Victor Phan
5396 lines
1.1 MiB
Plaintext
5396 lines
1.1 MiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "0cb933a1",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
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"*[data-root-id] > * {\n",
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" box-sizing: border-box;\n",
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" font-family: var(--jp-ui-font-family);\n",
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" font-size: var(--jp-ui-font-size1);\n",
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" color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
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"}\n",
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"\n",
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"/* Override VSCode background color */\n",
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".cell-output-ipywidget-background:has(\n",
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" > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
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" ),\n",
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".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
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" background-color: transparent !important;\n",
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"}\n",
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"</style>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/javascript": [
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"(function(root) {\n",
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" function now() {\n",
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" return new Date();\n",
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" }\n",
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"\n",
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" const force = true;\n",
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" const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
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" const reloading = false;\n",
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" const Bokeh = root.Bokeh;\n",
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"\n",
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" // Set a timeout for this load but only if we are not already initializing\n",
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" if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
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" root._bokeh_timeout = Date.now() + 5000;\n",
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" root._bokeh_failed_load = false;\n",
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" }\n",
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"\n",
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" function run_callbacks() {\n",
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" try {\n",
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" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
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" if (callback != null)\n",
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" callback();\n",
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" });\n",
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" } finally {\n",
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" delete root._bokeh_onload_callbacks;\n",
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" }\n",
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" console.debug(\"Bokeh: all callbacks have finished\");\n",
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" }\n",
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"\n",
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" function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
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" if (css_urls == null) css_urls = [];\n",
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" if (js_urls == null) js_urls = [];\n",
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" if (js_modules == null) js_modules = [];\n",
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" if (js_exports == null) js_exports = {};\n",
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"\n",
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" root._bokeh_onload_callbacks.push(callback);\n",
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"\n",
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" if (root._bokeh_is_loading > 0) {\n",
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" // Don't load bokeh if it is still initializing\n",
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" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
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" return null;\n",
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" } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
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" // There is nothing to load\n",
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" run_callbacks();\n",
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" return null;\n",
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" }\n",
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"\n",
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" function on_load() {\n",
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" root._bokeh_is_loading--;\n",
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" if (root._bokeh_is_loading === 0) {\n",
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" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
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" run_callbacks()\n",
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" }\n",
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" }\n",
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" window._bokeh_on_load = on_load\n",
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"\n",
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" function on_error(e) {\n",
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" const src_el = e.srcElement\n",
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" console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
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" }\n",
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"\n",
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" const skip = [];\n",
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" if (window.requirejs) {\n",
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" window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
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" root._bokeh_is_loading = css_urls.length + 0;\n",
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" } else {\n",
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" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
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" }\n",
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"\n",
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" const existing_stylesheets = []\n",
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" const links = document.getElementsByTagName('link')\n",
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" for (let i = 0; i < links.length; i++) {\n",
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" const link = links[i]\n",
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" if (link.href != null) {\n",
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" existing_stylesheets.push(link.href)\n",
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" }\n",
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" }\n",
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" for (let i = 0; i < css_urls.length; i++) {\n",
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" const url = css_urls[i];\n",
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" const escaped = encodeURI(url)\n",
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" if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
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" on_load()\n",
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" continue;\n",
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" }\n",
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" const element = document.createElement(\"link\");\n",
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" element.onload = on_load;\n",
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" element.onerror = on_error;\n",
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" element.rel = \"stylesheet\";\n",
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" element.type = \"text/css\";\n",
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" element.href = url;\n",
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" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
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" document.body.appendChild(element);\n",
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" } var existing_scripts = []\n",
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" const scripts = document.getElementsByTagName('script')\n",
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" for (let i = 0; i < scripts.length; i++) {\n",
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" var script = scripts[i]\n",
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" if (script.src != null) {\n",
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" existing_scripts.push(script.src)\n",
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" }\n",
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" }\n",
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" for (let i = 0; i < js_urls.length; i++) {\n",
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" const url = js_urls[i];\n",
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" const escaped = encodeURI(url)\n",
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" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
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" if (!window.requirejs) {\n",
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" on_load();\n",
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" }\n",
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" continue;\n",
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" }\n",
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" const element = document.createElement('script');\n",
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" element.onload = on_load;\n",
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" element.onerror = on_error;\n",
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" element.async = false;\n",
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" element.src = url;\n",
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" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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" document.head.appendChild(element);\n",
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" }\n",
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" for (let i = 0; i < js_modules.length; i++) {\n",
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" const url = js_modules[i];\n",
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" const escaped = encodeURI(url)\n",
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" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
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" if (!window.requirejs) {\n",
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" on_load();\n",
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" }\n",
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" continue;\n",
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" }\n",
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" var element = document.createElement('script');\n",
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" element.onload = on_load;\n",
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" element.onerror = on_error;\n",
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" element.async = false;\n",
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" element.src = url;\n",
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" element.type = \"module\";\n",
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" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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" document.head.appendChild(element);\n",
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" }\n",
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" for (const name in js_exports) {\n",
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" const url = js_exports[name];\n",
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" const escaped = encodeURI(url)\n",
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" if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
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" if (!window.requirejs) {\n",
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" on_load();\n",
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" }\n",
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" continue;\n",
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" }\n",
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" var element = document.createElement('script');\n",
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" element.onerror = on_error;\n",
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" element.async = false;\n",
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" element.type = \"module\";\n",
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" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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" element.textContent = `\n",
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" import ${name} from \"${url}\"\n",
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" window.${name} = ${name}\n",
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" window._bokeh_on_load()\n",
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" `\n",
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" document.head.appendChild(element);\n",
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" }\n",
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" if (!js_urls.length && !js_modules.length) {\n",
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" on_load()\n",
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" }\n",
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" };\n",
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"\n",
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" function inject_raw_css(css) {\n",
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" const element = document.createElement(\"style\");\n",
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" element.appendChild(document.createTextNode(css));\n",
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" document.body.appendChild(element);\n",
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" }\n",
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"\n",
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" const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.6.0.min.js\", \"https://cdn.holoviz.org/panel/1.5.3/dist/panel.min.js\"];\n",
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" const js_modules = [];\n",
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" const js_exports = {};\n",
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" const css_urls = [];\n",
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" const inline_js = [ function(Bokeh) {\n",
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" Bokeh.set_log_level(\"info\");\n",
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" },\n",
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"function(Bokeh) {} // ensure no trailing comma for IE\n",
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" ];\n",
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"\n",
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" function run_inline_js() {\n",
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" if ((root.Bokeh !== undefined) || (force === true)) {\n",
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" for (let i = 0; i < inline_js.length; i++) {\n",
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" try {\n",
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" inline_js[i].call(root, root.Bokeh);\n",
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" } catch(e) {\n",
|
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" if (!reloading) {\n",
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" throw e;\n",
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" }\n",
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" }\n",
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" }\n",
|
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" // Cache old bokeh versions\n",
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" if (Bokeh != undefined && !reloading) {\n",
|
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" var NewBokeh = root.Bokeh;\n",
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" if (Bokeh.versions === undefined) {\n",
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" Bokeh.versions = new Map();\n",
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" }\n",
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" if (NewBokeh.version !== Bokeh.version) {\n",
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" Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
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" }\n",
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" root.Bokeh = Bokeh;\n",
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" }\n",
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" } else if (Date.now() < root._bokeh_timeout) {\n",
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" setTimeout(run_inline_js, 100);\n",
|
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" } else if (!root._bokeh_failed_load) {\n",
|
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" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
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" root._bokeh_failed_load = true;\n",
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" }\n",
|
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" root._bokeh_is_initializing = false\n",
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" }\n",
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"\n",
|
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" function load_or_wait() {\n",
|
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" // Implement a backoff loop that tries to ensure we do not load multiple\n",
|
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" // versions of Bokeh and its dependencies at the same time.\n",
|
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" // In recent versions we use the root._bokeh_is_initializing flag\n",
|
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" // to determine whether there is an ongoing attempt to initialize\n",
|
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" // bokeh, however for backward compatibility we also try to ensure\n",
|
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" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
|
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" // before older versions are fully initialized.\n",
|
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" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
|
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" // If the timeout and bokeh was not successfully loaded we reset\n",
|
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" // everything and try loading again\n",
|
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" root._bokeh_timeout = Date.now() + 5000;\n",
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" root._bokeh_is_initializing = false;\n",
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" root._bokeh_onload_callbacks = undefined;\n",
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" root._bokeh_is_loading = 0\n",
|
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" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
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" load_or_wait();\n",
|
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" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
|
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" setTimeout(load_or_wait, 100);\n",
|
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" } else {\n",
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" root._bokeh_is_initializing = true\n",
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" root._bokeh_onload_callbacks = []\n",
|
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" const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
|
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" if (!reloading && !bokeh_loaded) {\n",
|
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" if (root.Bokeh) {\n",
|
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" root.Bokeh = undefined;\n",
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" }\n",
|
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" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
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" }\n",
|
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" load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
|
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" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
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" run_inline_js();\n",
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" });\n",
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" }\n",
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" }\n",
|
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" // Give older versions of the autoload script a head-start to ensure\n",
|
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" // they initialize before we start loading newer version.\n",
|
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" setTimeout(load_or_wait, 100)\n",
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"}(window));"
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],
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"application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = false;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.6.0.min.js\", \"https://cdn.holoviz.org/panel/1.5.3/dist/panel.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n var NewBokeh = root.Bokeh;\n if (Bokeh.versions === undefined) {\n Bokeh.versions = new Map();\n }\n if (NewBokeh.version !== Bokeh.version) {\n Bokeh.versions.set(NewBokeh.version, NewBokeh)\n }\n root.Bokeh = Bokeh;\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n if (!reloading && !bokeh_loaded) {\n if (root.Bokeh) {\n root.Bokeh = undefined;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"\n",
|
|
"if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
|
|
" window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
" function JupyterCommManager() {\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" comm_manager.register_target(comm_id, function(comm) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" });\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" });\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" console.log(message)\n",
|
|
" var content = {data: message.data, comm_id};\n",
|
|
" var buffers = []\n",
|
|
" for (var buffer of message.buffers || []) {\n",
|
|
" buffers.push(new DataView(buffer))\n",
|
|
" }\n",
|
|
" var metadata = message.metadata || {};\n",
|
|
" var msg = {content, buffers, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" })\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (comm_id in window.PyViz.comms) {\n",
|
|
" return window.PyViz.comms[comm_id];\n",
|
|
" } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" }\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
|
|
" comm.open();\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" }\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
|
|
" comm_promise.then((comm) => {\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" if (msg_handler) {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" var content = {data: message.data};\n",
|
|
" var metadata = message.metadata || {comm_id};\n",
|
|
" var msg = {content, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" }) \n",
|
|
" var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
|
|
" return comm_promise.then((comm) => {\n",
|
|
" comm.send(data, metadata, buffers, disposeOnDone);\n",
|
|
" });\n",
|
|
" };\n",
|
|
" var comm = {\n",
|
|
" send: sendClosure\n",
|
|
" };\n",
|
|
" }\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" return comm;\n",
|
|
" }\n",
|
|
" window.PyViz.comm_manager = new JupyterCommManager();\n",
|
|
" \n",
|
|
"\n",
|
|
"\n",
|
|
"var JS_MIME_TYPE = 'application/javascript';\n",
|
|
"var HTML_MIME_TYPE = 'text/html';\n",
|
|
"var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
|
|
"var CLASS_NAME = 'output';\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Render data to the DOM node\n",
|
|
" */\n",
|
|
"function render(props, node) {\n",
|
|
" var div = document.createElement(\"div\");\n",
|
|
" var script = document.createElement(\"script\");\n",
|
|
" node.appendChild(div);\n",
|
|
" node.appendChild(script);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when a new output is added\n",
|
|
" */\n",
|
|
"function handle_add_output(event, handle) {\n",
|
|
" var output_area = handle.output_area;\n",
|
|
" var output = handle.output;\n",
|
|
" if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
|
|
" return\n",
|
|
" }\n",
|
|
" var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
|
|
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
|
|
" if (id !== undefined) {\n",
|
|
" var nchildren = toinsert.length;\n",
|
|
" var html_node = toinsert[nchildren-1].children[0];\n",
|
|
" html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var scripts = [];\n",
|
|
" var nodelist = html_node.querySelectorAll(\"script\");\n",
|
|
" for (var i in nodelist) {\n",
|
|
" if (nodelist.hasOwnProperty(i)) {\n",
|
|
" scripts.push(nodelist[i])\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" scripts.forEach( function (oldScript) {\n",
|
|
" var newScript = document.createElement(\"script\");\n",
|
|
" var attrs = [];\n",
|
|
" var nodemap = oldScript.attributes;\n",
|
|
" for (var j in nodemap) {\n",
|
|
" if (nodemap.hasOwnProperty(j)) {\n",
|
|
" attrs.push(nodemap[j])\n",
|
|
" }\n",
|
|
" }\n",
|
|
" attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
|
|
" newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
|
|
" oldScript.parentNode.replaceChild(newScript, oldScript);\n",
|
|
" });\n",
|
|
" if (JS_MIME_TYPE in output.data) {\n",
|
|
" toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
|
|
" }\n",
|
|
" output_area._hv_plot_id = id;\n",
|
|
" if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
|
|
" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
|
|
" } else {\n",
|
|
" window.PyViz.plot_index[id] = null;\n",
|
|
" }\n",
|
|
" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
|
|
" var bk_div = document.createElement(\"div\");\n",
|
|
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var script_attrs = bk_div.children[0].attributes;\n",
|
|
" for (var i = 0; i < script_attrs.length; i++) {\n",
|
|
" toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
|
|
" }\n",
|
|
" // store reference to server id on output_area\n",
|
|
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when an output is cleared or removed\n",
|
|
" */\n",
|
|
"function handle_clear_output(event, handle) {\n",
|
|
" var id = handle.cell.output_area._hv_plot_id;\n",
|
|
" var server_id = handle.cell.output_area._bokeh_server_id;\n",
|
|
" if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
|
|
" var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
|
|
" if (server_id !== null) {\n",
|
|
" comm.send({event_type: 'server_delete', 'id': server_id});\n",
|
|
" return;\n",
|
|
" } else if (comm !== null) {\n",
|
|
" comm.send({event_type: 'delete', 'id': id});\n",
|
|
" }\n",
|
|
" delete PyViz.plot_index[id];\n",
|
|
" if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
|
|
" var doc = window.Bokeh.index[id].model.document\n",
|
|
" doc.clear();\n",
|
|
" const i = window.Bokeh.documents.indexOf(doc);\n",
|
|
" if (i > -1) {\n",
|
|
" window.Bokeh.documents.splice(i, 1);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle kernel restart event\n",
|
|
" */\n",
|
|
"function handle_kernel_cleanup(event, handle) {\n",
|
|
" delete PyViz.comms[\"hv-extension-comm\"];\n",
|
|
" window.PyViz.plot_index = {}\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle update_display_data messages\n",
|
|
" */\n",
|
|
"function handle_update_output(event, handle) {\n",
|
|
" handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
|
|
" handle_add_output(event, handle)\n",
|
|
"}\n",
|
|
"\n",
|
|
"function register_renderer(events, OutputArea) {\n",
|
|
" function append_mime(data, metadata, element) {\n",
|
|
" // create a DOM node to render to\n",
|
|
" var toinsert = this.create_output_subarea(\n",
|
|
" metadata,\n",
|
|
" CLASS_NAME,\n",
|
|
" EXEC_MIME_TYPE\n",
|
|
" );\n",
|
|
" this.keyboard_manager.register_events(toinsert);\n",
|
|
" // Render to node\n",
|
|
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
|
|
" render(props, toinsert[0]);\n",
|
|
" element.append(toinsert);\n",
|
|
" return toinsert\n",
|
|
" }\n",
|
|
"\n",
|
|
" events.on('output_added.OutputArea', handle_add_output);\n",
|
|
" events.on('output_updated.OutputArea', handle_update_output);\n",
|
|
" events.on('clear_output.CodeCell', handle_clear_output);\n",
|
|
" events.on('delete.Cell', handle_clear_output);\n",
|
|
" events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
|
|
"\n",
|
|
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
|
|
" safe: true,\n",
|
|
" index: 0\n",
|
|
" });\n",
|
|
"}\n",
|
|
"\n",
|
|
"if (window.Jupyter !== undefined) {\n",
|
|
" try {\n",
|
|
" var events = require('base/js/events');\n",
|
|
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
|
|
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
|
|
" register_renderer(events, OutputArea);\n",
|
|
" }\n",
|
|
" } catch(err) {\n",
|
|
" }\n",
|
|
"}\n"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.holoviews_exec.v0+json": "",
|
|
"text/html": [
|
|
"<div id='p1002'>\n",
|
|
" <div id=\"fa3afae8-b53f-47a0-8e26-bea51101d2f8\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
|
|
"</div>\n",
|
|
"<script type=\"application/javascript\">(function(root) {\n",
|
|
" var docs_json = {\"5cbf4120-e8ca-46c2-b61a-651adb33e05d\":{\"version\":\"3.6.0\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"a7caee17e6f54bf3a4474819bafe0465\",\"client_comm_id\":\"bc3d426afa014041888207d4b1fab7ff\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\"},{\"type\":\"model\",\"name\":\"JSComponent1\"},{\"type\":\"model\",\"name\":\"ReactComponent1\"},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\"},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
|
|
" var render_items = [{\"docid\":\"5cbf4120-e8ca-46c2-b61a-651adb33e05d\",\"roots\":{\"p1002\":\"fa3afae8-b53f-47a0-8e26-bea51101d2f8\"},\"root_ids\":[\"p1002\"]}];\n",
|
|
" var docs = Object.values(docs_json)\n",
|
|
" if (!docs) {\n",
|
|
" return\n",
|
|
" }\n",
|
|
" const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
|
|
" async function embed_document(root) {\n",
|
|
" var Bokeh = get_bokeh(root)\n",
|
|
" await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
|
|
" for (const render_item of render_items) {\n",
|
|
" for (const root_id of render_item.root_ids) {\n",
|
|
"\tconst id_el = document.getElementById(root_id)\n",
|
|
"\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
|
|
"\t const root_el = id_el.children[0]\n",
|
|
"\t root_el.id = root_el.id + '-rendered'\n",
|
|
"\t for (const child of root_el.children) {\n",
|
|
" // Ensure JupyterLab does not capture keyboard shortcuts\n",
|
|
" // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
|
|
"\t child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
|
|
"\t }\n",
|
|
"\t}\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" function get_bokeh(root) {\n",
|
|
" if (root.Bokeh === undefined) {\n",
|
|
" return null\n",
|
|
" } else if (root.Bokeh.version !== py_version) {\n",
|
|
" if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
|
|
"\treturn null\n",
|
|
" }\n",
|
|
" return root.Bokeh.versions.get(py_version);\n",
|
|
" } else if (root.Bokeh.version === py_version) {\n",
|
|
" return root.Bokeh\n",
|
|
" }\n",
|
|
" return null\n",
|
|
" }\n",
|
|
" function is_loaded(root) {\n",
|
|
" var Bokeh = get_bokeh(root)\n",
|
|
" return (Bokeh != null && Bokeh.Panel !== undefined)\n",
|
|
" }\n",
|
|
" if (is_loaded(root)) {\n",
|
|
" embed_document(root);\n",
|
|
" } else {\n",
|
|
" var attempts = 0;\n",
|
|
" var timer = setInterval(function(root) {\n",
|
|
" if (is_loaded(root)) {\n",
|
|
" clearInterval(timer);\n",
|
|
" embed_document(root);\n",
|
|
" } else if (document.readyState == \"complete\") {\n",
|
|
" attempts++;\n",
|
|
" if (attempts > 200) {\n",
|
|
" clearInterval(timer);\n",
|
|
"\t var Bokeh = get_bokeh(root)\n",
|
|
"\t if (Bokeh == null || Bokeh.Panel == null) {\n",
|
|
" console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
|
|
"\t } else {\n",
|
|
"\t console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
|
|
"\t embed_document(root)\n",
|
|
"\t }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }, 25, root)\n",
|
|
" }\n",
|
|
"})(window);</script>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"application/vnd.holoviews_exec.v0+json": {
|
|
"id": "p1002"
|
|
}
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
|
|
"*[data-root-id] > * {\n",
|
|
" box-sizing: border-box;\n",
|
|
" font-family: var(--jp-ui-font-family);\n",
|
|
" font-size: var(--jp-ui-font-size1);\n",
|
|
" color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Override VSCode background color */\n",
|
|
".cell-output-ipywidget-background:has(\n",
|
|
" > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
|
|
" ),\n",
|
|
".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
|
|
" background-color: transparent !important;\n",
|
|
"}\n",
|
|
"</style>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"(function(root) {\n",
|
|
" function now() {\n",
|
|
" return new Date();\n",
|
|
" }\n",
|
|
"\n",
|
|
" const force = false;\n",
|
|
" const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
|
|
" const reloading = true;\n",
|
|
" const Bokeh = root.Bokeh;\n",
|
|
"\n",
|
|
" // Set a timeout for this load but only if we are not already initializing\n",
|
|
" if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_failed_load = false;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function run_callbacks() {\n",
|
|
" try {\n",
|
|
" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
|
|
" if (callback != null)\n",
|
|
" callback();\n",
|
|
" });\n",
|
|
" } finally {\n",
|
|
" delete root._bokeh_onload_callbacks;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: all callbacks have finished\");\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
|
|
" if (css_urls == null) css_urls = [];\n",
|
|
" if (js_urls == null) js_urls = [];\n",
|
|
" if (js_modules == null) js_modules = [];\n",
|
|
" if (js_exports == null) js_exports = {};\n",
|
|
"\n",
|
|
" root._bokeh_onload_callbacks.push(callback);\n",
|
|
"\n",
|
|
" if (root._bokeh_is_loading > 0) {\n",
|
|
" // Don't load bokeh if it is still initializing\n",
|
|
" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
