mirror of
https://git.victorphan.net/basketballcantho/CSIROBoeingPhase5-Vietnam.git
synced 2026-08-05 13:43:11 +07:00
6237 lines
1.4 MiB
Plaintext
6237 lines
1.4 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": "c61a1a84-ca37-4bfb-8935-a21312c11410",
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"metadata": {
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"tags": []
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},
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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 = '3.5.2'.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/1.5.4/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.5.2.min.js\", \"https://cdn.holoviz.org/panel/1.5.4/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",
|
|
" // 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 = '3.5.2'.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/1.5.4/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.5.2.min.js\", \"https://cdn.holoviz.org/panel/1.5.4/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 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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": {},
|
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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/vnd.holoviews_exec.v0+json": "",
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"text/html": [
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|
|
"</div>\n",
|
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"<script type=\"application/javascript\">(function(root) {\n",
|
|
" var docs_json = {\"1d23d827-506c-4c81-b16b-2e20b9494f89\":{\"version\":\"3.5.2\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"5241c75c-67b6-43a8-ae5b-07639967566f\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"88e08001-8dea-4438-ac3b-05914234f584\",\"attributes\":{\"plot_id\":\"5241c75c-67b6-43a8-ae5b-07639967566f\",\"comm_id\":\"84ef4b84eb4948c6a1b65d5b67f1c7cc\",\"client_comm_id\":\"0849ef9b2d5a4f02a7e0a06964f1803f\"}}],\"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 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|
|
" var render_items = [{\"docid\":\"1d23d827-506c-4c81-b16b-2e20b9494f89\",\"roots\":{\"5241c75c-67b6-43a8-ae5b-07639967566f\":\"fe640fb2-97df-43f3-b7bd-3c4ae44fb11c\"},\"root_ids\":[\"5241c75c-67b6-43a8-ae5b-07639967566f\"]}];\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": {
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|
"application/vnd.holoviews_exec.v0+json": {
|
|
"id": "5241c75c-67b6-43a8-ae5b-07639967566f"
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|
}
|
|
},
|
|
"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": {},
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"output_type": "display_data"
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},
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{
|
|
"data": {
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"application/javascript": [
|
|
"(function(root) {\n",
|
|
" function now() {\n",
|
|
" return new Date();\n",
|
|
" }\n",
|
|
"\n",
|
|
" const force = false;\n",
|
|
" const py_version = '3.5.2'.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/1.5.4/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 = '3.5.2'.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/1.5.4/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 = '3.5.2'.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/1.5.4/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 = '3.5.2'.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/1.5.4/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 = '3.5.2'.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/1.5.4/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 = '3.5.2'.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/1.5.4/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": [
|
|
"CPU times: user 13.1 s, sys: 3.24 s, total: 16.4 s\n",
|
|
"Wall time: 10.3 s\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"%matplotlib inline\n",
|
|
"\n",
|
|
"import importlib\n",
|
|
"import new_import \n",
|
|
"\n",
|
|
"importlib.reload(new_import)\n",
|
|
"\n",
|
|
"\n",
|
|
"from new_import import *"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "2298b035-c320-4c52-a2e4-6d8084f66b92",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Starting new cluster.\n",
|
|
"CPU times: user 671 ms, sys: 68.2 ms, total: 739 ms\n",
|
|
"Wall time: 2min 43s\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-a865d2b6-d583-11ef-8082-79cd5c8df936</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.8daaa179e4964dc7b211b4302753bf26/status\" target=\"_blank\">https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.8daaa179e4964dc7b211b4302753bf26/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.8daaa179e4964dc7b211b4302753bf26/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.8daaa179e4964dc7b211b4302753bf26\n",
|
|
" <li><b>Dashboard: </b><a href='https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.8daaa179e4964dc7b211b4302753bf26/status' target='_blank'>https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.8daaa179e4964dc7b211b4302753bf26/status</a>\n",
|
|
" </ul>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </details>\n",
|
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" \n",
|
|
"\n",
|
|
" </div>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
"<Client: 'tls://10.0.44.52:8786' processes=0 threads=0, memory=0 B>"
|
|
]
|
|
},
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|
"execution_count": 2,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"2025-01-18 10:50:14,308 - distributed.client - ERROR - Failed to reconnect to scheduler after 30.00 seconds, closing client\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"# Cấu hình Daskgateway\n",
|
|
"cluster, client = notebook_utils.initialize_dask(use_gateway=True, workers=(1,10))\n",
|
|
"# Khai báo 1 Datacube là dc\n",
|
|
"dc = datacube.Datacube()\n",
|
|
"\n",
|
|
"client"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "c5df2663-2524-4b99-aef4-cc0c625519e4",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"date_range = ('2023-3-01', '2023-3-30')\n",
|
|
"longtitude_range = (105.5, 106.4)\n",
|
|
"latitude_range = (9.2, 10.0) \n",
|
|
"\n",
|
|
"coordinates = (longtitude_range, latitude_range)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
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"id": "f0422603-cca1-41bc-a12a-810d6a13e736",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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" *\n",
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" */\n",
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"\n",
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":root {\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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" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
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" --xr-border-color: #1f1f1f;\n",
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" --xr-disabled-color: #515151;\n",
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" --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",
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"\n",
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|
"\n",
|
|
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|
|
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" display: none;\n",
|
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"}\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",
|
|
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|
|
" margin-right: 10px;\n",
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|
"}\n",
|
|
"\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",
|
|
" padding-left: 0 !important;\n",
|
|
" display: grid;\n",
|
|
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
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"}\n",
|
|
"\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",
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" display: inline-block;\n",
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" opacity: 0;\n",
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"\n",
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".xr-section-item input + label {\n",
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|
" color: var(--xr-disabled-color);\n",
|
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|
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".xr-section-item input:enabled + label {\n",
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"\n",
|
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".xr-section-item input:focus + label {\n",
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|
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" text-align: center;\n",
|
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".xr-section-summary-in:checked ~ .xr-section-details {\n",
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".xr-array-preview,\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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|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
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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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|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
".xr-var-preview {\n",
|
|
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|
|
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|
|
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|
|
".xr-index-preview {\n",
|
|
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|
|
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|
|
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|
|
"\n",
|
|
".xr-var-name,\n",
|
|
".xr-var-dims,\n",
|
|
".xr-var-dtype,\n",
|
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|
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|
|
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|
|
".xr-var-name:hover,\n",
|
|
".xr-var-dims:hover,\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",
|
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".xr-var-attrs,\n",
|
|
".xr-var-data,\n",
|
|
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|
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|
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|
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|
|
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|
|
"\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",
|
|
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|
|
