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PINA/docs/source/tutorials/tutorial10/tutorial.html
github-actions[bot] e917753702 export tutorials changed in c161138 (#498) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-03-19 17:48:29 +01:00

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This file contains invisible Unicode characters
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<title>tutorial</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script><script>
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/* Icons urls */
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--jp-icon-add-above: url(data:image/svg+xml;base64,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);
--jp-icon-add-below: url(data:image/svg+xml;base64,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);
--jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-bell: url(data:image/svg+xml;base64,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);
--jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
--jp-icon-bug: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yMCA4aC0yLjgxYy0uNDUtLjc4LTEuMDctMS40NS0xLjgyLTEuOTZMMTcgNC40MSAxNS41OSAzbC0yLjE3IDIuMTdDMTIuOTYgNS4wNiAxMi40OSA1IDEyIDVjLS40OSAwLS45Ni4wNi0xLjQxLjE3TDguNDEgMyA3IDQuNDFsMS42MiAxLjYzQzcuODggNi41NSA3LjI2IDcuMjIgNi44MSA4SDR2MmgyLjA5Yy0uMDUuMzMtLjA5LjY2LS4wOSAxdjFINHYyaDJ2MWMwIC4zNC4wNC42Ny4wOSAxSDR2MmgyLjgxYzEuMDQgMS43OSAyLjk3IDMgNS4xOSAzczQuMTUtMS4yMSA1LjE5LTNIMjB2LTJoLTIuMDljLjA1LS4zMy4wOS0uNjYuMDktMXYtMWgydi0yaC0ydi0xYzAtLjM0LS4wNC0uNjctLjA5LTFIMjBWOHptLTYgOGgtNHYtMmg0djJ6bTAtNGgtNHYtMmg0djJ6Ii8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-build: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE0LjkgMTcuNDVDMTYuMjUgMTcuNDUgMTcuMzUgMTYuMzUgMTcuMzUgMTVDMTcuMzUgMTMuNjUgMTYuMjUgMTIuNTUgMTQuOSAxMi41NUMxMy41NCAxMi41NSAxMi40NSAxMy42NSAxMi40NSAxNUMxMi40NSAxNi4zNSAxMy41NCAxNy40NSAxNC45IDE3LjQ1Wk0yMC4xIDE1LjY4TDIxLjU4IDE2Ljg0QzIxLjcxIDE2Ljk1IDIxLjc1IDE3LjEzIDIxLjY2IDE3LjI5TDIwLjI2IDE5LjcxQzIwLjE3IDE5Ljg2IDIwIDE5LjkyIDE5LjgzIDE5Ljg2TDE4LjA5IDE5LjE2QzE3LjczIDE5LjQ0IDE3LjMzIDE5LjY3IDE2LjkxIDE5Ljg1TDE2LjY0IDIxLjdDMTYuNjIgMjEuODcgMTYuNDcgMjIgMTYuMyAyMkgxMy41QzEzLjMyIDIyIDEzLjE4IDIxLjg3IDEzLjE1IDIxLjdMMTIuODkgMTkuODVDMTIuNDYgMTkuNjcgMTIuMDcgMTkuNDQgMTEuNzEgMTkuMTZMOS45NjAwMiAxOS44NkM5LjgxMDAyIDE5LjkyIDkuNjIwMDIgMTkuODYgOS41NDAwMiAxOS43MUw4LjE0MDAyIDE3LjI5QzguMDUwMDIgMTcuMTMgOC4wOTAwMiAxNi45NSA4LjIyMDAyIDE2Ljg0TDkuNzAwMDIgMTUuNjhMOS42NTAwMSAxNUw5LjcwMDAyIDE0LjMxTDguMjIwMDIgMTMuMTZDOC4wOTAwMiAxMy4wNSA4LjA1MDAyIDEyLjg2IDguMTQwMDIgMTIuNzFMOS41NDAwMiAxMC4yOUM5LjYyMDAyIDEwLjEzIDkuODEwMDIgMTAuMDcgOS45NjAwMiAxMC4xM0wxMS43MSAxMC44NEMxMi4wNyAxMC41NiAxMi40NiAxMC4zMiAxMi44OSAxMC4xNUwxMy4xNSA4LjI4OTk4QzEzLjE4IDguMTI5OTggMTMuMzIgNy45OTk5OCAxMy41IDcuOTk5OThIMTYuM0MxNi40NyA3Ljk5OTk4IDE2LjYyIDguMTI5OTggMTYuNjQgOC4yODk5OEwxNi45MSAxMC4xNUMxNy4zMyAxMC4zMiAxNy43MyAxMC41NiAxOC4wOSAxMC44NEwxOS44MyAxMC4xM0MyMCAxMC4wNyAyMC4xNyAxMC4xMyAyMC4yNiAxMC4yOUwyMS42NiAxMi43MUMyMS43NSAxMi44NiAyMS43MSAxMy4wNSAyMS41OCAxMy4xNkwyMC4xIDE0LjMxTDIwLjE1IDE1TDIwLjEgMTUuNjhaIi8+CiAgICA8cGF0aCBkPSJNNy4zMjk2NiA3LjQ0NDU0QzguMDgzMSA3LjAwOTU0IDguMzM5MzIgNi4wNTMzMiA3LjkwNDMyIDUuMjk5ODhDNy40NjkzMiA0LjU0NjQzIDYuNTA4MSA0LjI4MTU2IDUuNzU0NjYgNC43MTY1NkM1LjM5MTc2IDQuOTI2MDggNS4xMjY5NSA1LjI3MTE4IDUuMDE4NDkgNS42NzU5NEM0LjkxMDA0IDYuMDgwNzEgNC45NjY4MiA2LjUxMTk4IDUuMTc2MzQgNi44NzQ4OEM1LjYxMTM0IDcuNjI4MzIgNi41NzYyMiA3Ljg3OTU0IDcuMzI5NjYgNy40NDQ1NFpNOS42NTcxOCA0Ljc5NTkzTDEwLjg2NzIgNC45NTE3OUMxMC45NjI4IDQuOTc3NDEgMTEuMDQwMiA1LjA3MTMzIDExLjAzODIgNS4xODc5M0wxMS4wMzg4IDYuOTg4OTNDMTEuMDQ1NSA3LjEwMDU0IDEwLjk2MTYgNy4xOTUxOCAxMC44NTUgNy4yMTA1NEw5LjY2MDAxIDcuMzgwODNMOS4yMzkxNSA4LjEzMTg4TDkuNjY5NjEgOS4yNTc0NUM5LjcwNzI5IDkuMzYyNzEgOS42NjkzNCA5LjQ3Njk5IDkuNTc0MDggOS41MzE5OUw4LjAxNTIzIDEwLjQzMkM3LjkxMTMxIDEwLjQ5MiA3Ljc5MzM3IDEwLjQ2NzcgNy43MjEwNSAxMC4zODI0TDYuOTg3NDggOS40MzE4OEw2LjEwOTMxIDkuNDMwODNMNS4zNDcwNCAxMC4zOTA1QzUuMjg5MDkgMTAuNDcwMiA1LjE3MzgzIDEwLjQ5MDUgNS4wNzE4NyAxMC40MzM5TDMuNTEyNDUgOS41MzI5M0MzLjQxMDQ5IDkuNDc2MzMgMy4zNzY0NyA5LjM1NzQxIDMuNDEwNzUgOS4yNTY3OUwzLjg2MzQ3IDguMTQwOTNMMy42MTc0OSA3Ljc3NDg4TDMuNDIzNDcgNy4zNzg4M0wyLjIzMDc1IDcuMjEyOTdDMi4xMjY0NyA3LjE5MjM1IDIuMDQwNDkgNy4xMDM0MiAyLjA0MjQ1IDYuOTg2ODJMMi4wNDE4NyA1LjE4NTgyQzIuMDQzODMgNS4wNjkyMiAyLjExOTA5IDQuOTc5NTggMi4yMTcwNCA0Ljk2OTIyTDMuNDIwNjUgNC43OTM5M0wzLjg2NzQ5IDQuMDI3ODhMMy40MTEwNSAyLjkxNzMxQzMuMzczMzcgMi44MTIwNCAzLjQxMTMxIDIuNjk3NzYgMy41MTUyMyAyLjYzNzc2TDUuMDc0MDggMS43Mzc3NkM1LjE2OTM0IDEuNjgyNzYgNS4yODcyOSAxLjcwNzA0IDUuMzU5NjEgMS43OTIzMUw2LjExOTE1IDIuNzI3ODhMNi45ODAwMSAyLjczODkzTDcuNzI0OTYgMS43ODkyMkM3Ljc5MTU2IDEuNzA0NTggNy45MTU0OCAxLjY3OTIyIDguMDA4NzkgMS43NDA4Mkw5LjU2ODIxIDIuNjQxODJDOS42NzAxNyAyLjY5ODQyIDkuNzEyODUgMi44MTIzNCA5LjY4NzIzIDIuOTA3OTdMOS4yMTcxOCA0LjAzMzgzTDkuNDYzMTYgNC4zOTk4OEw5LjY1NzE4IDQuNzk1OTNaIi8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
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--jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-regex: url(data:image/svg+xml;base64,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);
--jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-toc: url(data:image/svg+xml;base64,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);
--jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
--jp-icon-trusted: url(data:image/svg+xml;base64,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);
--jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-users: url(data:image/svg+xml;base64,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);
--jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-word: url(data:image/svg+xml;base64,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);
--jp-icon-yaml: url(data:image/svg+xml;base64,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);
}
/* Icon CSS class declarations */
.jp-AddAboveIcon {
background-image: var(--jp-icon-add-above);
}
.jp-AddBelowIcon {
background-image: var(--jp-icon-add-below);
}
.jp-AddIcon {
background-image: var(--jp-icon-add);
}
.jp-BellIcon {
background-image: var(--jp-icon-bell);
}
.jp-BugDotIcon {
background-image: var(--jp-icon-bug-dot);
}
.jp-BugIcon {
background-image: var(--jp-icon-bug);
}
.jp-BuildIcon {
background-image: var(--jp-icon-build);
}
.jp-CaretDownEmptyIcon {
background-image: var(--jp-icon-caret-down-empty);
}
.jp-CaretDownEmptyThinIcon {
background-image: var(--jp-icon-caret-down-empty-thin);
}
.jp-CaretDownIcon {
background-image: var(--jp-icon-caret-down);
}
.jp-CaretLeftIcon {
background-image: var(--jp-icon-caret-left);
}
.jp-CaretRightIcon {
background-image: var(--jp-icon-caret-right);
}
.jp-CaretUpEmptyThinIcon {
background-image: var(--jp-icon-caret-up-empty-thin);
}
.jp-CaretUpIcon {
background-image: var(--jp-icon-caret-up);
}
.jp-CaseSensitiveIcon {
background-image: var(--jp-icon-case-sensitive);
}
.jp-CheckIcon {
background-image: var(--jp-icon-check);
}
.jp-CircleEmptyIcon {
background-image: var(--jp-icon-circle-empty);
}
.jp-CircleIcon {
background-image: var(--jp-icon-circle);
}
.jp-ClearIcon {
background-image: var(--jp-icon-clear);
}
.jp-CloseIcon {
background-image: var(--jp-icon-close);
}
.jp-CodeCheckIcon {
background-image: var(--jp-icon-code-check);
}
.jp-CodeIcon {
background-image: var(--jp-icon-code);
}
.jp-CollapseAllIcon {
background-image: var(--jp-icon-collapse-all);
}
.jp-ConsoleIcon {
background-image: var(--jp-icon-console);
}
.jp-CopyIcon {
background-image: var(--jp-icon-copy);
}
.jp-CopyrightIcon {
background-image: var(--jp-icon-copyright);
}
.jp-CutIcon {
background-image: var(--jp-icon-cut);
}
.jp-DeleteIcon {
background-image: var(--jp-icon-delete);
}
.jp-DownloadIcon {
background-image: var(--jp-icon-download);
}
.jp-DuplicateIcon {
background-image: var(--jp-icon-duplicate);
}
.jp-EditIcon {
background-image: var(--jp-icon-edit);
}
.jp-EllipsesIcon {
background-image: var(--jp-icon-ellipses);
}
.jp-ErrorIcon {
background-image: var(--jp-icon-error);
}
.jp-ExpandAllIcon {
background-image: var(--jp-icon-expand-all);
}
.jp-ExtensionIcon {
background-image: var(--jp-icon-extension);
}
.jp-FastForwardIcon {
background-image: var(--jp-icon-fast-forward);
}
.jp-FileIcon {
background-image: var(--jp-icon-file);
}
.jp-FileUploadIcon {
background-image: var(--jp-icon-file-upload);
}
.jp-FilterDotIcon {
background-image: var(--jp-icon-filter-dot);
}
.jp-FilterIcon {
background-image: var(--jp-icon-filter);
}
.jp-FilterListIcon {
background-image: var(--jp-icon-filter-list);
}
.jp-FolderFavoriteIcon {
background-image: var(--jp-icon-folder-favorite);
}
.jp-FolderIcon {
background-image: var(--jp-icon-folder);
}
.jp-HomeIcon {
background-image: var(--jp-icon-home);
}
.jp-Html5Icon {
background-image: var(--jp-icon-html5);
}
.jp-ImageIcon {
background-image: var(--jp-icon-image);
}
.jp-InfoIcon {
background-image: var(--jp-icon-info);
}
.jp-InspectorIcon {
background-image: var(--jp-icon-inspector);
}
.jp-JsonIcon {
background-image: var(--jp-icon-json);
}
.jp-JuliaIcon {
background-image: var(--jp-icon-julia);
}
.jp-JupyterFaviconIcon {
background-image: var(--jp-icon-jupyter-favicon);
}
.jp-JupyterIcon {
background-image: var(--jp-icon-jupyter);
}
.jp-JupyterlabWordmarkIcon {
background-image: var(--jp-icon-jupyterlab-wordmark);
}
.jp-KernelIcon {
background-image: var(--jp-icon-kernel);
}
.jp-KeyboardIcon {
background-image: var(--jp-icon-keyboard);
}
.jp-LaunchIcon {
background-image: var(--jp-icon-launch);
}
.jp-LauncherIcon {
background-image: var(--jp-icon-launcher);
}
.jp-LineFormIcon {
background-image: var(--jp-icon-line-form);
}
.jp-LinkIcon {
background-image: var(--jp-icon-link);
}
.jp-ListIcon {
background-image: var(--jp-icon-list);
}
.jp-MarkdownIcon {
background-image: var(--jp-icon-markdown);
}
.jp-MoveDownIcon {
background-image: var(--jp-icon-move-down);
}
.jp-MoveUpIcon {
background-image: var(--jp-icon-move-up);
}
.jp-NewFolderIcon {
background-image: var(--jp-icon-new-folder);
}
.jp-NotTrustedIcon {
background-image: var(--jp-icon-not-trusted);
}
.jp-NotebookIcon {
background-image: var(--jp-icon-notebook);
}
.jp-NumberingIcon {
background-image: var(--jp-icon-numbering);
}
.jp-OfflineBoltIcon {
background-image: var(--jp-icon-offline-bolt);
}
.jp-PaletteIcon {
background-image: var(--jp-icon-palette);
}
.jp-PasteIcon {
background-image: var(--jp-icon-paste);
}
.jp-PdfIcon {
background-image: var(--jp-icon-pdf);
}
.jp-PythonIcon {
background-image: var(--jp-icon-python);
}
.jp-RKernelIcon {
background-image: var(--jp-icon-r-kernel);
}
.jp-ReactIcon {
background-image: var(--jp-icon-react);
}
.jp-RedoIcon {
background-image: var(--jp-icon-redo);
}
.jp-RefreshIcon {
background-image: var(--jp-icon-refresh);
}
.jp-RegexIcon {
background-image: var(--jp-icon-regex);
}
.jp-RunIcon {
background-image: var(--jp-icon-run);
}
.jp-RunningIcon {
background-image: var(--jp-icon-running);
}
.jp-SaveIcon {
background-image: var(--jp-icon-save);
}
.jp-SearchIcon {
background-image: var(--jp-icon-search);
}
.jp-SettingsIcon {
background-image: var(--jp-icon-settings);
}
.jp-ShareIcon {
background-image: var(--jp-icon-share);
}
.jp-SpreadsheetIcon {
background-image: var(--jp-icon-spreadsheet);
}
.jp-StopIcon {
background-image: var(--jp-icon-stop);
}
.jp-TabIcon {
background-image: var(--jp-icon-tab);
}
.jp-TableRowsIcon {
background-image: var(--jp-icon-table-rows);
}
.jp-TagIcon {
background-image: var(--jp-icon-tag);
}
.jp-TerminalIcon {
background-image: var(--jp-icon-terminal);
