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{
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" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
" if (id !== undefined) {\n",
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" 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",
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" } else {\n",
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" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
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" if (window.requirejs) {\n",
" window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
" root._bokeh_is_loading = css_urls.length + 0;\n",
" } else {\n",
" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
" }\n",
"\n",
" const existing_stylesheets = []\n",
" const links = document.getElementsByTagName('link')\n",
" for (let i = 0; i < links.length; i++) {\n",
" const link = links[i]\n",
" if (link.href != null) {\n",
" existing_stylesheets.push(link.href)\n",
" }\n",
" }\n",
" for (let i = 0; i < css_urls.length; i++) {\n",
" const url = css_urls[i];\n",
" const escaped = encodeURI(url)\n",
" if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
" on_load()\n",
" continue;\n",
" }\n",
" const element = document.createElement(\"link\");\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.rel = \"stylesheet\";\n",
" element.type = \"text/css\";\n",
" element.href = url;\n",
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
" document.body.appendChild(element);\n",
" } var existing_scripts = []\n",
" const scripts = document.getElementsByTagName('script')\n",
" for (let i = 0; i < scripts.length; i++) {\n",
" var script = scripts[i]\n",
" if (script.src != null) {\n",
" existing_scripts.push(script.src)\n",
" }\n",
" }\n",
" for (let i = 0; i < js_urls.length; i++) {\n",
" const url = js_urls[i];\n",
" const escaped = encodeURI(url)\n",
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
" if (!window.requirejs) {\n",
" on_load();\n",
" }\n",
" continue;\n",
" }\n",
" const element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.src = url;\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" for (let i = 0; i < js_modules.length; i++) {\n",
" const url = js_modules[i];\n",
" const escaped = encodeURI(url)\n",
" if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
" if (!window.requirejs) {\n",
" on_load();\n",
" }\n",
" continue;\n",
" }\n",
" var element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.src = url;\n",
" element.type = \"module\";\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" for (const name in js_exports) {\n",
" const url = js_exports[name];\n",
" const escaped = encodeURI(url)\n",
" if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
" if (!window.requirejs) {\n",
" on_load();\n",
" }\n",
" continue;\n",
" }\n",
" var element = document.createElement('script');\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.type = \"module\";\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" element.textContent = `\n",
" import ${name} from \"${url}\"\n",
" window.${name} = ${name}\n",
" window._bokeh_on_load()\n",
" `\n",
" document.head.appendChild(element);\n",
" }\n",
" if (!js_urls.length && !js_modules.length) {\n",
" on_load()\n",
" }\n",
" };\n",
"\n",
" function inject_raw_css(css) {\n",
" const element = document.createElement(\"style\");\n",
" element.appendChild(document.createTextNode(css));\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" const js_urls = [\"https://cdn.holoviz.org/panel/1.5.4/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n",
" const js_modules = [];\n",
" const js_exports = {};\n",
" const css_urls = [];\n",
" const inline_js = [ function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
" },\n",
"function(Bokeh) {} // ensure no trailing comma for IE\n",
" ];\n",
"\n",
" function run_inline_js() {\n",
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
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" try {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" } catch(e) {\n",
" if (!reloading) {\n",
" throw e;\n",
" }\n",
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" 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",
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" }\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",
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" // to determine whether there is an ongoing attempt to initialize\n",
" // bokeh, however for backward compatibility we also try to ensure\n",
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
