rlanzafame\Anaconda3\envs\mude-week-8\Lib\site-packages\IPython\core\events.py:82: UserWarning: Creating legend with loc="best" can be slow with large amounts of data.
+ func(*args, **kwargs)
+c:\Users\rlanzafame\Anaconda3\envs\mude-week-8\Lib\site-packages\IPython\core\pylabtools.py:170: UserWarning: Creating legend with loc="best" can be slow with large amounts of data.
+ fig.canvas.print_figure(bytes_io, **kw)
+</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=eeae26ba">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.4:</b> Create a semi-log plot of the exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=a432095b-9b71-4b1d-871a-21c0097c06e9">
+<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 [18]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('Exceedance Probability, $\mathrm{P}[Z > z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands upper tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'Exceedance Probability, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z > z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands upper tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"><p>In case you are wondering, the data for this exercise was computed with a Clayton Copula. A Copula is a useful way of modelling non-linear dependence. If you would like to learn more about this, you should consider the 2nd year cross-over module CEGM2005 Probabilistic Modelling of real-world phenomena through ObseRvations and Elicitation (MORE).</p></div>
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+<p><strong>End of notebook.</strong></p>
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+.highlight .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */
+.highlight .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */
+.highlight .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */
+.highlight .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */
+.highlight .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */
+.highlight .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */
+.highlight .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */
+.highlight .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */
+.highlight .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */
+.highlight .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */
+.highlight .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */
+.highlight .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */
+.highlight .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */
+.highlight .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */
+.highlight .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */
+.highlight .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */
+.highlight .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */
+.highlight .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */
+.highlight .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */
+.highlight .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */
+.highlight .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */
+.highlight .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */
+.highlight .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */
+.highlight .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */
+.highlight .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */
+.highlight .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */
+.highlight .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */
+.highlight .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */
+.highlight .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */
+.highlight .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */
+.highlight .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */
+.highlight .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */
+.highlight .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */
+.highlight .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */
+.highlight .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */
+ </style>
+<style type="text/css">
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/*
+ * Mozilla scrollbar styling
+ */
+
+/* use standard opaque scrollbars for most nodes */
+[data-jp-theme-scrollbars='true'] {
+ scrollbar-color: rgb(var(--jp-scrollbar-thumb-color))
+ var(--jp-scrollbar-background-color);
+}
+
+/* for code nodes, use a transparent style of scrollbar. These selectors
+ * will match lower in the tree, and so will override the above */
+[data-jp-theme-scrollbars='true'] .CodeMirror-hscrollbar,
+[data-jp-theme-scrollbars='true'] .CodeMirror-vscrollbar {
+ scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent;
+}
+
+/* tiny scrollbar */
+
+.jp-scrollbar-tiny {
+ scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent;
+ scrollbar-width: thin;
+}
+
+/* tiny scrollbar */
+
+.jp-scrollbar-tiny::-webkit-scrollbar,
+.jp-scrollbar-tiny::-webkit-scrollbar-corner {
+ background-color: transparent;
+ height: 4px;
+ width: 4px;
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-thumb {
+ background: rgba(var(--jp-scrollbar-thumb-color), 0.5);
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-track:horizontal {
+ border-left: 0 solid transparent;
+ border-right: 0 solid transparent;
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-track:vertical {
+ border-top: 0 solid transparent;
+ border-bottom: 0 solid transparent;
+}
+
+/*
+ * Lumino
+ */
+
+.lm-ScrollBar[data-orientation='horizontal'] {
+ min-height: 16px;
+ max-height: 16px;
+ min-width: 45px;
+ border-top: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] {
+ min-width: 16px;
+ max-width: 16px;
+ min-height: 45px;
+ border-left: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar-button {
+ background-color: #f0f0f0;
+ background-position: center center;
+ min-height: 15px;
+ max-height: 15px;
+ min-width: 15px;
+ max-width: 15px;
+}
+
+.lm-ScrollBar-button:hover {
+ background-color: #dadada;
+}
+
+.lm-ScrollBar-button.lm-mod-active {
+ background-color: #cdcdcd;
+}
+
+.lm-ScrollBar-track {
+ background: #f0f0f0;
+}
+
+.lm-ScrollBar-thumb {
+ background: #cdcdcd;
+}
+
+.lm-ScrollBar-thumb:hover {
+ background: #bababa;
+}
+
+.lm-ScrollBar-thumb.lm-mod-active {
+ background: #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='horizontal'] .lm-ScrollBar-thumb {
+ height: 100%;
+ min-width: 15px;
+ border-left: 1px solid #a0a0a0;
+ border-right: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] .lm-ScrollBar-thumb {
+ width: 100%;
+ min-height: 15px;
+ border-top: 1px solid #a0a0a0;
+ border-bottom: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='horizontal']
+ .lm-ScrollBar-button[data-action='decrement'] {
+ background-image: var(--jp-icon-caret-left);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='horizontal']
+ .lm-ScrollBar-button[data-action='increment'] {
+ background-image: var(--jp-icon-caret-right);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='vertical']
+ .lm-ScrollBar-button[data-action='decrement'] {
+ background-image: var(--jp-icon-caret-up);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='vertical']
+ .lm-ScrollBar-button[data-action='increment'] {
+ background-image: var(--jp-icon-caret-down);
+ background-size: 17px;
+}
+
+/*
+ * 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-Widget {
+ box-sizing: border-box;
+ position: relative;
+ overflow: hidden;
+}
+
+.lm-Widget.lm-mod-hidden {
+ display: none !important;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.lm-AccordionPanel[data-orientation='horizontal'] > .lm-AccordionPanel-title {
+ /* Title is rotated for horizontal accordion panel using CSS */
+ display: block;
+ transform-origin: top left;
+ transform: rotate(-90deg) translate(-100%);
+}
+
+/*
+ * 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-CommandPalette {
+ display: flex;
+ flex-direction: column;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-CommandPalette-search {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-content {
+ flex: 1 1 auto;
+ margin: 0;
+ padding: 0;
+ min-height: 0;
+ overflow: auto;
+ list-style-type: none;
+}
+
+.lm-CommandPalette-header {
+ overflow: hidden;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+}
+
+.lm-CommandPalette-item {
+ display: flex;
+ flex-direction: row;
+}
+
+.lm-CommandPalette-itemIcon {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-itemContent {
+ flex: 1 1 auto;
+ overflow: hidden;
+}
+
+.lm-CommandPalette-itemShortcut {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-itemLabel {
+ overflow: hidden;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+}
+
+.lm-close-icon {
+ border: 1px solid transparent;
+ background-color: transparent;
+ position: absolute;
+ z-index: 1;
+ right: 3%;
+ top: 0;
+ bottom: 0;
+ margin: auto;
+ padding: 7px 0;
+ display: none;
+ vertical-align: middle;
+ outline: 0;
+ cursor: pointer;
+}
+.lm-close-icon:after {
+ content: 'X';
+ display: block;
+ width: 15px;
+ height: 15px;
+ text-align: center;
+ color: #000;
+ font-weight: normal;
+ font-size: 12px;
+ cursor: pointer;
+}
+
+/*
+ * 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-DockPanel {
+ z-index: 0;
+}
+
+.lm-DockPanel-widget {
+ z-index: 0;
+}
+
+.lm-DockPanel-tabBar {
+ z-index: 1;
+}
+
+.lm-DockPanel-handle {
+ z-index: 2;
+}
+
+.lm-DockPanel-handle.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-DockPanel-handle:after {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ content: '';
+}
+
+.lm-DockPanel-handle[data-orientation='horizontal'] {
+ cursor: ew-resize;
+}
+
+.lm-DockPanel-handle[data-orientation='vertical'] {
+ cursor: ns-resize;
+}
+
+.lm-DockPanel-handle[data-orientation='horizontal']:after {
+ left: 50%;
+ min-width: 8px;
+ transform: translateX(-50%);
+}
+
+.lm-DockPanel-handle[data-orientation='vertical']:after {
+ top: 50%;
+ min-height: 8px;
+ transform: translateY(-50%);
+}
+
+.lm-DockPanel-overlay {
+ z-index: 3;
+ box-sizing: border-box;
+ pointer-events: none;
+}
+
+.lm-DockPanel-overlay.lm-mod-hidden {
+ display: none !important;
+}
+
+/*
+ * 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-Menu {
+ z-index: 10000;
+ position: absolute;
+ white-space: nowrap;
+ overflow-x: hidden;
+ overflow-y: auto;
+ outline: none;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-Menu-content {
+ margin: 0;
+ padding: 0;
+ display: table;
+ list-style-type: none;
+}
+
+.lm-Menu-item {
+ display: table-row;
+}
+
+.lm-Menu-item.lm-mod-hidden,
+.lm-Menu-item.lm-mod-collapsed {
+ display: none !important;
+}
+
+.lm-Menu-itemIcon,
+.lm-Menu-itemSubmenuIcon {
+ display: table-cell;
+ text-align: center;
+}
+
+.lm-Menu-itemLabel {
+ display: table-cell;
+ text-align: left;
+}
+
+.lm-Menu-itemShortcut {
+ display: table-cell;
+ text-align: right;
+}
+
+/*
+ * 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-MenuBar {
+ outline: none;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-MenuBar-content {
+ margin: 0;
+ padding: 0;
+ display: flex;
+ flex-direction: row;
+ list-style-type: none;
+}
+
+.lm-MenuBar-item {
+ box-sizing: border-box;
+}
+
+.lm-MenuBar-itemIcon,
+.lm-MenuBar-itemLabel {
+ display: inline-block;
+}
+
+/*
+ * 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-ScrollBar {
+ display: flex;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-ScrollBar[data-orientation='horizontal'] {
+ flex-direction: row;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] {
+ flex-direction: column;
+}
+
+.lm-ScrollBar-button {
+ box-sizing: border-box;
+ flex: 0 0 auto;
+}
+
+.lm-ScrollBar-track {
+ box-sizing: border-box;
+ position: relative;
+ overflow: hidden;
+ flex: 1 1 auto;
+}
+
+.lm-ScrollBar-thumb {
+ box-sizing: border-box;
+ position: absolute;
+}
+
+/*
+ * 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-SplitPanel-child {
+ z-index: 0;
+}
+
+.lm-SplitPanel-handle {
+ z-index: 1;
+}
+
+.lm-SplitPanel-handle.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-SplitPanel-handle:after {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ content: '';
+}
+
+.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle {
+ cursor: ew-resize;
+}
+
+.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle {
+ cursor: ns-resize;
+}
+
+.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle:after {
+ left: 50%;
+ min-width: 8px;
+ transform: translateX(-50%);
+}
+
+.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle:after {
+ top: 50%;
+ min-height: 8px;
+ transform: translateY(-50%);
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabBar {
+ display: flex;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] {
+ flex-direction: row;
+ align-items: flex-end;
+}
+
+.lm-TabBar[data-orientation='vertical'] {
+ flex-direction: column;
+ align-items: flex-end;
+}
+
+.lm-TabBar-content {
+ margin: 0;
+ padding: 0;
+ display: flex;
+ flex: 1 1 auto;
+ list-style-type: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] > .lm-TabBar-content {
+ flex-direction: row;
+}
+
+.lm-TabBar[data-orientation='vertical'] > .lm-TabBar-content {
+ flex-direction: column;
+}
+
+.lm-TabBar-tab {
+ display: flex;
+ flex-direction: row;
+ box-sizing: border-box;
+ overflow: hidden;
+ touch-action: none; /* Disable native Drag/Drop */
+}
+
+.lm-TabBar-tabIcon,
+.lm-TabBar-tabCloseIcon {
+ flex: 0 0 auto;
+}
+
+.lm-TabBar-tabLabel {
+ flex: 1 1 auto;
+ overflow: hidden;
+ white-space: nowrap;
+}
+
+.lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+}
+
+.lm-TabBar-tab.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar-addButton.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab {
+ position: relative;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab {
+ left: 0;
+ transition: left 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab {
+ top: 0;
+ transition: top 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging {
+ transition: none;
+}
+
+.lm-TabBar-tabLabel .lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+ background: inherit;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabPanel-tabBar {
+ z-index: 1;
+}
+
+.lm-TabPanel-stackedPanel {
+ z-index: 0;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Collapse {
+ display: flex;
+ flex-direction: column;
+ align-items: stretch;
+}
+
+.jp-Collapse-header {
+ padding: 1px 12px;
+ background-color: var(--jp-layout-color1);
+ border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
+ color: var(--jp-ui-font-color1);
+ cursor: pointer;
+ display: flex;
+ align-items: center;
+ font-size: var(--jp-ui-font-size0);
+ font-weight: 600;
+ text-transform: uppercase;
+ user-select: none;
+}
+
+.jp-Collapser-icon {
+ height: 16px;
+}
+
+.jp-Collapse-header-collapsed .jp-Collapser-icon {
+ transform: rotate(-90deg);
+ margin: auto 0;
+}
+
+.jp-Collapser-title {
+ line-height: 25px;
+}
+
+.jp-Collapse-contents {
+ padding: 0 12px;
+ background-color: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ overflow: auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/* This file was auto-generated by ensureUiComponents() in @jupyterlab/buildutils */
+
+/**
+ * (DEPRECATED) Support for consuming icons as CSS background images
+ */
+
+/* Icons urls */
+
+:root {
+ --jp-icon-add-above: url(data:image/svg+xml;base64,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);
+ --jp-icon-add-below: url(data:image/svg+xml;base64,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);
+ --jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-bell: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug: url(data:image/svg+xml;base64,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);
+ --jp-icon-build: url(data:image/svg+xml;base64,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);
+ --jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-caret-right: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik03LjIsNS4yTDEwLjksOWwtMy44LDMuOFY1LjJINy4yeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-caret-up-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iMTUuNCwxMy4zIDkuOSw3LjcgNC40LDEzLjIgMy42LDEyLjUgOS45LDYuMyAxNi4xLDEyLjYgIi8+Cgk8L2c+Cjwvc3ZnPgo=);
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+ --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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);
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+ --jp-icon-collapse-all: url(data:image/svg+xml;base64,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);
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+ --jp-icon-copyright: url(data:image/svg+xml;base64,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);
+ --jp-icon-cut: url(data:image/svg+xml;base64,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);
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+ --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-image: url(data:image/svg+xml;base64,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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);
+ --jp-icon-json: url(data:image/svg+xml;base64,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);
+ --jp-icon-julia: url(data:image/svg+xml;base64,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);
+ --jp-icon-jupyter-favicon: url(data:image/svg+xml;base64,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);
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+ --jp-icon-jupyterlab-wordmark: 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+ --jp-icon-kernel: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzYxNjE2MSIgZD0iTTE1IDlIOXY2aDZWOXptLTIgNGgtMnYtMmgydjJ6bTgtMlY5aC0yVjdjMC0xLjEtLjktMi0yLTJoLTJWM2gtMnYyaC0yVjNIOXYySDdjLTEuMSAwLTIgLjktMiAydjJIM3YyaDJ2MkgzdjJoMnYyYzAgMS4xLjkgMiAyIDJoMnYyaDJ2LTJoMnYyaDJ2LTJoMmMxLjEgMCAyLS45IDItMnYtMmgydi0yaC0ydi0yaDJ6bS00IDZIN1Y3aDEwdjEweiIvPgo8L3N2Zz4K);
+ --jp-icon-keyboard: url(data:image/svg+xml;base64,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);
+ --jp-icon-launch: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMzIgMzIiIHdpZHRoPSIzMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yNiwyOEg2YTIuMDAyNywyLjAwMjcsMCwwLDEtMi0yVjZBMi4wMDI3LDIuMDAyNywwLDAsMSw2LDRIMTZWNkg2VjI2SDI2VjE2aDJWMjZBMi4wMDI3LDIuMDAyNywwLDAsMSwyNiwyOFoiLz4KICAgIDxwb2x5Z29uIHBvaW50cz0iMjAgMiAyMCA0IDI2LjU4NiA0IDE4IDEyLjU4NiAxOS40MTQgMTQgMjggNS40MTQgMjggMTIgMzAgMTIgMzAgMiAyMCAyIi8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-launcher: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkgMTlINVY1aDdWM0g1YTIgMiAwIDAwLTIgMnYxNGEyIDIgMCAwMDIgMmgxNGMxLjEgMCAyLS45IDItMnYtN2gtMnY3ek0xNCAzdjJoMy41OWwtOS44MyA5LjgzIDEuNDEgMS40MUwxOSA2LjQxVjEwaDJWM2gtN3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-line-form: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGZpbGw9IndoaXRlIiBkPSJNNS44OCA0LjEyTDEzLjc2IDEybC03Ljg4IDcuODhMOCAyMmwxMC0xMEw4IDJ6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-link: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTMuOSAxMmMwLTEuNzEgMS4zOS0zLjEgMy4xLTMuMWg0VjdIN2MtMi43NiAwLTUgMi4yNC01IDVzMi4yNCA1IDUgNWg0di0xLjlIN2MtMS43MSAwLTMuMS0xLjM5LTMuMS0zLjF6TTggMTNoOHYtMkg4djJ6bTktNmgtNHYxLjloNGMxLjcxIDAgMy4xIDEuMzkgMy4xIDMuMXMtMS4zOSAzLjEtMy4xIDMuMWgtNFYxN2g0YzIuNzYgMCA1LTIuMjQgNS01cy0yLjI0LTUtNS01eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xOSA1djE0SDVWNWgxNG0xLjEtMkgzLjljLS41IDAtLjkuNC0uOS45djE2LjJjMCAuNC40LjkuOS45aDE2LjJjLjQgMCAuOS0uNS45LS45VjMuOWMwLS41LS41LS45LS45LS45ek0xMSA3aDZ2MmgtNlY3em0wIDRoNnYyaC02di0yem0wIDRoNnYyaC02ek03IDdoMnYySDd6bTAgNGgydjJIN3ptMCA0aDJ2Mkg3eiIvPgo8L3N2Zz4K);
+ --jp-icon-markdown: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-down: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-up: url(data:image/svg+xml;base64,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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,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);
+ --jp-icon-notebook: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtbm90ZWJvb2staWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiNFRjZDMDAiPgogICAgPHBhdGggZD0iTTE4LjcgMy4zdjE1LjRIMy4zVjMuM2gxNS40bTEuNS0xLjVIMS44djE4LjNoMTguM2wuMS0xOC4zeiIvPgogICAgPHBhdGggZD0iTTE2LjUgMTYuNWwtNS40LTQuMy01LjYgNC4zdi0xMWgxMXoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-numbering: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTQgMTlINlYxOS41SDVWMjAuNUg2VjIxSDRWMjJIN1YxOEg0VjE5Wk01IDEwSDZWNkg0VjdINVYxMFpNNCAxM0g1LjhMNCAxNS4xVjE2SDdWMTVINS4yTDcgMTIuOVYxMkg0VjEzWk05IDdWOUgyM1Y3SDlaTTkgMjFIMjNWMTlIOVYyMVpNOSAxNUgyM1YxM0g5VjE1WiIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-offline-bolt: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDIuMDJjLTUuNTEgMC05Ljk4IDQuNDctOS45OCA5Ljk4czQuNDcgOS45OCA5Ljk4IDkuOTggOS45OC00LjQ3IDkuOTgtOS45OFMxNy41MSAyLjAyIDEyIDIuMDJ6TTExLjQ4IDIwdi02LjI2SDhMMTMgNHY2LjI2aDMuMzVMMTEuNDggMjB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-palette: url(data:image/svg+xml;base64,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);
+ --jp-icon-paste: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE5IDJoLTQuMThDMTQuNC44NCAxMy4zIDAgMTIgMGMtMS4zIDAtMi40Ljg0LTIuODIgMkg1Yy0xLjEgMC0yIC45LTIgMnYxNmMwIDEuMS45IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjRjMC0xLjEtLjktMi0yLTJ6bS03IDBjLjU1IDAgMSAuNDUgMSAxcy0uNDUgMS0xIDEtMS0uNDUtMS0xIC40NS0xIDEtMXptNyAxOEg1VjRoMnYzaDEwVjRoMnYxNnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-pdf: url(data:image/svg+xml;base64,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);
+ --jp-icon-python: url(data:image/svg+xml;base64,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);
+ --jp-icon-r-kernel: url(data:image/svg+xml;base64,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);
+ --jp-icon-react: url(data:image/svg+xml;base64,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);
+ --jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-regex: url(data:image/svg+xml;base64,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);
+ --jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-running: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDUxMiA1MTIiPgogIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICA8cGF0aCBkPSJNMjU2IDhDMTE5IDggOCAxMTkgOCAyNTZzMTExIDI0OCAyNDggMjQ4IDI0OC0xMTEgMjQ4LTI0OFMzOTMgOCAyNTYgOHptOTYgMzI4YzAgOC44LTcuMiAxNi0xNiAxNkgxNzZjLTguOCAwLTE2LTcuMi0xNi0xNlYxNzZjMC04LjggNy4yLTE2IDE2LTE2aDE2MGM4LjggMCAxNiA3LjIgMTYgMTZ2MTYweiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-search: url(data:image/svg+xml;base64,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);
+ --jp-icon-settings: url(data:image/svg+xml;base64,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);
+ --jp-icon-share: url(data:image/svg+xml;base64,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);
+ --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-table-rows: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMSw4SDNWNGgxOFY4eiBNMjEsMTBIM3Y0aDE4VjEweiBNMjEsMTZIM3Y0aDE4VjE2eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-tag: url(data:image/svg+xml;base64,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);
+ --jp-icon-terminal: url(data:image/svg+xml;base64,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);
+ --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-toc: url(data:image/svg+xml;base64,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);
+ --jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-trusted: url(data:image/svg+xml;base64,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);
+ --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-users: url(data:image/svg+xml;base64,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);
+ --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-word: url(data:image/svg+xml;base64,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);
+ --jp-icon-yaml: url(data:image/svg+xml;base64,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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;
+}
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+.jp-RenderedText pre .ansi-yellow-fg {
+ color: #ddb62b;
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+.jp-RenderedText pre .ansi-blue-fg {
+ color: #208ffb;
+}
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+ color: #d160c4;
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+.jp-RenderedText pre .ansi-cyan-fg {
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+
+.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;
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+ * The following are the main layout colors use in JupyterLab. In a light
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+ * The following are the inverse layout colors use in JupyterLab. In a light
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+ --jp-inverse-layout-color4: var(--md-grey-600);
+
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+
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+
+ /*
+ 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;
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+
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+
+ /* Sidebar-related styles */
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+ --jp-sidebar-min-width: 250px;
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+ --jp-search-selected-match-color: black;
+ --jp-search-unselected-match-background-color: var(
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+ );
+ --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);
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+ --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);
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+ --jp-console-icon-color: white;
+ --jp-terminal-icon-background-color: var(--md-grey-800);
+ --jp-terminal-icon-color: var(--md-grey-200);
+ --jp-text-editor-icon-color: var(--md-grey-700);
+ --jp-inspector-icon-color: var(--md-grey-700);
+ --jp-switch-color: var(--md-grey-400);
+ --jp-switch-true-position-color: var(--md-orange-900);
+}
+</style>
+<style type="text/css">
+/* Force rendering true colors when outputing to pdf */
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+ -webkit-print-color-adjust: exact;
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+/* Input area styling */
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+<!-- End of mermaid configuration --></head>
+<body class="jp-Notebook" data-jp-theme-light="true" data-jp-theme-name="JupyterLab Light">
+<main>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=24fdc979">
+<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="GA-1.8:-Multivariate-Distributions">GA 1.8: Multivariate Distributions<a class="anchor-link" href="#GA-1.8:-Multivariate-Distributions">¶</a></h1><h1 style="position: absolute; display: flex; flex-grow: 0; flex-shrink: 0; flex-direction: row-reverse; top: 60px;right: 30px; margin: 0; border: 0">
+<style>
+ .markdown {width:100%; position: relative}
+ article { position: relative }
+ </style>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/tu-logo/TU_P1_full-color.png" style="width:100px; height: auto; margin: 0"/>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/mude-logo/MUDE_Logo-small.png" style="width:100px; height: auto; margin: 0"/>
+</h1>
+<h2 style="height: 10px">
+</h2>
+<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 1.8, Friday Oct 25, 2024.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8b5d241">
+<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="Objective">Objective<a class="anchor-link" href="#Objective">¶</a></h2><p>This notebook is structured in an identical way to WS 1.8. In particular, we have 3 main tasks:</p>
+<ol>
+<li>Build a multivariate distribution $F_{X_1,X_2}(x_1,x_2)$</li>
+<li>Use the distribution by comparing empirical probabilities to values computed with $F_{X_1,X_2}(x_1,x_2)$ for the AND, OR and function of random variable cases</li>
+<li>Validate the distribution using the distribution of the function of random variables, $Z(X_1,X_2)$.</li>
+</ol>
+<h3 id="Multivariate-Distribution-(Task-1)">Multivariate Distribution (Task 1)<a class="anchor-link" href="#Multivariate-Distribution-(Task-1)">¶</a></h3><p>As with WS 1.8, we will build a multivariate distribution, but this time we will include non-Gaussian marginal distributions using a Gaussian Copula:</p>
+$$
+F_{X_1,X_2}(x_1,x_2) = C[F_{X_1}(x_1)F_{X_2}(x_2)]
+$$<p>In this case, the Copula requires one parameter: the Pearson correlation coefficient, $\rho$.</p>
+<p>This distribution has been implemented in the class <code>Bivariate</code> within <code>helper.py</code>. You can define an instance of the class using:</p>
+<pre><code>my_bivariate_dist = Bivariate(marginal_1, marginal_2, rho)
+</code></pre>
+<p>where the arguments are the marginal distributions for your random variables and are instances of the class <code>rv_continuous</code> from <code>scipy.stats</code>. In fact, the <code>Bivariate</code> class has been created with similar methods to <code>multivariate_normal</code>; in other words, you can use the methods <code>pdf</code>, <code>cdf</code> and <code>rvs</code> in the same way as <code>multivariate_normal</code> in WS 1.8.</p>
+<p>Note that the function <code>plot_contours</code> will also work, but due to the way <code>Bivariate</code> is implemented, it is slow to make the plots, so you may want to use small sample sizes.</p>
+<h4 id="Python-Package:-pyvinecopulib">Python Package: <code>pyvinecopulib</code><a class="anchor-link" href="#Python-Package:-pyvinecopulib">¶</a></h4><p>A package <code>pyvinecopulib</code> is required for the Bivariate class. It is only available on PyPI, so it has to be installed using <code>pip</code>. Fortunately you should already have done this as part of PA 1.8, so all you need to do is remember to use your environment <code>mude-week-8</code>.</p>
+<h3 id="Probability-Calculations-for-3-Cases-(Task-2)">Probability Calculations for 3 Cases (Task 2)<a class="anchor-link" href="#Probability-Calculations-for-3-Cases-(Task-2)">¶</a></h3><p>For each data set, we will use the 90th percentile of each random variable to evaluate the AND, OR and function of random variable cases. In other words:</p>
+$$
+x_{1,90} = F_{X_1}^{-1}(0.90) \;\;\textrm{and}\;\; x_{2,90} = F_{X_2}^{-1}(0.90)
+$$<p>Since there were three data sets to choose from last week, each with different functions and variables, this notebook uses the notation $Z(X_1,X_2)$ to represent the function of random variables for your particular case. As we did in WS 1.8, we would like to evaluate $Z$ for a threshold condition (in WS 1.8 it was $Z<0$ for the Thingamajig). For this assignment, consider the threshold case to be all combinations of $x_1$ and $x_2$ such that:</p>
+$$
+Z>Z(x_{1,90},z_{2,90})
+$$<h3 id="Propagating-Uncertainty-(Task-3)">Propagating Uncertainty (Task 3)<a class="anchor-link" href="#Propagating-Uncertainty-(Task-3)">¶</a></h3><p>This proceeds as in WS 1.8 as well, where you will use the samples generated in Task 2 to evaluate the distribution of $Z$ and compare to the empirical data set.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=55bd0e2d">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below allows you to edit the contents of helper and incorporate the changes in the notebook without restarting the kernel.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=91463787">
+<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="o">%</span><span class="k">load_ext</span> autoreload
+<span class="o">%</span><span class="k">autoreload</span> 2
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=7eeb37e0-aca0-4759-866f-f5ad09ea8d0b">
+<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="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
+
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">plot_contour</span>
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">Bivariate</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=d0113213">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below is only for the solution.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=b4a22fde">
+<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">data_set</span> <span class="o">=</span> <span class="s1">'dataset_hu'</span>
+<span class="c1"># data_set = 'dataset_HT'</span>
+<span class="c1"># data_set = 'dataset_traffic'</span>
+<span class="n">N_factor_MCS</span> <span class="o">=</span> <span class="mi">100</span>
+<span class="n">make_figs</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="n">save_figs</span> <span class="o">=</span> <span class="kc">False</span>
+
+<span class="n">bivariate_lim</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span>
+
+<span class="n">plot_x2</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">z90</span><span class="p">:</span> <span class="n">z90</span><span class="o">/</span><span class="n">x1</span>
+<span class="n">Z</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">:</span> <span class="n">x1</span><span class="o">*</span><span class="n">x2</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4d11b3b2-5d82-4e67-a151-0e7025ab175a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-1:-Creating-a-Bivariate-Distribution">Part 1: Creating a Bivariate Distribution<a class="anchor-link" href="#Part-1:-Creating-a-Bivariate-Distribution">¶</a></h2><p>We need to represent our two dependent random variables with marginal distributions and use the correlation coefficient to model dependence, as found previously in GA 1.7.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=fbd5f10c-2c28-4dde-b5c4-e2781058997f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.1:</b>
+<p>Import your data set from last week and define the marginal distributions as frozen scipy stats objects.</p>
+<p><em>The cell below illustrates how to create a frozen Gaussian distribution</em></p>
+</p>
+
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f00a23b6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+Remember there is a <a href="https://mude.citg.tudelft.nl/2024/book/probability/python.html" target="_blank">new page on scipy stats in the book</a> in case you need a reference.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=2b3477a8-002c-42a8-bd30-6c24890156c2">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+<span class="c1"># parameters1 = st.norm.fit_loc_scale(data_x1)</span>
+<span class="c1"># dist_x1 = st.norm(*parameters1)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3aad6608-743f-4f49-bcab-440ab5b3d093">
+<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="n">data_path</span> <span class="o">=</span> <span class="s2">"data/dataset_hu.csv"</span>
+<span class="c1"># data_path = "data/dataset_HT.csv"</span>
+<span class="c1"># data_path = "data/dataset_traffic.csv"</span>
+
+<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">genfromtxt</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span>
+ <span class="n">delimiter</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span>
+ <span class="n">unpack</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">skip_header</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+
+<span class="n">data_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">,:])</span>
+<span class="n">data_x2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">,:])</span>
+
+<span class="n">parameters1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="n">dist_x1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="o">*</span><span class="n">parameters1</span><span class="p">)</span>
+
+<span class="n">parameters2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x2</span><span class="p">)</span>
+<span class="n">dist_x2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="p">(</span><span class="o">*</span><span class="n">parameters2</span><span class="p">)</span>
+
+<span class="n">N</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data: </span><span class="si">{</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'mean and std of X1 and X2: '</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x1</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x2</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x2</span><span class="o">.</span><span class="n">std</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>shape of data: (2, 68)
+shape of data_x1: (68,)
+min/max of data_x1: 0.461226714, 2.145350569
+shape of data_x2: (68,)
+min/max of data_x2: 1.053685265, 2.462845221
+
+
+mean and std of X1 and X2:
+1.2111498297794114 0.3575979381664016
+1.4639994874705884 0.3015882090612745
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=9b6d08ec-5e23-4efb-a9fc-d96776812429">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.2:</b>
+Compute the covariance and correlation coefficient between the two random variables. Print the results.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=c8a5e3ec-d87d-4d2d-b51d-85351bdd586d">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5c13ea7e-65b8-46ee-804e-f62fb4e68afd">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Covariance of two random variables X1 and X2 (numpy arrays).</span>
+<span class="sd"> '''</span>
+ <span class="n">mean_x1</span> <span class="o">=</span> <span class="n">X1</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">mean_x2</span> <span class="o">=</span> <span class="n">X2</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">diff_x1</span> <span class="o">=</span> <span class="n">X1</span> <span class="o">-</span> <span class="n">mean_x1</span>
+ <span class="n">diff_x2</span> <span class="o">=</span> <span class="n">X2</span> <span class="o">-</span> <span class="n">mean_x2</span>
+ <span class="n">product</span> <span class="o">=</span> <span class="n">diff_x1</span> <span class="o">*</span> <span class="n">diff_x2</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">product</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="k">return</span> <span class="n">covariance</span>
+
+<span class="k">def</span> <span class="nf">pearson_correlation</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">)</span>
+ <span class="n">correl_coeff</span> <span class="o">=</span> <span class="n">covariance</span><span class="o">/</span><span class="p">(</span><span class="n">X1</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="o">*</span><span class="n">X2</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+ <span class="k">return</span> <span class="n">correl_coeff</span>
+
+<span class="n">cov_x12</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The covariance of X1 and X2 is </span><span class="si">{</span><span class="n">cov_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="n">rho_x12</span> <span class="o">=</span> <span class="n">pearson_correlation</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The correlation coefficient of X1 and X2 is </span><span class="si">{</span><span class="n">rho_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>The covariance of X1 and X2 is 0.04166
+The correlation coefficient of X1 and X2 is 0.38625
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=23e4d105-dc2f-4aa8-902f-1872d517e547">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.3:</b>
+Build the bivariate distribution by instantiating the <code>Bivariate</code> class in <code>helper.py</code> (and described above). To validate the result, create a plot that shows contours of the joint PDF, compared with the data (see note below). Include the data in your plot and write a few comments on the quality of the fit for use in your Report.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f9ee9c39-6e6a-4257-9746-fdf118eef8aa">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Use the helper function <code>plot_contour</code> in <code>helper.py</code>; it works exactle the same as in WS 1.8.</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=896fd1c2">
+<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="c1"># plot_contour? # uncomment and run to read docstring</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5cd6a070">
+<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="c1"># bivar_dist = Bivariate(YOUR_CODE_HERE, YOUR_CODE_HERE, YOUR_CODE_HERE)</span>
+
+<span class="c1"># plot_contour(YOUR_CODE_HERE, YOUR_CODE_HERE, data=data)</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">bivar_dist</span> <span class="o">=</span> <span class="n">Bivariate</span><span class="p">(</span><span class="n">dist_x1</span><span class="p">,</span> <span class="n">dist_x2</span><span class="p">,</span> <span class="n">rho_x12</span><span class="p">)</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</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[9]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='$X_1$', ylabel='$X_2$'>)</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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+</div>
+</div>
+</div>
+</div>
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+<h2 id="Part-2:-Using-the-Bivariate-Distribution">Part 2: Using the Bivariate Distribution<a class="anchor-link" href="#Part-2:-Using-the-Bivariate-Distribution">¶</a></h2><p>Now that we have the distribution, we will use it compute probabilities related to the three cases, presented above, as follows:</p>
+<ol>
+<li>$P[X_1>x_{1,90} \;\cup\; X_2>x_{2,90}$</li>
+<li>$P[X_1>x_{1,90} \;\cap\; X_2>x_{2,90}]$</li>
+<li>$P[X_1,X_2:\; Z>Z(x_{1,90},x_{2,90})]$</li>
+</ol>
+<p>Note that the "critical" Z value in this case is that where your Z function is evaluated at the 90th percentile values of each random variable.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f544418c">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 2:</b>
+<p>For each of the three cases, do the following:</p>
+<ul>
+<li>Compute the requested probability using the empirical distribution.</li>
+<li>Compute the requested probability using the bivariate distribution.</li>
+<li>Create a bivariate plot that includes PDF contours <em>and</em> the region of interest.</li>
+<li>Repeat the calculations for additional cases of correlation coefficient (for example change $\rho$ to: +0.9, 0.0, then -0.9) to see how the answer changes (you can simply regenerate the plot, you don't need to make multiple versions). <em>You can save this sub-task for later if you are running out of time. It is more important to get through Task 3 during the in-class session.</em></li>
+<li>Write two or three sentences that summarize the results and explains the quantitative impact of correlation coefficient. Make a particular note about whether or not one case may or be affected more or less than the others.</li>
+</ul>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=bdab1a35-4e2f-42a2-804c-17f7f0917b6a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note that the optional arguments in the helper function <code>plot_contour</code> will be useful here.