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|
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|
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|
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|
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|
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".xr-var-attrs,\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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|
|
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|
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".xr-attrs dt,\n",
|
|
".xr-attrs dd {\n",
|
|
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|
|
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|
|
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|
|
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|
|
" width: auto;\n",
|
|
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|
|
"\n",
|
|
".xr-attrs dt {\n",
|
|
" font-weight: normal;\n",
|
|
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|
|
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|
|
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|
|
".xr-attrs dt:hover span {\n",
|
|
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|
|
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|
|
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|
|
"}\n",
|
|
"\n",
|
|
".xr-attrs dd {\n",
|
|
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|
|
" white-space: pre-wrap;\n",
|
|
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|
|
"}\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: 2GB\n",
|
|
"Dimensions: (time: 3, y: 8874, x: 9902)\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 24B 2023-03-05T22:46:10.500000 ... 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",
|
|
" vv (time, y, x) float32 1GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" vh (time, y, x) float32 1GB 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-e326b911-74b5-4ed5-9348-8b5762d8645d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e326b911-74b5-4ed5-9348-8b5762d8645d' 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>: 3</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-aa5a5322-2148-45e1-aeb6-90977c27d053' class='xr-section-summary-in' type='checkbox' checked><label for='section-aa5a5322-2148-45e1-aeb6-90977c27d053' 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'>2023-03-05T22:46:10.500000 ... 2...</div><input id='attrs-53ff7ab6-b2c3-4e48-a764-10e76191c7c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53ff7ab6-b2c3-4e48-a764-10e76191c7c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc0c1f64-dc58-4274-9253-9316fc14f513' class='xr-var-data-in' type='checkbox'><label for='data-cc0c1f64-dc58-4274-9253-9316fc14f513' 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(['2023-03-05T22:46:10.500000000', '2023-03-17T22:46:10.500000000',\n",
|
|
" '2023-03-29T22:46:10.500000000'], 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-7c2810f7-6c69-41e4-ac96-07d7c9f478c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c2810f7-6c69-41e4-ac96-07d7c9f478c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1dec7dd-c483-4f66-bca0-b6c3aaf07703' class='xr-var-data-in' type='checkbox'><label for='data-a1dec7dd-c483-4f66-bca0-b6c3aaf07703' 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-b2e61ccf-59b6-4019-9ea0-f637f839d92b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2e61ccf-59b6-4019-9ea0-f637f839d92b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09b15f6e-b318-4c95-9d19-868b407515c9' class='xr-var-data-in' type='checkbox'><label for='data-09b15f6e-b318-4c95-9d19-868b407515c9' 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-22a9b6ab-eaa1-4e98-8704-195ba616f3ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22a9b6ab-eaa1-4e98-8704-195ba616f3ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-caf9707a-683b-46e1-9dac-24c6928f66b9' class='xr-var-data-in' type='checkbox'><label for='data-caf9707a-683b-46e1-9dac-24c6928f66b9' 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-87f0fcf5-a04d-45d4-9b73-50e4f76d8d9c' class='xr-section-summary-in' type='checkbox' checked><label for='section-87f0fcf5-a04d-45d4-9b73-50e4f76d8d9c' 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-fae1dcee-d4eb-4970-9fb9-67bf4173d44c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fae1dcee-d4eb-4970-9fb9-67bf4173d44c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d121e87b-342d-419f-9530-9fca04403a90' class='xr-var-data-in' type='checkbox'><label for='data-d121e87b-342d-419f-9530-9fca04403a90' 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",
|
|
" </thead>\n",
|
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" <tbody>\n",
|
|
" \n",
|
|
" <tr>\n",
|
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" <th> Bytes </th>\n",
|
|
" <td> 0.98 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (3, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
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" <td colspan=\"2\"> 75 chunks in 1 graph layer </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=\"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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" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
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" <line x1=\"10\" y1=\"49\" x2=\"24\" y2=\"64\" />\n",
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" <line x1=\"10\" y1=\"74\" x2=\"24\" y2=\"89\" />\n",
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" <line x1=\"10\" y1=\"99\" x2=\"24\" y2=\"114\" />\n",
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" <line x1=\"10\" y1=\"107\" x2=\"24\" 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=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\n",
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" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Colored Rectangle -->\n",
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"\n",
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" <!-- Horizontal lines -->\n",
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" <line x1=\"84\" y1=\"0\" x2=\"99\" y2=\"14\" />\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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"\n",
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" <!-- Horizontal lines -->\n",
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"\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",
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" <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",
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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)\">3</text>\n",
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"</svg>\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>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-585c6d95-4cca-4686-b2fb-b194b33210c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-585c6d95-4cca-4686-b2fb-b194b33210c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddd2796d-eea0-42eb-afbe-b03c2edd1b02' class='xr-var-data-in' type='checkbox'><label for='data-ddd2796d-eea0-42eb-afbe-b03c2edd1b02' 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> 0.98 GiB </td>\n",
|
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" <td> 16.00 MiB </td>\n",
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" </tr>\n",
|
|
" \n",
|
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" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (3, 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\"> 75 chunks in 1 graph layer </td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
|
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" </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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" <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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" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
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" <line x1=\"10\" y1=\"107\" x2=\"24\" 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=\"10\" y1=\"0\" x2=\"10\" y2=\"107\" style=\"stroke-width:2\" />\n",
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" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\n",
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" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
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"\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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"\n",
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" <!-- Vertical lines -->\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",
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" <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",
|
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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)\">3</text>\n",
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"</svg>\n",
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" </td>\n",
|
|
" </tr>\n",
|
|
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-68407c27-4bd2-4c1c-8fe5-a2683bd3f15d' class='xr-section-summary-in' type='checkbox' ><label for='section-68407c27-4bd2-4c1c-8fe5-a2683bd3f15d' 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><input type='checkbox' disabled/><label></label><input id='index-a82082bf-39e7-4b4a-b949-1050075894b7' class='xr-index-data-in' type='checkbox'/><label for='index-a82082bf-39e7-4b4a-b949-1050075894b7' 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(['2023-03-05 22:46:10.500000', '2023-03-17 22:46:10.500000',\n",
|
|
" '2023-03-29 22:46:10.500000'],\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><input type='checkbox' disabled/><label></label><input id='index-a9d98a0f-cf61-4a2e-b457-377f9b7de528' class='xr-index-data-in' type='checkbox'/><label for='index-a9d98a0f-cf61-4a2e-b457-377f9b7de528' 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><input type='checkbox' disabled/><label></label><input id='index-c28a01a7-cb21-4662-a622-efa443d82ee4' class='xr-index-data-in' type='checkbox'/><label for='index-c28a01a7-cb21-4662-a622-efa443d82ee4' 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-b27701af-bbc7-4e95-86e5-c7114e66505f' class='xr-section-summary-in' type='checkbox' checked><label for='section-b27701af-bbc7-4e95-86e5-c7114e66505f' 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": [
|
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"<xarray.Dataset> Size: 2GB\n",
|
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"Dimensions: (time: 3, y: 8874, x: 9902)\n",
|
