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PINA/docs/source/tutorials/tutorial10/tutorial.html
github-actions[bot] d10c525e74 export tutorials changed in dd88513 (#559) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-04-23 18:53:30 +02:00

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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,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbi1jb250cmFzdDIganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjRDgxQjYwIj4KICAgIDxwYXRoIGQ9Ik03LjIgMTguNnYtNS40TDMgNS42aDMuM2wxLjQgMy4xYy4zLjkuNiAxLjYgMSAyLjUuMy0uOC42LTEuNiAxLTIuNWwxLjQtMy4xaDMuNGwtNC40IDcuNnY1LjVsLTIuOS0uMXoiLz4KICAgIDxjaXJjbGUgY2xhc3M9InN0MCIgY3g9IjE3LjYiIGN5PSIxNi41IiByPSIyLjEiLz4KICAgIDxjaXJjbGUgY2xhc3M9InN0MCIgY3g9IjE3LjYiIGN5PSIxMSIgcj0iMi4xIi8+CiAgPC9nPgo8L3N2Zz4K);
}
/* Icon CSS class declarations */
.jp-AddAboveIcon {
background-image: var(--jp-icon-add-above);
}
.jp-AddBelowIcon {
background-image: var(--jp-icon-add-below);
}
.jp-AddIcon {
background-image: var(--jp-icon-add);
}
.jp-BellIcon {
background-image: var(--jp-icon-bell);
}
.jp-BugDotIcon {
background-image: var(--jp-icon-bug-dot);
}
.jp-BugIcon {
background-image: var(--jp-icon-bug);
}
.jp-BuildIcon {
background-image: var(--jp-icon-build);
}
.jp-CaretDownEmptyIcon {
background-image: var(--jp-icon-caret-down-empty);
}
.jp-CaretDownEmptyThinIcon {
background-image: var(--jp-icon-caret-down-empty-thin);
}
.jp-CaretDownIcon {
background-image: var(--jp-icon-caret-down);
}
.jp-CaretLeftIcon {
background-image: var(--jp-icon-caret-left);
}
.jp-CaretRightIcon {
background-image: var(--jp-icon-caret-right);
}
.jp-CaretUpEmptyThinIcon {
background-image: var(--jp-icon-caret-up-empty-thin);
}
.jp-CaretUpIcon {
background-image: var(--jp-icon-caret-up);
}
.jp-CaseSensitiveIcon {
background-image: var(--jp-icon-case-sensitive);
}
.jp-CheckIcon {
background-image: var(--jp-icon-check);
}
.jp-CircleEmptyIcon {
background-image: var(--jp-icon-circle-empty);
}
.jp-CircleIcon {
background-image: var(--jp-icon-circle);
}
.jp-ClearIcon {
background-image: var(--jp-icon-clear);
}
.jp-CloseIcon {
background-image: var(--jp-icon-close);
}
.jp-CodeCheckIcon {
background-image: var(--jp-icon-code-check);
}
.jp-CodeIcon {
background-image: var(--jp-icon-code);
}
.jp-CollapseAllIcon {
background-image: var(--jp-icon-collapse-all);
}
.jp-ConsoleIcon {
background-image: var(--jp-icon-console);
}
.jp-CopyIcon {
background-image: var(--jp-icon-copy);
}
.jp-CopyrightIcon {
background-image: var(--jp-icon-copyright);
}
.jp-CutIcon {
background-image: var(--jp-icon-cut);
}
.jp-DeleteIcon {
background-image: var(--jp-icon-delete);
}
.jp-DownloadIcon {
background-image: var(--jp-icon-download);
}
.jp-DuplicateIcon {
background-image: var(--jp-icon-duplicate);
}
.jp-EditIcon {
background-image: var(--jp-icon-edit);
}
.jp-EllipsesIcon {
background-image: var(--jp-icon-ellipses);
}
.jp-ErrorIcon {
background-image: var(--jp-icon-error);
}
.jp-ExpandAllIcon {
background-image: var(--jp-icon-expand-all);
}
.jp-ExtensionIcon {
background-image: var(--jp-icon-extension);
}
.jp-FastForwardIcon {
background-image: var(--jp-icon-fast-forward);
}
.jp-FileIcon {
background-image: var(--jp-icon-file);
}
.jp-FileUploadIcon {
background-image: var(--jp-icon-file-upload);
}
.jp-FilterDotIcon {
background-image: var(--jp-icon-filter-dot);
}
.jp-FilterIcon {
background-image: var(--jp-icon-filter);
}
.jp-FilterListIcon {
background-image: var(--jp-icon-filter-list);
}
.jp-FolderFavoriteIcon {
background-image: var(--jp-icon-folder-favorite);
}
.jp-FolderIcon {
background-image: var(--jp-icon-folder);
}
.jp-HomeIcon {
background-image: var(--jp-icon-home);
}
.jp-Html5Icon {
background-image: var(--jp-icon-html5);
}
.jp-ImageIcon {
background-image: var(--jp-icon-image);
}
.jp-InfoIcon {
background-image: var(--jp-icon-info);
}
.jp-InspectorIcon {
background-image: var(--jp-icon-inspector);
}
.jp-JsonIcon {
background-image: var(--jp-icon-json);
}
.jp-JuliaIcon {
background-image: var(--jp-icon-julia);
}
.jp-JupyterFaviconIcon {
background-image: var(--jp-icon-jupyter-favicon);
}
.jp-JupyterIcon {
background-image: var(--jp-icon-jupyter);
}
.jp-JupyterlabWordmarkIcon {
background-image: var(--jp-icon-jupyterlab-wordmark);
}
.jp-KernelIcon {
background-image: var(--jp-icon-kernel);
}
.jp-KeyboardIcon {
background-image: var(--jp-icon-keyboard);
}
.jp-LaunchIcon {
background-image: var(--jp-icon-launch);
}
.jp-LauncherIcon {
background-image: var(--jp-icon-launcher);
}
.jp-LineFormIcon {
background-image: var(--jp-icon-line-form);
}
.jp-LinkIcon {
background-image: var(--jp-icon-link);
}
.jp-ListIcon {
background-image: var(--jp-icon-list);
}
.jp-MarkdownIcon {
background-image: var(--jp-icon-markdown);
}
.jp-MoveDownIcon {
background-image: var(--jp-icon-move-down);
}
.jp-MoveUpIcon {
background-image: var(--jp-icon-move-up);
}
.jp-NewFolderIcon {
background-image: var(--jp-icon-new-folder);
}
.jp-NotTrustedIcon {
background-image: var(--jp-icon-not-trusted);
}
.jp-NotebookIcon {
background-image: var(--jp-icon-notebook);
}
.jp-NumberingIcon {
background-image: var(--jp-icon-numbering);
}
.jp-OfflineBoltIcon {
background-image: var(--jp-icon-offline-bolt);
}
.jp-PaletteIcon {
background-image: var(--jp-icon-palette);
}
.jp-PasteIcon {
background-image: var(--jp-icon-paste);
}
.jp-PdfIcon {
background-image: var(--jp-icon-pdf);
}
.jp-PythonIcon {
background-image: var(--jp-icon-python);
}
.jp-RKernelIcon {
background-image: var(--jp-icon-r-kernel);
}
.jp-ReactIcon {
background-image: var(--jp-icon-react);
}
.jp-RedoIcon {
background-image: var(--jp-icon-redo);
}
.jp-RefreshIcon {
background-image: var(--jp-icon-refresh);
}
.jp-RegexIcon {
background-image: var(--jp-icon-regex);
}
.jp-RunIcon {
background-image: var(--jp-icon-run);
}
.jp-RunningIcon {
background-image: var(--jp-icon-running);
}
.jp-SaveIcon {
background-image: var(--jp-icon-save);
}
.jp-SearchIcon {
background-image: var(--jp-icon-search);
}
.jp-SettingsIcon {
background-image: var(--jp-icon-settings);
}
.jp-ShareIcon {
background-image: var(--jp-icon-share);
}
.jp-SpreadsheetIcon {
background-image: var(--jp-icon-spreadsheet);
}
.jp-StopIcon {
background-image: var(--jp-icon-stop);
}
.jp-TabIcon {
background-image: var(--jp-icon-tab);
}
.jp-TableRowsIcon {
background-image: var(--jp-icon-table-rows);
}
.jp-TagIcon {
background-image: var(--jp-icon-tag);
}
.jp-TerminalIcon {
background-image: var(--jp-icon-terminal);
}
.jp-TextEditorIcon {
background-image: var(--jp-icon-text-editor);
}
.jp-TocIcon {
background-image: var(--jp-icon-toc);
}
.jp-TreeViewIcon {
background-image: var(--jp-icon-tree-view);
}
.jp-TrustedIcon {
background-image: var(--jp-icon-trusted);
}
.jp-UndoIcon {
background-image: var(--jp-icon-undo);
}
.jp-UserIcon {
background-image: var(--jp-icon-user);
}
.jp-UsersIcon {
background-image: var(--jp-icon-users);
}
.jp-VegaIcon {
background-image: var(--jp-icon-vega);
}
.jp-WordIcon {
background-image: var(--jp-icon-word);
}
.jp-YamlIcon {
background-image: var(--jp-icon-yaml);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* (DEPRECATED) Support for consuming icons as CSS background images
*/
.jp-Icon,
.jp-MaterialIcon {
background-position: center;
background-repeat: no-repeat;
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-cover {
background-position: center;
background-repeat: no-repeat;
background-size: cover;
}
/**
* (DEPRECATED) Support for specific CSS icon sizes
*/
.jp-Icon-16 {
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-18 {
background-size: 18px;
min-width: 18px;
min-height: 18px;
}
.jp-Icon-20 {
background-size: 20px;
min-width: 20px;
min-height: 20px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.lm-TabBar .lm-TabBar-addButton {
align-items: center;
display: flex;
padding: 4px;
padding-bottom: 5px;
margin-right: 1px;
background-color: var(--jp-layout-color2);