|
|
" return null;\n",
|
|
" } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
|
|
" // There is nothing to load\n",
|
|
" run_callbacks();\n",
|
|
" return null;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function on_load() {\n",
|
|
" root._bokeh_is_loading--;\n",
|
|
" if (root._bokeh_is_loading === 0) {\n",
|
|
" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
|
|
" run_callbacks()\n",
|
|
" }\n",
|
|
" }\n",
|
|
" window._bokeh_on_load = on_load\n",
|
|
"\n",
|
|
" function on_error(e) {\n",
|
|
" const src_el = e.srcElement\n",
|
|
" console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
|
|
" }\n",
|
|
"\n",
|
|
" const skip = [];\n",
|
|
" if (window.requirejs) {\n",
|
|
" window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
|
|
" root._bokeh_is_loading = css_urls.length + 0;\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
|
|
" }\n",
|
|
"\n",
|
|
" const existing_stylesheets = []\n",
|
|
" const links = document.getElementsByTagName('link')\n",
|
|
" for (let i = 0; i < links.length; i++) {\n",
|
|
" const link = links[i]\n",
|
|
" if (link.href != null) {\n",
|
|
" existing_stylesheets.push(link.href)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < css_urls.length; i++) {\n",
|
|
" const url = css_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
|
|
" on_load()\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement(\"link\");\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.rel = \"stylesheet\";\n",
|
|
" element.type = \"text/css\";\n",
|
|
" element.href = url;\n",
|
|
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
|
|
" document.body.appendChild(element);\n",
|
|
" } var existing_scripts = []\n",
|
|
" const scripts = document.getElementsByTagName('script')\n",
|
|
" for (let i = 0; i < scripts.length; i++) {\n",
|
|
" var script = scripts[i]\n",
|
|
" if (script.src != null) {\n",
|
|
" existing_scripts.push(script.src)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_urls.length; i++) {\n",
|
|
" const url = js_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_modules.length; i++) {\n",
|
|
" const url = js_modules[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (const name in js_exports) {\n",
|
|
" const url = js_exports[name];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" element.textContent = `\n",
|
|
" import ${name} from \"${url}\"\n",
|
|
" window.${name} = ${name}\n",
|
|
" window._bokeh_on_load()\n",
|
|
" `\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" if (!js_urls.length && !js_modules.length) {\n",
|
|
" on_load()\n",
|
|
" }\n",
|
|
" };\n",
|
|
"\n",
|
|
" function inject_raw_css(css) {\n",
|
|
" const element = document.createElement(\"style\");\n",
|
|
" element.appendChild(document.createTextNode(css));\n",
|
|
" document.body.appendChild(element);\n",
|
|
" }\n",
|
|
"\n",
|
|
" const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n",
|
|
" const js_modules = [];\n",
|
|
" const js_exports = {};\n",
|
|
" const css_urls = [];\n",
|
|
" const inline_js = [ function(Bokeh) {\n",
|
|
" Bokeh.set_log_level(\"info\");\n",
|
|
" },\n",
|
|
"function(Bokeh) {} // ensure no trailing comma for IE\n",
|
|
" ];\n",
|
|
"\n",
|
|
" function run_inline_js() {\n",
|
|
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
|
|
" for (let i = 0; i < inline_js.length; i++) {\n",
|
|
" try {\n",
|
|
" inline_js[i].call(root, root.Bokeh);\n",
|
|
" } catch(e) {\n",
|
|
" if (!reloading) {\n",
|
|
" throw e;\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Cache old bokeh versions\n",
|
|
" if (Bokeh != undefined && !reloading) {\n",
|
|
" var NewBokeh = root.Bokeh;\n",
|
|
" if (Bokeh.versions === undefined) {\n",
|
|
" Bokeh.versions = new Map();\n",
|
|
" }\n",
|
|
" if (NewBokeh.version !== Bokeh.version) {\n",
|
|
" Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
|
|
" }\n",
|
|
" root.Bokeh = Bokeh;\n",
|
|
" }\n",
|
|
" } else if (Date.now() < root._bokeh_timeout) {\n",
|
|
" setTimeout(run_inline_js, 100);\n",
|
|
" } else if (!root._bokeh_failed_load) {\n",
|
|
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
|
|
" root._bokeh_failed_load = true;\n",
|
|
" }\n",
|
|
" root._bokeh_is_initializing = false\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_or_wait() {\n",
|
|
" // Implement a backoff loop that tries to ensure we do not load multiple\n",
|
|
" // versions of Bokeh and its dependencies at the same time.\n",
|
|
" // In recent versions we use the root._bokeh_is_initializing flag\n",
|
|
" // to determine whether there is an ongoing attempt to initialize\n",
|
|
" // bokeh, however for backward compatibility we also try to ensure\n",
|
|
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
|
|
" // before older versions are fully initialized.\n",
|
|
" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
|
|
" // If the timeout and bokeh was not successfully loaded we reset\n",
|
|
" // everything and try loading again\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_is_initializing = false;\n",
|
|
" root._bokeh_onload_callbacks = undefined;\n",
|
|
" root._bokeh_is_loading = 0\n",
|
|
" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
|
|
" load_or_wait();\n",
|
|
" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
|
|
" setTimeout(load_or_wait, 100);\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_initializing = true\n",
|
|
" root._bokeh_onload_callbacks = []\n",
|
|
" const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
|
|
" if (!reloading && !bokeh_loaded) {\n",
|
|
" if (root.Bokeh) {\n",
|
|
" root.Bokeh = undefined;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
|
|
" }\n",
|
|
" load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
|
|
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
|
|
" run_inline_js();\n",
|
|
" });\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Give older versions of the autoload script a head-start to ensure\n",
|
|
" // they initialize before we start loading newer version.\n",
|
|
" setTimeout(load_or_wait, 100)\n",
|
|
"}(window));"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n var NewBokeh = root.Bokeh;\n if (Bokeh.versions === undefined) {\n Bokeh.versions = new Map();\n }\n if (NewBokeh.version !== Bokeh.version) {\n Bokeh.versions.set(NewBokeh.version, NewBokeh)\n }\n root.Bokeh = Bokeh;\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n if (!reloading && !bokeh_loaded) {\n if (root.Bokeh) {\n root.Bokeh = undefined;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"\n",
|
|
"if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
|
|
" window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
" function JupyterCommManager() {\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" comm_manager.register_target(comm_id, function(comm) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" });\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" });\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" console.log(message)\n",
|
|
" var content = {data: message.data, comm_id};\n",
|
|
" var buffers = []\n",
|
|
" for (var buffer of message.buffers || []) {\n",
|
|
" buffers.push(new DataView(buffer))\n",
|
|
" }\n",
|
|
" var metadata = message.metadata || {};\n",
|
|
" var msg = {content, buffers, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" })\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (comm_id in window.PyViz.comms) {\n",
|
|
" return window.PyViz.comms[comm_id];\n",
|
|
" } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" }\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
|
|
" comm.open();\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" }\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
|
|
" comm_promise.then((comm) => {\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" if (msg_handler) {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" var content = {data: message.data};\n",
|
|
" var metadata = message.metadata || {comm_id};\n",
|
|
" var msg = {content, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" }) \n",
|
|
" var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
|
|
" return comm_promise.then((comm) => {\n",
|
|
" comm.send(data, metadata, buffers, disposeOnDone);\n",
|
|
" });\n",
|
|
" };\n",
|
|
" var comm = {\n",
|
|
" send: sendClosure\n",
|
|
" };\n",
|
|
" }\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" return comm;\n",
|
|
" }\n",
|
|
" window.PyViz.comm_manager = new JupyterCommManager();\n",
|
|
" \n",
|
|
"\n",
|
|
"\n",
|
|
"var JS_MIME_TYPE = 'application/javascript';\n",
|
|
"var HTML_MIME_TYPE = 'text/html';\n",
|
|
"var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
|
|
"var CLASS_NAME = 'output';\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Render data to the DOM node\n",
|
|
" */\n",
|
|
"function render(props, node) {\n",
|
|
" var div = document.createElement(\"div\");\n",
|
|
" var script = document.createElement(\"script\");\n",
|
|
" node.appendChild(div);\n",
|
|
" node.appendChild(script);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when a new output is added\n",
|
|
" */\n",
|
|
"function handle_add_output(event, handle) {\n",
|
|
" var output_area = handle.output_area;\n",
|
|
" var output = handle.output;\n",
|
|
" if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
|
|
" return\n",
|
|
" }\n",
|
|
" var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
|
|
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
|
|
" if (id !== undefined) {\n",
|
|
" var nchildren = toinsert.length;\n",
|
|
" var html_node = toinsert[nchildren-1].children[0];\n",
|
|
" html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var scripts = [];\n",
|
|
" var nodelist = html_node.querySelectorAll(\"script\");\n",
|
|
" for (var i in nodelist) {\n",
|
|
" if (nodelist.hasOwnProperty(i)) {\n",
|
|
" scripts.push(nodelist[i])\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" scripts.forEach( function (oldScript) {\n",
|
|
" var newScript = document.createElement(\"script\");\n",
|
|
" var attrs = [];\n",
|
|
" var nodemap = oldScript.attributes;\n",
|
|
" for (var j in nodemap) {\n",
|
|
" if (nodemap.hasOwnProperty(j)) {\n",
|
|
" attrs.push(nodemap[j])\n",
|
|
" }\n",
|
|
" }\n",
|
|
" attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
|
|
" newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
|
|
" oldScript.parentNode.replaceChild(newScript, oldScript);\n",
|
|
" });\n",
|
|
" if (JS_MIME_TYPE in output.data) {\n",
|
|
" toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
|
|
" }\n",
|
|
" output_area._hv_plot_id = id;\n",
|
|
" if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
|
|
" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
|
|
" } else {\n",
|
|
" window.PyViz.plot_index[id] = null;\n",
|
|
" }\n",
|
|
" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
|
|
" var bk_div = document.createElement(\"div\");\n",
|
|
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var script_attrs = bk_div.children[0].attributes;\n",
|
|
" for (var i = 0; i < script_attrs.length; i++) {\n",
|
|
" toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
|
|
" }\n",
|
|
" // store reference to server id on output_area\n",
|
|
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when an output is cleared or removed\n",
|
|
" */\n",
|
|
"function handle_clear_output(event, handle) {\n",
|
|
" var id = handle.cell.output_area._hv_plot_id;\n",
|
|
" var server_id = handle.cell.output_area._bokeh_server_id;\n",
|
|
" if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
|
|
" var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
|
|
" if (server_id !== null) {\n",
|
|
" comm.send({event_type: 'server_delete', 'id': server_id});\n",
|
|
" return;\n",
|
|
" } else if (comm !== null) {\n",
|
|
" comm.send({event_type: 'delete', 'id': id});\n",
|
|
" }\n",
|
|
" delete PyViz.plot_index[id];\n",
|
|
" if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
|
|
" var doc = window.Bokeh.index[id].model.document\n",
|
|
" doc.clear();\n",
|
|
" const i = window.Bokeh.documents.indexOf(doc);\n",
|
|
" if (i > -1) {\n",
|
|
" window.Bokeh.documents.splice(i, 1);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle kernel restart event\n",
|
|
" */\n",
|
|
"function handle_kernel_cleanup(event, handle) {\n",
|
|
" delete PyViz.comms[\"hv-extension-comm\"];\n",
|
|
" window.PyViz.plot_index = {}\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle update_display_data messages\n",
|
|
" */\n",
|
|
"function handle_update_output(event, handle) {\n",
|
|
" handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
|
|
" handle_add_output(event, handle)\n",
|
|
"}\n",
|
|
"\n",
|
|
"function register_renderer(events, OutputArea) {\n",
|
|
" function append_mime(data, metadata, element) {\n",
|
|
" // create a DOM node to render to\n",
|
|
" var toinsert = this.create_output_subarea(\n",
|
|
" metadata,\n",
|
|
" CLASS_NAME,\n",
|
|
" EXEC_MIME_TYPE\n",
|
|
" );\n",
|
|
" this.keyboard_manager.register_events(toinsert);\n",
|
|
" // Render to node\n",
|
|
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
|
|
" render(props, toinsert[0]);\n",
|
|
" element.append(toinsert);\n",
|
|
" return toinsert\n",
|
|
" }\n",
|
|
"\n",
|
|
" events.on('output_added.OutputArea', handle_add_output);\n",
|
|
" events.on('output_updated.OutputArea', handle_update_output);\n",
|
|
" events.on('clear_output.CodeCell', handle_clear_output);\n",
|
|
" events.on('delete.Cell', handle_clear_output);\n",
|
|
" events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
|
|
"\n",
|
|
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
|
|
" safe: true,\n",
|
|
" index: 0\n",
|
|
" });\n",
|
|
"}\n",
|
|
"\n",
|
|
"if (window.Jupyter !== undefined) {\n",
|
|
" try {\n",
|
|
" var events = require('base/js/events');\n",
|
|
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
|
|
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
|
|
" register_renderer(events, OutputArea);\n",
|
|
" }\n",
|
|
" } catch(err) {\n",
|
|
" }\n",
|
|
"}\n"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
|
|
"*[data-root-id] > * {\n",
|
|
" box-sizing: border-box;\n",
|
|
" font-family: var(--jp-ui-font-family);\n",
|
|
" font-size: var(--jp-ui-font-size1);\n",
|
|
" color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Override VSCode background color */\n",
|
|
".cell-output-ipywidget-background:has(\n",
|
|
" > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
|
|
" ),\n",
|
|
".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
|
|
" background-color: transparent !important;\n",
|
|
"}\n",
|
|
"</style>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"(function(root) {\n",
|
|
" function now() {\n",
|
|
" return new Date();\n",
|
|
" }\n",
|
|
"\n",
|
|
" const force = false;\n",
|
|
" const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
|
|
" const reloading = true;\n",
|
|
" const Bokeh = root.Bokeh;\n",
|
|
"\n",
|
|
" // Set a timeout for this load but only if we are not already initializing\n",
|
|
" if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_failed_load = false;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function run_callbacks() {\n",
|
|
" try {\n",
|
|
" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
|
|
" if (callback != null)\n",
|
|
" callback();\n",
|
|
" });\n",
|
|
" } finally {\n",
|
|
" delete root._bokeh_onload_callbacks;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: all callbacks have finished\");\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
|
|
" if (css_urls == null) css_urls = [];\n",
|
|
" if (js_urls == null) js_urls = [];\n",
|
|
" if (js_modules == null) js_modules = [];\n",
|
|
" if (js_exports == null) js_exports = {};\n",
|
|
"\n",
|
|
" root._bokeh_onload_callbacks.push(callback);\n",
|
|
"\n",
|
|
" if (root._bokeh_is_loading > 0) {\n",
|
|
" // Don't load bokeh if it is still initializing\n",
|
|
" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
|
|
" return null;\n",
|
|
" } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
|
|
" // There is nothing to load\n",
|
|
" run_callbacks();\n",
|
|
" return null;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function on_load() {\n",
|
|
" root._bokeh_is_loading--;\n",
|
|
" if (root._bokeh_is_loading === 0) {\n",
|
|
" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
|
|
" run_callbacks()\n",
|
|
" }\n",
|
|
" }\n",
|
|
" window._bokeh_on_load = on_load\n",
|
|
"\n",
|
|
" function on_error(e) {\n",
|
|
" const src_el = e.srcElement\n",
|
|
" console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
|
|
" }\n",
|
|
"\n",
|
|
" const skip = [];\n",
|
|
" if (window.requirejs) {\n",
|
|
" window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
|
|
" root._bokeh_is_loading = css_urls.length + 0;\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
|
|
" }\n",
|
|
"\n",
|
|
" const existing_stylesheets = []\n",
|
|
" const links = document.getElementsByTagName('link')\n",
|
|
" for (let i = 0; i < links.length; i++) {\n",
|
|
" const link = links[i]\n",
|
|
" if (link.href != null) {\n",
|
|
" existing_stylesheets.push(link.href)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < css_urls.length; i++) {\n",
|
|
" const url = css_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
|
|
" on_load()\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement(\"link\");\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.rel = \"stylesheet\";\n",
|
|
" element.type = \"text/css\";\n",
|
|
" element.href = url;\n",
|
|
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
|
|
" document.body.appendChild(element);\n",
|
|
" } var existing_scripts = []\n",
|
|
" const scripts = document.getElementsByTagName('script')\n",
|
|
" for (let i = 0; i < scripts.length; i++) {\n",
|
|
" var script = scripts[i]\n",
|
|
" if (script.src != null) {\n",
|
|
" existing_scripts.push(script.src)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_urls.length; i++) {\n",
|
|
" const url = js_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_modules.length; i++) {\n",
|
|
" const url = js_modules[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (const name in js_exports) {\n",
|
|
" const url = js_exports[name];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" element.textContent = `\n",
|
|
" import ${name} from \"${url}\"\n",
|
|
" window.${name} = ${name}\n",
|
|
" window._bokeh_on_load()\n",
|
|
" `\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" if (!js_urls.length && !js_modules.length) {\n",
|
|
" on_load()\n",
|
|
" }\n",
|
|
" };\n",
|
|
"\n",
|
|
" function inject_raw_css(css) {\n",
|
|
" const element = document.createElement(\"style\");\n",
|
|
" element.appendChild(document.createTextNode(css));\n",
|
|
" document.body.appendChild(element);\n",
|
|
" }\n",
|
|
"\n",
|
|
" const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n",
|
|
" const js_modules = [];\n",
|
|
" const js_exports = {};\n",
|
|
" const css_urls = [];\n",
|
|
" const inline_js = [ function(Bokeh) {\n",
|
|
" Bokeh.set_log_level(\"info\");\n",
|
|
" },\n",
|
|
"function(Bokeh) {} // ensure no trailing comma for IE\n",
|
|
" ];\n",
|
|
"\n",
|
|
" function run_inline_js() {\n",
|
|
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
|
|
" for (let i = 0; i < inline_js.length; i++) {\n",
|
|
" try {\n",
|
|
" inline_js[i].call(root, root.Bokeh);\n",
|
|
" } catch(e) {\n",
|
|
" if (!reloading) {\n",
|
|
" throw e;\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Cache old bokeh versions\n",
|
|
" if (Bokeh != undefined && !reloading) {\n",
|
|
" var NewBokeh = root.Bokeh;\n",
|
|
" if (Bokeh.versions === undefined) {\n",
|
|
" Bokeh.versions = new Map();\n",
|
|
" }\n",
|
|
" if (NewBokeh.version !== Bokeh.version) {\n",
|
|
" Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
|
|
" }\n",
|
|
" root.Bokeh = Bokeh;\n",
|
|
" }\n",
|
|
" } else if (Date.now() < root._bokeh_timeout) {\n",
|
|
" setTimeout(run_inline_js, 100);\n",
|
|
" } else if (!root._bokeh_failed_load) {\n",
|
|
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
|
|
" root._bokeh_failed_load = true;\n",
|
|
" }\n",
|
|
" root._bokeh_is_initializing = false\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_or_wait() {\n",
|
|
" // Implement a backoff loop that tries to ensure we do not load multiple\n",
|
|
" // versions of Bokeh and its dependencies at the same time.\n",
|
|
" // In recent versions we use the root._bokeh_is_initializing flag\n",
|
|
" // to determine whether there is an ongoing attempt to initialize\n",
|
|
" // bokeh, however for backward compatibility we also try to ensure\n",
|
|
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
|
|
" // before older versions are fully initialized.\n",
|
|
" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
|
|
" // If the timeout and bokeh was not successfully loaded we reset\n",
|
|
" // everything and try loading again\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_is_initializing = false;\n",
|
|
" root._bokeh_onload_callbacks = undefined;\n",
|
|
" root._bokeh_is_loading = 0\n",
|
|
" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
|
|
" load_or_wait();\n",
|
|
" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
|
|
" setTimeout(load_or_wait, 100);\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_initializing = true\n",
|
|
" root._bokeh_onload_callbacks = []\n",
|
|
" const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
|
|
" if (!reloading && !bokeh_loaded) {\n",
|
|
" if (root.Bokeh) {\n",
|
|
" root.Bokeh = undefined;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
|
|
" }\n",
|
|
" load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
|
|
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
|
|
" run_inline_js();\n",
|
|
" });\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Give older versions of the autoload script a head-start to ensure\n",
|
|
" // they initialize before we start loading newer version.\n",
|
|
" setTimeout(load_or_wait, 100)\n",
|
|
"}(window));"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n var NewBokeh = root.Bokeh;\n if (Bokeh.versions === undefined) {\n Bokeh.versions = new Map();\n }\n if (NewBokeh.version !== Bokeh.version) {\n Bokeh.versions.set(NewBokeh.version, NewBokeh)\n }\n root.Bokeh = Bokeh;\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n if (!reloading && !bokeh_loaded) {\n if (root.Bokeh) {\n root.Bokeh = undefined;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"\n",
|
|
"if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
|
|
" window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
" function JupyterCommManager() {\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" comm_manager.register_target(comm_id, function(comm) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" });\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" });\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" console.log(message)\n",
|
|
" var content = {data: message.data, comm_id};\n",
|
|
" var buffers = []\n",
|
|
" for (var buffer of message.buffers || []) {\n",
|
|
" buffers.push(new DataView(buffer))\n",
|
|
" }\n",
|
|
" var metadata = message.metadata || {};\n",
|
|
" var msg = {content, buffers, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" })\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (comm_id in window.PyViz.comms) {\n",
|
|
" return window.PyViz.comms[comm_id];\n",
|
|
" } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" }\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
|
|
" comm.open();\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" }\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
|
|
" comm_promise.then((comm) => {\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" if (msg_handler) {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" var content = {data: message.data};\n",
|
|
" var metadata = message.metadata || {comm_id};\n",
|
|
" var msg = {content, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" }) \n",
|
|
" var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
|
|
" return comm_promise.then((comm) => {\n",
|
|
" comm.send(data, metadata, buffers, disposeOnDone);\n",
|
|
" });\n",
|
|
" };\n",
|
|
" var comm = {\n",
|
|
" send: sendClosure\n",
|
|
" };\n",
|
|
" }\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" return comm;\n",
|
|
" }\n",
|
|
" window.PyViz.comm_manager = new JupyterCommManager();\n",
|
|
" \n",
|
|
"\n",
|
|
"\n",
|
|
"var JS_MIME_TYPE = 'application/javascript';\n",
|
|
"var HTML_MIME_TYPE = 'text/html';\n",
|
|
"var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
|
|
"var CLASS_NAME = 'output';\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Render data to the DOM node\n",
|
|
" */\n",
|
|
"function render(props, node) {\n",
|
|
" var div = document.createElement(\"div\");\n",
|
|
" var script = document.createElement(\"script\");\n",
|
|
" node.appendChild(div);\n",
|
|
" node.appendChild(script);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when a new output is added\n",
|
|
" */\n",
|
|
"function handle_add_output(event, handle) {\n",
|
|
" var output_area = handle.output_area;\n",
|
|
" var output = handle.output;\n",
|
|
" if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
|
|
" return\n",
|
|
" }\n",
|
|
" var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
|
|
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
|
|
" if (id !== undefined) {\n",
|
|
" var nchildren = toinsert.length;\n",
|
|
" var html_node = toinsert[nchildren-1].children[0];\n",
|
|
" html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var scripts = [];\n",
|
|
" var nodelist = html_node.querySelectorAll(\"script\");\n",
|
|
" for (var i in nodelist) {\n",
|
|
" if (nodelist.hasOwnProperty(i)) {\n",
|
|
" scripts.push(nodelist[i])\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" scripts.forEach( function (oldScript) {\n",
|
|
" var newScript = document.createElement(\"script\");\n",
|
|
" var attrs = [];\n",
|
|
" var nodemap = oldScript.attributes;\n",
|
|
" for (var j in nodemap) {\n",
|
|
" if (nodemap.hasOwnProperty(j)) {\n",
|
|
" attrs.push(nodemap[j])\n",
|
|
" }\n",
|
|
" }\n",
|
|
" attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
|
|
" newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
|
|
" oldScript.parentNode.replaceChild(newScript, oldScript);\n",
|
|
" });\n",
|
|
" if (JS_MIME_TYPE in output.data) {\n",
|
|
" toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
|
|
" }\n",
|
|
" output_area._hv_plot_id = id;\n",
|
|
" if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
|
|
" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
|
|
" } else {\n",
|
|
" window.PyViz.plot_index[id] = null;\n",
|
|
" }\n",
|
|
" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
|
|
" var bk_div = document.createElement(\"div\");\n",
|
|
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var script_attrs = bk_div.children[0].attributes;\n",
|
|
" for (var i = 0; i < script_attrs.length; i++) {\n",
|
|
" toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
|
|
" }\n",
|
|
" // store reference to server id on output_area\n",
|
|
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when an output is cleared or removed\n",
|
|
" */\n",
|
|
"function handle_clear_output(event, handle) {\n",
|
|
" var id = handle.cell.output_area._hv_plot_id;\n",
|
|
" var server_id = handle.cell.output_area._bokeh_server_id;\n",
|
|
" if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
|
|
" var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
|
|
" if (server_id !== null) {\n",
|
|
" comm.send({event_type: 'server_delete', 'id': server_id});\n",
|
|
" return;\n",
|
|
" } else if (comm !== null) {\n",
|
|
" comm.send({event_type: 'delete', 'id': id});\n",
|
|
" }\n",
|
|
" delete PyViz.plot_index[id];\n",
|
|
" if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
|
|
" var doc = window.Bokeh.index[id].model.document\n",
|
|
" doc.clear();\n",
|
|
" const i = window.Bokeh.documents.indexOf(doc);\n",
|
|
" if (i > -1) {\n",
|
|
" window.Bokeh.documents.splice(i, 1);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle kernel restart event\n",
|
|
" */\n",
|
|
"function handle_kernel_cleanup(event, handle) {\n",
|
|
" delete PyViz.comms[\"hv-extension-comm\"];\n",
|
|
" window.PyViz.plot_index = {}\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle update_display_data messages\n",
|
|
" */\n",
|
|
"function handle_update_output(event, handle) {\n",
|
|
" handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
|
|
" handle_add_output(event, handle)\n",
|
|
"}\n",
|
|
"\n",
|
|
"function register_renderer(events, OutputArea) {\n",
|
|
" function append_mime(data, metadata, element) {\n",
|
|
" // create a DOM node to render to\n",
|
|
" var toinsert = this.create_output_subarea(\n",
|
|
" metadata,\n",
|
|
" CLASS_NAME,\n",
|
|
" EXEC_MIME_TYPE\n",
|
|
" );\n",
|
|
" this.keyboard_manager.register_events(toinsert);\n",
|
|
" // Render to node\n",
|
|
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
|
|
" render(props, toinsert[0]);\n",
|
|
" element.append(toinsert);\n",
|
|
" return toinsert\n",
|
|
" }\n",
|
|
"\n",
|
|
" events.on('output_added.OutputArea', handle_add_output);\n",
|
|
" events.on('output_updated.OutputArea', handle_update_output);\n",
|
|
" events.on('clear_output.CodeCell', handle_clear_output);\n",
|
|
" events.on('delete.Cell', handle_clear_output);\n",
|
|
" events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
|
|
"\n",
|
|
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
|
|
" safe: true,\n",
|
|
" index: 0\n",
|
|
" });\n",
|
|
"}\n",
|
|
"\n",
|
|
"if (window.Jupyter !== undefined) {\n",
|
|
" try {\n",
|
|
" var events = require('base/js/events');\n",
|
|
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
|
|
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
|
|
" register_renderer(events, OutputArea);\n",
|
|
" }\n",
|
|
" } catch(err) {\n",
|
|
" }\n",
|
|
"}\n"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
|
|
"*[data-root-id] > * {\n",
|
|
" box-sizing: border-box;\n",
|
|
" font-family: var(--jp-ui-font-family);\n",
|
|
" font-size: var(--jp-ui-font-size1);\n",
|
|
" color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Override VSCode background color */\n",
|
|
".cell-output-ipywidget-background:has(\n",
|
|
" > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
|
|
" ),\n",
|
|
".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
|
|
" background-color: transparent !important;\n",
|
|
"}\n",
|
|
"</style>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"(function(root) {\n",
|
|
" function now() {\n",
|
|
" return new Date();\n",
|
|
" }\n",
|
|
"\n",
|
|
" const force = false;\n",
|
|
" const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
|
|
" const reloading = true;\n",
|
|
" const Bokeh = root.Bokeh;\n",
|
|
"\n",
|
|
" // Set a timeout for this load but only if we are not already initializing\n",
|
|
" if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_failed_load = false;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function run_callbacks() {\n",
|
|
" try {\n",
|
|
" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
|
|
" if (callback != null)\n",
|
|
" callback();\n",
|
|
" });\n",
|
|
" } finally {\n",
|
|
" delete root._bokeh_onload_callbacks;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: all callbacks have finished\");\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
|
|
" if (css_urls == null) css_urls = [];\n",
|
|
" if (js_urls == null) js_urls = [];\n",
|
|
" if (js_modules == null) js_modules = [];\n",
|
|
" if (js_exports == null) js_exports = {};\n",
|
|
"\n",
|
|
" root._bokeh_onload_callbacks.push(callback);\n",
|
|
"\n",
|
|
" if (root._bokeh_is_loading > 0) {\n",
|
|
" // Don't load bokeh if it is still initializing\n",
|
|
" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
|
|
" return null;\n",
|
|
" } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
|
|
" // There is nothing to load\n",
|
|
" run_callbacks();\n",
|
|
" return null;\n",
|
|
" }\n",
|
|
"\n",
|
|
" function on_load() {\n",
|
|
" root._bokeh_is_loading--;\n",
|
|
" if (root._bokeh_is_loading === 0) {\n",
|
|
" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
|
|
" run_callbacks()\n",
|
|
" }\n",
|
|
" }\n",
|
|
" window._bokeh_on_load = on_load\n",
|
|
"\n",
|
|
" function on_error(e) {\n",
|
|
" const src_el = e.srcElement\n",
|
|
" console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
|
|
" }\n",
|
|
"\n",
|
|
" const skip = [];\n",
|
|
" if (window.requirejs) {\n",
|
|
" window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
|
|
" root._bokeh_is_loading = css_urls.length + 0;\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
|
|
" }\n",
|
|
"\n",
|
|
" const existing_stylesheets = []\n",
|
|
" const links = document.getElementsByTagName('link')\n",
|
|
" for (let i = 0; i < links.length; i++) {\n",
|
|
" const link = links[i]\n",
|
|
" if (link.href != null) {\n",
|
|
" existing_stylesheets.push(link.href)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < css_urls.length; i++) {\n",
|
|
" const url = css_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
|
|
" on_load()\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement(\"link\");\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.rel = \"stylesheet\";\n",
|
|
" element.type = \"text/css\";\n",
|
|
" element.href = url;\n",
|
|
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
|
|
" document.body.appendChild(element);\n",
|
|
" } var existing_scripts = []\n",
|
|
" const scripts = document.getElementsByTagName('script')\n",
|
|
" for (let i = 0; i < scripts.length; i++) {\n",
|
|
" var script = scripts[i]\n",
|
|
" if (script.src != null) {\n",
|
|
" existing_scripts.push(script.src)\n",
|
|
" }\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_urls.length; i++) {\n",
|
|
" const url = js_urls[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" const element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (let i = 0; i < js_modules.length; i++) {\n",
|
|
" const url = js_modules[i];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onload = on_load;\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.src = url;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" for (const name in js_exports) {\n",
|
|
" const url = js_exports[name];\n",
|
|
" const escaped = encodeURI(url)\n",
|
|
" if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
|
|
" if (!window.requirejs) {\n",
|
|
" on_load();\n",
|
|
" }\n",
|
|
" continue;\n",
|
|
" }\n",
|
|
" var element = document.createElement('script');\n",
|
|
" element.onerror = on_error;\n",
|
|
" element.async = false;\n",
|
|
" element.type = \"module\";\n",
|
|
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
|
|
" element.textContent = `\n",
|
|
" import ${name} from \"${url}\"\n",
|
|
" window.${name} = ${name}\n",
|
|
" window._bokeh_on_load()\n",
|
|
" `\n",
|
|
" document.head.appendChild(element);\n",
|
|
" }\n",
|
|
" if (!js_urls.length && !js_modules.length) {\n",
|
|
" on_load()\n",
|
|
" }\n",
|
|
" };\n",
|
|
"\n",
|
|
" function inject_raw_css(css) {\n",
|
|
" const element = document.createElement(\"style\");\n",
|
|
" element.appendChild(document.createTextNode(css));\n",
|
|
" document.body.appendChild(element);\n",
|
|
" }\n",
|
|
"\n",
|
|
" const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n",
|
|
" const js_modules = [];\n",
|
|
" const js_exports = {};\n",
|
|
" const css_urls = [];\n",
|
|
" const inline_js = [ function(Bokeh) {\n",
|
|
" Bokeh.set_log_level(\"info\");\n",
|
|
" },\n",
|
|
"function(Bokeh) {} // ensure no trailing comma for IE\n",
|
|
" ];\n",
|
|
"\n",
|
|
" function run_inline_js() {\n",
|
|
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
|
|
" for (let i = 0; i < inline_js.length; i++) {\n",
|
|
" try {\n",
|
|
" inline_js[i].call(root, root.Bokeh);\n",
|
|
" } catch(e) {\n",
|
|
" if (!reloading) {\n",
|
|
" throw e;\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Cache old bokeh versions\n",
|
|
" if (Bokeh != undefined && !reloading) {\n",
|
|
" var NewBokeh = root.Bokeh;\n",
|
|
" if (Bokeh.versions === undefined) {\n",
|
|
" Bokeh.versions = new Map();\n",
|
|
" }\n",
|
|
