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Post-crash recovery analysis report (#355)
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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head><meta charset="utf-8"/> | |
| <meta content="width=device-width, initial-scale=1.0" name="viewport"/> | |
| <title>crash_recovery</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> | |
| <style type="text/css"> | |
| pre { line-height: 125%; } | |
| td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } | |
| span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } | |
| td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } | |
| span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } | |
| .highlight .hll { background-color: var(--jp-cell-editor-active-background) } | |
| .highlight { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } | |
| .highlight .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ | |
| .highlight .err { color: var(--jp-mirror-editor-error-color) } /* Error */ | |
| .highlight .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ | |
| .highlight .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ | |
| .highlight .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ | |
| .highlight .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ | |
| .highlight .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ | |
| .highlight .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ | |
| .highlight .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ | |
| .highlight .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ | |
| .highlight .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ | |
| .highlight .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ | |
| .highlight .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ | |
| .highlight .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ | |
| .highlight .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ | |
| .highlight .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ | |
| .highlight .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ | |
| .highlight .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ | |
| .highlight .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ | |
| .highlight .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ | |
| .highlight .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */ | |
| .highlight .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ | |
| .highlight .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ | |
| .highlight .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ | |
| .highlight .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ | |
| .highlight .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ | |
| .highlight .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ | |
| .highlight .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ | |
| .highlight .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ | |
| .highlight .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ | |
| .highlight .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ | |
| .highlight .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ | |
| .highlight .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ | |
| .highlight .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ | |
| .highlight .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ | |
| .highlight .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ | |
| .highlight .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ | |
| .highlight .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ | |
| .highlight .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ | |
| .highlight .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ | |
| .highlight .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ | |
| </style> | |
| <style type="text/css"> | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /* | |
| * Mozilla scrollbar styling | |
| */ | |
| /* use standard opaque scrollbars for most nodes */ | |
| [data-jp-theme-scrollbars='true'] { | |
| scrollbar-color: rgb(var(--jp-scrollbar-thumb-color)) | |
| var(--jp-scrollbar-background-color); | |
| } | |
| /* for code nodes, use a transparent style of scrollbar. These selectors | |
| * will match lower in the tree, and so will override the above */ | |
| [data-jp-theme-scrollbars='true'] .CodeMirror-hscrollbar, | |
| [data-jp-theme-scrollbars='true'] .CodeMirror-vscrollbar { | |
| scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent; | |
| } | |
| /* tiny scrollbar */ | |
| .jp-scrollbar-tiny { | |
| scrollbar-color: rgba(var(--jp-scrollbar-thumb-color), 0.5) transparent; | |
| scrollbar-width: thin; | |
| } | |
| /* tiny scrollbar */ | |
| .jp-scrollbar-tiny::-webkit-scrollbar, | |
| .jp-scrollbar-tiny::-webkit-scrollbar-corner { | |
| background-color: transparent; | |
| height: 4px; | |
| width: 4px; | |
| } | |
| .jp-scrollbar-tiny::-webkit-scrollbar-thumb { | |
| background: rgba(var(--jp-scrollbar-thumb-color), 0.5); | |
| } | |
| .jp-scrollbar-tiny::-webkit-scrollbar-track:horizontal { | |
| border-left: 0 solid transparent; | |
| border-right: 0 solid transparent; | |
| } | |
| .jp-scrollbar-tiny::-webkit-scrollbar-track:vertical { | |
| border-top: 0 solid transparent; | |
| border-bottom: 0 solid transparent; | |
| } | |
| /* | |
| * Lumino | |
| */ | |
| .lm-ScrollBar[data-orientation='horizontal'] { | |
| min-height: 16px; | |
| max-height: 16px; | |
| min-width: 45px; | |
| border-top: 1px solid #a0a0a0; | |
| } | |
| .lm-ScrollBar[data-orientation='vertical'] { | |
| min-width: 16px; | |
| max-width: 16px; | |
| min-height: 45px; | |
| border-left: 1px solid #a0a0a0; | |
| } | |
| .lm-ScrollBar-button { | |
| background-color: #f0f0f0; | |
| background-position: center center; | |
| min-height: 15px; | |
| max-height: 15px; | |
| min-width: 15px; | |
| max-width: 15px; | |
| } | |
| .lm-ScrollBar-button:hover { | |
| background-color: #dadada; | |
| } | |
| .lm-ScrollBar-button.lm-mod-active { | |
| background-color: #cdcdcd; | |
| } | |
| .lm-ScrollBar-track { | |
| background: #f0f0f0; | |
| } | |
| .lm-ScrollBar-thumb { | |
| background: #cdcdcd; | |
| } | |
| .lm-ScrollBar-thumb:hover { | |
| background: #bababa; | |
| } | |
| .lm-ScrollBar-thumb.lm-mod-active { | |
| background: #a0a0a0; | |
| } | |
| .lm-ScrollBar[data-orientation='horizontal'] .lm-ScrollBar-thumb { | |
| height: 100%; | |
| min-width: 15px; | |
| border-left: 1px solid #a0a0a0; | |
| border-right: 1px solid #a0a0a0; | |
| } | |
| .lm-ScrollBar[data-orientation='vertical'] .lm-ScrollBar-thumb { | |
| width: 100%; | |
| min-height: 15px; | |
| border-top: 1px solid #a0a0a0; | |
| border-bottom: 1px solid #a0a0a0; | |
| } | |
| .lm-ScrollBar[data-orientation='horizontal'] | |
| .lm-ScrollBar-button[data-action='decrement'] { | |
| background-image: var(--jp-icon-caret-left); | |
| background-size: 17px; | |
| } | |
| .lm-ScrollBar[data-orientation='horizontal'] | |
| .lm-ScrollBar-button[data-action='increment'] { | |
| background-image: var(--jp-icon-caret-right); | |
| background-size: 17px; | |
| } | |
| .lm-ScrollBar[data-orientation='vertical'] | |
| .lm-ScrollBar-button[data-action='decrement'] { | |
| background-image: var(--jp-icon-caret-up); | |
| background-size: 17px; | |
| } | |
| .lm-ScrollBar[data-orientation='vertical'] | |
| .lm-ScrollBar-button[data-action='increment'] { | |
| background-image: var(--jp-icon-caret-down); | |
| background-size: 17px; | |
| } | |
| /* | |
| * 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-Widget { | |
| box-sizing: border-box; | |
| position: relative; | |
| overflow: hidden; | |
| } | |
| .lm-Widget.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .lm-AccordionPanel[data-orientation='horizontal'] > .lm-AccordionPanel-title { | |
| /* Title is rotated for horizontal accordion panel using CSS */ | |
| display: block; | |
| transform-origin: top left; | |
| transform: rotate(-90deg) translate(-100%); | |
| } | |
| /* | |
| * 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-CommandPalette { | |
| display: flex; | |
| flex-direction: column; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .lm-CommandPalette-search { | |
| flex: 0 0 auto; | |
| } | |
| .lm-CommandPalette-content { | |
| flex: 1 1 auto; | |
| margin: 0; | |
| padding: 0; | |
| min-height: 0; | |
| overflow: auto; | |
| list-style-type: none; | |
| } | |
| .lm-CommandPalette-header { | |
| overflow: hidden; | |
| white-space: nowrap; | |
| text-overflow: ellipsis; | |
| } | |
| .lm-CommandPalette-item { | |
| display: flex; | |
| flex-direction: row; | |
| } | |
| .lm-CommandPalette-itemIcon { | |
| flex: 0 0 auto; | |
| } | |
| .lm-CommandPalette-itemContent { | |
| flex: 1 1 auto; | |
| overflow: hidden; | |
| } | |
| .lm-CommandPalette-itemShortcut { | |
| flex: 0 0 auto; | |
| } | |
| .lm-CommandPalette-itemLabel { | |
| overflow: hidden; | |
| white-space: nowrap; | |
| text-overflow: ellipsis; | |
| } | |
| .lm-close-icon { | |
| border: 1px solid transparent; | |
| background-color: transparent; | |
| position: absolute; | |
| z-index: 1; | |
| right: 3%; | |
| top: 0; | |
| bottom: 0; | |
| margin: auto; | |
| padding: 7px 0; | |
| display: none; | |
| vertical-align: middle; | |
| outline: 0; | |
| cursor: pointer; | |
| } | |
| .lm-close-icon:after { | |
| content: 'X'; | |
| display: block; | |
| width: 15px; | |
| height: 15px; | |
| text-align: center; | |
| color: #000; | |
| font-weight: normal; | |
| font-size: 12px; | |
| cursor: pointer; | |
| } | |
| /* | |
| * 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-DockPanel { | |
| z-index: 0; | |
| } | |
| .lm-DockPanel-widget { | |
| z-index: 0; | |
| } | |
| .lm-DockPanel-tabBar { | |
| z-index: 1; | |
| } | |
| .lm-DockPanel-handle { | |
| z-index: 2; | |
| } | |
| .lm-DockPanel-handle.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| .lm-DockPanel-handle:after { | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| width: 100%; | |
| height: 100%; | |
| content: ''; | |
| } | |
| .lm-DockPanel-handle[data-orientation='horizontal'] { | |
| cursor: ew-resize; | |
| } | |
| .lm-DockPanel-handle[data-orientation='vertical'] { | |
| cursor: ns-resize; | |
| } | |
| .lm-DockPanel-handle[data-orientation='horizontal']:after { | |
| left: 50%; | |
| min-width: 8px; | |
| transform: translateX(-50%); | |
| } | |
| .lm-DockPanel-handle[data-orientation='vertical']:after { | |
| top: 50%; | |
| min-height: 8px; | |
| transform: translateY(-50%); | |
| } | |
| .lm-DockPanel-overlay { | |
| z-index: 3; | |
| box-sizing: border-box; | |
| pointer-events: none; | |
| } | |
| .lm-DockPanel-overlay.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| /* | |
| * 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-Menu { | |
| z-index: 10000; | |
| position: absolute; | |
| white-space: nowrap; | |
| overflow-x: hidden; | |
| overflow-y: auto; | |
| outline: none; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .lm-Menu-content { | |
| margin: 0; | |
| padding: 0; | |
| display: table; | |
| list-style-type: none; | |
| } | |
| .lm-Menu-item { | |
| display: table-row; | |
| } | |
| .lm-Menu-item.lm-mod-hidden, | |
| .lm-Menu-item.lm-mod-collapsed { | |
| display: none !important; | |
| } | |
| .lm-Menu-itemIcon, | |
| .lm-Menu-itemSubmenuIcon { | |
| display: table-cell; | |
| text-align: center; | |
| } | |
| .lm-Menu-itemLabel { | |
| display: table-cell; | |
| text-align: left; | |
| } | |
| .lm-Menu-itemShortcut { | |
| display: table-cell; | |
| text-align: right; | |
| } | |
| /* | |
| * 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-MenuBar { | |
| outline: none; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .lm-MenuBar-content { | |
| margin: 0; | |
| padding: 0; | |
| display: flex; | |
| flex-direction: row; | |
| list-style-type: none; | |
| } | |
| .lm-MenuBar-item { | |
| box-sizing: border-box; | |
| } | |
| .lm-MenuBar-itemIcon, | |
| .lm-MenuBar-itemLabel { | |
| display: inline-block; | |
| } | |
| /* | |
| * 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-ScrollBar { | |
| display: flex; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .lm-ScrollBar[data-orientation='horizontal'] { | |
| flex-direction: row; | |
| } | |
| .lm-ScrollBar[data-orientation='vertical'] { | |
| flex-direction: column; | |
| } | |
| .lm-ScrollBar-button { | |
| box-sizing: border-box; | |
| flex: 0 0 auto; | |
| } | |
| .lm-ScrollBar-track { | |
| box-sizing: border-box; | |
| position: relative; | |
| overflow: hidden; | |
| flex: 1 1 auto; | |
| } | |
| .lm-ScrollBar-thumb { | |
| box-sizing: border-box; | |
| position: absolute; | |
| } | |
| /* | |
| * 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-SplitPanel-child { | |
| z-index: 0; | |
| } | |
| .lm-SplitPanel-handle { | |
| z-index: 1; | |
| } | |
| .lm-SplitPanel-handle.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| .lm-SplitPanel-handle:after { | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| width: 100%; | |
| height: 100%; | |
| content: ''; | |
| } | |
| .lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle { | |
| cursor: ew-resize; | |
| } | |
| .lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle { | |
| cursor: ns-resize; | |
| } | |
| .lm-SplitPanel[data-orientation='horizontal'] > .lm-SplitPanel-handle:after { | |
| left: 50%; | |
| min-width: 8px; | |
| transform: translateX(-50%); | |
| } | |
| .lm-SplitPanel[data-orientation='vertical'] > .lm-SplitPanel-handle:after { | |
| top: 50%; | |
| min-height: 8px; | |
| transform: translateY(-50%); | |
| } | |
| /* | |
| * 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-TabBar { | |
| display: flex; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .lm-TabBar[data-orientation='horizontal'] { | |
| flex-direction: row; | |
| align-items: flex-end; | |
| } | |
| .lm-TabBar[data-orientation='vertical'] { | |
| flex-direction: column; | |
| align-items: flex-end; | |
| } | |
| .lm-TabBar-content { | |
| margin: 0; | |
| padding: 0; | |
| display: flex; | |
| flex: 1 1 auto; | |
| list-style-type: none; | |
| } | |
| .lm-TabBar[data-orientation='horizontal'] > .lm-TabBar-content { | |
| flex-direction: row; | |
| } | |
| .lm-TabBar[data-orientation='vertical'] > .lm-TabBar-content { | |
| flex-direction: column; | |
| } | |
| .lm-TabBar-tab { | |
| display: flex; | |
| flex-direction: row; | |
| box-sizing: border-box; | |
| overflow: hidden; | |
| touch-action: none; /* Disable native Drag/Drop */ | |
| } | |
| .lm-TabBar-tabIcon, | |
| .lm-TabBar-tabCloseIcon { | |
| flex: 0 0 auto; | |
| } | |
| .lm-TabBar-tabLabel { | |
| flex: 1 1 auto; | |
| overflow: hidden; | |
| white-space: nowrap; | |
| } | |
| .lm-TabBar-tabInput { | |
| user-select: all; | |
| width: 100%; | |
| box-sizing: border-box; | |
| } | |
| .lm-TabBar-tab.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| .lm-TabBar-addButton.lm-mod-hidden { | |
| display: none !important; | |
| } | |
| .lm-TabBar.lm-mod-dragging .lm-TabBar-tab { | |
| position: relative; | |
| } | |
| .lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab { | |
| left: 0; | |
| transition: left 150ms ease; | |
| } | |
| .lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab { | |
| top: 0; | |
| transition: top 150ms ease; | |
| } | |
| .lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging { | |
| transition: none; | |
| } | |
| .lm-TabBar-tabLabel .lm-TabBar-tabInput { | |
| user-select: all; | |
| width: 100%; | |
| box-sizing: border-box; | |
| background: inherit; | |
| } | |
| /* | |
| * 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-TabPanel-tabBar { | |
| z-index: 1; | |
| } | |
| .lm-TabPanel-stackedPanel { | |
| z-index: 0; | |
| } | |
| /* | |
| * 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. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Collapse { | |
| display: flex; | |
| flex-direction: column; | |
| align-items: stretch; | |
| } | |
| .jp-Collapse-header { | |
| padding: 1px 12px; | |
| background-color: var(--jp-layout-color1); | |
| border-bottom: solid var(--jp-border-width) var(--jp-border-color2); | |
| color: var(--jp-ui-font-color1); | |
| cursor: pointer; | |
| display: flex; | |
| align-items: center; | |
| font-size: var(--jp-ui-font-size0); | |
| font-weight: 600; | |
| text-transform: uppercase; | |
| user-select: none; | |
| } | |
| .jp-Collapser-icon { | |
| height: 16px; | |
| } | |
| .jp-Collapse-header-collapsed .jp-Collapser-icon { | |
| transform: rotate(-90deg); | |
| margin: auto 0; | |
| } | |
| .jp-Collapser-title { | |
| line-height: 25px; | |
| } | |
| .jp-Collapse-contents { | |
| padding: 0 12px; | |
| background-color: var(--jp-layout-color1); | |
| color: var(--jp-ui-font-color1); | |
| overflow: auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /* This file was auto-generated by ensureUiComponents() in @jupyterlab/buildutils */ | |
| /** | |
| * (DEPRECATED) Support for consuming icons as CSS background images | |
| */ | |
| /* Icons urls */ | |
| :root { | |
| --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==); | |
| --jp-icon-caret-right: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik03LjIsNS4yTDEwLjksOWwtMy44LDMuOFY1LjJINy4yeiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-caret-up-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iMTUuNCwxMy4zIDkuOSw3LjcgNC40LDEzLjIgMy42LDEyLjUgOS45LDYuMyAxNi4xLDEyLjYgIi8+Cgk8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-caret-up: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik01LjIsMTAuNUw5LDYuOGwzLjgsMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-case-sensitive: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KICA8ZyBjbGFzcz0ianAtaWNvbjIiIGZpbGw9IiM0MTQxNDEiPgogICAgPHJlY3QgeD0iMiIgeT0iMiIgd2lkdGg9IjE2IiBoZWlnaHQ9IjE2Ii8+CiAgPC9nPgogIDxnIGNsYXNzPSJqcC1pY29uLWFjY2VudDIiIGZpbGw9IiNGRkYiPgogICAgPHBhdGggZD0iTTcuNiw4aDAuOWwzLjUsOGgtMS4xTDEwLDE0SDZsLTAuOSwySDRMNy42LDh6IE04LDkuMUw2LjQsMTNoMy4yTDgsOS4xeiIvPgogICAgPHBhdGggZD0iTTE2LjYsOS44Yy0wLjIsMC4xLTAuNCwwLjEtMC43LDAuMWMtMC4yLDAtMC40LTAuMS0wLjYtMC4yYy0wLjEtMC4xLTAuMi0wLjQtMC4yLTAuNyBjLTAuMywwLjMtMC42LDAuNS0wLjksMC43Yy0wLjMsMC4xLTAuNywwLjItMS4xLDAuMmMtMC4zLDAtMC41LDAtMC43LTAuMWMtMC4yLTAuMS0wLjQtMC4yLTAuNi0wLjNjLTAuMi0wLjEtMC4zLTAuMy0wLjQtMC41IGMtMC4xLTAuMi0wLjEtMC40LTAuMS0wLjdjMC0wLjMsMC4xLTAuNiwwLjItMC44YzAuMS0wLjIsMC4zLTAuNCwwLjQtMC41QzEyLDcsMTIuMiw2LjksMTIuNSw2LjhjMC4yLTAuMSwwLjUtMC4xLDAuNy0wLjIgYzAuMy0wLjEsMC41LTAuMSwwLjctMC4xYzAuMiwwLDAuNC0wLjEsMC42LTAuMWMwLjIsMCwwLjMtMC4xLDAuNC0wLjJjMC4xLTAuMSwwLjItMC4yLDAuMi0wLjRjMC0xLTEuMS0xLTEuMy0xIGMtMC40LDAtMS40LDAtMS40LDEuMmgtMC45YzAtMC40LDAuMS0wLjcsMC4yLTFjMC4xLTAuMiwwLjMtMC40LDAuNS0wLjZjMC4yLTAuMiwwLjUtMC4zLDAuOC0wLjNDMTMuMyw0LDEzLjYsNCwxMy45LDQgYzAuMywwLDAuNSwwLDAuOCwwLjFjMC4zLDAsMC41LDAuMSwwLjcsMC4yYzAuMiwwLjEsMC40LDAuMywwLjUsMC41QzE2LDUsMTYsNS4yLDE2LDUuNnYyLjljMCwwLjIsMCwwLjQsMCwwLjUgYzAsMC4xLDAuMSwwLjIsMC4zLDAuMmMwLjEsMCwwLjIsMCwwLjMsMFY5Ljh6IE0xNS4yLDYuOWMtMS4yLDAuNi0zLjEsMC4yLTMuMSwxLjRjMCwxLjQsMy4xLDEsMy4xLTAuNVY2Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-check: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik05IDE2LjE3TDQuODMgMTJsLTEuNDIgMS40MUw5IDE5IDIxIDdsLTEuNDEtMS40MXoiLz4KICA8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-circle-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDJDNi40NyAyIDIgNi40NyAyIDEyczQuNDcgMTAgMTAgMTAgMTAtNC40NyAxMC0xMFMxNy41MyAyIDEyIDJ6bTAgMThjLTQuNDEgMC04LTMuNTktOC04czMuNTktOCA4LTggOCAzLjU5IDggOC0zLjU5IDgtOCA4eiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-circle: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMTggMTgiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPGNpcmNsZSBjeD0iOSIgY3k9IjkiIHI9IjgiLz4KICA8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-clear: url(data:image/svg+xml;base64,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); | |
| --jp-icon-close: url(data:image/svg+xml;base64,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); | |
| --jp-icon-code-check: url(data:image/svg+xml;base64,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); | |
| --jp-icon-code: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTExLjQgMTguNkw2LjggMTRMMTEuNCA5LjRMMTAgOEw0IDE0TDEwIDIwTDExLjQgMTguNlpNMTYuNiAxOC42TDIxLjIgMTRMMTYuNiA5LjRMMTggOEwyNCAxNEwxOCAyMEwxNi42IDE4LjZWMTguNloiLz4KCTwvZz4KPC9zdmc+Cg==); | |
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| |
| --jp-icon-kernel: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiIgZmlsbD0iIzYxNjE2MSIgZD0iTTE1IDlIOXY2aDZWOXptLTIgNGgtMnYtMmgydjJ6bTgtMlY5aC0yVjdjMC0xLjEtLjktMi0yLTJoLTJWM2gtMnYyaC0yVjNIOXYySDdjLTEuMSAwLTIgLjktMiAydjJIM3YyaDJ2MkgzdjJoMnYyYzAgMS4xLjkgMiAyIDJoMnYyaDJ2LTJoMnYyaDJ2LTJoMmMxLjEgMCAyLS45IDItMnYtMmgydi0yaC0ydi0yaDJ6bS00IDZIN1Y3aDEwdjEweiIvPgo8L3N2Zz4K); | |
| --jp-icon-keyboard: url(data:image/svg+xml;base64,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); | |
| --jp-icon-launch: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMzIgMzIiIHdpZHRoPSIzMiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIj4KICAgIDxwYXRoIGQ9Ik0yNiwyOEg2YTIuMDAyNywyLjAwMjcsMCwwLDEtMi0yVjZBMi4wMDI3LDIuMDAyNywwLDAsMSw2LDRIMTZWNkg2VjI2SDI2VjE2aDJWMjZBMi4wMDI3LDIuMDAyNywwLDAsMSwyNiwyOFoiLz4KICAgIDxwb2x5Z29uIHBvaW50cz0iMjAgMiAyMCA0IDI2LjU4NiA0IDE4IDEyLjU4NiAxOS40MTQgMTQgMjggNS40MTQgMjggMTIgMzAgMTIgMzAgMiAyMCAyIi8+CiAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-launcher: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtaWNvbjMganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNjE2MTYxIiBkPSJNMTkgMTlINVY1aDdWM0g1YTIgMiAwIDAwLTIgMnYxNGEyIDIgMCAwMDIgMmgxNGMxLjEgMCAyLS45IDItMnYtN2gtMnY3ek0xNCAzdjJoMy41OWwtOS44MyA5LjgzIDEuNDEgMS40MUwxOSA2LjQxVjEwaDJWM2gtN3oiLz4KPC9zdmc+Cg==); | |
| --jp-icon-line-form: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGZpbGw9IndoaXRlIiBkPSJNNS44OCA0LjEyTDEzLjc2IDEybC03Ljg4IDcuODhMOCAyMmwxMC0xMEw4IDJ6Ii8+Cjwvc3ZnPgo=); | |
| --jp-icon-link: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTMuOSAxMmMwLTEuNzEgMS4zOS0zLjEgMy4xLTMuMWg0VjdIN2MtMi43NiAwLTUgMi4yNC01IDVzMi4yNCA1IDUgNWg0di0xLjlIN2MtMS43MSAwLTMuMS0xLjM5LTMuMS0zLjF6TTggMTNoOHYtMkg4djJ6bTktNmgtNHYxLjloNGMxLjcxIDAgMy4xIDEuMzkgMy4xIDMuMXMtMS4zOSAzLjEtMy4xIDMuMWgtNFYxN2g0YzIuNzYgMCA1LTIuMjQgNS01cy0yLjI0LTUtNS01eiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-list: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICAgIDxwYXRoIGNsYXNzPSJqcC1pY29uMiBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xOSA1djE0SDVWNWgxNG0xLjEtMkgzLjljLS41IDAtLjkuNC0uOS45djE2LjJjMCAuNC40LjkuOS45aDE2LjJjLjQgMCAuOS0uNS45LS45VjMuOWMwLS41LS41LS45LS45LS45ek0xMSA3aDZ2MmgtNlY3em0wIDRoNnYyaC02di0yem0wIDRoNnYyaC02ek03IDdoMnYySDd6bTAgNGgydjJIN3ptMCA0aDJ2Mkg3eiIvPgo8L3N2Zz4K); | |
| --jp-icon-markdown: url(data:image/svg+xml;base64,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); | |
| --jp-icon-move-down: url(data:image/svg+xml;base64,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); | |
| --jp-icon-move-up: url(data:image/svg+xml;base64,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); | |
| --jp-icon-new-folder: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIwIDZoLThsLTItMkg0Yy0xLjExIDAtMS45OS44OS0xLjk5IDJMMiAxOGMwIDEuMTEuODkgMiAyIDJoMTZjMS4xMSAwIDItLjg5IDItMlY4YzAtMS4xMS0uODktMi0yLTJ6bS0xIDhoLTN2M2gtMnYtM2gtM3YtMmgzVjloMnYzaDN2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-not-trusted: url(data:image/svg+xml;base64,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); | |
| --jp-icon-notebook: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtbm90ZWJvb2staWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiNFRjZDMDAiPgogICAgPHBhdGggZD0iTTE4LjcgMy4zdjE1LjRIMy4zVjMuM2gxNS40bTEuNS0xLjVIMS44djE4LjNoMTguM2wuMS0xOC4zeiIvPgogICAgPHBhdGggZD0iTTE2LjUgMTYuNWwtNS40LTQuMy01LjYgNC4zdi0xMWgxMXoiLz4KICA8L2c+Cjwvc3ZnPgo=); | |
| --jp-icon-numbering: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjIiIGhlaWdodD0iMjIiIHZpZXdCb3g9IjAgMCAyOCAyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CgkJPHBhdGggZD0iTTQgMTlINlYxOS41SDVWMjAuNUg2VjIxSDRWMjJIN1YxOEg0VjE5Wk01IDEwSDZWNkg0VjdINVYxMFpNNCAxM0g1LjhMNCAxNS4xVjE2SDdWMTVINS4yTDcgMTIuOVYxMkg0VjEzWk05IDdWOUgyM1Y3SDlaTTkgMjFIMjNWMTlIOVYyMVpNOSAxNUgyM1YxM0g5VjE1WiIvPgoJPC9nPgo8L3N2Zz4K); | |
| --jp-icon-offline-bolt: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyIDIuMDJjLTUuNTEgMC05Ljk4IDQuNDctOS45OCA5Ljk4czQuNDcgOS45OCA5Ljk4IDkuOTggOS45OC00LjQ3IDkuOTgtOS45OFMxNy41MSAyLjAyIDEyIDIuMDJ6TTExLjQ4IDIwdi02LjI2SDhMMTMgNHY2LjI2aDMuMzVMMTEuNDggMjB6Ii8+CiAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-palette: url(data:image/svg+xml;base64,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); | |
| --jp-icon-paste: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE5IDJoLTQuMThDMTQuNC44NCAxMy4zIDAgMTIgMGMtMS4zIDAtMi40Ljg0LTIuODIgMkg1Yy0xLjEgMC0yIC45LTIgMnYxNmMwIDEuMS45IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjRjMC0xLjEtLjktMi0yLTJ6bS03IDBjLjU1IDAgMSAuNDUgMSAxcy0uNDUgMS0xIDEtMS0uNDUtMS0xIC40NS0xIDEtMXptNyAxOEg1VjRoMnYzaDEwVjRoMnYxNnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-pdf: url(data:image/svg+xml;base64,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); | |
| --jp-icon-python: url(data:image/svg+xml;base64,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); | |
| --jp-icon-r-kernel: url(data:image/svg+xml;base64,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); | |
| --jp-icon-react: url(data:image/svg+xml;base64,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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,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KICA8ZyBjbGFzcz0ianAtaWNvbjIiIGZpbGw9IiM0MTQxNDEiPgogICAgPHJlY3QgeD0iMiIgeT0iMiIgd2lkdGg9IjE2IiBoZWlnaHQ9IjE2Ii8+CiAgPC9nPgoKICA8ZyBjbGFzcz0ianAtaWNvbi1hY2NlbnQyIiBmaWxsPSIjRkZGIj4KICAgIDxjaXJjbGUgY2xhc3M9InN0MiIgY3g9IjUuNSIgY3k9IjE0LjUiIHI9IjEuNSIvPgogICAgPHJlY3QgeD0iMTIiIHk9IjQiIGNsYXNzPSJzdDIiIHdpZHRoPSIxIiBoZWlnaHQ9IjgiLz4KICAgIDxyZWN0IHg9IjguNSIgeT0iNy41IiB0cmFuc2Zvcm09Im1hdHJpeCgwLjg2NiAtMC41IDAuNSAwLjg2NiAtMi4zMjU1IDcuMzIxOSkiIGNsYXNzPSJzdDIiIHdpZHRoPSI4IiBoZWlnaHQ9IjEiLz4KICAgIDxyZWN0IHg9IjEyIiB5PSI0IiB0cmFuc2Zvcm09Im1hdHJpeCgwLjUgLTAuODY2IDAuODY2IDAuNSAtMC42Nzc5IDE0LjgyNTIpIiBjbGFzcz0ic3QyIiB3aWR0aD0iMSIgaGVpZ2h0PSI4Ii8+CiAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-running: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDUxMiA1MTIiPgogIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICA8cGF0aCBkPSJNMjU2IDhDMTE5IDggOCAxMTkgOCAyNTZzMTExIDI0OCAyNDggMjQ4IDI0OC0xMTEgMjQ4LTI0OFMzOTMgOCAyNTYgOHptOTYgMzI4YzAgOC44LTcuMiAxNi0xNiAxNkgxNzZjLTguOCAwLTE2LTcuMi0xNi0xNlYxNzZjMC04LjggNy4yLTE2IDE2LTE2aDE2MGM4LjggMCAxNiA3LjIgMTYgMTZ2MTYweiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-search: url(data:image/svg+xml;base64,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); | |
| --jp-icon-settings: url(data:image/svg+xml;base64,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); | |
| --jp-icon-share: url(data:image/svg+xml;base64,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); | |
| --jp-icon-spreadsheet: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8cGF0aCBjbGFzcz0ianAtaWNvbi1jb250cmFzdDEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjNENBRjUwIiBkPSJNMi4yIDIuMnYxNy42aDE3LjZWMi4ySDIuMnptMTUuNCA3LjdoLTUuNVY0LjRoNS41djUuNXpNOS45IDQuNHY1LjVINC40VjQuNGg1LjV6bS01LjUgNy43aDUuNXY1LjVINC40di01LjV6bTcuNyA1LjV2LTUuNWg1LjV2NS41aC01LjV6Ii8+Cjwvc3ZnPgo=); | |
| --jp-icon-stop: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik02IDZoMTJ2MTJINnoiLz4KICAgIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-tab: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTIxIDNIM2MtMS4xIDAtMiAuOS0yIDJ2MTRjMCAxLjEuOSAyIDIgMmgxOGMxLjEgMCAyLS45IDItMlY1YzAtMS4xLS45LTItMi0yem0wIDE2SDNWNWgxMHY0aDh2MTB6Ii8+CiAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-table-rows: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMSw4SDNWNGgxOFY4eiBNMjEsMTBIM3Y0aDE4VjEweiBNMjEsMTZIM3Y0aDE4VjE2eiIvPgogICAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-tag: url(data:image/svg+xml;base64,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); | |
| --jp-icon-terminal: url(data:image/svg+xml;base64,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); | |
| --jp-icon-text-editor: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8cGF0aCBjbGFzcz0ianAtdGV4dC1lZGl0b3ItaWNvbi1jb2xvciBqcC1pY29uLXNlbGVjdGFibGUiIGZpbGw9IiM2MTYxNjEiIGQ9Ik0xNSAxNUgzdjJoMTJ2LTJ6bTAtOEgzdjJoMTJWN3pNMyAxM2gxOHYtMkgzdjJ6bTAgOGgxOHYtMkgzdjJ6TTMgM3YyaDE4VjNIM3oiLz4KPC9zdmc+Cg==); | |
| --jp-icon-toc: url(data:image/svg+xml;base64,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); | |
| --jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K); | |
| --jp-icon-trusted: url(data:image/svg+xml;base64,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); | |
| --jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-users: url(data:image/svg+xml;base64,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); | |
| --jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==); | |
| --jp-icon-word: url(data:image/svg+xml;base64,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); | |
| --jp-icon-yaml: url(data:image/svg+xml;base64,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); | |
| } | |
| /* Icon CSS class declarations */ | |
| .jp-AddAboveIcon { | |
| background-image: var(--jp-icon-add-above); | |
| } | |
| .jp-AddBelowIcon { | |
| background-image: var(--jp-icon-add-below); | |
| } | |
| .jp-AddIcon { | |
| background-image: var(--jp-icon-add); | |
| } | |
| .jp-BellIcon { | |
| background-image: var(--jp-icon-bell); | |
| } | |
| .jp-BugDotIcon { | |
| background-image: var(--jp-icon-bug-dot); | |
| } | |
| .jp-BugIcon { | |
| background-image: var(--jp-icon-bug); | |
| } | |
| .jp-BuildIcon { | |
| background-image: var(--jp-icon-build); | |
| } | |
| .jp-CaretDownEmptyIcon { | |
| background-image: var(--jp-icon-caret-down-empty); | |
| } | |
| .jp-CaretDownEmptyThinIcon { | |
| background-image: var(--jp-icon-caret-down-empty-thin); | |
| } | |
| .jp-CaretDownIcon { | |
| background-image: var(--jp-icon-caret-down); | |
| } | |
| .jp-CaretLeftIcon { | |
| background-image: var(--jp-icon-caret-left); | |
| } | |
| .jp-CaretRightIcon { | |
| background-image: var(--jp-icon-caret-right); | |
| } | |
| .jp-CaretUpEmptyThinIcon { | |
| background-image: var(--jp-icon-caret-up-empty-thin); | |
| } | |
| .jp-CaretUpIcon { | |
| background-image: var(--jp-icon-caret-up); | |
| } | |
| .jp-CaseSensitiveIcon { | |
| background-image: var(--jp-icon-case-sensitive); | |
| } | |
| .jp-CheckIcon { | |
| background-image: var(--jp-icon-check); | |
| } | |
| .jp-CircleEmptyIcon { | |
| background-image: var(--jp-icon-circle-empty); | |
| } | |
| .jp-CircleIcon { | |
| background-image: var(--jp-icon-circle); | |
| } | |
| .jp-ClearIcon { | |
| background-image: var(--jp-icon-clear); | |
| } | |
| .jp-CloseIcon { | |
| background-image: var(--jp-icon-close); | |
| } | |
| .jp-CodeCheckIcon { | |
| background-image: var(--jp-icon-code-check); | |
| } | |
| .jp-CodeIcon { | |
| background-image: var(--jp-icon-code); | |
| } | |
| .jp-CollapseAllIcon { | |
| background-image: var(--jp-icon-collapse-all); | |
| } | |
| .jp-ConsoleIcon { | |
| background-image: var(--jp-icon-console); | |
| } | |
| .jp-CopyIcon { | |
| background-image: var(--jp-icon-copy); | |
| } | |
| .jp-CopyrightIcon { | |
| background-image: var(--jp-icon-copyright); | |
| } | |
| .jp-CutIcon { | |
| background-image: var(--jp-icon-cut); | |
| } | |
| .jp-DeleteIcon { | |
| background-image: var(--jp-icon-delete); | |
| } | |
| .jp-DownloadIcon { | |
| background-image: var(--jp-icon-download); | |
| } | |
| .jp-DuplicateIcon { | |
| background-image: var(--jp-icon-duplicate); | |
| } | |
| .jp-EditIcon { | |
| background-image: var(--jp-icon-edit); | |
| } | |
| .jp-EllipsesIcon { | |
| background-image: var(--jp-icon-ellipses); | |
| } | |
| .jp-ErrorIcon { | |
| background-image: var(--jp-icon-error); | |
| } | |
| .jp-ExpandAllIcon { | |
| background-image: var(--jp-icon-expand-all); | |
| } | |
| .jp-ExtensionIcon { | |
| background-image: var(--jp-icon-extension); | |
| } | |
| .jp-FastForwardIcon { | |
| background-image: var(--jp-icon-fast-forward); | |
| } | |
| .jp-FileIcon { | |
| background-image: var(--jp-icon-file); | |
| } | |
| .jp-FileUploadIcon { | |
| background-image: var(--jp-icon-file-upload); | |
| } | |
| .jp-FilterDotIcon { | |
| background-image: var(--jp-icon-filter-dot); | |
| } | |
| .jp-FilterIcon { | |
| background-image: var(--jp-icon-filter); | |
| } | |
| .jp-FilterListIcon { | |
| background-image: var(--jp-icon-filter-list); | |
| } | |
| .jp-FolderFavoriteIcon { | |
| background-image: var(--jp-icon-folder-favorite); | |
| } | |
| .jp-FolderIcon { | |
| background-image: var(--jp-icon-folder); | |
| } | |
| .jp-HomeIcon { | |
| background-image: var(--jp-icon-home); | |
| } | |
| .jp-Html5Icon { | |
| background-image: var(--jp-icon-html5); | |
| } | |
| .jp-ImageIcon { | |
| background-image: var(--jp-icon-image); | |
| } | |
| .jp-InfoIcon { | |
| background-image: var(--jp-icon-info); | |
| } | |
| .jp-InspectorIcon { | |
| background-image: var(--jp-icon-inspector); | |
| } | |
| .jp-JsonIcon { | |
| background-image: var(--jp-icon-json); | |
| } | |
| .jp-JuliaIcon { | |
| background-image: var(--jp-icon-julia); | |
| } | |
| .jp-JupyterFaviconIcon { | |
| background-image: var(--jp-icon-jupyter-favicon); | |
| } | |
| .jp-JupyterIcon { | |
| background-image: var(--jp-icon-jupyter); | |
| } | |
| .jp-JupyterlabWordmarkIcon { | |
| background-image: var(--jp-icon-jupyterlab-wordmark); | |
| } | |
| .jp-KernelIcon { | |
| background-image: var(--jp-icon-kernel); | |
| } | |
| .jp-KeyboardIcon { | |
| background-image: var(--jp-icon-keyboard); | |
| } | |
| .jp-LaunchIcon { | |
| background-image: var(--jp-icon-launch); | |
| } | |
| .jp-LauncherIcon { | |
| background-image: var(--jp-icon-launcher); | |
| } | |
| .jp-LineFormIcon { | |
| background-image: var(--jp-icon-line-form); | |
| } | |
| .jp-LinkIcon { | |
| background-image: var(--jp-icon-link); | |
| } | |
| .jp-ListIcon { | |
| background-image: var(--jp-icon-list); | |
| } | |
| .jp-MarkdownIcon { | |
| background-image: var(--jp-icon-markdown); | |
| } | |
| .jp-MoveDownIcon { | |
| background-image: var(--jp-icon-move-down); | |
| } | |
| .jp-MoveUpIcon { | |
| background-image: var(--jp-icon-move-up); | |
| } | |
| .jp-NewFolderIcon { | |
| background-image: var(--jp-icon-new-folder); | |
| } | |
| .jp-NotTrustedIcon { | |
| background-image: var(--jp-icon-not-trusted); | |
| } | |
| .jp-NotebookIcon { | |
| background-image: var(--jp-icon-notebook); | |
| } | |
| .jp-NumberingIcon { | |
| background-image: var(--jp-icon-numbering); | |
| } | |
| .jp-OfflineBoltIcon { | |
| background-image: var(--jp-icon-offline-bolt); | |
| } | |
| .jp-PaletteIcon { | |
| background-image: var(--jp-icon-palette); | |
| } | |
| .jp-PasteIcon { | |
| background-image: var(--jp-icon-paste); | |
| } | |
| .jp-PdfIcon { | |
| background-image: var(--jp-icon-pdf); | |
| } | |
| .jp-PythonIcon { | |
| background-image: var(--jp-icon-python); | |
| } | |
| .jp-RKernelIcon { | |
| background-image: var(--jp-icon-r-kernel); | |
| } | |
| .jp-ReactIcon { | |
| background-image: var(--jp-icon-react); | |
| } | |
| .jp-RedoIcon { | |
| background-image: var(--jp-icon-redo); | |
| } | |
| .jp-RefreshIcon { | |
| background-image: var(--jp-icon-refresh); | |
| } | |
| .jp-RegexIcon { | |
| background-image: var(--jp-icon-regex); | |
| } | |
| .jp-RunIcon { | |
| background-image: var(--jp-icon-run); | |
| } | |
| .jp-RunningIcon { | |
| background-image: var(--jp-icon-running); | |
| } | |
| .jp-SaveIcon { | |
| background-image: var(--jp-icon-save); | |
| } | |
| .jp-SearchIcon { | |
| background-image: var(--jp-icon-search); | |
| } | |
| .jp-SettingsIcon { | |
| background-image: var(--jp-icon-settings); | |
| } | |
| .jp-ShareIcon { | |
| background-image: var(--jp-icon-share); | |
| } | |
| .jp-SpreadsheetIcon { | |
| background-image: var(--jp-icon-spreadsheet); | |
| } | |
| .jp-StopIcon { | |
| background-image: var(--jp-icon-stop); | |
| } | |
| .jp-TabIcon { | |
| background-image: var(--jp-icon-tab); | |
| } | |
| .jp-TableRowsIcon { | |
| background-image: var(--jp-icon-table-rows); | |
| } | |
| .jp-TagIcon { | |
| background-image: var(--jp-icon-tag); | |
| } | |
| .jp-TerminalIcon { | |
| background-image: var(--jp-icon-terminal); | |
| } | |
| .jp-TextEditorIcon { | |
| background-image: var(--jp-icon-text-editor); | |
| } | |
| .jp-TocIcon { | |
| background-image: var(--jp-icon-toc); | |
| } | |
| .jp-TreeViewIcon { | |
| background-image: var(--jp-icon-tree-view); | |
| } | |
| .jp-TrustedIcon { | |
| background-image: var(--jp-icon-trusted); | |
| } | |
| .jp-UndoIcon { | |
| background-image: var(--jp-icon-undo); | |
| } | |
| .jp-UserIcon { | |
| background-image: var(--jp-icon-user); | |
| } | |
| .jp-UsersIcon { | |
| background-image: var(--jp-icon-users); | |
| } | |
| .jp-VegaIcon { | |
| background-image: var(--jp-icon-vega); | |
| } | |
| .jp-WordIcon { | |
| background-image: var(--jp-icon-word); | |
| } | |
| .jp-YamlIcon { | |
| background-image: var(--jp-icon-yaml); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /** | |
| * (DEPRECATED) Support for consuming icons as CSS background images | |
| */ | |
| .jp-Icon, | |
| .jp-MaterialIcon { | |
| background-position: center; | |
| background-repeat: no-repeat; | |
| background-size: 16px; | |
| min-width: 16px; | |
| min-height: 16px; | |
| } | |
| .jp-Icon-cover { | |
| background-position: center; | |
| background-repeat: no-repeat; | |
| background-size: cover; | |
| } | |
| /** | |
| * (DEPRECATED) Support for specific CSS icon sizes | |
| */ | |
| .jp-Icon-16 { | |
| background-size: 16px; | |
| min-width: 16px; | |
| min-height: 16px; | |
| } | |
| .jp-Icon-18 { | |
| background-size: 18px; | |
| min-width: 18px; | |
| min-height: 18px; | |
