Predictive Modeling.html

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<title>Predictive Modeling</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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/* 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==);
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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);
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  --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;
}

.jp-RenderedText pre .ansi-yellow-fg {
  color: #ddb62b;
}

.jp-RenderedText pre .ansi-blue-fg {
  color: #208ffb;
}

.jp-RenderedText pre .ansi-magenta-fg {
  color: #d160c4;
}

.jp-RenderedText pre .ansi-cyan-fg {
  color: #60c6c8;
}

.jp-RenderedText pre .ansi-white-fg {
  color: #c5c1b4;
}

.jp-RenderedText pre .ansi-black-bg {
  background-color: #3e424d;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-red-bg {
  background-color: #e75c58;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-green-bg {
  background-color: #00a250;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-yellow-bg {
  background-color: #ddb62b;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-blue-bg {
  background-color: #208ffb;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-magenta-bg {
  background-color: #d160c4;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-cyan-bg {
  background-color: #60c6c8;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-white-bg {
  background-color: #c5c1b4;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-black-intense-fg {
  color: #282c36;
}

.jp-RenderedText pre .ansi-red-intense-fg {
  color: #b22b31;
}

.jp-RenderedText pre .ansi-green-intense-fg {
  color: #007427;
}

.jp-RenderedText pre .ansi-yellow-intense-fg {
  color: #b27d12;
}

.jp-RenderedText pre .ansi-blue-intense-fg {
  color: #0065ca;
}

.jp-RenderedText pre .ansi-magenta-intense-fg {
  color: #a03196;
}

.jp-RenderedText pre .ansi-cyan-intense-fg {
  color: #258f8f;
}

.jp-RenderedText pre .ansi-white-intense-fg {
  color: #a1a6b2;
}

.jp-RenderedText pre .ansi-black-intense-bg {
  background-color: #282c36;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-red-intense-bg {
  background-color: #b22b31;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-green-intense-bg {
  background-color: #007427;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-yellow-intense-bg {
  background-color: #b27d12;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-blue-intense-bg {
  background-color: #0065ca;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-magenta-intense-bg {
  background-color: #a03196;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-cyan-intense-bg {
  background-color: #258f8f;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-white-intense-bg {
  background-color: #a1a6b2;
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-default-inverse-fg {
  color: var(--jp-ui-inverse-font-color0);
}

.jp-RenderedText pre .ansi-default-inverse-bg {
  background-color: var(--jp-inverse-layout-color0);
  padding: var(--jp-private-code-span-padding) 0;
}

.jp-RenderedText pre .ansi-bold {
  font-weight: bold;
}

.jp-RenderedText pre .ansi-underline {
  text-decoration: underline;
}

.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
  background: var(--jp-rendermime-error-background);
  padding-top: var(--jp-code-padding);
}

/*-----------------------------------------------------------------------------
| RenderedLatex
|----------------------------------------------------------------------------*/

.jp-RenderedLatex {
  color: var(--jp-content-font-color1);
  font-size: var(--jp-content-font-size1);
  line-height: var(--jp-content-line-height);
}

/* Left-justify outputs.*/
.jp-OutputArea-output.jp-RenderedLatex {
  padding: var(--jp-code-padding);
  text-align: left;
}

/*-----------------------------------------------------------------------------
| RenderedHTML
|----------------------------------------------------------------------------*/

.jp-RenderedHTMLCommon {
  color: var(--jp-content-font-color1);
  font-family: var(--jp-content-font-family);
  font-size: var(--jp-content-font-size1);
  line-height: var(--jp-content-line-height);

  /* Give a bit more R padding on Markdown text to keep line lengths reasonable */
  padding-right: 20px;
}

.jp-RenderedHTMLCommon em {
  font-style: italic;
}

.jp-RenderedHTMLCommon strong {
  font-weight: bold;
}

.jp-RenderedHTMLCommon u {
  text-decoration: underline;
}

.jp-RenderedHTMLCommon a:link {
  text-decoration: none;
  color: var(--jp-content-link-color);
}

.jp-RenderedHTMLCommon a:hover {
  text-decoration: underline;
  color: var(--jp-content-link-color);
}

.jp-RenderedHTMLCommon a:visited {
  text-decoration: none;
  color: var(--jp-content-link-color);
}

/* Headings */

.jp-RenderedHTMLCommon h1,
.jp-RenderedHTMLCommon h2,
.jp-RenderedHTMLCommon h3,
.jp-RenderedHTMLCommon h4,
.jp-RenderedHTMLCommon h5,
.jp-RenderedHTMLCommon h6 {
  line-height: var(--jp-content-heading-line-height);
  font-weight: var(--jp-content-heading-font-weight);
  font-style: normal;
  margin: var(--jp-content-heading-margin-top) 0
    var(--jp-content-heading-margin-bottom) 0;
}

.jp-RenderedHTMLCommon h1:first-child,
.jp-RenderedHTMLCommon h2:first-child,
.jp-RenderedHTMLCommon h3:first-child,
.jp-RenderedHTMLCommon h4:first-child,
.jp-RenderedHTMLCommon h5:first-child,
.jp-RenderedHTMLCommon h6:first-child {
  margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
}

.jp-RenderedHTMLCommon h1:last-child,
.jp-RenderedHTMLCommon h2:last-child,
.jp-RenderedHTMLCommon h3:last-child,
.jp-RenderedHTMLCommon h4:last-child,
.jp-RenderedHTMLCommon h5:last-child,
.jp-RenderedHTMLCommon h6:last-child {
  margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
}

.jp-RenderedHTMLCommon h1 {
  font-size: var(--jp-content-font-size5);
}

.jp-RenderedHTMLCommon h2 {
  font-size: var(--jp-content-font-size4);
}

.jp-RenderedHTMLCommon h3 {
  font-size: var(--jp-content-font-size3);
}

.jp-RenderedHTMLCommon h4 {
  font-size: var(--jp-content-font-size2);
}

.jp-RenderedHTMLCommon h5 {
  font-size: var(--jp-content-font-size1);
}

.jp-RenderedHTMLCommon h6 {
  font-size: var(--jp-content-font-size0);
}

/* Lists */

/* stylelint-disable selector-max-type, selector-max-compound-selectors */

.jp-RenderedHTMLCommon ul:not(.list-inline),
.jp-RenderedHTMLCommon ol:not(.list-inline) {
  padding-left: 2em;
}

.jp-RenderedHTMLCommon ul {
  list-style: disc;
}

.jp-RenderedHTMLCommon ul ul {
  list-style: square;
}

.jp-RenderedHTMLCommon ul ul ul {
  list-style: circle;
}

.jp-RenderedHTMLCommon ol {
  list-style: decimal;
}

.jp-RenderedHTMLCommon ol ol {
  list-style: upper-alpha;
}

.jp-RenderedHTMLCommon ol ol ol {
  list-style: lower-alpha;
}

.jp-RenderedHTMLCommon ol ol ol ol {
  list-style: lower-roman;
}

.jp-RenderedHTMLCommon ol ol ol ol ol {
  list-style: decimal;
}

.jp-RenderedHTMLCommon ol,
.jp-RenderedHTMLCommon ul {
  margin-bottom: 1em;
}

.jp-RenderedHTMLCommon ul ul,
.jp-RenderedHTMLCommon ul ol,
.jp-RenderedHTMLCommon ol ul,
.jp-RenderedHTMLCommon ol ol {
  margin-bottom: 0;
}

/* stylelint-enable selector-max-type, selector-max-compound-selectors */

.jp-RenderedHTMLCommon hr {
  color: var(--jp-border-color2);
  background-color: var(--jp-border-color1);
  margin-top: 1em;
  margin-bottom: 1em;
}

.jp-RenderedHTMLCommon > pre {
  margin: 1.5em 2em;
}

.jp-RenderedHTMLCommon pre,
.jp-RenderedHTMLCommon code {
  border: 0;
  background-color: var(--jp-layout-color0);
  color: var(--jp-content-font-color1);
  font-family: var(--jp-code-font-family);
  font-size: inherit;
  line-height: var(--jp-code-line-height);
  padding: 0;
  white-space: pre-wrap;
}

.jp-RenderedHTMLCommon :not(pre) > code {
  background-color: var(--jp-layout-color2);
  padding: 1px 5px;
}

/* Tables */

.jp-RenderedHTMLCommon table {
  border-collapse: collapse;
  border-spacing: 0;
  border: none;
  color: var(--jp-ui-font-color1);
  font-size: var(--jp-ui-font-size1);
  table-layout: fixed;
  margin-left: auto;
  margin-bottom: 1em;
  margin-right: auto;
}

.jp-RenderedHTMLCommon thead {
  border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
  vertical-align: bottom;
}

.jp-RenderedHTMLCommon td,
.jp-RenderedHTMLCommon th,
.jp-RenderedHTMLCommon tr {
  vertical-align: middle;
  padding: 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}

.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
  max-width: none;
}

:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
  text-align: right;
}

.jp-RenderedHTMLCommon th {
  font-weight: bold;
}

.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
  background: var(--jp-layout-color0);
}

.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
  background: var(--jp-rendermime-table-row-background);
}

.jp-RenderedHTMLCommon tbody tr:hover {
  background: var(--jp-rendermime-table-row-hover-background);
}

.jp-RenderedHTMLCommon p {
  text-align: left;
  margin: 0;
  margin-bottom: 1em;
}

.jp-RenderedHTMLCommon img {
  -moz-force-broken-image-icon: 1;
}

/* Restrict to direct children as other images could be nested in other content. */
.jp-RenderedHTMLCommon > img {
  display: block;
  margin-left: 0;
  margin-right: 0;
  margin-bottom: 1em;
}

/* Change color behind transparent images if they need it... */
[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
  background-color: var(--jp-inverse-layout-color1);
}

[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
  background-color: var(--jp-inverse-layout-color1);
}

.jp-RenderedHTMLCommon img,
.jp-RenderedImage img,
.jp-RenderedHTMLCommon svg,
.jp-RenderedSVG svg {
  max-width: 100%;
  height: auto;
}

.jp-RenderedHTMLCommon img.jp-mod-unconfined,
.jp-RenderedImage img.jp-mod-unconfined,
.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
.jp-RenderedSVG svg.jp-mod-unconfined {
  max-width: none;
}

.jp-RenderedHTMLCommon .alert {
  padding: var(--jp-notebook-padding);
  border: var(--jp-border-width) solid transparent;
  border-radius: var(--jp-border-radius);
  margin-bottom: 1em;
}

.jp-RenderedHTMLCommon .alert-info {
  color: var(--jp-info-color0);
  background-color: var(--jp-info-color3);
  border-color: var(--jp-info-color2);
}

.jp-RenderedHTMLCommon .alert-info hr {
  border-color: var(--jp-info-color3);
}

.jp-RenderedHTMLCommon .alert-info > p:last-child,
.jp-RenderedHTMLCommon .alert-info > ul:last-child {
  margin-bottom: 0;
}

.jp-RenderedHTMLCommon .alert-warning {
  color: var(--jp-warn-color0);
  background-color: var(--jp-warn-color3);
  border-color: var(--jp-warn-color2);
}

.jp-RenderedHTMLCommon .alert-warning hr {
  border-color: var(--jp-warn-color3);
}

.jp-RenderedHTMLCommon .alert-warning > p:last-child,
.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
  margin-bottom: 0;
}

.jp-RenderedHTMLCommon .alert-success {
  color: var(--jp-success-color0);
  background-color: var(--jp-success-color3);
  border-color: var(--jp-success-color2);
}

.jp-RenderedHTMLCommon .alert-success hr {
  border-color: var(--jp-success-color3);
}

.jp-RenderedHTMLCommon .alert-success > p:last-child,
.jp-RenderedHTMLCommon .alert-success > ul:last-child {
  margin-bottom: 0;
}

.jp-RenderedHTMLCommon .alert-danger {
  color: var(--jp-error-color0);
  background-color: var(--jp-error-color3);
  border-color: var(--jp-error-color2);
}

.jp-RenderedHTMLCommon .alert-danger hr {
  border-color: var(--jp-error-color3);
}

.jp-RenderedHTMLCommon .alert-danger > p:last-child,
.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
  margin-bottom: 0;
}

.jp-RenderedHTMLCommon blockquote {
  margin: 1em 2em;
  padding: 0 1em;
  border-left: 5px solid var(--jp-border-color2);
}

a.jp-InternalAnchorLink {
  visibility: hidden;
  margin-left: 8px;
  color: var(--md-blue-800);
}

h1:hover .jp-InternalAnchorLink,
h2:hover .jp-InternalAnchorLink,
h3:hover .jp-InternalAnchorLink,
h4:hover .jp-InternalAnchorLink,
h5:hover .jp-InternalAnchorLink,
h6:hover .jp-InternalAnchorLink {
  visibility: visible;
}

.jp-RenderedHTMLCommon kbd {
  background-color: var(--jp-rendermime-table-row-background);
  border: 1px solid var(--jp-border-color0);
  border-bottom-color: var(--jp-border-color2);
  border-radius: 3px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
  display: inline-block;
  font-size: var(--jp-ui-font-size0);
  line-height: 1em;
  padding: 0.2em 0.5em;
}

/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
 * At the bottom of cells this is a bit too much as there is also spacing
 * between cells. Going all the way to 0 gets too tight between markdown and
 * code cells.
 */
.jp-RenderedHTMLCommon > *:last-child {
  margin-bottom: 0.5em;
}

/*
 * Copyright (c) Jupyter Development Team.
 * Distributed under the terms of the Modified BSD License.
 */

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Copyright (c) 2014-2017, PhosphorJS Contributors
|
| Distributed under the terms of the BSD 3-Clause License.
|
| The full license is in the file LICENSE, distributed with this software.
|----------------------------------------------------------------------------*/

.lm-cursor-backdrop {
  position: fixed;
  width: 200px;
  height: 200px;
  margin-top: -100px;
  margin-left: -100px;
  will-change: transform;
  z-index: 100;
}

.lm-mod-drag-image {
  will-change: transform;
}

/*
 * Copyright (c) Jupyter Development Team.
 * Distributed under the terms of the Modified BSD License.
 */

.jp-lineFormSearch {
  padding: 4px 12px;
  background-color: var(--jp-layout-color2);
  box-shadow: var(--jp-toolbar-box-shadow);
  z-index: 2;
  font-size: var(--jp-ui-font-size1);
}

.jp-lineFormCaption {
  font-size: var(--jp-ui-font-size0);
  line-height: var(--jp-ui-font-size1);
  margin-top: 4px;
  color: var(--jp-ui-font-color0);
}

.jp-baseLineForm {
  border: none;
  border-radius: 0;
  position: absolute;
  background-size: 16px;
  background-repeat: no-repeat;
  background-position: center;
  outline: none;
}

.jp-lineFormButtonContainer {
  top: 4px;
  right: 8px;
  height: 24px;
  padding: 0 12px;
  width: 12px;
}

.jp-lineFormButtonIcon {
  top: 0;
  right: 0;
  background-color: var(--jp-brand-color1);
  height: 100%;
  width: 100%;
  box-sizing: border-box;
  padding: 4px 6px;
}

.jp-lineFormButton {
  top: 0;
  right: 0;
  background-color: transparent;
  height: 100%;
  width: 100%;
  box-sizing: border-box;
}

.jp-lineFormWrapper {
  overflow: hidden;
  padding: 0 8px;
  border: 1px solid var(--jp-border-color0);
  background-color: var(--jp-input-active-background);
  height: 22px;
}

.jp-lineFormWrapperFocusWithin {
  border: var(--jp-border-width) solid var(--md-blue-500);
  box-shadow: inset 0 0 4px var(--md-blue-300);
}

.jp-lineFormInput {
  background: transparent;
  width: 200px;
  height: 100%;
  border: none;
  outline: none;
  color: var(--jp-ui-font-color0);
  line-height: 28px;
}

/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

.jp-JSONEditor {
  display: flex;
  flex-direction: column;
  width: 100%;
}

.jp-JSONEditor-host {
  flex: 1 1 auto;
  border: var(--jp-border-width) solid var(--jp-input-border-color);
  border-radius: 0;
  background: var(--jp-layout-color0);
  min-height: 50px;
  padding: 1px;
}

.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
  border-color: red;
  outline-color: red;
}

.jp-JSONEditor-header {
  display: flex;
  flex: 1 0 auto;
  padding: 0 0 0 12px;
}

.jp-JSONEditor-header label {
  flex: 0 0 auto;
}

.jp-JSONEditor-commitButton {
  height: 16px;
  width: 16px;
  background-size: 18px;
  background-repeat: no-repeat;
  background-position: center;
}

.jp-JSONEditor-host.jp-mod-focused {
  background-color: var(--jp-input-active-background);
  border: 1px solid var(--jp-input-active-border-color);
  box-shadow: var(--jp-input-box-shadow);
}

.jp-Editor.jp-mod-dropTarget {
  border: var(--jp-border-width) solid var(--jp-input-active-border-color);
  box-shadow: var(--jp-input-box-shadow);
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-DocumentSearch-input {
  border: none;
  outline: none;
  color: var(--jp-ui-font-color0);
  font-size: var(--jp-ui-font-size1);
  background-color: var(--jp-layout-color0);
  font-family: var(--jp-ui-font-family);
  padding: 2px 1px;
  resize: none;
}

.jp-DocumentSearch-overlay {
  position: absolute;
  background-color: var(--jp-toolbar-background);
  border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
  border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
  top: 0;
  right: 0;
  z-index: 7;
  min-width: 405px;
  padding: 2px;
  font-size: var(--jp-ui-font-size1);

  --jp-private-document-search-button-height: 20px;
}

.jp-DocumentSearch-overlay button {
  background-color: var(--jp-toolbar-background);
  outline: 0;
}

.jp-DocumentSearch-overlay button:hover {
  background-color: var(--jp-layout-color2);
}

.jp-DocumentSearch-overlay button:active {
  background-color: var(--jp-layout-color3);
}

.jp-DocumentSearch-overlay-row {
  display: flex;
  align-items: center;
  margin-bottom: 2px;
}

.jp-DocumentSearch-button-content {
  display: inline-block;
  cursor: pointer;
  box-sizing: border-box;
  width: 100%;
  height: 100%;
}

.jp-DocumentSearch-button-content svg {
  width: 100%;
  height: 100%;
}

.jp-DocumentSearch-input-wrapper {
  border: var(--jp-border-width) solid var(--jp-border-color0);
  display: flex;
  background-color: var(--jp-layout-color0);
  margin: 2px;
}

.jp-DocumentSearch-input-wrapper:focus-within {
  border-color: var(--jp-cell-editor-active-border-color);
}

.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper {
  all: initial;
  overflow: hidden;
  display: inline-block;
  border: none;
  box-sizing: border-box;
}

.jp-DocumentSearch-toggle-wrapper {
  width: 14px;
  height: 14px;
}

.jp-DocumentSearch-button-wrapper {
  width: var(--jp-private-document-search-button-height);
  height: var(--jp-private-document-search-button-height);
}

.jp-DocumentSearch-toggle-wrapper:focus,
.jp-DocumentSearch-button-wrapper:focus {
  outline: var(--jp-border-width) solid
    var(--jp-cell-editor-active-border-color);
  outline-offset: -1px;
}

.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper,
.jp-DocumentSearch-button-content:focus {
  outline: none;
}

.jp-DocumentSearch-toggle-placeholder {
  width: 5px;
}

.jp-DocumentSearch-input-button::before {
  display: block;
  padding-top: 100%;
}

.jp-DocumentSearch-input-button-off {
  opacity: var(--jp-search-toggle-off-opacity);
}

.jp-DocumentSearch-input-button-off:hover {
  opacity: var(--jp-search-toggle-hover-opacity);
}

.jp-DocumentSearch-input-button-on {
  opacity: var(--jp-search-toggle-on-opacity);
}

.jp-DocumentSearch-index-counter {
  padding-left: 10px;
  padding-right: 10px;
  user-select: none;
  min-width: 35px;
  display: inline-block;
}

.jp-DocumentSearch-up-down-wrapper {
  display: inline-block;
  padding-right: 2px;
  margin-left: auto;
  white-space: nowrap;
}

.jp-DocumentSearch-spacer {
  margin-left: auto;
}

.jp-DocumentSearch-up-down-wrapper button {
  outline: 0;
  border: none;
  width: var(--jp-private-document-search-button-height);
  height: var(--jp-private-document-search-button-height);
  vertical-align: middle;
  margin: 1px 5px 2px;
}

.jp-DocumentSearch-up-down-button:hover {
  background-color: var(--jp-layout-color2);
}

.jp-DocumentSearch-up-down-button:active {
  background-color: var(--jp-layout-color3);
}

.jp-DocumentSearch-filter-button {
  border-radius: var(--jp-border-radius);
}

.jp-DocumentSearch-filter-button:hover {
  background-color: var(--jp-layout-color2);
}

.jp-DocumentSearch-filter-button-enabled {
  background-color: var(--jp-layout-color2);
}

.jp-DocumentSearch-filter-button-enabled:hover {
  background-color: var(--jp-layout-color3);
}

.jp-DocumentSearch-search-options {
  padding: 0 8px;
  margin-left: 3px;
  width: 100%;
  display: grid;
  justify-content: start;
  grid-template-columns: 1fr 1fr;
  align-items: center;
  justify-items: stretch;
}

.jp-DocumentSearch-search-filter-disabled {
  color: var(--jp-ui-font-color2);
}

.jp-DocumentSearch-search-filter {
  display: flex;
  align-items: center;
  user-select: none;
}

.jp-DocumentSearch-regex-error {
  color: var(--jp-error-color0);
}

.jp-DocumentSearch-replace-button-wrapper {
  overflow: hidden;
  display: inline-block;
  box-sizing: border-box;
  border: var(--jp-border-width) solid var(--jp-border-color0);
  margin: auto 2px;
  padding: 1px 4px;
  height: calc(var(--jp-private-document-search-button-height) + 2px);
}

.jp-DocumentSearch-replace-button-wrapper:focus {
  border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
}

.jp-DocumentSearch-replace-button {
  display: inline-block;
  text-align: center;
  cursor: pointer;
  box-sizing: border-box;
  color: var(--jp-ui-font-color1);