" if (NewBokeh.version !== Bokeh.version) {\n",
|
|
" Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
|
|
" }\n",
|
|
" root.Bokeh = Bokeh;\n",
|
|
" }\n",
|
|
" } else if (Date.now() < root._bokeh_timeout) {\n",
|
|
" setTimeout(run_inline_js, 100);\n",
|
|
" } else if (!root._bokeh_failed_load) {\n",
|
|
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
|
|
" root._bokeh_failed_load = true;\n",
|
|
" }\n",
|
|
" root._bokeh_is_initializing = false\n",
|
|
" }\n",
|
|
"\n",
|
|
" function load_or_wait() {\n",
|
|
" // Implement a backoff loop that tries to ensure we do not load multiple\n",
|
|
" // versions of Bokeh and its dependencies at the same time.\n",
|
|
" // In recent versions we use the root._bokeh_is_initializing flag\n",
|
|
" // to determine whether there is an ongoing attempt to initialize\n",
|
|
" // bokeh, however for backward compatibility we also try to ensure\n",
|
|
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
|
|
" // before older versions are fully initialized.\n",
|
|
" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
|
|
" // If the timeout and bokeh was not successfully loaded we reset\n",
|
|
" // everything and try loading again\n",
|
|
" root._bokeh_timeout = Date.now() + 5000;\n",
|
|
" root._bokeh_is_initializing = false;\n",
|
|
" root._bokeh_onload_callbacks = undefined;\n",
|
|
" root._bokeh_is_loading = 0\n",
|
|
" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
|
|
" load_or_wait();\n",
|
|
" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
|
|
" setTimeout(load_or_wait, 100);\n",
|
|
" } else {\n",
|
|
" root._bokeh_is_initializing = true\n",
|
|
" root._bokeh_onload_callbacks = []\n",
|
|
" const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
|
|
" if (!reloading && !bokeh_loaded) {\n",
|
|
" if (root.Bokeh) {\n",
|
|
" root.Bokeh = undefined;\n",
|
|
" }\n",
|
|
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
|
|
" }\n",
|
|
" load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
|
|
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
|
|
" run_inline_js();\n",
|
|
" });\n",
|
|
" }\n",
|
|
" }\n",
|
|
" // Give older versions of the autoload script a head-start to ensure\n",
|
|
" // they initialize before we start loading newer version.\n",
|
|
" setTimeout(load_or_wait, 100)\n",
|
|
"}(window));"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const py_version = '3.6.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n var NewBokeh = root.Bokeh;\n if (Bokeh.versions === undefined) {\n Bokeh.versions = new Map();\n }\n if (NewBokeh.version !== Bokeh.version) {\n Bokeh.versions.set(NewBokeh.version, NewBokeh)\n }\n root.Bokeh = Bokeh;\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n if (!reloading && !bokeh_loaded) {\n if (root.Bokeh) {\n root.Bokeh = undefined;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/javascript": [
|
|
"\n",
|
|
"if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
|
|
" window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
" function JupyterCommManager() {\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" comm_manager.register_target(comm_id, function(comm) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" });\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" });\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" console.log(message)\n",
|
|
" var content = {data: message.data, comm_id};\n",
|
|
" var buffers = []\n",
|
|
" for (var buffer of message.buffers || []) {\n",
|
|
" buffers.push(new DataView(buffer))\n",
|
|
" }\n",
|
|
" var metadata = message.metadata || {};\n",
|
|
" var msg = {content, buffers, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" })\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
|
|
" if (comm_id in window.PyViz.comms) {\n",
|
|
" return window.PyViz.comms[comm_id];\n",
|
|
" } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
|
|
" var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
|
|
" var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.on_msg(msg_handler);\n",
|
|
" }\n",
|
|
" } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
|
|
" var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
|
|
" comm.open();\n",
|
|
" if (msg_handler) {\n",
|
|
" comm.onMsg = msg_handler;\n",
|
|
" }\n",
|
|
" } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
|
|
" var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
|
|
" comm_promise.then((comm) => {\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" if (msg_handler) {\n",
|
|
" var messages = comm.messages[Symbol.asyncIterator]();\n",
|
|
" function processIteratorResult(result) {\n",
|
|
" var message = result.value;\n",
|
|
" var content = {data: message.data};\n",
|
|
" var metadata = message.metadata || {comm_id};\n",
|
|
" var msg = {content, metadata}\n",
|
|
" msg_handler(msg);\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" return messages.next().then(processIteratorResult);\n",
|
|
" }\n",
|
|
" }) \n",
|
|
" var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
|
|
" return comm_promise.then((comm) => {\n",
|
|
" comm.send(data, metadata, buffers, disposeOnDone);\n",
|
|
" });\n",
|
|
" };\n",
|
|
" var comm = {\n",
|
|
" send: sendClosure\n",
|
|
" };\n",
|
|
" }\n",
|
|
" window.PyViz.comms[comm_id] = comm;\n",
|
|
" return comm;\n",
|
|
" }\n",
|
|
" window.PyViz.comm_manager = new JupyterCommManager();\n",
|
|
" \n",
|
|
"\n",
|
|
"\n",
|
|
"var JS_MIME_TYPE = 'application/javascript';\n",
|
|
"var HTML_MIME_TYPE = 'text/html';\n",
|
|
"var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
|
|
"var CLASS_NAME = 'output';\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Render data to the DOM node\n",
|
|
" */\n",
|
|
"function render(props, node) {\n",
|
|
" var div = document.createElement(\"div\");\n",
|
|
" var script = document.createElement(\"script\");\n",
|
|
" node.appendChild(div);\n",
|
|
" node.appendChild(script);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when a new output is added\n",
|
|
" */\n",
|
|
"function handle_add_output(event, handle) {\n",
|
|
" var output_area = handle.output_area;\n",
|
|
" var output = handle.output;\n",
|
|
" if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
|
|
" return\n",
|
|
" }\n",
|
|
" var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
|
|
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
|
|
" if (id !== undefined) {\n",
|
|
" var nchildren = toinsert.length;\n",
|
|
" var html_node = toinsert[nchildren-1].children[0];\n",
|
|
" html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var scripts = [];\n",
|
|
" var nodelist = html_node.querySelectorAll(\"script\");\n",
|
|
" for (var i in nodelist) {\n",
|
|
" if (nodelist.hasOwnProperty(i)) {\n",
|
|
" scripts.push(nodelist[i])\n",
|
|
" }\n",
|
|
" }\n",
|
|
"\n",
|
|
" scripts.forEach( function (oldScript) {\n",
|
|
" var newScript = document.createElement(\"script\");\n",
|
|
" var attrs = [];\n",
|
|
" var nodemap = oldScript.attributes;\n",
|
|
" for (var j in nodemap) {\n",
|
|
" if (nodemap.hasOwnProperty(j)) {\n",
|
|
" attrs.push(nodemap[j])\n",
|
|
" }\n",
|
|
" }\n",
|
|
" attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
|
|
" newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
|
|
" oldScript.parentNode.replaceChild(newScript, oldScript);\n",
|
|
" });\n",
|
|
" if (JS_MIME_TYPE in output.data) {\n",
|
|
" toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
|
|
" }\n",
|
|
" output_area._hv_plot_id = id;\n",
|
|
" if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
|
|
" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
|
|
" } else {\n",
|
|
" window.PyViz.plot_index[id] = null;\n",
|
|
" }\n",
|
|
" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
|
|
" var bk_div = document.createElement(\"div\");\n",
|
|
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
|
|
" var script_attrs = bk_div.children[0].attributes;\n",
|
|
" for (var i = 0; i < script_attrs.length; i++) {\n",
|
|
" toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
|
|
" }\n",
|
|
" // store reference to server id on output_area\n",
|
|
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle when an output is cleared or removed\n",
|
|
" */\n",
|
|
"function handle_clear_output(event, handle) {\n",
|
|
" var id = handle.cell.output_area._hv_plot_id;\n",
|
|
" var server_id = handle.cell.output_area._bokeh_server_id;\n",
|
|
" if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
|
|
" var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
|
|
" if (server_id !== null) {\n",
|
|
" comm.send({event_type: 'server_delete', 'id': server_id});\n",
|
|
" return;\n",
|
|
" } else if (comm !== null) {\n",
|
|
" comm.send({event_type: 'delete', 'id': id});\n",
|
|
" }\n",
|
|
" delete PyViz.plot_index[id];\n",
|
|
" if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
|
|
" var doc = window.Bokeh.index[id].model.document\n",
|
|
" doc.clear();\n",
|
|
" const i = window.Bokeh.documents.indexOf(doc);\n",
|
|
" if (i > -1) {\n",
|
|
" window.Bokeh.documents.splice(i, 1);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle kernel restart event\n",
|
|
" */\n",
|
|
"function handle_kernel_cleanup(event, handle) {\n",
|
|
" delete PyViz.comms[\"hv-extension-comm\"];\n",
|
|
" window.PyViz.plot_index = {}\n",
|
|
"}\n",
|
|
"\n",
|
|
"/**\n",
|
|
" * Handle update_display_data messages\n",
|
|
" */\n",
|
|
"function handle_update_output(event, handle) {\n",
|
|
" handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
|
|
" handle_add_output(event, handle)\n",
|
|
"}\n",
|
|
"\n",
|
|
"function register_renderer(events, OutputArea) {\n",
|
|
" function append_mime(data, metadata, element) {\n",
|
|
" // create a DOM node to render to\n",
|
|
" var toinsert = this.create_output_subarea(\n",
|
|
" metadata,\n",
|
|
" CLASS_NAME,\n",
|
|
" EXEC_MIME_TYPE\n",
|
|
" );\n",
|
|
" this.keyboard_manager.register_events(toinsert);\n",
|
|
" // Render to node\n",
|
|
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
|
|
" render(props, toinsert[0]);\n",
|
|
" element.append(toinsert);\n",
|
|
" return toinsert\n",
|
|
" }\n",
|
|
"\n",
|
|
" events.on('output_added.OutputArea', handle_add_output);\n",
|
|
" events.on('output_updated.OutputArea', handle_update_output);\n",
|
|
" events.on('clear_output.CodeCell', handle_clear_output);\n",
|
|
" events.on('delete.Cell', handle_clear_output);\n",
|
|
" events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
|
|
"\n",
|
|
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
|
|
" safe: true,\n",
|
|
" index: 0\n",
|
|
" });\n",
|
|
"}\n",
|
|
"\n",
|
|
"if (window.Jupyter !== undefined) {\n",
|
|
" try {\n",
|
|
" var events = require('base/js/events');\n",
|
|
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
|
|
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
|
|
" register_renderer(events, OutputArea);\n",
|
|
" }\n",
|
|
" } catch(err) {\n",
|
|
" }\n",
|
|
"}\n"
|
|
],
|
|
"application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Device: cpu\n",
|
|
"PyTorch version: 2.5.0+cpu\n",
|
|
"CPU times: user 21.2 s, sys: 3.75 s, total: 25 s\n",
|
|
"Wall time: 16.4 s\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"%matplotlib inline\n",
|
|
"\n",
|
|
"import importlib\n",
|
|
"import new_import_ODC\n",
|
|
"\n",
|
|
"importlib.reload(new_import_ODC)\n",
|
|
"from new_import_ODC import *\n",
|
|
"\n",
|
|
"import numpy as np\n",
|
|
"import torch\n",
|
|
"import torch.nn as nn\n",
|
|
"import torch.optim as optim\n",
|
|
"from torch.utils.data import Dataset, DataLoader, TensorDataset\n",
|
|
"from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
|
|
"\n",
|
|
"# ── Hyperparameters & constants ───────────────────────────────────────────────\n",
|
|
"N_VARS = 3 # số kênh mỗi bước thời gian (ndvi, vh, vv)\n",
|
|
"EMBED_DIM = 128 # kích thước embedding Swin blocks\n",
|
|
"NUM_HEADS = 4 # heads cho MultiheadAttention\n",
|
|
"NUM_CLASSES = 8 # số lớp phân loại\n",
|
|
"EPOCHS = 150 # số epoch tối đa\n",
|
|
"PATIENCE = 20 # early stopping patience\n",
|
|
"BATCH_SIZE = 32\n",
|
|
"LR = 1e-3\n",
|
|
"WEIGHT_DECAY = 0.01\n",
|
|
"\n",
|
|
"DEVICE = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
|
|
"print(f\"Device: {DEVICE}\")\n",
|
|
"print(f\"PyTorch version: {torch.__version__}\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "46b8f479",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Starting new cluster\n",
|
|
"CPU times: user 1.22 s, sys: 43.3 ms, total: 1.26 s\n",
|
|
"Wall time: 3min 35s\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
|
|
" <div style=\"margin-left: 48px;\">\n",
|
|
" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
|
|
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-4aee1612-1777-11f1-853a-3a1de9fa0a94</p>\n",
|
|
" <table style=\"width: 100%; text-align: left;\">\n",
|
|
"\n",
|
|
" <tr>\n",
|
|
" \n",
|
|
" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
|
|
" <td style=\"text-align: left;\"><strong>Cluster type:</strong> dask_gateway.GatewayCluster</td>\n",
|
|
" \n",
|
|
" </tr>\n",
|
|
"\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <td style=\"text-align: left;\">\n",
|
|
" <strong>Dashboard: </strong> <a href=\"https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.a77e8ba9669b4f1d813fe626cceb3002/status\" target=\"_blank\">https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.a77e8ba9669b4f1d813fe626cceb3002/status</a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: left;\"></td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
"\n",
|
|
" </table>\n",
|
|
"\n",
|
|
" \n",
|
|
" <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.a77e8ba9669b4f1d813fe626cceb3002/status\" }'>\n",
|
|
" Launch dashboard in JupyterLab\n",
|
|
" </button>\n",
|
|
" \n",
|
|
"\n",
|
|
" \n",
|
|
" <details>\n",
|
|
" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
|
|
" <div style='background-color: #f2f2f2; display: inline-block; padding: 10px; border: 1px solid #999999;'>\n",
|
|
" <h3>GatewayCluster</h3>\n",
|
|
" <ul>\n",
|
|
" <li><b>Name: </b>easihub.a77e8ba9669b4f1d813fe626cceb3002\n",
|
|
" <li><b>Dashboard: </b><a href='https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.a77e8ba9669b4f1d813fe626cceb3002/status' target='_blank'>https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.a77e8ba9669b4f1d813fe626cceb3002/status</a>\n",
|
|
" </ul>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </details>\n",
|
|
" \n",
|
|
"\n",
|
|
" </div>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
"<Client: 'tls://10.0.41.51:8786' processes=0 threads=0, memory=0 B>"
|
|
]
|
|
},
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Task exception was never retrieved\n",
|
|
"future: <Task finished name='Task-25113' coro=<Client._gather.<locals>.wait() done, defined at /env/lib/python3.12/site-packages/distributed/client.py:2391> exception=AllExit()>\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/env/lib/python3.12/site-packages/distributed/client.py\", line 2400, in wait\n",
|
|
" raise AllExit()\n",
|
|
"distributed.client.AllExit\n",
|
|
"Task exception was never retrieved\n",
|
|
"future: <Task finished name='Task-25119' coro=<Client._gather.<locals>.wait() done, defined at /env/lib/python3.12/site-packages/distributed/client.py:2391> exception=AllExit()>\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/env/lib/python3.12/site-packages/distributed/client.py\", line 2400, in wait\n",
|
|
" raise AllExit()\n",
|
|
"distributed.client.AllExit\n",
|
|
"Task exception was never retrieved\n",
|
|
"future: <Task finished name='Task-25120' coro=<Client._gather.<locals>.wait() done, defined at /env/lib/python3.12/site-packages/distributed/client.py:2391> exception=AllExit()>\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/env/lib/python3.12/site-packages/distributed/client.py\", line 2400, in wait\n",
|
|
" raise AllExit()\n",
|
|
"distributed.client.AllExit\n",
|
|
"Task exception was never retrieved\n",
|
|
"future: <Task finished name='Task-25116' coro=<Client._gather.<locals>.wait() done, defined at /env/lib/python3.12/site-packages/distributed/client.py:2391> exception=AllExit()>\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"/env/lib/python3.12/site-packages/distributed/client.py\", line 2400, in wait\n",
|
|
" raise AllExit()\n",
|
|
"distributed.client.AllExit\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"# ── Kết nối Dask + ODC + S3 ──────────────────────────────────────────────────\n",
|
|
"cluster, client = notebook_utils.initialize_dask(use_gateway=True, workers=(1, 10))\n",
|
|
"dc = datacube.Datacube()\n",
|
|
"configure_s3_access(aws_unsigned=False, requester_pays=True, client=client)\n",
|
|
"client\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "cb9a8d0c",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Most common native CRS: EPSG:32648\n",
|
|
"No datasets require offset correction\n",
|
|
"The valid_data_mask and scale (no offset) have been applied to the reflectance bands\n"
|
|
]
|
|
},
|
|
{
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"data": {
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"text/html": [
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],
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"text/plain": [
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]
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{
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"data": {
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"text/html": [
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"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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"</symbol>\n",
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"</defs>\n",
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"</svg>\n",
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" *\n",
|
|
" */\n",
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"\n",
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":root {\n",
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" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
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" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
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" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
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" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
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" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
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" --xr-background-color: var(--jp-layout-color0, white);\n",
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" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
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" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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"}\n",
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"\n",
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"html[theme=dark],\n",
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"html[data-theme=dark],\n",
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"body[data-theme=dark],\n",
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"body.vscode-dark {\n",
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" --xr-font-color0: rgba(255, 255, 255, 1);\n",
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" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
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" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
|
|
" --xr-border-color: #1F1F1F;\n",
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" --xr-disabled-color: #515151;\n",
|
|
" --xr-background-color: #111111;\n",
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" --xr-background-color-row-even: #111111;\n",
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" --xr-background-color-row-odd: #313131;\n",
|
|
"}\n",
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"\n",
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".xr-wrap {\n",
|
|
" display: block !important;\n",
|
|
" min-width: 300px;\n",
|
|
" max-width: 700px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-text-repr-fallback {\n",
|
|
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-header {\n",
|
|
" padding-top: 6px;\n",
|
|
" padding-bottom: 6px;\n",
|
|
" margin-bottom: 4px;\n",
|
|
" border-bottom: solid 1px var(--xr-border-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-header > div,\n",
|
|
".xr-header > ul {\n",
|
|
" display: inline;\n",
|
|
" margin-top: 0;\n",
|
|
" margin-bottom: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-obj-type,\n",
|
|
".xr-array-name {\n",
|
|
" margin-left: 2px;\n",
|
|
" margin-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-obj-type {\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-sections {\n",
|
|
" padding-left: 0 !important;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item {\n",
|
|
" display: contents;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input {\n",
|
|
" display: inline-block;\n",
|
|
" opacity: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input + label {\n",
|
|
" color: var(--xr-disabled-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:enabled + label {\n",
|
|
" cursor: pointer;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:focus + label {\n",
|
|
" border: 2px solid var(--xr-font-color0);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:enabled + label:hover {\n",
|
|
" color: var(--xr-font-color0);\n",
|
|
"}\n",
|
|
"\n",
|
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".xr-section-summary {\n",
|
|
" grid-column: 1;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
" font-weight: 500;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary > span {\n",
|
|
" display: inline-block;\n",
|
|
" padding-left: 0.5em;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:disabled + label {\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in + label:before {\n",
|
|
" display: inline-block;\n",
|
|
" content: '►';\n",
|
|
" font-size: 11px;\n",
|
|
" width: 15px;\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:disabled + label:before {\n",
|
|
" color: var(--xr-disabled-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:checked + label:before {\n",
|
|
" content: '▼';\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:checked + label > span {\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary,\n",
|
|
".xr-section-inline-details {\n",
|
|
" padding-top: 4px;\n",
|
|
" padding-bottom: 4px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-inline-details {\n",
|
|
" grid-column: 2 / -1;\n",
|
|
"}\n",
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|
"\n",
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".xr-section-details {\n",
|
|
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|
|
" grid-column: 1 / -1;\n",
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|
" margin-bottom: 5px;\n",
|
|
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|
|
"\n",
|
|
".xr-section-summary-in:checked ~ .xr-section-details {\n",
|
|
" display: contents;\n",
|
|
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|
|
"\n",
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|
".xr-array-wrap {\n",
|
|
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|
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|
" grid-template-columns: 20px auto;\n",
|
|
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|
|
"\n",
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|
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|
|
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|
" vertical-align: top;\n",
|
|
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|
|
"\n",
|
|
".xr-preview {\n",
|
|
" color: var(--xr-font-color3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-preview,\n",
|
|
".xr-array-data {\n",
|
|
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|
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|
|
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|
|
"\n",
|
|
".xr-array-data,\n",
|
|
".xr-array-in:checked ~ .xr-array-preview {\n",
|
|
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|
|
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|
|
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|
|
".xr-array-in:checked ~ .xr-array-data,\n",
|
|
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|
|
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|
|
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|
|
"\n",
|
|
".xr-dim-list {\n",
|
|
" display: inline-block !important;\n",
|
|
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|
|
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|
|
" margin: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list li {\n",
|
|
" display: inline-block;\n",
|
|
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|
|
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|
|
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|
|
"\n",
|
|
".xr-dim-list:before {\n",
|
|
" content: '(';\n",
|
|
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|
|
"\n",
|
|
".xr-dim-list:after {\n",
|
|
" content: ')';\n",
|
|
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|
|
"\n",
|
|
".xr-dim-list li:not(:last-child):after {\n",
|
|
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|
|
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|
|
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|
|
"\n",
|
|
".xr-has-index {\n",
|
|
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|
|
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|
|
"\n",
|
|
".xr-var-list,\n",
|
|
".xr-var-item {\n",
|
|
" display: contents;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-item > div,\n",
|
|
".xr-var-item label,\n",
|
|
".xr-var-item > .xr-var-name span {\n",
|
|
" background-color: var(--xr-background-color-row-even);\n",
|
|
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|
|
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|
|
"\n",
|
|
".xr-var-item > .xr-var-name:hover span {\n",
|
|
" padding-right: 5px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-list > li:nth-child(odd) > div,\n",
|
|
".xr-var-list > li:nth-child(odd) > label,\n",
|
|
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
|
|
" background-color: var(--xr-background-color-row-odd);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name {\n",
|
|
" grid-column: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-dims {\n",
|
|
" grid-column: 2;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-dtype {\n",
|
|
" grid-column: 3;\n",
|
|
" text-align: right;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-preview {\n",
|
|
" grid-column: 4;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-index-preview {\n",
|
|
" grid-column: 2 / 5;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name,\n",
|
|
".xr-var-dims,\n",
|
|
".xr-var-dtype,\n",
|
|
".xr-preview,\n",
|
|
".xr-attrs dt {\n",
|
|
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|
|
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|
|
" text-overflow: ellipsis;\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name:hover,\n",
|
|
".xr-var-dims:hover,\n",
|
|
".xr-var-dtype:hover,\n",
|
|
".xr-attrs dt:hover {\n",
|
|
" overflow: visible;\n",
|
|
" width: auto;\n",
|
|
" z-index: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-data {\n",
|
|
" display: none;\n",
|
|
" background-color: var(--xr-background-color) !important;\n",
|
|
" padding-bottom: 5px !important;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
|
|
".xr-var-data-in:checked ~ .xr-var-data,\n",
|
|
".xr-index-data-in:checked ~ .xr-index-data {\n",
|
|
" display: block;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-data > table {\n",
|
|
" float: right;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name span,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-name div,\n",
|
|
".xr-index-data,\n",
|
|
".xr-attrs {\n",
|
|
" padding-left: 25px !important;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs,\n",
|
|
".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-data {\n",
|
|
" grid-column: 1 / -1;\n",
|
|
"}\n",
|
|
"\n",
|
|
"dl.xr-attrs {\n",
|
|
" padding: 0;\n",
|
|
" margin: 0;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 125px auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt,\n",
|
|
".xr-attrs dd {\n",
|
|
" padding: 0;\n",
|
|
" margin: 0;\n",
|
|
" float: left;\n",
|
|
" padding-right: 10px;\n",
|
|
" width: auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt {\n",
|
|
" font-weight: normal;\n",
|
|
" grid-column: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt:hover span {\n",
|
|
" display: inline-block;\n",
|
|
" background: var(--xr-background-color);\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dd {\n",
|
|
" grid-column: 2;\n",
|
|
" white-space: pre-wrap;\n",
|
|
" word-break: break-all;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-icon-database,\n",
|
|
".xr-icon-file-text2,\n",
|
|
".xr-no-icon {\n",
|
|
" display: inline-block;\n",
|
|
" vertical-align: middle;\n",
|
|
" width: 1em;\n",
|
|
" height: 1.5em !important;\n",
|
|
" stroke-width: 0;\n",
|
|
" stroke: currentColor;\n",
|
|
" fill: currentColor;\n",
|
|
"}\n",
|
|
"</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 119GB\n",
|
|
"Dimensions: (time: 151, y: 8874, x: 9902)\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 1kB 2022-09-02T03:35:23.960000 ... 202...\n",
|
|
" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
|
|
" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
|
|
" spatial_ref int32 4B 32648\n",
|
|
"Data variables:\n",
|
|
" red (time, y, x) float32 53GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" nir (time, y, x) float32 53GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" scl (time, y, x) uint8 13GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
"Attributes:\n",
|
|
" crs: EPSG:32648\n",
|
|
" grid_mapping: spatial_ref</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-db2f0a28-7998-45e6-a732-e639ac1836b3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-db2f0a28-7998-45e6-a732-e639ac1836b3' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 151</li><li><span class='xr-has-index'>y</span>: 8874</li><li><span class='xr-has-index'>x</span>: 9902</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6a0c91a0-018c-41d1-90a0-3793c4a89e4d' class='xr-section-summary-in' type='checkbox' checked><label for='section-6a0c91a0-018c-41d1-90a0-3793c4a89e4d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-02T03:35:23.960000 ... 2...</div><input id='attrs-fd3ddd53-3b1a-4222-b9fd-b3f562652c64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd3ddd53-3b1a-4222-b9fd-b3f562652c64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb83eda3-59ae-4ae1-bc39-b534b9267146' class='xr-var-data-in' type='checkbox'><label for='data-bb83eda3-59ae-4ae1-bc39-b534b9267146' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array(['2022-09-02T03:35:23.960000000', '2022-09-04T03:25:18.037000000',\n",
|
|
" '2022-09-07T03:35:13.646000000', '2022-09-09T03:25:27.617000000',\n",
|
|
" '2022-09-12T03:35:22.247000000', '2022-09-14T03:25:18.529000000',\n",
|
|
" '2022-09-17T03:35:13.648000000', '2022-09-19T03:25:24.773000000',\n",
|
|
" '2022-09-22T03:35:18.931000000', '2022-09-24T03:25:17.431000000',\n",
|
|
" '2022-09-27T03:35:12.140000000', '2022-09-29T03:25:23.829000000',\n",
|
|
" '2022-10-02T03:35:19.048000000', '2022-10-07T03:35:09.133000000',\n",
|
|
" '2022-10-09T03:25:22.746000000', '2022-10-12T03:35:17.151000000',\n",
|
|
" '2022-10-14T03:25:15.533000000', '2022-10-17T03:35:11.148000000',\n",
|
|
" '2022-10-19T03:25:18.808000000', '2022-10-22T03:35:13.746000000',\n",
|
|
" '2022-10-24T03:25:15.878000000', '2022-10-27T03:35:10.923000000',\n",
|
|
" '2022-10-29T03:25:20.127000000', '2022-11-01T03:35:15.818000000',\n",
|
|
" '2022-11-03T03:25:14.204000000', '2022-11-06T03:35:10.096000000',\n",
|
|
" '2022-11-11T03:35:15.334000000', '2022-11-13T03:25:16.056000000',\n",
|
|
" '2022-11-16T03:35:11.542000000', '2022-11-18T03:25:18.155000000',\n",
|
|
" '2022-11-21T03:35:12.396000000', '2022-11-23T03:25:16.067000000',\n",
|
|
" '2022-11-26T03:35:11.063000000', '2022-11-28T03:25:16.297000000',\n",
|
|
" '2022-12-01T03:35:12.009000000', '2022-12-03T03:25:14.366000000',\n",
|
|
" '2022-12-06T03:35:10.293000000', '2022-12-08T03:25:17.072000000',\n",
|
|
" '2022-12-11T03:35:12.184000000', '2022-12-16T03:35:10.130000000',\n",
|
|
" '2022-12-18T03:25:15.584000000', '2022-12-21T03:35:09.988000000',\n",
|
|
" '2022-12-23T03:25:15.763000000', '2022-12-26T03:35:11.128000000',\n",
|
|
" '2022-12-28T03:25:15.151000000', '2022-12-31T03:35:10.753000000',\n",
|
|
" '2023-01-02T03:25:15.152000000', '2023-01-05T03:35:09.844000000',\n",
|
|
" '2023-01-07T03:25:15.343000000', '2023-01-10T03:35:10.149000000',\n",
|
|
" '2023-01-12T03:25:12.066000000', '2023-01-15T03:35:08.140000000',\n",
|
|
" '2023-01-17T03:25:12.454000000', '2023-01-20T03:35:06.593000000',\n",
|
|
" '2023-01-22T03:25:14.446000000', '2023-01-25T03:35:09.824000000',\n",
|
|
" '2023-01-27T03:25:13.987000000', '2023-01-30T03:35:09.963000000',\n",
|
|
" '2023-02-01T03:25:13.595000000', '2023-02-04T03:35:09.008000000',\n",
|
|
" '2023-02-06T03:25:15.471000000', '2023-02-09T03:35:10.646000000',\n",
|
|
" '2023-02-11T03:25:15.100000000', '2023-02-14T03:35:10.240000000',\n",
|
|
" '2023-02-16T03:25:28.099000000', '2023-02-24T03:35:12.118000000',\n",
|
|
" '2023-02-26T03:25:14.146000000', '2023-03-01T03:35:09.182000000',\n",
|
|
" '2023-03-03T03:25:17.841000000', '2023-03-06T03:35:14.717000000',\n",
|
|
" '2023-03-08T03:25:12.032000000', '2023-03-11T03:35:07.230000000',\n",
|
|
" '2023-03-13T03:25:20.837000000', '2023-03-16T03:35:15.940000000',\n",
|
|
" '2023-03-18T03:25:14.467000000', '2023-03-21T03:35:10.279000000',\n",
|
|
" '2023-03-23T03:25:18.795000000', '2023-03-26T03:35:14.570000000',\n",
|
|
" '2023-03-28T03:25:14.536000000', '2023-03-31T03:35:10.140000000',\n",
|
|
" '2023-04-02T03:25:19.945000000', '2023-04-05T03:35:14.925000000',\n",
|
|
" '2023-04-07T03:25:16.518000000', '2023-04-10T03:35:12.000000000',\n",
|
|
" '2023-04-15T03:35:12.743000000', '2023-04-20T03:35:10.328000000',\n",
|
|
" '2023-04-22T03:25:18.572000000', '2023-04-25T03:35:13.748000000',\n",
|
|
" '2023-04-27T03:25:16.567000000', '2023-04-30T03:35:12.151000000',\n",
|
|
" '2023-05-02T03:25:18.866000000', '2023-05-05T03:35:14.433000000',\n",
|
|
" '2023-05-07T03:25:16.583000000', '2023-05-10T03:35:11.284000000',\n",
|
|
" '2023-05-12T03:25:19.200000000', '2023-05-15T03:35:15.683000000',\n",
|
|
" '2023-05-17T03:25:17.911000000', '2023-05-20T03:35:14.193000000',\n",
|
|
" '2023-05-22T03:25:36.378000000', '2023-05-25T03:35:16.657000000',\n",
|
|
" '2023-05-27T03:25:20.078000000', '2023-05-30T03:35:15.642000000',\n",
|
|
" '2023-06-01T03:25:20.268000000', '2023-06-04T03:35:16.047000000',\n",
|
|
" '2023-06-06T03:25:20.180000000', '2023-06-09T03:35:15.534000000',\n",
|
|
" '2023-06-11T03:25:21.573000000', '2023-06-14T03:35:16.859000000',\n",
|
|
" '2023-06-16T03:25:20.769000000', '2023-06-19T03:35:15.908000000',\n",
|
|
" '2023-06-21T03:25:20.640000000', '2023-06-24T03:35:15.972000000',\n",
|
|
" '2023-06-26T03:25:19.927000000', '2023-06-29T03:35:15.752000000',\n",
|
|
" '2023-07-01T03:25:21.763000000', '2023-07-04T03:35:17.227000000',\n",
|
|
" '2023-07-06T03:25:21.702000000', '2023-07-09T03:35:17.102000000',\n",
|
|
" '2023-07-11T03:25:21.515000000', '2023-07-14T03:35:16.582000000',\n",
|
|
" '2023-07-16T03:25:21.326000000', '2023-07-19T03:35:16.050000000',\n",
|
|
" '2023-07-21T03:25:22.444000000', '2023-07-24T03:35:17.845000000',\n",
|
|
" '2023-07-26T03:25:21.503000000', '2023-07-29T03:35:17.083000000',\n",
|
|
" '2023-07-31T03:25:36.753000000', '2023-08-03T03:35:16.494000000',\n",
|
|
" '2023-08-05T03:25:21.570000000', '2023-08-08T03:35:16.313000000',\n",
|
|
" '2023-08-10T03:25:22.024000000', '2023-08-13T03:35:17.448000000',\n",
|
|
" '2023-08-15T03:25:22.075000000', '2023-08-18T03:35:17.812000000',\n",
|
|
" '2023-08-20T03:25:21.568000000', '2023-08-23T03:35:16.224000000',\n",
