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rmg55/NASA_STAC_stack.ipynb Secret

Created February 10, 2021 04:25
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NASA LPCloud HLS STAC to Xarray
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NASA_STAC_stack.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Matplotlib created a temporary config/cache directory at /tmp/matplotlib-ce70wawk because the default path (/home/jovyan/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.\n",
"/opt/conda/envs/py_geo/lib/python3.8/site-packages/intake/source/discovery.py:133: FutureWarning: The drivers ['sql_cat', 'sql', 'sql_auto', 'sql_manual'] do not specify entry_points and were only discovered via a package scan. This may break in a future release of intake. The packages should be updated.\n",
" warnings.warn(\n"
]
}
],
"source": [
"from dask.distributed import LocalCluster, Client\n",
"import dask\n",
"import xarray as xr\n",
"import intake\n",
"import gdal\n",
"from satsearch import Search\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"from tempfile import NamedTemporaryFile\n",
"import jinja2 as jj2\n",
"from rasterio.crs import CRS\n",
"import time\n",
"\n",
"import requests\n",
"import concurrent.futures\n",
"from urllib.request import urlopen\n",
"from xml.etree.ElementTree import parse,fromstring\n",
"from affine import Affine\n",
"from pandas import to_datetime\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# AUTHENTICATION CONFIGURATION\n",
"from netrc import netrc\n",
"from subprocess import Popen\n",
"from getpass import getpass\n",
"import os\n",
"\n",
"urs = 'urs.earthdata.nasa.gov' # Earthdata URL to call for authentication\n",
"prompts = ['Enter NASA Earthdata Login Username \\n(or create an account at urs.earthdata.nasa.gov): ',\n",
" 'Enter NASA Earthdata Login Password: ']\n",
"\n",
"# Determine if netrc file exists, and if so, if it includes NASA Earthdata Login Credentials\n",
"try:\n",
" netrcDir = os.path.expanduser(\"~/.netrc\")\n",
" netrc(netrcDir).authenticators(urs)[0]\n",
" del netrcDir\n",
"\n",
"# Below, create a netrc file and prompt user for NASA Earthdata Login Username and Password\n",
"except FileNotFoundError:\n",
" homeDir = os.path.expanduser(\"~\")\n",
" Popen('touch {0}.netrc | chmod og-rw {0}.netrc | echo machine {1} >> {0}.netrc'.format(homeDir + os.sep, urs), shell=True)\n",
" Popen('echo login {} >> {}.netrc'.format(getpass(prompt=prompts[0]), homeDir + os.sep), shell=True)\n",
" Popen('echo password {} >> {}.netrc'.format(getpass(prompt=prompts[1]), homeDir + os.sep), shell=True)\n",
" del homeDir\n",
"\n",
"# Determine OS and edit netrc file if it exists but is not set up for NASA Earthdata Login\n",
"except TypeError:\n",
" homeDir = os.path.expanduser(\"~\")\n",
" Popen('echo machine {1} >> {0}.netrc'.format(homeDir + os.sep, urs), shell=True)\n",
" Popen('echo login {} >> {}.netrc'.format(getpass(prompt=prompts[0]), homeDir + os.sep), shell=True)\n",
" Popen('echo password {} >> {}.netrc'.format(getpass(prompt=prompts[1]), homeDir + os.sep), shell=True)\n",
" del homeDir\n",
"del urs, prompts"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# s3_cred = requests.get('https://lpdaac.earthdata.nasa.gov/s3credentials').json()\n",
"# s3_cred"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# ### Try to Load from S3 - Just hangs when on AWS - need to email DAAC folks I thinkg\n",
"\n",
"# gdal.SetConfigOption('AWS_REGION', 'us-west-2')\n",
"# gdal.SetConfigOption('AWS_SECRET_ACCESS_KEY', s3_cred['secretAccessKey'])\n",
"# gdal.SetConfigOption('AWS_ACCESS_KEY_ID', s3_cred['accessKeyId'])\n",
