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PINA/docs/source/tutorials/tutorial2/tutorial.html
github-actions[bot] e917753702 export tutorials changed in c161138 (#498) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-03-19 17:48:29 +01:00

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<title>tutorial</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script><script>
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--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-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);
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--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),
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<h1 id="Tutorial:-Two-dimensional-Poisson-problem-using-Extra-Features-Learning">Tutorial: Two dimensional Poisson problem using Extra Features Learning<a class="anchor-link" href="#Tutorial:-Two-dimensional-Poisson-problem-using-Extra-Features-Learning"></a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial2/tutorial.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p>
<p>This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs) a 2D Poisson problem with Dirichlet boundary conditions. We will train with standard PINN's training, and with extrafeatures. For more insights on extrafeature learning please read <a href="https://www.sciencedirect.com/science/article/abs/pii/S0898122123002018"><em>An extended physics informed neural network for preliminary analysis of parametric optimal control problems</em></a>.</p>
<p>First of all, some useful imports.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab"</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</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">import</span><span class="w"> </span><span class="nn">warnings</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina</span><span class="w"> </span><span class="kn">import</span> <span class="n">LabelTensor</span><span class="p">,</span> <span class="n">Trainer</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.model</span><span class="w"> </span><span class="kn">import</span> <span class="n">FeedForward</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.solver</span><span class="w"> </span><span class="kn">import</span> <span class="n">PINN</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">torch.nn</span><span class="w"> </span><span class="kn">import</span> <span class="n">Softplus</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
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<h2 id="The-problem-definition">The problem definition<a class="anchor-link" href="#The-problem-definition"></a></h2>
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<p>The two-dimensional Poisson problem is mathematically written as:
\begin{equation}
\begin{cases}
\Delta u = 2\pi^2\sin{(\pi x)} \sin{(\pi y)} \text{ in } D, \\
u = 0 \text{ on } \Gamma_1 \cup \Gamma_2 \cup \Gamma_3 \cup \Gamma_4,
\end{cases}
\end{equation}
where $D$ is a square domain $[0,1]^2$, and $\Gamma_i$, with $i=1,...,4$, are the boundaries of the square.</p>
<p>The Poisson problem is written in <strong>PINA</strong> code as a class. The equations are written as <em>conditions</em> that should be satisfied in the corresponding domains. The <em>solution</em>
is the exact solution which will be compared with the predicted one. If interested in how to write problems see <a href="https://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html">this tutorial</a>.</p>
<p>We will directly import the problem from <code>pina.problem.zoo</code>, which contains a vast list of PINN problems and more.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">pina.problem.zoo</span><span class="w"> </span><span class="kn">import</span> <span class="n">Poisson2DSquareProblem</span> <span class="k">as</span> <span class="n">Poisson</span>
<span class="c1"># initialize the problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">Poisson</span><span class="p">()</span>
<span class="c1"># print the conditions</span>
<span class="nb">print</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">"The problem is made of </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">conditions</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="si">}</span><span class="s2"> conditions: </span><span class="se">\n</span><span class="s2">"</span>
<span class="sa">f</span><span class="s2">"They are: </span><span class="si">{</span><span class="nb">list</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">conditions</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="si">}</span><span class="s2">"</span>
<span class="p">)</span>
<span class="c1"># let's discretise the domain</span>
