def test_covariance_17ifgs(self):
# After raw data import
# (no reference pixel correction and units in radians)
exp_maxvar = [5.6149, 8.7710, 2.9373, 0.3114, 12.9931, 2.0459, 0.4236,
2.1243, 0.4745, 0.6725, 0.8333, 3.8232, 3.3052, 2.4925,
16.0159, 2.8025, 1.4345]
exp_alpha = [0.0356, 0.1601, 0.5128, 0.5736, 0.0691, 0.1337, 0.2333,
0.3202, 1.2338, 0.4273, 0.9024, 0.1280, 0.3585, 0.1599,
0.0110, 0.1287, 0.0676]
act_maxvar = []
act_alpha = []
for i in self.ifgs:
if bool((i.phase_data == 0).all()) is True:
raise Exception("All zero")
maxvar, alpha = cvd(i, self.params, self.r_dist, calc_alpha=True)
self.assertTrue(maxvar is not None)
self.assertTrue(alpha is not None)
act_maxvar.append(maxvar)
act_alpha.append(alpha)
assert_array_almost_equal(act_maxvar, exp_maxvar, decimal=3)
# This test fails for greater than 1 decimal place.
# Discrepancies observed in distance calculations.
assert_array_almost_equal(act_alpha, exp_alpha, decimal=1)
def setUpClass(cls):
params = Configuration(TEST_CONF_ROIPAC).__dict__
cls.temp_out_dir = tempfile.mkdtemp()
sys.argv = ['prepifg.py', TEST_CONF_ROIPAC]
params[cf.OUT_DIR] = cls.temp_out_dir
params[cf.TMPDIR] = os.path.join(cls.temp_out_dir, cf.TMPDIR)
shared.mkdir_p(params[cf.TMPDIR])
params[cf.REF_EST_METHOD] = 2
conv2tif.main(params)
prepifg.main(params)
cls.params = params
xlks, ylks, crop = cf.transform_params(params)
base_ifg_paths = cf.original_ifg_paths(params[cf.IFG_FILE_LIST],
params[cf.OBS_DIR])
dest_paths = cf.get_dest_paths(base_ifg_paths, crop, params, xlks)
ifgs = common.pre_prepare_ifgs(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, cls.ifgs = process._ref_phase_estimation(dest_paths, params, refx, refy)
ifgs[0].open()
r_dist = RDist(ifgs[0])()
ifgs[0].close()
# Calculate interferogram noise
cls.maxvar = [cvd(i, params, r_dist, calc_alpha=True,
save_acg=True, write_vals=True)[0] for i in dest_paths]
cls.vcmt = get_vcmt(ifgs, cls.maxvar)
for ifg in ifgs:
ifg.close()
def setUpClass(cls):
params = Configuration(common.TEST_CONF_ROIPAC).__dict__
cls.temp_out_dir = tempfile.mkdtemp()
sys.argv = ['prepifg.py', common.TEST_CONF_ROIPAC]
params[cf.OUT_DIR] = cls.temp_out_dir
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
xlks, ylks, crop = cf.transform_params(params)
base_ifg_paths = cf.original_ifg_paths(params[cf.IFG_FILE_LIST],
params[cf.OBS_DIR])
dest_paths = cf.get_dest_paths(base_ifg_paths, crop, params, xlks)
# start run_pyrate copy
ifgs = common.pre_prepare_ifgs(dest_paths, params)
mst_grid = common.mst_calculation(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = common.prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, ifgs = process._ref_phase_estimation(dest_paths, params, refx, refy)
ifgs[0].open()
r_dist = covariance.RDist(ifgs[0])()
ifgs[0].close()
maxvar = [covariance.cvd(i, params, r_dist)[0] for i in dest_paths]
for ifg in ifgs:
ifg.open()
vcmt = covariance.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
ifg.nodata_value = 0.0
params[cf.TIME_SERIES_METHOD] = 1
params[cf.PARALLEL] = 0
# Calculate time series
cls.tsincr_0, cls.tscum_0, _ = common.calculate_time_series(
ifgs, params, vcmt, mst=mst_grid)
params[cf.PARALLEL] = 1