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" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
" // If the timeout and bokeh was not successfully loaded we reset\n",
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" root._bokeh_timeout = Date.now() + 5000;\n",
" root._bokeh_is_initializing = false;\n",
" root._bokeh_onload_callbacks = undefined;\n",
" root._bokeh_is_loading = 0\n",
" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
" load_or_wait();\n",
" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
" setTimeout(load_or_wait, 100);\n",
" } else {\n",
" root._bokeh_is_initializing = true\n",
" root._bokeh_onload_callbacks = []\n",
" const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
" if (!reloading && !bokeh_loaded) {\n",
" if (root.Bokeh) {\n",
" root.Bokeh = undefined;\n",
" }\n",
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" }\n",
" load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
" }\n",
" // Give older versions of the autoload script a head-start to ensure\n",
" // they initialize before we start loading newer version.\n",
" setTimeout(load_or_wait, 100)\n",
"}(window));"
],
"application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const py_version = '3.5.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n con
},
"metadata": {},
"output_type": "display_data"
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{
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"\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",
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" * 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",
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" * 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",
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" 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",
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" }\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",
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" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
" } else {\n",
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" }\n",
" } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
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" 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",
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" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
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" window.Bokeh.documents.splice(i, 1);\n",
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"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",
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" function append_mime(data, metadata, element) {\n",
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" var toinsert = this.create_output_subarea(\n",
" metadata,\n",
" CLASS_NAME,\n",
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" events.on('delete.Cell', handle_clear_output);\n",
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"\n",
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
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"source": [
"\n",
"import importlib\n",
"import new_import\n",
"importlib.reload(new_import)\n",
"\n",
"from new_import import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "fc5decb7-259f-4df5-abca-f287035c55ec",
"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"Starting new cluster.\n"
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"text": [
"2025-02-14 01:02:35,415 - distributed.client - ERROR - Failed to reconnect to scheduler after 30.00 seconds, closing client\n"
]
}
],
"source": [
"cluster, client = notebook_utils.initialize_dask(use_gateway=True, workers=(1,10))\n",
"# Khai báo 1 Datacube là dc\n",
"dc = datacube.Datacube()\n",
"client"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "46931660-ebb5-40de-84fc-afc150c4855b",
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"outputs": [],
"source": [
"date_range = ('2023-09-01', '2023-10-01')\n",
"longtitude_range = (105.5, 106.4)\n",
"latitude_range = (9.2, 10.0) \n",
"\n",
"coordinates = (longtitude_range, latitude_range)"
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".xr-var-item > div,\n",
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".xr-var-item > .xr-var-name span {\n",
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"\n",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
"Dimensions: (time: 3, y: 8874, x: 9902)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 24B 2023-09-01T22:46:18.500000 ... 202...\n",
" * y (y) float64 71kB 1.106e+06 1.106e+06 ... 1.017e+06 1.017e+06\n",
" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
" spatial_ref int32 4B 32648\n",
"Data variables:\n",
" vv (time, y, x) float32 1GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" vh (time, y, x) float32 1GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
"Attributes:\n",
" crs: EPSG:32648\n",
" grid_mapping: spatial_ref</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2b483c75-694e-433d-b8ac-b002d2a6704c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2b483c75-694e-433d-b8ac-b002d2a6704c' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3</li><li><span class='xr-has-index'>y</span>: 8874</li><li><span class='xr-has-index'>x</span>: 9902</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6b1ee46a-06b6-4abd-b2c3-84cbd840082d' class='xr-section-summary-in' type='checkbox' checked><label for='section-6b1ee46a-06b6-4abd-b2c3-84cbd840082d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-01T22:46:18.500000 ... 2...</div><input id='attrs-296c9e31-1850-441a-a1c6-adc843ce3793' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-296c9e31-1850-441a-a1c6-adc843ce3793' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-294d981d-edae-4092-8c3c-4c462ab105f1' class='xr-var-data-in' type='checkbox'><label for='data-294d981d-edae-4092-8c3c-4c462ab105f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2023-09-01T22:46:18.500000000&#x27;, &#x27;2023-09-13T22:46:18.500000000&#x27;,\n",
" &#x27;2023-09-25T22:46:19.500000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e+06 1.106e+06 ... 1.017e+06</div><input id='attrs-1f44bbc7-87d5-40c7-bcbf-420c73b3cbcd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f44bbc7-87d5-40c7-bcbf-420c73b3cbcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32f5910d-0603-488f-a2ea-5cadecb10e40' class='xr-var-data-in' type='checkbox'><label for='data-32f5910d-0603-488f-a2ea-5cadecb10e40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1105735., 1105725., 1105715., ..., 1017025., 1017015., 1017005.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.548e+05 5.548e+05 ... 6.538e+05</div><input id='attrs-923f4f21-569e-46d4-b1b5-395dc34f0521' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-923f4f21-569e-46d4-b1b5-395dc34f0521' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3af90b48-2b33-4c38-b16a-ada4d336f0bb' class='xr-var-data-in' type='checkbox'><label for='data-3af90b48-2b33-4c38-b16a-ada4d336f0bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([554795., 554805., 554815., ..., 653785., 653795., 653805.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-22ea982b-61a6-4e37-b26f-1aff6a0d833b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22ea982b-61a6-4e37-b26f-1aff6a0d833b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fef845d-2e75-43ac-a625-6193cdfd69c3' class='xr-var-data-in' type='checkbox'><label for='data-0fef845d-2e75-43ac-a625-6193cdfd69c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-3e82f8cb-b661-478f-8ff1-d01e432f5f94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e82f8cb-b661-478f-8ff1-d01e432f5f94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4625a6d1-7e26-4f56-9a21-f4b9c39ed64c' class='xr-var-data-in' type='checkbox'><label for='data-4625a6d1-7e26-4f56-9a21-f4b9c39ed64c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>intensity</dd><dt><span>nodata :</span></dt><dd>nan</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
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" &#x27;2023-09-25 22:46:19.500000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-48a24e42-fa8c-4310-9342-17e9d29b9b3e' class='xr-index-data-in' type='checkbox'/><label for='index-48a24e42-fa8c-4310-9342-17e9d29b9b3e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1105735.0, 1105725.0, 1105715.0, 1105705.0, 1105695.0, 1105685.0,\n",
" 1105675.0, 1105665.0, 1105655.0, 1105645.0,\n",
" ...\n",
" 1017095.0, 1017085.0, 1017075.0, 1017065.0, 1017055.0, 1017045.0,\n",
" 1017035.0, 1017025.0, 1017015.0, 1017005.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=8874))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-8d71422c-ac45-4d97-b005-743ffde4de52' class='xr-index-data-in' type='checkbox'/><label for='index-8d71422c-ac45-4d97-b005-743ffde4de52' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([554795.0, 554805.0, 554815.0, 554825.0, 554835.0, 554845.0, 554855.0,\n",
" 554865.0, 554875.0, 554885.0,\n",
" ...\n",
" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
" 653785.0, 653795.0, 653805.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9e0e1779-f3f6-4316-a7e2-0282427ef964' class='xr-section-summary-in' type='checkbox' checked><label for='section-9e0e1779-f3f6-4316-a7e2-0282427ef964' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 9GB\n",