  /* height - 2 * (padding of wrapper) */
  line-height: calc(var(--jp-private-document-search-button-height) - 2px);
  width: 100%;
  height: 100%;
}

.jp-DocumentSearch-replace-button:focus {
  outline: none;
}

.jp-DocumentSearch-replace-wrapper-class {
  margin-left: 14px;
  display: flex;
}

.jp-DocumentSearch-replace-toggle {
  border: none;
  background-color: var(--jp-toolbar-background);
  border-radius: var(--jp-border-radius);
}

.jp-DocumentSearch-replace-toggle:hover {
  background-color: var(--jp-layout-color2);
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

.cm-editor {
  line-height: var(--jp-code-line-height);
  font-size: var(--jp-code-font-size);
  font-family: var(--jp-code-font-family);
  border: 0;
  border-radius: 0;
  height: auto;

  /* Changed to auto to autogrow */
}

.cm-editor pre {
  padding: 0 var(--jp-code-padding);
}

.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
  background-color: var(--jp-layout-color0);
  color: var(--jp-content-font-color1);
}

.jp-CodeMirrorEditor {
  cursor: text;
}

/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
    border-left: var(--jp-code-cursor-width1) solid
      var(--jp-editor-cursor-color);
  }
}

/* When zoomed out less than 33% */
@media screen and (min-width: 4320px) {
  .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
    border-left: var(--jp-code-cursor-width2) solid
      var(--jp-editor-cursor-color);
  }
}

.cm-editor.jp-mod-readOnly .cm-cursor {
  display: none;
}

.jp-CollaboratorCursor {
  border-left: 5px solid transparent;
  border-right: 5px solid transparent;
  border-top: none;
  border-bottom: 3px solid;
  background-clip: content-box;
  margin-left: -5px;
  margin-right: -5px;
}

.cm-searching,
.cm-searching span {
  /* `.cm-searching span`: we need to override syntax highlighting */
  background-color: var(--jp-search-unselected-match-background-color);
  color: var(--jp-search-unselected-match-color);
}

.cm-searching::selection,
.cm-searching span::selection {
  background-color: var(--jp-search-unselected-match-background-color);
  color: var(--jp-search-unselected-match-color);
}

.jp-current-match > .cm-searching,
.jp-current-match > .cm-searching span,
.cm-searching > .jp-current-match,
.cm-searching > .jp-current-match span {
  background-color: var(--jp-search-selected-match-background-color);
  color: var(--jp-search-selected-match-color);
}

.jp-current-match > .cm-searching::selection,
.cm-searching > .jp-current-match::selection,
.jp-current-match > .cm-searching span::selection {
  background-color: var(--jp-search-selected-match-background-color);
  color: var(--jp-search-selected-match-color);
}

.cm-trailingspace {
  background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
  background-position: center left;
  background-repeat: repeat-x;
}

.jp-CollaboratorCursor-hover {
  position: absolute;
  z-index: 1;
  transform: translateX(-50%);
  color: white;
  border-radius: 3px;
  padding-left: 4px;
  padding-right: 4px;
  padding-top: 1px;
  padding-bottom: 1px;
  text-align: center;
  font-size: var(--jp-ui-font-size1);
  white-space: nowrap;
}

.jp-CodeMirror-ruler {
  border-left: 1px dashed var(--jp-border-color2);
}

/* Styles for shared cursors (remote cursor locations and selected ranges) */
.jp-CodeMirrorEditor .cm-ySelectionCaret {
  position: relative;
  border-left: 1px solid black;
  margin-left: -1px;
  margin-right: -1px;
  box-sizing: border-box;
}

.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
  white-space: nowrap;
  position: absolute;
  top: -1.15em;
  padding-bottom: 0.05em;
  left: -1px;
  font-size: 0.95em;
  font-family: var(--jp-ui-font-family);
  font-weight: bold;
  line-height: normal;
  user-select: none;
  color: white;
  padding-left: 2px;
  padding-right: 2px;
  z-index: 101;
  transition: opacity 0.3s ease-in-out;
}

.jp-CodeMirrorEditor .cm-ySelectionInfo {
  transition-delay: 0.7s;
  opacity: 0;
}

.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
  opacity: 1;
  transition-delay: 0s;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

.jp-MimeDocument {
  outline: none;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/

:root {
  --jp-private-filebrowser-button-height: 28px;
  --jp-private-filebrowser-button-width: 48px;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

.jp-FileBrowser .jp-SidePanel-content {
  display: flex;
  flex-direction: column;
}

.jp-FileBrowser-toolbar.jp-Toolbar {
  flex-wrap: wrap;
  row-gap: 12px;
  border-bottom: none;
  height: auto;
  margin: 8px 12px 0;
  box-shadow: none;
  padding: 0;
  justify-content: flex-start;
}

.jp-FileBrowser-Panel {
  flex: 1 1 auto;
  display: flex;
  flex-direction: column;
}

.jp-BreadCrumbs {
  flex: 0 0 auto;
  margin: 8px 12px;
}

.jp-BreadCrumbs-item {
  margin: 0 2px;
  padding: 0 2px;
  border-radius: var(--jp-border-radius);
  cursor: pointer;
}

.jp-BreadCrumbs-item:hover {
  background-color: var(--jp-layout-color2);
}

.jp-BreadCrumbs-item:first-child {
  margin-left: 0;
}

.jp-BreadCrumbs-item.jp-mod-dropTarget {
  background-color: var(--jp-brand-color2);
  opacity: 0.7;
}

/*-----------------------------------------------------------------------------
| Buttons
|----------------------------------------------------------------------------*/

.jp-FileBrowser-toolbar > .jp-Toolbar-item {
  flex: 0 0 auto;
  padding-left: 0;
  padding-right: 2px;
  align-items: center;
  height: unset;
}

.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
  width: 40px;
}

/*-----------------------------------------------------------------------------
| Other styles
|----------------------------------------------------------------------------*/

.jp-FileDialog.jp-mod-conflict input {
  color: var(--jp-error-color1);
}

.jp-FileDialog .jp-new-name-title {
  margin-top: 12px;
}

.jp-LastModified-hidden {
  display: none;
}

.jp-FileSize-hidden {
  display: none;
}

.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
  display: none;
}

/*-----------------------------------------------------------------------------
| DirListing
|----------------------------------------------------------------------------*/

.jp-DirListing {
  flex: 1 1 auto;
  display: flex;
  flex-direction: column;
  outline: 0;
}

.jp-DirListing-header {
  flex: 0 0 auto;
  display: flex;
  flex-direction: row;
  align-items: center;
  overflow: hidden;
  border-top: var(--jp-border-width) solid var(--jp-border-color2);
  border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
  box-shadow: var(--jp-toolbar-box-shadow);
  z-index: 2;
}

.jp-DirListing-headerItem {
  padding: 4px 12px 2px;
  font-weight: 500;
}

.jp-DirListing-headerItem:hover {
  background: var(--jp-layout-color2);
}

.jp-DirListing-headerItem.jp-id-name {
  flex: 1 0 84px;
}

.jp-DirListing-headerItem.jp-id-modified {
  flex: 0 0 112px;
  border-left: var(--jp-border-width) solid var(--jp-border-color2);
  text-align: right;
}

.jp-DirListing-headerItem.jp-id-filesize {
  flex: 0 0 75px;
  border-left: var(--jp-border-width) solid var(--jp-border-color2);
  text-align: right;
}

.jp-id-narrow {
  display: none;
  flex: 0 0 5px;
  padding: 4px;
  border-left: var(--jp-border-width) solid var(--jp-border-color2);
  text-align: right;
  color: var(--jp-border-color2);
}

.jp-DirListing-narrow .jp-id-narrow {
  display: block;
}

.jp-DirListing-narrow .jp-id-modified,
.jp-DirListing-narrow .jp-DirListing-itemModified {
  display: none;
}

.jp-DirListing-headerItem.jp-mod-selected {
  font-weight: 600;
}

/* increase specificity to override bundled default */
.jp-DirListing-content {
  flex: 1 1 auto;
  margin: 0;
  padding: 0;
  list-style-type: none;
  overflow: auto;
  background-color: var(--jp-layout-color1);
}

.jp-DirListing-content mark {
  color: var(--jp-ui-font-color0);
  background-color: transparent;
  font-weight: bold;
}

.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
  color: var(--jp-ui-inverse-font-color0);
}

/* Style the directory listing content when a user drops a file to upload */
.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
  outline: 5px dashed rgba(128, 128, 128, 0.5);
  outline-offset: -10px;
  cursor: copy;
}

.jp-DirListing-item {
  display: flex;
  flex-direction: row;
  align-items: center;
  padding: 4px 12px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}

.jp-DirListing-checkboxWrapper {
  /* Increases hit area of checkbox. */
  padding: 4px;
}

.jp-DirListing-header
  .jp-DirListing-checkboxWrapper
  + .jp-DirListing-headerItem {
  padding-left: 4px;
}

.jp-DirListing-content .jp-DirListing-checkboxWrapper {
  position: relative;
  left: -4px;
  margin: -4px 0 -4px -8px;
}

.jp-DirListing-checkboxWrapper.jp-mod-visible {
  visibility: visible;
}

/* For devices that support hovering, hide checkboxes until hovered, selected...
*/
@media (hover: hover) {
  .jp-DirListing-checkboxWrapper {
    visibility: hidden;
  }

  .jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
  .jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
    visibility: visible;
  }
}

.jp-DirListing-item[data-is-dot] {
  opacity: 75%;
}

.jp-DirListing-item.jp-mod-selected {
  color: var(--jp-ui-inverse-font-color1);
  background: var(--jp-brand-color1);
}

.jp-DirListing-item.jp-mod-dropTarget {
  background: var(--jp-brand-color3);
}

.jp-DirListing-item:hover:not(.jp-mod-selected) {
  background: var(--jp-layout-color2);
}

.jp-DirListing-itemIcon {
  flex: 0 0 20px;
  margin-right: 4px;
}

.jp-DirListing-itemText {
  flex: 1 0 64px;
  white-space: nowrap;
  overflow: hidden;
  text-overflow: ellipsis;
  user-select: none;
}

.jp-DirListing-itemText:focus {
  outline-width: 2px;
  outline-color: var(--jp-inverse-layout-color1);
  outline-style: solid;
  outline-offset: 1px;
}

.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
  outline-color: var(--jp-layout-color1);
}

.jp-DirListing-itemModified {
  flex: 0 0 125px;
  text-align: right;
}

.jp-DirListing-itemFileSize {
  flex: 0 0 90px;
  text-align: right;
}

.jp-DirListing-editor {
  flex: 1 0 64px;
  outline: none;
  border: none;
  color: var(--jp-ui-font-color1);
  background-color: var(--jp-layout-color1);
}

.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
  color: var(--jp-success-color1);
  content: '\25CF';
  font-size: 8px;
  position: absolute;
  left: -8px;
}

.jp-DirListing-item.jp-mod-running.jp-mod-selected
  .jp-DirListing-itemIcon::before {
  color: var(--jp-ui-inverse-font-color1);
}

.jp-DirListing-item.lm-mod-drag-image,
.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
  font-size: var(--jp-ui-font-size1);
  padding-left: 4px;
  margin-left: 4px;
  width: 160px;
  background-color: var(--jp-ui-inverse-font-color2);
  box-shadow: var(--jp-elevation-z2);
  border-radius: 0;
  color: var(--jp-ui-font-color1);
  transform: translateX(-40%) translateY(-58%);
}

.jp-Document {
  min-width: 120px;
  min-height: 120px;
  outline: none;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Main OutputArea
| OutputArea has a list of Outputs
|----------------------------------------------------------------------------*/

.jp-OutputArea {
  overflow-y: auto;
}

.jp-OutputArea-child {
  display: table;
  table-layout: fixed;
  width: 100%;
  overflow: hidden;
}

.jp-OutputPrompt {
  width: var(--jp-cell-prompt-width);
  color: var(--jp-cell-outprompt-font-color);
  font-family: var(--jp-cell-prompt-font-family);
  padding: var(--jp-code-padding);
  letter-spacing: var(--jp-cell-prompt-letter-spacing);
  line-height: var(--jp-code-line-height);
  font-size: var(--jp-code-font-size);
  border: var(--jp-border-width) solid transparent;
  opacity: var(--jp-cell-prompt-opacity);

  /* Right align prompt text, don't wrap to handle large prompt numbers */
  text-align: right;
  white-space: nowrap;
  overflow: hidden;
  text-overflow: ellipsis;

  /* Disable text selection */
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}

.jp-OutputArea-prompt {
  display: table-cell;
  vertical-align: top;
}

.jp-OutputArea-output {
  display: table-cell;
  width: 100%;
  height: auto;
  overflow: auto;
  user-select: text;
  -moz-user-select: text;
  -webkit-user-select: text;
  -ms-user-select: text;
}

.jp-OutputArea .jp-RenderedText {
  padding-left: 1ch;
}

/**
 * Prompt overlay.
 */

.jp-OutputArea-promptOverlay {
  position: absolute;
  top: 0;
  width: var(--jp-cell-prompt-width);
  height: 100%;
  opacity: 0.5;
}

.jp-OutputArea-promptOverlay:hover {
  background: var(--jp-layout-color2);
  box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
  cursor: zoom-out;
}

.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
  cursor: zoom-in;
}

/**
 * Isolated output.
 */
.jp-OutputArea-output.jp-mod-isolated {
  width: 100%;
  display: block;
}

/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
  position: relative;
}

body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
  content: '';
  position: absolute;
  top: 0;
  left: 0;
  right: 0;
  bottom: 0;
  background: transparent;
}

/* pre */

.jp-OutputArea-output pre {
  border: none;
  margin: 0;
  padding: 0;
  overflow-x: auto;
  overflow-y: auto;
  word-break: break-all;
  word-wrap: break-word;
  white-space: pre-wrap;
}

/* tables */

.jp-OutputArea-output.jp-RenderedHTMLCommon table {
  margin-left: 0;
  margin-right: 0;
}

/* description lists */

.jp-OutputArea-output dl,
.jp-OutputArea-output dt,
.jp-OutputArea-output dd {
  display: block;
}

.jp-OutputArea-output dl {
  width: 100%;
  overflow: hidden;
  padding: 0;
  margin: 0;
}

.jp-OutputArea-output dt {
  font-weight: bold;
  float: left;
  width: 20%;
  padding: 0;
  margin: 0;
}

.jp-OutputArea-output dd {
  float: left;
  width: 80%;
  padding: 0;
  margin: 0;
}

.jp-TrimmedOutputs pre {
  background: var(--jp-layout-color3);
  font-size: calc(var(--jp-code-font-size) * 1.4);
  text-align: center;
  text-transform: uppercase;
}

/* Hide the gutter in case of
 *  - nested output areas (e.g. in the case of output widgets)
 *  - mirrored output areas
 */
.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
  display: none;
}

/* Hide empty lines in the output area, for instance due to cleared widgets */
.jp-OutputArea-prompt:empty {
  padding: 0;
  border: 0;
}

/*-----------------------------------------------------------------------------
| executeResult is added to any Output-result for the display of the object
| returned by a cell
|----------------------------------------------------------------------------*/

.jp-OutputArea-output.jp-OutputArea-executeResult {
  margin-left: 0;
  width: 100%;
}

/* Text output with the Out[] prompt needs a top padding to match the
 * alignment of the Out[] prompt itself.
 */
.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
  padding-top: var(--jp-code-padding);
  border-top: var(--jp-border-width) solid transparent;
}

/*-----------------------------------------------------------------------------
| The Stdin output
|----------------------------------------------------------------------------*/

.jp-Stdin-prompt {
  color: var(--jp-content-font-color0);
  padding-right: var(--jp-code-padding);
  vertical-align: baseline;
  flex: 0 0 auto;
}

.jp-Stdin-input {
  font-family: var(--jp-code-font-family);
  font-size: inherit;
  color: inherit;
  background-color: inherit;
  width: 42%;
  min-width: 200px;

  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;

  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0 0.25em;
  margin: 0 0.25em;
  flex: 0 0 70%;
}

.jp-Stdin-input::placeholder {
  opacity: 0;
}

.jp-Stdin-input:focus {
  box-shadow: none;
}

.jp-Stdin-input:focus::placeholder {
  opacity: 1;
}

/*-----------------------------------------------------------------------------
| Output Area View
|----------------------------------------------------------------------------*/

.jp-LinkedOutputView .jp-OutputArea {
  height: 100%;
  display: block;
}

.jp-LinkedOutputView .jp-OutputArea-output:only-child {
  height: 100%;
}

/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/

@media print {
  .jp-OutputArea-child {
    break-inside: avoid-page;
  }
}

/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
  .jp-OutputPrompt {
    display: table-row;
    text-align: left;
  }

  .jp-OutputArea-child .jp-OutputArea-output {
    display: table-row;
    margin-left: var(--jp-notebook-padding);
  }
}

/* Trimmed outputs warning */
.jp-TrimmedOutputs > a {
  margin: 10px;
  text-decoration: none;
  cursor: pointer;
}

.jp-TrimmedOutputs > a:hover {
  text-decoration: none;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Table of Contents
|----------------------------------------------------------------------------*/

:root {
  --jp-private-toc-active-width: 4px;
}

.jp-TableOfContents {
  display: flex;
  flex-direction: column;
  background: var(--jp-layout-color1);
  color: var(--jp-ui-font-color1);
  font-size: var(--jp-ui-font-size1);
  height: 100%;
}

.jp-TableOfContents-placeholder {
  text-align: center;
}

.jp-TableOfContents-placeholderContent {
  color: var(--jp-content-font-color2);
  padding: 8px;
}

.jp-TableOfContents-placeholderContent > h3 {
  margin-bottom: var(--jp-content-heading-margin-bottom);
}

.jp-TableOfContents .jp-SidePanel-content {
  overflow-y: auto;
}

.jp-TableOfContents-tree {
  margin: 4px;
}

.jp-TableOfContents ol {
  list-style-type: none;
}

/* stylelint-disable-next-line selector-max-type */
.jp-TableOfContents li > ol {
  /* Align left border with triangle icon center */
  padding-left: 11px;
}

.jp-TableOfContents-content {
  /* left margin for the active heading indicator */
  margin: 0 0 0 var(--jp-private-toc-active-width);
  padding: 0;
  background-color: var(--jp-layout-color1);
}

.jp-tocItem {
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}

.jp-tocItem-heading {
  display: flex;
  cursor: pointer;
}

.jp-tocItem-heading:hover {
  background-color: var(--jp-layout-color2);
}

.jp-tocItem-content {
  display: block;
  padding: 4px 0;
  white-space: nowrap;
  text-overflow: ellipsis;
  overflow-x: hidden;
}

.jp-tocItem-collapser {
  height: 20px;
  margin: 2px 2px 0;
  padding: 0;
  background: none;
  border: none;
  cursor: pointer;
}

.jp-tocItem-collapser:hover {
  background-color: var(--jp-layout-color3);
}

/* Active heading indicator */

.jp-tocItem-heading::before {
  content: ' ';
  background: transparent;
  width: var(--jp-private-toc-active-width);
  height: 24px;
  position: absolute;
  left: 0;
  border-radius: var(--jp-border-radius);
}

.jp-tocItem-heading.jp-tocItem-active::before {
  background-color: var(--jp-brand-color1);
}

.jp-tocItem-heading:hover.jp-tocItem-active::before {
  background: var(--jp-brand-color0);
  opacity: 1;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

.jp-Collapser {
  flex: 0 0 var(--jp-cell-collapser-width);
  padding: 0;
  margin: 0;
  border: none;
  outline: none;
  background: transparent;
  border-radius: var(--jp-border-radius);
  opacity: 1;
}

.jp-Collapser-child {
  display: block;
  width: 100%;
  box-sizing: border-box;

  /* height: 100% doesn't work because the height of its parent is computed from content */
  position: absolute;
  top: 0;
  bottom: 0;
}

/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/

/*
Hiding collapsers in print mode.

