{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Model building, start to finish: Traffic jams in ants: solution\n", "\n", "[Data set download](https://s3.amazonaws.com/bebi103.caltech.edu/data/ant_traffic.txt)\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In collective behavior, individual interactors often look out only for their own immediate, short term interest within a crowd. This leads to issues like traffic jams on the road or in crowded pedestrian settings. In general, the flow (speed of moving objects times their density), often increases as density increases until hitting a critical point where the increased density gives rise to a traffic jam and flow begins to decrease. [Poissonnier et al.]( https://doi.org/10.7554/eLife.48945) were interested in how ants handle traffic. Unlike human pedestrians or drivers, ants may act more cooperatively in foraging to maximize food acquisition since they share a common goal of raising more young. Today, we will model traffic in ants and see whether they get into jams. \n", "\n", "In order to look at ant collective behavior at different densities, the authors starved ant colonies of varying sizes for a few days, and then provided them a foraging object (sugar!) via a bridge of varying width (B). The ants would climb across the bridge to get to the sugar and then return to colony. The variable colony size and bridge width lead to different densities of foraging ants on the bridge, which the authors took (170!) videos of. They measured density and flow across the bridge from the videos. They were interested in how different older models of traffic jams from human behaviors (A) might fit their data and how this might inform whether ants get into traffic while trying to forage.\n", "\n", "![Ant traffic experiment](ant_Traffic_fig1.jpg)\n", "\n", "As this is an eLife paper, the data is (supposed to be) publicly available. There was an issue with the Dryad repository for the data (the DOI link was broken), but the corresponding author very promptly sent me the data when I emailed her. You can download the data set [here](https://s3.amazonaws.com/bebi103.caltech.edu/data/ant_traffic.txt). We will begin with some exploration for the data before building some models!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "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 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*/\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } 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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, 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.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: 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.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", " 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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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(\n", " df.groupby(\"D\").quantile(0.025).reset_index(),\n", " df.groupby(\"D\").mean().reset_index(),\n", " df.groupby(\"D\").quantile(0.975).reset_index(),\n", " df.groupby(\"D\").count().reset_index(),\n", ")\n", "\n", "p = bokeh.plotting.figure(\n", " frame_width=300,\n", " frame_height=150,\n", " x_axis_label=\"Density k (ant/cm²)\",\n", " y_axis_label=\"Mean flow q (ant/cm/s)\",\n", " title=\"Mean flow at various ant densities\",\n", ")\n", "\n", "for d, lb, ub in zip(df_lower[\"D\"].values, df_lower[\"F\"].values, df_upper[\"F\"].values):\n", " p.line([d, d], [lb, ub], line_width=2)\n", "p.circle(\"D\", \"F\", source=df_mean, alpha=0.75, size=11)\n", "\n", "q = bokeh.plotting.figure(\n", " frame_width=300,\n", " frame_height=150,\n", " x_axis_label=\"Density k (ant/cm²)\",\n", " y_axis_label=\"Number of observations\",\n", " y_axis_type=\"log\",\n", " title=\"Number of observations of ants taking on a given density on the bridge\",\n", ")\n", "\n", "q.circle(\"D\", \"F\", source=df_counts, alpha=1, size=9)\n", "\n", "bokeh.io.show(bokeh.layouts.gridplot([p, q], ncols=2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It looks like the data is pretty linear in the early part of the regime, before the data becomes both much more sparse and may plateau. In order to try to get a model for ant traffic at these variable densities, the authors pulled several models from the literature. They start off with a parabolic shaped model (which makes sense for traffic, at some high density you start to get jammed up and are not able to increase flow, but instead it starts to reduce), an exponential, a modified parabola with an additional shape parameter $\\alpha$, and their own two-phase flow, which describes the data as a piecewise linear relationship with a linearly increasing portion which goes to a flat line at some density. Here are the mathematical models:\n", "\n", "Greenshields:$$q=k \\cdot v_f \\cdot \\left( 1 - \\frac{k}{k_j}\\right) $$\n", "\n", "Underwood:$$q=k \\cdot v_f \\cdot \\mathrm{e}^{\\frac{-k}{k_j}} $$\n", "\n", "Pipes-Munjal:$$q=k \\cdot v_f \\cdot \\left( 1 - \\left(\\frac{k}{k_j}\\right)^\\alpha\\right) $$\n", "\n", "Two-phase flow:\n", "\n", "\\begin{align}\n", "q(k) = \\left\\{\n", "\\begin{array}{lr}\n", "k \\cdot v &\\mathrm{if} \\, k \\leq k_j\\\\\n", "k_j \\cdot v &\\mathrm{if} \\, k > k_j\n", "\\end{array}\n", "\\right.\n", "\\end{align} \n", "\n", "For these equations, $q$ is the flow, $k$ is the density, $k_j$ is the sort of threshold after which either jamming or plateauing of flow increase occurs, $v_f$ is the free speed of interactors without contact, $\\alpha$ defines how fast the flow decays after threshold. With these in hand, we can begin to define a statistical model for our data generating process. This is where you come in! The best way to get comfortable modeling is to do it. Pick one or multiple mathematical models from above and construct a statistical model from it. Code that up in Stan and get samples! For your model, then fit the thinned data set and the averaged data set and make some comparisons of the results. For the sake of time, I have included code from Justin to plot the results once you write down your model and code it in Stan.\n", "\n", "\n", "To decide on priors for some of these quantities, it may be usefult to take a look at what a set of ants looks like when sitting on a 20mm bridge, or to look up the size of an Argentine ant, *Linepithema humile*, the all too common invasive ant all over LA. Here are ants on a 20mm wide bridge:\n", "\n", "![Ants on a 20mm bridge](ants_on_bridge.PNG)\n", "\n", "This image was taken from a video of the experiment used to generate the density data we are analyzing today, which can be [found here](https://doi.org/10.7554/eLife.48945.012)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model implementation\n", "\n", "Statistical model for Greenshields:\n", "\n", "\\begin{align}\n", "&k_j \\sim \\text{Norm}(50, 10),\\\\[1em]\n", "&v_f \\sim \\text{Gamma}(3, 2),\\\\[1em]\n", "&\\sigma \\sim \\text{HalfNorm}(0,1.0),\\\\[1em]\n", "&k_i \\sim \\text{Norm}(\\text{greensheilds}(k_i, v_f, k_j), \\sigma)\\; \\forall i.\n", "\\end{align}\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:compiling stan file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_prior_predictive.stan to exe file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_prior_predictive\n", "INFO:cmdstanpy:compiled model executable: /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_prior_predictive\n" ] } ], "source": [ "sm_prior_pred = cmdstanpy.CmdStanModel(\n", " stan_file=\"ant_traffic_prior_predictive.stan\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the code ready for the prior predictive checks, you are ready to sample!" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:CmdStan start procesing\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c045990ceab141b192e92293b8577880", "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": [ "k = df_thin['D'].values\n", "\n", "k = np.linspace(0, k.max(), 2000)\n", "\n", "data = {\n", " \"N\": len(k),\n", " \"k\": k,\n", " \"k_j_mu\": 50.0,\n", " \"k_j_sigma\": 10.0,\n", " \"v_f_alpha\": 3.0,\n", " \"v_f_beta\": 2.0,\n", " \"sigma_mu\": 0.0,\n", " \"sigma_sigma\": 1.0,\n", " \"alpha_alpha\":3.0,\n", " \"alpha_beta\":2.0\n", "}\n", "\n", "samples = sm_prior_pred.sample(data=data, iter_sampling=1000, fixed_param=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we parse the data for our plots." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "samples_greensheilds = az.from_cmdstanpy(\n", " posterior=samples, prior=samples, prior_predictive=[\"q_greensheilds\"]\n", ")\n", "samples_underwood = az.from_cmdstanpy(\n", " posterior=samples, prior=samples, prior_predictive=[\"q_underwood\"]\n", ")\n", "samples_pipesmunjal = az.from_cmdstanpy(\n", " posterior=samples, prior=samples, prior_predictive=[\"q_pipesmunjal\"]\n", ")\n", "samples_twophase = az.from_cmdstanpy(\n", " posterior=samples, prior=samples, prior_predictive=[\"q_twophase\"]\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use a predictive regression here to get a sense of how we did." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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SeduAoMvE0Dd7yFZODgTQHL41K/tQBNABwGIBqNJE0CbCTtdWFITQDAS7rMNWxNAxBqhCsNjE0BZI1RheGwTQO0rB7gtdRNAgjS6DuN9E0AWPW1lmIYTQKtFILxNjxNAQE7TEgOYE0DUVoZpuKATQGlfOcBtqRNA/WfsFiOyE0CScJ9t2LoTQCZ5UsSNwxNAu4EFG0PME0BPirhx+NQTQOSSa8it3RNAeJseH2PmE0ANpNF1GO8TQKKshMzN9xNANrU3I4MAFEDLvep5OAkUQF/GndDtERRA9M5QJ6MaFECI1wN+WCMUQB3gttQNLBRAsehpK8M0FEBG8RyCeD0UQNv5z9gtRhRAbwKDL+NOFEAECzaGmFcUQJgT6dxNYBRALRycMwNpFEDBJE+KuHEUQFYtAuFtehRA6jW1NyODFEB/PmiO2IsUQBRHG+WNlBRAqE/OO0OdFEA9WIGS+KUUQNFgNOmtrhRAZmnnP2O3FED6cZqWGMAUQI96Te3NyBRAI4MARIPRFEC4i7OaONoUQE2UZvHt4hRA4ZwZSKPrFEB2pcyeWPQUQAquf/UN/RRAn7YyTMMFFUAzv+WieA4VQMjHmPktFxVAXNBLUOMfFUDx2P6mmCgVQIbhsf1NMRVAGupkVAM6FUCv8heruEIVQEP7ygFuSxVA2AN+WCNUFUBsDDGv2FwVQAEV5AWOZRVAlR2XXENuFUAqJkqz+HYVQL8u/QmufxVAUzewYGOIFUDoP2O3GJEVQHxIFg7OmRVAEVHJZIOiFUClWXy7OKsVQDpiLxLusxVAzmriaKO8FUBjc5W/WMUVQPh7SBYOzhVAjIT7bMPWFUAhja7DeN8VQLWVYRou6BVASp4UcePwFUDepsfHmPkVQHOveh5OAhZAB7gtdQMLFkCcwODLuBMWQDHJkyJuHBZAxdFGeSMlFkBa2vnP2C0WQO7irCaONhZAg+tffUM/FkAX9BLU+EcWQKz8xSquUBZAQAV5gWNZFkDVDSzYGGIWQGoW3y7OahZA/h6ShYNzFkCTJ0XcOHwWQCcw+DLuhBZAvDiriaONFkBQQV7gWJYWQOVJETcOnxZAeVLEjcOnFkAOW3fkeLAWQKNjKjsuuRZAN2zdkePBFkDMdJDomMoWQGB9Qz9O0xZA9YX2lQPcFkCJjqnsuOQWQB6XXENu7RZAsp8PmiP2FkBHqMLw2P4WQNywdUeOBxdAcLkonkMQF0AFwtv0+BgXQJnKjkuuIRdALtNBomMqF0DC2/T4GDMXQFfkp0/OOxdA6+xapoNEF0CA9Q39OE0XQBX+wFPuVRdAqQZ0qqNeF0A+DycBWWcXQNIX2lcOcBdAZyCNrsN4F0D7KEAFeYEXQJAx81suihdAJDqmsuOSF0C5QlkJmZsXQE5LDGBOpBdA4lO/tgOtF0B3XHINubUXQAtlJWRuvhdAoG3YuiPHF0A0dosR2c8XQMl+PmiO2BdAXYfxvkPhF0Dyj6QV+ekXQIaYV2yu8hdAG6EKw2P7F0Cwqb0ZGQQYQESycHDODBhA2bojx4MVGEBtw9YdOR4YQALMiXTuJhhAltQ8y6MvGEAr3e8hWTgYQL/longOQRhAVO5Vz8NJGEDp9ggmeVIYQH3/u3wuWxhAEghv0+NjGECmECIqmWwYQDsZ1YBOdRhAzyGI1wN+GEBkKjsuuYYYQPgy7oRujxhAjTuh2yOYGEAiRFQy2aAYQLZMB4mOqRhAS1W630OyGEDfXW02+boYQHRmII2uwxhACG/T42PMGECdd4Y6GdUYQDGAOZHO3RhAxojs54PmGEBbkZ8+Oe8YQO+ZUpXu9xhAhKIF7KMAGUAYq7hCWQkZQK2za5kOEhlAQbwe8MMaGUDWxNFGeSMZQGrNhJ0uLBlA/9U39OM0GUCU3upKmT0ZQCjnnaFORhlAve9Q+ANPGUBR+ANPuVcZQOYAt6VuYBlAeglq/CNpGUAPEh1T2XEZQKMa0KmOehlAOCODAESDGUDNKzZX+YsZQGE06a2ulBlA9jycBGSdGUCKRU9bGaYZQB9OArLOrhlAs1a1CIS3GUBIX2hfOcAZQNxnG7buyBlAcXDODKTRGUAGeYFjWdoZQJqBNLoO4xlAL4rnEMTrGUDDkppnefQZQFibTb4u/RlA7KMAFeQFGkCBrLNrmQ4aQBW1ZsJOFxpAqr0ZGQQgGkA/xsxvuSgaQNPOf8ZuMRpAaNcyHSQ6GkD83+Vz2UIaQJHomMqOSxpAJfFLIURUGkC6+f53+VwaQE4Css6uZRpA4wplJWRuGkB4Exh8GXcaQAwcy9LOfxpAoSR+KYSIGkA1LTGAOZEaQMo15NbumRpAXj6XLaSiGkDzRkqEWasaQIdP/doOtBpAHFiwMcS8GkCxYGOIecUaQEVpFt8uzhpA2nHJNeTWGkBuenyMmd8aQAODL+NO6BpAl4viOQTxGkAslJWQufkaQMCcSOduAhtAVaX7PSQLG0Dqra6U2RMbQH62YeuOHBtAE78UQkQlG0Cnx8eY+S0bQDzQeu+uNhtA0NgtRmQ/G0Bl4eCcGUgbQPnpk/POUBtAjvJGSoRZG0Aj+/mgOWIbQLcDrffuahtATAxgTqRzG0DgFBOlWXwbQHUdxvsOhRtACSZ5UsSNG0CeLiypeZYbQDI33/8unxtAxz+SVuSnG0BcSEWtmbAbQPBQ+ANPuRtAhVmrWgTCG0AZYl6xucobQK5qEQhv0xtAQnPEXiTcG0DXe3e12eQbQGuEKgyP7RtAAI3dYkT2G0CVlZC5+f4bQCmeQxCvBxxAvqb2ZmQQHEBSr6m9GRkcQOe3XBTPIRxAe8APa4QqHEAQycLBOTMcQKTRdRjvOxxAOdoob6REHEDO4tvFWU0cQGLrjhwPVhxA9/NBc8ReHECL/PTJeWccQCAFqCAvcBxAtA1bd+R4HEBJFg7OmYEcQN0ewSRPihxAcid0ewSTHEAGMCfSuZscQJs42ihvpBxAMEGNfyStHEDESUDW2bUcQFlS8yyPvhxA7Vqmg0THHECCY1na+c8cQBZsDDGv2BxAq3S/h2ThHEA/fXLeGeocQNSFJTXP8hxAaY7Yi4T7HED9loviOQQdQJKfPjnvDB1AJqjxj6QVHUC7sKTmWR4dQE+5Vz0PJx1A5MEKlMQvHUB4yr3qeTgdQA3TcEEvQR1AotsjmORJHUA25NbumVIdQMvsiUVPWx1AX/U8nARkHUD0/e/yuWwdQIgGo0lvdR1AHQ9WoCR+HUCxFwn32YYdQEYgvE2Pjx1A2yhvpESYHUBvMSL7+aAdQAQ61VGvqR1AmEKIqGSyHUAtSzv/GbsdQMFT7lXPwx1AVlyhrITMHUDqZFQDOtUdQH9tB1rv3R1AFHa6sKTmHUCofm0HWu8dQD2HIF4P+B1A0Y/TtMQAHkBmmIYLegkeQPqgOWIvEh5Aj6nsuOQaHkAjsp8PmiMeQLi6UmZPLB5ATcMFvQQ1HkDhy7gTuj0eQHbUa2pvRh5ACt0ewSRPHkCf5dEX2lceQDPuhG6PYB5AyPY3xURpHkBc/+ob+nEeQPEHnnKveh5AhhBRyWSDHkAaGQQgGoweQK8ht3bPlB5AQypqzYSdHkDYMh0kOqYeQGw70Hrvrh5AAUSD0aS3HkCVTDYoWsAeQCpV6X4PyR5Av12c1cTRHkBTZk8setoeQOhuAoMv4x5AfHe12eTrHkARgGgwmvQeQKWIG4dP/R5AOpHO3QQGH0DOmYE0ug4fQGOiNItvFx9A+Krn4SQgH0CMs5o42igfQCG8TY+PMR9AtcQA5kQ6H0BKzbM8+kIfQN7VZpOvSx9Ac94Z6mRUH0AH58xAGl0fQJzvf5fPZR9AMfgy7oRuH0DFAOZEOncfQFoJmZvvfx9A7hFM8qSIH0CDGv9IWpEfQBcjsp8Pmh9ArCtl9sSiH0BANBhNeqsfQNU8y6MvtB9AakV++uS8H0D+TTFRmsUfQJNW5KdPzh9AJ1+X/gTXH0C8Z0pVut8fQFBw/atv6B9A5XiwAiXxH0B5gWNZ2vkfQAdFC9hHASBAUclkg6IFIECcTb4u/QkgQObRF9pXDiBAMFZxhbISIEB62sowDRcgQMVeJNxnGyBAD+N9h8IfIEBZZ9cyHSQgQKPrMN53KCBA7m+KidIsIEA49OM0LTEgQIJ4PeCHNSBAzfyWi+I5IEAXgfA2PT4gQGEFSuKXQiBAq4mjjfJGIED2Df04TUsgQECSVuSnTyBAihawjwJUIEDVmgk7XVggQB8fY+a3XCBAaaO8kRJhIECzJxY9bWUgQP6rb+jHaSBASDDJkyJuIECStCI/fXIgQNw4fOrXdiBAJ73VlTJ7IEBxQS9BjX8gQLvFiOzngyBABkril0KIIEBQzjtDnYwgQJpSle73kCBA5NbumVKVIEAvW0hFrZkgQHnfofAHniBAw2P7m2KiIEAO6FRHvaYgQFhsrvIXqyBAovAHnnKvIEDsdGFJzbMgQDf5uvQnuCBAgX0UoIK8IEDLAW5L3cAgQBWGx/Y3xSBAYAohopLJIECqjnpN7c0gQPQS1PhH0iBAP5ctpKLWIECJG4dP/dogQNOf4PpX3yBAHSQ6prLjIEBoqJNRDeggQLIs7fxn7CBA/LBGqMLwIEBHNaBTHfUgQJG5+f53+SBA2z1TqtL9IEAlwqxVLQIhQHBGBgGIBiFAuspfrOIKIUAET7lXPQ8hQE7TEgOYEyFAmVdsrvIXIUDj28VZTRwhQC1gHwWoICFAeOR4sAIlIUDCaNJbXSkhQAztKwe4LSFAVnGFshIyIUCh9d5dbTYhQOt5OAnIOiFANf6RtCI/IUCAgutffUMhQMoGRQvYRyFAFIuetjJMIUBeD/hhjVAhQKmTUQ3oVCFA8xeruEJZIUA9nARknV0hQIcgXg/4YSFA0qS3ulJmIUAcKRFmrWohQGatahEIbyFAsTHEvGJzIUD7tR1ovXchQEU6dxMYfCFAj77QvnKAIUDaQipqzYQhQCTHgxUoiSFAbkvdwIKNIUC4zzZs3ZEhQANUkBc4liFATdjpwpKaIUCXXENu7Z4hQOLgnBlIoyFALGX2xKKnIUB26U9w/ashQMBtqRtYsCFAC/ICx7K0IUBVdlxyDbkhQJ/6tR1ovSFA6n4PycLBIUA0A2l0HcYhQH6Hwh94yiFAyAscy9LOIUATkHV2LdMhQF0UzyGI1yFAp5gozeLbIUDxHIJ4PeAhQDyh2yOY5CFAhiU1z/LoIUDQqY56Te0hQBsu6CWo8SFAZbJB0QL2IUCvNpt8XfohQPm69Ce4/iFARD9O0xIDIkCOw6d+bQciQNhHASrICyJAI8xa1SIQIkBtULSAfRQiQLfUDSzYGCJAAVln1zIdIkBM3cCCjSEiQJZhGi7oJSJA4OVz2UIqIkAqas2EnS4iQHXuJjD4MiJAv3KA21I3IkAJ99mGrTsiQFR7MzIIQCJAnv+M3WJEIkDog+aIvUgiQDIIQDQYTSJAfYyZ33JRIkDHEPOKzVUiQBGVTDYoWiJAXBmm4YJeIkCmnf+M3WIiQPAhWTg4ZyJAOqay45JrIkCFKgyP7W8iQM+uZTpIdCJAGTO/5aJ4IkBjtxiR/XwiQK47cjxYgSJA+L/L57KFIkBCRCWTDYoiQI3Ifj5ojiJA10zY6cKSIkAh0TGVHZciQGtVi0B4myJAttnk69KfIkAAXj6XLaQiQEril0KIqCJAlWbx7eKsIkDf6kqZPbEiQClvpESYtSJAc/P97/K5IkC+d1ebTb4iQAj8sEaowiJAUoAK8gLHIkCcBGSdXcsiQOeIvUi4zyJAMQ0X9BLUIkB7kXCfbdgiQMYVykrI3CJAEJoj9iLhIkBaHn2hfeUiQKSi1kzY6SJA7yYw+DLuIkA5q4mjjfIiQIMv407o9iJAzrM8+kL7IkAYOJalnf8iQGK871D4AyNArEBJ/FIII0D3xKKnrQwjQEFJ/FIIESNAi81V/mIVI0DVUa+pvRkjQCDWCFUYHiNAalpiAHMiI0C03rurzSYjQP9iFVcoKyNASeduAoMvI0CTa8it3TMjQN3vIVk4OCNAKHR7BJM8I0By+NSv7UAjQLx8LltIRSNABwGIBqNJI0BRheGx/U0jQJsJO11YUiNA5Y2UCLNWI0AwEu6zDVsjQHqWR19oXyNAxBqhCsNjI0AOn/q1HWgjQFkjVGF4bCNAo6etDNNwI0DtKwe4LXUjQDiwYGOIeSNAgjS6DuN9I0DMuBO6PYIjQBY9bWWYhiNAYcHGEPOKI0CrRSC8TY8jQPXJeWeokyNAQE7TEgOYI0CK0iy+XZwjQNRWhmm4oCNAHtvfFBOlI0BpXznAbakjQLPjkmvIrSNA/WfsFiOyI0BH7EXCfbYjQJJwn23YuiNA3PT4GDO/I0AmeVLEjcMjQHH9q2/oxyNAu4EFG0PMI0AFBl/GndAjQE+KuHH41CNAmg4SHVPZI0DkkmvIrd0jQC4XxXMI4iNAeJseH2PmI0DDH3jKveojQA2k0XUY7yNAVygrIXPzI0CirITMzfcjQOww3nco/CNANrU3I4MAJECAOZHO3QQkQMu96nk4CSRAFUJEJZMNJEBfxp3Q7REkQKpK93tIFiRA9M5QJ6MaJEA+U6rS/R4kQIjXA35YIyRA01tdKbMnJEAd4LbUDSwkQGdkEIBoMCRAsehpK8M0JED8bMPWHTkkQEbxHIJ4PSRAkHV2LdNBJEDb+c/YLUYkQCV+KYSISiRAbwKDL+NOJEC5htzaPVMkQAQLNoaYVyRATo+PMfNbJECYE+ncTWAkQOOXQoioZCRALRycMwNpJEB3oPXeXW0kQMEkT4q4cSRADKmoNRN2JEBWLQLhbXokQKCxW4zIfiRA6jW1NyODJEA1ug7jfYckQH8+aI7YiyRAycLBOTOQJEAURxvljZQkQF7LdJDomCRAqE/OO0OdJEDy0yfnnaEkQD1YgZL4pSRAh9zaPVOqJEDRYDTpra4kQBzljZQIsyRAZmnnP2O3JECw7UDrvbskQPpxmpYYwCRARfbzQXPEJECPek3tzcgkQNn+ppgozSRAI4MARIPRJEBuB1rv3dUkQLiLs5o42iRAAhANRpPeJEBNlGbx7eIkQJcYwJxI5yRA4ZwZSKPrJEArIXPz/e8kQHalzJ5Y9CRAwCkmSrP4JEAKrn/1Df0kQFUy2aBoASVAn7YyTMMFJUDpOoz3HQolQDO/5aJ4DiVAfkM/TtMSJUDIx5j5LRclQBJM8qSIGyVAXNBLUOMfJUCnVKX7PSQlQPHY/qaYKCVAO11YUvMsJUCG4bH9TTElQNBlC6moNSVAGupkVAM6JUBkbr7/XT4lQK/yF6u4QiVA+XZxVhNHJUBD+8oBbkslQI5/JK3ITyVA2AN+WCNUJUAiiNcDflglQGwMMa/YXCVAt5CKWjNhJUABFeQFjmUlQEuZPbHoaSVAlR2XXENuJUDgofAHnnIlQComSrP4diVAdKqjXlN7JUC/Lv0Jrn8lQAmzVrUIhCVAUzewYGOIJUCduwkMvowlQOg/Y7cYkSVAMsS8YnOVJUB8SBYOzpklQMfMb7koniVAEVHJZIOiJUBb1SIQ3qYlQKVZfLs4qyVA8N3VZpOvJUA6Yi8S7rMlQITmiL1IuCVAzmriaKO8JUAZ7zsU/sAlQGNzlb9YxSVArffuarPJJUD4e0gWDs4lQEIAosFo0iVAjIT7bMPWJUDWCFUYHtslQCGNrsN43yVAaxEIb9PjJUC1lWEaLuglQP8Zu8WI7CVASp4UcePwJUCUIm4cPvUlQN6mx8eY+SVAKSshc/P9JUBzr3oeTgImQL0z1MmoBiZAB7gtdQMLJkBSPIcgXg8mQJzA4Mu4EyZA5kQ6dxMYJkAxyZMibhwmQHtN7c3IICZAxdFGeSMlJkAPVqAkfikmQFra+c/YLSZApF5TezMyJkDu4qwmjjYmQDhnBtLoOiZAg+tffUM/JkDNb7konkMmQBf0EtT4RyZAYnhsf1NMJkCs/MUqrlAmQPaAH9YIVSZAQAV5gWNZJkCLidIsvl0mQNUNLNgYYiZAH5KFg3NmJkBqFt8uzmomQLSaONoobyZA/h6ShYNzJkBIo+sw3ncmQJMnRdw4fCZA3aueh5OAJkAnMPgy7oQmQHG0Ud5IiSZAvDiriaONJkAGvQQ1/pEmQFBBXuBYliZAm8W3i7OaJkDlSRE3Dp8mQC/OauJooyZAeVLEjcOnJkDE1h05HqwmQA5bd+R4sCZAWN/Qj9O0JkCjYyo7LrkmQO3ng+aIvSZAN2zdkePBJkCB8DY9PsYmQMx0kOiYyiZAFvnpk/POJkBgfUM/TtMmQKoBneqo1yZA9YX2lQPcJkA/ClBBXuAmQImOqey45CZA1BIDmBPpJkAel1xDbu0mQGgbtu7I8SZAsp8PmiP2JkD9I2lFfvomQEeowvDY/iZAkSwcnDMDJ0DcsHVHjgcnQCY1z/LoCydAcLkonkMQJ0C6PYJJnhQnQAXC2/T4GCdAT0Y1oFMdJ0CZyo5LriEnQONO6PYIJidALtNBomMqJ0B4V5tNvi4nQMLb9PgYMydADWBOpHM3J0BX5KdPzjsnQKFoAfsoQCdA6+xapoNEJ0A2cbRR3kgnQID1Df04TSdAynlnqJNRJ0AV/sBT7lUnQF+CGv9IWidAqQZ0qqNeJ0Dzis1V/mInQD4PJwFZZydAiJOArLNrJ0DSF9pXDnAnQBycMwNpdCdAZyCNrsN4J0CxpOZZHn0nQPsoQAV5gSdARq2ZsNOFJ0CQMfNbLoonQNq1TAeJjidAJDqmsuOSJ0Bvvv9dPpcnQLlCWQmZmydAA8eytPOfJ0BOSwxgTqQnQJjPZQupqCdA4lO/tgOtJ0As2BhiXrEnQHdccg25tSdAweDLuBO6J0ALZSVkbr4nQFXpfg/JwidAoG3YuiPHJ0Dq8TFmfssnQDR2ixHZzydAf/rkvDPUJ0DJfj5ojtgnQBMDmBPp3CdAXYfxvkPhJ0CoC0tqnuUnQPKPpBX56SdAPBT+wFPuJ0CGmFdsrvInQNEcsRcJ9ydAG6EKw2P7J0BlJWRuvv8nQLCpvRkZBChA+i0XxXMIKEBEsnBwzgwoQI42yhspEShA2bojx4MVKEAjP31y3hkoQG3D1h05HihAuEcwyZMiKEACzIl07iYoQExQ4x9JKyhAltQ8y6MvKEDhWJZ2/jMoQCvd7yFZOChAdWFJzbM8KEC/5aJ4DkEoQApq/CNpRShAVO5Vz8NJKECecq96Hk4oQOn2CCZ5UihAM3ti0dNWKEB9/7t8LlsoQMeDFSiJXyhAEghv0+NjKEBcjMh+PmgoQKYQIiqZbChA8ZR71fNwKEA7GdWATnUoQIWdLiypeShAzyGI1wN+KEAapuGCXoIoQGQqOy65hihArq6U2ROLKED4Mu6Ebo8oQEO3RzDJkyhAjTuh2yOYKEDXv/qGfpwoQCJEVDLZoChAbMit3TOlKEC2TAeJjqkoQADRYDTprShAS1W630OyKECV2ROLnrYoQN9dbTb5uihAKuLG4VO/KEB0ZiCNrsMoQL7qeTgJyChACG/T42PMKEBT8yyPvtAoQJ13hjoZ1ShA5/vf5XPZKEAxgDmRzt0oQHwEkzwp4ihAxojs54PmKEAQDUaT3uooQFuRnz457yhApRX56ZPzKEDvmVKV7vcoQDkerEBJ/ChAhKIF7KMAKUDOJl+X/gQpQBiruEJZCSlAYy8S7rMNKUCts2uZDhIpQPc3xURpFilAQbwe8MMaKUCMQHibHh8pQNbE0UZ5IylAIEkr8tMnKUBqzYSdLiwpQLVR3kiJMClA/9U39OM0KUBJWpGfPjkpQJTe6kqZPSlA3mJE9vNBKUAo552hTkYpQHJr90ypSilAve9Q+ANPKUAHdKqjXlMpQFH4A0+5VylAnHxd+hNcKUDmALelbmApQDCFEFHJZClAeglq/CNpKUDFjcOnfm0pQA8SHVPZcSlAWZZ2/jN2KUCjGtCpjnopQO6eKVXpfilAOCODAESDKUCCp9yrnocpQM0rNlf5iylAF7CPAlSQKUBhNOmtrpQpQKu4QlkJmSlA9jycBGSdKUBAwfWvvqEpQIpFT1sZpilA1cmoBnSqKUAfTgKyzq4pQGnSW10psylAs1a1CIS3KUD+2g603rspQEhfaF85wClAkuPBCpTEKUDcZxu27sgpQCfsdGFJzSlAcXDODKTRKUC79Ce4/tUpQAZ5gWNZ2ilAUP3aDrTeKUCagTS6DuMpQOQFjmVp5ylAL4rnEMTrKUB5DkG8HvApQMOSmmd59ClADhf0EtT4KUBYm02+Lv0pQKIfp2mJASpA7KMAFeQFKkA3KFrAPgoqQIGss2uZDipAyzANF/QSKkAVtWbCThcqQGA5wG2pGypAqr0ZGQQgKkD0QXPEXiQqQD/GzG+5KCpAiUomGxQtKkDTzn/GbjEqQB1T2XHJNSpAaNcyHSQ6KkCyW4zIfj4qQPzf5XPZQipARmQ/HzRHKkCR6JjKjksqQNts8nXpTypAJfFLIURUKkBwdaXMnlgqQLr5/nf5XCpABH5YI1RhKkBOArLOrmUqQJmGC3oJaipA4wplJWRuKkAtj77QvnIqQHgTGHwZdypAwpdxJ3R7KkAMHMvSzn8qQFagJH4phCpAoSR+KYSIKkDrqNfU3owqQDUtMYA5kSpAf7GKK5SVKkDKNeTW7pkqQBS6PYJJnipAXj6XLaSiKkCpwvDY/qYqQPNGSoRZqypAPcujL7SvKkCHT/3aDrQqQNLTVoZpuCpAHFiwMcS8KkBm3AndHsEqQLFgY4h5xSpA++S8M9TJKkBFaRbfLs4qQI/tb4qJ0ipA2nHJNeTWKkAk9iLhPtsqQG56fIyZ3ypAuP7VN/TjKkADgy/jTugqQE0HiY6p7CpAl4viOQTxKkDiDzzlXvUqQCyUlZC5+SpAdhjvOxT+KkDAnEjnbgIrQAshopLJBitAVaX7PSQLK0CfKVXpfg8rQOqtrpTZEytANDIIQDQYK0B+tmHrjhwrQMg6u5bpICtAE78UQkQlK0BdQ27tnikrQKfHx5j5LStA8UshRFQyK0A80HrvrjYrQIZU1JoJOytA0NgtRmQ/K0AbXYfxvkMrQGXh4JwZSCtAr2U6SHRMK0D56ZPzzlArQERu7Z4pVStAjvJGSoRZK0DYdqD13l0rQCP7+aA5YitAbX9TTJRmK0C3A6337morQAGIBqNJbytATAxgTqRzK0CWkLn5/ncrQOAUE6VZfCtAKplsULSAK0B1Hcb7DoUrQL+hH6dpiStACSZ5UsSNK0BUqtL9HpIrQJ4uLKl5litA6LKFVNSaK0AyN9//Lp8rQH27OKuJoytAxz+SVuSnK0ARxOsBP6wrQFxIRa2ZsCtApsyeWPS0K0DwUPgDT7krQDrVUa+pvStAhVmrWgTCK0DP3QQGX8YrQBliXrG5yitAY+a3XBTPK0CuahEIb9MrQPjuarPJ1ytAQnPEXiTcK0CN9x0Kf+ArQNd7d7XZ5CtAIQDRYDTpK0BrhCoMj+0rQLYIhLfp8StAAI3dYkT2K0BKETcOn/orQJWVkLn5/itA3xnqZFQDLEApnkMQrwcsQHMinbsJDCxAvqb2ZmQQLEAIK1ASvxQsQFKvqb0ZGSxAnDMDaXQdLEDnt1wUzyEsQDE8tr8pJixAe8APa4QqLEDGRGkW3y4sQBDJwsE5MyxAWk0cbZQ3LECk0XUY7zssQO9Vz8NJQCxAOdoob6RELECDXoIa/0gsQM7i28VZTSxAGGc1cbRRLEBi644cD1YsQKxv6MdpWixA9/NBc8ReLEBBeJseH2MsQIv89Ml5ZyxA1YBOddRrLEAgBaggL3AsQGqJAcyJdCxAtA1bd+R4LED/kbQiP30sQEkWDs6ZgSxAk5pnefSFLEDdHsEkT4osQCijGtCpjixAcid0ewSTLEC8q80mX5csQAYwJ9K5myxAUbSAfRSgLECbONoob6QsQOW8M9TJqCxAMEGNfyStLEB6xeYqf7EsQMRJQNbZtSxADs6ZgTS6LEBZUvMsj74sQKPWTNjpwixA7Vqmg0THLEA43/8un8ssQIJjWdr5zyxAzOeyhVTULEAWbAwxr9gsQGHwZdwJ3SxAq3S/h2ThLED1+Bgzv+UsQD99ct4Z6ixAigHMiXTuLEDUhSU1z/IsQB4Kf+Ap9yxAaY7Yi4T7LECzEjI33/8sQP2Wi+I5BC1ARxvljZQILUCSnz457wwtQNwjmORJES1AJqjxj6QVLUBxLEs7/xktQLuwpOZZHi1ABTX+kbQiLUBPuVc9DyctQJo9sehpKy1A5MEKlMQvLUAuRmQ/HzQtQHjKvep5OC1Aw04XltQ8LUAN03BBL0EtQFdXyuyJRS1AotsjmORJLUDsX31DP04tQDbk1u6ZUi1AgGgwmvRWLUDL7IlFT1stQBVx4/CpXy1AX/U8nARkLUCqeZZHX2gtQPT97/K5bC1APoJJnhRxLUCIBqNJb3UtQNOK/PTJeS1AHQ9WoCR+LUBnk69Lf4ItQLEXCffZhi1A/JtiojSLLUBGILxNj48tQJCkFfnpky1A2yhvpESYLUAlrchPn5wtQG8xIvv5oC1AubV7plSlLUAEOtVRr6ktQE6+Lv0Jri1AmEKIqGSyLUDjxuFTv7YtQC1LO/8Zuy1Ad8+UqnS/LUDBU+5Vz8MtQAzYRwEqyC1AVlyhrITMLUCg4PpX39AtQOpkVAM61S1ANemtrpTZLUB/bQda790tQMnxYAVK4i1AFHa6sKTmLUBe+hNc/+otQKh+bQda7y1A8gLHsrTzLUA9hyBeD/gtQIcLeglq/C1A0Y/TtMQALkAcFC1gHwUuQGaYhgt6CS5AsBzgttQNLkD6oDliLxIuQEUlkw2KFi5Aj6nsuOQaLkDZLUZkPx8uQCOynw+aIy5Abjb5uvQnLkC4ulJmTywuQAI/rBGqMC5ATcMFvQQ1LkCXR19oXzkuQOHLuBO6PS5AK1ASvxRCLkB21Gtqb0YuQMBYxRXKSi5ACt0ewSRPLkBVYXhsf1MuQJ/l0RfaVy5A6WkrwzRcLkAz7oRuj2AuQH5y3hnqZC5AyPY3xURpLkASe5Fwn20uQFz/6hv6cS5Ap4NEx1R2LkDxB55yr3ouQDuM9x0Kfy5AhhBRyWSDLkDQlKp0v4cuQBoZBCAajC5AZJ1dy3SQLkCvIbd2z5QuQPmlECIqmS5AQypqzYSdLkCNrsN436EuQNgyHSQ6pi5AIrd2z5SqLkBsO9B6764uQLe/KSZKsy5AAUSD0aS3LkBLyNx8/7suQJVMNihawC5A4NCP07TELkAqVel+D8kuQHTZQipqzS5Av12c1cTRLkAJ4vWAH9YuQFNmTyx62i5Aneqo19TeLkDobgKDL+MuQDLzWy6K5y5AfHe12eTrLkDG+w6FP/AuQBGAaDCa9C5AWwTC2/T4LkCliBuHT/0uQPAMdTKqAS9AOpHO3QQGL0CEFSiJXwovQM6ZgTS6Di9AGR7b3xQTL0BjojSLbxcvQK0mjjbKGy9A+Krn4SQgL0BCL0GNfyQvQIyzmjjaKC9A1jf04zQtL0AhvE2PjzEvQGtApzrqNS9AtcQA5kQ6L0D/SFqRnz4vQErNszz6Qi9AlFEN6FRHL0De1WaTr0svQClawD4KUC9Ac94Z6mRUL0C9YnOVv1gvQAfnzEAaXS9AUmsm7HRhL0Cc73+Xz2UvQOZz2UIqai9AMfgy7oRuL0B7fIyZ33IvQMUA5kQ6dy9AD4U/8JR7L0BaCZmb738vQKSN8kZKhC9A7hFM8qSIL0A4lqWd/4wvQIMa/0hakS9AzZ5Y9LSVL0AXI7KfD5ovQGKnC0tqni9ArCtl9sSiL0D2r76hH6cvQEA0GE16qy9Ai7hx+NSvL0DVPMujL7QvQB/BJE+KuC9AakV++uS8L0C0ydelP8EvQP5NMVGaxS9ASNKK/PTJL0CTVuSnT84vQN3aPVOq0i9AJ1+X/gTXL0Bx4/CpX9svQLxnSlW63y9ABuyjABXkL0BQcP2rb+gvQJv0VlfK7C9A5XiwAiXxL0Av/Qmuf/UvQHmBY1na+S9AxAW9BDX+L0AHRQvYRwEwQCwHuC11AzBAUclkg6IFMEB2ixHZzwcwQJxNvi79CTBAwQ9rhCoMMEDm0RfaVw4wQAuUxC+FEDBAMFZxhbISMEBVGB7b3xQwQHrayjANFzBAoJx3hjoZMEDFXiTcZxswQOog0TGVHTBAD+N9h8IfMEA0pSrd7yEwQFln1zIdJDBAfimEiEomMECj6zDedygwQMmt3TOlKjBA7m+KidIsMEATMjff/y4wQDj04zQtMTBAXbaQilozMECCeD3ghzUwQKc66jW1NzBAzfyWi+I5MEDyvkPhDzwwQBeB8DY9PjBAPEOdjGpAMEBhBUril0IwQIbH9jfFRDBAq4mjjfJGMEDRS1DjH0kwQPYN/ThNSzBAG9CpjnpNMEBAklbkp08wQGVUAzrVUTBAihawjwJUMECv2FzlL1YwQNWaCTtdWDBA+ly2kIpaMEAfH2Pmt1wwQEThDzzlXjBAaaO8kRJhMECOZWnnP2MwQLMnFj1tZTBA2OnCkppnMED+q2/ox2kwQCNuHD71azBASDDJkyJuMEBt8nXpT3AwQJK0Ij99cjBAt3bPlKp0MEDcOHzq13YwQAL7KEAFeTBAJ73VlTJ7MEBMf4LrX30wQHFBL0GNfzBAlgPclrqBMEC7xYjs54MwQOCHNUIVhjBABkril0KIMEArDI/tb4owQFDOO0OdjDBAdZDomMqOMECaUpXu95AwQL8UQkQlkzBA5NbumVKVMEAKmZvvf5cwQC9bSEWtmTBAVB31mtqbMEB536HwB54wQJ6hTkY1oDBAw2P7m2KiMEDoJajxj6QwQA7oVEe9pjBAM6oBneqoMEBYbK7yF6swQH0uW0hFrTBAovAHnnKvMEDHsrTzn7EwQOx0YUnNszBAETcOn/q1MEA3+br0J7gwQFy7Z0pVujBAgX0UoIK8MECmP8H1r74wQMsBbkvdwDBA8MMaoQrDMEAVhsf2N8UwQDtIdExlxzBAYAohopLJMECFzM33v8swQKqOek3tzTBAz1AnoxrQMED0EtT4R9IwQBnVgE511DBAP5ctpKLWMEBkWdr5z9gwQIkbh0/92jBArt0zpSrdMEDTn+D6V98wQPhhjVCF4TBAHSQ6prLjMEBD5ub73+UwQGiok1EN6DBAjWpApzrqMECyLO38Z+wwQNfumVKV7jBA/LBGqMLwMEAhc/P97/IwQEc1oFMd9TBAbPdMqUr3MECRufn+d/kwQLZ7plSl+zBA2z1TqtL9MEAAAAAAAAAxQAAAAAAAADFA2z1TqtL9MEC2e6ZUpfswQJG5+f53+TBAbPdMqUr3MEBHNaBTHfUwQCFz8/3v8jBA/LBGqMLwMEDX7plSle4wQLIs7fxn7DBAjWpApzrqMEBoqJNRDegwQEPm5vvf5TBAHSQ6prLjMED4YY1QheEwQNOf4PpX3zBArt0zpSrdMECJG4dP/dowQGRZ2vnP2DBAP5ctpKLWMEAZ1YBOddQwQPQS1PhH0jBAz1AnoxrQMECqjnpN7c0wQIXMzfe/yzBAYAohopLJMEA7SHRMZccwQBWGx/Y3xTBA8MMaoQrDMEDLAW5L3cAwQKY/wfWvvjBAgX0UoIK8MEBcu2dKVbowQDf5uvQnuDBAETcOn/q1MEDsdGFJzbMwQMeytPOfsTBAovAHnnKvMEB9LltIRa0wQFhsrvIXqzBAM6oBneqoMEAO6FRHvaYwQOglqPGPpDBAw2P7m2KiMECeoU5GNaAwQHnfofAHnjBAVB31mtqbMEAvW0hFrZkwQAqZm+9/lzBA5NbumVKVMEC/FEJEJZMwQJpSle73kDBAdZDomMqOMEBQzjtDnYwwQCsMj+1vijBABkril0KIMEDghzVCFYYwQLvFiOzngzBAlgPclrqBMEBxQS9BjX8wQEx/gutffTBAJ73VlTJ7MEAC+yhABXkwQNw4fOrXdjBAt3bPlKp0MECStCI/fXIwQG3ydelPcDBASDDJkyJuMEAjbhw+9WswQP6rb+jHaTBA2OnCkppnMECzJxY9bWUwQI5laec/YzBAaaO8kRJhMEBE4Q885V4wQB8fY+a3XDBA+ly2kIpaMEDVmgk7XVgwQK/YXOUvVjBAihawjwJUMEBlVAM61VEwQECSVuSnTzBAG9CpjnpNMED2Df04TUswQNFLUOMfSTBAq4mjjfJGMECGx/Y3xUQwQGEFSuKXQjBAPEOdjGpAMEAXgfA2PT4wQPK+Q+EPPDBAzfyWi+I5MECnOuo1tTcwQIJ4PeCHNTBAXbaQilozMEA49OM0LTEwQBMyN9//LjBA7m+KidIsMEDJrd0zpSowQKPrMN53KDBAfimEiEomMEBZZ9cyHSQwQDSlKt3vITBAD+N9h8IfMEDqINExlR0wQMVeJNxnGzBAoJx3hjoZMEB62sowDRcwQFUYHtvfFDBAMFZxhbISMEALlMQvhRAwQObRF9pXDjBAwQ9rhCoMMECcTb4u/QkwQHaLEdnPBzBAUclkg6IFMEAsB7gtdQMwQAdFC9hHATBAxAW9BDX+L0B5gWNZ2vkvQC/9Ca5/9S9A5XiwAiXxL0Cb9FZXyuwvQFBw/atv6C9ABuyjABXkL0C8Z0pVut8vQHHj8Klf2y9AJ1+X/gTXL0Dd2j1TqtIvQJNW5KdPzi9ASNKK/PTJL0D+TTFRmsUvQLTJ16U/wS9AakV++uS8L0AfwSRPirgvQNU8y6MvtC9Ai7hx+NSvL0BANBhNeqsvQPavvqEfpy9ArCtl9sSiL0BipwtLap4vQBcjsp8Pmi9AzZ5Y9LSVL0CDGv9IWpEvQDiWpZ3/jC9A7hFM8qSIL0CkjfJGSoQvQFoJmZvvfy9AD4U/8JR7L0DFAOZEOncvQHt8jJnfci9AMfgy7oRuL0Dmc9lCKmovQJzvf5fPZS9AUmsm7HRhL0AH58xAGl0vQL1ic5W/WC9Ac94Z6mRUL0ApWsA+ClAvQN7VZpOvSy9AlFEN6FRHL0BKzbM8+kIvQP9IWpGfPi9AtcQA5kQ6L0BrQKc66jUvQCG8TY+PMS9A1jf04zQtL0CMs5o42igvQEIvQY1/JC9A+Krn4SQgL0CtJo42yhsvQGOiNItvFy9AGR7b3xQTL0DOmYE0ug4vQIQVKIlfCi9AOpHO3QQGL0DwDHUyqgEvQKWIG4dP/S5AWwTC2/T4LkARgGgwmvQuQMb7DoU/8C5AfHe12eTrLkAy81suiucuQOhuAoMv4y5Aneqo19TeLkBTZk8setouQAni9YAf1i5Av12c1cTRLkB02UIqas0uQCpV6X4PyS5A4NCP07TELkCVTDYoWsAuQEvI3Hz/uy5AAUSD0aS3LkC3vykmSrMuQGw70Hrvri5AIrd2z5SqLkDYMh0kOqYuQI2uw3jfoS5AQypqzYSdLkD5pRAiKpkuQK8ht3bPlC5AZJ1dy3SQLkAaGQQgGowuQNCUqnS/hy5AhhBRyWSDLkA7jPcdCn8uQPEHnnKvei5Ap4NEx1R2LkBc/+ob+nEuQBJ7kXCfbS5AyPY3xURpLkB+ct4Z6mQuQDPuhG6PYC5A6WkrwzRcLkCf5dEX2lcuQFVheGx/Uy5ACt0ewSRPLkDAWMUVykouQHbUa2pvRi5AK1ASvxRCLkDhy7gTuj0uQJdHX2hfOS5ATcMFvQQ1LkACP6wRqjAuQLi6UmZPLC5Abjb5uvQnLkAjsp8PmiMuQNktRmQ/Hy5Aj6nsuOQaLkBFJZMNihYuQPqgOWIvEi5AsBzgttQNLkBmmIYLegkuQBwULWAfBS5A0Y/TtMQALkCHC3oJavwtQD2HIF4P+C1A8gLHsrTzLUCofm0HWu8tQF76E1z/6i1AFHa6sKTmLUDJ8WAFSuItQH9tB1rv3S1ANemtrpTZLUDqZFQDOtUtQKDg+lff0C1AVlyhrITMLUAM2EcBKsgtQMFT7lXPwy1Ad8+UqnS/LUAtSzv/GbstQOPG4VO/ti1AmEKIqGSyLUBOvi79Ca4tQAQ61VGvqS1AubV7plSlLUBvMSL7+aAtQCWtyE+fnC1A2yhvpESYLUCQpBX56ZMtQEYgvE2Pjy1A/JtiojSLLUCxFwn32YYtQGeTr0t/gi1AHQ9WoCR+LUDTivz0yXktQIgGo0lvdS1APoJJnhRxLUD0/e/yuWwtQKp5lkdfaC1AX/U8nARkLUAVcePwqV8tQMvsiUVPWy1AgGgwmvRWLUA25NbumVItQOxffUM/Ti1AotsjmORJLUBXV8rsiUUtQA3TcEEvQS1Aw04XltQ8LUB4yr3qeTgtQC5GZD8fNC1A5MEKlMQvLUCaPbHoaSstQE+5Vz0PJy1ABTX+kbQiLUC7sKTmWR4tQHEsSzv/GS1AJqjxj6QVLUDcI5jkSREtQJKfPjnvDC1ARxvljZQILUD9loviOQQtQLMSMjff/yxAaY7Yi4T7LEAeCn/gKfcsQNSFJTXP8ixAigHMiXTuLEA/fXLeGeosQPX4GDO/5SxAq3S/h2ThLEBh8GXcCd0sQBZsDDGv2CxAzOeyhVTULECCY1na+c8sQDjf/y6fyyxA7Vqmg0THLECj1kzY6cIsQFlS8yyPvixADs6ZgTS6LEDESUDW2bUsQHrF5ip/sSxAMEGNfyStLEDlvDPUyagsQJs42ihvpCxAUbSAfRSgLEAGMCfSuZssQLyrzSZflyxAcid0ewSTLEAooxrQqY4sQN0ewSRPiixAk5pnefSFLEBJFg7OmYEsQP+RtCI/fSxAtA1bd+R4LEBqiQHMiXQsQCAFqCAvcCxA1YBOddRrLECL/PTJeWcsQEF4mx4fYyxA9/NBc8ReLECsb+jHaVosQGLrjhwPVixAGGc1cbRRLEDO4tvFWU0sQINeghr/SCxAOdoob6RELEDvVc/DSUAsQKTRdRjvOyxAWk0cbZQ3LEAQycLBOTMsQMZEaRbfLixAe8APa4QqLEAxPLa/KSYsQOe3XBTPISxAnDMDaXQdLEBSr6m9GRksQAgrUBK/FCxAvqb2ZmQQLEBzIp27CQwsQCmeQxCvByxA3xnqZFQDLECVlZC5+f4rQEoRNw6f+itAAI3dYkT2K0C2CIS36fErQGuEKgyP7StAIQDRYDTpK0DXe3e12eQrQI33HQp/4CtAQnPEXiTcK0D47mqzydcrQK5qEQhv0ytAY+a3XBTPK0AZYl6xucorQM/dBAZfxitAhVmrWgTCK0A61VGvqb0rQPBQ+ANPuStApsyeWPS0K0BcSEWtmbArQBHE6wE/rCtAxz+SVuSnK0B9uziriaMrQDI33/8unytA6LKFVNSaK0CeLiypeZYrQFSq0v0ekitACSZ5UsSNK0C/oR+naYkrQHUdxvsOhStAKplsULSAK0DgFBOlWXwrQJaQufn+dytATAxgTqRzK0ABiAajSW8rQLcDrffuaitAbX9TTJRmK0Aj+/mgOWIrQNh2oPXeXStAjvJGSoRZK0BEbu2eKVUrQPnpk/POUCtAr2U6SHRMK0Bl4eCcGUgrQBtdh/G+QytA0NgtRmQ/K0CGVNSaCTsrQDzQeu+uNitA8UshRFQyK0Cnx8eY+S0rQF1Dbu2eKStAE78UQkQlK0DIOruW6SArQH62YeuOHCtANDIIQDQYK0Dqra6U2RMrQJ8pVel+DytAVaX7PSQLK0ALIaKSyQYrQMCcSOduAitAdhjvOxT+KkAslJWQufkqQOIPPOVe9SpAl4viOQTxKkBNB4mOqewqQAODL+NO6CpAuP7VN/TjKkBuenyMmd8qQCT2IuE+2ypA2nHJNeTWKkCP7W+KidIqQEVpFt8uzipA++S8M9TJKkCxYGOIecUqQGbcCd0ewSpAHFiwMcS8KkDS01aGabgqQIdP/doOtCpAPcujL7SvKkDzRkqEWasqQKnC8Nj+pipAXj6XLaSiKkAUuj2CSZ4qQMo15NbumSpAf7GKK5SVKkA1LTGAOZEqQOuo19TejCpAoSR+KYSIKkBWoCR+KYQqQAwcy9LOfypAwpdxJ3R7KkB4Exh8GXcqQC2PvtC+cipA4wplJWRuKkCZhgt6CWoqQE4Css6uZSpABH5YI1RhKkC6+f53+VwqQHB1pcyeWCpAJfFLIURUKkDbbPJ16U8qQJHomMqOSypARmQ/HzRHKkD83+Vz2UIqQLJbjMh+PipAaNcyHSQ6KkAdU9lxyTUqQNPOf8ZuMSpAiUomGxQtKkA/xsxvuSgqQPRBc8ReJCpAqr0ZGQQgKkBgOcBtqRsqQBW1ZsJOFypAyzANF/QSKkCBrLNrmQ4qQDcoWsA+CipA7KMAFeQFKkCiH6dpiQEqQFibTb4u/SlADhf0EtT4KUDDkppnefQpQHkOQbwe8ClAL4rnEMTrKUDkBY5laecpQJqBNLoO4ylAUP3aDrTeKUAGeYFjWdopQLv0J7j+1SlAcXDODKTRKUAn7HRhSc0pQNxnG7buyClAkuPBCpTEKUBIX2hfOcApQP7aDrTeuylAs1a1CIS3KUBp0ltdKbMpQB9OArLOrilA1cmoBnSqKUCKRU9bGaYpQEDB9a++oSlA9jycBGSdKUCruEJZCZkpQGE06a2ulClAF7CPAlSQKUDNKzZX+YspQIKn3KuehylAOCODAESDKUDunilV6X4pQKMa0KmOeilAWZZ2/jN2KUAPEh1T2XEpQMWNw6d+bSlAeglq/CNpKUAwhRBRyWQpQOYAt6VuYClAnHxd+hNcKUBR+ANPuVcpQAd0qqNeUylAve9Q+ANPKUBya/dMqUopQCjnnaFORilA3mJE9vNBKUCU3upKmT0pQElakZ8+OSlA/9U39OM0KUC1Ud5IiTApQGrNhJ0uLClAIEkr8tMnKUDWxNFGeSMpQIxAeJseHylAQbwe8MMaKUD3N8VEaRYpQK2za5kOEilAYy8S7rMNKUAYq7hCWQkpQM4mX5f+BClAhKIF7KMAKUA5HqxASfwoQO+ZUpXu9yhApRX56ZPzKEBbkZ8+Oe8oQBANRpPe6ihAxojs54PmKEB8BJM8KeIoQDGAOZHO3ShA5/vf5XPZKECdd4Y6GdUoQFPzLI++0ChACG/T42PMKEC+6nk4CcgoQHRmII2uwyhAKuLG4VO/KEDfXW02+booQJXZE4uetihAS1W630OyKEAA0WA06a0oQLZMB4mOqShAbMit3TOlKEAiRFQy2aAoQNe/+oZ+nChAjTuh2yOYKEBDt0cwyZMoQPgy7oRujyhArq6U2ROLKEBkKjsuuYYoQBqm4YJegihAzyGI1wN+KECFnS4sqXkoQDsZ1YBOdShA8ZR71fNwKECmECIqmWwoQFyMyH4+aChAEghv0+NjKEDHgxUoiV8oQH3/u3wuWyhAM3ti0dNWKEDp9ggmeVIoQJ5yr3oeTihAVO5Vz8NJKEAKavwjaUUoQL/longOQShAdWFJzbM8KEAr3e8hWTgoQOFYlnb+MyhAltQ8y6MvKEBMUOMfSSsoQALMiXTuJihAuEcwyZMiKEBtw9YdOR4oQCM/fXLeGShA2bojx4MVKECONsobKREoQESycHDODChA+i0XxXMIKECwqb0ZGQQoQGUlZG6+/ydAG6EKw2P7J0DRHLEXCfcnQIaYV2yu8idAPBT+wFPuJ0Dyj6QV+eknQKgLS2qe5SdAXYfxvkPhJ0ATA5gT6dwnQMl+PmiO2CdAf/rkvDPUJ0A0dosR2c8nQOrxMWZ+yydAoG3YuiPHJ0BV6X4PycInQAtlJWRuvidAweDLuBO6J0B3XHINubUnQCzYGGJesSdA4lO/tgOtJ0CYz2ULqagnQE5LDGBOpCdAA8eytPOfJ0C5QlkJmZsnQG++/10+lydAJDqmsuOSJ0DatUwHiY4nQJAx81suiidARq2ZsNOFJ0D7KEAFeYEnQLGk5lkefSdAZyCNrsN4J0AcnDMDaXQnQNIX2lcOcCdAiJOArLNrJ0A+DycBWWcnQPOKzVX+YidAqQZ0qqNeJ0Bfghr/SFonQBX+wFPuVSdAynlnqJNRJ0CA9Q39OE0nQDZxtFHeSCdA6+xapoNEJ0ChaAH7KEAnQFfkp0/OOydADWBOpHM3J0DC2/T4GDMnQHhXm02+LidALtNBomMqJ0DjTuj2CCYnQJnKjkuuISdAT0Y1oFMdJ0AFwtv0+BgnQLo9gkmeFCdAcLkonkMQJ0AmNc/y6AsnQNywdUeOBydAkSwcnDMDJ0BHqMLw2P4mQP0jaUV++iZAsp8PmiP2JkBoG7buyPEmQB6XXENu7SZA1BIDmBPpJkCJjqnsuOQmQD8KUEFe4CZA9YX2lQPcJkCqAZ3qqNcmQGB9Qz9O0yZAFvnpk/POJkDMdJDomMomQIHwNj0+xiZAN2zdkePBJkDt54PmiL0mQKNjKjsuuSZAWN/Qj9O0JkAOW3fkeLAmQMTWHTkerCZAeVLEjcOnJkAvzmriaKMmQOVJETcOnyZAm8W3i7OaJkBQQV7gWJYmQAa9BDX+kSZAvDiriaONJkBxtFHeSIkmQCcw+DLuhCZA3aueh5OAJkCTJ0XcOHwmQEij6zDedyZA/h6ShYNzJkC0mjjaKG8mQGoW3y7OaiZAH5KFg3NmJkDVDSzYGGImQIuJ0iy+XSZAQAV5gWNZJkD2gB/WCFUmQKz8xSquUCZAYnhsf1NMJkAX9BLU+EcmQM1vuSieQyZAg+tffUM/JkA4ZwbS6DomQO7irCaONiZApF5TezMyJkBa2vnP2C0mQA9WoCR+KSZAxdFGeSMlJkB7Te3NyCAmQDHJkyJuHCZA5kQ6dxMYJkCcwODLuBMmQFI8hyBeDyZAB7gtdQMLJkC9M9TJqAYmQHOveh5OAiZAKSshc/P9JUDepsfHmPklQJQibhw+9SVASp4UcePwJUD/GbvFiOwlQLWVYRou6CVAaxEIb9PjJUAhja7DeN8lQNYIVRge2yVAjIT7bMPWJUBCAKLBaNIlQPh7SBYOziVArffuarPJJUBjc5W/WMUlQBnvOxT+wCVAzmriaKO8JUCE5oi9SLglQDpiLxLusyVA8N3VZpOvJUClWXy7OKslQFvVIhDepiVAEVHJZIOiJUDHzG+5KJ4lQHxIFg7OmSVAMsS8YnOVJUDoP2O3GJElQJ27CQy+jCVAUzewYGOIJUAJs1a1CIQlQL8u/QmufyVAdKqjXlN7JUAqJkqz+HYlQOCh8AeeciVAlR2XXENuJUBLmT2x6GklQAEV5AWOZSVAt5CKWjNhJUBsDDGv2FwlQCKI1wN+WCVA2AN+WCNUJUCOfyStyE8lQEP7ygFuSyVA+XZxVhNHJUCv8heruEIlQGRuvv9dPiVAGupkVAM6JUDQZQupqDUlQIbhsf1NMSVAO11YUvMsJUDx2P6mmCglQKdUpfs9JCVAXNBLUOMfJUASTPKkiBslQMjHmPktFyVAfkM/TtMSJUAzv+WieA4lQOk6jPcdCiVAn7YyTMMFJUBVMtmgaAElQAquf/UN/SRAwCkmSrP4JEB2pcyeWPQkQCshc/P97yRA4ZwZSKPrJECXGMCcSOckQE2UZvHt4iRAAhANRpPeJEC4i7OaONokQG4HWu/d1SRAI4MARIPRJEDZ/qaYKM0kQI96Te3NyCRARfbzQXPEJED6cZqWGMAkQLDtQOu9uyRAZmnnP2O3JEAc5Y2UCLMkQNFgNOmtriRAh9zaPVOqJEA9WIGS+KUkQPLTJ+edoSRAqE/OO0OdJEBey3SQ6JgkQBRHG+WNlCRAycLBOTOQJEB/PmiO2IskQDW6DuN9hyRA6jW1NyODJECgsVuMyH4kQFYtAuFteiRADKmoNRN2JEDBJE+KuHEkQHeg9d5dbSRALRycMwNpJEDjl0KIqGQkQJgT6dxNYCRATo+PMfNbJEAECzaGmFckQLmG3No9UyRAbwKDL+NOJEAlfimEiEokQNv5z9gtRiRAkHV2LdNBJEBG8RyCeD0kQPxsw9YdOSRAsehpK8M0JEBnZBCAaDAkQB3gttQNLCRA01tdKbMnJECI1wN+WCMkQD5TqtL9HiRA9M5QJ6MaJECqSvd7SBYkQF/GndDtESRAFUJEJZMNJEDLvep5OAkkQIA5kc7dBCRANrU3I4MAJEDsMN53KPwjQKKshMzN9yNAVygrIXPzI0ANpNF1GO8jQMMfeMq96iNAeJseH2PmI0AuF8VzCOIjQOSSa8it3SNAmg4SHVPZI0BPirhx+NQjQAUGX8ad0CNAu4EFG0PMI0Bx/atv6McjQCZ5UsSNwyNA3PT4GDO/I0CScJ9t2LojQEfsRcJ9tiNA/WfsFiOyI0Cz45JryK0jQGlfOcBtqSNAHtvfFBOlI0DUVoZpuKAjQIrSLL5dnCNAQE7TEgOYI0D1yXlnqJMjQKtFILxNjyNAYcHGEPOKI0AWPW1lmIYjQMy4E7o9giNAgjS6DuN9I0A4sGBjiHkjQO0rB7gtdSNAo6etDNNwI0BZI1RheGwjQA6f+rUdaCNAxBqhCsNjI0B6lkdfaF8jQDAS7rMNWyNA5Y2UCLNWI0CbCTtdWFIjQFGF4bH9TSNABwGIBqNJI0C8fC5bSEUjQHL41K/tQCNAKHR7BJM8I0Dd7yFZODgjQJNryK3dMyNASeduAoMvI0D/YhVXKCsjQLTeu6vNJiNAalpiAHMiI0Ag1ghVGB4jQNVRr6m9GSNAi81V/mIVI0BBSfxSCBEjQPfEoqetDCNArEBJ/FIII0BivO9Q+AMjQBg4lqWd/yJAzrM8+kL7IkCDL+NO6PYiQDmriaON8iJA7yYw+DLuIkCkotZM2OkiQFoefaF95SJAEJoj9iLhIkDGFcpKyNwiQHuRcJ9t2CJAMQ0X9BLUIkDniL1IuM8iQJwEZJ1dyyJAUoAK8gLHIkAI/LBGqMIiQL53V5tNviJAc/P97/K5IkApb6REmLUiQN/qSpk9sSJAlWbx7eKsIkBK4pdCiKgiQABePpctpCJAttnk69KfIkBrVYtAeJsiQCHRMZUdlyJA10zY6cKSIkCNyH4+aI4iQEJEJZMNiiJA+L/L57KFIkCuO3I8WIEiQGO3GJH9fCJAGTO/5aJ4IkDPrmU6SHQiQIUqDI/tbyJAOqay45JrIkDwIVk4OGciQKad/4zdYiJAXBmm4YJeIkARlUw2KFoiQMcQ84rNVSJAfYyZ33JRIkAyCEA0GE0iQOiD5oi9SCJAnv+M3WJEIkBUezMyCEAiQAn32YatOyJAv3KA21I3IkB17iYw+DIiQCpqzYSdLiJA4OVz2UIqIkCWYRou6CUiQEzdwIKNISJAAVln1zIdIkC31A0s2BgiQG1QtIB9FCJAI8xa1SIQIkDYRwEqyAsiQI7Dp35tByJARD9O0xIDIkD5uvQnuP4hQK82m3xd+iFAZbJB0QL2IUAbLuglqPEhQNCpjnpN7SFAhiU1z/LoIUA8odsjmOQhQPEcgng94CFAp5gozeLbIUBdFM8hiNchQBOQdXYt0yFAyAscy9LOIUB+h8IfeMohQDQDaXQdxiFA6n4PycLBIUCf+rUdaL0hQFV2XHINuSFAC/ICx7K0IUDAbakbWLAhQHbpT3D9qyFALGX2xKKnIUDi4JwZSKMhQJdcQ27tniFATdjpwpKaIUADVJAXOJYhQLjPNmzdkSFAbkvdwIKNIUAkx4MVKIkhQNpCKmrNhCFAj77QvnKAIUBFOncTGHwhQPu1HWi9dyFAsTHEvGJzIUBmrWoRCG8hQBwpEWataiFA0qS3ulJmIUCHIF4P+GEhQD2cBGSdXSFA8xeruEJZIUCpk1EN6FQhQF4P+GGNUCFAFIuetjJMIUDKBkUL2EchQICC6199QyFANf6RtCI/IUDreTgJyDohQKH13l1tNiFAVnGFshIyIUAM7SsHuC0hQMJo0ltdKSFAeOR4sAIlIUAtYB8FqCAhQOPbxVlNHCFAmVdsrvIXIUBO0xIDmBMhQARPuVc9DyFAuspfrOIKIUBwRgYBiAYhQCXCrFUtAiFA2z1TqtL9IECRufn+d/kgQEc1oFMd9SBA/LBGqMLwIECyLO38Z+wgQGiok1EN6CBAHSQ6prLjIEDTn+D6V98gQIkbh0/92iBAP5ctpKLWIED0EtT4R9IgQKqOek3tzSBAYAohopLJIEAVhsf2N8UgQMsBbkvdwCBAgX0UoIK8IEA3+br0J7ggQOx0YUnNsyBAovAHnnKvIEBYbK7yF6sgQA7oVEe9piBAw2P7m2KiIEB536HwB54gQC9bSEWtmSBA5NbumVKVIECaUpXu95AgQFDOO0OdjCBABkril0KIIEC7xYjs54MgQHFBL0GNfyBAJ73VlTJ7IEDcOHzq13YgQJK0Ij99ciBASDDJkyJuIED+q2/ox2kgQLMnFj1tZSBAaaO8kRJhIEAfH2Pmt1wgQNWaCTtdWCBAihawjwJUIEBAklbkp08gQPYN/ThNSyBAq4mjjfJGIEBhBUril0IgQBeB8DY9PiBAzfyWi+I5IECCeD3ghzUgQDj04zQtMSBA7m+KidIsIECj6zDedyggQFln1zIdJCBAD+N9h8IfIEDFXiTcZxsgQHrayjANFyBAMFZxhbISIEDm0RfaVw4gQJxNvi79CSBAUclkg6IFIEAHRQvYRwEgQHmBY1na+R9A5XiwAiXxH0BQcP2rb+gfQLxnSlW63x9AJ1+X/gTXH0CTVuSnT84fQP5NMVGaxR9AakV++uS8H0DVPMujL7QfQEA0GE16qx9ArCtl9sSiH0AXI7KfD5ofQIMa/0hakR9A7hFM8qSIH0BaCZmb738fQMUA5kQ6dx9AMfgy7oRuH0Cc73+Xz2UfQAfnzEAaXR9Ac94Z6mRUH0De1WaTr0sfQErNszz6Qh9AtcQA5kQ6H0AhvE2PjzEfQIyzmjjaKB9A+Krn4SQgH0BjojSLbxcfQM6ZgTS6Dh9AOpHO3QQGH0CliBuHT/0eQBGAaDCa9B5AfHe12eTrHkDobgKDL+MeQFNmTyx62h5Av12c1cTRHkAqVel+D8keQJVMNihawB5AAUSD0aS3HkBsO9B6764eQNgyHSQ6ph5AQypqzYSdHkCvIbd2z5QeQBoZBCAajB5AhhBRyWSDHkDxB55yr3oeQFz/6hv6cR5AyPY3xURpHkAz7oRuj2AeQJ/l0RfaVx5ACt0ewSRPHkB21Gtqb0YeQOHLuBO6PR5ATcMFvQQ1HkC4ulJmTyweQCOynw+aIx5Aj6nsuOQaHkD6oDliLxIeQGaYhgt6CR5A0Y/TtMQAHkA9hyBeD/gdQKh+bQda7x1AFHa6sKTmHUB/bQda790dQOpkVAM61R1AVlyhrITMHUDBU+5Vz8MdQC1LO/8Zux1AmEKIqGSyHUAEOtVRr6kdQG8xIvv5oB1A2yhvpESYHUBGILxNj48dQLEXCffZhh1AHQ9WoCR+HUCIBqNJb3UdQPT97/K5bB1AX/U8nARkHUDL7IlFT1sdQDbk1u6ZUh1AotsjmORJHUAN03BBL0EdQHjKvep5OB1A5MEKlMQvHUBPuVc9DycdQLuwpOZZHh1AJqjxj6QVHUCSnz457wwdQP2Wi+I5BB1AaY7Yi4T7HEDUhSU1z/IcQD99ct4Z6hxAq3S/h2ThHEAWbAwxr9gcQIJjWdr5zxxA7Vqmg0THHEBZUvMsj74cQMRJQNbZtRxAMEGNfyStHECbONoob6QcQAYwJ9K5mxxAcid0ewSTHEDdHsEkT4ocQEkWDs6ZgRxAtA1bd+R4HEAgBaggL3AcQIv89Ml5ZxxA9/NBc8ReHEBi644cD1YcQM7i28VZTRxAOdoob6REHECk0XUY7zscQBDJwsE5MxxAe8APa4QqHEDnt1wUzyEcQFKvqb0ZGRxAvqb2ZmQQHEApnkMQrwccQJWVkLn5/htAAI3dYkT2G0BrhCoMj+0bQNd7d7XZ5BtAQnPEXiTcG0CuahEIb9MbQBliXrG5yhtAhVmrWgTCG0DwUPgDT7kbQFxIRa2ZsBtAxz+SVuSnG0AyN9//Lp8bQJ4uLKl5lhtACSZ5UsSNG0B1Hcb7DoUbQOAUE6VZfBtATAxgTqRzG0C3A6337mobQCP7+aA5YhtAjvJGSoRZG0D56ZPzzlAbQGXh4JwZSBtA0NgtRmQ/G0A80HrvrjYbQKfHx5j5LRtAE78UQkQlG0B+tmHrjhwbQOqtrpTZExtAVaX7PSQLG0DAnEjnbgIbQCyUlZC5+RpAl4viOQTxGkADgy/jTugaQG56fIyZ3xpA2nHJNeTWGkBFaRbfLs4aQLFgY4h5xRpAHFiwMcS8GkCHT/3aDrQaQPNGSoRZqxpAXj6XLaSiGkDKNeTW7pkaQDUtMYA5kRpAoSR+KYSIGkAMHMvSzn8aQHgTGHwZdxpA4wplJWRuGkBOArLOrmUaQLr5/nf5XBpAJfFLIURUGkCR6JjKjksaQPzf5XPZQhpAaNcyHSQ6GkDTzn/GbjEaQD/GzG+5KBpAqr0ZGQQgGkAVtWbCThcaQIGss2uZDhpA7KMAFeQFGkBYm02+Lv0ZQMOSmmd59BlAL4rnEMTrGUCagTS6DuMZQAZ5gWNZ2hlAcXDODKTRGUDcZxu27sgZQEhfaF85wBlAs1a1CIS3GUAfTgKyzq4ZQIpFT1sZphlA9jycBGSdGUBhNOmtrpQZQM0rNlf5ixlAOCODAESDGUCjGtCpjnoZQA8SHVPZcRlAeglq/CNpGUDmALelbmAZQFH4A0+5VxlAve9Q+ANPGUAo552hTkYZQJTe6kqZPRlA/9U39OM0GUBqzYSdLiwZQNbE0UZ5IxlAQbwe8MMaGUCts2uZDhIZQBiruEJZCRlAhKIF7KMAGUDvmVKV7vcYQFuRnz457xhAxojs54PmGEAxgDmRzt0YQJ13hjoZ1RhACG/T42PMGEB0ZiCNrsMYQN9dbTb5uhhAS1W630OyGEC2TAeJjqkYQCJEVDLZoBhAjTuh2yOYGED4Mu6Ebo8YQGQqOy65hhhAzyGI1wN+GEA7GdWATnUYQKYQIiqZbBhAEghv0+NjGEB9/7t8LlsYQOn2CCZ5UhhAVO5Vz8NJGEC/5aJ4DkEYQCvd7yFZOBhAltQ8y6MvGEACzIl07iYYQG3D1h05HhhA2bojx4MVGEBEsnBwzgwYQLCpvRkZBBhAG6EKw2P7F0CGmFdsrvIXQPKPpBX56RdAXYfxvkPhF0DJfj5ojtgXQDR2ixHZzxdAoG3YuiPHF0ALZSVkbr4XQHdccg25tRdA4lO/tgOtF0BOSwxgTqQXQLlCWQmZmxdAJDqmsuOSF0CQMfNbLooXQPsoQAV5gRdAZyCNrsN4F0DSF9pXDnAXQD4PJwFZZxdAqQZ0qqNeF0AV/sBT7lUXQID1Df04TRdA6+xapoNEF0BX5KdPzjsXQMLb9PgYMxdALtNBomMqF0CZyo5LriEXQAXC2/T4GBdAcLkonkMQF0DcsHVHjgcXQEeowvDY/hZAsp8PmiP2FkAel1xDbu0WQImOqey45BZA9YX2lQPcFkBgfUM/TtMWQMx0kOiYyhZAN2zdkePBFkCjYyo7LrkWQA5bd+R4sBZAeVLEjcOnFkDlSRE3Dp8WQFBBXuBYlhZAvDiriaONFkAnMPgy7oQWQJMnRdw4fBZA/h6ShYNzFkBqFt8uzmoWQNUNLNgYYhZAQAV5gWNZFkCs/MUqrlAWQBf0EtT4RxZAg+tffUM/FkDu4qwmjjYWQFra+c/YLRZAxdFGeSMlFkAxyZMibhwWQJzA4Mu4ExZAB7gtdQMLFkBzr3oeTgIWQN6mx8eY+RVASp4UcePwFUC1lWEaLugVQCGNrsN43xVAjIT7bMPWFUD4e0gWDs4VQGNzlb9YxRVAzmriaKO8FUA6Yi8S7rMVQKVZfLs4qxVAEVHJZIOiFUB8SBYOzpkVQOg/Y7cYkRVAUzewYGOIFUC/Lv0Jrn8VQComSrP4dhVAlR2XXENuFUABFeQFjmUVQGwMMa/YXBVA2AN+WCNUFUBD+8oBbksVQK/yF6u4QhVAGupkVAM6FUCG4bH9TTEVQPHY/qaYKBVAXNBLUOMfFUDIx5j5LRcVQDO/5aJ4DhVAn7YyTMMFFUAKrn/1Df0UQHalzJ5Y9BRA4ZwZSKPrFEBNlGbx7eIUQLiLs5o42hRAI4MARIPRFECPek3tzcgUQPpxmpYYwBRAZmnnP2O3FEDRYDTpra4UQD1YgZL4pRRAqE/OO0OdFEAURxvljZQUQH8+aI7YixRA6jW1NyODFEBWLQLhbXoUQMEkT4q4cRRALRycMwNpFECYE+ncTWAUQAQLNoaYVxRAbwKDL+NOFEDb+c/YLUYUQEbxHIJ4PRRAsehpK8M0FEAd4LbUDSwUQIjXA35YIxRA9M5QJ6MaFEBfxp3Q7REUQMu96nk4CRRANrU3I4MAFECirITMzfcTQA2k0XUY7xNAeJseH2PmE0DkkmvIrd0TQE+KuHH41BNAu4EFG0PME0AmeVLEjcMTQJJwn23YuhNA/WfsFiOyE0BpXznAbakTQNRWhmm4oBNAQE7TEgOYE0CrRSC8TY8TQBY9bWWYhhNAgjS6DuN9E0DtKwe4LXUTQFkjVGF4bBNAxBqhCsNjE0AwEu6zDVsTQJsJO11YUhNABwGIBqNJE0By+NSv7UATQN3vIVk4OBNASeduAoMvE0C03rurzSYTQCDWCFUYHhNAi81V/mIVE0D3xKKnrQwTQGK871D4AxNAzrM8+kL7EkA5q4mjjfISQKSi1kzY6RJAEJoj9iLhEkB7kXCfbdgSQOeIvUi4zxJAUoAK8gLHEkC+d1ebTb4SQClvpESYtRJAlWbx7eKsEkAAXj6XLaQSQGtVi0B4mxJA10zY6cKSEkBCRCWTDYoSQK47cjxYgRJAGTO/5aJ4EkCFKgyP7W8SQPAhWTg4ZxJAXBmm4YJeEkDHEPOKzVUSQDIIQDQYTRJAnv+M3WJEEkAJ99mGrTsSQHXuJjD4MhJA4OVz2UIqEkBM3cCCjSESQLfUDSzYGBJAI8xa1SIQEkCOw6d+bQcSQPm69Ce4/hFAZbJB0QL2EUDQqY56Te0RQDyh2yOY5BFAp5gozeLbEUATkHV2LdMRQH6Hwh94yhFA6n4PycLBEUBVdlxyDbkRQMBtqRtYsBFALGX2xKKnEUCXXENu7Z4RQANUkBc4lhFAbkvdwIKNEUDaQipqzYQRQEU6dxMYfBFAsTHEvGJzEUAcKRFmrWoRQIcgXg/4YRFA8xeruEJZEUBeD/hhjVARQMoGRQvYRxFANf6RtCI/EUCh9d5dbTYRQAztKwe4LRFAeOR4sAIlEUDj28VZTRwRQE7TEgOYExFAuspfrOIKEUAlwqxVLQIRQJG5+f53+RBA/LBGqMLwEEBoqJNRDegQQNOf4PpX3xBAP5ctpKLWEECqjnpN7c0QQBWGx/Y3xRBAgX0UoIK8EEDsdGFJzbMQQFhsrvIXqxBAw2P7m2KiEEAvW0hFrZkQQJpSle73kBBABkril0KIEEBxQS9BjX8QQNw4fOrXdhBASDDJkyJuEECzJxY9bWUQQB8fY+a3XBBAihawjwJUEED2Df04TUsQQGEFSuKXQhBAzfyWi+I5EEA49OM0LTEQQKPrMN53KBBAD+N9h8IfEEB62sowDRcQQObRF9pXDhBAUclkg6IFEEB5gWNZ2vkPQFBw/atv6A9AJ1+X/gTXD0D+TTFRmsUPQNU8y6MvtA9ArCtl9sSiD0CDGv9IWpEPQFoJmZvvfw9AMfgy7oRuD0AH58xAGl0PQN7VZpOvSw9AtcQA5kQ6D0CMs5o42igPQGOiNItvFw9AOpHO3QQGD0ARgGgwmvQOQOhuAoMv4w5Av12c1cTRDkCVTDYoWsAOQGw70Hrvrg5AQypqzYSdDkAaGQQgGowOQPEHnnKveg5AyPY3xURpDkCf5dEX2lcOQHbUa2pvRg5ATcMFvQQ1DkAjsp8PmiMOQPqgOWIvEg5A0Y/TtMQADkCofm0HWu8NQH9tB1rv3Q1AVlyhrITMDUAtSzv/GbsNQAQ61VGvqQ1A2yhvpESYDUCxFwn32YYNQIgGo0lvdQ1AX/U8nARkDUA25NbumVINQA3TcEEvQQ1A5MEKlMQvDUC7sKTmWR4NQJKfPjnvDA1AaY7Yi4T7DEA/fXLeGeoMQBZsDDGv2AxA7Vqmg0THDEDESUDW2bUMQJs42ihvpAxAcid0ewSTDEBJFg7OmYEMQCAFqCAvcAxA9/NBc8ReDEDO4tvFWU0MQKTRdRjvOwxAe8APa4QqDEBSr6m9GRkMQCmeQxCvBwxAAI3dYkT2C0DXe3e12eQLQK5qEQhv0wtAhVmrWgTCC0BcSEWtmbALQDI33/8unwtACSZ5UsSNC0DgFBOlWXwLQLcDrffuagtAjvJGSoRZC0Bl4eCcGUgLQDzQeu+uNgtAE78UQkQlC0Dqra6U2RMLQMCcSOduAgtAl4viOQTxCkBuenyMmd8KQEVpFt8uzgpAHFiwMcS8CkDzRkqEWasKQMo15NbumQpAoSR+KYSICkB4Exh8GXcKQE4Css6uZQpAJfFLIURUCkD83+Vz2UIKQNPOf8ZuMQpAqr0ZGQQgCkCBrLNrmQ4KQFibTb4u/QlAL4rnEMTrCUAGeYFjWdoJQNxnG7buyAlAs1a1CIS3CUCKRU9bGaYJQGE06a2ulAlAOCODAESDCUAPEh1T2XEJQOYAt6VuYAlAve9Q+ANPCUCU3upKmT0JQGrNhJ0uLAlAQbwe8MMaCUAYq7hCWQkJQO+ZUpXu9whAxojs54PmCECdd4Y6GdUIQHRmII2uwwhAS1W630OyCEAiRFQy2aAIQPgy7oRujwhAzyGI1wN+CECmECIqmWwIQH3/u3wuWwhAVO5Vz8NJCEAr3e8hWTgIQALMiXTuJghA2bojx4MVCECwqb0ZGQQIQIaYV2yu8gdAXYfxvkPhB0A0dosR2c8HQAtlJWRuvgdA4lO/tgOtB0C5QlkJmZsHQJAx81suigdAZyCNrsN4B0A+DycBWWcHQBX+wFPuVQdA6+xapoNEB0DC2/T4GDMHQJnKjkuuIQdAcLkonkMQB0BHqMLw2P4GQB6XXENu7QZA9YX2lQPcBkDMdJDomMoGQKNjKjsuuQZAeVLEjcOnBkBQQV7gWJYGQCcw+DLuhAZA/h6ShYNzBkDVDSzYGGIGQKz8xSquUAZAg+tffUM/BkBa2vnP2C0GQDHJkyJuHAZAB7gtdQMLBkDepsfHmPkFQLWVYRou6AVAjIT7bMPWBUBjc5W/WMUFQDpiLxLuswVAEVHJZIOiBUDoP2O3GJEFQL8u/QmufwVAlR2XXENuBUBsDDGv2FwFQEP7ygFuSwVAGupkVAM6BUDx2P6mmCgFQMjHmPktFwVAn7YyTMMFBUB2pcyeWPQEQE2UZvHt4gRAI4MARIPRBED6cZqWGMAEQNFgNOmtrgRAqE/OO0OdBEB/PmiO2IsEQFYtAuFtegRALRycMwNpBEAECzaGmFcEQNv5z9gtRgRAsehpK8M0BECI1wN+WCMEQF/GndDtEQRANrU3I4MABEANpNF1GO8DQOSSa8it3QNAu4EFG0PMA0CScJ9t2LoDQGlfOcBtqQNAQE7TEgOYA0AWPW1lmIYDQO0rB7gtdQNAxBqhCsNjA0CbCTtdWFIDQHL41K/tQANASeduAoMvA0Ag1ghVGB4DQPfEoqetDANAzrM8+kL7AkCkotZM2OkCQHuRcJ9t2AJAUoAK8gLHAkApb6REmLUCQABePpctpAJA10zY6cKSAkCuO3I8WIECQIUqDI/tbwJAXBmm4YJeAkAyCEA0GE0CQAn32YatOwJA4OVz2UIqAkC31A0s2BgCQI7Dp35tBwJAZbJB0QL2AUA8odsjmOQBQBOQdXYt0wFA6n4PycLBAUDAbakbWLABQJdcQ27tngFAbkvdwIKNAUBFOncTGHwBQBwpEWatagFA8xeruEJZAUDKBkUL2EcBQKH13l1tNgFAeOR4sAIlAUBO0xIDmBMBQCXCrFUtAgFA/LBGqMLwAEDTn+D6V98AQKqOek3tzQBAgX0UoIK8AEBYbK7yF6sAQC9bSEWtmQBABkril0KIAEDcOHzq13YAQLMnFj1tZQBAihawjwJUAEBhBUril0IAQDj04zQtMQBAD+N9h8IfAEDm0RfaVw4AQHmBY1na+f8/J1+X/gTX/z/VPMujL7T/P4Ma/0hakf8/Mfgy7oRu/z/e1WaTr0v/P4yzmjjaKP8/OpHO3QQG/z/obgKDL+P+P5VMNihawP4/QypqzYSd/j/xB55yr3r+P5/l0RfaV/4/TcMFvQQ1/j/6oDliLxL+P6h+bQda7/0/VlyhrITM/T8EOtVRr6n9P7EXCffZhv0/X/U8nARk/T8N03BBL0H9P7uwpOZZHv0/aY7Yi4T7/D8WbAwxr9j8P8RJQNbZtfw/cid0ewST/D8gBaggL3D8P87i28VZTfw/e8APa4Qq/D8pnkMQrwf8P9d7d7XZ5Ps/hVmrWgTC+z8yN9//Lp/7P+AUE6VZfPs/jvJGSoRZ+z880Hrvrjb7P+qtrpTZE/s/l4viOQTx+j9FaRbfLs76P/NGSoRZq/o/oSR+KYSI+j9OArLOrmX6P/zf5XPZQvo/qr0ZGQQg+j9Ym02+Lv35PwZ5gWNZ2vk/s1a1CIS3+T9hNOmtrpT5Pw8SHVPZcfk/ve9Q+ANP+T9qzYSdLiz5PxiruEJZCfk/xojs54Pm+D90ZiCNrsP4PyJEVDLZoPg/zyGI1wN++D99/7t8Llv4Pyvd7yFZOPg/2bojx4MV+D+GmFdsrvL3PzR2ixHZz/c/4lO/tgOt9z+QMfNbLor3Pz4PJwFZZ/c/6+xapoNE9z+Zyo5LriH3P0eowvDY/vY/9YX2lQPc9j+jYyo7Lrn2P1BBXuBYlvY//h6ShYNz9j+s/MUqrlD2P1ra+c/YLfY/B7gtdQML9j+1lWEaLuj1P2Nzlb9YxfU/EVHJZIOi9T+/Lv0Jrn/1P2wMMa/YXPU/GupkVAM69T/Ix5j5LRf1P3al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spOQ/m3G/6Jet5T+XVBJ+ToblPyYFFsCUgeU/hMTRsHPO4D/GYR9TLXjmP0ZwbfKlIeI/oG5FB8kH5j9PbbqvFBPkP92mLs85Duk/feyJCcUx5T9FUmbeBUXoP4wHSsCe5eg/qN2vAny36D+rCJLSxxfoP3sGw2/5Xuc/iQSdWsfC6D/+Rjtu+J3rPyVhOgiV0+Q/+aOoM/dQ5z+2sumtJrTnPw3Z5QBm4+U/6HdQP14e6j+EEmba/hXmP1xxcVRuIuk/9BsmGqRA7D8O3UfJBq3nP+JBDqVR/Oc/brzgeONJ5j9W8IBXcMToP5y0BHS6B+o/dstpqoLs6z8yU6QMZh3nPwq04Oql7uo/uq2I9aHG7D/dAehBi7brP0MRnETOzOs/oZwNnq6T6T8Mo2oFl3jsP8yFJXkJ6ek/tgdrrXkf5T99qUR+ohfpP0gb7PJSVu0/JDuAjwvY5D98okZ8gl/nP/rE8MejSuc/xatRtBcW7D+spF9saxXoP1JhEWhVEOk/j5VO2gqQ6D/9mlGYnB/oP3byjvi6Ue0/0CwJUFML6j+fj9cokL7vP7xNbsrLsO4/U5Iaf0d57D/wpZXnZuTtP/znxHmTKvA/2EgShCvA8D/Wl6WdmqvqPwvEoW3rLfA/7SXXXlWn7z9RTINHwG3sP3z8lBklvu4/IvO387Pn7j/2MdWCze/pP3hpedROw+w/fLAxVGob6T/FnixrUZXsPyxlGeJYF/E/gGPPnsuU8D/jUwCMZ7DwP0iKyLCKt/A/FFrW/WMh8j/a7z/oj4/wPzEWPDvPrus/95UH6SlS8T/F/ZEzXuTtPwcrqW6Jd+s/QsVx4NUy7T/t1FxuMPTwP5FVW/tMR+k/buAO1ClP8T/YxSOnZdruPwTpYtNKQfE/PS0/cJVn8D9PWyOCcZDxP9DgpYqYaOw/T46nik777j8BN4sXCwPxP4SezarPNfA/trsH6L5c8T/s/Ntlv07xP3juPVxyHPQ/9VZus8Ke7z+HNZVFYZfyP68YvzrYDO8/5MPsZdtp7T+c9/9xwiTwPzhOCvMeh/E/PcH+69z06z9ahjjWxQ3xPwIwnkFD//A/WVAYlGkU8z/JeJRKeCL0PwFFdu/y3u4/KbLWUGrv8j85fxMKEfDxP2AeMuVDUPI/GVbxRuYR8T8hZuVNNF7wP0lRZ+4hofI/sb0W9N447j+I9xxYjhDxP5BtGXCW0vE/s5jYfFy78z9/hGHAkovyP/N8BtSbsfE/FY+LahER8T+6wVCHFa7xP9ffEoB/CvM/ks7AyMsa8T86KGGm7T/yP7n/yHToNPE/coxkj1DT8D9RhNTt7CvyP9MyUu+pXPI/zcr2IW958j+PFmcMcwLxP+W7lLpkPPM/yLJg4o9C8D+/ZU6XxcTyPwu2EU92M/I/rFRQUfWL8z9/ETRmErXzP2XIsfUMAfM/h01k5gLX9D/Mgok/ijrzP3l1jgHZS/Q/3bHYJhVt9T+/1TpxOZ7xP+20NSIYx/E/mfOMfckm9D9DzZAqirfzP5zexftxe/M/NSkF3V4S8z96PC0/cNXxP1X4M7xZg/E/nyXICKjQ8z9SnKOOjiv1P04rhUAuEfQ/EtkHWRbs8z9jgEQTKOL1P7RdoQ+WcfM/Wk3XE1339D9Z3eo56V32P/nAjv8C4fQ/3zMSoRHs9D+qKjQQyyb1Pz4/jBAebfM/N8ZOeAkO9j8GSgosgEn0P8TsZdtpK/Q/HVVNEHXf9T+Czw8jhCf0P73Fw3sOTPQ/HClbJO0G9D8DmZ1F71TyP4DY0qOpXvY/wld06zU99T+3lV6bjZX1P6j7AKQ2kfY/zQcEOpO28j9xPQrXo1D0P7vvGB77mfQ/1iKimLzh+D+brbzkf/L1P1kczvxqDvY/UDblCu9y9T94z4HlCPn0P3FAS1ewzfQ/rcPRVbrb9j+NRGgEG3f1P2OYE7TJ4fY/m8jMBS7P9D9JLCl3nyP5P2ywcJLmT/c/6Nms+lwt9T+5MxMM59r1Pzlm2ZPA5vc/pmPOM/al9T/ZLm04LG31P/jGEAAcW/c/zT6PUZ459z+rCaLuA5D1P42ar5KPnfU/5e5zfLQ49j9qvko+dhf1P2U2yCQjx/Q/rFrSUQ6m9T9VUiegibD1P55g/3VumvY/GqTgKeRq+T/wqgfMQ8b1P4YCtoMRu/Y/zAuwj06d9z8urBvvjqz1P+sAiLt6Ffg/UPutnSiJ9z/XNO84Rcf4P5Gdt7HZUfg/+dfyyvWW9z9z1xLyQa/3P6N9rOC3Ifk/7DU9KCgF+D/Iemr11fX3P+VciqvKvvY/fErOiT109j8AxciSOXb4P7r6sUl+xPk/sD+Jz52g+D9lVu9wO/T4P3V0XI3syvg/mUnUCz4t9T/kK4GU2NX3P73IBPwa6fU/U7KchNIX+D/LwAEtXaH3P8tHUtLD8Pg/1QrT9xoi+D9DWI0lrO37P23DKAge//k/ZqNzfoqj+j88+IkD6Nf5P9RmnIaoIvk/b57qkJvh+j9B3xYs1aX6P4lkyLH1LPg/v2w7bY2I+T8lV7H4TUH3P/rwLEFG4Pk/fISaIVV0+j+5xJEHIov5P4SCUrRyD/s/rd12oblO+T/QgHozav75P2easP1kzPs/Rga5izCl+D8ibk4lA4D5Pwx9sIwNPfo/BhIUP8bc+T+AJy1cVoH7P87BM6FJIvs/zjl4JjRJ+j/RyVLr/Qb6P7e6nBIQs/g/x0lh3uNs+j8WjiCVYkf7P0SlETP73Po/qrNaYI8p+j+o5Qeu8iT7P8WUSKKXUfo/5dTOMLUF+j+p+L8jKnT7Pym2gqYllvo/gGPPnss0/T9yOV6B6Kn6Pxo09E9wUfo/xFxStd1k+z/vkjgroob5PwrbT8b4cP4/VTVB1H1g+z/obtdLUyT4Pzo6rkZ2pfo/UKc8uhEW+z9UILOz6N36PzV7oBUYEvs/fV9cqtI2+z+jrrX3qcr6P8dl3NRA0/o/ezGUE+0q+z9S8BRypR77P2k6OxkcJfs/+mTFcHXg+z9ckZighs/7P53Ul6WdGvw//G66ZYc4/T/bUgd5Pdj6PzT0T3CxIvs/fIDuy5mN/j+MLm8O12r8Pxyz7ElgE/s/4pS5+UZ0+z8JcHoX74f/PxPU8C2s2/o/lUVhF0Wv/T/sbTMV4vH/P4cUAySaYPw//3dEheom/j99VwT/W6n8Pzij5qvkI/4/OyF00CV8/D8oSGx3D3D8P7k16bZEPgBAJnZtb7dE/T8VWtb9Y4H8P/K1Z5YEaP4/EApK0co9/T9xjc9k/zz8P+92vTRFQP0/FoVdFD3w/D+63ct9clT8PwwG19zRn/0/Rn79EBsM/j/bNoyC4FH/PxgLQ+T0lfw/is3HtaGC/D8G9phIaXb9P3R+iuPAawBA8KMa9nsC/j924nK8AlH+P6RyE7U0N/0/FQSPb+/a/j9kzF1LyMf8P6Hctu9R3/0/H5xPHau0/z8sobskzloAQLDllettowBAfCx96ILa/z8OSphp+xf9P54MjpJX5/0/ehUZHZCk/z9gJR+7C3T9P3iZYaOsnwBAduEH51Mn/z+YTYBh+VP9P7kzEwznGvw/WoP3Vblw/T/X3qeq0BAAQKDjo8UZw/8/0GqBPSYS/j/uJCL8izAAQHh95qxPWf8/8gTCTrEq/T+wc9NmnGb+PzxLkBFQMQFAvOtsyD9zAUCygAncuqsAQG/43XTLTgBAc4i4OZUs/j8O/KiG/d7+P4Id/wWCwABAO420VN7OAEDGFRdH5VYBQNJwytx8A/8/wYwpWONMAEDxiArVzWX9P87EdCFW//4/Lh9JSQ8TAEDRJLGk3E0BQJmc2hmm9v8/g9+GGK/5/z/Jj/gVa4gAQIeOHVTiugBAE4B/SpVI/z9rC89LxeYAQGn/A6xVqwFA+WuyRj2EAEDnGfuSjRcAQIRm170Vif8/toe9UMAWAEBtxmmIKvz/P0/LD1zlGQFAFLAdjNjHAUBUOe0pOUf/P12pZ0EoPwFAowVoW83qAUCIgEOoUiMAQE2JJHoZ1QFA4yAhyhfUAEBWgO82b6wBQPbsuUxNMgFA0nXhB+cTAECaKhiV1DkCQEaYolwaTwFAiBHCo40zAUCJesGnOdkBQPZhvVErXAFAibfOv10WAEDEr1jDRW4CQPVGrTB9rwBARWlv8IWJAEAjaTf6mB8BQGt/Z3v01gJAgIeiQJ8IAEA99N2tLFEBQKG4401+mwFAEY5Z9iQQAkBk6xnCMYsBQLbbLjTXeQBA8GskCcJ1AECj0R3EzjQBQLwFEhQ/NgFAO1YpPdNbA0B6kJ4ih1gDQMnJxK2CuABAJZNTO8PUAUBWurvOhvwBQLGJzFzgMgJAc+/hkuPuAUBnYORlTcwAQIAtr1xvuwBAqpog6j6wAEBnQ/6ZQXwDQOmf4GJFDQFAa9laXySkAUDGVPoJZ7cAQHO+2HvxRQBAVKuvrgp0AUCQaAJFLOIBQLn98smKAQJAPDPBcK5RAUBZT62+utoCQA3iAzv+ywBA+mLvxRcdA0B7M2q+Sn4CQO6VeauuswJAI/WeymlvAkAw2XiwxV4CQLovZ7YrxAJAhQmjWdleAUCetkYE4zADQDsfniXI6AJALQ/SU+QQA0CQLGACt04BQLPPY5RnXgJAHO244XcjAkDtC+iFO/cBQEOLbOf76QFAEQGHUKXGAkCg+3Jmu8ICQPsgy4KJXwRAcoQM5NllAkAA4q5eRYYDQOXwSScSLARAGm7A54eBAkAnZr0YyhkDQFFoWfePxQNA1NfzNcvVAUD9h/Tb17ECQC+kw0MYXwNANScvMgGPA0CoNjgR/SoCQPyrx32rxQRAElDhCFIpBEBam8b2WoACQPokd9hE5gFAgqj7AKRWBECnIhXGFhIDQKWAtP8BlgNARyBe1y8oBUDDZRU2A7wCQGRfsvFgWwNAkMAffv67A0CyYOKPog4DQP6bFye+CgJAhE4IHXR5AkDu0/GYgRoDQHUAxF29WgRAsfm4NlTsBEDX9KCgFN0DQGkibHh6tQRACQCOPXvuBECf508b1SkEQORnI9dNOQNAHzF6bqFLA0A3NGWnH0QCQDRPrimQGQNAUAXc8/yZBEB4gZICC8AEQKIo0Cfy9ANAEkw1s5bSA0BxsDcxJFcEQHEeTmA6jQNAx549l6npAkAZWwhyUCIFQPbuj/eqZQNATiZuFcTgBUBlpx/URVoDQCgs8YCy+QNA6e+l8KC5A0Dgo/56hYUDQBtOmZtvZARAbm5MT1giBECeD88SZFQFQPcHym37jgNArORjd4FiAkAWS5F8JQAEQCBGCI82PgNAb7vQXKfxAkC9cyhDVSwFQNdMvtnmxgRAsKnzqPhvBECGIt3PKUgDQPH3i9mSpQRAcjWyKy3DBECdg2dCkyQEQK5nCMcsGwZAGuPD7GUrBUDrOel941sEQPIlVHB4YQVAqvV+ox23BECRRZp4BwgEQIcx6e+lAAZAtwiM9Q3cBkDIIHcRpogEQBGOWfYkwANAG5/J/nnaBkCsVFBR9QsGQAPRkzKpsQNAoMn+eRpwBUDbVN0jmysFQJp9HqM8AwRA1a2ek97nBUBU6/1GO94FQB5v8lt0kgVAkUlGzsK+BUBPrimQ2SkDQBlcc0f/6wVAon+CixVFA0Ctad5xiu4FQEuTUtDtNQVAU0Kwql4+BUCn6Egu/1EFQOaYLO4/QgVAb+8a9KWnBEDBHahTHr0DQKuxhLUxhgRAxhouck+XBkA6PITx0zgGQIxkj1AzdAVAa0YGuYuwBkA5K6Im+kwGQDLqWnufCgVA2VvK+WIfBUDYgAhx5RwGQEwXYvVHiAZA7+Nojqx8BUBqxw2/m94DQK1QpPs5dQVAT8jO29gsBEAfotEdxJ4FQBl0QuigGwZAiZro81FWBkCSnbex2VEGQP4nf/eOegRAqoJRSZ1gBkAlQiPYuA4GQDLnGfuSXQZAkiBcAYW6BUCXyXA8n3EFQHk/br988gRAMS3qk9zxBECu1onL8QoGQFFQilbu5QRAn+i68IMTBkCTVKaYg8AHQJqByvj3iQVAg/dVuVC5BUAT8GskCYIFQPbRqSufBQVAdQexM4VOB0A2zqYjgEsGQK+vdakRWgZASMK+nUQ0BkDeHK7VHsYGQGSw4lRrMQdAqtbCLLTzBkA7b2OzI9UEQCL99nXg/AZAlBYuq7BJBkDmllZD4q4GQHrGvmTjYQdAoFIlyt7iBUBSRlwAGgUHQDRrKSDtbwdA3xPrVPleCEDlDTDzHVwHQL14P26/jAdAuwm+afqsBUAK20/G+FAHQCb+KOrMXQdAJ/bQPlawBUDSVbq7zlYGQDaXGwx1aAdA4ZhlTwI7BUA3jliLTwEIQFILJZNT+whAF6HYCppGCED4jERoBPsGQPJ+3H75tAdAU67wLhdBB0DUhO0nY6wFQJW9pZwvNgdA1onL8QoECEBeoKTAArgHQEXzABb5FQhAZ9R8lXxMCEBVTKWfcCYHQP4PsFbt6gVAs7W+SGgbB0BJ2SJpNxoJQBXHgVfLTQZAyaze4XY4B0CSJXMs7xoJQBVVv9L5QAhAqwzjbhDtB0Bm2v6VlbYFQO0seqcC/gZAl3oWhPIeCUBx/FBpxOwHQH8a9+Y3HAhAdhn+0w0EB0AMXvQVpBkIQHxpigCnJwdAGT230JXoCEBzZrtCH9wGQC6thsQ9BghA4ugq3V3HCEDrHtlcNQ8IQEX5ghYS4AdAZr0YyommCECvz5z1KecGQOtYpfRMPwZATMXGvI7YBkC/ub963EcIQH0HP3EAHQpA12t6UFAqCUDFIRtIF+sGQPksz4O7AwpARrOyfcjrB0Do3sMlxz0JQN1++WTFIAlAfc9IhEaAB0C4mQrxSKwHQCi+2lGcMwlAI946/3apCEATtwpioHsHQLq6Y7FNigdA9s/TgEHyB0CdMcwJ2jQKQLh0zHnGvglAfUCgM2lzCUBtBrggW4YIQPJ4Wn7gKglA1PavrDSpCUAfn5Cdt6EHQEHWU6uvvghASYJwBRS6CUCdDflnBpEIQPnZyHVTGgpAuOS4UzrIB0DxLEFGQAUIQH2TpkHRPAhAEJiHTPmgB0A3UOCdfPoIQFHhCFIpNglABAXeyafXB0CmEMgljpwIQEuo4PCC+AlAfe9v0F59CkBpVUs6ygELQJMXmYBfwwhAjgOvljvjCkDtRElIpC0LQNb+zvbovQpA6FPHKqUHC0DwGYnQCAYJQMq9wKxQZAlAT+rL0k4dCEBoQpPEkqIKQFg6H54l2AhA8RExJZK4CkDPLAlQU5sJQOTCgZAswAtAPdo4Yi3+CUAG+69z01YJQJmh8UQQFwlA4dVyZyboCkANcEG2LJ8JQHOgh9o2nAhA0lPkEHHjCUBODp90IvEJQPeRW5NuawhAjDGwjuP3CEDKN9vcmG4LQHO/Q1GgbwlASih9IeT8CkDqHtlcNR8JQE+0q5DygwlAx/FDpRFDCUCWmGclrXgKQDs7GRwlDwpA+Fj60AX1CkBu/8pKkwILQKYLsfojvAlArAFKQ41SC0ClLhnHSLYIQNeDSfHxSQtAll6bjZWICUCnr+drlqsJQM6Pv7SoXw1AZ2FPO/zlCUDPL0rQX1gKQHWTGARWPghASDXs98Q6C0DnHafoSD4IQFpo5zQLVAxA7Pma5bKBCkBXfEPhs5UIQCridJKtjgpAKETAIVR5C0AY6xuY3OgMQAGQEyaMxgpA8wcDz70nC0ADRSxi2DEJQFHgnXx6vApASaEsfH1tC0Cq9X6jHdcNQPT+P06Y0AtAlUc3wqKSC0CbxvZa0FsLQKj6lc6HRwpA3BSPi2rRCkBiLxSwHRwKQO0S1VsD+wlAB13CobeYC0BaZaa0/hYLQNqyfF2GnwxAz+DvF7NlCkDWbyamC1EKQM+HZwkysgtAN+SfGcSnDEAr2bERiDcKQExw6gPJawtANPW6RWCsC0AYtJCA0bULQJ0OZD21GglAUFPL1vqSCkDByqFFtqMMQLxZg/dViQxA+Db92Y/UCkA7U+i8xo4LQNOFWP0RZgxAUjI5tTOMC0DpDIy8rDkMQKwdxTnqiAxAEkiJXdubC0D+R6ZDp1cMQPq84qlHCgtA26uPh76bC0AIILWJk4sLQNO+ub96XAtAeauuQzU1CkB8Zd6q67AKQOQz2T9P8wpA96+sNCl1DEDqlEc3wrIMQEinrnyWRwxAXywMkdOnDUDvAiUFFoAMQGIXRQ98HA1AByY3iqwVDEAVPfAxWNEMQEVKs3kcJg1Ap3oy/+j7DEDvy5ntCk0OQLdlwFlKRgxA8i2sG+9+DEA67Sk5J9YLQI7J4v4jkwpA5buUumRsDUB8YwgAjr0NQPSnjep08ApAkzXqIRptDECKITmZuBUNQLoSgeof9ApAYytoWmKFC0Aqpz0l58QMQFCpEmVvWQtALscrED2JDEAPnDOitJcNQC+NX3glqQxA6KbNOA2BC0A12xX6YMkLQLcos0Em2QxAf/W4b7W+DEBmUdhF0RMMQB78xAH0qwxAYtwNorVyDUDv5T45CuAMQNnRONTvogtA8n9HVKjuDEBDke7nFHQNQDsBTYQNbwxAKXtLOV9cDkCQaW0a2/sNQH1fXKrSlgtArBvvjoz1DEC/CvDd5m0NQF1sWikE8g1Ajzo6rkZWDUBruwm+aboMQKDGvfkNUw1A5iK+E7PODEAbE2IuqboNQMxkOJ7PYA5Ac2iR7XxfDUBMb38uGhIOQDwW26SikQxAzWJi83FNDUC8IvjfSgYNQECp9ul4zAxAyjMvh913DEB9yFuufpwNQG/yW3SyNA1AAad38X58DkCTj90FSloMQMMN+Pww0gxASSwpd59zDEA+KChFKwcOQDvLLEKxFQ5APN154jn7DkCGXKlnQSgPQOSiWkQUswxAF4IclDBDDkAKoYMu4ZAOQB09fm/Tvw1AWAVqMXgoDUBQ4978hokOQOuqQC0GTw1AK9oc5zbBDUAuGjIepcIOQPIuF/GduAxA1BOWeEAJDEBf04OCUrQPQMy209aIgA9Av7oqUIsZEEBBuAIK9TQMQPAWSFD86A1AoyB4fHsHD0DmOo20VF4OQKBTkJ+NzA5Ard7hdmj4DUBXlBKCVWUNQPRsVn2u9g5Awi/186aCDkClMsUcBBUQQBoYeVkTyw9ABFQ4glR6D0DD2hg74QUOQMnKL4MxehBAu7ciMUH9DkA4vvbMkkAQQHjWbrvQDA9Ace1ESUgkDkCNuAA0SncNQLvVc9L7Bg9AM+GX+nmTDUAX2jnNAr0OQJEotKz7Nw9A/ilVouxNDECRuTKoNvgNQE4On3QieRBA8FcBvtsEEEAVAOMZNKQOQB+kp8ghkg9AuW5Kea1UDkASGsHG9WcQQANC6+HL9A9AQ7CqXn6nDECyTSoaa78OQHfX2ZB/pg9Aj61nCMc8D0Bavi7DfyoQQJf9utOdBw1AQbrYtFIoEEDd7A+U2z4QQP4PsFbtChBA+L8jKlTHD0CsxhLWxhgQQGjuIeF7txBAOgK4WbzoD0DSrGwf8pYPQBpwlpLlPBBAnyEcs+yZD0C7Y7FNKgoNQAQCnUmbOhBAjSeCOA9XD0ApdjQO9SMQQMUI4dHGgQ5Ae6Lrwg8OEECVE+0qpOwOQMgL6fAQNhBAP1OvWwTWDUAydOygEgcQQAHD8ufbkgxAeEKvP4lvEEDkS6jg8AIPQJ1KBoAq7g5AaixhbYwNEECJJeXuc7QQQGbfFcH/1g9An3HhQEjGD0Dn4QSm04IQQKcmwRvSmA9AYeEkzR/DD0Cns5PBUXIOQHujVpi+tw9ABw39E1xsEED8i6Axk+gNQOM1r+qsBg9ALUDbatYhEEBpjUEnhKYQQM7eGW1Vog9AWycuxytgEEBF9Gvrp/8QQJimCHB6Nw9AURToE3k6EEA7Hch6asUPQLYr9MEyjhBA8+SaApnNDkAu4dBbPEQRQIc2ABsQ2RBAbY0IxsFFEECI9NvXgQMQQMsPXOUJtBBAAd2XM9sdEEDZI9QMqVIPQOyEl+DUjxBAg94bQwDQEECiREseT/sPQExUbw1sHRBAxR9FnbmnEEDUghd9BdkQQHuDL0ym2g9ANiOD3EWYEEDlz7cFS3URQOGBAYQPdRFALH++LVhyEUDghEIEHKIPQARUOIJUEhFANpVFYReNEUAylBPtKhQRQHXLDvEPGxFAD0WBPpGXEEBU/yCSIYcPQPa0w1+TfRBAE0azsn2AEUAouFhRg/kQQEIIyJdQYRFAEticg2caEUAO2NXkKZsRQG9JDtjVBBBArwlpjUHnEEB1WOGWjzwQQBiWP98WFBFA5nYv98mZEECDiNS0ixkSQICCixU1kBFAfCjRksdLEUBqMA3DR2wQQEOrkzMUpxBA2o6pu7LzEECOB1vs9pkRQKchqvBngBFA4PCCiNR0EECZ0vpbAlgRQGjvjLYqQRFApMSu7e1GEEBPWrisws4RQEYIjzaOCBFAyXiUSnhiEUDJrUm3JRoRQNMW1/hMlhFANNjUeVR0EEDDTUaVYewRQKFKzR5oPRFAcCTQYFOXEUAEb0ijAs8QQJlnJa34thBAZHYWvVMREUDCo40j1poQQHpx4qsdPRFA5gRtcvgcEUDZCpqWWMkQQLnmjv6XAxFAR3cQO1PwEUBEUDV6NXAQQHGt9rAXmhBAg/V/DvPtEUA3/dmPFGERQPZefNEePw9A18OXiSK0EUDfc2A5Qp4QQGqIKvwZvhFAoijQJ/JUEUB7vJAOD4ERQKRXA5SGEhJAhxqFJLOCEEDdQ8L3/mYRQOfj2lAxbhFAeV2/YDfsEEASaLCp8/AQQDpAMEeP7xBAp0BmZ9E7EUCjsmFNZfEQQFN+Uu3TWRFAknTN5JudEUASMSWS6I0QQK2MRj6vCBJAf9sTJLYrEUBtWikEctEQQLneNlMhthFAdcjNcAOWEUCWzodnCYoQQDGZKhiV5BBAJVgczvziEEAohA66hPMRQI+tZwjHVBFAUn+9woJDEkAVp1oLs0ARQPiOGhNinhFA04TtJ2PsEUBANPPkmpoSQATG+gYmfxFA46jcRC0FEkBCeR9Hc0QRQFlqvd9oFxFAv9h78UWrEUDLvFXXoSISQGKGxhNBZBJAJQLVP4hUEUBVUFH1K20SQLDo1mt6uBFAafzCK0keEkBFgNO7eI8RQIhJuJBHcBBApvELryTpEUBWn6ut2AcSQLvVc9L7fhJAm+yfpwHLEkANwtzu5T4SQL0eTIqPNxJA1Jy8yAScEUAhelImNYwSQDpCBvLsyhFA5e/eUWMqEkBxPQrXo7gSQA1TW+og1xBAOE2fHXAtE0BZ4gFlU94RQAmJtI0/mRFA/I7hsZ/tEkCI9xxYjhgSQPq5oSk7dRJAXas97IUKEkD6YBkbukESQHuCxHb3QBJAC55CrtQLE0BYVwVqMUgSQHXsoBLXcRJAXOSeru6QEkCH4o43+e0SQJT2Bl+YlBFA51JcVfZ1EkCy9KEL6gsTQA+Z8iGoahJAFcYWghzkEkC5p6s7FgMSQASr6uV3IhNA787abRcKE0DLLhhcc3cSQKhSswdacRFAp9HkYgzEEUDggJauYOsRQNofKLftoxJAmaHxRBBnEUAqHEEqxR4TQEmgwabOuxJAMx06Pe/2EUAPXru04TgTQKOXUSy3pBJAFO0qpPyUEkDlSj0LQkkRQNBIhEawiRJAjuVd9YCxEkDV6xaBsRYTQDoIOlrVQhJAUBxAv+8/FEBr8L4qF9ISQJbtQ95ytRJAOEiI8gXlEkALfEW3XusSQA/SU+QQ2RJAHtydtdtOE0C1jqomiJISQHwo0ZLHYxNAZ0gVxavkE0D822W/7uQSQN5UpMLYchNAinH+JhQaEkBeS8gHPasSQGIyVTAq2RJAYi8UsB3kEUBW8rG7QMESQLCtn/6z9hJAUaG6ufgTE0DPhCaJJa0SQPD7Ny9OhBJALPNWXYfKEkAlXMgjuCETQMZW0LTEUhNAN/qYDwjEE0BxdQDEXY0SQCkMyjSaFBNA7BhXXBy9E0B1yw7xD1MTQDRslPWbgRNApD1eSIf3EkBLd9fZkKcSQCrJOhxdTRNAmwKZnUUfE0A4NjtSfa8SQAAfvHZp0xFA8IY0KnCqEkD70XDK3CwUQAtFup9TKBRAWU5C6Qv5EUDG+gYmN0ITQGB0eXO41hNAEAnf+xusE0C4OZUMAC0TQPmDgefeIxJAcgD9vn9rE0A9murJ/AsTQLfxJyob7hNADAQBMnSUE0BaEMr7OLoTQEZ+/RAb7BJA0+EhjJ+GFECXyXA8n0ESQKshcY+lJxRA8rkT7L/eEkC+EkiJXVsTQLe28LxU7BFAgWCOHr/fEkBU5uYb0XUTQMZTjzS4dRRAbqErEah+E0B4YADhQ+ESQD+Skh6GnhRAP5KSHoauE0CsqSwKu2gUQCquKvuu6BJA0uKMYU4wFEAZG7rZHxATQEDc1avIsBNAGLFPAMWYEkBzS6shcYcUQGqF6XsNSRRAR6rv/KJEFECzeLEwRHYTQIC0/wHWehNA16GakqwjFEC5HK9A9JQUQJm5wOWxnhJA/gdYq3bdFECRYoBEE2gTQInpQqz+GBNAIeUn1T6lE0Dlf/J374gUQHWQ14NJaRNApbxWQndZE0DDR8SUSAoUQAdF8wAWURNAa7jIPV0VFEBUbqKW5k4TQM8wtaUOghRASDSBIhbJE0CvnL0z2soTQERTdvpBvRNA+3jou1vxE0A/G7luSoETQB6M2CeAOhVARpp4B3hSFEBDb/HwnrsTQGw9QzhmuRRAN6lorP31E0ARxHk4gWEUQKlSswdaKRRAQGoTJ/ejE0CSCfg1kjwUQKsKDcSycRNA65Cb4QbsE0AfotEdxKYUQHLAriZPURNATpZa7zdaFEDKw0KtaUYUQENbzqW4yhRAuVm8WBj6FEBWSs/0EmsUQERTdvpBpRRAclKY9zjDFEBHPNnNjMYTQGmqJ/OPZhRAsOO/QBCoE0BJMUCiCYwVQL9EvHX+lRNAV19dFahlFECD4PHtXdsTQIxK6gQ0ARVAI946/3ZpE0C8YduizL4UQLN8XYb/7BRAHm/yW3T6E0CAZ3v0huMTQJpBfGDHjxRA/YUeMXo+FUAiF5zB39cTQMrmqnmOmBVAtTf4wmQqFEAJNq5/148UQOYivhOz5hRA0Jm0qbpnFUCioX+Ci1UUQF1Q3zKnmxRALIL/rWQfFUCiDivc8jkUQB1Ea0WbkxRAOSf20D6OE0BKehhancwUQHJqZ5jaQhVAF2U2yCSTE0CHqS11kN8VQI/Ey9O5OhRA8S2sG+8OFUAz+tFwyuwUQL8LW7OV1xNAjdKlf0kKFUARcXMqGSgVQF+c+GpHwRRAQ6fn3VgYFEAGTUusjGYVQMWScvc5LhVAKCmwAKZsFUAOMV7zqkYVQMpzfR8O+hRAM1Naf0voE0AVNC2xMrIUQOyJrgs/WBVAx2ZHqu8sFEBFZFjFG/kTQHgI46dxlxRAVn+EYcBiFUCmejL/6CsVQNHoDmJnohRA+Um1T8fLFUA7xhUXRxUUQDT4+8VskRVAmgtcHmtGFUC8lpAPeo4UQHfYRGYuoBVAUoTU7exLFEDkpDDvcT4WQCJS0y6mkRVA/OHnvwc/FUCfILHdPdAVQEBPAwZJTxVAaGK6EKt/FkBxdJXurosVQPXYlgFnGRZAdVd2weDCFEA7M8FwroEWQNLkYgys8xVAMpBnl28NFkDZYrfPKtsVQOV8sfficxVAL/mf/N1TFUD3kVuTbtMVQGefxyjPvBVAQ6hSsweCFUC+iowOSFoVQHwMVpxqpRRAKlQ3F3/rFUBO8E3TZ2cVQEDDmzV4bxVAyPDYz2L5FUCKPh9lxAUVQJUrvMtFxBVADRmPUgknFkAZjuczoIYVQAHdlzPbZRVAldOeknNiFUBFvHX+7dIVQGHKwAEtvRVAynA8nwFdFEDRBIpYxDAVQHbIzXAD1hVA7wT7r3PbFEDdzOhHwykVQHaMKy6OQhZA9cDHYMUhFkA2qz5XW1EVQBuFJLN65xVAG4S53cs1FkCo4zEDlYkWQJEm3gGe3BVA1GachqiqF0BQO/w1WYsVQP0zg/jAphZA8s8M4gPDFUAuPC8VG/MVQERwXMZN/RVA2evdH+/dFUBfmEwVjHoVQC5W1GAaJhZAl3Mpriq7FUCYg6CjVfUVQLN6h9uhERZAKgDGM2hIFkCLFqBtNTMWQF7XL9gNCxZA3pGx2vznFUCphv2eWEcXQIJy275H5RVA/p3t0RtuFUBoeR7cnVUWQE7wTdNn5xVAe6Lrwg+2FkAyWHGqtTAWQNBdEmdF9BVAfNl22hrpFUDRd7eyRFcXQMlzfR8OAhZAb4Pab+1MFkD5Tsx6MUwWQEz4pX7e5BVAAP4pVaLMFUAHKXgKuWIVQPbuj/eqBRVAlFLQ7SXFFkAhHR7C+MEWQADHnj2XURdA3pIcsKsBF0CEnWLVIJwVQH/8pUV9WhdAyRtg5jtQFkAg1hu1wtQVQJtTyQBQ/RVAbaetEcF4FkC+iSE5mWgXQPZf56bN6BZABYpYxLBjFkBi3A2itXIVQEJ23sZmlxVAenB31m5jFkB1yqMbYeEWQPha0HtjQBVAz0vFxrxuFUBP6WD9n1MWQHLGMCdoGxVA4pF4eTrfFkCneFxUi5AWQP1qDhDMORdAS1gbYydMF0AHB3sTQ7IWQNqs+lxtHRdAfLq6Y7GlFkADnN7F+6kWQFLYRdEDbxdAb2WJzjLrFkBE9kGWBTsXQKTGhJhLIhdAxZCcTNwqGEAepn1zf70VQGkbf6KyYRhA022JXHAmF0Av9fOmIi0XQLBVgsXh1BZAnKxRD9FQF0D/RGXDmjoXQB08E5okThZAe0ykNJv/FkBdqWdBKI8XQPddEfxvXRZAqiwKuyh6F0Da5Vsf1lMXQPtA8s6hVBZAu5unOuQeF0ABw/Ln22IXQGK/J9apMhdAmgmGcw2DFkCTMqmhDZAXQLWPFfw21BZAeXb51ocdF0CXAz3UtpkXQACt+fGXvhZARwa5izAtF0AvhJz3/2EWQNHP1OsWiRZA6IcRwqPlF0DWrDO+LyYWQAJ/+PnveRdA8BRypZ4lF0AN38K68QYXQBg+IqZEMhdAAymxa3szGECYbhKDwIIXQGAJpMSuxRdADhR4J582F0CpF3yak5cYQIPBNXf05xdAeO+oMSF+F0BlVYSbjLIWQE3dlV0waBdA7rWg98aoF0Bhx3+BIMgWQFQDzefcvRdAjUgUWtbVF0Do24KluhAYQIBiZMkcQxhARBzr4jbyF0DJBtLFpuUXQDxQpzy6cRdAOiUgJuFqF0D3Bl+YTO0WQE0Ttp+MARhAoWmJldE4F0A/xXHg1dIXQK9+bJIfARdA6xhXXBw9GEC3LjVCP3sXQGl3SDFAkhdAWU3XE103F0CM22gAb8kXQEbURJ+PYhdAuk24V+YVGUDBHD1+bzMWQF+c+GpH4RVACp+tg4MVGEDtKw/SU7QXQP8EFytqyBhAk6zD0VWyF0DkE7LzNi4YQIuLo3ITRRhArDlAMEe3F0DYEYdsIPUXQH9QFymUNRZAvov34/YzGEA+z582qpMXQNiC3htDCBhAa0YGuYtgF0BfXKrSFicXQDQsRl1r9xdAj+Gxn8VCF0CQFmcMc/IXQKTgKeRKhRZAjXxe8dS7F0DdJXFWROUXQB0ewvhp5BhAS633G+2wGEDYe/FFezQYQBbcD3hgsBdAw2osYW1UGEAAyXTo9MwYQDzWjAxyxxhAD5wzorTXF0BAbOnRVG8XQH7IW65+rBdAiNuhYTFyGEDGbMmqCM8XQAnE6/oFQxhA06dV9Id2F0C/RpIgXAEYQD5i9NxCnxdAqg8k7xwKF0Do/BTHgVcYQNHLKJZb8hhAttYXCW3pFkA6kWCqmU0YQJ4N+WcGARhA18BWCRaPGEDi6CrdXS8YQHtNDwpKsRhAJgD/lCpRGEBvD0JAvoQYQFd+GYwR6RhACOkpcoiIGECmejL/6AsYQAoRcAhVihlA4stEEVJXF0DFbworFSwYQH47iQj/shdASphp+1duGEARww5j0o8XQMqLTMCv6RdAnPhqR3E+GEDYmxiSk0kXQPEUcqWe1RhANgNckC0LGUBt4uR+h5IWQFLUmXtIuBhATaHzGrukGEBe2nBYGmgZQAVtcvikaxlAyYy3lV5zF0BQU8vW+iIZQOcHrvIEihhAG9mVlpFaGEDg+rDeqO0YQIielEkNNRhAT5gwmpWNGUCPNo5Yi6cYQDLnGfuSZRlAyZBj6xliGECTizGwjpsYQOfkRSbgHxlANzemJyyJGEC8sgsG12wZQFwjgnFwsRhA8l1KXTKWGUCivI+jOeoZQMFWCRaH0xhA6BVPPdKwGEAkKelhaI0XQIiHMH4axxhAHaz/c5gXGEDGpL+XwtsXQLFXWHA/qBhAK97IPPInGUCxwcJJmh8YQG6FsBpLcBhAsAPnjChdF0DnxvSEJeYYQAk4hCo1ixdAdld2weDKGUCMnlvoSlwYQGhD/plBBBhAfHxCdt7+GEDskQa3tfUXQJ/nTxvVgRhAbycR4V+MGEBLsDic+aUZQNHOaRZotxlAx/Xv+szJGEBmhSLdzzkZQKrb2VceDBlA68VQTrSjGUBS76mc9pwZQBS0yeGTnhpAHsNjP4sVGUC22ViJec4ZQDZB1H0AMhlABkoKLIChGECenKG44wUaQEeWzLG8GxlA4n1VLlS+GUCMbOf7qXkaQPcF9MKdexlAVaTC2EIoGUBXPzbJj5AYQMKiIk4nIRlAIV9CBYe3GEB+/nvw2s0aQKhvmdNlWRpAQb/v37ywGUD1KjI6IIkZQJ90IsFUaxlAQKTfvg6kGECJfQIoRuYZQHGS5o9pVRpAntSXpZ16GUAMAcCxZxcaQLluSnmtfBhAB5ylZDl5GkBHJuDXSGoYQChGlsyxhBpAknh5OlcUGUC4yagyjPMYQNtOWyOCcRlAjnObcK88GUAhyhe0kDAZQPqYDwh0fhlAB3qobcM4GkCCqzyBsDsaQOXziqce8RhAFCLgEKocGkA+QPflzB4ZQJRL4xdeURpANIP4wI53GUA4bcZpiEIZQDCeQUP/xBlAuK8D54xYGUCFtTF2wpsZQBnkLsIURRpAhul7DcGBGkBkzjP2JTMaQDmZuFUQoxlACmgibHjaGEAipdk8DgsaQIyIYvIGIBpABtmyfF3uGECC6EmZ1NAYQMrC19e6FBpAMWKfAIoJGkAo1T4dj+EaQB0ibk4lQxpAUyegibBxG0BzS6shcS8ZQFCuKZDZ+RpAHuIftvQAGkDswaT4+IwaQOusFthjmhpAZeHra10iG0Dg8lgzMtAZQBXMmII1thlAKh2s/3MgGkDzkZT0MPwYQOay0Tk/ZRpAFXMQdLRyGkCkxRnDnGAaQEYm4NdIshlARztu+N28GkBYOh+eJTgZQHcU56ijuxlAU7ExryMGG0Dnx19a1K8ZQKpFRDF58xlAzFoKSPv/GkA0MshdhLEZQKNZ2T7k3RpAPdUhN8M1GkAB/ilVojwcQHSgh9o2NBpApkV9kjv8GUAw9IjRc5MbQHswKT4+IRpApS+EnPcPG0CJCP8iaBQbQPZf56bNeBtAsVJBRdWPGkBGtB1Td+UaQINQ3sfR7BpAmu51Ul+WGkCOXDelvKYbQNuNPuYDMhxAexhanZxRG0Ac746M1cYaQMxCO6dZYBpACTiEKjXLGUCXjGMkeywZQIC5Fi1AgxpAX7Uy4ZdyGkB+zAcEOgsbQCnqzD0k1BpAQnv18dCXGkDzPo7myCIaQFlt/l91rBpAlpwTe2ifG0DgRzXs99wYQJMa2gBs+BpAcSNli6SFG0Bma32R0PYZQCT0M/W6lRtAa3wm++fhGkAr+64I/rcaQDHzHfzEARpArqHUXkTzGkB5A8x8B68aQFab/1cd2RtAURn/PuOSGkCiYMYUrLEaQMakv5fC8xlAjUKSWb27GkCH+fIC7GsaQAgddAmHthpApB6i0R0MHEBJ93MK8gsaQKMDkrBvVxtA73a9NEXoGkA5l+Kqsj8bQOrqjsU2cR1A6e46G/LfGkC5TbhX5t0bQGX35GGh7EpAhu/ErBcJS0C/OSNKe/lKQDkeM1AZtUpAytb6IqH9SkA3Fakwtr5KQERpb/CFv0pAcqJdhZS1SkAV3uUivptKQFG9NbBVykpAUca/z7jMSkDoeMxAZdBKQInS3uAL7UpAPnRBfcvESkAxIHu9++FKQGEVb2Qep0pAJHDrbp4MS0A4Sl6dY5hKQPiDgefetUpA0vvG156xSkAWghyUMHlKQMwGmWTkokpAn3prYKuUSkD+t5IdG4VKQFdpUgq6uUpAp3Sw/s9vSkA4QDBHj1FKQA/Co40jmkpAp658lue1SkDZrPpcbU1KQNkWZTbIekpAH9eGinFgSkCks5PBUYJKQLacS3FViUpAr8QDyqaESkC/OSNKe1lKQD37kSIyUEpAwkKtad5NSkCI0t7gC2FKQOy2C811WEpAls5OBkdHSkDj8h/Sb1VKQF1txf6yQ0pAh/Tb14E5SkBsVn2utmBKQELrqGqCTEpArIbEPZYySkD1RUJbzpFKQC6GcqJdKUpASxqjdVQjSkBaIEHxYyxKQPq4NlSMI0pAzoO7s3YpSkA/2ZQrvDlKQBSuR+F6GEpAEVysqMEySkDKO07RkSZKQKqy74rgM0pAIoleRrH+SUA5jbRU3j5KQAt2w7ZFK0pAn8iTpGv0SUC+JmvUQ/xJQNTUsrW+8ElAbgM+P4z6SUBnb/CFyexJQBxVTRB15UlAFtS3zOn6SUB2Tx4Wag9KQO7hkuNO70lABzNt/8r2SUAytWytL95JQB0Wak3zBkpAj73e/fHwSUBPg2kYPuhJQK4D54wo80lA1VbsL7u1SUDB0ytlGfBJQEe6ZvLN4klAXPQVpBndSUBFmQ0yycJJQOi3rwPnyklAlE25wrvISUCLFTWYhqtJQI5TdCSX5UlArQj+t5KNSUCmRBK9jP5JQE8BMJ5Bu0lAq8WnABiTSUAS3uUivslJQJ1jQPZ6wUlA/+cwX16oSUDpX1lpUpRJQIsyG2SSv0lAIc1YNJ2LSUAaDeAtkGhJQAhLPKBsiklATihEwCGESUBFcvkP6Z9JQMIpOpLLuUlA2QjE6/qrSUCQvd798c5JQMEcPX5vsUlAo40j1uJZSUDdByC1iV1JQMA+OnXlcUlAq3MMyF6dSUA7cM6I0mJJQIDs9e6PXUlA+4wLB0JcSUAK16NwPVhJQL01sFWCc0lARiBe1y+ySUDOfqSIDHNJQP5byY6NQElA6/oFu2F3SUDkAMEcPVhJQDPSUnk7PElAqG+Z02VhSUCOcFrwoidJQARz9Pi9bUlA3CQGgZVRSUAd5ssLsFFJQAWZZOQsLklAr49OXfluSUBYUYNpGExJQM9IS+XtRElA64FWYMhcSUA4QDBHjzVJQNk9eVioM0lAXdxGA3hLSUD0oQvqWyxJQJM16iEaGUlArWnecYooSUBnCp3X2AFJQEAwR4/fFUlA7tx7uOQYSUDzVIfcDCFJQPTuj/eqVUlA2LERiNcLSUA/GHjuPe5IQJWQD3o21UhAZ3ke3J3fSEAC7KNTV+5IQJKRs7CnzUhAmv7sR4rASEDGxObj2gBJQIh7LH3o2khAZtr+lZXMSEDUJk7ud9hIQDnMlxdgCUlA/DpwzogESUC0jqomiORIQNy6m6c6zEhA7SB2ptD9SECp7Lsi+AdJQKeufJbnzUhAGP8+48LTSEAPzNHj9/BIQMiYu5aQ00hAigJ9Ik/kSEBsBOJ1/bJIQEM0uoPY+0hAxRaCHJS2SEDsPVxy3NtIQCTRyyiWv0hA9pfdk4flSEB88Qwa+p9IQDvVITfDeUhAx9eeWRKISEAORYE+kWVIQEArMGR1y0hAAtTUsrW+SEDHndLB+m9IQI4j1uJTqEhAo6oJou6TSECw74rgf3tIQCECDqFKnUhAI3oZxXJzSED0Zz9SRLZIQJQEqKllh0hA7m36sx+HSEBm8s02N5ZIQN6cEaW9j0hAApoIG56ASEDDu1zEd7BIQIjqrYGthkhAzeSbbW54SEBszywJUGdIQLq4jQbwdkhA2SCTjJxzSEAwZHWr50hIQPxSP28qPkhAjYychT0/SEB0yM1wAxxIQPG1Z5YETkhA+gCkNnEySECAfXTqyi9IQEj0MorlXkhAUH5S7dNDSEBjzF1LyD9IQN7b9Gc/QkhA46WbxCBiSEB36SYxCCxIQLO+SGjLI0hAKakT0ERaSECvX7AbtvNHQOiayTfbGkhAqf9zmC8FSEDyWZ4Hd1tIQCreyDzyNUhAsilXeJfzR0B1WUxsPj5IQBlR2ht8K0hAgATFjzH1R0ClMVpHVd9HQIYuqG+ZA0hAeh04Z0TrR0B8YTJVMB5IQFvmdFlM/EdAp1KzB1rdR0APuRluwOlHQNLZyeAo90dAlNkgk4zUR0BIopdRLBFIQOTaUDHOx0dA2T15WKgBSEB0WUxsPtZHQKaufJbn40dAeDvCacHLR0DzbFZ9rvRHQMgHPZtVA0hA4PPDCOHxR0DUghd9BTVIQOB1/YLd3EdAKH3ogvriR0DcupunOp5HQDLhl/p530dAMykF3V7UR0DxKQDGM8RHQBfxnZj1sEdA4Yi1+BSgR0AvrOKNzJlHQLW+SGjLmUdAwcn9DkWJR0C9b3ztmZlHQEvg1t08t0dAlMFR8uqiR0AtVtRgGohHQLyfGi/dQEdADse6uI1uR0BCCTNt/6RHQNhfdk8eeEdAtC3KbJBnR0A+OnXls0xHQBFOC170nUdAXtcv2A2lR0C6SQwCK3tHQOqtga0ScEdAvK5fsBuiR0CLjuTyH6RHQHehuU4jg0dAZRTLLa2ER0D8GHPXEkZHQGnBi76CiEdADaZh+IgyR0DQRNjw9H5HQKZEEr2MNEdAzVMdcjMmR0AbQpWaPTJHQNyX+nlTTUdAWItPATA4R0CsNCkF3VRHQCkn2lVIJ0dAIY51cRtDR0DUQzS6g1pHQBmZR/5gNkdAEpuPa0MJR0DRhy6obzVHQAkRcAhV/EZAQxfUt8wTR0AATYQNTzNHQKNYbmk1BkdA1FbsL7tXR0D6RJ4kXR1HQNE6qpogBEdAFcH/VrLrRkC7m6c65BZHQJSCbi9pHEdAB4ofY+4GR0AO8+UF2LNGQL3e/fFeXUdA5ldzgGA0R0CLw5lfzf1GQCjLEMe64kZA3SQGgZUlR0Agq1s9Jw9HQDuNtFTeIEdAXTdsW5TbRkAM/RNcrNpGQBHQRNjw1kZAcVDCTNsFR0A6WP/nML9GQFlGsdzSwkZAOcyXF2C1RkC9OseA7P9GQFIKur2krUZAXwK37ubRRkACvAUSFAVHQEB4tHHEsEZA3XahuU6lRkD+t5IdG7lGQD9vKlJhtkZASwfr/xy+RkBmg0wycpZGQI+93v3xrEZA2/l+aryyRkClvcEXJqlGQCR/MPDctUZAvk1/9iOHRkAQ5KCEmbxGQC53LSEfkEZAgAncupubRkByDMhe72hGQDGs4o3Mi0ZAAz4/jBCoRkBhTzv8Nc9GQPQyiuWWfkZAyXGndLCSRkBwzojS3rJGQKxzDMher0ZA+I2vPbNyRkBL27+y0pRGQN0CCYofaUZAEK/rF+yoRkA75Ga4AYFGQAStwJDVQ0ZAn6aWrfVHRkCRjJyFPUdGQNa7P96rXkZAdC0hH/RERkBP3zKny1ZGQMBDUaBPPkZAvYdLjjsLRkD3U+Olm3RGQF1ortNILUZAQD7o2axIRkAxdy0hH25GQIrDmV/NK0ZAMf59xoUzRkDI6lbPSStGQF5jl6jeFkZAMQOV8e81RkBLH7qgvhdGQHecoiO5WkZA5RiQvd5LRkC/fR04Z0xGQEtZhjjW/UVAfGEyVTD+RUBTeTvCaQVGQNy1hHzQIUZAOO6UDtYFRkCJH2PuWjJGQEMvo1huV0ZAU28NbJUQRkDngvqWOb9FQBKzXgzlyEVAilQYWwjgRUAJSzygbORFQEAwR4/fGUZA2jhiLT4DRkC/SGjLuQZGQBSRYRVvwEVAmlCIgEP+RUBgcTjzq9tFQMW/z7hwykVAWHOAYI7gRUAx8Nx7uL5FQCCYo8fv4UVAp7OTwVHaRUDsF+yGbQlGQKyowTQM60VAvLN224VqRUD4fmq8dNVFQE7MejGUp0VAkGYsms7cRUDqCUs8oJhFQBfUt8zpAEZAHzzaOGKZRUBRUiegiexFQP1IERlWo0VAn3HhQEjmRUD2x3vVypRFQD+p9ul4yEVApdTsgVaQRUBrJt9sc5FFQOaMKO0NmEVAOgFNhA2BRUBloDL+fahFQC4cCMkChkVARrbz/dR+RUBxFva0w8dFQAnSjEXTbUVAECf3OxSJRUB0GmmpvI1FQDWOWItPW0VAsW1RZoNaRUDVHCCYo1FFQPJ7m/7sf0VAEoPAyqFJRUCgppat9UlFQPS+8bVnVEVA20sao3VKRUBaR1UTRItFQHA486s5KkVAdWwE4nWbRUAPXVDfMl1FQKmCUUmdGEVAZ7Pqc7VfRUAYTMPwEUFFQHi5iO/EEEVAd2ZJgJpoRUAlTu53KC5FQE0oRMAhNEVAik8BMJ5RRUD//////3dFQOhg/Z/DHkVAogvqW+b6REARcAhVahJFQF1Q3zKnSUVApzrkZriTRUDhzK/mAPFEQAc4hCo1CUVAY5sb0xMKRUAHsTOFzvFEQJCDEmbaBEVArIvbaAD3REDIQQkzbUtFQE4LXvQV9kRAf2COHr/HREBuqBjnbyJFQLG/7J48JEVAsNzSakhGRUBfqwSLwylFQCfVPh2PCUVAtkWZDTK/REAmGTkLewJFQHi0ccRa7kRAFmU2yCQdRUCjO4idKchEQEpenWNAmkRAR6eufJbNREChKNAn8pREQBDaci7F2URAjt/b9GfDREAS1VsDW8tEQDWwVYLF7URAcrosJjYBRUCDL0ymCqZEQATdXtIY90RAT5KumXyjREAqHaz/c65EQB2KAn0icURAGt1B7EznREAWeO49XJ5EQD9vKlJh2ERAIEHxY8ybREDoJjEIrJBEQIhZL4ZyvkRAJk7udyiqREAPAYdQpWREQIv9ZffkhURA6EMX1LeEREDEfHkB9nlEQIqryr4rkERAKpFEL6OwREBk5CzsaXdEQCRdM/lmm0RA3eo56X1hRECLprOTwWFEQBoXDoRkX0RAc3YyOEq4REDc0mpI3G1EQA3M0eP3VkRAZwqd19hTREDcyDzyB4FEQHkKgPEMcERADiibcoVZREAUxhaCHGZEQG5MT1jic0RA++jUlc9UREDx7zMuHDhEQJLGaB1VaURA6glLPKA+RED5Bbth2zZEQKgwthDkNERAvOMUHckpRECUvDrHgGhEQOhNRSqMX0RAsYAJ3LobRECzmNh8XPNDQKtzDMheFURAKh2s/3MCREAZi6azkx9EQHVZTGw+CERAan2R0Jb5Q0C+8bVnlhpEQP/iGTT0EURA6ouEtpwzREBcPSe9bwBEQIhLjjulEURAkA96NqsyREC5iO/ErBNEQJJvtrkxJ0RAnG1uTE/4Q0Dqymd5HhBEQPw1WaMe5kNAksZoHVW9Q0DxtWeWBOBDQFmGONbF10NAG55eKcv+Q0A5BmSvdxNEQI6SV+cYNERAqB3+mqxDREDCacGLvspDQO22C811wENADKZh+IjiQ0Dk9zb92flDQLxIaMu5xkNAjfeqlQnvQ0C0C811Gr1DQCCwcmiR1UNAOqWD9X+oQ0D2Hi457rJDQNQXCW0540NAJwXdXtK+Q0DyQc9m1YdDQCUeUDblyENADE+vlGWmQ0D+fcaFA7tDQCaDo+TVkUNAuvdwyXGfQ0A3AvG6fqNDQPzBwHPvl0NAF3juPVziQ0A5HjNQGVtDQP4JLlbUrkNAYL68APuGQ0CxutVz0nVDQIXOa+wSh0NA7J48LNR4Q0AmCvSJPIVDQJwzorQ32ENAXkax3NJkQ0B6GcVyS3tDQBCq1OyBkkNAclDCTNtXQ0AynZ0MjlpDQHYQO1PoOENA8jy4O2uRQ0CS407pYE9DQNCuQspPVkNAms5OBkdHQ0B+JsKGp2lDQBWHM7+aV0NAkLjH0oeOQ0AbgXhdvzpDQNh8XBsqRENAL6NYbmlZQ0DkuFM6WFVDQHH+JhQiVENADB8RUyIjQ0BWfa62YkNDQNVW7C+7I0NAhVClZg9mQ0AN+PwwQgZDQB0gmKPHKUNA44OezaoJQ0BwrIvbaBJDQHFeY5eoJkNAmeEGfH42Q0CEDU+vlHlDQGbyzTY3NkNAQpCDEmb6QkBIp658liNDQGH9n8N8+UJAJ2Gm7V9pQ0D2evfHe+1CQPs6cM6IEENAKMsQx7r8QkDO/GoOEOBCQE4BMJ5Bw0JAWfW52ooJQ0CkiAyreP1CQG1Wfa621EJA3+6s3XbPQkAJaCJseNRCQPpXVpqUrkJAPVxy3CmvQkABJnDrbqJCQEDsTKHzxEJAwaikTkD/QkDxJOmaycdCQJW8OseAwEJAG9MTlngOQ0B8b9Of/cJCQDJLAtTU0EJAHr+36c/OQkAk2lVI+bFCQMnW+iKhqUJApIP1fw7RQkCCixU1mLhCQNKMRdPZqUJA77VnlgS0QkANdR+A1LBCQOsqpPyklEJAgmkYPiK2QkAZL90kBotCQHthMlUwsEJA9KEL6lu4QkBXCRaHM2dCQEZaKm9HqEJAzAuwj057QkCEu7N226lCQPibUIiAsUJAFB3J5T90QkAeotEdxI5CQCItlbcjwEJAPO3w12RRQkB5r1qZ8GFCQMA5I0p7X0JAVWXfFcFNQkBj7lpCPkhCQOTaUDHOUUJAdHYyOEpMQkCHS447pYdCQBxaZDvfM0JACMkCJnBHQkAG6/8c5nNCQOoX7IZtPUJAPIOG/gk6QkDmAMEcPV5CQMucLouJMUJAgyAHJcxmQkAnDwu1pi9CQCd5dY4BWUJAKETAIVRfQkD186YiFSRCQOFdLuI7KUJAJ2a9GMobQkDA/1ayYwlCQKuBrRIsHEJAfVcE/1sZQkCIAn0iTyRCQII5evzeLkJAw/ARMSUoQkCSBUzg1iVCQJXs2AjE70FAg5m2f2UdQkAT1VsDW+FBQKnsuyL4J0JAshGI1/XvQUBlqmBUUutBQIyEtpxLE0JALXO6LCYWQkCdQUP/BD1CQPW52or940FAas8sCVDxQUBEIF7XL9ZBQL+36c9+2EFAjlN0JJfxQUC/7J48LAJCQITwaOOIy0FAfrxXrUzoQUA8g4b+CchBQO4gdqbQz0FAEfxvJTviQUCt2F92TxBCQGscsRaftEFAOqWD9X/kQUCxRj1Eo/9BQF88g4b+s0FAkiIyrOKtQUBIopdRLKFBQFZ9rrZiyUFAc0F9y5zAQUAi2/l+aqhBQFOWIY51wUFAodEdxM6oQUACDqFKzaJBQLXz/dR4tUFAD5ccd0qfQUA+dEF9y5pBQHDOiNLegkFAkq6ZfLOvQUCEUKVmD4RBQCKOdXEbj0FA0lJ5O8KjQUCcoiO5/H9BQHyb/uxHlEFAPof58gJsQUDP1VbsL19BQAZHyatznkFAyeU/pN9+QUCTUtDtJVVBQBZNZyeDP0FABg39E1xUQUDPuHAgJFVBQMRVZd8Vg0FAFFysqMFkQUDbmJ6wxGlBQCmuKvuukEFAVZqUgm5fQUBoAG+BBDdBQGjon+BiRUFA2xZlNshOQUDsX1lpUnRBQGT8+4wLMUFAM/lmmxuPQUB7D5ccdzpBQNozSwLUTEFAgP+tZMcmQUDMAYI5elhBQOujU1c+K0FA0uP3Nv0PQUDtOEVHchVBQM07TtGRDEFA/FvJjo0wQUDMdRppqTZBQMotrYbEO0FAxdy1hHwuQUDF+ZtQiEpBQIe6D0BqLUFAYU87/DUrQUBJY7SOqgpBQODW3TzVNUFA3Xu45LgPQUAbZJKRszZBQKjjMQOVK0FADi2yne8tQUBq+1dWmuRAQDIuHAjJBEFAo5I6AU3kQED7AKQ2cdJAQD9XW7G/1kBAdWfttgv7QECh1jTvOA1BQHGiXYWUB0FAkT8YeO77QECC4seYu9xAQCWN0Tqq4EBATnrf+Nq7QEDSHcTOFLBAQMSFAyFZukBAf6SIDKveQEBmfjUHCL5AQMEv9fOm2kBA+I2vPbPMQEBwzojS3s5AQGUPtAJDpEBAQLyuX7DHQEBmlgSoqa1AQG9kHvmDtUBAr5RliGOdQEDkZrgBn6tAQBD8byU78kBAKjBkdauvQEDLZ3ke3LlAQB6/t+nPeEBAGoaPiCmDQEBlU67wLpVAQGk1JO6xhkBA+GuyRj3MQEBYBP9byYpAQKkmiLoPnEBAeAYN/RN0QEAUlnhA2YRAQHUaaam8g0BAgzRj0XRmQECHxD2WPmZAQCFZwARuc0BAdxA7U+hSQEAdcjPcgG9AQLKd76fGTUBAYOC593A/QEAlx53SwXZAQHd/vFethkBAcHztmSUjQED2OxQF+lhAQEzD8BExQ0BAbwhVavZaQEBZwARu3VNAQCxDHOviPkBAcY+lD10+QEA9CtejcENAQPmbUIiAXUBAHS457pQCQEBkHvmDgT1AQAxPr5RlJkBAigJ9Ik8UQEDohxHCoxNAQJEPejarBEBAqngj88gnQEAPlxx3SkVAQIMlHlA2GUBAMorlllb7P0DePNUhNwFAQP4mFCLg9D9ALNmxEYgVQEB5qkNuhv8/QPvxXrUy4T9AEr2MYrn1P0B0U5EKY+c/QF6YTBWMjj9Aa32R0JbHP0AVHcnlPwBAQCf8Uj9vBkBAJaq3BrYaQEDYWl8ktHk/QOv/HObLaz9AekljtI7aP0BXc4Bgjqo/QBM1mIbhXz9A5pE/GHgMQEBgl6jeGtg/QNZHp6582j9AAKlNnNy7P0A80AoMWfU/QIums5PBYT9AdO49XHLoP0C3dTdPdUw/QBniWBe3I0BAVkPiHksjP0Bk8s02Nwo/QNEdxM4Unj9Ar5RliGOpP0Cu/s9hvig/QEg8oGzKfT9AzojS3uBvP0Cz5VyKqx4/QIqhnGhXAT9AtWytLxIeP0AbX3tmSfg+QJAFTODW3T5AHhZqTfNOP0AZVvFG5k0/QMGGp1fKFj9A1plC5zXuPkA98gcDz+U+QL4rgv+t4D5AnC6Lic2/PkB7REyJJJo+QDt+b9OfST9AJYi6D0DSPkDC3Vm77dY+QMKedvhrIj9AGN1B7EyFPkBeY5eo3mY/QO1aQj7oVT5AyjtO0ZGgPkAi1uJTANA+QHMMyF7v/j5Al0f+YODJPkCuIM1YNIU+QCdJ10y++T5AC5jArbuxPkB58rBQa44+QJxx4UBIWj5AW79gN2zLPkCTJqWg21M+QBNm2v6VzT5AxJRIopdJPkB6LH3oghI+QLyV7NgIqD5Ay+7Jw0LRPkCCFtnO9xc+QPs6cM6IGj5AcNOf/UgdPkAJpwUv+uo+QDgQkgVM/D1AbDmX4qrGPUAj7rH0oRM+QL2d0sH6Cz5AdFlMbD7WPUB27j1cclA+QPDlBdhHIz5Ap1zhXS5ePkBAQ/8EF8s9QJZzKa4qsz1ABPpEniTJPUCYDI6SVxM+QCZJ10y+4T1AY2LzcW3cPUAgvhOzXgg+QG3/ykqTtj1At0CC4sfEPUAfmKPH7+09QECk374OnD1AOUAwR4+jPUDBTNu/spI9QOR+h6JAfz1AoE5AE2GnPUBMHhZqTYc9QKzrF+yGsT1ASL99HTifPUAxbf/KSjs9QJQw0/avQD1AcfT4vU1PPUCkGYums0M9QExTy9b6pj1A54cRwqP5PUBlJ4Oj5KE9QM01k2+22TxA0HmNXaIqPUD+VrJjIzg9QD0ipkQSET1AsOBFX0E6PUBMw/ARMUk9QCEVxhaCRD1Ahdf1C3aXPUCEWtO841w9QHtN1qiH7DxAi7lrCfm0PECFWtO849w8QNFvXwfO/TxAYbml1ZDEPECiNnFyvyc9QJZMFYxK3jxADrkZbsD7PECdY0D2eqs8QNozSwLUsDxACvSJPEm6PECBCdy6m+88QCiuKvuuvDxAQec1domSPECvEYjX9bs8QGVN845TqDxAn5xoVyE9PEBFzsKedsg8QKeMf59xVTxAHD1+b9NfPEAE6/8c5h88QI1AvK5fiDxAqbLviuCXPEB9HThnRHU8QM+bilQYLzxAqdkDrcBIPEADL/oK0ng8QPc/h/nySjxAnZj1YihXPEDZVUj5SUU8QCbyJOmaGTxAvNnmxvRoPECpLxLacio8QPBL/bypDDxA1ky+2eYaPEBMw/ARMWU8QE8Kur2kETxADGyVYHFUPED3cMlxp1Q8QIzzN6EQXTxAXDgQkgX4O0DJ5T+k38o7QGxWfa625jtAGo8ZqIwPPEDXX3ZPHso7QGIoJ9pV4DtAsde7P97DO0BU1GAahs87QE5FKowtmDtAN6YnLPGgO0ADTODW3bQ7QOyjU1c+SztAEJIFTODSO0CbrFEP0bQ7QB9iSiTRpztADIRkARMIO0AKgPEMGrI7QP1l9+RhcTtAsBu2LcpkO0CRcymuKl87QOdDF9S3HDtAsuVciqsaO0A3KGGm7Vs7QBN5knTNLDtAMAisHFpoO0AQoKaWrVE7QCegibDhQTtA7WRwlLwmO0DNvOMUHSk7QKboSC7/9TpABuv/HOZfO0AxCKwcWsA7QBGbj2tDKTtAbYEExY8ZO0B7AFKbOGk7QLJGPUSjSztAIb4Ts17UOkCVqN4a2PY6QBxfe2ZJLDtAoNtLGqO9OkAu4jsx6wE7QDS1bK0v9jpA8cgfDDy3OkC9b3ztmQE7QCw57pQOqjpAneqQm+EWO0C6xi5RvZ06QIUlHlA2FTtAGPUQje7QOkDqeMxAZYw6QKLC2EKQzzpAqy8S2nKmOkBVTRB1H7A6QMiqz9VWsDpAt40G8BZIOkBzzeSbbV46QFFrmnec6jpALvXzpiKROkCd76fGSz86QDUHCOboTTpAxzLEsS5OOkCLXaJ6a/g5QHnpJjEIMDpAIHu9++NVOkC+IVSp2S86QEcbR6zFZzpAvOgrSDMqOkDI/Q5FgS46QCWN0TqqWjpA2mgAb4EwOkAAgZVDizg6QIstBDko9TlAPPIHA8/tOUDf+NozS046QOE7MevFYDpA/4ZQpWZPOkCoGOdvQnU6QBHQRNjw/DlA54wo7Q2+OUD8YOC598A5QKcT0ETY5DlAszwP7s6qOUB+X+rnTb05QKbjMQOVETpAGCE82jieOUDot68D5wA6QE7Q7SWNiTlApe1fWWmqOUCjcD0K1585QIj029eBpzlAUI2XbhKbOUBrrIvbaHQ5QHoxlBPtvjlA9tGpK5+9OUDUOQZkr685QPzjvWplqjlAY+Qs7GnTOUDleXB31u45QOaMKO0NnjlABz2bVZ93OUC5uI0G8JI5QJv0vvG13zhAVYLF4cxfOUANLbKd7xs5QO6iryDNYDlACKcFL/oSOUBkARO4df84QNO84xQdVTlAyf0ORYH6OEDDzhQ6r/E4QKiMf59x3ThAeV2/YDfYOEAQcAhVatY4QOrJw0KtATlAdAexM4WqOECqQ26GG+w4QPJsVn2u2jhAzU4GR8kvOUDgC5Opgvk4QCbyJOma/ThAYPNxbahsOEBRuB6F6+04QPW+8bVnjjhAdJMYBFaWOEDnvMYuUWk4QBov3SQGcThAOUVHcvkbOUCd6pCb4aI4QCQGgZVDYzhAAJ8fRghHOED8TShEwGE4QPHSTWIQiDhA14FzRpRSOEBbGyrG+Sc4QKazk8FRajhAuDtrt11sOEDpQxfUt0Q4QBmZR/5gpDhA+lxtxf46OEA2sFWCxSU4QHU3T3XISThA9hkXDoRAOEBryhXe5S44QMp/SL99EThAoFNXPstLOEBxj6UPXfw3QDARNjy9NjhAjGK5pdVQOEBbrKjBNPQ3QJRgcTjz3zdArz2zJEBBOEA4oRABh+Q3QP9WsmMjODhAKhiV1Am8N0CcnQyOkrs3QP0rK01K3TdAV5BmLJqaN0Cw17s/3r83QCQUIuAQvjdAH9JvXwf6N0DBQq1p3sU3QPjaM0sCsDdAnBa86CuMN0AwPWGJB9A3QCzKbJBJmjdAwvUoXI9iN0AuCKwcWnw3QGHuWkI+WDdAHDNQGf8iN0BUn6ut2A84QMh71cqE0zdAvJ8aL92YN0B/EwoRcHg3QOpL/bypODdA1jTvOEVfN0BxbagY5xs3QGowDcNHxDdA+Yf029cZN0DMg7uzdj83QF4pyxDHfjdA2qz6XG1lN0AawFsgQWU3QDlrt11oHjdAgNQmTu5zN0AYBFYOLbY2QDC2EOSgDDdAN8yXF2DfNkAbfGEyVbA2QMFpwYu+1jZA84QlHlAWN0DErBdDOb02QCdEwCFUsTZApaDbSxpzNkDmqQ65GTY3QEUldQKanDZAXyS05VzCNkCLl24Sg8A2QI/yk2qfRjdA5zV2ierVNkBCVrd6Tno2QCItlbcjtDZAph3+mqyhNkCvzjEge3E2QNhaXyS06TZAQQkzbf+SNkCgSs0eaJ02QBhDOdGuAjdAypcXYB9pNkAEwHgGDTU2QEj5SbVPLzZA4dbdPNWRNkDVeOkmMYA2QLW+SGjLdTZAP1JEhlU8NkCA1CZO7nc2QHMuxVVlFzZArs4xIHtpNkAJpwUv+jY2QIypglFJKTZAvBjKiXYtNkCYDTLJyBU2QLNU3o5w8jVA6nw/NV7+NUC0MuGX+jk2QM64cCAkLzZA6MHdWbu5NUBBQ/8EF8s1QD5EozuI3TVA+4ZQpWbDNUBKsDic+d01QFzXL9gNvzVAf/YjRWTENUAHKT+p9uU1QOg+AKlN3DVAJXUCmgh/NUC8HeG04JU1QMNfkzXqhTVA+gCkNnHGNUAnZr0YyuE1QMVtNIC3jDVAT+lg/Z87NUD27o/3qq01QN3IPPIHmzVAQznRrkJaNUALq3gj8zg1QDOny2JiPzVA80VCW85BNUDHmLuWkEc1QAr0iTxJLjVAV+IBZVNWNUBqSNxj6Ws1QHja4a/JGjVA2NMOf03KNUBFzsKedhQ1QJV9VwT/xzRA5jV2iep5NUAFlE25wv80QFj1udqKZTVAGXPXEvLxNEAoRMAhVAk1QK8gzVg0MTVAEaW9wRcKNUAkl/+Qfu80QGCm7V9Z+TRAeNZuu9DQNEAC8bp+wd40QJaL+E7MCjVA0KQUdHstNUCGp1fKMgg1QLARiNf1uzRA2bERiNc9NUA2VIzzN200QEaZDTLJBDVAIeAQqtTMNECEu7N22400QGyoGOdvcjRARuaRPxjgNED1Bl+YTLE0QCAf9GxWaTRAXphMFYz2NEDfEKrU7Jk0QJIANbVsvTRAi6azk8GZNEAQAYdQpXI0QKeCUUmdXDRAPjp15bNgNECIhLacS0U0QM3fhEIETDRAoE/kSdINNEDAkNWtnlc0QNsRTgtecDRAzSN/MPDkM0Bz6spneU40QKaRlsrbgTRAyaZc4V3uM0CymNh8XOMzQJhuEoPAAjRAgOz17o/zM0CvA+eMKAU0QFYrE36pGzRAljRG66juM0BQNuUK76ozQF30FaQZMzRAU2XfFcG/M0C1Yn/ZPbEzQA0yychZoDNAixpMw/DhM0BVvJF55Cs0QEljtI6qfjNAPujZrPq4M0CUeEDZlA80QLiq7LsiDDRANo5Yi099M0Ag0m9fB3YzQD0nvW98aTNATS1b64toM0BhLT4FwGQzQIofY+5aVjNA9K+sNCltM0Bm1edqK6IzQIzWUdUEjTNA7rH0oQvOM0BU+3Q8ZnwzQD1IFjCBWzNAFwRWDi2CM0Bcj8L1KHgzQIx/n3HhQDNAtb5IaMuNM0AMyF7v/lQzQFC9NbBVFjNAPTp15bMYM0BX4gFlU14zQGwhyEEJEzNAdtZuu9BYM0Bhpu1fWeEyQNi2KLNBJjNAtsfShy7wMkC9pDFaR9kyQOnnTUUqCDNAZcIv9fMmM0Doaiv2l90yQGO9GMqJujJABvAWSFBcM0C1uTE9Ya0yQIdGdxA7CzNAvQD76NQ1M0ABE7h1N/8yQKaRlsrboTJAyB8MPPeWMkATYcPTK/0yQKKvIM1Y3DJAbMoV3uWiMkB62uGvyVoyQB+Yo8fvTTJApaDbSxpnMkA6cM6I0sIyQAzlRLsK2TJA4SNiSiTJMkC1LcpskGUyQNGtnpPeQzJAobQ3+MJEMkB07+GS4y4yQGnGounsYDJARqzFpwCIMkDT9q+sNEEyQODRxhFrITJADtHoDmJnMkARSfQyiv0xQB4f9GxWCTJAEEn0MopNMkCzccRafGIyQHX4a7JGGTJA8F61MuH3MUByv0NRoM8xQI8UkWEV6zFA/kP67etkMkC3MT1hiQMyQBduwOeH1TFAaHQHsTMNMkBkO99PjY8xQKZh+IiY9jFA/kP67evoMUD5LM+Du4sxQEKQgxJmdjFAYAK37uZ1MUBnjNZR1ZAxQA9FgT6RgzFAMsnIWdhrMUBgkzXqIdYxQPcBSG3irDFAdTdPdchNMUAj2/l+alwxQE0oRMAhTDFAfhghPNrIMUCuIM1YNEkxQP5WsmMjhDFA4NHGEWuZMUCSeeQPBoYxQJwRpb3BezFANO84RUdKMUAhk4ychRkxQDANw0fEgDFAlPYGX5iAMUCxLm6jAQwxQFmLTwEwAjFAGCE82jgeMUCIPEm6Zh4xQDcoYabtOzFAW+Z0WUwMMUAA++jUlf8wQPXWwFYJ9jBA+cvuycMGMUBCL6NYbu0wQGg1JO6xoDBAgD6RJ0nHMEAdigJ9IkMxQLtSliGOpTBACx8RUyLBMEAAste7P+owQLApV3iXlzBAcS7FVWWTMEAJ9Ik8SW4wQJjdk4eFsjBA5OPaUDF2MEC5g9iZQsMwQMOsF0M5wTBAbNRDNLrXMEC6TiMtlV8wQOcOYmcKnTBAumHbosxuMECJWS+GcnIwQFtCPujZnDBA8SkAxjNwMEAyETY8vTowQNUhN8MNRDBALlbUYBo+MEBCPujZrG4wQKW4quy7IjBAVpV9VwRjMEBYHM78amIwQL+BkCxgDjBAGFbxRuapMEBDF9S3zPkvQJ8kXTP5VjBAozZxcr/7L0DQeY1dooovQNTPm4pUIDBA3sg88gcDMECV8e8zLjQwQHeE04IXnS9AXaJ6a2AfMEC9b3ztmV0wQDrfT42Xri9AEkn0MoopMECdKXReYz8wQOgTeZJ0HTBAUdDtJY1BL0D7ag4QzIEvQKK4quy7Qi9APSKmRBJFL0AkC5jArcsvQPO+8bVnli9AMZQT7So8L0C0nEtxVTkvQL2MYrmlnS9AQoZVvJGRL0AEHEKVmkUvQJpeKcsQRy9ArKjBNAw3L0B8SL99HZguQOYrSDMWfS5AXS7iOzFjL0DhcOZXcyguQIGQLGACLy5AILTlXIrLLkBf6udNRVIuQBj6J7hYOS5ANUHUfQCSLkBGA3gLJAguQMi+K4L/BS5AFitqMA27LkCd9L7xtQcuQGowDcNHVC5Au9Vz0vt+LkAX7IZti6ItQJ1GWipvxy5AL/Dce7gMLkBtowG8BVIuQCbaVUj5IS5ArtNIS+VFLkAzLhwIyUouQJtattYXmS1AVD7L8+D2LUBqK/aX3bstQAkRcAhVIi5AesucLou5LUAetYmT++UsQMAXJlMFuy1A+RQA4xn8LEDqQnOdRlotQAt72uGvuS1AilkvhnJKLUDPxhFr8QktQL4Ts14MlS1AYJM16iGyLUCnlq31RaIsQHHN5Jttji1AN9GuQsqnLEDlkT8YeG4sQGM2yCQjZyxAuDtrt13ILECf4GJFDR4tQM7abReaWyxAeAH20akjLECUlSaloNssQOAjYkokaSxAL8A+OnV9LEBOBkfJq6MsQFslWBzO7CxABFYOLbItLEBhvrwA+5gsQKqVCb/U9yxA0QDeAgliLEB72uGvyZorQK+xS1Rv7StALOxph79mLEABh1ClZg8sQFlHVRNEJSxAhrlrCfmoK0B9xoUDIVErQNCRXP5DQitAcGiR7XznK0CZG9MTljgrQLnCu1zE7ytA3TzVITfDK0Bangd3Z+0qQB/vVSsTxitAgPEMGvpfK0Dr4jYawJsrQObG9IQlZitAsKcd/pq0KkDqDBr6JxgrQGa9GMqJLitAflLt0/EgK0Cvpx3+mhQqQC0+BcB4BitATulg/Z+zKkAAPj+MEI4qQMrW+iKh/SpAYB+duvLxKkDGbTSAt0gqQFoSoKaWtSpAXl6AfXQCK0Bz5bM8D44qQBLVWwNb1SlA7jhFR3K5KkA/eLRxxKIqQLGKNzKP/ClATTblCu/KKUAN8+UF2E8qQEm1T8dj7ilABKipZWsdKkDSdHYyODoqQGwvaYzW+SlACObo8Xt7KUBSCrq9pFkqQMai6exkMCpAJdpVSPlZKUAhBoGVQ7spQFCIgEOoqilAdtuF5jpFKUC/WyBB8WspQLEMcayLwylAXD0nvW/MKUC9amXCLz0pQAAYz6ChJylATYQNT6/EKEDJiXYVUv4oQN7gC5OpCilAhetRuB6FKUB2Tx4WajUpQL5bIEHxGylAbTSAt0DyKEBTXFX2XQkpQC/186Yi3ShA74/3qpUhKUCgf4KLFW0oQJ/9SBEZDilAb+tunurwKEAx5q4l5GMoQMIv9fOmyihA1A3bFmVuKECfQJ/Ik6QnQIy93v3x5idAiQeUTbmqKEDDv8+4cOgnQBB1H4DU3idA82c/UkQ2KED/TIQNT9cnQByUMNP2TyhASkG3lzR2J0C3NlSM89cnQEFD/wQXUydASkpBt5fMJ0Af+N9KdrQnQG2LMhtk8idAdu49XHL8JkBKtU/HY2YnQO9t+rMfiSdAGhuBeF2nJ0Al/FI/b5InQF9ZaVIKEidAX7Abti2KJ0A9eVioNa0nQFm77UJzdSdALfoK0ozlJkC6fsFu2PYmQH2utmJ/ISdAVdl3RfA/J0DxzTY3pi8nQGnBi76CdCdAHVVNEHUfJ0D9n8N8eeEmQLXbLjTXqSZAkdWtnpP+JkBP9wFIbYo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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]}},\"selected\":{\"id\":\"2604\"},\"selection_policy\":{\"id\":\"2603\"}},\"id\":\"2436\",\"type\":\"ColumnDataSource\"},{\"attri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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]}},\"selected\":{\"id\":\"2625\"},\"selection_policy\":{\"id\":\"2624\"}},\"id\":\"2499\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"text\":\"twophase\"},\"id\":\"2520\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"2645\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"2539\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"fill_alpha\":0.1,\"fill_color\":\"#9ecae1\",\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":0,\"x\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"K/RmecMCC8C+YUeIl6wPwDrYUYt3tgzA+tLbn4sOCsDGcTuP5QgFwFHWFG0zygjAhUYLK3A5EcCRAeoXNtQMwKNlk7L7lAnAj/0sliIBBcAFCDB2DJEMwJ/P2zOmawzADxL9NbQsCcAoUqv5Oy0KwKaqGs5GKAjAQQpDiTv7C8CvsIXFTeoHwERjN32HJAXATKlLxjE6C8CXl7LC41EKwOaknNQ8tArA5pKq7SZgB8DDQYwhSuUMwLPhVXt9EgjA+46G+CwMA8Cx89t8yMgJwMAUL2ATowPANf3IY7yMCsA3s/G7RHANwBQJpppZ+wnA9uy5TE3CBsAYioVr/7wOwPPAbKdSUAfAa524HK8ICcDh7NYyGa4HwAwfEVMiUQrASdEUS9tRC8DVBbzMsCEIwNF/xdCgvwTAKkTRTazdBsDxF2mYkMUIwGbR4Fv9lQnAwVzmzxKnBcDtpHSf0n8FwElrZ/OTPQbAisLT0Ku+BcBMvRNYpYEKwG8QCM/fzwzATZKdbSQfB8Ah4Fo371EFwDBVH/5QRw7A8DvhgPGHA8C8dDhfkcQCwJFmh1NBoAnA0NbBwd4EBsBaVUDrK9EHwLcylwrgLAfA9T6fEiGnCcBGa/sNyU8GwEmJuJRObwTAY+XhTjM+BcCbOLnfobgFwCs+9JMgCgjANOTppt6MBMAMR0a9lkYFwJ1cna3NKAbApics8YAiBsCIRhxXyIEHwPCkhcsqdAfAsE46NqfXB8BMEvAQa+4GwBsNhXQdpwvAcJ01LtJCBcDarPpcbR0BwIvLTMS2MAbAYqZIGcxyBcBKhz2jY60HwHu03aklAg/ANdMYCF0VBsDUDKmieMUHwEDS8eIOFQXAckrlkk80A8BzuiwmNvcCwPwbtFcfdwbA2VfD6jR3B8Dyjvi6sV0AwOm6Sz1m2wfAgWVbvA7jAsBGyVC6mSYHwJ4lyAioSAPA74xbcRazBMBKrNbTWEwGwNmEajmG/gPAfbvbq0WaBMBsTQS7qygEwEAOlCWEEAXANfEO8KTdAMAtcpnkkekAwE3oP7ULtwjAZB8JoL33BMBmszQB0KoCwH/xsWCHzgbAynA8nwFVAMDMQjunWXgDwKsGYW73KgHApTkNrD7SAsCyEB0CR6ICwFALFGf7DgbA+xbnuc/jAcBmKmlqfuH8v57AhYYPXgTA4SsVrw3oB8A69TdXgwYDwLIQeLu5GwHA2u0OhL+CAcAoCvSJPCkEwGLaN/dXlwXA8Wzql+O4B8BGelG7X7X8v22IluHkQwXAtT6bCxIZBcCzP1Bu27cDwH3nFyXoRwDA+vMjNDhwAsBNXZ5zXIL2vzidZKvLGf6/u9Rjtr82A8DC13wBYl8CwNj34SAhqgDAF4eOeA31AsBWq8DaYlgGwGKInL6etwLARSfw84RqAMB+EX7zLBL/v0ZfQZqxKATA84wiEFRyAMCXBANj2EQAwIFk8OZfYQLAg4zbw7nBAcCDBlGtdGUEwAtshDQZ5ALAKu8+IgHeAMDQLpVtlsH+vzg3XJoRZP+/mINF6uJLAcCLvbylQeYDwDdn6a/8BgTA/Zr23ilOB8BjrICMyq8CwID6hQ0FMgPAFzFH6pguBcBBAF/AgT/8v1dzgGCOvgHAjone8w0WAsCznhDwWtj9vzZMIxxpX/y/Fyqkoev3/b/c5WxLLtD8vzm536EoGAHA8zIvLCQ1/r8oyBnUyIj5v8dLkkK0Afy/sqAwKNO4/L+/Tdqvltb5v5S4M7hSBP2/749SZAjzAMDc2y3JAVsAwEAd6tIa/gDAe1heqLKeAsDuCn2wjF0EwE7GQr6VFgHAZdLwdzmuAMBNfFrqxRUCwKjIIeLmdP2/nTEnw0zGBsDK7ah7rggBwFNdwMsMK/u/NRWYBF6MBcB3zfXHxVoFwG6kbJG0i/e/TrvzHy0p+r8FY44v688AwEDdQIF30vu/YPGKlvIg/r/8i/vqBYr+v1jx/Fh3wv2/fLFBcKYz/r8M9D+vLv31v0F37uKiz/S/iO9p86Sh+L/A90iUB7P7vzcIKS59/gDAtV+I5ksp9b/M/LSbKnn7v+9eSU0WAgDAYroQqz/y/r+aYf5lUvYAwBwPbEvTHgHA+84vStCv+r+tkE1N3ZD7v24JCs2/J/+/d0lBXN4R8r8m4xjJHrH2vwsPUNDcWfe/en332KcN/L/w/tNozUr5vyJl1TH4/QLA+gG0Uq16+L+eUm9X+ccBwHTaCeUzXwTA3vHcMSvq/b9TVng80mX3v0C2duyxjv6/vf4kPncS/L8wm6UJgHbyvwmNu5xtOfm/hLpIoSxM/L/LO5herHn6v28qUmFsEf+/VqLsLeVc9b/kwlgR+zXuvzGe97Xkd/e/grqSLkcZ9r/YU7zbBu//v1CJkF/k2vS/mdsYlppAAsCLLhRVZJn1v6WPVDqz6PW/TN4AM99h/r/gki3cA174v56e0hy0kgHAgz+yb90D+r/z6QzndY/0v3Xav1cZUvW/M4Y5QZss+79XTjG9s2QCwODdyhKd5QDASi3vBcGu9L9h51xAHiAAwGjjLfyF4/y/2RpbGZ7o9L8iwyreyOz6vyCnnrsTQvO/bcZpiCpM8r+rZFthVfj1v1t4A3HDVPG/gR5q2zCK8r+yCpsBLvj4v8+XYjcBsOq/lPJaCd018b991pATgUUGwM0JNZ5jW/i/l30Nd+Qu9r8siaL2ERYFwDZDBeLQFvi/He1uVF229r9j0XR2Mijxv93BmalanPm/LR0Y5T5e7r+bw7Xaw17wv1Z0kHzKJvG/pR5YRANX8r9/Ns2WB4T1v9MzvcRY1vS/nLUlvE4k8b8YgQx49Erzvx1bKsoAu/C/2sgamldK87+QygNHuK/yv/61vHK97fa/UCorl9fr+7+ij0MOW2T1v222qAXl7P2/5R5cSxLV979Z9zTMdd/xv8zy0NJwRfW/qwHviRqR8b+pmVpbHcXyv30geedQpvC/l+SAXU2u9b9NMqzBf7Ppv0NORjI3wei/R3eMAq+c7r/K/MR9u1frv+l4Fs5/2fW/feZRlsY08b8bWq7I+Tz8v3auvYkA6+y/pmW9e/RU7r99CKpGr/b7vyrc+gLdm+G/54Ov+QKsBsAWeg521LL0vwE2e/vOKvO/O7iF+NH63r/J+g/hRjfqv2CgtexaDPq/19jK8EQV879NdmSTmX7sv1u1jFBD5um/izbHuU1Y978Q3f077GcDwE2F093Qz++/tK7RcqBH878Zn7Bh2d7ov5Zut8lNKfi/Fl6Tf3cM9r8b6bHSSTv9v/3g16PLNvO/AkNWt3o+8r86iISM09Lsv51yO+qeO/u/bmQe+YNx9r9o59lRQWrwv2VqtwKvS/q/q3ZNSGuM8b8uxsA6jq/yv/E4mI+cw+a/NpsiG6Ng8b8QxwRGqHP1v52GqMKfIf2/7xjDQed68r/ozCz4I8vyvw9wUuKEM/G/Ti9KM4qz5r+Q65Vof8bwv/lt46oNefa/GnrVFBKq/L+lZDkJpb/8v0L21bA6rfK/V/c8Pb7G7r/vhKgMLZzrv6CbaB12i+W/zBQpg1nX87+SzRPXSqvpv/rdKj70I+2/GQ3PATic+L+HhgfFPbPpvzi26K428PG/qe3LPjS48L/++Sq3vAvpv9jPi6jDie6/pm+Ipw1N+L/Czj254Dvvv12f3jHhrO6/doDMc+nU8b9j0XR2MmgAwHD9BcyNc/K/4jDiTF2T87+5fzS1z5fjv5VbQXDoz+2/a/QHVhe45r9vCJ/3EA72v+cj31tHS+u/MmvvdGNB7L/ammMvylL3v6smiLoPgPK/gmuTLw3o8b+jXQFc+1jtv8G/jFLX5OK//KawUkE18L+flKTG37H2v+Xv3lFjUvi/crIeCNpu87/zlsS8O9Drv8Dcm50UP+m/Ctrk8Em38r+/gxsA3JLev9VWkXZIFvW/s/1Uqn4057+8zBN8kVjrv3ydL1EYz/S/goTNpV2x3b8YYHpWLVTxvx6DXzR1mPW/RTgcTHmz7L/MYiDXnxfiv8AUDlIqoN+/YQ20juyC1r9dtzELJzjrv8uupKpDbe2/kkNAlQXp7r9F4z+Ts7bwv/Gef5JtFuG/sKssfhGM7b9KSjCLP1DovxEVqpuL7/6/mE4MRZGQ7r8Ze4p32wD1vyLgUsamMuq/vMD23b64579bXm9RHPbCv+Bw1SsbzPO/IG1v+UB57L8r5THaFYDDvyOGNmNFC9m/ObgysKfQ7b8MWbzcUIbov/cSEZsbJeG/keRmduUs2r/zIUXwATLXv14P5Kj1weu/MQEJ1Kwd87+XnMntTRLuvwWSZuIMJPC/iIi08GkM0b8Dd0WVBsP4v2ggVLFK7Oi/ZHVpy9Lx07/uvvjc6NfmvztA5rl00vW/oywy8JKO+78f628qzsjkv0jiQKPPAt+/LxuVggsl5L9Tdrgliz7jvyxAPpWRUum/WuCfEAkY57+7i+a3ngfmv/AGwXhA+N6/HdV+pdKD6r+44Rwauxnlv+ptO4Yqyee/IABAZzXR1L/Rt7u9WmT1vxKFM0tEEOm/JXcz/tjP579IOfMG86Lwv+E0r7ABPeC/8Jb1rLXB9r8WDkq5d/Trv4ecQtdTZd6/vrFvQK5h3r+2qyVXkFriv4ERLPXJfeW/mh1OBYEq4b8I8+wsWZngv5beJ9xlHse/cR4MRGg35b+S8s0VKb3lv+NVtSjcUOy/2Qi8erI+6785tY4F4Lrxv68cxkkGlfG/uY95cLnS7L+wrhOPck26v8vge8Gf6Ni/HcuK+oehyr/XPLs6zxHmv/foaLAEbdG/yhX/8wsB7b8+rSZ42H7Uv9w67kqBm/S/1FlWL/kO6b99HUDYjPDvv7bcT3xrVvS/XK2PXj+a5r8kzLxudBLvv4GeemKlK+q/vSIyi9SU5r9teWiPfzWpv8dAQ6RLxPa/Iy9rYoHv3b+tEYeNLrbkv3sMmLg8s9m/vuMtumnx5r+Deoay6MTgv4pm0JaUZ+e/GlRVRxIN5r+ZzvNM1Hfxv5AwqS23bMK/54cZM+yk47+C++AAI83mv3JhSV5C+uO/DZnA52bD1L92qEP6L4jav+QW6wL72+u/HUdBKqTg6r/eFvIpfC3sv/EZgV/Ant6/pbcmemxt0L8kcT2nrMjSvxVsp9aQstu/EeB4Z4Kb4b/3XY3Dy5ndv9gpVg3CnNm/v/VhvVGr0r9ZDKpPagbsv9zF/ChfusM/3ePxWUMO079COsC8ld/Bvx5b24Ms5aW/Fjfq+JqL07+FgxhDlBrwv8VfrNKKrdW/GRyp53J92L/gqbK13+bpv/xZReKSUeC/g83v6gun5L/A3zfXk83uv55p8pxGvbY/m9NVTyBLy78cHmc/9/rxv50C3APf+re/L6Hl7cbq27826ddSF5vdv5ls2a2njuu/wNUyAPGGyb84QWFxtLrmv/3yj99XvMS/ImncQCY+57+mxGRg0wnxv7LXeSMM9uG/qYstZ2Oz57/sItCJ0tjdv+nwSnHZUdu/7tAL0ue+1b+bYM07LRPgv99xaYD7j+O/RxOt5HxUwb+EDBIS0X6sP7fkwMSCr9q/nnOeTgUe4L+A/MZTZvW3PxgyaDIt6/W/aaEqx+Bo5b8cGbM+SAPHv+zF5bKwS+e/Zmuen7mZ4b/3gg9YS9ezvybvnUpmcqU/YWzfq29Dwb/gy+AvM9q1v56RzuHWNOO/EeBXWZl447+2ysC/EMvXvyus8SWWrOu/YkFpwe4owr+S6OHbJiLZvxJvU/Kgj9q/o6QL2nn11r9ZuqN7rdbnv8UHZdC/k6w/QJKKrT0/uL9u7tidKMjWv4eU0Y48TNy/2QDPaj/h07/1cgq4CMjPv0nWNei4C68/bhO06u/82L/sZXb1ZUuCvy0UwP8cp9O/EMxNq1Nb6b9CZA3uOXbWvxSRYRVvFPC/iA5gFZhD4b8QfIgd+D7av1zoCOjX+cq/zipUs96a1L88wVmlTxb5v1FcwJFh4em/68yY3e6A0r9Tp+q7rqHbv8mm6IpKcdM/628JwD+F0L+IMW0oSlzSP9NmzsDp2bq/ptan1wdEvj+4JTClR/bUvyqBnEn+1ME/JZ1YEmbr57/T3MhEY1C/v16MkqF0E+m/GTzHC9/+rL+hBGghIlHbv4iqiGiustO/aLU85m7dzr/s1cdD353NvxntDZhp9qk/VXMKCVCnwT9182RpbUvkv4vi0udZf6+/MxOxLaiU2b81BGysaVPtvxqaNgy0Vem/yJDOhh3CuT/OpFVGhqncv6qnwfpgte+/RsRkD4w6or9QuZHL4rLBvwirZ/eaVLq/Fd/UMBEpwr+RU4VQ7zPLv6506/MgBu2/vaCmEnVRz79+ge4FRffYv8A1wYHaudQ/3kb2TQnkuT+BYjtK67Dav6zkY3eB0t2/h1BCPFTL07/KMJNNXmnQv/NNBaJIs9K/WnkTjf9s5b/9jSxP1t7Zv7mAI8MibcC/XNuAdFYQ1r+k9BKEpwfgv2iP9sP4Hum/RimdH7HD0j90RR2wAxSEv0ldlbhM1cq/92loRczz47+/ety3Wkfav64LBY0VzNq/9b8ab0Rayr/OqNCrx17Hv2qDqDWsrb+/2vRvsJrb0L+vLGa+YlHTv1jgyI86Msq/82XUQuryyr85n3YC3qWtv0xg8B/Bw7q/wNSp1OeY0j+YN3eJJFnNv+ncm3wGlr2/wkNBvr5V0D+Gc09PBiTkv2oF+gKCwuK/VbqiMeaw2T+zhO/c/xDhv3UZGJWuQqg/ERCKtRHywD9cAuiT99qAP1jqcq1qh8+/YhAWHeKCxb+iL+NXwMWVv8Ork9Dpu5G/tZHTU7sRvr/sPmXUM3/UP5bm2kBPXdO/SFgSqBff2j/D6+FoGtbQP0ea56TRxro/GzXTezLYwr/JMQ4FngGwPyAUQKMHbcU/hZtKDvFyvr97S3t7vsPHP9uQ/uX6wbc/XN2Vg/fasb908YkFVn+0v/ECVz9X19c/o9LCRAfNyD8byty+Pwzcv9BFZNSMt8u/LXPoZBFZwD9xWWwwYIvOP2mhrv+ERM2/MgUx8cNYwT/Yp7loCrXQP28BVLBHWqu//zebM0d7r793Z7199Y/GPzQ9k8NIS+E/QKTuVtgEnD+4GdHqonDIv4IyU3uNtOE/csXFUblp0b/O45PCeuu0P7Cqf4yQTNc/7a2z51MD0r/chu7lgJXHP3DokEiZXNO/7GQueOp00r9y2NZ/OFDTP3wt4wR4W74/NGee2Bp847+TuOZyqWipvwUQfq8PVZ0/9hhkrOW3rL9+29l4LG3YPxuIAgnM+90/R+RYav+74L8xqS23rKmqP+aOxtNKl1k/B0KRciDp4L9qoDu5jcPRv3NaJHF/w4a/hC12+6yy4L+EPIqMcVLnvwrCvJdgkMA/1b2AJA2q1z9BaSQZpAbVP2f45JtMoMG/2QRh2ZJ2cz+aZD6cl3W6PwcfMRdEJtq/k8XcOb0g0D+q1l8C+araP6fXJEdToLw/lTU9akQX1L8dQr9jNlC6vzUm1YiqKb+/V/JOkYXgwT8j9k29FVmwv4yJFJ1B8M0/EyzE2WNY2r9bGHXv2eHZP8DQI0bPrdY/coE9ubWrsr9qMe+mmFmxv+2jJEiTv8w/HBfbkr+Vwz8C/4JHlY3KP67jjQbPqOG/0bupL+jw3j/SmP9G8QDfP+I40V37yri/mYtTCD/M0z94qo37oIjgP5guBgdiNt0/qcYJG7fbwz/3RxCV40HiP5pXpY8hSaC/tJm/GWdZxb88USuvCWfJvzwb6l7EStI/LSTDnjRc2z854wNUm6zAv77uvnSkRMg/M3O7du076T9ZB3AV7AiYPy1ERaS/6uE/Ba5lEQ6mwb9ZbmR8akXIPzmTPsY/gMA/TbxD6nO+rr9KIJJbu0/SP2irFAC4GbM/LBGci6NYtj9w+eJnMJHTP/odknPFueQ/Z1Gvxp8J1D/+E9hzBDbnv/1L726nZdK/+YeG9eGBpz/yuGb6Pl/CP60EYkRoBeE/OPIGuQc40b8LTAIvjmW3P94FUHpJXaE/A4abQp2I0z+sbkbk8/60v8kD9G9Vwdg/OIbf0e9w2z9eCn/uGsDKP2Ch7ofIfsY/NMD8HaMfrT9e/IbsMOTjP8wMBMmHFZa/Q5/6zeVC3T9WDNs/5OffP+DEqTntJ8A/KrjMp5bG1j82q8KP//zIP2EebJDNHtm/Ed3eLi5nr78dSJvT+pW7P0MzNhGJpN4/nbsjhMPi0j+52zfv5sbgvxkDLVVQzuQ/NcCv2PmTrj93HblU9sTYPyasS5VBmME/ak09HG4R0T93FJGo6hrEP+I1W1i7FqI/VTdyOE5l0D97AsEZhU/LPyCiZIGVJN8/KZwfd/jI0z9jJIP14hjUP+hEBuIKotM/HdNVskoGxz+4cEmjPNLfP5qg17ZgrdY/dulXIYI9zT8Mc7JvT1m0v1+qBFEYcN4/nNlTF5V5zD/qt8Pnzc/DP1FsYAa+reY/GMxfIXOlzT+JKZFEL2PeP7AdGIIUo7w/DroIfBN95z9ttmbpErfjP7GI3U6NfeM/VVNg8tcMpj+kaPVA8YTLP/I8wKyz7tQ/bIhIUnRi0T/fro81wFjiP1kISdGQEp6/z+khNjJxyz+0z/uw8oyyP6PNqs/VVss/hCpHXlx+pT8fOD7FN7XTPzuzZxODV9U/t+B3mYLx3z9X2U7GvmXaP/RCU9kkrdM/dvaE25A1wT9E+P6jwprmP25+LuCGdNU/m0PGYTig5D/3brkbwOLhP6BCbLjhGss/hN8bfavZ4784h2u1hx3XPzYf3/fSqNk/I/Dqybrn4j9om/JT4jvXPxRUZN/bVcA/2Euuvaqe4z8TxqIrCXfEv9ERbYW4K9k/zV++SKon3j9gxMfycde5P76LtcckhtA/j3VpqsRIxz92F6xhVIzkP8cf+w+fatU//tBx2viY0z9O5ag0RtHAPy6PNSODzOU/a0QmnLpLir+ssd9upEfmP+biPvikoZU/t+sIVL1k0j9jC//xd1LEv1f3n2d5D+Y/vrE1lSRD4D9V8BG6FgDiP8o4BJZ1YsM/3xR3OJEb4D+iV489c73TP3xyA/SxUeQ/jDS8HCD/yD+hz5Gmi/7jP5rBc0qbRcs/UsuVTJV5uD+00U0jrITWP0Xu6eqOZeE/CGbBXDzQbz9SnF1wZvGzP19Y221Hs8E/nCGPvziB6T8H6M5+at2ePwiK5bdkjOI/UNaXWxCAvT/NtYGeeqLaPw8InaWetOQ/dapH3Xj+xz8m8SSv77/MP9qlVxTADuY/CCP2CaBo4j/FkouU2sndP9w+Qej0asI/De2tktlq1b+tzSC6d7+4P/fUA0lMztI/5CdA2iBP5D9M4eb5eA3VP2iyA9eqB+g/8AAOK1rY/b4S8O9cre3gP8kr57336Og/mcvT2rCN4j9YUQ8TBSHQP5FFmngH6Oc/K/lclkSw0T9XUcE6dZmxP8yhPUWrZtQ/bGOJWtyH4T8mWJiVWH/kP2jwtW8HLdw/dmE5fLE76D9J2SJpNyrmP/odUFfzw+s/cgl2sopt1b/eDgUaCYDbP7VcK1ovuNI/g5pr4i4M3z9cMjPYefDiP9HeRu7cwKo/gerEir/S6T/TjvL+BQPhPzs4QTbx16U/yqs5YT7Q2z/mpnJ/mv/CP0Q3mNkpjtA/jmdbw8gPxj8viKt3dkHLPw56wlQretg//N3gsNk25T8HJCc0xQPmP3CHGyqlG+I/XfhmQGKA4z+ZoY4aVZ7sPzxWQtpzN+A/u6bVymMR3z9lhpUjx8rcP42LmwHL3dI/BGGf5+wg7j930kaeuUHkP24Tcs4dF9M/XKlOpIfz4z9/Xl267tK4vyX1ZB/gIK8/uL/ld7t64j+eDEx2heHhP4UP3oRmWtA/HlB4Ad0U1T+NeYCbg//hPyhHqlfgF6E/CMBoJHwu4T8/Kx84HZfXP0Jme7Ui+MU/oAzVZ+OVoz/lFDZmhgvmP4qqktohRMI/EvJqTpjv1j8YynDZdEbYP6wjgeWMcdA/EILIAT9j4j8hNh6NvzTjP1ypLZae8Oo/kRI3fhOA6T+W9Ac1Cb/TP1zOvlVLWN8/8r+Ne5CR4j+QmsC+57HfP9HN/kC5Hec/fG8EkHda3j/1e7acuN3RP6A/wJzRXdQ/m+P4ewv24T9SfPgJ0lLLv4INPoM8Ud8/A9nCXu4k6j818CwMVHDBP6CJ8v27e+i/4XWiyWpv7z+52zfv5mbeP9vL8H5gd+8/pzqJrUXw4j+0Ln/PWUDlP1PRs7SubOE/wNrmAKDO2j9+Lr94q+PhP7Ig3oSMcdo/f9LU2zRw2r+g878B0kPhP8LBvbanSeo/N2Nm2XIyyj+7GQMl5CfiP6+EpAUeLuQ/2RC5bLa64z9nsyyQh6viP70BQPfgE8I/O02wScgB5D9W2CjFcPC1P4/qdCDrKcc/2hjHihIr4z8OAZB4UfKmP6sgivKageQ/Yi4tExMe6T/G0vLJqy/VP0hiF3+61eo/9bs0bv9k5T/GYVn+tibcP7eD8Owbzes/a5uHuN6b5j+cqABziNPnP5WmOWD0SOI/f8dsoCt34z8qCJqmOirrP8P8cOvJx+g/WGeolhwj3z+gxt4H9xXjP7qEAVMfG/A/PXEne8XfxT+64+Lih17tP7VMbUZZodg/W6NYTVuM6D9MpWXF7FznPzAousvRJes/yYKZIRtZ5D/MuW8QCG/jP3JUbqKWpuo/XFPmByp61z/2JxLI/O7nP7hIkAAkScw/7/+Iy5Yx4T8onppo49rnPzhn6a/8/uw/sE2VtW5v6T8jXxbOxu6yvwn6j3UGEOM/o+lwnRTgwD/os/KB09HuP8XkcFquZuQ/OqWLZsgF3D8VP8bctQTRP6Fou5VnluM/honti9dO6z/CG9KowJnkP9rUs/+FDug/G5hgYVYC5D+Ym1anVgHdP0Phs3VwYOw/KDKtLFUS3D/ssyt2+dvRP2t/3IhrGM8/BtH/F3Rn3D+GFVVcqL7mP8wQhZ7mp+I/Xue2r8kL6T+TNAOFD1/cPzgOgq9kjuk/6R7IMN163T/1u9FDRHzhP8Yay0eUbtA/Oise7lWB8D+j7Kms2GXLP8x+OKNBFeo/0QqIIDkv6T+M6OgCqFvwP38xGZZYfNU/MJ0YiiKB7j8JeOtfBjHnP8buK6Q2oO8/QwgCQ9of4j8N675K2zvnPxv8Nw5A89c/1qlVaN6J6D9QAMXIkonvPxZmJdZ3eN8/rNzyLmp53T+KbzDt/jXkPyh10amO2eY/MdLkkkWCtD8/WN8jDwLKv5JspimfAeQ/Ln0iLoTl5D+nKRs5f3HXP79JqCAMmtE//V3IuBwu7D9lE8OCuSXnP3WkAkB48eo/5gSOgOFn6z9qdrTcXw7hP2xTp8mtJdY/vRGjCCXD5T8JG55eKSvbPxGxmEMYINM/KfYjh4Aq6D/lTgL+nWvSPzpUU5J1+Ok/PsaiCvuN2z8QVHTBbFTpPzupL0s71eY/aj9K0z1+3z+bg06l8pjqPyusTN8ILuM/Xy4c57rZ7z968bAWwDDYPx1MFjk8m+0/3zFdBJ0r7T89OhosQdvqP83c+KNAUIq/1fczH4Te7T8nAYMHetbnP/HX4FTWfOo/AfsJ437i7T9NbamDvI7kPzOj5WEdvuw/UFH1K50v5D/uYYrNIk/hP50TvYTxMNo/6cklI6Gs2D8q9XaV/wrxP9vQYmM92eg/iO6b8zr/7T9UIw3RlVbvP1Wx5yEJceQ/K1LdM30s7j/sCHXL7aLvP+XV9+mRAfE/6uePYfyh6j///hhj9cHrP58Nr9rrI+A/Qp2wzHRC4T9Uq6+uCvTxP1NR5UkMseg/vHOse/l35j9kZ9msXZflP1tTrFyg6+w/9GRIX1Jm6D+pzpMAb4DuP5FndmGU1d8/bHNr6woK7D8zXdsdShvtPy0BfOD4dOc/g7ovBIyA4D/ZVIJqKMrwPxJmXjc6MfI/4qDWlxk07j9b2fRWE/rtPzvDWM/ey/A/rMHiDbwc5T9Cx7Nw/rvwP8mXq3pUN+o/ENA7HeG37D/ApOfMLCjlP07tLWFEneQ/1vcrrjtX8T+I1h+bw7mvvynYFAKY5vA/nn3EM5FH8T+NexQqDxXwP0KLtnQWZ/I/L1tnU+D66z+qfXw6BZbkPwaB119dYuk/W+ToOwmW5T9c/43Bs/LbPzLqGF/N5OM/sXvAdg+k5z+dz8KWBdjxP8Z4KGWtXOw/4kU2wmg36D8N+nciLTrvP87HEFvVLes/dsKNjLxZ5z9lUbc36MjwP5u/rsuVdvE/BOCGtYQu4z8UK908WdrqP8uKfsBF3+0/Hyv4bYhx8z+l08J+shblPwZsYtxoK+4/+HL61XfZ4j9LAKNw4hDsPz82h3MmwOg/zccYzB316j9/LArcNlPjP/eMbec11eM/UhtqTj2W6j92DHRfYdC1PxjlgPoiu/A/04Ld0XvK5z8x1ScUfYnyPxSkCF9O3+U/aj6+76Vh7T8BLeH52m3tP/zfERWqu98/d2QPYbqY3z/anebLqM3xP66R0b8sptc/F4eOeA3F8T8oze7iYAPRP7gEO1nFdsQ/04MnmUHh5z+UVOBDDe/rP/VtXiiil+w/WtBBuH7B6j8He9EmoGziP/POX/CCm+U/9uEokhK/7j+25tiLsqjwP6ond8hi5fA/nxgfhz2k6D/izuBK0fXyPyBWblgJPO8/GDfBeWmx8T9xGT+mGFThPziKB+8GjOY/4l7TYnSZ5z/IC8jiJ+PpP3oZSavvVuw/WEUsILzv5T/vRtVl52PyP3FNaC8up+8/7erhDWHT5T9AGBXEgtPlP6NP9XUqWus/D590IsGU6D8hSsUQSgnyP21FUVbC2fM/TcivzhqEgb/nJIxNyNruP5JpAn/XO+U//26qg/bp6z/E8VOHopHhP9bQ3eDRF+k/lHIx5cdI5z/RG7R4LWjwP4lzuzTRefA/whfkNjN94z+gji/wyLfKP6rUDZA/U+o/HgjaLn5U7D8KsjO/eaXsPyekNQadUNw/zvbwfj9p7D+aWMeOGerYP9dqD3uhUO0/A5fHmpEh0z/pE3EhLIbmP6JZAr4VGO4/Bsdda4z54j/FStQk28XwPw4F4F020+0/UjOcGZp+5D+3++rk6+boP5VyzroM8PA/oNGpbbt36j9KaORWtRryP1wBZGwR5us/D62ACJKD7z8k3s9jc/nXPwNt3ZOok+Y/Crn3FRDn8T8axIM9WMzuP8UVvI1ytfM/WupqPCIQ7z+F3gthbzHwP0B0OQyDJe8/Ow1isZf38z9f/CPCdZvvP7U2S9HjOvA/AWK3dHEw8T8kglBiAAbpP31Pk7ZEqPE/CAEaIRML7D8fJxJtQ1znPzkpaVHhUOk/6Zmgfv7o7D9Hq73mf4/gPzy4Q9z/hOw/Kki/vzla6z+MONcPNRrhPyWeHqGHxuQ/HMUovpA06z+7kcNxKmPnP9ttk2FHueM/defkoN9S8z8a4rPQKZPrP5CKOecr8fA/WcKY/Gjr5z/1RJ3alb3vP/ngUiFgLfA/plE3BlND8j/t4st+vJviP5W2fhveo+8/YNncAzr03j8bQc8LHBXuP1njKh4wkuo/2e79kRKA8T87l7krgaXiP0gRIcc5Xu0/tjF2wkvA8j/zvGWYJMDhP5Vl4xzQLfE/cPjVA4N37D8LrVY/mVPwP2VqVNjzQuE/Swxd5PmX8T8/h545kCrzP5j4xLYc+uk/qGfu38SJ7D/uemmKADfzP8f4aiZj9e0/Yp3PJcFg8j80CSgeYarwP+HZmoQ989s/tDRcieXb8j9MZTg7peXjP91yHuPEZuI/OSDPT+2D6j8xgbYwZpbxP9QRn7/5Iuo/SQZv/hVo6z/akNofg2DzP0ei4d5GhOo/C4nFuZd16D+Cn8Qpa2LsP07FWyGLiOE/KNzhZTyA8z/YJezT2LPwP+9Uny/m7Og/XELbvR607z8Q8OahneDgP1D+UUjwXu8/YxnRLL9i8z8I3ZAMWmTvP+pAcynwxuw/b81nikok8D8DiTd8HAfyPzIWVdhvyvE/8tR+xuAc6z+Bz1E/Vt3uP4CslioHmfI/lLjxm4BO7z8H8mi6CQTuP1BXVh7N9u4/JhelfO8E8j9ejx2vmx3pPyIdeXtr++4/1VC0vLwK8z+K4vocxBPwP1OHicQM5u4/UdA3s6ee8T/vZ8JAISzyP92uPO2Vnu8/kIXoEDga8T+igh7FlJPxP6QhPgudsvI/u3q6X6qe7D8SwTi4dNzlP/Uas9OsL+o/kRaht/wg7j+QlrE+cXrwPxlPLfBPeO0/fIQ395kL4D/L1VWiaPXeP23VAVKTx+Q/XjF+dbA59T/j7mJQXKTtP/KSxR5W3+o/6xDNdmSQ6j+Ny58M4VLxP4GT0ArKvMo/j0zR2+kY8T95Ra6jww7xP13jTHbgYvA/gWAK5hoM5z8IMHYM2YrxP1PovMYuufA/E3PeOXNT7D9AS3i+dgvyPwxMPNoX1O4/myU7FfTn6j9xLDk4IsnzP2CPDc0Kf+k/vCL430pG8T9zWgHPB0XxP28VozLu6+8/t1OE5RkF8T+GTWxXSybzP/VGEFs4GOk//nJ355qT9T/PiC2YUz3xPwCoJOP/M/A/6zc04W577z8m0YGbe67yP3XNHkf33Os/Ed6ivCSI7z9UkOGpLl3tP1qhSPdzSvQ/JjUXLJN56D/r69iM/K/vP8LmuRFYQeQ/NNpoCOBZ4T/sSUfWbSLuP3aDkSya9fA/0HA1eIDD7D+XW7XG+8z0PyjQJ/IkqfE/sCOKoJxG8z83IDrr8EPxP53I5aLO2uc/5sYdBFe48z/ij6LO3IPzP24Ed9r5ivE/sZLiJTCU8D9GDJZFvMD0P81AhgrlP+k/J3tTqqdz8j9bllQSfv7xP5auPw0Ikus/9wiQ/Bzq8z8TBtC1UC7rP+VvlB9lEu4/hyoEiybU5D+sbYrHRUXwP64LkzctGdE/sC5VBmHw4j8juQT5PCvwP5/AhYYPRvM/MPeHNa5y7D8xuINkQ7/uP+ObXEL0GvQ/H0T4OE9M4D9aktE79OHsPz3yg8oq4u0/7/hAPFxM9D/IFIPyBGPzP+03JP/d3PI/PQOwIh975T8LjG4dGTSqP0m/2NaqSPE/FLI1UwiB8D+wc3itKfXyPxP31MEsGuY/t/L1KYUo7D/Ax+T9TcLsP2o2TaeOyPI/MwDQOD8b6z+oAd5dwozwPz29zl194uk/qsdLcTRL6z9oWqSBBhjsPym7LjaMRu8/Bi7q7pWU8D/tqlFZXsPyP2AmxDtEVPI/A+OFGb8V7z+HCt0+DifxP744yFZdiOc/vPXtZj6+6j+mZf+XxjrzP/BPTlnyxfI/hjHxYO5n8T8ZA0by8LnvP8Jf3cIEn/I/ea4x4BOY7T8NQ5pn25/zP1KThVT20us/VPdtLTiY8z9CbH42UZ/oP1Nwws5eB/I/5HRIIBQq8T+iOfx/5u3vP9URl06xo/E/bDorN4t27D+i20OpWm7hP2PuWkI+KPM/QYLix5ir8z9ZIZuautHxP03fxsEAre4/ENvM1xvr8D88GVbQON3pP+Wz4VV7XfM/bwt9TWJq8T+Ela9wN+3zPzBmS1ZFmPE/S3Ij2eHX7D/MJRO/e+rvP0f/qqd/Xus/W7bWFwlN9T/e4LDZNsHzP1m6J7RRkvI/b0seLr1m6T8De47ABnHkPzLqtTQSfO4/2QWDa+7I4D84Pd6aKlbxPxj8qhqMquw/UkVUVSak6z+g7cE5XfXgP2pA71N2puU/RwIuRF4h4D9PLr5P8pbzPw5/0Q5Nw/A/lciyHsZd4z8jPXdIUg7jP4GaWrbWd/M/6C3DJAFv8j/by1OpG6DuP3xSWG/1IPI/l8dYdW/I4j9e+rBB0yDhPxF0D2SYLvQ/BAHPSTG48j9XGwhuSdPwP8BAMS4sMvM/ijZsANuW8D9GjbbobIroP1syfWWUbfQ/7XlIQmy66D/ZPLPJhurmPxHu3wbGy/M/dUH5kviS5T8gO1bGEsjrPwAuMzLpE/Q/pLEPFVdD6z9f2xXZUpDvP28FuTB3YvQ/dXMz1A8v8T9N+OeasOrnP/6n0ZrVAfM/epqC60Dc4D9ZLTQA6eXlPzZ9E5a63Os/q3MUOacW5D/bY1TfGtTzP/sMJP/++u8/H4nyYObm4T/dEanE0HX0P5RrCmR2JuU/Xqlf0N+H5D+t2CXLxc/vP/sa7sj90/E/4Reo1gxK8z9C+ILcZibNv8TNDI+7YOU/DXx38Z+K5j/n1UoyvCP0P5mz4ysmu94/JbIwwBWL8D/h7qzddqHyP0VAqem/5tU/u+vwAOQe7D+bd96+9b7yP8PAzqhUdPM/BP8AEBzs8j9ZN1rldF/uPw0wf8foB+I/pGBbeagh7D89aE1eKnfrP8R/eGUwSfM/EggJi2kq1z/0FEG1JETxP0YEiCdggPU/zMaUWc7/8z+N2x5zVITzP9N0C5c0WvI/AgXmOvB+6j/E0l1lr5/oPzWKmwk8rvA/8sYXJ5087j8mmvaDcOv0P8OEj5Caues/AahNYjGG2z+bo5b/85jpPykB1k+ksPI/NpZNDAs+8D9GksWijsPvP3L9FvjlN/A/iT28AF6T6z+RZFbvcEv2P+B/bfWDt/A/LR5irATV7j8gQ6YAQX7wPyb1CrA0VfQ/C+GoR+CQ7D8U4lfN74PzP7xY/4QGtOg/lpUFl7fY6j/ZUvZM5fP0P/lEIl0BH+Q/BhzX+ZZN5D8+StuuhvriP+sL11njUuA/N1sOLvw07D/IYKSb7X/mP+FWrKd3neg/NQFtSC8s5T/gZMD+kLPzPyqpNN4tE/I/9fZr28V+7z+0IsVbQkntP5SvusRHmvI/woieEBG56T+D+StkrnzzP7v3qnT7rfE/ko+CTNf48D9nMKHdfL7zP0Uqc5BjxfA/KzyiIWd68z95sOZ8iHjSP6v0yUBUMN0/E4/V9yve8j9zsEhdfLvzP+qrUElCN+I/ZFaUt8gC8z8Zj2TsCpHVPy7Wgb3TzvE/DH/h8N0R8T+M4ajktbXwP4XERQeHi+Y/8AwJzs8j8T/n6Ew1DhD0P6z0JPrGUfM/7y8vfiI47z/N5nEYzM/iPxT8/BjvHuw/RASxppFy8D8jZElOYGHwPzoiXiW/mOk/uldaBM4b8D8AZXwtIlntP+seG3kHtds/gbUou7LO7T9d+10zVHD2P7zljw60Z/E/kYLALcxg6z/9v0WCBJDwP0XODCyRFfM/2evdH+818j/M0BX4zDruPw5DUNrA0vE/As9iztgs8z+PvFqLoinjP987g+koZd8/QVNEwADm7z9Vrqah/FPtP3EPdHr/2+E/Fp+npslx8z90ZEBRNNrxP/0qRLA/U+0/h8d+FkuB6z95LM/m5Q7pPycf1Kg0MOs/c2HmM4fB7j+2jibu4/7gPyIa3UHsDPQ/i0rydXxI8D+P2zcQ9dfwP7IdQksNE/M/HIHTFjJC9D+sVJreD8nuP5JnEzfZDN0/ipeGZVw25T/aW4jdkLnqPxlMLowVsfM/8QWYv2ME7D9IctgBAJXtP9IT4AVblvU/xaXPs/478j9WMPpv/QLZP/sFu2HbsvI/5jVd7EnS7D/i2v3oo8XxP74dlyfG+PE/cWu50OgA6D/BLWnWY8zzP0Dsli4OOOM/HXelwF1B8z9GzkbXGpTyP8q5f/KYDe4/2sRuRJwT8z8wXZBGaGjxP2qCTUKOMvQ/ZM/5hEdm5z9jT9jRevDZPwB2C7DRSto/0csollu68D9ItqlwuhvLPyScmvSMV+0/rDBLdeAg7D/PQxJi0w/xP1qNgGUAQ/E/e7bUYmyY5D8aAAVy5AzyP7fxBhwyG/A/aloY2Bll8T9boBfNTq/rP2/4OC4+YO4/hSFy+nru9D8TFHlxZoTwPyhCsMtsx9M/pnDzfLxG9D9oaPKDqdz0P28ZqkEc1OQ/G2DmO/gJ9T/w7327NnX3PwMwt97jivA/WiH2Uy1D8z81Tti43X/vP/feKS7Yp/I/ZJP8iF/h7D9P18nP/KDoP2OJnPhJuek/3RULjXGP2b+cS7Nxq33vP+p7aHrk2vA/Yafm3x9w2z9i1PcSEQvsP/6DJ3gziOc/LqgU4GBE9j8ldNngK7ftP0LAa+HDhvI/se3+wjwF9T/iZNEq6Xf3P5aJIKNDqfI/BJ9yjjJ58j9yQcdYt3vzP2P2T8P5rPE/2XPCGTaZ7T+Y5B0zkrXUP1f+xujKEfQ/FExn7deJ7T/k+tI2WY7yP1wTHKidS98/KFaZa8kh6z+DkIcZdTjzP0jyhV65JfM/PY0oq/Hb5z86M2a3O7D0PweUTbnC6+Y/ptaYY7sz8T+XrVD/tOzyPxfh3BWw8+k/DoDAHKCY6D9fVzjuOeX0PyD0xw/wX/M/ReniobVz8z8Ba9WuCWn0PzxsIjMX2PY/jzsAPWgx6D8Rto5gmc30Pzsc+noAO/E/UT7zKEuz8z/Ho697hgv0PztJoclRyvA/8vA72Q8Z7z/EqNaIgcrpP/annhbNxPY/Wuj3u3/18T+CFa/LU3rrP/bxKzEqxPA/yTSizdT47z/X98ASOJ/wP4UJo1nZDvU/5TA1lYcF8D8xTjIoiWv0Pw5xB0VOWvE/9gl/CnAP5T9zuFZ72DvzP+US/ZBtf/I/U0LRuEeR4j9pB9geKP3hPw51DlR88u8/dDhG9GOa6D8lWH/4t2vwP2aroqrPNvA/GNpSaqN47T8cQ2Oap6LvPwbSi/sLROw/tSns3JPb7z/jv+VWrRHyP4/lXfWA2fU/Tg2H550xyr/0RhjMgO/hPyAm4UIeYfU/AhLqdc0s7z8Gb0Ayur/lPyByAuwG7u0/emT/fim67z+keTo2hnnlPzYR7K6ihfE/sZvfUd9Z7j+xx2VYnFzzP059QYfQw+s/eEq9XeW/7D/QXK8C3+nxP11HZj+c4fI/q7a0fTyi7D/nUI4b4aH0Px0m2IcO9O4/qGGu+33l8D/npPeNr630P7BXWHA/sPQ/qXV2jfGM8T9SCCYvGVTuP5rIUD7Suuw/JOL3gIr09D9K4x/PkSHxP5cyFYfYpfQ/2r/8X79h9T9+bNysC8ncP2LgFLHjmvM/6ThMbvP66z+UmRyIdm/1P6XghJ29DvU/VNBI3/+C9T+A8+LEV1vzP563sdmRovI/Bxq/Mmc07T9SR+jjsanwP3Mr5/8TG+w/iXssfegK8T+hQCtygC/yP1vFh34SNPI/mC7E6o9w8D+BqGacp2bqP9SDglK0UvU/BxEEI4p07D8XAJmMGaf1P2j0tA3tbeg/aMzqPnxQ5z/Df1/Ijy31Pz9p0dB5TPA/NwiMWDiH6z+Rbjq4Kg/xP+rF9ZRBmvM/+RDYxQJB8D8Y/IkMo6fxPxxxEpTskvQ/Z8Um6OXm9D//kpbCaknIP2cyd4jaUcs/J3xCuPqI8z+TAdo1pYXwP8chj54qcPQ/oR6RpcVv8z8ZcDvZcjPtPyAqjZjZ1/U/LYaChO5D4T+ugKVnOI3sP/yXWqWqX/I/MfY1/Z+09D/bJf3/MIjwP0s5oQiQPvA/JiplY2+D9j9HLYMg9gjzP5qz4ysmG/E/aMQ32pLR4D+/Wr3cijHAP/+COGrgYvU/rOUQaQKS8j8sOd1otvHkPySOp6tc9PA/7WBphY7y8z/UqkzneabwP1GeHoB5DfU/WcbhJ2mp9T/r8MY4NdbyPxkW7TvQRPI/tdvTemTY7z/dgnw7Tx3uP7Ld+yMl6PA/zcQZaOMd9j9A+sMiyJntPwdP18nPrPQ/PX4UGi2s8z+i3GxiN/LwP9rARieFyOs/e8EC8+vi6z9yVwrcFQXvP1oKe+zEy8M/Z55cUyDz9D/tLu0npQjvP8zxZf3BW+E/PRIOQf5P8D+dhfvQHnLtPw//+jJigPQ/U2gPanWI8j868YsByJ/1P/DouWSgA/Y/LkTieQRq8j94Tf7d8dz0P2iZAwzkPO0/TLvB5evx6T+72uW22Ij0P/dTiOwoE+M/8YjIuPtf8T/danPvI8/rP0Q44qDvpOs/GEEhCn/J8T+K48Cr5Z70P2/D3noDQvU/nBJSr0Jn6j9l+QSaGcfgPxd4WdlfuvI/xMBKcLAg8j+V98ztuWf1P9S5/U2DjfU/43bDEf8r8z8f4WpTK1L1P6ATQgddsvI/fentz0UD9T9IiQIiaYz3P66hLxi37PQ/jvdXTd+08D/LDvEPW8ryPzk+/+K+CvU/yJEQ3ZoR0z9RJRRsbdvwP1mAIXGwc+8/v6svXGeN6z/4700VhMnlPwykOAUBm+0/Vak0vR9i8j+f/IKC9yr1PxGbGxUwWO4/KwtPfVo07T/N7E7SV/vyP5fze1FxIvQ/VLjU99AE9D/42pZ1vezzPxy2Lcps2PA/dKycB8E09T/UDZiwy9rzP3+S8d4HRvU/tVeb1thb7z9cfH7WBErmP1pTMJVEx+s/HYx9bg1h9T8TuvAoOqfyP8S6TKg7mu0/LQ9OG0C15D9+0bOToOPkP3AVm8GlRPU/y3soE68J8z+jlO+dwfTwP/1jKatMpeU/1OMpcT6x7j/oN6ftujLvP1sxEpDlI/E/O2lE3cWb8T8trSsLy3TzP2KJYk3Auu0/gblx5rLE8T+5za9ButPzP6PYn/6SiOc/ksjjDkBv8z8DNjFutH3xP4vTOdQptvA/lFb4Cj1Q8z9S4+8o353zP9sgMGLhjPA/Rh9enYR28z82em/r8gbqP+knQSTo1O8/1m9owt0m5T992tk+gdPsP2vl0rZpZec/ACvysdyO5D8WrU5htM3JP3TWn6tKrus/KCHcjdOq6D9p4h3gSWv0PyFlOFyzvvA/v42DATri9j+9S/PY4BbyP76dRIR/wfQ/vnHvbTyw7j/pjUk1ooryP/WN4C0t5uo/HU8VnXbi7D9+3GVcxIHxP3bsFGnqBvE/1DTeDO2i8T/G0agC5qjnPyY5YFeTN/E/rUFOTqOP8z9J7jTCcGjePzYk7rH0afA/tnbLo1Wc7j+rFExG3270P0m0cJuhD+w/vj5KV3YS6z+TEgaOme7oP2Zr2EpDGPM/DQwPUND88T8lHB/SFHb0P1LLWjPHbOo/bLGYAfyNvD/C9lmGtM3xP5ywksmIf+g/CZrg5TM67j9fKNwCdDXvP1eGJ6ptCe0/6DcKGHYr6z8cYpvYbIrkPw+cM6K0R/M/nRoFFCzW8j/MqfCplBXzP3JPHcyix9U/EDL7ApsH8D/8iW/NwtPyP+hGYMUMYeM/A5AkUuT69T/bXOtB9xv3P1CQVLZ6ROg/C5ZuOwIyzz/GnC1Bwj/0P0ZtLHKZhOw/ZYF++FwK9D8Fuv52PCrmP8ZoHVXNYlFA8+LEV7tOUUBgcw6eif9QQO21oPdGp1FA1GLwMG14UUDOhZFeVBJRQGd/oNy2WFFAU84Xe69hUUB/vi1YqkRRQIAlV7H4a1FABgySPq1jUUA+V1uxvyZRQD9UGjGzJlFA32sIjssMUUCd0sH6vzFRQPCD86njc1FAx5v8Fp1wUUCBme/gp2NRQKYKRiV1FlFAZ12j5UAoUUDMtWgB2jlRQHHEWnwKMlFA2VVI+clOUUDyfXGpyvlQQH0iT5Ku+VBAbQN3oM4rUUCNKy6OyktRQGDFqdZC11BA3nTLDvHTUECDfxE05t9QQL3g05w8HVFAqpZ0lAPqUEC3CIz1DThRQIZxN4jWAlFA4fJYM7IyUUCSA3Y1eQRRQNL+B1irEVFA4qjcRC0EUUAzEqER7ORQQDeGAOBYMFFAg7uzdtsSUUCaBG9II+ZQQNz0Zz9SHVFAMEj6tIroUEBKBoAqbgpRQINMMnIWyVBAWRXhJiPqUECsVib8UkNRQIpXWdsUHFFAHTf8bjrzUECj4ZS5+SNRQEc17PdE8FBAGVbxRub5UECq0asBSgJRQCBdbFqpxlBAp6/na5buUEAlNh/XBgtRQCQgJuFC/VBA0eXN4Vo4UUAtXcE2YthQQLGnHf4a+VBAayi1F1EOUUCLaDum7uRQQFDB4QWRo1BAQZlGkwvaUEAB8iVUcLVQQJGXNbFAy1BAzmqBPaYFUUBCXaRQlslQQIKPwYrTF1FAv5zZrlCxUEAmcOtunqlQQIBo5sm1IFFASpaTUHrQUEBfP8QGi+dQQDWzlgLSelBA+geRDDnFUEDGbworlf9QQATnjCht8FBA6A5iZwqsUEBk48EWu+dQQDBdiNUfblBAEFX4MzyiUEAnmZzaGbtQQOqT3GETz1BA30237BDBUEBWC+wxkWtQQNmu0AdLtFBAVl9dFSj+UECL+E7M+pZQQHUAxF29g1BAogkUsYjYUEAKfbCMDY5QQNUaSu1FlVBAoN0hxQANUUDQjbCoCJ5QQG3BUl1Ar1BAycaDLfbCUEDiyAORxZtQQFk33h2ZxlBAwCFUqVnBUEDnxB7aR6FQQJm1FJB2XFBAUfLqHIN1UEAyqgzjbtJQQJJWfEPhtVBAiLX4FAB2UEBN845T9ERQQI3KTdRSz1BA2xMktrtQUEBAu0OKAW1QQLwEpz4QhFBA9fOmIpWJUECDMo0mF49QQBd9BWnGclBAfjUHCGZFUEBqgT0mUilQQFz8bU8QU1BAyVLr/UZHUEDkLVc/trtQQF5iLNOvZ1BAmNh8XJsxUEC29Giqp0dQQNzsD5TbdlBAxQCJJtBYUEDKFd7lIslQQJKTiVuF11BAycFsAgxTUEBFgxQ8BUhQQCKOdXEbRVBAfJQRF4A9UEDuHTUmxChQQANhp1i1W1BA4Sh5dQ6HUEBHcvkP6TVQQDRCP1MvbFBACkJ5H0c/UEDbFI+L6rNQQEmAmlo2VlBAHDo978YNUEBXCRaHM1VQQBNjmX6JjlBAIbHdPcCEUECZSGk2j3BQQI1WtaSjFFBAhZLJqR0jUEAN3lflQllQQNQ/iGTIBlBAn+QOm0hfUEAclZuopS9QQKVJKej2J1BAswQZAZUpUEBP5EnStT9QQNO7eD9uU1BAtfrqqsAZUECeQUP/BDRQQNCTMqkhB1BAnzaq0wE/UEBZ+WUwxk1QQCs0EMtmLlBA/aAuUigGUEANp8zNNx5QQGLyBpj5I1BA6GZ/oNxVUECdtdsutChQQKmc9pQcEFBAh7mkarsWUEAjvhOz3hVQQH6MuWuJa1BA2AbuQJ34T0A7AyMvaz5QQMXa39keU1BAz2bV52oYUECZK4Nqg/BPQFDicyfYDFBAQCswZPUdUEA9PiE7byBQQJnwS/28309A929enPgWUECfyJOkayJQQBbVIqKYb09A96+sNCmeT0ALcayL2+NPQPgLPWL05k9AxI7GoX7nT0D5ZTBGJAFQQDG1pQ7yHVBApA7yejCWT0CYmZmZmaRPQNtrQe+NGVBAZiWt+IbaT0BDHVa45QpQQP50AwXewk9AA8+9h0v5T0DxY8xdS+ZPQOV0WUxsD1BAHpkOnZ5VT0CN0M/U6yhQQOsqpPyknk9ADipxHeOZT0DjZOJWQShPQO7/44QJ809AAWxAhLjjT0BgOq3boPhPQNcS8kHPjU9A0LTEymjwT0B+IatbPelOQHpKzok9xU9A4zWv6qzMT0BUlBKCVfZOQMoO8Q9bwU9Afa8hOK4WUECHKvwZ3oRPQHCJIw9E8E5AMk3YfjKyT0C7XS9NkQNQQCvwFd16Q09ADf0TXCwJUEBMofMauzNPQGp9kdCWA09A0OXN4VqXT0AUIXU7+2pPQIxJfy+FoU9AeHO4VnvITkBpMuNtpWJPQIEKR5BKAlBAa0qyDkeUT0AinYGRlxRPQFj0TgXcL09AEOULWkiKT0DBGJEotLNPQHO5wVCHyE9ADz6UaMl2T0AzDvW7sENPQNFxNbIr4k9AJOXuc3x3T0D0RNeFH0pPQJFX5xiQFU9AmPijqDOkT0AxC+2cZpRPQLeTiPAvLU9Acgrys5EsT0BFkbWGUkRPQHmthO6SEU9AN9TvwtakTkAp/BnerJlOQG+df7vsK09AUX3nFyWqTkA2FhQGZehOQFT3yOaqDk9AwrMEGQHeTkDEjsahfiZPQH+AtWrX1k5AM/W6RWBXT0AMkdPX8/1OQO8PW3o0D05AtfXTf9YgT0AnZyjueLdOQD0fZcQF1E5AVIMwt3uZTkBm22lrRI9OQEjx8QnZe05AcU9XdyzcTkA1/G66ZWdOQEkDP6phVU5AXRd+cD4dT0DnaFVLOmtPQNlRnKOOfE5Amx2pvvPeTkAo5bUSuqpOQNlOWyOCWU5Aa9CX3v6gTkBVC+wxkUdOQDK9xFimgU5AA2oxeJi4TkBZRBSTN2hOQMwqbAa4ek5Ae662Yn87TkB2mWGjrCxOQIXHfhZL0U5AL6LtmLrJTkAEMdC1LwpOQFYgelImV05Ak2OyuP+hTkCSrwRSYr5OQLXEymjknU5Ap7pHNlf0TUDA5EaRteJNQGCKcmn8+01ASICaWrbJTUDExryOOCFOQL2FdePdH05AgwmjWdn9TUBcwqG3eJ9OQHX6QV2kQE5A0BqDTggWTkBZXyS05cdNQPTDCOHRuk5AI9BgU+fzTUA4lnfVA+VNQLpGy4EeX05A/mSMD7PDTkDzN6EQAYxOQG6cFOY9dU5ALei9MQR5TkCjhjYAG91NQHoTQ3IybU5A6scm+REhTkBREDy+vdBNQC8Rb51/WU5AGHEBaJQDTkCCTZ1HxRZOQGe0VUlkMk5Aey5Tk+DnTUDqtkQuOJFNQK2RJAhXO01AHa1qSUfPTUBj3T8WorBNQPXLJyuGY05AwPuqXKjCTUCEcw0zNPhNQA2fdCLBbk1A/46oUN3bTUD8wcBz76hNQHJnJhjOi01A3OhjPiCGTUCaoiO5/HFNQBNZayi1q01AlOttMxXtTUCqCaLuA8BNQPB9calKlU1AjsAffv6lTUCq7pHNVX5NQIt8XvHU7UxA+xNcrKhiTUCabtkh/u9MQGTkLOxp2U1ATh4Wak3QTUDHYwYq46JNQJR31QPmN01A5vwUx4EpTUAo+64I/rlMQK+H9rGCy0xAe+asTzmtTEC2lslwPDRNQHyNJEG4R01AWxsqxvkDTUDRZpyGqL5MQCcLX1/rQk1AIkvmWN56TUAXITzaOERNQDiYTYBhXU1Aj87AyMvvTECXbDzYYoJNQOL2yycrKk1A0cd8QKB5TUD2VblQ+SJNQOnkDMUdxUxA2YMQkC/0TECjwthCkKFNQOK7lLpkRE1AQw98DFZgTUBkUdhF0TZNQNVvJqYLiE1AnFJeK6FhTUCGTWTmAvJMQP0nf/eOIE1Ant6Mmq8PTUBM9PkoI0pNQLWCpiVWj0xA1avI6IAoTUCDYcCSq7RMQB97vfvjH01AMMueBDbaTEAaSYJwBTBNQAP8GkmCl01AjAWFQZmoTEBuI2WLpMJMQG9a8KKv3ExAD2CRXz9QTUBobRrba9VMQKYVpu81IkxAkQn4NZJUTUDz/dR46S9NQNwGtd/askxARjtu+N2jTEADM6ZgjbNMQPAIbqRsy0xAkK6ZfLPwS0AH/yJozL9MQP0kPneC60xA9hxYjpBTTEAO8KSFy8FMQCFkIM8uIExAgCBAho5xTECyJ4HNOblMQKHsLeV88kxA/rEQHQK9TECa+dUcIEhMQMEpc/ONXExA6gCIu3qdTEC/w7Rv7ttLQNDQP8HFm0xAzLp/LESWTUD+BBcraqZMQHGkMzDyIUxAlo45z9inTECmdLD+z0pMQIszhjlBEE1A9lPjpZt1TEDdawiOyzxMQHj83qY/rEtA1I7iHHVKTEBKOsrBbHdMQOZyg6EOr0xA34eDhCivTECale1D3qVMQC8PmfIhVExAlA9B1eg6TECWnUXvVIxLQOx/gLVqikxAcggcCTTkS0DdlsgFZ85MQDvGFRdHlExABPhu88auTEAA9Pv+zSlMQJ8zaVN1UkxASKEsfH19TEDY5sb0hB9MQFYDlIYaqEtAamCrBIsRTEBnU3WPbMhLQBfQC3cuhExAO0UOETcjTEDahlEQPAJMQGNpp+Zyf0tA9H8O8+UsTEDFFoIclCJMQC2i7Zi6lUtANzP60XBSTEAxBADHnuhLQHjHKTqSzktAobCLogeWS0CfwabOo4xLQD9SRIZV10tAtIKmJVbkS0A5OxkcJb9LQO7lPjkK/0tAbXL4pBOYTEBP/u4dNZJLQDF1V3bBA0xA0UohkEtCS0Cd6/twkMdKQM1xbhPu5ktAJFEv+DTJS0BVoYFYNjZMQAfRWtHmQExAJJNTO8MeTEBzle6us3dLQNjKS/4nq0tAQdgpVg0sTEA6xhUXR35MQAzABkSI/UpAeI8zTdhnS0Cp7/yiBJVLQH9h+fNtfktAEoB/SpV8S0B0VgvsMaBLQNJJtrqclEtAoLlOIy0eS0BRuYlamqBLQC2kw0MY30pApx/URQrGS0Alol9bPwZLQFmkiXeAHUxAmxw+6USHS0DMKmwGuOZLQMtbdR2qK0tAjEephCegS0BAFqJD4K1LQFW7JqQ1v0tAmqvmOSIVS0A3jILg8ZxLQPhkxXB14UpAudQI/UxDS0DBFOXS+C9LQF4Lem8MX0tAOaxwy0c8S0DQWPs72zpLQEiAmlq2JktAF62jqglgSkBtyaoIN65LQPoD5bZ9PktAjh8qjZhoS0BKeEKvP19LQOjOE8/ZL0tADiibcoXcS0BnlgSoqW5LQMVwdQDErEtAaWXCL/WkSkB6/N6mP0xLQFATfT7KukpAurVMhuMgS0BSk+ANaepKQJy2RgTj/0pA4NHGEWuXS0CID+z4L3hLQCPP9X04lEpA5qc4Dry+SkAtxysQPfxKQGq4yD1dr0pAfhKfO8H1SkBOrb66KvJKQJeiXBq/tUpArCzRWWZqSkAseNFXkJRKQKDZdW9F/EpAMuNtpdciS0BIZ2DkZblKQEh+xK9Y1UpAfqKyYU0kS0DoI/CHnxdKQAsBwLFnZkpA8fEJ2XnRSkD3qL9eYcZKQKWU10rokEpATIHMzqI7SkCzPuWYLHBKQOV4BaInakpACKaaWUsdSkChYweVuAFLQDy2ZcBZBEtAO7t868OvSkCkbmdfeQNLQBAKStHKXEtAVBfwMsOCSkCkQ6fn3etJQEHxY8xdu0pAB5Pi4xN7SkDbEU4LXhNLQF+uRQvQSkpAgTgPJzCbSkBFzsKedlVKQEE6PITxH0pA0ocuqG+eSkBrGttrQa5JQDtO0ZFcOUpAFaHYCppPSkC6nX3lQZdKQDXPEfkuZ0pALAjlfRx4SkAtB3qobcNKQJhokIKnmUpABJ57D5ejSUDvGYnQCFJKQG+TUWUY10lAvSoXKv+9SUBtjJ3wEm1KQGQWodgKJUpA8dO4N78bSkCJr3YU58FKQBn8/WK2U0pAWdk+5C3fSkCJB5RNua5KQC1A22rWtEpANlfNc0RMSkCZeXJNgTVKQOxjBb8NqkpAZ7J/ngbaSUC+1qVG6AlKQMMmMnOBTUpAjjF3LSHMSUBN0vwxrbxKQDwmUprNv0lAUFPL1vofSkBOkUPEzbNJQMw4DVGFmElAmh4UlKLQSUDToGgewElKQKQUdHtJ4UlA76mc9pT2SUB9WG/UCrZJQDnP2JdspkpA/yYUIuCoSkAAxjNo6PJJQGabG9MTAEpAUDI5tTMySkBK6gQ0EUdKQCHmkqrtQUpAWMUbmUfLSUDJhcq/liFJQLt4P26/n0lAt7dbkgNmSkDuyi4YXKxJQDkdyHpqUElAXYO+9PaFSUCryOiAJJdJQHJp/MIr4UlA4STNH9MXSkDiLy3qkwdKQIWRXtTum0lAE4PAyqEDSkDjiSDOww9KQI46Oq5GSUpAZI16iEZXSUB/gosVNRlKQEDbatYZG0pAs67RcqAFSUA0g/jAjhFKQGfLuRRXKklA2hX6YBlVSUDL2TujratJQFwR/G8lFklAABdky/JBSUDewrrx7uJIQPJzQ1N210lAmZoEb0haSUC+SdOgaINJQJJWfEPhIklAeekmMQjXSUCC5nPudrxJQKYpApzexUlAga0SLA5ISUB9PPTdrVlKQMPvplt2yklAWfymsFKYSUBaYfpeQ9pJQKhSswdafUlAVSsTfqlPSUBEozuInbZJQGoy422lO0lA09fzNcuaSUDGpL+Xwk1JQEkofSHkbklAglDex9EySUBKtOTxtINJQHr7c9GQMklAkL5J06CSSUBPHauUnrlIQK/HREqzsklAOgFNhA0cSUB8WG/UCgZJQJrMeFvpG0lAtCRATS0vSUAq+64I/pxJQGn67IDrSElAJoqQup1nSUAff2lRnxlJQCS05VyKRUlAvVMB9zxNSUC8OseA7DBJQLOXbaetSElAarqe6LowSUAD54wo7TpJQG94QURqtkhAYD/EBgvOSECa6V4n9UlJQLNby2Q4n0hAoKUr2EbYSEBhFW9kHpFIQDfknxnEUUlAqBd8mpM+SUBS8X9HVN5IQInt7gG6/EhAN02fHXDkSEDMCdrk8CFJQKrnpPeNAElA1nCRe7rUSEC12sNeKEBJQGg/UkSG0EhAPzGyZI4RSUCiztxDwgdJQFzknq7u7khAqTXNO07gSEAP0egOYoJIQLt0kxgE9UdA7KaU10pvSECazk4GR/NIQI6u0t11L0hAdocUAySKSEB7uU+OAidIQJgW9UnufkhA7nVSX5Y/SEDSTWIQWMNIQHcwYp8AhkhABRA+lGiYSEAkKH6MuaxIQBRypZ4F90dAJHLBGfySSEDcKoiBrnZIQGX7kLdcaUhAmnrdIjBHSEBm8PeL2T9IQBSZucDlWUhAg57Nqs+XSED7iF+xhjFIQP1LUplipkhAUnb6QV14SEA/L9y5MI9HQFfGhm72qUdA4lZBDHTwR0D3AUht4m1IQHIycasghEhAhAmjWdk2SEA2/dmPFH1IQHUF24gnPkhA8kOlETMySEDfoSjQJ8hHQIC0/wHW8UdAEHUfgNQtSEDICKhwBD9IQMa8jjhkIUhAkKM5svLAR0D0pbc/FxpIQGppboWw8EdAT1H1K51RSEAeFf93RExIQJYcd0oHKEhAVyb8Uj/FR0A72GK3z+ZHQLp9VpkpsUdA6lc6H54iSEC2CmKga3VHQM6LE1/tNEhA9BH4w8+SR0ClZaTeU2FHQONJ0jWTLEhAVSjS/Zz6R0C1+BQA46lHQO6QYoBE+UdAc2A5QgbXR0BzXfjB+bxHQAsgfCjROkdAS633G+3ZR0AFuvYF9NVHQKj91k6UokdAjcwjfzDjR0DNpiOAm+RHQJfGL7yS00dA2t/ZHr28R0DPRxlxAXJHQJv/Vx05oEdAezApPj6jR0DBvwgaM8JHQGVSQxuAi0dAuFSlLa6mR0DcuMX83KZHQKjg8IKI00dAumQcI9nNR0AOQkC+hIpHQFDbhlEQj0dAGxAhrpxQR0B3gZICC5NHQLFMv0S8ikdAfD7KiAtWR0A+jubIymtHQGTll8EYe0dAjnHFxVGWR0AQjln2JHhHQM+52/XSKkdAXrNcNjo0R0D7er5muTlHQCTNH9PaIEdAFwtD5PQqR0AWuaerO2FHQOV/8nfvOkdAFyr/Wl4uR0Bwd9ZuuwxHQHGL+bmhS0dAyQVn8Pd5R0Bsk4rG2hxHQLCqXn6nGEdAgTl6/N4aR0AwXYjVH5pGQApAo3Tp60ZA4zPZP09bR0DzNctlo4FGQOF9VS5UHkdAsKpefqffRkBF7unqjtpGQDF2wktwFkdA57tbWaLuRkAKQ+T09cxGQPy+f/PiyUZAiohi8gZBR0A0yvrNxKBGQHIR34lZ2UZAuOulKQL5RkByEkpfCOlGQJj8T/7u3EZAVRNE3Qd1RkD/qE2c3NlGQHhdv2A3rEZAIef9f5zGRkAVoG0164xGQOTWpNsSlEZAjGg7pu7/RkCZPjvgupZGQIpYxLDDykZAL/KyJhapRkBHHLKBdKlGQDvj++JSbkZAYUhOJm4SRkCxaDo7GYZGQMLX17rUf0ZATPT5KCNwRkBy1TxH5IRGQMx38BMHqEZAM4gP7PiSRkBAECBDxwFGQIS4cvbOmkZANxPThViORkDHgsKgTDZGQHL6er5mVUZAvtpRnKN8RkBjJeZZSVZGQOY4twn3PUZA62exFMkkRkDw9bUuNTxGQDpzDwnfR0ZAKY2Y2edYRkA0f0xr0zlGQDUebLHbRkZAneqQm+FRRkD5JeKt8/dFQE8dq5SeN0ZAdmUXDK4tRkDs7ZbkgOtFQCxJnuv7M0ZAKa+V0F0MRkDsouiBjyFGQDYbKzHPDkZAGHPXEvJMRkCWVG03wQxGQHx716Av8UVACrPQzmn9RUAtPZrqyfdFQNdfdk8ewkVASzYebLEIRkAzvi8uVQBGQOEd4EkLxUVAVncstkndRUAcU3dlF7hFQPGBHf8FyEVADRR4J5/fRUBUouwt5bBFQC1cVmEzukVAe/MbJhqbRUCU0F0SZ7ZFQIkhOZm41EVARYDTu3gXRkAwQ+OJILxFQA4MIHwof0VAnGSryymhRUCjIeNRKtZFQIPXLm04y0VA70xoklihRUBWC+wxkahFQC0EOShhsEVAiOqtga2cRUCEPIIbKYtFQOwljdE6UEVA2+16aYpQRUBbQj7o2V5FQOv17o/3kEVAvHDnwkiSRUDm6PF7m2JFQMgljjwQOkVAFHtoHyuHRUA42nHD73NFQIMPJVryWkVA9x+ZDp1MRUA6qwX2mENFQObpXFFKGEVAFabvNQQ2RUDvxRft8RJFQFhOQukLVUVAq1RQUfUfRUDdBUoKLD1FQMA8ZMqHRUVAxtl0BHAiRUDjSGdg5B9FQAC9cOfCMkVAx5qRQe7iREDKEMe6uN5EQMfWM4RjP0VAqKROQBMLRUCASL99Hc9EQDR8C+vG8URAeJPfopPPREA+c9anHBhFQD0FwHgGIkVAKk1KQbf+RECKiGLyBq5EQBWel4qNA0VAA+YhUz67RECBme/gJ9pEQNBdEmdFukRAzcKedvjKREAOSwM/qvJEQHE1sistt0RAWj6Skh7LREBOyw9c5chEQIUfnE8d0kRARLde04OPREDlIVM+BJNEQN2Rsdr8lURAzcEzoUnRREAWYYpyaalEQLHAV3TrkkRAfZHQlnPcREAPO1PovG9EQLOs+8dCg0RAg72JITl5REAYbVUS2U1EQKBuoMA7x0RAw5PdzOhXREBPjgJEwdlEQGpEMA4uMERAhCUeUDaMREDl54am7IlEQKFns+pzqkRA2uOFdHg+RED92CQ/4p5EQDFXBtUGI0RAOuY8Y198RECx+E1hpW5EQI4AbhYvokRAE5M3wMxcREB4Xio25rlEQFwT0hqDF0RAjyv1LAgJRECrOqsF9jlEQJFy9zk+GkRAhAoOL4gtREDmilJCsA9EQI/cmnRbQURAa0JaY9AvREA9CAH5EkJEQD85ChAF/kNA4SNiSiTdQ0ATWWsotfBDQPXSFAFOJkRAviMqVDfVQ0ADqn8QyftDQLVoAdpWAkRAgtxFmKIDREAK9fQR+DxEQCd8tg4Or0NA1qaxvRbZQ0AxBWucTRdEQKfIIeLm9UNAEgznGmbmQ0AzRBX+DKhDQGKBr+jWi0NA00fgDz/PQ0Bd1O5XAeVDQFj9EYYB3UNAgCvZsRGdQ0DLg/QUOQ5EQMMj8fJ0sUNA9zdorz7GQ0BGJAot6xtEQBXcD3hgqUNAdVQ1QdTSQ0AkkX2QZX9DQOuJrgs/qUNA6Tu/KEG6Q0BU/N8RFQNEQF+owwq3XENAmxw+6URyQ0BD/MOWHopDQBCpaRfTXkNA81McB15xQ0AaRGtFm4pDQHSWWYRie0NA6EXtfhVwQ0CpDrkZblRDQObFia92fkNAHyV2bW9SQ0BkrDb/r4pDQEP67evAR0NAxoDs9e5sQ0Ai+N9KdqpDQII2OXzSW0NAvB5Mio88Q0DXoZqSrCdDQOxFtB1T7UJA19MOf039QkD1+pP43D9DQLbPKjOl+kJAp1DdXPwaQ0Dt7CsP0kZDQISWdf9Y/kJArs4xIHsgQ0Cjc36K4yBDQN6Hg4QoH0NASghW1csRQ0DWprG9FkxDQOR/8nfv70JAL9Y3MLneQkCRYKqZtRFDQMmCiT+KzUJAL0ROX8+0QkCu0AfL2MtCQBZi9UcY3kJAQXbexma2QkBu8fCeA5xCQPswQni0n0JAjjo6rka1QkBIZYo5CJtCQMqHoGr0v0JAnjvB/uvoQkBWCKuxhHJCQDIvh913rkJA7QbRWtGqQkC85H/yd5NCQMIv9fOm6EJAPvuRIjKnQkC12sNeKKxCQDo6rkZ2kEJATJzc71CaQkDog2Vs6MpCQAXYR6euWUJA4KC9+niUQkDYnINnQs5CQHwgeedQg0JAlGOyuP9vQkAwmL9C5ndCQAw9YvTcj0JA/ZjWprF3QkAsQrEVNHxCQAyreCPzhkJA9LwbCwqoQkCc+kDyzmhCQF5cqtIW/kFAWTDxR1E9QkAJoYMu4Q1CQBvr4jYaSUJAMZV+wtl8QkBx5IHIImZCQMJlFTYDPUJAEFt6NNUMQkD5ff/mxUJCQKEjufyHZ0JATji7tUwwQkAxjpHsERNCQJhIaTaPMEJAm4cTmE4bQkCw/zo3bSRCQHYrS3SWtkFAY64Mqg0WQkCvxW6fVRVCQHAC02nd6kFAehNDcjLYQUB9U1ipoONBQCJL5ljeBkJA6bXZWIlsQkC53ct9cgpCQA66hENvYUJA5lJcVfbbQUDCL/XzpsNBQCNE+YIW7UFAUZs4ud/HQUDcByC1ieVBQJhKP+HsakJARm+4j9z2QUALzXUaac5BQIheRrHcqkFAFWniHeDGQUDct1onLrBBQPg2/dmP50FAQGMmUS9/QUBuaMpOP41BQKC9+njoxkFAVGXfFcGBQUAW7IZti2JBQAfovpzZf0FAGcQHdvzwQUBg4o+izuZBQCGMn8a9VEFAwylz840eQkBsQIS4crJBQPttT5DYNEFAzQLtDilOQUC1SxsOS0ZBQEpYG2MnKEFAreyCwTU9QUDAOo4fKitBQFDgnXx6hkFAzEOmfAg+QUCNc5twrzdBQACEDyVaakFAWMSww5grQUDOLt/6sDBBQLqyCwbXFEFApZvEILA9QUDUsrW+SAlBQLqyCwbXY0FAh78ma9RTQUB9cD51rP5AQDDw3Hu4IEFA8x38xAEUQUBnzCTqBexAQD/7kSIyHEFAgAncupscQUBy1xLyQf1AQH8MHTuo20BAaCWt+IaSQUDsfhXgu/NAQOuJrgs/vEBA1lBqL6LMQED2KFyPwh1BQNQhN8MN2EBAERH+RdDeQEBwk1FlGC9BQF897lutq0BAsl4M5UTbQEDYsRGI151AQBLx1vm3pUBAu3STGASpQEAZTwRxHsRAQPQVpBmLpEBAGB77WSzVQED6IqEt541AQITP1sHBrkBAtaFinL+JQEC214LeGy5BQAYpeAq5y0BAgXNGlPaUQEDYW8r5YpZAQP0pVaLsk0BAcRk3NdBfQEBARdWvdF9AQFZe8j/5UUBAK2aEtwdgQEB6bMuAs75AQDy4O2u3cUBAMxDLZg6yQED6JHfYRGpAQAMdrWpJXEBAhyr8Gd5WQEDuAiUFFqBAQFnTvOMUYkBAxcA6jh9jQEDYfjLGhz1AQM3F3/YEQkBAc83km21NQEAgPUUOETFAQCi37XvUy0BA0M5pFmhfQECL22gAbw5AQJKMnIU9N0BA7na9NEUsQED5KY4DrxdAQAW8zLBRjEBARm5Nui37P0AkyXN9HwRAQJ1b6EoEB0BAw7MEGQEOQEDIef8fJ6NAQC9NEeD0G0BAAaH18GVVQECY1NAGYBNAQCvOGOYE2T9ABglRvqCuQEB3vp8aL2BAQKnmOSLfgT9A7xge+1m6P0B0Fr1TAak/QIixTL9EzD9AO8CTFi63P0BVZHRAErY/QEKXcOgtT0BAL9RhhVuEP0BM8iN+xWw/QGH4iJgSjT9A+AyoN6NCP0Co2QOtwKg/QLg4KjdR6T9AZgqd19hFP0DMOuP74mQ/QF1HHLKBTj9A/KIE/YWoP0AYrDjVWmQ/QMkRMpBnYT9AsLtASYE1P0AfZFkw8U0/QFSH3Aw37j9AG82RlV8YP0A2MLlRZPc+QGYpWU5C0T5A8SGoGr3UPkDSsyCU96E+QHynyYy3mz5AOSNKe4O3PkDnvpzZruo+QEzzjlN04j5AnSrfMxKdP0Be0a3X9IQ+QEHJ5NTOuj5AwrmGGRqHP0CePgJ/+Mc+QIjUtItpkD5ANxd/2xNyP0BEFf4Mb2I/QLnwg/OpKz5AhhVu+UhQPkAFxCRcyDs+QKXydoTTdj5A8jgM5q+0PkDkBG1y+CQ+QJFVEW4ycj5Ag584gH6HPkDSnpJzYhU+QPP256IhFz5Ay0I7p1nyPUB1btqM00w+QDZNnx1wFT5A570xBAATPkBBCTNt/yQ+QGa2K/TB7D1Atnh4z4HnPUCvwi0fSfM+QG1L5IIz0D1ActU8R+TvPUC8NEWA0589QGcqxCPxkD5Aq3gj88jfPUC6s3bbhaA9QEc7bvjdmD5AGBu62R+ePUCaHam+87c9QM0bJ4V5BT5AKi/5n/xDPUB5NxYUBn09QPFEEOfhkD1AlV6bjZW2PUBqD3uhgBs9QAFmvoOfzj1AdU6zQLtNPUD7xWzJqkg9QPC5E+y/eD1A17lpM05lPUA7w9SWOm49QFklWBzOAD1AUnQkl/8mPUAStTS3QhQ9QB5ssdtnYT1A6uOh724TPUCvAny3eQ89QC/3yVGAyD1AwSgIHt+GPEBWJvxSP/08QP0KmSuDAD1A+Q/pt6/1PEAkOWBXk6M8QF95kJ4inTxAm1PJAFCtPEAcG4F4XXE8QOfaF9ALnzxAqbpHNleHPED8xWzJqkI9QFfIXBlUmTxAkgN2NXnEPEDBTUaVYXI8QKNzforjcDxARLx1/u2oPEDU1ohgHG48QIlVgzC3WzxAVUyln3B6PEBgyVUsfpk8QAorFVRUdzxAtHHEWnw0PEDm4JnQJC08QJMUWABTJjxAVyJQ/YNKPEDBPc+fNqg8QJpcjIF1qjxAD2CRXz8EPEAH5ujxex88QFeTp6ymPTxAGrluSnmlO0Aj8fJ0rjA8QLKZQ1IL6TtAdeYeEr4HPEDjqrLvihI8QJVZhGIrMjxADFpIwOjqO0BdSfJc33k7QJoJhnMNeTtA0oiZfR5dO0CwkSQIV9o7QHWLwFjfdjtAa5If8StwO0BpUgq6vcI7QG7ajNMQdztA1k6UhEQ0O0CkqDP3kFw7QAL0+/7NdTtA91ROe0rKO0AurBvvjlQ7QBzqd2FrZDtAXMgjuJFeO0CuJHmu72s7QGFKJNHLKjtA6H+5Fi34OkC2upwSEEM7QBT7y+7JwzpAWYKMgAo5O0CV9DC0OmM7QHHLR1LS9TpA39keveEGO0DykZT0MN46QCAFTyFXLDtA/xfPoKG1OkCtwmaACxo7QE5cjlcglDpAnBn9aDgfO0DXhopx/lo6QPG8VGzMiTpAGOYEbXK4OkAC7nn+tIU6QNptF5rrQDpAeVioNc2LOkBaK9oc54o6QFzDDI0nLjpAjzNN2H5cOkB+UYL+Qkk6QMmRzsDIrzpAbti2KLNPOkAjtrsH6K45QK2ek943GDpAN92yQ/wjOkBaZDvfTxk6QFmg3SHFVjpArgyqDU5KOkBZ+zvbo2M6QBBy3v/HzzlAB5EMObbsOUAlW11OCeg5QHFzKhkAHDpArI2xE17AOUD9vRQeNNM5QPcF9MKdyTlAtkjajT6eOUDmkT8YeHA5QJ+rrdhfhDlAq5FdaRnVOUBv8fCeAxc6QLBwkuaPtTlAh6jCn+FtOUDZ6Qd1kX45QAfNrnsrgjlA///////9OECale1D3lQ5QIjyBS0khDlAA1slWBzIOEClYfiImKw5QLoRFhVx7jhAmzqPiv9BOUDXwFYJFmM5QBQ/xty1EDlAWRR2UfRIOUBf0hito/44QCPusfSh4zhA+WabG9PROEAFS3UBLzE5QHgj88gf3DhAR6ta0lHCOEDOwMjLmtQ4QGHj+nd9JjlAt1z92CRjOEB3+GuyRpc4QET2QZYFlThAChUcXhC/OEBUjV4NUKI4QHTN5JttwDhAX2BWKNKzOECp3a8CfI84QMuZ7Qp9cDhAcYqO5PKJOECrs1pgj2c4QCrCTUaVUThAiQeUTblkOED7OnDOiJ44QAc9m1WfizhAgbBTrBpiOECtLxLaclw4QK2FWWjnHjhAJ9U+HY87OEDcKLLWUBo4QMKFPIIbJzhAizBFuTQ0OECk+PiE7NI3QOk+AKlN2jdAyhmKO97WN0DkEdxI2cw3QKz7x0J03DdArDdqhenhN0B/n3HhQIo3QKWBH9Ww9TdAjT9R2bB2N0BS1m8mppE3QMExy54EbjdAF9aNd0eON0AI4GbxYoM3QJfiqrLvnjdA9+P2yydNN0DLlUG1wXM3QHHIBtLFdDdAS65i8ZtkN0Ca0Y+GU0Y3QGL3HcNjeTdAIxEawcZ3N0Bnt5bJcD43QDGtTWN7OTdAW0OpvYg+N0AmN4qsNaQ3QGA+WTFcBTdA1b6AXrh3N0BESx5PywE3QII2OXzS6zZATGvT2F7rN0ApAwe0dBE3QHhEhermDjdAfjhIiPK7NkAUdeYeEsQ2QEFg5dAiyTZAqSuf5XnaNkDKVMGopKQ2QMu6fyxE3zZAp8r3jESINkCYDMfzGZQ2QGqBPSZSnjZApmJjXkeWNkD/4EOJloY2QGjKTj+oSTZAU+V7RiIqNkAXCAJk6DQ2QKP2ItqOLzZAXeDyWDNKNkAHeqhtwzQ2QOAO1CmPLjZAEarU7IGmNUC0dXCwN/c1QHTsoBLXIzZAtKhPcodnNUD7PbFOlfE1QEPnNXaJGDZACr5p+uzwNUBPHEC/79k1QGU2yCQj2TVAww5j0t/rNUDlY3eBkpw1QEku/yH9mjVAeZCeIod2NUDqVzofnpU1QJjCg2bXtzVA8GlOXmR4NUA/hSNIpZQ1QHYXKCmwejVAjnIwmwBJNUBokIKnkJU1QMHDtG/ucTVAWDUIc7tRNUCUwyedSDA1QJ+VtOIbTDVAGo7nM6ByNUBsrwW9NyQ1QDNmEvWCDzVA/mSMD7MZNUDvqDEh5vI0QLcjnBa89DRAgV8jSRBCNUAjgnFw6QI1QA4om3KF0zRAz2VqErzfNEDHn6hsWNM0QD0FwHgGwTRADtO+ub/ENECXTus2qLE0QIzuIHamiDRADfs9sU6bNEBZ9E4F3HM0QPsApDZxeDRAeXb51odzNEAtsp3vp2o0QLX2PlWFoDRAHcNjP4uVNECE2QQYljk0QFp+4CpPRjRAaJWZ0voxNEBmLnB5rFM0QKvmOSLfKTRAeVp+4CoRNEAKYqBrXzA0QOTVOQZkHTRA0K+tn/47NEAV3A94YCY0QM3+QLlt6zNAwCK/fojzM0DvbI/ecNszQOHTnLzIsDNAKXPzjeh0NEAlr84xINczQKta0lEOBjNAsS0DzlKEM0BKtOTxtLAzQPrsgOuKnzNAEApK0cqlM0BU4jrGFX0zQAIK9fQRYjNAWikEcolNM0BCX3r7c2czQEi9p3LadzNARTfCoiJqM0AXCW05l0AzQGcQH9jxPTNAIM7DCUyfM0AW9UnusB8zQOT4odKIXTNAj8Ng/goTM0ApU8xB0HUyQKbtX1lpRjNAwMk2cAf4MkCpDONuEIMyQIwRiULLjDJAqiUd5WDAMkAEOL2L930yQKt5jsh3wzJA2m6Cb5rKMkAALzNslPUyQLSrkPKTsDJAf6KyYU3ZMkCEKjV7oH8yQPPkmgKZhTJA68A5I0qbMkCwOQfPhJoyQLcE4J9SdzJA0qQUdHtZMkBQEaeTbJ0yQDbK+s3EjjJAKuJ0kq14MkBaYmU08h8yQH/XZ876pjJAofZbO1EcMkDecYqO5BYyQAHcLF4sQDJAuREWFXGGMUAGggAZOuQxQBKI1/ULPDJAGeJYF7ftMUBLb38uGh4yQJBJRs7CfDFAHOxNDMkVMkCBrKdWX60xQGgRUUzexjFArDHohNDzMUB1OLpKd70xQGovou2YkDFAnP2BctvMMUAqVaLsLXMxQKp8z0iETjFAMZqV7UOIMUAGD9O+uWsxQII4DycwPzFAJvp8lBHFMUAdHOxNDFcxQOqURzfClDFACfZf56ZPMUDWMhmO5zExQIeGxahrATFAiPTb14GXMUCQa0PFONcwQPWeymlPHTFAO78oQX/VMEAl6gWf5gYxQILeG0MACDFAMzLIXYSxMEB+F7ZmK5kwQAgaM4l6izBAQ7+2fvo5MUCStvEnKoswQPhnBvGBoTBAgwzk2eWHMED2KcdkcbkwQJTZIJOMbDBApC+EnPeFMECCyY0ia7UwQGe3lslw5jBAyxDHurjDMEC7x5kmbLEwQFdZ2xSPPTBAI57sZkabMEDvoxr2e/gwQKCgFK3cFTBASdQLPs0LMEAiMUEN3wowQNOh0/NuyC9ACyqqfqVdMEAAV7JjIxIwQCb/k797OTBAiE1k5gIFMECZmC7E6o0wQMCxZ89lWi9A479AECA/L0BesBu2LQgwQOKt82+XuS5A2GMipdkkL0AhIjXtYtYvQBxxyAbSBS9A9KYiFcbqL0BlE2BY/mQvQKWVQiCXsC5ACAH5EipsL0A5XRYTmxcvQEkvaverPC9ArZ0oCYlkLkDzZWmn5iovQBCSBUzgSi9AvruVJToTLkBdXRWoxawvQPBG5pE/xC9AY2g8EcS1LkDTMHxETJktQO1hLxSw9S1AA6xVuybYLkALkgVM4HIuQC2xMhr5kC5AhNBBl3DMLUBPzlDc8couQORKPQtCrS1As+OG300fLUC71Aj9THUtQJcUH5+QES5AgF1NnrKOLUD44SAhym8tQAOTG0XW8i1A4gLQKF3yLUDG2XQEcKssQDMV4pF4xS1AJ0TAIVSNLEAI46dxbyouQLxQwHYwmixA47z/jxOuLECkETP7PD4sQEeMnlvoGixAw47GoX67KkBXHTnSGcgrQIAJ3LqbfyxAPxh47j0MLEA5mE2AYTUsQD2T/fM0MCxA7dKGw9LQLEA1OXzSiTQrQAKm07oNHixAdeCcEaUFLkBO7QxTW6IrQMdhMH+FUCtAwvf+Bu1VLECIZTOHpLIrQBn6J7hYfSpANjrnpzgKK0BAmxw+6RAqQPrxlxb1lStAvDlcqz3YK0A43bJD/JMqQAFGlzeHeypAUiy3tBraKkBZzqW4qvwpQIizImqiNypA0Mq9wKxEK0CAJOzbSTgqQAbuQJ3yCCpArgrUYvAEKkAoKbAAplAqQF8ktOVcyilAFhBaD1/uKUCspBXfUIQqQBhUG5yItitAwrZFmQ3eKUBFveDTnAQqQN8tkKD4DSlAVBUaiGWnKUCkiXeAJ7EpQNqlDYelkSlALGACt+7yKEBUO4pz1K0pQLhGy4EeCitAdnCwNzFoKUDDXFK13agpQA1QGmoU6ihAI4Wy8PXxKEAYjuczoFIoQIp1qnzPbClAR/31CgtiKEBhTtAmhzcoQKDyr+WVsyhAw5Wzd0YjKEBXBWoxeMgnQFiR0QFJqChAtUyG4/nIKEALBWwHIx4oQMpMaf0tPShAXrUy4ZfKJ0DyKQDGMwwoQNMq+kMzWydAaAOwARE2KEC8Azxp4TIoQGBH41C/LyhAG3+ismEBKEAxQni0cYgnQIZUUbzKtidADL3Fw3tKJkB3RluVRK4mQD2WPnRBUShA3W3eOCnQJ0Bw58JIL5InQNnpB3WRKihAfHpsy4DvJ0DttDUiGPMmQEP/BBcrIihAyd3n+GgRJkAOJO8cyuglQFGIgEOobihA4sluZvRbJkDw2xDjNR8nQHB5rBkZkCVAU7XdBN+MJUClZaTeU4EmQINnQpPE0iVAj2tDxTgnJUBpqFFIMtMmQKPhlLn5oiVAAG+BBMWvJUD17o/3qhEmQBnh7UEICCZAsU0qGmvDJUAQj8TL08EmQPvqqkAtMiVAptB5jV2yJEAYVBuciKolQAGFevoIsCRA/9E3aRp8JEC2fCQlPXwkQAcddAmHPiVAfLd546SYJUCvsOB+wIMkQAMCnUmbRiRAZdgo6zc/JEBZ7PZZZZ4kQOVBeooc7iRAoh6i0R2sJEBGkEqxo1UkQJoAaDl1zCNAXXjKDwGOI0DHGuTkNNIjQCdNg6J5aCRAWlt4XiqyJUDXOoJlttEjQFzmdFlMeiNABgsnaf6MJEDeo6PBEh4jQJwDXyxn6CJAI8BEFy/9I0D3rkFfekclQLO8YZEVMCNAqQ65GW6AJEDnHiPqT1AjQGHTSiGQ/SNAbW3heakQJUD55qMx/zsiQDVygtt/kyNASgLU1LIxJEDDUahdAkAjQF4XNOMjGCJA+eL320OtIkA5KSc1D7UiQL85bdeV0iFA+qQkNf50IkAmFY21vxEiQAq0ll2LZSJAdw5lqIprIkA+zX/+MZ8jQAwwPasW1CFAT9MdekG6IUA8S0aENaQhQI64W+28fiFAZnOLryxNIUA/kLxzKOEhQO6/33nzRyJAHwoLk06DI0A+eEiM+QoiQMNylTg87iBADMRX4NBKIECS1imgmuAhQEWWcfhJeCBAwNZbuc3QIUD3BInt7k0hQJg20gjsiCFAnjr7b8rzIEDmjw60pxUgQKCZzB2iHiBA2p1aIrxmIUCyXUZWI3ggQIsc2OAzcCBAc6pro/D1IECvpZHgV3IeQG4NbJVg3SFAMNRhhVu6IUA5Drxa7oYgQI8/YgUJ7SBAqiaIug8cHkBb2ImBZJwfQA6xZgnXZB5AYmcKnddyIECRNUXbjEofQER3WshtWR9A8hSD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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]}},\"selected\":{\"id\":\"2631\"},\"selection_policy\":{\"id\":\"2630\"}},\"id\":\"2514\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncabl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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2000]},\"y\":{\"__ndarray__\":\"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bokeh.layouts.gridplot([\n", " bebi103.viz.predictive_regression(\n", " samples_greensheilds.prior_predictive['q_greensheilds'],\n", " samples_x=k,\n", " percentiles=[30, 60, 90, 99],\n", " x_axis_label='density',\n", " y_axis_label='flow rate',\n", " title='greensheilds'\n", " ),\n", " bebi103.viz.predictive_regression(\n", " samples_underwood.prior_predictive['q_underwood'],\n", " samples_x=k,\n", " percentiles=[30, 60, 90, 99],\n", " x_axis_label='density',\n", " y_axis_label='flow rate',\n", " title='underwood'\n", " ),\n", " bebi103.viz.predictive_regression(\n", " samples_pipesmunjal.prior_predictive['q_pipesmunjal'],\n", " samples_x=k,\n", " percentiles=[30, 60, 90, 99],\n", " x_axis_label='density',\n", " y_axis_label='flow rate',\n", " title='pipesmunjal'\n", " ),\n", " bebi103.viz.predictive_regression(\n", " samples_twophase.prior_predictive['q_twophase'],\n", " samples_x=k,\n", " percentiles=[30, 60, 90, 99],\n", " x_axis_label='density',\n", " y_axis_label='flow rate',\n", " title='twophase'\n", " )\n", " ], ncols = 2\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These plots look pretty good! There are some cases where the flow rate goes negative, particularly at low values. This indicates it would probably be a good idea to model $\\sigma$ about our mathematical distribution differently (maybe as a function of the density?) but we will continue with an assumption of homoscedasticity for now. The nice thing about building models from scratch like this is that we can add additional layers of complexity if we are not happy with model performance. We are ready for sampling! Using the building blocks that we coded for the prior predictive, we can code up our model in Stan, prepare a dictionary with the data, and draw samples. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "k = df_thin['D'].values\n", "q = df_thin['F'].values\n", "\n", "#k = df_mean['D'].values\n", "#q = df_mean['F'].values\n", "\n", "N_ppc = 200\n", "k_ppc = np.linspace(0, k.max(), N_ppc)\n", "data = {\n", " \"N\": len(k),\n", " \"k\": k,\n", " \"q\": q,\n", " \"N_ppc\": N_ppc,\n", " \"k_ppc\": k_ppc,\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This format of the data will work to feed into all our models. The real work now is to code these up in Stan! I will just include one example of the Stan code here, as the only difference between the models is to call a different function for the mathematical model (all functions are here). For the Pipes-Munjal model, you would have to uncomment the lines declaring the parameter $\\alpha$ and it's prior. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```stan\n", "functions {\n", " real greensheilds(real k_i, real k_j, real v_f) {\n", " real q = k_i*v_f*(1- (k_i/k_j) );\n", " return q;\n", " }\n", " \n", " real underwood(real k_i, real k_j, real v_f) {\n", " real q = k_i*v_f*2.7182818285^(-k_i/k_j);\n", " return q;\n", " }\n", " \n", " real twophase(real k_i, real k_j, real v_f) {\n", " if (k_i <= k_j) {\n", " return k_i*v_f;\n", " } else {\n", " return k_j*v_f;\n", " }\n", " }\n", " \n", " real pipesmunjal(real k_i, real k_j, real v_f, real alpha) {\n", " real q = k_i*v_f*(1- (k_i/k_j)^alpha);\n", " return q;\n", " }\n", "}\n", "\n", "data {\n", " int N;\n", " int N_ppc;\n", " real k[N];\n", " real q[N];\n", " real k_ppc[N_ppc];\n", " \n", "}\n", "\n", "parameters {\n", " real k_j;\n", " real v_f;\n", " real sigma;\n", " //real alpha;\n", "}\n", "\n", "transformed parameters {\n", " real mu[N];\n", "\n", " for (i in 1:N) {\n", " mu[i] = greensheilds(k[i], k_j, v_f);\n", " }\n", "}\n", "\n", "model {\n", " k_j ~ normal(50.0, 10.0);\n", " v_f ~ gamma(3.0, 2.0);\n", " sigma ~ normal(0.0, 1.0);\n", " //alpha ~ gamma(3.0, 2.0);\n", "\n", " q ~ normal(mu, sigma);\n", "}\n", "\n", "\n", "generated quantities {\n", " real q_ppc[N_ppc];\n", "\n", "for (i in 1:N_ppc) {\n", " real mu_ppc = greensheilds(k_ppc[i], k_j, v_f);\n", " q_ppc[i] = normal_rng(mu_ppc, sigma);\n", " }\n", "}\n", "\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's sample!" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:cmdstanpy:compiling stan file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_model_greensheilds.stan to exe file /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_model_greensheilds\n", "INFO:cmdstanpy:compiled model executable: /Users/bois/Dropbox/git/bebi103_course/2022/b/content/recitations/05/ant_traffic_model_greensheilds\n", "INFO:cmdstanpy:CmdStan start procesing\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d7efc95f4bfc4685b1f4c03543c7c702", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 1 | | 00:00 Status" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "7bc9d8baa4da4849b43a5a633749d9b8", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 2 | | 00:00 Status" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ac61ea4bb17e482bbbc08ecf61f80e27", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 3 | | 00:00 Status" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "fdb6c3cb50c24f84b13206e3635b8f45", "version_major": 2, "version_minor": 0 }, "text/plain": [ "chain 4 | | 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": [ "sm = cmdstanpy.CmdStanModel(stan_file=\"ant_traffic_model_greensheilds.stan\")\n", "\n", "samples = sm.sample(data=data, iter_sampling=1000, chains=4)\n", "\n", "samples = az.from_cmdstanpy(posterior=samples, posterior_predictive=[\"q_ppc\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this model, we can now visualize the posterior with a corner plot!" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"sigma\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]}},\"selected\":{\"id\":\"3471\"},\"selection_policy\":{\"id\":\"3470\"}},\"id\":\"3203\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"3241\",\"type\":\"Line\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"3229\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"3481\",\"type\":\"BasicTickFormatter\"}],\"root_ids\":[\"3535\"]},\"title\":\"Bokeh 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bebi103.viz.corner(\n", " samples, parameters=[\"k_j\", \"v_f\", \"sigma\"], xtick_label_orientation=np.pi / 4\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "No divergences, so that's good. Before I comment on the results, let's take a look at the posterior predictive check data. We will display the plot as a PNG since there are so many data points to avoid choking the browser." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "q_ppc = samples.posterior_predictive['q_ppc'].stack(\n", " {\"sample\": (\"chain\", \"draw\")}\n", ").transpose(\"sample\", \"q_ppc_dim_0\")\n", "\n", "p = bebi103.viz.predictive_regression(\n", " q_ppc,\n", " samples_x=k_ppc,\n", " percentiles=[30, 50, 70, 99],\n", " data=np.vstack((k, q)).transpose(),\n", " x_axis_label='ant density, k [ant/cm²]',\n", " y_axis_label='ant flow, q [ant/cm/s]',\n", " x_range=[0, k.max()],\n", ")\n", "\n", "bokeh.io.export_png(p, filename=\"ppc_1.png\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![First posterior predictive check](ppc_1.png)\n", "\n", "To be on the safe side, we should also take a look at the parallel coordinate plot. " ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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bebi103.viz.parcoord(\n", " samples,\n", " transformation=\"minmax\",\n", " parameters=[\"k_j\", \"v_f\", \"sigma\"],\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looks good! Nothing looks out of the ordinary here. Now for some commentary on this model. Here, we are looking at the Greensheilds model. For one, it seems like a very simplistic model for this data: an uside down U shape (parabola). The data doesn't really capture the downward part of the function, and doesn't very convincingly enter the parabola peak regime either. This leads to a shape the is slightly curved, but mostly linear in the region with lots of data. Since almost all the data points fall in the regime of low-medium density, the full dataset pushes the model to prioritize fit in that regime. As a generative model this seems like a pretty pathological failure. Also, note that the parameter estimate is exceedingly high indeed for $k_f$. This variable represents the peak of the parabola, where increased density begins to lead to a traffic jam, and hence reduced flow overall. Thinking about the number given here, around 95 ants per square centimeter, this is evidently problematic. The ants used in this study are large enough that They would probably have to start stacking on top of each other to reach density, which would certainly change the paradigm. The largest densities seen experimentally were ~18 ants per square centimeter. Take a look at what these high ant densities looked like on the bridge: [here](https://doi.org/10.7554/eLife.48945.013). Based on the video, a 4-5 times increase in the number of ants seems improbable. Also note that this puts the parameter estimate at ≈5 standard deviations away from the prior mean that we set. Even with 10,000 data points, this will influence the parameter, maybe dramatically. Looking at the curve fits from the paper, they place the $k_j$ value for this parameter at ~$200$. This is an order of magnitude higher than any measured density! This is a case where the choice of prior actually hugely influenced the inference. In this case, it is largely because the model fairly catastrophically fails to explain the data. Thinking about the parameter estimates, though, in the case of this model (as bad as it is) the prior effecting the outcome strikes me as a philosophically good thing in this case: we know that the jamming density of the ants can't be extremely high simply given physical constraints of how many can pack into a given area. Also, video from above would be difficult to use to parse a situation where the ant density was also given by ants stacked on top of each other. If this model is an accurate representation of the generative process for the data, the data we have does not provide enough information to resolve this parameter. \n", "\n", "We will now take a look at what happens if we fit the averaged data with the same model. 