def gamma_multiprocessing(unw_path, params):
"""
Gamma multiprocessing wrapper for geotif conversion.
:param unw_path: Wnwrapped interferogram path
:param params: Parameters dictionary corresponding to config file
:return xxxx
"""
dem_hdr_path = params[cf.DEM_HEADER_FILE]
slc_dir = params[cf.SLC_DIR]
mkdir_p(params[cf.OUT_DIR])
header_paths = gamma_task.get_header_paths(unw_path, slc_dir=slc_dir)
combined_headers = gamma.manage_headers(dem_hdr_path, header_paths)
dest = output_tiff_filename(unw_path, params[cf.OUT_DIR])
if os.path.basename(unw_path).split('.')[1] == \
(params[cf.APS_INCIDENCE_EXT] or params[cf.APS_ELEVATION_EXT]):
# TODO: implement incidence class here
combined_headers['FILE_TYPE'] = 'Incidence'
write_geotiff(combined_headers,
unw_path,
dest,
nodata=params[cf.NO_DATA_VALUE])
return dest
def setUp(self):
random_text = tempfile.mktemp()
self.confFile = os.path.join(TEMPDIR,
'{}/roipac_test.cfg'.format(random_text))
self.ifgListFile = os.path.join(
TEMPDIR, '{}/roipac_ifg.list'.format(random_text))
self.base_dir = os.path.dirname(self.confFile)
shared.mkdir_p(self.base_dir)
self.hdr = SML_TEST_DEM_HDR
def setUp(self):
self.base = join(PYRATEPATH, 'tests', 'test_data', 'gamma')
self.hdr = join(self.base, 'dem16x20raw.dem.par')
temp_text = tempfile.mktemp()
self.confFile = os.path.join(TEMPDIR,
'{}/gamma_test.cfg'.format(temp_text))
self.ifgListFile = os.path.join(TEMPDIR,
'{}/gamma_ifg.list'.format(temp_text))
self.base_dir = os.path.dirname(self.confFile)
shared.mkdir_p(self.base_dir)
def test_spatio_temporal_filter():
import tempfile
from pyrate import shared
from os.path import basename, join
from collections import OrderedDict
from pyrate.scripts import run_prepifg
from osgeo import gdal
from pyrate import ifgconstants as ifc
ifg_out = sio.loadmat(
os.path.join(SML_TEST_DIR, 'matlab_aps',
'ifg_spatio_temp_out.mat'))['ifg']
tsincr = sio.loadmat(
os.path.join(SML_TEST_DIR, 'matlab_aps', 'tsincr_svd.mat'))['tsincr']
params = cf.get_config_params(os.path.join(TEST_CONF_GAMMA))
params[cf.OUT_DIR] = tempfile.mkdtemp()
params[cf.TMPDIR] = join(params[cf.OUT_DIR], cf.TMPDIR)
shared.mkdir_p(params[cf.TMPDIR])
params[cf.SLPF_METHOD] = 2
params[cf.SLPF_CUTOFF] = 0
params[cf.SLPF_ORDER] = 1
params[cf.SLPF_NANFILL] = 0
params[cf.TLPF_METHOD] = 3
params[cf.TLPF_CUTOFF] = 0.25
params[cf.TLPF_PTHR] = 5
ifgs = small_data_setup()
_ = [ifgs_pk.pop(k) for k in ['gt', 'epochlist', 'md', 'wkt']]
preread_ifgs = {
join(params[cf.OUT_DIR], basename(k)): v
for k, v in ifgs_pk.items()
}
preread_ifgs = OrderedDict(sorted(preread_ifgs.items()))
run_prepifg.main(params)
for k, v in preread_ifgs.items():
v.path = join(params[cf.OUT_DIR], basename(k))
preread_ifgs[k] = v
ifg = ifgs[0]
ifg.x_size = xpsize
ifg.y_size = ypsize
spatio_temporal_filter(tsincr, ifg, params, preread_ifgs)
for i in ifgs:
i.close()
for (p, v), i in zip(preread_ifgs.items(), range(ifg_out.shape[2])):
ds = gdal.Open(p)
metadata = ds.GetMetadata()
assert ifc.PYRATE_APS_ERROR in metadata
assert metadata[ifc.PYRATE_APS_ERROR] == ifc.APS_REMOVED
arr = ds.GetRasterBand(1).ReadAsArray()
np.testing.assert_array_almost_equal(arr, ifg_out[:, :, i], decimal=3)
def setUpClass(cls):
luigi_dir = tempfile.mktemp()
non_luigi_dir = tempfile.mkdtemp()
cls.luigi_confFile = os.path.join(
TEMPDIR, '{}/gamma_test.conf'.format(luigi_dir))
cls.luigi_ifgListFile = os.path.join(
TEMPDIR, '{}/gamma_ifg.list'.format(luigi_dir))
cls.non_luigi_confFile = os.path.join(
TEMPDIR, '{}/gamma_test.conf'.format(non_luigi_dir))
cls.non_luigi_ifgListFile = os.path.join(
TEMPDIR, '{}/gamma_ifg.list'.format(non_luigi_dir))
cls.luigi_base_dir = os.path.dirname(cls.luigi_confFile)
cls.non_luigi_base_dir = os.path.dirname(cls.non_luigi_confFile)
shared.mkdir_p(cls.luigi_base_dir)
shared.mkdir_p(cls.non_luigi_base_dir)
def main(params=None):
"""
Main workflow function for preparing interferograms for PyRate.