"# gdal.SetConfigOption('AWS_SESSION_TOKEN', s3_cred['sessionToken'])\n",
"\n",
"# gdalinfo_str = 'gdalinfo --config AWS_SECRET_ACCESS_KEY '+s3_cred['secretAccessKey']+' --config AWS_ACCESS_KEY_ID '+s3_cred['accessKeyId']+' --config AWS_SESSION_TOKEN \"'+s3_cred['sessionToken']+'\" /vsis3/lp-prod-public/HLSS30.015/HLS.S30.T10TEK.2020190T184919.v1.5.B02.tif'\n",
"# # 'sentinel-pds' is the S3 bucket name\n",
"# path = '/vsis3/lp-prod-protected/HLSS30.015/HLS.S30.T10TEK.2020190T184919.v1.5.B02.tif'\n",
"# ds = gdal.Open(path)\n",
"\n",
"# band = ds.GetRasterBand(1)\n",
"\n",
"# xoff, yoff, xcount, ycount = (0, 0, 10, 10)\n",
"# np_array = band.ReadAsArray(xoff, yoff, xcount, ycount)\n",
"# gdalinfo_str"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#Setup GDAL Env for optimum performance\n",
"env = dict(GDAL_DISABLE_READDIR_ON_OPEN='EMPTY_DIR', \n",
" AWS_NO_SIGN_REQUEST='YES',\n",
" GDAL_MAX_RAW_BLOCK_CACHE_SIZE='200000000',\n",
" GDAL_SWATH_SIZE='200000000',\n",
" VSI_CURL_CACHE_SIZE='200000000',\n",
" CPL_VSIL_CURL_ALLOWED_EXTENSIONS='TIF',\n",
" GDAL_HTTP_UNSAFESSL='YES',\n",
" GDAL_HTTP_COOKIEFILE=os.path.expanduser('~/cookies.txt'),\n",
" GDAL_HTTP_COOKIEJAR=os.path.expanduser('~/cookies.txt'),\n",
" AWS_REGION='us-west-2',\n",
" AWS_SECRET_ACCESS_KEY=s3_cred['secretAccessKey'],\n",
" AWS_ACCESS_KEY_ID=s3_cred['accessKeyId'],\n",
" AWS_SESSION_TOKEN=s3_cred['sessionToken'])\n",
"\n",
"\n",
"os.environ.update(env)\n",
"\n",
"#from osgeo import gdal\n",
"#gdal.SetConfigOption('GDAL_DISABLE_READDIR_ON_OPEN','EMPTY_DIR')\n",
"#gdal.SetConfigOption('AWS_NO_SIGN_REQUEST', 'YES')\n",
"#gdal.SetConfigOption('GDAL_MAX_RAW_BLOCK_CACHE_SIZE', '200000000')\n",
"#gdal.SetConfigOption('GDAL_SWATH_SIZE', '200000000')\n",
"#gdal.SetConfigOption('VSI_CURL_CACHE_SIZE', '200000000')\n",
"#gdal.SetConfigOption('CPL_VSIL_CURL_ALLOWED_EXTENSIONS', 'TIF')\n",
"#gdal.SetConfigOption('GDAL_HTTP_UNSAFESSL', 'YES')\n",
"#gdal.SetConfigOption('GDAL_HTTP_COOKIEFILE', '~/cookies.txt')\n",
"#gdal.SetConfigOption('GDAL_HTTP_COOKIEJAR', '~/cookies.txt')\n",
"\n",
"#gdal.SetConfigOption('VSI_CACHE', 'FALSE')\n",
"#gdal.SetConfigOption('GDAL_DISABLE_READDIR_ON_OPEN', 'YES')\n",
"#gdal.SetConfigOption('GDAL_HTTP_COOKIEFILE', os.path.expanduser('~\\\\cookies.txt'))\n",
"#gdal.SetConfigOption('GDAL_HTTP_COOKIEJAR', os.path.expanduser('~\\\\cookies.txt'))\n",
"#gdal.SetConfigOption(\"GDAL_HTTP_UNSAFESSL\", \"YES\")\n",
"#gdal.SetConfigOption('CPL_VSIL_CURL_ALLOWED_EXTENSIONS','.tif')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table style=\"border: 2px solid white;\">\n",
"<tr>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3 style=\"text-align: left;\">Client</h3>\n",
"<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
" <li><b>Scheduler: </b>tcp://127.0.0.1:33365</li>\n",
" <li><b>Dashboard: </b><a href='http://localhost:8888/proxy/38955/status' target='_blank'>http://localhost:8888/proxy/38955/status</a></li>\n",
"</ul>\n",
"</td>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3 style=\"text-align: left;\">Cluster</h3>\n",
"<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
" <li><b>Workers: </b>12</li>\n",
" <li><b>Cores: </b>12</li>\n",
" <li><b>Memory: </b>26.70 GB</li>\n",
"</ul>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<Client: 'tcp://127.0.0.1:33365' processes=12 threads=12, memory=26.70 GB>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dask.config.set({'distributed.dashboard.link':'http://localhost:8888/proxy/{port}/status'})\n",
"#dask.config.set(max_width=2)\n",
"clust = LocalCluster(threads_per_worker=1)\n",
"cl = Client(clust)\n",