| } | |
| .jp-Icon-20 { | |
| background-size: 20px; | |
| min-width: 20px; | |
| min-height: 20px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .lm-TabBar .lm-TabBar-addButton { | |
| align-items: center; | |
| display: flex; | |
| padding: 4px; | |
| padding-bottom: 5px; | |
| margin-right: 1px; | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .lm-TabBar .lm-TabBar-addButton:hover { | |
| background-color: var(--jp-layout-color1); | |
| } | |
| .lm-DockPanel-tabBar .lm-TabBar-tab { | |
| width: var(--jp-private-horizontal-tab-width); | |
| } | |
| .lm-DockPanel-tabBar .lm-TabBar-content { | |
| flex: unset; | |
| } | |
| .lm-DockPanel-tabBar[data-orientation='horizontal'] { | |
| flex: 1 1 auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /** | |
| * Support for icons as inline SVG HTMLElements | |
| */ | |
| /* recolor the primary elements of an icon */ | |
| .jp-icon0[fill] { | |
| fill: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon1[fill] { | |
| fill: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon2[fill] { | |
| fill: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon3[fill] { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon4[fill] { | |
| fill: var(--jp-inverse-layout-color4); | |
| } | |
| .jp-icon0[stroke] { | |
| stroke: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon1[stroke] { | |
| stroke: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon2[stroke] { | |
| stroke: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon3[stroke] { | |
| stroke: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon4[stroke] { | |
| stroke: var(--jp-inverse-layout-color4); | |
| } | |
| /* recolor the accent elements of an icon */ | |
| .jp-icon-accent0[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .jp-icon-accent1[fill] { | |
| fill: var(--jp-layout-color1); | |
| } | |
| .jp-icon-accent2[fill] { | |
| fill: var(--jp-layout-color2); | |
| } | |
| .jp-icon-accent3[fill] { | |
| fill: var(--jp-layout-color3); | |
| } | |
| .jp-icon-accent4[fill] { | |
| fill: var(--jp-layout-color4); | |
| } | |
| .jp-icon-accent0[stroke] { | |
| stroke: var(--jp-layout-color0); | |
| } | |
| .jp-icon-accent1[stroke] { | |
| stroke: var(--jp-layout-color1); | |
| } | |
| .jp-icon-accent2[stroke] { | |
| stroke: var(--jp-layout-color2); | |
| } | |
| .jp-icon-accent3[stroke] { | |
| stroke: var(--jp-layout-color3); | |
| } | |
| .jp-icon-accent4[stroke] { | |
| stroke: var(--jp-layout-color4); | |
| } | |
| /* set the color of an icon to transparent */ | |
| .jp-icon-none[fill] { | |
| fill: none; | |
| } | |
| .jp-icon-none[stroke] { | |
| stroke: none; | |
| } | |
| /* brand icon colors. Same for light and dark */ | |
| .jp-icon-brand0[fill] { | |
| fill: var(--jp-brand-color0); | |
| } | |
| .jp-icon-brand1[fill] { | |
| fill: var(--jp-brand-color1); | |
| } | |
| .jp-icon-brand2[fill] { | |
| fill: var(--jp-brand-color2); | |
| } | |
| .jp-icon-brand3[fill] { | |
| fill: var(--jp-brand-color3); | |
| } | |
| .jp-icon-brand4[fill] { | |
| fill: var(--jp-brand-color4); | |
| } | |
| .jp-icon-brand0[stroke] { | |
| stroke: var(--jp-brand-color0); | |
| } | |
| .jp-icon-brand1[stroke] { | |
| stroke: var(--jp-brand-color1); | |
| } | |
| .jp-icon-brand2[stroke] { | |
| stroke: var(--jp-brand-color2); | |
| } | |
| .jp-icon-brand3[stroke] { | |
| stroke: var(--jp-brand-color3); | |
| } | |
| .jp-icon-brand4[stroke] { | |
| stroke: var(--jp-brand-color4); | |
| } | |
| /* warn icon colors. Same for light and dark */ | |
| .jp-icon-warn0[fill] { | |
| fill: var(--jp-warn-color0); | |
| } | |
| .jp-icon-warn1[fill] { | |
| fill: var(--jp-warn-color1); | |
| } | |
| .jp-icon-warn2[fill] { | |
| fill: var(--jp-warn-color2); | |
| } | |
| .jp-icon-warn3[fill] { | |
| fill: var(--jp-warn-color3); | |
| } | |
| .jp-icon-warn0[stroke] { | |
| stroke: var(--jp-warn-color0); | |
| } | |
| .jp-icon-warn1[stroke] { | |
| stroke: var(--jp-warn-color1); | |
| } | |
| .jp-icon-warn2[stroke] { | |
| stroke: var(--jp-warn-color2); | |
| } | |
| .jp-icon-warn3[stroke] { | |
| stroke: var(--jp-warn-color3); | |
| } | |
| /* icon colors that contrast well with each other and most backgrounds */ | |
| .jp-icon-contrast0[fill] { | |
| fill: var(--jp-icon-contrast-color0); | |
| } | |
| .jp-icon-contrast1[fill] { | |
| fill: var(--jp-icon-contrast-color1); | |
| } | |
| .jp-icon-contrast2[fill] { | |
| fill: var(--jp-icon-contrast-color2); | |
| } | |
| .jp-icon-contrast3[fill] { | |
| fill: var(--jp-icon-contrast-color3); | |
| } | |
| .jp-icon-contrast0[stroke] { | |
| stroke: var(--jp-icon-contrast-color0); | |
| } | |
| .jp-icon-contrast1[stroke] { | |
| stroke: var(--jp-icon-contrast-color1); | |
| } | |
| .jp-icon-contrast2[stroke] { | |
| stroke: var(--jp-icon-contrast-color2); | |
| } | |
| .jp-icon-contrast3[stroke] { | |
| stroke: var(--jp-icon-contrast-color3); | |
| } | |
| .jp-icon-dot[fill] { | |
| fill: var(--jp-warn-color0); | |
| } | |
| .jp-jupyter-icon-color[fill] { | |
| fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0)); | |
| } | |
| .jp-notebook-icon-color[fill] { | |
| fill: var(--jp-notebook-icon-color, var(--jp-warn-color0)); | |
| } | |
| .jp-json-icon-color[fill] { | |
| fill: var(--jp-json-icon-color, var(--jp-warn-color1)); | |
| } | |
| .jp-console-icon-color[fill] { | |
| fill: var(--jp-console-icon-color, white); | |
| } | |
| .jp-console-icon-background-color[fill] { | |
| fill: var(--jp-console-icon-background-color, var(--jp-brand-color1)); | |
| } | |
| .jp-terminal-icon-color[fill] { | |
| fill: var(--jp-terminal-icon-color, var(--jp-layout-color2)); | |
| } | |
| .jp-terminal-icon-background-color[fill] { | |
| fill: var( | |
| --jp-terminal-icon-background-color, | |
| var(--jp-inverse-layout-color2) | |
| ); | |
| } | |
| .jp-text-editor-icon-color[fill] { | |
| fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3)); | |
| } | |
| .jp-inspector-icon-color[fill] { | |
| fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3)); | |
| } | |
| /* CSS for icons in selected filebrowser listing items */ | |
| .jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] { | |
| fill: #fff; | |
| } | |
| .jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] { | |
| fill: var(--jp-brand-color1); | |
| } | |
| /* stylelint-disable selector-max-class, selector-max-compound-selectors */ | |
| /** | |
| * TODO: come up with non css-hack solution for showing the busy icon on top | |
| * of the close icon | |
| * CSS for complex behavior of close icon of tabs in the main area tabbar | |
| */ | |
| .lm-DockPanel-tabBar | |
| .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty | |
| > .lm-TabBar-tabCloseIcon | |
| > :not(:hover) | |
| > .jp-icon3[fill] { | |
| fill: none; | |
| } | |
| .lm-DockPanel-tabBar | |
| .lm-TabBar-tab.lm-mod-closable.jp-mod-dirty | |
| > .lm-TabBar-tabCloseIcon | |
| > :not(:hover) | |
| > .jp-icon-busy[fill] { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| /* stylelint-enable selector-max-class, selector-max-compound-selectors */ | |
| /* CSS for icons in status bar */ | |
| #jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] { | |
| fill: #fff; | |
| } | |
| #jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] { | |
| fill: var(--jp-brand-color1); | |
| } | |
| /* special handling for splash icon CSS. While the theme CSS reloads during | |
| splash, the splash icon can loose theming. To prevent that, we set a | |
| default for its color variable */ | |
| :root { | |
| --jp-warn-color0: var(--md-orange-700); | |
| } | |
| /* not sure what to do with this one, used in filebrowser listing */ | |
| .jp-DragIcon { | |
| margin-right: 4px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /** | |
| * Support for alt colors for icons as inline SVG HTMLElements | |
| */ | |
| /* alt recolor the primary elements of an icon */ | |
| .jp-icon-alt .jp-icon0[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .jp-icon-alt .jp-icon1[fill] { | |
| fill: var(--jp-layout-color1); | |
| } | |
| .jp-icon-alt .jp-icon2[fill] { | |
| fill: var(--jp-layout-color2); | |
| } | |
| .jp-icon-alt .jp-icon3[fill] { | |
| fill: var(--jp-layout-color3); | |
| } | |
| .jp-icon-alt .jp-icon4[fill] { | |
| fill: var(--jp-layout-color4); | |
| } | |
| .jp-icon-alt .jp-icon0[stroke] { | |
| stroke: var(--jp-layout-color0); | |
| } | |
| .jp-icon-alt .jp-icon1[stroke] { | |
| stroke: var(--jp-layout-color1); | |
| } | |
| .jp-icon-alt .jp-icon2[stroke] { | |
| stroke: var(--jp-layout-color2); | |
| } | |
| .jp-icon-alt .jp-icon3[stroke] { | |
| stroke: var(--jp-layout-color3); | |
| } | |
| .jp-icon-alt .jp-icon4[stroke] { | |
| stroke: var(--jp-layout-color4); | |
| } | |
| /* alt recolor the accent elements of an icon */ | |
| .jp-icon-alt .jp-icon-accent0[fill] { | |
| fill: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-alt .jp-icon-accent1[fill] { | |
| fill: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-alt .jp-icon-accent2[fill] { | |
| fill: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-alt .jp-icon-accent3[fill] { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-alt .jp-icon-accent4[fill] { | |
| fill: var(--jp-inverse-layout-color4); | |
| } | |
| .jp-icon-alt .jp-icon-accent0[stroke] { | |
| stroke: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-alt .jp-icon-accent1[stroke] { | |
| stroke: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-alt .jp-icon-accent2[stroke] { | |
| stroke: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-alt .jp-icon-accent3[stroke] { | |
| stroke: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-alt .jp-icon-accent4[stroke] { | |
| stroke: var(--jp-inverse-layout-color4); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content { | |
| display: none !important; | |
| } | |
| /** | |
| * Support for hover colors for icons as inline SVG HTMLElements | |
| */ | |
| /** | |
| * regular colors | |
| */ | |
| /* recolor the primary elements of an icon */ | |
| .jp-icon-hover :hover .jp-icon0-hover[fill] { | |
| fill: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-hover :hover .jp-icon1-hover[fill] { | |
| fill: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-hover :hover .jp-icon2-hover[fill] { | |
| fill: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-hover :hover .jp-icon3-hover[fill] { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-hover :hover .jp-icon4-hover[fill] { | |
| fill: var(--jp-inverse-layout-color4); | |
| } | |
| .jp-icon-hover :hover .jp-icon0-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-hover :hover .jp-icon1-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-hover :hover .jp-icon2-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-hover :hover .jp-icon3-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-hover :hover .jp-icon4-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color4); | |
| } | |
| /* recolor the accent elements of an icon */ | |
| .jp-icon-hover :hover .jp-icon-accent0-hover[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent1-hover[fill] { | |
| fill: var(--jp-layout-color1); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent2-hover[fill] { | |
| fill: var(--jp-layout-color2); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent3-hover[fill] { | |
| fill: var(--jp-layout-color3); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent4-hover[fill] { | |
| fill: var(--jp-layout-color4); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent0-hover[stroke] { | |
| stroke: var(--jp-layout-color0); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent1-hover[stroke] { | |
| stroke: var(--jp-layout-color1); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent2-hover[stroke] { | |
| stroke: var(--jp-layout-color2); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent3-hover[stroke] { | |
| stroke: var(--jp-layout-color3); | |
| } | |
| .jp-icon-hover :hover .jp-icon-accent4-hover[stroke] { | |
| stroke: var(--jp-layout-color4); | |
| } | |
| /* set the color of an icon to transparent */ | |
| .jp-icon-hover :hover .jp-icon-none-hover[fill] { | |
| fill: none; | |
| } | |
| .jp-icon-hover :hover .jp-icon-none-hover[stroke] { | |
| stroke: none; | |
| } | |
| /** | |
| * inverse colors | |
| */ | |
| /* inverse recolor the primary elements of an icon */ | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] { | |
| fill: var(--jp-layout-color1); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] { | |
| fill: var(--jp-layout-color2); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] { | |
| fill: var(--jp-layout-color3); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] { | |
| fill: var(--jp-layout-color4); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] { | |
| stroke: var(--jp-layout-color0); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] { | |
| stroke: var(--jp-layout-color1); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] { | |
| stroke: var(--jp-layout-color2); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] { | |
| stroke: var(--jp-layout-color3); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] { | |
| stroke: var(--jp-layout-color4); | |
| } | |
| /* inverse recolor the accent elements of an icon */ | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] { | |
| fill: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] { | |
| fill: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] { | |
| fill: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] { | |
| fill: var(--jp-inverse-layout-color4); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color0); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color2); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] { | |
| stroke: var(--jp-inverse-layout-color4); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-IFrame { | |
| width: 100%; | |
| height: 100%; | |
| } | |
| .jp-IFrame > iframe { | |
| border: none; | |
| } | |
| /* | |
| When drag events occur, `lm-mod-override-cursor` is added to the body. | |
| Because iframes steal all cursor events, the following two rules are necessary | |
| to suppress pointer events while resize drags are occurring. There may be a | |
| better solution to this problem. | |
| */ | |
| body.lm-mod-override-cursor .jp-IFrame { | |
| position: relative; | |
| } | |
| body.lm-mod-override-cursor .jp-IFrame::before { | |
| content: ''; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| right: 0; | |
| bottom: 0; | |
| background: transparent; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2016, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-HoverBox { | |
| position: fixed; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-FormGroup-content fieldset { | |
| border: none; | |
| padding: 0; | |
| min-width: 0; | |
| width: 100%; | |
| } | |
| /* stylelint-disable selector-max-type */ | |
| .jp-FormGroup-content fieldset .jp-inputFieldWrapper input, | |
| .jp-FormGroup-content fieldset .jp-inputFieldWrapper select, | |
| .jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea { | |
| font-size: var(--jp-content-font-size2); | |
| border-color: var(--jp-input-border-color); | |
| border-style: solid; | |
| border-radius: var(--jp-border-radius); | |
| border-width: 1px; | |
| padding: 6px 8px; | |
| background: none; | |
| color: var(--jp-ui-font-color0); | |
| height: inherit; | |
| } | |
| .jp-FormGroup-content fieldset input[type='checkbox'] { | |
| position: relative; | |
| top: 2px; | |
| margin-left: 0; | |
| } | |
| .jp-FormGroup-content button.jp-mod-styled { | |
| cursor: pointer; | |
| } | |
| .jp-FormGroup-content .checkbox label { | |
| cursor: pointer; | |
| font-size: var(--jp-content-font-size1); | |
| } | |
| .jp-FormGroup-content .jp-root > fieldset > legend { | |
| display: none; | |
| } | |
| .jp-FormGroup-content .jp-root > fieldset > p { | |
| display: none; | |
| } | |
| /** copy of `input.jp-mod-styled:focus` style */ | |
| .jp-FormGroup-content fieldset input:focus, | |
| .jp-FormGroup-content fieldset select:focus { | |
| -moz-outline-radius: unset; | |
| outline: var(--jp-border-width) solid var(--md-blue-500); | |
| outline-offset: -1px; | |
| box-shadow: inset 0 0 4px var(--md-blue-300); | |
| } | |
| .jp-FormGroup-content fieldset input:hover:not(:focus), | |
| .jp-FormGroup-content fieldset select:hover:not(:focus) { | |
| background-color: var(--jp-border-color2); | |
| } | |
| /* stylelint-enable selector-max-type */ | |
| .jp-FormGroup-content .checkbox .field-description { | |
| /* Disable default description field for checkbox: | |
| because other widgets do not have description fields, | |
| we add descriptions to each widget on the field level. | |
| */ | |
| display: none; | |
| } | |
| .jp-FormGroup-content #root__description { | |
| display: none; | |
| } | |
| .jp-FormGroup-content .jp-modifiedIndicator { | |
| width: 5px; | |
| background-color: var(--jp-brand-color2); | |
| margin-top: 0; | |
| margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1); | |
| flex-shrink: 0; | |
| } | |
| .jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator { | |
| background-color: var(--jp-error-color0); | |
| margin-right: 0.5em; | |
| } | |
| /* RJSF ARRAY style */ | |
| .jp-arrayFieldWrapper legend { | |
| font-size: var(--jp-content-font-size2); | |
| color: var(--jp-ui-font-color0); | |
| flex-basis: 100%; | |
| padding: 4px 0; | |
| font-weight: var(--jp-content-heading-font-weight); | |
| border-bottom: 1px solid var(--jp-border-color2); | |
| } | |
| .jp-arrayFieldWrapper .field-description { | |
| padding: 4px 0; | |
| white-space: pre-wrap; | |
| } | |
| .jp-arrayFieldWrapper .array-item { | |
| width: 100%; | |
| border: 1px solid var(--jp-border-color2); | |
| border-radius: 4px; | |
| margin: 4px; | |
| } | |
| .jp-ArrayOperations { | |
| display: flex; | |
| margin-left: 8px; | |
| } | |
| .jp-ArrayOperationsButton { | |
| margin: 2px; | |
| } | |
| .jp-ArrayOperationsButton .jp-icon3[fill] { | |
| fill: var(--jp-ui-font-color0); | |
| } | |
| button.jp-ArrayOperationsButton.jp-mod-styled:disabled { | |
| cursor: not-allowed; | |
| opacity: 0.5; | |
| } | |
| /* RJSF form validation error */ | |
| .jp-FormGroup-content .validationErrors { | |
| color: var(--jp-error-color0); | |
| } | |
| /* Hide panel level error as duplicated the field level error */ | |
| .jp-FormGroup-content .panel.errors { | |
| display: none; | |
| } | |
| /* RJSF normal content (settings-editor) */ | |
| .jp-FormGroup-contentNormal { | |
| display: flex; | |
| align-items: center; | |
| flex-wrap: wrap; | |
| } | |
| .jp-FormGroup-contentNormal .jp-FormGroup-contentItem { | |
| margin-left: 7px; | |
| color: var(--jp-ui-font-color0); | |
| } | |
| .jp-FormGroup-contentNormal .jp-FormGroup-description { | |
| flex-basis: 100%; | |
| padding: 4px 7px; | |
| } | |
| .jp-FormGroup-contentNormal .jp-FormGroup-default { | |
| flex-basis: 100%; | |
| padding: 4px 7px; | |
| } | |
| .jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel { | |
| font-size: var(--jp-content-font-size1); | |
| font-weight: normal; | |
| min-width: 120px; | |
| } | |
| .jp-FormGroup-contentNormal fieldset:not(:first-child) { | |
| margin-left: 7px; | |
| } | |
| .jp-FormGroup-contentNormal .field-array-of-string .array-item { | |
| /* Display `jp-ArrayOperations` buttons side-by-side with content except | |
| for small screens where flex-wrap will place them one below the other. | |
| */ | |
| display: flex; | |
| align-items: center; | |
| flex-wrap: wrap; | |
| } | |
| .jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group { | |
| padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent); | |
| margin-top: 2px; | |
| } | |
| /* RJSF compact content (metadata-form) */ | |
| .jp-FormGroup-content.jp-FormGroup-contentCompact { | |
| width: 100%; | |
| } | |
| .jp-FormGroup-contentCompact .form-group { | |
| display: flex; | |
| padding: 0.5em 0.2em 0.5em 0; | |
| } | |
| .jp-FormGroup-contentCompact | |
| .jp-FormGroup-compactTitle | |
| .jp-FormGroup-description { | |
| font-size: var(--jp-ui-font-size1); | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel { | |
| padding-bottom: 0.3em; | |
| } | |
| .jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control { | |
| width: 100%; | |
| box-sizing: border-box; | |
| } | |
| .jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle { | |
| padding-bottom: 7px; | |
| } | |
| .jp-FormGroup-contentCompact | |
| .jp-objectFieldWrapper | |
| .jp-objectFieldWrapper | |
| .form-group { | |
| padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent); | |
| margin-top: 2px; | |
| } | |
| .jp-FormGroup-contentCompact ul.error-detail { | |
| margin-block-start: 0.5em; | |
| margin-block-end: 0.5em; | |
| padding-inline-start: 1em; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .jp-SidePanel { | |
| display: flex; | |
| flex-direction: column; | |
| min-width: var(--jp-sidebar-min-width); | |
| overflow-y: auto; | |
| color: var(--jp-ui-font-color1); | |
| background: var(--jp-layout-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| } | |
| .jp-SidePanel-header { | |
| flex: 0 0 auto; | |
| display: flex; | |
| border-bottom: var(--jp-border-width) solid var(--jp-border-color2); | |
| font-size: var(--jp-ui-font-size0); | |
| font-weight: 600; | |
| letter-spacing: 1px; | |
| margin: 0; | |
| padding: 2px; | |
| text-transform: uppercase; | |
| } | |
| .jp-SidePanel-toolbar { | |
| flex: 0 0 auto; | |
| } | |
| .jp-SidePanel-content { | |
| flex: 1 1 auto; | |
| } | |
| .jp-SidePanel-toolbar, | |
| .jp-AccordionPanel-toolbar { | |
| height: var(--jp-private-toolbar-height); | |
| } | |
| .jp-SidePanel-toolbar.jp-Toolbar-micro { | |
| display: none; | |
| } | |
| .lm-AccordionPanel .jp-AccordionPanel-title { | |
| box-sizing: border-box; | |
| line-height: 25px; | |
| margin: 0; | |
| display: flex; | |
| align-items: center; | |
| background: var(--jp-layout-color1); | |
| color: var(--jp-ui-font-color1); | |
| border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color); | |
| box-shadow: var(--jp-toolbar-box-shadow); | |
| font-size: var(--jp-ui-font-size0); | |
| } | |
| .jp-AccordionPanel-title { | |
| cursor: pointer; | |
| user-select: none; | |
| -moz-user-select: none; | |
| -webkit-user-select: none; | |
| text-transform: uppercase; | |
| } | |
| .lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title { | |
| /* Title is rotated for horizontal accordion panel using CSS */ | |
| display: block; | |
| transform-origin: top left; | |
| transform: rotate(-90deg) translate(-100%); | |
| } | |
| .jp-AccordionPanel-title .lm-AccordionPanel-titleLabel { | |
| user-select: none; | |
| text-overflow: ellipsis; | |
| white-space: nowrap; | |
| overflow: hidden; | |
| } | |
| .jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser { | |
| transform: rotate(-90deg); | |
| margin: auto 0; | |
| height: 16px; | |
| } | |
| .jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser { | |
| transform: rotate(0deg); | |
| } | |
| .lm-AccordionPanel .jp-AccordionPanel-toolbar { | |
| background: none; | |
| box-shadow: none; | |
| border: none; | |
| margin-left: auto; | |
| } | |
| .lm-AccordionPanel .lm-SplitPanel-handle:hover { | |
| background: var(--jp-layout-color3); | |
| } | |
| .jp-text-truncated { | |
| overflow: hidden; | |
| text-overflow: ellipsis; | |
| white-space: nowrap; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2017, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Spinner { | |
| position: absolute; | |
| display: flex; | |
| justify-content: center; | |
| align-items: center; | |
| z-index: 10; | |
| left: 0; | |
| top: 0; | |
| width: 100%; | |
| height: 100%; | |
| background: var(--jp-layout-color0); | |
| outline: none; | |
| } | |
| .jp-SpinnerContent { | |
| font-size: 10px; | |
| margin: 50px auto; | |
| text-indent: -9999em; | |
| width: 3em; | |
| height: 3em; | |
| border-radius: 50%; | |
| background: var(--jp-brand-color3); | |
| background: linear-gradient( | |
| to right, | |
| #f37626 10%, | |
| rgba(255, 255, 255, 0) 42% | |
| ); | |
| position: relative; | |
| animation: load3 1s infinite linear, fadeIn 1s; | |
| } | |
| .jp-SpinnerContent::before { | |
| width: 50%; | |
| height: 50%; | |
| background: #f37626; | |
| border-radius: 100% 0 0; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| content: ''; | |
| } | |
| .jp-SpinnerContent::after { | |
| background: var(--jp-layout-color0); | |
| width: 75%; | |
| height: 75%; | |
| border-radius: 50%; | |
| content: ''; | |
| margin: auto; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| bottom: 0; | |
| right: 0; | |
| } | |
| @keyframes fadeIn { | |
| 0% { | |
| opacity: 0; | |
| } | |
| 100% { | |
| opacity: 1; | |
| } | |
| } | |
| @keyframes load3 { | |
| 0% { | |
| transform: rotate(0deg); | |
| } | |
| 100% { | |
| transform: rotate(360deg); | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2017, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| button.jp-mod-styled { | |
| font-size: var(--jp-ui-font-size1); | |
| color: var(--jp-ui-font-color0); | |
| border: none; | |
| box-sizing: border-box; | |
| text-align: center; | |
| line-height: 32px; | |
| height: 32px; | |
| padding: 0 12px; | |
| letter-spacing: 0.8px; | |
| outline: none; | |
| appearance: none; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| } | |
| input.jp-mod-styled { | |
| background: var(--jp-input-background); | |
| height: 28px; | |
| box-sizing: border-box; | |
| border: var(--jp-border-width) solid var(--jp-border-color1); | |
| padding-left: 7px; | |
| padding-right: 7px; | |
| font-size: var(--jp-ui-font-size2); | |
| color: var(--jp-ui-font-color0); | |
| outline: none; | |
| appearance: none; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| } | |
| input[type='checkbox'].jp-mod-styled { | |
| appearance: checkbox; | |
| -webkit-appearance: checkbox; | |
| -moz-appearance: checkbox; | |
| height: auto; | |
| } | |
| input.jp-mod-styled:focus { | |
| border: var(--jp-border-width) solid var(--md-blue-500); | |
| box-shadow: inset 0 0 4px var(--md-blue-300); | |
| } | |
| .jp-select-wrapper { | |
| display: flex; | |
| position: relative; | |
| flex-direction: column; | |
| padding: 1px; | |
| background-color: var(--jp-layout-color1); | |
| box-sizing: border-box; | |
| margin-bottom: 12px; | |
| } | |
| .jp-select-wrapper:not(.multiple) { | |
| height: 28px; | |
| } | |
| .jp-select-wrapper.jp-mod-focused select.jp-mod-styled { | |
| border: var(--jp-border-width) solid var(--jp-input-active-border-color); | |
| box-shadow: var(--jp-input-box-shadow); | |
| background-color: var(--jp-input-active-background); | |
| } | |
| select.jp-mod-styled:hover { | |
| cursor: pointer; | |
| color: var(--jp-ui-font-color0); | |
| background-color: var(--jp-input-hover-background); | |
| box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5); | |
| } | |
| select.jp-mod-styled { | |
| flex: 1 1 auto; | |
| width: 100%; | |
| font-size: var(--jp-ui-font-size2); | |
| background: var(--jp-input-background); | |
| color: var(--jp-ui-font-color0); | |
| padding: 0 25px 0 8px; | |
| border: var(--jp-border-width) solid var(--jp-input-border-color); | |
| border-radius: 0; | |
| outline: none; | |
| appearance: none; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| } | |
| select.jp-mod-styled:not([multiple]) { | |
| height: 32px; | |
| } | |
| select.jp-mod-styled[multiple] { | |
| max-height: 200px; | |
| overflow-y: auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-switch { | |
| display: flex; | |
| align-items: center; | |
| padding-left: 4px; | |
| padding-right: 4px; | |
| font-size: var(--jp-ui-font-size1); | |
| background-color: transparent; | |
| color: var(--jp-ui-font-color1); | |
| border: none; | |
| height: 20px; | |
| } | |
| .jp-switch:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-switch-label { | |
| margin-right: 5px; | |
| font-family: var(--jp-ui-font-family); | |
| } | |
| .jp-switch-track { | |
| cursor: pointer; | |
| background-color: var(--jp-switch-color, var(--jp-border-color1)); | |
| -webkit-transition: 0.4s; | |
| transition: 0.4s; | |
| border-radius: 34px; | |
| height: 16px; | |
| width: 35px; | |
| position: relative; | |
| } | |
| .jp-switch-track::before { | |
| content: ''; | |
| position: absolute; | |
| height: 10px; | |
| width: 10px; | |
| margin: 3px; | |
| left: 0; | |
| background-color: var(--jp-ui-inverse-font-color1); | |
| -webkit-transition: 0.4s; | |
| transition: 0.4s; | |
| border-radius: 50%; | |
| } | |
| .jp-switch[aria-checked='true'] .jp-switch-track { | |
| background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0)); | |
| } | |
| .jp-switch[aria-checked='true'] .jp-switch-track::before { | |
| /* track width (35) - margins (3 + 3) - thumb width (10) */ | |
| left: 19px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2016, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-private-toolbar-height: calc( | |
| 28px + var(--jp-border-width) | |
| ); /* leave 28px for content */ | |
| } | |
| .jp-Toolbar { | |
| color: var(--jp-ui-font-color1); | |
| flex: 0 0 auto; | |
| display: flex; | |
| flex-direction: row; | |
| border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color); | |
| box-shadow: var(--jp-toolbar-box-shadow); | |
| background: var(--jp-toolbar-background); | |
| min-height: var(--jp-toolbar-micro-height); | |
| padding: 2px; | |
| z-index: 8; | |
| overflow-x: hidden; | |
| } | |
| /* Toolbar items */ | |
| .jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer { | |
| flex-grow: 1; | |
| flex-shrink: 1; | |
| } | |
| .jp-Toolbar-item.jp-Toolbar-kernelStatus { | |
| display: inline-block; | |
| width: 32px; | |
| background-repeat: no-repeat; | |
| background-position: center; | |
| background-size: 16px; | |
| } | |
| .jp-Toolbar > .jp-Toolbar-item { | |
| flex: 0 0 auto; | |
| display: flex; | |
| padding-left: 1px; | |
| padding-right: 1px; | |
| font-size: var(--jp-ui-font-size1); | |
| line-height: var(--jp-private-toolbar-height); | |
| height: 100%; | |
| } | |
| /* Toolbar buttons */ | |
| /* This is the div we use to wrap the react component into a Widget */ | |
| div.jp-ToolbarButton { | |
| color: transparent; | |
| border: none; | |
| box-sizing: border-box; | |
| outline: none; | |
| appearance: none; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| padding: 0; | |
| margin: 0; | |
| } | |
| button.jp-ToolbarButtonComponent { | |
| background: var(--jp-layout-color1); | |
| border: none; | |
| box-sizing: border-box; | |
| outline: none; | |
| appearance: none; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| padding: 0 6px; | |
| margin: 0; | |
| height: 24px; | |
| border-radius: var(--jp-border-radius); | |
| display: flex; | |
| align-items: center; | |
| text-align: center; | |
| font-size: 14px; | |
| min-width: unset; | |
| min-height: unset; | |
| } | |
| button.jp-ToolbarButtonComponent:disabled { | |
| opacity: 0.4; | |
| } | |
| button.jp-ToolbarButtonComponent > span { | |
| padding: 0; | |
| flex: 0 0 auto; | |
| } | |
| button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label { | |
| font-size: var(--jp-ui-font-size1); | |
| line-height: 100%; | |
| padding-left: 2px; | |
| color: var(--jp-ui-font-color1); | |
| font-family: var(--jp-ui-font-family); | |
| } | |
| #jp-main-dock-panel[data-mode='single-document'] | |
| .jp-MainAreaWidget | |
| > .jp-Toolbar.jp-Toolbar-micro { | |
| padding: 0; | |
| min-height: 0; | |
| } | |
| #jp-main-dock-panel[data-mode='single-document'] | |
| .jp-MainAreaWidget | |
| > .jp-Toolbar { | |
| border: none; | |
| box-shadow: none; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .jp-WindowedPanel-outer { | |
| position: relative; | |
| overflow-y: auto; | |
| } | |
| .jp-WindowedPanel-inner { | |
| position: relative; | |
| } | |
| .jp-WindowedPanel-window { | |
| position: absolute; | |
| left: 0; | |
| right: 0; | |
| overflow: visible; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /* Sibling imports */ | |
| body { | |
| color: var(--jp-ui-font-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| } | |
| /* Disable native link decoration styles everywhere outside of dialog boxes */ | |
| a { | |
| text-decoration: unset; | |
| color: unset; | |
| } | |
| a:hover { | |
| text-decoration: unset; | |
| color: unset; | |
| } | |
| /* Accessibility for links inside dialog box text */ | |
| .jp-Dialog-content a { | |
| text-decoration: revert; | |
| color: var(--jp-content-link-color); | |
| } | |
| .jp-Dialog-content a:hover { | |
| text-decoration: revert; | |
| } | |
| /* Styles for ui-components */ | |
| .jp-Button { | |
| color: var(--jp-ui-font-color2); | |
| border-radius: var(--jp-border-radius); | |
| padding: 0 12px; | |
| font-size: var(--jp-ui-font-size1); | |
| /* Copy from blueprint 3 */ | |
| display: inline-flex; | |
| flex-direction: row; | |
| border: none; | |
| cursor: pointer; | |
| align-items: center; | |
| justify-content: center; | |
| text-align: left; | |
| vertical-align: middle; | |
| min-height: 30px; | |
| min-width: 30px; | |
| } | |
| .jp-Button:disabled { | |
| cursor: not-allowed; | |
| } | |
| .jp-Button:empty { | |
| padding: 0 !important; | |
| } | |
| .jp-Button.jp-mod-small { | |
| min-height: 24px; | |
| min-width: 24px; | |
| font-size: 12px; | |
| padding: 0 7px; | |
| } | |
| /* Use our own theme for hover styles */ | |
| .jp-Button.jp-mod-minimal:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-Button.jp-mod-minimal { | |
| background: none; | |
| } | |
| .jp-InputGroup { | |
| display: block; | |
| position: relative; | |
| } | |
| .jp-InputGroup input { | |
| box-sizing: border-box; | |
| border: none; | |
| border-radius: 0; | |
| background-color: transparent; | |
| color: var(--jp-ui-font-color0); | |
| box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color); | |
| padding-bottom: 0; | |
| padding-top: 0; | |
| padding-left: 10px; | |
| padding-right: 28px; | |
| position: relative; | |
| width: 100%; | |
| -webkit-appearance: none; | |
| -moz-appearance: none; | |
| appearance: none; | |
| font-size: 14px; | |
| font-weight: 400; | |
| height: 30px; | |
| line-height: 30px; | |
| outline: none; | |
| vertical-align: middle; | |
| } | |
| .jp-InputGroup input:focus { | |
| box-shadow: inset 0 0 0 var(--jp-border-width) | |
| var(--jp-input-active-box-shadow-color), | |
| inset 0 0 0 3px var(--jp-input-active-box-shadow-color); | |
| } | |
| .jp-InputGroup input:disabled { | |
| cursor: not-allowed; | |
| resize: block; | |
| background-color: var(--jp-layout-color2); | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .jp-InputGroup input:disabled ~ span { | |
| cursor: not-allowed; | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .jp-InputGroup input::placeholder, | |
| input::placeholder { | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .jp-InputGroupAction { | |
| position: absolute; | |
| bottom: 1px; | |
| right: 0; | |
| padding: 6px; | |
| } | |
| .jp-HTMLSelect.jp-DefaultStyle select { | |
| background-color: initial; | |
| border: none; | |
| border-radius: 0; | |
| box-shadow: none; | |
| color: var(--jp-ui-font-color0); | |
| display: block; | |
| font-size: var(--jp-ui-font-size1); | |
| font-family: var(--jp-ui-font-family); | |
| height: 24px; | |
| line-height: 14px; | |
| padding: 0 25px 0 10px; | |
| text-align: left; | |
| -moz-appearance: none; | |
| -webkit-appearance: none; | |
| } | |
| .jp-HTMLSelect.jp-DefaultStyle select:disabled { | |
| background-color: var(--jp-layout-color2); | |
| color: var(--jp-ui-font-color2); | |
| cursor: not-allowed; | |
| resize: block; | |
| } | |
| .jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span { | |
| cursor: not-allowed; | |
| } | |
| /* Use our own theme for hover and option styles */ | |
| /* stylelint-disable-next-line selector-max-type */ | |
| .jp-HTMLSelect.jp-DefaultStyle select:hover, | |
| .jp-HTMLSelect.jp-DefaultStyle select > option { | |
| background-color: var(--jp-layout-color2); | |
| color: var(--jp-ui-font-color0); | |
| } | |
| select { | |
| box-sizing: border-box; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Styles | |
| |----------------------------------------------------------------------------*/ | |
| .jp-StatusBar-Widget { | |
| display: flex; | |
| align-items: center; | |
| background: var(--jp-layout-color2); | |
| min-height: var(--jp-statusbar-height); | |
| justify-content: space-between; | |
| padding: 0 10px; | |
| } | |
| .jp-StatusBar-Left { | |
| display: flex; | |
| align-items: center; | |
| flex-direction: row; | |
| } | |
| .jp-StatusBar-Middle { | |
| display: flex; | |
| align-items: center; | |
| } | |
| .jp-StatusBar-Right { | |
| display: flex; | |
| align-items: center; | |
| flex-direction: row-reverse; | |
| } | |
| .jp-StatusBar-Item { | |
| max-height: var(--jp-statusbar-height); | |
| margin: 0 2px; | |
| height: var(--jp-statusbar-height); | |
| white-space: nowrap; | |
| text-overflow: ellipsis; | |
| color: var(--jp-ui-font-color1); | |
| padding: 0 6px; | |
| } | |
| .jp-mod-highlighted:hover { | |
| background-color: var(--jp-layout-color3); | |
| } | |
| .jp-mod-clicked { | |
| background-color: var(--jp-brand-color1); | |
| } | |
| .jp-mod-clicked:hover { | |
| background-color: var(--jp-brand-color0); | |
| } | |
| .jp-mod-clicked .jp-StatusBar-TextItem { | |
| color: var(--jp-ui-inverse-font-color1); | |
| } | |
| .jp-StatusBar-HoverItem { | |
| box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)'; | |
| } | |
| .jp-StatusBar-TextItem { | |
| font-size: var(--jp-ui-font-size1); | |
| font-family: var(--jp-ui-font-family); | |
| line-height: 24px; | |
| color: var(--jp-ui-font-color1); | |
| } | |
| .jp-StatusBar-GroupItem { | |
| display: flex; | |
| align-items: center; | |
| flex-direction: row; | |
| } | |
| .jp-Statusbar-ProgressCircle svg { | |
| display: block; | |
| margin: 0 auto; | |
| width: 16px; | |