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"Coordinates:\n",
|
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" * time (time) datetime64[ns] 24B 2023-03-05T22:46:10.500000 ... 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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" vv (time, y, x) float32 1GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
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" vh (time, y, x) float32 1GB 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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"metadata": {},
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}
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],
|
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"source": [
|
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"# tải dữ liệu vh vv từ vệ tinh sentinel-1\n",
|
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"dsvh, dsvv = load_data_sen1(dc, date_range, coordinates)"
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]
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{
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"id": "c4d11ba1-b40a-4969-b911-e70914629dc9",
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"metadata": {
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"name": "stderr",
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"text": [
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"/env/lib/python3.12/site-packages/xarray/groupers.py:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
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" self.index_grouper = pd.Grouper(\n"
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"source": [
|
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"average_vh = calculate_average(dsvh, time_pattern='1M')\n",
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"progress(average_vh)"
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"outputs": [
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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:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
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" self.index_grouper = pd.Grouper(\n"
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},
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{
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"data": {
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"progress(average_vv)"
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{
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"text": [
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"CPU times: user 764 ms, sys: 635 ms, total: 1.4 s\n",
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|
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" 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.DataArray 'vv' (time: 1, y: 8874, x: 9902)> Size: 351MB\n",
|
|
"array([[[0.19917326, 0.2036858 , 0.20597248, ..., 0.23972352,\n",
|
|
" 0.23907872, 0.23844711],\n",
|
|
" [0.19917326, 0.2036858 , 0.20597248, ..., 0.25530738,\n",
|
|
" 0.25576517, 0.25507364],\n",
|
|
" [0.20632547, 0.20605431, 0.2029686 , ..., 0.28056654,\n",
|
|
" 0.28108242, 0.27629215],\n",
|
|
" ...,\n",
|
|
" [0.06841445, 0.07078951, 0.07297197, ..., 0.06806423,\n",
|
|
" 0.06924058, 0.06730109],\n",
|
|
" [0.07230996, 0.07190628, 0.07310792, ..., 0.06789783,\n",
|
|
" 0.06905217, 0.06681374],\n",
|
|
" [0.07501791, 0.07259221, 0.07343484, ..., 0.06789783,\n",
|
|
" 0.06905217, 0.06681374]]], dtype=float32)\n",
|
|
"Coordinates:\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",
|
|
" * time (time) datetime64[ns] 8B 2023-03-31\n",
|
|
"Attributes:\n",
|
|
" units: intensity\n",
|
|
" nodata: nan\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.DataArray</div><div class='xr-array-name'>'vv'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</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-b08ca762-5e43-4f6a-8a69-2f6a7e643e7b' class='xr-array-in' type='checkbox' checked><label for='section-b08ca762-5e43-4f6a-8a69-2f6a7e643e7b' 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>0.1992 0.2037 0.206 0.206 0.2044 ... 0.06654 0.0679 0.06905 0.06681</span></div><div class='xr-array-data'><pre>array([[[0.19917326, 0.2036858 , 0.20597248, ..., 0.23972352,\n",
|
|
" 0.23907872, 0.23844711],\n",
|
|
" [0.19917326, 0.2036858 , 0.20597248, ..., 0.25530738,\n",
|
|
" 0.25576517, 0.25507364],\n",
|
|
" [0.20632547, 0.20605431, 0.2029686 , ..., 0.28056654,\n",
|
|
" 0.28108242, 0.27629215],\n",
|
|
" ...,\n",
|
|
" [0.06841445, 0.07078951, 0.07297197, ..., 0.06806423,\n",
|
|
" 0.06924058, 0.06730109],\n",
|
|
" [0.07230996, 0.07190628, 0.07310792, ..., 0.06789783,\n",
|
|
" 0.06905217, 0.06681374],\n",
|
|
" [0.07501791, 0.07259221, 0.07343484, ..., 0.06789783,\n",
|
|
" 0.06905217, 0.06681374]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-ea8ad5ca-a0c6-4598-848b-9c5d078a5755' class='xr-section-summary-in' type='checkbox' checked><label for='section-ea8ad5ca-a0c6-4598-848b-9c5d078a5755' 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'>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-573d5235-d7af-41c7-97fb-bc9839767964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-573d5235-d7af-41c7-97fb-bc9839767964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73c740c7-9450-4a8d-8063-256a51294b42' class='xr-var-data-in' type='checkbox'><label for='data-73c740c7-9450-4a8d-8063-256a51294b42' 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-3ccab7b3-5167-4de6-9099-d9a19bb73a8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ccab7b3-5167-4de6-9099-d9a19bb73a8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-168c404e-4368-4353-bcc7-2e4b3a5551ad' class='xr-var-data-in' type='checkbox'><label for='data-168c404e-4368-4353-bcc7-2e4b3a5551ad' 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-339ea60e-6367-4e33-ba2f-35c22cb1b4cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-339ea60e-6367-4e33-ba2f-35c22cb1b4cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2be5dab8-b289-4bf2-a483-ff61ac4ec949' class='xr-var-data-in' type='checkbox'><label for='data-2be5dab8-b289-4bf2-a483-ff61ac4ec949' 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><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'>2023-03-31</div><input id='attrs-37f61892-5d5e-423b-ab55-a7698ad8516b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37f61892-5d5e-423b-ab55-a7698ad8516b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14769d85-18f6-4c41-94da-ed3a103c04c8' class='xr-var-data-in' type='checkbox'><label for='data-14769d85-18f6-4c41-94da-ed3a103c04c8' 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(['2023-03-31T00:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9ddada2-c727-4c5f-9b26-fdede7cb264b' class='xr-section-summary-in' type='checkbox' ><label for='section-e9ddada2-c727-4c5f-9b26-fdede7cb264b' 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>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f8fc5907-be31-4e6f-af4e-08381a642184' class='xr-index-data-in' type='checkbox'/><label for='index-f8fc5907-be31-4e6f-af4e-08381a642184' 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><input type='checkbox' disabled/><label></label><input id='index-2e1737e1-abe5-46a8-9202-8c1fad434803' class='xr-index-data-in' type='checkbox'/><label for='index-2e1737e1-abe5-46a8-9202-8c1fad434803' 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><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0a482f91-b68f-4485-9c4d-4fe9442103f4' class='xr-index-data-in' type='checkbox'/><label for='index-0a482f91-b68f-4485-9c4d-4fe9442103f4' 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(['2023-03-31'], dtype='datetime64[ns]', name='time', freq='ME'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c5f1e4db-6685-4503-aab6-fb9cc05569c2' class='xr-section-summary-in' type='checkbox' checked><label for='section-c5f1e4db-6685-4503-aab6-fb9cc05569c2' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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></li></ul></div></div>"
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],
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"text/plain": [
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"<xarray.DataArray 'vv' (time: 1, y: 8874, x: 9902)> Size: 351MB\n",
|
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"array([[[0.19917326, 0.2036858 , 0.20597248, ..., 0.23972352,\n",
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" 0.23907872, 0.23844711],\n",
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" [0.19917326, 0.2036858 , 0.20597248, ..., 0.25530738,\n",
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"Coordinates:\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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" * time (time) datetime64[ns] 8B 2023-03-31\n",
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"Attributes:\n",
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" units: intensity\n",
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" nodata: nan\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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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
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"%%time\n",
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"average_vh.compute()\n",
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"average_vv.compute()"
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]
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},
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{
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"execution_count": 8,
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"outputs": [
|
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{
|
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"name": "stdout",
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"output_type": "stream",
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"text": [
|
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"No datasets require offset correction\n",
|
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"The valid_data_mask and scale (no offset) have been applied to the reflectance bands\n"
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".xr-header > div,\n",
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|
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|
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|
"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: 9GB\n",
|
|
"Dimensions: (time: 12, y: 8874, x: 9902)\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 96B 2023-03-01T03:35:09.182000 ... 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 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" nir (time, y, x) float32 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
