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from unittest import main, TestCase
import numpy
from . import data
import ectrans4py
import platform
system = platform.system()
if system == "Linux":
ectrans4py.init_env(unlimited_stack=True)
elif system == "Darwin":
ectrans4py.init_env(unlimited_stack=False)
else:
raise NotImplementedError("ectrans4py does not support Windows")
KNUMMAXRESOL = 10
EPSILON = 1e-10
class ArraysAlmostEqual(object):
def assert_arrays_diff_under_epsilon(self, x, y):
diff = x - y
diffmax = abs(diff.max())
diffmin = abs(diff.min())
self.assertTrue(diffmax < EPSILON, "diffmax is {}".format(diffmax))
self.assertTrue(diffmin < EPSILON, "diffmin is {}".format(diffmin))
class TestLAM(TestCase, ArraysAlmostEqual):
gpdims = {'X':54,
'Y':48,
'X_CIzone':43,
'Y_CIzone':37,
'X_resolution':1300.0,
'Y_resolution':1300.0}
truncation = {'in_X':26,
'in_Y':23}
spectral_data_sizes = (2592, 1968)
spdata = data.antwrp1300['sp']
gpdata = data.antwrp1300['sp2gp']
def test_etrans_inq(self):
spectral_data_sizes = ectrans4py.etrans_inq4py(
self.gpdims['X'],
self.gpdims['Y'],
self.gpdims['X_CIzone'],
self.gpdims['Y_CIzone'],
self.truncation['in_X'],
self.truncation['in_Y'],
KNUMMAXRESOL,
self.gpdims['X_resolution'],
self.gpdims['Y_resolution'])
self.assertEqual(spectral_data_sizes, self.spectral_data_sizes)
def test_sp2gp(self):
gpdata = ectrans4py.sp2gp_lam4py(
self.gpdims['X'],
self.gpdims['Y'],
self.gpdims['X_CIzone'],
self.gpdims['Y_CIzone'],
self.truncation['in_X'],
self.truncation['in_Y'],
KNUMMAXRESOL,
len(self.spdata.flatten()),
False, # no derivatives
False, # spectral_coeff_order != 'model',
self.gpdims['X_resolution'],
self.gpdims['Y_resolution'],
self.spdata.flatten())[0]
self.assert_arrays_diff_under_epsilon(gpdata, gpdata.flatten())
def test_gp2sp(self):
spdata = ectrans4py.gp2sp_lam4py(
self.spectral_data_sizes[1],
self.gpdims['X'],
self.gpdims['Y'],
self.gpdims['X_CIzone'],
self.gpdims['Y_CIzone'],
self.truncation['in_X'],
self.truncation['in_Y'],
KNUMMAXRESOL,
self.gpdims['X_resolution'],
self.gpdims['Y_resolution'],
False, # spectral_coeff_order != 'model',
self.gpdata.flatten())
self.assert_arrays_diff_under_epsilon(spdata, spdata.flatten())
class TestGlobal(TestCase, ArraysAlmostEqual):
gpdims = {'lat_number':150,
'lon_number_by_lat':data.lon_number_by_lat}
truncation = {'max':148}
spectral_data_sizes = (
33052,
11175,
data.zonal_wavenumbers)
spdata = data.tl149_c24['sp']
gpdata_latlon = data.tl149_c24['sp2gp']
# Pack latlon gridded data to reduced grid
gpdata = numpy.zeros((sum(gpdims['lon_number_by_lat'])))
offset = 0
for i in range(gpdims['lat_number']):
nlon = gpdims['lon_number_by_lat'][i]
gpdata[offset:offset+nlon] = gpdata_latlon[i,:nlon]
offset += nlon
def test_get_legendre_assets(self):
nspec = sum([self.truncation['max'] + 2 - im for im in range(self.truncation['max']+1)])
knmeng, weights, polys = ectrans4py.get_legendre_assets(
self.gpdims['lat_number'],
self.truncation['max'],
len(self.gpdims['lon_number_by_lat']),
nspec,
self.gpdims['lon_number_by_lat'],
KNUMMAXRESOL
)
weights_sum = sum(weights)
# The sum of the Gaussian weights should be equal to 1.0
self.assertTrue(abs(weights_sum - 1.0) < EPSILON, f"sum of weights is {weights_sum}")
def test_trans_inq4py(self):
spectral_data_sizes = ectrans4py.trans_inq4py(
self.gpdims['lat_number'],
self.truncation['max'],
len(self.gpdims['lon_number_by_lat']),
self.gpdims['lon_number_by_lat'],
KNUMMAXRESOL)
self.assertEqual(spectral_data_sizes[0:2], self.spectral_data_sizes[0:2]) # dimensions
numpy.testing.assert_array_equal(spectral_data_sizes[2], self.spectral_data_sizes[2]) # zonal_wavenumbers
def test_sp2gp(self):
gpdata = ectrans4py.sp2gp_gauss4py(
self.gpdims['lat_number'],
self.truncation['max'],
KNUMMAXRESOL,
sum(self.gpdims['lon_number_by_lat']),
len(self.gpdims['lon_number_by_lat']),
self.gpdims['lon_number_by_lat'],
len(self.spdata),
False, # no derivatives
False, # spectral_coeff_order != 'model',
self.spdata)[0]
self.assert_arrays_diff_under_epsilon(self.gpdata, gpdata)
def test_gp2sp(self):
spdata = ectrans4py.gp2sp_gauss4py(
self.spectral_data_sizes[1] * 2, # *2 for complex coefficients
self.gpdims['lat_number'],
self.truncation['max'],
KNUMMAXRESOL,
len(self.gpdims['lon_number_by_lat']),
self.gpdims['lon_number_by_lat'],
len(self.gpdata),
False, # spectral_coeff_order != 'model',
self.gpdata)
self.assert_arrays_diff_under_epsilon(self.spdata, spdata)
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