| height: 24px; | |
| align-self: normal; | |
| } | |
| .jp-Statusbar-ProgressCircle path { | |
| fill: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-Statusbar-ProgressBar-progress-bar { | |
| height: 10px; | |
| width: 100px; | |
| border: solid 0.25px var(--jp-brand-color2); | |
| border-radius: 3px; | |
| overflow: hidden; | |
| align-self: center; | |
| } | |
| .jp-Statusbar-ProgressBar-progress-bar > div { | |
| background-color: var(--jp-brand-color2); | |
| background-image: linear-gradient( | |
| -45deg, | |
| rgba(255, 255, 255, 0.2) 25%, | |
| transparent 25%, | |
| transparent 50%, | |
| rgba(255, 255, 255, 0.2) 50%, | |
| rgba(255, 255, 255, 0.2) 75%, | |
| transparent 75%, | |
| transparent | |
| ); | |
| background-size: 40px 40px; | |
| float: left; | |
| width: 0%; | |
| height: 100%; | |
| font-size: 12px; | |
| line-height: 14px; | |
| color: #fff; | |
| text-align: center; | |
| animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite; | |
| } | |
| .jp-Statusbar-ProgressBar-progress-bar p { | |
| color: var(--jp-ui-font-color1); | |
| font-family: var(--jp-ui-font-family); | |
| font-size: var(--jp-ui-font-size1); | |
| line-height: 10px; | |
| width: 100px; | |
| } | |
| @keyframes jp-Statusbar-ExecutionTime-progress-bar { | |
| 0% { | |
| background-position: 0 0; | |
| } | |
| 100% { | |
| background-position: 40px 40px; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Variables | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-private-commandpalette-search-height: 28px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Overall styles | |
| |----------------------------------------------------------------------------*/ | |
| .lm-CommandPalette { | |
| padding-bottom: 0; | |
| color: var(--jp-ui-font-color1); | |
| background: var(--jp-layout-color1); | |
| /* This is needed so that all font sizing of children done in ems is | |
| * relative to this base size */ | |
| font-size: var(--jp-ui-font-size1); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Modal variant | |
| |----------------------------------------------------------------------------*/ | |
| .jp-ModalCommandPalette { | |
| position: absolute; | |
| z-index: 10000; | |
| top: 38px; | |
| left: 30%; | |
| margin: 0; | |
| padding: 4px; | |
| width: 40%; | |
| box-shadow: var(--jp-elevation-z4); | |
| border-radius: 4px; | |
| background: var(--jp-layout-color0); | |
| } | |
| .jp-ModalCommandPalette .lm-CommandPalette { | |
| max-height: 40vh; | |
| } | |
| .jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after { | |
| display: none; | |
| } | |
| .jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header { | |
| display: none; | |
| } | |
| .jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item { | |
| margin-left: 4px; | |
| margin-right: 4px; | |
| } | |
| .jp-ModalCommandPalette | |
| .lm-CommandPalette | |
| .lm-CommandPalette-item.lm-mod-disabled { | |
| display: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Search | |
| |----------------------------------------------------------------------------*/ | |
| .lm-CommandPalette-search { | |
| padding: 4px; | |
| background-color: var(--jp-layout-color1); | |
| z-index: 2; | |
| } | |
| .lm-CommandPalette-wrapper { | |
| overflow: overlay; | |
| padding: 0 9px; | |
| background-color: var(--jp-input-active-background); | |
| height: 30px; | |
| box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color); | |
| } | |
| .lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper { | |
| box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color), | |
| inset 0 0 0 3px var(--jp-input-active-box-shadow-color); | |
| } | |
| .jp-SearchIconGroup { | |
| color: white; | |
| background-color: var(--jp-brand-color1); | |
| position: absolute; | |
| top: 4px; | |
| right: 4px; | |
| padding: 5px 5px 1px; | |
| } | |
| .jp-SearchIconGroup svg { | |
| height: 20px; | |
| width: 20px; | |
| } | |
| .jp-SearchIconGroup .jp-icon3[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .lm-CommandPalette-input { | |
| background: transparent; | |
| width: calc(100% - 18px); | |
| float: left; | |
| border: none; | |
| outline: none; | |
| font-size: var(--jp-ui-font-size1); | |
| color: var(--jp-ui-font-color0); | |
| line-height: var(--jp-private-commandpalette-search-height); | |
| } | |
| .lm-CommandPalette-input::-webkit-input-placeholder, | |
| .lm-CommandPalette-input::-moz-placeholder, | |
| .lm-CommandPalette-input:-ms-input-placeholder { | |
| color: var(--jp-ui-font-color2); | |
| font-size: var(--jp-ui-font-size1); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Results | |
| |----------------------------------------------------------------------------*/ | |
| .lm-CommandPalette-header:first-child { | |
| margin-top: 0; | |
| } | |
| .lm-CommandPalette-header { | |
| border-bottom: solid var(--jp-border-width) var(--jp-border-color2); | |
| color: var(--jp-ui-font-color1); | |
| cursor: pointer; | |
| display: flex; | |
| font-size: var(--jp-ui-font-size0); | |
| font-weight: 600; | |
| letter-spacing: 1px; | |
| margin-top: 8px; | |
| padding: 8px 0 8px 12px; | |
| text-transform: uppercase; | |
| } | |
| .lm-CommandPalette-header.lm-mod-active { | |
| background: var(--jp-layout-color2); | |
| } | |
| .lm-CommandPalette-header > mark { | |
| background-color: transparent; | |
| font-weight: bold; | |
| color: var(--jp-ui-font-color1); | |
| } | |
| .lm-CommandPalette-item { | |
| padding: 4px 12px 4px 4px; | |
| color: var(--jp-ui-font-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| font-weight: 400; | |
| display: flex; | |
| } | |
| .lm-CommandPalette-item.lm-mod-disabled { | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .lm-CommandPalette-item.lm-mod-active { | |
| color: var(--jp-ui-inverse-font-color1); | |
| background: var(--jp-brand-color1); | |
| } | |
| .lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark { | |
| color: var(--jp-ui-inverse-font-color0); | |
| } | |
| .lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] { | |
| fill: var(--jp-layout-color0); | |
| } | |
| .lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) { | |
| color: var(--jp-ui-inverse-font-color1); | |
| background: var(--jp-brand-color1); | |
| } | |
| .lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) { | |
| background: var(--jp-layout-color2); | |
| } | |
| .lm-CommandPalette-itemContent { | |
| overflow: hidden; | |
| } | |
| .lm-CommandPalette-itemLabel > mark { | |
| color: var(--jp-ui-font-color0); | |
| background-color: transparent; | |
| font-weight: bold; | |
| } | |
| .lm-CommandPalette-item.lm-mod-disabled mark { | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .lm-CommandPalette-item .lm-CommandPalette-itemIcon { | |
| margin: 0 4px 0 0; | |
| position: relative; | |
| width: 16px; | |
| top: 2px; | |
| flex: 0 0 auto; | |
| } | |
| .lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon { | |
| opacity: 0.6; | |
| } | |
| .lm-CommandPalette-item .lm-CommandPalette-itemShortcut { | |
| flex: 0 0 auto; | |
| } | |
| .lm-CommandPalette-itemCaption { | |
| display: none; | |
| } | |
| .lm-CommandPalette-content { | |
| background-color: var(--jp-layout-color1); | |
| } | |
| .lm-CommandPalette-content:empty::after { | |
| content: 'No results'; | |
| margin: auto; | |
| margin-top: 20px; | |
| width: 100px; | |
| display: block; | |
| font-size: var(--jp-ui-font-size2); | |
| font-family: var(--jp-ui-font-family); | |
| font-weight: lighter; | |
| } | |
| .lm-CommandPalette-emptyMessage { | |
| text-align: center; | |
| margin-top: 24px; | |
| line-height: 1.32; | |
| padding: 0 8px; | |
| color: var(--jp-content-font-color3); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2017, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Dialog { | |
| position: absolute; | |
| z-index: 10000; | |
| display: flex; | |
| flex-direction: column; | |
| align-items: center; | |
| justify-content: center; | |
| top: 0; | |
| left: 0; | |
| margin: 0; | |
| padding: 0; | |
| width: 100%; | |
| height: 100%; | |
| background: var(--jp-dialog-background); | |
| } | |
| .jp-Dialog-content { | |
| display: flex; | |
| flex-direction: column; | |
| margin-left: auto; | |
| margin-right: auto; | |
| background: var(--jp-layout-color1); | |
| padding: 24px 24px 12px; | |
| min-width: 300px; | |
| min-height: 150px; | |
| max-width: 1000px; | |
| max-height: 500px; | |
| box-sizing: border-box; | |
| box-shadow: var(--jp-elevation-z20); | |
| word-wrap: break-word; | |
| border-radius: var(--jp-border-radius); | |
| /* This is needed so that all font sizing of children done in ems is | |
| * relative to this base size */ | |
| font-size: var(--jp-ui-font-size1); | |
| color: var(--jp-ui-font-color1); | |
| resize: both; | |
| } | |
| .jp-Dialog-content.jp-Dialog-content-small { | |
| max-width: 500px; | |
| } | |
| .jp-Dialog-button { | |
| overflow: visible; | |
| } | |
| button.jp-Dialog-button:focus { | |
| outline: 1px solid var(--jp-brand-color1); | |
| outline-offset: 4px; | |
| -moz-outline-radius: 0; | |
| } | |
| button.jp-Dialog-button:focus::-moz-focus-inner { | |
| border: 0; | |
| } | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus, | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus, | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus { | |
| outline-offset: 4px; | |
| -moz-outline-radius: 0; | |
| } | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus { | |
| outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1)); | |
| } | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus { | |
| outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1)); | |
| } | |
| button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus { | |
| outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600)); | |
| } | |
| button.jp-Dialog-close-button { | |
| padding: 0; | |
| height: 100%; | |
| min-width: unset; | |
| min-height: unset; | |
| } | |
| .jp-Dialog-header { | |
| display: flex; | |
| justify-content: space-between; | |
| flex: 0 0 auto; | |
| padding-bottom: 12px; | |
| font-size: var(--jp-ui-font-size3); | |
| font-weight: 400; | |
| color: var(--jp-ui-font-color1); | |
| } | |
| .jp-Dialog-body { | |
| display: flex; | |
| flex-direction: column; | |
| flex: 1 1 auto; | |
| font-size: var(--jp-ui-font-size1); | |
| background: var(--jp-layout-color1); | |
| color: var(--jp-ui-font-color1); | |
| overflow: auto; | |
| } | |
| .jp-Dialog-footer { | |
| display: flex; | |
| flex-direction: row; | |
| justify-content: flex-end; | |
| align-items: center; | |
| flex: 0 0 auto; | |
| margin-left: -12px; | |
| margin-right: -12px; | |
| padding: 12px; | |
| } | |
| .jp-Dialog-checkbox { | |
| padding-right: 5px; | |
| } | |
| .jp-Dialog-checkbox > input:focus-visible { | |
| outline: 1px solid var(--jp-input-active-border-color); | |
| outline-offset: 1px; | |
| } | |
| .jp-Dialog-spacer { | |
| flex: 1 1 auto; | |
| } | |
| .jp-Dialog-title { | |
| overflow: hidden; | |
| white-space: nowrap; | |
| text-overflow: ellipsis; | |
| } | |
| .jp-Dialog-body > .jp-select-wrapper { | |
| width: 100%; | |
| } | |
| .jp-Dialog-body > button { | |
| padding: 0 16px; | |
| } | |
| .jp-Dialog-body > label { | |
| line-height: 1.4; | |
| color: var(--jp-ui-font-color0); | |
| } | |
| .jp-Dialog-button.jp-mod-styled:not(:last-child) { | |
| margin-right: 12px; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .jp-Input-Boolean-Dialog { | |
| flex-direction: row-reverse; | |
| align-items: end; | |
| width: 100%; | |
| } | |
| .jp-Input-Boolean-Dialog > label { | |
| flex: 1 1 auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2016, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-MainAreaWidget > :focus { | |
| outline: none; | |
| } | |
| .jp-MainAreaWidget .jp-MainAreaWidget-error { | |
| padding: 6px; | |
| } | |
| .jp-MainAreaWidget .jp-MainAreaWidget-error > pre { | |
| width: auto; | |
| padding: 10px; | |
| background: var(--jp-error-color3); | |
| border: var(--jp-border-width) solid var(--jp-error-color1); | |
| border-radius: var(--jp-border-radius); | |
| color: var(--jp-ui-font-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| white-space: pre-wrap; | |
| word-wrap: break-word; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| /** | |
| * google-material-color v1.2.6 | |
| * https://github.com/danlevan/google-material-color | |
| */ | |
| :root { | |
| --md-red-50: #ffebee; | |
| --md-red-100: #ffcdd2; | |
| --md-red-200: #ef9a9a; | |
| --md-red-300: #e57373; | |
| --md-red-400: #ef5350; | |
| --md-red-500: #f44336; | |
| --md-red-600: #e53935; | |
| --md-red-700: #d32f2f; | |
| --md-red-800: #c62828; | |
| --md-red-900: #b71c1c; | |
| --md-red-A100: #ff8a80; | |
| --md-red-A200: #ff5252; | |
| --md-red-A400: #ff1744; | |
| --md-red-A700: #d50000; | |
| --md-pink-50: #fce4ec; | |
| --md-pink-100: #f8bbd0; | |
| --md-pink-200: #f48fb1; | |
| --md-pink-300: #f06292; | |
| --md-pink-400: #ec407a; | |
| --md-pink-500: #e91e63; | |
| --md-pink-600: #d81b60; | |
| --md-pink-700: #c2185b; | |
| --md-pink-800: #ad1457; | |
| --md-pink-900: #880e4f; | |
| --md-pink-A100: #ff80ab; | |
| --md-pink-A200: #ff4081; | |
| --md-pink-A400: #f50057; | |
| --md-pink-A700: #c51162; | |
| --md-purple-50: #f3e5f5; | |
| --md-purple-100: #e1bee7; | |
| --md-purple-200: #ce93d8; | |
| --md-purple-300: #ba68c8; | |
| --md-purple-400: #ab47bc; | |
| --md-purple-500: #9c27b0; | |
| --md-purple-600: #8e24aa; | |
| --md-purple-700: #7b1fa2; | |
| --md-purple-800: #6a1b9a; | |
| --md-purple-900: #4a148c; | |
| --md-purple-A100: #ea80fc; | |
| --md-purple-A200: #e040fb; | |
| --md-purple-A400: #d500f9; | |
| --md-purple-A700: #a0f; | |
| --md-deep-purple-50: #ede7f6; | |
| --md-deep-purple-100: #d1c4e9; | |
| --md-deep-purple-200: #b39ddb; | |
| --md-deep-purple-300: #9575cd; | |
| --md-deep-purple-400: #7e57c2; | |
| --md-deep-purple-500: #673ab7; | |
| --md-deep-purple-600: #5e35b1; | |
| --md-deep-purple-700: #512da8; | |
| --md-deep-purple-800: #4527a0; | |
| --md-deep-purple-900: #311b92; | |
| --md-deep-purple-A100: #b388ff; | |
| --md-deep-purple-A200: #7c4dff; | |
| --md-deep-purple-A400: #651fff; | |
| --md-deep-purple-A700: #6200ea; | |
| --md-indigo-50: #e8eaf6; | |
| --md-indigo-100: #c5cae9; | |
| --md-indigo-200: #9fa8da; | |
| --md-indigo-300: #7986cb; | |
| --md-indigo-400: #5c6bc0; | |
| --md-indigo-500: #3f51b5; | |
| --md-indigo-600: #3949ab; | |
| --md-indigo-700: #303f9f; | |
| --md-indigo-800: #283593; | |
| --md-indigo-900: #1a237e; | |
| --md-indigo-A100: #8c9eff; | |
| --md-indigo-A200: #536dfe; | |
| --md-indigo-A400: #3d5afe; | |
| --md-indigo-A700: #304ffe; | |
| --md-blue-50: #e3f2fd; | |
| --md-blue-100: #bbdefb; | |
| --md-blue-200: #90caf9; | |
| --md-blue-300: #64b5f6; | |
| --md-blue-400: #42a5f5; | |
| --md-blue-500: #2196f3; | |
| --md-blue-600: #1e88e5; | |
| --md-blue-700: #1976d2; | |
| --md-blue-800: #1565c0; | |
| --md-blue-900: #0d47a1; | |
| --md-blue-A100: #82b1ff; | |
| --md-blue-A200: #448aff; | |
| --md-blue-A400: #2979ff; | |
| --md-blue-A700: #2962ff; | |
| --md-light-blue-50: #e1f5fe; | |
| --md-light-blue-100: #b3e5fc; | |
| --md-light-blue-200: #81d4fa; | |
| --md-light-blue-300: #4fc3f7; | |
| --md-light-blue-400: #29b6f6; | |
| --md-light-blue-500: #03a9f4; | |
| --md-light-blue-600: #039be5; | |
| --md-light-blue-700: #0288d1; | |
| --md-light-blue-800: #0277bd; | |
| --md-light-blue-900: #01579b; | |
| --md-light-blue-A100: #80d8ff; | |
| --md-light-blue-A200: #40c4ff; | |
| --md-light-blue-A400: #00b0ff; | |
| --md-light-blue-A700: #0091ea; | |
| --md-cyan-50: #e0f7fa; | |
| --md-cyan-100: #b2ebf2; | |
| --md-cyan-200: #80deea; | |
| --md-cyan-300: #4dd0e1; | |
| --md-cyan-400: #26c6da; | |
| --md-cyan-500: #00bcd4; | |
| --md-cyan-600: #00acc1; | |
| --md-cyan-700: #0097a7; | |
| --md-cyan-800: #00838f; | |
| --md-cyan-900: #006064; | |
| --md-cyan-A100: #84ffff; | |
| --md-cyan-A200: #18ffff; | |
| --md-cyan-A400: #00e5ff; | |
| --md-cyan-A700: #00b8d4; | |
| --md-teal-50: #e0f2f1; | |
| --md-teal-100: #b2dfdb; | |
| --md-teal-200: #80cbc4; | |
| --md-teal-300: #4db6ac; | |
| --md-teal-400: #26a69a; | |
| --md-teal-500: #009688; | |
| --md-teal-600: #00897b; | |
| --md-teal-700: #00796b; | |
| --md-teal-800: #00695c; | |
| --md-teal-900: #004d40; | |
| --md-teal-A100: #a7ffeb; | |
| --md-teal-A200: #64ffda; | |
| --md-teal-A400: #1de9b6; | |
| --md-teal-A700: #00bfa5; | |
| --md-green-50: #e8f5e9; | |
| --md-green-100: #c8e6c9; | |
| --md-green-200: #a5d6a7; | |
| --md-green-300: #81c784; | |
| --md-green-400: #66bb6a; | |
| --md-green-500: #4caf50; | |
| --md-green-600: #43a047; | |
| --md-green-700: #388e3c; | |
| --md-green-800: #2e7d32; | |
| --md-green-900: #1b5e20; | |
| --md-green-A100: #b9f6ca; | |
| --md-green-A200: #69f0ae; | |
| --md-green-A400: #00e676; | |
| --md-green-A700: #00c853; | |
| --md-light-green-50: #f1f8e9; | |
| --md-light-green-100: #dcedc8; | |
| --md-light-green-200: #c5e1a5; | |
| --md-light-green-300: #aed581; | |
| --md-light-green-400: #9ccc65; | |
| --md-light-green-500: #8bc34a; | |
| --md-light-green-600: #7cb342; | |
| --md-light-green-700: #689f38; | |
| --md-light-green-800: #558b2f; | |
| --md-light-green-900: #33691e; | |
| --md-light-green-A100: #ccff90; | |
| --md-light-green-A200: #b2ff59; | |
| --md-light-green-A400: #76ff03; | |
| --md-light-green-A700: #64dd17; | |
| --md-lime-50: #f9fbe7; | |
| --md-lime-100: #f0f4c3; | |
| --md-lime-200: #e6ee9c; | |
| --md-lime-300: #dce775; | |
| --md-lime-400: #d4e157; | |
| --md-lime-500: #cddc39; | |
| --md-lime-600: #c0ca33; | |
| --md-lime-700: #afb42b; | |
| --md-lime-800: #9e9d24; | |
| --md-lime-900: #827717; | |
| --md-lime-A100: #f4ff81; | |
| --md-lime-A200: #eeff41; | |
| --md-lime-A400: #c6ff00; | |
| --md-lime-A700: #aeea00; | |
| --md-yellow-50: #fffde7; | |
| --md-yellow-100: #fff9c4; | |
| --md-yellow-200: #fff59d; | |
| --md-yellow-300: #fff176; | |
| --md-yellow-400: #ffee58; | |
| --md-yellow-500: #ffeb3b; | |
| --md-yellow-600: #fdd835; | |
| --md-yellow-700: #fbc02d; | |
| --md-yellow-800: #f9a825; | |
| --md-yellow-900: #f57f17; | |
| --md-yellow-A100: #ffff8d; | |
| --md-yellow-A200: #ff0; | |
| --md-yellow-A400: #ffea00; | |
| --md-yellow-A700: #ffd600; | |
| --md-amber-50: #fff8e1; | |
| --md-amber-100: #ffecb3; | |
| --md-amber-200: #ffe082; | |
| --md-amber-300: #ffd54f; | |
| --md-amber-400: #ffca28; | |
| --md-amber-500: #ffc107; | |
| --md-amber-600: #ffb300; | |
| --md-amber-700: #ffa000; | |
| --md-amber-800: #ff8f00; | |
| --md-amber-900: #ff6f00; | |
| --md-amber-A100: #ffe57f; | |
| --md-amber-A200: #ffd740; | |
| --md-amber-A400: #ffc400; | |
| --md-amber-A700: #ffab00; | |
| --md-orange-50: #fff3e0; | |
| --md-orange-100: #ffe0b2; | |
| --md-orange-200: #ffcc80; | |
| --md-orange-300: #ffb74d; | |
| --md-orange-400: #ffa726; | |
| --md-orange-500: #ff9800; | |
| --md-orange-600: #fb8c00; | |
| --md-orange-700: #f57c00; | |
| --md-orange-800: #ef6c00; | |
| --md-orange-900: #e65100; | |
| --md-orange-A100: #ffd180; | |
| --md-orange-A200: #ffab40; | |
| --md-orange-A400: #ff9100; | |
| --md-orange-A700: #ff6d00; | |
| --md-deep-orange-50: #fbe9e7; | |
| --md-deep-orange-100: #ffccbc; | |
| --md-deep-orange-200: #ffab91; | |
| --md-deep-orange-300: #ff8a65; | |
| --md-deep-orange-400: #ff7043; | |
| --md-deep-orange-500: #ff5722; | |
| --md-deep-orange-600: #f4511e; | |
| --md-deep-orange-700: #e64a19; | |
| --md-deep-orange-800: #d84315; | |
| --md-deep-orange-900: #bf360c; | |
| --md-deep-orange-A100: #ff9e80; | |
| --md-deep-orange-A200: #ff6e40; | |
| --md-deep-orange-A400: #ff3d00; | |
| --md-deep-orange-A700: #dd2c00; | |
| --md-brown-50: #efebe9; | |
| --md-brown-100: #d7ccc8; | |
| --md-brown-200: #bcaaa4; | |
| --md-brown-300: #a1887f; | |
| --md-brown-400: #8d6e63; | |
| --md-brown-500: #795548; | |
| --md-brown-600: #6d4c41; | |
| --md-brown-700: #5d4037; | |
| --md-brown-800: #4e342e; | |
| --md-brown-900: #3e2723; | |
| --md-grey-50: #fafafa; | |
| --md-grey-100: #f5f5f5; | |
| --md-grey-200: #eee; | |
| --md-grey-300: #e0e0e0; | |
| --md-grey-400: #bdbdbd; | |
| --md-grey-500: #9e9e9e; | |
| --md-grey-600: #757575; | |
| --md-grey-700: #616161; | |
| --md-grey-800: #424242; | |
| --md-grey-900: #212121; | |
| --md-blue-grey-50: #eceff1; | |
| --md-blue-grey-100: #cfd8dc; | |
| --md-blue-grey-200: #b0bec5; | |
| --md-blue-grey-300: #90a4ae; | |
| --md-blue-grey-400: #78909c; | |
| --md-blue-grey-500: #607d8b; | |
| --md-blue-grey-600: #546e7a; | |
| --md-blue-grey-700: #455a64; | |
| --md-blue-grey-800: #37474f; | |
| --md-blue-grey-900: #263238; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2017, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | RenderedText | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| /* This is the padding value to fill the gaps between lines containing spans with background color. */ | |
| --jp-private-code-span-padding: calc( | |
| (var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2 | |
| ); | |
| } | |
| .jp-RenderedText { | |
| text-align: left; | |
| padding-left: var(--jp-code-padding); | |
| line-height: var(--jp-code-line-height); | |
| font-family: var(--jp-code-font-family); | |
| } | |
| .jp-RenderedText pre, | |
| .jp-RenderedJavaScript pre, | |
| .jp-RenderedHTMLCommon pre { | |
| color: var(--jp-content-font-color1); | |
| font-size: var(--jp-code-font-size); | |
| border: none; | |
| margin: 0; | |
| padding: 0; | |
| } | |
| .jp-RenderedText pre a:link { | |
| text-decoration: none; | |
| color: var(--jp-content-link-color); | |
| } | |
| .jp-RenderedText pre a:hover { | |
| text-decoration: underline; | |
| color: var(--jp-content-link-color); | |
| } | |
| .jp-RenderedText pre a:visited { | |
| text-decoration: none; | |
| color: var(--jp-content-link-color); | |
| } | |
| /* console foregrounds and backgrounds */ | |
| .jp-RenderedText pre .ansi-black-fg { | |
| color: #3e424d; | |
| } | |
| .jp-RenderedText pre .ansi-red-fg { | |
| color: #e75c58; | |
| } | |
| .jp-RenderedText pre .ansi-green-fg { | |
| color: #00a250; | |
| } | |
| .jp-RenderedText pre .ansi-yellow-fg { | |
| color: #ddb62b; | |
| } | |
| .jp-RenderedText pre .ansi-blue-fg { | |
| color: #208ffb; | |
| } | |
| .jp-RenderedText pre .ansi-magenta-fg { | |
| color: #d160c4; | |
| } | |
| .jp-RenderedText pre .ansi-cyan-fg { | |
| color: #60c6c8; | |
| } | |
| .jp-RenderedText pre .ansi-white-fg { | |
| color: #c5c1b4; | |
| } | |
| .jp-RenderedText pre .ansi-black-bg { | |
| background-color: #3e424d; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-red-bg { | |
| background-color: #e75c58; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-green-bg { | |
| background-color: #00a250; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-yellow-bg { | |
| background-color: #ddb62b; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-blue-bg { | |
| background-color: #208ffb; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-magenta-bg { | |
| background-color: #d160c4; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-cyan-bg { | |
| background-color: #60c6c8; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-white-bg { | |
| background-color: #c5c1b4; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-black-intense-fg { | |
| color: #282c36; | |
| } | |
| .jp-RenderedText pre .ansi-red-intense-fg { | |
| color: #b22b31; | |
| } | |
| .jp-RenderedText pre .ansi-green-intense-fg { | |
| color: #007427; | |
| } | |
| .jp-RenderedText pre .ansi-yellow-intense-fg { | |
| color: #b27d12; | |
| } | |
| .jp-RenderedText pre .ansi-blue-intense-fg { | |
| color: #0065ca; | |
| } | |
| .jp-RenderedText pre .ansi-magenta-intense-fg { | |
| color: #a03196; | |
| } | |
| .jp-RenderedText pre .ansi-cyan-intense-fg { | |
| color: #258f8f; | |
| } | |
| .jp-RenderedText pre .ansi-white-intense-fg { | |
| color: #a1a6b2; | |
| } | |
| .jp-RenderedText pre .ansi-black-intense-bg { | |
| background-color: #282c36; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-red-intense-bg { | |
| background-color: #b22b31; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-green-intense-bg { | |
| background-color: #007427; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-yellow-intense-bg { | |
| background-color: #b27d12; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-blue-intense-bg { | |
| background-color: #0065ca; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-magenta-intense-bg { | |
| background-color: #a03196; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-cyan-intense-bg { | |
| background-color: #258f8f; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-white-intense-bg { | |
| background-color: #a1a6b2; | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-default-inverse-fg { | |
| color: var(--jp-ui-inverse-font-color0); | |
| } | |
| .jp-RenderedText pre .ansi-default-inverse-bg { | |
| background-color: var(--jp-inverse-layout-color0); | |
| padding: var(--jp-private-code-span-padding) 0; | |
| } | |
| .jp-RenderedText pre .ansi-bold { | |
| font-weight: bold; | |
| } | |
| .jp-RenderedText pre .ansi-underline { | |
| text-decoration: underline; | |
| } | |
| .jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] { | |
| background: var(--jp-rendermime-error-background); | |
| padding-top: var(--jp-code-padding); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | RenderedLatex | |
| |----------------------------------------------------------------------------*/ | |
| .jp-RenderedLatex { | |
| color: var(--jp-content-font-color1); | |
| font-size: var(--jp-content-font-size1); | |
| line-height: var(--jp-content-line-height); | |
| } | |
| /* Left-justify outputs.*/ | |
| .jp-OutputArea-output.jp-RenderedLatex { | |
| padding: var(--jp-code-padding); | |
| text-align: left; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | RenderedHTML | |
| |----------------------------------------------------------------------------*/ | |
| .jp-RenderedHTMLCommon { | |
| color: var(--jp-content-font-color1); | |
| font-family: var(--jp-content-font-family); | |
| font-size: var(--jp-content-font-size1); | |
| line-height: var(--jp-content-line-height); | |
| /* Give a bit more R padding on Markdown text to keep line lengths reasonable */ | |
| padding-right: 20px; | |
| } | |
| .jp-RenderedHTMLCommon em { | |
| font-style: italic; | |
| } | |
| .jp-RenderedHTMLCommon strong { | |
| font-weight: bold; | |
| } | |
| .jp-RenderedHTMLCommon u { | |
| text-decoration: underline; | |
| } | |
| .jp-RenderedHTMLCommon a:link { | |
| text-decoration: none; | |
| color: var(--jp-content-link-color); | |
| } | |
| .jp-RenderedHTMLCommon a:hover { | |
| text-decoration: underline; | |
| color: var(--jp-content-link-color); | |
| } | |
| .jp-RenderedHTMLCommon a:visited { | |
| text-decoration: none; | |
| color: var(--jp-content-link-color); | |
| } | |
| /* Headings */ | |
| .jp-RenderedHTMLCommon h1, | |
| .jp-RenderedHTMLCommon h2, | |
| .jp-RenderedHTMLCommon h3, | |
| .jp-RenderedHTMLCommon h4, | |
| .jp-RenderedHTMLCommon h5, | |
| .jp-RenderedHTMLCommon h6 { | |
| line-height: var(--jp-content-heading-line-height); | |
| font-weight: var(--jp-content-heading-font-weight); | |
| font-style: normal; | |
| margin: var(--jp-content-heading-margin-top) 0 | |
| var(--jp-content-heading-margin-bottom) 0; | |
| } | |
| .jp-RenderedHTMLCommon h1:first-child, | |
| .jp-RenderedHTMLCommon h2:first-child, | |
| .jp-RenderedHTMLCommon h3:first-child, | |
| .jp-RenderedHTMLCommon h4:first-child, | |
| .jp-RenderedHTMLCommon h5:first-child, | |
| .jp-RenderedHTMLCommon h6:first-child { | |
| margin-top: calc(0.5 * var(--jp-content-heading-margin-top)); | |
| } | |
| .jp-RenderedHTMLCommon h1:last-child, | |
| .jp-RenderedHTMLCommon h2:last-child, | |
| .jp-RenderedHTMLCommon h3:last-child, | |
| .jp-RenderedHTMLCommon h4:last-child, | |
| .jp-RenderedHTMLCommon h5:last-child, | |
| .jp-RenderedHTMLCommon h6:last-child { | |
| margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom)); | |
| } | |
| .jp-RenderedHTMLCommon h1 { | |
| font-size: var(--jp-content-font-size5); | |
| } | |
| .jp-RenderedHTMLCommon h2 { | |
| font-size: var(--jp-content-font-size4); | |
| } | |
| .jp-RenderedHTMLCommon h3 { | |
| font-size: var(--jp-content-font-size3); | |
| } | |
| .jp-RenderedHTMLCommon h4 { | |
| font-size: var(--jp-content-font-size2); | |
| } | |
| .jp-RenderedHTMLCommon h5 { | |
| font-size: var(--jp-content-font-size1); | |
| } | |
| .jp-RenderedHTMLCommon h6 { | |
| font-size: var(--jp-content-font-size0); | |
| } | |
| /* Lists */ | |
| /* stylelint-disable selector-max-type, selector-max-compound-selectors */ | |
| .jp-RenderedHTMLCommon ul:not(.list-inline), | |
| .jp-RenderedHTMLCommon ol:not(.list-inline) { | |
| padding-left: 2em; | |
| } | |
| .jp-RenderedHTMLCommon ul { | |
| list-style: disc; | |
| } | |
| .jp-RenderedHTMLCommon ul ul { | |
| list-style: square; | |
| } | |
| .jp-RenderedHTMLCommon ul ul ul { | |
| list-style: circle; | |
| } | |
| .jp-RenderedHTMLCommon ol { | |
| list-style: decimal; | |
| } | |
| .jp-RenderedHTMLCommon ol ol { | |
| list-style: upper-alpha; | |
| } | |
| .jp-RenderedHTMLCommon ol ol ol { | |
| list-style: lower-alpha; | |
| } | |
| .jp-RenderedHTMLCommon ol ol ol ol { | |
| list-style: lower-roman; | |
| } | |
| .jp-RenderedHTMLCommon ol ol ol ol ol { | |
| list-style: decimal; | |
| } | |
| .jp-RenderedHTMLCommon ol, | |
| .jp-RenderedHTMLCommon ul { | |
| margin-bottom: 1em; | |
| } | |
| .jp-RenderedHTMLCommon ul ul, | |
| .jp-RenderedHTMLCommon ul ol, | |
| .jp-RenderedHTMLCommon ol ul, | |
| .jp-RenderedHTMLCommon ol ol { | |
| margin-bottom: 0; | |
| } | |
| /* stylelint-enable selector-max-type, selector-max-compound-selectors */ | |
| .jp-RenderedHTMLCommon hr { | |
| color: var(--jp-border-color2); | |
| background-color: var(--jp-border-color1); | |
| margin-top: 1em; | |
| margin-bottom: 1em; | |
| } | |
| .jp-RenderedHTMLCommon > pre { | |
| margin: 1.5em 2em; | |
| } | |
| .jp-RenderedHTMLCommon pre, | |
| .jp-RenderedHTMLCommon code { | |
| border: 0; | |
| background-color: var(--jp-layout-color0); | |
| color: var(--jp-content-font-color1); | |
| font-family: var(--jp-code-font-family); | |
| font-size: inherit; | |
| line-height: var(--jp-code-line-height); | |
| padding: 0; | |
| white-space: pre-wrap; | |
| } | |
| .jp-RenderedHTMLCommon :not(pre) > code { | |
| background-color: var(--jp-layout-color2); | |
| padding: 1px 5px; | |
| } | |
| /* Tables */ | |
| .jp-RenderedHTMLCommon table { | |
| border-collapse: collapse; | |
| border-spacing: 0; | |
| border: none; | |
| color: var(--jp-ui-font-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| table-layout: fixed; | |
| margin-left: auto; | |
| margin-bottom: 1em; | |
| margin-right: auto; | |
| } | |
| .jp-RenderedHTMLCommon thead { | |
| border-bottom: var(--jp-border-width) solid var(--jp-border-color1); | |
| vertical-align: bottom; | |
| } | |
| .jp-RenderedHTMLCommon td, | |
| .jp-RenderedHTMLCommon th, | |
| .jp-RenderedHTMLCommon tr { | |
| vertical-align: middle; | |
| padding: 0.5em; | |
| line-height: normal; | |
| white-space: normal; | |
| max-width: none; | |
| border: none; | |
| } | |
| .jp-RenderedMarkdown.jp-RenderedHTMLCommon td, | |
| .jp-RenderedMarkdown.jp-RenderedHTMLCommon th { | |
| max-width: none; | |
| } | |
| :not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td, | |
| :not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th, | |
| :not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr { | |
| text-align: right; | |
| } | |
| .jp-RenderedHTMLCommon th { | |
| font-weight: bold; | |
| } | |
| .jp-RenderedHTMLCommon tbody tr:nth-child(odd) { | |
| background: var(--jp-layout-color0); | |
| } | |
| .jp-RenderedHTMLCommon tbody tr:nth-child(even) { | |
| background: var(--jp-rendermime-table-row-background); | |
| } | |
| .jp-RenderedHTMLCommon tbody tr:hover { | |
| background: var(--jp-rendermime-table-row-hover-background); | |
| } | |
| .jp-RenderedHTMLCommon p { | |
| text-align: left; | |
| margin: 0; | |
| margin-bottom: 1em; | |
| } | |
| .jp-RenderedHTMLCommon img { | |
| -moz-force-broken-image-icon: 1; | |
| } | |
| /* Restrict to direct children as other images could be nested in other content. */ | |
| .jp-RenderedHTMLCommon > img { | |
| display: block; | |
| margin-left: 0; | |
| margin-right: 0; | |
| margin-bottom: 1em; | |
| } | |
| /* Change color behind transparent images if they need it... */ | |
| [data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background { | |
| background-color: var(--jp-inverse-layout-color1); | |
| } | |
| [data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background { | |
| background-color: var(--jp-inverse-layout-color1); | |
| } | |
| .jp-RenderedHTMLCommon img, | |
| .jp-RenderedImage img, | |
| .jp-RenderedHTMLCommon svg, | |
| .jp-RenderedSVG svg { | |
| max-width: 100%; | |
| height: auto; | |
| } | |
| .jp-RenderedHTMLCommon img.jp-mod-unconfined, | |
| .jp-RenderedImage img.jp-mod-unconfined, | |
| .jp-RenderedHTMLCommon svg.jp-mod-unconfined, | |
| .jp-RenderedSVG svg.jp-mod-unconfined { | |
| max-width: none; | |
| } | |
| .jp-RenderedHTMLCommon .alert { | |
| padding: var(--jp-notebook-padding); | |
| border: var(--jp-border-width) solid transparent; | |
| border-radius: var(--jp-border-radius); | |
| margin-bottom: 1em; | |
| } | |
| .jp-RenderedHTMLCommon .alert-info { | |
| color: var(--jp-info-color0); | |
| background-color: var(--jp-info-color3); | |
| border-color: var(--jp-info-color2); | |
| } | |
| .jp-RenderedHTMLCommon .alert-info hr { | |
| border-color: var(--jp-info-color3); | |
| } | |
| .jp-RenderedHTMLCommon .alert-info > p:last-child, | |
| .jp-RenderedHTMLCommon .alert-info > ul:last-child { | |
| margin-bottom: 0; | |
| } | |
| .jp-RenderedHTMLCommon .alert-warning { | |
| color: var(--jp-warn-color0); | |
| background-color: var(--jp-warn-color3); | |
| border-color: var(--jp-warn-color2); | |
| } | |
| .jp-RenderedHTMLCommon .alert-warning hr { | |
| border-color: var(--jp-warn-color3); | |
| } | |
| .jp-RenderedHTMLCommon .alert-warning > p:last-child, | |
| .jp-RenderedHTMLCommon .alert-warning > ul:last-child { | |
| margin-bottom: 0; | |
| } | |
| .jp-RenderedHTMLCommon .alert-success { | |
| color: var(--jp-success-color0); | |
| background-color: var(--jp-success-color3); | |
| border-color: var(--jp-success-color2); | |
| } | |
| .jp-RenderedHTMLCommon .alert-success hr { | |
| border-color: var(--jp-success-color3); | |
| } | |
| .jp-RenderedHTMLCommon .alert-success > p:last-child, | |
| .jp-RenderedHTMLCommon .alert-success > ul:last-child { | |
| margin-bottom: 0; | |
| } | |
| .jp-RenderedHTMLCommon .alert-danger { | |
| color: var(--jp-error-color0); | |
| background-color: var(--jp-error-color3); | |
| border-color: var(--jp-error-color2); | |
| } | |
| .jp-RenderedHTMLCommon .alert-danger hr { | |
| border-color: var(--jp-error-color3); | |
| } | |
| .jp-RenderedHTMLCommon .alert-danger > p:last-child, | |
| .jp-RenderedHTMLCommon .alert-danger > ul:last-child { | |
| margin-bottom: 0; | |
| } | |
| .jp-RenderedHTMLCommon blockquote { | |
| margin: 1em 2em; | |
| padding: 0 1em; | |
| border-left: 5px solid var(--jp-border-color2); | |
| } | |
| a.jp-InternalAnchorLink { | |
| visibility: hidden; | |
| margin-left: 8px; | |
| color: var(--md-blue-800); | |
| } | |
| h1:hover .jp-InternalAnchorLink, | |
| h2:hover .jp-InternalAnchorLink, | |
| h3:hover .jp-InternalAnchorLink, | |
| h4:hover .jp-InternalAnchorLink, | |
| h5:hover .jp-InternalAnchorLink, | |
| h6:hover .jp-InternalAnchorLink { | |
| visibility: visible; | |
| } | |
| .jp-RenderedHTMLCommon kbd { | |
| background-color: var(--jp-rendermime-table-row-background); | |
| border: 1px solid var(--jp-border-color0); | |
| border-bottom-color: var(--jp-border-color2); | |
| border-radius: 3px; | |
| box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25); | |
| display: inline-block; | |
| font-size: var(--jp-ui-font-size0); | |
| line-height: 1em; | |
| padding: 0.2em 0.5em; | |
| } | |
| /* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0. | |
| * At the bottom of cells this is a bit too much as there is also spacing | |
| * between cells. Going all the way to 0 gets too tight between markdown and | |
| * code cells. | |
| */ | |
| .jp-RenderedHTMLCommon > *:last-child { | |
| margin-bottom: 0.5em; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Copyright (c) 2014-2017, PhosphorJS Contributors | |
| | | |
| | Distributed under the terms of the BSD 3-Clause License. | |
| | | |
| | The full license is in the file LICENSE, distributed with this software. | |
| |----------------------------------------------------------------------------*/ | |
| .lm-cursor-backdrop { | |
| position: fixed; | |
| width: 200px; | |
| height: 200px; | |
| margin-top: -100px; | |
| margin-left: -100px; | |
| will-change: transform; | |
| z-index: 100; | |
| } | |
| .lm-mod-drag-image { | |
| will-change: transform; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .jp-lineFormSearch { | |
| padding: 4px 12px; | |
| background-color: var(--jp-layout-color2); | |
| box-shadow: var(--jp-toolbar-box-shadow); | |
| z-index: 2; | |
| font-size: var(--jp-ui-font-size1); | |
| } | |
| .jp-lineFormCaption { | |
| font-size: var(--jp-ui-font-size0); | |
| line-height: var(--jp-ui-font-size1); | |
| margin-top: 4px; | |
| color: var(--jp-ui-font-color0); | |
| } | |
| .jp-baseLineForm { | |
| border: none; | |
| border-radius: 0; | |
| position: absolute; | |
| background-size: 16px; | |
| background-repeat: no-repeat; | |
| background-position: center; | |
| outline: none; | |
| } | |
| .jp-lineFormButtonContainer { | |
| top: 4px; | |
| right: 8px; | |
| height: 24px; | |
| padding: 0 12px; | |
| width: 12px; | |
| } | |
| .jp-lineFormButtonIcon { | |
| top: 0; | |
| right: 0; | |
