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PINA/docs/source/tutorials/tutorial10/tutorial.html
github-actions[bot] 4357f8681f export tutorials changed in 5aec5f5 (#540)
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This file contains invisible Unicode characters
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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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/* Icons urls */
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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:-Averaging-Neural-Operator-for-solving-Kuramoto-Sivashinsky-equation">Tutorial: Averaging Neural Operator for solving Kuramoto Sivashinsky equation<a class="anchor-link" href="#Tutorial:-Averaging-Neural-Operator-for-solving-Kuramoto-Sivashinsky-equation"></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
<code>AveragingNeuralOperator</code> model and the <code>SupervisedSolver</code>. At the end of the
tutorial you will be able to train a Neural Operator for learning
the operator of time dependent PDEs.</p>
<p>First of all, some useful imports. Note we use <code>scipy</code> for i/o operations.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab"</span>
<span class="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">Condition</span><span class="p">,</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>We will focus on solving a specific PDE, the <strong>Kuramoto Sivashinsky</strong> (KS) equation.
The KS PDE is a fourth-order nonlinear PDE with the following form:</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 the above $x\in \Omega=[0, 64]$ represents a spatial location, $t\in\mathbb{T}=[0,50]$ the time and $u(x, t)$ is the value of the function $u:\Omega \times\mathbb{T}\in\mathbb{R}$. We indicate with $\mathbb{U}$ a suitable space for $u$, i.e. we have that the solution $u\in\mathbb{U}$.</p>
<p>We impose Dirichlet boundary conditions on the derivative of $u$ on the border of the domain $\partial \Omega$
$$
\frac{\partial u}{\partial x}(x,t)=0 \quad \forall (x,t)\in \partial \Omega\times\mathbb{T}.
$$</p>
<p>Initial conditions are sampled from a distribution over truncated Fourier series with random coefficients
$\{A_k, \ell_k, \phi_k\}_k$ as
$$
u(x,0) = \sum_{k=1}^N A_k \sin(2 \pi \ell_k x / L + \phi_k) \ ,
$$</p>
<p>where $A_k \in [-0.4, -0.3]$, $\ell_k = 2$, $\phi_k = 2\pi \quad \forall k=1,\dots,N$.</p>
<p>We have already generated some data for differenti initial conditions, and our objective will
be to build a Neural Operator that, given $u(x, t)$ will output $u(x, t+\delta)$, where
$\delta$ is a fixed time step. We will come back on the Neural Operator architecture, for now
we first need to import the data.</p>
<p><strong>Note:</strong>
<em>The numerical integration is obtained by using pseudospectral method for spatial derivative discratization and
implicit Runge Kutta 5 for temporal dynamics.</em></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 are saved in the form <code>B \times N \times D</code>, where <code>B</code> is the batch_size
(basically how many initial conditions we sample), <code>N</code> the number of points in the mesh
(which is the product of the discretization in <code>x</code> timese the one in <code>t</code>), and
<code>D</code> the dimension of the problem (in this case we have three variables <code>[u, t, x]</code>).</p>
