{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 13. Model building with prior predictive checks\n", "\n", "[Data set download](https://s3.amazonaws.com/bebi103.caltech.edu/data/good_invitro_droplet_data.csv)\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "nbsphinx": "hidden", "tags": [] }, "outputs": [], "source": [ "# Colab setup ------------------\n", "import os, sys, subprocess\n", "if \"google.colab\" in sys.modules:\n", " cmd = \"pip install --upgrade iqplot colorcet bebi103 arviz cmdstanpy watermark\"\n", " process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n", " stdout, stderr = process.communicate()\n", " import cmdstanpy; cmdstanpy.install_cmdstan()\n", " data_path = \"https://s3.amazonaws.com/bebi103.caltech.edu/data/\"\n", "else:\n", " data_path = \"../data/\"\n", "# ------------------------------" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/bois/opt/anaconda3/lib/python3.9/site-packages/colorcet/__init__.py:74: UserWarning: Trying to register the cmap 'cet_gray' which already exists.\n", " register_cmap(\"cet_\"+name, cmap=cm[name])\n", "/Users/bois/opt/anaconda3/lib/python3.9/site-packages/colorcet/__init__.py:74: UserWarning: Trying to register the cmap 'cet_gray_r' which already exists.\n", " register_cmap(\"cet_\"+name, cmap=cm[name])\n" ] }, { "data": { "application/javascript": [ "\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", " root._bokeh_onload_callbacks = [];\n", " root._bokeh_is_loading = undefined;\n", " }\n", "\n", " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", "\n", " function run_callbacks() {\n", " try {\n", " root._bokeh_onload_callbacks.forEach(function(callback) {\n", " if (callback != null)\n", " callback();\n", " });\n", " } finally {\n", " delete root._bokeh_onload_callbacks\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(css_urls, js_urls, js_modules, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", " if (js_modules == null) js_modules = [];\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", " if (root._bokeh_is_loading > 0) {\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", " if (js_urls.length === 0 && js_modules.length === 0) {\n", " run_callbacks();\n", " return null;\n", " }\n", " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", " run_callbacks()\n", " }\n", " }\n", "\n", " function on_error() {\n", " console.error(\"failed to load \" + url);\n", " }\n", "\n", " for (var i = 0; i < css_urls.length; i++) {\n", " var url = css_urls[i];\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.rel = \"stylesheet\";\n", " element.type = \"text/css\";\n", " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", " }\n", "\n", " var skip = [];\n", " if (window.requirejs) {\n", " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", " \n", " }\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", " if (skip.indexOf(url) >= 0) { on_load(); continue; }\n", " var element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.async = false;\n", " element.src = url;\n", " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", " for (var i = 0; i < js_modules.length; i++) {\n", " var url = js_modules[i];\n", " if (skip.indexOf(url) >= 0) { on_load(); continue; }\n", " var element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.async = false;\n", " element.src = url;\n", " element.type = \"module\";\n", " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", " if (!js_urls.length && !js_modules.length) {\n", " on_load()\n", " }\n", " };\n", "\n", " function inject_raw_css(css) {\n", " const element = document.createElement(\"style\");\n", " element.appendChild(document.createTextNode(css));\n", " document.body.appendChild(element);\n", " }\n", "\n", " var js_urls = [];\n", " var js_modules = [];\n", " var css_urls = [];\n", " var inline_js = [\n", " function(Bokeh) {\n", " inject_raw_css(\".bk.alert {\\n padding: 0.75rem 1.25rem;\\n border: 1px solid transparent;\\n border-radius: 0.25rem;\\n /* Don't set margin because that will not render correctly! */\\n /* margin-bottom: 1rem; */\\n margin-top: 15px;\\n margin-bottom: 15px;\\n}\\n.bk.alert a {\\n color: rgb(11, 46, 19); /* #002752; */\\n font-weight: 700;\\n text-decoration: rgb(11, 46, 19);\\n text-decoration-color: rgb(11, 46, 19);\\n text-decoration-line: none;\\n text-decoration-style: solid;\\n text-decoration-thickness: auto;\\n }\\n.bk.alert a:hover {\\n color: rgb(11, 46, 19);\\n font-weight: 700;\\n text-decoration: underline;\\n}\\n\\n.bk.alert-primary {\\n color: #004085;\\n background-color: #cce5ff;\\n border-color: #b8daff;\\n}\\n.bk.alert-primary hr {\\n border-top-color: #9fcdff;\\n}\\n\\n.bk.alert-secondary {\\n color: #383d41;\\n background-color: #e2e3e5;\\n border-color: #d6d8db;\\n }\\n.bk.alert-secondary hr {\\n border-top-color: #c8cbcf;\\n}\\n\\n.bk.alert-success {\\n color: #155724;\\n background-color: #d4edda;\\n border-color: #c3e6cb;\\n }\\n\\n.bk.alert-success hr {\\n border-top-color: #b1dfbb;\\n}\\n\\n.bk.alert-info {\\n color: #0c5460;\\n background-color: #d1ecf1;\\n border-color: #bee5eb;\\n }\\n.bk.alert-info hr {\\n border-top-color: #abdde5;\\n}\\n\\n.bk.alert-warning {\\n color: #856404;\\n background-color: #fff3cd;\\n border-color: #ffeeba;\\n }\\n\\n.bk.alert-warning hr {\\n border-top-color: #ffe8a1;\\n}\\n\\n.bk.alert-danger {\\n color: #721c24;\\n background-color: #f8d7da;\\n border-color: #f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.card-button {\\n background-color: transparent;\\n margin-left: 0.5em;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n font-size: 1.4em;\\n font-weight: bold;\\n overflow-wrap: break-word;\\n}\\n.bk.card-header-row > .bk {\\n padding-right: 1.5em !important;\\n overflow-wrap: break-word;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".bk.panel-widget-box {\\n min-height: 20px;\\n background-color: #f5f5f5;\\n border: 1px solid #e3e3e3;\\n border-radius: 4px;\\n -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n overflow-x: hidden;\\n overflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n appearance: none;\\n -moz-appearance: none;\\n -webkit-appearance: none;\\n border: none;\\n height: 20px;\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n color: royalblue;\\n position: relative;\\n margin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n position: relative;\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n border-radius:3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n content:\\\" \\\";\\n position:absolute;\\n height: 20px;\\n top:0;\\n left:0;\\n right:0;\\n bottom:0;\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk-root .bk.loader {\\n overflow: hidden;\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled.primary div {\\n background-color: #007bff;\\n}\\n\\n.dot-filled.secondary div {\\n background-color: #6c757d;\\n}\\n\\n.dot-filled.success div {\\n background-color: #28a745;\\n}\\n\\n.dot-filled.danger div {\\n background-color: #dc3545;\\n}\\n\\n.dot-filled.warning div {\\n background-color: #ffc107;\\n}\\n\\n.dot-filled.info div {\\n background-color: #17a2b8;\\n}\\n\\n.dot-filled.dark div {\\n background-color: #343a40;\\n}\\n\\n.dot-filled.light div {\\n background-color: #f8f9fa;\\n}\\n\\n/* Slider editor */\\n.slider-edit .bk-input-group .bk-input {\\n border: 0;\\n border-radius: 0;\\n min-height: 0;\\n padding-left: 0;\\n padding-right: 0;\\n font-weight: bold;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper {\\n display: contents;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-up {\\n top: -6px;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-down {\\n bottom: 3px;\\n}\\n\\n/* JSON Pane */\\n.bk-root .json-formatter-row .json-formatter-string, .bk-root .json-formatter-row .json-formatter-stringifiable {\\n white-space: pre-wrap;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } 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*/\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".bk.pn-loading:before {\\n position: absolute;\\n height: 100%;\\n width: 100%;\\n content: '';\\n z-index: 1000;\\n background-color: rgb(255,255,255,0.50);\\n border-color: lightgray;\\n background-repeat: no-repeat;\\n background-position: center;\\n background-size: auto 50%;\\n border-width: 1px;\\n cursor: progress;\\n}\\n.bk.pn-loading.arcs:hover:before {\\n cursor: progress;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, .panel-df th, .panel-df td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\"\\n .bk.pn-loading.arcs:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\")\\n }\\n \");\n", " },\n", " function(Bokeh) {\n", " /* BEGIN bokeh.min.js */\n", " /*!\n", " * Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors\n", " * All rights reserved.\n", " * \n", " * Redistribution and use in source and binary forms, with or without modification,\n", " * are permitted provided that the following conditions are met:\n", " * \n", " * Redistributions of source code must retain the above copyright notice,\n", " * this list of conditions and the following disclaimer.\n", " * \n", " * Redistributions in binary form must reproduce the above copyright notice,\n", " * this list of conditions and the following disclaimer in the documentation\n", " * and/or other materials provided with the distribution.\n", " * \n", " * Neither the name of Anaconda nor the names of any contributors\n", " * may be used to endorse or promote products derived from this software\n", " * without specific prior written permission.\n", " * \n", " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", " * THE POSSIBILITY OF SUCH DAMAGE.\n", " */\n", " (function(root, factory) {\n", " const bokeh = factory();\n", " bokeh.__bokeh__ = true;\n", " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", " root.Bokeh = bokeh;\n", " }\n", " const Bokeh = root.Bokeh;\n", " Bokeh[bokeh.version] = bokeh;\n", " })(this, function() {\n", " var define;\n", " var parent_require = typeof require === \"function\" && require\n", " return (function(modules, entry, aliases, externals) {\n", " if (aliases === undefined) aliases = {};\n", " if (externals === undefined) externals = {};\n", "\n", " var cache = {};\n", "\n", " var normalize = function(name) {\n", " if (typeof name === \"number\")\n", " return name;\n", "\n", " if (name === \"bokehjs\")\n", " return entry;\n", "\n", " if (!externals[name]) {\n", " var prefix = \"@bokehjs/\"\n", " if (name.slice(0, prefix.length) === prefix)\n", " name = name.slice(prefix.length)\n", " }\n", "\n", " var alias = aliases[name]\n", " if (alias != null)\n", " return alias;\n", "\n", " var trailing = name.length > 0 && name[name.lenght-1] === \"/\";\n", " var index = aliases[name + (trailing ? \"\" : \"/\") + \"index\"];\n", " if (index != null)\n", " return index;\n", "\n", " return name;\n", " }\n", "\n", " var require = function(name) {\n", " var mod = cache[name];\n", " if (!mod) {\n", " var id = normalize(name);\n", "\n", " mod = cache[id];\n", " if (!mod) {\n", " if (!modules[id]) {\n", " if (externals[id] === false || (externals[id] == true && parent_require)) {\n", " try {\n", " mod = {exports: externals[id] ? parent_require(id) : {}};\n", " cache[id] = cache[name] = mod;\n", " return mod.exports;\n", " } catch (e) {}\n", " }\n", "\n", " var err = new Error(\"Cannot find module '\" + name + \"'\");\n", " err.code = 'MODULE_NOT_FOUND';\n", " throw err;\n", " }\n", "\n", " mod = {exports: {}};\n", " cache[id] = cache[name] = mod;\n", "\n", " function __esModule() {\n", " Object.defineProperty(mod.exports, \"__esModule\", {value: true});\n", " }\n", "\n", " function __esExport(name, value) {\n", " Object.defineProperty(mod.exports, name, {\n", " enumerable: true, get: function () { return value; }\n", " });\n", " }\n", "\n", " modules[id].call(mod.exports, require, mod, mod.exports, __esModule, __esExport);\n", " } else {\n", " cache[name] = mod;\n", " }\n", " }\n", "\n", " return mod.exports;\n", " }\n", " require.resolve = function(name) {\n", " 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e={};if(null!=t)for(var r in t)\"default\"!==r&&Object.prototype.hasOwnProperty.call(t,r)&&n.__createBinding(e,t,r);return f(e,t),e},n.__importDefault=function(t){return t&&t.__esModule?t:{default:t}},n.__classPrivateFieldGet=function(t,e){if(!e.has(t))throw new TypeError(\"attempted to get private field on non-instance\");return e.get(t)},n.__classPrivateFieldSet=function(t,e,n){if(!e.has(t))throw new TypeError(\"attempted to set private field on non-instance\");return e.set(t,n),n}},\n", " function _(e,t,o,s,l){s();const n=e(1);l(\"version\",e(3).version),l(\"index\",e(4).index),o.embed=n.__importStar(e(4)),o.protocol=n.__importStar(e(404)),o._testing=n.__importStar(e(405));var r=e(19);l(\"logger\",r.logger),l(\"set_log_level\",r.set_log_level),l(\"settings\",e(28).settings),l(\"Models\",e(7).Models),l(\"documents\",e(5).documents),l(\"safely\",e(406).safely)},\n", " function _(n,i,o,c,e){c(),o.version=\"2.3.3\"},\n", " function _(e,o,t,n,s){n();const 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a}s(\"embed_items_notebook\",g.embed_items_notebook),s(\"kernels\",g.kernels),s(\"BOKEH_ROOT\",e(396).BOKEH_ROOT),t.embed_item=async function(e,o){const t={},n=_.uuid4();t[n]=e.doc,null==o&&(o=e.target_id);const s=document.getElementById(o);null!=s&&s.classList.add(m.BOKEH_ROOT);const d={roots:{[e.root_id]:o},root_ids:[e.root_id],docid:n};await a.defer();const[r]=await w(t,[d]);return r},t.embed_items=async function(e,o,t,n){return await a.defer(),w(e,o,t,n)}},\n", " function _(t,_,o,r,n){r();const a=t(1);a.__exportStar(t(6),o),a.__exportStar(t(35),o)},\n", " function _(e,t,s,o,n){o();const r=e(1),i=e(7),l=e(3),_=e(19),a=e(264),c=e(14),d=e(30),h=e(15),f=e(17),u=e(31),m=e(9),g=e(13),v=r.__importStar(e(132)),w=e(26),p=e(8),b=e(319),y=e(130),k=e(53),M=e(394),j=e(35);class S{constructor(e){this.document=e,this.session=null,this.subscribed_models=new Set}send_event(e){const t=new j.MessageSentEvent(this.document,\"bokeh_event\",e.to_json());this.document._trigger_on_change(t)}trigger(e){for(const t of this.subscribed_models)null!=e.origin&&e.origin!=t||t._process_event(e)}}s.EventManager=S,S.__name__=\"EventManager\",s.documents=[],s.DEFAULT_TITLE=\"Bokeh Application\";class E{constructor(e){var t;s.documents.push(this),this._init_timestamp=Date.now(),this._resolver=null!==(t=null==e?void 0:e.resolver)&&void 0!==t?t:new i.ModelResolver,this._title=s.DEFAULT_TITLE,this._roots=[],this._all_models=new Map,this._all_models_freeze_count=0,this._callbacks=new Map,this._message_callbacks=new Map,this.event_manager=new S(this),this.idle=new h.Signal0(this,\"idle\"),this._idle_roots=new WeakMap,this._interactive_timestamp=null,this._interactive_plot=null}get layoutables(){return this._roots.filter((e=>e instanceof b.LayoutDOM))}get is_idle(){for(const e of this.layoutables)if(!this._idle_roots.has(e))return!1;return!0}notify_idle(e){this._idle_roots.set(e,!0),this.is_idle&&(_.logger.info(`document idle at ${Date.now()-this._init_timestamp} ms`),this.event_manager.send_event(new a.DocumentReady),this.idle.emit())}clear(){this._push_all_models_freeze();try{for(;this._roots.length>0;)this.remove_root(this._roots[0])}finally{this._pop_all_models_freeze()}}interactive_start(e){null==this._interactive_plot&&(this._interactive_plot=e,this._interactive_plot.trigger_event(new a.LODStart)),this._interactive_timestamp=Date.now()}interactive_stop(){null!=this._interactive_plot&&this._interactive_plot.trigger_event(new a.LODEnd),this._interactive_plot=null,this._interactive_timestamp=null}interactive_duration(){return null==this._interactive_timestamp?-1:Date.now()-this._interactive_timestamp}destructively_move(e){if(e===this)throw new Error(\"Attempted to overwrite a document with itself\");e.clear();const t=m.copy(this._roots);this.clear();for(const e of t)if(null!=e.document)throw new Error(`Somehow we didn't detach ${e}`);if(0!=this._all_models.size)throw new Error(`this._all_models still had stuff in it: ${this._all_models}`);for(const s of t)e.add_root(s);e.set_title(this._title)}_push_all_models_freeze(){this._all_models_freeze_count+=1}_pop_all_models_freeze(){this._all_models_freeze_count-=1,0===this._all_models_freeze_count&&this._recompute_all_models()}_invalidate_all_models(){_.logger.debug(\"invalidating document models\"),0===this._all_models_freeze_count&&this._recompute_all_models()}_recompute_all_models(){let e=new Set;for(const t of this._roots)e=v.union(e,t.references());const t=new Set(this._all_models.values()),s=v.difference(t,e),o=v.difference(e,t),n=new Map;for(const t of e)n.set(t.id,t);for(const e of s)e.detach_document();for(const e of o)e.attach_document(this);this._all_models=n}roots(){return this._roots}add_root(e,t){if(_.logger.debug(`Adding root: ${e}`),!m.includes(this._roots,e)){this._push_all_models_freeze();try{this._roots.push(e)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new j.RootAddedEvent(this,e,t))}}remove_root(e,t){const s=this._roots.indexOf(e);if(!(s<0)){this._push_all_models_freeze();try{this._roots.splice(s,1)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new j.RootRemovedEvent(this,e,t))}}title(){return this._title}set_title(e,t){e!==this._title&&(this._title=e,this._trigger_on_change(new j.TitleChangedEvent(this,e,t)))}get_model_by_id(e){var t;return null!==(t=this._all_models.get(e))&&void 0!==t?t:null}get_model_by_name(e){const t=[];for(const s of this._all_models.values())s instanceof k.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof j.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new j.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _instantiate_object(e,t,s,o){const n=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(o.get(t))(n)}static _instantiate_references_json(e,t,s){var o;const n=new Map;for(const r of e){const e=r.id,i=r.type,l=null!==(o=r.attributes)&&void 0!==o?o:{};let _=t.get(e);null==_&&(_=E._instantiate_object(e,i,l,s),null!=r.subtype&&_.set_subtype(r.subtype)),n.set(_.id,_)}return n}static _resolve_refs(e,t,s,o){function n(e){var r;if(f.is_ref(e)){const o=null!==(r=t.get(e.id))&&void 0!==r?r:s.get(e.id);if(null!=o)return o;throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}return u.is_NDArray_ref(e)?u.decode_NDArray(e,o):p.isArray(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):p.isPlainObject(e)?function(e){const t={};for(const[s,o]of g.entries(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:r,attributes:i}of e){const e=!t.has(r),l=e?s.get(r):t.get(r),_=E._resolve_refs(i,t,s,o);l.setv(_,{silent:!0}),n.set(r,{instance:l,is_new:e})}const r=[],i=new Set;function l(e){if(e instanceof c.HasProps){if(n.has(e.id)&&!i.has(e.id)){i.add(e.id);const{instance:t,is_new:s}=n.get(e.id),{attributes:o}=t;for(const e of g.values(o))l(e);s&&(t.finalize(),r.push(t))}}else if(p.isArray(e))for(const t of e)l(t);else if(p.isPlainObject(e))for(const t of g.values(e))l(t)}for(const e of n.values())l(e.instance);for(const e of r)e.connect_signals()}static _event_for_attribute_change(e,t,s,o,n){if(o.get_model_by_id(e.id).property(t).syncable){const r={kind:\"ModelChanged\",model:{id:e.id},attr:t,new:s};return c.HasProps._json_record_references(o,s,n,{recursive:!0}),r}return null}static _events_to_sync_objects(e,t,s,o){const n=Object.keys(e.attributes),r=Object.keys(t.attributes),i=m.difference(n,r),l=m.difference(r,n),a=m.intersection(n,r),c=[];for(const e of i)_.logger.warn(`Server sent key ${e} but we don't seem to have it in our JSON`);for(const n of l){const r=t.attributes[n];c.push(E._event_for_attribute_change(e,n,r,s,o))}for(const n of a){const r=e.attributes[n],i=t.attributes[n];null==r&&null==i||(null==r||null==i?c.push(E._event_for_attribute_change(e,n,i,s,o)):w.is_equal(r,i)||c.push(E._event_for_attribute_change(e,n,i,s,o)))}return c.filter((e=>null!=e))}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),r=new Map,i=[];for(const t of e.roots.root_ids)r.set(t,n.get(t)),i.push(t);const l=o(s),_=new Map,a=[];for(const e of s.roots.root_ids)_.set(e,l.get(e)),a.push(e);if(i.sort(),a.sort(),m.difference(i,a).length>0||m.difference(a,i).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=E._events_to_sync_objects(n.get(e),l.get(e),t,c);h=h.concat(s)}const f=new d.Serializer({include_defaults:!1});return f.to_serializable([...c]),{references:[...f.definitions],events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=new d.Serializer({include_defaults:e}),s=t.to_serializable(this._roots);return{version:l.version,title:this._title,roots:{root_ids:s.map((e=>e.id)),references:[...t.definitions]}}}static from_json_string(e){const t=JSON.parse(e);return E.from_json(t)}static from_json(e){_.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${l.version}) / Python (${t})`;s||l.version.replace(/-(dev|rc)\\./,\"$1\")==t?_.logger.debug(o):(_.logger.warn(\"JS/Python version mismatch\"),_.logger.warn(o));const n=new i.ModelResolver;null!=e.defs&&M.resolve_defs(e.defs,n);const r=e.roots,a=r.root_ids,c=r.references,d=E._instantiate_references_json(c,new Map,n);E._initialize_references_json(c,new Map,d,new Map);const h=new E({resolver:n});for(const e of a){const t=d.get(e);null!=t&&h.add_root(t)}return h.set_title(e.title),h}replace_with_json(e){E.from_json(e).destructively_move(this)}create_json_patch_string(e){return JSON.stringify(this.create_json_patch(e))}create_json_patch(e){for(const t of e)if(t.document!=this)throw new Error(\"Cannot create a patch using events from a different document\");const t=new d.Serializer,s=t.to_serializable(e);for(const e of this._all_models.values())t.remove_def(e);return{events:s,references:[...t.definitions]}}apply_json_patch(e,t=new Map,s){const o=e.references,n=e.events,r=E._instantiate_references_json(o,this._all_models,this._resolver);t instanceof Map||(t=new Map(t));for(const e of n)switch(e.kind){case\"RootAdded\":case\"RootRemoved\":case\"ModelChanged\":{const t=e.model.id,s=this._all_models.get(t);if(null!=s)r.set(t,s);else if(!r.has(t))throw _.logger.warn(`Got an event for unknown model ${e.model}\"`),new Error(\"event model wasn't known\");break}}const i=new Map(this._all_models),l=new Map;for(const[e,t]of r)i.has(e)||l.set(e,t);E._initialize_references_json(o,i,l,t);for(const e of n)switch(e.kind){case\"MessageSent\":{const{msg_type:s,msg_data:o}=e;let n;if(void 0===o){if(1!=t.size)throw new Error(\"expected exactly one buffer\");{const[[,e]]=t;n=e}}else n=E._resolve_refs(o,i,l,t);this._trigger_on_message(s,n);break}case\"ModelChanged\":{const o=e.model.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot apply patch to ${o} which is not in the document`);const r=e.attr,_=E._resolve_refs(e.new,i,l,t);n.setv({[r]:_},{setter_id:s});break}case\"ColumnDataChanged\":{const o=e.column_source.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot stream to ${o} which is not in the document`);const r=E._resolve_refs(e.new,new Map,new Map,t);if(null!=e.cols)for(const e in n.data)e in r||(r[e]=n.data[e]);n.setv({data:r},{setter_id:s,check_eq:!1});break}case\"ColumnsStreamed\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot stream to ${t} which is not in the document`);if(!(o instanceof y.ColumnDataSource))throw new Error(\"Cannot stream to non-ColumnDataSource\");const n=e.data,r=e.rollover;o.stream(n,r,s);break}case\"ColumnsPatched\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot patch ${t} which is not in the document`);if(!(o instanceof y.ColumnDataSource))throw new Error(\"Cannot patch non-ColumnDataSource\");const n=e.patches;o.patch(n,s);break}case\"RootAdded\":{const t=e.model.id,o=r.get(t);this.add_root(o,s);break}case\"RootRemoved\":{const t=e.model.id,o=r.get(t);this.remove_root(o,s);break}case\"TitleChanged\":this.set_title(e.title,s);break;default:throw new Error(\"Unknown patch event \"+JSON.stringify(e))}}}s.Document=E,E.__name__=\"Document\"},\n", " function _(e,o,s,r,t){r();const l=e(1),d=e(8),i=e(13),n=e(14);s.overrides={};const a=new Map;s.Models=e=>{const o=s.Models.get(e);if(null!=o)return o;throw new Error(`Model '${e}' does not exist. This could be due to a widget or a custom model not being registered before first usage.`)},s.Models.get=e=>{var o;return null!==(o=s.overrides[e])&&void 0!==o?o:a.get(e)},s.Models.register=(e,o)=>{s.overrides[e]=o},s.Models.unregister=e=>{delete s.overrides[e]},s.Models.register_models=(e,o=!1,s)=>{var r;if(null!=e)for(const t of d.isArray(e)?e:i.values(e))if(r=t,d.isObject(r)&&r.prototype instanceof n.HasProps){const e=t.__qualified__;o||!a.has(e)?a.set(e,t):null!=s?s(e):console.warn(`Model '${e}' was already registered`)}},s.register_models=s.Models.register_models,s.Models.registered_names=()=>[...a.keys()];class u{constructor(){this._known_models=new Map}get(e,o){var r;const t=null!==(r=s.Models.get(e))&&void 0!==r?r:this._known_models.get(e);if(null!=t)return t;if(void 0!==o)return o;throw new Error(`Model '${e}' does not exist. This could be due to a widget or a custom model not being registered before first usage.`)}register(e){const o=e.__qualified__;null==this.get(o,null)?this._known_models.set(o,e):console.warn(`Model '${o}' was already registered with this resolver`)}}s.ModelResolver=u,u.__name__=\"ModelResolver\";const _=l.__importStar(e(38));s.register_models(_)},\n", " function _(n,r,t,e,i){e();\n", " // (c) 2009-2015 Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors\n", " // Underscore may be freely distributed under the MIT license.\n", " const o=n(9),u=Object.prototype.toString;function c(n){return!0===n||!1===n||\"[object Boolean]\"===u.call(n)}function f(n){return\"[object Number]\"===u.call(n)}function a(n){return\"[object String]\"===u.call(n)}function l(n){const r=typeof n;return\"function\"===r||\"object\"===r&&!!n}function s(n){return l(n)&&void 0!==n[Symbol.iterator]}t.isBoolean=c,t.isNumber=f,t.isInteger=function(n){return 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Math.atan2(r[1]-n[1],r[0]-n[0])},t.radians=function(n){return n*(u/180)},t.degrees=function(n){return n/(u/180)},t.resolve_angle=function(n,r){return-i(r)*n},t.to_radians_coeff=i,t.rnorm=function(n,r){let t,e;for(;t=f(),e=f(),e=(2*e-1)*Math.sqrt(1/Math.E*2),!(-4*t*t*Math.log(t)>=e*e););let o=e/t;return o=n+r*o,o},t.clamp=function(n,r,t){return nt?t:n},t.log=function(n,r=Math.E){return Math.log(n)/Math.log(r)}},\n", " function _(r,n,e,o,s){o();class t extends Error{}e.AssertionError=t,t.__name__=\"AssertionError\",e.assert=function(r,n){if(!(!0===r||!1!==r&&r()))throw new t(null!=n?n:\"Assertion failed\")},e.unreachable=function(){throw new Error(\"unreachable code\")}},\n", " function _(n,t,e,r,o){r();const i=n(10);function l(n,t,e,...r){const o=n.length;t<0&&(t+=o),t<0?t=0:t>o&&(t=o),null==e||e>o-t?e=o-t:e<0&&(e=0);const i=o-e+r.length,l=new n.constructor(i);let u=0;for(;u0?0:r-1;for(;o>=0&&ot[t.length-1])return t.length;let e=0,r=t.length-1;for(;r-e!=1;){const 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o.Signal0(this,\"exprchange\"),this.properties={},this._pending=!1,this._changing=!1;const n=t instanceof Map?t.get.bind(t):e=>t[e];this.id=null!==(e=n(\"id\"))&&void 0!==e?e:h.uniqueId();for(const[t,{type:e,default_value:s,options:r}]of u.entries(this._props)){let i;e instanceof a.PropertyAlias?Object.defineProperty(this.properties,t,{get:()=>this.properties[e.attr],configurable:!1,enumerable:!1}):(i=e instanceof _.Kind?new a.PrimitiveProperty(this,t,e,s,n(t),r):new e(this,t,_.Any,s,n(t),r),this.properties[t]=i)}null!==(s=n(\"__deferred__\"))&&void 0!==s&&s||(this.finalize(),this.connect_signals())}get is_syncable(){return!0}set type(t){console.warn(\"prototype.type = 'ModelName' is deprecated, use static __name__ instead\"),this.constructor.__name__=t}get type(){return this.constructor.__qualified__}static get __qualified__(){const{__module__:t,__name__:e}=this;return null!=t?`${t}.${e}`:e}static get[Symbol.toStringTag](){return this.__name__}static 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this.constructor(e)}[g.equals](t,e){for(const s of this){const n=t.property(s.attr);if(e.eq(s.get_value(),n.get_value()))return!1}return!0}[y.pretty](t){const e=t.token,s=[];for(const n of this)if(n.dirty){const r=n.get_value();s.push(`${n.attr}${e(\":\")} ${t.to_string(r)}`)}return`${this.constructor.__qualified__}${e(\"(\")}${e(\"{\")}${s.join(`${e(\",\")} `)}${e(\"}\")}${e(\")\")}`}[p.serialize](t){const e=this.ref();t.add_ref(this,e);const s=this.struct();for(const e of this)e.syncable&&(t.include_defaults||e.dirty)&&(s.attributes[e.attr]=t.to_serializable(e.get_value()));return t.add_def(this,s),e}finalize(){for(const t of this){if(!(t instanceof a.VectorSpec||t instanceof a.ScalarSpec))continue;const e=t.get_value();if(null!=e){const{transform:t,expr:s}=e;null!=t&&this.connect(t.change,(()=>this.transformchange.emit())),null!=s&&this.connect(s.change,(()=>this.exprchange.emit()))}}this.initialize()}initialize(){}connect_signals(){}disconnect_signals(){o.Signal.disconnectReceiver(this)}destroy(){this.disconnect_signals(),this.destroyed.emit()}clone(){return(new v.Cloner).clone(this)}_setv(t,e){const s=e.check_eq,n=[],r=this._changing;this._changing=!0;for(const[e,r]of t)!1!==s&&f.is_equal(e.get_value(),r)||(e.set_value(r),n.push(e));n.length>0&&(this._pending=!0);for(const t of n)t.change.emit();if(!r){if(!e.no_change)for(;this._pending;)this._pending=!1,this.change.emit();this._pending=!1,this._changing=!1}}setv(t,e={}){const s=u.entries(t);if(0==s.length)return;if(!0===e.silent){for(const[t,e]of s)this.properties[t].set_value(e);return}const n=new Map,r=new Map;for(const[t,e]of s){const s=this.properties[t];n.set(s,e),r.set(s,s.get_value())}this._setv(n,e);const{document:i}=this;if(null!=i){const t=[];for(const[e,s]of r)t.push([e,s,e.get_value()]);for(const[,e,s]of t)if(this._needs_invalidate(e,s)){i._invalidate_all_models();break}this._push_changes(t,e)}}getv(t){return this.property(t).get_value()}ref(){return{id:this.id}}struct(){const t={type:this.type,id:this.id,attributes:{}};return null!=this._subtype&&(t.subtype=this._subtype),t}set_subtype(t){this._subtype=t}*[Symbol.iterator](){yield*u.values(this.properties)}*syncable_properties(){for(const t of this)t.syncable&&(yield t)}serializable_attributes(){const t={};for(const e of this.syncable_properties())t[e.attr]=e.get_value();return t}static _json_record_references(t,e,s,n){const{recursive:r}=n;if(c.is_ref(e)){const n=t.get_model_by_id(e.id);null==n||s.has(n)||b._value_record_references(n,s,{recursive:r})}else if(l.isArray(e))for(const n of e)b._json_record_references(t,n,s,{recursive:r});else 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e)t.appendChild(n)},n.remove=a,n.removeElement=a,n.replaceWith=function(t,e){const n=t.parentNode;null!=n&&n.replaceChild(e,t)},n.prepend=c,n.empty=function(t,e=!1){let n;for(;n=t.firstChild;)t.removeChild(n);if(e&&t instanceof Element)for(const e of t.attributes)t.removeAttributeNode(e)},n.display=function(t){t.style.display=\"\"},n.undisplay=function(t){t.style.display=\"none\"},n.show=function(t){t.style.visibility=\"\"},n.hide=function(t){t.style.visibility=\"hidden\"},n.offset=function(t){const e=t.getBoundingClientRect();return{top:e.top+window.pageYOffset-document.documentElement.clientTop,left:e.left+window.pageXOffset-document.documentElement.clientLeft}},n.matches=d,n.parent=function(t,e){let n=t;for(;n=n.parentElement;)if(d(n,e))return n;return null},n.extents=u,n.size=f,n.scroll_size=function(t){return{width:Math.ceil(t.scrollWidth),height:Math.ceil(t.scrollHeight)}},n.outer_size=function(t){const{margin:{left:e,right:n,top:i,bottom:o}}=u(t),{width:s,height:l}=f(t);return{width:Math.ceil(s+e+n),height:Math.ceil(l+i+o)}},n.content_size=function(t){const{left:e,top:n}=t.getBoundingClientRect(),{padding:i}=u(t);let o=0,s=0;for(const l of t.children){const t=l.getBoundingClientRect();o=Math.max(o,Math.ceil(t.left-e-i.left+t.width)),s=Math.max(s,Math.ceil(t.top-n-i.top+t.height))}return{width:o,height:s}},n.position=function(t,e,n){const{style:i}=t;if(i.left=`${e.x}px`,i.top=`${e.y}px`,i.width=`${e.width}px`,i.height=`${e.height}px`,null==n)i.margin=\"\";else{const{top:t,right:e,bottom:o,left:s}=n;i.margin=`${t}px ${e}px ${o}px ${s}px`}},n.children=function(t){return Array.from(t.children)};class p{constructor(t){this.el=t,this.classList=t.classList}get values(){const t=[];for(let e=0;e{document.addEventListener(\"DOMContentLoaded\",(()=>t()),{once:!0})}))}},\n", " function _(o,i,t,e,r){e(),t.root=\"bk-root\",t.default=\".bk-root{position:relative;width:auto;height:auto;box-sizing:border-box;font-family:Helvetica, Arial, sans-serif;font-size:13px;}.bk-root .bk,.bk-root .bk:before,.bk-root .bk:after{box-sizing:inherit;margin:0;border:0;padding:0;background-image:none;font-family:inherit;font-size:100%;line-height:1.42857143;}.bk-root pre.bk{font-family:Courier, monospace;}\"},\n", " function _(e,t,r,a,c){a();const l=e(1),n=e(46);c(\"Line\",n.Line),c(\"LineScalar\",n.LineScalar),c(\"LineVector\",n.LineVector);const i=e(49);c(\"Fill\",i.Fill),c(\"FillScalar\",i.FillScalar),c(\"FillVector\",i.FillVector);const s=e(50);c(\"Text\",s.Text),c(\"TextScalar\",s.TextScalar),c(\"TextVector\",s.TextVector);const o=e(51);c(\"Hatch\",o.Hatch),c(\"HatchScalar\",o.HatchScalar),c(\"HatchVector\",o.HatchVector);const u=l.__importStar(e(48)),V=e(47);c(\"VisualProperties\",V.VisualProperties),c(\"VisualUniforms\",V.VisualUniforms);class h{constructor(e){this._visuals=[];for(const[t,r]of e.model._mixins){const a=(()=>{switch(r){case u.Line:return new n.Line(e,t);case u.LineScalar:return new n.LineScalar(e,t);case u.LineVector:return new n.LineVector(e,t);case u.Fill:return new i.Fill(e,t);case u.FillScalar:return new i.FillScalar(e,t);case u.FillVector:return new i.FillVector(e,t);case u.Text:return new s.Text(e,t);case u.TextScalar:return new s.TextScalar(e,t);case u.TextVector:return new s.TextVector(e,t);case u.Hatch:return new o.Hatch(e,t);case u.HatchScalar:return new o.HatchScalar(e,t);case u.HatchVector:return new o.HatchVector(e,t);default:throw new Error(\"unknown visual\")}})();this._visuals.push(a),Object.defineProperty(this,t+a.type,{get:()=>a,configurable:!1,enumerable:!0})}}*[Symbol.iterator](){yield*this._visuals}}r.Visuals=h,h.__name__=\"Visuals\"},\n", " function _(e,t,i,l,s){l();const n=e(1),a=e(47),o=n.__importStar(e(48)),r=e(22),_=e(8);function h(e){if(_.isArray(e))return e;switch(e){case\"solid\":return[];case\"dashed\":return[6];case\"dotted\":return[2,4];case\"dotdash\":return[2,4,6,4];case\"dashdot\":return[6,4,2,4];default:return e.split(\" \").map(Number).filter(_.isInteger)}}i.resolve_line_dash=h;class c extends a.VisualProperties{get doit(){const e=this.line_color.get_value(),t=this.line_alpha.get_value(),i=this.line_width.get_value();return!(null==e||0==t||0==i)}set_value(e){const t=this.line_color.get_value(),i=this.line_alpha.get_value();e.strokeStyle=r.color2css(t,i),e.lineWidth=this.line_width.get_value(),e.lineJoin=this.line_join.get_value(),e.lineCap=this.line_cap.get_value(),e.lineDash=h(this.line_dash.get_value()),e.lineDashOffset=this.line_dash_offset.get_value()}}i.Line=c,c.__name__=\"Line\";class u extends a.VisualUniforms{get doit(){const e=this.line_color.value,t=this.line_alpha.value,i=this.line_width.value;return!(0==e||0==t||0==i)}set_value(e){const t=this.line_color.value,i=this.line_alpha.value;e.strokeStyle=r.color2css(t,i),e.lineWidth=this.line_width.value,e.lineJoin=this.line_join.value,e.lineCap=this.line_cap.value,e.lineDash=h(this.line_dash.value),e.lineDashOffset=this.line_dash_offset.value}}i.LineScalar=u,u.__name__=\"LineScalar\";class d extends a.VisualUniforms{get doit(){const{line_color:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{line_alpha:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{line_width:i}=this;return!i.is_Scalar()||0!=i.value}set_vectorize(e,t){const i=this.line_color.get(t),l=this.line_alpha.get(t),s=this.line_width.get(t),n=this.line_join.get(t),a=this.line_cap.get(t),o=this.line_dash.get(t),_=this.line_dash_offset.get(t);e.strokeStyle=r.color2css(i,l),e.lineWidth=s,e.lineJoin=n,e.lineCap=a,e.lineDash=h(o),e.lineDashOffset=_}}i.LineVector=d,d.__name__=\"LineVector\",c.prototype.type=\"line\",c.prototype.attrs=Object.keys(o.Line),u.prototype.type=\"line\",u.prototype.attrs=Object.keys(o.LineScalar),d.prototype.type=\"line\",d.prototype.attrs=Object.keys(o.LineVector)},\n", " function _(t,s,o,i,r){i();class e{constructor(t,s=\"\"){this.obj=t,this.prefix=s;const o=this;this._props=[];for(const i of this.attrs){const r=t.model.properties[s+i];r.change.connect((()=>this.update())),o[i]=r,this._props.push(r)}this.update()}*[Symbol.iterator](){yield*this._props}update(){}}o.VisualProperties=e,e.__name__=\"VisualProperties\";class p{constructor(t,s=\"\"){this.obj=t,this.prefix=s;for(const o of this.attrs)Object.defineProperty(this,o,{get:()=>t[s+o]})}*[Symbol.iterator](){for(const t of this.attrs)yield this.obj.model.properties[this.prefix+t]}update(){}}o.VisualUniforms=p,p.__name__=\"VisualUniforms\"},\n", " function _(e,l,t,a,c){a();const r=e(1),o=r.__importStar(e(18)),n=e(20),i=r.__importStar(e(21)),_=e(13);t.Line={line_color:[i.Nullable(i.Color),\"black\"],line_alpha:[i.Alpha,1],line_width:[i.Number,1],line_join:[n.LineJoin,\"bevel\"],line_cap:[n.LineCap,\"butt\"],line_dash:[i.Or(n.LineDash,i.Array(i.Number)),[]],line_dash_offset:[i.Number,0]},t.Fill={fill_color:[i.Nullable(i.Color),\"gray\"],fill_alpha:[i.Alpha,1]},t.Hatch={hatch_color:[i.Nullable(i.Color),\"black\"],hatch_alpha:[i.Alpha,1],hatch_scale:[i.Number,12],hatch_pattern:[i.Nullable(i.Or(n.HatchPatternType,i.String)),null],hatch_weight:[i.Number,1],hatch_extra:[i.Dict(i.AnyRef()),{}]},t.Text={text_color:[i.Nullable(i.Color),\"#444444\"],text_alpha:[i.Alpha,1],text_font:[o.Font,\"helvetica\"],text_font_size:[i.FontSize,\"16px\"],text_font_style:[n.FontStyle,\"normal\"],text_align:[n.TextAlign,\"left\"],text_baseline:[n.TextBaseline,\"bottom\"],text_line_height:[i.Number,1.2]},t.LineScalar={line_color:[o.ColorScalar,\"black\"],line_alpha:[o.NumberScalar,1],line_width:[o.NumberScalar,1],line_join:[o.LineJoinScalar,\"bevel\"],line_cap:[o.LineCapScalar,\"butt\"],line_dash:[o.LineDashScalar,[]],line_dash_offset:[o.NumberScalar,0]},t.FillScalar={fill_color:[o.ColorScalar,\"gray\"],fill_alpha:[o.NumberScalar,1]},t.HatchScalar={hatch_color:[o.ColorScalar,\"black\"],hatch_alpha:[o.NumberScalar,1],hatch_scale:[o.NumberScalar,12],hatch_pattern:[o.NullStringScalar,null],hatch_weight:[o.NumberScalar,1],hatch_extra:[o.AnyScalar,{}]},t.TextScalar={text_color:[o.ColorScalar,\"#444444\"],text_alpha:[o.NumberScalar,1],text_font:[o.FontScalar,\"helvetica\"],text_font_size:[o.FontSizeScalar,\"16px\"],text_font_style:[o.FontStyleScalar,\"normal\"],text_align:[o.TextAlignScalar,\"left\"],text_baseline:[o.TextBaselineScalar,\"bottom\"],text_line_height:[o.NumberScalar,1.2]},t.LineVector={line_color:[o.ColorSpec,\"black\"],line_alpha:[o.NumberSpec,1],line_width:[o.NumberSpec,1],line_join:[o.LineJoinSpec,\"bevel\"],line_cap:[o.LineCapSpec,\"butt\"],line_dash:[o.LineDashSpec,[]],line_dash_offset:[o.NumberSpec,0]},t.FillVector={fill_color:[o.ColorSpec,\"gray\"],fill_alpha:[o.NumberSpec,1]},t.HatchVector={hatch_color:[o.ColorSpec,\"black\"],hatch_alpha:[o.NumberSpec,1],hatch_scale:[o.NumberSpec,12],hatch_pattern:[o.NullStringSpec,null],hatch_weight:[o.NumberSpec,1],hatch_extra:[o.AnyScalar,{}]},t.TextVector={text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_font:[o.FontSpec,\"helvetica\"],text_font_size:[o.FontSizeSpec,\"16px\"],text_font_style:[o.FontStyleSpec,\"normal\"],text_align:[o.TextAlignSpec,\"left\"],text_baseline:[o.TextBaselineSpec,\"bottom\"],text_line_height:[o.NumberSpec,1.2]},t.attrs_of=function(e,l,t,a=!1){const c={};for(const r of _.keys(t)){const t=`${l}${r}`,o=e[t];c[a?t:r]=o}return c}},\n", " function _(l,t,e,i,s){i();const o=l(1),a=l(47),r=o.__importStar(l(48)),c=l(22);class _ extends a.VisualProperties{get doit(){const l=this.fill_color.get_value(),t=this.fill_alpha.get_value();return!(null==l||0==t)}set_value(l){const t=this.fill_color.get_value(),e=this.fill_alpha.get_value();l.fillStyle=c.color2css(t,e)}}e.Fill=_,_.__name__=\"Fill\";class n extends a.VisualUniforms{get doit(){const l=this.fill_color.value,t=this.fill_alpha.value;return!(0==l||0==t)}set_value(l){const t=this.fill_color.value,e=this.fill_alpha.value;l.fillStyle=c.color2css(t,e)}}e.FillScalar=n,n.__name__=\"FillScalar\";class p extends a.VisualUniforms{get doit(){const{fill_color:l}=this;if(l.is_Scalar()&&0==l.value)return!1;const{fill_alpha:t}=this;return!t.is_Scalar()||0!=t.value}set_vectorize(l,t){const e=this.fill_color.get(t),i=this.fill_alpha.get(t);l.fillStyle=c.color2css(e,i)}}e.FillVector=p,p.__name__=\"FillVector\",_.prototype.type=\"fill\",_.prototype.attrs=Object.keys(r.Fill),n.prototype.type=\"fill\",n.prototype.attrs=Object.keys(r.FillScalar),p.prototype.type=\"fill\",p.prototype.attrs=Object.keys(r.FillVector)},\n", " function _(t,e,s,l,a){l();const o=t(1),_=t(47),i=o.__importStar(t(48)),n=t(22);class x extends _.VisualProperties{get doit(){const t=this.text_color.get_value(),e=this.text_alpha.get_value();return!(null==t||0==e)}set_value(t){const e=this.text_color.get_value(),s=this.text_alpha.get_value();t.fillStyle=n.color2css(e,s),t.font=this.font_value(),t.textAlign=this.text_align.get_value(),t.textBaseline=this.text_baseline.get_value()}font_value(){return`${this.text_font_style.get_value()} ${this.text_font_size.get_value()} ${this.text_font.get_value()}`}}s.Text=x,x.__name__=\"Text\";class r extends _.VisualUniforms{get doit(){const t=this.text_color.value,e=this.text_alpha.value;return!(0==t||0==e)}set_value(t){const e=this.text_color.value,s=this.text_alpha.value,l=this.font_value(),a=this.text_align.value,o=this.text_baseline.value;t.fillStyle=n.color2css(e,s),t.font=l,t.textAlign=a,t.textBaseline=o}font_value(){return`${this.text_font_style.value} ${this.text_font_size.value} ${this.text_font.value}`}}s.TextScalar=r,r.__name__=\"TextScalar\";class u extends _.VisualUniforms{get doit(){const{text_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{text_alpha:e}=this;return!e.is_Scalar()||0!=e.value}set_vectorize(t,e){const s=this.text_color.get(e),l=this.text_alpha.get(e),a=this.font_value(e),o=this.text_align.get(e),_=this.text_baseline.get(e);t.fillStyle=n.color2css(s,l),t.font=a,t.textAlign=o,t.textBaseline=_}font_value(t){return`${this.text_font_style.get(t)} ${this.text_font_size.get(t)} ${this.text_font.get(t)}`}}s.TextVector=u,u.__name__=\"TextVector\",x.prototype.type=\"text\",x.prototype.attrs=Object.keys(i.Text),r.prototype.type=\"text\",r.prototype.attrs=Object.keys(i.TextScalar),u.prototype.type=\"text\",u.prototype.attrs=Object.keys(i.TextVector)},\n", " function _(t,e,a,h,r){h();const i=t(1),s=t(47),c=t(52),n=i.__importStar(t(18)),_=i.__importStar(t(48));class l extends s.VisualProperties{constructor(){super(...arguments),this._update_iteration=0}update(){if(this._update_iteration++,this._hatch_image=null,!this.doit)return;const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_scale.get_value(),h=this.hatch_pattern.get_value(),r=this.hatch_weight.get_value(),i=t=>{this._hatch_image=t},s=this.hatch_extra.get_value()[h];if(null!=s){const h=s.get_pattern(t,e,a,r);if(h instanceof Promise){const{_update_iteration:t}=this;h.then((e=>{this._update_iteration==t&&(i(e),this.obj.request_render())}))}else i(h)}else{const s=this.obj.canvas.create_layer(),n=c.get_pattern(s,h,t,e,a,r);i(n)}}get doit(){const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_pattern.get_value();return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}set_value(t){const e=this.pattern(t);t.fillStyle=null!=e?e:\"transparent\"}pattern(t){const e=this._hatch_image;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.get_value(),e=this.hatch_extra.get_value()[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.Hatch=l,l.__name__=\"Hatch\";class o extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const t=this.hatch_color.value,e=this.hatch_alpha.value,a=this.hatch_pattern.value;return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new n.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=this.hatch_color.value,a=this.hatch_alpha.value,h=this.hatch_scale.value,r=this.hatch_pattern.value,i=this.hatch_weight.value,s=e=>{this._hatch_image=new n.UniformScalar(e,t)},_=this.hatch_extra.value[r];if(null!=_){const t=_.get_pattern(e,a,h,i);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(s(t),this.obj.request_render())}))}else s(t)}else{const t=this.obj.canvas.create_layer(),n=c.get_pattern(t,r,e,a,h,i);s(n)}}get doit(){return this._static_doit}set_value(t){var e;t.fillStyle=null!==(e=this.pattern(t))&&void 0!==e?e:\"transparent\"}pattern(t){const e=this._hatch_image.value;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.value,e=this.hatch_extra.value[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchScalar=o,o.__name__=\"HatchScalar\";class u extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const{hatch_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{hatch_alpha:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{hatch_pattern:a}=this;if(a.is_Scalar()){const t=a.value;if(\" \"==t||\"blank\"==t||null==t)return!1}return!0}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new n.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=(t,e,a,h,r,i)=>{const s=this.hatch_extra.value[t];if(null!=s){const t=s.get_pattern(e,a,h,r);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(i(t),this.obj.request_render())}))}else i(t)}else{const s=this.obj.canvas.create_layer(),n=c.get_pattern(s,t,e,a,h,r);i(n)}};if(this.hatch_color.is_Scalar()&&this.hatch_alpha.is_Scalar()&&this.hatch_scale.is_Scalar()&&this.hatch_pattern.is_Scalar()&&this.hatch_weight.is_Scalar()){const a=this.hatch_color.value,h=this.hatch_alpha.value,r=this.hatch_scale.value;e(this.hatch_pattern.value,a,h,r,this.hatch_weight.value,(e=>{this._hatch_image=new n.UniformScalar(e,t)}))}else{const a=new Array(t);a.fill(null),this._hatch_image=new n.UniformVector(a);for(let h=0;h{a[h]=t}))}}}get doit(){return this._static_doit}set_vectorize(t,e){var a;t.fillStyle=null!==(a=this.pattern(t,e))&&void 0!==a?a:\"transparent\"}pattern(t,e){const a=this._hatch_image.get(e);return null==a?null:t.createPattern(a,this.repetition(e))}repetition(t){const e=this.hatch_pattern.get(t),a=this.hatch_extra.value[e];if(null==a)return\"repeat\";switch(a.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchVector=u,u.__name__=\"HatchVector\",l.prototype.type=\"hatch\",l.prototype.attrs=Object.keys(_.Hatch),o.prototype.type=\"hatch\",o.prototype.attrs=Object.keys(_.HatchScalar),u.prototype.type=\"hatch\",u.prototype.attrs=Object.keys(_.HatchVector)},\n", " function _(e,o,a,s,r){s();const i=e(22);function l(e,o,a){e.moveTo(0,a+.5),e.lineTo(o,a+.5),e.stroke()}function n(e,o,a){e.moveTo(a+.5,0),e.lineTo(a+.5,o),e.stroke()}function t(e,o){e.moveTo(0,o),e.lineTo(o,0),e.stroke(),e.moveTo(0,0),e.lineTo(o,o),e.stroke()}a.hatch_aliases={\" \":\"blank\",\".\":\"dot\",o:\"ring\",\"-\":\"horizontal_line\",\"|\":\"vertical_line\",\"+\":\"cross\",'\"':\"horizontal_dash\",\":\":\"vertical_dash\",\"@\":\"spiral\",\"/\":\"right_diagonal_line\",\"\\\\\":\"left_diagonal_line\",x:\"diagonal_cross\",\",\":\"right_diagonal_dash\",\"`\":\"left_diagonal_dash\",v:\"horizontal_wave\",\">\":\"vertical_wave\",\"*\":\"criss_cross\"},a.get_pattern=function(e,o,s,r,c,k){return e.resize(c,c),e.prepare(),function(e,o,s,r,c,k){var _;const T=c,v=T/2,h=v/2,d=i.color2css(s,r);switch(e.strokeStyle=d,e.fillStyle=d,e.lineCap=\"square\",e.lineWidth=k,null!==(_=a.hatch_aliases[o])&&void 0!==_?_:o){case\"blank\":break;case\"dot\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.fill();break;case\"ring\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.stroke();break;case\"horizontal_line\":l(e,T,v);break;case\"vertical_line\":n(e,T,v);break;case\"cross\":l(e,T,v),n(e,T,v);break;case\"horizontal_dash\":l(e,v,v);break;case\"vertical_dash\":n(e,v,v);break;case\"spiral\":{const o=T/30;e.moveTo(v,v);for(let a=0;a<360;a++){const s=.1*a,r=v+o*s*Math.cos(s),i=v+o*s*Math.sin(s);e.lineTo(r,i)}e.stroke();break}case\"right_diagonal_line\":e.moveTo(.5-h,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(5*h+.5,0),e.stroke(),e.stroke();break;case\"left_diagonal_line\":e.moveTo(h+.5,T),e.lineTo(.5-h,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(5*h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.stroke();break;case\"diagonal_cross\":t(e,T);break;case\"right_diagonal_dash\":e.moveTo(h+.5,3*h+.5),e.lineTo(3*h+.5,h+.5),e.stroke();break;case\"left_diagonal_dash\":e.moveTo(h+.5,h+.5),e.lineTo(3*h+.5,3*h+.5),e.stroke();break;case\"horizontal_wave\":e.moveTo(0,h),e.lineTo(v,3*h),e.lineTo(T,h),e.stroke();break;case\"vertical_wave\":e.moveTo(h,0),e.lineTo(3*h,v),e.lineTo(h,T),e.stroke();break;case\"criss_cross\":t(e,T),l(e,T,v),n(e,T,v)}}(e.ctx,o,s,r,c,k),e.canvas}},\n", " function _(e,t,s,n,c){n();const a=e(14),i=e(8),r=e(13),l=e(19);class o extends a.HasProps{constructor(e){super(e)}get is_syncable(){return this.syncable}static init_Model(){this.define((({Any:e,Unknown:t,Boolean:s,String:n,Array:c,Dict:a,Nullable:i})=>({tags:[c(t),[]],name:[i(n),null],js_property_callbacks:[a(c(e)),{}],js_event_callbacks:[a(c(e)),{}],subscribed_events:[c(n),[]],syncable:[s,!0]})))}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,(()=>this._update_property_callbacks())),this.connect(this.properties.js_event_callbacks.change,(()=>this._update_event_callbacks())),this.connect(this.properties.subscribed_events.change,(()=>this._update_event_callbacks()))}_process_event(e){var t;for(const s of null!==(t=this.js_event_callbacks[e.event_name])&&void 0!==t?t:[])s.execute(e);null!=this.document&&this.subscribed_events.some((t=>t==e.event_name))&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):l.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of r.entries(this.js_property_callbacks)){const n=s.map((e=>()=>e.execute(this)));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){r.isEmpty(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if(i.isString(e))return[...this.references()].filter((t=>t instanceof o&&t.name===e));if(e.prototype instanceof a.HasProps)return[...this.references()].filter((t=>t instanceof e));throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=o,o.__name__=\"Model\",o.init_Model()},\n", " function _(s,e,_,t,a){t();class r{constructor(s,e){this.x_scale=s,this.y_scale=e,this.x_range=this.x_scale.source_range,this.y_range=this.y_scale.source_range,this.ranges=[this.x_range,this.y_range],this.scales=[this.x_scale,this.y_scale]}map_to_screen(s,e){return[this.x_scale.v_compute(s),this.y_scale.v_compute(e)]}map_from_screen(s,e){return[this.x_scale.v_invert(s),this.y_scale.v_invert(e)]}}_.CoordinateTransform=r,r.__name__=\"CoordinateTransform\"},\n", " function _(t,e,s,a,i){a();const n=t(1),_=t(56),r=t(133),o=t(48),l=t(20),d=t(24),h=t(122),c=n.__importStar(t(18)),u=t(10);class v extends _.DataAnnotationView{async lazy_initialize(){await super.lazy_initialize();const{start:t,end:e}=this.model;null!=t&&(this.start=await h.build_view(t,{parent:this})),null!=e&&(this.end=await h.build_view(e,{parent:this}))}set_data(t){var e,s;super.set_data(t),null===(e=this.start)||void 0===e||e.set_data(t),null===(s=this.end)||void 0===s||s.set_data(t)}remove(){var t,e;null===(t=this.start)||void 0===t||t.remove(),null===(e=this.end)||void 0===e||e.remove(),super.remove()}map_data(){const{frame:t}=this.plot_view;\"data\"==this.model.start_units?(this._sx_start=this.coordinates.x_scale.v_compute(this._x_start),this._sy_start=this.coordinates.y_scale.v_compute(this._y_start)):(this._sx_start=t.bbox.xview.v_compute(this._x_start),this._sy_start=t.bbox.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(this._sx_end=this.coordinates.x_scale.v_compute(this._x_end),this._sy_end=this.coordinates.y_scale.v_compute(this._y_end)):(this._sx_end=t.bbox.xview.v_compute(this._x_end),this._sy_end=t.bbox.yview.v_compute(this._y_end));const{_sx_start:e,_sy_start:s,_sx_end:a,_sy_end:i}=this,n=e.length,_=this._angles=new d.ScreenArray(n);for(let t=0;t({x_start:[c.XCoordinateSpec,{field:\"x_start\"}],y_start:[c.YCoordinateSpec,{field:\"y_start\"}],start_units:[l.SpatialUnits,\"data\"],start:[e(t(r.ArrowHead)),null],x_end:[c.XCoordinateSpec,{field:\"x_end\"}],y_end:[c.YCoordinateSpec,{field:\"y_end\"}],end_units:[l.SpatialUnits,\"data\"],end:[e(t(r.ArrowHead)),()=>new r.OpenHead]})))}}s.Arrow=p,p.__name__=\"Arrow\",p.init_Arrow()},\n", " function _(t,n,s,a,e){a();const i=t(1),o=t(40),c=t(57),_=t(130),r=t(65),l=i.__importStar(t(18));class h extends o.AnnotationView{constructor(){super(...arguments),this._initial_set_data=!1}connect_signals(){super.connect_signals();const t=()=>{this.set_data(this.model.source),this.request_render()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}set_data(t){const n=this;for(const s of this.model)if(s instanceof l.VectorSpec||s instanceof l.ScalarSpec)if(s instanceof l.BaseCoordinateSpec){const a=s.array(t);n[`_${s.attr}`]=a}else{const a=s.uniform(t);n[`${s.attr}`]=a}this.plot_model.use_map&&(null!=n._x&&r.inplace.project_xy(n._x,n._y),null!=n._xs&&r.inplace.project_xsys(n._xs,n._ys));for(const t of this.visuals)t.update()}_render(){this._initial_set_data||(this.set_data(this.model.source),this._initial_set_data=!0),this.map_data(),this.paint(this.layer.ctx)}}s.DataAnnotationView=h,h.__name__=\"DataAnnotationView\";class u extends o.Annotation{constructor(t){super(t)}static init_DataAnnotation(){this.define((({Ref:t})=>({source:[t(c.ColumnarDataSource),()=>new _.ColumnDataSource]})))}}s.DataAnnotation=u,u.__name__=\"DataAnnotation\",u.init_DataAnnotation()},\n", " function _(t,e,n,a,i){a();const s=t(58),r=t(15),l=t(19),o=t(60),c=t(8),u=t(9),h=t(13),g=t(59),d=t(129),_=t(29);class m extends s.DataSource{constructor(t){super(t)}get_array(t){let e=this.data[t];return null==e?this.data[t]=e=[]:c.isArray(e)||(this.data[t]=e=Array.from(e)),e}static init_ColumnarDataSource(){this.define((({Ref:t})=>({selection_policy:[t(d.SelectionPolicy),()=>new d.UnionRenderers]}))),this.internal((({AnyRef:t})=>({selection_manager:[t(),t=>new o.SelectionManager({source:t})],inspected:[t(),()=>new g.Selection]})))}initialize(){super.initialize(),this._select=new r.Signal0(this,\"select\"),this.inspect=new r.Signal(this,\"inspect\"),this.streaming=new r.Signal0(this,\"streaming\"),this.patching=new r.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return h.keys(this.data)}get_length(t=!0){const e=u.uniq(h.values(this.data).map((t=>_.is_NDArray(t)?t.shape[0]:t.length)));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return l.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=m,m.__name__=\"ColumnarDataSource\",m.init_ColumnarDataSource()},\n", " function _(e,t,c,n,a){n();const o=e(53),i=e(59);class s extends o.Model{constructor(e){super(e)}static init_DataSource(){this.define((({Ref:e})=>({selected:[e(i.Selection),()=>new i.Selection]})))}}c.DataSource=s,s.__name__=\"DataSource\",s.init_DataSource()},\n", " function _(i,e,s,t,n){t();const l=i(53),c=i(9),h=i(13);class d extends l.Model{constructor(i){super(i)}get_view(){return this.view}static init_Selection(){this.define((({Int:i,Array:e,Dict:s})=>({indices:[e(i),[]],line_indices:[e(i),[]],multiline_indices:[s(e(i)),{}]}))),this.internal((({Int:i,Array:e,AnyRef:s,Struct:t,Nullable:n})=>({selected_glyphs:[e(s()),[]],view:[n(s()),null],image_indices:[e(t({index:i,dim1:i,dim2:i,flat_index:i})),[]]})))}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.selected_glyphs=i.selected_glyphs,this.view=i.view,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.view=null,this.selected_glyphs=[]}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=c.union(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=c.intersection(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=c.difference(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}}s.Selection=d,d.__name__=\"Selection\",d.init_Selection()},\n", " function _(e,t,s,n,i){n();const o=e(14),c=e(59),r=e(61),l=e(123);class p extends o.HasProps{constructor(e){super(e),this.inspectors=new Map}static init_SelectionManager(){this.internal((({AnyRef:e})=>({source:[e()]})))}select(e,t,s,n=\"replace\"){const i=[],o=[];for(const t of e)t instanceof r.GlyphRendererView?i.push(t):t instanceof l.GraphRendererView&&o.push(t);let c=!1;for(const e of o){const i=e.model.selection_policy.hit_test(t,e);c=c||e.model.selection_policy.do_selection(i,e.model,s,n)}if(i.length>0){const e=this.source.selection_policy.hit_test(t,i);c=c||this.source.selection_policy.do_selection(e,this.source,s,n)}return c}inspect(e,t){let s=!1;if(e instanceof r.GlyphRendererView){const n=e.hit_test(t);if(null!=n){s=!n.is_empty();const i=this.get_or_create_inspector(e.model);i.update(n,!0,\"replace\"),this.source.setv({inspected:i},{silent:!0}),this.source.inspect.emit([e.model,{geometry:t}])}}else if(e instanceof l.GraphRendererView){const n=e.model.inspection_policy.hit_test(t,e);s=s||e.model.inspection_policy.do_inspection(n,t,e,!1,\"replace\")}return s}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new c.Selection,this.inspectors.set(e,t)),t}}s.SelectionManager=p,p.__name__=\"SelectionManager\",p.init_SelectionManager()},\n", " function _(e,t,i,s,l){s();const h=e(62),n=e(63),o=e(116),a=e(117),c=e(119),d=e(98),_=e(57),r=e(120),p=e(24),g=e(12),u=e(9),y=e(13),m=e(122),v=e(104),f={fill:{},line:{}},w={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},b={fill:{fill_alpha:.2},line:{}};class V extends h.DataRendererView{get glyph_view(){return this.glyph}async lazy_initialize(){var e,t;await super.lazy_initialize();const i=this.model.glyph;this.glyph=await this.build_glyph_view(i);const s=\"fill\"in this.glyph.visuals,l=\"line\"in this.glyph.visuals,h=Object.assign({},i.attributes);function n(e){const t=y.clone(h);return s&&y.extend(t,e.fill),l&&y.extend(t,e.line),new i.constructor(t)}delete h.id;let{selection_glyph:o}=this.model;null==o?o=n({fill:{},line:{}}):\"auto\"==o&&(o=n(f)),this.selection_glyph=await this.build_glyph_view(o);let{nonselection_glyph:a}=this.model;null==a?a=n({fill:{},line:{}}):\"auto\"==a&&(a=n(b)),this.nonselection_glyph=await this.build_glyph_view(a);const{hover_glyph:c}=this.model;null!=c&&(this.hover_glyph=await this.build_glyph_view(c));const{muted_glyph:d}=this.model;null!=d&&(this.muted_glyph=await this.build_glyph_view(d));const _=n(w);this.decimated_glyph=await this.build_glyph_view(_),this.selection_glyph.set_base(this.glyph),this.nonselection_glyph.set_base(this.glyph),null===(e=this.hover_glyph)||void 0===e||e.set_base(this.glyph),null===(t=this.muted_glyph)||void 0===t||t.set_base(this.glyph),this.decimated_glyph.set_base(this.glyph),this.set_data()}async build_glyph_view(e){return m.build_view(e,{parent:this})}remove(){var e,t;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),null===(t=this.muted_glyph)||void 0===t||t.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals();const e=()=>this.request_render(),t=()=>this.update_data();this.connect(this.model.change,e),this.connect(this.glyph.model.change,t),this.connect(this.selection_glyph.model.change,t),this.connect(this.nonselection_glyph.model.change,t),null!=this.hover_glyph&&this.connect(this.hover_glyph.model.change,t),null!=this.muted_glyph&&this.connect(this.muted_glyph.model.change,t),this.connect(this.decimated_glyph.model.change,t),this.connect(this.model.data_source.change,t),this.connect(this.model.data_source.streaming,t),this.connect(this.model.data_source.patching,(e=>this.update_data(e))),this.connect(this.model.data_source.selected.change,e),this.connect(this.model.data_source._select,e),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,e),this.connect(this.model.properties.view.change,t),this.connect(this.model.view.properties.indices.change,t),this.connect(this.model.view.properties.masked.change,(()=>this.set_visuals())),this.connect(this.model.properties.visible.change,(()=>this.plot_view.invalidate_dataranges=!0));const{x_ranges:i,y_ranges:s}=this.plot_view.frame;for(const[,e]of i)e instanceof v.FactorRange&&this.connect(e.change,t);for(const[,e]of s)e instanceof v.FactorRange&&this.connect(e.change,t);const{transformchange:l,exprchange:h}=this.model.glyph;this.connect(l,t),this.connect(h,t)}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}update_data(e){this.set_data(e),this.request_render()}set_data(e){const t=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:i}=this;this.glyph.set_data(t,i,e),this.set_visuals(),this._update_masked_indices();const{lod_factor:s}=this.plot_model,l=this.all_indices.count;this.decimated=new p.Indices(l);for(let e=0;e!d||d.is_empty()?[]:d.selected_glyph?this.model.view.convert_indices_from_subset(i):d.indices.length>0?d.indices:Object.keys(d.multiline_indices).map((e=>parseInt(e))))()),r=g.filter(i,(e=>_.has(t[e]))),{lod_threshold:p}=this.plot_model;let y,m,v;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=p&&t.length>p?(i=[...this.decimated],y=this.decimated_glyph,m=this.decimated_glyph,v=this.selection_glyph):(y=this.model.muted&&null!=this.muted_glyph?this.muted_glyph:this.glyph,m=this.nonselection_glyph,v=this.selection_glyph),null!=this.hover_glyph&&r.length&&(i=u.difference(i,r)),h.length){const e={};for(const t of h)e[t]=!0;const l=new Array,o=new Array;if(this.glyph instanceof n.LineView)for(const i of t)null!=e[i]?l.push(i):o.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):o.push(s);m.render(s,o),v.render(s,l),null!=this.hover_glyph&&(this.glyph instanceof n.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(r)):this.hover_glyph.render(s,r))}else if(this.glyph instanceof n.LineView)this.hover_glyph&&r.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(r)):y.render(s,t);else if(this.glyph instanceof o.PatchView||this.glyph instanceof a.HAreaView||this.glyph instanceof c.VAreaView)if(0==d.selected_glyphs.length||null==this.hover_glyph)y.render(s,t);else for(const e of d.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t);else y.render(s,i),this.hover_glyph&&r.length&&this.hover_glyph.render(s,r);s.restore()}draw_legend(e,t,i,s,l,h,n,o){0!=this.glyph.data_size&&(null==o&&(o=this.model.get_reference_point(h,n)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o))}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=V,V.__name__=\"GlyphRendererView\";class G extends h.DataRenderer{constructor(e){super(e)}static init_GlyphRenderer(){this.prototype.default_view=V,this.define((({Boolean:e,Auto:t,Or:i,Ref:s,Null:l,Nullable:h})=>({data_source:[s(_.ColumnarDataSource)],view:[s(r.CDSView),e=>new r.CDSView({source:e.data_source})],glyph:[s(d.Glyph)],hover_glyph:[h(s(d.Glyph)),null],nonselection_glyph:[i(s(d.Glyph),t,l),\"auto\"],selection_glyph:[i(s(d.Glyph),t,l),\"auto\"],muted_glyph:[h(s(d.Glyph)),null],muted:[e,!1]})))}initialize(){super.initialize(),this.view.source!=this.data_source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){if(null!=e){const i=this.data_source.get_column(e);if(null!=i)for(const[e,s]of Object.entries(this.view.indices_map))if(i[parseInt(e)]==t)return s}return 0}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=G,G.__name__=\"GlyphRenderer\",G.init_GlyphRenderer()},\n", " function _(e,r,t,a,n){a();const s=e(41);class i extends s.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=i,i.__name__=\"DataRendererView\";class _ extends s.Renderer{constructor(e){super(e)}static init_DataRenderer(){this.override({level:\"glyph\"})}get selection_manager(){return this.get_selection_manager()}}t.DataRenderer=_,_.__name__=\"DataRenderer\",_.init_DataRenderer()},\n", " function _(e,i,t,s,n){s();const l=e(1),_=e(64),r=e(106),h=e(108),o=l.__importStar(e(48)),a=l.__importStar(e(107)),c=e(59);class d extends _.XYGlyphView{initialize(){super.initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;null!=e&&(this.glglyph=new h.LineGL(e.gl,this))}_render(e,i,t){const{sx:s,sy:n}=null!=t?t:this;let l=!0;e.beginPath();for(const t of i){const i=s[t],_=n[t];isFinite(i+_)?l?(e.moveTo(i,_),l=!1):e.lineTo(i,_):l=!0}this.visuals.line.set_value(e),e.stroke()}_hit_point(e){const i=new c.Selection,t={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.line_width.value/2);for(let e=0,l=this.sx.length-1;e({x:[p.XCoordinateSpec,{field:\"x\"}],y:[p.YCoordinateSpec,{field:\"y\"}]})))}}i.XYGlyph=d,d.__name__=\"XYGlyph\",d.init_XYGlyph()},\n", " function _(n,t,e,o,r){o();const c=n(1),l=c.__importDefault(n(66)),i=c.__importDefault(n(67)),u=n(24),a=new i.default(\"GOOGLE\"),s=new i.default(\"WGS84\"),f=l.default(s,a);e.wgs84_mercator={compute:(n,t)=>isFinite(n)&&isFinite(t)?f.forward([n,t]):[NaN,NaN],invert:(n,t)=>isFinite(n)&&isFinite(t)?f.inverse([n,t]):[NaN,NaN]};const _={lon:[-20026376.39,20026376.39],lat:[-20048966.1,20048966.1]},p={lon:[-180,180],lat:[-85.06,85.06]},{min:g,max:h}=Math;function m(n,t){const o=g(n.length,t.length),r=u.infer_type(n,t),c=new r(o),l=new r(o);return e.inplace.project_xy(n,t,c,l),[c,l]}e.clip_mercator=function(n,t,e){const[o,r]=_[e];return[h(n,o),g(t,r)]},e.in_bounds=function(n,t){const[e,o]=p[t];return e2?void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name?\"number\"==typeof r.z?[r.x,r.y,r.z].concat(t.splice(3)):[r.x,r.y,t[2]].concat(t.splice(3)):[r.x,r.y].concat(t.splice(2)):[r.x,r.y]):(o=c.default(e,n,t),2===(a=Object.keys(t)).length||a.forEach((function(r){if(void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name){if(\"x\"===r||\"y\"===r||\"z\"===r)return}else if(\"x\"===r||\"y\"===r)return;o[r]=t[r]})),o)}function l(e){return e instanceof i.default?e:e.oProj?e.oProj:i.default(e)}t.default=function(e,n,t){e=l(e);var r,o=!1;return void 0===n?(n=e,e=u,o=!0):(void 0!==n.x||Array.isArray(n))&&(t=n,n=e,e=u,o=!0),n=l(n),t?f(e,n,t):(r={forward:function(t){return f(e,n,t)},inverse:function(t){return f(n,e,t)}},o&&(r.oProj=n),r)}},\n", " function _(t,e,a,s,i){s();const u=t(1),l=u.__importDefault(t(68)),o=u.__importDefault(t(79)),r=u.__importDefault(t(80)),f=t(88),p=u.__importDefault(t(90)),d=u.__importDefault(t(91)),m=u.__importDefault(t(75));function n(t,e){if(!(this instanceof n))return new n(t);e=e||function(t){if(t)throw t};var a=l.default(t);if(\"object\"==typeof a){var s=n.projections.get(a.projName);if(s){if(a.datumCode&&\"none\"!==a.datumCode){var i=m.default(p.default,a.datumCode);i&&(a.datum_params=i.towgs84?i.towgs84.split(\",\"):null,a.ellps=i.ellipse,a.datumName=i.datumName?i.datumName:a.datumCode)}a.k0=a.k0||1,a.axis=a.axis||\"enu\",a.ellps=a.ellps||\"wgs84\";var u=f.sphere(a.a,a.b,a.rf,a.ellps,a.sphere),r=f.eccentricity(u.a,u.b,u.rf,a.R_A),h=a.datum||d.default(a.datumCode,a.datum_params,u.a,u.b,r.es,r.ep2);o.default(this,a),o.default(this,s),this.a=u.a,this.b=u.b,this.rf=u.rf,this.sphere=u.sphere,this.es=r.es,this.e=r.e,this.ep2=r.ep2,this.datum=h,this.init(),e(null,this)}else e(t)}else e(t)}n.projections=r.default,n.projections.start(),a.default=n},\n", " function _(t,r,n,u,e){u();const f=t(1),i=f.__importDefault(t(69)),a=f.__importDefault(t(76)),o=f.__importDefault(t(71)),l=f.__importDefault(t(75));var C=[\"PROJECTEDCRS\",\"PROJCRS\",\"GEOGCS\",\"GEOCCS\",\"PROJCS\",\"LOCAL_CS\",\"GEODCRS\",\"GEODETICCRS\",\"GEODETICDATUM\",\"ENGCRS\",\"ENGINEERINGCRS\"];var d=[\"3857\",\"900913\",\"3785\",\"102113\"];n.default=function(t){if(!function(t){return\"string\"==typeof t}(t))return t;if(function(t){return t in i.default}(t))return i.default[t];if(function(t){return C.some((function(r){return t.indexOf(r)>-1}))}(t)){var r=a.default(t);if(function(t){var r=l.default(t,\"authority\");if(r){var n=l.default(r,\"epsg\");return n&&d.indexOf(n)>-1}}(r))return i.default[\"EPSG:3857\"];var n=function(t){var r=l.default(t,\"extension\");if(r)return l.default(r,\"proj4\")}(r);return n?o.default(n):r}return function(t){return\"+\"===t[0]}(t)?o.default(t):void 0}},\n", " function _(t,r,i,e,n){e();const f=t(1),a=f.__importDefault(t(70)),l=f.__importDefault(t(71)),u=f.__importDefault(t(76));function o(t){var r=this;if(2===arguments.length){var i=arguments[1];\"string\"==typeof i?\"+\"===i.charAt(0)?o[t]=l.default(arguments[1]):o[t]=u.default(arguments[1]):o[t]=i}else if(1===arguments.length){if(Array.isArray(t))return t.map((function(t){Array.isArray(t)?o.apply(r,t):o(t)}));if(\"string\"==typeof t){if(t in o)return o[t]}else\"EPSG\"in t?o[\"EPSG:\"+t.EPSG]=t:\"ESRI\"in t?o[\"ESRI:\"+t.ESRI]=t:\"IAU2000\"in t?o[\"IAU2000:\"+t.IAU2000]=t:console.log(t);return}}a.default(o),i.default=o},\n", " function _(t,l,G,S,e){S(),G.default=function(t){t(\"EPSG:4326\",\"+title=WGS 84 (long/lat) +proj=longlat +ellps=WGS84 +datum=WGS84 +units=degrees\"),t(\"EPSG:4269\",\"+title=NAD83 (long/lat) +proj=longlat +a=6378137.0 +b=6356752.31414036 +ellps=GRS80 +datum=NAD83 +units=degrees\"),t(\"EPSG:3857\",\"+title=WGS 84 / Pseudo-Mercator +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +no_defs\"),t.WGS84=t[\"EPSG:4326\"],t[\"EPSG:3785\"]=t[\"EPSG:3857\"],t.GOOGLE=t[\"EPSG:3857\"],t[\"EPSG:900913\"]=t[\"EPSG:3857\"],t[\"EPSG:102113\"]=t[\"EPSG:3857\"]}},\n", " function _(t,n,o,a,u){a();const e=t(1),r=t(72),i=e.__importDefault(t(73)),f=e.__importDefault(t(74)),l=e.__importDefault(t(75));o.default=function(t){var n,o,a,u={},e=t.split(\"+\").map((function(t){return t.trim()})).filter((function(t){return t})).reduce((function(t,n){var o=n.split(\"=\");return o.push(!0),t[o[0].toLowerCase()]=o[1],t}),{}),c={proj:\"projName\",datum:\"datumCode\",rf:function(t){u.rf=parseFloat(t)},lat_0:function(t){u.lat0=t*r.D2R},lat_1:function(t){u.lat1=t*r.D2R},lat_2:function(t){u.lat2=t*r.D2R},lat_ts:function(t){u.lat_ts=t*r.D2R},lon_0:function(t){u.long0=t*r.D2R},lon_1:function(t){u.long1=t*r.D2R},lon_2:function(t){u.long2=t*r.D2R},alpha:function(t){u.alpha=parseFloat(t)*r.D2R},lonc:function(t){u.longc=t*r.D2R},x_0:function(t){u.x0=parseFloat(t)},y_0:function(t){u.y0=parseFloat(t)},k_0:function(t){u.k0=parseFloat(t)},k:function(t){u.k0=parseFloat(t)},a:function(t){u.a=parseFloat(t)},b:function(t){u.b=parseFloat(t)},r_a:function(){u.R_A=!0},zone:function(t){u.zone=parseInt(t,10)},south:function(){u.utmSouth=!0},towgs84:function(t){u.datum_params=t.split(\",\").map((function(t){return parseFloat(t)}))},to_meter:function(t){u.to_meter=parseFloat(t)},units:function(t){u.units=t;var n=l.default(f.default,t);n&&(u.to_meter=n.to_meter)},from_greenwich:function(t){u.from_greenwich=t*r.D2R},pm:function(t){var n=l.default(i.default,t);u.from_greenwich=(n||parseFloat(t))*r.D2R},nadgrids:function(t){\"@null\"===t?u.datumCode=\"none\":u.nadgrids=t},axis:function(t){var n=\"ewnsud\";3===t.length&&-1!==n.indexOf(t.substr(0,1))&&-1!==n.indexOf(t.substr(1,1))&&-1!==n.indexOf(t.substr(2,1))&&(u.axis=t)}};for(n in e)o=e[n],n in c?\"function\"==typeof(a=c[n])?a(o):u[a]=o:u[n]=o;return\"string\"==typeof u.datumCode&&\"WGS84\"!==u.datumCode&&(u.datumCode=u.datumCode.toLowerCase()),u}},\n", " function _(P,A,_,D,I){D(),_.PJD_3PARAM=1,_.PJD_7PARAM=2,_.PJD_WGS84=4,_.PJD_NODATUM=5,_.SEC_TO_RAD=484813681109536e-20,_.HALF_PI=Math.PI/2,_.SIXTH=.16666666666666666,_.RA4=.04722222222222222,_.RA6=.022156084656084655,_.EPSLN=1e-10,_.D2R=.017453292519943295,_.R2D=57.29577951308232,_.FORTPI=Math.PI/4,_.TWO_PI=2*Math.PI,_.SPI=3.14159265359},\n", " function _(o,r,a,e,s){e();var n={};a.default=n,n.greenwich=0,n.lisbon=-9.131906111111,n.paris=2.337229166667,n.bogota=-74.080916666667,n.madrid=-3.687938888889,n.rome=12.452333333333,n.bern=7.439583333333,n.jakarta=106.807719444444,n.ferro=-17.666666666667,n.brussels=4.367975,n.stockholm=18.058277777778,n.athens=23.7163375,n.oslo=10.722916666667},\n", " function _(t,e,f,o,u){o(),f.default={ft:{to_meter:.3048},\"us-ft\":{to_meter:1200/3937}}},\n", " function _(e,r,t,a,n){a();var o=/[\\s_\\-\\/\\(\\)]/g;t.default=function(e,r){if(e[r])return e[r];for(var t,a=Object.keys(e),n=r.toLowerCase().replace(o,\"\"),f=-1;++f0?90:-90),e.lat_ts=e.lat1)}(d),d}},\n", " function _(t,e,r,i,s){i(),r.default=function(t){return new d(t).output()};var h=/\\s/,o=/[A-Za-z]/,n=/[A-Za-z84]/,a=/[,\\]]/,u=/[\\d\\.E\\-\\+]/;function d(t){if(\"string\"!=typeof t)throw new Error(\"not a string\");this.text=t.trim(),this.level=0,this.place=0,this.root=null,this.stack=[],this.currentObject=null,this.state=1}d.prototype.readCharicter=function(){var t=this.text[this.place++];if(4!==this.state)for(;h.test(t);){if(this.place>=this.text.length)return;t=this.text[this.place++]}switch(this.state){case 1:return this.neutral(t);case 2:return this.keyword(t);case 4:return this.quoted(t);case 5:return this.afterquote(t);case 3:return this.number(t);case-1:return}},d.prototype.afterquote=function(t){if('\"'===t)return this.word+='\"',void(this.state=4);if(a.test(t))return this.word=this.word.trim(),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in afterquote yet, index '+this.place)},d.prototype.afterItem=function(t){return\",\"===t?(null!==this.word&&this.currentObject.push(this.word),this.word=null,void(this.state=1)):\"]\"===t?(this.level--,null!==this.word&&(this.currentObject.push(this.word),this.word=null),this.state=1,this.currentObject=this.stack.pop(),void(this.currentObject||(this.state=-1))):void 0},d.prototype.number=function(t){if(!u.test(t)){if(a.test(t))return this.word=parseFloat(this.word),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in number yet, index '+this.place)}this.word+=t},d.prototype.quoted=function(t){'\"'!==t?this.word+=t:this.state=5},d.prototype.keyword=function(t){if(n.test(t))this.word+=t;else{if(\"[\"===t){var e=[];return e.push(this.word),this.level++,null===this.root?this.root=e:this.currentObject.push(e),this.stack.push(this.currentObject),this.currentObject=e,void(this.state=1)}if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in keyword yet, index '+this.place);this.afterItem(t)}},d.prototype.neutral=function(t){if(o.test(t))return this.word=t,void(this.state=2);if('\"'===t)return this.word=\"\",void(this.state=4);if(u.test(t))return this.word=t,void(this.state=3);if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in neutral yet, index '+this.place);this.afterItem(t)},d.prototype.output=function(){for(;this.place90&&a*o.R2D<-90&&h*o.R2D>180&&h*o.R2D<-180)return null;if(Math.abs(Math.abs(a)-o.HALF_PI)<=o.EPSLN)return null;if(this.sphere)i=this.x0+this.a*this.k0*n.default(h-this.long0),s=this.y0+this.a*this.k0*Math.log(Math.tan(o.FORTPI+.5*a));else{var e=Math.sin(a),r=l.default(this.e,a,e);i=this.x0+this.a*this.k0*n.default(h-this.long0),s=this.y0-this.a*this.k0*Math.log(r)}return t.x=i,t.y=s,t}function M(t){var i,s,h=t.x-this.x0,a=t.y-this.y0;if(this.sphere)s=o.HALF_PI-2*Math.atan(Math.exp(-a/(this.a*this.k0)));else{var e=Math.exp(-a/(this.a*this.k0));if(-9999===(s=u.default(this.e,e)))return null}return i=n.default(this.long0+h/(this.a*this.k0)),t.x=i,t.y=s,t}s.init=f,s.forward=_,s.inverse=M,s.names=[\"Mercator\",\"Popular Visualisation Pseudo Mercator\",\"Mercator_1SP\",\"Mercator_Auxiliary_Sphere\",\"merc\"],s.default={init:f,forward:_,inverse:M,names:s.names}},\n", " function _(t,n,r,u,a){u(),r.default=function(t,n,r){var u=t*n;return r/Math.sqrt(1-u*u)}},\n", " function _(t,n,u,a,f){a();const e=t(1),o=t(72),_=e.__importDefault(t(84));u.default=function(t){return Math.abs(t)<=o.SPI?t:t-_.default(t)*o.TWO_PI}},\n", " function _(n,t,u,f,c){f(),u.default=function(n){return n<0?-1:1}},\n", " function _(t,n,a,o,u){o();const c=t(72);a.default=function(t,n,a){var o=t*a,u=.5*t;return o=Math.pow((1-o)/(1+o),u),Math.tan(.5*(c.HALF_PI-n))/o}},\n", " function _(t,a,n,r,f){r();const h=t(72);n.default=function(t,a){for(var n,r,f=.5*t,o=h.HALF_PI-2*Math.atan(a),u=0;u<=15;u++)if(n=t*Math.sin(o),o+=r=h.HALF_PI-2*Math.atan(a*Math.pow((1-n)/(1+n),f))-o,Math.abs(r)<=1e-10)return o;return-9999}},\n", " function _(n,i,e,t,r){function a(){}function f(n){return n}t(),e.init=a,e.forward=f,e.inverse=f,e.names=[\"longlat\",\"identity\"],e.default={init:a,forward:f,inverse:f,names:e.names}},\n", " function _(t,r,e,a,n){a();const f=t(1),i=t(72),u=f.__importStar(t(89)),c=f.__importDefault(t(75));e.eccentricity=function(t,r,e,a){var n=t*t,f=r*r,u=(n-f)/n,c=0;return a?(n=(t*=1-u*(i.SIXTH+u*(i.RA4+u*i.RA6)))*t,u=0):c=Math.sqrt(u),{es:u,e:c,ep2:(n-f)/f}},e.sphere=function(t,r,e,a,n){if(!t){var f=c.default(u.default,a);f||(f=u.WGS84),t=f.a,r=f.b,e=f.rf}return e&&!r&&(r=(1-1/e)*t),(0===e||Math.abs(t-r)3&&(0===r.datum_params[3]&&0===r.datum_params[4]&&0===r.datum_params[5]&&0===r.datum_params[6]||(r.datum_type=p.PJD_7PARAM,r.datum_params[3]*=p.SEC_TO_RAD,r.datum_params[4]*=p.SEC_TO_RAD,r.datum_params[5]*=p.SEC_TO_RAD,r.datum_params[6]=r.datum_params[6]/1e6+1))),r.a=_,r.b=t,r.es=u,r.ep2=d,r}},\n", " function _(t,e,a,r,u){r();const m=t(1),_=t(72),o=m.__importDefault(t(93)),d=m.__importDefault(t(95)),f=m.__importDefault(t(67)),n=m.__importDefault(t(96)),i=m.__importDefault(t(97));a.default=function t(e,a,r){var u;if(Array.isArray(r)&&(r=n.default(r)),i.default(r),e.datum&&a.datum&&function(t,e){return(t.datum.datum_type===_.PJD_3PARAM||t.datum.datum_type===_.PJD_7PARAM)&&\"WGS84\"!==e.datumCode||(e.datum.datum_type===_.PJD_3PARAM||e.datum.datum_type===_.PJD_7PARAM)&&\"WGS84\"!==t.datumCode}(e,a)&&(r=t(e,u=new f.default(\"WGS84\"),r),e=u),\"enu\"!==e.axis&&(r=d.default(e,!1,r)),\"longlat\"===e.projName)r={x:r.x*_.D2R,y:r.y*_.D2R,z:r.z||0};else if(e.to_meter&&(r={x:r.x*e.to_meter,y:r.y*e.to_meter,z:r.z||0}),!(r=e.inverse(r)))return;return e.from_greenwich&&(r.x+=e.from_greenwich),r=o.default(e.datum,a.datum,r),a.from_greenwich&&(r={x:r.x-a.from_greenwich,y:r.y,z:r.z||0}),\"longlat\"===a.projName?r={x:r.x*_.R2D,y:r.y*_.R2D,z:r.z||0}:(r=a.forward(r),a.to_meter&&(r={x:r.x/a.to_meter,y:r.y/a.to_meter,z:r.z||0})),\"enu\"!==a.axis?d.default(a,!0,r):r}},\n", " function _(t,e,a,u,c){u();const m=t(72),o=t(94);function _(t){return t===m.PJD_3PARAM||t===m.PJD_7PARAM}a.default=function(t,e,a){return o.compareDatums(t,e)||t.datum_type===m.PJD_NODATUM||e.datum_type===m.PJD_NODATUM?a:t.es!==e.es||t.a!==e.a||_(t.datum_type)||_(e.datum_type)?(a=o.geodeticToGeocentric(a,t.es,t.a),_(t.datum_type)&&(a=o.geocentricToWgs84(a,t.datum_type,t.datum_params)),_(e.datum_type)&&(a=o.geocentricFromWgs84(a,e.datum_type,e.datum_params)),o.geocentricToGeodetic(a,e.es,e.a,e.b)):a}},\n", " function _(a,t,r,m,s){m();const u=a(72);r.compareDatums=function(a,t){return a.datum_type===t.datum_type&&(!(a.a!==t.a||Math.abs(a.es-t.es)>5e-11)&&(a.datum_type===u.PJD_3PARAM?a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]:a.datum_type!