+<p>Here is an example code that shows you what it can do (the values are meaningless)</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=adb079f6">
+<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">region_example</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="mi">0</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">18</span><span class="p">,</span> <span class="mi">19</span><span class="p">,</span> <span class="mi">12</span><span class="p">]])</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="mi">23</span><span class="p">,</span> <span class="mi">13</span><span class="p">],</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_example</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8974e1b">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.1 and 2.2:</b> create cells below to carry out the OR and AND calculations.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=0999c23c">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a07bc27f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.3:</b> create cells below to carry out the Case 3 calculations.</p>
+<p>Note that in this case you need to make the plot to visualize the region over which we want to integrate. We need to define the boundary of the region of interest by solving the equation $Z(X_1,X_2)$ for $X_2$ when $Z=Z(x_{1,90},x_{2,90})$.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=0bea4cff">
+<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>The equation can be defined as follows:</p>
+$$
+\textrm{WRITE THE EQUATION HERE}
+$$<p>which is then defined in Python and included in the <code>plot_contours</code> function as an array for the keyword argument <code>region</code>.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=cf2e5192">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=da352934-c7b3-4dd2-a913-271f9ad38d26">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Start of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=096a378a-2256-489e-a99c-9458924b6e1a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: order of the tasks in this solution is not important.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=364b7689-2034-437f-b7cf-d59042ea93a8">
+<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="Case-1-and-2">Case 1 and 2<a class="anchor-link" href="#Case-1-and-2">¶</a></h3><p>First we will compute the probabilities from the distribution.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=74874fef-e398-45b6-8858-bebd1017e095">
+<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 [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="n">x90_1</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+<span class="n">x90_2</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+
+<span class="n">region_or</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">]]])</span>
+<span class="n">region_and</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">]])</span>
+
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">cdf</span><span class="p">([</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_2</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="c1"># Case 1 and 2 empirical probabilities</span>
+<span class="n">N</span> <span class="o">=</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">size</span>
+
+<span class="n">number_of_points_lower_left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">((</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">&</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">))</span>
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">number_of_points_lower_left</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 empirical probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_or</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_2.svg'</span><span class="p">))</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_and</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_3.svg'</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>Case 1 and 2 probabilities
+ lower left: 0.82592
+ left side: 0.90000
+ bottom side: 0.90000
+=============================
+Case 1, Union: 0.17408
+Case 2, Intersection: 0.02592
+
+
+Case 1 and 2 empirical probabilities
+ lower left: 0.81159
+ left side: 0.85507
+ bottom side: 0.88406
+=============================
+Case 1, Union: 0.18841
+Case 2, Intersection: 0.07246
+
+
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ee7d5b8c-1cee-4799-bd44-d01ae4266fc3">
+<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="Case-3">Case 3<a class="anchor-link" href="#Case-3">¶</a></h3><p>The Z function is defined at the top of this notebook in a solution code cell.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=cfe4b8df-e9e4-4086-a265-a67100f28fe0">
+<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="n">z_90</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">)</span>
+
+<span class="n">plot_Z_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">bivariate_lim</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">plot_Z_x2</span> <span class="o">=</span> <span class="n">plot_x2</span><span class="p">(</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">z_90</span><span class="p">)</span>
+<span class="n">region_Z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">plot_Z_x2</span><span class="p">])</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_Z</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_4.svg'</span><span class="p">))</span>
+
+<span class="n">sample_N</span> <span class="o">=</span> <span class="n">N_factor_MCS</span><span class="o">*</span><span class="n">N</span>
+<span class="n">sample</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">rvs</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">sample_N</span><span class="p">)</span>
+<span class="n">sample_X1</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">sample_X2</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span>
+
+<span class="n">sample_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">sample_X1</span><span class="p">,</span> <span class="n">sample_X2</span><span class="p">)</span>
+<span class="n">Z_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90</span> <span class="o">=</span> <span class="n">Z_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">sample_N</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="s1">'Z case MCS'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">sample_N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of samples of Z < 0 is: </span><span class="si">{</span><span class="n">Z_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The MCS probability is </span><span class="si">{</span><span class="n">p_Z90</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">sample_N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="n">empirical_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="n">Z_data_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">empirical_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90_data</span> <span class="o">=</span> <span class="n">Z_data_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">N</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="s1">'Z case empirical'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of data where Z < 0 is: </span><span class="si">{</span><span class="n">Z_data_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The empirical probability is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90_data</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</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="application/vnd.jupyter.stderr" tabindex="0">
+<pre>C:\Users\rlanzafame\AppData\Local\Temp\ipykernel_19956\2322207425.py:10: RuntimeWarning: divide by zero encountered in divide
+ plot_x2 = lambda x1, z90: z90/x1
+</pre>
+</div>
+</div>
+<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>Z case MCS
+N = 6800
+The number of samples of Z < 0 is: 425
+This is 6.249% of all samples.
+The MCS probability is 0.062.
+The c.o.v. is of p is 0.049.
+
+
+Z case empirical
+N = 68
+The number of data where Z < 0 is: 6
+This is 8.696% of all samples.
+The empirical probability is 0.087.
+The c.o.v. is of p is 0.408.
+
+
+</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=b95860c6-8cbb-47e1-89ab-4d4d56a6f1be">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: the bivariate figures are an important concept for the exam, so if using the code is too difficult for you to use when studying on your own, try sketching it on paper.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=839cec7d-2167-4572-9585-b1318ca41803">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>End of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2421b1e1-8adb-4dee-8095-5a54b02e6d44">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">Part 3: Validate Bivariate with Monte Carlo Simulation<a class="anchor-link" href="#Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">¶</a></h2><p>Now that we have seen how the different cases give different values of probability, let's focus on the function of random variables. This is a more interesting case because we can use the samples of $Z$ to approximate the distribution $f_Z(z)$ and use the empirical distribution of $Z$ to help validate the bivariate model.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=6d2196f5-c480-4810-81e4-d692819d648f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p>$\textbf{Task 3:}$</p>
+<p>Do the following:</p>
+<ul>
+<li>Use Monte Carlo Simulation to create a sample of $Z(X_1,X_2)$ and compare this distribution to the empirical distribution.</li>
+<li>Write 2-3 sentences assessing the quality of the distribution from MCS, and whether the bivariate distribution is acceptable for this problem. Use qualitative and quantitative measures from last week to support your arguments.</li>
+</ul>
+</p>
+<p>
+<em>Note: it would be interesting to fit a parametric distribution to the MCS sample, but it is not required for this assignment.</em>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=99ee3a19">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.1:</b> Plot histograms of $Z$ based on the Monte Carlo samples, and based on the data. Note that you probably already computed the samples in Part 2.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=446b73fe-5277-48ff-8187-e4eabcd21354">
+<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 [17]:</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"># plot_values = np.linspace(sample_Z.min(), sample_Z.max(), 30)</span>
+<span class="c1"># fig, ax = plt.subplots(1)</span>
+<span class="c1"># ax.hist([YOUR_CODE_HERE, YOUR_CODE_HERE],</span>
+<span class="c1"># bins=plot_values,</span>
+<span class="c1"># density=True,</span>
+<span class="c1"># edgecolor='black');</span>
+<span class="c1"># ax.legend(['Data', 'MCS Sample'])</span>
+<span class="c1"># ax.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># ax.set_xlabel('Empirical Density [--]')</span>
+<span class="c1"># ax.set_title('Comparison of Distributions of $Z$');</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">plot_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">sample_Z</span><span class="o">.</span><span class="n">max</span><span class="p">(),</span> <span class="mi">30</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="mi">1</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">([</span><span class="n">empirical_Z</span><span class="p">,</span> <span class="n">sample_Z</span><span class="p">],</span>
+ <span class="n">bins</span><span class="o">=</span><span class="n">plot_values</span><span class="p">,</span>
+ <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">edgecolor</span><span class="o">=</span><span class="s1">'black'</span><span class="p">);</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s1">'Data'</span><span class="p">,</span> <span class="s1">'MCS Sample'</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">'$Z(X_1,X_2)$'</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">'Empirical Density [--]'</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="s1">'Comparison of Distributions of $Z$'</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ebc6a6a6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.2:</b> Define a function to compute the ecdf.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=5804f940-23e1-480b-adf1-17c3f41fb5c1">
+<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 [19]:</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"># def ecdf(var):</span>
+<span class="c1"># x = YOUR_CODE_HERE # sort the values from small to large</span>
+<span class="c1"># n = YOUR_CODE_HERE # determine the number of datapoints</span>
+<span class="c1"># y = YOUR_CODE_HERE</span>
+<span class="c1"># return [y, x]</span>
+
+<span class="c1"># SOLUTION:</span>
+<span class="k">def</span> <span class="nf">ecdf</span><span class="p">(</span><span class="n">var</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">sort</span><span class="p">(</span><span class="n">var</span><span class="p">)</span> <span class="c1"># sort the values from small to large</span>
+ <span class="n">n</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span> <span class="c1"># determine the number of datapoints</span>
+ <span class="n">y</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">n</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+ <span class="k">return</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2efb02a2">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.3:</b> Create a semi-log plot of the non-exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3c0da378-d6b8-4bdf-9a24-ac7f38862b4d">
+<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 [20]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('CDF, $\mathrm{P}[Z < z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands lower tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'CDF, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z < z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands lower tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=eeae26ba">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.4:</b> Create a semi-log plot of the exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=a432095b-9b71-4b1d-871a-21c0097c06e9">
+<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 [21]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('Exceedance Probability, $\mathrm{P}[Z > z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands upper tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'Exceedance Probability, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z > z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands upper tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"><p>In case you are wondering, the data for this exercise was computed with a Clayton Copula. A Copula is a useful way of modelling non-linear dependence. If you would like to learn more about this, you should consider the 2nd year cross-over module CEGM2005 Probabilistic Modelling of real-world phenomena through ObseRvations and Elicitation (MORE).</p></div>
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+<p><strong>End of notebook.</strong></p>
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+
+/* for code nodes, use a transparent style of scrollbar. These selectors
+ * will match lower in the tree, and so will override the above */
+[data-jp-theme-scrollbars='true'] .CodeMirror-hscrollbar,
+[data-jp-theme-scrollbars='true'] .CodeMirror-vscrollbar {
+ scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent;
+}
+
+/* tiny scrollbar */
+
+.jp-scrollbar-tiny {
+ scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent;
+ scrollbar-width: thin;
+}
+
+/* tiny scrollbar */
+
+.jp-scrollbar-tiny::-webkit-scrollbar,
+.jp-scrollbar-tiny::-webkit-scrollbar-corner {
+ background-color: transparent;
+ height: 4px;
+ width: 4px;
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-thumb {
+ background: rgba(var(--jp-scrollbar-thumb-color), 0.5);
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-track:horizontal {
+ border-left: 0 solid transparent;
+ border-right: 0 solid transparent;
+}
+
+.jp-scrollbar-tiny::-webkit-scrollbar-track:vertical {
+ border-top: 0 solid transparent;
+ border-bottom: 0 solid transparent;
+}
+
+/*
+ * Lumino
+ */
+
+.lm-ScrollBar[data-orientation='horizontal'] {
+ min-height: 16px;
+ max-height: 16px;
+ min-width: 45px;
+ border-top: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] {
+ min-width: 16px;
+ max-width: 16px;
+ min-height: 45px;
+ border-left: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar-button {
+ background-color: #f0f0f0;
+ background-position: center center;
+ min-height: 15px;
+ max-height: 15px;
+ min-width: 15px;
+ max-width: 15px;
+}
+
+.lm-ScrollBar-button:hover {
+ background-color: #dadada;
+}
+
+.lm-ScrollBar-button.lm-mod-active {
+ background-color: #cdcdcd;
+}
+
+.lm-ScrollBar-track {
+ background: #f0f0f0;
+}
+
+.lm-ScrollBar-thumb {
+ background: #cdcdcd;
+}
+
+.lm-ScrollBar-thumb:hover {
+ background: #bababa;
+}
+
+.lm-ScrollBar-thumb.lm-mod-active {
+ background: #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='horizontal'] .lm-ScrollBar-thumb {
+ height: 100%;
+ min-width: 15px;
+ border-left: 1px solid #a0a0a0;
+ border-right: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] .lm-ScrollBar-thumb {
+ width: 100%;
+ min-height: 15px;
+ border-top: 1px solid #a0a0a0;
+ border-bottom: 1px solid #a0a0a0;
+}
+
+.lm-ScrollBar[data-orientation='horizontal']
+ .lm-ScrollBar-button[data-action='decrement'] {
+ background-image: var(--jp-icon-caret-left);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='horizontal']
+ .lm-ScrollBar-button[data-action='increment'] {
+ background-image: var(--jp-icon-caret-right);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='vertical']
+ .lm-ScrollBar-button[data-action='decrement'] {
+ background-image: var(--jp-icon-caret-up);
+ background-size: 17px;
+}
+
+.lm-ScrollBar[data-orientation='vertical']
+ .lm-ScrollBar-button[data-action='increment'] {
+ background-image: var(--jp-icon-caret-down);
+ background-size: 17px;
+}
+
+/*
+ * 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-Widget {
+ box-sizing: border-box;
+ position: relative;
+ overflow: hidden;
+}
+
+.lm-Widget.lm-mod-hidden {
+ display: none !important;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+.lm-AccordionPanel[data-orientation='horizontal'] > .lm-AccordionPanel-title {
+ /* Title is rotated for horizontal accordion panel using CSS */
+ display: block;
+ transform-origin: top left;
+ transform: rotate(-90deg) translate(-100%);
+}
+
+/*
+ * 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-CommandPalette {
+ display: flex;
+ flex-direction: column;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-CommandPalette-search {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-content {
+ flex: 1 1 auto;
+ margin: 0;
+ padding: 0;
+ min-height: 0;
+ overflow: auto;
+ list-style-type: none;
+}
+
+.lm-CommandPalette-header {
+ overflow: hidden;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+}
+
+.lm-CommandPalette-item {
+ display: flex;
+ flex-direction: row;
+}
+
+.lm-CommandPalette-itemIcon {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-itemContent {
+ flex: 1 1 auto;
+ overflow: hidden;
+}
+
+.lm-CommandPalette-itemShortcut {
+ flex: 0 0 auto;
+}
+
+.lm-CommandPalette-itemLabel {
+ overflow: hidden;
+ white-space: nowrap;
+ text-overflow: ellipsis;
+}
+
+.lm-close-icon {
+ border: 1px solid transparent;
+ background-color: transparent;
+ position: absolute;
+ z-index: 1;
+ right: 3%;
+ top: 0;
+ bottom: 0;
+ margin: auto;
+ padding: 7px 0;
+ display: none;
+ vertical-align: middle;
+ outline: 0;
+ cursor: pointer;
+}
+.lm-close-icon:after {
+ content: 'X';
+ display: block;
+ width: 15px;
+ height: 15px;
+ text-align: center;
+ color: #000;
+ font-weight: normal;
+ font-size: 12px;
+ cursor: pointer;
+}
+
+/*
+ * 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-DockPanel {
+ z-index: 0;
+}
+
+.lm-DockPanel-widget {
+ z-index: 0;
+}
+
+.lm-DockPanel-tabBar {
+ z-index: 1;
+}
+
+.lm-DockPanel-handle {
+ z-index: 2;
+}
+
+.lm-DockPanel-handle.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-DockPanel-handle:after {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ content: '';
+}
+
+.lm-DockPanel-handle[data-orientation='horizontal'] {
+ cursor: ew-resize;
+}
+
+.lm-DockPanel-handle[data-orientation='vertical'] {
+ cursor: ns-resize;
+}
+
+.lm-DockPanel-handle[data-orientation='horizontal']:after {
+ left: 50%;
+ min-width: 8px;
+ transform: translateX(-50%);
+}
+
+.lm-DockPanel-handle[data-orientation='vertical']:after {
+ top: 50%;
+ min-height: 8px;
+ transform: translateY(-50%);
+}
+
+.lm-DockPanel-overlay {
+ z-index: 3;
+ box-sizing: border-box;
+ pointer-events: none;
+}
+
+.lm-DockPanel-overlay.lm-mod-hidden {
+ display: none !important;
+}
+
+/*
+ * 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-Menu {
+ z-index: 10000;
+ position: absolute;
+ white-space: nowrap;
+ overflow-x: hidden;
+ overflow-y: auto;
+ outline: none;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-Menu-content {
+ margin: 0;
+ padding: 0;
+ display: table;
+ list-style-type: none;
+}
+
+.lm-Menu-item {
+ display: table-row;
+}
+
+.lm-Menu-item.lm-mod-hidden,
+.lm-Menu-item.lm-mod-collapsed {
+ display: none !important;
+}
+
+.lm-Menu-itemIcon,
+.lm-Menu-itemSubmenuIcon {
+ display: table-cell;
+ text-align: center;
+}
+
+.lm-Menu-itemLabel {
+ display: table-cell;
+ text-align: left;
+}
+
+.lm-Menu-itemShortcut {
+ display: table-cell;
+ text-align: right;
+}
+
+/*
+ * 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-MenuBar {
+ outline: none;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-MenuBar-content {
+ margin: 0;
+ padding: 0;
+ display: flex;
+ flex-direction: row;
+ list-style-type: none;
+}
+
+.lm-MenuBar-item {
+ box-sizing: border-box;
+}
+
+.lm-MenuBar-itemIcon,
+.lm-MenuBar-itemLabel {
+ display: inline-block;
+}
+
+/*
+ * 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-ScrollBar {
+ display: flex;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-ScrollBar[data-orientation='horizontal'] {
+ flex-direction: row;
+}
+
+.lm-ScrollBar[data-orientation='vertical'] {
+ flex-direction: column;
+}
+
+.lm-ScrollBar-button {
+ box-sizing: border-box;
+ flex: 0 0 auto;
+}
+
+.lm-ScrollBar-track {
+ box-sizing: border-box;
+ position: relative;
+ overflow: hidden;
+ flex: 1 1 auto;
+}
+
+.lm-ScrollBar-thumb {
+ box-sizing: border-box;
+ position: absolute;
+}
+
+/*
+ * 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-SplitPanel-child {
+ z-index: 0;
+}
+
+.lm-SplitPanel-handle {
+ z-index: 1;
+}
+
+.lm-SplitPanel-handle.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-SplitPanel-handle:after {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ content: '';
+}
+
+.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle {
+ cursor: ew-resize;
+}
+
+.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle {
+ cursor: ns-resize;
+}
+
+.lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle:after {
+ left: 50%;
+ min-width: 8px;
+ transform: translateX(-50%);
+}
+
+.lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle:after {
+ top: 50%;
+ min-height: 8px;
+ transform: translateY(-50%);
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabBar {
+ display: flex;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ user-select: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] {
+ flex-direction: row;
+ align-items: flex-end;
+}
+
+.lm-TabBar[data-orientation='vertical'] {
+ flex-direction: column;
+ align-items: flex-end;
+}
+
+.lm-TabBar-content {
+ margin: 0;
+ padding: 0;
+ display: flex;
+ flex: 1 1 auto;
+ list-style-type: none;
+}
+
+.lm-TabBar[data-orientation='horizontal'] > .lm-TabBar-content {
+ flex-direction: row;
+}
+
+.lm-TabBar[data-orientation='vertical'] > .lm-TabBar-content {
+ flex-direction: column;
+}
+
+.lm-TabBar-tab {
+ display: flex;
+ flex-direction: row;
+ box-sizing: border-box;
+ overflow: hidden;
+ touch-action: none; /* Disable native Drag/Drop */
+}
+
+.lm-TabBar-tabIcon,
+.lm-TabBar-tabCloseIcon {
+ flex: 0 0 auto;
+}
+
+.lm-TabBar-tabLabel {
+ flex: 1 1 auto;
+ overflow: hidden;
+ white-space: nowrap;
+}
+
+.lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+}
+
+.lm-TabBar-tab.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar-addButton.lm-mod-hidden {
+ display: none !important;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab {
+ position: relative;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab {
+ left: 0;
+ transition: left 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab {
+ top: 0;
+ transition: top 150ms ease;
+}
+
+.lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging {
+ transition: none;
+}
+
+.lm-TabBar-tabLabel .lm-TabBar-tabInput {
+ user-select: all;
+ width: 100%;
+ box-sizing: border-box;
+ background: inherit;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+.lm-TabPanel-tabBar {
+ z-index: 1;
+}
+
+.lm-TabPanel-stackedPanel {
+ z-index: 0;
+}
+
+/*
+ * Copyright (c) Jupyter Development Team.
+ * Distributed under the terms of the Modified BSD License.