cls.tsincr_1, cls.tscum_1, cls.tsvel_1 = common.calculate_time_series(
ifgs, params, vcmt, mst=mst_grid)
# load the legacy data
ts_dir = os.path.join(common.SML_TEST_DIR, 'time_series')
tsincr_path = os.path.join(ts_dir, 'ts_incr_interp0_method1.csv')
ts_incr = np.genfromtxt(tsincr_path)
tscum_path = os.path.join(ts_dir, 'ts_cum_interp0_method1.csv')
ts_cum = np.genfromtxt(tscum_path)
cls.ts_incr = np.reshape(ts_incr,
newshape=cls.tsincr_0.shape,
order='F')
cls.ts_cum = np.reshape(ts_cum, newshape=cls.tscum_0.shape, order='F')
def setup_class(cls):
params = Configuration(common.TEST_CONF_ROIPAC).__dict__
params[cf.TEMP_MLOOKED_DIR] = os.path.join(params[cf.OUT_DIR], cf.TEMP_MLOOKED_DIR)
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
xlks, _, crop = cf.transform_params(params)
dest_paths, headers = common.repair_params_for_correct_tests(params[cf.OUT_DIR], params)
correct._copy_mlooked(params)
copied_dest_paths = [os.path.join(params[cf.TEMP_MLOOKED_DIR], os.path.basename(d)) for d in dest_paths]
del dest_paths
# start run_pyrate copy
ifgs = pre_prepare_ifgs(copied_dest_paths, params)
mst_grid = tests.common.mst_calculation(copied_dest_paths, params)
refx, refy = pyrate.core.refpixel.ref_pixel_calc_wrapper(params)
params[cf.REFX] = refx
params[cf.REFY] = refy
params[cf.ORBFIT_OFFSET] = True
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(copied_dest_paths, params)
for ifg in ifgs:
ifg.close()
correct._update_params_with_tiles(params)
_, ifgs = pyrate.core.ref_phs_est.ref_phase_est_wrapper(params)
ifgs[0].open()
r_dist = vcm_module.RDist(ifgs[0])()
ifgs[0].close()
maxvar = [vcm_module.cvd(i, params, r_dist)[0] for i in copied_dest_paths]
for ifg in ifgs:
ifg.open()
vcmt = vcm_module.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
# Calculate stacked rate map
params[cf.PARALLEL] = 1
cls.rate, cls.error, cls.samples = tests.common.calculate_stack_rate(ifgs, params, vcmt, mst_mat=mst_grid)
# Calculate stacked rate map
params[cf.PARALLEL] = 0
cls.rate_s, cls.error_s, cls.samples_s = tests.common.calculate_stack_rate(ifgs, params, vcmt, mst_mat=mst_grid)
stackrate_dir = os.path.join(SML_TEST_DIR, 'stackrate')
cls.rate_container = np.genfromtxt(os.path.join(stackrate_dir, 'stackmap.csv'), delimiter=',')
cls.error_container = np.genfromtxt(os.path.join(stackrate_dir, 'errormap.csv'), delimiter=',')
cls.samples_container = np.genfromtxt(os.path.join(stackrate_dir, 'coh_sta.csv'), delimiter=',')
for ifg in ifgs:
ifg.close()
cls.params = params
def test_covariance_basic(self):
for i in small5_ifg_paths():
maxvar, alpha = cvd(i, self.params, self.r_dist, calc_alpha=True)
assert maxvar is not None
assert alpha is not None
print("maxvar: %s, alpha: %s" % (maxvar, alpha))
def setUpClass(cls):
cls.ifgs = common.small_data_setup()
cls.params = default_params()
cls.mstmat = mst.mst_boolean_array(cls.ifgs)
r_dist = covariance.RDist(cls.ifgs[0])()
cls.maxvar = [covariance.cvd(i, cls.params, r_dist)[0]
for i in cls.ifgs]
cls.vcmt = covariance.get_vcmt(cls.ifgs, cls.maxvar)
def setup_class(cls):
roipac_params = Configuration(TEST_CONF_ROIPAC).__dict__
from copy import deepcopy
params = deepcopy(roipac_params)