"cl"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def get_STAC_items(url, collection, dates, bbox):\n",
" results = Search.search(url=url,\n",
" collections=[collection], \n",
" datetime=dates,\n",
" bounding_box=bbox, \n",
" sortby=['-properties.datetime'])\n",
"\n",
" items = results.items()\n",
" print(f'Found {len(items)} Items')\n",
" return intake.open_stac_item_collection(items)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 45 Items\n"
]
}
],
"source": [
"url = 'https://cmr.earthdata.nasa.gov/stac/LPCLOUD' \n",
"collection = 'C1711924822-LPCLOUD' #HLS\n",
"bbox=[-104.79107047, 40.78311181, -104.67687336, 40.87008987]\n",
"dates = '2008-01-01/2022-01-10'\n",
"\n",
"cat = get_STAC_items(url,collection,dates,','.join(map(str, bbox)))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"#Function to build metadata for Stac Catalog\n",
"def open_hls_meta(stac_id):\n",
" var_url = urlopen('https://cmr.earthdata.nasa.gov/search/concepts/'+stac_id)\n",
" xmldoc = parse(var_url)\n",
" res={stac_id:{}}\n",
" for child in xmldoc.findall('.//AdditionalAttributes/AdditionalAttribute'):\n",
" if child.find('Name').text in ['ULX',\n",
" 'ULY',\n",
" 'NROWS',\n",
" 'NCOLS',\n",
" 'SPATIAL_RESOLUTION',\n",
" 'HORIZONTAL_CS_CODE',\n",
" 'SENSING_TIME',\n",
" 'MGRS_TILE_ID',\n",
" 'CLOUD_COVERAGE',\n",
" 'FILLVALUE',\n",
" 'QA_FILLVALUE',\n",
" 'MEAN_SUN_AZIMUTH_ANGLE',\n",
" 'MEAN_SUN_ZENITH_ANGLE',\n",
" 'MEAN_VIEW_AZIMUTH_ANGLE',\n",
" 'MEAN_VIEW_ZENITH_ANGLE',\n",
" 'NBAR_SOLAR_ZENITH',\n",
" 'IDENTIFIER_PRODUCT_DOI',\n",
" 'IDENTIFIER_PRODUCT_DOI_AUTHORITY',\n",
" 'REF_SCALE_FACTOR',\n",
" 'ADD_OFFSET']:\n",
" res[stac_id][child.find('Name').text]=child.find('.//Value').text\n",
" return(res)\n",
"\n",
"#Convert STAC catalog to VRT file(s) (1 vrt file per band)\n",
"#Outputs as single xarray dataset object (dims = x,y,t ; variables = bands)\n",
"def build_xr(catalog,bands,):\n",
" #Retreive Metadata using threads - not cpu bound, so works well\n",
" l_meta={}\n",
" t1 = time.time()\n",
" with concurrent.futures.ThreadPoolExecutor(5) as executor:\n",
" futures = []\n",
" for stac_id in list(catalog):\n",
" futures.append(executor.submit(open_hls_meta, stac_id=stac_id))\n",
" for future in concurrent.futures.as_completed(futures):\n",
" l_meta.update(future.result())\n",
" for stac_id in list(catalog):\n",
" for b in bands:\n",
" l_meta[stac_id][b+'_url'] = catalog[stac_id][b].urlpath\n",
" \n",
" t2 = time.time()\n",
" print('Get File Meta',t2-t1)\n",
" \n",
" #Setup template file for each raster. Use Jinja to quickly fill in metadata.\n",
" vrt_template = jj2.Template('''\n",
" <VRTDataset rasterXSize=\"{{rasterXSize}}\" rasterYSize=\"{{rasterYSize}}\">\n",
" <SRS>{{SRS}}</SRS>\n",
" <GeoTransform>{{GeoTransform}}</GeoTransform>\n",
" <VRTRasterBand dataType=\"{{dtype}}\" band=\"1\">\n",
" <NoDataValue>{{nodata}}</NoDataValue>\n",
" <Scale>{{scale}}</Scale>\n",
" <Metadata>\n",
" <MDI key=\"obs_date\">{{obs_date}}</MDI>\n",
" </Metadata>\n",
" <SimpleSource>\n",
" <SourceFilename relativeToVRT=\"1\">/vsicurl/{{SourceFilename}}</SourceFilename>\n",
" <SourceBand>1</SourceBand>\n",
" <SourceProperties RasterXSize=\"{{rasterXSize}}\" RasterYSize=\"{{rasterYSize}}\" DataType=\"{{dtype}}\" BlockXSize=\"1024\" BlockYSize=\"1024\" />\n",
" <SrcRect xOff=\"0\" yOff=\"0\" xSize=\"{{rasterXSize}}\" ySize=\"{{rasterYSize}}\" />\n",
" <DstRect xOff=\"0\" yOff=\"0\" xSize=\"{{rasterXSize}}\" ySize=\"{{rasterYSize}}\" />\n",
" <NODATA>{{nodata}}</NODATA>\n",
" </SimpleSource>\n",
" </VRTRasterBand>\n",
" </VRTDataset>\n",
" ''')\n",
" \n",
