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| { | |
| "cells": [ | |
| { | |
| "attachments": {}, | |
| "cell_type": "markdown", | |
| "id": "832ee97e-e259-4280-b2ab-42d7fe348a70", | |
| "metadata": {}, | |
| "source": [ | |
| "# Virtualizing Data Access: Towards \"Cloud Native\" Analysis Ready Data @ NSIDC\n", | |
| "\n", | |
| "2025 NSIDC UWG meeting\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "## Scaling horizontally with Dask\n", | |
| "\n", | |
| "We still need to process potentially thousands of files so either locally or in the cloud we need a framework that helps us with the parallelization of these tasks.\n", | |
| "Since Dask has been integrated into xarray and the rest of the Pangeo/Scientific Python data stack is the natural option to use (but not the only one)." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "id": "667cbcbf-d311-4b2c-8aeb-44919184fc18", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
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| "<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" | |
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| { | |
| "data": { | |
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| "(function(root) {\n", | |
| " function now() {\n", | |
| " return new Date();\n", | |
| " }\n", | |
| "\n", | |
| " const force = true;\n", | |
| " const py_version = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", | |
| " const reloading = false;\n", | |
| " const Bokeh = root.Bokeh;\n", | |
| "\n", | |
| " // Set a timeout for this load but only if we are not already initializing\n", | |
| " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", | |
| " root._bokeh_timeout = Date.now() + 5000;\n", | |
| " root._bokeh_failed_load = false;\n", | |
| " }\n", | |
| "\n", | |
| " function run_callbacks() {\n", | |
| " try {\n", | |
| " root._bokeh_onload_callbacks.forEach(function(callback) {\n", | |
| " if (callback != null)\n", | |
| " callback();\n", | |
| " });\n", | |
| " } finally {\n", | |
| " delete root._bokeh_onload_callbacks;\n", | |
| " }\n", | |
| " console.debug(\"Bokeh: all callbacks have finished\");\n", | |
| " }\n", | |
| "\n", | |
| " function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n", | |
| " if (css_urls == null) css_urls = [];\n", | |
| " if (js_urls == null) js_urls = [];\n", | |
| " if (js_modules == null) js_modules = [];\n", | |
| " if (js_exports == null) js_exports = {};\n", | |
| "\n", | |
| " root._bokeh_onload_callbacks.push(callback);\n", | |
| "\n", | |
| " if (root._bokeh_is_loading > 0) {\n", | |
| " // Don't load bokeh if it is still initializing\n", | |
| " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", | |
| " return null;\n", | |
| " } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", | |
| " // There is nothing to load\n", | |
| " run_callbacks();\n", | |
| " return null;\n", | |
| " }\n", | |
| "\n", | |
| " function on_load() {\n", | |
| " root._bokeh_is_loading--;\n", | |
| " if (root._bokeh_is_loading === 0) {\n", | |
| " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", | |
| " run_callbacks()\n", | |
| " }\n", | |
| " }\n", | |
| " window._bokeh_on_load = on_load\n", | |
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| " 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", | |
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| " 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/1.8.2/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.0.min.js\", \"https://cdn.holoviz.org/panel/1.8.2/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 = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = false;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.8.2/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.0.min.js\", \"https://cdn.holoviz.org/panel/1.8.2/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", | |
| " 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", | |
| " let retries = 0;\n", | |
| " const open = () => {\n", | |
| " if (comm.active) {\n", | |
| " comm.open();\n", | |
| " } else if (retries > 3) {\n", | |
| " console.warn('Comm target never activated')\n", | |
| " } else {\n", | |
| " retries += 1\n", | |
| " setTimeout(open, 500)\n", | |
| " }\n", | |
| " }\n", | |
| " if (comm.active) {\n", | |
| " comm.open();\n", | |
| " } else {\n", | |
| " setTimeout(open, 500)\n", | |
| " }\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 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 let retries = 0;\n const open = () => {\n if (comm.active) {\n comm.open();\n } else if (retries > 3) {\n console.warn('Comm target never activated')\n } else {\n retries += 1\n setTimeout(open, 500)\n }\n }\n if (comm.active) {\n comm.open();\n } else {\n setTimeout(open, 500)\n }\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 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| "metadata": {}, | |
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| " var docs_json = {\"bf7244ca-729c-4345-b72b-5147fb1ae69b\":{\"version\":\"3.8.0\",\"title\":\"Bokeh 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| |
| " var render_items = [{\"docid\":\"bf7244ca-729c-4345-b72b-5147fb1ae69b\",\"roots\":{\"c2a5e4ac-ea1c-42df-b3f8-f967c5e995a7\":\"dbf6f785-286c-4e8d-b688-958bdf22e82e\"},\"root_ids\":[\"c2a5e4ac-ea1c-42df-b3f8-f967c5e995a7\"]}];\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": "c2a5e4ac-ea1c-42df-b3f8-f967c5e995a7" | |
| } | |
| }, | |
| "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 = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", | |
| " const reloading = true;\n", | |
| " const Bokeh = root.Bokeh;\n", | |
| "\n", | |
| " // Set a timeout for this load but only if we are not already initializing\n", | |
| " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", | |
| " root._bokeh_timeout = Date.now() + 5000;\n", | |
| " root._bokeh_failed_load = false;\n", | |
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| "\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/1.8.2/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.jsdelivr.net/npm/@holoviz/[email protected]/dist/geoviews.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 = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.8.2/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.jsdelivr.net/npm/@holoviz/[email protected]/dist/geoviews.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", | |
| " 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", | |
| " let retries = 0;\n", | |
| " const open = () => {\n", | |
| " if (comm.active) {\n", | |
| " comm.open();\n", | |
| " } else if (retries > 3) {\n", | |
| " console.warn('Comm target never activated')\n", | |
| " } else {\n", | |
| " retries += 1\n", | |
| " setTimeout(open, 500)\n", | |
| " }\n", | |
| " }\n", | |
| " if (comm.active) {\n", | |
| " comm.open();\n", | |
| " } else {\n", | |
| " setTimeout(open, 500)\n", | |
| " }\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 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 let retries = 0;\n const open = () => {\n if (comm.active) {\n comm.open();\n } else if (retries > 3) {\n console.warn('Comm target never activated')\n } else {\n retries += 1\n setTimeout(open, 500)\n }\n }\n if (comm.active) {\n comm.open();\n } else {\n setTimeout(open, 500)\n }\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" | |
| } | |
| ], | |
| "source": [ | |
| "# data access and processing\n", | |
| "import earthaccess as ea\n", | |
| "import xarray as xr\n", | |
| "import rioxarray\n", | |
| "import hvplot.xarray\n", | |
| "import fsspec\n", | |
| "import zarr\n", | |
| "\n", | |
| "# distributed compute\n", | |
| "import dask\n", | |
| "from dask.distributed import Client, LocalCluster\n", | |
| "from coiled import Cluster as CoiledCluster\n", | |
| "\n", | |
| "# plotting\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "from holoviews import HoloMap\n", | |
| "import geoviews as gv\n", | |
| "import panel as pn\n", | |
| "import cartopy.crs as ccrs\n", | |
| "\n", | |
| "auth = ea.login()\n", | |
| "gv.extension(\"bokeh\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "id": "27d40abb-8fb1-482f-bc12-756ce23965bb", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "cloud_opts = {\n", | |
| " \"region\": \"us-west-2\",\n", | |
| " \"worker_vm_types\": [\"t4g.medium\"],\n", | |
| " \"spot_policy\": \"spot_with_fallback\",\n", | |
| " \"arm\": True,\n", | |
| " \"name\": \"test-vd\",\n", | |
| " \"environ\": {\"EARTHDATA_TOKEN\": auth.token[\"access_token\"]}\n", | |
| "}" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "id": "c0c4fead-db3d-44aa-ac50-84ff2f2db0d0", | |
| "metadata": { | |
| "jupyter": { | |
| "source_hidden": true | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def create_dask_cluster(environment=\"local\",\n", | |
| " n_workers=4,\n", | |
| " cloud_opts={}):\n", | |
| " import logging\n", | |
| " \n", | |
| " if \"client\" in locals() and \"cluster\" in locals():\n", | |
| " return (client, cluster)\n", | |
| " else:\n", | |
| " if environment==\"local\":\n", | |
| " print(\"Creating new local Dask client\")\n", | |
| " cluster = LocalCluster(\n", | |
| " n_workers=n_workers,\n", | |
| " threads_per_worker=1,\n", | |
| " silence_logs=logging.ERROR)\n", | |
| " else:\n", | |
| " print(\"Creating new Coiled Dask client\")\n", | |
| " cluster = CoiledCluster(n_workers=n_workers,\n", | |
| " **cloud_opts) \n", | |
| "\n", | |
| " client = Client(cluster)\n", | |
| " # obstore_plugin = RustacStorePlugin(obstore_opts)\n", | |
| " # client.register_plugin(obstore_plugin, name=\"rustac_store\")\n", | |
| " return (client, cluster)\n", | |
| "\n", | |
| "def silence_worker_warnings():\n", | |
| " import warnings\n", | |