Note: input and output wrappers have "display: block" propery in print mode.
*/

@media print {
  .jp-Collapser {
    display: none;
  }
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Header/Footer
|----------------------------------------------------------------------------*/

/* Hidden by zero height by default */
.jp-CellHeader,
.jp-CellFooter {
  height: 0;
  width: 100%;
  padding: 0;
  margin: 0;
  border: none;
  outline: none;
  background: transparent;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Input
|----------------------------------------------------------------------------*/

/* All input areas */
.jp-InputArea {
  display: table;
  table-layout: fixed;
  width: 100%;
  overflow: hidden;
}

.jp-InputArea-editor {
  display: table-cell;
  overflow: hidden;
  vertical-align: top;

  /* This is the non-active, default styling */
  border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
  border-radius: 0;
  background: var(--jp-cell-editor-background);
}

.jp-InputPrompt {
  display: table-cell;
  vertical-align: top;
  width: var(--jp-cell-prompt-width);
  color: var(--jp-cell-inprompt-font-color);
  font-family: var(--jp-cell-prompt-font-family);
  padding: var(--jp-code-padding);
  letter-spacing: var(--jp-cell-prompt-letter-spacing);
  opacity: var(--jp-cell-prompt-opacity);
  line-height: var(--jp-code-line-height);
  font-size: var(--jp-code-font-size);
  border: var(--jp-border-width) solid transparent;

  /* Right align prompt text, don't wrap to handle large prompt numbers */
  text-align: right;
  white-space: nowrap;
  overflow: hidden;
  text-overflow: ellipsis;

  /* Disable text selection */
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}

/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
  .jp-InputArea-editor {
    display: table-row;
    margin-left: var(--jp-notebook-padding);
  }

  .jp-InputPrompt {
    display: table-row;
    text-align: left;
  }
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/

.jp-Placeholder {
  display: table;
  table-layout: fixed;
  width: 100%;
}

.jp-Placeholder-prompt {
  display: table-cell;
  box-sizing: border-box;
}

.jp-Placeholder-content {
  display: table-cell;
  padding: 4px 6px;
  border: 1px solid transparent;
  border-radius: 0;
  background: none;
  box-sizing: border-box;
  cursor: pointer;
}

.jp-Placeholder-contentContainer {
  display: flex;
}

.jp-Placeholder-content:hover,
.jp-InputPlaceholder > .jp-Placeholder-content:hover {
  border-color: var(--jp-layout-color3);
}

.jp-Placeholder-content .jp-MoreHorizIcon {
  width: 32px;
  height: 16px;
  border: 1px solid transparent;
  border-radius: var(--jp-border-radius);
}

.jp-Placeholder-content .jp-MoreHorizIcon:hover {
  border: 1px solid var(--jp-border-color1);
  box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
  background-color: var(--jp-layout-color0);
}

.jp-PlaceholderText {
  white-space: nowrap;
  overflow-x: hidden;
  color: var(--jp-inverse-layout-color3);
  font-family: var(--jp-code-font-family);
}

.jp-InputPlaceholder > .jp-Placeholder-content {
  border-color: var(--jp-cell-editor-border-color);
  background: var(--jp-cell-editor-background);
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Private CSS variables
|----------------------------------------------------------------------------*/

:root {
  --jp-private-cell-scrolling-output-offset: 5px;
}

/*-----------------------------------------------------------------------------
| Cell
|----------------------------------------------------------------------------*/

.jp-Cell {
  padding: var(--jp-cell-padding);
  margin: 0;
  border: none;
  outline: none;
  background: transparent;
}

/*-----------------------------------------------------------------------------
| Common input/output
|----------------------------------------------------------------------------*/

.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
  display: flex;
  flex-direction: row;
  padding: 0;
  margin: 0;

  /* Added to reveal the box-shadow on the input and output collapsers. */
  overflow: visible;
}

/* Only input/output areas inside cells */
.jp-Cell-inputArea,
.jp-Cell-outputArea {
  flex: 1 1 auto;
}

/*-----------------------------------------------------------------------------
| Collapser
|----------------------------------------------------------------------------*/

/* Make the output collapser disappear when there is not output, but do so
 * in a manner that leaves it in the layout and preserves its width.
 */
.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
  border: none !important;
  background: transparent !important;
}

.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
  min-height: var(--jp-cell-collapser-min-height);
}

/*-----------------------------------------------------------------------------
| Output
|----------------------------------------------------------------------------*/

/* Put a space between input and output when there IS output */
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
  margin-top: 5px;
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
  overflow-y: auto;
  max-height: 24em;
  margin-left: var(--jp-private-cell-scrolling-output-offset);
  resize: vertical;
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
  max-height: unset;
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
  content: ' ';
  box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
  width: 100%;
  height: 100%;
  position: sticky;
  bottom: 0;
  top: 0;
  margin-top: -50%;
  float: left;
  display: block;
  pointer-events: none;
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
  padding-top: 6px;
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
  width: calc(
    var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
  );
}

.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
  left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
}

/*-----------------------------------------------------------------------------
| CodeCell
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| MarkdownCell
|----------------------------------------------------------------------------*/

.jp-MarkdownOutput {
  display: table-cell;
  width: 100%;
  margin-top: 0;
  margin-bottom: 0;
  padding-left: var(--jp-code-padding);
}

.jp-MarkdownOutput.jp-RenderedHTMLCommon {
  overflow: auto;
}

/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
.jp-collapseHeadingButton {
  display: flex;
  min-height: var(--jp-cell-collapser-min-height);
  font-size: var(--jp-code-font-size);
  position: absolute;
  background-color: transparent;
  background-size: 25px;
  background-repeat: no-repeat;
  background-position-x: center;
  background-position-y: top;
  background-image: var(--jp-icon-caret-down);
  right: 0;
  top: 0;
  bottom: 0;
}

.jp-collapseHeadingButton.jp-mod-collapsed {
  background-image: var(--jp-icon-caret-right);
}

/*
 set the container font size to match that of content
 so that the nested collapse buttons have the right size
*/
.jp-MarkdownCell .jp-InputPrompt {
  font-size: var(--jp-content-font-size1);
}

/*
  Align collapseHeadingButton with cell top header
  The font sizes are identical to the ones in packages/rendermime/style/base.css
*/
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
  font-size: var(--jp-content-font-size5);
  background-position-y: calc(0.3 * var(--jp-content-font-size5));
}

.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
  font-size: var(--jp-content-font-size4);
  background-position-y: calc(0.3 * var(--jp-content-font-size4));
}

.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
  font-size: var(--jp-content-font-size3);
  background-position-y: calc(0.3 * var(--jp-content-font-size3));
}

.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
  font-size: var(--jp-content-font-size2);
  background-position-y: calc(0.3 * var(--jp-content-font-size2));
}

.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
  font-size: var(--jp-content-font-size1);
  background-position-y: top;
}

.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
  font-size: var(--jp-content-font-size0);
  background-position-y: top;
}

/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
  display: none;
}

.jp-Notebook.jp-mod-showHiddenCellsButton
  :is(.jp-MarkdownCell:hover, .jp-mod-active)
  .jp-collapseHeadingButton {
  display: flex;
}

/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
  margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
  margin-top: var(--jp-code-padding);
  border: 1px solid var(--jp-border-color2);
  background-color: var(--jp-border-color3) !important;
  color: var(--jp-content-font-color0) !important;
  display: flex;
}

.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
  background-color: var(--jp-border-color2) !important;
}

.jp-showHiddenCellsButton {
  display: none;
}

/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/

/*
Using block instead of flex to allow the use of the break-inside CSS property for
cell outputs.
*/

@media print {
  .jp-Cell-inputWrapper,
  .jp-Cell-outputWrapper {
    display: block;
  }
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/

:root {
  --jp-notebook-toolbar-padding: 2px 5px 2px 2px;
}

/*-----------------------------------------------------------------------------

/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/

.jp-NotebookPanel-toolbar {
  padding: var(--jp-notebook-toolbar-padding);

  /* disable paint containment from lumino 2.0 default strict CSS containment */
  contain: style size !important;
}

.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
  border: none;
  box-shadow: none;
}

.jp-Notebook-toolbarCellTypeDropdown select {
  height: 24px;
  font-size: var(--jp-ui-font-size1);
  line-height: 14px;
  border-radius: 0;
  display: block;
}

.jp-Notebook-toolbarCellTypeDropdown span {
  top: 5px !important;
}

.jp-Toolbar-responsive-popup {
  position: absolute;
  height: fit-content;
  display: flex;
  flex-direction: row;
  flex-wrap: wrap;
  justify-content: flex-end;
  border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
  box-shadow: var(--jp-toolbar-box-shadow);
  background: var(--jp-toolbar-background);
  min-height: var(--jp-toolbar-micro-height);
  padding: var(--jp-notebook-toolbar-padding);
  z-index: 1;
  right: 0;
  top: 0;
}

.jp-Toolbar > .jp-Toolbar-responsive-opener {
  margin-left: auto;
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------

/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/

.jp-Notebook-ExecutionIndicator {
  position: relative;
  display: inline-block;
  height: 100%;
  z-index: 9997;
}

.jp-Notebook-ExecutionIndicator-tooltip {
  visibility: hidden;
  height: auto;
  width: max-content;
  width: -moz-max-content;
  background-color: var(--jp-layout-color2);
  color: var(--jp-ui-font-color1);
  text-align: justify;
  border-radius: 6px;
  padding: 0 5px;
  position: fixed;
  display: table;
}

.jp-Notebook-ExecutionIndicator-tooltip.up {
  transform: translateX(-50%) translateY(-100%) translateY(-32px);
}

.jp-Notebook-ExecutionIndicator-tooltip.down {
  transform: translateX(calc(-100% + 16px)) translateY(5px);
}

.jp-Notebook-ExecutionIndicator-tooltip.hidden {
  display: none;
}

.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
  visibility: visible;
}

.jp-Notebook-ExecutionIndicator span {
  font-size: var(--jp-ui-font-size1);
  font-family: var(--jp-ui-font-family);
  color: var(--jp-ui-font-color1);
  line-height: 24px;
  display: block;
}

.jp-Notebook-ExecutionIndicator-progress-bar {
  display: flex;
  justify-content: center;
  height: 100%;
}

/*
 * Copyright (c) Jupyter Development Team.
 * Distributed under the terms of the Modified BSD License.
 */

/*
 * Execution indicator
 */
.jp-tocItem-content::after {
  content: '';

  /* Must be identical to form a circle */
  width: 12px;
  height: 12px;
  background: none;
  border: none;
  position: absolute;
  right: 0;
}

.jp-tocItem-content[data-running='0']::after {
  border-radius: 50%;
  border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
  background: none;
}

.jp-tocItem-content[data-running='1']::after {
  border-radius: 50%;
  border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
  background-color: var(--jp-inverse-layout-color3);
}

.jp-tocItem-content[data-running='0'],
.jp-tocItem-content[data-running='1'] {
  margin-right: 12px;
}

/*
 * Copyright (c) Jupyter Development Team.
 * Distributed under the terms of the Modified BSD License.
 */

.jp-Notebook-footer {
  height: 27px;
  margin-left: calc(
    var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
      var(--jp-cell-padding)
  );
  width: calc(
    100% -
      (
        var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
          var(--jp-cell-padding) + var(--jp-cell-padding)
      )
  );
  border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
  color: var(--jp-ui-font-color3);
  margin-top: 6px;
  background: none;
  cursor: pointer;
}

.jp-Notebook-footer:focus {
  border-color: var(--jp-cell-editor-active-border-color);
}

/* For devices that support hovering, hide footer until hover */
@media (hover: hover) {
  .jp-Notebook-footer {
    opacity: 0;
  }

  .jp-Notebook-footer:focus,
  .jp-Notebook-footer:hover {
    opacity: 1;
  }
}

/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| Imports
|----------------------------------------------------------------------------*/

/*-----------------------------------------------------------------------------
| CSS variables
|----------------------------------------------------------------------------*/

:root {
  --jp-side-by-side-output-size: 1fr;
  --jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
  --jp-private-notebook-dragImage-width: 304px;
  --jp-private-notebook-dragImage-height: 36px;
  --jp-private-notebook-selected-color: var(--md-blue-400);
  --jp-private-notebook-active-color: var(--md-green-400);
}

/*-----------------------------------------------------------------------------
| Notebook
|----------------------------------------------------------------------------*/

/* stylelint-disable selector-max-class */

.jp-NotebookPanel {
  display: block;
  height: 100%;
}

.jp-NotebookPanel.jp-Document {
  min-width: 240px;
  min-height: 120px;
}

.jp-Notebook {
  padding: var(--jp-notebook-padding);
  outline: none;
  overflow: auto;
  background: var(--jp-layout-color0);
}

.jp-Notebook.jp-mod-scrollPastEnd::after {
  display: block;
  content: '';
  min-height: var(--jp-notebook-scroll-padding);
}

.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
  contain: strict;
}

.jp-Notebook .jp-Cell {
  overflow: visible;
}

.jp-Notebook .jp-Cell .jp-InputPrompt {
  cursor: move;
}

/*-----------------------------------------------------------------------------
| Notebook state related styling
|
| The notebook and cells each have states, here are the possibilities:
|
| - Notebook
|   - Command
|   - Edit
| - Cell
|   - None
|   - Active (only one can be active)
|   - Selected (the cells actions are applied to)
|   - Multiselected (when multiple selected, the cursor)
|   - No outputs
|----------------------------------------------------------------------------*/

/* Command or edit modes */

.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
  opacity: var(--jp-cell-prompt-not-active-opacity);
  color: var(--jp-cell-prompt-not-active-font-color);
}

.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
  opacity: var(--jp-cell-prompt-not-active-opacity);
  color: var(--jp-cell-prompt-not-active-font-color);
}

/* cell is active */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
  background: var(--jp-brand-color1);
}

/* cell is dirty */
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
  color: var(--jp-warn-color1);
}

.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
  color: var(--jp-warn-color1);
  content: '•';
}

.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
  background: var(--jp-warn-color1);
}

/* collapser is hovered */
.jp-Notebook .jp-Cell .jp-Collapser:hover {
  box-shadow: var(--jp-elevation-z2);
  background: var(--jp-brand-color1);
  opacity: var(--jp-cell-collapser-not-active-hover-opacity);
}

/* cell is active and collapser is hovered */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
  background: var(--jp-brand-color0);
  opacity: 1;
}

/* Command mode */

.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
  background: var(--jp-notebook-multiselected-color);
}

.jp-Notebook.jp-mod-commandMode
  .jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
  background: transparent;
}

/* Edit mode */

.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
  border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
  box-shadow: var(--jp-input-box-shadow);
  background-color: var(--jp-cell-editor-active-background);
}

/*-----------------------------------------------------------------------------
| Notebook drag and drop
|----------------------------------------------------------------------------*/

.jp-Notebook-cell.jp-mod-dropSource {
  opacity: 0.5;
}

.jp-Notebook-cell.jp-mod-dropTarget,
.jp-Notebook.jp-mod-commandMode
  .jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
  border-top-color: var(--jp-private-notebook-selected-color);
  border-top-style: solid;
  border-top-width: 2px;
}

.jp-dragImage {
  display: block;
  flex-direction: row;
  width: var(--jp-private-notebook-dragImage-width);
  height: var(--jp-private-notebook-dragImage-height);
  border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
  background: var(--jp-cell-editor-background);
  overflow: visible;
}

.jp-dragImage-singlePrompt {
  box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}

.jp-dragImage .jp-dragImage-content {
  flex: 1 1 auto;
  z-index: 2;
  font-size: var(--jp-code-font-size);
  font-family: var(--jp-code-font-family);
  line-height: var(--jp-code-line-height);
  padding: var(--jp-code-padding);
  border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
  background: var(--jp-cell-editor-background-color);
  color: var(--jp-content-font-color3);
  text-align: left;
  margin: 4px 4px 4px 0;
}

.jp-dragImage .jp-dragImage-prompt {
  flex: 0 0 auto;
  min-width: 36px;
  color: var(--jp-cell-inprompt-font-color);
  padding: var(--jp-code-padding);
  padding-left: 12px;
  font-family: var(--jp-cell-prompt-font-family);
  letter-spacing: var(--jp-cell-prompt-letter-spacing);
  line-height: 1.9;
  font-size: var(--jp-code-font-size);
  border: var(--jp-border-width) solid transparent;
}

.jp-dragImage-multipleBack {
  z-index: -1;
  position: absolute;
  height: 32px;
  width: 300px;
  top: 8px;
  left: 8px;
  background: var(--jp-layout-color2);
  border: var(--jp-border-width) solid var(--jp-input-border-color);
  box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}

/*-----------------------------------------------------------------------------
| Cell toolbar
|----------------------------------------------------------------------------*/

.jp-NotebookTools {
  display: block;
  min-width: var(--jp-sidebar-min-width);
  color: var(--jp-ui-font-color1);
  background: var(--jp-layout-color1);

  /* This is needed so that all font sizing of children done in ems is
    * relative to this base size */
  font-size: var(--jp-ui-font-size1);
  overflow: auto;
}

.jp-ActiveCellTool {
  padding: 12px 0;
  display: flex;
}

.jp-ActiveCellTool-Content {
  flex: 1 1 auto;
}

.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
  background: var(--jp-cell-editor-background);
  border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
  border-radius: 0;
  min-height: 29px;
}

.jp-ActiveCellTool .jp-InputPrompt {
  min-width: calc(var(--jp-cell-prompt-width) * 0.75);
}

.jp-ActiveCellTool-CellContent > pre {
  padding: 5px 4px;
  margin: 0;
  white-space: normal;
}

.jp-MetadataEditorTool {
  flex-direction: column;
  padding: 12px 0;
}

.jp-RankedPanel > :not(:first-child) {
  margin-top: 12px;
}

.jp-KeySelector select.jp-mod-styled {
  font-size: var(--jp-ui-font-size1);
  color: var(--jp-ui-font-color0);
  border: var(--jp-border-width) solid var(--jp-border-color1);
}

.jp-KeySelector label,
.jp-MetadataEditorTool label,
.jp-NumberSetter label {
  line-height: 1.4;
}

.jp-NotebookTools .jp-select-wrapper {
  margin-top: 4px;
  margin-bottom: 0;
}

.jp-NumberSetter input {
  width: 100%;
  margin-top: 4px;
}

.jp-NotebookTools .jp-Collapse {
  margin-top: 16px;
}

/*-----------------------------------------------------------------------------
| Presentation Mode (.jp-mod-presentationMode)
|----------------------------------------------------------------------------*/

.jp-mod-presentationMode .jp-Notebook {
  --jp-content-font-size1: var(--jp-content-presentation-font-size1);
  --jp-code-font-size: var(--jp-code-presentation-font-size);
}

.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
  flex: 0 0 110px;
}

/*-----------------------------------------------------------------------------
| Side-by-side Mode (.jp-mod-sideBySide)
|----------------------------------------------------------------------------*/
.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
  margin-top: 3em;
  margin-bottom: 3em;
  margin-left: 5%;
  margin-right: 5%;
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
  display: grid;
  grid-template-columns: minmax(0, 1fr) min-content minmax(
      0,
      var(--jp-side-by-side-output-size)
    );
  grid-template-rows: auto minmax(0, 1fr) auto;
  grid-template-areas:
    'header header header'
    'input handle output'
    'footer footer footer';
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
  grid-template-columns: minmax(0, 1fr) min-content minmax(
      0,
      var(--jp-side-by-side-resized-cell)
    );
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
  grid-area: header;
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
  grid-area: input;
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
  /* overwrite the default margin (no vertical separation needed in side by side move */
  margin-top: 0;
  grid-area: output;
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
  grid-area: footer;
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
  grid-area: handle;
  user-select: none;
  display: block;
  height: 100%;
  cursor: ew-resize;
  padding: 0 var(--jp-cell-padding);
}

.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
  content: '';
  display: block;
  background: var(--jp-border-color2);
  height: 100%;
  width: 5px;
}

.jp-mod-sideBySide.jp-Notebook
  .jp-CodeCell.jp-mod-resizedCell
  .jp-CellResizeHandle::after {
  background: var(--jp-border-color0);
}

.jp-CellResizeHandle {
  display: none;
}

/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/

.jp-Cell-Placeholder {
  padding-left: 55px;
}

.jp-Cell-Placeholder-wrapper {
  background: #fff;
  border: 1px solid;
  border-color: #e5e6e9 #dfe0e4 #d0d1d5;
  border-radius: 4px;
  -webkit-border-radius: 4px;
  margin: 10px 15px;
}

.jp-Cell-Placeholder-wrapper-inner {
  padding: 15px;
  position: relative;
}

.jp-Cell-Placeholder-wrapper-body {
  background-repeat: repeat;
  background-size: 50% auto;
}

.jp-Cell-Placeholder-wrapper-body div {
  background: #f6f7f8;
  background-image: -webkit-linear-gradient(
    left,
    #f6f7f8 0%,
    #edeef1 20%,
    #f6f7f8 40%,
    #f6f7f8 100%
  );
  background-repeat: no-repeat;
  background-size: 800px 104px;
  height: 104px;
  position: absolute;
  right: 15px;
  left: 15px;
  top: 15px;
}

div.jp-Cell-Placeholder-h1 {
  top: 20px;
  height: 20px;
  left: 15px;
  width: 150px;
}

div.jp-Cell-Placeholder-h2 {
  left: 15px;
  top: 50px;
  height: 10px;
  width: 100px;
}

div.jp-Cell-Placeholder-content-1,
div.jp-Cell-Placeholder-content-2,
div.jp-Cell-Placeholder-content-3 {
  left: 15px;
  right: 15px;
  height: 10px;
}

div.jp-Cell-Placeholder-content-1 {
  top: 100px;
}

div.jp-Cell-Placeholder-content-2 {
  top: 120px;
}

div.jp-Cell-Placeholder-content-3 {
  top: 140px;
}

</style>
<style type="text/css">
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.

