def test_output_datatype(self):
"""Test resampling method using a scaling factor of 4"""
scale = 4 # assumes square cells
self.ifgs.append(DEM(SML_TEST_DEM_TIF))
self.ifg_paths = [i.data_path for i in self.ifgs] + [SML_TEST_DEM_TIF]
self.headers.append(SML_TEST_DEM_HDR)
cext = self._custom_extents_tuple()
xlooks = ylooks = scale
prepare_ifgs(self.ifg_paths,
CUSTOM_CROP,
xlooks,
ylooks,
thresh=1.0,
user_exts=cext,
headers=self.headers)
for i in self.ifg_paths:
mlooked_ifg = mlooked_path(i, xlooks, CUSTOM_CROP)
ds1 = DEM(mlooked_ifg)
ds1.open()
ds2 = DEM(i)
ds2.open()
self.assertEqual(
ds1.dataset.GetRasterBand(1).DataType,
ds2.dataset.GetRasterBand(1).DataType)
ds1 = ds2 = None
def test_conv2tif_file_types(tempdir, gamma_conf):
tdir = Path(tempdir())
params = manipulate_test_conf(gamma_conf, tdir)
params[cf.COH_MASK] = 1
output_conf_file = 'conf.conf'
output_conf = tdir.joinpath(output_conf_file)
cf.write_config_file(params=params, output_conf_file=output_conf)
params_s = configuration.Configuration(output_conf).__dict__
conv2tif.main(params_s)
ifg_files = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_ifg.tif'))
coh_files = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_coh.tif'))
dem_file = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_dem.tif'))[0]
# assert coherence and ifgs have correct metadata
for i in itertools.chain(*[ifg_files, coh_files]):
ifg = Ifg(i)
ifg.open()
md = ifg.meta_data
if i.name.endswith('_ifg.tif'):
assert md[ifc.DATA_TYPE] == ifc.ORIG
continue
if i.name.endswith('_coh.tif'):
assert md[ifc.DATA_TYPE] == ifc.COH
continue
# assert dem has correct metadata
dem = DEM(dem_file.as_posix())
dem.open()
md = dem.dataset.GetMetadata()
assert md[ifc.DATA_TYPE] == ifc.DEM
shutil.rmtree(tdir)
def test_output_datatype(self):
"""Test resampling method using a scaling factor of 4"""
scale = 4 # assumes square cells
self.ifgs.append(DEM(SML_TEST_DEM_TIF))
ifg_paths = [i.data_path for i in self.ifgs]
data_types = [InputTypes.IFG] * len(self.ifg_paths)
ifg_paths.append(SML_TEST_DEM_TIF)
data_types.append(InputTypes.DEM)
self.headers.append(SML_TEST_DEM_HDR)
cext = self._custom_extents_tuple()
xlooks = ylooks = scale
prepare_ifgs(ifg_paths,
CUSTOM_CROP,
xlooks,
ylooks,
thresh=1.0,
user_exts=cext,
headers=self.headers,
params=self.params)
self.params[C.IFG_LKSX] = xlooks
self.params[C.IFG_LKSY] = ylooks
self.params[C.IFG_CROP_OPT] = CUSTOM_CROP
for i, t in zip(ifg_paths, data_types):
mlooked_ifg = mlooked_path(i, self.params, input_type=t)
ds1 = DEM(mlooked_ifg)
ds1.open()
ds2 = DEM(i)
ds2.open()
self.assertEqual(
ds1.dataset.GetRasterBand(1).DataType,
ds2.dataset.GetRasterBand(1).DataType)
ds1 = ds2 = None
def test_multilook(self):
"""Test resampling method using a scaling factor of 4"""
scale = 4 # assumes square cells
self.ifgs.append(DEM(SML_TEST_DEM_TIF))
self.ifg_paths = [i.data_path for i in self.ifgs]
# append the dem header
self.headers.append(SML_TEST_DEM_HDR)
cext = self._custom_extents_tuple()
xlooks = ylooks = scale
prepare_ifgs(self.ifg_paths,
CUSTOM_CROP,
xlooks,
ylooks,
thresh=1.0,
user_exts=cext,
headers=self.headers,
params=self.params)
for n, ipath in enumerate([self.exp_files[3], self.exp_files[7]]):
i = Ifg(ipath)
i.open()