" #Enumerate the stac catalog (by band) and create vrt objects in a dictionary (l_vrt)\n",
" l_vrt={}\n",
" for i, b in enumerate(bands):\n",
" l_tmp = []\n",
" for k in l_meta.keys():\n",
" item = l_meta[k]\n",
" vrt = vrt_template.render(rasterXSize = int(item['NCOLS']),\n",
" rasterYSize = int(item['NROWS']),\n",
" SourceFilename = catalog[k][b].urlpath,\n",
" SRS=CRS.from_epsg(item['HORIZONTAL_CS_CODE'].split(':')[1]).wkt,\n",
" GeoTransform=item['ULX']+', '+item['SPATIAL_RESOLUTION']+', 0, '+item['ULY']+', 0, -'+item['SPATIAL_RESOLUTION'],\n",
" band=b,\n",
" obs_date=item['SENSING_TIME'],\n",
" dtype='int16',\n",
" nodata=item['FILLVALUE'],\n",
" scale=item['REF_SCALE_FACTOR'])\n",
" l_tmp.append(vrt)\n",
" l_vrt[b] = l_tmp\n",
" \n",
" t3 = time.time()\n",
" print('STAC Item --> VRT',t3-t2)\n",
" \n",
" #Use GDAL to merge vrts from the same bands\n",
" vrt_files={}\n",
" for b in bands:\n",
" with NamedTemporaryFile() as tmpfile:\n",
" vrt_options = gdal.BuildVRTOptions(separate=True,bandList=[1])\n",
" my_vrt = gdal.BuildVRT(tmpfile.name, l_vrt[b], options=vrt_options)\n",
" my_vrt = None\n",
" f = tmpfile.read().decode(\"utf-8\")\n",
" vrt_files[b]=f\n",
" \n",
" t4 = time.time()\n",
" print('Build VRT',t4-t3)\n",
" \n",
" #Extract metadata and lazy-load a nd merge into single xarray object\n",
" if type(bands) == str:\n",
" bands = [bands]\n",
" b_l = []\n",
" for b in bands:\n",
" v = vrt_files[b]\n",
" xmldoc = fromstring(v)\n",
" dates = []\n",
" for child in xmldoc.findall('''.//VRTRasterBand/ComplexSource/SourceFilename'''):\n",
" dates.append(to_datetime(child.text[child.text.find('obs_date')+10:\n",
" child.text.find('obs_date')+36]).date())\n",
" ds_tmp = xr.open_rasterio(v,chunks={'band':1,\n",
" 'x':'auto',\n",
" 'y':'auto'}).to_dataset(name=b)\n",
" ds_tmp = ds_tmp.rename({'band':'t'})\n",
" ds_tmp['t'] = dates\n",
" b_l.append(ds_tmp)\n",
" \n",
" t5 = time.time()\n",
" print('Create/Merge Xarray',t5-t4)\n",
" \n",
" ds = xr.merge(b_l)\n",
" return(ds,vrt_files)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Get File Meta 3.755052328109741\n",
"STAC Item --> VRT 2.0991501808166504\n",
"Build VRT 0.34650278091430664\n",
"Create/Merge Xarray 0.1797325611114502\n",
"Completed IN: 6.388219118118286 seconds\n"
]
},
{
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".xr-wrap {\n",
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".xr-text-repr-fallback {\n",
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" display: none;\n",
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"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
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".xr-header > div,\n",
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".xr-obj-type,\n",
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" 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.Dataset&gt;\n",
"Dimensions: (t: 45, x: 3660, y: 3660)\n",
"Coordinates:\n",
" * t (t) object 2021-01-21 2021-02-07 ... 2020-09-18 2020-07-10\n",
" * y (y) float64 4.6e+06 4.6e+06 4.6e+06 ... 4.49e+06 4.49e+06 4.49e+06\n",
" * x (x) float64 5e+05 5e+05 5.001e+05 ... 6.097e+05 6.097e+05 6.098e+05\n",
"Data variables:\n",
" B01 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B02 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B03 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B04 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B05 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B06 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B07 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B08 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B09 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B10 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B11 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" B12 (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;\n",
