def __get_files_from_attr(self, attr, input_type=InputTypes.IFG):
val = self.__getattribute__(attr)
files = parse_namelist(val)
return [
MultiplePaths(p, self.__dict__, input_type=input_type)
for p in files
]
def test_get_epochs(self):
def str2date(s):
segs = s[:4], s[4:6], s[6:] # year, month, day
return date(*[int(sg) for sg in segs])
raw_date = [
'20060619', '20060828', '20061002', '20061106', '20061211',
'20070115', '20070219', '20070326', '20070430', '20070604',
'20070709', '20070813', '20070917'
]
exp_dates = [str2date(d) for d in raw_date]
exp_repeat = [1, 1, 3, 3, 4, 3, 3, 3, 3, 3, 3, 2, 2]
exp_spans = [
0, 0.1916, 0.2875, 0.3833, 0.4791, 0.5749, 0.6708, 0.7666, 0.8624,
0.9582, 1.0541, 1.1499, 1.2457
]
ifms = join(SML_TEST_TIF, "ifms_17")
ifgs = [Ifg(join(SML_TEST_TIF, p)) for p in parse_namelist(ifms)]
for i in ifgs:
i.open()
epochs = get_epochs(ifgs)[0]
self.assertTrue((exp_dates == epochs.dates).all())
self.assertTrue((exp_repeat == epochs.repeat).all())
assert_array_almost_equal(exp_spans, epochs.spans, decimal=4)
def test_parse_namelist():
nl = join(SML_TEST_TIF, 'ifms_17')
result = list(config.parse_namelist(nl))
assert len(result) == 17
files = [
"geo_060619-061002_unw.tif", "geo_060828-061211_unw.tif",
"geo_061002-070430_unw.tif", "geo_070115-070917_unw.tif",
"geo_070219-070604_unw.tif"
]
for path in files:
assert path in result
def validate_file_list_values(file_list, no_of_epochs):
if file_list is None: # pragma: no cover
raise ValueError("No value supplied for input file list: " + str(file_list))
files = parse_namelist(file_list)
for f in files:
if not Path(f).exists(): # pragma: no cover
raise ConfigException(f"{f} does not exist")
else:
matches = extract_epochs_from_filename(filename_with_epochs=f)
if len(matches) < no_of_epochs: # pragma: no cover
raise ConfigException(f"the number of epochs in {f} names are less the required number: {no_of_epochs}")
def get_header_paths(input_file, slc_file_list):
"""
Function that matches input GAMMA file names with GAMMA header file names
:param str input_file: input GAMMA image file.
:param str slc_dir: GAMMA SLC header file directory
:return: list of matching header files
:rtype: list
"""
f = Path(input_file)
epochs = extract_epochs_from_filename(f.name)
header_names = cf.parse_namelist(slc_file_list)
matches = [hdr for hdr in header_names if any(e in hdr for e in epochs)]
return matches
def get_header_paths(input_file, slc_file_list, slc_dir):
"""
Function that matches input GAMMA file names with GAMMA header file names
:param str input_file: input GAMMA image file.
:param str slc_dir: GAMMA SLC header file directory
:return: list of matching header files
:rtype: list
"""
_, file_name = split(input_file)
PTN = re.compile(r'\d{8}') # match 8 digits for the dates
epochs = PTN.findall(file_name)
header_names = cf.parse_namelist(slc_file_list)
matches = [hdr for hdr in header_names if any(e in hdr for e in epochs)]
return [os.path.join(slc_dir, hdr) for hdr in matches]
def setUpClass(cls):
cls.tif_dir = tempfile.mkdtemp()
cls.test_conf = common.TEST_CONF_GAMMA
# change the required params
cls.params = Configuration(cls.test_conf).__dict__
cls.params[cf.OBS_DIR] = common.SML_TEST_GAMMA
cls.params[cf.PROCESSOR] = 1 # gamma
file_list = list(
cf.parse_namelist(os.path.join(common.SML_TEST_GAMMA, 'ifms_17')))
fd, cls.params[cf.IFG_FILE_LIST] = tempfile.mkstemp(suffix='.conf',
dir=cls.tif_dir)
os.close(fd)
# write a short filelist with only 3 gamma unws
with open(cls.params[cf.IFG_FILE_LIST], 'w') as fp:
for f in file_list[:3]:
fp.write(os.path.join(common.SML_TEST_GAMMA, f) + '\n')
cls.params[cf.OUT_DIR] = cls.tif_dir
cls.params[cf.PARALLEL] = 0
cls.params[cf.REF_EST_METHOD] = 1
cls.params[cf.DEM_FILE] = common.SML_TEST_DEM_GAMMA
# base_unw_paths need to be geotiffed and multilooked by run_prepifg
cls.base_unw_paths = cf.original_ifg_paths(
cls.params[cf.IFG_FILE_LIST], cls.params[cf.OBS_DIR])
cls.base_unw_paths.append(common.SML_TEST_DEM_GAMMA)
# dest_paths are tifs that have been geotif converted and multilooked
conv2tif.main(cls.params)
prepifg.main(cls.params)
cls.dest_paths = [
Path(cls.tif_dir).joinpath(Path(c.sampled_path).name).as_posix()
for c in cls.params[cf.INTERFEROGRAM_FILES][:-2]
]
cls.ifgs = common.small_data_setup(datafiles=cls.dest_paths)
def setUpClass(cls):
cls.tif_dir = tempfile.mkdtemp()
cls.test_conf = common.TEST_CONF_GAMMA
# change the required params
cls.params = Configuration(cls.test_conf).__dict__
