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PINA/docs/source/tutorials/tutorial15/tutorial.html
github-actions[bot] f3ccfd4598 export tutorials changed in 85b9edc (#634) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-09-10 12:10:39 +02:00

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--jp-icon-add-above: url(data:image/svg+xml;base64,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);
--jp-icon-add-below: url(data:image/svg+xml;base64,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);
--jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-bell: url(data:image/svg+xml;base64,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);
--jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
--jp-icon-bug: url(data:image/svg+xml;base64,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);
--jp-icon-build: url(data:image/svg+xml;base64,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);
--jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
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--jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-regex: url(data:image/svg+xml;base64,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);
--jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-toc: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik03LDVIMjFWN0g3VjVNNywxM1YxMUgyMVYxM0g3TTQsNC41QTEuNSwxLjUgMCAwLDEgNS41LDZBMS41LDEuNSAwIDAsMSA0LDcuNUExLjUsMS41IDAgMCwxIDIuNSw2QTEuNSwxLjUgMCAwLDEgNCw0LjVNNCwxMC41QTEuNSwxLjUgMCAwLDEgNS41LDEyQTEuNSwxLjUgMCAwLDEgNCwxMy41QTEuNSwxLjUgMCAwLDEgMi41LDEyQTEuNSwxLjUgMCAwLDEgNCwxMC41TTcsMTlWMTdIMjFWMTlIN000LDE2LjVBMS41LDEuNSAwIDAsMSA1LjUsMThBMS41LDEuNSAwIDAsMSA0LDE5LjVBMS41LDEuNSAwIDAsMSAyLjUsMThBMS41LDEuNSAwIDAsMSA0LDE2LjVaIiAvPgogIDwvZz4KPC9zdmc+Cg==);
--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,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KIDxnIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzQxNDE0MSI+CiAgPHJlY3QgeD0iMiIgeT0iMiIgd2lkdGg9IjE2IiBoZWlnaHQ9IjE2Ii8+CiA8L2c+CiA8ZyBjbGFzcz0ianAtaWNvbi1hY2NlbnQyIiB0cmFuc2Zvcm09InRyYW5zbGF0ZSguNDMgLjA0MDEpIiBmaWxsPSIjZmZmIj4KICA8cGF0aCBkPSJtNC4xNCA4Ljc2cTAuMDY4Mi0xLjg5IDIuNDItMS44OSAxLjE2IDAgMS42OCAwLjQyIDAuNTY3IDAuNDEgMC41NjcgMS4xNnYzLjQ3cTAgMC40NjIgMC41MTQgMC40NjIgMC4xMDMgMCAwLjItMC4wMjMxdjAuNzE0cS0wLjM5OSAwLjEwMy0wLjY1MSAwLjEwMy0wLjQ1MiAwLTAuNjkzLTAuMjItMC4yMzEtMC4yLTAuMjg0LTAuNjYyLTAuOTU2IDAuODcyLTIgMC44NzItMC45MDMgMC0xLjQ3LTAuNDcyLTAuNTI1LTAuNDcyLTAuNTI1LTEuMjYgMC0wLjI2MiAwLjA0NTItMC40NzIgMC4wNTY3LTAuMjIgMC4xMTYtMC4zNzggMC4wNjgyLTAuMTY4IDAuMjMxLTAuMzA0IDAuMTU4LTAuMTQ3IDAuMjYyLTAuMjQyIDAuMTE2LTAuMDkxNCAwLjM2OC0wLjE2OCAwLjI2Mi0wLjA5MTQgMC4zOTktMC4xMjYgMC4xMzYtMC4wNDUyIDAuNDcyLTAuMTAzIDAuMzM2LTAuMDU3OCAwLjUwNC0wLjA3OTggMC4xNTgtMC4wMjMxIDAuNTY3LTAuMDc5OCAwLjU1Ni0wLjA2ODIgMC43NzctMC4yMjEgMC4yMi0wLjE1MiAwLjIyLTAuNDQxdi0wLjI1MnEwLTAuNDMtMC4zNTctMC42NjItMC4zMzYtMC4yMzEtMC45NzYtMC4yMzEtMC42NjIgMC0wLjk5OCAwLjI2Mi0wLjMzNiAwLjI1Mi0wLjM5OSAwLjc5OHptMS44OSAzLjY4cTAuNzg4IDAgMS4yNi0wLjQxIDAuNTA0LTAuNDIgMC41MDQtMC45MDN2LTEuMDVxLTAuMjg0IDAuMTM2LTAuODYxIDAuMjMxLTAuNTY3IDAuMDkxNC0wLjk4NyAwLjE1OC0wLjQyIDAuMDY4Mi0wLjc2NiAwLjMyNi0wLjMzNiAwLjI1Mi0wLjMzNiAwLjcwNHQwLjMwNCAwLjcwNCAwLjg2MSAwLjI1MnoiIHN0cm9rZS13aWR0aD0iMS4wNSIvPgogIDxwYXRoIGQ9Im0xMCA0LjU2aDAuOTQ1djMuMTVxMC42NTEtMC45NzYgMS44OS0wLjk3NiAxLjE2IDAgMS44OSAwLjg0IDAuNjgyIDAuODQgMC42ODIgMi4zMSAwIDEuNDctMC43MDQgMi40Mi0wLjcwNCAwLjg4Mi0xLjg5IDAuODgyLTEuMjYgMC0xLjg5LTEuMDJ2MC43NjZoLTAuODV6bTIuNjIgMy4wNHEtMC43NDYgMC0xLjE2IDAuNjQtMC40NTIgMC42My0wLjQ1MiAxLjY4IDAgMS4wNSAwLjQ1MiAxLjY4dDEuMTYgMC42M3EwLjc3NyAwIDEuMjYtMC42MyAwLjQ5NC0wLjY0IDAuNDk0LTEuNjggMC0xLjA1LTAuNDcyLTEuNjgtMC40NjItMC42NC0xLjI2LTAuNjR6IiBzdHJva2Utd2lkdGg9IjEuMDUiLz4KICA8cGF0aCBkPSJtMi43MyAxNS44IDEzLjYgMC4wMDgxYzAuMDA2OSAwIDAtMi42IDAtMi42IDAtMC4wMDc4LTEuMTUgMC0xLjE1IDAtMC4wMDY5IDAtMC4wMDgzIDEuNS0wLjAwODMgMS41LTJlLTMgLTAuMDAxNC0xMS4zLTAuMDAxNC0xMS4zLTAuMDAxNGwtMC4wMDU5Mi0xLjVjMC0wLjAwNzgtMS4xNyAwLjAwMTMtMS4xNyAwLjAwMTN6IiBzdHJva2Utd2lkdGg9Ii45NzUiLz4KIDwvZz4KPC9zdmc+Cg==);
--jp-icon-yaml: url(data:image/svg+xml;base64,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);
}
/* Icon CSS class declarations */
.jp-AddAboveIcon {
background-image: var(--jp-icon-add-above);
}
.jp-AddBelowIcon {
background-image: var(--jp-icon-add-below);
}
.jp-AddIcon {
background-image: var(--jp-icon-add);
}
.jp-BellIcon {
background-image: var(--jp-icon-bell);
}
.jp-BugDotIcon {
background-image: var(--jp-icon-bug-dot);
}
.jp-BugIcon {
background-image: var(--jp-icon-bug);
}
.jp-BuildIcon {
background-image: var(--jp-icon-build);
}
.jp-CaretDownEmptyIcon {
background-image: var(--jp-icon-caret-down-empty);
}
.jp-CaretDownEmptyThinIcon {
background-image: var(--jp-icon-caret-down-empty-thin);
}
.jp-CaretDownIcon {
background-image: var(--jp-icon-caret-down);
}
.jp-CaretLeftIcon {
background-image: var(--jp-icon-caret-left);
}
.jp-CaretRightIcon {
background-image: var(--jp-icon-caret-right);
}
.jp-CaretUpEmptyThinIcon {
background-image: var(--jp-icon-caret-up-empty-thin);
}
.jp-CaretUpIcon {
background-image: var(--jp-icon-caret-up);
}
.jp-CaseSensitiveIcon {
background-image: var(--jp-icon-case-sensitive);
}
.jp-CheckIcon {
background-image: var(--jp-icon-check);
}
.jp-CircleEmptyIcon {
background-image: var(--jp-icon-circle-empty);
}
.jp-CircleIcon {
background-image: var(--jp-icon-circle);
}
.jp-ClearIcon {
background-image: var(--jp-icon-clear);
}
.jp-CloseIcon {
background-image: var(--jp-icon-close);
}
.jp-CodeCheckIcon {
background-image: var(--jp-icon-code-check);
}
.jp-CodeIcon {
background-image: var(--jp-icon-code);
}
.jp-CollapseAllIcon {
background-image: var(--jp-icon-collapse-all);
}
.jp-ConsoleIcon {
background-image: var(--jp-icon-console);
}
.jp-CopyIcon {
background-image: var(--jp-icon-copy);
}
.jp-CopyrightIcon {
background-image: var(--jp-icon-copyright);
}
.jp-CutIcon {
background-image: var(--jp-icon-cut);
}
.jp-DeleteIcon {
background-image: var(--jp-icon-delete);
}
.jp-DownloadIcon {
background-image: var(--jp-icon-download);
}
.jp-DuplicateIcon {
background-image: var(--jp-icon-duplicate);
}
.jp-EditIcon {
background-image: var(--jp-icon-edit);
}
.jp-EllipsesIcon {
background-image: var(--jp-icon-ellipses);
}
.jp-ErrorIcon {
background-image: var(--jp-icon-error);
}
.jp-ExpandAllIcon {
background-image: var(--jp-icon-expand-all);
}
.jp-ExtensionIcon {
background-image: var(--jp-icon-extension);
}
.jp-FastForwardIcon {
background-image: var(--jp-icon-fast-forward);
}
.jp-FileIcon {
background-image: var(--jp-icon-file);
}
.jp-FileUploadIcon {
background-image: var(--jp-icon-file-upload);
}
.jp-FilterDotIcon {
background-image: var(--jp-icon-filter-dot);
}
.jp-FilterIcon {
background-image: var(--jp-icon-filter);
}
.jp-FilterListIcon {
background-image: var(--jp-icon-filter-list);
}
.jp-FolderFavoriteIcon {
background-image: var(--jp-icon-folder-favorite);
}
.jp-FolderIcon {
background-image: var(--jp-icon-folder);
}
.jp-HomeIcon {
background-image: var(--jp-icon-home);
}
.jp-Html5Icon {
background-image: var(--jp-icon-html5);
}
.jp-ImageIcon {
background-image: var(--jp-icon-image);
}
.jp-InfoIcon {
background-image: var(--jp-icon-info);
}
.jp-InspectorIcon {
background-image: var(--jp-icon-inspector);
}
.jp-JsonIcon {
background-image: var(--jp-icon-json);
}
.jp-JuliaIcon {
background-image: var(--jp-icon-julia);
}
.jp-JupyterFaviconIcon {
background-image: var(--jp-icon-jupyter-favicon);
}
.jp-JupyterIcon {
background-image: var(--jp-icon-jupyter);
}
.jp-JupyterlabWordmarkIcon {
background-image: var(--jp-icon-jupyterlab-wordmark);
}
.jp-KernelIcon {
background-image: var(--jp-icon-kernel);
}
.jp-KeyboardIcon {
background-image: var(--jp-icon-keyboard);
}
.jp-LaunchIcon {
background-image: var(--jp-icon-launch);
}
.jp-LauncherIcon {
background-image: var(--jp-icon-launcher);
}
.jp-LineFormIcon {
background-image: var(--jp-icon-line-form);
}
.jp-LinkIcon {
background-image: var(--jp-icon-link);
}
.jp-ListIcon {
background-image: var(--jp-icon-list);
}
.jp-MarkdownIcon {
background-image: var(--jp-icon-markdown);
}
.jp-MoveDownIcon {
background-image: var(--jp-icon-move-down);
}
.jp-MoveUpIcon {
background-image: var(--jp-icon-move-up);
}
.jp-NewFolderIcon {
background-image: var(--jp-icon-new-folder);
}
.jp-NotTrustedIcon {
background-image: var(--jp-icon-not-trusted);
}
.jp-NotebookIcon {
background-image: var(--jp-icon-notebook);
}
.jp-NumberingIcon {
background-image: var(--jp-icon-numbering);
}
.jp-OfflineBoltIcon {
background-image: var(--jp-icon-offline-bolt);
}
.jp-PaletteIcon {
background-image: var(--jp-icon-palette);
}
.jp-PasteIcon {
background-image: var(--jp-icon-paste);
}
.jp-PdfIcon {
background-image: var(--jp-icon-pdf);
}
.jp-PythonIcon {
background-image: var(--jp-icon-python);
}
.jp-RKernelIcon {
background-image: var(--jp-icon-r-kernel);
}
.jp-ReactIcon {
background-image: var(--jp-icon-react);
}
.jp-RedoIcon {
background-image: var(--jp-icon-redo);
}
.jp-RefreshIcon {
background-image: var(--jp-icon-refresh);
}
.jp-RegexIcon {
background-image: var(--jp-icon-regex);
}
.jp-RunIcon {
background-image: var(--jp-icon-run);
}
.jp-RunningIcon {
background-image: var(--jp-icon-running);
}
.jp-SaveIcon {
background-image: var(--jp-icon-save);
}
.jp-SearchIcon {
background-image: var(--jp-icon-search);
}
.jp-SettingsIcon {
background-image: var(--jp-icon-settings);
}
.jp-ShareIcon {
background-image: var(--jp-icon-share);
}
.jp-SpreadsheetIcon {
background-image: var(--jp-icon-spreadsheet);
}
.jp-StopIcon {
background-image: var(--jp-icon-stop);
}
.jp-TabIcon {
background-image: var(--jp-icon-tab);
}
.jp-TableRowsIcon {
background-image: var(--jp-icon-table-rows);
}
.jp-TagIcon {
background-image: var(--jp-icon-tag);
}
.jp-TerminalIcon {
background-image: var(--jp-icon-terminal);
}
.jp-TextEditorIcon {
background-image: var(--jp-icon-text-editor);
}
.jp-TocIcon {
background-image: var(--jp-icon-toc);
}
.jp-TreeViewIcon {
background-image: var(--jp-icon-tree-view);
}
.jp-TrustedIcon {
background-image: var(--jp-icon-trusted);
}
.jp-UndoIcon {
background-image: var(--jp-icon-undo);
}
.jp-UserIcon {
background-image: var(--jp-icon-user);
}
.jp-UsersIcon {
background-image: var(--jp-icon-users);
}
.jp-VegaIcon {
background-image: var(--jp-icon-vega);
}
.jp-WordIcon {
background-image: var(--jp-icon-word);
}
.jp-YamlIcon {
background-image: var(--jp-icon-yaml);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* (DEPRECATED) Support for consuming icons as CSS background images
*/
.jp-Icon,
.jp-MaterialIcon {
background-position: center;
background-repeat: no-repeat;
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-cover {
background-position: center;
background-repeat: no-repeat;
background-size: cover;
}
/**
* (DEPRECATED) Support for specific CSS icon sizes
*/
.jp-Icon-16 {
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-18 {
background-size: 18px;
min-width: 18px;
min-height: 18px;
}
.jp-Icon-20 {
background-size: 20px;
min-width: 20px;
min-height: 20px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.lm-TabBar .lm-TabBar-addButton {
align-items: center;
display: flex;
padding: 4px;
padding-bottom: 5px;
margin-right: 1px;
background-color: var(--jp-layout-color2);
}
.lm-TabBar .lm-TabBar-addButton:hover {
background-color: var(--jp-layout-color1);
}
.lm-DockPanel-tabBar .lm-TabBar-tab {
width: var(--jp-private-horizontal-tab-width);
}
.lm-DockPanel-tabBar .lm-TabBar-content {
flex: unset;
}
.lm-DockPanel-tabBar[data-orientation='horizontal'] {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for icons as inline SVG HTMLElements
*/
/* recolor the primary elements of an icon */
.jp-icon0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-accent0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-accent1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-accent2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-accent3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-accent4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-accent0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-accent1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-accent2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-accent3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-accent4[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-none[fill] {
fill: none;
}
.jp-icon-none[stroke] {
stroke: none;
}
/* brand icon colors. Same for light and dark */
.jp-icon-brand0[fill] {
fill: var(--jp-brand-color0);
}
.jp-icon-brand1[fill] {
fill: var(--jp-brand-color1);
}
.jp-icon-brand2[fill] {
fill: var(--jp-brand-color2);
}
.jp-icon-brand3[fill] {
fill: var(--jp-brand-color3);
}
.jp-icon-brand4[fill] {
fill: var(--jp-brand-color4);
}
.jp-icon-brand0[stroke] {
stroke: var(--jp-brand-color0);
}
.jp-icon-brand1[stroke] {
stroke: var(--jp-brand-color1);
}
.jp-icon-brand2[stroke] {
stroke: var(--jp-brand-color2);
}
.jp-icon-brand3[stroke] {
stroke: var(--jp-brand-color3);
}
.jp-icon-brand4[stroke] {
stroke: var(--jp-brand-color4);
}
/* warn icon colors. Same for light and dark */
.jp-icon-warn0[fill] {
fill: var(--jp-warn-color0);
}
.jp-icon-warn1[fill] {
fill: var(--jp-warn-color1);
}
.jp-icon-warn2[fill] {
fill: var(--jp-warn-color2);
}
.jp-icon-warn3[fill] {
fill: var(--jp-warn-color3);
}
.jp-icon-warn0[stroke] {
stroke: var(--jp-warn-color0);
}
.jp-icon-warn1[stroke] {
stroke: var(--jp-warn-color1);
}
.jp-icon-warn2[stroke] {
stroke: var(--jp-warn-color2);
}
.jp-icon-warn3[stroke] {
stroke: var(--jp-warn-color3);
}
/* icon colors that contrast well with each other and most backgrounds */
.jp-icon-contrast0[fill] {
fill: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[fill] {
fill: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[fill] {
fill: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[fill] {
fill: var(--jp-icon-contrast-color3);
}
.jp-icon-contrast0[stroke] {
stroke: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[stroke] {
stroke: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[stroke] {
stroke: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[stroke] {
stroke: var(--jp-icon-contrast-color3);
}
.jp-icon-dot[fill] {
fill: var(--jp-warn-color0);
}
.jp-jupyter-icon-color[fill] {
fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
}
.jp-notebook-icon-color[fill] {
fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
}
.jp-json-icon-color[fill] {
fill: var(--jp-json-icon-color, var(--jp-warn-color1));
}
.jp-console-icon-color[fill] {
fill: var(--jp-console-icon-color, white);
}
.jp-console-icon-background-color[fill] {
fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
}
.jp-terminal-icon-color[fill] {
fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
}
.jp-terminal-icon-background-color[fill] {
fill: var(
--jp-terminal-icon-background-color,
var(--jp-inverse-layout-color2)
);
}
.jp-text-editor-icon-color[fill] {
fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
}
.jp-inspector-icon-color[fill] {
fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
}
/* CSS for icons in selected filebrowser listing items */
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* stylelint-disable selector-max-class, selector-max-compound-selectors */
/**
* TODO: come up with non css-hack solution for showing the busy icon on top
* of the close icon