|
" scl (time, y, x) uint8 1GB 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-e71382f4-a8f2-4d68-ae0f-d0c0df04b406' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e71382f4-a8f2-4d68-ae0f-d0c0df04b406' 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>: 12</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-e6032e8a-e77c-46ad-8b38-b407ce0c0d97' class='xr-section-summary-in' type='checkbox' checked><label for='section-e6032e8a-e77c-46ad-8b38-b407ce0c0d97' 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'>2023-03-01T03:35:09.182000 ... 2...</div><input id='attrs-baf3b878-fee7-4c8c-8f7e-b42f758aac99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baf3b878-fee7-4c8c-8f7e-b42f758aac99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84458791-a1fc-469b-830c-bbfc97461e3e' class='xr-var-data-in' type='checkbox'><label for='data-84458791-a1fc-469b-830c-bbfc97461e3e' 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(['2023-03-01T03:35:09.182000000', '2023-03-03T03:25:17.841000000',\n",
|
|
" '2023-03-06T03:35:14.717000000', '2023-03-08T03:25:12.032000000',\n",
|
|
" '2023-03-11T03:35:07.230000000', '2023-03-13T03:25:20.837000000',\n",
|
|
" '2023-03-16T03:35:15.940000000', '2023-03-18T03:25:14.467000000',\n",
|
|
" '2023-03-21T03:35:10.279000000', '2023-03-23T03:25:18.795000000',\n",
|
|
" '2023-03-26T03:35:14.570000000', '2023-03-28T03:25:14.536000000'],\n",
|
|
" 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-557266f6-73d0-4829-8277-e19a349006ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-557266f6-73d0-4829-8277-e19a349006ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-861de701-ed0f-4801-8ec9-cae0c34a0628' class='xr-var-data-in' type='checkbox'><label for='data-861de701-ed0f-4801-8ec9-cae0c34a0628' 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-5d51e9c9-f7f9-4394-a200-cc35b61b8925' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d51e9c9-f7f9-4394-a200-cc35b61b8925' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e7b4e4a-8090-422d-bc59-049055dba504' class='xr-var-data-in' type='checkbox'><label for='data-8e7b4e4a-8090-422d-bc59-049055dba504' 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-5fb78602-b659-4bbb-bbca-f9e4236c60bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fb78602-b659-4bbb-bbca-f9e4236c60bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efa0eebd-58f0-4276-8004-07b9680a4cf2' class='xr-var-data-in' type='checkbox'><label for='data-efa0eebd-58f0-4276-8004-07b9680a4cf2' 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-dc2e225e-6cc9-43a8-85ae-4e2c34b0bb33' class='xr-section-summary-in' type='checkbox' checked><label for='section-dc2e225e-6cc9-43a8-85ae-4e2c34b0bb33' 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-168a2c21-4c2c-4306-a6df-ab85e8511295' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-168a2c21-4c2c-4306-a6df-ab85e8511295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0356f594-527a-4863-825e-72e329f67274' class='xr-var-data-in' type='checkbox'><label for='data-0356f594-527a-4863-825e-72e329f67274' 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> 3.93 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (12, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 300 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",
|
|
" <svg width=\"194\" height=\"172\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
|
|
" <line x1=\"10\" y1=\"49\" x2=\"24\" y2=\"64\" />\n",
|
|
" <line x1=\"10\" y1=\"74\" x2=\"24\" y2=\"89\" />\n",
|
|
" <line x1=\"10\" y1=\"99\" x2=\"24\" y2=\"114\" />\n",
|
|
" <line x1=\"10\" y1=\"107\" x2=\"24\" y2=\"122\" 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=\"11\" y1=\"1\" x2=\"11\" y2=\"108\" />\n",
|
|
" <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"110\" />\n",
|
|
" <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"111\" />\n",
|
|
" <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"112\" />\n",
|
|
" <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"113\" />\n",
|
|
" <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"115\" />\n",
|
|
" <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"116\" />\n",
|
|
" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\n",
|
|
" <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"118\" />\n",
|
|
" <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"119\" />\n",
|
|
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"121\" />\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,122.49050867486044 10.0,107.54191072510604\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
|
|
" <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
|
|
" <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
|
|
" <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
|
|
" <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
|
|
" <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
|
|
" <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
|
|
" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
|
|
" <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
|
|
" <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
|
|
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Vertical lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
|
|
" <line x1=\"59\" y1=\"0\" x2=\"74\" y2=\"14\" />\n",
|
|
" <line x1=\"84\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
|
|
" <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
|
|
" <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
|
|
" <line x1=\"24\" y1=\"64\" x2=\"144\" y2=\"64\" />\n",
|
|
" <line x1=\"24\" y1=\"89\" x2=\"144\" y2=\"89\" />\n",
|
|
" <line x1=\"24\" y1=\"114\" x2=\"144\" y2=\"114\" />\n",
|
|
" <line x1=\"24\" y1=\"122\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Vertical lines -->\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"122\" />\n",
|
|
" <line x1=\"74\" y1=\"14\" x2=\"74\" y2=\"122\" />\n",
|
|
" <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"122\" />\n",
|
|
" <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"122\" />\n",
|
|
" <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <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",
|
|
"\n",
|
|
" <!-- Text -->\n",
|
|
" <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)\">12</text>\n",
|
|
"</svg>\n",
|
|
" </td>\n",
|
|
" </tr>\n",
|
|
"</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-2acae4d9-2964-4adb-8ab0-c8cb9d2ca215' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acae4d9-2964-4adb-8ab0-c8cb9d2ca215' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da6c0822-527d-4cf4-8860-f8a3dd42b656' class='xr-var-data-in' type='checkbox'><label for='data-da6c0822-527d-4cf4-8860-f8a3dd42b656' 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",
|
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" <th> Chunk </th>\n",
|
|
" </tr>\n",
|
|
" </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> 3.93 GiB </td>\n",
|
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" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (12, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 300 chunks in 8 graph layers </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <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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"</svg>\n",
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|
" </td>\n",
|
|
" </tr>\n",
|
|
"</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-212aed99-d735-45c3-a418-59881ff49cf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-212aed99-d735-45c3-a418-59881ff49cf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a27f74f4-df79-4d88-9e76-561643b1a71a' class='xr-var-data-in' type='checkbox'><label for='data-a27f74f4-df79-4d88-9e76-561643b1a71a' 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> 0.98 GiB </td>\n",
|
|
" <td> 4.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (12, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 300 chunks in 1 graph layer </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Data type </th>\n",
|
|
" <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
" </table>\n",
|
|
" </td>\n",
|
|
" <td>\n",
|
|
" <svg width=\"194\" height=\"172\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
|
|
"\n",
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|
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"\n",
|
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|
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"\n",
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|
" <!-- Horizontal lines -->\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",
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" <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",
|
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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)\">12</text>\n",
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"</svg>\n",
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" </td>\n",
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" </tr>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5404426-da99-4362-99fc-692206858c05' class='xr-section-summary-in' type='checkbox' ><label for='section-a5404426-da99-4362-99fc-692206858c05' 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><input type='checkbox' disabled/><label></label><input id='index-29de3431-c459-4353-b2d5-2cc0fc89ca63' class='xr-index-data-in' type='checkbox'/><label for='index-29de3431-c459-4353-b2d5-2cc0fc89ca63' 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(['2023-03-01 03:35:09.182000', '2023-03-03 03:25:17.841000',\n",
|
|
" '2023-03-06 03:35:14.717000', '2023-03-08 03:25:12.032000',\n",
|
|
" '2023-03-11 03:35:07.230000', '2023-03-13 03:25:20.837000',\n",
|
|
" '2023-03-16 03:35:15.940000', '2023-03-18 03:25:14.467000',\n",
|
|
" '2023-03-21 03:35:10.279000', '2023-03-23 03:25:18.795000',\n",
|
|
" '2023-03-26 03:35:14.570000', '2023-03-28 03:25:14.536000'],\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><input type='checkbox' disabled/><label></label><input id='index-443a1276-f942-41b5-8b85-1af0fc651677' class='xr-index-data-in' type='checkbox'/><label for='index-443a1276-f942-41b5-8b85-1af0fc651677' 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><input type='checkbox' disabled/><label></label><input id='index-4016bfe6-c94e-4014-8692-4ee4b94cfbf1' class='xr-index-data-in' type='checkbox'/><label for='index-4016bfe6-c94e-4014-8692-4ee4b94cfbf1' 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-f3cdf257-ea97-4fc5-9a51-fb3ed55ae044' class='xr-section-summary-in' type='checkbox' checked><label for='section-f3cdf257-ea97-4fc5-9a51-fb3ed55ae044' 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": [
