Skip to content

Instantly share code, notes, and snippets.

@soxofaan

soxofaan/forum452.ipynb

Created September 9, 2022 15:45
Show Gist options
  • Save soxofaan/76fe58f98809efae189150a2bbf896e6 to your computer and use it in GitHub Desktop.
Save soxofaan/76fe58f98809efae189150a2bbf896e6 to your computer and use it in GitHub Desktop.
Download ZIP
openEO forum 452 use case
Display the source blob
Display the rendered blob
Raw
forum452.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "00c057e4-9fb7-46fb-b502-f3f95f7d1ed2",
"metadata": {},
"source": [
"https://discuss.eodc.eu/t/denser-time-series-of-lai/452"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0e4d4c75-d236-4ae2-89cb-e761439e50c5",
"metadata": {},
"outputs": [],
"source": [
"import openeo\n",
"import xarray as xa\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "de564a5a-45d0-423e-ac65-fc8b541ec5ae",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"OIDC token response did not contain refresh token.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Authenticated using refresh token.\n"
]
}
],
"source": [
"con = openeo.connect(\n",
" # url=\"https://openeo.vito.be\"\n",
" url=\"https://openeo-dev.vito.be\"\n",
").authenticate_oidc(provider_id=\"egi\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c604a878-4e97-428e-b2d2-c99465364929",
"metadata": {},
"outputs": [],
"source": [
"datacube = con.load_collection(\n",
" \"TERRASCOPE_S2_LAI_V2\",\n",
" # spatial_extent={\"west\": 5.60, \"south\": 50.42, \"east\": 6.3, \"north\": 50.7},\n",
" spatial_extent={\"west\": 4.00, \"south\": 51, \"east\": 4.1, \"north\": 51.1},\n",
" # temporal_extent=[\"2022-01-01\", \"2022-08-15\"],\n",
" temporal_extent=[\"2021-01-01\", \"2021-12-30\"],\n",
" bands=[\"LAI_10M\",\"SCENECLASSIFICATION_20M\"]\n",
")"
]
},
{
"cell_type": "markdown",
"id": "15382257-e6a4-42ff-98be-a523404deabe",
"metadata": {},
"source": [
"mask"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "02972fbc-920d-4ad8-9a4e-25bb9132ec6f",
"metadata": {},
"outputs": [],
"source": [
"SCL = datacube.band(\"SCENECLASSIFICATION_20M\")\n",
"mask = ~ ((SCL == 4) | (SCL == 5) | (SCL == 6))\n",
"\n",
"LAI = datacube.filter_bands([\"LAI_10M\"])\n",
"LAI_masked = LAI.mask(mask)"
]
},
{
"cell_type": "markdown",
"id": "38af3d1d-49e0-4e5c-8217-312e1b296370",
"metadata": {},
"source": [
"temporal aggregation"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "809bc36e-11b0-4901-8b37-876bd929ef48",
"metadata": {},
"outputs": [],
"source": [
"LAI_month = LAI.aggregate_temporal_period(period=\"month\", reducer=\"mean\")\n",
"LAI_masked_month = LAI_masked.aggregate_temporal_period(period=\"month\", reducer=\"mean\")"
]
},
{
"cell_type": "markdown",
"id": "d9c3c80c-f44b-4c4f-9161-eb1e0fa45e58",
"metadata": {},
"source": [
"interpolation attemps"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "cbab6f8a-0249-429c-8f14-7b506bcada11",
"metadata": {},
"outputs": [],
"source": [
"LAI_month_interpolate = LAI_month.apply_dimension(process = \"array_interpolate_linear\", dimension = \"t\")\n",
"LAI_masked_month_interpolate = LAI_masked_month.apply_dimension(process = \"array_interpolate_linear\", dimension = \"t\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "19bdbb08-4e84-4e11-8f2d-738832f93ae7",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"id": "55ef6d81-4e76-431e-9c93-95c9861399e7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 148 ms, sys: 148 ms, total: 296 ms\n",
"Wall time: 38.7 s\n"
]
}
],
"source": [
"%%time\n",
"LAI_month.download(\"LAI_month.nc\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "026daf61-732a-4e50-b3b5-f8105f708d64",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 136 ms, sys: 115 ms, total: 251 ms\n",
"Wall time: 1min 14s\n"
]
}
],
"source": [
"%%time\n",
"LAI_masked_month.download(\"LAI_masked_month.nc\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "aabb7ae8-17f0-4e89-8733-751e65b28767",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 183 ms, sys: 133 ms, total: 315 ms\n",
"Wall time: 56.4 s\n"
]
}
],
"source": [
"%%time\n",
"LAI_month_interpolate.download(\"LAI_month_interpolate.nc\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e31e5d15-dbb4-407d-a750-a6ccc7acb298",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 186 ms, sys: 117 ms, total: 304 ms\n",
"Wall time: 1min 9s\n"
]
}
],
"source": [
"%%time\n",
"LAI_masked_month_interpolate.download(\"LAI_masked_month_interpolate.nc\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "261a883b-ba94-493f-8545-fc7f71ed2987",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 12,
"id": "8a5b75bc-0602-4a4e-bb2b-de64f91ecc14",
"metadata": {},
"outputs": [],
"source": [
"def read_result(filename:str):\n",
" data = xa.load_dataset(filename)[\"LAI_10M\"]\n",
" # handle nodata=0: set nan\n",
" data = data.where(data != 0)\n",