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"Coordinates:\n",
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" red (time, y, x) float32 4GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" nir (time, y, x) float32 4GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
" scl (time, y, x) uint8 1GB dask.array&lt;chunksize=(1, 2048, 2048), meta=np.ndarray&gt;\n",
"Attributes:\n",
" crs: EPSG:32648\n",
" grid_mapping: spatial_ref</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-94484c3c-9b1e-4b86-8ac2-ec178c2d566a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-94484c3c-9b1e-4b86-8ac2-ec178c2d566a' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 12</li><li><span class='xr-has-index'>y</span>: 8874</li><li><span class='xr-has-index'>x</span>: 9902</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f693cce6-8a0b-4acb-b2dc-6e5238f8b8eb' class='xr-section-summary-in' type='checkbox' checked><label for='section-f693cce6-8a0b-4acb-b2dc-6e5238f8b8eb' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-02T03:35:16.627000 ... 2...</div><input id='attrs-962dfa44-fc50-4e68-aff5-f5a5b9b9df70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-962dfa44-fc50-4e68-aff5-f5a5b9b9df70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b49b18f1-57da-4b37-9cae-4da2c7651eb0' class='xr-var-data-in' type='checkbox'><label for='data-b49b18f1-57da-4b37-9cae-4da2c7651eb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2023-09-02T03:35:16.627000000&#x27;, &#x27;2023-09-04T03:25:21.856000000&#x27;,\n",
" &#x27;2023-09-07T03:35:17.134000000&#x27;, &#x27;2023-09-09T03:25:20.648000000&#x27;,\n",
" &#x27;2023-09-12T03:35:15.326000000&#x27;, &#x27;2023-09-14T03:25:35.755000000&#x27;,\n",
" &#x27;2023-09-17T03:35:15.269000000&#x27;, &#x27;2023-09-19T03:25:24.089000000&#x27;,\n",
" &#x27;2023-09-22T03:35:15.439000000&#x27;, &#x27;2023-09-24T03:25:18.524000000&#x27;,\n",
" &#x27;2023-09-27T03:35:14.112000000&#x27;, &#x27;2023-09-29T03:25:19.046000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e+06 1.106e+06 ... 1.017e+06</div><input id='attrs-316e8be1-7601-4d6c-8837-976dd4289575' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-316e8be1-7601-4d6c-8837-976dd4289575' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-307723a3-e5f2-42de-9bdc-3418a5c76fa6' class='xr-var-data-in' type='checkbox'><label for='data-307723a3-e5f2-42de-9bdc-3418a5c76fa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1105735., 1105725., 1105715., ..., 1017025., 1017015., 1017005.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.548e+05 5.548e+05 ... 6.538e+05</div><input id='attrs-0b1df866-0130-49f8-b98a-53efadcd1ded' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b1df866-0130-49f8-b98a-53efadcd1ded' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d3292ad-a1f2-4c44-8a0e-524228bf524a' class='xr-var-data-in' type='checkbox'><label for='data-8d3292ad-a1f2-4c44-8a0e-524228bf524a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([554795., 554805., 554815., ..., 653785., 653795., 653805.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-dae0b881-715b-44f7-9e8c-637d9d0c5c46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dae0b881-715b-44f7-9e8c-637d9d0c5c46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f5f8400-f843-4211-9895-03244787b9de' class='xr-var-data-in' type='checkbox'><label for='data-6f5f8400-f843-4211-9895-03244787b9de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pr
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6be8d0fe-28dc-43d0-9f2e-9761a7ca51ef' class='xr-section-summary-in' type='checkbox' ><label for='section-6be8d0fe-28dc-43d0-9f2e-9761a7ca51ef' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-91716114-261e-4be4-a6fc-68574a420d35' class='xr-index-data-in' type='checkbox'/><label for='index-91716114-261e-4be4-a6fc-68574a420d35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2023-09-02 03:35:16.627000&#x27;, &#x27;2023-09-04 03:25:21.856000&#x27;,\n",
" &#x27;2023-09-07 03:35:17.134000&#x27;, &#x27;2023-09-09 03:25:20.648000&#x27;,\n",
" &#x27;2023-09-12 03:35:15.326000&#x27;, &#x27;2023-09-14 03:25:35.755000&#x27;,\n",
" &#x27;2023-09-17 03:35:15.269000&#x27;, &#x27;2023-09-19 03:25:24.089000&#x27;,\n",
" &#x27;2023-09-22 03:35:15.439000&#x27;, &#x27;2023-09-24 03:25:18.524000&#x27;,\n",
" &#x27;2023-09-27 03:35:14.112000&#x27;, &#x27;2023-09-29 03:25:19.046000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2d4ae5d0-a1d5-4a66-a75e-4dbdb5285f97' class='xr-index-data-in' type='checkbox'/><label for='index-2d4ae5d0-a1d5-4a66-a75e-4dbdb5285f97' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1105735.0, 1105725.0, 1105715.0, 1105705.0, 1105695.0, 1105685.0,\n",