|
|
" '2023-08-25T03:25:22.592000000', '2023-08-28T03:35:17.571000000',\n",
|
|
" '2023-08-30T03:25:21.212000000', '2023-09-02T03:35:16.627000000',\n",
|
|
" '2023-09-04T03:25:21.856000000', '2023-09-07T03:35:17.134000000',\n",
|
|
" '2023-09-09T03:25:20.648000000', '2023-09-12T03:35:15.326000000',\n",
|
|
" '2023-09-14T03:25:35.755000000', '2023-09-17T03:35:15.269000000',\n",
|
|
" '2023-09-19T03:25:24.089000000', '2023-09-22T03:35:15.439000000',\n",
|
|
" '2023-09-24T03:25:18.524000000', '2023-09-27T03:35:14.112000000',\n",
|
|
" '2023-09-29T03:25:19.046000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e+06 1.106e+06 ... 1.017e+06</div><input id='attrs-ecaeb307-132c-4e8f-bcd3-6465b716a030' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecaeb307-132c-4e8f-bcd3-6465b716a030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ff1a1e8-7fe4-451a-8359-130cb3c9cc4d' class='xr-var-data-in' type='checkbox'><label for='data-5ff1a1e8-7fe4-451a-8359-130cb3c9cc4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1105735., 1105725., 1105715., ..., 1017025., 1017015., 1017005.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.548e+05 5.548e+05 ... 6.538e+05</div><input id='attrs-2e6769d1-7da9-40db-811a-6f8a2500db6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e6769d1-7da9-40db-811a-6f8a2500db6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cb9a1ce-6612-4b77-827a-a0da3da14368' class='xr-var-data-in' type='checkbox'><label for='data-4cb9a1ce-6612-4b77-827a-a0da3da14368' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([554795., 554805., 554815., ..., 653785., 653795., 653805.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-9689c93d-164d-4d87-b8e6-efa40f4ddbc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9689c93d-164d-4d87-b8e6-efa40f4ddbc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4148e29c-8b3b-4a17-96ce-ea7c5fa8301e' class='xr-var-data-in' type='checkbox'><label for='data-4148e29c-8b3b-4a17-96ce-ea7c5fa8301e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32648"]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cafa4e42-e3ad-48f0-a766-30973bbe209c' class='xr-section-summary-in' type='checkbox' checked><label for='section-cafa4e42-e3ad-48f0-a766-30973bbe209c' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>red</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></div><input id='attrs-963b3da8-72ba-4272-bf66-25c7f7c4893f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-963b3da8-72ba-4272-bf66-25c7f7c4893f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85c0dffd-30c5-4b30-adbc-275e382f60f5' class='xr-var-data-in' type='checkbox'><label for='data-85c0dffd-30c5-4b30-adbc-275e382f60f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
|
|
" <tr>\n",
|
|
" <td>\n",
|
|
" <table style=\"border-collapse: collapse;\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <td> </td>\n",
|
|
" <th> Array </th>\n",
|
|
" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Bytes </th>\n",
|
|
" <td> 49.43 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (151, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 3775 chunks in 8 graph layers </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
" </table>\n",
|
|
" </td>\n",
|
|
" <td>\n",
|
|
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" </td>\n",
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" </tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nir</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></div><input id='attrs-0b0465c8-241f-46d8-8596-ee4d04039c4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b0465c8-241f-46d8-8596-ee4d04039c4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83986637-0a86-45d6-b19a-e8f2d75d6162' class='xr-var-data-in' type='checkbox'><label for='data-83986637-0a86-45d6-b19a-e8f2d75d6162' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
|
|
" <tr>\n",
|
|
" <td>\n",
|
|
" <table style=\"border-collapse: collapse;\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <td> </td>\n",
|
|
" <th> Array </th>\n",
|
|
" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Bytes </th>\n",
|
|
" <td> 49.43 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (151, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 3775 chunks in 8 graph layers </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
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|
" </table>\n",
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|
" </td>\n",
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" <td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scl</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></div><input id='attrs-f412ceb5-f309-4381-a6c4-a5f70ced183c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f412ceb5-f309-4381-a6c4-a5f70ced183c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a14c4fc2-d2f5-48ce-bcb6-d5767619c89e' class='xr-var-data-in' type='checkbox'><label for='data-a14c4fc2-d2f5-48ce-bcb6-d5767619c89e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>nodata :</span></dt><dd>0</dd><dt><span>flags_definition :</span></dt><dd>{'qa': {'bits': [0, 1, 2, 3, 4, 5, 6, 7], 'values': {'0': 'no data', '1': 'saturated or defective', '2': 'dark area pixels', '3': 'cloud shadows', '4': 'vegetation', '5': 'bare soils', '6': 'water', '7': 'unclassified', '8': 'cloud medium probability', '9': 'cloud high probability', '10': 'thin cirrus', '11': 'snow or ice'}, 'description': 'Sen2Cor Scene Classification'}}</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
|
|
" <tr>\n",
|
|
" <td>\n",
|
|
" <table style=\"border-collapse: collapse;\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <td> </td>\n",
|
|
" <th> Array </th>\n",
|
|
" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Bytes </th>\n",
|
|
" <td> 12.36 GiB </td>\n",
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" <td> 4.00 MiB </td>\n",
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" </tr>\n",
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" \n",
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" <th> Shape </th>\n",
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" <td colspan=\"2\"> 3775 chunks in 1 graph layer </td>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-27fd4630-c307-43ef-9eba-3fddac951130' class='xr-section-summary-in' type='checkbox' ><label for='section-27fd4630-c307-43ef-9eba-3fddac951130' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bd71bfe8-2fc8-4883-a843-5b6909c09f98' class='xr-index-data-in' type='checkbox'/><label for='index-bd71bfe8-2fc8-4883-a843-5b6909c09f98' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2022-09-02 03:35:23.960000', '2022-09-04 03:25:18.037000',\n",
|
|
" '2022-09-07 03:35:13.646000', '2022-09-09 03:25:27.617000',\n",
|
|
" '2022-09-12 03:35:22.247000', '2022-09-14 03:25:18.529000',\n",
|
|
" '2022-09-17 03:35:13.648000', '2022-09-19 03:25:24.773000',\n",
|
|
" '2022-09-22 03:35:18.931000', '2022-09-24 03:25:17.431000',\n",
|
|
" ...\n",
|
|
" '2023-09-07 03:35:17.134000', '2023-09-09 03:25:20.648000',\n",
|
|
" '2023-09-12 03:35:15.326000', '2023-09-14 03:25:35.755000',\n",
|
|
" '2023-09-17 03:35:15.269000', '2023-09-19 03:25:24.089000',\n",
|
|
" '2023-09-22 03:35:15.439000', '2023-09-24 03:25:18.524000',\n",
|
|
" '2023-09-27 03:35:14.112000', '2023-09-29 03:25:19.046000'],\n",
|
|
" dtype='datetime64[ns]', name='time', length=151, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cfc0309c-aa7d-45cd-9ff8-340544bcb52c' class='xr-index-data-in' type='checkbox'/><label for='index-cfc0309c-aa7d-45cd-9ff8-340544bcb52c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1105735.0, 1105725.0, 1105715.0, 1105705.0, 1105695.0, 1105685.0,\n",
|
|
" 1105675.0, 1105665.0, 1105655.0, 1105645.0,\n",
|
|
" ...\n",
|
|
" 1017095.0, 1017085.0, 1017075.0, 1017065.0, 1017055.0, 1017045.0,\n",
|
|
" 1017035.0, 1017025.0, 1017015.0, 1017005.0],\n",
|
|
" dtype='float64', name='y', length=8874))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4621ab09-99cf-4adb-a653-3899b3922d32' class='xr-index-data-in' type='checkbox'/><label for='index-4621ab09-99cf-4adb-a653-3899b3922d32' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([554795.0, 554805.0, 554815.0, 554825.0, 554835.0, 554845.0, 554855.0,\n",
|
|
" 554865.0, 554875.0, 554885.0,\n",
|
|
" ...\n",
|
|
" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
|
|
" 653785.0, 653795.0, 653805.0],\n",
|
|
" dtype='float64', name='x', length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ac620903-7e8a-4ceb-acde-21a8fb21e681' class='xr-section-summary-in' type='checkbox' checked><label for='section-ac620903-7e8a-4ceb-acde-21a8fb21e681' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
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],
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"text/plain": [
|
|
"<xarray.Dataset> Size: 119GB\n",
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"Dimensions: (time: 151, y: 8874, x: 9902)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 1kB 2022-09-02T03:35:23.960000 ... 202...\n",
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" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
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" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
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" spatial_ref int32 4B 32648\n",
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"Data variables:\n",
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" red (time, y, x) float32 53GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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" nir (time, y, x) float32 53GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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" scl (time, y, x) uint8 13GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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"Attributes:\n",
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" crs: EPSG:32648\n",
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" grid_mapping: spatial_ref"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
|
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"source": [
|
|
"## cấu hình thời gian và tọa độ\n",
|
|
"date_range = (\"2022-09-01\", \"2023-10-01\")\n",
|
|
"longtitude_range = (105.5, 106.4)\n",
|
|
"latitude_range = (9.2, 10.0)\n",
|
|
"coordinates = (longtitude_range, latitude_range)\n",
|
|
"\n",
|
|
"## truy vấn ảnh Sentinel-2\n",
|
|
"data = load_data(dc, date_range, longtitude_range, latitude_range)\n",
|
|
"notebook_utils.heading(notebook_utils.xarray_object_size(data))\n",
|
|
"display(data)\n"
|
|
]
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},
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{
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"execution_count": 4,
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|
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" <td>[0, 1, 2, 3, 4, 5, 6, 7]</td>\n",
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" <td>{'0': 'no data', '1': 'saturated or defective'...</td>\n",
|
|
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" bits \\\n",
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" values \\\n",
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"qa {'0': 'no data', '1': 'saturated or defective'... \n",
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"\n",
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" description \n",
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"qa Sen2Cor Scene Classification "
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"{'0': 'no data',\n",
|
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" '1': 'saturated or defective',\n",
|
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" '2': 'dark area pixels',\n",
|
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" '3': 'cloud shadows',\n",
|
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" '4': 'vegetation',\n",
|
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" '5': 'bare soils',\n",
|
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" '6': 'water',\n",
|
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" '7': 'unclassified',\n",
|
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" '8': 'cloud medium probability',\n",
|
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" '9': 'cloud high probability',\n",
|
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" '10': 'thin cirrus',\n",
|
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" '11': 'snow or ice'}"
|
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]
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},
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"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
|
|
"</symbol>\n",
|
|
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|
|
"</svg>\n",
|
|
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
|
|
" *\n",
|
|
" */\n",
|
|
"\n",
|
|
":root {\n",
|
|
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|
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|
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|
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" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
|
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" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
|
|
" --xr-background-color: var(--jp-layout-color0, white);\n",
|
|
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
|
|
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
|
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"}\n",
|
|
"\n",
|
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"html[theme=dark],\n",
|
|
"html[data-theme=dark],\n",
|
|
"body[data-theme=dark],\n",
|
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"body.vscode-dark {\n",
|
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" --xr-font-color0: rgba(255, 255, 255, 1);\n",
|
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" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
|
|
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
|
|
" --xr-border-color: #1F1F1F;\n",
|
|
" --xr-disabled-color: #515151;\n",
|
|
" --xr-background-color: #111111;\n",
|
|
" --xr-background-color-row-even: #111111;\n",
|
|
" --xr-background-color-row-odd: #313131;\n",
|
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"}\n",
|
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"\n",
|
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".xr-wrap {\n",
|
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" display: block !important;\n",
|
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" min-width: 300px;\n",
|
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" max-width: 700px;\n",
|
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"}\n",
|
|
"\n",
|
|
".xr-text-repr-fallback {\n",
|
|
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
|
|
" display: none;\n",
|
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|
|
"\n",
|
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".xr-header {\n",
|
|
" padding-top: 6px;\n",
|
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" padding-bottom: 6px;\n",
|
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" margin-bottom: 4px;\n",
|
|
" border-bottom: solid 1px var(--xr-border-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-header > div,\n",
|
|
".xr-header > ul {\n",
|
|
" display: inline;\n",
|
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" margin-top: 0;\n",
|
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" margin-bottom: 0;\n",
|
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"}\n",
|
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"\n",
|
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".xr-obj-type,\n",
|
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".xr-array-name {\n",
|
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" margin-left: 2px;\n",
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|
|
"}\n",
|
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"\n",
|
|
".xr-obj-type {\n",
|
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" color: var(--xr-font-color2);\n",
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|
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".xr-sections {\n",
|
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" padding-left: 0 !important;\n",
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" display: grid;\n",
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|
|
"}\n",
|
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"\n",
|
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".xr-section-item {\n",
|
|
" display: contents;\n",
|
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"}\n",
|
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"\n",
|
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".xr-section-item input {\n",
|
|
" display: inline-block;\n",
|
|
" opacity: 0;\n",
|
|
"}\n",
|
|
"\n",
|
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".xr-section-item input + label {\n",
|
|
" color: var(--xr-disabled-color);\n",
|
|
"}\n",
|
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"\n",
|
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".xr-section-item input:enabled + label {\n",
|
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|
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|
|
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|
|
"\n",
|
|
".xr-section-item input:focus + label {\n",
|
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" border: 2px solid var(--xr-font-color0);\n",
|
|
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|
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"\n",
|
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".xr-section-item input:enabled + label:hover {\n",
|
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|
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"}\n",
|
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"\n",
|
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".xr-section-summary {\n",
|
|
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|
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|
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" font-weight: 500;\n",
|
|
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|
|
"\n",
|
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".xr-section-summary > span {\n",
|
|
" display: inline-block;\n",
|
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" padding-left: 0.5em;\n",
|
|
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|
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"\n",
|
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".xr-section-summary-in:disabled + label {\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
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|
|
"\n",
|
|
".xr-section-summary-in + label:before {\n",
|
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" display: inline-block;\n",
|
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" width: 15px;\n",
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|
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|
|
"\n",
|
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".xr-section-summary-in:disabled + label:before {\n",
|
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" color: var(--xr-disabled-color);\n",
|
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|
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"\n",
|
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".xr-section-summary-in:checked + label:before {\n",
|
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|
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|
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|
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".xr-section-summary-in:checked + label > span {\n",
|
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|
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".xr-section-summary,\n",
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".xr-section-inline-details {\n",
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".xr-section-details {\n",
|
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|
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"\n",
|
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".xr-section-summary-in:checked ~ .xr-section-details {\n",
|
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".xr-array-wrap {\n",
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|
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"\n",
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".xr-array-wrap > label {\n",
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".xr-array-preview,\n",
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"\n",
|
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".xr-array-data,\n",
|
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" display: none;\n",
|
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|
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".xr-array-in:checked ~ .xr-array-data,\n",
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".xr-array-preview {\n",
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|
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|
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"\n",
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".xr-dim-list {\n",
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".xr-dim-list li {\n",
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"\n",
|
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".xr-dim-list:before {\n",
|
|
" content: '(';\n",
|
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|
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"\n",
|
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".xr-dim-list:after {\n",
|
|
" content: ')';\n",
|
|
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|
|
"\n",
|
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".xr-dim-list li:not(:last-child):after {\n",
|
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" content: ',';\n",
|
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|
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|
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"\n",
|
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".xr-has-index {\n",
|
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" font-weight: bold;\n",
|
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|
|
"\n",
|
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".xr-var-list,\n",
|
|
".xr-var-item {\n",
|
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" display: contents;\n",
|
|
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|
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"\n",
|
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".xr-var-item > div,\n",
|
|
".xr-var-item label,\n",
|
|
".xr-var-item > .xr-var-name span {\n",
|
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" background-color: var(--xr-background-color-row-even);\n",
|
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" margin-bottom: 0;\n",
|
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"}\n",
|
|
"\n",
|
|
".xr-var-item > .xr-var-name:hover span {\n",
|
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" padding-right: 5px;\n",
|
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|
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"\n",
|
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".xr-var-list > li:nth-child(odd) > div,\n",
|
|
".xr-var-list > li:nth-child(odd) > label,\n",
|
|
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
|
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" background-color: var(--xr-background-color-row-odd);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name {\n",
|
|
" grid-column: 1;\n",
|
|
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|
|
"\n",
|
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".xr-var-dims {\n",
|
|
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|
|
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|
|
"\n",
|
|
".xr-var-dtype {\n",
|
|
" grid-column: 3;\n",
|
|
" text-align: right;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
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|
|
"\n",
|
|
".xr-var-preview {\n",
|
|
" grid-column: 4;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-index-preview {\n",
|
|
" grid-column: 2 / 5;\n",
|
|
" color: var(--xr-font-color2);\n",
|
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|
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"\n",
|
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".xr-var-name,\n",
|
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".xr-var-dims,\n",
|
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".xr-var-dtype,\n",
|
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|
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|
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|
|
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|
|
"\n",
|
|
".xr-var-name:hover,\n",
|
|
".xr-var-dims:hover,\n",
|
|
".xr-var-dtype:hover,\n",
|
|
".xr-attrs dt:hover {\n",
|
|
" overflow: visible;\n",
|
|
" width: auto;\n",
|
|
" z-index: 1;\n",
|
|
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|
|
"\n",
|
|
".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-data {\n",
|
|
" display: none;\n",
|
|
" background-color: var(--xr-background-color) !important;\n",
|
|
" padding-bottom: 5px !important;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
|
|
".xr-var-data-in:checked ~ .xr-var-data,\n",
|
|
".xr-index-data-in:checked ~ .xr-index-data {\n",
|
|
" display: block;\n",
|
|
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|
|
"\n",
|
|
".xr-var-data > table {\n",
|
|
" float: right;\n",
|
|
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|
|
"\n",
|
|
".xr-var-name span,\n",
|
|
".xr-var-data,\n",
|
|
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|
|
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|
|
".xr-attrs {\n",
|
|
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|
|
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|
|
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|
|
".xr-attrs,\n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
"\n",
|
|
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|
|
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|
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|
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|
|
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|
|
"\n",
|
|
".xr-attrs dt,\n",
|
|
".xr-attrs dd {\n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
"\n",
|
|
".xr-attrs dt {\n",
|
|
" font-weight: normal;\n",
|
|
" grid-column: 1;\n",
|
|
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|
|
"\n",
|
|
".xr-attrs dt:hover span {\n",
|
|
" display: inline-block;\n",
|
|
" background: var(--xr-background-color);\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dd {\n",
|
|
" grid-column: 2;\n",
|
|
" white-space: pre-wrap;\n",
|
|
" word-break: break-all;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-icon-database,\n",
|
|
".xr-icon-file-text2,\n",
|
|
".xr-no-icon {\n",
|
|
" display: inline-block;\n",
|
|
" vertical-align: middle;\n",
|
|
" width: 1em;\n",
|
|
" height: 1.5em !important;\n",
|
|
" stroke-width: 0;\n",
|
|
" stroke: currentColor;\n",
|
|
" fill: currentColor;\n",
|
|
"}\n",
|
|
"</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'NDVI' (time: 151, y: 8874, x: 9902)> Size: 53GB\n",
|
|
"dask.array<truediv, shape=(151, 8874, 9902), dtype=float32, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray>\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 1kB 2022-09-02T03:35:23.960000 ... 202...\n",
|
|
" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
|
|
" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
|
|
" spatial_ref int32 4B 32648</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 151</li><li><span class='xr-has-index'>y</span>: 8874</li><li><span class='xr-has-index'>x</span>: 9902</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-35603087-44ff-4a06-873b-5a01460f8f56' class='xr-array-in' type='checkbox' checked><label for='section-35603087-44ff-4a06-873b-5a01460f8f56' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n",
|
|
" <tr>\n",
|
|
" <td>\n",
|
|
" <table style=\"border-collapse: collapse;\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <td> </td>\n",
|
|
" <th> Array </th>\n",
|
|
" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Bytes </th>\n",
|
|
" <td> 49.43 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (151, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 3775 chunks in 7 graph layers </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
" </table>\n",
|
|
" </td>\n",
|
|
" <td>\n",
|
|
" <svg width=\"196\" height=\"173\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"10\" y1=\"24\" x2=\"26\" y2=\"41\" />\n",
|
|
" <line x1=\"10\" y1=\"49\" x2=\"26\" y2=\"65\" />\n",
|
|
" <line x1=\"10\" y1=\"74\" x2=\"26\" y2=\"90\" />\n",
|
|
" <line x1=\"10\" y1=\"99\" x2=\"26\" y2=\"115\" />\n",
|
|
" <line x1=\"10\" y1=\"107\" x2=\"26\" y2=\"123\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Vertical lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"107\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"108\" />\n",
|
|
" <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"109\" />\n",
|
|
" <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"110\" />\n",
|
|
" <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"110\" />\n",
|
|
" <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"111\" />\n",
|
|
" <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"112\" />\n",
|
|
" <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"113\" />\n",
|
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" <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"114\" />\n",
|
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" <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"115\" />\n",
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"</table></div></div></li><li class='xr-section-item'><input id='section-a55e4107-2bcb-44fa-9b0b-b07930b93190' class='xr-section-summary-in' type='checkbox' checked><label for='section-a55e4107-2bcb-44fa-9b0b-b07930b93190' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-02T03:35:23.960000 ... 2...</div><input id='attrs-1422add3-5690-4ad0-bd27-32cbd74eb3e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1422add3-5690-4ad0-bd27-32cbd74eb3e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5534b72e-8d6e-4f54-aceb-f40100c96152' class='xr-var-data-in' type='checkbox'><label for='data-5534b72e-8d6e-4f54-aceb-f40100c96152' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array(['2022-09-02T03:35:23.960000000', '2022-09-04T03:25:18.037000000',\n",
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|
|
" '2023-09-29T03:25:19.046000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e+06 1.106e+06 ... 1.017e+06</div><input id='attrs-d515c1de-96f9-4cb4-9ea8-2376a0fdf854' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d515c1de-96f9-4cb4-9ea8-2376a0fdf854' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0bea271-55f7-4385-bf13-bdc6977350ce' class='xr-var-data-in' type='checkbox'><label for='data-b0bea271-55f7-4385-bf13-bdc6977350ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1105735., 1105725., 1105715., ..., 1017025., 1017015., 1017005.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.548e+05 5.548e+05 ... 6.538e+05</div><input id='attrs-ed32a40b-fa55-419c-ba55-7f752da82066' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed32a40b-fa55-419c-ba55-7f752da82066' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec30dc85-56d7-497c-bf73-26368b463612' class='xr-var-data-in' type='checkbox'><label for='data-ec30dc85-56d7-497c-bf73-26368b463612' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([554795., 554805., 554815., ..., 653785., 653795., 653805.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-475d27b2-2f6e-47fe-9c3a-3ada41f2df6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-475d27b2-2f6e-47fe-9c3a-3ada41f2df6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-871c47ea-8ccd-455b-96ae-37447d47cc18' class='xr-var-data-in' type='checkbox'><label for='data-871c47ea-8ccd-455b-96ae-37447d47cc18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32648"]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-32b86fcd-ea61-4bf3-8223-90c0ea56a8b8' class='xr-section-summary-in' type='checkbox' ><label for='section-32b86fcd-ea61-4bf3-8223-90c0ea56a8b8' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ebd1bd40-a403-42ba-8b86-52aed9ff94dc' class='xr-index-data-in' type='checkbox'/><label for='index-ebd1bd40-a403-42ba-8b86-52aed9ff94dc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2022-09-02 03:35:23.960000', '2022-09-04 03:25:18.037000',\n",
|
|
" '2022-09-07 03:35:13.646000', '2022-09-09 03:25:27.617000',\n",
|
|
" '2022-09-12 03:35:22.247000', '2022-09-14 03:25:18.529000',\n",
|
|
" '2022-09-17 03:35:13.648000', '2022-09-19 03:25:24.773000',\n",
|
|
" '2022-09-22 03:35:18.931000', '2022-09-24 03:25:17.431000',\n",
|
|
" ...\n",
|
|
" '2023-09-07 03:35:17.134000', '2023-09-09 03:25:20.648000',\n",
|
|
" '2023-09-12 03:35:15.326000', '2023-09-14 03:25:35.755000',\n",
|
|
" '2023-09-17 03:35:15.269000', '2023-09-19 03:25:24.089000',\n",
|
|
" '2023-09-22 03:35:15.439000', '2023-09-24 03:25:18.524000',\n",
|
|
" '2023-09-27 03:35:14.112000', '2023-09-29 03:25:19.046000'],\n",
|
|
" dtype='datetime64[ns]', name='time', length=151, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c4ac72c8-3b0b-4cdc-a6a9-412923f47c35' class='xr-index-data-in' type='checkbox'/><label for='index-c4ac72c8-3b0b-4cdc-a6a9-412923f47c35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1105735.0, 1105725.0, 1105715.0, 1105705.0, 1105695.0, 1105685.0,\n",
|
|
" 1105675.0, 1105665.0, 1105655.0, 1105645.0,\n",
|
|
" ...\n",
|
|
" 1017095.0, 1017085.0, 1017075.0, 1017065.0, 1017055.0, 1017045.0,\n",
|
|
" 1017035.0, 1017025.0, 1017015.0, 1017005.0],\n",
|
|
" dtype='float64', name='y', length=8874))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f5cac22f-e976-4eea-9180-3396ae47c3da' class='xr-index-data-in' type='checkbox'/><label for='index-f5cac22f-e976-4eea-9180-3396ae47c3da' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([554795.0, 554805.0, 554815.0, 554825.0, 554835.0, 554845.0, 554855.0,\n",
|
|
" 554865.0, 554875.0, 554885.0,\n",
|
|
" ...\n",
|
|
" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
|
|
" 653785.0, 653795.0, 653805.0],\n",
|
|
" dtype='float64', name='x', length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-19ef1fc4-368d-4b40-a928-ffdade1b1942' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-19ef1fc4-368d-4b40-a928-ffdade1b1942' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
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],
|
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"text/plain": [
|
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"<xarray.DataArray 'NDVI' (time: 151, y: 8874, x: 9902)> Size: 53GB\n",
|
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"dask.array<truediv, shape=(151, 8874, 9902), dtype=float32, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray>\n",
|
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"Coordinates:\n",
|
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" * time (time) datetime64[ns] 1kB 2022-09-02T03:35:23.960000 ... 202...\n",
|
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" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
|
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" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
|
|