shared.mkdir_p(params[C.TMPDIR])
params[C.REF_EST_METHOD] = 2
conv2tif.main(params)
params = deepcopy(roipac_params)
prepifg.main(params)
params = deepcopy(roipac_params)
base_ifg_paths = [
c.unwrapped_path for c in params[C.INTERFEROGRAM_FILES]
]
dest_paths = [c.converted_path for c in params[C.INTERFEROGRAM_FILES]]
params[C.INTERFEROGRAM_FILES] = [
MultiplePaths(d, params) for d in dest_paths
]
for p in params[C.INTERFEROGRAM_FILES]: # hack
p.sampled_path = p.converted_path
for i in dest_paths:
Path(i).chmod(
0o664
) # assign write permission as conv2tif output is readonly
ifgs = common.pre_prepare_ifgs(dest_paths, params)
correct._copy_mlooked(params)
correct._update_params_with_tiles(params)
correct._create_ifg_dict(params)
pyrate.core.refpixel.ref_pixel_calc_wrapper(params)
params[C.ORBFIT_OFFSET] = True
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
for p in params[C.INTERFEROGRAM_FILES]: # hack
p.tmp_sampled_path = p.sampled_path
_, cls.ifgs = pyrate.core.ref_phs_est.ref_phase_est_wrapper(params)
ifgs[0].open()
r_dist = RDist(ifgs[0])()
ifgs[0].close()
# Calculate interferogram noise
cls.maxvar = [
cvd(i,
params,
r_dist,
calc_alpha=True,
save_acg=True,
write_vals=True)[0] for i in dest_paths
]
cls.vcmt = get_vcmt(ifgs, cls.maxvar)
for ifg in ifgs:
ifg.close()
cls.params = params
def test_covariance_basic(self):
ifgs = small5_ifgs()
for i in ifgs:
i.open()
if bool((i.phase_data == 0).all()) is True:
raise Exception("All zero")
maxvar, alpha = cvd(i, self.params, self.r_dist, calc_alpha=True)
self.assertTrue(maxvar is not None)
self.assertTrue(alpha is not None)
print("maxvar: %s, alpha: %s" % (maxvar, alpha))
def _maxvar_vcm_calc(ifg_paths, params, preread_ifgs):
"""
MPI wrapper for maxvar and vcmt computation
"""
log.info('Calculating the temporal variance-covariance matrix')
process_indices = mpiops.array_split(range(len(ifg_paths)))
def _get_r_dist(ifg_path):
"""
Get RDIst class object
"""
ifg = Ifg(ifg_path)
ifg.open()
r_dist = vcm_module.RDist(ifg)()
ifg.close()
return r_dist
r_dist = mpiops.run_once(_get_r_dist, ifg_paths[0])
prcs_ifgs = mpiops.array_split(ifg_paths)
process_maxvar = []
for n, i in enumerate(prcs_ifgs):
log.debug(
'Calculating maxvar for {} of process ifgs {} of total {}'.format(
n + 1, len(prcs_ifgs), len(ifg_paths)))
process_maxvar.append(
vcm_module.cvd(i,
params,
r_dist,
calc_alpha=True,
write_vals=True,
save_acg=True)[0])
if mpiops.rank == MASTER_PROCESS:
maxvar = np.empty(len(ifg_paths), dtype=np.float64)
maxvar[process_indices] = process_maxvar
for i in range(1, mpiops.size): # pragma: no cover
rank_indices = mpiops.array_split(range(len(ifg_paths)), i)
this_process_ref_phs = np.empty(len(rank_indices),
dtype=np.float64)
mpiops.comm.Recv(this_process_ref_phs, source=i, tag=i)
maxvar[rank_indices] = this_process_ref_phs
else: # pragma: no cover
maxvar = np.empty(len(ifg_paths), dtype=np.float64)
mpiops.comm.Send(np.array(process_maxvar, dtype=np.float64),
dest=MASTER_PROCESS,
tag=mpiops.rank)
mpiops.comm.barrier()
maxvar = mpiops.comm.bcast(maxvar, root=0)
vcmt = mpiops.run_once(vcm_module.get_vcmt, preread_ifgs, maxvar)
log.debug("Finished maxvar and vcm calc!")