}
.lm-TabBar .lm-TabBar-addButton:hover {
background-color: var(--jp-layout-color1);
}
.lm-DockPanel-tabBar .lm-TabBar-tab {
width: var(--jp-private-horizontal-tab-width);
}
.lm-DockPanel-tabBar .lm-TabBar-content {
flex: unset;
}
.lm-DockPanel-tabBar[data-orientation='horizontal'] {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for icons as inline SVG HTMLElements
*/
/* recolor the primary elements of an icon */
.jp-icon0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-accent0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-accent1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-accent2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-accent3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-accent4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-accent0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-accent1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-accent2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-accent3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-accent4[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-none[fill] {
fill: none;
}
.jp-icon-none[stroke] {
stroke: none;
}
/* brand icon colors. Same for light and dark */
.jp-icon-brand0[fill] {
fill: var(--jp-brand-color0);
}
.jp-icon-brand1[fill] {
fill: var(--jp-brand-color1);
}
.jp-icon-brand2[fill] {
fill: var(--jp-brand-color2);
}
.jp-icon-brand3[fill] {
fill: var(--jp-brand-color3);
}
.jp-icon-brand4[fill] {
fill: var(--jp-brand-color4);
}
.jp-icon-brand0[stroke] {
stroke: var(--jp-brand-color0);
}
.jp-icon-brand1[stroke] {
stroke: var(--jp-brand-color1);
}
.jp-icon-brand2[stroke] {
stroke: var(--jp-brand-color2);
}
.jp-icon-brand3[stroke] {
stroke: var(--jp-brand-color3);
}
.jp-icon-brand4[stroke] {
stroke: var(--jp-brand-color4);
}
/* warn icon colors. Same for light and dark */
.jp-icon-warn0[fill] {
fill: var(--jp-warn-color0);
}
.jp-icon-warn1[fill] {
fill: var(--jp-warn-color1);
}
.jp-icon-warn2[fill] {
fill: var(--jp-warn-color2);
}
.jp-icon-warn3[fill] {
fill: var(--jp-warn-color3);
}
.jp-icon-warn0[stroke] {
stroke: var(--jp-warn-color0);
}
.jp-icon-warn1[stroke] {
stroke: var(--jp-warn-color1);
}
.jp-icon-warn2[stroke] {
stroke: var(--jp-warn-color2);
}
.jp-icon-warn3[stroke] {
stroke: var(--jp-warn-color3);
}
/* icon colors that contrast well with each other and most backgrounds */
.jp-icon-contrast0[fill] {
fill: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[fill] {
fill: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[fill] {
fill: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[fill] {
fill: var(--jp-icon-contrast-color3);
}
.jp-icon-contrast0[stroke] {
stroke: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[stroke] {
stroke: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[stroke] {
stroke: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[stroke] {
stroke: var(--jp-icon-contrast-color3);
}
.jp-icon-dot[fill] {
fill: var(--jp-warn-color0);
}
.jp-jupyter-icon-color[fill] {
fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
}
.jp-notebook-icon-color[fill] {
fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
}
.jp-json-icon-color[fill] {
fill: var(--jp-json-icon-color, var(--jp-warn-color1));
}
.jp-console-icon-color[fill] {
fill: var(--jp-console-icon-color, white);
}
.jp-console-icon-background-color[fill] {
fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
}
.jp-terminal-icon-color[fill] {
fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
}
.jp-terminal-icon-background-color[fill] {
fill: var(
--jp-terminal-icon-background-color,
var(--jp-inverse-layout-color2)
);
}
.jp-text-editor-icon-color[fill] {
fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
}
.jp-inspector-icon-color[fill] {
fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
}
/* CSS for icons in selected filebrowser listing items */
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* stylelint-disable selector-max-class, selector-max-compound-selectors */
/**
* TODO: come up with non css-hack solution for showing the busy icon on top
* of the close icon
* CSS for complex behavior of close icon of tabs in the main area tabbar
*/
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon3[fill] {
fill: none;
}
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon-busy[fill] {
fill: var(--jp-inverse-layout-color3);
}
/* stylelint-enable selector-max-class, selector-max-compound-selectors */
/* CSS for icons in status bar */
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* special handling for splash icon CSS. While the theme CSS reloads during
splash, the splash icon can loose theming. To prevent that, we set a
default for its color variable */
:root {
--jp-warn-color0: var(--md-orange-700);
}
/* not sure what to do with this one, used in filebrowser listing */
.jp-DragIcon {
margin-right: 4px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for alt colors for icons as inline SVG HTMLElements
*/
/* alt recolor the primary elements of an icon */
.jp-icon-alt .jp-icon0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-alt .jp-icon0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[stroke] {
stroke: var(--jp-layout-color4);
}
/* alt recolor the accent elements of an icon */
.jp-icon-alt .jp-icon-accent0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-alt .jp-icon-accent0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
display: none !important;
}
/**
* Support for hover colors for icons as inline SVG HTMLElements
*/
/**
* regular colors
*/
/* recolor the primary elements of an icon */
.jp-icon-hover :hover .jp-icon0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-hover :hover .jp-icon-none-hover[fill] {
fill: none;
}
.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
stroke: none;
}
/**
* inverse colors
*/
/* inverse recolor the primary elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* inverse recolor the accent elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-IFrame {
width: 100%;
height: 100%;
}
.jp-IFrame > iframe {
border: none;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-IFrame {
position: relative;
}
body.lm-mod-override-cursor .jp-IFrame::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-HoverBox {
position: fixed;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FormGroup-content fieldset {
border: none;
padding: 0;
min-width: 0;
width: 100%;
}
/* stylelint-disable selector-max-type */
.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
font-size: var(--jp-content-font-size2);
border-color: var(--jp-input-border-color);
border-style: solid;
border-radius: var(--jp-border-radius);
border-width: 1px;
padding: 6px 8px;
background: none;
color: var(--jp-ui-font-color0);
height: inherit;
}
.jp-FormGroup-content fieldset input[type='checkbox'] {
position: relative;
top: 2px;
margin-left: 0;
}
.jp-FormGroup-content button.jp-mod-styled {
cursor: pointer;
}
.jp-FormGroup-content .checkbox label {
cursor: pointer;
font-size: var(--jp-content-font-size1);
}
.jp-FormGroup-content .jp-root > fieldset > legend {
display: none;
}
.jp-FormGroup-content .jp-root > fieldset > p {
display: none;
}
/** copy of `input.jp-mod-styled:focus` style */
.jp-FormGroup-content fieldset input:focus,
.jp-FormGroup-content fieldset select:focus {
-moz-outline-radius: unset;
outline: var(--jp-border-width) solid var(--md-blue-500);
outline-offset: -1px;
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-FormGroup-content fieldset input:hover:not(:focus),
.jp-FormGroup-content fieldset select:hover:not(:focus) {
background-color: var(--jp-border-color2);
}
/* stylelint-enable selector-max-type */
.jp-FormGroup-content .checkbox .field-description {
/* Disable default description field for checkbox:
because other widgets do not have description fields,
we add descriptions to each widget on the field level.
