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import cmor
import numpy
cmor.setup("Test", netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset_json("Test/CMOR_input_example.json")
cmor.load_table("Tables/CMIP6_Omon.json")
nlat = 90
dlat = 180 / nlat
lats = numpy.arange(-90 + dlat / 2., 90, dlat)
blats = numpy.arange(-90, 90 + dlat, dlat)
ilat = cmor.axis(
table_entry='latitude',
coord_vals=lats,
cell_bounds=blats,
units='degrees_north')
myregions = [
"atlantic_ocean",
"indian_pacific_ocean",
"pacific_ocean",
"atlantic_arctic_ocean",
"global_ocean"]
nreg = len(myregions)
ireg = cmor.axis(table_entry='basin', units='1', coord_vals=myregions)
ntime = 12
itim = cmor.axis(
table_entry='time',
units='months since 2030',
interval='1 month',
coord_vals=numpy.arange(ntime),
cell_bounds=numpy.arange(
ntime + 1))
var = cmor.variable(table_entry='htovgyre', units='W',
axis_ids=numpy.array([itim, ireg, ilat]))
data = numpy.random.random((ntime, nreg, nlat)) * 3.E14
cmor.write(var, data)
cmor.close()
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