basketballcantho/remote-sensing
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
Files
9194930c4ac0f0a74904cce524fc58cf9d46bfe6
remote-sensing/cloud_new/draw/test_result.ipynb
T

5252 lines
749 KiB
Plaintext
Executable File
Raw Blame History

{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "c61a1a84-ca37-4bfb-8935-a21312c11410",
"metadata": {
"tags": []
},
"outputs": [
{
"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 = 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",
" },\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 = 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 };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.holoviews_exec.v0+json": "",
"text/html": [
"<div id='eac966a2-0008-4cc7-8727-ed4e2755dacc'>\n",
" <div id=\"e8226bd2-4a9d-47f8-86c1-428040db0f03\" data-root-id=\"eac966a2-0008-4cc7-8727-ed4e2755dacc\" style=\"display: contents;\"></div>\n",
"</div>\n",
"<script type=\"application/javascript\">(function(root) {\n",
" var docs_json = {\"a52776e7-2a5f-4866-be93-1f791c23daea\":{\"version\":\"3.5.2\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"eac966a2-0008-4cc7-8727-ed4e2755dacc\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"6def5aa0-39ee-485e-a688-cf56a3092c93\",\"attributes\":{\"plot_id\":\"eac966a2-0008-4cc7-8727-ed4e2755dacc\",\"comm_id\":\"39b2811d78a74b388c1c7ab0e30df475\",\"client_comm_id\":\"62bae28c66c5448885a95efa75d95040\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
" var render_items = [{\"docid\":\"a52776e7-2a5f-4866-be93-1f791c23daea\",\"roots\":{\"eac966a2-0008-4cc7-8727-ed4e2755dacc\":\"e8226bd2-4a9d-47f8-86c1-428040db0f03\"},\"root_ids\":[\"eac966a2-0008-4cc7-8727-ed4e2755dacc\"]}];\n",
" var docs = Object.values(docs_json)\n",
" if (!docs) {\n",
" return\n",
" }\n",
" const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
" async function embed_document(root) {\n",
" var Bokeh = get_bokeh(root)\n",
" await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
" for (const render_item of render_items) {\n",
" for (const root_id of render_item.root_ids) {\n",
"\tconst id_el = document.getElementById(root_id)\n",
"\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
"\t const root_el = id_el.children[0]\n",
"\t root_el.id = root_el.id + '-rendered'\n",
"\t for (const child of root_el.children) {\n",
" // Ensure JupyterLab does not capture keyboard shortcuts\n",
" // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
"\t child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
"\t }\n",
"\t}\n",
" }\n",
" }\n",
" }\n",
" function get_bokeh(root) {\n",
" if (root.Bokeh === undefined) {\n",
" return null\n",
" } else if (root.Bokeh.version !== py_version) {\n",
" if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
"\treturn null\n",
" }\n",
" return root.Bokeh.versions.get(py_version);\n",
" } else if (root.Bokeh.version === py_version) {\n",
" return root.Bokeh\n",
" }\n",
" return null\n",
" }\n",
" function is_loaded(root) {\n",
" var Bokeh = get_bokeh(root)\n",
" return (Bokeh != null && Bokeh.Panel !== undefined)\n",
" }\n",
" if (is_loaded(root)) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (is_loaded(root)) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else if (document.readyState == \"complete\") {\n",
" attempts++;\n",
" if (attempts > 200) {\n",
" clearInterval(timer);\n",
"\t var Bokeh = get_bokeh(root)\n",
"\t if (Bokeh == null || Bokeh.Panel == null) {\n",
" console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
"\t } else {\n",
"\t console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
"\t embed_document(root)\n",
"\t }\n",
" }\n",
" }\n",
" }, 25, root)\n",
" }\n",
"})(window);</script>"
]
},
"metadata": {
"application/vnd.holoviews_exec.v0+json": {
"id": "eac966a2-0008-4cc7-8727-ed4e2755dacc"
}
},
"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"
},
{
"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 s, sys: 3.32 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 697 ms, sys: 38.1 ms, total: 736 ms\n",
"Wall time: 2min 53s\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-a04a8f1d-d1ba-11ef-8a6b-b7497cdc9971</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.247c1e48f7864d2e9d21d3beacbde30e/status\" target=\"_blank\">https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.247c1e48f7864d2e9d21d3beacbde30e/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.247c1e48f7864d2e9d21d3beacbde30e/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.247c1e48f7864d2e9d21d3beacbde30e\n",
