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PINA/docs/source/tutorials/tutorial15/tutorial.html
github-actions[bot] d10c525e74 export tutorials changed in dd88513 (#559) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-04-23 18:53:30 +02:00

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<title>tutorial</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script><script>
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--jp-icon-add-above: url(data:image/svg+xml;base64,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);
--jp-icon-add-below: url(data:image/svg+xml;base64,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);
--jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-bell: url(data:image/svg+xml;base64,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);
--jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
--jp-icon-bug: url(data:image/svg+xml;base64,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);
--jp-icon-build: url(data:image/svg+xml;base64,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);
--jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
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--jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-regex: url(data:image/svg+xml;base64,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);
--jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-toc: url(data:image/svg+xml;base64,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);
--jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
--jp-icon-trusted: url(data:image/svg+xml;base64,PHN2ZyBmaWxsPSJub25lIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI1Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgc3Ryb2tlPSIjMzMzMzMzIiBzdHJva2Utd2lkdGg9IjIiIHRyYW5zZm9ybT0idHJhbnNsYXRlKDIgMykiIGQ9Ik0xLjg2MDk0IDExLjQ0MDlDMC44MjY0NDggOC43NzAyNyAwLjg2Mzc3OSA2LjA1NzY0IDEuMjQ5MDcgNC4xOTkzMkMyLjQ4MjA2IDMuOTMzNDcgNC4wODA2OCAzLjQwMzQ3IDUuNjAxMDIgMi44NDQ5QzcuMjM1NDkgMi4yNDQ0IDguODU2NjYgMS41ODE1IDkuOTg3NiAxLjA5NTM5QzExLjA1OTcgMS41ODM0MSAxMi42MDk0IDIuMjQ0NCAxNC4yMTggMi44NDMzOUMxNS43NTAzIDMuNDEzOTQgMTcuMzk5NSAzLjk1MjU4IDE4Ljc1MzkgNC4yMTM4NUMxOS4xMzY0IDYuMDcxNzcgMTkuMTcwOSA4Ljc3NzIyIDE4LjEzOSAxMS40NDA5QzE3LjAzMDMgMTQuMzAzMiAxNC42NjY4IDE3LjE4NDQgOS45OTk5OSAxOC45MzU0QzUuMzMzMiAxNy4xODQ0IDIuOTY5NjggMTQuMzAzMiAxLjg2MDk0IDExLjQ0MDlaIi8+CiAgICA8cGF0aCBjbGFzcz0ianAtaWNvbjIiIGZpbGw9IiMzMzMzMzMiIHN0cm9rZT0iIzMzMzMzMyIgdHJhbnNmb3JtPSJ0cmFuc2xhdGUoOCA5Ljg2NzE5KSIgZD0iTTIuODYwMTUgNC44NjUzNUwwLjcyNjU0OSAyLjk5OTU5TDAgMy42MzA0NUwyLjg2MDE1IDYuMTMxNTdMOCAwLjYzMDg3Mkw3LjI3ODU3IDBMMi44NjAxNSA0Ljg2NTM1WiIvPgo8L3N2Zz4K);
--jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-users: url(data:image/svg+xml;base64,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);
--jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-word: url(data:image/svg+xml;base64,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);
--jp-icon-yaml: url(data:image/svg+xml;base64,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);
}
/* Icon CSS class declarations */
.jp-AddAboveIcon {
background-image: var(--jp-icon-add-above);
}
.jp-AddBelowIcon {
background-image: var(--jp-icon-add-below);
}
.jp-AddIcon {
background-image: var(--jp-icon-add);
}
.jp-BellIcon {
background-image: var(--jp-icon-bell);
}
.jp-BugDotIcon {
background-image: var(--jp-icon-bug-dot);
}
.jp-BugIcon {
background-image: var(--jp-icon-bug);
}
.jp-BuildIcon {
background-image: var(--jp-icon-build);
}
.jp-CaretDownEmptyIcon {
background-image: var(--jp-icon-caret-down-empty);
}
.jp-CaretDownEmptyThinIcon {
background-image: var(--jp-icon-caret-down-empty-thin);
}
.jp-CaretDownIcon {
background-image: var(--jp-icon-caret-down);
}
.jp-CaretLeftIcon {
background-image: var(--jp-icon-caret-left);
}
.jp-CaretRightIcon {
background-image: var(--jp-icon-caret-right);
}
.jp-CaretUpEmptyThinIcon {
background-image: var(--jp-icon-caret-up-empty-thin);
}
.jp-CaretUpIcon {
background-image: var(--jp-icon-caret-up);
}
.jp-CaseSensitiveIcon {
background-image: var(--jp-icon-case-sensitive);
}
.jp-CheckIcon {
background-image: var(--jp-icon-check);
}
.jp-CircleEmptyIcon {
background-image: var(--jp-icon-circle-empty);
}
.jp-CircleIcon {
background-image: var(--jp-icon-circle);
}
.jp-ClearIcon {
background-image: var(--jp-icon-clear);
}
.jp-CloseIcon {
background-image: var(--jp-icon-close);
}
.jp-CodeCheckIcon {
background-image: var(--jp-icon-code-check);
}
.jp-CodeIcon {
background-image: var(--jp-icon-code);
}
.jp-CollapseAllIcon {
background-image: var(--jp-icon-collapse-all);
}
.jp-ConsoleIcon {
background-image: var(--jp-icon-console);
}
.jp-CopyIcon {
background-image: var(--jp-icon-copy);
}
.jp-CopyrightIcon {
background-image: var(--jp-icon-copyright);
}
.jp-CutIcon {
background-image: var(--jp-icon-cut);
}
.jp-DeleteIcon {
background-image: var(--jp-icon-delete);
}
.jp-DownloadIcon {
background-image: var(--jp-icon-download);
}
.jp-DuplicateIcon {
background-image: var(--jp-icon-duplicate);
}
.jp-EditIcon {
background-image: var(--jp-icon-edit);
}
.jp-EllipsesIcon {
background-image: var(--jp-icon-ellipses);
}
.jp-ErrorIcon {
background-image: var(--jp-icon-error);
}
.jp-ExpandAllIcon {
background-image: var(--jp-icon-expand-all);
}
.jp-ExtensionIcon {
background-image: var(--jp-icon-extension);
}
.jp-FastForwardIcon {
background-image: var(--jp-icon-fast-forward);
}
.jp-FileIcon {
background-image: var(--jp-icon-file);
}
.jp-FileUploadIcon {
background-image: var(--jp-icon-file-upload);
}
.jp-FilterDotIcon {
background-image: var(--jp-icon-filter-dot);
}
.jp-FilterIcon {
background-image: var(--jp-icon-filter);
}
.jp-FilterListIcon {
background-image: var(--jp-icon-filter-list);
}
.jp-FolderFavoriteIcon {
background-image: var(--jp-icon-folder-favorite);
}
.jp-FolderIcon {
background-image: var(--jp-icon-folder);
}
.jp-HomeIcon {
background-image: var(--jp-icon-home);
}
.jp-Html5Icon {
background-image: var(--jp-icon-html5);
}
.jp-ImageIcon {
background-image: var(--jp-icon-image);
}
.jp-InfoIcon {
background-image: var(--jp-icon-info);
}
.jp-InspectorIcon {
background-image: var(--jp-icon-inspector);
}
.jp-JsonIcon {
background-image: var(--jp-icon-json);
}
.jp-JuliaIcon {
background-image: var(--jp-icon-julia);
}
.jp-JupyterFaviconIcon {
background-image: var(--jp-icon-jupyter-favicon);
}
.jp-JupyterIcon {
background-image: var(--jp-icon-jupyter);
}
.jp-JupyterlabWordmarkIcon {
background-image: var(--jp-icon-jupyterlab-wordmark);
}
.jp-KernelIcon {
background-image: var(--jp-icon-kernel);
}
.jp-KeyboardIcon {
background-image: var(--jp-icon-keyboard);
}
.jp-LaunchIcon {
background-image: var(--jp-icon-launch);
}
.jp-LauncherIcon {
background-image: var(--jp-icon-launcher);
}
.jp-LineFormIcon {
background-image: var(--jp-icon-line-form);
}
.jp-LinkIcon {
background-image: var(--jp-icon-link);
}
.jp-ListIcon {
background-image: var(--jp-icon-list);
}
.jp-MarkdownIcon {
background-image: var(--jp-icon-markdown);
}
.jp-MoveDownIcon {
background-image: var(--jp-icon-move-down);
}
.jp-MoveUpIcon {
background-image: var(--jp-icon-move-up);
}
.jp-NewFolderIcon {
background-image: var(--jp-icon-new-folder);
}
.jp-NotTrustedIcon {
background-image: var(--jp-icon-not-trusted);
}
.jp-NotebookIcon {
background-image: var(--jp-icon-notebook);
}
.jp-NumberingIcon {
background-image: var(--jp-icon-numbering);
}
.jp-OfflineBoltIcon {
background-image: var(--jp-icon-offline-bolt);
}
.jp-PaletteIcon {
background-image: var(--jp-icon-palette);
}
.jp-PasteIcon {
background-image: var(--jp-icon-paste);
}
.jp-PdfIcon {
background-image: var(--jp-icon-pdf);
}
.jp-PythonIcon {
background-image: var(--jp-icon-python);
}
.jp-RKernelIcon {
background-image: var(--jp-icon-r-kernel);
}
.jp-ReactIcon {
background-image: var(--jp-icon-react);
}
.jp-RedoIcon {
background-image: var(--jp-icon-redo);
}
.jp-RefreshIcon {
background-image: var(--jp-icon-refresh);
}
.jp-RegexIcon {
background-image: var(--jp-icon-regex);
}
.jp-RunIcon {
background-image: var(--jp-icon-run);
}
.jp-RunningIcon {
background-image: var(--jp-icon-running);
}
.jp-SaveIcon {
background-image: var(--jp-icon-save);
}
.jp-SearchIcon {
background-image: var(--jp-icon-search);
}
.jp-SettingsIcon {
background-image: var(--jp-icon-settings);
}
.jp-ShareIcon {
background-image: var(--jp-icon-share);
}
.jp-SpreadsheetIcon {
background-image: var(--jp-icon-spreadsheet);
}
.jp-StopIcon {
background-image: var(--jp-icon-stop);
}
.jp-TabIcon {
background-image: var(--jp-icon-tab);
}
.jp-TableRowsIcon {
background-image: var(--jp-icon-table-rows);
}
.jp-TagIcon {
background-image: var(--jp-icon-tag);
}
.jp-TerminalIcon {
background-image: var(--jp-icon-terminal);
}
.jp-TextEditorIcon {
background-image: var(--jp-icon-text-editor);
}
.jp-TocIcon {
background-image: var(--jp-icon-toc);
}
.jp-TreeViewIcon {
background-image: var(--jp-icon-tree-view);
}
.jp-TrustedIcon {
background-image: var(--jp-icon-trusted);
}
.jp-UndoIcon {
background-image: var(--jp-icon-undo);
}
.jp-UserIcon {
background-image: var(--jp-icon-user);
}
.jp-UsersIcon {
background-image: var(--jp-icon-users);
}
.jp-VegaIcon {
background-image: var(--jp-icon-vega);
}
.jp-WordIcon {
background-image: var(--jp-icon-word);
}
.jp-YamlIcon {
background-image: var(--jp-icon-yaml);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* (DEPRECATED) Support for consuming icons as CSS background images
*/
.jp-Icon,
.jp-MaterialIcon {
background-position: center;
background-repeat: no-repeat;
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-cover {
background-position: center;
background-repeat: no-repeat;
background-size: cover;
}
/**
* (DEPRECATED) Support for specific CSS icon sizes
*/
.jp-Icon-16 {
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-18 {
background-size: 18px;
min-width: 18px;
min-height: 18px;
}
.jp-Icon-20 {
background-size: 20px;
min-width: 20px;
min-height: 20px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.lm-TabBar .lm-TabBar-addButton {
align-items: center;
display: flex;
padding: 4px;
padding-bottom: 5px;
margin-right: 1px;
background-color: var(--jp-layout-color2);
}
.lm-TabBar .lm-TabBar-addButton:hover {
background-color: var(--jp-layout-color1);
}
.lm-DockPanel-tabBar .lm-TabBar-tab {
width: var(--jp-private-horizontal-tab-width);
}
.lm-DockPanel-tabBar .lm-TabBar-content {
flex: unset;
}
.lm-DockPanel-tabBar[data-orientation='horizontal'] {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for icons as inline SVG HTMLElements
*/
/* recolor the primary elements of an icon */
.jp-icon0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-accent0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-accent1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-accent2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-accent3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-accent4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-accent0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-accent1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-accent2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-accent3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-accent4[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-none[fill] {
fill: none;
}
.jp-icon-none[stroke] {
stroke: none;
}
/* brand icon colors. Same for light and dark */
.jp-icon-brand0[fill] {
fill: var(--jp-brand-color0);
}
.jp-icon-brand1[fill] {
fill: var(--jp-brand-color1);
}
.jp-icon-brand2[fill] {
fill: var(--jp-brand-color2);
}
.jp-icon-brand3[fill] {
fill: var(--jp-brand-color3);
}
.jp-icon-brand4[fill] {
fill: var(--jp-brand-color4);
}
.jp-icon-brand0[stroke] {
stroke: var(--jp-brand-color0);
}
.jp-icon-brand1[stroke] {
stroke: var(--jp-brand-color1);
}
.jp-icon-brand2[stroke] {
stroke: var(--jp-brand-color2);
}
.jp-icon-brand3[stroke] {
stroke: var(--jp-brand-color3);
}
.jp-icon-brand4[stroke] {
stroke: var(--jp-brand-color4);
}
/* warn icon colors. Same for light and dark */
.jp-icon-warn0[fill] {
fill: var(--jp-warn-color0);
}
.jp-icon-warn1[fill] {
fill: var(--jp-warn-color1);
}
.jp-icon-warn2[fill] {
fill: var(--jp-warn-color2);
}
.jp-icon-warn3[fill] {
fill: var(--jp-warn-color3);
}
.jp-icon-warn0[stroke] {
stroke: var(--jp-warn-color0);
}
.jp-icon-warn1[stroke] {
stroke: var(--jp-warn-color1);
}
.jp-icon-warn2[stroke] {
stroke: var(--jp-warn-color2);
}
.jp-icon-warn3[stroke] {
stroke: var(--jp-warn-color3);
}
/* icon colors that contrast well with each other and most backgrounds */
.jp-icon-contrast0[fill] {
fill: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[fill] {
fill: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[fill] {
fill: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[fill] {
fill: var(--jp-icon-contrast-color3);
}
.jp-icon-contrast0[stroke] {
stroke: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[stroke] {
stroke: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[stroke] {
stroke: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[stroke] {
stroke: var(--jp-icon-contrast-color3);
}
.jp-icon-dot[fill] {
fill: var(--jp-warn-color0);
}
.jp-jupyter-icon-color[fill] {
fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
}
.jp-notebook-icon-color[fill] {
fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
}
.jp-json-icon-color[fill] {
fill: var(--jp-json-icon-color, var(--jp-warn-color1));
}
.jp-console-icon-color[fill] {
fill: var(--jp-console-icon-color, white);
}
.jp-console-icon-background-color[fill] {
fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
}
.jp-terminal-icon-color[fill] {
fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
}
.jp-terminal-icon-background-color[fill] {
fill: var(
--jp-terminal-icon-background-color,
var(--jp-inverse-layout-color2)
);
}
.jp-text-editor-icon-color[fill] {
fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
}
.jp-inspector-icon-color[fill] {
fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
}
/* CSS for icons in selected filebrowser listing items */
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* stylelint-disable selector-max-class, selector-max-compound-selectors */
/**
* TODO: come up with non css-hack solution for showing the busy icon on top
* of the close icon
* CSS for complex behavior of close icon of tabs in the main area tabbar
*/
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon3[fill] {
fill: none;
}
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon-busy[fill] {
fill: var(--jp-inverse-layout-color3);
}
/* stylelint-enable selector-max-class, selector-max-compound-selectors */
/* CSS for icons in status bar */
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* special handling for splash icon CSS. While the theme CSS reloads during
splash, the splash icon can loose theming. To prevent that, we set a
default for its color variable */
:root {
--jp-warn-color0: var(--md-orange-700);
}
/* not sure what to do with this one, used in filebrowser listing */
.jp-DragIcon {
margin-right: 4px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for alt colors for icons as inline SVG HTMLElements
*/
/* alt recolor the primary elements of an icon */
.jp-icon-alt .jp-icon0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-alt .jp-icon0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[stroke] {
stroke: var(--jp-layout-color4);
}
/* alt recolor the accent elements of an icon */
.jp-icon-alt .jp-icon-accent0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-alt .jp-icon-accent0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
display: none !important;
}
/**
* Support for hover colors for icons as inline SVG HTMLElements
*/
/**
* regular colors
*/
/* recolor the primary elements of an icon */
.jp-icon-hover :hover .jp-icon0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-hover :hover .jp-icon-none-hover[fill] {
fill: none;
}
.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
stroke: none;
}
/**
* inverse colors
*/
/* inverse recolor the primary elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* inverse recolor the accent elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-IFrame {
width: 100%;
height: 100%;
}
.jp-IFrame > iframe {
border: none;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-IFrame {
position: relative;
}
body.lm-mod-override-cursor .jp-IFrame::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-HoverBox {
position: fixed;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FormGroup-content fieldset {
border: none;
padding: 0;
min-width: 0;
width: 100%;
}
/* stylelint-disable selector-max-type */
.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
font-size: var(--jp-content-font-size2);
border-color: var(--jp-input-border-color);
border-style: solid;
border-radius: var(--jp-border-radius);
border-width: 1px;
padding: 6px 8px;
background: none;
color: var(--jp-ui-font-color0);
height: inherit;
}
.jp-FormGroup-content fieldset input[type='checkbox'] {
position: relative;
top: 2px;
margin-left: 0;
}
.jp-FormGroup-content button.jp-mod-styled {
cursor: pointer;
}
.jp-FormGroup-content .checkbox label {
cursor: pointer;
font-size: var(--jp-content-font-size1);
}
.jp-FormGroup-content .jp-root > fieldset > legend {
display: none;
}
.jp-FormGroup-content .jp-root > fieldset > p {
display: none;
}
/** copy of `input.jp-mod-styled:focus` style */
.jp-FormGroup-content fieldset input:focus,
.jp-FormGroup-content fieldset select:focus {
-moz-outline-radius: unset;
outline: var(--jp-border-width) solid var(--md-blue-500);
outline-offset: -1px;
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-FormGroup-content fieldset input:hover:not(:focus),
.jp-FormGroup-content fieldset select:hover:not(:focus) {
background-color: var(--jp-border-color2);
}
/* stylelint-enable selector-max-type */
.jp-FormGroup-content .checkbox .field-description {
/* Disable default description field for checkbox:
because other widgets do not have description fields,
we add descriptions to each widget on the field level.