|
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"<xarray.Dataset> Size: 9GB\n",
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"Dimensions: (time: 12, y: 8874, x: 9902)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 96B 2023-03-01T03:35:09.182000 ... 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 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
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" nir (time, y, x) float32 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
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" scl (time, y, x) uint8 1GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
|
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"Attributes:\n",
|
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" crs: EPSG:32648\n",
|
|
" 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": [
|
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"data_sen2 = load_data_sen2(dc, date_range, coordinates)\n",
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"notebook_utils.heading(notebook_utils.xarray_object_size(data_sen2))\n",
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"display(data_sen2)"
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]
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{
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"metadata": {
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"outputs": [
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{
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"data": {
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"text/plain": [
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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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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CPU times: user 58.6 ms, sys: 480 μs, total: 59.1 ms\n",
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"Wall time: 57.5 ms\n"
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]
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},
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{
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"text/plain": [
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"source": [
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"%%time\n",
|
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"result = mask_cloud(data_sen2)\n",
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|
|
" 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.DataArray 'NDVI' (time: 12, y: 8874, x: 9902)> Size: 4GB\n",
|
|
"dask.array<truediv, shape=(12, 8874, 9902), dtype=float32, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray>\n",
|
|
"Coordinates:\n",
|
|
" * time (time) datetime64[ns] 96B 2023-03-01T03:35:09.182000 ... 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>: 12</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-290f86c8-8b82-4ed8-8925-73b7d4268bbf' class='xr-array-in' type='checkbox' checked><label for='section-290f86c8-8b82-4ed8-8925-73b7d4268bbf' 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> 3.93 GiB </td>\n",
|
|
" <td> 16.00 MiB </td>\n",
|
|
" </tr>\n",
|
|
" \n",
|
|
" <tr>\n",
|
|
" <th> Shape </th>\n",
|
|
" <td> (12, 8874, 9902) </td>\n",
|
|
" <td> (1, 2048, 2048) </td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th> Dask graph </th>\n",
|
|
" <td colspan=\"2\"> 300 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=\"194\" height=\"172\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
|
|
" <line x1=\"10\" y1=\"49\" x2=\"24\" y2=\"64\" />\n",
|
|
" <line x1=\"10\" y1=\"74\" x2=\"24\" y2=\"89\" />\n",
|
|
" <line x1=\"10\" y1=\"99\" x2=\"24\" y2=\"114\" />\n",
|
|
" <line x1=\"10\" y1=\"107\" x2=\"24\" y2=\"122\" 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=\"11\" y1=\"1\" x2=\"11\" y2=\"108\" />\n",
|
|
" <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"110\" />\n",
|
|
" <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"111\" />\n",
|
|
" <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"112\" />\n",
|
|
" <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"113\" />\n",
|
|
" <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"115\" />\n",
|
|
" <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"116\" />\n",
|
|
" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\n",
|
|
" <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"118\" />\n",
|
|
" <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"119\" />\n",
|
|
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"121\" />\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,122.49050867486044 10.0,107.54191072510604\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
|
|
" <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
|
|
" <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
|
|
" <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
|
|
" <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
|
|
" <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
|
|
" <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
|
|
" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
|
|
" <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
|
|
" <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
|
|
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Vertical lines -->\n",
|
|
" <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
|
|
" <line x1=\"59\" y1=\"0\" x2=\"74\" y2=\"14\" />\n",
|
|
" <line x1=\"84\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
|
|
" <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
|
|
" <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
|
|
"\n",
|
|
" <!-- Horizontal lines -->\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
|
|
" <line x1=\"24\" y1=\"64\" x2=\"144\" y2=\"64\" />\n",
|
|
" <line x1=\"24\" y1=\"89\" x2=\"144\" y2=\"89\" />\n",
|
|
" <line x1=\"24\" y1=\"114\" x2=\"144\" y2=\"114\" />\n",
|
|
" <line x1=\"24\" y1=\"122\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Vertical lines -->\n",
|
|
" <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
" <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"122\" />\n",
|
|
" <line x1=\"74\" y1=\"14\" x2=\"74\" y2=\"122\" />\n",
|
|
" <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"122\" />\n",
|
|
" <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"122\" />\n",
|
|
" <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"122\" style=\"stroke-width:2\" />\n",
|
|
"\n",
|
|
" <!-- Colored Rectangle -->\n",
|
|
" <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",
|
|
"\n",
|
|
" <!-- Text -->\n",
|
|
" <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)\">12</text>\n",
|
|
"</svg>\n",
|
|
" </td>\n",
|
|
" </tr>\n",
|
|
"</table></div></div></li><li class='xr-section-item'><input id='section-045b82f7-14fb-479a-b99e-59518aaa8dac' class='xr-section-summary-in' type='checkbox' checked><label for='section-045b82f7-14fb-479a-b99e-59518aaa8dac' 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'>2023-03-01T03:35:09.182000 ... 2...</div><input id='attrs-3ae849c4-f4fc-4de5-905b-3dbf38e4fc6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ae849c4-f4fc-4de5-905b-3dbf38e4fc6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e3ab0b7-f15f-4de6-af9c-cf29161aefb9' class='xr-var-data-in' type='checkbox'><label for='data-6e3ab0b7-f15f-4de6-af9c-cf29161aefb9' 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(['2023-03-01T03:35:09.182000000', '2023-03-03T03:25:17.841000000',\n",
|
|
" '2023-03-06T03:35:14.717000000', '2023-03-08T03:25:12.032000000',\n",
|
|
" '2023-03-11T03:35:07.230000000', '2023-03-13T03:25:20.837000000',\n",
|
|
" '2023-03-16T03:35:15.940000000', '2023-03-18T03:25:14.467000000',\n",
|
|
" '2023-03-21T03:35:10.279000000', '2023-03-23T03:25:18.795000000',\n",
|
|
" '2023-03-26T03:35:14.570000000', '2023-03-28T03:25:14.536000000'],\n",
|
|
" 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-4a04d986-8a03-460b-8c61-51c4a7f5b746' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a04d986-8a03-460b-8c61-51c4a7f5b746' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1aabb136-dfe2-40f9-8a7c-bf752f9ca6a1' class='xr-var-data-in' type='checkbox'><label for='data-1aabb136-dfe2-40f9-8a7c-bf752f9ca6a1' 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-2a4bc434-0aa6-4c76-9d85-c52a41c9be39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a4bc434-0aa6-4c76-9d85-c52a41c9be39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d7e1cb0-f15a-418a-b643-5545177b2d64' class='xr-var-data-in' type='checkbox'><label for='data-9d7e1cb0-f15a-418a-b643-5545177b2d64' 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-d4ce968e-9a4c-499e-a9d0-9bdf7d1f00ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4ce968e-9a4c-499e-a9d0-9bdf7d1f00ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a609810-7e3e-4bfe-a0c3-9f004650f0f1' class='xr-var-data-in' type='checkbox'><label for='data-5a609810-7e3e-4bfe-a0c3-9f004650f0f1' 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-e701ee5f-91b4-4e63-b8b2-f5e9167aa36c' class='xr-section-summary-in' type='checkbox' ><label for='section-e701ee5f-91b4-4e63-b8b2-f5e9167aa36c' 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><input type='checkbox' disabled/><label></label><input id='index-3523e5e9-34b5-41bd-93ea-e46ea9b0a482' class='xr-index-data-in' type='checkbox'/><label for='index-3523e5e9-34b5-41bd-93ea-e46ea9b0a482' 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(['2023-03-01 03:35:09.182000', '2023-03-03 03:25:17.841000',\n",
|
|
" '2023-03-06 03:35:14.717000', '2023-03-08 03:25:12.032000',\n",
|
|
" '2023-03-11 03:35:07.230000', '2023-03-13 03:25:20.837000',\n",
|
|
" '2023-03-16 03:35:15.940000', '2023-03-18 03:25:14.467000',\n",
|
|
" '2023-03-21 03:35:10.279000', '2023-03-23 03:25:18.795000',\n",
|
|
" '2023-03-26 03:35:14.570000', '2023-03-28 03:25:14.536000'],\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><input type='checkbox' disabled/><label></label><input id='index-c7d4eb5e-30d1-4611-a4c8-abd2b1530f36' class='xr-index-data-in' type='checkbox'/><label for='index-c7d4eb5e-30d1-4611-a4c8-abd2b1530f36' 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><input type='checkbox' disabled/><label></label><input id='index-ca95347a-6c89-4d04-a65e-6d0be72d7873' class='xr-index-data-in' type='checkbox'/><label for='index-ca95347a-6c89-4d04-a65e-6d0be72d7873' 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",
|
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" 554865.0, 554875.0, 554885.0,\n",
|