}
.jp-TextEditorIcon {
background-image: var(--jp-icon-text-editor);
}
.jp-TocIcon {
background-image: var(--jp-icon-toc);
}
.jp-TreeViewIcon {
background-image: var(--jp-icon-tree-view);
}
.jp-TrustedIcon {
background-image: var(--jp-icon-trusted);
}
.jp-UndoIcon {
background-image: var(--jp-icon-undo);
}
.jp-UserIcon {
background-image: var(--jp-icon-user);
}
.jp-UsersIcon {
background-image: var(--jp-icon-users);
}
.jp-VegaIcon {
background-image: var(--jp-icon-vega);
}
.jp-WordIcon {
background-image: var(--jp-icon-word);
}
.jp-YamlIcon {
background-image: var(--jp-icon-yaml);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* (DEPRECATED) Support for consuming icons as CSS background images
*/
.jp-Icon,
.jp-MaterialIcon {
background-position: center;
background-repeat: no-repeat;
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-cover {
background-position: center;
background-repeat: no-repeat;
background-size: cover;
}
/**
* (DEPRECATED) Support for specific CSS icon sizes
*/
.jp-Icon-16 {
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-18 {
background-size: 18px;
min-width: 18px;
min-height: 18px;
}
.jp-Icon-20 {
background-size: 20px;
min-width: 20px;
min-height: 20px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.lm-TabBar .lm-TabBar-addButton {
align-items: center;
display: flex;
padding: 4px;
padding-bottom: 5px;
margin-right: 1px;
background-color: var(--jp-layout-color2);
}
.lm-TabBar .lm-TabBar-addButton:hover {
background-color: var(--jp-layout-color1);
}
.lm-DockPanel-tabBar .lm-TabBar-tab {
width: var(--jp-private-horizontal-tab-width);
}
.lm-DockPanel-tabBar .lm-TabBar-content {
flex: unset;
}
.lm-DockPanel-tabBar[data-orientation='horizontal'] {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for icons as inline SVG HTMLElements
*/
/* recolor the primary elements of an icon */
.jp-icon0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-accent0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-accent1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-accent2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-accent3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-accent4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-accent0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-accent1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-accent2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-accent3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-accent4[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-none[fill] {
fill: none;
}
.jp-icon-none[stroke] {
stroke: none;
}
/* brand icon colors. Same for light and dark */
.jp-icon-brand0[fill] {
fill: var(--jp-brand-color0);
}
.jp-icon-brand1[fill] {
fill: var(--jp-brand-color1);
}
.jp-icon-brand2[fill] {
fill: var(--jp-brand-color2);
}
.jp-icon-brand3[fill] {
fill: var(--jp-brand-color3);
}
.jp-icon-brand4[fill] {
fill: var(--jp-brand-color4);
}
.jp-icon-brand0[stroke] {
stroke: var(--jp-brand-color0);
}
.jp-icon-brand1[stroke] {
stroke: var(--jp-brand-color1);
}
.jp-icon-brand2[stroke] {
stroke: var(--jp-brand-color2);
}
.jp-icon-brand3[stroke] {
stroke: var(--jp-brand-color3);
}
.jp-icon-brand4[stroke] {
stroke: var(--jp-brand-color4);
}
/* warn icon colors. Same for light and dark */
.jp-icon-warn0[fill] {
fill: var(--jp-warn-color0);
}
.jp-icon-warn1[fill] {
fill: var(--jp-warn-color1);
}
.jp-icon-warn2[fill] {
fill: var(--jp-warn-color2);
}
.jp-icon-warn3[fill] {
fill: var(--jp-warn-color3);
}
.jp-icon-warn0[stroke] {
stroke: var(--jp-warn-color0);
}
.jp-icon-warn1[stroke] {
stroke: var(--jp-warn-color1);
}
.jp-icon-warn2[stroke] {
stroke: var(--jp-warn-color2);
}
.jp-icon-warn3[stroke] {
stroke: var(--jp-warn-color3);
}
/* icon colors that contrast well with each other and most backgrounds */
.jp-icon-contrast0[fill] {
fill: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[fill] {
fill: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[fill] {
fill: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[fill] {
fill: var(--jp-icon-contrast-color3);
}
.jp-icon-contrast0[stroke] {
stroke: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[stroke] {
stroke: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[stroke] {
stroke: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[stroke] {
stroke: var(--jp-icon-contrast-color3);
}
.jp-icon-dot[fill] {
fill: var(--jp-warn-color0);
}
.jp-jupyter-icon-color[fill] {
fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
}
.jp-notebook-icon-color[fill] {
fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
}
.jp-json-icon-color[fill] {
fill: var(--jp-json-icon-color, var(--jp-warn-color1));
}
.jp-console-icon-color[fill] {
fill: var(--jp-console-icon-color, white);
}
.jp-console-icon-background-color[fill] {
fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
}
.jp-terminal-icon-color[fill] {
fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
}
.jp-terminal-icon-background-color[fill] {
fill: var(
--jp-terminal-icon-background-color,
var(--jp-inverse-layout-color2)
);
}
.jp-text-editor-icon-color[fill] {
fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
}
.jp-inspector-icon-color[fill] {
fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
}
/* CSS for icons in selected filebrowser listing items */
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* stylelint-disable selector-max-class, selector-max-compound-selectors */
/**
* TODO: come up with non css-hack solution for showing the busy icon on top
* of the close icon
* CSS for complex behavior of close icon of tabs in the main area tabbar
*/
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon3[fill] {
fill: none;
}
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon-busy[fill] {
fill: var(--jp-inverse-layout-color3);
}
/* stylelint-enable selector-max-class, selector-max-compound-selectors */
/* CSS for icons in status bar */
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* special handling for splash icon CSS. While the theme CSS reloads during
splash, the splash icon can loose theming. To prevent that, we set a
default for its color variable */
:root {
--jp-warn-color0: var(--md-orange-700);
}
/* not sure what to do with this one, used in filebrowser listing */
.jp-DragIcon {
margin-right: 4px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for alt colors for icons as inline SVG HTMLElements
*/
/* alt recolor the primary elements of an icon */
.jp-icon-alt .jp-icon0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-alt .jp-icon0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[stroke] {
stroke: var(--jp-layout-color4);
}
/* alt recolor the accent elements of an icon */
.jp-icon-alt .jp-icon-accent0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-alt .jp-icon-accent0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
display: none !important;
}
/**
* Support for hover colors for icons as inline SVG HTMLElements
*/
/**
* regular colors
*/
/* recolor the primary elements of an icon */
.jp-icon-hover :hover .jp-icon0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-hover :hover .jp-icon-none-hover[fill] {
fill: none;
}
.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
stroke: none;
}
/**
* inverse colors
*/
/* inverse recolor the primary elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* inverse recolor the accent elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-IFrame {
width: 100%;
height: 100%;
}
.jp-IFrame > iframe {
border: none;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-IFrame {
position: relative;
}
body.lm-mod-override-cursor .jp-IFrame::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-HoverBox {
position: fixed;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FormGroup-content fieldset {
border: none;
padding: 0;
min-width: 0;
width: 100%;
}
/* stylelint-disable selector-max-type */
.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
font-size: var(--jp-content-font-size2);
border-color: var(--jp-input-border-color);
border-style: solid;
border-radius: var(--jp-border-radius);
border-width: 1px;
padding: 6px 8px;
background: none;
color: var(--jp-ui-font-color0);
height: inherit;
}
.jp-FormGroup-content fieldset input[type='checkbox'] {
position: relative;
top: 2px;
margin-left: 0;
}
.jp-FormGroup-content button.jp-mod-styled {
cursor: pointer;
}
.jp-FormGroup-content .checkbox label {
cursor: pointer;
font-size: var(--jp-content-font-size1);
}
.jp-FormGroup-content .jp-root > fieldset > legend {
display: none;
}
.jp-FormGroup-content .jp-root > fieldset > p {
display: none;
}
/** copy of `input.jp-mod-styled:focus` style */
.jp-FormGroup-content fieldset input:focus,
.jp-FormGroup-content fieldset select:focus {
-moz-outline-radius: unset;
outline: var(--jp-border-width) solid var(--md-blue-500);
outline-offset: -1px;
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-FormGroup-content fieldset input:hover:not(:focus),
.jp-FormGroup-content fieldset select:hover:not(:focus) {
background-color: var(--jp-border-color2);
}
/* stylelint-enable selector-max-type */
.jp-FormGroup-content .checkbox .field-description {
/* Disable default description field for checkbox:
because other widgets do not have description fields,
we add descriptions to each widget on the field level.
*/
display: none;
}
.jp-FormGroup-content #root__description {
display: none;
}
.jp-FormGroup-content .jp-modifiedIndicator {
width: 5px;
background-color: var(--jp-brand-color2);
margin-top: 0;
margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
flex-shrink: 0;
}
.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
background-color: var(--jp-error-color0);
margin-right: 0.5em;
}
/* RJSF ARRAY style */
.jp-arrayFieldWrapper legend {
font-size: var(--jp-content-font-size2);
color: var(--jp-ui-font-color0);
flex-basis: 100%;
padding: 4px 0;
font-weight: var(--jp-content-heading-font-weight);
border-bottom: 1px solid var(--jp-border-color2);
}
.jp-arrayFieldWrapper .field-description {
padding: 4px 0;
white-space: pre-wrap;
}
.jp-arrayFieldWrapper .array-item {
width: 100%;
border: 1px solid var(--jp-border-color2);
border-radius: 4px;
margin: 4px;
}
.jp-ArrayOperations {
display: flex;
margin-left: 8px;
}
.jp-ArrayOperationsButton {
margin: 2px;
}
.jp-ArrayOperationsButton .jp-icon3[fill] {
fill: var(--jp-ui-font-color0);
}
button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
cursor: not-allowed;
opacity: 0.5;
}
/* RJSF form validation error */
.jp-FormGroup-content .validationErrors {
color: var(--jp-error-color0);
}
/* Hide panel level error as duplicated the field level error */
.jp-FormGroup-content .panel.errors {
display: none;
}
/* RJSF normal content (settings-editor) */
.jp-FormGroup-contentNormal {
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
margin-left: 7px;
color: var(--jp-ui-font-color0);
}
.jp-FormGroup-contentNormal .jp-FormGroup-description {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-default {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
font-size: var(--jp-content-font-size1);
font-weight: normal;
min-width: 120px;
}
.jp-FormGroup-contentNormal fieldset:not(:first-child) {
margin-left: 7px;
}
.jp-FormGroup-contentNormal .field-array-of-string .array-item {
/* Display `jp-ArrayOperations` buttons side-by-side with content except
for small screens where flex-wrap will place them one below the other.