| " import logging\n", | |
| " \n", | |
| " warnings.filterwarnings(\"ignore\")\n", | |
| " for name in [\"distributed\", \"xarray\", \"py.warnings\", \"fsspec\", \"h5netcdf\", \"h5py\"]:\n", | |
| " logging.getLogger(name).setLevel(logging.ERROR)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "id": "569a9b17-93fd-43fe-8d96-6e3d14d29136", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Creating new Coiled Dask client\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "d1f89fd52cb34686b28c4e4d5e5056af", | |
| "version_major": 2, | |
| "version_minor": 0 | |
| }, | |
| "text/plain": [ | |
| "Output()" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n" | |
| ], | |
| "text/plain": [] | |
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| "data": { | |
| "text/html": [ | |
| "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭────────────────────────── <span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Not Synced with Cluster</span> ───────────────────────────╮\n", | |
| "│ ╷ ╷ │\n", | |
| "│ <span style=\"font-weight: bold\"> Package </span>│<span style=\"font-weight: bold\"> Error </span>│<span style=\"font-weight: bold\"> Level </span> │\n", | |
| "│ ╶───────────┼────────────────────────────────────────────────────┼─────────╴ │\n", | |
| "│ numpy │ numpy==2.3.3 has no install candidate for Python │ Warning │\n", | |
| "│ │ 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ zstandard │ zstandard~=0.25.0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ shiboken6 │ cannot find shiboken6~=6.9.3 on pypi.org. If you │ Warning │\n", | |
| "│ │ are using a custom PyPI URL, please see │ │\n", | |
| "│ │ https://docs.coiled.io/user_guide/software/packag… │ │\n", | |
| "│ │ for more instructions. │ │\n", | |
| "│ debugpy │ debugpy~=1.8.17 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ crc32c │ crc32c~=2.7.1.post0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ cramjam │ cramjam~=2.11.0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ bcrypt │ bcrypt~=5.0.0 has no install candidate for Python │ Warning │\n", | |
| "│ │ 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ ╵ ╵ │\n", | |
| "╰──────────────────────────────────────────────────────────────────────────────╯\n", | |
| "</pre>\n" | |
| ], | |
| "text/plain": [ | |
| "╭────────────────────────── \u001b[1;31mNot Synced with Cluster\u001b[0m ───────────────────────────╮\n", | |
| "│ ╷ ╷ │\n", | |
| "│ \u001b[1m \u001b[0m\u001b[1mPackage \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1mError \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1mLevel \u001b[0m\u001b[1m \u001b[0m │\n", | |
| "│ ╶───────────┼────────────────────────────────────────────────────┼─────────╴ │\n", | |
| "│ numpy │ numpy==2.3.3 has no install candidate for Python │ Warning │\n", | |
| "│ │ 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ zstandard │ zstandard~=0.25.0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ shiboken6 │ cannot find shiboken6~=6.9.3 on pypi.org. If you │ Warning │\n", | |
| "│ │ are using a custom PyPI URL, please see │ │\n", | |
| "│ │ https://docs.coiled.io/user_guide/software/packag… │ │\n", | |
| "│ │ for more instructions. │ │\n", | |
| "│ debugpy │ debugpy~=1.8.17 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ crc32c │ crc32c~=2.7.1.post0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ cramjam │ cramjam~=2.11.0 has no install candidate for │ Warning │\n", | |
| "│ │ Python 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ bcrypt │ bcrypt~=5.0.0 has no install candidate for Python │ Warning │\n", | |
| "│ │ 3.13 linux-aarch64 on conda-forge │ │\n", | |
| "│ ╵ ╵ │\n", | |
| "╰──────────────────────────────────────────────────────────────────────────────╯\n" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "2bc7a803fd5e427b8d6ce36a54171760", | |
| "version_major": 2, | |
| "version_minor": 0 | |
| }, | |
| "text/plain": [ | |
| "Output()" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n" | |
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| "text/plain": [] | |
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| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "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-e84918f2-ab7b-11f0-9aa3-9c2dcd92e342</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> coiled.Cluster</td>\n", | |
| " \n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"https://cluster-hyjga.dask.host/yx0zywuvivzAW04Z/status\" target=\"_blank\">https://cluster-hyjga.dask.host/yx0zywuvivzAW04Z/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://cluster-hyjga.dask.host/yx0zywuvivzAW04Z/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 class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n", | |
| " </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">Cluster</h3>\n", | |
| " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">test-vd</p>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard:</strong> <a href=\"https://cluster-hyjga.dask.host/yx0zywuvivzAW04Z/status\" target=\"_blank\">https://cluster-hyjga.dask.host/yx0zywuvivzAW04Z/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Workers:</strong> 16\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads:</strong> 32\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total memory:</strong> 53.19 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " </table>\n", | |
| "\n", | |
| " <details>\n", | |
| " <summary style=\"margin-bottom: 20px;\">\n", | |
| " <h3 style=\"display: inline;\">Scheduler Info</h3>\n", | |
| " </summary>\n", | |
| "\n", | |
| " <div style=\"\">\n", | |
| " <div>\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n", | |
| " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-bde76eec-2107-4049-9ee4-fffb44f17da2</p>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm:</strong> tls://10.0.62.122:8786\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Workers:</strong> 16 \n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard:</strong> <a href=\"http://10.0.62.122:8788/status\" target=\"_blank\">http://10.0.62.122:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads:</strong> 32\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Started:</strong> Just now\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total memory:</strong> 53.19 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " </table>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| "\n", | |
| " <details style=\"margin-left: 48px;\">\n", | |
| " <summary style=\"margin-bottom: 20px;\">\n", | |
| " <h3 style=\"display: inline;\">Workers</h3>\n", | |
| " </summary>\n", | |
| "\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-001533c401</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.62.56:33755\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.62.56:8788/status\" target=\"_blank\">http://10.0.62.56:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.62.56:43875\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-dp793auo\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-2d61a9e7ae</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.53.225:39127\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.53.225:8788/status\" target=\"_blank\">http://10.0.53.225:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.53.225:34499\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-ihppqaih\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-317efba659</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.53.80:39061\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.53.80:8788/status\" target=\"_blank\">http://10.0.53.80:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.34 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.53.80:36699\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-8uuuah3v\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-6bcc76c025</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.49.18:40783\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.49.18:8788/status\" target=\"_blank\">http://10.0.49.18:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.35 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.49.18:37871\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-kni3h33k\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-8a2a915829</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.62.45:42717\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.62.45:8788/status\" target=\"_blank\">http://10.0.62.45:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.62.45:42345\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-i_g4oa9f\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-97825d23e4</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.59.95:44621\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.59.95:8788/status\" target=\"_blank\">http://10.0.59.95:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.59.95:44229\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-8v3r5zz5\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-9eb0973d90</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.63.43:42037\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.63.43:8788/status\" target=\"_blank\">http://10.0.63.43:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.63.43:40491\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-vvoqqtyh\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-aeb0a02ac5</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.55.186:46389\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.55.186:8788/status\" target=\"_blank\">http://10.0.55.186:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.33 