" spatial_ref int32 4B 32648"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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j4esjrbfB0lJp1u/aJ598QlhYGGq1mv79+9ukLIqIiIiIiFxvGAWTW7aWSLM1WL755htmz57N/PnzOXz4MD169GDEiBG1ypWLiIiIiIg0V0wIbtlaIs3WYFmyZAkzZsxg2rRpxMXFsXz5cjw9PVm5cmVTT01ERERERKROmNz0X0ukWcaw6HQ6Dh06xNy5c637pFIpw4YNY+/evXbP0Wq1NoqjJpOJwsJCWrVqJRYfExERERGpEUEQKC0tpX379jbVz0WaD83SYLl06RJGo5G2bdva7G/bti1paWl2z1m4cCGvv/56Y0xPREREROQG5dSpU3Ts2LHB+jcKAsZ6JufW9/zrlWZpsNSFuXPnMnv2bOvr4uJisyz2mpnsHL2I7t+9x7F7nnfrmGN3z0ElM2JCwvqB77m1b3vsyevBJaMP3tJKFBITg0KPWI+9dOxBvGVaXuq6rsY+Uk/F0CWk6QrCuUL/zW+xf9TLdF+/mFGdj3OH3zG+ungTn/f9qNZzHz80kxEBx/nPpd580e/DRpitLf/OvA1PiZ6/Rf5ee+MmYGnaOJ6J3dBk4/8n6xb+Fvk7v+T05/bw/TbH/p15GwqJiXjlWbSCjJ6dUhpkDi8de5C3u3/p0jnfZQ3mnshdbhl/U/ZAPKVahoYdckt/O3IT3NZXS6SkpISQkBB8fHwadBx3xKC01BiWZmmwBAUFIZPJOH/+vM3+8+fPExwcbPcclUqFSqWqtv9yRWt8fX3xCZK4PV89NriUSqMCqUTgpcyZlBrUfNmv4WJsRsbnsC0nFh+pngGhuTbHPr75P+zMja71GlU+8usmbz91krlac7sQLV1aFxHiqcVTI3Nq/nq1NypvBWFU8MWZcRwsCWVN/88bespWHu19kCn7p/NgHd/r/ltfZP+Id9w8q6vM7/drg/VdG+sy++DjK+GH87fT2kfC/sv9KDD4E6K4TFJlKIE+MjrIS9ha3ocrek9ucePndXN2N0ZFHGd1xgAmd7zg8nfhoV5Ham/kJD6+ErwkUvZcGoBaqqfUpGZ0RLLL/ezOjeRwZThD/Suvm+92c0YMIWi+NMuFOqVSSUJCAtu3b7fuM5lMbN++ncTERJf6imx/EYB2viXcvvNpl+cy8Jc5Do8V6jzxUWj4vO8qPu69Fh+5hrH/e4zJ+2a4PI6zDA9PQ+kg4ErmRCBWz06n3D2lBmfv7YsIlhdjEiROG4S3Baay/qK5aN/2S7FojIqGnKJd6mMgFeQHunEmjcOW7Dg+Shtaa7tgeTGeEi2/XolDLdWTrAnhtC6QUpOavh7ZlBrVFJk88ZNVIpW490lyVMRx7tkzk/N6PwaGZbu1b1fJ1ralwODHyIgUTIIUf2kFu3Mj2ZYTy+bsbi71FaE6z0WjF2P/91id53MwL5R9eWF1Pl/EOUwIGOu5tVQPS7M0WABmz57NihUr+PLLL0lNTeXRRx+lvLycadOmudRPrO95On+3gHMlvvwy5J/W/fE/znPq/Eq93O6PwJNH7mNd4md82Otr674+3jmEe13mTLkfd++eBcCryWNdmq8zXDZ52t2vERTszo0k61Tda5fsyY2otc24Px6ttc3hvE4czQ/hcF4nDuaFsjM3miWpw9mRE1OneR0oj0Dn5Md1bUY/1FI93yb+i/d7fsuPgz7mu4HL6zSus+zOjWRtRj8AVp1MdPmGcy2qAE2tbRI2N69SACMjUpBhYltObI3thoRlMDIihS/7rUSJEX9ZBb08cgmWlaARFAzwyEZjUhAoLyPW45zb5/ndwOXc7NX0y6LpFcH4yCoBGBqezqCwLAaFZSFDwF9awc7caA7ndar1O6kX5PhINVww+nBzYJbT42/MMlcN35kbzdqMfvxa1pU1lwfW/YJEnEJMa647zdZguffee1m8eDHz5s2jZ8+eHD16lC1btlQLxK2N81pfgv1LCfSqsNmffPcCAFakD6rx/MJT/sil1T0XOlP11bQ/y8KpNCnp4FXMj4M+ZuLef6AxKZh1eDK9fn6ZWYcn2x3DcqNzFh9p9ZvZ0fwQFBIj/lItFYKME/kdyDjVjhP5HVzq20+qJfd0zQZPQbkvsRtqDnAuFxR4SQz0Ds2nb2geZ/UBnNEGcMHoUyejJVBeTqnJuZoZk6MPcH/0PpfHqA8yBEpMHua/JQLlJhUbsnq5/G9r4c7IEw6PLUkdzpLU4dzSLrNOfTtLn/++5PI5FSYVekFeq9FiYWBYNsHyYvTI0AhyQuUl+En1tJaXcLAsnCNloSxOGeHyPGrjorFh4xScoZd3nt0loKHh6QwMy8YkSLls8qRcUNbYj49UgxIjp3WtCFVecnr8sZFJgNmAnBx9gLldN/Nx77WsOmnfi70oZaTDvlz9nWlqDud1auopiNSBZmuwAMyaNYu8vDy0Wi379++nf//+LvfxRb8PCfYqwUeptXt8RsxuAIeu1LyZz9t9Ol+esNr69zNH7mVJ6nBUUgOtlaWU6c2xNEdOd6RI70GlUUn31ucwCVff7jeP32X9O13jmkfk+6K+zDx0v/W15Qe9g6wM6V+Wd9dOZygwetK105lq5x/ND2FHTgxLUofb7d8oQMGZ9g7HfyXqZ6Z0Pujw+O7cSI5qQnk2d7x13wfZQynUebGnNJpvC12/iR8sCiVZE+LyeY3FwLBs/GXlrMvsQ6amLYfKwygyelJg8KtTf0t7fWN3/0dpQ2mvuEKwvJisstaM+v3J+kzbIbMOTybQo4JJex9x6bzn4rYyKuI4YfJituXE8kHqsFrPGRVxnNERyQwKyyIy5ByRIecYHp7G1MA/CFEXYkTCusw+1vbOGkM1cUYf6PDG3FhYfnscMTQ8nVxda4aH28+MtNA3NA+FxIifrIIioyerTiZavSd1YWrn6tIRqzMGUGG8GiO4OzeSLdlxrM3ox+bsbpw1+rAvL4wFx0fXedzGpHdofpONbckSqu/WEmmWQbfuRopAYaX9ZRSAKfuno5RdfStu3/m0zfKRI8b98SgnL7emfzsP9hVF8G3iv3j26ER6+J8G4LaIk5QZlKzp/znj/niUs+W2N69nj07k/Z7fEqU+b697wOwB8pJqmRx9tSxBL8881FI90w9O5fO+q3gubiurMwbQVXnW5os4KMzsHt6Q1YsCvR+Pxe4kOb8jpSYVl43ezO6yrdp4XlITxlq+Cz9e6WVjsF3LoLAsBgFPVLmvjAs5io9UQ3vFFbJ1bWoewA4dPYvQCzKXz2tMJkX9yY6cGPy9MvCSajljCCBaWeDWMZ6I3WH9e3K0W7u2siMnho972y6ZfJA6jKe6OB+oGx1yjozsboQoL9d5Hr1D8ynKieGMIYDUyg58lDYUhcRImKL+z1mdlQWkaduxJzeiyWNZaqI2o8ZC39A8yAtlV3ksEaoLVu+Ju6jqsTyYF0qpyYdykwqFxIhGUOAp1aKWGOnmcdqt4zY023JiKTV5MC7SfcHUtWH6a6tvHy2RZu1hcQe9Nr5Dkc6DQI8Kxv3xqN3A2/MVvqRfasOU/dOZtPcRlLLay3/3+e9LXNZ40cqrgvbqIr5N/BcAW/NjuazzZlHKSELVl/GQ6QFopSpH8Ve/i1JGcrN3Oh1UVwBqXL7YVdSZydEHrEtXqzPMGQXZ2jZ08bq6vn9/9D6HTw0Riks8FrsTgPhOp9ELciZE2U9/DOt4DpkELhodfzSqGivOBunNiduCESm+fxktbx6/i9UZA5w6F2CQz0mSSpqvh8XC0PB0RkakoJAY8ZVqUEiMHMwLdamPZWlDGmZyVei/9UWHLv6h4dXjO1wxVixkaIPrfSMYGp5Ob9UpwlUXeCJ2BzNjdjEyov5pzlKJiVjVuWZtrLjK1tJ4vGWaBr/56gUZoyKO4y8rx0uqxV9agUmQUmj0xFNi35PdXBkensa4yCMsTx/c1FMRcYIb3mDx8dRxqsifUp2KCoP9teBtty4lafQbHD4XwrrEz9g0qHadj16tT6M3yojyvcQb8Rut+4/fvYD0kjbMidvC3K6bCVaVMO3ANELUV4jwNq8vz4nbwpCwDMqMtcdkWDJNzuv92JkbTZ42iHKTin1F4fjJKlicMoL5yWMcnr8tJ5aLRi+bffZuSFUJ63iOnRWda50bUC29uibKjGrOGALMP3BIrIZa4i9zuH3n0yw8McrueeszEwiWF9HHz/mxmpoBobl4SrVoBIX56dcFLMZlQ7J/xDtEqxx79tzB0VL3GJhdO52xu0xRVzZnd8NLoqO1rNxtfTYHDlwJI6PStRi/umAx8vyllSgkBgoMfnhKtUglJvTIrA9XO3MbyAXYAMyMcY+2jjPUN0PIsrVEbvglobJKJVLMSwnnSnzR6uXE/zjPGnRblZSxr9Xa34MHHiKrOIj/Df/KYZux7Y5a/95zKYLtty5hfvIYvGW2Tx/zuv3k3EUAPTzz+L/zt3CzfybB8iIeDv6dNrIyTurbsOlyDw7ndUIhMWFEQoauDROiDvFq8lhu8pJSaPQmOb8j8Z2cd9ee0QY43RbMGQc1uaFXZwygj2cRFw2+pGvbU1rFWDt/2Y+EmOMEyMt56dg43u5uK2hm8QYNcmKc5sSQsIymnkKNNPST+Bf9vmjQ/uvC5uxunNEHoBNkzfJzFLpyEXkPOZZScMS+vDCGBEUTr65ZtmB5+mA6KArrpPdyLRZDfEdODGcNARgFqXXZdk9uBErMqe6n9K1oLS/BS6qtNR6nJWAUqHXZ3Zk+WiI3vIela3ABugolu25bTNLoNzCZJAT7lNLrZ8cpoVHfvuHw2IEznfjf8HdrHDO7srU1+KxMZ/bqlBjUaO1kFjnL76WxrOn/OTNjdlFk9MKElCKTB5Oi/mRK672UCCrKBTkmQYKXVMvR/BCyylsjk5jwkVWSpqv5yevaZYt1yX3YkNWLo/khbM7uxtH8EPblhTlMsawwVRfts7AlOw5/WTl6QU57xRX0ggxPqQ6Am7e9gI93JREeF4lVnWWYj+PsGAC1RF/jcRHXeD5pgsvnrDqZ6DBgu7kzKuI4YcqLhCkKm3oqdqmLsXL37lmkaDsQqzqHQlLzcrYME0ZBahPEXF+GhqczLvIIE6IOMTn6ADNidqOWGDAiIVvXhl1FnSkyeorf3b8wuWlridzwBsvq/v8k94EXra9P3jOPVupyhrR3nBIa3tr2xyxu42v0+vllxv3xKIJQuwri0l7fWL0n+0e8w7NHJ7I1rwutFHV3Qb/XY7317wlRh7hs9LbJmrFkIPUOzSdQVoYMgQ4eRXhJdJzRByKTmPUxdudGAuZU6g9Sh1njSNTX/NB1Cz1LhOISMgRGRRynZ6dTDAjNdbjmH6ZwnE45MiKF0RHJZOnaUGT0pKPyMt08TvPs0YlcKPYmafQbzO6yjSFhGbUuV42MSHFLlkhjsiGrV1NPwSEZpa1dFhsrNHoTLC9mc3Y3tmTHuTxmU6eUDg9Po8jJFPnmzIMHHgLg/nZ7ydMGsaU4ngytfSVwC/6yCgqN3pyo7FjjUnJ96R2az6CwLB6L3YnBJMNXpqHA4M/Kkzc12JgiNz43vMFij3WJnzlMGwVzTEtiFYVbmdRE99bnGBiQjZ9XpcvjxXqc4+7wZF7ptqlO87WHj7SSjMo2HMwLxVeqQSMorO7YIqMnl00e7L0QzgltB87p/Ck3qcjVteai0Zc9uREEysqQSkzkaYNYnDKiWszKnJDN9Ox0yqllpM3Z3Sgyedaa0vhE7A58pRrO6/35rbgLu85F0SGw2OVrT9O2r1faZmPzS1E3fsqOr7NoXkOy8eZlbLx5mcPj9tKSPaU61FI9BQY/vrnUnyeP3OfUWOsy+7AjJ4YTuvZN7qHpICtr0vHdgUX1eULUIV6P/4EPe33NobKwGo2CCVGHOK0LJKeiFV08zrAsbUiDf5fWJX5GiLyQSMVFPKXaZm3ANwYmJBjruZlomeUDbvgYlrpSob0aoOvnoeFsuR9tVKW08qjgySP32SjcXsuytCEYkWISpFSYlEglXvjJXTd0auKT/KGMb3+Yy0Yv9MjQC3LKDeZlGRPmteRov4t0UFzBR1bJaV0rpBITXiYtBfiRrW1DD488Lsp8bVKmLewq60LNknpXGRVxnEl7H+HuoKO1th0ano5FvH3krqdo61Hq5ChXsaT2bsuJta6J78iJqdU701QsT1jN8vTBKCWGpp6KS0w/OJVwDzXrMxNI17Rjzcm+PN11B77SSjQmBUZBitYkp6OLn+1WsjJKjWpWZwxodIE/C6cMvhTlhVq/P+6I6WgOWDL4nk+aQFeP0+TrgthzOYItgz+wtrk2dm5nbrS1xlJDcdnoRQd5CTIEioyOJSZaAibBvNW3j5ZIi/SwOEPSaHMcS8TXb+Mh11OiU1FuUNHJ6woB8ooaz30sdideUi3tFVfwlmkIlJUzt+tmt86vtUcZXlItJqQoMHLB4IuXVMu+vDA8pVouG70ZHnACtUTPpKg/eS5uK7O7bGNy9AGkmOjtkUsraYVdY+VEfgdCVc4rZgJ08zlLhPKCS+dsGfxBvYpFWtbrt2THIZU071XdmTG78Jdd/dxYluaaOx2Vl1FLdXRUXmZC9BFaycqs3rkw5UU6eBRZxQpro5O8kKHh6Wy60hONoECGiQ1ZvdiQ1cutMRXOMDQ8HRkCIfJiWstKr6uMFmeoNCrYVRRLqVFNZ98LLE4ZwYtJ4+22HRKW0aDGCpiXcuM7neay0RtAXBoSqROih6UGHjzwEAF+7RgQlMO+S+GUG5WEeVwmtcz+OvGytCHWlNRCgzfIzdk2kWrXbuTO0E5dXO3pNDm/I2cMvmgEBYUGb3p75DpMOzYicajb0rXTGbQuxhkM9MqwUfJtDGSY/noyTHGqBlJTY8nKWXnyJoLlHm7rN/GXOey9fZHb+rPgJdeyrzSKIX6pXDL40sszj3GRR9iWE4u/tILh4Wm4srBjiX/q55NFhUmFj6wSjUlJK1mZ9UZWlbUZ/YhWnueoppPTAmqu0JRqpw3Nx73XArDg+Gi6elxya1p4fZgZs4ufsuNJqnBNm+hGwrKsU98+WiIt2sNSU6YQQKlexaFRb3FZ5822W5cSpCzjRGk7fORa5iePsZHXf+nYuGq1bvaWRBKpvlAtg2baAdcKOF7LS8fG8X7Pb6vtj+90mlP6Vuwqia0xvVEpMdaaXujKj7n5BlbZ6CJcg8KyrE+G15MA2EOd/3DrE23BJT9m/PmA2/qzEO95mo6qK1YPncXgGh6eVi/xNsvNUy3Rc6wyBKnERKu/Ykoshueqk4lIJSYOVobTWl7ChqxefJA6jG05sdyzZyYH80JJzu/IifwODmMiIte9RefvqssXtCRUUj0bzic09TRsGB3h3ni+urAnN6LJvDz1jV9xh8FzvdKiPSz+Hhoi1r1F9iT7hsuGmz4FIMLjIgDv9/yWKfun83nfVYBZWh/MdYFkEjl6k5znkyZQaVSgkvqR6JvF4bJQOqiKWJE+iGKjJ4UGLyYEneSD1GEcLu3EtDa77ep1jNz1FB08i+nqfaaahH4frxyH16SW6hkTcJhSkwc6B1L2GkFR8xvjJAfzQukbmsfw8DSX1VxF6sfqjAH4SCt5ecVUfCs82GaIgz6uS+jXxPbCLvgr3Rt7ZcGybNlOUYRJkFpTXvdURDMQiFReoNTkwWlTK7ykWrwkOowKKYcrw7i3zUGMSNAIMvylOjQm8+d5fWYCp/SB9PXI5h9H7+fZnjupMKmsFdOD5GVue2+uF3p75FLh71hyoKUyMCwbsS719UeL9LDcvXsWAOeKfB0aK1V5Lm6r9e+u3lfl8MuNKj5IHYZWkKOQGLli8KSj8grRHhc4U+lPqdGDTft786/fh3JSE4zGpMBTqsNHWslTXX7ly34rSao03+ijFy6xGXPL4A+4ovMgTnWmWnZJTYJf90fv+0vnRMuhinDWZfaplgYcLKs9M2ddZp9aZfdlVWIXXFVzFakf90fvY2xkEtMe2ILeC/z+NN+U3HlDXpf4GccLXSvM6Yhr059jVefQC3I0goJcfRAFRj8WHB9t810zIuG5uK38VNSLM4YA8zKmRy7Rygv4S3WUmtSk6YOscVhGJMSpzrDo1Ch6tztFX48chnmn0NXjNG/Eb7xhjZUdOTEOyyy0klbQw/P6X/p68MBDTNz7j6aehlswCRK3bC2RFmmwpJwzi6hpymsu226P7Mog699RHheQSkykl7VFY1IglQgYkdBWUUSI5xV+LOiOvESKPFDD+qQE/nc5kiBFKRuLrrpovz9jdmdnzJ1dbaxQz0J+vNIbjaBwKShRhkBSZSgJnjmUGs2xEhuyerElO47N2d04pAmrtQ+lxEiuPqjGNhqhRTvomgXPxW3lHw/8TNKHzzRI/7WJJNZE1SBPU5WfmlUnE7lo9MFLqqXCqEIt0aMxKWyyVwaFZVkzd3p75aIRFBQZvTAKUipMCgqNavL1gTbZPZOi/mRkRAqbBn3ErODt+Ej1qCVGurq5AGVD4mx9rVt3PAuY3+Oh4enMidtit13v0PxGLezXEEzZP538sgD2p0YwZf/0pp5OvRGXhOpOi7rj3LX7CVLOBGPUKrjtt9lEdnS9j2BVCWBOGwyUy9iQ3xOFzGgtfjh53wyGBVbQSXWZU+oAWt+SRlJBe0xnPUgrCSHL/yxSyVXPRF6+Y6PAW65lafw3LEsbgo9M49T81mcmYMSH7Zdieaj9RaJVBSRVhtJecYUKVGhMCj5Nu8WmkrI9nPmRcyVuJPzfb9Mj9DQVBqVTlbBFnKe5eg5+yu1GdsU/iPC8hF6I4/Dxu6gwKenmYSRX1xoZJkxIyNS2paPSsfLs1M57eebIvUR7nCdd257eHjmcMQTQSu5YS0WGgF6QopYYqWjkYPD6cH/0PpanD661tk2Ur3mZ+p0e3zfGtJqUNf0/J/GXOXVSARa5sbh+vsluYNOgj8ie9DK+ARWEeRdSrHFd7fKN+I18kDqMUxUBHCwKZc/tiwjzufpjaxCknNf7AdDPP4d26mIMBhmSdhrad76I1iS3Ua3Ne2gOLx0bx/NJE+jz35eqjQWQUtGeny91d2p+E6IOmVOZgw/QRlbKWX2AtUDZZ6dv4aX9f6N3u1Nszu7Ghqxe/JQd7/J7UBce6L6f8W0PIwgSjuaHcCK/Q6OMK1J/Ir5+u07nxQRdIMTjCp09Chjim0pbRTGeUh0XDb4Ey4upMKnoqCyknaKIONUZa9E8R5zX+xGvPkWGLphJUX/WqJ3SNzSP+E6niQ45d91lAzlTiG9FH8e1zG5EGiILrqkwInXL1hJpkVedfPcCPGQ6Aj1q1lNxxCWDNz18T1OmN8cN9PbJ5/mkCcRtfI3uPmcIkpdyTudPhVFFmPoyPTqcoU1gCXtuX0Sc59lq/b3dfQPv9ViP3mA/SPbj3mtZl/iZ0/OzFHXTISNMcYnHYndyuCSU7IutyJ0yl1iv8/ynsDf+0gp+LKxZdXJfXhjbcmJZnTGgXqnDoapL7CyKJft8ED07naJrpzPWY3tyI2qNl3EH14v2SVNjkXwHc6aNQmngsUNTXOpjXWYfbg7MZKTfMXykGoyClBDFZdoqiglRXqbI6EmM+ixGQYqXVMtFow+t5SUO+zNiFmEcGp7ORYNPna+tqdmQ1cv6/rpaEkHkxkBwQ/yKMyVibkRapMECcLbSj3h/s/FgySJwhhXpgyg2eKCQGIn3P8szR+7FR1bJf/O6cFPHbDxlWkpNamQSE58nDWT3lShGBSXT2sNcR6impyeLWF1Vxv3xaLV9H6UNtWYoOWJy9AGGhGVYl22+6PcFJ++ZB0CM+hy3+J3kp6Ke9PKu+elTIyjQCArUEj2e0roXL3uo8x983ncVWdcEOf+UHU+RydOhXkx92ZETw57cCN48fheDwrJuCKOloaXUq4r5eXhqCW1VSJTn+VrP+yk7nsN5nfgpOx4vqRaFxMifFREUGT0pNHojk5jwl1UgxUSpSY1aoqeD4grB8mI6yIoJUxQ6NIo7qK5wq08qgMN4jebOivRBZGvb4CXTMXnfDMa3PdzUU2q2dPtxXlNPocEQY1jqTos1WHwUWor0Zoloy9KLM8yI2U2Qoozn4ray/XRnlvb6hh8v9ODusOOUG1TM7rINf1kFRkHK2Lgkjp7qSHJ5R/oEOJdFc61Gi49CW62Nl1RrV4fFGTZk9cJLqiW1sj1yqamadsy1+Eq0+EsryNMFUdAAT7ajI5IbVGVzaHg6A8OyiVKbAy8HhWU12FiNhcWDVhVXlWIjvn67xqyLsDULAeje5hx3tj2Oj1TD6owBfJQ21G77j9KGUv6X3pCXRIdRkFJmVKMXZPjIKmktL6GVtAKNoCBTG8zsLtsYHp7GqIjj6AQZWfrWKDDhKdWzOzfSZpxpB6bhJ6vEU1r9u3A9MSNmN8/FbaW1spT+fjkYW8hT8qqTiS6fc/zuBbXqZIm0PFqswfJlv5V4yHS8dGycy+dashmO3vUmYC4gd17rS6y3+aaokBjp5ZlHtMd5RndOJr20LSoH3olrK6Z28ijkmSP3EvneEus8ryVT09blOVtQSAz8r6wz57W+3OZzwiY12R5njH7oBTmHSzrhK3Uu8LcuJOfXIQLaBbyu85tdbbSSlblUPTm07WVCPR0HuuZOmcubx+8i0usiekFGsdGTVrIyuqrOVPPuLUoZyROxOwhTXCJL35qSv7wnUokJT6mOTE0wekFOiaDCS6ol8JpgWYsIXamgIEPXhgKDP2D2SCxKGckX/b5gZswulBjr9H2tKyvSB/Hm8bvo8dOrPHPkXrf1+3r8DzzV5ddmoz7b0NT1Oo/c+RYAYR8vdud0mhyjIHXL1hJpmVf9FwZBRm5FK7f09XnfVZzV+rM4ZQRqiZ4JUYcwImVpr29o51Hi0I0tk5hsqhy/Hv8DRXpPPGKKHI71y5nYGiv/1vS0va24G108zvL3oL2UmsxLW2sz+jlsX2T0QioxcV+bfXhK9TXGsdRHOdKZqtD1QS/Ib4jlIEec0rdCIyi4aPSttW3oZ+9xW5t0bvI+aROvci2vdNvEG/EbUUn1eMs0rLmQyAWjD7Ee52zaWT7bA0Jzra7q45oQ2sqL8ZZpuGLwxFOixVei5YLBl2g7acbpmnakaDvgI63kosGHVrIyZsTstvneDAzL5u3uGxqt7s9pXSDHSjsQ3+Ys6aV1f0gQqR+5s55r6im4FRMSTEjrubUM79y1tGiDBSBI5b4y81EeF3gubivHKkMAOFxiFoUb4GtehrDoUixLG2I9R2NSUGFU2hgZX/T7An8PszcjYXN1t2i/Nvl8edHWOIj65k3r3wtT73A4x2iP83hJteTrA1FIDIQqL6KW6vkgdRhLUqtXhrk/eh9DwjLI1rZFhlBjKvNZXYDDY03NuMgj1mKJNyIPdf4DwKnqx+pWlbzSbRMXDb7EeZ9lUcpIZh6632H7VrIyOikuo5Ia0JgU+Mgcq9/KEEjXtuOS3hv9Xzo9njIdRSZPNIIctUSHWmKoZjyakNBaXoIeGUakdotyWrCnDN0QtFUUE6x2HAgsIiLSuLQoHZZrsZRirw8r0gdxoDScFX2+slHpBLPhsSJ9EF5SLWsz+hGgCASg1KRmSepwguXFVBrD0Qsyzuptb/Y9W5k9DodGvVVtzBB1IXpBZpVhD1u2mH8M3sP85DH8kBdP0ug3q51jYevFrkxpZ3bRjo1M4pkj9zIu4E9QQqCsjJmH7idUfZkeHvk2sSUxqrOUmmyF9pakDqenOp+h4ekADPZOrfG9euzQFO4OOFyvOjT1oaECe5sLzgqEpY83BzRaCgpuyY7DT1bJhqxedvtI1bQnXHURf0UFXlIdshoqY3tJtTZekY1ZPcjVBKGW6Fl3pT9BijJ8ZRoK9H5knLwJKSamdt5LN4/T+Eg1FBj8kNH0lbcXp4zgcEk0cd7n8JZp6esrKjm7kyn7p7Om/+dNPY0mQSx+WHdavIelrliWcTSCghV9vmJ5+mDrsU35Xa3Bs2HKi5zSB6KQGLmk9+GlY+MoM6opM6rZeqUbcZ5naaMspdjgadP/tZWPq2YLze26mT6eOazONS/ljOp/lGKDB6sO3MTj0eYsJEeZRDE+5+kgv2JdV17a6xsGhWXRWlaCXpAxxC+VQoMXe8ujbM7bXtrVpgbRqpOJhCkvWY0Vy3tRE8sS1tTLWKlpGUyk7oyMSMFXWolCYrB7/Cavk4QoLjPK3xzs66i0w768MPyltlIBYyOTeKfH94yNTGKAdxYB8nJSKjvwWOxONCYFUzvvZV1mH3yklQwJyyBYXoy6Htlo7uK5uK2sHbCCV7pt4u3uG3iqy682S7ci9SNQWeFSduaNhBjDUnda5lW7AUvg7ROxOwDbdGVftZYzFX5M3jeD7wv7ckYbgF6QoTXJKdJ7klHWhlKjGq1RzoyY3VzRe/J6/A8A1grQF7TeNuNZCjFajJBREcd5MNzs/i8xqEgpacc9CX9an5rzta1sMol25kazLrMPHVRX7GbKDArLwihI0QtybvFJw1umsdHeSPDK4efiHtYfmamd91Z7Gq+tAnR9KRdcL6Ug4hy/FcdSZPRiS3ZctayOPysiUEiMXDZ6U25Ssuay/bJxA0Jza1wynBx9gCdid1gr9T4WuxMwS+pbPjuNtdxTF6qWDhAxsy6zj92l5NoIUpQR9Ffw9bWJByIijhANFhfZmNWjWjHBqsxPHkOEz2XkUhOBynKWJ6ymVK8mW9sGnUmOXGqknbqY93qst4rBLe31jfXcAp0vLyaN57uBy5nx5wPV+o9UX7D+bYnJWNP/czzlOjJK21iPVVXTBTirD0BjUlSr/FwVL6mWVrIy/KUV9PbIpbv3KeuxSVF/kuCVa62M25Dsywtjc3Y3m/d5d25ki32qaAxW9PmK+6P3MTIixSar49Ydz7Iuuze5uiCOVXTChJQYz4IGzdbRNVGNKleDsm/e9kIDzeT6YVLUn4QpL7l0zjNH7uWUJgCNIGdRykgUEiN3755F6JfvNNAsa2b4bw1Th8sR5qDb+m8tEfEO4CJjI5M4pb+aWfR80gSb4wqJkU4ehXjKdfjKzYGz7dTFZFS0oaPqCuUGFd5y+ym2ekFGqUFNkML85BGsKqkmV255KgV458DVCq3rEj+jvWd1V70lA+iy0dvmRrQxqwcrT95kk3ExKCwLf2mF1RCqMClZm9HP6govMXkwNWAPyfkdG0y8bE9uBHpBhlqiZ3h4GrMOT+an7Hg0gsKu/ohIwxLle5GwgCt8nHXrX7L6PrRVFPF29w0NNubMmF1szu7WYP07wlWNnvoUhryRaC+/4pIKdplRRXtVMRtP9+CCzpdAeRl9AvLoFWkWsey/9cWGmqpdtt26tFHHM7lBlt/UQm/dLTrotq5YMjKguifD4u6uSqVRwbCAFL4p6EuMz3lUDmIF3u6+gSeP3Mc5nbkWUYC83Bpc6ynVWpd7LOTeP9fmddUg4kUpI/n1fBe23WrOtqi4JmB2bGQSW7LjyNAG8/vx0VZ3d1WXvlduBH5SLe0VV1hwfDRpZZ3prjpFgdGPCMUlfsqOr7GeS+yG10kbN9/hcXtYxj+YZ86wqjQqKdD715iZItJwrOjzFc8nTWDToI8addyGFBO8nliX2YdJUX82ydibs7s59e+gF2T4SHUczTdnR140etW4PLyiz1fEbXyNDn7FvN/zW6bsn47OJEctM9Bz0yv0alO7qrJIy6RlmmmNzNJe33B/9D5uCszinMYPExI+SB1mt+2Hvb62xp5UGFVUmFTkalrxfUFvh6Xnrw1GXZ+ZQIii0ObJQW3HSNpe2pVzen+GeZ+w2+/AsGy6djqDXpDRUVlIodaTgWHZBMrKKDKpiZAXWscDqi2Vvdit/hLqCT65hCguVwvmFGk8rjXKG4u7dj9h4+FriTSVsQKw7MytTrUbFJZFz06n0AtSzhr8yNW1rvWclLGvWX+fYr3OMyQgnXWJn3H0rjf5ot8X9Zp3c6cpg24/+eQTwsLCUKvV9O/fnwMHapAPGDIEiURSbbvzzjutbaZOnVrt+MiRIx32WV9cvurff/+d0aNH0759eyQSCRs3brQ5LggC8+bNo127dnh4eDBs2DAyMmwD6QoLC/n73/+Or68v/v7+TJ8+nbIyWz2UY8eOMWjQINRqNSEhIbz77o3hfg3zvExWRWsUEkONUfJLUofTVlHMJb05+LbSoHCosXFtds6EqEPVdCye6vIrq04m2lRnPlHcDr0gqzFQEszBtOf1fgSqzEbDkLAMhoRl0LXTGVZnDEAvmIs2bim2rShdHyXPckHJvrwwa1XSIpOntS5QYy8XpJ1qX2sby9OliPsY1CqDaOV5unvk2xjrjsoDODLo7fHm8buYuPcfjPr9yXrP81osBvz1iGXuK9IHUVBmLsXh7Ge7b2geKwtuJkvTpvbGVXil2yabpe4bnfqLxtVtSeibb75h9uzZzJ8/n8OHD9OjRw9GjBjBhQsX7LbfsGED586ds27Hjx9HJpMxYYJtGMTIkSNt2n399dd1el+cweWrLi8vp0ePHnzyySd2j7/77rt8+OGHLF++nP379+Pl5cWIESPQaK7Kuv/973/nxIkTbNu2jU2bNvH777/zyCOPWI+XlJRw++23ExoayqFDh3jvvfd47bXX+Owz5ysWX8u0A9N49uhEayDrXbufqHNf19Jvy9zaGwF+sgou6rzp5FHIkbJOdFZXV/wE+CB1GKc0geRoW+Mt07K01zfsus2+PPVHaUN57aRzT6CFRm9KjR7W15tv+ZDbfRwv6VSlm8cp7mld/Wnv/uh9HK80y+qfqfSvdrwuqqTDf3sGX4kWvSBj95Vo2sjK8JVq8JRquWD0ocDg53Kf9SE2pHqF7Wvp2elUrW1ArBjtCgM9M+gbmkewvJjWsqsCbk/E7qimqrwus49TonkWXum2iVDPQtQyfbU4sfoyIeqQW/trLNZnJiCTmFiUMhIfWSVvxmxkW04sJhdqHn03cDllRhX9t77IPXtmNuBsr1+MgsQtm6ssWbKEGTNmMG3aNOLi4li+fDmenp6sXFm9/AtAYGAgwcHB1m3btm14enpWM1hUKpVNu4CAhhMQddlgueOOO3jzzTf529/+Vu2YIAj885//5JVXXmHMmDF0796dr776irNnz1o9MampqWzZsoX/+7//o3///tx888189NFHrFu3jrNnzTeGf//73+h0OlauXEnXrl2ZNGkSTz75JEuWLKnzhX7R7wtOVQawos9XPHnkPjYN+ogXk8Zzy6/PM/CXOU73Yy+i/MDIhU6d+/253gSrSris8+bOgCQOl4XaXRoqNnrQSlFOiUFtNyamKv6yCqfHn91lG0cqQqvtd0bfZHREskNhso5K89KQJevJwsqTN5GsMT+dOfuUtiU7jrvbJSGVCPxa2g0vmY4Tuvb4SCspNanxl5m9PPvywng1eSyrTiayOzeySYI064KldlPWqXYNNsb18l7UhiUIdkBobjX9nqpxZFC3pZPbfE7wtzZHiFYV2OgotVR2lcRQblIRozKXXvjmUn+MgpTLJk8bz2xtfNx7LQFqc8zZzEP3N3oQbUuipKTEZtNq7Sd06HQ6Dh06xLBhV+83UqmUYcOGsXevc57wzz//nEmTJuHl5WWzf+fOnbRp04aYmBgeffRRLl++XPcLqgW3xrDk5ORQUFBg86b4+fnRv39/65uyd+9e/P396dPnqhT9sGHDkEql7N+/39rmlltuQam8Gig6YsQI0tPTuXLlit2xtVpttX+8azn8u/nG/GEvs8vqnR7fo5bruVzqRfi/33bqGlt71F3Kf2BQNt+k9+bPiyFUmFS0UZaSUdmm2hr9vG4/4SPTEKau+R9+efpgl54qwRyPYMls2pIdh5dEj089ixo6cuc+1PkP+nqYl5s0fy0bLUoZyfSDU61trvXAfHXhJv559Db+WxpPkKKUEYHJ/Holjt/K4vizIoJSkxofqYZsXRvSy9oSLC9GL8hJ0XSw9uFKxkJd2JYTy+G8TnaPHc0PqXH8Q5owTuR3IDLknMM29WVUxHG25cQ2Ws2d65UjlWGc1ASTqwvikt6nXrWwrlcyqhjO3bzOsL80An9ZBZOi/uSLfl8wMiKF4eFpjI5IZnXGgBpLOFSlnUcJQapyskqC2D+iadKVm2vsU30zhCwbQEhICH5+ftZt4UL7D6+XLl3CaDTStq1tTay2bdtSUGDf01+VAwcOcPz4cR5++GGb/SNHjuSrr75i+/btLFq0iF27dnHHHXdgNDZMGRS3GiyWC6/pTSkoKKBNG9s1TrlcTmBgoE0be31UHeNaFi5caPMPFxJS/Yk+c87savt+GfJP0sfPIzEyx5lLZO2AFU61u5ZJex/hREk7Tt4zj9JKFR9kD+VQcSc+7r3WriCVXpDxyVHHT32zDk92yVVblXbKInJPt8OElHxDAF9cMrvE7d1oayqk6Ax6QcbBvFCrLH6c+gxjWx2yVhUeEpbBusw+1lpGd7VKol2rYr5IHYCXVEuk4iIjAo4jRaCHRz4pmg5k61pzVh+AXGKiwODHBaMP+dpAduTEsCU7DiMSmx/i+nKtd2h4eBq9Q/MdXK+0xpigJ2J3oG+EWHdLloYrT8YtjQB5OW/EbzQbvGXtqnltWgLRfxnOy9KGcE7nz1C/VIfiffdH78NL5lzV8y/6fUFuWSB+KsfZfR+kDmPi3n/w5JH76PqDa9mEzvCfvO61N2oCTILULRvAqVOnKC4utm5z5zoXnuAqn3/+OfHx8fTrZ1sod9KkSdx9993Ex8czduxYNm3axMGDB9m5c2eDzOOGyRKaO3euzT/cqVPOxRRYqKshYo9eP5sLFg78ZQ53754FgIdMT0fPIgCmxuxj/4h3OJhq/0n8g9RhPBe3lS4drxpni1NGsD4zgZUnb+KD1GGopIY6B6rFq08R1vEcnlItYyOTuCvgKNtyYsnVB9m0W5E+iP8W1u9LPygsy1r3wqLd0kFWbBM0pjEpaKsoIkJ5AR9ZJXMi/4tEYl7uytK3JkJ5gT6e2RiR0Nsjl0GeJ4lTn2Fa290UGr3ZWhjPcL/jaAQFXlItekFOuRvFx7KveV9qom9o7TVnnI13qS9DwjIoMnrV3rCFYlGnnhGz263f/+uRx2J38nr8D4TJa/bqWjIYB293XEHZony7ZfAHSCWCw3YqqZ4gZTnZZUEIgoQeP71qt9hrXdEbZW7rq7ni6+trs6lUKrvtgoKCkMlknD9vmzJ+/vx5goODaxyjvLycdevWMX369FrnExERQVBQEJmZmc5fhAu41WCxXHhNb0pwcHC1qGSDwUBhYaFNG3t9VB3jWlQqVbV/vLry4IGH6nwuwJE736LrD/MJ9iqhlarcWleonbKYl46NQ/uXWmze9OpKmfOTx7DkgHlJravfOWYdnszajH4E/iVjfdHgQ3vFFbsBrs5iefoOkZn7bC83C87l6cw3ZssPzoyY3XzZzxyQtSGrV53HS9F2YH1mAh3kRbSSltM79GphxTeP30V31RkqTCrUEj16QY6XRMfAkBw+O30LZ/UB/K88hiRNJ9QSPfvLo0jTteNwRRh6QU6IopB7g/bjL63AU6pFLTEglZhI0brPw2KJ3ck/bb9PZ7KImor7o/exJTuuRnVmERELjjyHjph+cCpLUoeT+Msc63JRa3mp9Xg/v1xmHrqfsf97jBXpg3g1eSxPHrmP5emDOVrWCZVUz4lT7dBp5ZSWq22KvXb+bgG3/Pq800kN13L87gWEfvZenc5tSNy5JOQsSqWShIQEtm/fbt1nMpnYvn07iYmJNZwJ69evR6vVMmXKlBrbAZw+fZrLly/Trl3DxOi51WAJDw8nODjY5k0pKSlh//791jclMTGRoqIiDh26Gkm/Y8cOTCYT/fv3t7b5/fff0euvFkHbtm0bMTExDRqBDOallrpEYF9Le98Srmg96ex1Hn9FBf6KCsJVF2irKLGmAdtj1cGBTO1tjvcp1HlhEGT8XhJDnjaIfWWRzInbQp4uiEKtp8M+aqJqgK2symUOD08jRm12D9uT73e2ErA9AmVlXDT4UC4oqy2XdPM4xSFNKKVGD3L1rQmUlXFCa45HuVThRXvFFbxlGoZ6pTI8PI0KkxJ/WQWvdNtkzRaqEFQUmTypMKnQCHIqTCqC5cX1MrIs7MsLs/6/U0f7cSfOZBE1JSMjUigw+Df1NGrF8u/1QeownjlyL3BVqVmkedFKXQ5Aa2Ups7tsI9b/Avnl5t/ms3p/FhwfzUvHxuEt0+Ah1TGx7Z9EqwrwlOpQSQ3sL46goNKHg5dCSQjLp19oHtmTbL0rJ++Zx6kLAbT3tl9s00LUt284PqisvfJ3/I/zavQYuRsT9c8Uqks989mzZ7NixQq+/PJLUlNTefTRRykvL2faNPMD9QMPPGB3Senzzz9n7NixtGrVymZ/WVkZzz//PPv27SM3N5ft27czZswYoqKiGDFiRB1mWDsuGyxlZWUcPXqUo0ePAuZA26NHj5Kfn49EIuHpp5/mzTff5McffyQ5OZkHHniA9u3bM3bsWAC6dOnCyJEjmTFjBgcOHOCPP/5g1qxZTJo0ifbtzU+qkydPRqlUMn36dE6cOME333zDBx98wOzZ1WNQ6suzRyfy5JH7GLz9OZ5PmkCEx0XW9P+cWYcnA7DwxKgaz3dUuCva9yK/DX2fuV034yvXEKIupNDgTYVJSbHBo1oqZeIvc4j65k3u7JFsNWhUUgNRHhcIVJRjQmJ1xwbJS/hlyD/rdL1tZWXW+I75Z+8A4NRfN7P6GCU10UFeRKzqnHVtvGpMSIXJ7ML0kVVyTudPgcGPwyWhDPZPY3C7TPJ0QXRQFFqXld7uvsE6z9TK9sgkZlUCAIXEQJHJbMiVC0qCZcV2M6AO5oVWi9ex3CCT8zvaBKtaYm+8HKgTNxXXloSoDUtwtitaJY2Nj7SSjVk9kEpMbMntwpLU4dX0hFoKdSko2JhsuOlTFhwfzTs9vgfMMSubb/kQgDPaAI6VdOCizpvfr3RmkO9JFBIj2bo2nNH608szDw+ZntTzwVwo9ib5XHv254bZHSdn8kucLbMvY9Djp1dJ/GUOBp2c0BX2dbqkitqDP5PvXoCPUstzR2tf8rieuffee1m8eDHz5s2jZ8+eHD16lC1btljjQ/Pz8zl3zvahLD09nf/97392l4NkMhnHjh3j7rvvpnPnzkyfPp2EhAR2797tcGmqvkgEQXC8yGiHnTt3cuut1RUQH3zwQVatWoUgCMyfP5/PPvuMoqIibr75ZpYtW0bnzp2tbQsLC5k1axY//fQTUqmU8ePH8+GHH+LtfbVC8bFjx3j88cc5ePAgQUFBPPHEE8yZ43z6cUlJCX5+fhQXF1dbHrp1x7N08r6Cn6KSUr0aL7kWX7mGSqOCYFUxc+K2MP3gVLp7n6a1vITJ0QeIXPcWWZOcX1995si91qKGCZtftro6V51MpJW8jIsGX0qNHrSWl7DhYm+yrrTiyJ3mNvOTx6CW6rmg86GVohw/eQV7iyKt6+wz/nyAFX2+qnUO0QuXkDHX1sjbmNWDIqMnpSYPlvxyJ607X3I6LbquLEkdjqdUZ1PR2hEbs3rgL6tAiZEdZXF8k92bl+M24y+tqJbaamFLdpzDY1XZlxeGRlDQSlrJRaMXv5R0I620Lb39T3GXTxJGJMgQOGP0q7HkQE0czQ9ptBiVurI6YwAnKjpYbzbNhT25ERzVdGKQZyaby7oRpz5T7d/hg9RhPNXl1yaaoUhVXjo2rtaaUivSB1lLiiw4Pppw1UX+KIlm9+kIBEFCZbmSTsGF5Oa2sbtEDuYik2M7JPFc3NZa5xT26WJyHzV7S0I/f5cOIZc5kxtE3iPP13puTfcMd2Dp/9PDffHwrl+MXWWZgUd7H2ywuTZXXDZYrhdq+vB1+3Eed4SmUm5QcaLIHBMzpn0SF3S+KKRG3ojfaP0yrs3o59RT3vNJE8gobU2wR6lNTZ+aWJY2hG/O9KGDV3G1oL+VJ28iR9uaizoffOQa3uuxnleTx/JG/Ebn3oAaxjyn9ye1NJjvBi7nySP3WdO83cX6zAQb8SxLRpAzRoVlCcCIlGB5EYcrwzhYFMa9bQ46FOR67NAUliWsqbXvn7Lj8ZdWWPU9xv7vMaa2+4OxkUkczQ9BI8jQCAqHWRJQe32V5PyOxHc6zYn8DnTtdKbWOTUlC6rUkGoMFqWMZE6c43INy9KGkK9thREpvTzziFUWuBxTIdJ49N/6Yq0py47qjUWse6vaEpCFgb/MYc/tixj1+5NWr82ilJFoTQqnPq/h/34bqUxw6QETGs9g+fhQf7cYLLMS9rc4g+WGL37Y7esl5P/jNevrxw5NASLQmuTIpUbyzgQxvvthig2e1ifOxSkjWJs0hLe7Q6qm9oDKsf97jI03X6238uzRibzf89tan0A+ThtCa58yvOxUb87RtuZ0ZQCRnhfxk5vF0uprrIA5G2B+8hguVpq9WclX3B8wajEsEja/zPKuawhT6Ck1KWo5y4zFONyWE4tCYiRUeYmNZT3I9ndcn6Sfj9kAqfo0Zw+1RG9TkfflkJ+tWT3OekVqKwYX3+m0U/00JM4WrWtMYwXgit6LV5PHcofPMcoFJV4SHReMPnSSX6FEUJGv7U5XzzN/1Y7SUGDwqfNY1xrNItXZkxtRa1mOmogNsC/pXhVHnkpHxgrAntsX8WLSeK5ooqz7ajJ0ryXn7y853Vbk+uKGN1iO3zebiK/fRiY3cnd0MoU6f4Z0zKRA44tSaiD3geoqjFKJifHxR1iSOpx2Cr2dXm3ZePMym9fef2kVODJWnj06kQ0pPfH0EritbTpHiztWa/NG/Ebu2TMTT5kWGSb6bZnrtqUbhcRIlO8lAO7v6JrwnCuYl8HeYl9eGEVG14KEy00qOsmvMCTqTyZF2R7blhOLRlBYfwzVUvO/0Xl9zZL911aQdSYFeVtOLGqJnmRNiEtp5KcMfhTmRtoYSI1Fa1lp7Y2aAMsDwcG8UFpJKpBKBNpQikJi4qLel9Maf4b4pOL/l5Chbz0EDSdEHaLzdws4ec88t8z9WvblhVnjm65XdpXHsi91OP6yCh7q/AcH80IpMPo6vRzaTlVzMGx9eKfH94z932MN1n9TYkKCifoldtT3/OuVG0aHpSb+3u0AD8XtxSRIOFvuh0JiDsRKK2xrt/3sLtuI9TiHv6zC2tYVrhiq35wtwbkfpA7j/Z7f4utTycyY3UgR2HDTp3b7+W7gcmZ32cZjsTvdGmeypzCCz/uuAqpLnDcEA0Jz8ZI6JzhlYWxkksPlALVET7CsxJqqawnctRgudcFRjZ/h4WmUm1RIJYJDdVt7eEm1ThkrDaFG64wh1pT0Dc1D85dOjqdUzymDP0VGT272z6SVrNxa+VcqqUsuxFVO3jPPqonkbq5HY2VfXhjPHp0ImJecOyoLaa+4gr+swqryW7XWWE1syOpFO2XDGSwAx053qL3RdUhTVmu+3rnhPSxg9la8efwuaxCshZpS2fxlFXV2KVeNCbG4pi2Gz5L/3c5TXeCOTilc0vvwevwPdRqjPljWhRsTd3sa+obmsS8vjG05sXhKzctbg73SajnLMTXN75S+FV1VpykXFOzJjeDXsq6M9z1cY4yKvf6qPpXvyInBR6rBJKhviKd1V6m6FJGW2QeNoOCJ2B1Wo9BdRpclkL2huJ7+7QaE5rL+ykQ2Z3cjWH51eXN5+mDayEvoG5pH31r6WJ0xABkmAmVaPKVaPkobyonyDk7H7blCTaJz1zN10VGx10dLpMVctY+sunvZUQVkqHvF1dj5S+32U2FSErnuLRS+OgACFOWUGRsm9au54q6ifFWL4g0PT7MWvqvpJrcnN8Ia/GthR06MUx6O1vISWssq8ZLoGRiWTaJXBmoXn/6vHWdoeDpGJATKKvCR1N0zdCMwKepPnojdAbguXNbUuGqsrDqZyItJ491aIXrlyZtYnj7YqQKOAfIKdIKMM/qrelYzY3Y5LWlwf/Q+8nRBZOvaMCNmN1cMXg1irABk3vsKcRtfa5C+Ra5PWoTBsuD4aFrLqxdDdBVzwO5VLO7VqqS9Xr2aM8APOfG83/dbMu99BYBig2edlpuuZ3yklfWuTVRXpBITpSZbd/fQ8HT8pZpaK0mPjUyiwiTn8l8aL8PD01wuXqgXZNZKzRYGhOaiwESxyb7hajFy3CGA1xCszhggqui6yNTOe3mnx/c1Boe7ykOd/2BmzC7aOPEbV2z04KLBlxBF3Svqzu262RrP1dCB2zqdjM7fLWDcH4826DiNiUmQuGVribQIgwUgXWNfKjh2nq1HxCIU9+bxu6q1XZawhheTxltfv9/z21qF5cC89HRizOuMjUyy7uusPkeY+pJTc79RGBSWZfWGNCY7c6MpNantGq0FBh8q7GQwXRvT0js0v1rQriv4SDXWuI2qdO10hiy9bTFQy7KI+i/PS4zigt3PY1Nzf/Q+Lhp96/W+iLgPtURfqxfzvR7rmRGz26oSXRV3en3cRebEVzl5zzz6B+RU85Ber5jcIMtvajm3bhtu+KtelzWUdooiu0tCAGkLbD0ic7turrE/P3mljZFSW/tZhyfTI9A21mFRykgKjd6UGdU1nitSPyyy+j8X98RLouOiwZedudF8kDrM2iZF24FyQVntXI3gOA3b0u+1WD4X9tzYMgT2V0RV2w8Qr7L9fJzUt+FofggyBDZnd6NrpzO80m2Tw/k0JRYF3RuR6PU1SL43Q0ZFHHcqnR3MN01LoO20A9O4Z89MfGSOKys3NXPitvDPU81b/Vek4bnhDZZLBh+2F3YhVOmaN8PRDWJu182UOmloLDg+mhjPAqI9zlsLKi5OGYGnVMc5nT8Vpuo3ymux3ASd8eTUhdhXl9be6DpmZ2407/VYT5HJE39ZOUVGTwLlZSxJHc7O3GiiVQV2PQR18RrM7bqZfXlhjI04Vu2Yp8TALxe6AOa03qpU1YA5nNeJHy/1omenU/QNzXP6BiTiXm7f+TSt/crqfP6OnBiXssoaG39ZhVVqQC418t3A5RQZvfgobWgTz8wxJ8+1Ieb7BU09jXpjEqRu2VoiN/xVp5e3pZvPWZsn5gXHR9erz0B5eY3HB/5iLiHgKdVRbPDES6qlj28uAM/FbeWJ2B2812M9RkHKS8fG1diXxYPTUPEuBm+BmNduLKPFspxzSn+1WFeWrg0+Ug1eUi0hisvEq0+hxGhddrFUmp2fPKbGmJHDeZ1Q1lB6bEBoLm9338CMPx+w7rNUc848HMLGrB6UmtQOb2b5hgCmtXVffINI3fhlyD/Zc/uiOp27IyeGIpMnUolgLjdQS4yUPRq66GOB3g+fv3RuLGU+cjVBNcoPOBPU25BkT3qZ9PENo6vTmBiRuGVridzwac03+WUiV6rI0bZmSepwZAgEyQ0sSR1utyqxM/jJKhwei93wOg/GJPNB6jC8ZXqei9vKypM3WbMgqqKQGPGUOadP4ow3pi7o2+rJnHq1RlN93pe64GzpA1ewFEA8qw9A8VfRwhPlHeiguEKY/DL5hgBayWyfnof4pQJY08y35cTa9bIoJCan1GzvDryadSFDoNCkRmKS4CXV0lpWjsJBllEn+ZUGzZRZefIm8rRBTZJO31LI1wdy3uBXr2KiDV300Z4IYm21pZypBSYi0pDc8B6WM7oAHur8B36ySi7ofDEiQS/ICZbXXfTIUYR/xNdvkzZuPpf03mRUtrFGcksdPJG/0m0TFU6mNq9Jq00hwZYXk8ZbPT01orX9CLRXXLFWil11MtGlMeuCfxXjr7ZsE2crDY+OSGZxygh8ZJUEy4tZkT6Im3wzGBd5hN6h+RQZPfGR6igXlJSbVFY126oBi8PD0+xmNDkyNK4lWnGZHTkxnMjvgE6QUmJSE903D4XESLkg56jWfkmEhk7rvWjwoY9X3eXYRWpnaue9LknJi7QsxCWhunPDX/WzXcxPDU91+ZWLOh9md9mGRpBztooOgbPUtr77jx6/A1BiUFNuUHGkzOz2n9p5r8NznH3SNeZ6196oCmP9D/FxzNdszOpRYzuJyda1+MrhMVYPS03zdhdVYzTStO1ZlDLS+npxygjA7IW5e/csp2OHwLz09lDnPxgQmsuMmN3oBZn12Dl9AD07naLU5IGvVEMraQXp2naEyq+QnH+1TIIlo+lE/lXFzdiQs9XGujYI93BeJ9QSAR+pBplEQCkxcaAikkc6/o6/VIOPRE9XZUG1fixjH8wLtRnTncyJ20K5SdUoxqjI9YklGFekYTDijmWhlskNb7BUxSJHPyduS42lyh2l9z0Ru4NFKSOtMvsA9+yZCZgj7cuMal46No7zlb6UG5WEqK/YnL8sbUid55713GxC//UeYZ8sJnTFu7W2HxCaS+/QfJtUansoL8lsXmdOfBXA5hobC5MgpcyoZlnaELZkx9FWUWydxxMdf3WY6eUM0VUMhIC/YpDGRR5haHg6vUPzmRO3hfNGbzSCrNq5tVVdzta14cWk8UQuXgJAgdGXbeVR7KmIJlsfyCmDLyuPDMRToqXCpKBCkNtdVrLs6xua16CVnidF/Wk1Rq8NABZpuezIiWF5+mAyNeaSJaJRK9LcaFEGS02sz0ywGio1iTrpTXKbuBODScqLSePxkOmt1ZTlUiM+cm01USVXiufZQ2KUIKhM9OqSW69+qnLyVftCd3pB1uCBf9fSWl5CkLyM1vJSTEjxkmpJ9MrAR1ZJmrY9/5d/c537VksMVh0HR2vxQ8PTa1TLdaSKW2Ly4LstN5H13GxWpA9ib3kUlww+nNf78ltpF05oO4AgIVvXhkOaMHZXdK7zdbib5l53SKRxWJE+iCxdG4LlRXhKdWzM6lGvZXMRx4hLQnWnZV61HSwS+lU1OuwRKC+zydiJ9L6EXpDhK7+qYbDhpk+t3hx30ibiMnkPv1CtOnRD8Hb3DQ0e+HctgbIy0iuCkUlMnNEHkFLZgZERKfxeGsvR0k48GGL2CmzO7uayiFTf0DxGRqS4PKcdOTHWv4eEZQBXDReLQZdR2RZZlDmIN0x5EW+Zhlu9Uxjmc4IHAvYSrz5F7gMvEq8+RU91Hn09GieGxBKLJCJSGzNidjMjZjdjI5Nor7xCqcmDi0bfpp6W27BkATYHxOKHdeeGzxJyhXN6fy7pvVmUMtJu0Nz0g1P5vO9O4ja+xuwu/JUJ5IWPTINekDE/eQxaBzLr9eWZI/fip7IfqNnQ3LrjWX4b+n6DjzMyIoVT6YMoMnraeLk8pTre67ueDVm92JjVg7GRxxtNrt6egNyQsAx250bSWm4+9n7Pb5FKJrA+M4FWMoGBnhl2a8y4uwDktRzMCxU9JiL1pmoF97pkDT6fNIEgRSlt5cWNEgfnDGWGq1mWN297gU4+V1g7YEWTzEVAgqmeacmCmNYsYlnCmZ88hjeP31VNPM7iNZkQeYSP0oYilUBbRTEVJhV6QdagqaJFek+23VpdL6Xzm0s4+crsBht3S3YcHbwaby372uW4jVk9SC4ZCGCTJlqflNGqfdcU47MzNxpPBw8yg8KyWJY2hEe/eZPMe1/hFp80WstKUWKyK8HviLpU+z2c1wlPqYFcvT8yiYnWsnJy9YGMjbQ1VgJldRc+ExEBXDJWFqWMxE9WiZ/MB4XESCdFYQPOzDXW9P/c+vf/htceAyjSPGnxBsusw5P5uPdam321GR7hqgvIJALHKkLorC7AU6qtMYjXHXzR7wu7++trrDx7dCLv9/zW4fGRESmMjKjXEPVibGQSebqal+nqiq+05iBejUlRo5CWVCJYi1leNniTrmlPqPIS5SYlA52cw4DQXI7mh9io3VqM5eT8jugFabVU53JBgdEkoZXsqoChvWtpLk+3NbEusw+Tov5kc3Y3UdX3OseeV/qD1GFoBDnx6tPk61uJWi7gliWdlrok1DKvugoqqcHlc6Z23kupUU2QopTzej+kEqH2k+pB5zeX1Ot8R2mKYZ8sxlOmq1ffjUFbRZHTGiyukKVrYw203pzdjReTxjPr8GQ2ZvVgW04semQUGPwdnl/1x1ct1TPYK40wxSV8Xcxm2ld51SLcnN3N6tnTC1KKrqkwDWbBwQKjL7n6IMBc/dWnFuOruWJJHR8VcdxhULPI9ctTXX5Fb5JjRMI5nX+d+ph2YJp7J9XEiNWa606LMVieOXIvYE4trhpY6/1Xxo/luD3slTY/rQvkkt6HjsrLFBvNNxVHAbsfpA6rVyXU+npRqq5JVyX38eesmU3NmWMVnbg/el+tAdGusq0wDi+plo/ShjIq4jjv9PieSqMS2V/icF4Snd2qtlVZnTGA1RkDUEv0yBDoG5pnlfuvGrBbE1UNH88qHp18Q4C1r6rIEAiWleAjrUSGgEJi4qLRx6mxmjNDwjJYljaEn7Ljm3oqIrXw2KEpLE8fzJNH7mPhiVGsSB9k1U26lle6beKMPhAfmYYPUoe5LO/gyLvsiMHbn3Opvcj1ww2/JPROykTa+hkI+0tzTC/IearLr9bjloyfpb2+4bFDU1iWsKZaHxtu+rTaPoXEyNvdN7A8fTCX9D68efwuPGX2rV4/WTlKiZEV6YNqTJluTMKWLSb3seb/xV6b0Y92SrNonkaQs+pkIhUmFY/F7mR5+mCOlYXY/Terid25kcgQeKitulrm0Od9V7Hy5E2EKczFMnM1QWzLibV+TiyZQhbsVSseFXGcVScTCVPaquLuyY1gYFjNGUJV+99S1J2e3vnVlpf0goxyQWkz9xvlFl/f1P+qNETZBxEzyxLW8GLSeD7s9TVgjl/xlDr21lY1yhenjOD5pAkU6T2sdYzcSbmuYcqYuAsjUoz19BXU9/zrlRv+qi9ozU/IFiPF8n/L00DVwNpKoznrwxnRNEucy8yYXQTKy3ml2yaHAWpKiZHJ0QeocEMGUcQS92TrXA/GCphrqljqMM2J28LUznutN7WZMbus/2bO8lHaUGvmj1pa3XsBZo/U0PB0wJwBpJAY0Qsyl7RpOiiuYBKk9Pr5ZXbkxLA+MwEjEpeq4S5PWG13zT9XH8SZOig1tzRa6o96Y1G19tCcuC1266XZw4iEUoO6WpmLJ4/c55Z5/XnH283ayyIuCdWdG/4bvaTXChuPioXn4rby2KEpNvu+6PcFC46PZm1a9RoyFiwZRFWxVFR2hOUGaW8erpI9+9l69+EscXObfxVnV93F0coCkjUhaAQFsio1nl5MGl+trcVo8ZVorf+Gzt4ELUs5QztkIJWYaCUro9TkQbHB02779ZkJTl9DmOISPdW1F2C8FncvqTVnNmd3I08b1NTTELHDnLgtdFRdsXpG79r9BODeivRyqYlJex9xW38izYMb3mCpCS959QyQdZkJZEx41eE5r8f/gFqq54PUYSw8McqpcRzFkDQmcS+ZjY/YV5cStci5IN6UhfZVcK93YlXnSNO2s9FFsTwt7syNriZKd8HojVqip8joxSu/jefV5LEczQ9x2L8ldiVXH0SCVy4yTOTqg/i9NIb+Xpl2z9ELMpviizWhlhhQOCioWROrc/tVM9JvVHSCrJosQUNy7UOMSM1kVbQGzFmKbdWlTN43g0Kdl9v6337rEtYlfua2/tyJCalbtpbIDX/Vy086/iEp0nsw488HbPaljH2t1j4tKcynNIH1mltjYqkmYPQQEKQQs6D5e08agpERKXhKtQ5jJZIqQzEhtWZW7ciJwV9WgUJi5Ovz/QiLPE+B1peDlWEOx7AE6n55KpESkweDwrJ4qPMfjPQ7RrmDZcHJ0Qe4bPS2FlLcnRsJ2PeK9A7Nr1OtoYcj/qCL11l25kYz7cC0G7pWTG01tNzNK902NUgm242KxTPqJ6+k0qjAIEiRS428mjy2aSfWCBgFiVu2lsgNb7D4yyocHtOZ5PyeF8Wsw5Nd7je1op3LwZ5V6fKf1+p8bl1Ift/sLcl4aTZZz88mfd6N6T1xhosGx5LjT3X5lVERxwlRXAbMWTsDQnMZEpbBkUNR7LptMSv6fFWjPsvk6AMMCsti122LuWK4+tQ4JCyjxhtp1QBei3s87pqln/oYGWGKi/jLKhgSlkFX77P4yjSsOpnIguOj69xnS2Xi3n9Y/7Z4Wu0FYIvUjBSBIFUZcomJFX2+Iqmoo0txXiItixveYJkUeTUQbH7yGJ48ch+LUkYC0N83Gx9PTTXhOGdYnrC62r6Y15z3WqT+7TWXx2wMJu+b0dRTaHCMTshaDw9PA7BRoe3S86qSrLPZJ47imxw9jR/+y3NjGdcyDzBL7zsKFHaGkREp1pvqc3FbOVAWQaTyQrUinY50e0SuEuN93lqrqbYYNhHHvNJtExc0PlY9rIJyH3ZfubH1eMSg27ojEQShYVXPmoiSkhL8/PwoLi7G1/fqE/X85DHW2j+7LkWzZfAHjTqv2PlLSXu95Xo36svy9MH8ryjKRmq7sXg+aQLv9VjfoGMczutUTdkWzEtEekGOVGKqllrtTuYnjyFKfV70Fog0CfaUxxsLR/cMd/f/yK4JKL1dy268Fl2Zns8Gr2+wuTZXXPKwLFy4kL59++Lj40ObNm0YO3Ys6enpNm00Gg2PP/44rVq1wtvbm/Hjx3P+/HmbNvn5+dx55514enrSpk0bnn/+eQwGW8XZnTt30rt3b1QqFVFRUaxatapuV3gNaqkeP1kFc7turrOxEvmu68qzMa8tJXbeUipDnVeWdVcK843CM0fupZWsjCMFHenz35fq3Z+zrufwD99n+sGpRKovNLi72p6xAmaxuBKTukGNFTAH/4qIiDQcRiRu2VoiLhksu3bt4vHHH2ffvn1s27YNvV7P7bffTnn51ZomzzzzDD/99BPr169n165dnD17lnHjxlmPG41G7rzzTnQ6HXv27OHLL79k1apVzJs3z9omJyeHO++8k1tvvZWjR4/y9NNP8/DDD7N1a/3r9cztupkfLvSsVx+Wj0r020sI+3RxteMxry+1kdOPWrSE9NeeIW3BM+Q9NMfpcUxqx86v0C8WWf8e+7/HgOZVQr0hWNrrGwoMfpwY8zodfYrq3M/GrB7c9ttsp3Uj2sVeoKv3GTooCumguFLncevDwLDsGuOx3MXb3TeI3hURu2zI6tXgWWYNXeZE5PrGJYNly5YtTJ06la5du9KjRw9WrVpFfn4+hw4dAqC4uJjPP/+cJUuWMHToUBISEvjiiy/Ys2cP+/aZfwR/+eUXUlJSWLNmDT179uSOO+7gjTfe4JNPPkGnM3sfli9fTnh4OO+//z5dunRh1qxZ3HPPPSxdWr/MlueTJgCwadBH9erHIugo1UtQFFZ/Cw2ego2cfuYc16X1I99bgqqt4xtU3rSrhs/Gm5cB9uNqbjSyK83pkH3885m095E6lTwoNXnweKffnG6f2CaHMOUlvCQ6/KUV7MsLY1tOrDWTx13UJln+U1Evt44nIuIK4yKPEKJu2ArMFuXcGxmT4I44lqa+iqahXkG3xcXFAAQGmtN7Dx06hF6vZ9iwq6mYsbGxdOrUib17zZVj9+7dS3x8PG3btrW2GTFiBCUlJZw4ccLapmofljaWPuyh1WopKSmx2Swk/mK+ubsr/sBijKTPf4aMl6sbI1nP16/2D0DH3mdtAi5FzCzt9Q0r0geRUxlEmUHFaZ3rqeU+0kqMgpQNWY4NgJUnbyL0i0UM/+0ZOqkK8ZRoKReUKCQGCgx+GAUpufrWbM7uZu2nvsJsaZXtajx+p1/jpuqKiFzL3K6bXcpUu3v3rAaczfWJSZC6ZWuJ1PmqTSYTTz/9NDfddBPdupkFrwoKClAqlfj7+9u0bdu2LQUFBdY2VY0Vy3HLsZralJSUUFlZaXc+CxcuxM/Pz7qFhFwV9gr1uULE12/X9VKbhF23LWZLZpemnkazZIBHDp/3XUW09wVkEhNLUodbZb1fOmZefnz26ESH5393qY9VudYRD3X+g7xpc+joVWRVKB4dkUyBwZ8KkwoTUoqMnnhKtZSbVEw7MA1VPTJ4AIb7HXco/X/bb7MpManZlhPrtqW/m7e9wLQD0+yq/IqIOOK8wc+p8iUfpQ1lSFB6Na0rEZG6UmeD5fHHH+f48eOsW7fOnfOpM3PnzqW4uNi6nTp1ynospyQQP9/yGs5unuivqImqQ4BvU7MtJ7ZB+4/vZNYmCVBUcOBKGHpBxokis3fCR6ZhXWYfyo0qFqWM5NmjE3np2DiWpA5nfWYCy9KGMDQgDYXEQHt57fEo10r/T4g6xOToA4yKOM4TsTvI0AbTSlbG5NZ7aSUrY0NWL7r+MN9pFWQLS1KHs624G3tKo6od6/zdAi6XezI2Mon95VFojdVrllY1Oh488JBTY/5v+Lt80e8Lm5owIldxV22bG405cVustdRqQoaJEEUhUZ7mYHVnjJyWgAmJW7a68MknnxAWFoZaraZ///4cOOBYnmHVqlVIJBKbTa1W27QRBIF58+bRrl07PDw8GDZsGBkZDZcYUCeDZdasWWzatInffvuNjh07WvcHBwej0+koKiqyaX/+/HmCg4Otba7NGrK8rq2Nr68vHh4eduekUqnw9fW12Sy09Syj7Firulxqk9Il9jReXZomyLM+VF3KmnZgWoONM6/bT6hleubEbaGLn9k7N7frZs7qA/h7qz0M9MxAITHSSXWZYoMnh8rDeCx2J4fLQpkU9SfZujZszOph02e/LXPtjuVIKK6D4gqjIo4zPDyNVrIyxkUe4cSY12v1tuzMjbZ6U15MGk9yaUc+7PU1N/ueBCB0+XuAWShucFgmR+96EzDrVsT7VK8jpJCaheb6b32RpAvtaxxbxDmu53iKV5PHNppq7LQD06zxgVV5LHYnE6IOMSduCxUmpVNGTkugqZRuv/nmG2bPns38+fM5fPgwPXr0YMSIEVy4cMHhOb6+vpw7d8665eXl2Rx/9913+fDDD1m+fDn79+/Hy8uLESNGoNFoXJ6fM7hksAiCwKxZs/jPf/7Djh07CA8PtzmekJCAQqFg+/bt1n3p6enk5+eTmGhe90xMTCQ5OdnmTdq2bRu+vr7ExcVZ21Ttw9LG0oer/DjoY3QBxjqlIzclJw93Imn0G009jXrxRb8vWJ4+uMH6t2QVVNVuSC03e1v0gpzunqeYGbOL1+N/INbjLABak9lDsbkwnmWnbuXBAw/R7cd5hP7rPQ6MXGh3nKp1h6oyKuK49W9LsUSA2V22OTR+ALYUd2fT5R4sShnJOz2+t3pyJkX9aW6gMF+Xr0zDij5f2Zxrryq4FIFnj05kQsgRq3HT0mhJxR1r4434jbwRv9Fm32OHpvDMkXvrFKheE1/0+6LW+MA5cVvcOqaI6yxZsoQZM2Ywbdo04uLiWL58OZ6enqxcudLhORKJhODgYOtWNVRDEAT++c9/8sorrzBmzBi6d+/OV199xdmzZ9m4cWODXINLBsvjjz/OmjVrWLt2LT4+PhQUFFBQUGCNK/Hz82P69OnMnj2b3377jUOHDjFt2jQSExMZMMCs7Hn77bcTFxfH/fffT1JSElu3buWVV17h8ccfR6Uy11mZOXMm2dnZvPDCC6SlpbFs2TK+/fZbnnmm7oJreTOfJ+uF+gfDNiY3iiRGB0XDZRbojNXfpFB1Ibn61hyuDLNRpJ3a2Ry0neibxUvHxtHZ6wKh3oVkFLWmk38R7pY2sGf8WIrkvdPje9YOWEF7RZHdc0NDLwLwUZ5zui9XDJ4M8km31rlqSpqqpk6M6myTjHu9sCxhDUt7fcOMmN1NPZUWjTuDbq9NNNFq7XuCdTodhw4dsklmkUqlDBs2rMZklrKyMkJDQwkJCWHMmDHWxBgwy48UFBTY9Onn50f//v1r7LM+uGSwfPrppxQXFzNkyBDatWtn3b755htrm6VLl3LXXXcxfvx4brnlFoKDg9mwYYP1uEwmY9OmTchkMhITE5kyZQoPPPAACxYssLYJDw/n559/Ztu2bfTo0YP333+f//u//2PEiBFuuOTrh5wnn23qKbiF0RHJDda3SZCyOGWENch2WdoQjpZ0RC3RO7x5P9T5D97uvoF53X7ifKUvRkFCW3Up0wf+3mDzfDFpPM8enVitgrAjzZOxHY4C8NvQ2sUD12X2QYaJCgeFFRubptJxuWj0rTHzS0SkOWDCDdL8fz1dhYSE2CSbLFxo30N86dIljEaj3WQWS7LLtcTExLBy5Up++OEH1qxZg8lkYuDAgZw+bV6StpznSp/1pXr0Xg04o+KvVqv55JNP+OSTTxy2CQ0NZfPmmutvDBkyhCNHjrgyPZEbjFeTx1Zza1+LQZCSrw20xhuopXqUUiMyicmpMX4c9DEbs3owNjKJdZl96jtlh7ga2NpTnW+dlzO0UZZSblKx6mSi1ZPUEliSOpzZXbax8uRNPNRZFLwTaVmcOnXKJl7TskrhDhITE23CMAYOHEiXLl3417/+xRtvNE2oQstM5hZp1ljUNDspL/PkkftqrKbdVl1qNVYWpYzkoc5/0N8vh3IXvA0Wo8ASP9IctCPy9YEcrwypvSHmef94Jp7TusAWZazA1Xiehzr/0cQzERFxDsENGULCXx6WaxNNHBksQUFByGQyu8kslmSX2lAoFPTq1YvMzEzgapJMffp0FdFgEWl2LEtYw+R9MzitC0RnktdYDO2y1guAn7LjCVVeAqC94kq9liV+HPRxnc91FzKJQE5lEFuy45xuf20WRlPoqzSkl6oufJA6jIUnRrmcZi4i0lA0RbVmpVJJQkKCTTKLyWRi+/btTiezGI1GkpOTadfOnNQQHh5OcHCwTZ8lJSXs37+/zgkytSEaLCLNkrUDVpBeZrs2uuD4aBaljASwel1aq8sAc5yMJfV4QtShRpxp/en6w/xq+zQmBd29T5Orb+1UH/8b/m61fe7WV7G89zUxKerPaqniTclTXX6lo7KQKNX52huLiDQCTaV0O3v2bFasWMGXX35Jamoqjz76KOXl5UybZpaeeOCBB5g792pm44IFC/jll1/Izs7m8OHDTJkyhby8PB5++GHAnEH09NNP8+abb/Ljjz+SnJzMAw88QPv27Rk7dqxb3qtrcSmGRUSkMVmX+JnN61KjGikCbx6/iw4qEyvSB/F536sZD5+fHcToiMaeZf2JDLxs/XvU70/yaMffqDC1JVBexv3R+1ib0c8m26mpcPZH0tm4m8ZCLOYoIgL33nsvFy9eZN68eRQUFNCzZ0+2bNliDZrNz89HKr36Hb9y5QozZsygoKCAgIAAEhIS2LNnj1V+BOCFF16gvLycRx55hKKiIm6++Wa2bNlSTWDOXUgEZyJpr0NKSkrw8/OjuLjYJihJxDG9fn6ZI3e+1dTTsMvajH6UmDyYGbOrxjaBsjJGRqQ43e+6zD5XtU/cQOyG10kbV91jUpW1Gf0wIuVgmVnHKEBeYV3OGbz9OV6J2IRekJOhDeapLr+yIyeGw5VhGJE0mJ7F4pQRTqdEX3uNk/fN4G9Bh6t5tpqLodVU3L17VrNYXhRxjoa+Z1j6H/PLQyi8lPXqS1+u44fbV7a4+5voYRGx0tTGyuqMAdwfvY83j99lTf9dnj4YrUlBW4WpRmPFwllDgEtjutNYAWo1VtZnJjA52nxjt1cRaNdti4HFNvuydG0IVV7iUHmYeyZpB1fqIMW2Oc/0g1ORSkys6PMVwwJTaCUrq9bOlcDnGxHRWBGxR32k9av20RIRY1hEmg0KiYEFx0cTpCi17is2evBUl1+dNiwUEmNDTc8t1CW+ZkbMbg6UR5BdEWT3+M7caOvfy9KGON3vM0fuZX7yGDZnd3Ppfft78H5MgoQQtblshKdUS5HJkw1ZvWzqSAU7EMVrrtiLJRIREWk+iAaLSLNhUtSfdFafI1J5NUDSlSUQjaCgyOjZEFNrFhzOt5/mPCTsarGxx2J3AuasqdoIVhXzevwPJGs6klHZlo/ShrLqZO3R/f6ycjp7mf+Nbt/5NGvPDSBD2xaFxIBGULDqZCI/ZcejluhthNwWpzRv4ccTY15v6imIuIH4H+c19RRqpCmyhG4URINFpMHZlhPrdLrrpKg/bYonQu0332ePTuSjtKE81PkPnojdUed5gnnJpiZu3/l0vfq/7TdzeYhRvz/pUmHI93qsJ/PeVxwetyj9WmgtK+WZI/eyObsbu3Mj7Z5jMQbnxG3hv7lx6AUZSomRUb8/6XCcl46N46LBl7TyYLafj6FMp6LSoCBOfYZSowd/lkfgL6tAY1KiF+ToqtSXKDWq2Zzdrdb3WESkPpgECVHfvkHoqkVNPRW7iAZL3RENFpEGRy/ICZYXA1frzCw4Ptrp82uT9n+/57f1NlQsWJZsduTE2D3exqPU7n5nGdbGbIy18yixFjx0B+/3/Jb5yWMAmLj3H8gQOHS5EwqJASNSduZGsyU7zmr8PXnkPpvzU8a+xuwu25gcfYDNt3zocJy3u29gcvQBvuy3kufCt1KhU7Dt1qWc0rVCKjFxXueLXjCHxumuKYb1evwPFBj8rru085p45si9TT0FkWtQyg2YTFKkCiM9Nzk28kWuP0SDRaTBKTJ6ohdkbMmO44+SaAZvf46vTvR32P6jNHPBP2dF0xqCqpWXq7Km/+dWw6AuzO1qLknxed9Vde7DEZZMo1Ol/nx5+SbGdzjCGX0ARUZPzuoDSNJ0wl9aAWBVB64PoyOSrZWhpRKBiwZfunudYkLUIasmzrXBuDeaIq23XOtWUTpXYpBE7BPoWYlUakIiBaEZeiJED0vdEQ0WkQZlwfHRBMrKOKMPYGRECr+fiqSowgOZ3MStO+wXd+ygMAdzupKe3Ji8Hv9Ds43HWJfZh9kRv/Jx77U81eVXpnbey46SONacG0ByaQcGhWU1yLiWDK6wv9SGR0UcZ2xkUrXlvWvZnN2tQebTWPx+IYpw1QUbI7Y+S16WGCSASXsfqc/UWixSBNoHlpB930skjW6amjc1IRosdUdMaxZxKztyYqzeiSn7p7Om/082x5+L24ZaokchMTIh6hDrMxPwkVbaGCfjIt1T9NKSJu0MH6UNxSRIydW0Ymmvb2pt76xmSVMQqbho89od3hRncHVZbuGJUczteryBZtM4xAecxV9aQaC83LrPXUte1wonNncWpYxsMJ2gqvT570v8ecfbDo/7qSr5buDyBp+HSOMjelhEqnHPnpkuxZhUZWh4uvVpc03/z6sdby+/wuToA9Yf9QlRh1A2UCryeb0fy9MHO9X2idgdKCQGenjl13vcmO8X1LuPqriyBDUp6k96h9b/GhoDP1lFU0+h3nzcey2FRm+e6vJrU0+lyTlYFEb/rS8y/eDUBh2no09Rjcd1xub9HC6AG4oftkxEg0UEuFohefhvzzCu9WGC5HUPLr22CJ8jLK7zoeHp7MyNZtXJRLdmkDwXt9W6VLE2o1+tNW4ei91JhUlV7zkYje511zr7fl5vPBa7s17xQM2FlqzmW5XvBi5n/4h3OHCuEzHfL2iwqucbb15W4/GMS/b1ipoL4pJQ3RENlmZOY1WZTS3+q55EYQCTow9wrNy+5kd9sSz9bMmOs3GdDwnLwFemQSYxWeMaqoqQ1ZfJ0Qec8uRIJQKt5SXsyInhYF5oncbKnPhqnc5riViMsd25kQ4zs0SuL5LvXkD6+HlNpvSb+rfXmmRcZxENlrojGizNFMuTZ6HBy+1LDPYoLDcLrqWPN4suLU9YXad+nF2CsRdQ6yOtRIrJKuk+PDzNmjVR1yWqqoyKqD1eQoaJiwZfygUlydqOAA51TBobS0r4jcigsCyHmVnNhcRf5jT1FEREWjSiwdJMiVKblUQvab15ptv2Bh+v6Jx7Cmg5U+/HEcPD0xgbmYRaqrPus2RNVBjrVyzMWSr+MpZkCBQavNmXF4ZCYmzSFGsL+mt0TUQaFx+ltt59WFL2Wxp37X6iqafQbBA9LHVHNFiaKZbslt6+efUyApwl75HnCf3svQYfxxnsCcVd1ns1ythPdfmVUpOaM/oAYtRnqTCpKDJ6NosU6x8v1ByDc71jEbVz51KgO/llyD/r3UdreUn9J3Id4q9s/gHWm7IHNso4osFSd0SDpZnjLgXXmrConuY98nyDj1VXEnzyGk1U66HOf5CjbY1RkNJaVo5/M8lmOVUSwMS9/2jqaTQYoyOSWXhiFBpB0dRTcSsWQ2zlyZvwkmqdXja9kbCXMdjcOG0IbOopiNSCRBCEGzJDqqSkBD8/P4qLi/H1dc9yR0tkY1YPxkYmNfU0Gh2zRohZlfZofgg9O51yuY/bdz7tlqdykRuDVScT8ZLqkElMHK/sSD/PLAoMfgTLiykw+NFKXlZrGQqRhqOh7xmW/m/6YRZyL1W9+jKUa/ljzMct7v4melhEaqS5GytLUocD7gnKrUrVtO66GCsAF8sbZxmrviw8MYqbt70gBpXWwNqMfjaVp+vC1M57KTD4UWT0xE9WySl9K4LlxaileqZ23ttkxkqPn8Sstsakvhoslq0l0rwVdkREHPB80gQUEiMKiTm7SWNSsDhlBIUGL97uvqFOfVZV6Z0Rs7vecywt86h3H43B3K6bmdvV/Hfov94DASTeBoQKebNeJnSGRSkjiVGdo8DgTytZWZ1VaCdHH3BL4HXVJd5tObG1li5oDJqbfL1l2dNPUYlKasAkSFmWsKaJZyXSHBA9LNcp7hRYaypWnUysVczNEQqJkY7KQhQSI4tSRtJRWUix0QPPKhlGrjI0PJ0V6YPqfP61