*/
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
/* RJSF compact content (metadata-form) */
.jp-FormGroup-content.jp-FormGroup-contentCompact {
width: 100%;
}
.jp-FormGroup-contentCompact .form-group {
display: flex;
padding: 0.5em 0.2em 0.5em 0;
}
.jp-FormGroup-contentCompact
.jp-FormGroup-compactTitle
.jp-FormGroup-description {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color2);
}
.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
padding-bottom: 0.3em;
}
.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
width: 100%;
box-sizing: border-box;
}
.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
padding-bottom: 7px;
}
.jp-FormGroup-contentCompact
.jp-objectFieldWrapper
.jp-objectFieldWrapper
.form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
.jp-FormGroup-contentCompact ul.error-detail {
margin-block-start: 0.5em;
margin-block-end: 0.5em;
padding-inline-start: 1em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-SidePanel {
display: flex;
flex-direction: column;
min-width: var(--jp-sidebar-min-width);
overflow-y: auto;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
font-size: var(--jp-ui-font-size1);
}
.jp-SidePanel-header {
flex: 0 0 auto;
display: flex;
border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin: 0;
padding: 2px;
text-transform: uppercase;
}
.jp-SidePanel-toolbar {
flex: 0 0 auto;
}
.jp-SidePanel-content {
flex: 1 1 auto;
}
.jp-SidePanel-toolbar,
.jp-AccordionPanel-toolbar {
height: var(--jp-private-toolbar-height);
}
.jp-SidePanel-toolbar.jp-Toolbar-micro {
display: none;
}
.lm-AccordionPanel .jp-AccordionPanel-title {
box-sizing: border-box;
line-height: 25px;
margin: 0;
display: flex;
align-items: center;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
font-size: var(--jp-ui-font-size0);
}
.jp-AccordionPanel-title {
cursor: pointer;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
text-transform: uppercase;
}
.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
/* Title is rotated for horizontal accordion panel using CSS */
display: block;
transform-origin: top left;
transform: rotate(-90deg) translate(-100%);
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
user-select: none;
text-overflow: ellipsis;
white-space: nowrap;
overflow: hidden;
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
transform: rotate(-90deg);
margin: auto 0;
height: 16px;
}
.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
transform: rotate(0deg);
}
.lm-AccordionPanel .jp-AccordionPanel-toolbar {
background: none;
box-shadow: none;
border: none;
margin-left: auto;
}
.lm-AccordionPanel .lm-SplitPanel-handle:hover {
background: var(--jp-layout-color3);
}
.jp-text-truncated {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Spinner {
position: absolute;
display: flex;
justify-content: center;
align-items: center;
z-index: 10;
left: 0;
top: 0;
width: 100%;
height: 100%;
background: var(--jp-layout-color0);
outline: none;
}
.jp-SpinnerContent {
font-size: 10px;
margin: 50px auto;
text-indent: -9999em;
width: 3em;
height: 3em;
border-radius: 50%;
background: var(--jp-brand-color3);
background: linear-gradient(
to right,
#f37626 10%,
rgba(255, 255, 255, 0) 42%
);
position: relative;
animation: load3 1s infinite linear, fadeIn 1s;
}
.jp-SpinnerContent::before {
width: 50%;
height: 50%;
background: #f37626;
border-radius: 100% 0 0;
position: absolute;
top: 0;
left: 0;
content: '';
}
.jp-SpinnerContent::after {
background: var(--jp-layout-color0);
width: 75%;
height: 75%;
border-radius: 50%;
content: '';
margin: auto;
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
@keyframes load3 {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
button.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: none;
box-sizing: border-box;
text-align: center;
line-height: 32px;
height: 32px;
padding: 0 12px;
letter-spacing: 0.8px;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input.jp-mod-styled {
background: var(--jp-input-background);
height: 28px;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color1);
padding-left: 7px;
padding-right: 7px;
font-size: var(--jp-ui-font-size2);
color: var(--jp-ui-font-color0);
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input[type='checkbox'].jp-mod-styled {
appearance: checkbox;
-webkit-appearance: checkbox;
-moz-appearance: checkbox;
height: auto;
}
input.jp-mod-styled:focus {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-select-wrapper {
display: flex;
position: relative;
flex-direction: column;
padding: 1px;
background-color: var(--jp-layout-color1);
box-sizing: border-box;
margin-bottom: 12px;
}
.jp-select-wrapper:not(.multiple) {
height: 28px;
}
.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-input-active-background);
}
select.jp-mod-styled:hover {
cursor: pointer;
color: var(--jp-ui-font-color0);
background-color: var(--jp-input-hover-background);
box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
}
select.jp-mod-styled {
flex: 1 1 auto;
width: 100%;
font-size: var(--jp-ui-font-size2);
background: var(--jp-input-background);
color: var(--jp-ui-font-color0);
padding: 0 25px 0 8px;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
select.jp-mod-styled:not([multiple]) {
height: 32px;
}
select.jp-mod-styled[multiple] {
max-height: 200px;
overflow-y: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-switch {
display: flex;
align-items: center;
padding-left: 4px;
padding-right: 4px;
font-size: var(--jp-ui-font-size1);
background-color: transparent;
color: var(--jp-ui-font-color1);
border: none;
height: 20px;
}
.jp-switch:hover {
background-color: var(--jp-layout-color2);
}
.jp-switch-label {
margin-right: 5px;
font-family: var(--jp-ui-font-family);
}
.jp-switch-track {
cursor: pointer;
background-color: var(--jp-switch-color, var(--jp-border-color1));
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 34px;
height: 16px;
width: 35px;
position: relative;
}
.jp-switch-track::before {
content: '';
position: absolute;
height: 10px;
width: 10px;
margin: 3px;
left: 0;
background-color: var(--jp-ui-inverse-font-color1);
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 50%;
}
.jp-switch[aria-checked='true'] .jp-switch-track {
background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
}
.jp-switch[aria-checked='true'] .jp-switch-track::before {
/* track width (35) - margins (3 + 3) - thumb width (10) */
left: 19px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
:root {
--jp-private-toolbar-height: calc(
28px + var(--jp-border-width)
); /* leave 28px for content */
}
.jp-Toolbar {
color: var(--jp-ui-font-color1);
flex: 0 0 auto;
display: flex;
flex-direction: row;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: 2px;
z-index: 8;
overflow-x: hidden;
}
/* Toolbar items */
.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
flex-grow: 1;
flex-shrink: 1;
}
.jp-Toolbar-item.jp-Toolbar-kernelStatus {
display: inline-block;
width: 32px;
background-repeat: no-repeat;
background-position: center;
background-size: 16px;
}
.jp-Toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
display: flex;
padding-left: 1px;
padding-right: 1px;
font-size: var(--jp-ui-font-size1);
line-height: var(--jp-private-toolbar-height);
height: 100%;
}
/* Toolbar buttons */
/* This is the div we use to wrap the react component into a Widget */
div.jp-ToolbarButton {
color: transparent;
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0;
margin: 0;
}
button.jp-ToolbarButtonComponent {
background: var(--jp-layout-color1);
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0 6px;
margin: 0;
height: 24px;
border-radius: var(--jp-border-radius);
display: flex;
align-items: center;
text-align: center;
font-size: 14px;
min-width: unset;
min-height: unset;
}
button.jp-ToolbarButtonComponent:disabled {
opacity: 0.4;
}
button.jp-ToolbarButtonComponent > span {
padding: 0;
flex: 0 0 auto;
}
button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
font-size: var(--jp-ui-font-size1);
line-height: 100%;
padding-left: 2px;
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar.jp-Toolbar-micro {
padding: 0;
min-height: 0;
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar {
border: none;
box-shadow: none;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-WindowedPanel-outer {
position: relative;
overflow-y: auto;
}
.jp-WindowedPanel-inner {
position: relative;
}
.jp-WindowedPanel-window {
position: absolute;
left: 0;
right: 0;
overflow: visible;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/* Sibling imports */
body {
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
}
/* Disable native link decoration styles everywhere outside of dialog boxes */
a {
text-decoration: unset;
color: unset;
}
a:hover {
text-decoration: unset;
color: unset;
}
/* Accessibility for links inside dialog box text */
.jp-Dialog-content a {
text-decoration: revert;
color: var(--jp-content-link-color);
}
.jp-Dialog-content a:hover {
text-decoration: revert;
}
/* Styles for ui-components */
.jp-Button {
color: var(--jp-ui-font-color2);
border-radius: var(--jp-border-radius);
padding: 0 12px;
font-size: var(--jp-ui-font-size1);
/* Copy from blueprint 3 */
display: inline-flex;
flex-direction: row;
border: none;
cursor: pointer;
align-items: center;
justify-content: center;
text-align: left;
vertical-align: middle;
min-height: 30px;
min-width: 30px;
}
.jp-Button:disabled {
cursor: not-allowed;
}
.jp-Button:empty {
padding: 0 !important;
}
.jp-Button.jp-mod-small {
min-height: 24px;
min-width: 24px;
font-size: 12px;
padding: 0 7px;
}
/* Use our own theme for hover styles */
.jp-Button.jp-mod-minimal:hover {
background-color: var(--jp-layout-color2);
}
.jp-Button.jp-mod-minimal {
background: none;
}
.jp-InputGroup {
display: block;
position: relative;
}
.jp-InputGroup input {
box-sizing: border-box;
border: none;
border-radius: 0;
background-color: transparent;
color: var(--jp-ui-font-color0);
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
padding-bottom: 0;
padding-top: 0;
padding-left: 10px;
padding-right: 28px;
position: relative;
width: 100%;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
font-size: 14px;
font-weight: 400;
height: 30px;
line-height: 30px;
outline: none;
vertical-align: middle;
}
.jp-InputGroup input:focus {
box-shadow: inset 0 0 0 var(--jp-border-width)
var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-InputGroup input:disabled {
cursor: not-allowed;
resize: block;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input:disabled ~ span {
cursor: not-allowed;
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input::placeholder,
input::placeholder {
color: var(--jp-ui-font-color2);
}
.jp-InputGroupAction {
position: absolute;
bottom: 1px;
right: 0;
padding: 6px;
}
.jp-HTMLSelect.jp-DefaultStyle select {
background-color: initial;
border: none;
border-radius: 0;
box-shadow: none;
color: var(--jp-ui-font-color0);
display: block;
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
height: 24px;
line-height: 14px;
padding: 0 25px 0 10px;
text-align: left;
-moz-appearance: none;
-webkit-appearance: none;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
cursor: not-allowed;
resize: block;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
cursor: not-allowed;
}
/* Use our own theme for hover and option styles */
/* stylelint-disable-next-line selector-max-type */
.jp-HTMLSelect.jp-DefaultStyle select:hover,
.jp-HTMLSelect.jp-DefaultStyle select > option {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color0);
}
select {
box-sizing: border-box;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-StatusBar-Widget {
display: flex;
align-items: center;
background: var(--jp-layout-color2);
min-height: var(--jp-statusbar-height);
justify-content: space-between;
padding: 0 10px;
}
.jp-StatusBar-Left {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-StatusBar-Middle {
display: flex;
align-items: center;
}
.jp-StatusBar-Right {
display: flex;
align-items: center;
flex-direction: row-reverse;
}
.jp-StatusBar-Item {
max-height: var(--jp-statusbar-height);
margin: 0 2px;
height: var(--jp-statusbar-height);
white-space: nowrap;
text-overflow: ellipsis;
color: var(--jp-ui-font-color1);
padding: 0 6px;
}
.jp-mod-highlighted:hover {
background-color: var(--jp-layout-color3);
}
.jp-mod-clicked {
background-color: var(--jp-brand-color1);
}
.jp-mod-clicked:hover {
background-color: var(--jp-brand-color0);
}
.jp-mod-clicked .jp-StatusBar-TextItem {
color: var(--jp-ui-inverse-font-color1);
}
.jp-StatusBar-HoverItem {
box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
}
.jp-StatusBar-TextItem {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
line-height: 24px;
color: var(--jp-ui-font-color1);
}
.jp-StatusBar-GroupItem {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-Statusbar-ProgressCircle svg {
display: block;
margin: 0 auto;
width: 16px;
height: 24px;
align-self: normal;
}
.jp-Statusbar-ProgressCircle path {
fill: var(--jp-inverse-layout-color3);
}
.jp-Statusbar-ProgressBar-progress-bar {
height: 10px;
width: 100px;
border: solid 0.25px var(--jp-brand-color2);
border-radius: 3px;
overflow: hidden;
align-self: center;
}
.jp-Statusbar-ProgressBar-progress-bar > div {
background-color: var(--jp-brand-color2);
background-image: linear-gradient(
-45deg,
rgba(255, 255, 255, 0.2) 25%,
transparent 25%,
transparent 50%,
rgba(255, 255, 255, 0.2) 50%,
rgba(255, 255, 255, 0.2) 75%,
transparent 75%,
transparent
);
background-size: 40px 40px;
float: left;
width: 0%;
height: 100%;
font-size: 12px;
line-height: 14px;
color: #fff;
text-align: center;
animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
}
.jp-Statusbar-ProgressBar-progress-bar p {
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
font-size: var(--jp-ui-font-size1);
line-height: 10px;
width: 100px;
}
@keyframes jp-Statusbar-ExecutionTime-progress-bar {
0% {
background-position: 0 0;
}
100% {
background-position: 40px 40px;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-commandpalette-search-height: 28px;
}
/*-----------------------------------------------------------------------------
| Overall styles
|----------------------------------------------------------------------------*/
.lm-CommandPalette {
padding-bottom: 0;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Modal variant
|----------------------------------------------------------------------------*/
.jp-ModalCommandPalette {
position: absolute;
z-index: 10000;
top: 38px;
left: 30%;
margin: 0;
padding: 4px;
width: 40%;
box-shadow: var(--jp-elevation-z4);
border-radius: 4px;
background: var(--jp-layout-color0);
}
.jp-ModalCommandPalette .lm-CommandPalette {
max-height: 40vh;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
margin-left: 4px;
margin-right: 4px;
}
.jp-ModalCommandPalette
.lm-CommandPalette
.lm-CommandPalette-item.lm-mod-disabled {
display: none;
}
/*-----------------------------------------------------------------------------
| Search
|----------------------------------------------------------------------------*/
.lm-CommandPalette-search {
padding: 4px;
background-color: var(--jp-layout-color1);
z-index: 2;
}
.lm-CommandPalette-wrapper {
overflow: overlay;
padding: 0 9px;
background-color: var(--jp-input-active-background);
height: 30px;
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
}
.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-SearchIconGroup {
color: white;
background-color: var(--jp-brand-color1);
position: absolute;
top: 4px;
right: 4px;
padding: 5px 5px 1px;
}
.jp-SearchIconGroup svg {
height: 20px;
width: 20px;
}
.jp-SearchIconGroup .jp-icon3[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-input {
background: transparent;
width: calc(100% - 18px);
float: left;
border: none;
outline: none;
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
line-height: var(--jp-private-commandpalette-search-height);
}
.lm-CommandPalette-input::-webkit-input-placeholder,
.lm-CommandPalette-input::-moz-placeholder,
.lm-CommandPalette-input:-ms-input-placeholder {
color: var(--jp-ui-font-color2);
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Results
|----------------------------------------------------------------------------*/
.lm-CommandPalette-header:first-child {
margin-top: 0;
}
.lm-CommandPalette-header {
border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
color: var(--jp-ui-font-color1);
cursor: pointer;
display: flex;
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin-top: 8px;
padding: 8px 0 8px 12px;
text-transform: uppercase;
}
.lm-CommandPalette-header.lm-mod-active {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-header > mark {
background-color: transparent;
font-weight: bold;
color: var(--jp-ui-font-color1);
}
.lm-CommandPalette-item {
padding: 4px 12px 4px 4px;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
font-weight: 400;
display: flex;
}
.lm-CommandPalette-item.lm-mod-disabled {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item.lm-mod-active {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-inverse-font-color0);
}
.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-itemContent {
overflow: hidden;
}
.lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.lm-CommandPalette-item.lm-mod-disabled mark {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
margin: 0 4px 0 0;
position: relative;
width: 16px;
top: 2px;
flex: 0 0 auto;
}
.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
opacity: 0.6;
}
.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
flex: 0 0 auto;
}
.lm-CommandPalette-itemCaption {
display: none;
}
.lm-CommandPalette-content {
background-color: var(--jp-layout-color1);
}
.lm-CommandPalette-content:empty::after {
content: 'No results';
margin: auto;
margin-top: 20px;
width: 100px;
display: block;
font-size: var(--jp-ui-font-size2);
font-family: var(--jp-ui-font-family);
font-weight: lighter;
}
.lm-CommandPalette-emptyMessage {
text-align: center;
margin-top: 24px;
line-height: 1.32;
padding: 0 8px;
color: var(--jp-content-font-color3);
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Dialog {
position: absolute;
z-index: 10000;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