Many variables appear in an ordered sequence (0,1,2,3). These sequences
are designed to work well together, so for example, `--jp-border-color1` should
be used with `--jp-layout-color1`. The numbers have the following meanings:

* 0: super-primary, reserved for special emphasis
* 1: primary, most important under normal situations
* 2: secondary, next most important under normal situations
* 3: tertiary, next most important under normal situations

Throughout JupyterLab, we are mostly following principles from Google's
Material Design when selecting colors. We are not, however, following
all of MD as it is not optimized for dense, information rich UIs.
*/

:root {
  /* Elevation
   *
   * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
   *
   * https://github.com/material-components/material-components-web
   * https://material-components-web.appspot.com/elevation.html
   */

  --jp-shadow-base-lightness: 0;
  --jp-shadow-umbra-color: rgba(
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    0.2
  );
  --jp-shadow-penumbra-color: rgba(
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    0.14
  );
  --jp-shadow-ambient-color: rgba(
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    var(--jp-shadow-base-lightness),
    0.12
  );
  --jp-elevation-z0: none;
  --jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
    0 1px 1px 0 var(--jp-shadow-penumbra-color),
    0 1px 3px 0 var(--jp-shadow-ambient-color);
  --jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
    0 2px 2px 0 var(--jp-shadow-penumbra-color),
    0 1px 5px 0 var(--jp-shadow-ambient-color);
  --jp-elevation-z4: 0 2px 4px -1px var(--jp-shadow-umbra-color),
    0 4px 5px 0 var(--jp-shadow-penumbra-color),
    0 1px 10px 0 var(--jp-shadow-ambient-color);
  --jp-elevation-z6: 0 3px 5px -1px var(--jp-shadow-umbra-color),
    0 6px 10px 0 var(--jp-shadow-penumbra-color),
    0 1px 18px 0 var(--jp-shadow-ambient-color);
  --jp-elevation-z8: 0 5px 5px -3px var(--jp-shadow-umbra-color),
    0 8px 10px 1px var(--jp-shadow-penumbra-color),
    0 3px 14px 2px var(--jp-shadow-ambient-color);
  --jp-elevation-z12: 0 7px 8px -4px var(--jp-shadow-umbra-color),
    0 12px 17px 2px var(--jp-shadow-penumbra-color),
    0 5px 22px 4px var(--jp-shadow-ambient-color);
  --jp-elevation-z16: 0 8px 10px -5px var(--jp-shadow-umbra-color),
    0 16px 24px 2px var(--jp-shadow-penumbra-color),
    0 6px 30px 5px var(--jp-shadow-ambient-color);
  --jp-elevation-z20: 0 10px 13px -6px var(--jp-shadow-umbra-color),
    0 20px 31px 3px var(--jp-shadow-penumbra-color),
    0 8px 38px 7px var(--jp-shadow-ambient-color);
  --jp-elevation-z24: 0 11px 15px -7px var(--jp-shadow-umbra-color),
    0 24px 38px 3px var(--jp-shadow-penumbra-color),
    0 9px 46px 8px var(--jp-shadow-ambient-color);

  /* Borders
   *
   * The following variables, specify the visual styling of borders in JupyterLab.
   */

  --jp-border-width: 1px;
  --jp-border-color0: var(--md-grey-400);
  --jp-border-color1: var(--md-grey-400);
  --jp-border-color2: var(--md-grey-300);
  --jp-border-color3: var(--md-grey-200);
  --jp-inverse-border-color: var(--md-grey-600);
  --jp-border-radius: 2px;

  /* UI Fonts
   *
   * The UI font CSS variables are used for the typography all of the JupyterLab
   * user interface elements that are not directly user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-ui-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

  --jp-ui-font-scale-factor: 1.2;
  --jp-ui-font-size0: 0.83333em;
  --jp-ui-font-size1: 13px; /* Base font size */
  --jp-ui-font-size2: 1.2em;
  --jp-ui-font-size3: 1.44em;
  --jp-ui-font-family: system-ui, -apple-system, blinkmacsystemfont, 'Segoe UI',
    helvetica, arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji',
    'Segoe UI Symbol';

  /*
   * Use these font colors against the corresponding main layout colors.
   * In a light theme, these go from dark to light.
   */

  /* Defaults use Material Design specification */
  --jp-ui-font-color0: rgba(0, 0, 0, 1);
  --jp-ui-font-color1: rgba(0, 0, 0, 0.87);
  --jp-ui-font-color2: rgba(0, 0, 0, 0.54);
  --jp-ui-font-color3: rgba(0, 0, 0, 0.38);

  /*
   * Use these against the brand/accent/warn/error colors.
   * These will typically go from light to darker, in both a dark and light theme.
   */

  --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1);
  --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1);
  --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7);
  --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5);

  /* Content Fonts
   *
   * Content font variables are used for typography of user generated content.
   *
   * The font sizing here is done assuming that the body font size of --jp-content-font-size1
   * is applied to a parent element. When children elements, such as headings, are sized
   * in em all things will be computed relative to that body size.
   */

  --jp-content-line-height: 1.6;
  --jp-content-font-scale-factor: 1.2;
  --jp-content-font-size0: 0.83333em;
  --jp-content-font-size1: 14px; /* Base font size */
  --jp-content-font-size2: 1.2em;
  --jp-content-font-size3: 1.44em;
  --jp-content-font-size4: 1.728em;
  --jp-content-font-size5: 2.0736em;

  /* This gives a magnification of about 125% in presentation mode over normal. */
  --jp-content-presentation-font-size1: 17px;
  --jp-content-heading-line-height: 1;
  --jp-content-heading-margin-top: 1.2em;
  --jp-content-heading-margin-bottom: 0.8em;
  --jp-content-heading-font-weight: 500;

  /* Defaults use Material Design specification */
  --jp-content-font-color0: rgba(0, 0, 0, 1);
  --jp-content-font-color1: rgba(0, 0, 0, 0.87);
  --jp-content-font-color2: rgba(0, 0, 0, 0.54);
  --jp-content-font-color3: rgba(0, 0, 0, 0.38);
  --jp-content-link-color: var(--md-blue-900);
  --jp-content-font-family: system-ui, -apple-system, blinkmacsystemfont,
    'Segoe UI', helvetica, arial, sans-serif, 'Apple Color Emoji',
    'Segoe UI Emoji', 'Segoe UI Symbol';

  /*
   * Code Fonts
   *
   * Code font variables are used for typography of code and other monospaces content.
   */

  --jp-code-font-size: 13px;
  --jp-code-line-height: 1.3077; /* 17px for 13px base */
  --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */
  --jp-code-font-family-default: menlo, consolas, 'DejaVu Sans Mono', monospace;
  --jp-code-font-family: var(--jp-code-font-family-default);

  /* This gives a magnification of about 125% in presentation mode over normal. */
  --jp-code-presentation-font-size: 16px;

  /* may need to tweak cursor width if you change font size */
  --jp-code-cursor-width0: 1.4px;
  --jp-code-cursor-width1: 2px;
  --jp-code-cursor-width2: 4px;

  /* Layout
   *
   * The following are the main layout colors use in JupyterLab. In a light
   * theme these would go from light to dark.
   */

  --jp-layout-color0: white;
  --jp-layout-color1: white;
  --jp-layout-color2: var(--md-grey-200);
  --jp-layout-color3: var(--md-grey-400);
  --jp-layout-color4: var(--md-grey-600);

  /* Inverse Layout
   *
   * The following are the inverse layout colors use in JupyterLab. In a light
   * theme these would go from dark to light.
   */

  --jp-inverse-layout-color0: #111;
  --jp-inverse-layout-color1: var(--md-grey-900);
  --jp-inverse-layout-color2: var(--md-grey-800);
  --jp-inverse-layout-color3: var(--md-grey-700);
  --jp-inverse-layout-color4: var(--md-grey-600);

  /* Brand/accent */

  --jp-brand-color0: var(--md-blue-900);
  --jp-brand-color1: var(--md-blue-700);
  --jp-brand-color2: var(--md-blue-300);
  --jp-brand-color3: var(--md-blue-100);
  --jp-brand-color4: var(--md-blue-50);
  --jp-accent-color0: var(--md-green-900);
  --jp-accent-color1: var(--md-green-700);
  --jp-accent-color2: var(--md-green-300);
  --jp-accent-color3: var(--md-green-100);

  /* State colors (warn, error, success, info) */

  --jp-warn-color0: var(--md-orange-900);
  --jp-warn-color1: var(--md-orange-700);
  --jp-warn-color2: var(--md-orange-300);
  --jp-warn-color3: var(--md-orange-100);
  --jp-error-color0: var(--md-red-900);
  --jp-error-color1: var(--md-red-700);
  --jp-error-color2: var(--md-red-300);
  --jp-error-color3: var(--md-red-100);
  --jp-success-color0: var(--md-green-900);
  --jp-success-color1: var(--md-green-700);
  --jp-success-color2: var(--md-green-300);
  --jp-success-color3: var(--md-green-100);
  --jp-info-color0: var(--md-cyan-900);
  --jp-info-color1: var(--md-cyan-700);
  --jp-info-color2: var(--md-cyan-300);
  --jp-info-color3: var(--md-cyan-100);

  /* Cell specific styles */

  --jp-cell-padding: 5px;
  --jp-cell-collapser-width: 8px;
  --jp-cell-collapser-min-height: 20px;
  --jp-cell-collapser-not-active-hover-opacity: 0.6;
  --jp-cell-editor-background: var(--md-grey-100);
  --jp-cell-editor-border-color: var(--md-grey-300);
  --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300);
  --jp-cell-editor-active-background: var(--jp-layout-color0);
  --jp-cell-editor-active-border-color: var(--jp-brand-color1);
  --jp-cell-prompt-width: 64px;
  --jp-cell-prompt-font-family: var(--jp-code-font-family-default);
  --jp-cell-prompt-letter-spacing: 0;
  --jp-cell-prompt-opacity: 1;
  --jp-cell-prompt-not-active-opacity: 0.5;
  --jp-cell-prompt-not-active-font-color: var(--md-grey-700);

  /* A custom blend of MD grey and blue 600
   * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */
  --jp-cell-inprompt-font-color: #307fc1;

  /* A custom blend of MD grey and orange 600
   * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */
  --jp-cell-outprompt-font-color: #bf5b3d;

  /* Notebook specific styles */

  --jp-notebook-padding: 10px;
  --jp-notebook-select-background: var(--jp-layout-color1);
  --jp-notebook-multiselected-color: var(--md-blue-50);

  /* The scroll padding is calculated to fill enough space at the bottom of the
  notebook to show one single-line cell (with appropriate padding) at the top
  when the notebook is scrolled all the way to the bottom. We also subtract one
  pixel so that no scrollbar appears if we have just one single-line cell in the
  notebook. This padding is to enable a 'scroll past end' feature in a notebook.
  */
  --jp-notebook-scroll-padding: calc(
    100% - var(--jp-code-font-size) * var(--jp-code-line-height) -
      var(--jp-code-padding) - var(--jp-cell-padding) - 1px
  );

  /* Rendermime styles */

  --jp-rendermime-error-background: #fdd;
  --jp-rendermime-table-row-background: var(--md-grey-100);
  --jp-rendermime-table-row-hover-background: var(--md-light-blue-50);

  /* Dialog specific styles */

  --jp-dialog-background: rgba(0, 0, 0, 0.25);

  /* Console specific styles */

  --jp-console-padding: 10px;

  /* Toolbar specific styles */

  --jp-toolbar-border-color: var(--jp-border-color1);
  --jp-toolbar-micro-height: 8px;
  --jp-toolbar-background: var(--jp-layout-color1);
  --jp-toolbar-box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.24);
  --jp-toolbar-header-margin: 4px 4px 0 4px;
  --jp-toolbar-active-background: var(--md-grey-300);

  /* Statusbar specific styles */

  --jp-statusbar-height: 24px;

  /* Input field styles */

  --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300);
  --jp-input-active-background: var(--jp-layout-color1);
  --jp-input-hover-background: var(--jp-layout-color1);
  --jp-input-background: var(--md-grey-100);
  --jp-input-border-color: var(--jp-inverse-border-color);
  --jp-input-active-border-color: var(--jp-brand-color1);
  --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3);

  /* General editor styles */

  --jp-editor-selected-background: #d9d9d9;
  --jp-editor-selected-focused-background: #d7d4f0;
  --jp-editor-cursor-color: var(--jp-ui-font-color0);

  /* Code mirror specific styles */

  --jp-mirror-editor-keyword-color: #008000;
  --jp-mirror-editor-atom-color: #88f;
  --jp-mirror-editor-number-color: #080;
  --jp-mirror-editor-def-color: #00f;
  --jp-mirror-editor-variable-color: var(--md-grey-900);
  --jp-mirror-editor-variable-2-color: rgb(0, 54, 109);
  --jp-mirror-editor-variable-3-color: #085;
  --jp-mirror-editor-punctuation-color: #05a;
  --jp-mirror-editor-property-color: #05a;
  --jp-mirror-editor-operator-color: #a2f;
  --jp-mirror-editor-comment-color: #408080;
  --jp-mirror-editor-string-color: #ba2121;
  --jp-mirror-editor-string-2-color: #708;
  --jp-mirror-editor-meta-color: #a2f;
  --jp-mirror-editor-qualifier-color: #555;
  --jp-mirror-editor-builtin-color: #008000;
  --jp-mirror-editor-bracket-color: #997;
  --jp-mirror-editor-tag-color: #170;
  --jp-mirror-editor-attribute-color: #00c;
  --jp-mirror-editor-header-color: blue;
  --jp-mirror-editor-quote-color: #090;
  --jp-mirror-editor-link-color: #00c;
  --jp-mirror-editor-error-color: #f00;
  --jp-mirror-editor-hr-color: #999;

  /*
    RTC user specific colors.
    These colors are used for the cursor, username in the editor,
    and the icon of the user.
  */

  --jp-collaborator-color1: #ffad8e;
  --jp-collaborator-color2: #dac83d;
  --jp-collaborator-color3: #72dd76;
  --jp-collaborator-color4: #00e4d0;
  --jp-collaborator-color5: #45d4ff;
  --jp-collaborator-color6: #e2b1ff;
  --jp-collaborator-color7: #ff9de6;

  /* Vega extension styles */

  --jp-vega-background: white;

  /* Sidebar-related styles */

  --jp-sidebar-min-width: 250px;

  /* Search-related styles */

  --jp-search-toggle-off-opacity: 0.5;
  --jp-search-toggle-hover-opacity: 0.8;
  --jp-search-toggle-on-opacity: 1;
  --jp-search-selected-match-background-color: rgb(245, 200, 0);
  --jp-search-selected-match-color: black;
  --jp-search-unselected-match-background-color: var(
    --jp-inverse-layout-color0
  );
  --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);

  /* Icon colors that work well with light or dark backgrounds */
  --jp-icon-contrast-color0: var(--md-purple-600);
  --jp-icon-contrast-color1: var(--md-green-600);
  --jp-icon-contrast-color2: var(--md-pink-600);
  --jp-icon-contrast-color3: var(--md-blue-600);

  /* Button colors */
  --jp-accept-color-normal: var(--md-blue-700);
  --jp-accept-color-hover: var(--md-blue-800);
  --jp-accept-color-active: var(--md-blue-900);
  --jp-warn-color-normal: var(--md-red-700);
  --jp-warn-color-hover: var(--md-red-800);
  --jp-warn-color-active: var(--md-red-900);
  --jp-reject-color-normal: var(--md-grey-600);
  --jp-reject-color-hover: var(--md-grey-700);
  --jp-reject-color-active: var(--md-grey-800);

  /* File or activity icons and switch semantic variables */
  --jp-jupyter-icon-color: #f37626;
  --jp-notebook-icon-color: #f37626;
  --jp-json-icon-color: var(--md-orange-700);
  --jp-console-icon-background-color: var(--md-blue-700);
  --jp-console-icon-color: white;
  --jp-terminal-icon-background-color: var(--md-grey-800);
  --jp-terminal-icon-color: var(--md-grey-200);
  --jp-text-editor-icon-color: var(--md-grey-700);
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">pandas</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pd</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">sklearn</span>
</pre></div>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [2]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.model_selection</span><span class="w"> </span><span class="kn">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.preprocessing</span><span class="w"> </span><span class="kn">import</span> <span class="n">StandardScaler</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.feature_selection</span><span class="w"> </span><span class="kn">import</span> <span class="n">SelectKBest</span><span class="p">,</span> <span class="n">f_regression</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.preprocessing</span><span class="w"> </span><span class="kn">import</span> <span class="n">PolynomialFeatures</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.linear_model</span><span class="w"> </span><span class="kn">import</span> <span class="n">LinearRegression</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.metrics</span><span class="w"> </span><span class="kn">import</span> <span class="n">mean_squared_error</span><span class="p">,</span> <span class="n">r2_score</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.metrics</span><span class="w"> </span><span class="kn">import</span> <span class="n">accuracy_score</span><span class="p">,</span> <span class="n">confusion_matrix</span><span class="p">,</span> <span class="n">classification_report</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.ensemble</span><span class="w"> </span><span class="kn">import</span> <span class="n">RandomForestClassifier</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.feature_selection</span><span class="w"> </span><span class="kn">import</span> <span class="n">SelectKBest</span><span class="p">,</span> <span class="n">f_classif</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.tree</span><span class="w"> </span><span class="kn">import</span> <span class="n">DecisionTreeClassifier</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.tree</span><span class="w"> </span><span class="kn">import</span> <span class="n">plot_tree</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.svm</span><span class="w"> </span><span class="kn">import</span> <span class="n">SVC</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.neighbors</span><span class="w"> </span><span class="kn">import</span> <span class="n">KNeighborsClassifier</span>
</pre></div>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [3]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">42</span><span class="p">)</span>
<span class="n">num_samples</span> <span class="o">=</span> <span class="mi">1000</span>
<span class="n">num_features</span> <span class="o">=</span> <span class="mi">5</span>
</pre></div>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [4]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="n">num_samples</span><span class="p">,</span> <span class="n">num_features</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">X</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">3</span> <span class="o">*</span> <span class="n">X</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="mf">1.5</span> <span class="o">*</span> <span class="n">X</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">num_samples</span><span class="p">)</span>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [5]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="sa">f</span><span class="s1">'feature_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1">'</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_features</span><span class="p">)])</span>
<span class="n">data</span><span class="p">[</span><span class="s1">'target'</span><span class="p">]</span> <span class="o">=</span> <span class="n">y</span>
<span class="n">data</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [6]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">'target'</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span> <span class="n">data</span><span class="p">[</span><span class="s1">'target'</span><span class="p">],</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">'Preprocessed Training Data:'</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">X_train</span><span class="p">[:</span><span class="mi">5</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Preprocessed Test Data:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">X_test</span><span class="p">[:</span><span class="mi">5</span><span class="p">])</span>
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<pre>Preprocessed Training Data:
[[-1.5473679   0.37872881  0.03089569 -1.55488568 -0.75189973]
 [-0.70063534 -0.41930746 -1.55164707 -1.34441438  0.07537366]
 [ 1.04135125  1.53844675  0.14927325 -0.02274824 -0.3221057 ]
 [-0.85419091  1.53747908 -1.05745737  1.60025265  1.74570635]
 [-0.31095684  0.58648415  0.66988519 -0.63016713 -1.25910019]]

Preprocessed Test Data:
[[ 0.05550636 -1.47861257 -0.77538262  0.74322377 -1.50503515]
 [ 0.24022411  1.43356579 -0.37972489 -1.5033965  -1.65685761]
 [ 0.39462326  0.60626423 -0.62808674  1.23802106  1.57950277]
 [-0.20696345  1.65813719  0.23158568 -0.60940267 -0.95603721]
 [ 0.58916395 -0.1073603  -0.29271802  0.54688279  0.17849699]]
</pre>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_regression</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [8]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">selected_feature_indices</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">get_support</span><span class="p">(</span><span class="n">indices</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">selected_feature_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">selected_feature_indices</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Selected Features:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">selected_feature_names</span><span class="p">)</span>
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<pre>Selected Features:
['feature_0', 'feature_1', 'feature_2']
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<div class="jp-InputPrompt jp-InputArea-prompt">In [9]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">poly</span> <span class="o">=</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">X_train_poly</span> <span class="o">=</span> <span class="n">poly</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">)</span>
<span class="n">X_test_poly</span> <span class="o">=</span> <span class="n">poly</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Engineered Training Features:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">X_train_poly</span><span class="p">[:</span><span class="mi">5</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Engineered Testing Features:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">X_test_poly</span><span class="p">[:</span><span class="mi">5</span><span class="p">])</span>
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<pre>
Engineered Training Features:
[[-1.54736790e+00  3.78728815e-01  3.08956924e-02  2.39434742e+00
  -5.86032811e-01 -4.78070027e-02  1.43435515e-01  1.17010890e-02
   9.54543809e-04]
 [-7.00635340e-01 -4.19307459e-01 -1.55164707e+00  4.90889880e-01
   2.93781624e-01  1.08713877e+00  1.75818745e-01  6.50617189e-01
   2.40760861e+00]
 [ 1.04135125e+00  1.53844675e+00  1.49273246e-01  1.08441243e+00
   1.60206345e+00  1.55445882e-01  2.36681839e+00  2.29648940e-01
   2.22825021e-02]
 [-8.54190911e-01  1.53747908e+00 -1.05745737e+00  7.29642112e-01
  -1.31330065e+00  9.03270474e-01  2.36384192e+00 -1.62581858e+00
   1.11821609e+00]
 [-3.10956843e-01  5.86484145e-01  6.69885191e-01  9.66941580e-02
  -1.82371258e-01 -2.08305384e-01  3.43963653e-01  3.92877044e-01
   4.48746169e-01]]