" <li><b>Dashboard: </b><a href='https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.247c1e48f7864d2e9d21d3beacbde30e/status' target='_blank'>https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.247c1e48f7864d2e9d21d3beacbde30e/status</a>\n",
" </ul>\n",
"</div>\n",
"\n",
" </details>\n",
" \n",
"\n",
" </div>\n",
"</div>"
],
"text/plain": [
"<Client: 'tls://10.0.56.247:8786' processes=0 threads=0, memory=0 B>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"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": 130,
"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": 131,
"id": "f0422603-cca1-41bc-a12a-810d6a13e736",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<h4>Dataset size: 1.96 GB</h4>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=\"dark\"],\n",
"html[data-theme=\"dark\"],\n",
"body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
" height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:focus + label {\n",
" border: 2px solid var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" vh (time, y, x) float32 1GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\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-c882314e-ef6d-4f33-afa9-9573c2e8cc81' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c882314e-ef6d-4f33-afa9-9573c2e8cc81' 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-53736313-95f8-4aec-9864-42ebfa863176' class='xr-section-summary-in' type='checkbox' checked><label for='section-53736313-95f8-4aec-9864-42ebfa863176' 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-da2c86b4-be69-4ef8-b1d1-d49534556107' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da2c86b4-be69-4ef8-b1d1-d49534556107' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de4f18db-a8e0-470f-a719-59697948e8d4' class='xr-var-data-in' type='checkbox'><label for='data-de4f18db-a8e0-470f-a719-59697948e8d4' 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([&#x27;2023-03-05T22:46:10.500000000&#x27;, &#x27;2023-03-17T22:46:10.500000000&#x27;,\n",
" &#x27;2023-03-29T22:46:10.500000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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-45530159-a941-4cd4-911d-0ef8f11bed52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45530159-a941-4cd4-911d-0ef8f11bed52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-481c3d66-e2b4-4206-a9c4-cabb4864a47e' class='xr-var-data-in' type='checkbox'><label for='data-481c3d66-e2b4-4206-a9c4-cabb4864a47e' 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-efd2b0da-90ce-4d1b-8959-0578043caf09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efd2b0da-90ce-4d1b-8959-0578043caf09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d3b0e41-c85c-4125-84df-631683684ca1' class='xr-var-data-in' type='checkbox'><label for='data-3d3b0e41-c85c-4125-84df-631683684ca1' 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-aa21b987-1aac-4964-8211-c928f892eb91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa21b987-1aac-4964-8211-c928f892eb91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a67f6ad8-f6a5-44cb-a241-af2b29f9e22d' class='xr-var-data-in' type='checkbox'><label for='data-a67f6ad8-f6a5-44cb-a241-af2b29f9e22d' 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[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</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-54c4ca49-3930-47e0-bcc2-bfc775e7b283' class='xr-section-summary-in' type='checkbox' checked><label for='section-54c4ca49-3930-47e0-bcc2-bfc775e7b283' 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-3b6b8811-1f11-4b2d-980f-35169150e6a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b6b8811-1f11-4b2d-980f-35169150e6a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d44cc153-e32a-444e-93ec-35e6f33e3026' class='xr-var-data-in' type='checkbox'><label for='data-d44cc153-e32a-444e-93ec-35e6f33e3026' 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",
" <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> 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",
" <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",
"\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=\"14\" y1=\"4\" x2=\"14\" y2=\"112\" />\n",
" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\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=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\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)\">3</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-a33e1d5c-ce76-49a8-a4b3-0f76a30b3904' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a33e1d5c-ce76-49a8-a4b3-0f76a30b3904' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eec8c810-142d-400f-8c8c-8455d8ffea28' class='xr-var-data-in' type='checkbox'><label for='data-eec8c810-142d-400f-8c8c-8455d8ffea28' 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",
" <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> 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",
" <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",
"\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=\"14\" y1=\"4\" x2=\"14\" y2=\"112\" />\n",
" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"117\" />\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=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
" <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\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)\">3</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-612ad63a-21ff-405f-aa0a-258705506fa6' class='xr-section-summary-in' type='checkbox' ><label for='section-612ad63a-21ff-405f-aa0a-258705506fa6' 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-13e54576-5e5b-4119-825e-de06227463e0' class='xr-index-data-in' type='checkbox'/><label for='index-13e54576-5e5b-4119-825e-de06227463e0' 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([&#x27;2023-03-05 22:46:10.500000&#x27;, &#x27;2023-03-17 22:46:10.500000&#x27;,\n",
" &#x27;2023-03-29 22:46:10.500000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, 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-1923a13f-9ca2-4d1c-8872-89d4b22979c3' class='xr-index-data-in' type='checkbox'/><label for='index-1923a13f-9ca2-4d1c-8872-89d4b22979c3' 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=&#x27;float64&#x27;, name=&#x27;y&#x27;, 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-79dfdd26-8bef-4584-917e-f80506dca901' class='xr-index-data-in' type='checkbox'/><label for='index-79dfdd26-8bef-4584-917e-f80506dca901' 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=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0e4c6dad-6632-444c-bb8f-97660966a599' class='xr-section-summary-in' type='checkbox' checked><label for='section-0e4c6dad-6632-444c-bb8f-97660966a599' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 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"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# tải dữ liệu vh vv từ vệ tinh sentinel-1\n",
"dsvh, dsvv = load_data_sen1(dc, date_range, coordinates)"
]
},
{
"cell_type": "code",
"execution_count": 132,
"id": "c4d11ba1-b40a-4969-b911-e70914629dc9",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/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",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6ba5c5cdff884614bc4837af5e2263c4",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"average_vh = calculate_average(dsvh, time_pattern='1M')\n",
"progress(average_vh)"
]
},
{
"cell_type": "code",
"execution_count": 133,
"id": "3849455c-e4ea-4c83-9693-990a8edce2e8",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/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",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f5b76c387b304305b12ee5dc67c48a35",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"average_vv = calculate_average(dsvv, time_pattern='1M')\n",
"progress(average_vv)"
]
},
{
"cell_type": "code",
"execution_count": 134,
"id": "b6a66c55-ae30-4af9-9b8d-8d4f2152cf93",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 566 ms, sys: 750 ms, total: 1.32 s\n",
"Wall time: 1min 9s\n"
]
},
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=\"dark\"],\n",
"html[data-theme=\"dark\"],\n",
"body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
" height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:focus + label {\n",