* CSS for complex behavior of close icon of tabs in the main area tabbar
*/
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon3[fill] {
fill: none;
}
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon-busy[fill] {
fill: var(--jp-inverse-layout-color3);
}
/* stylelint-enable selector-max-class, selector-max-compound-selectors */
/* CSS for icons in status bar */
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* special handling for splash icon CSS. While the theme CSS reloads during
splash, the splash icon can loose theming. To prevent that, we set a
default for its color variable */
:root {
--jp-warn-color0: var(--md-orange-700);
}
/* not sure what to do with this one, used in filebrowser listing */
.jp-DragIcon {
margin-right: 4px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for alt colors for icons as inline SVG HTMLElements
*/
/* alt recolor the primary elements of an icon */
.jp-icon-alt .jp-icon0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-alt .jp-icon0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[stroke] {
stroke: var(--jp-layout-color4);
}
/* alt recolor the accent elements of an icon */
.jp-icon-alt .jp-icon-accent0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-alt .jp-icon-accent0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
display: none !important;
}
/**
* Support for hover colors for icons as inline SVG HTMLElements
*/
/**
* regular colors
*/
/* recolor the primary elements of an icon */
.jp-icon-hover :hover .jp-icon0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-hover :hover .jp-icon-none-hover[fill] {
fill: none;
}
.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
stroke: none;
}
/**
* inverse colors
*/
/* inverse recolor the primary elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* inverse recolor the accent elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-IFrame {
width: 100%;
height: 100%;
}
.jp-IFrame > iframe {
border: none;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-IFrame {
position: relative;
}
body.lm-mod-override-cursor .jp-IFrame::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-HoverBox {
position: fixed;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FormGroup-content fieldset {
border: none;
padding: 0;
min-width: 0;
width: 100%;
}
/* stylelint-disable selector-max-type */
.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
font-size: var(--jp-content-font-size2);
border-color: var(--jp-input-border-color);
border-style: solid;
border-radius: var(--jp-border-radius);
border-width: 1px;
padding: 6px 8px;
background: none;
color: var(--jp-ui-font-color0);
height: inherit;
}
.jp-FormGroup-content fieldset input[type='checkbox'] {
position: relative;
top: 2px;
margin-left: 0;
}
.jp-FormGroup-content button.jp-mod-styled {
cursor: pointer;
}
.jp-FormGroup-content .checkbox label {
cursor: pointer;
font-size: var(--jp-content-font-size1);
}
.jp-FormGroup-content .jp-root > fieldset > legend {
display: none;
}
.jp-FormGroup-content .jp-root > fieldset > p {
display: none;
}
/** copy of `input.jp-mod-styled:focus` style */
.jp-FormGroup-content fieldset input:focus,
.jp-FormGroup-content fieldset select:focus {
-moz-outline-radius: unset;
outline: var(--jp-border-width) solid var(--md-blue-500);
outline-offset: -1px;
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-FormGroup-content fieldset input:hover:not(:focus),
.jp-FormGroup-content fieldset select:hover:not(:focus) {
background-color: var(--jp-border-color2);
}
/* stylelint-enable selector-max-type */
.jp-FormGroup-content .checkbox .field-description {
/* Disable default description field for checkbox:
because other widgets do not have description fields,
we add descriptions to each widget on the field level.
*/
display: none;
}
.jp-FormGroup-content #root__description {
display: none;
}
.jp-FormGroup-content .jp-modifiedIndicator {
width: 5px;
background-color: var(--jp-brand-color2);
margin-top: 0;
margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
flex-shrink: 0;
}
.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
background-color: var(--jp-error-color0);
margin-right: 0.5em;
}
/* RJSF ARRAY style */
.jp-arrayFieldWrapper legend {
font-size: var(--jp-content-font-size2);
color: var(--jp-ui-font-color0);
flex-basis: 100%;
padding: 4px 0;
font-weight: var(--jp-content-heading-font-weight);
border-bottom: 1px solid var(--jp-border-color2);
}
.jp-arrayFieldWrapper .field-description {
padding: 4px 0;
white-space: pre-wrap;
}
.jp-arrayFieldWrapper .array-item {
width: 100%;
border: 1px solid var(--jp-border-color2);
border-radius: 4px;
margin: 4px;
}
.jp-ArrayOperations {
display: flex;
margin-left: 8px;
}
.jp-ArrayOperationsButton {
margin: 2px;
}
.jp-ArrayOperationsButton .jp-icon3[fill] {
fill: var(--jp-ui-font-color0);
}
button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
cursor: not-allowed;
opacity: 0.5;
}
/* RJSF form validation error */
.jp-FormGroup-content .validationErrors {
color: var(--jp-error-color0);
}
/* Hide panel level error as duplicated the field level error */
.jp-FormGroup-content .panel.errors {
display: none;
}
/* RJSF normal content (settings-editor) */
.jp-FormGroup-contentNormal {
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
margin-left: 7px;
color: var(--jp-ui-font-color0);
}
.jp-FormGroup-contentNormal .jp-FormGroup-description {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-default {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
font-size: var(--jp-content-font-size1);
font-weight: normal;
min-width: 120px;
}
.jp-FormGroup-contentNormal fieldset:not(:first-child) {
margin-left: 7px;
}
.jp-FormGroup-contentNormal .field-array-of-string .array-item {
/* Display `jp-ArrayOperations` buttons side-by-side with content except
for small screens where flex-wrap will place them one below the other.
*/
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
/* RJSF compact content (metadata-form) */
.jp-FormGroup-content.jp-FormGroup-contentCompact {
width: 100%;
}
.jp-FormGroup-contentCompact .form-group {
display: flex;
padding: 0.5em 0.2em 0.5em 0;
}
.jp-FormGroup-contentCompact
.jp-FormGroup-compactTitle
.jp-FormGroup-description {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color2);
}
.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
padding-bottom: 0.3em;
}
.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
width: 100%;
box-sizing: border-box;
}
.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
padding-bottom: 7px;
}
.jp-FormGroup-contentCompact
.jp-objectFieldWrapper
.jp-objectFieldWrapper
.form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
.jp-FormGroup-contentCompact ul.error-detail {
margin-block-start: 0.5em;
margin-block-end: 0.5em;
padding-inline-start: 1em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-SidePanel {
display: flex;
flex-direction: column;
min-width: var(--jp-sidebar-min-width);
overflow-y: auto;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
font-size: var(--jp-ui-font-size1);
}
.jp-SidePanel-header {
flex: 0 0 auto;
display: flex;
border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin: 0;
padding: 2px;
text-transform: uppercase;
}
.jp-SidePanel-toolbar {
flex: 0 0 auto;
}
.jp-SidePanel-content {
flex: 1 1 auto;
}
.jp-SidePanel-toolbar,
.jp-AccordionPanel-toolbar {
height: var(--jp-private-toolbar-height);
}
.jp-SidePanel-toolbar.jp-Toolbar-micro {
display: none;
}
.lm-AccordionPanel .jp-AccordionPanel-title {
box-sizing: border-box;
line-height: 25px;
margin: 0;
display: flex;
align-items: center;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
font-size: var(--jp-ui-font-size0);
}
.jp-AccordionPanel-title {
cursor: pointer;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
text-transform: uppercase;
}
.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
/* Title is rotated for horizontal accordion panel using CSS */
display: block;
transform-origin: top left;
transform: rotate(-90deg) translate(-100%);
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
user-select: none;
text-overflow: ellipsis;
white-space: nowrap;
overflow: hidden;
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
transform: rotate(-90deg);
margin: auto 0;
height: 16px;
}
.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
transform: rotate(0deg);
}
.lm-AccordionPanel .jp-AccordionPanel-toolbar {
background: none;
box-shadow: none;
border: none;
margin-left: auto;
}
.lm-AccordionPanel .lm-SplitPanel-handle:hover {
background: var(--jp-layout-color3);
}
.jp-text-truncated {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Spinner {
position: absolute;
display: flex;
justify-content: center;
align-items: center;
z-index: 10;
left: 0;
top: 0;
width: 100%;
height: 100%;
background: var(--jp-layout-color0);
outline: none;
}
.jp-SpinnerContent {
font-size: 10px;
margin: 50px auto;
text-indent: -9999em;
width: 3em;
height: 3em;
border-radius: 50%;
background: var(--jp-brand-color3);
background: linear-gradient(
to right,
#f37626 10%,
rgba(255, 255, 255, 0) 42%
);
position: relative;
animation: load3 1s infinite linear, fadeIn 1s;
}
.jp-SpinnerContent::before {
width: 50%;
height: 50%;
background: #f37626;
border-radius: 100% 0 0;
position: absolute;
top: 0;
left: 0;
content: '';
}
.jp-SpinnerContent::after {
background: var(--jp-layout-color0);
width: 75%;
height: 75%;
border-radius: 50%;
content: '';
margin: auto;
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
@keyframes load3 {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
button.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: none;
box-sizing: border-box;
text-align: center;
line-height: 32px;
height: 32px;
padding: 0 12px;
letter-spacing: 0.8px;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input.jp-mod-styled {
background: var(--jp-input-background);
height: 28px;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color1);
padding-left: 7px;
padding-right: 7px;
font-size: var(--jp-ui-font-size2);
color: var(--jp-ui-font-color0);
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input[type='checkbox'].jp-mod-styled {
appearance: checkbox;
-webkit-appearance: checkbox;
-moz-appearance: checkbox;
height: auto;
}
input.jp-mod-styled:focus {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-select-wrapper {
display: flex;
position: relative;
flex-direction: column;
padding: 1px;
background-color: var(--jp-layout-color1);
box-sizing: border-box;
margin-bottom: 12px;
}
.jp-select-wrapper:not(.multiple) {
height: 28px;
}
.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-input-active-background);
}
select.jp-mod-styled:hover {
cursor: pointer;
color: var(--jp-ui-font-color0);
background-color: var(--jp-input-hover-background);
box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
}
select.jp-mod-styled {
flex: 1 1 auto;
width: 100%;
font-size: var(--jp-ui-font-size2);
background: var(--jp-input-background);
color: var(--jp-ui-font-color0);
padding: 0 25px 0 8px;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
select.jp-mod-styled:not([multiple]) {
height: 32px;
}
select.jp-mod-styled[multiple] {
max-height: 200px;
overflow-y: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-switch {
display: flex;
align-items: center;
padding-left: 4px;
padding-right: 4px;
font-size: var(--jp-ui-font-size1);
background-color: transparent;
color: var(--jp-ui-font-color1);
border: none;
height: 20px;
}
.jp-switch:hover {
background-color: var(--jp-layout-color2);
}
.jp-switch-label {
margin-right: 5px;
font-family: var(--jp-ui-font-family);
}
.jp-switch-track {
cursor: pointer;
background-color: var(--jp-switch-color, var(--jp-border-color1));
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 34px;
height: 16px;
width: 35px;
position: relative;
}
.jp-switch-track::before {
content: '';
position: absolute;
height: 10px;
width: 10px;
margin: 3px;
left: 0;
background-color: var(--jp-ui-inverse-font-color1);
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 50%;
}
.jp-switch[aria-checked='true'] .jp-switch-track {
background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
}
.jp-switch[aria-checked='true'] .jp-switch-track::before {
/* track width (35) - margins (3 + 3) - thumb width (10) */
left: 19px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
:root {
--jp-private-toolbar-height: calc(
28px + var(--jp-border-width)
); /* leave 28px for content */
}
.jp-Toolbar {
color: var(--jp-ui-font-color1);
flex: 0 0 auto;
display: flex;
flex-direction: row;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: 2px;
z-index: 8;
overflow-x: hidden;
}
/* Toolbar items */
.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
flex-grow: 1;
flex-shrink: 1;
}
.jp-Toolbar-item.jp-Toolbar-kernelStatus {
display: inline-block;
width: 32px;
background-repeat: no-repeat;
background-position: center;
background-size: 16px;
}
.jp-Toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
display: flex;
padding-left: 1px;
padding-right: 1px;
font-size: var(--jp-ui-font-size1);
line-height: var(--jp-private-toolbar-height);
height: 100%;
}
/* Toolbar buttons */
/* This is the div we use to wrap the react component into a Widget */
div.jp-ToolbarButton {
color: transparent;
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0;
margin: 0;
}
button.jp-ToolbarButtonComponent {
background: var(--jp-layout-color1);
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0 6px;
margin: 0;
height: 24px;
border-radius: var(--jp-border-radius);
display: flex;
align-items: center;
text-align: center;
font-size: 14px;
min-width: unset;
min-height: unset;
}
button.jp-ToolbarButtonComponent:disabled {
opacity: 0.4;
}
button.jp-ToolbarButtonComponent > span {
padding: 0;
flex: 0 0 auto;
}
button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
font-size: var(--jp-ui-font-size1);
line-height: 100%;
padding-left: 2px;
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar.jp-Toolbar-micro {
padding: 0;
min-height: 0;
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar {
border: none;
box-shadow: none;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-WindowedPanel-outer {
position: relative;
overflow-y: auto;
}
.jp-WindowedPanel-inner {
position: relative;
}
.jp-WindowedPanel-window {
position: absolute;
left: 0;
right: 0;
overflow: visible;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/* Sibling imports */
body {
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
}
/* Disable native link decoration styles everywhere outside of dialog boxes */
a {
text-decoration: unset;
color: unset;
}
a:hover {
text-decoration: unset;
color: unset;
}
/* Accessibility for links inside dialog box text */
.jp-Dialog-content a {
text-decoration: revert;
color: var(--jp-content-link-color);
}
.jp-Dialog-content a:hover {
text-decoration: revert;
}
/* Styles for ui-components */
.jp-Button {
color: var(--jp-ui-font-color2);
border-radius: var(--jp-border-radius);
padding: 0 12px;
font-size: var(--jp-ui-font-size1);
/* Copy from blueprint 3 */
display: inline-flex;
flex-direction: row;
border: none;
cursor: pointer;
align-items: center;
justify-content: center;
text-align: left;
vertical-align: middle;
min-height: 30px;
min-width: 30px;
}
.jp-Button:disabled {
cursor: not-allowed;
}