" 1105675.0, 1105665.0, 1105655.0, 1105645.0,\n",
" ...\n",
" 1017095.0, 1017085.0, 1017075.0, 1017065.0, 1017055.0, 1017045.0,\n",
" 1017035.0, 1017025.0, 1017015.0, 1017005.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=8874))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4e950243-05f7-47f5-8be1-5d6db05fa502' class='xr-index-data-in' type='checkbox'/><label for='index-4e950243-05f7-47f5-8be1-5d6db05fa502' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([554795.0, 554805.0, 554815.0, 554825.0, 554835.0, 554845.0, 554855.0,\n",
" 554865.0, 554875.0, 554885.0,\n",
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" 653715.0, 653725.0, 653735.0, 653745.0, 653755.0, 653765.0, 653775.0,\n",
" 653785.0, 653795.0, 653805.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=9902))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8865d5ab-175a-4adf-951f-e3ac4831ed08' class='xr-section-summary-in' type='checkbox' checked><label for='section-8865d5ab-175a-4adf-951f-e3ac4831ed08' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 9GB\n",
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"Coordinates:\n",
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" * x (x) float64 79kB 5.548e+05 5.548e+05 ... 6.538e+05 6.538e+05\n",
" spatial_ref int32 4B 32648\n",
"Data variables:\n",
" red (time, y, x) float32 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
" nir (time, y, x) float32 4GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
" scl (time, y, x) uint8 1GB dask.array<chunksize=(1, 2048, 2048), meta=np.ndarray>\n",
"Attributes:\n",
" crs: EPSG:32648\n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dsvh, dsvv = load_data_sen1(dc, date_range, coordinates)\n",
"data_sen2 = load_data_sen2(dc, date_range, coordinates)\n",
"notebook_utils.heading(notebook_utils.xarray_object_size(data_sen2))\n",
"display(data_sen2)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "0a2d24b1-76f2-47c7-9b66-d41185fda32e",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/env/lib/python3.12/site-packages/xarray/groupers.py:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
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"model_id": "4c49ea68bc414bd19b9e66621b9b7f97",
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"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"average_vh = calculate_average(dsvh, time_pattern='1M')\n",
"progress(average_vh)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "73576914-a371-4cc1-a0fd-226e2512608b",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/env/lib/python3.12/site-packages/xarray/groupers.py:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
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},
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}
],
"source": [
"average_vv = calculate_average(dsvv, time_pattern='1M')\n",
"progress(average_vv)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f8bc286b-7c61-4b3c-9399-237dff32af51",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'0': 'no data',\n",
" '1': 'saturated or defective',\n",
" '2': 'dark area pixels',\n",
" '3': 'cloud shadows',\n",
" '4': 'vegetation',\n",
" '5': 'bare soils',\n",
" '6': 'water',\n",
" '7': 'unclassified',\n",
" '8': 'cloud medium probability',\n",
" '9': 'cloud high probability',\n",
" '10': 'thin cirrus',\n",
" '11': 'snow or ice'}"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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"version_minor": 0
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"text/plain": [
"VBox()"
]
},
"metadata": {},
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}
],
"source": [
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"progress(result)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "40c69eed-9775-48fe-a13c-1a634912082f",
"metadata": {},
"outputs": [],
"source": [
"dsNDVI = calculate_indices(result, index='NDVI', satellite_mission='s2')\n",
"ndvi = dsNDVI[\"NDVI\"]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "83041967-f770-4bf6-8617-c1842e10da7e",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/env/lib/python3.12/site-packages/xarray/groupers.py:487: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
" self.index_grouper = pd.Grouper(\n"
]
},
{
"data": {
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"source": [
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"progress(average_ndvi)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "624f3fd0-2583-418e-a6a9-177b5983fb32",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.12 s, sys: 1.13 s, total: 2.24 s\n",
