def seed_file_reference_value(File, outName, refList, ref_y='', ref_x=''):
## Seed Input File with reference value in refList
print('Reference value: ')
print(refList)
##### IO Info
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
print('file type: ' + k)
##### Multiple Dataset File
if k in ['timeseries', 'interferograms', 'wrapped', 'coherence']:
##### Input File Info
h5file = h5py.File(File, 'r')
epochList = sorted(h5file[k].keys())
epochNum = len(epochList)
##### Check Epoch Number
if not epochNum == len(refList):
print('\nERROR: Reference value has different epoch number'+\
'from input file.')
print('Reference List epoch number: ' + str(refList))
print('Input file epoch number: ' + str(epochNum))
sys.exit(1)
##### Output File Info
h5out = h5py.File(outName, 'w')
group = h5out.create_group(k)
print('writing >>> ' + outName)
prog_bar = ptime.progress_bar(maxValue=epochNum, prefix='seeding: ')
## Loop
if k == 'timeseries':
print('number of acquisitions: ' + str(epochNum))
for i in range(epochNum):
epoch = epochList[i]
data = h5file[k].get(epoch)[:]
data -= refList[i]
dset = group.create_dataset(epoch, data=data, compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
atr = seed_attributes(atr, ref_x, ref_y)
for key, value in atr.items():
group.attrs[key] = value
elif k in ['interferograms', 'wrapped', 'coherence']:
print('number of interferograms: ' + str(epochNum))
date12_list = ptime.list_ifgram2date12(epochList)
for i in range(epochNum):
epoch = epochList[i]
#print epoch
data = h5file[k][epoch].get(epoch)[:]
atr = h5file[k][epoch].attrs
data -= refList[i]
atr = seed_attributes(atr, ref_x, ref_y)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in atr.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
##### Single Dataset File
else:
print('writing >>> ' + outName)
data, atr = readfile.read(File)
data -= refList
atr = seed_attributes(atr, ref_x, ref_y)
writefile.write(data, atr, outName)
##### End & Cleaning
try:
prog_bar.close()
h5file.close()
h5out.close()
except:
pass
return outName
def unwrap_error_correction_bridging(ifgram_file, mask_file, y_list, x_list, ramp_type='plane',\
ifgram_cor_file=None, save_cor_deramp_file=False):
'''Unwrapping error correction with bridging.
Inputs:
ifgram_file : string, name/path of interferogram(s) to be corrected
mask_file : string, name/path of mask file to mark different patches
y/x_list : list of int, bonding points in y/x
ifgram_cor_file : string, optional, output file name
save_cor_deramp_file : bool, optional
Output:
ifgram_cor_file
Example:
y_list = [235, 270, 350, 390]
x_list = [880, 890, 1200, 1270]
unwrap_error_correction_bridging('unwrapIfgram.h5', 'mask_all.h5', y_list, x_list, 'quadratic')
'''
##### Mask and Ramp
mask = readfile.read(mask_file)[0]
ramp_mask = mask == 1
print('estimate phase ramp during the correction')
print('ramp type: '+ramp_type)
##### Bridge Info
# Check
for i in range(len(x_list)):
if mask[y_list[i],x_list[i]] == 0:
print('\nERROR: Connecting point (%d,%d) is out of masked area! Select them again!\n' % (y_list[i],x_list[i]))
sys.exit(1)
print('Number of bridges: '+str(len(x_list)/2))
print('Bonding points coordinates:\nx: '+str(x_list)+'\ny: '+str(y_list))
# Plot Connecting Pair of Points
plot_bonding_points = False
if plot_bonding_points:
point_yx = ''
line_yx = ''
n_bridge = len(x)/2
for i in range(n_bridge):
pair_yx = str(y[2*i])+','+str(x[2*i])+','+str(y[2*i+1])+','+str(x[2*i+1])
if not i == n_bridge-1:
point_yx += pair_yx+','
line_yx += pair_yx+';'
else:
point_yx += pair_yx
line_yx += pair_yx
try:
plot_cmd = 'view.py --point-yx="'+point_yx+'" --line-yx="'+line_yx+\
'" --nodisplay -o bonding_points.png -f '+maskFile
print(plot_cmd)
os.system(plot_cmd)
except: pass
# Basic info
ext = os.path.splitext(ifgram_file)[1]
atr = readfile.read_attribute(ifgram_file)
k = atr['FILE_TYPE']
try:
ref_y = int(atr['ref_y'])
ref_x = int(atr['ref_x'])
except:
sys.exit('ERROR: Can not find ref_y/x value, input file is not referenced in space!')