| background-color: var(--jp-brand-color1); | |
| height: 100%; | |
| width: 100%; | |
| box-sizing: border-box; | |
| padding: 4px 6px; | |
| } | |
| .jp-lineFormButton { | |
| top: 0; | |
| right: 0; | |
| background-color: transparent; | |
| height: 100%; | |
| width: 100%; | |
| box-sizing: border-box; | |
| } | |
| .jp-lineFormWrapper { | |
| overflow: hidden; | |
| padding: 0 8px; | |
| border: 1px solid var(--jp-border-color0); | |
| background-color: var(--jp-input-active-background); | |
| height: 22px; | |
| } | |
| .jp-lineFormWrapperFocusWithin { | |
| border: var(--jp-border-width) solid var(--md-blue-500); | |
| box-shadow: inset 0 0 4px var(--md-blue-300); | |
| } | |
| .jp-lineFormInput { | |
| background: transparent; | |
| width: 200px; | |
| height: 100%; | |
| border: none; | |
| outline: none; | |
| color: var(--jp-ui-font-color0); | |
| line-height: 28px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) 2014-2016, Jupyter Development Team. | |
| | | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-JSONEditor { | |
| display: flex; | |
| flex-direction: column; | |
| width: 100%; | |
| } | |
| .jp-JSONEditor-host { | |
| flex: 1 1 auto; | |
| border: var(--jp-border-width) solid var(--jp-input-border-color); | |
| border-radius: 0; | |
| background: var(--jp-layout-color0); | |
| min-height: 50px; | |
| padding: 1px; | |
| } | |
| .jp-JSONEditor.jp-mod-error .jp-JSONEditor-host { | |
| border-color: red; | |
| outline-color: red; | |
| } | |
| .jp-JSONEditor-header { | |
| display: flex; | |
| flex: 1 0 auto; | |
| padding: 0 0 0 12px; | |
| } | |
| .jp-JSONEditor-header label { | |
| flex: 0 0 auto; | |
| } | |
| .jp-JSONEditor-commitButton { | |
| height: 16px; | |
| width: 16px; | |
| background-size: 18px; | |
| background-repeat: no-repeat; | |
| background-position: center; | |
| } | |
| .jp-JSONEditor-host.jp-mod-focused { | |
| background-color: var(--jp-input-active-background); | |
| border: 1px solid var(--jp-input-active-border-color); | |
| box-shadow: var(--jp-input-box-shadow); | |
| } | |
| .jp-Editor.jp-mod-dropTarget { | |
| border: var(--jp-border-width) solid var(--jp-input-active-border-color); | |
| box-shadow: var(--jp-input-box-shadow); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-DocumentSearch-input { | |
| border: none; | |
| outline: none; | |
| color: var(--jp-ui-font-color0); | |
| font-size: var(--jp-ui-font-size1); | |
| background-color: var(--jp-layout-color0); | |
| font-family: var(--jp-ui-font-family); | |
| padding: 2px 1px; | |
| resize: none; | |
| } | |
| .jp-DocumentSearch-overlay { | |
| position: absolute; | |
| background-color: var(--jp-toolbar-background); | |
| border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color); | |
| border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color); | |
| top: 0; | |
| right: 0; | |
| z-index: 7; | |
| min-width: 405px; | |
| padding: 2px; | |
| font-size: var(--jp-ui-font-size1); | |
| --jp-private-document-search-button-height: 20px; | |
| } | |
| .jp-DocumentSearch-overlay button { | |
| background-color: var(--jp-toolbar-background); | |
| outline: 0; | |
| } | |
| .jp-DocumentSearch-overlay button:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-DocumentSearch-overlay button:active { | |
| background-color: var(--jp-layout-color3); | |
| } | |
| .jp-DocumentSearch-overlay-row { | |
| display: flex; | |
| align-items: center; | |
| margin-bottom: 2px; | |
| } | |
| .jp-DocumentSearch-button-content { | |
| display: inline-block; | |
| cursor: pointer; | |
| box-sizing: border-box; | |
| width: 100%; | |
| height: 100%; | |
| } | |
| .jp-DocumentSearch-button-content svg { | |
| width: 100%; | |
| height: 100%; | |
| } | |
| .jp-DocumentSearch-input-wrapper { | |
| border: var(--jp-border-width) solid var(--jp-border-color0); | |
| display: flex; | |
| background-color: var(--jp-layout-color0); | |
| margin: 2px; | |
| } | |
| .jp-DocumentSearch-input-wrapper:focus-within { | |
| border-color: var(--jp-cell-editor-active-border-color); | |
| } | |
| .jp-DocumentSearch-toggle-wrapper, | |
| .jp-DocumentSearch-button-wrapper { | |
| all: initial; | |
| overflow: hidden; | |
| display: inline-block; | |
| border: none; | |
| box-sizing: border-box; | |
| } | |
| .jp-DocumentSearch-toggle-wrapper { | |
| width: 14px; | |
| height: 14px; | |
| } | |
| .jp-DocumentSearch-button-wrapper { | |
| width: var(--jp-private-document-search-button-height); | |
| height: var(--jp-private-document-search-button-height); | |
| } | |
| .jp-DocumentSearch-toggle-wrapper:focus, | |
| .jp-DocumentSearch-button-wrapper:focus { | |
| outline: var(--jp-border-width) solid | |
| var(--jp-cell-editor-active-border-color); | |
| outline-offset: -1px; | |
| } | |
| .jp-DocumentSearch-toggle-wrapper, | |
| .jp-DocumentSearch-button-wrapper, | |
| .jp-DocumentSearch-button-content:focus { | |
| outline: none; | |
| } | |
| .jp-DocumentSearch-toggle-placeholder { | |
| width: 5px; | |
| } | |
| .jp-DocumentSearch-input-button::before { | |
| display: block; | |
| padding-top: 100%; | |
| } | |
| .jp-DocumentSearch-input-button-off { | |
| opacity: var(--jp-search-toggle-off-opacity); | |
| } | |
| .jp-DocumentSearch-input-button-off:hover { | |
| opacity: var(--jp-search-toggle-hover-opacity); | |
| } | |
| .jp-DocumentSearch-input-button-on { | |
| opacity: var(--jp-search-toggle-on-opacity); | |
| } | |
| .jp-DocumentSearch-index-counter { | |
| padding-left: 10px; | |
| padding-right: 10px; | |
| user-select: none; | |
| min-width: 35px; | |
| display: inline-block; | |
| } | |
| .jp-DocumentSearch-up-down-wrapper { | |
| display: inline-block; | |
| padding-right: 2px; | |
| margin-left: auto; | |
| white-space: nowrap; | |
| } | |
| .jp-DocumentSearch-spacer { | |
| margin-left: auto; | |
| } | |
| .jp-DocumentSearch-up-down-wrapper button { | |
| outline: 0; | |
| border: none; | |
| width: var(--jp-private-document-search-button-height); | |
| height: var(--jp-private-document-search-button-height); | |
| vertical-align: middle; | |
| margin: 1px 5px 2px; | |
| } | |
| .jp-DocumentSearch-up-down-button:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-DocumentSearch-up-down-button:active { | |
| background-color: var(--jp-layout-color3); | |
| } | |
| .jp-DocumentSearch-filter-button { | |
| border-radius: var(--jp-border-radius); | |
| } | |
| .jp-DocumentSearch-filter-button:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-DocumentSearch-filter-button-enabled { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-DocumentSearch-filter-button-enabled:hover { | |
| background-color: var(--jp-layout-color3); | |
| } | |
| .jp-DocumentSearch-search-options { | |
| padding: 0 8px; | |
| margin-left: 3px; | |
| width: 100%; | |
| display: grid; | |
| justify-content: start; | |
| grid-template-columns: 1fr 1fr; | |
| align-items: center; | |
| justify-items: stretch; | |
| } | |
| .jp-DocumentSearch-search-filter-disabled { | |
| color: var(--jp-ui-font-color2); | |
| } | |
| .jp-DocumentSearch-search-filter { | |
| display: flex; | |
| align-items: center; | |
| user-select: none; | |
| } | |
| .jp-DocumentSearch-regex-error { | |
| color: var(--jp-error-color0); | |
| } | |
| .jp-DocumentSearch-replace-button-wrapper { | |
| overflow: hidden; | |
| display: inline-block; | |
| box-sizing: border-box; | |
| border: var(--jp-border-width) solid var(--jp-border-color0); | |
| margin: auto 2px; | |
| padding: 1px 4px; | |
| height: calc(var(--jp-private-document-search-button-height) + 2px); | |
| } | |
| .jp-DocumentSearch-replace-button-wrapper:focus { | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color); | |
| } | |
| .jp-DocumentSearch-replace-button { | |
| display: inline-block; | |
| text-align: center; | |
| cursor: pointer; | |
| box-sizing: border-box; | |
| color: var(--jp-ui-font-color1); | |
| /* height - 2 * (padding of wrapper) */ | |
| line-height: calc(var(--jp-private-document-search-button-height) - 2px); | |
| width: 100%; | |
| height: 100%; | |
| } | |
| .jp-DocumentSearch-replace-button:focus { | |
| outline: none; | |
| } | |
| .jp-DocumentSearch-replace-wrapper-class { | |
| margin-left: 14px; | |
| display: flex; | |
| } | |
| .jp-DocumentSearch-replace-toggle { | |
| border: none; | |
| background-color: var(--jp-toolbar-background); | |
| border-radius: var(--jp-border-radius); | |
| } | |
| .jp-DocumentSearch-replace-toggle:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .cm-editor { | |
| line-height: var(--jp-code-line-height); | |
| font-size: var(--jp-code-font-size); | |
| font-family: var(--jp-code-font-family); | |
| border: 0; | |
| border-radius: 0; | |
| height: auto; | |
| /* Changed to auto to autogrow */ | |
| } | |
| .cm-editor pre { | |
| padding: 0 var(--jp-code-padding); | |
| } | |
| .jp-CodeMirrorEditor[data-type='inline'] .cm-dialog { | |
| background-color: var(--jp-layout-color0); | |
| color: var(--jp-content-font-color1); | |
| } | |
| .jp-CodeMirrorEditor { | |
| cursor: text; | |
| } | |
| /* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */ | |
| @media screen and (min-width: 2138px) and (max-width: 4319px) { | |
| .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor { | |
| border-left: var(--jp-code-cursor-width1) solid | |
| var(--jp-editor-cursor-color); | |
| } | |
| } | |
| /* When zoomed out less than 33% */ | |
| @media screen and (min-width: 4320px) { | |
| .jp-CodeMirrorEditor[data-type='inline'] .cm-cursor { | |
| border-left: var(--jp-code-cursor-width2) solid | |
| var(--jp-editor-cursor-color); | |
| } | |
| } | |
| .cm-editor.jp-mod-readOnly .cm-cursor { | |
| display: none; | |
| } | |
| .jp-CollaboratorCursor { | |
| border-left: 5px solid transparent; | |
| border-right: 5px solid transparent; | |
| border-top: none; | |
| border-bottom: 3px solid; | |
| background-clip: content-box; | |
| margin-left: -5px; | |
| margin-right: -5px; | |
| } | |
| .cm-searching, | |
| .cm-searching span { | |
| /* `.cm-searching span`: we need to override syntax highlighting */ | |
| background-color: var(--jp-search-unselected-match-background-color); | |
| color: var(--jp-search-unselected-match-color); | |
| } | |
| .cm-searching::selection, | |
| .cm-searching span::selection { | |
| background-color: var(--jp-search-unselected-match-background-color); | |
| color: var(--jp-search-unselected-match-color); | |
| } | |
| .jp-current-match > .cm-searching, | |
| .jp-current-match > .cm-searching span, | |
| .cm-searching > .jp-current-match, | |
| .cm-searching > .jp-current-match span { | |
| background-color: var(--jp-search-selected-match-background-color); | |
| color: var(--jp-search-selected-match-color); | |
| } | |
| .jp-current-match > .cm-searching::selection, | |
| .cm-searching > .jp-current-match::selection, | |
| .jp-current-match > .cm-searching span::selection { | |
| background-color: var(--jp-search-selected-match-background-color); | |
| color: var(--jp-search-selected-match-color); | |
| } | |
| .cm-trailingspace { | |
| background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=); | |
| background-position: center left; | |
| background-repeat: repeat-x; | |
| } | |
| .jp-CollaboratorCursor-hover { | |
| position: absolute; | |
| z-index: 1; | |
| transform: translateX(-50%); | |
| color: white; | |
| border-radius: 3px; | |
| padding-left: 4px; | |
| padding-right: 4px; | |
| padding-top: 1px; | |
| padding-bottom: 1px; | |
| text-align: center; | |
| font-size: var(--jp-ui-font-size1); | |
| white-space: nowrap; | |
| } | |
| .jp-CodeMirror-ruler { | |
| border-left: 1px dashed var(--jp-border-color2); | |
| } | |
| /* Styles for shared cursors (remote cursor locations and selected ranges) */ | |
| .jp-CodeMirrorEditor .cm-ySelectionCaret { | |
| position: relative; | |
| border-left: 1px solid black; | |
| margin-left: -1px; | |
| margin-right: -1px; | |
| box-sizing: border-box; | |
| } | |
| .jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo { | |
| white-space: nowrap; | |
| position: absolute; | |
| top: -1.15em; | |
| padding-bottom: 0.05em; | |
| left: -1px; | |
| font-size: 0.95em; | |
| font-family: var(--jp-ui-font-family); | |
| font-weight: bold; | |
| line-height: normal; | |
| user-select: none; | |
| color: white; | |
| padding-left: 2px; | |
| padding-right: 2px; | |
| z-index: 101; | |
| transition: opacity 0.3s ease-in-out; | |
| } | |
| .jp-CodeMirrorEditor .cm-ySelectionInfo { | |
| transition-delay: 0.7s; | |
| opacity: 0; | |
| } | |
| .jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo { | |
| opacity: 1; | |
| transition-delay: 0s; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-MimeDocument { | |
| outline: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Variables | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-private-filebrowser-button-height: 28px; | |
| --jp-private-filebrowser-button-width: 48px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-FileBrowser .jp-SidePanel-content { | |
| display: flex; | |
| flex-direction: column; | |
| } | |
| .jp-FileBrowser-toolbar.jp-Toolbar { | |
| flex-wrap: wrap; | |
| row-gap: 12px; | |
| border-bottom: none; | |
| height: auto; | |
| margin: 8px 12px 0; | |
| box-shadow: none; | |
| padding: 0; | |
| justify-content: flex-start; | |
| } | |
| .jp-FileBrowser-Panel { | |
| flex: 1 1 auto; | |
| display: flex; | |
| flex-direction: column; | |
| } | |
| .jp-BreadCrumbs { | |
| flex: 0 0 auto; | |
| margin: 8px 12px; | |
| } | |
| .jp-BreadCrumbs-item { | |
| margin: 0 2px; | |
| padding: 0 2px; | |
| border-radius: var(--jp-border-radius); | |
| cursor: pointer; | |
| } | |
| .jp-BreadCrumbs-item:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-BreadCrumbs-item:first-child { | |
| margin-left: 0; | |
| } | |
| .jp-BreadCrumbs-item.jp-mod-dropTarget { | |
| background-color: var(--jp-brand-color2); | |
| opacity: 0.7; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Buttons | |
| |----------------------------------------------------------------------------*/ | |
| .jp-FileBrowser-toolbar > .jp-Toolbar-item { | |
| flex: 0 0 auto; | |
| padding-left: 0; | |
| padding-right: 2px; | |
| align-items: center; | |
| height: unset; | |
| } | |
| .jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent { | |
| width: 40px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Other styles | |
| |----------------------------------------------------------------------------*/ | |
| .jp-FileDialog.jp-mod-conflict input { | |
| color: var(--jp-error-color1); | |
| } | |
| .jp-FileDialog .jp-new-name-title { | |
| margin-top: 12px; | |
| } | |
| .jp-LastModified-hidden { | |
| display: none; | |
| } | |
| .jp-FileSize-hidden { | |
| display: none; | |
| } | |
| .jp-FileBrowser .lm-AccordionPanel > h3:first-child { | |
| display: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | DirListing | |
| |----------------------------------------------------------------------------*/ | |
| .jp-DirListing { | |
| flex: 1 1 auto; | |
| display: flex; | |
| flex-direction: column; | |
| outline: 0; | |
| } | |
| .jp-DirListing-header { | |
| flex: 0 0 auto; | |
| display: flex; | |
| flex-direction: row; | |
| align-items: center; | |
| overflow: hidden; | |
| border-top: var(--jp-border-width) solid var(--jp-border-color2); | |
| border-bottom: var(--jp-border-width) solid var(--jp-border-color1); | |
| box-shadow: var(--jp-toolbar-box-shadow); | |
| z-index: 2; | |
| } | |
| .jp-DirListing-headerItem { | |
| padding: 4px 12px 2px; | |
| font-weight: 500; | |
| } | |
| .jp-DirListing-headerItem:hover { | |
| background: var(--jp-layout-color2); | |
| } | |
| .jp-DirListing-headerItem.jp-id-name { | |
| flex: 1 0 84px; | |
| } | |
| .jp-DirListing-headerItem.jp-id-modified { | |
| flex: 0 0 112px; | |
| border-left: var(--jp-border-width) solid var(--jp-border-color2); | |
| text-align: right; | |
| } | |
| .jp-DirListing-headerItem.jp-id-filesize { | |
| flex: 0 0 75px; | |
| border-left: var(--jp-border-width) solid var(--jp-border-color2); | |
| text-align: right; | |
| } | |
| .jp-id-narrow { | |
| display: none; | |
| flex: 0 0 5px; | |
| padding: 4px; | |
| border-left: var(--jp-border-width) solid var(--jp-border-color2); | |
| text-align: right; | |
| color: var(--jp-border-color2); | |
| } | |
| .jp-DirListing-narrow .jp-id-narrow { | |
| display: block; | |
| } | |
| .jp-DirListing-narrow .jp-id-modified, | |
| .jp-DirListing-narrow .jp-DirListing-itemModified { | |
| display: none; | |
| } | |
| .jp-DirListing-headerItem.jp-mod-selected { | |
| font-weight: 600; | |
| } | |
| /* increase specificity to override bundled default */ | |
| .jp-DirListing-content { | |
| flex: 1 1 auto; | |
| margin: 0; | |
| padding: 0; | |
| list-style-type: none; | |
| overflow: auto; | |
| background-color: var(--jp-layout-color1); | |
| } | |
| .jp-DirListing-content mark { | |
| color: var(--jp-ui-font-color0); | |
| background-color: transparent; | |
| font-weight: bold; | |
| } | |
| .jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark { | |
| color: var(--jp-ui-inverse-font-color0); | |
| } | |
| /* Style the directory listing content when a user drops a file to upload */ | |
| .jp-DirListing.jp-mod-native-drop .jp-DirListing-content { | |
| outline: 5px dashed rgba(128, 128, 128, 0.5); | |
| outline-offset: -10px; | |
| cursor: copy; | |
| } | |
| .jp-DirListing-item { | |
| display: flex; | |
| flex-direction: row; | |
| align-items: center; | |
| padding: 4px 12px; | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .jp-DirListing-checkboxWrapper { | |
| /* Increases hit area of checkbox. */ | |
| padding: 4px; | |
| } | |
| .jp-DirListing-header | |
| .jp-DirListing-checkboxWrapper | |
| + .jp-DirListing-headerItem { | |
| padding-left: 4px; | |
| } | |
| .jp-DirListing-content .jp-DirListing-checkboxWrapper { | |
| position: relative; | |
| left: -4px; | |
| margin: -4px 0 -4px -8px; | |
| } | |
| .jp-DirListing-checkboxWrapper.jp-mod-visible { | |
| visibility: visible; | |
| } | |
| /* For devices that support hovering, hide checkboxes until hovered, selected... | |
| */ | |
| @media (hover: hover) { | |
| .jp-DirListing-checkboxWrapper { | |
| visibility: hidden; | |
| } | |
| .jp-DirListing-item:hover .jp-DirListing-checkboxWrapper, | |
| .jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper { | |
| visibility: visible; | |
| } | |
| } | |
| .jp-DirListing-item[data-is-dot] { | |
| opacity: 75%; | |
| } | |
| .jp-DirListing-item.jp-mod-selected { | |
| color: var(--jp-ui-inverse-font-color1); | |
| background: var(--jp-brand-color1); | |
| } | |
| .jp-DirListing-item.jp-mod-dropTarget { | |
| background: var(--jp-brand-color3); | |
| } | |
| .jp-DirListing-item:hover:not(.jp-mod-selected) { | |
| background: var(--jp-layout-color2); | |
| } | |
| .jp-DirListing-itemIcon { | |
| flex: 0 0 20px; | |
| margin-right: 4px; | |
| } | |
| .jp-DirListing-itemText { | |
| flex: 1 0 64px; | |
| white-space: nowrap; | |
| overflow: hidden; | |
| text-overflow: ellipsis; | |
| user-select: none; | |
| } | |
| .jp-DirListing-itemText:focus { | |
| outline-width: 2px; | |
| outline-color: var(--jp-inverse-layout-color1); | |
| outline-style: solid; | |
| outline-offset: 1px; | |
| } | |
| .jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus { | |
| outline-color: var(--jp-layout-color1); | |
| } | |
| .jp-DirListing-itemModified { | |
| flex: 0 0 125px; | |
| text-align: right; | |
| } | |
| .jp-DirListing-itemFileSize { | |
| flex: 0 0 90px; | |
| text-align: right; | |
| } | |
| .jp-DirListing-editor { | |
| flex: 1 0 64px; | |
| outline: none; | |
| border: none; | |
| color: var(--jp-ui-font-color1); | |
| background-color: var(--jp-layout-color1); | |
| } | |
| .jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before { | |
| color: var(--jp-success-color1); | |
| content: '\25CF'; | |
| font-size: 8px; | |
| position: absolute; | |
| left: -8px; | |
| } | |
| .jp-DirListing-item.jp-mod-running.jp-mod-selected | |
| .jp-DirListing-itemIcon::before { | |
| color: var(--jp-ui-inverse-font-color1); | |
| } | |
| .jp-DirListing-item.lm-mod-drag-image, | |
| .jp-DirListing-item.jp-mod-selected.lm-mod-drag-image { | |
| font-size: var(--jp-ui-font-size1); | |
| padding-left: 4px; | |
| margin-left: 4px; | |
| width: 160px; | |
| background-color: var(--jp-ui-inverse-font-color2); | |
| box-shadow: var(--jp-elevation-z2); | |
| border-radius: 0; | |
| color: var(--jp-ui-font-color1); | |
| transform: translateX(-40%) translateY(-58%); | |
| } | |
| .jp-Document { | |
| min-width: 120px; | |
| min-height: 120px; | |
| outline: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Main OutputArea | |
| | OutputArea has a list of Outputs | |
| |----------------------------------------------------------------------------*/ | |
| .jp-OutputArea { | |
| overflow-y: auto; | |
| } | |
| .jp-OutputArea-child { | |
| display: table; | |
| table-layout: fixed; | |
| width: 100%; | |
| overflow: hidden; | |
| } | |
| .jp-OutputPrompt { | |
| width: var(--jp-cell-prompt-width); | |
| color: var(--jp-cell-outprompt-font-color); | |
| font-family: var(--jp-cell-prompt-font-family); | |
| padding: var(--jp-code-padding); | |
| letter-spacing: var(--jp-cell-prompt-letter-spacing); | |
| line-height: var(--jp-code-line-height); | |
| font-size: var(--jp-code-font-size); | |
| border: var(--jp-border-width) solid transparent; | |
| opacity: var(--jp-cell-prompt-opacity); | |
| /* Right align prompt text, don't wrap to handle large prompt numbers */ | |
| text-align: right; | |
| white-space: nowrap; | |
| overflow: hidden; | |
| text-overflow: ellipsis; | |
| /* Disable text selection */ | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .jp-OutputArea-prompt { | |
| display: table-cell; | |
| vertical-align: top; | |
| } | |
| .jp-OutputArea-output { | |
| display: table-cell; | |
| width: 100%; | |
| height: auto; | |
| overflow: auto; | |
| user-select: text; | |
| -moz-user-select: text; | |
| -webkit-user-select: text; | |
| -ms-user-select: text; | |
| } | |
| .jp-OutputArea .jp-RenderedText { | |
| padding-left: 1ch; | |
| } | |
| /** | |
| * Prompt overlay. | |
| */ | |
| .jp-OutputArea-promptOverlay { | |
| position: absolute; | |
| top: 0; | |
| width: var(--jp-cell-prompt-width); | |
| height: 100%; | |
| opacity: 0.5; | |
| } | |
| .jp-OutputArea-promptOverlay:hover { | |
| background: var(--jp-layout-color2); | |
| box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0); | |
| cursor: zoom-out; | |
| } | |
| .jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover { | |
| cursor: zoom-in; | |
| } | |
| /** | |
| * Isolated output. | |
| */ | |
| .jp-OutputArea-output.jp-mod-isolated { | |
| width: 100%; | |
| display: block; | |
| } | |
| /* | |
| When drag events occur, `lm-mod-override-cursor` is added to the body. | |
| Because iframes steal all cursor events, the following two rules are necessary | |
| to suppress pointer events while resize drags are occurring. There may be a | |
| better solution to this problem. | |
| */ | |
| body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated { | |
| position: relative; | |
| } | |
| body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before { | |
| content: ''; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| right: 0; | |
| bottom: 0; | |
| background: transparent; | |
| } | |
| /* pre */ | |
| .jp-OutputArea-output pre { | |
| border: none; | |
| margin: 0; | |
| padding: 0; | |
| overflow-x: auto; | |
| overflow-y: auto; | |
| word-break: break-all; | |
| word-wrap: break-word; | |
| white-space: pre-wrap; | |
| } | |
| /* tables */ | |
| .jp-OutputArea-output.jp-RenderedHTMLCommon table { | |
| margin-left: 0; | |
| margin-right: 0; | |
| } | |
| /* description lists */ | |
| .jp-OutputArea-output dl, | |
| .jp-OutputArea-output dt, | |
| .jp-OutputArea-output dd { | |
| display: block; | |
| } | |
| .jp-OutputArea-output dl { | |
| width: 100%; | |
| overflow: hidden; | |
| padding: 0; | |
| margin: 0; | |
| } | |
| .jp-OutputArea-output dt { | |
| font-weight: bold; | |
| float: left; | |
| width: 20%; | |
| padding: 0; | |
| margin: 0; | |
| } | |
| .jp-OutputArea-output dd { | |
| float: left; | |
| width: 80%; | |
| padding: 0; | |
| margin: 0; | |
| } | |
| .jp-TrimmedOutputs pre { | |
| background: var(--jp-layout-color3); | |
| font-size: calc(var(--jp-code-font-size) * 1.4); | |
| text-align: center; | |
| text-transform: uppercase; | |
| } | |
| /* Hide the gutter in case of | |
| * - nested output areas (e.g. in the case of output widgets) | |
| * - mirrored output areas | |
| */ | |
| .jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt { | |
| display: none; | |
| } | |
| /* Hide empty lines in the output area, for instance due to cleared widgets */ | |
| .jp-OutputArea-prompt:empty { | |
| padding: 0; | |
| border: 0; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | executeResult is added to any Output-result for the display of the object | |
| | returned by a cell | |
| |----------------------------------------------------------------------------*/ | |
| .jp-OutputArea-output.jp-OutputArea-executeResult { | |
| margin-left: 0; | |
| width: 100%; | |
| } | |
| /* Text output with the Out[] prompt needs a top padding to match the | |
| * alignment of the Out[] prompt itself. | |
| */ | |
| .jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output { | |
| padding-top: var(--jp-code-padding); | |
| border-top: var(--jp-border-width) solid transparent; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | The Stdin output | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Stdin-prompt { | |
| color: var(--jp-content-font-color0); | |
| padding-right: var(--jp-code-padding); | |
| vertical-align: baseline; | |
| flex: 0 0 auto; | |
| } | |
| .jp-Stdin-input { | |
| font-family: var(--jp-code-font-family); | |
| font-size: inherit; | |
| color: inherit; | |
| background-color: inherit; | |
| width: 42%; | |
| min-width: 200px; | |
| /* make sure input baseline aligns with prompt */ | |
| vertical-align: baseline; | |
| /* padding + margin = 0.5em between prompt and cursor */ | |
| padding: 0 0.25em; | |
| margin: 0 0.25em; | |
| flex: 0 0 70%; | |
| } | |
| .jp-Stdin-input::placeholder { | |
| opacity: 0; | |
| } | |
| .jp-Stdin-input:focus { | |
| box-shadow: none; | |
| } | |
| .jp-Stdin-input:focus::placeholder { | |
| opacity: 1; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Output Area View | |
| |----------------------------------------------------------------------------*/ | |
| .jp-LinkedOutputView .jp-OutputArea { | |
| height: 100%; | |
| display: block; | |
| } | |
| .jp-LinkedOutputView .jp-OutputArea-output:only-child { | |
| height: 100%; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Printing | |
| |----------------------------------------------------------------------------*/ | |
| @media print { | |
| .jp-OutputArea-child { | |
| break-inside: avoid-page; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Mobile | |
| |----------------------------------------------------------------------------*/ | |
| @media only screen and (max-width: 760px) { | |
| .jp-OutputPrompt { | |
| display: table-row; | |
| text-align: left; | |
| } | |
| .jp-OutputArea-child .jp-OutputArea-output { | |
| display: table-row; | |
| margin-left: var(--jp-notebook-padding); | |
| } | |
| } | |
| /* Trimmed outputs warning */ | |
| .jp-TrimmedOutputs > a { | |
| margin: 10px; | |
| text-decoration: none; | |
| cursor: pointer; | |
| } | |
| .jp-TrimmedOutputs > a:hover { | |
| text-decoration: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Table of Contents | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-private-toc-active-width: 4px; | |
| } | |
| .jp-TableOfContents { | |
| display: flex; | |
| flex-direction: column; | |
| background: var(--jp-layout-color1); | |
| color: var(--jp-ui-font-color1); | |
| font-size: var(--jp-ui-font-size1); | |
| height: 100%; | |
| } | |
| .jp-TableOfContents-placeholder { | |
| text-align: center; | |
| } | |
| .jp-TableOfContents-placeholderContent { | |
| color: var(--jp-content-font-color2); | |
| padding: 8px; | |
| } | |
| .jp-TableOfContents-placeholderContent > h3 { | |
| margin-bottom: var(--jp-content-heading-margin-bottom); | |
| } | |
| .jp-TableOfContents .jp-SidePanel-content { | |
| overflow-y: auto; | |
| } | |
| .jp-TableOfContents-tree { | |
| margin: 4px; | |
| } | |
| .jp-TableOfContents ol { | |
| list-style-type: none; | |
| } | |
| /* stylelint-disable-next-line selector-max-type */ | |
| .jp-TableOfContents li > ol { | |
| /* Align left border with triangle icon center */ | |
| padding-left: 11px; | |
| } | |
| .jp-TableOfContents-content { | |
| /* left margin for the active heading indicator */ | |
| margin: 0 0 0 var(--jp-private-toc-active-width); | |
| padding: 0; | |
| background-color: var(--jp-layout-color1); | |
| } | |
| .jp-tocItem { | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| .jp-tocItem-heading { | |
| display: flex; | |
| cursor: pointer; | |
| } | |
| .jp-tocItem-heading:hover { | |
| background-color: var(--jp-layout-color2); | |
| } | |
| .jp-tocItem-content { | |
| display: block; | |
| padding: 4px 0; | |
| white-space: nowrap; | |
| text-overflow: ellipsis; | |
| overflow-x: hidden; | |
| } | |
| .jp-tocItem-collapser { | |
| height: 20px; | |
| margin: 2px 2px 0; | |
| padding: 0; | |
| background: none; | |
| border: none; | |
| cursor: pointer; | |
| } | |
| .jp-tocItem-collapser:hover { | |
| background-color: var(--jp-layout-color3); | |
| } | |
| /* Active heading indicator */ | |
| .jp-tocItem-heading::before { | |
| content: ' '; | |
| background: transparent; | |
| width: var(--jp-private-toc-active-width); | |
| height: 24px; | |
| position: absolute; | |
| left: 0; | |
| border-radius: var(--jp-border-radius); | |
| } | |
| .jp-tocItem-heading.jp-tocItem-active::before { | |
| background-color: var(--jp-brand-color1); | |
| } | |
| .jp-tocItem-heading:hover.jp-tocItem-active::before { | |
| background: var(--jp-brand-color0); | |
| opacity: 1; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Collapser { | |
| flex: 0 0 var(--jp-cell-collapser-width); | |
| padding: 0; | |
| margin: 0; | |
| border: none; | |
| outline: none; | |
| background: transparent; | |
| border-radius: var(--jp-border-radius); | |
| opacity: 1; | |
| } | |
| .jp-Collapser-child { | |
| display: block; | |
| width: 100%; | |
| box-sizing: border-box; | |
| /* height: 100% doesn't work because the height of its parent is computed from content */ | |
| position: absolute; | |
| top: 0; | |
| bottom: 0; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Printing | |
| |----------------------------------------------------------------------------*/ | |
| /* | |
| Hiding collapsers in print mode. | |
| Note: input and output wrappers have "display: block" propery in print mode. | |
| */ | |
| @media print { | |
| .jp-Collapser { | |
| display: none; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Header/Footer | |
| |----------------------------------------------------------------------------*/ | |
| /* Hidden by zero height by default */ | |
| .jp-CellHeader, | |
| .jp-CellFooter { | |
| height: 0; | |
| width: 100%; | |
| padding: 0; | |
| margin: 0; | |
| border: none; | |
| outline: none; | |
| background: transparent; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Input | |
| |----------------------------------------------------------------------------*/ | |
| /* All input areas */ | |
| .jp-InputArea { | |
| display: table; | |
| table-layout: fixed; | |
| width: 100%; | |
| overflow: hidden; | |
| } | |
| .jp-InputArea-editor { | |
| display: table-cell; | |
| overflow: hidden; | |
| vertical-align: top; | |
| /* This is the non-active, default styling */ | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); | |
| border-radius: 0; | |
| background: var(--jp-cell-editor-background); | |
| } | |
| .jp-InputPrompt { | |
| display: table-cell; | |
| vertical-align: top; | |
| width: var(--jp-cell-prompt-width); | |
| color: var(--jp-cell-inprompt-font-color); | |
| font-family: var(--jp-cell-prompt-font-family); | |
| padding: var(--jp-code-padding); | |
| letter-spacing: var(--jp-cell-prompt-letter-spacing); | |
| opacity: var(--jp-cell-prompt-opacity); | |
| line-height: var(--jp-code-line-height); | |
| font-size: var(--jp-code-font-size); | |
| border: var(--jp-border-width) solid transparent; | |
| /* Right align prompt text, don't wrap to handle large prompt numbers */ | |
| text-align: right; | |
| white-space: nowrap; | |
| overflow: hidden; | |
| text-overflow: ellipsis; | |
| /* Disable text selection */ | |
| -webkit-user-select: none; | |
| -moz-user-select: none; | |
| -ms-user-select: none; | |
| user-select: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Mobile | |
| |----------------------------------------------------------------------------*/ | |
| @media only screen and (max-width: 760px) { | |
| .jp-InputArea-editor { | |
| display: table-row; | |
| margin-left: var(--jp-notebook-padding); | |
| } | |
| .jp-InputPrompt { | |
| display: table-row; | |
| text-align: left; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Placeholder | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Placeholder { | |
| display: table; | |
| table-layout: fixed; | |
| width: 100%; | |
| } | |
| .jp-Placeholder-prompt { | |
| display: table-cell; | |
| box-sizing: border-box; | |
| } | |
| .jp-Placeholder-content { | |
| display: table-cell; | |
| padding: 4px 6px; | |
| border: 1px solid transparent; | |
| border-radius: 0; | |
| background: none; | |
| box-sizing: border-box; | |
| cursor: pointer; | |
| } | |
| .jp-Placeholder-contentContainer { | |
| display: flex; | |
| } | |
| .jp-Placeholder-content:hover, | |
| .jp-InputPlaceholder > .jp-Placeholder-content:hover { | |
| border-color: var(--jp-layout-color3); | |
| } | |
| .jp-Placeholder-content .jp-MoreHorizIcon { | |
| width: 32px; | |
| height: 16px; | |
| border: 1px solid transparent; | |
| border-radius: var(--jp-border-radius); | |
| } | |
| .jp-Placeholder-content .jp-MoreHorizIcon:hover { | |
| border: 1px solid var(--jp-border-color1); | |
| box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25); | |
| background-color: var(--jp-layout-color0); | |
| } | |
| .jp-PlaceholderText { | |
| white-space: nowrap; | |
| overflow-x: hidden; | |
| color: var(--jp-inverse-layout-color3); | |
| font-family: var(--jp-code-font-family); | |
| } | |
| .jp-InputPlaceholder > .jp-Placeholder-content { | |
| border-color: var(--jp-cell-editor-border-color); | |
| background: var(--jp-cell-editor-background); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Private CSS variables | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-private-cell-scrolling-output-offset: 5px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Cell | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Cell { | |
| padding: var(--jp-cell-padding); | |
| margin: 0; | |
| border: none; | |
| outline: none; | |
| background: transparent; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Common input/output | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Cell-inputWrapper, | |
| .jp-Cell-outputWrapper { | |
| display: flex; | |
| flex-direction: row; | |
| padding: 0; | |
| margin: 0; | |
| /* Added to reveal the box-shadow on the input and output collapsers. */ | |
| overflow: visible; | |
| } | |
| /* Only input/output areas inside cells */ | |
| .jp-Cell-inputArea, | |
| .jp-Cell-outputArea { | |
| flex: 1 1 auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Collapser | |
| |----------------------------------------------------------------------------*/ | |
| /* Make the output collapser disappear when there is not output, but do so | |
| * in a manner that leaves it in the layout and preserves its width. | |
| */ | |
| .jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser { | |
| border: none !important; | |
| background: transparent !important; | |
| } | |
| .jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser { | |
| min-height: var(--jp-cell-collapser-min-height); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Output | |
| |----------------------------------------------------------------------------*/ | |
| /* Put a space between input and output when there IS output */ | |
| .jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper { | |
| margin-top: 5px; | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea { | |
| overflow-y: auto; | |
| max-height: 24em; | |
| margin-left: var(--jp-private-cell-scrolling-output-offset); | |
| resize: vertical; | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] { | |
| max-height: unset; | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after { | |
| content: ' '; | |
| box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%); | |
| width: 100%; | |
| height: 100%; | |
| position: sticky; | |
| bottom: 0; | |
| top: 0; | |
| margin-top: -50%; | |
| float: left; | |
| display: block; | |
| pointer-events: none; | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child { | |
| padding-top: 6px; | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt { | |
| width: calc( | |
| var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset) | |
| ); | |
| } | |
| .jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay { | |
| left: calc(-1 * var(--jp-private-cell-scrolling-output-offset)); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | CodeCell | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | MarkdownCell | |
| |----------------------------------------------------------------------------*/ | |
| .jp-MarkdownOutput { | |
| display: table-cell; | |
| width: 100%; | |
| margin-top: 0; | |
| margin-bottom: 0; | |
| padding-left: var(--jp-code-padding); | |
| } | |
| .jp-MarkdownOutput.jp-RenderedHTMLCommon { | |
| overflow: auto; | |
