def test_reproject_input_data_odd_downsample(self):
"""test function reproject_input_data with odd downsampling"""
data_in, meta_list = data_arrays_resampling_demo()
#
data_out, meta_out = \
lp.reproject_input_data(data_in, meta_list,
i_align=0, # high res data as reference
target_res_arcsec=6120, # 1.7 degree
global_origins=(-180, 90),
)
self.assertEqual(1.7, meta_out['transform'][0]) # check resolution
reference_array = np.array([[0.425, 1.7631578], [3.425, 4.763158]],
dtype='float32')
np.testing.assert_array_equal(reference_array, data_out[0])
def test_reproject_input_data_downsample_conserve_sum(self):
"""test function reproject_input_data downsampling with conservation of sum"""
data_in, meta_list = data_arrays_resampling_demo()
#
data_out, meta_out = lp.reproject_input_data(data_in,
meta_list,
i_align=0,
target_res_arcsec=None,
global_origins=(-180, 90),
conserve='sum')
# test reference data unchanged:
np.testing.assert_array_equal(data_in[0], data_out[0])
# test conserve sum:
for i, _ in enumerate(data_in):
self.assertAlmostEqual(data_in[i].sum(), data_out[i].sum())
def test_reproject_input_data_downsample(self):
"""test function reproject_input_data downsampling lit to pop grid
(default resampling for LitPop)"""
data_in, meta_list = data_arrays_resampling_demo()
#
data_out, meta_out = lp.reproject_input_data(data_in,
meta_list,
i_align=0,
target_res_arcsec=None,
global_origins=(-180, 90))
# test reference data unchanged:
np.testing.assert_array_equal(data_in[0], data_out[0])
# test northward shift:
np.testing.assert_array_equal(data_in[1][1, :], data_out[1][0, :])
# test reprojected nl data:
reference_array = np.array([[5.020408, 2.267857, 0.12244898],
[1.1224489, 0.6785714, 0.7346939]],
dtype='float32')
np.testing.assert_array_almost_equal_nulp(reference_array, data_out[2])
def test_reproject_input_data_upsample(self):
"""test function reproject_input_data with upsampling
(usually not required for LitPop)"""
data_in, meta_list = data_arrays_resampling_demo()
#
data_out, meta_out = lp.reproject_input_data(
data_in,
meta_list,
i_align=2, # high res data as reference
target_res_arcsec=None,
global_origins=(-180, 90))
# test reference data unchanged:
np.testing.assert_array_equal(data_in[2], data_out[2])
# test northward shift:
np.testing.assert_array_equal(data_out[0][2, :], data_out[1][0, :])
np.testing.assert_array_equal(data_out[0][3, :], data_out[1][1, :])
# test reprojected nl data:
reference_array = np.array(
[[0., 0.25, 0.75, 1.25, 1.75, 2.], [0.75, 1., 1.5, 2., 2.5, 2.75],
[2.25, 2.5, 3., 3.5, 4., 4.25], [3., 3.25, 3.75, 4.25, 4.75, 5.]],
dtype='float32')
np.testing.assert_array_equal(reference_array, data_out[0])