.jp-Button:empty {
padding: 0 !important;
}
.jp-Button.jp-mod-small {
min-height: 24px;
min-width: 24px;
font-size: 12px;
padding: 0 7px;
}
/* Use our own theme for hover styles */
.jp-Button.jp-mod-minimal:hover {
background-color: var(--jp-layout-color2);
}
.jp-Button.jp-mod-minimal {
background: none;
}
.jp-InputGroup {
display: block;
position: relative;
}
.jp-InputGroup input {
box-sizing: border-box;
border: none;
border-radius: 0;
background-color: transparent;
color: var(--jp-ui-font-color0);
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
padding-bottom: 0;
padding-top: 0;
padding-left: 10px;
padding-right: 28px;
position: relative;
width: 100%;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
font-size: 14px;
font-weight: 400;
height: 30px;
line-height: 30px;
outline: none;
vertical-align: middle;
}
.jp-InputGroup input:focus {
box-shadow: inset 0 0 0 var(--jp-border-width)
var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-InputGroup input:disabled {
cursor: not-allowed;
resize: block;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input:disabled ~ span {
cursor: not-allowed;
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input::placeholder,
input::placeholder {
color: var(--jp-ui-font-color2);
}
.jp-InputGroupAction {
position: absolute;
bottom: 1px;
right: 0;
padding: 6px;
}
.jp-HTMLSelect.jp-DefaultStyle select {
background-color: initial;
border: none;
border-radius: 0;
box-shadow: none;
color: var(--jp-ui-font-color0);
display: block;
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
height: 24px;
line-height: 14px;
padding: 0 25px 0 10px;
text-align: left;
-moz-appearance: none;
-webkit-appearance: none;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
cursor: not-allowed;
resize: block;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
cursor: not-allowed;
}
/* Use our own theme for hover and option styles */
/* stylelint-disable-next-line selector-max-type */
.jp-HTMLSelect.jp-DefaultStyle select:hover,
.jp-HTMLSelect.jp-DefaultStyle select > option {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color0);
}
select {
box-sizing: border-box;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-StatusBar-Widget {
display: flex;
align-items: center;
background: var(--jp-layout-color2);
min-height: var(--jp-statusbar-height);
justify-content: space-between;
padding: 0 10px;
}
.jp-StatusBar-Left {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-StatusBar-Middle {
display: flex;
align-items: center;
}
.jp-StatusBar-Right {
display: flex;
align-items: center;
flex-direction: row-reverse;
}
.jp-StatusBar-Item {
max-height: var(--jp-statusbar-height);
margin: 0 2px;
height: var(--jp-statusbar-height);
white-space: nowrap;
text-overflow: ellipsis;
color: var(--jp-ui-font-color1);
padding: 0 6px;
}
.jp-mod-highlighted:hover {
background-color: var(--jp-layout-color3);
}
.jp-mod-clicked {
background-color: var(--jp-brand-color1);
}
.jp-mod-clicked:hover {
background-color: var(--jp-brand-color0);
}
.jp-mod-clicked .jp-StatusBar-TextItem {
color: var(--jp-ui-inverse-font-color1);
}
.jp-StatusBar-HoverItem {
box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
}
.jp-StatusBar-TextItem {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
line-height: 24px;
color: var(--jp-ui-font-color1);
}
.jp-StatusBar-GroupItem {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-Statusbar-ProgressCircle svg {
display: block;
margin: 0 auto;
width: 16px;
height: 24px;
align-self: normal;
}
.jp-Statusbar-ProgressCircle path {
fill: var(--jp-inverse-layout-color3);
}
.jp-Statusbar-ProgressBar-progress-bar {
height: 10px;
width: 100px;
border: solid 0.25px var(--jp-brand-color2);
border-radius: 3px;
overflow: hidden;
align-self: center;
}
.jp-Statusbar-ProgressBar-progress-bar > div {
background-color: var(--jp-brand-color2);
background-image: linear-gradient(
-45deg,
rgba(255, 255, 255, 0.2) 25%,
transparent 25%,
transparent 50%,
rgba(255, 255, 255, 0.2) 50%,
rgba(255, 255, 255, 0.2) 75%,
transparent 75%,
transparent
);
background-size: 40px 40px;
float: left;
width: 0%;
height: 100%;
font-size: 12px;
line-height: 14px;
color: #fff;
text-align: center;
animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
}
.jp-Statusbar-ProgressBar-progress-bar p {
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
font-size: var(--jp-ui-font-size1);
line-height: 10px;
width: 100px;
}
@keyframes jp-Statusbar-ExecutionTime-progress-bar {
0% {
background-position: 0 0;
}
100% {
background-position: 40px 40px;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-commandpalette-search-height: 28px;
}
/*-----------------------------------------------------------------------------
| Overall styles
|----------------------------------------------------------------------------*/
.lm-CommandPalette {
padding-bottom: 0;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Modal variant
|----------------------------------------------------------------------------*/
.jp-ModalCommandPalette {
position: absolute;
z-index: 10000;
top: 38px;
left: 30%;
margin: 0;
padding: 4px;
width: 40%;
box-shadow: var(--jp-elevation-z4);
border-radius: 4px;
background: var(--jp-layout-color0);
}
.jp-ModalCommandPalette .lm-CommandPalette {
max-height: 40vh;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
margin-left: 4px;
margin-right: 4px;
}
.jp-ModalCommandPalette
.lm-CommandPalette
.lm-CommandPalette-item.lm-mod-disabled {
display: none;
}
/*-----------------------------------------------------------------------------
| Search
|----------------------------------------------------------------------------*/
.lm-CommandPalette-search {
padding: 4px;
background-color: var(--jp-layout-color1);
z-index: 2;
}
.lm-CommandPalette-wrapper {
overflow: overlay;
padding: 0 9px;
background-color: var(--jp-input-active-background);
height: 30px;
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
}
.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-SearchIconGroup {
color: white;
background-color: var(--jp-brand-color1);
position: absolute;
top: 4px;
right: 4px;
padding: 5px 5px 1px;
}
.jp-SearchIconGroup svg {
height: 20px;
width: 20px;
}
.jp-SearchIconGroup .jp-icon3[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-input {
background: transparent;
width: calc(100% - 18px);
float: left;
border: none;
outline: none;
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
line-height: var(--jp-private-commandpalette-search-height);
}
.lm-CommandPalette-input::-webkit-input-placeholder,
.lm-CommandPalette-input::-moz-placeholder,
.lm-CommandPalette-input:-ms-input-placeholder {
color: var(--jp-ui-font-color2);
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Results
|----------------------------------------------------------------------------*/
.lm-CommandPalette-header:first-child {
margin-top: 0;
}
.lm-CommandPalette-header {
border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
color: var(--jp-ui-font-color1);
cursor: pointer;
display: flex;
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin-top: 8px;
padding: 8px 0 8px 12px;
text-transform: uppercase;
}
.lm-CommandPalette-header.lm-mod-active {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-header > mark {
background-color: transparent;
font-weight: bold;
color: var(--jp-ui-font-color1);
}
.lm-CommandPalette-item {
padding: 4px 12px 4px 4px;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
font-weight: 400;
display: flex;
}
.lm-CommandPalette-item.lm-mod-disabled {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item.lm-mod-active {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-inverse-font-color0);
}
.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-itemContent {
overflow: hidden;
}
.lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.lm-CommandPalette-item.lm-mod-disabled mark {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
margin: 0 4px 0 0;
position: relative;
width: 16px;
top: 2px;
flex: 0 0 auto;
}
.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
opacity: 0.6;
}
.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
flex: 0 0 auto;
}
.lm-CommandPalette-itemCaption {
display: none;
}
.lm-CommandPalette-content {
background-color: var(--jp-layout-color1);
}
.lm-CommandPalette-content:empty::after {
content: 'No results';
margin: auto;
margin-top: 20px;
width: 100px;
display: block;
font-size: var(--jp-ui-font-size2);
font-family: var(--jp-ui-font-family);
font-weight: lighter;
}
.lm-CommandPalette-emptyMessage {
text-align: center;
margin-top: 24px;
line-height: 1.32;
padding: 0 8px;
color: var(--jp-content-font-color3);
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Dialog {
position: absolute;
z-index: 10000;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
top: 0;
left: 0;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
background: var(--jp-dialog-background);
}
.jp-Dialog-content {
display: flex;
flex-direction: column;
margin-left: auto;
margin-right: auto;
background: var(--jp-layout-color1);
padding: 24px 24px 12px;
min-width: 300px;
min-height: 150px;
max-width: 1000px;
max-height: 500px;
box-sizing: border-box;
box-shadow: var(--jp-elevation-z20);
word-wrap: break-word;
border-radius: var(--jp-border-radius);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color1);
resize: both;
}
.jp-Dialog-content.jp-Dialog-content-small {
max-width: 500px;
}
.jp-Dialog-button {
overflow: visible;
}
button.jp-Dialog-button:focus {
outline: 1px solid var(--jp-brand-color1);
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button:focus::-moz-focus-inner {
border: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
}
button.jp-Dialog-close-button {
padding: 0;
height: 100%;
min-width: unset;
min-height: unset;
}
.jp-Dialog-header {
display: flex;
justify-content: space-between;
flex: 0 0 auto;
padding-bottom: 12px;
font-size: var(--jp-ui-font-size3);
font-weight: 400;
color: var(--jp-ui-font-color1);
}
.jp-Dialog-body {
display: flex;
flex-direction: column;
flex: 1 1 auto;
font-size: var(--jp-ui-font-size1);
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
overflow: auto;
}
.jp-Dialog-footer {
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
flex: 0 0 auto;
margin-left: -12px;
margin-right: -12px;
padding: 12px;
}
.jp-Dialog-checkbox {
padding-right: 5px;
}
.jp-Dialog-checkbox > input:focus-visible {
outline: 1px solid var(--jp-input-active-border-color);
outline-offset: 1px;
}
.jp-Dialog-spacer {
flex: 1 1 auto;
}
.jp-Dialog-title {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.jp-Dialog-body > .jp-select-wrapper {
width: 100%;
}
.jp-Dialog-body > button {
padding: 0 16px;
}
.jp-Dialog-body > label {
line-height: 1.4;
color: var(--jp-ui-font-color0);
}
.jp-Dialog-button.jp-mod-styled:not(:last-child) {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Input-Boolean-Dialog {
flex-direction: row-reverse;
align-items: end;
width: 100%;
}
.jp-Input-Boolean-Dialog > label {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MainAreaWidget > :focus {
outline: none;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error {
padding: 6px;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
width: auto;
padding: 10px;
background: var(--jp-error-color3);
border: var(--jp-border-width) solid var(--jp-error-color1);
border-radius: var(--jp-border-radius);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
white-space: pre-wrap;
word-wrap: break-word;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/**
* google-material-color v1.2.6
* https://github.com/danlevan/google-material-color
*/
:root {
--md-red-50: #ffebee;
--md-red-100: #ffcdd2;
--md-red-200: #ef9a9a;
--md-red-300: #e57373;
--md-red-400: #ef5350;
--md-red-500: #f44336;
--md-red-600: #e53935;
--md-red-700: #d32f2f;
--md-red-800: #c62828;
--md-red-900: #b71c1c;
--md-red-A100: #ff8a80;
--md-red-A200: #ff5252;
--md-red-A400: #ff1744;
--md-red-A700: #d50000;
--md-pink-50: #fce4ec;
--md-pink-100: #f8bbd0;
--md-pink-200: #f48fb1;
--md-pink-300: #f06292;
--md-pink-400: #ec407a;
--md-pink-500: #e91e63;
--md-pink-600: #d81b60;
--md-pink-700: #c2185b;
--md-pink-800: #ad1457;
--md-pink-900: #880e4f;
--md-pink-A100: #ff80ab;
--md-pink-A200: #ff4081;
--md-pink-A400: #f50057;
--md-pink-A700: #c51162;
--md-purple-50: #f3e5f5;
--md-purple-100: #e1bee7;
--md-purple-200: #ce93d8;
--md-purple-300: #ba68c8;
--md-purple-400: #ab47bc;
--md-purple-500: #9c27b0;
--md-purple-600: #8e24aa;
--md-purple-700: #7b1fa2;
--md-purple-800: #6a1b9a;
--md-purple-900: #4a148c;
--md-purple-A100: #ea80fc;
--md-purple-A200: #e040fb;
--md-purple-A400: #d500f9;
--md-purple-A700: #a0f;
--md-deep-purple-50: #ede7f6;
--md-deep-purple-100: #d1c4e9;
--md-deep-purple-200: #b39ddb;
--md-deep-purple-300: #9575cd;
--md-deep-purple-400: #7e57c2;
--md-deep-purple-500: #673ab7;
--md-deep-purple-600: #5e35b1;
--md-deep-purple-700: #512da8;
--md-deep-purple-800: #4527a0;
--md-deep-purple-900: #311b92;
--md-deep-purple-A100: #b388ff;
--md-deep-purple-A200: #7c4dff;
--md-deep-purple-A400: #651fff;
--md-deep-purple-A700: #6200ea;
--md-indigo-50: #e8eaf6;
--md-indigo-100: #c5cae9;
--md-indigo-200: #9fa8da;
--md-indigo-300: #7986cb;
--md-indigo-400: #5c6bc0;
--md-indigo-500: #3f51b5;
--md-indigo-600: #3949ab;
--md-indigo-700: #303f9f;
--md-indigo-800: #283593;
--md-indigo-900: #1a237e;
--md-indigo-A100: #8c9eff;
--md-indigo-A200: #536dfe;
--md-indigo-A400: #3d5afe;
--md-indigo-A700: #304ffe;
--md-blue-50: #e3f2fd;
--md-blue-100: #bbdefb;
--md-blue-200: #90caf9;
--md-blue-300: #64b5f6;
--md-blue-400: #42a5f5;
--md-blue-500: #2196f3;
--md-blue-600: #1e88e5;
--md-blue-700: #1976d2;
--md-blue-800: #1565c0;
--md-blue-900: #0d47a1;
--md-blue-A100: #82b1ff;
--md-blue-A200: #448aff;
--md-blue-A400: #2979ff;
--md-blue-A700: #2962ff;
--md-light-blue-50: #e1f5fe;
--md-light-blue-100: #b3e5fc;
--md-light-blue-200: #81d4fa;
--md-light-blue-300: #4fc3f7;
--md-light-blue-400: #29b6f6;
--md-light-blue-500: #03a9f4;
--md-light-blue-600: #039be5;
--md-light-blue-700: #0288d1;
--md-light-blue-800: #0277bd;
--md-light-blue-900: #01579b;
--md-light-blue-A100: #80d8ff;
--md-light-blue-A200: #40c4ff;
--md-light-blue-A400: #00b0ff;
--md-light-blue-A700: #0091ea;
--md-cyan-50: #e0f7fa;
--md-cyan-100: #b2ebf2;
--md-cyan-200: #80deea;
--md-cyan-300: #4dd0e1;
--md-cyan-400: #26c6da;
--md-cyan-500: #00bcd4;
--md-cyan-600: #00acc1;
--md-cyan-700: #0097a7;
--md-cyan-800: #00838f;
--md-cyan-900: #006064;
--md-cyan-A100: #84ffff;
--md-cyan-A200: #18ffff;
--md-cyan-A400: #00e5ff;
--md-cyan-A700: #00b8d4;
--md-teal-50: #e0f2f1;
--md-teal-100: #b2dfdb;
--md-teal-200: #80cbc4;
--md-teal-300: #4db6ac;
--md-teal-400: #26a69a;
--md-teal-500: #009688;
--md-teal-600: #00897b;
--md-teal-700: #00796b;
--md-teal-800: #00695c;
--md-teal-900: #004d40;
--md-teal-A100: #a7ffeb;
--md-teal-A200: #64ffda;
--md-teal-A400: #1de9b6;
--md-teal-A700: #00bfa5;
--md-green-50: #e8f5e9;
--md-green-100: #c8e6c9;
--md-green-200: #a5d6a7;
--md-green-300: #81c784;
--md-green-400: #66bb6a;
--md-green-500: #4caf50;
--md-green-600: #43a047;
--md-green-700: #388e3c;
--md-green-800: #2e7d32;
--md-green-900: #1b5e20;
--md-green-A100: #b9f6ca;
--md-green-A200: #69f0ae;
--md-green-A400: #00e676;
--md-green-A700: #00c853;
--md-light-green-50: #f1f8e9;
--md-light-green-100: #dcedc8;