Engineered Testing Features:
[[ 0.05550636 -1.47861257 -0.77538262  0.00308096 -0.0820724  -0.04303867
   2.18629512  1.14649049  0.60121821]
 [ 0.24022411  1.43356579 -0.37972489  0.05770762  0.34437706 -0.09121907
   2.05511086 -0.54436061  0.14419099]
 [ 0.39462326  0.60626423 -0.62808674  0.15572752  0.23924597 -0.24785764
   0.36755632 -0.38078652  0.39449295]
 [-0.20696345  1.65813719  0.23158568  0.04283387 -0.34317379 -0.04792977
   2.74941893  0.38400083  0.05363193]
 [ 0.58916395 -0.1073603  -0.29271802  0.34711415 -0.06325282 -0.1724589
   0.01152623  0.0314263   0.08568384]]
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<div class="jp-InputPrompt jp-InputArea-prompt">In [11]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_poly</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_poly</span><span class="p">)</span>
<span class="n">mse</span> <span class="o">=</span> <span class="n">mean_squared_error</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">r2</span> <span class="o">=</span> <span class="n">r2_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Mean Squared Error (MSE): </span><span class="si">{</span><span class="n">mse</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"R-Squared (R2) Score: </span><span class="si">{</span><span class="n">r2</span><span class="si">}</span><span class="s2"> "</span><span class="p">)</span>
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<pre>Mean Squared Error (MSE): 1.1183008767157094
R-Squared (R2) Score: 0.5059535177636776 
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<div class="jp-InputPrompt jp-InputArea-prompt">In [13]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'blue'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Predicted vs Actual'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">y_test</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">y_test</span><span class="p">)],</span> <span class="p">[</span><span class="nb">min</span><span class="p">(</span><span class="n">y_test</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">y_test</span><span class="p">)],</span> <span class="n">color</span><span class="o">=</span><span class="s1">'red'</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s1">'--'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'Ideal Prediction'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Actual Values'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Predicted Values'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Actual vs Predicted Values'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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pORIRM48OGHxqM8jzeXX345/v77b/zxxx+455579C/3ESNGBN326NGjjh23ePHiETum+omNGzdi/vz56Nu3L95+++1kD4cQQkg2KGocZMoUoHJloEUL4MYbjUd5LuvjSb58+XRxtUqVKuH2229Hq1atMG3atCwuo2HDhqFcuXKoWbOmXr9p0yZcf/312nog4qR9+/ZYv359lhT3u+++W78uKe733XefrnsSSHb305EjRzBw4EDdHl7GJFajt956S++3hVwMAKeeeqq22Mi4hBMnTmD48OGoUqWKTj+uU6cOJk2alOU406dPxxlnnKFfl/0EjjMYN954Izp16pRlnWT+lCxZEu+9955+Lsc455xz9D7l/OSaHThwIOx+x4wZg7Zt2+pr/OGHH+LQoUNZXhcr1G233YYyZcogf/78OPvss/HZZ59pK9XNN9+MPXv2ZFrVRHgK8vcnn3ySZT9yzcWyYyLXVM5fspiqVq2Khx9+mJlMhBASBIoahxDhct11wObNWddv2WKsj7ewCUQm6kCLzDfffIPVq1dj5syZepKVCVHcKGJlmTt3Lr7//nsULlxYW3zM9z377LN6YhWLxLx587Br1y58/PHHYY/brVs3Pdm/9NJL+O233zB69Gi9XxE5kydP1tvIOMSq9OKLL+rnImhEaLz22mv49ddfcdddd+Gmm27CnDlzMsXXNddcg6uuugrLly/H//73P9x///1hx9GlSxd8+umn2L9/f+a6r776Shei69Chgz5+586d0bNnTz1OER1yjOyiLRB5TUSNjK1WrVpasAWKLxFnV1xxhb6WH3zwAVauXIknn3xSu6qaNGmCF154AUWKFNHHluXee++FVeRzks9C9inX7Y033sDzzz9v+f2EEBJXVq6Ea1ApxJ49e2TW0o/ZOXTokFq5cqV+tMvx40pVqCAzYvAlLU2pihWN7Zyme/fuqn379vrvEydOqJkzZ6p8+fKpe++9N/P1MmXKqCNHjmS+5/3331c1a9bU25vI6wUKFFBfffWVfn7aaaepp59+OvP1Y8eOqQoVKmQeS2jWrJnq16+f/nv16tX62srxgzFr1iz9+u7duzPXHT58WBUsWFDNnz8/y7a9evVSnTt31n8PGjRI1a5dO8vrAwcOzLGvQGSsJUuWVO+9917mOtlfp06d9N8//vijfv/69euVVWbMmKFKlSql9y08//zz+vxN5Lqlp6fr6xCMMWPGqKJFi+ZYL+P4+OOPs6yT7WT7UIwYMULVq1cv8/ngwYNVnTp1Qm4fy71NCCEhOXhQqVtvVSo9Xalvv1XJmr8DYUVhB5g7N6eFJhCZujZtMrZr3tz544v1RSwiYoERi4G4X0z3hiBuFgkiNvnpp5+wZs2aHPEwhw8fxtq1a7WbRKwJF1xwQeZruXPnRv369UNaM8SKIlaJZs2aWR63jEGsJ5deemmW9WItOu+88/TfYkkJHIfQuHHjsPuVsYprbezYsejatat2K02dOhXjx4/Xr4uLq2XLlvq6iMXqsssuw3XXXaddY6EQi5W4tGTfglh6BgwYoK9XtWrV9PlXqFBBu4mcZsKECdr6JccS65MEgYvVhxBCksaqVcD11wMrVogfHVi61Ii5SDKeETUySQ8dOjTLOokPWSUXNsn8/bez29lF4kxeffVVLVwkbsaceE0KFSqU5blMjPXq1dOTfnZKlSoVUzl+O5juoc8//xzly5fP8prE5MSCuKBEYEl7AHG7yfjEvSaI+JJ1EvQ7Y8YMjBw5Eg8++CAWLVqkY3uyY7reRDTKdQ6MOxKxI/FK0Zy/GVOTXSgGxsssWLBAn4vc+yLAihYtqsWZuAcJISQpvP8+cPvtgMQhlikDfPAB0KoV3IBnRI1w1lln4euvv858nn3yThZW+wTGq5+giBaJ8bDK+eefr3/9Sy+gUL/4pfmhTPIXX3yxfi7WgR9//FG/Nxhi9RArkcTCSNBtdkxLkQgBk9q1a2vxIllFoSw8Z555ZmbQs8nChQsjnqPEsUgsj5znF198gY4dOyJPnjxZxETTpk318sgjj+ggaxEuEhydHRF/YoXJHtArgkjEhaTQn3vuudi8eTN+//33oNYaOf/Acw8UkWIVM5EMNrFemYjwkrGJ6DLZsGFDxPMnhBDHERFzxx2SNWE8v+QS+YIEypaFW3CHKrCIiBjJ8nEbF10EVKhgBAUH886IZU5el+3cgPzyl5RvyXiSCVkmbJkope6MZDnJ8379+ulA1xo1aujA2Oeeey5sjZnKlSuje/fuOvhWXCXi4pF9iqVEXEEyMYuQEFfZlVdeqS0b4v6SgFkJDhZBdOGFF2rXlwTbitiS/fXu3VsLB3H1SJCwCKvAzKBwiBtOApBFaMyaNStzvYg1CZ4Wt5MIO3m+fft2LaCCIRlc4p6SbKZARDQNGjQIX375Jdq0aaMF4LXXXquvlYhMsSLKOYuFSK6PWKbkuHJtJJNJlksuuQSjRo3SLjURPZLpFCi+5PqL6BPrTIMGDbRVK1LANiGExAX5gSmCJj1d3CfAAw+I6RuuQnkECYaUoFIJYK1SpYq68cYb1YYNG8K+RwJRJajIXDZt2hSXQGFh8mQjIFiW7EHCssjr8SAwUNjO63///bfq1q2bDqiVwOKqVauqW265JfPaSECsBAEXKVJEFStWTN199916+1CBwoJcu7vuukt/Rnnz5lXVq1dXb7/9dubrjz76qCpbtqxKS0vT4xIkWPmFF17Qgct58uTRwbitW7dWc+bMyXzfp59+qvcl47zooov0PsMFCpvI5ynbVapUKUtQtKyXY8ixZJ9nnHGGGjlyZNB9LFmyRO/jhx9+CPr6FVdcoTp06KD/3rlzp7r55ptViRIlVP78+dXZZ5+tPvvss8xte/furV+T/cn9LGzZskVddtllqlChQqpGjRpq+vTpOQKFBwwYoN9XuHBhHewsQcqBQccMFCaEJIQTJ5Tq318yPxJ+aKuBwmnyDzyAuBDkl67E0Yi5XmIMtmzZgl9++SVkAbhgcTiCWAOyu10kSHbdunU6pkJqjESDpG3365c1aLhiReCFF4Brrolql4TEjBP3NiEkBdm/H3jkEeDhh6XIWFKHsnfvXh1TGGz+DsQzoiY74goRl4aY+nv16hV0GykGJ0vgRRGXQbxEjSBhE5LlJGESEkMjLie3WedIakFRQwixzU8/GdlNv/8OXHutVCz1hKjxVExN9qqrEpApacGhkCDUWLNo7CICJh5p24QQQkjcUQp4/XXD7SBGAQkITULj4pSrKCyuKKnbIVk6hBBCCImRvXulCBfQu7chaNq0AZYtAy68EF7BM6JGsmQkXVj6/kiaq5S7l3ojUgSNEEIIITEgNd+kZMeECZJqDEhTZMl2KlkSXsIz7iepASICZufOnbq2h6T/Sr2SaIvFEUIIIeQ/SpeWyp9ApUqAVF9v1AhexDOixixxTwghhBCHiukVLGgUUyteXMq7A1LdPcmZTinhfiKEEEKIQ/zwAyAFRd966+Q6ee5hQSNQ1BBCCCGplN30/PNG8O/69UYhtePH4RcoagghhJBUYNcuoH17QHrcSfzMddcB339vBAb7BIqaFKB58+bo73CdgXjsM1qkF5TULQqsJF23bt2Y9unEPgghxDUsWADId9qnn0oRN+CVV4CJE4GiReEnKGo8To8ePXD11VfDbYjQkGaOsqSnp+smmTfffLNucJmI9H9pHGkVGWP2Dtx290EIIa5lyxajKuymTdIlF1i4ELj9diNA2Gf4x+ZEXIeUsl69erXuwP3TTz9pUfPXX3/hq6++yrGtdKg2BVCsFC5cWC/J3gchhLiC8uWBQYOMlgejRwMh+iX6AVpqfMaBAwfQrVs3PSFLteVnn302xzbSD0ssEeXLl0ehQoVwwQUXYPbs2ZmvSy0gqQkkrxcsWBDnnHMOPvzwQ9tjEZFStmxZlCtXDldccQXuvPNOfP311zh06FCmy2jatGmoXbu2bmexcePGiGMT5L2nn366HpsUYZTxRnIdvf322zjrrLP0ceS69O3bV6+vXLmyfpT9yHjN59n3IcLs0Ucf1RYn2Ye89uWXX2a+LkUh5f1TpkxBixYt9Njq1KmDBWLyJYSQRPPdd8Aff5x8Lo0px471taARKGqs5PGHWg4ftr7toUPWto2RAQMG6MrLU6dOxYwZM7QgWLp0aZZtZEKXyVZq//z888/o2LEjLr/8cvzx338AaYBYr149fP7557oL+q233oquXbviB0kBjIECBQpocXD8v0j7gwcP4qmnnsKbb76JX3/9FaVLl444tkWLFukGprLd8uXLtYB4/PHHwx731VdfRZ8+ffR5rFixQgup6tWr69cWL16sH8eMGaO7v5vPs/Piiy9qgfjMM8/ocbVu3Rrt2rXLHJfJgw8+qEWZjE16k4k4NM+XEELiTkYGIN+JLVoYDSnNeUqs4D50N+VApRB79uyRjuT6MTuHDh1SK1eu1I9ZMBLggi9XXpl124IFQ2/brFnWbUuWDL6dTbp3767at2+v/963b5/KmzevmjhxYubrO3fuVAUKFFD9+vXTzzds2KBy5cqltmzZkmU/LVu2VIMGDQp5nDZt2qh77rkn83mzZs0y9xmMMWPGqKJFi2Y+//3339UZZ5yh6tevn/m6fBbLly/P3MbK2Dp37qyuzHbdO3XqlOVYgwcPVnXq1Ml8Xq5cOfXggw+GHKuM4+OPP86yLtg+hg0blmWbBg0aqP/7v//Tf69bt07v580338x8/ddff9XrfvvtN5VMQt7bhBB/8c8/SrVqdXI+6dpVqf37ld/n70AYU+MjpMHn0aNHtcvGpHjx4qhZs2bmc7FUSPyKWBECEbdPiRIl9N/y+hNPPIGJEydiy5Ytep/yurhU7CAt4sUNJtYZsf5IawuxypjkzZsX5557rq2x/fbbb9pVFEjjxo2zuIICkcBkieNp2bKlrbFnb3kv+2jatGmW9fJcYoUCCTwfs9mqjKFWrVpRH58QQiLy7bdAly7AP/8YVYJfflkySZBqUNREYv/+0K/lypX1ebjMnuwBsFL0KEndzaUR6I8//qgfAzEDY0eMGKHdLS+88IKOp5HYFknfFnFjh1NOOUW7viT4VyZ4cT8FIs8lDsXO2OyS/ZjxJk+ePJl/m+cmoo4QQuLmbnrsMeDRRw37zFlnGanatWsjFaGoiUShQsnf1iLVqlXTk6rEnUggrbB79278/vvvaNasmX5+3nnnaWuIWA8uuuiioPv5/vvv0b59e9x0002Zk7LsQwJ67SBixoxdsYKVsZ155pn6/AKRxqbhhJUE/0p6tsTfBEOumRw3XBaXBDvLdTGvoyDPGzZsaOHMCCEkTsiPJrFUi6Dp1Qt46SXDUpOiUNT4CLFmSBCtBAuLu0YCbyVwNTBNWlw7Xbp00RlSEvgqQmL79u160hfXSZs2bVCjRg1MmjQJ8+fPx6mnnornnnsOW7dutS1q7GJlbJJBJW4fCdgV4SXp4aFcTyaSydS7d299PSQLa9++fVqQ3HHHHfp1U/TIfiWzSc45O3JNBw8erIWjZD5JYLEEA4+VbAJCCEk0ImLEGizW4QkTjMrAN96IVIfZTz5DXEdi5bjqqqvQqlUrHccimUyByIQswuGee+7R8TZSvE+yfkzrzkMPPYTzzz9fZ/hI5WBJy05Ugb9IY2vUqBHeeOMN7R6TlGnJ8JLxhqN79+7alfbKK6/otO62bdtmyVoSATVz5kxUrFhRC6lgiJi6++679bjEJSdCSrKoRAASQkjCkGzKBx8EHnjg5LpKlSho/iNNooWRIkjAZ9GiRXUAq7gUApFA1nXr1qFKlSrInz9/0sZIiNPw3ibEJ2zeDHTuDMybZzxfscLorJ3i83cgtNQQQgghbmf6dKN3kwgaKaAnLqcUETR2oKghhBBC3Ip0077vPqBNGyn3Dpx/PiAFVaWwHskBA4UJIYSQ/7Kj584F/v5b6kwBkoSZvXJHQpHokLZtgRkzjOeS3DBihNFlmwSFlhpCCCEpz5QpkglpdBeQmFt5lOeyPmlIdlO3bkDRosDkyUa6NgVNWChqspFCcdMkReA9TUh4RLhcd50RhxvIli3G+oQKGylyumrVyedSJXjNGuCaaxI4CO9CUZOtEqw0WSTET5j3dGC1Y0LISZdTv36Gpyc75rr+/Y3t4s6ff0r/FeCSS7JWqC9ZMgEH9weMqfkPKctfrFgxXc1WkD5HgSX8CfGihUYEjdzTcm9nbz1BCDFiaLJbaLILm02bjO2aN4/jQMS91LOn5C4DUgBUammVLh3HA/oTipoApMicYAobQvyACBrz3iaEZEWCgp3czjaHDwP33ms0oBQaNwbGjwf+KzhK7EFRE4BYZqTxopTTPyZpdIR4HHE50UJDSGgky8nJ7Wwh1phOnYBly4znAwcazSnpKo4aipogyCTAiYAQQvyPpG1XqGAEBQeLq5EoBHk9RI/d2HjqKUPQSMzMe+8BV1wRh4OkFgwUJoQQkrLI79cXXzT+zh5GaT5/4YU41at57jkjZXv5cgoah6CoIYQQktJItvSkSUD58lnXi4VG1juWTS2p2uJiMk1C0sPo3XdzHphEDd1PhBBCUh4RLu3bx7Gi8PvvA7ffDhw4YFT1k7+J41DUEEIIIf+5ohxP2xYRI+0Nxowxnkup4quv9kcbBxeOjaKGEEIIiQe//mo0nly5EkhPBwYPBh58MKrZXqoaS5HAwJo64h6TeKBkFxue4qKxMaaGEEIIcZqJE4EGDQxBI3WivvkGeOSRqAWNa9o4uHxsnhU1Tz75pK4r01/qVxNCCCFuQkwV0sfpssuAn36K2q/lqjYOHhibJ0XN4sWLMXr0aJx77rnJHgohhBBisG/fyb+bNAHmzQO++CKmdgd22jgkGjeOzXOiZv/+/ejSpQveeOMNnCr9MQghhJBkIrP36NFGVpPE0Zg0amTE0ni5jYPHxuY5UdOnTx+0adMGrVq1irjtkSNHsHfv3iwLIYQQ4hgyr3TuDPTuDezaZYgbv7Rx8ODYPCVqxo8fj6VLl2L48OGWtpftihYtmrlUrFgx7mMkhBCSIixdCtSrB0yYAOTODTz9tFF+OA5tHLJXOzaR9TK1xaWNgwfH5hlRs2nTJvTr1w9jx45F/vz5Lb1n0KBB2LNnT+Yi+yCEEEJidjeNGmV01F6zxuio/d13wIABMbubXNXGwYNjS1MqWNyy+/jkk0/QoUOHLI0mMzIydAZUenq6djVFakIp7iex2IjAKSLlqQkhhPiKhBSBGz/ecDkJ7doZhfWKF4/rOIPVghEriIgGN9apqejw2KzO354RNfv27cOGDRuyrLv55ptRq1YtDBw4EGeffXbEfVDUEEKIf0lYEThRJFdeaSx33hna/+LwON1StTcZY/OdqAlG8+bNUbduXbxg0YdJUUMIIf7ELAKXfUYz9UZMjSllp++9B9xwA5Avn7HuxImoXE1xHaePsTp/eyamhhBCCEl4ETjJaJJOlz16APfee3J9erre3+zZwIcfGo+R9u/GYnV+w9O9n2bLXUQIISSlsVMEzlZh3/nzDeuMvDlvXqBWrZhcSHEbJ8mElhpCCCGexvEicOJakvTsiy82VEb16sDChVIoLaZ+R24sVuc3KGoIIYR4GkeLwO3YAbRtCwwcaPiBxFLz44/AeefF7EJyY7E6v0FRQwghxNM4WgRu/35gwQJA6qFJdeBx44CAwNRY+h25sVid36CoIYQQ4mliLgIXaHaR/k1Sh2bRIuDWW3PsMBYXkhuL1fkNihpCCCGeR4JzJR26fPms60uWNNxFUhsvaFbR1q3AFVcAX355cl3r1sC55wY9TqwupFDjFAsO07ljx9N1auzCOjWEEOJvzCJwU6cCH3xghMiEzE769lugSxfgn3+ASpWAP/4A8uSJuH8x5khQcLDZUywucpx168JbXNxcSM/L87enU7oJIYSQQEQYSGkZES/ZRYeZnTRpQgau+fUx4NFHjY1q1wY++iiioDH3L/uW/YiACTyGHReSvM60beeh+4kQQkhM2C1CF++xhMtOKqv+RpmulwJDhxorevYEFi82hI1F6EJyL7TUEEIIcX+/JYuEy04qja1Yhrooc2QbMvIXQq43XgNuuimq48i5SaFhupDcBUUNIYSQqAjVxyjTzZMEq0W47KRtKIPP0Bb1sQSbHpuAtjedrBAcDXQhuQ+6nwghhNjGrX2MsmcdlcdmlMT2zOd3YCQaYSEK149N0BB3QlFDCCHENrEUoYsngQXursB0LEddvI+uSMMJ/frhtIIoVbEAC9z5FIoaQgghtnFrHyNxCb307DE8pe7DdLRBSexEaWxDcexigbsUgDE1hBBCbOPaPkYbN6LDCzcAWKCfjkRfDMAIHEF+VKxgCBpmJ/kXihpCCCFRu3kiFaFLqJtn2jSgRw9g926gaFFkvPEWzil1LcYwOylloKghhBBiG6eK0DnG0aPAPfcYgqZBA92/KVfVqmByUmrBmBpCCCFR4aoidHnzAhMmGMJm3jygatUEHpy4BfZ+IoQQEhNJ62MkhXKkJ8L//pfccZC4w95PhBBCEkLCi9AdPgwMGACMGmVYaBo1wpTfz3ZVZWOSHOh+IoQQ4h3WrAGaNDEEjdC/Pz5eWVPH9mSvm2NWNhaDDkkNaKkhhBDiDSRm5pZbgH37gBIlgPfeQ0brK3Fn5dCVjSVoWSobS5+mWFxRdG15A4oaQggh7qdvX+Dll42/L7zQaAleoQLmzrZe2TiciyycaAnWtFOCo2+9FahRw38iJ8PDAo6ihhBCiPsxex888AAwZAiQO7djlY3DdRoXQjXtHDzYf/E7U1zWdd0uzH4ihBDiTvbuBczv6hMngCVLgIYNs2wyezbQokXkXT30ENCyZU6rQ6hO42atneLFgZ07I+/f3D4ZncmdYkqEa5HMc7M6f1PUEEIIcRcHDwJ33AEsXAj88ANQqFBYV0nlyqErG2enVCnglVeMydt8bzj3lR3MKsrr1nnHXWMS6Vok+9yszt/MfiKEEOIeVq40KgK//Tbw22/AN99YqmwcaFEIx/btQMeOwH33Re40bpdkdSb3c9d1u1DUEEIIST4ya44ZA9SvbwibsmWBr78G2rWLurJxOEaMAD7+GHEh0Z3J/dx13S4UNYQQQpLL/v1A9+5Az57AoUPApZcCy5cDl1xieRcibNavB2bNMuJnrPDuu4gLCe9M7ueu6zahqCGEEJfGOEgQrGQuy6M89y2SbvP++1Dp6fiz1zB82P1LzP6tjO1zNisb165tbfs9e4wYm1BuK1kv5XDMvyMh21SsmODO5A53XU9L8/a5UdQQQogLs1AkaFOyem680XiU576tjPvoo/i3Sl1cV2I2qr31AG68KT2mc7ZjTejSxXjMPpmbz19/HZg8ObJrKymdyR0kV5jYJC+dG0UNIYS4MK3W1yX/JVX7/fczn05ZVB7F1y3FlO0XOXLOYk0QC4wVpNJwpE7jga6tceOAoUON10Nt71WucVPX9SjxTEr3q6++qpf1cmcBOOuss/DII4/giiuusLwPpnQTQtyM29NqHalGu2wZcP31Rg+nKVOQ0a5DXM5ZJmHJcgqHuFPM/dqtouvlqruRcOO5+a5OzaeffopcuXKhRo0akCG/++67GDFiBJYtW6YFjhUoagghbsZqITmxGCS0K7YT1Wg7KKNAzN13A0ePGopiwgTMPtLY0jlLIpQUz7ODpG1LllMoseQV6wOB/+rUXHXVVbjyyiu1qDnjjDMwbNgwFC5cGAulOBMhhPgAt6fVhgteDuc263ntv1hQsaPRv+noUair2hnZTY0bWz4XMe7YdUM9/TQwcSJQsmTW9aKnKGj8iWdETSAZGRkYP348Dhw4gMaNG4fc7siRI1rdBS6EEOJW3JxWGy54WcSNWGiC2f3rqcVYivPReMtkHEUe3IXnUOr7TzBldnFb57JrV3TxNeKC+uefk/Ew8iguJwoaf+IZ95OwYsUKLWIOHz6srTTjxo3T1ptQDBkyBEMloisbdD8RQtxIpJL/scTUxBInEaknkPSXDGzuGEgHTMEUXIt1qIxOmIDFONm7SbKKJFDXapsDL8QUkfjgu5ga4ejRo9i4caM+qUmTJuHNN9/EnDlzUDtEUQKx1MgSeFEqVqxIUUMIcS2mgBACv51jaSoYS+dlK8HLOZs+ysBP5gX3wBh8jA7Yg2JZ3itjkNyPqVODiyavxRT5nYwkBhBbjolVHqZly5bq1ltvtbz9nj175L+MfiSEELcyebJSFSrIFH9yqVjRWB/NvtLSsu5LFlknS6R9zpqV873hlguwQP2A+uo0bLG0vezfHGfx4taOMW7cyfEdP27sQ9bJozwnibkn5Xk092Q0WJ2/PRlTY3LixIkslhhCCPED2euiRBsHEi7WxVzXv3/4asVWA3lPKXQC92IE5uIiNMASDMcgS+8z9y/nJkG9VjDjcILF+chrd92VAlWYE8gUL9VOUh7h/vvvV3PmzFHr1q1TP//8s36elpamZsyYYXkftNQQQlIJq1YW01oS7T5KYLv6FG0yV3yITuoU7LF9bLGyyK//YJalQOuAbDdxYuR9J9KS4FeO//eZhLrG8lmJFTHeFjLfWWq2bduGbt26oWbNmmjZsiUWL16Mr776CpdK4zNCCCFxSRGP1BOoKeZhOeqiLT7HYeTDbXgNnfEh9iFy3KLs1+wlZMZrRIqtkX6XAwcCnTtH3L22LLjOkuAx5s4NHU8lyGe1aZOxnRvIDY/w1ltvJXsIhBCSciniZk8gEQcibAIFx5WYjqloh9zIwGqcgesxET+jjuXxyX5l/8ECmdPTJcQg53skIPnZZ2ELcbFJlhUzpuwH/rq9dlJ2PGOpIYQQYg/TyhIOK52XQ/UEWlO+GXYUr4n3cRPq4UfLgkY6X0s6t+w3VLxGMEETDW6zJLilE/sUi01T3Vw7ydOWGkJIcnBjHxhiDfmcxE0TqlWAcMMN1j5PESBt2wIfPbAMiw7XQdXq6fi//yuEH76ah27tJFU7hH/qP266yZg0JRVbFrPfUqhAZqdxiyXBiTT7WP/PTglRd8gM/A0sG2AK40i1kyIJ44ShUggGChPijTROr6TphhqnW8YfKcjTTBU/ciTyeCdPPK6eKTJEHUe6GoCnMu8FCdgNF9wbLpDUbrp4LEu4YOhEE2uafSz/Z49HEfhrjjf7mJ0Yr9PzN0UNIcTRL95YJ/Rk18OIdZwDBrhn/FZFQ8mS4cf72Zt/q69xSeYGo3GLAk5k3gtyztFMenKPxFvMJCo7xw3ZRJMt/J+NNiPOydpJ0UBREwSKGkKc++KV17/+Oqt4iVWQxPMXrJOEGme465WM8ccqGsaPV+rHp2aqrWml9Yp9KKRuwntBJ+GPPrI/6cXbUuO2+8apNPtYxNIHH9gvcBh4jGRZIK3O34ypIYRElcYpr7dqlTX4M2up/NB++mgKxYnv3g1ZLNHEgSRr/LEEb+bCcfxxwxB0xBNIh8LPOEdnN61GraCBuNIJWwoG2om/ktdD3TdOILEeL7zgXPNKJ+LL4pVNZDX1evv26O8dOVe3t6egqCGEOBJUGWpisjqh26mHkcwv1kjjdNP4IwV5hqMmVmMARmhBMxq3oj9ewGEUCHvPWJn0AoVB6dKRx5U9tVuytSS4WTKGAj8HWf/cc4a4MvctbNtmZBaZAiRaYeJUYK9Vobl1q3GOVsdo9f9sqVIeC/y1CUUNISTu6ZlWJnSv1MOI9fiJHH+4GjORWImzcAdGYi+KYAJucOSeCSYMIiGCRurSyP4DJ/jhw0OLEzlOjx45BYhkgmUXQ1aEiZ1soexkF1FNmkQWmnIe0urBzhit/p8tXz70PWEWWBTrlmczHFUKwZgaQqxhpVx9NEswP328Yw2cJtY4kGSMP1isU/YlN46qYRikzsOPtuNWrAS22o1DClyk0WWscVnRxt3EEtgrmWHBgrBDBVZHO8bAcaZZzEJLduCvXRgoHASKGkKsEyqNM14TuhUhVaqUkX7sRcFnTipW0qfjNW4J7A7WCbsiNqh5aKKf/I7qKi8OOzbZBl6zWO6deB7HibTz7Pe2CJdwxwuWJZcrV3RjjDb1+rhLSg9YgaImCBQ1hDj/Cz/WScOukHJDnRy7gi8w9dlKdlik40c7GQWboNtimtqJU/WTf1FEXYuPLH+uVn/ZO5HlZOUeiocVzWoGWaAVUjLBrFy7QIH7/PPRjzGQyR6zwFiFoiYIFDWE2CdwApVf+natFHbTaiMJqXin6VpNSw81eQQTLuZ6K+nqkY4fS9p84ASdB0fUM7g7c8UPqK+qYK2lz7RQIeNesCqmnKxHY07qwYRdrMcJ5h61a6mRcYhF0a5AiUY8heK4hywwVqGoCQJFDSGxE87ELY8lSsT+K1F+wYabGOJVUM1unRyrFYXlfKzU/Rk8OLyQCyWMzEUsBOEwJ+hTsVMtRMPMNz6H/lrkWJ38hw61d12drEcj1zSUsJNxOSGYYolVsXOugQLFKzFlyYKiJggUNSSe+PHXUTQmbieuQzK+4ONZ6dUp90u4mAtZ5HUJTo10junIUF/iMrULxVQ7fGJrHCJa7V4DJwPPRbiEEp7m+KKNdwp1XnZiVexYiwLvX7viKdXYkyhRIwf4+OOP1cqVK5Xboagh8cIrpf29IuKcNMW7QUgloh1A4BL0vjt8WKmDB/Vrsk0pbFWnY73tyT/aezqShc/KIkHO5cuHH58papzMLLITq2L1PhJLpNVYLTdWRvaNqOnYsaMaOXKk/vvgwYOqRo0aKk+ePCp37txq0qRJys1Q1JB44JXS/l4iGZYap4VUoOizGgTq1JLjF/0ffyh1/vlK9eql12d3EVrdp7i3nO7rJfu16ja6+WZr28n+7MQ7Wf0/akXIW83ACmVR82ugr2tFTZkyZdTy5cv132PHjlXVq1dXBw4cUK+88oqqW7eucjMUNcRp4umySGWSYYq3KqREoFjJ4rKTrhuPJVPwTZig1CmnGCuLF1ffT/rL0vsfeMA4V+kVJPsyu3FbsUaGm/yDvWbFPSVCzE7fomR2UI9UK0fEVThSyZWddFGTP39+tXHjRv13165d1cCBA/XfGzZsUIUkJN7FUNQQp2FwX/xItCneTtxHONdiLEXmIi3p6da3nfDOQaV69z654sILldq0ybIwEFFjTqpiobFqjYzWFRspTT6WDtPJINh1EJdTpGBukmBRI+6mCRMmqP3796tSpUqpb775Rq8X600JkdIuhqKGOE0yYj9SiVhM8dH82rVafyZcNlQk10MsFhvT4BJpOQOr1L6q554crCiUY8f0GKNxhVktCherKzbS5+21YFpaXDwgal5++WUdP1OsWDF17rnnqoyMDL3+pZdeUs2bN1duhqKGOI2Xfjl6lWjFSbSB21YLDgabQO24sB56KDphM2RIeJGRG8fUhlxVTpoGvvoqy/lZtdTYXcwaRnauVzSfdyThGS77i3iXuGY/LV68WE2ZMkXt27cvc91nn32m5s2bp9wMRQ1xGq/9ckwFnAjcls8rmgqvVi13Imj69o1OPMgxZOIOdb/JMu+Bz5Vq0UKpLVviWjMm+znZvV6xfMahBJTfsw5TlT0W5+/0aJpg1q9fH23atMGWLVtw/PhxvU6eN23a1Ol+m4S4GrMLcmCHW191vPUY0hFZukDL9JYdc13//sZ24ZDPq0wZ+123rXZKfvxxYNQoRIUco2NHYPJko3uzcCZWohVm6ufSMbrpsCuBb75BRplymD3b6Ewtj3Le0s3afF8ycKJLuXSrfv754K+ZnbOlszZJPWyLmoMHD6JXr14oWLAgzjrrLGzcuFGvv+OOO/Dkk0/GY4yEuBr5gpWJpHz5rOvNCUZeJ4lh7lxg8+bQr4uw2bTJ2C4SVgVK4HamYMgucJ2iYkXjGILcV+vXA78NfAc/52uA6YWvx7pZ6zPvtykfp6FyZaBFC+DGG41HeT51qiHEZYxOjFP2IeNq3tza9lavazhEnN11V/DX7IhX4j9si5pBgwbhp59+wuzZs5E/f/7M9a1atcKECROcHh8hnsCcYGbNAsaNMx7XraOgcasVwMp2kQSKOZmbIiOS5c4JbrghwOq3fz9y9eyOWk/djNxHDiJPo/rIVbiAfkmsFGKtyC7wTCuGEEyI2yXQGimixu71coN4JSkuaj755BOMGjUKF154IdIC7l6x2qxdu9bp8RHiGWSykS/2zp2NR7qcEk801hWnXYuhLHdOMH78f9aHFSuABg2A994D0tMNf9aXX2qfmVUXXPv2WYX4118bYw4nxrKfa6A1MpGuWCfFq5uQzy67u5DYI7fN7bF9+3aULl06x/oDBw5kETmE+An5cpFfffIlKROi/NqkaHEfpnVFLBLBJnX5ipLXrVoLTIEiIiHQMiD7kAk60BKX/R6R33jz5xvPV640dEesiPVhzf1vouaoO4DDh4Fy5YwZ8OKLo7JiiPgOdBu99JJhyZHrFHj9zK92OVSpUqH/H9i5Xm4Rr25BrGvBrpsIRVp8bWA3Avmiiy7S6dtC4cKF1Z9//qn/7tu3r2rdurVyM8x+ItGQin2dvFxnIx5F+6ykGYe7R5zMOFp96f8Zf1x+uVLbtuUYq9UMrP7941emP973jZV6QF7KOmSrlSSmdM+dO1eLmd69e+vqwv369VOXXnqpria8ZMkS5WYoaohdUvnLxstiLpH9c6zcI1ZS/6WkTOhJ+kTm33O+OqTUG28o9V+NsOxCwmpqdbCGil4Ss9JqINz5RWpF4BbYasUFdWrWrFmj/ve//6kGDRqoM888U3Xp0kX9/PPPyu1Q1BA7pPKXjR/EXCImZjv3SCQLkpTPzyl8Tqjb8bKajstVOo7r14Odh9WCgX4pCuknSw0LeLpA1HgVihpih1T9skllMRfveySSBSlQ+BTBv2oirsvcsAve100dswvKWHpNebV9h5/+b7LVirPzt+1AYbMuTShOP/10u7skxJX4NcMiEnYDTVM5KNzuPSIBn5J1FLj/Jk2MgGIJwpXnEycCr/1vCUbv6YRq+BPHkBsD8RTGogvSdhmBvGbGUbhMJ78F0vr1/6Yfg56TiW1RU7ly5bBZThlxykEbPnw4pkyZglWrVqFAgQJo0qQJnnrqKdSsWTMuxyMkVb9s/DRhxDsDxepnH5gwaqb+m8erVi3weAqPFH0J0/cMQF4cw3pUQidMwA+4wHhVGZlIZkp2JAEaCrtZYG7DT/83nc7YS3Vs16lZtmwZli5dmrksWrQIr732Gs444wx89NFH8RklgDlz5qBPnz5YuHAhZs6ciWPHjuGyyy7TqeSExINoiq/5AbdMGImu2RGpYF2wsvtWKwj36JHz/cGONwIDMHRPfy1opqADzsOyTEETzFIWjbD0Q/sOK9ddzm3HDrgetlpxGOUQ0tCyWbNmKlFs27ZN+9fmzJlj+T2MqSFuSA92O25o0pnozKtY4ogidY0Odr+EOt5ZWKF2oZjqg5FZMp5CxVhEkyoeryywRGMllshL/0cTmbHnRRIeKPzHH3+oggULOrU7S8eTE1yxYkXIbQ4fPqwvgLls2rSJoobYJhW/bJIp5pKReRVr4KmMqXz5yBOsKYzM46UhQ9XD4izbSYCw1bHIviR4ONwx5d79+mt3p2dHi3Qrz5UrOjHqRryQSu87URMoEmT5999/1W+//aY6deqk6tSpoxJBRkaGatOmjWratGnY7QYPHqwvQvaFoobYJRW/bJIh5pKVeeVEBooIByv7kO2klkxx7FCfoo06itzqAiywZW0xU7vls4i0baB1yA33sJPj8FMWFEmSqElLS1Pp6elZFll3+umnq/nz56tEIIX/KlWqpC0v4aClhqQaTk9ciZ4IkzVJOXFcq8KoeHGlmmKu2ghDvR1CPnUjPrAlasQ6Y9a1ibSdKX7cUEjR6XEwHTp12BOvlO5Z0v0sgPT0dJQqVQrVq1dH7ty2d2ebvn374rPPPsN3332HChIpFoZ8+fLphZBUIB69YwIzdfyceeVEBoqVwOk0nMCtu57CY3gYuZGB1TgD12MifkadHMcrXtz4e+fOnPvZtQvo2DHy8eS9w4YBQ4bkPC8zANpMD483ZmC0k+NwS1A7cRHKI5w4cUL16dNHlStXTv3+++9R7YOBwsSv+KECcLLdCZECfocODW+pihRgXQpb1RdonbnifXRRhbE35Gcm8SLRVAkOZhlKdszJkSPh20BEOw4/VRYmzszfafJPJOEzbdo0yyKpXbt2iAf/93//h3HjxmHq1KlZatMULVpU162xwt69e/X2e/bsQZEiReIyTkISjaQ6V64cul6JaWVYt879aaHmuUSymMTrXIJZuwKJZPkyrRFC9vHfhtfwGm7HQRTAHRiJt9FT226yI2UCJIVXLDUtWiAhiAE+XhY5uSa33WYtvTqacdx3HzBiROjXBwwAnn4arizeSKxjef6OII4M5ZOWZmmR+Jp4ESzgV5YxY8ZY3gctNcSP+C1YMtlp9PKrXqwyoSwKkcYQLG7EyFA6oZ7B3TptO9RnJAHEplXBarxIOOtHuMyoRMSc2G3hYHccsVpqnI4Zc0vskh9h76cgUNQQP+LHYMlkptE7kYElr30/+W+1pnkv9d3ney1nRgUKz2hq0GQXX6HEWSIErxXBEes4YhH0TgsQv7iAvT5/264oTAhxF34MlhT3zvr1hjti3DjjUVxOwdw+TlcettP7KhS5Zn2NJv9XF9Vmv4WLJvfXLhW71amtVisOhrxPekidOBF523hVxbbTwiHa6tzRBpZHUz06HOF6cJnrpLVFvKtikyh6PwnSmkDaFkhzy6NHj2Z57c4773RqbIQQBzJ3hFKljMaJXsJK5lU8Mr6mTo1hQj1+HBg61Eg5kg/j7LN1UIdZCl8mTJnAAz+nUKXww70nHPJZS4yJTKJyT0Ti2WedifnIHkti5diBRNMKIBpBH0mABPbWsjqeVG8C6yrsmoCWLl2qypYtq4oUKaJy5cqlSpUqpeNpChUqpKpUqaLcDN1PxK9YKdXvN99+PMz94jIJl6UT1qWxebNSF198coNbblHq4MGY3WrB3uPk4oTrKdgYrV5H2S7a+zKalh7xiEHzows4ZWJqpL/TLbfcoqv6Fi5cWK1du1Zt3LhRXXzxxWqyy78xKWqIn4k0+XnFt28leDNelYetTngyEWfZ94IFSpUsabxYuHDY2SvU+YU7b/O1vn2dFzWxTrThxKWV6yjp3okMLI+HAPFbsH5KiZqiRYuqVatWZf69cuVK/ffChQtVzZo1lZuhqCF+RyYIc251crKPN+ak3b9/zvEHszDFaxKxOuHJOLPwzz9KlS2rVN26Sq1ebfv8rQatxhI8HI+JNppg4HCCI1rsWMDice+4oQms39kTr0DhPHny6CrCQunSpXVcjSD545vEaUgISRrz54evB2IlyDXRSFyM1KaRmiwSV5F9/MGCN+NVedhqjIbEW2D37pMrypQBvvkGWLAAOOMMW8e0E7QaS/CwU8G5gYHZI0daCwYuWTLrczkHJysZ2wksj3QNo7kuZvyT+f7s+4s2ZogkIFD4vPPOw+LFi1GjRg00a9YMjzzyCHbs2IH3338fZ0tQHCEkaSSrzYDTpfMDCRa8Ga+Mr+3bI2+jJ7w9nwHVuwOjRgGdOxsv1K5t72BRBK1GCjgOdx2DYXeijVScMNxxypePb0E6qy09ognatoIIKBFqwQLXZX+JaEVBbAQKH//PbrZ48WL17bff6r+3bt2qWrdurU455RR1/vnnq+XLlys3Q/cT8Tte8u3HUsckHuZ+K+PJgyNqddu7T65o0UJ6uCT88wrlbjGbXEaKZ4kmaNxuIb1o7rdENlCNVy0kt3RD9xuOx9SUKVNGDRw4UK2Owl/sFihqiN/xkm8/mviQwOBNpysPRxpPJaxTC3DByRX9+il1+HBME1ssQauhjhFrDyunY2es3m/JqMZLAZLCoubRRx9V1apV060QLrzwQt2e4MCBA8pLUNSQVCDZbQasEk0bAKsWi2jOMdx42uNjtQvF9JPdacXU8ckfOzI5R2OpsTIRO22FiEaA2rnfWI2XJC37adasWapbt266Lo3Uqvnf//6nM5+8AEUNSRWS2WYgHhNluF/8Tv3aDjWeM/Fr5hOx1IjFJpQ7xe7kbNeyZkcwOWmFiEaAWr3f4pWeT/xF3Hs/7du3T73xxhuqadOmuvhe7dq11bPPPqvcDEUNSSXcblqPNKFnn9gS0ciyePHgx38KA9QI3KNjasK5g6KZnK1a1pJpzbAqQJ9/3v795qU4MJIiDS0/++wzVbx48bh26XYCihpCvFcJOZEWJrMB5LX4SJ2O9QHjOBFxgnW6uWLgeSfbmhHPWC2p+WPlurEab2qzJ94NLQ8ePIh33nlHp3W3a9cOJUqUwDDpd0IIITbTYCXdN5BixYArrgCefx5YsyZx6bAP3nMYb+X7P0xCR4zHDciNY/+9khaxhkks6fSR6qzY6S3kdIPPeNZhkRRxeZ/fGrKSJGJXLX3//feqV69eOp6mYMGCOr5mzpw5ygvQUkOIO7FbUTguSGZnnTqZBx6GQSoXjll288TTjWKn0nE8M4icjNWyk1HlRDsF4m0cdz899dRTqlatWtrF1LBhQzV69Gi1d+9e5SUoaghxL3ZiRhyPFxo71ujZ9N8MOvehL21P3vGqnSPn99BD1ib/UMd1MuYm3oHZqdKQlSRZ1JQsWVL1799frVixQnkVihpC3ImdmBFH65lIF+1evU7uqFkzpbZsiXrydjKd3m537ly5khdzk4iMKqZ3pzZ7LM7fafKPFTfVsWPHdN8nL7N3717do2rPnj0oUqRIsodDPIbEJkjMQjxLvacqEvshvZ8iMXQoMGSIMc0Fi+uw3U/o8GGgUSPg55+Bhx82lty2u8dEbCUgcTh2SuVbaR8RDV9/DbRsCU995tk/Z2k7IPFG/L+XWuy1OH9bFjV+gKKGODlRyZerBE+6vadLssWYleNLUOuNN0beV/HiwK5dDkx48rVnKqHffzeibC3M9lavZSzXXN4rDT7t9leygly/N95wxz1rnqc07rQ7C0kgtZU+TyQF52+VQtD9RKLBy9VOk1F6PprjR1OxNqpA3P37lereXakhQ+J2LrHi5LUI5cYJNeZE1zayktIfbGF6d+qxJ5F1arwCRQ2xS7Lrg7hRjFmd+OwG/lotxBf1hCfxgLVqGRvlyaPUxo2uFLbRVO+1K2pCFQFMhgC2GzsUUbgSX0JREwSKGhKvX81ff61SQoxZnfiiOX4sXaDDTXjHj51Qq+59Qx3Lk19vcKJcOaVmz076tUyWpSbYdUq2NXLixJyp/Im41iRFi++JL8vqQoifsFpQ7frrjbgbt2CnWJtVPvoIuPbanPuVmAgJag08/2iOL3EeEgQcLcEK400buw/TityEms/cgtzHDuMLXI66ajmm7GyW0GtppyCejF9ig7IXuYvXvS1jkXgxOY/smOv693emiF8w5L7p1AnYsSP8drEU+SOpgyVRU6xYMZx66qmWFkL8hNUqphK8mn1ijxYnKsLGUt02GJJV1Llz8NeCTXzRHr9GDURFsAlvykcZOP2mi9Dh0DgcRy4MxJNog8+x4p9SIT+rYNc+1mspx5GAWMn0kWBoeZTnoe6VcNV743Fvx0MAWyWcoMqOCD3b2W0k5bCUuzhLQs3/Y/369bj//vvRo0cPNG7cWK9bsGAB3n33XQwfPjx+IyUkCZi/mq1maMjE3r599L8kncqysirGrGwnY+rYMfw2gROfZKVYPX7p0oZ4MLOE5LkVSpbM+sterlFgyrSeLO/OhcvRB4/gUdyA8ZiPpv8N1hAL8lm1bQvMn28c/48/gNdfNz7rwP3ecou1MQU751Cp2aZ1K9QkbbaPyH4vOIGZJWZatJwWwHaIJKhMpF3GHXfQQkMsYNevdckll6hxQSLxxo4dq5pJ4SoXw5gaEg12Yz2iDWJ0Mq7Bqeq2dkrZy2J+NVg5fokSSpUvn3W9PJf1kcYtJfODBiv/+69Sv/4aEJdyQp0C+X8fuvx+pBgOc6x2r6UTsThOVBSOdC8ls0u21aBoZjuRPfFqaClWmfr16+dYL+t++OEHu7sjxPWYv5qlxke8ftE6HdfgVANCq7+ks1srIh1fzmnnzqxWEeGvv4z18nq4cefNa1iExCUmj/o8liwBzj8fuPJK7Phjt/ku7EPomhbbt4c/n8DPI9KYsl9LJ9w6sk85v9q1YQsZV4kShkUmkgsnUgxPuCaeseKkRZEQwbaoqVixIt6Q6k3ZePPNN/VrhPgRmQQmTozfF3AsE2CoGJxQHbDtxCbYEWjZJ75Qx5fnMuEGwxQO8rrlccubXnoJaNIE+PNPver03H/BKUwBJtWM7VxLJ906du4pU5yIKy1c5+94d+C2QjIFFfEpdk1An3/+ucqfP786++yzdbduWc455xy9Tl5zM3Q/kViIR8PCWM3wVlKsYymoZie92GpBN0l/t7I/2S7iuHftUurqq0++Sf7etcvRujeB197OtXTSrWPnfKLtmu1kB267x3WqXxbxL3GtU7Nx40Y1aNAg1aFDB7088MADep3boaghbv0CjmYCTERtESuTqTRSlDojCY+jWLhQqUqVThbTe/FFpU6ciLlabahl6NDkiuBw95489u8fexXgRFcUTragIt6BxfeCQFFD3PoFbHcCTGRBuEji4KOP7O3PMQvGtdcaG1atqtTixSHHnv06RQoODrXIfqIpVuikCPbz5J8sQUW8QVxFzXfffae6dOmiGjdurDZv3qzXvffee2ru3LkqnsyZM0e1bdtWnXbaafrkPv74Y1vvp6ghbv4CtjMBJjpjxcnJ1DELxs6dSvXpY2Q82fisJHMqWtdUNNfTaSHCyZ+kInvilf00efJktG7dGgUKFMDSpUtx5MgRvV46Zz7xxBOIJwcOHECdOnXw8ssvx/U4hETCzErJkn0TI3YCexNdW0SObSXo1ApRB6Z+/z1w772GLhAkHW3UKKBoUVuflWRORVvcLprr6eS1i9e9R4hvsKuW6tatq9599139d+HChdXatWv130uXLlVlypRRiYKWGuJGnPgVbWUfdoJtncRJK4FlC0ZGhlLDhxvBO7LRBx/Eehohj58oyxchRMVl/rZUUTiQ1atX4+KLL86xvmjRovj333/hJsSKZFqSBPamIvHEqWrA5i/xUEjK9vLl8Oz5mch7pPqypKmbFYUldTeL5UEKyXTrBnz5pX66teWN+O5IO5SaHWTbGI4v9XKkDlCo/kPZq/AmA/ncw14rQoh9S02VKlXUzJkzc1hqxHpz5plnKjdZagYPHqy3y77QUkOcJlFdju1aF5yqxJqULs7SSVs6agPqeN786p5T39QVggMDd+W4TlmPEpFaHO1YrXZHj/c4CPFdoPATTzyhateurRYuXKhOOeUUHRz8wQcfqFKlSqmXXnpJuUnUHD58WF8Ac9m0aRNFDXGcRGUi2W3X4JS7JJGZVplIenZ6uj7AngpnqrOxIuhx5VFaGDg12cczuyhaYeK0oHRaIBHiaVFz4sQJ9fjjj6tChQqptLQ0vUjhvYekOUkCSZWYGv6icj+JyESy24PJSaGRlN5AEgyUlqYyunVXNcrttyXkYrWsxDOzLdR4wxUudFJQJsXiRogX6tQcOXJE/frrr2rRokVq3759KtGkgqjhLypvkIimfHYq+zo9Qdk9v6hFwY4dWZ8vX27rvLMvjluP4ihIxdoUbKzxqEqcCCFMiGdSunv27Il9+/Yhb968qF27Nho2bIjChQvrdGt5LZ7s378fy5cv14uwbt06/ffGjRvhNyQo87rrcvYDkoBGWS+vE3fwxx/xb8pnJ5XYTm8np5sOyn1ZuTLQogVw443GozwPe79KBOzgwUC1alkvZp06MaWkR2oWmSisNAWV3lLDhuVc72TqvhMNNglxPXbVUnp6utq6dWuO9du3b1e5JOUyjsyaNSto4G/37t19ZanhLyrvINaQRLiCrP5if/555+8Lq8XypFVCKNeGPPbrZ4xPMrIzLThbtijVrFnmxmtvGZ7FwhOLpcbB7O+EWLqKF8/52TlpqUmERZEQz6R0Szr0f+4qbanJnz9/5msZGRmYPn06SpcujXjSvHlzfXy/Y+cXVbjUXxJfxMAgKc5WMIvJRZuWa3YzFktdsP8CZsrxHXc4n+ZrFssTC6EcJ/D4ZvG6554D7ror+NjMdWbBO5MuJb/Cm0e7Iv/e7TiWvzDuLjgao964EXjDeF3O5/nnw593JCQjPNlYtXTt2pXz/7TVz91Kqrkdi5sdmGpOXIVVlSQBwWKlCbWIlUYCiN2MVyw1/EXljeBqq7+izUaIscZIJbubcbjMIDsWlVw4pp7A/ZkrtpSqo87A6qAWHlkGDIi+MaUbLDVy/4kVJtr/00597vHoMs+4P+LZQOHZs2dr94+ImylTpujn5jJ//ny1RczILscroiYp2SY+IZFfsnbEp1NZJ8luaBhKMFq9FrL0wcjMJy/jdlUw/VDIbQNdW3ar/7rp/0inTrGN16nP3UlhzEwq4ovsp/Xr1+u0bi/iFVETj19UqUCiv2Stik/JTnYyRsqNaf52LDW5cVR9ictUR0ywJU7M8+7bN/oYlWQgY8heSyeaLuBOFhmMVSAx7o/4RtS8/fbbaqL8bMqGrHvnnXeUm/GKqHGDq8FrJONL1qr4tNqnyS1WBaevhYiYvnhJP55cf7IysF23jF23X7Kx+vkPGZK4McUqkGhNJr5J6R4+fDhKliyZY70ECce7S3cqYadjM0lOuqrVbtPbtlnb3+TJwOzZRuBlNMj75P0ffhjbfpy8FqdjA+biIozEnXgcDwW8w1577MDgVTN4NlyH7RIlgAcfhCuQz8IKx48jYcTa6TvRXeIJsYptUSM1YapUqZJjfaVKlXxZLyaZiHBZvx6YNQsYN854XLeOgsZNX7JWxKfVbJJRoyzWdQlCVPVhEN9r0R6fYDnqohEWYTeKYQEaB32fTKihBIqsr1gxa3ZPODFprnv9dWbgxJN4ZVIREjN2TUAVK1ZUU6dOzbH+k08+UeXLl1duxkvuJ+Itc3g4c34kN5UTwcNOxBI5FbNx/MBhteGafpkDWYALVCWsC3m+obKbzHXiRgo2pmQHTTvtfpLtvALj/ohvYmruu+8+ValSJfXtt9+q48eP6+Wbb77R6+655x7lZihq/Ivbv2RDxUjFGgPkVCyRY1ljf/6pVL16mTsZgXtUHhwJOjYJnjX3H+z48nqkZpVuDJqOJlA4VJsEN8O4P+ILUSM9n66//nqd2p0nTx69SI2am2++Wb/mZihq/I2dL9lkTIbBJu5YLUvRWKiyn3u4SsC2J6dVq5QqVMhIPfr006DnLC+J9SX7NQ8cl7we7nyCvd/Llaf793evKAuHV6xlxPvEvaHl6tWrdcbTp59+qtO8vQBFjf+x8iWbzIJhdtOSIxVYtFuoMdi5S3eTmCw9GRlZn3/xhVIbN0YtIK12JPdakTcZq3joA88hPd3b5+QVaxnxPlbn7zT5BymCtHooWrQo9uzZgyJFiiR7OCROhCvbbjYKzX7XmwGnicosk4wYCeaNhASHh2uFYWc/UoY/2LlbIeQ4pAGlpNA8+yzQrBmcwOo5mZ+bl7IBzXtz6lQjMy47ib4PCfHb/G1J1Nx999147LHHUKhQIf13OJ6TJjAuhaImtZEJRTKCQqV+m310JMMs3pkz5lgi9fSJNBar+1mzxmiCHalbdCgk+060SxYkd/zWW4H9+3VHbSxbFj7P2iKyW8ngskIiPzM/3oeEeAWr87elhpbLli3DsWPHMv8ORZoDX2iEpEKjUCtNIs0mmE7sZ/786AVNjtTcQ4eMTp5v/Nd5Uiw0onoc+v9vJw04kZ+ZH+9DQvyGJVEzS2zPQf4mxEu4rWCYWddF9EHgJCe/0kWIWHU/WNmPWD+iIUcX6FWrgI4dgV9+MV58+GFjyW3pq8QSkTpTe73Im9vuQ0L8hHPfRIS4HDcWDBPB0b596Bggp/YTzTnlsBhJ/Ey9esDBg0CZMsDYsUDLlnCaQOuTVbxU5M2N9yEhfsFSTM01NiLWpiSyhKlNGFOT2kSKPzHL62/d6r9YBivnLucc2FpBKvlmsRjJGyWwZscO4IMPgLJl4zpm+Sq5805jzKHwYvyJU/FUhKQSey3O35baJMiOzEV29s0332DJkiWZr//44496nbxOiFsxLQDhZPzOnUZmit+I1KdKlvHjg7TkqPkrsHv3yQ3ffhv46qu4CxpBxNSGDcDQocFftxN75Cas