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.55.186:35843\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-sc6gqwer\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-c7570c2364</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.61.147:37167\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.61.147:8788/status\" target=\"_blank\">http://10.0.61.147:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.31 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.61.147:42701\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-411wureh\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-ce502c04da</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.61.224:35229\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.61.224:8788/status\" target=\"_blank\">http://10.0.61.224:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.61.224:40963\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-6bdu__xu\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-d93b8ac0af</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.51.60:42837\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.51.60:8788/status\" target=\"_blank\">http://10.0.51.60:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.51.60:45583\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-ajzjqwxy\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-ea8a8b0631</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.59.30:43359\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.59.30:8788/status\" target=\"_blank\">http://10.0.59.30:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.34 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.59.30:34481\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-kg0gejs9\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-ec537c8d15</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.56.66:39305\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.56.66:8788/status\" target=\"_blank\">http://10.0.56.66:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.56.66:39599\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-6izgk21y\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-ec6e098f59</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.58.206:42319\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.58.206:8788/status\" target=\"_blank\">http://10.0.58.206:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.31 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.58.206:44569\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-vmznqdq2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-ecf6a1e687</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.61.247:41577\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.61.247:8788/status\" target=\"_blank\">http://10.0.61.247:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.34 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.61.247:37843\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-meukwdg6\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| " <div style=\"margin-bottom: 20px;\">\n", | |
| " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", | |
| " <div style=\"margin-left: 48px;\">\n", | |
| " <details>\n", | |
| " <summary>\n", | |
| " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: test-vd-worker-fe2bf3f45a</h4>\n", | |
| " </summary>\n", | |
| " <table style=\"width: 100%; text-align: left;\">\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Comm: </strong> tls://10.0.48.117:41367\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Total threads: </strong> 2\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Dashboard: </strong> <a href=\"http://10.0.48.117:8788/status\" target=\"_blank\">http://10.0.48.117:8788/status</a>\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Memory: </strong> 3.32 GiB\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td style=\"text-align: left;\">\n", | |
| " <strong>Nanny: </strong> tls://10.0.48.117:46741\n", | |
| " </td>\n", | |
| " <td style=\"text-align: left;\"></td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td colspan=\"2\" style=\"text-align: left;\">\n", | |
| " <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-4ak9vlq_\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " \n", | |
| "\n", | |
| " </table>\n", | |
| " </details>\n", | |
| " </div>\n", | |
| " </div>\n", | |
| " \n", | |
| "\n", | |
| " </details>\n", | |
| "</div>\n", | |
| "\n", | |
| " </details>\n", | |
| " </div>\n", | |
| "</div>\n", | |
| " </details>\n", | |
| " \n", | |
| "\n", | |
| " </div>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "<Client: 'tls://10.0.62.122:8786' processes=16 threads=32, memory=53.19 GiB>" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "2025-10-17 13:31:35,462 - distributed.client - ERROR - Failed to reconnect to scheduler after 30.00 seconds, closing client\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client, cluster = create_dask_cluster(environment=\"cloud\",\n", | |
| " n_workers=16,\n", | |
| " cloud_opts=cloud_opts)\n", | |
| "client" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "id": "b79c7af4-8cd4-41fd-9162-c4c42249e4dc", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "%%capture\n", | |
| "client.run(silence_worker_warnings)" | |
| ] | |
| }, | |
| { | |
| "attachments": { | |
| "a0fa1797-e4dd-46fe-be59-ff4ecc997770.png": { | |
| "image/png": 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| } | |
| }, | |
| "cell_type": "markdown", | |
| "id": "ccfdfc10-5699-41b5-8bd9-803e93e17c7a", | |
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| "source": [ | |
| "<img src=\"attachment:a0fa1797-e4dd-46fe-be59-ff4ecc997770.png\" width=\"80%\"/>\n", | |
| "\n", | |
| "\n", | |
| "**Downloading and processing 4TB of data (broadband) ~= 18 hours to a day**\n", | |
| " * If we have the storage and compute available, downloading is not a bad option but we are creating copies that later need to be synced or potentially reprocessed.\n", | |
| "\n", | |
| "## Accessing Virtual Data Cubes\n", | |
| "\n", | |
| "Once created and persisted, virtual data cubes are accessible as Zarr regular stores. As of now there is not a canonical way to publish them and advertising them in CMR, although PODAAC/GESDISC have been prototyping using related-links. When we agree on what conventions to use accessing years worth of data will be as simple as \n", | |
| "\n", | |
| "```python\n", | |
| "vds = earthaccess.smart_open(short_name=\"SPL4SMGP\", virtualized=True)\n", | |
| "```" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 28, | |
| "id": "70cbe56d-32c5-4ecf-ad32-fbe405cdef28", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
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| "text": [ | |
| "CPU times: user 603 ms, sys: 34.1 ms, total: 637 ms\n", | |
| "Wall time: 1.73 s\n" | |
| ] | |
| }, | |
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| " min-width: 300px;\n", | |
| " max-width: 700px;\n", | |
| " line-height: 1.6;\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-obj-name,\n", | |
| ".xr-group-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-name::before {\n", | |
| " content: \"📁\";\n", | |
| " padding-right: 0.3em;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-name,\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", | |
| " margin-block-start: 0;\n", | |
| " margin-block-end: 0;\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", | |
| " margin: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input + label {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| " border: 2px solid transparent !important;\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) !important;\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", | |
| "}\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-top: 4px;\n", | |
| " margin-bottom: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-box {\n", | |
| " display: inline-grid;\n", | |
| " grid-template-columns: 0px 20px auto;\n", | |
| " width: 100%;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-box-vline {\n", | |
| " grid-column-start: 1;\n", | |
| " border-right: 0.2em solid;\n", | |
| " border-color: var(--xr-border-color);\n", | |
| " width: 0px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-box-hline {\n", | |
| " grid-column-start: 2;\n", | |
| " grid-row-start: 1;\n", | |
| " height: 1em;\n", | |
| " width: 20px;\n", | |
| " border-bottom: 0.2em solid;\n", | |
| " border-color: var(--xr-border-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-group-box-contents {\n", | |
| " grid-column-start: 3;\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", | |
| " border-color: var(--xr-background-color-row-odd);\n", | |
| " margin-bottom: 0;\n", | |
| " padding-top: 2px;\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", | |
| " border-color: var(--xr-background-color-row-even);\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", | |
| " border-top: 2px dotted var(--xr-background-color);\n", | |
| " padding-bottom: 20px !important;\n", | |
| " padding-top: 10px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in + label,\n", | |
| ".xr-var-data-in + label,\n", | |
| ".xr-index-data-in + label {\n", | |
| " padding: 0 1px;\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-data > pre,\n", | |
| ".xr-index-data > pre,\n", | |
| ".xr-var-data > table > tbody > tr {\n", | |
| " background-color: transparent !important;\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", | |
| "\n", | |
| ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n", | |
| ".xr-var-data-in:checked + label > .xr-icon-database,\n", | |
| ".xr-index-data-in:checked + label > .xr-icon-database {\n", | |
| " color: var(--xr-font-color0);\n", | |
| " filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n", | |
| " stroke-width: 0.8px;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 39TB\n", | |
| "Dimensions: (time: 30704, y: 1624, x: 3856)\n", | |
| "Coordinates:\n", | |
| " * time (time) datetime64[ns] 246kB 2015-03-31...\n", | |
| " * y (y) float64 13kB 7.31e+06 ... -7.31e+06\n", | |
| " * x (x) float64 31kB -1.736e+07 ... 1.736e+07\n", | |
| "Data variables: (12/49)\n", | |
| " baseflow_flux (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_column (time, y, x) float64 2TB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_lat (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_lon (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_row (time, y, x) float64 2TB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " depth_to_water_table_from_surface (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " specific_humidity_lowatmmodlay (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " surface_pressure (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " surface_temp (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " temp_lowatmmodlay (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " vegetation_greenness_fraction (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " windspeed_lowatmmodlay (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Source: v18.1.0\n", | |
| " Institution: NASA Global Modeling and Assimilation Office\n", | |
| " History: File written by ldas2daac.x\n", | |
| " Comment: HDF-5\n", | |
| " Filename: /discover/nobackup/projects/gmao/smap/SMAP_L4/L4_SM/Vv8010/...\n", | |
| " Title: SMAP L4_SM Geophysical (GPH) Data Granule\n", | |
| " Conventions: CF\n", | |
| " References: see SMAP L4_SM Product Specification Documentation\n", | |
| " Contact: http://gmao.gsfc.nasa.gov</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-95e3989e-545a-46f0-a655-557e28656640' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-95e3989e-545a-46f0-a655-557e28656640' 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>: 30704</li><li><span class='xr-has-index'>y</span>: 1624</li><li><span class='xr-has-index'>x</span>: 3856</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9adbb843-5c43-4bf8-81c7-ec46f6e97364' class='xr-section-summary-in' type='checkbox' checked><label for='section-9adbb843-5c43-4bf8-81c7-ec46f6e97364' class='xr-section-summary' >Coordinates: <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 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'>2015-03-31T01:30:00 ... 2025-10-...</div><input id='attrs-b7f7df55-b95f-4097-9022-38030ba0afcc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7f7df55-b95f-4097-9022-38030ba0afcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f814533b-b009-4ed8-aa9b-64dc1240660f' class='xr-var-data-in' type='checkbox'><label for='data-f814533b-b009-4ed8-aa9b-64dc1240660f' 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'><pre>array(['2015-03-31T01:30:00.000000000', '2015-03-31T04:30:00.000000000',\n", | |
| " '2015-03-31T07:30:00.000000000', ..., '2025-10-01T16:30:00.000000000',\n", | |
| " '2025-10-01T19:30:00.000000000', '2025-10-01T22:30:00.000000000'],\n", | |
| " shape=(30704,), dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.31e+06 7.301e+06 ... -7.31e+06</div><input id='attrs-7e751d8a-c2e4-4e8b-acf4-c41821f135ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e751d8a-c2e4-4e8b-acf4-c41821f135ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f06de955-3558-4443-a91f-1abe15021c98' class='xr-var-data-in' type='checkbox'><label for='data-f06de955-3558-4443-a91f-1abe15021c98' 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>long_name :</span></dt><dd>Y coordinate of cell center in EASE 2.0 global projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 7310037.171387, 7301029.115723, 7292021.060059, ..., -7292021.060059,\n", | |
| " -7301029.115723, -7310037.171387], shape=(1624,))</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'>-1.736e+07 -1.735e+07 ... 1.736e+07</div><input id='attrs-f99fd07b-ecb2-4653-920c-a5034ed58578' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f99fd07b-ecb2-4653-920c-a5034ed58578' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27313107-b9af-4b65-bc01-a8bbe7c11a7a' class='xr-var-data-in' type='checkbox'><label for='data-27313107-b9af-4b65-bc01-a8bbe7c11a7a' 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>long_name :</span></dt><dd>X coordinate of cell center in EASE 2.0 global projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-17363027.29248 , -17354019.236816, -17345011.181152, ...,\n", | |
| " 17345011.181152, 17354019.236816, 17363027.29248 ], shape=(3856,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-713c3fc7-fcd2-4388-9e39-d41edae50fac' class='xr-section-summary-in' type='checkbox' ><label for='section-713c3fc7-fcd2-4388-9e39-d41edae50fac' class='xr-section-summary' >Data variables: <span>(49)</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>baseflow_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-741eaf90-02ee-4522-b7a9-2e25c3704658' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-741eaf90-02ee-4522-b7a9-2e25c3704658' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be9476c7-a7b0-431e-978c-f639a9a088d4' class='xr-var-data-in' type='checkbox'><label for='data-be9476c7-a7b0-431e-978c-f639a9a088d4' 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>long_name :</span></dt><dd>Baseflow</dd><dt><span>valid_max :</span></dt><dd>0.009999999776482582</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_column</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-3947296b-4c2c-4fe1-93ed-336f27034a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3947296b-4c2c-4fe1-93ed-336f27034a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ae56f1e-c949-4b68-b904-30c1c1596249' class='xr-var-data-in' type='checkbox'><label for='data-5ae56f1e-c949-4b68-b904-30c1c1596249' 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>long_name :</span></dt><dd>The column index of each cell in the cylindrical 9 km Earth-fixed EASE-Grid 2.0. Type is Unsigned32.</dd><dt><span>valid_max :</span></dt><dd>3855</dd><dt><span>fmissing_value :</span></dt><dd>4294967294</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0</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> 1.40 TiB </td>\n", | |
| " <td> 47.78 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float64 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_lat</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-cef78621-104c-4001-ae47-699bf844b615' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cef78621-104c-4001-ae47-699bf844b615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dc40686-8b53-490e-9a07-44e9c86db051' class='xr-var-data-in' type='checkbox'><label for='data-8dc40686-8b53-490e-9a07-44e9c86db051' 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>long_name :</span></dt><dd>The geodetic latitude of the center of each cell in the cylindrical 9 km Earth-fixed EASE-Grid 2.0. Zero latitude represents the Equator. Positive latitudes represent locations North of the Equator. Negative latitudes represent locations South of the Equator.</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-90.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_lon</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-7b8967c0-b7ff-43d4-bc96-9242cfbc2ea8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b8967c0-b7ff-43d4-bc96-9242cfbc2ea8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b2fe8c-e948-4b2a-b3ec-cf153325d667' class='xr-var-data-in' type='checkbox'><label for='data-d1b2fe8c-e948-4b2a-b3ec-cf153325d667' 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>long_name :</span></dt><dd>The longitude of the center of each cell in the cylindrical 9 km Earth-fixed EASE-Grid 2.0. Zero longitude represents the Prime Meridian. Positive longitudes represent locations to the East of the Prime Meridian. Negative longitudes represent locations to the West of the Prime Meridian.</dd><dt><span>valid_max :</span></dt><dd>179.99899291992188</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
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| " <tr>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_row</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-241b3081-8240-48a0-a33e-cb5953c3f6d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-241b3081-8240-48a0-a33e-cb5953c3f6d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7ebbd9e-774a-4d55-854f-b08bb3cbc019' class='xr-var-data-in' type='checkbox'><label for='data-f7ebbd9e-774a-4d55-854f-b08bb3cbc019' 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>long_name :</span></dt><dd>The row index of each cell in the cylindrical 9 km Earth-fixed EASE-Grid 2.0. Type is Unsigned32.</dd><dt><span>valid_max :</span></dt><dd>1623</dd><dt><span>fmissing_value :</span></dt><dd>4294967294</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0</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> 1.40 TiB </td>\n", | |