*/
display: none;
}
.jp-FormGroup-content #root__description {
display: none;
}
.jp-FormGroup-content .jp-modifiedIndicator {
width: 5px;
background-color: var(--jp-brand-color2);
margin-top: 0;
margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
flex-shrink: 0;
}
.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
background-color: var(--jp-error-color0);
margin-right: 0.5em;
}
/* RJSF ARRAY style */
.jp-arrayFieldWrapper legend {
font-size: var(--jp-content-font-size2);
color: var(--jp-ui-font-color0);
flex-basis: 100%;
padding: 4px 0;
font-weight: var(--jp-content-heading-font-weight);
border-bottom: 1px solid var(--jp-border-color2);
}
.jp-arrayFieldWrapper .field-description {
padding: 4px 0;
white-space: pre-wrap;
}
.jp-arrayFieldWrapper .array-item {
width: 100%;
border: 1px solid var(--jp-border-color2);
border-radius: 4px;
margin: 4px;
}
.jp-ArrayOperations {
display: flex;
margin-left: 8px;
}
.jp-ArrayOperationsButton {
margin: 2px;
}
.jp-ArrayOperationsButton .jp-icon3[fill] {
fill: var(--jp-ui-font-color0);
}
button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
cursor: not-allowed;
opacity: 0.5;
}
/* RJSF form validation error */
.jp-FormGroup-content .validationErrors {
color: var(--jp-error-color0);
}
/* Hide panel level error as duplicated the field level error */
.jp-FormGroup-content .panel.errors {
display: none;
}
/* RJSF normal content (settings-editor) */
.jp-FormGroup-contentNormal {
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
margin-left: 7px;
color: var(--jp-ui-font-color0);
}
.jp-FormGroup-contentNormal .jp-FormGroup-description {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-default {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
font-size: var(--jp-content-font-size1);
font-weight: normal;
min-width: 120px;
}
.jp-FormGroup-contentNormal fieldset:not(:first-child) {
margin-left: 7px;
}
.jp-FormGroup-contentNormal .field-array-of-string .array-item {
/* Display `jp-ArrayOperations` buttons side-by-side with content except
for small screens where flex-wrap will place them one below the other.
*/
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
/* RJSF compact content (metadata-form) */
.jp-FormGroup-content.jp-FormGroup-contentCompact {
width: 100%;
}
.jp-FormGroup-contentCompact .form-group {
display: flex;
padding: 0.5em 0.2em 0.5em 0;
}
.jp-FormGroup-contentCompact
.jp-FormGroup-compactTitle
.jp-FormGroup-description {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color2);
}
.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
padding-bottom: 0.3em;
}
.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
width: 100%;
box-sizing: border-box;
}
.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
padding-bottom: 7px;
}
.jp-FormGroup-contentCompact
.jp-objectFieldWrapper
.jp-objectFieldWrapper
.form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
.jp-FormGroup-contentCompact ul.error-detail {
margin-block-start: 0.5em;
margin-block-end: 0.5em;
padding-inline-start: 1em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-SidePanel {
display: flex;
flex-direction: column;
min-width: var(--jp-sidebar-min-width);
overflow-y: auto;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
font-size: var(--jp-ui-font-size1);
}
.jp-SidePanel-header {
flex: 0 0 auto;
display: flex;
border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin: 0;
padding: 2px;
text-transform: uppercase;
}
.jp-SidePanel-toolbar {
flex: 0 0 auto;
}
.jp-SidePanel-content {
flex: 1 1 auto;
}
.jp-SidePanel-toolbar,
.jp-AccordionPanel-toolbar {
height: var(--jp-private-toolbar-height);
}
.jp-SidePanel-toolbar.jp-Toolbar-micro {
display: none;
}
.lm-AccordionPanel .jp-AccordionPanel-title {
box-sizing: border-box;
line-height: 25px;
margin: 0;
display: flex;
align-items: center;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
font-size: var(--jp-ui-font-size0);
}
.jp-AccordionPanel-title {
cursor: pointer;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
text-transform: uppercase;
}
.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
/* Title is rotated for horizontal accordion panel using CSS */
display: block;
transform-origin: top left;
transform: rotate(-90deg) translate(-100%);
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
user-select: none;
text-overflow: ellipsis;
white-space: nowrap;
overflow: hidden;
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
transform: rotate(-90deg);
margin: auto 0;
height: 16px;
}
.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
transform: rotate(0deg);
}
.lm-AccordionPanel .jp-AccordionPanel-toolbar {
background: none;
box-shadow: none;
border: none;
margin-left: auto;
}
.lm-AccordionPanel .lm-SplitPanel-handle:hover {
background: var(--jp-layout-color3);
}
.jp-text-truncated {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Spinner {
position: absolute;
display: flex;
justify-content: center;
align-items: center;
z-index: 10;
left: 0;
top: 0;
width: 100%;
height: 100%;
background: var(--jp-layout-color0);
outline: none;
}
.jp-SpinnerContent {
font-size: 10px;
margin: 50px auto;
text-indent: -9999em;
width: 3em;
height: 3em;
border-radius: 50%;
background: var(--jp-brand-color3);
background: linear-gradient(
to right,
#f37626 10%,
rgba(255, 255, 255, 0) 42%
);
position: relative;
animation: load3 1s infinite linear, fadeIn 1s;
}
.jp-SpinnerContent::before {
width: 50%;
height: 50%;
background: #f37626;
border-radius: 100% 0 0;
position: absolute;
top: 0;
left: 0;
content: '';
}
.jp-SpinnerContent::after {
background: var(--jp-layout-color0);
width: 75%;
height: 75%;
border-radius: 50%;
content: '';
margin: auto;
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
@keyframes load3 {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
button.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: none;
box-sizing: border-box;
text-align: center;
line-height: 32px;
height: 32px;
padding: 0 12px;
letter-spacing: 0.8px;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input.jp-mod-styled {
background: var(--jp-input-background);
height: 28px;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color1);
padding-left: 7px;
padding-right: 7px;
font-size: var(--jp-ui-font-size2);
color: var(--jp-ui-font-color0);
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input[type='checkbox'].jp-mod-styled {
appearance: checkbox;
-webkit-appearance: checkbox;
-moz-appearance: checkbox;
height: auto;
}
input.jp-mod-styled:focus {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-select-wrapper {
display: flex;
position: relative;
flex-direction: column;
padding: 1px;
background-color: var(--jp-layout-color1);
box-sizing: border-box;
margin-bottom: 12px;
}
.jp-select-wrapper:not(.multiple) {
height: 28px;
}
.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-input-active-background);
}
select.jp-mod-styled:hover {
cursor: pointer;
color: var(--jp-ui-font-color0);
background-color: var(--jp-input-hover-background);
box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
}
select.jp-mod-styled {
flex: 1 1 auto;
width: 100%;
font-size: var(--jp-ui-font-size2);
background: var(--jp-input-background);
color: var(--jp-ui-font-color0);
padding: 0 25px 0 8px;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
select.jp-mod-styled:not([multiple]) {
height: 32px;
}
select.jp-mod-styled[multiple] {
max-height: 200px;
overflow-y: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-switch {
display: flex;
align-items: center;
padding-left: 4px;
padding-right: 4px;
font-size: var(--jp-ui-font-size1);
background-color: transparent;
color: var(--jp-ui-font-color1);
border: none;
height: 20px;
}
.jp-switch:hover {
background-color: var(--jp-layout-color2);
}
.jp-switch-label {
margin-right: 5px;
font-family: var(--jp-ui-font-family);
}
.jp-switch-track {
cursor: pointer;
background-color: var(--jp-switch-color, var(--jp-border-color1));
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 34px;
height: 16px;
width: 35px;
position: relative;
}
.jp-switch-track::before {
content: '';
position: absolute;
height: 10px;
width: 10px;
margin: 3px;
left: 0;
background-color: var(--jp-ui-inverse-font-color1);
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 50%;
}
.jp-switch[aria-checked='true'] .jp-switch-track {
background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
}
.jp-switch[aria-checked='true'] .jp-switch-track::before {
/* track width (35) - margins (3 + 3) - thumb width (10) */
left: 19px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
:root {
--jp-private-toolbar-height: calc(
28px + var(--jp-border-width)
); /* leave 28px for content */
}
.jp-Toolbar {
color: var(--jp-ui-font-color1);
flex: 0 0 auto;
display: flex;
flex-direction: row;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: 2px;
z-index: 8;
overflow-x: hidden;
}
/* Toolbar items */
.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
flex-grow: 1;
flex-shrink: 1;
}
.jp-Toolbar-item.jp-Toolbar-kernelStatus {
display: inline-block;
width: 32px;
background-repeat: no-repeat;
background-position: center;
background-size: 16px;
}
.jp-Toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
display: flex;
padding-left: 1px;
padding-right: 1px;
font-size: var(--jp-ui-font-size1);
line-height: var(--jp-private-toolbar-height);
height: 100%;
}
/* Toolbar buttons */
/* This is the div we use to wrap the react component into a Widget */
div.jp-ToolbarButton {
color: transparent;
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0;
margin: 0;
}
button.jp-ToolbarButtonComponent {
background: var(--jp-layout-color1);
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0 6px;
margin: 0;
height: 24px;
border-radius: var(--jp-border-radius);
display: flex;
align-items: center;
text-align: center;
font-size: 14px;
min-width: unset;
min-height: unset;
}
button.jp-ToolbarButtonComponent:disabled {
opacity: 0.4;
}
button.jp-ToolbarButtonComponent > span {
padding: 0;
flex: 0 0 auto;
}
button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
font-size: var(--jp-ui-font-size1);
line-height: 100%;
padding-left: 2px;
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar.jp-Toolbar-micro {
padding: 0;
min-height: 0;
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar {
border: none;
box-shadow: none;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-WindowedPanel-outer {
position: relative;
overflow-y: auto;
}
.jp-WindowedPanel-inner {
position: relative;
}
.jp-WindowedPanel-window {
position: absolute;
left: 0;
right: 0;
overflow: visible;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/* Sibling imports */
body {
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
}
/* Disable native link decoration styles everywhere outside of dialog boxes */
a {
text-decoration: unset;
color: unset;
}
a:hover {
text-decoration: unset;
color: unset;
}
/* Accessibility for links inside dialog box text */
.jp-Dialog-content a {
text-decoration: revert;
color: var(--jp-content-link-color);
}
.jp-Dialog-content a:hover {
text-decoration: revert;
}
/* Styles for ui-components */
.jp-Button {
color: var(--jp-ui-font-color2);
border-radius: var(--jp-border-radius);
padding: 0 12px;
font-size: var(--jp-ui-font-size1);
/* Copy from blueprint 3 */
display: inline-flex;
flex-direction: row;
border: none;
cursor: pointer;
align-items: center;
justify-content: center;
text-align: left;
vertical-align: middle;
min-height: 30px;
min-width: 30px;
}
.jp-Button:disabled {
cursor: not-allowed;
}
.jp-Button:empty {
padding: 0 !important;
}
.jp-Button.jp-mod-small {
min-height: 24px;
min-width: 24px;
font-size: 12px;
padding: 0 7px;
}
/* Use our own theme for hover styles */
.jp-Button.jp-mod-minimal:hover {
background-color: var(--jp-layout-color2);
}
.jp-Button.jp-mod-minimal {
background: none;
}
.jp-InputGroup {
display: block;
position: relative;
}
.jp-InputGroup input {
box-sizing: border-box;
border: none;
border-radius: 0;
background-color: transparent;
color: var(--jp-ui-font-color0);
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
padding-bottom: 0;
padding-top: 0;
padding-left: 10px;
padding-right: 28px;
position: relative;
width: 100%;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
font-size: 14px;
font-weight: 400;
height: 30px;
line-height: 30px;
outline: none;
vertical-align: middle;
}
.jp-InputGroup input:focus {
box-shadow: inset 0 0 0 var(--jp-border-width)
var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-InputGroup input:disabled {
cursor: not-allowed;
resize: block;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input:disabled ~ span {
cursor: not-allowed;
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input::placeholder,
input::placeholder {
color: var(--jp-ui-font-color2);
}
.jp-InputGroupAction {
position: absolute;
bottom: 1px;
right: 0;
padding: 6px;
}
.jp-HTMLSelect.jp-DefaultStyle select {
background-color: initial;
border: none;
border-radius: 0;
box-shadow: none;
color: var(--jp-ui-font-color0);
display: block;
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
height: 24px;
line-height: 14px;
padding: 0 25px 0 10px;
text-align: left;
-moz-appearance: none;
-webkit-appearance: none;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
cursor: not-allowed;
resize: block;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
cursor: not-allowed;
}
/* Use our own theme for hover and option styles */
/* stylelint-disable-next-line selector-max-type */
.jp-HTMLSelect.jp-DefaultStyle select:hover,
.jp-HTMLSelect.jp-DefaultStyle select > option {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color0);
}
select {
box-sizing: border-box;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-StatusBar-Widget {
display: flex;
align-items: center;
background: var(--jp-layout-color2);
min-height: var(--jp-statusbar-height);
justify-content: space-between;
padding: 0 10px;
}
.jp-StatusBar-Left {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-StatusBar-Middle {
display: flex;
align-items: center;
}