" border: 2px solid var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;vv&#x27; (time: 1, y: 8874, x: 9902)&gt; 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-705cca6c-63df-4378-b5cd-61615e53527e' class='xr-array-in' type='checkbox' checked><label for='section-705cca6c-63df-4378-b5cd-61615e53527e' 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-52fb4dbe-802c-4c8f-8d35-3b26edfa33a0' class='xr-section-summary-in' type='checkbox' checked><label for='section-52fb4dbe-802c-4c8f-8d35-3b26edfa33a0' 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-28a9ee3f-790c-41e6-a672-246936317342' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28a9ee3f-790c-41e6-a672-246936317342' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e413fd4-7fad-4cd9-a254-6943c1b8566d' class='xr-var-data-in' type='checkbox'><label for='data-1e413fd4-7fad-4cd9-a254-6943c1b8566d' 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-cfb8280b-9312-4dda-ae7b-6f63451b4c56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfb8280b-9312-4dda-ae7b-6f63451b4c56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48b90feb-3c4c-4054-80e4-ffaa8ef789e7' class='xr-var-data-in' type='checkbox'><label for='data-48b90feb-3c4c-4054-80e4-ffaa8ef789e7' 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-62e04393-331a-4d56-998e-8baf8640ce33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62e04393-331a-4d56-998e-8baf8640ce33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6986ecce-226f-403c-bb43-7bf329021981' class='xr-var-data-in' type='checkbox'><label for='data-6986ecce-226f-403c-bb43-7bf329021981' 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[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</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-fb0d3867-e9aa-4807-a806-966cf2288091' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb0d3867-e9aa-4807-a806-966cf2288091' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57250ee0-a22b-41b8-81ed-ebdd5bb4a3bb' class='xr-var-data-in' type='checkbox'><label for='data-57250ee0-a22b-41b8-81ed-ebdd5bb4a3bb' 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([&#x27;2023-03-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0cfa66d4-e1a8-4e3a-8d32-58960649ecdf' class='xr-section-summary-in' type='checkbox' ><label for='section-0cfa66d4-e1a8-4e3a-8d32-58960649ecdf' 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-6a477179-de90-4b78-a6a2-f21f43a6a2d7' class='xr-index-data-in' type='checkbox'/><label for='index-6a477179-de90-4b78-a6a2-f21f43a6a2d7' 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=&#x27;float64&#x27;, name=&#x27;y&#x27;, 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-189ff7b8-76e9-4d11-8328-4527e245c040' class='xr-index-data-in' type='checkbox'/><label for='index-189ff7b8-76e9-4d11-8328-4527e245c040' 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=&#x27;float64&#x27;, name=&#x27;x&#x27;, 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-f91bff26-f92d-473d-be90-247eee536633' class='xr-index-data-in' type='checkbox'/><label for='index-f91bff26-f92d-473d-be90-247eee536633' 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([&#x27;2023-03-31&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;ME&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5c400dc-dae5-48e4-be17-01b4e50f7ea8' class='xr-section-summary-in' type='checkbox' checked><label for='section-a5c400dc-dae5-48e4-be17-01b4e50f7ea8' 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>"
],
"text/plain": [
"<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"
]
},
"execution_count": 134,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time\n",
"average_vh.compute()\n",
"average_vv.compute()"
]
},
{
"cell_type": "code",
"execution_count": 135,
"id": "46f285ce-490c-42e1-9822-8154b37704f6",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"No datasets require offset correction\n",
"The valid_data_mask and scale (no offset) have been applied to the reflectance bands\n"
]
},
{
"data": {
"text/html": [
"<h4>Dataset size: 8.84 GB</h4>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=\"dark\"],\n",
"html[data-theme=\"dark\"],\n",
"body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
" height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:focus + label {\n",
" border: 2px solid var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" nir (time, y, x) float32 4GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" scl (time, y, x) uint8 1GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\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-2b3c6f68-4029-4996-8d3e-abfb76f70923' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2b3c6f68-4029-4996-8d3e-abfb76f70923' 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-f4b40fd4-ef77-48db-bb91-94a72b5bb812' class='xr-section-summary-in' type='checkbox' checked><label for='section-f4b40fd4-ef77-48db-bb91-94a72b5bb812' 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-cc575520-1d56-4900-b1d1-e25ac1bf63a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc575520-1d56-4900-b1d1-e25ac1bf63a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80e55906-86db-4ae0-8021-7c5567134f79' class='xr-var-data-in' type='checkbox'><label for='data-80e55906-86db-4ae0-8021-7c5567134f79' 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([&#x27;2023-03-01T03:35:09.182000000&#x27;, &#x27;2023-03-03T03:25:17.841000000&#x27;,\n",