*/
display: none;
}
.jp-FormGroup-content #root__description {
display: none;
}
.jp-FormGroup-content .jp-modifiedIndicator {
width: 5px;
background-color: var(--jp-brand-color2);
margin-top: 0;
margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
flex-shrink: 0;
}
.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
background-color: var(--jp-error-color0);
margin-right: 0.5em;
}
/* RJSF ARRAY style */
.jp-arrayFieldWrapper legend {
font-size: var(--jp-content-font-size2);
color: var(--jp-ui-font-color0);
flex-basis: 100%;
padding: 4px 0;
font-weight: var(--jp-content-heading-font-weight);
border-bottom: 1px solid var(--jp-border-color2);
}
.jp-arrayFieldWrapper .field-description {
padding: 4px 0;
white-space: pre-wrap;
}
.jp-arrayFieldWrapper .array-item {
width: 100%;
border: 1px solid var(--jp-border-color2);
border-radius: 4px;
margin: 4px;
}
.jp-ArrayOperations {
display: flex;
margin-left: 8px;
}
.jp-ArrayOperationsButton {
margin: 2px;
}
.jp-ArrayOperationsButton .jp-icon3[fill] {
fill: var(--jp-ui-font-color0);
}
button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
cursor: not-allowed;
opacity: 0.5;
}
/* RJSF form validation error */
.jp-FormGroup-content .validationErrors {
color: var(--jp-error-color0);
}
/* Hide panel level error as duplicated the field level error */
.jp-FormGroup-content .panel.errors {
display: none;
}
/* RJSF normal content (settings-editor) */
.jp-FormGroup-contentNormal {
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
margin-left: 7px;
color: var(--jp-ui-font-color0);
}
.jp-FormGroup-contentNormal .jp-FormGroup-description {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-default {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
font-size: var(--jp-content-font-size1);
font-weight: normal;
min-width: 120px;
}
.jp-FormGroup-contentNormal fieldset:not(:first-child) {
margin-left: 7px;
}
.jp-FormGroup-contentNormal .field-array-of-string .array-item {
/* Display `jp-ArrayOperations` buttons side-by-side with content except
for small screens where flex-wrap will place them one below the other.
*/
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
/* RJSF compact content (metadata-form) */
.jp-FormGroup-content.jp-FormGroup-contentCompact {
width: 100%;
}
.jp-FormGroup-contentCompact .form-group {
display: flex;
padding: 0.5em 0.2em 0.5em 0;
}
.jp-FormGroup-contentCompact
.jp-FormGroup-compactTitle
.jp-FormGroup-description {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color2);
}
.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
padding-bottom: 0.3em;
}
.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
width: 100%;
box-sizing: border-box;
}
.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
padding-bottom: 7px;
}
.jp-FormGroup-contentCompact
.jp-objectFieldWrapper
.jp-objectFieldWrapper
.form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
.jp-FormGroup-contentCompact ul.error-detail {
margin-block-start: 0.5em;
margin-block-end: 0.5em;
padding-inline-start: 1em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-SidePanel {
display: flex;
flex-direction: column;
min-width: var(--jp-sidebar-min-width);
overflow-y: auto;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
font-size: var(--jp-ui-font-size1);
}
.jp-SidePanel-header {
flex: 0 0 auto;
display: flex;
border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin: 0;
padding: 2px;
text-transform: uppercase;
}
.jp-SidePanel-toolbar {
flex: 0 0 auto;
}
.jp-SidePanel-content {
flex: 1 1 auto;
}
.jp-SidePanel-toolbar,
.jp-AccordionPanel-toolbar {
height: var(--jp-private-toolbar-height);
}
.jp-SidePanel-toolbar.jp-Toolbar-micro {
display: none;
}
.lm-AccordionPanel .jp-AccordionPanel-title {
box-sizing: border-box;
line-height: 25px;
margin: 0;
display: flex;
align-items: center;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
font-size: var(--jp-ui-font-size0);
}
.jp-AccordionPanel-title {
cursor: pointer;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
text-transform: uppercase;
}
.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
/* Title is rotated for horizontal accordion panel using CSS */
display: block;
transform-origin: top left;
transform: rotate(-90deg) translate(-100%);
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
user-select: none;
text-overflow: ellipsis;
white-space: nowrap;
overflow: hidden;
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
transform: rotate(-90deg);
margin: auto 0;
height: 16px;
}
.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
transform: rotate(0deg);
}
.lm-AccordionPanel .jp-AccordionPanel-toolbar {
background: none;
box-shadow: none;
border: none;
margin-left: auto;
}
.lm-AccordionPanel .lm-SplitPanel-handle:hover {
background: var(--jp-layout-color3);
}
.jp-text-truncated {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Spinner {
position: absolute;
display: flex;
justify-content: center;
align-items: center;
z-index: 10;
left: 0;
top: 0;
width: 100%;
height: 100%;
background: var(--jp-layout-color0);
outline: none;
}
.jp-SpinnerContent {
font-size: 10px;
margin: 50px auto;
text-indent: -9999em;
width: 3em;
height: 3em;
border-radius: 50%;
background: var(--jp-brand-color3);
background: linear-gradient(
to right,
#f37626 10%,
rgba(255, 255, 255, 0) 42%
);
position: relative;
animation: load3 1s infinite linear, fadeIn 1s;
}
.jp-SpinnerContent::before {
width: 50%;
height: 50%;
background: #f37626;
border-radius: 100% 0 0;
position: absolute;
top: 0;
left: 0;
content: '';
}
.jp-SpinnerContent::after {
background: var(--jp-layout-color0);
width: 75%;
height: 75%;
border-radius: 50%;
content: '';
margin: auto;
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
@keyframes load3 {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
button.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: none;
box-sizing: border-box;
text-align: center;
line-height: 32px;
height: 32px;
padding: 0 12px;
letter-spacing: 0.8px;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input.jp-mod-styled {
background: var(--jp-input-background);
height: 28px;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color1);
padding-left: 7px;
padding-right: 7px;
font-size: var(--jp-ui-font-size2);
color: var(--jp-ui-font-color0);
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input[type='checkbox'].jp-mod-styled {
appearance: checkbox;
-webkit-appearance: checkbox;
-moz-appearance: checkbox;
height: auto;
}
input.jp-mod-styled:focus {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-select-wrapper {
display: flex;
position: relative;
flex-direction: column;
padding: 1px;
background-color: var(--jp-layout-color1);
box-sizing: border-box;
margin-bottom: 12px;
}
.jp-select-wrapper:not(.multiple) {
height: 28px;
}
.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-input-active-background);
}
select.jp-mod-styled:hover {
cursor: pointer;
color: var(--jp-ui-font-color0);
background-color: var(--jp-input-hover-background);
box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
}
select.jp-mod-styled {
flex: 1 1 auto;
width: 100%;
font-size: var(--jp-ui-font-size2);
background: var(--jp-input-background);
color: var(--jp-ui-font-color0);
padding: 0 25px 0 8px;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
select.jp-mod-styled:not([multiple]) {
height: 32px;
}
select.jp-mod-styled[multiple] {
max-height: 200px;
overflow-y: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-switch {
display: flex;
align-items: center;
padding-left: 4px;
padding-right: 4px;
font-size: var(--jp-ui-font-size1);
background-color: transparent;
color: var(--jp-ui-font-color1);
border: none;
height: 20px;
}
.jp-switch:hover {
background-color: var(--jp-layout-color2);
}
.jp-switch-label {
margin-right: 5px;
font-family: var(--jp-ui-font-family);
}
.jp-switch-track {
cursor: pointer;
background-color: var(--jp-switch-color, var(--jp-border-color1));
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 34px;
height: 16px;
width: 35px;
position: relative;
}
.jp-switch-track::before {
content: '';
position: absolute;
height: 10px;
width: 10px;
margin: 3px;
left: 0;
background-color: var(--jp-ui-inverse-font-color1);
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 50%;
}
.jp-switch[aria-checked='true'] .jp-switch-track {
background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