--md-light-green-200: #c5e1a5;
--md-light-green-300: #aed581;
--md-light-green-400: #9ccc65;
--md-light-green-500: #8bc34a;
--md-light-green-600: #7cb342;
--md-light-green-700: #689f38;
--md-light-green-800: #558b2f;
--md-light-green-900: #33691e;
--md-light-green-A100: #ccff90;
--md-light-green-A200: #b2ff59;
--md-light-green-A400: #76ff03;
--md-light-green-A700: #64dd17;
--md-lime-50: #f9fbe7;
--md-lime-100: #f0f4c3;
--md-lime-200: #e6ee9c;
--md-lime-300: #dce775;
--md-lime-400: #d4e157;
--md-lime-500: #cddc39;
--md-lime-600: #c0ca33;
--md-lime-700: #afb42b;
--md-lime-800: #9e9d24;
--md-lime-900: #827717;
--md-lime-A100: #f4ff81;
--md-lime-A200: #eeff41;
--md-lime-A400: #c6ff00;
--md-lime-A700: #aeea00;
--md-yellow-50: #fffde7;
--md-yellow-100: #fff9c4;
--md-yellow-200: #fff59d;
--md-yellow-300: #fff176;
--md-yellow-400: #ffee58;
--md-yellow-500: #ffeb3b;
--md-yellow-600: #fdd835;
--md-yellow-700: #fbc02d;
--md-yellow-800: #f9a825;
--md-yellow-900: #f57f17;
--md-yellow-A100: #ffff8d;
--md-yellow-A200: #ff0;
--md-yellow-A400: #ffea00;
--md-yellow-A700: #ffd600;
--md-amber-50: #fff8e1;
--md-amber-100: #ffecb3;
--md-amber-200: #ffe082;
--md-amber-300: #ffd54f;
--md-amber-400: #ffca28;
--md-amber-500: #ffc107;
--md-amber-600: #ffb300;
--md-amber-700: #ffa000;
--md-amber-800: #ff8f00;
--md-amber-900: #ff6f00;
--md-amber-A100: #ffe57f;
--md-amber-A200: #ffd740;
--md-amber-A400: #ffc400;
--md-amber-A700: #ffab00;
--md-orange-50: #fff3e0;
--md-orange-100: #ffe0b2;
--md-orange-200: #ffcc80;
--md-orange-300: #ffb74d;
--md-orange-400: #ffa726;
--md-orange-500: #ff9800;
--md-orange-600: #fb8c00;
--md-orange-700: #f57c00;
--md-orange-800: #ef6c00;
--md-orange-900: #e65100;
--md-orange-A100: #ffd180;
--md-orange-A200: #ffab40;
--md-orange-A400: #ff9100;
--md-orange-A700: #ff6d00;
--md-deep-orange-50: #fbe9e7;
--md-deep-orange-100: #ffccbc;
--md-deep-orange-200: #ffab91;
--md-deep-orange-300: #ff8a65;
--md-deep-orange-400: #ff7043;
--md-deep-orange-500: #ff5722;
--md-deep-orange-600: #f4511e;
--md-deep-orange-700: #e64a19;
--md-deep-orange-800: #d84315;
--md-deep-orange-900: #bf360c;
--md-deep-orange-A100: #ff9e80;
--md-deep-orange-A200: #ff6e40;
--md-deep-orange-A400: #ff3d00;
--md-deep-orange-A700: #dd2c00;
--md-brown-50: #efebe9;
--md-brown-100: #d7ccc8;
--md-brown-200: #bcaaa4;
--md-brown-300: #a1887f;
--md-brown-400: #8d6e63;
--md-brown-500: #795548;
--md-brown-600: #6d4c41;
--md-brown-700: #5d4037;
--md-brown-800: #4e342e;
--md-brown-900: #3e2723;
--md-grey-50: #fafafa;
--md-grey-100: #f5f5f5;
--md-grey-200: #eee;
--md-grey-300: #e0e0e0;
--md-grey-400: #bdbdbd;
--md-grey-500: #9e9e9e;
--md-grey-600: #757575;
--md-grey-700: #616161;
--md-grey-800: #424242;
--md-grey-900: #212121;
--md-blue-grey-50: #eceff1;
--md-blue-grey-100: #cfd8dc;
--md-blue-grey-200: #b0bec5;
--md-blue-grey-300: #90a4ae;
--md-blue-grey-400: #78909c;
--md-blue-grey-500: #607d8b;
--md-blue-grey-600: #546e7a;
--md-blue-grey-700: #455a64;
--md-blue-grey-800: #37474f;
--md-blue-grey-900: #263238;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| RenderedText
|----------------------------------------------------------------------------*/
:root {
/* This is the padding value to fill the gaps between lines containing spans with background color. */
--jp-private-code-span-padding: calc(
(var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
);
}
.jp-RenderedText {
text-align: left;
padding-left: var(--jp-code-padding);
line-height: var(--jp-code-line-height);
font-family: var(--jp-code-font-family);
}
.jp-RenderedText pre,
.jp-RenderedJavaScript pre,
.jp-RenderedHTMLCommon pre {
color: var(--jp-content-font-color1);
font-size: var(--jp-code-font-size);
border: none;
margin: 0;
padding: 0;
}
.jp-RenderedText pre a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* console foregrounds and backgrounds */
.jp-RenderedText pre .ansi-black-fg {
color: #3e424d;
}
.jp-RenderedText pre .ansi-red-fg {
color: #e75c58;
}
.jp-RenderedText pre .ansi-green-fg {
color: #00a250;
}
.jp-RenderedText pre .ansi-yellow-fg {
color: #ddb62b;
}
.jp-RenderedText pre .ansi-blue-fg {
color: #208ffb;
}
.jp-RenderedText pre .ansi-magenta-fg {
color: #d160c4;
}
.jp-RenderedText pre .ansi-cyan-fg {
color: #60c6c8;
}
.jp-RenderedText pre .ansi-white-fg {
color: #c5c1b4;
}
.jp-RenderedText pre .ansi-black-bg {
background-color: #3e424d;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-bg {
background-color: #e75c58;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-bg {
background-color: #00a250;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-bg {
background-color: #ddb62b;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-bg {
background-color: #208ffb;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-bg {
background-color: #d160c4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-bg {
background-color: #60c6c8;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-bg {
background-color: #c5c1b4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-black-intense-fg {
color: #282c36;
}
.jp-RenderedText pre .ansi-red-intense-fg {
color: #b22b31;
}
.jp-RenderedText pre .ansi-green-intense-fg {
color: #007427;
}
.jp-RenderedText pre .ansi-yellow-intense-fg {
color: #b27d12;
}
.jp-RenderedText pre .ansi-blue-intense-fg {
color: #0065ca;
}
.jp-RenderedText pre .ansi-magenta-intense-fg {
color: #a03196;
}
.jp-RenderedText pre .ansi-cyan-intense-fg {
color: #258f8f;
}
.jp-RenderedText pre .ansi-white-intense-fg {
color: #a1a6b2;
}
.jp-RenderedText pre .ansi-black-intense-bg {
background-color: #282c36;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-intense-bg {
background-color: #b22b31;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-intense-bg {
background-color: #007427;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-intense-bg {
background-color: #b27d12;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-intense-bg {
background-color: #0065ca;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-intense-bg {
background-color: #a03196;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-intense-bg {
background-color: #258f8f;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-intense-bg {
background-color: #a1a6b2;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-default-inverse-fg {
color: var(--jp-ui-inverse-font-color0);
}
.jp-RenderedText pre .ansi-default-inverse-bg {
background-color: var(--jp-inverse-layout-color0);
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-bold {
font-weight: bold;
}
.jp-RenderedText pre .ansi-underline {
text-decoration: underline;
}
.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
background: var(--jp-rendermime-error-background);
padding-top: var(--jp-code-padding);
}
/*-----------------------------------------------------------------------------
| RenderedLatex
|----------------------------------------------------------------------------*/
.jp-RenderedLatex {
color: var(--jp-content-font-color1);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
}
/* Left-justify outputs.*/
.jp-OutputArea-output.jp-RenderedLatex {
padding: var(--jp-code-padding);
text-align: left;
}
/*-----------------------------------------------------------------------------
| RenderedHTML
|----------------------------------------------------------------------------*/
.jp-RenderedHTMLCommon {
color: var(--jp-content-font-color1);
font-family: var(--jp-content-font-family);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
/* Give a bit more R padding on Markdown text to keep line lengths reasonable */
padding-right: 20px;
}
.jp-RenderedHTMLCommon em {
font-style: italic;
}
.jp-RenderedHTMLCommon strong {
font-weight: bold;
}
.jp-RenderedHTMLCommon u {
text-decoration: underline;
}
.jp-RenderedHTMLCommon a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* Headings */
.jp-RenderedHTMLCommon h1,
.jp-RenderedHTMLCommon h2,
.jp-RenderedHTMLCommon h3,
.jp-RenderedHTMLCommon h4,
.jp-RenderedHTMLCommon h5,
.jp-RenderedHTMLCommon h6 {
line-height: var(--jp-content-heading-line-height);
font-weight: var(--jp-content-heading-font-weight);
font-style: normal;
margin: var(--jp-content-heading-margin-top) 0
var(--jp-content-heading-margin-bottom) 0;
}
.jp-RenderedHTMLCommon h1:first-child,
.jp-RenderedHTMLCommon h2:first-child,
.jp-RenderedHTMLCommon h3:first-child,
.jp-RenderedHTMLCommon h4:first-child,
.jp-RenderedHTMLCommon h5:first-child,
.jp-RenderedHTMLCommon h6:first-child {
margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
}
.jp-RenderedHTMLCommon h1:last-child,
.jp-RenderedHTMLCommon h2:last-child,
.jp-RenderedHTMLCommon h3:last-child,
.jp-RenderedHTMLCommon h4:last-child,
.jp-RenderedHTMLCommon h5:last-child,
.jp-RenderedHTMLCommon h6:last-child {
margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
}
.jp-RenderedHTMLCommon h1 {
font-size: var(--jp-content-font-size5);
}
.jp-RenderedHTMLCommon h2 {
font-size: var(--jp-content-font-size4);
}
.jp-RenderedHTMLCommon h3 {
font-size: var(--jp-content-font-size3);
}
.jp-RenderedHTMLCommon h4 {
font-size: var(--jp-content-font-size2);
}
.jp-RenderedHTMLCommon h5 {
font-size: var(--jp-content-font-size1);
}
.jp-RenderedHTMLCommon h6 {
font-size: var(--jp-content-font-size0);
}
/* Lists */
/* stylelint-disable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon ul:not(.list-inline),
.jp-RenderedHTMLCommon ol:not(.list-inline) {
padding-left: 2em;
}
.jp-RenderedHTMLCommon ul {
list-style: disc;
}
.jp-RenderedHTMLCommon ul ul {
list-style: square;
}
.jp-RenderedHTMLCommon ul ul ul {
list-style: circle;
}
.jp-RenderedHTMLCommon ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol ol {
list-style: upper-alpha;
}
.jp-RenderedHTMLCommon ol ol ol {
list-style: lower-alpha;
}
.jp-RenderedHTMLCommon ol ol ol ol {
list-style: lower-roman;
}
.jp-RenderedHTMLCommon ol ol ol ol ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol,
.jp-RenderedHTMLCommon ul {
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon ul ul,
.jp-RenderedHTMLCommon ul ol,
.jp-RenderedHTMLCommon ol ul,
.jp-RenderedHTMLCommon ol ol {
margin-bottom: 0;
}
/* stylelint-enable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon hr {
color: var(--jp-border-color2);
background-color: var(--jp-border-color1);
margin-top: 1em;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon > pre {
margin: 1.5em 2em;
}
.jp-RenderedHTMLCommon pre,
.jp-RenderedHTMLCommon code {
border: 0;
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
font-family: var(--jp-code-font-family);
font-size: inherit;
line-height: var(--jp-code-line-height);
padding: 0;
white-space: pre-wrap;
}
.jp-RenderedHTMLCommon :not(pre) > code {
background-color: var(--jp-layout-color2);
padding: 1px 5px;
}
/* Tables */
.jp-RenderedHTMLCommon table {
border-collapse: collapse;
border-spacing: 0;
border: none;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
table-layout: fixed;
margin-left: auto;
margin-bottom: 1em;
margin-right: auto;
}
.jp-RenderedHTMLCommon thead {
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
vertical-align: bottom;
}
.jp-RenderedHTMLCommon td,
.jp-RenderedHTMLCommon th,
.jp-RenderedHTMLCommon tr {
vertical-align: middle;
padding: 0.5em;
line-height: normal;
white-space: normal;
max-width: none;
border: none;
}
.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
max-width: none;
}
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
text-align: right;
}
.jp-RenderedHTMLCommon th {
font-weight: bold;
}
.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
background: var(--jp-layout-color0);
}
.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
background: var(--jp-rendermime-table-row-background);
}
.jp-RenderedHTMLCommon tbody tr:hover {
background: var(--jp-rendermime-table-row-hover-background);
}
.jp-RenderedHTMLCommon p {
text-align: left;
margin: 0;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon img {
-moz-force-broken-image-icon: 1;
}
/* Restrict to direct children as other images could be nested in other content. */
.jp-RenderedHTMLCommon > img {
display: block;
margin-left: 0;
margin-right: 0;
margin-bottom: 1em;
}
/* Change color behind transparent images if they need it... */
[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
background-color: var(--jp-inverse-layout-color1);
}
[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
background-color: var(--jp-inverse-layout-color1);
}
.jp-RenderedHTMLCommon img,
.jp-RenderedImage img,
.jp-RenderedHTMLCommon svg,
.jp-RenderedSVG svg {
max-width: 100%;
height: auto;
}
.jp-RenderedHTMLCommon img.jp-mod-unconfined,
.jp-RenderedImage img.jp-mod-unconfined,
.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
.jp-RenderedSVG svg.jp-mod-unconfined {
max-width: none;
}
.jp-RenderedHTMLCommon .alert {
padding: var(--jp-notebook-padding);
border: var(--jp-border-width) solid transparent;
border-radius: var(--jp-border-radius);
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon .alert-info {
color: var(--jp-info-color0);
background-color: var(--jp-info-color3);
border-color: var(--jp-info-color2);
}
.jp-RenderedHTMLCommon .alert-info hr {
border-color: var(--jp-info-color3);
}
.jp-RenderedHTMLCommon .alert-info > p:last-child,
.jp-RenderedHTMLCommon .alert-info > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-warning {
color: var(--jp-warn-color0);
background-color: var(--jp-warn-color3);
border-color: var(--jp-warn-color2);
}
.jp-RenderedHTMLCommon .alert-warning hr {
border-color: var(--jp-warn-color3);
}
.jp-RenderedHTMLCommon .alert-warning > p:last-child,
.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-success {
color: var(--jp-success-color0);
background-color: var(--jp-success-color3);
border-color: var(--jp-success-color2);
}
.jp-RenderedHTMLCommon .alert-success hr {
border-color: var(--jp-success-color3);
}
.jp-RenderedHTMLCommon .alert-success > p:last-child,
.jp-RenderedHTMLCommon .alert-success > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-danger {
color: var(--jp-error-color0);
background-color: var(--jp-error-color3);
border-color: var(--jp-error-color2);
}
.jp-RenderedHTMLCommon .alert-danger hr {
border-color: var(--jp-error-color3);
}
.jp-RenderedHTMLCommon .alert-danger > p:last-child,
.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon blockquote {
margin: 1em 2em;
padding: 0 1em;
border-left: 5px solid var(--jp-border-color2);
}
a.jp-InternalAnchorLink {
visibility: hidden;
margin-left: 8px;
color: var(--md-blue-800);
}
h1:hover .jp-InternalAnchorLink,
h2:hover .jp-InternalAnchorLink,
h3:hover .jp-InternalAnchorLink,
h4:hover .jp-InternalAnchorLink,
h5:hover .jp-InternalAnchorLink,
h6:hover .jp-InternalAnchorLink {
visibility: visible;
}
.jp-RenderedHTMLCommon kbd {
background-color: var(--jp-rendermime-table-row-background);
border: 1px solid var(--jp-border-color0);
border-bottom-color: var(--jp-border-color2);
border-radius: 3px;
box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
display: inline-block;
font-size: var(--jp-ui-font-size0);
line-height: 1em;
padding: 0.2em 0.5em;
}
/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
* At the bottom of cells this is a bit too much as there is also spacing
* between cells. Going all the way to 0 gets too tight between markdown and
* code cells.