" &#x27;2023-03-06T03:35:14.717000000&#x27;, &#x27;2023-03-08T03:25:12.032000000&#x27;,\n",
" &#x27;2023-03-11T03:35:07.230000000&#x27;, &#x27;2023-03-13T03:25:20.837000000&#x27;,\n",
" &#x27;2023-03-16T03:35:15.940000000&#x27;, &#x27;2023-03-18T03:25:14.467000000&#x27;,\n",
" &#x27;2023-03-21T03:35:10.279000000&#x27;, &#x27;2023-03-23T03:25:18.795000000&#x27;,\n",
" &#x27;2023-03-26T03:35:14.570000000&#x27;, &#x27;2023-03-28T03:25:14.536000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</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-bc27735f-c71b-45d1-9d60-c1c2ed3e3dc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc27735f-c71b-45d1-9d60-c1c2ed3e3dc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c139b780-6a56-4c64-bcb9-8697538a9ad8' class='xr-var-data-in' type='checkbox'><label for='data-c139b780-6a56-4c64-bcb9-8697538a9ad8' 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-3bd2df5f-de76-4ed8-a978-156d5ced7f5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bd2df5f-de76-4ed8-a978-156d5ced7f5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d9b4a9c-8ba7-4da9-82c4-2397cc86f89b' class='xr-var-data-in' type='checkbox'><label for='data-7d9b4a9c-8ba7-4da9-82c4-2397cc86f89b' 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-30696b51-d003-4ee4-9353-d2044cf6fcaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30696b51-d003-4ee4-9353-d2044cf6fcaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e761610-062d-4252-8533-d7328cc989a6' class='xr-var-data-in' type='checkbox'><label for='data-3e761610-062d-4252-8533-d7328cc989a6' 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[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</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-001784f6-61ae-43ef-b919-adf049a258ed' class='xr-section-summary-in' type='checkbox' checked><label for='section-001784f6-61ae-43ef-b919-adf049a258ed' 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-ab1953ad-608a-4ca3-a494-f2e60f052108' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab1953ad-608a-4ca3-a494-f2e60f052108' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddabee66-3cfc-4d34-bff0-02b9014b91b4' class='xr-var-data-in' type='checkbox'><label for='data-ddabee66-3cfc-4d34-bff0-02b9014b91b4' 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-5384e036-a3ce-4d09-8a1f-fb4328d2b3d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5384e036-a3ce-4d09-8a1f-fb4328d2b3d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c734f53-2e51-4677-b15a-d65c13c6c5c3' class='xr-var-data-in' type='checkbox'><label for='data-8c734f53-2e51-4677-b15a-d65c13c6c5c3' 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>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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-b0cc8dd3-3fba-4ab9-abb4-4a22e2247073' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0cc8dd3-3fba-4ab9-abb4-4a22e2247073' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d9cd443-90bc-4ade-86a2-d133d2396b9f' class='xr-var-data-in' type='checkbox'><label for='data-0d9cd443-90bc-4ade-86a2-d133d2396b9f' 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>{&#x27;qa&#x27;: {&#x27;bits&#x27;: [0, 1, 2, 3, 4, 5, 6, 7], &#x27;values&#x27;: {&#x27;0&#x27;: &#x27;no data&#x27;, &#x27;1&#x27;: &#x27;saturated or defective&#x27;, &#x27;2&#x27;: &#x27;dark area pixels&#x27;, &#x27;3&#x27;: &#x27;cloud shadows&#x27;, &#x27;4&#x27;: &#x27;vegetation&#x27;, &#x27;5&#x27;: &#x27;bare soils&#x27;, &#x27;6&#x27;: &#x27;water&#x27;, &#x27;7&#x27;: &#x27;unclassified&#x27;, &#x27;8&#x27;: &#x27;cloud medium probability&#x27;, &#x27;9&#x27;: &#x27;cloud high probability&#x27;, &#x27;10&#x27;: &#x27;thin cirrus&#x27;, &#x27;11&#x27;: &#x27;snow or ice&#x27;}, &#x27;description&#x27;: &#x27;Sen2Cor Scene Classification&#x27;}}</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",