" return data"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "90b87d95-3760-43ab-b190-b48eb0691593",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"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 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\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: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-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",
" 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",
" 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-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-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",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;LAI_10M&#x27; (t: 12, y: 1123, x: 718)&gt;\n",
"array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ nan, nan, nan, ..., 9., 5., 4.],\n",
" [ nan, nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])\n",
"Coordinates:\n",
" * t (t) datetime64[ns] 2021-01-01 2021-02-01 ... 2021-11-01 2021-12-01\n",
" * x (x) float64 5.7e+05 5.7e+05 5.7e+05 ... 5.772e+05 5.772e+05\n",
" * y (y) float64 5.662e+06 5.662e+06 5.662e+06 ... 5.65e+06 5.65e+06\n",
"Attributes:\n",
" long_name: LAI_10M\n",
" units: \n",
" grid_mapping: crs</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'>'LAI_10M'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 12</li><li><span class='xr-has-index'>y</span>: 1123</li><li><span class='xr-has-index'>x</span>: 718</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3a242d91-d325-4d0c-9f6c-1a833da709a8' class='xr-array-in' type='checkbox' checked><label for='section-3a242d91-d325-4d0c-9f6c-1a833da709a8' 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>nan nan nan nan nan 14.0 5.0 nan ... 18.0 nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ nan, nan, nan, ..., 9., 5., 4.],\n",
" [ nan, nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])</pre></div></div></li><li class='xr-section-item'><input id='section-817303b9-4eec-4f28-aef6-af88c5c42710' class='xr-section-summary-in' type='checkbox' checked><label for='section-817303b9-4eec-4f28-aef6-af88c5c42710' 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'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-12-01</div><input id='attrs-f4c0f4a5-e4b6-4180-9109-6d64c10e0b8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4c0f4a5-e4b6-4180-9109-6d64c10e0b8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1b3606a-d2d9-4c83-9a81-007d6ea5ea16' class='xr-var-data-in' type='checkbox'><label for='data-b1b3606a-d2d9-4c83-9a81-007d6ea5ea16' 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>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-03-01T00:00:00.000000000&#x27;, &#x27;2021-04-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-05-01T00:00:00.000000000&#x27;, &#x27;2021-06-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-07-01T00:00:00.000000000&#x27;, &#x27;2021-08-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-09-01T00:00:00.000000000&#x27;, &#x27;2021-10-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-11-01T00:00:00.000000000&#x27;, &#x27;2021-12-01T00:00:00.000000000&#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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.7e+05 5.7e+05 ... 5.772e+05</div><input id='attrs-06f94334-991b-4c2b-a10d-e447e059f077' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06f94334-991b-4c2b-a10d-e447e059f077' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b11eb911-a098-413d-bfe9-f5101abf55c5' class='xr-var-data-in' type='checkbox'><label for='data-b11eb911-a098-413d-bfe9-f5101abf55c5' 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>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([570015., 570025., 570035., ..., 577165., 577175., 577185.])</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'>5.662e+06 5.662e+06 ... 5.65e+06</div><input id='attrs-4acaeaf4-6de4-4690-972f-990aa94858e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4acaeaf4-6de4-4690-972f-990aa94858e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02c256f5-ef45-4f74-9668-aaae6d341c5f' class='xr-var-data-in' type='checkbox'><label for='data-02c256f5-ef45-4f74-9668-aaae6d341c5f' 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>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([5661525., 5661515., 5661505., ..., 5650325., 5650315., 5650305.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-58a32121-3866-4775-8f6e-fad77ede920f' class='xr-section-summary-in' type='checkbox' checked><label for='section-58a32121-3866-4775-8f6e-fad77ede920f' class='xr-section-summary' >Attributes: <span>(3)</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>LAI_10M</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'LAI_10M' (t: 12, y: 1123, x: 718)>\n",
"array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ nan, nan, nan, ..., 9., 5., 4.],\n",
" [ nan, nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])\n",
"Coordinates:\n",
" * t (t) datetime64[ns] 2021-01-01 2021-02-01 ... 2021-11-01 2021-12-01\n",