.jp-StatusBar-Right {
display: flex;
align-items: center;
flex-direction: row-reverse;
}
.jp-StatusBar-Item {
max-height: var(--jp-statusbar-height);
margin: 0 2px;
height: var(--jp-statusbar-height);
white-space: nowrap;
text-overflow: ellipsis;
color: var(--jp-ui-font-color1);
padding: 0 6px;
}
.jp-mod-highlighted:hover {
background-color: var(--jp-layout-color3);
}
.jp-mod-clicked {
background-color: var(--jp-brand-color1);
}
.jp-mod-clicked:hover {
background-color: var(--jp-brand-color0);
}
.jp-mod-clicked .jp-StatusBar-TextItem {
color: var(--jp-ui-inverse-font-color1);
}
.jp-StatusBar-HoverItem {
box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
}
.jp-StatusBar-TextItem {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
line-height: 24px;
color: var(--jp-ui-font-color1);
}
.jp-StatusBar-GroupItem {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-Statusbar-ProgressCircle svg {
display: block;
margin: 0 auto;
width: 16px;
height: 24px;
align-self: normal;
}
.jp-Statusbar-ProgressCircle path {
fill: var(--jp-inverse-layout-color3);
}
.jp-Statusbar-ProgressBar-progress-bar {
height: 10px;
width: 100px;
border: solid 0.25px var(--jp-brand-color2);
border-radius: 3px;
overflow: hidden;
align-self: center;
}
.jp-Statusbar-ProgressBar-progress-bar > div {
background-color: var(--jp-brand-color2);
background-image: linear-gradient(
-45deg,
rgba(255, 255, 255, 0.2) 25%,
transparent 25%,
transparent 50%,
rgba(255, 255, 255, 0.2) 50%,
rgba(255, 255, 255, 0.2) 75%,
transparent 75%,
transparent
);
background-size: 40px 40px;
float: left;
width: 0%;
height: 100%;
font-size: 12px;
line-height: 14px;
color: #fff;
text-align: center;
animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
}
.jp-Statusbar-ProgressBar-progress-bar p {
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
font-size: var(--jp-ui-font-size1);
line-height: 10px;
width: 100px;
}
@keyframes jp-Statusbar-ExecutionTime-progress-bar {
0% {
background-position: 0 0;
}
100% {
background-position: 40px 40px;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-commandpalette-search-height: 28px;
}
/*-----------------------------------------------------------------------------
| Overall styles
|----------------------------------------------------------------------------*/
.lm-CommandPalette {
padding-bottom: 0;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Modal variant
|----------------------------------------------------------------------------*/
.jp-ModalCommandPalette {
position: absolute;
z-index: 10000;
top: 38px;
left: 30%;
margin: 0;
padding: 4px;
width: 40%;
box-shadow: var(--jp-elevation-z4);
border-radius: 4px;
background: var(--jp-layout-color0);
}
.jp-ModalCommandPalette .lm-CommandPalette {
max-height: 40vh;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
margin-left: 4px;
margin-right: 4px;
}
.jp-ModalCommandPalette
.lm-CommandPalette
.lm-CommandPalette-item.lm-mod-disabled {
display: none;
}
/*-----------------------------------------------------------------------------
| Search
|----------------------------------------------------------------------------*/
.lm-CommandPalette-search {
padding: 4px;
background-color: var(--jp-layout-color1);
z-index: 2;
}
.lm-CommandPalette-wrapper {
overflow: overlay;
padding: 0 9px;
background-color: var(--jp-input-active-background);
height: 30px;
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
}
.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-SearchIconGroup {
color: white;
background-color: var(--jp-brand-color1);
position: absolute;
top: 4px;
right: 4px;
padding: 5px 5px 1px;
}
.jp-SearchIconGroup svg {
height: 20px;
width: 20px;
}
.jp-SearchIconGroup .jp-icon3[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-input {
background: transparent;
width: calc(100% - 18px);
float: left;
border: none;
outline: none;
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
line-height: var(--jp-private-commandpalette-search-height);
}
.lm-CommandPalette-input::-webkit-input-placeholder,
.lm-CommandPalette-input::-moz-placeholder,
.lm-CommandPalette-input:-ms-input-placeholder {
color: var(--jp-ui-font-color2);
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Results
|----------------------------------------------------------------------------*/
.lm-CommandPalette-header:first-child {
margin-top: 0;
}
.lm-CommandPalette-header {
border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
color: var(--jp-ui-font-color1);
cursor: pointer;
display: flex;
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin-top: 8px;
padding: 8px 0 8px 12px;
text-transform: uppercase;
}
.lm-CommandPalette-header.lm-mod-active {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-header > mark {
background-color: transparent;
font-weight: bold;
color: var(--jp-ui-font-color1);
}
.lm-CommandPalette-item {
padding: 4px 12px 4px 4px;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
font-weight: 400;
display: flex;
}
.lm-CommandPalette-item.lm-mod-disabled {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item.lm-mod-active {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-inverse-font-color0);
}
.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-itemContent {
overflow: hidden;
}
.lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.lm-CommandPalette-item.lm-mod-disabled mark {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
margin: 0 4px 0 0;
position: relative;
width: 16px;
top: 2px;
flex: 0 0 auto;
}
.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
opacity: 0.6;
}
.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
flex: 0 0 auto;
}
.lm-CommandPalette-itemCaption {
display: none;
}
.lm-CommandPalette-content {
background-color: var(--jp-layout-color1);
}
.lm-CommandPalette-content:empty::after {
content: 'No results';
margin: auto;
margin-top: 20px;
width: 100px;
display: block;
font-size: var(--jp-ui-font-size2);
font-family: var(--jp-ui-font-family);
font-weight: lighter;
}
.lm-CommandPalette-emptyMessage {
text-align: center;
margin-top: 24px;
line-height: 1.32;
padding: 0 8px;
color: var(--jp-content-font-color3);
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Dialog {
position: absolute;
z-index: 10000;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
top: 0;
left: 0;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
background: var(--jp-dialog-background);
}
.jp-Dialog-content {
display: flex;
flex-direction: column;
margin-left: auto;
margin-right: auto;
background: var(--jp-layout-color1);
padding: 24px 24px 12px;
min-width: 300px;
min-height: 150px;
max-width: 1000px;
max-height: 500px;
box-sizing: border-box;
box-shadow: var(--jp-elevation-z20);
word-wrap: break-word;
border-radius: var(--jp-border-radius);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color1);
resize: both;
}
.jp-Dialog-content.jp-Dialog-content-small {
max-width: 500px;
}
.jp-Dialog-button {
overflow: visible;
}
button.jp-Dialog-button:focus {
outline: 1px solid var(--jp-brand-color1);
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button:focus::-moz-focus-inner {
border: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
}
button.jp-Dialog-close-button {
padding: 0;
height: 100%;
min-width: unset;
min-height: unset;
}
.jp-Dialog-header {
display: flex;
justify-content: space-between;
flex: 0 0 auto;
padding-bottom: 12px;
font-size: var(--jp-ui-font-size3);
font-weight: 400;
color: var(--jp-ui-font-color1);
}
.jp-Dialog-body {
display: flex;
flex-direction: column;
flex: 1 1 auto;
font-size: var(--jp-ui-font-size1);
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
overflow: auto;
}
.jp-Dialog-footer {
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
flex: 0 0 auto;
margin-left: -12px;
margin-right: -12px;
padding: 12px;
}
.jp-Dialog-checkbox {
padding-right: 5px;
}
.jp-Dialog-checkbox > input:focus-visible {
outline: 1px solid var(--jp-input-active-border-color);
outline-offset: 1px;
}
.jp-Dialog-spacer {
flex: 1 1 auto;
}
.jp-Dialog-title {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.jp-Dialog-body > .jp-select-wrapper {
width: 100%;
}
.jp-Dialog-body > button {
padding: 0 16px;
}
.jp-Dialog-body > label {
line-height: 1.4;
color: var(--jp-ui-font-color0);
}
.jp-Dialog-button.jp-mod-styled:not(:last-child) {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Input-Boolean-Dialog {
flex-direction: row-reverse;
align-items: end;
width: 100%;
}
.jp-Input-Boolean-Dialog > label {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MainAreaWidget > :focus {
outline: none;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error {
padding: 6px;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
width: auto;
padding: 10px;
background: var(--jp-error-color3);
border: var(--jp-border-width) solid var(--jp-error-color1);
border-radius: var(--jp-border-radius);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
white-space: pre-wrap;
word-wrap: break-word;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/**
* google-material-color v1.2.6
* https://github.com/danlevan/google-material-color
*/
:root {
--md-red-50: #ffebee;
--md-red-100: #ffcdd2;
--md-red-200: #ef9a9a;
--md-red-300: #e57373;
--md-red-400: #ef5350;
--md-red-500: #f44336;
--md-red-600: #e53935;
--md-red-700: #d32f2f;
--md-red-800: #c62828;
--md-red-900: #b71c1c;
--md-red-A100: #ff8a80;
--md-red-A200: #ff5252;
--md-red-A400: #ff1744;
--md-red-A700: #d50000;
--md-pink-50: #fce4ec;
--md-pink-100: #f8bbd0;
--md-pink-200: #f48fb1;
--md-pink-300: #f06292;
--md-pink-400: #ec407a;
--md-pink-500: #e91e63;
--md-pink-600: #d81b60;
--md-pink-700: #c2185b;
--md-pink-800: #ad1457;
--md-pink-900: #880e4f;
--md-pink-A100: #ff80ab;
--md-pink-A200: #ff4081;
--md-pink-A400: #f50057;
--md-pink-A700: #c51162;
--md-purple-50: #f3e5f5;
--md-purple-100: #e1bee7;
--md-purple-200: #ce93d8;
--md-purple-300: #ba68c8;
--md-purple-400: #ab47bc;
--md-purple-500: #9c27b0;
--md-purple-600: #8e24aa;
--md-purple-700: #7b1fa2;
--md-purple-800: #6a1b9a;
--md-purple-900: #4a148c;
--md-purple-A100: #ea80fc;
--md-purple-A200: #e040fb;
--md-purple-A400: #d500f9;
--md-purple-A700: #a0f;
--md-deep-purple-50: #ede7f6;
--md-deep-purple-100: #d1c4e9;
--md-deep-purple-200: #b39ddb;
--md-deep-purple-300: #9575cd;
--md-deep-purple-400: #7e57c2;
--md-deep-purple-500: #673ab7;
--md-deep-purple-600: #5e35b1;
--md-deep-purple-700: #512da8;
--md-deep-purple-800: #4527a0;
--md-deep-purple-900: #311b92;
--md-deep-purple-A100: #b388ff;
--md-deep-purple-A200: #7c4dff;
--md-deep-purple-A400: #651fff;
--md-deep-purple-A700: #6200ea;
--md-indigo-50: #e8eaf6;
--md-indigo-100: #c5cae9;
--md-indigo-200: #9fa8da;
--md-indigo-300: #7986cb;
--md-indigo-400: #5c6bc0;
--md-indigo-500: #3f51b5;
--md-indigo-600: #3949ab;
--md-indigo-700: #303f9f;
--md-indigo-800: #283593;
--md-indigo-900: #1a237e;
--md-indigo-A100: #8c9eff;
--md-indigo-A200: #536dfe;
--md-indigo-A400: #3d5afe;
--md-indigo-A700: #304ffe;
--md-blue-50: #e3f2fd;
--md-blue-100: #bbdefb;
--md-blue-200: #90caf9;
--md-blue-300: #64b5f6;
--md-blue-400: #42a5f5;
--md-blue-500: #2196f3;
--md-blue-600: #1e88e5;
--md-blue-700: #1976d2;
--md-blue-800: #1565c0;
--md-blue-900: #0d47a1;
--md-blue-A100: #82b1ff;
--md-blue-A200: #448aff;
--md-blue-A400: #2979ff;
--md-blue-A700: #2962ff;
--md-light-blue-50: #e1f5fe;
--md-light-blue-100: #b3e5fc;
--md-light-blue-200: #81d4fa;
--md-light-blue-300: #4fc3f7;
--md-light-blue-400: #29b6f6;
--md-light-blue-500: #03a9f4;
--md-light-blue-600: #039be5;
--md-light-blue-700: #0288d1;
--md-light-blue-800: #0277bd;
--md-light-blue-900: #01579b;
--md-light-blue-A100: #80d8ff;
--md-light-blue-A200: #40c4ff;
--md-light-blue-A400: #00b0ff;
--md-light-blue-A700: #0091ea;
--md-cyan-50: #e0f7fa;
--md-cyan-100: #b2ebf2;
--md-cyan-200: #80deea;
--md-cyan-300: #4dd0e1;
--md-cyan-400: #26c6da;
--md-cyan-500: #00bcd4;
--md-cyan-600: #00acc1;
--md-cyan-700: #0097a7;
--md-cyan-800: #00838f;
--md-cyan-900: #006064;
--md-cyan-A100: #84ffff;
--md-cyan-A200: #18ffff;
--md-cyan-A400: #00e5ff;
--md-cyan-A700: #00b8d4;
--md-teal-50: #e0f2f1;
--md-teal-100: #b2dfdb;
--md-teal-200: #80cbc4;
--md-teal-300: #4db6ac;
--md-teal-400: #26a69a;
--md-teal-500: #009688;
--md-teal-600: #00897b;
--md-teal-700: #00796b;
--md-teal-800: #00695c;
--md-teal-900: #004d40;
--md-teal-A100: #a7ffeb;
--md-teal-A200: #64ffda;
--md-teal-A400: #1de9b6;
--md-teal-A700: #00bfa5;
--md-green-50: #e8f5e9;
--md-green-100: #c8e6c9;
--md-green-200: #a5d6a7;
--md-green-300: #81c784;
--md-green-400: #66bb6a;
--md-green-500: #4caf50;
--md-green-600: #43a047;
--md-green-700: #388e3c;
--md-green-800: #2e7d32;
--md-green-900: #1b5e20;
--md-green-A100: #b9f6ca;
--md-green-A200: #69f0ae;
--md-green-A400: #00e676;
--md-green-A700: #00c853;
--md-light-green-50: #f1f8e9;
--md-light-green-100: #dcedc8;
--md-light-green-200: #c5e1a5;
--md-light-green-300: #aed581;
--md-light-green-400: #9ccc65;
--md-light-green-500: #8bc34a;
--md-light-green-600: #7cb342;
--md-light-green-700: #689f38;
--md-light-green-800: #558b2f;
--md-light-green-900: #33691e;
--md-light-green-A100: #ccff90;
--md-light-green-A200: #b2ff59;
--md-light-green-A400: #76ff03;
--md-light-green-A700: #64dd17;
--md-lime-50: #f9fbe7;
--md-lime-100: #f0f4c3;
--md-lime-200: #e6ee9c;
--md-lime-300: #dce775;
--md-lime-400: #d4e157;
--md-lime-500: #cddc39;
--md-lime-600: #c0ca33;
--md-lime-700: #afb42b;
--md-lime-800: #9e9d24;
--md-lime-900: #827717;
--md-lime-A100: #f4ff81;
--md-lime-A200: #eeff41;
--md-lime-A400: #c6ff00;
--md-lime-A700: #aeea00;
--md-yellow-50: #fffde7;
--md-yellow-100: #fff9c4;
--md-yellow-200: #fff59d;
--md-yellow-300: #fff176;
--md-yellow-400: #ffee58;
--md-yellow-500: #ffeb3b;
--md-yellow-600: #fdd835;
--md-yellow-700: #fbc02d;
--md-yellow-800: #f9a825;
--md-yellow-900: #f57f17;
--md-yellow-A100: #ffff8d;
--md-yellow-A200: #ff0;
--md-yellow-A400: #ffea00;
--md-yellow-A700: #ffd600;
--md-amber-50: #fff8e1;
--md-amber-100: #ffecb3;
--md-amber-200: #ffe082;
--md-amber-300: #ffd54f;
--md-amber-400: #ffca28;
--md-amber-500: #ffc107;
--md-amber-600: #ffb300;