return maxvar, vcmt
def setUpClass(cls):
params = Configuration(TEST_CONF_ROIPAC).__dict__
cls.temp_out_dir = tempfile.mkdtemp()
sys.argv = ['prepifg.py', TEST_CONF_ROIPAC]
params[cf.OUT_DIR] = cls.temp_out_dir
params[cf.TMPDIR] = os.path.join(cls.temp_out_dir, cf.TMPDIR)
shared.mkdir_p(params[cf.TMPDIR])
params[cf.REF_EST_METHOD] = 2
conv2tif.main(params)
prepifg.main(params)
cls.params = params
base_ifg_paths = [
c.unwrapped_path for c in params[cf.INTERFEROGRAM_FILES]
]
dest_paths = [c.converted_path for c in params[cf.INTERFEROGRAM_FILES]]
dest_paths = dest_paths[:-2]
for i in dest_paths:
Path(i).chmod(
0o664
) # assign write permission as conv2tif output is readonly
ifgs = common.pre_prepare_ifgs(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
headers = [roipac.roipac_header(i, cls.params) for i in base_ifg_paths]
pyrate.core.orbital.remove_orbital_error(ifgs, params, headers)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, cls.ifgs = process._ref_phase_estimation(dest_paths, params, refx,
refy)
ifgs[0].open()
r_dist = RDist(ifgs[0])()
ifgs[0].close()
# Calculate interferogram noise
cls.maxvar = [
cvd(i,
params,
r_dist,
calc_alpha=True,
save_acg=True,
write_vals=True)[0] for i in dest_paths
]
cls.vcmt = get_vcmt(ifgs, cls.maxvar)
for ifg in ifgs:
ifg.close()
def test_covariance_17ifgs(self):
# After raw data import
# (no reference pixel correction and units in radians)
exp_maxvar = [
5.6149, 8.7710, 2.9373, 0.3114, 12.9931, 2.0459, 0.4236, 2.1243,
0.4745, 0.6725, 0.8333, 3.8232, 3.3052, 2.4925, 16.0159, 2.8025,
1.4345
]
exp_alpha = [
0.0356, 0.1601, 0.5128, 0.5736, 0.0691, 0.1337, 0.2333, 0.3202,
1.2338, 0.4273, 0.9024, 0.1280, 0.3585, 0.1599, 0.0110, 0.1287,
0.0676
]
act_maxvar = []
act_alpha = []
for i in self.ifgs:
maxvar, alpha = cvd(i.data_path,
self.params,
self.r_dist,
calc_alpha=True)
assert maxvar is not None
assert alpha is not None
act_maxvar.append(maxvar /
20.02) # rough conversion factor back to radians
act_alpha.append(alpha)
# below tests fails at 3 d.p. on account of above conversion factor not being accurate enough
assert_array_almost_equal(act_maxvar, exp_maxvar, decimal=2)
# This test fails for greater than 1 decimal place.
# Discrepancies observed in distance calculations.
assert_array_almost_equal(act_alpha, exp_alpha, decimal=1)
def setUpClass(cls):
params = Configuration(common.TEST_CONF_ROIPAC).__dict__
cls.temp_out_dir = tempfile.mkdtemp()
params[cf.OUT_DIR] = cls.temp_out_dir
params[cf.PARALLEL] = 0
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
base_ifg_paths = [
c.unwrapped_path for c in params[cf.INTERFEROGRAM_FILES]
]
headers = [roipac.roipac_header(i, params) for i in base_ifg_paths]
dest_paths = [
Path(cls.temp_out_dir).joinpath(Path(
c.sampled_path).name).as_posix()
for c in params[cf.INTERFEROGRAM_FILES][:-2]
]
# start run_pyrate copy
ifgs = common.pre_prepare_ifgs(dest_paths, params)
mst_grid = common.mst_calculation(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params, headers)
ifgs = common.prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, ifgs = process._ref_phase_estimation(dest_paths, params, refx, refy)
ifgs[0].open()
r_dist = covariance.RDist(ifgs[0])()
ifgs[0].close()
# Calculate interferogram noise
maxvar = [covariance.cvd(i, params, r_dist)[0] for i in dest_paths]
for ifg in ifgs:
ifg.open()
vcmt = covariance.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
ifg.nodata_value = 0.0