" <!-- 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></ul></div></li><li class='xr-section-item'><input id='section-e76c0ce2-56b6-4ec4-a58c-a035877e9636' class='xr-section-summary-in' type='checkbox' ><label for='section-e76c0ce2-56b6-4ec4-a58c-a035877e9636' 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-2dedca59-9025-4784-b8c4-21892ffbce0c' class='xr-index-data-in' type='checkbox'/><label for='index-2dedca59-9025-4784-b8c4-21892ffbce0c' 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([&#x27;2023-03-01 03:35:09.182000&#x27;, &#x27;2023-03-03 03:25:17.841000&#x27;,\n",
" &#x27;2023-03-06 03:35:14.717000&#x27;, &#x27;2023-03-08 03:25:12.032000&#x27;,\n",
" &#x27;2023-03-11 03:35:07.230000&#x27;, &#x27;2023-03-13 03:25:20.837000&#x27;,\n",
" &#x27;2023-03-16 03:35:15.940000&#x27;, &#x27;2023-03-18 03:25:14.467000&#x27;,\n",
" &#x27;2023-03-21 03:35:10.279000&#x27;, &#x27;2023-03-23 03:25:18.795000&#x27;,\n",
" &#x27;2023-03-26 03:35:14.570000&#x27;, &#x27;2023-03-28 03:25:14.536000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, 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-e2e00235-8029-4eea-a2c6-948104641aad' class='xr-index-data-in' type='checkbox'/><label for='index-e2e00235-8029-4eea-a2c6-948104641aad' 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=&#x27;float64&#x27;, name=&#x27;y&#x27;, 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-44516e32-406c-43cb-8257-3d905029559b' class='xr-index-data-in' type='checkbox'/><label for='index-44516e32-406c-43cb-8257-3d905029559b' 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=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4848680c-c0be-4cb1-8b78-d5e5e2c00adb' class='xr-section-summary-in' type='checkbox' checked><label for='section-4848680c-c0be-4cb1-8b78-d5e5e2c00adb' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 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"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_sen2 = load_data_sen2(dc, date_range, coordinates)\n",
"notebook_utils.heading(notebook_utils.xarray_object_size(data_sen2))\n",
"display(data_sen2)"
]
},
{
"cell_type": "code",
"execution_count": 136,
"id": "8cb877b1-a69e-4ee8-b54c-235b5ba83084",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"{'0': 'no data',\n",
" '1': 'saturated or defective',\n",
" '2': 'dark area pixels',\n",
" '3': 'cloud shadows',\n",
" '4': 'vegetation',\n",
" '5': 'bare soils',\n",
" '6': 'water',\n",
" '7': 'unclassified',\n",
" '8': 'cloud medium probability',\n",
" '9': 'cloud high probability',\n",
" '10': 'thin cirrus',\n",
" '11': 'snow or ice'}"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 57.1 ms, sys: 4.1 ms, total: 61.2 ms\n",
"Wall time: 59.2 ms\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ab513b33c73b4344a3ca1a576c510a2a",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2025-01-13 15:34:16,456 - tornado.application - ERROR - Exception in callback functools.partial(<bound method IOLoop._discard_future_result of <tornado.platform.asyncio.AsyncIOMainLoop object at 0x7fa1d24670e0>>, <Task finished name='Task-4823' coro=<MultiProgressBar.listen() done, defined at /env/lib/python3.12/site-packages/distributed/diagnostics/progressbar.py:281> exception=OSError('Timed out trying to connect to gateway://traefik-dask-gateway.easihub:80/easihub.247c1e48f7864d2e9d21d3beacbde30e after 30 s')>)\n",
"Traceback (most recent call last):\n",
" File \"/env/lib/python3.12/site-packages/distributed/utils.py\", line 1952, in wait_for\n",
" return await fut\n",
" ^^^^^^^^^\n",
" File \"/env/lib/python3.12/site-packages/dask_gateway/comm.py\", line 45, in connect\n",
" plain_stream = await self.client.connect(\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/env/lib/python3.12/site-packages/tornado/tcpclient.py\", line 269, in connect\n",
" addrinfo = await self.resolver.resolve(host, port, af)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
"asyncio.exceptions.CancelledError\n",
"\n",
"The above exception was the direct cause of the following exception:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/env/lib/python3.12/site-packages/distributed/comm/core.py\", line 342, in connect\n",
" comm = await wait_for(\n",
" ^^^^^^^^^^^^^^^\n",
" File \"/env/lib/python3.12/site-packages/distributed/utils.py\", line 1951, in wait_for\n",
" async with asyncio.timeout(timeout):\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/opt/uv/python-installs/cpython-3.12.7-linux-x86_64-gnu/lib/python3.12/asyncio/timeouts.py\", line 115, in __aexit__\n",
" raise TimeoutError from exc_val\n",
"TimeoutError\n",
"\n",