top: 0;
left: 0;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
background: var(--jp-dialog-background);
}
.jp-Dialog-content {
display: flex;
flex-direction: column;
margin-left: auto;
margin-right: auto;
background: var(--jp-layout-color1);
padding: 24px 24px 12px;
min-width: 300px;
min-height: 150px;
max-width: 1000px;
max-height: 500px;
box-sizing: border-box;
box-shadow: var(--jp-elevation-z20);
word-wrap: break-word;
border-radius: var(--jp-border-radius);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color1);
resize: both;
}
.jp-Dialog-content.jp-Dialog-content-small {
max-width: 500px;
}
.jp-Dialog-button {
overflow: visible;
}
button.jp-Dialog-button:focus {
outline: 1px solid var(--jp-brand-color1);
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button:focus::-moz-focus-inner {
border: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
}
button.jp-Dialog-close-button {
padding: 0;
height: 100%;
min-width: unset;
min-height: unset;
}
.jp-Dialog-header {
display: flex;
justify-content: space-between;
flex: 0 0 auto;
padding-bottom: 12px;
font-size: var(--jp-ui-font-size3);
font-weight: 400;
color: var(--jp-ui-font-color1);
}
.jp-Dialog-body {
display: flex;
flex-direction: column;
flex: 1 1 auto;
font-size: var(--jp-ui-font-size1);
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
overflow: auto;
}
.jp-Dialog-footer {
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
flex: 0 0 auto;
margin-left: -12px;
margin-right: -12px;
padding: 12px;
}
.jp-Dialog-checkbox {
padding-right: 5px;
}
.jp-Dialog-checkbox > input:focus-visible {
outline: 1px solid var(--jp-input-active-border-color);
outline-offset: 1px;
}
.jp-Dialog-spacer {
flex: 1 1 auto;
}
.jp-Dialog-title {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.jp-Dialog-body > .jp-select-wrapper {
width: 100%;
}
.jp-Dialog-body > button {
padding: 0 16px;
}
.jp-Dialog-body > label {
line-height: 1.4;
color: var(--jp-ui-font-color0);
}
.jp-Dialog-button.jp-mod-styled:not(:last-child) {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Input-Boolean-Dialog {
flex-direction: row-reverse;
align-items: end;
width: 100%;
}
.jp-Input-Boolean-Dialog > label {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MainAreaWidget > :focus {
outline: none;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error {
padding: 6px;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
width: auto;
padding: 10px;
background: var(--jp-error-color3);
border: var(--jp-border-width) solid var(--jp-error-color1);
border-radius: var(--jp-border-radius);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
white-space: pre-wrap;
word-wrap: break-word;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/**
* google-material-color v1.2.6
* https://github.com/danlevan/google-material-color
*/
:root {
--md-red-50: #ffebee;
--md-red-100: #ffcdd2;
--md-red-200: #ef9a9a;
--md-red-300: #e57373;
--md-red-400: #ef5350;
--md-red-500: #f44336;
--md-red-600: #e53935;
--md-red-700: #d32f2f;
--md-red-800: #c62828;
--md-red-900: #b71c1c;
--md-red-A100: #ff8a80;
--md-red-A200: #ff5252;
--md-red-A400: #ff1744;
--md-red-A700: #d50000;
--md-pink-50: #fce4ec;
--md-pink-100: #f8bbd0;
--md-pink-200: #f48fb1;
--md-pink-300: #f06292;
--md-pink-400: #ec407a;
--md-pink-500: #e91e63;
--md-pink-600: #d81b60;
--md-pink-700: #c2185b;
--md-pink-800: #ad1457;
--md-pink-900: #880e4f;
--md-pink-A100: #ff80ab;
--md-pink-A200: #ff4081;
--md-pink-A400: #f50057;
--md-pink-A700: #c51162;
--md-purple-50: #f3e5f5;
--md-purple-100: #e1bee7;
--md-purple-200: #ce93d8;
--md-purple-300: #ba68c8;
--md-purple-400: #ab47bc;
--md-purple-500: #9c27b0;
--md-purple-600: #8e24aa;
--md-purple-700: #7b1fa2;
--md-purple-800: #6a1b9a;
--md-purple-900: #4a148c;
--md-purple-A100: #ea80fc;
--md-purple-A200: #e040fb;
--md-purple-A400: #d500f9;
--md-purple-A700: #a0f;
--md-deep-purple-50: #ede7f6;
--md-deep-purple-100: #d1c4e9;
--md-deep-purple-200: #b39ddb;
--md-deep-purple-300: #9575cd;
--md-deep-purple-400: #7e57c2;
--md-deep-purple-500: #673ab7;
--md-deep-purple-600: #5e35b1;
--md-deep-purple-700: #512da8;
--md-deep-purple-800: #4527a0;
--md-deep-purple-900: #311b92;
--md-deep-purple-A100: #b388ff;
--md-deep-purple-A200: #7c4dff;
--md-deep-purple-A400: #651fff;
--md-deep-purple-A700: #6200ea;
--md-indigo-50: #e8eaf6;
--md-indigo-100: #c5cae9;
--md-indigo-200: #9fa8da;
--md-indigo-300: #7986cb;
--md-indigo-400: #5c6bc0;
--md-indigo-500: #3f51b5;
--md-indigo-600: #3949ab;
--md-indigo-700: #303f9f;
--md-indigo-800: #283593;
--md-indigo-900: #1a237e;
--md-indigo-A100: #8c9eff;
--md-indigo-A200: #536dfe;
--md-indigo-A400: #3d5afe;
--md-indigo-A700: #304ffe;
--md-blue-50: #e3f2fd;
--md-blue-100: #bbdefb;
--md-blue-200: #90caf9;
--md-blue-300: #64b5f6;
--md-blue-400: #42a5f5;
--md-blue-500: #2196f3;
--md-blue-600: #1e88e5;
--md-blue-700: #1976d2;
--md-blue-800: #1565c0;
--md-blue-900: #0d47a1;
--md-blue-A100: #82b1ff;
--md-blue-A200: #448aff;
--md-blue-A400: #2979ff;
--md-blue-A700: #2962ff;
--md-light-blue-50: #e1f5fe;
--md-light-blue-100: #b3e5fc;
--md-light-blue-200: #81d4fa;
--md-light-blue-300: #4fc3f7;
--md-light-blue-400: #29b6f6;
--md-light-blue-500: #03a9f4;
--md-light-blue-600: #039be5;
--md-light-blue-700: #0288d1;
--md-light-blue-800: #0277bd;
--md-light-blue-900: #01579b;
--md-light-blue-A100: #80d8ff;
--md-light-blue-A200: #40c4ff;
--md-light-blue-A400: #00b0ff;
--md-light-blue-A700: #0091ea;
--md-cyan-50: #e0f7fa;
--md-cyan-100: #b2ebf2;
--md-cyan-200: #80deea;
--md-cyan-300: #4dd0e1;
--md-cyan-400: #26c6da;
--md-cyan-500: #00bcd4;
--md-cyan-600: #00acc1;
--md-cyan-700: #0097a7;
--md-cyan-800: #00838f;
--md-cyan-900: #006064;
--md-cyan-A100: #84ffff;
--md-cyan-A200: #18ffff;
--md-cyan-A400: #00e5ff;
--md-cyan-A700: #00b8d4;
--md-teal-50: #e0f2f1;
--md-teal-100: #b2dfdb;
--md-teal-200: #80cbc4;
--md-teal-300: #4db6ac;
--md-teal-400: #26a69a;
--md-teal-500: #009688;
--md-teal-600: #00897b;
--md-teal-700: #00796b;
--md-teal-800: #00695c;
--md-teal-900: #004d40;
--md-teal-A100: #a7ffeb;
--md-teal-A200: #64ffda;
--md-teal-A400: #1de9b6;
--md-teal-A700: #00bfa5;
--md-green-50: #e8f5e9;
--md-green-100: #c8e6c9;
--md-green-200: #a5d6a7;
--md-green-300: #81c784;
--md-green-400: #66bb6a;
--md-green-500: #4caf50;
--md-green-600: #43a047;
--md-green-700: #388e3c;
--md-green-800: #2e7d32;
--md-green-900: #1b5e20;
--md-green-A100: #b9f6ca;
--md-green-A200: #69f0ae;
--md-green-A400: #00e676;
--md-green-A700: #00c853;
--md-light-green-50: #f1f8e9;
--md-light-green-100: #dcedc8;
--md-light-green-200: #c5e1a5;
--md-light-green-300: #aed581;
--md-light-green-400: #9ccc65;
--md-light-green-500: #8bc34a;
--md-light-green-600: #7cb342;
--md-light-green-700: #689f38;
--md-light-green-800: #558b2f;
--md-light-green-900: #33691e;
--md-light-green-A100: #ccff90;
--md-light-green-A200: #b2ff59;
--md-light-green-A400: #76ff03;
--md-light-green-A700: #64dd17;
--md-lime-50: #f9fbe7;
--md-lime-100: #f0f4c3;
--md-lime-200: #e6ee9c;
--md-lime-300: #dce775;
--md-lime-400: #d4e157;
--md-lime-500: #cddc39;
--md-lime-600: #c0ca33;
--md-lime-700: #afb42b;
--md-lime-800: #9e9d24;
--md-lime-900: #827717;
--md-lime-A100: #f4ff81;
--md-lime-A200: #eeff41;
--md-lime-A400: #c6ff00;
--md-lime-A700: #aeea00;
--md-yellow-50: #fffde7;
--md-yellow-100: #fff9c4;
--md-yellow-200: #fff59d;
--md-yellow-300: #fff176;
--md-yellow-400: #ffee58;
--md-yellow-500: #ffeb3b;
--md-yellow-600: #fdd835;
--md-yellow-700: #fbc02d;
--md-yellow-800: #f9a825;
--md-yellow-900: #f57f17;
--md-yellow-A100: #ffff8d;
--md-yellow-A200: #ff0;
--md-yellow-A400: #ffea00;
--md-yellow-A700: #ffd600;
--md-amber-50: #fff8e1;
--md-amber-100: #ffecb3;
--md-amber-200: #ffe082;
--md-amber-300: #ffd54f;
--md-amber-400: #ffca28;
--md-amber-500: #ffc107;
--md-amber-600: #ffb300;
--md-amber-700: #ffa000;
--md-amber-800: #ff8f00;
--md-amber-900: #ff6f00;
--md-amber-A100: #ffe57f;
--md-amber-A200: #ffd740;
--md-amber-A400: #ffc400;
--md-amber-A700: #ffab00;
--md-orange-50: #fff3e0;
--md-orange-100: #ffe0b2;
--md-orange-200: #ffcc80;
--md-orange-300: #ffb74d;
--md-orange-400: #ffa726;
--md-orange-500: #ff9800;
--md-orange-600: #fb8c00;
--md-orange-700: #f57c00;
--md-orange-800: #ef6c00;
--md-orange-900: #e65100;
--md-orange-A100: #ffd180;
--md-orange-A200: #ffab40;
--md-orange-A400: #ff9100;
--md-orange-A700: #ff6d00;
--md-deep-orange-50: #fbe9e7;
--md-deep-orange-100: #ffccbc;
--md-deep-orange-200: #ffab91;
--md-deep-orange-300: #ff8a65;
--md-deep-orange-400: #ff7043;
--md-deep-orange-500: #ff5722;
--md-deep-orange-600: #f4511e;
--md-deep-orange-700: #e64a19;
--md-deep-orange-800: #d84315;
--md-deep-orange-900: #bf360c;
--md-deep-orange-A100: #ff9e80;
--md-deep-orange-A200: #ff6e40;
--md-deep-orange-A400: #ff3d00;
--md-deep-orange-A700: #dd2c00;
--md-brown-50: #efebe9;
--md-brown-100: #d7ccc8;
--md-brown-200: #bcaaa4;
--md-brown-300: #a1887f;
--md-brown-400: #8d6e63;
--md-brown-500: #795548;
--md-brown-600: #6d4c41;
--md-brown-700: #5d4037;
--md-brown-800: #4e342e;
--md-brown-900: #3e2723;
--md-grey-50: #fafafa;
--md-grey-100: #f5f5f5;
--md-grey-200: #eee;
--md-grey-300: #e0e0e0;
--md-grey-400: #bdbdbd;
--md-grey-500: #9e9e9e;
--md-grey-600: #757575;
--md-grey-700: #616161;
--md-grey-800: #424242;
--md-grey-900: #212121;
--md-blue-grey-50: #eceff1;
--md-blue-grey-100: #cfd8dc;
--md-blue-grey-200: #b0bec5;
--md-blue-grey-300: #90a4ae;
--md-blue-grey-400: #78909c;
--md-blue-grey-500: #607d8b;
--md-blue-grey-600: #546e7a;
--md-blue-grey-700: #455a64;
--md-blue-grey-800: #37474f;
--md-blue-grey-900: #263238;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| RenderedText
|----------------------------------------------------------------------------*/
:root {
/* This is the padding value to fill the gaps between lines containing spans with background color. */
--jp-private-code-span-padding: calc(
(var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
);
}
.jp-RenderedText {
text-align: left;
padding-left: var(--jp-code-padding);
line-height: var(--jp-code-line-height);
font-family: var(--jp-code-font-family);
}
.jp-RenderedText pre,
.jp-RenderedJavaScript pre,
.jp-RenderedHTMLCommon pre {
color: var(--jp-content-font-color1);
font-size: var(--jp-code-font-size);
border: none;
margin: 0;
padding: 0;
}
.jp-RenderedText pre a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* console foregrounds and backgrounds */
.jp-RenderedText pre .ansi-black-fg {
color: #3e424d;
}
.jp-RenderedText pre .ansi-red-fg {
color: #e75c58;
}
.jp-RenderedText pre .ansi-green-fg {
color: #00a250;
}
.jp-RenderedText pre .ansi-yellow-fg {
color: #ddb62b;
}
.jp-RenderedText pre .ansi-blue-fg {
color: #208ffb;
}
.jp-RenderedText pre .ansi-magenta-fg {
color: #d160c4;
}
.jp-RenderedText pre .ansi-cyan-fg {
color: #60c6c8;
}
.jp-RenderedText pre .ansi-white-fg {
color: #c5c1b4;
}
.jp-RenderedText pre .ansi-black-bg {
background-color: #3e424d;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-bg {
background-color: #e75c58;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-bg {
background-color: #00a250;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-bg {
background-color: #ddb62b;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-bg {
background-color: #208ffb;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-bg {
background-color: #d160c4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-bg {
background-color: #60c6c8;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-bg {
background-color: #c5c1b4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-black-intense-fg {
color: #282c36;
}
.jp-RenderedText pre .ansi-red-intense-fg {
color: #b22b31;
}
.jp-RenderedText pre .ansi-green-intense-fg {
color: #007427;
}
.jp-RenderedText pre .ansi-yellow-intense-fg {
color: #b27d12;
}
.jp-RenderedText pre .ansi-blue-intense-fg {
color: #0065ca;
}
.jp-RenderedText pre .ansi-magenta-intense-fg {
color: #a03196;
}
.jp-RenderedText pre .ansi-cyan-intense-fg {
color: #258f8f;
}
.jp-RenderedText pre .ansi-white-intense-fg {
color: #a1a6b2;
}
.jp-RenderedText pre .ansi-black-intense-bg {
background-color: #282c36;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-intense-bg {
background-color: #b22b31;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-intense-bg {
background-color: #007427;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-intense-bg {
background-color: #b27d12;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-intense-bg {
background-color: #0065ca;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-intense-bg {
background-color: #a03196;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-intense-bg {
background-color: #258f8f;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-intense-bg {
background-color: #a1a6b2;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-default-inverse-fg {
color: var(--jp-ui-inverse-font-color0);
}
.jp-RenderedText pre .ansi-default-inverse-bg {
background-color: var(--jp-inverse-layout-color0);
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-bold {
font-weight: bold;
}
.jp-RenderedText pre .ansi-underline {
text-decoration: underline;
}
.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
background: var(--jp-rendermime-error-background);
padding-top: var(--jp-code-padding);
}
/*-----------------------------------------------------------------------------
| RenderedLatex
|----------------------------------------------------------------------------*/
.jp-RenderedLatex {
color: var(--jp-content-font-color1);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
}
/* Left-justify outputs.*/
.jp-OutputArea-output.jp-RenderedLatex {
padding: var(--jp-code-padding);
text-align: left;
}
/*-----------------------------------------------------------------------------
| RenderedHTML
|----------------------------------------------------------------------------*/
.jp-RenderedHTMLCommon {
color: var(--jp-content-font-color1);
font-family: var(--jp-content-font-family);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
/* Give a bit more R padding on Markdown text to keep line lengths reasonable */
padding-right: 20px;
}
.jp-RenderedHTMLCommon em {
font-style: italic;
}
.jp-RenderedHTMLCommon strong {
font-weight: bold;
}
.jp-RenderedHTMLCommon u {
text-decoration: underline;
}
.jp-RenderedHTMLCommon a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* Headings */
.jp-RenderedHTMLCommon h1,
.jp-RenderedHTMLCommon h2,
.jp-RenderedHTMLCommon h3,
.jp-RenderedHTMLCommon h4,
.jp-RenderedHTMLCommon h5,
.jp-RenderedHTMLCommon h6 {
line-height: var(--jp-content-heading-line-height);
font-weight: var(--jp-content-heading-font-weight);
font-style: normal;
margin: var(--jp-content-heading-margin-top) 0
var(--jp-content-heading-margin-bottom) 0;
}
.jp-RenderedHTMLCommon h1:first-child,
.jp-RenderedHTMLCommon h2:first-child,
.jp-RenderedHTMLCommon h3:first-child,
.jp-RenderedHTMLCommon h4:first-child,
.jp-RenderedHTMLCommon h5:first-child,
.jp-RenderedHTMLCommon h6:first-child {
margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
}
.jp-RenderedHTMLCommon h1:last-child,
.jp-RenderedHTMLCommon h2:last-child,
.jp-RenderedHTMLCommon h3:last-child,
.jp-RenderedHTMLCommon h4:last-child,
.jp-RenderedHTMLCommon h5:last-child,
.jp-RenderedHTMLCommon h6:last-child {
margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
}
.jp-RenderedHTMLCommon h1 {
font-size: var(--jp-content-font-size5);
}
.jp-RenderedHTMLCommon h2 {
font-size: var(--jp-content-font-size4);
}
.jp-RenderedHTMLCommon h3 {
font-size: var(--jp-content-font-size3);
}
.jp-RenderedHTMLCommon h4 {
font-size: var(--jp-content-font-size2);
}
.jp-RenderedHTMLCommon h5 {
font-size: var(--jp-content-font-size1);
}
.jp-RenderedHTMLCommon h6 {
font-size: var(--jp-content-font-size0);
}
/* Lists */
/* stylelint-disable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon ul:not(.list-inline),
.jp-RenderedHTMLCommon ol:not(.list-inline) {
padding-left: 2em;
}
.jp-RenderedHTMLCommon ul {
list-style: disc;
}
.jp-RenderedHTMLCommon ul ul {
list-style: square;
}
.jp-RenderedHTMLCommon ul ul ul {
list-style: circle;
}
.jp-RenderedHTMLCommon ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol ol {
list-style: upper-alpha;
}
.jp-RenderedHTMLCommon ol ol ol {
list-style: lower-alpha;
}
.jp-RenderedHTMLCommon ol ol ol ol {
list-style: lower-roman;
}
.jp-RenderedHTMLCommon ol ol ol ol ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol,
.jp-RenderedHTMLCommon ul {
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon ul ul,
.jp-RenderedHTMLCommon ul ol,
.jp-RenderedHTMLCommon ol ul,
.jp-RenderedHTMLCommon ol ol {
margin-bottom: 0;
}
/* stylelint-enable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon hr {
color: var(--jp-border-color2);
background-color: var(--jp-border-color1);
margin-top: 1em;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon > pre {
margin: 1.5em 2em;
}
.jp-RenderedHTMLCommon pre,
.jp-RenderedHTMLCommon code {
border: 0;
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
font-family: var(--jp-code-font-family);
font-size: inherit;
line-height: var(--jp-code-line-height);
padding: 0;
white-space: pre-wrap;
}
.jp-RenderedHTMLCommon :not(pre) > code {
background-color: var(--jp-layout-color2);
padding: 1px 5px;
}
/* Tables */
.jp-RenderedHTMLCommon table {
border-collapse: collapse;
border-spacing: 0;
border: none;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
table-layout: fixed;
margin-left: auto;
margin-bottom: 1em;
margin-right: auto;
}
.jp-RenderedHTMLCommon thead {
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
vertical-align: bottom;
}
.jp-RenderedHTMLCommon td,
.jp-RenderedHTMLCommon th,
.jp-RenderedHTMLCommon tr {
vertical-align: middle;
padding: 0.5em;
line-height: normal;
white-space: normal;
max-width: none;
border: none;
}
.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
max-width: none;
}
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
text-align: right;
}
.jp-RenderedHTMLCommon th {
font-weight: bold;
}
.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
background: var(--jp-layout-color0);
}
.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
background: var(--jp-rendermime-table-row-background);