# output file name
if not ifgram_cor_file:
ifgram_cor_file = os.path.splitext(ifgram_file)[0]+'_unwCor'+ext
ifgram_cor_deramp_file = os.path.splitext(ifgram_cor_file)[0]+'_'+ramp_type+ext
##### HDF5 file
if ext == '.h5':
##### Read
h5 = h5py.File(ifgram_file,'r')
ifgram_list = sorted(h5[k].keys())
ifgram_num = len(ifgram_list)
h5out = h5py.File(ifgram_cor_file,'w')
group = h5out.create_group(k)
print('writing >>> '+ifgram_cor_file)
if save_cor_deramp_file:
h5out_deramp = h5py.File(ifgram_cor_deramp_file,'w')
group_deramp = h5out_deramp.create_group(k)
print('writing >>> '+ifgram_cor_deramp_file)
##### Loop
print('Number of interferograms: '+str(ifgram_num))
prog_bar = ptime.progress_bar(maxValue=ifgram_num)
date12_list = ptime.list_ifgram2date12(ifgram_list)
for i in range(ifgram_num):
ifgram = ifgram_list[i]
data = h5[k][ifgram].get(ifgram)[:]
data -= data[ref_y, ref_x]
data_deramp, ramp = rm.remove_data_surface(data, ramp_mask, ramp_type)
data_derampCor = bridging_data(data_deramp, mask, x_list, y_list)
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram, data=data_derampCor-ramp, compression='gzip')
for key, value in h5[k][ifgram].attrs.items():
gg.attrs[key]=value
if save_cor_deramp_file:
gg_deramp = group_deramp.create_group(ifgram)
dset = gg_deramp.create_dataset(ifgram, data=data_derampCor, compression='gzip')
for key, value in h5[k][ifgram].attrs.items():
gg_deramp.attrs[key]=value
prog_bar.update(i+1, suffix=date12_list[i])
prog_bar.close()
h5.close()
h5out.close()
try: h5out_deramp.close()
except: pass
#### .unw file
elif ext == '.unw':
print('read '+ifgram_file)
data = readfile.read(ifgram_file)[0]
data -= data[ref_y, ref_x]
data_deramp,ramp = rm.remove_data_surface(data,ramp_mask,ramp_type)
data_derampCor = bridging_data(data_deramp,mask,x_list,y_list)
data_cor = data_derampCor - ramp
print('writing >>> '+ifgram_cor_file)
ifgram_cor_file = writefile.write(data_cor, atr, ifgram_cor_file)
if save_cor_deramp_file:
print('writing >>> '+ifgram_cor_deramp_file)
ifgram_cor_deramp_file = writefile.write(data_derampCor, atr, ifgram_cor_deramp_file)
else:
sys.exit('Un-supported file type: '+ext)
return ifgram_cor_file, ifgram_cor_deramp_file
def main(argv):
##### Read Inputs
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file)
date12_orig = pnet.get_date12_list(inps.file[0])
print('input file(s) to be modified: ' + str(inps.file))
print('number of interferograms: ' + str(len(date12_orig)))
atr = readfile.read_attribute(inps.file[0])
# Update inps if template is input
if inps.template_file:
inps = read_template2inps(inps.template_file, inps)
if inps.reset:
print(
'----------------------------------------------------------------------------'
)
for file in inps.file:
reset_pairs(file)
mean_coh_txt_file = os.path.splitext(
inps.coherence_file)[0] + '_spatialAverage.txt'
if os.path.isfile(mean_coh_txt_file):
rmCmd = 'rm ' + mean_coh_txt_file
print(rmCmd)
os.system(rmCmd)
return
if all(not i for i in [inps.reference_file, inps.max_temp_baseline, inps.max_perp_baseline,\
inps.exclude_ifg_index, inps.exclude_date, inps.coherence_based, inps.start_date, inps.end_date]):