params[cf.TIME_SERIES_METHOD] = 2
params[cf.PARALLEL] = 1
# Calculate time series
cls.tsincr, cls.tscum, _ = common.calculate_time_series(ifgs,
params,
vcmt,
mst=mst_grid)
params[cf.PARALLEL] = 0
# Calculate time series serailly by the pixel
cls.tsincr_0, cls.tscum_0, _ = common.calculate_time_series(
ifgs, params, vcmt, mst=mst_grid)
# copy legacy data
SML_TIME_SERIES_DIR = os.path.join(common.SML_TEST_DIR, 'time_series')
tsincr_path = os.path.join(SML_TIME_SERIES_DIR,
'ts_incr_interp0_method2.csv')
ts_incr = np.genfromtxt(tsincr_path)
tscum_path = os.path.join(SML_TIME_SERIES_DIR,
'ts_cum_interp0_method2.csv')
ts_cum = np.genfromtxt(tscum_path)
cls.ts_incr = np.reshape(ts_incr,
newshape=cls.tsincr_0.shape,
order='F')
cls.ts_cum = np.reshape(ts_cum, newshape=cls.tscum_0.shape, order='F')
def setup_class(cls):
params = Configuration(common.TEST_CONF_ROIPAC).__dict__
params[cf.TEMP_MLOOKED_DIR] = os.path.join(params[cf.OUT_DIR],
cf.TEMP_MLOOKED_DIR)
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
xlks, _, crop = cf.transform_params(params)
dest_paths, headers = common.repair_params_for_correct_tests(
params[cf.OUT_DIR], params)
correct._copy_mlooked(params)
copied_dest_paths = [
os.path.join(params[cf.TEMP_MLOOKED_DIR], os.path.basename(d))
for d in dest_paths
]
del dest_paths
# start run_pyrate copy
ifgs = common.pre_prepare_ifgs(copied_dest_paths, params)
mst_grid = common.mst_calculation(copied_dest_paths, params)
refx, refy = pyrate.core.refpixel.ref_pixel_calc_wrapper(params)
params[cf.REFX] = refx
params[cf.REFY] = refy
params[cf.ORBFIT_OFFSET] = True
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = common.prepare_ifgs_without_phase(copied_dest_paths, params)
for ifg in ifgs:
ifg.close()
correct._update_params_with_tiles(params)
_, ifgs = pyrate.core.ref_phs_est.ref_phase_est_wrapper(params)
ifgs[0].open()
r_dist = covariance.RDist(ifgs[0])()
ifgs[0].close()
# Calculate interferogram noise
maxvar = [
covariance.cvd(i, params, r_dist)[0] for i in copied_dest_paths
]
for ifg in ifgs:
ifg.open()
vcmt = covariance.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
ifg.nodata_value = 0.0
params[cf.TIME_SERIES_METHOD] = 2
params[cf.PARALLEL] = 1
# Calculate time series
cls.tsincr, cls.tscum, _ = common.calculate_time_series(ifgs,
params,
vcmt,
mst=mst_grid)
params[cf.PARALLEL] = 0
# Calculate time series serailly by the pixel
cls.tsincr_0, cls.tscum_0, _ = common.calculate_time_series(
ifgs, params, vcmt, mst=mst_grid)
# copy legacy data
SML_TIME_SERIES_DIR = os.path.join(common.SML_TEST_DIR, 'time_series')
tsincr_path = os.path.join(SML_TIME_SERIES_DIR,
'ts_incr_interp0_method2.csv')
ts_incr = np.genfromtxt(tsincr_path)
tscum_path = os.path.join(SML_TIME_SERIES_DIR,
'ts_cum_interp0_method2.csv')
ts_cum = np.genfromtxt(tscum_path)
cls.ts_incr = np.reshape(ts_incr,
newshape=cls.tsincr_0.shape,
order='F')
cls.ts_cum = np.reshape(ts_cum, newshape=cls.tscum_0.shape, order='F')
cls.params = params
def setUpClass(cls):
params = cf.get_config_params(TEST_CONF_ROIPAC)
cls.temp_out_dir = tempfile.mkdtemp()
params[cf.OUT_DIR] = cls.temp_out_dir
params[cf.TMPDIR] = os.path.join(params[cf.OUT_DIR], cf.TMPDIR)
shared.mkdir_p(params[cf.TMPDIR])
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
xlks, _, crop = cf.transform_params(params)
base_ifg_paths = cf.original_ifg_paths(params[cf.IFG_FILE_LIST],
params[cf.OBS_DIR])
dest_paths = cf.get_dest_paths(base_ifg_paths, crop, params, xlks)