}
.jp-switch[aria-checked='true'] .jp-switch-track::before {
/* track width (35) - margins (3 + 3) - thumb width (10) */
left: 19px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
:root {
--jp-private-toolbar-height: calc(
28px + var(--jp-border-width)
); /* leave 28px for content */
}
.jp-Toolbar {
color: var(--jp-ui-font-color1);
flex: 0 0 auto;
display: flex;
flex-direction: row;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: 2px;
z-index: 8;
overflow-x: hidden;
}
/* Toolbar items */
.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
flex-grow: 1;
flex-shrink: 1;
}
.jp-Toolbar-item.jp-Toolbar-kernelStatus {
display: inline-block;
width: 32px;
background-repeat: no-repeat;
background-position: center;
background-size: 16px;
}
.jp-Toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
display: flex;
padding-left: 1px;
padding-right: 1px;
font-size: var(--jp-ui-font-size1);
line-height: var(--jp-private-toolbar-height);
height: 100%;
}
/* Toolbar buttons */
/* This is the div we use to wrap the react component into a Widget */
div.jp-ToolbarButton {
color: transparent;
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0;
margin: 0;
}
button.jp-ToolbarButtonComponent {
background: var(--jp-layout-color1);
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0 6px;
margin: 0;
height: 24px;
border-radius: var(--jp-border-radius);
display: flex;
align-items: center;
text-align: center;
font-size: 14px;
min-width: unset;
min-height: unset;
}
button.jp-ToolbarButtonComponent:disabled {
opacity: 0.4;
}
button.jp-ToolbarButtonComponent > span {
padding: 0;
flex: 0 0 auto;
}
button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
font-size: var(--jp-ui-font-size1);
line-height: 100%;
padding-left: 2px;
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar.jp-Toolbar-micro {
padding: 0;
min-height: 0;
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar {
border: none;
box-shadow: none;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-WindowedPanel-outer {
position: relative;
overflow-y: auto;
}
.jp-WindowedPanel-inner {
position: relative;
}
.jp-WindowedPanel-window {
position: absolute;
left: 0;
right: 0;
overflow: visible;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/* Sibling imports */
body {
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
}
/* Disable native link decoration styles everywhere outside of dialog boxes */
a {
text-decoration: unset;
color: unset;
}
a:hover {
text-decoration: unset;
color: unset;
}
/* Accessibility for links inside dialog box text */
.jp-Dialog-content a {
text-decoration: revert;
color: var(--jp-content-link-color);
}
.jp-Dialog-content a:hover {
text-decoration: revert;
}
/* Styles for ui-components */
.jp-Button {
color: var(--jp-ui-font-color2);
border-radius: var(--jp-border-radius);
padding: 0 12px;
font-size: var(--jp-ui-font-size1);
/* Copy from blueprint 3 */
display: inline-flex;
flex-direction: row;
border: none;
cursor: pointer;
align-items: center;
justify-content: center;
text-align: left;
vertical-align: middle;
min-height: 30px;
min-width: 30px;
}
.jp-Button:disabled {
cursor: not-allowed;
}
.jp-Button:empty {
padding: 0 !important;
}
.jp-Button.jp-mod-small {
min-height: 24px;
min-width: 24px;
font-size: 12px;
padding: 0 7px;
}
/* Use our own theme for hover styles */
.jp-Button.jp-mod-minimal:hover {
background-color: var(--jp-layout-color2);
}
.jp-Button.jp-mod-minimal {
background: none;
}
.jp-InputGroup {
display: block;
position: relative;
}
.jp-InputGroup input {
box-sizing: border-box;
border: none;
border-radius: 0;
background-color: transparent;
color: var(--jp-ui-font-color0);
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
padding-bottom: 0;
padding-top: 0;
padding-left: 10px;
padding-right: 28px;
position: relative;
width: 100%;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
font-size: 14px;
font-weight: 400;
height: 30px;
line-height: 30px;
outline: none;
vertical-align: middle;
}
.jp-InputGroup input:focus {
box-shadow: inset 0 0 0 var(--jp-border-width)
var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-InputGroup input:disabled {
cursor: not-allowed;
resize: block;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input:disabled ~ span {
cursor: not-allowed;
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input::placeholder,
input::placeholder {
color: var(--jp-ui-font-color2);
}
.jp-InputGroupAction {
position: absolute;
bottom: 1px;
right: 0;
padding: 6px;
}
.jp-HTMLSelect.jp-DefaultStyle select {
background-color: initial;
border: none;
border-radius: 0;
box-shadow: none;
color: var(--jp-ui-font-color0);
display: block;
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
height: 24px;
line-height: 14px;
padding: 0 25px 0 10px;
text-align: left;
-moz-appearance: none;
-webkit-appearance: none;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
cursor: not-allowed;
resize: block;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
cursor: not-allowed;
}
/* Use our own theme for hover and option styles */
/* stylelint-disable-next-line selector-max-type */
.jp-HTMLSelect.jp-DefaultStyle select:hover,
.jp-HTMLSelect.jp-DefaultStyle select > option {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color0);
}
select {
box-sizing: border-box;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-StatusBar-Widget {
display: flex;
align-items: center;
background: var(--jp-layout-color2);
min-height: var(--jp-statusbar-height);
justify-content: space-between;
padding: 0 10px;
}
.jp-StatusBar-Left {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-StatusBar-Middle {
display: flex;
align-items: center;
}
.jp-StatusBar-Right {
display: flex;
align-items: center;
flex-direction: row-reverse;
}
.jp-StatusBar-Item {
max-height: var(--jp-statusbar-height);
margin: 0 2px;
height: var(--jp-statusbar-height);
white-space: nowrap;
text-overflow: ellipsis;
color: var(--jp-ui-font-color1);
padding: 0 6px;
}
.jp-mod-highlighted:hover {
background-color: var(--jp-layout-color3);
}
.jp-mod-clicked {
background-color: var(--jp-brand-color1);
}
.jp-mod-clicked:hover {
background-color: var(--jp-brand-color0);
}
.jp-mod-clicked .jp-StatusBar-TextItem {
color: var(--jp-ui-inverse-font-color1);
}
.jp-StatusBar-HoverItem {
box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
}
.jp-StatusBar-TextItem {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
line-height: 24px;
color: var(--jp-ui-font-color1);
}
.jp-StatusBar-GroupItem {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-Statusbar-ProgressCircle svg {
display: block;
margin: 0 auto;
width: 16px;
height: 24px;
align-self: normal;
}
.jp-Statusbar-ProgressCircle path {
fill: var(--jp-inverse-layout-color3);
}
.jp-Statusbar-ProgressBar-progress-bar {
height: 10px;
width: 100px;
border: solid 0.25px var(--jp-brand-color2);
border-radius: 3px;
overflow: hidden;
align-self: center;
}
.jp-Statusbar-ProgressBar-progress-bar > div {
background-color: var(--jp-brand-color2);
background-image: linear-gradient(
-45deg,
rgba(255, 255, 255, 0.2) 25%,
transparent 25%,
transparent 50%,
rgba(255, 255, 255, 0.2) 50%,
rgba(255, 255, 255, 0.2) 75%,
transparent 75%,
transparent
);
background-size: 40px 40px;
float: left;
width: 0%;
height: 100%;
font-size: 12px;
line-height: 14px;
color: #fff;
text-align: center;
animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
}
.jp-Statusbar-ProgressBar-progress-bar p {
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
font-size: var(--jp-ui-font-size1);
line-height: 10px;
width: 100px;
}
@keyframes jp-Statusbar-ExecutionTime-progress-bar {
0% {
background-position: 0 0;
}
100% {
background-position: 40px 40px;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-commandpalette-search-height: 28px;
}
/*-----------------------------------------------------------------------------
| Overall styles
|----------------------------------------------------------------------------*/
.lm-CommandPalette {
padding-bottom: 0;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Modal variant
|----------------------------------------------------------------------------*/
.jp-ModalCommandPalette {
position: absolute;
z-index: 10000;
top: 38px;
left: 30%;
margin: 0;
padding: 4px;
width: 40%;
box-shadow: var(--jp-elevation-z4);
border-radius: 4px;
