def get_common_region_int_ambiguity(ifgram_file, cc_mask_file, water_mask_file=None, num_sample=100,
dsNameIn='unwrapPhase'):
"""Solve the phase unwrapping integer ambiguity for the common regions among all interferograms
Parameters: ifgram_file : str, path of interferogram stack file
cc_mask_file : str, path of common connected components file
water_mask_file : str, path of water mask file
num_sample : int, number of pixel sampled for each region
dsNameIn : str, dataset name of the unwrap phase to be corrected
Returns: common_regions : list of skimage.measure._regionprops._RegionProperties object
modified by adding two more variables:
sample_coords : 2D np.ndarray in size of (num_sample, 2) in int64 format
int_ambiguity : 1D np.ndarray in size of (num_ifgram,) in int format
"""
print('-'*50)
print('calculating the integer ambiguity for the common regions defined in', cc_mask_file)
# stack info
stack_obj = ifgramStack(ifgram_file)
stack_obj.open()
date12_list = stack_obj.get_date12_list(dropIfgram=True)
num_ifgram = len(date12_list)
C = matrix(ifgramStack.get_design_matrix4triplet(date12_list).astype(float))
ref_phase = stack_obj.get_reference_phase(unwDatasetName=dsNameIn, dropIfgram=True).reshape(num_ifgram, -1)
# prepare common label
print('read common mask from', cc_mask_file)
cc_mask = readfile.read(cc_mask_file)[0]
if water_mask_file is not None and os.path.isfile(water_mask_file):
water_mask = readfile.read(water_mask_file)[0]
print('refine common mask based on water mask file', water_mask_file)
cc_mask[water_mask == 0] = 0
label_img, num_label = connectComponent.get_large_label(cc_mask, min_area=2.5e3, print_msg=True)
common_regions = measure.regionprops(label_img)
print('number of common regions:', num_label)
# add sample_coords / int_ambiguity
print('number of samples per region:', num_sample)
print('solving the phase-unwrapping integer ambiguity for {}'.format(dsNameIn))
print('\tbased on the closure phase of interferograms triplets (Yunjun et al., 2019)')
print('\tusing the L1-norm regularzed least squares approximation (LASSO) ...')
for i in range(num_label):
common_reg = common_regions[i]
# sample_coords
idx = sorted(np.random.choice(common_reg.area, num_sample, replace=False))
common_reg.sample_coords = common_reg.coords[idx, :].astype(int)
# solve for int_ambiguity
U = np.zeros((num_ifgram, num_sample))
if common_reg.label == label_img[stack_obj.refY, stack_obj.refX]:
print('{}/{} skip calculation for the reference region'.format(i+1, num_label))
else:
prog_bar = ptime.progressBar(maxValue=num_sample, prefix='{}/{}'.format(i+1, num_label))
for j in range(num_sample):
# read unwrap phase
y, x = common_reg.sample_coords[j, :]
unw = ifginv.read_unwrap_phase(stack_obj,
box=(x, y, x+1, y+1),
ref_phase=ref_phase,
unwDatasetName=dsNameIn,
dropIfgram=True,
print_msg=False).reshape(num_ifgram, -1)
# calculate closure_int
closure_pha = np.dot(C, unw)
closure_int = matrix(np.round((closure_pha - ut.wrap(closure_pha)) / (2.*np.pi)))
# solve for U
U[:,j] = np.round(l1regls(-C, closure_int, alpha=1e-2, show_progress=0)).flatten()
prog_bar.update(j+1, every=5)
prog_bar.close()
# add int_ambiguity
common_reg.int_ambiguity = np.median(U, axis=1)
common_reg.date12_list = date12_list
#sort regions by size to facilitate the region matching later
common_regions.sort(key=lambda x: x.area, reverse=True)
# plot sample result
fig_size = pp.auto_figure_size(label_img.shape, disp_cbar=False)
fig, ax = plt.subplots(figsize=fig_size)
ax.imshow(label_img, cmap='jet')
for common_reg in common_regions:
ax.plot(common_reg.sample_coords[:,1],
common_reg.sample_coords[:,0], 'k.', ms=2)
pp.auto_flip_direction(stack_obj.metadata, ax, print_msg=False)
out_img = 'common_region_sample.png'
fig.savefig(out_img, bbox_inches='tight', transparent=True, dpi=300)
print('saved common regions and sample pixels to file', out_img)
return common_regions
def get_common_region_int_ambiguity(ifgram_file,
cc_mask_file,
water_mask_file=None,
num_sample=100,
dsNameIn='unwrapPhase'):
"""Solve the phase unwrapping integer ambiguity for the common regions among all interferograms
Parameters: ifgram_file : str, path of interferogram stack file
cc_mask_file : str, path of common connected components file
water_mask_file : str, path of water mask file
num_sample : int, number of pixel sampled for each region
dsNameIn : str, dataset name of the unwrap phase to be corrected
Returns: common_regions : list of skimage.measure._regionprops._RegionProperties object
modified by adding two more variables:
sample_coords : 2D np.ndarray in size of (num_sample, 2) in int64 format
int_ambiguity : 1D np.ndarray in size of (num_ifgram,) in int format
"""
print('-' * 50)
print(
'calculating the integer ambiguity for the common regions defined in',
cc_mask_file)
# stack info
stack_obj = ifgramStack(ifgram_file)
stack_obj.open()
date12_list = stack_obj.get_date12_list(dropIfgram=True)
num_ifgram = len(date12_list)
C = matrix(
ifgramStack.get_design_matrix4triplet(date12_list).astype(float))
ref_phase = stack_obj.get_reference_phase(unwDatasetName=dsNameIn,
dropIfgram=True).reshape(
num_ifgram, -1)
# prepare common label
print('read common mask from', cc_mask_file)
cc_mask = readfile.read(cc_mask_file)[0]
if water_mask_file is not None and os.path.isfile(water_mask_file):
water_mask = readfile.read(water_mask_file)[0]
print('refine common mask based on water mask file', water_mask_file)
cc_mask[water_mask == 0] = 0
label_img, num_label = connectComponent.get_large_label(cc_mask,
min_area=2.5e3,
print_msg=True)
common_regions = measure.regionprops(label_img)
print('number of common regions:', num_label)
# add sample_coords / int_ambiguity
print('number of samples per region:', num_sample)
print('solving the phase-unwrapping integer ambiguity for {}'.format(
dsNameIn))
print(
'\tbased on the closure phase of interferograms triplets (Yunjun et al., 2019)'
)
print(
'\tusing the L1-norm regularzed least squares approximation (LASSO) ...'
)
for i in range(num_label):
common_reg = common_regions[i]
# sample_coords
idx = sorted(
np.random.choice(common_reg.area, num_sample, replace=False))
common_reg.sample_coords = common_reg.coords[idx, :].astype(int)
# solve for int_ambiguity
U = np.zeros((num_ifgram, num_sample))
if common_reg.label == label_img[stack_obj.refY, stack_obj.refX]:
print('{}/{} skip calculation for the reference region'.format(
i + 1, num_label))
else:
prog_bar = ptime.progressBar(maxValue=num_sample,
prefix='{}/{}'.format(
i + 1, num_label))
for j in range(num_sample):
# read unwrap phase
y, x = common_reg.sample_coords[j, :]
unw = ifginv.read_unwrap_phase(stack_obj,
box=(x, y, x + 1, y + 1),
ref_phase=ref_phase,
unwDatasetName=dsNameIn,
dropIfgram=True,
print_msg=False).reshape(
num_ifgram, -1)
# calculate closure_int
closure_pha = np.dot(C, unw)
closure_int = matrix(
np.round(
(closure_pha - ut.wrap(closure_pha)) / (2. * np.pi)))
# solve for U
U[:, j] = np.round(
l1regls(-C, closure_int, alpha=1e-2,
show_progress=0)).flatten()
prog_bar.update(j + 1, every=5)
prog_bar.close()
# add int_ambiguity
common_reg.int_ambiguity = np.median(U, axis=1)
common_reg.date12_list = date12_list
#sort regions by size to facilitate the region matching later
common_regions.sort(key=lambda x: x.area, reverse=True)
# plot sample result
fig_size = pp.auto_figure_size(label_img.shape, disp_cbar=False)
fig, ax = plt.subplots(figsize=fig_size)
ax.imshow(label_img, cmap='jet')
for common_reg in common_regions:
ax.plot(common_reg.sample_coords[:, 1],
common_reg.sample_coords[:, 0],
'k.',
ms=2)
pp.auto_flip_direction(stack_obj.metadata, ax, print_msg=False)
out_img = 'common_region_sample.png'
fig.savefig(out_img, bbox_inches='tight', transparent=True, dpi=300)
print('saved common regions and sample pixels to file', out_img)
return common_regions
def main(argv):
inps = cmdLineParse()
ifgram = inps.ifgram_file
Bperp = readfile.read(ifgram, datasetName='bperp')[0]
Date = readfile.read(ifgram, datasetName='date')[0]
DropIfgram = readfile.read(ifgram, datasetName='dropIfgram')[0]
#invRes = inps.inversion_res
mask_file = inps.mask_file
mask = readfile.read(mask_file, datasetName='mask')[0]
meta = readfile.read_attribute(ifgram, datasetName=None)
REF_X = int(meta['REF_X'])
REF_Y = int(meta['REF_Y'])
if inps.out_file:
OUT = inps.out_file
else:
OUT = 'ifgramStackCor.h5'
sliceList = readfile.get_slice_list(ifgram)
N_list =len(sliceList)
g_list = []
for i in range(N_list):
if 'unwrapPhase-' in sliceList[i]:
g_list.append(sliceList[i])
N_list = len(g_list)
Ifg = []
print('Start to calculate the integer ambugity for each closure')
for i in range(N_list):
print_progress(i+1, N_list, prefix='Data: ', suffix=g_list[i])
dset = g_list[i]
ifgram1 = readfile.read(ifgram, datasetName=dset)[0]
ifgram0 = ifgram1 - ifgram1[REF_Y,REF_X]
Ifg.append(np.mean(ifgram0[mask==1]))
stack_obj = ifgramStack(ifgram)
stack_obj.open()
date12_list = stack_obj.get_date12_list(dropIfgram=True)
num_ifgram = len(date12_list)
date12_list = stack_obj.get_date12_list(dropIfgram=True)
num_ifgram = len(date12_list)
C0 = ifgramStack.get_design_matrix4triplet(date12_list)
#Ifg = np.asarray(Ifg);Ifg=Ifg.reshape(len(Ifg),)
#ResC = np.dot(C0,Ifg)
#good_pair = get_good_pair_closure(C,ResC)
#good_pair = list(good_pair)
#bad_pair = get_bad_pair(good_pair,N_list)
#print('Bad interferograms: ' + str(bad_pair))
#Ifg_org = []
#for k in bad_pair:
# Ifg_org.append(Ifg[k])
#Ifg_org = np.asarray(Ifg_org)
#Ifg_org.reshape(len(bad_pair),)
#A,L = get_design_matrix_unwrap_error(C,bad_pair,Ifg)
#Ifg_est, var_ts = estimate_timeseries(A, -L, weight_sqrt=None, rcond=1e-5)
#Ifg_est = Ifg_est.reshape(len(Ifg_est),)
#kk = np.round((Ifg_est - Ifg_org)/(2*np.pi))
#print('Cycle shift of the bad interferogram: ' + str(kk))
C = matrix(ifgramStack.get_design_matrix4triplet(date12_list).astype(float))
ResC = np.dot(C,Ifg)
L = matrix(np.round(ResC/(2*np.pi)))
U = l1regls(-C, L, alpha=1e-2, show_progress=0)
kk = np.round(U)
num_row = stack_obj.length
num_col = stack_obj.width
box = [0,0,stack_obj.width,stack_obj.length]
ref_phase = stack_obj.get_reference_phase(unwDatasetName='unwrapPhase',
skip_reference=None,
dropIfgram=True)
pha_data = read_unwrap_phase(stack_obj,box,ref_phase,unwDatasetName='unwrapPhase',dropIfgram=True)
data = pha_data.reshape(N_list,num_row,num_col)
data0 = data
print('Start to correct and write new unwrapIfg file ...')
for i in range(N_list):
ifgram1 = data[i,:,:]
ifgram0 = ifgram1 - ifgram1[REF_Y,REF_X]
#print(ifgram0.shape)
#ifgram0 = ifgram0 + mask*(kk*(2*np.pi))
ifgram0[mask==1] = ifgram0[mask==1] + kk[i]*(2*np.pi)
data0[i,:,:] = ifgram0
datasetDict = dict()
datasetDict['unwrapPhase'] = data0
datasetDict['IntAmbiguity'] = kk
datasetDict['bperp'] = Bperp
datasetDict['date'] = Date
datasetDict['dropIfgram'] = DropIfgram
datasetDict['C'] = C0
write_variogram_h5(datasetDict, OUT, metadata=meta, ref_file=ifgram, compression=None)
sys.exit(1)