--md-amber-700: #ffa000;
--md-amber-800: #ff8f00;
--md-amber-900: #ff6f00;
--md-amber-A100: #ffe57f;
--md-amber-A200: #ffd740;
--md-amber-A400: #ffc400;
--md-amber-A700: #ffab00;
--md-orange-50: #fff3e0;
--md-orange-100: #ffe0b2;
--md-orange-200: #ffcc80;
--md-orange-300: #ffb74d;
--md-orange-400: #ffa726;
--md-orange-500: #ff9800;
--md-orange-600: #fb8c00;
--md-orange-700: #f57c00;
--md-orange-800: #ef6c00;
--md-orange-900: #e65100;
--md-orange-A100: #ffd180;
--md-orange-A200: #ffab40;
--md-orange-A400: #ff9100;
--md-orange-A700: #ff6d00;
--md-deep-orange-50: #fbe9e7;
--md-deep-orange-100: #ffccbc;
--md-deep-orange-200: #ffab91;
--md-deep-orange-300: #ff8a65;
--md-deep-orange-400: #ff7043;
--md-deep-orange-500: #ff5722;
--md-deep-orange-600: #f4511e;
--md-deep-orange-700: #e64a19;
--md-deep-orange-800: #d84315;
--md-deep-orange-900: #bf360c;
--md-deep-orange-A100: #ff9e80;
--md-deep-orange-A200: #ff6e40;
--md-deep-orange-A400: #ff3d00;
--md-deep-orange-A700: #dd2c00;
--md-brown-50: #efebe9;
--md-brown-100: #d7ccc8;
--md-brown-200: #bcaaa4;
--md-brown-300: #a1887f;
--md-brown-400: #8d6e63;
--md-brown-500: #795548;
--md-brown-600: #6d4c41;
--md-brown-700: #5d4037;
--md-brown-800: #4e342e;
--md-brown-900: #3e2723;
--md-grey-50: #fafafa;
--md-grey-100: #f5f5f5;
--md-grey-200: #eee;
--md-grey-300: #e0e0e0;
--md-grey-400: #bdbdbd;
--md-grey-500: #9e9e9e;
--md-grey-600: #757575;
--md-grey-700: #616161;
--md-grey-800: #424242;
--md-grey-900: #212121;
--md-blue-grey-50: #eceff1;
--md-blue-grey-100: #cfd8dc;
--md-blue-grey-200: #b0bec5;
--md-blue-grey-300: #90a4ae;
--md-blue-grey-400: #78909c;
--md-blue-grey-500: #607d8b;
--md-blue-grey-600: #546e7a;
--md-blue-grey-700: #455a64;
--md-blue-grey-800: #37474f;
--md-blue-grey-900: #263238;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| RenderedText
|----------------------------------------------------------------------------*/
:root {
/* This is the padding value to fill the gaps between lines containing spans with background color. */
--jp-private-code-span-padding: calc(
(var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
);
}
.jp-RenderedText {
text-align: left;
padding-left: var(--jp-code-padding);
line-height: var(--jp-code-line-height);
font-family: var(--jp-code-font-family);
}
.jp-RenderedText pre,
.jp-RenderedJavaScript pre,
.jp-RenderedHTMLCommon pre {
color: var(--jp-content-font-color1);
font-size: var(--jp-code-font-size);
border: none;
margin: 0;
padding: 0;
}
.jp-RenderedText pre a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* console foregrounds and backgrounds */
.jp-RenderedText pre .ansi-black-fg {
color: #3e424d;
}
.jp-RenderedText pre .ansi-red-fg {
color: #e75c58;
}
.jp-RenderedText pre .ansi-green-fg {
color: #00a250;
}
.jp-RenderedText pre .ansi-yellow-fg {
color: #ddb62b;
}
.jp-RenderedText pre .ansi-blue-fg {
color: #208ffb;
}
.jp-RenderedText pre .ansi-magenta-fg {
color: #d160c4;
}
.jp-RenderedText pre .ansi-cyan-fg {
color: #60c6c8;
}
.jp-RenderedText pre .ansi-white-fg {
color: #c5c1b4;
}
.jp-RenderedText pre .ansi-black-bg {
background-color: #3e424d;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-bg {
background-color: #e75c58;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-bg {
background-color: #00a250;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-bg {
background-color: #ddb62b;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-bg {
background-color: #208ffb;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-bg {
background-color: #d160c4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-bg {
background-color: #60c6c8;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-bg {
background-color: #c5c1b4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-black-intense-fg {
color: #282c36;
}
.jp-RenderedText pre .ansi-red-intense-fg {
color: #b22b31;
}
.jp-RenderedText pre .ansi-green-intense-fg {
color: #007427;
}
.jp-RenderedText pre .ansi-yellow-intense-fg {
color: #b27d12;
}
.jp-RenderedText pre .ansi-blue-intense-fg {
color: #0065ca;
}
.jp-RenderedText pre .ansi-magenta-intense-fg {
color: #a03196;
}
.jp-RenderedText pre .ansi-cyan-intense-fg {
color: #258f8f;
}
.jp-RenderedText pre .ansi-white-intense-fg {
color: #a1a6b2;
}
.jp-RenderedText pre .ansi-black-intense-bg {
background-color: #282c36;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-intense-bg {
background-color: #b22b31;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-intense-bg {
background-color: #007427;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-intense-bg {
background-color: #b27d12;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-intense-bg {
background-color: #0065ca;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-intense-bg {
background-color: #a03196;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-intense-bg {
background-color: #258f8f;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-intense-bg {
background-color: #a1a6b2;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-default-inverse-fg {
color: var(--jp-ui-inverse-font-color0);
}
.jp-RenderedText pre .ansi-default-inverse-bg {
background-color: var(--jp-inverse-layout-color0);
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-bold {
font-weight: bold;
}
.jp-RenderedText pre .ansi-underline {
text-decoration: underline;
}
.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
background: var(--jp-rendermime-error-background);
padding-top: var(--jp-code-padding);
}
/*-----------------------------------------------------------------------------
| RenderedLatex
|----------------------------------------------------------------------------*/
.jp-RenderedLatex {
color: var(--jp-content-font-color1);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
}
/* Left-justify outputs.*/
.jp-OutputArea-output.jp-RenderedLatex {
padding: var(--jp-code-padding);
text-align: left;
}
/*-----------------------------------------------------------------------------
| RenderedHTML
|----------------------------------------------------------------------------*/
.jp-RenderedHTMLCommon {
color: var(--jp-content-font-color1);
font-family: var(--jp-content-font-family);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
/* Give a bit more R padding on Markdown text to keep line lengths reasonable */
padding-right: 20px;
}
.jp-RenderedHTMLCommon em {
font-style: italic;
}
.jp-RenderedHTMLCommon strong {
font-weight: bold;
}
.jp-RenderedHTMLCommon u {
text-decoration: underline;
}
.jp-RenderedHTMLCommon a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* Headings */
.jp-RenderedHTMLCommon h1,
.jp-RenderedHTMLCommon h2,
.jp-RenderedHTMLCommon h3,
.jp-RenderedHTMLCommon h4,
.jp-RenderedHTMLCommon h5,
.jp-RenderedHTMLCommon h6 {
line-height: var(--jp-content-heading-line-height);
font-weight: var(--jp-content-heading-font-weight);
font-style: normal;
margin: var(--jp-content-heading-margin-top) 0
var(--jp-content-heading-margin-bottom) 0;
}
.jp-RenderedHTMLCommon h1:first-child,
.jp-RenderedHTMLCommon h2:first-child,
.jp-RenderedHTMLCommon h3:first-child,
.jp-RenderedHTMLCommon h4:first-child,
.jp-RenderedHTMLCommon h5:first-child,
.jp-RenderedHTMLCommon h6:first-child {
margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
}
.jp-RenderedHTMLCommon h1:last-child,
.jp-RenderedHTMLCommon h2:last-child,
.jp-RenderedHTMLCommon h3:last-child,
.jp-RenderedHTMLCommon h4:last-child,
.jp-RenderedHTMLCommon h5:last-child,
.jp-RenderedHTMLCommon h6:last-child {
margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
}
.jp-RenderedHTMLCommon h1 {
font-size: var(--jp-content-font-size5);
}
.jp-RenderedHTMLCommon h2 {
font-size: var(--jp-content-font-size4);
}
.jp-RenderedHTMLCommon h3 {
font-size: var(--jp-content-font-size3);
}
.jp-RenderedHTMLCommon h4 {
font-size: var(--jp-content-font-size2);
}
.jp-RenderedHTMLCommon h5 {
font-size: var(--jp-content-font-size1);
}
.jp-RenderedHTMLCommon h6 {
font-size: var(--jp-content-font-size0);
}
/* Lists */
/* stylelint-disable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon ul:not(.list-inline),
.jp-RenderedHTMLCommon ol:not(.list-inline) {
padding-left: 2em;
}
.jp-RenderedHTMLCommon ul {
list-style: disc;
}
.jp-RenderedHTMLCommon ul ul {
list-style: square;
}
.jp-RenderedHTMLCommon ul ul ul {
list-style: circle;
}
.jp-RenderedHTMLCommon ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol ol {
list-style: upper-alpha;
}
.jp-RenderedHTMLCommon ol ol ol {
list-style: lower-alpha;
}
.jp-RenderedHTMLCommon ol ol ol ol {
list-style: lower-roman;
}
.jp-RenderedHTMLCommon ol ol ol ol ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol,
.jp-RenderedHTMLCommon ul {
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon ul ul,
.jp-RenderedHTMLCommon ul ol,
.jp-RenderedHTMLCommon ol ul,
.jp-RenderedHTMLCommon ol ol {
margin-bottom: 0;
}
/* stylelint-enable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon hr {
color: var(--jp-border-color2);
background-color: var(--jp-border-color1);
margin-top: 1em;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon > pre {
margin: 1.5em 2em;
}
.jp-RenderedHTMLCommon pre,
.jp-RenderedHTMLCommon code {
border: 0;
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
font-family: var(--jp-code-font-family);
font-size: inherit;
line-height: var(--jp-code-line-height);
padding: 0;
white-space: pre-wrap;
}
.jp-RenderedHTMLCommon :not(pre) > code {
background-color: var(--jp-layout-color2);
padding: 1px 5px;
}
/* Tables */
.jp-RenderedHTMLCommon table {
border-collapse: collapse;
border-spacing: 0;
border: none;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
table-layout: fixed;
margin-left: auto;
margin-bottom: 1em;
margin-right: auto;
}
.jp-RenderedHTMLCommon thead {
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
vertical-align: bottom;
}
.jp-RenderedHTMLCommon td,
.jp-RenderedHTMLCommon th,
.jp-RenderedHTMLCommon tr {
vertical-align: middle;
padding: 0.5em;
line-height: normal;
white-space: normal;
max-width: none;
border: none;
}
.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
max-width: none;
}
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
text-align: right;
}
.jp-RenderedHTMLCommon th {
font-weight: bold;
}
.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
background: var(--jp-layout-color0);
}
.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
background: var(--jp-rendermime-table-row-background);
}
.jp-RenderedHTMLCommon tbody tr:hover {
background: var(--jp-rendermime-table-row-hover-background);
}
.jp-RenderedHTMLCommon p {
text-align: left;
margin: 0;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon img {
-moz-force-broken-image-icon: 1;
}
/* Restrict to direct children as other images could be nested in other content. */
.jp-RenderedHTMLCommon > img {
display: block;
margin-left: 0;
margin-right: 0;
margin-bottom: 1em;
}
/* Change color behind transparent images if they need it... */
[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
background-color: var(--jp-inverse-layout-color1);
}
[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
background-color: var(--jp-inverse-layout-color1);
}
.jp-RenderedHTMLCommon img,
.jp-RenderedImage img,
.jp-RenderedHTMLCommon svg,
.jp-RenderedSVG svg {
max-width: 100%;
height: auto;
}
.jp-RenderedHTMLCommon img.jp-mod-unconfined,
.jp-RenderedImage img.jp-mod-unconfined,
.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
.jp-RenderedSVG svg.jp-mod-unconfined {
max-width: none;
}
.jp-RenderedHTMLCommon .alert {
padding: var(--jp-notebook-padding);
border: var(--jp-border-width) solid transparent;
border-radius: var(--jp-border-radius);
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon .alert-info {
color: var(--jp-info-color0);
background-color: var(--jp-info-color3);
border-color: var(--jp-info-color2);
}
.jp-RenderedHTMLCommon .alert-info hr {
border-color: var(--jp-info-color3);
}
.jp-RenderedHTMLCommon .alert-info > p:last-child,
.jp-RenderedHTMLCommon .alert-info > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-warning {
color: var(--jp-warn-color0);
background-color: var(--jp-warn-color3);
border-color: var(--jp-warn-color2);
}
.jp-RenderedHTMLCommon .alert-warning hr {
border-color: var(--jp-warn-color3);
}
.jp-RenderedHTMLCommon .alert-warning > p:last-child,
.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-success {
color: var(--jp-success-color0);
background-color: var(--jp-success-color3);
border-color: var(--jp-success-color2);
}
.jp-RenderedHTMLCommon .alert-success hr {
border-color: var(--jp-success-color3);
}
.jp-RenderedHTMLCommon .alert-success > p:last-child,
.jp-RenderedHTMLCommon .alert-success > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-danger {
color: var(--jp-error-color0);
background-color: var(--jp-error-color3);
border-color: var(--jp-error-color2);
}
.jp-RenderedHTMLCommon .alert-danger hr {
border-color: var(--jp-error-color3);
}
.jp-RenderedHTMLCommon .alert-danger > p:last-child,
.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon blockquote {
margin: 1em 2em;
padding: 0 1em;
border-left: 5px solid var(--jp-border-color2);
}
a.jp-InternalAnchorLink {
visibility: hidden;
margin-left: 8px;
color: var(--md-blue-800);
}
h1:hover .jp-InternalAnchorLink,
h2:hover .jp-InternalAnchorLink,
h3:hover .jp-InternalAnchorLink,
h4:hover .jp-InternalAnchorLink,
h5:hover .jp-InternalAnchorLink,
h6:hover .jp-InternalAnchorLink {
visibility: visible;
}
.jp-RenderedHTMLCommon kbd {
background-color: var(--jp-rendermime-table-row-background);
border: 1px solid var(--jp-border-color0);
border-bottom-color: var(--jp-border-color2);
border-radius: 3px;
box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
display: inline-block;
font-size: var(--jp-ui-font-size0);
line-height: 1em;
padding: 0.2em 0.5em;
}
/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
* At the bottom of cells this is a bit too much as there is also spacing
* between cells. Going all the way to 0 gets too tight between markdown and
* code cells.