" * x (x) float64 5.7e+05 5.7e+05 5.7e+05 ... 5.772e+05 5.772e+05\n",
" * y (y) float64 5.662e+06 5.662e+06 5.662e+06 ... 5.65e+06 5.65e+06\n",
"Attributes:\n",
" long_name: LAI_10M\n",
" units: \n",
" grid_mapping: crs"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_masked_month = read_result(\"LAI_masked_month.nc\")\n",
"data_masked_month"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "7ae6f4f2-db38-48b4-b512-93d3cbab0fff",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f87976758b0>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 360x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize= (5, 5))\n",
"data_masked_month[0, :100, :100].plot(ax=ax)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "6b441d8d-ab81-4b6c-8cb7-3470e5d715fc",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
"<defs>\n",
"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
"</symbol>\n",
"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
"</symbol>\n",
"</defs>\n",
"</svg>\n",
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"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 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\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: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-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",
" 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",
" 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-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-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",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;LAI_10M&#x27; (t: 12, y: 1123, x: 718)&gt;\n",
"array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ 12., nan, nan, ..., 9., 5., 4.],\n",
" [ 11., nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 36., 38., 55.],\n",
" [ nan, nan, nan, ..., 34., 34., 50.],\n",
" [ nan, nan, nan, ..., 33., 33., 45.],\n",
" ...,\n",
" [ nan, 19., 27., ..., 21., 11., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])\n",
"Coordinates:\n",
" * t (t) datetime64[ns] 2021-01-01 2021-02-01 ... 2021-11-01 2021-12-01\n",
" * x (x) float64 5.7e+05 5.7e+05 5.7e+05 ... 5.772e+05 5.772e+05\n",
" * y (y) float64 5.662e+06 5.662e+06 5.662e+06 ... 5.65e+06 5.65e+06\n",
"Attributes:\n",
" long_name: LAI_10M\n",
" units: \n",
" grid_mapping: crs</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'>'LAI_10M'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 12</li><li><span class='xr-has-index'>y</span>: 1123</li><li><span class='xr-has-index'>x</span>: 718</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f0849a38-995f-44e5-9978-a15d9f5a4196' class='xr-array-in' type='checkbox' checked><label for='section-f0849a38-995f-44e5-9978-a15d9f5a4196' 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>nan nan nan nan nan 14.0 5.0 nan ... 18.0 nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ 12., nan, nan, ..., 9., 5., 4.],\n",
" [ 11., nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 36., 38., 55.],\n",
" [ nan, nan, nan, ..., 34., 34., 50.],\n",
" [ nan, nan, nan, ..., 33., 33., 45.],\n",
" ...,\n",
" [ nan, 19., 27., ..., 21., 11., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])</pre></div></div></li><li class='xr-section-item'><input id='section-46965b3e-da4d-4713-bbd6-d595b6372713' class='xr-section-summary-in' type='checkbox' checked><label for='section-46965b3e-da4d-4713-bbd6-d595b6372713' 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'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-12-01</div><input id='attrs-247befde-e0fb-4b91-9acf-7c36d9fa421e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-247befde-e0fb-4b91-9acf-7c36d9fa421e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3845aa0a-b20b-4e65-b585-c9a9cf5b3450' class='xr-var-data-in' type='checkbox'><label for='data-3845aa0a-b20b-4e65-b585-c9a9cf5b3450' 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>standard_name :</span></dt><dd>t</dd><dt><span>long_name :</span></dt><dd>t</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-03-01T00:00:00.000000000&#x27;, &#x27;2021-04-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-05-01T00:00:00.000000000&#x27;, &#x27;2021-06-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-07-01T00:00:00.000000000&#x27;, &#x27;2021-08-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-09-01T00:00:00.000000000&#x27;, &#x27;2021-10-01T00:00:00.000000000&#x27;,\n",
