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import json
import cmor
import unittest
import numpy
from netCDF4 import Dataset
CMIP7_TABLES_PATH = "cmip7-cmor-tables/tables"
CV_PATH = "TestTables/CMIP7_CV.json"
USER_INPUT = {
"_AXIS_ENTRY_FILE": "CMIP7_coordinate.json",
"_FORMULA_VAR_FILE": "CMIP7_formula_terms.json",
"_cmip7_option": 1,
"_controlled_vocabulary_file": CV_PATH,
"activity_id": "CMIP",
"branch_method": "standard",
"branch_time_in_child": 30.0,
"branch_time_in_parent": 10800.0,
"calendar": "360_day",
"cv_version": "6.2.19.0",
"experiment": "Simulation of the pre-industrial climate",
"experiment_id": "piControl",
"forcing_index": "f30",
"grid": "N96",
"grid_label": "gn",
"initialization_index": "i000001d",
"institution_id": "PCMDI",
"license_id": "CC BY 4.0",
"nominal_resolution": "250 km",
"outpath": ".",
"parent_mip_era": "CMIP7",
"parent_time_units": "days since 1850-01-01",
"parent_activity_id": "CMIP",
"parent_source_id": "PCMDI-test-1-0",
"parent_experiment_id": "piControl",
"parent_variant_label": "r1i1p1f3",
"physics_index": "p1",
"realization_index": "r009",
"source_id": "PCMDI-test-1-0",
"source_type": "AOGCM CHEM BGC",
"tracking_prefix": "hdl:21.14100",
"host_collection": "CMIP7",
"frequency": "mon",
"region": "glb",
"archive_id": "WCRP",
"output_path_template": "<activity_id><source_id><experiment_id><member_id><variable_id><branding_suffix><grid_label>",
"output_file_template": "<variable_id><branding_suffix><frequency><region><grid_label><source_id><experiment_id><variant_id>[<time_range>].nc",
}
class TestCMIP7(unittest.TestCase):
def setUp(self):
"""
Write out a simple file using CMOR
"""
# Set up CMOR
cmor.setup(inpath=CMIP7_TABLES_PATH, netcdf_file_action=cmor.CMOR_REPLACE)
# Define dataset using USER_INPUT
with open("Test/input_cmip7.json", "w") as input_file_handle:
json.dump(USER_INPUT, input_file_handle, sort_keys=True, indent=4)
# read dataset info
error_flag = cmor.dataset_json("Test/input_cmip7.json")
if error_flag:
raise RuntimeError("CMOR dataset_json call failed")
def test_cmip7(self):
data = [27] * (2 * 3 * 4)
tos = numpy.array(data)
tos.shape = (2, 3, 4)
lat = numpy.array([10, 20, 30])
lat_bnds = numpy.array([5, 15, 25, 35])
lon = numpy.array([0, 90, 180, 270])
lon_bnds = numpy.array([-45, 45,
135,
225,
315
])
time = numpy.array([15.5, 45])
time_bnds = numpy.array([0, 31, 60])
cmor.load_table("CMIP7_ocean.json")
cmorlat = cmor.axis("latitude",
coord_vals=lat,
cell_bounds=lat_bnds,
units="degrees_north")
cmorlon = cmor.axis("longitude",
coord_vals=lon,
cell_bounds=lon_bnds,
units="degrees_east")
cmortime = cmor.axis("time",
coord_vals=time,
cell_bounds=time_bnds,
units="days since 2018")
axes = [cmortime, cmorlat, cmorlon]
cmortos = cmor.variable("tos_tavg-u-hxy-sea", "degC", axes)
self.assertEqual(cmor.write(cmortos, tos), 0)
filename = cmor.close(cmortos, file_name=True)
self.assertEqual(cmor.close(), 0)
ds = Dataset(filename)
attrs = ds.ncattrs()
test_attrs = {
'branded_variable': 'tos_tavg-u-hxy-sea',
'branding_suffix': 'tavg-u-hxy-sea',
'temporal_label': 'tavg',
'vertical_label': 'u',
'horizontal_label': 'hxy',
'area_label': 'sea',
'region': 'glb',
'frequency': 'mon',
'archive_id': 'WCRP',
'mip_era': 'CMIP7',
'data_specs_version': 'CMIP-7.0.0.0',
'host_collection': 'CMIP7',
}
for attr, val in test_attrs.items():
self.assertIn(attr, attrs)
self.assertEqual(val, ds.getncattr(attr))
institution_id = USER_INPUT["institution_id"]
license_id = "CC BY 4.0"
license_type = "Creative Commons Attribution 4.0 International"
license_url = "https://creativecommons.org/licenses/by/4.0/"
license = \
(f"{license_id}; CMIP7 data produced by {institution_id} is "
f"licensed under a {license_type} License ({license_url}). "
"Consult https://pcmdi.llnl.gov/CMIP7/TermsOfUse for terms of "
"use governing CMIP7 output, including citation requirements and "
"proper acknowledgment. The data producers and data providers "
"make no warranty, either express or implied, including, but not "
"limited to, warranties of merchantability and fitness for a "
"particular purpose. All liabilities arising from the supply of "
"the information (including any liability arising in negligence) "
"are excluded to the fullest extent permitted by law."
)
self.assertTrue("license" in attrs)
self.assertTrue("license_id" not in attrs)
self.assertTrue("license_type" not in attrs)
self.assertTrue("license_url" not in attrs)
self.assertEqual(license, ds.getncattr("license"))
ds.close()
def test_secondary_modeling_realm(self):
data = [27] * (2 * 3 * 4)
pr = numpy.array(data)
pr.shape = (2, 3, 4)
lat = numpy.array([10, 20, 30])
lat_bnds = numpy.array([5, 15, 25, 35])
lon = numpy.array([0, 90, 180, 270])
lon_bnds = numpy.array([-45, 45,
135,
225,
315
])
time = numpy.array([15.5, 45])
time_bnds = numpy.array([0, 31, 60])
cmor.load_table("CMIP7_atmos.json")
cmorlat = cmor.axis("latitude",
coord_vals=lat,
cell_bounds=lat_bnds,
units="degrees_north")
cmorlon = cmor.axis("longitude",
coord_vals=lon,
cell_bounds=lon_bnds,
units="degrees_east")
cmortime = cmor.axis("time",
coord_vals=time,
cell_bounds=time_bnds,
units="days since 2018")
axes = [cmortime, cmorlat, cmorlon]
cmorpr = cmor.variable("prra_tavg-u-hxy-is", "kg m-2 s-1", axes)
self.assertEqual(cmor.write(cmorpr, pr), 0)
filename = cmor.close(cmorpr, file_name=True)
self.assertEqual(cmor.close(), 0)
ds = Dataset(filename)
attrs = ds.ncattrs()
test_attrs = {
'branded_variable': 'prra_tavg-u-hxy-is',
'branding_suffix': 'tavg-u-hxy-is',
'temporal_label': 'tavg',
'vertical_label': 'u',
'horizontal_label': 'hxy',
'area_label': 'is',
'region': 'glb',
'frequency': 'mon',
'archive_id': 'WCRP',
'mip_era': 'CMIP7',
'data_specs_version': 'CMIP-7.0.0.0',
'host_collection': 'CMIP7',
'realm': 'atmos land landIce',
}
for attr, val in test_attrs.items():
self.assertIn(attr, attrs)
self.assertEqual(val, ds.getncattr(attr))
ds.close()
if __name__ == '__main__':
unittest.main()
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