*/
.jp-RenderedHTMLCommon > *:last-child {
margin-bottom: 0.5em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Copyright (c) 2014-2017, PhosphorJS Contributors
|
| Distributed under the terms of the BSD 3-Clause License.
|
| The full license is in the file LICENSE, distributed with this software.
|----------------------------------------------------------------------------*/
.lm-cursor-backdrop {
position: fixed;
width: 200px;
height: 200px;
margin-top: -100px;
margin-left: -100px;
will-change: transform;
z-index: 100;
}
.lm-mod-drag-image {
will-change: transform;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-lineFormSearch {
padding: 4px 12px;
background-color: var(--jp-layout-color2);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
font-size: var(--jp-ui-font-size1);
}
.jp-lineFormCaption {
font-size: var(--jp-ui-font-size0);
line-height: var(--jp-ui-font-size1);
margin-top: 4px;
color: var(--jp-ui-font-color0);
}
.jp-baseLineForm {
border: none;
border-radius: 0;
position: absolute;
background-size: 16px;
background-repeat: no-repeat;
background-position: center;
outline: none;
}
.jp-lineFormButtonContainer {
top: 4px;
right: 8px;
height: 24px;
padding: 0 12px;
width: 12px;
}
.jp-lineFormButtonIcon {
top: 0;
right: 0;
background-color: var(--jp-brand-color1);
height: 100%;
width: 100%;
box-sizing: border-box;
padding: 4px 6px;
}
.jp-lineFormButton {
top: 0;
right: 0;
background-color: transparent;
height: 100%;
width: 100%;
box-sizing: border-box;
}
.jp-lineFormWrapper {
overflow: hidden;
padding: 0 8px;
border: 1px solid var(--jp-border-color0);
background-color: var(--jp-input-active-background);
height: 22px;
}
.jp-lineFormWrapperFocusWithin {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-lineFormInput {
background: transparent;
width: 200px;
height: 100%;
border: none;
outline: none;
color: var(--jp-ui-font-color0);
line-height: 28px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-JSONEditor {
display: flex;
flex-direction: column;
width: 100%;
}
.jp-JSONEditor-host {
flex: 1 1 auto;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
background: var(--jp-layout-color0);
min-height: 50px;
padding: 1px;
}
.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
border-color: red;
outline-color: red;
}
.jp-JSONEditor-header {
display: flex;
flex: 1 0 auto;
padding: 0 0 0 12px;
}
.jp-JSONEditor-header label {
flex: 0 0 auto;
}
.jp-JSONEditor-commitButton {
height: 16px;
width: 16px;
background-size: 18px;
background-repeat: no-repeat;
background-position: center;
}
.jp-JSONEditor-host.jp-mod-focused {
background-color: var(--jp-input-active-background);
border: 1px solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
.jp-Editor.jp-mod-dropTarget {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-DocumentSearch-input {
border: none;
outline: none;
color: var(--jp-ui-font-color0);
font-size: var(--jp-ui-font-size1);
background-color: var(--jp-layout-color0);
font-family: var(--jp-ui-font-family);
padding: 2px 1px;
resize: none;
}
.jp-DocumentSearch-overlay {
position: absolute;
background-color: var(--jp-toolbar-background);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
top: 0;
right: 0;
z-index: 7;
min-width: 405px;
padding: 2px;
font-size: var(--jp-ui-font-size1);
--jp-private-document-search-button-height: 20px;
}
.jp-DocumentSearch-overlay button {
background-color: var(--jp-toolbar-background);
outline: 0;
}
.jp-DocumentSearch-overlay button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-overlay button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-overlay-row {
display: flex;
align-items: center;
margin-bottom: 2px;
}
.jp-DocumentSearch-button-content {
display: inline-block;
cursor: pointer;
box-sizing: border-box;
width: 100%;
height: 100%;
}
.jp-DocumentSearch-button-content svg {
width: 100%;
height: 100%;
}
.jp-DocumentSearch-input-wrapper {
border: var(--jp-border-width) solid var(--jp-border-color0);
display: flex;
background-color: var(--jp-layout-color0);
margin: 2px;
}
.jp-DocumentSearch-input-wrapper:focus-within {
border-color: var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper {
all: initial;
overflow: hidden;
display: inline-block;
border: none;
box-sizing: border-box;
}
.jp-DocumentSearch-toggle-wrapper {
width: 14px;
height: 14px;
}
.jp-DocumentSearch-button-wrapper {
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
}
.jp-DocumentSearch-toggle-wrapper:focus,
.jp-DocumentSearch-button-wrapper:focus {
outline: var(--jp-border-width) solid
var(--jp-cell-editor-active-border-color);
outline-offset: -1px;
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper,
.jp-DocumentSearch-button-content:focus {
outline: none;
}
.jp-DocumentSearch-toggle-placeholder {
width: 5px;
}
.jp-DocumentSearch-input-button::before {
display: block;
padding-top: 100%;
}
.jp-DocumentSearch-input-button-off {
opacity: var(--jp-search-toggle-off-opacity);
}
.jp-DocumentSearch-input-button-off:hover {
opacity: var(--jp-search-toggle-hover-opacity);
}
.jp-DocumentSearch-input-button-on {
opacity: var(--jp-search-toggle-on-opacity);
}
.jp-DocumentSearch-index-counter {
padding-left: 10px;
padding-right: 10px;
user-select: none;
min-width: 35px;
display: inline-block;
}
.jp-DocumentSearch-up-down-wrapper {
display: inline-block;
padding-right: 2px;
margin-left: auto;
white-space: nowrap;
}
.jp-DocumentSearch-spacer {
margin-left: auto;
}
.jp-DocumentSearch-up-down-wrapper button {
outline: 0;
border: none;
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
vertical-align: middle;
margin: 1px 5px 2px;
}
.jp-DocumentSearch-up-down-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-up-down-button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-filter-button {
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-filter-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled:hover {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-search-options {
padding: 0 8px;
margin-left: 3px;
width: 100%;
display: grid;
justify-content: start;
grid-template-columns: 1fr 1fr;
align-items: center;
justify-items: stretch;
}
.jp-DocumentSearch-search-filter-disabled {
color: var(--jp-ui-font-color2);
}
.jp-DocumentSearch-search-filter {
display: flex;
align-items: center;
user-select: none;
}
.jp-DocumentSearch-regex-error {
color: var(--jp-error-color0);
}
.jp-DocumentSearch-replace-button-wrapper {
overflow: hidden;
display: inline-block;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color0);
margin: auto 2px;
padding: 1px 4px;
height: calc(var(--jp-private-document-search-button-height) + 2px);
}
.jp-DocumentSearch-replace-button-wrapper:focus {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-replace-button {
display: inline-block;
text-align: center;
cursor: pointer;
box-sizing: border-box;
color: var(--jp-ui-font-color1);
/* height - 2 * (padding of wrapper) */
line-height: calc(var(--jp-private-document-search-button-height) - 2px);
width: 100%;
height: 100%;
}
.jp-DocumentSearch-replace-button:focus {
outline: none;
}
.jp-DocumentSearch-replace-wrapper-class {
margin-left: 14px;
display: flex;
}
.jp-DocumentSearch-replace-toggle {
border: none;
background-color: var(--jp-toolbar-background);
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-replace-toggle:hover {
background-color: var(--jp-layout-color2);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.cm-editor {
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
border: 0;
border-radius: 0;
height: auto;
/* Changed to auto to autogrow */
}
.cm-editor pre {
padding: 0 var(--jp-code-padding);
}
.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
}
.jp-CodeMirrorEditor {
cursor: text;
}
/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
@media screen and (min-width: 2138px) and (max-width: 4319px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width1) solid
var(--jp-editor-cursor-color);
}
}
/* When zoomed out less than 33% */
@media screen and (min-width: 4320px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width2) solid
var(--jp-editor-cursor-color);
}
}
.cm-editor.jp-mod-readOnly .cm-cursor {
display: none;
}
.jp-CollaboratorCursor {
border-left: 5px solid transparent;
border-right: 5px solid transparent;
border-top: none;
border-bottom: 3px solid;
background-clip: content-box;
margin-left: -5px;
margin-right: -5px;
}
.cm-searching,
.cm-searching span {
/* `.cm-searching span`: we need to override syntax highlighting */
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.cm-searching::selection,
.cm-searching span::selection {
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.jp-current-match > .cm-searching,
.jp-current-match > .cm-searching span,
.cm-searching > .jp-current-match,
.cm-searching > .jp-current-match span {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.jp-current-match > .cm-searching::selection,
.cm-searching > .jp-current-match::selection,
.jp-current-match > .cm-searching span::selection {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.cm-trailingspace {
background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
background-position: center left;
background-repeat: repeat-x;
}
.jp-CollaboratorCursor-hover {
position: absolute;
z-index: 1;
transform: translateX(-50%);
color: white;
border-radius: 3px;
padding-left: 4px;
padding-right: 4px;
padding-top: 1px;
padding-bottom: 1px;
text-align: center;
font-size: var(--jp-ui-font-size1);
white-space: nowrap;
}
.jp-CodeMirror-ruler {
border-left: 1px dashed var(--jp-border-color2);
}
/* Styles for shared cursors (remote cursor locations and selected ranges) */
.jp-CodeMirrorEditor .cm-ySelectionCaret {
position: relative;
border-left: 1px solid black;
margin-left: -1px;
margin-right: -1px;
box-sizing: border-box;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
white-space: nowrap;
position: absolute;
top: -1.15em;
padding-bottom: 0.05em;
left: -1px;
font-size: 0.95em;
font-family: var(--jp-ui-font-family);
font-weight: bold;
line-height: normal;
user-select: none;
color: white;
padding-left: 2px;
padding-right: 2px;
z-index: 101;
transition: opacity 0.3s ease-in-out;
}
.jp-CodeMirrorEditor .cm-ySelectionInfo {
transition-delay: 0.7s;
opacity: 0;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
opacity: 1;
transition-delay: 0s;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MimeDocument {
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-filebrowser-button-height: 28px;
--jp-private-filebrowser-button-width: 48px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FileBrowser .jp-SidePanel-content {
display: flex;
flex-direction: column;
}
.jp-FileBrowser-toolbar.jp-Toolbar {
flex-wrap: wrap;
row-gap: 12px;
border-bottom: none;
height: auto;
margin: 8px 12px 0;
box-shadow: none;
padding: 0;
justify-content: flex-start;
}
.jp-FileBrowser-Panel {
flex: 1 1 auto;
display: flex;
flex-direction: column;
}
.jp-BreadCrumbs {
flex: 0 0 auto;
margin: 8px 12px;
}
.jp-BreadCrumbs-item {
margin: 0 2px;
padding: 0 2px;
border-radius: var(--jp-border-radius);
cursor: pointer;
}
.jp-BreadCrumbs-item:hover {
background-color: var(--jp-layout-color2);
}
.jp-BreadCrumbs-item:first-child {
margin-left: 0;
}
.jp-BreadCrumbs-item.jp-mod-dropTarget {
background-color: var(--jp-brand-color2);
opacity: 0.7;
}
/*-----------------------------------------------------------------------------
| Buttons
|----------------------------------------------------------------------------*/
.jp-FileBrowser-toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
padding-left: 0;
padding-right: 2px;
align-items: center;
height: unset;
}
.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
width: 40px;
}
/*-----------------------------------------------------------------------------
| Other styles
|----------------------------------------------------------------------------*/
.jp-FileDialog.jp-mod-conflict input {
color: var(--jp-error-color1);
}
.jp-FileDialog .jp-new-name-title {
margin-top: 12px;
}
.jp-LastModified-hidden {
display: none;
}
.jp-FileSize-hidden {
display: none;
}
.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
display: none;
}
/*-----------------------------------------------------------------------------
| DirListing
|----------------------------------------------------------------------------*/
.jp-DirListing {
flex: 1 1 auto;
display: flex;
flex-direction: column;
outline: 0;
}
.jp-DirListing-header {
flex: 0 0 auto;
display: flex;
flex-direction: row;
align-items: center;
overflow: hidden;
border-top: var(--jp-border-width) solid var(--jp-border-color2);
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
}
.jp-DirListing-headerItem {
padding: 4px 12px 2px;
font-weight: 500;
}
.jp-DirListing-headerItem:hover {
background: var(--jp-layout-color2);
}
.jp-DirListing-headerItem.jp-id-name {
flex: 1 0 84px;
}
.jp-DirListing-headerItem.jp-id-modified {
flex: 0 0 112px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-DirListing-headerItem.jp-id-filesize {
flex: 0 0 75px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-id-narrow {
display: none;
flex: 0 0 5px;
padding: 4px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
color: var(--jp-border-color2);
}
.jp-DirListing-narrow .jp-id-narrow {
display: block;
}
.jp-DirListing-narrow .jp-id-modified,
.jp-DirListing-narrow .jp-DirListing-itemModified {
display: none;
}
.jp-DirListing-headerItem.jp-mod-selected {
font-weight: 600;
}
/* increase specificity to override bundled default */
.jp-DirListing-content {
flex: 1 1 auto;
margin: 0;
padding: 0;
list-style-type: none;
overflow: auto;
background-color: var(--jp-layout-color1);
}
.jp-DirListing-content mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
color: var(--jp-ui-inverse-font-color0);
}
/* Style the directory listing content when a user drops a file to upload */
.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
outline: 5px dashed rgba(128, 128, 128, 0.5);
outline-offset: -10px;
cursor: copy;
}
.jp-DirListing-item {
display: flex;
flex-direction: row;
align-items: center;
padding: 4px 12px;
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-DirListing-checkboxWrapper {
/* Increases hit area of checkbox. */
padding: 4px;
}
.jp-DirListing-header
.jp-DirListing-checkboxWrapper
+ .jp-DirListing-headerItem {
padding-left: 4px;
}
.jp-DirListing-content .jp-DirListing-checkboxWrapper {
position: relative;
left: -4px;
margin: -4px 0 -4px -8px;
}
.jp-DirListing-checkboxWrapper.jp-mod-visible {
visibility: visible;
}
/* For devices that support hovering, hide checkboxes until hovered, selected...