*/
.jp-RenderedHTMLCommon > *:last-child {
margin-bottom: 0.5em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Copyright (c) 2014-2017, PhosphorJS Contributors
|
| Distributed under the terms of the BSD 3-Clause License.
|
| The full license is in the file LICENSE, distributed with this software.
|----------------------------------------------------------------------------*/
.lm-cursor-backdrop {
position: fixed;
width: 200px;
height: 200px;
margin-top: -100px;
margin-left: -100px;
will-change: transform;
z-index: 100;
}
.lm-mod-drag-image {
will-change: transform;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-lineFormSearch {
padding: 4px 12px;
background-color: var(--jp-layout-color2);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
font-size: var(--jp-ui-font-size1);
}
.jp-lineFormCaption {
font-size: var(--jp-ui-font-size0);
line-height: var(--jp-ui-font-size1);
margin-top: 4px;
color: var(--jp-ui-font-color0);
}
.jp-baseLineForm {
border: none;
border-radius: 0;
position: absolute;
background-size: 16px;
background-repeat: no-repeat;
background-position: center;
outline: none;
}
.jp-lineFormButtonContainer {
top: 4px;
right: 8px;
height: 24px;
padding: 0 12px;
width: 12px;
}
.jp-lineFormButtonIcon {
top: 0;
right: 0;
background-color: var(--jp-brand-color1);
height: 100%;
width: 100%;
box-sizing: border-box;
padding: 4px 6px;
}
.jp-lineFormButton {
top: 0;
right: 0;
background-color: transparent;
height: 100%;
width: 100%;
box-sizing: border-box;
}
.jp-lineFormWrapper {
overflow: hidden;
padding: 0 8px;
border: 1px solid var(--jp-border-color0);
background-color: var(--jp-input-active-background);
height: 22px;
}
.jp-lineFormWrapperFocusWithin {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-lineFormInput {
background: transparent;
width: 200px;
height: 100%;
border: none;
outline: none;
color: var(--jp-ui-font-color0);
line-height: 28px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-JSONEditor {
display: flex;
flex-direction: column;
width: 100%;
}
.jp-JSONEditor-host {
flex: 1 1 auto;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
background: var(--jp-layout-color0);
min-height: 50px;
padding: 1px;
}
.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
border-color: red;
outline-color: red;
}
.jp-JSONEditor-header {
display: flex;
flex: 1 0 auto;
padding: 0 0 0 12px;
}
.jp-JSONEditor-header label {
flex: 0 0 auto;
}
.jp-JSONEditor-commitButton {
height: 16px;
width: 16px;
background-size: 18px;
background-repeat: no-repeat;
background-position: center;
}
.jp-JSONEditor-host.jp-mod-focused {
background-color: var(--jp-input-active-background);
border: 1px solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
.jp-Editor.jp-mod-dropTarget {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-DocumentSearch-input {
border: none;
outline: none;
color: var(--jp-ui-font-color0);
font-size: var(--jp-ui-font-size1);
background-color: var(--jp-layout-color0);
font-family: var(--jp-ui-font-family);
padding: 2px 1px;
resize: none;
}
.jp-DocumentSearch-overlay {
position: absolute;
background-color: var(--jp-toolbar-background);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
top: 0;
right: 0;
z-index: 7;
min-width: 405px;
padding: 2px;
font-size: var(--jp-ui-font-size1);
--jp-private-document-search-button-height: 20px;
}
.jp-DocumentSearch-overlay button {
background-color: var(--jp-toolbar-background);
outline: 0;
}
.jp-DocumentSearch-overlay button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-overlay button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-overlay-row {
display: flex;
align-items: center;
margin-bottom: 2px;
}
.jp-DocumentSearch-button-content {
display: inline-block;
cursor: pointer;
box-sizing: border-box;
width: 100%;
height: 100%;
}
.jp-DocumentSearch-button-content svg {
width: 100%;
height: 100%;
}
.jp-DocumentSearch-input-wrapper {
border: var(--jp-border-width) solid var(--jp-border-color0);
display: flex;
background-color: var(--jp-layout-color0);
margin: 2px;
}
.jp-DocumentSearch-input-wrapper:focus-within {
border-color: var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper {
all: initial;
overflow: hidden;
display: inline-block;
border: none;
box-sizing: border-box;
}
.jp-DocumentSearch-toggle-wrapper {
width: 14px;
height: 14px;
}
.jp-DocumentSearch-button-wrapper {
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
}
.jp-DocumentSearch-toggle-wrapper:focus,
.jp-DocumentSearch-button-wrapper:focus {
outline: var(--jp-border-width) solid
var(--jp-cell-editor-active-border-color);
outline-offset: -1px;
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper,
.jp-DocumentSearch-button-content:focus {
outline: none;
}
.jp-DocumentSearch-toggle-placeholder {
width: 5px;
}
.jp-DocumentSearch-input-button::before {
display: block;
padding-top: 100%;
}
.jp-DocumentSearch-input-button-off {
opacity: var(--jp-search-toggle-off-opacity);
}
.jp-DocumentSearch-input-button-off:hover {
opacity: var(--jp-search-toggle-hover-opacity);
}
.jp-DocumentSearch-input-button-on {
opacity: var(--jp-search-toggle-on-opacity);
}
.jp-DocumentSearch-index-counter {
padding-left: 10px;
padding-right: 10px;
user-select: none;
min-width: 35px;
display: inline-block;
}
.jp-DocumentSearch-up-down-wrapper {
display: inline-block;
padding-right: 2px;
margin-left: auto;
white-space: nowrap;
}
.jp-DocumentSearch-spacer {
margin-left: auto;
}
.jp-DocumentSearch-up-down-wrapper button {
outline: 0;
border: none;
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
vertical-align: middle;
margin: 1px 5px 2px;
}
.jp-DocumentSearch-up-down-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-up-down-button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-filter-button {
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-filter-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled:hover {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-search-options {
padding: 0 8px;
margin-left: 3px;
width: 100%;
display: grid;
justify-content: start;
grid-template-columns: 1fr 1fr;
align-items: center;
justify-items: stretch;
}
.jp-DocumentSearch-search-filter-disabled {
color: var(--jp-ui-font-color2);
}
.jp-DocumentSearch-search-filter {
display: flex;
align-items: center;
user-select: none;
}
.jp-DocumentSearch-regex-error {
color: var(--jp-error-color0);
}
.jp-DocumentSearch-replace-button-wrapper {
overflow: hidden;
display: inline-block;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color0);
margin: auto 2px;
padding: 1px 4px;
height: calc(var(--jp-private-document-search-button-height) + 2px);
}
.jp-DocumentSearch-replace-button-wrapper:focus {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-replace-button {
display: inline-block;
text-align: center;
cursor: pointer;
box-sizing: border-box;
color: var(--jp-ui-font-color1);
/* height - 2 * (padding of wrapper) */
line-height: calc(var(--jp-private-document-search-button-height) - 2px);
width: 100%;
height: 100%;
}
.jp-DocumentSearch-replace-button:focus {
outline: none;
}
.jp-DocumentSearch-replace-wrapper-class {
margin-left: 14px;
display: flex;
}
.jp-DocumentSearch-replace-toggle {
border: none;
background-color: var(--jp-toolbar-background);
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-replace-toggle:hover {
background-color: var(--jp-layout-color2);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.cm-editor {
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
border: 0;
border-radius: 0;
height: auto;
/* Changed to auto to autogrow */
}
.cm-editor pre {
padding: 0 var(--jp-code-padding);
}
.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
}
.jp-CodeMirrorEditor {
cursor: text;
}
/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
@media screen and (min-width: 2138px) and (max-width: 4319px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width1) solid
var(--jp-editor-cursor-color);
}
}
/* When zoomed out less than 33% */
@media screen and (min-width: 4320px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width2) solid
var(--jp-editor-cursor-color);
}
}
.cm-editor.jp-mod-readOnly .cm-cursor {
display: none;
}
.jp-CollaboratorCursor {
border-left: 5px solid transparent;
border-right: 5px solid transparent;
border-top: none;
border-bottom: 3px solid;
background-clip: content-box;
margin-left: -5px;
margin-right: -5px;
}
.cm-searching,
.cm-searching span {
/* `.cm-searching span`: we need to override syntax highlighting */
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.cm-searching::selection,
.cm-searching span::selection {
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.jp-current-match > .cm-searching,
.jp-current-match > .cm-searching span,
.cm-searching > .jp-current-match,
.cm-searching > .jp-current-match span {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.jp-current-match > .cm-searching::selection,
.cm-searching > .jp-current-match::selection,
.jp-current-match > .cm-searching span::selection {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.cm-trailingspace {
background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
background-position: center left;
background-repeat: repeat-x;
}
.jp-CollaboratorCursor-hover {
position: absolute;
z-index: 1;
transform: translateX(-50%);
color: white;
border-radius: 3px;
padding-left: 4px;
padding-right: 4px;
padding-top: 1px;
padding-bottom: 1px;
text-align: center;
font-size: var(--jp-ui-font-size1);
white-space: nowrap;
}
.jp-CodeMirror-ruler {
border-left: 1px dashed var(--jp-border-color2);
}
/* Styles for shared cursors (remote cursor locations and selected ranges) */
.jp-CodeMirrorEditor .cm-ySelectionCaret {
position: relative;
border-left: 1px solid black;
margin-left: -1px;
margin-right: -1px;
box-sizing: border-box;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
white-space: nowrap;
position: absolute;
top: -1.15em;
padding-bottom: 0.05em;
left: -1px;
font-size: 0.95em;
font-family: var(--jp-ui-font-family);
font-weight: bold;
line-height: normal;
user-select: none;
color: white;
padding-left: 2px;
padding-right: 2px;
z-index: 101;
transition: opacity 0.3s ease-in-out;
}
.jp-CodeMirrorEditor .cm-ySelectionInfo {
transition-delay: 0.7s;
opacity: 0;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
opacity: 1;
transition-delay: 0s;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MimeDocument {
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-filebrowser-button-height: 28px;
--jp-private-filebrowser-button-width: 48px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FileBrowser .jp-SidePanel-content {
display: flex;
flex-direction: column;
}
.jp-FileBrowser-toolbar.jp-Toolbar {
flex-wrap: wrap;
row-gap: 12px;
border-bottom: none;
height: auto;
margin: 8px 12px 0;
box-shadow: none;
padding: 0;
justify-content: flex-start;
}
.jp-FileBrowser-Panel {
flex: 1 1 auto;
display: flex;
flex-direction: column;
}
.jp-BreadCrumbs {
flex: 0 0 auto;
margin: 8px 12px;
}
.jp-BreadCrumbs-item {
margin: 0 2px;
padding: 0 2px;
border-radius: var(--jp-border-radius);
cursor: pointer;
}
.jp-BreadCrumbs-item:hover {
background-color: var(--jp-layout-color2);
}
.jp-BreadCrumbs-item:first-child {
margin-left: 0;
}
.jp-BreadCrumbs-item.jp-mod-dropTarget {
background-color: var(--jp-brand-color2);
opacity: 0.7;
}
/*-----------------------------------------------------------------------------
| Buttons
|----------------------------------------------------------------------------*/
.jp-FileBrowser-toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
padding-left: 0;
padding-right: 2px;
align-items: center;
height: unset;
}
.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
width: 40px;
}
/*-----------------------------------------------------------------------------
| Other styles
|----------------------------------------------------------------------------*/
.jp-FileDialog.jp-mod-conflict input {
color: var(--jp-error-color1);
}
.jp-FileDialog .jp-new-name-title {
margin-top: 12px;
}
.jp-LastModified-hidden {
display: none;
}
.jp-FileSize-hidden {
display: none;
}
.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
display: none;
}
/*-----------------------------------------------------------------------------
| DirListing
|----------------------------------------------------------------------------*/
.jp-DirListing {
flex: 1 1 auto;
display: flex;
flex-direction: column;
outline: 0;
}
.jp-DirListing-header {
flex: 0 0 auto;
display: flex;
flex-direction: row;
align-items: center;
overflow: hidden;
border-top: var(--jp-border-width) solid var(--jp-border-color2);
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
}
.jp-DirListing-headerItem {
padding: 4px 12px 2px;
font-weight: 500;
}
.jp-DirListing-headerItem:hover {
background: var(--jp-layout-color2);
}
.jp-DirListing-headerItem.jp-id-name {
flex: 1 0 84px;
}
.jp-DirListing-headerItem.jp-id-modified {
flex: 0 0 112px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-DirListing-headerItem.jp-id-filesize {
flex: 0 0 75px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-id-narrow {
display: none;
flex: 0 0 5px;
padding: 4px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
color: var(--jp-border-color2);
}
.jp-DirListing-narrow .jp-id-narrow {
display: block;
}
.jp-DirListing-narrow .jp-id-modified,
.jp-DirListing-narrow .jp-DirListing-itemModified {
display: none;
}
.jp-DirListing-headerItem.jp-mod-selected {
font-weight: 600;
}
/* increase specificity to override bundled default */
.jp-DirListing-content {
flex: 1 1 auto;
margin: 0;
padding: 0;
list-style-type: none;
overflow: auto;
background-color: var(--jp-layout-color1);
}
.jp-DirListing-content mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
color: var(--jp-ui-inverse-font-color0);
}
/* Style the directory listing content when a user drops a file to upload */
.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
outline: 5px dashed rgba(128, 128, 128, 0.5);
outline-offset: -10px;
cursor: copy;
}
.jp-DirListing-item {
display: flex;
flex-direction: row;
align-items: center;
padding: 4px 12px;
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-DirListing-checkboxWrapper {
/* Increases hit area of checkbox. */
padding: 4px;
}
.jp-DirListing-header
.jp-DirListing-checkboxWrapper
+ .jp-DirListing-headerItem {
padding-left: 4px;
}
.jp-DirListing-content .jp-DirListing-checkboxWrapper {
position: relative;
left: -4px;
margin: -4px 0 -4px -8px;
}
.jp-DirListing-checkboxWrapper.jp-mod-visible {
visibility: visible;
}
/* For devices that support hovering, hide checkboxes until hovered, selected...