| " <td> 47.78 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float64 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_to_water_table_from_surface</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-23729ee7-c6b8-440f-bd2e-e568af412ac6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23729ee7-c6b8-440f-bd2e-e568af412ac6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c845633-6f48-4080-9f07-7d8f285d0180' class='xr-var-data-in' type='checkbox'><label for='data-5c845633-6f48-4080-9f07-7d8f285d0180' 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>long_name :</span></dt><dd>Depth to water table from surface.</dd><dt><span>valid_max :</span></dt><dd>10.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>free_surface_water_on_peat_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-084cb595-f630-4856-b306-e1a053a308be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-084cb595-f630-4856-b306-e1a053a308be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c0f51a0-06a2-473f-bd70-8d5938743ce7' class='xr-var-data-in' type='checkbox'><label for='data-7c0f51a0-06a2-473f-bd70-8d5938743ce7' 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>long_name :</span></dt><dd>Free surface water flux on peatlands.</dd><dt><span>valid_max :</span></dt><dd>0.0010000000474974513</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-0.0010000000474974513</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heat_flux_ground</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-62c0fe90-2f0d-487a-a544-2139e5a61d8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62c0fe90-2f0d-487a-a544-2139e5a61d8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63e8afd2-9a1b-48a7-85c5-7e3589a908b0' class='xr-var-data-in' type='checkbox'><label for='data-63e8afd2-9a1b-48a7-85c5-7e3589a908b0' 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>long_name :</span></dt><dd>Downward ground heat flux into layer 1 of soil heat diffusion model</dd><dt><span>valid_max :</span></dt><dd>1000.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-1000.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
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| " <th> Dask graph </th>\n", | |
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| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heat_flux_latent</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-d4d21c4a-8fbf-4b86-8cab-90a3467b7f85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4d21c4a-8fbf-4b86-8cab-90a3467b7f85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b5dd426-f215-4bb9-b807-df559c462e9f' class='xr-var-data-in' type='checkbox'><label for='data-8b5dd426-f215-4bb9-b807-df559c462e9f' 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>long_name :</span></dt><dd>Latent heat flux from land (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>3000.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-2500.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
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| " <th> Data type </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heat_flux_sensible</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-07e66a26-cc56-4259-b944-9f4a5cd26744' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07e66a26-cc56-4259-b944-9f4a5cd26744' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6585cbae-a4b5-4456-8bc5-35e2afd6ba0e' class='xr-var-data-in' type='checkbox'><label for='data-6585cbae-a4b5-4456-8bc5-35e2afd6ba0e' 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>long_name :</span></dt><dd>Sensible heat flux from land (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>3000.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-2500.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <tr>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_evapotranspiration_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-4344854e-0db7-481f-bbba-85a52ae59a4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4344854e-0db7-481f-bbba-85a52ae59a4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4043f1b-5a58-4763-8ec8-5cc94296aa10' class='xr-var-data-in' type='checkbox'><label for='data-c4043f1b-5a58-4763-8ec8-5cc94296aa10' 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>long_name :</span></dt><dd>Evapotranspiration from land (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>0.0010000000474974513</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-0.0010000000474974513</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_fraction_saturated</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-05eb4105-b64c-47cd-b3ab-bf0f16291968' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05eb4105-b64c-47cd-b3ab-bf0f16291968' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-505ae999-eda8-4331-b2b4-3a3f11e7f4d8' class='xr-var-data-in' type='checkbox'><label for='data-505ae999-eda8-4331-b2b4-3a3f11e7f4d8' 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>long_name :</span></dt><dd>Fractional land area that is saturated and snow-free (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_fraction_snow_covered</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-4ea6e832-e4a2-454e-a1fe-1def492168de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ea6e832-e4a2-454e-a1fe-1def492168de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3451fe7-ded3-4a87-94ed-501dd40ab72f' class='xr-var-data-in' type='checkbox'><label for='data-e3451fe7-ded3-4a87-94ed-501dd40ab72f' 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>long_name :</span></dt><dd>Fractional land area that is snow-covered (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_fraction_unsaturated</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-5e597e1d-e373-4b56-8c20-8613f14b8884' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e597e1d-e373-4b56-8c20-8613f14b8884' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4cc2dcf-b8ae-4069-8071-8ca8ebb6be86' class='xr-var-data-in' type='checkbox'><label for='data-f4cc2dcf-b8ae-4069-8071-8ca8ebb6be86' 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>long_name :</span></dt><dd>Fractional land area that is unsaturated (but non-wilting) and snow-free (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_fraction_wilting</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-cb2ac053-f453-4b56-9df6-24e228c39471' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb2ac053-f453-4b56-9df6-24e228c39471' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-305f8885-771b-4c24-a2d8-7d822539de2f' class='xr-var-data-in' type='checkbox'><label for='data-305f8885-771b-4c24-a2d8-7d822539de2f' 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>long_name :</span></dt><dd>Fractional land area that is wilting and snow-free (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>leaf_area_index</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-581c81be-210d-4ff5-8c94-95a293d731a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-581c81be-210d-4ff5-8c94-95a293d731a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8791b545-ec80-49e6-b69b-3bc6aedfa6ba' class='xr-var-data-in' type='checkbox'><label for='data-8791b545-ec80-49e6-b69b-3bc6aedfa6ba' 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>long_name :</span></dt><dd>Vegetation leaf area index</dd><dt><span>valid_max :</span></dt><dd>10.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>m2 m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwrtm_vegopacity</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-6308ce94-27fa-49d8-b678-ce9476544aea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6308ce94-27fa-49d8-b678-ce9476544aea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e68a19e1-1317-437b-ac05-1c28f84b3922' class='xr-var-data-in' type='checkbox'><label for='data-e68a19e1-1317-437b-ac05-1c28f84b3922' 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>long_name :</span></dt><dd>Microwave radiative transfer model: Vegetation opacity.</dd><dt><span>valid_max :</span></dt><dd>2.5</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>net_downward_longwave_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-60a16e6d-a897-494b-83dc-10a7d0842dba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60a16e6d-a897-494b-83dc-10a7d0842dba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44b18c0e-4f0c-4bed-8f08-cda3b69d4da3' class='xr-var-data-in' type='checkbox'><label for='data-44b18c0e-4f0c-4bed-8f08-cda3b69d4da3' 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>long_name :</span></dt><dd>Net downward longwave flux over land (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>200.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-1000.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>net_downward_shortwave_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-cb50e4ee-bcb4-497e-ba8b-d4607cb3e95b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb50e4ee-bcb4-497e-ba8b-d4607cb3e95b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fa24b13-bfc9-41bc-b807-f10fe3ff14b0' class='xr-var-data-in' type='checkbox'><label for='data-4fa24b13-bfc9-41bc-b807-f10fe3ff14b0' 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>long_name :</span></dt><dd>Net downward shortwave flux over land (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>1365.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>overland_runoff_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-55b40ab5-1fcc-4b45-9f20-0fe9fffb01dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55b40ab5-1fcc-4b45-9f20-0fe9fffb01dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f87f751c-291b-4c9d-b30f-34ff516f4cd8' class='xr-var-data-in' type='checkbox'><label for='data-f87f751c-291b-4c9d-b30f-34ff516f4cd8' 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>long_name :</span></dt><dd>Overland (surface) runoff (including throughflow - excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>0.05000000074505806</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <td>\n", | |
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| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