}
.jp-RenderedHTMLCommon tbody tr:hover {
background: var(--jp-rendermime-table-row-hover-background);
}
.jp-RenderedHTMLCommon p {
text-align: left;
margin: 0;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon img {
-moz-force-broken-image-icon: 1;
}
/* Restrict to direct children as other images could be nested in other content. */
.jp-RenderedHTMLCommon > img {
display: block;
margin-left: 0;
margin-right: 0;
margin-bottom: 1em;
}
/* Change color behind transparent images if they need it... */
[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
background-color: var(--jp-inverse-layout-color1);
}
[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
background-color: var(--jp-inverse-layout-color1);
}
.jp-RenderedHTMLCommon img,
.jp-RenderedImage img,
.jp-RenderedHTMLCommon svg,
.jp-RenderedSVG svg {
max-width: 100%;
height: auto;
}
.jp-RenderedHTMLCommon img.jp-mod-unconfined,
.jp-RenderedImage img.jp-mod-unconfined,
.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
.jp-RenderedSVG svg.jp-mod-unconfined {
max-width: none;
}
.jp-RenderedHTMLCommon .alert {
padding: var(--jp-notebook-padding);
border: var(--jp-border-width) solid transparent;
border-radius: var(--jp-border-radius);
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon .alert-info {
color: var(--jp-info-color0);
background-color: var(--jp-info-color3);
border-color: var(--jp-info-color2);
}
.jp-RenderedHTMLCommon .alert-info hr {
border-color: var(--jp-info-color3);
}
.jp-RenderedHTMLCommon .alert-info > p:last-child,
.jp-RenderedHTMLCommon .alert-info > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-warning {
color: var(--jp-warn-color0);
background-color: var(--jp-warn-color3);
border-color: var(--jp-warn-color2);
}
.jp-RenderedHTMLCommon .alert-warning hr {
border-color: var(--jp-warn-color3);
}
.jp-RenderedHTMLCommon .alert-warning > p:last-child,
.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-success {
color: var(--jp-success-color0);
background-color: var(--jp-success-color3);
border-color: var(--jp-success-color2);
}
.jp-RenderedHTMLCommon .alert-success hr {
border-color: var(--jp-success-color3);
}
.jp-RenderedHTMLCommon .alert-success > p:last-child,
.jp-RenderedHTMLCommon .alert-success > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-danger {
color: var(--jp-error-color0);
background-color: var(--jp-error-color3);
border-color: var(--jp-error-color2);
}
.jp-RenderedHTMLCommon .alert-danger hr {
border-color: var(--jp-error-color3);
}
.jp-RenderedHTMLCommon .alert-danger > p:last-child,
.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon blockquote {
margin: 1em 2em;
padding: 0 1em;
border-left: 5px solid var(--jp-border-color2);
}
a.jp-InternalAnchorLink {
visibility: hidden;
margin-left: 8px;
color: var(--md-blue-800);
}
h1:hover .jp-InternalAnchorLink,
h2:hover .jp-InternalAnchorLink,
h3:hover .jp-InternalAnchorLink,
h4:hover .jp-InternalAnchorLink,
h5:hover .jp-InternalAnchorLink,
h6:hover .jp-InternalAnchorLink {
visibility: visible;
}
.jp-RenderedHTMLCommon kbd {
background-color: var(--jp-rendermime-table-row-background);
border: 1px solid var(--jp-border-color0);
border-bottom-color: var(--jp-border-color2);
border-radius: 3px;
box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
display: inline-block;
font-size: var(--jp-ui-font-size0);
line-height: 1em;
padding: 0.2em 0.5em;
}
/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
* At the bottom of cells this is a bit too much as there is also spacing
* between cells. Going all the way to 0 gets too tight between markdown and
* code cells.
*/
.jp-RenderedHTMLCommon > *:last-child {
margin-bottom: 0.5em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Copyright (c) 2014-2017, PhosphorJS Contributors
|
| Distributed under the terms of the BSD 3-Clause License.
|
| The full license is in the file LICENSE, distributed with this software.
|----------------------------------------------------------------------------*/
.lm-cursor-backdrop {
position: fixed;
width: 200px;
height: 200px;
margin-top: -100px;
margin-left: -100px;
will-change: transform;
z-index: 100;
}
.lm-mod-drag-image {
will-change: transform;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-lineFormSearch {
padding: 4px 12px;
background-color: var(--jp-layout-color2);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
font-size: var(--jp-ui-font-size1);
}
.jp-lineFormCaption {
font-size: var(--jp-ui-font-size0);
line-height: var(--jp-ui-font-size1);
margin-top: 4px;
color: var(--jp-ui-font-color0);
}
.jp-baseLineForm {
border: none;
border-radius: 0;
position: absolute;
background-size: 16px;
background-repeat: no-repeat;
background-position: center;
outline: none;
}
.jp-lineFormButtonContainer {
top: 4px;
right: 8px;
height: 24px;
padding: 0 12px;
width: 12px;
}
.jp-lineFormButtonIcon {
top: 0;
right: 0;
background-color: var(--jp-brand-color1);
height: 100%;
width: 100%;
box-sizing: border-box;
padding: 4px 6px;
}
.jp-lineFormButton {
top: 0;
right: 0;
background-color: transparent;
height: 100%;
width: 100%;
box-sizing: border-box;
}
.jp-lineFormWrapper {
overflow: hidden;
padding: 0 8px;
border: 1px solid var(--jp-border-color0);
background-color: var(--jp-input-active-background);
height: 22px;
}
.jp-lineFormWrapperFocusWithin {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-lineFormInput {
background: transparent;
width: 200px;
height: 100%;
border: none;
outline: none;
color: var(--jp-ui-font-color0);
line-height: 28px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-JSONEditor {
display: flex;
flex-direction: column;
width: 100%;
}
.jp-JSONEditor-host {
flex: 1 1 auto;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
background: var(--jp-layout-color0);
min-height: 50px;
padding: 1px;
}
.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
border-color: red;
outline-color: red;
}
.jp-JSONEditor-header {
display: flex;
flex: 1 0 auto;
padding: 0 0 0 12px;
}
.jp-JSONEditor-header label {
flex: 0 0 auto;
}
.jp-JSONEditor-commitButton {
height: 16px;
width: 16px;
background-size: 18px;
background-repeat: no-repeat;
background-position: center;
}
.jp-JSONEditor-host.jp-mod-focused {
background-color: var(--jp-input-active-background);
border: 1px solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
.jp-Editor.jp-mod-dropTarget {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-DocumentSearch-input {
border: none;
outline: none;
color: var(--jp-ui-font-color0);
font-size: var(--jp-ui-font-size1);
background-color: var(--jp-layout-color0);
font-family: var(--jp-ui-font-family);
padding: 2px 1px;
resize: none;
}
.jp-DocumentSearch-overlay {
position: absolute;
background-color: var(--jp-toolbar-background);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
top: 0;
right: 0;
z-index: 7;
min-width: 405px;
padding: 2px;
font-size: var(--jp-ui-font-size1);
--jp-private-document-search-button-height: 20px;
}
.jp-DocumentSearch-overlay button {
background-color: var(--jp-toolbar-background);
outline: 0;
}
.jp-DocumentSearch-overlay button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-overlay button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-overlay-row {
display: flex;
align-items: center;
margin-bottom: 2px;
}
.jp-DocumentSearch-button-content {
display: inline-block;
cursor: pointer;
box-sizing: border-box;
width: 100%;
height: 100%;
}
.jp-DocumentSearch-button-content svg {
width: 100%;
height: 100%;
}
.jp-DocumentSearch-input-wrapper {
border: var(--jp-border-width) solid var(--jp-border-color0);
display: flex;
background-color: var(--jp-layout-color0);
margin: 2px;
}
.jp-DocumentSearch-input-wrapper:focus-within {
border-color: var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper {
all: initial;
overflow: hidden;
display: inline-block;
border: none;
box-sizing: border-box;
}
.jp-DocumentSearch-toggle-wrapper {
width: 14px;
height: 14px;
}
.jp-DocumentSearch-button-wrapper {
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
}
.jp-DocumentSearch-toggle-wrapper:focus,
.jp-DocumentSearch-button-wrapper:focus {
outline: var(--jp-border-width) solid
var(--jp-cell-editor-active-border-color);
outline-offset: -1px;
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper,
.jp-DocumentSearch-button-content:focus {
outline: none;
}
.jp-DocumentSearch-toggle-placeholder {
width: 5px;
}
.jp-DocumentSearch-input-button::before {
display: block;
padding-top: 100%;
}
.jp-DocumentSearch-input-button-off {
opacity: var(--jp-search-toggle-off-opacity);
}
.jp-DocumentSearch-input-button-off:hover {
opacity: var(--jp-search-toggle-hover-opacity);
}
.jp-DocumentSearch-input-button-on {
opacity: var(--jp-search-toggle-on-opacity);
}
.jp-DocumentSearch-index-counter {
padding-left: 10px;
padding-right: 10px;
user-select: none;
min-width: 35px;
display: inline-block;
}
.jp-DocumentSearch-up-down-wrapper {
display: inline-block;
padding-right: 2px;
margin-left: auto;
white-space: nowrap;
}
.jp-DocumentSearch-spacer {
margin-left: auto;
}
.jp-DocumentSearch-up-down-wrapper button {
outline: 0;
border: none;
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
vertical-align: middle;
margin: 1px 5px 2px;
}
.jp-DocumentSearch-up-down-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-up-down-button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-filter-button {
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-filter-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled:hover {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-search-options {
padding: 0 8px;
margin-left: 3px;
width: 100%;
display: grid;
justify-content: start;
grid-template-columns: 1fr 1fr;
align-items: center;
justify-items: stretch;
}
.jp-DocumentSearch-search-filter-disabled {
color: var(--jp-ui-font-color2);
}
.jp-DocumentSearch-search-filter {
display: flex;
align-items: center;
user-select: none;
}
.jp-DocumentSearch-regex-error {
color: var(--jp-error-color0);
}
.jp-DocumentSearch-replace-button-wrapper {
overflow: hidden;
display: inline-block;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color0);
margin: auto 2px;
padding: 1px 4px;
height: calc(var(--jp-private-document-search-button-height) + 2px);
}
.jp-DocumentSearch-replace-button-wrapper:focus {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-replace-button {
display: inline-block;
text-align: center;
cursor: pointer;
box-sizing: border-box;
color: var(--jp-ui-font-color1);
/* height - 2 * (padding of wrapper) */
line-height: calc(var(--jp-private-document-search-button-height) - 2px);
width: 100%;
height: 100%;
}
.jp-DocumentSearch-replace-button:focus {
outline: none;
}
.jp-DocumentSearch-replace-wrapper-class {
margin-left: 14px;
display: flex;
}
.jp-DocumentSearch-replace-toggle {
border: none;
background-color: var(--jp-toolbar-background);
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-replace-toggle:hover {
background-color: var(--jp-layout-color2);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.cm-editor {
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
border: 0;
border-radius: 0;
height: auto;
/* Changed to auto to autogrow */
}
.cm-editor pre {
padding: 0 var(--jp-code-padding);
}
.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
}
.jp-CodeMirrorEditor {
cursor: text;
}
/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
@media screen and (min-width: 2138px) and (max-width: 4319px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width1) solid
var(--jp-editor-cursor-color);
}
}
/* When zoomed out less than 33% */
@media screen and (min-width: 4320px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width2) solid
var(--jp-editor-cursor-color);
}
}
.cm-editor.jp-mod-readOnly .cm-cursor {
display: none;
}
.jp-CollaboratorCursor {
border-left: 5px solid transparent;
border-right: 5px solid transparent;
border-top: none;
border-bottom: 3px solid;
background-clip: content-box;
margin-left: -5px;
margin-right: -5px;
}
.cm-searching,
.cm-searching span {
/* `.cm-searching span`: we need to override syntax highlighting */
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.cm-searching::selection,
.cm-searching span::selection {
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.jp-current-match > .cm-searching,
.jp-current-match > .cm-searching span,
.cm-searching > .jp-current-match,
.cm-searching > .jp-current-match span {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.jp-current-match > .cm-searching::selection,
.cm-searching > .jp-current-match::selection,
.jp-current-match > .cm-searching span::selection {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.cm-trailingspace {
background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
background-position: center left;
background-repeat: repeat-x;
}
.jp-CollaboratorCursor-hover {
position: absolute;
z-index: 1;
transform: translateX(-50%);
color: white;
border-radius: 3px;
padding-left: 4px;
padding-right: 4px;
padding-top: 1px;
padding-bottom: 1px;
text-align: center;
font-size: var(--jp-ui-font-size1);
white-space: nowrap;
}
.jp-CodeMirror-ruler {
border-left: 1px dashed var(--jp-border-color2);
}
/* Styles for shared cursors (remote cursor locations and selected ranges) */
.jp-CodeMirrorEditor .cm-ySelectionCaret {
position: relative;
border-left: 1px solid black;
margin-left: -1px;
margin-right: -1px;
box-sizing: border-box;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
white-space: nowrap;
position: absolute;
top: -1.15em;
padding-bottom: 0.05em;
left: -1px;
font-size: 0.95em;
font-family: var(--jp-ui-font-family);
font-weight: bold;
line-height: normal;
user-select: none;
color: white;
padding-left: 2px;
padding-right: 2px;
z-index: 101;
transition: opacity 0.3s ease-in-out;
}
.jp-CodeMirrorEditor .cm-ySelectionInfo {
transition-delay: 0.7s;
opacity: 0;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
opacity: 1;
transition-delay: 0s;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MimeDocument {
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-filebrowser-button-height: 28px;
--jp-private-filebrowser-button-width: 48px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FileBrowser .jp-SidePanel-content {
display: flex;
flex-direction: column;
}
.jp-FileBrowser-toolbar.jp-Toolbar {
flex-wrap: wrap;
row-gap: 12px;
border-bottom: none;
height: auto;
margin: 8px 12px 0;
box-shadow: none;
padding: 0;
justify-content: flex-start;
}
.jp-FileBrowser-Panel {
flex: 1 1 auto;
display: flex;
flex-direction: column;
}
.jp-BreadCrumbs {
flex: 0 0 auto;
margin: 8px 12px;
}
.jp-BreadCrumbs-item {
margin: 0 2px;
padding: 0 2px;
border-radius: var(--jp-border-radius);
cursor: pointer;
}
.jp-BreadCrumbs-item:hover {
background-color: var(--jp-layout-color2);
}
.jp-BreadCrumbs-item:first-child {
margin-left: 0;
}
.jp-BreadCrumbs-item.jp-mod-dropTarget {
background-color: var(--jp-brand-color2);
opacity: 0.7;
}
/*-----------------------------------------------------------------------------
| Buttons
|----------------------------------------------------------------------------*/
.jp-FileBrowser-toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
padding-left: 0;
padding-right: 2px;
align-items: center;
height: unset;
}
.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
width: 40px;
}
/*-----------------------------------------------------------------------------
| Other styles
|----------------------------------------------------------------------------*/
.jp-FileDialog.jp-mod-conflict input {
color: var(--jp-error-color1);
}
.jp-FileDialog .jp-new-name-title {
margin-top: 12px;
}
.jp-LastModified-hidden {
display: none;
}
.jp-FileSize-hidden {
display: none;
}
.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
display: none;
}
/*-----------------------------------------------------------------------------
| DirListing
|----------------------------------------------------------------------------*/
.jp-DirListing {
flex: 1 1 auto;
display: flex;
flex-direction: column;
outline: 0;
}
.jp-DirListing-header {
flex: 0 0 auto;
display: flex;
flex-direction: row;
align-items: center;
overflow: hidden;
border-top: var(--jp-border-width) solid var(--jp-border-color2);
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
}
.jp-DirListing-headerItem {
padding: 4px 12px 2px;
font-weight: 500;
}
.jp-DirListing-headerItem:hover {
background: var(--jp-layout-color2);
}
.jp-DirListing-headerItem.jp-id-name {
flex: 1 0 84px;
}
.jp-DirListing-headerItem.jp-id-modified {
flex: 0 0 112px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-DirListing-headerItem.jp-id-filesize {
flex: 0 0 75px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-id-narrow {
display: none;
flex: 0 0 5px;
padding: 4px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
color: var(--jp-border-color2);
}
.jp-DirListing-narrow .jp-id-narrow {
display: block;
}
.jp-DirListing-narrow .jp-id-modified,
.jp-DirListing-narrow .jp-DirListing-itemModified {
display: none;
}
.jp-DirListing-headerItem.jp-mod-selected {
font-weight: 600;
}
/* increase specificity to override bundled default */
.jp-DirListing-content {
flex: 1 1 auto;
margin: 0;
padding: 0;
list-style-type: none;
overflow: auto;
background-color: var(--jp-layout-color1);
}
.jp-DirListing-content mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
color: var(--jp-ui-inverse-font-color0);
}
/* Style the directory listing content when a user drops a file to upload */
.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
outline: 5px dashed rgba(128, 128, 128, 0.5);
outline-offset: -10px;
cursor: copy;
}
.jp-DirListing-item {
display: flex;
flex-direction: row;
align-items: center;
padding: 4px 12px;
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-DirListing-checkboxWrapper {
/* Increases hit area of checkbox. */
padding: 4px;
}
.jp-DirListing-header
.jp-DirListing-checkboxWrapper
+ .jp-DirListing-headerItem {
padding-left: 4px;
}
.jp-DirListing-content .jp-DirListing-checkboxWrapper {
position: relative;
left: -4px;
margin: -4px 0 -4px -8px;
}
.jp-DirListing-checkboxWrapper.jp-mod-visible {
visibility: visible;
}
/* For devices that support hovering, hide checkboxes until hovered, selected...