# Display network for manually modification when there is no other modification input.
print('No input option found to remove interferogram')
print('To manually modify network, please use --manual option ')
return
# Convert index : input to continous index list
if inps.exclude_ifg_index:
ifg_index = list(inps.exclude_ifg_index)
inps.exclude_ifg_index = []
for index in ifg_index:
index_temp = [int(i) for i in index.split(':')]
index_temp.sort()
if len(index_temp) == 2:
for j in range(index_temp[0], index_temp[1] + 1):
inps.exclude_ifg_index.append(j)
elif len(index_temp) == 1:
inps.exclude_ifg_index.append(int(index))
else:
print('Unrecoganized input: ' + index)
inps.exclude_ifg_index = sorted(inps.exclude_ifg_index)
if max(inps.exclude_ifg_index) > len(date12_orig):
raise Exception('Input index out of range!\n'+\
'input index:'+str(inps.exclude_ifg_index)+'\n'+\
'index range of file: '+str(len(date12_orig)))
##### Get date12_to_rmv
date12_to_rmv = []
# 1. Update date12_to_rmv from reference file
if inps.reference_file:
date12_to_keep = pnet.get_date12_list(inps.reference_file)
print(
'----------------------------------------------------------------------------'
)
print('use reference pairs info from file: ' + inps.reference_file)
print('number of interferograms in reference: ' +
str(len(date12_to_keep)))
print('date12 not in reference file:')
for date12 in date12_orig:
if date12 not in date12_to_keep:
date12_to_rmv.append(date12)
print(date12)
# 2.1 Update date12_to_rmv from coherence file
if inps.coherence_based and os.path.isfile(inps.coherence_file):
print(
'----------------------------------------------------------------------------'
)
print(
'use coherence-based network modification from coherence file: ' +
inps.coherence_file)
# check mask AOI in lalo
if inps.aoi_geo_box and inps.trans_file:
print('input AOI in (lon0, lat1, lon1, lat0): ' +
str(inps.aoi_geo_box))
inps.aoi_pix_box = subset.bbox_geo2radar(inps.aoi_geo_box, atr,
inps.trans_file)
if inps.aoi_pix_box:
# check mask AOI within the data coverage
inps.aoi_pix_box = subset.check_box_within_data_coverage(
inps.aoi_pix_box, atr)
print('input AOI in (x0,y0,x1,y1): ' + str(inps.aoi_pix_box))
# Calculate spatial average coherence
coh_list, coh_date12_list = ut.spatial_average(inps.coherence_file, inps.mask_file,\
inps.aoi_pix_box, saveList=True)
# MST network
if inps.keep_mst:
print(
'Get minimum spanning tree (MST) of interferograms with inverse of coherence.'
)
print('date12 with 1) average coherence < ' +
str(inps.min_coherence) + ' AND 2) not in MST network: ')
mst_date12_list = pnet.threshold_coherence_based_mst(
coh_date12_list, coh_list)
else:
print('date12 with average coherence < ' + str(inps.min_coherence))
mst_date12_list = []
for i in range(len(coh_date12_list)):
date12 = coh_date12_list[i]
if coh_list[
i] < inps.min_coherence and date12 not in mst_date12_list:
date12_to_rmv.append(date12)
print(date12)
# 2.2 Update date12_to_rmv from perp baseline threshold
if inps.max_perp_baseline:
print(
'----------------------------------------------------------------------------'
)
print('Drop pairs with perpendicular spatial baseline > ' +
str(inps.max_perp_baseline) + ' meters')
ifg_bperp_list = pnet.igram_perp_baseline_list(inps.file[0])
for i in range(len(ifg_bperp_list)):
if ifg_bperp_list[i] > inps.max_perp_baseline:
date12 = date12_orig[i]
date12_to_rmv.append(date12)
print(date12)
# 2.3 Update date12_to_rmv from temp baseline threshold
if inps.max_temp_baseline:
print(
'----------------------------------------------------------------------------'
)
print('Drop pairs with temporal baseline > ' +
str(inps.max_temp_baseline) + ' days')
date8_list = ptime.ifgram_date_list(inps.file[0])
date6_list = ptime.yymmdd(date8_list)
tbase_list = ptime.date_list2tbase(date8_list)[0]
for i in range(len(date12_orig)):
date1, date2 = date12_orig[i].split('-')
idx1 = date6_list.index(date1)
idx2 = date6_list.index(date2)
t_diff = tbase_list[idx2] - tbase_list[idx1]
if t_diff > inps.max_temp_baseline:
date12 = date12_orig[i]
date12_to_rmv.append(date12)
print(date12)
# 2.4 Update date12_to_rmv from exclude_ifg_index
if inps.exclude_ifg_index:
print(
'----------------------------------------------------------------------------'
)
print('drop date12/pair with the following index number:')
for index in inps.exclude_ifg_index:
date12 = date12_orig[index - 1]
date12_to_rmv.append(date12)
print(str(index) + ' ' + date12)
# 2.5 Update date12_to_rmv from exclude_date
if inps.exclude_date:
inps.exclude_date = ptime.yymmdd(inps.exclude_date)
print(
'----------------------------------------------------------------------------'