+ */
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Copyright (c) 2014-2017, PhosphorJS Contributors
+|
+| Distributed under the terms of the BSD 3-Clause License.
+|
+| The full license is in the file LICENSE, distributed with this software.
+|----------------------------------------------------------------------------*/
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+.jp-Collapse {
+ display: flex;
+ flex-direction: column;
+ align-items: stretch;
+}
+
+.jp-Collapse-header {
+ padding: 1px 12px;
+ background-color: var(--jp-layout-color1);
+ border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
+ color: var(--jp-ui-font-color1);
+ cursor: pointer;
+ display: flex;
+ align-items: center;
+ font-size: var(--jp-ui-font-size0);
+ font-weight: 600;
+ text-transform: uppercase;
+ user-select: none;
+}
+
+.jp-Collapser-icon {
+ height: 16px;
+}
+
+.jp-Collapse-header-collapsed .jp-Collapser-icon {
+ transform: rotate(-90deg);
+ margin: auto 0;
+}
+
+.jp-Collapser-title {
+ line-height: 25px;
+}
+
+.jp-Collapse-contents {
+ padding: 0 12px;
+ background-color: var(--jp-layout-color1);
+ color: var(--jp-ui-font-color1);
+ overflow: auto;
+}
+
+/*-----------------------------------------------------------------------------
+| Copyright (c) Jupyter Development Team.
+| Distributed under the terms of the Modified BSD License.
+|----------------------------------------------------------------------------*/
+
+/* This file was auto-generated by ensureUiComponents() in @jupyterlab/buildutils */
+
+/**
+ * (DEPRECATED) Support for consuming icons as CSS background images
+ */
+
+/* Icons urls */
+
+:root {
+ --jp-icon-add-above: url(data:image/svg+xml;base64,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);
+ --jp-icon-add-below: url(data:image/svg+xml;base64,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);
+ --jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-bell: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
+ --jp-icon-bug: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yMCA4aC0yLjgxYy0uNDUtLjc4LTEuMDctMS40NS0xLjgyLTEuOTZMMTcgNC40MSAxNS41OSAzbC0yLjE3IDIuMTdDMTIuOTYgNS4wNiAxMi40OSA1IDEyIDVjLS40OSAwLS45Ni4wNi0xLjQxLjE3TDguNDEgMyA3IDQuNDFsMS42MiAxLjYzQzcuODggNi41NSA3LjI2IDcuMjIgNi44MSA4SDR2MmgyLjA5Yy0uMDUuMzMtLjA5LjY2LS4wOSAxdjFINHYyaDJ2MWMwIC4zNC4wNC42Ny4wOSAxSDR2MmgyLjgxYzEuMDQgMS43OSAyLjk3IDMgNS4xOSAzczQuMTUtMS4yMSA1LjE5LTNIMjB2LTJoLTIuMDljLjA1LS4zMy4wOS0uNjYuMDktMXYtMWgydi0yaC0ydi0xYzAtLjM0LS4wNC0uNjctLjA5LTFIMjBWOHptLTYgOGgtNHYtMmg0djJ6bTAtNGgtNHYtMmg0djJ6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --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=);
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+ --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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);
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+ --jp-icon-collapse-all: url(data:image/svg+xml;base64,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);
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+ --jp-icon-copyright: url(data:image/svg+xml;base64,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);
+ --jp-icon-cut: url(data:image/svg+xml;base64,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);
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+ --jp-icon-filter: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiNGRkYiPgogICAgPHBhdGggZD0iTTE0LDEyVjE5Ljg4QzE0LjA0LDIwLjE4IDEzLjk0LDIwLjUgMTMuNzEsMjAuNzFDMTMuMzIsMjEuMSAxMi42OSwyMS4xIDEyLjMsMjAuNzFMMTAuMjksMTguN0MxMC4wNiwxOC40NyA5Ljk2LDE4LjE2IDEwLDE3Ljg3VjEySDkuOTdMNC4yMSw0LjYyQzMuODcsNC4xOSAzLjk1LDMuNTYgNC4zOCwzLjIyQzQuNTcsMy4wOCA0Ljc4LDMgNSwzVjNIMTlWM0MxOS4yMiwzIDE5LjQzLDMuMDggMTkuNjIsMy4yMkMyMC4wNSwzLjU2IDIwLjEzLDQuMTkgMTkuNzksNC42MkwxNC4wMywxMkgxNFoiIC8+CiAgPC9nPgo8L3N2Zz4K);
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+ --jp-icon-home: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjRweCIgdmlld0JveD0iMCAwIDI0IDI0IiB3aWR0aD0iMjRweCIgZmlsbD0iIzAwMDAwMCI+CiAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPjxwYXRoIGNsYXNzPSJqcC1pY29uMyBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xMCAyMHYtNmg0djZoNXYtOGgzTDEyIDMgMiAxMmgzdjh6Ii8+Cjwvc3ZnPgo=);
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+ --jp-icon-image: url(data:image/svg+xml;base64,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);
+ --jp-icon-info: url(data:image/svg+xml;base64,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);
+ --jp-icon-inspector: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaW5zcGVjdG9yLWljb24tY29sb3IganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMjAgNEg0Yy0xLjEgMC0xLjk5LjktMS45OSAyTDIgMThjMCAxLjEuOSAyIDIgMmgxNmMxLjEgMCAyLS45IDItMlY2YzAtMS4xLS45LTItMi0yem0tNSAxNEg0di00aDExdjR6bTAtNUg0VjloMTF2NHptNSA1aC00VjloNHY5eiIvPgo8L3N2Zz4K);
+ --jp-icon-json: url(data:image/svg+xml;base64,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);
+ --jp-icon-julia: url(data:image/svg+xml;base64,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);
+ --jp-icon-jupyter-favicon: url(data:image/svg+xml;base64,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);
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+ --jp-icon-jupyterlab-wordmark: 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+ --jp-icon-kernel: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzYxNjE2MSIgZD0iTTE1IDlIOXY2aDZWOXptLTIgNGgtMnYtMmgydjJ6bTgtMlY5aC0yVjdjMC0xLjEtLjktMi0yLTJoLTJWM2gtMnYyaC0yVjNIOXYySDdjLTEuMSAwLTIgLjktMiAydjJIM3YyaDJ2MkgzdjJoMnYyYzAgMS4xLjkgMiAyIDJoMnYyaDJ2LTJoMnYyaDJ2LTJoMmMxLjEgMCAyLS45IDItMnYtMmgydi0yaC0ydi0yaDJ6bS00IDZIN1Y3aDEwdjEweiIvPgo8L3N2Zz4K);
+ --jp-icon-keyboard: url(data:image/svg+xml;base64,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);
+ --jp-icon-launch: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMzIgMzIiIHdpZHRoPSIzMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yNiwyOEg2YTIuMDAyNywyLjAwMjcsMCwwLDEtMi0yVjZBMi4wMDI3LDIuMDAyNywwLDAsMSw2LDRIMTZWNkg2VjI2SDI2VjE2aDJWMjZBMi4wMDI3LDIuMDAyNywwLDAsMSwyNiwyOFoiLz4KICAgIDxwb2x5Z29uIHBvaW50cz0iMjAgMiAyMCA0IDI2LjU4NiA0IDE4IDEyLjU4NiAxOS40MTQgMTQgMjggNS40MTQgMjggMTIgMzAgMTIgMzAgMiAyMCAyIi8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-launcher: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkgMTlINVY1aDdWM0g1YTIgMiAwIDAwLTIgMnYxNGEyIDIgMCAwMDIgMmgxNGMxLjEgMCAyLS45IDItMnYtN2gtMnY3ek0xNCAzdjJoMy41OWwtOS44MyA5LjgzIDEuNDEgMS40MUwxOSA2LjQxVjEwaDJWM2gtN3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-line-form: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGZpbGw9IndoaXRlIiBkPSJNNS44OCA0LjEyTDEzLjc2IDEybC03Ljg4IDcuODhMOCAyMmwxMC0xMEw4IDJ6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-link: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTMuOSAxMmMwLTEuNzEgMS4zOS0zLjEgMy4xLTMuMWg0VjdIN2MtMi43NiAwLTUgMi4yNC01IDVzMi4yNCA1IDUgNWg0di0xLjlIN2MtMS43MSAwLTMuMS0xLjM5LTMuMS0zLjF6TTggMTNoOHYtMkg4djJ6bTktNmgtNHYxLjloNGMxLjcxIDAgMy4xIDEuMzkgMy4xIDMuMXMtMS4zOSAzLjEtMy4xIDMuMWgtNFYxN2g0YzIuNzYgMCA1LTIuMjQgNS01cy0yLjI0LTUtNS01eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xOSA1djE0SDVWNWgxNG0xLjEtMkgzLjljLS41IDAtLjkuNC0uOS45djE2LjJjMCAuNC40LjkuOS45aDE2LjJjLjQgMCAuOS0uNS45LS45VjMuOWMwLS41LS41LS45LS45LS45ek0xMSA3aDZ2MmgtNlY3em0wIDRoNnYyaC02di0yem0wIDRoNnYyaC02ek03IDdoMnYySDd6bTAgNGgydjJIN3ptMCA0aDJ2Mkg3eiIvPgo8L3N2Zz4K);
+ --jp-icon-markdown: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-down: url(data:image/svg+xml;base64,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);
+ --jp-icon-move-up: url(data:image/svg+xml;base64,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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,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);
+ --jp-icon-notebook: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtbm90ZWJvb2staWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiNFRjZDMDAiPgogICAgPHBhdGggZD0iTTE4LjcgMy4zdjE1LjRIMy4zVjMuM2gxNS40bTEuNS0xLjVIMS44djE4LjNoMTguM2wuMS0xOC4zeiIvPgogICAgPHBhdGggZD0iTTE2LjUgMTYuNWwtNS40LTQuMy01LjYgNC4zdi0xMWgxMXoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-numbering: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTQgMTlINlYxOS41SDVWMjAuNUg2VjIxSDRWMjJIN1YxOEg0VjE5Wk01IDEwSDZWNkg0VjdINVYxMFpNNCAxM0g1LjhMNCAxNS4xVjE2SDdWMTVINS4yTDcgMTIuOVYxMkg0VjEzWk05IDdWOUgyM1Y3SDlaTTkgMjFIMjNWMTlIOVYyMVpNOSAxNUgyM1YxM0g5VjE1WiIvPgoJPC9nPgo8L3N2Zz4K);
+ --jp-icon-offline-bolt: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDIuMDJjLTUuNTEgMC05Ljk4IDQuNDctOS45OCA5Ljk4czQuNDcgOS45OCA5Ljk4IDkuOTggOS45OC00LjQ3IDkuOTgtOS45OFMxNy41MSAyLjAyIDEyIDIuMDJ6TTExLjQ4IDIwdi02LjI2SDhMMTMgNHY2LjI2aDMuMzVMMTEuNDggMjB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-palette: url(data:image/svg+xml;base64,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);
+ --jp-icon-paste: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE5IDJoLTQuMThDMTQuNC44NCAxMy4zIDAgMTIgMGMtMS4zIDAtMi40Ljg0LTIuODIgMkg1Yy0xLjEgMC0yIC45LTIgMnYxNmMwIDEuMS45IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjRjMC0xLjEtLjktMi0yLTJ6bS03IDBjLjU1IDAgMSAuNDUgMSAxcy0uNDUgMS0xIDEtMS0uNDUtMS0xIC40NS0xIDEtMXptNyAxOEg1VjRoMnYzaDEwVjRoMnYxNnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-pdf: url(data:image/svg+xml;base64,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);
+ --jp-icon-python: url(data:image/svg+xml;base64,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);
+ --jp-icon-r-kernel: url(data:image/svg+xml;base64,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);
+ --jp-icon-react: url(data:image/svg+xml;base64,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);
+ --jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
+ --jp-icon-regex: url(data:image/svg+xml;base64,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);
+ --jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-running: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDUxMiA1MTIiPgogIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICA8cGF0aCBkPSJNMjU2IDhDMTE5IDggOCAxMTkgOCAyNTZzMTExIDI0OCAyNDggMjQ4IDI0OC0xMTEgMjQ4LTI0OFMzOTMgOCAyNTYgOHptOTYgMzI4YzAgOC44LTcuMiAxNi0xNiAxNkgxNzZjLTguOCAwLTE2LTcuMi0xNi0xNlYxNzZjMC04LjggNy4yLTE2IDE2LTE2aDE2MGM4LjggMCAxNiA3LjIgMTYgMTZ2MTYweiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-search: url(data:image/svg+xml;base64,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);
+ --jp-icon-settings: url(data:image/svg+xml;base64,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);
+ --jp-icon-share: url(data:image/svg+xml;base64,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);
+ --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=);
+ --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-table-rows: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMSw4SDNWNGgxOFY4eiBNMjEsMTBIM3Y0aDE4VjEweiBNMjEsMTZIM3Y0aDE4VjE2eiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-tag: url(data:image/svg+xml;base64,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);
+ --jp-icon-terminal: url(data:image/svg+xml;base64,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);
+ --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==);
+ --jp-icon-toc: url(data:image/svg+xml;base64,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);
+ --jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
+ --jp-icon-trusted: url(data:image/svg+xml;base64,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);
+ --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-users: url(data:image/svg+xml;base64,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);
+ --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
+ --jp-icon-word: url(data:image/svg+xml;base64,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);
+ --jp-icon-yaml: url(data:image/svg+xml;base64,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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;
+}
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+.jp-RenderedText pre .ansi-yellow-fg {
+ color: #ddb62b;
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+.jp-RenderedText pre .ansi-blue-fg {
+ color: #208ffb;
+}
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+ color: #d160c4;
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+.jp-RenderedText pre .ansi-cyan-fg {
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+
+.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;
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+ --jp-inverse-layout-color4: var(--md-grey-600);
+
+ /* Brand/accent */
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+ * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
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+
+ /*
+ RTC user specific colors.
+ These colors are used for the cursor, username in the editor,
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+ */
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+ --jp-collaborator-color1: #ffad8e;
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+
+ /* 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;
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+ --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);
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+ --jp-terminal-icon-background-color: var(--md-grey-800);
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+ --jp-text-editor-icon-color: var(--md-grey-700);
+ --jp-inspector-icon-color: var(--md-grey-700);
+ --jp-switch-color: var(--md-grey-400);
+ --jp-switch-true-position-color: var(--md-orange-900);
+}
+</style>
+<style type="text/css">
+/* Force rendering true colors when outputing to pdf */
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+/* Input area styling */
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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=24fdc979">
+<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="GA-1.8:-Multivariate-Distributions">GA 1.8: Multivariate Distributions<a class="anchor-link" href="#GA-1.8:-Multivariate-Distributions">¶</a></h1><h1 style="position: absolute; display: flex; flex-grow: 0; flex-shrink: 0; flex-direction: row-reverse; top: 60px;right: 30px; margin: 0; border: 0">
+<style>
+ .markdown {width:100%; position: relative}
+ article { position: relative }
+ </style>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/tu-logo/TU_P1_full-color.png" style="width:100px; height: auto; margin: 0"/>
+<img alt="No description has been provided for this image" src="https://gitlab.tudelft.nl/mude/public/-/raw/main/mude-logo/MUDE_Logo-small.png" style="width:100px; height: auto; margin: 0"/>
+</h1>
+<h2 style="height: 10px">
+</h2>
+<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 1.8, Friday Oct 25, 2024.</em></p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8b5d241">
+<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="Objective">Objective<a class="anchor-link" href="#Objective">¶</a></h2><p>This notebook is structured in an identical way to WS 1.8. In particular, we have 3 main tasks:</p>
+<ol>
+<li>Build a multivariate distribution $F_{X_1,X_2}(x_1,x_2)$</li>
+<li>Use the distribution by comparing empirical probabilities to values computed with $F_{X_1,X_2}(x_1,x_2)$ for the AND, OR and function of random variable cases</li>
+<li>Validate the distribution using the distribution of the function of random variables, $Z(X_1,X_2)$.</li>
+</ol>
+<h3 id="Multivariate-Distribution-(Task-1)">Multivariate Distribution (Task 1)<a class="anchor-link" href="#Multivariate-Distribution-(Task-1)">¶</a></h3><p>As with WS 1.8, we will build a multivariate distribution, but this time we will include non-Gaussian marginal distributions using a Gaussian Copula:</p>
+<p>$$
+F_{X_1,X_2}(x_1,x_2) = C[F_{X_1}(x_1)F_{X_2}(x_2)]
+$$</p>
+<p>In this case, the Copula requires one parameter: the Pearson correlation coefficient, $\rho$.</p>
+<p>This distribution has been implemented in the class <code>Bivariate</code> within <code>helper.py</code>. You can define an instance of the class using:</p>
+<pre><code>my_bivariate_dist = Bivariate(marginal_1, marginal_2, rho)
+</code></pre>
+<p>where the arguments are the marginal distributions for your random variables and are instances of the class <code>rv_continuous</code> from <code>scipy.stats</code>. In fact, the <code>Bivariate</code> class has been created with similar methods to <code>multivariate_normal</code>; in other words, you can use the methods <code>pdf</code>, <code>cdf</code> and <code>rvs</code> in the same way as <code>multivariate_normal</code> in WS 1.8.</p>
+<p>Note that the function <code>plot_contours</code> will also work, but due to the way <code>Bivariate</code> is implemented, it is slow to make the plots, so you may want to use small sample sizes.</p>
+<h4 id="Python-Package:-pyvinecopulib">Python Package: <code>pyvinecopulib</code><a class="anchor-link" href="#Python-Package:-pyvinecopulib">¶</a></h4><p>A package <code>pyvinecopulib</code> is required for the Bivariate class. It is only available on PyPI, so it has to be installed using <code>pip</code>. Fortunately you should already have done this as part of PA 1.8, so all you need to do is remember to use your environment <code>mude-week-8</code>.</p>
+<h3 id="Probability-Calculations-for-3-Cases-(Task-2)">Probability Calculations for 3 Cases (Task 2)<a class="anchor-link" href="#Probability-Calculations-for-3-Cases-(Task-2)">¶</a></h3><p>For each data set, we will use the 90th percentile of each random variable to evaluate the AND, OR and function of random variable cases. In other words:</p>
+<p>$$
+x_{1,90} = F_{X_1}^{-1}(0.90) \;\;\textrm{and}\;\; x_{2,90} = F_{X_2}^{-1}(0.90)
+$$</p>
+<p>Since there were three data sets to choose from last week, each with different functions and variables, this notebook uses the notation $Z(X_1,X_2)$ to represent the function of random variables for your particular case. As we did in WS 1.8, we would like to evaluate $Z$ for a threshold condition (in WS 1.8 it was $Z<0$ for the Thingamajig). For this assignment, consider the threshold case to be all combinations of $x_1$ and $x_2$ such that:</p>
+<p>$$
+Z>Z(x_{1,90},z_{2,90})
+$$</p>
+<h3 id="Propagating-Uncertainty-(Task-3)">Propagating Uncertainty (Task 3)<a class="anchor-link" href="#Propagating-Uncertainty-(Task-3)">¶</a></h3><p>This proceeds as in WS 1.8 as well, where you will use the samples generated in Task 2 to evaluate the distribution of $Z$ and compare to the empirical data set.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=55bd0e2d">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below allows you to edit the contents of helper and incorporate the changes in the notebook without restarting the kernel.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=91463787">
+<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="o">%</span><span class="k">load_ext</span> autoreload
+<span class="o">%</span><span class="k">autoreload</span> 2
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=7eeb37e0-aca0-4759-866f-f5ad09ea8d0b">
+<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="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
+
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">plot_contour</span>
+<span class="kn">from</span> <span class="nn">helper</span> <span class="kn">import</span> <span class="n">Bivariate</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=d0113213">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+The cell below is only for the solution.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=b4a22fde">
+<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">data_set</span> <span class="o">=</span> <span class="s1">'dataset_traffic'</span>
+<span class="n">N_factor_MCS</span> <span class="o">=</span> <span class="mi">100</span>
+<span class="n">make_figs</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="n">save_figs</span> <span class="o">=</span> <span class="kc">False</span>
+
+<span class="n">bivariate_lim</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">250</span><span class="p">,</span> <span class="o">-</span><span class="mi">20</span><span class="p">,</span> <span class="mi">100</span><span class="p">]</span>
+
+<span class="n">plot_x2</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">z90</span><span class="p">:</span> <span class="p">(</span><span class="n">z90</span> <span class="o">-</span> <span class="mi">143</span><span class="o">*</span><span class="n">x1</span><span class="p">)</span><span class="o">/</span><span class="mi">469</span>
+<span class="n">Z</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">:</span> <span class="mi">143</span><span class="o">*</span><span class="n">x1</span> <span class="o">+</span> <span class="mi">469</span><span class="o">*</span><span class="n">x2</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4d11b3b2-5d82-4e67-a151-0e7025ab175a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-1:-Creating-a-Bivariate-Distribution">Part 1: Creating a Bivariate Distribution<a class="anchor-link" href="#Part-1:-Creating-a-Bivariate-Distribution">¶</a></h2><p>We need to represent our two dependent random variables with marginal distributions and use the correlation coefficient to model dependence, as found previously in GA 1.7.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=fbd5f10c-2c28-4dde-b5c4-e2781058997f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.1:</b>
+<p>Import your data set from last week and define the marginal distributions as frozen scipy stats objects.</p>
+<p><em>The cell below illustrates how to create a frozen Gaussian distribution</em></p>
+</p>
+
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f00a23b6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+Remember there is a <a href="https://mude.citg.tudelft.nl/2024/book/probability/python.html" target="_blank">new page on scipy stats in the book</a> in case you need a reference.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=2b3477a8-002c-42a8-bd30-6c24890156c2">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+<span class="c1"># parameters1 = st.norm.fit_loc_scale(data_x1)</span>
+<span class="c1"># dist_x1 = st.norm(*parameters1)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3aad6608-743f-4f49-bcab-440ab5b3d093">
+<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="n">data_path</span> <span class="o">=</span> <span class="s2">"data/dataset_traffic.csv"</span>
+
+<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">genfromtxt</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span>
+ <span class="n">delimiter</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span>
+ <span class="n">unpack</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">skip_header</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="c1"># first is C, then H</span>
+<span class="n">data_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">,:])</span>
+<span class="n">data_x2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">,:])</span>
+
+<span class="n">parameters1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">uniform</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="n">dist_x1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">*</span><span class="n">parameters1</span><span class="p">)</span>
+
+<span class="n">parameters2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x2</span><span class="p">)</span>
+<span class="n">dist_x2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="p">(</span><span class="o">*</span><span class="n">parameters2</span><span class="p">)</span>
+
+<span class="n">N</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data: </span><span class="si">{</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x1: </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x1</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'shape of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'min/max of data_x2: </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">}</span><span class="s1">, </span><span class="si">{</span><span class="n">data_x2</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'mean and std of X1 and X2: '</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x1</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">data_x2</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">data_x2</span><span class="o">.</span><span class="n">std</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>shape of data: (2, 2976)
+shape of data_x1: (2976,)
+min/max of data_x1: 6.0, 180.0
+shape of data_x2: (2976,)
+min/max of data_x2: 0.0, 68.0
+
+
+mean and std of X1 and X2:
+68.69657258064517 45.842988981854475
+30.604502688172044 12.317805263113748
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=9b6d08ec-5e23-4efb-a9fc-d96776812429">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.2:</b>
+Compute the covariance and correlation coefficient between the two random variables. Print the results.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=c8a5e3ec-d87d-4d2d-b51d-85351bdd586d">
+<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="c1"># YOUR_CODE_HERE # many lines</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5c13ea7e-65b8-46ee-804e-f62fb4e68afd">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea">
+<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
+<div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
+<div class="cm-editor cm-s-jupyter">
+<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+<span class="w"> </span><span class="sd">'''</span>
+<span class="sd"> Covariance of two random variables X1 and X2 (numpy arrays).</span>
+<span class="sd"> '''</span>
+ <span class="n">mean_x1</span> <span class="o">=</span> <span class="n">X1</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">mean_x2</span> <span class="o">=</span> <span class="n">X2</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="n">diff_x1</span> <span class="o">=</span> <span class="n">X1</span> <span class="o">-</span> <span class="n">mean_x1</span>
+ <span class="n">diff_x2</span> <span class="o">=</span> <span class="n">X2</span> <span class="o">-</span> <span class="n">mean_x2</span>
+ <span class="n">product</span> <span class="o">=</span> <span class="n">diff_x1</span> <span class="o">*</span> <span class="n">diff_x2</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">product</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+ <span class="k">return</span> <span class="n">covariance</span>
+
+<span class="k">def</span> <span class="nf">pearson_correlation</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">):</span>
+ <span class="n">covariance</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">X1</span><span class="p">,</span> <span class="n">X2</span><span class="p">)</span>
+ <span class="n">correl_coeff</span> <span class="o">=</span> <span class="n">covariance</span><span class="o">/</span><span class="p">(</span><span class="n">X1</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="o">*</span><span class="n">X2</span><span class="o">.</span><span class="n">std</span><span class="p">())</span>
+ <span class="k">return</span> <span class="n">correl_coeff</span>
+
+<span class="n">cov_x12</span> <span class="o">=</span> <span class="n">calculate_covariance</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The covariance of X1 and X2 is </span><span class="si">{</span><span class="n">cov_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="n">rho_x12</span> <span class="o">=</span> <span class="n">pearson_correlation</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The correlation coefficient of X1 and X2 is </span><span class="si">{</span><span class="n">rho_x12</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
+<pre>The covariance of X1 and X2 is 150.24962
+The correlation coefficient of X1 and X2 is 0.26608
+</pre>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=23e4d105-dc2f-4aa8-902f-1872d517e547">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 1.3:</b>
+Build the bivariate distribution by instantiating the <code>Bivariate</code> class in <code>helper.py</code> (and described above). To validate the result, create a plot that shows contours of the joint PDF, compared with the data (see note below). Include the data in your plot and write a few comments on the quality of the fit for use in your Report.
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f9ee9c39-6e6a-4257-9746-fdf118eef8aa">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Use the helper function <code>plot_contour</code> in <code>helper.py</code>; it works exactle the same as in WS 1.8.</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=896fd1c2">
+<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="c1"># plot_contour? # uncomment and run to read docstring</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=5cd6a070">
+<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="c1"># bivar_dist = Bivariate(YOUR_CODE_HERE, YOUR_CODE_HERE, YOUR_CODE_HERE)</span>
+
+<span class="c1"># plot_contour(YOUR_CODE_HERE, YOUR_CODE_HERE, data=data)</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">bivar_dist</span> <span class="o">=</span> <span class="n">Bivariate</span><span class="p">(</span><span class="n">dist_x1</span><span class="p">,</span> <span class="n">dist_x2</span><span class="p">,</span> <span class="n">rho_x12</span><span class="p">)</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</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[9]:</div>
+<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
+<pre>(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='$X_1$', ylabel='$X_2$'>)</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=c7336c15-ffd9-4548-8bd6-6a156e184037">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-2:-Using-the-Bivariate-Distribution">Part 2: Using the Bivariate Distribution<a class="anchor-link" href="#Part-2:-Using-the-Bivariate-Distribution">¶</a></h2><p>Now that we have the distribution, we will use it compute probabilities related to the three cases, presented above, as follows:</p>
+<ol>
+<li>$P[X_1>x_{1,90} \;\cup\; X_2>x_{2,90}$</li>
+<li>$P[X_1>x_{1,90} \;\cap\; X_2>x_{2,90}]$</li>
+<li>$P[X_1,X_2:\; Z>Z(x_{1,90},x_{2,90})]$</li>
+</ol>
+<p>Note that the "critical" Z value in this case is that where your Z function is evaluated at the 90th percentile values of each random variable.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f544418c">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Task 2:</b>
+<p>For each of the three cases, do the following:</p>
+<ul>
+<li>Compute the requested probability using the empirical distribution.</li>
+<li>Compute the requested probability using the bivariate distribution.</li>
+<li>Create a bivariate plot that includes PDF contours <em>and</em> the region of interest.</li>
+<li>Repeat the calculations for additional cases of correlation coefficient (for example change $\rho$ to: +0.9, 0.0, then -0.9) to see how the answer changes (you can simply regenerate the plot, you don't need to make multiple versions). <em>You can save this sub-task for later if you are running out of time. It is more important to get through Task 3 during the in-class session.</em></li>
+<li>Write two or three sentences that summarize the results and explains the quantitative impact of correlation coefficient. Make a particular note about whether or not one case may or be affected more or less than the others.</li>
+</ul>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=bdab1a35-4e2f-42a2-804c-17f7f0917b6a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note that the optional arguments in the helper function <code>plot_contour</code> will be useful here.