" Fmask (t, y, x) int16 dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><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-f66213ca-9b82-46c4-ba8e-6b62b1573a3a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f66213ca-9b82-46c4-ba8e-6b62b1573a3a' 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'>t</span>: 45</li><li><span class='xr-has-index'>x</span>: 3660</li><li><span class='xr-has-index'>y</span>: 3660</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1979d569-9b88-4495-94c0-f84050b28615' class='xr-section-summary-in' type='checkbox' checked><label for='section-1979d569-9b88-4495-94c0-f84050b28615' 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'>object</div><div class='xr-var-preview xr-preview'>2021-01-21 ... 2020-07-10</div><input id='attrs-b01c2f08-6078-4c5f-9ebb-d790b0226e0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b01c2f08-6078-4c5f-9ebb-d790b0226e0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45a21aba-ef43-422d-88e0-c9572b22ebac' class='xr-var-data-in' type='checkbox'><label for='data-45a21aba-ef43-422d-88e0-c9572b22ebac' 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([datetime.date(2021, 1, 21), datetime.date(2021, 2, 7),\n",
" datetime.date(2021, 1, 31), datetime.date(2021, 1, 23),\n",
" datetime.date(2021, 2, 2), datetime.date(2021, 1, 6),\n",
" datetime.date(2021, 1, 11), datetime.date(2021, 1, 18),\n",
" datetime.date(2021, 1, 16), datetime.date(2021, 1, 8),\n",
" datetime.date(2021, 1, 3), datetime.date(2020, 12, 27),\n",
" datetime.date(2020, 12, 29), datetime.date(2020, 12, 24),\n",
" datetime.date(2021, 1, 1), datetime.date(2020, 12, 22),\n",
" datetime.date(2020, 12, 19), datetime.date(2020, 12, 17),\n",
" datetime.date(2020, 12, 7), datetime.date(2020, 12, 9),\n",
" datetime.date(2020, 12, 4), datetime.date(2020, 12, 2),\n",
" datetime.date(2020, 11, 29), datetime.date(2020, 11, 27),\n",
" datetime.date(2020, 11, 24), datetime.date(2020, 11, 22),\n",
" datetime.date(2020, 11, 19), datetime.date(2020, 11, 17),\n",
" datetime.date(2020, 11, 12), datetime.date(2020, 11, 14),\n",
" datetime.date(2020, 11, 7), datetime.date(2020, 11, 4),\n",
" datetime.date(2020, 11, 2), datetime.date(2020, 10, 30),\n",
" datetime.date(2020, 10, 28), datetime.date(2020, 10, 20),\n",
" datetime.date(2020, 10, 15), datetime.date(2020, 10, 13),\n",
" datetime.date(2020, 10, 10), datetime.date(2020, 10, 8),\n",
" datetime.date(2020, 10, 3), datetime.date(2020, 10, 5),\n",
" datetime.date(2020, 9, 30), datetime.date(2020, 9, 18),\n",
" datetime.date(2020, 7, 10)], dtype=object)</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'>4.6e+06 4.6e+06 ... 4.49e+06</div><input id='attrs-52c62d51-5175-4156-80ab-2699300983c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52c62d51-5175-4156-80ab-2699300983c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a2c519d-4bf5-4891-b9d9-b636a8c6e147' class='xr-var-data-in' type='checkbox'><label for='data-5a2c519d-4bf5-4891-b9d9-b636a8c6e147' 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([4600005., 4599975., 4599945., ..., 4490295., 4490265., 4490235.])</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'>5e+05 5e+05 ... 