*/
@media (hover: hover) {
.jp-DirListing-checkboxWrapper {
visibility: hidden;
}
.jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
.jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
visibility: visible;
}
}
.jp-DirListing-item[data-is-dot] {
opacity: 75%;
}
.jp-DirListing-item.jp-mod-selected {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.jp-DirListing-item.jp-mod-dropTarget {
background: var(--jp-brand-color3);
}
.jp-DirListing-item:hover:not(.jp-mod-selected) {
background: var(--jp-layout-color2);
}
.jp-DirListing-itemIcon {
flex: 0 0 20px;
margin-right: 4px;
}
.jp-DirListing-itemText {
flex: 1 0 64px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
user-select: none;
}
.jp-DirListing-itemText:focus {
outline-width: 2px;
outline-color: var(--jp-inverse-layout-color1);
outline-style: solid;
outline-offset: 1px;
}
.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
outline-color: var(--jp-layout-color1);
}
.jp-DirListing-itemModified {
flex: 0 0 125px;
text-align: right;
}
.jp-DirListing-itemFileSize {
flex: 0 0 90px;
text-align: right;
}
.jp-DirListing-editor {
flex: 1 0 64px;
outline: none;
border: none;
color: var(--jp-ui-font-color1);
background-color: var(--jp-layout-color1);
}
.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
color: var(--jp-success-color1);
content: '\25CF';
font-size: 8px;
position: absolute;
left: -8px;
}
.jp-DirListing-item.jp-mod-running.jp-mod-selected
.jp-DirListing-itemIcon::before {
color: var(--jp-ui-inverse-font-color1);
}
.jp-DirListing-item.lm-mod-drag-image,
.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
font-size: var(--jp-ui-font-size1);
padding-left: 4px;
margin-left: 4px;
width: 160px;
background-color: var(--jp-ui-inverse-font-color2);
box-shadow: var(--jp-elevation-z2);
border-radius: 0;
color: var(--jp-ui-font-color1);
transform: translateX(-40%) translateY(-58%);
}
.jp-Document {
min-width: 120px;
min-height: 120px;
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Main OutputArea
| OutputArea has a list of Outputs
|----------------------------------------------------------------------------*/
.jp-OutputArea {
overflow-y: auto;
}
.jp-OutputArea-child {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-OutputPrompt {
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-outprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
opacity: var(--jp-cell-prompt-opacity);
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-OutputArea-prompt {
display: table-cell;
vertical-align: top;
}
.jp-OutputArea-output {
display: table-cell;
width: 100%;
height: auto;
overflow: auto;
user-select: text;
-moz-user-select: text;
-webkit-user-select: text;
-ms-user-select: text;
}
.jp-OutputArea .jp-RenderedText {
padding-left: 1ch;
}
/**
* Prompt overlay.
*/
.jp-OutputArea-promptOverlay {
position: absolute;
top: 0;
width: var(--jp-cell-prompt-width);
height: 100%;
opacity: 0.5;
}
.jp-OutputArea-promptOverlay:hover {
background: var(--jp-layout-color2);
box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
cursor: zoom-out;
}
.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
cursor: zoom-in;
}
/**
* Isolated output.
*/
.jp-OutputArea-output.jp-mod-isolated {
width: 100%;
display: block;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
position: relative;
}
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/* pre */
.jp-OutputArea-output pre {
border: none;
margin: 0;
padding: 0;
overflow-x: auto;
overflow-y: auto;
word-break: break-all;
word-wrap: break-word;
white-space: pre-wrap;
}
/* tables */
.jp-OutputArea-output.jp-RenderedHTMLCommon table {
margin-left: 0;
margin-right: 0;
}
/* description lists */
.jp-OutputArea-output dl,
.jp-OutputArea-output dt,
.jp-OutputArea-output dd {
display: block;
}
.jp-OutputArea-output dl {
width: 100%;
overflow: hidden;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dt {
font-weight: bold;
float: left;
width: 20%;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dd {
float: left;
width: 80%;
padding: 0;
margin: 0;
}
.jp-TrimmedOutputs pre {
background: var(--jp-layout-color3);
font-size: calc(var(--jp-code-font-size) * 1.4);
text-align: center;
text-transform: uppercase;
}
/* Hide the gutter in case of
* - nested output areas (e.g. in the case of output widgets)
* - mirrored output areas
*/
.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
display: none;
}
/* Hide empty lines in the output area, for instance due to cleared widgets */
.jp-OutputArea-prompt:empty {
padding: 0;
border: 0;
}
/*-----------------------------------------------------------------------------
| executeResult is added to any Output-result for the display of the object
| returned by a cell
|----------------------------------------------------------------------------*/
.jp-OutputArea-output.jp-OutputArea-executeResult {
margin-left: 0;
width: 100%;
}
/* Text output with the Out[] prompt needs a top padding to match the
* alignment of the Out[] prompt itself.
*/
.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
padding-top: var(--jp-code-padding);
border-top: var(--jp-border-width) solid transparent;
}
/*-----------------------------------------------------------------------------
| The Stdin output
|----------------------------------------------------------------------------*/
.jp-Stdin-prompt {
color: var(--jp-content-font-color0);
padding-right: var(--jp-code-padding);
vertical-align: baseline;
flex: 0 0 auto;
}
.jp-Stdin-input {
font-family: var(--jp-code-font-family);
font-size: inherit;
color: inherit;
background-color: inherit;
width: 42%;
min-width: 200px;
/* make sure input baseline aligns with prompt */
vertical-align: baseline;
/* padding + margin = 0.5em between prompt and cursor */
padding: 0 0.25em;
margin: 0 0.25em;
flex: 0 0 70%;
}
.jp-Stdin-input::placeholder {
opacity: 0;
}
.jp-Stdin-input:focus {
box-shadow: none;
}
.jp-Stdin-input:focus::placeholder {
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Output Area View
|----------------------------------------------------------------------------*/
.jp-LinkedOutputView .jp-OutputArea {
height: 100%;
display: block;
}
.jp-LinkedOutputView .jp-OutputArea-output:only-child {
height: 100%;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
@media print {
.jp-OutputArea-child {
break-inside: avoid-page;
}
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-OutputPrompt {
display: table-row;
text-align: left;
}
.jp-OutputArea-child .jp-OutputArea-output {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
}
/* Trimmed outputs warning */
.jp-TrimmedOutputs > a {
margin: 10px;
text-decoration: none;
cursor: pointer;
}
.jp-TrimmedOutputs > a:hover {
text-decoration: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Table of Contents
|----------------------------------------------------------------------------*/
:root {
--jp-private-toc-active-width: 4px;
}
.jp-TableOfContents {
display: flex;
flex-direction: column;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
height: 100%;
}
.jp-TableOfContents-placeholder {
text-align: center;
}
.jp-TableOfContents-placeholderContent {
color: var(--jp-content-font-color2);
padding: 8px;
}
.jp-TableOfContents-placeholderContent > h3 {
margin-bottom: var(--jp-content-heading-margin-bottom);
}
.jp-TableOfContents .jp-SidePanel-content {
overflow-y: auto;
}
.jp-TableOfContents-tree {
margin: 4px;
}
.jp-TableOfContents ol {
list-style-type: none;
}
/* stylelint-disable-next-line selector-max-type */
.jp-TableOfContents li > ol {
/* Align left border with triangle icon center */
padding-left: 11px;
}
.jp-TableOfContents-content {
/* left margin for the active heading indicator */
margin: 0 0 0 var(--jp-private-toc-active-width);
padding: 0;
background-color: var(--jp-layout-color1);
}
.jp-tocItem {
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-tocItem-heading {
display: flex;
cursor: pointer;
}
.jp-tocItem-heading:hover {
background-color: var(--jp-layout-color2);
}
.jp-tocItem-content {
display: block;
padding: 4px 0;
white-space: nowrap;
text-overflow: ellipsis;
overflow-x: hidden;
}
.jp-tocItem-collapser {
height: 20px;
margin: 2px 2px 0;
padding: 0;
background: none;
border: none;
cursor: pointer;
}
.jp-tocItem-collapser:hover {
background-color: var(--jp-layout-color3);
}
/* Active heading indicator */
.jp-tocItem-heading::before {
content: ' ';
background: transparent;
width: var(--jp-private-toc-active-width);
height: 24px;
position: absolute;
left: 0;
border-radius: var(--jp-border-radius);
}
.jp-tocItem-heading.jp-tocItem-active::before {
background-color: var(--jp-brand-color1);
}
.jp-tocItem-heading:hover.jp-tocItem-active::before {
background: var(--jp-brand-color0);
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Collapser {
flex: 0 0 var(--jp-cell-collapser-width);
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
border-radius: var(--jp-border-radius);
opacity: 1;
}
.jp-Collapser-child {
display: block;
width: 100%;
box-sizing: border-box;
/* height: 100% doesn't work because the height of its parent is computed from content */
position: absolute;
top: 0;
bottom: 0;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Hiding collapsers in print mode.
Note: input and output wrappers have "display: block" propery in print mode.
*/
@media print {
.jp-Collapser {
display: none;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Header/Footer
|----------------------------------------------------------------------------*/
/* Hidden by zero height by default */
.jp-CellHeader,
.jp-CellFooter {
height: 0;
width: 100%;
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Input
|----------------------------------------------------------------------------*/
/* All input areas */
.jp-InputArea {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-InputArea-editor {
display: table-cell;
overflow: hidden;
vertical-align: top;
/* This is the non-active, default styling */
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
background: var(--jp-cell-editor-background);
}
.jp-InputPrompt {
display: table-cell;
vertical-align: top;
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-inprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
opacity: var(--jp-cell-prompt-opacity);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-InputArea-editor {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
.jp-InputPrompt {
display: table-row;
text-align: left;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Placeholder {
display: table;
table-layout: fixed;
width: 100%;
}
.jp-Placeholder-prompt {
display: table-cell;
box-sizing: border-box;
}
.jp-Placeholder-content {
display: table-cell;
padding: 4px 6px;
border: 1px solid transparent;
border-radius: 0;
background: none;
box-sizing: border-box;
cursor: pointer;
}
.jp-Placeholder-contentContainer {
display: flex;
}
.jp-Placeholder-content:hover,
.jp-InputPlaceholder > .jp-Placeholder-content:hover {
border-color: var(--jp-layout-color3);
}
.jp-Placeholder-content .jp-MoreHorizIcon {
width: 32px;
height: 16px;
border: 1px solid transparent;
border-radius: var(--jp-border-radius);
}
.jp-Placeholder-content .jp-MoreHorizIcon:hover {
border: 1px solid var(--jp-border-color1);
box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
background-color: var(--jp-layout-color0);
}
.jp-PlaceholderText {
white-space: nowrap;
overflow-x: hidden;
color: var(--jp-inverse-layout-color3);
font-family: var(--jp-code-font-family);
}
.jp-InputPlaceholder > .jp-Placeholder-content {
border-color: var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Private CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-cell-scrolling-output-offset: 5px;
}
/*-----------------------------------------------------------------------------
| Cell
|----------------------------------------------------------------------------*/
.jp-Cell {
padding: var(--jp-cell-padding);
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Common input/output
|----------------------------------------------------------------------------*/
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: flex;
flex-direction: row;
padding: 0;
margin: 0;
/* Added to reveal the box-shadow on the input and output collapsers. */
overflow: visible;
}
/* Only input/output areas inside cells */
.jp-Cell-inputArea,
.jp-Cell-outputArea {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Collapser
|----------------------------------------------------------------------------*/
/* Make the output collapser disappear when there is not output, but do so
* in a manner that leaves it in the layout and preserves its width.