| } | |
| /* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */ | |
| .jp-collapseHeadingButton { | |
| display: flex; | |
| min-height: var(--jp-cell-collapser-min-height); | |
| font-size: var(--jp-code-font-size); | |
| position: absolute; | |
| background-color: transparent; | |
| background-size: 25px; | |
| background-repeat: no-repeat; | |
| background-position-x: center; | |
| background-position-y: top; | |
| background-image: var(--jp-icon-caret-down); | |
| right: 0; | |
| top: 0; | |
| bottom: 0; | |
| } | |
| .jp-collapseHeadingButton.jp-mod-collapsed { | |
| background-image: var(--jp-icon-caret-right); | |
| } | |
| /* | |
| set the container font size to match that of content | |
| so that the nested collapse buttons have the right size | |
| */ | |
| .jp-MarkdownCell .jp-InputPrompt { | |
| font-size: var(--jp-content-font-size1); | |
| } | |
| /* | |
| Align collapseHeadingButton with cell top header | |
| The font sizes are identical to the ones in packages/rendermime/style/base.css | |
| */ | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] { | |
| font-size: var(--jp-content-font-size5); | |
| background-position-y: calc(0.3 * var(--jp-content-font-size5)); | |
| } | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] { | |
| font-size: var(--jp-content-font-size4); | |
| background-position-y: calc(0.3 * var(--jp-content-font-size4)); | |
| } | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] { | |
| font-size: var(--jp-content-font-size3); | |
| background-position-y: calc(0.3 * var(--jp-content-font-size3)); | |
| } | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] { | |
| font-size: var(--jp-content-font-size2); | |
| background-position-y: calc(0.3 * var(--jp-content-font-size2)); | |
| } | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] { | |
| font-size: var(--jp-content-font-size1); | |
| background-position-y: top; | |
| } | |
| .jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] { | |
| font-size: var(--jp-content-font-size0); | |
| background-position-y: top; | |
| } | |
| /* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */ | |
| .jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton { | |
| display: none; | |
| } | |
| .jp-Notebook.jp-mod-showHiddenCellsButton | |
| :is(.jp-MarkdownCell:hover, .jp-mod-active) | |
| .jp-collapseHeadingButton { | |
| display: flex; | |
| } | |
| /* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which | |
| is a consequence of the showHiddenCellsButton option in Notebook Settings)*/ | |
| .jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton { | |
| margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding)); | |
| margin-top: var(--jp-code-padding); | |
| border: 1px solid var(--jp-border-color2); | |
| background-color: var(--jp-border-color3) !important; | |
| color: var(--jp-content-font-color0) !important; | |
| display: flex; | |
| } | |
| .jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover { | |
| background-color: var(--jp-border-color2) !important; | |
| } | |
| .jp-showHiddenCellsButton { | |
| display: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Printing | |
| |----------------------------------------------------------------------------*/ | |
| /* | |
| Using block instead of flex to allow the use of the break-inside CSS property for | |
| cell outputs. | |
| */ | |
| @media print { | |
| .jp-Cell-inputWrapper, | |
| .jp-Cell-outputWrapper { | |
| display: block; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Variables | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-notebook-toolbar-padding: 2px 5px 2px 2px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| /*----------------------------------------------------------------------------- | |
| | Styles | |
| |----------------------------------------------------------------------------*/ | |
| .jp-NotebookPanel-toolbar { | |
| padding: var(--jp-notebook-toolbar-padding); | |
| /* disable paint containment from lumino 2.0 default strict CSS containment */ | |
| contain: style size !important; | |
| } | |
| .jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused { | |
| border: none; | |
| box-shadow: none; | |
| } | |
| .jp-Notebook-toolbarCellTypeDropdown select { | |
| height: 24px; | |
| font-size: var(--jp-ui-font-size1); | |
| line-height: 14px; | |
| border-radius: 0; | |
| display: block; | |
| } | |
| .jp-Notebook-toolbarCellTypeDropdown span { | |
| top: 5px !important; | |
| } | |
| .jp-Toolbar-responsive-popup { | |
| position: absolute; | |
| height: fit-content; | |
| display: flex; | |
| flex-direction: row; | |
| flex-wrap: wrap; | |
| justify-content: flex-end; | |
| border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color); | |
| box-shadow: var(--jp-toolbar-box-shadow); | |
| background: var(--jp-toolbar-background); | |
| min-height: var(--jp-toolbar-micro-height); | |
| padding: var(--jp-notebook-toolbar-padding); | |
| z-index: 1; | |
| right: 0; | |
| top: 0; | |
| } | |
| .jp-Toolbar > .jp-Toolbar-responsive-opener { | |
| margin-left: auto; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Variables | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| /*----------------------------------------------------------------------------- | |
| | Styles | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Notebook-ExecutionIndicator { | |
| position: relative; | |
| display: inline-block; | |
| height: 100%; | |
| z-index: 9997; | |
| } | |
| .jp-Notebook-ExecutionIndicator-tooltip { | |
| visibility: hidden; | |
| height: auto; | |
| width: max-content; | |
| width: -moz-max-content; | |
| background-color: var(--jp-layout-color2); | |
| color: var(--jp-ui-font-color1); | |
| text-align: justify; | |
| border-radius: 6px; | |
| padding: 0 5px; | |
| position: fixed; | |
| display: table; | |
| } | |
| .jp-Notebook-ExecutionIndicator-tooltip.up { | |
| transform: translateX(-50%) translateY(-100%) translateY(-32px); | |
| } | |
| .jp-Notebook-ExecutionIndicator-tooltip.down { | |
| transform: translateX(calc(-100% + 16px)) translateY(5px); | |
| } | |
| .jp-Notebook-ExecutionIndicator-tooltip.hidden { | |
| display: none; | |
| } | |
| .jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip { | |
| visibility: visible; | |
| } | |
| .jp-Notebook-ExecutionIndicator span { | |
| font-size: var(--jp-ui-font-size1); | |
| font-family: var(--jp-ui-font-family); | |
| color: var(--jp-ui-font-color1); | |
| line-height: 24px; | |
| display: block; | |
| } | |
| .jp-Notebook-ExecutionIndicator-progress-bar { | |
| display: flex; | |
| justify-content: center; | |
| height: 100%; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| /* | |
| * Execution indicator | |
| */ | |
| .jp-tocItem-content::after { | |
| content: ''; | |
| /* Must be identical to form a circle */ | |
| width: 12px; | |
| height: 12px; | |
| background: none; | |
| border: none; | |
| position: absolute; | |
| right: 0; | |
| } | |
| .jp-tocItem-content[data-running='0']::after { | |
| border-radius: 50%; | |
| border: var(--jp-border-width) solid var(--jp-inverse-layout-color3); | |
| background: none; | |
| } | |
| .jp-tocItem-content[data-running='1']::after { | |
| border-radius: 50%; | |
| border: var(--jp-border-width) solid var(--jp-inverse-layout-color3); | |
| background-color: var(--jp-inverse-layout-color3); | |
| } | |
| .jp-tocItem-content[data-running='0'], | |
| .jp-tocItem-content[data-running='1'] { | |
| margin-right: 12px; | |
| } | |
| /* | |
| * Copyright (c) Jupyter Development Team. | |
| * Distributed under the terms of the Modified BSD License. | |
| */ | |
| .jp-Notebook-footer { | |
| height: 27px; | |
| margin-left: calc( | |
| var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) + | |
| var(--jp-cell-padding) | |
| ); | |
| width: calc( | |
| 100% - | |
| ( | |
| var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) + | |
| var(--jp-cell-padding) + var(--jp-cell-padding) | |
| ) | |
| ); | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); | |
| color: var(--jp-ui-font-color3); | |
| margin-top: 6px; | |
| background: none; | |
| cursor: pointer; | |
| } | |
| .jp-Notebook-footer:focus { | |
| border-color: var(--jp-cell-editor-active-border-color); | |
| } | |
| /* For devices that support hovering, hide footer until hover */ | |
| @media (hover: hover) { | |
| .jp-Notebook-footer { | |
| opacity: 0; | |
| } | |
| .jp-Notebook-footer:focus, | |
| .jp-Notebook-footer:hover { | |
| opacity: 1; | |
| } | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | Imports | |
| |----------------------------------------------------------------------------*/ | |
| /*----------------------------------------------------------------------------- | |
| | CSS variables | |
| |----------------------------------------------------------------------------*/ | |
| :root { | |
| --jp-side-by-side-output-size: 1fr; | |
| --jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size); | |
| --jp-private-notebook-dragImage-width: 304px; | |
| --jp-private-notebook-dragImage-height: 36px; | |
| --jp-private-notebook-selected-color: var(--md-blue-400); | |
| --jp-private-notebook-active-color: var(--md-green-400); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Notebook | |
| |----------------------------------------------------------------------------*/ | |
| /* stylelint-disable selector-max-class */ | |
| .jp-NotebookPanel { | |
| display: block; | |
| height: 100%; | |
| } | |
| .jp-NotebookPanel.jp-Document { | |
| min-width: 240px; | |
| min-height: 120px; | |
| } | |
| .jp-Notebook { | |
| padding: var(--jp-notebook-padding); | |
| outline: none; | |
| overflow: auto; | |
| background: var(--jp-layout-color0); | |
| } | |
| .jp-Notebook.jp-mod-scrollPastEnd::after { | |
| display: block; | |
| content: ''; | |
| min-height: var(--jp-notebook-scroll-padding); | |
| } | |
| .jp-MainAreaWidget-ContainStrict .jp-Notebook * { | |
| contain: strict; | |
| } | |
| .jp-Notebook .jp-Cell { | |
| overflow: visible; | |
| } | |
| .jp-Notebook .jp-Cell .jp-InputPrompt { | |
| cursor: move; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Notebook state related styling | |
| | | |
| | The notebook and cells each have states, here are the possibilities: | |
| | | |
| | - Notebook | |
| | - Command | |
| | - Edit | |
| | - Cell | |
| | - None | |
| | - Active (only one can be active) | |
| | - Selected (the cells actions are applied to) | |
| | - Multiselected (when multiple selected, the cursor) | |
| | - No outputs | |
| |----------------------------------------------------------------------------*/ | |
| /* Command or edit modes */ | |
| .jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt { | |
| opacity: var(--jp-cell-prompt-not-active-opacity); | |
| color: var(--jp-cell-prompt-not-active-font-color); | |
| } | |
| .jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt { | |
| opacity: var(--jp-cell-prompt-not-active-opacity); | |
| color: var(--jp-cell-prompt-not-active-font-color); | |
| } | |
| /* cell is active */ | |
| .jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser { | |
| background: var(--jp-brand-color1); | |
| } | |
| /* cell is dirty */ | |
| .jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt { | |
| color: var(--jp-warn-color1); | |
| } | |
| .jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before { | |
| color: var(--jp-warn-color1); | |
| content: '•'; | |
| } | |
| .jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser { | |
| background: var(--jp-warn-color1); | |
| } | |
| /* collapser is hovered */ | |
| .jp-Notebook .jp-Cell .jp-Collapser:hover { | |
| box-shadow: var(--jp-elevation-z2); | |
| background: var(--jp-brand-color1); | |
| opacity: var(--jp-cell-collapser-not-active-hover-opacity); | |
| } | |
| /* cell is active and collapser is hovered */ | |
| .jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover { | |
| background: var(--jp-brand-color0); | |
| opacity: 1; | |
| } | |
| /* Command mode */ | |
| .jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected { | |
| background: var(--jp-notebook-multiselected-color); | |
| } | |
| .jp-Notebook.jp-mod-commandMode | |
| .jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) { | |
| background: transparent; | |
| } | |
| /* Edit mode */ | |
| .jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor { | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color); | |
| box-shadow: var(--jp-input-box-shadow); | |
| background-color: var(--jp-cell-editor-active-background); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Notebook drag and drop | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Notebook-cell.jp-mod-dropSource { | |
| opacity: 0.5; | |
| } | |
| .jp-Notebook-cell.jp-mod-dropTarget, | |
| .jp-Notebook.jp-mod-commandMode | |
| .jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget { | |
| border-top-color: var(--jp-private-notebook-selected-color); | |
| border-top-style: solid; | |
| border-top-width: 2px; | |
| } | |
| .jp-dragImage { | |
| display: block; | |
| flex-direction: row; | |
| width: var(--jp-private-notebook-dragImage-width); | |
| height: var(--jp-private-notebook-dragImage-height); | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); | |
| background: var(--jp-cell-editor-background); | |
| overflow: visible; | |
| } | |
| .jp-dragImage-singlePrompt { | |
| box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12); | |
| } | |
| .jp-dragImage .jp-dragImage-content { | |
| flex: 1 1 auto; | |
| z-index: 2; | |
| font-size: var(--jp-code-font-size); | |
| font-family: var(--jp-code-font-family); | |
| line-height: var(--jp-code-line-height); | |
| padding: var(--jp-code-padding); | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); | |
| background: var(--jp-cell-editor-background-color); | |
| color: var(--jp-content-font-color3); | |
| text-align: left; | |
| margin: 4px 4px 4px 0; | |
| } | |
| .jp-dragImage .jp-dragImage-prompt { | |
| flex: 0 0 auto; | |
| min-width: 36px; | |
| color: var(--jp-cell-inprompt-font-color); | |
| padding: var(--jp-code-padding); | |
| padding-left: 12px; | |
| font-family: var(--jp-cell-prompt-font-family); | |
| letter-spacing: var(--jp-cell-prompt-letter-spacing); | |
| line-height: 1.9; | |
| font-size: var(--jp-code-font-size); | |
| border: var(--jp-border-width) solid transparent; | |
| } | |
| .jp-dragImage-multipleBack { | |
| z-index: -1; | |
| position: absolute; | |
| height: 32px; | |
| width: 300px; | |
| top: 8px; | |
| left: 8px; | |
| background: var(--jp-layout-color2); | |
| border: var(--jp-border-width) solid var(--jp-input-border-color); | |
| box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12); | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Cell toolbar | |
| |----------------------------------------------------------------------------*/ | |
| .jp-NotebookTools { | |
| display: block; | |
| min-width: var(--jp-sidebar-min-width); | |
| color: var(--jp-ui-font-color1); | |
| background: var(--jp-layout-color1); | |
| /* This is needed so that all font sizing of children done in ems is | |
| * relative to this base size */ | |
| font-size: var(--jp-ui-font-size1); | |
| overflow: auto; | |
| } | |
| .jp-ActiveCellTool { | |
| padding: 12px 0; | |
| display: flex; | |
| } | |
| .jp-ActiveCellTool-Content { | |
| flex: 1 1 auto; | |
| } | |
| .jp-ActiveCellTool .jp-ActiveCellTool-CellContent { | |
| background: var(--jp-cell-editor-background); | |
| border: var(--jp-border-width) solid var(--jp-cell-editor-border-color); | |
| border-radius: 0; | |
| min-height: 29px; | |
| } | |
| .jp-ActiveCellTool .jp-InputPrompt { | |
| min-width: calc(var(--jp-cell-prompt-width) * 0.75); | |
| } | |
| .jp-ActiveCellTool-CellContent > pre { | |
| padding: 5px 4px; | |
| margin: 0; | |
| white-space: normal; | |
| } | |
| .jp-MetadataEditorTool { | |
| flex-direction: column; | |
| padding: 12px 0; | |
| } | |
| .jp-RankedPanel > :not(:first-child) { | |
| margin-top: 12px; | |
| } | |
| .jp-KeySelector select.jp-mod-styled { | |
| font-size: var(--jp-ui-font-size1); | |
| color: var(--jp-ui-font-color0); | |
| border: var(--jp-border-width) solid var(--jp-border-color1); | |
| } | |
| .jp-KeySelector label, | |
| .jp-MetadataEditorTool label, | |
| .jp-NumberSetter label { | |
| line-height: 1.4; | |
| } | |
| .jp-NotebookTools .jp-select-wrapper { | |
| margin-top: 4px; | |
| margin-bottom: 0; | |
| } | |
| .jp-NumberSetter input { | |
| width: 100%; | |
| margin-top: 4px; | |
| } | |
| .jp-NotebookTools .jp-Collapse { | |
| margin-top: 16px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Presentation Mode (.jp-mod-presentationMode) | |
| |----------------------------------------------------------------------------*/ | |
| .jp-mod-presentationMode .jp-Notebook { | |
| --jp-content-font-size1: var(--jp-content-presentation-font-size1); | |
| --jp-code-font-size: var(--jp-code-presentation-font-size); | |
| } | |
| .jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt, | |
| .jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt { | |
| flex: 0 0 110px; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Side-by-side Mode (.jp-mod-sideBySide) | |
| |----------------------------------------------------------------------------*/ | |
| .jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell { | |
| margin-top: 3em; | |
| margin-bottom: 3em; | |
| margin-left: 5%; | |
| margin-right: 5%; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell { | |
| display: grid; | |
| grid-template-columns: minmax(0, 1fr) min-content minmax( | |
| 0, | |
| var(--jp-side-by-side-output-size) | |
| ); | |
| grid-template-rows: auto minmax(0, 1fr) auto; | |
| grid-template-areas: | |
| 'header header header' | |
| 'input handle output' | |
| 'footer footer footer'; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell { | |
| grid-template-columns: minmax(0, 1fr) min-content minmax( | |
| 0, | |
| var(--jp-side-by-side-resized-cell) | |
| ); | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader { | |
| grid-area: header; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper { | |
| grid-area: input; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper { | |
| /* overwrite the default margin (no vertical separation needed in side by side move */ | |
| margin-top: 0; | |
| grid-area: output; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter { | |
| grid-area: footer; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle { | |
| grid-area: handle; | |
| user-select: none; | |
| display: block; | |
| height: 100%; | |
| cursor: ew-resize; | |
| padding: 0 var(--jp-cell-padding); | |
| } | |
| .jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after { | |
| content: ''; | |
| display: block; | |
| background: var(--jp-border-color2); | |
| height: 100%; | |
| width: 5px; | |
| } | |
| .jp-mod-sideBySide.jp-Notebook | |
| .jp-CodeCell.jp-mod-resizedCell | |
| .jp-CellResizeHandle::after { | |
| background: var(--jp-border-color0); | |
| } | |
| .jp-CellResizeHandle { | |
| display: none; | |
| } | |
| /*----------------------------------------------------------------------------- | |
| | Placeholder | |
| |----------------------------------------------------------------------------*/ | |
| .jp-Cell-Placeholder { | |
| padding-left: 55px; | |
| } | |
| .jp-Cell-Placeholder-wrapper { | |
| background: #fff; | |
| border: 1px solid; | |
| border-color: #e5e6e9 #dfe0e4 #d0d1d5; | |
| border-radius: 4px; | |
| -webkit-border-radius: 4px; | |
| margin: 10px 15px; | |
| } | |
| .jp-Cell-Placeholder-wrapper-inner { | |
| padding: 15px; | |
| position: relative; | |
| } | |
| .jp-Cell-Placeholder-wrapper-body { | |
| background-repeat: repeat; | |
| background-size: 50% auto; | |
| } | |
| .jp-Cell-Placeholder-wrapper-body div { | |
| background: #f6f7f8; | |
| background-image: -webkit-linear-gradient( | |
| left, | |
| #f6f7f8 0%, | |
| #edeef1 20%, | |
| #f6f7f8 40%, | |
| #f6f7f8 100% | |
| ); | |
| background-repeat: no-repeat; | |
| background-size: 800px 104px; | |
| height: 104px; | |
| position: absolute; | |
| right: 15px; | |
| left: 15px; | |
| top: 15px; | |
| } | |
| div.jp-Cell-Placeholder-h1 { | |
| top: 20px; | |
| height: 20px; | |
| left: 15px; | |
| width: 150px; | |
| } | |
| div.jp-Cell-Placeholder-h2 { | |
| left: 15px; | |
| top: 50px; | |
| height: 10px; | |
| width: 100px; | |
| } | |
| div.jp-Cell-Placeholder-content-1, | |
| div.jp-Cell-Placeholder-content-2, | |
| div.jp-Cell-Placeholder-content-3 { | |
| left: 15px; | |
| right: 15px; | |
| height: 10px; | |
| } | |
| div.jp-Cell-Placeholder-content-1 { | |
| top: 100px; | |
| } | |
| div.jp-Cell-Placeholder-content-2 { | |
| top: 120px; | |
| } | |
| div.jp-Cell-Placeholder-content-3 { | |
| top: 140px; | |
| } | |
| </style> | |
| <style type="text/css"> | |
| /*----------------------------------------------------------------------------- | |
| | Copyright (c) Jupyter Development Team. | |
| | Distributed under the terms of the Modified BSD License. | |
| |----------------------------------------------------------------------------*/ | |
| /* | |
| The following CSS variables define the main, public API for styling JupyterLab. | |
| These variables should be used by all plugins wherever possible. In other | |
| words, plugins should not define custom colors, sizes, etc unless absolutely | |
| necessary. This enables users to change the visual theme of JupyterLab | |
| by changing these variables. | |
| Many variables appear in an ordered sequence (0,1,2,3). These sequences | |
| are designed to work well together, so for example, `--jp-border-color1` should | |
| be used with `--jp-layout-color1`. The numbers have the following meanings: | |
| * 0: super-primary, reserved for special emphasis | |
| * 1: primary, most important under normal situations | |
| * 2: secondary, next most important under normal situations | |
| * 3: tertiary, next most important under normal situations | |
| Throughout JupyterLab, we are mostly following principles from Google's | |
| Material Design when selecting colors. We are not, however, following | |
| all of MD as it is not optimized for dense, information rich UIs. | |
| */ | |
| :root { | |
| /* Elevation | |
| * | |
| * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: | |
| * | |
| * https://github.com/material-components/material-components-web | |
| * https://material-components-web.appspot.com/elevation.html | |
| */ | |
| --jp-shadow-base-lightness: 0; | |
| --jp-shadow-umbra-color: rgba( | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| 0.2 | |
| ); | |
| --jp-shadow-penumbra-color: rgba( | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| 0.14 | |
| ); | |
| --jp-shadow-ambient-color: rgba( | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| var(--jp-shadow-base-lightness), | |
| 0.12 | |
| ); | |
| --jp-elevation-z0: none; | |
| --jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color), | |
| 0 1px 1px 0 var(--jp-shadow-penumbra-color), | |
| 0 1px 3px 0 var(--jp-shadow-ambient-color); | |
| --jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color), | |
| 0 2px 2px 0 var(--jp-shadow-penumbra-color), | |
| 0 1px 5px 0 var(--jp-shadow-ambient-color); | |
| --jp-elevation-z4: 0 2px 4px -1px var(--jp-shadow-umbra-color), | |
| 0 4px 5px 0 var(--jp-shadow-penumbra-color), | |
| 0 1px 10px 0 var(--jp-shadow-ambient-color); | |
| --jp-elevation-z6: 0 3px 5px -1px var(--jp-shadow-umbra-color), | |
| 0 6px 10px 0 var(--jp-shadow-penumbra-color), | |
| 0 1px 18px 0 var(--jp-shadow-ambient-color); | |
| --jp-elevation-z8: 0 5px 5px -3px var(--jp-shadow-umbra-color), | |
| 0 8px 10px 1px var(--jp-shadow-penumbra-color), | |
| 0 3px 14px 2px var(--jp-shadow-ambient-color); | |
| --jp-elevation-z12: 0 7px 8px -4px var(--jp-shadow-umbra-color), | |
| 0 12px 17px 2px var(--jp-shadow-penumbra-color), | |
| 0 5px 22px 4px var(--jp-shadow-ambient-color); | |
| --jp-elevation-z16: 0 8px 10px -5px var(--jp-shadow-umbra-color), | |
| 0 16px 24px 2px var(--jp-shadow-penumbra-color), | |
| 0 6px 30px 5px var(--jp-shadow-ambient-color); | |
| --jp-elevation-z20: 0 10px 13px -6px var(--jp-shadow-umbra-color), | |
| 0 20px 31px 3px var(--jp-shadow-penumbra-color), | |
| 0 8px 38px 7px var(--jp-shadow-ambient-color); | |
| --jp-elevation-z24: 0 11px 15px -7px var(--jp-shadow-umbra-color), | |
| 0 24px 38px 3px var(--jp-shadow-penumbra-color), | |
| 0 9px 46px 8px var(--jp-shadow-ambient-color); | |
| /* Borders | |
| * | |
| * The following variables, specify the visual styling of borders in JupyterLab. | |
| */ | |
| --jp-border-width: 1px; | |
| --jp-border-color0: var(--md-grey-400); | |
| --jp-border-color1: var(--md-grey-400); | |
| --jp-border-color2: var(--md-grey-300); | |
| --jp-border-color3: var(--md-grey-200); | |
| --jp-inverse-border-color: var(--md-grey-600); | |
| --jp-border-radius: 2px; | |
| /* UI Fonts | |
| * | |
| * The UI font CSS variables are used for the typography all of the JupyterLab | |
| * user interface elements that are not directly user generated content. | |
| * | |
| * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 | |
| * is applied to a parent element. When children elements, such as headings, are sized | |
| * in em all things will be computed relative to that body size. | |
| */ | |
| --jp-ui-font-scale-factor: 1.2; | |
| --jp-ui-font-size0: 0.83333em; | |
| --jp-ui-font-size1: 13px; /* Base font size */ | |
| --jp-ui-font-size2: 1.2em; | |
| --jp-ui-font-size3: 1.44em; | |
| --jp-ui-font-family: system-ui, -apple-system, blinkmacsystemfont, 'Segoe UI', | |
| helvetica, arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', | |
| 'Segoe UI Symbol'; | |
| /* | |
| * Use these font colors against the corresponding main layout colors. | |
| * In a light theme, these go from dark to light. | |
| */ | |
| /* Defaults use Material Design specification */ | |
| --jp-ui-font-color0: rgba(0, 0, 0, 1); | |
| --jp-ui-font-color1: rgba(0, 0, 0, 0.87); | |
| --jp-ui-font-color2: rgba(0, 0, 0, 0.54); | |
| --jp-ui-font-color3: rgba(0, 0, 0, 0.38); | |
| /* | |
| * Use these against the brand/accent/warn/error colors. | |
| * These will typically go from light to darker, in both a dark and light theme. | |
| */ | |
| --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); | |
| --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); | |
| --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); | |
| --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); | |
| /* Content Fonts | |
| * | |
| * Content font variables are used for typography of user generated content. | |
| * | |
| * The font sizing here is done assuming that the body font size of --jp-content-font-size1 | |
| * is applied to a parent element. When children elements, such as headings, are sized | |
| * in em all things will be computed relative to that body size. | |
| */ | |
| --jp-content-line-height: 1.6; | |
| --jp-content-font-scale-factor: 1.2; | |
| --jp-content-font-size0: 0.83333em; | |
| --jp-content-font-size1: 14px; /* Base font size */ | |
| --jp-content-font-size2: 1.2em; | |
| --jp-content-font-size3: 1.44em; | |
| --jp-content-font-size4: 1.728em; | |
| --jp-content-font-size5: 2.0736em; | |
| /* This gives a magnification of about 125% in presentation mode over normal. */ | |
| --jp-content-presentation-font-size1: 17px; | |
| --jp-content-heading-line-height: 1; | |
| --jp-content-heading-margin-top: 1.2em; | |
| --jp-content-heading-margin-bottom: 0.8em; | |
| --jp-content-heading-font-weight: 500; | |
| /* Defaults use Material Design specification */ | |
| --jp-content-font-color0: rgba(0, 0, 0, 1); | |
| --jp-content-font-color1: rgba(0, 0, 0, 0.87); | |
| --jp-content-font-color2: rgba(0, 0, 0, 0.54); | |
| --jp-content-font-color3: rgba(0, 0, 0, 0.38); | |
| --jp-content-link-color: var(--md-blue-900); | |
| --jp-content-font-family: system-ui, -apple-system, blinkmacsystemfont, | |
| 'Segoe UI', helvetica, arial, sans-serif, 'Apple Color Emoji', | |
| 'Segoe UI Emoji', 'Segoe UI Symbol'; | |
| /* | |
| * Code Fonts | |
| * | |
| * Code font variables are used for typography of code and other monospaces content. | |
| */ | |
| --jp-code-font-size: 13px; | |
| --jp-code-line-height: 1.3077; /* 17px for 13px base */ | |
| --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ | |
| --jp-code-font-family-default: menlo, consolas, 'DejaVu Sans Mono', monospace; | |
| --jp-code-font-family: var(--jp-code-font-family-default); | |
| /* This gives a magnification of about 125% in presentation mode over normal. */ | |
| --jp-code-presentation-font-size: 16px; | |
| /* may need to tweak cursor width if you change font size */ | |
| --jp-code-cursor-width0: 1.4px; | |
| --jp-code-cursor-width1: 2px; | |
| --jp-code-cursor-width2: 4px; | |
| /* Layout | |
| * | |
| * The following are the main layout colors use in JupyterLab. In a light | |
| * theme these would go from light to dark. | |
| */ | |
| --jp-layout-color0: white; | |
| --jp-layout-color1: white; | |
| --jp-layout-color2: var(--md-grey-200); | |
| --jp-layout-color3: var(--md-grey-400); | |
| --jp-layout-color4: var(--md-grey-600); | |
| /* Inverse Layout | |
| * | |
| * The following are the inverse layout colors use in JupyterLab. In a light | |
| * theme these would go from dark to light. | |
| */ | |
| --jp-inverse-layout-color0: #111; | |
| --jp-inverse-layout-color1: var(--md-grey-900); | |
| --jp-inverse-layout-color2: var(--md-grey-800); | |
| --jp-inverse-layout-color3: var(--md-grey-700); | |
| --jp-inverse-layout-color4: var(--md-grey-600); | |
| /* Brand/accent */ | |
| --jp-brand-color0: var(--md-blue-900); | |
| --jp-brand-color1: var(--md-blue-700); | |
| --jp-brand-color2: var(--md-blue-300); | |
| --jp-brand-color3: var(--md-blue-100); | |
| --jp-brand-color4: var(--md-blue-50); | |
| --jp-accent-color0: var(--md-green-900); | |
| --jp-accent-color1: var(--md-green-700); | |
| --jp-accent-color2: var(--md-green-300); | |
| --jp-accent-color3: var(--md-green-100); | |
| /* State colors (warn, error, success, info) */ | |
| --jp-warn-color0: var(--md-orange-900); | |
| --jp-warn-color1: var(--md-orange-700); | |
| --jp-warn-color2: var(--md-orange-300); | |
| --jp-warn-color3: var(--md-orange-100); | |
| --jp-error-color0: var(--md-red-900); | |
| --jp-error-color1: var(--md-red-700); | |
| --jp-error-color2: var(--md-red-300); | |
| --jp-error-color3: var(--md-red-100); | |
| --jp-success-color0: var(--md-green-900); | |
| --jp-success-color1: var(--md-green-700); | |
| --jp-success-color2: var(--md-green-300); | |
| --jp-success-color3: var(--md-green-100); | |
| --jp-info-color0: var(--md-cyan-900); | |
| --jp-info-color1: var(--md-cyan-700); | |
| --jp-info-color2: var(--md-cyan-300); | |
| --jp-info-color3: var(--md-cyan-100); | |
| /* Cell specific styles */ | |
| --jp-cell-padding: 5px; | |
| --jp-cell-collapser-width: 8px; | |
| --jp-cell-collapser-min-height: 20px; | |
| --jp-cell-collapser-not-active-hover-opacity: 0.6; | |
| --jp-cell-editor-background: var(--md-grey-100); | |
| --jp-cell-editor-border-color: var(--md-grey-300); | |
| --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); | |
| --jp-cell-editor-active-background: var(--jp-layout-color0); | |
| --jp-cell-editor-active-border-color: var(--jp-brand-color1); | |
| --jp-cell-prompt-width: 64px; | |
| --jp-cell-prompt-font-family: var(--jp-code-font-family-default); | |
| --jp-cell-prompt-letter-spacing: 0; | |
| --jp-cell-prompt-opacity: 1; | |
| --jp-cell-prompt-not-active-opacity: 0.5; | |
| --jp-cell-prompt-not-active-font-color: var(--md-grey-700); | |
| /* A custom blend of MD grey and blue 600 | |
| * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ | |
| --jp-cell-inprompt-font-color: #307fc1; | |
| /* A custom blend of MD grey and orange 600 | |
| * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ | |
| --jp-cell-outprompt-font-color: #bf5b3d; | |
| /* Notebook specific styles */ | |
| --jp-notebook-padding: 10px; | |
| --jp-notebook-select-background: var(--jp-layout-color1); | |
| --jp-notebook-multiselected-color: var(--md-blue-50); | |
| /* The scroll padding is calculated to fill enough space at the bottom of the | |
| notebook to show one single-line cell (with appropriate padding) at the top | |
| when the notebook is scrolled all the way to the bottom. We also subtract one | |
| pixel so that no scrollbar appears if we have just one single-line cell in the | |
| notebook. This padding is to enable a 'scroll past end' feature in a notebook. | |
| */ | |
| --jp-notebook-scroll-padding: calc( | |
| 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - | |
| var(--jp-code-padding) - var(--jp-cell-padding) - 1px | |
| ); | |
| /* Rendermime styles */ | |
| --jp-rendermime-error-background: #fdd; | |
| --jp-rendermime-table-row-background: var(--md-grey-100); | |
| --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); | |
| /* Dialog specific styles */ | |
| --jp-dialog-background: rgba(0, 0, 0, 0.25); | |
| /* Console specific styles */ | |
| --jp-console-padding: 10px; | |
| /* Toolbar specific styles */ | |
| --jp-toolbar-border-color: var(--jp-border-color1); | |
| --jp-toolbar-micro-height: 8px; | |
| --jp-toolbar-background: var(--jp-layout-color1); | |
| --jp-toolbar-box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.24); | |
| --jp-toolbar-header-margin: 4px 4px 0 4px; | |
| --jp-toolbar-active-background: var(--md-grey-300); | |
| /* Statusbar specific styles */ | |
| --jp-statusbar-height: 24px; | |
| /* Input field styles */ | |
| --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); | |
| --jp-input-active-background: var(--jp-layout-color1); | |
| --jp-input-hover-background: var(--jp-layout-color1); | |
| --jp-input-background: var(--md-grey-100); | |
| --jp-input-border-color: var(--jp-inverse-border-color); | |
| --jp-input-active-border-color: var(--jp-brand-color1); | |
| --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); | |
| /* General editor styles */ | |
| --jp-editor-selected-background: #d9d9d9; | |
| --jp-editor-selected-focused-background: #d7d4f0; | |
| --jp-editor-cursor-color: var(--jp-ui-font-color0); | |
| /* Code mirror specific styles */ | |
| --jp-mirror-editor-keyword-color: #008000; | |
| --jp-mirror-editor-atom-color: #88f; | |
| --jp-mirror-editor-number-color: #080; | |
| --jp-mirror-editor-def-color: #00f; | |
| --jp-mirror-editor-variable-color: var(--md-grey-900); | |
| --jp-mirror-editor-variable-2-color: rgb(0, 54, 109); | |
| --jp-mirror-editor-variable-3-color: #085; | |
| --jp-mirror-editor-punctuation-color: #05a; | |
| --jp-mirror-editor-property-color: #05a; | |
| --jp-mirror-editor-operator-color: #a2f; | |
| --jp-mirror-editor-comment-color: #408080; | |
| --jp-mirror-editor-string-color: #ba2121; | |
| --jp-mirror-editor-string-2-color: #708; | |
| --jp-mirror-editor-meta-color: #a2f; | |
| --jp-mirror-editor-qualifier-color: #555; | |
| --jp-mirror-editor-builtin-color: #008000; | |
| --jp-mirror-editor-bracket-color: #997; | |
| --jp-mirror-editor-tag-color: #170; | |
| --jp-mirror-editor-attribute-color: #00c; | |
| --jp-mirror-editor-header-color: blue; | |
| --jp-mirror-editor-quote-color: #090; | |
| --jp-mirror-editor-link-color: #00c; | |
| --jp-mirror-editor-error-color: #f00; | |
| --jp-mirror-editor-hr-color: #999; | |
| /* | |
| RTC user specific colors. | |
| These colors are used for the cursor, username in the editor, | |
| and the icon of the user. | |
| */ | |
| --jp-collaborator-color1: #ffad8e; | |
| --jp-collaborator-color2: #dac83d; | |
| --jp-collaborator-color3: #72dd76; | |
| --jp-collaborator-color4: #00e4d0; | |
| --jp-collaborator-color5: #45d4ff; | |
| --jp-collaborator-color6: #e2b1ff; | |
| --jp-collaborator-color7: #ff9de6; | |
| /* Vega extension styles */ | |
| --jp-vega-background: white; | |
| /* Sidebar-related styles */ | |
| --jp-sidebar-min-width: 250px; | |
| /* Search-related styles */ | |
| --jp-search-toggle-off-opacity: 0.5; | |
| --jp-search-toggle-hover-opacity: 0.8; | |
| --jp-search-toggle-on-opacity: 1; | |
| --jp-search-selected-match-background-color: rgb(245, 200, 0); | |
| --jp-search-selected-match-color: black; | |
| --jp-search-unselected-match-background-color: var( | |
| --jp-inverse-layout-color0 | |
| ); | |
| --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); | |
| /* Icon colors that work well with light or dark backgrounds */ | |
| --jp-icon-contrast-color0: var(--md-purple-600); | |
| --jp-icon-contrast-color1: var(--md-green-600); | |
| --jp-icon-contrast-color2: var(--md-pink-600); | |
| --jp-icon-contrast-color3: var(--md-blue-600); | |
| /* Button colors */ | |
| --jp-accept-color-normal: var(--md-blue-700); | |
| --jp-accept-color-hover: var(--md-blue-800); | |
| --jp-accept-color-active: var(--md-blue-900); | |
| --jp-warn-color-normal: var(--md-red-700); | |
| --jp-warn-color-hover: var(--md-red-800); | |
| --jp-warn-color-active: var(--md-red-900); | |
| --jp-reject-color-normal: var(--md-grey-600); | |
| --jp-reject-color-hover: var(--md-grey-700); | |
| --jp-reject-color-active: var(--md-grey-800); | |
| /* File or activity icons and switch semantic variables */ | |
| --jp-jupyter-icon-color: #f37626; | |
| --jp-notebook-icon-color: #f37626; | |
| --jp-json-icon-color: var(--md-orange-700); | |
| --jp-console-icon-background-color: var(--md-blue-700); | |
| --jp-console-icon-color: white; | |
| --jp-terminal-icon-background-color: var(--md-grey-800); | |
| --jp-terminal-icon-color: var(--md-grey-200); | |
| --jp-text-editor-icon-color: var(--md-grey-700); | |
| --jp-inspector-icon-color: var(--md-grey-700); | |
| --jp-switch-color: var(--md-grey-400); | |
| --jp-switch-true-position-color: var(--md-orange-900); | |
| } | |
| </style> | |
| <style type="text/css"> | |
| /* Force rendering true colors when outputing to pdf */ | |
| * { | |