self.assertEqual(i.dataset.RasterXSize, 20 / scale)
self.assertEqual(i.dataset.RasterYSize, 28 / scale)
# verify resampling
path = join(PREP_TEST_TIF,
"geo_%s.tif" % Path(ipath).name.split('_ifg')[0])
ds = gdal.Open(path)
src_data = ds.GetRasterBand(2).ReadAsArray()
exp_resample = multilooking(src_data, scale, scale, thresh=0)
self.assertEqual(exp_resample.shape, (7, 5))
assert_array_almost_equal(exp_resample, i.phase_band.ReadAsArray())
ds = None
i.close()
os.remove(ipath)
# verify DEM has been correctly processed
# ignore output values as resampling has already been tested for phase
exp_dem_path = join(self.params[C.GEOMETRY_DIR], 'dem.tif')
self.assertTrue(exists(exp_dem_path))
orignal_dem = DEM(SML_TEST_DEM_TIF)
orignal_dem.open()
dem_dtype = orignal_dem.dataset.GetRasterBand(1).DataType
orignal_dem.close()
dem = DEM(exp_dem_path)
dem.open()
# test multilooked dem is of the same datatype as the original dem tif
self.assertEqual(dem_dtype, dem.dataset.GetRasterBand(1).DataType)
self.assertEqual(dem.dataset.RasterXSize, 20 / scale)
self.assertEqual(dem.dataset.RasterYSize, 28 / scale)
data = dem.data
self.assertTrue(data.ptp() != 0)
# close ifgs
dem.close()
for i in self.ifgs:
i.close()
os.remove(exp_dem_path)
def gen_color_file(input_file):
fp, temp_file = tempfile.mkstemp(suffix='.txt')
dem = DEM(input_file)
dem.open()
phase_data = dem.height_band.ReadAsArray()
max_ph = np.nanmax(phase_data)
min_ph = np.nanmin(phase_data)
range_ph = max_ph - min_ph
colors = ['black', 'blue', 'yellow', 'orange', 'red', 'white']
with open(temp_file, 'w') as f:
for i, c in enumerate(colors[:-1]):
f.write(
str(int(min_ph + (i + 1) * range_ph / len(colors))) + ' ' + c +
'\n')
f.write(
str(int(max_ph - range_ph / len(colors))) + ' ' + colors[-1] +
'\n')
os.close(fp)
return temp_file
class TestDEMTests:
'Unit tests to verify operations on GeoTIFF format DEMs'
def setup_method(self):
self.ras = DEM(SML_TEST_DEM_TIF)
def test_create_raster(self):
# validate header path
assert os.path.exists(self.ras.data_path)
def test_headers_as_attr(self):
self.ras.open()
attrs = ['ncols', 'nrows', 'x_first', 'x_step', 'y_first', 'y_step']
# TODO: are 'projection' and 'datum' attrs needed?
for a in attrs:
assert getattr(self.ras, a) is not None
def test_is_dem(self):
self.ras = DEM(join(SML_TEST_TIF, 'geo_060619-061002_unw.tif'))
assert ~hasattr(self.ras, 'datum')
def test_open(self):
assert self.ras.dataset is None
self.ras.open()
assert self.ras.dataset is not None
assert isinstance(self.ras.dataset, Dataset)
# ensure open cannot be called twice
with pytest.raises(RasterException):
self.ras.open()
def test_band_fails_with_unopened_raster(self):
# test accessing bands with open and unopened datasets
with pytest.raises(RasterException):
self.ras.height_band
def test_band_read_with_open_raster(self):
self.ras.open()
data = self.ras.height_band.ReadAsArray()
assert data.shape == (72, 47)
class DEMTests(unittest.TestCase):
'Unit tests to verify operations on GeoTIFF format DEMs'
def setUp(self):
self.ras = DEM(SML_TEST_DEM_TIF)
def test_create_raster(self):
# validate header path
self.assertTrue(os.path.exists(self.ras.data_path))
def test_headers_as_attr(self):
self.ras.open()
attrs = ['ncols', 'nrows', 'x_first', 'x_step', 'y_first', 'y_step']