ZN57/VWKzfvH86A2kTtlLkgEnk+awMhdT7n1fWlM5sRtocKkYmbMrnpL5rs78PpaY6W278KNnNZelW8T/8W3if9iRZ+v+Lj32hvOWBGDbuuO6GG5TsnTNW81x9p45si9hKm9rGnErrDwxCgC5WYRuNPaADqqrqCW6/GTVaKS6us1L3d4Vq538qaal4byZrzQxDNxD9eLEm1ty6852taNNBORhkQQJPWuIt0cq1A3BqKH5TqlORffc4alvb7hksHbpjptbaw8eRPL0oYwt+tmPKVaHovdyfKE1fjJK9AJci7pvTmjDWi4SYvUG0vGjIgtK0/eVOPxxSkjyKkIuiFKGQANJtsvcmMjGiwiTcYb8RsB58W0pJg4rTOnHlb1zCgkRpQSAxUmJX7ySpanD260FGgR1xCzYOzzUOc/ajy+rygcExK2nTNr1NgLAH7yyH3MOjy5QeYHuDWlvqlk+5sD4pJQ3bnhDZZe75q/GNELlzTxTETssSJ9EF5SrVMxOecNfgTKywEIlJexJHU4Tx65D39ZOTna1sR7nqajspAOikLaK65w645nG3r6Im7mnj0zm3oKzZLvBi7ny34rKdGYDfUfLlc3WD7s9TUf917bIONHffsGB7PrVltLxBbLklB9t5bIDW+wmNQQ/dYSMDX1TETgqkidhRkxu1FL9MgkJhaljLTutxfkqZYYCJSXsTGrBz5SDScrgon2OE+FSYXeJOO0LpCzen/0gpxT+laU6xpHzl/EfXw3cLn17/WZCSxOGWF9PXj7c00xpWaFBLO+z5f9VjbquJkTXyXn7y816pg3KoIbvCuiweIEn376Kd27d8fX1xdfX18SExP573//az2u0Wh4/PHHadWqFd7e3owfP57z58/b9JGfn8+dd96Jp6cnbdq04fnnn8dgMNi02blzJ71790alUhEVFcWqVavqfIFJT84i4+XZZLw8u8591AdL4cLQL99pkvGbG2HqS1ZjZMr+6YA5KNIoSPGRatiSHcdP2fEoJIZq54YqLxKmuMTYyCQmRB1iecJq9IKM5PKOaE1y2iqKCZSVo5AYeCJ2BwdGLmzUa2spLE8fzKvJYxt8nFayMrxlGjZk9WJ1xgD+0el3VqQP4rbfZhO38TUAEja/3KKUYw1GqShGKNJicclg6dixI++88w6HDh3izz//ZOjQoYwZM4YTJ04A8Mwzz/DTTz+xfv16du3axdmzZxk3bpz1fKPRyJ133olOp2PPnj18+eWXrFq1innz5lnb5OTkcOedd3Lrrbdy9OhRnn76aR5++GG2bq1/kGnMa0vr3YertA8oBiDvwRcbfezmyOwu26xS91Xlui8bvfGXVZCta0O5SUWh0dt6zOJ5GRuZVK2i7+wu21ja6xuW9vqGfG0r1FI92dq2jXAlLZeZMbus8UcNya6yWGbG7GJc5BHuj97H5OgDzIjZTTvPYlLGvsYtvz5PpU7BFYMXH6QOa/D51EZjSA2k/u21Bh+jJRCx7q0mG1sABKGeW5PNvmlxyWAZPXo0o0aNIjo6ms6dO/PWW2/h7e3Nvn37KC4u5vPPP2fJkiUMHTqUhIQEvvjiC/bs2cO+feZCfr/88gspKSmsWbOGnj17cscdd/DGG2/wySefoNOZ9TOWL19OeHg477//Pl26dGHWrFncc889LF1aN2Oj6xcfAOYnMX1s49eEOXXJv9HHdAdVl2fczeUqxoiFM7oANIKCjMq25OmCUEiM1mNz4rY41e87Pb4nU9OWdaeuf40aEXg9/ge7+y2G7p3tk7k/+gDf5PTm5/Pd3DJmXXWBgHrrvIg0HipV/eQP6oOodFt36hzDYjQaWbduHeXl5SQmJnLo0CH0ej3Dhl190omNjaVTp07s3bsXgL179xIfH0/btlefgEeMGEFJSYnVS7N3716bPixtLH04QqvVUlJSYrMByCqkhH28mEtn/Mie9DLg3mj3mrjtt9lkTrx+ZK9XZwywpp1ajIQNWb146di4mk5zGXvVp8sMKh7q/AdLe33DnLgtPBG7g7UZ/Vzu+/X4H9h7+yJ3TFOkGfPkkfsY4X2CKNV5urU+R+6l+hWuezFpPFuy45pFKYrm4C2ycNfuJ5p6Cg1C17YFTT0FkTrgssGSnJyMt7c3KpWKmTNn8p///Ie4uDgKCgpQKpX4+/vbtG/bti0FBeYPR0FBgY2xYjluOVZTm5KSEiorKx3Oa+HChfj5+Vm3kJAQAIYOPEburOdsRLB6+datNoyrbL/1+spMkmGqlnY6LvIIfbxyqrV1NhXZWZb2+qbavsYU/HKH7LpI4/Fhr6+pMClQS3Xc2/oA2tL6FZPr6nnGTTOrP091+bWpp2DD80kTGiVmqTHp65/LopSRLE4Z0aDeZHuIWUJ1x2Wl25iYGI4ePUpxcTHfffcdDz74ILt2VX9ibmzmzp3L7NlXA2tLSkoICQlhV15k9bZ/VeEVscWRgTAu8ki1fZY4FDCLgV3v+hq+Uk1TT0HERXaUxaGQGsirDAK9687izdndKDGp8ZVqUEtUaARFA8zy+mZoUBqzu2xr6mm4HT9ZJTJMnNf78Uq3TY06tkmQIKmnwdFSdVhcNliUSiVRUVEAJCQkcPDgQT744APuvfdedDodRUVFNl6W8+fPExwcDEBwcDAHDtjeFC1ZRFXbXJtZdP78eXx9ffHwcFxMTqVSoVJVf8oy5VaPlxCpP61kZYDZM1Fq9GZzdjdGRRxv4lnVHalEzHu/3ghVXeL34s6s6PMVH3gOY3n6JrI0bfjuRC9yJteegltk9EQt1VNuUnFKH0h7xRXWZvRjcvQB1mX2YVLUn41wFc2bS3qfpp5Cg2BvWVqk+VNvHRaTyYRWqyUhIQGFQsH27dutx9LT08nPzycxMRGAxMREkpOTuXDhgrXNtm3b8PX1JS4uztqmah+WNpY+XCXpaVEC2hkcFbezp6i5Mzfa+jQ6MiKFydEHGBVxnC3ZcWzJjmNztnsCIBuTAaG5TT2FejF4+3NNmvnQFOgFGb8cMX/Wdl+JYmbMLt7rsR6TVkbiL3NqPf+sPgCjIKXcpCREUcjR8lCrl7HQ0PIedHr8ZI63e/LIfbyYNJ7bfptd58rnIo6pd4bQX1tLxCUPy9y5c7njjjvo1KkTpaWlrF27lp07d7J161b8/PyYPn06s2fPJjAwEF9fX5544gkSExMZMMBcZfT2228nLi6O+++/n3fffZeCggJeeeUVHn/8cat3ZObMmXz88ce88MILPPTQQ+zYsYNvv/2Wn3/+2f1XL2Kl1KS2u39c5BEWp4ygraIYH2klSokRI2rUkupR9kqJEanEhElwvx7hqpOJTO1cc+C1O9mXF3bdGDGLUkZy7spAjBXNr5bpusw+KCVGLhu83V5Y8qHOf/BRxsuM++NR2qjLrx4wSjib18rqLXFEW0UxxypDuKjz4RbfdN7p8b31mKXG1dqMflw0+Da7uJKGINCrgtDP3iPvka+beio3NGLxw7rj0p3lwoULPPDAA8TExHDbbbdx8OBBtm7dyvDhwwFYunQpd911F+PHj+eWW24hODiYDRuuWugymYxNmzYhk8lITExkypQpPPDAAyxYsMDaJjw8nJ9//plt27bRo0cP3n//ff7v//6PESNGVJuPiPuQ/ZXZby8zJ059Bh9pJSakaAQFMgSkmKoVsjMfM6ETZG4PYm1MYwWuL4/LH5ejOHnPPPIeqt2r0NgEy4t5KWks7x67vUH6fyp6B4dSw1mesJrpB6cCkPfwC0grZawrqDnL7P7ofXT3OEVP73xKTPaXmydHH2gRxgrAb0PfJ++R55t6GiIiDpEIwo3pXCopKcHPz4/i4mJ8fX2bejrNlhXpg2yefKu+Xp+ZQGt5CaUmNXpBjsakQC3Vo5AY8JKYdXN0goyRESmsz0zAR2rO4ioyeYrr/yIAxG18Da1GgVEvJff+uUza+wjdfM5yQe/DiaJ2bL91CcvTB9crpiDsq3fIfeDFOvWzLG0IGkGBSZBe9xXQRepHQ98zLP13+XoOMs/6ZbUZK7Sk3reoxd3fbvhaQiJXCftkcbV917rp9YKM1RkD2JETg7+sHI1JgZdER7lJhUJixChIkSFgvEa4yF9WzsiIFEZGpDRbY2V1hnlp8s3jdzXxTBxjiSO4Hjmc16navpSxr2EoUSIYpESue4sDeaF8mdqf3WcjMAkSEja/zL8yb67fwOXmpbDFR4e7fOpjsTspM6pFY0Wk0WjKas2ffPIJYWFhqNVq+vfvXy0JpiorVqxg0KBBBAQEEBAQwLBhw6q1nzp1KhKJxGYbObLh0sRFg6UFkft4zcXjVp68iWBFMR3kVygyeVr3SyUmWstKMCLBS6pFLdGjkBjxkWrwkmoBmn1K6OqMAXhJtazOGEBbRXG1IozNhaTRbzT1FOpMkYNllbxHnidv2hyyJr1M9qSX0ZUrKSn15M7g45RWmJ80w1bXve6TIDcRtmYh+nIF3X6cV/sJ1zCv2091HltExFWaKuj2m2++Yfbs2cyfP5/Dhw/To0cPRowYYZMEU5WdO3dy33338dtvv7F3715CQkK4/fbbOXPGVrNo5MiRnDt3zrp9/XXDxUCJS0IigDkbyEdaSanJg9ayEi4afQmUlVkDaNUSPSV/BeYq/5LNV0gMFJk8rxsNltUZA9ALMh7q/EdTT6XZEvP9AtLHu37Trwvzk8ew+nh/pFITJpOU7PvEasAiTUdjLQl1/veLblkSOvn3d1yaa//+/enbty8ff/wxYM7wDQkJ4YknnuDFF2uvdWc0GgkICODjjz/mgQceAMwelqKiIjZu3Fjna3EF0cPSAoleX/0pXiExoBEUVpE4hcRAqUmNVGJCKjGhEczxK7K/XoM5UFcvNL/MFEfcH72PclP9figaGksV4qZCU6Ii7NPqS4e1MfPQ/S6f83r8D7QOLMHHu7JFGisLT4xiSarry1gi1zdmD0l9lW7NfV1bjkar1dodU6fTcejQIZuyN1KplGHDhtVa9sZCRUUFer2ewEDbMhg7d+6kTZs2xMTE8Oijj3L58uW6vTFOIBosLZCMCdXjJEZHJFs9JYPCsqyvh4RloDEpUEgM6AWZtSihEQkDw7LdbgDUp/icIz5IHWatz/JE7A639+9OIlpdbrLlqlt+fR6pykjuozUvHVZl1O9Psi0nlrbKkjqNuX/EOxy58/rXj1l4YpRL7afsnw5wQ6rIitSMO6X5Q0JCbErSLFxof2n10qVLGI1Gu2VvLGVxamPOnDm0b9/exugZOXIkX331Fdu3b2fRokXs2rWLO+64A6PRWENPdef6eTwWaTKUEiPlJhVKiREZJspNKkZGpABmr0VVFqWMZE7cFrblxDI8PM2lcdZl9qGNTMPGrB6c0rdym3HxVJdfr5taKJsGfdRkYytkRqcUYquy+ZYPAfhod8MJNC48MarZl9PoqCxkWdoQq35LbVgqTouI1IdTp07ZLAnZU3t3B++88w7r1q1j586dqNVXNbsmTZpk/Ts+Pp7u3bsTGRnJzp07ue2229w+D9HD0gLpuekVl9qXmNTokWFEQrlJRaHRsQqopcpzhjaY3bmRbMuJtdvuWr2XtRn9CJYXI5WYqPgrIwng5m3mopU1VbB1RvPljfiNtbZp6fgpHRcXrY0fB5nXxQdvd9474yzN3Vix8FjsTlaevKlFL/PMTx7D3Q1ovN4ICG7aAHx9fW02RwZLUFAQMpnMbtkbS1kcRyxevJh33nmHX375he7du9fYNiIigqCgIDIzM2tsV1dEg6UFcvSuN11qPzYyidERyQwPT6PU5OFUFeV8bSvOGAIcelkmRx/gp+x4Xk0ey+KUEUyOPsBFgy8XDb5Mjj5g1dO4vV0qP2XH1yjeZfH2iNSP9h7F9e5j122LSdj8shtmc31RdWm02OBZQ8sbm9fjf+BipRcPHnioqafSbGmKas1KpZKEhASbsjcmk4nt27fXWPbm3Xff5Y033mDLli306dOn1nFOnz7N5cuXadeunUvzcxbRYBFxiQlRh5xq906P7zmrD6ixzeiIZN6I32jVwJgQdaha/308c2qMk/kobahT8xGpnY97r7WqxdaHdj4lPHZoCr1+bjmGS762FQCeUi1BilKWpQ1p2gk1IXtvX0Sk58WmnobINcyePZsVK1bw5ZdfkpqayqOPPkp5eTnTpk0D4IEHHmDu3LnW9osWLeLVV19l5cqVhIWFUVBQQEFBAWVl5sK3ZWVlPP/88+zbt4/c3Fy2b9/OmDFjiIqKajBletFgEWkwguXFdg2KxSnOf5hHRRyvUYiuuQfRXm983neVzevwf7/tsuFhEiQsS1hzQwTTOkuQopT5yWPQC3Lyta2cjmW5lmePTnTvxJoIUdumBty5JuQC9957L4sXL2bevHn07NmTo0ePsmXLFmsgbn5+PufOnbO2//TTT9HpdNxzzz20a9fOui1ebM4ilMlkHDt2jLvvvpvOnTszffp0EhIS2L17d4PF0ohBty2EnptecXkpyB2c0Vb3sjwXt9WlAMXrnbBPF7uUedOc8POrwGCUEfXtG2ROrJ5d9kHqsGrLda3VZY01vQZj4YlRSCUmdl+OdioQOlhejEmQVgtCd5X3e35br/NFrgPcUPyQOp4/a9YsZs2yH2O0c+dOm9e5ubk19uXh4cHWrY2rEC16WFoIeqOM6IVLCPvo/UYbs8Dgh5+80m4g4iWDT6PNo76ErlxUr/Obs7FSW5DsrR0y0GgVmExSQr98p9rxDWd7Vtv3Zb+V7ppeo/PYoSm8mDSeAHk5beXFhHlddioeI1XTXpT3F3GKplK6vREQDZYWwokxr5Mxdza5TzzbaGPKEIhSncdTqiVMeclGY8Wey/j2nU832txcQXHBPWUHpuyf3qxKAryYNJ52njXrpyzt9Q0ZE14le9LLSOUmOn+3wOZ4bedfbyxLWINKaqDMqEYjKJFKBPwUlS4tY4qIiDQMosEiUm/sPYGuy+xDW0URrWRlyK5ZcB37v8esf6/PTGDVyUQWpYykR8AZfsqOb/D5ukrmi7NrbeNMkOWa/p/zYS/7dTbi61ADp75kVwTh70Iqc87fX+LkPbbzXJf4mbun5RKT981we5+vx/+At0yD1qQgUn0RkyCh1Kiu8Zzmnja/IatXU09B5C+aIkvoRkE0WETqjb0lgElRf2ISpFww+jAh6hBGQcqvxV0BaKWqYEt2HCtP3oRGUHDJ4EtbeTGR6gvXTV2ia6lP8ceem15BKW8YZcia+DbxXxy+2LHRx3Unf6RHOtUubM1CEn+Z43Sl7pkxu3iqy6+UGtXc7HsStVRfn2k2OjP+fMDqFfogdZi15EZLZNTvTzb1FGwRJO7ZWiCiwSICQNc5S+t1/rNHJ7Ixqwebs7tZ902OPmDN8PkodyiVRiUbs3rQxescf1ZE8FDnP1BIDADoBblVe8UelmyjDVm9WJdZux5AY+OMxHr42qsZN1U9KkfvepPLl72J+X6Bo1MbjAMj614luTmQ96Djom1hqxcS+tl7hH30PpJCJecLfTHh2g/9K902cf7/2zvv8CiqtYH/ZralFwIkIJBGCU1AEAyiXgUBwXbBgiIqInwoqPSiNEE6CYoNUSkqiOWqF8tFEbs0jYD0lgICCSWkZ+vM98eSTZYkJJtssinn9zzzsDtzzpl3huzOu2+1BFVSyurn7W7vOWJqrlbDqLbQ8uOKdzEvqMYsqP0IhUUAgKX04rXlIq7zxxhVHQOi9pd4/Jc+S3n3+rXcG72XZvqLNNDaM0mGtPyTSe2+ZWSbXx1jr4wX+CaxA4209liJQdG7r5rmXBOIeM8enBrz2YtORdRURcJi0wCw725n5SR52PRq65JcwJDto6r1fNVN8rDppIyaDLKK1MhE6ybnmNXhS57/e5BL68iSQktDWtkDBW4j4gNnRbqkDLXaigi6rTgirbkeE70snhOT7PEZR2eOr/R65VUk9JKtxJTm5/8eRKThPJPa/eq0vzQlqKaS/Kj9V//hQbPp/WNh/Etoo0z89GZPiVUMT8efVBsyTt2gc2wG7vz1mXL3bSqo9TNz371EG9J4vHX5utsKXCdy/QIUiwakOuzyqGAdlWJr1EOEhaU+o0D42sql7FaE0vzpffwPOFlaajNRHy4AIPFsQ8e+nf0W0TawfJ1RBe7jyrTyFV0+rFCTyXkdv+CC1d5obuxfDzN57/1ukU9QiGLRoDHYCAjO87QoghqIUFjqITEz7fEqJ6ZMIOXxqTXmi/e2yCOeFsElCuJQbv+x0DoV/vYSAGwmDR02zaJtM2cF5bXrNjiNF9QudJKNpxMeoY1PKqG6upXSXROQdTaCA3MxmtxTSqAmIrKEKo5QWOohh+c5PzCXdvrEpflvH7nJneLUWgriULbcWhiwnDLS3l065fGp7L97Ln46k8PaUkCIV271CSlwK8+1/Z7dF6/BX86noVYoLO5GscrkGvXYbHX80VTNZfnrCnX8r0JQFYxs8yvLDvZzZOvEfje12JiVR26pbrFqJB/HvuUUPwH1KHakjnL+kj9Bmjx8Zed4pKqoCVOf6LVlCimPTSPQN59mDTM8LY6gBiIUFkGFyLZ58VqSPdV4e9/FbDjW3en4tYZTnhBLIKhyjj84g3uj9xbbv+GGt0scP23v4KoWyWWuplytPHILY/96mJn77q0+gYDfbre7U/30ZloFnmfsXw8z8s9HHccjNywgcsMCWn0yr1Jpzp5GuIQqjlBYBBXix7TWdA75x1FB8+FWu5yO94xI9IRYHuXKfkmCus39LRPKNW5Rp/9UsSSuc2eIs8I1fveDjtej2/xMgNboseq91wadxiBbOZnbgB8TWxH14QIi1y9AkqBBUC7H7p+JJUfvEdncgoe6NdcFJFWtmxndWVlZBAYGkpmZSUBAgKfFqZNsTmyHRlLIVrzrdSVNgaC2s/F4t1LLEoxOGEYzwyWS8hvy7vVrq0WeiPcWoRrtNYtSRk2ulnNW9TOjYP3mK+cge1+91UNZKPlGTo2eU++eb8LC4kYiX6m+Tsg1gf5RB8lWvGmkEcGH7kBYaASe4res1kDJPbFWdn2fGR2+4t3r15arc7U7SH50GrpAU7UpK4LagSgc505KcCtGLY9DlUETls/xB2dUv0xVjLCsuI9tl6Ipu82iQOBeOmyaxf67N/BNYgd0UrDTscl773fKIiypb1hVURe/LwFROK4SCAuLmwhft4jAqEtEbihMYY1aHoeqgaTnJtI4ONuD0glqA5/2XOlpEQT1kKjgdACOmcKKFW48lBXmCZHqNiKGpcIIC4sbsKf1BnMpNQA5R0PkijhQAAk0YfaKjdv6Vn9FWYFAICiLCL+LQMlNEitSEVggqCoqZWFZtGgRkiQxbtw4xz6j0ciYMWMICQnBz8+PwYMHk5bm3Djs5MmTDBw4EB8fHxo3bszkyZOxWq1OY3766Seuu+46DAYDLVu2ZO3atZURtcqIeGMZZ88FIWfokHM0SCooflZ8ozKJuPYMWq3iaREFbib87SWM+ONxT4shELiFFV0+9LQI9QtVcs9WD6mwwvLHH3/w1ltvce211zrtHz9+PF9++SWffPIJP//8M2fOnGHQoMLuqDabjYEDB2I2m9m2bRvr1q1j7dq1zJpV2Kk2KSmJgQMHcuutt7Jnzx7GjRvHk08+ybfffltRcasOCTSpBpBACbTSqN15GjXJZP/dc/nxtjgOD5rtaQkrxex993hahBpHysgpZWZLtP/vbF7af2f1CCSo0xRUln718G0elqR8zN1/FyC+O0pDdGuuOBVSWHJychg6dChvv/02wcGFQVqZmZm8++67xMfHc9ttt9G1a1fWrFnDtm3b2LFjBwDfffcdBw8e5IMPPqBz587ccccdzJs3j9dffx2z2V45cuXKlURGRhIXF0fbtm0ZO3Ys9913H8uXLy9RHk8S2CwT9RojSc9OJGX4VHb2W0T6wYZlT6wldPI56WkRaiUH7nmRGR2+qtJzFPQtEtQdhu8aXmzfwbymQGHXaHdwpfIzOmEYN3/vnoycWR2+ZNDvT/Fix/+6ZT2BoIAKKSxjxoxh4MCB9OnTx2l/QkICFovFaX9MTAwtWrRg+3Z7S/bt27fTsWNHQkNDHWP69etHVlYWBw4ccIy5cu1+/fo51igJk8lEVlaW01YdWGyaYqXXZWspg2shJWUBibL7NYOCvkWC6qE6Kr+u6b6m2L7lXT5y+3muVH4yzN780mep29b/7MY3nd4/sP3/3LZ2rUcE3VYYlxWWjRs38tdff7Fw4cJix1JTU9Hr9QQFBTntDw0NJTU11TGmqLJScLzg2NXGZGVlkZ+fX6JcCxcuJDAw0LE1b97c1Utziajl9por5sPFi/Ycn1r1yanRS+Or/BylMbrNzx47t0BQlFYLq+9z0ESXUW3nqm6qqr9V+//aXeJKPY25KBERw1JhXFJYTp06xXPPPcf69evx8qpcpT53M336dDIzMx3bqVNV18um1SfzkE0SEa8tQ5Uh4s1lVXauAh7eMZLWL9m/nAtquwgE9R3ZUn1f3Mv39Sbi/eI/1ASl81B0An1/GidS9gVuwaXHXkJCAufOneO6665Dq9Wi1Wr5+eefWbFiBVqtltDQUMxmMxkZGU7z0tLSCAuz5/OHhYUVyxoqeF/WmICAALy9vUuUzWAwEBAQ4LRVFcfun8nxaRMIbXWBE1MmkPzUpCo7VwEnMkM4OmMCURvnA5A4UZQYEwgsfvYsvOpwOagq6L0tLDvYr8rPVVf4xxRMhrHk7+z6iqS6Z6uPuKSw9O7dm3379rFnzx7H1q1bN4YOHep4rdPp2Lp1q2POkSNHOHnyJLGxsQDExsayb98+zp075xizZcsWAgICaNeunWNM0TUKxhSs4W4KLBeusrPfIjdLUjry5b9Q6ZQ3ieMnVtt5BYKaSPg6+2cvcYL9s3CNV0aVn/P4AzM5et8sJrX7lg3HujM6YViVn7O2s7Lr+7QMuuBpMWoWIoalwriksPj7+9OhQwenzdfXl5CQEDp06EBgYCAjRoxgwoQJ/PjjjyQkJDB8+HBiY2O54YYbAOjbty/t2rVj2LBh7N27l2+//ZYZM2YwZswYDAYDAKNHjyYxMZEpU6Zw+PBh3njjDT7++GPGjx/v/jsAHJ1R860V2y8Xnjsx2f2y3v3rWLevKRBUJVKulqj4wt5dbXxSq/X8sqQg19enhotsuOFtT4tA9GXLdI1AxLBUGLdHQixfvpw777yTwYMHc/PNNxMWFsZnn33mOK7RaPjqq6/QaDTExsbyyCOP8OijjzJ37lzHmMjISL7++mu2bNlCp06diIuL45133qFfP2GKrQo23fSap0UQVCMLDwwo99hXDvUpe5ALPJ3wiFvWSX56EoZIe7uLh3eMxKToHPVKqoPPzncl3FtYDmoLJ4a84GkRBG5AUtW6WYKmoJV3+IKXuLX3cdZ0X0OrhfEcm17zrSkCwZX0/G4q2/ouZua+e5nX8YtyzYneOB9JUtHprRz69xynY7f+MJG2gWmYFG2pRfC2JMVwe+ThygleDXT73/Pc2vQYobosJrWrnuKSN38/mV/6LOWNw//i6ZifquWcgqql4JmRmZlZJTGQBes3j5+H7F25pBUl38ipCTOrTNaaSp3vJfT3mGcc/6FCWRHUVrb1Xcz43Q+yvMsX5Z5js8qoNgmDl4Xn/x7EgmsLLZ0/3hZ3lZl2aoOyAuCjs7DlVBvC/LOp+vB3Ow833wWAv8ZYTWcU1BlEt+YKU+cVFoGgruBqAbHkR6ZXkSQ1i1/6LGXa3sEczg7l3t+e5lRWMAkDiscsTNzzAHGdP670+V451AedZI8haKTJElYWgaCaENU8BAJBrWdRp//wRa83yLUY0GpsJQaSXzD7Ebl+QaXP9Vzb7x0KSrrNjzBdpttjfQR1GJElVGGEwiIQCOoMW25dTo7RQIA+39GED+wxJ9kWAz5+Jreda8QfjyNLCommxlyw+pU5vus3IvCzqoj4oBYV9BNZQhVGuIQEAkGdokvYPyiqTKThPG0/n0Nemi+64EDO6fzIv+i+Iman8wI56t2EU8Zg8m26MseX5KYSuIf64v6s7wgLSz3kzl+f8bQIAkGV0cQriw03vM1xYyhdm55CH2Lk+IMzODxoNpKXzW3n2XzLK8zq8CVvd3uP9n5nRQVcQbkQlW4rjrCw1DMiX44jadyrnhZDUI3M3ncPL3b8r6fFqDaWdvoEoPCaexQeSx5WNb/EE/MbYlU09e5eCyqAyBKqMMLCUs9IGifK+tc3xAPUPfTaMqXUY293e49sq4EjOaFuK2A3e989Tu/L0y8pepnnurgLaj6vv/46EREReHl50aNHD3bt2nXV8Z988gkxMTF4eXnRsWNHvvnmG6fjqqoya9YsmjRpgre3N3369OHYsWNVJr9QWAQARLxR9R2nBYLaSs/vpvLb7UuuOuZUdhCJmSGkWQJZffTGCp3nixOd6PTlTKC4ovlx7Fulzll2sB+fHO/KvX12OB2bue9eACJeE5/v+s5HH33EhAkTmD17Nn/99RedOnWiX79+Tn39irJt2zYeeughRowYwe7du7n33nu599572b9/v2PMkiVLWLFiBStXrmTnzp34+vrSr18/jMaqqU8kFBYXiIqrm79eIl5bRvLT1VVySyCofWy73MvrauzstwhvnYVN/3TkH3ODCp3n3ui9PNnqd6d9iw/25+EdIx3vp+0dXGzOpHbfcsjYtFidmY2HuwLg1TS3QvII3I+EG2JYKnDe+Ph4Ro4cyfDhw2nXrh0rV67Ex8eH1atXlzj+lVdeoX///kyePJm2bdsyb948rrvuOl57zd7KRVVVXn75ZWbMmME999zDtddey3vvvceZM2f44osvKnx/roZQWFwgcWLdq5Qb+XIcgeGZnhZDUAupUQ3lagjBhjyCvPLJtnkxee/9FVrjmZgfGLJ9FHf++gyP7BzBF/90cmoguKjTf0qcN6vDl8X2RTa6CMDhQbMrJIugCnBjWnNWVpbTZjKVnLZvNptJSEigT5/CekGyLNOnTx+2b99e4pzt27c7jQfo16+fY3xSUhKpqalOYwIDA+nRo0epa1YWEXRbj4l8JY6kcRNp9ck8T4siqIUEB4pf7VfyRa833LLOxthVhK9aSsqoyZVa57t/vewWeQQ1k+bNmzu9nz17NnPmzCk27sKFC9hsNkJDQ532h4aGcvhwyS04UlNTSxyfmprqOF6wr7Qx7kZYWOoxSc/ZA3At571puahuurvqK93+93yVn+PPOypfNbamcmXAqyeorLIiqKG4sdLtqVOnyMzMdGzTp9ftejRCYRGQ/PQkjk+re+4uT3Pnr88w8s9HeTrhkWo/d3mVCeHWcab1p3MZ8cfjNNRlO/2/9fh2mgelEtQp3KiwBAQEOG0Gg6HEUzZs2BCNRkNaWprT/rS0NMLCwkqcExYWdtXxBf+6smZlEQqLwImWi6vX0jLo96eq9XzVwWO7nuDOX58h22wg36bjja4feFokJ+buv4vFB/sDcGJI3SsXX9ES+N3+9zwGvZVQQxYnTSH8kNKK8DWLCV+7mPOX/B1xJdVFRWNgBIIr0ev1dO3ala1btzr2KYrC1q1biY2NLXFObGys03iALVu2OMZHRkYSFhbmNCYrK4udO3eWumZlETEsAieOT61eS8tnN75Zreerap5OeASL4s1XN9XM4nyT996Pjyxz2hTsaVGqjIqWwI8KuojRai+xn2s10KLBJU4STKBvPiHeeVw0+nJDw6Rq685cUABPULdwR6XaisyfMGECjz32GN26daN79+68/PLL5ObmMnz4cAAeffRRrrnmGhYutPdleu6557jllluIi4tj4MCBbNy4kT///JNVq1bZZZAkxo0bx0svvUSrVq2IjIxk5syZNG3alHvvvbdyF1gKQmERCNxIhsXbKaOjJvHKoT4s7fQ9ALf/ON6ta/faMqXMOiU1nQb6PM4pfpw3+xGky6el/wWMVh25Zj0+WjOB3kZ0ko08xcArh/qQbfNiRoevPC22oLbhoUq3Dz74IOfPn2fWrFmkpqbSuXNnNm/e7AiaPXnyJLJc6HTp2bMnGzZsYMaMGTz//PO0atWKL774gg4dOjjGTJkyhdzcXEaNGkVGRga9evVi8+bNeHl5VfICS0ZSVbVOFvnNysoiMDCQzMxMAgICPC2OQOBxqssyUBMZv/tBlnf5qMxxE/c8QL5Nj7fGjEXVkG3xItemJy3PnwFN9pOS35Ao7/MYFR0WVSOqCNchqvqZUbB+xEvzkSv5QFeMRpJnvFDvnm8ihkUg8DDhaxdXeWr55L33k271c+uabxz+l1vXcyejE4Y5Xg/6/SlsyIzf/WCZ8747GYMsKeTaDCTmNOSnY61Iy/Mn+Vgo35ztQL5Nh0G2cMYUxKGcqgksFNRx3Bh0W98QCotA4GF03haO3T+zSs8RqMnnnMXfrWtWpbUm4s3SS8mHr1pa5vwbAwr7mZxIb8if51uQcLFFsXFXdljuFnaKAK0Rk01LgM6IYtaQnNgYNCqnzgdjUWXOmoM4kx9AnlXvwhUJBHZEt+aKIxQWgUfYc7I5+04286gM4avLLrdeHRx/cEaVn6OBNocm+ppf0Th643xGJwyjYUS60/7wd4rEx8hlf1sPa1XYUycn14ttfRfzS5/iis6qg4U9f2buuxdZUrGoGvJtOnsskkUGRULjb0Gvt6KRVL5OaU+k70XyLwfoCgSC6kEoLIJqZUdKBH+l2H/p2pD4IyXcY7KkPDG13tQhSbME0kyfXvZAD2PN1XHwUhj5Zh3RG+cTud5eT8avUWFV3ZQnS++a7CpH75vleD2v4xeczAlmaadP2Bhrz4RIGTUZ2ShzS9Rx+kYeJt+m47rQfwjR5dI5+B9GJwyrk6n5girEjaX56xtCYRGUm/C1lbdIGFUdWaqBPEVHnqIjQ/Fm4/Fu/JTcirVHqyZ3/2q4sw5JQWfc6qY8900n2ThqrFkxF+HrFhG+djERHywk5rMXeWzXE8S2O84vfZZitWrQ6mxIGpWI9xZx4J4XiXhvER02zSp74Stw5f84wv9isX2qVuWvtGZsSW5DmFcWPQIT0UgKOsmGyaatcan5JRUqXHnkFg9IIigREcNSYURacz0l8pU4UCEgOoPM5CBUg1JqKfCI15eBCiljp7p8ntn77nFkUvyREo6vBNmKF2YJFFVGg4pespGteBGizeGbxA4MiNpfxqo1kxO5jarlPC/tv9MpnTbNGljmnAbaHNIszuM8nYqc8pi9emzEBwuxmLVYFA19Qw4A0PWaU7TwTmfnxQgsNg0AN7RKxFtjqVKZNCUEB6jeNjLS/MEq0bhVNgfzmmJWtGSYvR2WmJpEmCGzWFbU6DY/e1AiQVE8VYelLiAUlnpK0nMTiXh/IW0bprE9zR/JYCt1bPKYSRU+z50Be9iREoFR1WFRvfGVzBhVHTqsjtc+kgkv2YJR0ZGh+FT4XJ4m1JBFl69fYPdAu5tp7v67mNXhS0YnDCPHqueDHu9W+hxXKisAU9ttLnNeSQGyN4cer7Q87sA/IB8/LxMBOiNmVcsnx7vSK8if3Tkt6NXoBKkme9qmQWNlTfc1bj9/xPsLUS0yDcOy6NCweFxKyhN2RT3itWX8nX0NAMfSG9I25JzbZSnK9Y/H88da1ws5zurwJZ8c71ps/6Dfn+Kh0F2kWgO5ZPUtsbuzQFCTqbcuoagP627jttKIXBHn9F61yuw71wSsEqpRQ/jKsrMvysM3iYWFhZItDUm3+aGoMhZVS6otEH85H3/ZXoRLJ1nRSzaMig6NpBCiyWFbcpRb5Khulnf5CFWVHG6LPJs9i0QvW92irACVLlT2wPb/475toxn718OcNga5RabKogIXs3w5ltWII3lhvHHyX+zOacFFky8fH72O305Fce9vT7P/QhO3n7sghknna8HPYEJG5fm/B5X4/ZA8dhIfx75FS9/zXEr3Y0/qNW6XpygVUVYKOG8tnhEWYsjFSzaTbGzIr+dbsvDAgMqIJ6gowiVUYeqthSXxoeLdbKPi40icMNED0lQPSc86X5vez0zOOV8kVQLr5c0F9pxsjlHV4CXZyFb0doXEGkiuUlj2PcPmg7+cjw0JnWTlmCmMDI0PjbRZBMl5ZCveAJhVDV5YUJAxS6Vbe2o67RqmOSrdypLKtL2DWdHlPx6WqhBFlbghKIlw/QV+zW7taXEA2H/3XKI2zkcn2/hfUjvyz/twKjgIvd6GTmelWWAmZ3MDCPXLdut5HQHXOTrkRhZCfbJpaMgBoGfUiVLnLbj2M3JsD3Emv2xXXHkY+eejWBUNoYYsFnWq/N/Kq4dv41h+E9r8Zy7Ptf+BIE0eD7faRYgulwybLzrJxpZbl7P2aCx3/vpMjW0jUWdxR1qyUFgEqmw3+yaPrbgLpKYSvSSeE1MKf7FFvBqHf7gFs04PJpDKoaz8ldICo6rFhkSqNYhonYRF1WBUdaTb/JBRyFK8yVP0fJnYEX/ZSIxB4aaIE7x6+DYuWX3xkc34yCY0qOQqBoLkPMxosCleaCQFRZVJt7m3wFl1UrQs/4JrPyvXnLafz+HQv+cU2z9t72D8NCa3ln+/s+FezlqC0UgKMd5n3bZuZUm8IjC2w6ZZZKf7gk3ipCJz8N45bj+nl7cZq1WDzd9C69Dz+GtN5e7fk272IVif5xY53u72nlvWKSAxvxEdff5hxeAPgcIgZRsyKaaGXOtzCoAL1gDa+KeVsopAUPMQCksRksbVTutKUSUrauN8VJtE0lBnC1JRZQVANkv4GMxkmf1RtZfV9RJS5f5ICceGhJdkQ5bApkpoUGmkzeJv0zUEafLQX3bt+EpmUsHu7sHec+WizY+bAA0KHbz/oan2EmeswfjIJvIUA7KkoCg6bKrMRcWPEE0OF2uxwlIeCqqwruz6PgBajUL3zdPp3jiF167b4BiXZfV2+Rf32L8eRpZUArX5tPf+hyEt/3Q6/njr7Y7X0/YOruglVDn7755b5ec4cI89MynbYiDMK9ulrtof9HiXkX8+yrS9g91iFSlg5r57mdfxi0qt8XfGNSW2IbhSGZvU7ttKnUdQQTzUS6gu4FIMy5w5c5AkyWmLiYlxHDcajYwZM4aQkBD8/PwYPHgwaWnOGvzJkycZOHAgPj4+NG7cmMmTJ2O1Wp3G/PTTT1x33XUYDAZatmzJ2rVrK36F9QDZVPjfmDjkhWLKSkkkTpzAzn6LQFZJGT2Z5LGTSH6mUGHbd7IZXyZ2JFfVc97mT56iw6hq0KDSMyIRRbWfs0BZsahadJKV0W1+JkyXgUZSMKsafGUTG451x0u2MCh6NxZVg5dkIcPmQ7K5IRk2HzIUHzJsPqRZgrg98rBT0a+6yMqu7xPpfZ5lB/sx6Pen2Hf3XHb1X+ikrDy26wmXHqAFmBQtfhoTOVYDeYqB+EO3A5SYDmxStDy7+6GKX0gpRLwaV/agGsK67qv57MY3UXC9rsXb3d5jUaf/OLUBqCyVVVYAhl2zvexBAs8hYlgqjMsWlvbt2/P9998XLqAtXGL8+PF8/fXXfPLJJwQGBjJ27FgGDRrE77//DoDNZmPgwIGEhYWxbds2zp49y6OPPopOp2PBAnuQW1JSEgMHDmT06NGsX7+erVu38uSTT9KkSRP69XMuoy2wkzjx6sF50cviOTGp5DGlFeGyqDIhci65qh6bKmNDomd4suO4XRkxY1Y1+Mv5IMPqczdzUwSEabKwITnFpwRp7ObzU5YQdJINX9lEmC6TdJsf/pp8QrQ5tdoV5CplZfas677a5TWfTniEpoZsdJKN47mNyLJ6c9HkwwQgpmHxjJblXT5i5r57iT90O3uzm3Od/0kybd7oJBu/p0ez72hzUka4XqTN65ocl+d4mt0XriFq4/xirqnyUGApqykUtaIJBHUJlxUWrVZLWFjxAlSZmZm8++67bNiwgdtuuw2ANWvW0LZtW3bs2MENN9zAd999x8GDB/n+++8JDQ2lc+fOzJs3j6lTpzJnzhz0ej0rV64kMjKSuDj7r7S2bdvy22+/sXz5cqGwVBBF77o6bkbGjIbbIw/z/rEbCJCNTsf7Rx3k/WM34CWb8ZUs2JDx1ZoAuD48xVHB1qjoaKzNxkc28faRmwjR2utoZCle+MomvDSWWlt3pSbQcdMsGvvnYLFpMFqbc1uTo0R6n6Nlo1Qnd9CnPVeWOP+f/GCaBGRwjVcGaZYAWnql8X16OwD6XHuQEX88Tlf/5BLTosfvfhCDbC3mEjk8aLb7LrCayDXpK6SsCASuIuqwVByX05qPHTtG06ZNiYqKYujQoZw8eRKAhIQELBYLffr0cYyNiYmhRYsWbN9u1/i3b99Ox44dCQ0NdYzp168fWVlZHDhwwDGm6BoFYwrWKA2TyURWVpbTJrBzZXZQebghPBmjYq9JMazVDnLV4o3e/OV8x2tfyezk0rg+PIVT5hB+y2qNj2zCS7IQpMnDX85nUPRuhrT8k7ui9gllpYLc/etYAIJ98snI9ybXrKeBdx7tfU5zwRpQLHalNGL8zuKvMdLa6yynjUH8ntmKhoYcovwucCo3iHDvi/yd25zHdj1RbO7yLh85lJUh20cRvm6R+y6wmrFaNZ4WoVayIyWCufvv8rQYgnqCSxaWHj16sHbtWtq0acPZs2d58cUXuemmm9i/fz+pqano9XqCgoKc5oSGhpKamgpAamqqk7JScLzg2NXGZGVlkZ+fj7e3d4myLVy4kBdffNGVyxGUgUZSHK8vWv34JrGDw72TpxjQSBJ3Re3jh6Q2+MimYvOv905k64UY0oP8GBS9mxuqU/g6zqabXgNwNPS7+fvJ9G18kEP5TfnseCcmtSt7jVcO9UEnSaRb/WigzUErKZzMCSbC/yL5Nh3f/etl4g/dTqT3+TJdWBtjV0H1d1a4KhP3PECW1YsjGaElNj4sSpMg8QOnItwQniw+14JqwyWF5Y477nC8vvbaa+nRowfh4eF8/PHHpSoS1cX06dOZMKEwTiMrK4vmzZt7UKLaT9FsncbabGQUFHTkKQayFC/Hr/jbIo/wa3J0sfk9IxLZFFFd0tZvBjbdx4S2WwBYcG355jzX1h6L9v6xGwjR5KCT7fU5inIot4nb024LGPnno2Wu/fCOkXT0P8309t+4tPYjO0fwQY+Pyz3+x9viGL5reJVU0hUInBBZQhWmUpVug4KCaN26NcePHycsLAyz2UxGRobTmLS0NEfMS1hYWLGsoYL3ZY0JCAi4qlJkMBgICAhw2qqTiDeXVev5qgNNkU+Fl2Shf9RBLlr98JIsxWJavCTrldMF1Uh5yvOXxrBWOzhpCSkxeLSqlJXHdj1Rrr5AtwYfxk9jLHPclbirsnBZrD56Y7Wcp7rwVAPP+kRBDEtlt/pIpRSWnJwcTpw4QZMmTejatSs6nY6tW7c6jh85coSTJ08SG2u3FcfGxrJv3z7OnSvMWNiyZQsBAQG0a9fOMaboGgVjCtaoqSQ/VfeKzd3fMgGw12Ixq3Yff4T+PLdFHkEnWZ2sKteHp3hERoF7qK7mePdtG02Pb6dx4GIYGpQyx2fafHgm5odqkAzWdF/D5L330/Wb8gffnjEHlz2oFnHGGMQrh/rQ87updPlaBCFXGSKluUJIqqqW+/InTZrEXXfdRXh4OGfOnGH27Nns2bOHgwcP0qhRI5566im++eYb1q5dS0BAAM888wwA27ZtA+xpzZ07d6Zp06YsWbKE1NRUhg0bxpNPPumU1tyhQwfGjBnDE088wQ8//MCzzz7L119/7VKWUFZWFoGBgWRmZla7tcXdeLJlwI6UCBRVxqjaA3BvizziETkEdYvIDQvw9TNybeOzTtWBayMrj9zCBYs/OtlaKUtXTeHZ3Q+xosuHTNzzAHGdy+9Wq2nsSInghiKlGMqiqp8ZBeu3nLYAjcGrUmvZTEaOL3q+TjzfXMElC8s///zDQw89RJs2bXjggQcICQlhx44dNGrUCIDly5dz5513MnjwYG6++WbCwsL47LPC8uQajYavvvoKjUZDbGwsjzzyCI8++ihz5xZWtYyMjOTrr79my5YtdOrUibi4ON555516ndKcOGEiUcvLV4wr4tU4tzUxBHtQXc+IRG6LPCKUFYHbSHr4eSwWLSeza7+FYnSbn0k1B3DJ4svzfw+i948Vb1pYE1jR5UOAWq2s/JTcCg2qo7xCjUIUjqswLllYahN1ycLiCuHrFpHy2DRPi1EmUXHxZRa8E9QfXtp/JxpJcTm4tqbQ+asZmK1aLBYNNpuMwWApsT+UoHr47EQXwjSZ9IxILNf4qOVx2MxGTk6bUeUWllZT3GNhObZEWFgEFSB87eIKzYt8xf0lzF+M/a/jdd+fxrl9fXchlBVBAeN3P8gZUxCHc8O4b9voGt3jqDS6ND6NxaLBnK3Hlq0jP9fA7T+Or/S6mxPblVnnpOcDdS/g3x2YKX9tncTxE5EtrrdnEFQvQmFxAymPT3V5TlRcPEnPuScuZe3RWLYkxbAlKYYQbQ7vH7NXRvjuXy+7ZX2BoCpZ3uUjsqwG9LIVraSQYfVh8t77ARj0+1Melq58rOm+hibBWTQMyyI88jyRTS/Q1DfTaUxZPYd6bbG3QXh4x0jHvoOma4Cr34dtH1cs4H/EH4+z8MCAciuIO1IiKnSe6ibizWUMit7NvyKOuTRv77Njq0iiKxAuoQojFJZqos1/CuN0ouLiUTXu+Yv7MrEjjbXZl5sP2vCXjXW+eaCg7mGQbQRojfhqzazs+j4mxV4i6rMb3yz3GssO9qP/z89VlYhl4qW1EB6YTrvgVH68La5YP6hQfZYjA6nlRy/R7os5PLD9/xzH/znbgPb/nc22Y1EM+OVZAPZm22tJWRUNrT6Z51Z5371+LbKk8Nel5kzc80CZ428IT+aPlHBG/vmoW+VwNzU9Y1OkNVccEcNSxUS8vgzJKrnNmlLAFyc6oZdsyCj0jzro1rUFgtrKzd9PLrOqbVXQ8uN5WPL0GPxMHL2veGfsotyydRJtg9LIMHtz4HwY/l4m0nN8MObpkWQVxajh8eu38dO5VqRmBGDK1aMqEqiQMtx1a+7VWHhgAOlWX5rpLzkKCdZXqitLqPUk98SwHF1W/2JYXG5+KCg/4esW4dcsH0Wx+0ZbLorn+DT3xG7cG70XgG3JUW5ZT1A/KEhZrat4QlkB0GhUGoRlcCnbp8yxP/cuOeak81cziAhKJzmjARZVw8+9lxH+9hJSRk6h948TaOTl/i7Yfhojp4wNaOWf6va1BaUgKt1WGOESqkpMGvKSAjCbdMUOtVwcT8SbyypdIbe8UfC1ndoSy+AqL+2/s1rPV5eVFU8xfveD3N1yH3c324c5w1Dhdfbc+RLRfhfo2SSZ47n2UhFBYdkAbL013t6vyU0UuICO5IVxwezLL9lt3La2oAxEDEuFEQpLFSLnyagaCG1gb6xW1LpyfOoEkp+aVOP9rTWFaL8L3Pz9ZE+L4RYKAkon772fTJt3mcGYgprNiRy7crF6X0/QVe5JEtf5Y2RJ4e+zTRnwy7P4GMzuELEYp/PtFW1vCThCY0M2Z02BVXIegcCdCIWlCkkaNxFNvkR6TtlmYsHV+SU1mjyLjpYfzyPi/YWeFqdSZFu9GJ0wjIa6bFp7pdLMcMnTItVrFh4YUKn5m256jXSzL7LGRsrjU+n6zQsOpbQivHbdBg4Pms2pjCC29y27ZMKNg1230m6MXcVzbb/n/pYJhOhyOZQeyn3bRldEXIGLiKDbiiMUFjcTuSKOqPjC+ionpkzg8KDZHpSo9lLUXZZ6NpjzZ4I4/sBM1Dwt4as8E6vgDn4/Hck5ox8WRUtCTgT/mGp/tdcCWn9amA3n6gMw4r1F7hanTCbueQCLWv56HaXx7vVrOf7ATACigy+gk2yVXnPf3fZ7WVZvo9//Uzkr7Ysd/8u5CwGcyg6q1DqCciJcQhVGBN26maRnPdPzpy4R/u4SkFRSnrJnRHTcNAtM/kiXCzul/J/dNRTx3iKSH635VX2vJMw/m8ZeOfxjCmZ/ehN+u32Jp0VyG6b0wo7qn/ZcSdTG+fj6mOjb4jDbz0XSwv+SIxZjxB+PY5CtpBr9Mdp0tG5R/b+f9mU05eaGx926ZnPvS/jIZsbvfpDlXT6q9HoJA+a7QaqrM77rVq73TgSqX2msd4ig2wojLCwVoP205Z4WoVbQa8uUClXblQw2dL4Wx/ucpEAkq4R6RXxAbVNWYr+byuS999Mh6Awmm5YGutw6pawApIxyjjNqGXYefy8Tnx/uREaeN4mZITyycwTRG+0P4VybnmB9Pj5as0cKHSZfaMDBnCZuXTNYm4eXbMFPa3LbmgVF5aqKnj7H0Ek2dqRE1JoCcYL6R72zsLSftpwDi1wvmd36pXiOzrAHzVZkfn2iw6ZZ+OgtNPXLwU/n2pf2nb8+w62tc1jTfQ0RHyyETB3oQdUqlQ5o9CQz991LZEAjTuQ0pHPgP/hpTRzIcu+DsiYSoDfSrcFJ1v/TAyOgqqBpoKI3WDidF4iP1kyYVzaf9lzpEfmO3jeLqA8XwA3uW3NGh6/ct9hlbg51rxWoKD8lt8JLklBU++/X+pJ56CncEYNSX2NY6rzC0mHlq5ycUugDrqiyUaCsuJuCOgt1iRZBGRw/15BL2T7c0fIg9/72NIfPhSLLKnqtlT13vkTUxvk0DMphV397AG33zdPZ1X8hqTn+JF+yx3R4+ZgxSSpKrg4UCUy1t9fHvI5fOF7P3HcvZ4xBLlVxra2czArGaNPhF5JHbpYXh4bM8bRIxbAZNbT9fA4Gnf1vsyay4NrPiu37K6UF14WfrPTaBSXsPzvRheba9EqvJygD4RKqMHXeJbR/9DOeFuGq1DVlpdUn81BUCZ3Ohqra636kG30BuCYwkwAvE/1/fo7WTc5xY2git/84nhF/PI7FZv9TzDPpUVWJrt+8gCyrePmYkf0saAPNSN6VD2SsCczr+AWKWnuVr/LS6cuZ5BgNHD4TSsfGZ9F7W8qe5AEknULeJW/yjHoiPlhot+xVAe5OX3eHslKUIDmPE5ZGbl1TUPtIT09n6NChBAQEEBQUxIgRI8jJKb1oYXp6Os888wxt2rTB29ubFi1a8Oyzz5KZ6dxLS5KkYtvGjRtdkq3OW1gE1UPkhgU0aZgJ+GFRNOg0NvKs9iJaF3N9ODxoNh03zSLQ24gsqfYmdxYfrKrMTydaodNbGbJ9FFZrM0ICcjlzugGo4B1kJDAgj4xTQeBfMx94JTF3/13M6vBlqcfXdF9T6rG3j9zEyDa/VoVY1UrmJV80ehsnhlw9y8XTSJJK8hPOJe97bZni9viig5fCKjX/ge3/x8exb7lJmuL8lR/BpHbfVtn6Ajs13SU0dOhQzp49y5YtW7BYLAwfPpxRo0axYcOGEsefOXOGM2fOsGzZMtq1a0dKSgqjR4/mzJkzfPrpp05j16xZQ//+/R3vg4KCXJKtXigs4e8sQcrXkPyMyOCpKpIeft7xetDvT7H11nhHiuuBe14EQCMrpOf6cOZiILKsYDBYCfA2IkkqAT5Gjl1qhDlfx5nMEPsnUpHIz/IiXzLg1TgPnc5Kz++mYrZpaB18Hl+tiUtmH24KPo5BtjC6zc8eufaS8NMYyzVu5r57kVE5kN2ET3uuZMj2UTQ02BveDfjlWb65eUVVilmlSFqlxisrAElDny+2z93KSviqpUREV/wp0+PbaezsV3XKCiCUleqiBruEDh06xObNm/njjz/o1q0bAK+++ioDBgxg2bJlNG3atNicDh068J///MfxPjo6mvnz5/PII49gtVrRagvVjKCgIMLCKq6413mXEEDKk1OEslKNFMRmXNkEbs+dL3Hw3jkkDnkBq0lL86AMMnK9CW+cjl5jIz3Dl9DGdjOiZNIgmWVkvQ0vPzM6nRVfg5nMfC989WaOZzTErGjx15pIswTUKGUFYELbLeUaN6/jF2w+09YRdLoxdhWvXWf/JXMhz7fK5KsOiiqx9ZnwVUtBUgn1ya7wGl0annajRIK6QlZWltNmMlUuM2379u0EBQU5lBWAPn36IMsyO3fuLPc6BU0ZiyorAGPGjKFhw4Z0796d1atX42rv5XphYRHUPCSNytEzoWh1Vpr5ZqCVFPItOhr55EIzyMjxwXjRGwnw8TIR5G3kdHogrUPP0zXoJHmKnnMmfy6afMm2Vrx/S01gZz977YsrTf4FAcml8cbhf/F0zE9VKZqggtz961hOpIeQn2dAH2wj0C8fs63iBepC9VlulE7gUdxoYWnevLnT7tmzZzNnzpwKL5uamkrjxo2d9mm1Who0aEBqavkaZF64cIF58+YxatQop/1z587ltttuw8fHh++++46nn36anJwcnn322XLLVy8sLIKq5Zatk1yuUqoYNQT453H0vlms674ak6KhgXce2WYDPjoLd0bvxyskn6DAXHz1Fs5l+xHV6CJZJi8sqgadZKOxIZtGXjmcyQkk9jt7DEJNKi9+969jXRrvanxCutXP0cRO4HnG736Qh3eMJOazFzErGpoGZNEwOJvQoGx89Wb0Ghv9f36OW7ZO4uEdI11ae19WU/r//FwVSS6oTiQ3bQCnTp0iMzPTsU2fPr3Ec06bNq3EoNei2+HDhyt9bVlZWQwcOJB27doVU5xmzpzJjTfeSJcuXZg6dSpTpkxh6VLXKpYLC4ug0vzcu3gvk1afzMN61oekZycSuX5BsTiBlCem8tiuJxzvvTUWttzqXJDv+1Mzyc23W096XpOEt8bCvkt2H2q6xRetZEMn29jWdzFj/3oYgMaGHCbvvZ90sy+N9NlkWb15o+sHxeQb+9fDDtdLVbHpptfcvubohGGs7Po+UDX1PgQVZ3mXjxj0+1ME+uYTpM/notGXPLMOrZdCM58sdp9pRnSjC4T6ZBPte96ltetKCnyr+fGO18deqJpSEfWJgIAAAgICyhw3ceJEHn/88auOiYqKIiwsjHPnzjntt1qtpKenlxl7kp2dTf/+/fH39+fzzz9Hp9NddXyPHj2YN28eJpMJg6F8VnJhYRFUCcfun+loU3ClstJxkz22pZP/Kce+MENxk/feu+ZxY4skGvrk8ffFpnyXFEObwHNkWHwI0ubhrbGQb7N/KAqUjxB9DhoUDLKVLKu9TPzTCY8A9qJ0Be+DdXmM3/2gOy+5WihQVsLfqVsVcusKfUIOsbPfIgwaK0Ov2cHzbTczqNkeugSe5IbmyRw/15CUrGDybHpPi1rttFoYD9LlLBml7qf1l4oHegk1atSImJiYq256vZ7Y2FgyMjJISEhwzP3hhx9QFIUePXqUun5WVhZ9+/ZFr9ezadMmvLy8ypRpz549BAcHl1tZAWFh8QjRS+JRDCqKQUHys5L8SMlmvLpKQVO3CW23sPhgf3xkM3m2hiWOVZA4droxap4WycvGsaxGHD/ZmNHdfsFPYyRU56zonMxvQL5NR5eAU0xv/w23/zgencZGx02zaB4kOZQXnWRDKytVe6GXiXwljqTn3Bv0nfJk3arfU1coiCnKthj4xxxCS69U/DRGTIqOjn6nWXffarecx11F46qTY9OFRQVqdlpz27Zt6d+/PyNHjmTlypVYLBbGjh3LkCFDHBlCp0+fpnfv3rz33nt0797doazk5eXxwQcfOAKAwa4oaTQavvzyS9LS0rjhhhvw8vJiy5YtLFiwgEmTXGvcKSwsHuDElAmoepXgZpkEB5dekKc+MLXdZp6J+YGzxkCeTnjEYQUp4LzRj+7RyVwTcQEvPxMXc33ApGF7ehTH8kNpoHW+fxZFw8exbzG9/TcAbLl1Od/cvIJ9d8/lQFJTjmU1QkEi0+rtlo66pRG1sbBhnbuVlfJQtNO1oPr57MY3yVP0HDU24aw5iEybt1vThmuCstL6pXhavxTvtK/NXNFnrUxqeLfm9evXExMTQ+/evRkwYAC9evVi1apVjuMWi4UjR46Ql5cHwF9//cXOnTvZt28fLVu2pEmTJo7t1Cm7FV2n0/H6668TGxtL586deeutt4iPj2f27NkuySYsLB6iSfR5tvdd7Gkxagwbbnibu38dy1c3vUqrT+Zx7P6ZAATp80k3+XBtyBm+vdCW/GwD6BSSLjXgRHoIDaNziq1TGlKuFp3GxsFLYUQGXOSSyadKrqXzVzNIHOLhEu91oyhwjaDjplkMb7W93KnqBWRZvbBoNA63ZV2izZzlSLKEonF+ch6ZJfqs1XYaNGhQapE4gIiICKd05H/9619lpif379/fqWBcRREWFjcSvSS+7EGXqYyyUpMyYdxJQZBq27A0Ht4xkiHbR6GTbaSkB7P9TIR90GXft9Um0yXsH07kNeKB7f9XrvXlYDNWReaXPktZ1301J9JDquIyHP1ooj5cUCXrl4fksa6ZWmsj4WtK/gy5swT+Y7ueYHir7fjL5SsEWJTXrtuASdGSb9NjUurWb8Mjc8YjWUC21uNYlMpQQ60rNR2hsLiRE1Oqx0drtOnsxajqIL1/nECuVU+QLh9/nZF/coPQahR8DWZujD5ByvCppAyfisWs5URmQ/7JDSLPWr4AxuDAXIzWwl+7udllB4ZVhsSHrl44LXy18wPX1dTw+k5ok4wS96/s+r7blBZvjYULFn/OWoIqNN8gW2nqlUGILtct8tQkDs8bX5hfKyg3BTEsld3qI3VL7a8n7DvejIjoNE+LUSVsvTWe4buG83d6U1oFnifCLx2dbOOS0Zu0vML0veMPznC8Lq/FKWHAfKf3Wp1n/SZSvobwNYtJGW6vIZP86DSPylPbuFphvYJsqsoS7nWRhMwWtPVPZeGBARgVHS92/G+551sVmXmdvnCLLDURyeppCQT1CaGw1CLCVy0FFVL+b2rZg2sxf19oSq5RT5BXPsfONeLfLfeSnBfCxthVJY4vKGtfEv1/fo7WAedY0eXDYscMXp5tppg8pu67bWo7mVZvvDQWdJKN43n2CqBRHy4o03pWwI7zEVUoXQ2gnv7SrxQ1uJdQTUe4hGoJjqyPevCHmjBgPi0bXeDQ6TBkWWFRp/+UqKy8tP/OMtdqG5CKopZstz5wz4t0+brmN+cTuAdXq8sCLOr0Hzr7/8M5sz+ypOCtMWPL1xRz55VGoMH12JfahFQ9lQHqFMIlVHFcVlhOnz7NI488QkhICN7e3nTs2JE///zTcVxVVWbNmkWTJk3w9vamT58+HDt2zGmN9PR0hg4dSkBAAEFBQYwYMYKcHOdsj7///pubbroJLy8vmjdvzpIl9btQVvJTk2jU/BIpoyd7WpRqwUtjt37k55ReVKg8lV73ZzTFW1O6JWX3wPmlHqss4evKjkkpKKInqHo23PA2I/98lIl7HmDmvnvLPc+iamjlba/+GazLI+WJqY7g77Lo0SC5ApLWLtq+IFKZBdWDSwrLpUuXuPHGG9HpdPzvf//j4MGDxMXFERwc7BizZMkSVqxYwcqVK9m5cye+vr7069cPo7Hwl8bQoUM5cOAAW7Zs4auvvuKXX35xapRUUIgmPDychIQEli5dypw5c5xywesjF5IbeFqEShPz2Yu0+c/cq47psGkWxiKpoAVVXYvOi1xfvgycLbcux6rIdPufBzoHm0pvdldQp6WgiF5FEEG6rnM2PxAfjZl5Hb8o95zp7b/hubbf09SQiVG5/HepK920MG3vYMDeY6uBNtcl5ai20H7acto9v5xD88dzaL5IZXaJGl6HpSbjksKyePFimjdvzpo1a+jevTuRkZH07duX6OhowG5defnll5kxYwb33HMP1157Le+99x5nzpzhiy++AODQoUNs3ryZd955hx49etCrVy9effVVNm7cyJkzZwB74Rqz2czq1atp3749Q4YM4dlnnyU+vvxpw3WR5KfsMQ8FD6rZ++7xpDguExUfB4BOZ3WyPoSvWUzE+wuJ+GAh7b6Yw/6755JtNhAddh6tweqo6mq1FJriryz3fzUyLD54aa30/K78sT/uUHBSRhVaw4oWkgNIHFJ5V5SUUXJ9j4jXRdG40ggx5BJtsAesu9qa4cWO/2Vpp0/sbyylf3W29k7l2d0P0TLgAulWX/7JD2bEH49XVOQayYFF4zm4QCgqFUG4hCqOSwrLpk2b6NatG/fffz+NGzemS5cuvP12YaGupKQkUlNT6dOnj2NfYGAgPXr0YPv27QBs376doKAgunXr5hjTp08fZFlm586djjE333wzen1humq/fv04cuQIly5dKlE2k8nkKAlctDRwXaPzVzMcf62uZCvUBBInTOTwoNlkp/qj87YQvmopEe8vRNKoqBaZxg2zyLvsAgr1ySblYgOspsK4cFWV0PlayrTQXMma7mv47fYlbOu7mA6bZtnvYRlcuODv2sWVQuQGuyWoJAXl9h9d/8IPf7vQNapqS/7WEsG8pbOu+2qyFW+e/3sQBrniKS5Xa42w7lQsTfSZyJKCSdHSzPsS716/tsLnEggEdlxSWBITE3nzzTdp1aoV3377LU899RTPPvss69atAyA1NRWA0NBQp3mhoaGOY6mpqTRu3NjpuFarpUGDBk5jSlqj6DmuZOHChQQGBjq25s2bu3JptYZLF/xRzaW7GmoDKaMmE97osuKZo0NVJCS9Qr5ZByr02mJ/GAT65iMXMb3bcrVodTakSvy88NJZHYXdrkbysMr1dypwYyU9XLqlJvlCgxKVr5Yfzyt1TsrIwgdl8tNCMakIz8T8wIJrP2NRp/9UyfqtA88xvf03vN3tPQK1+VVyDkEtRriEKoxLCouiKFx33XUsWLCALl26MGrUKEeTJE8zffp0MjMzHVtBD4O6QoELJeXxqaSMqP2N70K8cvELzXG4uVSjhtw8A7JOIS3Dn0BdPi0CLoEqEblhARHvLUIyyzQOyCH/krfDcuEqf95Rueqz4e+WL/i7PM0Jj90/kyODZzlZTQCOPzCzQrIVpe3ncyq9hsB1Ju55oFiQtyvxMoJ6gFBYKoxLCkuTJk1o166d0762bdty8qS9EVdYWBgAaWnORc3S0tIcx8LCwjh37pzTcavVSnp6utOYktYoeo4rMRgMBAQEOG11CSm3/CVzev9Y87ui/pEUTs4FXwBkvQ3JYEMxa9BoFAJ8jXTwPUOW2YvgwFwUi4xqlVBllcx8L6R8GcVYPitTj2+LF2Mrj0uoNCqiLJZWQt6x5kj3K6CH/j3H7WsKysakaJ1q/mTbqraasqD2IWJYKo5LCsuNN97IkSNHnPYdPXqU8PBwACIjIwkLC2Pr1q2O41lZWezcuZPY2FgAYmNjycjIICEhwTHmhx9+QFEUevTo4Rjzyy+/YLEU/lLZsmULbdq0ccpIqos8snMEAOFvLXXUXgl/dwmqvtA10v6/s2n/39nF3AkFQaUnDjetJmkrTtLDz4NNIuLNZXaXkEZF0irYbDJ+BhP7c+3X4K2zgE0Cm0RA02xahZxH9bOBBK0/LTuW5fyl4rEoFlv1udQi3l+IbChfRd1OX1besiJwHwsPDChzTFScPREgemk8N38/mdeuc24at+Daz9wiy9tHbnLLOgJBbcYlhWX8+PHs2LGDBQsWcPz4cTZs2MCqVasYM2YMAJIkMW7cOF566SU2bdrEvn37ePTRR2natCn33nsvYLfI9O/fn5EjR7Jr1y5+//13xo4dy5AhQ2ja1P6Qevjhh9Hr9YwYMYIDBw7w0Ucf8corrzBhQs23HFSWHSkR9hdeNqRAM12+foEb2x8j5ckpjriI3DP+HLjnRY4Mdq7hkWe+nDXiay0sNFeT0Smo3vaYFFWRLps6JXJMBtLyA2jsnc3pc0FIOgV0KoMi9xLmlUXr8FT8GuRhMZVsdWr3xRzC311C5Io4FItMuy/mOB0/cM+LVX9tl0keNp1GDbLLNXbvXaXHrgiqnzxFz8g/H73qGMVbodUn80CCX/pUXX+vkW1+rbK1BdWMcAlVGJdK819//fV8/vnnTJ8+nblz5xIZGcnLL7/M0KFDHWOmTJlCbm4uo0aNIiMjg169erF582a8vApNo+vXr2fs2LH07t0bWZYZPHgwK1ascBwPDAzku+++Y8yYMXTt2pWGDRsya9Ysp1ot5aX71ws4/FDtqFfR+asZHH/AHhAa1CC32AOsIC6iIO7jSjIzfezHH51GzGfV91CuKJJOQbVJaLQKiiqhWGVUK1y86Ecj3xx7LRYJZK2KzSRxyepDiC6X87m+3NA0hTSjP5HrFxAYmEezwEwOnwnFkmkAvTeSSUbVqKi5Wmw+ni3BX1qlXUHN5mR+Axobsun70zg6BZ9mcNAfWFQNN0WccIxJfnoS7b6Yg1n01BGUE0lVkdTKaRyVnV9bkVS1bl55VlYWgYGBZGZm1pp4lvBVS51qd1yNiNeXkTxmEpGvxKFtmsex+53dCeFvL6mS2Ah3Eb1xPlaTxu4KklRUVbJXD5VUZK1Kz6gTHMtoRNq5QLvLKE/LsF6/YZCs7LoUQe+Gh/k7pxkmRcPZvEDOZgZgOhaANdAGGtWusHjZkPI0qAalRt8LQc1jyPZRtPFLw0u2cCCnCUG6fAYE/U1zbQavn7/Vbc0VBTWHqn5mFKzfedh8NPrKxTbZzEb2vP9CrXq+uQPRS6gGUV5lBey1NgqCOS0XvIuv5YYHdMuPyk7/rQgPbP8/mjW6hEavIMl2fVm12ZUVVAlVgbN5geSZ9PbjJg0oYJCseMkWugcnk271JdeqZ3dqM07sv4bciz7YfBW7qVTB0fZe1ar2GBiBwAU2xq7ixY7/xU9jRCOpvHbdBk5aQki1+ZWqrBSk4wsEV0W4hCqMUFhqIeGr7L7ylOFTSXpuYqkuogqvfznN9viDFc+muRofx75FWqY/DYJyaByShVZvQ3M5qFhVJHQGK4H6fCxWDbJGBYPNUQwtzRJAUn5DPkvqhK/WTO4Zf6QGJtCo4G+xKyqqhKpV7BYbXT39ZAvcwjMxP7Cu+2oARrf5mdsjD5c69toGZ1h8sD8rj9xSXeIJaiEiS6jiCIWlFlKaJSZ6SflbF0R9WHI9kqiN85F9qt4h38Avjz/vWEC74DTuaHnQXgxOldB5WzDorZzL88eYq0eSFdpGnAVg16UITuUFczyrITk5XpzMCQY/u5Ii5Wsgx154TrJIoF4O4rVJdmVGIKhijmU1Ymq7zZw21+1MRndxR4tx9G9T/nYZAkG9UVhKy5qJeDWumiWpOAUplEUpWkDtxJTyZ1HZSqhjErkiDs56IZ0zVHljvW197e6saJ/z+MhmTgx5AY3eRusm5+je5CTeWguyVqVzs9MoqkT42sUcPBvK9v0tSTkUhpKj49ipUHq2SsTPz95YU5VVJOtlRUVSQQbJZldewt+qugwOgQDsjTYBLpr9AIheVr97n5WFEuSPlGcse2BdQ7iEKky9UVhKcptExceR/MxED0hTMRInTqDL1849aa5W+v2qXI4difhgoWOXGmRBlUEfnmPv9bOuapWWNv+Zy9dn2pNltcfgtGpyjktGb07lBpFr0dMgKIeTWcEcOd4UTboW60VvJG8bql5Fskh4+ZnIsRgY3mo72pB8uyVFBjQ4arcUfLglc935U6+q2CKBe8iw2P+erQ08m51W0/n273n879Qr9O06x9OiVCvCJVRx6s63eAVInFB7lJUCdg+cX/agUghfWYKVocgfvmqTaNAqncODZmO1aOzBrlWIqtqLuGVZDUS8uYxDJ5qSnu1LY+9sbKrEn3csYFf/haBVsfkpqBoV6YIeySwhWSWMab78vS8Cf9mIzapBMslgu3xNl/+yVa2KZJaRlKtJUnu4+9exVRZbJKgYL+2/0+n9hhvsDWFTnhDujvKQ18LX0yIIagku1WER1G5kU6F+mvKYvWS9l6+Z6I3zOTHkBQz+JnLy7d2Sff2MZLvQDqAiHL2vsPBdj4xpXMz0xcfLxK5T4Wi1hRqGX3AeVqsG0zkfJBUUnYpslpDyJWw+Ches/igmDWjtLiHVx15ZVsrXoF6OX5EtdSNTaNNNr3laBMEV/JnRgrn77+KUMZhr/f7hmZgfPC1SrULV1I3PZrlxh0tHWFgEdZ2k54pblA4Pmg3YM49MGV6O6rn7755brbVLdvZbhJ+PiSBvI1GNLmLQ2c3pj+16ggP3vEi/qEMkPzWJ6M7/oAsyAaB4q6SMnmzv12KTwMuGqrPbSyVZtVtkTLLD/SWoP9z56zPVcp7RCcM4fC6UWR2+5O1u7wllpQL4H0r3tAjVinAJVRyhsAgI8M8DytdhuCrJOBmEQWPl0JFmDtfXL8dbArDzXDhgD2w8/uAMEidMtKcuA+t3xDoygiSTDFaZ5EenkTJqMqq3DVWvYPNSaDVfBEHWVa5sMPnVTa9Wy3lXdn3fofQLKsbmAwvoe/0cT4tRfYig2wojFJYqoKqDVUsjZtbyqx7v+k1hwG7RrClVlZC8PV9bXNWoHD0T6pS2XRBUvLNf8XtaYAHSBxtJGTmFlCemkvzMRKeOyilPTkGTpQVVwtywfE0IBbWPlOH2eJGiWXOC2sN3f8zxtAiCWoCIYakCCuJDqpvDc8df9fiF04GO15JFInz1YsKuuYSPXsUWmF/V4pVJyv9NtqdWu8iVbQmuJHFiYbp3y49eEkGrdZgKZ80JBNVIfXXpVBZhYalHFI1JUbwUUp6YSp5JT5ugc5jMWjp/5fkHuaJXeHjHyCpbXygrgprEgZPXcODkNfyREs6Bk9eUe16fG1/i5ruWVKFkgipDVd2z1UOEhaWeUuB22Xf3XPuO7h4Upih6hb/ONPO0FAJBtWBBRoPK9eEpJP/ThBOnmtB/x9NlWg1t3lqs3jI337mEX74SPYwE9QOhsNQywt9dQkCjnEJFoyrOsWopSGqVZQlFvLYM1UshKiqNH29zdgFJJk21BzFGvLaM5LHu7cckEJSHzi1OOV5nKxo6tviH6MTnypz34/eecTsLKo87snzqq0tJuIRqGSkjplSpsgJ260tVpjQnj50ENolLed7FSuar1ZyCbFfOLr/2ULC0QADwVfa1AAxtutPDkgiqFJElVGHqhcIS+13NrDhZn9vRp/zfZCw2DXK+TOQrhVYW/ybZ1SvHqMkkj5lE5IYF+AV5PvBYUP/YcMzuj53e/hsAhrXa4UlxBIIaS71QWLb3XVz2IA+Qmh7gaRE8il5rRQmwggStP53LgF+eJTfHC4DwtdX7f5b08PMcuOfFUrtYCwRVxcOtdjleJ//TxIOSCKoDSXHPVh+pFwpLZen707gqWbcuZ6y0+c9cbv5+st3lUgq7B85HNthQvBT0eisX830cx1Ie94xVLPEhkRYrEAiqEOESqjAi6LYcfPevlz16/vB3l4CsOopj1QbCQ9K5xieTX0aVrrAAJA0triCEr1vksVo2AkF18k1iBwZE7Qfg2ClhXREIroawsFzB7T9evfhadRO+bhGS3oZ0uYlfdbtKKso/GUGs6b6mQnPbRpwl4oOFbpZIIKh5tNNfdLzWSZCt6DwojaA6qOm9hNLT0xk6dCgBAQEEBQUxYsQIcnJyrjrnX//6F5IkOW2jR492GnPy5EkGDhyIj48PjRs3ZvLkyVitrlVYFwrLFRw9GeppEZxIeWwaycOmk/yo3eLgKVeJqxy8d47jddRy16rXHjrRFOmCvsRjrq4lENRE2vzHnuknAyeLxK000Fg8JJGg2qjhheOGDh3KgQMH2LJlC1999RW//PILo0aNKnPeyJEjOXv2rGNbsqSwsKHNZmPgwIGYzWa2bdvGunXrWLt2LbNmzXJJNqGwXEFJroguX79QwkhBebH5uBYhJuVqUTUlH0scX7zjtEBQ2zAb7d54iwoKcOJUEyKanSWi2VnPCiaocmqyheXQoUNs3ryZd955hx49etCrVy9effVVNm7cyJkzZ64618fHh7CwMMcWEFCYVPLdd99x8OBBPvjgAzp37swdd9zBvHnzeP311zGbzeWWr14qLFd2di2Lgs7B9Y3wt51Lf0e8Gkf4qqXc/evY8s1ftZSI15aR8n+Tyx5clEALyc8IxURQd9F72U3h0c3PIpxAgoqSlZXltJlMpkqtt337doKCgujWrZtjX58+fZBlmZ07r14faP369TRs2JAOHTowffp08vLynNbt2LEjoaGFHox+/fqRlZXFgQMHyi1f/Qy6tUqelqDGE7lhAWg0RH24ACVdj+pnBT8JKVfDmZzypWOHhV8kx2hw+dwF7i+BoK5yZHChKfwaYVWpX7gjy+fy/ObNmzvtnj17NnPmzKnwsqmpqTRu3Nhpn1arpUGDBqSmppY67+GHHyY8PJymTZvy999/M3XqVI4cOcJnn33mWLeosgI43l9t3SuplwpLQOjVA4jqAgVWJEmnkPzIdJfnJz38POHrFqFc0qPqVLDINGyaSU6+gZz88ikhqSkhLp834tU4YV0RCAR1FneW5j916pST68VgKPm7edq0aSxefHXPwqFDhyosT9EYl44dO9KkSRN69+7NiRMniI6OrvC6V1IvFRa91uZpEaocSaMiaRSkSjj9GjXOwmjRYrVqMOisXDgVhGSTyl0+XzbKKHoX41dCrm7SjIqPI3GCUGgEAoEgICDASWEpjYkTJ/L4449fdUxUVBRhYWGcO3fOab/VaiU9PZ2wsLByy9WjRw8Ajh8/TnR0NGFhYezatctpTFpaGoBL69bLGJaEAXU/JsU/KA9ff2OlCqH9eccCGvjkk3/Rm4xUf2SjDCpIVonwd5c4Uo8j3lxW4nypsRE05VNuIt63rxUUmAtAh00lR48LZUVQ1zgpqtvWLzyQJdSoUSNiYmKuuun1emJjY8nIyCAhIcEx94cffkBRFIcSUh727NkDQJMm9r/t2NhY9u3b56QMbdmyhYCAANq1a1fudeulwlIf2Hf3XPaXo0li+MqltPpkHuGrFxO+srDIW4ECkXKqId4h+WiytCjeCqqXgupjt1CpOVrCVy1F1SmlKi2oktO6paEa7WlBeUYDkRsWsP/uuUS8XsqaAkEdooWIYalX1OQsobZt29K/f39GjhzJrl27+P333xk7dixDhgyhadOmAJw+fZqYmBiHxeTEiRPMmzePhIQEkpOT2bRpE48++ig333wz115rb+jZt29f2rVrx7Bhw9i7dy/ffvstM2bMYMyYMaW6sUpCKCx1jJYfz3NpfMroyaiKRMoTU9FmO+cSR22cj6RVyM/wQm6Wh+xnQdIpaLxteAUZ8QnNRfKykfLkFJKfmlRs7cQhLyBZJEc35NKI3LAAyduuBEU3uoCaaa/Bkjym+JoCgUAgqDrWr19PTEwMvXv3ZsCAAfTq1YtVq1Y5jlssFo4cOeLIAtLr9Xz//ff07duXmJgYJk6cyODBg/nyyy8dczQaDV999RUajYbY2FgeeeQRHn30UebOLftHdVFcUlgiIiKKVbOTJIkxY8YAYDQaGTNmDCEhIfj5+TF48GCHn6qA8lS7++mnn7juuuswGAy0bNmStWvXunRR9ZnjD8x0eY4lz55YafNSiYq3F2ZT87T4+pjslg+rDJJK0sPPo9oklEt6jNkG8rK8ylT15QZmJB/rVa0svn5G1Bx7ONW5XL8SlR+BoCq4ZeskBv3+lKfFENQnangvoQYNGrBhwways7PJzMxk9erV+Pn5OY5HRESgqir/+te/AHum0s8//8zFixcxGo0cO3aMJUuWFIutCQ8P55tvviEvL4/z58+zbNkytFrXwmhdUlj++OMPp0p2W7ZsAeD+++8HYPz48Xz55Zd88skn/Pzzz5w5c4ZBgwY55pen2l1SUhIDBw7k1ltvZc+ePYwbN44nn3ySb7/91qULcwVX67LUFiJfKV9V2JThUwlftwhkFclWaA7JzTOQMnIKSCo262Xri6yi+tjQpGvRXNRBRskVaQtQLDKqRXZa90r23z2XlNH2Wi1/3iG6JQuqj597L+OzG9/0tBiCekRNdgnVdFxSWBo1auRUye6rr74iOjqaW265hczMTN59913i4+O57bbb6Nq1K2vWrGHbtm3s2LEDKF+1u5UrVxIZGUlcXBxt27Zl7Nix3HfffSxfvtz9V3+Z2tRUsCQ6f2Xv+nxln6Gk58ofoNox6jSqTkUxqPbYEQlspstKiio5NPqgBrloDDZsfgqKtwqBFiLXLyi1K7N/UB6tI1PRh+aVeLwo0cviyy2vQCAQCOoXFY5hMZvNfPDBBzzxxBNIkkRCQgIWi4U+ffo4xsTExNCiRQu2b98OlK/a3fbt253WKBhTsEZpmEymYlX/6gt77nwJqFifoVYL44lcEcf+pGvQ5MpINlA1KhhsyJk6Om6aBZKKkmN3GymqhI+vEcnbaq8pnquF8wa0GXblZuKeBxxrh7+zhKwz/hw/0wjTJa8yZVGLZBRFvHb1gNvwt8oO5BUIBIIah6K6Z6uHVFhh+eKLL8jIyHDkdqempqLX6wkKCnIaFxoa6qhkV55qd6WNycrKIj8/v1R5Fi5cSGBgoGO7sgJgbSHizWW0WhDPiD8