def test_compare_column_and_integrated_profile(self):
from CALIOPy.utils import integrate_profile, mask_data
ext_data = cis.read_data(self.TEST_FILENAME,
"Extinction_Coefficient_532",
"Caliop_V4_QC_NO_PRESSURE")
col_data = cis.read_data(
self.TEST_FILENAME,
"Column_Optical_Depth_Tropospheric_Aerosols_532", "Caliop_V4_QC")
backscatter = cis.read_data(self.TEST_FILENAME,
"Total_Backscatter_Coefficient_532",
"Caliop_V4_QC_NO_PRESSURE")
int_backscatter = cis.read_data(
self.TEST_FILENAME, "Column_Integrated_Attenuated_Backscatter_532",
"Caliop_V4_QC")
# Integrate the profile
int_data = integrate_profile(ext_data)
my_int_back = integrate_profile(backscatter)
assert np.abs((my_int_back.data - int_backscatter.data[:, 0]
).mean()) < 0.016, "Backscatter integrations differ"
print(np.abs((my_int_back.data - int_backscatter.data[:, 0]).mean()))
#-0.0154302524737
# There are a *few* values which are quite different, but I really don't know why, and they also have fairly
# large uncertainty. On average the differences are very small.
print(np.abs(np.mean(int_data.data - col_data.data[:, 0])))
assert np.abs(np.mean(int_data.data - col_data.data[:, 0])
) < 0.015, 'Extinction integrations are different'
assert np.array_equal(
int_data.data.mask,
col_data.data[:, 0].mask), 'Arrays have different masks'
def test_integrate_profile(self):
from CALIOPy.utils import integrate_profile
from cf_units import Unit
int_data = integrate_profile(mock_extinction,
spacing=mock_vertical_spacing)
assert_almost_equal(int_data.data, mock_col_aod.data[:, 0])
assert int_data.units == Unit(1)
def compare_column_and_integrated_profile(self):
from CALIOPy.utils import integrate_profile
ext_data = cis.read_data(self.TEST_FILENAME,
"Extinction_Coefficient_532")
col_data = cis.read_data(self.TEST_FILENAME,
"Column_Optical_Depth_Aerosols_532")
int_data = integrate_profile(ext_data)
assert_almost_equal(int_data.data, col_data.data, delta=0.05)
def test_compare_column_and_integrated_profile(self):
from CALIOPy.utils import integrate_profile, mask_data, remove_air_pressure
ext_data = cis.read_data(self.TEST_FILENAME,
"Extinction_Coefficient_532",
"Caliop_V4_NO_PRESSURE")
col_data = cis.read_data(
self.TEST_FILENAME,
"Column_Optical_Depth_Tropospheric_Aerosols_532")
cum_prob = cis.read_data(self.TEST_FILENAME,
"Column_IAB_Cumulative_Probability")
backscatter = cis.read_data(self.TEST_FILENAME,
"Total_Backscatter_Coefficient_532")
int_backscatter = cis.read_data(
self.TEST_FILENAME, "Column_Integrated_Attenuated_Backscatter_532")
remove_air_pressure(ext_data)
remove_air_pressure(col_data)
remove_air_pressure(cum_prob)
remove_air_pressure(backscatter)
remove_air_pressure(int_backscatter)
# Mask both datasets
col_data, cum_data, int_backscatter = mask_data(
[col_data, cum_prob, int_backscatter], self.cad_score,
self.extinction_qc)
ext_data, backscatter = mask_data([ext_data, backscatter],
self.cad_score, self.extinction_qc)
# Integrate the profile
int_data = integrate_profile(ext_data)
my_int_back = integrate_profile(backscatter)
assert np.abs((my_int_back.data - int_backscatter.data[:, 0]
).mean()) < 0.016, "Backscatter integrations differ"
#-0.0154302524737
print(np.abs((my_int_back.data - int_backscatter.data[:, 0]).mean()))
# There are a *few* values which are quite different, but I really don't know why, and they also have fairly
# large uncertainty. On average the differences are very small.
print(np.abs(np.mean(int_data.data - col_data.data[:, 0])))
assert np.abs(np.mean(int_data.data - col_data.data[:, 0])
) < 0.015, 'Extinction integrations are different'
assert np.array_equal(
int_data.data.mask,
col_data.data[:, 0].mask), 'Arrays have different masks'
def test_integrate_profile(self):
from CALIOPy.utils import integrate_profile, mask_data
ext_data = cis.read_data(self.TEST_FILENAME,
"Extinction_Coefficient_532",
"Caliop_V4_QC_NO_PRESSURE")
int_data = integrate_profile(ext_data)
assert np.all(int_data.data > 0.0)
assert int_data.data.count() == 639
# This isn't the same as the above test because we're doing the masking before the integration
assert_almost_equal(int_data.data.mean(), 0.15009987)
def test_integrate_profile(self):
from CALIOPy.utils import integrate_profile, remove_air_pressure, mask_data
ext_data = cis.read_data(self.TEST_FILENAME,
"Extinction_Coefficient_532",
"Caliop_V4_NO_PRESSURE")
remove_air_pressure(ext_data)
int_data = integrate_profile(ext_data)
assert np.all(int_data.data > 0.0)
assert int_data.data.shape == (4224, )
# Now check that masking this data produces something sensible
masked_int_data, = mask_data([int_data], self.cad_score,
self.extinction_qc)
assert masked_int_data.data.count() == 639
assert_almost_equal(masked_int_data.data.mean(), 0.1535116)
def test_compare_column_and_integrated_profile(self):
from CALIOPy.utils import integrate_profile, mask_data
# Mask the Column data first, so the air_pressure gets popped off the cad score and extinction_qc
col_data, = mask_data([mock_col_aod], self.cad_score,
self.extinction_qc)
ext_data, = mask_data([mock_extinction], self.cad_score,
self.extinction_qc)
# To match the pain of the original CALIOP data :-)
col_data.data = col_data.data[:, 0]
# Integrate the profile, set the spacing to one for this unit test
int_data = integrate_profile(ext_data, spacing=mock_vertical_spacing)
assert_array_equal(int_data.data, col_data.data)