==u.PJD_7PARAM||a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]&&a.datum_params[3]===t.datum_params[3]&&a.datum_params[4]===t.datum_params[4]&&a.datum_params[5]===t.datum_params[5]&&a.datum_params[6]===t.datum_params[6]))},r.geodeticToGeocentric=function(a,t,r){var m,s,_,e,n=a.x,d=a.y,i=a.z?a.z:0;if(d<-u.HALF_PI&&d>-1.001*u.HALF_PI)d=-u.HALF_PI;else if(d>u.HALF_PI&&d<1.001*u.HALF_PI)d=u.HALF_PI;else{if(d<-u.HALF_PI)return{x:-1/0,y:-1/0,z:a.z};if(d>u.HALF_PI)return{x:1/0,y:1/0,z:a.z}}return n>Math.PI&&(n-=2*Math.PI),s=Math.sin(d),e=Math.cos(d),_=s*s,{x:((m=r/Math.sqrt(1-t*_))+i)*e*Math.cos(n),y:(m+i)*e*Math.sin(n),z:(m*(1-t)+i)*s}},r.geocentricToGeodetic=function(a,t,r,m){var s,_,e,n,d,i,p,P,y,z,M,o,A,c,x,h=1e-12,f=a.x,I=a.y,F=a.z?a.z:0;if(s=Math.sqrt(f*f+I*I),_=Math.sqrt(f*f+I*I+F*F),s/r1e-24&&A<30);return{x:c,y:Math.atan(M/Math.abs(z)),z:x}},r.geocentricToWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x+r[0],y:a.y+r[1],z:a.z+r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6];return{x:i*(a.x-d*a.y+n*a.z)+m,y:i*(d*a.x+a.y-e*a.z)+s,z:i*(-n*a.x+e*a.y+a.z)+_}}},r.geocentricFromWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x-r[0],y:a.y-r[1],z:a.z-r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6],p=(a.x-m)/i,P=(a.y-s)/i,y=(a.z-_)/i;return{x:p+d*P-n*y,y:-d*p+P+e*y,z:n*p-e*P+y}}}},\n", " function _(e,a,i,r,s){r(),i.default=function(e,a,i){var r,s,n,c=i.x,d=i.y,f=i.z||0,u={};for(n=0;n<3;n++)if(!a||2!==n||void 0!==i.z)switch(0===n?(r=c,s=-1!==\"ew\".indexOf(e.axis[n])?\"x\":\"y\"):1===n?(r=d,s=-1!==\"ns\".indexOf(e.axis[n])?\"y\":\"x\"):(r=f,s=\"z\"),e.axis[n]){case\"e\":u[s]=r;break;case\"w\":u[s]=-r;break;case\"n\":u[s]=r;break;case\"s\":u[s]=-r;break;case\"u\":void 0!==i[s]&&(u.z=r);break;case\"d\":void 0!==i[s]&&(u.z=-r);break;default:return null}return u}},\n", " function _(n,t,e,u,f){u(),e.default=function(n){var t={x:n[0],y:n[1]};return n.length>2&&(t.z=n[2]),n.length>3&&(t.m=n[3]),t}},\n", " function _(e,i,n,t,r){function o(e){if(\"function\"==typeof Number.isFinite){if(Number.isFinite(e))return;throw new TypeError(\"coordinates must be finite numbers\")}if(\"number\"!=typeof e||e!=e||!isFinite(e))throw new TypeError(\"coordinates must be finite numbers\")}t(),n.default=function(e){o(e.x),o(e.y)}},\n", " function _(e,t,s,i,n){i();const r=e(1),a=r.__importStar(e(18)),o=r.__importStar(e(99)),_=r.__importStar(e(45)),l=e(42),c=e(53),h=e(19),d=e(24),u=e(8),f=e(100),p=e(12),g=e(26),y=e(101),x=e(104),v=e(59),{abs:b,ceil:m}=Math;class w extends l.View{constructor(){super(...arguments),this._index=null,this._data_size=null,this._nohit_warned=new Set}get renderer(){return this.parent}get has_webgl(){return null!=this.glglyph}get index(){const{_index:e}=this;if(null!=e)return e;throw new Error(`${this}.index_data() wasn't called`)}get data_size(){const{_data_size:e}=this;if(null!=e)return e;throw new Error(`${this}.set_data() wasn't called`)}initialize(){super.initialize(),this.visuals=new _.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.renderer.parent.canvas_view}render(e,t,s){var i;null!=this.glglyph&&(this.renderer.needs_webgl_blit=this.glglyph.render(e,t,null!==(i=this.base)&&void 0!==i?i:this),this.renderer.needs_webgl_blit)||(e.beginPath(),this._render(e,t,null!=s?s:this.base))}has_finished(){return!0}notify_finished(){this.renderer.notify_finished()}_bounds(e){return e}bounds(){return this._bounds(this.index.bbox)}log_bounds(){const{x0:e,x1:t}=this.index.bounds(o.positive_x()),{y0:s,y1:i}=this.index.bounds(o.positive_y());return this._bounds({x0:e,y0:s,x1:t,y1:i})}get_anchor_point(e,t,[s,i]){switch(e){case\"center\":case\"center_center\":{const[e,n]=this.scenterxy(t,s,i);return{x:e,y:n}}default:return null}}scenterx(e,t,s){return this.scenterxy(e,t,s)[0]}scentery(e,t,s){return this.scenterxy(e,t,s)[1]}sdist(e,t,s,i=\"edge\",n=!1){const r=t.length,a=new d.ScreenArray(r),o=e.s_compute;if(\"center\"==i)for(let e=0;em(e))),a}draw_legend_for_index(e,t,s){}hit_test(e){switch(e.type){case\"point\":if(null!=this._hit_point)return this._hit_point(e);break;case\"span\":if(null!=this._hit_span)return this._hit_span(e);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(e);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(e)}return this._nohit_warned.has(e.type)||(h.logger.debug(`'${e.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(e.type)),null}_hit_rect_against_index(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.coordinates.x_scale.r_invert(t,s),[o,_]=this.renderer.coordinates.y_scale.r_invert(i,n),l=[...this.index.indices({x0:r,x1:a,y0:o,y1:_})];return new v.Selection({indices:l})}_project_data(){}*_iter_visuals(){for(const e of this.visuals)for(const t of e)(t instanceof a.VectorSpec||t instanceof a.ScalarSpec)&&(yield t)}set_base(e){e!=this&&e instanceof this.constructor&&(this.base=e)}_configure(e,t){Object.defineProperty(this,u.isString(e)?e:e.attr,Object.assign({configurable:!0,enumerable:!0},t))}set_visuals(e,t){var s;for(const s of this._iter_visuals()){const{base:i}=this;if(null!=i){const e=i.model.properties[s.attr];if(null!=e&&g.is_equal(s.get_value(),e.get_value())){this._configure(s,{get:()=>i[`${s.attr}`]});continue}}const n=s.uniform(e).select(t);this._configure(s,{value:n})}for(const e of this.visuals)e.update();null===(s=this.glglyph)||void 0===s||s.set_visuals_changed()}set_data(e,t,s){var i;const{x_range:n,y_range:r}=this.renderer.coordinates,o=new Set(this._iter_visuals());this._data_size=t.count;for(const s of this.model)if((s instanceof a.VectorSpec||s instanceof a.ScalarSpec)&&!o.has(s))if(s instanceof a.BaseCoordinateSpec){const i=s.array(e);let o=t.select(i);const _=\"x\"==s.dimension?n:r;if(_ instanceof x.FactorRange)if(s instanceof a.CoordinateSpec)o=_.v_synthetic(o);else if(s instanceof a.CoordinateSeqSpec)for(let e=0;e=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}static from_rect({left:t,right:i,top:e,bottom:h}){return new o({x0:Math.min(t,i),y0:Math.min(e,h),x1:Math.max(t,i),y1:Math.max(e,h)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}[n.equals](t,i){return i.eq(this.x0,t.x0)&&i.eq(this.y0,t.y0)&&i.eq(this.x1,t.x1)&&i.eq(this.y1,t.y1)}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get size(){return{width:this.width,height:this.height}}get rect(){const{x0:t,y0:i,x1:e,y1:h}=this;return{p0:{x:t,y:i},p1:{x:e,y:i},p2:{x:e,y:h},p3:{x:t,y:h}}}get box(){const{x:t,y:i,width:e,height:h}=this;return{x:t,y:i,width:e,height:h}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}get area(){return this.width*this.height}relative(){const{width:t,height:i}=this;return new o({x:0,y:0,width:t,height:i})}translate(t,i){const{x:e,y:h,width:r,height:s}=this;return new o({x:t+e,y:i+h,width:r,height:s})}relativize(t,i){return[t-this.x,i-this.y]}contains(t,i){return this.x0<=t&&t<=this.x1&&this.y0<=i&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}grow_by(t){return new o({left:this.left-t,right:this.right+t,top:this.top-t,bottom:this.bottom+t})}shrink_by(t){return new o({left:this.left+t,right:this.right-t,top:this.top+t,bottom:this.bottom-t})}union(t){return new o({x0:x(this.x0,t.x0),y0:x(this.y0,t.y0),x1:y(this.x1,t.x1),y1:y(this.y1,t.y1)})}intersection(t){return this.intersects(t)?new o({x0:y(this.x0,t.x0),y0:y(this.y0,t.y0),x1:x(this.x1,t.x1),y1:x(this.y1,t.y1)}):null}intersects(t){return!(t.x1this.x1||t.y1this.y1)}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.bottom;for(let h=0;h{const s=new Uint32Array(r);for(let n=0;n>1;i[s]>n?e=s:t=s+1}return i[t]}class r extends o.default{search_indices(n,i,t,e){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let s=this._boxes.length-4;const o=[],x=new d.Indices(this.numItems);for(;void 0!==s;){const d=Math.min(s+4*this.nodeSize,h(s,this._levelBounds));for(let h=s;h>2];tthis._boxes[h+2]||i>this._boxes[h+3]||(s<4*this.numItems?x.set(d):o.push(d)))}s=o.pop()}return x}}r.__name__=\"_FlatBush\";class l{constructor(n){this.index=null,n>0&&(this.index=new r(n))}add(n,i,t,e){var s;null===(s=this.index)||void 0===s||s.add(n,i,t,e)}add_empty(){var n;null===(n=this.index)||void 0===n||n.add(1/0,1/0,-1/0,-1/0)}finish(){var n;null===(n=this.index)||void 0===n||n.finish()}_normalize(n){let{x0:i,y0:t,x1:e,y1:s}=n;return i>e&&([i,e]=[e,i]),t>s&&([t,s]=[s,t]),{x0:i,y0:t,x1:e,y1:s}}get bbox(){if(null==this.index)return x.empty();{const{minX:n,minY:i,maxX:t,maxY:e}=this.index;return{x0:n,y0:i,x1:t,y1:e}}}indices(n){if(null==this.index)return new d.Indices(0);{const{x0:i,y0:t,x1:e,y1:s}=this._normalize(n);return this.index.search_indices(i,t,e,s)}}bounds(n){const i=x.empty();for(const t of this.indices(n)){const n=this.index._boxes,e=n[4*t+0],s=n[4*t+1],o=n[4*t+2],d=n[4*t+3];ei.x1&&(i.x1=o),si.y1&&(i.y1=d)}return i}}t.SpatialIndex=l,l.__name__=\"SpatialIndex\"},\n", " function _(t,s,i,e,h){e();const n=t(1).__importDefault(t(103)),o=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class r{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got v${i>>4} data when expected v3.`);const[e]=new Uint16Array(t,2,1),[h]=new Uint32Array(t,4,1);return new r(h,e,o[15&i],t)}constructor(t,s=16,i=Float64Array,e){if(void 0===t)throw new Error(\"Missing required argument: numItems.\");if(isNaN(t)||t<=0)throw new Error(`Unpexpected numItems value: ${t}.`);this.numItems=+t,this.nodeSize=Math.min(Math.max(+s,2),65535);let h=t,r=h;this._levelBounds=[4*h];do{h=Math.ceil(h/this.nodeSize),r+=h,this._levelBounds.push(4*r)}while(1!==h);this.ArrayType=i||Float64Array,this.IndexArrayType=r<16384?Uint16Array:Uint32Array;const a=o.indexOf(this.ArrayType),_=4*r*this.ArrayType.BYTES_PER_ELEMENT;if(a<0)throw new Error(`Unexpected typed array class: ${i}.`);e&&e instanceof ArrayBuffer?(this.data=e,this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=4*r,this.minX=this._boxes[this._pos-4],this.minY=this._boxes[this._pos-3],this.maxX=this._boxes[this._pos-2],this.maxY=this._boxes[this._pos-1]):(this.data=new ArrayBuffer(8+_+r*this.IndexArrayType.BYTES_PER_ELEMENT),this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=0,this.minX=1/0,this.minY=1/0,this.maxX=-1/0,this.maxY=-1/0,new Uint8Array(this.data,0,2).set([251,48+a]),new Uint16Array(this.data,2,1)[0]=s,new Uint32Array(this.data,4,1)[0]=t),this._queue=new n.default}add(t,s,i,e){const h=this._pos>>2;return this._indices[h]=h,this._boxes[this._pos++]=t,this._boxes[this._pos++]=s,this._boxes[this._pos++]=i,this._boxes[this._pos++]=e,tthis.maxX&&(this.maxX=i),e>this.maxY&&(this.maxY=e),h}finish(){if(this._pos>>2!==this.numItems)throw new Error(`Added ${this._pos>>2} items when expected ${this.numItems}.`);if(this.numItems<=this.nodeSize)return this._boxes[this._pos++]=this.minX,this._boxes[this._pos++]=this.minY,this._boxes[this._pos++]=this.maxX,void(this._boxes[this._pos++]=this.maxY);const t=this.maxX-this.minX,s=this.maxY-this.minY,i=new Uint32Array(this.numItems);for(let e=0;e>2]=t,this._boxes[this._pos++]=e,this._boxes[this._pos++]=h,this._boxes[this._pos++]=n,this._boxes[this._pos++]=o}}}search(t,s,i,e,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=[],r=[];for(;void 0!==n;){const a=Math.min(n+4*this.nodeSize,_(n,this._levelBounds));for(let _=n;_>2];ithis._boxes[_+2]||s>this._boxes[_+3]||(n<4*this.numItems?(void 0===h||h(a))&&r.push(a):o.push(a)))}n=o.pop()}return r}neighbors(t,s,i=1/0,e=1/0,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=this._queue,r=[],x=e*e;for(;void 0!==n;){const e=Math.min(n+4*this.nodeSize,_(n,this._levelBounds));for(let i=n;i>2],r=a(t,this._boxes[i],this._boxes[i+2]),_=a(s,this._boxes[i+1],this._boxes[i+3]),x=r*r+_*_;n<4*this.numItems?(void 0===h||h(e))&&o.push(-e-1,x):o.push(e,x)}for(;o.length&&o.peek()<0;){if(o.peekValue()>x)return o.clear(),r;if(r.push(-o.pop()-1),r.length===i)return o.clear(),r}n=o.pop()}return o.clear(),r}}function a(t,s,i){return t>1;s[h]>t?e=h:i=h+1}return s[i]}function x(t,s,i,e,h,n){if(Math.floor(e/n)>=Math.floor(h/n))return;const o=t[e+h>>1];let r=e-1,a=h+1;for(;;){do{r++}while(t[r]o);if(r>=a)break;d(t,s,i,r,a)}x(t,s,i,e,a,n),x(t,s,i,a+1,h,n)}function d(t,s,i,e,h){const n=t[e];t[e]=t[h],t[h]=n;const o=4*e,r=4*h,a=s[o],_=s[o+1],x=s[o+2],d=s[o+3];s[o]=s[r],s[o+1]=s[r+1],s[o+2]=s[r+2],s[o+3]=s[r+3],s[r]=a,s[r+1]=_,s[r+2]=x,s[r+3]=d;const m=i[e];i[e]=i[h],i[h]=m}function m(t,s){let i=t^s,e=65535^i,h=65535^(t|s),n=t&(65535^s),o=i|e>>1,r=i>>1^i,a=h>>1^e&n>>1^h,_=i&h>>1^n>>1^n;i=o,e=r,h=a,n=_,o=i&i>>2^e&e>>2,r=i&e>>2^e&(i^e)>>2,a^=i&h>>2^e&n>>2,_^=e&h>>2^(i^e)&n>>2,i=o,e=r,h=a,n=_,o=i&i>>4^e&e>>4,r=i&e>>4^e&(i^e)>>4,a^=i&h>>4^e&n>>4,_^=e&h>>4^(i^e)&n>>4,i=o,e=r,h=a,n=_,a^=i&h>>8^e&n>>8,_^=e&h>>8^(i^e)&n>>8,i=a^a>>1,e=_^_>>1;let x=t^s,d=e|65535^(x|i);return x=16711935&(x|x<<8),x=252645135&(x|x<<4),x=858993459&(x|x<<2),x=1431655765&(x|x<<1),d=16711935&(d|d<<8),d=252645135&(d|d<<4),d=858993459&(d|d<<2),d=1431655765&(d|d<<1),(d<<1|x)>>>0}i.default=r},\n", " function _(s,t,i,h,e){h();i.default=class{constructor(){this.ids=[],this.values=[],this.length=0}clear(){this.length=0}push(s,t){let i=this.length++;for(this.ids[i]=s,this.values[i]=t;i>0;){const s=i-1>>1,h=this.values[s];if(t>=h)break;this.ids[i]=this.ids[s],this.values[i]=h,i=s}this.ids[i]=s,this.values[i]=t}pop(){if(0===this.length)return;const s=this.ids[0];if(this.length--,this.length>0){const s=this.ids[0]=this.ids[this.length],t=this.values[0]=this.values[this.length],i=this.length>>1;let h=0;for(;h=t)break;this.ids[h]=e,this.values[h]=l,h=s}this.ids[h]=s,this.values[h]=t}return s}peek(){if(0!==this.length)return this.ids[0]}peekValue(){if(0!==this.length)return this.values[0]}}},\n", " function _(t,n,e,i,s){i();const r=t(105),a=t(20),o=t(21),g=t(24),p=t(9),c=t(8),l=t(11);function u(t,n,e=0){const i=new Map;for(let s=0;sa.get(t).value)));r.set(t,{value:l/s,mapping:a}),o+=s+n+c}return[r,(a.size-1)*n+g]}function d(t,n,e,i,s=0){var r;const a=new Map,o=new Map;for(const[n,e,i]of t){const t=null!==(r=o.get(n))&&void 0!==r?r:[];o.set(n,[...t,[e,i]])}let g=s,c=0;for(const[t,s]of o){const r=s.length,[o,l]=h(s,e,i,g);c+=l;const u=p.sum(s.map((([t])=>o.get(t).value)));a.set(t,{value:u/r,mapping:o}),g+=r+n+l}return[a,(o.size-1)*n+c]}e.Factor=o.Or(o.String,o.Tuple(o.String,o.String),o.Tuple(o.String,o.String,o.String)),e.FactorSeq=o.Or(o.Array(o.String),o.Array(o.Tuple(o.String,o.String)),o.Array(o.Tuple(o.String,o.String,o.String))),e.map_one_level=u,e.map_two_levels=h,e.map_three_levels=d;class _ extends r.Range{constructor(t){super(t)}static init_FactorRange(){this.define((({Number:t})=>({factors:[e.FactorSeq,[]],factor_padding:[t,0],subgroup_padding:[t,.8],group_padding:[t,1.4],range_padding:[t,0],range_padding_units:[a.PaddingUnits,\"percent\"],start:[t],end:[t]}))),this.internal((({Number:t,String:n,Array:e,Tuple:i,Nullable:s})=>({levels:[t],mids:[s(e(i(n,n))),null],tops:[s(e(n)),null]})))}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,(()=>this.reset())),this.connect(this.properties.factor_padding.change,(()=>this.reset())),this.connect(this.properties.group_padding.change,(()=>this.reset())),this.connect(this.properties.subgroup_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding_units.change,(()=>this.reset()))}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[n]=t,e=this._mapping.get(n);return null!=e?e.value:NaN}case 2:{const[n,e]=t,i=this._mapping.get(n);if(null!=i){const t=i.mapping.get(e);if(null!=t)return t.value}return NaN}case 3:{const[n,e,i]=t,s=this._mapping.get(n);if(null!=s){const t=s.mapping.get(e);if(null!=t){const n=t.mapping.get(i);if(null!=n)return n.value}}return NaN}default:l.unreachable()}}synthetic(t){if(c.isNumber(t))return t;if(c.isString(t))return this._lookup([t]);let n=0;const e=t[t.length-1];return c.isNumber(e)&&(n=e,t=t.slice(0,-1)),this._lookup(t)+n}v_synthetic(t){const n=t.length,e=new g.ScreenArray(n);for(let i=0;i{if(p.every(this.factors,c.isString)){const t=this.factors,[n,e]=u(t,this.factor_padding);return{levels:1,mapping:n,tops:null,mids:null,inside_padding:e}}if(p.every(this.factors,(t=>c.isArray(t)&&2==t.length&&c.isString(t[0])&&c.isString(t[1])))){const t=this.factors,[n,e]=h(t,this.group_padding,this.factor_padding),i=[...n.keys()];return{levels:2,mapping:n,tops:i,mids:null,inside_padding:e}}if(p.every(this.factors,(t=>c.isArray(t)&&3==t.length&&c.isString(t[0])&&c.isString(t[1])&&c.isString(t[2])))){const t=this.factors,[n,e]=d(t,this.group_padding,this.subgroup_padding,this.factor_padding),i=[...n.keys()],s=[];for(const[t,e]of n)for(const n of e.mapping.keys())s.push([t,n]);return{levels:3,mapping:n,tops:i,mids:s,inside_padding:e}}l.unreachable()})();this._mapping=e,this.tops=i,this.mids=s;let a=0,o=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(o-a)*this.range_padding/2;a-=t,o+=t}else a-=this.range_padding,o+=this.range_padding;this.setv({start:a,end:o,levels:n},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,o]},{silent:!0})}}e.FactorRange=_,_.__name__=\"FactorRange\",_.init_FactorRange()},\n", " function _(e,t,i,n,s){n();const a=e(53);class l extends a.Model{constructor(e){super(e),this.have_updated_interactively=!1}static init_Range(){this.define((({Number:e,Tuple:t,Or:i,Auto:n,Nullable:s})=>({bounds:[s(i(t(s(e),s(e)),n)),null],min_interval:[s(e),null],max_interval:[s(e),null]}))),this.internal((({Array:e,AnyRef:t})=>({plots:[e(t()),[]]})))}get is_reversed(){return this.start>this.end}get is_valid(){return isFinite(this.min)&&isFinite(this.max)}}i.Range=l,l.__name__=\"Range\",l.init_Range()},\n", " function _(e,t,i,n,l){n();const o=e(1).__importStar(e(107));function a(e,t,{x0:i,x1:n,y0:l,y1:o},a){t.save(),t.beginPath(),t.moveTo(i,(l+o)/2),t.lineTo(n,(l+o)/2),e.line.doit&&(e.line.set_vectorize(t,a),t.stroke()),t.restore()}function r(e,t,{x0:i,x1:n,y0:l,y1:o},a){var r,c;const s=.1*Math.abs(n-i),_=.1*Math.abs(o-l),v=i+s,d=n-s,h=l+_,g=o-_;t.beginPath(),t.rect(v,h,d-v,g-h),e.fill.doit&&(e.fill.set_vectorize(t,a),t.fill()),(null===(r=e.hatch)||void 0===r?void 0:r.doit)&&(e.hatch.set_vectorize(t,a),t.fill()),(null===(c=e.line)||void 0===c?void 0:c.doit)&&(e.line.set_vectorize(t,a),t.stroke())}i.generic_line_scalar_legend=function(e,t,{x0:i,x1:n,y0:l,y1:o}){t.save(),t.beginPath(),t.moveTo(i,(l+o)/2),t.lineTo(n,(l+o)/2),e.line.doit&&(e.line.set_value(t),t.stroke()),t.restore()},i.generic_line_vector_legend=a,i.generic_line_legend=a,i.generic_area_scalar_legend=function(e,t,{x0:i,x1:n,y0:l,y1:o}){var a,r;const c=.1*Math.abs(n-i),s=.1*Math.abs(o-l),_=i+c,v=n-c,d=l+s,h=o-s;t.beginPath(),t.rect(_,d,v-_,h-d),e.fill.doit&&(e.fill.set_value(t),t.fill()),(null===(a=e.hatch)||void 0===a?void 0:a.doit)&&(e.hatch.set_value(t),t.fill()),(null===(r=e.line)||void 0===r?void 0:r.doit)&&(e.line.set_value(t),t.stroke())},i.generic_area_vector_legend=r,i.generic_area_legend=r,i.line_interpolation=function(e,t,i,n,l,a){const{sx:r,sy:c}=t;let s,_,v,d;\"point\"==t.type?([v,d]=e.yscale.r_invert(c-1,c+1),[s,_]=e.xscale.r_invert(r-1,r+1)):\"v\"==t.direction?([v,d]=e.yscale.r_invert(c,c),[s,_]=[Math.min(i-1,l-1),Math.max(i+1,l+1)]):([s,_]=e.xscale.r_invert(r,r),[v,d]=[Math.min(n-1,a-1),Math.max(n+1,a+1)]);const{x:h,y:g}=o.check_2_segments_intersect(s,v,_,d,i,n,l,a);return[h,g]}},\n", " function _(t,n,e,i,r){function s(t,n){return(t.x-n.x)**2+(t.y-n.y)**2}function o(t,n,e){const i=s(n,e);if(0==i)return s(t,n);const r=((t.x-n.x)*(e.x-n.x)+(t.y-n.y)*(e.y-n.y))/i;if(r<0)return s(t,n);if(r>1)return s(t,e);return s(t,{x:n.x+r*(e.x-n.x),y:n.y+r*(e.y-n.y)})}i(),e.point_in_poly=function(t,n,e,i){let r=!1,s=e[e.length-1],o=i[i.length-1];for(let u=0;u0&&_<1&&h>0&&h<1,x:t+_*(e-t),y:n+_*(i-n)}}}},\n", " function _(t,e,s,i,a){i();const o=t(1),n=t(109),_=t(113),r=o.__importDefault(t(114)),h=o.__importDefault(t(115)),l=t(22),g=t(46);class u{constructor(t){this._atlas=new Map,this._width=256,this._height=256,this.tex=new n.Texture2d(t),this.tex.set_wrapping(t.REPEAT,t.REPEAT),this.tex.set_interpolation(t.NEAREST,t.NEAREST),this.tex.set_size([this._width,this._height],t.RGBA),this.tex.set_data([0,0],[this._width,this._height],new Uint8Array(4*this._width*this._height)),this.get_atlas_data([1])}get_atlas_data(t){const e=t.join(\"-\");let s=this._atlas.get(e);if(null==s){const[i,a]=this.make_pattern(t),o=this._atlas.size;this.tex.set_data([0,o],[this._width,1],new Uint8Array(i.map((t=>t+10)))),s=[o/this._height,a],this._atlas.set(e,s)}return s}make_pattern(t){t.length>1&&t.length%2&&(t=t.concat(t));let e=0;for(const s of t)e+=s;const s=[];let i=0;for(let e=0,a=t.length+2;es[h]?-1:0,n=s[h-1],i=s[h]),o[4*t+0]=s[h],o[4*t+1]=_,o[4*t+2]=n,o[4*t+3]=i}return[o,e]}}u.__name__=\"DashAtlas\";const f={miter:0,round:1,bevel:2},c={\"\":0,none:0,\".\":0,round:1,\")\":1,\"(\":1,o:1,\"triangle in\":2,\"<\":2,\"triangle out\":3,\">\":3,square:4,\"[\":4,\"]\":4,\"=\":4,butt:5,\"|\":5};class d extends _.BaseGLGlyph{constructor(t,e){super(t,e),this.glyph=e,this._scale_aspect=0;const s=r.default,i=h.default;this.prog=new n.Program(t),this.prog.set_shaders(s,i),this.index_buffer=new n.IndexBuffer(t),this.vbo_position=new n.VertexBuffer(t),this.vbo_tangents=new n.VertexBuffer(t),this.vbo_segment=new n.VertexBuffer(t),this.vbo_angles=new n.VertexBuffer(t),this.vbo_texcoord=new n.VertexBuffer(t),this.dash_atlas=new u(t)}draw(t,e,s){const i=e.glglyph;if(i.data_changed&&(i._set_data(),i.data_changed=!1),this.visuals_changed&&(this._set_visuals(),this.visuals_changed=!1),i._update_scale(1,1),this._scale_aspect=1,this.prog.set_attribute(\"a_position\",\"vec2\",i.vbo_position),this.prog.set_attribute(\"a_tangents\",\"vec4\",i.vbo_tangents),this.prog.set_attribute(\"a_segment\",\"vec2\",i.vbo_segment),this.prog.set_attribute(\"a_angles\",\"vec2\",i.vbo_angles),this.prog.set_attribute(\"a_texcoord\",\"vec2\",i.vbo_texcoord),this.prog.set_uniform(\"u_length\",\"float\",[i.cumsum]),this.prog.set_texture(\"u_dash_atlas\",this.dash_atlas.tex),this.prog.set_uniform(\"u_pixel_ratio\",\"float\",[s.pixel_ratio]),this.prog.set_uniform(\"u_canvas_size\",\"vec2\",[s.width,s.height]),this.prog.set_uniform(\"u_scale_aspect\",\"vec2\",[1,1]),this.prog.set_uniform(\"u_scale_length\",\"float\",[Math.sqrt(2)]),this.I_triangles=i.I_triangles,this.I_triangles.length<65535)this.index_buffer.set_size(2*this.I_triangles.length),this.index_buffer.set_data(0,new Uint16Array(this.I_triangles)),this.prog.draw(this.gl.TRIANGLES,this.index_buffer);else{t=Array.from(this.I_triangles);const e=this.I_triangles.length,s=64008,a=[];for(let t=0,i=Math.ceil(e/s);t1)for(let e=0;e0||console.log(`Variable ${t} is not an active attribute`));else if(this._unset_variables.has(t)&&this._unset_variables.delete(t),this.activate(),i instanceof r.VertexBuffer){const[r,o]=this.ATYPEINFO[e],l=\"vertexAttribPointer\",_=[r,o,n,s,a];this._attributes.set(t,[i.handle,h,l,_])}else{const s=this.ATYPEMAP[e];this._attributes.set(t,[null,h,s,i])}}_pre_draw(){this.activate();for(const[t,e,i]of this._samplers.values())this.gl.activeTexture(this.gl.TEXTURE0+i),this.gl.bindTexture(t,e);for(const[t,e,i,s]of this._attributes.values())null!=t?(this.gl.bindBuffer(this.gl.ARRAY_BUFFER,t),this.gl.enableVertexAttribArray(e),this.gl[i].apply(this.gl,[e,...s])):(this.gl.bindBuffer(this.gl.ARRAY_BUFFER,null),this.gl.disableVertexAttribArray(e),this.gl[i].apply(this.gl,[e,...s]));this._validated||(this._validated=!0,this._validate())}_validate(){if(this._unset_variables.size&&console.log(`Program has unset variables: ${this._unset_variables}`),this.gl.validateProgram(this.handle),!this.gl.getProgramParameter(this.handle,this.gl.VALIDATE_STATUS))throw console.log(this.gl.getProgramInfoLog(this.handle)),new Error(\"Program validation error\")}draw(t,e){if(!this._linked)throw new Error(\"Cannot draw program if code has not been set\");if(e instanceof r.IndexBuffer){this._pre_draw(),e.activate();const i=e.buffer_size/2,s=this.gl.UNSIGNED_SHORT;this.gl.drawElements(t,i,s,0),e.deactivate()}else{const[i,s]=e;0!=s&&(this._pre_draw(),this.gl.drawArrays(t,i,s))}}}i.Program=n,n.__name__=\"Program\"},\n", " function _(t,e,s,i,a){i();class r{constructor(t){this.gl=t,this._usage=35048,this.buffer_size=0,this.handle=this.gl.createBuffer()}delete(){this.gl.deleteBuffer(this.handle)}activate(){this.gl.bindBuffer(this._target,this.handle)}deactivate(){this.gl.bindBuffer(this._target,null)}set_size(t){t!=this.buffer_size&&(this.activate(),this.gl.bufferData(this._target,t,this._usage),this.buffer_size=t)}set_data(t,e){this.activate(),this.gl.bufferSubData(this._target,t,e)}}s.Buffer=r,r.__name__=\"Buffer\";class f extends r{constructor(){super(...arguments),this._target=34962}}s.VertexBuffer=f,f.__name__=\"VertexBuffer\";class h extends r{constructor(){super(...arguments),this._target=34963}}s.IndexBuffer=h,h.__name__=\"IndexBuffer\"},\n", " function _(t,e,i,a,r){a();const s=t(11);class h{constructor(t){this.gl=t,this._target=3553,this._types={Int8Array:5120,Uint8Array:5121,Int16Array:5122,Uint16Array:5123,Int32Array:5124,Uint32Array:5125,Float32Array:5126},this.handle=this.gl.createTexture()}delete(){this.gl.deleteTexture(this.handle)}activate(){this.gl.bindTexture(this._target,this.handle)}deactivate(){this.gl.bindTexture(this._target,0)}_get_alignment(t){const e=[4,8,2,1];for(const i of e)if(t%i==0)return i;s.unreachable()}set_wrapping(t,e){this.activate(),this.gl.texParameterf(this._target,this.gl.TEXTURE_WRAP_S,t),this.gl.texParameterf(this._target,this.gl.TEXTURE_WRAP_T,e)}set_interpolation(t,e){this.activate(),this.gl.texParameterf(this._target,this.gl.TEXTURE_MIN_FILTER,t),this.gl.texParameterf(this._target,this.gl.TEXTURE_MAG_FILTER,e)}set_size([t,e],i){var a,r,s;t==(null===(a=this._shape_format)||void 0===a?void 0:a.width)&&e==(null===(r=this._shape_format)||void 0===r?void 0:r.height)&&i==(null===(s=this._shape_format)||void 0===s?void 0:s.format)||(this._shape_format={width:t,height:e,format:i},this.activate(),this.gl.texImage2D(this._target,0,i,t,e,0,i,this.gl.UNSIGNED_BYTE,null))}set_data(t,[e,i],a){this.activate();const{format:r}=this._shape_format,[s,h]=t,l=this._types[a.constructor.name];if(null==l)throw new Error(`Type ${a.constructor.name} not allowed for texture`);const _=this._get_alignment(e);4!=_&&this.gl.pixelStorei(this.gl.UNPACK_ALIGNMENT,_),this.gl.texSubImage2D(this._target,0,s,h,e,i,r,l,a),4!=_&&this.gl.pixelStorei(this.gl.UNPACK_ALIGNMENT,4)}}i.Texture2d=h,h.__name__=\"Texture2d\"},\n", " function _(e,t,s,i,h){i();class a{constructor(e,t){this.gl=e,this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,s){if(0==t.length)return!0;const{width:i,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:i,height:h};return this.draw(t,s,a),!0}}s.BaseGLGlyph=a,a.__name__=\"BaseGLGlyph\"},\n", " function _(n,e,t,a,i){a();t.default=\"\\nprecision mediump float;\\n\\nconst float PI = 3.14159265358979323846264;\\nconst float THETA = 15.0 * 3.14159265358979323846264/180.0;\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size, u_offset;\\nuniform vec2 u_scale_aspect;\\nuniform float u_scale_length;\\n\\nuniform vec4 u_color;\\nuniform float u_antialias;\\nuniform float u_length;\\nuniform float u_linewidth;\\nuniform float u_dash_index;\\nuniform float u_closed;\\n\\nattribute vec2 a_position;\\nattribute vec4 a_tangents;\\nattribute vec2 a_segment;\\nattribute vec2 a_angles;\\nattribute vec2 a_texcoord;\\n\\nvarying vec4 v_color;\\nvarying vec2 v_segment;\\nvarying vec2 v_angles;\\nvarying vec2 v_texcoord;\\nvarying vec2 v_miter;\\nvarying float v_length;\\nvarying float v_linewidth;\\n\\nfloat cross(in vec2 v1, in vec2 v2)\\n{\\n return v1.x*v2.y - v1.y*v2.x;\\n}\\n\\nfloat signed_distance(in vec2 v1, in vec2 v2, in vec2 v3)\\n{\\n return cross(v2-v1,v1-v3) / length(v2-v1);\\n}\\n\\nvoid rotate( in vec2 v, in float alpha, out vec2 result )\\n{\\n float c = cos(alpha);\\n float s = sin(alpha);\\n result = vec2( c*v.x - s*v.y,\\n s*v.x + c*v.y );\\n}\\n\\nvoid main()\\n{\\n bool closed = (u_closed > 0.0);\\n\\n // Attributes and uniforms to varyings\\n v_color = u_color;\\n v_linewidth = u_linewidth;\\n v_segment = a_segment * u_scale_length;\\n v_length = u_length * u_scale_length;\\n\\n // Scale to map to pixel coordinates. The original algorithm from the paper\\n // assumed isotropic scale. We obviously do not have this.\\n vec2 abs_scale_aspect = abs(u_scale_aspect);\\n vec2 abs_scale = u_scale_length * abs_scale_aspect;\\n\\n // Correct angles for aspect ratio\\n vec2 av;\\n av = vec2(1.0, tan(a_angles.x)) / abs_scale_aspect;\\n v_angles.x = atan(av.y, av.x);\\n av = vec2(1.0, tan(a_angles.y)) / abs_scale_aspect;\\n v_angles.y = atan(av.y, av.x);\\n\\n // Thickness below 1 pixel are represented using a 1 pixel thickness\\n // and a modified alpha\\n v_color.a = min(v_linewidth, v_color.a);\\n v_linewidth = max(v_linewidth, 1.0);\\n\\n // If color is fully transparent we just will discard the fragment anyway\\n if( v_color.a <= 0.0 ) {\\n gl_Position = vec4(0.0,0.0,0.0,1.0);\\n return;\\n }\\n\\n // This is the actual half width of the line\\n float w = ceil(u_antialias+v_linewidth)/2.0;\\n\\n vec2 position = a_position;\\n\\n vec2 t1 = normalize(a_tangents.xy * abs_scale_aspect); // note the scaling for aspect ratio here\\n vec2 t2 = normalize(a_tangents.zw * abs_scale_aspect);\\n float u = a_texcoord.x;\\n float v = a_texcoord.y;\\n vec2 o1 = vec2( +t1.y, -t1.x);\\n vec2 o2 = vec2( +t2.y, -t2.x);\\n\\n // This is a join\\n // ----------------------------------------------------------------\\n if( t1 != t2 ) {\\n float angle = atan (t1.x*t2.y-t1.y*t2.x, t1.x*t2.x+t1.y*t2.y); // Angle needs recalculation for some reason\\n vec2 t = normalize(t1+t2);\\n vec2 o = vec2( + t.y, - t.x);\\n\\n if ( u_dash_index > 0.0 )\\n {\\n // Broken angle\\n // ----------------------------------------------------------------\\n if( (abs(angle) > THETA) ) {\\n position += v * w * o / cos(angle/2.0);\\n float s = sign(angle);\\n if( angle < 0.0 ) {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n if( v == 1.0 ) {\\n position -= 2.0 * w * t1 / sin(angle);\\n u -= 2.0 * w / sin(angle);\\n }\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n if( v == 1.0 ) {\\n position += 2.0 * w * t2 / sin(angle);\\n u += 2.0*w / sin(angle);\\n }\\n }\\n } else {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n if( v == -1.0 ) {\\n position += 2.0 * w * t1 / sin(angle);\\n u += 2.0 * w / sin(angle);\\n }\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n if( v == -1.0 ) {\\n position -= 2.0 * w * t2 / sin(angle);\\n u -= 2.0*w / sin(angle);\\n }\\n }\\n }\\n // Continuous angle\\n // ------------------------------------------------------------\\n } else {\\n position += v * w * o / cos(angle/2.0);\\n if( u == +1.0 ) u = v_segment.y;\\n else u = v_segment.x;\\n }\\n }\\n\\n // Solid line\\n // --------------------------------------------------------------------\\n else\\n {\\n position.xy += v * w * o / cos(angle/2.0);\\n if( angle < 0.0 ) {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n }\\n } else {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n }\\n }\\n }\\n\\n // This is a line start or end (t1 == t2)\\n // ------------------------------------------------------------------------\\n } else {\\n position += v * w * o1;\\n if( u == -1.0 ) {\\n u = v_segment.x - w;\\n position -= w * t1;\\n } else {\\n u = v_segment.y + w;\\n position += w * t2;\\n }\\n }\\n\\n // Miter distance\\n // ------------------------------------------------------------------------\\n vec2 t;\\n vec2 curr = a_position * abs_scale;\\n if( a_texcoord.x < 0.0 ) {\\n vec2 next = curr + t2*(v_segment.y-v_segment.x);\\n\\n rotate( t1, +v_angles.x/2.0, t);\\n v_miter.x = signed_distance(curr, curr+t, position);\\n\\n rotate( t2, +v_angles.y/2.0, t);\\n v_miter.y = signed_distance(next, next+t, position);\\n } else {\\n vec2 prev = curr - t1*(v_segment.y-v_segment.x);\\n\\n rotate( t1, -v_angles.x/2.0,t);\\n v_miter.x = signed_distance(prev, prev+t, position);\\n\\n rotate( t2, -v_angles.y/2.0,t);\\n v_miter.y = signed_distance(curr, curr+t, position);\\n }\\n\\n if (!closed && v_segment.x <= 0.0) {\\n v_miter.x = 1e10;\\n }\\n if (!closed && v_segment.y >= v_length)\\n {\\n v_miter.y = 1e10;\\n }\\n\\n v_texcoord = vec2( u, v*w );\\n\\n // Calculate position in device coordinates. Note that we\\n // already scaled with abs scale above.\\n vec2 normpos = position * sign(u_scale_aspect);\\n normpos += 0.5; // make up for Bokeh's offset\\n normpos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(normpos*2.0-1.0, 0.0, 1.0);\\n gl_Position.y *= -1.0;\\n}\\n\"},\n", " function _(n,t,e,s,a){s();e.default=\"\\nprecision mediump float;\\n\\nconst float PI = 3.14159265358979323846264;\\nconst float THETA = 15.0 * 3.14159265358979323846264/180.0;\\n\\nuniform sampler2D u_dash_atlas;\\n\\nuniform vec2 u_linecaps;\\nuniform float u_miter_limit;\\nuniform float u_linejoin;\\nuniform float u_antialias;\\nuniform float u_dash_phase;\\nuniform float u_dash_period;\\nuniform float u_dash_index;\\nuniform vec2 u_dash_caps;\\nuniform float u_closed;\\n\\nvarying vec4 v_color;\\nvarying vec2 v_segment;\\nvarying vec2 v_angles;\\nvarying vec2 v_texcoord;\\nvarying vec2 v_miter;\\nvarying float v_length;\\nvarying float v_linewidth;\\n\\n// Compute distance to cap ----------------------------------------------------\\nfloat cap( int type, float dx, float dy, float t, float linewidth )\\n{\\n float d = 0.0;\\n dx = abs(dx);\\n dy = abs(dy);\\n if (type == 0) discard; // None\\n else if (type == 1) d = sqrt(dx*dx+dy*dy); // Round\\n else if (type == 3) d = (dx+abs(dy)); // Triangle in\\n else if (type == 2) d = max(abs(dy),(t+dx-abs(dy))); // Triangle out\\n else if (type == 4) d = max(dx,dy); // Square\\n else if (type == 5) d = max(dx+t,dy); // Butt\\n return d;\\n}\\n\\n// Compute distance to join -------------------------------------------------\\nfloat join( in int type, in float d, in vec2 segment, in vec2 texcoord, in vec2 miter,\\n in float linewidth )\\n{\\n // texcoord.x is distance from start\\n // texcoord.y is distance from centerline\\n // segment.x and y indicate the limits (as for texcoord.x) for this segment\\n\\n float dx = texcoord.x;\\n\\n // Round join\\n if( type == 1 ) {\\n if (dx < segment.x) {\\n d = max(d,length( texcoord - vec2(segment.x,0.0)));\\n //d = length( texcoord - vec2(segment.x,0.0));\\n } else if (dx > segment.y) {\\n d = max(d,length( texcoord - vec2(segment.y,0.0)));\\n //d = length( texcoord - vec2(segment.y,0.0));\\n }\\n }\\n // Bevel join\\n else if ( type == 2 ) {\\n if (dx < segment.x) {\\n vec2 x = texcoord - vec2(segment.x,0.0);\\n d = max(d, max(abs(x.x), abs(x.y)));\\n\\n } else if (dx > segment.y) {\\n vec2 x = texcoord - vec2(segment.y,0.0);\\n d = max(d, max(abs(x.x), abs(x.y)));\\n }\\n /* Original code for bevel which does not work for us\\n if( (dx < segment.x) || (dx > segment.y) )\\n d = max(d, min(abs(x.x),abs(x.y)));\\n */\\n }\\n\\n return d;\\n}\\n\\nvoid main()\\n{\\n // If color is fully transparent we just discard the fragment\\n if( v_color.a <= 0.0 ) {\\n discard;\\n }\\n\\n // Test if dash pattern is the solid one (0)\\n bool solid = (u_dash_index == 0.0);\\n\\n // Test if path is closed\\n bool closed = (u_closed > 0.0);\\n\\n vec4 color = v_color;\\n float dx = v_texcoord.x;\\n float dy = v_texcoord.y;\\n float t = v_linewidth/2.0-u_antialias;\\n float width = 1.0; //v_linewidth; original code had dashes scale with line width, we do not\\n float d = 0.0;\\n\\n vec2 linecaps = u_linecaps;\\n vec2 dash_caps = u_dash_caps;\\n float line_start = 0.0;\\n float line_stop = v_length;\\n\\n // Apply miter limit; fragments too far into the miter are simply discarded\\n if( (dx < v_segment.x) || (dx > v_segment.y) ) {\\n float into_miter = max(v_segment.x - dx, dx - v_segment.y);\\n if (into_miter > u_miter_limit*v_linewidth/2.0)\\n discard;\\n }\\n\\n // Solid line --------------------------------------------------------------\\n if( solid ) {\\n d = abs(dy);\\n if( (!closed) && (dx < line_start) ) {\\n d = cap( int(u_linecaps.x), abs(dx), abs(dy), t, v_linewidth );\\n }\\n else if( (!closed) && (dx > line_stop) ) {\\n d = cap( int(u_linecaps.y), abs(dx)-line_stop, abs(dy), t, v_linewidth );\\n }\\n else {\\n d = join( int(u_linejoin), abs(dy), v_segment, v_texcoord, v_miter, v_linewidth );\\n }\\n\\n // Dash line --------------------------------------------------------------\\n } else {\\n float segment_start = v_segment.x;\\n float segment_stop = v_segment.y;\\n float segment_center= (segment_start+segment_stop)/2.0;\\n float freq = u_dash_period*width;\\n float u = mod( dx + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n float dash_center= tex.x * width;\\n float dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n float dash_start = dx - u + _start;\\n float dash_stop = dx - u + _stop;\\n\\n // Compute extents of the first dash (the one relative to v_segment.x)\\n // Note: this could be computed in the vertex shader\\n if( (dash_stop < segment_start) && (dash_caps.x != 5.0) ) {\\n float u = mod(segment_start + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n dash_center= tex.x * width;\\n //dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n dash_start = segment_start - u + _start;\\n dash_stop = segment_start - u + _stop;\\n }\\n\\n // Compute extents of the last dash (the one relatives to v_segment.y)\\n // Note: This could be computed in the vertex shader\\n else if( (dash_start > segment_stop) && (dash_caps.y != 5.0) ) {\\n float u = mod(segment_stop + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n dash_center= tex.x * width;\\n //dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n dash_start = segment_stop - u + _start;\\n dash_stop = segment_stop - u + _stop;\\n }\\n\\n // This test if the we are dealing with a discontinuous angle\\n bool discontinuous = ((dx < segment_center) && abs(v_angles.x) > THETA) ||\\n ((dx >= segment_center) && abs(v_angles.y) > THETA);\\n //if( dx < line_start) discontinuous = false;\\n //if( dx > line_stop) discontinuous = false;\\n\\n float d_join = join( int(u_linejoin), abs(dy),\\n v_segment, v_texcoord, v_miter, v_linewidth );\\n\\n // When path is closed, we do not have room for linecaps, so we make room\\n // by shortening the total length\\n if (closed) {\\n line_start += v_linewidth/2.0;\\n line_stop -= v_linewidth/2.0;\\n }\\n\\n // We also need to take antialias area into account\\n //line_start += u_antialias;\\n //line_stop -= u_antialias;\\n\\n // Check is dash stop is before line start\\n if( dash_stop <= line_start ) {\\n discard;\\n }\\n // Check is dash start is beyond line stop\\n if( dash_start >= line_stop ) {\\n discard;\\n }\\n\\n // Check if current dash start is beyond segment stop\\n if( discontinuous ) {\\n // Dash start is beyond segment, we discard\\n if( (dash_start > segment_stop) ) {\\n discard;\\n //gl_FragColor = vec4(1.0,0.0,0.0,.25); return;\\n }\\n\\n // Dash stop is before segment, we discard\\n if( (dash_stop < segment_start) ) {\\n discard; //gl_FragColor = vec4(0.0,1.0,0.0,.25); return;\\n }\\n\\n // Special case for round caps (nicer with this)\\n if( dash_caps.x == 1.0 ) {\\n if( (u > _stop) && (dash_stop > segment_stop ) && (abs(v_angles.y) < PI/2.0)) {\\n discard;\\n }\\n }\\n\\n // Special case for round caps (nicer with this)\\n if( dash_caps.y == 1.0 ) {\\n if( (u < _start) && (dash_start < segment_start ) && (abs(v_angles.x) < PI/2.0)) {\\n discard;\\n }\\n }\\n\\n // Special case for triangle caps (in & out) and square\\n // We make sure the cap stop at crossing frontier\\n if( (dash_caps.x != 1.0) && (dash_caps.x != 5.0) ) {\\n if( (dash_start < segment_start ) && (abs(v_angles.x) < PI/2.0) ) {\\n float a = v_angles.x/2.0;\\n float x = (segment_start-dx)*cos(a) - dy*sin(a);\\n float y = (segment_start-dx)*sin(a) + dy*cos(a);\\n if( x > 0.0 ) discard;\\n // We transform the cap into square to avoid holes\\n dash_caps.x = 4.0;\\n }\\n }\\n\\n // Special case for triangle caps (in & out) and square\\n // We make sure the cap stop at crossing frontier\\n if( (dash_caps.y != 1.0) && (dash_caps.y != 5.0) ) {\\n if( (dash_stop > segment_stop ) && (abs(v_angles.y) < PI/2.0) ) {\\n float a = v_angles.y/2.0;\\n float x = (dx-segment_stop)*cos(a) - dy*sin(a);\\n float y = (dx-segment_stop)*sin(a) + dy*cos(a);\\n if( x > 0.0 ) discard;\\n // We transform the caps into square to avoid holes\\n dash_caps.y = 4.0;\\n }\\n }\\n }\\n\\n // Line cap at start\\n if( (dx < line_start) && (dash_start < line_start) && (dash_stop > line_start) ) {\\n d = cap( int(linecaps.x), dx-line_start, dy, t, v_linewidth);\\n }\\n // Line cap at stop\\n else if( (dx > line_stop) && (dash_stop > line_stop) && (dash_start < line_stop) ) {\\n d = cap( int(linecaps.y), dx-line_stop, dy, t, v_linewidth);\\n }\\n // Dash cap left - dash_type = -1, 0 or 1, but there may be roundoff errors\\n else if( dash_type < -0.5 ) {\\n d = cap( int(dash_caps.y), abs(u-dash_center), dy, t, v_linewidth);\\n if( (dx > line_start) && (dx < line_stop) )\\n d = max(d,d_join);\\n }\\n // Dash cap right\\n else if( dash_type > 0.5 ) {\\n d = cap( int(dash_caps.x), abs(dash_center-u), dy, t, v_linewidth);\\n if( (dx > line_start) && (dx < line_stop) )\\n d = max(d,d_join);\\n }\\n // Dash body (plain)\\n else {// if( dash_type > -0.5 && dash_type < 0.5) {\\n d = abs(dy);\\n }\\n\\n // Line join\\n if( (dx > line_start) && (dx < line_stop)) {\\n if( (dx <= segment_start) && (dash_start <= segment_start)\\n && (dash_stop >= segment_start) ) {\\n d = d_join;\\n // Antialias at outer border\\n float angle = PI/2.+v_angles.x;\\n float f = abs( (segment_start - dx)*cos(angle) - dy*sin(angle));\\n d = max(f,d);\\n }\\n else if( (dx > segment_stop) && (dash_start <= segment_stop)\\n && (dash_stop >= segment_stop) ) {\\n d = d_join;\\n // Antialias at outer border\\n float angle = PI/2.+v_angles.y;\\n float f = abs((dx - segment_stop)*cos(angle) - dy*sin(angle));\\n d = max(f,d);\\n }\\n else if( dx < (segment_start - v_linewidth/2.)) {\\n discard;\\n }\\n else if( dx > (segment_stop + v_linewidth/2.)) {\\n discard;\\n }\\n }\\n else if( dx < (segment_start - v_linewidth/2.)) {\\n discard;\\n }\\n else if( dx > (segment_stop + v_linewidth/2.)) {\\n discard;\\n }\\n }\\n\\n // Distance to border ------------------------------------------------------\\n d = d - t;\\n if( d < 0.0 ) {\\n gl_FragColor = color;\\n } else {\\n d /= u_antialias;\\n gl_FragColor = vec4(color.rgb, exp(-d*d)*color.a);\\n }\\n}\\n\"},\n", " function _(i,t,s,e,l){e();const a=i(1),n=i(64),_=i(106),o=a.__importStar(i(107)),h=a.__importStar(i(48)),c=i(59);class r extends n.XYGlyphView{_inner_loop(i,t,s,e,l){for(const a of t){const t=s[a],n=e[a];0!=a?isNaN(t+n)?(i.closePath(),l.apply(i),i.beginPath()):i.lineTo(t,n):(i.beginPath(),i.moveTo(t,n))}i.closePath(),l.call(i)}_render(i,t,s){const{sx:e,sy:l}=null!=s?s:this;this.visuals.fill.doit&&(this.visuals.fill.set_value(i),this._inner_loop(i,t,e,l,i.fill)),this.visuals.hatch.doit&&(this.visuals.hatch.set_value(i),this._inner_loop(i,t,e,l,i.fill)),this.visuals.line.doit&&(this.visuals.line.set_value(i),this._inner_loop(i,t,e,l,i.stroke))}draw_legend_for_index(i,t,s){_.generic_area_scalar_legend(this.visuals,i,t)}_hit_point(i){const t=new c.Selection;return o.point_in_poly(i.sx,i.sy,this.sx,this.sy)&&(t.add_to_selected_glyphs(this.model),t.view=this),t}}s.PatchView=r,r.__name__=\"PatchView\";class p extends n.XYGlyph{constructor(i){super(i)}static init_Patch(){this.prototype.default_view=r,this.mixins([h.LineScalar,h.FillScalar,h.HatchScalar])}}s.Patch=p,p.__name__=\"Patch\",p.init_Patch()},\n", " function _(t,e,s,i,n){i();const a=t(1),r=t(24),h=t(118),_=a.__importStar(t(107)),l=a.__importStar(t(18)),o=t(59);class c extends h.AreaView{_index_data(t){const{min:e,max:s}=Math,{data_size:i}=this;for(let n=0;n=0;e--)t.lineTo(s[e],i[e]);t.closePath(),n.call(t)}_render(t,e,s){const{sx1:i,sx2:n,sy:a}=null!=s?s:this;this.visuals.fill.doit&&(this.visuals.fill.set_value(t),this._inner(t,i,n,a,t.fill)),this.visuals.hatch.doit&&(this.visuals.hatch.set_value(t),this._inner(t,i,n,a,t.fill))}_hit_point(t){const e=this.sy.length,s=new r.ScreenArray(2*e),i=new r.ScreenArray(2*e);for(let t=0,n=e;t({x1:[l.XCoordinateSpec,{field:\"x1\"}],x2:[l.XCoordinateSpec,{field:\"x2\"}],y:[l.YCoordinateSpec,{field:\"y\"}]})))}}s.HArea=d,d.__name__=\"HArea\",d.init_HArea()},\n", " function _(e,a,_,i,r){i();const s=e(1),n=e(98),t=e(106),c=s.__importStar(e(48));class l extends n.GlyphView{draw_legend_for_index(e,a,_){t.generic_area_scalar_legend(this.visuals,e,a)}}_.AreaView=l,l.__name__=\"AreaView\";class d extends n.Glyph{constructor(e){super(e)}static init_Area(){this.mixins([c.FillScalar,c.HatchScalar])}}_.Area=d,d.__name__=\"Area\",d.init_Area()},\n", " function _(t,e,s,i,n){i();const a=t(1),r=t(24),h=t(118),_=a.__importStar(t(107)),l=a.__importStar(t(18)),o=t(59);class c extends h.AreaView{_index_data(t){const{min:e,max:s}=Math,{data_size:i}=this;for(let n=0;n=0;s--)t.lineTo(e[s],i[s]);t.closePath(),n.call(t)}_render(t,e,s){const{sx:i,sy1:n,sy2:a}=null!=s?s:this;this.visuals.fill.doit&&(this.visuals.fill.set_value(t),this._inner(t,i,n,a,t.fill)),this.visuals.hatch.doit&&(this.visuals.hatch.set_value(t),this._inner(t,i,n,a,t.fill))}scenterxy(t){return[this.sx[t],(this.sy1[t]+this.sy2[t])/2]}_hit_point(t){const e=this.sx.length,s=new r.ScreenArray(2*e),i=new r.ScreenArray(2*e);for(let t=0,n=e;t({x:[l.XCoordinateSpec,{field:\"x\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],y2:[l.YCoordinateSpec,{field:\"y2\"}]})))}}s.VArea=d,d.__name__=\"VArea\",d.init_VArea()},\n", " function _(i,e,s,t,n){t();const c=i(53),o=i(59),r=i(24),a=i(121),u=i(57);class _ extends c.Model{constructor(i){super(i)}static init_CDSView(){this.define((({Array:i,Ref:e})=>({filters:[i(e(a.Filter)),[]],source:[e(u.ColumnarDataSource)]}))),this.internal((({Int:i,Dict:e,Ref:s,Nullable:t})=>({indices:[s(r.Indices)],indices_map:[e(i),{}],masked:[t(s(r.Indices)),null]})))}initialize(){super.initialize(),this.compute_indices()}connect_signals(){super.connect_signals(),this.connect(this.properties.filters.change,(()=>this.compute_indices()));const i=()=>{const i=()=>this.compute_indices();null!=this.source&&(this.connect(this.source.change,i),this.source instanceof u.ColumnarDataSource&&(this.connect(this.source.streaming,i),this.connect(this.source.patching,i)))};let e=null!=this.source;e?i():this.connect(this.properties.source.change,(()=>{e||(i(),e=!0)}))}compute_indices(){var i;const{source:e}=this;if(null==e)return;const s=null!==(i=e.get_length())&&void 0!==i?i:1,t=r.Indices.all_set(s);for(const i of this.filters)t.intersect(i.compute_indices(e));this.indices=t,this._indices=[...t],this.indices_map_to_subset()}indices_map_to_subset(){this.indices_map={};for(let i=0;ithis._indices[i]));return new o.Selection(Object.assign(Object.assign({},i.attributes),{indices:e}))}convert_selection_to_subset(i){const e=i.indices.map((i=>this.indices_map[i]));return new o.Selection(Object.assign(Object.assign({},i.attributes),{indices:e}))}convert_indices_from_subset(i){return i.map((i=>this._indices[i]))}}s.CDSView=_,_.__name__=\"CDSView\",_.init_CDSView()},\n", " function _(e,t,n,s,c){s();const o=e(53);class r extends o.Model{constructor(e){super(e)}}n.Filter=r,r.__name__=\"Filter\"},\n", " function _(n,e,t,i,o){i();const s=n(9);async function c(n,e,t){const i=new n(Object.assign(Object.assign({},t),{model:e}));return i.initialize(),await i.lazy_initialize(),i}t.build_view=async function(n,e={parent:null},t=(n=>n.default_view)){const i=await c(t(n),n,e);return i.connect_signals(),i},t.build_views=async function(n,e,t={parent:null},i=(n=>n.default_view)){const o=s.difference([...n.keys()],e);for(const e of o)n.get(e).remove(),n.delete(e);const a=[],f=e.filter((e=>!n.has(e)));for(const e of f){const o=await c(i(e),e,t);n.set(e,o),a.push(o)}for(const n of a)n.connect_signals();return a},t.remove_views=function(n){for(const[e,t]of n)t.remove(),n.delete(e)}},\n", " function _(e,r,n,t,i){t();const s=e(62),o=e(61),l=e(124),d=e(125),a=e(126),p=e(122),_=e(64),h=e(127),c=e(128),u=e(11);class y extends s.DataRendererView{get glyph_view(){return this.node_view.glyph}async lazy_initialize(){await super.lazy_initialize();const e=this.model;let r=null,n=null;const t=new class extends l.Expression{_v_compute(n){u.assert(null==r);const[t]=r=e.layout_provider.get_edge_coordinates(n);return t}},i=new class extends l.Expression{_v_compute(e){u.assert(null!=r);const[,n]=r;return r=null,n}},s=new class extends l.Expression{_v_compute(r){u.assert(null==n);const[t]=n=e.layout_provider.get_node_coordinates(r);return t}},o=new class extends l.Expression{_v_compute(e){u.assert(null!=n);const[,r]=n;return n=null,r}},{edge_renderer:d,node_renderer:a}=this.model;if(!(d.glyph instanceof h.MultiLine||d.glyph instanceof c.Patches))throw new Error(`${this}.edge_renderer.glyph must be a MultiLine glyph`);if(!(a.glyph instanceof _.XYGlyph))throw new Error(`${this}.node_renderer.glyph must be a XYGlyph glyph`);d.glyph.properties.xs.internal=!0,d.glyph.properties.ys.internal=!0,a.glyph.properties.x.internal=!0,a.glyph.properties.y.internal=!0,d.glyph.xs={expr:t},d.glyph.ys={expr:i},a.glyph.x={expr:s},a.glyph.y={expr:o};const{parent:y}=this;this.edge_view=await p.build_view(d,{parent:y}),this.node_view=await p.build_view(a,{parent:y})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,(()=>{this.edge_view.set_data(),this.node_view.set_data(),this.request_render()}))}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}renderer_view(e){if(e instanceof o.GlyphRenderer){if(e==this.edge_view.model)return this.edge_view;if(e==this.node_view.model)return this.node_view}return super.renderer_view(e)}}n.GraphRendererView=y,y.__name__=\"GraphRendererView\";class g extends s.DataRenderer{constructor(e){super(e)}static init_GraphRenderer(){this.prototype.default_view=y,this.define((({Ref:e})=>({layout_provider:[e(d.LayoutProvider)],node_renderer:[e(o.GlyphRenderer)],edge_renderer:[e(o.GlyphRenderer)],selection_policy:[e(a.GraphHitTestPolicy),()=>new a.NodesOnly],inspection_policy:[e(a.GraphHitTestPolicy),()=>new a.NodesOnly]})))}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}n.GraphRenderer=g,g.__name__=\"GraphRenderer\",g.init_GraphRenderer()},\n", " function _(e,t,s,n,i){n();const c=e(53);class l extends c.Model{constructor(e){super(e)}initialize(){super.initialize(),this._connected=new Set,this._result=new Map}v_compute(e){this._connected.has(e)||(this.connect(e.change,(()=>this._result.delete(e))),this.connect(e.patching,(()=>this._result.delete(e))),this.connect(e.streaming,(()=>this._result.delete(e))),this._connected.add(e));let t=this._result.get(e);return null==t&&(t=this._v_compute(e),this._result.set(e,t)),t}}s.Expression=l,l.__name__=\"Expression\";class h extends c.Model{constructor(e){super(e)}initialize(){super.initialize(),this._connected=new Set,this._result=new Map}compute(e){this._connected.has(e)||(this.connect(e.change,(()=>this._result.delete(e))),this.connect(e.patching,(()=>this._result.delete(e))),this.connect(e.streaming,(()=>this._result.delete(e))),this._connected.add(e));let t=this._result.get(e);return null==t&&(t=this._compute(e),this._result.set(e,t)),t}}s.ScalarExpression=h,h.__name__=\"ScalarExpression\"},\n", " function _(o,e,r,t,n){t();const s=o(53);class c extends s.Model{constructor(o){super(o)}}r.LayoutProvider=c,c.__name__=\"LayoutProvider\"},\n", " function _(e,t,d,n,s){n();const o=e(53),r=e(12),_=e(9),i=e(59);class c extends o.Model{constructor(e){super(e)}_hit_test(e,t,d){if(!t.model.visible)return null;const n=d.glyph.hit_test(e);return null==n?null:d.model.view.convert_selection_from_subset(n)}}d.GraphHitTestPolicy=c,c.__name__=\"GraphHitTestPolicy\";class a extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.edge_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;return s.update(e,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{edge_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.edge_view.model);return r.update(e,n,s),d.edge_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!r.is_empty()}}d.EdgesOnly=a,a.__name__=\"EdgesOnly\";class l extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,d,n),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{node_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.node_view.model);return r.update(e,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.node_view.model.data_source.inspect.emit([d.node_view.model,{geometry:t}]),!r.is_empty()}}d.NodesOnly=l,l.__name__=\"NodesOnly\";class u extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}get_linked_edges(e,t,d){let n=[];\"selection\"==d?n=e.selected.indices.map((t=>e.data.index[t])):\"inspection\"==d&&(n=e.inspected.indices.map((t=>e.data.index[t])));const s=[];for(let e=0;er.indexOf(e.data.index,t)));return new i.Selection({indices:o})}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,d,n);const o=t.node_renderer.data_source.selected,r=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(r,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const o=d.edge_view.model.data_source.selection_manager.get_or_create_inspector(d.edge_view.model);o.update(e,n,s),d.edge_view.model.data_source.setv({inspected:o},{silent:!0});const r=d.node_view.model.data_source.selection_manager.get_or_create_inspector(d.node_view.model),_=this.get_linked_nodes(d.node_view.model.data_source,d.edge_view.model.data_source,\"inspection\");return r.update(_,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!o.is_empty()}}d.EdgesAndLinkedNodes=m,m.__name__=\"EdgesAndLinkedNodes\"},\n", " function _(t,e,i,n,s){n();const o=t(1),l=t(65),r=t(48),_=o.__importStar(t(107)),c=o.__importStar(t(18)),h=t(12),a=t(13),d=t(98),x=t(106),y=t(59);class g extends d.GlyphView{_project_data(){l.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(t){const{data_size:e}=this;for(let i=0;i0&&o.set(t,i)}return new y.Selection({indices:[...o.keys()],multiline_indices:a.to_object(o)})}get_interpolation_hit(t,e,i){const n=this._xs.get(t),s=this._ys.get(t),o=n[e],l=s[e],r=n[e+1],_=s[e+1];return x.line_interpolation(this.renderer,i,o,l,r,_)}draw_legend_for_index(t,e,i){x.generic_line_vector_legend(this.visuals,t,e,i)}scenterxy(){throw new Error(`${this}.scenterxy() is not implemented`)}}i.MultiLineView=g,g.__name__=\"MultiLineView\";class u extends d.Glyph{constructor(t){super(t)}static init_MultiLine(){this.prototype.default_view=g,this.define((({})=>({xs:[c.XCoordinateSeqSpec,{field:\"xs\"}],ys:[c.YCoordinateSeqSpec,{field:\"ys\"}]}))),this.mixins(r.LineVector)}}i.MultiLine=u,u.__name__=\"MultiLine\",u.init_MultiLine()},\n", " function _(e,t,s,i,n){i();const r=e(1),o=e(98),a=e(106),_=e(12),c=e(48),l=r.__importStar(e(107)),h=r.__importStar(e(18)),d=e(59),y=e(11),p=e(65);class x extends o.GlyphView{_project_data(){p.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s({xs:[h.XCoordinateSeqSpec,{field:\"xs\"}],ys:[h.YCoordinateSeqSpec,{field:\"ys\"}]}))),this.mixins([c.LineVector,c.FillVector,c.HatchVector])}}s.Patches=f,f.__name__=\"Patches\",f.init_Patches()},\n", " function _(e,t,n,s,o){s();const r=e(53);class c extends r.Model{do_selection(e,t,n,s){return null!=e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=c,c.__name__=\"SelectionPolicy\";class l extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=l,l.__name__=\"IntersectRenderers\";class _ extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=_,_.__name__=\"UnionRenderers\"},\n", " function _(t,n,e,s,o){s();const r=t(1),i=t(57),l=t(8),c=t(13),a=r.__importStar(t(131)),u=t(132),h=t(35);function d(t,n,e){if(l.isArray(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if(l.isTypedArray(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let i;t.length({data:[t(n),{}]})))}stream(t,n,e){const{data:s}=this;for(const[e,o]of c.entries(t))s[e]=d(s[e],o,n);if(this.setv({data:s},{silent:!0}),this.streaming.emit(),null!=this.document){const s=new h.ColumnsStreamedEvent(this.document,this.ref(),t,n);this.document._notify_change(this,\"data\",null,null,{setter_id:e,hint:s})}}patch(t,n){const{data:e}=this;let s=new Set;for(const[n,o]of c.entries(t))s=u.union(s,m(e[n],o));if(this.setv({data:e},{silent:!0}),this.patching.emit([...s]),null!=this.document){const e=new h.ColumnsPatchedEvent(this.document,this.ref(),t);this.document._notify_change(this,\"data\",null,null,{setter_id:n,hint:e})}}}e.ColumnDataSource=_,_.__name__=\"ColumnDataSource\",_.init_ColumnDataSource()},\n", " function _(t,n,o,e,c){e(),o.concat=function(t,...n){let o=t.length;for(const t of n)o+=t.length;const e=new t.constructor(o);e.set(t,0);let c=t.length;for(const t of n)e.set(t,c),c+=t.length;return e}},\n", " function _(n,o,t,e,f){function c(...n){const o=new Set;for(const t of n)for(const n of t)o.add(n);return o}e(),t.union=c,t.intersection=function(n,...o){const t=new Set;n:for(const e of n){for(const n of o)if(!n.has(e))continue n;t.add(e)}return t},t.difference=function(n,...o){const t=new Set(n);for(const n of c(...o))t.delete(n);return t}},\n", " function _(e,i,t,s,o){s();const n=e(1),a=e(53),l=e(42),r=n.__importStar(e(45)),_=e(48),c=n.__importStar(e(18));class d extends l.View{initialize(){super.initialize(),this.visuals=new r.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.parent.canvas}set_data(e){const i=this;for(const t of this.model){if(!(t instanceof c.VectorSpec||t instanceof c.ScalarSpec))continue;const s=t.uniform(e);i[`${t.attr}`]=s}}}t.ArrowHeadView=d,d.__name__=\"ArrowHeadView\";class h extends a.Model{constructor(e){super(e)}static init_ArrowHead(){this.define((()=>({size:[c.NumberSpec,25]})))}}t.ArrowHead=h,h.__name__=\"ArrowHead\",h.init_ArrowHead();class v extends d{clip(e,i){this.visuals.line.set_vectorize(e,i);const t=this.size.get(i);e.moveTo(.5*t,t),e.lineTo(.5*t,-2),e.lineTo(-.5*t,-2),e.lineTo(-.5*t,t),e.lineTo(0,0),e.lineTo(.5*t,t)}render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const t=this.size.get(i);e.beginPath(),e.moveTo(.5*t,t),e.lineTo(0,0),e.lineTo(-.5*t,t),e.stroke()}}}t.OpenHeadView=v,v.__name__=\"OpenHeadView\";class u extends h{constructor(e){super(e)}static init_OpenHead(){this.prototype.default_view=v,this.mixins(_.LineVector)}}t.OpenHead=u,u.__name__=\"OpenHead\",u.init_OpenHead();class m extends d{clip(e,i){this.visuals.line.set_vectorize(e,i);const t=this.size.get(i);e.moveTo(.5*t,t),e.lineTo(.5*t,-2),e.lineTo(-.5*t,-2),e.lineTo(-.5*t,t),e.lineTo(.5*t,t)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._normal(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._normal(e,i),e.stroke())}_normal(e,i){const t=this.size.get(i);e.beginPath(),e.moveTo(.5*t,t),e.lineTo(0,0),e.lineTo(-.5*t,t),e.closePath()}}t.NormalHeadView=m,m.__name__=\"NormalHeadView\";class T extends h{constructor(e){super(e)}static init_NormalHead(){this.prototype.default_view=m,this.mixins([_.LineVector,_.FillVector]),this.override({fill_color:\"black\"})}}t.NormalHead=T,T.__name__=\"NormalHead\",T.init_NormalHead();class p extends d{clip(e,i){this.visuals.line.set_vectorize(e,i);const t=this.size.get(i);e.moveTo(.5*t,t),e.lineTo(.5*t,-2),e.lineTo(-.5*t,-2),e.lineTo(-.5*t,t),e.lineTo(0,.5*t),e.lineTo(.5*t,t)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._vee(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._vee(e,i),e.stroke())}_vee(e,i){const t=this.size.get(i);e.beginPath(),e.moveTo(.5*t,t),e.lineTo(0,0),e.lineTo(-.5*t,t),e.lineTo(0,.5*t),e.closePath()}}t.VeeHeadView=p,p.__name__=\"VeeHeadView\";class H extends h{constructor(e){super(e)}static init_VeeHead(){this.prototype.default_view=p,this.mixins([_.LineVector,_.FillVector]),this.override({fill_color:\"black\"})}}t.VeeHead=H,H.__name__=\"VeeHead\",H.init_VeeHead();class V extends d{render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const t=this.size.get(i);e.beginPath(),e.moveTo(.5*t,0),e.lineTo(-.5*t,0),e.stroke()}}clip(e,i){}}t.TeeHeadView=V,V.__name__=\"TeeHeadView\";class f extends h{constructor(e){super(e)}static init_TeeHead(){this.prototype.default_view=V,this.mixins(_.LineVector)}}t.TeeHead=f,f.__name__=\"TeeHead\",f.init_TeeHead()},\n", " function _(s,e,i,t,l){t();const _=s(1),o=s(135),r=_.__importStar(s(48));class h extends o.UpperLowerView{paint(s){s.beginPath(),s.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let e=0,i=this._lower_sx.length;e=0;e--)s.lineTo(this._upper_sx[e],this._upper_sy[e]);s.closePath(),this.visuals.fill.doit&&(this.visuals.fill.set_value(s),s.fill()),s.beginPath(),s.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let e=0,i=this._lower_sx.length;e({dimension:[n.Dimension,\"height\"],lower:[h,{field:\"lower\"}],upper:[h,{field:\"upper\"}],base:[h,{field:\"base\"}]})))}}i.UpperLower=d,d.__name__=\"UpperLower\",d.init_UpperLower()},\n", " function _(t,i,o,n,e){n();const s=t(1),l=t(40),a=s.__importStar(t(48)),r=t(20),h=t(99);o.EDGE_TOLERANCE=2.5;class c extends l.AnnotationView{constructor(){super(...arguments),this.bbox=new h.BBox}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{left:t,right:i,top:o,bottom:n}=this.model;if(null==t&&null==i&&null==o&&null==n)return;const{frame:e}=this.plot_view,s=this.coordinates.x_scale,l=this.coordinates.y_scale,a=(t,i,o,n,e)=>{let s;return s=null!=t?this.model.screen?t:\"data\"==i?o.compute(t):n.compute(t):e,s};this.bbox=h.BBox.from_rect({left:a(t,this.model.left_units,s,e.bbox.xview,e.bbox.left),right:a(i,this.model.right_units,s,e.bbox.xview,e.bbox.right),top:a(o,this.model.top_units,l,e.bbox.yview,e.bbox.top),bottom:a(n,this.model.bottom_units,l,e.bbox.yview,e.bbox.bottom)}),this._paint_box()}_paint_box(){const{ctx:t}=this.layer;t.save();const{left:i,top:o,width:n,height:e}=this.bbox;t.beginPath(),t.rect(i,o,n,e),this.visuals.fill.doit&&(this.visuals.fill.set_value(t),t.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_value(t),t.fill()),this.visuals.line.doit&&(this.visuals.line.set_value(t),t.stroke()),t.restore()}interactive_bbox(){const t=this.model.line_width+o.EDGE_TOLERANCE;return this.bbox.grow_by(t)}interactive_hit(t,i){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,i)}cursor(t,i){const{left:o,right:n,bottom:e,top:s}=this.bbox;return Math.abs(t-o)<3||Math.abs(t-n)<3?this.model.ew_cursor:Math.abs(i-e)<3||Math.abs(i-s)<3?this.model.ns_cursor:this.bbox.contains(t,i)?this.model.in_cursor:null}}o.BoxAnnotationView=c,c.__name__=\"BoxAnnotationView\";class u extends l.Annotation{constructor(t){super(t)}static init_BoxAnnotation(){this.prototype.default_view=c,this.mixins([a.Line,a.Fill,a.Hatch]),this.define((({Number:t,Nullable:i})=>({top:[i(t),null],top_units:[r.SpatialUnits,\"data\"],bottom:[i(t),null],bottom_units:[r.SpatialUnits,\"data\"],left:[i(t),null],left_units:[r.SpatialUnits,\"data\"],right:[i(t),null],right_units:[r.SpatialUnits,\"data\"],render_mode:[r.RenderMode,\"canvas\"]}))),this.internal((({Boolean:t,String:i,Nullable:o})=>({screen:[t,!1],ew_cursor:[o(i),null],ns_cursor:[o(i),null],in_cursor:[o(i),null]}))),this.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})}update({left:t,right:i,top:o,bottom:n}){this.setv({left:t,right:i,top:o,bottom:n,screen:!0})}}o.BoxAnnotation=u,u.__name__=\"BoxAnnotation\",u.init_BoxAnnotation()},\n", " function _(t,e,i,o,n){o();const a=t(1),r=t(40),s=t(138),l=t(144),_=t(162),c=t(165),h=t(198),u=t(166),p=t(205),m=t(169),g=t(203),d=t(202),f=t(209),w=t(217),b=t(220),v=t(20),x=a.__importStar(t(48)),y=t(9),k=t(221),C=t(222),z=t(225),j=t(140),B=t(11),L=t(122),S=t(99),M=t(8);class T extends r.AnnotationView{get orientation(){return this._orientation}initialize(){super.initialize();const{ticker:t,formatter:e,color_mapper:i}=this.model;this._ticker=\"auto\"!=t?t:(()=>{switch(!0){case i instanceof f.LogColorMapper:return new h.LogTicker;case i instanceof f.ScanningColorMapper:return new h.BinnedTicker({mapper:i});case i instanceof f.CategoricalColorMapper:return new h.CategoricalTicker;default:return new h.BasicTicker}})(),this._formatter=\"auto\"!=e?e:(()=>{switch(!0){case this._ticker instanceof h.LogTicker:return new p.LogTickFormatter;case i instanceof f.CategoricalColorMapper:return new p.CategoricalTickFormatter;default:return new p.BasicTickFormatter}})(),this._major_range=(()=>{if(i instanceof f.CategoricalColorMapper){const{factors:t}=i;return new b.FactorRange({factors:t})}if(i instanceof d.ContinuousColorMapper){const{min:t,max:e}=i.metrics;return new b.Range1d({start:t,end:e})}B.unreachable()})(),this._major_scale=(()=>{if(i instanceof f.LinearColorMapper)return new w.LinearScale;if(i instanceof f.LogColorMapper)return new w.LogScale;if(i instanceof f.ScanningColorMapper){const{binning:t}=i.metrics;return new w.LinearInterpolationScale({binning:t})}if(i instanceof f.CategoricalColorMapper)return new w.CategoricalScale;B.unreachable()})(),this._minor_range=new b.Range1d({start:0,end:1}),this._minor_scale=new w.LinearScale;const o=x.attrs_of(this.model,\"major_label_\",x.Text,!0),n=x.attrs_of(this.model,\"major_tick_\",x.Line,!0),a=x.attrs_of(this.model,\"minor_tick_\",x.Line,!0),r=x.attrs_of(this.model,\"title_\",x.Text),l=i instanceof f.CategoricalColorMapper?_.CategoricalAxis:i instanceof f.LogColorMapper?_.LogAxis:_.LinearAxis;this._axis=new l(Object.assign(Object.assign(Object.assign({ticker:this._ticker,formatter:this._formatter,major_tick_in:this.model.major_tick_in,major_tick_out:this.model.major_tick_out,minor_tick_in:this.model.minor_tick_in,minor_tick_out:this.model.minor_tick_out,major_label_standoff:this.model.label_standoff,major_label_overrides:this.model.major_label_overrides,major_label_policy:this.model.major_label_policy,axis_line_color:null},o),n),a));const{title:c}=this.model;c&&(this._title=new s.Title(Object.assign({text:c,standoff:this.model.title_standoff},r)))}async lazy_initialize(){await super.lazy_initialize();const t=this,e={get parent(){return t.parent},get root(){return t.root},get frame(){return t._frame},get canvas_view(){return t.parent.canvas_view},request_layout(){t.parent.request_layout()}};this._axis_view=await L.build_view(this._axis,{parent:e}),null!=this._title&&(this._title_view=await L.build_view(this._title,{parent:e}))}remove(){var t;null===(t=this._title_view)||void 0===t||t.remove(),this._axis_view.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this._ticker.change,(()=>this.request_render())),this.connect(this._formatter.change,(()=>this.request_render())),this.connect(this.model.color_mapper.metrics_change,(()=>{const t=this._major_range,e=this._major_scale,{color_mapper:i}=this.model;if(i instanceof d.ContinuousColorMapper&&t instanceof b.Range1d){const{min:e,max:o}=i.metrics;t.setv({start:e,end:o})}if(i instanceof f.ScanningColorMapper&&e instanceof w.LinearInterpolationScale){const{binning:t}=i.metrics;e.binning=t}this._set_canvas_image(),this.plot_view.request_layout()}))}_set_canvas_image(){const{orientation:t}=this,e=(()=>{const{palette:e}=this.model.color_mapper;return\"vertical\"==t?y.reversed(e):e})(),[i,o]=\"vertical\"==t?[1,e.length]:[e.length,1],n=this._image=document.createElement(\"canvas\");n.width=i,n.height=o;const a=n.getContext(\"2d\"),r=a.getImageData(0,0,i,o),s=new f.LinearColorMapper({palette:e}).rgba_mapper.v_compute(y.range(0,e.length));r.data.set(s),a.putImageData(r,0,0)}update_layout(){const{location:t,width:e,height:i,padding:o,margin:n}=this.model,[a,r]=(()=>{if(!M.isString(t))return[\"end\",\"start\"];switch(t){case\"top_left\":return[\"start\",\"start\"];case\"top\":case\"top_center\":return[\"start\",\"center\"];case\"top_right\":return[\"start\",\"end\"];case\"bottom_left\":return[\"end\",\"start\"];case\"bottom\":case\"bottom_center\":return[\"end\",\"center\"];case\"bottom_right\":return[\"end\",\"end\"];case\"left\":case\"center_left\":return[\"center\",\"start\"];case\"center\":case\"center_center\":return[\"center\",\"center\"];case\"right\":case\"center_right\":return[\"center\",\"end\"]}})(),s=this._orientation=(()=>{const{orientation:t}=this.model;return\"auto\"==t?null!=this.panel?this.panel.is_horizontal?\"horizontal\":\"vertical\":\"start\"==r||\"end\"==r||\"center\"==r&&\"center\"==a?\"vertical\":\"horizontal\":t})(),_=new C.NodeLayout,c=new C.VStack,h=new C.VStack,u=new C.HStack,p=new C.HStack;_.absolute=!0,c.absolute=!0,h.absolute=!0,u.absolute=!0,p.absolute=!0;const[m,g,d,f]=(()=>\"horizontal\"==s?[this._major_scale,this._minor_scale,this._major_range,this._minor_range]:[this._minor_scale,this._major_scale,this._minor_range,this._major_range])();this._frame=new l.CartesianFrame(m,g,d,f),_.on_resize((t=>this._frame.set_geometry(t)));const w=new z.BorderLayout;this._inner_layout=w,w.absolute=!0,w.center_panel=_,w.top_panel=c,w.bottom_panel=h,w.left_panel=u,w.right_panel=p;const b={left:o,right:o,top:o,bottom:o},v=(()=>{if(null==this.panel){if(M.isString(t))return{left:n,right:n,top:n,bottom:n};{const[e,i]=t;return{left:e,right:n,top:n,bottom:i}}}if(!M.isString(t)){const[e,i]=t;return w.fixup_geometry=(t,o)=>{const n=t,a=this.layout.bbox,{width:r,height:s}=t;if(t=new S.BBox({left:a.left+e,bottom:a.bottom-i,width:r,height:s}),null!=o){const e=t.left-n.left,i=t.top-n.top,{left:a,top:r,width:s,height:l}=o;o=new S.BBox({left:a+e,top:r+i,width:s,height:l})}return[t,o]},{left:e,right:0,top:0,bottom:i}}w.fixup_geometry=(t,e)=>{const i=t;if(\"horizontal\"==s){const{top:e,width:i,height:o}=t;if(\"end\"==r){const{right:n}=this.layout.bbox;t=new S.BBox({right:n,top:e,width:i,height:o})}else if(\"center\"==r){const{hcenter:n}=this.layout.bbox;t=new S.BBox({hcenter:Math.round(n),top:e,width:i,height:o})}}else{const{left:e,width:i,height:o}=t;if(\"end\"==a){const{bottom:n}=this.layout.bbox;t=new S.BBox({left:e,bottom:n,width:i,height:o})}else if(\"center\"==a){const{vcenter:n}=this.layout.bbox;t=new S.BBox({left:e,vcenter:Math.round(n),width:i,height:o})}}if(null!=e){const o=t.left-i.left,n=t.top-i.top,{left:a,top:r,width:s,height:l}=e;e=new S.BBox({left:a+o,top:r+n,width:s,height:l})}return[t,e]}})();let x,y,B,L;if(w.padding=b,null!=this.panel?(x=\"max\",y=void 0,B=void 0,L=void 0):\"auto\"==(\"horizontal\"==s?e:i)?(x=\"fixed\",y=25*this.model.color_mapper.palette.length,B={percent:.3},L={percent:.8}):(x=\"fit\",y=void 0),\"horizontal\"==s){const t=\"auto\"==e?void 0:e,o=\"auto\"==i?25:i;w.set_sizing({width_policy:x,height_policy:\"min\",width:y,min_width:B,max_width:L,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"auto\"==e?\"fit\":\"fixed\",height_policy:\"fixed\",width:t,height:o})}else{const t=\"auto\"==e?25:e,o=\"auto\"==i?void 0:i;w.set_sizing({width_policy:\"min\",height_policy:x,height:y,min_height:B,max_height:L,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"fixed\",height_policy:\"auto\"==i?\"fit\":\"fixed\",width:t,height:o})}c.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),h.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),u.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),p.set_sizing({width_policy:\"min\",height_policy:\"fit\"});const{_title_view:T}=this;null!=T&&(\"horizontal\"==s?(T.panel=new j.Panel(\"above\"),T.update_layout(),c.children.push(T.layout)):(T.panel=new j.Panel(\"left\"),T.update_layout(),u.children.push(T.layout)));const{panel:A}=this,O=null!=A&&s==A.orientation?A.side:\"horizontal\"==s?\"below\":\"right\",R=(()=>{switch(O){case\"above\":return c;case\"below\":return h;case\"left\":return u;case\"right\":return p}})(),{_axis_view:F}=this;if(F.panel=new j.Panel(O),F.update_layout(),R.children.push(F.layout),null!=this.panel){const t=new k.Grid([{layout:w,row:0,col:0}]);t.absolute=!0,\"horizontal\"==s?t.set_sizing({width_policy:\"max\",height_policy:\"min\"}):t.set_sizing({width_policy:\"min\",height_policy:\"max\"}),this.layout=t}else this.layout=this._inner_layout;const{visible:I}=this.model;this.layout.sizing.visible=I,this._set_canvas_image()}_render(){var t;const{ctx:e}=this.layer;e.save(),this._paint_bbox(e,this._inner_layout.bbox),this._paint_image(e,this._inner_layout.center_panel.bbox),null===(t=this._title_view)||void 0===t||t.render(),this._axis_view.render(),e.restore()}_paint_bbox(t,e){const{x:i,y:o}=e;let{width:n,height:a}=e;i+n>=this.parent.canvas_view.bbox.width&&(n-=1),o+a>=this.parent.canvas_view.bbox.height&&(a-=1),t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(i,o,n,a)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}_paint_image(t,e){const{x:i,y:o,width:n,height:a}=e;t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this._image,i,o,n,a),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}serializable_state(){const t=super.serializable_state(),{children:e=[]}=t,i=a.__rest(t,[\"children\"]);return null!=this._title_view&&e.push(this._title_view.serializable_state()),e.push(this._axis_view.serializable_state()),Object.assign(Object.assign({},i),{children:e})}}i.ColorBarView=T,T.__name__=\"ColorBarView\";class A extends r.Annotation{constructor(t){super(t)}static init_ColorBar(){this.prototype.default_view=T,this.mixins([[\"major_label_\",x.Text],[\"title_\",x.Text],[\"major_tick_\",x.Line],[\"minor_tick_\",x.Line],[\"border_\",x.Line],[\"bar_\",x.Line],[\"background_\",x.Fill]]),this.define((({Alpha:t,Number:e,String:i,Tuple:o,Dict:n,Or:a,Ref:r,Auto:s,Nullable:l})=>({location:[a(v.Anchor,o(e,e)),\"top_right\"],orientation:[a(v.Orientation,s),\"auto\"],title:[l(i),null],title_standoff:[e,2],width:[a(e,s),\"auto\"],height:[a(e,s),\"auto\"],scale_alpha:[t,1],ticker:[a(r(c.Ticker),s),\"auto\"],formatter:[a(r(u.TickFormatter),s),\"auto\"],major_label_overrides:[n(i),{}],major_label_policy:[r(m.LabelingPolicy),()=>new m.NoOverlap],color_mapper:[r(g.ColorMapper)],label_standoff:[e,5],margin:[e,30],padding:[e,10],major_tick_in:[e,5],major_tick_out:[e,0],minor_tick_in:[e,0],minor_tick_out:[e,0]}))),this.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})}}i.ColorBar=A,A.__name__=\"ColorBar\",A.init_ColorBar()},\n", " function _(t,e,i,s,l){s();const o=t(1),a=t(139),n=t(20),r=t(143),c=o.__importStar(t(48));class h extends a.TextAnnotationView{_get_location(){const t=this.model.offset,e=this.model.standoff/2;let i,s;const{bbox:l}=this.layout;switch(this.panel.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":s=l.top+e;break;case\"middle\":s=l.vcenter;break;case\"bottom\":s=l.bottom-e}switch(this.model.align){case\"left\":i=l.left+t;break;case\"center\":i=l.hcenter;break;case\"right\":i=l.right-t}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=l.left+e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.right-e}switch(this.model.align){case\"left\":s=l.bottom-t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.top+t}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=l.right-e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.left+e}switch(this.model.align){case\"left\":s=l.top+t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.bottom-t}}return[i,s]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),s=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,s)}_get_size(){const{text:t}=this.model;if(null==t||0==t.length)return{width:0,height:0};{const{ctx:e}=this.layer;this.visuals.text.set_value(e);const{width:i}=this.layer.ctx.measureText(t),{height:s}=r.font_metrics(e.font);return{width:i,height:2+s*this.model.text_line_height+this.model.standoff}}}}i.TitleView=h,h.__name__=\"TitleView\";class _ extends a.TextAnnotation{constructor(t){super(t)}static init_Title(){this.prototype.default_view=h,this.mixins([c.Text,[\"border_\",c.Line],[\"background_\",c.Fill]]),this.define((({Number:t,String:e})=>({text:[e,\"\"],vertical_align:[n.VerticalAlign,\"bottom\"],align:[n.TextAlign,\"left\"],offset:[t,0],standoff:[t,10]}))),this.prototype._props.text_align.options.internal=!0,this.prototype._props.text_baseline.options.internal=!0,this.override({text_font_size:\"13px\",text_font_style:\"bold\",text_line_height:1,background_fill_color:null,border_line_color:null})}}i.Title=_,_.__name__=\"Title\",_.init_Title()},\n", " function _(e,t,s,i,n){i();const l=e(40),a=e(43),o=e(20),r=e(140),d=e(143),c=e(11);class _ extends l.AnnotationView{update_layout(){const{panel:e}=this;this.layout=null!=e?new r.SideLayout(e,(()=>this.get_size()),!0):void 0}initialize(){super.initialize(),\"css\"==this.model.render_mode&&(this.el=a.div(),this.plot_view.canvas_view.add_overlay(this.el))}remove(){null!=this.el&&a.remove(this.el),super.remove()}connect_signals(){super.connect_signals(),\"css\"==this.model.render_mode?this.connect(this.model.change,(()=>this.render())):this.connect(this.model.change,(()=>this.request_render()))}render(){this.model.visible||\"css\"!=this.model.render_mode||a.undisplay(this.el),super.render()}_calculate_text_dimensions(e,t){const{width:s}=e.measureText(t),{height:i}=d.font_metrics(this.visuals.text.font_value());return[s,i]}_calculate_bounding_box_dimensions(e,t){const[s,i]=this._calculate_text_dimensions(e,t);let n,l;switch(e.textAlign){case\"left\":n=0;break;case\"center\":n=-s/2;break;case\"right\":n=-s;break;default:c.unreachable()}switch(e.textBaseline){case\"top\":l=0;break;case\"middle\":l=-.5*i;break;case\"bottom\":l=-1*i;break;case\"alphabetic\":l=-.8*i;break;case\"hanging\":l=-.17*i;break;case\"ideographic\":l=-.83*i;break;default:c.unreachable()}return[n,l,s,i]}_canvas_text(e,t,s,i,n){this.visuals.text.set_value(e);const l=this._calculate_bounding_box_dimensions(e,t);e.save(),e.beginPath(),e.translate(s,i),n&&e.rotate(n),e.rect(l[0],l[1],l[2],l[3]),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fill()),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),e.stroke()),this.visuals.text.doit&&(this.visuals.text.set_value(e),e.fillText(t,0,0)),e.restore()}_css_text(e,t,s,i,n){const{el:l}=this;c.assert(null!=l),a.undisplay(l),this.visuals.text.set_value(e);const[o,r]=this._calculate_bounding_box_dimensions(e,t);l.style.position=\"absolute\",l.style.left=`${s+o}px`,l.style.top=`${i+r}px`,l.style.color=e.fillStyle,l.style.font=e.font,l.style.lineHeight=\"normal\",n&&(l.style.transform=`rotate(${n}rad)`),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),l.style.backgroundColor=e.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),l.style.borderStyle=e.lineDash.length<2?\"solid\":\"dashed\",l.style.borderWidth=`${e.lineWidth}px`,l.style.borderColor=e.strokeStyle),l.textContent=t,a.display(l)}}s.TextAnnotationView=_,_.__name__=\"TextAnnotationView\";class u extends l.Annotation{constructor(e){super(e)}static init_TextAnnotation(){this.define((()=>({render_mode:[o.RenderMode,\"canvas\"]})))}}s.TextAnnotation=u,u.__name__=\"TextAnnotation\",u.init_TextAnnotation()},\n", " function _(t,e,i,l,r){l();const a=t(141),o=t(142),n=t(8),h=Math.PI/2,s={above:{parallel:0,normal:-h,horizontal:0,vertical:-h},below:{parallel:0,normal:h,horizontal:0,vertical:h},left:{parallel:-h,normal:0,horizontal:0,vertical:-h},right:{parallel:h,normal:0,horizontal:0,vertical:h}},c={above:{parallel:\"bottom\",normal:\"center\",horizontal:\"bottom\",vertical:\"center\"},below:{parallel:\"top\",normal:\"center\",horizontal:\"top\",vertical:\"center\"},left:{parallel:\"bottom\",normal:\"center\",horizontal:\"center\",vertical:\"bottom\"},right:{parallel:\"bottom\",normal:\"center\",horizontal:\"center\",vertical:\"bottom\"}},g={above:{parallel:\"center\",normal:\"left\",horizontal:\"center\",vertical:\"left\"},below:{parallel:\"center\",normal:\"left\",horizontal:\"center\",vertical:\"left\"},left:{parallel:\"center\",normal:\"right\",horizontal:\"right\",vertical:\"center\"},right:{parallel:\"center\",normal:\"left\",horizontal:\"left\",vertical:\"center\"}},_={above:\"right\",below:\"left\",left:\"right\",right:\"left\"},b={above:\"left\",below:\"right\",left:\"right\",right:\"left\"};class z{constructor(t){this.side=t}get dimension(){return\"above\"==this.side||\"below\"==this.side?0:1}get normals(){switch(this.side){case\"above\":return[0,-1];case\"below\":return[0,1];case\"left\":return[-1,0];case\"right\":return[1,0]}}get orientation(){return this.is_horizontal?