print(f"base_ifg_paths={base_ifg_paths}")
print(f"dest_paths={dest_paths}")
# start run_pyrate copy
ifgs = pre_prepare_ifgs(dest_paths, params)
mst_grid = tests.common.mst_calculation(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, ifgs = process._ref_phase_estimation(dest_paths, params, refx, refy)
ifgs[0].open()
r_dist = vcm_module.RDist(ifgs[0])()
ifgs[0].close()
maxvar = [vcm_module.cvd(i, params, r_dist)[0] for i in dest_paths]
for ifg in ifgs:
ifg.open()
vcmt = vcm_module.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
# Calculate linear rate map
params[cf.PARALLEL] = 1
cls.rate, cls.error, cls.samples = tests.common.calculate_linear_rate(
ifgs, params, vcmt, mst_mat=mst_grid)
params[cf.PARALLEL] = 2
cls.rate_2, cls.error_2, cls.samples_2 = \
tests.common.calculate_linear_rate(ifgs, params, vcmt,
mst_mat=mst_grid)
params[cf.PARALLEL] = 0
# Calculate linear rate map
cls.rate_s, cls.error_s, cls.samples_s = \
tests.common.calculate_linear_rate(ifgs, params, vcmt,
mst_mat=mst_grid)
linrate_dir = os.path.join(SML_TEST_DIR, 'linrate')
cls.rate_container = np.genfromtxt(os.path.join(
linrate_dir, 'stackmap.csv'),
delimiter=',')
cls.error_container = np.genfromtxt(os.path.join(
linrate_dir, 'errormap.csv'),
delimiter=',')
cls.samples_container = np.genfromtxt(os.path.join(
linrate_dir, 'coh_sta.csv'),
delimiter=',')
for ifg in ifgs:
ifg.close()
def setUpClass(cls):
params = Configuration(TEST_CONF_ROIPAC).__dict__
cls.temp_out_dir = tempfile.mkdtemp()
params[cf.OUT_DIR] = cls.temp_out_dir
params[cf.TMPDIR] = os.path.join(params[cf.OUT_DIR], cf.TMPDIR)
shared.mkdir_p(params[cf.TMPDIR])
conv2tif.main(params)
prepifg.main(params)
params[cf.REF_EST_METHOD] = 2
xlks, _, crop = cf.transform_params(params)
base_ifg_paths = [
c.unwrapped_path for c in params[cf.INTERFEROGRAM_FILES]
]
headers = [roipac.roipac_header(i, params) for i in base_ifg_paths]
dest_paths = [
Path(cls.temp_out_dir).joinpath(Path(
c.sampled_path).name).as_posix()
for c in params[cf.INTERFEROGRAM_FILES][:-2]
]
# start run_pyrate copy
ifgs = pre_prepare_ifgs(dest_paths, params)
mst_grid = tests.common.mst_calculation(dest_paths, params)
refx, refy = process._ref_pixel_calc(dest_paths, params)
# Estimate and remove orbit errors
pyrate.core.orbital.remove_orbital_error(ifgs, params, headers)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
for ifg in ifgs:
ifg.close()
_, ifgs = process._ref_phase_estimation(dest_paths, params, refx, refy)
ifgs[0].open()
r_dist = vcm_module.RDist(ifgs[0])()
ifgs[0].close()
maxvar = [vcm_module.cvd(i, params, r_dist)[0] for i in dest_paths]
for ifg in ifgs:
ifg.open()
vcmt = vcm_module.get_vcmt(ifgs, maxvar)
for ifg in ifgs:
ifg.close()
ifg.open()
# Calculate stacked rate map
params[cf.PARALLEL] = 1
cls.rate, cls.error, cls.samples = tests.common.calculate_stack_rate(
ifgs, params, vcmt, mst_mat=mst_grid)
# Calculate stacked rate map
params[cf.PARALLEL] = 0
cls.rate_s, cls.error_s, cls.samples_s = tests.common.calculate_stack_rate(
ifgs, params, vcmt, mst_mat=mst_grid)
stackrate_dir = os.path.join(SML_TEST_DIR, 'stackrate')
cls.rate_container = np.genfromtxt(os.path.join(
stackrate_dir, 'stackmap.csv'),
delimiter=',')
cls.error_container = np.genfromtxt(os.path.join(
stackrate_dir, 'errormap.csv'),
delimiter=',')
cls.samples_container = np.genfromtxt(os.path.join(
stackrate_dir, 'coh_sta.csv'),
delimiter=',')
for ifg in ifgs:
ifg.close()