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OUBI4XoUrpc6QPkx5q4lxDlAwOyePCx0OkAIPZtVnxs6QGfV52orNjlAmpmZmZnJOUDZzvdT41U5QCQofoy5azlAkst/SL8dOUC2hHzQs9k4QEoMAiuH9jhA1XjpJjEYOUCqglFJnaA6QMe6uI0G8DlAtFn1udpKOUCLbOf7qaE4QDY8vVKWgThASFD8GHN3OECIY13cRjM5QNqs+lxtNTlA4zYawFvgOEAwKqkT0NQ4QBNhw9MrpTlAVHQkl/9wOkCBBMWPMVc6QB1aZDvfXzpAdLUV+8tOOUDl0CLb+d45QJAxdy0hzzlA9+RhodYUOUBv8IXJVGE4QFMFo5I6oTlAarx0kxgkOkAEVg4tss05QBueXinL8DlAL90kBoF1OUBNFYxK6oQ5QC0hH/RshjlABoGVQ4s8OUB88rBQa1o5QCS5/If0+zhAVHQkl/8AOkAlBoGVQ9s5QE7RkVz+MzlAzhlR2htcOUAZBFYOLVI5QJp3nKIjOTpAZmZmZmbWOUAPC7Wmedc5QP7UeOkmkTlAQYLix5irOUAhsHJokb05QMpUwaikfjpA/tR46SYxOUCu2F92T245QD55WKg1DTpAB84ZUdoLOkD1SlmGOFY6QKabxCCwwjlAY3/ZPXlIOUDUK2UZ4pg5QBKDwMqhpTlAp3nHKTriOEDtDb4wmeo4QAfwFkhQXDlAM8SxLm4DOUAAAAAAAEA5QOXyH9JvvzlAGeJYF7fROUBn1edqK2Y5QAkbnl4pqzlAAAAAAAAwOkBoke18P+U5QGlv8IXJRDlAGsBbIEGROUB0tRX7y545QB1aZDvf7zdAFD/G3LUUOUDswDkjSos4QLIubqMBnDhALGUZ4lj3OECoxks3iTE6QEdy+Q/ppzlAhxbZzvdDOUC6SQwCKyc5QKH4MeauFTlAkst/SL/9OEA2zTtO0QE5QMsQx7q4nThAJlMFo5KqOEA7AU2EDa84QEhQ/BhzNzlAGlHaG3zBOEBCPujZrKo5QBx8YTJVUDpAKxiV1AkYOkDKMsSxLi45QMxdS8gHDTlAAiuHFtk+OUAMAiuHFjk6QDMzMzMzkzpAaJHtfD+FOUDwhclUwcg5QMKGp1fKMjlAxyk6ksufOUA5tMh2vj85QIhjXdxGQzpAJQaBlUPrOUAYJlMFozI6QKAaL90k5jlAz/dT46XLOUBj7lpCPsg4QIJzRpT2JjlAT0ATYcPzOEDHuriNBmA5QPtcbcX+8jlAZMxdS8hnOUD7XG3F/sI5QLwFEhQ/ljlAg8DKoUX2OUD67evAOQM6QN0kBoGV0zlAeAskKH4cO0Bb07zjFM06QBBYObTItjlAJQaBlUNLOUDWVuwvu6c6QAKaCBueLjlA8KfGSzcZOUADeAskKE45QIEmwoanlzlA6pWyDHFcOUB3LSEf9Kw5QIj029eBMzlAp+hILv8xOUB6pSxDHFs5QE7RkVz+8zlA1sVtNIBnOUCOdXEbDZA5QPJBz2bVVzlAzTtO0ZFMOUAJ+aBns1o5QIj029eBQzlApSxDHOuCOED/snvysMA4QDvfT42XHjlAbjSAt0CSOEC6awn5oOc4QF3+Q/rtazlAj+TyH9J/OUCBlUOLbPc4QATnjCjt/ThAf2q8dJNoOUA3iUFg5XA5QMnlP6TffjlA2qz6XG0lOEDarPpcbSU4QFr1udqKXThAmbuWkA9aOEBYqDXNO244QMrDQq1prjhAdQKaCBvOOEAAkX77OuA5QOLplbIM4ThAHhZqTfMeOUAYJlMFo7I4QP8h/fZ1cDlAnzws1JrGOUDuWkI+6Mk4QJZDi2znezhAhetRuB6VN0DDZKpgVII5QKd5xyk6kjlAImx4eqXsOUBkXdxGA3g5QBb7y+7JIzlAx0s3iUGgOUBUUiegiVA5QOcdp+hI/jlA07zjFB0JOkDjx5i7lsA4QIZa07zjNDlAWMoyxLFeOUALtaZ5x4k5QOviNhrAGzlAirDh6ZXiOECgGi/dJDY5QB/0bFZ93jhAJzEIrBzKOUAW+8vuybM5QAWjkjoBjTlAhjjWxW2kOkCcoiO5/Bc6QCDSb18HrjlAEFg5tMiGOUASFD/G3KU5QGx4eqUswzlAKcsQx7r4OED3deCcESU6QA6+MJkqCDlAbqMBvAXiOUCOBvAWSOA5QI/k8h/SfzlAJ8KGp1d6OUCBBMWPMTc5QKg1zTtOMTlA/mX35GEROkBMN4lBYMU5QF66SQwCizlAiIVa07zDOEDsUbgehTs5QC6QoPgxhjlAxm00gLcAOUAp7Q2+MIk4QEi/fR041zhAvAUSFD8GOUBYyjLEsf45QL6fGi/d5DhAoyO5/IckOkC1N/jCZDo5QBdIUPwYAzpAGw3gLZDAOkAhsHJokZ06QIEExY8x1zlAEoPAyqHVOUAnMQisHIo5QJ0Rpb3B5zlAZ9Xnaiv2OECyLm6jATw5QM4ZUdob3DhAokW28/2UOECze/KwUMs4QPW52or9lThAOwFNhA2vOkD5oGez6sM5QMoyxLEu/jlAWMoyxLG+OUBSuB6F69E4QGB2Tx4WqjhAtMh2vp+6OEBgdk8eFto4QN5xio7kUjhAEoPAyqE1OECZu5aQD2o4QH3Qs1n12TlAHcnlP6TPOUA9LNSa5g05QPp+arx0IzlAWRe30QDOOEAbDeAtkGA4QE0VjErqhDpAvAUSFD/2OUAp7Q2+MCk5QLx0kxgEBjlAPL1SliEeOUDnjCjtDc45QJMYBFYOPTlAwcqhRbbjOEAydy0hH9Q4QO7rwDkjWjlAb4EExY8ROkDUmuYdp+g5QBb7y+7JYzpA001iEFg5OkClTkATYUM6QOF6FK5H4TlA0ETY8PRKOkC5jQbwFlg6QCNKe4MvXDlA07zjFB2pOUAIrBxaZHs5QCSX/5B+izlAUI2XbhIjOkCsi9toAD86QLU3+MJk6jlAi2zn+6kxOEBVMCqpE9A4QAu1pnnHqTlAsi5uowF8OEDl8h/Sb884QJhuEoPACjlAS8gHPZulOUDJdr6fGi86QHDOiNLeoDhAorQ3+MIUOUCL/WX35BE5QOOlm8QgADpAz2bV52qLOUBE+u3rwGk5QPcGX5hMRTlAnzws1JqWOUCTOgFNhP04QC1DHOviVjpAseHplbJsOUA5tMh2vt85QPLSTWIQuDhADeAtkKA4OUDeAgmKHxM5QH3Qs1n1aTlAJCh+jLmLOkBfB84ZUQo5QM4ZUdob7DhAj+TyH9LfOUAHX5hMFRw6QI4G8BZIEDpArK3YX3bvOEAFo5I6Ae05QKd5xyk6UjpATKYKRiVFOkCgGi/dJNY4QNk9eVio5TlAih9j7lpyOUDvycNCrWk5QDAqqRPQJDlA7Z48LNSaOUDOGVHaGyw5QDC7Jw8LpTlAdQKaCBt+OUAMk6mCURk5QBzr4jYacDlAWKg1zTtOOUBDrWnecUo5QGgibHh6NTlAejarPlc7OUDZX3ZPHmY5QI2XbhKDUDhA6Ugu/yHtOEBn1edqKxY5QNXnaiv29zhACRueXik7OUD5oGez6iM5QF66SQwCOzlAvJaQD3pmOUBaZDvfT/04QDeJQWDlUDpAnzws1JrGOUAWak3zjvM5QFkXt9EADjpAQ61p3nHaOUAhH/RsVv05QGN/2T15qDlAZmZmZmbGOUD1udqK/QU6QOm3rwPnHDhAL90kBoGlOUCfq63YX6Y5QMGopE5AUzlAOUVHcvlPOkArhxbZzhc6QEvqBDQRxjhA9dvXgXN2OUAyVTAqqcM5QMSxLm6j8ThA9wZfmEyFOkCBBMWPMbc5QABvgQTF7zlAh6dXyjI0OUCoV8oyxHE5QJHtfD81DjlA0ZFc/kPKOEDmriXkg844QNlfdk8eZjhAUkmdgCZyOEAy5q4l5CM5QOJYF7fRYDhAtRX7y+6ZOECDL0ymCrY4QJf/kH77OjpADAIrhxa5OEAIrBxaZMs4QMiYu5aQnzhAZapgVFKXOkDZX3ZPHhY6QMe6uI0GoDlAGJXUCWgCOkDiWBe30SA5QOCcEaW9ATlAw/UoXI+SOUC8dJMYBGY5QE5iEFg55DpAEFg5tMjGOkBFR3L5D4k5QOf7qfHSrTlAHhZqTfP+OUAg0m9fB644QL4wmSoYtThAutqK/WWHOEA0gLdAgrI6QM/3U+OlSzlA1QloImzYOkAawFsgQdE4QIzbaABvQTlAwTkjSnvDOEAukKD4MXY4QOPHmLuW4DlAmggbnl65OkD0bFZ9rqY6QGUZ4lgXBztAUwWjkjrxOkAu/yH99hU6QMSxLm6jMTlAB/AWSFA8OECwcmiR7fw3QEku/yH9VjhAbef7qfHyOUAIPZtVn6s6QOC+DpwzcjpA1zTvOEVHOkAE54wo7W06QI/k8h/SrzpA78nDQq2pOUDXNO84RYc5QClcj8L1uDlAY+5aQj64OUAeFmpN8+44QMPTK2UZ4jlAJQaBlUO7OEBKe4MvTGY5QO0NvjCZejlA2ht8YTJVOUAHzhlR2ms5QPXb14FzZjlAz/dT46XrOEDwhclUwQg5QLTIdr6f6jhAt2J/2T2ZOECNKO0NvnA6QOm3rwPnrDpAp+hILv/hOkCwA+eMKB06QG3n+6nxIjpAXI/C9SicOkBwzojS3rA6QMzuycNCDTlA9dvXgXNGOUArGJXUCdg4QE+vlGWI0zhA/yH99nWgOUAQejarPtc6QPkx5q4lZDpAYOXQItt5OkCVZYhjXXw5QINRSZ2AxjlA+8vuycNSOUDn+6nx0n05QFr1udqKrTlAb4EExY9hOkBz1xLyQX86QMsQx7q4fThAhetRuB71OUD3Bl+YTFU5QK5H4XoUfjlA3nGKjuSyOUD+ZffkYQE5QP5l9+Rh4ThAFNBE2PDUOUAFo5I6Af05QF3cRgN4izhAgZVDi2zXN0Bd3EYDePs3QMzuycNCLThAP1dbsb98OUAOLbKd7+c4QKabxCCwAjlAdnEbDeD9OEAg0m9fB844QPOOU3QkNzlA6+I2GsALOUCIhVrTvNM4QGEyVTAqyThAL26jAbz1OUCmCkYldfI5QILix5i7BjpA0LNZ9blqOkBX7C+7J085QPp+arx04zlAxY8xdy3BOUBiEFg5tJg5QDeJQWDlEDpA/Yf029cBOUBiEFg5tOg7QDGZKhiV9DhAzqrP1VasOUBDHOviNlo5QNBE2PD0WjlAcM6I0t5gOUDSb18Hzkk5QIEmwoantzlAQYLix5h7OUD5D+m3r4M5QF66SQwC+zhA2ht8YTIFOUCMuWsJ+aA5QNSa5h2nyDlA2V92Tx4mOUC30QDeAnk5QKAaL90kxjlAOPjCZKogOkAj2/l+aow6QOxRuB6FqzlApHA9CtfDOkBaZDvfT506QFUwKqkTMDlAwcqhRbazOUAAb4EExZ86QH4dOGdECTpAE/JBz2bVOUBfKcsQx+o5QNk9eVioFTpAhjjWxW30OkBt5/up8dI5QLPqc7UVKzlATmIQWDl0OEDfT42XbrI5QBgmUwWjwjlAsHJoke2sOUDSb18Hzik6QBB6Nqs+lzpA2qz6XG1lOkDaG3xhMiU5QGN/2T15qDlAu7iNBvCmOUAGgZVDiyw6QC1DHOviNjlAXdxGA3gbOUDQRNjw9Fo5QAisHFpkSzlAqaROQBMxO0DZzvdT4xU7QCfChqdXWjpAr5RliGO9OEBUdCSX/+A4QMKGp1fKojlAtvP91HgJOUAnwoanV1o5QCh+jLlr2TlAYhBYObRoOUCutmJ/2U05QOM2GsBbwDlATx4Wak3DOUCGONbFbeQ5QPrt68A5YzpAFR3J5T8kOkA2zTtO0dE6QHUCmggbvjpAQKTfvg5MOkBEi2zn+yk5QEOtad5xSjlAMlUwKqkzOUAhH/RsVj05QKMjufyHxDhAdCSX/5DeOEA2PL1SlmE5QPCFyVTBiDlAUkmdgCYSOUDnHafoSI44QHL5D+m3nzhAtTf4wmQ6OEBB8WPMXYs4QJYhjnVxmzhAEoPAyqG1OUB7FK5H4Qo5QG1Wfa62MjlAJLn8h/Q7OUANcayL2xg5QCQofoy52zlAf9k9eVh4OUB4CyQofpw5QIEExY8xdzlA2T15WKjFOEDT3uALk0k5QGDl0CLbiThAdy0hH/QcOUAcfGEyVeA4QEMc6+I2yjhAu7iNBvCGOEARNjy9UoY4QOf7qfHSHTpA1JrmHafIOUADCYofY845QARWDi2yHTpAfPKwUGvaOUB0tRX7y845QCL99nXg7DlADr4wmSo4OkBVwaikTvA5QAskKH6MOTlA+u3rwDnTOUCoxks3ifE5QEw3iUFgxTlAkxgEVg5NOkCUh4Va01w5QPXb14FzZjlAQxzr4jYqOUCad5yiIxk6QMRCrWneITpAHThnRGnPOUBnRGlv8LU5QJF++zpwHjlAnzws1JrWOUCGONbFbdQ5QNobfGEypTlAsVBrmnfMOUBiEFg5tGg5QL1SliGOZTlA0LNZ9blqOUCKH2PuWuI5QAYSFD/G7DlAlkOLbOfLOUCOBvAWSNA5QBfZzvdTQzlAMQisHFrUOEBdbcX+sts4QFvTvOMU3ThA3pOHhVrzOUBjf9k9ecg5QA4tsp3vdzlAKqkT0EQYOkA1XrpJDII5QMRCrWnewTlA6Gor9pdNOUCBlUOLbNc5QOPHmLuW4DlAH4XrUbjOOUDBqKROQDM6QCntDb4wqTlAvHSTGATGOUAaUdobfOE5QAfwFkhQvDlAIv32deBMOUCh+DHmroU5QLPqc7UVCzlAN4lBYOXQOUA5tMh2vu84QKTfvg6cwzhAb4EExY9BOUDUmuYdp5g5QHe+nxovrThA4lgXt9EAOkDy0k1iEDg5QNv5fmq8lDlAxf6ye/KAOUDpt68D54w5QJHtfD81jjlAEqW9wRcmOUCDwMqhRRY5QAfwFkhQzDhA1sVtNIAXOkC/fR04Z9Q5QL7BFyZTBTpAObTIdr6fOEAU0ETY8CQ6QMUgsHJoUTpAklz+Q/rtOEDChqdXyvI4QMKGp1fK8jhAGw3gLZDwOUA6I0p7g+84QHbgnBGlzThAWmQ7308NOUA/V1uxvzw4QIhjXdxG0zhAhslUwahUOUAkKH6MuSs5QIXrUbgedTlATmIQWDnUOUDqBDQRNiw5QO84RUdyCTpAcoqO5PI/OkClvcEXJpM6QMpUwaikXjlACyQofozZOUBEi2zn+6k5QAfOGVHaOzlA+n5qvHRTOUCDL0ymCpY5QKhXyjLEQTlAj1N0JJevOEDZzvdT4yU5QBx8YTJVcDhA1XjpJjEIOUB9rrZif/k4QH2utmJ/+ThAXwfOGVGqOUAU0ETY8EQ5QDBMpgpG9ThAnKIjufz3OED2l92Th6U4QH4dOGdEiTlAFmpN844zOUCwA+eMKO04QKvP1VbsjzhA+MJkqmDkOEAK16NwPeo4QK36XG3FTjlA24r9ZfcUOUAijnVxGy05QBe30QDe8jhARUdy+Q9pOUC28/3UeBk5QGfV52or5jlA+1xtxf5yOUBlGeJYF2c5QLsnDwu1BjpAXI/C9ShcOUCoNc07TkE5QDMzMzMzszhA4umVsgzROEAOLbKd76c4QE3zjlN0pDhAvVKWIY5FOkA/NV66SQw5QFTjpZvE8DhAsi5uowHMOECR7Xw/NX44QGx4eqUsYzlAUrgeheuROUC+nxov3YQ4QPd14JwRtThA7C+7Jw+bOEC1FfvL7nk4QF3+Q/rtWzlABhIUP8acOUBj7lpCPqg6QEhQ/BhzlzpA07zjFB2ZOEDTvOMUHZk4QCntDb4wiThAXdxGA3ibOEDNO07Rkew4QNV46SYxyDhAIbByaJHNOEBHA3gLJHg6QJEPejarzjpAzH9Iv32NOUAFxY8xd704QLRZ9bnaKjlANxrAWyBxOUAMk6mCUak5QDtwzojSnjhAOpLLf0h/OEB24JwRpY05QBKDwMqhdTlA/7J78rAQOUBfB84ZUTo4QIzbaABv8ThA2/l+arwUOUCz6nO1Fes5QF+YTBWMCjpAKA8LtaY5OkDCFyZTBeM5QP8h/fZ1wDhAGeJYF7eROEDwFkhQ/Dg5QARWDi2yrThAHhZqTfP+OUA1XrpJDBI6QJLLf0i/3TlAL26jAbyFOUCamZmZmTk5QOPHmLuW4DlAorQ3+MLkOEAep+hILt84QNBE2PD0ijlA3pOHhVpDOUDLEMe6uH06QI4G8BZI0DpAtvP91HgpOkCASL99HWg6QDarPldbcTpAMEymCkaVOUDY8PRKWbY5QIY41sVtBDpAJXUCmgirOUAZc9cS8vE5QD0s1JrmvTlAhJ7Nqs9lOUB88rBQa7o4QGpN845TBDlAV1uxv+wOOUB1kxgEVt44QLyWkA96ljlAEhQ/xtxVOUCWQ4ts57s5QNGRXP5DqjlAFK5H4XqUOUBL6gQ0EXY5QJhuEoPAujhAvjCZKhjVOEBVwaikTgA5QEGC4seY+zhAF7fRAN7SOUAibHh6pdw6QMx/SL993TlAZRniWBdXOUBCz2bV5/o4QKjGSzeJkTlADXGsi9voOEDoaiv2lw05QPcGX5hMJTlACyQofoyJOUBz1xLyQe85QKabxCCwQjlAxm00gLfgOEDByqFFtlM4QDBMpgpGZThAlWWIY12cOUBUUiegiaA5QLn8h/TbtzlAUiegibBROUC/DpwzogQ5QMx/SL99jThAtvP91HhZOEAUrkfhelQ6QIiFWtO8wzlADJOpglF5OUD2l92ThwU5QH3Qs1n1KTlAM8SxLm4zOUDChqdXysI4QCcxCKwcCjpAPujZrPpsOkD+1HjpJvE4QNuK/WX3VDlAsb/snjw8OUD3deCcEYU5QMZtNIC3oDlAsp3vp8aLOUDufD81Xuo5QPjCZKpgtDlA9+RhodZ0OUAhsHJokS05QBNhw9Mr5TlAodY07zgFOUCPwvUoXJ85QLhAguLHeDlAowG8BRI0OUDb+X5qvIQ5QL99HThnFDlAMCqpE9AEOUCdEaW9wec4QGQ730+NBzpACfmgZ7MqOkAUP8bctRQ5QLgehetRSDpAzTtO0ZHMOECUh4Va03w5QKJFtvP9NDlAaW/whckEOUAsZRniWCc5QKd5xyk6YjlAMEymCkZVOUCzDHGsi1s5QMoyxLEuDjlA1JrmHaeYOUCR7Xw/NX45QBdIUPwYMzlAEce6uI02OUB4nKIjuRw5QGDl0CLbKTpAAwmKH2PeOUBLWYY41kU6QI4G8BZIMDlAZ9XnaisWOUCIhVrTvPM5QKMBvAUSBDpAh6dXyjIkOUDbiv1l93Q5QOOlm8QgwDlAQBNhw9ObOkBU46WbxBA7QJhMFYxK2jpAw/UoXI/COED+Q/rt6yA6QGgibHh69ThACYofY+46OUCt+lxtxZ45QBZqTfOO8zlAOUVHcvkPOkB4CyQofhw6QCh+jLlrmTlAF9nO91OjOUBfKcsQx6o5QOwvuycPyzlAirDh6ZUCOkA8vVKWIT45QBDpt68DZzlAysNCrWkuOUA6I0p7g085QKH4MeauBTlAOGdEaW+gOEASpb3BF7Y4QBKlvcEXtjhA/yH99nXAOEAs1JrmHcc5QJhuEoPAejlAy6FFtvMtOkA4+MJkqsA5QAKaCBue7jlAVn2utmI/OkAj2/l+alw6QNDVVuwvKzpAkDF3LSF/OkBWn6ut2I86QCegibDhSTlASnuDL0xWOUB1ApoIG545QF+YTBWM6jlABcWPMXftOUA/V1uxv/w4QOauJeSDXjhAyeU/pN9OOEAK16NwPdo4QPkP6bev4zhAxLEubqNxOUBEaW/whXk5QFOWIY518TlAn6ut2F82OkAv3SQGgSU6QGdEaW/w1ThAEhQ/xtyFOUAK16NwPfo4QLprCfmgVzlABOeMKO1NOUCDwMqhRaY5QG/whclUwTlA/Knx0k0iOkDBqKROQIM6QL3jFB3J5TlAeekmMQiMOUDtnjws1Io5QAN4CyQofjhA+FPjpZsEOEAAAAAAAIA5QIxK6gQ04ThAIv32deBsOkAB3gIJih86QFJJnYAmMjlAsi5uowFsOUCRfvs6cE45QHBfB84ZITlAgnNGlPYWOECNKO0NvuA6QBniWBe38TpAJLn8h/TbOkCSXP5D+v06QEjhehSuVzpAxyk6kst/OUBDHOviNoo5QMoyxLEuXjlA+1xtxf5SOUAdyeU/pO84QDMzMzMzgzhAZvfkYaF2OEC4HoXrUZg4QM6I0t7gyzpAyAc9m1VfOkAX2c73U3M5QDnWxW00oDlAZRniWBfHOECrPldbsb85QDXvOEVH0jlAZMxdS8hnOUDRItv5foo5QHE9CtejIDlA6bevA+c8OEApXI/C9cg5QG3n+6nxYjpANV66SQwyOkANcayL2xg5QDSitDf48jlAjNtoAG9BOUAukKD4MWY5QCv2l92TlzlAIbByaJE9OUBN845TdGQ5QJqZmZmZiTlAxY8xdy0xOUAsZRniWBc5QL8OnDOiNDlAklz+Q/qdOUCq8dJNYuA4QG40gLdA8jhA63O1FfvbOECZu5aQD0o5QLpJDAIr5zlAlrIMcazbOEDJ5T+k3/45QLpJDAIrFzpAHOviNhpAOkD0/dR46dY5QCBB8WPMfTlAPZtVn6vdOUAW+8vuydM5QOJYF7fRIDpAVg4tsp0fOkC4QILix6g5QKUsQxzrgjlAke18PzUuOUCoxks3iQE5QG3F/rJ7QjlArK3YX3ZPOUCtad5xiu45QFZ9rrZi3zlA54wo7Q3OOUCxUGuad8w5QG/whclUsTlA/fZ14JzxOUCAt0CC4hc5QCuHFtnONzlAAd4CCYpPOUD3Bl+YTHU5QPvL7snDojlAhxbZzvdDOUBsCfmgZ5M5QLhAguLHCDlAOGdEaW9wOUDUmuYdp3g5QHWTGARWbjlATmIQWDn0OEDZPXlYqNU5QFHaG3xhkjlA6gQ0ETZcOkCvlGWIYz06QM4ZUdobrDhAVTAqqRMAOUA3GsBbIHE5QOf7qfHSLTpAbAn5oGfDOUA8vVKWIb44QK1p3nGKfjlAI0p7gy8sOUCcM6K0N4g5QC6QoPgxpjlAGeJYF7cxOUBJLv8h/cY4QJ/Nqs/VZjpAtTf4wmTaOUCZu5aQD6o5QE5iEFg5xDhA+THmriWkOEDdtYR80HM5QCntDb4wyThA7lpCPuiZOUDjNhrAWzA6QIBIv30dqDlAayv2l92zOUBy+Q/pt/84QHL5D+m3/zhATx4Wak3jOEAtsp3vp4Y5QIGVQ4tsZzlAPzVeukkMOUASFD/G3LU5QPLSTWIQeDlAYhBYObT4OEAj2/l+anw5QL7BFyZTtTlAVTAqqRPgOUC62or9ZUc5QPAWSFD8mDlAY+5aQj7YOUC1N/jCZHo5QKyL22gA/zlAz/dT46XrOUCzDHGsi0s5QKyL22gATzhAgZVDi2xnOUD4U+Olm9Q4QLpJDAIrNzlAvp8aL90UOkDLoUW28705QOtztRX7GzlAqFfKMsRhOUDF/rJ78hA5QKvP1VbsjzpA/yH99nVwOkBDHOviNoo5QPCFyVTBKDpAxLEubqMBOkD3Bl+YTMU5QL99HThn1DlAWMoyxLGOOUB2Tx4Wao05QPJBz2bVJzlAdk8eFmrtOUBxrIvbaCA5QBWMSuoENDlAxLEubqMROUCh1jTvONU4QPRsVn2uNjlADXGsi9sIOUD8GHPXEiI5QEOtad5x+jhAhetRuB7lOEClTkATYZM4QBiV1AlogjhANIC3QIJiOkAbDeAtkJA5QF+YTBWMajlApb3BFyaTOUAPnDOitGc5QHRGlPYGrzlAO99PjZfeOUD129eBc8Y5QARWDi2yDTpA5dAi2/nOOUDEQq1p3sE5QDarPldbITpAnKIjufxXOUC1FfvL7pk5QGHD0ytlWTlABFYOLbKtOUDpJjEIrKw5QCBj7lpCvjlA6Nms+lyNOEB6xyk6kls5QK36XG3FPjlAescpOpJLOUARNjy9UgY6QLfRAN4CCTpAfPKwUGuaOUCZu5aQD+o5QCv2l92TpzlA9P3UeOl2OUDLEMe6uB05QMl2vp8afzhAV1uxv+wOOUCvlGWIY904QO2ePCzU2jhAIo51cRsNOUDFILByaBE5QNnO91Pj5TlAbVZ9rrbiOEAFxY8xd+04QMBbIEHxwzhA3EYDeAtUOEBEaW/whQk5QB3J5T+kHzhA2PD0Sll2OEBg5dAi20k4QJzEILByuDhAyXa+nxovOUC8lpAPeoY6QMHKoUW2wzlAKjqSy3+IOUB7FK5H4Ro5QDojSnuD/zhAliGOdXFbOEDXNO84Rbc5QKpgVFIn8DhAtaZ5xyn6OUD+1HjpJvE5QOqVsgxxPDpAQmDl0CIbOUBLyAc9m2U5QEa28/3UODpAWYY41sVdOUDUK2UZ4pg5QHNoke18TzlA5IOezaovOUBseHqlLFM5QEI+6NmsWjlAMQisHFpUOUADCYofYw45QDojSnuDLzpAhA1Pr5SlOUAAb4EExX84QAU0ETY8/ThA5/up8dI9OkDzjlN0JNc5QB/0bFZ9bjpA54wo7Q2OOkCP5PIf0m86QBUdyeU/5DlAFmpN847jOkAcfGEyVaA4QAIrhxbZLjhAseHplbJ8OEC6SQwCKyc6QOQUHcnlvzhACfmgZ7OqOUDIBz2bVb85QOjZrPpczTlA/Knx0k2SOUBDrWnecco5QAMJih9jHjlA4lgXt9FwOEBjf9k9edg4QHrHKTqSOzpANKK0N/gyOUA2zTtO0QE5QDC7Jw8L9ThAF9nO91MTOUAJ+aBns8o4QMpUwaikPjlAQKTfvg58OUCppE5AEyE5QAtGJXUCSjlAi2zn+6nxOEAK16NwPTo5QOkmMQisPDlA8WPMXUtIOUAIrBxaZPs4QBb7y+7JszlAveMUHckFOkBtxf6yexI6QEI+6NmsujhAtvP91HjJOEDZzvdT4+U4QJhMFYxKujhAf2q8dJNYOECPwvUoXC84QI/k8h/SXzlAf2q8dJMoOUC7Jw8LtZY5QILix5i7VjlAOpLLf0gPOUDEsS5uo5E5QDm0yHa+zzhAHqfoSC4POUDUK2UZ4vg5QPVKWYY4ZjlAk6mCUUkNOUDqlbIMcXw5QGEyVTAqCTpAy6FFtvM9OUCyne+nxqs5QAg9m1WfGzlAn82qz9XWOECgGi/dJIY5QOtztRX7qzlAUPwYc9ciOUCze/KwUEs5QBsN4C2QIDlAhetRuB4lOkASg8DKoTU6QC0hH/RsxjlA8kHPZtWXOUBLyAc9m/U5QJkqGJXUqTlAVcGopE6gOECQoPgx5v44QF5LyAc9ezpAAG+BBMUfOUByio7k8o84QJqZmZmZyTlA7MA5I0rbOUDswDkjSvs5QCgPC7WmaTlASOF6FK4HOUA2PL1SljE4QLG/7J48vDhAvw6cM6LEOkBPQBNhw5M6QDJVMCqpszpA4L4OnDPCOkBJnYAmwuY5QH/7OnDOuDlApb3BFyaDOUCze/KwUJs5QH3Qs1n1eTlApSxDHOsCOUAjSnuDLxw6QB/0bFZ9bjlAtoR80LP5OUAOvjCZKpg6QOzAOSNKazpAfGEyVTBKOkDu68A5Iyo7QEHxY8xdWzpAzO7Jw0J9OUB0RpT2Bn85QDPEsS5uczlAdEaU9gZ/OUASg8DKoXU5QBBYObTINjpAsAPnjCg9OUDpSC7/IT06QNSa5h2n2DlABcWPMXdNOUCrPldbsY85QF+YTBWMSjlAsb/snjzcOUC/fR04ZyQ6QC1DHOvipjlARpT2Bl8YOUBhw9MrZRk4QGHD0ytlGThAzH9Iv339OkAIrBxaZNs7QGq8dJMYpDdAsVBrmndsOUDJ5T+k3944QHqlLEMcyzhAiUFg5dBCOUB2Tx4Wag06QJAxdy0hLzpA0LNZ9bnqOUCtad5xis45QN5xio7k0jlA9wZfmEz1OUCU9gZfmLw5QL4wmSoYFTlAppvEILByOUB4nKIjuaw4QMpUwaikLjlAEOm3rwOXOUBrK/aX3XM5QAtGJXUCWjlAvJaQD3pWOkAc6+I2GvA4QAFNhA1P3zlAEHo2qz4nOkDKVMGopD46QLFQa5p3DDpAWYY41sXdOUDDZKpgVLI5QDqSy39I3zlAZDvfT40nOkAbL90kBhE6QE7RkVz+czpAescpOpJ7OkBtVn2utjI6QMNkqmBUojlAsb/snjw8O0CIhVrTvGM6QDojSnuDfzhAtTf4wmRaOEC1pnnHKQo5QPW52or91ThAAG+BBMVvOUCneccpOkI5QGHD0ytl2TlA9UpZhjhmOkBCz2bV5zo6QLraiv1lBzlAsp3vp8abOEAr9pfdk+c4QCo6kst/2DlA+8vuycMCOkCM22gAbzE5QOzAOSNKCzlAI9v5fmoMOUBnRGlv8NU4QJp3nKIjyTlAQYLix5i7OUAnMQisHHo5QAtGJXUCmjhAx7q4jQZQOkAOT6+UZbg5QBniWBe3MTlA/tR46SbhOUCYbhKDwKo6QCuHFtnOdzlAj8L1KFxvOUADCYofYy45QOVhodY0PzlAVn2utmLvOEB56SYxCBw5QClcj8L1GDlAOwFNhA2POUCX/5B++xo5QD9XW7G/3DhAETY8vVL2OUCvJeSDnt05QDojSnuDHzlAMlUwKqljOUA9CtejcB05QL6fGi/dBDlABOeMKO1dOUBvEoPAykE5QDBMpgpGVTlARwN4CyQIOkDQ1VbsL3s6QCgPC7WmyTpAeqUsQxzLOUBMpgpGJaU5QKYKRiV1AjpAT0ATYcMzOkD129eBc0Y5QEcDeAskKDhAbef7qfHyOEB/+zpwzkg5QF3cRgN4uzlAUwWjkjrROUBbQj7o2Xw5QCnLEMe6aDlAejarPlc7OUCWsgxxrBs5QO0NvjCZmjlAbqMBvAWSOED99nXgnAE5QJp3nKIjeTlAnRGlvcG3OEDfT42XbnI5QIqO5PIfwjhAVcGopE6gOEDVeOkmMXg4QKHWNO84ZThAhA1Pr5SlOEC7Jw8LtUY6QEJg5dAiazpAUWuad5yCOEARx7q4jUY5QCNKe4MvXDtAjErqBDTBOUCqYFRSJ7A5QCsYldQJqDlAukkMAiuXOUDrc7UV+8s5QAisHFpk2zlANIC3QIKSOECcoiO5/Oc4QDqSy39IvzlAcT0K16MQOkBzaJHtfE85QLTIdr6fujlAW0I+6Nl8OUDY8PRKWZY5QH2utmJ/qThA3GgAb4HkO0CQoPgx5u45QBb7y+7J0zlAVg4tsp0POUB/arx0k2g5QDsBTYQNTzlA1edqK/Y3OEDvOEVHchk6QOC+DpwzQjlAIR/0bFZdOUDhehSuR+E5QL3jFB3JpTlABoGVQ4tcOkB9PzVeujk5QD2bVZ+rrThAokW28/1kOEDPZtXnaks5QF66SQwCyzlAt2J/2T1ZOUB2cRsN4G05QHzysFBr6jhAMEymCkblOECGWtO84yQ4QILix5i7ljlAj8L1KFwfOUBYObTIdv44QHctIR/0XDlAwaikTkDjOEC+MJkqGAU6QDarPldbETpAt2J/2T0pOUD7XG3F/tI5QAwCK4cW6ThA4lgXt9HQOEB0RpT2Bq85QGDl0CLbWTpA3bWEfNATOkBYObTIds46QGaIY13c1jpAXrpJDAL7OUDPZtXnars5QELPZtXnGjpAe4MvTKYqOkBVwaikTkA4QL4wmSoYZThAlkOLbOe7OkAFo5I6AY05QCGwcmiRHTlAtoR80LMJOUBrK/aX3ZM4QG+BBMWP8ThAak3zjlPkOUCYTBWMSoo5QLivA+eM2DhAHcnlP6TvOEDek4eFWlM4QGaIY13cRjlAofgx5q41OUB6xyk6khs6QEMc6+I2ejlA7uvAOSN6OkDi6ZWyDDE6QPaX3ZOH9TlAdy0hH/SsOUAAb4EExb84QNiBc0aUJjlA9bnaiv1VOUCF61G4HmU5QD2bVZ+rvTlAOUVHcvnPOUBVMCqpE+A5QM6qz9VWDDlArfpcbcUOOkDtDb4wmQo5QLpJDAIrJzlAnl4pyxB3OUDkg57Nqn85QCBj7lpC7jhAQj7o2awqOEBrmnecohM4QHKKjuTy/zhAdy0hH/RcOUCNl24Sg3A5QNejcD0K1zlAOiNKe4MvOUAQWDm0yIY5QFXBqKRO4DlAWDm0yHZ+OUBeS8gHPVs5QGiz6nO1JTpAkKD4Meb+OEA5tMh2vo85QMpUwaikLjlAUdobfGGSOUDXo3A9Cnc5QPT91Hjp9jhAxY8xdy2xOEA/NV66Sbw5QDC7Jw8LRTlAFYxK6gS0OUBU46WbxPA5QCEf9GxW7TlA+n5qvHTDOUAmUwWjkpo4QMPTK2UZsjhAio7k8h9iOUDnjCjtDW44QEGC4seYmzlAkQ96NqteOUD8GHPXEkI5QDbNO07RQTlAhJ7Nqs8lOkBE+u3rwJk6QDqSy39IjzlACD2bVZ/LOEArGJXUCZg5QIBIv30dCDpAMlUwKqmTOED4wmSqYGQ5QHuDL0ymKjlAQKTfvg5sOUAH8BZIUOw4QFMFo5I68ThA/Knx0k0SOUD7y+7Jw+I5QPyp8dJNkjlAGy/dJAbhOUA7AU2EDY85QHS1FfvLrjlA/7J78rBgOUDG3LWEfOA4QOm3rwPn7DhAR3L5D+nHOECHFtnO99M5QN/gC5OpEjlAI0p7gy8MOUALRiV1Aho5QHxhMlUwOjlAWMoyxLH+OEDiWBe30fA3QOxRuB6F2zdA5BQdyeXvN0Bd/kP67cs4QN6Th4Va0zhANKK0N/iyOEAWak3zjpM4QDbNO07RIThAV1uxv+x+OEB4CyQoftw4QOM2GsBbMDlAeekmMQhcOUB/2T15WKg4QELPZtXnGjlAiUFg5dDiOECPU3Qkl/84QF+YTBWMWjlAGJXUCWjiOUBDHOviNoo5QDSitDf44jhAAJF++zogOUArhxbZztc4QHUCmggb/jhACRueXilbOUAMk6mCUVk5QHKKjuTynzlAl5APejabOUB6Nqs+V5s5QHEbDeAtIDlAVcGopE4QOUCxv+yePOw5QCh+jLlrqTlAE2HD0ysVOUAqOpLLf8g4QAfOGVHaezlAI9v5fmpcOkAbDeAtkOA4QP5D+u3rkDlAO3DOiNK+OUCTGARWDt05QDlFR3L5LzpAxSCwcmhROkBFR3L5D5k6QBsN4C2QADlAofgx5q5VOUDpt68D5yw5QEvIBz2bZTlA8BZIUPxIOUDdtYR80FM6QGZmZmZmxjlAvw6cM6LEOUBYyjLEsb45QGIQWDm0KDlAyeU/pN8+OkBcIEHxY/w5QJM6AU2EfTlALv8h/falOUCsi9toAF85QNzXgXNGtDlANjy9UpbROUDsL7snD2s4QDJVMCqpozhAayv2l93TOkCamZmZmZk7QPp+arx0kzpAswxxrIvLOkAwKqkT0KQ5QGfV52orljlAl5APejbbOEBSuB6F66E4QKjGSzeJkTlAw/UoXI9iOUALJCh+jNk5QJ5eKcsQ1zlAgQTFjzG3OUC62or9ZXc6QMZtNIC3oDlA54wo7Q2uOEByio7k8l84QOOlm8QgoDlArthfdk/ON0Bj7lpCPjg4QDojSnuDLzhAirDh6ZVSOECamZmZmUk5QJ/Nqs/VZjlA3bWEfNBDOECqglFJnSA4QP8h/fZ1ADlA54wo7Q0+OkBeukkMAts5QIxK6gQ0wTlASS7/If1WOkAgQfFjzM05QNZW7C+71zlA5j+k375+OUDJ5T+k3245QNEi2/l+GjpAOGdEaW+gOECk374OnNM4QCQofoy56zhAINJvXwduOEAaUdobfHE5QMl2vp8aLzlAD5wzorRnOUCJ0t7gC+M4QJf/kH77KjlAIGPuWkLeOEDVeOkmMbg5QNDVVuwvazlAsp3vp8bLOUC7uI0G8AY6QPjCZKpg1DhA7lpCPuiZOEAFo5I6Ac05QAfwFkhQDDtA4zYawFsQOkCOdXEbDeA7QLRZ9bnaGjtAj1N0JJcfO0BL6gQ0EWY6QPvL7snDMjlAN4lBYOUwOUD+1HjpJpE5QPW52or91TlARrbz/dS4OUCitDf4woQ5QD0K16NwPTlArBxaZDtvOUCoNc07TnE5QHZPHhZqTTlATfOOU3R0OkBWfa62Ys85QAskKH6MCTlAVp+rrdivOUBCYOXQIts5QLaEfNCz6TlAbcX+snsyOUB8YTJVMFo5QKpgVFInEDlAGsBbIEGBOUD/If32dVA5QN/gC5OpYjlA4lgXt9HQOUDgLZCg+IE5QESLbOf7yTpAZmZmZmYmOkByio7k8p86QKYKRiV1AjlAMQisHFrUOEB9PzVeumk5QEku/yH95jdA5/up8dLtN0CYbhKDwMo3QEATYcPTezpAJlMFo5L6N0AxCKwcWgQ5QBUdyeU/VDlAZ0Rpb/D1OEC6awn5oLc4QFR0JJf/kDlAw9MrZRkSOUCMSuoENOE4QCh+jLlr+ThASZ2AJsImOUCEDU+vlJU4QMzuycNCPTpA9P3UeOnWOUAgY+5aQp45QOhqK/aXbTlASL99HTinOUDufD81Xso5QM6I0t7gazlAxm00gLdQOUBzaJHtfI85QMNkqmBUMjlA/mX35GFROUCmCkYldVI5QK62Yn/ZzThAUkmdgCbSOUCoV8oyxLE5QJCg+DHmrjlAldQJaCLcOEDoaiv2l206QDVeukkMojpA+FPjpZukOkAgY+5aQk44QEHxY8xdazpA9ihcj8J1OkD+1HjpJgE6QP+ye/KwoDhAzTtO0ZH8OEB/arx0k4g4QCsYldQJ6DhAkzoBTYTdOECYbhKDwDo5QJ7vp8ZLJzlAdCSX/5COOUBqvHSTGPQ5QI/C9ShcrzlAFYxK6gSUOUAU0ETY8LQ5QLmNBvAW6DlAc2iR7XxvOUAGgZVDi3w6QNzXgXNGxDlApSxDHOvSN0BSJ6CJsHE4QMZtNIC38DdAkQ96NquOOEAibHh6pSw4QKFns+pzhThA9+RhodYEOUCfPCzUmhY6QCPb+X5qHDpAb4EExY8BOUBbQj7o2Rw6QN5xio7kQjlATx4Wak1DOEBnRGlv8AU5QOoENBE27DhAcT0K16OwOEAv3SQGgWU4QEmdgCbCBjpAnu+nxks3OUCIY13cRoM5QJp3nKIjeTlAc9cS8kF/OUA1XrpJDFI5QE+vlGWIYzlAbxKDwMoxOkA/NV66SQw5QNIA3gIJmjlAn6ut2F/WOUDM7snDQo05QAisHFpkKzpAcvkP6befOEDmriXkg+45QBkEVg4t4jlAXI/C9ShsOUCmCkYldaI5QE5iEFg5JDlA63O1FfsrOUAZBFYOLQI5QC7/If329TlAi/1l9+RBOUCamZmZmdk4QERpb/CFuTlACmgibHi6OUB/+zpwzpg5QLU3+MJk2jlA4zYawFvwOUDGbTSAtxA6QMZtNIC3EDpAC0YldQI6OEBWfa62Yt84QGgibHh61ThA2IFzRpSGOED+Q/rt6zA5QMzuycNCPTlAQxzr4jbaOUCgGi/dJBY6QMSxLm6jgThAyAc9m1X/OUDLoUW28405QP5l9+Rh8ThACyQofozZOUBQ/Bhz1yI5QLaEfNCzOTpAMlUwKqmjOEAr9pfdk9c5QE8eFmpNIzlAkKD4MeYeOUDeAgmKH7M5QMZtNIC3UDlAEFg5tMgGOkCDwMqhRTY6QPd14JwRFTpAMCqpE9D0OED99nXgnBE6QKH4Meau9TlAuK8D54zIOUAj2/l+auw5QAisHFpkqzlArrZif9m9OUDdtYR80EM6QGFUUiegGTpAbHh6pSzTOkBPHhZqTUM7QJYhjnVx6zpAcT0K16NwOECV1AloIjw6QFvTvOMUjTlAqRPQRNggOkDhC5OpgkE6QJM6AU2ETTlAObTIdr7vOEAQejarPgc5QHqlLEMcqzhA5BQdyeUvOUD1udqK/bU4QBfZzvdTszhAVn2utmJvOUDChqdXykI6QKpgVFIn0DhAl/+QfvuaOEBO0ZFc/kM6QJf/kH77ajpADr4wmSoYOkASg8DKoRU6QBUdyeU/lDpABOeMKO1NOkD4U+OlmxQ6QNjw9EpZljpA4QuTqYKBOkAZ4lgXt9E5QL7BFyZTBTpAm1Wfq63YOEDBOSNKe8M5QC/dJAaBxThApb3BFyYTOUCR7Xw/NT45QM/3U+OlyzhAk6mCUUntOEBMN4lBYJU5QDojSnuDnzlArWnecYoOOkCXkA96Nms5QKHWNO84BTlASOF6FK5XOUBhw9MrZck5QOjZrPpcDTlAoBov3ST2OECtad5xin44QL4wmSoYlThAs3vysFALOUDLoUW28104QDLmriXk0zhALNSa5h3HOECh+DHmrnU4QHRGlPYGnzlAbAn5oGdDOkBbsb/snjw5QKH4MeauxTlAiPTb14HjOUD5oGez6vM5QFRSJ6CJUDpAnMQgsHK4OUAg0m9fBz46QNobfGEy5ThA2ht8YTLlOEAGgZVDi9w4QLhAguLHiDhABOeMKO19OUB9rrZifyk5QNZW7C+7JzlA7zhFR3KpOEB0tRX7y544QAtGJXUCWjlAaLPqc7VFOkASFD/G3MU4QLMMcayLKzpAlkOLbOeLOkC4QILix9g6QP2H9NvXsTlAt2J/2T1pOUCu2F92Tx45QARWDi2yXThAmpmZmZkJOkDA7J48LBQ5QMrDQq1p7jlAkQ96NqueOEBn1edqK8Y5QC0hH/RsVjlA0m9fB87JOUBTBaOSOuE5QIY41sVtZDlA/yH99nVwOUDMf0i/fT05QJ5eKcsQVzlAnl4pyxBXOUAQWDm0yDY5QClcj8L1qDhA097gC5NJOUAnwoanV2o5QL6fGi/ddDpAUwWjkjoROkAbDeAtkGA6QEoMAiuHhjlAPQrXo3A9OUBhMlUwKsk5QOCcEaW9kTlALv8h/fYlOUBvgQTFj2E5QGx4eqUsgzhAPujZrPqMOUDf4AuTqZI6QJT2Bl+YLDlAwoanV8oSOUCIY13cRjM5QMbctYR8wDlAgLdAguJXOUC3Yn/ZPYk5QKfoSC7/ATlAVOOlm8TgOED7XG3F/jI5QA6+MJkquDlAsVBrmne8OEDM7snDQh05QCgPC7WmaTlA7Q2+MJl6OEDfT42XbkI6QDhnRGlvcDpA48eYu5bwOUC1N/jCZCo5QBniWBe3ITlAuK8D54z4OECneccpOiI5QJJc/kP6LTlAm+Ydp+hYOUAnwoanV4o4QKH4Meau1TlAB1+YTBVMOUB90LNZ9dk4QERpb/CFiTlAKxiV1AkoOUBeS8gHPds4QIqw4emVUjhA4XoUrkdhOkDEsS5uo+E5QEXY8PRKmThAGlHaG3xhOkBxrIvbaHA5QKyL22gAvzhAHHxhMlWQOECcoiO5/Hc5QEoMAiuHxjhANs07TtHBOEAW+8vuyZM5QMDsnjwsRDlAB84ZUdrLOEAy5q4l5EM4QArXo3