*/
.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
border: none !important;
background: transparent !important;
}
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
min-height: var(--jp-cell-collapser-min-height);
}
/*-----------------------------------------------------------------------------
| Output
|----------------------------------------------------------------------------*/
/* Put a space between input and output when there IS output */
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
margin-top: 5px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
overflow-y: auto;
max-height: 24em;
margin-left: var(--jp-private-cell-scrolling-output-offset);
resize: vertical;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
max-height: unset;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
content: ' ';
box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
width: 100%;
height: 100%;
position: sticky;
bottom: 0;
top: 0;
margin-top: -50%;
float: left;
display: block;
pointer-events: none;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
padding-top: 6px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
width: calc(
var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
);
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
}
/*-----------------------------------------------------------------------------
| CodeCell
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| MarkdownCell
|----------------------------------------------------------------------------*/
.jp-MarkdownOutput {
display: table-cell;
width: 100%;
margin-top: 0;
margin-bottom: 0;
padding-left: var(--jp-code-padding);
}
.jp-MarkdownOutput.jp-RenderedHTMLCommon {
overflow: auto;
}
/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
.jp-collapseHeadingButton {
display: flex;
min-height: var(--jp-cell-collapser-min-height);
font-size: var(--jp-code-font-size);
position: absolute;
background-color: transparent;
background-size: 25px;
background-repeat: no-repeat;
background-position-x: center;
background-position-y: top;
background-image: var(--jp-icon-caret-down);
right: 0;
top: 0;
bottom: 0;
}
.jp-collapseHeadingButton.jp-mod-collapsed {
background-image: var(--jp-icon-caret-right);
}
/*
set the container font size to match that of content
so that the nested collapse buttons have the right size
*/
.jp-MarkdownCell .jp-InputPrompt {
font-size: var(--jp-content-font-size1);
}
/*
Align collapseHeadingButton with cell top header
The font sizes are identical to the ones in packages/rendermime/style/base.css
*/
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
font-size: var(--jp-content-font-size5);
background-position-y: calc(0.3 * var(--jp-content-font-size5));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
font-size: var(--jp-content-font-size4);
background-position-y: calc(0.3 * var(--jp-content-font-size4));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
font-size: var(--jp-content-font-size3);
background-position-y: calc(0.3 * var(--jp-content-font-size3));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
font-size: var(--jp-content-font-size2);
background-position-y: calc(0.3 * var(--jp-content-font-size2));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
font-size: var(--jp-content-font-size1);
background-position-y: top;
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
font-size: var(--jp-content-font-size0);
background-position-y: top;
}
/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
display: none;
}
.jp-Notebook.jp-mod-showHiddenCellsButton
:is(.jp-MarkdownCell:hover, .jp-mod-active)
.jp-collapseHeadingButton {
display: flex;
}
/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
margin-top: var(--jp-code-padding);
border: 1px solid var(--jp-border-color2);
background-color: var(--jp-border-color3) !important;
color: var(--jp-content-font-color0) !important;
display: flex;
}
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
background-color: var(--jp-border-color2) !important;
}
.jp-showHiddenCellsButton {
display: none;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Using block instead of flex to allow the use of the break-inside CSS property for
cell outputs.
*/
@media print {
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: block;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-notebook-toolbar-padding: 2px 5px 2px 2px;
}
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-NotebookPanel-toolbar {
padding: var(--jp-notebook-toolbar-padding);
/* disable paint containment from lumino 2.0 default strict CSS containment */
contain: style size !important;
}
.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
border: none;
box-shadow: none;
}
.jp-Notebook-toolbarCellTypeDropdown select {
height: 24px;
font-size: var(--jp-ui-font-size1);
line-height: 14px;
border-radius: 0;
display: block;
}
.jp-Notebook-toolbarCellTypeDropdown span {
top: 5px !important;
}
.jp-Toolbar-responsive-popup {
position: absolute;
height: fit-content;
display: flex;
flex-direction: row;
flex-wrap: wrap;
justify-content: flex-end;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: var(--jp-notebook-toolbar-padding);
z-index: 1;
right: 0;
top: 0;
}
.jp-Toolbar > .jp-Toolbar-responsive-opener {
margin-left: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-Notebook-ExecutionIndicator {
position: relative;
display: inline-block;
height: 100%;
z-index: 9997;
}
.jp-Notebook-ExecutionIndicator-tooltip {
visibility: hidden;
height: auto;
width: max-content;
width: -moz-max-content;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color1);
text-align: justify;
border-radius: 6px;
padding: 0 5px;
position: fixed;
display: table;
}
.jp-Notebook-ExecutionIndicator-tooltip.up {
transform: translateX(-50%) translateY(-100%) translateY(-32px);
}
.jp-Notebook-ExecutionIndicator-tooltip.down {
transform: translateX(calc(-100% + 16px)) translateY(5px);
}
.jp-Notebook-ExecutionIndicator-tooltip.hidden {
display: none;
}
.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
visibility: visible;
}
.jp-Notebook-ExecutionIndicator span {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
color: var(--jp-ui-font-color1);
line-height: 24px;
display: block;
}
.jp-Notebook-ExecutionIndicator-progress-bar {
display: flex;
justify-content: center;
height: 100%;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*
* Execution indicator
*/
.jp-tocItem-content::after {
content: '';
/* Must be identical to form a circle */
width: 12px;
height: 12px;
background: none;
border: none;
position: absolute;
right: 0;
}
.jp-tocItem-content[data-running='0']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background: none;
}
.jp-tocItem-content[data-running='1']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background-color: var(--jp-inverse-layout-color3);
}
.jp-tocItem-content[data-running='0'],
.jp-tocItem-content[data-running='1'] {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Notebook-footer {
height: 27px;
margin-left: calc(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding)
);
width: calc(
100% -
(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding) + var(--jp-cell-padding)
)
);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
color: var(--jp-ui-font-color3);
margin-top: 6px;
background: none;
cursor: pointer;
}
.jp-Notebook-footer:focus {
border-color: var(--jp-cell-editor-active-border-color);
}
/* For devices that support hovering, hide footer until hover */
@media (hover: hover) {
.jp-Notebook-footer {
opacity: 0;
}
.jp-Notebook-footer:focus,
.jp-Notebook-footer:hover {
opacity: 1;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Imports
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-side-by-side-output-size: 1fr;
--jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
--jp-private-notebook-dragImage-width: 304px;
--jp-private-notebook-dragImage-height: 36px;
--jp-private-notebook-selected-color: var(--md-blue-400);
--jp-private-notebook-active-color: var(--md-green-400);
}
/*-----------------------------------------------------------------------------
| Notebook
|----------------------------------------------------------------------------*/
/* stylelint-disable selector-max-class */
.jp-NotebookPanel {
display: block;
height: 100%;
}
.jp-NotebookPanel.jp-Document {
min-width: 240px;
min-height: 120px;
}
.jp-Notebook {
padding: var(--jp-notebook-padding);
outline: none;
overflow: auto;
background: var(--jp-layout-color0);
}
.jp-Notebook.jp-mod-scrollPastEnd::after {
display: block;
content: '';
min-height: var(--jp-notebook-scroll-padding);
}
.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
contain: strict;
}
.jp-Notebook .jp-Cell {
overflow: visible;
}
.jp-Notebook .jp-Cell .jp-InputPrompt {
cursor: move;
}
/*-----------------------------------------------------------------------------
| Notebook state related styling
|
| The notebook and cells each have states, here are the possibilities:
|
| - Notebook
| - Command
| - Edit
| - Cell
| - None
| - Active (only one can be active)
| - Selected (the cells actions are applied to)
| - Multiselected (when multiple selected, the cursor)
| - No outputs
|----------------------------------------------------------------------------*/
/* Command or edit modes */
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
/* cell is active */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
background: var(--jp-brand-color1);
}
/* cell is dirty */
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
color: var(--jp-warn-color1);
}
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
color: var(--jp-warn-color1);
content: '•';
}
.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
background: var(--jp-warn-color1);
}
/* collapser is hovered */
.jp-Notebook .jp-Cell .jp-Collapser:hover {
box-shadow: var(--jp-elevation-z2);
background: var(--jp-brand-color1);
opacity: var(--jp-cell-collapser-not-active-hover-opacity);
}
/* cell is active and collapser is hovered */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
background: var(--jp-brand-color0);
opacity: 1;
}
/* Command mode */
.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
background: var(--jp-notebook-multiselected-color);
}
.jp-Notebook.jp-mod-commandMode
.jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
background: transparent;
}
/* Edit mode */
.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-cell-editor-active-background);
}
/*-----------------------------------------------------------------------------
| Notebook drag and drop
|----------------------------------------------------------------------------*/
.jp-Notebook-cell.jp-mod-dropSource {
opacity: 0.5;
}
.jp-Notebook-cell.jp-mod-dropTarget,
.jp-Notebook.jp-mod-commandMode
.jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
border-top-color: var(--jp-private-notebook-selected-color);
border-top-style: solid;
border-top-width: 2px;
}
.jp-dragImage {
display: block;
flex-direction: row;
width: var(--jp-private-notebook-dragImage-width);
height: var(--jp-private-notebook-dragImage-height);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
overflow: visible;
}
.jp-dragImage-singlePrompt {
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
.jp-dragImage .jp-dragImage-content {
flex: 1 1 auto;
z-index: 2;
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
line-height: var(--jp-code-line-height);
padding: var(--jp-code-padding);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background-color);
color: var(--jp-content-font-color3);
text-align: left;
margin: 4px 4px 4px 0;
}
.jp-dragImage .jp-dragImage-prompt {
flex: 0 0 auto;
min-width: 36px;
color: var(--jp-cell-inprompt-font-color);
padding: var(--jp-code-padding);
padding-left: 12px;
font-family: var(--jp-cell-prompt-font-family);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: 1.9;
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
}
.jp-dragImage-multipleBack {
z-index: -1;
position: absolute;
height: 32px;
width: 300px;
top: 8px;
left: 8px;
background: var(--jp-layout-color2);
border: var(--jp-border-width) solid var(--jp-input-border-color);
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
/*-----------------------------------------------------------------------------
| Cell toolbar
|----------------------------------------------------------------------------*/
.jp-NotebookTools {
display: block;
min-width: var(--jp-sidebar-min-width);
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
overflow: auto;
}
.jp-ActiveCellTool {
padding: 12px 0;
display: flex;
}
.jp-ActiveCellTool-Content {
flex: 1 1 auto;
}
.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
background: var(--jp-cell-editor-background);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
min-height: 29px;
}
.jp-ActiveCellTool .jp-InputPrompt {
min-width: calc(var(--jp-cell-prompt-width) * 0.75);
}
.jp-ActiveCellTool-CellContent > pre {
padding: 5px 4px;
margin: 0;
white-space: normal;
}
.jp-MetadataEditorTool {
flex-direction: column;
padding: 12px 0;
}
.jp-RankedPanel > :not(:first-child) {
margin-top: 12px;
}
.jp-KeySelector select.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: var(--jp-border-width) solid var(--jp-border-color1);
}
.jp-KeySelector label,
.jp-MetadataEditorTool label,
.jp-NumberSetter label {
line-height: 1.4;
}
.jp-NotebookTools .jp-select-wrapper {
margin-top: 4px;
margin-bottom: 0;
}
.jp-NumberSetter input {
width: 100%;
margin-top: 4px;
}
.jp-NotebookTools .jp-Collapse {
margin-top: 16px;
}
/*-----------------------------------------------------------------------------
| Presentation Mode (.jp-mod-presentationMode)
|----------------------------------------------------------------------------*/
.jp-mod-presentationMode .jp-Notebook {
--jp-content-font-size1: var(--jp-content-presentation-font-size1);
--jp-code-font-size: var(--jp-code-presentation-font-size);
}
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
flex: 0 0 110px;
}
/*-----------------------------------------------------------------------------
| Side-by-side Mode (.jp-mod-sideBySide)
|----------------------------------------------------------------------------*/
.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
margin-top: 3em;
margin-bottom: 3em;
margin-left: 5%;
margin-right: 5%;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
display: grid;
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-output-size)
);
grid-template-rows: auto minmax(0, 1fr) auto;
grid-template-areas:
'header header header'
'input handle output'
'footer footer footer';
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-resized-cell)
);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
grid-area: header;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
grid-area: input;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
/* overwrite the default margin (no vertical separation needed in side by side move */
margin-top: 0;
grid-area: output;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
grid-area: footer;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
grid-area: handle;
user-select: none;
display: block;
height: 100%;
cursor: ew-resize;
padding: 0 var(--jp-cell-padding);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
content: '';
display: block;
background: var(--jp-border-color2);
height: 100%;
width: 5px;
}
.jp-mod-sideBySide.jp-Notebook
.jp-CodeCell.jp-mod-resizedCell
.jp-CellResizeHandle::after {
background: var(--jp-border-color0);
}
.jp-CellResizeHandle {
display: none;
}
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Cell-Placeholder {
padding-left: 55px;
}
.jp-Cell-Placeholder-wrapper {
background: #fff;
border: 1px solid;
border-color: #e5e6e9 #dfe0e4 #d0d1d5;
border-radius: 4px;
-webkit-border-radius: 4px;
margin: 10px 15px;
}
.jp-Cell-Placeholder-wrapper-inner {
padding: 15px;
position: relative;
}
.jp-Cell-Placeholder-wrapper-body {
background-repeat: repeat;
background-size: 50% auto;
}
.jp-Cell-Placeholder-wrapper-body div {
background: #f6f7f8;
background-image: -webkit-linear-gradient(
left,
#f6f7f8 0%,
#edeef1 20%,
#f6f7f8 40%,
#f6f7f8 100%
);
background-repeat: no-repeat;
background-size: 800px 104px;
height: 104px;
position: absolute;
right: 15px;
left: 15px;
top: 15px;
}
div.jp-Cell-Placeholder-h1 {
top: 20px;
height: 20px;
left: 15px;
width: 150px;
}
div.jp-Cell-Placeholder-h2 {
left: 15px;
top: 50px;
height: 10px;
width: 100px;
}
div.jp-Cell-Placeholder-content-1,
div.jp-Cell-Placeholder-content-2,
div.jp-Cell-Placeholder-content-3 {
left: 15px;
right: 15px;
height: 10px;
}
div.jp-Cell-Placeholder-content-1 {
top: 100px;
}
div.jp-Cell-Placeholder-content-2 {
top: 120px;
}
div.jp-Cell-Placeholder-content-3 {
top: 140px;
}
</style>
<style type="text/css">
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.
Many variables appear in an ordered sequence (0,1,2,3). These sequences
are designed to work well together, so for example, `--jp-border-color1` should
be used with `--jp-layout-color1`. The numbers have the following meanings:
* 0: super-primary, reserved for special emphasis
* 1: primary, most important under normal situations
* 2: secondary, next most important under normal situations
* 3: tertiary, next most important under normal situations
Throughout JupyterLab, we are mostly following principles from Google's
Material Design when selecting colors. We are not, however, following
all of MD as it is not optimized for dense, information rich UIs.