*/
@media (hover: hover) {
.jp-DirListing-checkboxWrapper {
visibility: hidden;
}
.jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
.jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
visibility: visible;
}
}
.jp-DirListing-item[data-is-dot] {
opacity: 75%;
}
.jp-DirListing-item.jp-mod-selected {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.jp-DirListing-item.jp-mod-dropTarget {
background: var(--jp-brand-color3);
}
.jp-DirListing-item:hover:not(.jp-mod-selected) {
background: var(--jp-layout-color2);
}
.jp-DirListing-itemIcon {
flex: 0 0 20px;
margin-right: 4px;
}
.jp-DirListing-itemText {
flex: 1 0 64px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
user-select: none;
}
.jp-DirListing-itemText:focus {
outline-width: 2px;
outline-color: var(--jp-inverse-layout-color1);
outline-style: solid;
outline-offset: 1px;
}
.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
outline-color: var(--jp-layout-color1);
}
.jp-DirListing-itemModified {
flex: 0 0 125px;
text-align: right;
}
.jp-DirListing-itemFileSize {
flex: 0 0 90px;
text-align: right;
}
.jp-DirListing-editor {
flex: 1 0 64px;
outline: none;
border: none;
color: var(--jp-ui-font-color1);
background-color: var(--jp-layout-color1);
}
.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
color: var(--jp-success-color1);
content: '\25CF';
font-size: 8px;
position: absolute;
left: -8px;
}
.jp-DirListing-item.jp-mod-running.jp-mod-selected
.jp-DirListing-itemIcon::before {
color: var(--jp-ui-inverse-font-color1);
}
.jp-DirListing-item.lm-mod-drag-image,
.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
font-size: var(--jp-ui-font-size1);
padding-left: 4px;
margin-left: 4px;
width: 160px;
background-color: var(--jp-ui-inverse-font-color2);
box-shadow: var(--jp-elevation-z2);
border-radius: 0;
color: var(--jp-ui-font-color1);
transform: translateX(-40%) translateY(-58%);
}
.jp-Document {
min-width: 120px;
min-height: 120px;
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Main OutputArea
| OutputArea has a list of Outputs
|----------------------------------------------------------------------------*/
.jp-OutputArea {
overflow-y: auto;
}
.jp-OutputArea-child {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-OutputPrompt {
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-outprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
opacity: var(--jp-cell-prompt-opacity);
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-OutputArea-prompt {
display: table-cell;
vertical-align: top;
}
.jp-OutputArea-output {
display: table-cell;
width: 100%;
height: auto;
overflow: auto;
user-select: text;
-moz-user-select: text;
-webkit-user-select: text;
-ms-user-select: text;
}
.jp-OutputArea .jp-RenderedText {
padding-left: 1ch;
}
/**
* Prompt overlay.
*/
.jp-OutputArea-promptOverlay {
position: absolute;
top: 0;
width: var(--jp-cell-prompt-width);
height: 100%;
opacity: 0.5;
}
.jp-OutputArea-promptOverlay:hover {
background: var(--jp-layout-color2);
box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
cursor: zoom-out;
}
.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
cursor: zoom-in;
}
/**
* Isolated output.
*/
.jp-OutputArea-output.jp-mod-isolated {
width: 100%;
display: block;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
position: relative;
}
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/* pre */
.jp-OutputArea-output pre {
border: none;
margin: 0;
padding: 0;
overflow-x: auto;
overflow-y: auto;
word-break: break-all;
word-wrap: break-word;
white-space: pre-wrap;
}
/* tables */
.jp-OutputArea-output.jp-RenderedHTMLCommon table {
margin-left: 0;
margin-right: 0;
}
/* description lists */
.jp-OutputArea-output dl,
.jp-OutputArea-output dt,
.jp-OutputArea-output dd {
display: block;
}
.jp-OutputArea-output dl {
width: 100%;
overflow: hidden;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dt {
font-weight: bold;
float: left;
width: 20%;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dd {
float: left;
width: 80%;
padding: 0;
margin: 0;
}
.jp-TrimmedOutputs pre {
background: var(--jp-layout-color3);
font-size: calc(var(--jp-code-font-size) * 1.4);
text-align: center;
text-transform: uppercase;
}
/* Hide the gutter in case of
* - nested output areas (e.g. in the case of output widgets)
* - mirrored output areas
*/
.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
display: none;
}
/* Hide empty lines in the output area, for instance due to cleared widgets */
.jp-OutputArea-prompt:empty {
padding: 0;
border: 0;
}
/*-----------------------------------------------------------------------------
| executeResult is added to any Output-result for the display of the object
| returned by a cell
|----------------------------------------------------------------------------*/
.jp-OutputArea-output.jp-OutputArea-executeResult {
margin-left: 0;
width: 100%;
}
/* Text output with the Out[] prompt needs a top padding to match the
* alignment of the Out[] prompt itself.
*/
.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
padding-top: var(--jp-code-padding);
border-top: var(--jp-border-width) solid transparent;
}
/*-----------------------------------------------------------------------------
| The Stdin output
|----------------------------------------------------------------------------*/
.jp-Stdin-prompt {
color: var(--jp-content-font-color0);
padding-right: var(--jp-code-padding);
vertical-align: baseline;
flex: 0 0 auto;
}
.jp-Stdin-input {
font-family: var(--jp-code-font-family);
font-size: inherit;
color: inherit;
background-color: inherit;
width: 42%;
min-width: 200px;
/* make sure input baseline aligns with prompt */
vertical-align: baseline;
/* padding + margin = 0.5em between prompt and cursor */
padding: 0 0.25em;
margin: 0 0.25em;
flex: 0 0 70%;
}
.jp-Stdin-input::placeholder {
opacity: 0;
}
.jp-Stdin-input:focus {
box-shadow: none;
}
.jp-Stdin-input:focus::placeholder {
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Output Area View
|----------------------------------------------------------------------------*/
.jp-LinkedOutputView .jp-OutputArea {
height: 100%;
display: block;
}
.jp-LinkedOutputView .jp-OutputArea-output:only-child {
height: 100%;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
@media print {
.jp-OutputArea-child {
break-inside: avoid-page;
}
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-OutputPrompt {
display: table-row;
text-align: left;
}
.jp-OutputArea-child .jp-OutputArea-output {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
}
/* Trimmed outputs warning */
.jp-TrimmedOutputs > a {
margin: 10px;
text-decoration: none;
cursor: pointer;
}
.jp-TrimmedOutputs > a:hover {
text-decoration: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Table of Contents
|----------------------------------------------------------------------------*/
:root {
--jp-private-toc-active-width: 4px;
}
.jp-TableOfContents {
display: flex;
flex-direction: column;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
height: 100%;
}
.jp-TableOfContents-placeholder {
text-align: center;
}
.jp-TableOfContents-placeholderContent {
color: var(--jp-content-font-color2);
padding: 8px;
}
.jp-TableOfContents-placeholderContent > h3 {
margin-bottom: var(--jp-content-heading-margin-bottom);
}
.jp-TableOfContents .jp-SidePanel-content {
overflow-y: auto;
}
.jp-TableOfContents-tree {
margin: 4px;
}
.jp-TableOfContents ol {
list-style-type: none;
}
/* stylelint-disable-next-line selector-max-type */
.jp-TableOfContents li > ol {
/* Align left border with triangle icon center */
padding-left: 11px;
}
.jp-TableOfContents-content {
/* left margin for the active heading indicator */
margin: 0 0 0 var(--jp-private-toc-active-width);
padding: 0;
background-color: var(--jp-layout-color1);
}
.jp-tocItem {
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-tocItem-heading {
display: flex;
cursor: pointer;
}
.jp-tocItem-heading:hover {
background-color: var(--jp-layout-color2);
}
.jp-tocItem-content {
display: block;
padding: 4px 0;
white-space: nowrap;
text-overflow: ellipsis;
overflow-x: hidden;
}
.jp-tocItem-collapser {
height: 20px;
margin: 2px 2px 0;
padding: 0;
background: none;
border: none;
cursor: pointer;
}
.jp-tocItem-collapser:hover {
background-color: var(--jp-layout-color3);
}
/* Active heading indicator */
.jp-tocItem-heading::before {
content: ' ';
background: transparent;
width: var(--jp-private-toc-active-width);
height: 24px;
position: absolute;
left: 0;
border-radius: var(--jp-border-radius);
}
.jp-tocItem-heading.jp-tocItem-active::before {
background-color: var(--jp-brand-color1);
}
.jp-tocItem-heading:hover.jp-tocItem-active::before {
background: var(--jp-brand-color0);
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Collapser {
flex: 0 0 var(--jp-cell-collapser-width);
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
border-radius: var(--jp-border-radius);
opacity: 1;
}
.jp-Collapser-child {
display: block;
width: 100%;
box-sizing: border-box;
/* height: 100% doesn't work because the height of its parent is computed from content */
position: absolute;
top: 0;
bottom: 0;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Hiding collapsers in print mode.
Note: input and output wrappers have "display: block" propery in print mode.
*/
@media print {
.jp-Collapser {
display: none;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Header/Footer
|----------------------------------------------------------------------------*/
/* Hidden by zero height by default */
.jp-CellHeader,
.jp-CellFooter {
height: 0;
width: 100%;
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Input
|----------------------------------------------------------------------------*/
/* All input areas */
.jp-InputArea {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-InputArea-editor {
display: table-cell;
overflow: hidden;
vertical-align: top;
/* This is the non-active, default styling */
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
background: var(--jp-cell-editor-background);
}
.jp-InputPrompt {
display: table-cell;
vertical-align: top;
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-inprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
opacity: var(--jp-cell-prompt-opacity);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-InputArea-editor {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
.jp-InputPrompt {
display: table-row;
text-align: left;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Placeholder {
display: table;
table-layout: fixed;
width: 100%;
}
.jp-Placeholder-prompt {
display: table-cell;
box-sizing: border-box;
}
.jp-Placeholder-content {
display: table-cell;
padding: 4px 6px;
border: 1px solid transparent;
border-radius: 0;
background: none;
box-sizing: border-box;
cursor: pointer;
}
.jp-Placeholder-contentContainer {
display: flex;
}
.jp-Placeholder-content:hover,
.jp-InputPlaceholder > .jp-Placeholder-content:hover {
border-color: var(--jp-layout-color3);
}
.jp-Placeholder-content .jp-MoreHorizIcon {
width: 32px;
height: 16px;
border: 1px solid transparent;
border-radius: var(--jp-border-radius);
}
.jp-Placeholder-content .jp-MoreHorizIcon:hover {
border: 1px solid var(--jp-border-color1);
box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
background-color: var(--jp-layout-color0);
}
.jp-PlaceholderText {
white-space: nowrap;
overflow-x: hidden;
color: var(--jp-inverse-layout-color3);
font-family: var(--jp-code-font-family);
}
.jp-InputPlaceholder > .jp-Placeholder-content {
border-color: var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Private CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-cell-scrolling-output-offset: 5px;
}
/*-----------------------------------------------------------------------------
| Cell
|----------------------------------------------------------------------------*/
.jp-Cell {
padding: var(--jp-cell-padding);
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Common input/output
|----------------------------------------------------------------------------*/
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: flex;
flex-direction: row;
padding: 0;
margin: 0;
/* Added to reveal the box-shadow on the input and output collapsers. */
overflow: visible;
}
/* Only input/output areas inside cells */
.jp-Cell-inputArea,
.jp-Cell-outputArea {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Collapser
|----------------------------------------------------------------------------*/
/* Make the output collapser disappear when there is not output, but do so
* in a manner that leaves it in the layout and preserves its width.
*/
.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
border: none !important;
background: transparent !important;
}
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
min-height: var(--jp-cell-collapser-min-height);
}
/*-----------------------------------------------------------------------------
| Output
|----------------------------------------------------------------------------*/
/* Put a space between input and output when there IS output */
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
margin-top: 5px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
overflow-y: auto;
max-height: 24em;
margin-left: var(--jp-private-cell-scrolling-output-offset);
resize: vertical;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
max-height: unset;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
content: ' ';
box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
width: 100%;
height: 100%;
position: sticky;
bottom: 0;
top: 0;
margin-top: -50%;
float: left;
display: block;
pointer-events: none;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
padding-top: 6px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
width: calc(
var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
);
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
}
/*-----------------------------------------------------------------------------
| CodeCell
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| MarkdownCell
|----------------------------------------------------------------------------*/
.jp-MarkdownOutput {
display: table-cell;
width: 100%;
margin-top: 0;
margin-bottom: 0;
padding-left: var(--jp-code-padding);
}
.jp-MarkdownOutput.jp-RenderedHTMLCommon {
overflow: auto;
}
/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
.jp-collapseHeadingButton {
display: flex;
min-height: var(--jp-cell-collapser-min-height);
font-size: var(--jp-code-font-size);
position: absolute;
background-color: transparent;
background-size: 25px;
background-repeat: no-repeat;
background-position-x: center;
background-position-y: top;
background-image: var(--jp-icon-caret-down);
right: 0;
top: 0;
bottom: 0;
}
.jp-collapseHeadingButton.jp-mod-collapsed {
background-image: var(--jp-icon-caret-right);
}
/*
set the container font size to match that of content
so that the nested collapse buttons have the right size
*/
.jp-MarkdownCell .jp-InputPrompt {
font-size: var(--jp-content-font-size1);
}
/*
Align collapseHeadingButton with cell top header
The font sizes are identical to the ones in packages/rendermime/style/base.css
*/
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
font-size: var(--jp-content-font-size5);
background-position-y: calc(0.3 * var(--jp-content-font-size5));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
font-size: var(--jp-content-font-size4);
background-position-y: calc(0.3 * var(--jp-content-font-size4));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
font-size: var(--jp-content-font-size3);
background-position-y: calc(0.3 * var(--jp-content-font-size3));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
font-size: var(--jp-content-font-size2);
background-position-y: calc(0.3 * var(--jp-content-font-size2));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
font-size: var(--jp-content-font-size1);
background-position-y: top;
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
font-size: var(--jp-content-font-size0);
background-position-y: top;
}
/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
display: none;
}
.jp-Notebook.jp-mod-showHiddenCellsButton
:is(.jp-MarkdownCell:hover, .jp-mod-active)
.jp-collapseHeadingButton {
display: flex;
}
/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
margin-top: var(--jp-code-padding);
border: 1px solid var(--jp-border-color2);
background-color: var(--jp-border-color3) !important;
color: var(--jp-content-font-color0) !important;
display: flex;
}
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
background-color: var(--jp-border-color2) !important;
}
.jp-showHiddenCellsButton {
display: none;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Using block instead of flex to allow the use of the break-inside CSS property for
cell outputs.
