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Interim commit to try to figure out dimensionality for irregular axes.
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@BobTorgerson
BobTorgerson committed Sep 25, 2023
1 parent 0e9d44c commit 2497f4c
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Showing 4 changed files with 254 additions and 7 deletions.
12 changes: 8 additions & 4 deletions iem/tas_projected_2km/ingest.json
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Expand Up @@ -11,9 +11,9 @@
"automated": true
},
"input": {
"coverage_id": "tas_projected_2km",
"coverage_id": "tas_2km_projected",
"paths": [
"/usr/local/data/torgerso/temperature/tas/*.nc"
"/usr/local/data/torgerso/temperature/tas/attempt/*.nc"
]
},
"recipe": {
Expand All @@ -22,7 +22,7 @@
"wms_import": true,
"import_order": "ascending",
"coverage": {
"crs": "OGC/0/Index1D?axis-label=\"model\"@OGC/0/Index1D?axis-label=\"scenario\"@OGC/0/Index1D?axis-label=\"month\"@OGC/0/Index1D?axis-label=\"year\"@EPSG/0/4269",
"crs": "OGC/0/Index1D?axis-label=\"model\"@OGC/0/Index1D?axis-label=\"scenario\"@OGC/0/Index1D?axis-label=\"month\"@OGC/0/Index1D?axis-label=\"year\"@EPSG/0/3338",
"metadata": {
"type": "xml",
"global": {
Expand Down Expand Up @@ -180,22 +180,26 @@
"axes": {
"model": {
"min": "0",
"max": "4",
"max": "5",
"irregular": true,
"gridOrder": 0
},
"scenario": {
"min": "0",
"max": "2",
"irregular": true,
"gridOrder": 1
},
"month": {
"min": "0",
"max": "11",
"irregular": true,
"gridOrder": 2
},
"year": {
"min": "0",
"max": "94",
"irregular": true,
"gridOrder": 3
},
"X": {
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22 changes: 22 additions & 0 deletions iem/tas_projected_2km/luts.py
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@@ -0,0 +1,22 @@
models = {
"GFDL-CM3": 0,
"GISS-E2-R": 1,
"IPSL-CM5A-LR": 2,
"MRI-CGCM3": 3,
"NCAR-CCSM4": 4,
}