\"horizontal\":\"vertical\"}get is_horizontal(){return 0==this.dimension}get is_vertical(){return 1==this.dimension}get_label_text_heuristics(t){const{side:e}=this;return n.isString(t)?{vertical_align:c[e][t],align:g[e][t]}:{vertical_align:\"center\",align:(t<0?_:b)[e]}}get_label_angle_heuristic(t){return n.isString(t)?s[this.side][t]:-t}}i.Panel=z,z.__name__=\"Panel\";class m extends o.ContentLayoutable{constructor(t,e,i=!1){super(),this.panel=t,this.get_size=e,this.rotate=i,this.panel.is_horizontal?this.set_sizing({width_policy:\"max\",height_policy:\"fixed\"}):this.set_sizing({width_policy:\"fixed\",height_policy:\"max\"})}_content_size(){const{width:t,height:e}=this.get_size();return!this.rotate||this.panel.is_horizontal?new a.Sizeable({width:t,height:e}):new a.Sizeable({width:e,height:t})}has_size_changed(){const{width:t,height:e}=this._content_size();return this.panel.is_horizontal?this.bbox.height!=e:this.bbox.width!=t}}i.SideLayout=m,m.__name__=\"SideLayout\"},\n", " function _(h,t,i,e,w){e();const n=h(21),{min:d,max:s}=Math;class g{constructor(h={}){this.width=null!=h.width?h.width:0,this.height=null!=h.height?h.height:0}bounded_to({width:h,height:t}){return new g({width:this.width==1/0&&null!=h?h:this.width,height:this.height==1/0&&null!=t?t:this.height})}expanded_to({width:h,height:t}){return new g({width:h!=1/0?s(this.width,h):this.width,height:t!=1/0?s(this.height,t):this.height})}expand_to({width:h,height:t}){this.width=s(this.width,h),this.height=s(this.height,t)}narrowed_to({width:h,height:t}){return new g({width:d(this.width,h),height:d(this.height,t)})}narrow_to({width:h,height:t}){this.width=d(this.width,h),this.height=d(this.height,t)}grow_by({left:h,right:t,top:i,bottom:e}){const w=this.width+h+t,n=this.height+i+e;return new g({width:w,height:n})}shrink_by({left:h,right:t,top:i,bottom:e}){const w=s(this.width-h-t,0),n=s(this.height-i-e,0);return new g({width:w,height:n})}map(h,t){return new g({width:h(this.width),height:(null!=t?t:h)(this.height)})}}i.Sizeable=g,g.__name__=\"Sizeable\",i.SizingPolicy=n.Enum(\"fixed\",\"fit\",\"min\",\"max\")},\n", " function _(i,t,h,e,n){e();const s=i(141),r=i(99),g=i(8),{min:l,max:a,round:_}=Math;class o{constructor(){this.absolute=!1,this._bbox=new r.BBox,this._inner_bbox=new r.BBox,this._dirty=!1,this._handlers=[]}*[Symbol.iterator](){}get bbox(){return this._bbox}get inner_bbox(){return this._inner_bbox}get sizing(){return this._sizing}set visible(i){this._sizing.visible=i,this._dirty=!0}set_sizing(i){var t,h,e,n,s;const r=null!==(t=i.width_policy)&&void 0!==t?t:\"fit\",g=i.width,l=i.min_width,a=i.max_width,_=null!==(h=i.height_policy)&&void 0!==h?h:\"fit\",o=i.height,d=i.min_height,u=i.max_height,c=i.aspect,w=null!==(e=i.margin)&&void 0!==e?e:{top:0,right:0,bottom:0,left:0},m=!1!==i.visible,x=null!==(n=i.halign)&&void 0!==n?n:\"start\",b=null!==(s=i.valign)&&void 0!==s?s:\"start\";this._sizing={width_policy:r,min_width:l,width:g,max_width:a,height_policy:_,min_height:d,height:o,max_height:u,aspect:c,margin:w,visible:m,halign:x,valign:b,size:{width:g,height:o}},this._init()}_init(){}_set_geometry(i,t){this._bbox=i,this._inner_bbox=t}set_geometry(i,t){const{fixup_geometry:h}=this;null!=h&&([i,t]=h(i,t)),this._set_geometry(i,null!=t?t:i);for(const i of this._handlers)i(this._bbox,this._inner_bbox)}on_resize(i){this._handlers.push(i)}is_width_expanding(){return\"max\"==this.sizing.width_policy}is_height_expanding(){return\"max\"==this.sizing.height_policy}apply_aspect(i,{width:t,height:h}){const{aspect:e}=this.sizing;if(null!=e){const{width_policy:n,height_policy:s}=this.sizing,r=(i,t)=>{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=n&&\"fixed\"!=s)if(n==s){const n=t,s=_(t/e),r=_(h*e),g=h;Math.abs(i.width-n)+Math.abs(i.height-s)<=Math.abs(i.width-r)+Math.abs(i.height-g)?(t=n,h=s):(t=r,h=g)}else r(n,s)?h=_(t/e):t=_(h*e);else\"fixed\"==n?h=_(t/e):\"fixed\"==s&&(t=_(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,e=new s.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(e),r=this.clip_size(n,e),g=t(r.width),l=h(r.height),a=this.apply_aspect(e,{width:g,height:l});return Object.assign(Object.assign({},n),a)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new r.BBox({left:0,top:0,width:h,height:e});let s;if(null!=t.inner){const{left:i,top:n,right:g,bottom:l}=t.inner;s=new r.BBox({left:i,top:n,right:h-g,bottom:e-l})}this.set_geometry(n,s)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_size(i,t){function h(i,t,h,e){return null==h?h=0:g.isNumber(h)||(h=Math.round(h.percent*t)),null==e?e=1/0:g.isNumber(e)||(e=Math.round(e.percent*t)),a(h,l(i,e))}return{width:h(i.width,t.width,this.sizing.min_width,this.sizing.max_width),height:h(i.height,t.height,this.sizing.min_height,this.sizing.max_height)}}has_size_changed(){const{_dirty:i}=this;return this._dirty=!1,i}}h.Layoutable=o,o.__name__=\"Layoutable\";class d extends o{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;return{width:(()=>{const{width:h}=this.sizing;if(i.width==1/0)return null!=h?h:0;switch(t){case\"fixed\":return null!=h?h:0;case\"min\":return null!=h?l(i.width,h):0;case\"fit\":return null!=h?l(i.width,h):i.width;case\"max\":return null!=h?a(i.width,h):i.width}})(),height:(()=>{const{height:t}=this.sizing;if(i.height==1/0)return null!=t?t:0;switch(h){case\"fixed\":return null!=t?t:0;case\"min\":return null!=t?l(i.height,t):0;case\"fit\":return null!=t?l(i.height,t):i.height;case\"max\":return null!=t?a(i.height,t):i.height}})()}}}h.LayoutItem=d,d.__name__=\"LayoutItem\";class u extends o{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=u,u.__name__=\"ContentLayoutable\"},\n", " function _(t,e,n,r,l){r();const a=t(11),c=(()=>{try{return\"undefined\"!=typeof OffscreenCanvas&&null!=new OffscreenCanvas(0,0).getContext(\"2d\")}catch(t){return!1}})()?(t,e)=>new OffscreenCanvas(t,e):(t,e)=>{const n=document.createElement(\"canvas\");return n.width=t,n.height=e,n},o=(()=>{const t=c(0,0).getContext(\"2d\");return e=>{t.font=e;const n=t.measureText(\"M\"),r=t.measureText(\"x\"),l=t.measureText(\"ÅŚg|\"),c=l.fontBoundingBoxAscent,o=l.fontBoundingBoxDescent;if(null!=c&&null!=o)return{height:c+o,ascent:c,descent:o,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};const s=l.actualBoundingBoxAscent,u=l.actualBoundingBoxDescent;if(null!=s&&null!=u)return{height:s+u,ascent:s,descent:u,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};a.unreachable()}})(),s=(()=>{const t=c(0,0).getContext(\"2d\");return(e,n)=>{t.font=n;const r=t.measureText(e),l=r.actualBoundingBoxAscent,c=r.actualBoundingBoxDescent;if(null!=l&&null!=c)return{width:r.width,height:l+c,ascent:l,descent:c};a.unreachable()}})(),u=(()=>{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a=1)=>{e.font=l;const{width:c}=e.measureText(\"M\"),o=c*a,s=Math.ceil(o),u=Math.ceil(2*o),i=Math.ceil(1.5*o);n{let e=0;for(let n=0;n<=i;n++)for(let r=0;r{let e=t.length-4;for(let n=u;n>=i;n--)for(let r=0;r{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a,c=1)=>{e.font=a;const{width:o}=e.measureText(\"M\"),s=o*c,u=Math.ceil(s),i=Math.ceil(2*s),f=Math.ceil(1.5*s);(n{let e=0;for(let n=0;n<=f;n++)for(let r=0;r{let e=t.length-4;for(let n=i;n>=f;n--)for(let r=0;r{try{return o(\"normal 10px sans-serif\"),o}catch(t){return u}})(),h=(()=>{try{return s(\"A\",\"normal 10px sans-serif\"),s}catch(t){return i}})(),g=new Map;function d(t){let e=g.get(t);return null==e&&(e={font:f(t),glyphs:new Map},g.set(t,e)),e.font}n.font_metrics=d,n.glyph_metrics=function(t,e){let n=g.get(e);null==n&&(d(e),n=g.get(e));let r=n.glyphs.get(t);return null==r&&(r=h(t,e),n.glyphs.set(t,r)),r},n.parse_css_font_size=function(t){const e=t.match(/^\\s*(\\d+(\\.\\d+)?)(\\w+)\\s*$/);if(null!=e){const[,t,,n]=e,r=Number(t);if(isFinite(r))return{value:r,unit:n}}return null}},\n", " function _(e,t,s,_,a){_();const r=e(145),n=e(157),g=e(156),i=e(159),c=e(104),h=e(99),o=e(13),l=e(11);class x{constructor(e,t,s,_,a={},r={}){this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=_,this.extra_x_ranges=a,this.extra_y_ranges=r,this._bbox=new h.BBox,l.assert(null==e.source_range&&null==e.target_range),l.assert(null==t.source_range&&null==t.target_range),this._configure_scales()}get bbox(){return this._bbox}_get_ranges(e,t){return new Map(o.entries(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s){const _=new Map;for(const[a,g]of t){if(g instanceof c.FactorRange!=e instanceof r.CategoricalScale)throw new Error(`Range ${g.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&g instanceof i.DataRange1d&&(g.scale_hint=\"log\");const t=e.clone();t.setv({source_range:g,target_range:s}),_.set(a,t)}return _}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new g.Range1d({start:e.left,end:e.right}),this._y_target=new g.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}set_geometry(e){this._bbox=e,this._update_scales()}get x_target(){return this._x_target}get y_target(){return this._y_target}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return o.to_object(this.x_scales)}get yscales(){return o.to_object(this.y_scales)}}s.CartesianFrame=x,x.__name__=\"CartesianFrame\"},\n", " function _(e,t,r,n,_){n();const c=e(146);class s extends c.Scale{constructor(e){super(e)}get s_compute(){const[e,t]=this._linear_compute_state(),r=this.source_range;return n=>e*r.synthetic(n)+t}compute(e){return super._linear_compute(this.source_range.synthetic(e))}v_compute(e){return super._linear_v_compute(this.source_range.v_synthetic(e))}invert(e){return this._linear_invert(e)}v_invert(e){return this._linear_v_invert(e)}}r.CategoricalScale=s,s.__name__=\"CategoricalScale\"},\n", " function _(t,e,r,n,s){n();const i=t(147),_=t(105),a=t(156),c=t(24);class o extends i.Transform{constructor(t){super(t)}static init_Scale(){this.internal((({Ref:t})=>({source_range:[t(_.Range)],target_range:[t(a.Range1d)]})))}r_compute(t,e){return this.target_range.is_reversed?[this.compute(e),this.compute(t)]:[this.compute(t),this.compute(e)]}r_invert(t,e){return this.target_range.is_reversed?[this.invert(e),this.invert(t)]:[this.invert(t),this.invert(e)]}_linear_compute(t){const[e,r]=this._linear_compute_state();return e*t+r}_linear_v_compute(t){const[e,r]=this._linear_compute_state(),n=new c.ScreenArray(t.length);for(let s=0;s({args:[s(t),{}],func:[r,\"\"],v_func:[r,\"\"]})))}get names(){return o.keys(this.args)}get values(){return o.values(this.args)}_make_transform(t,r){return new Function(...this.names,t,u.use_strict(r))}get scalar_transform(){return this._make_transform(\"x\",this.func)}get vector_transform(){return this._make_transform(\"xs\",this.v_func)}compute(t){return this.scalar_transform(...this.values,t)}v_compute(t){return this.vector_transform(...this.values,t)}}s.CustomJSTransform=m,m.__name__=\"CustomJSTransform\",m.init_CustomJSTransform()},\n", " function _(n,s,o,r,c){r();const e=n(53);class t extends e.Model{constructor(n){super(n)}}o.Transform=t,t.__name__=\"Transform\"},\n", " function _(e,t,n,o,s){o();const i=e(151);class r extends i.RangeTransform{constructor(e){super(e)}static init_Dodge(){this.define((({Number:e})=>({value:[e,0]})))}_compute(e){return e+this.value}}n.Dodge=r,r.__name__=\"Dodge\",r.init_Dodge()},\n", " function _(e,n,t,r,s){r();const a=e(149),i=e(105),o=e(104),c=e(24),f=e(8);class u extends a.Transform{constructor(e){super(e)}static init_RangeTransform(){this.define((({Ref:e,Nullable:n})=>({range:[n(e(i.Range)),null]})))}v_compute(e){let n;if(this.range instanceof o.FactorRange)n=this.range.v_synthetic(e);else{if(!f.isArrayableOf(e,f.isNumber))throw new Error(\"unexpected\");n=e}const t=new(c.infer_type(n))(n.length);for(let e=0;e({x:[s(r,o(e))],y:[s(r,o(e))],data:[a(n(i.ColumnarDataSource)),null],clip:[t,!0]})))}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._sorted_dirty=!0))}v_compute(t){const e=new(a.infer_type(t))(t.length);for(let r=0;rs*(e[t]-e[r]))),this._x_sorted=new(a.infer_type(e))(n),this._y_sorted=new(a.infer_type(r))(n);for(let t=0;t({mean:[t,0],width:[t,1],distribution:[o.Distribution,\"uniform\"]})))}v_compute(t){return null!=this.previous_values&&this.previous_values.length==t.length||(this.previous_values=super.v_compute(t)),this.previous_values}_compute(t){switch(this.distribution){case\"uniform\":return t+this.mean+(a.random()-.5)*this.width;case\"normal\":return t+a.rnorm(this.mean,this.width)}}}e.Jitter=h,h.__name__=\"Jitter\",h.init_Jitter()},\n", " function _(t,s,_,r,e){r();const i=t(9),o=t(152);class n extends o.Interpolator{constructor(t){super(t)}compute(t){if(this.sort(!1),this.clip){if(tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}if(t==this._x_sorted[0])return this._y_sorted[0];const s=i.find_last_index(this._x_sorted,(s=>s({mode:[_.StepMode,\"after\"]})))}compute(t){if(this.sort(!1),this.clip){if(tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}let e;switch(this.mode){case\"after\":e=n.find_last_index(this._x_sorted,(e=>t>=e));break;case\"before\":e=n.find_index(this._x_sorted,(e=>t<=e));break;case\"center\":{const s=n.map(this._x_sorted,(e=>Math.abs(e-t))),r=n.min(s);e=n.find_index(s,(t=>r===t));break}default:throw new Error(`unknown mode: ${this.mode}`)}return-1!=e?this._y_sorted[e]:NaN}}s.StepInterpolator=d,d.__name__=\"StepInterpolator\",d.init_StepInterpolator()},\n", " function _(t,e,s,n,i){n();const a=t(105);class r extends a.Range{constructor(t){super(t)}static init_Range1d(){this.define((({Number:t,Nullable:e})=>({start:[t,0],end:[t,1],reset_start:[e(t),null,{on_update(t,e){e._reset_start=null!=t?t:e.start}}],reset_end:[e(t),null,{on_update(t,e){e._reset_end=null!=t?t:e.end}}]})))}_set_auto_bounds(){if(\"auto\"==this.bounds){const t=Math.min(this._reset_start,this._reset_end),e=Math.max(this._reset_start,this._reset_end);this.setv({bounds:[t,e]},{silent:!0})}}initialize(){super.initialize(),this._set_auto_bounds()}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}reset(){this._set_auto_bounds();const{_reset_start:t,_reset_end:e}=this;this.start!=t||this.end!=e?this.setv({start:t,end:e}):this.change.emit()}map(t){return new r({start:t(this.start),end:t(this.end)})}widen(t){let{start:e,end:s}=this;return this.is_reversed?(e+=t,s-=t):(e-=t,s+=t),new r({start:e,end:s})}}s.Range1d=r,r.__name__=\"Range1d\",r.init_Range1d()},\n", " function _(t,e,o,n,s){n();const a=t(158),r=t(24);class c extends a.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e,o,n]=this._compute_state();return s=>{if(0==o)return 0;{const a=(Math.log(s)-n)/o;return isFinite(a)?a*t+e:NaN}}}compute(t){const[e,o,n,s]=this._compute_state();let a;if(0==n)a=0;else{const r=(Math.log(t)-s)/n;a=isFinite(r)?r*e+o:NaN}return a}v_compute(t){const[e,o,n,s]=this._compute_state(),a=new r.ScreenArray(t.length);if(0==n)for(let e=0;e({start:[i],end:[i],range_padding:[i,.1],range_padding_units:[_.PaddingUnits,\"percent\"],flipped:[t,!1],follow:[n(_.StartEnd),null],follow_interval:[n(i),null],default_span:[i,2],only_visible:[t,!1]}))),this.internal((({Enum:t})=>({scale_hint:[t(\"log\",\"auto\"),\"auto\"]})))}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const{renderers:t,names:i}=this,n=o.concat(this.plots.map((t=>t.data_renderers)));return d.compute_renderers(0==t.length?\"auto\":t,n,i)}_compute_plot_bounds(t,i){let n=r.empty();for(const a of t){const t=i.get(a);null==t||!a.visible&&this.only_visible||(n=r.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=r.empty();let a=t.x1-t.x0;a<=0&&(a=1);let e=t.y1-t.y0;e<=0&&(e=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return al&&(\"start\"==this.follow?e=a+s*l:\"end\"==this.follow&&(a=e-s*l)),[a,e]}update(t,i,n,a){if(this.have_updated_interactively)return;const e=this.computed_renderers();let s=this._compute_plot_bounds(e,t);null!=a&&(s=this.adjust_bounds_for_aspect(s,a)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.values(),i);let[o,h]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(h=this._initial_end):h=this._initial_end);let r=!1;\"auto\"==this.bounds&&(this.setv({bounds:[o,h]},{silent:!0}),r=!0);const[d,u]=[this.start,this.end];if(o!=d||h!=u){const t={};o!=d&&(t.start=o),h!=u&&(t.end=h),this.setv(t),r=!1}r&&this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=u,u.__name__=\"DataRange1d\",u.init_DataRange1d()},\n", " function _(a,e,n,t,r){t();const s=a(105),i=a(62);class R extends s.Range{constructor(a){super(a)}static init_DataRange(){this.define((({String:a,Array:e,Ref:n})=>({names:[e(a),[]],renderers:[e(n(i.DataRenderer)),[]]})))}}n.DataRange=R,R.__name__=\"DataRange\",R.init_DataRange()},\n", " function _(n,e,t,r,u){r();const l=n(9);t.compute_renderers=function(n,e,t){if(null==n)return[];let r=\"auto\"==n?e:n;return t.length>0&&(r=r.filter((n=>l.includes(t,n.name)))),r}},\n", " function _(i,s,x,A,o){A(),o(\"Axis\",i(163).Axis),o(\"CategoricalAxis\",i(170).CategoricalAxis),o(\"ContinuousAxis\",i(173).ContinuousAxis),o(\"DatetimeAxis\",i(174).DatetimeAxis),o(\"LinearAxis\",i(175).LinearAxis),o(\"LogAxis\",i(192).LogAxis),o(\"MercatorAxis\",i(195).MercatorAxis)},\n", " function _(t,e,i,s,o){s();const n=t(1),a=t(164),l=t(165),r=t(166),_=t(169),h=n.__importStar(t(48)),c=t(20),b=t(24),m=t(140),d=t(9),u=t(8),x=t(167),g=t(104),{abs:f}=Math;class p extends a.GuideRendererView{update_layout(){this.layout=new m.SideLayout(this.panel,(()=>this.get_size()),!0),this.layout.on_resize((()=>this._coordinates=void 0))}get_size(){const{visible:t,fixed_location:e}=this.model;if(t&&null==e&&this.is_renderable){const{extents:t}=this;return{width:0,height:Math.round(t.tick+t.tick_label+t.axis_label)}}return{width:0,height:0}}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const{tick_coords:e,extents:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,i),this._draw_major_ticks(s,i,e),this._draw_minor_ticks(s,i,e),this._draw_major_labels(s,i,e),this._draw_axis_label(s,i,e),null===(t=this._paint)||void 0===t||t.call(this,s,i,e),s.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_layout()))}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[o,n]=this.coordinates.map_to_screen(i,s),[a,l]=this.normals,[r,_]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath();for(let e=0;e0?o+s+3:0}_draw_axis_label(t,e,i){const s=this.model.axis_label;if(!s||null!=this.model.fixed_location)return;const o=new x.TextBox({text:s});o.visuals=this.visuals.axis_label_text,o.angle=this.panel.get_label_angle_heuristic(\"parallel\"),o.base_font_size=this.plot_view.base_font_size;const[n,a]=(()=>{const{bbox:t}=this.layout;switch(this.panel.side){case\"above\":return[t.hcenter,t.bottom];case\"below\":return[t.hcenter,t.top];case\"left\":return[t.right,t.vcenter];case\"right\":return[t.left,t.vcenter]}})(),[l,r]=this.normals,_=e.tick+e.tick_label+this.model.axis_label_standoff,{vertical_align:h,align:c}=this.panel.get_label_text_heuristics(\"parallel\");o.position={sx:n+l*_,sy:a+r*_,x_anchor:c,y_anchor:h},o.align=c,o.paint(t)}_draw_ticks(t,e,i,s,o){if(!o.doit)return;const[n,a]=e,[l,r]=this.coordinates.map_to_screen(n,a),[_,h]=this.normals,[c,b]=this.offsets,[m,d]=[_*(c-i),h*(b-i)],[u,x]=[_*(c+s),h*(b+s)];o.set_value(t),t.beginPath();for(let e=0;et.bbox())),T=(()=>{const[t]=this.ranges;return t.is_reversed?0==this.dimension?(t,e)=>z[t].left-z[e].right:(t,e)=>z[e].top-z[t].bottom:0==this.dimension?(t,e)=>z[e].left-z[t].right:(t,e)=>z[t].top-z[e].bottom})(),{major_label_policy:O}=this.model,A=O.filter(v,z,T),M=[...A.ones()];if(0!=M.length){const t=this.parent.canvas_view.bbox,e=e=>{const i=z[e];if(i.left<0){const t=-i.left,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sx:s.sx+t})}else if(i.right>t.width){const s=i.right-t.width,{position:o}=y[e];y[e].position=Object.assign(Object.assign({},o),{sx:o.sx-s})}},i=e=>{const i=z[e];if(i.top<0){const t=-i.top,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sy:s.sy+t})}else if(i.bottom>t.height){const s=i.bottom-t.height,{position:o}=y[e];y[e].position=Object.assign(Object.assign({},o),{sy:o.sy-s})}},s=M[0],o=M[M.length-1];0==this.dimension?(e(s),e(o)):(i(s),i(o))}for(const e of A){y[e].paint(t)}}_tick_extent(){return this.model.major_tick_out}_tick_label_extents(){const t=this.tick_coords.major,e=this.compute_labels(t[this.dimension]),i=this.model.major_label_orientation,s=this.model.major_label_standoff,o=this.visuals.major_label_text;return[this._oriented_labels_extent(e,i,s,o)]}get extents(){const t=this._tick_label_extents();return{tick:this._tick_extent(),tick_labels:t,tick_label:d.sum(t),axis_label:this._axis_label_extent()}}_oriented_labels_extent(t,e,i,s){if(0==t.length)return 0;const o=this.panel.get_label_angle_heuristic(e);t.visuals=s,t.angle=o,t.base_font_size=this.plot_view.base_font_size;const n=t.max_size(),a=0==this.dimension?n.height:n.width;return a>0?i+a+3:0}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.format_graphics(t,this),{major_label_overrides:i}=this.model;for(let s=0;sf(a-l)?(t=_(r(o,n),a),s=r(_(o,n),l)):(t=r(o,n),s=_(o,n)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,o]=this.computed_bounds,n=[new Array(2),new Array(2)];return n[t][0]=Math.max(s,i.min),n[t][1]=Math.min(o,i.max),n[t][0]>n[t][1]&&(n[t][0]=n[t][1]=NaN),n[e][0]=this.loc,n[e][1]=this.loc,n}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,o]=this.computed_bounds,n=this.model.ticker.get_ticks(s,o,i,this.loc),a=n.major,l=n.minor,r=[[],[]],_=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(r[t].push(a[i]),r[e].push(this.loc));for(let i=0;ic||(_[t].push(l[i]),_[e].push(this.loc));return{major:r,minor:_}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if(u.isNumber(t))return t;const[,e]=this.ranges;if(e instanceof g.FactorRange)return e.synthetic(t);throw new Error(\"unexpected\")}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}}i.AxisView=p,p.__name__=\"AxisView\";class k extends a.GuideRenderer{constructor(t){super(t)}static init_Axis(){this.prototype.default_view=p,this.mixins([[\"axis_\",h.Line],[\"major_tick_\",h.Line],[\"minor_tick_\",h.Line],[\"major_label_\",h.Text],[\"axis_label_\",h.Text]]),this.define((({Any:t,Int:e,Number:i,String:s,Ref:o,Dict:n,Tuple:a,Or:h,Nullable:b,Auto:m})=>({bounds:[h(a(i,i),m),\"auto\"],ticker:[o(l.Ticker)],formatter:[o(r.TickFormatter)],axis_label:[b(s),\"\"],axis_label_standoff:[e,5],major_label_standoff:[e,5],major_label_orientation:[h(c.TickLabelOrientation,i),\"horizontal\"],major_label_overrides:[n(s),{}],major_label_policy:[o(_.LabelingPolicy),()=>new _.AllLabels],major_tick_in:[i,2],major_tick_out:[i,6],minor_tick_in:[i,0],minor_tick_out:[i,4],fixed_location:[b(h(i,t)),null]}))),this.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})}}i.Axis=k,k.__name__=\"Axis\",k.init_Axis()},\n", " function _(e,r,d,i,n){i();const s=e(41);class t extends s.RendererView{}d.GuideRendererView=t,t.__name__=\"GuideRendererView\";class _ extends s.Renderer{constructor(e){super(e)}static init_GuideRenderer(){this.override({level:\"guide\"})}}d.GuideRenderer=_,_.__name__=\"GuideRenderer\",_.init_GuideRenderer()},\n", " function _(c,e,n,s,o){s();const r=c(53);class t extends r.Model{constructor(c){super(c)}}n.Ticker=t,t.__name__=\"Ticker\"},\n", " function _(t,o,r,e,c){e();const n=t(53),a=t(167);class m extends n.Model{constructor(t){super(t)}format_graphics(t,o){return this.doFormat(t,o).map((t=>new a.TextBox({text:t})))}compute(t,o){return this.doFormat([t],null!=o?o:{loc:0})[0]}v_compute(t,o){return this.doFormat(t,null!=o?o:{loc:0})}}r.TickFormatter=m,m.__name__=\"TickFormatter\"},\n", " function _(t,e,s,i,n){i();const h=t(99),o=t(143),a=t(9),r=t(8),c=t(168),_=t(22);s.text_width=(()=>{const t=document.createElement(\"canvas\").getContext(\"2d\");let e=\"\";return(s,i)=>(i!=e&&(e=i,t.font=i),t.measureText(s).width)})();class l{constructor(){this._position={sx:0,sy:0},this.font_size_scale=1,this._base_font_size=13}set base_font_size(t){this._base_font_size=t}get base_font_size(){return this._base_font_size}set position(t){this._position=t}get position(){return this._position}infer_text_height(){return\"ascent_descent\"}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),a=Math.max(t.x,e.x,s.x,i.x),r=Math.max(t.y,e.y,s.y,i.y);return new h.BBox({left:n,right:a,top:o,bottom:r})}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new c.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e.x),h(e.y)),t.lineTo(h(s.x),h(s.y)),t.lineTo(h(i.x),h(i.y)),t.lineTo(h(n.x),h(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e),h(s)),t.lineTo(h(e),h(s+n)),t.lineTo(h(e+i),h(s+n)),t.lineTo(h(e+i),h(s)),t.closePath(),t.stroke(),t.restore()}}s.GraphicsBox=l,l.__name__=\"GraphicsBox\";class x extends l{constructor({text:t}){super(),this.align=\"left\",this.text=t}set visuals(t){const e=t.text_color.get_value(),s=t.text_alpha.get_value(),i=t.text_font_style.get_value();let n=t.text_font_size.get_value();const h=t.text_font.get_value(),{font_size_scale:a,base_font_size:r}=this,c=o.parse_css_font_size(n);if(null!=c){let{value:t,unit:e}=c;t*=a,\"em\"==e&&r&&(t*=r,e=\"px\"),n=`${t}${e}`}const l=`${i} ${n} ${h}`;this.font=l,this.color=_.color2css(e,s),this.line_height=t.text_line_height.get_value()}infer_text_height(){if(this.text.includes(\"\\n\"))return\"ascent_descent\";return function(t){for(const e of new Set(t))if(!(\"0\"<=e&&e<=\"9\"))switch(e){case\",\":case\".\":case\"+\":case\"-\":case\"−\":case\"e\":continue;default:return!1}return!0}(this.text)?\"cap\":\"ascent_descent\"}_text_line(t){var e;const s=null!==(e=this.text_height_metric)&&void 0!==e?e:this.infer_text_height(),i=(()=>{switch(s){case\"x\":case\"x_descent\":return t.x_height;case\"cap\":case\"cap_descent\":return t.cap_height;case\"ascent\":case\"ascent_descent\":return t.ascent}})(),n=(()=>{switch(s){case\"x\":case\"cap\":case\"ascent\":return 0;case\"x_descent\":case\"cap_descent\":case\"ascent_descent\":return t.descent}})();return{height:i+n,ascent:i,descent:n}}get nlines(){return this.text.split(\"\\n\").length}_size(){var t,e;const{font:i}=this,n=o.font_metrics(i),h=(this.line_height-1)*n.height,r=\"\"==this.text,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>s.text_width(t,i))),x=this._text_line(n).height*_,u=\"%\"==(null===(t=this.width)||void 0===t?void 0:t.unit)?this.width.value:1,p=\"%\"==(null===(e=this.height)||void 0===e?void 0:e.unit)?this.height.value:1;return{width:a.max(l)*u,height:r?0:(x+h*(_-1))*p,metrics:n}}_computed_position(t,e,s){const{width:i,height:n}=t,{sx:h,sy:o,x_anchor:a=\"left\",y_anchor:c=\"center\"}=this.position;return{x:h-(()=>{if(r.isNumber(a))return a*i;switch(a){case\"left\":return 0;case\"center\":return.5*i;case\"right\":return i}})(),y:o-(()=>{var t;if(r.isNumber(c))return c*n;switch(c){case\"top\":return 0;case\"center\":return.5*n;case\"bottom\":return n;case\"baseline\":if(1!=s)return.5*n;switch(null!==(t=this.text_height_metric)&&void 0!==t?t:this.infer_text_height()){case\"x\":case\"x_descent\":return e.x_height;case\"cap\":case\"cap_descent\":return e.cap_height;case\"ascent\":case\"ascent_descent\":return e.ascent}}})()}}_rect(){const{width:t,height:e,metrics:s}=this._size(),i=this.text.split(\"\\n\").length,{x:n,y:o}=this._computed_position({width:t,height:e},s,i);return new h.BBox({x:n,y:o,width:t,height:e}).rect}paint(t){var e,i;const{font:n}=this,h=o.font_metrics(n),r=(this.line_height-1)*h.height,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>s.text_width(t,n))),x=this._text_line(h),u=x.height*_,p=\"%\"==(null===(e=this.width)||void 0===e?void 0:e.unit)?this.width.value:1,f=\"%\"==(null===(i=this.height)||void 0===i?void 0:i.unit)?this.height.value:1,g=a.max(l)*p,d=(u+r*(_-1))*f;t.save(),t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\";const{sx:b,sy:m}=this.position,{align:y}=this,{angle:v}=this;v&&(t.translate(b,m),t.rotate(v),t.translate(-b,-m));let{x:w,y:z}=this._computed_position({width:g,height:d},h,_);if(\"justify\"==y)for(let e=0;e<_;e++){let i=w;const h=c[e].split(\" \"),o=h.length,_=h.map((t=>s.text_width(t,n))),l=(g-a.sum(_))/(o-1);for(let e=0;e{switch(y){case\"left\":return 0;case\"center\":return.5*(g-l[e]);case\"right\":return g-l[e]}})();t.fillStyle=this.color,t.fillText(c[e],s,z+x.ascent),z+=x.height+r}t.restore()}}s.TextBox=x,x.__name__=\"TextBox\";class u extends l{constructor(t,e){super(),this.base=t,this.expo=e}get children(){return[this.base,this.expo]}set base_font_size(t){super.base_font_size=t,this.base.base_font_size=t,this.expo.base_font_size=t}set position(t){this._position=t;const e=this.base.size(),s=this.expo.size(),i=this._shift_scale()*e.height,n=Math.max(e.height,i+s.height);this.base.position={sx:0,x_anchor:\"left\",sy:n,y_anchor:\"bottom\"},this.expo.position={sx:e.width,x_anchor:\"left\",sy:i,y_anchor:\"bottom\"}}get position(){return this._position}set visuals(t){this.expo.font_size_scale=.7,this.base.visuals=t,this.expo.visuals=t}_shift_scale(){if(this.base instanceof x&&1==this.base.nlines){const{x_height:t,cap_height:e}=o.font_metrics(this.base.font);return t/e}return 2/3}infer_text_height(){return this.base.infer_text_height()}_rect(){const t=this.base.bbox(),e=this.expo.bbox(),s=t.union(e),{x:i,y:n}=this._computed_position();return s.translate(i,n).rect}_size(){const t=this.base.size(),e=this.expo.size();return{width:t.width+e.width,height:Math.max(t.height,this._shift_scale()*t.height+e.height)}}paint(t){t.save();const{angle:e}=this;if(e){const{sx:s,sy:i}=this.position;t.translate(s,i),t.rotate(e),t.translate(-s,-i)}const{x:s,y:i}=this._computed_position();t.translate(s,i),this.base.paint(t),this.expo.paint(t),t.restore()}paint_bbox(t){super.paint_bbox(t);const{x:e,y:s}=this._computed_position();t.save(),t.translate(e,s);for(const e of this.children)e.paint_bbox(t);t.restore()}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=\"left\",y_anchor:h=\"center\"}=this.position;return{x:s-(()=>{if(r.isNumber(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if(r.isNumber(h))return h*e;switch(h){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}}s.BaseExpo=u,u.__name__=\"BaseExpo\";class p{constructor(t){this.items=t}set base_font_size(t){for(const e of this.items)e.base_font_size=t}get length(){return this.items.length}set visuals(t){for(const e of this.items)e.visuals=t;const e={x:0,cap:1,ascent:2,x_descent:3,cap_descent:4,ascent_descent:5},s=a.max_by(this.items.map((t=>t.infer_text_height())),(t=>e[t]));for(const t of this.items)t.text_height_metric=s}set angle(t){for(const e of this.items)e.angle=t}max_size(){let t=0,e=0;for(const s of this.items){const i=s.size();t=Math.max(t,i.width),e=Math.max(e,i.height)}return{width:t,height:e}}}s.GraphicsBoxes=p,p.__name__=\"GraphicsBoxes\"},\n", " function _(t,s,r,n,i){n();const{sin:e,cos:a}=Math;class h{constructor(t=1,s=0,r=0,n=1,i=0,e=0){this.a=t,this.b=s,this.c=r,this.d=n,this.e=i,this.f=e}toString(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return`matrix(${t}, ${s}, ${r}, ${n}, ${i}, ${e})`}clone(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new h(t,s,r,n,i,e)}get is_identity(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return 1==t&&0==s&&0==r&&1==n&&0==i&&0==e}apply_point(t){const[s,r]=this.apply(t.x,t.y);return{x:s,y:r}}apply_rect(t){return{p0:this.apply_point(t.p0),p1:this.apply_point(t.p1),p2:this.apply_point(t.p2),p3:this.apply_point(t.p3)}}apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this;return[r*t+i*s+a,n*t+e*s+h]}iv_apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this,p=t.length;for(let o=0;o({min_distance:[e,5]})))}filter(e,n,s){const{min_distance:t}=this;let i=null;for(const n of e)null!=i&&s(i,n)({args:[s(e),{}],code:[n,\"\"]})))}get names(){return c.keys(this.args)}get values(){return c.values(this.args)}get func(){const e=o.use_strict(this.code);return new a.GeneratorFunction(\"indices\",\"bboxes\",\"distance\",...this.names,e)}filter(e,n,s){const t=Object.create(null),i=this.func.call(t,e,n,s,...this.values);let l=i.next();if(l.done&&void 0!==l.value){const{value:n}=l;return n instanceof a.Indices?n:void 0===n?e:r.isIterable(n)?a.Indices.from_indices(e.size,n):a.Indices.all_unset(e.size)}{const n=[];do{n.push(l.value),l=i.next()}while(!l.done);return a.Indices.from_indices(e.size,n)}}}s.CustomLabelingPolicy=m,m.__name__=\"CustomLabelingPolicy\",m.init_CustomLabelingPolicy()},\n", " function _(t,s,e,o,i){o();const a=t(1),r=t(163),l=t(171),_=t(172),n=a.__importStar(t(48)),c=t(20),p=t(167),h=t(8);class m extends r.AxisView{_paint(t,s,e){this._draw_group_separators(t,s,e)}_draw_group_separators(t,s,e){const[o]=this.ranges,[i,a]=this.computed_bounds;if(!o.tops||o.tops.length<2||!this.visuals.separator_line.doit)return;const r=this.dimension,l=(r+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&cnew p.GraphicsBoxes(t.map((t=>h.isString(t)?new p.TextBox({text:t}):t))),_=t=>l(this.model.formatter.doFormat(t,this));if(1==t.levels){const t=_(i.major);r.push([t,a.major,this.model.major_label_orientation,this.visuals.major_label_text])}else if(2==t.levels){const t=_(i.major.map((t=>t[1])));r.push([t,a.major,this.model.major_label_orientation,this.visuals.major_label_text]),r.push([l(i.tops),a.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=_(i.major.map((t=>t[2]))),s=i.mids.map((t=>t[1]));r.push([t,a.major,this.model.major_label_orientation,this.visuals.major_label_text]),r.push([l(s),a.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),r.push([l(i.tops),a.tops,this.model.group_label_orientation,this.visuals.group_text])}return r}get tick_coords(){const t=this.dimension,s=(t+1)%2,[e]=this.ranges,[o,i]=this.computed_bounds,a=this.model.ticker.get_ticks(o,i,e,this.loc),r={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return r.major[t]=a.major,r.major[s]=a.major.map((()=>this.loc)),3==e.levels&&(r.mids[t]=a.mids,r.mids[s]=a.mids.map((()=>this.loc))),e.levels>1&&(r.tops[t]=a.tops,r.tops[s]=a.tops.map((()=>this.loc))),r}}e.CategoricalAxisView=m,m.__name__=\"CategoricalAxisView\";class u extends r.Axis{constructor(t){super(t)}static init_CategoricalAxis(){this.prototype.default_view=m,this.mixins([[\"separator_\",n.Line],[\"group_\",n.Text],[\"subgroup_\",n.Text]]),this.define((({Number:t,Or:s})=>({group_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"],subgroup_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"]}))),this.override({ticker:()=>new l.CategoricalTicker,formatter:()=>new _.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})}}e.CategoricalAxis=u,u.__name__=\"CategoricalAxis\",u.init_CategoricalAxis()},\n", " function _(t,c,o,s,e){s();const r=t(165);class i extends r.Ticker{constructor(t){super(t)}get_ticks(t,c,o,s){var e,r;return{major:this._collect(o.factors,o,t,c),minor:[],tops:this._collect(null!==(e=o.tops)&&void 0!==e?e:[],o,t,c),mids:this._collect(null!==(r=o.mids)&&void 0!==r?r:[],o,t,c)}}_collect(t,c,o,s){const e=[];for(const r of t){const t=c.synthetic(r);t>o&&tnew m.DatetimeTicker,formatter:()=>new r.DatetimeTickFormatter})}}i.DatetimeAxis=c,c.__name__=\"DatetimeAxis\",c.init_DatetimeAxis()},\n", " function _(i,e,s,n,t){n();const r=i(173),a=i(176),o=i(177);class c extends r.ContinuousAxisView{}s.LinearAxisView=c,c.__name__=\"LinearAxisView\";class _ extends r.ContinuousAxis{constructor(i){super(i)}static init_LinearAxis(){this.prototype.default_view=c,this.override({ticker:()=>new o.BasicTicker,formatter:()=>new a.BasicTickFormatter})}}s.LinearAxis=_,_.__name__=\"LinearAxis\",_.init_LinearAxis()},\n", " function _(i,t,e,n,o){n();const s=i(166),r=i(34);function c(i){let t=\"\";for(const e of i)t+=\"-\"==e?\"−\":e;return t}e.unicode_replace=c;class _ extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}static init_BasicTickFormatter(){this.define((({Boolean:i,Int:t,Auto:e,Or:n})=>({precision:[n(t,e),\"auto\"],use_scientific:[i,!0],power_limit_high:[t,5],power_limit_low:[t,-3]})))}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 10**this.power_limit_high}_need_sci(i){if(!this.use_scientific)return!1;const{scientific_limit_high:t}=this,{scientific_limit_low:e}=this,n=i.length<2?0:Math.abs(i[1]-i[0])/1e4;for(const o of i){const i=Math.abs(o);if(!(i<=n)&&(i>=t||i<=e))return!0}return!1}_format_with_precision(i,t,e){return t?i.map((i=>c(i.toExponential(e)))):i.map((i=>c(r.to_fixed(i,e))))}_auto_precision(i,t){const e=new Array(i.length),n=this.last_precision<=15;i:for(let o=this.last_precision;n?o<=15:o>=1;n?o++:o--){if(t){e[0]=i[0].toExponential(o);for(let t=1;t({base:[t,10],mantissas:[i(t),[1,2,5]],min_interval:[t,0],max_interval:[a(t),null]})))}get_min_interval(){return this.min_interval}get_max_interval(){var t;return null!==(t=this.max_interval)&&void 0!==t?t:1/0}initialize(){super.initialize();const t=r.nth(this.mantissas,-1)/this.base,i=r.nth(this.mantissas,0)*this.base;this.extended_mantissas=[t,...this.mantissas,i],this.base_factor=0===this.get_min_interval()?1:this.get_min_interval()}get_interval(t,i,a){const e=i-t,s=this.get_ideal_interval(t,i,a),n=Math.floor(_.log(s/this.base_factor,this.base)),l=this.base**n*this.base_factor,h=this.extended_mantissas,m=h.map((t=>Math.abs(a-e/(t*l)))),v=h[r.argmin(m)]*l;return _.clamp(v,this.get_min_interval(),this.get_max_interval())}}a.AdaptiveTicker=l,l.__name__=\"AdaptiveTicker\",l.init_AdaptiveTicker()},\n", " function _(t,i,n,s,e){s();const o=t(165),r=t(9);class c extends o.Ticker{constructor(t){super(t)}static init_ContinuousTicker(){this.define((({Int:t})=>({num_minor_ticks:[t,5],desired_num_ticks:[t,6]})))}get_ticks(t,i,n,s){return this.get_ticks_no_defaults(t,i,s,this.desired_num_ticks)}get_ticks_no_defaults(t,i,n,s){const e=this.get_interval(t,i,s),o=Math.floor(t/e),c=Math.ceil(i/e);let _;_=isFinite(o)&&isFinite(c)?r.range(o,c+1):[];const u=_.map((t=>t*e)).filter((n=>t<=n&&n<=i)),a=this.num_minor_ticks,f=[];if(a>0&&u.length>0){const n=e/a,s=r.range(0,a).map((t=>t*n));for(const n of s.slice(1)){const s=u[0]-n;t<=s&&s<=i&&f.push(s)}for(const n of u)for(const e of s){const s=n+e;t<=s&&s<=i&&f.push(s)}}return{major:u,minor:f}}get_ideal_interval(t,i,n){return(i-t)/n}}n.ContinuousTicker=c,c.__name__=\"ContinuousTicker\",c.init_ContinuousTicker()},\n", " function _(t,s,e,i,n){i();const r=t(1).__importDefault(t(181)),o=t(166),a=t(19),c=t(182),m=t(9),u=t(8);function h(t){return r.default(t,\"%Y %m %d %H %M %S\").split(/\\s+/).map((t=>parseInt(t,10)))}function d(t,s){if(u.isFunction(s))return s(t);{const e=c.sprintf(\"$1%06d\",function(t){return Math.round(t/1e3%1*1e6)}(t));return-1==(s=s.replace(/((^|[^%])(%%)*)%f/,e)).indexOf(\"%\")?s:r.default(t,s)}}const l=[\"microseconds\",\"milliseconds\",\"seconds\",\"minsec\",\"minutes\",\"hourmin\",\"hours\",\"days\",\"months\",\"years\"];class f extends o.TickFormatter{constructor(t){super(t),this.strip_leading_zeros=!0}static init_DatetimeTickFormatter(){this.define((({String:t,Array:s})=>({microseconds:[s(t),[\"%fus\"]],milliseconds:[s(t),[\"%3Nms\",\"%S.%3Ns\"]],seconds:[s(t),[\"%Ss\"]],minsec:[s(t),[\":%M:%S\"]],minutes:[s(t),[\":%M\",\"%Mm\"]],hourmin:[s(t),[\"%H:%M\"]],hours:[s(t),[\"%Hh\",\"%H:%M\"]],days:[s(t),[\"%m/%d\",\"%a%d\"]],months:[s(t),[\"%m/%Y\",\"%b %Y\"]],years:[s(t),[\"%Y\"]]})))}initialize(){super.initialize(),this._update_width_formats()}_update_width_formats(){const t=+r.default(new Date),s=function(s){const e=s.map((s=>d(t,s).length)),i=m.sort_by(m.zip(e,s),(([t])=>t));return m.unzip(i)};this._width_formats={microseconds:s(this.microseconds),milliseconds:s(this.milliseconds),seconds:s(this.seconds),minsec:s(this.minsec),minutes:s(this.minutes),hourmin:s(this.hourmin),hours:s(this.hours),days:s(this.days),months:s(this.months),years:s(this.years)}}_get_resolution_str(t,s){const e=1.1*t;switch(!1){case!(e<.001):return\"microseconds\";case!(e<1):return\"milliseconds\";case!(e<60):return s>=60?\"minsec\":\"seconds\";case!(e<3600):return s>=3600?\"hourmin\":\"minutes\";case!(e<86400):return\"hours\";case!(e<2678400):return\"days\";case!(e<31536e3):return\"months\";default:return\"years\"}}doFormat(t,s){if(0==t.length)return[];const e=Math.abs(t[t.length-1]-t[0])/1e3,i=e/(t.length-1),n=this._get_resolution_str(i,e),[,[r]]=this._width_formats[n],o=[],c=l.indexOf(n),m={};for(const t of l)m[t]=0;m.seconds=5,m.minsec=4,m.minutes=4,m.hourmin=3,m.hours=3;for(const s of t){let t,e;try{e=h(s),t=d(s,r)}catch(t){a.logger.warn(`unable to format tick for timestamp value ${s}`),a.logger.warn(` - ${t}`),o.push(\"ERR\");continue}let i=!1,u=c;for(;0==e[m[l[u]]];){let r;if(u+=1,u==l.length)break;if((\"minsec\"==n||\"hourmin\"==n)&&!i){if(\"minsec\"==n&&0==e[4]&&0!=e[5]||\"hourmin\"==n&&0==e[3]&&0!=e[4]){r=this._width_formats[l[c-1]][1][0],t=d(s,r);break}i=!0}r=this._width_formats[l[u]][1][0],t=d(s,r)}if(this.strip_leading_zeros){let s=t.replace(/^0+/g,\"\");s!=t&&isNaN(parseInt(s))&&(s=`0${s}`),o.push(s)}else o.push(t)}return o}}e.DatetimeTickFormatter=f,f.__name__=\"DatetimeTickFormatter\",f.init_DatetimeTickFormatter()},\n", " function _(e,t,n,r,o){!function(e){\"object\"==typeof t&&t.exports?t.exports=e():\"function\"==typeof define?define(e):this.tz=e()}((function(){function e(e,t,n){var r,o=t.day[1];do{r=new Date(Date.UTC(n,t.month,Math.abs(o++)))}while(t.day[0]<7&&r.getUTCDay()!=t.day[0]);return(r={clock:t.clock,sort:r.getTime(),rule:t,save:6e4*t.save,offset:e.offset})[r.clock]=r.sort+6e4*t.time,r.posix?r.wallclock=r[r.clock]+(e.offset+t.saved):r.posix=r[r.clock]-(e.offset+t.saved),r}function t(t,n,r){var o,a,u,i,l,s,c,f=t[t.zone],h=[],T=new Date(r).getUTCFullYear(),g=1;for(o=1,a=f.length;o=T-g;--c)for(o=0,a=s.length;o=h[o][n]&&h[o][h[o].clock]>u[h[o].clock]&&(i=h[o])}return i&&((l=/^(.*)\\/(.*)$/.exec(u.format))?i.abbrev=l[i.save?2:1]:i.abbrev=u.format.replace(/%s/,i.rule.letter)),i||u}function n(e,n){return\"UTC\"==e.zone?n:(e.entry=t(e,\"posix\",n),n+e.entry.offset+e.entry.save)}function r(e,n){return\"UTC\"==e.zone?n:(e.entry=r=t(e,\"wallclock\",n),0<(o=n-r.wallclock)&&o9)t+=s*l[c-10];else{if(a=new Date(n(e,t)),c<7)for(;s;)a.setUTCDate(a.getUTCDate()+i),a.getUTCDay()==c&&(s-=i);else 7==c?a.setUTCFullYear(a.getUTCFullYear()+s):8==c?a.setUTCMonth(a.getUTCMonth()+s):a.setUTCDate(a.getUTCDate()+s);null==(t=r(e,a.getTime()))&&(t=r(e,a.getTime()+864e5*i)-864e5*i)}return t}var a={clock:function(){return+new Date},zone:\"UTC\",entry:{abbrev:\"UTC\",offset:0,save:0},UTC:1,z:function(e,t,n,r){var 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supported\");i.push({placeholder:t[0],param_no:t[1],keys:t[2],sign:t[3],pad_char:t[4],align:t[5],width:t[6],precision:t[7],type:t[8]})}r=r.substring(t[0].length)}return s[n]=i}void 0!==t&&(t.sprintf=n,t.vsprintf=r),\"undefined\"!=typeof window&&(window.sprintf=n,window.vsprintf=r,\"function\"==typeof define&&define.amd&&define((function(){return{sprintf:n,vsprintf:r}})))}()},\n", " function _(e,i,n,t,a){t();const s=e(9),r=e(178),c=e(186),m=e(187),_=e(190),k=e(191),o=e(189);class T extends c.CompositeTicker{constructor(e){super(e)}static init_DatetimeTicker(){this.override({num_minor_ticks:0,tickers:()=>[new r.AdaptiveTicker({mantissas:[1,2,5],base:10,min_interval:0,max_interval:500*o.ONE_MILLI,num_minor_ticks:0}),new r.AdaptiveTicker({mantissas:[1,2,5,10,15,20,30],base:60,min_interval:o.ONE_SECOND,max_interval:30*o.ONE_MINUTE,num_minor_ticks:0}),new r.AdaptiveTicker({mantissas:[1,2,4,6,8,12],base:24,min_interval:o.ONE_HOUR,max_interval:12*o.ONE_HOUR,num_minor_ticks:0}),new m.DaysTicker({days:s.range(1,32)}),new m.DaysTicker({days:s.range(1,31,3)}),new m.DaysTicker({days:[1,8,15,22]}),new m.DaysTicker({days:[1,15]}),new _.MonthsTicker({months:s.range(0,12,1)}),new _.MonthsTicker({months:s.range(0,12,2)}),new _.MonthsTicker({months:s.range(0,12,4)}),new _.MonthsTicker({months:s.range(0,12,6)}),new k.YearsTicker({})]})}}n.DatetimeTicker=T,T.__name__=\"DatetimeTicker\",T.init_DatetimeTicker()},\n", " function _(t,e,i,s,r){s();const n=t(179),_=t(9);class a extends n.ContinuousTicker{constructor(t){super(t)}static init_CompositeTicker(){this.define((({Array:t,Ref:e})=>({tickers:[t(e(n.ContinuousTicker)),[]]})))}get min_intervals(){return this.tickers.map((t=>t.get_min_interval()))}get max_intervals(){return this.tickers.map((t=>t.get_max_interval()))}get_min_interval(){return this.min_intervals[0]}get_max_interval(){return this.max_intervals[0]}get_best_ticker(t,e,i){const s=e-t,r=this.get_ideal_interval(t,e,i),n=[_.sorted_index(this.min_intervals,r)-1,_.sorted_index(this.max_intervals,r)],a=[this.min_intervals[n[0]],this.max_intervals[n[1]]].map((t=>Math.abs(i-s/t)));let c;if(_.is_empty(a.filter((t=>!isNaN(t)))))c=this.tickers[0];else{const t=n[_.argmin(a)];c=this.tickers[t]}return c}get_interval(t,e,i){return this.get_best_ticker(t,e,i).get_interval(t,e,i)}get_ticks_no_defaults(t,e,i,s){return this.get_best_ticker(t,e,s).get_ticks_no_defaults(t,e,i,s)}}i.CompositeTicker=a,a.__name__=\"CompositeTicker\",a.init_CompositeTicker()},\n", " function _(t,e,n,i,s){i();const a=t(188),o=t(189),r=t(9);class c extends a.SingleIntervalTicker{constructor(t){super(t)}static init_DaysTicker(){this.define((({Int:t,Array:e})=>({days:[e(t),[]]}))),this.override({num_minor_ticks:0})}initialize(){super.initialize();const t=this.days;t.length>1?this.interval=(t[1]-t[0])*o.ONE_DAY:this.interval=31*o.ONE_DAY}get_ticks_no_defaults(t,e,n,i){const s=function(t,e){const n=o.last_month_no_later_than(new Date(t)),i=o.last_month_no_later_than(new Date(e));i.setUTCMonth(i.getUTCMonth()+1);const s=[],a=n;for(;s.push(o.copy_date(a)),a.setUTCMonth(a.getUTCMonth()+1),!(a>i););return s}(t,e),a=this.days,c=this.interval;return{major:r.concat(s.map((t=>((t,e)=>{const n=t.getUTCMonth(),i=[];for(const s of a){const a=o.copy_date(t);a.setUTCDate(s),new Date(a.getTime()+e/2).getUTCMonth()==n&&i.push(a)}return i})(t,c)))).map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.DaysTicker=c,c.__name__=\"DaysTicker\",c.init_DaysTicker()},\n", " function _(e,t,n,i,r){i();const l=e(179);class a extends l.ContinuousTicker{constructor(e){super(e)}static init_SingleIntervalTicker(){this.define((({Number:e})=>({interval:[e]})))}get_interval(e,t,n){return this.interval}get_min_interval(){return this.interval}get_max_interval(){return this.interval}}n.SingleIntervalTicker=a,a.__name__=\"SingleIntervalTicker\",a.init_SingleIntervalTicker()},\n", " function _(t,n,e,_,E){function N(t){return new Date(t.getTime())}function O(t){const n=N(t);return n.setUTCDate(1),n.setUTCHours(0),n.setUTCMinutes(0),n.setUTCSeconds(0),n.setUTCMilliseconds(0),n}_(),e.ONE_MILLI=1,e.ONE_SECOND=1e3,e.ONE_MINUTE=60*e.ONE_SECOND,e.ONE_HOUR=60*e.ONE_MINUTE,e.ONE_DAY=24*e.ONE_HOUR,e.ONE_MONTH=30*e.ONE_DAY,e.ONE_YEAR=365*e.ONE_DAY,e.copy_date=N,e.last_month_no_later_than=O,e.last_year_no_later_than=function(t){const n=O(t);return n.setUTCMonth(0),n}},\n", " function _(t,e,n,i,s){i();const r=t(188),a=t(189),o=t(9);class c extends r.SingleIntervalTicker{constructor(t){super(t)}static init_MonthsTicker(){this.define((({Int:t,Array:e})=>({months:[e(t),[]]})))}initialize(){super.initialize();const t=this.months;t.length>1?this.interval=(t[1]-t[0])*a.ONE_MONTH:this.interval=12*a.ONE_MONTH}get_ticks_no_defaults(t,e,n,i){const s=function(t,e){const n=a.last_year_no_later_than(new Date(t)),i=a.last_year_no_later_than(new Date(e));i.setUTCFullYear(i.getUTCFullYear()+1);const s=[],r=n;for(;s.push(a.copy_date(r)),r.setUTCFullYear(r.getUTCFullYear()+1),!(r>i););return s}(t,e),r=this.months;return{major:o.concat(s.map((t=>r.map((e=>{const n=a.copy_date(t);return n.setUTCMonth(e),n}))))).map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.MonthsTicker=c,c.__name__=\"MonthsTicker\",c.init_MonthsTicker()},\n", " function _(e,t,a,i,r){i();const n=e(177),_=e(188),s=e(189);class c extends _.SingleIntervalTicker{constructor(e){super(e)}initialize(){super.initialize(),this.interval=s.ONE_YEAR,this.basic_ticker=new n.BasicTicker({num_minor_ticks:0})}get_ticks_no_defaults(e,t,a,i){const r=s.last_year_no_later_than(new Date(e)).getUTCFullYear(),n=s.last_year_no_later_than(new Date(t)).getUTCFullYear();return{major:this.basic_ticker.get_ticks_no_defaults(r,n,a,i).major.map((e=>Date.UTC(e,0,1))).filter((a=>e<=a&&a<=t)),minor:[]}}}a.YearsTicker=c,c.__name__=\"YearsTicker\"},\n", " function _(i,s,t,e,o){e();const n=i(173),r=i(193),_=i(194);class c extends n.ContinuousAxisView{}t.LogAxisView=c,c.__name__=\"LogAxisView\";class x extends n.ContinuousAxis{constructor(i){super(i)}static init_LogAxis(){this.prototype.default_view=c,this.override({ticker:()=>new _.LogTicker,formatter:()=>new r.LogTickFormatter})}}t.LogAxis=x,x.__name__=\"LogAxis\",x.init_LogAxis()},\n", " function _(t,e,r,i,n){i();const o=t(166),a=t(176),s=t(194),c=t(167),{log:l,round:u}=Math;class _ extends o.TickFormatter{constructor(t){super(t)}static init_LogTickFormatter(){this.define((({Ref:t,Nullable:e})=>({ticker:[e(t(s.LogTicker)),null]})))}initialize(){super.initialize(),this.basic_formatter=new a.BasicTickFormatter}format_graphics(t,e){var r,i;if(0==t.length)return[];const n=null!==(i=null===(r=this.ticker)||void 0===r?void 0:r.base)&&void 0!==i?i:10,o=this._exponents(t,n);return null==o?this.basic_formatter.format_graphics(t,e):o.map((t=>{const e=new c.TextBox({text:a.unicode_replace(`${n}`)}),r=new c.TextBox({text:a.unicode_replace(`${t}`)});return new c.BaseExpo(e,r)}))}_exponents(t,e){let r=null;const i=[];for(const n of t){const t=u(l(n)/l(e));if(r==t)return null;r=t,i.push(t)}return i}doFormat(t,e){var r,i;if(0==t.length)return[];const n=null!==(i=null===(r=this.ticker)||void 0===r?void 0:r.base)&&void 0!==i?i:10,o=this._exponents(t,n);return null==o?this.basic_formatter.doFormat(t,e):o.map((t=>a.unicode_replace(`${n}^${t}`)))}}r.LogTickFormatter=_,_.__name__=\"LogTickFormatter\",_.init_LogTickFormatter()},\n", " function _(t,o,e,i,s){i();const n=t(178),r=t(9);class c extends n.AdaptiveTicker{constructor(t){super(t)}static init_LogTicker(){this.override({mantissas:[1,5]})}get_ticks_no_defaults(t,o,e,i){const s=this.num_minor_ticks,n=[],c=this.base,a=Math.log(t)/Math.log(c),f=Math.log(o)/Math.log(c),l=f-a;let h;if(isFinite(l))if(l<2){const e=this.get_interval(t,o,i),c=Math.floor(t/e),a=Math.ceil(o/e);if(h=r.range(c,a+1).filter((t=>0!=t)).map((t=>t*e)).filter((e=>t<=e&&e<=o)),s>0&&h.length>0){const t=e/s,o=r.range(0,s).map((o=>o*t));for(const t of o.slice(1))n.push(h[0]-t);for(const t of h)for(const e of o)n.push(t+e)}}else{const t=Math.ceil(.999999*a),o=Math.floor(1.000001*f),e=Math.ceil((o-t)/9);if(h=r.range(t-1,o+1,e).map((t=>c**t)),s>0&&h.length>0){const t=c**e/s,o=r.range(1,s+1).map((o=>o*t));for(const t of o)n.push(h[0]/t);n.push(h[0]);for(const t of h)for(const e of o)n.push(t*e)}}else h=[];return{major:h.filter((e=>t<=e&&e<=o)),minor:n.filter((e=>t<=e&&e<=o))}}}e.LogTicker=c,c.__name__=\"LogTicker\",c.init_LogTicker()},\n", " function _(e,t,i,r,s){r();const a=e(163),o=e(175),c=e(196),n=e(197);class _ extends a.AxisView{}i.MercatorAxisView=_,_.__name__=\"MercatorAxisView\";class x extends o.LinearAxis{constructor(e){super(e)}static init_MercatorAxis(){this.prototype.default_view=_,this.override({ticker:()=>new n.MercatorTicker({dimension:\"lat\"}),formatter:()=>new c.MercatorTickFormatter({dimension:\"lat\"})})}}i.MercatorAxis=x,x.__name__=\"MercatorAxis\",x.init_MercatorAxis()},\n", " function _(r,t,e,o,n){o();const i=r(176),c=r(20),a=r(65);class s extends i.BasicTickFormatter{constructor(r){super(r)}static init_MercatorTickFormatter(){this.define((({Nullable:r})=>({dimension:[r(c.LatLon),null]})))}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n({dimension:[t(e.LatLon),null]})))}get_ticks_no_defaults(t,o,n,r){if(null==this.dimension)throw new Error(`${this}.dimension wasn't configured`);return[t,o]=c.clip_mercator(t,o,this.dimension),\"lon\"==this.dimension?this._get_ticks_lon(t,o,n,r):this._get_ticks_lat(t,o,n,r)}_get_ticks_lon(t,o,n,r){const[s]=c.wgs84_mercator.invert(t,n),[i,e]=c.wgs84_mercator.invert(o,n),_=super.get_ticks_no_defaults(s,i,n,r),a=[];for(const t of _.major)if(c.in_bounds(t,\"lon\")){const[o]=c.wgs84_mercator.compute(t,e);a.push(o)}const m=[];for(const t of _.minor)if(c.in_bounds(t,\"lon\")){const[o]=c.wgs84_mercator.compute(t,e);m.push(o)}return{major:a,minor:m}}_get_ticks_lat(t,o,n,r){const[,s]=c.wgs84_mercator.invert(n,t),[i,e]=c.wgs84_mercator.invert(n,o),_=super.get_ticks_no_defaults(s,e,n,r),a=[];for(const t of _.major)if(c.in_bounds(t,\"lat\")){const[,o]=c.wgs84_mercator.compute(i,t);a.push(o)}const m=[];for(const t of _.minor)if(c.in_bounds(t,\"lat\")){const[,o]=c.wgs84_mercator.compute(i,t);m.push(o)}return{major:a,minor:m}}}n.MercatorTicker=_,_.__name__=\"MercatorTicker\",_.init_MercatorTicker()},\n", " function _(e,i,r,c,k){c(),k(\"AdaptiveTicker\",e(178).AdaptiveTicker),k(\"BasicTicker\",e(177).BasicTicker),k(\"CategoricalTicker\",e(171).CategoricalTicker),k(\"CompositeTicker\",e(186).CompositeTicker),k(\"ContinuousTicker\",e(179).ContinuousTicker),k(\"DatetimeTicker\",e(185).DatetimeTicker),k(\"DaysTicker\",e(187).DaysTicker),k(\"FixedTicker\",e(199).FixedTicker),k(\"LogTicker\",e(194).LogTicker),k(\"MercatorTicker\",e(197).MercatorTicker),k(\"MonthsTicker\",e(190).MonthsTicker),k(\"SingleIntervalTicker\",e(188).SingleIntervalTicker),k(\"Ticker\",e(165).Ticker),k(\"YearsTicker\",e(191).YearsTicker),k(\"BinnedTicker\",e(200).BinnedTicker)},\n", " function _(i,t,e,r,n){r();const s=i(179);class _ extends s.ContinuousTicker{constructor(i){super(i)}static init_FixedTicker(){this.define((({Number:i,Array:t})=>({ticks:[t(i),[]],minor_ticks:[t(i),[]]})))}get_ticks_no_defaults(i,t,e,r){return{major:this.ticks,minor:this.minor_ticks}}get_interval(i,t,e){return 0}get_min_interval(){return 0}get_max_interval(){return 0}}e.FixedTicker=_,_.__name__=\"FixedTicker\",_.init_FixedTicker()},\n", " function _(e,n,t,i,r){i();const c=e(165),o=e(201),s=e(12);class a extends c.Ticker{constructor(e){super(e)}static init_BinnedTicker(){this.define((({Number:e,Ref:n,Or:t,Auto:i})=>({mapper:[n(o.ScanningColorMapper)],num_major_ticks:[t(e,i),8]})))}get_ticks(e,n,t,i){const{binning:r}=this.mapper.metrics,c=Math.max(0,s.left_edge_index(e,r)),o=Math.min(s.left_edge_index(n,r)+1,r.length-1),a=[];for(let e=c;e<=o;e++)a.push(r[e]);const{num_major_ticks:_}=this,m=[],h=\"auto\"==_?a.length:_,l=Math.max(1,Math.floor(a.length/h));for(let e=0;eo.binning[o.binning.length-1])return r;return e[a.left_edge_index(n,o.binning)]}}i.ScanningColorMapper=c,c.__name__=\"ScanningColorMapper\"},\n", " function _(t,o,e,n,s){n();const l=t(203),i=t(61),c=t(9),a=t(8);class r extends l.ColorMapper{constructor(t){super(t),this._scan_data=null}static init_ContinuousColorMapper(){this.define((({Number:t,String:o,Ref:e,Color:n,Or:s,Tuple:l,Array:c,Nullable:a})=>({high:[a(t),null],low:[a(t),null],high_color:[a(n),null],low_color:[a(n),null],domain:[c(l(e(i.GlyphRenderer),s(o,c(o)))),[]]})))}connect_signals(){super.connect_signals();const t=()=>{for(const[t]of this.domain)this.connect(t.view.change,(()=>this.update_data())),this.connect(t.data_source.selected.change,(()=>this.update_data()))};this.connect(this.properties.domain.change,(()=>t())),t()}update_data(){const{domain:t,palette:o}=this,e=[...this._collect(t)];this._scan_data=this.scan(e,o.length),this.metrics_change.emit(),this.change.emit()}get metrics(){return null==this._scan_data&&this.update_data(),this._scan_data}*_collect(t){for(const[o,e]of t)for(const t of a.isArray(e)?e:[e]){let e=o.data_source.get_column(t);e=o.view.indices.select(e);const n=o.view.masked,s=o.data_source.selected.indices;let l;if(null!=n&&s.length>0?l=c.intersection([...n],s):null!=n?l=[...n]:s.length>0&&(l=s),null!=l&&(e=c.map(l,(t=>e[t]))),e.length>0&&!a.isNumber(e[0]))for(const t of e)yield*t;else yield*e}}_v_compute(t,o,e,n){const{nan_color:s}=n;let{low_color:l,high_color:i}=n;null==l&&(l=e[0]),null==i&&(i=e[e.length-1]);const{domain:a}=this,r=c.is_empty(a)?t:[...this._collect(a)];this._scan_data=this.scan(r,e.length),this.metrics_change.emit();for(let n=0,c=t.length;n({palette:[r(t)],nan_color:[t,\"gray\"]})))}v_compute(t){const r=new Array(t.length);return this._v_compute(t,r,this.palette,this._colors((t=>t))),r}get rgba_mapper(){const t=this,r=p(this.palette),e=this._colors(s);return{v_compute(n){const o=new c.ColorArray(n.length);return t._v_compute(n,o,r,e),new Uint8ClampedArray(l.to_big_endian(o).buffer)}}}_colors(t){return{nan_color:t(this.nan_color)}}}e.ColorMapper=u,u.__name__=\"ColorMapper\",u.init_ColorMapper()},\n", " function _(r,e,n,s,o){s();const p=r(149);class t extends p.Transform{constructor(r){super(r)}compute(r){throw new Error(\"mapping single values is not supported\")}}n.Mapper=t,t.__name__=\"Mapper\"},\n", " function _(t,r,a,e,c){e(),c(\"BasicTickFormatter\",t(176).BasicTickFormatter),c(\"CategoricalTickFormatter\",t(172).CategoricalTickFormatter),c(\"DatetimeTickFormatter\",t(180).DatetimeTickFormatter),c(\"FuncTickFormatter\",t(206).FuncTickFormatter),c(\"LogTickFormatter\",t(193).LogTickFormatter),c(\"MercatorTickFormatter\",t(196).MercatorTickFormatter),c(\"NumeralTickFormatter\",t(207).NumeralTickFormatter),c(\"PrintfTickFormatter\",t(208).PrintfTickFormatter),c(\"TickFormatter\",t(166).TickFormatter)},\n", " function _(t,n,e,s,i){s();const r=t(166),c=t(13),a=t(34);class u extends r.TickFormatter{constructor(t){super(t)}static init_FuncTickFormatter(){this.define((({Unknown:t,String:n,Dict:e})=>({args:[e(t),{}],code:[n,\"\"]})))}get names(){return c.keys(this.args)}get values(){return c.values(this.args)}_make_func(){const t=a.use_strict(this.code);return new Function(\"tick\",\"index\",\"ticks\",...this.names,t)}doFormat(t,n){const e=this._make_func().bind({});return t.map(((t,n,s)=>`${e(t,n,s,...this.values)}`))}}e.FuncTickFormatter=u,u.__name__=\"FuncTickFormatter\",u.init_FuncTickFormatter()},\n", " function _(r,t,n,e,a){e();const o=r(1).__importStar(r(183)),i=r(166),u=r(20);class c extends i.TickFormatter{constructor(r){super(r)}static init_NumeralTickFormatter(){this.define((({String:r})=>({format:[r,\"0,0\"],language:[r,\"en\"],rounding:[u.RoundingFunction,\"round\"]})))}get _rounding_fn(){switch(this.rounding){case\"round\":case\"nearest\":return Math.round;case\"floor\":case\"rounddown\":return Math.floor;case\"ceil\":case\"roundup\":return Math.ceil}}doFormat(r,t){const{format:n,language:e,_rounding_fn:a}=this;return r.map((r=>o.format(r,n,e,a)))}}n.NumeralTickFormatter=c,c.__name__=\"NumeralTickFormatter\",c.init_NumeralTickFormatter()},\n", " function _(t,r,i,n,o){n();const a=t(166),e=t(182);class c extends a.TickFormatter{constructor(t){super(t)}static init_PrintfTickFormatter(){this.define((({String:t})=>({format:[t,\"%s\"]})))}doFormat(t,r){return t.map((t=>e.sprintf(this.format,t)))}}i.PrintfTickFormatter=c,c.__name__=\"PrintfTickFormatter\",c.init_PrintfTickFormatter()},\n", " function _(r,o,a,p,e){p(),e(\"CategoricalColorMapper\",r(210).CategoricalColorMapper),e(\"CategoricalMarkerMapper\",r(212).CategoricalMarkerMapper),e(\"CategoricalPatternMapper\",r(213).CategoricalPatternMapper),e(\"ContinuousColorMapper\",r(202).ContinuousColorMapper),e(\"ColorMapper\",r(203).ColorMapper),e(\"LinearColorMapper\",r(214).LinearColorMapper),e(\"LogColorMapper\",r(215).LogColorMapper),e(\"ScanningColorMapper\",r(201).ScanningColorMapper),e(\"EqHistColorMapper\",r(216).EqHistColorMapper)},\n", " function _(t,o,a,r,e){r();const c=t(211),l=t(203),i=t(104);class s extends l.ColorMapper{constructor(t){super(t)}static init_CategoricalColorMapper(){this.define((({Number:t,Nullable:o})=>({factors:[i.FactorSeq],start:[t,0],end:[o(t),null]})))}_v_compute(t,o,a,{nan_color:r}){c.cat_v_compute(t,this.factors,a,o,this.start,this.end,r)}}a.CategoricalColorMapper=s,s.__name__=\"CategoricalColorMapper\",s.init_CategoricalColorMapper()},\n", " function _(n,t,e,l,i){l();const c=n(12),u=n(8);function f(n,t){if(n.length!=t.length)return!1;for(let e=0,l=n.length;ef(n,h)))),s=_<0||_>=e.length?r:e[_],l[g]=s}}},\n", " function _(r,e,a,t,s){t();const c=r(211),i=r(104),l=r(204),n=r(20);class p extends l.Mapper{constructor(r){super(r)}static init_CategoricalMarkerMapper(){this.define((({Number:r,Array:e,Nullable:a})=>({factors:[i.FactorSeq],markers:[e(n.MarkerType)],start:[r,0],end:[a(r),null],default_value:[n.MarkerType,\"circle\"]})))}v_compute(r){const e=new Array(r.length);return c.cat_v_compute(r,this.factors,this.markers,e,this.start,this.end,this.default_value),e}}a.CategoricalMarkerMapper=p,p.__name__=\"CategoricalMarkerMapper\",p.init_CategoricalMarkerMapper()},\n", " function _(t,a,e,r,n){r();const s=t(211),c=t(104),i=t(204),p=t(20);class l extends i.Mapper{constructor(t){super(t)}static init_CategoricalPatternMapper(){this.define((({Number:t,Array:a,Nullable:e})=>({factors:[c.FactorSeq],patterns:[a(p.HatchPatternType)],start:[t,0],end:[e(t),null],default_value:[p.HatchPatternType,\" \"]})))}v_compute(t){const a=new Array(t.length);return s.cat_v_compute(t,this.factors,this.patterns,a,this.start,this.end,this.default_value),a}}e.CategoricalPatternMapper=l,l.__name__=\"CategoricalPatternMapper\",l.init_CategoricalPatternMapper()},\n", " function _(n,r,o,t,a){t();const e=n(202),i=n(12);class s extends e.ContinuousColorMapper{constructor(n){super(n)}scan(n,r){const o=null!=this.low?this.low:i.min(n),t=null!=this.high?this.high:i.max(n);return{max:t,min:o,norm_factor:1/(t-o),normed_interval:1/r}}cmap(n,r,o,t,a){const e=r.length-1;if(n==a.max)return r[e];const i=(n-a.min)*a.norm_factor,s=Math.floor(i/a.normed_interval);return s<0?o:s>e?t:r[s]}}o.LinearColorMapper=s,s.__name__=\"LinearColorMapper\"},\n", " function _(o,t,n,r,l){r();const a=o(202),s=o(12);class e extends a.ContinuousColorMapper{constructor(o){super(o)}scan(o,t){const n=null!=this.low?this.low:s.min(o),r=null!=this.high?this.high:s.max(o);return{max:r,min:n,scale:t/(Math.log(r)-Math.log(n))}}cmap(o,t,n,r,l){const a=t.length-1;if(o>l.max)return r;if(o==l.max)return t[a];if(oa&&(e=a),t[e]}}n.LogColorMapper=e,e.__name__=\"LogColorMapper\"},\n", " function _(n,t,i,e,o){e();const s=n(201),r=n(12),a=n(9),l=n(19);class c extends s.ScanningColorMapper{constructor(n){super(n)}static init_EqHistColorMapper(){this.define((({Int:n})=>({bins:[n,65536]})))}scan(n,t){const i=null!=this.low?this.low:r.min(n),e=null!=this.high?this.high:r.max(n),o=this.bins,s=a.linspace(i,e,o+1),c=r.bin_counts(n,s),h=new Array(o);for(let n=0,t=s.length;nn/g));let m=t-1,M=[],_=0,f=2*t;for(;m!=t&&_<4&&0!=m;){const n=f/m;if(n>1e3)break;f=Math.round(Math.max(t*n,t));const i=a.range(0,f),e=r.map(u,(n=>n*(f-1)));M=r.interpolate(i,e,h);m=a.uniq(M).length-1,_++}if(0==m){M=[i,e];for(let n=0;ne*n+t}compute(e){return this._linear_compute(e)}v_compute(e){return this._linear_v_compute(e)}invert(e){return this._linear_invert(e)}v_invert(e){return this._linear_v_invert(e)}}n.LinearScale=u,u.__name__=\"LinearScale\"},\n", " function _(n,t,e,r,i){r();const a=n(146),o=n(12);class c extends a.Scale{constructor(n){super(n)}static init_LinearInterpolationScale(){this.internal((({Arrayable:n})=>({binning:[n]})))}get s_compute(){throw new Error(\"not implemented\")}compute(n){return n}v_compute(n){const{binning:t}=this,{start:e,end:r}=this.source_range,i=e,a=r,c=t.length,l=(r-e)/(c-1),s=new Float64Array(c);for(let n=0;n{if(na)return a;const e=o.left_edge_index(n,t);if(-1==e)return i;if(e>=c-1)return a;const r=t[e],l=(n-r)/(t[e+1]-r),u=s[e];return u+l*(s[e+1]-u)}));return this._linear_v_compute(u)}invert(n){return n}v_invert(n){return new Float64Array(n)}}e.LinearInterpolationScale=c,c.__name__=\"LinearInterpolationScale\",c.init_LinearInterpolationScale()},\n", " function _(a,n,e,g,R){g(),R(\"DataRange\",a(160).DataRange),R(\"DataRange1d\",a(159).DataRange1d),R(\"FactorRange\",a(104).FactorRange),R(\"Range\",a(105).Range),R(\"Range1d\",a(156).Range1d)},\n", " function _(a,o,i,t,e){t();var n=a(141);e(\"Sizeable\",n.Sizeable),e(\"SizingPolicy\",n.SizingPolicy);var c=a(142);e(\"Layoutable\",c.Layoutable),e(\"LayoutItem\",c.LayoutItem);var r=a(222);e(\"HStack\",r.HStack),e(\"VStack\",r.VStack);var l=a(223);e(\"Grid\",l.Grid),e(\"Row\",l.Row),e(\"Column\",l.Column);var S=a(224);e(\"ContentBox\",S.ContentBox),e(\"VariadicBox\",S.VariadicBox)},\n", " function _(t,e,h,i,r){i();const n=t(142),o=t(99);class s extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}}h.Stack=s,s.__name__=\"Stack\";class c extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e+=i.width,h=Math.max(h,i.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.top:0;let i=this.absolute?t.left:0;const{height:r}=t;for(const t of this.children){const{width:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({left:i,width:e,top:h,height:r})),i+=e}}}h.HStack=c,c.__name__=\"HStack\";class a extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e=Math.max(e,i.width),h+=i.height}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.left:0;let i=this.absolute?t.top:0;const{width:r}=t;for(const t of this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({top:i,height:e,left:h,width:r})),i+=e}}}h.VStack=a,a.__name__=\"VStack\";class l extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}_measure(t){const{width_policy:e,height_policy:h}=this.sizing,{min:i,max:r}=Math;let n=0,o=0;for(const e of this.children){const{width:h,height:i}=e.measure(t);n=r(n,h),o=r(o,i)}return{width:(()=>{const{width:h}=this.sizing;if(t.width==1/0)return\"fixed\"==e&&null!=h?h:n;switch(e){case\"fixed\":return null!=h?h:n;case\"min\":return n;case\"fit\":return null!=h?i(t.width,h):t.width;case\"max\":return null!=h?r(t.width,h):t.width}})(),height:(()=>{const{height:e}=this.sizing;if(t.height==1/0)return\"fixed\"==h&&null!=e?e:o;switch(h){case\"fixed\":return null!=e?e:o;case\"min\":return o;case\"fit\":return null!=e?i(t.height,e):t.height;case\"max\":return null!=e?r(t.height,e):t.height}})()}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t:t.relative(),{left:i,right:r,top:n,bottom:s}=h,c=Math.round(h.vcenter),a=Math.round(h.hcenter);for(const e of this.children){const{margin:h,halign:l,valign:d}=e.sizing,{width:u,height:g,inner:_}=e.measure(t),w=(()=>{switch(`${d}_${l}`){case\"start_start\":return new o.BBox({left:i+h.left,top:n+h.top,width:u,height:g});case\"start_center\":return new o.BBox({hcenter:a,top:n+h.top,width:u,height:g});case\"start_end\":return new o.BBox({right:r-h.right,top:n+h.top,width:u,height:g});case\"center_start\":return new o.BBox({left:i+h.left,vcenter:c,width:u,height:g});case\"center_center\":return new o.BBox({hcenter:a,vcenter:c,width:u,height:g});case\"center_end\":return new o.BBox({right:r-h.right,vcenter:c,width:u,height:g});case\"end_start\":return new o.BBox({left:i+h.left,bottom:s-h.bottom,width:u,height:g});case\"end_center\":return new o.BBox({hcenter:a,bottom:s-h.bottom,width:u,height:g});case\"end_end\":return new o.BBox({right:r-h.right,bottom:s-h.bottom,width:u,height:g})}})(),m=null==_?w:new o.BBox({left:w.left+_.left,top:w.top+_.top,right:w.right-_.right,bottom:w.bottom-_.bottom});e.set_geometry(w,m)}}}h.NodeLayout=l,l.__name__=\"NodeLayout\"},\n", " function _(t,i,s,e,o){e();const n=t(141),l=t(142),r=t(8),h=t(99),c=t(9),{max:a,round:g}=Math;class p{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}p.__name__=\"DefaultMap\";class f{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=a(this._nrows,s+1),this._ncols=a(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter((({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1)).map((({data:t})=>t))}row(t){return this._items.filter((({span:i})=>i.r0<=t&&t<=i.r1)).map((({data:t})=>t))}col(t){return this._items.filter((({span:i})=>i.c0<=t&&t<=i.c1)).map((({data:t})=>t))}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new f;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}f.__name__=\"Container\";class _ extends l.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0}*[Symbol.iterator](){for(const{layout:t}of this.items)yield t}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return c.some(t,(t=>\"max\"==t.policy))}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return c.some(t,(t=>\"max\"==t.policy))}_init(){var t,i,s,e;super._init();const o=new f;for(const{layout:t,row:i,col:s,row_span:e,col_span:n}of this.items)if(t.sizing.visible){const l=i,r=s,h=i+(null!=e?e:1)-1,c=s+(null!=n?n:1)-1;o.add({r0:l,c0:r,r1:h,c1:c},t)}const{nrows:n,ncols:l}=o,h=new Array(n);for(let s=0;s{var t;const i=r.isPlainObject(this.rows)?null!==(t=this.rows[s])&&void 0!==t?t:this.rows[\"*\"]:this.rows;return null==i?{policy:\"auto\"}:r.isNumber(i)?{policy:\"fixed\",height:i}:r.isString(i)?{policy:i}:i})(),n=null!==(t=e.align)&&void 0!==t?t:\"auto\";if(\"fixed\"==e.policy)h[s]={policy:\"fixed\",height:e.height,align:n};else if(\"min\"==e.policy)h[s]={policy:\"min\",align:n};else if(\"fit\"==e.policy||\"max\"==e.policy)h[s]={policy:e.policy,flex:null!==(i=e.flex)&&void 0!==i?i:1,align:n};else{if(\"auto\"!=e.policy)throw new Error(\"unrechable\");c.some(o.row(s),(t=>t.is_height_expanding()))?h[s]={policy:\"max\",flex:1,align:n}:h[s]={policy:\"min\",align:n}}}const a=new Array(l);for(let t=0;t{var i;const s=r.isPlainObject(this.cols)?null!==(i=this.cols[t])&&void 0!==i?i:this.cols[\"*\"]:this.cols;return null==s?{policy:\"auto\"}:r.isNumber(s)?{policy:\"fixed\",width:s}:r.isString(s)?{policy:s}:s})(),n=null!==(s=i.align)&&void 0!==s?s:\"auto\";if(\"fixed\"==i.policy)a[t]={policy:\"fixed\",width:i.width,align:n};else if(\"min\"==i.policy)a[t]={policy:\"min\",align:n};else if(\"fit\"==i.policy||\"max\"==i.policy)a[t]={policy:i.policy,flex:null!==(e=i.flex)&&void 0!==e?e:1,align:n};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");c.some(o.col(t),(t=>t.is_width_expanding()))?a[t]={policy:\"max\",flex:1,align:n}:a[t]={policy:\"min\",align:n}}}const[g,p]=r.isNumber(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:o,nrows:n,ncols:l,rows:h,cols:a,rspacing:g,cspacing:p}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:c.sum(t)+(s-1)*o,width:c.sum(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:e,rows:o,cols:l,rspacing:r,cspacing:h}=this._state,c=new Array(s);for(let t=0;t{const{r0:e,c0:f,r1:d,c1:u}=i,w=(d-e)*r,m=(u-f)*h;let y=0;for(let i=e;i<=d;i++)y+=t(i,f).height;y+=w;let x=0;for(let i=f;i<=u;i++)x+=t(e,i).width;x+=m;const b=s.measure({width:x,height:y});_.add(i,{layout:s,size_hint:b});const z=new n.Sizeable(b).grow_by(s.sizing.margin);z.height-=w,z.width-=m;const v=[];for(let t=e;t<=d;t++){const i=o[t];\"fixed\"==i.policy?z.height-=i.height:v.push(t)}if(z.height>0){const t=g(z.height/v.length);for(const i of v)c[i]=a(c[i],t)}const j=[];for(let t=f;t<=u;t++){const i=l[t];\"fixed\"==i.policy?z.width-=i.width:j.push(t)}if(z.width>0){const t=g(z.width/j.length);for(const i of j)p[i]=a(p[i],t)}}));return{size:this._measure_totals(c,p),row_heights:c,col_widths:p,size_hints:_}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:l}=this._state,r=this._measure_cells(((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}}));let h;h=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:r.size.height;let c,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}c=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:r.size.width;let f=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:_,col_widths:d,size_hints:u}=this._measure_cells(((t,i)=>({width:r.col_widths[i],height:r.row_heights[t]})));return{size:this._measure_totals(_,d),row_heights:_,col_widths:d,size_hints:u}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:l,col_widths:r,size_hints:c}=this._measure_grid(t),f=this._state.rows.map(((t,i)=>Object.assign(Object.assign({},t),{top:0,height:l[i],get bottom(){return this.top+this.height}}))),_=this._state.cols.map(((t,i)=>Object.assign(Object.assign({},t),{left:0,width:r[i],get right(){return this.left+this.width}}))),d=c.map(((t,i)=>Object.assign(Object.assign({},i),{outer:new h.BBox,inner:new h.BBox})));for(let i=0,e=this.absolute?t.top:0;i{const{layout:r,size_hint:c}=l,{sizing:a}=r,{width:p,height:d}=c,u=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=_[e].width;return s}(i,e),w=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=f[e].height;return s}(t,s),m=i==e&&\"auto\"!=_[i].align?_[i].align:a.halign,y=t==s&&\"auto\"!=f[t].align?f[t].align:a.valign;let x=_[i].left;\"start\"==m?x+=a.margin.left:\"center\"==m?x+=g((u-p)/2):\"end\"==m&&(x+=u-a.margin.right-p);let b=f[t].top;\"start\"==y?b+=a.margin.top:\"center\"==y?b+=g((w-d)/2):\"end\"==y&&(b+=w-a.margin.bottom-d),l.outer=new h.BBox({left:x,top:b,width:p,height:d})}));const u=f.map((()=>({start:new p((()=>0)),end:new p((()=>0))}))),w=_.map((()=>({start:new p((()=>0)),end:new p((()=>0))})));d.foreach((({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:l}=o;null!=l&&(u[t].start.apply(n.top,(t=>a(t,l.top))),u[s].end.apply(f[s].bottom-n.bottom,(t=>a(t,l.bottom))),w[i].start.apply(n.left,(t=>a(t,l.left))),w[e].end.apply(_[e].right-n.right,(t=>a(t,l.right))))})),d.foreach((({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:l}=o,r=t=>{const i=this.absolute?l:l.relative(),s=i.left+t.left,e=i.top+t.top,o=i.right-t.right,n=i.bottom-t.bottom;return new h.BBox({left:s,top:e,right:o,bottom:n})};if(null!=n.inner){let h=r(n.inner);if(!1!==n.align){const o=u[t].start.get(l.top),n=u[s].end.get(f[s].bottom-l.bottom),c=w[i].start.get(l.left),a=w[e].end.get(_[e].right-l.right);try{h=r({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=h}else o.inner=l})),d.foreach(((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)}))}}s.Grid=_,_.__name__=\"Grid\";class d extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:0,col:i}))),this.rows=\"fit\"}}s.Row=d,d.__name__=\"Row\";class u extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:i,col:0}))),this.cols=\"fit\"}}s.Column=u,u.__name__=\"Column\"},\n", " function _(e,t,s,n,i){n();const a=e(142),c=e(141),o=e(43);class r extends a.ContentLayoutable{constructor(e){super(),this.content_size=o.unsized(e,(()=>new c.Sizeable(o.size(e))))}_content_size(){return this.content_size}}s.ContentBox=r,r.__name__=\"ContentBox\";class _ extends a.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new c.Sizeable(e).bounded_to(this.sizing.size);return o.sized(this.el,t,(()=>{const e=new c.Sizeable(o.content_size(this.el)),{border:t,padding:s}=o.extents(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)}))}}s.VariadicBox=_,_.__name__=\"VariadicBox\";class h extends _{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=h,h.__name__=\"CachedVariadicBox\"},\n", " function _(t,e,i,h,o){h();const s=t(141),r=t(142),n=t(99);class g extends r.Layoutable{constructor(){super(...arguments),this.min_border={left:0,top:0,right:0,bottom:0},this.padding={left:0,top:0,right:0,bottom:0}}*[Symbol.iterator](){yield this.top_panel,yield this.bottom_panel,yield this.left_panel,yield this.right_panel,yield this.center_panel}_measure(t){t=new s.Sizeable({width:\"fixed\"==this.sizing.width_policy||t.width==1/0?this.sizing.width:t.width,height:\"fixed\"==this.sizing.height_policy||t.height==1/0?this.sizing.height:t.height});const e=this.left_panel.measure({width:0,height:t.height}),i=Math.max(e.width,this.min_border.left)+this.padding.left,h=this.right_panel.measure({width:0,height:t.height}),o=Math.max(h.width,this.min_border.right)+this.padding.right,r=this.top_panel.measure({width:t.width,height:0}),n=Math.max(r.height,this.min_border.top)+this.padding.top,g=this.bottom_panel.measure({width:t.width,height:0}),a=Math.max(g.height,this.min_border.bottom)+this.padding.bottom,d=new s.Sizeable(t).shrink_by({left:i,right:o,top:n,bottom:a}),l=this.center_panel.measure(d);return{width:i+l.width+o,height:n+l.height+a,inner:{left:i,right:o,top:n,bottom:a},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const i=this.left_panel.measure({width:0,height:t.height}),h=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:r,top:g,right:a,bottom:d}=e;this.top_panel.set_geometry(new n.BBox({left:r,right:a,bottom:g,height:o.height})),this.bottom_panel.set_geometry(new n.BBox({left:r,right:a,top:d,height:s.height})),this.left_panel.set_geometry(new n.BBox({top:g,bottom:d,right:r,width:i.width})),this.right_panel.set_geometry(new n.BBox({top:g,bottom:d,left:a,width:h.width}))}}i.BorderLayout=g,g.__name__=\"BorderLayout\"},\n", " function _(t,e,i,s,n){s();const o=t(1),l=t(139),a=t(10),_=t(143),d=t(20),h=o.__importStar(t(48));class r extends l.TextAnnotationView{_get_size(){const{ctx:t}=this.layer;this.visuals.text.set_value(t);const{width:e}=t.measureText(this.model.text),{height:i}=_.font_metrics(t.font);return{width:e,height:i}}_render(){const{angle:t,angle_units:e}=this.model,i=a.resolve_angle(t,e),s=null!=this.layout?this.layout:this.plot_view.frame,n=this.coordinates.x_scale,o=this.coordinates.y_scale;let l=\"data\"==this.model.x_units?n.compute(this.model.x):s.bbox.xview.compute(this.model.x),_=\"data\"==this.model.y_units?o.compute(this.model.y):s.bbox.yview.compute(this.model.y);l+=this.model.x_offset,_-=this.model.y_offset;(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,this.model.text,l,_,i)}}i.LabelView=r,r.__name__=\"LabelView\";class c extends l.TextAnnotation{constructor(t){super(t)}static init_Label(){this.prototype.default_view=r,this.mixins([h.Text,[\"border_\",h.Line],[\"background_\",h.Fill]]),this.define((({Number:t,String:e,Angle:i})=>({x:[t],x_units:[d.SpatialUnits,\"data\"],y:[t],y_units:[d.SpatialUnits,\"data\"],text:[e,\"\"],angle:[i,0],angle_units:[d.AngleUnits,\"rad\"],x_offset:[t,0],y_offset:[t,0]}))),this.override({background_fill_color:null,border_line_color:null})}}i.Label=c,c.__name__=\"Label\",c.init_Label()},\n", " function _(t,e,s,i,o){i();const l=t(1),n=t(139),a=t(56),r=t(130),_=l.__importStar(t(48)),c=t(20),h=t(43),d=l.__importStar(t(18)),u=t(143);class x extends n.TextAnnotationView{set_data(t){a.DataAnnotationView.prototype.set_data.call(this,t)}initialize(){if(super.initialize(),this.set_data(this.model.source),\"css\"==this.model.render_mode)for(let t=0,e=this.text.length;t{this.set_data(this.model.source),\"css\"==this.model.render_mode?this.render():this.request_render()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}_calculate_text_dimensions(t,e){const{width:s}=t.measureText(e),{height:i}=u.font_metrics(this.visuals.text.font_value(0));return[s,i]}_map_data(){const t=this.coordinates.x_scale,e=this.coordinates.y_scale,s=null!