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]
}
],
"source": [
"%%time\n",
"average_vh = average_vh.compute()\n",
"average_vv = average_vv.compute()\n",
"average_ndvi = average_ndvi.compute()"
]
},
{
"cell_type": "markdown",
"id": "609df555-8150-4c3b-95b7-15c09be1cf69",
"metadata": {},
"source": [
"#####################################CREATE DATASET#######################################################"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "e6d6b656-a077-4515-8492-4ecdebeabf55",
"metadata": {
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},
"outputs": [
{
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"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=\"dark\"],\n",
"html[data-theme=\"dark\"],\n",
"body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
" height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:focus + label {\n",
" border: 2px solid var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 1, y: 6727, x: 7151)&gt; Size: 48MB\n",
"[48104777 values with dtype=uint8]\n",
"Coordinates:\n",
" * band (band) int64 8B 1\n",
" * x (x) float64 57kB 5.597e+05 5.598e+05 ... 6.312e+05 6.312e+05\n",
" * y (y) float64 54kB 1.097e+06 1.097e+06 ... 1.03e+06 1.03e+06\n",
" spatial_ref int64 8B 0\n",
"Attributes:\n",
" AREA_OR_POINT: Area\n",
" RepresentationType: THEMATIC\n",
" _FillValue: 255\n",
" scale_factor: 1.0\n",
" add_offset: 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-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 6727</li><li><span class='xr-has-index'>x</span>: 7151</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-838fb1c6-0aeb-4588-89fa-3c5885cd0eb6' class='xr-array-in' type='checkbox' checked><label for='section-838fb1c6-0aeb-4588-89fa-3c5885cd0eb6' 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>...</span></div><div class='xr-array-data'><pre>[48104777 values with dtype=uint8]</pre></div></div></li><li class='xr-section-item'><input id='section-e2fd4c2e-9c5f-459e-9800-6bd118f563d6' class='xr-section-summary-in' type='checkbox' checked><label for='section-e2fd4c2e-9c5f-459e-9800-6bd118f563d6' 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'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-a5b625bf-b0de-4b1d-8539-1f71f9bfef4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5b625bf-b0de-4b1d-8539-1f71f9bfef4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e094f6d-d820-4878-a1a2-3f8712fed7c0' class='xr-var-data-in' type='checkbox'><label for='data-8e094f6d-d820-4878-a1a2-3f8712fed7c0' 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([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.597e+05 5.598e+05 ... 6.312e+05</div><input id='attrs-ff43ede3-e4ce-47fb-87d2-4df883df486f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff43ede3-e4ce-47fb-87d2-4df883df486f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce2377d7-069a-452e-804d-aa6ac4529322' class='xr-var-data-in' type='checkbox'><label for='data-ce2377d7-069a-452e-804d-aa6ac4529322' 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([559742.754, 559752.754, 559762.754, ..., 631222.754, 631232.754,\n",
" 631242.754])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.097e+06 1.097e+06 ... 1.03e+06</div><input id='attrs-a00f5ad1-2a0e-49f4-9358-c4e45470fa58' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a00f5ad1-2a0e-49f4-9358-c4e45470fa58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cea5be9-9f9e-46ee-bb1a-77b698efdbc7' class='xr-var-data-in' type='checkbox'><label for='data-0cea5be9-9f9e-46ee-bb1a-77b698efdbc7' 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([1097385.3978, 1097375.3978, 1097365.3978, ..., 1030145.3978,\n",
" 1030135.3978, 1030125.3978])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-d2f2e14a-9be6-4577-90d9-2299b139085a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2f2e14a-9be6-4577-90d9-2299b139085a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c356d54e-a2ba-4e88-b064-b5746866d049' class='xr-var-data-in' type='checkbox'><label for='data-c356d54e-a2ba-4e88-b064-b5746866d049' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 48N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>105.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 48N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,105],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32648&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>559737.7539999997 10.0 0.0 1097390.3978000004 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f158968a-b3d8-4bb2-ab87-c5269254b83c' class='xr-section-summary-in' type='checkbox' ><label for='section-f158968a-b3d8-4bb2-ab87-c5269254b83c' class='xr-section-summary' >Indexes: <span>(3)</span></label><di