*/
@media (hover: hover) {
.jp-DirListing-checkboxWrapper {
visibility: hidden;
}
.jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
.jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
visibility: visible;
}
}
.jp-DirListing-item[data-is-dot] {
opacity: 75%;
}
.jp-DirListing-item.jp-mod-selected {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.jp-DirListing-item.jp-mod-dropTarget {
background: var(--jp-brand-color3);
}
.jp-DirListing-item:hover:not(.jp-mod-selected) {
background: var(--jp-layout-color2);
}
.jp-DirListing-itemIcon {
flex: 0 0 20px;
margin-right: 4px;
}
.jp-DirListing-itemText {
flex: 1 0 64px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
user-select: none;
}
.jp-DirListing-itemText:focus {
outline-width: 2px;
outline-color: var(--jp-inverse-layout-color1);
outline-style: solid;
outline-offset: 1px;
}
.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
outline-color: var(--jp-layout-color1);
}
.jp-DirListing-itemModified {
flex: 0 0 125px;
text-align: right;
}
.jp-DirListing-itemFileSize {
flex: 0 0 90px;
text-align: right;
}
.jp-DirListing-editor {
flex: 1 0 64px;
outline: none;
border: none;
color: var(--jp-ui-font-color1);
background-color: var(--jp-layout-color1);
}
.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
color: var(--jp-success-color1);
content: '\25CF';
font-size: 8px;
position: absolute;
left: -8px;
}
.jp-DirListing-item.jp-mod-running.jp-mod-selected
.jp-DirListing-itemIcon::before {
color: var(--jp-ui-inverse-font-color1);
}
.jp-DirListing-item.lm-mod-drag-image,
.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
font-size: var(--jp-ui-font-size1);
padding-left: 4px;
margin-left: 4px;
width: 160px;
background-color: var(--jp-ui-inverse-font-color2);
box-shadow: var(--jp-elevation-z2);
border-radius: 0;
color: var(--jp-ui-font-color1);
transform: translateX(-40%) translateY(-58%);
}
.jp-Document {
min-width: 120px;
min-height: 120px;
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Main OutputArea
| OutputArea has a list of Outputs
|----------------------------------------------------------------------------*/
.jp-OutputArea {
overflow-y: auto;
}
.jp-OutputArea-child {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-OutputPrompt {
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-outprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
opacity: var(--jp-cell-prompt-opacity);
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-OutputArea-prompt {
display: table-cell;
vertical-align: top;
}
.jp-OutputArea-output {
display: table-cell;
width: 100%;
height: auto;
overflow: auto;
user-select: text;
-moz-user-select: text;
-webkit-user-select: text;
-ms-user-select: text;
}
.jp-OutputArea .jp-RenderedText {
padding-left: 1ch;
}
/**
* Prompt overlay.
*/
.jp-OutputArea-promptOverlay {
position: absolute;
top: 0;
width: var(--jp-cell-prompt-width);
height: 100%;
opacity: 0.5;
}
.jp-OutputArea-promptOverlay:hover {
background: var(--jp-layout-color2);
box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
cursor: zoom-out;
}
.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
cursor: zoom-in;
}
/**
* Isolated output.
*/
.jp-OutputArea-output.jp-mod-isolated {
width: 100%;
display: block;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
position: relative;
}
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/* pre */
.jp-OutputArea-output pre {
border: none;
margin: 0;
padding: 0;
overflow-x: auto;
overflow-y: auto;
word-break: break-all;
word-wrap: break-word;
white-space: pre-wrap;
}
/* tables */
.jp-OutputArea-output.jp-RenderedHTMLCommon table {
margin-left: 0;
margin-right: 0;
}
/* description lists */
.jp-OutputArea-output dl,
.jp-OutputArea-output dt,
.jp-OutputArea-output dd {
display: block;
}
.jp-OutputArea-output dl {
width: 100%;
overflow: hidden;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dt {
font-weight: bold;
float: left;
width: 20%;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dd {
float: left;
width: 80%;
padding: 0;
margin: 0;
}
.jp-TrimmedOutputs pre {
background: var(--jp-layout-color3);
font-size: calc(var(--jp-code-font-size) * 1.4);
text-align: center;
text-transform: uppercase;
}
/* Hide the gutter in case of
* - nested output areas (e.g. in the case of output widgets)
* - mirrored output areas
*/
.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
display: none;
}
/* Hide empty lines in the output area, for instance due to cleared widgets */
.jp-OutputArea-prompt:empty {
padding: 0;
border: 0;
}
/*-----------------------------------------------------------------------------
| executeResult is added to any Output-result for the display of the object
| returned by a cell
|----------------------------------------------------------------------------*/
.jp-OutputArea-output.jp-OutputArea-executeResult {
margin-left: 0;
width: 100%;
}
/* Text output with the Out[] prompt needs a top padding to match the
* alignment of the Out[] prompt itself.
*/
.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
padding-top: var(--jp-code-padding);
border-top: var(--jp-border-width) solid transparent;
}
/*-----------------------------------------------------------------------------
| The Stdin output
|----------------------------------------------------------------------------*/
.jp-Stdin-prompt {
color: var(--jp-content-font-color0);
padding-right: var(--jp-code-padding);
vertical-align: baseline;
flex: 0 0 auto;
}
.jp-Stdin-input {
font-family: var(--jp-code-font-family);
font-size: inherit;
color: inherit;
background-color: inherit;
width: 42%;
min-width: 200px;
/* make sure input baseline aligns with prompt */
vertical-align: baseline;
/* padding + margin = 0.5em between prompt and cursor */
padding: 0 0.25em;
margin: 0 0.25em;
flex: 0 0 70%;
}
.jp-Stdin-input::placeholder {
opacity: 0;
}
.jp-Stdin-input:focus {
box-shadow: none;
}
.jp-Stdin-input:focus::placeholder {
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Output Area View
|----------------------------------------------------------------------------*/
.jp-LinkedOutputView .jp-OutputArea {
height: 100%;
display: block;
}
.jp-LinkedOutputView .jp-OutputArea-output:only-child {
height: 100%;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
@media print {
.jp-OutputArea-child {
break-inside: avoid-page;
}
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-OutputPrompt {
display: table-row;
text-align: left;
}
.jp-OutputArea-child .jp-OutputArea-output {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
}
/* Trimmed outputs warning */
.jp-TrimmedOutputs > a {
margin: 10px;
text-decoration: none;
cursor: pointer;
}
.jp-TrimmedOutputs > a:hover {
text-decoration: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Table of Contents
|----------------------------------------------------------------------------*/
:root {
--jp-private-toc-active-width: 4px;
}
.jp-TableOfContents {
display: flex;
flex-direction: column;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
height: 100%;
}
.jp-TableOfContents-placeholder {
text-align: center;
}
.jp-TableOfContents-placeholderContent {
color: var(--jp-content-font-color2);
padding: 8px;
}
.jp-TableOfContents-placeholderContent > h3 {
margin-bottom: var(--jp-content-heading-margin-bottom);
}
.jp-TableOfContents .jp-SidePanel-content {
overflow-y: auto;
}
.jp-TableOfContents-tree {
margin: 4px;
}
.jp-TableOfContents ol {
list-style-type: none;
}
/* stylelint-disable-next-line selector-max-type */
.jp-TableOfContents li > ol {
/* Align left border with triangle icon center */
padding-left: 11px;
}
.jp-TableOfContents-content {
/* left margin for the active heading indicator */
margin: 0 0 0 var(--jp-private-toc-active-width);
padding: 0;
background-color: var(--jp-layout-color1);
}
.jp-tocItem {
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-tocItem-heading {
display: flex;
cursor: pointer;
}
.jp-tocItem-heading:hover {
background-color: var(--jp-layout-color2);
}
.jp-tocItem-content {
display: block;
padding: 4px 0;
white-space: nowrap;
text-overflow: ellipsis;
overflow-x: hidden;
}
.jp-tocItem-collapser {
height: 20px;
margin: 2px 2px 0;
padding: 0;
background: none;
border: none;
cursor: pointer;
}
.jp-tocItem-collapser:hover {
background-color: var(--jp-layout-color3);
}
/* Active heading indicator */
.jp-tocItem-heading::before {
content: ' ';
background: transparent;
width: var(--jp-private-toc-active-width);
height: 24px;
position: absolute;
left: 0;
border-radius: var(--jp-border-radius);
}
.jp-tocItem-heading.jp-tocItem-active::before {
background-color: var(--jp-brand-color1);
}
.jp-tocItem-heading:hover.jp-tocItem-active::before {
background: var(--jp-brand-color0);
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Collapser {
flex: 0 0 var(--jp-cell-collapser-width);
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
border-radius: var(--jp-border-radius);
opacity: 1;
}
.jp-Collapser-child {
display: block;
width: 100%;
box-sizing: border-box;
/* height: 100% doesn't work because the height of its parent is computed from content */
position: absolute;
top: 0;
bottom: 0;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Hiding collapsers in print mode.
Note: input and output wrappers have "display: block" propery in print mode.
*/
@media print {
.jp-Collapser {
display: none;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Header/Footer
|----------------------------------------------------------------------------*/
/* Hidden by zero height by default */
.jp-CellHeader,
.jp-CellFooter {
height: 0;
width: 100%;
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Input
|----------------------------------------------------------------------------*/
/* All input areas */
.jp-InputArea {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-InputArea-editor {
display: table-cell;
overflow: hidden;
vertical-align: top;
/* This is the non-active, default styling */
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
background: var(--jp-cell-editor-background);
}
.jp-InputPrompt {
display: table-cell;
vertical-align: top;
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-inprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
opacity: var(--jp-cell-prompt-opacity);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-InputArea-editor {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
.jp-InputPrompt {
display: table-row;
text-align: left;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Placeholder {
display: table;
table-layout: fixed;
width: 100%;
}
.jp-Placeholder-prompt {
display: table-cell;
box-sizing: border-box;
}
.jp-Placeholder-content {
display: table-cell;
padding: 4px 6px;
border: 1px solid transparent;
border-radius: 0;
background: none;
box-sizing: border-box;
cursor: pointer;
}
.jp-Placeholder-contentContainer {
display: flex;
}
.jp-Placeholder-content:hover,
.jp-InputPlaceholder > .jp-Placeholder-content:hover {
border-color: var(--jp-layout-color3);
}
.jp-Placeholder-content .jp-MoreHorizIcon {
width: 32px;
height: 16px;
border: 1px solid transparent;
border-radius: var(--jp-border-radius);
}
.jp-Placeholder-content .jp-MoreHorizIcon:hover {
border: 1px solid var(--jp-border-color1);
box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
background-color: var(--jp-layout-color0);
}
.jp-PlaceholderText {
white-space: nowrap;
overflow-x: hidden;
color: var(--jp-inverse-layout-color3);
font-family: var(--jp-code-font-family);
}
.jp-InputPlaceholder > .jp-Placeholder-content {
border-color: var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Private CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-cell-scrolling-output-offset: 5px;
}
/*-----------------------------------------------------------------------------
| Cell
|----------------------------------------------------------------------------*/
.jp-Cell {
padding: var(--jp-cell-padding);
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Common input/output
|----------------------------------------------------------------------------*/
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: flex;
flex-direction: row;
padding: 0;
margin: 0;
/* Added to reveal the box-shadow on the input and output collapsers. */
overflow: visible;
}
/* Only input/output areas inside cells */
.jp-Cell-inputArea,
.jp-Cell-outputArea {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Collapser
|----------------------------------------------------------------------------*/
/* Make the output collapser disappear when there is not output, but do so
* in a manner that leaves it in the layout and preserves its width.
*/
.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
border: none !important;
background: transparent !important;
}
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
min-height: var(--jp-cell-collapser-min-height);
}
/*-----------------------------------------------------------------------------
| Output
|----------------------------------------------------------------------------*/
/* Put a space between input and output when there IS output */
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
margin-top: 5px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
overflow-y: auto;
max-height: 24em;
margin-left: var(--jp-private-cell-scrolling-output-offset);
resize: vertical;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
max-height: unset;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
content: ' ';
box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
width: 100%;
height: 100%;
position: sticky;
bottom: 0;
top: 0;
margin-top: -50%;
float: left;
display: block;
pointer-events: none;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
padding-top: 6px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
width: calc(
var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
);
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
}
/*-----------------------------------------------------------------------------
| CodeCell
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| MarkdownCell
|----------------------------------------------------------------------------*/
.jp-MarkdownOutput {
display: table-cell;
width: 100%;
margin-top: 0;
margin-bottom: 0;
padding-left: var(--jp-code-padding);
}
.jp-MarkdownOutput.jp-RenderedHTMLCommon {
overflow: auto;
}
/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
.jp-collapseHeadingButton {
display: flex;
min-height: var(--jp-cell-collapser-min-height);
font-size: var(--jp-code-font-size);
position: absolute;
background-color: transparent;
background-size: 25px;
background-repeat: no-repeat;
background-position-x: center;
background-position-y: top;
background-image: var(--jp-icon-caret-down);
right: 0;
top: 0;
bottom: 0;
}
.jp-collapseHeadingButton.jp-mod-collapsed {
background-image: var(--jp-icon-caret-right);
}
/*
set the container font size to match that of content
so that the nested collapse buttons have the right size
*/
.jp-MarkdownCell .jp-InputPrompt {
font-size: var(--jp-content-font-size1);
}
/*
Align collapseHeadingButton with cell top header
The font sizes are identical to the ones in packages/rendermime/style/base.css
*/
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
font-size: var(--jp-content-font-size5);
background-position-y: calc(0.3 * var(--jp-content-font-size5));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
font-size: var(--jp-content-font-size4);
background-position-y: calc(0.3 * var(--jp-content-font-size4));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
font-size: var(--jp-content-font-size3);
background-position-y: calc(0.3 * var(--jp-content-font-size3));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
font-size: var(--jp-content-font-size2);
background-position-y: calc(0.3 * var(--jp-content-font-size2));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
font-size: var(--jp-content-font-size1);
background-position-y: top;
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
font-size: var(--jp-content-font-size0);
background-position-y: top;
}
/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
display: none;
}
.jp-Notebook.jp-mod-showHiddenCellsButton
:is(.jp-MarkdownCell:hover, .jp-mod-active)
.jp-collapseHeadingButton {
display: flex;
}
/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
margin-top: var(--jp-code-padding);
border: 1px solid var(--jp-border-color2);
background-color: var(--jp-border-color3) !important;
color: var(--jp-content-font-color0) !important;
display: flex;
}
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
background-color: var(--jp-border-color2) !important;
}
.jp-showHiddenCellsButton {
display: none;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Using block instead of flex to allow the use of the break-inside CSS property for
cell outputs.