=this.layout?this.layout:this.plot_view.frame;return[\"data\"==this.model.x_units?t.v_compute(this._x):s.bbox.xview.v_compute(this._x),\"data\"==this.model.y_units?e.v_compute(this._y):s.bbox.yview.v_compute(this._y)]}_render(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer,[s,i]=this._map_data();for(let o=0,l=this.text.length;o({x:[d.XCoordinateSpec,{field:\"x\"}],y:[d.YCoordinateSpec,{field:\"y\"}],x_units:[c.SpatialUnits,\"data\"],y_units:[c.SpatialUnits,\"data\"],text:[d.StringSpec,{field:\"text\"}],angle:[d.AngleSpec,0],x_offset:[d.NumberSpec,{value:0}],y_offset:[d.NumberSpec,{value:0}],source:[t(r.ColumnDataSource),()=>new r.ColumnDataSource]}))),this.override({background_fill_color:null,border_line_color:null})}}s.LabelSet=v,v.__name__=\"LabelSet\",v.init_LabelSet()},\n", " function _(t,e,i,s,l){s();const n=t(1),h=t(40),o=t(229),a=t(20),_=n.__importStar(t(48)),r=t(15),d=t(140),c=t(143),g=t(99),m=t(9),b=t(8),f=t(11);class u extends h.AnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new d.SideLayout(t,(()=>this.get_size())):void 0}cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.model.border_line_color?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.item_change,(()=>this.request_render()))}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:s,label_width:l}=this.model;this.max_label_height=m.max([c.font_metrics(this.visuals.label_text.font_value()).height,s,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,m.max([n.measureText(e).width,l]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?c.font_metrics(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const h=Math.max(m.max([...this.text_widths.values()]),0),o=this.model.margin,{legend_padding:a}=this,_=this.model.spacing,{label_standoff:r}=this.model;let d,u;if(\"vertical\"==this.model.orientation)d=t.length*this.max_label_height+Math.max(t.length-1,0)*_+2*a+this.title_height,u=m.max([h+i+r+2*a,this.title_width+2*a]);else{let e=2*a+Math.max(t.length-1,0)*_;for(const[,t]of this.text_widths)e+=m.max([t,l])+i+r;u=m.max([this.title_width+2*a,e]),d=this.max_label_height+this.title_height+2*a}const x=null!=this.layout?this.layout:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if(b.isString(v))switch(v){case\"top_left\":y=p.start+o,k=w.start+o;break;case\"top\":case\"top_center\":y=(p.end+p.start)/2-u/2,k=w.start+o;break;case\"top_right\":y=p.end-o-u,k=w.start+o;break;case\"bottom_right\":y=p.end-o-u,k=w.end-o-d;break;case\"bottom\":case\"bottom_center\":y=(p.end+p.start)/2-u/2,k=w.end-o-d;break;case\"bottom_left\":y=p.start+o,k=w.end-o-d;break;case\"left\":case\"center_left\":y=p.start+o,k=(w.end+w.start)/2-d/2;break;case\"center\":case\"center_center\":y=(p.end+p.start)/2-u/2,k=(w.end+w.start)/2-d/2;break;case\"right\":case\"center_right\":y=p.end-o-u,k=(w.end+w.start)/2-d/2}else if(b.isArray(v)&&2==v.length){const[t,e]=v;y=x.bbox.xview.compute(t),k=x.bbox.yview.compute(e)-d}else f.unreachable();return new g.BBox({left:y,top:k,width:u,height:d})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:s}=this.model,{legend_padding:l}=this,n=this.model.spacing,{label_standoff:h}=this.model;let o=i=l;const a=this.compute_legend_bbox(),_=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop();for(const c of d){const d=a.x+o,m=a.y+i+this.title_height;let b,f;[b,f]=_?[a.width-2*l,this.max_label_height]:[this.text_widths.get(c)+s+h,this.max_label_height];if(new g.BBox({left:d,top:m,width:b,height:f}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of r.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of r.renderers)t.muted=!t.muted}return!0}_?i+=this.max_label_height+n:o+=this.text_widths.get(c)+s+h+n}}return!1}_render(){if(0==this.model.items.length)return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.set_value(t),t.fill(),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.stroke())}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:s}=this.model,{legend_padding:l}=this,n=this.model.spacing,{label_standoff:h}=this.model;let o=l,a=l;const _=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop(),c=r.get_field_from_label_prop();if(0==d.length)continue;const g=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return m.every(r.renderers,(t=>t.visible));case\"mute\":return m.every(r.renderers,(t=>!t.muted))}})();for(const m of d){const d=e.x+o,b=e.y+a+this.title_height,f=d+i,u=b+s;_?a+=this.max_label_height+n:o+=this.text_widths.get(m)+i+h+n,this.visuals.label_text.set_value(t),t.fillText(m,f+h,b+this.max_label_height/2);for(const e of r.renderers){const i=this.plot_view.renderer_view(e);null==i||i.draw_legend(t,d,f,b,u,c,m,r.index)}if(!g){let s,n;[s,n]=_?[e.width-2*l,this.max_label_height]:[this.text_widths.get(m)+i+h,this.max_label_height],t.beginPath(),t.rect(d,b,s,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){const{title:i}=this.model;i&&this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(i,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=u,u.__name__=\"LegendView\";class x extends h.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new r.Signal0(this,\"item_change\")}static init_Legend(){this.prototype.default_view=u,this.mixins([[\"label_\",_.Text],[\"title_\",_.Text],[\"inactive_\",_.Fill],[\"border_\",_.Line],[\"background_\",_.Fill]]),this.define((({Number:t,String:e,Array:i,Tuple:s,Or:l,Ref:n,Nullable:h})=>({orientation:[a.Orientation,\"vertical\"],location:[l(a.LegendLocation,s(t,t)),\"top_right\"],title:[h(e),null],title_standoff:[t,5],label_standoff:[t,5],glyph_height:[t,20],glyph_width:[t,20],label_height:[t,20],label_width:[t,20],margin:[t,10],padding:[t,10],spacing:[t,3],items:[i(n(o.LegendItem)),[]],click_policy:[a.LegendClickPolicy,\"none\"]}))),this.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=x,x.__name__=\"Legend\",x.init_Legend()},\n", " function _(e,r,n,l,t){l();const i=e(1),s=e(53),o=e(61),_=e(57),a=e(230),u=i.__importStar(e(18)),d=e(19),c=e(9);class f extends s.Model{constructor(e){super(e)}static init_LegendItem(){this.define((({Int:e,Array:r,Ref:n,Nullable:l})=>({label:[u.NullStringSpec,null],renderers:[r(n(o.GlyphRenderer)),[]],index:[l(e),null]})))}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!c.includes(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,(()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()}));this._check_data_sources_on_renderers()||d.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||d.logger.error(`Bad column name on label: ${this.label}`)}get_field_from_label_prop(){const{label:e}=this;return a.isField(e)?e.field:null}get_labels_list_from_label_prop(){if(a.isValue(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof _.ColumnarDataSource){const n=r.get_column(e);return null!=n?c.uniq(Array.from(n)):[\"Invalid field\"]}}return[]}}n.LegendItem=f,f.__name__=\"LegendItem\",f.init_LegendItem()},\n", " function _(i,n,e,t,u){t();const c=i(8);e.isValue=function(i){return c.isPlainObject(i)&&\"value\"in i},e.isField=function(i){return c.isPlainObject(i)&&\"field\"in i},e.isExpr=function(i){return c.isPlainObject(i)&&\"expr\"in i}},\n", " function _(t,i,s,n,e){n();const o=t(1),l=t(40),a=o.__importStar(t(48)),c=t(20);class h extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{xs:t,ys:i}=this.model;if(t.length!=i.length)return;const s=t.length;if(s<3)return;const{frame:n}=this.plot_view,{ctx:e}=this.layer,o=this.coordinates.x_scale,l=this.coordinates.y_scale,{screen:a}=this.model;function c(t,i,s,n){return a?t:\"data\"==i?s.v_compute(t):n.v_compute(t)}const h=c(t,this.model.xs_units,o,n.bbox.xview),r=c(i,this.model.ys_units,l,n.bbox.yview);e.beginPath();for(let t=0;t({xs:[i(t),[]],xs_units:[c.SpatialUnits,\"data\"],ys:[i(t),[]],ys_units:[c.SpatialUnits,\"data\"]}))),this.internal((({Boolean:t})=>({screen:[t,!1]}))),this.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})}update({xs:t,ys:i}){this.setv({xs:t,ys:i,screen:!0},{check_eq:!1})}}s.PolyAnnotation=r,r.__name__=\"PolyAnnotation\",r.init_PolyAnnotation()},\n", " function _(e,t,i,n,o){n();const s=e(1),l=e(40),r=s.__importStar(e(48));class c extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{gradient:e,y_intercept:t}=this.model;if(null==e||null==t)return;const{frame:i}=this.plot_view,n=this.coordinates.x_scale,o=this.coordinates.y_scale;let s,l,r,c;if(0==e)s=o.compute(t),l=s,r=i.bbox.left,c=r+i.bbox.width;else{s=i.bbox.top,l=s+i.bbox.height;const a=(o.invert(s)-t)/e,_=(o.invert(l)-t)/e;r=n.compute(a),c=n.compute(_)}const{ctx:a}=this.layer;a.save(),a.beginPath(),this.visuals.line.set_value(a),a.moveTo(r,s),a.lineTo(c,l),a.stroke(),a.restore()}}i.SlopeView=c,c.__name__=\"SlopeView\";class a extends l.Annotation{constructor(e){super(e)}static init_Slope(){this.prototype.default_view=c,this.mixins(r.Line),this.define((({Number:e,Nullable:t})=>({gradient:[t(e),null],y_intercept:[t(e),null]}))),this.override({line_color:\"black\"})}}i.Slope=a,a.__name__=\"Slope\",a.init_Slope()},\n", " function _(e,i,t,n,o){n();const s=e(1),a=e(40),l=s.__importStar(e(48)),h=e(20);class c extends a.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_paint(this)))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:i}=this.plot_view,t=this.coordinates.x_scale,n=this.coordinates.y_scale,o=(i,t)=>\"data\"==this.model.location_units?i.compute(e):this.model.for_hover?e:t.compute(e);let s,a,l,h;\"width\"==this.model.dimension?(l=o(n,i.bbox.yview),a=i.bbox.left,h=i.bbox.width,s=this.model.line_width):(l=i.bbox.top,a=o(t,i.bbox.xview),h=this.model.line_width,s=i.bbox.height);const{ctx:c}=this.layer;c.save(),c.beginPath(),this.visuals.line.set_value(c),c.moveTo(a,l),\"width\"==this.model.dimension?c.lineTo(a+h,l):c.lineTo(a,l+s),c.stroke(),c.restore()}}t.SpanView=c,c.__name__=\"SpanView\";class d extends a.Annotation{constructor(e){super(e)}static init_Span(){this.prototype.default_view=c,this.mixins(l.Line),this.define((({Number:e,Nullable:i})=>({render_mode:[h.RenderMode,\"canvas\"],location:[i(e),null],location_units:[h.SpatialUnits,\"data\"],dimension:[h.Dimension,\"width\"]}))),this.internal((({Boolean:e})=>({for_hover:[e,!1]}))),this.override({line_color:\"black\"})}}t.Span=d,d.__name__=\"Span\",d.init_Span()},\n", " function _(i,e,t,o,l){o();const s=i(40),a=i(235),n=i(122),r=i(43),_=i(140),h=i(99);class b extends s.AnnotationView{constructor(){super(...arguments),this._invalidate_toolbar=!0,this._previous_bbox=new h.BBox}update_layout(){this.layout=new _.SideLayout(this.panel,(()=>this.get_size()),!0)}initialize(){super.initialize(),this.el=r.div(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){await super.lazy_initialize(),this._toolbar_view=await n.build_view(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push((i=>this._toolbar_view.set_visibility(i)))}remove(){this._toolbar_view.remove(),r.remove(this.el),super.remove()}render(){this.model.visible||r.undisplay(this.el),super.render()}_render(){const{bbox:i}=this.layout;this._previous_bbox.equals(i)||(r.position(this.el,i),this._previous_bbox=i),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",this._toolbar_view.render(),r.empty(this.el),this.el.appendChild(this._toolbar_view.el),this._invalidate_toolbar=!1),r.display(this.el)}_get_size(){const{tools:i,logo:e}=this.model.toolbar;return{width:30*i.length+(null!=e?25:0),height:30}}}t.ToolbarPanelView=b,b.__name__=\"ToolbarPanelView\";class d extends s.Annotation{constructor(i){super(i)}static init_ToolbarPanel(){this.prototype.default_view=b,this.define((({Ref:i})=>({toolbar:[i(a.Toolbar)]})))}}t.ToolbarPanel=d,d.__name__=\"ToolbarPanel\",d.init_ToolbarPanel()},\n", " function _(t,s,e,i,o){i();const c=t(8),n=t(9),a=t(13),l=t(236),r=t(237),_=t(247),p=t(248);e.Drag=l.Tool,e.Inspection=l.Tool,e.Scroll=l.Tool,e.Tap=l.Tool;const u=t=>{switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null},h=t=>\"tap\"==t||\"pan\"==t;class v extends p.ToolbarBase{constructor(t){super(t)}static init_Toolbar(){this.prototype.default_view=p.ToolbarBaseView,this.define((({Or:t,Ref:s,Auto:i,Null:o,Nullable:c})=>({active_drag:[t(s(e.Drag),i,o),\"auto\"],active_inspect:[t(s(e.Inspection),i,o),\"auto\"],active_scroll:[t(s(e.Scroll),i,o),\"auto\"],active_tap:[t(s(e.Tap),i,o),\"auto\"],active_multi:[c(s(r.GestureTool)),null]})))}connect_signals(){super.connect_signals();const{tools:t,active_drag:s,active_inspect:e,active_scroll:i,active_tap:o,active_multi:c}=this.properties;this.on_change([t,s,e,i,o,c],(()=>this._init_tools()))}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof _.InspectTool){let t=!1;for(const s of this.inspectors)s!=this.active_inspect?s.active=!1:t=!0;t||(this.active_inspect=null)}else if(c.isArray(this.active_inspect)){const t=n.intersection(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)n.includes(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of a.values(this.gestures)){t.tools=n.sort_by(t.tools,(t=>t.default_order));for(const s of t.tools)this.connect(s.properties.active.change,(()=>this._active_change(s)))}for(const[s,e]of a.entries(this.gestures)){const i=u(s);if(i){const o=this[i];\"auto\"==o?0!=e.tools.length&&h(s)&&t(e.tools[0]):null!=o&&(n.includes(this.tools,o)?t(o):this[i]=null)}}}}e.Toolbar=v,v.__name__=\"Toolbar\",v.init_Toolbar()},\n", " function _(t,e,n,i,o){i();const s=t(42),a=t(9),r=t(53);class l extends s.View{get plot_view(){return this.parent}get plot_model(){return this.parent.model}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>{this.model.active?this.activate():this.deactivate()}))}activate(){}deactivate(){}}n.ToolView=l,l.__name__=\"ToolView\";class _ extends r.Model{constructor(t){super(t)}static init_Tool(){this.prototype._known_aliases=new Map,this.define((({String:t,Nullable:e})=>({description:[e(t),null]}))),this.internal((({Boolean:t})=>({active:[t,!1]})))}get synthetic_renderers(){return[]}_get_dim_limits([t,e],[n,i],o,s){const r=o.bbox.h_range;let l;\"width\"==s||\"both\"==s?(l=[a.min([t,n]),a.max([t,n])],l=[a.max([l[0],r.start]),a.min([l[1],r.end])]):l=[r.start,r.end];const _=o.bbox.v_range;let c;return\"height\"==s||\"both\"==s?(c=[a.min([e,i]),a.max([e,i])],c=[a.max([c[0],_.start]),a.min([c[1],_.end])]):c=[_.start,_.end],[l,c]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}n.Tool=_,_.__name__=\"Tool\",_.init_Tool()},\n", " function _(e,o,t,s,n){s();const u=e(238),_=e(246);class l extends u.ButtonToolView{}t.GestureToolView=l,l.__name__=\"GestureToolView\";class i extends u.ButtonTool{constructor(e){super(e),this.button_view=_.OnOffButtonView}}t.GestureTool=i,i.__name__=\"GestureTool\"},\n", " function _(t,e,o,i,s){i();const n=t(1),l=n.__importDefault(t(239)),r=t(240),a=t(236),u=t(43),h=t(34),_=t(8),c=t(9),d=n.__importStar(t(241)),m=d,p=n.__importDefault(t(242)),g=n.__importDefault(t(243)),v=t(244);class f extends r.DOMView{initialize(){super.initialize();const t=this.model.menu;if(null!=t){const e=this.parent.model.toolbar_location,o=\"left\"==e||\"above\"==e,i=this.parent.model.horizontal?\"vertical\":\"horizontal\";this._menu=new v.ContextMenu(o?c.reversed(t):t,{orientation:i,prevent_hide:t=>t.target==this.el})}this._hammer=new l.default(this.el,{touchAction:\"auto\",inputClass:l.default.TouchMouseInput}),this.connect(this.model.change,(()=>this.render())),this._hammer.on(\"tap\",(t=>{var e;(null===(e=this._menu)||void 0===e?void 0:e.is_open)?this._menu.hide():t.target==this.el&&this._clicked()})),this._hammer.on(\"press\",(()=>this._pressed()))}remove(){var t;this._hammer.destroy(),null===(t=this._menu)||void 0===t||t.remove(),super.remove()}styles(){return[...super.styles(),d.default,p.default,g.default]}css_classes(){return super.css_classes().concat(m.toolbar_button)}render(){u.empty(this.el);const t=this.model.computed_icon;_.isString(t)&&(h.startsWith(t,\"data:image\")?this.el.style.backgroundImage=\"url('\"+t+\"')\":this.el.classList.add(t)),this.el.title=this.model.tooltip,null!=this._menu&&this.root.el.appendChild(this._menu.el)}_pressed(){var t;const{left:e,top:o,right:i,bottom:s}=this.el.getBoundingClientRect(),n=(()=>{switch(this.parent.model.toolbar_location){case\"right\":return{right:e,top:o};case\"left\":return{left:i,top:o};case\"above\":return{left:e,top:s};case\"below\":return{left:e,bottom:o}}})();null===(t=this._menu)||void 0===t||t.toggle(n)}}o.ButtonToolButtonView=f,f.__name__=\"ButtonToolButtonView\";class b extends a.ToolView{}o.ButtonToolView=b,b.__name__=\"ButtonToolView\";class B extends a.Tool{constructor(t){super(t)}static init_ButtonTool(){this.internal((({Boolean:t})=>({disabled:[t,!1]})))}_get_dim_tooltip(t){const{description:e,tool_name:o}=this;return null!=e?e:\"both\"==t?o:`${o} (${\"width\"==t?\"x\":\"y\"}-axis)`}get tooltip(){var t;return null!==(t=this.description)&&void 0!==t?t:this.tool_name}get computed_icon(){return this.icon}get menu(){return null}}o.ButtonTool=B,B.__name__=\"ButtonTool\",B.init_ButtonTool()},\n", " function _(t,e,i,n,r){\n", " /*! Hammer.JS - v2.0.7 - 2016-04-22\n", " * http://hammerjs.github.io/\n", " *\n", " * Copyright (c) 2016 Jorik Tangelder;\n", " * Licensed under the MIT license */\n", " !function(t,i,n,r){\"use strict\";var s,o=[\"\",\"webkit\",\"Moz\",\"MS\",\"ms\",\"o\"],a=i.createElement(\"div\"),h=Math.round,u=Math.abs,c=Date.now;function l(t,e,i){return setTimeout(T(t,i),e)}function p(t,e,i){return!!Array.isArray(t)&&(f(t,i[e],i),!0)}function f(t,e,i){var n;if(t)if(t.forEach)t.forEach(e,i);else if(t.length!==r)for(n=0;n\\s*\\(/gm,\"{anonymous}()@\"):\"Unknown Stack Trace\",s=t.console&&(t.console.warn||t.console.log);return s&&s.call(t.console,r,n),e.apply(this,arguments)}}s=\"function\"!=typeof Object.assign?function(t){if(t===r||null===t)throw new TypeError(\"Cannot convert undefined or null to object\");for(var e=Object(t),i=1;i-1}function S(t){return t.trim().split(/\\s+/g)}function b(t,e,i){if(t.indexOf&&!i)return t.indexOf(e);for(var n=0;ni[e]})):n.sort()),n}function x(t,e){for(var i,n,s=e[0].toUpperCase()+e.slice(1),a=0;a1&&!i.firstMultiple?i.firstMultiple=H(e):1===s&&(i.firstMultiple=!1);var o=i.firstInput,a=i.firstMultiple,h=a?a.center:o.center,l=e.center=L(n);e.timeStamp=c(),e.deltaTime=e.timeStamp-o.timeStamp,e.angle=G(h,l),e.distance=j(h,l),function(t,e){var i=e.center,n=t.offsetDelta||{},r=t.prevDelta||{},s=t.prevInput||{};1!==e.eventType&&4!==s.eventType||(r=t.prevDelta={x:s.deltaX||0,y:s.deltaY||0},n=t.offsetDelta={x:i.x,y:i.y});e.deltaX=r.x+(i.x-n.x),e.deltaY=r.y+(i.y-n.y)}(i,e),e.offsetDirection=V(e.deltaX,e.deltaY);var p=U(e.deltaTime,e.deltaX,e.deltaY);e.overallVelocityX=p.x,e.overallVelocityY=p.y,e.overallVelocity=u(p.x)>u(p.y)?p.x:p.y,e.scale=a?(f=a.pointers,v=n,j(v[0],v[1],W)/j(f[0],f[1],W)):1,e.rotation=a?function(t,e){return G(e[1],e[0],W)+G(t[1],t[0],W)}(a.pointers,n):0,e.maxPointers=i.prevInput?e.pointers.length>i.prevInput.maxPointers?e.pointers.length:i.prevInput.maxPointers:e.pointers.length,function(t,e){var i,n,s,o,a=t.lastInterval||e,h=e.timeStamp-a.timeStamp;if(8!=e.eventType&&(h>25||a.velocity===r)){var c=e.deltaX-a.deltaX,l=e.deltaY-a.deltaY,p=U(h,c,l);n=p.x,s=p.y,i=u(p.x)>u(p.y)?p.x:p.y,o=V(c,l),t.lastInterval=e}else i=a.velocity,n=a.velocityX,s=a.velocityY,o=a.direction;e.velocity=i,e.velocityX=n,e.velocityY=s,e.direction=o}(i,e);var f,v;var d=t.element;_(e.srcEvent.target,d)&&(d=e.srcEvent.target);e.target=d}(t,i),t.emit(\"hammer.input\",i),t.recognize(i),t.session.prevInput=i}function H(t){for(var e=[],i=0;i=u(e)?t<0?2:4:e<0?8:16}function j(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return Math.sqrt(n*n+r*r)}function G(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return 180*Math.atan2(r,n)/Math.PI}q.prototype={handler:function(){},init:function(){this.evEl&&I(this.element,this.evEl,this.domHandler),this.evTarget&&I(this.target,this.evTarget,this.domHandler),this.evWin&&I(O(this.element),this.evWin,this.domHandler)},destroy:function(){this.evEl&&A(this.element,this.evEl,this.domHandler),this.evTarget&&A(this.target,this.evTarget,this.domHandler),this.evWin&&A(O(this.element),this.evWin,this.domHandler)}};var Z={mousedown:1,mousemove:2,mouseup:4},B=\"mousedown\",$=\"mousemove mouseup\";function J(){this.evEl=B,this.evWin=$,this.pressed=!1,q.apply(this,arguments)}g(J,q,{handler:function(t){var e=Z[t.type];1&e&&0===t.button&&(this.pressed=!0),2&e&&1!==t.which&&(e=4),this.pressed&&(4&e&&(this.pressed=!1),this.callback(this.manager,e,{pointers:[t],changedPointers:[t],pointerType:X,srcEvent:t}))}});var K={pointerdown:1,pointermove:2,pointerup:4,pointercancel:8,pointerout:8},Q={2:N,3:\"pen\",4:X,5:\"kinect\"},tt=\"pointerdown\",et=\"pointermove pointerup pointercancel\";function it(){this.evEl=tt,this.evWin=et,q.apply(this,arguments),this.store=this.manager.session.pointerEvents=[]}t.MSPointerEvent&&!t.PointerEvent&&(tt=\"MSPointerDown\",et=\"MSPointerMove MSPointerUp MSPointerCancel\"),g(it,q,{handler:function(t){var e=this.store,i=!1,n=t.type.toLowerCase().replace(\"ms\",\"\"),r=K[n],s=Q[t.pointerType]||t.pointerType,o=s==N,a=b(e,t.pointerId,\"pointerId\");1&r&&(0===t.button||o)?a<0&&(e.push(t),a=e.length-1):12&r&&(i=!0),a<0||(e[a]=t,this.callback(this.manager,r,{pointers:e,changedPointers:[t],pointerType:s,srcEvent:t}),i&&e.splice(a,1))}});var nt={touchstart:1,touchmove:2,touchend:4,touchcancel:8},rt=\"touchstart\",st=\"touchstart touchmove touchend touchcancel\";function ot(){this.evTarget=rt,this.evWin=st,this.started=!1,q.apply(this,arguments)}function at(t,e){var i=P(t.touches),n=P(t.changedTouches);return 12&e&&(i=D(i.concat(n),\"identifier\",!0)),[i,n]}g(ot,q,{handler:function(t){var e=nt[t.type];if(1===e&&(this.started=!0),this.started){var i=at.call(this,t,e);12&e&&i[0].length-i[1].length==0&&(this.started=!1),this.callback(this.manager,e,{pointers:i[0],changedPointers:i[1],pointerType:N,srcEvent:t})}}});var ht={touchstart:1,touchmove:2,touchend:4,touchcancel:8},ut=\"touchstart touchmove touchend touchcancel\";function ct(){this.evTarget=ut,this.targetIds={},q.apply(this,arguments)}function lt(t,e){var i=P(t.touches),n=this.targetIds;if(3&e&&1===i.length)return n[i[0].identifier]=!0,[i,i];var r,s,o=P(t.changedTouches),a=[],h=this.target;if(s=i.filter((function(t){return _(t.target,h)})),1===e)for(r=0;r-1&&n.splice(t,1)}),2500)}}function dt(t){for(var e=t.srcEvent.clientX,i=t.srcEvent.clientY,n=0;n-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){var e=this,i=this.state;function n(i){e.manager.emit(i,t)}i<8&&n(e.options.event+Dt(i)),n(e.options.event),t.additionalEvent&&n(t.additionalEvent),i>=8&&n(e.options.event+Dt(i))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=bt},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return Ot.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=xt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(Mt,Ot,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(zt,Pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[yt]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distancee.time;if(this._input=t,!n||!i||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return bt},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Nt,Ot,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(Xt,Ot,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return Rt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&Y&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(Yt,Pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[Et]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance .bk-divider{cursor:default;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-context-menu.bk-horizontal > .bk-divider{width:1px;margin:5px 0;}.bk-root .bk-context-menu.bk-vertical > .bk-divider{height:1px;margin:0 5px;}.bk-root .bk-context-menu > :not(.bk-divider){border:1px solid transparent;}.bk-root .bk-context-menu > :not(.bk-divider).bk-active{border-color:#26aae1;}.bk-root .bk-context-menu > :not(.bk-divider):hover{background-color:#f9f9f9;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child{border-top-left-radius:4px;border-bottom-left-radius:4px;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child{border-top-right-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child{border-top-left-radius:4px;border-top-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child{border-bottom-left-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-menu{position:absolute;left:0;width:100%;z-index:100;cursor:pointer;font-size:12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;box-shadow:0 6px 12px rgba(0, 0, 0, 0.175);}.bk-root .bk-menu.bk-above{bottom:100%;}.bk-root .bk-menu.bk-below{top:100%;}.bk-root .bk-menu > .bk-divider{height:1px;margin:7.5px 0;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-menu > :not(.bk-divider){padding:6px 12px;}.bk-root .bk-menu > :not(.bk-divider):hover,.bk-root .bk-menu > :not(.bk-divider).bk-active{background-color:#e6e6e6;}.bk-root .bk-caret{display:inline-block;vertical-align:middle;width:0;height:0;margin:0 5px;}.bk-root .bk-caret.bk-down{border-top:4px solid;}.bk-root .bk-caret.bk-up{border-bottom:4px solid;}.bk-root .bk-caret.bk-down,.bk-root .bk-caret.bk-up{border-right:4px solid transparent;border-left:4px solid transparent;}.bk-root .bk-caret.bk-left{border-right:4px solid;}.bk-root .bk-caret.bk-right{border-left:4px solid;}.bk-root .bk-caret.bk-left,.bk-root .bk-caret.bk-right{border-top:4px solid transparent;border-bottom:4px solid transparent;}\"},\n", " function _(t,e,i,n,s){n();const o=t(1),l=t(43),h=t(245),d=o.__importStar(t(243));class r{constructor(t,e={}){this.items=t,this.options=e,this.el=l.div(),this._open=!1,this._item_click=t=>{var e;null===(e=this.items[t])||void 0===e||e.handler(),this.hide()},this._on_mousedown=t=>{var e,i;const{target:n}=t;n instanceof Node&&this.el.contains(n)||(null===(i=(e=this.options).prevent_hide)||void 0===i?void 0:i.call(e,t))||this.hide()},this._on_keydown=t=>{t.keyCode==l.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},l.undisplay(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){l.remove(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=e.getBoundingClientRect();this.el.style.left=null!=t.left?t.left-i.left+\"px\":\"\",this.el.style.top=null!=t.top?t.top-i.top+\"px\":\"\",this.el.style.right=null!=t.right?i.right-t.right+\"px\":\"\",this.el.style.bottom=null!=t.bottom?i.bottom-t.bottom+\"px\":\"\"}}render(){var t,e;l.empty(this.el,!0);const i=null!==(t=this.options.orientation)&&void 0!==t?t:\"vertical\";l.classes(this.el).add(\"bk-context-menu\",`bk-${i}`);for(const[t,i]of h.enumerate(this.items)){let n;if(null==t)n=l.div({class:d.divider});else{if(null!=t.if&&!t.if())continue;{const i=null!=t.icon?l.div({class:[\"bk-menu-icon\",t.icon]}):null;n=l.div({class:(null===(e=t.active)||void 0===e?void 0:e.call(t))?\"bk-active\":null,title:t.tooltip},i,t.label)}}n.addEventListener(\"click\",(()=>this._item_click(i))),this.el.appendChild(n)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),l.display(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),l.undisplay(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=r,r.__name__=\"ContextMenu\"},\n", " function _(n,e,o,t,r){t();const f=n(9);function*i(n,e){const o=n.length;if(e>o)return;const t=f.range(e);for(yield t.map((e=>n[e]));;){let r;for(const n of f.reversed(f.range(e)))if(t[n]!=n+o-e){r=n;break}if(null==r)return;t[r]+=1;for(const n of f.range(r+1,e))t[n]=t[n-1]+1;yield t.map((e=>n[e]))}}o.enumerate=function*(n){let e=0;for(const o of n)yield[o,e++]},o.combinations=i,o.subsets=function*(n){for(const e of f.range(n.length+1))yield*i(n,e)}},\n", " function _(t,e,i,n,o){n();const s=t(1),c=t(238),l=s.__importStar(t(241)),a=t(43);class _ extends c.ButtonToolButtonView{render(){super.render(),a.classes(this.el).toggle(l.active,this.model.active)}_clicked(){const{active:t}=this.model;this.model.active=!t}}i.OnOffButtonView=_,_.__name__=\"OnOffButtonView\"},\n", " function _(t,e,o,n,s){n();const i=t(238),c=t(246);class l extends i.ButtonToolView{}o.InspectToolView=l,l.__name__=\"InspectToolView\";class _ extends i.ButtonTool{constructor(t){super(t),this.event_type=\"move\"}static init_InspectTool(){this.prototype.button_view=c.OnOffButtonView,this.define((({Boolean:t})=>({toggleable:[t,!0]}))),this.override({active:!0})}}o.InspectTool=_,_.__name__=\"InspectTool\",_.init_InspectTool()},\n", " function _(t,o,e,i,s){i();const l=t(1),n=t(19),a=t(43),r=t(122),c=t(240),_=t(20),u=t(9),h=t(13),v=t(8),p=t(249),d=t(99),b=t(53),g=t(236),f=t(237),m=t(251),w=t(252),y=t(247),T=l.__importStar(t(241)),z=T,B=l.__importStar(t(253)),x=B;class L extends b.Model{constructor(t){super(t)}static init_ToolbarViewModel(){this.define((({Boolean:t,Nullable:o})=>({_visible:[o(t),null],autohide:[t,!1]})))}get visible(){return!this.autohide||null!=this._visible&&this._visible}}e.ToolbarViewModel=L,L.__name__=\"ToolbarViewModel\",L.init_ToolbarViewModel();class M extends c.DOMView{constructor(){super(...arguments),this.layout={bbox:new d.BBox}}initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new L({autohide:this.model.autohide})}async lazy_initialize(){await super.lazy_initialize(),await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,(async()=>{await this._build_tool_button_views(),this.render()})),this.connect(this.model.properties.autohide.change,(()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()})),this.connect(this._toolbar_view_model.properties._visible.change,(()=>this._on_visible_change()))}styles(){return[...super.styles(),T.default,B.default]}remove(){r.remove_views(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await r.build_views(this._tool_button_views,t,{parent:this},(t=>t.button_view))}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const t=this._toolbar_view_model.visible,o=z.toolbar_hidden;this.el.classList.contains(o)&&t?this.el.classList.remove(o):t||this.el.classList.add(o)}render(){if(a.empty(this.el),this.el.classList.add(z.toolbar),this.el.classList.add(z[this.model.toolbar_location]),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change(),null!=this.model.logo){const t=\"grey\"===this.model.logo?x.grey:null,o=a.a({href:\"https://bokeh.org/\",target:\"_blank\",class:[x.logo,x.logo_small,t]});this.el.appendChild(o)}for(const[,t]of this._tool_button_views)t.render();const t=[],o=t=>this._tool_button_views.get(t).el,{gestures:e}=this.model;for(const i of h.values(e))t.push(i.tools.map(o));t.push(this.model.actions.map(o)),t.push(this.model.inspectors.filter((t=>t.toggleable)).map(o));for(const o of t)if(0!==o.length){const t=a.div({class:z.button_bar},o);this.el.appendChild(t)}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}export(t,o=!0){const e=\"png\"==t?\"canvas\":\"svg\",i=new p.CanvasLayer(e,o);return i.resize(0,0),i}}function V(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=M,M.__name__=\"ToolbarBaseView\";class S extends b.Model{constructor(t){super(t)}static init_ToolbarBase(){this.prototype.default_view=M,this.define((({Boolean:t,Array:o,Ref:e,Nullable:i})=>({tools:[o(e(g.Tool)),[]],logo:[i(_.Logo),\"normal\"],autohide:[t,!1]}))),this.internal((({Array:t,Struct:o,Ref:e,Nullable:i})=>{const s=o({tools:t(e(f.GestureTool)),active:i(e(g.Tool))});return{gestures:[o({pan:s,scroll:s,pinch:s,tap:s,doubletap:s,press:s,pressup:s,rotate:s,move:s,multi:s}),V],actions:[t(e(m.ActionTool)),[]],inspectors:[t(e(y.InspectTool)),[]],help:[t(e(w.HelpTool)),[]],toolbar_location:[_.Location,\"right\"]}}))}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map((t=>t.id)));return u.some(t,(t=>!e.has(t.id)))},o=this.tools.filter((t=>t instanceof y.InspectTool));t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter((t=>t instanceof w.HelpTool));t(this.help,e)&&(this.help=e);const i=this.tools.filter((t=>t instanceof m.ActionTool));t(this.actions,i)&&(this.actions=i);const s=(t,o)=>{t in this.gestures||n.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},l={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof f.GestureTool&&t.event_type)if(v.isString(t.event_type))l[t.event_type].tools.push(t),s(t.event_type,t);else{l.multi.tools.push(t);for(const o of t.event_type)s(o,t)}for(const o of Object.keys(l)){const e=this.gestures[o];t(e.tools,l[o].tools)&&(e.tools=l[o].tools),e.active&&u.every(e.tools,(t=>t.id!=e.active.id))&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=v.isString(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(n.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,n.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=S,S.__name__=\"ToolbarBase\",S.init_ToolbarBase()},\n", " function _(e,t,i,n,s){n();const o=e(250),a=e(99),r=e(43);function h(e){!function(e){void 0===e.lineDash&&Object.defineProperty(e,\"lineDash\",{get:()=>e.getLineDash(),set:t=>e.setLineDash(t)})}(e),function(e){e.setImageSmoothingEnabled=t=>{e.imageSmoothingEnabled=t,e.mozImageSmoothingEnabled=t,e.oImageSmoothingEnabled=t,e.webkitImageSmoothingEnabled=t,e.msImageSmoothingEnabled=t},e.getImageSmoothingEnabled=()=>{const t=e.imageSmoothingEnabled;return null==t||t}}(e),function(e){e.ellipse||(e.ellipse=function(t,i,n,s,o,a,r,h=!1){const l=.551784;e.translate(t,i),e.rotate(o);let c=n,g=s;h&&(c=-n,g=-s),e.moveTo(-c,0),e.bezierCurveTo(-c,g*l,-c*l,g,0,g),e.bezierCurveTo(c*l,g,c,g*l,c,0),e.bezierCurveTo(c,-g*l,c*l,-g,0,-g),e.bezierCurveTo(-c*l,-g,-c,-g*l,-c,0),e.rotate(-o),e.translate(-t,-i)})}(e)}const l={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class c{constructor(e,t){switch(this.backend=e,this.hidpi=t,this.pixel_ratio=1,this.bbox=new a.BBox,e){case\"webgl\":case\"canvas\":{this._el=this._canvas=r.canvas({style:l});const e=this.canvas.getContext(\"2d\");if(null==e)throw new Error(\"unable to obtain 2D rendering context\");this._ctx=e,t&&(this.pixel_ratio=devicePixelRatio);break}case\"svg\":{const e=new o.SVGRenderingContext2D;this._ctx=e,this._canvas=e.get_svg(),this._el=r.div({style:l},this._canvas);break}}h(this._ctx)}get canvas(){return this._canvas}get ctx(){return this._ctx}get el(){return this._el}resize(e,t){this.bbox=new a.BBox({left:0,top:0,width:e,height:t});const i=this._ctx instanceof o.SVGRenderingContext2D?this._ctx:this.canvas;i.width=e*this.pixel_ratio,i.height=t*this.pixel_ratio}prepare(){const{ctx:e,hidpi:t,pixel_ratio:i}=this;e.save(),t&&(e.scale(i,i),e.translate(.5,.5)),this.clear()}clear(){const{x:e,y:t,width:i,height:n}=this.bbox;this.ctx.clearRect(e,t,i,n)}finish(){this.ctx.restore()}to_blob(){const{_canvas:e}=this;if(e instanceof HTMLCanvasElement)return null!=e.msToBlob?Promise.resolve(e.msToBlob()):new Promise(((t,i)=>{e.toBlob((e=>null!=e?t(e):i()),\"image/png\")}));{const e=this._ctx.get_serialized_svg(!0),t=new Blob([e],{type:\"image/svg+xml\"});return Promise.resolve(t)}}}i.CanvasLayer=c,c.__name__=\"CanvasLayer\"},\n", " function _(t,e,i,s,n){s();const r=t(168),a=t(8),o=t(43);function l(t){if(!t)throw new Error(\"cannot create a random attribute name for an undefined object\");const e=\"ABCDEFGHIJKLMNOPQRSTUVWXTZabcdefghiklmnopqrstuvwxyz\";let i=\"\";do{i=\"\";for(let t=0;t<12;t++)i+=e[Math.floor(Math.random()*e.length)]}while(t[i]);return 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t=this.__currentElement.cloneNode(!0);this.__root.appendChild(t),this.__currentElement=t}this.__applyCurrentDefaultPath(),this.__applyStyleToCurrentElement(\"fill\"),null!=t&&this.__currentElement.setAttribute(\"fill-rule\",t),null!=this._clip_path&&this.__currentElement.setAttribute(\"clip-path\",this._clip_path)}rect(t,e,i,s){isFinite(t+e+i+s)&&(\"path\"!==this.__currentElement.nodeName&&this.beginPath(),this.moveTo(t,e),this.lineTo(t+i,e),this.lineTo(t+i,e+s),this.lineTo(t,e+s),this.lineTo(t,e))}fillRect(t,e,i,s){isFinite(t+e+i+s)&&(this.beginPath(),this.rect(t,e,i,s),this.fill())}strokeRect(t,e,i,s){isFinite(t+e+i+s)&&(this.beginPath(),this.rect(t,e,i,s),this.stroke())}__clearCanvas(){o.empty(this.__defs),o.empty(this.__root),this.__root.appendChild(this.__defs),this.__currentElement=this.__root}clearRect(t,e,i,s){if(!isFinite(t+e+i+s))return;if(0===t&&0===e&&i===this.width&&s===this.height)return void this.__clearCanvas();const n=this.__createElement(\"rect\",{x:t,y:e,width:i,height:s,fill:\"#FFFFFF\"},!0);this._apply_transform(n),this.__root.appendChild(n)}createLinearGradient(t,e,i,s){if(!isFinite(t+e+i+s))throw new Error(\"The provided double value is non-finite\");const[n,r]=this._transform.apply(t,e),[a,o]=this._transform.apply(i,s),h=this.__createElement(\"linearGradient\",{id:l(this.__ids),x1:`${n}px`,x2:`${a}px`,y1:`${r}px`,y2:`${o}px`,gradientUnits:\"userSpaceOnUse\"},!1);return this.__defs.appendChild(h),new p(h,this)}createRadialGradient(t,e,i,s,n,r){if(!isFinite(t+e+i+s+n+r))throw new Error(\"The provided double value is non-finite\");const[a,o]=this._transform.apply(t,e),[h,c]=this._transform.apply(s,n),_=this.__createElement(\"radialGradient\",{id:l(this.__ids),cx:`${h}px`,cy:`${c}px`,r:`${r}px`,fx:`${a}px`,fy:`${o}px`,gradientUnits:\"userSpaceOnUse\"},!1);return this.__defs.appendChild(_),new p(_,this)}__parseFont(){var t,e,i,s,n;const 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n=this.__parseFont(),r=this.__createElement(\"text\",{\"font-family\":n.family,\"font-size\":n.size,\"font-style\":n.style,\"font-weight\":n.weight,\"text-decoration\":n.decoration,x:e,y:i,\"text-anchor\":h(this.textAlign),\"dominant-baseline\":c(this.textBaseline)},!0);r.appendChild(this.__document.createTextNode(t)),this._apply_transform(r),this.__currentElement=r,this.__applyStyleToCurrentElement(s),this.__root.appendChild(this.__wrapTextLink(n,r))}fillText(t,e,i){null!=t&&isFinite(e+i)&&this.__applyText(t,e,i,\"fill\")}strokeText(t,e,i){null!=t&&isFinite(e+i)&&this.__applyText(t,e,i,\"stroke\")}measureText(t){return this.__ctx.font=this.font,this.__ctx.measureText(t)}arc(t,e,i,s,n,r=!1){if(!isFinite(t+e+i+s+n))return;if(s===n)return;(s%=2*Math.PI)===(n%=2*Math.PI)&&(n=(n+2*Math.PI-.001*(r?-1:1))%(2*Math.PI));const a=t+i*Math.cos(n),o=e+i*Math.sin(n),l=t+i*Math.cos(s),h=e+i*Math.sin(s),c=r?0:1;let _=0,u=n-s;u<0&&(u+=2*Math.PI),_=r?u>Math.PI?0:1:u>Math.PI?1:0,this.lineTo(l,h);const 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i=this.__document.createElement(\"canvas\");i.width=n,i.height=r;const s=i.getContext(\"2d\");s.imageSmoothingEnabled=!1,s.drawImage(t,a,o,l,h,0,0,n,r),t=i,this._apply_transform(e,_),e.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",t.toDataURL()),c.appendChild(e)}}createPattern(t,e){const i=this.__document.createElementNS(\"http://www.w3.org/2000/svg\",\"pattern\"),s=l(this.__ids);if(i.setAttribute(\"id\",s),i.setAttribute(\"width\",`${this._to_number(t.width)}`),i.setAttribute(\"height\",`${this._to_number(t.height)}`),i.setAttribute(\"patternUnits\",\"userSpaceOnUse\"),t instanceof HTMLCanvasElement||t instanceof HTMLImageElement||t instanceof SVGImageElement){const e=this.__document.createElementNS(\"http://www.w3.org/2000/svg\",\"image\"),s=t instanceof HTMLCanvasElement?t.toDataURL():t.getAttribute(\"src\");e.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",s),i.appendChild(e),this.__defs.appendChild(i)}else if(t instanceof m){for(const e of[...t.__root.childNodes])e instanceof SVGDefsElement||i.appendChild(e);this.__defs.appendChild(i)}else{if(!(t instanceof SVGSVGElement))throw new Error(\"unsupported\");for(const e of[...t.childNodes])e instanceof SVGDefsElement||i.appendChild(e);this.__defs.appendChild(i)}return new d(i,this)}setLineDash(t){t&&t.length>0?this.lineDash=t.join(\",\"):this.lineDash=null}_to_number(t){return a.isNumber(t)?t:t.baseVal.value}}i.SVGRenderingContext2D=m,m.__name__=\"SVGRenderingContext2D\"},\n", " function _(o,t,n,i,e){i();const s=o(238),c=o(15);class l extends s.ButtonToolButtonView{_clicked(){this.model.do.emit(void 0)}}n.ActionToolButtonView=l,l.__name__=\"ActionToolButtonView\";class _ extends s.ButtonToolView{connect_signals(){super.connect_signals(),this.connect(this.model.do,(o=>this.doit(o)))}}n.ActionToolView=_,_.__name__=\"ActionToolView\";class d extends s.ButtonTool{constructor(o){super(o),this.button_view=l,this.do=new c.Signal(this,\"do\")}}n.ActionTool=d,d.__name__=\"ActionTool\"},\n", " function _(o,e,t,i,l){i();const s=o(251),n=o(242);class r extends s.ActionToolView{doit(){window.open(this.model.redirect)}}t.HelpToolView=r,r.__name__=\"HelpToolView\";class c extends s.ActionTool{constructor(o){super(o),this.tool_name=\"Help\",this.icon=n.tool_icon_help}static init_HelpTool(){this.prototype.default_view=r,this.define((({String:o})=>({redirect:[o,\"https://docs.bokeh.org/en/latest/docs/user_guide/tools.html\"]}))),this.override({description:\"Click the question mark to learn more about Bokeh plot tools.\"}),this.register_alias(\"help\",(()=>new c))}}t.HelpTool=c,c.__name__=\"HelpTool\",c.init_HelpTool()},\n", " function _(o,l,g,A,r){A(),g.root=\"bk-root\",g.logo=\"bk-logo\",g.grey=\"bk-grey\",g.logo_small=\"bk-logo-small\",g.logo_notebook=\"bk-logo-notebook\",g.default=\".bk-root .bk-logo{margin:5px;position:relative;display:block;background-repeat:no-repeat;}.bk-root .bk-logo.bk-grey{filter:url(\\\"data:image/svg+xml;utf8,#grayscale\\\");filter:gray;-webkit-filter:grayscale(100%);}.bk-root .bk-logo-small{width:20px;height:20px;background-image:url(data:image/png;base64,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);}.bk-root .bk-logo-notebook{display:inline-block;vertical-align:middle;margin-right:5px;}\"},\n", " function _(t,e,i,s,l){s();const o=t(1),n=t(40),h=t(20),a=t(43),r=o.__importStar(t(255)),c=r;class d extends n.AnnotationView{initialize(){super.initialize(),this.el=a.div({class:c.tooltip}),a.undisplay(this.el),this.plot_view.canvas_view.add_overlay(this.el)}remove(){a.remove(this.el),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.content.change,(()=>this.render())),this.connect(this.model.properties.position.change,(()=>this._reposition()))}styles(){return[...super.styles(),r.default]}render(){this.model.visible||a.undisplay(this.el),super.render()}_render(){const{content:t}=this.model;null!=t?(a.empty(this.el),a.classes(this.el).toggle(\"bk-tooltip-custom\",this.model.custom),this.el.appendChild(t),this.model.show_arrow&&this.el.classList.add(c.tooltip_arrow)):a.undisplay(this.el)}_reposition(){const{position:t}=this.model;if(null==t)return void a.undisplay(this.el);const[e,i]=t,s=(()=>{const t=this.parent.layout.bbox.relative(),{attachment:s}=this.model;switch(s){case\"horizontal\":return e({attachment:[h.TooltipAttachment,\"horizontal\"],inner_only:[t,!0],show_arrow:[t,!0]}))),this.internal((({Boolean:t,Number:e,Tuple:i,Ref:s,Nullable:l})=>({position:[l(i(e,e)),null],content:[s(HTMLElement),()=>a.div()],custom:[t]}))),this.override({level:\"overlay\"})}clear(){this.position=null}}i.Tooltip=p,p.__name__=\"Tooltip\",p.init_Tooltip()},\n", " function _(o,t,r,e,l){e(),r.root=\"bk-root\",r.tooltip=\"bk-tooltip\",r.left=\"bk-left\",r.tooltip_arrow=\"bk-tooltip-arrow\",r.right=\"bk-right\",r.above=\"bk-above\",r.below=\"bk-below\",r.tooltip_row_label=\"bk-tooltip-row-label\",r.tooltip_row_value=\"bk-tooltip-row-value\",r.tooltip_color_block=\"bk-tooltip-color-block\",r.default='.bk-root{}.bk-root .bk-tooltip{font-weight:300;font-size:12px;position:absolute;padding:5px;border:1px solid #e5e5e5;color:#2f2f2f;background-color:white;pointer-events:none;opacity:0.95;z-index:100;}.bk-root .bk-tooltip > div:not(:first-child){margin-top:5px;border-top:#e5e5e5 1px dashed;}.bk-root .bk-tooltip.bk-left.bk-tooltip-arrow::before{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-left::before{left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-right.bk-tooltip-arrow::after{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-right::after{right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-above::before{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;top:-10px;border-bottom-width:10px;border-bottom-color:#909599;}.bk-root .bk-tooltip.bk-below::after{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;bottom:-10px;border-top-width:10px;border-top-color:#909599;}.bk-root .bk-tooltip-row-label{text-align:right;color:#26aae1;}.bk-root .bk-tooltip-row-value{color:default;}.bk-root .bk-tooltip-color-block{width:12px;height:12px;margin-left:5px;margin-right:5px;outline:#dddddd solid 1px;display:inline-block;}'},\n", " function _(e,t,i,s,r){s();const a=e(135),h=e(133),_=e(122),l=e(48);class o extends a.UpperLowerView{async lazy_initialize(){await super.lazy_initialize();const{lower_head:e,upper_head:t}=this.model;null!=e&&(this.lower_head=await _.build_view(e,{parent:this})),null!=t&&(this.upper_head=await _.build_view(t,{parent:this}))}set_data(e){var t,i;super.set_data(e),null===(t=this.lower_head)||void 0===t||t.set_data(e),null===(i=this.upper_head)||void 0===i||i.set_data(e)}paint(e){if(this.visuals.line.doit)for(let t=0,i=this._lower_sx.length;t({lower_head:[t(e(h.ArrowHead)),()=>new h.TeeHead({size:10})],upper_head:[t(e(h.ArrowHead)),()=>new h.TeeHead({size:10})]}))),this.override({level:\"underlay\"})}}i.Whisker=n,n.__name__=\"Whisker\",n.init_Whisker()},\n", " function _(n,o,t,u,e){u(),e(\"CustomJS\",n(258).CustomJS),e(\"OpenURL\",n(260).OpenURL)},\n", " function _(t,s,e,n,c){n();const u=t(259),i=t(13),a=t(34);class r extends u.Callback{constructor(t){super(t)}static init_CustomJS(){this.define((({Unknown:t,String:s,Dict:e})=>({args:[e(t),{}],code:[s,\"\"]})))}get names(){return i.keys(this.args)}get values(){return i.values(this.args)}get func(){const t=a.use_strict(this.code);return new Function(...this.names,\"cb_obj\",\"cb_data\",t)}execute(t,s={}){return this.func.apply(t,this.values.concat(t,s))}}e.CustomJS=r,r.__name__=\"CustomJS\",r.init_CustomJS()},\n", " function _(c,a,l,n,s){n();const e=c(53);class o extends e.Model{constructor(c){super(c)}}l.Callback=o,o.__name__=\"Callback\"},\n", " function _(e,t,n,i,o){i();const s=e(259),c=e(182),r=e(8);class a extends s.Callback{constructor(e){super(e)}static init_OpenURL(){this.define((({Boolean:e,String:t})=>({url:[t,\"http://\"],same_tab:[e,!1]})))}navigate(e){this.same_tab?window.location.href=e:window.open(e)}execute(e,{source:t}){const n=e=>{const n=c.replace_placeholders(this.url,t,e,void 0,void 0,encodeURI);if(!r.isString(n))throw new Error(\"HTML output is not supported in this context\");this.navigate(n)},{selected:i}=t;for(const e of i.indices)n(e);for(const e of i.line_indices)n(e)}}n.OpenURL=a,a.__name__=\"OpenURL\",a.init_OpenURL()},\n", " function _(a,n,e,r,s){r(),s(\"Canvas\",a(262).Canvas),s(\"CartesianFrame\",a(144).CartesianFrame)},\n", " function _(e,t,s,i,a){i();const l=e(14),n=e(240),r=e(19),o=e(43),h=e(20),_=e(13),c=e(263),d=e(99),p=e(249),v=(()=>{const e=document.createElement(\"canvas\"),t=e.getContext(\"webgl\",{premultipliedAlpha:!0});return null!=t?{canvas:e,gl:t}:void r.logger.trace(\"WebGL is not supported\")})(),u={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class b extends n.DOMView{constructor(){super(...arguments),this.bbox=new d.BBox}initialize(){super.initialize(),\"webgl\"==this.model.output_backend&&(this.webgl=v),this.underlays_el=o.div({style:u}),this.primary=this.create_layer(),this.overlays=this.create_layer(),this.overlays_el=o.div({style:u}),this.events_el=o.div({class:\"bk-canvas-events\",style:u});const e=[this.underlays_el,this.primary.el,this.overlays.el,this.overlays_el,this.events_el];_.extend(this.el.style,u),o.append(this.el,...e),this.ui_event_bus=new c.UIEventBus(this)}remove(){this.ui_event_bus.destroy(),super.remove()}add_underlay(e){this.underlays_el.appendChild(e)}add_overlay(e){this.overlays_el.appendChild(e)}add_event(e){this.events_el.appendChild(e)}get pixel_ratio(){return this.primary.pixel_ratio}resize(e,t){this.bbox=new d.BBox({left:0,top:0,width:e,height:t}),this.primary.resize(e,t),this.overlays.resize(e,t)}prepare_webgl(e){const{webgl:t}=this;if(null!=t){const{width:s,height:i}=this.bbox;t.canvas.width=this.pixel_ratio*s,t.canvas.height=this.pixel_ratio*i;const{gl:a}=t;a.enable(a.SCISSOR_TEST);const[l,n,r,o]=e,{xview:h,yview:_}=this.bbox,c=h.compute(l),d=_.compute(n+o),p=this.pixel_ratio;a.scissor(p*c,p*d,p*r,p*o),a.enable(a.BLEND),a.blendFuncSeparate(a.SRC_ALPHA,a.ONE_MINUS_SRC_ALPHA,a.ONE_MINUS_DST_ALPHA,a.ONE),this._clear_webgl()}}blit_webgl(e){const{webgl:t}=this;if(null!=t){if(r.logger.debug(\"Blitting WebGL canvas\"),e.restore(),e.drawImage(t.canvas,0,0),e.save(),this.model.hidpi){const t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}this._clear_webgl()}}_clear_webgl(){const{webgl:e}=this;if(null!=e){const{gl:t,canvas:s}=e;t.viewport(0,0,s.width,s.height),t.clearColor(0,0,0,0),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}}compose(){const e=this.create_layer(),{width:t,height:s}=this.bbox;return e.resize(t,s),e.ctx.drawImage(this.primary.canvas,0,0),e.ctx.drawImage(this.overlays.canvas,0,0),e}create_layer(){const{output_backend:e,hidpi:t}=this.model;return new p.CanvasLayer(e,t)}to_blob(){return this.compose().to_blob()}}s.CanvasView=b,b.__name__=\"CanvasView\";class g extends l.HasProps{constructor(e){super(e)}static init_Canvas(){this.prototype.default_view=b,this.internal((({Boolean:e})=>({hidpi:[e,!0],output_backend:[h.OutputBackend,\"canvas\"]})))}}s.Canvas=g,g.__name__=\"Canvas\",g.init_Canvas()},\n", " function _(t,e,s,n,i){n();const r=t(1),a=r.__importDefault(t(239)),_=t(15),h=t(19),o=t(43),l=r.__importStar(t(264)),c=t(265),p=t(9),u=t(8),v=t(27),d=t(244);class g{constructor(t){this.canvas_view=t,this.pan_start=new _.Signal(this,\"pan:start\"),this.pan=new _.Signal(this,\"pan\"),this.pan_end=new _.Signal(this,\"pan:end\"),this.pinch_start=new _.Signal(this,\"pinch:start\"),this.pinch=new _.Signal(this,\"pinch\"),this.pinch_end=new _.Signal(this,\"pinch:end\"),this.rotate_start=new _.Signal(this,\"rotate:start\"),this.rotate=new _.Signal(this,\"rotate\"),this.rotate_end=new _.Signal(this,\"rotate:end\"),this.tap=new _.Signal(this,\"tap\"),this.doubletap=new _.Signal(this,\"doubletap\"),this.press=new _.Signal(this,\"press\"),this.pressup=new _.Signal(this,\"pressup\"),this.move_enter=new _.Signal(this,\"move:enter\"),this.move=new _.Signal(this,\"move\"),this.move_exit=new _.Signal(this,\"move:exit\"),this.scroll=new _.Signal(this,\"scroll\"),this.keydown=new _.Signal(this,\"keydown\"),this.keyup=new _.Signal(this,\"keyup\"),this.hammer=new a.default(this.hit_area,{touchAction:\"auto\",inputClass:a.default.TouchMouseInput}),this._prev_move=null,this._curr_pan=null,this._curr_pinch=null,this._curr_rotate=null,this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",(t=>this._mouse_move(t))),this.hit_area.addEventListener(\"mouseenter\",(t=>this._mouse_enter(t))),this.hit_area.addEventListener(\"mouseleave\",(t=>this._mouse_exit(t))),this.hit_area.addEventListener(\"contextmenu\",(t=>this._context_menu(t))),this.hit_area.addEventListener(\"wheel\",(t=>this._mouse_wheel(t))),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new d.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}get hit_area(){return this.canvas_view.events_el}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",(t=>this._doubletap(t))),this.hammer.on(\"tap\",(t=>this._tap(t))),this.hammer.on(\"press\",(t=>this._press(t))),this.hammer.on(\"pressup\",(t=>this._pressup(t))),this.hammer.get(\"pan\").set({direction:a.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",(t=>this._pan_start(t))),this.hammer.on(\"pan\",(t=>this._pan(t))),this.hammer.on(\"panend\",(t=>this._pan_end(t))),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",(t=>this._pinch_start(t))),this.hammer.on(\"pinch\",(t=>this._pinch(t))),this.hammer.on(\"pinchend\",(t=>this._pinch_end(t))),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",(t=>this._rotate_start(t))),this.hammer.on(\"rotate\",(t=>this._rotate(t))),this.hammer.on(\"rotateend\",(t=>this._rotate_end(t)))}register_tool(t){const e=t.model.event_type;null!=e&&(u.isString(e)?this._register_tool(t,e):e.forEach(((e,s)=>this._register_tool(t,e,s<1))))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},a=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n))),null!=n._doubletap&&n.connect(this.doubletap,r(n._doubletap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(`unsupported event_type: ${e}`)}s&&(null!=n._keydown&&n.connect(this.keydown,a(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,a(n._keyup.bind(n))),v.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(h.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e,s){var n;const i=t.get_renderer_views();for(const t of p.reversed(i))if(null===(n=t.interactive_hit)||void 0===n?void 0:n.call(t,e,s))return t;return null}set_cursor(t=\"default\"){this.hit_area.style.cursor=t}_hit_test_frame(t,e,s){return t.frame.bbox.contains(e,s)}_hit_test_canvas(t,e,s){return t.layout.bbox.contains(e,s)}_hit_test_plot(t,e){for(const s of this.canvas_view.plot_views)if(s.layout.bbox.relative().contains(t,e))return s;return null}_trigger(t,e,s){var n;const{sx:i,sy:r}=e,a=this._hit_test_plot(i,r),_=t=>{const[s,n]=[i,r];return Object.assign(Object.assign({},e),{sx:s,sy:n})};if(\"panstart\"==e.type||\"pan\"==e.type||\"panend\"==e.type){let n;if(\"panstart\"==e.type&&null!=a?(this._curr_pan={plot_view:a},n=a):\"pan\"==e.type&&null!=this._curr_pan?n=this._curr_pan.plot_view:\"panend\"==e.type&&null!=this._curr_pan?(n=this._curr_pan.plot_view,this._curr_pan=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"pinchstart\"==e.type||\"pinch\"==e.type||\"pinchend\"==e.type){let n;if(\"pinchstart\"==e.type&&null!=a?(this._curr_pinch={plot_view:a},n=a):\"pinch\"==e.type&&null!=this._curr_pinch?n=this._curr_pinch.plot_view:\"pinchend\"==e.type&&null!=this._curr_pinch?(n=this._curr_pinch.plot_view,this._curr_pinch=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"rotatestart\"==e.type||\"rotate\"==e.type||\"rotateend\"==e.type){let n;if(\"rotatestart\"==e.type&&null!=a?(this._curr_rotate={plot_view:a},n=a):\"rotate\"==e.type&&null!=this._curr_rotate?n=this._curr_rotate.plot_view:\"rotateend\"==e.type&&null!=this._curr_rotate?(n=this._curr_rotate.plot_view,this._curr_rotate=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"mouseenter\"==e.type||\"mousemove\"==e.type||\"mouseleave\"==e.type){const h=null===(n=this._prev_move)||void 0===n?void 0:n.plot_view;if(null!=h&&(\"mouseleave\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(h,this.move_exit,{type:\"mouseleave\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&(\"mouseenter\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(a,this.move_enter,{type:\"mouseenter\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&\"mousemove\"==e.type){const e=_();this.__trigger(a,t,e,s)}this._prev_move={sx:i,sy:r,plot_view:a}}else if(null!=a){const e=_();this.__trigger(a,t,e,s)}}__trigger(t,e,s,n){var i,r;const a=t.model.toolbar.gestures,_=e.name.split(\":\")[0],h=this._hit_test_renderers(t,s.sx,s.sy),o=this._hit_test_canvas(t,s.sx,s.sy);switch(_){case\"move\":{const n=a[_].active;null!=n&&this.trigger(e,s,n.id);const r=t.model.toolbar.inspectors.filter((t=>t.active));let l=\"default\";null!=h?(l=null!==(i=h.cursor(s.sx,s.sy))&&void 0!==i?i:l,p.is_empty(r)||(e=this.move_exit)):this._hit_test_frame(t,s.sx,s.sy)&&(p.is_empty(r)||(l=\"crosshair\")),this.set_cursor(l),t.set_toolbar_visibility(o),r.map((t=>this.trigger(e,s,t.id)));break}case\"tap\":{const{target:t}=n;if(null!=t&&t!=this.hit_area)return;null!=h&&null!=h.on_hit&&h.on_hit(s.sx,s.sy);const i=a[_].active;null!=i&&this.trigger(e,s,i.id);break}case\"doubletap\":{const t=null!==(r=a.doubletap.active)&&void 0!==r?r:a.tap.active;null!=t&&this.trigger(e,s,t.id);break}case\"scroll\":{const t=a[v.is_mobile?\"pinch\":\"scroll\"].active;null!=t&&(n.preventDefault(),n.stopPropagation(),this.trigger(e,s,t.id));break}case\"pan\":{const t=a[_].active;null!=t&&(n.preventDefault(),this.trigger(e,s,t.id));break}default:{const t=a[_].active;null!=t&&this.trigger(e,s,t.id)}}this._trigger_bokeh_event(t,s)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t,e){const s=(()=>{const{sx:s,sy:n}=e,i=t.frame.x_scale.invert(s),r=t.frame.y_scale.invert(n);switch(e.type){case\"wheel\":return new l.MouseWheel(s,n,i,r,e.delta);case\"mousemove\":return new l.MouseMove(s,n,i,r);case\"mouseenter\":return new l.MouseEnter(s,n,i,r);case\"mouseleave\":return new l.MouseLeave(s,n,i,r);case\"tap\":return new l.Tap(s,n,i,r);case\"doubletap\":return new l.DoubleTap(s,n,i,r);case\"press\":return new l.Press(s,n,i,r);case\"pressup\":return new l.PressUp(s,n,i,r);case\"pan\":return new l.Pan(s,n,i,r,e.deltaX,e.deltaY);case\"panstart\":return new l.PanStart(s,n,i,r);case\"panend\":return new l.PanEnd(s,n,i,r);case\"pinch\":return new l.Pinch(s,n,i,r,e.scale);case\"pinchstart\":return new l.PinchStart(s,n,i,r);case\"pinchend\":return new l.PinchEnd(s,n,i,r);case\"rotate\":return new l.Rotate(s,n,i,r,e.rotation);case\"rotatestart\":return new l.RotateStart(s,n,i,r);case\"rotateend\":return new l.RotateEnd(s,n,i,r);default:return}})();null!=s&&t.model.trigger_event(s)}_get_sxy(t){const{pageX:e,pageY:s}=function(t){return\"undefined\"!=typeof TouchEvent&&t instanceof TouchEvent}(t)?(0!=t.touches.length?t.touches:t.changedTouches)[0]:t,{left:n,top:i}=o.offset(this.hit_area);return{sx:e-n,sy:s-i}}_pan_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{deltaX:t.deltaX,deltaY:t.deltaY,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_pinch_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{scale:t.scale,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_rotate_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{rotation:t.rotation,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_tap_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_move_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_scroll_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{delta:c.getDeltaY(t),shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_key_event(t){return{type:t.type,keyCode:t.keyCode}}_pan_start(t){const e=this._pan_event(t);e.sx-=t.deltaX,e.sy-=t.deltaY,this._trigger(this.pan_start,e,t.srcEvent)}_pan(t){this._trigger(this.pan,this._pan_event(t),t.srcEvent)}_pan_end(t){this._trigger(this.pan_end,this._pan_event(t),t.srcEvent)}_pinch_start(t){this._trigger(this.pinch_start,this._pinch_event(t),t.srcEvent)}_pinch(t){this._trigger(this.pinch,this._pinch_event(t),t.srcEvent)}_pinch_end(t){this._trigger(this.pinch_end,this._pinch_event(t),t.srcEvent)}_rotate_start(t){this._trigger(this.rotate_start,this._rotate_event(t),t.srcEvent)}_rotate(t){this._trigger(this.rotate,this._rotate_event(t),t.srcEvent)}_rotate_end(t){this._trigger(this.rotate_end,this._rotate_event(t),t.srcEvent)}_tap(t){this._trigger(this.tap,this._tap_event(t),t.srcEvent)}_doubletap(t){this._trigger(this.doubletap,this._tap_event(t),t.srcEvent)}_press(t){this._trigger(this.press,this._tap_event(t),t.srcEvent)}_pressup(t){this._trigger(this.pressup,this._tap_event(t),t.srcEvent)}_mouse_enter(t){this._trigger(this.move_enter,this._move_event(t),t)}_mouse_move(t){this._trigger(this.move,this._move_event(t),t)}_mouse_exit(t){this._trigger(this.move_exit,this._move_event(t),t)}_mouse_wheel(t){this._trigger(this.scroll,this._scroll_event(t),t)}_context_menu(t){!this.menu.is_open&&this.menu.can_open&&t.preventDefault();const{sx:e,sy:s}=this._get_sxy(t);this.menu.toggle({left:e,top:s})}_key_down(t){this.trigger(this.keydown,this._key_event(t))}_key_up(t){this.trigger(this.keyup,this._key_event(t))}}s.UIEventBus=g,g.__name__=\"UIEventBus\"},\n", " function _(e,t,s,n,_){n();var a=this&&this.__decorate||function(e,t,s,n){var _,a=arguments.length,o=a<3?t:null===n?n=Object.getOwnPropertyDescriptor(t,s):n;if(\"object\"==typeof Reflect&&\"function\"==typeof Reflect.decorate)o=Reflect.decorate(e,t,s,n);else for(var c=e.length-1;c>=0;c--)(_=e[c])&&(o=(a<3?_(o):a>3?_(t,s,o):_(t,s))||o);return a>3&&o&&Object.defineProperty(t,s,o),o};function o(e){return function(t){t.prototype.event_name=e}}class c{to_json(){const{event_name:e}=this;return{event_name:e,event_values:this._to_json()}}}s.BokehEvent=c,c.__name__=\"BokehEvent\";class r extends c{constructor(){super(...arguments),this.origin=null}_to_json(){return{model:this.origin}}}s.ModelEvent=r,r.__name__=\"ModelEvent\";let l=class extends c{_to_json(){return{}}};s.DocumentReady=l,l.__name__=\"DocumentReady\",s.DocumentReady=l=a([o(\"document_ready\")],l);let i=class extends r{};s.ButtonClick=i,i.__name__=\"ButtonClick\",s.ButtonClick=i=a([o(\"button_click\")],i);let u=class extends r{constructor(e){super(),this.item=e}_to_json(){const{item:e}=this;return Object.assign(Object.assign({},super._to_json()),{item:e})}};s.MenuItemClick=u,u.__name__=\"MenuItemClick\",s.MenuItemClick=u=a([o(\"menu_item_click\")],u);class d extends r{}s.UIEvent=d,d.__name__=\"UIEvent\";let h=class extends d{};s.LODStart=h,h.__name__=\"LODStart\",s.LODStart=h=a([o(\"lodstart\")],h);let m=class extends d{};s.LODEnd=m,m.__name__=\"LODEnd\",s.LODEnd=m=a([o(\"lodend\")],m);let x=class extends d{constructor(e,t){super(),this.geometry=e,this.final=t}_to_json(){const{geometry:e,final:t}=this;return Object.assign(Object.assign({},super._to_json()),{geometry:e,final:t})}};s.SelectionGeometry=x,x.__name__=\"SelectionGeometry\",s.SelectionGeometry=x=a([o(\"selectiongeometry\")],x);let p=class extends d{};s.Reset=p,p.__name__=\"Reset\",s.Reset=p=a([o(\"reset\")],p);class j extends d{constructor(e,t,s,n){super(),this.sx=e,this.sy=t,this.x=s,this.y=n}_to_json(){const{sx:e,sy:t,x:s,y:n}=this;return Object.assign(Object.assign({},super._to_json()),{sx:e,sy:t,x:s,y:n})}}s.PointEvent=j,j.__name__=\"PointEvent\";let y=class extends j{constructor(e,t,s,n,_,a){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.delta_x=_,this.delta_y=a}_to_json(){const{delta_x:e,delta_y:t}=this;return Object.assign(Object.assign({},super._to_json()),{delta_x:e,delta_y:t})}};s.Pan=y,y.__name__=\"Pan\",s.Pan=y=a([o(\"pan\")],y);let P=class extends j{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.scale=_}_to_json(){const{scale:e}=this;return Object.assign(Object.assign({},super._to_json()),{scale:e})}};s.Pinch=P,P.__name__=\"Pinch\",s.Pinch=P=a([o(\"pinch\")],P);let v=class extends j{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.rotation=_}_to_json(){const{rotation:e}=this;return Object.assign(Object.assign({},super._to_json()),{rotation:e})}};s.Rotate=v,v.__name__=\"Rotate\",s.Rotate=v=a([o(\"rotate\")],v);let g=class extends j{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.delta=_}_to_json(){const{delta:e}=this;return Object.assign(Object.assign({},super._to_json()),{delta:e})}};s.MouseWheel=g,g.__name__=\"MouseWheel\",s.MouseWheel=g=a([o(\"wheel\")],g);let E=class extends j{};s.MouseMove=E,E.__name__=\"MouseMove\",s.MouseMove=E=a([o(\"mousemove\")],E);let O=class extends j{};s.MouseEnter=O,O.__name__=\"MouseEnter\",s.MouseEnter=O=a([o(\"mouseenter\")],O);let b=class extends j{};s.MouseLeave=b,b.__name__=\"MouseLeave\",s.MouseLeave=b=a([o(\"mouseleave\")],b);let M=class extends j{};s.Tap=M,M.__name__=\"Tap\",s.Tap=M=a([o(\"tap\")],M);let R=class extends j{};s.DoubleTap=R,R.__name__=\"DoubleTap\",s.DoubleTap=R=a([o(\"doubletap\")],R);let f=class extends j{};s.Press=f,f.__name__=\"Press\",s.Press=f=a([o(\"press\")],f);let S=class extends j{};s.PressUp=S,S.__name__=\"PressUp\",s.PressUp=S=a([o(\"pressup\")],S);let D=class extends j{};s.PanStart=D,D.__name__=\"PanStart\",s.PanStart=D=a([o(\"panstart\")],D);let k=class extends j{};s.PanEnd=k,k.__name__=\"PanEnd\",s.PanEnd=k=a([o(\"panend\")],k);let L=class extends j{};s.PinchStart=L,L.__name__=\"PinchStart\",s.PinchStart=L=a([o(\"pinchstart\")],L);let C=class extends j{};s.PinchEnd=C,C.__name__=\"PinchEnd\",s.PinchEnd=C=a([o(\"pinchend\")],C);let T=class extends j{};s.RotateStart=T,T.__name__=\"RotateStart\",s.RotateStart=T=a([o(\"rotatestart\")],T);let B=class extends j{};s.RotateEnd=B,B.__name__=\"RotateEnd\",s.RotateEnd=B=a([o(\"rotateend\")],B)},\n", " function _(t,e,n,l,o){\n", " /*!\n", " * jQuery Mousewheel 3.1.13\n", " *\n", " * Copyright jQuery Foundation and other contributors\n", " * Released under the MIT license\n", " * http://jquery.org/license\n", " */\n", " function u(t){const e=getComputedStyle(t).fontSize;return null!=e?parseInt(e,10):null}l(),n.getDeltaY=function(t){let e=-t.deltaY;if(t.target instanceof HTMLElement)switch(t.deltaMode){case t.DOM_DELTA_LINE:e*=(n=t.target,null!==(a=null!==(o=u(null!==(l=n.offsetParent)&&void 0!==l?l:document.body))&&void 0!==o?o:u(n))&&void 0!==a?a:16);break;case t.DOM_DELTA_PAGE:e*=function(t){return t.clientHeight}(t.target)}var n,l,o,a;return e}},\n", " function _(m,i,u,s,a){s(),a(\"Expression\",m(124).Expression),a(\"CustomJSExpr\",m(267).CustomJSExpr),a(\"Stack\",m(268).Stack),a(\"CumSum\",m(269).CumSum),a(\"ScalarExpression\",m(124).ScalarExpression),a(\"Minimum\",m(270).Minimum),a(\"Maximum\",m(271).Maximum)},\n", " function _(t,e,s,n,r){n();const i=t(14),o=t(124),a=t(24),c=t(9),u=t(13),l=t(34),h=t(8);class p extends o.Expression{constructor(t){super(t)}static init_CustomJSExpr(){this.define((({Unknown:t,String:e,Dict:s})=>({args:[s(t),{}],code:[e,\"\"]})))}connect_signals(){super.connect_signals();for(const t of u.values(this.args))t instanceof i.HasProps&&t.change.connect((()=>{this._result.clear(),this.change.emit()}))}get names(){return u.keys(this.args)}get values(){return u.values(this.args)}get func(){const t=l.use_strict(this.code);return new a.GeneratorFunction(...this.names,t)}_v_compute(t){const e=this.func.apply(t,this.values);let s=e.next();if(s.done&&void 0!==s.value){const{value:e}=s;return h.isArray(e)||h.isTypedArray(e)?e:h.isIterable(e)?[...e]:c.repeat(e,t.length)}{const t=[];do{t.push(s.value),s=e.next()}while(!s.done);return t}}}s.CustomJSExpr=p,p.__name__=\"CustomJSExpr\",p.init_CustomJSExpr()},\n", " function _(t,n,e,i,s){i();const a=t(124);class c extends a.Expression{constructor(t){super(t)}static init_Stack(){this.define((({String:t,Array:n})=>({fields:[n(t),[]]})))}_v_compute(t){var n;const e=null!==(n=t.get_length())&&void 0!==n?n:0,i=new Float64Array(e);for(const n of this.fields){const s=t.data[n];if(null!=s)for(let t=0,n=Math.min(e,s.length);t({field:[t],include_zero:[e,!1]})))}_v_compute(e){var t;const n=new Float64Array(null!==(t=e.get_length())&&void 0!==t?t:0),i=e.data[this.field],u=this.include_zero?1:0;n[0]=this.include_zero?0:i[0];for(let e=1;e({field:[n],initial:[t(i),null]})))}_compute(i){var n,t;const l=null!==(n=i.data[this.field])&&void 0!==n?n:[];return Math.min(null!==(t=this.initial)&&void 0!==t?t:1/0,m.min(l))}}t.Minimum=s,s.__name__=\"Minimum\",s.init_Minimum()},\n", " function _(i,t,a,n,l){n();const u=i(124),e=i(9);class m extends u.ScalarExpression{constructor(i){super(i)}static init_Maximum(){this.define((({Number:i,String:t,Nullable:a})=>({field:[t],initial:[a(i),null]})))}_compute(i){var t,a;const n=null!==(t=i.data[this.field])&&void 0!==t?t:[];return Math.max(null!==(a=this.initial)&&void 0!==a?a:-1/0,e.max(n))}}a.Maximum=m,m.__name__=\"Maximum\",m.init_Maximum()},\n", " function _(e,t,l,r,i){r(),i(\"BooleanFilter\",e(273).BooleanFilter),i(\"CustomJSFilter\",e(274).CustomJSFilter),i(\"Filter\",e(121).Filter),i(\"GroupFilter\",e(275).GroupFilter),i(\"IndexFilter\",e(276).IndexFilter)},\n", " function _(e,n,l,o,t){o();const i=e(121),s=e(24);class a extends i.Filter{constructor(e){super(e)}static init_BooleanFilter(){this.define((({Boolean:e,Array:n,Nullable:l})=>({booleans:[l(n(e)),null]})))}compute_indices(e){const n=e.length,{booleans:l}=this;return null==l?s.Indices.all_set(n):s.Indices.from_booleans(n,l)}}l.BooleanFilter=a,a.__name__=\"BooleanFilter\",a.init_BooleanFilter()},\n", " function _(e,t,s,n,r){n();const i=e(121),o=e(24),u=e(13),c=e(8),a=e(34);class l extends i.Filter{constructor(e){super(e)}static init_CustomJSFilter(){this.define((({Unknown:e,String:t,Dict:s})=>({args:[s(e),{}],code:[t,\"\"]})))}get names(){return u.keys(this.args)}get values(){return u.values(this.args)}get func(){const e=a.use_strict(this.code);return new Function(...this.names,\"source\",e)}compute_indices(e){const t=e.length,s=this.func(...this.values,e);if(null==s)return o.Indices.all_set(t);if(c.isArrayOf(s,c.isInteger))return o.Indices.from_indices(t,s);if(c.isArrayOf(s,c.isBoolean))return o.Indices.from_booleans(t,s);throw new Error(`expect an array of integers or booleans, or null, got ${s}`)}}s.CustomJSFilter=l,l.__name__=\"CustomJSFilter\",l.init_CustomJSFilter()},\n", " function _(n,t,e,i,o){i();const r=n(121),u=n(24),s=n(19);class c extends r.Filter{constructor(n){super(n)}static init_GroupFilter(){this.define((({String:n})=>({column_name:[n],group:[n]})))}compute_indices(n){const t=n.get_column(this.column_name);if(null==t)return s.logger.warn(`${this}: groupby column '${this.column_name}' not found in the data source`),new u.Indices(n.length,1);{const e=new u.Indices(n.length);for(let n=0;n({indices:[i(n(e)),null]})))}compute_indices(e){const n=e.length,{indices:i}=this;return null==i?c.Indices.all_set(n):c.Indices.from_indices(n,i)}}i.IndexFilter=r,r.__name__=\"IndexFilter\",r.init_IndexFilter()},\n", " function _(e,a,l,i,t){i(),t(\"AnnularWedge\",e(278).AnnularWedge),t(\"Annulus\",e(279).Annulus),t(\"Arc\",e(280).Arc),t(\"Bezier\",e(281).Bezier),t(\"Circle\",e(282).Circle),t(\"Ellipse\",e(286).Ellipse),t(\"EllipseOval\",e(287).EllipseOval),t(\"Glyph\",e(98).Glyph),t(\"HArea\",e(117).HArea),t(\"HBar\",e(289).HBar),t(\"HexTile\",e(291).HexTile),t(\"Image\",e(292).Image),t(\"ImageRGBA\",e(294).ImageRGBA),t(\"ImageURL\",e(295).ImageURL),t(\"Line\",e(63).Line),t(\"MultiLine\",e(127).MultiLine),t(\"MultiPolygons\",e(297).MultiPolygons),t(\"Oval\",e(298).Oval),t(\"Patch\",e(116).Patch),t(\"Patches\",e(128).Patches),t(\"Quad\",e(299).Quad),t(\"Quadratic\",e(300).Quadratic),t(\"Ray\",e(301).Ray),t(\"Rect\",e(302).Rect),t(\"Scatter\",e(303).Scatter),t(\"Segment\",e(306).Segment),t(\"Spline\",e(307).Spline),t(\"Step\",e(309).Step),t(\"Text\",e(310).Text),t(\"VArea\",e(119).VArea),t(\"VBar\",e(311).VBar),t(\"Wedge\",e(312).Wedge)},\n", " function _(e,t,s,i,r){i();const n=e(1),a=e(64),o=e(106),_=e(48),d=e(24),u=e(20),h=n.__importStar(e(18)),l=e(10),c=e(59);class g extends a.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=d.to_screen(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=d.to_screen(this.outer_radius)}_render(e,t,s){const{sx:i,sy:r,start_angle:n,end_angle:a,sinner_radius:o,souter_radius:_}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of t){const t=i[s],u=r[s],h=o[s],l=_[s],c=n.get(s),g=a.get(s);if(isNaN(t+u+h+l+c+g))continue;const x=g-c;e.translate(t,u),e.rotate(c),e.beginPath(),e.moveTo(l,0),e.arc(0,0,l,0,x,d),e.rotate(x),e.lineTo(h,0),e.arc(0,0,h,0,-x,!d),e.closePath(),e.rotate(-x-c),e.translate(-t,-u),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,s),e.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_vectorize(e,s),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,s),e.stroke())}}_hit_point(e){const{sx:t,sy:s}=e,i=this.renderer.xscale.invert(t),r=this.renderer.yscale.invert(s);let n,a,o,_;if(\"data\"==this.model.properties.outer_radius.units)n=i-this.max_outer_radius,o=i+this.max_outer_radius,a=r-this.max_outer_radius,_=r+this.max_outer_radius;else{const e=t-this.max_outer_radius,i=t+this.max_outer_radius;[n,o]=this.renderer.xscale.r_invert(e,i);const r=s-this.max_outer_radius,d=s+this.max_outer_radius;[a,_]=this.renderer.yscale.r_invert(r,d)}const d=[];for(const e of this.index.indices({x0:n,x1:o,y0:a,y1:_})){const t=this.souter_radius[e]**2,s=this.sinner_radius[e]**2,[n,a]=this.renderer.xscale.r_compute(i,this._x[e]),[o,_]=this.renderer.yscale.r_compute(r,this._y[e]),u=(n-a)**2+(o-_)**2;u<=t&&u>=s&&d.push(e)}const u=\"anticlock\"==this.model.direction,h=[];for(const e of d){const i=Math.atan2(s-this.sy[e],t-this.sx[e]);l.angle_between(-i,-this.start_angle.get(e),-this.end_angle.get(e),u)&&h.push(e)}return new c.Selection({indices:h})}draw_legend_for_index(e,t,s){o.generic_area_vector_legend(this.visuals,e,t,s)}scenterxy(e){const t=(this.sinner_radius[e]+this.souter_radius[e])/2,s=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+t*Math.cos(s),this.sy[e]+t*Math.sin(s)]}}s.AnnularWedgeView=g,g.__name__=\"AnnularWedgeView\";class x extends a.XYGlyph{constructor(e){super(e)}static init_AnnularWedge(){this.prototype.default_view=g,this.mixins([_.LineVector,_.FillVector,_.HatchVector]),this.define((({})=>({direction:[u.Direction,\"anticlock\"],inner_radius:[h.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[h.DistanceSpec,{field:\"outer_radius\"}],start_angle:[h.AngleSpec,{field:\"start_angle\"}],end_angle:[h.AngleSpec,{field:\"end_angle\"}]})))}}s.AnnularWedge=x,x.__name__=\"AnnularWedge\",x.init_AnnularWedge()},\n", " function _(s,i,t,e,r){e();const n=s(1),a=s(64),u=s(24),_=s(48),o=n.__importStar(s(18)),h=s(27),d=s(59);class c extends a.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=u.to_screen(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=u.to_screen(this.outer_radius)}_render(s,i,t){const{sx:e,sy:r,sinner_radius:n,souter_radius:a}=null!=t?t:this;for(const t of i){const i=e[t],_=r[t],o=n[t],d=a[t];function u(){if(s.beginPath(),h.is_ie)for(const t of[!1,!0])s.arc(i,_,o,0,Math.PI,t),s.arc(i,_,d,Math.PI,0,!t);else s.arc(i,_,o,0,2*Math.PI,!0),s.arc(i,_,d,2*Math.PI,0,!1)}isNaN(i+_+o+d)||(this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(s,t),u(),s.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_vectorize(s,t),u(),s.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(s,t),s.beginPath(),s.arc(i,_,o,0,2*Math.PI),s.moveTo(i+d,_),s.arc(i,_,d,0,2*Math.PI),s.stroke()))}}_hit_point(s){const{sx:i,sy:t}=s,e=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(t);let n,a,u,_;if(\"data\"==this.model.properties.outer_radius.units)n=e-this.max_outer_radius,u=e+this.max_outer_radius,a=r-this.max_outer_radius,_=r+this.max_outer_radius;else{const s=i-this.max_outer_radius,e=i+this.max_outer_radius;[n,u]=this.renderer.xscale.r_invert(s,e);const r=t-this.max_outer_radius,o=t+this.max_outer_radius;[a,_]=this.renderer.yscale.r_invert(r,o)}const o=[];for(const s of this.index.indices({x0:n,x1:u,y0:a,y1:_})){const i=this.souter_radius[s]**2,t=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(e,this._x[s]),[u,_]=this.renderer.yscale.r_compute(r,this._y[s]),h=(n-a)**2+(u-_)**2;h<=i&&h>=t&&o.push(s)}return new d.Selection({indices:o})}draw_legend_for_index(s,{x0:i,y0:t,x1:e,y1:r},n){const a=n+1,u=new Array(a);u[n]=(i+e)/2;const _=new Array(a);_[n]=(t+r)/2;const o=.5*Math.min(Math.abs(e-i),Math.abs(r-t)),h=new Array(a);h[n]=.4*o;const d=new Array(a);d[n]=.8*o,this._render(s,[n],{sx:u,sy:_,sinner_radius:h,souter_radius:d})}}t.AnnulusView=c,c.__name__=\"AnnulusView\";class l extends a.XYGlyph{constructor(s){super(s)}static init_Annulus(){this.prototype.default_view=c,this.mixins([_.LineVector,_.FillVector,_.HatchVector]),this.define((({})=>({inner_radius:[o.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[o.DistanceSpec,{field:\"outer_radius\"}]})))}}t.Annulus=l,l.__name__=\"Annulus\",l.init_Annulus()},\n", " function _(e,i,s,t,n){t();const r=e(1),a=e(64),c=e(106),d=e(48),_=e(24),l=e(20),o=r.__importStar(e(18));class h extends a.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=_.to_screen(this.radius)}_render(e,i,s){if(this.visuals.line.doit){const{sx:t,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of i){const i=t[s],_=n[s],l=r[s],o=a.get(s),h=c.get(s);isNaN(i+_+l+o+h)||(e.beginPath(),e.arc(i,_,l,o,h,d),this.visuals.line.set_vectorize(e,s),e.stroke())}}}draw_legend_for_index(e,i,s){c.generic_line_vector_legend(this.visuals,e,i,s)}}s.ArcView=h,h.__name__=\"ArcView\";class u extends a.XYGlyph{constructor(e){super(e)}static init_Arc(){this.prototype.default_view=h,this.mixins(d.LineVector),this.define((({})=>({direction:[l.Direction,\"anticlock\"],radius:[o.DistanceSpec,{field:\"radius\"}],start_angle:[o.AngleSpec,{field:\"start_angle\"}],end_angle:[o.AngleSpec,{field:\"end_angle\"}]})))}}s.Arc=u,u.__name__=\"Arc\",u.init_Arc()},\n", " function _(e,t,i,s,n){s();const o=e(1),c=e(48),r=e(98),a=e(106),_=e(65),d=o.__importStar(e(18));function l(e,t,i,s,n,o,c,r){const a=[],_=[[],[]];for(let _=0;_<=2;_++){let d,l,x;if(0===_?(l=6*e-12*i+6*n,d=-3*e+9*i-9*n+3*c,x=3*i-3*e):(l=6*t-12*s+6*o,d=-3*t+9*s-9*o+3*r,x=3*s-3*t),Math.abs(d)<1e-12){if(Math.abs(l)<1e-12)continue;const e=-x/l;0({x0:[d.XCoordinateSpec,{field:\"x0\"}],y0:[d.YCoordinateSpec,{field:\"y0\"}],x1:[d.XCoordinateSpec,{field:\"x1\"}],y1:[d.YCoordinateSpec,{field:\"y1\"}],cx0:[d.XCoordinateSpec,{field:\"cx0\"}],cy0:[d.YCoordinateSpec,{field:\"cy0\"}],cx1:[d.XCoordinateSpec,{field:\"cx1\"}],cy1:[d.YCoordinateSpec,{field:\"cy1\"}]}))),this.mixins(c.LineVector)}}i.Bezier=h,h.__name__=\"Bezier\",h.init_Bezier()},\n", " function _(s,i,e,t,r){t();const a=s(1),n=s(64),h=s(283),d=s(48),l=s(24),c=s(20),_=a.__importStar(s(107)),u=a.__importStar(s(18)),o=s(9),x=s(12),m=s(59);class y extends n.XYGlyphView{initialize(){super.initialize();const{webgl:s}=this.renderer.plot_view.canvas_view;null!=s&&(this.glglyph=new h.MarkerGL(s.gl,this,\"circle\"))}get use_radius(){return!(this.radius.is_Scalar()&&isNaN(this.radius.value))}_map_data(){if(this.use_radius)if(\"data\"==this.model.properties.radius.units)switch(this.model.radius_dimension){case\"x\":this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius);break;case\"y\":this.sradius=this.sdist(this.renderer.yscale,this._y,this.radius);break;case\"max\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=x.map(s,((s,e)=>Math.max(s,i[e])));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=x.map(s,((s,e)=>Math.min(s,i[e])));break}}else this.sradius=l.to_screen(this.radius),this._configure(\"max_size\",{value:2*this.max_radius});else{const s=new l.ScreenArray(this.size);this.sradius=x.map(s,(s=>s/2))}}_mask_data(){const{frame:s}=this.renderer.plot_view,i=s.x_target,e=s.y_target;let t,r;return this.use_radius&&\"data\"==this.model.properties.radius.units?(t=i.map((s=>this.renderer.xscale.invert(s))).widen(this.max_radius),r=e.map((s=>this.renderer.yscale.invert(s))).widen(this.max_radius)):(t=i.widen(this.max_size).map((s=>this.renderer.xscale.invert(s))),r=e.widen(this.max_size).map((s=>this.renderer.yscale.invert(s)))),this.index.indices({x0:t.start,x1:t.end,y0:r.start,y1:r.end})}_render(s,i,e){const{sx:t,sy:r,sradius:a}=null!=e?e:this;for(const e of i){const i=t[e],n=r[e],h=a[e];isNaN(i+n+h)||(s.beginPath(),s.arc(i,n,h,0,2*Math.PI,!1),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(s,e),s.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_vectorize(s,e),s.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(s,e),s.stroke()))}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e),{hit_dilation:a}=this.model;let n,h,d,l;if(this.use_radius&&\"data\"==this.model.properties.radius.units)n=t-this.max_radius*a,h=t+this.max_radius*a,d=r-this.max_radius*a,l=r+this.max_radius*a;else{const s=i-this.max_size*a,t=i+this.max_size*a;[n,h]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size*a,c=e+this.max_size*a;[d,l]=this.renderer.yscale.r_invert(r,c)}const c=this.index.indices({x0:n,x1:h,y0:d,y1:l}),_=[];if(this.use_radius&&\"data\"==this.model.properties.radius.units)for(const s of c){const i=(this.sradius[s]*a)**2,[e,n]=this.renderer.xscale.r_compute(t,this._x[s]),[h,d]=this.renderer.yscale.r_compute(r,this._y[s]);(e-n)**2+(h-d)**2<=i&&_.push(s)}else for(const s of c){const t=(this.sradius[s]*a)**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&_.push(s)}return new m.Selection({indices:_})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new m.