background: var(--jp-layout-color0);
}
.jp-ModalCommandPalette .lm-CommandPalette {
max-height: 40vh;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
margin-left: 4px;
margin-right: 4px;
}
.jp-ModalCommandPalette
.lm-CommandPalette
.lm-CommandPalette-item.lm-mod-disabled {
display: none;
}
/*-----------------------------------------------------------------------------
| Search
|----------------------------------------------------------------------------*/
.lm-CommandPalette-search {
padding: 4px;
background-color: var(--jp-layout-color1);
z-index: 2;
}
.lm-CommandPalette-wrapper {
overflow: overlay;
padding: 0 9px;
background-color: var(--jp-input-active-background);
height: 30px;
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
}
.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-SearchIconGroup {
color: white;
background-color: var(--jp-brand-color1);
position: absolute;
top: 4px;
right: 4px;
padding: 5px 5px 1px;
}
.jp-SearchIconGroup svg {
height: 20px;
width: 20px;
}
.jp-SearchIconGroup .jp-icon3[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-input {
background: transparent;
width: calc(100% - 18px);
float: left;
border: none;
outline: none;
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
line-height: var(--jp-private-commandpalette-search-height);
}
.lm-CommandPalette-input::-webkit-input-placeholder,
.lm-CommandPalette-input::-moz-placeholder,
.lm-CommandPalette-input:-ms-input-placeholder {
color: var(--jp-ui-font-color2);
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Results
|----------------------------------------------------------------------------*/
.lm-CommandPalette-header:first-child {
margin-top: 0;
}
.lm-CommandPalette-header {
border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
color: var(--jp-ui-font-color1);
cursor: pointer;
display: flex;
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin-top: 8px;
padding: 8px 0 8px 12px;
text-transform: uppercase;
}
.lm-CommandPalette-header.lm-mod-active {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-header > mark {
background-color: transparent;
font-weight: bold;
color: var(--jp-ui-font-color1);
}
.lm-CommandPalette-item {
padding: 4px 12px 4px 4px;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
font-weight: 400;
display: flex;
}
.lm-CommandPalette-item.lm-mod-disabled {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item.lm-mod-active {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-inverse-font-color0);
}
.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-itemContent {
overflow: hidden;
}
.lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.lm-CommandPalette-item.lm-mod-disabled mark {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
margin: 0 4px 0 0;
position: relative;
width: 16px;
top: 2px;
flex: 0 0 auto;
}
.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
opacity: 0.6;
}
.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
flex: 0 0 auto;
}
.lm-CommandPalette-itemCaption {
display: none;
}
.lm-CommandPalette-content {
background-color: var(--jp-layout-color1);
}
.lm-CommandPalette-content:empty::after {
content: 'No results';
margin: auto;
margin-top: 20px;
width: 100px;
display: block;
font-size: var(--jp-ui-font-size2);
font-family: var(--jp-ui-font-family);
font-weight: lighter;
}
.lm-CommandPalette-emptyMessage {
text-align: center;
margin-top: 24px;
line-height: 1.32;
padding: 0 8px;
color: var(--jp-content-font-color3);
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Dialog {
position: absolute;
z-index: 10000;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
top: 0;
left: 0;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
background: var(--jp-dialog-background);
}
.jp-Dialog-content {
display: flex;
flex-direction: column;
margin-left: auto;
margin-right: auto;
background: var(--jp-layout-color1);
padding: 24px 24px 12px;
min-width: 300px;
min-height: 150px;
max-width: 1000px;
max-height: 500px;
box-sizing: border-box;
box-shadow: var(--jp-elevation-z20);
word-wrap: break-word;
border-radius: var(--jp-border-radius);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color1);
resize: both;
}
.jp-Dialog-content.jp-Dialog-content-small {
max-width: 500px;
}
.jp-Dialog-button {
overflow: visible;
}
button.jp-Dialog-button:focus {
outline: 1px solid var(--jp-brand-color1);
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button:focus::-moz-focus-inner {
border: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
}
button.jp-Dialog-close-button {
padding: 0;
height: 100%;
min-width: unset;
min-height: unset;
}
.jp-Dialog-header {
display: flex;
justify-content: space-between;
flex: 0 0 auto;
padding-bottom: 12px;
font-size: var(--jp-ui-font-size3);
font-weight: 400;
color: var(--jp-ui-font-color1);
}
.jp-Dialog-body {
display: flex;
flex-direction: column;
flex: 1 1 auto;
font-size: var(--jp-ui-font-size1);
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
overflow: auto;
}
.jp-Dialog-footer {
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
flex: 0 0 auto;
margin-left: -12px;
margin-right: -12px;
padding: 12px;
}
.jp-Dialog-checkbox {
padding-right: 5px;
}
.jp-Dialog-checkbox > input:focus-visible {
outline: 1px solid var(--jp-input-active-border-color);
outline-offset: 1px;
}
.jp-Dialog-spacer {
flex: 1 1 auto;
}
.jp-Dialog-title {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.jp-Dialog-body > .jp-select-wrapper {
width: 100%;
}
.jp-Dialog-body > button {
padding: 0 16px;
}
.jp-Dialog-body > label {
line-height: 1.4;
color: var(--jp-ui-font-color0);
}
.jp-Dialog-button.jp-mod-styled:not(:last-child) {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Input-Boolean-Dialog {
flex-direction: row-reverse;
align-items: end;
width: 100%;
}
.jp-Input-Boolean-Dialog > label {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MainAreaWidget > :focus {
outline: none;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error {
padding: 6px;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
width: auto;
padding: 10px;
background: var(--jp-error-color3);
border: var(--jp-border-width) solid var(--jp-error-color1);
border-radius: var(--jp-border-radius);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
white-space: pre-wrap;
word-wrap: break-word;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/**
* google-material-color v1.2.6
* https://github.com/danlevan/google-material-color
*/
:root {
--md-red-50: #ffebee;
--md-red-100: #ffcdd2;
--md-red-200: #ef9a9a;
--md-red-300: #e57373;
--md-red-400: #ef5350;
--md-red-500: #f44336;
--md-red-600: #e53935;
--md-red-700: #d32f2f;
--md-red-800: #c62828;
--md-red-900: #b71c1c;
--md-red-A100: #ff8a80;
--md-red-A200: #ff5252;
--md-red-A400: #ff1744;
--md-red-A700: #d50000;
--md-pink-50: #fce4ec;
--md-pink-100: #f8bbd0;
--md-pink-200: #f48fb1;
--md-pink-300: #f06292;
--md-pink-400: #ec407a;
--md-pink-500: #e91e63;
--md-pink-600: #d81b60;
--md-pink-700: #c2185b;
--md-pink-800: #ad1457;
--md-pink-900: #880e4f;
--md-pink-A100: #ff80ab;
--md-pink-A200: #ff4081;
--md-pink-A400: #f50057;
--md-pink-A700: #c51162;
--md-purple-50: #f3e5f5;
--md-purple-100: #e1bee7;
--md-purple-200: #ce93d8;
--md-purple-300: #ba68c8;
--md-purple-400: #ab47bc;
--md-purple-500: #9c27b0;
--md-purple-600: #8e24aa;
--md-purple-700: #7b1fa2;
--md-purple-800: #6a1b9a;
--md-purple-900: #4a148c;
--md-purple-A100: #ea80fc;
--md-purple-A200: #e040fb;
--md-purple-A400: #d500f9;
--md-purple-A700: #a0f;
--md-deep-purple-50: #ede7f6;
--md-deep-purple-100: #d1c4e9;
--md-deep-purple-200: #b39ddb;
--md-deep-purple-300: #9575cd;
--md-deep-purple-400: #7e57c2;
--md-deep-purple-500: #673ab7;
--md-deep-purple-600: #5e35b1;
--md-deep-purple-700: #512da8;
--md-deep-purple-800: #4527a0;
--md-deep-purple-900: #311b92;
--md-deep-purple-A100: #b388ff;
--md-deep-purple-A200: #7c4dff;
--md-deep-purple-A400: #651fff;
--md-deep-purple-A700: #6200ea;
--md-indigo-50: #e8eaf6;
--md-indigo-100: #c5cae9;
--md-indigo-200: #9fa8da;
--md-indigo-300: #7986cb;
--md-indigo-400: #5c6bc0;
--md-indigo-500: #3f51b5;
--md-indigo-600: #3949ab;
--md-indigo-700: #303f9f;
--md-indigo-800: #283593;
--md-indigo-900: #1a237e;
--md-indigo-A100: #8c9eff;
--md-indigo-A200: #536dfe;
--md-indigo-A400: #3d5afe;
--md-indigo-A700: #304ffe;
--md-blue-50: #e3f2fd;
--md-blue-100: #bbdefb;
--md-blue-200: #90caf9;
--md-blue-300: #64b5f6;