*/
@media print {
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: block;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-notebook-toolbar-padding: 2px 5px 2px 2px;
}
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-NotebookPanel-toolbar {
padding: var(--jp-notebook-toolbar-padding);
/* disable paint containment from lumino 2.0 default strict CSS containment */
contain: style size !important;
}
.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
border: none;
box-shadow: none;
}
.jp-Notebook-toolbarCellTypeDropdown select {
height: 24px;
font-size: var(--jp-ui-font-size1);
line-height: 14px;
border-radius: 0;
display: block;
}
.jp-Notebook-toolbarCellTypeDropdown span {
top: 5px !important;
}
.jp-Toolbar-responsive-popup {
position: absolute;
height: fit-content;
display: flex;
flex-direction: row;
flex-wrap: wrap;
justify-content: flex-end;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: var(--jp-notebook-toolbar-padding);
z-index: 1;
right: 0;
top: 0;
}
.jp-Toolbar > .jp-Toolbar-responsive-opener {
margin-left: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-Notebook-ExecutionIndicator {
position: relative;
display: inline-block;
height: 100%;
z-index: 9997;
}
.jp-Notebook-ExecutionIndicator-tooltip {
visibility: hidden;
height: auto;
width: max-content;
width: -moz-max-content;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color1);
text-align: justify;
border-radius: 6px;
padding: 0 5px;
position: fixed;
display: table;
}
.jp-Notebook-ExecutionIndicator-tooltip.up {
transform: translateX(-50%) translateY(-100%) translateY(-32px);
}
.jp-Notebook-ExecutionIndicator-tooltip.down {
transform: translateX(calc(-100% + 16px)) translateY(5px);
}
.jp-Notebook-ExecutionIndicator-tooltip.hidden {
display: none;
}
.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
visibility: visible;
}
.jp-Notebook-ExecutionIndicator span {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
color: var(--jp-ui-font-color1);
line-height: 24px;
display: block;
}
.jp-Notebook-ExecutionIndicator-progress-bar {
display: flex;
justify-content: center;
height: 100%;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*
* Execution indicator
*/
.jp-tocItem-content::after {
content: '';
/* Must be identical to form a circle */
width: 12px;
height: 12px;
background: none;
border: none;
position: absolute;
right: 0;
}
.jp-tocItem-content[data-running='0']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background: none;
}
.jp-tocItem-content[data-running='1']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background-color: var(--jp-inverse-layout-color3);
}
.jp-tocItem-content[data-running='0'],
.jp-tocItem-content[data-running='1'] {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Notebook-footer {
height: 27px;
margin-left: calc(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding)
);
width: calc(
100% -
(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding) + var(--jp-cell-padding)
)
);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
color: var(--jp-ui-font-color3);
margin-top: 6px;
background: none;
cursor: pointer;
}
.jp-Notebook-footer:focus {
border-color: var(--jp-cell-editor-active-border-color);
}
/* For devices that support hovering, hide footer until hover */
@media (hover: hover) {
.jp-Notebook-footer {
opacity: 0;
}
.jp-Notebook-footer:focus,
.jp-Notebook-footer:hover {
opacity: 1;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Imports
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-side-by-side-output-size: 1fr;
--jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
--jp-private-notebook-dragImage-width: 304px;
--jp-private-notebook-dragImage-height: 36px;
--jp-private-notebook-selected-color: var(--md-blue-400);
--jp-private-notebook-active-color: var(--md-green-400);
}
/*-----------------------------------------------------------------------------
| Notebook
|----------------------------------------------------------------------------*/
/* stylelint-disable selector-max-class */
.jp-NotebookPanel {
display: block;
height: 100%;
}
.jp-NotebookPanel.jp-Document {
min-width: 240px;
min-height: 120px;
}
.jp-Notebook {
padding: var(--jp-notebook-padding);
outline: none;
overflow: auto;
background: var(--jp-layout-color0);
}
.jp-Notebook.jp-mod-scrollPastEnd::after {
display: block;
content: '';
min-height: var(--jp-notebook-scroll-padding);
}
.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
contain: strict;
}
.jp-Notebook .jp-Cell {
overflow: visible;
}
.jp-Notebook .jp-Cell .jp-InputPrompt {
cursor: move;
}
/*-----------------------------------------------------------------------------
| Notebook state related styling
|
| The notebook and cells each have states, here are the possibilities:
|
| - Notebook
| - Command
| - Edit
| - Cell
| - None
| - Active (only one can be active)
| - Selected (the cells actions are applied to)
| - Multiselected (when multiple selected, the cursor)
| - No outputs
|----------------------------------------------------------------------------*/
/* Command or edit modes */
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
/* cell is active */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
background: var(--jp-brand-color1);
}
/* cell is dirty */
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
color: var(--jp-warn-color1);
}
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
color: var(--jp-warn-color1);
content: '•';
}
.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
background: var(--jp-warn-color1);
}
/* collapser is hovered */
.jp-Notebook .jp-Cell .jp-Collapser:hover {
box-shadow: var(--jp-elevation-z2);
background: var(--jp-brand-color1);
opacity: var(--jp-cell-collapser-not-active-hover-opacity);
}
/* cell is active and collapser is hovered */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
background: var(--jp-brand-color0);
opacity: 1;
}
/* Command mode */
.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
background: var(--jp-notebook-multiselected-color);
}
.jp-Notebook.jp-mod-commandMode
.jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
background: transparent;
}
/* Edit mode */
.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-cell-editor-active-background);
}
/*-----------------------------------------------------------------------------
| Notebook drag and drop
|----------------------------------------------------------------------------*/
.jp-Notebook-cell.jp-mod-dropSource {
opacity: 0.5;
}
.jp-Notebook-cell.jp-mod-dropTarget,
.jp-Notebook.jp-mod-commandMode
.jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
border-top-color: var(--jp-private-notebook-selected-color);
border-top-style: solid;
border-top-width: 2px;
}
.jp-dragImage {
display: block;
flex-direction: row;
width: var(--jp-private-notebook-dragImage-width);
height: var(--jp-private-notebook-dragImage-height);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
overflow: visible;
}
.jp-dragImage-singlePrompt {
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
.jp-dragImage .jp-dragImage-content {
flex: 1 1 auto;
z-index: 2;
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
line-height: var(--jp-code-line-height);
padding: var(--jp-code-padding);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background-color);
color: var(--jp-content-font-color3);
text-align: left;
margin: 4px 4px 4px 0;
}
.jp-dragImage .jp-dragImage-prompt {
flex: 0 0 auto;
min-width: 36px;
color: var(--jp-cell-inprompt-font-color);
padding: var(--jp-code-padding);
padding-left: 12px;
font-family: var(--jp-cell-prompt-font-family);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: 1.9;
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
}
.jp-dragImage-multipleBack {
z-index: -1;
position: absolute;
height: 32px;
width: 300px;
top: 8px;
left: 8px;
background: var(--jp-layout-color2);
border: var(--jp-border-width) solid var(--jp-input-border-color);
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
/*-----------------------------------------------------------------------------
| Cell toolbar
|----------------------------------------------------------------------------*/
.jp-NotebookTools {
display: block;
min-width: var(--jp-sidebar-min-width);
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
overflow: auto;
}
.jp-ActiveCellTool {
padding: 12px 0;
display: flex;
}
.jp-ActiveCellTool-Content {
flex: 1 1 auto;
}
.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
background: var(--jp-cell-editor-background);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
min-height: 29px;
}
.jp-ActiveCellTool .jp-InputPrompt {
min-width: calc(var(--jp-cell-prompt-width) * 0.75);
}
.jp-ActiveCellTool-CellContent > pre {
padding: 5px 4px;
margin: 0;
white-space: normal;
}
.jp-MetadataEditorTool {
flex-direction: column;
padding: 12px 0;
}
.jp-RankedPanel > :not(:first-child) {
margin-top: 12px;
}
.jp-KeySelector select.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: var(--jp-border-width) solid var(--jp-border-color1);
}
.jp-KeySelector label,
.jp-MetadataEditorTool label,
.jp-NumberSetter label {
line-height: 1.4;
}
.jp-NotebookTools .jp-select-wrapper {
margin-top: 4px;
margin-bottom: 0;
}
.jp-NumberSetter input {
width: 100%;
margin-top: 4px;
}
.jp-NotebookTools .jp-Collapse {
margin-top: 16px;
}
/*-----------------------------------------------------------------------------
| Presentation Mode (.jp-mod-presentationMode)
|----------------------------------------------------------------------------*/
.jp-mod-presentationMode .jp-Notebook {
--jp-content-font-size1: var(--jp-content-presentation-font-size1);
--jp-code-font-size: var(--jp-code-presentation-font-size);
}
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
flex: 0 0 110px;
}
/*-----------------------------------------------------------------------------
| Side-by-side Mode (.jp-mod-sideBySide)
|----------------------------------------------------------------------------*/
.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
margin-top: 3em;
margin-bottom: 3em;
margin-left: 5%;
margin-right: 5%;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
display: grid;
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-output-size)
);
grid-template-rows: auto minmax(0, 1fr) auto;
grid-template-areas:
'header header header'
'input handle output'
'footer footer footer';
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-resized-cell)
);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
grid-area: header;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
grid-area: input;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
/* overwrite the default margin (no vertical separation needed in side by side move */
margin-top: 0;
grid-area: output;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
grid-area: footer;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
grid-area: handle;
user-select: none;
display: block;
height: 100%;
cursor: ew-resize;
padding: 0 var(--jp-cell-padding);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
content: '';
display: block;
background: var(--jp-border-color2);
height: 100%;
width: 5px;
}
.jp-mod-sideBySide.jp-Notebook
.jp-CodeCell.jp-mod-resizedCell
.jp-CellResizeHandle::after {
background: var(--jp-border-color0);
}
.jp-CellResizeHandle {
display: none;
}
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Cell-Placeholder {
padding-left: 55px;
}
.jp-Cell-Placeholder-wrapper {
background: #fff;
border: 1px solid;
border-color: #e5e6e9 #dfe0e4 #d0d1d5;
border-radius: 4px;
-webkit-border-radius: 4px;
margin: 10px 15px;
}
.jp-Cell-Placeholder-wrapper-inner {
padding: 15px;
position: relative;
}
.jp-Cell-Placeholder-wrapper-body {
background-repeat: repeat;
background-size: 50% auto;
}
.jp-Cell-Placeholder-wrapper-body div {
background: #f6f7f8;
background-image: -webkit-linear-gradient(
left,
#f6f7f8 0%,
#edeef1 20%,
#f6f7f8 40%,
#f6f7f8 100%
);
background-repeat: no-repeat;
background-size: 800px 104px;
height: 104px;
position: absolute;
right: 15px;
left: 15px;
top: 15px;
}
div.jp-Cell-Placeholder-h1 {
top: 20px;
height: 20px;
left: 15px;
width: 150px;
}
div.jp-Cell-Placeholder-h2 {
left: 15px;
top: 50px;
height: 10px;
width: 100px;
}
div.jp-Cell-Placeholder-content-1,
div.jp-Cell-Placeholder-content-2,
div.jp-Cell-Placeholder-content-3 {
left: 15px;
right: 15px;
height: 10px;
}
div.jp-Cell-Placeholder-content-1 {
top: 100px;
}
div.jp-Cell-Placeholder-content-2 {
top: 120px;
}
div.jp-Cell-Placeholder-content-3 {
top: 140px;
}
</style>
<style type="text/css">
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.
Many variables appear in an ordered sequence (0,1,2,3). These sequences
are designed to work well together, so for example, `--jp-border-color1` should
be used with `--jp-layout-color1`. The numbers have the following meanings:
* 0: super-primary, reserved for special emphasis
* 1: primary, most important under normal situations
* 2: secondary, next most important under normal situations
* 3: tertiary, next most important under normal situations
Throughout JupyterLab, we are mostly following principles from Google's
Material Design when selecting colors. We are not, however, following
all of MD as it is not optimized for dense, information rich UIs.
*/
:root {
/* Elevation
*
* We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
*
* https://github.com/material-components/material-components-web
* https://material-components-web.appspot.com/elevation.html
*/
--jp-shadow-base-lightness: 0;
--jp-shadow-umbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.2
);
--jp-shadow-penumbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.14
);
--jp-shadow-ambient-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.12
);
--jp-elevation-z0: none;
--jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
0 1px 1px 0 var(--jp-shadow-penumbra-color),
0 1px 3px 0 var(--jp-shadow-ambient-color);
--jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
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<h1 id="Tutorial:-Chemical-Properties-Prediction-with-Graph-Neural-Networks">Tutorial: Chemical Properties Prediction with Graph Neural Networks<a class="anchor-link" href="#Tutorial:-Chemical-Properties-Prediction-with-Graph-Neural-Networks"></a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial15/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 use <strong>Graph Neural Networks</strong> (GNNs) for chemical properties prediction. Chemical properties prediction involves estimating or determining the physical, chemical, or biological characteristics of molecules based on their structure.</p>
<p>Molecules can naturally be represented as graphs, where atoms serve as the nodes and chemical bonds as the edges connecting them. This graph-based structure makes GNNs a great fit for predicting chemical properties.</p>
<p>In the tutorial we will use the <a href="https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_geometric.datasets.QM9.html#torch_geometric.datasets.QM9">QM9 dataset</a> from Pytorch Geometric. The dataset contains small molecules, each consisting of up to 29 atoms, with every atom having a corresponding 3D position. Each atom is also represented by a five-dimensional one-hot encoded vector that indicates the atom type (H, C, N, O, F).</p>
<p>First of all, let's start by importing useful modules!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab[tutorial]"</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina</span><span class="w"> </span><span class="kn">import</span> <span class="n">Trainer</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="kn">from</span><span class="w"> </span><span class="nn">torch_geometric.datasets</span><span class="w"> </span><span class="kn">import</span> <span class="n">QM9</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">torch_geometric.nn</span><span class="w"> </span><span class="kn">import</span> <span class="n">GCNConv</span><span class="p">,</span> <span class="n">global_mean_pool</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="Download-Data-and-create-the-Problem">Download Data and create the Problem<a class="anchor-link" href="#Download-Data-and-create-the-Problem"></a></h2>
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<p>We download the dataset and save the molecules as a list of <code>Data</code> objects (<code>input_</code>), where each element contains one molecule encoded in a graph structure. The corresponding target properties (<code>target_</code>) are listed below:</p>
<table>
<thead>
<tr>
<th>Target</th>
<th>Property</th>
<th>Description</th>
<th>Unit</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>$\mu$</td>
<td>Dipole moment</td>
<td>$D$</td>
</tr>
<tr>
<td>1</td>
<td>$\alpha$</td>
<td>Isotropic polarizability</td>
<td>$a₀³$</td>
</tr>
<tr>
<td>2</td>
<td>$\epsilon_{\textrm{HOMO}}$</td>
<td>Highest occupied molecular orbital energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>3</td>
<td>$\epsilon_{\textrm{LUMO}}$</td>
<td>Lowest unoccupied molecular orbital energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>4</td>
<td>$\Delta \epsilon$</td>
<td>Gap between $\epsilon_{\textrm{HOMO}}$ and $\epsilon_{\textrm{LUMO}}$</td>
<td>$eV$</td>
</tr>
<tr>
<td>5</td>
<td>$\langle R^2 \rangle$</td>
<td>Electronic spatial extent</td>
<td>$a₀²$</td>
</tr>
<tr>
<td>6</td>
<td>$\textrm{ZPVE}$</td>
<td>Zero point vibrational energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>7</td>
<td>$U_0$</td>
<td>Internal energy at 0K</td>
<td>$eV$</td>
</tr>
<tr>
<td>8</td>
<td>$U$</td>
<td>Internal energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>9</td>
<td>$H$</td>
<td>Enthalpy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>10</td>
<td>$G$</td>
<td>Free energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>11</td>
<td>$c_{\textrm{v}}$</td>
<td>Heat capacity at 298.15K</td>
<td>$cal/(mol·K)$</td>
</tr>
<tr>
<td>12</td>
<td>$U_0^{\textrm{ATOM}}$</td>
<td>Atomization energy at 0K</td>
<td>$eV$</td>
</tr>
<tr>
<td>13</td>
<td>$U^{\textrm{ATOM}}$</td>
<td>Atomization energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>14</td>
<td>$H^{\textrm{ATOM}}$</td>
<td>Atomization enthalpy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>15</td>
<td>$G^{\textrm{ATOM}}$</td>
<td>Atomization free energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>16</td>
<td>$A$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
<tr>
<td>17</td>
<td>$B$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
<tr>
<td>18</td>
<td>$C$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
</tbody>
</table>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># download the data + shuffling</span>
<span class="n">dataset</span> <span class="o">=</span> <span class="n">QM9</span><span class="p">(</span><span class="n">root</span><span class="o">=</span><span class="s2">"./tutorial_logs"</span><span class="p">)</span><span class="o">.</span><span class="n">shuffle</span><span class="p">()</span>
<span class="c1"># save the dataset</span>
<span class="n">input_</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span> <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">dataset</span><span class="p">]</span>
<span class="n">target_</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">data</span><span class="o">.</span><span class="n">y</span> <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">dataset</span><span class="p">])</span>
<span class="c1"># normalize the target</span>
<span class="n">mean</span> <span class="o">=</span> <span class="n">target_</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">std</span> <span class="o">=</span> <span class="n">target_</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">target_</span> <span class="o">=</span> <span class="p">(</span><span class="n">target_</span> <span class="o">-</span> <span class="n">mean</span><span class="p">)</span> <span class="o">/</span> <span class="n">std</span>
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<pre>Downloading https://data.pyg.org/datasets/qm9_v3.zip
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<pre>Extracting tutorial_logs/raw/qm9_v3.zip
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<pre>Processing...