+
+<p>Here is an example code that shows you what it can do (the values are meaningless)</p>
+</p></div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=adb079f6">
+<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">region_example</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="mi">0</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">18</span><span class="p">,</span> <span class="mi">19</span><span class="p">,</span> <span class="mi">12</span><span class="p">]])</span>
+
+<span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">30</span><span class="p">],</span>
+ <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="mi">23</span><span class="p">,</span> <span class="mi">13</span><span class="p">],</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_example</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a8974e1b">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.1 and 2.2:</b> create cells below to carry out the OR and AND calculations.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=0999c23c">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=a07bc27f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 2.3:</b> create cells below to carry out the Case 3 calculations.</p>
+<p>Note that in this case you need to make the plot to visualize the region over which we want to integrate. We need to define the boundary of the region of interest by solving the equation $Z(X_1,X_2)$ for $X_2$ when $Z=Z(x_{1,90},x_{2,90})$.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=0bea4cff">
+<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>The equation can be defined as follows:</p>
+<p>$$
+\textrm{WRITE THE EQUATION HERE}
+$$</p>
+<p>which is then defined in Python and included in the <code>plot_contours</code> function as an array for the keyword argument <code>region</code>.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=cf2e5192">
+<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="c1"># YOUR_CODE_HERE</span>
+<span class="c1"># DEFINITELY more than one line.</span>
+<span class="c1"># probably several cells too ;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=da352934-c7b3-4dd2-a913-271f9ad38d26">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>Start of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=096a378a-2256-489e-a99c-9458924b6e1a">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: order of the tasks in this solution is not important.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=364b7689-2034-437f-b7cf-d59042ea93a8">
+<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="Case-1-and-2">Case 1 and 2<a class="anchor-link" href="#Case-1-and-2">¶</a></h3><p>First we will compute the probabilities from the distribution.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=74874fef-e398-45b6-8858-bebd1017e095">
+<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="n">x90_1</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+<span class="n">x90_2</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mf">.9</span><span class="p">)</span>
+
+<span class="n">region_or</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">2</span><span class="p">]]])</span>
+<span class="n">region_and</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_1</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span>
+ <span class="p">[</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="n">x90_2</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">]])</span>
+
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">cdf</span><span class="p">([</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="n">dist_x1</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="n">dist_x2</span><span class="o">.</span><span class="n">cdf</span><span class="p">(</span><span class="n">x90_2</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="c1"># Case 1 and 2 empirical probabilities</span>
+<span class="n">N</span> <span class="o">=</span> <span class="n">data_x1</span><span class="o">.</span><span class="n">size</span>
+
+<span class="n">number_of_points_lower_left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">((</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">&</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">))</span>
+<span class="n">lower_left</span> <span class="o">=</span> <span class="n">number_of_points_lower_left</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">union</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">lower_left</span>
+
+<span class="n">left</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x1</span> <span class="o"><</span> <span class="n">x90_1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">bottom</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">data_x2</span> <span class="o"><</span> <span class="n">x90_2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+<span class="n">intersection</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">bottom</span> <span class="o">-</span> <span class="n">lower_left</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1 and 2 empirical probabilities'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' lower left: </span><span class="si">{</span><span class="n">lower_left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' left side: </span><span class="si">{</span><span class="n">left</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">' bottom side: </span><span class="si">{</span><span class="n">bottom</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'============================='</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 1, Union: </span><span class="si">{</span><span class="n">union</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Case 2, Intersection: </span><span class="si">{</span><span class="n">intersection</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_or</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_2.svg'</span><span class="p">))</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_and</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_3.svg'</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>Case 1 and 2 probabilities
+ lower left: 0.82005
+ left side: 0.90000
+ bottom side: 0.90000
+=============================
+Case 1, Union: 0.17995
+Case 2, Intersection: 0.02005
+
+
+Case 1 and 2 empirical probabilities
+ lower left: 0.88277
+ left side: 0.88949
+ bottom side: 0.99227
+=============================
+Case 1, Union: 0.11723
+Case 2, Intersection: 0.00101
+
+
+</pre>
+</div>
+</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ee7d5b8c-1cee-4799-bd44-d01ae4266fc3">
+<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="Case-3">Case 3<a class="anchor-link" href="#Case-3">¶</a></h3><p>The Z function is defined at the top of this notebook in a solution code cell.</p>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=cfe4b8df-e9e4-4086-a265-a67100f28fe0">
+<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 [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="n">z_90</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">)</span>
+
+<span class="n">plot_Z_x1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">bivariate_lim</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">bivariate_lim</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">plot_Z_x2</span> <span class="o">=</span> <span class="n">plot_x2</span><span class="p">(</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">z_90</span><span class="p">)</span>
+<span class="n">region_Z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">plot_Z_x1</span><span class="p">,</span> <span class="n">plot_Z_x2</span><span class="p">])</span>
+
+<span class="k">if</span> <span class="n">make_figs</span><span class="p">:</span>
+ <span class="n">plot_contour</span><span class="p">(</span><span class="n">bivar_dist</span><span class="p">,</span> <span class="n">bivariate_lim</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span>
+ <span class="n">region</span><span class="o">=</span><span class="n">region_Z</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="p">[</span><span class="n">x90_1</span><span class="p">,</span> <span class="n">x90_2</span><span class="p">])</span>
+ <span class="k">if</span> <span class="n">save_figs</span><span class="p">:</span>
+ <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">figure_path</span><span class="p">,</span><span class="s1">'figure_4.svg'</span><span class="p">))</span>
+
+<span class="n">sample_N</span> <span class="o">=</span> <span class="n">N_factor_MCS</span><span class="o">*</span><span class="n">N</span>
+<span class="n">sample</span> <span class="o">=</span> <span class="n">bivar_dist</span><span class="o">.</span><span class="n">rvs</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">sample_N</span><span class="p">)</span>
+<span class="n">sample_X1</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">sample_X2</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span>
+
+<span class="n">sample_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">sample_X1</span><span class="p">,</span> <span class="n">sample_X2</span><span class="p">)</span>
+<span class="n">Z_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90</span> <span class="o">=</span> <span class="n">Z_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">sample_N</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="s1">'Z case MCS'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">sample_N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of samples of Z < 0 is: </span><span class="si">{</span><span class="n">Z_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The MCS probability is </span><span class="si">{</span><span class="n">p_Z90</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">sample_N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
+
+<span class="n">empirical_Z</span> <span class="o">=</span> <span class="n">Z</span><span class="p">(</span><span class="n">data_x1</span><span class="p">,</span> <span class="n">data_x2</span><span class="p">)</span>
+<span class="n">Z_data_beyond_90</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">empirical_Z</span><span class="o">></span><span class="n">z_90</span><span class="p">)</span>
+<span class="n">p_Z90_data</span> <span class="o">=</span> <span class="n">Z_data_beyond_90</span><span class="o">/</span><span class="p">(</span><span class="n">N</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="s1">'Z case empirical'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'N = </span><span class="si">{</span><span class="n">N</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The number of data where Z < 0 is: </span><span class="si">{</span><span class="n">Z_data_beyond_90</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'This is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">% of all samples.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The empirical probability is </span><span class="si">{</span><span class="n">p_Z90_data</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">'The c.o.v. is of p is </span><span class="si">{</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">N</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="n">p_Z90_data</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">.'</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</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>Z case MCS
+N = 297600
+The number of samples of Z < 0 is: 15591
+This is 5.239% of all samples.
+The MCS probability is 0.052.
+The c.o.v. is of p is 0.008.
+
+
+Z case empirical
+N = 2976
+The number of data where Z < 0 is: 11
+This is 0.369% of all samples.
+The empirical probability is 0.004.
+The c.o.v. is of p is 0.302.
+
+
+</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=b95860c6-8cbb-47e1-89ab-4d4d56a6f1be">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"> <p>Note: the bivariate figures are an important concept for the exam, so if using the code is too difficult for you to use when studying on your own, try sketching it on paper.</p></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=839cec7d-2167-4572-9585-b1318ca41803">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#FAE99E; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<b>End of solution for Task 2.</b>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2421b1e1-8adb-4dee-8095-5a54b02e6d44">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<h2 id="Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">Part 3: Validate Bivariate with Monte Carlo Simulation<a class="anchor-link" href="#Part-3:-Validate-Bivariate-with-Monte-Carlo-Simulation">¶</a></h2><p>Now that we have seen how the different cases give different values of probability, let's focus on the function of random variables. This is a more interesting case because we can use the samples of $Z$ to approximate the distribution $f_Z(z)$ and use the empirical distribution of $Z$ to help validate the bivariate model.</p>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=6d2196f5-c480-4810-81e4-d692819d648f">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p>$\textbf{Task 3:}$</p>
+<p>Do the following:</p>
+<ul>
+<li>Use Monte Carlo Simulation to create a sample of $Z(X_1,X_2)$ and compare this distribution to the empirical distribution.</li>
+<li>Write 2-3 sentences assessing the quality of the distribution from MCS, and whether the bivariate distribution is acceptable for this problem. Use qualitative and quantitative measures from last week to support your arguments.</li>
+</ul>
+</p>
+<p>
+<em>Note: it would be interesting to fit a parametric distribution to the MCS sample, but it is not required for this assignment.</em>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=99ee3a19">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.1:</b> Plot histograms of $Z$ based on the Monte Carlo samples, and based on the data. Note that you probably already computed the samples in Part 2.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=446b73fe-5277-48ff-8187-e4eabcd21354">
+<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="c1"># plot_values = np.linspace(sample_Z.min(), sample_Z.max(), 30)</span>
+<span class="c1"># fig, ax = plt.subplots(1)</span>
+<span class="c1"># ax.hist([YOUR_CODE_HERE, YOUR_CODE_HERE],</span>
+<span class="c1"># bins=plot_values,</span>
+<span class="c1"># density=True,</span>
+<span class="c1"># edgecolor='black');</span>
+<span class="c1"># ax.legend(['Data', 'MCS Sample'])</span>
+<span class="c1"># ax.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># ax.set_xlabel('Empirical Density [--]')</span>
+<span class="c1"># ax.set_title('Comparison of Distributions of $Z$');</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">plot_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">sample_Z</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">sample_Z</span><span class="o">.</span><span class="n">max</span><span class="p">(),</span> <span class="mi">30</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="mi">1</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">([</span><span class="n">empirical_Z</span><span class="p">,</span> <span class="n">sample_Z</span><span class="p">],</span>
+ <span class="n">bins</span><span class="o">=</span><span class="n">plot_values</span><span class="p">,</span>
+ <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+ <span class="n">edgecolor</span><span class="o">=</span><span class="s1">'black'</span><span class="p">);</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s1">'Data'</span><span class="p">,</span> <span class="s1">'MCS Sample'</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">'$Z(X_1,X_2)$'</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">'Empirical Density [--]'</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="s1">'Comparison of Distributions of $Z$'</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=ebc6a6a6">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.2:</b> Define a function to compute the ecdf.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=5804f940-23e1-480b-adf1-17c3f41fb5c1">
+<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="c1"># def ecdf(var):</span>
+<span class="c1"># x = YOUR_CODE_HERE # sort the values from small to large</span>
+<span class="c1"># n = YOUR_CODE_HERE # determine the number of datapoints</span>
+<span class="c1"># y = YOUR_CODE_HERE</span>
+<span class="c1"># return [y, x]</span>
+
+<span class="c1"># SOLUTION:</span>
+<span class="k">def</span> <span class="nf">ecdf</span><span class="p">(</span><span class="n">var</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">sort</span><span class="p">(</span><span class="n">var</span><span class="p">)</span> <span class="c1"># sort the values from small to large</span>
+ <span class="n">n</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span> <span class="c1"># determine the number of datapoints</span>
+ <span class="n">y</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">n</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
+ <span class="k">return</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=2efb02a2">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.3:</b> Create a semi-log plot of the non-exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=3c0da378-d6b8-4bdf-9a24-ac7f38862b4d">
+<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 [17]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('CDF, $\mathrm{P}[Z < z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands lower tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'CDF, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z < z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands lower tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
+<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=eeae26ba">
+<div class="jp-Cell-inputWrapper" tabindex="0">
+<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
+</div>
+<div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt">
+</div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown">
+<div style="background-color:#AABAB2; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px">
+<p>
+<p><b>Task 3.4:</b> Create a semi-log plot of the exceedance probability.</p>
+</p>
+</div>
+</div>
+</div>
+</div>
+</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=a432095b-9b71-4b1d-871a-21c0097c06e9">
+<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 [18]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
+
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE, </span>
+<span class="c1"># color='k', label='Data')</span>
+<span class="c1"># axes.step(YOUR_CODE_HERE, YOUR_CODE_HERE,</span>
+<span class="c1"># color='r', label='MCS Sample')</span>
+<span class="c1"># axes.set_xlabel('$Z(X_1,X_2)$')</span>
+<span class="c1"># axes.set_ylabel('Exceedance Probability, $\mathrm{P}[Z > z]$')</span>
+<span class="c1"># axes.set_title('Comparison: CDF (log scale expands upper tail)')</span>
+<span class="c1"># axes.set_yscale('log')</span>
+<span class="c1"># axes.legend()</span>
+<span class="c1"># axes.grid()</span>
+
+<span class="c1"># SOLUTION</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
+
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">empirical_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Data'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">1</span><span class="o">-</span><span class="n">ecdf</span><span class="p">(</span><span class="n">sample_Z</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'MCS Sample'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'$Z(X_1,X_2)$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'Exceedance Probability, $\mathrm</span><span class="si">{P}</span><span class="s1">[Z > z]$'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">'Comparison: CDF (log scale expands upper tail)'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+<span class="n">axes</span><span class="o">.</span><span class="n">grid</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</div>
+<div class="jp-Cell-outputWrapper">
+<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
+</div>
+<div class="jp-OutputArea jp-Cell-outputArea">
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
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+<img alt="No description has been provided for this image" class="" 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"/>
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+<div style="background-color:#facb8e; color: black; width: 95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px"><p>In case you are wondering, the data for this exercise was computed with a Clayton Copula. A Copula is a useful way of modelling non-linear dependence. If you would like to learn more about this, you should consider the 2nd year cross-over module CEGM2005 Probabilistic Modelling of real-world phenomena through ObseRvations and Elicitation (MORE).</p></div>
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+<p><strong>End of notebook.</strong></p>
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+</img></a>
+</h3>
+<span style="font-size: 75%">
+© Copyright 2024 <a href="http://mude.citg.tudelft.nl/" rel="MUDE">MUDE</a> TU Delft. This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" rel="license">CC BY 4.0 License</a>.
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diff --git a/src/teachers/GA_1_8/GA_1_8_solution_HT.html b/src/teachers/GA_1_8/GA_1_8_solution_HT.html
index 4574e56ac1c9cb06f0375c17e877aba7c1952283..eb7a0c33432c14be9ef0365b59d57695eec4179e 100644
--- a/src/teachers/GA_1_8/GA_1_8_solution_HT.html
+++ b/src/teachers/GA_1_8/GA_1_8_solution_HT.html
@@ -7759,7 +7759,7 @@ Remember there is a <a href="https://mude.citg.tudelft.nl/2024/book/probability/
<span class="n">data_x2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">2</span><span class="p">,:])</span>
<span class="n">parameters1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">expon</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x1</span><span class="p">)</span>