"The above exception was the direct cause of the following exception:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/env/lib/python3.12/site-packages/tornado/ioloop.py\", line 750, in _run_callback\n",
" ret = callback()\n",
" ^^^^^^^^^^\n",
" File \"/env/lib/python3.12/site-packages/tornado/ioloop.py\", line 774, in _discard_future_result\n",
" future.result()\n",
" File \"/env/lib/python3.12/site-packages/distributed/diagnostics/progressbar.py\", line 306, in listen\n",
" self.comm = await connect(\n",
" ^^^^^^^^^^^^^^\n",
" File \"/env/lib/python3.12/site-packages/distributed/comm/core.py\", line 368, in connect\n",
" raise OSError(\n",
"OSError: Timed out trying to connect to gateway://traefik-dask-gateway.easihub:80/easihub.247c1e48f7864d2e9d21d3beacbde30e after 30 s\n"
]
}
],
"source": [
"%%time\n",
"# Tiến hành loại bỏ các vị trí bị mây ảnh hưởng\n",
"result = mask_cloud(data_sen2)\n",
"progress(result)"
]
},
{
"cell_type": "code",
"execution_count": 137,
"id": "325668db-040c-44d1-8cac-749f1850067d",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=\"dark\"],\n",
"html[data-theme=\"dark\"],\n",
"body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
" height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:focus + label {\n",
" border: 2px solid var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;NDVI&#x27; (time: 12, y: 8874, x: 9902)&gt; Size: 4GB\n",
"dask.array&lt;truediv, shape=(12, 8874, 9902), dtype=float32, chunksize=(1, 2048, 2048), chunktype=numpy.ndarray&gt;\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-26c16856-9b1c-4d46-ade2-8bc2856cee5b' class='xr-array-in' type='checkbox' checked><label for='section-26c16856-9b1c-4d46-ade2-8bc2856cee5b' 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&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</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-9768cb6a-0afd-4e96-8431-01dcd060ff6b' class='xr-section-summary-in' type='checkbox' checked><label for='section-9768cb6a-0afd-4e96-8431-01dcd060ff6b' 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-cd883007-b865-4b33-b4fd-fb17ff1dc5d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd883007-b865-4b33-b4fd-fb17ff1dc5d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db69d77b-ecdc-4cf9-88a8-bba7d05e0f48' class='xr-var-data-in' type='checkbox'><label for='data-db69d77b-ecdc-4cf9-88a8-bba7d05e0f48' 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([&#x27;2023-03-01T03:35:09.182000000&#x27;, &#x27;2023-03-03T03:25:17.841000000&#x27;,\n",
" &#x27;2023-03-06T03:35:14.717000000&#x27;, &#x27;2023-03-08T03:25:12.032000000&#x27;,\n",
" &#x27;2023-03-11T03:35:07.230000000&#x27;, &#x27;2023-03-13T03:25:20.837000000&#x27;,\n",
" &#x27;2023-03-16T03:35:15.940000000&#x27;, &#x27;2023-03-18T03:25:14.467000000&#x27;,\n",
" &#x27;2023-03-21T03:35:10.279000000&#x27;, &#x27;2023-03-23T03:25:18.795000000&#x27;,\n",
" &#x27;2023-03-26T03:35:14.570000000&#x27;, &#x27;2023-03-28T03:25:14.536000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</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-91ae03e9-b1e2-460d-aa9a-0034c469e8fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91ae03e9-b1e2-460d-aa9a-0034c469e8fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5e9396d-08e4-43c0-b019-70fdbe62814d' class='xr-var-data-in' type='checkbox'><label for='data-f5e9396d-08e4-43c0-b019-70fdbe62814d' 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-90c5c6e1-5c39-4700-8025-e5b71f36d0b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90c5c6e1-5c39-4700-8025-e5b71f36d0b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75b3e637-3db7-4ebc-a372-5b55c3ca0a76' class='xr-var-data-in' type='checkbox'><label for='data-75b3e637-3db7-4ebc-a372-5b55c3ca0a76' 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-7d4f3216-603d-4c1d-9226-fd2a78a64fc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d4f3216-603d-4c1d-9226-fd2a78a64fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d48f8765-6dee-429b-b870-ae6c326a9a55' class='xr-var-data-in' type='checkbox'><label for='data-d48f8765-6dee-429b-b870-ae6c326a9a55' 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[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</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-58b117dc-0afb-41df-a1cc-508ec4034176' class='xr-section-summary-in' type='checkbox' ><label for='section-58b117dc-0afb-41df-a1cc-508ec4034176' 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-d82091eb-e131-4fe6-8eaa-669e96d5661b' class='xr-index-data-in' type='checkbox'/><label for='index-d82091eb-e131-4fe6-8eaa-669e96d5661b' 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([&#x27;2023-03-01 03:35:09.182000&#x27;, &#x27;2023-03-03 03:25:17.841000&#x27;,\n",
