def test_gdal_python_vs_old_prepifg_prep2(self):
for i in range(10):
thresh = 0.5
x_looks = y_looks = 2
res = 2
extents = [10, 0, 20, 10]
extents_str = [str(e) for e in extents]
data = np.array(np.random.randint(0, 3, size=(10, 10)),
dtype=np.float32)
# create the self.temp_tiff
self.manipulation(data, self.temp_tif, self.md)
# only band 1 is resapled in warp_old
averaged_and_resampled, _ = gdalwarp.crop_resample_average(
self.temp_tif,
extents, [res, -res],
self.out_tif,
thresh,
match_pirate=True)
ifg = Ifg(self.temp_tif)
# only band 1 is resampled in warp_old
data, self.old_prepifg_path = warp_old(ifg,
x_looks,
y_looks,
extents_str, [res, -res],
thresh=thresh,
crop_out=4,
verbose=False)
np.testing.assert_array_almost_equal(data,
averaged_and_resampled,
decimal=4)
def _warp(ifg, x_looks, y_looks, extents, resolution, thresh, crop_out,
write_to_disk=True):
"""
Convenience function for calling GDAL functionality
"""
if x_looks != y_looks:
raise ValueError('X and Y looks mismatch')
# cut, average, resample the final output layers
looks_path = cf.mlooked_path(ifg.data_path, y_looks, crop_out)
# # Add missing/updated metadata to resampled ifg/DEM
# new_lyr = type(ifg)(looks_path)
# new_lyr.open(readonly=True)
# # for non-DEMs, phase bands need extra metadata & conversions
# if hasattr(new_lyr, "phase_band"):
# # TODO: LOS conversion to vertical/horizontal (projection)
# # TODO: push out to workflow
# #if params.has_key(REPROJECTION_FLAG):
# # reproject()
driver_type = 'GTiff' if write_to_disk else 'MEM'
resampled_data, out_ds = gdalwarp.crop_resample_average(
input_tif=ifg.data_path,
extents=extents,
new_res=resolution,
output_file=looks_path,
thresh=thresh,
out_driver_type=driver_type)
if not write_to_disk:
return resampled_data, out_ds
def warp(ifg,
x_looks,
y_looks,
extents,
resolution,
thresh,
crop_out,
write_to_disc=True):
"""
Resamples 'ifg' and returns a new interferogram object.
:param xlooks: Factor to scale X axis by, 5 is 5x smaller, 1 is no change
:param ylooks: Factor to scale Y axis by, 5 is 5x smaller, 1 is no change
:param extents: Georeferenced extents for new file: (xfirst, yfirst, xlast, ylast)
:param resolution: [xres, yres] or None. Sets resolution output interferogram metadata.
Use *None* if raster size is not being changed
:param thresh: See thresh in prepare_ifgs()
:param verbose: True to print gdalwarp output to stdout
:param write_to_disc: Whether to write to disc during warp
:return xxxx
"""
if x_looks != y_looks:
raise ValueError('X and Y looks mismatch')
# cut, average, resample the final output layers
looks_path = cf.mlooked_path(ifg.data_path, y_looks, crop_out)
# # Add missing/updated metadata to resampled ifg/DEM
# new_lyr = type(ifg)(looks_path)
# new_lyr.open(readonly=True)
# # for non-DEMs, phase bands need extra metadata & conversions
# if hasattr(new_lyr, "phase_band"):
# # TODO: LOS conversion to vertical/horizontal (projection)
# # TODO: push out to workflow
# #if params.has_key(REPROJECTION_FLAG):
# # reproject()
driver_type = 'GTiff' if write_to_disc else 'MEM'
resampled_data, out_ds = gdalwarp.crop_resample_average(
input_tif=ifg.data_path,
extents=extents,
new_res=resolution,
output_file=looks_path,
thresh=thresh,
out_driver_type=driver_type)
if not write_to_disc:
return resampled_data, out_ds
def test_gdal_python_vs_old_prepifg_no_match_pirate(self):
for ifg in self.ifgs:
extents = [150.91, -34.229999976, 150.949166651, -34.17]
extents_str = [str(e) for e in extents]