-<span class="n">dist_x1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="o">*</span><span class="n">parameters1</span><span class="p">)</span>
+<span class="n">dist_x1</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">expon</span><span class="p">(</span><span class="o">*</span><span class="n">parameters1</span><span class="p">)</span>
<span class="n">parameters2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="o">.</span><span class="n">fit_loc_scale</span><span class="p">(</span><span class="n">data_x2</span><span class="p">)</span>
<span class="n">dist_x2</span> <span class="o">=</span> <span class="n">st</span><span class="o">.</span><span class="n">gumbel_r</span><span class="p">(</span><span class="o">*</span><span class="n">parameters2</span><span class="p">)</span>
@@ -7874,6 +7874,7 @@ Compute the covariance and correlation coefficient between the two random variab
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
<pre>The covariance of X1 and X2 is 0.80639
The correlation coefficient of X1 and X2 is 0.45580
+The correlation coefficient of X1 and X2 is 0.45580
</pre>
</div>
</div>
@@ -7954,7 +7955,7 @@ Build the bivariate distribution by instantiating the <code>Bivariate</code> cla
<div class="jp-OutputArea-child">
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
<div class="jp-RenderedImage jp-OutputArea-output" tabindex="0">
-<img alt="No description has been provided for this image" class="" 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"/>
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"/>
</div>
</div>
</div>
@@ -8039,7 +8040,7 @@ Build the bivariate distribution by instantiating the <code>Bivariate</code> cla
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"/>
</div>
</div>
</div>
@@ -8244,12 +8245,12 @@ Case 2, Intersection: 0.02977
Case 1 and 2 empirical probabilities
- lower left: 0.66460
- left side: 0.71081
+ lower left: 0.82112
+ left side: 0.90200
bottom side: 0.88094
=============================
-Case 1, Union: 0.33540
-Case 2, Intersection: 0.07285
+Case 1, Union: 0.17888
+Case 2, Intersection: 0.03818
</pre>
@@ -8258,13 +8259,13 @@ Case 2, Intersection: 0.07285
<div class="jp-OutputArea-child">
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
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"/>
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"/>
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"/>
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"/>
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@@ -8340,7 +8341,7 @@ Case 2, Intersection: 0.07285
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<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
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-<pre>C:\Users\rlanzafame\AppData\Local\Temp\ipykernel_5780\3263440411.py:8: RuntimeWarning: invalid value encountered in sqrt
+<pre>C:\Users\rlanzafame\AppData\Local\Temp\ipykernel_12520\3263440411.py:8: RuntimeWarning: invalid value encountered in sqrt
plot_x2 = lambda x1, z90: np.sqrt(z90/(255.4*x1 - 490.4))
</pre>
</div>
@@ -8350,18 +8351,18 @@ Case 2, Intersection: 0.07285
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<pre>Z case MCS
N = 58275500
-The number of samples of Z < 0 is: 16976295
-This is 29.131% of all samples.
-The MCS probability is 0.291.
+The number of samples of Z < 0 is: 4466776
+This is 7.665% of all samples.
+The MCS probability is 0.077.
The c.o.v. is of p is 0.000.
Z case empirical
N = 582755
-The number of data where Z < 0 is: 388296
-This is 66.631% of all samples.
-The empirical probability is 0.666.
-The c.o.v. is of p is 0.002.
+The number of data where Z < 0 is: 46473
+This is 7.975% of all samples.
+The empirical probability is 0.080.
+The c.o.v. is of p is 0.005.
</pre>
@@ -8370,7 +8371,7 @@ The c.o.v. is of p is 0.002.
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"/>
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27QoEHMmjULq9VKcnIy48aNIzs7m7lz59bK9p1r3PkiqewakKPxlXOGMTo6mgEDBjB8+HA2bdrkejwhIYEBAwbQqlUr+vfvzyeffOL2+p07dzJ48GDXQpFr1651W+9927ZtxMTEkJWV5XrNqlWrGDRoEPHx8fTu3bvcdNbqLFBZH0jYNSCVvXqOHz/Oxo0bMRqNgGN662uvvcb/+3//j40bNzJx4kRef/11li1bBjiOS4wePZoOHTqwdu1axo8fz6uvvlrle+zdu5cnnniC4cOH89133zFu3Dhef/11EhIS3J43f/58rrnmGtatW8eoUaOYNGkSKSkpdfOL1xHpxmtAxsZXzrngpN1ud+3vO+erv/3227z44ovceuutgGORx8OHD7N48WLuvfdeli9fjqIovP766/j5+dGuXTvS09MZP358pe/3wQcfcP311/Pss88C0Lp1a5KTk3n//ffdZqRVtUBlfSFh14Az7FLZy3MuOFlQUMDSpUs5evQojz76KOfPn+f06dM899xzbuG12WwEBwcDcOTIETp27Iifn5/rcecKrpVJTk7m5ptvdruvV69efPjhh9hsNvR6PVD1ApX1hYRdA9KNr1zpBSenTZvGyJEjmTVrFn/5y18AeP31110r2Tg5A1nRgpSX+4yr+5qqFqisL6Q/qQE5QFd948aNY/78+dhsNiIjIzl+/Djx8fFut9jYWADatGlDUlISFovF9fq9e/dWuf127drx888/u923a9cuWrVq5foj0lBI2DUglb36+vbtS7t27Xj33Xd57rnnmDNnDh9++CFHjhwhKSmJhIQE15VU7rrrLux2OxMmTCA5OZmNGze6jqxX9gf28ccfZ8uWLbz11lscOXKEZcuWsXDhwmotFVXfSNg1oMUBOj8/P49XKr1e77b/fKX+9re/sWTJEgYMGMAbb7zBsmXLuOmmmxg5ciTLli1zVfbg4GA++eQT9u/fz5AhQ3jttddcB97MZnOF2+7atSvvv/8+K1eu5MYbb+SNN95g/PjxHl0uylNkwUkNFpx8+eWXmTJlCt26deOuu+6q9e1XtuCkL46NX758OePGjSMpKckja7PXFVlwsp7Sap89KChI8/DVtf/85z/ExcURGRnJgQMHePXVVxk2bFi9DnptkbBrQPbZ687vv//OG2+8we+//05ERAS33347EydO1LpZXkHCrgEZVFN3nnzySZ588kmtm+GVvPZbN2PGDHr16kVwcDARERHceeed5a7ZpaoqU6dOJTo6Gn9/fwYOHMj+/fs1anH1SWUXWvDasG/atIkxY8awfft21q9fj9VqZciQIW4HJ2bOnMmsWbOYM2cOO3fuJDIyksGDB5OTk6Nhyy9PzrMLLXhtN37t2rVuPy9cuJCIiAh++eUX+vfvj6qqvP3220yePJkRI0YA8Omnn9KsWTOWLFni1edJpbILLXhtZS/LOSUxPDwcgNTUVNLT0xkyZIjrOWazmQEDBrBt27YKt2GxWMjOzna7aUEqu9BCvQi7qqqMGzeO66+/ni5dugCQnp4OQLNmzdye26xZM9djZc2YMYPQ0FDXrUWLFnXb8EpIZRdaqBdh/8c//sHevXtZunRpuccqmsRQWeWcNGkSWVlZrltaWlqdtPdy5Gi80ILX7rM7PfXUU6xcuZLNmzfTvHlz1/2RkZGAo8JHRUW57s/IyChX7Z3MZnOlwyY9qd5McbXZMO3YgT4jA1tEBEW9e0MDmxziS7y2xKiqyj/+8Q+WL1/ODz/84Jr26BQfH09kZCTr16933VdUVMSmTZvo27evp5tbI/WhG++3ejXNevemyT33EDZmDE3uuYdmvXvjt3q1R9uhqiqLFy/m9ttvp23btnTs2JGhQ4eyYMECCgoKPNqW+s5rK/uYMWNYsmQJX3/9NcHBwa798NDQUPz9/VEUhbFjxzJ9+nTatm1L27ZtmT59OgEBATz44IMat75q3t6N91u9mrC//c0xUaAUXXo6YX/7Gxc/+IDCktVi6trTTz/N6tWreeaZZ3jllVdo3LgxBw4cYMGCBbRo0YJbbrnFI+1oCLw27PPmzQNg4MCBbvcvXLjQtTzQhAkTKCgo4Mknn+TixYv07t2bb7/91rVyibfy6spusxH64ougqpQ98qGoKqqiEDJlCoU331znXfqVK1eyfPlyPv74Y7fVZFq0aMGQIUNc4yl2797Nv//9b/bt24fVaqVz585MnTqVrl27ul7z5ptv8sUXX3Du3DnCwsK47bbbmDZtGuDoEc6cOZMVK1aQlZVFhw4deOGFF7y+h1hTXhv26gRBURSmTp3K1KlT675BtcibT72ZduxAf+ZMpY8rqorh9GlMO3ZQVMdhWLFiBa1bty63bBQ4PkPnDK/c3FzuueceV3jnz5/PI488wpYtWwgKCuKbb75hwYIFzJ07l/bt25ORkcGBAwdc2xo3bhxpaWnMnTuXZs2asXbtWh5++GG+++47WrVqVae/oyd5bdgbMm+u7PqMjFp93tVITU2ldevWl33e9ddf7/bza6+9RqdOnfjpp58YPHgwp06domnTpvTr1w+j0UhMTIxraatjx47x1VdfsWvXLtdB3yeeeIINGzaQkJDApEmTav8X04iEXQPevM9uq+YFFKr7vKtR1WnU0s6dO8frr7/O1q1bOXfuHDabjYKCAk6dOgXA7bffzocffsif/vQnBg0axA033MDgwYMxGAz89ttvqKpKv3793LZZVFREWFhYnfxeWpGwa8CbK3tR797YoqLQpaejVNA+VVGwRUU5TsPVsVatWpGcnHzZ5z377LOcP3+el156iebNm2MymRg+fDjFxcUAxMTEsHnzZn788Ud+/PFHXnjhBebNm8eXX36J3W5Hr9ezZs2aciv5BAYG1snvpRXvLTENmDdXdvR6sl5+GXAEuzTnz9kvveSR8+133nknR48eZd26deUeU1XVNdx5x44dPProo9x44420b98ek8nEhQsX3J7v7+/PkCFDmDZtGv/5z3/45ZdfOHjwIF26dMFms3H+/PlyC1k2tMtEefG3ruHy5soOUHjrrVz84APsJfuwTraoKI+edhs+fDjDhw/nySef5N1332XPnj2cPHmS9evXc99997nmQLRs2ZIvv/yS5ORkfv31V5566im3te8SEhJYunQpBw8e5Pjx43z55Zf4+fkRExND69atGTFiBM888wyrV6/mxIkT7N69m/fee4/vv//eI7+np0g3XgPefDTeqfDWWym8+WZNR9ApisJ7773H4sWLSUhIYPbs2RgMBuLj4xk5ciQDBgwAYNasWUyYMIGbb76Z6OhoJk6c6DoyD46xGXPmzOGll17CZrPRoUMHPvnkE9ekqlmzZjF79mxefvll0tPTCQsLo0ePHtxwww0e+109QRac1GDByY8++oj/+7//o02bNjz88MO1vv3KFpwU9VdtLDgp3XgNePU+u2iw5FunAW/fZxcNk4RdA/Vhn100PBJ2DZS+EKEQniJh14CnuvHyx6ThqI3/lxJ2DdT1Abri4mLsdnu9u6SwqFxxcTE2m+2qLt8l52U0UNeVvaioiN9//53AwEDCwsLkGEE9pqoqxcXFXLhwgePHj2Oz2a54WxJ2DXgifIcOHSIkJERWc2kAbDYbx48fJyUl5aq2I2HXgCf22QsLC9myZYtrVR9RfxUWFl5VRXeSsGvAU+FTVZX8/HyPvJfwfnKATgMyqEZoQcKuAelWCy1I2DUglV1oQcKuAansQgsSdg1IZRdakLBrQCq70IKEXQNS2YUWJOwakMoutCBh14BUdqEFCbsG6s0lm0WDImHXgHTjhRYk7BqQbrzQgoRdA1LZhRYk7BqQyi60IGHXgFR2oQUJuwaksgstSNg1IJVdaEHCrgGp7EILEnYNyEUihBYk7BowmUwAtbKIoBDVJWHXgIRdaEHCrgGz2Qw4rrkthKdI2DXgDLtUduFJEnYNSGUXWpCwa6B0ZZcj8sJTJOwacB6gA+RKq8JjJOwacFZ2kK688BwJuwZKh10O0glPkbBrQK/Xu5amksouPEXCrhGDwXEBXanswlMk7BoxGo2AhF14joRdI84j8tKNF54iYdeIVHbhaRJ2jUhlF54mYdeIVHbhaRJ2jcg0V+FpEnaNSDdeeJqEXSNS2YWnSdg1ItNchadJ2DUiB+iEp0nYNSKr1QhPk7BrRLrxwtMk7Brx8/MDpLILz5Gwa0ROvQlPk7BrRCq78DQJu0Yk7MLTvDbsmzdvZtiwYURHR6MoCl999ZXb46NHj0ZRFLdbnz59tGnsFZADdMLTvDbseXl5dOvWjTlz5lT6nFtuuYUzZ864bqtXr/ZgC6+Ov78/IJVdeI5B6wZUZujQoQwdOrTK55jNZiIjIz3UotollV14mtdW9urYuHEjERERtGvXjscee4yMjIwqn2+xWMjOzna7aUX22YWn1duwDx06lM8//5wffviBN998k507d3LDDTdgsVgqfc2MGTMIDQ113Vq0aOHBFruTbrzwNK/txl/Offfd5/p3ly5d6NmzJ3FxcaxatYoRI0ZU+JpJkyYxbtw418/Z2dmaBd4ZdunGC0+pt2EvKyoqiri4OJKTkyt9jtlsdrtAg5akGy88rd5248s6f/48aWlpREVFad2UapGwC0/z2sqem5tLSkqK6+fU1FR2795NeHg44eHhTJ06lbvvvpuoqCiOHTvGCy+8QJMmTbjrrrs0bHX1ydF44WleG/Zdu3YxaNAg18/Ofe1Ro0Yxb948fvvtNxYtWkRmZiZRUVEMGjSIhIQEgoODtWpyjcgUV+FpXhv2gQMHVnnt8nXr1nmwNbVPKrvwtAazz17fyBp0wtMk7BqRbrzwNAm7RqQbLzxNwq4RqezC0yTsGpHKLjxNwq4R5wE6u92O3W7XuDXCF0jYNVJ62K6EXXiChF0jpcMuXXnhCRJ2jTi78SAH6YRnSNg1otPp0Ov1gFR24RkSdg3J9d6EJ0nYNSRhF54kYdeQM+zSjReeIGHXkEyGEZ4kYdeQVHbhSRJ2Dck+u/AkCbuGpBsvPEnCriG5bLPwJAm7hqSyC0+SsGtIprkKT6q1sNvtdvbt28fp06fLPVZcXMzmzZtr660aDKnswpNqJezHjx+na9euXHPNNbRo0YLhw4dz/vx51+MXLlxwWxZaOMhqNcKTaiXsEyZMoHnz5pw4cYI9e/ZgsVi47rrr3Kp8VctC+yrpxgtPqpWwb9q0iZkzZ9K8eXO6dOnC2rVr6devH/369ePEiRMAKIpSG2/VoEhlF55UK2HPz893W4xBURQWLFjAkCFD6N+/P0eOHKmNt2lwpLILT6qVsLdv355du3aVu3/evHnceuut3H777bXxNg2OXNxReFKthH3EiBEsWbKkwsfmzp3LfffdJ/vsFZCwC0+qlbBPmjSJ1atXV/r4vHnzZFHFCjjDLt144QnVDvumTZvqsh0+SQ7QCU+qdthvvvnmSrvq4so4Ly9dXFyscUuEL6h22Js0acIjjzzCjBkzqr3xY8eOXUmbfEZ4eDgAFotF45YIX1DtsO/YsYMuXbrwz3/+k8cff7zKffDDhw8zevRo2rdvXyuNbKgaNWoEQGFhobYNET6h2mGPiYlhy5Yt3HjjjSxYsIBhw4aRl5fn9py9e/dy33330blzZxYtWkSnTp1qvcENSWhoKCCVXXhGjY7GBwcHs2bNGkaPHs2aNWvo378/6enp/Pzzz9xxxx384Q9/4D//+Q89evTg66+/JjExsa7a3SBI2IUnGWr6Ar1ez8cff0x8fDxTpkyhffv25ObmoqoqAwYMYPLkydx000110dYGJyQkBJCwC8+ocdgB1q1bx/r16wHIyclBURReeeUVXnjhhVptXENXOuyqqsr8AVGnatSNX7FiBT179uTWW29l69at3H333Xz88ceEhIQwbdo0vvjii7pqZ4Pk7Marqiqn30Sdq3Zl79KlC0lJSeh0Oh566CFeeOEFOnToAEDPnj0ZOnQoDz/8MGlpaYwfP77OGtyQBAQEoNPpsNvtWCwWt4s9ClHbql3Zk5OT+etf/8rhw4dZtGiRK+jg+EOwfft2OnfuzMSJE/nHP/4hY+GrQVEU/P39ATn9JupetSv70aNHiYmJqfRx56m5u+66i3nz5nHq1CmWLl3qGv8tKhYYGEheXp4cpBN1rkbn2S8nODiYtWvX8tBDD/H111/LUlTVEBQUBMgReVH3ruhofJUbNBhYtGgRzZs357XXXqvtzTc4EnbhKbUedqfp06cTHx9fV5tvMJyTYSTsoq7V6brxjz32WF1uvkGQUXTCU+QiERqTsAtPkbBrTMIuPEXCrrGwsDBAzrOLuidh15gz7FLZRV2TsGtMVqsRniJh15hUduEpEnaNyZx24SkSdo3J0XjhKRJ2jUllF54iYddY2dVqhKgrEnaNOcOuqipFRUUat0Y0ZBJ2jTlXqwHpyou6JWHXmKIoBAQEABJ2Ubck7F4gMDAQkLCLuiVh9wKygIXwBAm7F5CwC0+QsHsBOdcuPEHC7gWcV3PNz8/XtiGiQZOwe4GoqCiAclfFFaI2eW3YN2/ezLBhw4iOjkZRFL766iu3x1VVZerUqURHR+Pv78/AgQPZv3+/No29Ss5lunNzczVuiWjIvDbseXl5dOvWjTlz5lT4+MyZM5k1axZz5sxh586dREZGMnjwYHJycjzc0qsXGxsLSNhF3aqzpaSv1tChQxk6dGiFj6mqyttvv83kyZMZMWIEAJ9++inNmjVjyZIlPP74455s6lWTbrzwBK+t7FVJTU0lPT2dIUOGuO4zm80MGDCAbdu2Vfo6i8VCdna2280bNGvShAHA0MxM4lJTUex2rZskGiCvrexVSU9PB6BZs2Zu9zdr1ozjx49X+roZM2bw0ksv1Wnbamz5crr+4x9sBLBY4NNPyQoJYe0tt3CwUyeNGycaknpZ2Z0URXH7WVXVcveVNmnSJLKysly3tLS0um5i1ZYvh5Ej0Z0543Z3SHY29y5bRocDBzRqmGiI6mXYIyMjgUsV3ikjI6NctS/NbDYTEhLidtOMzQbPPAOqStk/T86fb1m7Vrr0otbUy7DHx8cTGRnJ+vXrXfcVFRWxadMm+vbtq2HLauDHH+HkyUofVoDQ7Gxiq9gtEaImvHafPTc3l5SUFNfPqamp7N69m/DwcGJjYxk7dizTp0+nbdu2tG3blunTpxMQEMCDDz6oYatroEzXvTLBcjpO1BKvDfuuXbvcru8+btw4AEaNGsUnn3zChAkTKCgo4Mknn+TixYv07t2bb7/91nVVVK9XcrrtcnJKJskIcbUU1YcXPsvOziY0NJSsrKxSy0OBxeZ43KyHKo73XR2bDVq2hFOnHG9ahgpkh4Qwe+xYVF293NsSHmKxWJgxY4bb97gi8i3Sil4Ps2c7/l32rELJf9fecosEXdQa+SZpacQI+O9/oWRsvFN2SAjL7r1XzrOLWiVh19qIEXDsGD+/9hoPACPCwpg9dqwEXdQ6Cbs30Osx33wzXwDfFhVJ113UCflWeQnnYKD8/HzsMpBG1AEJu5do0qQJiqKgqqqsWCPqhIS9hlRVdd1qk8FgcF3ksT7OyRfeT8JeA4XFdk5nFZF20XHLyCnCYq29LrezK5+VlVVr2xTCScJeTdkFVjJyirGVynZhscrZ7GIu5ltrpdLHxcUBkJmZedXbEqIsCXs1FNvsZBY4htUFmnXENDIRFWok0OT4+HIKbVzIu/rAt23bFoCLFy9eXYOFqICEvRqySoLuZ9TRONCIXqdg1OtoHGQkPNAxvSCvyO563pXq0KEDIGEXdUPCfhnFNjv5RY6+eyN/fbnHg8x6GpcEPrvQRkHRle/Dt2vXDpCwi7ohYb+M7EJHtfY36jAZKv64As16gsyOx87nFWOzX1l3vlWrVoBjn92H5yeJOiJhv4wiqyN0geaqP6qwAANGvYJdhawC6xW9V2xsLIqiUFxcLCvNilonYb8Ma0mVNuqrnuuqKAphAY7ufK7FTtEVnJIzmUw0bdoUkK68qH0S9irYVdU11Vyvu/zEdj+jDn+j4yPNvMLq3qJFC0DCLmqfhL0Kzn1vRQFdNVexaFRS3QuL1SsacBMfHw9I2EXtk7BXwZlVQzWqupNRrxBQ6vx7Tcm5dlFXJOxVsJdU9svsrpcT7Oc4RZdfZK/xkfmOHTsCMopO1D4JexWcQa3O/nppZoMOU8lfiDxLzap7mzZtAKnsovZJ2KtgU68s7OAYbAOOI/M1OWfuPNeelZVFcXFxjd9XiMpI2KvgnPSiv4JPKaDkvLzVrlJsq37YIyIiXCuE/v777zV/YyEqIWGvgr2kIlf3SHxpOkXBr+Q0XEFx9Y/KK4riOkiXkZFR4/cVojIS9ipcquwKeRYb53KKyCmwug7cXU6AM+w1HC9/zTXXAHD27NkavU6IqkjYq+Cs7PkWK4fO5HH8fCGHz+az/1QuhcWXP/DmX3IKrsimukbiVUfPnj0BqeyidknYK6GqKnYVrDY7x88Xui7cYNApFNlUDp3JJ7+o6sA7psI6dgEsNejKd+/eHZDKLmqXhL0SzkKcW2jFrjqOrv8hNphOMYH4m3RY7SpHMwpc1b8yfiUz5Woymq5Lly6O987NlQkxotZI2CvhPF3mPNceE2ZGV7JoRbtmgRj0CharnfSsoiq3YzaWVHZr9bvxQUFBRJVc+FG68qK2SNgrYVcvdeUBt7nsBr1Ci3A/ANKzLBRXUbXNJa8rtqmX7QWU5hxJJ115UVsk7JWwlwo6lJ/iGhZgINCsR1XhbHbl1V2vU1zDbWtyvv3aa68FpLKL2iNhr4RdvTQ23mRQUMqca1cUhchQEwDnc4urrNrOPxTFNejK9+rVC4D09PQatVuIykjYK2G3q67hsqZKhtCF+jtWp7HaVTLzKp+/bjRcOgVXXX369AEcYZdhs6I2SNgrYVfVUpW94o9JURQaBxkBuJhfeSCNJWPra3KuPS4ujvDwcOx2O6dPn67264SojIS9EnaVUgfnKh8u2yjAEfbsKkbWOTsGNZnuqigKPXr0ACAtLa3arxOiMhL2StjtKja7itVu52RWAesP/c4PyecoKDNyLsCkcy00mVPJdFbnrLmazm0fOHAgIGEXtUPCXglbSTf+XEERaVmFZBVauZBfzJajF9xCqygKIf6OpahyKll3zhl25+m86nKG/eTJk7K0tLhqEvYKqCULTdpVleKS2TBRIWYMOoWsQiu7T2W7Pd+5Mk1lC1WUng5fk+LevXt3DAYDeXl5spiFuGoS9go4K7DNrmItqajdm4fyp5ZhAKReyCev6FIV9zc5l6GyVViBFUXBmfeaDKzx8/NzDa6Rrry4WhL2CjgH1Fhd89kdY9ybBZuJCHKcWz9yLt/1fH+jDgXHH4nKhsU6q3tNe+N9+/YF4Pjx4zV7oRBlSNgroJYMqHGeKgs06V2Dato0CQTg+MUCVxVXFMU1nbWgkplwztfX9MpQt99+OwBHjhyR/XZxVSTsFbCrjgE1Vrtjfz3AZHA9FhlixqhzTIK5WHDp3LpzDPyVXAmmKoMGDcJgMJCVlcX58+drddvCt0jYK6CqjtNkxaUqu5NOUYgINgOQnm1x3W+q5ii5mi5wFRgY6JrfnpKSUsNXC3GJhL0CztFzVrud8/lFbDhynoMZua7Hm5WEPSP30gSYS+PfK6vsV94FHzZsGODoygtxpSTsFVBLRs9Z7SoXC6zkF9v5z950ks46At8k0HGQ7mJ+kWs/2qi/NJW1wm06/1HztSsZPnw4AMeOHcNqvbJryAkhYa+AiuMAXZHN5jaefcW+dHIsVoLMehTApl5aOVZX8klWdmrNuZkrWIKerl27Eh4eTnFxsRyVF1dMwl4BtWQwTZFNdVXkZkEmbCocOJuLTlFcF4HIsTgqra6Ko+3OQTqln1cTiqJw0003AXDw4MEav14IkLBXyG5Xsdjsri55I38D10Y7LtxwoKQrH2QuGSLrCnvJayuo7KXvupLKDjBq1CjH+x84gN1eu0f8hW+QsFfArkKx3U5RyVDZcH8j7Zo6zq+fzi7EarO7jtA7J8a4FreooLI758UrpZ9XQ4MHDyYoKIi8vDzpyosrImGvgM3uqOqWkrA3DTQR6mfA36jDrsLveUXlDsiVHmBTluvSzzW9HGwpRqOR2267DYD9+/df8XaE75KwV8CmglW1Y7Gq5BfZOJiRR7FNpVmQ45Tb2ZyiS6faSv4gOPfVKyrcNtuVXyCyNGdXPikpSbryosYk7BVQS+ayW2x20i4U8lNqJkt+PU1kyfn1s7kWjLqKK3tFeXYe0a9kwZtqu+mmmwgJCSEvL0/OuYsak7BXwK5CgdVGsc3umrv+8/EsQvwcB+Vyi2yU3UV3Brqi6u38g1B2hdqaMhqN3HvvvQD8+uuvV7Ut4Xsk7BWwqyq5RTaspQbIZBUWYygJcmGxrdSpNMd/rVUE2nmgz3gl134u45lnngHg0KFD5OTkXPX2hO+QsFfAZreTX2yjsNTQV7sK50qGxxZY7a6K7oy2s3obygTaZlddV4M1XWVlB8elobp27Yrdbmf37t1XvT3hOyTsFbDZHd3ywjIXYzxTMvHFYrW7zqc7j767wl6mG19kvbS/rrvKA3ROY8aMARxdeTlQJ6pLwl4Ba0k1zi5ZUy68ZAXZnMJL49KdU1mda8o7r9LqZ3T/SJ29A/PVHp0r5eGHHyYoKIiLFy9y6NChWtuuaNgk7BWwqSq5FisWqx29TmFQm3DAcWAOHPvpllIhVlWVQqvjMXOZsLueZ6y9jzowMJDHHnsMgK1bt9badkXDJmGvgNVu50LJRR/aRwQSFeK4iGNuydBYBcUt7NZS++V+pSq4qqqubnxtVnaACRMmYDAYOHnyJCdOnKjVbYuGScJeAZv9UkVu1difANfQWMd9Bp3iGibrZ9BRUFTSpTcobvvlhSVB1ytXf469rMjISEaOHAnAli1banfjokGSsJehlixH5Ty/3sjPiHPum/MIvL9R57ogRJDZQG7JvrxzcoyTcz06f5PuisfEV+Wll15CURQOHz4sq8+Ky5KwV6DYZsdqs1NUbMNs0F2atqpe6pI7z50Hm/XkuoJ/afkqVVVdFd+/FvfXS2vXrp1rkM0PP/xQJ+8hGg4JexkqjkEw57OLOPV7Lv9csZ+dqRdcjwHoS6q0v1GHXqeQXxLqgFJhL7Kq2FTHefiyR+hr02uvvYbBYCA1NVWG0IoqSdgrYLVDQamLQPx6ItPtcWePPMTPSGGxo8uvKLiWkwbIq+MuvFNcXByjR48GYN26ddhsFS9lLUS9DvvUqVMdV1spdYuMjLy6jaqOEXSlr+eWnuUYTOPMrHO1mUb+BnIKL3Xhnferquqq9qVXpq0r//73vwkODiYjI4Ndu3bV+fuJ+qlehx2gc+fOnDlzxnX77bffrmp7Ko59drtdxWazo6oq53MtqCVXiQHHrDiAUD+ja+CNc5IMQGGx47k6BfyMdVfVnRo3bswrr7wCOPbdc3NzL/MK4YvqfdgNBgORkZGuW9OmTa96m0U2lczMAs6cyiI3x+JYadZ2aYis6+Ccn951JD7Y/1LYnV34gDruwpc2ZswY2rdvj8ViYfXq1R55T1G/1PuwJycnEx0dTXx8PPfffz9Hjx6t9LkWi4Xs7Gy3W0WK7HZ+/91RHbMyC1z363UK5pLhsQadgmp3LHRh1CsElOyvW+2XuvClj87XNb1ez+eff45Op+PAgQOymo0op16HvXfv3ixatIh169axYMEC0tPT6du3b6WXSZoxYwahoaGuW4sWLSp8XrFNRV9mhpqiKBj1OkL9DCiKQpNAE1n5jgoeFmB0VfDckn14s0FxXSXGU3r06MGzzz4LwKpVq2QKrHBTr8M+dOhQ7r77brp27cpNN93EqlWrAPj0008rfP6kSZPIyspy3SoaiKLimJuuLxVUu11FpygY9QpmgyPUTYNMrv31RgGOLryqqq5rtHuyqpf26quv0qZNG/Lz81mxYoXMihMu9TrsZQUGBtK1a1eSk5MrfNxsNhMSEuJ2q4hVVVEUxbXUlNXqWJnGqNe5Fq0INOmx2lV0CgT6Oa/PbsdWcmAuwKTNR2s2m/nqq68wmUwcPXpUhtIKlwYVdovFQlJSElFRUVe1HZvdTn52HhdOpWPJywfVsY+u1zlGz/kZdBQXO1IfFmhEV/KHIavAUdWD/fQeOzBXkc6dOzN79mwANmzYIBeEFEA9D/vzzz/Ppk2bSE1NZceOHYwcOZLs7GzXKqxXpOQab5kZjlFzuRezQHFMUTXpdRh1jv31zHxHF75xkGOue0GxHWvJ4JpgP2268KU9/vjj3H///aiqyn//+1+53LOo32E/efIkDzzwAO3bt2fEiBGYTCa2b99OXFzcVW3XWuYaTgqOiu5vdJxKCzTqsauOg3BBZj2qqroG1wSXGlyjJUVR+OSTT+jWrRuFhYV8/vnn5OXlad0soSHD5Z/ivb744os62a6tgiuxmkvGwYNjPjuohAc6jsIXFDnWmAfvqOpOZrOZtWvXcu2113L27Fk+//xzRo8ejclk0rppQgP1urLXlbIXZ9TrFEx6x756kFmPpWR/PTzIhKqqZJYclQ/201/1hSBqW2RkJBs3biQ4OJjTp0+zdOlSiouLtW6W0ICEvRp0Oh16vYK/QU8jP8c+epBZj59RR0Gx41JRChDiRVW9tA4dOrB27Vr8/PxITU0lISFBAu+DJOwVsJU5N61TFMx6BZNeQV+yeHSTYGO5I/DeVtVL69u3L6tXr8ZsNpOSksKSJUuwWCxaN0t4kIS9AmWPr+n1CkFmAyaDDkV1nIILCzCSV1RS1b3kCPzlDBo0iNWrV7sq/GeffSYH7XyIhL0COsX9YzEadISYDQQZHUNlHQfmIKtkXz3Uy6t6aTfccAMbNmwgKCiIkydP8tFHH8lpOR8hYa9A2Q/FZNRj0utcK9Q0DjKRY7Fhs4NeVz+qeml9+vRhx44dREZGcuHCBRYsWCCr3PgACXsFyl65xWR0VG4/vR6zQYfZoJBdsq8e6m/QdLTclerUqROJiYl06dKFwsJCFi9ezNatW11DhEXDI2GvgNHgHl6zUYe/QcGgU2gabCTHYsdeMrU1UKMx8LUhMjKSnTt3cs8996CqKuvXr2fp0qXk5+dr3TRRB+rvN7WuKGDU6QgKCwUgsFEIJqOeYJNjDHyjAKNrtFyjelrVS/Pz8yMhIYG3334bo9HI4cOHmTt3rnTrGyAJewX0OgVzYABh0c3wCwrEz6jD36B3rExjuTRf3RNLTnmCoig888wzbN++ndjYWHJzc/nss8/45ptv5PRcAyJhL0MBjCX77Dqd4+MJMDn22QP99OSVrELTKKD+V/WyunfvTlJSkmu12l27dvHee+/JxSMbCAl7BcquMBPsZ0CvKK5TcgEmXa1fu81bBAQEsHDhQr799luioqLIzs5m6dKlLF26lAsXLmjdPHEVGuY39ir5GfSENQ4AIKxxAP5GA2H+BopKJsiE+tevU21XYvDgwaSkpPDUU0+h1+s5dOgQ7733HuvXr6ewsFDr5okrIGEvwzmdNTDQTHTzRgQGmgk06zAZHQEPMOkw6n3jYwsICOCdd95hz5499O3bF5vNxtatW5k9ezbbtm2T8fX1jG98a2tCAZPeuc/u+G+QSe+6JLMvVPWyOnfuzJYtW/jqq69o2bIlBQUFfPvtt7zzzjvs2LFDQl9PSNjLUHB04yPCAlAUiAgLIMhkQKdT8DP6TlUvS1EU7rjjDpKTk3n//feJiIggJyeHNWvWMHv2bLZs2SLdey/nm9/cy/Az6Aj0NxIXGUKgv5EAox6dAkFm+bgMBgOPP/44J06cYPbs2URERJCbm8t3333HW2+9xbp167h48aLWzRQVkG9vGc714QNMjkUj/U06Ao16DDqlzi69XB+ZzWaefvpp0tLS+OCDD2jZsiUWi4WffvqJd955h6VLl5KSkiJLWXsR+fZWwKTXERNmpkmQkeZhfvgZ9QSatV0x1luZTCYee+wxjhw5wsqVK+nTpw+qqnLo0CEWL17Mu+++y+bNmyu9+o7wHAl7BfwMjn3ziBAzRr1j9FxdXmO9IdDpdAwbNoyffvqJAwcO8OijjxIQEMDFixf54YcfeOutt/jss8/Yu3cvRUVFWjfXJ8k3uAIGvY7oYDMAMcFm/Aw66sl0da/QsWNHPvroIzIyMliwYAHXXnstqqpy5MgRli9fzuuvv86XX37JwYMH5Ui+BymqD89pzM7OJjQ0lKysLNfVYVQVUs8V8OvpTNSSK8N0iQihbbOAerNAhTdKSUlh/vz5LFmyhNOnT7vuN5lMtG/fng4dOtCmTRvMZrOGrayfLBYLM2bMcPseV0TCXkHYT14sJPF0FkU2Oyadjs7NQmjV1E/22WuBqqrs2LGDjz/+mBUrVnDu3DnXY3q9nvj4eNq1a0e7du1o1KiRdg2tRyTs1VBZ2M/mFHH8XD6ZlmIamY3EhPnTPEwqTm2z2+1s376dxYsX8/XXX7tVfIAmTZrQpk0b2rRpQ2xsrKx3XwkJezVUFvZzeVZOnLu0gEOLxn5EBMsXrS6pqkpSUhLLli3j66+/Zs+ePW6r5uj1elq0aEF8fDwtW7YkJiYGg6FeX+Ok1kjYq6GysF/Mt3LqYiFFVjsmg+M0XHigUePW+paLFy+ybt06VqxYwYYNG/j999/dHjcYDLRo0YK4uDhiY2Np3ry5z1Z+CXs1VBb2HIudC7lFFBbb8DPpaRpkJFCj660LR9VPTk5mzZo1rFmzhp9++qnceXtFUYiKiqJ58+auW1hYmE8cZ5GwV0NlYS+wqpzLuXQuOLqRCYMcifcadrudpKQkvvvuO7777jt27NhRrvKDY9ZedHQ0MTExREdHExUVVWUY6isJezVUFnaLDTKyLy3HFBsuB+e83YkTJ9iyZQvff/8927dv5/Dhw1it1nLPCwoKIjIykqioKCIjI2nWrBnh4eGuVYnqIwl7NVQV9sz8YoqsdvyMOiKCZX+9vrFYLOzZs4ctW7awdetWEhMTOXbsWIVLZRuNRiIiIsrdgoKC6sVugIS9GqoKu92uUmS1ef013ET15eXlsXfvXn7++We2b9/Onj17OHLkSKXDd/39/WnSpAlNmzaladOmNGnShCZNmhAaGupVPQEJezVUFXYAs778dd9Ew2Kz2UhJSWH37t3s3LmTxMREDh8+zKlTpyq9YIbBYCA8PJzGjRu7buHh4YSHh2vSG6hu2OVEpfBper2e9u3b0759e+677z7X/QUFBRw6dIh9+/aRmJjIvn37OHz4MCdPnsRqtZKRkUFGRka57RmNRsLDwwkLC3P913kLDQ3VdGyAVHap7KIGbDYbx44dc/0h2LdvH8nJyRw7doyzZ89e9vJZwcHBNGrUyHULDQ11/Tc0NPSKxgpIZReiDuj1elq3bk3r1q259dZb3R6zWCwcO3aMlJQUDh48yMGDB0lJSeH48eOcOXOGwsJCcnJyyMnJIS0trcLt+/v7ExoaSkhIiOu/ISEhBAcHu/59pYOHpLJLZRceoKoq586dIzU1lSNHjpCcnOz6Q5CWlsbZs2erfY09s9ns+gMQHBxMQEAAP/30kxygq4qEXXiTzMxM0tLSSEtL4+jRoxw9epRjx45x6tQpzpw5w++//17lop7SjReinnDux3ft2rXCx1VVJTs7m9OnT3Pq1ClOnDjB8ePHOXr0KIsXL77s9qWyS2UX9VxF3+OKeM/IACFEnZKwC+EjJOxC+AgJuxA+QsIuhI+QsAvhIyTsQvgICbsQPkLCLoSPkLAL4SMk7EL4CAm7ED5Cwi6Ej5CwC+EjJOxC+AgJuxA+QsIuhI+QsAvhIyTsQvgICbsQPkLCLoSPkLAL4SMk7EL4CAm7ED6iQYR97ty5xMfH4+fnR48ePfjxxx+1bpIQXqfehz0hIYGxY8cyefJkEhMT6devH0OHDuXEiRNaN00Ir1LvL//Uu3dvunfvzrx581z3dezYkTvvvJMZM2a4PddisWCxWFw/Z2VlERsbS1pamlz+SdRb2dnZtGjRgszMTEJDQyt/olqPWSwWVa/Xq8uXL3e7/+mnn1b79+9f7vlTpkxRAbnJrUHe0tLSqsxLvb6K67lz57DZbDRr1szt/mbNmpGenl7u+ZMmTWLcuHGunzMzM4mLi+PEiRNV/0X0cc7KUboHJMrT6nNSVZWcnByio6OrfF69DruTUqavrapqufvAcRF7s9lc7v7Q0FD5EldDSEiIfE7VoMXnVJ1iVa8P0DVp0gS9Xl+uimdkZJSr9kL4unoddpPJRI8ePVi/fr3b/evXr6dv374atUoI71Tvu/Hjxo3jkUceoWfPnvzpT3/igw8+4MSJEzzxxBOXfa3ZbGbKlCkVdu3FJfI5VY+3f071/tQbOAbVzJw5kzNnztClSxfeeust+vfvr3WzhPAqDSLsQojLq9f77EKI6pOwC+EjJOxC+AgJuxA+wqfDLlNjqzZ16lQURXG7RUZGat0szW3evJlhw4YRHR2Noih89dVXbo+rqsrUqVOJjo7G39+fgQMHsn//fm0aW4rPhl2mxlZP586dOXPmjOv222+/ad0kzeXl5dGtWzfmzJlT4eMzZ85k1qxZzJkzh507dxIZGcngwYPJycnxcEvLqJ35Z/XPH//4R/WJJ55wu69Dhw7qxIkTNWqR95kyZYrarVs3rZvh1QB1xYoVrp/tdrsaGRmp/vvf/3bdV1hYqIaGhqrvv/++Bi28xCcre1FREb/88gtDhgxxu3/IkCFs27ZNo1Z5p+TkZKKjo4mPj+f+++/n6NGjWjfJq6WmppKenu723TKbzQwYMEDz75ZPhr2mU2N9Ve/evVm0aBHr1q1jwYIFpKen07dvX86fP69107yW8/vjjd+tej82/mpUd2qsrxo6dKjr3127duVPf/oTrVu35tNPP3VbF0CU543fLZ+s7DI19soEBgbStWtXkpOTtW6K13KerfDG75ZPhl2mxl4Zi8VCUlISUVFRWjfFa8XHxxMZGen23SoqKmLTpk2af7d8tht/NVNjfcXzzz/PsGHDiI2NJSMjg1deeYXs7GxGjRqlddM0lZubS0pKiuvn1NRUdu/eTXh4OLGxsYwdO5bp06fTtm1b2rZty/Tp0wkICODBBx/UsNX47qk3VVXV9957T42Li1NNJpPavXt3ddOmTVo3yavcd999alRUlGo0GtXo6Gh1xIgR6v79+7VuluY2bNhQ4YKPo0aNUlXVcfptypQpamRkpGo2m9X+/furv/32m7aNVlVVprgK4SN8cp9dCF8kYRfCR0jYhfAREnYhfISEXQgfIWEXwkdI2IXwERJ2IXyEhF0IHyFhF1fl5MmTmM1mOnXqhN1uL/f4qVOnaN68OSaTiQ0bNmjQQuEkYRdXpXnz5vz5z38mKSmJFStWuD2WnZ3NrbfeyqlTp/joo48YNGiQRq0UIJd/ErXg6NGjtGvXjmuuuYZff/0VAKvVyq233sr69euZNm0a//znPzVupZDKLq5aq1ateOCBB0hMTGTNmjUA/O1vf2P9+vX89a9/laB7CansolYkJSXRuXNn+vbty5AhQ5gyZQo333wz33zzDQaDzy6b4FUk7KLWjBw5ki+//BKAbt268eOPPxIcHKxxq4STdONFrbntttsACAoKYvXq1RJ0LyNhF7Vi3759PPvss4Bj2aaqrqyzfPlyBg8eTHh4OIqicOzYMQ+10rdJ2MVVO3XqFEOHDqWgoIBp06YB8Oqrr1b6/Ly8PPr161flc0Qd0G5FLNEQZGVlqddcc42qKIq6ePFiVVVVdcCAASqgJiYmVvnapKQkFVBTU1PrvqHCNy//JGpHcXExI0aMYO/evUyfPp2HHnoIgMmTJwNVV3fheRJ2ccX++te/8v333/PEE08wceJE1/2DBw/mj3/8I8uXL+fgwYMatlCUJmEXV+SFF17gs88+Y9iwYRVeunjy5MnY7XamT5+uQetERSTsosY++OADZsyYQa9evfjiiy/Q6/XlnjNs2DC6devG0qVL5cqvXkIG1QjNHDx4kI4dO5KamkrLli21bk6DJ+MYhcdduHCBEydOuM6vHzhwgMzMTGJjYwkPD9e2cQ2YVHbhcZ988gl/+ctfyt2/cOFCRo8e7fkG+QgJuxA+Qg7QCeEjJOxC+AgJuxA+QsIuhI+QsAvhIyTsQvgICbsQPkLCLoSPkLAL4SMk7EL4CAm7ED7i/wPojET1up9OHgAAAABJRU5ErkJggg=="/>
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@@ -8492,7 +8493,7 @@ The c.o.v. is of p is 0.002.