months = {
"01": 0,
"02": 1,
"03": 2,
"04": 3,
"05": 4,
"06": 5,
"07": 6,
"08": 7,
"09": 8,
"10": 9,
"11": 10,
"12": 11,
}
221 changes: 221 additions & 0 deletions iem/tas_projected_2km/luts_ingest.json
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@@ -0,0 +1,221 @@
{
"config": {
"service_url": "http://localhost:8080/rasdaman/ows",
"tmp_directory": "/tmp/",
"crs_resolver": "http://localhost:8080/def/",
"default_crs": "http://localhost:8080/def/crs/EPSG/0/3338",
"default_null_values": [
"-9999"
],
"mock": false,
"automated": true
},
"input": {
"coverage_id": "tas_2km_projected",
"paths": [
"/usr/local/data/torgerso/temperature/tas/attempt/*.nc"
]
},
"recipe": {
"name": "general_coverage",
"options": {
"wms_import": true,
"import_order": "ascending",
"coverage": {
"crs": "OGC/0/Index1D?axis-label=\"model\"@OGC/0/Index1D?axis-label=\"scenario\"@OGC/0/Index1D?axis-label=\"month\"@OGC/0/Index1D?axis-label=\"year\"@EPSG/0/3338",
"metadata": {
"type": "xml",
"global": {
"Title": "'Projected 2km Temperature'",
"Encoding": {
"tas": "C",
"tasmax": "C",
"tasmin": "C",
"model": {
"0": "GFDL-CM3",
"1": "GISS-E2-R",
"2": "IPSL-CM5A-LR",
"3": "MRI-CGCM3",
"4": "NCAR-CCSM4"
},
"scenario": {
"0": "rcp45",
"1": "rcp60",
"2": "rcp85"
},
"month": {
"0": "01",
"1": "02",
"2": "03",
"3": "04",
"4": "05",
"5": "06",
"6": "07",
"7": "08",
"8": "09",
"9": "10",
"10": "11",
"11": "12"
},
"year": {
"0": "2006",
"1": "2007",
"2": "2008",
"3": "2009",
"4": "2010",
"5": "2011",
"6": "2012",
"7": "2013",
"8": "2014",
"9": "2015",
"10": "2016",
"11": "2017",
"12": "2018",
"13": "2019",
"14": "2020",
"15": "2021",
"16": "2022",
"17": "2023",
"18": "2024",
"19": "2025",
"20": "2026",
"21": "2027",
"22": "2028",
"23": "2029",
"24": "2030",
"25": "2031",
"26": "2032",
"27": "2033",
"28": "2034",
"29": "2035",
"30": "2036",
"31": "2037",
"32": "2038",
"33": "2039",
"34": "2040",
"35": "2041",
"36": "2042",
"37": "2043",
"38": "2044",
"39": "2045",
"40": "2046",
"41": "2047",
"42": "2048",
"43": "2049",
"44": "2050",
"45": "2051",
"46": "2052",
"47": "2053",
"48": "2054",
"49": "2055",
"50": "2056",
"51": "2057",
"52": "2058",
"53": "2059",
"54": "2060",
"55": "2061",
"56": "2062",
"57": "2063",
"58": "2064",
"59": "2065",
"60": "2066",
"61": "2067",
"62": "2068",
"63": "2069",
"64": "2070",
"65": "2071",
"66": "2072",
"67": "2073",
"68": "2074",
"69": "2075",
"70": "2076",
"71": "2077",
"72": "2078",
"73": "2079",
"74": "2080",
"75": "2081",
"76": "2082",
"77": "2083",
"78": "2084",
"79": "2085",
"80": "2086",
"81": "2087",
"82": "2088",
"83": "2089",
"84": "2090",
"85": "2091",
"86": "2092",
"87": "2093",
"88": "2094",
"89": "2095",
"90": "2096",
"91": "2097",
"92": "2098",
"93": "2099",
"94": "2100"
}
}
}
},
"slicer": {
"type": "netcdf",
"pixelIsPoint": true,
"bands": [
{
"name": "tas",
"identifier": "tas",
"nilValue": "-9999.0"
},
{
"name": "tasmax",
"identifier": "tasmax",
"nilValue": "-9999.0"
},
{
"name": "tasmin",
"identifier": "tasmin",
"nilValue": "-9999.0"
}
],
"axes": {
"model": {
"statements": "import imp, os; luts = imp.load_source('luts', os.getenv('LUTS_PATH')); regex_str = 'combined_(GFDL-CM3|GISS-E2-R|IPSL-CM5A-LR|MRI-CGCM3|NCAR-CCSM4)_(01|02|03|04|05|06|07|08|09|10|11|12)_temperature.nc'",
"min": "luts.models[regex_extract('${file:name}', regex_str, 1)]",
"irregular": true,
"gridOrder": 0
},
"scenario": {
"min": "0",
"max": "2",
"irregular": true,
"gridOrder": 1
},
"month": {
"min": "luts.months[regex_extract('${file:name}', regex_str, 2)]",
"irregular": true,
"gridOrder": 2
},
"year": {
"min": "0",
"max": "94",
"irregular": true,
"gridOrder": 3
},
"X": {
"min": "${netcdf:variable:x:min}",
"max": "${netcdf:variable:x:max}",
"resolution": "${netcdf:variable:x:resolution}",
"gridOrder": 5
},
"Y": {
"min": "${netcdf:variable:y:min}",
"max": "${netcdf:variable:y:max}",
"resolution": "${netcdf:variable:y:resolution}",
"gridOrder": 4
}
}
}
}
}
}
}
6 changes: 3 additions & 3 deletions iem/tas_projected_2km/merge.py
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Expand Up @@ -29,7 +29,7 @@
)

# No data value
nodata_value = -3.4e38
nodata_value = -9999

# Get the projected x and y coordinates from a single geotiff
with rio.open(files[0]) as src:
Expand All @@ -47,7 +47,7 @@

with rio.open(file) as src:
data = src.read(1, masked=True)
data = np.where(data.mask, -3.4e38, data)
data = np.where(data.mask, -9999, data)

data_array = xr.DataArray(
data=np.expand_dims(data, axis=(0, 1, 2, 3)),
Expand Down Expand Up @@ -77,7 +77,7 @@
ds = xr.merge(var_datasets)

# Define the CRS as EPSG:4269 or NAD83
crs_dict = {"crs": "EPSG:4269"}
crs_dict = {"crs": "EPSG:3338"}

# Add the CRS as an attribute to the dataset
ds.attrs.update(crs_dict)
Expand Down

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