" &#x27;2023-03-06 03:35:14.717000&#x27;, &#x27;2023-03-08 03:25:12.032000&#x27;,\n",
" &#x27;2023-03-11 03:35:07.230000&#x27;, &#x27;2023-03-13 03:25:20.837000&#x27;,\n",
" &#x27;2023-03-16 03:35:15.940000&#x27;, &#x27;2023-03-18 03:25:14.467000&#x27;,\n",
" &#x27;2023-03-21 03:35:10.279000&#x27;, &#x27;2023-03-23 03:25:18.795000&#x27;,\n",
" &#x27;2023-03-26 03:35:14.570000&#x27;, &#x27;2023-03-28 03:25:14.536000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, 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-46553aa6-bc8b-4f56-b8af-f4d0e152b9f5' class='xr-index-data-in' type='checkbox'/><label for='index-46553aa6-bc8b-4f56-b8af-f4d0e152b9f5' 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=&#x27;float64&#x27;, name=&#x27;y&#x27;, 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-2fabc366-eeef-4b48-9bb2-4b851282eede' class='xr-index-data-in' type='checkbox'/><label for='index-2fabc366-eeef-4b48-9bb2-4b851282eede' 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=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3cfce8a5-1db9-46c5-a231-406fe5c9b411' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3cfce8a5-1db9-46c5-a231-406fe5c9b411' 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>"
],
"text/plain": [
"<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"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# calculate NDVI\n",
"dsNDVI = calculate_indices(result, index='NDVI', satellite_mission='s2')\n",
"ndvi = dsNDVI[\"NDVI\"]\n",
"display(ndvi)\n"
]
},
{
"cell_type": "code",
"execution_count": 138,
"id": "f94969d8-d04f-4495-af63-6323d5c730ef",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 21.3 ms, sys: 4.15 ms, total: 25.5 ms\n",
"Wall time: 29.2 ms\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/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",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "97bb9b230f8e4a99bec7871f7a81502f",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%time\n",
"# calculate average NDVI\n",
"average_ndvi = calculate_average(ndvi,time_pattern=\"1M\")\n",
"progress(average_ndvi)"
]
},
{
"cell_type": "code",
"execution_count": 139,
"id": "06bd6bda-aa8b-44a0-9c8a-d17ccf5b86c3",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"average_ndvi = average_ndvi.compute()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "af4fe58b-358a-42f8-b9a4-f3547d2c230b",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7fa0a90e4980>"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"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": "markdown",
"id": "edab3c39-1d85-4ef5-831c-f64070c31355",
"metadata": {},
"source": [
"#####################################################################################"
]
},
{
"cell_type": "code",
"execution_count": 146,
"id": "c83d666e-139c-4215-909e-32c535532b19",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"fill_nan_model = joblib.load('output/regressors/mean_no_negative/gb_cloud.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 141,
"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": 142,
"id": "11e7be59-8982-4b72-a709-f2da5e015dcc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(85080123,)"
]
},
"execution_count": 142,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"label.shape"
]
},
{
"cell_type": "code",
"execution_count": 143,
"id": "c38dda57-604f-4705-a282-eaec22f3ea12",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(5000000, 2)\n",
"(5000000,)\n"
]
}
],
"source": [
"num_samples = 5000000\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": 144,
"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": 147,
"id": "8cdc9d56-6e4a-4da9-9280-e632a1434f12",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MSE: 0.06232030271316629\n",
"MAE: 0.20292019157833405\n",
"R^2: 0.5583783284198397\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": [
"#####################################################################################"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5b1314c0-57d0-499f-adcb-6bd249cc5d44",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "6d6f2194-24a6-49d9-8591-4839606fd43e",
"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
}
Reference in New Issue View Git Blame Copy Permalink