--md-blue-400: #42a5f5;
--md-blue-500: #2196f3;
--md-blue-600: #1e88e5;
--md-blue-700: #1976d2;
--md-blue-800: #1565c0;
--md-blue-900: #0d47a1;
--md-blue-A100: #82b1ff;
--md-blue-A200: #448aff;
--md-blue-A400: #2979ff;
--md-blue-A700: #2962ff;
--md-light-blue-50: #e1f5fe;
--md-light-blue-100: #b3e5fc;
--md-light-blue-200: #81d4fa;
--md-light-blue-300: #4fc3f7;
--md-light-blue-400: #29b6f6;
--md-light-blue-500: #03a9f4;
--md-light-blue-600: #039be5;
--md-light-blue-700: #0288d1;
--md-light-blue-800: #0277bd;
--md-light-blue-900: #01579b;
--md-light-blue-A100: #80d8ff;
--md-light-blue-A200: #40c4ff;
--md-light-blue-A400: #00b0ff;
--md-light-blue-A700: #0091ea;
--md-cyan-50: #e0f7fa;
--md-cyan-100: #b2ebf2;
--md-cyan-200: #80deea;
--md-cyan-300: #4dd0e1;
--md-cyan-400: #26c6da;
--md-cyan-500: #00bcd4;
--md-cyan-600: #00acc1;
--md-cyan-700: #0097a7;
--md-cyan-800: #00838f;
--md-cyan-900: #006064;
--md-cyan-A100: #84ffff;
--md-cyan-A200: #18ffff;
--md-cyan-A400: #00e5ff;
--md-cyan-A700: #00b8d4;
--md-teal-50: #e0f2f1;
--md-teal-100: #b2dfdb;
--md-teal-200: #80cbc4;
--md-teal-300: #4db6ac;
--md-teal-400: #26a69a;
--md-teal-500: #009688;
--md-teal-600: #00897b;
--md-teal-700: #00796b;
--md-teal-800: #00695c;
--md-teal-900: #004d40;
--md-teal-A100: #a7ffeb;
--md-teal-A200: #64ffda;
--md-teal-A400: #1de9b6;
--md-teal-A700: #00bfa5;
--md-green-50: #e8f5e9;
--md-green-100: #c8e6c9;
--md-green-200: #a5d6a7;
--md-green-300: #81c784;
--md-green-400: #66bb6a;
--md-green-500: #4caf50;
--md-green-600: #43a047;
--md-green-700: #388e3c;
--md-green-800: #2e7d32;
--md-green-900: #1b5e20;
--md-green-A100: #b9f6ca;
--md-green-A200: #69f0ae;
--md-green-A400: #00e676;
--md-green-A700: #00c853;
--md-light-green-50: #f1f8e9;
--md-light-green-100: #dcedc8;
--md-light-green-200: #c5e1a5;
--md-light-green-300: #aed581;
--md-light-green-400: #9ccc65;
--md-light-green-500: #8bc34a;
--md-light-green-600: #7cb342;
--md-light-green-700: #689f38;
--md-light-green-800: #558b2f;
--md-light-green-900: #33691e;
--md-light-green-A100: #ccff90;
--md-light-green-A200: #b2ff59;
--md-light-green-A400: #76ff03;
--md-light-green-A700: #64dd17;
--md-lime-50: #f9fbe7;
--md-lime-100: #f0f4c3;
--md-lime-200: #e6ee9c;
--md-lime-300: #dce775;
--md-lime-400: #d4e157;
--md-lime-500: #cddc39;
--md-lime-600: #c0ca33;
--md-lime-700: #afb42b;
--md-lime-800: #9e9d24;
--md-lime-900: #827717;
--md-lime-A100: #f4ff81;
--md-lime-A200: #eeff41;
--md-lime-A400: #c6ff00;
--md-lime-A700: #aeea00;
--md-yellow-50: #fffde7;
--md-yellow-100: #fff9c4;
--md-yellow-200: #fff59d;
--md-yellow-300: #fff176;
--md-yellow-400: #ffee58;
--md-yellow-500: #ffeb3b;
--md-yellow-600: #fdd835;
--md-yellow-700: #fbc02d;
--md-yellow-800: #f9a825;
--md-yellow-900: #f57f17;
--md-yellow-A100: #ffff8d;
--md-yellow-A200: #ff0;
--md-yellow-A400: #ffea00;
--md-yellow-A700: #ffd600;
--md-amber-50: #fff8e1;
--md-amber-100: #ffecb3;
--md-amber-200: #ffe082;
--md-amber-300: #ffd54f;
--md-amber-400: #ffca28;
--md-amber-500: #ffc107;
--md-amber-600: #ffb300;
--md-amber-700: #ffa000;
--md-amber-800: #ff8f00;
--md-amber-900: #ff6f00;
--md-amber-A100: #ffe57f;
--md-amber-A200: #ffd740;
--md-amber-A400: #ffc400;
--md-amber-A700: #ffab00;
--md-orange-50: #fff3e0;
--md-orange-100: #ffe0b2;
--md-orange-200: #ffcc80;
--md-orange-300: #ffb74d;
--md-orange-400: #ffa726;
--md-orange-500: #ff9800;
--md-orange-600: #fb8c00;
--md-orange-700: #f57c00;
--md-orange-800: #ef6c00;
--md-orange-900: #e65100;
--md-orange-A100: #ffd180;
--md-orange-A200: #ffab40;
--md-orange-A400: #ff9100;
--md-orange-A700: #ff6d00;
--md-deep-orange-50: #fbe9e7;
--md-deep-orange-100: #ffccbc;
--md-deep-orange-200: #ffab91;
--md-deep-orange-300: #ff8a65;
--md-deep-orange-400: #ff7043;
--md-deep-orange-500: #ff5722;
--md-deep-orange-600: #f4511e;
--md-deep-orange-700: #e64a19;
--md-deep-orange-800: #d84315;
--md-deep-orange-900: #bf360c;
--md-deep-orange-A100: #ff9e80;
--md-deep-orange-A200: #ff6e40;
--md-deep-orange-A400: #ff3d00;
--md-deep-orange-A700: #dd2c00;
--md-brown-50: #efebe9;
--md-brown-100: #d7ccc8;
--md-brown-200: #bcaaa4;
--md-brown-300: #a1887f;
--md-brown-400: #8d6e63;
--md-brown-500: #795548;
--md-brown-600: #6d4c41;
--md-brown-700: #5d4037;
--md-brown-800: #4e342e;
--md-brown-900: #3e2723;
--md-grey-50: #fafafa;
--md-grey-100: #f5f5f5;
--md-grey-200: #eee;
--md-grey-300: #e0e0e0;
--md-grey-400: #bdbdbd;
--md-grey-500: #9e9e9e;
--md-grey-600: #757575;
--md-grey-700: #616161;
--md-grey-800: #424242;
--md-grey-900: #212121;
--md-blue-grey-50: #eceff1;
--md-blue-grey-100: #cfd8dc;
--md-blue-grey-200: #b0bec5;
--md-blue-grey-300: #90a4ae;
--md-blue-grey-400: #78909c;
--md-blue-grey-500: #607d8b;
--md-blue-grey-600: #546e7a;
--md-blue-grey-700: #455a64;
--md-blue-grey-800: #37474f;
--md-blue-grey-900: #263238;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| RenderedText
|----------------------------------------------------------------------------*/
:root {
/* This is the padding value to fill the gaps between lines containing spans with background color. */
--jp-private-code-span-padding: calc(
(var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
);
}
.jp-RenderedText {
text-align: left;
padding-left: var(--jp-code-padding);
line-height: var(--jp-code-line-height);
font-family: var(--jp-code-font-family);
}
.jp-RenderedText pre,
.jp-RenderedJavaScript pre,
.jp-RenderedHTMLCommon pre {
color: var(--jp-content-font-color1);
font-size: var(--jp-code-font-size);
border: none;
margin: 0;
padding: 0;
}
.jp-RenderedText pre a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* console foregrounds and backgrounds */
.jp-RenderedText pre .ansi-black-fg {
color: #3e424d;
}
.jp-RenderedText pre .ansi-red-fg {
color: #e75c58;
}
.jp-RenderedText pre .ansi-green-fg {
color: #00a250;
}
.jp-RenderedText pre .ansi-yellow-fg {
color: #ddb62b;
}
.jp-RenderedText pre .ansi-blue-fg {
color: #208ffb;
}
.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:-Solving-the-Kuramoto%E2%80%93Sivashinsky-Equation-with-Averaging-Neural-Operator">Tutorial: Solving the Kuramoto–Sivashinsky Equation with Averaging Neural Operator<a class="anchor-link" href="#Tutorial:-Solving-the-Kuramoto%E2%80%93Sivashinsky-Equation-with-Averaging-Neural-Operator"></a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial10/tutorial.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p>
<p>In this tutorial, we will build a Neural Operator using the <strong><code>AveragingNeuralOperator</code></strong> model and the <strong><code>SupervisedSolver</code></strong>. By the end of this tutorial, you will be able to train a Neural Operator to learn the operator for time-dependent PDEs.</p>
<p>Let's start by importing the necessary modules.</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[tutorial]"</span>
<span class="c1"># get the data</span>
<span class="o">!</span>mkdir<span class="w"> </span><span class="s2">"data"</span>
<span class="o">!</span>wget<span class="w"> </span><span class="s2">"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS.mat"</span><span class="w"> </span>-O<span class="w"> </span><span class="s2">"data/Data_KS.mat"</span>
<span class="o">!</span>wget<span class="w"> </span><span class="s2">"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS2.mat"</span><span class="w"> </span>-O<span class="w"> </span><span class="s2">"data/Data_KS2.mat"</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">scipy</span><span class="w"> </span><span class="kn">import</span> <span class="n">io</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">Trainer</span><span class="p">,</span> <span class="n">LabelTensor</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">AveragingNeuralOperator</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">SupervisedSolver</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">SupervisedProblem</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="Data-Generation">Data Generation<a class="anchor-link" href="#Data-Generation"></a></h2><p>In this tutorial, we will focus on solving the <strong>Kuramoto-Sivashinsky (KS)</strong> equation, a fourth-order nonlinear PDE. The equation is given by:</p>
<p>$$
\frac{\partial u}{\partial t}(x,t) = -u(x,t)\frac{\partial u}{\partial x}(x,t) - \frac{\partial^{4}u}{\partial x^{4}}(x,t) - \frac{\partial^{2}u}{\partial x^{2}}(x,t).