eJ3zdIkeTtKogelk8x6ZPQDEo9tgUvf1DIFklUh6bRtKzEwvdQjqF1p/OZd/dc1EUGY1OQdWpqBoVSQVrgI2WH88j11YY8a3J1KLJt/+JSUYNEW+UkfWjSES+HMfwXcNR9Vf/QLpc7l8gEAhqAjU8hqUmU+HCce+++y533HGHI9XJ00yfPp0JEyY43mdlZdU6pSXig4XgK6Fk6zmVG8Q1TS6xrW/VxddILew1T658+N+3rbAteEHkiXeQEflywbi8bANNQzPQNlRIOR2CTVLR5GiwnfUhJ7wwpkW2gtXHvobqY0OTVUpHw8skTiz8/6N7xa9LIBAIaioSbqh06xZJah8VsrCkpKTw/fff8+STTzr2hYWFYTabycjIcBqblpbmqGQXFhZWLGvoymp3pY0JCAjA29u7VJkMBoOj6l95q//VNFSTBllvQ2lm5Lt/vVxlykrEe4sAaN4wg9afFrfg/LG/sJTyiSH2TtX5F705eO8c+84cHecy/NDIir27tWL/+CjeCtE+FwoXkkCXJeHrb0TO1dTaXwWR6xcQ9aEIBhYIahLtp1ZdXKOgZlIhhWXNmjU0btyYgQMHOvZ17doVnU7H1q1bHfuOHDnCyZMniY2NBcpX7S42NtZpjYIxBWvUaWwSjYKzUYxXt0SUl7afzylxf0FzwR9vi+PofcUrymqzNLR+qTAA9u5fx9rdQgUooNGonLkUCEBoeDqJ4yeSMmoyL3b8r2PY8SkTkBTJXsDOtQr9NYqkoc+jpF89G0ogEFQvBxaP97QIFcMDlW7rCi4rLIqisGbNGh577DGnHOrAwEBGjBjBhAkT+PHHH0lISGD48OHExsZyww03AOWrdjd69GgSExOZMmUKhw8f5o033uDjjz9m/Pha+sfpAimjJqOqElJ+yQpLqdVkS+HQv+e4LEPEa8uwhlg4OqPQPbPpptecBykSxgveWJLtufm7+i8sdb2jM+3/b0njJtaqsvrh7y5x3uFvLXmgQCAQuIBIa644Liss33//PSdPnuSJJ54odmz58uXceeedDB48mJtvvpmwsDBHe2koX7W7yMhIvv76a7Zs2UKnTp2Ii4vjnXfeoV+/fhW8xNrFrv4LS63wWlJBtVt/cK8SkDx2klOa95DthV045+6/CwDVy4Zkk9Dm1V1PasqIKU7vC6xSAkFdoOcDou2FoPYhqWrdtC1lZWURGBhIZmZmrYxnKS+Rr8S5VG+lMoSvW2SPWanjRG+c74jdEQjqGv1Dn8bSrhlbf6x4Y9S6SFU/MwrW73XrHLTasss8XA2r1chvP86p88+3KxG9hGo51aWsAGUqK6MThlWTJFWLUFYErvLJ8a4ArD1a82PtNqe9IZQVDyKpqlu2+ohQWGo44W8vKXtQDWFl1/cdrx/bVdxlKBDUVbxkM3tONqe94YynRREI6ixCYanpqBIRHyyk/X9ne1qScnP3r2OJ8U31tBgVRjTDE7jC6qM3EqbJwqhquD48xdPiCGo6ipu2eohQWGog4asXE7neXvcjZdRkVIuMyWTPyIr4wDkjJ+KDhU6BsTUBqypzODfMY+cvKNsfvnqxw0IVvm5RuedXRTO88NV1s8FmfefLxI4EafL4Iz+SG8KTPS2OoBYgXEIVRygsNZCUJ6aSNLTQx5wyfCrHH5gJgHpFjZbkR6az40RktcpXQOTLJXeDjvBNJy3fv5qlKUQ22v+svQJNHpPhSlKeqN0NNgUlY1G1/JQVw9MxP3laFIGgziMUllpGypOF6bYRr9oVBq2+sEZIz++mFot7iXhjGZEr4hyvw99Z4nhfGXyjMoleFk/4SudGhEeyGpN4PqTS61eE8DWLUS7XTDFm2fsgRby3CCmv/F0oCu6roH7R+8cJZQ+6gkHRu1nR5cMqkEZQZxG9hCqMUFhqMbLF/m+B9QVgW9/FSF42p3GqrKJqVSJeX4aqV5BMMpKl8jVU9t89F2uIhZTRzr2Itt4aX2IF3aqk/X9nE/XhAqRcDUiXg5ULPtSSWmINm6IUfVhJ9dQ/XN+ZE/lfvkzsyF8pLVh99MZix79M7Oh4vfDAgOoUTVCXEJVuK0yFmx8KPE9plWO1+kKF5Zatk9CHBKKk+GINsSDlalB9bQRGXCrXOaKXxHNiSum/PIsWmatuWn70EqoqodgkdAYNikVG9VKQ8jUkP21XUCI3LCB5WNkpnFtvLWxFUJ2p4gLP8ENSGzIUH3wkE16yBT02fCUrGjkXGxLXeZ1k38lmdGzxDwCbE9txV9RBAPr+NI4jibfw9rdxtap6s6Bm4I5KtfW10q1QWOoglkx7m4OWi+OxBIcS2iKdtGADyCqqwf5Az8j0LddaV1NWIl+OI2mc576wZY2CJAE6MBu1qDYJrBJyfqHhMOlhUW9CUByzqsGmymhkBUWVyVJ1IBuRJQUbEkZFj1HVcSqxA1mKF9uyO9EfiNo4n8QhL8O/PHwBAkE9RLiEajEdNs2iw6birhfd5WDT41MnkDJqMhcy/GjYJBOtwYZkkVH1Ckpu5XTViDeWIV/hVnIlE8cdmPP0eOkt2KwyqiKh87GARkVulufSOrUpZVxQcbYkxTi9v79lArdHHua2yCMAnLYGc8wcxvfZHXgz9TYmH7iPsTsfZkjLP9n0WzciX4lDTa1chVKBQLiEKo6wsNRSwtcuRpJ98PY3Xv7V51ydNSounsSJduuIYpFJGDCfHt9O49w5LySzxh7T8t6iCvfI0WbJHJ/mbH0pGtj62K4n+Cc3yMnV4m5Um0SeUY/NKiPrFGxWGTQq17U45dI6B+55sYokFNQkbo887Hjd/7J7p+j72O+mcuZ0A6R8DZJFcnINJj8jXD8C9yAplY+Tq69xdkJhqcFEvhyH4mcDjVosVsQnMJ+8c75YvDR4e5udlJbjD85wGps8bDoAl7J9SHp2IpEvxyFZJbikK3bOVp/M49j9M4vvnx/PsRcKFRT1iobSkSvinP6atJLC6UuBLl2vK0RvnI+kk9HpbCXKKxC4SuqhxmhspceGCQQCzyIUlhpIxJvLkMx2d4tklFH1KuHvLEH2tqJe0iMFm1FyfZEUCZ3OhiSpBPjll7luQeaOV3g2h/49h4g3l9mVFxUUvYrqpdAm+mKxeW3mLkfxtr8OX7kUTZ6MqrNn4qSMtKdZq7KKJrfQw7j1cBu8fM2VvRWlUtDvp81/5pYx0k5RWQWCkpBNknCSC6oed7h06qlLSHw8ayJWCcmG/X9HlezWEI2KYtFAgBWNzoZkllA1Kof+PQcJ2HPnS05LdPqydKtDsK9duVElFckmoUogWSRkLyuqWjzd+cis8ZyYPIHIDQuQfK0kTphI0riJTgpA8thJqJf/msJXLkU+r+fwoNnEfle1WURHBpcvfbo6lZXwd2tP/ydBISemTECV6+eDQFCNiDosFUYoLDUQv/BMkAAFVB8bqv6yw1JSkbQK8hVfqvvuLm5l2HvXPCLeX1hsP9hrtdiXkxz+1KRxE/H2NXMyPbhUuWRZhRIUmgIKYmZkf4vDrB7sVbblp7bS+tOSrTspI4Qlp7Yi2Spfn0ggEFQNQmGpYUS8uYzc5ECUhmZU3eWEfZ0CNgmN3q6s6PVWvJrmgqZkNbugb41qvfp/b1DzDKwNLXYLDpCX5UWrxudLHW/N14KkEv7WUsLXlNwbJ3zdIlTFvt4tWyehXEXBqe1YzMKjWtdQxTeioIoRvYQqjvh41jCSn5oECui8rCCDZNSASQM6hcSHnufEkBfYf/dc8rMNyN5Wp7mRr8TR9ZsXSHliKuHvLCmzqJtGVglvfgFriJWI9xahWiW+uunVYuOi4u2l6mW9Df/AfLSBZjRXnBug46ZZ6LwtSLJKy49e4ufeyzie1rBUS08Bz+5+iMl77y/r1lQ53f7nWs0Wrc5W9iBBrSF6WWFmnUBQZYi05gojFJYaiOKlYPvHxx6nolXtpfavsFSkPDbNURSt6zcvEL7K3s9Hufx3XLTnUGlcyvTllz5LSRkxBUmjwGXLSPfN053GaVvk0uY/cwkKygXsAa82o5beP05wGrvv7rkcf2Amfv7GwkwlVaJpaEaJ55+97x5m7rsXH9mMppr7pbf6ZF6xfX/escClNUR2Ut3ixCShrAgENRmhsNRAUkZPJnH8RAzNc0BSUc1X/29KGDCflFGTUbUq6WfKTiWOeH0Z4auWYitSPK5l0/P2HjyrF3P+or9DEem4aRa+3iYsFnses02xy9I+6jRbb43HbNUUW7+hn12xeXb3QyiKTFTghWJjxv71MD4aEwbJip/GRKC2emNdhLIhELiHjhOWe1qE2oUKKJXc6qeBRSgsNZnDg2aTMnIKKU9OIeXxsrNtksdMKlc2TPKYSWgCzEiXg3nbfj6HtkGpBDTKIeWJqXDe4FBMbIrM7oH2Gi/tG6YCEPHBQg4cbg4Uz04CyDXrAThn9EfW2Lhg9Cs25rXrNnDOHICChNflLo4j/ni8TNndSfi6RSVWChYIBOVnX/x4T4tQqxAxLBVHKCz1FFueFlmnEPHaMvJzDBzIaOLINlIbmkkYMN/+usjnIjkrBI2sIF3RvavvT+Oc1s7M9ab75ukkZoaAKpFvLV6gDqCJPpMTeY3QSTYCNXnIJZRvbPfFHKf3Xb95odiYihDx/kK8/Mzk5XqVmu0jEAgEbkfFDTEsnr4IzyAUlvqKVcaWrYMgu3VDvvwJ6L55Oq2uOecYdujfc2j5sT3e47fblxDmn01IgxwaXpPpGGOyOWfLhPjnYrZqMFs1qKpERp53iSI0019kXffVnDQ1IN3qR0pOA27/0fnX2sF75xC5vjC2pEPDs5W46EIKqv8mPvS8o6CeQCAQCGouQmGpR3T+yh4IG7U8DtnXgi7QREiDHBo3yiI934dHdo5gWMROvLUWp3nHHyiM99hy63L6ND3isMAA/Nx7mdN4b50Fs1WLXmtDUSRHTAvYY2IK+DjtegDiOn/MX5nNae6bQY5FX0zupKHP0//n5wA4f9m9NPavhyt0D4pivNzVWiAQCKoNkSVUYYTCUo/IPBFM+KqlqBrQaBWQVO5svp+mfplEBl3kgx7v8kzMD1zI9y1xfkGMyaJO/wFwKBGAk2Uk5XwwQT75DIvYiWLWkHi2IWAP6PUxmOn81Qzu2zaaz2580zHnsxvf5N3r17K9b8n1XWRJ5b5tozHZtIxOGEaILpdlB/tV6n6kPFH+KrxRG+e7RUkSCAT1nMoG3BZs9RChsNQjVJ2KT6NcFF8blnwd/r5GTuY3ILZBIp/2XOkYV1AJt9OXM7n1B3vF2i5fv8BFk49jTJevX8BHa2bingfo9r/nybfqmL3vHgAkCUxWLTszI0GF2KgkwK4g7Oy3iDD/bKfzlYez2f6czAom0+jFP3lB+GhMTGr3bbnnFxTTqyi2XB3/O9q+UmsIBAKBoOIIhaU+odhjUgoq5CqKTL5Nx9R2m0scvveuefx4m71o3O6B8/mi1xv02jKFLl+/QJ7RwLGLjYjr/DE6jY3fbl/Cix3/S68tU2gWkoHZquHAhTBkg40NN7ztLEYFqt9m53hz7kIATf2yOHCySakyl0TEq3Ho/CreiDHivUWkjJjiaLhYXsLfWlrhcwoEgrpJTc8SSk9PZ+jQoQQEBBAUFMSIESPIyckpdXxycjKSJJW4ffLJJ4XXXcLxjRs3uiSbUFjqEaqX3Y6Y8vhUWoensveueTTxsgfPdvna/jBu+VHxNOWi/Hb7EnYPnM+RwbMcWUWtg847HffVmTGadOQZS44ROXamscuyH39wBsmPTGdvYjOShrpWkTb5mYl4eVkqnGHUJOxSqcci3lxW6rFGLezz7vz1GQAm7nmgQucXCAR1iBoewzJ06FAOHDjAli1b+Oqrr/jll18YNWpUqeObN2/O2bNnnbYXX3wRPz8/7rjjDqexa9ascRp37733uiSbaIZSjyha/TbUJwuA5V0+ouOmWey72x5Ee03DDJfXXdd9tdP71Bx/VBU6NT3NgXNhRG2cj4+Pif13zyV81VJSRpWscAz45Vmsisx3/3q59Gt4bJrL8gHsL6FBZHkpLa4GQDKVbi2KaZDGs7sfIkjvw/jdD5JuKV6PRiAQCGoKhw4dYvPmzfzxxx9069YNgFdffZUBAwawbNkymjZtWmyORqMhLCzMad/nn3/OAw88gJ+f83deUFBQsbGuICws9ZQPerzreF202/OVGT+lUdAKoCT+vGMBXl4W9qc1QSsr2LL0ZJ/zI3xlyXPu/e1punz9AooqXVVZqYlIoSbAbqGK/W4qoxOG8diuJ3g64RGaeGWRb9NxXcBJrvdLop3fGQ9LK2g/TVRlrYl0HF+P/l/caGHJyspy2kwmU6VE2759O0FBQQ5lBaBPnz7IsszOnTvLtUZCQgJ79uxhxIgRxY6NGTOGhg0b0r17d1avXo3qoqXIJYXFZrMxc+ZMIiMj8fb2Jjo6mnnz5jmdVFVVZs2aRZMmTfD29qZPnz4cO3bMaZ3y+Mj+/vtvbrrpJry8vGjevDlLlixx6cIEVUvKqMlXPa6RVHLP+ZKV7Y1Po9zCQkclRLd/0esNooMvcj7XPRaIgrox1UFgQC6P7XqCm5om0sg7lyyLFzIqWtmGVZF5u9t7TGi7hf35zVyKuxFUDQcWiaqsNZF9y+vR/4sbFZbmzZsTGBjo2BYuvHqj2bJITU2lcWNnl71Wq6VBgwakpqaWa413332Xtm3b0rNnT6f9c+fO5eOPP2bLli0MHjyYp59+mldfLd5s92q45BJavHgxb775JuvWraN9+/b8+eefDB8+nMDAQJ599lkAlixZwooVK1i3bh2RkZHMnDmTfv36cfDgQby8vAC7j+zs2bNs2bIFi8XC8OHDGTVqFBs2bADsWmPfvn3p06cPK1euZN++fTzxxBMEBQVd1ZcmqDkE+eSTofVDVSTah6by6b8Ls4K6/e/5Yo0GP+250qlAnKtEvhyH2sBePyb50arvE7T66I2ct/rzQITMBYsfFlWDLCkE6fJ5o+sHxcYvuPazKpdJIBDUL06dOkVAQIDjvcFQctzgtGnTWLz46pmShw4dqrQ8+fn5bNiwgZkzi38HF93XpUsXcnNzWbp0qUN3KA8uKSzbtm3jnnvuYeDAgQBERETw4YcfsmvXLsBuXXn55ZeZMWMG99xjT3F97733CA0N5YsvvmDIkCHl8pGtX78es9nM6tWr0ev1tG/fnj179hAfHy8UllrCz72XEfPZi1itMn+dbA5FlO3SuiIrFg3haxcjySrJj5Y/ViV83SI0qg41S4sU7JwNFPH6MpLHTKrQNVyNXMWASdHhpzHipzHxYsf/uv0cgppDp2fsLou9r9YjS4CgalAA1xMli68BBAQEOCkspTFx4kQef/zxq46JiooiLCyMc+fOOe23Wq2kp6eXK/bk008/JS8vj0cffbTMsT169GDevHmYTKZSFa0rcckl1LNnT7Zu3crRo0cB2Lt3L7/99psjEjgpKYnU1FT69OnjmBMYGEiPHj3Yvn07UD4f2fbt27n55pvR6wurnvbr148jR45w6VLJGRsmk6mYP0/gWUIDswkLziaxnOnAKY9PRcrXuKSsAPgF5WMLsCEpUrEMIncrK8sO9iP+0O08E/MDszp8yYS2W/j4eJdyzS3ogF1AzGz7QzB6WbxbZRS4n72vjkdS6md1UYF78URac6NGjYiJibnqptfriY2NJSMjg4SEBMfcH374AUVR6NGjR5nneffdd7n77rtp1KhRmWP37NlDcHBwuZUVcFFhmTZtGkOGDCEmJgadTkeXLl0YN24cQ4cOBXD4uEJDQ53mhYaGOo6Vx0eWmppa4hpFz3ElCxcudPLlNW/e3JVLqxXUliZ9URvtGUc/917Gb7e7FnuU/JTrCkZOhjeSUUayuTzVZXSSjQlttzjtO/TvOU7vn054xOl95Ap7LZuL+xvRcnGhcmLzuvyl0yzf/YIK3M6e1yd4WgRBXaAGpzW3bduW/v37M3LkSHbt2sXvv//O2LFjGTJkiCND6PTp08TExDg8KwUcP36cX375hSeffLLYul9++SXvvPMO+/fv5/jx47z55pssWLCAZ555xiX5XFJYPv74Y9avX8+GDRv466+/WLduHcuWLWPdunUunbQqmD59OpmZmY7t1KlTnhbJ7RQ06WvzH7viEr6mctVbq4ryWlRKI3yta9eV8tg0ksdMQtFV3S/gnt9NZdDvT2G7ii134p4HGPT7U44Yllbz7cpJ0rP2asGqBDaDXcbwNYs5Nt3+AHS1IJ1AIBBUFevXrycmJobevXszYMAAevXqxapVqxzHLRYLR44cIS8vz2ne6tWradasGX379i22pk6n4/XXXyc2NpbOnTvz1ltvER8fz+zZs12SzaUYlsmTJzusLAAdO3YkJSWFhQsX8thjjzl8XGlpaTRp0sQxLy0tjc6dOwOUy0cWFhZGWlqa05iC96X50QwGg0umpdrMkcF2xSVlePl74dRUwtcupm+HA7zd7T3HvpTHK3ZdyWPd5/6ZvPd+TuQ05LMb3+T5vwfRzL8RMirtDKd55VAfnmv7fbE5n+68Hm22Bm6ElovikWSIio8jcYJdYbFbgOwKj6QrfzOQ94/dwLBWO5z2Ra6IQ5XVYtcc+XIcSJD03ETXLlggEFQPigpSJX9cVaF7skGDBo4EmJKIiIgoMR15wYIFLFhQcnxi//796d+/f6Vlc8nCkpeXhyw7T9FoNCiK/cs3MjKSsLAwtm7d6jielZXFzp07iY2NBSiXjyw2NpZffvkFi6Wwa/CWLVto06YNwcHBLl5i1RH14QKiNs6n/X9nX7UuiaB0Uh6f6qSsuGo1Kqsyb0X5/p/WHLto98PqJBvNvS/RLTCFRHNj0q2FzSEL3F8AhvMaJAWil8RzfNoEjk2fgCpD5CtxRMXFo+hVpAI95VJhfNaQ7fZA8lcO2WO/4g/d7jgWuSKumLIStTwOyQayubi1R1JAtlQ2ok8gEFQZNdglVNNxSWG56667mD9/Pl9//TXJycl8/vnnxMfH8+9//xuw9woYN24cL730Eps2bWLfvn08+uijNG3a1FGCtzw+socffhi9Xs+IESM4cOAAH330Ea+88goTJnjeh9z28zlEvLmMVp/MQ7FK+PsaadsoDTlfJvzdJTUqzqTow7S2UJLVqKTraPv5HMBesr8qyM71wsdgzzjSSAqtvNOY1O5b9uc244MD3R3jCtxfLRfFY9PD8SkTODGl8O9UUuyWFckGslVC1ar2OJagwmym/iH7eGzXEw6rTdEYmQJ3UlESx08EFYflpiiSVUKyQsslIpBXIBDULVxyCb366qvMnDmTp59+mnPnztG0aVP+7//+j1mzZjnGTJkyhdzcXEaNGkVGRga9evVi8+bNjhosYPeRjR07lt69eyPLMoMHD2bFihWO44GBgXz33XeMGTOGrl270rBhQ2bNmuXRlOau37xAdp4BjQZUbxsWkxbVIrP3LnuRsojdy0gZMaWMVaqXysaSVBetPpnHsftLr51iM2mK7bsy0PVqjPjjcd69fi1PJzxSYo2Ukrin9T5Hk8ZZNRn5jAAAHLhJREFUHb507N/8c5cSFQVFB4kTiyvUmnwJRQ8npkwg4rVl+LfIYlDkXsINF2j/XyOypLLv7u08fhVZopfEOylBULKyAvbzxMxejiKabggENRR3WEjqp4XFpa81f39/Xn75ZV5++eVSx0iSxNy5c5k7t3RLQ1k+MoBrr72WX3/91RXxSiVy/QIkjVqhB3j4O0tIeXIKjXxzSBgwn5Yfz0PK1aD6gOxVmJZSFbU+6jrdN09nV/+FmLNKjz2KeG9RhfsHDdk+ioaGHGTJ/mdemrISf+j2Ypk/cZ0/LjYuekk8iVNKVhQUn5JjUo69MIHwt+2ZUrP6fk62zZuVh3uRl+GNnK0t0YJyJa66uw+/OJ42L9ajUucCQW3CHS6deuoSqvO/w/psnUXS0JcBe7+X9PMBVw3qjHjjci8dm0TDlheRTA2IeHMZhsYhALRrksYJQwjGfL3I7qgE4WsXk/K4vYx0UcvUldYWKV1X7jVn77sHnWTjRF4jLKrMxth3GfvXw04xMgWM/ethGuuzybPpucHvHIsP9i+1dH70Urt7RS0hCyn87SWkjJxy1XTslJH263ui9e8APNe23JcE2N1KLRfZ42LKy5HZosCZQCCoW9R5heX73oWWnt0D7bEQ4e8sQR9ocjwY+//8HIdPhkGmDlQJSXWOHWj50Ut4X45n2HeqKUkPl9xtWFB+tF7WEvdf6RpKGle2BeLtIzexOyecDEtjDLJ93YLmjq9dV9ySN3nv/YTozPjIZgyyhY3nerAxdlWxcQWoGpXECRMd9VSKUqCMFKXL1y84/tbcwbHpE2i1IJ5W8+M59oLn47gEAkElUFQq7dKpp0UM62W3Zp2/2enBeCi5CcnDppM8dhKyWUINsjiNP/7gDPbc+RKR6xdUqbJy56/ORXRGJwxzaX7HTbOc3reZU3PdApWxTt3961hGJwxjyPZRDPr9KUa2+ZU3un6AWdGwpvsa1nRfU2zOY7uecLy+YPLjktWHSe2+ZWq7zez4s81Vz1cQL1KW++bWH+zH3amsOHBDJqRAIKgBqIp7tnpIvVRYQoKcO0MHBBcWwJGb55ZaGv7Ksu/u4pGdI+jx7TS6BNmL3X12ogt7TjZnTKMfXVrH9HeQ03tzsELrl6omWyR81VLu2zba0bCw05czidxQ8eaF5WXI9lFE+51HRmVj7Co+u/FNx7FPe64sNv72H8fzdMIj5Fr1TNs7GIA13dewosuHjjHaXMnh9ikPRbtBR8XHEfGB3bWVdLqhy9dTXlSNfSsoRicQCAT1jXqpsBjNOvr+NM7xXi7y01Wnq4b67lfwQY936dE4hRO59rofg6J34yXZrlpVtSht5totKZLNebzGVHX1OMLCL/Jpz5UkDX2e1p/OJTvXi6SHny+zjkp0JVOt86x60i2+yFL5fmFsuXU5JkWL0abjYFaTEsccnzaBE5NdcLWohffVFmxFzbN7VpOHTS9tRqWRrfb6KrJNou2M5bR9oXqsZ9c+t5yOE2qupU4gqHWIOiwVpl4qLBkX/PjuXy8T+509+LYgNRlcS5d1hfB3Su6p82ViRwBWdPmQBxoV9maIaX6Gzi1O8VdKizLXthlUWn70UvFAS9VuZakKdvZb5HhtyjFgy7YHx0raks8Xtdwe/+HtY3L5XLHfTeWWrZOI/W4q2RYD/loj50z+5Z7/7vVr+eqmVzl2ofIWkPCVS7FkFmY1pQyfSsqoyZVetyyOzpiAZMG+KXBofvUE1RbUkAHoOFEoLgJBpVFU92z1kHqpsBQUJ9vet/p68aQ8WXKNlhA51/H6Gm1GsePlsbKoMlhy9CUek4LNJe53JymPT3UEn5ZmZUgcb4/vCPCyKyzd/ld+95qfzoyqSjT3z8CgsaKTbHwc+xZgz/YpYOWRW666jjuUUUmRkPM987E5PG88GgscXFB9GUBOXWHr53ekQOBehIWlwtRLhQVce2BWJT0jEh0PWl0Jbg4fycqek1fvPH1i8gQko/2/MuLVwkyW41Mn1LiMJrPNXgQuJ798fZ8iV8ThqzOh09iVlM23vIJFta8xd/9dWNXConKj2/zsfoGBiDeXEfHGMiJXxCFZJI/26TmwqPqUlev+Lx7JBhqz/ctxX/x4ujwlYmgEAoFnqLcKy593VH2AaHkJu2xZ6dzCucP0npPNad/idLH9JSFd7h+jy7m6RcadsQ+RLxdP8y3KvpPNiu1rEXCJqA8XYDaXL6M+6dmJxPin0bNhomNfiC6X94/dgEG2sLLr+07jI15bVq51y0PE68uIeDUOySwhmySoZ4H5qmSPndEU8eLtflOkVQsElULFDRYWT1+EZ6jzdVhqAztyWrLgctXXopRHUSlAY5SIiotHluxWidJScN0Z+1BWjZSOLf4ptu+zG98kMmUBN0efKPd5ZEkl1RQA2FO9V3b9b6ljK+sCi9o4H+W8l733z+Xg2oIy9/WlA3LXJ+NJeGcCWiNISpGGjQKBoPKISrcVpt5aWGoSAwP3sKZd8WqsrnB82gQUb4Xj0yagNqj6uJWyuFqwcNLDz3PJ5FOudeIP3c6Caz8jJacBQDGLSrG1XUw9/+xEF1YeuYXwdYuIeH0ZapoXsvVyzRPVbmWQ1PqjrIA9fbrriMuun8v34LqR9vfXPicCbwUCgWcQFpYagK9kQUFiW3IUPSPsro8vTnTi3ui9V53XdsZyDr1UaDFJftpeHj75kbLTayPXL6iyujIA14WfvOrxsjJ23j92A3tyW+CnsSs23/3rZdr8Zy5HBs+66rzyEvXhAmRZQZIHYUnzRrZJSFa7dqJqAKnsQnF1FUULGiv2YnWKXWEzB0lc93/x+GSrdHp2OXtXiNL/NZX205aDAgeWiP+jGomiUGn/slI/zZ5CYakBGFUtBsk53Vcph/GrqLLiKtoUr7IHVRHtvphDfo6BqI3zSRzyAi0/eonjD84AYOSfj/J2t/f44VLbYhVrjRe8nd6Hr16M9oIOVVNyp+SSmLv/Ltbui8WWo0XNuxywK2NXVii9C3J9QjaDqr1cUFO2pzV7n1ORbSo2vYT/KSs3D1zCL1/XrO7kAjuqDAerMThb4CLCJVRhhMJSAwiUTbRvcZr3j91Az8v7vrzYmbVnxrLpptcqvG5UfBw0MZH40PNO+2x+CinPV33tkNI4eO8cIj5YSIPAXPr+NI4bIrIdxwoaFZZUXj/l/5xl1mRqkS2gzZRouTgeS4gVOU9TomVk2cF+fPZPZ04n3oxklRzJ4pINFG+FxGc8dz9qAjffuQRFJ6FoJfRaCUUHZn8JbZ6EpKpoLKrdPaao/Pb5ZDpMFq6hmkjMzOWgKXucQFAbEQpLDcBy2ZoyrNUOx7413dew+uiNlVq3JGtB4oSJtFzi+dTUkAY5ZGR70/eaw/x+Psrl+a0WxCNpJVQtKHqQzRLadC2KXiV643xODHmBpxMewSBb+D0tirR/eiPnadBYJFStiqpXUbQKKaPrt6ICcNM9S9FYVXLDtPictyEpINvsGUK5YTKyWUK2qtgMEuYg+xzZctUlBVVMzMzlHJ5XghVFpt5mkNQahIWlwgiFpQZw2BxK5xL2f3X+Wp5o7f7zHZ/i+dRUX72ZbNnAgms/c2lezOzl2LxUZLOExgRWH3uK39GZ9i/vbv97nudb/48RfxwjOacxxxPDkLM1aBR70TcArJ6tpVKTiB0Sh96soGgk9NkK6mVPpGy1ZwdZfEHyAdkqIZvsAbkA2vz6+YVZY7jCY+xodCrZt5jZ9veHXxxP2xeWV1tlZEE5EN2aK4zIEqoBDGn5J1+c6MSOlAjHvog3lqGXq7+vUVlEvOGeOifnsvwwZbgeR2P1Vjk2fQJH5oxHlezF8UwhhQFowyJ2Mf/IAN69fi1Je65BztUgWyUkRULRqpyYNKHc8S71gdxQGYu/BiTsbh+NZH/oXf5O1ZhAm2cPxPU5r+B1Hjo9u5y/3qpf97AgS6q6iZlVsuvt8ItXKCASHJkz3vGvKuNQPhVdFQspEFQTQmGpIVyZEZT89CQ2xq5y2/q3bJ3k9D581dIKrVOQiQSVa2R4eNDsUtsVXI3j0woflOYGdkXl5QGFKeHxv/YjYYBdrsTxE0l6diInJk3gxKQJZdaNqS90fjqebsPj6fFIHJIKilZC0UmosuR4yCHZrSxBJ2wEHbfic1bF+5wFqy/1LkOoy+h4ZJv9vlUHBUpKzOzlTtYShxWlBIr1ESu6TyqcGzNzOe2mi/gjT6Kqilu2+ohQWGoQN4Qnl3osupJxJz/3draMaLIrH5l3YsgL5R4b8br7KtAWKFvv3rWKbclRBMhG+v/8HBGvxnmsz09tYs8bE5AU0JhUNJddO6pGKtqE+nJKswoS6LMtNP75LLJNrdbWADUFSQVjA4k9b1TeqtT2heW0nVGoMMTMLEF5uPz/oEqFW9H9bV4sh+JyeWzMrOUcmT3ebn0BtEY4uLD+/R/WKFQ3ND6spzEs4tu9luDuaqPV7RZJHmO3zLRcXKh4Rby/sLThTkS+4twC4LmbvuOPlHDCtVlsyuzC8B+f4PDB5qBRKUevSAFg87IrKYZsFbNfEctKwfegBKYADZkRGrKbGVDTL6E/dclT4nqUv96agOqmaD9VxkkxPDxvvMOCUnQMFLp4kKDN3MIxJVlTSqLN3OUcnus8dv9Soax4HNH8sMIIhaWWUNQVUlFafzrXDZJUDtksEb7SbiGRL5TcYfpKrgyQndB2C8fMoQw79Cgf/9ATbboOySKR/PSkelvszVX+emsCxmAJk7+ExgyK5rLSUvCrXrY/VTUmMAXJoKhsPrrEs0J7ENniJpfQZQWkKKrk7O4pppAUsbAUVVxazyvdUuNkmREI6ghCYalHHL3PPVViK4PVT0EfYgTAFmSt8DoPt9rFtr6LSRxvj1Gpb40J3YEq21PCrV5g9ZawGaRCxUUFrVHF6g02A2T1betpcT2KKoGic4MGUERhiZm9vNS4FIdiUoJyU1RRcYy94pv86MzxHJ05ntYvlaxkXc2tJKhiFMU9Wz1EKCyCKqdoZpHNV+HY/TMBSBk+FYAuX5ccCzPij8cB2JIUU+Y5RECt6+x5fQJ7Xp+AopXIbyRh9rMXjFM1ElYvCWOQDDIEJVrZ9vGkshesw6gy/P2K6+6UK7N8ilo+1ALlpcDt8+Jy2sxd7lBIWs9bXiyOpSB9v0ARaT1vOaqsOhp0FpNbokSlpbxuJUEVIFxCFUYoLPWQqA8XVOv5imYWSd7FrSrp5wPo/WNxl9fMJt8y4Jdn+Ty9W5XKV99RtfbUZauP3cJiNUhojSr6HIWAJBuKtn77FjpMXm5vhlkRity6K2NVnNxDV7iKCgNtVcdWVGk5OmOCQ3lBlQpfX6bAQnPshQkcnVG/UtAFdRehsNRDipbqr2q6b3ZuxOgbYHS8jvnsRQCkfA2B+vxicyOaneWbm1fw7Q/XVa2Q9RxJAV2OiqSCxddeh0XRSWgsKpnRGvIbyLR9of66EPYvHY9cgQboMbOWc/jFwqDags7fYI9ZOTJ7fOn1wwoGXmFiudId5FBoruDIrOIWlAIlps2Ly0ut7yKoelRFcctWHxEKi6DKCH9nCeeP2rsyF6Rlmw4HOo4fHjQbAK/QXA6dCwXg3t+eLrbOicniF2JVsnfFeIwhEihgDrTHrCga0GXZ8Lqo4n/aStBxGz2GxpW9WB1FtrhuYinI0CmwjBQUOyxqTTkye3yxNGanSeBkZSlQTgrcPK4E10rWwnNemT0kqEaES6jCCIWlltH6pfga0QuoXMgqisH+S+DElAlExcVzfGpx5ePwoNkc+vccAL7o9UZ1Sii4zP5l49m3fDyH5o/HHGBvgqjoZbzSFSw+MqZAmbzG9ffrQnXRLVbUglFQAwWwf+NeVlgKrCVXKhxHZ44vdAPJqpORRZXsfbSurM3SakE8rRZc/XtBVLwV1HbqbC8h9bIGmpWV5WFJSqf9B8s58EjxXzodV77KvtHPFNvf4Z0V4AOqrNLi7dnsf7BmBJp2fONV9j1dXF4lz4Sktzn+D3ybny32//H20QGMbP1NtcgpKB/bXxhB7JTXUf0VbLrLwbh6kCw1+/NUVdzw/Ouglv/ar1v4On9NH0PL6Qv5a/oYp2NWk5HdU8fQZfHrIKlEz7ginkyyn8dmMhbbfyXRsxYUtlG4/G/07AXsnjiWLnGvsXviWAC6LLvc8d2Fa6iPFNwbtaqtF0rJbjyXqKcWFkmt8v8dz5CYmEh0dLSnxRAIBAJBLeLUqVM0a9bM7etmZWURGBjIbfr70UqVM3dZVQs/mD8hMzOTgIAAN0lY86mzFpYGDRoAcPLkSQIDA8sYLbiSrKwsmjdvzqlTp+rVB8JdiPtXOcT9qxzi/rmOqqpkZ2fTtGlTT4siKIU6q7DIst3fHhgYKD6wlSAgIEDcv0og7l/lEPevcoj75xrV8eNWVVTUSrqE6qhjpEzqrMIiEAgEAkGNQ1WodGnuetqtWSgsAoFAIBBUE8LCUnHqbJ6iwWBg9uzZGAwGT4tSKxH3r3KI+1c5xP2rHOL+CeoidTZLSCAQCASCmkJBllAvBqClkllCWPiNb0SWkEAgEAgEAvei1+sJCwvjt1T31J0KCwtDr9e7Za3agrCwCAQCgUBQDRiNRszmCjSmKgG9Xo+Xl5db1qotCIVFIBAIBAJBjafOBt0KBAKBQCCoOwiFRSAQCAQCQY2nTiosr7/+OhEREXh5edGjRw927drlaZE8wsKFC7n++uvx9/encePG3HvvvRw5csRpjNFoZMyYMYSEhODn58fgwYNJS0tzGnPy5EkGDhyIj48PjRs3ZvLkyVitVqcxP/30E9dddx0Gg4GWLVuydu3aqr68amXRokVIksS4ceMc+8S9K5vTp0/zyCOPEBISgre3Nx07duTPP/90HFdVlVmzZtGkSRO8vb3p06cPx44dc1ojPT2doUOHEhAQQFBQECNGjCAnJ8dpzN9//81NN92El5cXzZs3Z8mSJdVyfVWJzWZj5syZREZG4u3tTXR0NPPmzXOqwSHun6BeodYxNm7cqOr1enX16tXqgQMH1JEjR6pBQUFqWlqap0Wrdvr166euWbNG3b9/v7pnzx51wIABaosWLdScnBzHmNGjR6vNmzdXt27dqv7555/qDTfcoPbs2dNx3Gq1qh06dFD79Omj7t69W/3mm2/Uhg0bqtOnT3eMSUxMVH18fNQJEyaoBw8eVF999VVVo9GomzdvrtbrrSp27dqlRkREqNdee6363HPPOfaLe3d10tPT1fDwcPXxxx9Xd+7cqSYmJqrffvutevz4cceYRYsWqYGBgeoXX3yh7t27V7377rvVyMhINT8/3zGmf//+aqdOndQdO3aov/76q9qyZUv1oYcechzPzMxUQ0ND1aFDh6r79+9XP/zwQ9Xb21t96623qvV63c38+fPVkJAQ9auvvlKTkpLUTz75RPXz81NfeeUVxxhx/wT1iTqnsHTv3l0dM2aM473NZlObNm2qLly40INS1QzOnTunAurPP/+sqqqqZmRkqDqdTv3kk08cYw4dOqQC6vbt21VVVdVvvvlGlWVZTU1NdYx588031YCAANVkMqmqqqpTpkxR27dv73SuBx98UO3Xr19VX1KVk52drbZq1UrdsmWLessttzgUFnHvymbq1Klqr169Sj2uKIoaFhamLl261LEvIyNDNRgM6ocffqiqqqoePHhQBdQ//vjDMeZ///ufKkmSevr0aVVVVfWNN95Qg4ODHfe04Nxt2rRx9yVVKwMHDlSfeOIJp32DBg1Shw4dqqqquH+C+kedcgmZzWYSEhLo06ePY58sy/Tp04ft27d7ULKaQWZmJlDYyTohIQGLxeJ0v2JiYmjRooXjfm3fvp2OHTsSGhrqGNOvXz+ysrI4cOCAY0zRNQrG1IV7PmbMGAYOHFjs+sS9K5tNmzbRrVs37r//fho3bkyXLl14++23HceTkpJITU11uv7AwEB69OjhdA+DgoLo1q2bY0yfPn2QZZmdO3c6xtx8881ONSn69evHkSNHuHTpUlVfZpXRs2dPtm7dytGjRwHYu3cvv/32G3fccQcg7p+g/lGnCsdduHABm83m9IAACA0N5fDhwx6SqmagKArjxo3jxhtvpEOHDgCkpqai1+sJCgpyGhsaGkpqaqpjTEn3s+DY1cZkZWWRn5+Pt7d3VVxSlbNx40b++usv/vjjj2LHxL0rm8TERN58800mTJjA888/zx9//MGzzz6LXq/nsccec9yDkq6/6P1p3Lix03GtVkuDBg2cxkRGRhZbo+BYcHBwlVxfVTNt2jSysrKIiYlBo9Fgs9mYP38+Q4cOBRD3T1DvqFMKi6B0xowZw/79+/ntt988LUqt4NSpUzz33HNs2bKl3hVncheKotCtWzcWLFgAQJcuXdi/fz8rV67kscce87B0NZ+PP/6Y9evXs2HDBtq3b8+ePXsYN24cTZs2FfdPUC+pUy6hhg0botFoimVqpKWlERYW5iGpPM/YsWP56quv+PHHH2nWrJljf1hYGGazmYyMDKfxRe9XWFhYifez4NjVxgQEBNRaC0FCQgLnzp3juuuuQ6vVotVq+fnnn1mxYgVarZbQ0FBx78qgSZMmtGvXzmlf27ZtOXnyJFB4D672eQ0LC+PcuXNOx61WK+np6S7d59rI5MmTmTZtGkOGDKFjx44MGzaM8ePHs3DhQkDcP0H9o04pLHq9nq5du7J161bHPkVR2Lp1K7GxsR6UzDOoqsrYsWP5/PPP+eGHH4qZfbt27YpOp3O6X0eOHOHkyZOO+xUbG8u+ffucvvS2bNlCQECA42EUGxvrtEbBmNp8z3v37s2+ffvYs2ePY+vWrRtDhw51vBb37urceOONxdLojx49Snh4OACRkZGEhYU5XX9WVhY7d+50uocZGRkkJCQ4xvzwww8oikKPHj0cY3755RcsFotjzJYtW2jTpk2tdmfk5eUhy85f0RqNBkVRAHH/BPUQT0f9upuNGzeqBoNBXbt2rXrw4EF11KhRalBQkFOmRn3hqaeeUgMDA9WffvpJPXv2rGPLy8tzjBk9erTaokUL9YcfflD//PNPNTY2Vo2NjXUcL0jN7du3r7pnzx518+bNaqNGjUpMzZ08ebJ66NAh9fXXX68zqblFKZolpKri3pXFrl27VK1Wq86fP189duyYun79etXHx0f94IMPHGMWLVqkBgUFqf/973/Vv//+W73nnntKTMvt0qWLunPnTvW3335TW7Vq5ZSWm5GRoYaGhqrDhg1T9+/fr27cuFH18fGp9Wm5jz32mHrNNdc40po/++wztWHDhuqUKVMcY8T9E9Qn6pzCoqqq+uqrr6otWrRQ9Xq92r17d3XHjh2eFskjACVua9ascYzJz89Xn376aTU4OFj18fFR//3vf6tnz551Wic5OVm94447VG9vb7Vhw4bqxIkTVYvF4jTmxx9/VDt37qzq9Xo1KirK6Rx1hSsVFnHvyubLL79UO3TooBoMBjUmJkZdtWqV03FFUdSZM2eqoaGhqsFgUHv37q0eOXLEaczFixfVhx56SPXz81MDAgLU4cOHq9nZ2U5j9u7dq/bq1Us1GAzqNddcoy5atKjKr62qycrKUp977jm1RYsWqpeXlxoVFaW+8MILTunH4v4J6hOi+aFAIBAIBIIaT52KYREIBAKBQFA3EQqLQCAQCASCGo9QWAQCgUAgENR4hMIiEAgEAoGgxiMUFoFAIBAIBDUeobAIBAKBQCCo8QiFRSAQCAQCQY1HKCwCgUAgEAhqPEJhEQgEAoFAUOMRCotAIBAIBIIaj1BYBAKBQCAQ1Hj+H+wMVdfw6vxiAAAAAElFTkSuQmCC",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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"text/plain": [
|
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"<Figure size 640x480 with 2 Axes>"
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|
]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/env/lib/python3.12/site-packages/xarray/groupers.py:392: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
|
" self.index_grouper = pd.Grouper(\n"
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]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
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"text": [
|
|
"NDVI monthly shape: (13, 8874, 9902)\n",
|
|
"CPU times: user 19.7 s, sys: 7.91 s, total: 27.6 s\n",
|
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"Wall time: 9min 43s\n"
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]
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}
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],
|
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"source": [
|
|
"%%time\n",
|
|
"# ── Loại bỏ mây + tính NDVI ───────────────────────────────────────────────────\n",
|
|
"result = mask_clean(data)\n",
|
|
"progress(result)\n",
|
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"\n",
|
|
"ds1 = calculate_indices(result, index=\"NDVI\", satellite_mission=\"s2\")\n",
|
|
"ndvi = ds1[\"NDVI\"]\n",
|
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"display(ndvi)\n",
|
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"\n",
|
|
"## Hiển thị ảnh NDVI trước khi fill mây\n",
|
|
"plt.imshow(ndvi.isel(time=6))\n",
|
|
"plt.title(\"NDVI (before cloud fill)\")\n",
|
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"plt.colorbar()\n",
|
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"plt.show()\n",
|
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"\n",
|
|
"# ── Fill nan theo mùa vụ ──────────────────────────────────────────────────────\n",
|
|
"time_split = [\n",
|
|
" slice(\"2022-09-01\", \"2023-01-01\"),\n",
|
|
" slice(\"2023-01-01\", \"2023-05-01\"),\n",
|
|
" slice(\"2023-05-01\", \"2023-07-01\"),\n",
|
|
" slice(\"2023-07-01\", \"2023-10-01\"),\n",
|
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"]\n",
|
|
"fill_nan_ndvi = fill_nan(ndvi, time_split)\n",
|
|
"\n",
|
|
"plt.imshow(fill_nan_ndvi.isel(time=6))\n",
|
|
"plt.title(\"NDVI (after cloud fill)\")\n",
|
|
"plt.colorbar()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# ── Resample về trung bình tháng ─────────────────────────────────────────────\n",
|
|
"average_ndvi = fill_nan_ndvi.resample(time=\"1M\").mean().persist()\n",
|
|
"progress(average_ndvi)\n",
|
|
"average_ndvi = average_ndvi.compute()\n",
|
|
"print(f\"NDVI monthly shape: {average_ndvi.shape}\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "7cae5302",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
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"text/html": [
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"<h4>Dataset size: 21.60 GB</h4>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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":root {\n",
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|
|
" --xr-background-color: var(--jp-layout-color0, white);\n",
|
|
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
|
|
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
|
|
"}\n",
|
|
"\n",
|
|
"html[theme=dark],\n",
|
|
"html[data-theme=dark],\n",
|
|
"body[data-theme=dark],\n",
|
|
"body.vscode-dark {\n",
|
|
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
|
|
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
|
|
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
|
|
" --xr-border-color: #1F1F1F;\n",
|
|
" --xr-disabled-color: #515151;\n",
|
|
" --xr-background-color: #111111;\n",
|
|
" --xr-background-color-row-even: #111111;\n",
|
|
" --xr-background-color-row-odd: #313131;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-wrap {\n",
|
|
" display: block !important;\n",
|
|
" min-width: 300px;\n",
|
|
" max-width: 700px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-text-repr-fallback {\n",
|
|
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-header {\n",
|
|
" padding-top: 6px;\n",
|
|
" padding-bottom: 6px;\n",
|
|
" margin-bottom: 4px;\n",
|
|
" border-bottom: solid 1px var(--xr-border-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-header > div,\n",
|
|
".xr-header > ul {\n",
|
|
" display: inline;\n",
|
|
" margin-top: 0;\n",
|
|
" margin-bottom: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-obj-type,\n",
|
|
".xr-array-name {\n",
|
|
" margin-left: 2px;\n",
|
|
" margin-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-obj-type {\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-sections {\n",
|
|
" padding-left: 0 !important;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item {\n",
|
|
" display: contents;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input {\n",
|
|
" display: inline-block;\n",
|
|
" opacity: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input + label {\n",
|
|
" color: var(--xr-disabled-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:enabled + label {\n",
|
|
" cursor: pointer;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:focus + label {\n",
|
|
" border: 2px solid var(--xr-font-color0);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-item input:enabled + label:hover {\n",
|
|
" color: var(--xr-font-color0);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary {\n",
|
|
" grid-column: 1;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
" font-weight: 500;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary > span {\n",
|
|
" display: inline-block;\n",
|
|
" padding-left: 0.5em;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:disabled + label {\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in + label:before {\n",
|
|
" display: inline-block;\n",
|
|
" content: '►';\n",
|
|
" font-size: 11px;\n",
|
|
" width: 15px;\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:disabled + label:before {\n",
|
|
" color: var(--xr-disabled-color);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:checked + label:before {\n",
|
|
" content: '▼';\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:checked + label > span {\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary,\n",
|
|
".xr-section-inline-details {\n",
|
|
" padding-top: 4px;\n",
|
|
" padding-bottom: 4px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-inline-details {\n",
|
|
" grid-column: 2 / -1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-details {\n",
|
|
" display: none;\n",
|
|
" grid-column: 1 / -1;\n",
|
|
" margin-bottom: 5px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-section-summary-in:checked ~ .xr-section-details {\n",
|
|
" display: contents;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-wrap {\n",
|
|
" grid-column: 1 / -1;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 20px auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-wrap > label {\n",
|
|
" grid-column: 1;\n",
|
|
" vertical-align: top;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-preview {\n",
|
|
" color: var(--xr-font-color3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-preview,\n",
|
|
".xr-array-data {\n",
|
|
" padding: 0 5px !important;\n",
|
|
" grid-column: 2;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-data,\n",
|
|
".xr-array-in:checked ~ .xr-array-preview {\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-array-in:checked ~ .xr-array-data,\n",
|
|
".xr-array-preview {\n",
|
|
" display: inline-block;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list {\n",
|
|
" display: inline-block !important;\n",
|
|
" list-style: none;\n",
|
|
" padding: 0 !important;\n",
|
|
" margin: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list li {\n",
|
|
" display: inline-block;\n",
|
|
" padding: 0;\n",
|
|
" margin: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list:before {\n",
|
|
" content: '(';\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list:after {\n",
|
|
" content: ')';\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-dim-list li:not(:last-child):after {\n",
|
|
" content: ',';\n",
|
|
" padding-right: 5px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-has-index {\n",
|
|
" font-weight: bold;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-list,\n",
|
|
".xr-var-item {\n",
|
|
" display: contents;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-item > div,\n",
|
|
".xr-var-item label,\n",
|
|
".xr-var-item > .xr-var-name span {\n",
|
|
" background-color: var(--xr-background-color-row-even);\n",
|
|
" margin-bottom: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-item > .xr-var-name:hover span {\n",
|
|
" padding-right: 5px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-list > li:nth-child(odd) > div,\n",
|
|
".xr-var-list > li:nth-child(odd) > label,\n",
|
|
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
|
|
" background-color: var(--xr-background-color-row-odd);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name {\n",
|
|
" grid-column: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-dims {\n",
|
|
" grid-column: 2;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-dtype {\n",
|
|
" grid-column: 3;\n",
|
|
" text-align: right;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-preview {\n",
|
|
" grid-column: 4;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-index-preview {\n",
|
|
" grid-column: 2 / 5;\n",
|
|
" color: var(--xr-font-color2);\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name,\n",
|
|
".xr-var-dims,\n",
|
|
".xr-var-dtype,\n",
|
|
".xr-preview,\n",
|
|
".xr-attrs dt {\n",
|
|
" white-space: nowrap;\n",
|
|
" overflow: hidden;\n",
|
|
" text-overflow: ellipsis;\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name:hover,\n",
|
|
".xr-var-dims:hover,\n",
|
|
".xr-var-dtype:hover,\n",
|
|
".xr-attrs dt:hover {\n",
|
|
" overflow: visible;\n",
|
|
" width: auto;\n",
|
|
" z-index: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-data {\n",
|
|
" display: none;\n",
|
|
" background-color: var(--xr-background-color) !important;\n",
|
|
" padding-bottom: 5px !important;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
|
|
".xr-var-data-in:checked ~ .xr-var-data,\n",
|
|
".xr-index-data-in:checked ~ .xr-index-data {\n",
|
|
" display: block;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-data > table {\n",
|
|
" float: right;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-var-name span,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-name div,\n",
|
|
".xr-index-data,\n",
|
|
".xr-attrs {\n",
|
|
" padding-left: 25px !important;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs,\n",
|
|
".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
".xr-index-data {\n",
|
|
" grid-column: 1 / -1;\n",
|
|
"}\n",
|
|
"\n",
|
|
"dl.xr-attrs {\n",
|
|
" padding: 0;\n",
|
|
" margin: 0;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 125px auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt,\n",
|
|
".xr-attrs dd {\n",
|
|
" padding: 0;\n",
|
|
" margin: 0;\n",
|
|
" float: left;\n",
|
|
" padding-right: 10px;\n",
|
|
" width: auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt {\n",
|
|
" font-weight: normal;\n",
|
|
" grid-column: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dt:hover span {\n",
|
|
" display: inline-block;\n",
|
|
" background: var(--xr-background-color);\n",
|
|
" padding-right: 10px;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dd {\n",
|
|
" grid-column: 2;\n",
|
|
" white-space: pre-wrap;\n",
|
|
" word-break: break-all;\n",
|
|
"}\n",
|
|
"\n",
|
|
".xr-icon-database,\n",
|
|
".xr-icon-file-text2,\n",
|
|
".xr-no-icon {\n",
|
|
" display: inline-block;\n",
|
|
" vertical-align: middle;\n",
|
|
" width: 1em;\n",
|
|
" height: 1.5em !important;\n",
|
|
" stroke-width: 0;\n",
|
|
" stroke: currentColor;\n",
|
|
" fill: currentColor;\n",
|
|
"}\n",
|
|
"</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 23GB\n",
|
|
"Dimensions: (time: 33, y: 8874, x: 9902)\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 264B 2022-09-06T22:46:14.500000 ... 20...\n",
|
|
" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
|
|
" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
|
|
" spatial_ref int32 4B 32648\n",
|
|
"Data variables:\n",
|
|
" vv (time, y, x) float32 12GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" vh (time, y, x) float32 12GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
"Attributes:\n",
|
|
" crs: EPSG:32648\n",
|
|
" grid_mapping: spatial_ref</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-648e4b05-267a-4cc5-a3ed-b16d44b3f510' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-648e4b05-267a-4cc5-a3ed-b16d44b3f510' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 33</li><li><span class='xr-has-index'>y</span>: 8874</li><li><span class='xr-has-index'>x</span>: 9902</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9f8ecfe5-142c-4c7c-8b12-05e9043251c1' class='xr-section-summary-in' type='checkbox' checked><label for='section-9f8ecfe5-142c-4c7c-8b12-05e9043251c1' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-06T22:46:14.500000 ... 2...</div><input id='attrs-8f825309-6b41-4932-883d-97e5687199c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f825309-6b41-4932-883d-97e5687199c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-523111bf-97ce-4596-b967-8a4a6c88df6f' class='xr-var-data-in' type='checkbox'><label for='data-523111bf-97ce-4596-b967-8a4a6c88df6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array(['2022-09-06T22:46:14.500000000', '2022-09-18T22:46:13.500000000',\n",
|
|
" '2022-09-30T22:46:14.500000000', '2022-10-12T22:46:14.500000000',\n",
|
|
" '2022-10-24T22:46:14.500000000', '2022-11-05T22:46:14.500000000',\n",
|
|
" '2022-11-17T22:46:13.500000000', '2022-11-29T22:46:13.500000000',\n",
|
|
" '2022-12-11T22:46:13.500000000', '2022-12-23T22:46:12.500000000',\n",
|
|
" '2023-01-04T22:46:11.500000000', '2023-01-16T22:46:10.500000000',\n",
|
|
" '2023-01-28T22:46:11.500000000', '2023-02-09T22:46:10.500000000',\n",
|
|
" '2023-02-21T22:46:09.500000000', '2023-03-05T22:46:10.500000000',\n",
|
|
" '2023-03-17T22:46:10.500000000', '2023-03-29T22:46:10.500000000',\n",
|
|
" '2023-04-10T22:46:11.500000000', '2023-04-22T22:46:11.500000000',\n",
|
|
" '2023-05-04T22:46:11.500000000', '2023-05-17T11:11:32.500000000',\n",
|
|
" '2023-05-29T11:11:32.500000000', '2023-06-10T11:11:28.500000000',\n",
|
|
" '2023-06-21T22:46:13.500000000', '2023-07-04T11:11:34.500000000',\n",
|
|
" '2023-07-16T11:11:35.500000000', '2023-07-28T11:11:36.500000000',\n",
|
|
" '2023-08-08T22:46:16.500000000', '2023-08-20T22:46:17.500000000',\n",
|
|
" '2023-09-01T22:46:18.500000000', '2023-09-13T22:46:18.500000000',\n",
|
|
" '2023-09-25T22:46:19.500000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e+06 1.106e+06 ... 1.017e+06</div><input id='attrs-f9543cdb-fea3-40ed-a40a-e937e0918fb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9543cdb-fea3-40ed-a40a-e937e0918fb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a4a9156-9a59-4a0f-b7d2-276a16a2bf7c' class='xr-var-data-in' type='checkbox'><label for='data-5a4a9156-9a59-4a0f-b7d2-276a16a2bf7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1105735., 1105725., 1105715., ..., 1017025., 1017015., 1017005.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.548e+05 5.548e+05 ... 6.538e+05</div><input id='attrs-d668edd4-65ce-498e-b7ff-1c084e9e718f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d668edd4-65ce-498e-b7ff-1c084e9e718f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e9eb622-0137-4f92-9321-985c1d9ca2c7' class='xr-var-data-in' type='checkbox'><label for='data-7e9eb622-0137-4f92-9321-985c1d9ca2c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([554795., 554805., 554815., ..., 653785., 653795., 653805.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-6724ece7-1ec1-4746-ae5a-f90633c2888c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6724ece7-1ec1-4746-ae5a-f90633c2888c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4ce3e04-0453-450f-b5d2-0ef8b1447e9e' class='xr-var-data-in' type='checkbox'><label for='data-f4ce3e04-0453-450f-b5d2-0ef8b1447e9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32648"]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-165e1d6a-550f-46f8-b15e-778eab61360b' class='xr-section-summary-in' type='checkbox' checked><label for='section-165e1d6a-550f-46f8-b15e-778eab61360b' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>vv</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></div><input id='attrs-eb036761-cb23-47fa-bf93-f86c4a031d65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb036761-cb23-47fa-bf93-f86c4a031d65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7fcd1da-665e-4993-9947-a672dca80151' class='xr-var-data-in' type='checkbox'><label for='data-a7fcd1da-665e-4993-9947-a672dca80151' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>intensity</dd><dt><span>nodata :</span></dt><dd>nan</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