<span class="n">problem</span><span class="o">.</span><span class="n">discretise_domain</span><span class="p">(</span><span class="mi">30</span><span class="p">,</span> <span class="s2">"grid"</span><span class="p">,</span> <span class="n">domains</span><span class="o">=</span><span class="p">[</span><span class="s2">"D"</span><span class="p">])</span>
<span class="n">problem</span><span class="o">.</span><span class="n">discretise_domain</span><span class="p">(</span>
<span class="mi">100</span><span class="p">,</span>
<span class="s2">"grid"</span><span class="p">,</span>
<span class="n">domains</span><span class="o">=</span><span class="p">[</span><span class="s2">"g1"</span><span class="p">,</span> <span class="s2">"g2"</span><span class="p">,</span> <span class="s2">"g3"</span><span class="p">,</span> <span class="s2">"g4"</span><span class="p">],</span>
<span class="p">)</span>
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<pre>The problem is made of 5 conditions:
They are: ['g1', 'g2', 'g3', 'g4', 'D']
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<h2 id="Solving-the-problem-with-standard-PINNs">Solving the problem with standard PINNs<a class="anchor-link" href="#Solving-the-problem-with-standard-PINNs"></a></h2>
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<p>After the problem, the feed-forward neural network is defined, through the class <code>FeedForward</code>. This neural network takes as input the coordinates (in this case $x$ and $y$) and provides the unkwown field of the Poisson problem. The residual of the equations are evaluated at several sampling points and the loss minimized by the neural network is the sum of the residuals.</p>
<p>In this tutorial, the neural network is composed by two hidden layers of 10 neurons each, and it is trained for 1000 epochs with a learning rate of 0.006 and $l_2$ weight regularization set to $10^{-8}$. These parameters can be modified as desired. We set the <code>train_size</code> to 0.8 and <code>test_size</code> to 0.2, this mean that the discretised points will be divided in a 80%-20% fashion, where 80% will be used for training and the remaining 20% for testing.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># make model + solver + trainer</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.optim</span><span class="w"> </span><span class="kn">import</span> <span class="n">TorchOptimizer</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">FeedForward</span><span class="p">(</span>
<span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span>
<span class="n">func</span><span class="o">=</span><span class="n">Softplus</span><span class="p">,</span>
<span class="n">output_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">output_variables</span><span class="p">),</span>
<span class="n">input_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">input_variables</span><span class="p">),</span>
<span class="p">)</span>
<span class="n">pinn</span> <span class="o">=</span> <span class="n">PINN</span><span class="p">(</span>
<span class="n">problem</span><span class="p">,</span>
<span class="n">model</span><span class="p">,</span>
<span class="n">optimizer</span><span class="o">=</span><span class="n">TorchOptimizer</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.006</span><span class="p">,</span> <span class="n">weight_decay</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">),</span>
<span class="p">)</span>
<span class="n">trainer_base</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="o">=</span><span class="n">pinn</span><span class="p">,</span> <span class="c1"># setting the solver, i.e. PINN</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="c1"># setting max epochs in training</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span> <span class="c1"># we train on cpu, also other are available</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="c1"># model summary statistics not printed</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="c1"># set train size</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="c1"># set validation size</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="c1"># set testing size</span>
<span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="c1"># shuffle the data</span>
<span class="p">)</span>
<span class="c1"># train</span>
<span class="n">trainer_base</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>Missing logger folder: /home/runner/work/PINA/PINA/tutorials/tutorial2/lightning_logs
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<pre>`Trainer.fit` stopped: `max_epochs=1000` reached.
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<p>Now we plot the results using <code>matplotlib</code>.