| -webkit-print-color-adjust: exact; | |
| } | |
| /* Misc */ | |
| a.anchor-link { | |
| display: none; | |
| } | |
| /* Input area styling */ | |
| .jp-InputArea { | |
| overflow: hidden; | |
| } | |
| .jp-InputArea-editor { | |
| overflow: hidden; | |
| } | |
| .cm-editor.cm-s-jupyter .highlight pre { | |
| /* weird, but --jp-code-padding defined to be 5px but 4px horizontal padding is hardcoded for pre.cm-line */ | |
| padding: var(--jp-code-padding) 4px; | |
| margin: 0; | |
| font-family: inherit; | |
| font-size: inherit; | |
| line-height: inherit; | |
| color: inherit; | |
| } | |
| .jp-OutputArea-output pre { | |
| line-height: inherit; | |
| font-family: inherit; | |
| } | |
| .jp-RenderedText pre { | |
| color: var(--jp-content-font-color1); | |
| font-size: var(--jp-code-font-size); | |
| } | |
| /* Hiding the collapser by default */ | |
| .jp-Collapser { | |
| display: none; | |
| } | |
| @page { | |
| margin: 0.5in; /* Margin for each printed piece of paper */ | |
| } | |
| @media print { | |
| .jp-Cell-inputWrapper, | |
| .jp-Cell-outputWrapper { | |
| display: block; | |
| } | |
| } | |
| </style> | |
| <!-- Load mathjax --> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/latest.js?config=TeX-AMS_CHTML-full,Safe"> </script> | |
| <!-- MathJax configuration --> | |
| <script type="text/x-mathjax-config"> | |
| init_mathjax = function() { | |
| if (window.MathJax) { | |
| // MathJax loaded | |
| MathJax.Hub.Config({ | |
| TeX: { | |
| equationNumbers: { | |
| autoNumber: "AMS", | |
| useLabelIds: true | |
| } | |
| }, | |
| tex2jax: { | |
| inlineMath: [ ['$','$'], ["\\(","\\)"] ], | |
| displayMath: [ ['$$','$$'], ["\\[","\\]"] ], | |
| processEscapes: true, | |
| processEnvironments: true | |
| }, | |
| displayAlign: 'center', | |
| messageStyle: 'none', | |
| CommonHTML: { | |
| linebreaks: { | |
| automatic: true | |
| } | |
| } | |
| }); | |
| MathJax.Hub.Queue(["Typeset", MathJax.Hub]); | |
| } | |
| } | |
| init_mathjax(); | |
| </script> | |
| <!-- End of mathjax configuration --><script type="module"> | |
| document.addEventListener("DOMContentLoaded", async () => { | |
| const diagrams = document.querySelectorAll(".jp-Mermaid > pre.mermaid"); | |
| // do not load mermaidjs if not needed | |
| if (!diagrams.length) { | |
| return; | |
| } | |
| const mermaid = (await import("https://cdnjs.cloudflare.com/ajax/libs/mermaid/10.7.0/mermaid.esm.min.mjs")).default; | |
| const parser = new DOMParser(); | |
| mermaid.initialize({ | |
| maxTextSize: 100000, | |
| maxEdges: 100000, | |
| startOnLoad: false, | |
| fontFamily: window | |
| .getComputedStyle(document.body) | |
| .getPropertyValue("--jp-ui-font-family"), | |
| theme: document.querySelector("body[data-jp-theme-light='true']") | |
| ? "default" | |
| : "dark", | |
| }); | |
| let _nextMermaidId = 0; | |
| function makeMermaidImage(svg) { | |
| const img = document.createElement("img"); | |
| const doc = parser.parseFromString(svg, "image/svg+xml"); | |
| const svgEl = doc.querySelector("svg"); | |
| const { maxWidth } = svgEl?.style || {}; | |
| const firstTitle = doc.querySelector("title"); | |
| const firstDesc = doc.querySelector("desc"); | |
| img.setAttribute("src", `data:image/svg+xml,${encodeURIComponent(svg)}`); | |
| if (maxWidth) { | |
| img.width = parseInt(maxWidth); | |
| } | |
| if (firstTitle) { | |
| img.setAttribute("alt", firstTitle.textContent); | |
| } | |
| if (firstDesc) { | |
| const caption = document.createElement("figcaption"); | |
| caption.className = "sr-only"; | |
| caption.textContent = firstDesc.textContent; | |
| return [img, caption]; | |
| } | |
| return [img]; | |
| } | |
| async function makeMermaidError(text) { | |
| let errorMessage = ""; | |
| try { | |
| await mermaid.parse(text); | |
| } catch (err) { | |
| errorMessage = `${err}`; | |
| } | |
| const result = document.createElement("details"); | |
| result.className = 'jp-RenderedMermaid-Details'; | |
| const summary = document.createElement("summary"); | |
| summary.className = 'jp-RenderedMermaid-Summary'; | |
| const pre = document.createElement("pre"); | |
| const code = document.createElement("code"); | |
| code.innerText = text; | |
| pre.appendChild(code); | |
| summary.appendChild(pre); | |
| result.appendChild(summary); | |
| const warning = document.createElement("pre"); | |
| warning.innerText = errorMessage; | |
| result.appendChild(warning); | |
| return [result]; | |
| } | |
| async function renderOneMarmaid(src) { | |
| const id = `jp-mermaid-${_nextMermaidId++}`; | |
| const parent = src.parentNode; | |
| let raw = src.textContent.trim(); | |
| const el = document.createElement("div"); | |
| el.style.visibility = "hidden"; | |
| document.body.appendChild(el); | |
| let results = null; | |
| let output = null; | |
| try { | |
| let { svg } = await mermaid.render(id, raw, el); | |
| svg = cleanMermaidSvg(svg); | |
| results = makeMermaidImage(svg); | |
| output = document.createElement("figure"); | |
| results.map(output.appendChild, output); | |
| } catch (err) { | |
| parent.classList.add("jp-mod-warning"); | |
| results = await makeMermaidError(raw); | |
| output = results[0]; | |
| } finally { | |
| el.remove(); | |
| } | |
| parent.classList.add("jp-RenderedMermaid"); | |
| parent.appendChild(output); | |
| } | |
| /** | |
| * Post-process to ensure mermaid diagrams contain only valid SVG and XHTML. | |
| */ | |
| function cleanMermaidSvg(svg) { | |
| return svg.replace(RE_VOID_ELEMENT, replaceVoidElement); | |
| } | |
| /** | |
| * A regular expression for all void elements, which may include attributes and | |
| * a slash. | |
| * | |
| * @see https://developer.mozilla.org/en-US/docs/Glossary/Void_element | |
| * | |
| * Of these, only `<br>` is generated by Mermaid in place of `\n`, | |
| * but _any_ "malformed" tag will break the SVG rendering entirely. | |
| */ | |
| const RE_VOID_ELEMENT = | |
| /<\s*(area|base|br|col|embed|hr|img|input|link|meta|param|source|track|wbr)\s*([^>]*?)\s*>/gi; | |
| /** | |
| * Ensure a void element is closed with a slash, preserving any attributes. | |
| */ | |
| function replaceVoidElement(match, tag, rest) { | |
| rest = rest.trim(); | |
| if (!rest.endsWith('/')) { | |
| rest = `${rest} /`; | |
| } | |
| return `<${tag} ${rest}>`; | |
| } | |
| void Promise.all([...diagrams].map(renderOneMarmaid)); | |
| }); | |
| </script> | |
| <style> | |
| .jp-Mermaid:not(.jp-RenderedMermaid) { | |
| display: none; | |
| } | |
| .jp-RenderedMermaid { | |
| overflow: auto; | |
| display: flex; | |
| } | |
| .jp-RenderedMermaid.jp-mod-warning { | |
| width: auto; | |
| padding: 0.5em; | |
| margin-top: 0.5em; | |
| border: var(--jp-border-width) solid var(--jp-warn-color2); | |
| 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; | |
| } | |
| .jp-RenderedMermaid figure { | |
| margin: 0; | |
| overflow: auto; | |
| max-width: 100%; | |
| } | |
| .jp-RenderedMermaid img { | |
| max-width: 100%; | |
| } | |
| .jp-RenderedMermaid-Details > pre { | |
| margin-top: 1em; | |
| } | |
| .jp-RenderedMermaid-Summary { | |
| color: var(--jp-warn-color2); | |
| } | |
| .jp-RenderedMermaid:not(.jp-mod-warning) pre { | |
| display: none; | |
| } | |
| .jp-RenderedMermaid-Summary > pre { | |
| display: inline-block; | |
| white-space: normal; | |
| } | |
| </style> | |
| <!-- End of mermaid configuration --></head> | |
| <body class="jp-Notebook" data-jp-theme-light="true" data-jp-theme-name="JupyterLab Light"> | |
| <main><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=2b17940f"> | |
| <div class="jp-Cell-inputWrapper" tabindex="0"> | |
| <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> | |
| </div> | |
| <div class="jp-InputArea jp-Cell-inputArea"> | |
| <div class="jp-InputPrompt jp-InputArea-prompt">In [1]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="sd">"""Post-crash recovery analysis.</span> | |
| <span class="sd">Investigates whether crash events on manipulation-susceptible tokens</span> | |
| <span class="sd">can be profitably traded by going long after the crash completes.</span> | |
| <span class="sd">Reference: #348 (crash strategy), #346/#310 (crime detection)</span> | |
| <span class="sd">"""</span> | |
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| <pre>'Post-crash recovery analysis.\n\nInvestigates whether crash events on manipulation-susceptible tokens\ncan be profitably traded by going long after the crash completes.\n\nReference: #348 (crash strategy), #346/#310 (crime detection)\n'</pre> | |
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| <h1 id="Post-Crash-Recovery-Analysis">Post-Crash Recovery Analysis<a class="anchor-link" href="#Post-Crash-Recovery-Analysis">¶</a></h1><p><strong>Question:</strong> Can one systematically detect crash events on manipulation-susceptible | |
| tokens and profitably go long on the recovery?</p> | |
| <p><strong>Background:</strong> The crash analysis (#348) showed that low-liquidity tokens experience | |
| repeated 10-20%+ drops driven by thin constituent spot order books. The crime detection | |
| analysis (#346) found that continuous premium mean-reversion <em>fails</em> on these tokens. | |
| This notebook tests an <strong>event-driven</strong> approach instead: detect crash events, wait for | |
| stabilization, then go long to capture recovery.</p> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [2]:</div> | |
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| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">sys</span> | |
| <span class="kn">from</span><span class="w"> </span><span class="nn">pathlib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Path</span> | |
| <span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span> | |
| <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span> | |
| <span class="kn">import</span><span class="w"> </span><span class="nn">pandas</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pd</span> | |
| <span class="n">sys</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="s2">".."</span><span class="p">)</span><span class="o">.</span><span class="n">resolve</span><span class="p">()))</span> | |
| <span class="kn">from</span><span class="w"> </span><span class="nn">shared</span><span class="w"> </span><span class="kn">import</span> <span class="p">(</span> | |
| <span class="n">load_binance_futures_klines</span><span class="p">,</span> | |
| <span class="n">load_binance_futures_index_price_klines</span><span class="p">,</span> | |
| <span class="n">binance_symbol</span><span class="p">,</span> | |
| <span class="n">should_exclude</span><span class="p">,</span> | |
| <span class="p">)</span> | |
| <span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s2">"seaborn-v0_8-whitegrid"</span><span class="p">)</span> | |
| <span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">"figure.figsize"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
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| <h2 id="1.-Token-Selection">1. Token Selection<a class="anchor-link" href="#1.-Token-Selection">¶</a></h2><p>Focus on tokens that are susceptible to index manipulation — those with high | |
| OI relative to constituent spot depth. Use the top-50 by Binance futures OI | |
| as the candidate pool, excluding majors and stablecoins.</p> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [3]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
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| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Load the OI universe — point-in-time membership panel (date x coin -> bool).</span> | |
| <span class="c1"># A coin is only eligible for crash detection on dates when it was in the top-50</span> | |
| <span class="c1"># by OI, avoiding lookahead bias.</span> | |
| <span class="kn">from</span><span class="w"> </span><span class="nn">universe</span><span class="w"> </span><span class="kn">import</span> <span class="n">OIUniverse</span> | |
| <span class="n">oi_universe</span> <span class="o">=</span> <span class="n">OIUniverse</span><span class="o">.</span><span class="n">from_cache</span><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">lag</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> | |
| <span class="n">membership</span> <span class="o">=</span> <span class="n">oi_universe</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">50</span><span class="p">)</span> | |
| <span class="c1"># Load data for all coins that were ever in top-50 (kline loading is separate</span> | |
| <span class="c1"># from the point-in-time filter, which is applied after crash detection).</span> | |
| <span class="c1"># Deduplicate 1000x aliases (e.g. PEPE/1000PEPE map to the same Binance stream).</span> | |
| <span class="n">seen_binance</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> | |
| <span class="n">ever_in_top50</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">membership</span><span class="o">.</span><span class="n">columns</span><span class="p">):</span> | |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">membership</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">any</span><span class="p">()</span> <span class="ow">or</span> <span class="n">should_exclude</span><span class="p">(</span><span class="n">c</span><span class="p">):</span> | |
| <span class="k">continue</span> | |
| <span class="n">bs</span> <span class="o">=</span> <span class="n">binance_symbol</span><span class="p">(</span><span class="n">c</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">bs</span> <span class="ow">in</span> <span class="n">seen_binance</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">seen_binance</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">bs</span><span class="p">)</span> | |
| <span class="n">ever_in_top50</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Coins ever in top-50 OI: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">ever_in_top50</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">"Membership panel: </span><span class="si">{</span><span class="n">membership</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2"> dates x </span><span class="si">{</span><span class="n">membership</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2"> coins"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">oi_universe</span><span class="o">.</span><span class="n">panel</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">oi_universe</span><span class="o">.</span><span class="n">panel</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| </pre></div> | |
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| <pre>Coins ever in top-50 OI: 316 | |
| Membership panel: 2201 dates x 1079 coins | |
| Date range: 2020-03-04 to 2026-03-15 | |
| </pre> | |
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| <pre>/Users/andreas/src/abrkn/norrath/.worktrees/issue-355-crash-recovery/analysis/universe.py:154: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)` | |
| return pd.DataFrame(rows).T.fillna(False).reindex( | |
| </pre> | |
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| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Analysis period</span> | |
| <span class="n">START</span> <span class="o">=</span> <span class="s2">"2020-01-01"</span> | |
| <span class="n">END</span> <span class="o">=</span> <span class="s2">"2025-12-31"</span> | |
| <span class="c1"># Load hourly futures klines (cache only, no downloads — avoids multi-hour wait)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"Loading hourly klines from cache..."</span><span class="p">)</span> | |
| <span class="n">klines</span> <span class="o">=</span> <span class="p">{}</span> | |
| <span class="n">failed</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">coin</span> <span class="ow">in</span> <span class="n">ever_in_top50</span><span class="p">:</span> | |
| <span class="k">try</span><span class="p">:</span> | |
| <span class="n">df</span> <span class="o">=</span> <span class="n">load_binance_futures_klines</span><span class="p">(</span> | |
| <span class="n">binance_symbol</span><span class="p">(</span><span class="n">coin</span><span class="p">),</span> <span class="n">interval</span><span class="o">=</span><span class="s2">"1h"</span><span class="p">,</span> | |
| <span class="n">start</span><span class="o">=</span><span class="n">START</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">END</span><span class="p">,</span> <span class="n">progress</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">download</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> | |
| <span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">df</span><span class="p">)</span> <span class="o">></span> <span class="mi">100</span><span class="p">:</span> | |
| <span class="n">klines</span><span class="p">[</span><span class="n">coin</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span> | |
| <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span> | |
| <span class="n">failed</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">coin</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">klines</span><span class="p">)</span><span class="si">}</span><span class="s2"> coins (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">failed</span><span class="p">)</span><span class="si">}</span><span class="s2"> skipped — no cached data)"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">klines</span><span class="p">:</span> | |
| <span class="n">sample</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">klines</span><span class="o">.</span><span class="n">keys</span><span class="p">())[:</span><span class="mi">10</span><span class="p">]</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sample coins: </span><span class="si">{</span><span class="n">sample</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
| </div> | |
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| <pre>Loading hourly klines from cache... | |
| </pre> | |
| </div> | |
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| <pre>Loaded 201 coins (0 skipped — no cached data) | |
| Sample coins: ['0G', '1000BONK', '1000FLOKI', '1000PEPE', '1INCH', 'AAVE', 'ACT', 'ADA', 'AERGO', 'AEVO'] | |
| </pre> | |
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| <h2 id="2.-Crash-Event-Detection">2. Crash Event Detection<a class="anchor-link" href="#2.-Crash-Event-Detection">¶</a></h2><p>A "crash" is defined as a drop exceeding a threshold within a rolling window. | |
| Parameters:</p> | |
| <ul> | |
| <li><strong>Window:</strong> 4 hours (the crash must happen within this window)</li> | |
| <li><strong>Threshold:</strong> -10% (minimum drop to qualify as a crash)</li> | |
| <li><strong>Cooldown:</strong> 24 hours (no overlapping crash events)</li> | |
| </ul> | |
| <p><code>low_price</code> is the close at detection time (no forward-looking trough) to | |
| avoid lookahead bias. Recovery metrics are measured from this level.</p> | |
| </div> | |
| </div> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [5]:</div> | |
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| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">detect_crashes</span><span class="p">(</span> | |
| <span class="n">close</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> | |
| <span class="n">window_hours</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span> | |
| <span class="n">threshold</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> | |
| <span class="n">cooldown_hours</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">24</span><span class="p">,</span> | |
| <span class="p">)</span> <span class="o">-></span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span> | |
| <span class="w"> </span><span class="sd">"""Detect crash events in an hourly price series.</span> | |
| <span class="sd"> Returns DataFrame with columns: time, drop_pct, low_price, pre_crash_price.</span> | |
| <span class="sd"> low_price is the close at detection time (no lookahead).</span> | |
| <span class="sd"> """</span> | |
| <span class="c1"># Drop from recent peak to current price within the window</span> | |
| <span class="n">peak</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">shift</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">rolling</span><span class="p">(</span><span class="n">window_hours</span><span class="p">,</span> <span class="n">min_periods</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> | |
| <span class="n">drop</span> <span class="o">=</span> <span class="p">(</span><span class="n">close</span> <span class="o">-</span> <span class="n">peak</span><span class="p">)</span> <span class="o">/</span> <span class="n">peak</span> | |
| <span class="n">crash_mask</span> <span class="o">=</span> <span class="n">drop</span> <span class="o"><=</span> <span class="n">threshold</span> | |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">crash_mask</span><span class="o">.</span><span class="n">any</span><span class="p">():</span> | |
| <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"time"</span><span class="p">,</span> <span class="s2">"drop_pct"</span><span class="p">,</span> <span class="s2">"low_price"</span><span class="p">,</span> <span class="s2">"pre_crash_price"</span><span class="p">])</span> | |
| <span class="c1"># Apply cooldown: keep only the first event in each cooldown window</span> | |
| <span class="n">events</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="n">last_event_time</span> <span class="o">=</span> <span class="kc">None</span> | |
| <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">close</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">crash_mask</span><span class="p">]:</span> | |
| <span class="k">if</span> <span class="n">last_event_time</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> | |
| <span class="n">hours_since</span> <span class="o">=</span> <span class="p">(</span><span class="n">t</span> <span class="o">-</span> <span class="n">last_event_time</span><span class="p">)</span><span class="o">.</span><span class="n">total_seconds</span><span class="p">()</span> <span class="o">/</span> <span class="mi">3600</span> | |
| <span class="k">if</span> <span class="n">hours_since</span> <span class="o"><</span> <span class="n">cooldown_hours</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">events</span><span class="o">.</span><span class="n">append</span><span class="p">({</span> | |
| <span class="s2">"time"</span><span class="p">:</span> <span class="n">t</span><span class="p">,</span> | |
| <span class="s2">"drop_pct"</span><span class="p">:</span> <span class="n">drop</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> | |
| <span class="s2">"low_price"</span><span class="p">:</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> | |
| <span class="s2">"pre_crash_price"</span><span class="p">:</span> <span class="n">peak</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> | |
| <span class="p">})</span> | |
| <span class="n">last_event_time</span> <span class="o">=</span> <span class="n">t</span> | |
| <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">events</span><span class="p">)</span> | |
| <span class="c1"># Detect crashes across all coins</span> | |
| <span class="n">all_crashes</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">coin</span><span class="p">,</span> <span class="n">df</span> <span class="ow">in</span> <span class="n">klines</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> | |
| <span class="n">crashes</span> <span class="o">=</span> <span class="n">detect_crashes</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s2">"close"</span><span class="p">])</span> | |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">crashes</span><span class="o">.</span><span class="n">empty</span><span class="p">:</span> | |
| <span class="n">crashes</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> <span class="o">=</span> <span class="n">coin</span> | |
| <span class="n">all_crashes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">crashes</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">all_crashes</span><span class="p">:</span> | |
| <span class="n">crashes_raw</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">all_crashes</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> | |
| <span class="k">else</span><span class="p">:</span> | |
| <span class="n">crashes_raw</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"time"</span><span class="p">,</span> <span class="s2">"drop_pct"</span><span class="p">,</span> <span class="s2">"low_price"</span><span class="p">,</span> <span class="s2">"pre_crash_price"</span><span class="p">,</span> <span class="s2">"coin"</span><span class="p">])</span> | |
| <span class="c1"># Point-in-time filter: keep only crashes where the coin was in the top-50</span> | |
| <span class="c1"># OI universe on the crash date. This avoids lookahead bias — a coin that</span> | |
| <span class="c1"># only enters the top-50 in 2024 will not have its 2022 crashes included.</span> | |
| <span class="k">def</span><span class="w"> </span><span class="nf">is_in_universe</span><span class="p">(</span><span class="n">row</span><span class="p">):</span> | |
| <span class="n">crash_date</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span><span class="o">.</span><span class="n">normalize</span><span class="p">()</span> | |
| <span class="n">coin</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> | |
| <span class="k">if</span> <span class="n">coin</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">membership</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span> | |
| <span class="k">return</span> <span class="kc">False</span> | |
| <span class="n">valid</span> <span class="o">=</span> <span class="n">membership</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">membership</span><span class="o">.</span><span class="n">index</span> <span class="o"><=</span> <span class="n">crash_date</span><span class="p">]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">valid</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="k">return</span> <span class="kc">False</span> | |
| <span class="k">return</span> <span class="n">membership</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">valid</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">coin</span><span class="p">]</span> | |
| <span class="n">mask</span> <span class="o">=</span> <span class="n">crashes_raw</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">is_in_universe</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> | |
| <span class="n">crashes_df</span> <span class="o">=</span> <span class="n">crashes_raw</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Raw crash events: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_raw</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">"After point-in-time OI filter: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> "</span> | |
| <span class="sa">f</span><span class="s2">"(</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_raw</span><span class="p">)</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> removed — coin not in top-50 at crash date)"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Coins with crashes: </span><span class="si">{</span><span class="n">crashes_df</span><span class="p">[</span><span class="s1">'coin'</span><span class="p">]</span><span class="o">.</span><span class="n">nunique</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">"</span><span class="se">\n</span><span class="s2">Drop distribution:"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="n">crashes_df</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span><span class="o">.</span><span class="n">describe</span><span class="p">())</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="jp-Cell-outputWrapper"> | |
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| <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> | |
| <pre>Raw crash events: 4977 | |
| After point-in-time OI filter: 2245 (2732 removed — coin not in top-50 at crash date) | |
| Coins with crashes: 150 | |
| Drop distribution: | |
| count 2245.000000 | |
| mean -0.126355 | |
| std 0.040387 | |
| min -0.780268 | |
| 25% -0.131555 | |
| 50% -0.114395 | |
| 75% -0.105807 | |
| max -0.100000 | |
| Name: drop_pct, dtype: float64 | |
| </pre> | |
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| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=92757c13"> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [6]:</div> | |
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| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Distribution of crashes by magnitude</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">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">crashes_df</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"black"</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.7</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Drop (%)"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Count"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Distribution of Crash Magnitudes"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=-</span><span class="mi">15</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"red"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">"-15%"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=-</span><span class="mi">20</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"darkred"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">"-20%"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span> | |
| <span class="c1"># Crashes per coin (top 20)</span> | |
| <span class="n">top_crashers</span> <span class="o">=</span> <span class="n">crashes_df</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">barh</span><span class="p">(</span><span class="n">top_crashers</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">top_crashers</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"steelblue"</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"black"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Number of Crash Events"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Top 20 Coins by Crash Frequency"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">invert_yaxis</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> | |
| </div> | |
| </div> | |
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| <div class="jp-OutputArea-child"> | |
| <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> | |
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"/> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
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| <h2 id="3.-Recovery-Characterization">3. Recovery Characterization<a class="anchor-link" href="#3.-Recovery-Characterization">¶</a></h2><p>For each crash event, measure the recovery over the next 1, 4, 12, 24, 48, 72h. | |
| Recovery is defined as <code>(price_t - crash_low) / (pre_crash_price - crash_low)</code>, | |
| i.e. 100% means the price fully recovered to the pre-crash level.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=42dcd4b7"> | |
| <div class="jp-Cell-inputWrapper" tabindex="0"> | |
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| </div> | |
| <div class="jp-InputArea jp-Cell-inputArea"> | |
| <div class="jp-InputPrompt jp-InputArea-prompt">In [7]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">measure_recovery</span><span class="p">(</span> | |
| <span class="n">close</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> | |
| <span class="n">crash_time</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">,</span> | |
| <span class="n">pre_crash_price</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> | |
| <span class="n">low_price</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> | |
| <span class="n">horizons_hours</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">24</span><span class="p">,</span> <span class="mi">48</span><span class="p">,</span> <span class="mi">72</span><span class="p">],</span> | |
| <span class="p">)</span> <span class="o">-></span> <span class="nb">dict</span><span class="p">:</span> | |
| <span class="w"> </span><span class="sd">"""Measure recovery at various horizons after a crash event."""</span> | |
| <span class="n">result</span> <span class="o">=</span> <span class="p">{}</span> | |
| <span class="n">crash_range</span> <span class="o">=</span> <span class="n">pre_crash_price</span> <span class="o">-</span> <span class="n">low_price</span> | |
| <span class="k">if</span> <span class="n">crash_range</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">out</span> <span class="o">=</span> <span class="p">{</span><span class="sa">f</span><span class="s2">"recovery_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">horizons_hours</span><span class="p">}</span> | |
| <span class="n">out</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="sa">f</span><span class="s2">"return_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">horizons_hours</span><span class="p">})</span> | |
| <span class="n">out</span><span class="p">[</span><span class="s2">"further_dd"</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> | |
| <span class="k">return</span> <span class="n">out</span> | |
| <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">horizons_hours</span><span class="p">:</span> | |
| <span class="n">target_time</span> <span class="o">=</span> <span class="n">crash_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="n">h</span><span class="p">)</span> | |
| <span class="c1"># Start from after the crash candle</span> | |
| <span class="n">future</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">crash_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="mi">1</span><span class="p">):]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">future</span><span class="p">)</span> <span class="o"><</span> <span class="mi">1</span><span class="p">:</span> | |
| <span class="n">result</span><span class="p">[</span><span class="sa">f</span><span class="s2">"recovery_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> | |
| <span class="n">result</span><span class="p">[</span><span class="sa">f</span><span class="s2">"return_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> | |
| <span class="k">continue</span> | |
| <span class="c1"># Get price at horizon</span> | |
| <span class="n">idx</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">searchsorted</span><span class="p">(</span><span class="n">target_time</span><span class="p">)</span> | |
| <span class="n">idx</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">future</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> | |
| <span class="n">price_at_h</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> | |
| <span class="c1"># Recovery: fraction of the drop that has been recouped</span> | |
| <span class="n">recovery</span> <span class="o">=</span> <span class="p">(</span><span class="n">price_at_h</span> <span class="o">-</span> <span class="n">low_price</span><span class="p">)</span> <span class="o">/</span> <span class="n">crash_range</span> | |
| <span class="n">result</span><span class="p">[</span><span class="sa">f</span><span class="s2">"recovery_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">]</span> <span class="o">=</span> <span class="n">recovery</span> | |
| <span class="c1"># Simple return from crash low</span> | |
| <span class="n">result</span><span class="p">[</span><span class="sa">f</span><span class="s2">"return_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">price_at_h</span> <span class="o">-</span> <span class="n">low_price</span><span class="p">)</span> <span class="o">/</span> <span class="n">low_price</span> | |
| <span class="c1"># Max further downside: how much lower does price go after detection?</span> | |
| <span class="n">future_24h</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">crash_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span><span class="n">crash_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="mi">24</span><span class="p">)]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">future_24h</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">further_low</span> <span class="o">=</span> <span class="n">future_24h</span><span class="o">.</span><span class="n">min</span><span class="p">()</span> | |
| <span class="n">result</span><span class="p">[</span><span class="s2">"further_dd"</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">further_low</span> <span class="o">-</span> <span class="n">low_price</span><span class="p">)</span> <span class="o">/</span> <span class="n">low_price</span> | |
| <span class="k">else</span><span class="p">:</span> | |
| <span class="n">result</span><span class="p">[</span><span class="s2">"further_dd"</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span> | |
| <span class="k">return</span> <span class="n">result</span> | |
| <span class="c1"># Measure recovery for all crash events</span> | |
| <span class="n">recovery_rows</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">_</span><span class="p">,</span> <span class="n">event</span> <span class="ow">in</span> <span class="n">crashes_df</span><span class="o">.</span><span class="n">iterrows</span><span class="p">():</span> | |
| <span class="n">coin</span> <span class="o">=</span> <span class="n">event</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> | |
| <span class="n">close</span> <span class="o">=</span> <span class="n">klines</span><span class="p">[</span><span class="n">coin</span><span class="p">][</span><span class="s2">"close"</span><span class="p">]</span> | |
| <span class="n">rec</span> <span class="o">=</span> <span class="n">measure_recovery</span><span class="p">(</span> | |