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new m.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=o.range(0,this.sx.length),r=[];for(let s=0,a=t.length;s({angle:[u.AngleSpec,0],size:[u.ScreenDistanceSpec,{value:4}],radius:[u.NullDistanceSpec,null],radius_dimension:[c.RadiusDimension,\"x\"],hit_dilation:[s,1]})))}}e.Circle=p,p.__name__=\"Circle\",p.init_Circle()},\n", " function _(t,e,s,i,a){i();const r=t(1),o=t(109),_=t(113),l=r.__importDefault(t(284)),h=r.__importDefault(t(285)),n=t(282),f=t(12),u=t(19),c=t(24),g=t(22),b=t(11);function d(t,e,s,i,a,r,o){if(a.doit)if(r.is_Scalar()&&o.is_Scalar()){e.used=!1;const[i,a,_,l]=g.color2rgba(r.value,o.value);t.set_attribute(s,\"vec4\",[i/255,a/255,_/255,l/255])}else{let a;if(e.used=!0,r.is_Vector()){const t=new c.ColorArray(r.array);if(a=new c.RGBAArray(t.buffer),!o.is_Scalar()||1!=o.value)for(let t=0;t2*t))),i.data_changed=!1),this.visuals_changed&&(this._set_visuals(a),this.visuals_changed=!1),this.prog.set_uniform(\"u_pixel_ratio\",\"float\",[s.pixel_ratio]),this.prog.set_uniform(\"u_canvas_size\",\"vec2\",[s.width,s.height]),this.prog.set_attribute(\"a_sx\",\"float\",i.vbo_sx),this.prog.set_attribute(\"a_sy\",\"float\",i.vbo_sy),this.prog.set_attribute(\"a_size\",\"float\",i.vbo_s),this.prog.set_attribute(\"a_angle\",\"float\",i.vbo_a),0!=t.length)if(t.length===a)this.prog.draw(this.gl.POINTS,[0,a]);else if(a<65535){const e=window.navigator.userAgent;e.indexOf(\"MSIE \")+e.indexOf(\"Trident/\")+e.indexOf(\"Edge/\")>0&&u.logger.warn(\"WebGL warning: IE is known to produce 1px sprites whith selections.\"),this.index_buffer.set_size(2*t.length),this.index_buffer.set_data(0,new Uint16Array(t)),this.prog.draw(this.gl.POINTS,this.index_buffer)}else{const e=64e3,s=[];for(let t=0,i=Math.ceil(a/e);t2*t))):this.vbo_s.set_data(0,new Float32Array(this.glyph.size))}_set_visuals(t){const{line:e,fill:s}=this.glyph.visuals;!function(t,e,s,i,a,r){if(a.doit){if(r.is_Scalar())e.used=!1,t.set_attribute(s,\"float\",[r.value]);else if(r.is_Vector()){e.used=!0;const a=new Float32Array(r.array);e.set_size(4*i),e.set_data(0,a),t.set_attribute(s,\"float\",e)}}else e.used=!1,t.set_attribute(s,\"float\",[0])}(this.prog,this.vbo_linewidth,\"a_linewidth\",t,e,e.line_width),d(this.prog,this.vbo_fg_color,\"a_fg_color\",t,e,e.line_color,e.line_alpha),d(this.prog,this.vbo_bg_color,\"a_bg_color\",t,s,s.fill_color,s.fill_alpha),this.prog.set_uniform(\"u_antialias\",\"float\",[.8])}}s.MarkerGL=p,p.__name__=\"MarkerGL\"},\n", " function _(n,i,a,o,_){o();a.default=\"\\nprecision mediump float;\\nconst float SQRT_2 = 1.4142135623730951;\\n//\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform vec2 u_offset;\\nuniform vec2 u_scale;\\nuniform float u_antialias;\\n//\\nattribute float a_sx;\\nattribute float a_sy;\\nattribute float a_size;\\nattribute float a_angle; // in radians\\nattribute float a_linewidth;\\nattribute vec4 a_fg_color;\\nattribute vec4 a_bg_color;\\n//\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec4 v_fg_color;\\nvarying vec4 v_bg_color;\\nvarying vec2 v_rotation;\\n\\nvoid main (void)\\n{\\n v_size = a_size * u_pixel_ratio;\\n v_linewidth = a_linewidth * u_pixel_ratio;\\n v_fg_color = a_fg_color;\\n v_bg_color = a_bg_color;\\n v_rotation = vec2(cos(-a_angle), sin(-a_angle));\\n vec2 pos = vec2(a_sx, a_sy); // in pixels\\n pos += 0.5; // make up for Bokeh's offset\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(pos*2.0-1.0, 0.0, 1.0);\\n gl_Position.y *= -1.0;\\n gl_PointSize = SQRT_2 * v_size + 2.0 * (v_linewidth + 1.5*u_antialias);\\n}\\n\"},\n", " function _(n,a,s,e,t){e();s.default='\\nprecision mediump float;\\n\\nconst float SQRT_2 = 1.4142135623730951;\\nconst float PI = 3.14159265358979323846264;\\n\\nconst float IN_ANGLE = 0.6283185307179586; // PI/5. = 36 degrees (star of 5 pikes)\\n//const float OUT_ANGLE = PI/2. - IN_ANGLE; // External angle for regular stars\\nconst float COS_A = 0.8090169943749475; // cos(IN_ANGLE)\\nconst float SIN_A = 0.5877852522924731; // sin(IN_ANGLE)\\nconst float COS_B = 0.5877852522924731; // cos(OUT_ANGLE)\\nconst float SIN_B = 0.8090169943749475; // sin(OUT_ANGLE)\\n\\n//\\nuniform float u_antialias;\\n//\\nvarying vec4 v_fg_color;\\nvarying vec4 v_bg_color;\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec2 v_rotation;\\n\\n#ifdef USE_ASTERISK\\n// asterisk\\nfloat marker(vec2 P, float size)\\n{\\n // Masks\\n float diamond = max(abs(SQRT_2 / 2.0 * (P.x - P.y)), abs(SQRT_2 / 2.0 * (P.x + P.y))) - size / (2.0 * SQRT_2);\\n float square = max(abs(P.x), abs(P.y)) - size / (2.0 * SQRT_2);\\n // Shapes\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n float cross = min(abs(P.x), abs(P.y)) - size / 100.0; // bit of \"width\" for aa\\n // Result is union of masked shapes\\n return min(max(X, diamond), max(cross, square));\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE\\n// circle\\nfloat marker(vec2 P, float size)\\n{\\n return length(P) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_SQUARE\\n// square\\nfloat marker(vec2 P, float size)\\n{\\n return max(abs(P.x), abs(P.y)) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND\\n// diamond\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n return r1 / SQRT_2;\\n}\\n#endif\\n\\n#ifdef USE_HEX\\n// hex\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n return max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n}\\n#endif\\n\\n#ifdef USE_STAR\\n// star\\n// https://iquilezles.org/www/articles/distfunctions2d/distfunctions2d.htm\\nfloat marker(vec2 P, float size)\\n{\\n float bn = mod(atan(P.x, -P.y), 2.0*IN_ANGLE) - IN_ANGLE;\\n P = length(P)*vec2(cos(bn), abs(sin(bn)));\\n P -= size*vec2(COS_A, SIN_A)/2.;\\n P += vec2(COS_B, SIN_B)*clamp(-(P.x*COS_B + P.y*SIN_B), 0.0, size*SIN_A/SIN_B/2.);\\n\\n return length(P)*sign(P.x);\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE\\n// triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_INVERTED_TRIANGLE\\n// inverted_triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y += size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = - P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_CROSS\\n// cross\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.5; // 2.5 is a tweak\\n float cross = min(abs(P.x), abs(P.y)) - size / 100.0; // bit of \"width\" for aa\\n return max(square, cross);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_CROSS\\n// circle_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_CROSS\\n// square_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND_CROSS\\n// diamond_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float diamond = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n diamond /= SQRT_2;\\n float c1 = max(diamond, s1);\\n float c2 = max(diamond, s2);\\n float c3 = max(diamond, s3);\\n float c4 = max(diamond, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_X\\n// x\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 1.6;\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n return max(circle, X);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_X\\n// circle_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n float almost = min(min(min(c1, c2), c3), c4);\\n // In this case, the X is also outside of the main shape\\n float Xmask = length(P) - size / 1.6; // a circle\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n return min(max(X, Xmask), almost);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_X\\n// square_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\nvec4 outline(float distance, float linewidth, float antialias, vec4 fg_color, vec4 bg_color)\\n{\\n vec4 frag_color;\\n float t = linewidth/2.0 - antialias;\\n float signed_distance = distance;\\n float border_distance = abs(signed_distance) - t;\\n float alpha = border_distance/antialias;\\n alpha = exp(-alpha*alpha);\\n\\n // If fg alpha is zero, it probably means no outline. To avoid a dark outline\\n // shining through due to aa, we set the fg color to the bg color. Avoid if (i.e. branching).\\n float select = float(bool(fg_color.a));\\n fg_color.rgb = select * fg_color.rgb + (1.0 - select) * bg_color.rgb;\\n // Similarly, if we want a transparent bg\\n select = float(bool(bg_color.a));\\n bg_color.rgb = select * bg_color.rgb + (1.0 - select) * fg_color.rgb;\\n\\n if( border_distance < 0.0)\\n frag_color = fg_color;\\n else if( signed_distance < 0.0 ) {\\n frag_color = mix(bg_color, fg_color, sqrt(alpha));\\n } else {\\n if( abs(signed_distance) < (linewidth/2.0 + antialias) ) {\\n frag_color = vec4(fg_color.rgb, fg_color.a * alpha);\\n } else {\\n discard;\\n }\\n }\\n return frag_color;\\n}\\n\\nvoid main()\\n{\\n vec2 P = gl_PointCoord.xy - vec2(0.5, 0.5);\\n P = vec2(v_rotation.x*P.x - v_rotation.y*P.y,\\n v_rotation.y*P.x + v_rotation.x*P.y);\\n float point_size = SQRT_2*v_size + 2.0 * (v_linewidth + 1.5*u_antialias);\\n float distance = marker(P*point_size, v_size);\\n gl_FragColor = outline(distance, v_linewidth, u_antialias, v_fg_color, v_bg_color);\\n}\\n'},\n", " function _(e,l,i,s,t){s();const _=e(287);class p extends _.EllipseOvalView{}i.EllipseView=p,p.__name__=\"EllipseView\";class n extends _.EllipseOval{constructor(e){super(e)}static init_Ellipse(){this.prototype.default_view=p}}i.Ellipse=n,n.__name__=\"Ellipse\",n.init_Ellipse()},\n", " function _(t,s,i,e,h){e();const r=t(1),a=t(288),n=r.__importStar(t(107)),l=t(24),o=t(59),_=r.__importStar(t(18));class d extends a.CenterRotatableView{_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"):this.sw=l.to_screen(this.width),\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"):this.sh=l.to_screen(this.height)}_render(t,s,i){const{sx:e,sy:h,sw:r,sh:a,angle:n}=null!=i?i:this;for(const i of s){const s=e[i],l=h[i],o=r[i],_=a[i],d=n.get(i);isNaN(s+l+o+_+d)||(t.beginPath(),t.ellipse(s,l,o/2,_/2,d,0,2*Math.PI),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(t,i),t.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_vectorize(t,i),t.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(t,i),t.stroke()))}}_hit_point(t){let s,i,e,h,r,a,l,_,d;const{sx:c,sy:w}=t,x=this.renderer.xscale.invert(c),p=this.renderer.yscale.invert(w);\"data\"==this.model.properties.width.units?(s=x-this.max_width,i=x+this.max_width):(a=c-this.max_width,l=c+this.max_width,[s,i]=this.renderer.xscale.r_invert(a,l)),\"data\"==this.model.properties.height.units?(e=p-this.max_height,h=p+this.max_height):(_=w-this.max_height,d=w+this.max_height,[e,h]=this.renderer.yscale.r_invert(_,d));const m=this.index.indices({x0:s,x1:i,y0:e,y1:h}),v=[];for(const t of m)r=n.point_in_ellipse(c,w,this.angle.get(t),this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),r&&v.push(t);return new o.Selection({indices:v})}draw_legend_for_index(t,{x0:s,y0:i,x1:e,y1:h},r){const a=r+1,n=new Array(a);n[r]=(s+e)/2;const l=new Array(a);l[r]=(i+h)/2;const o=this.sw[r]/this.sh[r],d=.8*Math.min(Math.abs(e-s),Math.abs(h-i)),c=new Array(a),w=new Array(a);o>1?(c[r]=d,w[r]=d/o):(c[r]=d*o,w[r]=d);const x=new _.UniformScalar(0,a);this._render(t,[r],{sx:n,sy:l,sw:c,sh:w,angle:x})}}i.EllipseOvalView=d,d.__name__=\"EllipseOvalView\";class c extends a.CenterRotatable{constructor(t){super(t)}}i.EllipseOval=c,c.__name__=\"EllipseOval\"},\n", " function _(t,e,i,a,n){a();const s=t(1),h=t(64),r=t(48),o=s.__importStar(t(18));class _ extends h.XYGlyphView{get max_w2(){return\"data\"==this.model.properties.width.units?this.max_width/2:0}get max_h2(){return\"data\"==this.model.properties.height.units?this.max_height/2:0}_bounds({x0:t,x1:e,y0:i,y1:a}){const{max_w2:n,max_h2:s}=this;return{x0:t-n,x1:e+n,y0:i-s,y1:a+s}}}i.CenterRotatableView=_,_.__name__=\"CenterRotatableView\";class l extends h.XYGlyph{constructor(t){super(t)}static init_CenterRotatable(){this.mixins([r.LineVector,r.FillVector,r.HatchVector]),this.define((({})=>({angle:[o.AngleSpec,0],width:[o.DistanceSpec,{field:\"width\"}],height:[o.DistanceSpec,{field:\"height\"}]})))}}i.CenterRotatable=l,l.__name__=\"CenterRotatable\",l.init_CenterRotatable()},\n", " function _(t,e,s,i,h){i();const r=t(1),a=t(290),n=t(24),_=r.__importStar(t(18));class o extends a.BoxView{scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){const e=this._left[t],s=this._right[t],i=this._y[t],h=this.height.get(t)/2;return[Math.min(e,s),Math.max(e,s),i+h,i-h]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new n.ScreenArray(t),this.sbottom=new n.ScreenArray(t);for(let e=0;e({left:[_.XCoordinateSpec,{value:0}],y:[_.YCoordinateSpec,{field:\"y\"}],height:[_.NumberSpec,{value:1}],right:[_.XCoordinateSpec,{field:\"right\"}]})))}}s.HBar=c,c.__name__=\"HBar\",c.init_HBar()},\n", " function _(t,e,s,i,r){i();const n=t(48),o=t(98),a=t(106),h=t(59);class c extends o.GlyphView{get_anchor_point(t,e,s){const i=Math.min(this.sleft[e],this.sright[e]),r=Math.max(this.sright[e],this.sleft[e]),n=Math.min(this.stop[e],this.sbottom[e]),o=Math.max(this.sbottom[e],this.stop[e]);switch(t){case\"top_left\":return{x:i,y:n};case\"top\":case\"top_center\":return{x:(i+r)/2,y:n};case\"top_right\":return{x:r,y:n};case\"bottom_left\":return{x:i,y:o};case\"bottom\":case\"bottom_center\":return{x:(i+r)/2,y:o};case\"bottom_right\":return{x:r,y:o};case\"left\":case\"center_left\":return{x:i,y:(n+o)/2};case\"center\":case\"center_center\":return{x:(i+r)/2,y:(n+o)/2};case\"right\":case\"center_right\":return{x:r,y:(n+o)/2}}}_index_data(t){const{min:e,max:s}=Math,{data_size:i}=this;for(let r=0;r({r:[c.NumberSpec,{field:\"r\"}],q:[c.NumberSpec,{field:\"q\"}],scale:[c.NumberSpec,1],size:[e,1],aspect_scale:[e,1],orientation:[h.HexTileOrientation,\"pointytop\"]}))),this.override({line_color:null})}}s.HexTile=y,y.__name__=\"HexTile\",y.init_HexTile()},\n", " function _(e,a,t,_,s){_();const i=e(293),n=e(203),r=e(214);class o extends i.ImageBaseView{connect_signals(){super.connect_signals(),this.connect(this.model.color_mapper.change,(()=>this._update_image()))}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}t.ImageView=o,o.__name__=\"ImageView\";class m extends i.ImageBase{constructor(e){super(e)}static init_Image(){this.prototype.default_view=o,this.define((({Ref:e})=>({color_mapper:[e(n.ColorMapper),()=>new r.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})))}}t.Image=m,m.__name__=\"Image\",m.init_Image()},\n", " function _(e,t,i,s,a){s();const h=e(1),n=e(64),r=e(24),_=h.__importStar(e(18)),d=e(59),l=e(9),g=e(29),o=e(11);class c extends n.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_render(e,t,i){const{image_data:s,sx:a,sy:h,sw:n,sh:r}=null!=i?i:this,_=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1),e.globalAlpha=this.model.global_alpha;for(const i of t){const t=s[i],_=a[i],d=h[i],l=n[i],g=r[i];if(null==t||isNaN(_+d+l+g))continue;const o=d;e.translate(0,o),e.scale(1,-1),e.translate(0,-o),e.drawImage(t,0|_,0|d,l,g),e.translate(0,o),e.scale(1,-1),e.translate(0,-o)}e.setImageSmoothingEnabled(_)}_set_data(e){this._set_width_heigh_data();for(let t=0,i=this.image.length;t({image:[_.NDArraySpec,{field:\"image\"}],dw:[_.DistanceSpec,{field:\"dw\"}],dh:[_.DistanceSpec,{field:\"dh\"}],dilate:[e,!1],global_alpha:[t,1]})))}}i.ImageBase=m,m.__name__=\"ImageBase\",m.init_ImageBase()},\n", " function _(e,a,t,_,i){_();const n=e(293),s=e(8);class r extends n.ImageBaseView{_flat_img_to_buf8(e){let a;return a=s.isArray(e)?new Uint32Array(e):e,new Uint8ClampedArray(a.buffer)}}t.ImageRGBAView=r,r.__name__=\"ImageRGBAView\";class m extends n.ImageBase{constructor(e){super(e)}static init_ImageRGBA(){this.prototype.default_view=r}}t.ImageRGBA=m,m.__name__=\"ImageRGBA\",m.init_ImageRGBA()},\n", " function _(e,t,s,r,a){r();const i=e(1),n=e(64),o=e(24),c=e(20),_=i.__importStar(e(18)),h=e(12),l=e(296);class d extends n.XYGlyphView{constructor(){super(...arguments),this._images_rendered=!1,this._set_data_iteration=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_index_data(e){const{data_size:t}=this;for(let s=0;s{this._set_data_iteration==r&&(this.image[a]=e,this.renderer.request_render())},attempts:t+1,timeout:s})}const a=\"data\"==this.model.properties.w.units,i=\"data\"==this.model.properties.h.units,n=this._x.length,c=new o.ScreenArray(a?2*n:n),_=new o.ScreenArray(i?2*n:n),{anchor:d}=this.model;function m(e,t){switch(d){case\"top_left\":case\"bottom_left\":case\"left\":case\"center_left\":return[e,e+t];case\"top\":case\"top_center\":case\"bottom\":case\"bottom_center\":case\"center\":case\"center_center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"right\":case\"center_right\":return[e-t,e]}}function g(e,t){switch(d){case\"top_left\":case\"top\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"left\":case\"center_left\":case\"center\":case\"center_center\":case\"right\":case\"center_right\":return[e+t/2,e-t/2]}}if(a)for(let e=0;e({url:[_.StringSpec,{field:\"url\"}],anchor:[c.Anchor,\"top_left\"],global_alpha:[s,1],angle:[_.AngleSpec,0],w:[_.NullDistanceSpec,null],h:[_.NullDistanceSpec,null],dilate:[e,!1],retry_attempts:[t,0],retry_timeout:[t,0]})))}}s.ImageURL=m,m.__name__=\"ImageURL\",m.init_ImageURL()},\n", " function _(i,e,t,s,o){s();const a=i(19);class n{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:s=1}=e;this.promise=new Promise(((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const s=`unable to load ${i} image after ${t} attempts`;if(a.logger.warn(s),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());a.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout((()=>this._image.src=i),s)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i}))}get finished(){return this._finished}get image(){if(this._finished)return this._image;throw new Error(\"not loaded yet\")}}t.ImageLoader=n,n.__name__=\"ImageLoader\"},\n", " function _(t,s,e,i,n){i();const o=t(1),l=t(101),r=t(98),h=t(106),_=t(12),a=t(12),c=t(48),d=o.__importStar(t(107)),x=o.__importStar(t(18)),y=t(59),f=t(11);class g extends r.GlyphView{_project_data(){}_index_data(t){const{min:s,max:e}=Math,{data_size:i}=this;for(let n=0;n1&&c.length>1)for(let e=1,i=n.length;e1){let l=!1;for(let t=1;t({xs:[x.XCoordinateSeqSeqSeqSpec,{field:\"xs\"}],ys:[x.YCoordinateSeqSeqSeqSpec,{field:\"ys\"}]}))),this.mixins([c.LineVector,c.FillVector,c.HatchVector])}}e.MultiPolygons=p,p.__name__=\"MultiPolygons\",p.init_MultiPolygons()},\n", " function _(a,t,e,l,s){l();const _=a(287),i=a(12);class n extends _.EllipseOvalView{_map_data(){super._map_data(),i.mul(this.sw,.75)}}e.OvalView=n,n.__name__=\"OvalView\";class v extends _.EllipseOval{constructor(a){super(a)}static init_Oval(){this.prototype.default_view=n}}e.Oval=v,v.__name__=\"Oval\",v.init_Oval()},\n", " function _(t,e,i,o,s){o();const r=t(1),_=t(290),d=r.__importStar(t(18));class n extends _.BoxView{scenterxy(t){return[this.sleft[t]/2+this.sright[t]/2,this.stop[t]/2+this.sbottom[t]/2]}_lrtb(t){return[this._left[t],this._right[t],this._top[t],this._bottom[t]]}}i.QuadView=n,n.__name__=\"QuadView\";class a extends _.Box{constructor(t){super(t)}static init_Quad(){this.prototype.default_view=n,this.define((({})=>({right:[d.XCoordinateSpec,{field:\"right\"}],bottom:[d.YCoordinateSpec,{field:\"bottom\"}],left:[d.XCoordinateSpec,{field:\"left\"}],top:[d.YCoordinateSpec,{field:\"top\"}]})))}}i.Quad=a,a.__name__=\"Quad\",a.init_Quad()},\n", " function _(e,t,i,s,n){s();const a=e(1),c=e(48),o=e(65),r=e(98),_=e(106),d=a.__importStar(e(18));function l(e,t,i){if(t==(e+i)/2)return[e,i];{const s=(e-t)/(e-2*t+i),n=e*(1-s)**2+2*t*(1-s)*s+i*s**2;return[Math.min(e,i,n),Math.max(e,i,n)]}}class x extends r.GlyphView{_project_data(){o.inplace.project_xy(this._x0,this._y0),o.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{_x0:t,_x1:i,_y0:s,_y1:n,_cx:a,_cy:c,data_size:o}=this;for(let r=0;r({x0:[d.XCoordinateSpec,{field:\"x0\"}],y0:[d.YCoordinateSpec,{field:\"y0\"}],x1:[d.XCoordinateSpec,{field:\"x1\"}],y1:[d.YCoordinateSpec,{field:\"y1\"}],cx:[d.XCoordinateSpec,{field:\"cx\"}],cy:[d.YCoordinateSpec,{field:\"cy\"}]}))),this.mixins(c.LineVector)}}i.Quadratic=y,y.__name__=\"Quadratic\",y.init_Quadratic()},\n", " function _(e,t,s,i,n){i();const a=e(1),l=e(64),h=e(106),r=e(48),o=e(24),_=a.__importStar(e(18));class c extends l.XYGlyphView{_map_data(){\"data\"==this.model.properties.length.units?this.slength=this.sdist(this.renderer.xscale,this._x,this.length):this.slength=o.to_screen(this.length);const{width:e,height:t}=this.renderer.plot_view.frame.bbox,s=2*(e+t),{slength:i}=this;for(let e=0,t=i.length;e({length:[_.DistanceSpec,0],angle:[_.AngleSpec,0]})))}}s.Ray=g,g.__name__=\"Ray\",g.init_Ray()},\n", " function _(t,s,e,i,h){i();const r=t(288),n=t(106),a=t(24),o=t(12),l=t(59);class _ extends r.CenterRotatableView{_map_data(){if(\"data\"==this.model.properties.width.units)[this.sw,this.sx0]=this._map_dist_corner_for_data_side_length(this._x,this.width,this.renderer.xscale);else{this.sw=a.to_screen(this.width);const t=this.sx.length;this.sx0=new a.ScreenArray(t);for(let s=0;s({dilate:[t,!1]})))}}e.Rect=c,c.__name__=\"Rect\",c.init_Rect()},\n", " function _(e,t,r,s,i){s();const a=e(1),n=e(304),_=e(305),l=e(283),c=a.__importStar(e(18));class o extends n.MarkerView{_init_webgl(){const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e){const t=new Set(this.marker);if(1==t.size){const[r]=[...t];if(l.MarkerGL.is_supported(r)){const{glglyph:t}=this;if(null==t||t.marker_type!=r)return void(this.glglyph=new l.MarkerGL(e.gl,this,r))}}}delete this.glglyph}_set_data(e){super._set_data(e),this._init_webgl()}_render(e,t,r){const{sx:s,sy:i,size:a,angle:n,marker:l}=null!=r?r:this;for(const r of t){const t=s[r],c=i[r],o=a.get(r),g=n.get(r),h=l.get(r);if(isNaN(t+c+o+g)||null==h)continue;const d=o/2;e.beginPath(),e.translate(t,c),g&&e.rotate(g),_.marker_funcs[h](e,r,d,this.visuals),g&&e.rotate(-g),e.translate(-t,-c)}}draw_legend_for_index(e,{x0:t,x1:r,y0:s,y1:i},a){const n=a+1,_=this.marker.get(a),l=Object.assign(Object.assign({},this._get_legend_args({x0:t,x1:r,y0:s,y1:i},a)),{marker:new c.UniformScalar(_,n)});this._render(e,[a],l)}}r.ScatterView=o,o.__name__=\"ScatterView\";class g extends n.Marker{constructor(e){super(e)}static init_Scatter(){this.prototype.default_view=o,this.define((()=>({marker:[c.MarkerSpec,{value:\"circle\"}]})))}}r.Scatter=g,g.__name__=\"Scatter\",g.init_Scatter()},\n", " function _(e,t,s,i,n){i();const r=e(1),a=e(64),c=e(48),_=r.__importStar(e(107)),o=r.__importStar(e(18)),h=e(9),l=e(59);class x extends a.XYGlyphView{_render(e,t,s){const{sx:i,sy:n,size:r,angle:a}=null!=s?s:this;for(const s of t){const t=i[s],c=n[s],_=r.get(s),o=a.get(s);if(isNaN(t+c+_+o))continue;const h=_/2;e.beginPath(),e.translate(t,c),o&&e.rotate(o),this._render_one(e,s,h,this.visuals),o&&e.rotate(-o),e.translate(-t,-c)}}_mask_data(){const{x_target:e,y_target:t}=this.renderer.plot_view.frame,s=e.widen(this.max_size).map((e=>this.renderer.xscale.invert(e))),i=t.widen(this.max_size).map((e=>this.renderer.yscale.invert(e)));return this.index.indices({x0:s.start,x1:s.end,y0:i.start,y1:i.end})}_hit_point(e){const{sx:t,sy:s}=e,{max_size:i}=this,{hit_dilation:n}=this.model,r=t-i*n,a=t+i*n,[c,_]=this.renderer.xscale.r_invert(r,a),o=s-i*n,h=s+i*n,[x,d]=this.renderer.yscale.r_invert(o,h),y=this.index.indices({x0:c,x1:_,y0:x,y1:d}),g=[];for(const e of y){const i=this.size.get(e)/2*n;Math.abs(this.sx[e]-t)<=i&&Math.abs(this.sy[e]-s)<=i&&g.push(e)}return new l.Selection({indices:g})}_hit_span(e){const{sx:t,sy:s}=e,i=this.bounds(),n=this.max_size/2;let r,a,c,_;if(\"h\"==e.direction){c=i.y0,_=i.y1;const e=t-n,s=t+n;[r,a]=this.renderer.xscale.r_invert(e,s)}else{r=i.x0,a=i.x1;const e=s-n,t=s+n;[c,_]=this.renderer.yscale.r_invert(e,t)}const o=[...this.index.indices({x0:r,x1:a,y0:c,y1:_})];return new l.Selection({indices:o})}_hit_rect(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.xscale.r_invert(t,s),[c,_]=this.renderer.yscale.r_invert(i,n),o=[...this.index.indices({x0:r,x1:a,y0:c,y1:_})];return new l.Selection({indices:o})}_hit_poly(e){const{sx:t,sy:s}=e,i=h.range(0,this.sx.length),n=[];for(let e=0,r=i.length;e({size:[o.ScreenDistanceSpec,{value:4}],angle:[o.AngleSpec,0],hit_dilation:[e,1]})))}}s.Marker=d,d.__name__=\"Marker\",d.init_Marker()},\n", " function _(t,e,i,o,l){o();const n=Math.sqrt(3),c=Math.sqrt(5),r=(c+1)/4,s=Math.sqrt((5-c)/8),f=(c-1)/4,a=Math.sqrt((5+c)/8);function h(t,e){t.rotate(Math.PI/4),d(t,e),t.rotate(-Math.PI/4)}function v(t,e){const i=e*n,o=i/3;t.moveTo(-i/2,-o),t.lineTo(0,0),t.lineTo(i/2,-o),t.lineTo(0,0),t.lineTo(0,e)}function d(t,e){t.moveTo(0,e),t.lineTo(0,-e),t.moveTo(-e,0),t.lineTo(e,0)}function _(t,e){t.moveTo(0,e),t.lineTo(e/1.5,0),t.lineTo(0,-e),t.lineTo(-e/1.5,0),t.closePath()}function u(t,e){const i=e*n,o=i/3;t.moveTo(-e,o),t.lineTo(e,o),t.lineTo(0,o-i),t.closePath()}function z(t,e,i,o){t.arc(0,0,i,0,2*Math.PI,!1),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}function T(t,e,i,o){_(t,i),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}function k(t,e,i,o){!function(t,e){t.beginPath(),t.arc(0,0,e/4,0,2*Math.PI,!1),t.closePath()}(t,i),o.line.set_vectorize(t,e),t.fillStyle=t.strokeStyle,t.fill()}function P(t,e,i,o){!function(t,e){const i=e/2,o=n*i;t.moveTo(e,0),t.lineTo(i,-o),t.lineTo(-i,-o),t.lineTo(-e,0),t.lineTo(-i,o),t.lineTo(i,o),t.closePath()}(t,i),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}function m(t,e,i,o){const l=2*i;t.rect(-i,-i,l,l),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}function q(t,e,i,o){!function(t,e){const i=Math.sqrt(5-2*c)*e;t.moveTo(0,-e),t.lineTo(i*f,i*a-e),t.lineTo(i*(1+f),i*a-e),t.lineTo(i*(1+f-r),i*(a+s)-e),t.lineTo(i*(1+2*f-r),i*(2*a+s)-e),t.lineTo(0,2*i*a-e),t.lineTo(-i*(1+2*f-r),i*(2*a+s)-e),t.lineTo(-i*(1+f-r),i*(a+s)-e),t.lineTo(-i*(1+f),i*a-e),t.lineTo(-i*f,i*a-e),t.closePath()}(t,i),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}function M(t,e,i,o){u(t,i),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}i.marker_funcs={asterisk:function(t,e,i,o){d(t,i),h(t,i),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},circle:z,circle_cross:function(t,e,i,o){t.arc(0,0,i,0,2*Math.PI,!1),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),d(t,i),t.stroke())},circle_dot:function(t,e,i,o){z(t,e,i,o),k(t,e,i,o)},circle_y:function(t,e,i,o){t.arc(0,0,i,0,2*Math.PI,!1),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),v(t,i),t.stroke())},circle_x:function(t,e,i,o){t.arc(0,0,i,0,2*Math.PI,!1),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),h(t,i),t.stroke())},cross:function(t,e,i,o){d(t,i),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},diamond:T,diamond_dot:function(t,e,i,o){T(t,e,i,o),k(t,e,i,o)},diamond_cross:function(t,e,i,o){_(t,i),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.moveTo(0,i),t.lineTo(0,-i),t.moveTo(-i/1.5,0),t.lineTo(i/1.5,0),t.stroke())},dot:k,hex:P,hex_dot:function(t,e,i,o){P(t,e,i,o),k(t,e,i,o)},inverted_triangle:function(t,e,i,o){t.rotate(Math.PI),u(t,i),t.rotate(-Math.PI),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},plus:function(t,e,i,o){const l=3*i/8,n=[l,l,i,i,l,l,-l,-l,-i,-i,-l,-l],c=[i,l,l,-l,-l,-i,-i,-l,-l,l,l,i];t.beginPath();for(let e=0;e<12;e++)t.lineTo(n[e],c[e]);t.closePath(),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},square:m,square_cross:function(t,e,i,o){const l=2*i;t.rect(-i,-i,l,l),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),d(t,i),t.stroke())},square_dot:function(t,e,i,o){m(t,e,i,o),k(t,e,i,o)},square_pin:function(t,e,i,o){const l=3*i/8;t.moveTo(-i,-i),t.quadraticCurveTo(0,-l,i,-i),t.quadraticCurveTo(l,0,i,i),t.quadraticCurveTo(0,l,-i,i),t.quadraticCurveTo(-l,0,-i,-i),t.closePath(),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},square_x:function(t,e,i,o){const l=2*i;t.rect(-i,-i,l,l),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.moveTo(-i,i),t.lineTo(i,-i),t.moveTo(-i,-i),t.lineTo(i,i),t.stroke())},star:q,star_dot:function(t,e,i,o){q(t,e,i,o),k(t,e,i,o)},triangle:M,triangle_dot:function(t,e,i,o){M(t,e,i,o),k(t,e,i,o)},triangle_pin:function(t,e,i,o){const l=i*n,c=l/3,r=3*c/8;t.moveTo(-i,c),t.quadraticCurveTo(0,r,i,c),t.quadraticCurveTo(n*r/2,r/2,0,c-l),t.quadraticCurveTo(-n*r/2,r/2,-i,c),t.closePath(),o.fill.doit&&(o.fill.set_vectorize(t,e),t.fill()),o.hatch.doit&&(o.hatch.set_vectorize(t,e),t.fill()),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},dash:function(t,e,i,o){!function(t,e){t.moveTo(-e,0),t.lineTo(e,0)}(t,i),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},x:function(t,e,i,o){h(t,i),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())},y:function(t,e,i,o){v(t,i),o.line.doit&&(o.line.set_vectorize(t,e),t.stroke())}}},\n", " function _(e,t,s,i,n){i();const r=e(1),_=r.__importStar(e(107)),o=r.__importStar(e(18)),h=e(48),a=e(65),c=e(98),d=e(106),x=e(59);class y extends c.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{min:t,max:s}=Math,{_x0:i,_x1:n,_y0:r,_y1:_,data_size:o}=this;for(let h=0;h({x0:[o.XCoordinateSpec,{field:\"x0\"}],y0:[o.YCoordinateSpec,{field:\"y0\"}],x1:[o.XCoordinateSpec,{field:\"x1\"}],y1:[o.YCoordinateSpec,{field:\"y1\"}]}))),this.mixins(h.LineVector)}}s.Segment=l,l.__name__=\"Segment\",l.init_Segment()},\n", " function _(t,e,s,i,n){i();const _=t(1),l=t(64),o=_.__importStar(t(48)),a=t(308);class c extends l.XYGlyphView{_set_data(){const{tension:t,closed:e}=this.model;[this._xt,this._yt]=a.catmullrom_spline(this._x,this._y,20,t,e)}_map_data(){const{x_scale:t,y_scale:e}=this.renderer.coordinates;this.sxt=t.v_compute(this._xt),this.syt=e.v_compute(this._yt)}_render(t,e,s){const{sxt:i,syt:n}=null!=s?s:this;this.visuals.line.set_value(t);const _=i.length;for(let e=0;e<_;e++)0!=e?isNaN(i[e])||isNaN(n[e])?(t.stroke(),t.beginPath()):t.lineTo(i[e],n[e]):(t.beginPath(),t.moveTo(i[e],n[e]));t.stroke()}}s.SplineView=c,c.__name__=\"SplineView\";class h extends l.XYGlyph{constructor(t){super(t)}static init_Spline(){this.prototype.default_view=c,this.mixins(o.LineScalar),this.define((({Boolean:t,Number:e})=>({tension:[e,.5],closed:[t,!1]})))}}s.Spline=h,h.__name__=\"Spline\",h.init_Spline()},\n", " function _(n,t,e,o,s){o();const c=n(24),l=n(11);e.catmullrom_spline=function(n,t,e=10,o=.5,s=!1){l.assert(n.length==t.length);const r=n.length,f=s?r+1:r,w=c.infer_type(n,t),i=new w(f+2),u=new w(f+2);i.set(n,1),u.set(t,1),s?(i[0]=n[r-1],u[0]=t[r-1],i[f]=n[0],u[f]=t[0],i[f+1]=n[1],u[f+1]=t[1]):(i[0]=n[0],u[0]=t[0],i[f+1]=n[r-1],u[f+1]=t[r-1]);const g=new w(4*(e+1));for(let n=0,t=0;n<=e;n++){const o=n/e,s=o**2,c=o*s;g[t++]=2*c-3*s+1,g[t++]=-2*c+3*s,g[t++]=c-2*s+o,g[t++]=c-s}const h=new w((f-1)*(e+1)),_=new w((f-1)*(e+1));for(let n=1,t=0;n1&&(e.stroke(),o=!1)}o?(e.lineTo(t,a),e.lineTo(r,_)):(e.beginPath(),e.moveTo(n[i],s[i]),o=!0),l=i}e.lineTo(n[r-1],s[r-1]),e.stroke()}}draw_legend_for_index(e,t,i){r.generic_line_scalar_legend(this.visuals,e,t)}}i.StepView=c,c.__name__=\"StepView\";class d extends l.XYGlyph{constructor(e){super(e)}static init_Step(){this.prototype.default_view=c,this.mixins(a.LineScalar),this.define((()=>({mode:[_.StepMode,\"before\"]})))}}i.Step=d,d.__name__=\"Step\",d.init_Step()},\n", " function _(t,e,s,i,n){i();const o=t(1),_=t(64),h=t(48),l=o.__importStar(t(107)),r=o.__importStar(t(18)),a=t(143),c=t(11),x=t(59);class u extends _.XYGlyphView{_rotate_point(t,e,s,i,n){return[(t-s)*Math.cos(n)-(e-i)*Math.sin(n)+s,(t-s)*Math.sin(n)+(e-i)*Math.cos(n)+i]}_text_bounds(t,e,s,i){return[[t,t+s,t+s,t,t],[e,e,e-i,e-i,e]]}_render(t,e,s){const{sx:i,sy:n,x_offset:o,y_offset:_,angle:h,text:l}=null!=s?s:this;this._sys=[],this._sxs=[];for(const s of e){const e=this._sxs[s]=[],r=this._sys[s]=[],c=i[s],x=n[s],u=o.get(s),f=_.get(s),p=h.get(s),g=l.get(s);if(!isNaN(c+x+u+f+p)&&null!=g&&this.visuals.text.doit){const i=`${g}`;t.save(),t.translate(c+u,x+f),t.rotate(p),this.visuals.text.set_vectorize(t,s);const n=this.visuals.text.font_value(s),{height:o}=a.font_metrics(n),_=this.text_line_height.get(s)*o;if(-1==i.indexOf(\"\\n\")){t.fillText(i,0,0);const s=c+u,n=x+f,o=t.measureText(i).width,[h,l]=this._text_bounds(s,n,o,_);e.push(h),r.push(l)}else{const n=i.split(\"\\n\"),o=_*n.length,h=this.text_baseline.get(s);let l;switch(h){case\"top\":l=0;break;case\"middle\":l=-o/2+_/2;break;case\"bottom\":l=-o+_;break;default:l=0,console.warn(`'${h}' baseline not supported with multi line text`)}for(const s of n){t.fillText(s,0,l);const i=c+u,n=l+x+f,o=t.measureText(s).width,[h,a]=this._text_bounds(i,n,o,_);e.push(h),r.push(a),l+=_}}t.restore()}}}_hit_point(t){const{sx:e,sy:s}=t,i=[];for(let t=0;t({text:[r.NullStringSpec,{field:\"text\"}],angle:[r.AngleSpec,0],x_offset:[r.NumberSpec,0],y_offset:[r.NumberSpec,0]})))}}s.Text=f,f.__name__=\"Text\",f.init_Text()},\n", " function _(t,s,e,i,r){i();const h=t(1),o=t(290),a=t(24),n=h.__importStar(t(18));class _ extends o.BoxView{scenterxy(t){return[this.sx[t],(this.stop[t]+this.sbottom[t])/2]}_lrtb(t){const s=this.width.get(t)/2,e=this._x[t],i=this._top[t],r=this._bottom[t];return[e-s,e+s,Math.max(i,r),Math.min(i,r)]}_map_data(){this.sx=this.renderer.xscale.v_compute(this._x),this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"),this.stop=this.renderer.yscale.v_compute(this._top),this.sbottom=this.renderer.yscale.v_compute(this._bottom);const t=this.sx.length;this.sleft=new a.ScreenArray(t),this.sright=new a.ScreenArray(t);for(let s=0;s({x:[n.XCoordinateSpec,{field:\"x\"}],bottom:[n.YCoordinateSpec,{value:0}],width:[n.NumberSpec,{value:1}],top:[n.YCoordinateSpec,{field:\"top\"}]})))}}e.VBar=c,c.__name__=\"VBar\",c.init_VBar()},\n", " function _(e,t,s,i,n){i();const r=e(1),a=e(64),l=e(106),c=e(48),d=e(24),h=e(20),o=r.__importStar(e(18)),_=e(10),u=e(59);class g extends a.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=d.to_screen(this.radius)}_render(e,t,s){const{sx:i,sy:n,sradius:r,start_angle:a,end_angle:l}=null!=s?s:this,c=\"anticlock\"==this.model.direction;for(const s of t){const t=i[s],d=n[s],h=r[s],o=a.get(s),_=l.get(s);isNaN(t+d+h+o+_)||(e.beginPath(),e.arc(t,d,h,o,_,c),e.lineTo(t,d),e.closePath(),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,s),e.fill()),this.visuals.hatch.doit&&(this.visuals.hatch.set_vectorize(e,s),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,s),e.stroke()))}}_hit_point(e){let t,s,i,n,r,a,l,c,d;const{sx:h,sy:o}=e,g=this.renderer.xscale.invert(h),p=this.renderer.yscale.invert(o),x=2*this.max_radius;\"data\"===this.model.properties.radius.units?(a=g-x,l=g+x,c=p-x,d=p+x):(s=h-x,i=h+x,[a,l]=this.renderer.xscale.r_invert(s,i),n=o-x,r=o+x,[c,d]=this.renderer.yscale.r_invert(n,r));const f=[];for(const e of this.index.indices({x0:a,x1:l,y0:c,y1:d})){const a=this.sradius[e]**2;[s,i]=this.renderer.xscale.r_compute(g,this._x[e]),[n,r]=this.renderer.yscale.r_compute(p,this._y[e]),t=(s-i)**2+(n-r)**2,t<=a&&f.push(e)}const v=\"anticlock\"==this.model.direction,y=[];for(const e of f){const t=Math.atan2(o-this.sy[e],h-this.sx[e]);_.angle_between(-t,-this.start_angle.get(e),-this.end_angle.get(e),v)&&y.push(e)}return new u.Selection({indices:y})}draw_legend_for_index(e,t,s){l.generic_area_vector_legend(this.visuals,e,t,s)}scenterxy(e){const t=this.sradius[e]/2,s=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+t*Math.cos(s),this.sy[e]+t*Math.sin(s)]}}s.WedgeView=g,g.__name__=\"WedgeView\";class p extends a.XYGlyph{constructor(e){super(e)}static init_Wedge(){this.prototype.default_view=g,this.mixins([c.LineVector,c.FillVector,c.HatchVector]),this.define((({})=>({direction:[h.Direction,\"anticlock\"],radius:[o.DistanceSpec,{field:\"radius\"}],start_angle:[o.AngleSpec,{field:\"start_angle\"}],end_angle:[o.AngleSpec,{field:\"end_angle\"}]})))}}s.Wedge=p,p.__name__=\"Wedge\",p.init_Wedge()},\n", " function _(t,_,r,o,a){o();const e=t(1);e.__exportStar(t(126),r),e.__exportStar(t(125),r),e.__exportStar(t(314),r)},\n", " function _(t,a,o,r,e){r();const n=t(125);class l extends n.LayoutProvider{constructor(t){super(t)}static init_StaticLayoutProvider(){this.define((({Number:t,Tuple:a,Dict:o})=>({graph_layout:[o(a(t,t)),{}]})))}get_node_coordinates(t){var a;const o=null!==(a=t.data.index)&&void 0!==a?a:[],r=o.length,e=new Float64Array(r),n=new Float64Array(r);for(let t=0;tthis.request_render()))}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;const[e,t]=this.grid_coords(\"major\",!1);for(let s=0;st[1]&&(n=t[1]);else{[s,n]=t;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,n]=i.computed_bounds)}return[s,n]}grid_coords(i,e=!0){const t=this.model.dimension,s=(t+1)%2,[n,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const l=[[],[]],_=this.model.get_ticker();if(null==_)return l;const a=_.get_ticks(o,d,n,r.min)[i],h=n.min,u=n.max,c=r.min,m=r.max;e||(a[0]!=h&&a.splice(0,0,h),a[a.length-1]!=u&&a.push(u));for(let i=0;i({bounds:[r(n(i,i),e),\"auto\"],dimension:[t(0,1),0],axis:[d(s(o.Axis)),null],ticker:[d(s(l.Ticker)),null]}))),this.override({level:\"underlay\",band_fill_color:null,band_fill_alpha:0,grid_line_color:\"#e5e5e5\",minor_grid_line_color:null})}get_ticker(){return null!=this.ticker?this.ticker:null!=this.axis?this.axis.ticker:null}}t.Grid=u,u.__name__=\"Grid\",u.init_Grid()},\n", " function _(o,a,x,B,e){B(),e(\"Box\",o(318).Box),e(\"Column\",o(320).Column),e(\"GridBox\",o(321).GridBox),e(\"HTMLBox\",o(322).HTMLBox),e(\"LayoutDOM\",o(319).LayoutDOM),e(\"Panel\",o(323).Panel),e(\"Row\",o(324).Row),e(\"Spacer\",o(325).Spacer),e(\"Tabs\",o(326).Tabs),e(\"WidgetBox\",o(329).WidgetBox)},\n", " function _(e,n,i,t,s){t();const o=e(319);class c extends o.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,(()=>this.rebuild()))}get child_models(){return this.model.children}}i.BoxView=c,c.__name__=\"BoxView\";class r extends o.LayoutDOM{constructor(e){super(e)}static init_Box(){this.define((({Number:e,Array:n,Ref:i})=>({children:[n(i(o.LayoutDOM)),[]],spacing:[e,0]})))}}i.Box=r,r.__name__=\"Box\",r.init_Box()},\n", " function _(t,i,e,s,o){s();const l=t(53),n=t(20),h=t(43),a=t(19),r=t(8),_=t(22),d=t(143),c=t(122),u=t(240),m=t(221),p=t(44),g=t(249);class f extends u.DOMView{constructor(){super(...arguments),this._idle_notified=!1,this._offset_parent=null,this._viewport={}}get base_font_size(){const t=getComputedStyle(this.el).fontSize,i=d.parse_css_font_size(t);if(null!=i){const{value:t,unit:e}=i;if(\"px\"==e)return t}return 13}initialize(){super.initialize(),this.el.style.position=this.is_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this.build_child_views()}remove(){for(const t of this.child_views)t.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval((()=>{const t=this.el.offsetParent;this._offset_parent!=t&&(this._offset_parent=t,null!=t&&(this.compute_viewport(),this.invalidate_layout()))}),250));const t=this.model.properties;this.on_change([t.width,t.height,t.min_width,t.min_height,t.max_width,t.max_height,t.margin,t.width_policy,t.height_policy,t.sizing_mode,t.aspect_ratio,t.visible],(()=>this.invalidate_layout())),this.on_change([t.background,t.css_classes],(()=>this.invalidate_render()))}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map((t=>this._child_views.get(t)))}async build_child_views(){await c.build_views(this._child_views,this.child_models,{parent:this})}render(){super.render(),h.empty(this.el);const{background:t}=this.model;this.el.style.backgroundColor=null!=t?_.color2css(t):\"\",h.classes(this.el).clear().add(...this.css_classes());for(const t of this.child_views)this.el.appendChild(t.el),t.render()}update_layout(){for(const t of this.child_views)t.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const t=this.is_root?this.layout.sizing.margin:void 0;h.position(this.el,this.layout.bbox,t);for(const t of this.child_views)t.update_position()}after_layout(){for(const t of this.child_views)t.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(t){t.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build()}build(){return this.assert_root(),this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const t=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),a.logger.debug(`layout computed in ${Date.now()-t} ms`),this.notify_finished()}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const t of this.child_views)if(!t.has_finished())return!1;return!0}notify_finished(){this.is_root?!this._idle_notified&&this.has_finished()&&null!=this.model.document&&(this._idle_notified=!0,this.model.document.notify_idle(this.model)):this.root.notify_finished()}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:t,height_policy:i,aspect_ratio:e}=this.model;\"auto\"==t&&(t=this._width_policy()),\"auto\"==i&&(i=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)t=i=\"fixed\";else if(\"stretch_both\"==s)t=i=\"max\";else if(\"stretch_width\"==s)t=\"max\";else if(\"stretch_height\"==s)i=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":t=\"max\",i=\"min\";break;case\"scale_height\":t=\"min\",i=\"max\";break;case\"scale_both\":t=\"max\",i=\"max\"}const o={width_policy:t,height_policy:i},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:h,height:a}=this.model;null!=h&&(o.width=h),null!=a&&(o.height=a);const{max_width:_,max_height:d}=this.model;null!=_&&(o.max_width=_),null!=d&&(o.max_height=d),\"auto\"==e&&null!=h&&null!=a?o.aspect=h/a:r.isNumber(e)&&(o.aspect=e);const{margin:c}=this.model;if(null!=c)if(r.isNumber(c))o.margin={top:c,right:c,bottom:c,left:c};else if(2==c.length){const[t,i]=c;o.margin={top:t,right:i,bottom:t,left:i}}else{const[t,i,e,s]=c;o.margin={top:t,right:i,bottom:e,left:s}}o.visible=this.model.visible;const{align:u}=this.model;return r.isArray(u)?[o.halign,o.valign]=u:o.halign=o.valign=u,o}_viewport_size(){return h.undisplayed(this.el,(()=>{let t=this.el;for(;t=t.parentElement;){if(t.classList.contains(p.root))continue;if(t==document.body){const{margin:{left:t,right:i,top:e,bottom:s}}=h.extents(document.body);return{width:Math.ceil(document.documentElement.clientWidth-t-i),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:i,right:e,top:s,bottom:o}}=h.extents(t),{width:l,height:n}=t.getBoundingClientRect(),a=Math.ceil(l-i-e),r=Math.ceil(n-s-o);if(a>0||r>0)return{width:a>0?a:void 0,height:r>0?r:void 0}}return{}}))}export(t,i=!0){const e=\"png\"==t?\"canvas\":\"svg\",s=new g.CanvasLayer(e,i),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(t,i),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map((t=>t.serializable_state()))})}}e.LayoutDOMView=f,f.__name__=\"LayoutDOMView\";class w extends l.Model{constructor(t){super(t)}static init_LayoutDOM(){this.define((t=>{const{Boolean:i,Number:e,String:s,Auto:o,Color:l,Array:h,Tuple:a,Or:r,Null:_,Nullable:d}=t,c=a(e,e),u=a(e,e,e,e);return{width:[d(e),null],height:[d(e),null],min_width:[d(e),null],min_height:[d(e),null],max_width:[d(e),null],max_height:[d(e),null],margin:[d(r(e,c,u)),[0,0,0,0]],width_policy:[r(m.SizingPolicy,o),\"auto\"],height_policy:[r(m.SizingPolicy,o),\"auto\"],aspect_ratio:[r(e,o,_),null],sizing_mode:[d(n.SizingMode),null],visible:[i,!0],disabled:[i,!1],align:[r(n.Align,a(n.Align,n.Align)),\"start\"],background:[d(l),null],css_classes:[h(s),[]]}}))}}e.LayoutDOM=w,w.__name__=\"LayoutDOM\",w.init_LayoutDOM()},\n", " function _(t,s,i,o,n){o();const e=t(318),l=t(223);class u extends e.BoxView{_update_layout(){const t=this.child_views.map((t=>t.layout));this.layout=new l.Column(t),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}i.ColumnView=u,u.__name__=\"ColumnView\";class a extends e.Box{constructor(t){super(t)}static init_Column(){this.prototype.default_view=u,this.define((({Any:t})=>({rows:[t,\"auto\"]})))}}i.Column=a,a.__name__=\"Column\",a.init_Column()},\n", " function _(t,s,i,o,e){o();const n=t(319),l=t(223);class a extends n.LayoutDOMView{connect_signals(){super.connect_signals();const{children:t,rows:s,cols:i,spacing:o}=this.model.properties;this.on_change([t,s,i,o],(()=>this.rebuild()))}get child_models(){return this.model.children.map((([t])=>t))}_update_layout(){this.layout=new l.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[t,s,i,o,e]of this.model.children){const n=this._child_views.get(t);this.layout.items.push({layout:n.layout,row:s,col:i,row_span:o,col_span:e})}this.layout.set_sizing(this.box_sizing())}}i.GridBoxView=a,a.__name__=\"GridBoxView\";class r extends n.LayoutDOM{constructor(t){super(t)}static init_GridBox(){this.prototype.default_view=a,this.define((({Any:t,Int:s,Number:i,Tuple:o,Array:e,Ref:l,Or:a,Opt:r})=>({children:[e(o(l(n.LayoutDOM),s,s,r(s),r(s))),[]],rows:[t,\"auto\"],cols:[t,\"auto\"],spacing:[a(i,o(i,i)),0]})))}}i.GridBox=r,r.__name__=\"GridBox\",r.init_GridBox()},\n", " function _(t,e,o,s,n){s();const _=t(319),i=t(221);class a extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new i.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=a,a.__name__=\"HTMLBoxView\";class u extends _.LayoutDOM{constructor(t){super(t)}}o.HTMLBox=u,u.__name__=\"HTMLBox\"},\n", " function _(e,n,t,i,l){i();const a=e(53),o=e(319);class s extends a.Model{constructor(e){super(e)}static init_Panel(){this.define((({Boolean:e,String:n,Ref:t})=>({title:[n,\"\"],child:[t(o.LayoutDOM)],closable:[e,!1]})))}}t.Panel=s,s.__name__=\"Panel\",s.init_Panel()},\n", " function _(t,s,i,o,e){o();const n=t(318),a=t(223);class _ extends n.BoxView{_update_layout(){const t=this.child_views.map((t=>t.layout));this.layout=new a.Row(t),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}i.RowView=_,_.__name__=\"RowView\";class l extends n.Box{constructor(t){super(t)}static init_Row(){this.prototype.default_view=_,this.define((({Any:t})=>({cols:[t,\"auto\"]})))}}i.Row=l,l.__name__=\"Row\",l.init_Row()},\n", " function _(t,e,a,i,s){i();const _=t(319),c=t(221);class n extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new c.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=n,n.__name__=\"SpacerView\";class o extends _.LayoutDOM{constructor(t){super(t)}static init_Spacer(){this.prototype.default_view=n}}a.Spacer=o,o.__name__=\"Spacer\",o.init_Spacer()},\n", " function _(e,t,s,i,l){i();const h=e(1),a=e(221),o=e(43),r=e(9),c=e(10),d=e(20),n=e(319),_=e(323),p=h.__importStar(e(327)),b=p,u=h.__importStar(e(328)),m=u,g=h.__importStar(e(243)),v=g;class w extends n.LayoutDOMView{constructor(){super(...arguments),this._scroll_index=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,(()=>this.rebuild())),this.connect(this.model.properties.active.change,(()=>this.on_active_change()))}styles(){return[...super.styles(),u.default,g.default,p.default]}get child_models(){return this.model.tabs.map((e=>e.child))}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends a.ContentBox{_measure(e){const l=o.size(s),h=o.children(i).slice(0,3).map((e=>o.size(e))),{width:a,height:c}=super._measure(e);if(t){const t=l.width+r.sum(h.map((e=>e.width)));return{width:e.width!=1/0?e.width:t,height:c}}{const t=l.height+r.sum(h.map((e=>e.height)));return{width:a,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let l=1,h=1;switch(e){case\"above\":l-=1;break;case\"below\":l+=1;break;case\"left\":h-=1;break;case\"right\":h+=1}const c={layout:this.header,row:l,col:h},d=this.child_views.map((e=>({layout:e.layout,row:1,col:1})));this.layout=new a.Grid([c,...d]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",o.position(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=o.size(this.scroll_el),i=o.scroll_size(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",o.display(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxWidth=\"\",o.undisplay(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",o.display(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxHeight=\"\",o.undisplay(this.scroll_el))}const{child_views:l}=this;for(const e of l)o.hide(e.el);const h=l[this.model.active];null!=h&&o.show(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs.map(((t,s)=>{const i=o.div({class:[b.tab,s==e?b.active:null]},t.title);if(i.addEventListener(\"click\",(e=>{e.target==e.currentTarget&&this.change_active(s)})),t.closable){const e=o.div({class:b.close});e.addEventListener(\"click\",(e=>{if(e.target==e.currentTarget){this.model.tabs=r.remove_at(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}})),i.appendChild(e)}return i}));this.headers_el=o.div({class:[b.headers]},t),this.wrapper_el=o.div({class:b.headers_wrapper},this.headers_el),this.left_el=o.div({class:[m.btn,m.btn_default],disabled:\"\"},o.div({class:[v.caret,b.left]})),this.right_el=o.div({class:[m.btn,m.btn_default]},o.div({class:[v.caret,b.right]})),this.left_el.addEventListener(\"click\",(()=>this.do_scroll(\"left\"))),this.right_el.addEventListener(\"click\",(()=>this.do_scroll(\"right\"))),this.scroll_el=o.div({class:m.btn_group},this.left_el,this.right_el);const s=this.model.tabs_location;this.header_el=o.div({class:[b.tabs_header,b[s]]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}do_scroll(e){const t=this.model.tabs.length;\"left\"==e?this._scroll_index-=1:\"right\"==e?this._scroll_index+=1:this._scroll_index=e,this._scroll_index=c.clamp(this._scroll_index,0,t-1),0==this._scroll_index?this.left_el.setAttribute(\"disabled\",\"\"):this.left_el.removeAttribute(\"disabled\"),this._scroll_index==t-1?this.right_el.setAttribute(\"disabled\",\"\"):this.right_el.removeAttribute(\"disabled\");const s=o.children(this.headers_el).slice(0,this._scroll_index).map((e=>e.getBoundingClientRect())),i=this.model.tabs_location;if(\"above\"==i||\"below\"==i){const e=-r.sum(s.map((e=>e.width)));this.headers_el.style.left=`${e}px`}else{const e=-r.sum(s.map((e=>e.height)));this.headers_el.style.top=`${e}px`}}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=o.children(this.headers_el);for(const e of t)e.classList.remove(b.active);t[e].classList.add(b.active);const{child_views:s}=this;for(const e of s)o.hide(e.el);o.show(s[e].el)}}s.TabsView=w,w.__name__=\"TabsView\";class f extends n.LayoutDOM{constructor(e){super(e)}static init_Tabs(){this.prototype.default_view=w,this.define((({Int:e,Array:t,Ref:s})=>({tabs:[t(s(_.Panel)),[]],tabs_location:[d.Location,\"above\"],active:[e,0]})))}}s.Tabs=f,f.__name__=\"Tabs\",f.init_Tabs()},\n", " function _(e,r,b,o,t){o(),b.root=\"bk-root\",b.tabs_header=\"bk-tabs-header\",b.btn_group=\"bk-btn-group\",b.btn=\"bk-btn\",b.headers_wrapper=\"bk-headers-wrapper\",b.above=\"bk-above\",b.right=\"bk-right\",b.below=\"bk-below\",b.left=\"bk-left\",b.headers=\"bk-headers\",b.tab=\"bk-tab\",b.active=\"bk-active\",b.close=\"bk-close\",b.default='.bk-root .bk-tabs-header{display:flex;display:-webkit-flex;flex-wrap:nowrap;-webkit-flex-wrap:nowrap;align-items:center;-webkit-align-items:center;overflow:hidden;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-tabs-header .bk-btn-group{height:auto;margin-right:5px;}.bk-root .bk-tabs-header .bk-btn-group > .bk-btn{flex-grow:0;-webkit-flex-grow:0;height:auto;padding:4px 4px;}.bk-root .bk-tabs-header .bk-headers-wrapper{flex-grow:1;-webkit-flex-grow:1;overflow:hidden;color:#666666;}.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper{border-bottom:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper{border-left:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper{border-top:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper{border-right:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-above,.bk-root .bk-tabs-header.bk-below{flex-direction:row;-webkit-flex-direction:row;}.bk-root .bk-tabs-header.bk-above .bk-headers,.bk-root .bk-tabs-header.bk-below .bk-headers{flex-direction:row;-webkit-flex-direction:row;}.bk-root .bk-tabs-header.bk-left,.bk-root .bk-tabs-header.bk-right{flex-direction:column;-webkit-flex-direction:column;}.bk-root .bk-tabs-header.bk-left .bk-headers,.bk-root .bk-tabs-header.bk-right .bk-headers{flex-direction:column;-webkit-flex-direction:column;}.bk-root .bk-tabs-header .bk-headers{position:relative;display:flex;display:-webkit-flex;flex-wrap:nowrap;-webkit-flex-wrap:nowrap;align-items:center;-webkit-align-items:center;}.bk-root .bk-tabs-header .bk-tab{padding:4px 8px;border:solid transparent;white-space:nowrap;cursor:pointer;}.bk-root .bk-tabs-header .bk-tab:hover{background-color:#f2f2f2;}.bk-root .bk-tabs-header .bk-tab.bk-active{color:#4d4d4d;background-color:white;border-color:#e6e6e6;}.bk-root .bk-tabs-header .bk-tab .bk-close{margin-left:10px;}.bk-root .bk-tabs-header.bk-above .bk-tab{border-width:3px 1px 0px 1px;border-radius:4px 4px 0 0;}.bk-root .bk-tabs-header.bk-right .bk-tab{border-width:1px 3px 1px 0px;border-radius:0 4px 4px 0;}.bk-root .bk-tabs-header.bk-below .bk-tab{border-width:0px 1px 3px 1px;border-radius:0 0 4px 4px;}.bk-root .bk-tabs-header.bk-left .bk-tab{border-width:1px 0px 1px 3px;border-radius:4px 0 0 4px;}.bk-root .bk-close{display:inline-block;width:10px;height:10px;vertical-align:middle;background-image:url(\\'data:image/svg+xml;utf8, \\');}.bk-root .bk-close:hover{background-image:url(\\'data:image/svg+xml;utf8, \\');}'},\n", " function _(o,b,r,t,e){t(),r.root=\"bk-root\",r.btn=\"bk-btn\",r.active=\"bk-active\",r.btn_default=\"bk-btn-default\",r.btn_primary=\"bk-btn-primary\",r.btn_success=\"bk-btn-success\",r.btn_warning=\"bk-btn-warning\",r.btn_danger=\"bk-btn-danger\",r.btn_light=\"bk-btn-light\",r.btn_group=\"bk-btn-group\",r.dropdown_toggle=\"bk-dropdown-toggle\",r.default=\".bk-root .bk-btn{height:100%;display:inline-block;text-align:center;vertical-align:middle;white-space:nowrap;cursor:pointer;padding:6px 12px;font-size:12px;border:1px solid transparent;border-radius:4px;outline:0;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-btn:hover,.bk-root .bk-btn:focus{text-decoration:none;}.bk-root .bk-btn:active,.bk-root .bk-btn.bk-active{background-image:none;box-shadow:inset 0 3px 5px rgba(0, 0, 0, 0.125);}.bk-root .bk-btn[disabled]{cursor:not-allowed;pointer-events:none;opacity:0.65;box-shadow:none;}.bk-root .bk-btn-default{color:#333;background-color:#fff;border-color:#ccc;}.bk-root .bk-btn-default:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-default.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-default[disabled],.bk-root .bk-btn-default[disabled]:hover,.bk-root .bk-btn-default[disabled]:focus,.bk-root .bk-btn-default[disabled]:active,.bk-root .bk-btn-default[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-primary{color:#fff;background-color:#428bca;border-color:#357ebd;}.bk-root .bk-btn-primary:hover{background-color:#3681c1;border-color:#2c699e;}.bk-root .bk-btn-primary.bk-active{background-color:#3276b1;border-color:#285e8e;}.bk-root .bk-btn-primary[disabled],.bk-root .bk-btn-primary[disabled]:hover,.bk-root .bk-btn-primary[disabled]:focus,.bk-root .bk-btn-primary[disabled]:active,.bk-root .bk-btn-primary[disabled].bk-active{background-color:#506f89;border-color:#357ebd;}.bk-root .bk-btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c;}.bk-root .bk-btn-success:hover{background-color:#4eb24e;border-color:#409240;}.bk-root .bk-btn-success.bk-active{background-color:#47a447;border-color:#398439;}.bk-root .bk-btn-success[disabled],.bk-root .bk-btn-success[disabled]:hover,.bk-root .bk-btn-success[disabled]:focus,.bk-root .bk-btn-success[disabled]:active,.bk-root .bk-btn-success[disabled].bk-active{background-color:#667b66;border-color:#4cae4c;}.bk-root .bk-btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236;}.bk-root .bk-btn-warning:hover{background-color:#eea43b;border-color:#e89014;}.bk-root .bk-btn-warning.bk-active{background-color:#ed9c28;border-color:#d58512;}.bk-root .bk-btn-warning[disabled],.bk-root .bk-btn-warning[disabled]:hover,.bk-root .bk-btn-warning[disabled]:focus,.bk-root .bk-btn-warning[disabled]:active,.bk-root .bk-btn-warning[disabled].bk-active{background-color:#c89143;border-color:#eea236;}.bk-root .bk-btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a;}.bk-root .bk-btn-danger:hover{background-color:#d5433e;border-color:#bd2d29;}.bk-root .bk-btn-danger.bk-active{background-color:#d2322d;border-color:#ac2925;}.bk-root .bk-btn-danger[disabled],.bk-root .bk-btn-danger[disabled]:hover,.bk-root .bk-btn-danger[disabled]:focus,.bk-root .bk-btn-danger[disabled]:active,.bk-root .bk-btn-danger[disabled].bk-active{background-color:#a55350;border-color:#d43f3a;}.bk-root .bk-btn-light{color:#333;background-color:#fff;border-color:#ccc;border-color:transparent;}.bk-root .bk-btn-light:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-light.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-light[disabled],.bk-root .bk-btn-light[disabled]:hover,.bk-root .bk-btn-light[disabled]:focus,.bk-root .bk-btn-light[disabled]:active,.bk-root .bk-btn-light[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-group{height:100%;display:flex;display:-webkit-flex;flex-wrap:nowrap;-webkit-flex-wrap:nowrap;align-items:center;-webkit-align-items:center;flex-direction:row;-webkit-flex-direction:row;}.bk-root .bk-btn-group > .bk-btn{flex-grow:1;-webkit-flex-grow:1;}.bk-root .bk-btn-group > .bk-btn + .bk-btn{margin-left:-1px;}.bk-root .bk-btn-group > .bk-btn:first-child:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group > .bk-btn:not(:first-child):last-child{border-bottom-left-radius:0;border-top-left-radius:0;}.bk-root .bk-btn-group > .bk-btn:not(:first-child):not(:last-child){border-radius:0;}.bk-root .bk-btn-group .bk-dropdown-toggle{flex:0 0 0;-webkit-flex:0 0 0;padding:6px 6px;}\"},\n", " function _(t,e,i,o,n){o();const _=t(320);class s extends _.ColumnView{}i.WidgetBoxView=s,s.__name__=\"WidgetBoxView\";class d extends _.Column{constructor(t){super(t)}static init_WidgetBox(){this.prototype.default_view=s}}i.WidgetBox=d,d.__name__=\"WidgetBox\",d.init_WidgetBox()},\n", " function _(p,o,t,a,n){a(),n(\"MapOptions\",p(331).MapOptions),n(\"GMapOptions\",p(331).GMapOptions),n(\"GMapPlot\",p(331).GMapPlot),n(\"Plot\",p(332).Plot)},\n", " function _(t,i,n,e,a){e();const s=t(332),o=t(53),p=t(156),_=t(337);a(\"GMapPlotView\",_.GMapPlotView);class l extends o.Model{constructor(t){super(t)}static init_MapOptions(){this.define((({Int:t,Number:i})=>({lat:[i],lng:[i],zoom:[t,12]})))}}n.MapOptions=l,l.__name__=\"MapOptions\",l.init_MapOptions();class r extends l{constructor(t){super(t)}static init_GMapOptions(){this.define((({Boolean:t,Int:i,String:n})=>({map_type:[n,\"roadmap\"],scale_control:[t,!1],styles:[n],tilt:[i,45]})))}}n.GMapOptions=r,r.__name__=\"GMapOptions\",r.init_GMapOptions();class c extends s.Plot{constructor(t){super(t),this.use_map=!0}static init_GMapPlot(){this.prototype.default_view=_.GMapPlotView,this.define((({String:t,Ref:i})=>({map_options:[i(r)],api_key:[t],api_version:[t,\"3.43\"]}))),this.override({x_range:()=>new p.Range1d,y_range:()=>new p.Range1d})}}n.GMapPlot=c,c.__name__=\"GMapPlot\",c.init_GMapPlot()},\n", " function _(e,t,i,n,r){n();const o=e(1),a=o.__importStar(e(48)),s=o.__importStar(e(18)),l=e(15),_=e(20),h=e(9),c=e(13),d=e(8),u=e(319),g=e(163),p=e(316),f=e(40),b=e(138),w=e(218),m=e(235),y=e(105),v=e(146),x=e(130),A=e(41),R=e(62),S=e(61),P=e(159),D=e(333);r(\"PlotView\",D.PlotView);class L extends u.LayoutDOM{constructor(e){super(e),this.use_map=!1}static init_Plot(){this.prototype.default_view=D.PlotView,this.mixins([[\"outline_\",a.Line],[\"background_\",a.Fill],[\"border_\",a.Fill]]),this.define((({Boolean:e,Number:t,String:i,Array:n,Dict:r,Or:o,Ref:a,Null:l,Nullable:h})=>({toolbar:[a(m.Toolbar),()=>new m.Toolbar],toolbar_location:[h(_.Location),\"right\"],toolbar_sticky:[e,!0],plot_width:[s.Alias(\"width\")],plot_height:[s.Alias(\"height\")],frame_width:[h(t),null],frame_height:[h(t),null],title:[o(a(b.Title),i,l),()=>new b.Title({text:\"\"})],title_location:[h(_.Location),\"above\"],above:[n(o(a(f.Annotation),a(g.Axis))),[]],below:[n(o(a(f.Annotation),a(g.Axis))),[]],left:[n(o(a(f.Annotation),a(g.Axis))),[]],right:[n(o(a(f.Annotation),a(g.Axis))),[]],center:[n(o(a(f.Annotation),a(p.Grid))),[]],renderers:[n(a(A.Renderer)),[]],x_range:[a(y.Range),()=>new P.DataRange1d],extra_x_ranges:[r(a(y.Range)),{}],y_range:[a(y.Range),()=>new P.DataRange1d],extra_y_ranges:[r(a(y.Range)),{}],x_scale:[a(v.Scale),()=>new w.LinearScale],y_scale:[a(v.Scale),()=>new w.LinearScale],lod_factor:[t,10],lod_interval:[t,300],lod_threshold:[h(t),2e3],lod_timeout:[t,500],hidpi:[e,!0],output_backend:[_.OutputBackend,\"canvas\"],min_border:[h(t),5],min_border_top:[h(t),null],min_border_left:[h(t),null],min_border_bottom:[h(t),null],min_border_right:[h(t),null],inner_width:[t,0],inner_height:[t,0],outer_width:[t,0],outer_height:[t,0],match_aspect:[e,!1],aspect_scale:[t,1],reset_policy:[_.ResetPolicy,\"standard\"]}))),this.override({width:600,height:600,outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"})}_doc_attached(){super._doc_attached(),this._push_changes([[this.properties.inner_height,null,this.inner_height],[this.properties.inner_width,null,this.inner_width]])}initialize(){super.initialize(),this.reset=new l.Signal0(this,\"reset\");for(const e of c.values(this.extra_x_ranges).concat(this.x_range)){let t=e.plots;d.isArray(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}for(const e of c.values(this.extra_y_ranges).concat(this.y_range)){let t=e.plots;d.isArray(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}}add_layout(e,t=\"center\"){const i=this.properties[t].get_value();this.setv({[t]:[...i,e]})}remove_layout(e){const t=t=>{h.remove_by(t,(t=>t==e))};t(this.left),t(this.right),t(this.above),t(this.below),t(this.center)}get data_renderers(){return this.renderers.filter((e=>e instanceof R.DataRenderer))}add_renderers(...e){this.renderers=this.renderers.concat(e)}add_glyph(e,t=new x.ColumnDataSource,i={}){const n=new S.GlyphRenderer(Object.assign(Object.assign({},i),{data_source:t,glyph:e}));return this.add_renderers(n),n}add_tools(...e){this.toolbar.tools=this.toolbar.tools.concat(e)}get panels(){return[...this.side_panels,...this.center]}get side_panels(){const{above:e,below:t,left:i,right:n}=this;return h.concat([e,t,i,n])}}i.Plot=L,L.__name__=\"Plot\",L.init_Plot()},\n", " function _(e,t,i,s,a){s();const n=e(1),o=e(144),l=e(262),r=e(319),_=e(40),h=e(138),d=e(163),u=e(234),c=e(264),p=e(122),v=e(45),b=e(19),g=e(334),m=e(8),w=e(9),y=e(249),f=e(222),x=e(225),z=e(223),k=e(140),q=e(99),M=e(335),V=e(336),P=e(28);class R extends r.LayoutDOMView{constructor(){super(...arguments),this._outer_bbox=new q.BBox,this._inner_bbox=new q.BBox,this._needs_paint=!0,this._needs_layout=!1,this._invalidated_painters=new Set,this._invalidate_all=!0}get canvas(){return this.canvas_view}get state(){return this._state_manager}set invalidate_dataranges(e){this._range_manager.invalidate_dataranges=e}renderer_view(e){const t=this.renderer_views.get(e);if(null==t)for(const[,t]of this.renderer_views){const i=t.renderer_view(e);if(null!=i)return i}return t}get is_paused(){return null!=this._is_paused&&0!==this._is_paused}get child_models(){return[]}pause(){null==this._is_paused?this._is_paused=1:this._is_paused+=1}unpause(e=!1){if(null==this._is_paused)throw new Error(\"wasn't paused\");this._is_paused-=1,0!=this._is_paused||e||this.request_paint(\"everything\")}request_render(){this.request_paint(\"everything\")}request_paint(e){this.invalidate_painters(e),this.schedule_paint()}invalidate_painters(e){if(\"everything\"==e)this._invalidate_all=!0;else if(m.isArray(e))for(const t of e)this._invalidated_painters.add(t);else this._invalidated_painters.add(e)}schedule_paint(){if(!this.is_paused){const e=this.throttled_paint();this._ready=this._ready.then((()=>e))}}request_layout(){this._needs_layout=!0,this.request_paint(\"everything\")}reset(){\"standard\"==this.model.reset_policy&&(this.state.clear(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){p.remove_views(this.renderer_views),p.remove_views(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.lod_started=!1,this.visuals=new v.Visuals(this),this._initial_state={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.renderer_views=new Map,this.tool_views=new Map,this.frame=new o.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges),this._range_manager=new M.RangeManager(this),this._state_manager=new V.StateManager(this,this._initial_state),this.throttled_paint=g.throttle((()=>this.repaint()),1e3/60);const{title_location:e,title:t}=this.model;null!=e&&null!=t&&(this._title=t instanceof h.Title?t:new h.Title({text:t}));const{toolbar_location:i,toolbar:s}=this.model;null!=i&&null!=s&&(this._toolbar=new u.ToolbarPanel({toolbar:s}),s.toolbar_location=i)}async lazy_initialize(){await super.lazy_initialize();const{hidpi:e,output_backend:t}=this.model,i=new l.Canvas({hidpi:e,output_backend:t});this.canvas_view=await p.build_view(i,{parent:this}),this.canvas_view.plot_views=[this],await this.build_renderer_views(),await this.build_tool_views(),this._range_manager.update_dataranges(),this.unpause(!0),b.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){var e,t,i,s,a;this.layout=new x.BorderLayout,this.layout.set_sizing(this.box_sizing());const n=w.copy(this.model.above),o=w.copy(this.model.below),l=w.copy(this.model.left),r=w.copy(this.model.right),d=e=>{switch(e){case\"above\":return n;case\"below\":return o;case\"left\":return l;case\"right\":return r}},{title_location:c,title:p}=this.model;null!=c&&null!=p&&d(c).push(this._title);const{toolbar_location:v,toolbar:b}=this.model;if(null!=v&&null!=b){const e=d(v);let t=!0;if(this.model.toolbar_sticky)for(let i=0;i{var i;const s=this.renderer_view(t);return s.panel=new k.Panel(e),null===(i=s.update_layout)||void 0===i||i.call(s),s.layout},y=(e,t)=>{const i=\"above\"==e||\"below\"==e,s=[];for(const a of t)if(m.isArray(a)){const t=a.map((t=>{const s=g(e,t);if(t instanceof u.ToolbarPanel){const e=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[e]:\"min\"}))}return s}));let n;i?(n=new z.Row(t),n.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(n=new z.Column(t),n.set_sizing({width_policy:\"min\",height_policy:\"max\"})),n.absolute=!0,s.push(n)}else s.push(g(e,a));return s},q=null!==(e=this.model.min_border)&&void 0!==e?e:0;this.layout.min_border={left:null!==(t=this.model.min_border_left)&&void 0!==t?t:q,top:null!==(i=this.model.min_border_top)&&void 0!==i?i:q,right:null!==(s=this.model.min_border_right)&&void 0!==s?s:q,bottom:null!==(a=this.model.min_border_bottom)&&void 0!==a?a:q};const M=new f.NodeLayout,V=new f.VStack,P=new f.VStack,R=new f.HStack,O=new f.HStack;M.absolute=!0,V.absolute=!0,P.absolute=!0,R.absolute=!0,O.absolute=!0,M.children=this.model.center.filter((e=>e instanceof _.Annotation)).map((e=>{var t;const i=this.renderer_view(e);return null===(t=i.update_layout)||void 0===t||t.call(i),i.layout})).filter((e=>null!=e));const{frame_width:S,frame_height:j}=this.model;M.set_sizing(Object.assign(Object.assign({},null!=S?{width_policy:\"fixed\",width:S}:{width_policy:\"fit\"}),null!=j?{height_policy:\"fixed\",height:j}:{height_policy:\"fit\"})),M.on_resize((e=>this.frame.set_geometry(e))),V.children=w.reversed(y(\"above\",n)),P.children=y(\"below\",o),R.children=w.reversed(y(\"left\",l)),O.children=y(\"right\",r),V.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),P.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),R.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.center_panel=M,this.layout.top_panel=V,this.layout.bottom_panel=P,this.layout.left_panel=R,this.layout.right_panel=O}get axis_views(){const e=[];for(const[,t]of this.renderer_views)t instanceof d.AxisView&&e.push(t);return e}set_toolbar_visibility(e){for(const t of this.visibility_callbacks)t(e)}update_range(e,t){this.pause(),this._range_manager.update(e,t),this.unpause()}reset_range(){this.update_range(null)}get_selection(){const e=new Map;for(const t of this.model.data_renderers){const{selected:i}=t.selection_manager.source;e.set(t,i)}return e}update_selection(e){for(const t of this.model.data_renderers){const i=t.selection_manager.source;if(null!=e){const s=e.get(t);null!=s&&i.selected.update(s,!0)}else i.selection_manager.clear()}}reset_selection(){this.update_selection(null)}_invalidate_layout(){(()=>{var e;for(const t of this.model.side_panels){const i=this.renderer_views.get(t);if(null===(e=i.layout)||void 0===e?void 0:e.has_size_changed())return this.invalidate_painters(i),!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map((e=>this.renderer_views.get(e)))}*_compute_renderers(){const{above:e,below:t,left:i,right:s,center:a,renderers:n}=this.model;yield*n,yield*e,yield*t,yield*i,yield*s,yield*a,null!=this._title&&(yield this._title),null!=this._toolbar&&(yield this._toolbar);for(const e of this.model.toolbar.tools)null!=e.overlay&&(yield e.overlay),yield*e.synthetic_renderers}async build_renderer_views(){this.computed_renderers=[...this._compute_renderers()],await p.build_views(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const e=this.model.toolbar.tools;(await p.build_views(this.tool_views,e,{parent:this})).map((e=>this.canvas_view.ui_event_bus.register_tool(e)))}connect_signals(){super.connect_signals();const{x_ranges:e,y_ranges:t}=this.frame;for(const[,t]of e)this.connect(t.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));for(const[,e]of t)this.connect(e.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));const{above:i,below:s,left:a,right:n,center:o,renderers:l}=this.model.properties;this.on_change([i,s,a,n,o,l],(async()=>await this.build_renderer_views())),this.connect(this.model.toolbar.properties.tools.change,(async()=>{await this.build_renderer_views(),await this.build_tool_views()})),this.connect(this.model.change,(()=>this.request_paint(\"everything\"))),this.connect(this.model.reset,(()=>this.reset()))}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,e]of this.renderer_views)if(!e.has_finished())return!1;return!0}after_layout(){var e;super.after_layout();for(const[,t]of this.renderer_views)t instanceof _.AnnotationView&&(null===(e=t.after_layout)||void 0===e||e.call(t));if(this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this._range_manager.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:e,height:t}=this.layout.bbox;this.canvas_view.resize(e,t),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}const{inner_bbox:t}=this.layout;this._inner_bbox.equals(t)||(this._inner_bbox=t,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){var e;if(this.is_paused||!this.model.visible)return;b.logger.trace(`PlotView.paint() for ${this.model.id}`);const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint(\"everything\")}),this.model.lod_timeout):t.interactive_stop()}this._range_manager.invalidate_dataranges&&(this._range_manager.update_dataranges(),this._invalidate_layout());let i=!1,s=!1;if(this._invalidate_all)i=!0,s=!0;else for(const e of this._invalidated_painters){const{level:t}=e.model;if(\"overlay\"!=t?i=!0:s=!0,i&&s)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const a=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:o}=this.canvas_view;i&&(n.prepare(),this.canvas_view.prepare_webgl(a),this._map_hook(n.ctx,a),this._paint_empty(n.ctx,a),this._paint_outline(n.ctx,a),this._paint_levels(n.ctx,\"image\",a,!0),this._paint_levels(n.ctx,\"underlay\",a,!0),this._paint_levels(n.ctx,\"glyph\",a,!0),this._paint_levels(n.ctx,\"guide\",a,!1),this._paint_levels(n.ctx,\"annotation\",a,!1),n.finish()),(s||P.settings.wireframe)&&(o.prepare(),this._paint_levels(o.ctx,\"overlay\",a,!1),P.settings.wireframe&&this._paint_layout(o.ctx,this.layout),o.finish()),null==this._initial_state.range&&(this._initial_state.range=null!==(e=this._range_manager.compute_initial())&&void 0!==e?e:void 0),this._needs_paint=!1}_paint_levels(e,t,i,s){for(const a of this.computed_renderers){if(a.level!=t)continue;const n=this.renderer_views.get(a);e.save(),(s||n.needs_clip)&&(e.beginPath(),e.rect(...i),e.clip()),n.render(),e.restore(),n.has_webgl&&n.needs_webgl_blit&&this.canvas_view.blit_webgl(e)}}_paint_layout(e,t){const{x:i,y:s,width:a,height:n}=t.bbox;e.strokeStyle=\"blue\",e.strokeRect(i,s,a,n);for(const a of t)e.save(),t.absolute||e.translate(i,s),this._paint_layout(e,a),e.restore()}_map_hook(e,t){}_paint_empty(e,t){const[i,s,a,n]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,_]=t;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(e),e.fillRect(i,s,a,n),e.clearRect(o,l,r,_)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fillRect(o,l,r,_))}_paint_outline(e,t){if(this.visuals.outline_line.doit){e.save(),this.visuals.outline_line.set_value(e);let[i,s,a,n]=t;i+a==this.layout.bbox.width&&(a-=1),s+n==this.layout.bbox.height&&(n-=1),e.strokeRect(i,s,a,n),e.restore()}}to_blob(){return this.canvas_view.to_blob()}export(e,t=!0){const i=\"png\"==e?\"canvas\":\"svg\",s=new y.CanvasLayer(i,t),{width:a,height:n}=this.layout.bbox;s.resize(a,n);const{canvas:o}=this.canvas_view.compose();return s.ctx.drawImage(o,0,0),s}serializable_state(){const e=super.serializable_state(),{children:t}=e,i=n.__rest(e,[\"children\"]),s=this.get_renderer_views().map((e=>e.serializable_state())).filter((e=>null!=e.bbox));return Object.assign(Object.assign({},i),{children:[...null!=t?t:[],...s]})}}i.PlotView=R,R.__name__=\"PlotView\"},\n", " function _(t,n,e,o,u){o(),e.throttle=function(t,n){let e=null,o=0,u=!1;return function(){return new Promise(((r,i)=>{const l=function(){o=Date.now(),e=null,u=!1;try{t(),r()}catch(t){i(t)}},a=Date.now(),c=n-(a-o);c<=0&&!u?(null!=e&&clearTimeout(e),u=!0,requestAnimationFrame(l)):e||u?r():e=setTimeout((()=>requestAnimationFrame(l)),c)}))}}},\n", " function _(t,n,e,s,a){s();const o=t(159),r=t(19);class l{constructor(t){this.parent=t,this.invalidate_dataranges=!0}get frame(){return this.parent.frame}update(t,n){const{x_ranges:e,y_ranges:s}=this.frame;if(null==t){for(const[,t]of e)t.reset();for(const[,t]of s)t.reset();this.update_dataranges()}else{const a=[];for(const[n,s]of e)a.push([s,t.xrs.get(n)]);for(const[n,e]of s)a.push([e,t.yrs.get(n)]);(null==n?void 0:n.scrolling)&&this._update_ranges_together(a),this._update_ranges_individually(a,n)}}reset(){this.update(null)}update_dataranges(){const t=new Map,n=new Map;let e=!1;for(const[,t]of this.frame.x_ranges)t instanceof o.DataRange1d&&\"log\"==t.scale_hint&&(e=!0);for(const[,t]of this.frame.y_ranges)t instanceof o.DataRange1d&&\"log\"==t.scale_hint&&(e=!0);for(const s of this.parent.model.data_renderers){const a=this.parent.renderer_view(s);if(null==a)continue;const o=a.glyph_view.bounds();if(null!=o&&t.set(s,o),e){const t=a.glyph_view.log_bounds();null!=t&&n.set(s,t)}}let s=!1,a=!1;const{width:l,height:i}=this.frame.bbox;let d;!1!==this.parent.model.match_aspect&&0!=l&&0!=i&&(d=1/this.parent.model.aspect_scale*(l/i));for(const[,e]of this.frame.x_ranges){if(e instanceof o.DataRange1d){const a=\"log\"==e.scale_hint?n:t;e.update(a,0,this.parent.model,d),e.follow&&(s=!0)}null!=e.bounds&&(a=!0)}for(const[,e]of this.frame.y_ranges){if(e instanceof o.DataRange1d){const a=\"log\"==e.scale_hint?n:t;e.update(a,1,this.parent.model,d),e.follow&&(s=!0)}null!=e.bounds&&(a=!0)}if(s&&a){r.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,t]of this.frame.x_ranges)t.bounds=null;for(const[,t]of this.frame.y_ranges)t.bounds=null}this.invalidate_dataranges=!1}compute_initial(){let t=!0;const{x_ranges:n,y_ranges:e}=this.frame,s=new Map,a=new Map;for(const[e,a]of n){const{start:n,end:o}=a;if(null==n||null==o||isNaN(n+o)){t=!1;break}s.set(e,{start:n,end:o})}if(t)for(const[n,s]of e){const{start:e,end:o}=s;if(null==e||null==o||isNaN(e+o)){t=!1;break}a.set(n,{start:e,end:o})}return t?{xrs:s,yrs:a}:(r.logger.warn(\"could not set initial ranges\"),null)}_update_ranges_together(t){let n=1;for(const[e,s]of t)n=Math.min(n,this._get_weight_to_constrain_interval(e,s));if(n<1)for(const[e,s]of t)s.start=n*s.start+(1-n)*e.start,s.end=n*s.end+(1-n)*e.end}_update_ranges_individually(t,n){const e=!!(null==n?void 0:n.panning),s=!!(null==n?void 0:n.scrolling);let a=!1;for(const[n,o]of t){if(!s){const t=this._get_weight_to_constrain_interval(n,o);t<1&&(o.start=t*o.start+(1-t)*n.start,o.end=t*o.end+(1-t)*n.end)}if(null!=n.bounds&&\"auto\"!=n.bounds){const[t,r]=n.bounds,l=Math.abs(o.end-o.start);n.is_reversed?(null!=t&&t>=o.end&&(a=!0,o.end=t,(e||s)&&(o.start=t+l)),null!=r&&r<=o.start&&(a=!0,o.start=r,(e||s)&&(o.end=r-l))):(null!=t&&t>=o.start&&(a=!0,o.start=t,(e||s)&&(o.end=t+l)),null!=r&&r<=o.end&&(a=!0,o.end=r,(e||s)&&(o.start=r-l)))}}if(!(s&&a&&(null==n?void 0:n.maintain_focus)))for(const[n,e]of t)n.have_updated_interactively=!0,n.start==e.start&&n.end==e.end||n.setv(e)}_get_weight_to_constrain_interval(t,n){const{min_interval:e}=t;let{max_interval:s}=t;if(null!=t.bounds&&\"auto\"!=t.bounds){const[n,e]=t.bounds;if(null!=n&&null!=e){const t=Math.abs(e-n);s=null!=s?Math.min(s,t):t}}let a=1;if(null!=e||null!=s){const o=Math.abs(t.end-t.start),r=Math.abs(n.end-n.start);null!=e&&e>0&&r0&&r>s&&(a=(s-o)/(r-o)),a=Math.max(0,Math.min(1,a))}return a}}e.RangeManager=l,l.__name__=\"RangeManager\"},\n", " function _(t,i,s,e,n){e();const h=t(15);class a{constructor(t,i){this.parent=t,this.initial_state=i,this.changed=new h.Signal0(this.parent,\"state_changed\"),this.history=[],this.index=-1}_do_state_change(t){const i=null!=this.history[t]?this.history[t].state:this.initial_state;null!=i.range&&this.parent.update_range(i.range),null!=i.selection&&this.parent.update_selection(i.selection)}push(t,i){const{history:s,index:e}=this,n=null!=s[e]?s[e].state:{},h=Object.assign(Object.assign(Object.assign({},this.initial_state),n),i);this.history=this.history.slice(0,this.index+1),this.history.push({type:t,state:h}),this.index=this.history.length-1,this.changed.emit()}clear(){this.history=[],this.index=-1,this.changed.emit()}undo(){this.can_undo&&(this.index-=1,this._do_state_change(this.index),this.changed.emit())}redo(){this.can_redo&&(this.index+=1,this._do_state_change(this.index),this.changed.emit())}get can_undo(){return this.index>=0}get can_redo(){return this.indexm.emit();const s=encodeURIComponent,o=document.createElement(\"script\");o.type=\"text/javascript\",o.src=`https://maps.googleapis.com/maps/api/js?v=${s(e)}&key=${s(t)}&callback=_bokeh_gmaps_callback`,document.body.appendChild(o)}(t,e)}m.connect((()=>this.request_paint(\"everything\")))}this.unpause()}remove(){p.remove(this.map_el),super.remove()}update_range(t,e){var s,o;if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null,e);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(null!==(s=t.sdx)&&void 0!==s?s:0,null!==(o=t.sdy)&&void 0!==o?o:0),super.update_range(t,e);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t,e);const s=t.factor<0?