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"/>
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"/>
</div>
</div>
</div>
@@ -8557,7 +8558,7 @@ The c.o.v. is of p is 0.002.
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
<div class="jp-InputArea jp-Cell-inputArea">
-<div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [17]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
@@ -8600,9 +8601,17 @@ The c.o.v. is of p is 0.002.
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
<pre>c:\Users\rlanzafame\Anaconda3\envs\mude-week-8\Lib\site-packages\IPython\core\events.py:82: UserWarning: Creating legend with loc="best" can be slow with large amounts of data.
func(*args, **kwargs)
+c:\Users\rlanzafame\Anaconda3\envs\mude-week-8\Lib\site-packages\IPython\core\pylabtools.py:170: UserWarning: Creating legend with loc="best" can be slow with large amounts of data.
+ fig.canvas.print_figure(bytes_io, **kw)
</pre>
</div>
</div>
+<div class="jp-OutputArea-child">
+<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
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+<img alt="No description has been provided for this image" class="" 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"/>
+</div>
+</div>
</div>
</div>
</div>
@@ -8625,7 +8634,7 @@ The c.o.v. is of p is 0.002.
<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 [21]:</div>
+<div class="jp-InputPrompt jp-InputArea-prompt">In [18]:</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"># fig, axes = plt.subplots(1, 1, figsize=(8, 5))</span>
@@ -8666,7 +8675,7 @@ The c.o.v. is of p is 0.002.
<div class="jp-OutputArea-child">
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
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-<img alt="No description has been provided for this image" class="" 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HHV5x89ehRjDGFhYemev2HDhnTPrVq1Ki1atLAXnBm9x5D+eyytLTExkbi4OKde8/U+62nH9Gr7vtzQoUN588032bBhA+3ataNYsWLcfvvtbN68OcPX46yMPkdpWa78Xr7ee+bMsb7a8ckKZz+b1xMQEJCt50v+oVEjxKN4e3tz++23s2jRIv7555/rFgBpv9wOHz6cbt1Dhw5lemzZrDhy5Ahly5a1LycnJ3Py5El7lhUrVnDo0CFWrVplPwsMcObMmQy3l9FFZVfTuXNnOnfuzMWLF9mwYQPjxo2jW7duVKpUiaZNm1KsWDEOHz6c7nlpZ0Nz4v1IU7p0aWrVqsXSpUvtI19khzGG7777jqCgIBo2bJjtfGmv/dSpU9f9BZ/Z97FYsWJs3Lgx3XpHjhzJVKagoCBGjRrFqFGjOHr0qP3scKdOnfjjjz/sFyFdeeHnlT799FN69uzJq6++6tB+4sSJa14YWKRIEby9venRoweRkZEZrhMeHn7V5xcvXhyLxcLatWszvLD1yrYPP/yQH374gZtvvpl3332XBx98kMaNG6d7Xkbv35EjR/Dz8yM4OBhw/jVfTdr379X2ffmFqz4+PgwePJjBgwdz5swZfvzxR1588UXatm3LwYMHr/rZT/sj7OLFi+kyZ+To0aMZZrk875XtV7alvWe+vr5ZPtZZ+dl0Na4+TmlOnTqVb8dZl6zRGWHxOEOHDsUYw+OPP05iYmK6x5OSkvjuu+8A7MPnfPrppw7rbNq0iZ07d9pHYHClzz77zGH5yy+/JDk52T5+ZtovjyuLgPfee89lGfz9/bn11lvtw4pt27YNgNtvv52YmBi2bt3qsP7HH3+MxWKhdevWLsuQkWHDhnH69GmeeuqpDLs1xMXFXXWijCuNGjWKmJgYnn766Uydxb2e6tWrA2TqSvPMvo+33nor586dSzeywBdffJHlfGFhYfTu3ZuuXbuya9cuEhISuPHGG6lSpQozZsxIVzxdzmKxpPu8/fDDD9f917HVaqV169Zs27aN2rVrpzvL3rBhw3QF1+U6duyIMYZ///03w+fWqlXLvu727dt56qmn6NmzJ2vXrqV27do8+OCDnD59Ot12582b5/DfmHPnzvHdd9/RokULe1cKZ1/z1TRp0oSAgIB0398///xzhl2k0hQuXJj777+fyMhITp06lW5EiMulFW6//fabQ/u3336b4frnzp1L99jnn3+Ol5cXLVu2dGi/3nuW3WN9Ldf6T5KrjxPYTj4cPHiQiIgIp7ch+YfOCIvHadq0KVOnTqV///40aNCAfv36UaNGDZKSkti2bRvvv/8+NWvWpFOnTlSrVo3/+7//45133sHLy4t27dqxb98+hg0bRvny5Rk0aJDL882bNw8fHx/uvPNOduzYwbBhw6hTpw4PPPAAYOtTWKRIEfr27cuIESPw9fXls88+49dff83WfocPH84///zD7bffTrly5Thz5gxvvfWWQ//jQYMG8fHHH9OhQwdGjx5NxYoV+eGHH5gyZQr9+vXjxhtvzPJ+9+/fT5UqVejVq9d1+wn/73//Y9iwYbzyyiv88ccf9OnTxz6hxi+//MJ7773Hgw8+6DCE2pkzZ+x9E+Pj4+0TaqTNTpc2UH92NW7cmMDAQDZs2JCu3+WVMvs+9urVi0mTJtG9e3fGjBlD1apVWbRoEUuWLAHAy+va5zIaN25Mx44dqV27NkWKFGHnzp188sknNG3a1H5WMSoqik6dOtGkSRMGDRpEhQoVOHDgAEuWLLEXbR07dmTWrFlUr16d2rVrs2XLFt54443r/kcF4K233uKWW26hRYsW9OvXj0qVKnHu3Dn++usvvvvuu3T9yi/XvHlz/u///o9HHnmEzZs307JlS4KCgjh8+DA//fQTtWrVol+/fsTHx/PAAw8QHh7OlClT8PPz48svv6R+/fo88sgjLFiwwGG73t7e3HnnnQwePJjU1FRef/11YmNjHT4L2XnNGSlSpAhDhgxhzJgxPPbYY/zvf//j4MGDjBw5Ml23g06dOlGzZk0aNmxIiRIl2L9/P5MnT6ZixYrccMMNV91Ho0aNqFatGkOGDCE5OZkiRYowf/58fvrppwzXL1asGP369ePAgQPceOONLFy4kA8++IB+/frZuyJl5T3LzrG+lpCQECpWrMg333zD7bffTtGiRSlevDiVKlVy+XEC2x8SCQkJOf6HveQRbrtMT8TNoqOjTa9evUyFChWMn5+ffZiy4cOHm2PHjtnXS0lJMa+//rq58cYbja+vrylevLjp3r27OXjwoMP2br31VlOjRo10+7nayAVcMUxR2qgRW7ZsMZ06dTLBwcEmJCTEdO3a1Rw9etThuT///LNp2rSpsVqtpkSJEuaxxx4zW7duTXdVdK9evUxQUFCGr//KUSO+//57065dO1O2bFnj5+dnSpYsadq3b+8wtJgxxuzfv99069bNFCtWzPj6+ppq1aqZN954w6SkpNjXSbtC+4033sjwdV9+9Xdmh0+73OrVq839999vSpcubXx9fU1oaKhp2rSpeeONN0xsbKx9vYoVK9pHfbBYLCY4ONhUq1bN9OjRwz6MXEb5Lj8uWdGjRw8TERGRrv3KUSOMydz7aIwxBw4cMPfee6/983DfffeZhQsXZnjF/5VeeOEF07BhQ1OkSBHj7+9vKleubAYNGmROnDjhsN769etNu3btTKFChYy/v7+pUqWKwxX3p0+fNn369DElS5Y0VqvV3HLLLWbt2rXm1ltvdRjtIKMr89PaH330UVO2bFnj6+trSpQoYZo1a2bGjBlzzfxpZsyYYRo3bmyCgoJMYGCgqVKliunZs6d9hJbu3bsbq9VqduzY4fC8uXPnGsBMmjTJId/rr79uRo0aZcqVK2f8/PxMvXr10n0eMvua00ZAmDt3brrXfOV7kZqaasaNG2fKly9v/Pz8TO3atc13332XbpsTJkwwzZo1M8WLFzd+fn6mQoUKpk+fPmbfvn3Xfa/+/PNP06ZNGxMaGmpKlChhnnzySfPDDz9kOGpEjRo1zKpVq0zDhg2Nv7+/KV26tHnxxRdNUlJSuteRmfcsbf3rHeurvWfX8uOPP5p69eoZf39/h58X2flsXm3UiGHDhpnixYubCxcuZDqf5F8WY65y2bSI5Kq0mc6OHz+eo31tJeds3ryZRo0asWHDhgz7prrKq6++yssvv8yBAweydebL0+zbt4/w8HDeeOMNhgwZ4u44btWqVStOnDjB77//fs31PO09S0lJoWrVqnTr1o2xY8e6O47kAnWNEBFxkYYNG/LAAw/wyiuv8P3337tkm2mzpVWvXp2kpCRWrFjB22+/Tffu3VUEi7jYp59+SlxcHM8++6y7o0guUSEsIuJCEyZMYPr06Zw7d46QkJBsb89qtTJp0iT27dvHxYsXqVChAs8//zwvv/yyC9KKyOVSU1P57LPPsjXihOQv6hohIiIiIh5Jw6eJiIiIiEdSISwiIiIiHkmFsIiIiIh4JF0sl0WpqakcOnSIkJAQl0wPKSIiIiKuZYzh3LlzlClT5pqTD6kQzqJDhw5Rvnx5d8cQERERkes4ePDgNYeaVCGcRWnDIR08eJDQ0FA3p7m2pKQkli5dSps2bfD19XV3HMllOv6eS8fec+nYey4de0exsbGUL1/+usNYqhDOorTuEKGhofmiELZarYSGhuqbwgPp+HsuHXvPpWPvuXTsM3a9bqy6WE5EREREPJIKYRERERHxSCqERURERMQjqY+wiIiI5GkpKSkkJSW5O0aelpSUhI+PDxcuXCAlJcXdcXKcr68v3t7e2d6OCmERERHJk4wxHDlyhDNnzrg7Sp5njKFUqVIcPHjQY+Y5KFy4MKVKlcrW61UhLCIiInlSWhFcsmRJrFarxxR4zkhNTSUuLo7g4OBrTiBREBhjSEhI4NixYwCULl3a6W2pEBYREZE8JyUlxV4EFytWzN1x8rzU1FQSExMJCAgo8IUwQGBgIADHjh2jZMmSTneTKPjvlIiIiOQ7aX2CrVarm5NIXpX22chO/3EVwiIiIpJnqTuEXI0rPhseWQh///33VKtWjRtuuIEPP/zQ3XFERERExA08ro9wcnIygwcPZuXKlYSGhlK/fn3uvfdeihYt6u5oIiIiIpKLPO6M8MaNG6lRowZly5YlJCSE9u3bs2TJEnfHEhERkQKid+/eWCwWLBYLvr6+hIWFceeddzJjxgxSU1MzvZ1Zs2ZRuHDhnAsq+a8QXrNmDZ06daJMmTJYLBYWLFiQbp0pU6YQHh5OQEAADRo0YO3atfbHDh06RNmyZe3L5cqV499//82N6CIiIuIh7rrrLg4fPsy+fftYtGgRrVu35umnn6Zjx44kJye7O578J991jYiPj6dOnTo88sgj3HfffekenzNnDgMHDmTKlCk0b96c9957j3bt2hETE0OFChUwxqR7Tp7tiJ+cDJs2wdat0KABeHmBxXL9G9i+JicTcvAg7NwJfn7XX/9qj/n6go8PeHun/5rBEC1p4/sBGvdRREQ8kr+/P6VKlQKgbNmy1K9fnyZNmnD77bcza9YsHnvsMSZOnMjMmTP5+++/KVq0KJ06dWL8+PEEBwezatUqHnnkEeBSnTJixAhGjhzJp59+yuTJk9m1axdBQUHcdtttTJw4kYCAALe93vwq3xXC7dq1o127dld9fOLEifTp04fHHnsMgMmTJ7NkyRKmTp3KuHHjKFu2rMMZ4H/++YfGjRtfdXsXL17k4sWL9uXY2FjANlRHjk/3ePYsvs2aOf10X+A216W5JlO0KPj7Yzl8mJRatTi1fTv/AHU6dsQ7NBQCAjABAfgWKQKFCmFKloSSJTEVKkDZshAUlEtJPUfa51PTknoeHXvPVZCOfVJSEsYYUlNTSU1NdTjJktuyelLHGGPPfrlWrVpRp04dvv76ax599FEsFguTJ0+mUqVK7N27lwEDBvDss88SFRVFkyZNmDRpEiNGjGDnzp0ABAcHk5qayoULFxg1ahTVqlXj2LFjPPPMMzzyyCPMnj07w/0WVGmfi6SkpHTjCGf2eyDfFcLXkpiYyJYtW3jhhRcc2tu0acPPP/8MwM0338zvv//Ov//+S2hoKAsXLmT48OFX3ea4ceMYNWpUuvalS5fmytiGdW+/neLbt2NJO5NtTMb3/1vGGCwZ3b/Wcy9vu+y53ln4143l1Cn7fZ/t2ykPlAf4/vtMPd9YLBhvb07edBMJJUuS6ufH6RtuICEsjISSJTlftKjtDLRk2bJly9wdQdxEx95zFYRj7+PjQ6lSpYiLiyMxMZH4+HjKlSvnliz//PMPQVk4YZOUlERycrL95NnlKleuTExMDLGxsfYzvgDFihXjhRde4JlnnmHcuHEA+Pn5AZfGy01NTSU2Npb777/f/rzixYszduxYbr/9duLi4px6fflVYmIi58+fZ82aNem6m2T2j6YCVQifOHGClJQUwsLCHNrDwsI4cuQIYPvGmjBhAq1btyY1NZXnnnvumjPWDB06lMGDB9uXY2NjKV++PG3atCE0NDRnXsjl2rd3+qlJSUksW7aMO++8E19f33SPp+8k4thm/3vSGEhNtXXVSElx/HrxIiQlwYULWM6ehdRUzJEjjB02jH27dxMCWIHA/74GA0WAkkApIPy/dosxWJKTKbF9u33/4YsWXcrl50dK9eqk1K1LSp06pNSoQUrduuDvn+FrV5eM6x9/Kbh07D1XQTr2Fy5c4ODBgwQHBxMQEOD0zGGuEBoamqVC2NfXFx8fnwzrBB8fH7y9vQkNDWXlypWMGzeOnTt3EhsbS3JyMhcuXMDb25ugoCACAgKwWCzptrNt2zZGjRrFr7/+yqlTp+xngP/55x8aNWrkMb//Lly4QGBgIC1btkzXLSSjP0IyUqAK4TRXfgCMMQ5td999N3fffXemtuXv749/BsWWr69vvvkh446sIx54wOGvMWMMLVq0IDo6Ot26oUBlbAXyjUAdIACoCrQAUgDvxER8fvsNn99+sz/vIvAbEA1sAX4E9vz3WN26dVm7dm26z4InFsj56bMqrqVj77kKwrFPSUnBYrHg5eWFl5cXwcHBbjvjmdXfHWkjRmQ01fEff/xBeHg4Bw8epGPHjvTt25cxY8ZQtGhRfvrpJ/r06UNKSor9dQMO24mPj+euu+6iTZs2fPrpp5QoUYIDBw7Qtm1bkpKSrrrfgsjLy8s+MseVn/fMfv4LVCFcvHhxvL297Wd/0xw7dizdWWLJWRaLJd1fz1u3bs3wXxVpRfLK6GhWZrAtb6ACUB9oBNT672uJ/742Ah7/b92/gBXAwuhowkJCuHJvlxfInlgUi4jkVxn9XslvVqxYwfbt2xk0aBCbN28mOTmZCRMm2AvXL7/80mF9Pz8/UlJSHNr++OMPTpw4wWuvvUb58uUB2Lx5c+68gAKoQBXCfn5+NGjQgGXLltGlSxd7+7Jly+jcuXO2th0VFUVUVFS6D6Rk3rV+iF2tSL6q1FQS9u7FKzoar99/x3v9erw2bKBqcjJVgf8DEoB1wCZgPbAKiI6OJiQkBLAVxVu2bPGYv5xFRCT3XLx4kSNHjpCSksLRo0dZvHgx48aNo2PHjvTs2ZPt27eTnJzMO++8Q6dOnVi3bh3Tpk1z2EalSpWIi4tj+fLl1KlTB6vVSoUKFfDz8+Odd96hb9++/P7777zyyituepUFgMlnzp07Z7Zt22a2bdtmADNx4kSzbds2s3//fmOMMV988YXx9fU106dPNzExMWbgwIEmKCjI7Nu3zyX7P3v2rAHM2bNnXbK9nJSYmGgWLFhgEhMT3R0ld5w5Y8y335rUJ580KRUr/nfJ36VbosViNoIZCaaGrTu0ueGGG8y5c+dMXFyciYuLM6mpqe5+FS7jccdf7HTsPVdBOvbnz583MTEx5vz58+6OkmW9evUy/Pd7xsfHx5QoUcLccccdZsaMGSYlJcW+3sSJE03p0qVNYGCgadu2rfn4448NYE6fPm1fp2/fvqZYsWIGMCNGjDDGGPP555+bSpUqGX9/f9O0aVPz7bffGsCsWbPGYfsF3bU+I5mt1yzGZDCwbh62atUqWrduna69V69ezJo1C7BNqDF+/HgOHz5MzZo1mTRpEi1btnTJ/mNjYylUqBBnz57NnYvlsiEpKYmFCxfSvn37fN9XLMuMgR07YM0a2LwZVq2CvXsdVtkDfPbf7c//2grSWWKPPv4eTsfecxWkY3/hwgX27t1rnyBLri1tRInQ0NAC8TssM671GclsvZbvuka0atUqw0kxLte/f3/69++fS4kkT7JYoGZN2w1shfH+/bB6Ncydi1m2jCqJiQwHhmO70G4MsDo6murVq/PHH394zA8SERERT6Xf9OIZLBaoVAl69YLvv8dy6hTmo49IbtsWgDuw9SFeBlTfvZubqlUjLi6O+Ph4+y2f/fNERERErkOFcCZFRUURERFBo0aN3B1FXCEoCEvPnvgsXgx79kDfvhgfH+4AvgW++esvxoSEUDY4mOD/bi1atFAxLCIiUoCoEM6kyMhIYmJi2LRpk7ujiKtVrgxTp2L580/M009zzsuL6sBrwL/AeGzDt61bt474+Hi3RhURERHXUSEskiY8HMvkyQSfPMnFd94htVo1goBngf3AWmB01aqkummuexEREXEtFcIiV7AULoz/gAF4xcTAvHmYFi0AuAUYf/QoxwoV4uKrr2LOnXNvUBEREckWFcIiV+PlBV26YFmzhtQDB3i3aFGOA6WSk/F/6SXOFi2KGTsW3DTlp4iIiGSPCuFM0sVyns2rfHn6Hz/O3bVr0xfbVM6Fk5OxvPyyrY/x0KFw4oS7Y4qIiEgWqBDOJF0sJ15eXvwcHc3oo0epDvQCDvj6wvHj8NprEBEBn31mG7NYRERE8jwVwiJZYLFYKFGiBLXq1uVjoGpSEg8CewMDbQVx9+5w++2wa5e7o4qIiORZ+/btw2KxEB0d7dYcKoRFsshisbBlyxbq1q1LEvAlUP38eS6++CIEBMDKlVCjBvTrB8eOuTuuiIjkot69e2OxWOjbt2+6x/r374/FYqF3794O7UeOHOHJJ5+kcuXK+Pv7U758eTp16sTy5cvt62zbto2OHTtSsmRJAgICqFSpEg8++CAnrtEt7++//6Zr166UKVOGgIAAypUrR+fOnfnzzz9d9nrzOxXCIk7w8vJi69atHD16FIBEoNbcucT/8gsprVtDSgpMmwbVq8P779uWRUTEI5QvX54vvviC8+fP29suXLjA7NmzqVChgsO6+/bto0GDBqxYsYLx48ezfft2Fi9eTOvWrYmMjATg2LFj3HHHHRQvXpwlS5awc+dOZsyYQenSpUm4ypCeiYmJ3HnnncTGxjJv3jx27drFnDlzqFmzJmfPns25F5/PqBAWcVJaN4m6desCsHv3boLr1MFn5UqGRERgqlSB06fhiSegZk34/nv1HxYR8QD169enQoUKzJs3z942b948ypcvT7169RzWTTtLvHHjRu6//35uvPFGatSoweDBg9mwYQMAP//8M7GxsXz44YfUq1eP8PBwbrvtNiZPnpyusE4TExPD33//zZQpU2jSpAkVK1akefPmjB071uHC/+eff54bb7wRq9VK5cqVGTZsGElJSfbHR44cSd26dZkxYwYVKlQgODiYfv36kZKSwvjx4ylVqhQlS5Zk7NixDvu3WCxMnTqVdu3aERgYSHh4OHPnzr3m+xYTE0P79u0JDg4mLCyMHj16XPOMtyuoEM4kjRohGbm8m8TlJsTEkLBpE0ycCIULwx9/QKdOcNttsHOnW7KKiORrxkB8vHtuTpzEeOSRR5g5c6Z9ecaMGTz66KMO65w6dYrFixcTGRlJUFBQum0ULlwYgFKlSpGcnMz8+fMxmcxSokQJvLy8+Oqrr0i5xn8lQ0JCmDVrFjExMbz11lt88MEHTJo0yWGdPXv2sGjRIhYvXszs2bOZMWMGHTp04J9//mH16tW8/vrrvPzyy/bCPc2wYcO47777+PXXX+nevTtdu3Zl51V+Bx4+fJhbb72VunXrsnnzZhYvXszRo0d54IEHMvV6nWYkS86ePWsAc/bsWXdHua7ExESzYMECk5iY6O4oBV5qaqqJi4szR48eNYABzLlz52wPnj1rTL9+xvj7GwPGeHkZ88QTxhw5kqOZdPw9l4695ypIx/78+fMmJibGnD9/3tYQF2f7GeqOW1xcpnP36tXLdO7c2Rw/ftz4+/ubvXv3mn379pmAgABz/Phx07lzZ9OrVy9jjDG//PKLAcy8efOuu90XX3zR+Pj4mKJFi5q77rrLjB8/3hy57PdISkqKOX36tElJSbG3vfvuu8ZqtZqQkBDTunVrM3r0aLNnz55r7mf8+PGmQYMG9uURI0YYq9VqYmNj7W1t27Y1lSpVcthXtWrVzLhx4+zLgOnbt6/Dths3bmz69etnjDFm7969BjDbtm0zxhgzbNgw06ZNG4f1Dx48aACza9euDLOm+4xcJrP1ms4Ii7iAxWIhKCjI4S/6Fi1a2P5yDw2FKVNsZ4LbtoXUVHjvPahWDT7/3I2pRUQkpxQvXpwOHTrw0UcfMXPmTDp06EDx4sUd1jH/nd21WCzX3d7YsWM5cuQI06ZNIyIigmnTplG9enW2b99+1edERkZy5MgRPv30U5o2bcrcuXOpUaMGy5Yts6/z1Vdfccstt1CqVCmCg4MZNmwYBw4ccNhOpUqVCAkJsS+HhYURERGBl5eXQ9uxKy4Qb9q0abrlq50R3rJlCytXriQ4ONh+q169OmA7I51TVAiLuJDVarV3k4iOjub48eOX/o0VHg6LF8PChXDTTXD2LDz8MLRpA3//7b7QIiL5gdVqm8nTHTer1anIjz76KLNmzeKjjz5K1y0C4IYbbsBisVy1OLxSsWLF+N///seECRPYuXMnZcqU4c0337zmc0JCQrj77rsZO3Ysv/76Ky1atGDMmDEAbNiwgYceeoh27drx/fffs23bNl566SUSExMdtuHr6+uwbLFYMmxLTU297mu4WtGfmppKp06diI6Odrjt3r2bli1bXne7zlIhLOJCFouFtWvX2pfDwsKoX78+cXFxxMfH24ridu3g11/hxRdtKy1bBg0awOrVbkotIpIPWCwQFOSeWybO2GbkrrvuIjExkcTERNq2bZvu8aJFi9K2bVuioqKIj49P9/iZM2euum0/Pz+qVKmS4fOuxmKxUL16dftz1q1bR8WKFXnppZdo2LAhN9xwA/v378/09q7nyj7DGzZssJ/lvVL9+vXZsWMHlSpVomrVqg63jPpPu4oKYREXCwoKonnz5vbl6OhoQkJCCA4OthfFxscHxo6F6GioVw/OnLFNxPHKK3Dxotuyi4iI63h7e7Nz50527tyJt7d3hutMmTKFlJQUbr75Zr7++mt2797Nzp07efvtt+1dC77//nu6d+/O999/z59//smuXbt48803WbhwIZ07d85wu9HR0XTu3JmvvvqKmJgY/vrrL6ZPn86MGTPsz6latSoHDhzgiy++YM+ePbz99tvMnz/fZa9/7ty5zJgxgz///JMRI0awceNGBgwYkOG6kZGRnDp1iq5du7Jx40b+/vtvli5dyqOPPnrNi/2yS4WwiIulnRU+d+5cutEk0opi+1niqlUxq1fD//5nG2t4+HBbV4lDh9wTXkREXCo0NJTQ0NCrPh4eHs7WrVtp3bo1zzzzDDVr1uTOO+9k+fLlTJ06FYCIiAisVivPPPMMdevWpUmTJnz55Zd8+OGH9OjRI8PtlitXjkqVKjFq1CgaN25M/fr1eeuttxg1ahQvvfQSAJ07d2bQoEEMGDCAunXr8vPPPzNs2DCXvfZRo0bxxRdfULt2bT766CM+++wzIiIiMly3TJkyrFu3jpSUFNq2bUvNmjV5+umnKVSokENfZFezGHsHRrmWqKgooqKiSElJ4c8//+Ts2bPX/GDnBUlJSSxcuJD27dun68sjucMYQ0JCAsYYWrRokeFUknXr1mXtmjUEffUVlieftA3VY7XC+PHQv7/T/5LT8fdcOvaeqyAd+wsXLrB3717Cw8MJCAhwd5w8LzU1ldjYWEJDQ3O0cMwsi8XC/Pnzueeee3JsH9f6jMTGxlKoUKHr1mvuf6fyicjISGJiYti0aZO7o0g+kjaaRHBwMFu3br36WeLQUOq//TYJK1di6taFhAQYMADuvx9c2F9LRERELlEhLJJLLBaLvSCOi4tLVxRHR0cTdPPNtLRaMSNH2s4Ez5sHtWvDjz+6LbeIiEhBpUJYJJdd7yzxTz//TMKQIbBxIzRqBLGxtpEmPv7YfaFFRESywBiTo90iXEWFsIgbXX6W+OjRo44PNmwIa9bYukckJ0OvXtC7t60PsYiIiGSbCmGRPCDtLHEa+zWsAQG22eeefdbWVeKjj+Dmm+H3392UVEREpOBQISySB9mnZwbw9bWNILFiBYSFQUwMNGkCS5e6N6SISC7IzGxl4plc8dnwcUEOEXGBtOmZ06aVPH78uP0ssdVqxdKqlW1GugcftM1C17YtdO0K77wDxYq5NbuIiKv5+fnh5eXFoUOHKFGiBH5+flednldsRWFiYiIXLlzIE8On5SRjDImJiRw/fhwvLy/8/Pyc3pYKYZE8Im0ijpCQEMA2PXOaunXrsnbtWizBwVh/+AFLZKStm8Ts2bB5M6xaBWXKuCm5iIjreXl5ER4ezuHDhzmkSYauyxjD+fPnCQwM9Jg/GKxWKxUqVMhW4a9COJMun1BDJKekTc+8bt06h/a0GekAmjdvbiuKe/eG7t1h925bv+Fvv4X69d2QWkQkZ/j5+VGhQgWSk5P1+/c6kpKSWLNmDS1btsz3k6lkhre3Nz4+Ptku+lUIZ1JkZCSRkZH2mUpEckLaWeGEhASADGekW7duna3bRKNGWJcuxdK5M/z1l60YHjwYxo619SsWESkALBYLvr6+HlHcZYe3tzfJyckEBATovcqCgt2JRCQfShtB4vKxhuPi4hyGVwsLCyM4OJj6Dz9M/NKlpLRuDSkp8MYbmHbt4OBBN74CERGR/EGFsEgel1YYlyhRgubNmzs8Fh0dTXDlyvisXEkv4AJgWb4cKlTAsmiRW/KKiIjkFyqERfKJtG4TGU3PDPAx0BHY8d+yd7dulP7pp1xOKSIikn+oj7BIPnL5xBtbt2619yUGiI+PJywsjPrAMqBlfDw3v/kmyUWKwNChtgk5RERExE5nhEXyqcv7El/edSIRaAu8+996Pi+9hHn1VTcmFRERyZtUCIsUEJd3nTh+7hxvVanCqLTHXn4ZXnwREhPdmlFERCQvUSEsUoCknSUODg5m46ZNjASmpz04bpxtauZjx9wXUEREJA9RISxSQKUNMv4YkBQZCf7+sG0bNGxoG3dYRETEw6kQFvEAia+/DuvWQalStjGGb7sNDhxwdywRERG3UiEs4gHi4+OJr16dhDVrMJUq2YrhZs1g+3Z3RxMREXEbFcKZFBUVRUREBI0aNXJ3FJEsS5uJLujGG7m/eHFMtWrw779wyy22M8UiIiIeSIVwJkVGRhITE8OmTZvcHUUkU6xWKzfddFO69nmbN5OwcKGtr3BsLLRvDzExbkgoIiLiXiqERQooi8XCq6++yunTp4mLi+Po0aP2x2657z7MihVQq5atGO7cGU6edGNaERGR3KdCWKQAu3zSjRIlStinZY6Ojub4+fMkzJmDCQqyjSJRrx7s3u3ewCIiIrlIhbCIh0ibcCNNWFgYQRER3BIfz2lfX9sFdC1bqpuEiIh4DBXCIh4kKCiI5s2bO7T9DNRMSiL5hhvgyBFo0ABmzXJLPhERkdykQljEg1w+DfPl/YYPARV272ZXUBBcuACPPAJ3323rPywiIlJAqRAW8TBX9htOO0N8GKgVH0/i4MG2Fb/7Dm69FYxxX1gREZEcpEJYxIOlnSFOOzOcBCSOGgWffQbe3hAdDR07wrlzbs0pIiKSE1QIi3i4tDPEaVq0aIHp2hWmTrU1LFxoOzOckOCmhCIiIjlDhbCIYLVaHYZWS0hIgMcfh8WLISAAtm2znRk+f969QUVERFxIhbCIpBtaza5tW/j6a9v9lSttE3Ds35+74URERHKICmERAWzFcIbat4fZs8HXF/bsgVat4PjxXM0mIiKSE3zcHUBE8p74+HjHhk6dsGzZQkDHjnjt20dqs2acX7IEwsIyfL7Var16YS0iIpJHqBAWkXTCrlLg1gW2AV5//cXaKlXoAKRmsF7z5s1Zu3atimEREcnT1DVCRADbWdwrZ527UjTQEtswa3cBswG/DNZbt26d7YI7ERGRPCxLZ4S//fbbLO/gzjvvJDAwMMvPy2uioqKIiooiJSXF3VFEckTaBXOZKWBTvvwSnz59eMAY7qtfnwtLlkBgIPHx8fazyUYTcYiISB6XpUL4nnvuydLGLRYLu3fvpnLlyll6Xl4UGRlJZGQksbGxFCpUyN1xRHLElWMKX9Ujj0DhwnDvvXhv3UpQv37w5ZcOq7Ro0YKtW7eqe4SIiORZWe4aceTIEVJTUzN1s1qtOZFZRPKCLl3gm2/AYoGvvoJBg7AGBKQfj1hERCSPylIh3KtXryx1c+jevTuhoaFZDiUi+cTdd8OYMbb7b72FpVs31q5ZY384Pj5eXSRERCTPylIhPHPmTEJCQgCYPHkyhw4duub6U6dOpXjx4s6nE5G8b+hQmDjRdv/LL7HWr0/Afw+FhYXZpmxWMSwiInmQ06NGDB48mBYtWvDPP/84tCcmJrJp06ZsBxORfMJigUGDYPRowDa02vrQUNJ6BmsECRERyauyNXzaXXfdRcuWLR2K4dOnT9OkSZNsBxORfGbYMPj4YwDqxsaSkMWLa0VERHKb04WwxWJhxIgR9OrVK10xrH+DinioHj1g8GAAAhYsYAXgi62vcNpNPx9ERCSvyPaEGhkVwxouScSDTZgAkycD0BpYBVQMCyM4OJjg4GD1GRYRkTzD6UL48l9klxfDBw4ccEkwEcnHnn4a89lnADQDzgON/ntIfYZFRCSvyNKEGpcbO3asw8D7I0aMAKBDhw7ZTyUi+Z6lWzfM2bNY+vcHYCNQE9iBratEGqvVqv8iiYiIWzh9Rnjo0KHpZqAaMWIETz31lH2INRHxbJZ+/eCPP6BqVQC+wvbXd5i6SoiISB6Q7T7CV3r55Zc5c+aMqzcrIvlVtWrw1VcYb2+qAxuAwpc9rK4SIiLiLi4vhEVE0qlTB8snnwDQADhZsiRHrxiDXEREJLepEBaR3NG1K/z4IwBex45RvHVr5y9SEBERcYFsF8IpKSn89ttvJCcnuyKPiBRkt98Ob74JgNfu3WwB/HAcZzijm/oQi4hITsh2Ifzdd99Rr1495syZ44o8IlLQPfMMzJoFQG3gRxwvnsvopgvqREQkJ2S7EP7oo48oUaIEs/77xSYicl29emHmzQOgBfA14H2N1XVBnYiI5IRsFcInTpxg0aJFzJo1i9WrVztMsywici2WLl0wzz8PwL1AYtWqxB05QlxcnP129OhR94YUEZECLVuF8Oeff07NmjW56667aNGiBR9//LGrcomIB7C89hqMGweA119/EdSyJUF+fgQFBdlvadQ1QkREXC1bhfBHH31Ez549AejevbsKYRHJuhdegE8/td3/80+oVQvOnUu3mvoJi4iIqzldCP/+++/8/vvvdOvWDYD//e9/HDx4kF9++cVl4XJKly5dKFKkCPfff7+7o4gIwMMPw4QJtvu7dkGxYvDnn1itVurWrQtAdHS0+gmLiIhLOV0Iz5o1i7Zt21K8eHEAgoODueeee5g5c6bLwuWUp556SmevRfKawYPhpZds95OSoEULLEePsnbtWvfmEhGRAsupQjglJYXPPvvM3i0iTffu3fnyyy9JTEx0Sbic0rp1a0JCQtwdQ0SuNGYM/PUXWK1w7BiULo3PihXuTiUiIgWUU4XwsWPH6NevH3fffbdDe9u2bRk8eDBHjhxxOtCaNWvo1KkTZcqUwWKxsGDBgnTrTJkyhfDwcAICAmjQoIHOGIkUJFWqwFdf2Rf977+fG90YR0RECi6nZjgtXbo0w4cPT9fu5eXFyy+/nK1A8fHx1KlTh0ceeYT77rsv3eNz5sxh4MCBTJkyhebNm/Pee+/Rrl07YmJiqFChAgANGjTg4sWL6Z67dOlSypQpk618IpIL2rWD2FioWxfL33+zDqiO7edDdlitViwWi0siiohI/udUIZyT2rVrR7t27a76+MSJE+nTpw+PPfYYAJMnT2bJkiVMnTqVcf8Nw7RlyxaX5bl48aJDUR0bGwtAUlISSUlJLttPTkjLl9dzSs7I98c/IAC++gqfhg0pnprKCaBpWBgbsrHJZs2asXLlygJfDOf7Yy9O07H3XDr2jjL7PuS5QvhaEhMT2bJlCy+88IJDe5s2bfj5559zZJ/jxo1j1KhR6dqXLl2K1WrNkX262rJly9wdQdwovx//UkOG0Hj8eADWAx2BH5zc1s8//8z8+fMJCAhwVbw8Lb8fe3Gejr3n0rG3yewoQ1kuhB966CGGDx9ORERElkNl14kTJ0hJSSEsLMyhPSwsLEv9ktu2bcvWrVuJj4+nXLlyzJ8/n0aNGmW47tChQxk8eLB9OTY2lvLly9OmTRtCQ0OdeyG5JCkpiWXLlnHnnXfi6+vr7jiSywrM8W/fnuRatfDp0QOA74GzMTGY0qUzvYm073Wwff9fPlFHQVRgjr1kmY6959Kxd5T2H/zryXIh/OWXX7Jq1SpWrFiRYTFsjOHcuXM5WiRe+W9NY0yW/tW5ZMmSTK/r7++Pv79/unZfX99880HLT1nF9QrE8e/e3dZv+L/hGgs1bAj79kGJEpl6+uWvv0C8H5nkSa9VHOnYey4de5vMvgdOjRpRp04dWrduzY4dO9I9duzYMYoUKeLMZq+rePHieHt7pzv7e+zYsXRniUWkgClWDL75xnY/IQFKloTDh92bSURE8rUsF8IWi4VZs2Zx22230bp1a37//fd06+TUNKh+fn40aNAgXf+XZcuW0axZsxzZZ5qoqCgiIiKu2oVCRHLB3XfbpmROU6YMvPlmljYRHx+f7qapm0VEPFOWC2FjDN7e3nz22Wfcfvvt3HbbbemK4exckR0XF0d0dDTR0dEA7N27l+joaA4cOADA4MGD+fDDD5kxYwY7d+5k0KBBHDhwgL59+zq9z8yIjIwkJiaGTZs25eh+ROQ6xo2DadMuLT/7LNxyS6afHhYWRnBwsMOtRYsWKoZFRDyQ01Mse3l58dlnn3HHHXdw2223sX37dpcE2rx5M/Xq1aNevXqArfCtV6+efdziBx98kMmTJzN69Gjq1q3LmjVrWLhwIRUrVnTJ/kUkH3jiCTh06NLyunVgscDx4xmubrVaad68+VU3t27dukxfYSwiIgVHli+Wu/xsr5eXF59++indu3fntttuY/ny5dnuq9uqVavrnpnp378//fv3z9Z+RCSfK10aUlPh5pth82ZbW3i4bWrmK4Y2tFgsrF27Nl2xGx8fr+sLREQ8mFNdIxw28F8xfOedd3L77bfbuzSIiOQ4iwU2bYIXX7Qtx8dDUBDExWWwqoWgoKB0NxER8VxZLoR/+OEHChUq5LiR/4rhNm3aZDgtckGgi+VE8rCxY+Hy6wRatnRfFhERyTeyXAi3a9cuw3F1vby8+OSTT+jcubNLguU1ulhOJI+bOhVeesl2f9u2S/dFRESuwumL5TLc2H9nhtevX+/KzYqIZM6YMZdGkHj1Vfjll0w/VcOoiYh4niwVwr/99hupqanXXMdisXDzzTcDsGPHDpKTk51PJyKSVYsXX7rfpAn8+mumnhYWFqZh1EREPEyWCuF69epx8uTJTK/ftGlT+/i/IiK5IigI9u69tFy3LlzlIt4rh1XTMGoiIp4lS8OnGWMYNmwY1iuGJrqaxMREp0LlRVFRUURFRZGSkuLuKCJyPZUq2c4M33WXbblePfj+e+jQwWG1tGHVjh8/rmHUREQ8UJYK4ZYtW7Jr165Mr9+0aVMCAwOzHCovioyMJDIyktjY2HSjZohIHtS2LcyZAw8+aFvu2BGmT4dHH3VYLW1YNRER8TxZKoRXrVqVQzFERHLAAw9A5cqQNuxhnz62fsMREe7NJSIieUKWR404f/48kZGRlC1blpIlS9KtWzdOnDiRE9lERLKvYUPYt+/Sco0al2aiExERj5blQnj48OHMmjWLDh068NBDD7Fs2TL69euXE9lERFyjYkVYs+bScqNG0LUraIQIERGPlqWuEQDz5s1j+vTpPPTQQwB0796d5s2bk5KSgre3t8sDioi4RIsWtgvmunWD2Fj44gv48Uc4eNDdyURExE2yfEb44MGDtGjRwr5888034+Pjw6FDh1waLK/RFMsiBUCHDnD2rO1COoATJ6BXL4dV4uPjnb5pDGIRkfwly2eEU1JS8PPzc9yIj0+BnzhDo0aIFCCLFkHz5rB+PXz5Jf6XDYuYnWHUmjdvztq1a7FYLK5IKSIiOSzLhbAxht69e+Pv729vu3DhAn379nUYgmjevHmuSSgi4moWC6xaBf/9HPP5+muO+vlxY2IiZ7Ox2bQJOTQcm4hI/pDlQrjXFf9GBFs/YRGRfMXPDxISbBfSHT9OycREzgDxZ86AT9Z+NMbHx2tCDhGRfCjLhfDMmTNzIoeISO4LDIRjx2DQIJg8GYCgwoXh8GEoVcqt0UREJOdl+WI5EZECZ9IkeOKJS8ulS8PGje7LIyIiuUKFsIgIwNSp0KPHpeXGjd2XRUREcoUKYRERsF1A9/HH8N8Y6fa2y0aUEBGRgkWFcCZpHGERDzF7tuNyFi+cExGR/EOFcCZFRkYSExPDpk2b3B1FRHLalRNjaFxgEZECSYWwiEhGUlMdly0WGDPGPVlERCRH5Egh7OXlxW233caWLVtyYvMiIjnPYklfDA8bBhUqXPNpmmZZRCT/yJFCeMaMGdx666089dRTObF5EZHcYbHYuklMn36p7eDBa54ZbtGihYphEZF8IkcK4d69ezNixAjWrVuXE5sXEcldjz4KZy+bfHnYMKhSxb5otVqpW7cuANHR0SQkJORyQBERcYbThXDv3r1Zs2aNK7OIiORdoaHw6aeXlv/+G774AgCLxcLatWvdFExERJzldCF87tw52rRpww033MCrr77Kv//+68pcIiJ5z8MPw4kTl5a7doUjRwBbMSwiIvmL04Xw119/zb///suAAQOYO3culSpVol27dnz11VckJSW5MmOeoHGERQSAYsXgu+8uLZcuDefPuy+PiIg4LVt9hIsVK8bTTz/Ntm3b2LhxI1WrVqVHjx6UKVOGQYMGsXv3blfldDuNIywidh07wg03XFq2Wh37EIuISL7gkovlDh8+zNKlS1m6dCne3t60b9+eHTt2EBERwaRJk1yxCxGRvOXPP6FcOfui38svuzGMiIg4w+lCOCkpia+//pqOHTtSsWJF5s6dy6BBgzh8+DAfffQRS5cu5ZNPPmH06NGuzCsiknccPAgBAQD4zpzJYcDXvYlERCQLfJx9YunSpUlNTaVr165s3LjRPnTQ5dq2bUvhwoWzEU9EJI/76itbVwmgFJAInP/tN2ja1K2xRETk+pw+Izxp0iQOHTpEVFRUhkUwQJEiRdi7d6+zuxARyfs6dIDDhx2aAps1g9dfd1MgERHJLKcL4VtvvRV/f/907cYYDhw4kK1QIiL5SqlSxMfF0f/ythdegJo13ZVIREQywelCODw8nOPHj6drP3XqFOHh4dkKJSKSH00FHErfHTts0zSLiEie5HQhbIzJcAD5uLg4Av67eERExNPsABJ+/92xUSNKiIjkSVm+WG7w4MGAbRalYcOGYbVa7Y+lpKTwyy+/XLXPsIiIJzCVKoExl84Gjx0L7dtDs2ZuzSUiIo6yXAhv27YNsJ0R3r59O35+fvbH/Pz8qFOnDkOGDHFdQhGR/GrNGmjZ0na/eXNbcSwiInlGlgvhlStXAvDII4/w1ltvERoa6vJQIiL5WXx8vO1O/fr4d+iAzw8/AGBuvRXL6tVuTCYiIpdzehzhmTNnujJHnhcVFUVUVBQpKSnujiIieVxYWJjDctp5YMuaNZgSJbAcPgw+Tv/4FRERF8nST+LBgwfzyiuvEBQUZO8rfDUTJ07MVrC8JjIyksjISGJjYylUqJC744hIHmO1WmnevDnr1q1L91gR4PR/9y0nTkBYGJw8mav5REQkvSwVwtu2bSMpKcl+X0REbCwWC2vXriUhISHdY/Hx8VQJC2NPWsOpU3DPPbBgQS4mFBGRK2WpEE7rH3zlfRERsRXDQUFBGT72NxAAXEhr+OYb6NULPvool9KJiMiVstw1IjMsFgsTJkxwKpCISEF1EUjYvh1rrVq2ho8/hrfegsKF3RlLRMRjZblrRGZkNNGGiIiACQ+HjRvh5pttDUWKQGqqZqATEXEDp7tGiIiIkxo1clweOhRee809WUREPJjTUyyLiEg2XD4U4+uvw9Gj7ssiIuKhNHyaiIg7eHnBunW2GecASpVSFwkRkVyWI8OnqY+wiEgmNGsGt9wCP/1kW/bygrFj4cUX3ZtLRMRDaPg0ERF3WrvW8SzwSy/ZbtOmQe/e4O/vtmgiIgWdS/oIG2Mwxlx/RRERSc8YW0F8ub59ISDAPXlERDxEtgrh6dOnU7NmTQICAggICKBmzZp8+OGHrsomIuI5brkFzpyB++93bLdY4Oef3RJJRKSgy1LXiMsNGzaMSZMm8eSTT9K0aVMA1q9fz6BBg9i3bx9jxoxxWUgREY9QqBDMnWs7Q+x12XmK5s0hLg6uMmudiIg4x+lCeOrUqXzwwQd07drV3nb33XdTu3ZtnnzySRXCIiLOslhsI0gMGQJpI/BERMD+/e7NJSJSwDjdNSIlJYWGDRuma2/QoAHJycnZCiUi4vEsFpgwAcqVsy0fOABLlrg3k4hIAeN0Idy9e3emTp2arv3999/n4YcfzlaovCgqKoqIiAgaXTkjlIhITvrtt0v3773XfTlERAqgLE+okcZisfDhhx+ydOlSmjRpAsCGDRs4ePAgPXv2dG3KPCAyMpLIyEhiY2MpVKiQu+OIiKcoUgRat4aVKyEhwXam+J9/oGxZdycTEcn3sjyhxuUaNGgAwJ49ewAoUaIEJUqUYMeOHS6KJyIifPEFhIVdWi5XDpKTwdvbfZlERAoApyfUEBGRXFKyJJw+DU2awK5dtjYfH9voEiIi4jSXTKghIiI5rHBh+OMPCA291DZ0qNviiIgUBE4Pn5YmJiaGAwcOkJiY6NB+9913Z3fTIiJypVOnbGeDAV57DVavhhUrNAudiIgTnC6E//77b7p06cL27duxWCz2KZYtFgtgG15NRERczNsbdu6Em26yLa9fD1YrJCZeKpBFRCRTnO4a8fTTTxMeHs7Ro0exWq3s2LGDNWvW0LBhQ1atWuXCiCIi4qB6dbj84mVjwNcXPvrIfZlERPIhpwvh9evXM3r0aEqUKIGXlxdeXl7ccsstjBs3jqeeesqVGUVE5Ep169qmXb5c795w4YI70oiI5EvZmlkuODgYgOLFi3Po0CEAKlasyK60q5pFRCTnBAXZzgYvXnyp7cMP3ZdHRCSfcboQrlmzJr/9N+NR48aNGT9+POvWrWP06NFUrlzZZQFFROQ62ra9dP/JJ21jDIuIyHU5fWXFyy+/THx8PACvvPIKnTp1okWLFhQrVow5c+a4LKCISEGS9nPT1fx698Z31iwAfK1WmDqV+Ph4fH19c2R/7mK1Wu0XZYuIZJfThXDby85AVK5cmR07dnD69GmKFCmiH1IiIlcRdvkMcS52+fQanfv1455+/fgmx/bmHnFxcQQFBbk7hogUENmaUGP69OnUrFmTgIAAAgICaNmyJdOnT3dVNhGRAsFqtdK8efMc348FeOuy5QXAUeCWHN+ziEj+5PQZ4WHDhjFp0iSefPJJmjZtCthGkhg0aBD79u1jzJgxLgspIpKfWSwW1q5dS0JCQq7sL+777wl+6CEASgJrvL1J+OsvKFEiV/afk6xWq7sjiEgB4nQhPHXqVD744AO6du1qb7v77rupXbs2Tz75pAphEZHLWCyWXPuXftK99/LD55/TbsECvL78EktKCkFvvAFvv22bkENERIBsDp/WsGHDdO0NGjQgWVcsi4i4VbLVSsqnn4K/v61hyhTbzHPGXPuJIiIexOlCuHv37kydOjVd+/vvv8/DDz+crVAiIuIiS5c6LpcvD+++C1Onwj//uCeTiEgekaWuEYMHD7bft1gsfPjhhyxdupQmTZoAsGHDBg4ePEjPnj1dm1JERJzTsiWkpoLXf+c9/v3XNtYwQP/+OkMsIh4tS4XwtsvntsfWDQJgz549AJQoUYISJUqwY8cOF8UTEZFss1ggJgaGD7cVxOvXw8GDtsdiYyE01L35RETcJEuF8MqVK3Mqh4iI5KSbboK5c233k5MhbaKNQoVg0ybI4JoPEZGCLlvjCOdHBw8epFWrVkRERFC7dm3mpv1iEBHxFD4+cMMNl5YbNYKhQ92XR0TETZwePg3gzJkzTJ8+nZ07d2KxWLjpppvo06cPhQoVclU+l/Px8WHy5MnUrVuXY8eOUb9+fdq3b6+ZikTEs2zZAi+8YBtNAuC112DYMNA4vSLiQZw+I7x582aqVKnCpEmTOHXqFCdOnGDSpElUqVKFrVu3ujKjS5UuXZq6desCULJkSYoWLcqpU6fcG0pEJLeFhEBUFBw9eqlNJwRExMM4XQgPGjSIu+++m3379jFv3jzmz5/P3r176dixIwMHDnQ60Jo1a+jUqRNlypTBYrGwYMGCdOtMmTKF8PBwAgICaNCgAWvXrnVqX5s3byY1NZXy5cs7nVdEJF8rWRKKFLm0PH68+7KIiOSybJ0Rfv755/HxudS7wsfHh+eee47Nmzc7HSg+Pp46derw7rvvZvj4nDlzGDhwIC+99BLbtm2jRYsWtGvXjgMHDtjXadCgATVr1kx3O3TokH2dkydP0rNnT95//32ns4qIFAjHj1+6//zz8MgjsGsXnDvnvkwiIrnA6T7CoaGhHDhwgOrVqzu0Hzx4kJCQEKcDtWvXjnbt2l318YkTJ9KnTx8ee+wxACZPnsySJUuYOnUq48aNA2DLli3X3MfFixfp0qULQ4cOpVmzZtdd9+LFi/bl2NhYAJKSkkhKSsrUa3KXtHx5PafkDB1/z+XUsY+JwTciwnZ/1izbDUjavx9Kl3ZtQMkx+r73XDr2jjL7PjhdCD/44IP06dOHN998k2bNmmGxWPjpp5949tln6dq1q7ObvabExES2bNnCCy+84NDepk0bfv7550xtwxhD7969ue222+jRo8d11x83bhyjRo1K17506VKs+eSikmXLlrk7griRjr/nyuqxLzRxIs2GDcNiDL4JCQCk1qzJ4k8+yYl4koP0fe+5dOxtEv77GXY9ThfCb775JhaLhZ49e5KcnAyAr68v/fr147XXXnN2s9d04sQJUlJSCAsLc2gPCwvjyJEjmdrGunXrmDNnDrVr17b3P/7kk0+oVatWhusPHTrUYUa92NhYypcvT5s2bQjN44PQJyUlsWzZMu68805808YMFY+h4++5snXsBwwAwBQvjiU2Fv9z52jfrp1tUg7J8/R977l07B2l/Qf/epwuhP38/HjrrbcYN24ce/bswRhD1apVc+UsqeWKH8jGmHRtV3PLLbeQmpqa6X35+/vj7++frt3X1zfffNDyU1ZxPR1/z5WtY791K1StattOSAjExV2ahEPyPH3fey4de5vMvgdOXSyXlJRE69at+fPPP7FardSqVYvatWvneBFcvHhxvL290539PXbsWLqzxCIikg1Vqly6n5gIH33kviwiIjnEqULY19eX33//PdNnYV3Fz8+PBg0apOv/smzZsute9CYiIll0+b8WH38cevWCxYvdl0dExMWcHj6tZ8+eTJ8+3ZVZAIiLiyM6Opro6GgA9u7dS3R0tH14tMGDB/Phhx8yY8YMdu7cyaBBgzhw4AB9+/Z1eZbLRUVFERERQaNGjXJ0PyIieUZICHz//aXljz+Gdu0gC93LRETyMqf7CCcmJvLhhx+ybNkyGjZsmG6K4okTJzq13c2bN9O6dWv7ctqFar169WLWrFk8+OCDnDx5ktGjR3P48GFq1qzJwoULqVixorMvJVMiIyOJjIwkNjY2T08hLSLiUh06wLp18N13tmmYAVauhNtvd28uEREXcLoQ/v3336lfvz4Af/75p8Nj2eky0apVK4wx11ynf//+9O/f3+l9iIhIFjRrZrulFcJ33AF//eXYj1hEJB9yuhBeuXKlK3OIiEhed/fd8O23tvtVq0LHjrYzxSIi+VSW+wgnJCQQGRlJ2bJlKVmyJN26dePEiRM5kS1PUR9hEfF48+fDXXddWv7+ezh50n15RESyKcuF8IgRI5g1axYdOnTgoYceYtmyZfTr1y8nsuUpkZGRxMTEsGnTJndHERFxDy8vWLQIjh271LZ7t/vyiIhkU5a7RsybN4/p06fz0EMPAdC9e3eaN29OSkoK3t7eLg8oIiJ5TIkSUKoUHDkCTZvCH39AtWruTiUikmVZPiN88OBBWrRoYV+++eab8fHx4dChQy4NJiIieVifPpfuV68O17nIWUQkL8pyIZySkoKfn59Dm4+PD8nJyS4LJSIiedyYMY79ha+Y6EhEJD/IctcIYwy9e/fG