cls.params[cf.OBS_DIR] = common.SML_TEST_GAMMA
cls.params[cf.PROCESSOR] = 1 # gamma
file_list = list(
cf.parse_namelist(os.path.join(common.SML_TEST_GAMMA, 'ifms_17')))
fd, cls.params[cf.IFG_FILE_LIST] = tempfile.mkstemp(suffix='.conf',
dir=cls.tif_dir)
os.close(fd)
# write a short filelist with only 3 gamma unws
with open(cls.params[cf.IFG_FILE_LIST], 'w') as fp:
for f in file_list[:3]:
fp.write(os.path.join(common.SML_TEST_GAMMA, f) + '\n')
cls.params[cf.OUT_DIR] = cls.tif_dir
cls.params[cf.PARALLEL] = 0
cls.params[cf.REF_EST_METHOD] = 1
cls.params[cf.DEM_FILE] = common.SML_TEST_DEM_GAMMA
# base_unw_paths need to be geotiffed and multilooked by run_prepifg
cls.base_unw_paths = cf.original_ifg_paths(
cls.params[cf.IFG_FILE_LIST], cls.params[cf.OBS_DIR])
cls.base_unw_paths.append(common.SML_TEST_DEM_GAMMA)
xlks, ylks, crop = cf.transform_params(cls.params)
# dest_paths are tifs that have been geotif converted and multilooked
conv2tif.main(cls.params)
prepifg.main(cls.params)
# run_prepifg.gamma_prepifg(cls.base_unw_paths, cls.params)
cls.base_unw_paths.pop() # removed dem as we don't want it in ifgs
cls.dest_paths = cf.get_dest_paths(cls.base_unw_paths, crop,
cls.params, xlks)
cls.ifgs = common.small_data_setup(datafiles=cls.dest_paths)
def setUpClass(cls):
rate_types = ['stack_rate', 'stack_error', 'stack_samples']
cls.tif_dir = tempfile.mkdtemp()
cls.test_conf = common.TEST_CONF_GAMMA
from pyrate.configuration import Configuration
# change the required params
params = Configuration(cls.test_conf).__dict__
params[cf.OBS_DIR] = common.SML_TEST_GAMMA
params[cf.PROCESSES] = 4
params[cf.PROCESSOR] = 1 # gamma
params[cf.IFG_FILE_LIST] = os.path.join(common.SML_TEST_GAMMA,
'ifms_17')
params[cf.OUT_DIR] = cls.tif_dir
params[cf.PARALLEL] = 1
params[cf.APS_CORRECTION] = False
params[cf.TMPDIR] = os.path.join(params[cf.OUT_DIR], cf.TMPDIR)
rows, cols = params["rows"], params["cols"]
# xlks, ylks, crop = cf.transform_params(params)
# base_unw_paths need to be geotiffed by converttogeotif
# and multilooked by run_prepifg
base_unw_paths = list(cf.parse_namelist(params[cf.IFG_FILE_LIST]))
multi_paths = [
MultiplePaths(params[cf.OUT_DIR],
b,
ifglksx=params[cf.IFG_LKSX],
ifgcropopt=params[cf.IFG_CROP_OPT])
for b in base_unw_paths
]
# dest_paths are tifs that have been geotif converted and multilooked
cls.converted_paths = [b.converted_path for b in multi_paths]
cls.sampled_paths = [b.sampled_path for b in multi_paths]
from copy import copy
orig_params = copy(params)
conv2tif.main(params)
prepifg.main(orig_params)
tiles = pyrate.core.shared.get_tiles(cls.sampled_paths[0], rows, cols)
ifgs = common.small_data_setup()
params[cf.INTERFEROGRAM_FILES] = multi_paths
cls.refpixel_p, cls.maxvar_p, cls.vcmt_p = process.process_ifgs(
cls.sampled_paths, params, rows, cols)
cls.mst_p = common.reconstruct_mst(ifgs[0].shape, tiles,
params[cf.TMPDIR])
cls.rate_p, cls.error_p, cls.samples_p = \
[common.reconstruct_stack_rate(ifgs[0].shape, tiles, params[cf.TMPDIR], t) for t in rate_types]
common.remove_tifs(params[cf.OBS_DIR])
# now create the non parallel version
cls.tif_dir_s = tempfile.mkdtemp()
params[cf.PARALLEL] = 0
params[cf.PROCESSES] = 1
params[cf.OUT_DIR] = cls.tif_dir_s
params[cf.TMPDIR] = os.path.join(params[cf.OUT_DIR], cf.TMPDIR)
multi_paths = [
MultiplePaths(params[cf.OUT_DIR],
b,
ifglksx=params[cf.IFG_LKSX],
ifgcropopt=params[cf.IFG_CROP_OPT])
for b in base_unw_paths
]
cls.converted_paths_s = [b.converted_path for b in multi_paths]
cls.sampled_paths_s = [b.sampled_path for b in multi_paths]
orig_params = copy(params)
conv2tif.main(params)
prepifg.main(orig_params)
params[cf.INTERFEROGRAM_FILES] = multi_paths
cls.refpixel, cls.maxvar, cls.vcmt = process.process_ifgs(
cls.sampled_paths_s, params, rows, cols)
cls.mst = common.reconstruct_mst(ifgs[0].shape, tiles,
params[cf.TMPDIR])
cls.rate, cls.error, cls.samples = \
[common.reconstruct_stack_rate(ifgs[0].shape, tiles, params[cf.TMPDIR], t) for t in rate_types]
def __get_files_from_attr(self, attr, input_type=InputTypes.IFG):
val = self.__getattribute__(attr)
files = parse_namelist(val)
return [MultiplePaths(self.outdir, p, self.ifglksx, self.ifgcropopt, input_type=input_type) for p in files]
def __get_files_from_attr(self, attr):
val = self.__getattribute__(attr)
files = parse_namelist(val)
return [MultiplePaths(self.outdir, p, self.ifglksx, self.ifgcropopt) for p in files]