The solution predicted by the neural network is plotted on the left, the exact one is represented at the center and on the right the error between the exact and the predicted solutions is showed.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="nd">@torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">()</span>
<span class="k">def</span><span class="w"> </span><span class="nf">plot_solution</span><span class="p">(</span><span class="n">solver</span><span class="p">):</span>
<span class="c1"># get the problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">solver</span><span class="o">.</span><span class="n">problem</span>
<span class="c1"># get spatial points</span>
<span class="n">spatial_samples</span> <span class="o">=</span> <span class="n">problem</span><span class="o">.</span><span class="n">spatial_domain</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">30</span><span class="p">,</span> <span class="s2">"grid"</span><span class="p">)</span>
<span class="c1"># compute pinn solution, true solution and absolute difference</span>
<span class="n">data</span> <span class="o">=</span> <span class="p">{</span>
<span class="s2">"PINN solution"</span><span class="p">:</span> <span class="n">solver</span><span class="p">(</span><span class="n">spatial_samples</span><span class="p">),</span>
<span class="s2">"True solution"</span><span class="p">:</span> <span class="n">problem</span><span class="o">.</span><span class="n">solution</span><span class="p">(</span><span class="n">spatial_samples</span><span class="p">),</span>
<span class="s2">"Absolute Difference"</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span>
<span class="n">solver</span><span class="p">(</span><span class="n">spatial_samples</span><span class="p">)</span> <span class="o">-</span> <span class="n">problem</span><span class="o">.</span><span class="n">solution</span><span class="p">(</span><span class="n">spatial_samples</span><span class="p">)</span>
<span class="p">),</span>
<span class="p">}</span>
<span class="c1"># plot the solution</span>
<span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="p">(</span><span class="n">title</span><span class="p">,</span> <span class="n">field</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">idx</span> <span class="o">+</span> <span class="mi">1</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="n">title</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tricontourf</span><span class="p">(</span> <span class="c1"># convert to torch tensor + flatten</span>
<span class="n">spatial_samples</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)</span><span class="o">.</span><span class="n">tensor</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span>
<span class="n">spatial_samples</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"y"</span><span class="p">)</span><span class="o">.</span><span class="n">tensor</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span>
<span class="n">field</span><span class="o">.</span><span class="n">tensor</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span>
<span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(),</span> <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
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<p>Here the solution:</p>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [5]:</div>
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<div class="cm-editor cm-s-jupyter">
<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">12</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="n">plot_solution</span><span class="p">(</span><span class="n">solver</span><span class="o">=</span><span class="n">pinn</span><span class="p">)</span>
</pre></div>
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9cmIiICXbt2RVBQkHPb0KFDUV5eDrvdDpPJ5NeaW+NNPytWrEBSUhJee+01AMCIESNQU1OD+fPnY/ny5QgM7Fjr1S3NBT179uRfLwzOSNlhpNwAmB0As0PvmB2dk5FyA2B2MDvUxexgdqhB83eEyWTCmDFjkJ+f79zW0NCA/Px8xMfHu90nPj7eZTwAHDlypMXxavKmHwBYv349Vq9ejcOHD2Ps2LFqlNompb3Exsbi8uXLKCwsdP5MmzYNkyZNQmFhIaKiotQsvxlvXpvx48fj6tWrzrADgJ9//hkRERGaBgTgXT93795tFgSNASgi/ivWT/Q8F5B/GSk7jJQbALMDYHbonV7nAvIvI+UGwOxgdqiL2aHv+cAwtPw29ka5ubliNpslJydHioqKZP78+dKrVy8pLy8XEZGkpCRJT093jj916pR06dJFNmzYIMXFxZKRkaG727oq6ScrK0tMJpN8/fXXcvPmTedPdXW1Vi04Ke2lKb3dNUNpP2VlZRIcHCxvvPGGlJSUyMGDByUsLEzWrFmjVQsulPaTkZEhwcHB8uWXX8q1a9fku+++k4EDB8qMGTO0asFFdXW1XLp0SS5duiQAZOPGjXLp0iW5ceOGiIikp6dLUlKSc3zjLV3feecdKS4uluzsbN7StRMxUnYYKTdEmB3MDnUxO8hTRsoNEWZHU8wO/2J2MDv8TReLUyIimzdvlujoaDGZTBIXFydnzpxx/m7ixImSnJzsMn7Pnj0yePBgMZlMMmzYMDl06JDKFbdOST/9+vUTAM1+MjIy1C/cDaWvzYP0FhIiyvs5ffq02Gw2MZvNEhMTI2vXrhWHw6Fy1S1T0k9dXZ2sXLlSBg4cKBaLRaKiomThwoVy+/Zt9Qt34/jx426PhcYekpOTZeLEic32GTVqlJhMJomJiZGdO3eqXjdpx0jZYaTcEGF2MDvUw+wgJYyUGyLMjgcxO/yP2cHs8KcAkQ54TR0RERERERERERmC5t85RUREREREREREnRcXp4iIiIiIiIiISDNcnCIiIiIiIiIiIs1wcYqIiIiIiIiIiDTDxSkiIiIiIiIiItIMF6eIiIiIiIiIiEgzXJwiIiIiIiIiIiLNcHGKiIiIiIiIiIg0w8UpIiIiIiIiIiLSDBeniIiIiIiIiIhIM1ycIiIiIiIiIiIizXBxioiIiIiIiIiINPN/0uk5GyUhSnoAAAAASUVORK5CYII="/>
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<p>As you can see the solution is not very accurate, in what follows we will use <strong>Extra Feature</strong> as introduced in <a href="https://www.sciencedirect.com/science/article/abs/pii/S0898122123002018"><em>An extended physics informed neural network for preliminary analysis of parametric optimal control problems</em></a> to boost the training accuracy. Of course, even extra training will benefit, this tutorial is just to show that convergence using Extra Features is usally faster.</p>
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<h2 id="Solving-the-problem-with-extra-features-PINNs">Solving the problem with extra-features PINNs<a class="anchor-link" href="#Solving-the-problem-with-extra-features-PINNs"></a></h2>
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<p>Now, the same problem is solved in a different way.