*/
@media print {
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: block;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-notebook-toolbar-padding: 2px 5px 2px 2px;
}
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-NotebookPanel-toolbar {
padding: var(--jp-notebook-toolbar-padding);
/* disable paint containment from lumino 2.0 default strict CSS containment */
contain: style size !important;
}
.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
border: none;
box-shadow: none;
}
.jp-Notebook-toolbarCellTypeDropdown select {
height: 24px;
font-size: var(--jp-ui-font-size1);
line-height: 14px;
border-radius: 0;
display: block;
}
.jp-Notebook-toolbarCellTypeDropdown span {
top: 5px !important;
}
.jp-Toolbar-responsive-popup {
position: absolute;
height: fit-content;
display: flex;
flex-direction: row;
flex-wrap: wrap;
justify-content: flex-end;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: var(--jp-notebook-toolbar-padding);
z-index: 1;
right: 0;
top: 0;
}
.jp-Toolbar > .jp-Toolbar-responsive-opener {
margin-left: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-Notebook-ExecutionIndicator {
position: relative;
display: inline-block;
height: 100%;
z-index: 9997;
}
.jp-Notebook-ExecutionIndicator-tooltip {
visibility: hidden;
height: auto;
width: max-content;
width: -moz-max-content;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color1);
text-align: justify;
border-radius: 6px;
padding: 0 5px;
position: fixed;
display: table;
}
.jp-Notebook-ExecutionIndicator-tooltip.up {
transform: translateX(-50%) translateY(-100%) translateY(-32px);
}
.jp-Notebook-ExecutionIndicator-tooltip.down {
transform: translateX(calc(-100% + 16px)) translateY(5px);
}
.jp-Notebook-ExecutionIndicator-tooltip.hidden {
display: none;
}
.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
visibility: visible;
}
.jp-Notebook-ExecutionIndicator span {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
color: var(--jp-ui-font-color1);
line-height: 24px;
display: block;
}
.jp-Notebook-ExecutionIndicator-progress-bar {
display: flex;
justify-content: center;
height: 100%;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*
* Execution indicator
*/
.jp-tocItem-content::after {
content: '';
/* Must be identical to form a circle */
width: 12px;
height: 12px;
background: none;
border: none;
position: absolute;
right: 0;
}
.jp-tocItem-content[data-running='0']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background: none;
}
.jp-tocItem-content[data-running='1']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background-color: var(--jp-inverse-layout-color3);
}
.jp-tocItem-content[data-running='0'],
.jp-tocItem-content[data-running='1'] {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Notebook-footer {
height: 27px;
margin-left: calc(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding)
);
width: calc(
100% -
(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding) + var(--jp-cell-padding)
)
);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
color: var(--jp-ui-font-color3);
margin-top: 6px;
background: none;
cursor: pointer;
}
.jp-Notebook-footer:focus {
border-color: var(--jp-cell-editor-active-border-color);
}
/* For devices that support hovering, hide footer until hover */
@media (hover: hover) {
.jp-Notebook-footer {
opacity: 0;
}
.jp-Notebook-footer:focus,
.jp-Notebook-footer:hover {
opacity: 1;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Imports
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-side-by-side-output-size: 1fr;
--jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
--jp-private-notebook-dragImage-width: 304px;
--jp-private-notebook-dragImage-height: 36px;
--jp-private-notebook-selected-color: var(--md-blue-400);
--jp-private-notebook-active-color: var(--md-green-400);
}
/*-----------------------------------------------------------------------------
| Notebook
|----------------------------------------------------------------------------*/
/* stylelint-disable selector-max-class */
.jp-NotebookPanel {
display: block;
height: 100%;
}
.jp-NotebookPanel.jp-Document {
min-width: 240px;
min-height: 120px;
}
.jp-Notebook {
padding: var(--jp-notebook-padding);
outline: none;
overflow: auto;
background: var(--jp-layout-color0);
}
.jp-Notebook.jp-mod-scrollPastEnd::after {
display: block;
content: '';
min-height: var(--jp-notebook-scroll-padding);
}
.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
contain: strict;
}
.jp-Notebook .jp-Cell {
overflow: visible;
}
.jp-Notebook .jp-Cell .jp-InputPrompt {
cursor: move;
}
/*-----------------------------------------------------------------------------
| Notebook state related styling
|
| The notebook and cells each have states, here are the possibilities:
|
| - Notebook
| - Command
| - Edit
| - Cell
| - None
| - Active (only one can be active)
| - Selected (the cells actions are applied to)
| - Multiselected (when multiple selected, the cursor)
| - No outputs
|----------------------------------------------------------------------------*/
/* Command or edit modes */
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
/* cell is active */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
background: var(--jp-brand-color1);
}
/* cell is dirty */
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
color: var(--jp-warn-color1);
}
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
color: var(--jp-warn-color1);
content: '•';
}
.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
background: var(--jp-warn-color1);
}
/* collapser is hovered */
.jp-Notebook .jp-Cell .jp-Collapser:hover {
box-shadow: var(--jp-elevation-z2);
background: var(--jp-brand-color1);
opacity: var(--jp-cell-collapser-not-active-hover-opacity);
}
/* cell is active and collapser is hovered */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
background: var(--jp-brand-color0);
opacity: 1;
}
/* Command mode */
.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
background: var(--jp-notebook-multiselected-color);
}
.jp-Notebook.jp-mod-commandMode
.jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
background: transparent;
}
/* Edit mode */
.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-cell-editor-active-background);
}
/*-----------------------------------------------------------------------------
| Notebook drag and drop
|----------------------------------------------------------------------------*/
.jp-Notebook-cell.jp-mod-dropSource {
opacity: 0.5;
}
.jp-Notebook-cell.jp-mod-dropTarget,
.jp-Notebook.jp-mod-commandMode
.jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
border-top-color: var(--jp-private-notebook-selected-color);
border-top-style: solid;
border-top-width: 2px;
}
.jp-dragImage {
display: block;
flex-direction: row;
width: var(--jp-private-notebook-dragImage-width);
height: var(--jp-private-notebook-dragImage-height);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
overflow: visible;
}
.jp-dragImage-singlePrompt {
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
.jp-dragImage .jp-dragImage-content {
flex: 1 1 auto;
z-index: 2;
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
line-height: var(--jp-code-line-height);
padding: var(--jp-code-padding);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background-color);
color: var(--jp-content-font-color3);
text-align: left;
margin: 4px 4px 4px 0;
}
.jp-dragImage .jp-dragImage-prompt {
flex: 0 0 auto;
min-width: 36px;
color: var(--jp-cell-inprompt-font-color);
padding: var(--jp-code-padding);
padding-left: 12px;
font-family: var(--jp-cell-prompt-font-family);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: 1.9;
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
}
.jp-dragImage-multipleBack {
z-index: -1;
position: absolute;
height: 32px;
width: 300px;
top: 8px;
left: 8px;
background: var(--jp-layout-color2);
border: var(--jp-border-width) solid var(--jp-input-border-color);
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
/*-----------------------------------------------------------------------------
| Cell toolbar
|----------------------------------------------------------------------------*/
.jp-NotebookTools {
display: block;
min-width: var(--jp-sidebar-min-width);
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
overflow: auto;
}
.jp-ActiveCellTool {
padding: 12px 0;
display: flex;
}
.jp-ActiveCellTool-Content {
flex: 1 1 auto;
}
.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
background: var(--jp-cell-editor-background);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
min-height: 29px;
}
.jp-ActiveCellTool .jp-InputPrompt {
min-width: calc(var(--jp-cell-prompt-width) * 0.75);
}
.jp-ActiveCellTool-CellContent > pre {
padding: 5px 4px;
margin: 0;
white-space: normal;
}
.jp-MetadataEditorTool {
flex-direction: column;
padding: 12px 0;
}
.jp-RankedPanel > :not(:first-child) {
margin-top: 12px;
}
.jp-KeySelector select.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: var(--jp-border-width) solid var(--jp-border-color1);
}
.jp-KeySelector label,
.jp-MetadataEditorTool label,
.jp-NumberSetter label {
line-height: 1.4;
}
.jp-NotebookTools .jp-select-wrapper {
margin-top: 4px;
margin-bottom: 0;
}
.jp-NumberSetter input {
width: 100%;
margin-top: 4px;
}
.jp-NotebookTools .jp-Collapse {
margin-top: 16px;
}
/*-----------------------------------------------------------------------------
| Presentation Mode (.jp-mod-presentationMode)
|----------------------------------------------------------------------------*/
.jp-mod-presentationMode .jp-Notebook {
--jp-content-font-size1: var(--jp-content-presentation-font-size1);
--jp-code-font-size: var(--jp-code-presentation-font-size);
}
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
flex: 0 0 110px;
}
/*-----------------------------------------------------------------------------
| Side-by-side Mode (.jp-mod-sideBySide)
|----------------------------------------------------------------------------*/
.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
margin-top: 3em;
margin-bottom: 3em;
margin-left: 5%;
margin-right: 5%;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
display: grid;
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-output-size)
);
grid-template-rows: auto minmax(0, 1fr) auto;
grid-template-areas:
'header header header'
'input handle output'
'footer footer footer';
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-resized-cell)
);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
grid-area: header;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
grid-area: input;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
/* overwrite the default margin (no vertical separation needed in side by side move */
margin-top: 0;
grid-area: output;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
grid-area: footer;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
grid-area: handle;
user-select: none;
display: block;
height: 100%;
cursor: ew-resize;
padding: 0 var(--jp-cell-padding);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
content: '';
display: block;
background: var(--jp-border-color2);
height: 100%;
width: 5px;
}
.jp-mod-sideBySide.jp-Notebook
.jp-CodeCell.jp-mod-resizedCell
.jp-CellResizeHandle::after {
background: var(--jp-border-color0);
}
.jp-CellResizeHandle {
display: none;
}
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Cell-Placeholder {
padding-left: 55px;
}
.jp-Cell-Placeholder-wrapper {
background: #fff;
border: 1px solid;
border-color: #e5e6e9 #dfe0e4 #d0d1d5;
border-radius: 4px;
-webkit-border-radius: 4px;
margin: 10px 15px;
}
.jp-Cell-Placeholder-wrapper-inner {
padding: 15px;
position: relative;
}
.jp-Cell-Placeholder-wrapper-body {
background-repeat: repeat;
background-size: 50% auto;
}
.jp-Cell-Placeholder-wrapper-body div {
background: #f6f7f8;
background-image: -webkit-linear-gradient(
left,
#f6f7f8 0%,
#edeef1 20%,
#f6f7f8 40%,
#f6f7f8 100%
);
background-repeat: no-repeat;
background-size: 800px 104px;
height: 104px;
position: absolute;
right: 15px;
left: 15px;
top: 15px;
}
div.jp-Cell-Placeholder-h1 {
top: 20px;
height: 20px;
left: 15px;
width: 150px;
}
div.jp-Cell-Placeholder-h2 {
left: 15px;
top: 50px;
height: 10px;
width: 100px;
}
div.jp-Cell-Placeholder-content-1,
div.jp-Cell-Placeholder-content-2,
div.jp-Cell-Placeholder-content-3 {
left: 15px;
right: 15px;
height: 10px;
}
div.jp-Cell-Placeholder-content-1 {
top: 100px;
}
div.jp-Cell-Placeholder-content-2 {
top: 120px;
}
div.jp-Cell-Placeholder-content-3 {
top: 140px;
}
</style>
<style type="text/css">
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.
Many variables appear in an ordered sequence (0,1,2,3). These sequences
are designed to work well together, so for example, `--jp-border-color1` should
be used with `--jp-layout-color1`. The numbers have the following meanings:
* 0: super-primary, reserved for special emphasis
* 1: primary, most important under normal situations
* 2: secondary, next most important under normal situations
* 3: tertiary, next most important under normal situations
Throughout JupyterLab, we are mostly following principles from Google's
Material Design when selecting colors. We are not, however, following
all of MD as it is not optimized for dense, information rich UIs.
*/
:root {
/* Elevation
*
* We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
*
* https://github.com/material-components/material-components-web
* https://material-components-web.appspot.com/elevation.html
*/
--jp-shadow-base-lightness: 0;
--jp-shadow-umbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.2
);
--jp-shadow-penumbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.14
);
--jp-shadow-ambient-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.12
);
--jp-elevation-z0: none;
--jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
0 1px 1px 0 var(--jp-shadow-penumbra-color),
0 1px 3px 0 var(--jp-shadow-ambient-color);
--jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
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<h1 id="Tutorial:-Chemical-Properties-Prediction-with-Graph-Neural-Networks">Tutorial: Chemical Properties Prediction with Graph Neural Networks<a class="anchor-link" href="#Tutorial:-Chemical-Properties-Prediction-with-Graph-Neural-Networks"></a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial15/tutorial.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p>
<p>In this tutorial we will use <strong>Graph Neural Networks</strong> (GNNs) for chemical properties prediction. Chemical properties prediction involves estimating or determining the physical, chemical, or biological characteristics of molecules based on their structure.</p>
<p>Molecules can naturally be represented as graphs, where atoms serve as the nodes and chemical bonds as the edges connecting them. This graph-based structure makes GNNs a great fit for predicting chemical properties.</p>
<p>In the tutorial we will use the <a href="https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_geometric.datasets.QM9.html#torch_geometric.datasets.QM9">QM9 dataset</a> from Pytorch Geometric. The dataset contains small molecules, each consisting of up to 29 atoms, with every atom having a corresponding 3D position. Each atom is also represented by a five-dimensional one-hot encoded vector that indicates the atom type (H, C, N, O, F).</p>
<p>First of all, let's start by importing useful modules!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab[tutorial]"</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina</span><span class="w"> </span><span class="kn">import</span> <span class="n">Trainer</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.solver</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedSolver</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.problem.zoo</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedProblem</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">torch_geometric.datasets</span><span class="w"> </span><span class="kn">import</span> <span class="n">QM9</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">torch_geometric.nn</span><span class="w"> </span><span class="kn">import</span> <span class="n">GCNConv</span><span class="p">,</span> <span class="n">global_mean_pool</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
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<h2 id="Download-Data-and-create-the-Problem">Download Data and create the Problem<a class="anchor-link" href="#Download-Data-and-create-the-Problem"></a></h2>
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<p>We download the dataset and save the molecules as a list of <code>Data</code> objects (<code>input_</code>), where each element contains one molecule encoded in a graph structure. The corresponding target properties (<code>target_</code>) are listed below:</p>
<table>
<thead>
<tr>
<th>Target</th>
<th>Property</th>
<th>Description</th>
<th>Unit</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>$\mu$</td>
<td>Dipole moment</td>
<td>$D$</td>
</tr>
<tr>
<td>1</td>
<td>$\alpha$</td>
<td>Isotropic polarizability</td>
<td>$a₀³$</td>
</tr>
<tr>
<td>2</td>
<td>$\epsilon_{\textrm{HOMO}}$</td>
<td>Highest occupied molecular orbital energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>3</td>
<td>$\epsilon_{\textrm{LUMO}}$</td>
<td>Lowest unoccupied molecular orbital energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>4</td>
<td>$\Delta \epsilon$</td>
<td>Gap between $\epsilon_{\textrm{HOMO}}$ and $\epsilon_{\textrm{LUMO}}$</td>
<td>$eV$</td>
</tr>
<tr>
<td>5</td>
<td>$\langle R^2 \rangle$</td>
<td>Electronic spatial extent</td>
<td>$a₀²$</td>
</tr>
<tr>
<td>6</td>
<td>$\textrm{ZPVE}$</td>
<td>Zero point vibrational energy</td>
<td>$eV$</td>
</tr>
<tr>
<td>7</td>
<td>$U_0$</td>
<td>Internal energy at 0K</td>
<td>$eV$</td>
</tr>
<tr>
<td>8</td>
<td>$U$</td>
<td>Internal energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>9</td>
<td>$H$</td>
<td>Enthalpy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>10</td>
<td>$G$</td>
<td>Free energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>11</td>
<td>$c_{\textrm{v}}$</td>
<td>Heat capacity at 298.15K</td>
<td>$cal/(mol·K)$</td>
</tr>
<tr>
<td>12</td>
<td>$U_0^{\textrm{ATOM}}$</td>
<td>Atomization energy at 0K</td>
<td>$eV$</td>
</tr>
<tr>
<td>13</td>
<td>$U^{\textrm{ATOM}}$</td>
<td>Atomization energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>14</td>
<td>$H^{\textrm{ATOM}}$</td>
<td>Atomization enthalpy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>15</td>
<td>$G^{\textrm{ATOM}}$</td>
<td>Atomization free energy at 298.15K</td>
<td>$eV$</td>
</tr>
<tr>
<td>16</td>
<td>$A$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
<tr>
<td>17</td>
<td>$B$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
<tr>
<td>18</td>
<td>$C$</td>
<td>Rotational constant</td>
<td>$GHz$</td>
</tr>
</tbody>
</table>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># download the data + shuffling</span>
<span class="n">dataset</span> <span class="o">=</span> <span class="n">QM9</span><span class="p">(</span><span class="n">root</span><span class="o">=</span><span class="s2">"./tutorial_logs"</span><span class="p">)</span><span class="o">.</span><span class="n">shuffle</span><span class="p">()</span>
<span class="c1"># save the dataset</span>
<span class="n">input_</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span> <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">dataset</span><span class="p">]</span>
<span class="n">target_</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">([</span><span class="n">data</span><span class="o">.</span><span class="n">y</span> <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">dataset</span><span class="p">])</span>
<span class="c1"># normalize the target</span>
<span class="n">mean</span> <span class="o">=</span> <span class="n">target_</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">std</span> <span class="o">=</span> <span class="n">target_</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">target_</span> <span class="o">=</span> <span class="p">(</span><span class="n">target_</span> <span class="o">-</span> <span class="n">mean</span><span class="p">)</span> <span class="o">/</span> <span class="n">std</span>
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<pre>Downloading https://data.pyg.org/datasets/qm9_v3.zip
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<pre>Extracting tutorial_logs/raw/qm9_v3.zip
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<pre>Processing...