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| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precipitation_total_surface_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-57d56e39-675b-4ca9-a5ea-d522f34652bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57d56e39-675b-4ca9-a5ea-d522f34652bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-610111ba-aa15-486d-be24-e844ec5ad566' class='xr-var-data-in' type='checkbox'><label for='data-610111ba-aa15-486d-be24-e844ec5ad566' 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>long_name :</span></dt><dd>Total surface precipitation (incl. snow fall)</dd><dt><span>valid_max :</span></dt><dd>0.05000000074505806</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radiation_longwave_absorbed_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-de4c4eee-d633-4cc6-9114-ca4029ea4d0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de4c4eee-d633-4cc6-9114-ca4029ea4d0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92beb0c8-991c-4b02-9d96-646328f41407' class='xr-var-data-in' type='checkbox'><label for='data-92beb0c8-991c-4b02-9d96-646328f41407' 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>long_name :</span></dt><dd>Absorbed (downward) longwave radiation at the surface</dd><dt><span>valid_max :</span></dt><dd>800.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>35.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radiation_shortwave_downward_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-2acabe8f-23fa-4908-bc9d-a4d220378eb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2acabe8f-23fa-4908-bc9d-a4d220378eb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88549d4c-16d0-4247-acac-d730dc5cf850' class='xr-var-data-in' type='checkbox'><label for='data-88549d4c-16d0-4247-acac-d730dc5cf850' 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>long_name :</span></dt><dd>Downward shortwave flux incident on the surface</dd><dt><span>valid_max :</span></dt><dd>1500.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_profile_wetness</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-5aa31d5c-d41d-458f-bf5b-dd4340498635' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5aa31d5c-d41d-458f-bf5b-dd4340498635' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2253e15-846a-4641-8036-8642e848f62f' class='xr-var-data-in' type='checkbox'><label for='data-f2253e15-846a-4641-8036-8642e848f62f' 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>long_name :</span></dt><dd>Total profile soil wetness (0 cm to model bedrock depth; wetness units). Soil wetness units (dimensionless) vary between 0 and 1, indicating relative saturation between completely dry conditions and completely saturated conditions, respectively. See also Appendix E in the PSD.</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_rootzone</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-2a9bcaeb-7a6b-4be9-a5be-9b9e5f10b399' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a9bcaeb-7a6b-4be9-a5be-9b9e5f10b399' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-996ea05a-7fc2-451d-b6ff-0a5b79899cba' class='xr-var-data-in' type='checkbox'><label for='data-996ea05a-7fc2-451d-b6ff-0a5b79899cba' 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>long_name :</span></dt><dd>Root zone soil moisture (0-100 cm)</dd><dt><span>valid_max :</span></dt><dd>0.8999999761581421</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_rootzone_pctl</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-0762b761-2c36-4ab6-91d1-aa1b7f171db7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0762b761-2c36-4ab6-91d1-aa1b7f171db7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08f071aa-56aa-4a6f-b563-6d4a8bc25356' class='xr-var-data-in' type='checkbox'><label for='data-08f071aa-56aa-4a6f-b563-6d4a8bc25356' 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>long_name :</span></dt><dd>Root zone soil moisture (0-100 cm; percentile units)</dd><dt><span>valid_max :</span></dt><dd>100.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <th> Dask graph </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_rootzone_wetness</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-2b374f08-76ca-47b1-8b5c-c0a88469bc46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b374f08-76ca-47b1-8b5c-c0a88469bc46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8aa9c425-7b87-4608-9d4c-a916c63aadc9' class='xr-var-data-in' type='checkbox'><label for='data-8aa9c425-7b87-4608-9d4c-a916c63aadc9' 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>long_name :</span></dt><dd>Root zone soil wetness (0-100 cm; wetness units). Soil wetness units (dimensionless) vary between 0 and 1, indicating relative saturation between completely dry conditions and completely saturated conditions, respectively. See also Appendix E in the PSD.</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_surface</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-c9c84387-f537-4616-8551-69d09f82a438' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9c84387-f537-4616-8551-69d09f82a438' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-411ee9f4-3b1d-4175-9713-e1b236cb68f4' class='xr-var-data-in' type='checkbox'><label for='data-411ee9f4-3b1d-4175-9713-e1b236cb68f4' 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>long_name :</span></dt><dd>Top layer soil moisture (0-5 cm)</dd><dt><span>valid_max :</span></dt><dd>0.8999999761581421</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <tr>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_surface_wetness</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-ff639523-ea74-46c2-bdeb-50a95cfa85a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff639523-ea74-46c2-bdeb-50a95cfa85a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1e9cd2e-5df8-4bd7-b6de-9535f2f66239' class='xr-var-data-in' type='checkbox'><label for='data-a1e9cd2e-5df8-4bd7-b6de-9535f2f66239' 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>long_name :</span></dt><dd>Top layer soil wetness (0-5 cm; wetness units). Soil wetness units (dimensionless) vary between 0 and 1, indicating relative saturation between completely dry conditions and completely saturated conditions, respectively. See also Appendix E in the PSD.</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
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| " <tr>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_mass</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-151b5dcc-c9b7-4938-aaed-593da30f8b00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-151b5dcc-c9b7-4938-aaed-593da30f8b00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33ceb656-69ff-4e34-a100-1d0d4ae5972a' class='xr-var-data-in' type='checkbox'><label for='data-33ceb656-69ff-4e34-a100-1d0d4ae5972a' 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>long_name :</span></dt><dd>Average snow mass (or snow water equivalent) over land fraction of grid cell (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>10000.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_melt_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-762cd006-f238-49bc-bc65-4b555828b276' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-762cd006-f238-49bc-bc65-4b555828b276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f2b5db9-17f6-4867-89d5-0c2fd53b988b' class='xr-var-data-in' type='checkbox'><label for='data-4f2b5db9-17f6-4867-89d5-0c2fd53b988b' 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>long_name :</span></dt><dd>Snowmelt (excluding areas of open water and permanent ice)</dd><dt><span>valid_max :</span></dt><dd>0.05000000074505806</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snowfall_surface_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-da2746d0-0214-475c-b887-b16d7077211f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da2746d0-0214-475c-b887-b16d7077211f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-424e6a29-83a5-40ab-aadc-0f1d320e4ef8' class='xr-var-data-in' type='checkbox'><label for='data-424e6a29-83a5-40ab-aadc-0f1d320e4ef8' 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>long_name :</span></dt><dd>Surface snow fall</dd><dt><span>valid_max :</span></dt><dd>0.05000000074505806</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
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| " <tr>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
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| " <th> Dask graph </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>soil_temp_layer1</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-e3c43dd4-8bf8-425c-8dff-66834a6c857c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3c43dd4-8bf8-425c-8dff-66834a6c857c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08298b25-9b6f-478c-8857-ffdbb7572d4f' class='xr-var-data-in' type='checkbox'><label for='data-08298b25-9b6f-478c-8857-ffdbb7572d4f' 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>long_name :</span></dt><dd>Soil temperature in layer 1 of soil heat diffusion model</dd><dt><span>valid_max :</span></dt><dd>340.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>210.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>soil_temp_layer2</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-257f6d15-a934-4d58-8b51-1c630f45f26f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-257f6d15-a934-4d58-8b51-1c630f45f26f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d580d205-afaa-4bad-986c-d9dd0466993d' class='xr-var-data-in' type='checkbox'><label for='data-d580d205-afaa-4bad-986c-d9dd0466993d' 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>long_name :</span></dt><dd>Soil temperature in layer 2 of soil heat diffusion model</dd><dt><span>valid_max :</span></dt><dd>330.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>210.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