" 559772.7539999997, 559782.7539999997, 559792.7539999997,\n",
" 559802.7539999997, 559812.7539999997, 559822.7539999997,\n",
" 559832.7539999997,\n",
" ...\n",
" 631152.7539999997, 631162.7539999997, 631172.7539999997,\n",
" 631182.7539999997, 631192.7539999997, 631202.7539999997,\n",
" 631212.7539999997, 631222.7539999997, 631232.7539999997,\n",
" 631242.7539999997],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=7151))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f14682e7-3094-40e6-9d7d-b90fcc8592a6' class='xr-index-data-in' type='checkbox'/><label for='index-f14682e7-3094-40e6-9d7d-b90fcc8592a6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1097385.3978000004, 1097375.3978000004, 1097365.3978000004,\n",
" 1097355.3978000004, 1097345.3978000004, 1097335.3978000004,\n",
" 1097325.3978000004, 1097315.3978000004, 1097305.3978000004,\n",
" 1097295.3978000004,\n",
" ...\n",
" 1030215.3978000004, 1030205.3978000004, 1030195.3978000004,\n",
" 1030185.3978000004, 1030175.3978000004, 1030165.3978000004,\n",
" 1030155.3978000004, 1030145.3978000004, 1030135.3978000004,\n",
" 1030125.3978000004],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=6727))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18a15997-8214-4a8a-92f8-82a345fd7d3b' class='xr-section-summary-in' type='checkbox' checked><label for='section-18a15997-8214-4a8a-92f8-82a345fd7d3b' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>RepresentationType :</span></dt><dd>THEMATIC</dd><dt><span>_FillValue :</span></dt><dd>255</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>add_offset :</span></dt><dd>0.0</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray (band: 1, y: 6727, x: 7151)> Size: 48MB\n",
"[48104777 values with dtype=uint8]\n",
"Coordinates:\n",
" * band (band) int64 8B 1\n",
" * x (x) float64 57kB 5.597e+05 5.598e+05 ... 6.312e+05 6.312e+05\n",
" * y (y) float64 54kB 1.097e+06 1.097e+06 ... 1.03e+06 1.03e+06\n",
" spatial_ref int64 8B 0\n",
"Attributes:\n",
" AREA_OR_POINT: Area\n",
" RepresentationType: THEMATIC\n",
" _FillValue: 255\n",
" scale_factor: 1.0\n",
" add_offset: 0.0"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"input_path = \"./input/masks/ST_lua2v.tif\"\n",
"data = rioxarray.open_rasterio(input_path)\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a3185634-0d67-42a7-82c0-7ef2807d0448",
"metadata": {},
"outputs": [],
"source": [
"# Convert to numpy array (assuming a single-band raster)\n",
"data_np = data.values.squeeze()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "04a23ee1-305a-4139-b3d2-26e34366286d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 598782.754 1097385.3978]\n",
" [ 610132.754 1087655.3978]\n",
" [ 607522.754 1087455.3978]\n",
" ...\n",
" [ 608912.754 1030175.3978]\n",
" [ 608922.754 1030175.3978]\n",
" [ 608132.754 1030125.3978]]\n"
]
}
],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"\n",
"# Assuming 'data' is your xarray.DataArray\n",
"mask = data != 255 # Boolean mask where values are not 255\n",
"\n",
"# Stack x and y dimensions into a single index\n",
"data_stacked = data.stack(points=(\"y\", \"x\"))\n",
"\n",
"# Apply the mask and drop NaN values\n",
"filtered = data_stacked.where(data_stacked != 255, drop=True)\n",
"\n",
"# Extract x and y coordinates\n",
"x_indices = filtered.coords[\"x\"].values\n",
"y_indices = filtered.coords[\"y\"].values\n",
"\n",
"# Stack into a (N, 2) NumPy array\n",
"xy_valid = np.column_stack((x_indices, y_indices))\n",
"\n",
"print(xy_valid) # Print or use the filtered coordinates\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "32018eaf-d96a-4d93-aa60-6f73f564c8a2",
"metadata": {},
"outputs": [],
"source": [
"ndvi = []\n",
"vh = []\n",
"vv = []\n",
"\n",
"def extract_data(index):\n",
" ndvi_data = average_ndvi.sel(x=index[0], y=index[1], method='nearest').values\n",
" vh_data = average_vh.sel(x=index[0], y=index[1], method='nearest').values\n",
" vv_data = average_vv.sel(x=index[0], y=index[1], method='nearest').values\n",
" return ndvi_data, vh_data, vv_data\n",
"\n",
"# Process data sequentially\n",
"i = 0\n",
"for index in xy_valid:\n",
" ndvi_data, vh_data, vv_data = extract_data(index)\n",
" ndvi.append(ndvi_data)\n",
" vh.append(vh_data)\n",
" vv.append(vv_data)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1a602b28-a98f-4606-8e91-c4a29d3ebe67",
"metadata": {},
"outputs": [],
"source": [
"ndvi = np.concatenate(ndvi)\n",
"vh = np.concatenate(vh)\n",