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" ...\n",
|
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" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
|
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" 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-9471386b-8aa0-43bb-b60b-0387cd694fe6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9471386b-8aa0-43bb-b60b-0387cd694fe6' 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: 12, y: 8874, x: 9902)> Size: 4GB\n",
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"dask.array<truediv, shape=(12, 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] 96B 2023-03-01T03:35:09.182000 ... 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"
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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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"source": [
|
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"# calculate NDVI\n",
|
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"dsNDVI = calculate_indices(result, index='NDVI', satellite_mission='s2')\n",
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"ndvi = dsNDVI[\"NDVI\"]\n",
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"display(ndvi)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "f94969d8-d04f-4495-af63-6323d5c730ef",
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"metadata": {
|
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"tags": []
|
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},
|
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"outputs": [
|
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{
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"name": "stdout",
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"output_type": "stream",
|
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"text": [
|
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"CPU times: user 24.2 ms, sys: 0 ns, total: 24.2 ms\n",
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"Wall time: 23.3 ms\n"
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]
|
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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:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
|
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" self.index_grouper = pd.Grouper(\n"
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]
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},
|
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{
|
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"data": {
|
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"application/vnd.jupyter.widget-view+json": {
|
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"model_id": "51e16a0b9fcc432daddf5b30356f07b6",
|
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"version_major": 2,
|
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"version_minor": 0
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},
|
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"text/plain": [
|
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"VBox()"
|
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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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"2025-01-18 10:49:45,082 - tornado.application - ERROR - Exception in callback functools.partial(<bound method IOLoop._discard_future_result of <tornado.platform.asyncio.AsyncIOMainLoop object at 0x7f40e8c330e0>>, <Task finished name='Task-412' coro=<MultiProgressBar.listen() done, defined at /env/lib/python3.12/site-packages/distributed/diagnostics/progressbar.py:281> exception=CommClosedError('in <TLS (closed) local=tls://10.0.74.241:58968 remote=gateway://traefik-dask-gateway.easihub:80/easihub.8daaa179e4964dc7b211b4302753bf26>: Stream is closed')>)\n",
|
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"Traceback (most recent call last):\n",
|
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" File \"/env/lib/python3.12/site-packages/distributed/comm/tcp.py\", line 225, in read\n",
|
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" frames_nosplit_nbytes_bin = await stream.read_bytes(fmt_size)\n",
|
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
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"tornado.iostream.StreamClosedError: Stream is closed\n",
|
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"\n",
|
|
"The above exception was the direct cause of the following exception:\n",
|
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"\n",
|
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"Traceback (most recent call last):\n",
|
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" File \"/env/lib/python3.12/site-packages/tornado/ioloop.py\", line 750, in _run_callback\n",
|
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" ret = callback()\n",
|
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" ^^^^^^^^^^\n",
|
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" File \"/env/lib/python3.12/site-packages/tornado/ioloop.py\", line 774, in _discard_future_result\n",
|
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" future.result()\n",
|
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" File \"/env/lib/python3.12/site-packages/distributed/diagnostics/progressbar.py\", line 321, in listen\n",
|
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" response = await self.comm.read(\n",
|
|
" ^^^^^^^^^^^^^^^^^^^^^\n",
|
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" File \"/env/lib/python3.12/site-packages/distributed/comm/tcp.py\", line 236, in read\n",
|
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" convert_stream_closed_error(self, e)\n",
|
|
" File \"/env/lib/python3.12/site-packages/distributed/comm/tcp.py\", line 142, in convert_stream_closed_error\n",
|
|
" raise CommClosedError(f\"in {obj}: {exc}\") from exc\n",
|
|
"distributed.comm.core.CommClosedError: in <TLS (closed) local=tls://10.0.74.241:58968 remote=gateway://traefik-dask-gateway.easihub:80/easihub.8daaa179e4964dc7b211b4302753bf26>: Stream is closed\n"
|
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]
|
|
}
|
|
],
|
|
"source": [
|
|
"%%time\n",
|
|
"# calculate average NDVI\n",
|
|
"average_ndvi = calculate_average (ndvi,time_pattern=\"1M\")\n",
|
|
"progress(average_ndvi)"
|
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]
|
|
},
|
|
{
|
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"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "06bd6bda-aa8b-44a0-9c8a-d17ccf5b86c3",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
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"outputs": [],
|
|
"source": [
|
|
"average_ndvi = average_ndvi.compute()"
|
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]
|
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},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 13,
|
|
"id": "af4fe58b-358a-42f8-b9a4-f3547d2c230b",
|
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"metadata": {
|
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"tags": []
|
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},
|
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"outputs": [
|
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{
|
|
"data": {
|
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"text/plain": [
|
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"<matplotlib.image.AxesImage at 0x7f3fd2bcbef0>"
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]
|
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},
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
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},
|
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{
|
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.imshow(average_ndvi.isel(time=0))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "93929102-3ab5-4609-b9e9-dfafd3f32bcd",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "81220350-c319-4ed8-831c-5150c2a4e163",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3a1a254b-78f6-4783-accc-d7b898bf1e2a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "edab3c39-1d85-4ef5-831c-f64070c31355",
|
|
"metadata": {},
|
|
"source": [
|
|
"###########################################CALCULATE ACCURACY##########################################"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 68,
|
|
"id": "c83d666e-139c-4215-909e-32c535532b19",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fill_nan_model = joblib.load('output/regressors/max/gb_cloud.pkl')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 64,
|
|
"id": "044303a9-e620-46e7-953f-e7f9b3ef91c6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"mask = ~np.isnan(average_ndvi)\n",
|
|
"data = np.stack([average_vh.values[mask], average_vv.values[mask]], axis=1)\n",
|
|
"label = average_ndvi.values[mask]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 65,
|
|
"id": "c38dda57-604f-4705-a282-eaec22f3ea12",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(1000, 2)\n",
|
|
"(1000,)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"num_samples = 1000\n",
|
|
"\n",
|
|
"# Generate random indices\n",
|
|
"random_indices = np.random.choice(data.shape[0], size=num_samples, replace=False)\n",
|
|
"\n",
|
|
"# Subset the data using the random indices\n",
|
|
"x = data[random_indices]\n",
|
|
"y = label[random_indices]\n",
|
|
"\n",
|
|
"# Check the new shape\n",
|
|
"print(x.shape)\n",
|
|
"print(y.shape)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 66,
|
|
"id": "89039d87-49cf-4cac-8020-350c516d9332",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# np.savez(\"input/saved_datasets/test_aug.npz\", data=x, label=y)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 69,
|
|
"id": "8cdc9d56-6e4a-4da9-9280-e632a1434f12",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"MSE: 0.04130829795907553\n",
|
|
"MAE: 0.1617092873613522\n",
|
|
"R^2: 0.6916845336468708\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"preds = fill_nan_model.predict(x)\n",
|
|
"mse = mean_squared_error(y, preds)\n",
|
|
"mae = mean_absolute_error(y, preds)\n",
|
|
"r2 = r2_score(y, preds)\n",
|
|
"print(f\"MSE: {mse}\")\n",
|
|
"print(f\"MAE: {mae}\")\n",
|
|
"print(f\"R^2: {r2}\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "859e29ca-731c-4877-ace3-033f828185f7",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "115ac772-ced4-4671-aeb3-9ee92aeef230",
|
|
"metadata": {},
|
|
"source": [
|
|