A new neural network is now defined, with an additional input variable, named extra-feature, which coincides with the forcing term in the Laplace equation.
The set of input variables to the neural network is:</p>
<p>\begin{equation}
[x, y, k(x, y)], \text{ with } k(x, y)= 2\pi^2\sin{(\pi x)}\sin{(\pi y)},
\end{equation}</p>
<p>where $x$ and $y$ are the spatial coordinates and $k(x, y)$ is the added feature which is equal to the forcing term.</p>
<p>This feature is initialized in the class <code>SinSin</code>, which is a simple <code>torch.nn.Module</code>. After declaring such feature, we can just adjust the <code>FeedForward</code> class by creating a subclass <code>FeedForwardWithExtraFeatures</code> with an adjusted forward method and the additional attribute <code>extra_features</code>.</p>
<p>Finally, we perform the same training as before: the problem is <code>Poisson</code>, the network is composed by the same number of neurons and optimizer parameters are equal to previous test, the only change is the new extra feature.</p>
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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="k">class</span><span class="w"> </span><span class="nc">SinSin</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
<span class="w"> </span><span class="sd">"""Feature: sin(x)*sin(y)"""</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pts</span><span class="p">):</span>
<span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">pts</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"x"</span><span class="p">]),</span> <span class="n">pts</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"y"</span><span class="p">])</span>
<span class="n">f</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">pi</span><span class="o">**</span><span class="mi">2</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">y</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span>
<span class="k">return</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="p">[</span><span class="s2">"feat"</span><span class="p">])</span>
<span class="k">class</span><span class="w"> </span><span class="nc">FeedForwardWithExtraFeatures</span><span class="p">(</span><span class="n">FeedForward</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="n">extra_features</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">extra_features</span> <span class="o">=</span> <span class="n">extra_features</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="n">extra_feature</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">extra_features</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="c1"># we append extra features</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">extra_feature</span><span class="p">)</span>
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">model_feat</span> <span class="o">=</span> <span class="n">FeedForwardWithExtraFeatures</span><span class="p">(</span>
<span class="n">input_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">input_variables</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span>
<span class="n">output_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">output_variables</span><span class="p">),</span>
<span class="n">func</span><span class="o">=</span><span class="n">Softplus</span><span class="p">,</span>
<span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span>
<span class="n">extra_features</span><span class="o">=</span><span class="n">SinSin</span><span class="p">(),</span>
<span class="p">)</span>
<span class="n">pinn_feat</span> <span class="o">=</span> <span class="n">PINN</span><span class="p">(</span>
<span class="n">problem</span><span class="p">,</span>
<span class="n">model_feat</span><span class="p">,</span>
<span class="n">optimizer</span><span class="o">=</span><span class="n">TorchOptimizer</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.006</span><span class="p">,</span> <span class="n">weight_decay</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">),</span>
<span class="p">)</span>
<span class="n">trainer_feat</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="o">=</span><span class="n">pinn_feat</span><span class="p">,</span> <span class="c1"># setting the solver, i.e. PINN</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="c1"># setting max epochs in training</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span> <span class="c1"># we train on cpu, also other are available</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="c1"># model summary statistics not printed</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="c1"># set train size</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="c1"># set validation size</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="c1"># set testing size</span>
<span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="c1"># shuffle the data</span>
<span class="p">)</span>
<span class="n">trainer_feat</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=1000` reached.
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<p>The predicted and exact solutions and the error between them are represented below.
We can easily note that now our network, having almost the same condition as before, is able to reach additional order of magnitudes in accuracy.</p>
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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">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">12</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="n">plot_solution</span><span class="p">(</span><span class="n">solver</span><span class="o">=</span><span class="n">pinn_feat</span><span class="p">)</span>
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"/>
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<h2 id="Solving-the-problem-with-learnable-extra-features-PINNs">Solving the problem with learnable extra-features PINNs<a class="anchor-link" href="#Solving-the-problem-with-learnable-extra-features-PINNs"></a></h2>
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<p>We can still do better!</p>
<p>Another way to exploit the extra features is the addition of learnable parameter inside them.
In this way, the added parameters are learned during the training phase of the neural network. In this case, we use:</p>
<p>\begin{equation}
k(x, \mathbf{y}) = \beta \sin{(\alpha x)} \sin{(\alpha y)},
\end{equation}</p>
<p>where $\alpha$ and $\beta$ are the abovementioned parameters.
Their implementation is quite trivial: by using the class <code>torch.nn.Parameter</code> we cam define all the learnable parameters we need, and they are managed by <code>autograd</code> module!</p>
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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="k">class</span><span class="w"> </span><span class="nc">SinSinAB</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
<span class="w"> </span><span class="sd">""" """</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">]))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">beta</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">]))</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="n">t</span> <span class="o">=</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">beta</span>
<span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">*</span> <span class="n">x</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"x"</span><span class="p">])</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span>
<span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">*</span> <span class="n">x</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"y"</span><span class="p">])</span> <span class="o">*</span> <span class="n">torch</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span>
<span class="p">)</span>
<span class="k">return</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="p">[</span><span class="s2">"b*sin(a*x)sin(a*y)"</span><span class="p">])</span>
<span class="c1"># make model + solver + trainer</span>
<span class="n">model_learn</span> <span class="o">=</span> <span class="n">FeedForwardWithExtraFeatures</span><span class="p">(</span>
<span class="n">input_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">input_variables</span><span class="p">)</span>
<span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="c1"># we add one as also we consider the extra feature dimension</span>
<span class="n">output_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">output_variables</span><span class="p">),</span>
<span class="n">func</span><span class="o">=</span><span class="n">Softplus</span><span class="p">,</span>
<span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span>
<span class="n">extra_features</span><span class="o">=</span><span class="n">SinSinAB</span><span class="p">(),</span>
<span class="p">)</span>
<span class="n">pinn_learn</span> <span class="o">=</span> <span class="n">PINN</span><span class="p">(</span>
<span class="n">problem</span><span class="p">,</span>
<span class="n">model_learn</span><span class="p">,</span>
<span class="n">optimizer</span><span class="o">=</span><span class="n">TorchOptimizer</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.006</span><span class="p">,</span> <span class="n">weight_decay</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">),</span>
<span class="p">)</span>
<span class="n">trainer_learn</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="o">=</span><span class="n">pinn_learn</span><span class="p">,</span> <span class="c1"># setting the solver, i.e. PINN</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="c1"># setting max epochs in training</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span> <span class="c1"># we train on cpu, also other are available</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="c1"># model summary statistics not printed</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="c1"># set train size</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="c1"># set validation size</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="c1"># set testing size</span>
<span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="c1"># shuffle the data</span>
<span class="p">)</span>
<span class="c1"># train</span>
<span class="n">trainer_learn</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=1000` reached.