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" <td>\n",
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" <table style=\"border-collapse: collapse;\">\n",
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" <thead>\n",
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" <tr>\n",
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" <td> </td>\n",
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" <th> Array </th>\n",
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" <th> Chunk </th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" \n",
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" <tr>\n",
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" <th> Bytes </th>\n",
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" <td> 10.80 GiB </td>\n",
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" <td> 16.00 MiB </td>\n",
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" </tr>\n",
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" \n",
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" <tr>\n",
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" <th> Shape </th>\n",
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" <td> (33, 8874, 9902) </td>\n",
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" <td> (1, 2048, 2048) </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th> Dask graph </th>\n",
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" <td colspan=\"2\"> 825 chunks in 1 graph layer </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th> Data type </th>\n",
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" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </tr>\n",
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" </tbody>\n",
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" </table>\n",
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" </td>\n",
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" <td>\n",
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" <svg width=\"194\" height=\"172\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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" <text x=\"7.474299\" y=\"135.016210\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,135.016210)\">33</text>\n",
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"</svg>\n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray></div><input id='attrs-4f1e621b-30b8-43f3-9251-c608da176ac5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f1e621b-30b8-43f3-9251-c608da176ac5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c5f43ab-1e94-4aa8-97a7-94f1cbaa561c' class='xr-var-data-in' type='checkbox'><label for='data-4c5f43ab-1e94-4aa8-97a7-94f1cbaa561c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>intensity</dd><dt><span>nodata :</span></dt><dd>nan</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
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" <td>\n",
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" <table style=\"border-collapse: collapse;\">\n",
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" <thead>\n",
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" <tr>\n",
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" <td> </td>\n",
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" <th> Array </th>\n",
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" <th> Chunk </th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" \n",
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" <tr>\n",
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" <th> Bytes </th>\n",
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" <td> 10.80 GiB </td>\n",
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" <td> 16.00 MiB </td>\n",
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" </tr>\n",
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" \n",
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" <tr>\n",
|
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" <th> Shape </th>\n",
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" <td> (33, 8874, 9902) </td>\n",
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" <td> (1, 2048, 2048) </td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th> Dask graph </th>\n",
|
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" <td colspan=\"2\"> 825 chunks in 1 graph layer </td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th> Data type </th>\n",
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" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </tr>\n",
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" </tbody>\n",
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" </table>\n",
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" </td>\n",
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" <td>\n",
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" <svg width=\"194\" height=\"172\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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"\n",
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" <!-- Horizontal lines -->\n",
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"\n",
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"\n",
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" <!-- Horizontal lines -->\n",
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" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
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" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
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" <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
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" <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
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" <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
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" <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
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" <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
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" <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
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" <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
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" <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
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" <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
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" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
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" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
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" <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
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" <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
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" <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
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" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Vertical lines -->\n",
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" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
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" <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Colored Rectangle -->\n",
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" <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
|
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"\n",
|
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" <!-- Horizontal lines -->\n",
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" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
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" <line x1=\"24\" y1=\"64\" x2=\"144\" y2=\"64\" />\n",
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" <line x1=\"24\" y1=\"122\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Vertical lines -->\n",
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" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
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" <line x1=\"74\" y1=\"14\" x2=\"74\" y2=\"122\" />\n",
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" <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"122\" />\n",
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" <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"122\" />\n",
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" <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Colored Rectangle -->\n",
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" <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,122.49050867486044 24.9485979497544,122.49050867486044\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
|
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"\n",
|
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" <!-- Text -->\n",
|
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" <text x=\"84.948598\" y=\"142.490509\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >9902</text>\n",
|
|
" <text x=\"164.948598\" y=\"68.719553\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,68.719553)\">8874</text>\n",
|
|
" <text x=\"7.474299\" y=\"135.016210\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,135.016210)\">33</text>\n",
|
|
"</svg>\n",
|
|
" </td>\n",
|
|
" </tr>\n",
|
|
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-1813962f-9cee-4050-beb8-7b61327142af' class='xr-section-summary-in' type='checkbox' ><label for='section-1813962f-9cee-4050-beb8-7b61327142af' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b1f234fd-50da-4d6f-8ce4-b7297db86ba3' class='xr-index-data-in' type='checkbox'/><label for='index-b1f234fd-50da-4d6f-8ce4-b7297db86ba3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2022-09-06 22:46:14.500000', '2022-09-18 22:46:13.500000',\n",
|
|
" '2022-09-30 22:46:14.500000', '2022-10-12 22:46:14.500000',\n",
|
|
" '2022-10-24 22:46:14.500000', '2022-11-05 22:46:14.500000',\n",
|
|
" '2022-11-17 22:46:13.500000', '2022-11-29 22:46:13.500000',\n",
|
|
" '2022-12-11 22:46:13.500000', '2022-12-23 22:46:12.500000',\n",
|
|
" '2023-01-04 22:46:11.500000', '2023-01-16 22:46:10.500000',\n",
|
|
" '2023-01-28 22:46:11.500000', '2023-02-09 22:46:10.500000',\n",
|
|
" '2023-02-21 22:46:09.500000', '2023-03-05 22:46:10.500000',\n",
|
|
" '2023-03-17 22:46:10.500000', '2023-03-29 22:46:10.500000',\n",
|
|
" '2023-04-10 22:46:11.500000', '2023-04-22 22:46:11.500000',\n",
|
|
" '2023-05-04 22:46:11.500000', '2023-05-17 11:11:32.500000',\n",
|
|
" '2023-05-29 11:11:32.500000', '2023-06-10 11:11:28.500000',\n",
|
|
" '2023-06-21 22:46:13.500000', '2023-07-04 11:11:34.500000',\n",
|
|
" '2023-07-16 11:11:35.500000', '2023-07-28 11:11:36.500000',\n",
|
|
" '2023-08-08 22:46:16.500000', '2023-08-20 22:46:17.500000',\n",
|
|
" '2023-09-01 22:46:18.500000', '2023-09-13 22:46:18.500000',\n",
|
|
" '2023-09-25 22:46:19.500000'],\n",
|
|
" dtype='datetime64[ns]', name='time', freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-40c5727b-4748-4a82-b7fb-47ef3a602556' class='xr-index-data-in' type='checkbox'/><label for='index-40c5727b-4748-4a82-b7fb-47ef3a602556' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1105735.0, 1105725.0, 1105715.0, 1105705.0, 1105695.0, 1105685.0,\n",
|
|
" 1105675.0, 1105665.0, 1105655.0, 1105645.0,\n",
|
|
" ...\n",
|
|
" 1017095.0, 1017085.0, 1017075.0, 1017065.0, 1017055.0, 1017045.0,\n",
|
|
" 1017035.0, 1017025.0, 1017015.0, 1017005.0],\n",
|
|
" dtype='float64', name='y', length=8874))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7ae5db78-3465-49b6-80f2-ac3a7f95028a' class='xr-index-data-in' type='checkbox'/><label for='index-7ae5db78-3465-49b6-80f2-ac3a7f95028a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([554795.0, 554805.0, 554815.0, 554825.0, 554835.0, 554845.0, 554855.0,\n",
|
|
" 554865.0, 554875.0, 554885.0,\n",
|
|
" ...\n",
|
|
" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
|
|
" 653785.0, 653795.0, 653805.0],\n",
|
|
" dtype='float64', name='x', length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd2932f5-68b5-4296-b219-9a6f19491e60' class='xr-section-summary-in' type='checkbox' checked><label for='section-dd2932f5-68b5-4296-b219-9a6f19491e60' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
|
|
],
|
|
"text/plain": [
|
|
"<xarray.Dataset> Size: 23GB\n",
|
|
"Dimensions: (time: 33, y: 8874, x: 9902)\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 264B 2022-09-06T22:46:14.500000 ... 20...\n",
|
|
" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
|
|
" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
|
|
" spatial_ref int32 4B 32648\n",
|
|
"Data variables:\n",
|
|
" vv (time, y, x) float32 12GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" vh (time, y, x) float32 12GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
"Attributes:\n",
|
|
" crs: EPSG:32648\n",
|
|
" grid_mapping: spatial_ref"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/env/lib/python3.12/site-packages/xarray/groupers.py:392: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
|
" self.index_grouper = pd.Grouper(\n",
|
|
"/env/lib/python3.12/site-packages/xarray/groupers.py:392: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
|
" self.index_grouper = pd.Grouper(\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"VV monthly shape: (13, 8874, 9902)\n",
|
|
"VH monthly shape: (13, 8874, 9902)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# ── Load Sentinel-1 (VH, VV) và tính trung bình tháng ────────────────────────\n",
|
|
"dsvh, dsvv = load_data_sen1(dc, date_range, coordinates)\n",
|
|
"average_vv = calculate_average(dsvv, time_pattern=\"1M\")\n",
|
|
"average_vh = calculate_average(dsvh, time_pattern=\"1M\")\n",
|
|
"\n",
|
|
"print(f\"VV monthly shape: {average_vv.shape}\")\n",
|
|
"print(f\"VH monthly shape: {average_vh.shape}\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "8901a611",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"X_train: (678, 39) y_train: (678,)\n",
|
|
"X_val : (226, 39) y_val : (226,)\n",
|
|
"X_test : (226, 39) y_test : (226,)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"## ── Chuẩn bị dữ liệu train ───────────────────────────────────────────────────\n",
|
|
"train_path = \"train/ST_training_data_updated_1130points_new.shp\"\n",
|
|
"\n",
|
|
"train = load_train_data(train_path)\n",
|
|
"train.head()\n",
|
|
"\n",
|
|
"label_mapping = {\n",
|
|
" \"Lua tom\": \"0\",\n",
|
|
" \"Lua\": \"1\",\n",
|
|
" \"CHN\": \"2\",\n",
|
|
" \"CLN\": \"3\",\n",
|
|
" \"TS\": \"4\",\n",
|
|
" \"Song\": \"5\",\n",
|
|
" \"Dat xay dung\": \"6\",\n",
|
|
" \"Rung\": \"7\",\n",
|
|
"}\n",
|
|
"\n",
|
|
"# Xây dựng dataset gồm VH, VV, NDVI\n",
|
|
"datasets = get_data_sen1_and_sen2(train, average_ndvi, average_vh, average_vv)\n",
|
|
"\n",
|
|
"# Chia 80-20-20\n",
|
|
"X_train, X_val, X_test, y_train, y_val, y_test = split_train_data(\n",
|
|
" train, label_mapping, datasets\n",
|
|
")\n",
|
|
"\n",
|
|
"print(f\"X_train: {np.asarray(X_train).shape} y_train: {np.asarray(y_train).shape}\")\n",
|
|
"print(f\"X_val : {np.asarray(X_val).shape} y_val : {np.asarray(y_val).shape}\")\n",
|
|
"print(f\"X_test : {np.asarray(X_test).shape} y_test : {np.asarray(y_test).shape}\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "64492335",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"SwinUNetClassifier(\n",
|
|
" (adapter): Sequential(\n",
|
|
" (0): Linear(in_features=39, out_features=256, bias=True)\n",
|
|
" (1): ReLU()\n",
|
|
" (2): Dropout(p=0.1, inplace=False)\n",
|
|
" (3): Linear(in_features=256, out_features=128, bias=True)\n",
|
|
" )\n",
|
|
" (encoder1): Sequential(\n",
|
|
" (0): Linear(in_features=128, out_features=128, bias=True)\n",
|
|
" (1): LayerNorm((128,), eps=1e-05, elementwise_affine=True)\n",
|
|
" (2): GELU(approximate='none')\n",
|
|
" (3): Dropout(p=0.1, inplace=False)\n",
|
|
" )\n",
|
|
" (down1): Linear(in_features=128, out_features=256, bias=True)\n",
|
|
" (encoder2): Sequential(\n",
|
|
" (0): Linear(in_features=256, out_features=256, bias=True)\n",
|
|
" (1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
|
|
" (2): GELU(approximate='none')\n",
|
|
" (3): Dropout(p=0.1, inplace=False)\n",
|
|
" )\n",
|
|
" (down2): Linear(in_features=256, out_features=512, bias=True)\n",
|
|
" (encoder3): Sequential(\n",
|
|
" (0): Linear(in_features=512, out_features=512, bias=True)\n",
|
|
" (1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
|
|
" (2): GELU(approximate='none')\n",
|
|
" (3): Dropout(p=0.1, inplace=False)\n",
|
|
" )\n",
|
|
" (up2): Linear(in_features=512, out_features=256, bias=True)\n",
|
|
" (decoder2): Sequential(\n",
|
|
" (0): Linear(in_features=512, out_features=256, bias=True)\n",
|
|
" (1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
|
|
" (2): GELU(approximate='none')\n",
|
|
" (3): Dropout(p=0.1, inplace=False)\n",
|
|
" )\n",
|
|
" (up1): Linear(in_features=256, out_features=128, bias=True)\n",
|
|
" (decoder1): Sequential(\n",
|
|
" (0): Linear(in_features=256, out_features=128, bias=True)\n",
|
|
" (1): LayerNorm((128,), eps=1e-05, elementwise_affine=True)\n",
|
|
" (2): GELU(approximate='none')\n",
|
|
" (3): Dropout(p=0.1, inplace=False)\n",
|
|
" )\n",
|
|
" (attention): MultiheadAttention(\n",
|
|
" (out_proj): NonDynamicallyQuantizableLinear(in_features=128, out_features=128, bias=True)\n",
|
|
" )\n",
|
|
" (classifier): Sequential(\n",
|
|
" (0): Linear(in_features=128, out_features=64, bias=True)\n",
|
|
" (1): GELU(approximate='none')\n",
|
|
" (2): Dropout(p=0.3, inplace=False)\n",
|
|
" (3): Linear(in_features=64, out_features=8, bias=True)\n",
|
|
" )\n",
|
|
")\n",
|
|
"\n",
|
|
"Total parameters: 958,536\n",
|
|
"n_features=39 n_classes=8 embed_dim=128\n",
|
|
"\n",
|
|
"CPU times: user 11.6 ms, sys: 299 μs, total: 11.9 ms\n",
|
|
"Wall time: 12.6 ms\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"# ── Kiến trúc Swin-UNet (giống train_module.py / api_server) ─────────────────\n",
|
|
"import numpy as np\n",
|
|
"import torch\n",
|
|
"import torch.nn as nn\n",
|
|
"import torch.optim as optim\n",
|
|
"from torch.utils.data import TensorDataset, DataLoader\n",
|
|
"\n",
|
|
"class SwinUNetClassifier(nn.Module):\n",
|
|
" \"\"\"\n",
|
|
" Swin Transformer U-Net style architecture adapted for feature vector classification.\n",
|
|
" Combines hierarchical Swin Transformer blocks with skip connections.\n",
|
|
" Identical to SwinUNetClassifier in train_module.py.\n",
|
|
" \"\"\"\n",
|
|
" def __init__(self, n_features, n_classes, embed_dim=128):\n",
|
|
" super().__init__()\n",
|
|
" self.n_features = n_features\n",
|
|
" self.n_classes = n_classes\n",
|
|
" self.embed_dim = embed_dim\n",
|
|
"\n",
|
|
" # Feature adapter\n",
|
|
" self.adapter = nn.Sequential(\n",
|
|
" nn.Linear(n_features, embed_dim * 2),\n",
|
|
" nn.ReLU(),\n",
|
|
" nn.Dropout(0.1),\n",
|
|
" nn.Linear(embed_dim * 2, embed_dim),\n",
|
|
" )\n",
|
|
"\n",
|
|
" # Encoder\n",
|
|
" self.encoder1 = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim, embed_dim), nn.LayerNorm(embed_dim), nn.GELU(), nn.Dropout(0.1)\n",
|
|
" )\n",
|
|
" self.down1 = nn.Linear(embed_dim, embed_dim * 2)\n",
|
|
"\n",
|
|
" self.encoder2 = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim * 2, embed_dim * 2), nn.LayerNorm(embed_dim * 2), nn.GELU(), nn.Dropout(0.1)\n",
|
|
" )\n",
|
|
" self.down2 = nn.Linear(embed_dim * 2, embed_dim * 4)\n",
|
|
"\n",
|
|
" self.encoder3 = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim * 4, embed_dim * 4), nn.LayerNorm(embed_dim * 4), nn.GELU(), nn.Dropout(0.1)\n",
|
|
" )\n",
|
|
"\n",
|
|
" # Decoder with skip connections\n",
|
|
" self.up2 = nn.Linear(embed_dim * 4, embed_dim * 2)\n",
|
|
" self.decoder2 = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim * 4, embed_dim * 2), nn.LayerNorm(embed_dim * 2), nn.GELU(), nn.Dropout(0.1)\n",
|
|
" )\n",
|
|
"\n",
|
|
" self.up1 = nn.Linear(embed_dim * 2, embed_dim)\n",
|
|
" self.decoder1 = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim * 2, embed_dim), nn.LayerNorm(embed_dim), nn.GELU(), nn.Dropout(0.1)\n",
|
|
" )\n",
|
|
"\n",
|
|
" # Attention for better aggregation\n",
|
|
" self.attention = nn.MultiheadAttention(embed_dim, num_heads=4, batch_first=True)\n",
|
|
"\n",
|
|
" # Classification head\n",
|
|
" self.classifier = nn.Sequential(\n",
|
|
" nn.Linear(embed_dim, embed_dim // 2),\n",
|
|
" nn.GELU(),\n",
|
|
" nn.Dropout(0.3),\n",
|
|
" nn.Linear(embed_dim // 2, n_classes),\n",
|
|
" )\n",
|
|
"\n",
|
|
" def forward(self, x):\n",
|
|
" if len(x.shape) == 3:\n",
|
|
" x = x.squeeze(1)\n",
|
|
"\n",
|
|
" # Adapter\n",
|
|
" x = self.adapter(x) # (B, embed_dim)\n",
|
|
" x_seq = x.unsqueeze(1) # (B, 1, embed_dim)\n",
|
|
"\n",
|
|
" # Encoder\n",
|
|
" x1 = self.encoder1(x_seq) # (B, 1, embed_dim)\n",
|
|
" x_d1 = self.down1(x1.squeeze(1)) # (B, embed_dim*2)\n",
|
|
"\n",
|
|
" x2 = self.encoder2(x_d1.unsqueeze(1)) # (B, 1, embed_dim*2)\n",
|
|
" x_d2 = self.down2(x2.squeeze(1)) # (B, embed_dim*4)\n",
|
|
"\n",
|
|
" x3 = self.encoder3(x_d2.unsqueeze(1)) # (B, 1, embed_dim*4)\n",
|
|
"\n",
|
|
" # Decoder\n",
|
|
" x_u2 = self.up2(x3.squeeze(1)) # (B, embed_dim*2)\n",
|
|
" x_cat2 = torch.cat([x_u2, x_d1], dim=1) # (B, embed_dim*4)\n",
|
|
" x_dec2 = self.decoder2(x_cat2) # (B, embed_dim*2)\n",
|
|
"\n",
|
|
" x_u1 = self.up1(x_dec2) # (B, embed_dim)\n",
|
|
" x_cat1 = torch.cat([x_u1, x.squeeze(1) if len(x.shape)==3 else x], dim=1) # (B, embed_dim*2)\n",
|
|
" x_dec1 = self.decoder1(x_cat1) # (B, embed_dim)\n",
|
|
"\n",
|
|
" # Attention\n",
|
|
" x_seq2 = x_dec1.unsqueeze(1)\n",
|
|
" attn, _ = self.attention(x_seq2, x_seq2, x_seq2)\n",
|
|
"\n",
|
|
" return self.classifier(attn.squeeze(1))\n",
|
|
"\n",
|
|
" def predict(self, X):\n",
|
|
" \"\"\"Scikit-learn style predict.\"\"\"\n",
|
|
" self.eval()\n",
|
|
" with torch.no_grad():\n",
|
|
" if isinstance(X, np.ndarray):\n",
|
|
" X = torch.FloatTensor(X)\n",
|
|
" outputs = self(X)\n",
|
|
" return outputs.argmax(1).cpu().numpy()\n",
|
|
"\n",
|
|
" def score(self, X, y):\n",
|
|
" preds = self.predict(X)\n",
|
|
" if isinstance(y, torch.Tensor):\n",
|
|
" y = y.cpu().numpy()\n",
|
|
" return float(np.mean(preds == y))\n",
|
|
"\n",
|
|
"\n",
|
|
"# ── Chuẩn bị tensor & DataLoader ─────────────────────────────────────────────\n",
|
|
"X_train_np = np.asarray(X_train, dtype=np.float32)\n",
|
|
"X_val_np = np.asarray(X_val, dtype=np.float32)\n",
|
|
"y_train_np = np.asarray(y_train, dtype=np.int64)\n",
|
|
"y_val_np = np.asarray(y_val, dtype=np.int64)\n",
|
|
"\n",
|
|
"n_features = X_train_np.shape[1]\n",
|
|
"NUM_CLASSES = len(label_mapping)\n",
|
|
"\n",
|
|
"X_train_t = torch.from_numpy(X_train_np)\n",
|
|
"X_val_t = torch.from_numpy(X_val_np)\n",
|
|
"y_train_t = torch.from_numpy(y_train_np)\n",
|
|
"y_val_t = torch.from_numpy(y_val_np)\n",
|
|
"\n",
|
|
"train_loader = DataLoader(TensorDataset(X_train_t, y_train_t), batch_size=BATCH_SIZE, shuffle=True)\n",
|
|
"val_loader = DataLoader(TensorDataset(X_val_t, y_val_t), batch_size=64, shuffle=False)\n",
|
|
"\n",
|
|
"# ── Khởi tạo mô hình ─────────────────────────────────────────────────────────\n",
|
|
"model = SwinUNetClassifier(n_features, NUM_CLASSES, embed_dim=EMBED_DIM).to(DEVICE)\n",
|
|
"print(model)\n",
|
|
"total_params = sum(p.numel() for p in model.parameters())\n",
|
|
"print(f\"\\nTotal parameters: {total_params:,}\")\n",
|
|
"print(f\"n_features={n_features} n_classes={NUM_CLASSES} embed_dim={EMBED_DIM}\\n\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "d26a3308",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Class distribution : [ 34 123 40 106 90 73 130 82]\n",
|
|
"Class weights : [2.017 0.557 1.714 0.647 0.762 0.939 0.527 0.836]\n",
|
|
"\n",
|
|
"🚀 Training Swin-UNet model (PyTorch)...\n",
|
|
"Epoch 1/150 train_loss=1.7518 train_acc=0.2817 val_loss=1.3761 val_acc=0.5000 lr=0.000999\n",
|
|
"Epoch 10/150 train_loss=0.7992 train_acc=0.7198 val_loss=0.8853 val_acc=0.7080 lr=0.000905\n",
|
|
"Epoch 20/150 train_loss=0.6027 train_acc=0.7906 val_loss=0.6083 val_acc=0.8097 lr=0.000655\n",
|
|
"Epoch 30/150 train_loss=0.4327 train_acc=0.8555 val_loss=0.5047 val_acc=0.8761 lr=0.000345\n",
|
|
"Epoch 40/150 train_loss=0.3410 train_acc=0.8953 val_loss=0.5917 val_acc=0.8850 lr=0.000095\n",
|
|
"Epoch 50/150 train_loss=0.3022 train_acc=0.8968 val_loss=0.5913 val_acc=0.8761 lr=0.000000\n",
|
|
"Epoch 60/150 train_loss=0.3282 train_acc=0.8923 val_loss=0.5988 val_acc=0.8761 lr=0.000095\n",
|
|
"\n",
|
|
"Early stopping tại epoch 61 (không cải thiện 20 epochs liên tiếp)\n",
|
|
"\n",
|
|
"✅ Training hoàn tất! Best val accuracy: 0.8938 (89.38%)\n",
|
|
"CPU times: user 6min 42s, sys: 297 ms, total: 6min 43s\n",
|
|
"Wall time: 23.3 s\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"# ── Train Swin-UNet ───────────────────────────────────────────────────────────\n",
|
|
"\n",
|
|
"# Class weights để xử lý mất cân bằng dữ liệu (giống api_server)\n",
|
|
"class_counts = np.bincount(y_train_np)\n",
|
|
"class_weights = 1.0 / (class_counts + 1e-6)\n",
|
|
"class_weights = class_weights / class_weights.sum() * len(class_counts)\n",
|
|
"class_weights_t = torch.FloatTensor(class_weights).to(DEVICE)\n",
|
|
"\n",
|
|
"print(f\"Class distribution : {class_counts}\")\n",
|
|
"print(f\"Class weights : {np.round(class_weights, 3)}\\n\")\n",
|
|
"\n",
|
|
"criterion = nn.CrossEntropyLoss(weight=class_weights_t)\n",
|
|
"optimizer = optim.AdamW(model.parameters(), lr=LR, weight_decay=WEIGHT_DECAY)\n",
|
|
"scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=50)\n",
|
|
"\n",
|
|
"best_val_acc = 0.0\n",
|
|
"best_state = None\n",
|
|
"no_improve = 0\n",
|
|
"history = {\"train_loss\": [], \"train_acc\": [], \"val_loss\": [], \"val_acc\": []}\n",
|
|
"\n",
|
|
"def evaluate(loader):\n",
|
|
" model.eval()\n",
|
|
" total_loss, correct, n = 0.0, 0, 0\n",
|
|
" with torch.no_grad():\n",
|
|
" for xb, yb in loader:\n",
|
|
" xb, yb = xb.to(DEVICE), yb.to(DEVICE)\n",
|
|
" logits = model(xb)\n",
|
|
" total_loss += criterion(logits, yb).item() * len(yb)\n",
|
|
" correct += (logits.argmax(1) == yb).sum().item()\n",
|
|
" n += len(yb)\n",
|
|
" return total_loss / n, correct / n\n",
|
|
"\n",
|
|
"print(\"🚀 Training Swin-UNet model (PyTorch)...\")\n",
|
|
"for epoch in range(1, EPOCHS + 1):\n",
|
|
" model.train()\n",
|
|
" t_loss, t_correct, t_n = 0.0, 0, 0\n",
|
|
" for xb, yb in train_loader:\n",
|
|
" xb, yb = xb.to(DEVICE), yb.to(DEVICE)\n",
|
|
" optimizer.zero_grad()\n",
|
|
" logits = model(xb)\n",
|
|
" loss = criterion(logits, yb)\n",
|
|
" loss.backward()\n",
|
|
" # Gradient clipping — quan trọng cho Swin blocks\n",
|
|
" torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)\n",
|
|
" optimizer.step()\n",
|
|
" t_loss += loss.item() * len(yb)\n",
|
|
" t_correct += (logits.argmax(1) == yb).sum().item()\n",
|
|
" t_n += len(yb)\n",
|
|
"\n",
|
|
" scheduler.step()\n",
|
|
" train_loss, train_acc = t_loss / t_n, t_correct / t_n\n",
|
|
" val_loss, val_acc = evaluate(val_loader)\n",
|
|
" lr_now = optimizer.param_groups[0][\"lr\"]\n",
|
|
"\n",
|
|
" history[\"train_loss\"].append(train_loss)\n",
|
|
" history[\"train_acc\"].append(train_acc)\n",
|
|
" history[\"val_loss\"].append(val_loss)\n",
|
|
" history[\"val_acc\"].append(val_acc)\n",
|
|
"\n",
|
|
" if val_acc > best_val_acc:\n",
|
|
" best_val_acc = val_acc\n",
|
|
" best_state = {k: v.cpu().clone() for k, v in model.state_dict().items()}\n",
|
|
" no_improve = 0\n",
|
|
" else:\n",
|
|
" no_improve += 1\n",
|
|
"\n",
|
|
" if epoch % 10 == 0 or epoch == 1:\n",
|
|
" print(f\"Epoch {epoch:3d}/{EPOCHS} \"\n",
|
|
" f\"train_loss={train_loss:.4f} train_acc={train_acc:.4f} \"\n",
|
|
" f\"val_loss={val_loss:.4f} val_acc={val_acc:.4f} lr={lr_now:.6f}\")\n",
|
|
"\n",
|
|
" if no_improve >= PATIENCE:\n",
|
|
" print(f\"\\nEarly stopping tại epoch {epoch} (không cải thiện {PATIENCE} epochs liên tiếp)\")\n",
|
|
" break\n",
|
|
"\n",
|
|
"model.load_state_dict(best_state)\n",
|
|
"print(f\"\\n✅ Training hoàn tất! Best val accuracy: {best_val_acc:.4f} ({best_val_acc*100:.2f}%)\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "4a806eaf",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"📊 Evaluating Swin-UNet on test set...\n",
|
|
"\n",
|
|
"📈 Test Results:\n",
|
|
" Accuracy : 0.8540 (85.40%)\n",
|
|
" Precision: 0.8893\n",
|
|
" Recall : 0.8540\n",
|
|
" F1-Score : 0.8667\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
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"<Figure size 1400x400 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
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"image/png": 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",
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"text/plain": [
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"<Figure size 1000x800 with 2 Axes>"
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]
|
|
},
|
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"metadata": {},
|
|
"output_type": "display_data"
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},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
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"CPU times: user 1.06 s, sys: 307 ms, total: 1.36 s\n",
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"Wall time: 581 ms\n"
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]
|
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}
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],
|
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"source": [
|
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"%%time\n",
|
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"import matplotlib.pyplot as plt\n",
|
|
"from sklearn.metrics import (\n",
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" accuracy_score, precision_score, recall_score, f1_score,\n",
|
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" confusion_matrix, ConfusionMatrixDisplay,\n",
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")\n",
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"\n",
|
|
"# ── 1. Đánh giá trên tập test ────────────────────────────────────────────────\n",
|
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"X_test_np = np.asarray(X_test, dtype=np.float32)\n",
|
|
"y_test_np = np.asarray(y_test, dtype=np.int64)\n",
|
|
"X_test_t = torch.from_numpy(X_test_np)\n",
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"\n",
|
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"print(\"📊 Evaluating Swin-UNet on test set...\\n\")\n",
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"\n",
|
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"model.eval()\n",
|
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"all_preds = []\n",
|
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"with torch.no_grad():\n",
|
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" for i in range(0, len(X_test_t), 64):\n",
|
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" xb = X_test_t[i:i+64].to(DEVICE)\n",
|
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" preds = model(xb).argmax(1).cpu().numpy()\n",
|
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" all_preds.append(preds)\n",
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"\n",
|
|
"y_pred_test = np.concatenate(all_preds)\n",
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"\n",
|
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"test_accuracy = accuracy_score(y_test_np, y_pred_test)\n",
|
|
"precision = precision_score(y_test_np, y_pred_test, average=\"weighted\", zero_division=0)\n",
|
|
"recall = recall_score(y_test_np, y_pred_test, average=\"weighted\", zero_division=0)\n",
|
|
"f1 = f1_score(y_test_np, y_pred_test, average=\"weighted\", zero_division=0)\n",
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"\n",
|
|
"print(f\"📈 Test Results:\")\n",
|
|
"print(f\" Accuracy : {test_accuracy:.4f} ({test_accuracy*100:.2f}%)\")\n",
|
|
"print(f\" Precision: {precision:.4f}\")\n",
|
|
"print(f\" Recall : {recall:.4f}\")\n",
|
|
"print(f\" F1-Score : {f1:.4f}\\n\")\n",
|
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"\n",
|
|
"# ── 2. Learning curves ───────────────────────────────────────────────────────\n",
|
|
"fig, axes = plt.subplots(1, 2, figsize=(14, 4))\n",
|
|
"\n",
|
|
"axes[0].plot(history[\"train_loss\"], label=\"Train loss\")\n",
|
|
"axes[0].plot(history[\"val_loss\"], label=\"Val loss\")\n",
|
|
"axes[0].set_title(\"Loss over epochs\"); axes[0].set_xlabel(\"Epoch\"); axes[0].legend()\n",
|
|
"\n",
|
|
"axes[1].plot(history[\"train_acc\"], label=\"Train accuracy\")\n",
|
|
"axes[1].plot(history[\"val_acc\"], label=\"Val accuracy\")\n",
|
|
"axes[1].set_title(\"Accuracy over epochs\"); axes[1].set_xlabel(\"Epoch\"); axes[1].legend()\n",
|
|
"\n",
|
|
"plt.tight_layout(); plt.show()\n",
|
|
"\n",
|
|
"# ── 3. Confusion matrix ──────────────────────────────────────────────────────\n",
|
|
"class_names = list(label_mapping.keys())\n",
|
|
"cm = confusion_matrix(y_test_np, y_pred_test)\n",
|
|
"disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=class_names)\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(figsize=(10, 8))\n",
|
|
"disp.plot(cmap=\"Blues\", ax=ax)\n",
|
|
"plt.xticks(rotation=45, ha=\"right\")\n",
|
|
"plt.title(\"Swin-UNet Confusion Matrix — Test Set\")\n",
|
|
"plt.tight_layout(); plt.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"id": "cf1b5923",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"✅ Model saved to model_swinunet_land_use.pth\n",
|
|
"✅ Metadata saved to model_swinunet_land_use_info.json\n",
|
|
"\n",
|
|
"Summary:\n",
|
|
" n_features : 39\n",
|
|
" Parameters : 958,536\n",
|
|
" Test accuracy: 85.40%\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"# ── Lưu weights mô hình Swin-UNet ────────────────────────────────────────────\n",
|
|
"model_path = \"model_swinunet_land_use.pth\"\n",
|
|
"torch.save({\n",
|
|
" \"model_state_dict\": model.state_dict(),\n",
|
|
" \"n_features\": n_features,\n",
|
|
" \"num_classes\": NUM_CLASSES,\n",
|
|
" \"embed_dim\": EMBED_DIM,\n",
|
|
" \"label_mapping\": label_mapping,\n",
|
|
"}, model_path)\n",
|
|
"print(f\"✅ Model saved to {model_path}\")\n",
|
|
"\n",
|
|
"# ── Lưu metadata ─────────────────────────────────────────────────────────────\n",
|
|
"info = {\n",
|
|
" \"model_type\": \"Swin-UNet (PyTorch)\",\n",
|
|
" \"input_shape\": [n_features],\n",
|
|
" \"embed_dim\": EMBED_DIM,\n",
|
|
" \"num_classes\": NUM_CLASSES,\n",
|
|
" \"classes\": list(label_mapping.keys()),\n",
|
|
" \"label_mapping\": label_mapping,\n",
|
|
" \"num_parameters\": sum(p.numel() for p in model.parameters()),\n",
|
|
" \"accuracy\": float(test_accuracy),\n",
|
|
" \"precision\": float(precision),\n",
|
|
" \"recall\": float(recall),\n",
|
|
" \"f1_score\": float(f1),\n",
|
|
"}\n",
|
|
"\n",
|
|
"info_path = \"model_swinunet_land_use_info.json\"\n",
|
|
"with open(info_path, \"w\") as f:\n",
|
|
" json.dump(info, f, indent=2, ensure_ascii=False)\n",
|
|
"\n",
|
|
"print(f\"✅ Metadata saved to {info_path}\")\n",
|
|
"print(f\"\\nSummary:\")\n",
|
|
"print(f\" n_features : {n_features}\")\n",
|
|
"print(f\" Parameters : {info['num_parameters']:,}\")\n",
|
|
"print(f\" Test accuracy: {test_accuracy*100:.2f}%\")\n",
|
|
"\n",
|
|
"# ── Ví dụ load lại mô hình ──────────────────────────────────────────────────\n",
|
|
"# ck = torch.load(\"model_swinunet_land_use.pth\")\n",
|
|
"# model_loaded = SwinUNetClassifier(ck[\"n_features\"], ck[\"num_classes\"], ck[\"embed_dim\"])\n",
|
|
"# model_loaded.load_state_dict(ck[\"model_state_dict\"])\n",
|
|
"# model_loaded.eval()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "93c9d96e",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# đóng client, cluster\n",
|
|
"client.close()\n",
|
|
"cluster.close()\n"
|
|
]
|
|
}
|
|
],
|
|
"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": "3.12.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|