"#######################################DRAW GRAPH WITH DOTS##############################################"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0863baf5-5b38-4abe-bb9d-455dfcb188c6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "73fb2cc1-71cd-4361-a876-f2ad35203848",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "1be81b66-9ee6-4b4c-b511-3a57a541be31",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>No</th>\n",
|
|
" <th>X</th>\n",
|
|
" <th>Y</th>\n",
|
|
" <th>LU2022</th>\n",
|
|
" <th>Hientrang</th>\n",
|
|
" <th>HT_code</th>\n",
|
|
" <th>geometry</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>603860.819</td>\n",
|
|
" <td>1081162.862</td>\n",
|
|
" <td>Pomelo</td>\n",
|
|
" <td>CLN</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>POINT (603860.819 1081162.862)</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>2.0</td>\n",
|
|
" <td>601306.410</td>\n",
|
|
" <td>1082782.940</td>\n",
|
|
" <td>Pomelo</td>\n",
|
|
" <td>CLN</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>POINT (601306.41 1082782.94)</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>3.0</td>\n",
|
|
" <td>601084.510</td>\n",
|
|
" <td>1081351.870</td>\n",
|
|
" <td>Pomelo</td>\n",
|
|
" <td>CLN</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>POINT (601084.51 1081351.87)</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>602193.760</td>\n",
|
|
" <td>1079205.220</td>\n",
|
|
" <td>Pomelo</td>\n",
|
|
" <td>CLN</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>POINT (602193.76 1079205.22)</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>5.0</td>\n",
|
|
" <td>602459.000</td>\n",
|
|
" <td>1080946.000</td>\n",
|
|
" <td>Pomelo</td>\n",
|
|
" <td>CLN</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>POINT (602459 1080946)</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" No X Y LU2022 Hientrang HT_code \\\n",
|
|
"0 1.0 603860.819 1081162.862 Pomelo CLN 3 \n",
|
|
"1 2.0 601306.410 1082782.940 Pomelo CLN 3 \n",
|
|
"2 3.0 601084.510 1081351.870 Pomelo CLN 3 \n",
|
|
"3 4.0 602193.760 1079205.220 Pomelo CLN 3 \n",
|
|
"4 5.0 602459.000 1080946.000 Pomelo CLN 3 \n",
|
|
"\n",
|
|
" geometry \n",
|
|
"0 POINT (603860.819 1081162.862) \n",
|
|
"1 POINT (601306.41 1082782.94) \n",
|
|
"2 POINT (601084.51 1081351.87) \n",
|
|
"3 POINT (602193.76 1079205.22) \n",
|
|
"4 POINT (602459 1080946) "
|
|
]
|
|
},
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"train_path = \"input/train_points/1130/ST_1130_points.shp\" \n",
|
|
"# train_path = \"train/updated_data/ThuanHoa_DKS_Kappa.shp\"\n",
|
|
"ground_points = load_data_geo(train_path)\n",
|
|
"ground_points.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 57,
|
|
"id": "a24a5b13-a620-4154-bf17-6d277c8d6eb8",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fill_nan_model = joblib.load('output/regressors/mean_no_negative/rf_cloud.pkl')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"id": "fa9191d7-6784-4e1d-a1dd-69a9dab56228",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"\n",
|
|
"def extract_data_with_HTcode(ground_points, average_ndvi, dsvh, dsvv):\n",
|
|
" datasets = {}\n",
|
|
" for idx, point in ground_points.iterrows():\n",
|
|
" \n",
|
|
" # Ensure each HT_code has its own dictionary\n",
|
|
" if point.HT_code not in datasets:\n",
|
|
" datasets[point.HT_code] = {'ndvi': [], 'vh': [], 'vv': []}\n",
|
|
" # Get the data for this point\n",
|
|
" ndvi_data = average_ndvi.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values\n",
|
|
" vh_data = dsvh.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values\n",
|
|
" vv_data = dsvv.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values\n",
|
|
" \n",
|
|
" # Append the data to the lists for this HT_code\n",
|
|
" datasets[point.HT_code]['ndvi'].append(ndvi_data)\n",
|
|
" datasets[point.HT_code]['vh'].append(vh_data)\n",
|
|
" datasets[point.HT_code]['vv'].append(vv_data)\n",
|
|
" \n",
|
|
" return datasets"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "069c9adb-1671-4470-93b2-abda9d855be4",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"data = extract_data_with_HTcode(ground_points, average_ndvi, average_vh, average_vv)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 361,
|
|
"id": "cabb6f91-ff1c-43a5-b02d-d83266e3a4c2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"index = 0"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 362,
|
|
"id": "0d6f0534-17c7-413a-9cdd-742c4a12b221",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(62,) (62, 2)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"ndvi = np.concatenate(data[index]['ndvi'])\n",
|
|
"vh = np.concatenate(data[index]['vh'])\n",
|
|
"vv = np.concatenate(data[index]['vv'])\n",
|
|
"X_pred = np.stack([vh, vv], axis=1)\n",
|
|
"print(ndvi.shape, X_pred.shape)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 363,
|
|
"id": "3d9375c0-6300-4aa5-8c8b-f36004f908eb",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(59,)"
|
|
]
|
|
},
|
|
"execution_count": 363,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"mask = ~np.isnan(ndvi)\n",
|
|
"nonan_ndvi = ndvi[mask]\n",
|
|
"nonan_ndvi.shape"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 357,
|
|
"id": "1a191ed6-d10a-49b9-aa43-d87509a050f6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(55, 2)"
|
|
]
|
|
},
|
|
"execution_count": 357,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pred_data = X_pred[mask]\n",
|
|
"pred_data.shape"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ef84d16b-afce-4527-bfd0-b8d5f7dfb2c8",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 349,
|
|
"id": "423a14e8-46e7-4741-bc19-4dbac6edd14d",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(75, 2)"
|
|
]
|
|
},
|
|
"execution_count": 349,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pred_data = pred_data[:75]\n",
|
|
"nonan_ndvi = nonan_ndvi[:75]\n",
|
|
"pred_data.shape"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 344,
|
|
"id": "9d0a8983-01ae-42b1-95d7-918219dcbcb3",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"preds = fill_nan_model.predict(pred_data)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 223,
|
|
"id": "6cb5be9a-9420-43ce-aa1b-6d98aef655f0",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# print(nonan_ndvi)\n",
|
|
"# print(preds)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 224,
|
|
"id": "02d51159-1654-4a44-9b30-1ee3f955538c",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"MAE: 0.062313261248912975\n",
|
|
"R^2: 0.3451370208505795\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"mae = mean_squared_error(nonan_ndvi, preds)\n",
|
|
"r2 = r2_score(preds, nonan_ndvi)\n",
|
|
"print(\"MAE: \", mae)\n",
|
|
"print(\"R^2: \", r2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b6402503-4e27-483d-94c5-052121e702f6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "74318d1a-6e4d-423b-ba2c-26f6f32cfd96",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"\n",
|
|
"# Create the scatter plot\n",
|
|
"plt.figure(figsize=(10, 6))\n",
|
|
"plt.scatter(nonan_ndvi, preds, color='blue', alpha=0.7, s=15)\n",
|
|
"plt.plot([-1, 1], [-1, 1], color='red', linestyle='--', label='y = x')\n",
|
|
"# plt.plot( color='red', linestyle='--', label='y = x')\n",
|
|
"# Set equal scaling and adjust x and y axis limits from -1 to 1\n",
|
|
"plt.gca().set_aspect('equal', adjustable='box')\n",
|
|
"# plt.xlim(-1, 1) # Set x-axis limits from -1 to 1\n",
|
|
"# plt.ylim(-1, 1) # Set y-axis limits from -1 to 1\n",
|
|
"\n",
|
|
"# Add minor ticks at intervals of 0.1\n",
|
|
"plt.xticks([i * 0.1 for i in range(-10, 11)], rotation=45)\n",
|
|
"plt.yticks([i * 0.1 for i in range(-10, 11)])\n",
|
|
"\n",
|
|
"plt.xlabel('Actual NDVI')\n",
|
|
"plt.ylabel('Predicted NDVI')\n",
|
|
"plt.title('Comparison between Actual and Predicted NDVI LUA TOM')\n",
|
|
"plt.legend()\n",
|
|
"plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n",
|
|
"plt.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3632b6f7-edd8-4a94-9f87-9484515465e1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"##############################LOOP OVER 7 HT ##############"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 58,
|
|
"id": "c949778a-1ac4-4287-8ab2-dbbd514eb849",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def draw_dots(nonan_ndvi, preds, label):\n",
|
|
" plt.figure(figsize=(10, 6))\n",
|
|
" plt.scatter(nonan_ndvi, preds, color='blue', alpha=0.7, s=15)\n",
|
|
" plt.plot([-1, 1], [-1, 1], color='red', linestyle='--', label='y = x')\n",
|
|
" # plt.plot( color='red', linestyle='--', label='y = x')\n",
|
|
" # Set equal scaling and adjust x and y axis limits from -1 to 1\n",
|
|
" plt.gca().set_aspect('equal', adjustable='box')\n",
|
|
" # plt.xlim(-1, 1) # Set x-axis limits from -1 to 1\n",
|
|
" # plt.ylim(-1, 1) # Set y-axis limits from -1 to 1\n",
|
|
" # Add minor ticks at intervals of 0.1\n",
|
|
" plt.xticks([i * 0.1 for i in range(-10, 11)], rotation=45)\n",
|
|
" plt.yticks([i * 0.1 for i in range(-10, 11)])\n",
|
|
" plt.xlabel('Actual NDVI')\n",
|
|
" plt.ylabel('Predicted NDVI')\n",
|
|
" plt.title('Comparison between Actual and Predicted NDVI ' + label) \n",
|
|
" plt.legend()\n",
|
|
" plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n",
|
|
" plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 59,
|
|
"id": "175499f0-891b-4cdf-a7d9-d957d46744e2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"labels = [\"LUA TOM\", \"LUA\", \"CHN\", \"CLN\", \"TS\", \"DXD\", \"RUNG\"]\n",
|
|
"def get_data(data, labels):\n",
|
|
" for index in range(0, 7):\n",
|
|
" ndvi = np.concatenate(data[index]['ndvi'])\n",
|
|
" vh = np.concatenate(data[index]['vh'])\n",
|
|
" vv = np.concatenate(data[index]['vv'])\n",
|
|
" X_pred = np.stack([vh, vv], axis=1)\n",
|
|
" mask = ~np.isnan(ndvi)\n",
|
|
" nonan_ndvi = ndvi[mask]\n",
|
|
" pred_data = X_pred[mask]\n",
|
|
" pred_data = pred_data[:75]\n",
|
|
" nonan_ndvi = nonan_ndvi[:75]\n",
|
|
" preds = fill_nan_model.predict(pred_data)\n",
|
|
" draw_dots(nonan_ndvi, preds, labels[index])\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 60,
|
|
"id": "a5127bb0-364e-48d6-a45b-3589019e63f7",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 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 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 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 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"get_data(data, labels)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "685a99cc-10f9-4ca9-8423-074ed1de817c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"for index in range(0, 7):\n",
|
|
" ndvi = np.concatenate(data[index]['ndvi'])\n",
|
|
" vh = np.concatenate(data[index]['vh'])\n",
|
|
" vv = np.concatenate(data[index]['vv'])\n",
|
|
"\n",
|
|
" mask = ~np.isnan(ndvi)\n",
|
|
" nonan_ndvi = ndvi[mask]\n",
|
|
" pred_data = X_pred[mask]\n",
|
|
" pred_data = pred_data[:75]\n",