:param dict params: Parameters dictionary read in from the config file
"""
# TODO: looks like base_ifg_paths are ordered according to ifg list
# This probably won't be a problem because input list won't be reordered
# and the original gamma generated list is ordered) this may not affect
# the important pyrate stuff anyway, but might affect gen_thumbs.py.
# Going to assume base_ifg_paths is ordered correcly
# pylint: disable=too-many-branches
usage = 'Usage: pyrate prepifg <config_file>'
if mpiops.size > 1: # Over-ride input options if this is an MPI job
params[cf.PARALLEL] = False
if params:
base_ifg_paths = cf.original_ifg_paths(params[cf.IFG_FILE_LIST])
else:
# if params not provided read from config file
if (not params) and (len(sys.argv) < 3):
print(usage)
return
base_ifg_paths, _, params = cf.get_ifg_paths(sys.argv[2])
base_ifg_paths.append(params[cf.DEM_FILE])
processor = params[cf.PROCESSOR] # roipac or gamma
if processor == GAMMA: # Incidence/elevation only supported for GAMMA
if params[cf.APS_INCIDENCE_MAP]:
base_ifg_paths.append(params[cf.APS_INCIDENCE_MAP])
if params[cf.APS_ELEVATION_MAP]:
base_ifg_paths.append(params[cf.APS_ELEVATION_MAP])
mkdir_p(params[cf.OUT_DIR]) # create output dir
process_base_ifgs_paths = np.array_split(base_ifg_paths,
mpiops.size)[mpiops.rank]
if processor == ROIPAC:
roipac_prepifg(process_base_ifgs_paths, params)
elif processor == GAMMA:
gamma_prepifg(process_base_ifgs_paths, params)
else:
raise prepifg.PreprocessError(
'Processor must be ROI_PAC (0) or GAMMA (1)')
log.info("Finished prepifg")
def setUpClass(cls):
cls.serial_dir = tempfile.mkdtemp()
cls.parallel_dir = tempfile.mkdtemp()
unw_paths = glob.glob(os.path.join(SML_TEST_GAMMA, "*_utm.unw"))
# read in the params
_, _, params = cf.get_ifg_paths(TEST_CONF_GAMMA)
params[cf.OUT_DIR] = cls.serial_dir
params[cf.PARALLEL] = False
shared.mkdir_p(cls.serial_dir)
run_prepifg.gamma_prepifg(unw_paths, params)
params[cf.OUT_DIR] = cls.parallel_dir
params[cf.PARALLEL] = True
shared.mkdir_p(cls.parallel_dir)
run_prepifg.gamma_prepifg(unw_paths, params)
def setUpClass(cls):
params = cf.get_config_params(TEST_CONF_ROIPAC)
cls.temp_out_dir = tempfile.mkdtemp()
sys.argv = ['run_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
run_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])
dest_paths = cf.get_dest_paths(base_ifg_paths, crop, params, xlks)
ifgs = common.pre_prepare_ifgs(dest_paths, params)
refx, refy = run_pyrate._ref_pixel_calc(dest_paths, params)
pyrate.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
_, cls.ifgs = rpe.estimate_ref_phase(ifgs, params, refx, refy)
r_dist = RDist(ifgs[0])()
# Calculate interferogram noise
cls.maxvar = [cvd(i, params, r_dist, calc_alpha=True,
save_acg=True, write_vals=True)[0] for i in ifgs]
cls.vcmt = get_vcmt(ifgs, cls.maxvar)
def setUpClass(cls):
params = cf.get_config_params(TEST_CONF_ROIPAC)
cls.temp_out_dir = tempfile.mkdtemp()
sys.argv = ['run_prepifg.py', TEST_CONF_ROIPAC]
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])
run_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])
dest_paths = cf.get_dest_paths(base_ifg_paths, crop, params, xlks)
# start run_pyrate copy
ifgs = pre_prepare_ifgs(dest_paths, params)
mst_grid = tests.common.mst_calculation(dest_paths, params)
refx, refy = run_pyrate._ref_pixel_calc(dest_paths, params)
# Estimate and remove orbit errors
pyrate.orbital.remove_orbital_error(ifgs, params)
ifgs = prepare_ifgs_without_phase(dest_paths, params)
_, ifgs = rpe.estimate_ref_phase(ifgs, params, refx, refy)
r_dist = vcm_module.RDist(ifgs[0])()
maxvar = [vcm_module.cvd(i, params, r_dist)[0] for i in ifgs]
vcmt = vcm_module.get_vcmt(ifgs, maxvar)
# 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)
matlab_linrate_dir = os.path.join(SML_TEST_DIR, 'matlab_linrate')
cls.rate_matlab = np.genfromtxt(os.path.join(matlab_linrate_dir,
'stackmap.csv'),
delimiter=',')
cls.error_matlab = np.genfromtxt(os.path.join(matlab_linrate_dir,
'errormap.csv'),
delimiter=',')
cls.samples_matlab = np.genfromtxt(os.path.join(
matlab_linrate_dir, 'coh_sta.csv'),
delimiter=',')