39/f3nbhwgX69u3rMJbwvHnzXJNQRETypi+/hNBQ2/3Vq6FNG/fmERHJoiwXwr169UrX1r17d5eEycuioqKIiooiJSXF3VFERPKGkBC45x5YsABefRV69lRfYRHJV7JcCM+cOTMncuR5mllORCQDDz9sK4TB1lVi1y64ovuciEheleU+wiIiInb33w8REbb7+/bBwIHuTCMikiUqhEVEJHu++OLS/alT4a23bEOriYjkcSqERUQke2rVgilTLi0PHAg33ui2OCIimaVCWEREsq93b3jxRbBYbMvnztnaTp1yZyoRkWtSIZxJUVFRRERE0KhRI3dHERHJewIDYexYOHv2UttHH0H9+qDRdkQkj8pWIbx27Vq6d+9O06ZN+ffffwH45JNP+Omnn1wSLi+JjIwkJiaGTZs2uTuKiEjeFRIC69ZdWt6/H26/HX780X2ZRESuwulC+Ouvv6Zt27YEBgaybds2Ll68CMC5c+d49dVXXRZQRETymWbN4NChS8urV8Odd8KFC+7LJCKSAacL4TFjxjBt2jQ++OADfH197e3NmjVj69atLgknIiL5VOnSsGULPPHEpbbXXoPZs21nh1NT3ZdNROQ/ThfCu3btomXLlunaQ0NDOXPmTHYyiYhIQVC/Pkybdml51Cjo1s12dvibb9yXS0TkP04XwqVLl+avv/5K1/7TTz9RuXLlbIUSEZEC5OOP4Y47bH2F04wb5748IiL/cboQfuKJJ3j66af55ZdfsFgsHDp0iM8++4whQ4bQv39/V2YUEZH8rEcPWLbM1iWiWzdbW4kS7s0kIkI2CuHnnnuOe+65h9atWxMXF0fLli157LHHeOKJJxgwYIArM+YJGj5NRMQF7r7b9nXhQhg50q1RRESyNXza2LFjOXHiBBs3bmTDhg0cP36cV155xVXZ8hQNnyYi4gK1al26P2oUHDvmviwi4vGyPaGG1WqlYcOG3HzzzQQHB7sik4iIFFQREbB586Xldu3g9Gn35RERj+Z0ITxu3DhmzJiRrn3GjBm8/vrr2QolIiIFWIMGUKWK7f7WrTBihHvziIjHcroQfu+996hevXq69ho1ajDt8uFyRERErjR//qX7R464L4eIeDSnC+EjR45QunTpdO0lSpTg8OHD2QolIiIFXK1al8YYnjsX/v7bvXlExCM5XQiXL1+edZfPJ/+fdevWUaZMmWyFEhERD1Cx4qX7H37ovhwi4rGcLoQfe+wxBg4cyMyZM9m/fz/79+9nxowZDBo0iMcff9yVGUVEpCBq2xbSJmBautS9WUTEI/k4+8TnnnuOU6dO0b9/fxITEzHGEBgYyPPPP88LL7zgyowiIlIQWSzQoQO88w5s2QKFC9vaH3wQ3nvPrdFExDM4XQhbLBZef/11hg0bxs6dOwkMDOSGG27A39/flfnyjKioKKKiokhJSXF3FBGRguOhh2DKFEhJgbNnbW3Tp0MGF2MDl4rnG27IvYwiUmA5XQgDLF++nOXLl3Ps2DFSU1MdHstoaLX8LDIyksjISGJjYylUqJC744iIFAzNmtlGjTh92nZr3NhWFA8efPXnfPEFbNiQexlFpMByuhAeNWoUo0ePpmHDhpQuXRqLxeLKXCIi4imKF7fdAN56C375JeP1jh+HZctsE3KULw8tW8Knn9rOEouIOMHpQnjatGnMmjWLHj16uDKPiIh4sqeeuvpjhw5BeDgkJsI//8Dnn9sK57QiWkQki5weNSIxMZFmzZq5MouIiMjVlSkDBw86TtG8ZIn78ohIvpet4dM+//xzV2YRERG5tpIlbVM0p+ndG2Ji3BZHRPI3p7tGXLhwgffff58ff/yR2rVr4+vr6/D4xIkTsx1OREQkQ3362EaXSE6G4cPhq6/cnUhE8iGnC+HffvuNunXrAvD77787PKYL50REJEeNHAk//QS7dsHXX0NUFERGujuViOQzThfCK1eudGUOERGRzCtXzjbpRqtWtuU331QhLCJZ5nQfYREREbe69VZIG7Nekx2JiBOyNaEGQExMDAcOHCAxMdGh/e67787upkVERK6tdm3b15QU27Bqfn7uzSMi+YrThfDff/9Nly5d2L59OxaLBWMMcKl/cEGbilhTLIuI5EFp16QcOgRWq62v8BNPuDeTiOQbTneNePrppwkPD+fo0aNYrVZ27NjBmjVraNiwIatWrXJhxLwhMjKSmJgYNm3a5O4oIiKS5sYboWJF2/2UFPjxR/fmEZF8xelCeP369YwePZoSJUrg5eWFl5cXt9xyC+PGjeOpa80MJCIi4irBwbBnD0yYYFv+6ivbWWKLBUqVsj0mInIVThfCKSkpBAcHA1C8eHEOHToEQMWKFdm1a5dr0omIiFyPtzc0awYBAY7tR4/Chg3uySQi+YLThXDNmjX57bffAGjcuDHjx49n3bp1jB49msqVK7ssoIiIyHU1aQInT8KxY7bbrbfa2h99FP67hkVE5EpOF8Ivv/wyqampAIwZM4b9+/fTokULFi5cyNtvv+2ygCIiIplitUKJErZbRIStLTERjhxxby4RybOcHjWibdu29vuVK1cmJiaGU6dOUaRIEc0sJyIi7vXOOzB1qu3+889DhQrw7LNQqJB7c4lInpLtcYQvV7RoUVduTkRExDne3lCsmK27xCef2NoqVYLHHnNrLBHJW7JUCA8ePDjT606cODHLYURERFzmm29sw6nNnQs7dsDu3fDrr1CyJJQu7e50IpIHZKkQ3rZtm8Pyli1bSElJoVq1agD8+eefeHt706BBA9clFBERcUbz5rbbH3/YCuHx4203Ly/YtAnq13d3QhFxsywVwitXrrTfnzhxIiEhIXz00UcUKVIEgNOnT/PII4/QokUL16YUERFx1kMPwS+/wIULcOIEJCXBrl0qhEXE+VEjJkyYwLhx4+xFMECRIkUYM2YME9IGNhcREXG3zp3h779t0zC3bGlrmzoVeveG4cMhOdmt8UTEfZy+WC42NpajR49So0YNh/Zjx45x7ty5bAcTERFxubSTN2vX2m4ArVvbbiLicZwuhLt06cIjjzzChAkTaNKkCQAbNmzg2Wef5d5773VZQBEREZeZNMnWbzgpCd56C/79F86fd3cqEXETpwvhadOmMWTIELp3705SUpJtYz4+9OnThzfeeMNlAUVERFymXDkYONB2f84cWyH8999ujSQi7uN0IWy1WpkyZQpvvPEGe/bswRhD1apVCQoKcmU+ERGRnPHrr7avmoJZxGM5fbEcwNq1a3niiSfo27cvxYsXJygoiE8++YSffvrJVfnyjKioKCIiImjUqJG7o4iIiCvcfbftq1e2fhWKSD7m9Hf/119/Tdu2bQkMDGTr1q1cvHgRgHPnzvHqq6+6LGBeERkZSUxMDJs2bXJ3FBERcQVvb9vXt992bw4RcRunC+ExY8Ywbdo0PvjgA3x9fe3tzZo1Y+vWrS4JJyIikuN8nO4lKCL5nNOF8K5du2iZNh7jZUJDQzlz5kx2MomIiOS8fv1sXy0W9+YQEbdxuhAuXbo0f/31V7r2n376icqVK2crlIiISK7ZsweaNbPdRo1ydxoRyUVOF8JPPPEETz/9NL/88gsWi4VDhw7x2WefMWTIEPr37+/KjCIiIq5Xtqzt64ULsH697TZqFPx3zYuIFHxOd4x67rnnOHv2LK1bt+bChQu0bNkSf39/hgwZwoABA1yZUURExPVuvBGio2HfPkhIgG7dbEOpaTg1EY+RrSsExo4dy0svvURMTAypqalEREQQHBzsqmwiIiI5q04d2y029lLb/Png53f15zRpculssojka9m+VNZqtdKwYUNXZBEREXGPtKHUwHZm+FqqVIEMrpERkfwnW4Xw2rVree+999izZw9fffUVZcuW5ZNPPiE8PJxbbrnFVRlFRERyVlAQjBgBK1ZcfZ0LF2DTJtu0zCJSIDhdCH/99df06NGDhx9+mG3btqWbUGPhwoUuCykiIpLjRo603a7mwAGoWDG30ohILtCEGiIiIlmRlATPPnvpNn687WI7Ecl3nD4jrAk1RETEo1ittsk3UlLgzTcdHytfHrp2dU8uEXGa04Vw2oQalSpVcmjXhBoiIlIgFS8Os2fDli2X2ubPt104d+6c+3KJiNOcLoTTJtSYMWOGfUKN9evXM2TIEIYPH+7KjCIiInnDgw/abml279YIEiL5mCbUEBERya5ffoH27aFcOXcnEZEs0IQaIiIizkq7WHzGDNi2DXSxuEi+ogk1REREnDVoEBw/DqtWwZEj7k4jIlnk9PBp48aNY8aMGenaZ8yYweuvv56tUCIiIvlC06YwaZK7U4iIk5wuhN977z2qV6+err1GjRpMmzYtW6FERERERHKa04XwkSNHKF26dLr2EiVKcPjw4WyFEhERyXdOnYLOneHhh22jSYhInud0IVy+fHnWrVuXrn3dunWUKVMmW6FERETyjeLFbV8vXoRvv4XPP4fp092bSUQyxemL5R577DEGDhxIUlISt912GwDLly/nueee45lnnnFZQFc7d+4ct912G0lJSaSkpPDUU0/x+OOPuzuWiIjkV+XKwdq18Mcf8PXXsHgxJCa6O5WIZEK2xhE+deoU/fv3J/G/b/iAgACef/55XnjhBZcFdDWr1crq1auxWq0kJCRQs2ZN7r33XooVK+buaCIikl/dcovttmePrRAWkXzB6ULYYrHw+uuvM2zYMHbu3ElgYCA33HAD/v7+rsznct7e3litVgAuXLhASkoKxhg3pxIRERGR3OZ0H+Eff/wRgODgYBo1akTNmjXtRfB7773ndKA1a9bQqVMnypQpg8ViYcGCBenWmTJlCuHh4QQEBNCgQQPWrl2bpX2cOXOGOnXqUK5cOZ577jmKp/XvEhERcYXffoONG92dQkSuw+lCuEOHDjzzzDP2bhEAx48fp1OnTgwdOtTpQPHx8dSpU4d33303w8fnzJnDwIEDeemll9i2bRstWrSgXbt2HDhwwL5OgwYNqFmzZrrboUOHAChcuDC//vore/fu5fPPP+fo0aNO5xUREbHz87N9Xb4cWraE2Fj35hGRa3K6a8SaNWvo0aMHP/74I59//jn79u3j0UcfJSIigl9//dXpQO3ataNdu3ZXfXzixIn06dOHxx57DIDJkyezZMkSpk6dyrhx4wDYsmVLpvYVFhZG7dq1WbNmDf/73/8yXOfixYtcvHjRvhz73w+1pKQkkpKSMrUfd0nLl9dzSs7Q8fdcOvZu9PDDeO/Zg9dnn8HFiySdOgWBgbm2ex17z6Vj7yiz74PFZKODbHx8PH379mXu3LmkpqYyZswYnn32WSwWi7ObdAxnsTB//nzuueceABITE7FarcydO5cuXbrY13v66aeJjo5m9erV193m0aNHCQwMJDQ0lNjYWJo2bcrs2bOpXbt2huuPHDmSUaNGpWv//PPP7X2NRURELtfp/vvxSk5myfTpXNDF2CK5LiEhgW7dunH27FlCQ0Ovup7TZ4QBdu3axaZNmyhXrhyHDh3ijz/+ICEhgaCgoOxs9qpOnDhBSkoKYWFhDu1hYWEcyeQc7//88w99+vTBGIMxhgEDBly1CAYYOnQogwcPti/HxsZSvnx52rRpc803Ni9ISkpi2bJl3Hnnnfj6+ro7juQyHX/PpWPvfmknhG677TYoWzbX9qtj77l07B3FZrJbktOF8GuvvcaIESP4v//7P9544w327NlD9+7dqV27Np9++ilNmzZ1dtPXdeUZZ2NMps9CN2jQgOjo6Ezvy9/fP8ORMHx9ffPNBy0/ZRXX0/H3XDr27ufr6wtuOAY69p5Lx94ms++B04XwW2+9xYIFC+z9eWvUqMHGjRt58cUXadWqlUO/WlcpXrw43t7e6c7+Hjt2LN1ZYhEREbdbscI281ypUlC3Lrio66CIuIbTo0Zs37493UVtvr6+vPHGGyxdujTbwTLi5+dHgwYNWLZsmUP7smXLaNasWY7sM01UVBQRERE0atQoR/cjIiIFgLe37WvPntC+PdSvD5m4jkVEcleWC+H27dtz9uxZ+9i7Y8eO5cyZM/bHT548Sb9+/ZwOFBcXR3R0tL37wt69e4mOjrYPjzZ48GA+/PBDZsyYwc6dOxk0aBAHDhygb9++Tu8zMyIjI4mJiWHTpk05uh8RESkAhg2zFb/160NIiK3tsmE+RSRvyHIhvGTJEoduD6+//jqnTp2yLycnJ7Nr1y6nA23evJl69epRr149wFb41qtXj+HDhwPw4IMPMnnyZEaPHk3dunVZs2YNCxcupGLFik7vU0RExKVefBG2bLHdcvg/liLivCz3Eb5ytDVXT0/cqlWr626zf//+9O/f36X7FRERERHP4nQfYRERERGR/CzLhbDFYkk3VJmrJtDIy3SxnIiIiEjB4lTXiN69e9vH1r1w4QJ9+/a1T6KRE8Om5QWRkZFERkYSGxtLoUKF3B1HRETym/Pn4dy59O3+/uDnl/t5RCTrhXCvXr0clrt3755unZ49ezqfSEREpCDq29d2u1JwsG1otfr1cz+TiIfLciE8c+bMnMghIiJSMLVpA8uWQWpqxo/HxcHGjSqERdxAF8uJiIjkpMGDbd0iMrp17uzudCIezekplj1NVFQUUVFRpKSkuDuKiIjkN1frA5w2A52IuIXOCGeSZpYTERERKVhUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkXSwnIiLibvv3w+bN2d6MJTmZwn/9hWXLFvDJ4Fd8RARYrdnej0hBoUI4kzRqhIiIuJzFYvv62mu2Wzb5ALdea4XateHXX7O9H5GCQoVwJmmKZRERcbmHH7YVphcvumRzBjh//jyBgYFYLn8gORkOH4Zdu1yyH5GCQoWwiIiIu3TpYru5SHJSEssWLqR9+/b4+vpeeuDgQahQwWX7ESkodLGciIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYVwJkVFRREREUGjRo3cHUVEREREXECFcCZFRkYSExPDpk2b3B1FRERERFxAhbCIiIiIeCQVwiIiIiLikTShhoiIiKe4eBFy+1qXm26CmTPB2zt39yuSCSqERURECroiRSAoCOLjYfPm3N335s0wZAjUrp27+xXJBBXCIiIiBV1wMPz+O+zYkbv77dkTTp2ClJTc3a9IJqkQFhER8QSVKtluuSkwMHf3J5JFulhORERERDySCuFM0oQaIiIiIgWLCuFM0oQaIiIiIgWLCmERERER8UgqhEVERETEI6kQFhERERGPpEJYRERERDySCmERERER8UgqhEVERETEI6kQFhERERGPpEJYRERERDySCmERERER8Ug+7g4gIiIiBdyAAVCokLtTZE7RovDGG1C6tLuTSC5QIZxJUVFRREVFkZKS4u4oIiIi+UNYGPz7L/z8s7uTZE3jxvDkk+5OIblAhXAmRUZGEhkZSWxsLIXyy1+1IiIi7rRgAaxcCca4O0nmvPcerF8PSUnuTiK5RIWwiIiI5Izy5aFnT3enyLwff7QVwuIxdLGciIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkFcKZFBUVRUREBI0aNXJ3FBERERFxARXCmRQZGUlMTAybNm1ydxQRERERcQEVwiIiIiLikVQIi4iIiIhHUiEsIiIiIh5JhbCIiIiIeCQVwiIiIiLikVQIi4iIiIhHUiEsIiIiIh5JhbCIiIiIeCQfdwcQERERyVP27YMNG9ydIkssyckU2bULS7Fi4JNHy7tixeCGG9ydwkEefadEREREcpnFYvv6zju2Wz7iA7R0d4jreeABmDPH3SkcqBAWERERAXj4YdiyBS5ccHeSLDNAQnw81qAgLO4OczVhYe5OkI4KYRERERGAtm1hxw53p3BKclISPy5cSPv27fH19XV3nHxDF8uJiIiIiEdSISwiIiIiHkmFsIiIiIh4JBXCIiIiIuKRVAiLiIiIiEdSISwiIiIiHkmFsIiIiIh4JI8thBMSEqhYsSJDhgxxdxQRERERcQOPLYTHjh1L48aN3R1DRERERNzEIwvh3bt388cff9C+fXt3RxERERERN8lzhfCaNWvo1KkTZcqUwWKxsGDBgnTrTJkyhfDwcAICAmjQoAFr167N0j6GDBnCuHHjXJRYRERERPKjPFcIx8fHU6dOHd59990MH58zZw4DBw7kpZdeYtu2bbRo0YJ27dpx4MAB+zoNGjSgZs2a6W6HDh3im2++4cYbb+TGG2/MrZckIiIiInmQj7sDXKldu3a0a9fuqo9PnDiRPn368NhjjwEwefJklixZwtSpU+1nebds2XLV52/YsIEvvviCuXPnEhcXR1JSEqGhoQwfPjzD9S9evMjFixfty7GxsQAkJSWRlJSU5deXm9Ly5fWckjN0/D2Xjr3n0rH3XDr2jjL7PliMMSaHszjNYrEwf/587rnnHgASExOxWq3MnTuXLl262Nd7+umniY6OZvXq1Vna/qxZs/j999958803r7rOyJEjGTVqVLr2zz//HKvVmqX9iYiIiEjOS0hIoFu3bpw9e5bQ0NCrrpfnzghfy4kTJ0hJSSEsLMyhPSwsjCNHjuTIPocOHcrgwYPty2fPnqVChQo0bdqUkJCQHNmnqyQlJbFy5Upat26Nr6+vu+NILtPx91w69p5Lx95z6dg7OnfuHADXO9+brwrhNBaLxWHZGJOuLTN69+593XX8/f3x9/e3L6d1jQgPD8/y/kREREQk95w7d45ChQpd9fF8VQgXL14cb2/vdGd/jx07lu4scU4pU6YMBw8eJCQkxKniOzfFxsZSvnx5Dh48eM1/C0jBpOPvuXTsPZeOvefSsXdkjOHcuXOUKVPmmuvlq0LYz8+PBg0asGzZMoc+wsuWLaNz5865ksHLy4ty5crlyr5cJTQ0VN8UHkzH33Pp2HsuHXvPpWN/ybXOBKfJc4VwXFwcf/31l3157969REdHU7RoUSpUqMDgwYPp0aMHDRs2pGnTprz//vscOHCAvn37ujG1iIiIiOQ3ea4Q3rx5M61bt7Yvp12o1qtXL2bNmsWDDz7IyZMnGT16NIcPH6ZmzZosXLiQihUruiuyiIiIiORDea4QbtWq1XWv8Ovfvz/9+/fPpUT5l7+/PyNGjHC42E88h46/59Kx91w69p5Lx945eXocYRERERGRnJLnplgWEREREckNKoRFRERExCOpEBYRERERj6RCWEREREQ8kgrhAmzKlCmEh4cTEBBAgwYNWLt2rbsjSQ4bN24cjRo1IiQkhJIlS3LPPfewa9cud8cSNxg3bhwWi4WBAwe6O4rkkn///Zfu3btTrFgxrFYrdevWZcuWLe6OJTksOTmZl19+mfDwcAIDA6lcuTKjR48mNTXV3dHyBRXCBdScOXMYOHAgL730Etu2baNFixa0a9eOAwcOuDua5KDVq1cTGRnJhg0bWLZsGcnJybRp04b4+Hh3R5NctGnTJt5//31q167t7iiSS06fPk3z5s3x9fVl0aJFxMTEMGHCBAoXLuzuaJLDXn/9daZNm8a7777Lzp07GT9+PG+88QbvvPOOu6PlCxo+rYBq3Lgx9evXZ+rUqfa2m266iXvuuYdx48a5MZnkpuPHj1OyZElWr15Ny5Yt3R1HckFcXBz169dnypQpjBkzhrp16zJ58mR3x5Ic9sILL7Bu3Tr9588DdezYkbCwMKZPn25vu++++7BarXzyySduTJY/6IxwAZSYmMiWLVto06aNQ3ubNm34+eef3ZRK3OHs2bMAFC1a1M1JJLdERkbSoUMH7rjjDndHkVz07bff0rBhQ/73v/9RsmRJ6tWrxwcffODuWJILbrnlFpYvX86ff/4JwK+//spPP/1E+/bt3Zwsf8hzM8tJ9p04cYKUlBTCwsIc2sPCwjhy5IibUkluM8YwePBgbrnlFmrWrOnuOJILvvjiC7Zu3cqmTZvcHUVy2d9//83UqVMZPHgwL774Ihs3buSpp57C39+fnj17ujue5KDnn3+es2fPUr16dby9vUlJSWHs2LF07drV3dHyBRXCBZjFYnFYNsaka5OCa8CAAfz222/89NNP7o4iueDgwYM8/fTTLF26lICAAHfHkVyWmppKw4YNefXVVwGoV68eO3bsYOrUqSqEC7g5c+bw6aef8vnnn1OjRg2io6MZOHAgZcqUoVevXu6Ol+epEC6Aihcvjre3d7qzv8eOHUt3llgKpieffJJvv/2WNWvWUK5cOXfHkVywZcsWjh07RoMGDextKSkprFmzhnfffZeLFy/i7e3txoSSk0qXLk1ERIRD20033cTXX3/tpkSSW5599lleeOEFHnroIQBq1arF/v37GTdunArhTFAf4QLIz8+PBg0asGzZMof2ZcuW0axZMzelktxgjGHAgAHMmzePFStWEB4e7u5Ikktuv/12tm/fTnR0tP3WsGFDHn74YaKjo1UEF3DNmzdPN1Tin3/+ScWKFd2USHJLQkICXl6O5Zy3t7eGT8sknREuoAYPHkyPHj1o2LAhTZs25f333+fAgQP07dvX3dEkB0VGRvL555/zzTffEBISYv+vQKFChQgMDHRzOslJISEh6fqCBwUFUaxYMfUR9wCDBg2iWbNmvPrqqzzwwANs3LiR999/n/fff9/d0SSHderUibFjx1KhQgVq1KjBtm3bmDhxIo8++qi7o+ULGj6tAJsyZQrjx4/n8OHD1KxZk0mTJmkIrQLuan3AZ86cSe/evXM3jLhdq1atNHyaB/n+++8ZOnQou3fvJjw8nMGDB/P444+7O5bksHPnzjFs2DDmz5/PsWPHKFOmDF27dmX48OH4+fm5O16ep0JYRERERDyS+giLiIiIiEdSISwiIiIiHkmFsIiIiIh4JBXCIiIiIuKRVAiLiIiIiEdSISwiIiIiHkmFsIiIiIh4JBXCIiIiIuKRVAiLiIiIiEdSISwikk+dPHmSkiVLsm/fPndHyZT777+fiRMnujuGiIidCmERkTxm4cKFWCyWq94eeOABAMaNG0enTp2oVKmS/bmpqalUr16d559/3mGbS5Yswc/Pj7lz5zqdK7vbHj58OGPHjiU2NtbpDCIirmQxxhh3hxARkUvOnz/P2bNnHdpSUlJ45JFH2LZtGytWrKBq1aqUKVOGhQsX0rRpU4d1P/roI5588kn2799PkSJF+PXXX2nRogXDhw9nyJAh2cqW3W03aNCAxx57jH79+mUrh4iIK6gQFhHJ41JSUujevTs//vgjK1asoFatWsybN48nnniC48ePp1s/OTmZG2+8kV69etGnTx+aNGlC586diYqKynaW7G571KhRLF++nDVr1mQ7i4hIdqkQFhHJw9KK4GXLlrFixQpq164NwMCBA9m1axeLFi3K8HnvvfceL774ImXLlqVSpUrMnz8fb29vl2TKzrYXLVpEly5dOHv2LP7+/i7JIyLiLPURFhHJo1JSUujRowfLli1j+fLl9iIYYN++fZQpU+aqz3344YdJSEjAGMPs2bMdCtUuXbpQpEgR7r//fqdyXW3bBw8epFWrVkRERFC7du0M+wyXLVuWixcvcuTIEaf2LSLiSiqERUTyoLQieOnSpSxfvpw6deo4PH7+/HkCAgKu+vwBAwYAcOLEiXRna5966ik+/vhjp7Ndbds+Pj5MnjyZmJgYfvzxRwYNGkR8fLzDcwMDAwFISEhwev8iIq6iQlhEJI9JK4KXLFnCjz/+mK4IBihevDinT5/O8PnDhg3jhx9+YMOGDSQnJzN9+nSHx1u3bk1ISIhT2a617dKlS1O3bl0ASpYsSdGiRTl16pTD89OWS5Qo4dT+RURcSYWwiEgekpKSQs+ePe1FcFpheaV69eoRExOTrv3DDz9kwoQJfPfdd9SpU4eBAwcyfvx4kpKSsp0tK9vevHkzqamplC9f3qH9999/p1y5chQvXjzbeUREskuFsIhIHpGamkrPnj1ZsGABn376KaVLl+bIkSMOt5SUFADatm3Ljh07HM4KL1q0iMjISD799FOaNGkCwJNPPklsbCyffPJJtrJlZdsnT56kZ8+evP/+++m2s3btWtq0aZOtLCIirqJCWEQkj9i0aROff/45CQkJtG/fntKlS6e7nTt3DoBatWrRsGFDvvzySwC2bNnC//73P8aPH8+9995r32ZoaChPPvkkr732mr2IvpZZs2ZhsVgc2rKy7YsXL9KlSxeGDh1Ks2bNHLZz4cIF5s+fz+OPP+7cGyQi4mIaPk1EJJ9auHAhQ4YM4ffff8fLK2vnNVatWsW7777LV1995dA+cuRIVq1axapVq7KcxxhDt27dqFatGiNHjkz3eFRUFN988w1Lly7N8rZFRHKCj7sDiIiIc9q3b8/u3bv5999/0/XFvZa2bduydetW4uPjKVeuHPPnz6dRo0aAbbrkt956y6k869atY86cOdSuXZsFCxYA8Mknn1CrVi0AfH19eeedd5zatohITtAZYRERERHxSOojLCIiIiIeSYWwiIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkFcIiIiIi4pFUCIuIiIiIR1IhLCIiIiIeSYWwiIiIiHgkFcIiIiIi4pFUCIuIiIiIR/p/LYkSVTDrjbEAAAAASUVORK5CYII="/>
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"/>
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