<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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+8+LF++vIUzExEREREREZFukuoVKACwdu1anH/++TjllFNw6qmn4vrrr0epVMKFF17Y6qmJiIiIiIiISJdI/Q2Ud77znXj++edx1VVXYdu2bTjppJNw9913v+jBsvtSKBRw9dVX7zXWI9IptJ9LN9B+Lt1A+7l0A+3n0g20n3emIO6WukoiIiIiIiIiInOU6megiIiIiIiIiIikgW6giIiIiIiIiIgYdANFRERERERERMSgGygiIiIiIiIiIoaOvoGyfv16HHnkkSgWizjttNPwgx/8oNVTEmnKgw8+iLe+9a047LDDEAQB7rrrrhk/j+MYV111FQ499FD09PRg5cqVeOqpp1ozWZE5WLduHV7zmtdgYGAACxcuxLnnnotNmzbNaFMul7FmzRocfPDB6O/vx+rVq7F9+/YWzVhk/91www044YQTMDg4iMHBQSxfvhz//u//Pv1z7ePSiT71qU8hCAJcdtll09/Tvi7t7pprrkEQBDO+jjvuuOmfax/vPB17A+XLX/4y1q5di6uvvho//OEPceKJJ+Kcc87Bjh07Wj01kTkrlUo48cQTsX79+r3+/DOf+Qy+8IUv4MYbb8T3v/999PX14ZxzzkG5XE54piJz88ADD2DNmjV4+OGHce+996JWq+H3fu/3UCqVpttcfvnl+Nd//VfccccdeOCBB/Dcc8/hvPPOa+GsRfbP4Ycfjk996lPYuHEjHn30UZx11ll429vehp/85CcAtI9L53nkkUdw00034YQTTpjxfe3r0gl+53d+B1u3bp3++u53vzv9M+3jHSjuUKeeemq8Zs2a6f9uNBrxYYcdFq9bt66FsxLxAyC+8847p/87iqJ48eLF8Wc/+9np7w0PD8eFQiH+l3/5lxbMUKR5O3bsiAHEDzzwQBzHU/t0LpeL77jjjuk2P/3pT2MA8UMPPdSqaYo07aCDDor/4R/+Qfu4dJyxsbH4mGOOie+99974jW98Y/yhD30ojmMdz6UzXH311fGJJ564159pH+9MHbkCpVqtYuPGjVi5cuX098IwxMqVK/HQQw+1cGYiB84zzzyDbdu2zdjvh4aGcNppp2m/l7Y1MjICAJg/fz4AYOPGjajVajP28+OOOw5Lly7Vfi5tqdFo4Etf+hJKpRKWL1+ufVw6zpo1a/D7v//7M/ZpQMdz6RxPPfUUDjvsMBx11FF497vfjc2bNwPQPt6psq2ewIGwc+dONBoNLFq0aMb3Fy1ahCeffLJFsxI5sLZt2wYAe93vX/iZSDuJogiXXXYZTj/9dLziFa8AMLWf5/N5zJs3b0Zb7efSbn784x9j+fLlKJfL6O/vx5133onjjz8ejz32mPZx6Rhf+tKX8MMf/hCPPPLIi36m47l0gtNOOw0bNmzAsccei61bt+Laa6/F61//ejz++OPaxztUR95AERGR9rdmzRo8/vjjM7LEIp3i2GOPxWOPPYaRkRF89atfxfnnn48HHnig1dMScbNlyxZ86EMfwr333otisdjq6YgcEKtWrZr+/yeccAJOO+00HHHEEfjKV76Cnp6eFs5MDpSOjPAccsghyGQyL3rC8fbt27F48eIWzUrkwHph39Z+L53gkksuwTe+8Q185zvfweGHHz79/cWLF6NarWJ4eHhGe+3n0m7y+TyOPvponHzyyVi3bh1OPPFE/M3f/I32cekYGzduxI4dO/DqV78a2WwW2WwWDzzwAL7whS8gm81i0aJF2tel48ybNw8ve9nL8PTTT+t43qE68gZKPp/HySefjPvuu2/6e1EU4b777sPy5ctbODORA2fZsmVYvHjxjP1+dHQU3//+97XfS9uI4xiXXHIJ7rzzTnz729/GsmXLZvz85JNPRi6Xm7Gfb9q0CZs3b9Z+Lm0tiiJUKhXt49Ixfvd3fxc//vGP8dhjj01/nXLKKXj3u989/f+1r0unGR8fx89//nMceuihOp53qI6N8Kxduxbnn38+TjnlFJx66qm4/vrrUSqVcOGFF7Z6aiJzNj4+jqeffnr6v5955hk89thjmD9/PpYuXYrLLrsMn/zkJ3HMMcdg2bJl+PjHP47DDjsM5557busmLbIf1qxZg9tvvx1f+9rXMDAwMJ0RHhoaQk9PD4aGhnDRRRdh7dq1mD9/PgYHB3HppZdi+fLleO1rX9vi2YtwrrzySqxatQpLly7F2NgYbr/9dtx///245557tI9LxxgYGJh+ftUL+vr6cPDBB09/X/u6tLsPf/jDeOtb34ojjjgCzz33HK6++mpkMhm8613v0vG8Q3XsDZR3vvOdeP7553HVVVdh27ZtOOmkk3D33Xe/6AGbIu3k0UcfxZlnnjn932vXrgUAnH/++diwYQM++tGPolQq4f3vfz+Gh4dxxhln4O6771b2WNrGDTfcAABYsWLFjO/feuutuOCCCwAA1113HcIwxOrVq1GpVHDOOefgi1/8YsIzFZm7HTt24D3veQ+2bt2KoaEhnHDCCbjnnntw9tlnA9A+Lt1D+7q0u1/96ld417vehV27dmHBggU444wz8PDDD2PBggUAtI93oiCO47jVkxARERERERERSbOOfAaKiIiIiIiIiIgn3UARERERERERETHoBoqIiIiIiIiIiEE3UEREREREREREDLqBIiIiIiIiIiJi0A0UERERERERERGDbqCIiIiIiIiIiBh0A0VERERERERExKAbKCIiIiIiIiIiBt1AERERkb1asWIFLrvsslZPQ0RERCQVdANFRERERERERMQQxHEct3oSIiIiki4XXHABbrvtthnfe+aZZ3DkkUe2ZkIiIiIiLaYbKCIiIvIiIyMjWLVqFV7xilfgE5/4BABgwYIFyGQyLZ6ZiIiISGtkWz0BERERSZ+hoSHk83n09vZi8eLFrZ6OiIiISMvpGSgiIiIiIiIiIgbdQBERERERERERMegGioiIiOxVPp9Ho9Fo9TREREREUkE3UERERGSvjjzySHz/+9/HL3/5S+zcuRNRFLV6SiIiIiItoxsoIiIislcf/vCHkclkcPzxx2PBggXYvHlzq6ckIiIi0jIqYywiIiIiIiIiYtAKFBERERERERERg26giIiIiIiIiIgYdANFRERERERERMSgGygiIiIiIiIiIgbdQBERERERERERMegGioiIiIiIiIiIQTdQREREREREREQMuoEiIiIiIiIiImLQDRQREREREREREYNuoIiIiIiIiIiIGHQDRURERERERETE8P8DodxJcDPHK18AAAAASUVORK5CYII="/>