9gzz0jkR4hZsp3QPHDgQu3btwmuvvYZc//2vy8jIwP/93/9pwTNixAi4FVpqiPxKFs+JiJdg+P1Xslg/ssfe5LDICPK1IAKmb1/giiuMbptJTASwPG4P4cdzIsQTKd2BlCpVCvPmzUPNmjWzrF+9ejWaNGmCnaFmCxdAUeONWjJeqA/j62u/bx9w++1GzIxw+eVGJHKhQkjFeyae43LrORHi65TuQI4fP45Vq1blEDWy7sSJE9GNlqQUwX6hinVETPLx/oWaSpknoSZMWUIKtp9+Aq6/Hvj9d2PDYcOAAQOAdEue6rgSdtwevZfdeE6EeBnboubmm29Gr169sHbtWjRs2FCvW7RoEZ588kn9GiHhCFXRV4ImZX28K6mmSuaJ7clWPpDRo4H+/YEjR4yNJcimadPMTWhVcNe9TAgJgt3+CxkZGeqpp55S5cqV000tZZG/ZZ107HYz7P2UXJzqKO3nbt5ONva01aBS/k/IicuGbdsqtWNHjn0mq1+WG3HDvUxIKrEnEb2fxMcleCU+hTE1ycUt8SzmL2whWAVeL//CjqkE/4IFRulhaYUSEBQcqV/WhAkSa+ceC04iLEpW7+Wvv45LKR9CUo69TqZ0B4ur+frrr/Hhhx9mtkb466+/sF96wBDi8ngWswJv+fJZ18tk72VBY6sE/3cKGDUKePfdky82bgzcc08WQSMCQdxYwX76mHYJKV0jE7z0a5JHEVXJKlclx5Xjx3s8Vu9RCU9ycekuQnyH7ZiaDRs24PLLL8fGjRtx5MgRXHrppTjllFPw1FNP6eeS6k2I2+NZnKrk6zasTLZF8S+qDewFLJ4CFCgAXHwxUKVKVCJJCCzYl8yYkkTGuFi9R83O6F4Xy4R4BduWmn79+qF+/frYvXs3CsgX4n906NBBF+AjJFJPn1DlTmS91OnI7DMUZ8zME7E0yGOyBI2IAnFnSH8mecwuEpycbBvgByzDeagogiZPHuDJJw1ThoNWM1NUSMxxLOdih0gWJafHE+lezk4irwUhqYxtUTN37lw89NBDyJs3b5b1lStXxpZw9cxJysNKqvF3l4SebBXuwnP4Hk1RBeuhqlY14mekD0GYmTlaq1lgp2m3db52+l5227UgJJWxLWqkFo1UEM7O5s2btRuKEL/HszhlWTHdJdknY9NdEo2wCSYc03ACU3ANnsM9yIPj2Ny4I9KWLgXq13fcIpGsej/JiNcy7+XixRN/bEKIQ6Lmsssuwwvyc/o/JFBYAoQHDx6MK6+8EqmGk66DVEEmg/Xrg/QZuiZ1LCvxdJdkF44K6ViBc3AY+bDslldQ4fsJ0tAtZuuam+r9JCteS671xInWtpUm54SQ+GI7pXvTpk06UFje9scff+j4GnksWbIkvvvuO5QuXRqpktKdzMq4JPFESm22Y2mKe3q7WFR37MbclSWMQOjSGbiozO/IdfaZjt3r2bt6J7OHVjI7X0dKozeR44uYTyX3KiGu7/1kpnRPmDABP/30k7bSnH/++ejSpUuWwGG/ixonJzji8/ovQRDLnlh6IiGWLAlktsX27UD37sDWrUbcTL58iEf9lx07jJRlt9T7SWb9oUcfBQYPTu2eYoS4Yv62U9Hv6NGjqmrVqmrlypUqWYwaNUpVqlRJ5cuXTzVs2FAtWrQo4RWFWU009Zg1K/TnHbjIdsnYXyZz5ihVrpzx5vz5lZo3T8WTYJWG5d5PVqXhZI1n3Dhrn6dsRwixj9X521ZMTZ48eXD48GEkC7EO3X333Tp+Z+nSpahTpw5at26Nbdu2JXQcic60IMmPcXI6ENXx9HY50ccfN3xaf/0F1KoF/PBDlt5NqRAflazxuKkGEyEpjV21NGzYMNW9e3d17NgxlWjEMtOnT58sfaik79Tw4cMTaqnhrzJ3Es/+RPGwrJg9mrL3aQrboykY//yjVKtWJ3fQvbtS+/dHe6okClKhpxghycTq/G27ovDixYt1kb0ZM2bgnHPOQaFChbK8PiVONcGPHj2KH3/8EYMGDcpcl56ejlatWmGB9KwJglQ4liV7r6pY4a8y9xHvarKmZSVSIKqdwoFmllKwYHNJMLQ83ltvNZoMFSwIvPKKEU9DEtpDyswSk3tN7oVgMT2pVoOJEE+kdBcrVgzXXnutdvuUK1dOB+4ELvFix44duj5OmTJlsqyX5//880/Q9wwfPjzL2CqKPd+HlXFTnURUk41X4UBH3CVy4AsvlF8cFDRJTN33Qw0mQrxOTF26E4k0zCxfvjzmz5+PxtJ47z/uu+8+zJkzB4sWLbJkqRFh42T2k1syP1KZRHb/DpbaLALWlmUlViRm5ssvgZ49E3TA1CLWzMZEdAknJNXYazH7KbedSsIjRozAtGnTtCuoZcuWOmA3UWncUgcnV65c2CppqgHI87JlywZ9T758+fQSDxxzHRBXBPFanYiS3ghzxgzgppuMtO1y5YDLL0/IYVNloo5k9RNhI1Y/uQfCuaKYtk2Iy91Pw4YNwwMPPIDChQtri8mLL76IPn36IFFIr6l69eplaZopQkueB1puEonbMj9SlVhjnOy6GpLSCPP4ceCBB4DWrQ1BU6cOIP2bPNifys0ws5EQj2M18rh69erqtddey3w+c+ZMlTdvXp2BlCjGjx+v69O88847ulbOrbfeqooVK6b+keyPBGY/Ef9knpgZSMHeYysDKZ5s2qTUhReeHNzttyt16FBCDu2J6+MgzGwkJEXq1GzcuDFLbyfJOpK+TxLrkig6deqEZ555Bo888gjq1q2L5cuX48svv8wRPExSi2iDeBMRYBxzTZ0vvgDq1gXmzQPEjzxhgpHhlD9/dPuzOb5kXp9kwMxGQjyOVZWUnp6utm3blmVd4cKF1Z9//qm8Ai01/sZuNdm4VfV1sqbOe+8ZL9arp9SaNbHvzwbJvD7JgvVmCEmROjWSJNWjR48sgbdSXbh3795ZatXEq04NIZEwg3jFSiGLIDEvoYI2na4S7FhNnYkncM11/xlRu3Y1TEzXXhuyh1O8avQk6/okE9abIcTbWHY/de/eXXfgDqz7ctNNN+WoVUNIMpk6FejRw+gYIEurVqGDWpPhaojk0mmnpqL2jXWQ8c/2ky9IdG4IQRNPF1GqumJYb4YQ7+KZOjVu69JNvF9fxOy8HalKsNXO27HU1MmDo3ga96E/jOCgTdffg4oTnol6f07U6EnG9XETqZLGToif5m/bFYUJcSPRWCziVSXYrqumCv7E92iaKWiewT2Y3/aJqPcXy3aBJOP6uImkpO4TQmKCooakdH2RRLsasrtqrsFkLMN5aIAl2IniuArTMADPoEzFvFHtL9btskNXDCHES9huaEmIG4nFYpHIKsGBjTG7qnfxLnro9fPQFJ3xIbakVURFG40x49Fo03VVlAkhxCIUNcQXxGqxSFRp+8Dsmk/QAX/gcUzCdXgEjyIjLY9tl06isnVY+p8Q4gXofiK+wDOd07/7Dtd0UNp1U6RCEdTFcjyA4TiOPFG7dOgiIoQQA2Y/Ed/g6s7phw4Zkcqvvw6MHAn07et4dg2zdQghfsXxLt2EuB3Xdk5ftQq4/npgxQpDYe3eHReXDl1EhJBUh6KG+ArXBbW+/z5w++3AgQOA9Cj74AOjIiAhhBDHoaghvsMVFgsRMX37Au+8Yzy/5BJg7FigbNkkD4wQQvwLA4UJiQe//GJYadLTgUcfBWbMoKAhhJA4Q0sNIfHggguMgOAzz3SB2YgQQlIDWmoIcYL9+4FbbgFWrjy5TmJpKGgIISRh0FJDSKz8/DPQsSPw++/A4sXA0qWG24kQQkhC4TcvIdEixXBGjwYaNjQEjVS/GzWKgoYQQpIELTWERMPevcCttwITJhjP27QxMp1Klkz2yAghJGWhqCHELtLuW1K016wBcucGnnwSuOsuWmgIISTJUNQQYhep6CfLsWPA+PFAo0bJHhEhhBCKGkIs8u+/QIECQL58hnVm4kTj71NPTfbICCGE/Aft5YRE4ocfgPPOA+677+Q6KaRHQUMIIa6CooZ4EulIPXs28OGHxqM8j0t20/PPAxdeCKxfD3z2mREgTAghxJVQ1BDPMWUKULky0KIFcOONxqM8l/WOsWsXcPXVwN13G7Ez111n1J8J0/KeEEJIcqGoIZ5ChIvoi82bs67fssVY74iwWbAAqFsXmDbNiJt55RUjhqZoUQd2TgghJF6kKSU29tRg7969KFq0KPbs2YMi/MXtOcTFJBaZ7ILGJC0NqFABWLfO6NQddXdtOciOHUCNGoaYEYFDCCHE9fM3LTXEM8ydG1rQCCLPpYSMbBc1hQoBr70GdO4M/PgjBQ0hhHgIpnQTz/D3385ul8l33xlxMy1bGs+vvdZYCCGEeApaaohnkHp3Tm6HEyeAYcOMSGOxzPz1VyzDI4QQkmRoqSGe4aKLjJgZCQoOFglmxtTIdhHZuhXo2hWYOdN4fsUVzGwihBCPQ0sN8QwS/PviiycFTCDm8xdesBAk/O23RqyMCJqCBYExY4B33wUKF47PwAkhhCQEz4iaYcOGoUmTJihYsCCKFSuW7OGQJHHNNcCkSUD58lnXi4VG1svrIRHzzpAhQKtWwD//AGedBSxeDPToEe9hE0IISQCecT8dPXoUHTt2ROPGjfHWW28lezgkiYhwad/eyHKSoGCJoRGXU0QLjZhzpDKwiJtevYCXXjIsNYQQQnyBZ0TN0KFD9eM777yT7KEQFyACpnlzGwVuTMXz8stAu3YRTDqEEEK8iGdETTQcOXJEL4HFe0gKcfw48MgjwM8/G9WB09ONOjQUNIQQ4ks8E1MTDcOHD9cVCM2lYsWKyR4SSRRSpU9StYcPBz7//GSWEyGEEN+SVFFz//33Iy0tLeyyatWqqPc/aNAgXVLZXDZJuVnif6ZPN7Kb5s0DTjkFGD8eaN062aMihBDiZ/fTPffcgx4RMk+qVq0a9f7z5cunF5IiSFXgBx8ERowwnp9/PjBhAlC9erJHRgghxO+iplSpUnohxBFEII8bZ/x9xx2GuKGoJYSQlMEzgcIbN27Erl279GNGRgaWL1+u11evXh2FWTSNCHfdBXz9NfDqqwwGJoSQFCRNqWAF592HuKnelaqv2Zg1axaaW8zttdq6nHiEo0eBRYuy9kU4eJC1ZwghxGdYnb89I2qcgKLGR6xbB3TqBPz0E7BwIXDeeckeESGEkCTP375O6SY+ZfJkQ8RIiwOpO7NjR7JHRAghxAVQ1BDvcPgw0LcvcN11wJ49QJMmgMRWXXppskdGCCHEBVDUEG+wZo0hYqTNgTBwIDB7NnD66ckeGSGEEJfgmewnkuJMmQIsWwaULAm89x5wxRXJHhEhhBCXQVFDvMG99wK7dxvup/Llkz0aQgghLoTuJ+JOpD3GDTcYKdqCNKOUPk4UNIQQQkJASw1xH++/D9x+O3DgAFCuHPDcc8keESGEEA9ASw1xD2KV6dkT6NbNEDTSZXvAgGSPihBCiEegqCHuYOVKoEEDYMwYw9U0dCgwcyZw2mnJHhkhhBCPQPcTST7Tpxu1Zw4dMkSMNKW02PqCEEIIMaGoIcnn3HONfk3Sw0niaUqXTvaICCGEeBCKGpIc/v77pGupQgVgwQKgWjXD9UQIIYREAWcQklikf+ro0UDVqsAnn5xcX6MGBQ0hhJCY4CxCEsfevUDnzkDv3kYfp0mTkj0iQgghPoKihiSGpUuB888HJkwAcucGRoww2h0QQgghDsGYGhJ/d5M0obznHuDoUaMB5fjxQOPGyR4ZIYQQn0FLDYkv8+cDd9xhCJp27YymlBQ0hBBC4gAtNSS+NG0K9O8PVKoE9OsHpKUle0SEEEJ8CkUNcd7d9MorQIcORt8m4fnnkz0qQgghKQDdT8Q5du0Crr4a6NsX6NIFyMhI9ogIIYSkELTUEGeQ4nmdOgGbNgF58xptD1h3hhBCSALhrENi48QJ4OmnjRYHImiqVwcWLgT69GH8DCGEkIRCSw2Jzd10003AF18Yz2+4wagWXKRIskdGCCEkBaGlhkRPvnzAunVA/vyGmJHu2hQ0hBBCkgQtNcS+u0mQeJlChYxWBxIQLJ22CSGEkCRCSw2xztatwOWXA889d3LdWWdR0BBCCHEFFDXEGt9+C9StC8ycCTz2GLB7d7JHRAghhGSBooaER1xLQ4YArVoB//wD1K5ttD449dRkj4wQQgjJAmNqSGj+/tsoojdrlvG8Z09g5EigYMFkj4wQQgjJAUUNCc6hQ0DDhsDmzUZA8KuvAl27JntUhBBCSEjofiLBKVAAuPde4JxzgCVLKGgIIYS4Hk+ImvXr16NXr16oUqUKChQogGrVqmHw4ME4evRosofmL8Qq8+uvJ5/feSfwww9ArVrJHBUhhBDiH/fTqlWrcOLECYwePRrVq1fHL7/8gltuuQUHDhzAM888k+zh+YPp04Fu3YDixYEffwROOcVocyCF9QghhBAP4AlRc/nll+vFpGrVqli9ejVeffVVippYOXYMePBBYMQI4/nppwP//muIGkIIIcRDeELUBGPPnj0oLlaFMBw5ckQvJnv37k3AyDzExo1GvybpsC307QuISJT2B4QQQojH8ERMTXbWrFmDkSNH4rbbbgu73fDhw1G0aNHMpWLFigkbo+uZNs0opieCpmhRo92BpGtT0BBCCPEoSRU1999/P9LS0sIuEk8TyJYtW7QrqmPHjjquJhyDBg3SFh1z2bRpU5zPyCMoBbz8slEVuEEDYNky4Nprkz0qQgghJCbSlJIZLjls374dO3fuDLuNxM/kzZtX//3XX3+hefPmaNSoEd555x2kS1NFG4j7SSw2InCKpHo3aenjNGoU8PDDwH/XlxBCCHEjVufvpIoaO4iFpkWLFqhXrx4++OAD5MqVy/Y+UlrUTJlitDdgYDUhhBCPYXX+zu0VQSMWmkqVKulsJ7HwmJQtWzapY3M9hw8DAwYYVhnhkkuAK69M9qgIIYQQx/GEqJk5c6YODpalQoUKWV7ziKEpOaxZA1x/vREzI9x3H3DppckeFSGEEJK62U89evTQ4iXYQkIwYQJw/vmGoClRAvj8c+Cpp4A8eZI9MkIIISR1RQ2xyf33G/Vn9u0DLroIWL6cLidCCCG+h6LGj4iQkcwwqRT87bdANpcdIYQQ4kc8EVNDLLBlC1C+vPF3mzbA6tVA9erJHhUhhBCSMGip8ToHDwK9egHnnANs2HByPQUNIYSQFIOixsusXGlUBH77baMJ5axZyR4RIYQQkjQoaryIZH2NGQPUr28IG6nV8803kiaW7JERQgghSYOixmvs3w907w707AkcOmTUnZHsphYtkj0yQgghJKlQ1HiNZ58F3n/fyG4aNgz48kugTJlkj4oQQghJOsx+8hoDBwKLFxuPkrpNCCGEEA0tNW5n717giSeAjAzjef78wGefUdAQQggh2aClxs1IiwPp3SQ9nI4dAwYPTvaICCGEENdCS41bs5tefhlo1MgQNBUrshElIYQQEgFaatyG1Ju55RZg0iTjebt2Rvp28eLJHhkhhBDiamipcZu7STpri6CRbtrPPQd88gkFDSGEEGIBWmrcRO7cwN9/A5UrAxMmAA0bJntEhBBCiGegqEk2x48bYkaQ/k3TphmtD4oVS/bICCGEEE9B91MyWbAAqFULWLjw5DoJCKagIYQQQmxDUZMMTpwARowALr4YWLsWeOihZI+IEEII8Tx0PyWaHTuM3k3TpxvPO3UCXn892aMihBBCPA8tNYlk7lygbl1D0OTLB7z2GvDhh0CRIskeGSGEEOJ5aKlJFNKvSTppS7uDM84AJk4E6tRJ9qgIIYQQ30BRkyjq1wfatDGsMq++ChQunOwREUIIIb6CoiaezJtnWGNOOQVISzOsM3nzGn8TQgghxFEYUxMPxMU0dCjQrBlw++1GLydB4mgoaAghhJC4QEuN00hF4JtuAr791ngulhkpsCdtDwghhBASN2ipcZKZM43sJhE0hQoB770HvP02BQ0hhBCSAChqnEAsMVJAr3VrYNs2o93BkiVA167JHhkhhBCSMlDUOMHu3cCbbxqxM7feCixaZLQ/IIQQQkjCYEyNE5QqBYwbZ1hpbrgh2aMhhBBCUhKKGqe45JJkj4AQQghJaeh+IoQQQogv8IyoadeuHU4//XTkz58fp512Grp27Yq//vor2cMihBBCiEvwjKhp0aIFJk6ciNWrV2Py5MlYu3YtrrvuumQPixBCCCEuIU0ps9ytt5g2bRquvvpqHDlyBHks1oHZu3cvihYtij179qAIO2MTQgghnsDq/O0ZS00gu3btwtixY9GkSRPLgoYQQggh/sZTombgwIEoVKgQSpQogY0bN2Lq1Klhtxcrjqi7wIUQQggh/iSpoub+++9HWlpa2GXVqlWZ2w8YMADLli3DjBkzkCtXLnTr1g3hvGfDhw/X5ipzqVixYoLOjBBCCCEpFVOzfft27Ny5M+w2VatWRV5pCpmNzZs3a5Eyf/58NG7cOKSlRhYTsdTIexhTQwghhPgvpiapxfdKlSqll2g4ceKEfgwULdnJly+fXgghhBDifzxRUXjRokVYvHgxLrzwQpx66qk6nfvhhx9GtWrVQlppCCGEEJJaeCJQuGDBgpgyZQpatmyJmjVrolevXjj33HMxZ84cWmIIIYQQ4h1LzTnnnINvv/022cMghBBCiIvxhKWGEEIIISQSFDWEEEII8QWecD85hZm9ziJ8hBBCiHcw5+1IVWhSStTs27dPP7IIHyGEEOLNeVzq1fiuoWW0tW3++usvnHLKKbpacSTMYn2bNm3ybbE+v5+j388vFc7R7+eXCufo9/NLhXPcm+TzE6kigqZcuXJITw8dOZNSlhq5EBUqVLD9PvkA/XiTptI5+v38UuEc/X5+qXCOfj+/VDjHIkk8v3AWGhMGChNCCCHEF1DUEEIIIcQXUNSEQaoVDx482NdVi/1+jn4/v1Q4R7+fXyqco9/PLxXOMZ9Hzi+lAoUJIYQQ4l9oqSGEEEKIL6CoIYQQQogvoKghhBBCiC+gqCGEEEKIL6CosUi7du1w+umnI3/+/DjttNPQtWtXXZ3YL6xfvx69evVClSpVUKBAAVSrVk1Huh89ehR+YdiwYWjSpAkKFiyIYsWKwQ+8/PLLqFy5sr4vL7jgAvzwww/wC9999x2uuuoqXUFUKoB/8skn8BPDhw9HgwYNdIXz0qVL4+qrr8bq1avhJ1599VWce+65mQXbGjdujC+++AJ+5cknn9T3av/+/eEXhgwZos8pcKlVqxbcCkWNRVq0aIGJEyfqL53Jkydj7dq1uO666+AXVq1apdtIjB49Gr/++iuef/55vPbaa3jggQfgF0SgdezYEbfffjv8wIQJE3D33Xdr8bl06VLUqVMHrVu3xrZt2+AHDhw4oM9JhJsfmTNnDvr06YOFCxdi5syZOHbsGC677DJ93n5BKrjLRP/jjz9iyZIluOSSS9C+fXv9HeM3Fi9erL8/RcT5jbPOOgt///135jJv3jy4FknpJvaZOnWqSktLU0ePHlV+5emnn1ZVqlRRfmPMmDGqaNGiyus0bNhQ9enTJ/N5RkaGKleunBo+fLjyG/JV9fHHHys/s23bNn2ec+bMUX7m1FNPVW+++abyE/v27VM1atRQM2fOVM2aNVP9+vVTfmHw4MGqTp06yivQUhMFu3btwtixY7UrI0+ePPAre/bsQfHixZM9DBLC6iS/flu1apWlt5k8X7BgQVLHRqL//yb49f9cRkYGxo8fry1R4obyE2Jxa9OmTZb/j37ijz/+0G7gqlWrokuXLti4cSPcCkWNDQYOHIhChQqhRIkS+kOdOnUq/MqaNWswcuRI3HbbbckeCgnCjh079CRRpkyZLOvl+T///JO0cZHoENevxGE0bdoUZ599NvzEihUrULhwYV2Jtnfv3vj4449Ru3Zt+AURauL+lRgpP3LBBRfgnXfewZdffqljpNatW4eLLrpId8x2Iyktau6///4cAVDZF4k1MRkwYACWLVuGGTNmIFeuXOjWrZtuh+6ncxS2bNmCyy+/XMef3HLLLfDb+RHixl/6v/zyi54g/UbNmjWxfPlyLFq0SMezde/eHStXroQf2LRpE/r166ct9xKs70euuOIKPRdIrJDE7E2fPh3//vuvjjF1IyndJmH79u3YuXNn2G3E3JY3b94c6zdv3oyKFSti/vz5rjal2j1Hyehq3rw5GjVqpNW5uDT89hnKecmvYvmP6WX3k2RxTZo0SWfNmMiEIeflNyuiiFP5hR94rn6hb9+++vOSbC/JPvQ74qKR7EoJqvU6kpHXoUMH/SPXRCyocr/Kd+eRI0eyvOYXGjRooD9HN1qnciOFKVWqlF6iNRcLctO6GTvnKBYayfKqV68exowZ43pBE+tn6GVEpMnn9M0332RO9HJPynOZJIn7kd+Td9xxhxZrs2fPTglBY96nbv/etErLli21ey2Qm2++Wac8S7iCHwXN/v37dfavlDVxIyktaqwiZlNJ17vwwgtx6qmn6g/04Ycf1r823GylsYMIGrHQVKpUCc8884y2gJiULVsWfkDioCTIWx7l15SYxIXq1atrn7/XkHRusczUr18fDRs2xAsvvKCDMOVL1S9fnhLbZSK+fPnMJJBWakb5weU0btw4baWRWjVmLFTRokV1rSg/MGjQIO2+kM9LYjDkfEXAffXVV/AD8rllj4Ey4y79Eht177336npRMjeIJV9KSIhY69y5M1xJstOvvMDPP/+sWrRooYoXL67y5cunKleurHr37q02b96s/JTmLLdDsMUvdO/ePej5zZo1S3mVkSNHqtNPP13lzZtXp3gvXLhQ+QX5XIJ9XvI5+oFQ/9/k/6Jf6Nmzp6pUqZK+P0uVKqVatmypZsyYofyM31K6O3XqpE477TT9GZYvX14/X7NmjXIrKR1TQwghhBD/4P6gCUIIIYQQC1DUEEIIIcQXUNQQQgghxBdQ1BBCCCHEF1DUEEIIIcQXUNQQQgghxBdQ1BBCCCHEF1DUEEI8h/TWkb478UQqbEuPMEKId6CoIYSEZMGCBbokeps2bWy/t3Llyrp1Q6KRku7SZT4Yc+fO1YLo559/Tvi4CCHxh6KGEBKSt956SzddlA7S0vfFC/Tq1QszZ87E5s2bc7wmjVqlV9a5556blLERQuILRQ0hJGRDyQkTJuD222/Xlpp33nknxzaffvopGjRogPz586NkyZLo0KFDputmw4YNuOuuu7RlRBZhyJAhqFu3bpZ9iDVHrDom0jz20ksv1fuT5o7NmjXD0qVLLY+7bdu2unN79vHK+Xz00Uda9OzcuVM35CtfvjwKFiyIc845Bx9++KFtl1exYsWyHGfTpk24/vrr9XppvNm+fXusX78+83Vp5ijNR6XpoWzTtGlTfZ0IIc5AUUMICcrEiRNRq1Yt1KxZEzfddBPefvtt6W6a+frnn3+uRcyVV16JZcuW4ZtvvtETtjBlyhRUqFABjz76KP7++2+9WEW6OUv38Xnz5mHhwoWoUaOGPoast0Lu3LnRrVs3LTYCxyuCRrqzi5g5fPgw6tWrp8/hl19+wa233oquXbvihx9+QLQcO3YMrVu31p2bxc31/fff6+7v4go7evQojh8/jquvvlqLNHF/iWtPjmsKPkJI7OR2YB+EEJ+6nkTMCDIx79mzB3PmzNFWGGHYsGG44YYbMHTo0Mz31KlTRz+KlUJicWSCL1u2rK3jXnLJJVmev/7669qqIccWK4wVevbsiREjRmQZr7ierr32Wm39keXee+/N3F5cbF999ZUWcqYws4tYtU6cOIE333wzU6jIMWXsYqERt5dcQzmHatWq6dfPPPPMqI5FCAkOLTWEkBysXr1aWy3EqmFaPzp16qSFjsny5cvRsmVLx4+9detW3HLLLdpCI+KjSJEi2nW0ceNGy/sQC1OTJk20dUlYs2aNtp6I60kQi81jjz2m3U4iwMSiIqLGzjGy89NPP+njiJCT/cki+xar0Nq1a/XfPXr00NYcCWZ+8cUXbVmwCCGRoaWGEJIDES/iLilXrlzmOnHl5MuXD6NGjdJio0CBArb3m56ensUlZLptAhHXk8S8yKRfqVIlfczGjRtrF44dRMCIBebll1/WFhOxjojrRxArjuxf4nlE2EiMi6RvhzuGWF/CjV2El7i0xo4dm+O9EuMjyDjuvPNOfPnll9qy89BDD+mg5kaNGtk6N0JIcGipIYRkQcTMe++9h2effVZbY8xFLBEicsyAWskgkjiaUOTNm1dbRLJP7v/8808WcSD7DkRiUWTilzias846S4uaHTt22D4PCdgVETVu3Dh9PuKSMt1CcgwJ4hX3mrjMqlatit9//z3s/mTsgZaVP/74AwcPHsx8fv755+t1pUuXRvXq1bMsIgJNzjvvPAwaNAjz58/H2WefrcdHCHEGihpCSBY+++wz7N69W1s6ZNINXCQmxXRBDR48WAscefztt9+wYsUKPPXUU5n7kYwmSQXfsmVLpiiR+Jbt27fj6aef1i4ZsaJ88cUXWY4vbqf3339f73PRokXo0qVLVFYhcf+Iy0wEhIgRcf0EHkMsJCIs5Di33XabdntFivURK5UERS9ZsgS9e/dGnjx5Ml+XcUrGloglcXWtW7dOx9KIQJP0cnkuY5EAYcl4mjFjhhZBjKshxDkoagghWRDR0qpVqyzWBRMRNTKhS/aOCBTJKJo2bZpO05ZJPzB7SDKfJJ1Z3D6m+0Um8FdeeUWLGbGQyPaBAbvm8UVUieVDMpJEFIj1IxpEmMm+JI4l0JUmbh/Zv6yX85BgZslMCodYripWrIiLLroIN954ox63pIObyN8i4k4//XRcc801+lzl+BJTI3FB8vqqVav0NTzjjDN05lOfPn20oCKEOEOayu4kJoQQQgjxILTUEEIIIcQXUNQQQgghxBdQ1BBCCCHEF1DUEEIIIcQXUNQQQgghxBdQ1BBCCCHEF1DUEEIIIcQXUNQQQgghxBdQ1BBCCCHEF1DUEEIIIcQXUNQQQgghxBdQ1BBCCCEEfuD/Abi+LSrudY9gAAAAAElFTkSuQmCC"/>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [18]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.preprocessing</span><span class="w"> </span><span class="kn">import</span> <span class="n">KBinsDiscretizer</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.linear_model</span><span class="w"> </span><span class="kn">import</span> <span class="n">LogisticRegression</span>