*/
:root {
/* Elevation
*
* We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
*
* https://github.com/material-components/material-components-web
* https://material-components-web.appspot.com/elevation.html
*/
--jp-shadow-base-lightness: 0;
--jp-shadow-umbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.2
);
--jp-shadow-penumbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.14
);
--jp-shadow-ambient-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.12
);
--jp-elevation-z0: none;
--jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
0 1px 1px 0 var(--jp-shadow-penumbra-color),
0 1px 3px 0 var(--jp-shadow-ambient-color);
--jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
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<h1 id="Tutorial:-Averaging-Neural-Operator-for-solving-Kuramoto-Sivashinsky-equation">Tutorial: Averaging Neural Operator for solving Kuramoto Sivashinsky equation<a class="anchor-link" href="#Tutorial:-Averaging-Neural-Operator-for-solving-Kuramoto-Sivashinsky-equation"></a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial10/tutorial.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p>
<p>In this tutorial we will build a Neural Operator using the
<code>AveragingNeuralOperator</code> model and the <code>SupervisedSolver</code>. At the end of the
tutorial you will be able to train a Neural Operator for learning
the operator of time dependent PDEs.</p>
<p>First of all, some useful imports. Note we use <code>scipy</code> for i/o operations.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab"</span><span class="w"> </span>
<span class="c1"># get the data</span>
<span class="o">!</span>mkdir<span class="w"> </span><span class="s2">"data"</span>
<span class="o">!</span>wget<span class="w"> </span><span class="s2">"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS.mat"</span><span class="w"> </span>-O<span class="w"> </span><span class="s2">"data/Data_KS.mat"</span>
<span class="o">!</span>wget<span class="w"> </span><span class="s2">"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS2.mat"</span><span class="w"> </span>-O<span class="w"> </span><span class="s2">"data/Data_KS2.mat"</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">scipy</span><span class="w"> </span><span class="kn">import</span> <span class="n">io</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina</span><span class="w"> </span><span class="kn">import</span> <span class="n">Condition</span><span class="p">,</span> <span class="n">Trainer</span><span class="p">,</span> <span class="n">LabelTensor</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.model</span><span class="w"> </span><span class="kn">import</span> <span class="n">AveragingNeuralOperator</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.solver</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedSolver</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.problem.zoo</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedProblem</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
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<h2 id="Data-Generation">Data Generation<a class="anchor-link" href="#Data-Generation"></a></h2><p>We will focus on solving a specific PDE, the <strong>Kuramoto Sivashinsky</strong> (KS) equation.
The KS PDE is a fourth-order nonlinear PDE with the following form:</p>
<p>$$
\frac{\partial u}{\partial t}(x,t) = -u(x,t)\frac{\partial u}{\partial x}(x,t)- \frac{\partial^{4}u}{\partial x^{4}}(x,t) - \frac{\partial^{2}u}{\partial x^{2}}(x,t).
$$</p>
<p>In the above $x\in \Omega=[0, 64]$ represents a spatial location, $t\in\mathbb{T}=[0,50]$ the time and $u(x, t)$ is the value of the function $u:\Omega \times\mathbb{T}\in\mathbb{R}$. We indicate with $\mathbb{U}$ a suitable space for $u$, i.e. we have that the solution $u\in\mathbb{U}$.</p>
<p>We impose Dirichlet boundary conditions on the derivative of $u$ on the border of the domain $\partial \Omega$
$$
\frac{\partial u}{\partial x}(x,t)=0 \quad \forall (x,t)\in \partial \Omega\times\mathbb{T}.
$$</p>
<p>Initial conditions are sampled from a distribution over truncated Fourier series with random coefficients
$\{A_k, \ell_k, \phi_k\}_k$ as
$$
u(x,0) = \sum_{k=1}^N A_k \sin(2 \pi \ell_k x / L + \phi_k) \ ,
$$</p>
<p>where $A_k \in [-0.4, -0.3]$, $\ell_k = 2$, $\phi_k = 2\pi \quad \forall k=1,\dots,N$.</p>
<p>We have already generated some data for differenti initial conditions, and our objective will
be to build a Neural Operator that, given $u(x, t)$ will output $u(x, t+\delta)$, where
$\delta$ is a fixed time step. We will come back on the Neural Operator architecture, for now
we first need to import the data.</p>
<p><strong>Note:</strong>
<em>The numerical integration is obtained by using pseudospectral method for spatial derivative discratization and
implicit Runge Kutta 5 for temporal dynamics.</em></p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># load data</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">loadmat</span><span class="p">(</span><span class="s2">"data/Data_KS.mat"</span><span class="p">)</span>
<span class="c1"># converting to label tensor</span>
<span class="n">initial_cond_train</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span>
<span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s2">"initial_cond_train"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span>
<span class="p">[</span><span class="s2">"t"</span><span class="p">,</span> <span class="s2">"x"</span><span class="p">,</span> <span class="s2">"u0"</span><span class="p">],</span>
<span class="p">)</span>
<span class="n">initial_cond_test</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span>
<span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s2">"initial_cond_test"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"t"</span><span class="p">,</span> <span class="s2">"x"</span><span class="p">,</span> <span class="s2">"u0"</span><span class="p">]</span>
<span class="p">)</span>
<span class="n">sol_train</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span>
<span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s2">"sol_train"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"u"</span><span class="p">]</span>
<span class="p">)</span>
<span class="n">sol_test</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s2">"sol_test"</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">),</span> <span class="p">[</span><span class="s2">"u"</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Data Loaded"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" shape initial condition: </span><span class="si">{</span><span class="n">initial_cond_train</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" shape solution: </span><span class="si">{</span><span class="n">sol_train</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Data Loaded
shape initial condition: torch.Size([100, 12800, 3])
shape solution: torch.Size([100, 12800, 1])
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<p>The data are saved in the form <code>B \times N \times D</code>, where <code>B</code> is the batch_size
(basically how many initial conditions we sample), <code>N</code> the number of points in the mesh
(which is the product of the discretization in <code>x</code> timese the one in <code>t</code>), and
<code>D</code> the dimension of the problem (in this case we have three variables <code>[u, t, x]</code>).</p>
<p>We are now going to plot some trajectories!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># helper function</span>
<span class="k">def</span><span class="w"> </span><span class="nf">plot_trajectory</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="n">real</span><span class="p">,</span> <span class="n">no_sol</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="c1"># find the x-t shapes</span>
<span class="n">dim_x</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">coords</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)))</span>
<span class="n">dim_t</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">coords</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)))</span>
<span class="c1"># if we don't have the Neural Operator solution we simply plot the real one</span>
<span class="k">if</span> <span class="n">no_sol</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">5</span><span class="p">),</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">axs</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">real</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Real solution"</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">c</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">axs</span><span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)</span>
<span class="n">axs</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)</span>
<span class="c1"># otherwise we plot the real one, the Neural Operator one, and their difference</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">5</span><span class="p">),</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">real</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Real solution"</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="n">no_sol</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"NO solution"</span><span class="p">)</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span>
<span class="p">(</span><span class="n">real</span> <span class="o">-</span> <span class="n">no_sol</span><span class="p">)</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dim_t</span><span class="p">,</span> <span class="n">dim_x</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">64</span><span class="p">],</span>
<span class="n">cmap</span><span class="o">=</span><span class="s2">"PuOr_r"</span><span class="p">,</span>
<span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Absolute difference"</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">c</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">axs</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
<span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">axs</span><span class="p">:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"t"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"x"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="c1"># a sample trajectory (we use the sample 5, feel free to change)</span>
<span class="n">sample_number</span> <span class="o">=</span> <span class="mi">20</span>
<span class="n">plot_trajectory</span><span class="p">(</span>
<span class="n">coords</span><span class="o">=</span><span class="n">initial_cond_train</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">]),</span>
<span class="n">real</span><span class="o">=</span><span class="n">sol_train</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span>
<span class="p">)</span>
</pre></div>
</div>
</div>
</div>
</div>
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"/>
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<p>As we can see, as the time progresses the solution becomes chaotic, which makes
it really hard to learn! We will now focus on building a Neural Operator using the
<code>SupervisedSolver</code> class to tackle the problem.</p>
<h2 id="Averaging-Neural-Operator">Averaging Neural Operator<a class="anchor-link" href="#Averaging-Neural-Operator"></a></h2><p>We will build a neural operator $\texttt{NO}$ which takes the solution at time $t=0$ for any $x\in\Omega$,
the time $(t)$ at which we want to compute the solution, and gives back the solution to the KS equation $u(x, t)$, mathematically:
$$
\texttt{NO}_\theta : \mathbb{U} \rightarrow \mathbb{U},
$$
such that
$$
\texttt{NO}_\theta[u(t=0)](x, t) \rightarrow u(x, t).
$$</p>
<p>There are many ways on approximating the following operator, e.g. by 2D <a href="https://mathlab.github.io/PINA/_rst/models/fno.html">FNO</a> (for regular meshes),
a <a href="https://mathlab.github.io/PINA/_rst/models/deeponet.html">DeepOnet</a>, <a href="https://mathlab.github.io/PINA/_rst/layers/convolution.html">Continuous Convolutional Neural Operator</a>,
<a href="https://mathlab.github.io/PINA/_rst/models/mionet.html">MIONet</a>.
In this tutorial we will use the <em>Averaging Neural Operator</em> presented in <a href="https://arxiv.org/abs/2304.13221"><em>The Nonlocal Neural Operator: Universal Approximation</em></a>
which is a <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">Kernel Neural Operator</a> with integral kernel:</p>
<p>$$
K(v) = \sigma\left(Wv(x) + b + \frac{1}{|\Omega|}\int_\Omega v(y)dy\right)
$$</p>
<p>where:</p>
<ul>
<li>$v(x)\in\mathbb{R}^{\rm{emb}}$ is the update for a function $v$ with $\mathbb{R}^{\rm{emb}}$ the embedding (hidden) size</li>
<li>$\sigma$ is a non-linear activation</li>
<li>$W\in\mathbb{R}^{\rm{emb}\times\rm{emb}}$ is a tunable matrix.</li>
<li>$b\in\mathbb{R}^{\rm{emb}}$ is a tunable bias.</li>
</ul>
<p>If PINA many Kernel Neural Operators are already implemented, and the modular componets of the <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">Kernel Neural Operator</a> class permits to create new ones by composing base kernel layers.</p>
<p>**Note:*** We will use the already built class* <code>AveragingNeuralOperator</code>, <em>as constructive excercise try to use the</em> <a href="https://mathlab.github.io/PINA/_rst/models/base_no.html">KernelNeuralOperator</a> <em>class for building a kernel neural operator from scratch. You might employ the different layers that we have in pina, e.g.</em> <a href="https://mathlab.github.io/PINA/_rst/models/fnn.html">FeedForward</a>, <em>and</em> <a href="https://mathlab.github.io/PINA/_rst/layers/avno_layer.html">AveragingNeuralOperator</a> <em>layers</em>.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="k">class</span><span class="w"> </span><span class="nc">SIREN</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">embedding_dimesion</span> <span class="o">=</span> <span class="mi">40</span> <span class="c1"># hyperparameter embedding dimension</span>
<span class="n">input_dimension</span> <span class="o">=</span> <span class="mi">3</span> <span class="c1"># ['u', 'x', 't']</span>
<span class="n">number_of_coordinates</span> <span class="o">=</span> <span class="mi">2</span> <span class="c1"># ['x', 't']</span>
<span class="n">lifting_net</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">input_dimension</span><span class="p">,</span> <span class="n">embedding_dimesion</span><span class="p">)</span>
<span class="n">projecting_net</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">embedding_dimesion</span> <span class="o">+</span> <span class="n">number_of_coordinates</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">AveragingNeuralOperator</span><span class="p">(</span>
<span class="n">lifting_net</span><span class="o">=</span><span class="n">lifting_net</span><span class="p">,</span>
<span class="n">projecting_net</span><span class="o">=</span><span class="n">projecting_net</span><span class="p">,</span>
<span class="n">coordinates_indices</span><span class="o">=</span><span class="p">[</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">],</span>
<span class="n">field_indices</span><span class="o">=</span><span class="p">[</span><span class="s2">"u0"</span><span class="p">],</span>
<span class="n">n_layers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
<span class="n">func</span><span class="o">=</span><span class="n">SIREN</span><span class="p">,</span>
<span class="p">)</span>
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<p>Super easy! Notice that we use the <code>SIREN</code> activation function, more on <a href="https://arxiv.org/abs/2006.09661">Implicit Neural Representations with Periodic Activation Functions</a>.</p>
<h2 id="Solving-the-KS-problem">Solving the KS problem<a class="anchor-link" href="#Solving-the-KS-problem"></a></h2><p>We will now focus on solving the KS equation using the <code>SupervisedSolver</code> class
and the <code>AveragingNeuralOperator</code> model. As done in the <a href="https://github.com/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb">FNO tutorial</a> we now create the Neural Operator problem class with <code>SupervisedProblem</code>.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># initialize problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">SupervisedProblem</span><span class="p">(</span>
<span class="n">initial_cond_train</span><span class="p">,</span>
<span class="n">sol_train</span><span class="p">,</span>
<span class="n">input_variables</span><span class="o">=</span><span class="n">initial_cond_train</span><span class="o">.</span><span class="n">labels</span><span class="p">,</span>
<span class="n">output_variables</span><span class="o">=</span><span class="n">sol_train</span><span class="o">.</span><span class="n">labels</span><span class="p">,</span>
<span class="p">)</span>
<span class="c1"># initialize solver</span>
<span class="n">solver</span> <span class="o">=</span> <span class="n">SupervisedSolver</span><span class="p">(</span><span class="n">problem</span><span class="o">=</span><span class="n">problem</span><span class="p">,</span> <span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">)</span>
<span class="c1"># train, only CPU and avoid model summary at beginning of training (optional)</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="o">=</span><span class="n">solver</span><span class="p">,</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="c1"># we train on CPU and avoid model summary at beginning of training (optional)</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>Missing logger folder: /home/runner/work/PINA/PINA/tutorials/tutorial10/lightning_logs
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<pre>`Trainer.fit` stopped: `max_epochs=40` reached.
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<p>We can now see some plots for the solutions</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">sample_number</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">no_sol</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_test</span><span class="p">)</span>
<span class="n">plot_trajectory</span><span class="p">(</span>
<span class="n">coords</span><span class="o">=</span><span class="n">initial_cond_test</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">([</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">]),</span>
<span class="n">real</span><span class="o">=</span><span class="n">sol_test</span><span class="p">[</span><span class="n">sample_number</span><span class="p">]</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span>
<span class="n">no_sol</span><span class="o">=</span><span class="n">no_sol</span><span class="p">[</span><span class="mi">5</span><span class="p">],</span>
<span class="p">)</span>
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<p>As we can see we can obtain nice result considering the small training time and the difficulty of the problem!
Let's take a look at the training and testing error:</p>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">pina.loss</span><span class="w"> </span><span class="kn">import</span> <span class="n">PowerLoss</span>
<span class="n">error_metric</span> <span class="o">=</span> <span class="n">PowerLoss</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="c1"># we use the MSE loss</span>
<span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
<span class="n">no_sol_train</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_train</span><span class="p">)</span>
<span class="n">err_train</span> <span class="o">=</span> <span class="n">error_metric</span><span class="p">(</span>
<span class="n">sol_train</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span> <span class="n">no_sol_train</span>
<span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="c1"># we average the error over trajectories</span>
<span class="n">no_sol_test</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">initial_cond_test</span><span class="p">)</span>
<span class="n">err_test</span> <span class="o">=</span> <span class="n">error_metric</span><span class="p">(</span>
<span class="n">sol_test</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"u"</span><span class="p">),</span> <span class="n">no_sol_test</span>
<span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="c1"># we average the error over trajectories</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Training error: </span><span class="si">{</span><span class="nb">float</span><span class="p">(</span><span class="n">err_train</span><span class="p">)</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Testing error: </span><span class="si">{</span><span class="nb">float</span><span class="p">(</span><span class="n">err_test</span><span class="p">)</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Training error: 0.150
Testing error: 0.144
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<p>As we can see the error is pretty small, which agrees with what we can see from the previous plots.</p>
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<h2 id="What's-next?">What's next?<a class="anchor-link" href="#What's-next?"></a></h2><p>Now you know how to solve a time dependent neural operator problem in <strong>PINA</strong>! There are multiple directions you can go now:</p>
<ol>
<li><p>Train the network for longer or with different layer sizes and assert the final accuracy</p>
</li>
<li><p>We left a more challenging dataset <a href="dat/Data_KS2.mat">Data_KS2.mat</a> where $A_k \in [-0.5, 0.5]$, $\ell_k \in [1, 2, 3]$, $\phi_k \in [0, 2\pi]$ for longer training</p>
</li>
<li><p>Compare the performance between the different neural operators (you can even try to implement your favourite one!)</p>
</li>
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