|
|
" nonan_ndvi = nonan_ndvi[:75]\n",
|
|
" preds = fill_nan_model.predict(pred_data)\n",
|
|
" draw_dots(nonan_ndvi, preds)\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "978d596b-bc48-4491-8616-880f6661ea53",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0a15077a-b1da-4037-b28b-1871d0446d85",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f13c8c73-8c73-4561-82f4-6c0b0f7d7afc",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"###################################################################################################################"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "abf0ec42-817b-4806-aae5-fd34b2e10727",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"# Function to filter out NaN values for each 'ndvi' array in each HT_code\n",
|
|
"def filter_non_nan_ndvi(data):\n",
|
|
" filtered_data = {}\n",
|
|
" \n",
|
|
" for ht_code, attributes in data.items():\n",
|
|
" # Initialize lists to store filtered arrays for 'ndvi', 'vh', and 'vv'\n",
|
|
" filtered_ndvi = []\n",
|
|
" filtered_vh = []\n",
|
|
" filtered_vv = []\n",
|
|
" \n",
|
|
" # Iterate through each set of ndvi, vh, vv arrays\n",
|
|
" for ndvi, vh, vv in zip(attributes['ndvi'], attributes['vh'], attributes['vv']):\n",
|
|
" # Create masks to filter out NaN values based on 'ndvi' array\n",
|
|
" non_nan_mask = ~np.isnan(ndvi)\n",
|
|
" \n",
|
|
" # Filter the arrays based on the mask\n",
|
|
" filtered_ndvi.append(ndvi[non_nan_mask])\n",
|
|
" filtered_vh.append(vh[non_nan_mask])\n",
|
|
" filtered_vv.append(vv[non_nan_mask])\n",
|
|
" \n",
|
|
" # Only add if there are non-empty filtered values\n",
|
|
" filtered_data[ht_code] = {\n",
|
|
" 'ndvi': filtered_ndvi,\n",
|
|
" 'vh': filtered_vh,\n",
|
|
" 'vv': filtered_vv\n",
|
|
" }\n",
|
|
" \n",
|
|
" return filtered_data\n",
|
|
"\n",
|
|
"# Example usage\n",
|
|
"filtered_datasets = filter_non_nan_ndvi(data)\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e9bb9522-3aec-42b0-930a-cbc647d50d8f",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"filtered_datasets"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7b96cbbd-0b5f-4dc7-87c4-f960554409a8",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"# Set the range of indices you want to include\n",
|
|
"indices = range(0, 11) # Selects indices from 0 to 10\n",
|
|
"ht_code = 1\n",
|
|
"# Initialize empty lists to hold data for the selected range\n",
|
|
"X_list = []\n",
|
|
"y_list = []\n",
|
|
"\n",
|
|
"# Loop over the indices and collect data\n",
|
|
"for index in indices:\n",
|
|
" vh_data = filtered_datasets[ht_code]['vh'][index]\n",
|
|
" vv_data = filtered_datasets[ht_code]['vv'][index]\n",
|
|
" ndvi_data = filtered_datasets[ht_code]['ndvi'][index]\n",
|
|
" \n",
|
|
" # Stack VH and VV data for the current index\n",
|
|
" X = np.column_stack((vh_data, vv_data))\n",
|
|
" X_list.append(X)\n",
|
|
" y_list.append(ndvi_data)\n",
|
|
"\n",
|
|
"# Concatenate the lists to form the complete dataset\n",
|
|
"X_combined = np.concatenate(X_list, axis=0)\n",
|
|
"y_combined = np.concatenate(y_list, axis=0)\n",
|
|
"print(\"X shape:\", X_combined.shape)\n",
|
|
"print(\"y shape:\", y_combined.shape)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7508e5b2-d93c-466a-8a2b-6a01765348a2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"preds = fill_nan_model.predict(X_combined)\n",
|
|
"mse = mean_squared_error(y_combined, preds)\n",
|
|
"mae = mean_absolute_error(y_combined, preds)\n",
|
|
"r2 = r2_score(preds, y_combined)\n",
|
|
"print(f\"MSE: {mse}\")\n",
|
|
"print(f\"MAE: {mae}\")\n",
|
|
"print(f\"R^2: {r2}\")\n",
|
|
"# print(y)\n",
|
|
"# print(preds)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "94a2344f-9a3e-41f2-980b-661d247d9719",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"# Tạo biểu đồ với độ chia đồng nhất cho cả hai trục\n",
|
|
"# plt.figure(figsize=(10, 6))\n",
|
|
"plt.scatter(y_combined, preds, color='blue', alpha=0.7)\n",
|
|
"plt.plot([y_combined.min(), y_combined.max()],\n",
|
|
" [y_combined.min(), y_combined.max()], color='red', linestyle='--', label='y = x')\n",
|
|
"\n",
|
|
"# Thiết lập tỷ lệ các trục đồng nhất\n",
|
|
"plt.gca().set_aspect('equal', adjustable='box')\n",
|
|
"plt.xlim(y_combined.min() - 0.1, y_combined.max() + 0.1) # Điều chỉnh giới hạn trục x\n",
|
|
"plt.ylim(y_combined.min() - 0.1, y_combined.max() + 0.1) # Điều chỉnh giới hạn trục y\n",
|
|
"\n",
|
|
"plt.xlabel('Actual NDVI')\n",
|
|
"plt.ylabel(' predicted NDVI')\n",
|
|
"plt.title('Comparing between actual and predict NDVI')\n",
|
|
"plt.legend()\n",
|
|
"plt.grid(True)\n",
|
|
"plt.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d3996556-fb13-46c3-b1a2-01af71c1ca1b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "907302e4-724b-4555-812d-5badc4129cea",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "600e86b5-fcda-4d75-a488-af51f91a7215",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2b163c49-0b1e-481e-9f83-2fe9f4ba2c35",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e0a7e22b-c7bb-4b0d-b31a-f63cb2df015d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d6985c3b-1687-48d4-8322-d7b7bfa9deb2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7a416c4f-8c97-4069-8dd6-f17bded7783b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "76feffb6-b842-41ab-8289-561df2be66f1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9baa110e-4fd2-4f37-afae-b786b07a8030",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Assuming 'data' is the output of the function\n",
|
|
"ht_code = 1 # Replace with the specific HT code you want to extract\n",
|
|
"index = 3 # Replace with the index of the point you want to access (if multiple points are available)\n",
|
|
"\n",
|
|
"# Extract the NDVI, VH, and VV values for that HT_code\n",
|
|
"ndvi_values = data[ht_code]['ndvi'][index]\n",
|
|
"vh_values = data[ht_code]['vh'][index]\n",
|
|
"vv_values = data[ht_code]['vv'][index]\n",
|
|
"\n",
|
|
"# print(\"NDVI Values:\", ndvi_values)\n",
|
|
"# print(\"VH Values:\", vh_values)\n",
|
|
"# print(\"VV Values:\", vv_values)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "109e94bf-30a8-445d-b57a-6e71bb57dfa6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"print(data[ht_code]['vv'][index].shape)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "eb83b856-4772-4bc1-91d0-08fe7e229d7f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"input_data = np.column_stack((vh_values, vv_values))\n",
|
|
"\n",
|
|
"# Make predictions for each month\n",
|
|
"predicted_ndvi = fill_nan_model.predict(input_data)\n",
|
|
"\n",
|
|
"# Print the predictions\n",
|
|
"print(\"Predicted NDVI for each month:\", predicted_ndvi)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3a17c632-1f57-4d09-98ab-3b444da78749",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.plot(ndvi_values, marker='o', linestyle='-', color='b', label='Actual Values')\n",
|
|
"\n",
|
|
"# Plotting the adjusted values\n",
|
|
"plt.plot(predicted_ndvi, marker='x', linestyle='--', color='r', label='Predicted Values')\n",
|
|
"\n",
|
|
"# Adding labels and title\n",
|
|
"plt.xlabel('Index')\n",
|
|
"plt.ylabel('Values')\n",
|
|
"plt.title('Comparison: Actual vs predicted Values in CLN code over 24 months')\n",
|
|
"# Adding grid\n",
|
|
"plt.grid(True)\n",
|
|
"# Adding legend to differentiate the lines\n",
|
|
"plt.legend()\n",
|
|
"# # # Adjusting the limits of the axes\n",
|
|
"# plt.xlim(0, 75) # Example: Setting x-axis limits from 0 to 12\n",
|
|
"# plt.ylim(-1, 1) # Example: Setting y-axis limits from 0 to 1\n",
|
|
"# Display the plot\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "547eb119-d70f-4d60-bdd3-07f0b77ec577",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# cấu hình nhãn dữ liệu\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",
|
|
"}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a8e8ca9f-cf1e-4c4e-a692-a5eff9dfb380",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def draw(ndvi_values, predicted_ndvi, name):\n",
|
|
" plt.plot(ndvi_values, marker='o', linestyle='-', color='b', label='Actual Values')\n",
|
|
" plt.plot(predicted_ndvi, marker='x', linestyle='--', color='r', label='Predicted Values')\n",
|
|
" # Adding labels and title\n",
|
|
" plt.xlabel('Index')\n",
|
|
" plt.ylabel('Values')\n",
|
|
" plt.title(f'Comparison: Actual vs predicted Values in {name} code over 24 months')\n",
|
|
" # Adding grid\n",
|
|
" plt.grid(True)\n",
|
|
" # Adding legend to differentiate the lines\n",
|
|
" plt.legend()\n",
|
|
" # # # Adjusting the limits of the axes\n",
|
|
" plt.xlim(0, 25) # Example: Setting x-axis limits from 0 to 12\n",
|
|
" plt.ylim(-1, 1) # Example: Setting y-axis limits from 0 to 1\n",
|
|
" # Display the plot\n",
|
|
" plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0a0d2657-ebeb-4b29-bfe2-84a5b2599087",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def show_images (ht_code, index, name):\n",
|
|
" ndvi_values = data[ht_code]['ndvi'][index]\n",
|
|
" vh_values = data[ht_code]['vh'][index]\n",
|
|
" vv_values = data[ht_code]['vv'][index]\n",
|
|
" input_data = np.column_stack((vh_values, vv_values))\n",
|
|
" predicted_ndvi = fill_nan_model.predict(input_data)\n",
|
|
" draw(ndvi_values, predicted_ndvi, name)\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f91bbc3c-a089-4cea-ad36-a99b4c5da22b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"for i in range(50):\n",
|
|
" show_images(1, i, 'TS')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c5d58692-d816-4940-8df7-c449e900c5fe",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "11626d33-c5b1-4e36-a9be-ee23fc8bd5d5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5681dda8-3573-48fb-8f0c-3c69a1706bc6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6a01e665-23e7-4c74-a99b-cea2c2e243bb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.plot(data[6]['ndvi'], marker='x', linestyle='--', color='b')\n",
|
|
" # Adding labels and title\n",
|
|
"plt.xlabel('Index')\n",
|
|
"plt.ylabel('Values')\n",
|
|
"plt.title(f'NDVI values')\n",
|
|
"# Adding grid\n",
|
|
"plt.grid(True)\n",
|
|
"# Adding legend to differentiate the lines\n",
|
|
"plt.legend()\n",
|
|
"# # # Adjusting the limits of the axes\n",
|
|
"# plt.xlim(0, 25) # Example: Setting x-axis limits from 0 to 12\n",
|
|
"plt.ylim(-1, 1) # Example: Setting y-axis limits from 0 to 1\n",
|
|
"# Display the plot\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "51629670-5cd3-49d0-8b8f-5dc60c7bc0ea",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "885dbd0b-0595-4c98-b037-e3b2cf7f18dc",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"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": "3.12.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|