-1:1,o=this.map.getZoom(),i=o+s;if(i>=2){this.map.setZoom(i);const[t,e,,]=this._get_projected_bounds();e-t<0&&this.map.setZoom(o)}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=p.div({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",(()=>this._set_bokeh_ranges())),t.event.addListener(this.map,\"bounds_changed\",(()=>this._set_bokeh_ranges())),t.event.addListenerOnce(this.map,\"tilesloaded\",(()=>this._render_finished())),this.connect(this.model.properties.map_options.change,(()=>this._update_options())),this.connect(this.model.map_options.properties.styles.change,(()=>this._update_styles())),this.connect(this.model.map_options.properties.lat.change,(()=>this._update_center(\"lat\"))),this.connect(this.model.map_options.properties.lng.change,(()=>this._update_center(\"lng\"))),this.connect(this.model.map_options.properties.zoom.change,(()=>this._update_zoom())),this.connect(this.model.map_options.properties.map_type.change,(()=>this._update_map_type())),this.connect(this.model.map_options.properties.scale_control.change,(()=>this._update_scale_control())),this.connect(this.model.map_options.properties.tilt.change,(()=>this._update_tilt()))}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,o]=this._get_latlon_bounds(),[i,a]=l.wgs84_mercator.compute(t,s),[n,p]=l.wgs84_mercator.compute(e,o);return[i,n,a,p]}_set_bokeh_ranges(){const[t,e,s,o]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:o})}_update_center(t){const e=this.map.getCenter().toJSON();e[t]=this.model.map_options[t],this.map.setCenter(e),this._set_bokeh_ranges()}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,o,i]=e;this.map_el.style.top=`${s}px`,this.map_el.style.left=`${t}px`,this.map_el.style.width=`${o}px`,this.map_el.style.height=`${i}px`}}_paint_empty(t,e){const s=this.layout.bbox.width,o=this.layout.bbox.height,[i,a,n,p]=e;t.clearRect(0,0,s,o),t.beginPath(),t.moveTo(0,0),t.lineTo(0,o),t.lineTo(s,o),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(i,a),t.lineTo(i+n,a),t.lineTo(i+n,a+p),t.lineTo(i,a+p),t.lineTo(i,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=_.color2css(this.model.border_fill_color),t.fill())}}s.GMapPlotView=d,d.__name__=\"GMapPlotView\"},\n", " function _(t,_,n,o,r){o();t(1).__exportStar(t(169),n)},\n", " function _(e,r,d,n,R){n(),R(\"GlyphRenderer\",e(61).GlyphRenderer),R(\"GraphRenderer\",e(123).GraphRenderer),R(\"GuideRenderer\",e(164).GuideRenderer),R(\"Renderer\",e(41).Renderer)},\n", " function _(e,t,n,o,c){o();e(1).__exportStar(e(129),n),c(\"Selection\",e(59).Selection)},\n", " function _(a,e,S,o,r){o(),r(\"ServerSentDataSource\",a(342).ServerSentDataSource),r(\"AjaxDataSource\",a(344).AjaxDataSource),r(\"ColumnDataSource\",a(130).ColumnDataSource),r(\"ColumnarDataSource\",a(57).ColumnarDataSource),r(\"CDSView\",a(120).CDSView),r(\"DataSource\",a(58).DataSource),r(\"GeoJSONDataSource\",a(345).GeoJSONDataSource),r(\"WebDataSource\",a(343).WebDataSource)},\n", " function _(e,t,i,a,s){a();const n=e(343);class r extends n.WebDataSource{constructor(e){super(e),this.initialized=!1}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{var t;this.load_data(JSON.parse(e.data),this.mode,null!==(t=this.max_size)&&void 0!==t?t:void 0)}}}}i.ServerSentDataSource=r,r.__name__=\"ServerSentDataSource\"},\n", " function _(t,e,a,n,s){n();const r=t(130),i=t(20);class l extends r.ColumnDataSource{constructor(t){super(t)}get_column(t){const e=this.data[t];return null!=e?e:[]}get_length(){var t;return null!==(t=super.get_length())&&void 0!==t?t:0}initialize(){super.initialize(),this.setup()}load_data(t,e,a){const{adapter:n}=this;let s;switch(s=null!=n?n.execute(this,{response:t}):t,e){case\"replace\":this.data=s;break;case\"append\":{const t=this.data;for(const e of this.columns()){const n=Array.from(t[e]),r=Array.from(s[e]),i=n.concat(r);s[e]=null!=a?i.slice(-a):i}this.data=s;break}}}static init_WebDataSource(){this.define((({Any:t,Int:e,String:a,Nullable:n})=>({max_size:[n(e),null],mode:[i.UpdateMode,\"replace\"],adapter:[n(t),null],data_url:[a]})))}}a.WebDataSource=l,l.__name__=\"WebDataSource\",l.init_WebDataSource()},\n", " function _(t,e,i,s,a){s();const n=t(343),r=t(20),o=t(19),l=t(13);class d extends n.WebDataSource{constructor(t){super(t),this.interval=null,this.initialized=!1}static init_AjaxDataSource(){this.define((({Boolean:t,Int:e,String:i,Dict:s,Nullable:a})=>({polling_interval:[a(e),null],content_type:[i,\"application/json\"],http_headers:[s(i),{}],method:[r.HTTPMethod,\"POST\"],if_modified:[t,!1]})))}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),null!=this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=null,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",(()=>this.do_load(s,t,null!=e?e:void 0))),s.addEventListener(\"error\",(()=>this.do_error(s))),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of l.entries(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){o.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=d,d.__name__=\"AjaxDataSource\",d.init_AjaxDataSource()},\n", " function _(e,t,o,r,n){r();const s=e(57),a=e(19),i=e(9),l=e(13);function c(e){return null!=e?e:NaN}const{hasOwnProperty:_}=Object.prototype;class g extends s.ColumnarDataSource{constructor(e){super(e)}static init_GeoJSONDataSource(){this.define((({String:e})=>({geojson:[e]}))),this.internal((({Dict:e,Arrayable:t})=>({data:[e(t),{}]})))}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,(()=>this._update_data()))}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return i.range(0,e).map((e=>[]))}_get_new_nan_array(e){return i.range(0,e).map((e=>NaN))}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of l.entries(s))_.call(t,e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=c(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=c(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&a.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&a.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const s=n.reduce(r);for(let e=0;e({use_latlon:[e,!1]})))}get_image_url(e,t,r){const i=this.string_lookup_replace(this.url,this.extra_url_vars);let o,l,n,s;return this.use_latlon?[l,s,o,n]=this.get_tile_geographic_bounds(e,t,r):[l,s,o,n]=this.get_tile_meter_bounds(e,t,r),i.replace(\"{XMIN}\",l.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",o.toString()).replace(\"{YMAX}\",n.toString())}}r.BBoxTileSource=n,n.__name__=\"BBoxTileSource\",n.init_BBoxTileSource()},\n", " function _(t,e,i,_,s){_();const r=t(349),o=t(9),n=t(350);class l extends r.TileSource{constructor(t){super(t)}static init_MercatorTileSource(){this.define((({Boolean:t})=>({snap_to_zoom:[t,!1],wrap_around:[t,!0]}))),this.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})}initialize(){super.initialize(),this._resolutions=o.range(this.min_zoom,this.max_zoom+1).map((t=>this.get_resolution(t)))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=l,l.__name__=\"MercatorTileSource\",l.init_MercatorTileSource()},\n", " function _(e,t,r,i,n){i();const l=e(53),s=e(13);class a extends l.Model{constructor(e){super(e)}static init_TileSource(){this.define((({Number:e,String:t,Dict:r,Nullable:i})=>({url:[t,\"\"],tile_size:[e,256],max_zoom:[e,30],min_zoom:[e,0],extra_url_vars:[r(t),{}],attribution:[t,\"\"],x_origin_offset:[e],y_origin_offset:[e],initial_resolution:[i(e),null]})))}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._clear_cache()))}string_lookup_replace(e,t){let r=e;for(const[e,i]of s.entries(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map((e=>parseInt(e)));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,l]=t,s=(n-r)/2+r,a=(l-i)/2+i;e.sort((function(e,t){return Math.sqrt((s-e[0])**2+(a-e[1])**2)-Math.sqrt((s-t[0])**2+(a-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=a,a.__name__=\"TileSource\",a.init_TileSource()},\n", " function _(t,e,r,n,o){n();const c=t(65);function _(t,e){return c.wgs84_mercator.compute(t,e)}function g(t,e){return c.wgs84_mercator.invert(t,e)}r.geographic_to_meters=_,r.meters_to_geographic=g,r.geographic_extent_to_meters=function(t){const[e,r,n,o]=t,[c,g]=_(e,r),[i,u]=_(n,o);return[c,g,i,u]},r.meters_extent_to_geographic=function(t){const[e,r,n,o]=t,[c,_]=g(e,r),[i,u]=g(n,o);return[c,_,i,u]}},\n", " function _(e,t,r,s,_){s();const o=e(348);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const s=this.string_lookup_replace(this.url,this.extra_url_vars),[_,o,c]=this.tms_to_wmts(e,t,r),i=this.tile_xyz_to_quadkey(_,o,c);return s.replace(\"{Q}\",i)}}r.QUADKEYTileSource=c,c.__name__=\"QUADKEYTileSource\"},\n", " function _(t,e,i,s,_){s();const n=t(1),a=t(349),h=t(353),r=t(41),o=t(156),l=t(43),d=t(296),m=t(9),c=t(8),p=n.__importStar(t(354));class g extends r.RendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.tile_source.change,(()=>this.request_render()))}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&l.removeElement(this.attribution_el);const{attribution:t}=this.model.tile_source;if(c.isString(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=l.div({class:p.tile_attribution,style:{position:\"absolute\",right:`${s}px`,bottom:`${_}px`,\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof o.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof o.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const[n,a,h]=this.model.tile_source.normalize_xyz(t,e,i),r={img:void 0,tile_coords:[t,e,i],normalized_coords:[n,a,h],quadkey:this.model.tile_source.tile_xyz_to_quadkey(t,e,i),cache_key:this.model.tile_source.tile_xyz_to_key(t,e,i),bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]},o=this.model.tile_source.get_image_url(n,a,h);new d.ImageLoader(o,{loaded:t=>{Object.assign(r,{img:t,loaded:!0}),_?(r.finished=!0,this.notify_finished()):this.request_render()},failed(){r.finished=!0}}),this.model.tile_source.tiles.set(r.cache_key,r),this._tiles.push(r)}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0===this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,h=t,r=i,o=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,h,r,n,a),this.map_canvas.setImageSmoothingEnabled(o),e.finished=!0}}_set_rect(){const t=this.plot_model.outline_line_width,e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,h=i,r=!0),r&&(this.x_range.setv({start:s[0],end:s[2]}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const o=t.get_tiles_by_extent(s,h),l=[],d=[],c=[],p=[];for(const e of o){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),h=t.tiles.get(a);if(null!=h&&h.loaded)d.push(a);else if(this.model.render_parents){const[e,a,h]=t.get_closest_parent_by_tile_xyz(i,s,n),r=t.tile_xyz_to_key(e,a,h),o=t.tiles.get(r);if(null!=o&&o.loaded&&!m.includes(c,r)&&c.push(r),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&p.push(e)}}}null==h&&l.push(e)}this._render_tiles(c),this._render_tiles(p),this._render_tiles(d),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout((()=>this._fetch_tiles(l)),65)}}i.TileRendererView=g,g.__name__=\"TileRendererView\";class u extends r.Renderer{constructor(t){super(t)}static init_TileRenderer(){this.prototype.default_view=g,this.define((({Boolean:t,Number:e,Ref:i})=>({alpha:[e,1],smoothing:[t,!0],tile_source:[i(a.TileSource),()=>new h.WMTSTileSource],render_parents:[t,!0]}))),this.override({level:\"image\"})}}i.TileRenderer=u,u.__name__=\"TileRenderer\",u.init_TileRenderer()},\n", " function _(t,e,r,o,s){o();const c=t(348);class i extends c.MercatorTileSource{constructor(t){super(t)}get_image_url(t,e,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,i]=this.tms_to_wmts(t,e,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",i.toString())}}r.WMTSTileSource=i,i.__name__=\"WMTSTileSource\"},\n", " function _(t,o,i,b,r){b(),i.root=\"bk-root\",i.tile_attribution=\"bk-tile-attribution\",i.default=\".bk-root .bk-tile-attribution a{color:black;}\"},\n", " function _(e,r,t,c,o){c();const i=e(348);class l extends i.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=l,l.__name__=\"TMSTileSource\"},\n", " function _(e,t,u,a,r){a(),r(\"CanvasTexture\",e(357).CanvasTexture),r(\"ImageURLTexture\",e(359).ImageURLTexture),r(\"Texture\",e(358).Texture)},\n", " function _(t,e,n,c,s){c();const a=t(358),i=t(34);class r extends a.Texture{constructor(t){super(t)}static init_CanvasTexture(){this.define((({String:t})=>({code:[t]})))}get func(){const t=i.use_strict(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),c}}n.CanvasTexture=r,r.__name__=\"CanvasTexture\",r.init_CanvasTexture()},\n", " function _(e,t,i,n,r){n();const s=e(53),u=e(20);class o extends s.Model{constructor(e){super(e)}static init_Texture(){this.define((()=>({repetition:[u.TextureRepetition,\"repeat\"]})))}}i.Texture=o,o.__name__=\"Texture\",o.init_Texture()},\n", " function _(e,t,i,r,n){r();const a=e(358),s=e(296);class u extends a.Texture{constructor(e){super(e)}static init_ImageURLTexture(){this.define((({String:e})=>({url:[e]})))}initialize(){super.initialize(),this._loader=new s.ImageLoader(this.url)}get_pattern(e,t,i){const{_loader:r}=this;return this._loader.finished?r.image:r.promise}}i.ImageURLTexture=u,u.__name__=\"ImageURLTexture\",u.init_ImageURLTexture()},\n", " function _(o,l,T,e,t){e(),t(\"ActionTool\",o(251).ActionTool),t(\"CustomAction\",o(361).CustomAction),t(\"HelpTool\",o(252).HelpTool),t(\"RedoTool\",o(362).RedoTool),t(\"ResetTool\",o(363).ResetTool),t(\"SaveTool\",o(364).SaveTool),t(\"UndoTool\",o(365).UndoTool),t(\"ZoomInTool\",o(366).ZoomInTool),t(\"ZoomOutTool\",o(369).ZoomOutTool),t(\"ButtonTool\",o(238).ButtonTool),t(\"EditTool\",o(370).EditTool),t(\"BoxEditTool\",o(371).BoxEditTool),t(\"FreehandDrawTool\",o(372).FreehandDrawTool),t(\"PointDrawTool\",o(373).PointDrawTool),t(\"PolyDrawTool\",o(374).PolyDrawTool),t(\"PolyTool\",o(375).PolyTool),t(\"PolyEditTool\",o(376).PolyEditTool),t(\"BoxSelectTool\",o(377).BoxSelectTool),t(\"BoxZoomTool\",o(379).BoxZoomTool),t(\"GestureTool\",o(237).GestureTool),t(\"LassoSelectTool\",o(380).LassoSelectTool),t(\"LineEditTool\",o(382).LineEditTool),t(\"PanTool\",o(384).PanTool),t(\"PolySelectTool\",o(381).PolySelectTool),t(\"RangeTool\",o(385).RangeTool),t(\"SelectTool\",o(378).SelectTool),t(\"TapTool\",o(386).TapTool),t(\"WheelPanTool\",o(387).WheelPanTool),t(\"WheelZoomTool\",o(388).WheelZoomTool),t(\"CrosshairTool\",o(389).CrosshairTool),t(\"CustomJSHover\",o(390).CustomJSHover),t(\"HoverTool\",o(391).HoverTool),t(\"InspectTool\",o(247).InspectTool),t(\"Tool\",o(236).Tool),t(\"ToolProxy\",o(392).ToolProxy),t(\"Toolbar\",o(235).Toolbar),t(\"ToolbarBase\",o(248).ToolbarBase),t(\"ProxyToolbar\",o(393).ProxyToolbar),t(\"ToolbarBox\",o(393).ToolbarBox)},\n", " function _(t,o,i,s,n){s();const e=t(251);class c extends e.ActionToolButtonView{css_classes(){return super.css_classes().concat(\"bk-toolbar-button-custom-action\")}}i.CustomActionButtonView=c,c.__name__=\"CustomActionButtonView\";class u extends e.ActionToolView{doit(){var t;null===(t=this.model.callback)||void 0===t||t.execute(this.model)}}i.CustomActionView=u,u.__name__=\"CustomActionView\";class l extends e.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=c}static init_CustomAction(){this.prototype.default_view=u,this.define((({Any:t,String:o,Nullable:i})=>({callback:[i(t)],icon:[o]}))),this.override({description:\"Perform a Custom Action\"})}}i.CustomAction=l,l.__name__=\"CustomAction\",l.init_CustomAction()},\n", " function _(o,e,t,i,s){i();const n=o(251),d=o(242);class l extends n.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_redo))}doit(){this.plot_view.state.redo()}}t.RedoToolView=l,l.__name__=\"RedoToolView\";class _ extends n.ActionTool{constructor(o){super(o),this.tool_name=\"Redo\",this.icon=d.tool_icon_redo}static init_RedoTool(){this.prototype.default_view=l,this.override({disabled:!0}),this.register_alias(\"redo\",(()=>new _))}}t.RedoTool=_,_.__name__=\"RedoTool\",_.init_RedoTool()},\n", " function _(e,t,o,s,i){s();const _=e(251),n=e(242);class l extends _.ActionToolView{doit(){this.plot_view.reset()}}o.ResetToolView=l,l.__name__=\"ResetToolView\";class c extends _.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=n.tool_icon_reset}static init_ResetTool(){this.prototype.default_view=l,this.register_alias(\"reset\",(()=>new c))}}o.ResetTool=c,c.__name__=\"ResetTool\",c.init_ResetTool()},\n", " function _(o,e,t,a,i){a();const n=o(251),s=o(242);class c extends n.ActionToolView{async copy(){const o=await this.plot_view.to_blob(),e=new ClipboardItem({[o.type]:o});await navigator.clipboard.write([e])}async save(o){const e=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(e),t.download=o,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(o=\"save\"){switch(o){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=c,c.__name__=\"SaveToolView\";class l extends n.ActionTool{constructor(o){super(o),this.tool_name=\"Save\",this.icon=s.tool_icon_save}static init_SaveTool(){this.prototype.default_view=c,this.register_alias(\"save\",(()=>new l))}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=l,l.__name__=\"SaveTool\",l.init_SaveTool()},\n", " function _(o,t,n,i,e){i();const s=o(251),d=o(242);class l extends s.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_undo))}doit(){this.plot_view.state.undo()}}n.UndoToolView=l,l.__name__=\"UndoToolView\";class _ extends s.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=d.tool_icon_undo}static init_UndoTool(){this.prototype.default_view=l,this.override({disabled:!0}),this.register_alias(\"undo\",(()=>new _))}}n.UndoTool=_,_.__name__=\"UndoTool\",_.init_UndoTool()},\n", " function _(o,i,n,s,e){s();const t=o(367),_=o(242);class m extends t.ZoomBaseToolView{}n.ZoomInToolView=m,m.__name__=\"ZoomInToolView\";class l extends t.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=_.tool_icon_zoom_in}static init_ZoomInTool(){this.prototype.default_view=m,this.register_alias(\"zoom_in\",(()=>new l({dimensions:\"both\"}))),this.register_alias(\"xzoom_in\",(()=>new l({dimensions:\"width\"}))),this.register_alias(\"yzoom_in\",(()=>new l({dimensions:\"height\"})))}}n.ZoomInTool=l,l.__name__=\"ZoomInTool\",l.init_ZoomInTool()},\n", " function _(o,t,e,i,s){i();const n=o(251),l=o(20),a=o(368);class _ extends n.ActionToolView{doit(){var o;const t=this.plot_view.frame,e=this.model.dimensions,i=\"width\"==e||\"both\"==e,s=\"height\"==e||\"both\"==e,n=a.scale_range(t,this.model.sign*this.model.factor,i,s);this.plot_view.state.push(\"zoom_out\",{range:n}),this.plot_view.update_range(n,{scrolling:!0}),null===(o=this.model.document)||void 0===o||o.interactive_start(this.plot_model)}}e.ZoomBaseToolView=_,_.__name__=\"ZoomBaseToolView\";class m extends n.ActionTool{constructor(o){super(o)}static init_ZoomBaseTool(){this.define((({Percent:o})=>({factor:[o,.1],dimensions:[l.Dimensions,\"both\"]})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.ZoomBaseTool=m,m.__name__=\"ZoomBaseTool\",m.init_ZoomBaseTool()},\n", " function _(n,t,o,r,s){r();const c=n(10);function e(n,t,o){const[r,s]=[n.start,n.end],c=null!=o?o:(s+r)/2;return[r-(r-c)*t,s-(s-c)*t]}function a(n,[t,o]){const r=new Map;for(const[s,c]of n){const[n,e]=c.r_invert(t,o);r.set(s,{start:n,end:e})}return r}o.scale_highlow=e,o.get_info=a,o.scale_range=function(n,t,o=!0,r=!0,s){t=c.clamp(t,-.9,.9);const l=o?t:0,[u,i]=e(n.bbox.h_range,l,null!=s?s.x:void 0),_=a(n.x_scales,[u,i]),f=r?t:0,[g,x]=e(n.bbox.v_range,f,null!=s?s.y:void 0);return{xrs:_,yrs:a(n.y_scales,[g,x]),factor:t}}},\n", " function _(o,t,i,s,e){s();const n=o(367),_=o(242);class m extends n.ZoomBaseToolView{}i.ZoomOutToolView=m,m.__name__=\"ZoomOutToolView\";class l extends n.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=_.tool_icon_zoom_out}static init_ZoomOutTool(){this.prototype.default_view=m,this.register_alias(\"zoom_out\",(()=>new l({dimensions:\"both\"}))),this.register_alias(\"xzoom_out\",(()=>new l({dimensions:\"width\"}))),this.register_alias(\"yzoom_out\",(()=>new l({dimensions:\"height\"})))}}i.ZoomOutTool=l,l.__name__=\"ZoomOutTool\",l.init_ZoomOutTool()},\n", " function _(e,t,s,o,n){o();const i=e(9),r=e(8),c=e(11),a=e(61),_=e(237);class l extends _.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void c.unreachable():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,s){if(!this.plot_view.frame.bbox.contains(e,t))return null;const o=this.plot_view.renderer_view(s);if(null==o)return null;return[o.coordinates.x_scale.invert(e),o.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,s=t.selected.indices;s.sort();for(const e of t.columns()){const o=t.get_array(e);for(let e=0;e({custom_icon:[n(t),null],empty_value:[e],renderers:[s(o(a.GlyphRenderer)),[]]})))}get computed_icon(){var e;return null!==(e=this.custom_icon)&&void 0!==e?e:this.icon}}s.EditTool=d,d.__name__=\"EditTool\",d.init_EditTool()},\n", " function _(e,t,s,i,_){i();const o=e(43),n=e(20),a=e(370),d=e(242);class l extends a.EditToolView{_tap(e){null==this._draw_basepoint&&null==this._basepoint&&this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)if(e.keyCode===o.Keys.Backspace)this._delete_selected(t);else if(e.keyCode==o.Keys.Esc){t.data_source.selection_manager.clear()}}_set_extent([e,t],[s,i],_,o=!1){const n=this.model.renderers[0],a=this.plot_view.renderer_view(n);if(null==a)return;const d=n.glyph,l=n.data_source,[r,h]=a.coordinates.x_scale.r_invert(e,t),[p,u]=a.coordinates.y_scale.r_invert(s,i),[c,m]=[(r+h)/2,(p+u)/2],[f,b]=[h-r,u-p],[x,y]=[d.x.field,d.y.field],[w,v]=[d.width.field,d.height.field];if(_)this._pop_glyphs(l,this.model.num_objects),x&&l.get_array(x).push(c),y&&l.get_array(y).push(m),w&&l.get_array(w).push(f),v&&l.get_array(v).push(b),this._pad_empty_columns(l,[x,y,w,v]);else{const e=l.data[x].length-1;x&&(l.data[x][e]=c),y&&(l.data[y][e]=m),w&&(l.data[w][e]=f),v&&(l.data[v][e]=b)}this._emit_cds_changes(l,!0,!1,o)}_update_box(e,t=!1,s=!1){if(null==this._draw_basepoint)return;const i=[e.sx,e.sy],_=this.plot_view.frame,o=this.model.dimensions,n=this.model._get_dim_limits(this._draw_basepoint,i,_,o);if(null!=n){const[e,i]=n;this._set_extent(e,i,t,s)}}_doubletap(e){this.model.active&&(null!=this._draw_basepoint?(this._update_box(e,!1,!0),this._draw_basepoint=null):(this._draw_basepoint=[e.sx,e.sy],this._select_event(e,\"append\",this.model.renderers),this._update_box(e,!0,!1)))}_move(e){this._update_box(e,!1,!1)}_pan_start(e){if(e.shiftKey){if(null!=this._draw_basepoint)return;this._draw_basepoint=[e.sx,e.sy],this._update_box(e,!0,!1)}else{if(null!=this._basepoint)return;this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy]}}_pan(e,t=!1,s=!1){if(e.shiftKey){if(null==this._draw_basepoint)return;this._update_box(e,t,s)}else{if(null==this._basepoint)return;this._drag_points(e,this.model.renderers)}}_pan_end(e){if(this._pan(e,!1,!0),e.shiftKey)this._draw_basepoint=null;else{this._basepoint=null;for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0)}}}s.BoxEditToolView=l,l.__name__=\"BoxEditToolView\";class r extends a.EditTool{constructor(e){super(e),this.tool_name=\"Box Edit Tool\",this.icon=d.tool_icon_box_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=1}static init_BoxEditTool(){this.prototype.default_view=l,this.define((({Int:e})=>({dimensions:[n.Dimensions,\"both\"],num_objects:[e,0]})))}}s.BoxEditTool=r,r.__name__=\"BoxEditTool\",r.init_BoxEditTool()},\n", " function _(e,t,a,s,r){s();const _=e(43),i=e(8),o=e(370),d=e(242);class n extends o.EditToolView{_draw(e,t,a=!1){if(!this.model.active)return;const s=this.model.renderers[0],r=this._map_drag(e.sx,e.sy,s);if(null==r)return;const[_,o]=r,d=s.data_source,n=s.glyph,[h,l]=[n.xs.field,n.ys.field];if(\"new\"==t)this._pop_glyphs(d,this.model.num_objects),h&&d.get_array(h).push([_]),l&&d.get_array(l).push([o]),this._pad_empty_columns(d,[h,l]);else if(\"add\"==t){if(h){const e=d.data[h].length-1;let t=d.get_array(h)[e];i.isArray(t)||(t=Array.from(t),d.data[h][e]=t),t.push(_)}if(l){const e=d.data[l].length-1;let t=d.get_array(l)[e];i.isArray(t)||(t=Array.from(t),d.data[l][e]=t),t.push(o)}}this._emit_cds_changes(d,!0,!0,a)}_pan_start(e){this._draw(e,\"new\")}_pan(e){this._draw(e,\"add\")}_pan_end(e){this._draw(e,\"add\",!0)}_tap(e){this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===_.Keys.Esc?t.data_source.selection_manager.clear():e.keyCode===_.Keys.Backspace&&this._delete_selected(t)}}a.FreehandDrawToolView=n,n.__name__=\"FreehandDrawToolView\";class h extends o.EditTool{constructor(e){super(e),this.tool_name=\"Freehand Draw Tool\",this.icon=d.tool_icon_freehand_draw,this.event_type=[\"pan\",\"tap\"],this.default_order=3}static init_FreehandDrawTool(){this.prototype.default_view=n,this.define((({Int:e})=>({num_objects:[e,0]}))),this.register_alias(\"freehand_draw\",(()=>new h))}}a.FreehandDrawTool=h,h.__name__=\"FreehandDrawTool\",h.init_FreehandDrawTool()},\n", " function _(e,t,s,o,i){o();const a=e(43),n=e(370),_=e(242);class r extends n.EditToolView{_tap(e){if(this._select_event(e,this._select_mode(e),this.model.renderers).length||!this.model.add)return;const t=this.model.renderers[0],s=this._map_drag(e.sx,e.sy,t);if(null==s)return;const o=t.glyph,i=t.data_source,[a,n]=[o.x.field,o.y.field],[_,r]=s;this._pop_glyphs(i,this.model.num_objects),a&&i.get_array(a).push(_),n&&i.get_array(n).push(r),this._pad_empty_columns(i,[a,n]),i.change.emit(),i.data=i.data,i.properties.data.change.emit()}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===a.Keys.Backspace?this._delete_selected(t):e.keyCode==a.Keys.Esc&&t.data_source.selection_manager.clear()}_pan_start(e){this.model.drag&&(this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy])}_pan(e){this.model.drag&&null!=this._basepoint&&this._drag_points(e,this.model.renderers)}_pan_end(e){if(this.model.drag){this._pan(e);for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0);this._basepoint=null}}}s.PointDrawToolView=r,r.__name__=\"PointDrawToolView\";class d extends n.EditTool{constructor(e){super(e),this.tool_name=\"Point Draw Tool\",this.icon=_.tool_icon_point_draw,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=2}static init_PointDrawTool(){this.prototype.default_view=r,this.define((({Boolean:e,Int:t})=>({add:[e,!0],drag:[e,!0],num_objects:[t,0]})))}}s.PointDrawTool=d,d.__name__=\"PointDrawTool\",d.init_PointDrawTool()},\n", " function _(e,t,s,i,a){i();const o=e(43),r=e(8),n=e(375),_=e(242);class d extends n.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._initialized=!1}_tap(e){this._drawing?this._draw(e,\"add\",!0):this._select_event(e,this._select_mode(e),this.model.renderers)}_draw(e,t,s=!1){const i=this.model.renderers[0],a=this._map_drag(e.sx,e.sy,i);if(this._initialized||this.activate(),null==a)return;const[o,n]=this._snap_to_vertex(e,...a),_=i.data_source,d=i.glyph,[l,h]=[d.xs.field,d.ys.field];if(\"new\"==t)this._pop_glyphs(_,this.model.num_objects),l&&_.get_array(l).push([o,o]),h&&_.get_array(h).push([n,n]),this._pad_empty_columns(_,[l,h]);else if(\"edit\"==t){if(l){const e=_.data[l][_.data[l].length-1];e[e.length-1]=o}if(h){const e=_.data[h][_.data[h].length-1];e[e.length-1]=n}}else if(\"add\"==t){if(l){const e=_.data[l].length-1;let t=_.get_array(l)[e];const s=t[t.length-1];t[t.length-1]=o,r.isArray(t)||(t=Array.from(t),_.data[l][e]=t),t.push(s)}if(h){const e=_.data[h].length-1;let t=_.get_array(h)[e];const s=t[t.length-1];t[t.length-1]=n,r.isArray(t)||(t=Array.from(t),_.data[h][e]=t),t.push(s)}}this._emit_cds_changes(_,!0,!1,s)}_show_vertices(){if(!this.model.active)return;const e=[],t=[];for(let s=0;sthis._show_vertices()))}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=d,d.__name__=\"PolyDrawToolView\";class l extends n.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}static init_PolyDrawTool(){this.prototype.default_view=d,this.define((({Boolean:e,Int:t})=>({drag:[e,!0],num_objects:[t,0]})))}}s.PolyDrawTool=l,l.__name__=\"PolyDrawTool\",l.init_PolyDrawTool()},\n", " function _(e,t,r,o,s){o();const i=e(8),l=e(370);class _ extends l.EditToolView{_set_vertices(e,t){const r=this.model.vertex_renderer.glyph,o=this.model.vertex_renderer.data_source,[s,l]=[r.x.field,r.y.field];s&&(i.isArray(e)?o.data[s]=e:r.x={value:e}),l&&(i.isArray(t)?o.data[l]=t:r.y={value:t}),this._emit_cds_changes(o,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,t,r){if(this.model.vertex_renderer){const o=this._select_event(e,\"replace\",[this.model.vertex_renderer]),s=this.model.vertex_renderer.data_source,i=this.model.vertex_renderer.glyph,[l,_]=[i.x.field,i.y.field];if(o.length){const e=s.selected.indices[0];l&&(t=s.data[l][e]),_&&(r=s.data[_][e]),s.selection_manager.clear()}}return[t,r]}}r.PolyToolView=_,_.__name__=\"PolyToolView\";class d extends l.EditTool{constructor(e){super(e)}static init_PolyTool(){this.define((({AnyRef:e})=>({vertex_renderer:[e()]})))}}r.PolyTool=d,d.__name__=\"PolyTool\",d.init_PolyTool()},\n", " function _(e,t,s,r,i){r();const _=e(43),d=e(8),n=e(375),l=e(242);class a extends n.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._cur_index=null}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this.model.renderers[0],s=()=>this._update_vertices(t),r=null==t?void 0:t.data_source,i=this._select_event(e,\"replace\",this.model.renderers);if(!i.length)return this._set_vertices([],[]),this._selected_renderer=null,this._drawing=!1,this._cur_index=null,void(null!=r&&r.disconnect(r.properties.data.change,s));null!=r&&r.connect(r.properties.data.change,s),this._cur_index=i[0].data_source.selected.indices[0],this._update_vertices(i[0])}_update_vertices(e){const t=e.glyph,s=e.data_source,r=this._cur_index,[i,_]=[t.xs.field,t.ys.field];if(this._drawing)return;if(null==r&&(i||_))return;let n,l;i&&null!=r?(n=s.data[i][r],d.isArray(n)||(s.data[i][r]=n=Array.from(n))):n=t.xs.value,_&&null!=r?(l=s.data[_][r],d.isArray(l)||(s.data[_][r]=l=Array.from(l))):l=t.ys.value,this._selected_renderer=e,this._set_vertices(n,l)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===_.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==_.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=a,a.__name__=\"PolyEditToolView\";class c extends n.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=l.tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}static init_PolyEditTool(){this.prototype.default_view=a}}s.PolyEditTool=c,c.__name__=\"PolyEditTool\",c.init_PolyEditTool()},\n", " function _(e,t,o,s,i){s();const l=e(378),n=e(136),_=e(20),c=e(242);class h extends l.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.state.push(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const n={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(n,i,l)}}o.BoxSelectToolView=h,h.__name__=\"BoxSelectToolView\";const r=()=>new n.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class a extends l.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=c.tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}static init_BoxSelectTool(){this.prototype.default_view=h,this.define((({Boolean:e,Ref:t})=>({dimensions:[_.Dimensions,\"both\"],select_every_mousemove:[e,!1],overlay:[t(n.BoxAnnotation),r],origin:[_.BoxOrigin,\"corner\"]}))),this.register_alias(\"box_select\",(()=>new a)),this.register_alias(\"xbox_select\",(()=>new a({dimensions:\"width\"}))),this.register_alias(\"ybox_select\",(()=>new a({dimensions:\"height\"})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}o.BoxSelectTool=a,a.__name__=\"BoxSelectTool\",a.init_BoxSelectTool()},\n", " function _(e,t,s,n,o){n();const r=e(237),c=e(61),i=e(123),l=e(62),a=e(161),_=e(20),d=e(43),h=e(264),p=e(15),u=e(11);class m extends r.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect((()=>this._clear()))}get computed_renderers(){const{renderers:e,names:t}=this.model,s=this.plot_model.data_renderers;return a.compute_renderers(e,s,t)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof c.GlyphRenderer)n=s.data_source;else{if(!(s instanceof i.GraphRenderer))continue;n=s.node_renderer.data_source}const o=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...o,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void u.unreachable():this.model.mode}_keyup(e){e.keyCode==d.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();const e=this.computed_renderers.map((e=>this.plot_view.renderer_view(e)));this.plot_view.request_paint(e)}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,o]of n){const n=o[0].get_selection_manager(),r=[];for(const e of o){const t=this.plot_view.renderer_view(e);null!=t&&r.push(t)}n.select(r,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let o;switch(e.type){case\"point\":{const{sx:t,sy:r}=e,c=s.invert(t),i=n.invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:r}=e,c=s.invert(t),i=n.invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:r,sy0:c,sy1:i}=e,[l,a]=s.r_invert(t,r),[_,d]=n.r_invert(c,i);o=Object.assign(Object.assign({},e),{x0:l,y0:_,x1:a,y1:d});break}case\"poly\":{const{sx:t,sy:r}=e,c=s.v_invert(t),i=n.v_invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new h.SelectionGeometry(o,t))}}s.SelectToolView=m,m.__name__=\"SelectToolView\";class v extends r.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new p.Signal0(this,\"clear\")}static init_SelectTool(){this.define((({String:e,Array:t,Ref:s,Or:n,Auto:o})=>({renderers:[n(t(s(l.DataRenderer)),o),\"auto\"],names:[t(e),[]],mode:[_.SelectionMode,\"replace\"]})))}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=v,v.__name__=\"SelectTool\",v.init_SelectTool()},\n", " function _(t,o,e,s,i){s();const n=t(237),_=t(136),a=t(20),l=t(242);class r extends n.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew _.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class c extends n.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=l.tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}static init_BoxZoomTool(){this.prototype.default_view=r,this.define((({Boolean:t,Ref:o})=>({dimensions:[a.Dimensions,\"both\"],overlay:[o(_.BoxAnnotation),h],match_aspect:[t,!1],origin:[a.BoxOrigin,\"corner\"]}))),this.register_alias(\"box_zoom\",(()=>new c({dimensions:\"both\"}))),this.register_alias(\"xbox_zoom\",(()=>new c({dimensions:\"width\"}))),this.register_alias(\"ybox_zoom\",(()=>new c({dimensions:\"height\"})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.BoxZoomTool=c,c.__name__=\"BoxZoomTool\",c.init_BoxZoomTool()},\n", " function _(s,e,t,o,i){o();const l=s(378),_=s(231),a=s(381),c=s(43),n=s(242);class h extends l.SelectToolView{constructor(){super(...arguments),this.sxs=[],this.sys=[]}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_overlay()}_keyup(s){s.keyCode==c.Keys.Enter&&this._clear_overlay()}_pan_start(s){this.sxs=[],this.sys=[];const{sx:e,sy:t}=s;this._append_overlay(e,t)}_pan(s){const[e,t]=this.plot_view.frame.bbox.clip(s.sx,s.sy);this._append_overlay(e,t),this.model.select_every_mousemove&&this._do_select(this.sxs,this.sys,!1,this._select_mode(s))}_pan_end(s){const{sxs:e,sys:t}=this;this._clear_overlay(),this._do_select(e,t,!0,this._select_mode(s)),this.plot_view.state.push(\"lasso_select\",{selection:this.plot_view.get_selection()})}_append_overlay(s,e){const{sxs:t,sys:o}=this;t.push(s),o.push(e),this.model.overlay.update({xs:t,ys:o})}_clear_overlay(){this.sxs=[],this.sys=[],this.model.overlay.update({xs:this.sxs,ys:this.sys})}_do_select(s,e,t,o){const i={type:\"poly\",sx:s,sy:e};this._select(i,t,o)}}t.LassoSelectToolView=h,h.__name__=\"LassoSelectToolView\";class r extends l.SelectTool{constructor(s){super(s),this.tool_name=\"Lasso Select\",this.icon=n.tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}static init_LassoSelectTool(){this.prototype.default_view=h,this.define((({Boolean:s,Ref:e})=>({select_every_mousemove:[s,!0],overlay:[e(_.PolyAnnotation),a.DEFAULT_POLY_OVERLAY]}))),this.register_alias(\"lasso_select\",(()=>new r))}}t.LassoSelectTool=r,r.__name__=\"LassoSelectTool\",r.init_LassoSelectTool()},\n", " function _(e,t,s,l,o){l();const i=e(378),a=e(231),_=e(43),c=e(9),n=e(242);class h extends i.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==_.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.state.push(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:c.copy(this.data.sx),ys:c.copy(this.data.sy)}))}_do_select(e,t,s,l){const o={type:\"poly\",sx:e,sy:t};this._select(o,s,l)}}s.PolySelectToolView=h,h.__name__=\"PolySelectToolView\";s.DEFAULT_POLY_OVERLAY=()=>new a.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class y extends i.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=n.tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}static init_PolySelectTool(){this.prototype.default_view=h,this.define((({Ref:e})=>({overlay:[e(a.PolyAnnotation),s.DEFAULT_POLY_OVERLAY]}))),this.register_alias(\"poly_select\",(()=>new y))}}s.PolySelectTool=y,y.__name__=\"PolySelectTool\",y.init_PolySelectTool()},\n", " function _(e,t,i,s,n){s();const r=e(20),_=e(383),d=e(242);class o extends _.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const i of t){1==this._select_event(e,\"replace\",[i]).length&&(this._selected_renderer=i)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[i,s]=[t.x.field,t.y.field],n=e.get_array(i),r=e.get_array(s);this._set_intersection(n,r)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const i=this._select_mode(e);if(0==this._select_event(e,i,[t]).length)return}const i=this._select_mode(e);this._select_event(e,i,[t]),this._select_event(e,i,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[i,s]=[e.x.field,e.y.field];if(i&&s){const e=t.data[i],n=t.data[s];this._selected_renderer.data_source.data[i]=e,this._selected_renderer.data_source.data[s]=n}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}i.LineEditToolView=o,o.__name__=\"LineEditToolView\";class l extends _.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=d.tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}static init_LineEditTool(){this.prototype.default_view=o,this.define((()=>({dimensions:[r.Dimensions,\"both\"]})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}i.LineEditTool=l,l.__name__=\"LineEditTool\",l.init_LineEditTool()},\n", " function _(e,i,t,n,o){n();const s=e(8),_=e(370);class r extends _.EditToolView{_set_intersection(e,i){const t=this.model.intersection_renderer.glyph,n=this.model.intersection_renderer.data_source,[o,_]=[t.x.field,t.y.field];o&&(s.isArray(e)?n.data[o]=e:t.x={value:e}),_&&(s.isArray(i)?n.data[_]=i:t.y={value:i}),this._emit_cds_changes(n,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}t.LineToolView=r,r.__name__=\"LineToolView\";class c extends _.EditTool{constructor(e){super(e)}static init_LineTool(){this.define((({AnyRef:e})=>({intersection_renderer:[e()]})))}}t.LineTool=c,c.__name__=\"LineTool\",c.init_LineTool()},\n", " function _(t,s,i,n,e){n();const o=t(1),a=t(237),_=t(20),h=o.__importStar(t(242));function l(t,s,i){const n=new Map;for(const[e,o]of t){const[t,a]=o.r_invert(s,i);n.set(e,{start:t,end:a})}return n}i.update_ranges=l;class r extends a.GestureToolView{_pan_start(t){var s;this.last_dx=0,this.last_dy=0;const{sx:i,sy:n}=t,e=this.plot_view.frame.bbox;if(!e.contains(i,n)){const t=e.h_range,s=e.v_range;(it.end)&&(this.v_axis_only=!0),(ns.end)&&(this.h_axis_only=!0)}null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan(t){var s;this._update(t.deltaX,t.deltaY),null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.state.push(\"pan\",{range:this.pan_info})}_update(t,s){const i=this.plot_view.frame,n=t-this.last_dx,e=s-this.last_dy,o=i.bbox.h_range,a=o.start-n,_=o.end-n,h=i.bbox.v_range,r=h.start-e,d=h.end-e,p=this.model.dimensions;let c,m,u,x,v,y;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,m=o.end,u=0):(c=a,m=_,u=-n),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(x=h.start,v=h.end,y=0):(x=r,v=d,y=-e),this.last_dx=t,this.last_dy=s;const{x_scales:g,y_scales:w}=i,f=l(g,c,m),b=l(w,x,v);this.pan_info={xrs:f,yrs:b,sdx:u,sdy:y},this.plot_view.update_range(this.pan_info,{panning:!0})}}i.PanToolView=r,r.__name__=\"PanToolView\";class d extends a.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}static init_PanTool(){this.prototype.default_view=r,this.define((()=>({dimensions:[_.Dimensions,\"both\",{on_update(t,s){switch(t){case\"both\":s.icon=h.tool_icon_pan;break;case\"width\":s.icon=h.tool_icon_xpan;break;case\"height\":s.icon=h.tool_icon_ypan}}}]}))),this.register_alias(\"pan\",(()=>new d({dimensions:\"both\"}))),this.register_alias(\"xpan\",(()=>new d({dimensions:\"width\"}))),this.register_alias(\"ypan\",(()=>new d({dimensions:\"height\"})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}i.PanTool=d,d.__name__=\"PanTool\",d.init_PanTool()},\n", " function _(t,e,i,s,n){s();const l=t(136),a=t(156),r=t(19),o=t(237),_=t(242);function h(t){switch(t){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return t}}function d(t,e,i,s){if(null==e)return!1;const n=i.compute(e);return Math.abs(t-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const t=s.invert(e);(tn.top)&&(l=!1)}return l}function c(t,e,i){let s=0;return t>=i.start&&t<=i.end&&(s+=1),e>=i.start&&e<=i.end&&(s+=1),s}function g(t,e,i,s){const n=e.compute(t),l=e.invert(n+i);return l>=s.start&&l<=s.end?l:t}function y(t,e,i){return t>e.start?(e.end=t,i):(e.end=e.start,e.start=t,h(i))}function f(t,e,i){return t=o&&(t.start=a,t.end=r)}i.flip_side=h,i.is_near=d,i.is_inside=u,i.sides_inside=c,i.compute_value=g,i.update_range_end_side=y,i.update_range_start_side=f,i.update_range=m;class v extends o.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,(()=>this.model.update_overlay_from_ranges())),null!=this.model.y_range&&this.connect(this.model.y_range.change,(()=>this.model.update_overlay_from_ranges()))}_pan_start(t){this.last_dx=0,this.last_dy=0;const e=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,n=s.x_scale,a=s.y_scale,r=this.model.overlay,{left:o,right:_,top:h,bottom:c}=r,g=this.model.overlay.line_width+l.EDGE_TOLERANCE;null!=e&&this.model.x_interaction&&(d(t.sx,o,n,g)?this.side=1:d(t.sx,_,n,g)?this.side=2:u(t.sx,t.sy,n,a,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&d(t.sy,c,a,g)&&(this.side=4),0==this.side&&d(t.sy,h,a,g)?this.side=5:u(t.sx,t.sy,n,a,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(t){const e=this.plot_view.frame,i=t.deltaX-this.last_dx,s=t.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=e.x_scale,r=e.y_scale;if(null!=n)if(3==this.side||7==this.side)m(n,a,i,e.x_range);else if(1==this.side){const t=g(n.start,a,i,e.x_range);this.side=f(t,n,this.side)}else if(2==this.side){const t=g(n.end,a,i,e.x_range);this.side=y(t,n,this.side)}if(null!=l)if(6==this.side||7==this.side)m(l,r,s,e.y_range);else if(4==this.side){const t=g(l.start,r,s,e.y_range);this.side=f(t,l,this.side)}else if(5==this.side){const t=g(l.end,r,s,e.y_range);this.side=y(t,l,this.side)}this.last_dx=t.deltaX,this.last_dy=t.deltaY}_pan_end(t){this.side=0}}i.RangeToolView=v,v.__name__=\"RangeToolView\";const p=()=>new l.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class x extends o.GestureTool{constructor(t){super(t),this.tool_name=\"Range Tool\",this.icon=_.tool_icon_range,this.event_type=\"pan\",this.default_order=1}static init_RangeTool(){this.prototype.default_view=v,this.define((({Boolean:t,Ref:e,Nullable:i})=>({x_range:[i(e(a.Range1d)),null],x_interaction:[t,!0],y_range:[i(e(a.Range1d)),null],y_interaction:[t,!0],overlay:[e(l.BoxAnnotation),p]})))}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,r.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=x,x.__name__=\"RangeTool\",x.init_RangeTool()},\n", " function _(e,t,s,o,i){o();const l=e(378),a=e(20),n=e(242);class c extends l.SelectToolView{_tap(e){\"tap\"==this.model.gesture&&this._handle_tap(e)}_doubletap(e){\"doubletap\"==this.model.gesture&&this._handle_tap(e)}_handle_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const{callback:o}=this.model;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,l]of i){const i=l[0].get_selection_manager(),a=l.map((e=>this.plot_view.renderer_view(e))).filter((e=>null!=e));if(i.select(a,e,t,s)&&null!=o){const t=a[0].coordinates.x_scale.invert(e.sx),s=a[0].coordinates.y_scale.invert(e.sy),l={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,l)}}this._emit_selection_event(e),this.plot_view.state.push(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_view(t);if(null==s)continue;const i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),l=s.coordinates.y_scale.invert(e.sy),a={geometries:Object.assign(Object.assign({},e),{x:t,y:l}),source:i.source};o.execute(this.model,a)}}}}s.TapToolView=c,c.__name__=\"TapToolView\";class _ extends l.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=n.tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}static init_TapTool(){this.prototype.default_view=c,this.define((({Any:e,Enum:t,Nullable:s})=>({behavior:[a.TapBehavior,\"select\"],gesture:[t(\"tap\",\"doubletap\"),\"tap\"],callback:[s(e)]}))),this.register_alias(\"click\",(()=>new _({behavior:\"inspect\"}))),this.register_alias(\"tap\",(()=>new _)),this.register_alias(\"doubletap\",(()=>new _({gesture:\"doubletap\"})))}}s.TapTool=_,_.__name__=\"TapTool\",_.init_TapTool()},\n", " function _(e,t,s,i,n){i();const o=e(237),a=e(20),l=e(242),_=e(384);class h extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){var t;const{frame:s}=this.plot_view,i=s.bbox.h_range,n=s.bbox.v_range,[o,a]=[i.start,i.end],[l,h]=[n.start,n.end];let r,d,c,p;switch(this.model.dimension){case\"height\":{const t=Math.abs(h-l);r=o,d=a,c=l-t*e,p=h-t*e;break}case\"width\":{const t=Math.abs(a-o);r=o-t*e,d=a-t*e,c=l,p=h;break}}const{x_scales:m,y_scales:u}=s,w={xrs:_.update_ranges(m,r,d),yrs:_.update_ranges(u,c,p),factor:e};this.plot_view.state.push(\"wheel_pan\",{range:w}),this.plot_view.update_range(w,{scrolling:!0}),null===(t=this.model.document)||void 0===t||t.interactive_start(this.plot_model)}}s.WheelPanToolView=h,h.__name__=\"WheelPanToolView\";class r extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=l.tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}static init_WheelPanTool(){this.prototype.default_view=h,this.define((()=>({dimension:[a.Dimension,\"width\"]}))),this.internal((({Number:e})=>({speed:[e,.001]}))),this.register_alias(\"xwheel_pan\",(()=>new r({dimension:\"width\"}))),this.register_alias(\"ywheel_pan\",(()=>new r({dimension:\"height\"})))}get tooltip(){return this._get_dim_tooltip(this.dimension)}}s.WheelPanTool=r,r.__name__=\"WheelPanTool\",r.init_WheelPanTool()},\n", " function _(e,o,t,s,i){s();const l=e(237),n=e(368),h=e(20),_=e(27),a=e(242);class m extends l.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:l}=e;let n;n=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:n,ctrlKey:i,shiftKey:l})}_scroll(e){var o;const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,{sx:l,sy:h}=e,_=this.model.dimensions,a=(\"width\"==_||\"both\"==_)&&s.start({dimensions:[h.Dimensions,\"both\"],maintain_focus:[e,!0],zoom_on_axis:[e,!0],speed:[o,1/600]}))),this.register_alias(\"wheel_zoom\",(()=>new r({dimensions:\"both\"}))),this.register_alias(\"xwheel_zoom\",(()=>new r({dimensions:\"width\"}))),this.register_alias(\"ywheel_zoom\",(()=>new r({dimensions:\"height\"})))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}t.WheelZoomTool=r,r.__name__=\"WheelZoomTool\",r.init_WheelZoomTool()},\n", " function _(i,s,t,o,e){o();const n=i(247),l=i(233),h=i(20),a=i(13),r=i(242);class _ extends n.InspectToolView{_move(i){if(!this.model.active)return;const{sx:s,sy:t}=i;this.plot_view.frame.bbox.contains(s,t)?this._update_spans(s,t):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,s){const t=this.model.dimensions;\"width\"!=t&&\"both\"!=t||(this.model.spans.width.location=s),\"height\"!=t&&\"both\"!=t||(this.model.spans.height.location=i)}}t.CrosshairToolView=_,_.__name__=\"CrosshairToolView\";class c extends n.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=r.tool_icon_crosshair}static init_CrosshairTool(){function i(i,s){return new l.Span({for_hover:!0,dimension:s,location_units:\"screen\",level:\"overlay\",line_color:i.line_color,line_width:i.line_width,line_alpha:i.line_alpha})}this.prototype.default_view=_,this.define((({Alpha:i,Number:s,Color:t})=>({dimensions:[h.Dimensions,\"both\"],line_color:[t,\"black\"],line_width:[s,1],line_alpha:[i,1]}))),this.internal((({Struct:s,Ref:t})=>({spans:[s({width:t(l.Span),height:t(l.Span)}),s=>({width:i(s,\"width\"),height:i(s,\"height\")})]}))),this.register_alias(\"crosshair\",(()=>new c))}get tooltip(){return this._get_dim_tooltip(this.dimensions)}get synthetic_renderers(){return a.values(this.spans)}}t.CrosshairTool=c,c.__name__=\"CrosshairTool\",c.init_CrosshairTool()},\n", " function _(t,e,s,o,r){o();const n=t(53),i=t(13),a=t(34);class u extends n.Model{constructor(t){super(t)}static init_CustomJSHover(){this.define((({Unknown:t,String:e,Dict:s})=>({args:[s(t),{}],code:[e,\"\"]})))}get values(){return i.values(this.args)}_make_code(t,e,s,o){return new Function(...i.keys(this.args),t,e,s,a.use_strict(o))}format(t,e,s){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,t,e,s)}}s.CustomJSHover=u,u.__name__=\"CustomJSHover\",u.init_CustomJSHover()},\n", " function _(e,t,n,s,o){s();const i=e(1),r=e(247),l=e(390),a=e(254),c=e(61),_=e(123),d=e(62),p=e(63),h=e(127),u=i.__importStar(e(107)),m=e(182),y=e(43),f=e(22),x=e(13),v=e(245),w=e(8),g=e(122),b=e(20),k=e(242),C=e(15),S=e(161),T=i.__importStar(e(255));function $(e,t,n,s,o,i){const r={x:o[e],y:i[e]},l={x:o[e+1],y:i[e+1]};let a,c;if(\"span\"==t.type)\"h\"==t.direction?(a=Math.abs(r.x-n),c=Math.abs(l.x-n)):(a=Math.abs(r.y-s),c=Math.abs(l.y-s));else{const e={x:n,y:s};a=u.dist_2_pts(r,e),c=u.dist_2_pts(l,e)}return adelete this._template_el)),this.on_change([e,t,n],(async()=>await this._update_ttmodels()))}async _update_ttmodels(){const{_ttmodels:e,computed_renderers:t}=this;e.clear();const{tooltips:n}=this.model;if(null!=n)for(const t of this.computed_renderers){const s=new a.Tooltip({custom:w.isString(n)||w.isFunction(n),attachment:this.model.attachment,show_arrow:this.model.show_arrow});t instanceof c.GlyphRenderer?e.set(t,s):t instanceof _.GraphRenderer&&(e.set(t.node_renderer,s),e.set(t.edge_renderer,s))}const s=await g.build_views(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of s)e.render();const o=[...function*(){for(const e of t)e instanceof c.GlyphRenderer?yield e:e instanceof _.GraphRenderer&&(yield e.node_renderer,yield e.edge_renderer)}()],i=this._slots.get(this._update);if(null!=i){const e=new Set(o.map((e=>e.data_source)));C.Signal.disconnect_receiver(this,i,e)}for(const e of o)this.connect(e.data_source.inspect,this._update)}get computed_renderers(){const{renderers:e,names:t}=this.model,n=this.plot_model.data_renderers;return S.compute_renderers(e,n,t)}get ttmodels(){return this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:n}=e;this.plot_view.frame.bbox.contains(t,n)?this._inspect(t,n):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let n;if(\"mouse\"==this.model.mode)n={type:\"point\",sx:e,sy:t};else{n={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){const t=e.get_selection_manager(),s=this.plot_view.renderer_view(e);null!=s&&t.inspect(s,n)}this._emit_callback(n)}_update([e,{geometry:t}]){var n,s;if(!this.model.active)return;if(\"point\"!=t.type&&\"span\"!=t.type)return;if(!(e instanceof c.GlyphRenderer))return;if(\"ignore\"==this.model.muted_policy&&e.muted)return;const o=this.ttmodels.get(e);if(null==o)return;const i=e.get_selection_manager();let r=i.inspectors.get(e);if(r=e.view.convert_selection_to_subset(r),r.is_empty())return void o.clear();const l=i.source,a=this.plot_view.renderer_view(e);if(null==a)return;const{sx:_,sy:d}=t,u=a.coordinates.x_scale,m=a.coordinates.y_scale,f=u.invert(_),v=m.invert(d),{glyph:w}=a,g=[];if(w instanceof p.LineView)for(const n of r.line_indices){let s,o,i=w._x[n+1],a=w._y[n+1],c=n;switch(this.model.line_policy){case\"interp\":[i,a]=w.get_interpolation_hit(n,t),s=u.compute(i),o=m.compute(a);break;case\"prev\":[[s,o],c]=R(w.sx,w.sy,n);break;case\"next\":[[s,o],c]=R(w.sx,w.sy,n+1);break;case\"nearest\":[[s,o],c]=$(n,t,_,d,w.sx,w.sy),i=w._x[c],a=w._y[c];break;default:[s,o]=[_,d]}const p={index:c,x:f,y:v,sx:_,sy:d,data_x:i,data_y:a,rx:s,ry:o,indices:r.line_indices,name:e.name};g.push([s,o,this._render_tooltips(l,c,p)])}for(const t of r.image_indices){const n={index:t.index,x:f,y:v,sx:_,sy:d,name:e.name},s=this._render_tooltips(l,t,n);g.push([_,d,s])}for(const o of r.indices)if(w instanceof h.MultiLineView&&!x.isEmpty(r.multiline_indices))for(const n of r.multiline_indices[o.toString()]){let s,i,a,p=w._xs.get(o)[n],h=w._ys.get(o)[n],y=n;switch(this.model.line_policy){case\"interp\":[p,h]=w.get_interpolation_hit(o,n,t),s=u.compute(p),i=m.compute(h);break;case\"prev\":[[s,i],y]=R(w.sxs.get(o),w.sys.get(o),n);break;case\"next\":[[s,i],y]=R(w.sxs.get(o),w.sys.get(o),n+1);break;case\"nearest\":[[s,i],y]=$(n,t,_,d,w.sxs.get(o),w.sys.get(o)),p=w._xs.get(o)[y],h=w._ys.get(o)[y];break;default:throw new Error(\"shouldn't have happened\")}a=e instanceof c.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const x={index:a,x:f,y:v,sx:_,sy:d,data_x:p,data_y:h,segment_index:y,indices:r.multiline_indices,name:e.name};g.push([s,i,this._render_tooltips(l,a,x)])}else{const t=null===(n=w._x)||void 0===n?void 0:n[o],i=null===(s=w._y)||void 0===s?void 0:s[o];let a,p,h;if(\"snap_to_data\"==this.model.point_policy){let e=w.get_anchor_point(this.model.anchor,o,[_,d]);if(null==e&&(e=w.get_anchor_point(\"center\",o,[_,d]),null==e))continue;a=e.x,p=e.y}else[a,p]=[_,d];h=e instanceof c.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const u={index:h,x:f,y:v,sx:_,sy:d,data_x:t,data_y:i,indices:r.indices,name:e.name};g.push([a,p,this._render_tooltips(l,h,u)])}if(0==g.length)o.clear();else{const{content:e}=o;y.empty(o.content);for(const[,,t]of g)null!=t&&e.appendChild(t);const[t,n]=g[g.length-1];o.setv({position:[t,n]},{check_eq:!1})}}_emit_callback(e){const{callback:t}=this.model;if(null!=t)for(const n of this.computed_renderers){if(!(n instanceof c.GlyphRenderer))continue;const s=this.plot_view.renderer_view(n);if(null==s)continue;const{x_scale:o,y_scale:i}=s.coordinates,r=o.invert(e.sx),l=i.invert(e.sy),a=n.data_source.inspected;t.execute(this.model,{geometry:Object.assign({x:r,y:l},e),renderer:n,index:a})}}_create_template(e){const t=y.div({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[n]of e){const e=y.div({style:{display:\"table-row\"}});t.appendChild(e);const s=y.div({style:{display:\"table-cell\"},class:T.tooltip_row_label},0!=n.length?`${n}: `:\"\");e.appendChild(s);const o=y.span();o.dataset.value=\"\";const i=y.span({class:T.tooltip_color_block},\" \");i.dataset.swatch=\"\",y.undisplay(i);const r=y.div({style:{display:\"table-cell\"},class:T.tooltip_row_value},o,i);e.appendChild(r)}return t}_render_template(e,t,n,s,o){const i=e.cloneNode(!0),r=i.querySelectorAll(\"[data-value]\"),l=i.querySelectorAll(\"[data-swatch]\"),a=/\\$color(\\[.*\\])?:(\\w*)/,c=/\\$swatch:(\\w*)/;for(const[[,e],i]of v.enumerate(t)){const t=e.match(c),_=e.match(a);if(null!=t||null!=_){if(null!=t){const[,e]=t,o=n.get_column(e);if(null==o)r[i].textContent=`${e} unknown`;else{const e=w.isNumber(s)?o[s]:null;null!=e&&(l[i].style.backgroundColor=f.color2css(e),y.display(l[i]))}}if(null!=_){const[,e=\"\",t]=_,o=n.get_column(t);if(null==o){r[i].textContent=`${t} unknown`;continue}const a=e.indexOf(\"hex\")>=0,c=e.indexOf(\"swatch\")>=0,d=w.isNumber(s)?o[s]:null;if(null==d){r[i].textContent=\"(null)\";continue}r[i].textContent=a?f.color2hex(d):f.color2css(d),c&&(l[i].style.backgroundColor=f.color2css(d),y.display(l[i]))}}else{const t=m.replace_placeholders(e.replace(\"$~\",\"$data_\"),n,s,this.model.formatters,o);if(w.isString(t))r[i].textContent=t;else for(const e of t)r[i].appendChild(e)}}return i}_render_tooltips(e,t,n){var s;const{tooltips:o}=this.model;if(w.isString(o)){const s=m.replace_placeholders({html:o},e,t,this.model.formatters,n);return y.div({},s)}if(w.isFunction(o))return o(e,n);if(null!=o){const i=null!==(s=this._template_el)&&void 0!==s?s:this._template_el=this._create_template(o);return this._render_template(i,o,e,t,n)}return null}}n.HoverToolView=H,H.__name__=\"HoverToolView\";class M extends r.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=k.tool_icon_hover}static init_HoverTool(){this.prototype.default_view=H,this.define((({Any:e,Boolean:t,String:n,Array:s,Tuple:o,Dict:i,Or:r,Ref:a,Function:c,Auto:_,Nullable:p})=>({tooltips:[p(r(n,s(o(n,n)),c())),[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[i(r(a(l.CustomJSHover),m.FormatterType)),{}],renderers:[r(s(a(d.DataRenderer)),_),\"auto\"],names:[s(n),[]],mode:[b.HoverMode,\"mouse\"],muted_policy:[b.MutedPolicy,\"show\"],point_policy:[b.PointPolicy,\"snap_to_data\"],line_policy:[b.LinePolicy,\"nearest\"],show_arrow:[t,!0],anchor:[b.Anchor,\"center\"],attachment:[b.TooltipAttachment,\"horizontal\"],callback:[p(e)]}))),this.register_alias(\"hover\",(()=>new M))}}n.HoverTool=M,M.__name__=\"HoverTool\",M.init_HoverTool()},\n", " function _(t,o,e,n,i){n();const s=t(15),l=t(53),c=t(238),r=t(247),a=t(245);class u extends l.Model{constructor(t){super(t)}static init_ToolProxy(){this.define((({Boolean:t,Array:o,Ref:e})=>({tools:[o(e(c.ButtonTool)),[]],active:[t,!1],disabled:[t,!1]})))}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof r.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new s.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,(()=>this.doit())),this.connect(this.properties.active.change,(()=>this.set_active()));for(const t of this.tools)this.connect(t.properties.active.change,(()=>{this.active=t.active}))}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,n]of a.enumerate(t))if(null==e)o.push(null);else{const t=()=>{var t,o;for(const e of this.tools)null===(o=null===(t=e.menu)||void 0===t?void 0:t[n])||void 0===o||o.handler()};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=u,u.__name__=\"ToolProxy\",u.init_ToolProxy()},\n", " function _(o,t,s,i,e){i();const n=o(20),r=o(9),l=o(13),c=o(248),h=o(235),a=o(392),_=o(319),p=o(221);class f extends c.ToolbarBase{constructor(o){super(o)}static init_ProxyToolbar(){this.define((({Array:o,Ref:t})=>({toolbars:[o(t(h.Toolbar)),[]]})))}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},i=[],e=[];for(const o of this.help)r.includes(e,o.redirect)||(i.push(o),e.push(o.redirect));this._proxied_tools.push(...i),this.help=i;for(const[o,t]of l.entries(this.gestures)){o in s||(s[o]={});for(const i of t.tools)i.type in s[o]||(s[o][i.type]=[]),s[o][i.type].push(i)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const n=(o,t=!1)=>{const s=new a.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of l.keys(s)){const t=this.gestures[o];t.tools=[];for(const i of l.keys(s[o])){const e=s[o][i];if(e.length>0)if(\"multi\"==o)for(const o of e){const s=n([o]);t.tools.push(s),this.connect(s.properties.active.change,(()=>this._active_change(s)))}else{const o=n(e);t.tools.push(o),this.connect(o.properties.active.change,(()=>this._active_change(o)))}}}this.actions=[];for(const[o,s]of l.entries(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(n([o]));else s.length>0&&this.actions.push(n(s));this.inspectors=[];for(const t of l.values(o))t.length>0&&this.inspectors.push(n(t,!0));for(const[o,t]of l.entries(this.gestures))0!=t.tools.length&&(t.tools=r.sort_by(t.tools,(o=>o.default_order)),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=f,f.__name__=\"ProxyToolbar\",f.init_ProxyToolbar();class u extends _.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new p.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}}s.ToolbarBoxView=u,u.__name__=\"ToolbarBoxView\";class y extends _.LayoutDOM{constructor(o){super(o)}static init_ToolbarBox(){this.prototype.default_view=u,this.define((({Ref:o})=>({toolbar:[o(c.ToolbarBase)],toolbar_location:[n.Location,\"right\"]})))}}s.ToolbarBox=y,y.__name__=\"ToolbarBox\",y.init_ToolbarBox()},\n", " function _(e,n,r,t,o){t();const s=e(1),u=e(53),c=s.__importStar(e(21)),a=e(8),l=e(13);r.resolve_defs=function(e,n){var r,t,o,s;function i(e){return null!=e.module?`${e.module}.${e.name}`:e.name}function f(e){if(a.isString(e))switch(e){case\"Any\":return c.Any;case\"Unknown\":return c.Unknown;case\"Boolean\":return c.Boolean;case\"Number\":return c.Number;case\"Int\":return c.Int;case\"String\":return c.String;case\"Null\":return c.Null}else switch(e[0]){case\"Nullable\":{const[,n]=e;return c.Nullable(f(n))}case\"Or\":{const[,...n]=e;return c.Or(...n.map(f))}case\"Tuple\":{const[,n,...r]=e;return c.Tuple(f(n),...r.map(f))}case\"Array\":{const[,n]=e;return c.Array(f(n))}case\"Struct\":{const[,...n]=e,r=n.map((([e,n])=>[e,f(n)]));return c.Struct(l.to_object(r))}case\"Dict\":{const[,n]=e;return c.Dict(f(n))}case\"Map\":{const[,n,r]=e;return c.Map(f(n),f(r))}case\"Enum\":{const[,...n]=e;return c.Enum(...n)}case\"Ref\":{const[,r]=e,t=n.get(i(r));if(null!=t)return c.Ref(t);throw new Error(`${i(r)} wasn't defined before referencing it`)}case\"AnyRef\":return c.AnyRef()}}for(const c of e){const e=(()=>{if(null==c.extends)return u.Model;{const e=n.get(i(c.extends));if(null!=e)return e;throw new Error(`base model ${i(c.extends)} of ${i(c)} is not defined`)}})(),a=((s=class extends e{}).__name__=c.name,s.__module__=c.module,s);for(const e of null!==(r=c.properties)&&void 0!==r?r:[]){const n=f(null!==(t=e.kind)&&void 0!==t?t:\"Unknown\");a.define({[e.name]:[n,e.default]})}for(const e of null!==(o=c.overrides)&&void 0!==o?o:[])a.override({[e.name]:e.default});n.register(a)}}},\n", " function _(n,e,t,o,i){o();const d=n(5),c=n(240),s=n(122),a=n(43),l=n(396);t.index={},t.add_document_standalone=async function(n,e,o=[],i=!1){const u=new Map;async function f(i){let d;const f=n.roots().indexOf(i),r=o[f];null!=r?d=r:e.classList.contains(l.BOKEH_ROOT)?d=e:(d=a.div({class:l.BOKEH_ROOT}),e.appendChild(d));const w=await s.build_view(i,{parent:null});return w instanceof c.DOMView&&w.renderTo(d),u.set(i,w),t.index[i.id]=w,w}for(const e of n.roots())await f(e);return i&&(window.document.title=n.title()),n.on_change((n=>{n instanceof d.RootAddedEvent?f(n.model):n instanceof d.RootRemovedEvent?function(n){const e=u.get(n);null!=e&&(e.remove(),u.delete(n),delete t.index[n.id])}(n.model):i&&n instanceof d.TitleChangedEvent&&(window.document.title=n.title)})),[...u.values()]}},\n", " function _(o,e,n,t,r){t();const l=o(43),d=o(44);function u(o){let e=document.getElementById(o);if(null==e)throw new Error(`Error rendering Bokeh model: could not find #${o} HTML tag`);if(!document.body.contains(e))throw new Error(`Error rendering Bokeh model: element #${o} must be under `);if(\"SCRIPT\"==e.tagName){const o=l.div({class:n.BOKEH_ROOT});l.replaceWith(e,o),e=o}return e}n.BOKEH_ROOT=d.root,n._resolve_element=function(o){const{elementid:e}=o;return null!=e?u(e):document.body},n._resolve_root_elements=function(o){const e=[];if(null!=o.root_ids&&null!=o.roots)for(const n of o.root_ids)e.push(u(o.roots[n]));return e}},\n", " function _(n,o,t,s,e){s();const c=n(398),r=n(19),a=n(395);t._get_ws_url=function(n,o){let t,s=\"ws:\";return\"https:\"==window.location.protocol&&(s=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),s+\"//\"+t.host+n+\"/ws\"};const i={};t.add_document_from_session=async function(n,o,t,s=[],e=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=c.parse_token(o).session_id;n in i||(i[n]={});const e=i[n];return s in e||(e[s]=c.pull_session(n,o,t)),e[s]}(n,o,l)}catch(n){const t=c.parse_token(o).session_id;throw r.logger.error(`Failed to load Bokeh session 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connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=i.Document.from_json(n),t=i.Document._compute_patch_since_json(n,s);if(t.events.length>0){r.logger.debug(`Sending ${t.events.length} changes from model construction back to server`);const e=c.Message.create(\"PATCH-DOC\",{},t);this.send(e)}this.session=new _.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],r.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),r.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),r.logger.error(`Failed to repull session ${e}`),s(e instanceof Error?e:`${e}`)}}_on_open(e,s){r.logger.info(`Websocket connection ${this._number} is now open`),this._current_handler=n=>{this._awaiting_ack_handler(n,e,s)}}_on_message(e){null==this._current_handler&&r.logger.error(\"Got a message with no current handler set\");try{this._receiver.consume(e.data)}catch(e){this._close_bad_protocol(`${e}`)}const s=this._receiver.message;if(null!=s){const e=s.problem();null!=e&&this._close_bad_protocol(e),this._current_handler(s)}}_on_close(e,s){r.logger.info(`Lost websocket ${this._number} connection, ${e.code} (${e.reason})`),this.socket=null,this._pending_replies.forEach((e=>e.reject(\"Disconnected\"))),this._pending_replies.clear(),this.closed_permanently||this._schedule_reconnect(2e3),s(new Error(`Lost websocket connection, ${e.code} (${e.reason})`))}_on_error(e){r.logger.debug(`Websocket error on socket ${this._number}`);const s=\"Could not open websocket\";r.logger.error(`Failed to connect to Bokeh server: ${s}`),e(new Error(s))}_close_bad_protocol(e){r.logger.error(`Closing connection: 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this.request_server_info()}_document_changed(e){if(e.setter_id===this.id)return;const t=e instanceof c.DocumentEventBatch?e.events:[e],n=this.document.create_json_patch(t),s=i.Message.create(\"PATCH-DOC\",{},n);this._connection.send(s)}_handle_patch(e){this.document.apply_json_patch(e.content,e.buffers,this.id)}_handle_ok(e){_.logger.trace(`Unhandled OK reply to ${e.reqid()}`)}_handle_error(e){_.logger.error(`Unhandled ERROR reply to ${e.reqid()}: ${e.content.text}`)}}n.ClientSession=r,r.__name__=\"ClientSession\"},\n", " function _(e,o,t,n,r){n();const s=e(1),l=e(5),i=e(400),a=e(19),c=e(43),g=e(13),f=e(395),u=e(396),m=s.__importDefault(e(44)),p=s.__importDefault(e(253)),d=s.__importDefault(e(403));function _(e,o){o.buffers.length>0?e.consume(o.buffers[0].buffer):e.consume(o.content.data);const t=e.message;null!=t&&this.apply_json_patch(t.content,t.buffers)}function b(e,o){if(\"undefined\"!=typeof Jupyter&&null!=Jupyter.notebook.kernel){a.logger.info(`Registering Jupyter comms for 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permission.\n", " * \n", " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", " * THE POSSIBILITY OF SUCH DAMAGE.\n", " */\n", " (function(root, factory) {\n", " factory(root[\"Bokeh\"], \"2.3.3\");\n", " })(this, function(Bokeh, version) {\n", " var define;\n", " return (function(modules, entry, aliases, externals) {\n", " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? 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u.TextLikeInput{constructor(t){super(t)}static init_TextInput(){this.prototype.default_view=a}}n.TextInput=c,c.__name__=\"TextInput\",c.init_TextInput()},\n", " 425: function _(e,t,n,i,l){i();const s=e(426);class h extends s.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>this.input_el.value=this.model.value)),this.connect(this.model.properties.value_input.change,(()=>this.input_el.value=this.model.value_input)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.max_length.change,(()=>{const{max_length:e}=this.model;null!=e?this.input_el.maxLength=e:this.input_el.removeAttribute(\"maxLength\")}))}render(){var e;super.render(),this._render_input();const{input_el:t}=this;t.name=null!==(e=this.model.name)&&void 0!==e?e:\"\",t.value=this.model.value,t.disabled=this.model.disabled,t.placeholder=this.model.placeholder,null!=this.model.max_length&&(t.maxLength=this.model.max_length),t.addEventListener(\"change\",(()=>this.change_input())),t.addEventListener(\"input\",(()=>this.change_input_value())),this.group_el.appendChild(t)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_value(){this.model.value_input=this.input_el.value,super.change_input()}}n.TextLikeInputView=h,h.__name__=\"TextLikeInputView\";class a extends s.InputWidget{constructor(e){super(e)}static init_TextLikeInput(){this.define((({Int:e,String:t,Nullable:n})=>({value:[t,\"\"],value_input:[t,\"\"],placeholder:[t,\"\"],max_length:[n(e),null]})))}}n.TextLikeInput=a,a.__name__=\"TextLikeInput\",a.init_TextLikeInput()},\n", " 426: function _(t,e,i,n,s){n();const l=t(1),o=t(420),r=t(43),_=l.__importStar(t(427)),p=_;class d extends o.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,(()=>{this.label_el.textContent=this.model.title}))}styles(){return[...super.styles(),_.default]}render(){super.render();const{title:t}=this.model;this.label_el=r.label({style:{display:0==t.length?\"none\":\"\"}},t),this.group_el=r.div({class:p.input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}i.InputWidgetView=d,d.__name__=\"InputWidgetView\";class u extends o.Control{constructor(t){super(t)}static init_InputWidget(){this.define((({String:t})=>({title:[t,\"\"]})))}}i.InputWidget=u,u.__name__=\"InputWidget\",u.init_InputWidget()},\n", " 427: function _(o,i,t,n,p){n(),t.root=\"bk-root\",t.input=\"bk-input\",t.input_group=\"bk-input-group\",t.inline=\"bk-inline\",t.spin_wrapper=\"bk-spin-wrapper\",t.spin_btn=\"bk-spin-btn\",t.spin_btn_up=\"bk-spin-btn-up\",t.spin_btn_down=\"bk-spin-btn-down\",t.default='.bk-root .bk-input{display:inline-block;width:100%;flex-grow:1;-webkit-flex-grow:1;min-height:31px;padding:0 12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;}.bk-root .bk-input:focus{border-color:#66afe9;outline:0;box-shadow:inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);}.bk-root .bk-input::placeholder,.bk-root .bk-input:-ms-input-placeholder,.bk-root .bk-input::-moz-placeholder,.bk-root .bk-input::-webkit-input-placeholder{color:#999;opacity:1;}.bk-root .bk-input[disabled]{cursor:not-allowed;background-color:#eee;opacity:1;}.bk-root select:not([multiple]).bk-input,.bk-root select:not([size]).bk-input{height:auto;appearance:none;-webkit-appearance:none;background-image:url(\\'data:image/svg+xml;utf8,\\');background-position:right 0.5em center;background-size:8px 6px;background-repeat:no-repeat;}.bk-root select[multiple].bk-input,.bk-root select[size].bk-input,.bk-root textarea.bk-input{height:auto;}.bk-root .bk-input-group{width:100%;height:100%;display:inline-flex;display:-webkit-inline-flex;flex-wrap:nowrap;-webkit-flex-wrap:nowrap;align-items:start;-webkit-align-items:start;flex-direction:column;-webkit-flex-direction:column;white-space:nowrap;}.bk-root .bk-input-group.bk-inline{flex-direction:row;-webkit-flex-direction:row;}.bk-root .bk-input-group.bk-inline > *:not(:first-child){margin-left:5px;}.bk-root .bk-input-group input[type=\"checkbox\"] + span,.bk-root .bk-input-group input[type=\"radio\"] + span{position:relative;top:-2px;margin-left:3px;}.bk-root .bk-input-group > .bk-spin-wrapper{display:inherit;width:inherit;height:inherit;position:relative;overflow:hidden;padding:0;vertical-align:middle;}.bk-root .bk-input-group > .bk-spin-wrapper input{padding-right:20px;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn{position:absolute;display:block;height:50%;min-height:0;min-width:0;width:30px;padding:0;margin:0;right:0;border:none;background:none;cursor:pointer;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before{content:\"\";display:inline-block;transform:translateY(-50%);border-left:5px solid transparent;border-right:5px solid transparent;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up{top:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before{border-bottom:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before{border-bottom-color:grey;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down{bottom:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before{border-top:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before{border-top-color:grey;}'},\n", " 428: function _(t,e,n,i,o){i();const s=t(419),u=t(264);class c extends s.AbstractButtonView{click(){this.model.trigger_event(new u.ButtonClick),super.click()}}n.ButtonView=c,c.__name__=\"ButtonView\";class _ extends s.AbstractButton{constructor(t){super(t)}static init_Button(){this.prototype.default_view=c,this.override({label:\"Button\"})}}n.Button=_,_.__name__=\"Button\",_.init_Button()},\n", " 429: function _(t,e,o,i,c){i();const n=t(1),s=t(430),a=t(43),u=n.__importStar(t(328));class r extends s.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach(((e,o)=>{a.classes(e).toggle(u.active,t.has(o))}))}}o.CheckboxButtonGroupView=r,r.__name__=\"CheckboxButtonGroupView\";class _ extends s.ButtonGroup{constructor(t){super(t)}static init_CheckboxButtonGroup(){this.prototype.default_view=r,this.define((({Int:t,Array:e})=>({active:[e(t),[]]})))}}o.CheckboxButtonGroup=_,_.__name__=\"CheckboxButtonGroup\",_.init_CheckboxButtonGroup()},\n", " 430: function _(t,e,n,s,i){s();const o=t(1),r=t(420),u=t(20),a=t(43),_=o.__importStar(t(328)),l=_;class c extends r.ControlView{*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,(()=>this.render())),this.on_change(t.labels,(()=>this.render())),this.on_change(t.active,(()=>this._update_active()))}styles(){return[...super.styles(),_.default]}render(){super.render(),this._buttons=this.model.labels.map(((t,e)=>{const n=a.div({class:[l.btn,l[`btn_${this.model.button_type}`]],disabled:this.model.disabled},t);return n.addEventListener(\"click\",(()=>this.change_active(e))),n})),this._update_active();const t=a.div({class:l.btn_group},this._buttons);this.el.appendChild(t)}}n.ButtonGroupView=c,c.__name__=\"ButtonGroupView\";class d extends r.Control{constructor(t){super(t)}static init_ButtonGroup(){this.define((({String:t,Array:e})=>({labels:[e(t),[]],button_type:[u.ButtonType,\"default\"]})))}}n.ButtonGroup=d,d.__name__=\"ButtonGroup\",d.init_ButtonGroup()},\n", " 431: function _(e,t,i,n,s){n();const o=e(1),c=e(432),a=e(43),l=e(9),d=o.__importStar(e(427));class h extends c.InputGroupView{render(){super.render();const e=a.div({class:[d.input_group,this.model.inline?d.inline:null]});this.el.appendChild(e);const{active:t,labels:i}=this.model;this._inputs=[];for(let n=0;nthis.change_active(n))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),l.includes(t,n)&&(s.checked=!0);const o=a.label({},s,a.span({},i[n]));e.appendChild(o)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}i.CheckboxGroupView=h,h.__name__=\"CheckboxGroupView\";class p extends c.InputGroup{constructor(e){super(e)}static init_CheckboxGroup(){this.prototype.default_view=h,this.define((({Boolean:e,Int:t,String:i,Array:n})=>({active:[n(t),[]],labels:[n(i),[]],inline:[e,!1]})))}}i.CheckboxGroup=p,p.__name__=\"CheckboxGroup\",p.init_CheckboxGroup()},\n", " 432: function _(n,t,e,s,o){s();const r=n(1),u=n(420),c=r.__importDefault(n(427));class _ extends u.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}styles(){return[...super.styles(),c.default]}}e.InputGroupView=_,_.__name__=\"InputGroupView\";class i extends u.Control{constructor(n){super(n)}}e.InputGroup=i,i.__name__=\"InputGroup\"},\n", " 433: function _(e,i,t,n,o){n();const s=e(1),l=e(426),r=e(43),c=e(22),a=s.__importStar(e(427));class d extends l.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.color.change,(()=>this.input_el.value=c.color2hexrgb(this.model.color))),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled))}render(){super.render(),this.input_el=r.input({type:\"color\",class:a.input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}t.ColorPickerView=d,d.__name__=\"ColorPickerView\";class h extends l.InputWidget{constructor(e){super(e)}static init_ColorPicker(){this.prototype.default_view=d,this.define((({Color:e})=>({color:[e,\"#000000\"]})))}}t.ColorPicker=h,h.__name__=\"ColorPicker\",h.init_ColorPicker()},\n", " 434: function _(e,t,i,n,s){n();const a=e(1),l=a.__importDefault(e(435)),o=e(426),d=e(43),r=e(20),c=e(8),h=a.__importStar(e(427)),u=a.__importDefault(e(436));function _(e){const t=[];for(const i of e)if(c.isString(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class p extends o.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.setDate(this.model.value)})),this.connect(t.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",this.model.min_date)})),this.connect(i.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",this.model.max_date)})),this.connect(n.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",this.model.disabled_dates)})),this.connect(s.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",this.model.enabled_dates)})),this.connect(a.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",this.model.position)})),this.connect(l.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",this.model.inline)}))}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),u.default]}render(){var e,t;null==this._picker&&(super.render(),this.input_el=d.input({type:\"text\",class:h.input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=l.default(this.input_el,{defaultDate:this.model.value,minDate:null!==(e=this.model.min_date)&&void 0!==e?e:void 0,maxDate:null!==(t=this.model.max_date)&&void 0!==t?t:void 0,inline:this.model.inline,position:this.model.position,disable:_(this.model.disabled_dates),enable:_(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=p,p.__name__=\"DatePickerView\";class m extends o.InputWidget{constructor(e){super(e)}static init_DatePicker(){this.prototype.default_view=p,this.define((({Boolean:e,String:t,Array:i,Tuple:n,Or:s,Nullable:a})=>{const l=i(s(t,n(t,t)));return{value:[t],min_date:[a(t),null],max_date:[a(t),null],disabled_dates:[l,[]],enabled_dates:[l,[]],position:[r.CalendarPosition,\"auto\"],inline:[e,!1]}}))}}i.DatePicker=m,m.__name__=\"DatePicker\",m.init_DatePicker()},\n", " 435: function _(e,n,t,a,i){\n", " /* flatpickr v4.6.6, @license MIT */var o,r;o=this,r=function(){\"use strict\";\n", " /*! *****************************************************************************\n", " Copyright (c) Microsoft Corporation.\n", " \n", " Permission to use, copy, modify, and/or distribute this software for any\n", " purpose with or without fee is hereby granted.\n", " \n", " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", " AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n", " INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n", " LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n", " OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n", " PERFORMANCE OF THIS SOFTWARE.\n", " ***************************************************************************** */var e=function(){return(e=Object.assign||function(e){for(var n,t=1,a=arguments.length;t\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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Date(parseFloat(n))},w:p,y:function(e,n){e.setFullYear(2e3+parseFloat(n))}},D={D:\"(\\\\w+)\",F:\"(\\\\w+)\",G:\"(\\\\d\\\\d|\\\\d)\",H:\"(\\\\d\\\\d|\\\\d)\",J:\"(\\\\d\\\\d|\\\\d)\\\\w+\",K:\"\",M:\"(\\\\w+)\",S:\"(\\\\d\\\\d|\\\\d)\",U:\"(.+)\",W:\"(\\\\d\\\\d|\\\\d)\",Y:\"(\\\\d{4})\",Z:\"(.+)\",d:\"(\\\\d\\\\d|\\\\d)\",h:\"(\\\\d\\\\d|\\\\d)\",i:\"(\\\\d\\\\d|\\\\d)\",j:\"(\\\\d\\\\d|\\\\d)\",l:\"(\\\\w+)\",m:\"(\\\\d\\\\d|\\\\d)\",n:\"(\\\\d\\\\d|\\\\d)\",s:\"(\\\\d\\\\d|\\\\d)\",u:\"(.+)\",w:\"(\\\\d\\\\d|\\\\d)\",y:\"(\\\\d{2})\"},w={Z:function(e){return e.toISOString()},D:function(e,n,t){return n.weekdays.shorthand[w.w(e,n,t)]},F:function(e,n,t){return h(w.n(e,n,t)-1,!1,n)},G:function(e,n,t){return o(w.h(e,n,t))},H:function(e){return o(e.getHours())},J:function(e,n){return void 0!