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| " <tr>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>soil_temp_layer5</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-357e82dc-c92d-4645-a277-344d5764c41d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-357e82dc-c92d-4645-a277-344d5764c41d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01b9e261-05e5-441e-aee0-d92dd12a7a92' class='xr-var-data-in' type='checkbox'><label for='data-01b9e261-05e5-441e-aee0-d92dd12a7a92' 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>long_name :</span></dt><dd>Soil temperature in layer 5 of soil heat diffusion model</dd><dt><span>valid_max :</span></dt><dd>325.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>225.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
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| " <tr>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
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| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <th> Dask graph </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>soil_temp_layer6</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-1372a858-16ee-4533-af39-d3ce0b609423' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1372a858-16ee-4533-af39-d3ce0b609423' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7116b3dc-f549-4904-afe7-12ee23795b51' class='xr-var-data-in' type='checkbox'><label for='data-7116b3dc-f549-4904-afe7-12ee23795b51' 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>long_name :</span></dt><dd>Soil temperature in layer 6 of soil heat diffusion model</dd><dt><span>valid_max :</span></dt><dd>320.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>230.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
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| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
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| " <th> Data type </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>soil_water_infiltration_flux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-8b663b71-a6ee-444f-be83-3da3f90d5b5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b663b71-a6ee-444f-be83-3da3f90d5b5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ee5b339-bfd4-41a3-88b3-478a26cedeb3' class='xr-var-data-in' type='checkbox'><label for='data-8ee5b339-bfd4-41a3-88b3-478a26cedeb3' 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>long_name :</span></dt><dd>Soil water infiltration rate</dd><dt><span>valid_max :</span></dt><dd>0.05000000074505806</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>specific_humidity_lowatmmodlay</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-b7e9d1fa-5def-4936-a437-35c6cc4abc91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7e9d1fa-5def-4936-a437-35c6cc4abc91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aba3b1dc-edef-4bd3-8d2d-357c82c49392' class='xr-var-data-in' type='checkbox'><label for='data-aba3b1dc-edef-4bd3-8d2d-357c82c49392' 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>long_name :</span></dt><dd>Air specific humidity at center height of lowest atmospheric model layer</dd><dt><span>valid_max :</span></dt><dd>0.4000000059604645</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_pressure</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-59f2fc8e-dcdb-47ea-b4f6-6c923dc3d955' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59f2fc8e-dcdb-47ea-b4f6-6c923dc3d955' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dea5fc5b-1de7-4320-9747-6d4805bb22f6' class='xr-var-data-in' type='checkbox'><label for='data-dea5fc5b-1de7-4320-9747-6d4805bb22f6' 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>long_name :</span></dt><dd>Surface pressure</dd><dt><span>valid_max :</span></dt><dd>110000.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>40000.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
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| " <tr>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
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| " <tr>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vegetation_greenness_fraction</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-d14e157c-63b8-4806-80ec-2d665ab9168d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d14e157c-63b8-4806-80ec-2d665ab9168d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b0e08a0-9865-4c7d-aead-c32499be2ad8' class='xr-var-data-in' type='checkbox'><label for='data-9b0e08a0-9865-4c7d-aead-c32499be2ad8' 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>long_name :</span></dt><dd>Vegetation "greenness" or fraction of transpiring leaves averaged over the land area (excluding areas of open water and permanent ice) of the grid cell</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>windspeed_lowatmmodlay</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray></div><input id='attrs-ee2e6e0b-43e3-4e3f-95bb-c43eb9c994b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee2e6e0b-43e3-4e3f-95bb-c43eb9c994b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b53e6eec-04e0-4ae7-afe1-d4cdd56c9d2f' class='xr-var-data-in' type='checkbox'><label for='data-b53e6eec-04e0-4ae7-afe1-d4cdd56c9d2f' 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>long_name :</span></dt><dd>Surface wind speed at center height of lowest atmospheric model layer</dd><dt><span>valid_max :</span></dt><dd>60.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>-60.0</dd></dl></div><div class='xr-var-data'><table>\n", | |
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| " <td>\n", | |
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| " <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> 716.27 GiB </td>\n", | |
| " <td> 23.89 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (30704, 1624, 3856) </td>\n", | |
| " <td> (1, 1624, 3856) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 30704 chunks in 2 graph layers </td>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| "text/plain": [ | |
| "<xarray.Dataset> Size: 39TB\n", | |
| "Dimensions: (time: 30704, y: 1624, x: 3856)\n", | |
| "Coordinates:\n", | |
| " * time (time) datetime64[ns] 246kB 2015-03-31...\n", | |
| " * y (y) float64 13kB 7.31e+06 ... -7.31e+06\n", | |
| " * x (x) float64 31kB -1.736e+07 ... 1.736e+07\n", | |
| "Data variables: (12/49)\n", | |
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| " cell_column (time, y, x) float64 2TB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_lat (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " cell_lon (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
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| " depth_to_water_table_from_surface (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " specific_humidity_lowatmmodlay (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " surface_pressure (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
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| " vegetation_greenness_fraction (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| " windspeed_lowatmmodlay (time, y, x) float32 769GB dask.array<chunksize=(1, 1624, 3856), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Source: v18.1.0\n", | |
| " Institution: NASA Global Modeling and Assimilation Office\n", | |
| " History: File written by ldas2daac.x\n", | |
| " Comment: HDF-5\n", | |
| " Filename: /discover/nobackup/projects/gmao/smap/SMAP_L4/L4_SM/Vv8010/...\n", | |
| " Title: SMAP L4_SM Geophysical (GPH) Data Granule\n", | |
| " Conventions: CF\n", | |
| " References: see SMAP L4_SM Product Specification Documentation\n", | |
| " Contact: http://gmao.gsfc.nasa.gov" | |
| ] | |
| }, | |
| "execution_count": 28, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "%%time\n", | |
| "\n", | |
| "refs = \"https://its-live-data.s3-us-west-2.amazonaws.com/test-space/vds/SPL4SMGP.parquet\"\n", | |
| "daac_fs = ea.get_fsspec_https_session()\n", | |
| "\n", | |
| "fs = fsspec.filesystem(\"reference\",\n", | |
| " fo=refs,\n", | |
| " remote_protocol=\"https\",\n", | |
| " asynchronous=True,\n", | |
| " remote_options={\"asynchronous\": True, **daac_fs.storage_options}\n", | |
| " )\n", | |
| "\n", | |
| "store = zarr.storage.FsspecStore(fs, read_only=True)\n", | |
| "ds = xr.open_zarr(store, consolidated=False)\n", | |
| "ds" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 22, | |
| "id": "c9ed2908-9b62-4112-b07d-5ad784cc5ef9", | |
| "metadata": { | |
| "jupyter": { | |
| "source_hidden": true | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def get_seasonal_ts(ds, varname, lat, lon, month_start, month_end,\n", | |
| " window_days=7, split_day_night=True):\n", | |
| " WGS84 = ccrs.PlateCarree()\n", | |
| " EASEGrid2 = ccrs.epsg(6933)\n", | |
| " x, y = EASEGrid2.transform_point(lon, lat, WGS84)\n", | |
| " da = ds[varname].sel(x=x, y=y, method=\"nearest\")\n", | |
| " \n", | |
| " if month_end < month_start:\n", | |
| " mask = (da.time.dt.month >= month_start) | (da.time.dt.month <= month_end)\n", | |
| " else:\n", | |
| " mask = (da.time.dt.month >= month_start) & (da.time.dt.month <= month_end)\n", | |
| " \n", | |
| " da_seasonal = da.sel(time=mask)\n", | |
| " if not split_day_night:\n", | |
| " return da_seasonal.rolling(time=window_days, center=True).mean()\n", | |
| " \n", | |
| " hour = da_seasonal.time.dt.hour\n", | |
| " da_day = da_seasonal.where((hour >= 6) & (hour < 18), drop=True)\n", | |
| " da_night = da_seasonal.where((hour < 6) | (hour >= 18), drop=True)\n", | |
| " \n", | |
| " day_rolling = da_day.rolling(time=window_days, center=True).mean()\n", | |
| " night_rolling = da_night.rolling(time=window_days, center=True).mean()\n", | |
| " \n", | |
| " combined = xr.concat([day_rolling, night_rolling],\n", | |