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<p>As we can see, as the time progresses the solution becomes chaotic, which makes
it really hard to learn! We will now focus on building a Neural Operator using the
<code>SupervisedSolver</code> class to tackle the 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:
$$
\texttt{NO}_\theta : \mathbb{U} \rightarrow \mathbb{U},
$$
such that
$$
\texttt{NO}_\theta[u(t=0)](x, t) \rightarrow u(x, t).
$$</p>
<p>There are many ways on approximating the following operator, e.g. by 2D <a href="https://mathlab.github.io/PINA/_rst/models/fno.html">FNO</a> (for regular meshes),
a <a href="https://mathlab.github.io/PINA/_rst/models/deeponet.html">DeepOnet</a>, <a href="https://mathlab.github.io/PINA/_rst/layers/convolution.html">Continuous Convolutional Neural Operator</a>,
<a href="https://mathlab.github.io/PINA/_rst/models/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/models/base_no.html">Kernel Neural Operator</a> with 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 $\mathbb{R}^{\rm{emb}}$ the embedding (hidden) size</li>
<li>$\sigma$ is a non-linear activation</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>If PINA many Kernel Neural Operators are already implemented, and the modular componets of the <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">Kernel Neural Operator</a> class permits to create new ones by composing base kernel layers.</p>
<p>**Note:*** We will use the already built class* <code>AveragingNeuralOperator</code>, <em>as constructive excercise try to use the</em> <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">KernelNeuralOperator</a> <em>class for building a kernel neural operator from scratch. You might employ the different layers that we have in pina, e.g.</em> <a href="https://mathlab.github.io/PINA/_rst/models/fnn.html">FeedForward</a>, <em>and</em> <a href="https://mathlab.github.io/PINA/_rst/layers/avno_layer.html">AveragingNeuralOperator</a> <em>layers</em>.</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, more on <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>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>Missing logger folder: /home/runner/work/PINA/PINA/tutorials/tutorial10/lightning_logs
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<pre>`Trainer.fit` stopped: `max_epochs=40` reached.
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<p>We can now see 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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<p>As we can see we can obtain nice result 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: 0.164
Testing error: 0.158
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<p>As we can see the error is pretty small, which agrees with what we can see 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>Now you know how to solve a time dependent neural operator problem in <strong>PINA</strong>! There are multiple directions you can go now:</p>
<ol>
<li><p>Train the network for longer or with different layer sizes and assert the final accuracy</p>
</li>
<li><p>We left a more challenging dataset <a href="dat/Data_KS2.mat">Data_KS2.mat</a> where $A_k \in [-0.5, 0.5]$, $\ell_k \in [1, 2, 3]$, $\phi_k \in [0, 2\pi]$ for longer training</p>
</li>
<li><p>Compare the performance between the different neural operators (you can even try to implement your favourite one!)</p>
</li>
</ol>
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