==n.ordinal?e.getDate()+n.ordinal(e.getDate()):e.getDate()},K:function(e,n){return n.amPM[r(e.getHours()>11)]},M:function(e,n){return h(e.getMonth(),!0,n)},S:function(e){return 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n=g(e),t=V(n),a=n===w.input||n===w.altInput||w.element.contains(n)||e.path&&e.path.indexOf&&(~e.path.indexOf(w.input)||~e.path.indexOf(w.altInput)),i=\"blur\"===e.type?a&&e.relatedTarget&&!V(e.relatedTarget):!a&&!t&&!V(e.relatedTarget),o=!w.config.ignoredFocusElements.some((function(e){return e.contains(n)}));i&&o&&(void 0!==w.timeContainer&&void 0!==w.minuteElement&&void 0!==w.hourElement&&\"\"!==w.input.value&&void 0!==w.input.value&&T(),w.close(),w.config&&\"range\"===w.config.mode&&1===w.selectedDates.length&&(w.clear(!1),w.redraw()))}}function Q(e){if(!(!e||w.config.minDate&&ew.config.maxDate.getFullYear())){var n=e,t=w.currentYear!==n;w.currentYear=n||w.currentYear,w.config.maxDate&&w.currentYear===w.config.maxDate.getFullYear()?w.currentMonth=Math.min(w.config.maxDate.getMonth(),w.currentMonth):w.config.minDate&&w.currentYear===w.config.minDate.getFullYear()&&(w.currentMonth=Math.max(w.config.minDate.getMonth(),w.currentMonth)),t&&(w.redraw(),pe(\"onYearChange\"),K())}}function 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e.slice().map((function(e){return\"string\"==typeof e||\"number\"==typeof e||e instanceof Date?w.parseDate(e,void 0,!0):e&&\"object\"==typeof e&&e.from&&e.to?{from:w.parseDate(e.from,void 0),to:w.parseDate(e.to,void 0)}:e})).filter((function(e){return e}))}function pe(e,n){if(void 0!==w.config){var t=w.config[e];if(void 0!==t&&t.length>0)for(var a=0;t[a]&&a1||\"static\"===w.config.monthSelectorType?w.monthElements[n].textContent=h(t.getMonth(),w.config.shorthandCurrentMonth,w.l10n)+\" \":w.monthsDropdownContainer.value=t.getMonth().toString(),e.value=t.getFullYear().toString()})),w._hidePrevMonthArrow=void 0!==w.config.minDate&&(w.currentYear===w.config.minDate.getFullYear()?w.currentMonth<=w.config.minDate.getMonth():w.currentYearw.config.maxDate.getMonth():w.currentYear>w.config.maxDate.getFullYear()))}function we(e){return w.selectedDates.map((function(n){return w.formatDate(n,e)})).filter((function(e,n,t){return\"range\"!==w.config.mode||w.config.enableTime||t.indexOf(e)===n})).join(\"range\"!==w.config.mode?w.config.conjunction:w.l10n.rangeSeparator)}function be(e){void 0===e&&(e=!0),void 0!==w.mobileInput&&w.mobileFormatStr&&(w.mobileInput.value=void 0!==w.latestSelectedDateObj?w.formatDate(w.latestSelectedDateObj,w.mobileFormatStr):\"\"),w.input.value=we(w.config.dateFormat),void 0!==w.altInput&&(w.altInput.value=we(w.config.altFormat)),!1!==e&&pe(\"onValueUpdate\")}function Ce(e){var n=g(e),t=w.prevMonthNav.contains(n),a=w.nextMonthNav.contains(n);t||a?G(t?-1:1):w.yearElements.indexOf(n)>=0?n.select():n.classList.contains(\"arrowUp\")?w.changeYear(w.currentYear+1):n.classList.contains(\"arrowDown\")&&w.changeYear(w.currentYear-1)}return function(){w.element=w.input=p,w.isOpen=!1,function(){var n=[\"wrap\",\"weekNumbers\",\"allowInput\",\"allowInvalidPreload\",\"clickOpens\",\"time_24hr\",\"enableTime\",\"noCalendar\",\"altInput\",\"shorthandCurrentMonth\",\"inline\",\"static\",\"enableSeconds\",\"disableMobile\"],i=e(e({},JSON.parse(JSON.stringify(p.dataset||{}))),v),o={};w.config.parseDate=i.parseDate,w.config.formatDate=i.formatDate,Object.defineProperty(w.config,\"enable\",{get:function(){return w.config._enable},set:function(e){w.config._enable=ge(e)}}),Object.defineProperty(w.config,\"disable\",{get:function(){return w.config._disable},set:function(e){w.config._disable=ge(e)}});var r=\"time\"===i.mode;if(!i.dateFormat&&(i.enableTime||r)){var l=k.defaultConfig.dateFormat||a.dateFormat;o.dateFormat=i.noCalendar||r?\"H:i\"+(i.enableSeconds?\":S\":\"\"):l+\" H:i\"+(i.enableSeconds?\":S\":\"\")}if(i.altInput&&(i.enableTime||r)&&!i.altFormat){var d=k.defaultConfig.altFormat||a.altFormat;o.altFormat=i.noCalendar||r?\"h:i\"+(i.enableSeconds?\":S K\":\" K\"):d+\" h:i\"+(i.enableSeconds?\":S\":\"\")+\" K\"}Object.defineProperty(w.config,\"minDate\",{get:function(){return w.config._minDate},set:oe(\"min\")}),Object.defineProperty(w.config,\"maxDate\",{get:function(){return w.config._maxDate},set:oe(\"max\")});var s=function(e){return function(n){w.config[\"min\"===e?\"_minTime\":\"_maxTime\"]=w.parseDate(n,\"H:i:S\")}};Object.defineProperty(w.config,\"minTime\",{get:function(){return w.config._minTime},set:s(\"min\")}),Object.defineProperty(w.config,\"maxTime\",{get:function(){return w.config._maxTime},set:s(\"max\")}),\"time\"===i.mode&&(w.config.noCalendar=!0,w.config.enableTime=!0),Object.assign(w.config,o,i);for(var u=0;u-1?w.config[m]=c(f[m]).map(x).concat(w.config[m]):void 0===i[m]&&(w.config[m]=f[m])}i.altInputClass||(w.config.altInputClass=re().className+\" 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e=w.config.defaultDate||(\"INPUT\"!==w.input.nodeName&&\"TEXTAREA\"!==w.input.nodeName||!w.input.placeholder||w.input.value!==w.input.placeholder?w.input.value:null);e&&me(e,w.config.dateFormat),w._initialDate=w.selectedDates.length>0?w.selectedDates[0]:w.config.minDate&&w.config.minDate.getTime()>w.now.getTime()?w.config.minDate:w.config.maxDate&&w.config.maxDate.getTime()0&&(w.latestSelectedDateObj=w.selectedDates[0]),void 0!==w.config.minTime&&(w.config.minTime=w.parseDate(w.config.minTime,\"H:i\")),void 0!==w.config.maxTime&&(w.config.maxTime=w.parseDate(w.config.maxTime,\"H:i\")),w.minDateHasTime=!!w.config.minDate&&(w.config.minDate.getHours()>0||w.config.minDate.getMinutes()>0||w.config.minDate.getSeconds()>0),w.maxDateHasTime=!!w.config.maxDate&&(w.config.maxDate.getHours()>0||w.config.maxDate.getMinutes()>0||w.config.maxDate.getSeconds()>0)}(),w.utils={getDaysInMonth:function(e,n){return void 0===e&&(e=w.currentMonth),void 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w.__hideNextMonthArrow},set:function(e){w.__hideNextMonthArrow!==e&&(d(w.nextMonthNav,\"flatpickr-disabled\",e),w.__hideNextMonthArrow=e)}}),w.currentYearElement=w.yearElements[0],De(),w.monthNav)),w.innerContainer=s(\"div\",\"flatpickr-innerContainer\"),w.config.weekNumbers){var n=function(){w.calendarContainer.classList.add(\"hasWeeks\");var e=s(\"div\",\"flatpickr-weekwrapper\");e.appendChild(s(\"span\",\"flatpickr-weekday\",w.l10n.weekAbbreviation));var n=s(\"div\",\"flatpickr-weeks\");return e.appendChild(n),{weekWrapper:e,weekNumbers:n}}(),t=n.weekWrapper,a=n.weekNumbers;w.innerContainer.appendChild(t),w.weekNumbers=a,w.weekWrapper=t}w.rContainer=s(\"div\",\"flatpickr-rContainer\"),w.rContainer.appendChild($()),w.daysContainer||(w.daysContainer=s(\"div\",\"flatpickr-days\"),w.daysContainer.tabIndex=-1),J(),w.rContainer.appendChild(w.daysContainer),w.innerContainer.appendChild(w.rContainer),e.appendChild(w.innerContainer)}w.config.enableTime&&e.appendChild(function(){w.calendarContainer.classList.add(\"hasTime\"),w.config.noCalendar&&w.calendarContainer.classList.add(\"noCalendar\"),w.timeContainer=s(\"div\",\"flatpickr-time\"),w.timeContainer.tabIndex=-1;var e=s(\"span\",\"flatpickr-time-separator\",\":\"),n=m(\"flatpickr-hour\",{\"aria-label\":w.l10n.hourAriaLabel});w.hourElement=n.getElementsByTagName(\"input\")[0];var t=m(\"flatpickr-minute\",{\"aria-label\":w.l10n.minuteAriaLabel});if(w.minuteElement=t.getElementsByTagName(\"input\")[0],w.hourElement.tabIndex=w.minuteElement.tabIndex=-1,w.hourElement.value=o(w.latestSelectedDateObj?w.latestSelectedDateObj.getHours():w.config.time_24hr?w.config.defaultHour:function(e){switch(e%24){case 0:case 12:return 12;default:return 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C(t){if(function(t){return\"object\"==typeof t&&\"function\"==typeof t.to&&\"function\"==typeof t.from}(t))return!0;throw new Error(\"noUiSlider (14.6.3): 'format' requires 'to' and 'from' methods.\")}function P(t,e){if(!i(e))throw new Error(\"noUiSlider (14.6.3): 'step' is not numeric.\");t.singleStep=e}function N(t,e){if(!i(e))throw new Error(\"noUiSlider (14.6.3): 'keyboardPageMultiplier' is not numeric.\");t.keyboardPageMultiplier=e}function k(t,e){if(!i(e))throw new Error(\"noUiSlider (14.6.3): 'keyboardDefaultStep' is not numeric.\");t.keyboardDefaultStep=e}function U(t,e){if(\"object\"!=typeof e||Array.isArray(e))throw new Error(\"noUiSlider (14.6.3): 'range' is not an object.\");if(void 0===e.min||void 0===e.max)throw new Error(\"noUiSlider (14.6.3): Missing 'min' or 'max' in 'range'.\");if(e.min===e.max)throw new Error(\"noUiSlider (14.6.3): 'range' 'min' and 'max' cannot be equal.\");t.spectrum=new x(e,t.snap,t.singleStep)}function 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u(v=w,r.cssClasses.target),0===r.dir?u(v,r.cssClasses.ltr):u(v,r.cssClasses.rtl),0===r.ort?u(v,r.cssClasses.horizontal):u(v,r.cssClasses.vertical),u(v,\"rtl\"===getComputedStyle(v).direction?r.cssClasses.textDirectionRtl:r.cssClasses.textDirectionLtr),l=L(v,r.cssClasses.base),function(t,e){var n=L(e,r.cssClasses.connects);f=[],(d=[]).push(H(n,t[0]));for(var i=0;i=0&&t .noUi-tooltip{-webkit-transform:translate(50%, 0);transform:translate(50%, 0);left:auto;bottom:10px;}.bk-root .noUi-vertical .noUi-origin > .noUi-tooltip{-webkit-transform:translate(0, -18px);transform:translate(0, -18px);top:auto;right:28px;}.bk-root .noUi-handle{cursor:grab;cursor:-webkit-grab;}.bk-root .noUi-handle.noUi-active{cursor:grabbing;cursor:-webkit-grabbing;}.bk-root .noUi-handle:after,.bk-root .noUi-handle:before{display:none;}.bk-root .noUi-tooltip{display:none;white-space:nowrap;}.bk-root .noUi-handle:hover .noUi-tooltip{display:block;}.bk-root .noUi-horizontal{width:100%;height:10px;}.bk-root .noUi-vertical{width:10px;height:100%;}.bk-root .noUi-horizontal .noUi-handle{width:14px;height:18px;right:-7px;top:-5px;}.bk-root .noUi-vertical .noUi-handle{width:18px;height:14px;right:-5px;top:-7px;}.bk-root .noUi-target.noUi-horizontal{margin:5px 0px;}.bk-root .noUi-target.noUi-vertical{margin:0px 5px;}'},\n", " 442: function _(t,e,i,r,a){r();const s=t(1).__importDefault(t(181)),d=t(438),_=t(8);class n extends d.AbstractSliderView{}i.DateSliderView=n,n.__name__=\"DateSliderView\";class l extends d.AbstractSlider{constructor(t){super(t),this.behaviour=\"tap\",this.connected=[!0,!1]}static init_DateSlider(){this.prototype.default_view=n,this.override({format:\"%d %b %Y\"})}_formatter(t,e){return _.isString(e)?s.default(t,e):e.compute(t)}}i.DateSlider=l,l.__name__=\"DateSlider\",l.init_DateSlider()},\n", " 443: function _(e,t,i,n,s){n();const r=e(444);class _ extends r.MarkupView{render(){super.render(),this.model.render_as_text?this.markup_el.textContent=this.model.text:this.markup_el.innerHTML=this.model.text}}i.DivView=_,_.__name__=\"DivView\";class a extends r.Markup{constructor(e){super(e)}static init_Div(){this.prototype.default_view=_,this.define((({Boolean:e})=>({render_as_text:[e,!1]})))}}i.Div=a,a.__name__=\"Div\",a.init_Div()},\n", " 444: function _(t,e,s,i,a){i();const n=t(1),l=t(224),r=t(43),c=t(488),u=n.__importStar(t(445));class _ extends c.WidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>{this.layout.invalidate_cache(),this.render(),this.root.compute_layout()}))}styles(){return[...super.styles(),u.default]}_update_layout(){this.layout=new l.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render();const t=Object.assign(Object.assign({},this.model.style),{display:\"inline-block\"});this.markup_el=r.div({class:u.clearfix,style:t}),this.el.appendChild(this.markup_el)}}s.MarkupView=_,_.__name__=\"MarkupView\";class o extends c.Widget{constructor(t){super(t)}static init_Markup(){this.define((({String:t,Dict:e})=>({text:[t,\"\"],style:[e(t),{}]})))}}s.Markup=o,o.__name__=\"Markup\",o.init_Markup()},\n", " 445: function _(o,r,e,t,a){t(),e.root=\"bk-root\",e.clearfix=\"bk-clearfix\",e.default='.bk-root .bk-clearfix:before,.bk-root .bk-clearfix:after{content:\"\";display:table;}.bk-root .bk-clearfix:after{clear:both;}'},\n", " 446: function _(e,t,i,n,s){n();const o=e(1),r=e(419),l=e(264),d=e(43),_=e(8),u=o.__importStar(e(328)),c=o.__importStar(e(243)),h=c;class p extends r.AbstractButtonView{constructor(){super(...arguments),this._open=!1}styles(){return[...super.styles(),c.default]}render(){super.render();const e=d.div({class:[h.caret,h.down]});if(this.model.is_split){const t=this._render_button(e);t.classList.add(u.dropdown_toggle),t.addEventListener(\"click\",(()=>this._toggle_menu())),this.group_el.appendChild(t)}else this.button_el.appendChild(e);const t=this.model.menu.map(((e,t)=>{if(null==e)return d.div({class:h.divider});{const i=_.isString(e)?e:e[0],n=d.div({},i);return n.addEventListener(\"click\",(()=>this._item_click(t))),n}}));this.menu=d.div({class:[h.menu,h.below]},t),this.el.appendChild(this.menu),d.undisplay(this.menu)}_show_menu(){if(!this._open){this._open=!0,d.display(this.menu);const e=t=>{const{target:i}=t;i instanceof HTMLElement&&!this.el.contains(i)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,d.undisplay(this.menu))}_toggle_menu(){this._open?this._hide_menu():this._show_menu()}click(){this.model.is_split?(this._hide_menu(),this.model.trigger_event(new l.ButtonClick),super.click()):this._toggle_menu()}_item_click(e){this._hide_menu();const t=this.model.menu[e];if(null!=t){const i=_.isString(t)?t:t[1];_.isString(i)?this.model.trigger_event(new l.MenuItemClick(i)):i.execute(this.model,{index:e})}}}i.DropdownView=p,p.__name__=\"DropdownView\";class m extends r.AbstractButton{constructor(e){super(e)}static init_Dropdown(){this.prototype.default_view=p,this.define((({Null:e,Boolean:t,String:i,Array:n,Tuple:s,Or:o})=>({split:[t,!1],menu:[n(o(i,s(i,o(i)),e)),[]]}))),this.override({label:\"Dropdown\"})}get is_split(){return this.split}}i.Dropdown=m,m.__name__=\"Dropdown\",m.init_Dropdown()},\n", " 447: function _(e,i,l,t,s){t();const n=e(43),a=e(488);class o extends a.WidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}render(){const{multiple:e,accept:i,disabled:l,width:t}=this.model;null==this.dialog_el&&(this.dialog_el=n.input({type:\"file\",multiple:e}),this.dialog_el.onchange=()=>{const{files:e}=this.dialog_el;null!=e&&this.load_files(e)},this.el.appendChild(this.dialog_el)),null!=i&&\"\"!=i&&(this.dialog_el.accept=i),this.dialog_el.style.width=`${t}px`,this.dialog_el.disabled=l}async load_files(e){const i=[],l=[],t=[];for(const s of e){const e=await this._read_file(s),[,n=\"\",,a=\"\"]=e.split(/[:;,]/,4);i.push(a),l.push(s.name),t.push(n)}this.model.multiple?(this.model.value=i,this.model.filename=l,this.model.mime_type=t):(this.model.value=i[0],this.model.filename=l[0],this.model.mime_type=t[0])}_read_file(e){return new Promise(((i,l)=>{const t=new FileReader;t.onload=()=>{var s;const{result:n}=t;null!=n?i(n):l(null!==(s=t.error)&&void 0!==s?s:new Error(`unable to read '${e.name}'`))},t.readAsDataURL(e)}))}}l.FileInputView=o,o.__name__=\"FileInputView\";class d extends a.Widget{constructor(e){super(e)}static init_FileInput(){this.prototype.default_view=o,this.define((({Boolean:e,String:i,Array:l,Or:t})=>({value:[t(i,l(i)),\"\"],mime_type:[t(i,l(i)),\"\"],filename:[t(i,l(i)),\"\"],accept:[i,\"\"],multiple:[e,!1]})))}}l.FileInput=d,d.__name__=\"FileInput\",d.init_FileInput()},\n", " 448: function _(e,t,i,s,n){s();const l=e(1),o=e(43),r=e(8),c=e(426),h=l.__importStar(e(427));class p extends c.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.value.change,(()=>this.render_selection())),this.connect(this.model.properties.options.change,(()=>this.render())),this.connect(this.model.properties.name.change,(()=>this.render())),this.connect(this.model.properties.title.change,(()=>this.render())),this.connect(this.model.properties.size.change,(()=>this.render())),this.connect(this.model.properties.disabled.change,(()=>this.render()))}render(){super.render();const e=this.model.options.map((e=>{let t,i;return r.isString(e)?t=i=e:[t,i]=e,o.option({value:t},i)}));this.input_el=o.select({multiple:!0,class:h.input,name:this.model.name,disabled:this.model.disabled},e),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el),this.render_selection()}render_selection(){const e=new Set(this.model.value);for(const t of this.el.querySelectorAll(\"option\"))t.selected=e.has(t.value);this.input_el.size=this.model.size}change_input(){const e=null!=this.el.querySelector(\"select:focus\"),t=[];for(const e of this.el.querySelectorAll(\"option\"))e.selected&&t.push(e.value);this.model.value=t,super.change_input(),e&&this.input_el.focus()}}i.MultiSelectView=p,p.__name__=\"MultiSelectView\";class u extends c.InputWidget{constructor(e){super(e)}static init_MultiSelect(){this.prototype.default_view=p,this.define((({Int:e,String:t,Array:i,Tuple:s,Or:n})=>({value:[i(t),[]],options:[i(n(t,s(t,t))),[]],size:[e,4]})))}}i.MultiSelect=u,u.__name__=\"MultiSelect\",u.init_MultiSelect()},\n", " 449: function _(a,r,e,t,p){t();const s=a(444),i=a(43);class n extends s.MarkupView{render(){super.render();const a=i.p({style:{margin:0}},this.model.text);this.markup_el.appendChild(a)}}e.ParagraphView=n,n.__name__=\"ParagraphView\";class _ extends s.Markup{constructor(a){super(a)}static init_Paragraph(){this.prototype.default_view=n}}e.Paragraph=_,_.__name__=\"Paragraph\",_.init_Paragraph()},\n", " 450: function _(s,t,e,n,r){n();const p=s(424);class u extends p.TextInputView{render(){super.render(),this.input_el.type=\"password\"}}e.PasswordInputView=u,u.__name__=\"PasswordInputView\";class a extends p.TextInput{constructor(s){super(s)}static init_PasswordInput(){this.prototype.default_view=u}}e.PasswordInput=a,a.__name__=\"PasswordInput\",a.init_PasswordInput()},\n", " 451: function _(e,t,i,l,s){l();const o=e(1),n=o.__importDefault(e(452)),h=e(43),a=e(8),u=e(224),c=o.__importStar(e(427)),d=o.__importDefault(e(453)),_=e(426);class r extends _.InputWidgetView{constructor(){super(...arguments),this._last_height=null}connect_signals(){super.connect_signals(),this.connect(this.model.properties.disabled.change,(()=>this.set_disabled()));const{value:e,max_items:t,option_limit:i,delete_button:l,placeholder:s,options:o,name:n,title:h}=this.model.properties;this.on_change([e,t,i,l,s,o,n,h],(()=>this.render()))}styles(){return[...super.styles(),d.default]}_update_layout(){this.layout=new u.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render(),this.input_el=h.select({multiple:!0,class:c.input,name:this.model.name,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el);const e=new Set(this.model.value),t=this.model.options.map((t=>{let i,l;return a.isString(t)?i=l=t:[i,l]=t,{value:i,label:l,selected:e.has(i)}})),i=this.model.solid?\"solid\":\"light\",l=`choices__item ${i}`,s=`choices__button ${i}`,o={choices:t,duplicateItemsAllowed:!1,removeItemButton:this.model.delete_button,classNames:{item:l,button:s}};null!=this.model.placeholder&&(o.placeholderValue=this.model.placeholder),null!=this.model.max_items&&(o.maxItemCount=this.model.max_items),null!=this.model.option_limit&&(o.renderChoiceLimit=this.model.option_limit),this.choice_el=new n.default(this.input_el,o);const u=()=>this.choice_el.containerOuter.element.getBoundingClientRect().height;null!=this._last_height&&this._last_height!=u()&&this.root.invalidate_layout(),this._last_height=u(),this.input_el.addEventListener(\"change\",(()=>this.change_input()))}set_disabled(){this.model.disabled?this.choice_el.disable():this.choice_el.enable()}change_input(){const e=null!=this.el.querySelector(\"select:focus\"),t=[];for(const e of this.el.querySelectorAll(\"option\"))e.selected&&t.push(e.value);this.model.value=t,super.change_input(),e&&this.input_el.focus()}}i.MultiChoiceView=r,r.__name__=\"MultiChoiceView\";class m extends 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Apache Software License 2.0\n", " *\n", " * http://www.apache.org/licenses/LICENSE-2.0\n", " */\n", " e.exports=function(e){var t={};function i(n){if(t[n])return t[n].exports;var s=t[n]={i:n,l:!1,exports:{}};return e[n].call(s.exports,s,s.exports,i),s.l=!0,s.exports}return i.m=e,i.c=t,i.d=function(e,t,n){i.o(e,t)||Object.defineProperty(e,t,{enumerable:!0,get:n})},i.r=function(e){\"undefined\"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:\"Module\"}),Object.defineProperty(e,\"__esModule\",{value:!0})},i.t=function(e,t){if(1&t&&(e=i(e)),8&t)return e;if(4&t&&\"object\"==typeof e&&e&&e.__esModule)return e;var n=Object.create(null);if(i.r(n),Object.defineProperty(n,\"default\",{enumerable:!0,value:e}),2&t&&\"string\"!=typeof e)for(var s in e)i.d(n,s,function(t){return e[t]}.bind(null,s));return n},i.n=function(e){var t=e&&e.__esModule?function(){return e.default}:function(){return e};return i.d(t,\"a\",t),t},i.o=function(e,t){return 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i=e.split(this.options.tokenSeparator),n=0,s=i.length;n0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1?arguments[1]:void 0,i=this.list,n={},s=[];if(\"string\"==typeof i[0]){for(var r=0,o=i.length;r1)throw new Error(\"Key weight has to be > 0 and <= 1\");p=p.name}else a[p]={weight:1};this._analyze({key:p,value:this.options.getFn(h,p),record:h,index:c},{resultMap:n,results:s,tokenSearchers:e,fullSearcher:t})}return{weights:a,results:s}}},{key:\"_analyze\",value:function(e,t){var i=e.key,n=e.arrayIndex,s=void 0===n?-1:n,r=e.value,o=e.record,c=e.index,l=t.tokenSearchers,h=void 0===l?[]:l,u=t.fullSearcher,d=void 0===u?[]:u,p=t.resultMap,m=void 0===p?{}:p,f=t.results,v=void 0===f?[]:f;if(null!=r){var g=!1,_=-1,b=0;if(\"string\"==typeof r){this._log(\"\\nKey: \".concat(\"\"===i?\"-\":i));var y=d.search(r);if(this._log('Full text: \"'.concat(r,'\", score: ').concat(y.score)),this.options.tokenize){for(var E=r.split(this.options.tokenSeparator),I=[],S=0;S-1&&(P=(P+_)/2),this._log(\"Score average:\",P);var D=!this.options.tokenize||!this.options.matchAllTokens||b>=h.length;if(this._log(\"\\nCheck Matches: \".concat(D)),(g||y.isMatch)&&D){var M=m[c];M?M.output.push({key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}):(m[c]={item:o,output:[{key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}]},v.push(m[c]))}}else if(a(r))for(var N=0,F=r.length;N-1&&(o.arrayIndex=r.arrayIndex),t.matches.push(o)}}})),this.options.includeScore&&s.push((function(e,t){t.score=e.score}));for(var r=0,o=e.length;ri)return s(e,this.pattern,n);var o=this.options,a=o.location,c=o.distance,l=o.threshold,h=o.findAllMatches,u=o.minMatchCharLength;return r(e,this.pattern,this.patternAlphabet,{location:a,distance:c,threshold:l,findAllMatches:h,minMatchCharLength:u})}}])&&n(t.prototype,i),a&&n(t,a),e}();e.exports=a},function(e,t){var i=/[\\-\\[\\]\\/\\{\\}\\(\\)\\*\\+\\?\\.\\\\\\^\\$\\|]/g;e.exports=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:/ +/g,s=new RegExp(t.replace(i,\"\\\\$&\").replace(n,\"|\")),r=e.match(s),o=!!r,a=[];if(o)for(var c=0,l=r.length;c=P;N-=1){var F=N-1,j=i[e.charAt(F)];if(j&&(E[F]=1),M[N]=(M[N+1]<<1|1)&j,0!==T&&(M[N]|=(O[N+1]|O[N])<<1|1|O[N+1]),M[N]&L&&(C=n(t,{errors:T,currentLocation:F,expectedLocation:v,distance:l}))<=_){if(_=C,(b=F)<=v)break;P=Math.max(1,2*v-b)}}if(n(t,{errors:T+1,currentLocation:v,expectedLocation:v,distance:l})>_)break;O=M}return{isMatch:b>=0,score:0===C?.001:C,matchedIndices:s(E,f)}}},function(e,t){e.exports=function(e,t){var i=t.errors,n=void 0===i?0:i,s=t.currentLocation,r=void 0===s?0:s,o=t.expectedLocation,a=void 0===o?0:o,c=t.distance,l=void 0===c?100:c,h=n/e.length,u=Math.abs(a-r);return l?h+u/l:u?1:h}},function(e,t){e.exports=function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,i=[],n=-1,s=-1,r=0,o=e.length;r=t&&i.push([n,s]),n=-1)}return e[r-1]&&r-n>=t&&i.push([n,r-1]),i}},function(e,t){e.exports=function(e){for(var t={},i=e.length,n=0;n/g,\"&rt;\").replace(/-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!0),i})):e;case\"REMOVE_ITEM\":return t.choiceId>-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!1),i})):e;case\"FILTER_CHOICES\":return e.map((function(e){var i=e;return i.active=t.results.some((function(e){var t=e.item,n=e.score;return t.id===i.id&&(i.score=n,!0)})),i}));case\"ACTIVATE_CHOICES\":return e.map((function(e){var i=e;return i.active=t.active,i}));case\"CLEAR_CHOICES\":return v;default:return e}},general:_}),A=function(e,t){var i=e;if(\"CLEAR_ALL\"===t.type)i=void 0;else if(\"RESET_TO\"===t.type)return O(t.state);return C(i,t)};function L(e,t){for(var i=0;i\"'+I(e)+'\"'},maxItemText:function(e){return\"Only \"+e+\" values can be added\"},valueComparer:function(e,t){return e===t},fuseOptions:{includeScore:!0},callbackOnInit:null,callbackOnCreateTemplates:null,classNames:{containerOuter:\"choices\",containerInner:\"choices__inner\",input:\"choices__input\",inputCloned:\"choices__input--cloned\",list:\"choices__list\",listItems:\"choices__list--multiple\",listSingle:\"choices__list--single\",listDropdown:\"choices__list--dropdown\",item:\"choices__item\",itemSelectable:\"choices__item--selectable\",itemDisabled:\"choices__item--disabled\",itemChoice:\"choices__item--choice\",placeholder:\"choices__placeholder\",group:\"choices__group\",groupHeading:\"choices__heading\",button:\"choices__button\",activeState:\"is-active\",focusState:\"is-focused\",openState:\"is-open\",disabledState:\"is-disabled\",highlightedState:\"is-highlighted\",selectedState:\"is-selected\",flippedState:\"is-flipped\",loadingState:\"is-loading\",noResults:\"has-no-results\",noChoices:\"has-no-choices\"}},D=\"showDropdown\",M=\"hideDropdown\",N=\"change\",F=\"choice\",j=\"search\",K=\"addItem\",R=\"removeItem\",H=\"highlightItem\",B=\"highlightChoice\",V=\"ADD_CHOICE\",G=\"FILTER_CHOICES\",q=\"ACTIVATE_CHOICES\",U=\"CLEAR_CHOICES\",z=\"ADD_GROUP\",W=\"ADD_ITEM\",X=\"REMOVE_ITEM\",$=\"HIGHLIGHT_ITEM\",J=46,Y=8,Z=13,Q=65,ee=27,te=38,ie=40,ne=33,se=34,re=\"text\",oe=\"select-one\",ae=\"select-multiple\",ce=function(){function e(e){var t=e.element,i=e.type,n=e.classNames,s=e.position;this.element=t,this.classNames=n,this.type=i,this.position=s,this.isOpen=!1,this.isFlipped=!1,this.isFocussed=!1,this.isDisabled=!1,this.isLoading=!1,this._onFocus=this._onFocus.bind(this),this._onBlur=this._onBlur.bind(this)}var t=e.prototype;return t.addEventListeners=function(){this.element.addEventListener(\"focus\",this._onFocus),this.element.addEventListener(\"blur\",this._onBlur)},t.removeEventListeners=function(){this.element.removeEventListener(\"focus\",this._onFocus),this.element.removeEventListener(\"blur\",this._onBlur)},t.shouldFlip=function(e){if(\"number\"!=typeof e)return!1;var t=!1;return\"auto\"===this.position?t=!window.matchMedia(\"(min-height: \"+(e+1)+\"px)\").matches:\"top\"===this.position&&(t=!0),t},t.setActiveDescendant=function(e){this.element.setAttribute(\"aria-activedescendant\",e)},t.removeActiveDescendant=function(){this.element.removeAttribute(\"aria-activedescendant\")},t.open=function(e){this.element.classList.add(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"true\"),this.isOpen=!0,this.shouldFlip(e)&&(this.element.classList.add(this.classNames.flippedState),this.isFlipped=!0)},t.close=function(){this.element.classList.remove(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"false\"),this.removeActiveDescendant(),this.isOpen=!1,this.isFlipped&&(this.element.classList.remove(this.classNames.flippedState),this.isFlipped=!1)},t.focus=function(){this.isFocussed||this.element.focus()},t.addFocusState=function(){this.element.classList.add(this.classNames.focusState)},t.removeFocusState=function(){this.element.classList.remove(this.classNames.focusState)},t.enable=function(){this.element.classList.remove(this.classNames.disabledState),this.element.removeAttribute(\"aria-disabled\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"0\"),this.isDisabled=!1},t.disable=function(){this.element.classList.add(this.classNames.disabledState),this.element.setAttribute(\"aria-disabled\",\"true\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"-1\"),this.isDisabled=!0},t.wrap=function(e){!function(e,t){void 0===t&&(t=document.createElement(\"div\")),e.nextSibling?e.parentNode.insertBefore(t,e.nextSibling):e.parentNode.appendChild(t),t.appendChild(e)}(e,this.element)},t.unwrap=function(e){this.element.parentNode.insertBefore(e,this.element),this.element.parentNode.removeChild(this.element)},t.addLoadingState=function(){this.element.classList.add(this.classNames.loadingState),this.element.setAttribute(\"aria-busy\",\"true\"),this.isLoading=!0},t.removeLoadingState=function(){this.element.classList.remove(this.classNames.loadingState),this.element.removeAttribute(\"aria-busy\"),this.isLoading=!1},t._onFocus=function(){this.isFocussed=!0},t._onBlur=function(){this.isFocussed=!1},e}();function le(e,t){for(var i=0;i0?this.element.scrollTop+o-s:e.offsetTop;requestAnimationFrame((function(){i._animateScroll(a,t)}))}},t._scrollDown=function(e,t,i){var n=(i-e)/t,s=n>1?n:1;this.element.scrollTop=e+s},t._scrollUp=function(e,t,i){var n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function de(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},be=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ye=function(e,t){return{type:$,id:e,highlighted:t}},Ee=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},Ie=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function Se(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ye(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ye(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(be(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(be(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(be(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1,p=\"[data-choice-selectable]\";if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(p);else{var m=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=m?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(m,p,d):this.dropdown.element.querySelector(p)}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(we&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(Ee({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(Ee({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;r{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value})),this.connect(this.model.properties.low.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&d.assert(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&(this.model.value=Math.max(e,t))})),this.connect(this.model.properties.high.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&d.assert(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&(this.model.value=Math.min(e,l))})),this.connect(this.model.properties.high.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder))}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",(()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}}))}render(){super.render(),this.input_el=a.input({type:\"text\",class:p.input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.input_el.addEventListener(\"focusout\",(()=>this.input_el.value=this.format_value)),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter((e=>_.test(e))):\"float\"==this.model.mode&&this._set_input_filter((e=>m.test(e)))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!=this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=c,c.__name__=\"NumericInputView\";class v extends h.InputWidget{constructor(e){super(e)}static init_NumericInput(){this.prototype.default_view=c,this.define((({Number:e,String:t,Enum:l,Ref:i,Or:n,Nullable:s})=>({value:[s(e),null],placeholder:[t,\"\"],mode:[l(\"int\",\"float\"),\"int\"],format:[s(n(t,i(o.TickFormatter))),null],low:[s(e),null],high:[s(e),null]})))}_formatter(e,t){return r.isString(t)?u.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):`${e}`}}l.NumericInput=v,v.__name__=\"NumericInput\",v.init_NumericInput()},\n", " 455: function _(e,t,r,s,i){s();const n=e(444),_=e(43);class a extends n.MarkupView{render(){super.render();const e=_.pre({style:{overflow:\"auto\"}},this.model.text);this.markup_el.appendChild(e)}}r.PreTextView=a,a.__name__=\"PreTextView\";class o extends n.Markup{constructor(e){super(e)}static init_PreText(){this.prototype.default_view=a}}r.PreText=o,o.__name__=\"PreText\",o.init_PreText()},\n", " 456: function _(t,o,i,e,a){e();const n=t(1),u=t(430),s=t(43),c=n.__importStar(t(328));class _ extends u.ButtonGroupView{change_active(t){this.model.active!==t&&(this.model.active=t)}_update_active(){const{active:t}=this.model;this._buttons.forEach(((o,i)=>{s.classes(o).toggle(c.active,t===i)}))}}i.RadioButtonGroupView=_,_.__name__=\"RadioButtonGroupView\";class r extends u.ButtonGroup{constructor(t){super(t)}static init_RadioButtonGroup(){this.prototype.default_view=_,this.define((({Int:t,Nullable:o})=>({active:[o(t),null]})))}}i.RadioButtonGroup=r,r.__name__=\"RadioButtonGroup\",r.init_RadioButtonGroup()},\n", " 457: function _(e,i,t,n,a){n();const s=e(1),o=e(43),l=e(34),d=e(432),p=s.__importStar(e(427));class u extends d.InputGroupView{render(){super.render();const e=o.div({class:[p.input_group,this.model.inline?p.inline:null]});this.el.appendChild(e);const i=l.uniqueId(),{active:t,labels:n}=this.model;this._inputs=[];for(let a=0;athis.change_active(a))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),a==t&&(s.checked=!0);const l=o.label({},s,o.span({},n[a]));e.appendChild(l)}}change_active(e){this.model.active=e}}t.RadioGroupView=u,u.__name__=\"RadioGroupView\";class r extends d.InputGroup{constructor(e){super(e)}static init_RadioGroup(){this.prototype.default_view=u,this.define((({Boolean:e,Int:i,String:t,Array:n,Nullable:a})=>({active:[a(i),null],labels:[n(t),[]],inline:[e,!1]})))}}t.RadioGroup=r,r.__name__=\"RadioGroup\",r.init_RadioGroup()},\n", " 458: function _(e,t,i,r,a){r();const n=e(1).__importStar(e(183)),s=e(438),_=e(8);class d extends s.AbstractRangeSliderView{}i.RangeSliderView=d,d.__name__=\"RangeSliderView\";class o extends s.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}static init_RangeSlider(){this.prototype.default_view=d,this.override({format:\"0[.]00\"})}_formatter(e,t){return _.isString(t)?n.format(e,t):t.compute(e)}}i.RangeSlider=o,o.__name__=\"RangeSlider\",o.init_RangeSlider()},\n", " 459: function _(e,t,n,i,s){i();const l=e(1),u=e(43),a=e(8),o=e(13),_=e(426),p=l.__importStar(e(427));class r extends _.InputWidgetView{constructor(){super(...arguments),this._known_values=new Set}connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,(()=>{this._update_value()})),this.on_change(t,(()=>{u.empty(this.input_el),u.append(this.input_el,...this.options_el()),this._update_value()}))}options_el(){const{_known_values:e}=this;function t(t){return t.map((t=>{let n,i;return a.isString(t)?n=i=t:[n,i]=t,e.add(n),u.option({value:n},i)}))}e.clear();const{options:n}=this.model;return a.isArray(n)?t(n):o.entries(n).map((([e,n])=>u.optgroup({label:e},t(n))))}render(){super.render(),this.input_el=u.select({class:p.input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;this._known_values.has(e)?this.input_el.value=e:this.input_el.removeAttribute(\"value\")}}n.SelectView=r,r.__name__=\"SelectView\";class c extends _.InputWidget{constructor(e){super(e)}static init_Select(){this.prototype.default_view=r,this.define((({String:e,Array:t,Tuple:n,Dict:i,Or:s})=>{const l=t(s(e,n(e,e)));return{value:[e,\"\"],options:[s(l,i(l)),[]]}}))}}n.Select=c,c.__name__=\"Select\",c.init_Select()},\n", " 460: function _(t,e,i,r,s){r();const _=t(1).__importStar(t(183)),a=t(438),n=t(8);class o extends a.AbstractSliderView{}i.SliderView=o,o.__name__=\"SliderView\";class d extends a.AbstractSlider{constructor(t){super(t),this.behaviour=\"tap\",this.connected=[!0,!1]}static init_Slider(){this.prototype.default_view=o,this.override({format:\"0[.]00\"})}_formatter(t,e){return n.isString(e)?_.format(t,e):e.compute(t)}}i.Slider=d,d.__name__=\"Slider\",d.init_Slider()},\n", " 461: function _(e,t,i,n,s){n();const l=e(454),o=e(43),{min:r,max:a,floor:h,abs:_}=Math;function u(e){return h(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class d extends l.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._handles={interval:void 0,timeout:void 0},this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,(()=>{for(const e of this.buttons())o.toggle_attribute(e,\"disabled\",this.model.disabled)}))}render(){super.render(),this.wrapper_el=o.div({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=o.button({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=o.button({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())o.toggle_attribute(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",(e=>this._btn_mouse_down(e))),e.addEventListener(\"mouseup\",(()=>this._btn_mouse_up())),e.addEventListener(\"mouseleave\",(()=>this._btn_mouse_leave()));this.input_el.addEventListener(\"keydown\",(e=>this._input_key_down(e))),this.input_el.addEventListener(\"keyup\",(()=>this.model.value_throttled=this.model.value)),this.input_el.addEventListener(\"wheel\",(e=>this._input_mouse_wheel(e))),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,o=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),o&&e.apply(l,s)}}((()=>{this.model.value_throttled=this.model.value}),this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model,n=u;return a(n(_(null!=e?e:0)),n(_(null!=t?t:0)),n(_(i)))}remove(){this._stop_incrementation(),super.remove()}_start_incrementation(e){clearInterval(this._handles.interval),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(e)),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(2*e)),this._interval/10))}this.increment(e)};this._handles.interval=setInterval((()=>i(e*t)),this._interval)}_stop_incrementation(){clearTimeout(this._handles.timeout),this._handles.timeout=void 0,clearInterval(this._handles.interval),this._handles.interval=void 0,this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._handles.timeout=setTimeout((()=>this._start_incrementation(t)),this._interval)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case o.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case o.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case o.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case o.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?r(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?a(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=d,d.__name__=\"SpinnerView\";class p extends l.NumericInput{constructor(e){super(e)}static init_Spinner(){this.prototype.default_view=d,this.define((({Number:e,Nullable:t})=>({value_throttled:[t(e),null],step:[e,1],page_step_multiplier:[e,10],wheel_wait:[e,100]}))),this.override({mode:\"float\"})}}i.Spinner=p,p.__name__=\"Spinner\",p.init_Spinner()},\n", " 462: function _(e,t,s,n,i){n();const r=e(1),o=e(425),p=e(43),c=r.__importStar(e(427));class l extends o.TextLikeInputView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.rows.change,(()=>this.input_el.rows=this.model.rows)),this.connect(this.model.properties.cols.change,(()=>this.input_el.cols=this.model.cols))}_render_input(){this.input_el=p.textarea({class:c.input})}render(){super.render(),this.input_el.cols=this.model.cols,this.input_el.rows=this.model.rows}}s.TextAreaInputView=l,l.__name__=\"TextAreaInputView\";class _ extends o.TextLikeInput{constructor(e){super(e)}static init_TextAreaInput(){this.prototype.default_view=l,this.define((({Int:e})=>({cols:[e,20],rows:[e,2]}))),this.override({max_length:500})}}s.TextAreaInput=_,_.__name__=\"TextAreaInput\",_.init_TextAreaInput()},\n", " 463: function _(e,t,i,s,c){s();const o=e(1),a=e(419),n=e(43),l=o.__importStar(e(328));class _ extends a.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._update_active()))}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){n.classes(this.button_el).toggle(l.active,this.model.active)}}i.ToggleView=_,_.__name__=\"ToggleView\";class g extends a.AbstractButton{constructor(e){super(e)}static init_Toggle(){this.prototype.default_view=_,this.define((({Boolean:e})=>({active:[e,!1]}))),this.override({label:\"Toggle\"})}}i.Toggle=g,g.__name__=\"Toggle\",g.init_Toggle()},\n", " }, 417, {\"models/widgets/main\":417,\"models/widgets/index\":418,\"models/widgets/abstract_button\":419,\"models/widgets/control\":420,\"models/widgets/widget\":488,\"models/widgets/abstract_icon\":422,\"models/widgets/autocomplete_input\":423,\"models/widgets/text_input\":424,\"models/widgets/text_like_input\":425,\"models/widgets/input_widget\":426,\"styles/widgets/inputs.css\":427,\"models/widgets/button\":428,\"models/widgets/checkbox_button_group\":429,\"models/widgets/button_group\":430,\"models/widgets/checkbox_group\":431,\"models/widgets/input_group\":432,\"models/widgets/color_picker\":433,\"models/widgets/date_picker\":434,\"styles/widgets/flatpickr.css\":436,\"models/widgets/date_range_slider\":437,\"models/widgets/abstract_slider\":438,\"styles/widgets/sliders.css\":440,\"styles/widgets/nouislider.css\":441,\"models/widgets/date_slider\":442,\"models/widgets/div\":443,\"models/widgets/markup\":444,\"styles/clearfix.css\":445,\"models/widgets/dropdown\":446,\"models/widgets/file_input\":447,\"models/widgets/multiselect\":448,\"models/widgets/paragraph\":449,\"models/widgets/password_input\":450,\"models/widgets/multichoice\":451,\"styles/widgets/choices.css\":453,\"models/widgets/numeric_input\":454,\"models/widgets/pretext\":455,\"models/widgets/radio_button_group\":456,\"models/widgets/radio_group\":457,\"models/widgets/range_slider\":458,\"models/widgets/selectbox\":459,\"models/widgets/slider\":460,\"models/widgets/spinner\":461,\"models/widgets/textarea_input\":462,\"models/widgets/toggle\":463}, {});});\n", "\n", " /* END bokeh-widgets.min.js */\n", " },\n", " \n", " function(Bokeh) {\n", " /* BEGIN bokeh-tables.min.js */\n", " /*!\n", " * Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors\n", " * All rights reserved.\n", " * \n", " * Redistribution and use in source and binary forms, with or without modification,\n", " * are permitted provided that the following conditions are met:\n", " * \n", " * Redistributions of source code must retain the above copyright notice,\n", " * this list of conditions and the following disclaimer.\n", " * \n", " * Redistributions in binary form must reproduce the above copyright notice,\n", " * this list of conditions and the following disclaimer in the documentation\n", " * and/or other materials provided with the distribution.\n", " * \n", " * Neither the name of Anaconda nor the names of any contributors\n", " * may be used to endorse or promote products derived from this software\n", " * without specific prior written permission.\n", " * \n", " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", " * THE POSSIBILITY OF SUCH DAMAGE.\n", " */\n", " (function(root, factory) {\n", " factory(root[\"Bokeh\"], \"2.3.3\");\n", " })(this, function(Bokeh, version) {\n", " var define;\n", " return (function(modules, entry, aliases, externals) {\n", " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", " if (bokeh != null) {\n", " return bokeh.register_plugin(modules, entry, aliases);\n", " } else {\n", " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", " }\n", " })\n", " ({\n", " 464: function _(t,e,o,r,s){r();const _=t(1).__importStar(t(465));o.Tables=_;t(7).register_models(_)},\n", " 465: function _(g,a,r,e,t){e();const o=g(1);o.__exportStar(g(466),r),o.__exportStar(g(469),r),t(\"DataTable\",g(472).DataTable),t(\"TableColumn\",g(490).TableColumn),t(\"TableWidget\",g(489).TableWidget);var n=g(492);t(\"AvgAggregator\",n.AvgAggregator),t(\"MinAggregator\",n.MinAggregator),t(\"MaxAggregator\",n.MaxAggregator),t(\"SumAggregator\",n.SumAggregator);var A=g(493);t(\"GroupingInfo\",A.GroupingInfo),t(\"DataCube\",A.DataCube)},\n", " 466: function _(e,t,i,s,r){s();const a=e(1),n=e(43),l=e(240),u=e(53),d=e(467),o=a.__importStar(e(468));class _ extends l.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(o.cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",(e=>{switch(e.keyCode){case n.Keys.Left:case n.Keys.Right:case n.Keys.Up:case n.Keys.Down:case n.Keys.PageUp:case n.Keys.PageDown:e.stopImmediatePropagation()}}))}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[d.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=_,_.__name__=\"CellEditorView\";class c extends u.Model{}i.CellEditor=c,c.__name__=\"CellEditor\";class p extends _{get emptyValue(){return\"\"}_createInput(){return n.input({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=p,p.__name__=\"StringEditorView\";class h extends c{static init_StringEditor(){this.prototype.default_view=p,this.define((({String:e,Array:t})=>({completions:[t(e),[]]})))}}i.StringEditor=h,h.__name__=\"StringEditor\",h.init_StringEditor();class E extends _{_createInput(){return n.textarea()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=E,E.__name__=\"TextEditorView\";class V extends c{static init_TextEditor(){this.prototype.default_view=E}}i.TextEditor=V,V.__name__=\"TextEditor\",V.init_TextEditor();class m extends _{_createInput(){return n.select()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild(n.option({value:e},e));this.focus()}}i.SelectEditorView=m,m.__name__=\"SelectEditorView\";class f extends c{static init_SelectEditor(){this.prototype.default_view=m,this.define((({String:e,Array:t})=>({options:[t(e),[]]})))}}i.SelectEditor=f,f.__name__=\"SelectEditor\",f.init_SelectEditor();class x extends _{_createInput(){return n.input({type:\"text\"})}}i.PercentEditorView=x,x.__name__=\"PercentEditorView\";class g extends c{static init_PercentEditor(){this.prototype.default_view=x}}i.PercentEditor=g,g.__name__=\"PercentEditor\",g.init_PercentEditor();class w extends _{_createInput(){return n.input({type:\"checkbox\"})}renderEditor(){this.focus()}loadValue(e){this.defaultValue=!!e[this.args.column.field],this.inputEl.checked=this.defaultValue}serializeValue(){return this.inputEl.checked}}i.CheckboxEditorView=w,w.__name__=\"CheckboxEditorView\";class v extends c{static init_CheckboxEditor(){this.prototype.default_view=w}}i.CheckboxEditor=v,v.__name__=\"CheckboxEditor\",v.init_CheckboxEditor();class y extends _{_createInput(){return n.input({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseInt(this.getValue(),10))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid integer\"}:super.validateValue(e)}}i.IntEditorView=y,y.__name__=\"IntEditorView\";class I extends c{static init_IntEditor(){this.prototype.default_view=y,this.define((({Int:e})=>({step:[e,1]})))}}i.IntEditor=I,I.__name__=\"IntEditor\",I.init_IntEditor();class b extends _{_createInput(){return n.input({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseFloat(this.getValue()))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid number\"}:super.validateValue(e)}}i.NumberEditorView=b,b.__name__=\"NumberEditorView\";class N extends c{static init_NumberEditor(){this.prototype.default_view=b,this.define((({Number:e})=>({step:[e,.01]})))}}i.NumberEditor=N,N.__name__=\"NumberEditor\",N.init_NumberEditor();class S extends _{_createInput(){return n.input({type:\"text\"})}}i.TimeEditorView=S,S.__name__=\"TimeEditorView\";class C extends c{static init_TimeEditor(){this.prototype.default_view=S}}i.TimeEditor=C,C.__name__=\"TimeEditor\",C.init_TimeEditor();class D extends _{_createInput(){return n.input({type:\"text\"})}get emptyValue(){return new Date}renderEditor(){this.inputEl.focus(),this.inputEl.select()}destroy(){super.destroy()}show(){super.show()}hide(){super.hide()}position(){return super.position()}getValue(){}setValue(e){}}i.DateEditorView=D,D.__name__=\"DateEditorView\";class T extends c{static init_DateEditor(){this.prototype.default_view=D}}i.DateEditor=T,T.__name__=\"DateEditor\",T.init_DateEditor()},\n", " 467: function _(_,n,i,t,d){t(),i.DTINDEX_NAME=\"__bkdt_internal_index__\"},\n", " 468: function _(e,l,o,t,r){t(),o.root=\"bk-root\",o.data_table=\"bk-data-table\",o.cell_special_defaults=\"bk-cell-special-defaults\",o.cell_select=\"bk-cell-select\",o.cell_index=\"bk-cell-index\",o.header_index=\"bk-header-index\",o.cell_editor=\"bk-cell-editor\",o.cell_editor_completion=\"bk-cell-editor-completion\",o.default='.bk-root .bk-data-table{box-sizing:content-box;font-size:11px;}.bk-root .bk-data-table input[type=\"checkbox\"]{margin-left:4px;margin-right:4px;}.bk-root .bk-cell-special-defaults{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .bk-cell-select{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .slick-cell.bk-cell-index{border-right-color:silver;border-right-style:solid;background:#f5f5f5;text-align:right;background:#f0f0f0;color:#909090;}.bk-root .bk-header-index .slick-column-name{float:right;}.bk-root .slick-row.selected .bk-cell-index{background-color:transparent;}.bk-root .slick-row.odd{background:#f0f0f0;}.bk-root .slick-cell{padding-left:4px;padding-right:4px;border-right-color:transparent;border:0.25px solid transparent;}.bk-root .slick-cell .bk{line-height:inherit;}.bk-root .slick-cell.active{border-style:dashed;}.bk-root .slick-cell.selected{background-color:#F0F8FF;}.bk-root .slick-cell.editable{padding-left:0;padding-right:0;}.bk-root .bk-cell-editor{display:contents;}.bk-root .bk-cell-editor input,.bk-root .bk-cell-editor select{width:100%;height:100%;border:0;margin:0;padding:0;outline:0;background:transparent;vertical-align:baseline;}.bk-root .bk-cell-editor input{padding-left:4px;padding-right:4px;}.bk-root .bk-cell-editor-completion{font-size:11px;}'},\n", " 469: function _(t,e,r,a,n){a();const i=t(1),o=i.__importDefault(t(181)),s=i.__importStar(t(183)),l=t(470),c=t(43),m=t(20),u=t(8),_=t(34),F=t(22),d=t(53);class f extends d.Model{constructor(t){super(t)}doFormat(t,e,r,a,n){return null==r?\"\":(r+\"\").replace(/&/g,\"&\").replace(//g,\">\")}}r.CellFormatter=f,f.__name__=\"CellFormatter\";class h extends f{constructor(t){super(t)}static init_StringFormatter(){this.define((({Color:t,Nullable:e})=>({font_style:[m.FontStyle,\"normal\"],text_align:[m.TextAlign,\"left\"],text_color:[e(t),null]})))}doFormat(t,e,r,a,n){const{font_style:i,text_align:o,text_color:s}=this,l=c.div({},null==r?\"\":`${r}`);switch(i){case\"bold\":l.style.fontWeight=\"bold\";break;case\"italic\":l.style.fontStyle=\"italic\"}return null!=o&&(l.style.textAlign=o),null!=s&&(l.style.color=F.color2css(s)),l.outerHTML}}r.StringFormatter=h,h.__name__=\"StringFormatter\",h.init_StringFormatter();class g extends h{constructor(t){super(t)}static init_ScientificFormatter(){this.define((({Number:t,String:e,Nullable:r})=>({nan_format:[r(e),null],precision:[t,10],power_limit_high:[t,5],power_limit_low:[t,-3]})))}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 10**this.power_limit_high}doFormat(t,e,r,a,n){const i=Math.abs(r)<=this.scientific_limit_low||Math.abs(r)>=this.scientific_limit_high;let o=this.precision;return o<1&&(o=1),r=null!=r&&!isNaN(r)||null==this.nan_format?0==r?_.to_fixed(r,1):i?r.toExponential(o):_.to_fixed(r,o):this.nan_format,super.doFormat(t,e,r,a,n)}}r.ScientificFormatter=g,g.__name__=\"ScientificFormatter\",g.init_ScientificFormatter();class p extends h{constructor(t){super(t)}static init_NumberFormatter(){this.define((({String:t,Nullable:e})=>({format:[t,\"0,0\"],language:[t,\"en\"],rounding:[m.RoundingFunction,\"round\"],nan_format:[e(t),null]})))}doFormat(t,e,r,a,n){const{format:i,language:o,nan_format:l}=this,c=(()=>{switch(this.rounding){case\"round\":case\"nearest\":return Math.round;case\"floor\":case\"rounddown\":return Math.floor;case\"ceil\":case\"roundup\":return Math.ceil}})();return 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function(){n&&(n=r=s.onload=s.onerror=s.onabort=s.ontimeout=s.onreadystatechange=null,\"abort\"===e?s.abort():\"error\"===e?\"number\"!=typeof s.status?o(0,\"error\"):o(s.status,s.statusText):o(_t[s.status]||s.status,s.statusText,\"text\"!==(s.responseType||\"text\")||\"string\"!=typeof s.responseText?{binary:s.response}:{text:s.responseText},s.getAllResponseHeaders()))}},s.onload=n(),r=s.onerror=s.ontimeout=n(\"error\"),void 0!==s.onabort?s.onabort=r:s.onreadystatechange=function(){4===s.readyState&&e.setTimeout((function(){n&&r()}))},n=n(\"abort\");try{s.send(t.hasContent&&t.data||null)}catch(e){if(n)throw e}},abort:function(){n&&n()}}})),w.ajaxPrefilter((function(e){e.crossDomain&&(e.contents.script=!1)})),w.ajaxSetup({accepts:{script:\"text/javascript, application/javascript, application/ecmascript, application/x-ecmascript\"},contents:{script:/\\b(?:java|ecma)script\\b/},converters:{\"text script\":function(e){return w.globalEval(e),e}}}),w.ajaxPrefilter(\"script\",(function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type=\"GET\")})),w.ajaxTransport(\"script\",(function(e){var t,n;if(e.crossDomain||e.scriptAttrs)return{send:function(r,i){t=w(\"" ], "text/plain": [ ":Scatter [Droplet Diameter (um)] (Spindle Length (um))" ] }, "execution_count": 3, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "1003" } }, "output_type": "execute_result" } ], "source": [ "# Load in Data Frame\n", "df = pd.read_csv(os.path.join(data_path, \"good_invitro_droplet_data.csv\"), comment=\"#\")\n", "\n", "hv.Scatter(\n", " data=df,\n", " kdims='Droplet Diameter (um)',\n", " vdims='Spindle Length (um)',\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We have already built generative models for this in [our lesson on brute force plotting of posteriors](../02/plotting_posteriors.ipynb) and [our lesson on regression using MCMC](../11/regression_with_stan.ipynb). We have been working with two models, the *independent size model* in which the length of the spindle is independent of the droplet diameter and the *conserved tubulin model* in which the spindle length $l$ is dependent on the total amount of tubulin present in the droplet.\n", " \n", "We will build generative models for each, starting with the independent size model. We will use prior predictive checks to hone in on the priors.\n", "\n", "In order to do the prior predictive checks, we will assume we will measure 1000 spindle lengths in drops with diameters ranging from about 25 µm to 250 µm in diameter. Though we do have a data set available (which as 670 measurements concentrated between droplet diameters of 25 and 75 µm), we will assume we can make droplets uniformly throughout that range. We will therefore take our droplet diameters to range from 25 to 250 µm uniformly." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Number of measurements\n", "N = 1000\n", "\n", "# Droplet diameters\n", "d = np.linspace(25, 250, N)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model 1: Spindle size is independent of droplet size\n", "\n", "As a first model, we propose that the size of a mitotic spindle is inherent to the spindle itself. This means that the size of the spindle is independent of the size of the droplet or cell in which it resides. This would be the case, for example, if construction of the spindle involves length-sensing molecules, such as depolymerizing motor proteins. We define that set length as $\\phi$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The likelihood\n", "\n", "Not all spindles will be measured to be exactly $\\phi$ µm in length. Rather, there may be some variation about $\\phi$ due to natural variation and measurement error. So, we would expect measured length of spindle $i$ to be\n", "\n", "\\begin{align}\n", "l_i = \\phi + e_i,\n", "\\end{align}\n", "\n", "where $e_i$ is the stochastic component of the $i$th datum. Modeling this stochasticity with a Normal distribution and assuming the measurements are i.i.d. leads to the likelihood\n", "\n", "\\begin{align}\n", "l_i \\mid \\phi, \\sigma \\sim \\text{Norm}(\\phi, \\sigma) \\;\\;\\forall i.\n", "\\end{align}\n", "\n", "Note that in writing this generative model, we have necessarily introduced another parameter, $\\sigma$, the standard deviation parametrizing the Normal distribution. So, we have two parameters in our model, $\\phi$ and $\\sigma$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The prior\n", "\n", "With our likelihood specified, we need to give a prior for $\\phi$ and $\\sigma$, $g(\\phi, \\sigma)$. We will assume that $\\phi$ and $\\sigma$ are independent; that is, $g(\\phi, \\sigma) = g(\\phi)\\,g(\\sigma)$. So, we need to specify separate priors for $\\phi$ and $\\sigma$.\n", "\n", "Let's start with $\\phi$. We ask, \"How big are spindles?\" and perform an order-of-magnitude estimate to establish the prior. I think a mitotic spindle should be somewhere around 20 µm. Certainly no smaller than 1 µm, and probably not bigger than 100 µm, which is the on the large end of a typical size of a eukaryotic cell. (I know it sounds strange to say typical size of a eukaryotic cell, since they come in some many varieties, but 30 µm seems like a good upper limit to me.) I'm pretty uncertain, though, so I should not assign a sharp distribution. So, a broad distribution centered at $\\phi = 20$ µm will suffice.\n", "\n", "\\begin{align}\n", "\\phi \\sim \\text{Norm}(20, 20).\n", "\\end{align}\n", "\n", "Next, let's try $\\sigma$. How much do we expect the spindle length to vary? I would think that 20% variation seems reasonable, but it could be more or less. So, I will again choose a broad distribution centered at $\\sigma = 4$ µm.\n", "\n", "\\begin{align}\n", "\\sigma \\sim \\text{Norm}(4, 5).\n", "\\end{align}\n", "\n", "So, we now have a complete model; the likelihood and prior, and therefore the joint distribution, are specified. Here it is (all units are µm):\n", "\n", "\\begin{align}\n", "&\\phi \\sim \\text{Norm}(20, 20), \\\\[1em]\n", "&\\sigma \\sim \\text{Norm}(4, 5), \\\\[1em]\n", "&l_i \\sim \\text{Norm}(\\phi, \\sigma) \\;\\;\\forall i.\n", "\\end{align}\n", "\n", "The measurements of the droplet diameters $d_i$ are irrelevant under this model.\n", "\n", "If we look at the model with a critical eye, we can immediately see that it has a problem. It is possible that parameters $\\phi$ and $\\sigma$ could be nonpositive, as could the length, $l_i$. This is impossible in the case of $\\sigma$ and unphysical in the cases of $\\phi$ and $l_i$. So, these really should be truncated distributions.\n", "\n", "That said, **it is generally a bad idea to truncate distributions** (except and points where their derivatives vanish, like for the Half Normal distribution) when building models. It's both unrealistic and results in more difficult posterior sampling, which ultimately is what we need to do when doing statistical inference.\n", "\n", "We will therefore jettison this model and develop a model that is closer to being physically reasonable. We will keep the same likelihood, since its tails should decay away fast enough to prevent negative values of $l_i$. We instead focus on the prior." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The prior, take 2\n", "\n", "Let's start with $\\sigma$. It is possible that the spindle size is very carefully controlled. It is also possible that it could be highly variable. So, we can choose a Half Normal prior for $\\sigma$ with a large scale parameter. It looks something like this." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
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\n", "" ], "text/plain": [ ":Curve [σ [µm]] (g(σ) [1/µm])" ] }, "execution_count": 5, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "1125" } }, "output_type": "execute_result" } ], "source": [ "sigma = np.linspace(0, 40, 200)\n", "hv.Curve(\n", " (sigma, st.halfnorm.pdf(sigma, 0, 10)),\n", " kdims='σ [µm]',\n", " vdims='g(σ) [1/µm]'\n", ").opts(\n", " xlim=(0, 40)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For $\\phi$, we can instead take a Log-Normal distribution, with a median of 20 µm. The Log-Normal distribution is strictly positive and is useful for modeling parameters where we only have order-of-magnitude estimates. It looks like this." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
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\n", "" ], "text/plain": [ ":Curve [ϕ [µm]] (g(ϕ) [1/µm])" ] }, "execution_count": 6, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "1247" } }, "output_type": "execute_result" } ], "source": [ "phi = np.linspace(0, 80, 200)\n", "hv.Curve(\n", " (phi, st.lognorm.pdf(phi, 0.75, loc=0, scale=20)),\n", " kdims='ϕ [µm]',\n", " vdims='g(ϕ) [1/µm]'\n", ").opts(\n", " xlim=(0, 80)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, we have an updated model.\n", "\n", "\\begin{align}\n", "&\\phi \\sim \\text{LogNorm}(\\ln 20, 0.75),\\\\[1em]\n", "&\\sigma \\sim \\text{HalfNorm}(0, 10),\\\\[1em]\n", "&l_i \\sim \\text{Norm}(\\phi, \\sigma) \\;\\forall i.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Prior predictive checks\n", "\n", "Let us now generate samples out of this generative model. This procedure is known as **prior predictive checking**. We first generate parameter values drawing out of the prior distributions for $\\phi$ and $\\sigma$. We then use those parameter values to generate a data set using the likelihood. We repeat this over and over again to see what kind of data sets we might expect out of our generative model. Each of these generated data sets is called a **prior predictive sample**. We can do this efficiently using Numpy's random number generators." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "n_ppc_samples = 1000\n", "\n", "# Draw parameters out of the prior\n", "phi = np.random.lognormal(np.log(20), 0.75, size=n_ppc_samples)\n", "sigma = np.abs(np.random.normal(0, 10, size=n_ppc_samples))\n", "\n", "# Draw data sets out of the likelihood for each set of prior params\n", "ell = np.array([np.random.normal(ph, sig, size=N) for ph, sig in zip(phi, sigma)])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are many ways we could visualize the results. One informative plot is to make an ECDF of each of the data sets. We will thin them out a bit, taking only every 20th data set, to keep the file size of the plot down." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1761\"},\"selection_policy\":{\"id\":\"1760\"}},\"id\":\"1538\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1765\"},\"selection_policy\":{\"id\":\"1764\"}},\"id\":\"1550\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1538\"}},\"id\":\"1543\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1769\"},\"selection_policy\":{\"id\":\"1768\"}},\"id\":\"1562\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1598\"},\"glyph\":{\"id\":\"1600\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1601\"},\"view\":{\"id\":\"1603\"}},\"id\":\"1602\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1777\"},\"selection_policy\":{\"id\":\"1776\"}},\"id\":\"1586\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1604\"},\"glyph\":{\"id\":\"1606\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1607\"},\"view\":{\"id\":\"1609\"}},\"id\":\"1608\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1767\"},\"selection_policy\":{\"id\":\"1766\"}},\"id\":\"1556\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1760\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"source\":{\"id\":\"1544\"}},\"id\":\"1549\",\"type\":\"CDSView\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1763\"},\"selection_policy\":{\"id\":\"1762\"}},\"id\":\"1544\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1538\"},\"glyph\":{\"id\":\"1540\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1541\"},\"view\":{\"id\":\"1543\"}},\"id\":\"1542\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1783\"},\"selection_policy\":{\"id\":\"1782\"}},\"id\":\"1604\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1764\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1775\"},\"selection_policy\":{\"id\":\"1774\"}},\"id\":\"1580\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"zczMzMzM3D8OLbKd76fWP0SLbOf7qeU/K4cW2c730z9CYOXQItvRP166SQwCK+c/fT81XrpJ7D8j2/l+arzoP8/3U+Olm+g/mpmZmZmZqT/ByqFFtvPlP7Kd76fGS+s/GQRWDi2y1T/8qfHSTWKwP3npJjEIrIw/y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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1781\"},\"selection_policy\":{\"id\":\"1780\"}},\"id\":\"1598\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1791\"},\"selection_policy\":{\"id\":\"1790\"}},\"id\":\"1628\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1779\"},\"selection_policy\":{\"id\":\"1778\"}},\"id\":\"1592\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1598\"}},\"id\":\"1603\",\"type\":\"CDSView\"},{\"attributes\":{\"source\":{\"id\":\"1622\"}},\"id\":\"1627\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01}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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1751\"},\"selection_policy\":{\"id\":\"1750\"}},\"id\":\"1508\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1753\"},\"selection_policy\":{\"id\":\"1752\"}},\"id\":\"1514\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1391\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1390\",\"type\":\"ResetTool\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"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NMEWew/QPym6/vkLEFAm7cjRX5NP0BtfTUsmXZCQL7pXbueKkJALTDaOJrBQEDjm1tnkWE+QM1cUffpt0FABF1IZp5cO0AIGCH4kSFBQDvY00UYJUBAzqq1ZMgxPUCkiVRHZDw9QK1R6SYsRUNAI9h1zH5yQECTvvcDNGQ/QIbwcJKA+TpANqC3dZI+PkCuaccRLrdBQK9Him1+Hj1Aur4U9p7DQEC+HLII90hBQOLM3HTo6zxAREzTIjwyPEAKkThug7U/QIrU5DcHej1AkSJOOyunQUB4T+nYQoFCQM5m1V0EikFAZxSYZp1/QEDXCsGiVq5AQJRLpvJGvUBAxzWjc/7EPkD9CqNFPog+QFWhNJ8ujj9Atf/VntI2QEBIbpaO2FZAQFXknwcOMT9Av/AFIvxkOkBDvJyfH4NAQBlM74uruj9Atj4af7gjQUC6EwaKdJg8QNKSNPZe+ThADZVg6pY3QECIpzHjPlk+QPtx0KgH2TtAAB21hQPGP0CzOBD08VVBQJrSTFQJAj9A712J68krQ0BYRBFy5vVBQNeHX8pIT0VAPbvHpb3hPEDEDkWhWGlCQMuKbA/PPEBAsydAO22WQEDjn0wRlLpBQNLi6ELIWjZAwzv5OxOvOUCbC7iK29xBQGCLxEpdUUNA4zh/RwYGQUCPYLdZE6NAQGtZ6OLKZ0BAKKaekEyFQ0DWSBZwUkQ9QOGtYD5q5jdAwzWueOh7PEAmFJNxGzRCQFDVRTR6HD5Aw+0aFc8rQUACkVzoEFRBQONgw93HmkBAeokoZkhlPUCDUZFXYUA+QBPgkW9gZjxAHRU8zexIQUBV3F/X1sdBQFjO4c6Z+z9A5fjuNb+WQEBDKj0KWJk/QHUZM08Rkz1AWu3Izty4QUAs5h7XHCc6QLm/I8AkPj9Abc+aADk9QEBO+HbV29o6QOtWo6k9SkBAh5xTd9ZEPEDqxRhFlrBBQHXG/gAEp0BAb+x9WW0BQEAxd3HF4gU/QCxPBOXbrT9Aaots04+rPkBpz2/Z4m5AQBF5zEnzYTxARyPLRyH/QkCmISOUTSBBQCzU5WpkRUBA5yQJIrNmPkB/CQHkJiFBQCwe4XfZij5A2DKxMe+yPUAwqhnt6FFAQE0dOImaFUBArs6LeiOdQEDY+HnlqqM9QEGR3W4mKkFAqENht+JJQEDQkoQ3r285QJE0N6CD10FAcGAHx4koQUAhfsZBbRE8QOrTZS6zez1A9P9DhLiVOUCzQwLYTRNAQJyhG4XncEJAUR+JQ6VTPkAUOH7ZDHdAQGJb3ySqs0BA6WjLykQ3P0C6m9NMtJ5BQOp9QjU13kFA7YVCyyJMRECu0FSOmfxBQD2yEZXURD1Aj1Al3JQfQUCD2fy797ZAQPZjrMRkGkBAUVivJUG/P0COSTuTr4NBQO5inhDZ50JAueOVifGtQEBdZ99Gp6ZAQBlPCMVWJD1Aq5OvPZVZQECMm2khBT4/QMjpbIqe3j5AeAhEckI+PUA/KO706gVAQO8iVGAm3D9AU9s3HRmePkDu2UAPiiI5QGmu3ScmhkJAhYgmnu1tPUCdGtVYxqM+QMr9ZOmnHkFAOosGiRTBOkByTB9MLtFAQOEKZ1uIYEJAnpRWpGOWQkDZz5Xj6KdBQFao0KEKdEVAyt7VSpf1PkD40Mw7soxAQAoc1lEhfz1A2+7kFoXxQUAqXpLtSOdBQOsm0QcisT5A7olSGL7xP0Ap18AHeVk+QExgd+/e0TdAKJK+9vREP0Cbpz90tBE/QLUxSh+eY0BATDumyJTqP0Do92FjCs4/QLhmlVq51ztAlJBAET2AP0ChWrjOqh0+QAM2jwJfdEBAaXOHN6tOQEAatxFchyI/QOnRBdAxnkBA755ehJclPUAqo02Rh0I8QAb4uzPR+D1A1JPvJ0LLPkAaIDjkTmFAQPPp3HQ2uj1Anev4+rt2QEAxLJnkUQI+QGGcXvf1O0RATWGnmUIbQUD1811n/6Y+QLBzPrtKnztARnizK3cTQkDxp2mkG7ZAQE6WkRJrcDtAGwITzoMxPkCBIelvWIM/QJuQIT5iyT9AmtWwsdckQEC2nj5ce0A9QMsMp+ONyUFAOt8fp18uQUC2gaaSz0xCQDDq7/yMnD1AiRZkYRBjQkAjhgud1oQ9QDex5iuEnT9Ar0Efid1BPUB76IjfWqVAQPDXGEQvPkJAj59QaPaGPEA2c49wEfU/QP9k5e9ANkJAVFUCg7YJQUB1n6DNsAo/QAyigk+9iEBA9FfT0NHLQECkRjdbJzo8QEYXIKuDZT1A6i8QdyD7PEB4X/rNaThBQFIQuiKY6TtAqmqrgmK9PECp5hWRKek/QEcVb1hIckJAqWxy2UNWQUCdnAIUZgg5QFWS/7rPWj9Ay5RJaIXNQECMW9XdRDRAQK4EOxiVIkJAB1nHcDWHP0CoF9Dz3Sw/QEMIwaLtB0JAzIMI/36VPED79Wfed4FBQDL/cbiwFDtAErFA/Ng0QEBn7tSDzvtAQFzqT8Tp30BAVCBlQ8SkQEA8NZvHmhhBQHazqYzuqEBAaI3KG1iZQEBbqnIqhEJDQC074FF39z9AAvQJY51KO0Ckzk9SRQk/QM5gMe7w8EBAIzUG20/kQEBjQ8B+9QI/QLRg9kqnpD5Aq9p+niTbQUCZw9ICuY5BQKrV6XXrLD5AFIqGuuF8P0CYohT9JT9AQIEzu1Ehzz5A9feMKkg0P0AZus/HiThCQBCQe9qm2T5ATP/gEy6BQEASl831gNg8QD2AfexSPD9AuSzXHrP7QEBAPeZmP6U3QBfWq5z2gUBAzgZKX7eyPkC3mjjdyyc6QCds74DYQD9A8esCZE5rQkD3DXpXCrpAQPHFa9jHLENAdcxLbCUxQEAMinC69B07QEwAvzeLADxA8syuS4+FP0Ajgg/S1Wc+QE3CFcnAPTpAW3euyxlzPEAhLPxYK+A8QDF6lFXbD0BAdbBPLMFhPkCOfHpOTrk9QDPmr9ujgUFAMJtSnwLJPkB20bP4QZVBQMdSG4zoUUFA22nX37WjQEBWO3+3sWw8QAQ/UNfQqzdA6mogbti8QEB52xpFCxU8QJZru1tPjEFATF7c8djFQUDlVRIo1rk/QD5VbELrkT9AcjIQpyzNN0D+WZRS+Rs5QIihuuaqhkFARPhIxpioQUCdfHLddio/QArSSE4iiT5AJgFurIsGQUAPN9i35Qs/QJza8jUg3z9AGOHw1/TNQEDllKzHoLE9QMzMLerUCkFAuhom+CzSQUAGaoF/cqdBQBKUd59ZOkBA+rxa5a8JPUARm6MuSABBQHv0LUQOXkJAiCUilUICQECSfCiYQIFAQPQBcKlY5ERA+ulwfmogOEBlCz3S9PA9QIAv/BKZxkBAbhZpTMuUQECSdOS66EJBQJfsgBqP90BAbsLDR8hWPkACZEvnJH46QPUPuyNc6EBAPZPaVECpQUDXVwudvdVAQPcTwonnEj9ApZqJC2CtQEAZDkh+tJtBQE6YKn3C6D1A3LUY/bw4QED3n/hVWtlDQNkyOQGvzD5A65WkcSKzP0AucbunyqRBQMCSXXv8+DtAGRuyyPOyQkCD6V+ZdN04QHbLGz17TUJAQ7iBSifQQkDIaAmASg1AQH7z5NMXrDxAts54peFAQ0AyweewUg5CQC3Bo1jUMkFAKcjvLQqSQEATXewi46E/QPgsfwy/fT1A5/wwF0NEPEA8b64Hz8lAQMOCETykB0FATuulj1nZP0DHQ5dc5P8+QJUzJYOpaj1AnI5lX412P0A4I5yfEHtAQF/UdDEcZEFA3UecQhE/QkBdag6eH8c7QFLUrlS7JTpAtDlesDU6QkABo9B7hBM9QGE3JXSzUDlAPaTZxCGWPECS8HMXFhVBQBd6QVEJxT9A3kPlyLWGP0BQpasFGd1AQAeG80/eMEFA8ZJjCJXMP0AHg9bg5HE9QI4wC/EQ+UFAKp7re7HhQUCWp3uYjbs8QIebhvBI6EBA2aFPiy6EQkBFkli0Tn88QGLtOlzCpD1AsXCHF8FYQEAy+xioL7RAQBorWIAXnz9APfWQl8aVQEDiVrFBwvNBQGAEBb9vD0RAqhXBoIL7PUAYsVD7dVtBQAqjcSfcEz5AJHDK1BbsOkA3NH6oNMhDQLEDRcj10D5AYnpm2WXvPkC8LgGwWvM8QEDGnkxbuz9ASYLAFC+mPEBWVmk7BzFCQFImdsFWPkBAv4e5o47pQECUrvzUO8pBQOpt56bTGDZAcL0p4nZOP0Dm+N1BZppAQPQBj55PgkBAMhsIuX5HQEAwZdkgl449QK1RFCytGUFAe/3/yx9mP0A0g4XPoZ8+QABKRo8KYT5A0JF7eNElPkDocAzy/P07QK9C9cXYUT9ARfX1WdQtQEBSrL2fXIpDQOJ9dS76nzxA8BSmJpXzQEA8Pu7LH4tAQJy2FCkU1EBALZI1OlYBPkD4n8I6r7k9QMkjfFzvqUFAgFdDSE0aOUByM18X1uU9QFO2976aeEJAcmRSlrbpQEAGS1evl9I7QHiYNoE9yD5AT0aU37cyP0CPa0kIq69AQLN1fcsPJjtAhG98sEKYQkAWnI46B2pCQGZCEgUnlkFAU+FzLFw5QEAicoj4e0VAQMmxAmKEgzxAwP6aofmLNkDMlgf9hCBBQF4MgSMBQT9Au2ScrndsQEDtshJoroBBQNjjyYYROUFAfQ0CXrs6P0A4R3cv1C47QNvEV2yQGT1Ax2iBD0DQP0CgyOpuU8tAQA34DnittEBA0CfF3LIvOUDQDSSDnSE2QMjG/nY1WjtAc48r+IwlQUCgNSY9SYU/QABkCE7wCT5ATizti+NAO0CBo9HQrNxAQN19sIy6JUBAgKVMc1wzQUBhEaDlFeY6QFd30MiJCT5Ax845+LLmN0CjhYz28F08QAD8rFiu6ENAKjwXHCBgQUCoS9mDfg1AQJC/Z3ZmskJAkGPB7DoZQUD6FdJVXR88QKANpCBufENAJfAcX5btPUDBewQgAH1AQFYKFd22zT9ATn5jc7DmOUCTe1wjB75BQANb/V2mD0FAErGiQUhoP0DtekZZFG5CQJWADhHvzDxA79PtTUUrQECFS5AqPX1BQIhtEAQ8yz9AkjTjpJCFOUD3k4/ZP3E/QEyBwf4CiD5A5ozGIU01QUCEKcgYbJk9QO4agGVCjUFAl1WDCoPuPkB07ZUVrWxBQOWK6vEMjUJAygvCbMBUQEBCB5tiKVdBQM2RAPU4K0JA4w15zs0nQkBKMgfyWThCQErYrbTHiz9ANmTcWqBuREC9g8xxhPlCQCQlmcrO00BAP45aixsLQUCmxvxQWhZBQAuC0FDEWEBAQ6bWRp/3O0Dddg5F40M7QFdRKX/4ckNAmt0DMU0MPkBa3cTTZd4+QK5bQRC2ojxALaNAcKXPQEB0u/ZjEuBBQFwkOremWT1ALFpxMdvpQEAeyBRz+7k8QJbX9JodLDtAaLh833IDPkD/O9LwfmQ/QMibIEYlmT1Ac2ORUTjuPUDLX/DNq1M7QL5vkoNgWDtALtd4LZqzP0AncJW4NU87QJcOm3vx2j5AneNQkjxNO0DbAfEYvQE+QEfaFQZ7ez5AxYmdIouuQkAD6OgW7otAQBUOgWnSMkBACOGyu9UoQUC9pkPdtbtAQB1GBD+umUBAMAM6iQF7P0C8irHgtsw9QLLObCpyq0JAfsSAIlgxN0A6s0bv7yg8QHd9m8dBAj9AoL/sJ2h1QECG+JHqiiJAQN/YDlZLbUNAh2UDLDMrQUDBX6XELdNBQOyMbJ5d2D1A5F+CtE2fP0B31VMpZ5hDQEY301BiSEFAOajvf9bFQUCtJxoP8uI/QJDSifyIYD5A9sZzRu8+QEB8d4eOclE/QFTVCUtn5D5AtKEG/wkJQECrst/J0Cc6QOwMZvRmWEFA5QCLQOLNQECHv7+RvQs+QDQEitRck0BARfFaKZ6hQUB7CIEu5jJBQG2F5zPccUFA0UkZoCpSO0AZ4c9pnvdBQNd998V6rEBA5nwJ6P6nPkBu6c/xXmtAQDgHl3JA+UBA4HJA68zTQECsOhvA75tAQCOOksfJhjxAweZkOLsTPUDxwV6oD5FCQAa8L9TNtj1ArZq1dEM6QUDK0Jqm24o+QJZPqQMonEJALFGdZE6tQEAOlaGyGktDQJKjH/JltTlAe818UulcPkDODWfAh4o8QDf/7kNwRkJA0kJvDMR4Q0AkcVou20U/QP6losxchD9AENnjtDVxPUBBSQkxCWpBQMIJsazG0zxAKIRMdHJ+PEDKE6yprRlAQOat9xudi0BApmze6wVfQkBuZTuZXkJBQDxQqzlDx0FAXcuy/GKQQEAkzQY87wg9QN+RT1vzcUBAH9Kv5cw/QUBAlGjMQxFAQN3tmQAnDDxASpVFbeiiPEDdlAY8+HBBQLLibDZVo0BACKql1pyBP0DAGI5mHb0/QOrdCsi5lUFArdzEgMepQED7nfgZ479AQESE7FN72EFAbm2dnJwLPkDhQlAaA7U+QHk3vSy07D9Av2+Z738YPEBY0KYN57ZAQA9wAe90ozxA1Vs0mj6/PEBIerewWTQ/QONW+xeQbTtAfIVSjQEjPUAVa4HMqdxAQADkjpr370NAZhddodApQEBOkUqS7/Q9QF8UzXAPCkJAxmhb6SBUP0AHbsX//Pg8QIdvcDeLmz5AwnQPkew3PUCcBNIOXLQ9QB0IH9kI1D9ADmHs7qWPO0AZ39VMxOc/QGj6GEuEokFAlyeuIaiFQEAtrsE79bk8QGeQTocQC0BAWOhv9MX4QEDIJAe+9mE8QACl8nu9+z5Ah9PSVUgeQUCawvUzeG07QGog4+/VKUBAxQaXY4S8QEBc+TgP9Oc+QFHtxDeH/jtAvqwbYh0+PkAzeKGLZp49QOPePT6cHkBAYIkVRAmOQUCbGgbcziNAQL9sl52DhEFA94vev6rrP0Bu2ederVhBQIWBc7AB70BAZ7ZKlzwzO0COg2fBIy48QHl4QGfLmj5ApSfkWhb9QEA6oyTRzD0/QMlOjky/W0BAVt6sDvn7QUB5htyLEY5AQG6giVemnEBAcCMjyyc7QUCocIGmqRhAQB5mKi2PA0BAFdfVLUoGQECsgWgFflNBQINw9S8vtTxAnm0wn15AQkAkN2X99Hg+QGdPOc9fZkBACD0X1u76PkA7KTaqVDxAQHaU20dq0EJA5cmlSMd+QUCLb0AEXo1AQGoiAtPDvERAYq/5veAlQkBJsIsnXBE8QOyNj7K9JUBAg3fLqin2PUCeJZGGvPtAQNJIfS9+P0BAYvcV3dS/OkCuU4Y8q11CQEbdEBfgRj5AEN/7XwsFP0Cbp0dTRGxBQMus/58w2j9AgSkUDMwzP0BoxlBoPEw5QNJqpkBlFkBAdboyMPZ2PkBCGT/D9i9DQPVke8awfkNAA46vRhJ/QkAg4uiCXhFBQJ3AMW85cT9AOjAsx/ZhQUAqWaTg0WJAQP+JYsxxtEFAR7gaRxsdPEATXsKAVsU7QCARxGwi0ztAkCrFfHMiQUCMY1rrGD1CQLT/ptOz1z5AKOeg6P2TPEBR+Yd8rpZBQJQDjtcZzT9A0+fm+EakQUCd7Q4STAZAQJRYc2ioe0NAjPR776eLQkCdtNfJvNRAQF5DCW6HTEBAsGedgSLYPECqKjtyEao7QCG4V63KLUFAOIKSPhwhQUB+/CokcWI9QI5+8uSORTxAk30mVe/hPECw4N7sT7xBQPMfFAfh9EFANArixvp4PkBsMWL0aKRAQPUXiRmyiT9At0CIsYH1O0BN9qJeC7U+QM6JtmlNfEFAWYH8tNpEQUDG5AnbmWxAQBVhWolapEFAbW16qw8YQ0AP7qQvkYg7QGMjWr2IND5A1R8Gc5JRP0DBOpwoN39BQHQGA8ZFyD9ARFRa7BXmPEATH/36scJCQCq8RXmpXD1A8ByvX6w0QECKHW9vrCVAQDr0wD14VUBA01r1ygfKQEB0Iizck8lAQJPD1f6340FA93cwEoGTPUD22siMiCZBQHoPZ/yaQEFAPfzfZOReQED6cSlNKVVAQJ5CLxoGfD1AEM9o5UqoPUB2VHrpR3g9QGxtm5dgAztAg5q4BG67PkBAxj9z4h9AQBMOLgGf1UBAgknhF0l7Q0DyU/McMkBCQLWi9olDOz1A1PFck8wvPUCQ7+t6bYVDQFUTkdbF5DxAtq9qkUqaQkAmOge0mbtBQOE2BbS5tEJA8XbXKai9QEB+jpWzp8Q/QHImOakPbj9AAgwpbcfnQUCIWWc4wTJAQImlPl8qmjxAWOE4cL47Q0BFWY+vKIo+QGUniOGTuUBAjSapVLuMQkDs/RXlCZE7QMa62aizKUFAh3JXghs/PUDYj7raFuc+QC6gOnPCBj5AQEfhNSMPPkDeC/2oYOVCQLzt/Ed6Bz5A8Gg4Ogo6QEAg2KjnbDM7QMdVXGGvYTxAzyj/Qyt5O0DYoukhKutCQM8ZRKvtRUFAc8uiS60SQEDmyXub2VVBQP1SZIl+0zxAxptK0M3NQkDIzkJBeEZAQNJv51ijCUFAJv7bB9tFQ0Ahm4WmGB4/QBrzQlP+XjlAL5xf28JUQUDazQAmfSRAQFJrXC0Fq0JAi+lSwOSCQkC+tliSdxk5QBrYzvSwNEBAzh1jPT5qQkCipphInNc6QGJdsi0wxD5ABDU3qyPeQEATQEY3QLBBQMr5dQHS60BADhreGn9gOkCZ0ebH0nVBQJBAAkkE7ztAdpDrg8ISQEDtKUNhITFBQKh4ZQ9NL0FAmTtakA3UP0ByK4imdW1AQExCdTBOxkJACyMM/mOeQUA0MkvGTeA5QBTLwXlDSj5AL8nZm4CRP0CruEYjzmdDQHQv5iVbPUBA5YYkThBBQUB8qEw4Kz1DQLK7Xg7caEFAfIiD31EMQECn95L0V3BBQDI2g1z8xTxAa2pamWNjPEAOpPifmXs7QCo4M6PpAz5AI6uzy2QTPkCGHTXPIvg9QIjCv0DA/T9Afqekmy4nPEB38kcVqshBQIP9bnrJP0BA3SIr+wkJP0AArQEdY3E9QHUIA/oKwD9AWbjvEaGlQECkCZO9ul08QIhhtKqf+DhA7WUNCluPQUALMJT+8Gk9QPoyfF5qa0BAfBoL066ZQUBIO8Lhe9I9QKUXhV+NmT1AfmgrO8wXN0D1t/OCHtA/QBKuzfv+DkNAwIe9salXP0A82umLAEM8QFfD0bjgoj9AePpDhzuZQUD8qUU0x186QJhoH6iEiz1Aoz3f6iRnQECwNByjv7Q9QHC96gLLcz1AdbfwqY2zQUDpliXkw1pDQGJhMmdnDTpAJvv+jfnOP0Dl5k1HqDxAQGS04qyIOjdAIHooGeteQUAqJZIJZvk/QPTCyFf6K0RA4VjP1xjrPEBnigteUCw9QHQYrWZrBkBAzo+bzBXqPECsAJEHrfU7QInIVfxEET9AeexnkQszP0D6uGz1GqJAQOSM+eLKT0NANmdlikVWQEBro0xN4dNAQJp36MMBDkBAW2WU/SucQECYVeEHj7E9QOFjWqc26j9ASmCm1tC2PkAopcmAiHY9QOBXRzc3iUBASCb8DsvyPkACEJSwL449QIoUF9ddW0FA8nS5MH4lQEA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1771\"},\"selection_policy\":{\"id\":\"1770\"}},\"id\":\"1568\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"Gy/dJAaB5T+LbOf7qfGyP0jhehSuR+0/2c73U+Ol6z81XrpJDALjP1pkO99Pjes/fT81XrpJ6D97FK5H4Xp0PxKDwMqhRe4/VOOlm8Qg7D8pXI/C9SjoPyuHFtnO9+8/QmDl0CLbuT81XrpJDALTPx1aZDvfT+0/k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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1735\"},\"selection_policy\":{\"id\":\"1734\"}},\"id\":\"1460\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1727\"},\"selection_policy\":{\"id\":\"1726\"}},\"id\":\"1436\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1785\"},\"selection_policy\":{\"id\":\"1784\"}},\"id\":\"1610\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1484\"}},\"id\":\"1489\",\"type\":\"CDSView\"},{\"attributes\":{\"source\":{\"id\":\"1658\"}},\"id\":\"1663\",\"type\":\"CDSView\"},{\"attributes\":{\"source\":{\"id\":\"1460\"}},\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1741\"},\"selection_policy\":{\"id\":\"1740\"}},\"id\":\"1478\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1640\"}},\"id\":\"1645\",\"type\":\"CDSView\"},{\"attributes\":{\"source\":{\"id\":\"1610\"}},\"id\":\"1615\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1789\"},\"selection_policy\":{\"id\":\"1788\"}},\"id\":\"1622\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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FP7XkVLYjxAfTfckpzgOED443kbmS87QN9lCW6aVUJA87OQCowwQEA5qVHeYDI7QGr/VxFyUjhAEwb/iu8YNkAOHkPyvHs0QLvTyQUGb0FANEDCJF89Q0DvcAtHPo02QG0W21bvEUBAVIpRKTwNPEBF36acDO43QN18QdHwxj1Ac6msHaneNkAgaZ1Exeo8QOx6xURiST9A2TB3ymEAQEBprb/RNtk+QFF7pxGOdzZA6j3a8OldPUBwc8k0Vsw7QBMI0qUUZTlApuL9D6ZTQUDhCUvwWoU6QES8uxWdBEBA9OyvFcrPQECpHBlnWyo9QC725xtAlzlAc7veHKIKO0BLEW/qnns9QNluxIiPuThAtGJ0xcYGP0BPfTeO/uZBQHxGVrLBgzpATxXPc7VTO0B2db9tT4xDQBAPGa9B8DpA8ELnBehKPECkWEEl9BZDQFAsfNxc7kFACgxIafAIOkCM9lgZ2LszQHKLMGhZqT5AOWZC8lR6PUD6jLeoFMs3QK73NJNXAjtAzl5WEqCcPkC7QvqtKEtAQASgXOkjZzdAuf3xxJrZPEAylYyy0C87QGnaG+kM1D1AJt8HDZ0NQEAnPfU+E/M/QKtfv+laTjpA3IdduEU2NkBMNMNBy5A/QPycF0JywD9ACNEKjQe7OUAbw0/jFWU9QMb8kA1WqjhAZMTAOqPbOkBE9RfqOxRAQAZjIr0wA0BALw2R6ahyQECLeV4V+uE/QB34VQpcPjtAJs/p882zNUC/7IyjOhNAQBIkEXyUnENACHierH1fPUDjB7a40IY8QCXm6JovYEBAU4xgqMijQEAABjBtWl09QEEJC+Qt+DpAkC2YIhfzOUA3dBi2haw3QHTKpDSB6T5AINktgcaqOUCfLaVW+CM9QNaUd1eTYUBAdDST/gsbPUDr5u4gUKY9QI0DwVfoIzhAMOR5qagOOUAZq8zjDqQ1QMjrn4p5SjtAqzFTklkSOkCVEwes8WdBQNwa0GkxQD5ASBOST2A3QEDFjobdZHc7QKMyIqReez9AtuxfcSpJPUAP2g0IDNxAQOiYTkGzbzhAuS08YvmRQUAqJC82E+g6QCJk+A+3TkBAsP4e4fPROEBundu08LQ2QDgpWLsnDjhAIOL/p6l1M0DWGtSmG8I+QE668lW5fjdAa97YFvTUOUA5aEHDiuE+QPmP4RdJpztAAT6U5VmlOUCmRU0bslc7QJoWgTbsyEBA4bAh94rGPkDPE+NSpOA9QH1qaGjBCUNAHaWR15XcPkC7A8aRye5BQMKHrkOoqT5AlZpLiKLUQEASJ95rdgJAQAHNXYmtGUBA1Ql24lc7QEBGJhPJPs85QPMn/eSSgztAbm1DENiwOUAA0Yb4Am88QBvI2v5jNTlAUiOF0PHPPUCITCBZeQ88QBHT/1VQkkBA3bor2chnQUD+ilzJ24g6QB8ZoJaRzzZAM0DLw/EFQ0AggY6Tqng5QMrGXeqOajpAh7/Iq6iNOkAox9Gc95xEQJL3tCWdID1AYSNxGkOqQEBp/tRZtGZAQHjw9SVcDkNA/TpOT7fjQEDOHn+eBoY9QPtv0J6C6TZA9Rt2cMCRP0AjoRH1KLA2QGusFaKw0zRA5Dz2o3VcOUBH0jYyfrE9QJm/1+EN80NAaRFqmZwxPkB9F4p6u5s3QECqu7TW/DRA2jTB1T+mOUDZ+VA1Z3M+QKbd4wXEVD1AGY3RdCVzNECiibw1bTg/QJAGp0l1/TZAi3na8DCaQ0CBZJi8L3k8QGjw2361MzpAA4wBvvw8QUDRq7bn5ppBQNn7JCPcBzdAbIRBj05zPkASOgwrWjM/QNhhlqV/BD5A5inrx9G5P0BTrzcF7ZE+QMGZnRUadzxAXdo/23tHOkDGLXErixU7QCZowfZe2DxA+c+qob4rOEDWEuASVGZBQPaKAohDTz1AdK7MamaZPEA27Piy3Eo/QF5tz8nMyThAomkMYhH2P0BgriPeR1FAQFSUKhzw6D9AIzrulcfzO0CKghGBkz9BQLz4fnCwFUJAgX+kZGQFPUAXyz+U9PU7QEwkfL0eOEJAn4yANKHXQECvzhEyGHxBQGr0/UhBiD1AmgWJtmwcQUCXrGVSDe47QIu5XDX1szlAhahK1wS2O0ABjdDi4LNAQH34KbnTBDlAe0V3qMgxPkD0jVZ+usY3QN8inHQTdztA/cYTDU8eQEDLUIKdEFc6QLVUcQl3vD1AI7D3g0B5OUAGg5w69jU2QD+yA7agNUFAkT6aU+EOPkAtpK2fAb5CQP694dzFWDhAuF0Q5xDVNkDTZtbEEHQ7QPWBvPhdmzlAVjqvf4/iP0Bb42LsBoA9QNf5PyfPuDtAmzYDh2rYN0ASlGelItY9QNFf23HFrzxAcBxdtD6KOEAhR2bDb2A6QEiULE3nkzxAjoLYYyuxQUD6KxNHAmM7QDBvSVaW70BANO6m/3WzO0BTYbYaQRBAQMynUyrVu0FAnjANiH+QP0BXKXeglSVBQBTedYxhuD5AR2ZumtvFN0Af6NJzKG4/QCWlbxMFwD5AGx48X2F2PUACOktznhA8QKOKVgnPJ0BAC0c5XP6FPEB9gSr5oGg+QJK4OwVDmDdAL6ROdtC1QUBJYMJnPH83QPJNo+ZfgjpA97LaHRb/PkDNCKsxOP4/QMi0LdiVWkFAe8TqFbKrP0ALbpNRJkg6QJ8rWxpCADtAjDquT1BKP