| " dim=xr.DataArray([\"day\", \"night\"], dims=\"period\", name=\"period\"),\n", | |
| " join=\"outer\")\n", | |
| " \n", | |
| " return combined\n" | |
| ] | |
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| "execution_count": 23, | |
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| " 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", | |
| " border-color: var(--xr-background-color-row-odd);\n", | |
| " margin-bottom: 0;\n", | |
| " padding-top: 2px;\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", | |
| " border-color: var(--xr-background-color-row-even);\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", | |
| " border-top: 2px dotted var(--xr-background-color);\n", | |
| " padding-bottom: 20px !important;\n", | |
| " padding-top: 10px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in + label,\n", | |
| ".xr-var-data-in + label,\n", | |
| ".xr-index-data-in + label {\n", | |
| " padding: 0 1px;\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-data > pre,\n", | |
| ".xr-index-data > pre,\n", | |
| ".xr-var-data > table > tbody > tr {\n", | |
| " background-color: transparent !important;\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", | |
| "\n", | |
| ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n", | |
| ".xr-var-data-in:checked + label > .xr-icon-database,\n", | |
| ".xr-index-data-in:checked + label > .xr-icon-database {\n", | |
| " color: var(--xr-font-color0);\n", | |
| " filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n", | |
| " stroke-width: 0.8px;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'sm_surface_wetness' (period: 2, time: 7856)> Size: 63kB\n", | |
| "dask.array<concatenate, shape=(2, 7856), dtype=float32, chunksize=(1, 8), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * period (period) <U5 40B 'day' 'night'\n", | |
| " * time (time) datetime64[ns] 63kB 2015-03-31T01:30:00 ... 2025-05-31T22...\n", | |
| " x float64 8B -1.069e+07\n", | |
| " y float64 8B 3.563e+06\n", | |
| "Attributes:\n", | |
| " long_name: Top layer soil wetness (0-5 cm; wetness units). Soil w...\n", | |
| " valid_max: 1.0\n", | |
| " fmissing_value: -9999.0\n", | |
| " DIMENSION_LABELS: ['y', 'x']\n", | |
| " units: dimensionless\n", | |
| " grid_mapping: EASE2_global_projection\n", | |
| " valid_min: 0.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>'sm_surface_wetness'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>period</span>: 2</li><li><span class='xr-has-index'>time</span>: 7856</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b2c63e7f-286f-4b6d-8195-b6a39fcc444b' class='xr-array-in' type='checkbox' checked><label for='section-b2c63e7f-286f-4b6d-8195-b6a39fcc444b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(1, 6), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 61.38 kiB </td>\n", | |
| " <td> 32 B </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (2, 7856) </td>\n", | |
| " <td> (1, 8) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 2618 chunks in 69 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=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"12\" x2=\"120\" y2=\"12\" />\n", | |
| " <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n", | |
| " <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n", | |
| " <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n", | |
| " <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n", | |
| " <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n", | |
| " <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n", | |
| " <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n", | |
| " <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n", | |
| " <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n", | |
| " <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n", | |
| " <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n", | |
| " <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n", | |
| " <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n", | |
| " <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n", | |
| " <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n", | |
| " <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n", | |
| " <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"25\" />\n", | |
| " <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >7856</text>\n", | |
| " <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">2</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></div></li><li class='xr-section-item'><input id='section-bb0cc02c-60e6-4c8e-8909-ec314a593615' class='xr-section-summary-in' type='checkbox' checked><label for='section-bb0cc02c-60e6-4c8e-8909-ec314a593615' 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'>period</span></div><div class='xr-var-dims'>(period)</div><div class='xr-var-dtype'><U5</div><div class='xr-var-preview xr-preview'>'day' 'night'</div><input id='attrs-55c849a4-be74-4533-b8ec-e3cc1804a57d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55c849a4-be74-4533-b8ec-e3cc1804a57d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-500f3e97-95b7-454b-9ebd-e2a196c11f9a' class='xr-var-data-in' type='checkbox'><label for='data-500f3e97-95b7-454b-9ebd-e2a196c11f9a' 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'><pre>array(['day', 'night'], dtype='<U5')</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'>2015-03-31T01:30:00 ... 2025-05-...</div><input id='attrs-619f186d-e8ee-4de8-be0a-aed7361ef032' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-619f186d-e8ee-4de8-be0a-aed7361ef032' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b8da19-39c0-4b57-b4eb-dcd3e98781bf' class='xr-var-data-in' type='checkbox'><label for='data-d1b8da19-39c0-4b57-b4eb-dcd3e98781bf' 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'><pre>array(['2015-03-31T01:30:00.000000000', '2015-03-31T04:30:00.000000000',\n", | |
| " '2015-03-31T07:30:00.000000000', ..., '2025-05-31T16:30:00.000000000',\n", | |
| " '2025-05-31T19:30:00.000000000', '2025-05-31T22:30:00.000000000'],\n", | |
| " shape=(7856,), dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.069e+07</div><input id='attrs-2cb15112-4d4e-4db8-be9e-66c48ed4833b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cb15112-4d4e-4db8-be9e-66c48ed4833b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffa11a18-1433-4db9-bcdb-2739bfee2e64' class='xr-var-data-in' type='checkbox'><label for='data-ffa11a18-1433-4db9-bcdb-2739bfee2e64' 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>long_name :</span></dt><dd>X coordinate of cell center in EASE 2.0 global projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-10688058.04541016)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.563e+06</div><input id='attrs-ec8ee3ec-0248-4022-ad29-09728820c132' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec8ee3ec-0248-4022-ad29-09728820c132' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58b1c4f9-c4c8-4d00-9660-9285049b9a2e' class='xr-var-data-in' type='checkbox'><label for='data-58b1c4f9-c4c8-4d00-9660-9285049b9a2e' 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>long_name :</span></dt><dd>Y coordinate of cell center in EASE 2.0 global projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(3562686.01513672)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f782b993-411f-4de0-bbb9-ee7f2612ec92' class='xr-section-summary-in' type='checkbox' checked><label for='section-f782b993-411f-4de0-bbb9-ee7f2612ec92' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Top layer soil wetness (0-5 cm; wetness units). Soil wetness units (dimensionless) vary between 0 and 1, indicating relative saturation between completely dry conditions and completely saturated conditions, respectively. See also Appendix E in the PSD.</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>fmissing_value :</span></dt><dd>-9999.0</dd><dt><span>DIMENSION_LABELS :</span></dt><dd>['y', 'x']</dd><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>grid_mapping :</span></dt><dd>EASE2_global_projection</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.DataArray 'sm_surface_wetness' (period: 2, time: 7856)> Size: 63kB\n", | |
| "dask.array<concatenate, shape=(2, 7856), dtype=float32, chunksize=(1, 8), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * period (period) <U5 40B 'day' 'night'\n", | |
| " * time (time) datetime64[ns] 63kB 2015-03-31T01:30:00 ... 2025-05-31T22...\n", | |
| " x float64 8B -1.069e+07\n", | |
| " y float64 8B 3.563e+06\n", | |
| "Attributes:\n", | |
| " long_name: Top layer soil wetness (0-5 cm; wetness units). Soil w...\n", | |
| " valid_max: 1.0\n", | |
| " fmissing_value: -9999.0\n", | |
| " DIMENSION_LABELS: ['y', 'x']\n", | |
| " units: dimensionless\n", | |
| " grid_mapping: EASE2_global_projection\n", | |
| " valid_min: 0.0" | |
| ] | |
| }, | |
| "execution_count": 23, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# lat, lon = 40.0, -105.0\n", | |
| "lon, lat = -110.78, 29.15\n", | |
| "\n", | |
| "da = get_seasonal_ts(\n", | |
| " ds,\n", | |
| " \"sm_surface_wetness\",\n", | |
| " lat,\n", | |
| " lon,\n", | |
| " month_start=3,\n", | |
| " month_end=5, \n", | |
| " window_days=7)\n", | |
| "da" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "id": "0013493c-63ab-4e4e-bd4d-1ab729eb4f3b", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "cluster.scale(32)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 26, | |
| "id": "63f0f77a-40f9-4fb0-b703-98210937083b", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "CPU times: user 1.05 s, sys: 72 ms, total: 1.12 s\n", | |
| "Wall time: 1min 26s\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
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