| <span class="n">close</span><span class="p">,</span> <span class="n">event</span><span class="p">[</span><span class="s2">"time"</span><span class="p">],</span> <span class="n">event</span><span class="p">[</span><span class="s2">"pre_crash_price"</span><span class="p">],</span> <span class="n">event</span><span class="p">[</span><span class="s2">"low_price"</span><span class="p">]</span> | |
| <span class="p">)</span> | |
| <span class="n">rec</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> <span class="o">=</span> <span class="n">coin</span> | |
| <span class="n">rec</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> <span class="o">=</span> <span class="n">event</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> | |
| <span class="n">rec</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">=</span> <span class="n">event</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> | |
| <span class="n">recovery_rows</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">rec</span><span class="p">)</span> | |
| <span class="n">recovery_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">recovery_rows</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"Recovery statistics by horizon:"</span><span class="p">)</span> | |
| <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">24</span><span class="p">,</span> <span class="mi">48</span><span class="p">,</span> <span class="mi">72</span><span class="p">]:</span> | |
| <span class="n">col</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"recovery_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span> | |
| <span class="k">if</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">recovery_df</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span> | |
| <span class="n">data</span> <span class="o">=</span> <span class="n">recovery_df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span> | |
| <span class="n">full_recovery</span> <span class="o">=</span> <span class="p">(</span><span class="n">data</span> <span class="o">>=</span> <span class="mf">1.0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</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">h</span><span class="si">:</span><span class="s2">2d</span><span class="si">}</span><span class="s2">h: mean=</span><span class="si">{</span><span class="n">data</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">, median=</span><span class="si">{</span><span class="n">data</span><span class="o">.</span><span class="n">median</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">, "</span> | |
| <span class="sa">f</span><span class="s2">"full_recovery=</span><span class="si">{</span><span class="n">full_recovery</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%, n=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| </pre></div> | |
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| <pre>Recovery statistics by horizon: | |
| 1h: mean=0.05, median=0.06, full_recovery=0.1%, n=2245 | |
| 4h: mean=0.10, median=0.12, full_recovery=2.4%, n=2245 | |
| 12h: mean=0.15, median=0.15, full_recovery=8.0%, n=2245 | |
| 24h: mean=0.23, median=0.25, full_recovery=14.8%, n=2245 | |
| 48h: mean=0.25, median=0.19, full_recovery=20.5%, n=2245 | |
| 72h: mean=0.29, median=0.20, full_recovery=21.9%, n=2245 | |
| </pre> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [8]:</div> | |
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| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Recovery curves by crash severity</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">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span> | |
| <span class="c1"># Group crashes by severity</span> | |
| <span class="n">severity_bins</span> <span class="o">=</span> <span class="p">[</span> | |
| <span class="p">(</span><span class="s2">"Moderate (-10% to -15%)"</span><span class="p">,</span> <span class="p">(</span><span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">)),</span> | |
| <span class="p">(</span><span class="s2">"Severe (-15% to -25%)"</span><span class="p">,</span> <span class="p">(</span><span class="o">-</span><span class="mf">0.25</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">)),</span> | |
| <span class="p">(</span><span class="s2">"Extreme (< -25%)"</span><span class="p">,</span> <span class="p">(</span><span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.25</span><span class="p">)),</span> | |
| <span class="p">]</span> | |
| <span class="n">horizons</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">24</span><span class="p">,</span> <span class="mi">48</span><span class="p">,</span> <span class="mi">72</span><span class="p">]</span> | |
| <span class="n">colors</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"steelblue"</span><span class="p">,</span> <span class="s2">"darkorange"</span><span class="p">,</span> <span class="s2">"darkred"</span><span class="p">]</span> | |
| <span class="k">for</span> <span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="p">(</span><span class="n">lo</span><span class="p">,</span> <span class="n">hi</span><span class="p">)),</span> <span class="n">color</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">severity_bins</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> | |
| <span class="n">mask</span> <span class="o">=</span> <span class="p">(</span><span class="n">recovery_df</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">>=</span> <span class="n">lo</span><span class="p">)</span> <span class="o">&</span> <span class="p">(</span><span class="n">recovery_df</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o"><</span> <span class="n">hi</span><span class="p">)</span> | |
| <span class="n">subset</span> <span class="o">=</span> <span class="n">recovery_df</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">subset</span><span class="p">)</span> <span class="o"><</span> <span class="mi">3</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">recoveries</span> <span class="o">=</span> <span class="p">[</span><span class="n">subset</span><span class="p">[</span><span class="sa">f</span><span class="s2">"recovery_</span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">h"</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span> <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">horizons</span><span class="p">]</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">horizons</span><span class="p">,</span> <span class="n">recoveries</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s2">"o"</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="s2"> (n=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">subset</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axhline</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"gray"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">"Full recovery"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Hours After Crash"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Recovery (fraction of drop recouped)"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Median Recovery by Crash Severity"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span> | |
| <span class="c1"># Return distribution at 24h</span> | |
| <span class="n">returns_24h</span> <span class="o">=</span> <span class="n">recovery_df</span><span class="p">[</span><span class="s2">"return_24h"</span><span class="p">]</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">returns_24h</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"black"</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.7</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"steelblue"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"red"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Return from Crash Low (%)"</span><span class="p">)</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Count"</span><span class="p">)</span> | |
| <span class="n">mean_ret</span> <span class="o">=</span> <span class="n">returns_24h</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">median_ret</span> <span class="o">=</span> <span class="n">returns_24h</span><span class="o">.</span><span class="n">median</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="sa">f</span><span class="s2">"24h Return from Crash Low (mean=</span><span class="si">{</span><span class="n">mean_ret</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%, median=</span><span class="si">{</span><span class="n">median_ret</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%)"</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> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="jp-Cell-outputWrapper"> | |
| <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> | |
| </div> | |
| <div class="jp-OutputArea jp-Cell-outputArea"> | |
| <div class="jp-OutputArea-child"> | |
| <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> | |
| <div class="jp-RenderedImage jp-OutputArea-output" tabindex="0"> | |
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"/> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=fcb79383"> | |
| <div class="jp-Cell-inputWrapper" tabindex="0"> | |
| <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> | |
| </div> | |
| <div class="jp-InputArea jp-Cell-inputArea"> | |
| <div class="jp-InputPrompt jp-InputArea-prompt">In [9]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Further downside risk: how much further does price drop after the crash?</span> | |
| <span class="n">further_dd</span> <span class="o">=</span> <span class="n">recovery_df</span><span class="p">[</span><span class="s2">"further_dd"</span><span class="p">]</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"Further downside after crash (24h window):"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Mean: </span><span class="si">{</span><span class="n">further_dd</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Median: </span><span class="si">{</span><span class="n">further_dd</span><span class="o">.</span><span class="n">median</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Worst: </span><span class="si">{</span><span class="n">further_dd</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" No further downside: </span><span class="si">{</span><span class="p">(</span><span class="n">further_dd</span><span class="w"> </span><span class="o">>=</span><span class="w"> </span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
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| <div class="jp-Cell-outputWrapper"> | |
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| <pre>Further downside after crash (24h window): | |
| Mean: -6.31% | |
| Median: -3.86% | |
| Worst: -99.69% | |
| No further downside: 22.6% | |
| </pre> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
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| </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> | |
| <h2 id="4.-Event-Driven-Long-Strategy-Backtest">4. Event-Driven Long Strategy Backtest<a class="anchor-link" href="#4.-Event-Driven-Long-Strategy-Backtest">¶</a></h2><p>Strategy logic:</p> | |
| <ol> | |
| <li>Detect a crash event (>= threshold drop within 4h window)</li> | |
| <li>Wait for a stabilization delay (e.g., 4h, 12h, 24h after crash)</li> | |
| <li>Enter long at stabilization price</li> | |
| <li>Exit after a fixed hold period (e.g., 24h, 48h, 72h)</li> | |
| </ol> | |
| <p><strong>Train/test split:</strong> Parameters are optimized on 2020-2023 data, | |
| then validated on 2024-2025 data to avoid in-sample overfitting.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=4d19c524"> | |
| <div class="jp-Cell-inputWrapper" tabindex="0"> | |
| <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> | |
| </div> | |
| <div class="jp-InputArea jp-Cell-inputArea"> | |
| <div class="jp-InputPrompt jp-InputArea-prompt">In [10]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">backtest_crash_recovery</span><span class="p">(</span> | |
| <span class="n">crashes</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> | |
| <span class="n">klines_dict</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">],</span> | |
| <span class="n">entry_delay_hours</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span> | |
| <span class="n">hold_hours</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">24</span><span class="p">,</span> | |
| <span class="n">slippage_bps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span> | |
| <span class="p">)</span> <span class="o">-></span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span> | |
| <span class="w"> </span><span class="sd">"""Backtest a crash-recovery long strategy.</span> | |
| <span class="sd"> For each crash event:</span> | |
| <span class="sd"> - Entry: entry_delay_hours after crash, at close price</span> | |
| <span class="sd"> - Exit: hold_hours after entry, at close price</span> | |
| <span class="sd"> - Slippage: 10 bps round-trip (5 bps per leg, consistent with najena backtester)</span> | |
| <span class="sd"> Returns DataFrame of trades with PnL.</span> | |
| <span class="sd"> """</span> | |
| <span class="n">trades</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">_</span><span class="p">,</span> <span class="n">event</span> <span class="ow">in</span> <span class="n">crashes</span><span class="o">.</span><span class="n">iterrows</span><span class="p">():</span> | |
| <span class="n">coin</span> <span class="o">=</span> <span class="n">event</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> | |
| <span class="n">crash_time</span> <span class="o">=</span> <span class="n">event</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> | |
| <span class="n">close</span> <span class="o">=</span> <span class="n">klines_dict</span><span class="p">[</span><span class="n">coin</span><span class="p">][</span><span class="s2">"close"</span><span class="p">]</span> | |
| <span class="n">entry_time</span> <span class="o">=</span> <span class="n">crash_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="n">entry_delay_hours</span><span class="p">)</span> | |
| <span class="n">exit_time</span> <span class="o">=</span> <span class="n">entry_time</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timedelta</span><span class="p">(</span><span class="n">hours</span><span class="o">=</span><span class="n">hold_hours</span><span class="p">)</span> | |
| <span class="c1"># Find closest candles</span> | |
| <span class="n">future</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">entry_time</span><span class="p">:]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">future</span><span class="p">)</span> <span class="o"><</span> <span class="mi">2</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">entry_idx</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">searchsorted</span><span class="p">(</span><span class="n">entry_time</span><span class="p">)</span> | |
| <span class="n">entry_idx</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">entry_idx</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">future</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> | |
| <span class="n">entry_price</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">entry_idx</span><span class="p">]</span> | |
| <span class="n">actual_entry_time</span> <span class="o">=</span> <span class="n">future</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">entry_idx</span><span class="p">]</span> | |
| <span class="n">future_exit</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">exit_time</span><span class="p">:]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">future_exit</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">exit_idx</span> <span class="o">=</span> <span class="n">future_exit</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">searchsorted</span><span class="p">(</span><span class="n">exit_time</span><span class="p">)</span> | |
| <span class="n">exit_idx</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">exit_idx</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">future_exit</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> | |
| <span class="n">exit_price</span> <span class="o">=</span> <span class="n">future_exit</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">exit_idx</span><span class="p">]</span> | |
| <span class="n">actual_exit_time</span> <span class="o">=</span> <span class="n">future_exit</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">exit_idx</span><span class="p">]</span> | |
| <span class="k">if</span> <span class="n">entry_price</span> <span class="o"><=</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">entry_price</span><span class="p">)</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">exit_price</span><span class="p">):</span> | |
| <span class="k">continue</span> | |
| <span class="n">gross_return</span> <span class="o">=</span> <span class="p">(</span><span class="n">exit_price</span> <span class="o">/</span> <span class="n">entry_price</span><span class="p">)</span> <span class="o">-</span> <span class="mf">1.0</span> | |
| <span class="n">net_return</span> <span class="o">=</span> <span class="n">gross_return</span> <span class="o">-</span> <span class="p">(</span><span class="n">slippage_bps</span> <span class="o">/</span> <span class="mi">10_000</span><span class="p">)</span> | |
| <span class="n">trades</span><span class="o">.</span><span class="n">append</span><span class="p">({</span> | |
| <span class="s2">"coin"</span><span class="p">:</span> <span class="n">coin</span><span class="p">,</span> | |
| <span class="s2">"crash_time"</span><span class="p">:</span> <span class="n">crash_time</span><span class="p">,</span> | |
| <span class="s2">"drop_pct"</span><span class="p">:</span> <span class="n">event</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">],</span> | |
| <span class="s2">"entry_time"</span><span class="p">:</span> <span class="n">actual_entry_time</span><span class="p">,</span> | |
| <span class="s2">"exit_time"</span><span class="p">:</span> <span class="n">actual_exit_time</span><span class="p">,</span> | |
| <span class="s2">"entry_price"</span><span class="p">:</span> <span class="n">entry_price</span><span class="p">,</span> | |
| <span class="s2">"exit_price"</span><span class="p">:</span> <span class="n">exit_price</span><span class="p">,</span> | |
| <span class="s2">"gross_return"</span><span class="p">:</span> <span class="n">gross_return</span><span class="p">,</span> | |
| <span class="s2">"net_return"</span><span class="p">:</span> <span class="n">net_return</span><span class="p">,</span> | |
| <span class="p">})</span> | |
| <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">trades</span><span class="p">)</span> | |
| <span class="c1"># Split crashes into train (2020-2023) and test (2024-2025)</span> | |
| <span class="n">train_cutoff</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s2">"2024-01-01"</span><span class="p">,</span> <span class="n">tz</span><span class="o">=</span><span class="s2">"UTC"</span><span class="p">)</span> | |
| <span class="n">crashes_train</span> <span class="o">=</span> <span class="n">crashes_df</span><span class="p">[</span><span class="n">crashes_df</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> <span class="o"><</span> <span class="n">train_cutoff</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> | |
| <span class="n">crashes_test</span> <span class="o">=</span> <span class="n">crashes_df</span><span class="p">[</span><span class="n">crashes_df</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> <span class="o">>=</span> <span class="n">train_cutoff</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Train (2020-2023): </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_train</span><span class="p">)</span><span class="si">}</span><span class="s2"> crashes"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Test (2024-2025): </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_test</span><span class="p">)</span><span class="si">}</span><span class="s2"> crashes"</span><span class="p">)</span> | |
| <span class="c1"># Parameter grid — optimize on TRAIN set only</span> | |
| <span class="n">entry_delays</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">24</span><span class="p">]</span> | |
| <span class="n">hold_periods</span> <span class="o">=</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">24</span><span class="p">,</span> <span class="mi">48</span><span class="p">,</span> <span class="mi">72</span><span class="p">]</span> | |
| <span class="n">results_train</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">delay</span> <span class="ow">in</span> <span class="n">entry_delays</span><span class="p">:</span> | |
| <span class="k">for</span> <span class="n">hold</span> <span class="ow">in</span> <span class="n">hold_periods</span><span class="p">:</span> | |
| <span class="n">trades</span> <span class="o">=</span> <span class="n">backtest_crash_recovery</span><span class="p">(</span> | |
| <span class="n">crashes_train</span><span class="p">,</span> <span class="n">klines</span><span class="p">,</span> <span class="n">entry_delay_hours</span><span class="o">=</span><span class="n">delay</span><span class="p">,</span> <span class="n">hold_hours</span><span class="o">=</span><span class="n">hold</span><span class="p">,</span> | |
| <span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">trades</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">mean_ret</span> <span class="o">=</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> | |
| <span class="n">median_ret</span> <span class="o">=</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span> | |
| <span class="n">win_rate</span> <span class="o">=</span> <span class="p">(</span><span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> | |
| <span class="n">total_pnl</span> <span class="o">=</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span> | |
| <span class="n">n_trades</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">trades</span><span class="p">)</span> | |
| <span class="n">sharpe</span> <span class="o">=</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">/</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="k">if</span> <span class="n">trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span> | |
| <span class="n">results_train</span><span class="o">.</span><span class="n">append</span><span class="p">({</span> | |
| <span class="s2">"entry_delay_h"</span><span class="p">:</span> <span class="n">delay</span><span class="p">,</span> | |
| <span class="s2">"hold_h"</span><span class="p">:</span> <span class="n">hold</span><span class="p">,</span> | |
| <span class="s2">"n_trades"</span><span class="p">:</span> <span class="n">n_trades</span><span class="p">,</span> | |
| <span class="s2">"mean_ret_%"</span><span class="p">:</span> <span class="n">mean_ret</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> | |
| <span class="s2">"median_ret_%"</span><span class="p">:</span> <span class="n">median_ret</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> | |
| <span class="s2">"win_rate_%"</span><span class="p">:</span> <span class="n">win_rate</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> | |
| <span class="s2">"sharpe_per_trade"</span><span class="p">:</span> <span class="n">sharpe</span><span class="p">,</span> | |
| <span class="s2">"total_pnl_%"</span><span class="p">:</span> <span class="n">total_pnl</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> | |
| <span class="p">})</span> | |
| <span class="n">results_train_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">results_train</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Train Set (2020-2023) Parameter Grid:"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="n">results_train_df</span><span class="o">.</span><span class="n">to_string</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">float_format</span><span class="o">=</span><span class="s2">"</span><span class="si">%.2f</span><span class="s2">"</span><span class="p">))</span> | |
| <span class="c1"># Select best params by Sharpe on train set</span> | |
| <span class="n">best_row_train</span> <span class="o">=</span> <span class="n">results_train_df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">results_train_df</span><span class="p">[</span><span class="s2">"sharpe_per_trade"</span><span class="p">]</span><span class="o">.</span><span class="n">idxmax</span><span class="p">()]</span> | |
| <span class="n">best_delay</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">best_row_train</span><span class="p">[</span><span class="s2">"entry_delay_h"</span><span class="p">])</span> | |
| <span class="n">best_hold</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">best_row_train</span><span class="p">[</span><span class="s2">"hold_h"</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="se">\n</span><span class="s2">Best train params (by Sharpe): delay=</span><span class="si">{</span><span class="n">best_delay</span><span class="si">}</span><span class="s2">h, hold=</span><span class="si">{</span><span class="n">best_hold</span><span class="si">}</span><span class="s2">h"</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
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| <pre>Train (2020-2023): 1555 crashes | |
| Test (2024-2025): 690 crashes | |
| </pre> | |
| </div> | |
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| <pre> | |
| Train Set (2020-2023) Parameter Grid: | |
| entry_delay_h hold_h n_trades mean_ret_% median_ret_% win_rate_% sharpe_per_trade total_pnl_% | |
| 1 4 1555 0.55 0.67 56.78 0.09 854.22 | |
| 1 12 1555 0.72 0.62 55.05 0.07 1123.65 | |
| 1 24 1554 2.57 2.49 62.61 0.16 3991.53 | |
| 1 48 1553 2.13 0.84 53.38 0.12 3302.95 | |
| 1 72 1551 3.29 1.67 55.19 0.16 5103.59 | |
| 4 4 1555 -0.70 -0.25 47.59 -0.09 -1090.42 | |
| 4 12 1554 -0.06 -0.04 49.61 -0.01 -93.31 | |
| 4 24 1554 2.21 1.74 61.07 0.16 3435.90 | |
| 4 48 1553 1.55 0.23 50.93 0.09 2403.53 | |
| 4 72 1551 3.77 1.48 55.71 0.19 5851.69 | |
| 12 4 1554 -0.38 -0.16 48.39 -0.06 -591.48 | |
| 12 12 1554 1.30 1.16 59.40 0.14 2024.36 | |
| 12 24 1554 1.41 0.73 53.35 0.11 2187.96 | |
| 12 48 1553 2.05 0.97 53.38 0.13 3187.19 | |
| 12 72 1551 3.05 1.33 55.32 0.17 4734.61 | |
| 24 4 1554 0.42 -0.03 49.61 0.09 653.25 | |
| 24 12 1554 -0.06 -0.44 45.95 -0.01 -99.90 | |
| 24 24 1553 -0.04 -0.62 45.85 -0.00 -67.96 | |
| 24 48 1551 0.68 -0.78 46.94 0.04 1054.08 | |
| 24 72 1550 1.64 0.27 50.97 0.10 2539.79 | |
| Best train params (by Sharpe): delay=4h, hold=72h | |
| </pre> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [11]:</div> | |
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| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Validate on TEST set (2025) with params chosen on train set</span> | |
| <span class="n">strategy_trades_test</span> <span class="o">=</span> <span class="n">backtest_crash_recovery</span><span class="p">(</span> | |
| <span class="n">crashes_test</span><span class="p">,</span> <span class="n">klines</span><span class="p">,</span> <span class="n">entry_delay_hours</span><span class="o">=</span><span class="n">best_delay</span><span class="p">,</span> <span class="n">hold_hours</span><span class="o">=</span><span class="n">best_hold</span><span class="p">,</span> | |
| <span class="p">)</span> | |
| <span class="c1"># Also run on full dataset for reference</span> | |
| <span class="n">strategy_trades_full</span> <span class="o">=</span> <span class="n">backtest_crash_recovery</span><span class="p">(</span> | |
| <span class="n">crashes_df</span><span class="p">,</span> <span class="n">klines</span><span class="p">,</span> <span class="n">entry_delay_hours</span><span class="o">=</span><span class="n">best_delay</span><span class="p">,</span> <span class="n">hold_hours</span><span class="o">=</span><span class="n">best_hold</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">"Out-of-sample (2024-2025) performance (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span><span class="si">}</span><span class="s2"> trades):"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Mean return: </span><span class="si">{</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Median return: </span><span class="si">{</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Win rate: </span><span class="si">{</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="w"> </span><span class="o">></span><span class="w"> </span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span> | |
| <span class="n">std</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> | |
| <span class="k">if</span> <span class="n">std</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Sharpe/trade: </span><span class="si">{</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="n">std</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| </pre></div> | |
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| <pre>Out-of-sample (2024-2025) performance (689 trades): | |
| Mean return: 2.82% | |
| Median return: 2.20% | |
| Win rate: 57.0% | |
| Sharpe/trade: 0.182 | |
| </pre> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [12]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Heatmap of mean return by entry delay and hold period (train set)</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">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span> | |
| <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">metric</span><span class="p">,</span> <span class="n">title</span> <span class="ow">in</span> <span class="p">[</span> | |
| <span class="p">(</span><span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="s2">"mean_ret_%"</span><span class="p">,</span> <span class="s2">"Mean Return (%) — Train 2020-2023"</span><span class="p">),</span> | |
| <span class="p">(</span><span class="n">axes</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="s2">"win_rate_%"</span><span class="p">,</span> <span class="s2">"Win Rate (%) — Train 2020-2023"</span><span class="p">),</span> | |
| <span class="p">(</span><span class="n">axes</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="s2">"sharpe_per_trade"</span><span class="p">,</span> <span class="s2">"Sharpe per Trade — Train 2020-2023"</span><span class="p">),</span> | |
| <span class="p">]:</span> | |
| <span class="n">piv</span> <span class="o">=</span> <span class="n">results_train_df</span><span class="o">.</span><span class="n">pivot</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="s2">"entry_delay_h"</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="s2">"hold_h"</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">metric</span><span class="p">)</span> | |
| <span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">"RdYlGn"</span><span class="p">,</span> <span class="n">aspect</span><span class="o">=</span><span class="s2">"auto"</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">columns</span><span class="p">)))</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">index</span><span class="p">)))</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">set_yticklabels</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">index</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">"Hold Period (hours)"</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">"Entry Delay (hours)"</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">title</span><span class="p">)</span> | |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">index</span><span class="p">)):</span> | |
| <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">piv</span><span class="o">.</span><span class="n">columns</span><span class="p">)):</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">j</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">piv</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">i</span><span class="p">,</span><span class="w"> </span><span class="n">j</span><span class="p">]</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="n">ha</span><span class="o">=</span><span class="s2">"center"</span><span class="p">,</span> <span class="n">va</span><span class="o">=</span><span class="s2">"center"</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">9</span><span class="p">)</span> | |
| <span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">im</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</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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| <h2 id="5.-Comparison-Against-Baselines">5. Comparison Against Baselines<a class="anchor-link" href="#5.-Comparison-Against-Baselines">¶</a></h2><p>To establish whether crash-event conditioning genuinely adds alpha, compare against | |
| <strong>random entry on the same tokens</strong> at the same frequency. The comparison uses | |
| the test set (2025) with parameters chosen on the train set (2024).</p> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [13]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Random entry baseline on TEST set</span> | |
| <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">42</span><span class="p">)</span> | |
| <span class="n">random_trades_list</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="n">n_random_trials</span> <span class="o">=</span> <span class="mi">10</span> | |
| <span class="k">for</span> <span class="n">trial</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_random_trials</span><span class="p">):</span> | |
| <span class="n">random_crashes</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">coin</span> <span class="ow">in</span> <span class="n">crashes_test</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">():</span> | |
| <span class="n">close</span> <span class="o">=</span> <span class="n">klines</span><span class="p">[</span><span class="n">coin</span><span class="p">][</span><span class="s2">"close"</span><span class="p">]</span> | |
| <span class="n">n_events</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">crashes_test</span><span class="p">[</span><span class="n">crashes_test</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">]</span> <span class="o">==</span> <span class="n">coin</span><span class="p">])</span> | |
| <span class="c1"># Pick random times from 2024-2025 only</span> | |
| <span class="n">test_close</span> <span class="o">=</span> <span class="n">close</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">train_cutoff</span><span class="p">:]</span> | |
| <span class="n">valid_times</span> <span class="o">=</span> <span class="n">test_close</span><span class="o">.</span><span class="n">index</span><span class="p">[:</span><span class="o">-</span><span class="nb">int</span><span class="p">(</span><span class="n">best_hold</span> <span class="o">+</span> <span class="n">best_delay</span> <span class="o">+</span> <span class="mi">24</span><span class="p">)]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">valid_times</span><span class="p">)</span> <span class="o"><</span> <span class="n">n_events</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">chosen</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">valid_times</span><span class="p">),</span> <span class="n">size</span><span class="o">=</span><span class="n">n_events</span><span class="p">,</span> <span class="n">replace</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> | |
| <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">chosen</span><span class="p">:</span> | |
| <span class="n">random_crashes</span><span class="o">.</span><span class="n">append</span><span class="p">({</span> | |
| <span class="s2">"time"</span><span class="p">:</span> <span class="n">valid_times</span><span class="p">[</span><span class="n">idx</span><span class="p">],</span> | |
| <span class="s2">"coin"</span><span class="p">:</span> <span class="n">coin</span><span class="p">,</span> | |
| <span class="s2">"drop_pct"</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> | |
| <span class="s2">"pre_crash_price"</span><span class="p">:</span> <span class="n">close</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">],</span> | |
| <span class="s2">"low_price"</span><span class="p">:</span> <span class="n">close</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">],</span> | |
| <span class="p">})</span> | |
| <span class="n">random_crashes_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">random_crashes</span><span class="p">)</span> | |
| <span class="n">random_trades</span> <span class="o">=</span> <span class="n">backtest_crash_recovery</span><span class="p">(</span> | |
| <span class="n">random_crashes_df</span><span class="p">,</span> <span class="n">klines</span><span class="p">,</span> | |
| <span class="n">entry_delay_hours</span><span class="o">=</span><span class="n">best_delay</span><span class="p">,</span> | |
| <span class="n">hold_hours</span><span class="o">=</span><span class="n">best_hold</span><span class="p">,</span> | |
| <span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">random_trades</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">random_trades_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">random_trades</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">])</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Best parameters (from train): entry_delay=</span><span class="si">{</span><span class="n">best_delay</span><span class="si">}</span><span class="s2">h, hold=</span><span class="si">{</span><span class="n">best_hold</span><span class="si">}</span><span class="s2">h"</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="se">\n</span><span class="s2">Out-of-sample strategy (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span><span class="si">}</span><span class="s2"> trades):"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Mean return: </span><span class="si">{</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Median return: </span><span class="si">{</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">" Win rate: </span><span class="si">{</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s1">'net_return'</span><span class="p">]</span><span class="w"> </span><span class="o">></span><span class="w"> </span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">random_trades_list</span><span class="p">:</span> | |