6.097e+05 6.098e+05</div><input id='attrs-1738270d-cf31-4ff5-8bdd-f69728473590' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1738270d-cf31-4ff5-8bdd-f69728473590' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3226236c-b286-4d9d-aa88-097804a933c3' class='xr-var-data-in' type='checkbox'><label for='data-3226236c-b286-4d9d-aa88-097804a933c3' 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([499995., 500025., 500055., ..., 609705., 609735., 609765.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6450856-e32a-4cde-b61b-46ddc4420f6f' class='xr-section-summary-in' type='checkbox' checked><label for='section-a6450856-e32a-4cde-b61b-46ddc4420f6f' class='xr-section-summary' >Data variables: <span>(13)</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>B01</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 3660, 3660), meta=np.ndarray&gt;</div><input id='attrs-d906062e-a754-4fd1-b2a7-a951dd245e66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d906062e-a754-4fd1-b2a7-a951dd245e66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74e6359d-3df9-4bb6-8841-de6c0a8c5d57' class='xr-var-data-in' type='checkbox'><label for='data-74e6359d-3df9-4bb6-8841-de6c0a8c5d57' 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>transform :</span></dt><dd>(30.0, 0.0, 499980.0, 0.0, -30.0, 4600020.0)</dd><dt><span>crs :</span></dt><dd>+init=epsg:32613</dd><dt><span>res :</span></dt><dd>(30.0, 30.0)</dd><dt><span>is_tiled :</span></dt><dd>1</dd><dt><span>nodatavals :</span></dt><dd>(-9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0, -9999.0)</dd><dt><span>scales :</span></dt><dd>(0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001)</dd><dt><span>offsets :</span></dt><dd>(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
"<table>\n",
" <thead>\n",
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr><th> Bytes </th><td> 1.21 GB </td> <td> 26.79 MB </td></tr>\n",
" <tr><th> Shape </th><td> (45, 3660, 3660) </td> <td> (1, 3660, 3660) </td></tr>\n",
" <tr><th> Count </th><td> 46 Tasks </td><td> 45 Chunks </td></tr>\n",
" <tr><th> Type </th><td> int16 </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
"</table>\n",
"</td>\n",
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" <tr><th> Type </th><td> int16 </td><td> numpy.ndarray </td></tr>\n",
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],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (t: 45, x: 3660, y: 3660)\n",
"Coordinates:\n",
" * t (t) object 2021-01-21 2021-02-07 ... 2020-09-18 2020-07-10\n",
" * y (y) float64 4.6e+06 4.6e+06 4.6e+06 ... 4.49e+06 4.49e+06 4.49e+06\n",
" * x (x) float64 5e+05 5e+05 5.001e+05 ... 6.097e+05 6.097e+05 6.098e+05\n",
"Data variables:\n",
" B01 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B02 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B03 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B04 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B05 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B06 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B07 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B08 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B09 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B10 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B11 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" B12 (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>\n",
" Fmask (t, y, x) int16 dask.array<chunksize=(1, 3660, 3660), meta=np.ndarray>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t1 = time.time()\n",
"ds,vrts = build_xr(cat,['B01','B02','B03','B04','B05','B06','B07','B08','B09','B10','B11','B12','Fmask'])\n",
"print('Completed IN:',time.time()-t1,'seconds')\n",
"ds"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
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