" &#x27;2021-11-01T00:00:00.000000000&#x27;, &#x27;2021-12-01T00:00:00.000000000&#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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.7e+05 5.7e+05 ... 5.772e+05</div><input id='attrs-db3a2268-e41d-4831-912c-716146f5bce0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db3a2268-e41d-4831-912c-716146f5bce0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce2e77dc-3a89-4dc3-a519-51bc1f670cea' class='xr-var-data-in' type='checkbox'><label for='data-ce2e77dc-3a89-4dc3-a519-51bc1f670cea' 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>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([570015., 570025., 570035., ..., 577165., 577175., 577185.])</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'>5.662e+06 5.662e+06 ... 5.65e+06</div><input id='attrs-7815a62a-ea5b-4c11-9574-34a02f3ef0f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7815a62a-ea5b-4c11-9574-34a02f3ef0f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-320e5381-c4da-48be-ac59-b0ca325df9fc' class='xr-var-data-in' type='checkbox'><label for='data-320e5381-c4da-48be-ac59-b0ca325df9fc' 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>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([5661525., 5661515., 5661505., ..., 5650325., 5650315., 5650305.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-29489db7-0cb6-4cc0-862a-1e83a87c82bc' class='xr-section-summary-in' type='checkbox' checked><label for='section-29489db7-0cb6-4cc0-862a-1e83a87c82bc' class='xr-section-summary' >Attributes: <span>(3)</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>LAI_10M</dd><dt><span>units :</span></dt><dd></dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'LAI_10M' (t: 12, y: 1123, x: 718)>\n",
"array([[[ nan, nan, nan, ..., 106., 112., 115.],\n",
" [ nan, nan, nan, ..., 107., 99., 88.],\n",
" [ nan, nan, nan, ..., 67., 54., 39.],\n",
" ...,\n",
" [ nan, nan, nan, ..., 16., 10., 7.],\n",
" [ 13., nan, nan, ..., nan, nan, nan],\n",
" [ 10., nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ 3., nan, nan, ..., 129., 134., 140.],\n",
" [ nan, nan, nan, ..., 127., 130., 121.],\n",
" [ nan, nan, nan, ..., 97., 75., 54.],\n",
" ...,\n",
" [ 5., nan, nan, ..., 18., 11., 8.],\n",
" [ 12., nan, nan, ..., 9., 5., 4.],\n",
" [ 11., nan, nan, ..., 7., 4., 3.]],\n",
"\n",
" [[ 5., nan, nan, ..., 108., 109., 114.],\n",
" [ nan, nan, nan, ..., 108., 106., 97.],\n",
" [ nan, nan, nan, ..., 79., 62., 47.],\n",
" ...,\n",
"...\n",
" ...,\n",
" [ 30., 31., 44., ..., 29., 16., 13.],\n",
" [ 49., 46., 45., ..., nan, nan, nan],\n",
" [ 50., 50., 51., ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 36., 38., 55.],\n",
" [ nan, nan, nan, ..., 34., 34., 50.],\n",
" [ nan, nan, nan, ..., 33., 33., 45.],\n",
" ...,\n",
" [ nan, 19., 27., ..., 21., 11., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]],\n",
"\n",
" [[ nan, nan, nan, ..., 53., 59., 57.],\n",
" [ nan, nan, nan, ..., 49., 51., 51.],\n",
" [ nan, nan, nan, ..., 50., 48., 46.],\n",
" ...,\n",
" [ nan, 8., 11., ..., 13., 6., nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]]])\n",
"Coordinates:\n",
" * t (t) datetime64[ns] 2021-01-01 2021-02-01 ... 2021-11-01 2021-12-01\n",
" * x (x) float64 5.7e+05 5.7e+05 5.7e+05 ... 5.772e+05 5.772e+05\n",
" * y (y) float64 5.662e+06 5.662e+06 5.662e+06 ... 5.65e+06 5.65e+06\n",
"Attributes:\n",
" long_name: LAI_10M\n",
" units: \n",
" grid_mapping: crs"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_masked_month_interpolate = read_result(\"LAI_masked_month_interpolate.nc\")\n",
"data_masked_month_interpolate"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "e42dacff-112d-4491-9801-6fb753a4fefc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Increase')"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 648x216 with 6 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(figsize= (9, 3), ncols=3)\n",
"\n",
"count_masked_month = data_masked_month.count(axis=0)\n",
"count_masked_month_interpolate = data_masked_month_interpolate.count(axis=0)\n",
"\n",
"count_masked_month.plot(ax=axes[0])\n",
"axes[0].set_title(\"masked_month: valid count\")\n",
"count_masked_month_interpolate.plot(ax=axes[1])\n",
"axes[1].set_title(\"masked_month_interpolate: valid count\")\n",
"(count_masked_month_interpolate - count_masked_month).plot(ax=axes[2])\n",
"axes[2].set_title(\"Increase\")\n"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "324df0b3-7ac8-4f13-9502-3660911392bb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"80.16634958589334 total masked_month valid percentage\n",
"87.94681724489467 total masked_month_interpolate valid percentage\n"
]
}
],
"source": [
"print(\n",
" 100 * float(data_masked_month.count()) / data_masked_month.size,\n",
" \"total masked_month valid percentage\", \n",
")\n",
"print(\n",
" 100 * float(data_masked_month_interpolate.count()) / data_masked_month_interpolate.size,\n",
" \"total masked_month_interpolate valid percentage\", \n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "609c4d1e-1759-4558-9d19-5efa4e7a7c3f",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "e262f830-0940-49fc-964a-5b36276f94ae",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "0be193ee-050e-4e3f-a81d-8376b1b0b32b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "openeo-py39",
"language": "python",
"name": "openeo-py39"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment