def main(iargs=None):
inps = cmd_line_parse(iargs)
inps.processor = isce_utils.get_processor(inps.metaFile)
# read common metadata
metadata = {}
if inps.metaFile:
rsc_file = os.path.join(os.path.dirname(inps.metaFile), 'data.rsc')
metadata = isce_utils.extract_isce_metadata(inps.metaFile,
geom_dir=inps.geometryDir,
rsc_file=rsc_file,
update_mode=inps.update_mode)[0]
# prepare metadata for geometry file
if inps.geometryDir:
metadata = prepare_geometry(inps.geometryDir,
metadata=metadata,
update_mode=inps.update_mode)
# read baseline info
baseline_dict = {}
if inps.baselineDir:
baseline_dict = isce_utils.read_baseline_timeseries(inps.baselineDir,
processor=inps.processor)
# prepare metadata for ifgram file
if inps.dsetDir and inps.dsetFiles:
for namePattern in inps.dsetFiles:
prepare_stack(inps.dsetDir, namePattern,
metadata=metadata,
baseline_dict=baseline_dict,
update_mode=inps.update_mode)
print('Done.')
return
def main(iargs=None):
inps = cmd_line_parse(iargs)
inps.processor = isce_utils.get_processor(inps.metaFile)
# read common metadata
metadata = {}
if inps.metaFile:
rsc_file = os.path.join(os.path.dirname(inps.metaFile), 'data.rsc')
metadata = isce_utils.extract_isce_metadata(
inps.metaFile,
geom_dir=inps.geometryDir,
rsc_file=rsc_file,
update_mode=inps.update_mode)[0]
# prepare metadata for geometry file
if inps.geometryDir:
prepare_geometry(inps.geometryDir,
geom_files=inps.geometryFiles,
metadata=metadata,
processor=inps.processor,
update_mode=inps.update_mode)
# read baseline info
baseline_dict = {}
if inps.baselineDir:
if inps.baselineDir.startswith(
'rand') and inps.dsetDir and inps.dsetFiles:
if '-' in inps.baselineDir:
max_bperp = float(inps.baselineDir.split('-')[1])
else:
max_bperp = 10
baseline_dict = gen_random_baseline_timeseries(
dset_dir=inps.dsetDir,
dset_file=inps.dsetFiles[0],
max_bperp=max_bperp)
else:
baseline_dict = isce_utils.read_baseline_timeseries(
inps.baselineDir, processor=inps.processor)
# prepare metadata for ifgram file
if inps.dsetDir and inps.dsetFiles:
for namePattern in inps.dsetFiles:
prepare_stack(inps.dsetDir,
namePattern,
metadata=metadata,
baseline_dict=baseline_dict,
processor=inps.processor,
update_mode=inps.update_mode)
print('Done.')
return
def prepare_timeseries(outfile, unw_file, metadata, processor, baseline_dir=None):
print('-'*50)
print('preparing timeseries file: {}'.format(outfile))
# copy metadata to meta
meta = {key : value for key, value in metadata.items()}
phase2range = -1. * float(meta['WAVELENGTH']) / (4. * np.pi)
# grab date list from the filename
unw_files = sorted(glob.glob(unw_file))
date12_list = [os.path.splitext(os.path.basename(i))[0] for i in unw_files]
num_file = len(unw_files)
print('number of unwrapped interferograms: {}'.format(num_file))
ref_date = date12_list[0].split('_')[0]
date_list = [ref_date] + [date12.split('_')[1] for date12 in date12_list]
num_date = len(date_list)
print('number of acquisitions: {}\n{}'.format(num_date, date_list))
# define dataset structure
length, width = int(meta['LENGTH']), int(meta['WIDTH'])
dsNameDict = {
"date" : (np.dtype("S8"), (num_date,)),
"timeseries" : (np.float32, (num_date, length, width))
}
# baseline info
baseline_dict = {}
if baseline_dir is not None:
# read baseline data
baseline_dict = isce_utils.read_baseline_timeseries(baseline_dir,
processor=processor,
ref_date=ref_date)
# dict to array
pbase = np.zeros(num_date, dtype=np.float32)
for i in range(num_date):
pbase_top, pbase_bottom = baseline_dict[date_list[i]]
pbase[i] = (pbase_top + pbase_bottom) / 2.0
# update dataset structure
dsNameDict["bperp"] = (np.float32, (num_date,))
# initiate HDF5 file
meta["FILE_TYPE"] = "timeseries"
meta["UNIT"] = "m"
meta['REF_DATE'] = ref_date
writefile.layout_hdf5(outfile, dsNameDict, meta)
# writing data to HDF5 file
print('writing data to HDF5 file {} with a mode ...'.format(outfile))
with h5py.File(outfile, "a") as f:
f["date"][:,] = np.array([np.string_(i) for i in date_list])
f["bperp"][:,] = pbase
prog_bar = ptime.progressBar(maxValue=num_file)
for i in range(num_file):
# read data using gdal
ds = gdal.Open(unw_files[i], gdal.GA_ReadOnly)
data = np.array(ds.GetRasterBand(2).ReadAsArray())
f["timeseries"][i+1] = data * phase2range
prog_bar.update(i+1, suffix=date12_list[i])
prog_bar.close()
print('set value at the first acquisition to ZERO.')
f["timeseries"][0] = 0.
print('finished writing to HDF5 file: {}'.format(outfile))
return outfile
def prepare_timeseries(outfile,
unw_file,
metadata,
processor,
baseline_dir=None,
box=None):
print('-' * 50)
print('preparing timeseries file: {}'.format(outfile))
# copy metadata to meta
meta = {key: value for key, value in metadata.items()}
phase2range = float(meta['WAVELENGTH']) / (4. * np.pi)
# grab date list from the filename
unw_files = sorted(glob.glob(unw_file))
date12_list = [os.path.splitext(os.path.basename(i))[0] for i in unw_files]
num_file = len(unw_files)
print('number of unwrapped interferograms: {}'.format(num_file))
ref_date = date12_list[0].split('_')[0]
date_list = [ref_date] + [date12.split('_')[1] for date12 in date12_list]
num_date = len(date_list)
print('number of acquisitions: {}\n{}'.format(num_date, date_list))
# baseline info
if baseline_dir is not None:
# read baseline data
baseline_dict = isce_utils.read_baseline_timeseries(
baseline_dir, processor=processor, ref_date=ref_date)
# dict to array
pbase = np.zeros(num_date, dtype=np.float32)
for i in range(num_date):
pbase_top, pbase_bottom = baseline_dict[date_list[i]]
pbase[i] = (pbase_top + pbase_bottom) / 2.0
# size info
if not box:
box = (0, 0, int(meta['WIDTH']), int(meta['LENGTH']))
kwargs = dict(xoff=box[0],
yoff=box[1],
win_xsize=box[2] - box[0],
win_ysize=box[3] - box[1])
# define dataset structure
dates = np.array(date_list, dtype=np.string_)
ds_name_dict = {
"date": [dates.dtype, (num_date, ), dates],
"bperp": [np.float32, (num_date, ), pbase],
"timeseries":
[np.float32, (num_date, box[3] - box[1], box[2] - box[0]), None],
}
# initiate HDF5 file
meta["FILE_TYPE"] = "timeseries"
meta["UNIT"] = "m"
meta['REF_DATE'] = ref_date
writefile.layout_hdf5(outfile, ds_name_dict, metadata=meta)
# writing data to HDF5 file
print('writing data to HDF5 file {} with a mode ...'.format(outfile))
with h5py.File(outfile, "a") as f:
prog_bar = ptime.progressBar(maxValue=num_file)
for i, unw_file in enumerate(unw_files):
# read data using gdal
ds = gdal.Open(unw_file, gdal.GA_ReadOnly)
data = np.array(ds.GetRasterBand(2).ReadAsArray(**kwargs),
dtype=np.float32)
f["timeseries"][i + 1] = data * phase2range
prog_bar.update(i + 1, suffix=date12_list[i])
prog_bar.close()
print('set value at the first acquisition to ZERO.')
f["timeseries"][0] = 0.
print('finished writing to HDF5 file: {}'.format(outfile))
return outfile
def prepare_stack(outfile,
unw_file,
metadata,
processor,
baseline_dir=None,
box=None):
print('-' * 50)
print('preparing ifgramStack file: {}'.format(outfile))
# copy metadata to meta
meta = {key: value for key, value in metadata.items()}
# get list of *.unw file
unw_files = sorted(glob.glob(unw_file))
num_pair = len(unw_files)
print('number of interferograms:', num_pair)
# get list of *.unw.conncomp file
cc_files = [f'{x}.conncomp' for x in unw_files]
cc_files = [x for x in cc_files if os.path.isfile(x)]
print(f'number of connected components files: {len(cc_files)}')
if len(cc_files) != len(unw_files):
print(
'the number of *.unw and *.unw.conncomp files are NOT consistent')
print('skip creating ifgramStack.h5 file.')
return
# get date info: date12_list
date12_list = [os.path.basename(x).split('.')[0] for x in unw_files]
# prepare baseline info
if baseline_dir is not None:
# read baseline timeseries
baseline_dict = isce_utils.read_baseline_timeseries(
baseline_dir, processor=processor)
# calc baseline for each pair
print('calc perp baseline pairs from time-series')
pbase = np.zeros(num_pair, dtype=np.float32)
for i, date12 in enumerate(date12_list):
[date1, date2] = date12.split('_')
pbase[i] = np.subtract(baseline_dict[date2],
baseline_dict[date1]).mean()
# size info
box = box if box else (0, 0, int(meta['WIDTH']), int(meta['LENGTH']))
kwargs = dict(xoff=box[0],
yoff=box[1],
win_xsize=box[2] - box[0],
win_ysize=box[3] - box[1])
# define (and fill out some) dataset structure
date12_arr = np.array([x.split('_') for x in date12_list],
dtype=np.string_)
drop_ifgram = np.ones(num_pair, dtype=np.bool_)
ds_name_dict = {
"date": [date12_arr.dtype, (num_pair, 2), date12_arr],
"bperp": [np.float32, (num_pair, ), pbase],
"dropIfgram": [np.bool_, (num_pair, ), drop_ifgram],
"unwrapPhase":
[np.float32, (num_pair, box[3] - box[1], box[2] - box[0]), None],
"connectComponent":
[np.float32, (num_pair, box[3] - box[1], box[2] - box[0]), None],
}
# initiate HDF5 file
meta["FILE_TYPE"] = "ifgramStack"
writefile.layout_hdf5(outfile, ds_name_dict, metadata=meta)
# writing data to HDF5 file
print('writing data to HDF5 file {} with a mode ...'.format(outfile))
with h5py.File(outfile, "a") as f:
prog_bar = ptime.progressBar(maxValue=num_pair)
for i, (unw_file, cc_file) in enumerate(zip(unw_files, cc_files)):
# read/write *.unw file
ds = gdal.Open(unw_file, gdal.GA_ReadOnly)
data = np.array(ds.GetRasterBand(2).ReadAsArray(**kwargs),
dtype=np.float32)
f["unwrapPhase"][i] = data
# read/write *.unw.conncomp file
ds = gdal.Open(cc_file, gdal.GA_ReadOnly)
data = np.array(ds.GetRasterBand(1).ReadAsArray(**kwargs),
dtype=np.float32)
f["connectComponent"][i] = data
prog_bar.update(i + 1, suffix=date12_list[i])
prog_bar.close()
print('finished writing to HDF5 file: {}'.format(outfile))
return outfile