$$</p>
<p>In this equation, $x \in \Omega = [0, 64]$ represents a spatial location, and $t \in \mathbb{T} = [0, 50]$ represents time. The function $u(x, t)$ is the value of the function at each point in space and time, with $u(x, t) \in \mathbb{R}$. We denote the solution space as $\mathbb{U}$, where $u \in \mathbb{U}$.</p>
<p>We impose Dirichlet boundary conditions on the derivative of $u$ at the boundary of the domain $\partial \Omega$:</p>
<p>$$
\frac{\partial u}{\partial x}(x,t) = 0 \quad \forall (x,t) \in \partial \Omega \times \mathbb{T}.
$$</p>
<p>The initial conditions are sampled from a distribution over truncated Fourier series with random coefficients $\{A_k, \ell_k, \phi_k\}_k$, as follows:</p>
<p>$$
u(x,0) = \sum_{k=1}^N A_k \sin\left(2 \pi \frac{\ell_k x}{L} + \phi_k\right),
$$</p>
<p>where:</p>
<ul>
<li>$A_k \in [-0.4, -0.3]$,</li>
<li>$\ell_k = 2$,</li>
<li>$\phi_k = 2\pi \quad \forall k=1,\dots,N$.</li>
</ul>
<p>We have already generated data for different initial conditions. The goal is to build a Neural Operator that, given $u(x,t)$, outputs $u(x,t+\delta)$, where $\delta$ is a fixed time step.</p>
<p>We will cover the Neural Operator architecture later, but for now, let’s start by importing the data.</p>
<p><strong>Note:</strong>
The numerical integration is obtained using a pseudospectral method for spatial derivative discretization and implicit Runge-Kutta 5 for temporal dynamics.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># load data</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">loadmat</span><span class="p">(</span><span class="s2">"data/Data_KS.mat"</span><span class="p">)</span>
<span class="c1"># converting to label tensor</span>
<span class="n">initial_cond_train</span> <span class="o">=</span> <span class="n">LabelTensor</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="n">data</span><span class="p">[</span><span class="s2">"initial_cond_train"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span>
<span class="p">[</span><span class="s2">"t"</span><span class="p">,</span> <span class="s2">"x"</span><span class="p">,</span> <span class="s2">"u0"</span><span class="p">],</span>
<span class="p">)</span>
<span class="n">initial_cond_test</span> <span class="o">=</span> <span class="n">LabelTensor</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="n">data</span><span class="p">[</span><span class="s2">"initial_cond_test"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"t"</span><span class="p">,</span> <span class="s2">"x"</span><span class="p">,</span> <span class="s2">"u0"</span><span class="p">]</span>
<span class="p">)</span>
<span class="n">sol_train</span> <span class="o">=</span> <span class="n">LabelTensor</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="n">data</span><span class="p">[</span><span class="s2">"sol_train"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"u"</span><span class="p">]</span>
<span class="p">)</span>
<span class="n">sol_test</span> <span class="o">=</span> <span class="n">LabelTensor</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="n">data</span><span class="p">[</span><span class="s2">"sol_test"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"u"</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Data Loaded"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" shape initial condition: </span><span class="si">{</span><span class="n">initial_cond_train</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" shape solution: </span><span class="si">{</span><span class="n">sol_train</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Data Loaded
shape initial condition: torch.Size([100, 12800, 3])
shape solution: torch.Size([100, 12800, 1])
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<p>The data is saved in the form <code>[B, N, D]</code>, where:</p>
<ul>
<li><code>B</code> is the batch size (i.e., how many initial conditions we sample),</li>
<li><code>N</code> is the number of points in the mesh (which is the product of the discretization in $x$ times the one in $t$),</li>
<li><code>D</code> is the dimension of the problem (in this case, we have three variables: $[u, t, x]$).</li>
</ul>
<p>We are now going to plot some trajectories!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># helper function</span>
<span class="k">def</span><span class="w"> </span><span class="nf">plot_trajectory</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="n">real</span><span class="p">,</span> <span class="n">no_sol</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="c1"># find the x-t shapes</span>
<span class="n">dim_x</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">coords</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">dim_t</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">coords</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)))</span>
<span class="c1"># if we don't have the Neural Operator solution we simply plot the real one</span>
<span class="k">if</span> <span class="n">no_sol</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">5</span><span class="p">),</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">axs</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">real</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Real solution"</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">c</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">axs</span><span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)</span>
<span class="c1"># otherwise we plot the real one, the Neural Operator one, and their difference</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">5</span><span class="p">),</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">real</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Real solution"</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">no_sol</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"NO solution"</span><span class="p">)</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="p">(</span><span class="n">real</span> <span class="o">-</span> <span class="n">no_sol</span><span class="p">)</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Absolute difference"</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">c</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">axs</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
<span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">axs</span><span class="p">:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="c1"># a sample trajectory (we use the sample 5, feel free to change)</span>
<span class="n">sample_number</span> <span class="o">=</span> <span class="mi">20</span>
<span class="n">plot_trajectory</span><span class="p">(</span>
<span class="n">coords</span><span class="o">=</span><span class="n">initial_cond_train</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</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="s2">"t"</span><span class="p">]),</span>
<span class="n">real</span><span class="o">=</span><span class="n">sol_train</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span>
<span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
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"/>
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<p>As we can see, as time progresses, the solution becomes chaotic, making it very difficult to learn! We will now focus on building a Neural Operator using the <code>SupervisedSolver</code> class to tackle this problem.</p>
<h2 id="Averaging-Neural-Operator">Averaging Neural Operator<a class="anchor-link" href="#Averaging-Neural-Operator"></a></h2><p>We will build a neural operator $\texttt{NO}$, which takes the solution at time $t=0$ for any $x\in\Omega$, the time $t$ at which we want to compute the solution, and gives back the solution to the KS equation $u(x, t)$. Mathematically:</p>
<p>$$
\texttt{NO}_\theta : \mathbb{U} \rightarrow \mathbb{U},
$$</p>
<p>such that</p>
<p>$$
\texttt{NO}_\theta[u(t=0)](x, t) \rightarrow u(x, t).