Using a pre-processed version of the dataset. Please install 'rdkit' to alternatively process the raw data.
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<pre>Done!
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<p>Great! Once the data are downloaded, building the problem is straightforward by using the <a href="https://mathlab.github.io/PINA/_rst/problem/zoo/supervised_problem.html"><code>SupervisedProblem</code></a> class.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># build the problem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">SupervisedProblem</span><span class="p">(</span><span class="n">input_</span><span class="o">=</span><span class="n">input_</span><span class="p">,</span> <span class="n">output_</span><span class="o">=</span><span class="n">target_</span><span class="p">)</span>
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<h2 id="Build-the-Model">Build the Model<a class="anchor-link" href="#Build-the-Model"></a></h2><p>To predict molecular properties, we will construct a simple Convolutional Graph Neural Network using the <a href=""><code>GCNConv</code></a> module from PyG. While this tutorial focuses on a straightforward model, more advanced architectures—such as Equivariant Networks—could potentially yield better performance. Please note that this tutorial serves only for demonstration purposes.</p>
<p><strong>Importantly</strong> notice that in the <code>forward</code> pass we pass a data object as input, and unpack inside the graph attributes. This is the only requirement in <strong>PINA</strong> to use graphs and solvers together.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="k">class</span><span class="w"> </span><span class="nc">GNN</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_features</span><span class="p">,</span> <span class="n">out_features</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="o">=</span><span class="mi">256</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">GNN</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">GCNConv</span><span class="p">(</span><span class="n">in_features</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">GCNConv</span><span class="p">(</span><span class="n">hidden_dim</span><span class="p">,</span> <span class="n">hidden_dim</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">hidden_dim</span><span class="p">,</span> <span class="n">out_features</span><span class="p">)</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="c1"># extract attributes, N.B. in PINA Data object are passed as input</span>
<span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">,</span> <span class="n">batch</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">edge_index</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">batch</span>
<span class="c1"># perform normal graph operations</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">))</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_index</span><span class="p">))</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">global_mean_pool</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">batch</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
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<h2 id="Train-the-Model">Train the Model<a class="anchor-link" href="#Train-the-Model"></a></h2><p>Now that the problem is created and the model is built, we can train the model using the <a href="https://mathlab.github.io/PINA/_rst/solver/supervised.html"><code>SupervisedSolver</code></a>, which is the solver for standard supervised learning task. We will optimize the Maximum Absolute Error and test on the same metric. In the <a href="https://mathlab.github.io/PINA/_rst/trainer.html"><code>Trainer</code></a> class we specify the optimization hyperparameters.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># define the solver</span>
<span class="n">solver</span> <span class="o">=</span> <span class="n">SupervisedSolver</span><span class="p">(</span>
<span class="n">problem</span><span class="o">=</span><span class="n">problem</span><span class="p">,</span>
<span class="n">model</span><span class="o">=</span><span class="n">GNN</span><span class="p">(</span><span class="n">in_features</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> <span class="n">out_features</span><span class="o">=</span><span class="mi">19</span><span class="p">),</span>
<span class="n">use_lt</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="n">loss</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">L1Loss</span><span class="p">(),</span>
<span class="p">)</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="p">,</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.7</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">512</span><span class="p">,</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=3` reached.
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<h2 id="Testing-Chemical-Predictions">Testing Chemical Predictions<a class="anchor-link" href="#Testing-Chemical-Predictions"></a></h2>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">trainer</span><span class="o">.</span><span class="n">test</span><span class="p">()</span>
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<pre>────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Test metric DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
test_loss_epoch 0.4035990834236145
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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<p>We observe that the model achieves an average error of approximately 0.4 MAE across all property predictions. This error is an average, but we can also inspect the error for each individual property prediction.</p>
<p>To do this, we need access to the test dataset, which can be retrieved from the trainer's datamodule. Each datamodule contains both the dataloader and dataset objects. For the dataset, we can use the <a href="https://mathlab.github.io/PINA/_rst/data/dataset.html#pina.data.dataset.PinaDataset.get_all_data"><code>get_all_data()</code></a> method. This function returns the entire dataset as a dictionary, where the keys represent the Condition names, and the values are dictionaries containing input and target tensors.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># get the test dataset</span>
<span class="n">test_dataset</span> <span class="o">=</span> <span class="n">trainer</span><span class="o">.</span><span class="n">datamodule</span><span class="o">.</span><span class="n">test_dataset</span><span class="o">.</span><span class="n">get_all_data</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Here the dataset"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Dataset keys: </span><span class="si">{</span><span class="n">test_dataset</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Dataset keys for data condition: </span><span class="si">{</span><span class="n">test_dataset</span><span class="p">[</span><span class="s1">'data'</span><span class="p">]</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">"Dataset values type for data condition: </span><span class="si">{</span><span class="p">[</span><span class="n">v</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">v</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">test_dataset</span><span class="p">[</span><span class="s1">'data'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">()]</span><span class="si">}</span><span class="s2">"</span>
<span class="p">)</span>
<span class="c1"># extract input and target for test dataset</span>
<span class="n">input_test</span> <span class="o">=</span> <span class="n">test_dataset</span><span class="p">[</span><span class="s2">"data"</span><span class="p">][</span><span class="s2">"input"</span><span class="p">]</span>
<span class="n">target_test</span> <span class="o">=</span> <span class="n">test_dataset</span><span class="p">[</span><span class="s2">"data"</span><span class="p">][</span><span class="s2">"target"</span><span class="p">]</span>
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<pre>Here the dataset
Dataset keys: dict_keys(['data'])
Dataset keys for data condition: dict_keys(['input', 'target'])
Dataset values type for data condition: ['DataLabelBatch', 'Tensor']
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<p>Now we obtain the prediction my calling the forward pass for the <code>SupervisedSolver</code>.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1"># get the prediction</span>
<span class="n">prediction_test</span> <span class="o">=</span> <span class="n">solver</span><span class="p">(</span><span class="n">input_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of prediction properties: </span><span class="si">{</span><span class="n">prediction_test</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Number of prediction properties: 19
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<p>As you can see we obtain a tensor with 19 prediction properties as output, which is what we are looking for. Now let's compute the error for each property:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">properties</span> <span class="o">=</span> <span class="p">[</span>
<span class="s2">"μ"</span><span class="p">,</span>
<span class="s2">"α"</span><span class="p">,</span>
<span class="s2">"ε HOMO"</span><span class="p">,</span>
<span class="s2">"ε LUMO"</span><span class="p">,</span>
<span class="s2">"Δε"</span><span class="p">,</span>
<span class="s2">"⟨R²⟩"</span><span class="p">,</span>
<span class="s2">"ZPVE"</span><span class="p">,</span>
<span class="s2">"U₀"</span><span class="p">,</span>
<span class="s2">"U"</span><span class="p">,</span>
<span class="s2">"H"</span><span class="p">,</span>
<span class="s2">"G"</span><span class="p">,</span>
<span class="s2">"cv"</span><span class="p">,</span>
<span class="s2">"U₀ ATOM"</span><span class="p">,</span>
<span class="s2">"U ATOM"</span><span class="p">,</span>
<span class="s2">"H ATOM"</span><span class="p">,</span>
<span class="s2">"G ATOM"</span><span class="p">,</span>
<span class="s2">"A"</span><span class="p">,</span>
<span class="s2">"B"</span><span class="p">,</span>
<span class="s2">"C"</span><span class="p">,</span>
<span class="p">]</span>
<span class="n">units</span> <span class="o">=</span> <span class="p">[</span>
<span class="s2">"D"</span><span class="p">,</span>
<span class="s2">"a₀³"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"a₀²"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"cal/(mol·K)"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"eV"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="s2">"GHz"</span><span class="p">,</span>
<span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="s1">'Property'</span><span class="si">:</span><span class="s2">&lt;10</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="s1">'Error'</span><span class="si">:</span><span class="s2">&lt;8</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="s1">'Unit'</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"-"</span> <span class="o">*</span> <span class="mi">34</span><span class="p">)</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">19</span><span class="p">):</span>
<span class="n">error</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">prediction_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span> <span class="o">-</span> <span class="n">target_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">])</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">properties</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">&lt;10</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">error</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">units</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
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<pre>Property | Error | Unit
----------------------------------
μ | 0.6903 | D
α | 0.4514 | a₀³
ε HOMO | 0.6874 | eV
ε LUMO | 0.6221 | eV
Δε | 0.6680 | eV
⟨R²⟩ | 0.6613 | a₀²
ZPVE | 0.2487 | eV
U₀ | 0.3803 | eV
U | 0.3811 | eV
H | 0.3786 | eV
G | 0.3813 | eV
cv | 0.5490 | cal/(mol·K)
U₀ ATOM | 0.2847 | eV
U ATOM | 0.2835 | eV
H ATOM | 0.2831 | eV
G ATOM | 0.2879 | eV
A | 0.0018 | GHz
B | 0.2134 | GHz
C | 0.2142 | GHz
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<p>We can see that predicting the some properties are easier and some harder to predict. For example, the rotational constant $A$ is way easier to predict than dipole moment $\mu$. To have a better idea we can also plot a scatter plot between predicted and observed properties:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="c1"># Set up the plot grid</span>
<span class="n">num_properties</span> <span class="o">=</span> <span class="mi">19</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">8</span><span class="p">))</span>
<span class="n">axes</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span>
<span class="c1"># Outlier removal using IQR (with torch)</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_properties</span><span class="p">):</span>
<span class="n">target_vals</span> <span class="o">=</span> <span class="n">target_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span>
<span class="n">pred_vals</span> <span class="o">=</span> <span class="n">prediction_test</span><span class="p">[:,</span> <span class="n">idx</span><span class="p">]</span>
<span class="c1"># Calculate Q1 (25th percentile) and Q3 (75th percentile) using torch</span>
<span class="n">Q1</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">target_vals</span><span class="p">,</span> <span class="mf">0.25</span><span class="p">)</span>
<span class="n">Q3</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">target_vals</span><span class="p">,</span> <span class="mf">0.75</span><span class="p">)</span>
<span class="n">IQR</span> <span class="o">=</span> <span class="n">Q3</span> <span class="o">-</span> <span class="n">Q1</span>
<span class="c1"># Define the outlier range</span>
<span class="n">lower_bound</span> <span class="o">=</span> <span class="n">Q1</span> <span class="o">-</span> <span class="mf">1.5</span> <span class="o">*</span> <span class="n">IQR</span>
<span class="n">upper_bound</span> <span class="o">=</span> <span class="n">Q3</span> <span class="o">+</span> <span class="mf">1.5</span> <span class="o">*</span> <span class="n">IQR</span>
<span class="c1"># Filter out the outliers</span>
<span class="n">mask</span> <span class="o">=</span> <span class="p">(</span><span class="n">target_vals</span> <span class="o">&gt;=</span> <span class="n">lower_bound</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">target_vals</span> <span class="o">&lt;=</span> <span class="n">upper_bound</span><span class="p">)</span>
<span class="n">filtered_target</span> <span class="o">=</span> <span class="n">target_vals</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span>
<span class="n">filtered_pred</span> <span class="o">=</span> <span class="n">pred_vals</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span>
<span class="c1"># Plotting</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
<span class="n">ax</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span>
<span class="n">filtered_target</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">filtered_pred</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="s2">"Data points (no outliers)"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span>
<span class="p">[</span><span class="n">filtered_target</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">filtered_target</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()],</span>
<span class="p">[</span><span class="n">filtered_target</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">filtered_target</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()],</span>
<span class="s2">"r--"</span><span class="p">,</span>
<span class="n">label</span><span class="o">=</span><span class="s2">"y=x"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">properties</span><span class="p">[</span><span class="n">idx</span><span class="p">])</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Target"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Prediction"</span><span class="p">)</span>
<span class="c1"># Remove the extra subplot (since there are 19 properties, not 20)</span>
<span class="k">if</span> <span class="n">num_properties</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">axes</span><span class="p">):</span>
<span class="n">fig</span><span class="o">.</span><span class="n">delaxes</span><span class="p">(</span><span class="n">axes</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
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<p>By looking more into details, we can see that $A$ is not predicted that well, but the small values of the quantity lead to a lower MAE than the other properties. From the plot we can see that the atomatization energies, free energy and enthalpy are the predicted properties with higher correlation with the true chemical properties.</p>
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<h2 id="What's-Next?">What's Next?<a class="anchor-link" href="#What's-Next?"></a></h2><p>Congratulations on completing the tutorial on chemical properties prediction with <strong>PINA</strong>! Now that you've got the basics, there are several exciting directions to explore:</p>
<ol>
<li><p><strong>Train the network for longer or with different layer sizes</strong>: Experiment with various configurations to see how the network's accuracy improves.</p>
</li>
<li><p><strong>Use a different network</strong>: For example, Equivariant Graph Neural Networks (EGNNs) have shown great results on molecular tasks by leveraging group symmetries. If you're interested, check out <a href="https://arxiv.org/abs/2102.09844"><em>E(n) Equivariant Graph Neural Networks</em></a> for more details.</p>
</li>
<li><p><strong>What if the input is time-dependent?</strong>: For example, predicting force fields in Molecular Dynamics simulations. In PINA, you can predict force fields with ease, as it's still a supervised learning task. If this interests you, have a look at <a href="https://pubs.acs.org/doi/10.1021/acs.chemrev.0c01111"><em>Machine Learning Force Fields</em></a>.</p>
</li>
<li><p><strong>...and many more!</strong>: The possibilities are vast, including exploring new architectures, working with larger datasets, and applying this framework to more complex systems.</p>
</li>
</ol>
<p>For more resources and tutorials, check out the <a href="https://mathlab.github.io/PINA/">PINA Documentation</a>.</p>
</div>
</div>
</div>
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