# TODO: are 'projection' and 'datum' attrs needed?
for a in attrs:
self.assertTrue(getattr(self.ras, a) is not None)
def test_is_dem(self):
self.ras = DEM(join(SML_TEST_TIF, 'geo_060619-061002_unw.tif'))
self.assertFalse(hasattr(self.ras, 'datum'))
def test_open(self):
self.assertTrue(self.ras.dataset is None)
self.ras.open()
self.assertTrue(self.ras.dataset is not None)
self.assertTrue(isinstance(self.ras.dataset, Dataset))
# ensure open cannot be called twice
self.assertRaises(RasterException, self.ras.open)
def test_band(self):
# test accessing bands with open and unopened datasets
try:
_ = self.ras.height_band
self.fail("Should not be able to access band without open dataset")
except RasterException:
pass
self.ras.open()
data = self.ras.height_band.ReadAsArray()
self.assertEqual(data.shape, (72, 47))
def test_prepifg_file_types(tempdir, gamma_conf, coh_mask):
tdir = Path(tempdir())
params = manipulate_test_conf(gamma_conf, tdir)
params[cf.COH_MASK] = coh_mask
params[cf.PARALLEL] = 0
output_conf_file = 'conf.conf'
output_conf = tdir.joinpath(output_conf_file)
cf.write_config_file(params=params, output_conf_file=output_conf)
params_s = Configuration(output_conf).__dict__
conv2tif.main(params_s)
# reread params from config
params_s = Configuration(output_conf).__dict__
prepifg.main(params_s)
ifg_files = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_ifg.tif'))
assert len(ifg_files) == 17
mlooked_files = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_ifg_1rlks_1cr.tif'))
assert len(mlooked_files) == 17
coh_files = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_cc_coh.tif'))
mlooked_coh_files = list(
Path(tdir.joinpath(
params_s[cf.OUT_DIR])).glob('*_cc_coh_1rlks_1cr.tif'))
if coh_mask:
assert len(coh_files) == 17
assert len(mlooked_coh_files) == 17
dem_file = list(
Path(tdir.joinpath(params_s[cf.OUT_DIR])).glob('*_dem.tif'))[0]
mlooked_dem_file = list(
Path(tdir.joinpath(
params_s[cf.OUT_DIR])).glob('*_dem_1rlks_1cr.tif'))[0]
import itertools
# assert coherence and ifgs have correct metadata
for i in itertools.chain(
*[ifg_files, mlooked_files, coh_files, mlooked_coh_files]):
ifg = Ifg(i)
ifg.open()
md = ifg.meta_data
if i.name.endswith('_ifg.tif'):
assert md[ifc.DATA_TYPE] == ifc.ORIG
continue
if i.name.endswith('_coh.tif'):
assert md[ifc.DATA_TYPE] == ifc.COH
continue
if i.name.endswith('_cc_coh_1rlks_1cr.tif'):
assert md[ifc.DATA_TYPE] == ifc.MULTILOOKED_COH
continue
if i.name.endswith('_ifg_1rlks_1cr.tif'):
if coh_mask:
assert md[ifc.DATA_TYPE] == ifc.COHERENCE
else:
assert md[ifc.DATA_TYPE] == ifc.MULTILOOKED
continue
# assert dem has correct metadata
dem = DEM(dem_file.as_posix())
dem.open()
md = dem.dataset.GetMetadata()
assert md[ifc.DATA_TYPE] == ifc.DEM
dem = DEM(mlooked_dem_file.as_posix())
dem.open()