<span class="c1"># Bin the continuous target values into discrete classes</span>
<span class="n">kbins</span> <span class="o">=</span> <span class="n">KBinsDiscretizer</span><span class="p">(</span><span class="n">n_bins</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">encode</span><span class="o">=</span><span class="s1">'ordinal'</span><span class="p">,</span> <span class="n">strategy</span><span class="o">=</span><span class="s1">'uniform'</span><span class="p">)</span>
<span class="n">y_train_binned</span> <span class="o">=</span> <span class="n">kbins</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">y_train</span><span class="o">.</span><span class="n">values</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="n">y_test_binned</span> <span class="o">=</span> <span class="n">kbins</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">y_test</span><span class="o">.</span><span class="n">values</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>

<span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">LogisticRegression</span><span class="p">()</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="n">accuracy</span> <span class="o">=</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">conf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">class_report</span> <span class="o">=</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Accuracy: </span><span class="si">{</span><span class="n">accuracy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Confusion Matrix:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">conf_matrix</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Classification Report:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">class_report</span><span class="p">)</span>
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<pre>Accuracy: 0.73
Confusion Matrix:
[[  1  21   0]
 [  0 118   3]
 [  0  30  27]]
Classification Report:
              precision    recall  f1-score   support

         0.0       1.00      0.05      0.09        22
         1.0       0.70      0.98      0.81       121
         2.0       0.90      0.47      0.62        57

    accuracy                           0.73       200
   macro avg       0.87      0.50      0.51       200
weighted avg       0.79      0.73      0.68       200

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<div class="jp-InputPrompt jp-InputArea-prompt">In [20]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="n">accuracy</span> <span class="o">=</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">conf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">class_report</span> <span class="o">=</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Accuracy: </span><span class="si">{</span><span class="n">accuracy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Confusion Matrix:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">conf_matrix</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Classification Report:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">class_report</span><span class="p">)</span>
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<pre>Accuracy: 0.655
Confusion Matrix:
[[  2  20   0]
 [  1 107  13]
 [  0  35  22]]
Classification Report:
              precision    recall  f1-score   support

         0.0       0.67      0.09      0.16        22
         1.0       0.66      0.88      0.76       121
         2.0       0.63      0.39      0.48        57

    accuracy                           0.66       200
   macro avg       0.65      0.45      0.46       200
weighted avg       0.65      0.66      0.61       200

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<div class="jp-InputPrompt jp-InputArea-prompt">In [21]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="n">accuracy</span> <span class="o">=</span> <span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">conf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="n">class_report</span> <span class="o">=</span> <span class="n">classification_report</span><span class="p">(</span><span class="n">y_test_binned</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Accuracy: </span><span class="si">{</span><span class="n">accuracy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Confusion Matrix:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">conf_matrix</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Classification Report:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">class_report</span><span class="p">)</span>
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<pre>Accuracy: 0.565
Confusion Matrix:
[[ 6 15  1]
 [ 7 92 22]
 [ 0 42 15]]
Classification Report:
              precision    recall  f1-score   support

         0.0       0.46      0.27      0.34        22
         1.0       0.62      0.76      0.68       121
         2.0       0.39      0.26      0.32        57

    accuracy                           0.56       200
   macro avg       0.49      0.43      0.45       200
weighted avg       0.54      0.56      0.54       200

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<div class="jp-InputPrompt jp-InputArea-prompt">In [24]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">))</span>
<span class="n">plot_tree</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">filled</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">feature_names</span><span class="o">=</span><span class="n">selected_feature_names</span><span class="p">,</span> <span class="n">class_names</span><span class="o">=</span><span class="p">[</span><span class="s1">'Class 0'</span><span class="p">,</span> <span class="s1">'Class 1'</span><span class="p">,</span> <span class="s1">'Class 2'</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Decision Tree Visualization'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [25]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">SVC</span><span class="p">(</span><span class="n">kernel</span><span class="o">=</span><span class="s1">'linear'</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Accuracy: </span><span class="si">{</span><span class="n">accuracy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Confusion Matrix:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">conf_matrix</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Classification Report:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">class_report</span><span class="p">)</span>
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<pre>Accuracy: 0.565
Confusion Matrix:
[[ 6 15  1]
 [ 7 92 22]
 [ 0 42 15]]
Classification Report:
              precision    recall  f1-score   support

         0.0       0.46      0.27      0.34        22
         1.0       0.62      0.76      0.68       121
         2.0       0.39      0.26      0.32        57

    accuracy                           0.56       200
   macro avg       0.49      0.43      0.45       200
weighted avg       0.54      0.56      0.54       200

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<div class="highlight hl-ipython3"><pre><span></span><span class="n">scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">selector</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">X_train_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">X_test_selected</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_selected</span><span class="p">,</span> <span class="n">y_train_binned</span><span class="p">)</span>
<span class="n">y_pred</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test_selected</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Accuracy: </span><span class="si">{</span><span class="n">accuracy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Confusion Matrix:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">conf_matrix</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Classification Report:"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">class_report</span><span class="p">)</span>
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<pre>Accuracy: 0.565
Confusion Matrix:
[[ 6 15  1]
 [ 7 92 22]
 [ 0 42 15]]
Classification Report:
              precision    recall  f1-score   support

         0.0       0.46      0.27      0.34        22
         1.0       0.62      0.76      0.68       121
         2.0       0.39      0.26      0.32        57

    accuracy                           0.56       200
   macro avg       0.49      0.43      0.45       200
weighted avg       0.54      0.56      0.54       200

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