orig_res = 0.000833333
thresh = 0.5
for looks in range(10):
x_looks = y_looks = looks
res = orig_res * x_looks
averaged_and_resapled, out_ds = gdalwarp.crop_resample_average(
ifg.data_path,
extents,
new_res=[res, -res],
output_file=self.temp_tif,
thresh=thresh,
match_pirate=False)
# only band 1 is resampled in warp_old
data, self.old_prepifg_path = warp_old(ifg,
x_looks,
y_looks,
extents_str,
[res, -res],
thresh=thresh,
crop_out=4,
verbose=False)
yres, xres = data.shape
# old_prepifg warp resample method loses one
# row at the bottom if nrows % 2 == 1
averaged_and_resapled = averaged_and_resapled[:yres, :xres]
nrows, ncols = averaged_and_resapled.shape
np.testing.assert_array_almost_equal(data,
averaged_and_resapled,
decimal=4)
# make sure they are the same after they are opened again
# Last [yres:nrows, xres:ncols] won't match due to Pirate
# dropping last few rows/columns depending on resolution/looks
data_from_file = gdal.Open(self.old_prepifg_path).ReadAsArray()
new_from_file = out_ds.ReadAsArray()
np.testing.assert_array_almost_equal(
data_from_file[:yres, :xres], new_from_file[:yres, :xres])
out_ds = None # manual close
def test_no_out_file_when_driver_type_is_mem(self):
for ifg in self.ifgs:
extents = [150.91, -34.229999976, 150.949166651, -34.17]
extents_str = [str(e) for e in extents]
orig_res = 0.000833333
thresh = 0.5
x_looks = y_looks = 6
res = orig_res * x_looks
averaged_and_resampled, out_ds = gdalwarp.crop_resample_average(
ifg.data_path,
extents,
new_res=[res, -res],
output_file=self.temp_tif,
thresh=thresh,
out_driver_type='MEM',
match_pirate=True)
# only band 1 is resampled in warp_old
data, self.old_prepifg_path = warp_old(ifg,
x_looks,
y_looks,
extents_str, [res, -res],
thresh=thresh,
crop_out=4,
verbose=False)
yres, xres = data.shape
# old_prepifg warp resample method loses one row at the bottom if
# nrows % 2 == 1
averaged_and_resampled = averaged_and_resampled[:yres, :xres]
np.testing.assert_array_almost_equal(data,
averaged_and_resampled,
decimal=4)
# make sure they are the same after they are opened again
data_from_file = gdal.Open(self.old_prepifg_path).ReadAsArray()
new_from_file = out_ds.ReadAsArray()
np.testing.assert_array_almost_equal(data_from_file, new_from_file)
self.assertFalse(os.path.exists(self.temp_tif))
out_ds = None # manual close
def test_gdal_python_vs_old_prepifg(self):
for ifg in self.ifgs:
extents = [150.91, -34.229999976, 150.949166651, -34.17]
extents_str = [str(e) for e in extents]
orig_res = 0.000833333
thresh = 0.5
for looks in range(1, 10):
x_looks = y_looks = looks
res = orig_res * x_looks
averaged_and_resampled = gdalwarp.crop_resample_average(
ifg.data_path,
extents,
new_res=[res, -res],
output_file=self.temp_tif,
thresh=thresh,
match_pirate=True)[0]
# only band 1 is resampled in warp_old
data, self.old_prepifg_path = warp_old(ifg,
x_looks,
y_looks,
extents_str,
[res, -res],
thresh=thresh,
crop_out=4,
verbose=False)
yres, xres = data.shape
# old_prepifg warp resample method loses one row
# at the bottom if nrows % 2 == 1
np.testing.assert_array_almost_equal(
data, averaged_and_resampled[:yres, :xres], decimal=4)
nrows, ncols = averaged_and_resampled.shape
# make sure they are the same after they are opened again
data_from_file = gdal.Open(self.old_prepifg_path).ReadAsArray()
self.assertTrue(os.path.exists(self.temp_tif))
new_from_file = gdal.Open(self.temp_tif).ReadAsArray()
np.testing.assert_array_almost_equal(data_from_file,
new_from_file)