def test_aligngrids_samesize(precip_rate_ncdata_cnrmcm5, wdir_ncdata_cnrmcm5):
wdir, precip, lats, lons = MonsoonData.align_grids(
wdir_ncdata_cnrmcm5, precip_rate_ncdata_cnrmcm5)
assert_almost_equal(precip, precip_rate_ncdata_cnrmcm5.variable)
assert_almost_equal(wdir, wdir_ncdata_cnrmcm5.variable)
assert_almost_equal(lats, precip_rate_ncdata_cnrmcm5.lats)
assert_almost_equal(lons, precip_rate_ncdata_cnrmcm5.lons)
def test_aligngrids_largernc2(precip_rate_ncdata_access13,
wdir_ncdata_access13,
path_wdir_cnrmcm5_adj_coords):
wdir, precip, lats, lons = MonsoonData.align_grids(
wdir_ncdata_access13, precip_rate_ncdata_access13)
wdir_truth = np.load(path_wdir_cnrmcm5_adj_coords)
assert_almost_equal(precip, precip_rate_ncdata_access13.variable)
assert_almost_equal(wdir, wdir_truth)
assert_almost_equal(lats, precip_rate_ncdata_access13.lats)
assert_almost_equal(lons, precip_rate_ncdata_access13.lons)
def test_init(path_monsoon_access13, precip_rate_ncdata_access13,
wdir_ncdata_access13, truth_monsoon_indx_access13):
with nc.Dataset(path_monsoon_access13, 'r') as monsoon_reader:
monsoon = MonsoonData(monsoon_reader)
assert_almost_equal(truth_monsoon_indx_access13, monsoon.variable)
assert monsoon.var_name == 'monsoon'
assert_almost_equal(monsoon.lats, precip_rate_ncdata_access13.lats)
assert monsoon.time_units == wdir_ncdata_access13.time_units
assert monsoon.globalattrs[
'frequency'] == precip_rate_ncdata_access13.globalattrs['frequency']
assert monsoon.globalattrs[
'institute_id'] == wdir_ncdata_access13.globalattrs['institute_id']
def test_monsoon_compute_nc_input(precip_rate_ncdata_access13,
wdir_ncdata_access13,
truth_monsoon_indx_access13):
criteria = criteria_generator(pr_min=5, wd_min=180, wd_max=270)
monsoon = MonsoonData.compute(precip_rate_ncdata_access13,
wdir_ncdata_access13, criteria)
assert_almost_equal(truth_monsoon_indx_access13, monsoon.variable)
assert monsoon.var_name == 'monsoon'
assert_almost_equal(monsoon.lats, precip_rate_ncdata_access13.lats)
assert monsoon.time_units == wdir_ncdata_access13.time_units
assert monsoon.globalattrs[
'frequency'] == precip_rate_ncdata_access13.globalattrs['frequency']
assert monsoon.globalattrs[
'institute_id'] == wdir_ncdata_access13.globalattrs['institute_id']
assert monsoon.globalattrs['monsoon_criteria'] == criteria['summary_dict']
def test_monsoon_compute_misaligned_models(precip_rate_ncdata_access13,
wdir_ncdata_cnrmcm5):
with pytest.raises(TypeError):
MonsoonData.compute(
precip_rate_ncdata_access13, wdir_ncdata_cnrmcm5,
criteria_generator(pr_min=5, wd_min=180, wd_max=270))
def test_monsoon_compute_wdir_typeerror(precip_rate_ncdata_access13,
path_uas_access13):
with pytest.raises(TypeError):
MonsoonData.compute(
precip_rate_ncdata_access13, path_uas_access13,
criteria_generator(pr_min=5, wd_min=180, wd_max=270))
def test_init_improper_input(path_monsoon_access13):
with pytest.raises(TypeError):
MonsoonData(path_monsoon_access13)
p_rate_path = os.path.join(folder, r"created/pr_from_flux_ACCESS1-3.nc")
# p_rate.write(p_rate_path)
# Generate wind direction
with nc.Dataset(uas_test_file_lin, 'r') as uas_reader, \
nc.Dataset(vas_test_file_lin, 'r') as vas_reader:
wdir = NCdata.wind_dir_from_components(uas_reader, vas_reader)
wdir_path = os.path.join(folder, r"created/wdir_ACCESS1-3.nc")
# wdir.write(wdir_path)
# Compute monsoon
criteria = criteria_generator(pr_min=5, wd_min=180, wd_max=270)
with nc.Dataset(p_rate_path, 'r') as pr_reader, \
nc.Dataset(wdir_path, 'r') as wd_reader:
output = MonsoonData.compute(pr_reader, wd_reader, criteria)
filepath = '/home/rwegener/repos/wnpmonsoon/tests/data/created/monsoon_index_access13_pr5plus_180270wd_nomask.nc'
# output.write(filepath)
src = nc.Dataset(filepath, 'r')
print(src.variables['monsoon'][:])
output.variable = output.variable * 5
from wnpmonsoon.netcdf import NetCDFWriter
writer = NetCDFWriter(filepath)
writer.set_global_attributes(**output.globalattrs)
writer.set_global_attributes(model_id=output.model_id)
writer.create_time_variable("time",
output.time,