$$</p>
<p>There are many ways to approximate the following operator, for example, by using a 2D <a href="https://mathlab.github.io/PINA/_rst/model/fourier_neural_operator.html">FNO</a> (for regular meshes), a <a href="https://mathlab.github.io/PINA/_rst/model/deeponet.html">DeepOnet</a>, <a href="https://mathlab.github.io/PINA/_rst/model/block/convolution.html">Continuous Convolutional Neural Operator</a>, or <a href="https://mathlab.github.io/PINA/_rst/model/mionet.html">MIONet</a>. In this tutorial, we will use the <em>Averaging Neural Operator</em> presented in <a href="https://arxiv.org/abs/2304.13221"><em>The Nonlocal Neural Operator: Universal Approximation</em></a>, which is a <a href="https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html">Kernel Neural Operator</a> with an integral kernel:</p>
<p>$$
K(v) = \sigma\left(Wv(x) + b + \frac{1}{|\Omega|}\int_\Omega v(y)dy\right)
$$</p>
<p>where:</p>
<ul>
<li>$v(x) \in \mathbb{R}^{\rm{emb}}$ is the update for a function $v$, with $\mathbb{R}^{\rm{emb}}$ being the embedding (hidden) size.</li>
<li>$\sigma$ is a non-linear activation function.</li>
<li>$W \in \mathbb{R}^{\rm{emb} \times \rm{emb}}$ is a tunable matrix.</li>
<li>$b \in \mathbb{R}^{\rm{emb}}$ is a tunable bias.</li>
</ul>
<p>In PINA, many Kernel Neural Operators are already implemented. The modular components of the <a href="https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html">Kernel Neural Operator</a> class allow you to create new ones by composing base kernel layers.</p>
<p><strong>Note:</strong> We will use the already built class <code>AveragingNeuralOperator</code>. As a constructive exercise, try to use the <a href="https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html">KernelNeuralOperator</a> class to build a kernel neural operator from scratch. You might employ the different layers that we have in PINA, such as <a href="https://mathlab.github.io/PINA/_rst/model/feed_forward.html">FeedForward</a> and <a href="https://mathlab.github.io/PINA/_rst/model/average_neural_operator.html">AveragingNeuralOperator</a> layers.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="k">class</span><span class="w"> </span><span class="nc">SIREN</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="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="k">return</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="p">)</span>
<span class="n">embedding_dimesion</span> <span class="o">=</span> <span class="mi">40</span> <span class="c1"># hyperparameter embedding dimension</span>
<span class="n">input_dimension</span> <span class="o">=</span> <span class="mi">3</span> <span class="c1"># ['u', 'x', 't']</span>
<span class="n">number_of_coordinates</span> <span class="o">=</span> <span class="mi">2</span> <span class="c1"># ['x', 't']</span>
<span class="n">lifting_net</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">Linear</span><span class="p">(</span><span class="n">input_dimension</span><span class="p">,</span> <span class="n">embedding_dimesion</span><span class="p">)</span>
<span class="n">projecting_net</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">Linear</span><span class="p">(</span><span class="n">embedding_dimesion</span> <span class="o">+</span> <span class="n">number_of_coordinates</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">AveragingNeuralOperator</span><span class="p">(</span>
<span class="n">lifting_net</span><span class="o">=</span><span class="n">lifting_net</span><span class="p">,</span>
<span class="n">projecting_net</span><span class="o">=</span><span class="n">projecting_net</span><span class="p">,</span>
<span class="n">coordinates_indices</span><span class="o">=</span><span class="p">[</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">],</span>
<span class="n">field_indices</span><span class="o">=</span><span class="p">[</span><span class="s2">"u0"</span><span class="p">],</span>
<span class="n">n_layers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
<span class="n">func</span><span class="o">=</span><span class="n">SIREN</span><span class="p">,</span>
<span class="p">)</span>
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<p>Super easy! Notice that we use the <code>SIREN</code> activation function, which is discussed in more detail in the paper <a href="https://arxiv.org/abs/2006.09661">Implicit Neural Representations with Periodic Activation Functions</a>.</p>
<h2 id="Solving-the-KS-problem">Solving the KS problem<a class="anchor-link" href="#Solving-the-KS-problem"></a></h2><p>We will now focus on solving the KS equation using the <code>SupervisedSolver</code> class and the <code>AveragingNeuralOperator</code> model. As done in the <a href="https://github.com/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb">FNO tutorial</a>, we now create the Neural Operator problem class with <code>SupervisedProblem</code>.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># initialize problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">SupervisedProblem</span><span class="p">(</span>
<span class="n">initial_cond_train</span><span class="p">,</span>
<span class="n">sol_train</span><span class="p">,</span>
<span class="n">input_variables</span><span class="o">=</span><span class="n">initial_cond_train</span><span class="o">.</span><span class="n">labels</span><span class="p">,</span>
<span class="n">output_variables</span><span class="o">=</span><span class="n">sol_train</span><span class="o">.</span><span class="n">labels</span><span class="p">,</span>
<span class="p">)</span>
<span class="c1"># initialize solver</span>
<span class="n">solver</span> <span class="o">=</span> <span class="n">SupervisedSolver</span><span class="p">(</span><span class="n">problem</span><span class="o">=</span><span class="n">problem</span><span class="p">,</span> <span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">)</span>
<span class="c1"># train, only CPU and avoid model summary at beginning of training (optional)</span>
<span class="n">trainer</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">solver</span><span class="p">,</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="c1"># we train on CPU and avoid model summary at beginning of training (optional)</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>You are using the plain ModelCheckpoint callback. Consider using LitModelCheckpoint which with seamless uploading to Model registry.
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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=40` reached.
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<p>We can now visualize some plots for the solutions!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">sample_number</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">no_sol</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_test</span><span class="p">)</span>
<span class="n">plot_trajectory</span><span class="p">(</span>
<span class="n">coords</span><span class="o">=</span><span class="n">initial_cond_test</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</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="s2">"t"</span><span class="p">]),</span>
<span class="n">real</span><span class="o">=</span><span class="n">sol_test</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span>
<span class="n">no_sol</span><span class="o">=</span><span class="n">no_sol</span><span class="p">[</span><span class="mi">5</span><span class="p">],</span>
<span class="p">)</span>
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"/>
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<p>As we can see, we can obtain nice results considering the small training time and the difficulty of the problem!
Let's take a look at the training and testing error:</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="kn">from</span><span class="w"> </span><span class="nn">pina.loss</span><span class="w"> </span><span class="kn">import</span> <span class="n">PowerLoss</span>
<span class="n">error_metric</span> <span class="o">=</span> <span class="n">PowerLoss</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="c1"># we use the MSE loss</span>
<span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
<span class="n">no_sol_train</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_train</span><span class="p">)</span>
<span class="n">err_train</span> <span class="o">=</span> <span class="n">error_metric</span><span class="p">(</span>
<span class="n">sol_train</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span> <span class="n">no_sol_train</span>
<span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="c1"># we average the error over trajectories</span>
<span class="n">no_sol_test</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_test</span><span class="p">)</span>
<span class="n">err_test</span> <span class="o">=</span> <span class="n">error_metric</span><span class="p">(</span>
<span class="n">sol_test</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span> <span class="n">no_sol_test</span>
<span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="c1"># we average the error over trajectories</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Training error: </span><span class="si">{</span><span class="nb">float</span><span class="p">(</span><span class="n">err_train</span><span class="p">)</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Testing error: </span><span class="si">{</span><span class="nb">float</span><span class="p">(</span><span class="n">err_test</span><span class="p">)</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Training error: 0.077
Testing error: 0.065
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<p>As we can see, the error is pretty small, which aligns with the observations from the previous plots.</p>
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<h2 id="What's-Next?">What's Next?<a class="anchor-link" href="#What's-Next?"></a></h2><p>You have completed the tutorial on solving time-dependent PDEs using Neural Operators in <strong>PINA</strong>. Great job! Here are some potential next steps you can explore:</p>
<ol>
<li><p><strong>Train the network for longer or with different layer sizes</strong>: Experiment with various configurations, such as adjusting the number of layers or hidden dimensions, to further improve accuracy and observe the impact on performance.</p>
</li>
<li><p><strong>Use a more challenging dataset</strong>: Try using the more complex dataset <a href="dat/Data_KS2.mat">Data_KS2.mat</a> where $A_k \in [-0.5, 0.5]$, $\ell_k \in [1, 2, 3]$, and $\phi_k \in [0, 2\pi]$ for a more difficult task. This dataset may require longer training and testing.</p>
</li>
<li><p><strong>... and many more...</strong>: Explore other models, such as the <a href="https://mathlab.github.io/PINA/_rst/models/fno.html">FNO</a>, <a href="https://mathlab.github.io/PINA/_rst/models/deeponet.html">DeepOnet</a>, or implement your own operator using the <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">KernelNeuralOperator</a> class to compare performance and find the best model for your task.</p>
</li>
</ol>
<p>For more resources and tutorials, check out the <a href="https://mathlab.github.io/PINA/">PINA Documentation</a>.</p>
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