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<p>Umh, the final loss is not appreciabily better than previous model (with static extra features), despite the usage of learnable parameters. This is mainly due to the over-parametrization of the network: there are many parameter to optimize during the training, and the model in unable to understand automatically that only the parameters of the extra feature (and not the weights/bias of the FFN) should be tuned in order to fit our problem. A longer training can be helpful, but in this case the faster way to reach machine precision for solving the Poisson problem is removing all the hidden layers in the <code>FeedForward</code>, keeping only the $\alpha$ and $\beta$ parameters of the extra feature.</p>
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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="c1"># make model + solver + trainer</span>
<span class="n">model_learn</span> <span class="o">=</span> <span class="n">FeedForwardWithExtraFeatures</span><span class="p">(</span>
<span class="n">layers</span><span class="o">=</span><span class="p">[],</span>
<span class="n">func</span><span class="o">=</span><span class="n">Softplus</span><span class="p">,</span>
<span class="n">output_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">output_variables</span><span class="p">),</span>
<span class="n">input_dimensions</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">input_variables</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span>
<span class="n">extra_features</span><span class="o">=</span><span class="n">SinSinAB</span><span class="p">(),</span>
<span class="p">)</span>
<span class="n">pinn_learn</span> <span class="o">=</span> <span class="n">PINN</span><span class="p">(</span>
<span class="n">problem</span><span class="p">,</span>
<span class="n">model_learn</span><span class="p">,</span>
<span class="n">optimizer</span><span class="o">=</span><span class="n">TorchOptimizer</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.006</span><span class="p">,</span> <span class="n">weight_decay</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">),</span>
<span class="p">)</span>
<span class="n">trainer_learn</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="o">=</span><span class="n">pinn_learn</span><span class="p">,</span> <span class="c1"># setting the solver, i.e. PINN</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="c1"># setting max epochs in training</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span> <span class="c1"># we train on cpu, also other are available</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="c1"># model summary statistics not printed</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="c1"># set train size</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="c1"># set validation size</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="c1"># set testing size</span>
<span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="c1"># shuffle the data</span>
<span class="p">)</span>
<span class="c1"># train</span>
<span class="n">trainer_learn</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=1000` reached.
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<p>In such a way, the model is able to reach a very high accuracy!
Of course, this is a toy problem for understanding the usage of extra features: similar precision could be obtained if the extra features are very similar to the true solution. The analyzed Poisson problem shows a forcing term very close to the solution, resulting in a perfect problem to address with such an approach.</p>
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<p>We conclude here by showing the test error for the analysed methodologies: the standard PINN, PINN with extra features, and PINN with learnable extra features.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># test error base pinn</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"PINN"</span><span class="p">)</span>
<span class="n">trainer_base</span><span class="o">.</span><span class="n">test</span><span class="p">()</span>
<span class="c1"># test error extra features pinn</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"PINN with extra features"</span><span class="p">)</span>
<span class="n">trainer_feat</span><span class="o">.</span><span class="n">test</span><span class="p">()</span>
<span class="c1"># test error learnable extra features pinn</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"PINN with learnable extra features"</span><span class="p">)</span>
<span class="n">_</span> <span class="o">=</span> <span class="n">trainer_learn</span><span class="o">.</span><span class="n">test</span><span class="p">()</span>
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<pre>PINN
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<pre>────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Test metric DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
test_loss 0.30236542224884033
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
PINN with extra features
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<pre>────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Test metric DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
test_loss 0.0028569151181727648
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
PINN with learnable extra features
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<pre>────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Test metric DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
test_loss 1.570544562456977e-11
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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<h2 id="What's-next?">What's next?<a class="anchor-link" href="#What's-next?"></a></h2><p>Congratulations on completing the two dimensional Poisson tutorial of <strong>PINA</strong>! There are multiple directions you can go now:</p>
<ol>
<li><p>Train the network for longer or with different layer sizes and assert the finaly accuracy</p>
</li>
<li><p>Propose new types of extrafeatures and see how they affect the learning</p>
</li>
<li><p>Exploit extrafeature training in more complex problems</p>
</li>
<li><p>Many more...</p>
</li>
</ol>
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