0A7Nc5wV/g/QP0W8lUUiTtAPP4ikIzkOkBov6FwdL83QDx8LO3kKDlAPARUXji4PUBvckGDBA0xQKLSuU3twUFAFIcbewc+OUBZtYaren44QDxJ0x+pfD9Ae3ABiSbOPkCGejLgcBg3QJGa75iB4D5AG3yXgzVoQECGq4V/D8Q9QNfoAuApeDZAsrdRf4MIQEDANGHxnApAQKGhXj1PJTpAdlnh/8OLNEDAiR8o2R8/QIkJY2sscz9APIJYGI04P0A6V6eE0P86QK/p5yaKFDtA15Opjl7ePkDROwz1iKk6QLxq/xF9kTlAuVt/dhrGO0DMXYCTeX9CQMiJg+LwEjlAfuAiG4KuN0B2krPD4cJCQCYxBKt+fz9A2mdF0bxWQUDcqii8MnpCQEDC0PW89j1ACBA0qbk9OEBwrQoF4QVAQMkxJ+JjMDpAckyMx0vqP0Bepfr24qk3QE9Z/bASakBAcJi5oDA/PUBu8VYjny43QLLcxu7H9D1ATqKSpFRoN0A9QI4IjZ1AQOJYdISXpTlAjBiA8KGBNEAO6zcamWw+QDnZclKI+zlATFncxT0aQEBpd4mLngVCQGLY3yPgCjxA/5wc/l58PUA+sNvxKUE4QNG9tpk/cztAoqG6uz6XQkCQXYOTXCo6QFgP+6RERkBAmBls0nv1PUBsgzWuisM3QHcYK3CLlDZA66akJYI8PkCMSiuqChdAQCSQjZXzMkFAhkSQQ2o/P0C2+z7zgfU9QOl0WR6npkFAP0izdDnJPkCSYU1aFgY8QE4n0lTnrjVAMnVLiH4uP0BH5teRxARAQKZp5qp+8TxABNHSZI/1PEBeco4yxTw5QEEYWnv5Vz5AgrAOuxBRQUC+eygLOmI4QDCCsAtD6UBAA8QD01k6OkAZROTqG/0+QJfUHI09ZDlA8ZJsQuC2OUDMHuZVFo0+QDk+TCjjBTtAad78nRsiPkB5VXwCU6E6QFp9yiwPyz9AfhZ5LFfcOUALNjI2ar5CQB6WQov5FEBAtby9Imd9MEBt00QM9CY8QIYyqyKjWjtAV0ASdXpZPUDUpDMMkgRAQNmNaEMWNj5A2oIH3kXJPkASE+bFhYc/QDGbMRtd0jlAXmeTY5t4OECIHfx0NPU/QDN0SNvu0DlAiIAi+pf+QEDV0kykbOA8QEoA3CbR4DdAvHxfa+eiOkDWtiwiUt43QCaDHJd3oTtAWhVRurUTPEAeRh6ieC08QNiIJ/xskjxAVKKhLHhEPEBLxsQDvkI7QI5HManP1jNATWQAmhQIQkD2A8UJSLk6QETcEk1nLjVA7Lw2mvjfOkDvx2mYvvgyQBc3mMmHIzxAaq3QqowwPUB1BIQ2TypAQDeKLO57EDlA5sdntOW6PkAX0Tb/FN8+QK5fzWm/bDxAqBOqPk8cNkBJmz4SgRM+QP4G2xL+kz5ABgyxrys7OUA4qQK1TbM9QKwd9+ezYUBAqFnhPk8FQEDgvd4oYKBAQH4bhQThVz9AB+ggmFX+PEC9OyEAQuAzQI41kIzhrEBAI+o7Z5zgPEATpKJupXY5QMlUDflWNz1AyQkAsF8ZQECb2quS9Yw+QMUGe/G/dD1ADSFI14dJPkCkPpZwy4o+QKGNjWIS0j1Alo4caTApPkCgEYNEMOA8QG1HE6ICWz5AhYnLzhpBOUA7iXD3lt87QJavvFc6rDlAiERE0l3zNED4LXYoIwo9QLtO0ZuqzzZA1xJqVCwWPkCjeyN7q546QJwNIlCx1DhA3qwt/PPTNkDAizPI+qs3QDoyxbMzuUFA1bscWi1hP0DqRNAlX8I4QI7ptn0CtDlAuyJWcLWIPEB9GPDWLBQ9QKK/iF5zyD5AS6LhB/y2O0CUFV29dXxBQCPXp2+K0ThALh1w8hwLNUA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1755\"},\"selection_policy\":{\"id\":\"1754\"}},\"id\":\"1520\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"NV66SQwC7z/RItv5fmrUP9v5fmq8dOs/8KfGSzeJ6T85tMh2vp+6P/YoXI/C9cg/Gy/dJAaB6T/n+6nx0k3qPylcj8L1KKw/MzMzMzMzwz8/NV66SQzuP/p+arx0k3g/YOXQItv57j+iRbbz/dS4P9NNYhBYOdw/z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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1797\"},\"selection_policy\":{\"id\":\"1796\"}},\"id\":\"1646\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1759\"},\"selection_policy\":{\"id\":\"1758\"}},\"id\":\"1532\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"yXa+nxov4T9I4XoUrkfRP8l2vp8aL9U/WmQ730+N1z/P91PjpZvEP8P1KFyPwuE/gZVDi2zn4z/ZzvdT46XrP4/C9Shcj9o/+n5qvHSTmD+gGi/dJAbtP3WTGARWDuU/UrgehetR5D/y0k1iEFjlP99PjZduEts/n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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1737\"},\"selection_policy\":{\"id\":\"1736\"}},\"id\":\"1466\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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PVZvVtVQMI7ufVQ21RAAxXtRKJ8VkDnqVoTxDVWQK47iGWtAVhAaKslxWeyYEAZ5sjpieVZQCxkzB3WKVtADIumqbobYEAS4bh73iJUQFW7+5upMFpAGtKRH9fgWEDpTuet0oJfQAruZLzHclNAcWw4Wd8JXUBhpMDdg6VcQIr/SufNNF5AmL6raE0UXkDxIHwb+etdQA1UvDxJ5FNAcw9aZbm+XkDl5YzSDYBZQGY5iBlUkmBAUY2/fzXkWkB/KXokAUdeQO9/2QODEFpAtut30SICXUBKpUph/YFbQHNJVADqmGBATMlMZefkX0DR8sl0p6RbQPUZBCBgbGFAUhFuto2GYED7jcXwmxNhQO0ArOyaAlpANiq5LXKKWkC2/u++0QhbQDMnwBxALVVAIYbB9LF4VUC1I3SKYT9dQNKn2nuwpFxAb5WMrxSgV0B3p9XtjIJXQDZQfZziyV5Aag/LFlHeW0DcOhEDIHhYQO3jGVinTFtAeeV6m6joXEBiQdLWFXtWQIIQknxm7FZAu9s6oANpVkAKzj5SYrpZQCshYBhaV1lArkE/+FMAXUBIMlzImQFcQBWLY+H7xVhAIQ4vIiG8WUB4EB+hzEtaQJuzRCzhkl1AfrZdcIR7XUDSRghNwQ1eQD7Vk5osHV9AkRvTlh9EXEC2Cna5hBFeQBl1IBQ8BmJAA6IxKY0pXUCJVtncfWVbQNrISaUyXV1AWkrROY62YEDcywVtxFVaQFBbsBoW8FtAymAOOuIwXEDKwNnaJx5dQL73YQ3VQ1tASyshmrEnXEC8p4AS8P1dQIQ65RjCOFxAuqH3UsmpXEA1zmNINONXQM5euyNxfVdAn8ZRc0U5XUALvt0pv1BeQDsJgfPcDVhAVFrTWKaXV0AzEwjfkZ5aQLoyS4K7vVxABafpFHqQWEBWkXaTdFtSQFYykG4/FVhAF9KBvSgWYUDXLLTomQ9ZQAAxQsQX6VtAudgI2keqWkBn53Y10C9bQP6vEJLzIltAVvkocMy1X0Ds+gvqmChgQGnrXp4G9mBAMhazv/imV0Ablm1mWVdbQAiBF3IZN19A+dH6mssKW0CtrHHJEGxeQD7ZM17A71hA8ceRd4ILX0BHCbt3YZ9dQDxM8ANonFpA8ZyfrEYwWkBBnn/0FrJZQDiDrZWCmFtAT2CICguuWEA5L/feTghaQFo7BF7G51dAT0bEK+PJXkCmhxDMfA9VQIjocIiCslpAOoptjDGNV0Cvzt+TD4VdQItVGnIJ81dAlHLcAJViW0BvX/l9seBYQHjWWHsUjVhA5ZdJ8BDAWUAq89wf/51UQEqJsDy/WFhAWveZmo3ZWEAqecFm7B1eQNnKnl6IO11AqPHuLDMDWEBu+8WrRK1cQMN0ZaeR7lhAhGeHb/d0W0DoOpez0hZWQABAOBlQbVxA/GBH2xbLWEBXwdWb7ZBdQNpsw1fPClhAEGY+GzVKXED3bRj360deQPone30WiFlANxKkE4iJY0CiPAAEIeFdQF9SFSpdTFhAW+bYL9dnXkD/5rBCI7VbQPbOM3D28FtAfOaB69FLYEBNHyvGAcJZQGI5GW1//l5AqIinQB1OWkAlWqorwn9WQHVFmLl0VltAqX9yUEqeVUD1xICooDNaQMLP1oJBSGBAAJm1e5NpW0CkXaJNgUFWQG8Co5sJ51lAI/UpWTCQXUA8nGJNGARfQI5VfnkGdVxABG8WaYPbWECbbp0KfppaQJrVriNRf2FAxpG0NJ+2XkDouW+pehpcQMoj/qUZ6V1AAnLihYmMW0DZmgUw915VQM/O1lwypVtAoSSHDz/3XUD+Zg6EDmBXQJlblmPtql1A11CuKpjWXEAQtBAxffpaQCKRfDU45l1Asr/mgr1fWUDK40au0D9VQAGAazEkkFtAoq6V1E/5V0DaA/1ppFFYQJlEi0kW1FpAIA4+rzYPWUCYeWWseU9WQGwDtnNl1V9ABPOXC9i4XUDwixKQrndWQPrilD2ulFlADRjFJm8UXkCFqlOdX0pbQGUCz1LtSlpA+5rVCGlJX0ALebcuMo5cQAArKrCi7FtA7NuhVnd0XkANB4kUu39dQHJ0IXXZGV1AiyEp7RrqXkAYv1b/AQpdQDmmI0/3rlxA5jkGymxsVED1bhqycWleQErViJ5b+1hAxpLP71QWYECrhy93cTVdQNyxQUiACFlAjSi1OKu6XkBb67qY399bQG41vYAt0lpAjIjNY2g/X0AAy7YOPUJTQDd5Jtb/v1lAkaZIHQj+WkAGj5LzH0FeQEMBFqPGaWBA/oHXxa1SWEBp3x5ixYRaQA3IkoE/jFlArMjiLVkLW0A/rnHDOhFdQKqA1r898lZA1uM5CFUkV0BV3jiB0axbQGaBO4GnHWFASgUbNfi3XEACdtCE43pZQP/wN+aNrlhAcLmPMh9qWEBK9uE/XrdcQDZimOiqo1tA4mn05uPNWkDAtHcGkChhQNnEWgJQ9lpA1k/+YS2fV0D5TbFYoyZdQFcYtsbZJl5AkLnPmzphWUBF7De6f6hYQNGhAHxFvVpA451fP+AiXkAGMKWNU+ZhQBiHt8zjl1NARsdRqmlFW0B34tyqCMVcQERgOOL3315A4X8Q0ippWEDesMFiyfBYQGS6Cq0DE1hA2dJ1fc9FWkD8521/4JRZQMtIiSeYWllAlYU21N40YEAYFaCeVxddQFfbLGoW6lhA4SfHhGPSV0A9Ex47tl1aQDUBE2b0Zl9AqWdP33TYW0AAg5gc9ZNZQHM6AmwCc1ZAUWr6G3mtWUCSluKZj/BfQH18cK46IllAzKiL7vHbX0AIrWvdoHJaQMaa02aNtVpAd1vvd1SEW0B2nHkGw8dbQPjmnFLBh1ZAPwFQUbygX0BIgmnCLKdbQEqMrh0vbV5AOl3eDitfXEA4nOEwVjhiQHrjMF9Mb1RAQC6+PgdKWkD58X8hpDhaQJ0nTDqVflVAQTToJO6qWUDHE4nKi09bQMBrYsPkF19ACYmhtvxTX0D+3zyH05tdQEJLT/AkgltAZTqlXOgzYUB+7deKVbRbQKBfP6Ijf1hAiwXz+UVkWUBzDthCPQhdQLXMesl6wFtAMBuqXz5yWkD6C3uZmbRYQMEyn/Bg6V9AcqZzF3wNXUCJ2h+1xHpbQAFy96PlWF5AU/viY82CWkCOjwDDf+1ZQCS1u1KOcldAzPsqV2lPV0D8Zo/lE41YQOYzu3tiVFpASVlvR2aBWkAC6Bi/j7JTQApSr+wn51tANu26UB6lWUDnl3+dhvlbQPj9r5faM19A78VK9uguYEB6Ul81UTtcQAzsTcXrB19AHZ5ByObeXED8S1Mi4H1YQPoYuJqil1dAZv8dSz5IYECdZ5lpFTpcQH7LGpH8j2FAQT/3sahIYEAyKH8wnmFdQMUau6yYElVAwU+0kao3W0B1KsqFbHxbQCTZNMtkZlxAmMNT0hHKWUA+a44DQixaQA+7ZfjDj2BA118fBCyZXED3vU7ZLi5gQGG2Tc0ULV1AU78RNKidXECGfHVe50taQPXfOFCzXllA3ZZg9e6+YUCSyCmUsCRcQGuBHV9vuFdApaAQChXAWEAG6RfQkUtaQOtaQ6PACFdA65SoURYRYEBG1LTZ9CJcQDYxvOk8I1xAeQHzXhjRXUA8CODkOetaQPckx1mGO1dAij4tUiPiXkAd2IhNGixcQPDEbOSALFpAOrJDU8cmX0AoGH10OxRWQKYx44Jnj1lAkkA+AvCUXkAo0Fr/d+BbQHPgdLUIVVtADmogcWmwWkAeJP1WWE1YQKfw7DtW21ZAt5II+UHWXUDgIjP9WS9UQEsjVs+aE2FAplN/U1FfVECFS2ewJ1BhQLEeMczeGFhAGnQORMcbYEBKQVz5koRgQMI4pQ58L1hATJXsuqofXkDYsiOn7AVXQDjesQJivlZAtcs4Q/3bWkCzYWkbS2tbQKZRZqtxllZArQkRTHoxYECSoUlZbcVbQIDum30biFZAcoiRw8syYEAx04FGfYdgQCIVQ3Sf1VJAClkOe2/OXkCawIlFocFXQIKjL+hYNVtAbBNXbMzxW0DtEbxUXFtdQJMmuNwlPllA6kQerobkW0CkunKyMJNhQL31h0nJk11AE6ItVViFW0C5ACIGBulgQLJmFIkGylxA/NpYeLoKVkAbd99iq0dcQAiffh7TqlxAbqrj83MzW0DQzyes6+pfQBdqRgtit1lA4Ht9z8faXEAiKEoOn91ZQF4tCwKjjVhARR2Ia/z8WkC9TFE9p7NhQKboE0mpYVtApXviqWjaW0B0cKTc5Y5hQJmhNjm5MFpAnVUBMVR4WUDt/9rHyKxQQA6szbXL1VpAjdkYPBQ7YEB2fcBa5SxbQMRgfRfhrFpAwrx0qIjXXEDFxZOR1k1eQBO818RdnVVAd83urWUGW0B80ygFOANbQKHS8a92kVdA9LAIWtaaX0C0ppRDJBlgQM8ZdLwH5FhAKZZ+FTyWXEARcXovLg9VQDOhYYolY15ARw7mc8gIYUDAlPScl85XQBoMj6ifWl5A2Y3aMzDuXUAA6Ps49YVWQDlssnpdjl9AAubvEYNDXkC7DuDSjeheQFh8w0CFIl9Ab98rDQx8WUBY/ky+nPBaQLrSfugUn1VA/tFybVNNYEAwKQnJ+LVXQCUGM9lV/l5AW7fC8H4pXkAIG0w93DFeQHtxqBElX1hA96Gig5NHWUAgrkizKcldQMXEavlmU1pAkcHJjEykXkB0X3f/LwldQCny/4Zp/F9AvuDWiZN5V0AN9r+UlLxbQDa6YXowL1tAsr1jW4eOXkD1uXAXTchZQC/G1dsMDFpAIHpKb1jrV0AY3bckBUlaQNu4CqrgIVtARYcTrj+HW0D7BsHbB95YQPaXB1PiCF1A5jBMXfY4XUDFIhLeNQFfQANLqqjhPF5AGG0cTXfAXEDUf+aHgkdbQKTqkrAt51dAFY1s+AuwWUC0+0pyIj5gQIXiUz2QbFZA5zPLADZWYUDy9I0I0mJcQD6iU06eG1hAzECOfoYSVkAxEMdn1PlYQFIrsLbELltAGTU1ehI2VkCokDgW1oJXQGY1DsDiAl5AXOYPrHh9VkCInnOAFdBdQPSbOsNYa1hAKcftAq7DYkAP+9eyysBaQFCnHcQOQlxA6nHk2C48V0BtHQPlsxlfQJ1csJWuUFtATMwhEM4aUEAIDCrXzg5fQC7MF7/sJFRACSljayMFXkAD7YLsTplcQKBA2YFuDWFABsYEPyakXkAERiDmWbRaQG1oyaN2U1xA1RaYc25hWEC5alzbxAZiQJOG40hrdltAFxSIrQUnXUD+h3lngN1bQBisk517UFxAUW1GMvXXXkByLbMCCL5WQLO9l8uQu1pAlam+K+p3V0BbK7yFvYZZQO9rXtEpHllAFUdGHp67W0Bc89pA02BfQI3Gp/Vrs15A4WN5GFTMWkCTfukhqeBcQMjAE0onulZAfvtHNLYLWkDW6Sg9rb1ZQFB10n9AhF5AXOD8LkijWECh29A4MQBdQFrUWHVdLFpARYjdcAquWkDocqJbgsZcQNsJPmz5llZA8SqT4X88WUD28n5EY8FdQMf8BRx/iFtA2is51pTaYEB87RTmkhteQCc3reaihVhAH3g0bYA0XEDOFSkDEadcQAQS35fBwFtA/PB9VRNRV0Bedr+UpLhdQKoy9k22QlhAZiNxF1R7XkB6r4HVW9BVQO+u561r3lRAGIghSG5yWEBckfc3indYQDv7238Q5VxA6df9r9ozXkBYHkNbGFtdQNMUdpwghVpAhmtKrEHBXUB2o7MmZhFaQHHBfdKEHlhA3UdcbhLHWEAepMv2o/5ZQFi+583iI1lAmrEFYSQBXECkpk/+n4BdQC9JX+U/rF5A7k03Y+DCWkD23liOI9ZXQAFqfvswBltA0dJ8dG+oWkDyM/GICuFgQEIkTBM+UFpAnErIAMAjYECFctygKERbQD+O+oASclxAWwSCYNOgW0D0UXxlLRNZQMEHyn6VHGFAtDdsyPIgW0CC0hxNt9ZdQIX2sfB3HF5AWx0K0piJV0C/SIcJyfBZQPl6SdmBymFA0CyjmDIWUUADoBQ4PvdeQI/3S2P0IFhAvF+mxYX7X0A3519kB8BbQIJ/PjqmgFdA/9PniSQ5WUBdKSgWEx9gQFzQEsRhUF5AWT4+wkVxVkB3X7O7FXVdQOeZD2A9rVtAAmEz/jjrXUD0JXa8y3xdQNaRVRPCfV1APR7vC9uVX0DRhKbcfrhXQLNAMU4DL1tAwXbya9NGWEBleIVsVmliQHBXfbQ+0VpANoexGz2oXEDIyvWtbhZdQLvOwneHIVtAmncZlXTVYEA1SPhVqAxfQDMCo7tvdlxAKGgwaU0CYEBixKuzsgteQKFIu4gRVVdAv0RDrHBSXEBvRtnt0LdVQBs0iCZom1tAMvEwl439X0C43k0Iz3VSQCJQmvVXaVlABROwOeQJWUABE8UOctNTQCySW0C7V2BABCQi2GwFWEAiLyuPMz5bQPE92GTSr1RA44MKMI31WEA0ioVYU/ZZQDULUgCntFtAMytfo3yjXUBTbwL5O7FcQN/JMkUi/V1Aw5xpItM5XEBsl7eTL2BbQNYXgsRCb11AwSVOWsFsW0BGnVN7oDFdQNfwhyNRgllAnDrp7/m7YUC9CRJOnJlaQH0zEjRbu2FACC7p2lB+WEDCBlmkavtcQKr7t3db+19Ayi3iTegXYECXnAWtbYJgQDOXvtTrnl9AJ1Bn232OWUCVJxfcAsRYQMtWWIUaVWJAsNgrBAcXWkB0/tppHrBdQJRPiBi3NlpAQkEAG4yKYECkFkXNWLteQPZ+SlatlFlAecnOLaxKXEADwE6Iz7FhQOAJZ90Nj1xANcUL6SxsWkCHViQ6fjFdQF6FdpkGCl5AySPWjncNW0BsyFk2lIpZQJq8A5Y2hVpA9PpF/c5BXUBJOV0AS/1dQLIUVspn/FVAMN0/7YCoWUCARfIccQNhQBxMt1otY1dATIAoV7bYXkB1JH9ZnDxbQKk+OnnqsVtAyjpDN/ekXkCQNorGQjRaQHlTkGuzZV9AdfPcV8fjYUBOuQ7VlgZfQPRWdmbnIFlAbzFLzQ2QVkAZsloISFtZQCBVpFlEFF5AJoa0JrEaYUCI2nIKlf5SQDnQ1u9SfVpAHsbyCjveX0CVO6lN53BbQGzL3IzQI1NA8zUXF4N3XkDlCMM5cLlRQAtY5ZGG42BAd3l0IkONVUCJ/JlKpBNbQLmMMcRvIVFABGIgmw0yV0ACQLYIEVdaQCoJ/LmBJVdAFnj2+TNJXkDc7tvATZNXQM/WchehvllA8bClrc7RV0D1x95137ZbQAEX/pCCDWBApkY7w6woWkCPfEahRWVeQM79MOvzO1lA6rtvLzRIYEDW4+VPMpFfQMCuzYrMdltAVJidBdVhXkBSRkamDZZdQFRAb47QiFJAzDNGIVQOW0CMd93aBqBhQA2QHQ2E+FxAjTfK4HRjWEAvoWfiU+JVQCz8tKUukWBAjzNnmRSXVUCswCAMAzhZQIXE7K5VcFpAGkWb0MgCXUCGZdEKjxhaQA5/mnviOVtAbasvBgdzWUDBLMdVplhcQMaXAaM+rl9ARO7FcWKmT0BHTYscqKxeQJ2SQdRR7llAW/Xnyd+rYUBpXmy3cU5VQPipWlnVeGBATK/lo794XkCI5w5YwFxhQEMy3dO9GlxAuhZUGEBGWEBkp4g0GT1UQHIoxY1kV11AiGaza5/EUkDEcShad1pWQPOeMD+L1VtA186mmItYW0Cl28kI8bFeQDgm+FK88FZAvlAps7ehX0AuLpqJIoBcQEs9UZzc9FdA4eJw6ZH4XEBAlHkNePlbQPKRYfC0QVxA+WYHvZV1WUCjiapC6nthQL/AuVg7d11ADI8O1zfBX0AOxPjr6ZhWQNg3HByvhVlAirhzGGroWECex7iOq8leQDyiwL9XJl5AlCHPg6WkW0BUtRDr8qJfQIwYlqi2mFdA5iuHCvSlYEB+2COV4opWQGHcmFN0tFpAAuh3cjNcX0AhWZO0o4pbQGBAMenxI1xA2GYD885WYUDmqgOiFlRXQJvzG/OOEmFAUXHeLCscWkBeWATPwypgQJ9JLF4VyFpAm1/fkpzeXkBVDI1LXNxaQLVeQiyvsVxAWPPXlpuQWEBeslS7zRdZQHg0DZHiylpAof8JE5scXEBYPdYvdM1aQDpHCT3m6VtA6F3tU0ogXUD1/3W87VtcQNTav4sDd11ARDjh7qnYW0BHDNPc5DtaQDlpfhLA2ltAfQ3e96BnW0CSqiqPkVJXQLttT0dG7FhA+dWapT8tXUDonrjhxLBdQII9jXcti15AnSpCAHGkXECIPsJZfCtcQBM6e7y6qldA47T1mlBHV0BQ6ZOhiCthQKqjZEgni2BABdEShcLMXkDhCgL2YnFbQJyJbzoNyl9Av3BFMF95XUAHu2rhN1xeQLP5l3yEFGBAmj0E7WTVWkBnE1eeaXtaQL2Ndeo0nV5Ah2tGO6XPXkDqEYvOtvtYQH94NOum6FpAIY37TPziXEDXK9padMJfQJHdDK5+TVlA9Ir+mar/XkA8lq8vsGVWQJiWxmnBwF5AUb0CvBWTWEAjV52mfVBYQHj4VTtWu19AkbSjycUaX0ClIUY81wJcQKgIIMRwx1hAEa0KgdtCWkDp7zzbbkthQI5LpBXKhl9Ae6zm9yvuXkCxgkbqivBaQNQ50H9Qm1VA8fI+AKCOW0BYWrD4RpldQNb3jbl1U15AeuitHIEaYECnB0+DIq9bQMnQoHdjjV9AjURtUCgcX0AlDJ3/Z8hXQLYUIo5FzlxAKKQFwaYNYUCZoGQOk4tWQOe49eqQk1VAu7eX7ASqWkDY6zUAXe9cQIFGSWBJ1FpAo+O7IURQXED3YqkLB69iQCLxxTVlal5Ae8d+NagLYUDWDTIHPNNcQBeyC08VQVhA7l0vokDYWECrUh3GDzRbQLuD9gticWJAn+ufDTiRXUCduxLyQSRdQKk5RymL2ldA+nrZnLTxU0C50NQv+LxcQBPVLsNrNmFAsdjPQfEbVkDtw/JSa7RdQM3xR6coB1lAYpr34lDtWkBY1I6nx8deQDfX8rJ35FRAUgJXCEIPXkCoDoZ7sHZgQOIpP6OoH1lAYdS6LgknWkDMAEv26EtcQEB9Uf4uEVpASzkdkJh5W0ANZOKjBL5bQD4yzKKUx11ARWaRNPIAWkBCQufr0RNXQHBPtf9gUl5AYcT87ckOW0D8Zopxf2FbQEcSxtBm9llA3EXJ7hiyWUD/zmzFtHpXQCpApaB+KFxAuXhtNTKwWUBr3JVtllBcQIhdJLGN0lpAz3aCOwlxXUACuxXj3xBcQNsjU//Re1tAJx6iU7QxYUDIC0LvY4NdQDgEFiYt1l1A9kuCSXMAXUB4GtnM0/BYQCTq7Qp4LFlAV+potu49XECGiFjLsKBgQKwd3PKKcllAM7jPin8dX0BxDOdUE3tVQOqoL4dGwFxA07hZal0jVEAUd/zprjlbQA6Qb8wvL1pAb8b0geMAW0CEoghGRltaQKyvOd6h6l9AHoUCMNqJXUB7RlZarHZWQLarFp6zLGFAHWUVeqQeXUA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1757\"},\"selection_policy\":{\"id\":\"1756\"}},\"id\":\"1526\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1721\"},\"selection_policy\":{\"id\":\"1720\"}},\"id\":\"1418\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1787\"},\"selection_policy\":{\"id\":\"1786\"}},\"id\":\"1616\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1700\"},\"glyph\":{\"id\":\"1702\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1703\"},\"view\":{\"id\":\"1705\"}},\"id\":\"1704\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1801\"},\"selection_policy\":{\"id\":\"1800\"}},\"id\":\"1658\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1799\"},\"selection_policy\":{\"id\":\"1798\"}},\"id\":\"1652\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1694\"},\"glyph\":{\"id\":\"1696\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1697\"},\"view\":{\"id\":\"1699\"}},\"id\":\"1698\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1715\"},\"selection_policy\":{\"id\":\"1714\"}},\"id\":\"1400\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"nu+nxks3yT+YbhKDwMrpPzvfT42XbtI/EoPAyqFFxj93vp8aL93gP166SQwCK+s/BoGVQ4ts4z9YObTIdr7XP8l2vp8aL+U/7FG4HoXroT97FK5H4XqkP2IQWDm0yOI/Gy/dJAaB5T/hehSuR+G6PyPb+X5qvOQ/b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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1723\"},\"selection_policy\":{\"id\":\"1722\"}},\"id\":\"1424\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data\":{\"__ECDF\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1793\"},\"selection_policy\":{\"id\":\"1792\"}},\"id\":\"1634\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1745\"},\"selection_policy\":{\"id\":\"1744\"}},\"id\":\"1490\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1652\"}},\"id\":\"1657\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1805\"},\"selection_policy\":{\"id\":\"1804\"}},\"id\":\"1670\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1747\"},\"selection_policy\":{\"id\":\"1746\"}},\"id\":\"1496\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1717\"},\"selection_policy\":{\"id\":\"1716\"}},\"id\":\"1406\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1406\"}},\"id\":\"1411\",\"type\":\"CDSView\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0.1},\"line_color\":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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1749\"},\"selection_policy\":{\"id\":\"1748\"}},\"id\":\"1502\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1442\"},\"glyph\":{\"id\":\"1444\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1445\"},\"view\":{\"id\":\"1447\"}},\"id\":\"1446\",\"type\":\"G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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]}},\"selected\":{\"id\":\"1725\"},\"selection_policy\":{\"id\":\"1724\"}},\"id\":\"1430\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.01},\"fill_color\":{\"value\":\"#1f77b3\"},\"line_alpha\":{\"value\":0},\"line_color\":{\"value\":\"#1f77b3\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"__ECDF\"}},\"id\":\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x_axis_label=\"spindle length (µm)\",\n", " marker_kwargs=dict(alpha=0.01, line_alpha=0),\n", ")\n", "for ell_vals in ell[19::20]:\n", " p = iqplot.ecdf(ell_vals, p=p, marker_kwargs=dict(alpha=0.01, line_alpha=0))\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This looks reasonable, except for the occasional negative spindle lengths. We will investigate treating these in a moment.\n", "\n", "Another option for display is to plot percentiles of the ECDFs. We can do this using the `bebi103.viz.predictive_ecdf()` function. It expects input as a Numpy array of shape $n_s \\times N$, where $n_s$ is the number of samples and $N$ is the number of data points. This is exactly what the variable `ell` is now." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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ryHjkJkCCR2vIeOQmQMiZJ+v0BCdAyJkn6/QEJ0CMPN26WBQnQIw83bpYFCdAiMnwaOYeJ0CIyfBo5h4nQLinBeQrICdAuKcF5CsgJ0Bs9wJJ4yonQGz3AknjKidAfKHxzdA0J0B8ofHN0DQnQKjtQMr0OCdAqO1AyvQ4J0DuOI/67l0nQO44j/ruXSdA7+PfpixeJ0Dv49+mLF4nQDfOLfWIXydAN84t9YhfJ0D5ebUqP2AnQPl5tSo/YCdAsmuVlTtxJ0Cya5WVO3EnQIRv0WeKiydAhG/RZ4qLJ0D+tkOGWpsnQP62Q4ZamydAZg3EQa+xJ0BmDcRBr7EnQLaVfBaHwSdAtpV8FofBJ0B0b8sAHsgnQHRvywAeyCdAomGeSNTMJ0CiYZ5I1MwnQH5w9+fpzSdAfnD35+nNJ0D8GPJo+N8nQPwY8mj43ydAdxSBbXDgJ0B3FIFtcOAnQGCWXXhc4SdAYJZdeFzhJ0Aga1gs2uInQCBrWCza4idA8OT3pNbmJ0Dw5Pek1uYnQPwuD9Cu9idA/C4P0K72J0ARviGjs/wnQBG+IaOz/CdA5UnLKBoZKEDlScsoGhkoQEbiLKlhJShARuIsqWElKEDol3U4dC4oQOiXdTh0LihARol05rNAKEBGiXTms0AoQIeJ4AePUyhAh4ngB49TKEAKx4P++VYoQArHg/75VihALKNuoQxgKEAso26hDGAoQC7rAIDGeihALusAgMZ6KEDk5j+0MIQoQOTmP7QwhChAgGrygJCUKECAavKAkJQoQDc4pNwfmyhANzik3B+bKECMfnoNqqEoQIx+eg2qoShAdmgNL3nDKEB2aA0vecMoQH2G+fbIAilAfYb59sgCKUAUP8BM6RYpQBQ/wEzpFilAQH8h4Lo9KUBAfyHguj0pQFmgWX5AWilAWaBZfkBaKUDAeDzSel0pQMB4PNJ6XSlAglMJfBVlKUCCUwl8FWUpQLZtYzMXcClAtm1jMxdwKUB2UInFf4EpQHZQicV/gSlAjM2vaOWVKUCMza9o5ZUpQFRRmjDSqilAVFGaMNKqKUCIuNr5gLEpQIi42vmAsSlAngyfKg24KUCeDJ8qDbgpQKCr0Cv7wSlAoKvQK/vBKUBqOmViu+MpQGo6ZWK74ylA1FZv2Ej6KUDUVm/YSPopQIIPK+mXCipAgg8r6ZcKKkDeV8sVmBMqQN5XyxWYEypAdGIMZeMgKkB0Ygxl4yAqQO3/6K8cTSpA7f/orxxNKkCMhql49VcqQIyGqXj1VypAhoBuy11tKkCGgG7LXW0qQFwtqIzQfCpAXC2ojNB8KkCMFn3sx5cqQIwWfezHlypArvN9OtWrKkCu83061asqQARNcFMJsipABE1wUwmyKkBS075eN7MqQFLTvl43sypApOHM3ijGKkCk4czeKMYqQKzTJVLozSpArNMlUujNKkDMi2m7uc8qQMyLabu5zypAVvWbFtrXKkBW9ZsW2tcqQBKahoEJ4CpAEpqGgQngKkCuI8bMGOEqQK4jxswY4SpAhKBXZ7nhKkCEoFdnueEqQL6U5kMG7CpAvpTmQwbsKkBSVB3/0OwqQFJUHf/Q7CpAh8MtkAT+KkCHwy2QBP4qQJS6grolACtAlLqCuiUAK0CQOoo22EUrQJA6ijbYRStASQ+BjsVGK0BJD4GOxUYrQHIgsNeHVCtAciCw14dUK0Dp2DrlulwrQOnYOuW6XCtACmE+s8x9K0AKYT6zzH0rQP6BueItiitA/oG54i2KK0D8unR7ZJcrQPy6dHtklytA1Yg1+We0K0DViDX5Z7QrQOm9CdL3wCtA6b0J0vfAK0Cje4bOFsMrQKN7hs4WwytAEYP85drEK0ARg/zl2sQrQFdhmbENxitAV2GZsQ3GK0AGCe3olMkrQAYJ7eiUyStA8lb9aZXMK0DyVv1plcwrQHBp2lkY1StAcGnaWRjVK0A2O2YWnNYrQDY7Zhac1itAhlri8YzZK0CGWuLxjNkrQF4VhAbg2itAXhWEBuDaK0CcWeSQidsrQJxZ5JCJ2ytAfITPRNX2K0B8hM9E1fYrQOYHpFN5BSxA5gekU3kFLEAhiR+i6AcsQCGJH6LoByxAPHlXvg8JLEA8eVe+DwksQMx99M+jJixAzH30z6MmLEBSSZshYDEsQFJJmyFgMSxAgG8gdCgzLECAbyB0KDMsQIZEqm+DTyxAhkSqb4NPLEB1OfmjB1IsQHU5+aMHUixAdMFYPphVLEB0wVg+mFUsQMvLv9TpWSxAy8u/1OlZLEA6tX4hSVwsQDq1fiFJXCxA/hlHOFJjLED+GUc4UmMsQOJWutlfaCxA4la62V9oLEBmFUZ02X0sQGYVRnTZfSxAx8QBEgOULEDHxAESA5QsQEGW5LlQpCxAQZbkuVCkLECGjKI5G6UsQIaMojkbpSxAyGZdOLKpLEDIZl04sqksQDZUrc5YrSxANlStzlitLECiKv1gG68sQKIq/WAbryxARvGsYFOwLEBG8axgU7AsQLZT8wmbsyxAtlPzCZuzLEAdABffL7QsQB0AF98vtCxABlnr6Sa7LEAGWevpJrssQDKhhRe3uyxAMqGFF7e7LEBSr85EY74sQFKvzkRjvixACpBgzXW+LEAKkGDNdb4sQJDTdiZN2yxAkNN2Jk3bLECs7aBlP+MsQKztoGU/4yxA3NQQsPTjLEDc1BCw9OMsQD4eugkY6yxAPh66CRjrLECg79nBvussQKDv2cG+6yxA/ibUQDbvLED+JtRANu8sQKcRvERbAy1ApxG8RFsDLUCcCV7PgBAtQJwJXs+AEC1AAYdtsEQ3LUABh22wRDctQBaMc4zlNy1AFoxzjOU3LUBWottN8UQtQFai203xRC1AjhDZvgZfLUCOENm+Bl8tQP4IvyPKZy1A/gi/I8pnLUDKTtUJq4ctQMpO1Qmrhy1AfK29/q+PLUB8rb3+r48tQATMj61ZoC1ABMyPrVmgLUBD8pM2VKEtQEPykzZUoS1AMtUaaWajLUAy1RppZqMtQGoS3hO3xi1AahLeE7fGLUDg1MDk8sstQODUwOTyyy1AU2X/i7DRLUBTZf+LsNEtQBK4rRsr1i1AEritGyvWLUAiMU1OE9gtQCIxTU4T2C1AINDXRWHhLUAg0NdFYeEtQCorbaJu5y1AKittom7nLUDyJSXeB/YtQPIlJd4H9i1A1mGL3uL8LUDWYYve4vwtQEwX5sHyEC5ATBfmwfIQLkCHaaJcSh8uQIdpolxKHy5AkHeEckQwLkCQd4RyRDAuQECaYjJVOi5AQJpiMlU6LkAABzOUoT0uQAAHM5ShPS5A2vA4iCFGLkDa8DiIIUYuQHVqQMNQSi5AdWpAw1BKLkBTFCxGS0wuQFMULEZLTC5AEPDYU5BuLkAQ8NhTkG4uQHam41uPdi5AdqbjW492LkAa42sxp4ouQBrjazGnii5Az1eJBOSXLkDPV4kE5JcuQM4Yald2qC5AzhhqV3aoLkDgaOlKoLMuQOBo6Uqgsy5Ann/lNfK/LkCef+U18r8uQPOrQh4Dxi5A86tCHgPGLkD1iw3DysYuQPWLDcPKxi5AZArqKlzbLkBkCuoqXNsuQN5k1/yZ4C5A3mTX/JngLkBKcKK07ecuQEpworTt5y5ARGu7t7jzLkBEa7u3uPMuQHJRKinX/y5AclEqKdf/LkAj/uBfYgovQCP+4F9iCi9A6pwcsasLL0DqnByxqwsvQENR91qUDy9AQ1H3WpQPL0DucWkpWhovQO5xaSlaGi9Ah1x9tnEeL0CHXH22cR4vQMbzMO5vIi9AxvMw7m8iL0DLGoUJCTEvQMsahQkJMS9Amb63pdQ6L0CZvrel1DovQDCe5d4LPy9AMJ7l3gs/L0DIHetAHkQvQMgd60AeRC9AJFEg9CBUL0AkUSD0IFQvQGVgJucjaS9AZWAm5yNpL0DC8KcZcHAvQMLwpxlwcC9Ajyji+36EL0CPKOL7foQvQCSvT+Umji9AJK9P5SaOL0DP321jhbEvQM/fbWOFsS9AA62Iw56+L0ADrYjDnr4vQHxQ3A8C1C9AfFDcDwLUL0CAbiNynOIvQIBuI3Kc4i9AZiH1LYv0L0BmIfUti/QvQKLFs/FhADBAosWz8WEAMEAWyhDRfQkwQBbKENF9CTBARawnJJ0QMEBFrCcknRAwQG6yKk0aIzBAbrIqTRojMEBSyYNmjC8wQFLJg2aMLzBAS7FK8pUyMEBLsUrylTIwQK4ko9BYNTBAriSj0Fg1MECwovOmcDowQLCi86ZwOjBAgkhpzP08MECCSGnM/TwwQF4YG7pHQjBAXhgbukdCMEByqy5J0EUwQHKrLknQRTBAYgVz23VKMEBiBXPbdUowQAsXmrsIWDBACxeauwhYMEDc9F702lowQNz0XvTaWjBAXm7tTlFfMEBebu1OUV8wQN7UYim8ajBA3tRiKbxqMEBQXsJMh4AwQFBewkyHgDBA0hlDWBKFMEDSGUNYEoUwQGPNlJgZiTBAY82UmBmJMEDqxQ7a2oowQOrFDtraijBAwKoGfiGMMEDAqgZ+IYwwQMM00UnBjjBAwzTRScGOMECoqDTmQpMwQKioNOZCkzBAZGxJO2mVMEBkbEk7aZUwQHuw0naZmDBAe7DSdpmYMEBYISY5TJ0wQFghJjlMnTBAkKCqGLOfMECQoKoYs58wQLpTsolCoTBAulOyiUKhMEBqmCYvhKEwQGqYJi+EoTBA8l//fwGoMEDyX/9/AagwQGYB1VNErzBAZgHVU0SvMEACHLzRbrIwQAIcvNFusjBAkJCJlyG6MECQkImXIbowQMJhvjOQujBAwmG+M5C6MEC7MFny28QwQLswWfLbxDBAgWZ/N93JMECBZn833ckwQAXJHdJ81zBABckd0nzXMECG3izcUd8wQIbeLNxR3zBAEvaVpPDnMEAS9pWk8OcwQIIxnsdU7jBAgjGex1TuMEDA930Y0/AwQMD3fRjT8DBAsROjhmz/MECxE6OGbP8wQODx74gZAjFA4PHviBkCMUA1CalIQggxQDUJqUhCCDFAu8QR5scNMUC7xBHmxw0xQJQQH7ZxDjFAlBAftnEOMUCNVQhvrxAxQI1VCG+vEDFAThN+5rEdMUBOE37msR0xQJgw8vAUHzFAmDDy8BQfMUBpExziJCAxQGkTHOIkIDFAojCmlFEhMUCiMKaUUSExQHfNmXwrKDFAd82ZfCsoMUA5TuDTkTgxQDlO4NORODFA/CCEHCI7MUD8IIQcIjsxQPqjucltRDFA+qO5yW1EMUCubEltqEQxQK5sSW2oRDFARuFtwmRQMUBG4W3CZFAxQKqi47yzVTFAqqLjvLNVMUAsnev1tVkxQCyd6/W1WTFAQtckVFtcMUBC1yRUW1wxQAQIcxCiYjFABAhzEKJiMUBoo5xaEmUxQGijnFoSZTFAhz8RxltpMUCHPxHGW2kxQN75dp9cazFA3vl2n1xrMUAmB2rfD24xQCYHat8PbjFAJPRNgO5vMUAk9E2A7m8xQMgvcYlJcDFAyC9xiUlwMUAWUidgcnQxQBZSJ2BydDFAYQBi7Wl4MUBhAGLtaXgxQI5fWr9xeTFAjl9av3F5MUD+yq4yhnwxQP7KrjKGfDFAvvHxbE2AMUC+8fFsTYAxQAiNxiAhgjFACI3GICGCMUD87if4eYUxQPzuJ/h5hTFAAA2O14eHMUAADY7Xh4cxQB5ypeRiizFAHnKl5GKLMUBcGRJ6/o0xQFwZEnr+jTFAsRMoOoyOMUCxEyg6jI4xQJAN6nP7kDFAkA3qc/uQMUCw6XQp4JMxQLDpdCngkzFAoZ5uhySYMUChnm6HJJgxQBGIcSZ7nDFAEYhxJnucMUCwxON9pqAxQLDE432moDFABogy9fSuMUAGiDL19K4xQE7r+h73tDFATuv6Hve0MUCjQRIE1bUxQKNBEgTVtTFAZot8YyC+MUBmi3xjIL4xQHD67YgyvzFAcPrtiDK/MUCPJrasicIxQI8mtqyJwjFAPKuI2LPGMUA8q4jYs8YxQAQ+oviryTFABD6i+KvJMUCNEwSAlsoxQI0TBICWyjFAmmb2RHvMMUCaZvZEe8wxQFjj7/XY0TFAWOPv9djRMUAASJf2UNMxQABIl/ZQ0zFAuM76HgzdMUC4zvoeDN0xQI5z4BV24zFAjnPgFXbjMUDsqgjd9uYxQOyqCN325jFAkg1KjlLtMUCSDUqOUu0xQFD9rXQC8jFAUP2tdALyMUAT0yzu4/0xQBPTLO7j/TFA6qJVgLUAMkDqolWAtQAyQI1fU2UiETJAjV9TZSIRMkAUnkX7AhQyQBSeRfsCFDJAetO+ckUYMkB6075yRRgyQLopx/o4GTJAuinH+jgZMkDsXBp1RRwyQOxcGnVFHDJANXgv95wmMkA1eC/3nCYyQMihMJeJMDJAyKEwl4kwMkCWKxvf3jEyQJYrG9/eMTJALPFCnFAzMkAs8UKcUDMyQDkkCTjOOTJAOSQJOM45MkAJOad+FkMyQAk5p34WQzJA3CIwCuJFMkDcIjAK4kUyQFc5rYV2SzJAVzmthXZLMkAADpNWsE8yQAAOk1awTzJA6oo/DxVRMkDqij8PFVEyQC42gbXOUzJALjaBtc5TMkBLHTa0KVYyQEsdNrQpVjJAm4kdizpbMkCbiR2LOlsyQFgP9cYGYzJAWA/1xgZjMkAzfk3wcWcyQDN+TfBxZzJAAngAwcJpMkACeADBwmkyQPw3KFN2ajJA/DcoU3ZqMkBWZYRIj24yQFZlhEiPbjJAINRxa8xzMkAg1HFrzHMyQLQMz5g9dzJAtAzPmD13MkDkrcBpc3wyQOStwGlzfDJA6jTymjKAMkDqNPKaMoAyQB2qONOLgzJAHao404uDMkCvpHg9d4gyQK+keD13iDJA9AgKueyQMkD0CAq57JAyQHwPadL7mTJAfA9p0vuZMkAM9Id5TJwyQAz0h3lMnDJADLeBZOGgMkAMt4Fk4aAyQMZAmxq1pzJAxkCbGrWnMkAQVPxKTKsyQBBU/EpMqzJAe88xMfOsMkB7zzEx86wyQFHGT6hRrjJAUcZPqFGuMkDmaJVxmrIyQOZolXGasjJArLJlY7OyMkCssmVjs7IyQO/3yDFKtTJA7/fIMUq1MkCdQGBuvcEyQJ1AYG69wTJAdMMXTrjCMkB0wxdOuMIyQG78a/UhxTJAbvxr9SHFMkCBr/koMMcyQIGv+SgwxzJAfNpwdz3JMkB82nB3PckyQBEoFonhyjJAESgWieHKMkAWg4ULVcwyQBaDhQtVzDJAW8tx75bOMkBby3Hvls4yQBDuFb2S0jJAEO4VvZLSMkAWWloEy9UyQBZaWgTL1TJAqM0s90DbMkCozSz3QNsyQOGZ3M0y3jJA4ZnczTLeMkCOKFYFR+cyQI4oVgVH5zJA3mmztX7pMkDeabO1fukyQPXb+N6t7TJA9dv43q3tMkDyT/d0HvEyQPJP93Qe8TJAqSUQTEf1MkCpJRBMR/UyQHfuwAng+DJAd+7ACeD4MkAPfAPqaPwyQA98A+po/DJAFqJsA5wDM0AWomwDnAMzQF4ZDU2CBDNAXhkNTYIEM0BrfsB02gczQGt+wHTaBzNAxzznvwUJM0DHPOe/BQkzQPZPR35gFTNA9k9HfmAVM0AEuSxsehgzQAS5LGx6GDNAUgmXsHwaM0BSCZewfBozQCbx6jMkJTNAJvHqMyQlM0AKlSJ48ikzQAqVInjyKTNAOALKLXE1M0A4AsotcTUzQAkwZNHsQzNACTBk0exDM0CGX04+WkYzQIZfTj5aRjNA+c0TSGZNM0D5zRNIZk0zQOV28jqUTjNA5XbyOpROM0Dy+3Re008zQPL7dF7TTzNAeDxRfcdSM0B4PFF9x1IzQAEJtQdoUzNAAQm1B2hTM0DmMeLY5lUzQOYx4tjmVTNAqrK/8xtYM0Cqsr/zG1gzQFZwgN4/XDNAVnCA3j9cM0Dm4syDFGQzQObizIMUZDNA0HWHTA1oM0DQdYdMDWgzQGoeJ81VazNAah4nzVVrM0BovHXlyXEzQGi8deXJcTNAJ2zPfylyM0AnbM9/KXIzQEREgomvczNARESCia9zM0CZIhCEknQzQJkiEISSdDNAHjhjSAF5M0AeOGNIAXkzQDjS2rpafTNAONLaulp9M0B2tWIjMIczQHa1YiMwhzNAybO04qyNM0DJs7TirI0zQMoqFxyQkTNAyioXHJCRM0DjhYswCZIzQOOFizAJkjNAfALTWBuTM0B8AtNYG5MzQNeiO6jelDNA16I7qN6UM0DhoyHLO5gzQOGjIcs7mDNAdOTOkqWhM0B05M6SpaEzQD6LF4JopDNAPosXgmikM0D4DqFLDKczQPgOoUsMpzNA1LlutEarM0DUuW60RqszQECL0IqlrDNAQIvQiqWsM0B4kOdXX68zQHiQ51dfrzNANCpALhK2M0A0KkAuErYzQM5yP7qguzNAznI/uqC7M0A7JAOas8IzQDskA5qzwjNAGN0Gh8TEM0AY3QaHxMQzQKQLCVQFxjNApAsJVAXGM0BCvFeB4MwzQEK8V4HgzDNA77VndBPWM0DvtWd0E9YzQPK+NKrG2jNA8r40qsbaM0C4siv+td8zQLiyK/613zNAkipYsSbjM0CSKlixJuMzQAiSBOVI7TNACJIE5UjtM0DQg5oXBvAzQNCDmhcG8DNAImXo/mf0M0AiZej+Z/QzQLwLJEdt9zNAvAskR233M0CUuBNjsv4zQJS4E2Oy/jNAldm/T4UCNECV2b9PhQI0QIJ6c2yECDRAgnpzbIQINEAg1x/PJA80QCDXH88kDzRAcAQ9OfUPNEBwBD059Q80QMHINqV7EzRAwcg2pXsTNECgaDNDuRc0QKBoM0O5FzRAqL1OfYYeNECovU59hh40QA5lIRXfHzRADmUhFd8fNEBQGqgKuiA0QFAaqAq6IDRAkRsf/lskNECRGx/+WyQ0QIIyxcO/KzRAgjLFw78rNEDCc9nG8Dg0QMJz2cbwODRA2RAlxpM8NEDZECXGkzw0QC70N484SDRALvQ3jzhINEBu1XoJh000QG7VegmHTTRArNT+quVQNECs1P6q5VA0QPAfNowtWTRA8B82jC1ZNEDYA1fsUl80QNgDV+xSXzRATuuE22hiNEBO64TbaGI0QIqH/9S4ZDRAiof/1LhkNEBWMXLmh2U0QFYxcuaHZTRARFpBki9mNEBEWkGSL2Y0QE+y3dT2aDRAT7Ld1PZoNEBa2t8O+Gk0QFra3w74aTRAas3kKLtrNEBqzeQou2s0QHT2LC51bzRAdPYsLnVvNED9uX9LyHI0QP25f0vIcjRAJpnauglzNEAmmdq6CXM0QHbnw60ieDRAdufDrSJ4NEBINvyrM3k0QEg2/KszeTRAFI3i8ox/NEAUjeLyjH80QFLg8OCugTRAUuDw4K6BNEC5rkRAE5Y0QLmuREATljRA9uUtPa2dNED25S09rZ00QGxAf5StoDRAbEB/lK2gNEAhxZOmGKM0QCHFk6YYozRAkFZBaniyNECQVkFqeLI0QK8yvP8hvjRArzK8/yG+NEAAUvFY6sA0QABS8VjqwDRAZnRA4qrBNEBmdEDiqsE0QNLQmewMxDRA0tCZ7AzENEBb1WJyMMw0QFvVYnIwzDRArXEfXoPPNECtcR9eg880QB0bv3121jRAHRu/fXbWNEAqrINFGd80QCqsg0UZ3zRAAA2oIsXlNEAADagixeU0QFJeXvMt8zRAUl5e8y3zNEBgGZeP5fs0QGAZl4/l+zRA3G5uWR4ANUDcbm5ZHgA1QBKm4CnRBjVAEqbgKdEGNUAMTzZ2+gY1QAxPNnb6BjVAou5iJRkINUCi7mIlGQg1QIDVUoWfDTVAgNVShZ8NNUA6t1jqxRU1QDq3WOrFFTVAwt3kntYVNUDC3eSe1hU1QNSXSw8zFjVA1JdLDzMWNUC1hrpOYhY1QLWGuk5iFjVA1uEd0GEaNUDW4R3QYRo1QDSq2FqPHDVANKrYWo8cNUB02DxGyhw1QHTYPEbKHDVAKkIkYYkdNUAqQiRhiR01QA2cFWDLITVADZwVYMshNUBuyhv3gSc1QG7KG/eBJzVAkDhFsOYoNUCQOEWw5ig1QALYDesUKjVAAtgN6xQqNUBGeHoHjio1QEZ4egeOKjVAVCO69MIrNUBUI7r0wis1QP1QpYvUMDVA/VCli9QwNUD0aXZlQjM1QPRpdmVCMzVAmVUy9bNDNUCZVTL1s0M1QOj+B7hlRTVA6P4HuGVFNUBotyFo2001QGi3IWjbTTVA1HsYm4tONUDUexibi041QBZNWYrxWDVAFk1ZivFYNUCuhZD2Alo1QK6FkPYCWjVAvHyw6eFlNUC8fLDp4WU1QB5fO0kWbjVAHl87SRZuNUDe0R6xN4Q1QN7RHrE3hDVAury8mZGGNUC6vLyZkYY1QHDd9RYjkTVAcN31FiORNUDL9Jnqz5I1QMv0merPkjVAGrtkgmWXNUAau2SCZZc1QOjvHfYepjVA6O8d9h6mNUBXp7nubKg1QFenue5sqDVAem+XjG2tNUB6b5eMba01QBeWtb+mtDVAF5a1v6a0NUDe2XN6x7k1QN7Zc3rHuTVA/pQe26O9NUD+lB7bo701QMyPRWg6vzVAzI9FaDq/NUCiOqk/icA1QKI6qT+JwDVAYv9EIhTRNUBi/0QiFNE1QHQYF0X/0jVAdBgXRf/SNUD0nHa6aNY1QPScdrpo1jVA8xh4WUnXNUDzGHhZSdc1QB75SEkF2DVAHvlISQXYNUCg3wKh3+k1QKDfAqHf6TVAqJedDvL+NUCol50O8v41QFnEo4bcAzZAWcSjhtwDNkAVm6qoAA02QBWbqqgADTZAyrYMh4wPNkDKtgyHjA82QKlkIS08FDZAqWQhLTwUNkAo05KRsRQ2QCjTkpGxFDZAQb6kl7oUNkBBvqSXuhQ2QHJLO33IFDZAcks7fcgUNkC7x60HERg2QLvHrQcRGDZALmAJHwQZNkAuYAkfBBk2QBIBoO10KDZAEgGg7XQoNkCbCb8GXSo2QJsJvwZdKjZAIEZ7AWIrNkAgRnsBYis2QN3zIDCMLTZA3fMgMIwtNkD4PwGiCjo2QPg/AaIKOjZApFzwSutCNkCkXPBK60I2QIpGrSiSSDZAikatKJJINkDICo4CAUs2QMgKjgIBSzZAn3eENmpYNkCfd4Q2alg2QLRI5AxMXTZAtEjkDExdNkAeXRSAJGA2QB5dFIAkYDZAor3Cq5RtNkCivcKrlG02QPhX8YaIfDZA+Ffxhoh8NkDZ79Wen4g2QNnv1Z6fiDZAyM4O1UuSNkDIzg7VS5I2QFlPzOP+ozZAWU/M4/6jNkCwVQvLtqU2QLBVC8u2pTZA8lRGjX2sNkDyVEaNfaw2QNa0y/nVsTZA1rTL+dWxNkCwjMcNKbY2QLCMxw0ptjZA9mYCdZi6NkD2ZgJ1mLo2QL6yFItVwDZAvrIUi1XANkDgFZrmZcU2QOAVmuZlxTZA2swL1oDSNkDazAvWgNI2QF5y9XPK4DZAXnL1c8rgNkCiA7geDeg2QKIDuB4N6DZAK8RjUC/pNkArxGNQL+k2QOsj9NQh7jZA6yP01CHuNkBdU8fiAO82QF1Tx+IA7zZA/x+7AXTvNkD/H7sBdO82QK75+6pL8DZArvn7qkvwNkBC3CGIDfU2QELcIYgN9TZAMBKXzCH8NkAwEpfMIfw2QBpfKu4g/jZAGl8q7iD+NkCjbjPgSwU3QKNuM+BLBTdABKgCBpkNN0AEqAIGmQ03QPb8GttfHzdA9vwa218fN0Cos7Qm0SY3QKiztCbRJjdAbrISC7EnN0BushILsSc3QDtyiwOCKTdAO3KLA4IpN0Ds3SPyBC43QOzdI/IELjdAaTGig9I1N0BpMaKD0jU3QPC6OKJmODdA8Lo4omY4N0CO4XnD6jk3QI7hecPqOTdA6tVTJKU6N0Dq1VMkpTo3QOoOGwCHRzdA6g4bAIdHN0CwqPkzbks3QLCo+TNuSzdAKg+GDfxNN0AqD4YN/E03QJ8eN/L9UTdAnx438v1RN0BsacLZwFc3QGxpwtnAVzdA/qEKWhtaN0D+oQpaG1o3QLpymoP8XzdAunKag/xfN0CIRmWwf2o3QIhGZbB/ajdAZ9gQvcJwN0Bn2BC9wnA3QAbvzgV8eDdABu/OBXx4N0BUc6Qd8oA3QFRzpB3ygDdA1VJ1LCaEN0DVUnUsJoQ3QPne1fn+jDdA+d7V+f6MN0CGzHhylpk3QIbMeHKWmTdAXdFMyeCeN0Bd0UzJ4J43QLQdMs98oTdAtB0yz3yhN0CAnqHQ7aQ3QICeodDtpDdAsmDyJlurN0CyYPImW6s3QN8ZstjetTdA3xmy2N61N0AMO7umZ7w3QAw7u6ZnvDdAPADVSPPFN0A8ANVI88U3QOSptn5lyzdA5Km2fmXLN0Cvz5mo/9A3QK/Pmaj/0DdArOhuzGDkN0Cs6G7MYOQ3QGQ3fnaS6DdAZDd+dpLoN0D6xuXveu83QPrG5e967zdAcF/CbHHyN0BwX8JscfI3QCKhnLRR9jdAIqGctFH2N0DCba3TS/03QMJtrdNL/TdA6STrtCwAOEDpJOu0LAA4QDWm5bewAThANablt7ABOECeRxlgTgQ4QJ5HGWBOBDhA4kZR20wLOEDiRlHbTAs4QB/MDqKgGzhAH8wOoqAbOEClLiJKnyA4QKUuIkqfIDhApkb5dSAqOECmRvl1ICo4QBIQgkyaLjhAEhCCTJouOEAmOBFl7C84QCY4EWXsLzhAoNUGkXg0OECg1QaReDQ4QECiniHuNjhAQKKeIe42OEAGHFqraDk4QAYcWqtoOThAVjwCfQA+OEBWPAJ9AD44QLhR/UlBRzhAuFH9SUFHOED6eR4FF0o4QPp5HgUXSjhAGgMnV3BWOEAaAydXcFY4QKKvn3sGWDhAoq+fewZYOEDExL/rJ2I4QMTEv+snYjhAN+X63u5oOEA35fre7mg4QFy+UE3mazhAXL5QTeZrOEAuWH6u7Hk4QC5Yfq7seThALtZ/VDt/OEAu1n9UO384QPCqzQj7iDhA8KrNCPuIOEBIjDYHW484QEiMNgdbjzhAQr8XEKeaOEBCvxcQp5o4QHT+l7qBnThAdP6XuoGdOEAi+bZLnqo4QCL5tkueqjhArMgRH5myOECsyBEfmbI4QBfAA9a2tjhAF8AD1ra2OEDM0RkbBMI4QMzRGRsEwjhAuNnmDyTIOEC42eYPJMg4QCOx6du3zDhAI7Hp27fMOEB26BSarM84QHboFJqszzhAyPKjXb/ZOEDI8qNdv9k4QB7Uwn0L3DhAHtTCfQvcOEDSa6GTLdw4QNJroZMt3DhAztaRQOvcOEDO1pFA69w4QEhXba1R4zhASFdtrVHjOEALJbrCdO44QAslusJ07jhAEnqVyvnxOEASepXK+fE4QICztjWm+jhAgLO2Nab6OEAkhf5pEf44QCSF/mkR/jhAurLpKzoCOUC6sukrOgI5QCqk1caiAjlAKqTVxqICOUAFitDy/AM5QAWK0PL8AzlAoEy8vUEMOUCgTLy9QQw5QCZIlTyiDzlAJkiVPKIPOUBUojVv/xw5QFSiNW//HDlALnFW1GsrOUAucVbUays5QKXXu1skPDlApde7WyQ8OUBUXUhoQz45QFRdSGhDPjlAVv5egRtEOUBW/l6BG0Q5QEAjl8htTjlAQCOXyG1OOUBkMo4cr1o5QGQyjhyvWjlARP3nHV1iOUBE/ecdXWI5QAI5nmyUdTlAAjmebJR1OUCFyo+FAIA5QIXKj4UAgDlALInGObCKOUAsicY5sIo5QM+gNRYTkTlAz6A1FhOROUBezK+hmJY5QF7Mr6GYljlAVXlwI06iOUBVeXAjTqI5QJSpnA6spjlAlKmcDqymOUASK5dnaK45QBIrl2dorjlA5kv3bj+zOUDmS/duP7M5QCzhsDb2tTlALOGwNva1OUBtWVlPiLg5QG1ZWU+IuDlAkfMTfIe+OUCR8xN8h745QGabzLm2yTlAZpvMubbJOUBG1hLtOMo5QEbWEu04yjlAOCqjRmvMOUA4KqNGa8w5QMMsUNu92DlAwyxQ273YOUACFn42Itk5QAIWfjYi2TlA+HERtfzaOUD4cRG1/No5QBrNxTM/3zlAGs3FMz/fOUCZUKdCReA5QJlQp0JF4DlAOEhzMwfpOUA4SHMzB+k5QBmukAkc6jlAGa6QCRzqOUAMr5L8Y+s5QAyvkvxj6zlAJ/jtmoXrOUAn+O2ahes5QDSJdh8S7DlANIl2HxLsOUBEDqi4S/c5QEQOqLhL9zlAfBLcSGP5OUB8EtxIY/k5QOQPtU3O/jlA5A+1Tc7+OUDZjq7c0gQ6QNmOrtzSBDpA1GafdKINOkDUZp90og06QDRViMn+HTpANFWIyf4dOkDgQ8UAujI6QOBDxQC6MjpAMBDLxmA2OkAwEMvGYDY6QNJJQ7zgOTpA0klDvOA5OkB7QDUNdUU6QHtANQ11RTpAtmhIwxhQOkC2aEjDGFA6QGTkBmMCWjpAZOQGYwJaOkA94doEJmw6QD3h2gQmbDpAVCWaCAp/OkBUJZoICn86QP7kLr1UiTpA/uQuvVSJOkBRtjUgG446QFG2NSAbjjpAVsbFwvyVOkBWxsXC/JU6QFIm7YJpnTpAUibtgmmdOkAkWD1dNqU6QCRYPV02pTpAnNaRTqa2OkCc1pFOprY6QEA3TikguDpAQDdOKSC4OkBQjqwfZMA6QFCOrB9kwDpAUON9W83KOkBQ431bzco6QAYfCgYf1jpABh8KBh/WOkAOGqP2T906QA4ao/ZP3TpA7iVUXIfjOkDuJVRch+M6QKrd+uo65jpAqt366jrmOkCOiZjWO+c6QI6JmNY75zpA85Zo/6nrOkDzlmj/qes6QPpBsAkp7DpA+kGwCSnsOkC/m0mZjvM6QL+bSZmO8zpAKoi3uUQBO0AqiLe5RAE7QH930Z6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"bokeh.io.show(bebi103.viz.predictive_ecdf(ell, x_axis_label=\"spindle length (µm)\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this plot, the median ECDF is shown in the middle, the darker blue filled region contains 68% of the samples, and the light blue contains 95% of the samples. The extent of the ECDF gives an indication of the extreme values in the prior predictive data set. The bulk of the spindle lengths lie in a reasonable region, somewhere between zero and 30 µm.\n", "\n", "We may be willing to tolerate the negative spindle length values in our model, since any data set, containing no negative values, could easily tug the posterior into positive spindle lengths. Nonetheless, let's check how many negative spindle lengths we get from our generative model. We will compute the fraction of spindle lengths that are negative from our generative model for each of the 1000 data sets we generated and then plot the results as an ECDF." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", "\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " var attempts = 0;\n", " var timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "2653" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.ecdf(\n", " (ell < 0).sum(axis=1) / len(df), x_axis_label=\"fraction of negative spindle lengths\"\n", ")\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nearly half of the data sets we generated had negative spindle lengths, and many of them had a substantial fraction that were negative. The total fraction of negative spindle lengths of all generated data sets can be calculated." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.054521" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(ell < 0).sum() / (N * n_ppc_samples)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, more than 5% of generated data points are unphysical. Again, we could decide to tolerate this, but I will instead propose another model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The prior, take 3\n", "\n", "It makes sense that the standard deviation of the spindle length may scale with the spindle length itself. We can express this as\n", "\n", "\\begin{align}\n", "&\\sigma_0 \\sim \\text{Gamma}(2, 10), \\\\[1em]\n", "&\\sigma = \\sigma_0\\, \\phi.\n", "\\end{align}\n", "\n", "That is, $\\sigma$ scales linearly with $\\phi$ with constant of proportionality $\\sigma_0$. The prior we have chosen for $\\sigma_0$ looks like this." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "
\n", "
\n", "" ], "text/plain": [ ":Curve [σ₀ [µm]] (g(σ₀) [1/µm])" ] }, "execution_count": 12, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "2886" } }, "output_type": "execute_result" } ], "source": [ "sigma_0 = np.linspace(0, 1, 200)\n", "hv.Curve(\n", " (sigma_0, st.gamma.pdf(sigma_0, 2, loc=0, scale=0.1)),\n", " kdims='σ₀ [µm]',\n", " vdims='g(σ₀) [1/µm]'\n", ").opts(\n", " xlim=(0, 1)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, our new complete generative model is\n", "\n", "\\begin{align}\n", "&\\phi \\sim \\text{LogNorm}(\\ln 20, 0.75),\\\\[1em]\n", "&\\sigma_0 \\sim \\text{Gamma}(2, 10),\\\\[1em]\n", "&\\sigma = \\sigma_0\\,\\phi,\\\\[1em]\n", "&l_i \\sim \\text{Norm}(\\phi, \\sigma)\\; \\forall i.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Prior predictive checks, take 2\n", "\n", "We can again generate our prior predictive data sets." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2680]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1340]},\"y\":{\"__ndarray__\":\"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{\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "3008" } }, "output_type": "display_data" } ], "source": [ "# Draw parameters out of the prior\n", "phi = np.random.lognormal(np.log(20), 0.75, size=n_ppc_samples)\n", "sigma_0 = np.random.gamma(2, 1 / 10, size=n_ppc_samples)\n", "sigma = sigma_0 * phi\n", "\n", "# Draw data sets out of the likelihood for each set of prior params\n", "ell = np.array([np.random.normal(ph, sig, size=len(df)) for ph, sig in zip(phi, sigma)])\n", "\n", "# Show the prior predictive ECDF\n", "bokeh.io.show(bebi103.viz.predictive_ecdf(ell, x_axis_label=\"spindle length (µm)\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We still get some negative spindle lengths, but far fewer. 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0).sum(axis=1) / len(df), x_axis_label=\"fraction of negative spindle lengths\"\n", ")\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now most data sets do not contain any negative spindle lengths and those that do contain a much smaller fraction. This seems like a more reasonable prior, and we settle on this as our generative model for the case where spindle length is independent of droplet size." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prior predictive checks with Stan\n", "\n", "While generating the data sets to be used in prior predictive checks is intuitive and easy using Numpy, I find it is more convenient to do it in Stan. This may not be obvious now, but will become clearer later when we construct an entire workflow including prior and posterior predictive checks and use simulation-based calibration.\n", "\n", "Generating prior predictive samples typically does not require Markov chain Monte Carlo, but the random number generation we are more familiar with. Stan does allow for this kind of random number generation. If you want to draw a sample out of one of Stan's distributions, append the name of the distribution with `_rng`. Unlike Numpy's and Scipy's random number generators, Stan's RNGs can only draw one sample at a time. Therefore, we have to put the random number generation in a `for` loop. The code below demonstrates this.\n", "\n", "```stan\n", "data {\n", " int N;\n", "}\n", "\n", "\n", "generated quantities {\n", " // Parameters\n", " real phi;\n", " real sigma_0;\n", "\n", " // Data\n", " real ell[N];\n", "\n", " phi = lognormal_rng(3.0, 0.75);\n", " sigma_0 = gamma_rng(2.0, 10.0);\n", " \n", " for (i in 1:N) {\n", " ell[i] = normal_rng(phi, sigma_0 * phi);\n", " }\n", "}\n", "```\n", "\n", "The `data` block contains `N`, the number of `ell` values we want to generate. The `generated quantities` block defines variables we want to store, in this case `phi`, `sigma_0` and `ell`. We first generate values for `phi` and `sigma_0` and then use those values to generate data `ell`. Note that the parameter `sigma`, which is given by the product of $\\sigma_0$ and $\\phi$, is also generated and is used to generate `ell`. However, we do not need to store this, since it is determined from `sigma_0` and `phi` samples. Note that though we are not using this syntax here, parameters in the `generated quantities` block that are enclosed in braces (outside of if statements and for loops, of course) are not saved in the output.\n", "\n", "The above code will be useful for our prior predictive checks, but if we want to tweak some of the parametrizations of the priors (e.g., we might want $\\phi\\sim \\text{LogNorm}(4, 1)$ instead of $\\phi \\sim \\text{LogNorm}(3, 0.75)$), we will have to adjust the Stan code and recompile. For the purposes of prior predictive checks, we may also want to include these values in the `data` block and pass them in as the `data` kwarg when sampling.\n", "\n", "```stan\n", "data {\n", " int N;\n", " real phi_mu;\n", " real phi_sigma;\n", " real sigma_0_alpha;\n", " real sigma_0_beta;\n", "}\n", "\n", "\n", "generated quantities {\n", " // Parameters\n", " real phi;\n", " real sigma_0;\n", "\n", " // Data\n", " real ell[N];\n", "\n", " phi = lognormal_rng(phi_mu, phi_sigma);\n", " sigma_0 = gamma_rng(sigma_0_alpha, sigma_0_beta);\n", "\n", " for (i in 1:N) {\n", " ell[i] = normal_rng(phi, sigma_0 * phi);\n", " }\n", "}\n", "\n", "\n", "```\n", "\n", "Let's build this Stan model." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:compiling stan file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/indep_size_model_prior_predictive.stan to exe file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/indep_size_model_prior_predictive\n", "INFO:cmdstanpy:compiled model executable: /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/indep_size_model_prior_predictive\n" ] } ], "source": [ "sm_prior_pred = cmdstanpy.CmdStanModel(\n", " stan_file=\"indep_size_model_prior_predictive.stan\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To draw the samples, we specify the contents of the inputted `data` block, and then sample. We need to use the kwarg `fixed_param=True` to alert Stan that it will not need to do any MCMC sampling, but rather just run the `generated quantities` block." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:CmdStan start procesing\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "dc5bf04d96d340b3aa2905929bbb9a01", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 1 | | 00:00 Status" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " " ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:CmdStan done processing.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "data = {\n", " \"N\": N,\n", " \"phi_mu\": 3.0,\n", " \"phi_sigma\": 0.75,\n", " \"sigma_0_alpha\": 2.0,\n", " \"sigma_0_beta\": 10.0,\n", "}\n", "\n", "samples = sm_prior_pred.sample(data=data, iter_sampling=1000, fixed_param=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As usual, we would like to convert the output to an ArviZ `InferenceData` instance." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "samples = az.from_cmdstanpy(prior=samples, prior_predictive=['ell'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can pass the array stored in `samples.prior_predictive['ell']` directly into the `bebi103.viz.predictive_ecdf()` function to get the predictive ECDF." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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bebi103.viz.predictive_ecdf(samples.prior_predictive['ell'])\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The result is of course the same as when generating data sets with Numpy.\n", "\n", "As you can see, it is a bit more verbose to use Stan to generate the prior predictive samples. The calculation time is also substantially longer because of the time required for compilation. Nonetheless, it is often advantageous to use Stan for this stage of an analysis pipeline because when we do [simulation based calibration (SBC)](https://arxiv.org/pdf/1804.06788.pdf) of our models, it is useful to have everything written in Stan." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model 2: Spindle size dependent on total tubulin concentration\n", "\n", "While we have already worked with the conserved tubulin model, it is instructive to consider again how it is derived. This enables us to think about model building in terms of identifiability of parameters.\n", "\n", "The conserved tubulin model hinges on the following principles.\n", "\n", "1. The total amount of tubulin in the droplet or cell is conserved.\n", "2. The total length of polymerized microtubules is a function of the total tubulin concentration after assembly of the spindle. This results from the balances of microtubule polymerization rate with catastrophe frequencies.\n", "3. The density of tubulin in the spindle is independent of droplet or cell volume.\n", "\n", "Assumption 1 (conservation of tubulin) implies\n", "\n", "\\begin{align}\n", "T_0 V_0 = T_1(V_0 - V_\\mathrm{s}) + T_\\mathrm{s}V_\\mathrm{s},\n", "\\end{align}\n", "\n", "where $V_0$ is the volume of the droplet or cell, $V_\\mathrm{s}$ is the volume of the spindle, $T_0$ is the total tubulin concentration (polymerized or not), $T_1$ is the tubulin concentration in the cytoplasm after the the spindle has formed, and $T_\\mathrm{s}$ is the concentration of tubulin in the spindle. If we assume the spindle does not take up much of the total volume of the droplet or cell ($V_0 \\gg V_\\mathrm{s}$, which is the case as we will see when we look at the data), we have\n", "\n", "\\begin{align}\n", "T_1 \\approx T_0 - \\frac{V_\\mathrm{s}}{V_0}\\,T_\\mathrm{s}.\n", "\\end{align}\n", "\n", "The amount of tubulin in the spindle can we written in terms of the total length of polymerized microtubules, $L_\\mathrm{MT}$ as\n", "\n", "\\begin{align}\n", "T_s V_\\mathrm{s} = \\alpha L_\\mathrm{MT},\n", "\\end{align}\n", "\n", "where $\\alpha$ is the tubulin concentration per unit microtubule length. (We will see that it is unimportant, but from the known geometry of microtubules, $\\alpha \\approx 2.7$ nmol/µm.)\n", "\n", "We formalize assumption 2 into a mathematical expression. Microtubule length should grow with increasing $T_1$. There should also be a minimal threshold $T_\\mathrm{min}$ where polymerization stops. We therefore approximate the total microtubule length as a linear function,\n", "\n", "\\begin{align}\n", "L_\\mathrm{MT} \\approx \\left\\{\\begin{array}{ccl}\n", "0 & &T_1 \\le T_\\mathrm{min} \\\\\n", "\\beta(T_1 - T_\\mathrm{min}) & & T_1 > T_\\mathrm{min}.\n", "\\end{array}\\right.\n", "\\end{align}\n", "\n", "Because spindles form in *Xenopus* extract, $T_0 > T_\\mathrm{min}$, so there exists a $T_1$ with $T_\\mathrm{min} < T_1 < T_0$, so going forward, we are assured that $T_1 > T_\\mathrm{min}$. Thus, we have\n", "\n", "\\begin{align}\n", "V_\\mathrm{s} \\approx \\alpha\\beta\\,\\frac{T_1 - T_\\mathrm{min}}{T_\\mathrm{s}}.\n", "\\end{align}\n", "\n", "With insertion of our expression for $T_1$, this becomes\n", "\n", "\\begin{align}\n", "V_{\\mathrm{s}} \\approx \\alpha \\beta\\left(\\frac{T_0 - T_\\mathrm{min}}{T_\\mathrm{s}} - \\frac{V_\\mathrm{s}}{V_0}\\right).\n", "\\end{align}\n", "\n", "Solving for $V_\\mathrm{s}$, we have\n", "\n", "\\begin{align}\n", "V_\\mathrm{s} \\approx \\frac{\\alpha\\beta}{1 + \\alpha\\beta/V_0}\\,\\frac{T_0 - T_\\mathrm{min}}{T_\\mathrm{s}}\n", "=\\frac{V_0}{1 + V_0/\\alpha\\beta}\\,\\frac{T_0 - T_\\mathrm{min}}{T_\\mathrm{s}}.\n", "\\end{align}\n", "\n", "We approximate the shape of the spindle as a prolate spheroid with major axis length $l$ and minor axis length $w$, giving\n", "\n", "\\begin{align}\n", "V_\\mathrm{s} = \\frac{\\pi}{6}\\,l w^2 = \\frac{\\pi}{6}\\,k^2 l^3,\n", "\\end{align}\n", "\n", "where $k \\equiv w/l$ is the aspect ratio of the spindle. We can now write an expression for the spindle length as\n", "\n", "\\begin{align}\n", "l \\approx \\left(\\frac{6}{\\pi k^2}\\,\n", "\\frac{T_0 - T_\\mathrm{min}}{T_\\mathrm{s}}\\,\n", "\\frac{V_0}{1+V_0/\\alpha\\beta}\\right)^{\\frac{1}{3}}.\n", "\\end{align}\n", "\n", "For a spherical droplet, $V_0 \\approx \\pi d^3 / 6$, giving\n", "\n", "\\begin{align}\n", "l \\approx \\left(\n", "\\frac{T_0 - T_\\mathrm{min}}{k^2\\,T_\\mathrm{s}}\\,\n", "\\frac{d^3}{1+\\pi d^3/6\\alpha\\beta}\\right)^{\\frac{1}{3}}.\n", "\\end{align}\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Indentifiability of parameters\n", "\n", "Good and coworkers measured the microtubule length $l$ and droplet diameter $d$ directly from their microscope images. They can also measure the spindle aspect ratio $k$ directly from the images. Thus, we have four unknown parameters, since we already know α ≈ 2.7 nmol/µm. The unknown parameters are:\n", "\n", "| parameter | meaning |\n", "| :------: | :-----|\n", "|$\\beta$ | rate constant for MT growth |\n", "|$T_0$ | total tubulin concentration |\n", "|$T_\\mathrm{min}$ | critical tubulin concentration for polymerization |\n", "|$T_s$ | tubulin concentration in the spindle |\n", "\n", "We would like to determine all of these parameters. We could measure them all either in this experiment or in other experiments. We could measure the total tubulin concentration $T_0$ by doing spectroscopic or other quantitative methods on the *Xenopus* extract. We can $T_\\mathrm{min}$ and $T_s$ might be assessed by other in vitro assays, though these parameters may by strongly dependent on the conditions of the extract.\n", "\n", "Importantly, though, the parameters only appear in combinations with each other in our theoretical model. Specifically, we can define two parameters,\n", "\n", "\\begin{align}\n", "\\gamma &= \\left(\\frac{T_0-T_\\mathrm{min}}{k^2T_\\mathrm{s}}\\right)^\\frac{1}{3} \\\\[1em]\n", "\\phi &= \\gamma\\left(\\frac{6\\alpha\\beta}{\\pi}\\right)^{\\frac{1}{3}}.\n", "\\end{align}\n", "\n", "We can then rewrite the general model expression in terms of these parameters as\n", "\n", "\\begin{align}\n", "l(d) \\approx \\frac{\\gamma d}{\\left(1+(\\gamma d/\\phi)^3\\right)^{\\frac{1}{3}}}.\n", "\\end{align}\n", "\n", "If we tried to determine all four parameters from this experiment only, we would be in trouble. This experiment alone cannot distinguish all of the parameters. Rather, we can only distinguish two combinations of them, which we have defined as $\\gamma$ and $\\phi$. This is an issue of **identifiability**. We may not be able to distinguish all parameters in a given model, and it is important to think carefully *before* the analysis about which ones we can identify. \n", "\n", "We are not quite done with characterizing identifiability." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Limiting behavior\n", "\n", "For large droplets, with $d \\gg \\phi/\\gamma$, the spindle size becomes independent of $d$, with\n", "\n", "\\begin{align}\n", "l \\approx \\phi.\n", "\\end{align}\n", "\n", "Conversely, for $d \\ll \\phi/\\gamma$, the spindle length varies approximately linearly with diameter.\n", "\n", "\\begin{align}\n", "l(d) \\approx \\gamma\\,d.\n", "\\end{align}\n", "\n", "Note that the expression for the linear regime gives bounds for $\\gamma$. Obviously, $\\gamma > 0$, lest we have spindles of negative length in the small $d$ regime. Because $l \\le d$, lest the spindle not fit in the droplet, we also have $\\gamma \\le 1$. \n", "\n", "Importantly, if the experiment is done in the regime where $d$ is large (and we do not really know a priori how large that is since we do not know the parameters $\\phi$ and $\\gamma$), we cannot tell the difference between this conserved tubulin model and the independent size model, since they are equivalent in that regime. Further, if the experiment is in this regime the model is unidentifiable because we cannot resolve $\\gamma$.\n", "\n", "This sounds kind of dire, but this is actually a convenient fact. The conserved tubulin model is more complex, but it has a simpler model, the independent size model, as a limit. Thus, the two models are in fact commensurate with each other. Knowledge of how these limits also enhances the experimental design. We should strive for small droplets. And perhaps most importantly, if we didn't consider the second model, we might automatically assume that droplet size has nothing to do with spindle length if we happened to do the experiment in larger droplets." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Generative model\n", "\n", "We have a theoretical model relating the droplet diameter to the spindle length. Let us now build a generative model. For spindle, droplet pair $i$, we assume\n", "\n", "\\begin{align}\n", "l_i = \\frac{\\gamma d_i}{\\left(1+(\\gamma d/\\phi)^3\\right)^{\\frac{1}{3}}} + e_i.\n", "\\end{align}\n", "\n", "We again assume that $e_i$ is Normally distributed with variance $\\sigma^2$. In the independent size model, we assumed that $\\sigma$ scaled with the characteristic spindle size, which was $\\phi$ in that case. We will do the same here, scaling $\\sigma$ with the theoretical spindle size for each droplet diameter. We can choose the same prior as before for $\\phi$, and we choose a Beta prior for $\\gamma$ with a slight preference for intermediate $\\gamma$ values. Our model is then\n", "\n", "\\begin{align}\n", "&\\phi \\sim \\text{LogNorm}(\\ln 20, 0.75),\\\\[1em]\n", "&\\gamma \\sim \\text{Beta}(1.1, 1.1), \\\\[1em]\n", "&\\sigma_0 \\sim \\text{Gamma}(2, 10),\\\\[1em]\n", "&\\mu_i = \\frac{\\gamma d_i}{\\left(1+(\\gamma d_i/\\phi)^3\\right)^{\\frac{1}{3}}}, \\\\[1em]\n", "&\\sigma_i = \\sigma_0\\,\\mu_i,\\\\[1em]\n", "&l_i \\sim \\text{Norm}(\\mu_i, \\sigma_i) \\;\\forall i.\n", "\\end{align}\n", "\n", "Importantly, note that this model builds upon our first model. Generally, when doing Bayesian modeling, it is a good idea to build more complex models on your initial baseline model such that the models are related to each other by limiting behavior. This gives you a continuum of models and a sound basis for making comparisons among models." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Prior predictive checks\n", "\n", "We will now will perform the prior predictive checks using Stan. Here is the Stan code:\n", "\n", "```stan\n", "functions {\n", " real ell_theor(real d, real phi, real gamma) {\n", " real denom_ratio = (gamma * d / phi)^3;\n", " return gamma * d / (1 + denom_ratio)^(1.0 / 3.0); \n", " }\n", "}\n", "\n", "\n", "data {\n", " int N;\n", " real d[N];\n", "\n", " real phi_mu;\n", " real phi_sigma;\n", " real gamma_alpha;\n", " real gamma_beta;\n", " real sigma_0_alpha;\n", " real sigma_0_beta;\n", "}\n", "\n", "\n", "generated quantities {\n", " // Parameters\n", " real phi;\n", " real gamma;\n", " real sigma_0;\n", " real sigma;\n", "\n", " // Data\n", " real ell[N];\n", "\n", " phi = lognormal_rng(phi_mu, phi_sigma);\n", " gamma = beta_rng(gamma_alpha, gamma_beta);\n", " sigma_0 = gamma_rng(sigma_0_alpha, sigma_0_beta);\n", " sigma = sigma_0 * phi;\n", "\n", " {\n", " real mu;\n", " \n", " for (i in 1:N) {\n", " mu = ell_theor(d[i], phi, gamma);\n", " ell[i] = normal_rng(mu, sigma_0 * mu);\n", " }\n", " }\n", "}\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's compile and generate our prior predictive samples!" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:compiling stan file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/cons_tubulin_model_prior_predictive.stan to exe file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/cons_tubulin_model_prior_predictive\n", "INFO:cmdstanpy:compiled model executable: /Users/bois/Dropbox/git/bebi103_course/2022/b/content/lessons/13/cons_tubulin_model_prior_predictive\n" ] } ], "source": [ "sm_prior_pred = cmdstanpy.CmdStanModel(\n", " stan_file=\"cons_tubulin_model_prior_predictive.stan\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we'll set up the input data, draw our samples, and convert to an ArviZ `InferenceData` instance." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:CmdStan start procesing\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4b69db34abc048c9911e4e5a0b27d774", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 1 | | 00:00 Status" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " " ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:CmdStan done processing.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "data = {\n", " \"N\": N,\n", " \"d\": d,\n", " \"phi_mu\": 3.0,\n", " \"phi_sigma\": 0.75,\n", " \"gamma_alpha\": 1.1,\n", " \"gamma_beta\": 1.1,\n", " \"sigma_0_alpha\": 2.0,\n", " \"sigma_0_beta\": 10.0,\n", "}\n", "\n", "samples = sm_prior_pred.sample(data=data, iter_sampling=1000, fixed_param=True)\n", "\n", "samples = az.from_cmdstanpy(prior=samples, prior_predictive=['ell'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can start our graphical posterior predictive checks by looking at an ECDF of the values of the spindle length, ignoring for a moment the dependence on droplet diameter." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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dACtejcD3qJ0CF61G4HvUnQIXrUbge9SdAHOviNhoAKEAc6+I2GgAoQHDOiNLeAChAcM6I0t4AKEDyY8xdSwgoQPJjzF1LCChAkML1KFwPKECQwvUoXA8oQEa28/3UGChARrbz/dQYKEDufD81XhooQO58PzVeGihAImx4eqUcKEAibHh6pRwoQEA1XrpJLChAQDVeukksKECvJeSDnj0oQK8l5IOePShAqvHSTWJQKECq8dJNYlAoQFfsL7snXyhAV+wvuydfKEDrc7UV+2soQOtztRX7ayhAxks3iUFwKEDGSzeJQXAoQA5Pr5RleChADk+vlGV4KED5MeauJYQoQPkx5q4lhChAEAu1pnmHKEAQC7WmeYcoQFr1udqKjShAWvW52oqNKEC5/If025coQLn8h/TblyhAArwFEhSvKEACvAUSFK8oQKYKRiV1wihApgpGJXXCKEC/fR04Z8QoQL99HThnxChAvCcPC7XGKEC8Jw8LtcYoQOJ6FK5H0ShA4noUrkfRKEAH8BZIUNwoQAfwFkhQ3ChA5q4l5IPeKEDmriXkg94oQMQgsHJo4ShAxCCwcmjhKEA+CtejcP0oQD4K16Nw/ShAiPTb14EDKUCI9NvXgQMpQKwcWmQ7DylArBxaZDsPKUBR2ht8YRIpQFHaG3xhEilADJOpglEZKUAMk6mCURkpQJaQD3o2GylAlpAPejYbKUAIPZtVnyspQAg9m1WfKylANIC3QIIyKUA0gLdAgjIpQCUGgZVDOylAJQaBlUM7KUBzaJHtfD8pQHNoke18PylAvAUSFD9GKUC8BRIUP0YpQMrDQq1pTilAysNCrWlOKUCKsOHplVIpQIqw4emVUilA9P3UeOlWKUD0/dR46VYpQHnpJjEIXClAeekmMQhcKUB6xyk6kmspQHrHKTqSaylAhlrTvON0KUCGWtO843QpQPYoXI/CdSlA9ihcj8J1KUBbQj7o2XwpQFtCPujZfClAOpLLf0iPKUA6kst/SI8pQKZ5xyk6kilApnnHKTqSKUDkg57Nqp8pQOSDns2qnylA6Pup8dKtKUDo+6nx0q0pQCBj7lpCvilAIGPuWkK+KUDImLuWkM8pQMiYu5aQzylAxm00gLfQKUDGbTSAt9ApQOSlm8Qg4ClA5KWbxCDgKUCEDU+vlOUpQIQNT6+U5SlAHOviNhrwKUAc6+I2GvApQHQkl/+Q/ilAdCSX/5D+KUAUP8bctQQqQBQ/xty1BCpAKhiV1AkIKkAqGJXUCQgqQEVHcvkPCSpARUdy+Q8JKkD6fmq8dBMqQPp+arx0EypAmG4Sg8AqKkCYbhKDwCoqQD2bVZ+rLSpAPZtVn6stKkA1XrpJDDIqQDVeukkMMipAHOviNhpAKkAc6+I2GkAqQBriWBe3QSpAGuJYF7dBKkB0RpT2Bk8qQHRGlPYGTypADi2yne9XKkAOLbKd71cqQHbgnBGlXSpAduCcEaVdKkDf4AuTqWIqQN/gC5OpYipA8IXJVMFoKkDwhclUwWgqQNIA3gIJaipA0gDeAglqKkB0JJf/kG4qQHQkl/+QbipAlGWIY118KkCUZYhjXXwqQAK8BRIUfypAArwFEhR/KkCNKO0NvoAqQI0o7Q2+gCpArkfhehSOKkCuR+F6FI4qQI0o7Q2+kCpAjSjtDb6QKkDA7J48LJQqQMDsnjwslCpA1jTvOEWXKkDWNO84RZcqQF8pyxDHmipAXynLEMeaKkApXI/C9agqQClcj8L1qCpAJXUCmgirKkAldQKaCKsqQMuhRbbzrSpAy6FFtvOtKkB0kxgEVq4qQHSTGARWripArIvbaACvKkCsi9toAK8qQDlFR3L5vypAOUVHcvm/KkDDZKpgVMIqQMNkqmBUwipA93XgnBHFKkD3deCcEcUqQBHHuriNxipAEce6uI3GKkDtDb4wmcoqQO0NvjCZyipAw2SqYFTSKkDDZKpgVNIqQBB6Nqs+1ypAEHo2qz7XKkCqglFJneAqQKqCUUmd4CpAZvfkYaHmKkBm9+RhoeYqQAIrhxbZ7ipAAiuHFtnuKkBeKcsQx/oqQF4pyxDH+ipA5BQdyeUPK0DkFB3J5Q8rQDSAt0CCEitANIC3QIISK0DqlbIMcRwrQOqVsgxxHCtAg8DKoUUmK0CDwMqhRSYrQEjhehSuJytASOF6FK4nK0CKjuTyHzIrQIqO5PIfMitA9+RhodY0K0D35GGh1jQrQIPAyqFFNitAg8DKoUU2K0DUCWgibDgrQNQJaCJsOCtACtejcD06K0AK16NwPTorQGrecYqORCtAat5xio5EK0DWxW00gEcrQNbFbTSARytAzF1LyAdNK0DMXUvIB00rQOq3rwPnXCtA6revA+dcK0DiWBe30WArQOJYF7fRYCtAmLuWkA9qK0CYu5aQD2orQOM2GsBbcCtA4zYawFtwK0AFNBE2PH0rQAU0ETY8fStABOeMKO2NK0AE54wo7Y0rQCo6kst/mCtAKjqSy3+YK0A2PL1SlqErQDY8vVKWoStAeC0hH/SsK0B4LSEf9KwrQAN4CyQoritAA3gLJCiuK0Coxks3ibErQKjGSzeJsStA3gIJih+zK0DeAgmKH7MrQNobfGEyxStA2ht8YTLFK0C4HoXrUcgrQLgehetRyCtAyjLEsS7OK0DKMsSxLs4rQPjkYaHW5CtA+ORhodbkK0CwlGWIY+0rQLCUZYhj7StApixDHOvyK0CmLEMc6/IrQFXBqKROACxAVcGopE4ALEBF2PD0SiksQEXY8PRKKSxArD5XW7EvLECsPldbsS8sQGDl0CLbOSxAYOXQIts5LEC0yHa+nzosQLTIdr6fOixAXCBB8WNcLEBcIEHxY1wsQIofY+5aYixAih9j7lpiLEBoImx4emUsQGgibHh6ZSxADXGsi9toLEANcayL22gsQMsQx7q4bSxAyxDHurhtLEBQjZduEnMsQFCNl24ScyxACtejcD16LEAK16NwPXosQGiz6nO1hSxAaLPqc7WFLECEL0ymCoYsQIQvTKYKhixA4noUrkeRLEDiehSuR5EsQPJBz2bVlyxA8kHPZtWXLEA7cM6I0p4sQDtwzojSnixAbJp3nKKjLEBsmnecoqMsQBIUP8bcpSxAEhQ/xtylLEB6xyk6kqssQHrHKTqSqyxArBxaZDuvLECsHFpkO68sQN/gC5OpsixA3+ALk6myLEDzH9JvX7csQPMf0m9ftyxAuI0G8Ba4LEC4jQbwFrgsQLivA+eMuCxAuK8D54y4LEBFR3L5D7ksQEVHcvkPuSxAoWez6nPFLEChZ7Pqc8UsQKs+V1uxzyxAqz5XW7HPLEClTkATYdMsQKVOQBNh0yxA1sVtNIDXLEDWxW00gNcsQJrmHafo2CxAmuYdp+jYLEBc/kP67dssQFz+Q/rt2yxABTQRNjzdLEAFNBE2PN0sQDj4wmSq4CxAOPjCZKrgLEC4HoXrUegsQLgehetR6CxA7J48LNTqLEDsnjws1OosQFyxv+ye7CxAXLG/7J7sLEAUrkfhevQsQBSuR+F69CxASS7/If32LEBJLv8h/fYsQJT2Bl+Y/CxAlPYGX5j8LEDIBz2bVf8sQMgHPZtV/yxAiPTb14EDLUCI9NvXgQMtQLmNBvAWCC1AuY0G8BYILUBhw9MrZQktQGHD0ytlCS1Ax7q4jQYQLUDHuriNBhAtQKLWNO84FS1AotY07zgVLUAqGJXUCRgtQCoYldQJGC1AOpLLf0gfLUA6kst/SB8tQLaEfNCzKS1AtoR80LMpLUBBguLHmCstQEGC4seYKy1AWDm0yHYuLUBYObTIdi4tQDj4wmSqMC1AOPjCZKowLUAIPZtVnzstQAg9m1WfOy1AFvvL7slDLUAW+8vuyUMtQOQUHcnlTy1A5BQdyeVPLUDysFBrmlctQPKwUGuaVy1AB1+YTBVcLUAHX5hMFVwtQO7Jw0KtaS1A7snDQq1pLUCkTkATYXMtQKROQBNhcy1AjuTyH9J/LUCO5PIf0n8tQBniWBe3gS1AGeJYF7eBLUC+MJkqGIUtQL4wmSoYhS1A8rBQa5qHLUDysFBrmoctQJT2Bl+YjC1AlPYGX5iMLUC6/If025ctQLr8h/Tbly1AfT81XrqZLUB9PzVeupktQGzn+6nxoi1AbOf7qfGiLUCfq63YX6YtQJ+rrdhfpi1A8fRKWYaoLUDx9EpZhqgtQOxRuB6Fqy1A7FG4HoWrLUCMuWsJ+bAtQIy5awn5sC1AvsEXJlO1LUC+wRcmU7UtQJoIG55euS1Amggbnl65LUDu68A5I7otQO7rwDkjui1AYVRSJ6DJLUBhVFInoMktQNQJaCJs2C1A1AloImzYLUC2FfvL7tktQLYV+8vu2S1AWDm0yHbeLUBYObTIdt4tQE7RkVz+4y1ATtGRXP7jLUCG61G4HuUtQIbrUbge5S1ASS7/If3mLUBJLv8h/eYtQKabxCCw8i1AppvEILDyLUAm5IOezfotQCbkg57N+i1Anu+nxksHLkCe76fGSwcuQI2XbhKDEC5AjZduEoMQLkDSb18HzhkuQNJvXwfOGS5ArD5XW7EfLkCsPldbsR8uQMbctYR8IC5Axty1hHwgLkDgvg6cMyIuQOC+DpwzIi5AcoqO5PIvLkByio7k8i8uQJyiI7n8Ny5AnKIjufw3LkDJ5T+k3z4uQMnlP6TfPi5AVFInoIlALkBUUiegiUAuQJhuEoPASi5AmG4Sg8BKLkB4eqUsQ0wuQHh6pSxDTC5AjGzn+6lRLkCMbOf7qVEuQKRwPQrXUy5ApHA9CtdTLkAwKqkT0FQuQDAqqRPQVC5AZDvfT41XLkBkO99PjVcuQDtwzojSXi5AO3DOiNJeLkDwOEVHcmkuQPA4RUdyaS5ArIvbaABvLkCsi9toAG8uQFFrmnecci5AUWuad5xyLkBmiGNd3HYuQGaIY13cdi5AK4cW2c6HLkArhxbZzocuQMbctYR8kC5Axty1hHyQLkDbiv1l95QuQNuK/WX3lC5AtoR80LOZLkC2hHzQs5kuQDq0yHa+ny5AOrTIdr6fLkAYJlMFo6IuQBgmUwWjoi5A7FG4HoWrLkDsUbgehasuQFBrmnecsi5AUGuad5yyLkCEL0ymCrYuQIQvTKYKti5AJuSDns26LkAm5IOezbouQNnO91PjxS5A2c73U+PFLkBiMlUwKskuQGIyVTAqyS5ABhIUP8bMLkAGEhQ/xswuQFfsL7snzy5AV+wvuyfPLkBSJ6CJsNEuQFInoImw0S5AUtobfGHSLkBS2ht8YdIuQEhy+Q/p1y5ASHL5D+nXLkBwzojS3uAuQHDOiNLe4C5ApU5AE2HjLkClTkATYeMuQFpkO99P7S5AWmQ730/tLkACTYQNT+8uQAJNhA1P7y5A9UpZhjj2LkD1SlmGOPYuQLprCfmg9y5AumsJ+aD3LkCaKhiV1PkuQJoqGJXU+S5AJCh+jLn7LkAkKH6MufsuQHDOiNLeAC9AcM6I0t4AL0D1SlmGOAYvQPVKWYY4Bi9A1LzjFB0JL0DUvOMUHQkvQHw/NV66CS9AfD81XroJL0A2PL1SlhEvQDY8vVKWES9ANe84RUcSL0A17zhFRxIvQLsnDwu1Fi9AuycPC7UWL0CASL99HRgvQIBIv30dGC9Arthfdk8eL0Cu2F92Tx4vQGuad5yiIy9Aa5p3nKIjL0DW52or9icvQNbnaiv2Jy9AB1+YTBUsL0AHX5hMFSwvQIts5/upMS9Ai2zn+6kxL0CGp1fKMjQvQIanV8oyNC9AS1mGONY1L0BLWYY41jUvQHqlLEMcOy9AeqUsQxw7L0AEVg4tsj0vQARWDi2yPS9A0SLb+X5KL0DRItv5fkovQAYSFD/GTC9ABhIUP8ZML0BUwaikTlAvQFTBqKROUC9ApE5AE2FTL0CkTkATYVMvQLbz/dR4WS9AtvP91HhZL0DjNhrAW2AvQOM2GsBbYC9A9NvXgXNmL0D029eBc2YvQNQJaCJsaC9A1AloImxoL0Ct+lxtxW4vQK36XG3Fbi9A/Yf029dxL0D9h/Tb13EvQIpBYOXQci9AikFg5dByL0C6uI0G8HYvQLq4jQbwdi9AWDm0yHZ+L0BYObTIdn4vQLx0kxgEhi9AvHSTGASGL0AJih9j7oovQAmKH2Puii9AdnEbDeCNL0B2cRsN4I0vQIxs5/upkS9AjGzn+6mRL0BqTfOOU5QvQGpN845TlC9AelioNc2bL0B6WKg1zZsvQOhqK/aXnS9A6Gor9pedL0AsQxzr4qYvQCxDHOvipi9AkzoBTYStL0CTOgFNhK0vQK5p3nGKri9ArmnecYquL0CkcD0K17MvQKRwPQrXsy9AgLdAguK3L0CAt0CC4rcvQD4K16NwvS9APgrXo3C9L0BWDi2ynb8vQFYOLbKdvy9AUkmdgCbCL0BSSZ2AJsIvQL1SliGOxS9AvVKWIY7FL0AQejarPscvQBB6Nqs+xy9AArwFEhTPL0ACvAUSFM8vQMNkqmBU0i9Aw2SqYFTSL0CJQWDl0NIvQIlBYOXQ0i9AFtnO91PTL0AW2c73U9MvQGIQWDm02C9AYhBYObTYL0Dm0CLb+d4vQObQItv53i9Aqz5XW7HfL0CrPldbsd8vQBZqTfOO4y9AFmpN847jL0C+MJkqGOUvQL4wmSoY5S9A5BQdyeXvL0DkFB3J5e8vQDQRNjy98i9ANBE2PL3yL0CgibDh6fUvQKCJsOHp9S9AQxzr4jYCMEBDHOviNgIwQIbrUbgeDTBAhutRuB4NMED0bFZ9rg4wQPRsVn2uDjBA9P3UeOkOMED0/dR46Q4wQMh2vp8aDzBAyHa+nxoPMEBhw9MrZREwQGHD0ytlETBA9pfdk4cVMED2l92ThxUwQMnlP6TfFjBAyeU/pN8WMEC6awn5oB8wQLprCfmgHzBAQILix5gjMEBAguLHmCMwQNnO91PjJTBA2c73U+MlMEBSSZ2AJiowQFJJnYAmKjBAQBNhw9MrMEBAE2HD0yswQNo9eVioLTBA2j15WKgtMEDOGVHaGzQwQM4ZUdobNDBAq8/VVuw3MECrz9VW7DcwQO7Jw0KtOTBA7snDQq05MED4MeauJUQwQPgx5q4lRDBAGCZTBaNKMEAYJlMFo0owQBrAWyBBUTBAGsBbIEFRMEAyVTAqqVMwQDJVMCqpUzBAIGPuWkJWMEAgY+5aQlYwQMbctYR8WDBAxty1hHxYMEBMN4lBYF0wQEw3iUFgXTBA3gIJih9jMEDeAgmKH2MwQK8l5IOeZTBAryXkg55lMEBkzF1LyGcwQGTMXUvIZzBAKqkT0ERoMEAqqRPQRGgwQLbz/dR4aTBAtvP91HhpMEAkufyH9GswQCS5/If0azBAMLsnDwttMEAwuycPC20wQHUCmggbbjBAdQKaCBtuMEA8TtGRXG4wQDxO0ZFcbjBAArwFEhRvMEACvAUSFG8wQDY8vVKWcTBANjy9UpZxMEC0WfW52nIwQLRZ9bnacjBAHqfoSC53MEAep+hILncwQBZqTfOOezBAFmpN8457MECyv+yePHwwQLK/7J48fDBAIEHxY8yFMEAgQfFjzIUwQFfsL7snhzBAV+wvuyeHMEBGJXUCmogwQEYldQKaiDBAC7WmeceJMEALtaZ5x4kwQIhjXdxGizBAiGNd3EaLMEDqBDQRNowwQOoENBE2jDBAHFpkO9+PMEAcWmQ7348wQEwVjErqlDBATBWMSuqUMECuR+F6FJYwQK5H4XoUljBAhxbZzvebMECHFtnO95swQJEPejarnjBAkQ96NqueMEA1XrpJDKIwQDVeukkMojBATDeJQWClMEBMN4lBYKUwQBwN4C2QqDBAHA3gLZCoMECY/5B++6owQJj/kH77qjBASL99HTivMEBIv30dOK8wQHKKjuTyrzBAcoqO5PKvMEBiMlUwKrEwQGIyVTAqsTBA/If029exMED8h/Tb17EwQGsr9pfdszBAayv2l92zMEDyQc9m1bcwQPJBz2bVtzBAAJF++zq4MEAAkX77OrgwQGx4eqUsuzBAbHh6pSy7MEAwTKYKRr0wQDBMpgpGvTBA4umVsgzBMEDi6ZWyDMEwQHzysFBrwjBAfPKwUGvCMEDQ1VbsL8MwQNDVVuwvwzBArrZif9nFMECutmJ/2cUwQOQUHcnlxzBA5BQdyeXHMEBQjZduEsswQFCNl24SyzBAk6mCUUnNMECTqYJRSc0wQPH0SlmG0DBA8fRKWYbQMEAwuycPC9UwQDC7Jw8L1TBAvAUSFD/WMEC8BRIUP9YwQPrt68A52zBA+u3rwDnbMED4wmSqYNwwQPjCZKpg3DBAMCqpE9DcMEAwKqkT0NwwQCKOdXEb3TBAIo51cRvdMEDm0CLb+d4wQObQItv53jBAbjSAt0DiMEBuNIC3QOIwQCIf9GxW5TBAIh/0bFblMECQD3o2q+YwQJAPejar5jBAiIVa07zrMECIhVrTvOswQL8OnDOi7DBAvw6cM6LsMECEDU+vlO0wQIQNT6+U7TBARdjw9ErxMEBF2PD0SvEwQInS3uAL8zBAidLe4AvzMECSXP5D+vUwQJJc/kP69TBAZohjXdz2MEBmiGNd3PYwQMb+snvy+DBAxv6ye/L4MECmeccpOvowQKZ5xyk6+jBAFvvL7sn7MEAW+8vuyfswQNv5fmq8/DBA2/l+arz8MEDM7snDQv0wQMzuycNC/TBA2BLyQc/+MEDYEvJBz/4wQApoImx4AjFACmgibHgCMUAijnVxGwUxQCKOdXEbBTFAEoPAyqEFMUASg8DKoQUxQIJRSZ2ADjFAglFJnYAOMUDE0ytlGRIxQMTTK2UZEjFAsp3vp8YbMUCyne+nxhsxQD/G3LWEHDFAP8bctYQcMUC28/3UeCExQLbz/dR4ITFAMZkqGJUkMUAxmSoYlSQxQJ2AJsKGJzFAnYAmwoYnMUBkXdxGAygxQGRd3EYDKDFAotY07zgtMUCi1jTvOC0xQIofY+5aMjFAih9j7loyMUB24JwRpTUxQHbgnBGlNTFA2PD0Slk2MUDY8PRKWTYxQKwcWmQ7NzFArBxaZDs3MUBw8IXJVDkxQHDwhclUOTFA/Dpwzog6MUD8OnDOiDoxQM/3U+OlOzFAz/dT46U7MUC5/If02z8xQLn8h/TbPzFAfNCzWfVBMUB80LNZ9UExQDMzMzMzQzFAMzMzMzNDMUBIUPwYc0cxQEhQ/BhzRzFAItv5fmpMMUAi2/l+akwxQJAxdy0hTzFAkDF3LSFPMUD8qfHSTVIxQPyp8dJNUjFA3bWEfNBTMUDdtYR80FMxQKyL22gAVzFArIvbaABXMUD4U+Olm1wxQPhT46WbXDFAxm00gLdgMUDGbTSAt2AxQLYV+8vuYTFAthX7y+5hMUDY8PRKWWYxQNjw9EpZZjFA/vZ14JxpMUD+9nXgnGkxQP6ye/KwcDFA/rJ78rBwMUBgdk8eFnIxQGB2Tx4WcjFAzTtO0ZF0MUDNO07RkXQxQH77OnDOeDFAfvs6cM54MUAK+aBns3oxQAr5oGezejFAgnNGlPZ+MUCCc0aU9n4xQAxxrIvbgDFADHGsi9uAMUA0gLdAgoIxQDSAt0CCgjFAX5hMFYyKMUBfmEwVjIoxQCS5/If0izFAJLn8h/SLMUBZF7fRAI4xQFkXt9EAjjFAwaikTkCTMUDBqKROQJMxQB4Wak3zljFAHhZqTfOWMUBGlPYGX5gxQEaU9gZfmDFAMuauJeSbMUAy5q4l5JsxQH77OnDOoDFAfvs6cM6gMUCIY13cRqsxQIhjXdxGqzFAhJ7Nqs+tMUCEns2qz60xQLsnDwu1tjFAuycPC7W2MUCcM6K0N7gxQJwzorQ3uDFARGlv8IW5MUBEaW/whbkxQMIXJlMFuzFAwhcmUwW7MUB46SYxCLwxQHjpJjEIvDFAAN4CCYq/MUAA3gIJir8xQLhAguLHwDFAuECC4sfAMUCZKhiV1MExQJkqGJXUwTFAowG8BRLEMUCjAbwFEsQxQIbrUbgexTFAhutRuB7FMUDmP6TfvsYxQOY/pN++xjFAGARWDi3KMUAYBFYOLcoxQHgLJCh+zDFAeAskKH7MMUCsHFpkO88xQKwcWmQ7zzFAescpOpLTMUB6xyk6ktMxQM6qz9VW1DFAzqrP1VbUMUAubqMBvNUxQC5uowG81TFA1lbsL7vXMUDWVuwvu9cxQA6+MJkq2DFADr4wmSrYMUDFILByaNkxQMUgsHJo2TFACtejcD3aMUAK16NwPdoxQE+vlGWI2zFAT6+UZYjbMUDk8h/Sb98xQOTyH9Jv3zFA8WPMXUvoMUDxY8xdS+gxQIv9Zffk6TFAi/1l9+TpMUCkTkATYesxQKROQBNh6zFATDeJQWDtMUBMN4lBYO0xQEoMAiuH7jFASgwCK4fuMUCQMXctIe8xQJAxdy0h7zFAnKIjufzvMUCcoiO5/O8xQG1Wfa628jFAbVZ9rrbyMUAIPZtVn/MxQAg9m1Wf8zFAsAPnjCj1MUCwA+eMKPUxQAyTqYJR+TFADJOpglH5MUD8qfHSTfoxQPyp8dJN+jFAescpOpL7MUB6xyk6kvsxQL99HThn/DFAv30dOGf8MUC6awn5oP8xQLprCfmg/zFAqDXNO04BMkCoNc07TgEyQGwJ+aBnAzJAbAn5oGcDMkBNhA1PrwQyQE2EDU+vBDJAPgrXo3AFMkA+CtejcAUyQBI2PL1SBjJAEjY8vVIGMkBfKcsQxwoyQF8pyxDHCjJAke18PzUOMkCR7Xw/NQ4yQI4G8BZIEDJAjgbwFkgQMkCMbOf7qREyQIxs5/upETJAlrIMcawTMkCWsgxxrBMyQBRhw9MrFTJAFGHD0ysVMkDYgXNGlBYyQNiBc0aUFjJAylTBqKQWMkDKVMGopBYyQCuHFtnOFzJAK4cW2c4XMkCMSuoENBkyQIxK6gQ0GTJA3GgAb4EcMkDcaABvgRwyQKCJsOHpJTJAoImw4eklMkDFjzF3LSkyQMWPMXctKTJATmIQWDk0MkBOYhBYOTQyQHctIR/0NDJAdy0hH/Q0MkA3iUFg5TgyQDeJQWDlODJAlPYGX5g8MkCU9gZfmDwyQPYoXI/CPTJA9ihcj8I9MkCmLEMc60IyQKYsQxzrQjJAhjjWxW1MMkCGONbFbUwyQHPXEvJBTzJAc9cS8kFPMkAAkX77OlAyQACRfvs6UDJAXW3F/rJTMkBdbcX+slMyQE5iEFg5VDJATmIQWDlUMkDaG3xhMlUyQNobfGEyVTJA3nGKjuRaMkDecYqO5FoyQNjw9EpZXjJA2PD0SlleMkD6D+m3r2MyQPoP6bevYzJAhjjWxW1kMkCGONbFbWQyQIJRSZ2AZjJAglFJnYBmMkBSJ6CJsGkyQFInoImwaTJAih9j7lpqMkCKH2PuWmoyQGbV52orbjJAZtXnaituMkCfPCzUmm4yQJ88LNSabjJA1XjpJjFwMkDVeOkmMXAyQIlBYOXQcjJAiUFg5dByMkAi/fZ14HQyQCL99nXgdDJAdEaU9gZ3MkB0RpT2BncyQNV46SYxgDJA1XjpJjGAMkA8LNSa5oUyQDws1JrmhTJAUGuad5yKMkBQa5p3nIoyQIiFWtO8izJAiIVa07yLMkA+eVioNY0yQD55WKg1jTJAguLHmLuWMkCC4seYu5YyQDq0yHa+lzJAOrTIdr6XMkB/arx0k5gyQH9qvHSTmDJAZ0Rpb/CdMkBnRGlv8J0yQJCg+DHmnjJAkKD4MeaeMkB3vp8aL6UyQHe+nxovpTJAoImw4emtMkCgibDh6a0yQPa52or9rTJA9rnaiv2tMkCPwvUoXK8yQI/C9ShcrzJAJzEIrByyMkAnMQisHLIyQDIIrBxatDJAMgisHFq0MkAtQxzr4rYyQC1DHOvitjJAfNCzWfW5MkB80LNZ9bkyQGxWfa62ujJAbFZ9rra6MkB7FK5H4boyQHsUrkfhujJACM4ZUdq7MkAIzhlR2rsyQIcW2c73uzJAhxbZzve7MkB0RpT2Br8yQHRGlPYGvzJAuECC4sfAMkC4QILix8AyQKg1zTtOwTJAqDXNO07BMkAtQxzr4sYyQC1DHOvixjJA/7J78rDIMkD/snvysMgyQEku/yH9zjJASS7/If3OMkBg5dAi29EyQGDl0CLb0TJAPnlYqDXVMkA+eVioNdUyQIqO5PIf2jJAio7k8h/aMkD5oGez6tsyQPmgZ7Pq2zJAhlrTvOPcMkCGWtO849wyQEoMAiuH3jJASgwCK4feMkCBJsKGp98yQIEmwoan3zJAXkvIBz3jMkBeS8gHPeMyQAAAAAAA6DJAAAAAAADoMkCqglFJnegyQKqCUUmd6DJAXrpJDALrMkBeukkMAusyQCBj7lpC7jJAIGPuWkLuMkAzxLEubvsyQDPEsS5u+zJAK/aX3ZP/MkAr9pfdk/8yQAyTqYJRATNADJOpglEBM0CASL99HQgzQIBIv30dCDNAVn2utmIPM0BWfa62Yg8zQDQRNjy9EjNANBE2PL0SM0CXkA96NhMzQJeQD3o2EzNAPldbsb8UM0A+V1uxvxQzQGQ730+NFzNAZDvfT40XM0BUwaikThgzQFTBqKROGDNARNjw9EoZM0BE2PD0ShkzQBQ/xty1HDNAFD/G3LUcM0D0/dR46R4zQPT91HjpHjNADuAtkKAgM0AO4C2QoCAzQHDwhclUKTNAcPCFyVQpM0AwuycPCzUzQDC7Jw8LNTNAjnVxGw04M0COdXEbDTgzQARWDi2yPTNABFYOLbI9M0CsrdhfdkczQKyt2F92RzNAL90kBoFNM0Av3SQGgU0zQFioNc07TjNAWKg1zTtOM0DFjzF3LVEzQMWPMXctUTNA+aBns+pTM0D5oGez6lMzQDojSnuDVzNAOiNKe4NXM0CY3ZOHhVozQJjdk4eFWjNAs3vysFBbM0Cze/KwUFszQNo9eVioXTNA2j15WKhdM0AkBoGVQ2MzQCQGgZVDYzNAguLHmLtmM0CC4seYu2YzQF5LyAc9azNAXkvIBz1rM0CQwvUoXG8zQJDC9ShcbzNA4C2QoPhxM0DgLZCg+HEzQMpUwaikdjNAylTBqKR2M0DXNO84RX8zQNc07zhFfzNA3gIJih+DM0DeAgmKH4MzQKOSOgFNhDNAo5I6AU2EM0AwTKYKRo0zQDBMpgpGjTNAK/aX3ZOPM0Ar9pfdk48zQLRZ9bnakjNAtFn1udqSM0B0RpT2Bp8zQHRGlPYGnzNAbVZ9rraqM0BtVn2utqozQPMf0m9frzNA8x/Sb1+vM0AMAiuHFrEzQAwCK4cWsTNA+u3rwDmzM0D67evAObMzQKCrrdhftjNAoKut2F+2M0ACvAUSFL8zQAK8BRIUvzNAGlHaG3zBM0AaUdobfMEzQPp+arx0wzNA+n5qvHTDM0AAAAAAAMgzQAAAAAAAyDNAJ6CJsOHJM0AnoImw4ckzQH9qvHST0DNAf2q8dJPQM0C2hHzQs9EzQLaEfNCz0TNAKVyPwvXYM0ApXI/C9dgzQE9AE2HD2zNAT0ATYcPbM0COBvAWSOAzQI4G8BZI4DNANe84RUfiM0A17zhFR+IzQEATYcPT4zNAQBNhw9PjM0CTqYJRSeUzQJOpglFJ5TNAmnecoiPpM0Cad5yiI+kzQKTfvg6c6zNApN++DpzrM0Ay5q4l5OszQDLmriXk6zNA1lbsL7vvM0DWVuwvu+8zQFkXt9EA9jNAWRe30QD2M0AsQxzr4vYzQCxDHOvi9jNA5BQdyeX3M0DkFB3J5fczQLK/7J48/DNAsr/snjz8M0DYgXNGlP4zQNiBc0aU/jNAZMxdS8gHNEBkzF1LyAc0QLWmeccpCjRAtaZ5xykKNEDnjCjtDQ40QOeMKO0NDjRAXP5D+u0TNEBc/kP67RM0QEwVjErqFDRATBWMSuoUNEDjNhrAWxg0QOM2GsBbGDRArkfhehQeNECuR+F6FB40QCUGgZVDIzRAJQaBlUMjNEDF/rJ78ig0QMX+snvyKDRAl/+QfvsqNECX/5B++yo0QLraiv1lLzRAutqK/WUvNEDdJAaBlTM0QN0kBoGVMzRAsHJoke00NECwcmiR7TQ0QPLSTWIQQDRA8tJNYhBANEDcaABvgUQ0QNxoAG+BRDRASOF6FK5HNEBI4XoUrkc0QA3gLZCgUDRADeAtkKBQNEB4CyQoflw0QHgLJCh+XDRALbKd76deNEAtsp3vp140QMZtNIC3YDRAxm00gLdgNEAIPZtVn2M0QAg9m1WfYzRACmgibHhqNEAKaCJseGo0QCo6kst/cDRAKjqSy39wNEAu/yH99nU0QC7/If32dTRAS1mGONZ9NEBLWYY41n00QAgbnl4pgzRACBueXimDNEC4rwPnjIg0QLivA+eMiDRAdLUV+8uONEB0tRX7y440QBrAWyBBkTRAGsBbIEGRNEB0tRX7y5Y0QHS1FfvLljRAoWez6nOdNEChZ7Pqc500QNIA3gIJojRA0gDeAgmiNEAWak3zjqM0QBZqTfOOozRA9UpZhjimNED1SlmGOKY0QO58PzVeqjRA7nw/NV6qNEC9UpYhjq00QL1SliGOrTRAAgmKH2O2NEACCYofY7Y0QFwgQfFjvDRAXCBB8WO8NECcVZ+rrcA0QJxVn6utwDRAx7q4jQbINEDHuriNBsg0QJ7Nqs/VzjRAns2qz9XONECEns2qz9U0QISezarP1TRAQYLix5jbNEBBguLHmNs0QJm7lpAP4jRAmbuWkA/iNEBz1xLyQec0QHPXEvJB5zRAduCcEaXtNEB24JwRpe00QGRd3EYD8DRAZF3cRgPwNEBAE2HD0/M0QEATYcPT8zRAyJi7lpD/NEDImLuWkP80QHxhMlUwCjVAfGEyVTAKNUCBBMWPMQ81QIEExY8xDzVA4seYu5YQNUDix5i7lhA1QNo9eVioFTVA2j15WKgVNUCKQWDl0Bo1QI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bebi103.viz.predictive_ecdf(\n", " samples.prior_predictive[\"ell\"], x_axis_label=\"spindle length (µm)\"\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This looks quite similar to the first model. There are a few negative values, but we will accept this and move forward.\n", "\n", "Next, we would like to look at some scatter plots of spindle length versus droplet diameter. As a start, we can make a plot of the ranges we might expect the data to span using the `bebi103.viz.predictive_regression()` function. For each value of $d$, we plot the percentiles of the spindle lengths drawn from the generative model. We will plot the middle 30th, 60th, 90th, and 99th percentiles to get an idea how the data sets are distributed." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]}},\"selected\":{\"id\":\"4557\"},\"selection_policy\":{\"id\":\"4556\"}},\"id\":\"4314\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"4286\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"4283\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.3\"}};\n", " var render_items = [{\"docid\":\"6c4136a6-9204-4d62-b7ae-4e14fff83523\",\"root_ids\":[\"4283\"],\"roots\":{\"4283\":\"9bc4cfbd-922b-4f0f-ac8a-6829a38ef39a\"}}];\n", " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", "\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " var attempts = 0;\n", " var timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "4283" } }, "output_type": "display_data" } ], "source": [ "bokeh.io.show(\n", " bebi103.viz.predictive_regression(\n", " samples.prior_predictive['ell'],\n", " samples_x=d,\n", " percentiles=[30, 60, 90, 99],\n", " x_axis_label='droplet diameter [µm]',\n", " y_axis_label='spindle length [µm]'\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These results look reasonable; there are very few values of spindle length below zero, and the spindle length is also only rarely greater than the droplet diameter.\n", "\n", "It is also useful to look at individual curves to make sure they are within reason. We can build a quick dashboard to check this out. In fact, **dashboarding** is quite useful for prior (and posterior) predictive checks.\n", "\n", "Note that the interaction will only work in a running Jupyter notebook, and will not work in the HTML rendering of this notebook." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "
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\n", "" ], "text/plain": [ "Row\n", " [0] ParamFunction(function)\n", " [1] Spacer(width=30)\n", " [2] Column\n", " [0] Spacer(height=30)\n", " [1] IntSlider(end=1000, name='draw')\n", " [2] Spacer(height=30)\n", " [3] ParamFunction(function)" ] }, "execution_count": 23, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "4662" } }, "output_type": "execute_result" } ], "source": [ "draw_slider = pn.widgets.IntSlider(name=\"draw\", start=0, end=1000, step=1, value=0)\n", "\n", "\n", "@pn.depends(draw_slider.param.value)\n", "def plot_prior_pred_data(draw):\n", " ell = samples.prior_predictive[\"ell\"].sel(chain=0, draw=draw).values\n", "\n", " return hv.Scatter(\n", " (d, ell), kdims=\"droplet diameter [µm]\", vdims=\"spindle length [µm]\"\n", " ).opts(frame_height=250, frame_width=250, size=2, xlim=(0, 275), ylim=(-5, 140))\n", "\n", "\n", "@pn.depends(draw_slider.param.value)\n", "def markdown_params(draw):\n", " gamma = float(samples.prior[\"gamma_\"].sel(chain=0, draw=draw))\n", " phi = float(samples.prior[\"phi\"].sel(chain=0, draw=draw))\n", " sigma_0 = float(samples.prior[\"sigma_0\"].sel(chain=0, draw=draw))\n", "\n", " return f\"\"\"\n", "| Parameter | Value |\n", "|:-----------:|-----------:|\n", "| γ | {gamma} |\n", "| ϕ | {phi} |\n", "| σ₀ | {sigma_0} |\n", " \"\"\"\n", "\n", "\n", "widgets = pn.Column(\n", " pn.Spacer(height=30), draw_slider, pn.Spacer(height=30), pn.panel(markdown_params)\n", ")\n", "\n", "pn.Row(plot_prior_pred_data, pn.Spacer(width=30), widgets)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We do get some negative spindle lengths, but we may be willing to tolerate these, as they are few. We also see all sorts of behaviors. We see some curves in the asymptotic regime where the spindle length is independent of diameter, some in the linear regime, and some that encompass both regimes.\n", "\n", "So, we now have two sound generative models that we can use to perform parameter estimation. Performing prior predictive checks honed our model, priors including. \n", "\n", "Before moving on to parameter estimation with posterior predictive checks, let's take a look at the data set and think about some further considerations of the model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Checking model assumptions\n", "\n", "Now that we have two generative models in place, let's take a quick look at the data. I'll first replot it, as we did at the top of this notebook." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
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\n", "" ], "text/plain": [ ":Scatter [Droplet Diameter (um)] (Spindle Length (um))" ] }, "execution_count": 24, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "8780" } }, "output_type": "execute_result" } ], "source": [ "hv.Scatter(\n", " data=df,\n", " kdims='Droplet Diameter (um)',\n", " vdims='Spindle Length (um)',\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The experiment more heavily sampled droplet diameters between 20 and 80 µm. It is hard to say if it sampled the droplet diameter-independent regime. We will explore the posterior distribution for this model, informed by these data in the likelihood, in the next lesson. Before we do, we should check to make sure the model assumptions hold.\n", "\n", "In deriving the model, we made a couple key assumptions. First, we assumed that $V_s/V_0 \\ll 1$. Second, we assumed that all spindles have the same aspect ratio, $k$. We should examine how these assumptions hold up and maybe relax those assumptions and build a more complex model if need be." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Is $V_\\mathrm{s} / V_0 \\ll 1$?\n", "\n", "Let's do a quick verification that the droplet volume is indeed much larger than the spindle volume. Remember, the spindle volume for a prolate spheroid of length $l$ and width $w$ is $V_\\mathrm{s} = \\pi l w^2 / 6$." ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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"spindle_volume = np.pi * df[\"Spindle Length (um)\"] * df[\"Spindle Width (um)\"] ** 2 / 6\n", "\n", "# Compute the ratio V_s / V_0 (taking care of units)\n", "vol_ratio = spindle_volume / df[\"Droplet Volume (uL)\"] * 1e-9\n", "\n", "# Plot an ECDF of the results\n", "bokeh.io.show(iqplot.ecdf(vol_ratio.values, x_axis_label=\"Vs/V0\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that for pretty much all spindles that were measured, $V_\\mathrm{s} / V_0$ is small, so this is a sound assumption." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Do all spindles have the same aspect ratio $k$?\n", "\n", "In setting up our model, we assumed that all spindles had the same aspect ratio. 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df['Spindle Width (um)'] / df['Spindle Length (um)']\n", "\n", "# Plot ECDF\n", "bokeh.io.show(iqplot.ecdf(k.values, x_axis_label='k'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The mean aspect ratio is about 0.4, and we see spindle lengths about $\\pm 25\\%$ of that. This could be significant variation. Going forward, we will assume $k$ is constant, but you may wish to perform the analysis with nonconstant $k$ as an exercise.\n", "\n", "Importantly, these checks of the model highlight the importance of checking your assumptions against your data. Always a good idea!" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "bebi103.stan.clean_cmdstan()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python implementation: CPython\n", "Python version : 3.9.7\n", "IPython version : 7.29.0\n", "\n", "numpy : 1.20.3\n", "pandas : 1.3.5\n", "scipy : 1.7.3\n", "cmdstanpy : 1.0.0\n", "arviz : 0.11.4\n", "bokeh : 2.3.3\n", "holoviews : 1.14.6\n", "panel : 0.12.1\n", "iqplot : 0.2.4\n", "bebi103 : 0.1.10\n", "jupyterlab: 3.2.1\n", "\n", "cmdstan : 2.28.2\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,pandas,scipy,cmdstanpy,arviz,bokeh,holoviews,panel,iqplot,bebi103,jupyterlab\n", "print(\"cmdstan :\", bebi103.stan.cmdstan_version())" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 4 }