md = dem.dataset.GetMetadata()
assert md[ifc.DATA_TYPE] == ifc.MLOOKED_DEM
shutil.rmtree(tdir)
def test_prepifg_file_types(tempdir, gamma_conf, coh_mask):
tdir = Path(tempdir())
params = manipulate_test_conf(gamma_conf, tdir)
params[C.COH_MASK] = coh_mask
params[C.PARALLEL] = 0
output_conf_file = 'conf.conf'
output_conf = tdir.joinpath(output_conf_file)
pyrate.configuration.write_config_file(params=params,
output_conf_file=output_conf)
params_s = Configuration(output_conf).__dict__
conv2tif.main(params_s)
# reread params from config
params_s = Configuration(output_conf).__dict__
prepifg.main(params_s)
ifg_files = list(
Path(tdir.joinpath(params_s[C.INTERFEROGRAM_DIR])).glob('*_unw.tif'))
assert len(ifg_files) == 17
mlooked_files = list(
Path(tdir.joinpath(params_s[C.INTERFEROGRAM_DIR])).glob('*_ifg.tif'))
assert len(mlooked_files) == 17
coh_files = list(
Path(tdir.joinpath(params_s[C.COHERENCE_DIR])).glob('*_cc.tif'))
mlooked_coh_files = list(
Path(tdir.joinpath(params_s[C.COHERENCE_DIR])).glob('*_coh.tif'))
if coh_mask:
assert len(coh_files) == 17
assert len(mlooked_coh_files) == 17
dem_file = list(
Path(tdir.joinpath(params_s[C.GEOMETRY_DIR])).glob('*_dem.tif'))[0]
mlooked_dem_file = list(
Path(tdir.joinpath(params_s[C.GEOMETRY_DIR])).glob('dem.tif'))[0]
import itertools
# assert coherence and ifgs have correct metadata
for i in itertools.chain(
*[ifg_files, mlooked_files, coh_files, mlooked_coh_files]):
ifg = Ifg(i)
ifg.open()
md = ifg.meta_data
if i.name.endswith('_unw.tif'):
assert md[ifc.DATA_TYPE] == ifc.ORIG
assert ifc.IFG_LKSX not in md
assert ifc.IFG_LKSY not in md
assert ifc.IFG_CROP not in md
continue
if i.name.endswith('_cc.tif'):
assert md[ifc.DATA_TYPE] == ifc.COH
assert ifc.IFG_LKSX not in md
assert ifc.IFG_LKSY not in md
assert ifc.IFG_CROP not in md
continue
if i.name.endswith('_coh.tif'):
assert md[ifc.DATA_TYPE] == ifc.MULTILOOKED_COH
assert md[ifc.IFG_LKSX] == '1'
assert md[ifc.IFG_LKSY] == '1'
assert md[ifc.IFG_CROP] == '1'
continue
if i.name.endswith('_ifg.tif'):
if coh_mask:
assert md[ifc.DATA_TYPE] == ifc.MLOOKED_COH_MASKED_IFG
assert md[ifc.IFG_LKSX] == '1'
assert md[ifc.IFG_LKSY] == '1'
assert md[ifc.IFG_CROP] == '1'
else:
assert md[ifc.DATA_TYPE] == ifc.MULTILOOKED
assert md[ifc.IFG_LKSX] == '1'
assert md[ifc.IFG_LKSY] == '1'
assert md[ifc.IFG_CROP] == '1'
continue
# assert dem has correct metadata
dem = DEM(dem_file.as_posix())
dem.open()
md = dem.dataset.GetMetadata()
assert md[ifc.DATA_TYPE] == ifc.DEM
assert ifc.IFG_LKSX not in md
assert ifc.IFG_LKSY not in md
assert ifc.IFG_CROP not in md
dem = DEM(mlooked_dem_file.as_posix())
dem.open()
md = dem.dataset.GetMetadata()
assert md[ifc.DATA_TYPE] == ifc.MLOOKED_DEM
assert ifc.IFG_LKSX in md
assert ifc.IFG_LKSY in md
assert ifc.IFG_CROP in md
shutil.rmtree(tdir)