| <span class="n">random_means</span> <span class="o">=</span> <span class="p">[</span><span class="n">rt</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> <span class="k">for</span> <span class="n">rt</span> <span class="ow">in</span> <span class="n">random_trades_list</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="se">\n</span><span class="s2">Random baseline (</span><span class="si">{</span><span class="n">n_random_trials</span><span class="si">}</span><span class="s2"> trials, 2024-2025 only):"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Mean return: </span><span class="si">{</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">random_means</span><span class="p">)</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">% (+/-</span><span class="si">{</span><span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">random_means</span><span class="p">)</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%)"</span><span class="p">)</span> | |
| <span class="c1"># Alpha over random</span> | |
| <span class="n">alpha</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">random_means</span><span class="p">)</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> Out-of-sample alpha over random: </span><span class="si">{</span><span class="n">alpha</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">% per trade"</span><span class="p">)</span> | |
| </pre></div> | |
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| <pre>Best parameters (from train): entry_delay=4h, hold=72h | |
| Out-of-sample strategy (689 trades): | |
| Mean return: 2.82% | |
| Median return: 2.20% | |
| Win rate: 57.0% | |
| Random baseline (10 trials, 2024-2025 only): | |
| Mean return: 0.19% (+/-0.38%) | |
| Out-of-sample alpha over random: 2.63% per trade | |
| </pre> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [14]:</div> | |
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| <div class="highlight hl-ipython3"><pre><span></span><span class="c1"># Visualize: strategy vs random return distributions (test set)</span> | |
| <span class="n">fig</span><span class="p">,</span> <span class="n">ax</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="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.6</span><span class="p">,</span> | |
| <span class="n">label</span><span class="o">=</span><span class="sa">f</span><span class="s2">"Post-crash strategy (n=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"steelblue"</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"black"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">random_trades_list</span><span class="p">:</span> | |
| <span class="n">all_random</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">random_trades_list</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">all_random</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.4</span><span class="p">,</span> | |
| <span class="n">label</span><span class="o">=</span><span class="sa">f</span><span class="s2">"Random entry (n=</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">all_random</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"gray"</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"black"</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"red"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Net Return per Trade (%)"</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">"Count"</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="s2">"Post-Crash Strategy vs Random Entry (Out-of-Sample, 2024-2025)"</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">legend</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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| <h2 id="6.-Analysis-by-Crash-Severity">6. Analysis by Crash Severity<a class="anchor-link" href="#6.-Analysis-by-Crash-Severity">¶</a></h2><p>Check whether deeper crashes produce better recovery alpha. | |
| Uses out-of-sample (2025) trades.</p> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [15]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">trade_analysis</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> | |
| <span class="n">severity_bins</span> <span class="o">=</span> <span class="p">[</span> | |
| <span class="p">(</span><span class="s2">"Moderate (-10% to -15%)"</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">),</span> | |
| <span class="p">(</span><span class="s2">"Severe (-15% to -25%)"</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.25</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">),</span> | |
| <span class="p">(</span><span class="s2">"Extreme (< -25%)"</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.25</span><span class="p">),</span> | |
| <span class="p">]</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"Performance by crash severity (out-of-sample, 2024-2025):"</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">'Severity'</span><span class="si">:</span><span class="s2"><25</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="s1">'N'</span><span class="si">:</span><span class="s2">>5</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="s1">'Mean%'</span><span class="si">:</span><span class="s2">>8</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="s1">'Median%'</span><span class="si">:</span><span class="s2">>8</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="s1">'Win%'</span><span class="si">:</span><span class="s2">>7</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="s1">'Sharpe'</span><span class="si">:</span><span class="s2">>7</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">65</span><span class="p">)</span> | |
| <span class="k">for</span> <span class="n">label</span><span class="p">,</span> <span class="n">lo</span><span class="p">,</span> <span class="n">hi</span> <span class="ow">in</span> <span class="n">severity_bins</span><span class="p">:</span> | |
| <span class="n">mask</span> <span class="o">=</span> <span class="p">(</span><span class="n">trade_analysis</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">>=</span> <span class="n">lo</span><span class="p">)</span> <span class="o">&</span> <span class="p">(</span><span class="n">trade_analysis</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o"><</span> <span class="n">hi</span><span class="p">)</span> | |
| <span class="n">subset</span> <span class="o">=</span> <span class="n">trade_analysis</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">subset</span><span class="p">)</span> <span class="o"><</span> <span class="mi">3</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">mean_r</span> <span class="o">=</span> <span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">med_r</span> <span class="o">=</span> <span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">wr</span> <span class="o">=</span> <span class="p">(</span><span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">sh</span> <span class="o">=</span> <span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">/</span> <span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="k">if</span> <span class="n">subset</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</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">label</span><span class="si">:</span><span class="s2"><25</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">subset</span><span class="p">)</span><span class="si">:</span><span class="s2">>5</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">mean_r</span><span class="si">:</span><span class="s2">>8.2f</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">med_r</span><span class="si">:</span><span class="s2">>8.2f</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">wr</span><span class="si">:</span><span class="s2">>7.1f</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">sh</span><span class="si">:</span><span class="s2">>7.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
| </div> | |
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| <div class="jp-Cell-outputWrapper"> | |
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| <div class="jp-OutputArea-child"> | |
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| <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> | |
| <pre>Performance by crash severity (out-of-sample, 2024-2025): | |
| Severity N Mean% Median% Win% Sharpe | |
| ----------------------------------------------------------------- | |
| Moderate (-10% to -15%) 594 2.49 1.56 55.2 0.168 | |
| Severe (-15% to -25%) 78 4.60 6.29 69.2 0.266 | |
| Extreme (< -25%) 17 6.11 14.16 64.7 0.232 | |
| </pre> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
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| <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> | |
| </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> | |
| <h2 id="7.-Equity-Curve-Simulation">7. Equity Curve Simulation<a class="anchor-link" href="#7.-Equity-Curve-Simulation">¶</a></h2><p>Simulate a realistic equity curve using fixed allocation per trade | |
| with the best parameters, accounting for concurrent position limits. | |
| Uses full dataset for the equity curve visualization.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=7d29b258"> | |
| <div class="jp-Cell-inputWrapper" tabindex="0"> | |
| <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> | |
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| <div class="jp-InputArea jp-Cell-inputArea"> | |
| <div class="jp-InputPrompt jp-InputArea-prompt">In [16]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">simulate_equity_curve</span><span class="p">(</span> | |
| <span class="n">trades_df</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> | |
| <span class="n">alloc_per_trade</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.05</span><span class="p">,</span> | |
| <span class="n">max_concurrent</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">5</span><span class="p">,</span> | |
| <span class="p">)</span> <span class="o">-></span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">:</span> | |
| <span class="w"> </span><span class="sd">"""Simulate equity curve from trade list, respecting position limits.</span> | |
| <span class="sd"> Tracks which trades were actually entered so that exit events for</span> | |
| <span class="sd"> skipped trades are correctly ignored.</span> | |
| <span class="sd"> """</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">trades_df</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">)</span> | |
| <span class="n">trades_sorted</span> <span class="o">=</span> <span class="n">trades_df</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s2">"entry_time"</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> | |
| <span class="c1"># Build event timeline with trade IDs to track skipped entries</span> | |
| <span class="n">events</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="k">for</span> <span class="n">trade_id</span><span class="p">,</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">trades_sorted</span><span class="o">.</span><span class="n">iterrows</span><span class="p">():</span> | |
| <span class="n">events</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="s2">"entry"</span><span class="p">,</span> <span class="n">t</span><span class="p">[</span><span class="s2">"entry_time"</span><span class="p">],</span> <span class="n">t</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">],</span> <span class="n">t</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">],</span> <span class="n">trade_id</span><span class="p">))</span> | |
| <span class="n">events</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="s2">"exit"</span><span class="p">,</span> <span class="n">t</span><span class="p">[</span><span class="s2">"exit_time"</span><span class="p">],</span> <span class="n">t</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">],</span> <span class="n">t</span><span class="p">[</span><span class="s2">"coin"</span><span class="p">],</span> <span class="n">trade_id</span><span class="p">))</span> | |
| <span class="n">events</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> | |
| <span class="n">equity</span> <span class="o">=</span> <span class="mf">1.0</span> | |
| <span class="n">equity_points</span> <span class="o">=</span> <span class="p">[]</span> | |
| <span class="n">entered_trades</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> | |
| <span class="n">skipped</span> <span class="o">=</span> <span class="mi">0</span> | |
| <span class="k">for</span> <span class="n">event_type</span><span class="p">,</span> <span class="n">time</span><span class="p">,</span> <span class="n">ret</span><span class="p">,</span> <span class="n">coin</span><span class="p">,</span> <span class="n">trade_id</span> <span class="ow">in</span> <span class="n">events</span><span class="p">:</span> | |
| <span class="k">if</span> <span class="n">event_type</span> <span class="o">==</span> <span class="s2">"entry"</span><span class="p">:</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">entered_trades</span><span class="p">)</span> <span class="o">>=</span> <span class="n">max_concurrent</span><span class="p">:</span> | |
| <span class="n">skipped</span> <span class="o">+=</span> <span class="mi">1</span> | |
| <span class="k">continue</span> | |
| <span class="n">entered_trades</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">trade_id</span><span class="p">)</span> | |
| <span class="k">elif</span> <span class="n">event_type</span> <span class="o">==</span> <span class="s2">"exit"</span><span class="p">:</span> | |
| <span class="k">if</span> <span class="n">trade_id</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">entered_trades</span><span class="p">:</span> | |
| <span class="k">continue</span> | |
| <span class="n">entered_trades</span><span class="o">.</span><span class="n">discard</span><span class="p">(</span><span class="n">trade_id</span><span class="p">)</span> | |
| <span class="n">equity</span> <span class="o">+=</span> <span class="n">alloc_per_trade</span> <span class="o">*</span> <span class="n">ret</span> | |
| <span class="n">equity_points</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s2">"time"</span><span class="p">:</span> <span class="n">time</span><span class="p">,</span> <span class="s2">"equity"</span><span class="p">:</span> <span class="n">equity</span><span class="p">})</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Skipped </span><span class="si">{</span><span class="n">skipped</span><span class="si">}</span><span class="s2"> trades due to position limit"</span><span class="p">)</span> | |
| <span class="n">eq</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">equity_points</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s2">"time"</span><span class="p">)[</span><span class="s2">"equity"</span><span class="p">]</span> | |
| <span class="k">return</span> <span class="n">eq</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_full</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">equity</span> <span class="o">=</span> <span class="n">simulate_equity_curve</span><span class="p">(</span><span class="n">strategy_trades_full</span><span class="p">,</span> <span class="n">alloc_per_trade</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">max_concurrent</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">equity</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">fig</span><span class="p">,</span> <span class="n">ax</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="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">14</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span> | |
| <span class="n">equity</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">1.5</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"steelblue"</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">"Date"</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">"Equity"</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="s2">"Crash Recovery Strategy — Equity Curve (5</span><span class="si">% a</span><span class="s2">lloc, max 5 concurrent)"</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">axhline</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"gray"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.3</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">train_cutoff</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"orange"</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s2">"--"</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">"Train/Test split"</span><span class="p">)</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span> | |
| <span class="c1"># Annotate final equity</span> | |
| <span class="n">final</span> <span class="o">=</span> <span class="n">equity</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> | |
| <span class="n">ax</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Final: </span><span class="si">{</span><span class="n">final</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="n">equity</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">final</span><span class="p">),</span> | |
| <span class="n">fontsize</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> <span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"steelblue"</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> | |
| <span class="c1"># Metrics</span> | |
| <span class="n">total_ret</span> <span class="o">=</span> <span class="p">(</span><span class="n">final</span> <span class="o">-</span> <span class="mf">1.0</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">days</span> <span class="o">=</span> <span class="p">(</span><span class="n">equity</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">equity</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">total_seconds</span><span class="p">()</span> <span class="o">/</span> <span class="mi">86400</span> | |
| <span class="n">years</span> <span class="o">=</span> <span class="n">days</span> <span class="o">/</span> <span class="mf">365.25</span> | |
| <span class="n">cagr</span> <span class="o">=</span> <span class="p">((</span><span class="n">final</span> <span class="o">**</span> <span class="p">(</span><span class="mi">1</span> <span class="o">/</span> <span class="n">years</span><span class="p">))</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span> <span class="k">if</span> <span class="n">years</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span> | |
| <span class="n">running_max</span> <span class="o">=</span> <span class="n">equity</span><span class="o">.</span><span class="n">cummax</span><span class="p">()</span> | |
| <span class="n">dd</span> <span class="o">=</span> <span class="p">(</span><span class="n">equity</span> <span class="o">-</span> <span class="n">running_max</span><span class="p">)</span> <span class="o">/</span> <span class="n">running_max</span> | |
| <span class="n">max_dd</span> <span class="o">=</span> <span class="n">dd</span><span class="o">.</span><span class="n">min</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="c1"># Annualized Sharpe from daily returns</span> | |
| <span class="c1"># Forward-fill to include flat days (no trades) before resampling,</span> | |
| <span class="c1"># so multi-day gaps produce 0% returns instead of being compressed.</span> | |
| <span class="n">eq_dedup</span> <span class="o">=</span> <span class="n">equity</span><span class="p">[</span><span class="o">~</span><span class="n">equity</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">duplicated</span><span class="p">(</span><span class="n">keep</span><span class="o">=</span><span class="s2">"last"</span><span class="p">)]</span> | |
| <span class="n">full_range</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">eq_dedup</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="n">eq_dedup</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">max</span><span class="p">(),</span> <span class="n">freq</span><span class="o">=</span><span class="s2">"1h"</span><span class="p">)</span> | |
| <span class="n">daily_eq</span> <span class="o">=</span> <span class="n">eq_dedup</span><span class="o">.</span><span class="n">reindex</span><span class="p">(</span><span class="n">full_range</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"ffill"</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">"1D"</span><span class="p">)</span><span class="o">.</span><span class="n">last</span><span class="p">()</span> | |
| <span class="n">daily_returns</span> <span class="o">=</span> <span class="n">daily_eq</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span> | |
| <span class="n">ann_sharpe</span> <span class="o">=</span> <span class="p">(</span><span class="n">daily_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">/</span> <span class="n">daily_returns</span><span class="o">.</span><span class="n">std</span><span class="p">())</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">365</span><span class="p">)</span> <span class="k">if</span> <span class="n">daily_returns</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Equity curve metrics:"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Total return: </span><span class="si">{</span><span class="n">total_ret</span><span class="si">:</span><span class="s2">.2f</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">" CAGR: </span><span class="si">{</span><span class="n">cagr</span><span class="si">:</span><span class="s2">.2f</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">" Sharpe (ann): </span><span class="si">{</span><span class="n">ann_sharpe</span><span class="si">:</span><span class="s2">.2f</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">" Max drawdown: </span><span class="si">{</span><span class="n">max_dd</span><span class="si">:</span><span class="s2">.2f</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">" Period: </span><span class="si">{</span><span class="n">days</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2"> days"</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
| </div> | |
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| <pre>Skipped 1366 trades due to position limit | |
| </pre> | |
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| <pre> | |
| Equity curve metrics: | |
| Total return: 82.13% | |
| CAGR: 10.91% | |
| Sharpe (ann): 1.05 | |
| Max drawdown: -13.36% | |
| Period: 2114 days | |
| </pre> | |
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| <h2 id="8.-Risk-Analysis">8. Risk Analysis<a class="anchor-link" href="#8.-Risk-Analysis">¶</a></h2><p>Examine worst-case scenarios and tail risk (out-of-sample trades).</p> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [17]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"Worst 10 trades (out-of-sample):"</span><span class="p">)</span> | |
| <span class="n">worst</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="o">.</span><span class="n">nsmallest</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="s2">"net_return"</span><span class="p">)[[</span><span class="s2">"coin"</span><span class="p">,</span> <span class="s2">"crash_time"</span><span class="p">,</span> <span class="s2">"drop_pct"</span><span class="p">,</span> <span class="s2">"net_return"</span><span class="p">]]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> | |
| <span class="n">worst</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">=</span> <span class="n">worst</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">worst</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">=</span> <span class="n">worst</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="n">worst</span><span class="o">.</span><span class="n">to_string</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">float_format</span><span class="o">=</span><span class="s2">"</span><span class="si">%.2f</span><span class="s2">"</span><span class="p">))</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n\n</span><span class="s2">Best 10 trades (out-of-sample):"</span><span class="p">)</span> | |
| <span class="n">best</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="s2">"net_return"</span><span class="p">)[[</span><span class="s2">"coin"</span><span class="p">,</span> <span class="s2">"crash_time"</span><span class="p">,</span> <span class="s2">"drop_pct"</span><span class="p">,</span> <span class="s2">"net_return"</span><span class="p">]]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> | |
| <span class="n">best</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">=</span> <span class="n">best</span><span class="p">[</span><span class="s2">"drop_pct"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">best</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">=</span> <span class="n">best</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="n">best</span><span class="o">.</span><span class="n">to_string</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">float_format</span><span class="o">=</span><span class="s2">"</span><span class="si">%.2f</span><span class="s2">"</span><span class="p">))</span> | |
| <span class="c1"># Consecutive losses</span> | |
| <span class="n">returns</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s2">"entry_time"</span><span class="p">)[</span><span class="s2">"net_return"</span><span class="p">]</span> | |
| <span class="n">is_loss</span> <span class="o">=</span> <span class="n">returns</span> <span class="o"><</span> <span class="mi">0</span> | |
| <span class="n">streaks</span> <span class="o">=</span> <span class="n">is_loss</span><span class="o">.</span><span class="n">ne</span><span class="p">(</span><span class="n">is_loss</span><span class="o">.</span><span class="n">shift</span><span class="p">())</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span> | |
| <span class="n">loss_streaks</span> <span class="o">=</span> <span class="n">is_loss</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">streaks</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span> | |
| <span class="n">max_loss_streak</span> <span class="o">=</span> <span class="n">loss_streaks</span><span class="o">.</span><span class="n">max</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="se">\n</span><span class="s2">Max consecutive losses: </span><span class="si">{</span><span class="n">max_loss_streak</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| <span class="c1"># VaR and CVaR</span> | |
| <span class="n">sorted_returns</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">returns</span><span class="o">.</span><span class="n">values</span><span class="p">)</span> | |
| <span class="n">var_5</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">sorted_returns</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span> | |
| <span class="n">cvar_5</span> <span class="o">=</span> <span class="n">sorted_returns</span><span class="p">[</span><span class="n">sorted_returns</span> <span class="o"><=</span> <span class="n">var_5</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">"VaR (5%): </span><span class="si">{</span><span class="n">var_5</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</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">"CVaR (5%): </span><span class="si">{</span><span class="n">cvar_5</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span> | |
| </pre></div> | |
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| <pre>Worst 10 trades (out-of-sample): | |
| coin crash_time drop_pct net_return | |
| POWR 2024-01-07 02:00:00+00:00 -10.47 -63.72 | |
| AUCTION 2025-03-21 23:00:00+00:00 -21.77 -62.25 | |
| ZEREBRO 2025-04-24 17:00:00+00:00 -14.70 -45.09 | |
| ACT 2025-04-01 10:00:00+00:00 -51.09 -42.32 | |
| OM 2025-04-13 18:00:00+00:00 -78.03 -34.80 | |
| FARTCOIN 2025-02-04 20:00:00+00:00 -11.69 -34.69 | |
| AUCTION 2025-03-22 23:00:00+00:00 -31.62 -31.77 | |
| PNUT 2025-01-18 03:00:00+00:00 -14.80 -31.36 | |
| TRB 2024-01-01 16:00:00+00:00 -14.14 -31.03 | |
| MOODENG 2025-05-14 08:00:00+00:00 -20.93 -30.85 | |
| Best 10 trades (out-of-sample): | |
| coin crash_time drop_pct net_return | |
| MOODENG 2024-11-12 11:00:00+00:00 -11.34 90.91 | |
| MOODENG 2024-11-13 16:00:00+00:00 -10.87 79.49 | |
| MOODENG 2025-05-10 00:00:00+00:00 -15.80 74.79 | |
| AERGO 2025-04-16 12:00:00+00:00 -30.12 65.95 | |
| NOT 2024-07-05 00:00:00+00:00 -10.89 59.15 | |
| 1000PEPE 2024-11-12 10:00:00+00:00 -11.52 57.60 | |
| TAO 2025-10-10 21:00:00+00:00 -19.09 55.97 | |
| FARTCOIN 2025-12-01 00:00:00+00:00 -10.59 48.19 | |
| FARTCOIN 2025-11-22 15:00:00+00:00 -10.10 46.93 | |
| FARTCOIN 2025-02-07 16:00:00+00:00 -14.23 46.51 | |
| Max consecutive losses: 16 | |
| VaR (5%): -19.21% | |
| CVaR (5%): -28.64% | |
| </pre> | |
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| <h2 id="9.-Summary-&-Recommendation">9. Summary & Recommendation<a class="anchor-link" href="#9.-Summary-&-Recommendation">¶</a></h2> | |
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| </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=8f02ecc6"> | |
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| <div class="jp-InputPrompt jp-InputArea-prompt">In [18]:</div> | |
| <div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> | |
| <div class="cm-editor cm-s-jupyter"> | |
| <div class="highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"="</span> <span class="o">*</span> <span class="mi">70</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"CRASH RECOVERY ANALYSIS — SUMMARY"</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">70</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="se">\n</span><span class="s2">Crash events detected: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_train</span><span class="p">)</span><span class="si">}</span><span class="s2"> train, </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">crashes_test</span><span class="p">)</span><span class="si">}</span><span class="s2"> test)"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Coins with crashes: </span><span class="si">{</span><span class="n">crashes_df</span><span class="p">[</span><span class="s1">'coin'</span><span class="p">]</span><span class="o">.</span><span class="n">nunique</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">results_train_df</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</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="se">\n</span><span class="s2">Best configuration (by Sharpe, train 2020-2023):"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Entry delay: </span><span class="si">{</span><span class="n">best_delay</span><span class="si">}</span><span class="s2">h"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Hold period: </span><span class="si">{</span><span class="n">best_hold</span><span class="si">}</span><span class="s2">h"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Train mean return: </span><span class="si">{</span><span class="n">best_row_train</span><span class="p">[</span><span class="s1">'mean_ret_%'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</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">" Train win rate: </span><span class="si">{</span><span class="n">best_row_train</span><span class="p">[</span><span class="s1">'win_rate_%'</span><span class="p">]</span><span class="si">:</span><span class="s2">.1f</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">" Train Sharpe/trade: </span><span class="si">{</span><span class="n">best_row_train</span><span class="p">[</span><span class="s1">'sharpe_per_trade'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> | |
| <span class="n">oos_mean</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">oos_median</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">oos_wr</span> <span class="o">=</span> <span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> | |
| <span class="n">oos_std</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> | |
| <span class="n">oos_sharpe</span> <span class="o">=</span> <span class="n">strategy_trades_test</span><span class="p">[</span><span class="s2">"net_return"</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">/</span> <span class="n">oos_std</span> <span class="k">if</span> <span class="n">oos_std</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> Out-of-sample (2024-2025):"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" Mean return: </span><span class="si">{</span><span class="n">oos_mean</span><span class="si">:</span><span class="s2">.2f</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">" Median return: </span><span class="si">{</span><span class="n">oos_median</span><span class="si">:</span><span class="s2">.2f</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">" Win rate: </span><span class="si">{</span><span class="n">oos_wr</span><span class="si">:</span><span class="s2">.1f</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">" Sharpe/trade: </span><span class="si">{</span><span class="n">oos_sharpe</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" N trades: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">strategy_trades_test</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">random_trades_list</span><span class="p">:</span> | |
| <span class="n">random_mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="n">rt</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="mi">100</span> <span class="k">for</span> <span class="n">rt</span> <span class="ow">in</span> <span class="n">random_trades_list</span><span class="p">])</span> | |
| <span class="n">alpha</span> <span class="o">=</span> <span class="n">oos_mean</span> <span class="o">-</span> <span class="n">random_mean</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> Out-of-sample alpha over random: </span><span class="si">{</span><span class="n">alpha</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">% per trade"</span><span class="p">)</span> | |
| <span class="k">if</span> <span class="n">alpha</span> <span class="o">></span> <span class="mf">0.5</span> <span class="ow">and</span> <span class="n">oos_wr</span> <span class="o">></span> <span class="mi">55</span> <span class="ow">and</span> <span class="n">oos_sharpe</span> <span class="o">></span> <span class="mf">0.1</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> RECOMMENDATION: GO — Out-of-sample alpha confirms train-set signal."</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" Consider implementing as a signal layer in najena or standalone strategy."</span><span class="p">)</span> | |
| <span class="k">elif</span> <span class="n">alpha</span> <span class="o">></span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">oos_wr</span> <span class="o">></span> <span class="mi">50</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> RECOMMENDATION: MAYBE — Marginal out-of-sample alpha detected."</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" Consider further research: tighter crash detection, severity filtering,"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" or combining with other signals (funding rate, OI change)."</span><span class="p">)</span> | |
| <span class="k">else</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> RECOMMENDATION: NO-GO — Insufficient out-of-sample alpha."</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" Post-crash recovery does not appear to be a reliable alpha source"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" on its own. The crime analysis finding (mean-reversion fails on"</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">" manipulable tokens) may extend to event-driven approaches too."</span><span class="p">)</span> | |
| <span class="k">else</span><span class="p">:</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2"> RECOMMENDATION: INCONCLUSIVE — Insufficient data for comparison."</span><span class="p">)</span> | |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span> <span class="o">+</span> <span class="s2">"="</span> <span class="o">*</span> <span class="mi">70</span><span class="p">)</span> | |
| </pre></div> | |
| </div> | |
| </div> | |
| </div> | |
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| <pre>====================================================================== | |
| CRASH RECOVERY ANALYSIS — SUMMARY | |
| ====================================================================== | |
| Crash events detected: 2245 (1555 train, 690 test) | |
| Coins with crashes: 150 | |
| Best configuration (by Sharpe, train 2020-2023): | |
| Entry delay: 4h | |
| Hold period: 72h | |
| Train mean return: 3.77% | |
| Train win rate: 55.7% | |
| Train Sharpe/trade: 0.190 | |
| Out-of-sample (2024-2025): | |
| Mean return: 2.82% | |
| Median return: 2.20% | |
| Win rate: 57.0% | |
| Sharpe/trade: 0.182 | |
| N trades: 689 | |
| Out-of-sample alpha over random: 2.63% per trade | |
| RECOMMENDATION: GO — Out-of-sample alpha confirms train-set signal. | |
| Consider implementing as a signal layer in najena or standalone strategy. | |
| ====================================================================== | |
| </pre> | |
| </div> | |
| </div> | |
| </div> | |
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