Using a pre-processed version of the dataset. Please install 'rdkit' to alternatively process the raw data.
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<pre>Done!
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<p>Great! Once the data are downloaded, building the problem is straightforward by using the <a href="https://mathlab.github.io/PINA/_rst/problem/zoo/supervised_problem.html"><code>SupervisedProblem</code></a> class.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># build the problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">SupervisedProblem</span><span class="p">(</span><span class="n">input_</span><span class="o">=</span><span class="n">input_</span><span class="p">,</span> <span class="n">output_</span><span class="o">=</span><span class="n">target_</span><span class="p">)</span>
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<h2 id="Build-the-Model">Build the Model<a class="anchor-link" href="#Build-the-Model"></a></h2><p>To predict molecular properties, we will construct a simple Convolutional Graph Neural Network using the <a href=""><code>GCNConv</code></a> module from PyG. While this tutorial focuses on a straightforward model, more advanced architectures—such as Equivariant Networks—could potentially yield better performance. Please note that this tutorial serves only for demonstration purposes.</p>
<p><strong>Importantly</strong> notice that in the <code>forward</code> pass we pass a data object as input, and unpack inside the graph attributes. This is the only requirement in <strong>PINA</strong> to use graphs and solvers together.</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">GNN</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="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_features</span><span class="p">,</span> <span class="n">out_features</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="o">=</span><span class="mi">256</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">GNN</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">GCNConv</span><span class="p">(</span><span class="n">in_features</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">GCNConv</span><span class="p">(</span><span class="n">hidden_dim</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">fc</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">hidden_dim</span><span class="p">,</span> <span class="n">out_features</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">data</span><span class="p">):</span>
<span class="c1"># extract attributes, N.B. in PINA Data object are passed as input</span>
<span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">,</span> <span class="n">batch</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">edge_index</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">batch</span>
<span class="c1"># perform normal graph operations</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">))</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">))</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">global_mean_pool</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">batch</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
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<h2 id="Train-the-Model">Train the Model<a class="anchor-link" href="#Train-the-Model"></a></h2><p>Now that the problem is created and the model is built, we can train the model using the <a href="https://mathlab.github.io/PINA/_rst/solver/supervised.html"><code>SupervisedSolver</code></a>, which is the solver for standard supervised learning task. We will optimize the Maximum Absolute Error and test on the same metric. In the <a href="https://mathlab.github.io/PINA/_rst/trainer.html"><code>Trainer</code></a> class we specify the optimization hyperparameters.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># define the 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">GNN</span><span class="p">(</span><span class="n">in_features</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> <span class="n">out_features</span><span class="o">=</span><span class="mi">19</span><span class="p">),</span>
<span class="n">use_lt</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="n">loss</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">L1Loss</span><span class="p">(),</span>
<span class="p">)</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="p">,</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.7</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">512</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="p">)</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>You are using the plain ModelCheckpoint callback. Consider using LitModelCheckpoint which with seamless uploading to Model registry.
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=3` reached.
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<h2 id="Testing-Chemical-Predictions">Testing Chemical Predictions<a class="anchor-link" href="#Testing-Chemical-Predictions"></a></h2>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">trainer</span><span class="o">.</span><span class="n">test</span><span class="p">()</span>
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<pre>────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Test metric DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
test_loss_epoch 0.40489107370376587
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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<p>We observe that the model achieves an average error of approximately 0.4 MAE across all property predictions. This error is an average, but we can also inspect the error for each individual property prediction.</p>
<p>To do this, we need access to the test dataset, which can be retrieved from the trainer's datamodule. Each datamodule contains both the dataloader and dataset objects. For the dataset, we can use the <a href="https://mathlab.github.io/PINA/_rst/data/dataset.html#pina.data.dataset.PinaDataset.get_all_data"><code>get_all_data()</code></a> method. This function returns the entire dataset as a dictionary, where the keys represent the Condition names, and the values are dictionaries containing input and target tensors.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># get the test dataset</span>
<span class="n">test_dataset</span> <span class="o">=</span> <span class="n">trainer</span><span class="o">.</span><span class="n">datamodule</span><span class="o">.</span><span class="n">test_dataset</span><span class="o">.</span><span class="n">get_all_data</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Here the dataset"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Dataset keys: </span><span class="si">{</span><span class="n">test_dataset</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Dataset keys for data condition: </span><span class="si">{</span><span class="n">test_dataset</span><span class="p">[</span><span class="s1">'data'</span><span class="p">]</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">"Dataset values type for data condition: </span><span class="si">{</span><span class="p">[</span><span class="n">v</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">v</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">test_dataset</span><span class="p">[</span><span class="s1">'data'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">()]</span><span class="si">}</span><span class="s2">"</span>
<span class="p">)</span>
<span class="c1"># extract input and target for test dataset</span>
<span class="n">input_test</span> <span class="o">=</span> <span class="n">test_dataset</span><span class="p">[</span><span class="s2">"data"</span><span class="p">][</span><span class="s2">"input"</span><span class="p">]</span>
<span class="n">target_test</span> <span class="o">=</span> <span class="n">test_dataset</span><span class="p">[</span><span class="s2">"data"</span><span class="p">][</span><span class="s2">"target"</span><span class="p">]</span>
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<pre>Here the dataset
Dataset keys: dict_keys(['data'])
Dataset keys for data condition: dict_keys(['input', 'target'])
Dataset values type for data condition: ['DataLabelBatch', 'Tensor']
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<p>Now we obtain the prediction my calling the forward pass for the <code>SupervisedSolver</code>.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># get the prediction</span>
<span class="n">prediction_test</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">input_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of prediction properties: </span><span class="si">{</span><span class="n">prediction_test</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Number of prediction properties: 19
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<p>As you can see we obtain a tensor with 19 prediction properties as output, which is what we are looking for. Now let's compute the error for each property:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">properties</span> <span class="o">=</span> <span class="p">[</span>
<span class="s2">"μ"</span><span class="p">,</span>
<span class="s2">"α"</span><span class="p">,</span>
<span class="s2">"ε HOMO"</span><span class="p">,</span>
<span class="s2">"ε LUMO"</span><span class="p">,</span>
<span class="s2">"Δε"</span><span class="p">,</span>
<span class="s2">"⟨R²⟩"</span><span class="p">,</span>
<span class="s2">"ZPVE"</span><span class="p">,</span>
<span class="s2">"U₀"</span><span class="p">,</span>
<span class="s2">"U"</span><span class="p">,</span>
<span class="s2">"H"</span><span class="p">,</span>
<span class="s2">"G"</span><span class="p">,</span>
<span class="s2">"cv"</span><span class="p">,</span>
<span class="s2">"U₀ ATOM"</span><span class="p">,</span>
<span class="s2">"U ATOM"</span><span class="p">,</span>
<span class="s2">"H ATOM"</span><span class="p">,</span>
<span class="s2">"G ATOM"</span><span class="p">,</span>
<span class="s2">"A"</span><span class="p">,</span>
<span class="s2">"B"</span><span class="p">,</span>
<span class="s2">"C"</span><span class="p">,</span>
<span class="p">]</span>
<span class="n">units</span> <span class="o">=</span> <span class="p">[</span>
<span class="s2">"D"</span><span class="p">,</span>
<span class="s2">"a₀³"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"a₀²"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"cal/(mol·K)"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="s1">'Property'</span><span class="si">:</span><span class="s2">&lt;10</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="s1">'Error'</span><span class="si">:</span><span class="s2">&lt;8</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="s1">'Unit'</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"-"</span> <span class="o">*</span> <span class="mi">34</span><span class="p">)</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">19</span><span class="p">):</span>
<span class="n">error</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">prediction_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span> <span class="o">-</span> <span class="n">target_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">])</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">properties</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">&lt;10</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">error</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">units</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Property | Error | Unit
----------------------------------
μ | 0.6880 | D
α | 0.4528 | a₀³
ε HOMO | 0.6876 | eV
ε LUMO | 0.6286 | eV
Δε | 0.6713 | eV
⟨R²⟩ | 0.6495 | a₀²
ZPVE | 0.2448 | eV
U₀ | 0.3794 | eV
U | 0.3858 | eV
H | 0.3779 | eV
G | 0.3921 | eV
cv | 0.5453 | cal/(mol·K)
U₀ ATOM | 0.2836 | eV
U ATOM | 0.2835 | eV
H ATOM | 0.2838 | eV
G ATOM | 0.2877 | eV
A | 0.0045 | GHz
B | 0.2234 | GHz
C | 0.2233 | GHz
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<p>We can see that predicting the some properties are easier and some harder to predict. For example, the rotational constant $A$ is way easier to predict than dipole moment $\mu$. To have a better idea we can also plot a scatter plot between predicted and observed properties:</p>
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<div class="highlight hl-ipython3"><pre><span></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="c1"># Set up the plot grid</span>
<span class="n">num_properties</span> <span class="o">=</span> <span class="mi">19</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">8</span><span class="p">))</span>
<span class="n">axes</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span>
<span class="c1"># Outlier removal using IQR (with torch)</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_properties</span><span class="p">):</span>
<span class="n">target_vals</span> <span class="o">=</span> <span class="n">target_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span>
<span class="n">pred_vals</span> <span class="o">=</span> <span class="n">prediction_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span>
<span class="c1"># Calculate Q1 (25th percentile) and Q3 (75th percentile) using torch</span>
<span class="n">Q1</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">target_vals</span><span class="p">,</span> <span class="mf">0.25</span><span class="p">)</span>
<span class="n">Q3</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">target_vals</span><span class="p">,</span> <span class="mf">0.75</span><span class="p">)</span>
<span class="n">IQR</span> <span class="o">=</span> <span class="n">Q3</span> <span class="o">-</span> <span class="n">Q1</span>
<span class="c1"># Define the outlier range</span>
<span class="n">lower_bound</span> <span class="o">=</span> <span class="n">Q1</span> <span class="o">-</span> <span class="mf">1.5</span> <span class="o">*</span> <span class="n">IQR</span>
<span class="n">upper_bound</span> <span class="o">=</span> <span class="n">Q3</span> <span class="o">+</span> <span class="mf">1.5</span> <span class="o">*</span> <span class="n">IQR</span>
<span class="c1"># Filter out the outliers</span>
<span class="n">mask</span> <span class="o">=</span> <span class="p">(</span><span class="n">target_vals</span> <span class="o">&gt;=</span> <span class="n">lower_bound</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">target_vals</span> <span class="o">&lt;=</span> <span class="n">upper_bound</span><span class="p">)</span>
<span class="n">filtered_target</span> <span class="o">=</span> <span class="n">target_vals</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span>
<span class="n">filtered_pred</span> <span class="o">=</span> <span class="n">pred_vals</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span>
<span class="c1"># Plotting</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="n">ax</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span>
<span class="n">filtered_target</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">filtered_pred</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="s2">"Data points (no outliers)"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span>
<span class="p">[</span><span class="n">filtered_target</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">filtered_target</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()],</span>
<span class="p">[</span><span class="n">filtered_target</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">filtered_target</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()],</span>
<span class="s2">"r--"</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="s2">"y=x"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">properties</span><span class="p">[</span><span class="n">idx</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">"Target"</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">"Prediction"</span><span class="p">)</span>
<span class="c1"># Remove the extra subplot (since there are 19 properties, not 20)</span>
<span class="k">if</span> <span class="n">num_properties</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">axes</span><span class="p">):</span>
<span class="n">fig</span><span class="o">.</span><span class="n">delaxes</span><span class="p">(</span><span class="n">axes</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
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<p>By looking more into details, we can see that $A$ is not predicted that well, but the small values of the quantity lead to a lower MAE than the other properties. From the plot we can see that the atomatization energies, free energy and enthalpy are the predicted properties with higher correlation with the true chemical properties.</p>
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<h2 id="What's-Next?">What's Next?<a class="anchor-link" href="#What's-Next?"></a></h2><p>Congratulations on completing the tutorial on chemical properties prediction with <strong>PINA</strong>! Now that you've got the basics, there are several exciting directions to explore:</p>
<ol>
<li><p><strong>Train the network for longer or with different layer sizes</strong>: Experiment with various configurations to see how the network's accuracy improves.</p>
</li>
<li><p><strong>Use a different network</strong>: For example, Equivariant Graph Neural Networks (EGNNs) have shown great results on molecular tasks by leveraging group symmetries. If you're interested, check out <a href="https://arxiv.org/abs/2102.09844"><em>E(n) Equivariant Graph Neural Networks</em></a> for more details.</p>
</li>
<li><p><strong>What if the input is time-dependent?</strong>: For example, predicting force fields in Molecular Dynamics simulations. In PINA, you can predict force fields with ease, as it's still a supervised learning task. If this interests you, have a look at <a href="https://pubs.acs.org/doi/10.1021/acs.chemrev.0c01111"><em>Machine Learning Force Fields</em></a>.</p>
</li>
<li><p><strong>...and many more!</strong>: The possibilities are vast, including exploring new architectures, working with larger datasets, and applying this framework to more complex systems.</p>
</li>
</ol>
<p>For more resources and tutorials, check out the <a href="https://mathlab.github.io/PINA/">PINA Documentation</a>.</p>
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