"vv = np.concatenate(vv)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a3984403-a902-4d1f-a149-d738be564120",
"metadata": {},
"outputs": [],
"source": [
"nan_indices = ~np.isnan(ndvi)\n",
"print(nan_indices)\n",
"ndvi_nan = ndvi[nan_indices]\n",
"vh_nan = vh[nan_indices]\n",
"vv_nan = vv[nan_indices]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2ec67453-d3d6-4b6b-b130-0b3419e7336c",
"metadata": {},
"outputs": [],
"source": [
"ndvi_nan = ndvi_nan[:2000000]\n",
"vh_nan = vh_nan[:2000000]\n",
"vv_nan = vv_nan[:2000000]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7ab63797-a8d7-413e-b74a-a244c1e019a7",
"metadata": {},
"outputs": [],
"source": [
"ndvi_nan.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "03d48b76-273b-4561-98e3-96e51e88ba51",
"metadata": {},
"outputs": [],
"source": [
"features = np.stack([vh_nan, vv_nan], axis=1)\n",
"features.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "20461197-dd98-42ce-988c-492129117af3",
"metadata": {},
"outputs": [],
"source": [
"X_train, X_test, y_train, y_test = train_test_split(features, ndvi_nan, test_size=0.2, random_state=42)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3f24df45-fe21-4df0-89e6-917fca496040",
"metadata": {},
"outputs": [],
"source": [
"from sklearn.neural_network import MLPRegressor\n",
"regressors = {\n",
" 'random_forest': RandomForestRegressor(random_state=42),\n",
" 'svr': SVR(),\n",
" 'gradient_boosting': GradientBoostingRegressor(random_state=42),\n",
" 'linear_regression': LinearRegression(),\n",
" 'knn': KNeighborsRegressor(),\n",
" 'mlp': MLPRegressor(random_state=42, max_iter=1000)\n",
" }\n",
"param_grids_regressor = {\n",
" 'random_forest': {\n",
" 'n_estimators': [500],\n",
" 'max_depth': [ 10],\n",
" },\n",
" 'svr': {\n",
" 'kernel': ['poly', 'linear'],\n",
" 'C': [0.1, 1, 10],\n",
" 'degree': [2, 3], # For poly kernel\n",
" },\n",
" 'gradient_boosting': {\n",
" 'n_estimators': [300],\n",
" 'learning_rate': [ 0.05],\n",
" 'max_depth': [3, 4, 5],\n",
" },\n",
" 'linear_regression': {\n",
" # 'alpha': [0.01, 0.1, 1, 10, 100], # Regularization strength\n",
" # 'fit_intercept': [True, False],\n",
" # 'solver': ['auto', 'svd', 'cholesky', 'lsqr', 'sparse_cg'],\n",
" },\n",
" 'knn': {\n",
" 'n_neighbors': [3, 5, 7, 10, 20, 30, 50],\n",
" 'weights': ['uniform', 'distance'],\n",
" 'p': [1, 2, 3],\n",
" },\n",
" 'mlp' : {\n",
" 'hidden_layer_sizes': [(64, 32), (128, 64), (64, 32, 16), (128, 64, 32)],\n",
" 'activation': ['relu', 'tanh'],\n",
" 'solver': ['adam', 'sgd'],\n",
" 'learning_rate_init': [0.001, 0.01, 0.1]\n",
" }\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9c06dac1-c412-4a70-a91b-32dbd2ead8d6",
"metadata": {},
"outputs": [],
"source": [
"%%time\n",
"best_model, best_params, best_score_r2, best_score_mae, cv_results = find_best_regression(\n",
" X_train, y_train, regressors['random_forest'], param_grids_regressor['random_forest']\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "47ac0ca2-a2e2-491e-ad61-904fd68fc963",
"metadata": {},
"outputs": [],
"source": [
"folder_path = 'output/regressors/mask'\n",
"file_path = os.path.join(folder_path, 'rf_lua2v2.pkl')\n",
"joblib.dump(best_model, file_path)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fdab7a3c-bcf6-442e-a048-ebf51d31629d",
"metadata": {},
"outputs": [],
"source": [
"y_pred = best_model.predict(X_test)\n",
"# Calculate R² score\n",
"r2 = r2_score(y_test, y_pred)\n",
"# Calculate Mean Squared Error\n",
"mse = mean_squared_error(y_test, y_pred)\n",
"mae = mean_absolute_error(y_test, y_pred)\n",
"print(f\"R² Score: {r2}\")\n",
"print(f\"Mean Squared Error: {mse}\")\n",
"print(\"Mean Absolute Error:\", abs(mae))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f2dbefc9-c5c0-41de-8563-99680f124ac2",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "681830ed-ff71-45cd-bfc8-cec5d3808fb7",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "c86c3262-9246-4799-ad0b-ccb609f0b9cb",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "9b2bc79c-fb67-4282-a34e-9771c7e0b10c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "27b04b78-67dc-48db-9950-6a6d7ffaf239",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "20fb8078-70cc-4788-abbf-99ee4a2228f2",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "35649588-196c-4cd6-be62-d11c17cd2ce3",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 13,
"id": "d9cbb9cc-1ac7-45bf-a134-f4e29df29d75",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.imshow(mask[0], cmap='gray') # Show the first band\n",
"plt.colorbar()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0bd5c3aa-333e-45d0-b990-473b86aed5f8",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}