A9GjlAbjSAt0ByOEApXI/C9fg4QGuad5yiszhAbef7qfHCOECRD3o2q744QCsYldQJuDhACRueXin7OEB/+zpwzkg5QPAWSFD8qDlAXf5D+u37OUDsUbgehfs5QME5I0p7gzlA9GxWfa42OkB4eqUsQ3w5QFTjpZvEYDlAY3/ZPXk4OUDpJjEIrLw5QKs+V1uxrzhApU5AE2GjOEC+wRcmU1U6QKVOQBNhkzpAZF3cRgPoOUDYgXNGlOY4QD9XW7G/jDlAnDOitDdoOUAoDwu1pqk5QFtCPujZfDhAPSzUmua9OEAjSnuDLzw5QArXo3A9CjpAa5p3nKLzOUCjI7n8h7Q5QGKh1jTv+DhAsVBrmnfsOEDarPpcbSU5QM07TtGRXDpA6bevA+f8OEDXo3A9Ckc5QOqVsgxxXDlAdCSX/5CeOEAcfGEyVeA5QNcS8kHPhjhAXwfOGVFKOEAOvjCZKlg3QCntDb4wiTdA7lpCPui5OEAijnVxG505QE0VjErqxDhAX5hMFYwKOkBfmEwVjPo4QLn8h/Tb1zhA4C2QoPghOUAvbqMBvPU5QFg5tMh2vjpAhxbZzvezOUBYyjLEsZ46QEdy+Q/p5zlAXkvIBz1rOkCfPCzUmvY4QELPZtXnWjhAgSbChqcHOUDNO07RkVw5QAMJih9jTjhA8tJNYhDYOECcoiO5/Ic5QF3+Q/rtGzpA+zpwzoiSOkDaG3xhMrU4QMPTK2UZ8jhAarx0kxhUOEBUdCSX/+A4QLbz/dR4CTlAsb/snjyMOECxv+yePOw4QOoENBE2TDlA5BQdyeXvOEBfB84ZUWo5QAu1pnnHWTlAF7fRAN5yOUAukKD4MbY4QOSDns2qXzhAeHqlLEOcOED2KFyPwuU4QO7rwDkjKjlA2/l+arz0OEDqBDQRNsw5QLAD54woXTlATYQNT6+0OUCYTBWMSho5QKvP1VbsjzhA7C+7Jw+7OEAAAAAAAEA6QNxoAG+B1DlA8IXJVMFIOkCeXinLEEc6QKW9wRcmYzlARpT2Bl8oOkD+ZffkYRE5QKOSOgFNVDlAJ8KGp1cKOUCdgCbChsc5QMNkqmBUcjpAtRX7y+7pOECjI7n8h4Q5QL6fGi/dpDlArfpcbcVeOUB8YTJVMKo4QHxhMlUwqjhAUWuad5ziOUBz1xLyQc84QFjKMsSxfjlABTQRNjwdOUBI4XoUrkc5QM07TtGRrDpAtTf4wmSKOkBYyjLEsZ46QOzAOSNKWzpAcRsN4C1gO0CjAbwFEkQ7QF8pyxDH2jpArK3YX3bPOkBSuB6F67E6QG3F/rJ7AjpAwhcmUwXTOUC8BRIUP9Y5QE3zjlN0dDlAaJHtfD+VOkCgibDh6WU5QFioNc07TjlARGlv8IXZOUCze/KwUOs6QARWDi2yHTtAliGOdXFbOUAHX5hMFdw5QAtGJXUCijhA9wZfmExFOkASpb3BF5Y5QMsQx7q4HTlAoBov3SSmOECF61G4HtU4QNuK/WX3xDhAbHh6pSyjOECYbhKDwLo5QG1Wfa62IjpAfoy5awkZOUDVCWgibIg4QIenV8oyxDhAQBNhw9MbOkCmm8QgsFI6QEGC4seYqzlAQKTfvg4sO0Dx9EpZhgg7QBUdyeU/tDpAfPKwUGvKOkBLWYY41kU7QHe+nxovzTpAhetRuB5FOUC7uI0G8GY4QOf7qfHSvThAhxbZzvcTOUCM22gAb9E5QKqCUUmdEDpAPQrXo3DdOUC30QDeAmk5QI0o7Q2+MDlA46WbxCDAOEC7Jw8LteY5QDhnRGlv8DlAswxxrItbOkC+nxov3UQ6QIhjXdxGUzpAnu+nxkt3OUBLyAc9m7U5QPtcbcX+YjlAsb/snjxsOEBtVn2utmI4QNiBc0aUhjhAPE7RkVxeOEAVHcnlP4Q5QK7YX3ZPPjlA3pOHhVozOUDsL7snD6s5QFpkO99PzThAFmpN846zOUBeukkMAms6QMrDQq1pXjlAXdxGA3i7OUC8lpAPetY5QK7YX3ZP/jhAt2J/2T3ZOUD/snvysEA5QFafq63YTzlAejarPlerOEA5tMh2vk85QCqpE9BESDlABOeMKO3NOEDjpZvEIDA5QDLmriXk8zhAlWWIY12MOkBhw9MrZbk6QKMBvAUS9DlAlkOLbOdLOUD4U+OlmyQ5QKMBvAUSpDhAF0hQ/BjjOEACvAUSFC86QNcS8kHP1jhADi2yne83O0B6pSxDHFs6QEymCkYldTlAnRGlvcG3OUCF61G4HiU5QNv5fmq8FDlAcRsN4C0QOkDZX3ZPHoY5QP8h/fZ1MDlACtejcD3aOUDwp8ZLN7k5QO58PzVeqjhAWDm0yHaOOUBE+u3rwBk6QEdy+Q/pNzpApb3BFyYjO0BUUiegiWA7QC/dJAaBNTtAxyk6kstPOEDqBDQRNqw5QH2utmJ/yThApN++DpzDOUALRiV1Aro5QKK0N/jCRDlAHcnlP6TfOUAFNBE2PI05QDqSy39InzlAFvvL7sljOkDfT42XbtI4QGiz6nO1tThApgpGJXXCOUDjx5i7lsA5QET67evA2TlAINJvXwfOOUBN845TdPQ5QNbFbTSApzlAGeJYF7cROkBpb/CFydQ6QEI+6Nms2jpA9ihcj8KVOkAAkX77OpA5QL3jFB3JVTlAjErqBDRBOUAnwoanV9o5QBzr4jYaADpAzojS3uDbOEDbiv1l95Q5QACRfvs6kDlAuECC4sd4OUAZBFYOLfI5QKyL22gADzpANqs+V1vxOECEns2qz5U5QBWMSuoEBDlAduCcEaXNOEC94xQdyRU5QP5l9+RhMTlArBxaZDvvOEBVwaikTnA4QOM2GsBbMDlAarx0kxi0OEDZzvdT44U4QBB6Nqs+5zhAgQTFjzHHOUDsUbgehes5QInS3uAL0zlA4C2QoPhBOUD99nXgnFE6QDBMpgpGpTlAxf6ye/LgOUAm5IOezQo5QIEmwoandzlAxyk6kst/OEAAkX77OoA4QB+F61G4vjhA/fZ14JxBOUAZc9cS8iE5QHicoiO5vDlACyQofoyJOUDnjCjtDf45QMIXJlMFQzpAOwFNhA1vOkCSXP5D+m06QFioNc07TjlAdCSX/5DeOEAX2c73U0M5QE9AE2HDUzlAJzEIrByqOUASFD/G3BU6QPOOU3QkpzhAowG8BRI0OUA8TtGRXG46QI0o7Q2+oDlA/7J78rDQOUC1pnnHKco5QHPXEvJBbzlAysNCrWn+OUArhxbZzqc5QOPHmLuW8DlA3+ALk6kyOUCpE9BE2KA4QKYKRiV1IjpADi2yne93OUAGgZVDi8w5QHzysFBrmjlAayv2l91DOUCppE5AE0E5QJVliGNdrDlAl/+Qfvv6OEBIUPwYc/c4QFmGONbFPTlAVTAqqROgOEBKe4MvTIY6QIC3QILipzlAKcsQx7ooOUDqlbIMcaw4QJAxdy0h3zhAFvvL7smzOEB4nKIjuWw4QKUsQxzrcjhAUwWjkjrxOEAIPZtVn9s4QPYoXI/C5TlAV+wvuyePOUD4wmSqYKQ5QPCnxks36TpApgpGJXXCOkA51sVtNMA5QJHtfD81HjlAmN2Th4X6OEB2cRsN4G04QFdbsb/s/jhA7uvAOSNqOEC1N/jCZDo4QMBbIEHxwzpAyxDHurh9OUArGJXUCXg5QPT91HjpJjpAirDh6ZXiOUDD9Shcj1I5QGN/2T15uDlALbKd76cWOkCHp1fKMhQ6QO7rwDkjajpAMuauJeQTOUAOT6+UZUg5QF5LyAc9izlARrbz/dQoOUDBqKROQFM5QM07TtGRfDlA7lpCPuhZOUDhehSuR9E5QATnjCjtDTlAzF1LyAedOEAFNBE2PK05QNxGA3gLNDlACfmgZ7M6OkDZPXlYqBU6QFvTvOMUjThA0gDeAgnaOECaCBueXuk5QOJYF7fRQDlAldQJaCJcOUAukKD4MUY5QFTjpZvE0DlAIEHxY8ydOUASFD/G3GU5QF66SQwCOzlAVFInoImwOUDVeOkmMdg3QMPTK2UZAjhAQBNhw9MrOkBoke18PyU5QKK0N/jCBDpAzqrP1VbMOUCgibDh6YU5QM6qz9VWDDlA9pfdk4dlOUCsrdhfdh85QCBj7lpCHjlAD5wzorRHOkBL6gQ0EeY4QJp3nKIjOTlADAIrhxYpOUD4U+OlmyQ5QL3jFB3JRTlA+n5qvHQTOUBTBaOSOsE4QGkAb4EEhThAbAn5oGdjOEAqOpLLf3g3QFRSJ6CJgDhA4zYawFtQOEDbiv1l95Q4QN9PjZduEjlAQYLix5jrOEBVMCqpEwA5QNO84xQdCTlAPZtVn6vdOkDgvg6cM9I6QDnWxW00MDtAQYLix5jLOEA5RUdy+f84QBZqTfOOAzlAJCh+jLlrOEAgY+5aQq46QP32deCckTlAuycPC7WmOUC6awn5oKc5QMgHPZtV/zlAxm00gLcQOkB+HThnRAk5QHzysFBrGjlASFD8GHPHOUDD9Shcj0I5QFCNl24SUzlAqFfKMsRhOUAQ6bevA5c4QOJYF7fRwDhAm+Ydp+j4OUB4CyQofrw5QBWMSuoEFDpAXf5D+u2bOUDr4jYawCs5QD7o2az6/DhAFR3J5T8kOUA17zhFR9I4QL8OnDOilDlA6Nms+lyNOUBg5dAi2+k5QGwJ+aBnszlAfT81XrqZOkAv3SQGgbU6QCgPC7WmyTlAMzMzMzPTOUCIY13cRnM5QJjdk4eF+jhAcvkP6bfvOUDSAN4CCVo5QCL99nXgjDpADr4wmSo4OEBXW7G/7K44QOeMKO0NzjlAcF8HzhkROUDy0k1iEGg5QBzr4jYaIDlAliGOdXHbOUCcM6K0N+g5QAN4CyQorjlArK3YX3bPOECC4seYu1Y5QG6jAbwFsjhA7FG4HoWrOECPU3Qkl784QJM6AU2EfTlA4C2QoPgROUDIBz2bVc84QApoImx46jlALUMc6+K2OUDKw0KtaQ47QPp+arx0UzlASS7/If22OkAUP8bctWQ6QEI+6NmsyjlAf2q8dJNIOkB6pSxDHBs5QCDSb18HfjlAih9j7lriOEDQ1VbsLzs5QK62Yn/ZzTlANqs+V1sROkD2l92Th7U5QBB6Nqs+RzpAjErqBDShOUA4Z0Rpb2A5QPrt68A5gzlAMlUwKqlzOUDjx5i7llA5QFtCPujZ7DhA8IXJVMHoOECbVZ+rrTg5QC7/If32xTlAcvkP6bcPOUDOGVHaG7w5QNc07zhF1zlAxyk6kss/OkAwTKYKRuU4QNv5fmq8tDlAIEHxY8xNOkCsrdhfdi86QNZW7C+7hzpA1xLyQc9mOUCJQWDl0NI5QDEIrBxatDlATfOOU3QUOUCOBvAWSMA5QD55WKg17ThAu7iNBvB2OUCwcmiR7Yw5QOVhodY0LzlAbqMBvAWyOUBB8WPMXXs5QHWTGARWjjlAQYLix5hbOUB1kxgEVr45QDcawFsgETpAWDm0yHauOEAXSFD8GDM5QN4CCYofUzlAYVRSJ6CpOUBCYOXQIjs5QCDSb18HXjlAL90kBoFVOUArGJXUCcg4QG1Wfa62MjhATfOOU3T0OkBPr5RliGM6QKjGSzeJsTlAy6FFtvMdOkBuowG8BZI5QNzXgXNGFDpAnu+nxku3OUACmggbnn45QMHKoUW2YzlA6gQ0ETbcOUDHKTqSy185QEi/fR045zlAsVBrmndcOUBnRGlv8IU5QNcS8kHPljlAJQaBlUNrO0A4+MJkqlA7QOeMKO0NDjtAAiuHFtleO0C0yHa+n0o6QBueXinL4DlAETY8vVJmOkDTTWIQWHk5QA1xrIvbmDlADXGsi9tIOUAvbqMBvOU5QGkAb4EExTlA3GgAb4EEOkCUh4Va02w6QJAxdy0hnzpAC7Wmece5OEBjf9k9eSg5QNjw9EpZZjlAj1N0JJc/OUB24JwRpf04QDcawFsgwTlAXW3F/rIbOUA2zTtO0UE5QFafq63YzzlA3pOHhVqzOUDKw0Ktaf44QJhuEoPAujhA2PD0SllWOUAOLbKd7yc5QBDpt68DNzlAKA8LtaY5OUDV52or9tc5QLG/7J487DlAUI2XbhJjOkCDwMqhRaY5QC9uowG8VTpAYcPTK2XJOUBg5dAi2wk5QKpgVFInoDlA2/l+arwkOUAHX5hMFaw5QGlv8IXJ1DlAqmBUUiewOUDmriXkg+45QIenV8oyBDlAQxzr4jYKOUCHFtnO9xM5QFJJnYAmUjlATmIQWDm0OUCQoPgx5h45QDPEsS5ugzlALSEf9GwmOUCRD3o2qx45QO84RUdyOTlAwTkjSntTOUD67evAOfM4QH/7OnDOCDpAI0p7gy88OUCKjuTyH0I5QMPTK2UZQjlArIvbaAAvOUAwTKYKRtU5QBB6Nqs+9zlAOpLLf0gfOkCASL99HRg6QHbgnBGlzTlAklz+Q/pNOUCVZYhjXTw5QAg9m1WfizlA6Ugu/yENOkDuWkI+6Jk5QFfsL7snDzlAkDF3LSGfOUDCFyZTBQM6QMX+snvy4DhA0ETY8PQaOUA4+MJkqtA4QGRd3EYDuDhACyQofozpOEAUP8bctRQ5QPRsVn2uNjlAswxxrItLOUAc6+I2GiA5QBHHuriNtjlAQBNhw9NLOEBxGw3gLRA6QIJzRpT2pjlAbcX+snuyOUClLEMc66I5QD2bVZ+rLTpAiUFg5dDyOUBYqDXNO445QJ88LNSaBjlAR3L5D+m3OECSXP5D+q04QAU0ETY8/ThALv8h/faFOECkcD0K15M4QKYKRiV1QjlA2T15WKh1OEDM7snDQn05QKg1zTtOATpA6+I2GsA7OECrz9VW7M84QFuxv+yefDhAPZtVn6t9OUBzaJHtfH85QNejcD0KhzpAAJF++zrAOkBEi2zn+/k5QIC3QILiJzpAL90kBoH1OUCfPCzUmnY6QDsBTYQNLzlA7C+7Jw8LOUBKe4MvTJY5QNobfGEydTlAs3vysFCrOUDjpZvEIMA5QHxhMlUwyjlAL90kBoG1OUABTYQNT985QPMf0m9flzlA2c73U+OlOkBpAG+BBEU6QMKGp1fKYjpAguLHmLv2OUAJih9j7uo5QN21hHzQ8zhA1lbsL7vXOUCSy39Iv706QHuDL0ymejpAwoanV8oyOkDJdr6fGu84QHrHKTqSyzlApU5AE2FDOUCamZmZmck5QAg9m1WfWzlAUdobfGFSOUA7AU2EDS85QCqpE9BEyDlAz/dT46XLOUAVHcnlP9Q4QOjZrPpcTTlAf9k9eViYOUDo2az6XK05QGIQWDm0CDpAnRGlvcEHOkBSJ6CJsCE7QGiz6nO1RTlAl/+QfvuaOUDoaiv2l505QFyPwvUonDlAYOXQIttZOkBWfa62Yr85QEvqBDQRdjhAbqMBvAXCOUACvAUSFO85QPT91HjptjlAMnctIR9EOEBI4XoUrqc4QBDpt68DVzlA3+ALk6mSOUDvycNCrYk5QGEyVTAqKTlA+THmriVEOUCkcD0K16M5QCSX/5B+WzlATfOOU3Q0OUAeFmpN8245QF66SQwCqzlAhJ7Nqs+1OUBEi2zn+9k5QBsv3SQG8TlAFmpN844DOUCYTBWMSso4QJf/kH77qjhAHThnRGmfOEAB3gIJis85QLprCfmgNzlA07zjFB35OEAxCKwcWpQ5QKkT0ETYgDpAIv32deDcOUDGbTSAt8A5QBPyQc9mpTlAKcsQx7oYOUDVeOkmMSg5QE7RkVz+EzlAVOOlm8QwOkDOiNLe4Cs6QF1txf6yGzlAImx4eqUMOEB0RpT2Bt85QDeJQWDlwDlAHVpkO98fOkC4QILixxg5QBkEVg4tsjhA8KfGSze5OUDtDb4wmao5QL99HThnJDlAf2q8dJN4OUC0WfW52uo4QKK0N/jCRDlACmgibHhKOUAdyeU/pF85QOviNhrA6zlAl/+Qfvu6OUBQ/Bhz18I5QB+F61G4XjlA48eYu5ZgOUCjI7n8h1Q5QMgHPZtVDzpA24r9ZffEOUCe76fGS9c5QEymCkYldThA8kHPZtWHOEDZX3ZPHgY4QHNoke18bzhABoGVQ4u8OkCad5yiI8k4QO0NvjCZWjlAHThnRGkPOkDLEMe6uB05QEw3iUFgVThA9bnaiv11OEClLEMc61I5QBlz1xLy8TlAE/JBz2a1OUDZX3ZPHjY5QK1p3nGKTjpAQmDl0CLbOECYTBWMSqo4QPyp8dJNMjlAGlHaG3yhOEDD0ytlGSI6QDsBTYQNvzlAcM6I0t7wOUClLEMc66I5QAaBlUOLPDlAH4XrUbjeOEAwuycPC8U5QDnWxW00sDhAApoIG54uOUAhH/RsVu04QCS5/If0azhAjgbwFkhgOUAnMQisHAo5QACRfvs60DlAFvvL7smTOUCad5yiIwk6QHe+nxov7TlAidLe4AtDOkDOiNLe4Ls4QFTjpZvEgDhA4zYawFuQOECt+lxtxQ46QCo6kst/uDlAfoy5awnpOUD2KFyPwgU6QOqVsgxxHDpANqs+V1sBOkCMuWsJ+SA5QCSX/5B++zlASnuDL0xWOkDjpZvEINA5QLyWkA96tjlA097gC5MpOUDLEMe6uA05QHe+nxovzThApU5AE2ETOUDF/rJ78jA5QOhqK/aX3ThACmgibHhqOUBuowG8BRI5QHNoke18bzlAmpmZmZm5OUBNhA1Pr2Q5QIbJVMGoZDlAdLUV+8tuOUA5tMh2vh86QBe30QDesjlAh6dXyjLUOUBxGw3gLbA5QEXY8PRKKTlAqMZLN4mhOEBSJ6CJsHE4QPMf0m9fVzhAswxxrItbOECgibDh6VU4QKwcWmQ7TzhAodY07zglOUDnHafoSF45QNxGA3gLVDlA8fRKWYaoOECjAbwFEoQ5QAkbnl4pezlAqFfKMsTBOUAtsp3vp6Y5QEp7gy9MtjlA93XgnBElOkB88rBQa8o5QCGwcmiRvTlA001iEFj5OEDoaiv2l704QIEmwoanJzlA7nw/NV56OUAX2c73U8M6QJhuEoPAijpAGeJYF7dhOkD3Bl+YTLU6QL99HThnxDpAaQBvgQT1OUDHSzeJQaA4QLraiv1lBzhANe84RUcSOkB/+zpwzqg4QDGZKhiVFDlAjSjtDb5AOUAW+8vuyfM4QJVliGNdDDpAUiegibBxOUATYcPTK9U5QCEf9GxWLTlAaQBvgQRlOUAQ6bevA5c5QCntDb4wmTlAGCZTBaMCOUCh1jTvOEU4QNejcD0KZzhAxyk6ksufOEA0ETY8vRI5QJf/kH77ujlAfT81Xrq5OUB3vp8aL905QPKwUGuaFzlA4L4OnDOyOUDy0k1iEAg6QGTMXUvIlzpABcWPMXd9OUAtsp3vp6Y5QCBB8WPMnTlANIC3QIISOUDZzvdT4xU5QArXo3A92jlArIvbaABvOkBnRGlv8CU6QDtwzojSfjlARUdy+Q+JOUCsrdhfdh85QLUV+8vumTlAokW28/1kOUAwKqkT0OQ4QPvL7snDUjlA+FPjpZs0OkAXSFD8GIM5QOviNhrAyzlAUI2XbhLDOUDXNO84Rcc5QOeMKO0NvjlA78nDQq3pOUCad5yiI2k4QMrDQq1pvjlAgZVDi2z3OUC4HoXrUYg7QEtZhjjWJTpAW7G/7J5sOUCNKO0NvlA5QCuHFtnOlzhAU5YhjnVhOUD/If32dUA5QEku/yH95jlAZ0Rpb/CFOUCze/KwUNs4QGHD0ytl+TlAH/RsVn3+OUCh+DHmroU5QFJJnYAm0jhANV66SQyyOECIhVrTvMM4QKJFtvP9pDlAVHQkl/8AOkC+MJkqGPU5QB1aZDvfLzpA7MA5I0pbOkD99nXgnKE5QNZW7C+7hzlAdnEbDeA9OkDi6ZWyDEE4QBHHuriNtjlAwhcmUwWzOUAVjErqBAQ6QHNoke18LzpAjLlrCfmwOUCfzarP1SY5QJOpglFJ3ThAEHo2qz63OEAijnVxGx05QOC+DpwzAjlATDeJQWClOUB8YTJVMGo5QEvIBz2bhTlAGsBbIEFBOUDr4jYawBs5QFtCPujZvDlA6+I2GsA7OUBkXdxGA2g5QIbJVMGoJDhAW7G/7J5cOkAkKH6MuTs6QPjCZKpgZDlAbHh6pSyTOECL/WX35IE5QPs6cM6IgjlAmG4Sg8CaOUBIv30dOFc5QFkXt9EAbjlAEFg5tMjmOUDfT42XbqI5QM/3U+Ol2zlA1zTvOEWHOUCb5h2n6Dg4QAdfmEwVvDtAn6ut2F+2OkD2l92ThwU6QCntDb4wiThAAd4CCYrfOEDZX3ZPHuY4QOcdp+hILjlAwhcmUwUjOEC4QILix0g6QK1p3nGK/jhA001iEFipOUBX7C+7J785QPtcbcX+4jhADi2yne+HOUDjpZvEIFA5QPRsVn2udjlACyQofox5OkBzaJHtfD85QM07TtGRfDlA+aBns+qTOUCIY13cRhM5QDxO0ZFc3jhA/Bhz1xLiOEAIPZtVn5s5QOAtkKD4ATlA6bevA+d8OkDkg57Nqv85QKYKRiV1wjhARUdy+Q8pOUDoaiv2lx05QK7YX3ZP/jlAmggbnl4ZOUCze/KwUBs6QLx0kxgEljlABoGVQ4uMOkC4rwPnjCg6QGRd3EYDiDlA8WPMXUtYOUDG3LWEfDA5QHEbDeAtMDlA+aBns+oTOUCWQ4ts57s4QEymCkYlNTlAtRX7y+4ZOUBSJ6CJsAE6QKyL22gAjzlAeekmMQhcOUBbQj7o2Sw5QCJseHqlbDlAke18PzW+OEC3Yn/ZPQk5QHRGlPYGDzlALGUZ4lg3OUDsUbgehRs5QMxdS8gH7TlAOpLLf0jvOUCHp1fKMsQ5QC6QoPgxdjlA+THmriVkOUAldQKaCJs5QKVOQBNhszhAHcnlP6QfOUDJdr6fGt84QBTQRNjwZDlAejarPlcrOUB56SYxCCw5QLivA+eMCDlASFD8GHOHOUCtad5xip44QCBB8WPMbThAI9v5fmoMOkDWxW00gPc5QPOOU3QkBzpA9wZfmExVOkBL6gQ0EWY4QKmkTkATETlAYcPTK2XJOkChZ7Pqc8U6QA4tsp3v5zhAJlMFo5LKOUARNjy9UoY5QN6Th4VakzlADr4wmSoIOUAN4C2QoMg4QFR0JJf/gDlAysNCrWneOUCMuWsJ+YA5QFK4HoXrETlATtGRXP7TOECoV8oyxHE5QNc07zhFxzhAgy9MpgpWOEBd/kP67Vs4QPT91HjpljlAjLlrCflAOUDKVMGopG46QGQ730+NlzpAdy0hH/QsOkBnRGlv8DU6QFafq63YHzlAmN2Th4WaOUD3deCcEfU5QMuhRbbzLTpAoWez6nPlOECHp1fKMiQ6QIiFWtO8AzpA4L4OnDOyOUCDUUmdgOY5QOoENBE2HDpAHqfoSC6POEDWVuwvu4c5QHxhMlUwyjlA2IFzRpTmOEDpSC7/Id04QDBMpgpGZTpAUPwYc9ciOkA/xty1hPw5QP8h/fZ1sDlA1zTvOEWHOkBoImx4emU6QGq8dJMYxDhAt9EA3gJpOUC7Jw8LtaY5QBgmUwWjEjlA0SLb+X7qOEA+eVioNR06QCBB8WPM7TlAT0ATYcPjOEBkO99PjVc5QE5iEFg5BDlAmbuWkA8aOUCL/WX35IE5QIEmwoan1zlA2/l+arxUOEA0orQ3+CI6QLwFEhQ/FjpATfOOU3TkOUCyLm6jAVw4QMdLN4lBADlABTQRNjxtOUBmiGNd3EY5QEw3iUFgtTlAyxDHurh9OUDpt68D5+w6QLRZ9bnaqjpA1CtlGeI4OUDjNhrAWzA6QBkEVg4twjhAZF3cRgMIOUD1SlmGONY5QO/Jw0KtqTlACYofY+76OECGyVTBqPQ4QPmgZ7PqozlAxEKtad5ROUBEi2zn+/k5QL3jFB3JZThAyeU/pN+uOECneccpOmI4QHnpJjEI/DlACKwcWmRbOUAjSnuDLzw5QDMzMzMz0zlAZDvfT40nOUCP5PIf0k85QK7YX3ZPfjlAPSzUmuZtOUB2cRsN4M05QAXFjzF3nThAhslUwagkOkBEaW/whdk5QN9PjZdu8jlAbAn5oGcDO0D+1HjpJnE6QDhnRGlv4DlAJuSDns0qOkAGgZVDi+w5QMxdS8gH3ThAmN2Th4X6OED9h/Tb1wE5QI2XbhKD4DlAjZduEoOAOUAeFmpN8946QNZW7C+7lzlA+Q/pt69TOUCh1jTvOKU5QFtCPujZHDlAEqW9wRd2OECU9gZfmPw4QIiFWtO8gzhAofgx5q4VOUCoNc07TiE6QO7rwDkjmjlAlIeFWtO8OUB5WKg1zfs5QMPTK2UZgjlAumsJ+aDnOUB+HThnRGk5QPfkYaHWpDlAvAUSFD82OUCsi9toAL85QEw3iUFg5TlA46WbxCDQOUDGbTSAt+A4QJYhjnVxazlAB84ZUdp7OUDuWkI+6Nk4QJ+rrdhf1jhAT0ATYcPTOEAyVTAqqRM5QJqZmZmZ2TlAzO7Jw0JNOUClLEMc6yI5QGIQWDm0CDpA+u3rwDnjOUDhC5OpgsE4QEGC4seYWzpA6Gor9pedOUBuNIC3QPI4QCqpE9BEeDpADk+vlGUoOkBgdk8eFro4QHL5D+m3fzpAhslUwaiEOkASpb3BF6Y5QOLplbIMcTlAEce6uI0WOUAAkX77OrA4QHUCmggbzjlAdLUV+8tOOUA7cM6I0q45QBfZzvdT0zlA097gC5MZOkDDZKpgVKI5QILix5i7hjlAeHqlLEO8OUCPU3Qkl684QNcS8kHP1jlAJzEIrBw6OUBhMlUwKik5QMrDQq1pPjlArfpcbcX+OUD+ZffkYdE5QNCzWfW5+jhAPZtVn6tdOkDkg57Nqo84QELPZtXnGjlAXf5D+u3bOEDnHafoSF45QNDVVuwvmzlAqvHSTWJQOUAnMQisHNo4QPOOU3QkhzlApSxDHOvSOEBbQj7o2Tw5QJZDi2znWzlA2V92Tx7mOUCu2F92T945QN5xio7kojlAQxzr4jbaOECYbhKDwOo3QEp7gy9MBjlAOPjCZKrQOEBd/kP67es3QBKDwMqh1ThAS8gHPZt1OEDXEvJBz8Y4QHlYqDXN6zlAKe0NvjAJOkBb07zjFM04QIQNT6+UdTlAaCJseHq1OUCxUGuad6w5QJCg+DHm3jhA5WGh1jTvOUCL/WX35ME5QB/0bFZ9/jhAKVyPwvVIOUDfT42XbqI4QEw3iUFgtTlA5WGh1jSPOUAOT6+UZZg5QA6+MJkqmDlAliGOdXHLOUCF61G4HpU8QHE9CtejMDxAj1N0JJefPEDJdr6fGm87QH/ZPXlY+DxAHOviNhqwPEBzaJHtfC87QBB6Nqs+BzpAgy9MpgoWOkAPC7WmeYc6QJT2Bl+YTDlALv8h/faVOEBuNIC3QNI4QCgPC7Wm+ThAp+hILv/hOEDNO07Rkdw5QPH0SlmG6DhANe84RUdCOUCgibDh6bU4QHqlLEMcyzhAGCZTBaPSOUC8BRIUP2Y6QMDsnjwslDpAqaROQBPhOUCe76fGS6c4QHzysFBrujhArthfdk9OOUCBlUOLbFc5QABvgQTF/zlAgLdAguInOkDpt68D5xw6QLByaJHtDDpAAJF++zpwOkDDZKpgVAI6QNk9eViohTpARUdy+Q9JOkC2hHzQs3k5QPs6cM6IQjlAHVpkO9+/OUCMSuoENME5QPkx5q4lxDhAK4cW2c4nOkCqYFRSJ2A7QISezarPVTtAarx0kxi0OUDnjCjtDU46QHL5D+m3HztA7Q2+MJnaOkCGyVTBqGQ6QH2utmJ/CTpAmN2Th4UqOkDc14FzRiQ6QEaU9gZfWDlAV+wvuyf/OUA8TtGRXO45QPmgZ7PqkzlAZRniWBe3OUBVMCqpEwA6QLyWkA96RjlAs3vysFD7OUAQ6bevA7c5QN5xio7k0jlAgy9MpgoGOUC30QDeAik5QN4CCYofwzlANIC3QILSOUBj7lpCPig6QJ5eKcsQVzlA845TdCTXOkA5RUdy+c85QPRsVn2uVjhAWDm0yHZuOUBI4XoUrpc5QPAWSFD8mDhAF7fRAN5COUDEQq1p3nE4QHQkl/+QbjhA9ihcj8KlOEAxmSoYleQ4QJhMFYxKmjhAX5hMFYyaOUDQs1n1uQo5QKjGSzeJETpA4zYawFuAOkC94xQdyaU4QK+UZYhjvThAE/JBz2blOECSy39Ivw05QOkmMQisPDlAXCBB8WO8OUBn1edqK5Y5QOjZrPpcPTpA3NeBc0ZUOUBQ/Bhz1wI6QO/Jw0KtGTpAB84ZUdq7OUB8YTJVMMo5QJXUCWgi7DhAufyH9NvHOUBseHqlLJM5QBTQRNjwpDlA+n5qvHSjOUA0ETY8vcI5QBsN4C2QIDlArfpcbcXuOECDUUmdgAY6QFOWIY51YTlA4QuTqYJxOUBGlPYGX3g5QHGsi9togDhAPujZrPpcOkBF2PD0Sqk4QHqlLEMc+zlAzO7Jw0LtOEDSAN4CCRo5QDarPldbMTlA7Z48LNSqOUARx7q4jZY5QB6n6EguzzlAIGPuWkK+OUAc6+I2GiA7QF+YTBWM2jhAqDXNO05ROEC7Jw8LtfY4QPXb14Fz9jhAqDXNO05hOUC28/3UeOk5QOCcEaW9MTlA0gDeAgk6OUBd/kP67Ys6QC0hH/RsljhARPrt68DpOEB7gy9Mpro5QF66SQwCuzlAK/aX3ZO3OUCitDf4wpQ5QFfsL7snfzlAj8L1KFyfOED8GHPXEkI6QCGwcmiRrTlAlPYGX5jMOEBoImx4ekU6QF1txf6ySzlA0NVW7C9LOUCu2F92Tz45QGaIY13cpjlAGXPXEvKBOUCJQWDl0OI5QOoENBE2TDlA9bnaiv2lOUDxY8xdS2g5QO2ePCzUCjlAnYAmwob3OEDLoUW28w05QK36XG3F7jhASgwCK4d2OUCkcD0K19M4QDVeukkMkjlAqDXNO07BOUDOiNLe4Bs6QPd14JwRZTlA9pfdk4d1OUCQMXctIX85QJ0Rpb3BxzhAWDm0yHb+OEADCYofY944QCJseHqlTDlAJlMFo5L6OEBYqDXNO645QJjdk4eFGjlAtMh2vp8KOkAFNBE2PE06QDqSy39I3zpAnzws1JrGOkAdOGdEaa86QIxK6gQ08ThAjErqBDTxOED2KFyPwgU5QCDSb18HDjlAwhcmUwVzOUC7uI0G8OY5QNCzWfW5ujlAAAAAAABgOEBn1edqKwY5QHsUrkfhWjlAqaROQBMhOkAcfGEyVdA4QBx8YTJV0DhAaLPqc7VVOUDkg57Nqn84QBWMSuoEJDlANBE2PL3yOEC4rwPnjCg5QHPXEvJBjzlALNSa5h0HOUAxmSoYlXQ5QE5iEFg55DlA6gQ0ETZcOUCaCBueXok5QIBIv30d+DhANqs+V1txOUAAkX77OpA5QNiBc0aUdjhAL26jAbyFOEDKw0KtaQ46QHicoiO5XDpAfoy5awnZOECneccpOhI5QDsBTYQNDztAio7k8h/yOUAgQfFjzA05QPd14JwR9TlAu7iNBvAWOkDwhclUwTg5QN9PjZduQjlAMEymCkYFOUAFo5I6AR05QLHh6ZWyTDlAZmZmZmYWOUC5jQbwFsg5QA+cM6K0BzpARPrt68AZOUDD9Shcj3I5QOviNhrAOzlA9bnaiv3lOECgibDh6WU5QLG/7J48fDlA3EYDeAukOEBTliGOdQE6QFMFo5I6cTlAUWuad5xiOUBPHhZqTTM6QJ88LNSaVjpARUdy+Q/pOUCKsOHpleI4QHBfB84ZITlAbjSAt0DSOEA/V1uxvxw5QI2XbhKDcDhAayv2l90DOUAwKqkT0FQ4QPvL7snDAjlAMZkqGJVkOEDy0k1iEBg5QPVKWYY4FjlAIo51cRvtOEDf4AuTqbI5QHE9CtejQDhAkst/SL89OkBOYhBYOdQ4QGWqYFRSxzhAI9v5fmrMOEAMk6mCUSk6QET67evAaTpA3pOHhVpzOUBqvHSTGGQ5QIj029eBozlA1QloImy4OUBGtvP91Ig6QIhjXdxG4zhAF9nO91PDOUAT8kHPZsU4QBueXinLsDhABOeMKO39OUC9UpYhjgU6QMBbIEHxQzpAat5xio7UOUDecYqO5KI5QMuhRbbzDTlA9ihcj8I1OkBfKcsQxxo5QMHKoUW28zdA1QloImxIOUBZhjjWxQ06QLbz/dR4GTpAe4MvTKYaOkA9CtejcP04QE0VjErq1DlA3SQGgZXDOUCneccpOoI5QC7/If32xThAufyH9NunOUBfB84ZUVo6QJHtfD81XjlA/Bhz1xKCOEBO0ZFc/sM5QOPHmLuWgDlAKe0NvjCJOkAYldQJaAI6QNv5fmq8pDhAbxKDwMqxOUC3Yn/ZPYk5QGfV52ordjlAYOXQItsJOkAJG55eKTs7QNCzWfW56jhAokW28/2UOEA8vVKWIS45QG6jAbwFgjlALGUZ4linOEAldQKaCOs4QB04Z0RpLzlA097gC5N5OUAxCKwcWgQ5QGQ730+N5zhA2V92Tx72OEDmP6Tfvo44QCV1ApoIizpAodY07zilOkBQjZduEhM7QAkbnl4puzpA8rBQa5qnOEBBguLHmLs6QIqO5PIfAjlAJzEIrBzKOUCASL99Hcg4QBdIUPwYUzlA097gC5MJOkBmiGNd3GY6QDBMpgpG1TlA2PD0SllWOUBDrWnecfo4QDC7Jw8LNTlAH/RsVn3+OEDcaABvgXQ5QJJc/kP6fTlAguLHmLsGOUAJ+aBnsxo5QIxK6gQ04TpANjy9UpbROkC3Yn/ZPVk6QFR0JJf/wDpAowG8BRIkOkBZhjjWxQ06QKVOQBNhAzpAJCh+jLmrOEAOvjCZKmg5QB3J5T+k/zhAx7q4jQYAOUALRiV1Avo5QL1SliGOxTlAZ0Rpb/CVOUAFxY8xd105QHrHKTqSKzlAseHplbJcOUBQ/Bhz19I5QIGVQ4tsBzpAkQ96Nqs+OkDRkVz+Q5o6QGuad5yiczpAcT0K16OAOkAeFmpN8/44QP7UeOkmETpAmbuWkA+6OUDOGVHaGxw6QGuad5yiYzlAzTtO0ZGMOUCmCkYldYI5QJhMFYxKGjpAWDm0yHZuOkAGEhQ/xtw6QEvIBz2bVTlAZohjXdwWOUCamZmZmak4QAyTqYJRyThAswxxrIvLOUCCc0aU9uY5QBdIUPwYAzpAKjqSy38oOkDD9Shcj0I6QCegibDhmTlAqoJRSZ3AOUDKw0KtaV45QHgLJCh+TDlAw/UoXI+COUAwKqkT0BQ5QHPXEvJBPzlA5j+k375eOUD6fmq8dAM5QDm0yHa+vzhArrZif9ldOUBJnYAmwpY5QFUwKqkToDlA9bnaiv0FOkAf9GxWfQ46QHicoiO53DlApN++DpxTOUB4eqUsQ9w5QIGVQ4tsVzlAi2zn+6lxOUDn+6nx0q05QMRCrWneITlAMzMzMzNjOUCKsOHplXI6QMWPMXctATpA8kHPZtUnOkCEns2qzwU6QHo2qz5XCzpAJQaBlUMbOkBWfa62Yh84QN21hHzQMzhADeAtkKA4OEBHA3gLJMg4QARWDi2yfTpARIts5/vpOEByio7k8t84QPYoXI/CRTlAdEaU9ga/OEC1N/jCZAo6QDSitDf4AjpAj+TyH9K/OkA+eVioNb06QKCJsOHphTlAOUVHcvnfOEAZ4lgXtwE5QIZa07zjZDhAbjSAt0CyOkA5tMh2vj86QJHtfD81vjlAQYLix5gbOkCcoiO5/Fc6QIMvTKYKJjpAbxKDwMrhOECfzarP1cY4QBgmUwWj0jhAxyk6kst/OEAyVTAqqVM4QAK8BRIU/zhAWmQ730+tOUBLyAc9m1U5QPhT46WbBDlAs3vysFDbOEDgnBGlvdE4QNzXgXNGdDhAvVKWIY4FOUDQRNjw9Bo5QPYoXI/CJTlA001iEFhJOUCgGi/dJAY5QPH0SlmGiDlAQYLix5jLOUBg5dAi20k6QMBbIEHxszhAYqHWNO8YOkAj2/l+ajw6QMx/SL997TlAYOXQItv5OEDMXUvIB105QLhAguLHCDpAK4cW2c7HOECjI7n8h7Q4QKMjufyHtDhA4zYawFtAOkBpAG+BBMU5QClcj8L1KDlAvjCZKhi1OUAkufyH9Hs5QAU0ETY87TlAvVKWIY4VOkCKjuTyHzI5QLaEfNCzyTlAP8bctYRsOECsrdhfdj84QK+UZYhjbThASFD8GHNnOUA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"sigma\":{\"__ndarray__\":\"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Application\",\"version\":\"2.3.3\"}};\n", " var render_items = [{\"docid\":\"4c4e7786-6620-4cd1-900e-b58dfa4372ea\",\"root_ids\":[\"5124\"],\"roots\":{\"5124\":\"2912bc8a-7acd-4e08-b625-3c3d1507d347\"}}];\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": "5124" } }, "output_type": "display_data" } ], "source": [ "k = df_mean[\"D\"].values\n", "q = df_mean[\"F\"].values\n", "\n", "N_ppc = 200\n", "k_ppc = np.linspace(0, k.max(), N_ppc)\n", "data = {\n", " \"N\": len(k),\n", " \"k\": k,\n", " \"q\": q,\n", " \"N_ppc\": N_ppc,\n", " \"k_ppc\": k_ppc,\n", "}\n", "\n", "sm = cmdstanpy.CmdStanModel(stan_file=\"ant_traffic_model_greensheilds.stan\")\n", "\n", "samples = sm.sample(data=data, iter_sampling=1000, chains=4)\n", "\n", "samples = az.from_cmdstanpy(posterior=samples, posterior_predictive=[\"q_ppc\"])\n", "\n", "bokeh.io.show(\n", " bebi103.viz.corner(\n", " samples, parameters=[\"k_j\", \"v_f\", \"sigma\"], xtick_label_orientation=np.pi / 4\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These parameter estimates look totally different! $v_f$ is pretty similar, which is a good sign, and makes sense for an ant: ~ 1-2 cm per second as max speed. This is also consistent with the value reported from a different experiment for speed of an ant alone on a bridge. Good on that front! For $k_j$, the value given here is very different. Using the averaging approach much more heavily weighs the large data points, which results in model seeming to resolve this parameter, i.e. it indicates that we have sufficient information to see the jam density for the ants. However, the model then rather badly overshoots the early parts of the data, and undershoots in the center of the graph. The issue here is that the weighting leads to a model that explains much less of the data, though captures the upper points better (see posterior predictive below). This is a potential bias for the fit. However, this model is evidently a pretty bad one for this data, so much of the pathology is due to that mismatch. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "q_ppc = samples.posterior_predictive['q_ppc'].stack(\n", " {\"sample\": (\"chain\", \"draw\")}\n", ").transpose(\"sample\", \"q_ppc_dim_0\")\n", "\n", "p = bebi103.viz.predictive_regression(\n", " q_ppc,\n", " samples_x=k_ppc,\n", " percentiles=[30, 50, 70, 99],\n", " data=np.vstack((k, q)).transpose(),\n", " y_axis_label='ant flow, q [ant/cm/s]',\n", " x_range=[0, k.max()],\n", ")\n", "\n", "bokeh.io.export_png(p, filename=\"ppc_2.png\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![Second posterior predictive check](ppc_2.png)\n", "\n", "Building the other models will also give an idea of what is going on with the data, and what underlying generative process is at play. Soon, we will go into model selection, which will give a principled way of calling which model performs best to capture our data with the fewest needed parameters. " ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "bebi103.stan.clean_cmdstan()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 18, "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", "cmdstanpy : 1.0.0\n", "arviz : 0.11.4\n", "bokeh : 2.3.3\n", "bebi103 : 0.1.10\n", "iqplot : 0.2.4\n", "jupyterlab: 3.2.1\n", "datashader: 0.13.0\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,pandas,cmdstanpy,arviz,bokeh,bebi103,iqplot,jupyterlab,datashader\n", "bebi103.stan.clean_cmdstan()" ] } ], "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 }