)
print('Drop pairs including the following dates: \n' +
str(inps.exclude_date))
for i in range(len(date12_orig)):
date1, date2 = date12_orig[i].split('-')
if (date1 in inps.exclude_date) or (date2 in inps.exclude_date):
date12 = date12_orig[i]
date12_to_rmv.append(date12)
print(date12)
# 2.6 Update date12_to_rmv from start_date
if inps.start_date:
inps.start_date = ptime.yymmdd(inps.start_date)
print(
'----------------------------------------------------------------------------'
)
print('Drop pairs with date earlier than start-date: ' +
inps.start_date)
min_date = int(ptime.yyyymmdd(inps.start_date))
for i in range(len(date12_orig)):
date12 = date12_orig[i]
if any(
int(j) < min_date
for j in ptime.yyyymmdd(date12.split('-'))):
date12_to_rmv.append(date12)
print(date12)
# 2.7 Update date12_to_rmv from end_date
if inps.end_date:
inps.end_date = ptime.yymmdd(inps.end_date)
print(
'----------------------------------------------------------------------------'
)
print('Drop pairs with date earlier than end-date: ' + inps.end_date)
max_date = int(ptime.yyyymmdd(inps.end_date))
for i in range(len(date12_orig)):
date12 = date12_orig[i]
if any(
int(j) > max_date
for j in ptime.yyyymmdd(date12.split('-'))):
date12_to_rmv.append(date12)
print(date12)
# 3. Manually drop pairs
if inps.disp_network:
date12_click = manual_select_pairs_to_remove(inps.file[0])
for date12 in list(date12_click):
if date12 not in date12_orig:
date12_click.remove(date12)
print('date12 selected to remove:')
print(date12_click)
date12_to_rmv += date12_click
# 4. drop duplicate date12 and sort in order
date12_to_rmv = list(set(date12_to_rmv))
date12_to_rmv = sorted(date12_to_rmv)
print(
'----------------------------------------------------------------------------'
)
print('number of interferograms to remove: ' + str(len(date12_to_rmv)))
print('list of interferograms to remove:')
print(date12_to_rmv)
##### Calculated date12_to_drop v.s. existing date12_to_drop
# Get list of date12 of interferograms already been marked to drop
k = readfile.read_attribute(inps.file[0])['FILE_TYPE']
h5 = h5py.File(inps.file[0], 'r')
ifgram_list_all = sorted(h5[k].keys())
ifgram_list_keep = ut.check_drop_ifgram(h5,
atr,
ifgram_list_all,
print_msg=False)
ifgram_list_dropped = sorted(
list(set(ifgram_list_all) - set(ifgram_list_keep)))
date12_list_dropped = ptime.list_ifgram2date12(ifgram_list_dropped)
h5.close()
if date12_to_rmv == date12_list_dropped and inps.mark_attribute:
print(
'Calculated date12 to drop is the same as exsiting marked input file, skip update file attributes.'
)
return
##### Update date12 to drop
if date12_to_rmv:
##### Update Input Files with date12_to_rmv
Modified_CoherenceFile = 'Modified_coherence.h5'
for File in inps.file:
Modified_File = modify_file_date12_list(File, date12_to_rmv,
inps.mark_attribute)
k = readfile.read_attribute(File)['FILE_TYPE']
# Update Mask File
if k == 'interferograms':
print('update mask file for input ' + k + ' file based on ' +
Modified_File)
inps.mask_file = 'mask.h5'
print('writing >>> ' + inps.mask_file)
ut.nonzero_mask(Modified_File, inps.mask_file)
elif k == 'coherence':
print('update average spatial coherence for input ' + k +
' file based on: ' + Modified_File)
outFile = 'averageSpatialCoherence.h5'
print('writing >>> ' + outFile)
ut.temporal_average(Modified_File, outFile)
Modified_CoherenceFile = Modified_File
# Plot result
if inps.plot:
print('\nplot modified network and save to file.')
plotCmd = 'plot_network.py ' + Modified_File + ' --coherence ' + Modified_CoherenceFile + ' --nodisplay'
if inps.mask_file:
plotCmd += ' --mask ' + inps.mask_file
print(plotCmd)
os.system(plotCmd)
print('Done.')
return
else:
print('No new interferograms to drop, skip update.')
return
def file_operation(fname, operator, operand, fname_out=None):
'''Mathmathic operation of file'''
# Basic Info
atr = readfile.read_attribute(fname)
k = atr['FILE_TYPE']
print('input is '+k+' file: '+fname)
print('operation: file %s %f' % (operator, operand))
# default output filename
if not fname_out:
if operator in ['+','plus', 'add', 'addition']: suffix = 'plus'
elif operator in ['-','minus', 'substract','substraction']: suffix = 'minus'
elif operator in ['*','times', 'multiply', 'multiplication']: suffix = 'multiply'
elif operator in ['/','obelus','divide', 'division']: suffix = 'divide'
elif operator in ['^','pow','power']: suffix = 'pow'
ext = os.path.splitext(fname)[1]
fname_out = os.path.splitext(fname)[0]+'_'+suffix+str(operand)+ext
##### Multiple Dataset HDF5 File
if k in multi_group_hdf5_file+multi_dataset_hdf5_file:
h5 = h5py.File(fname,'r')
epoch_list = sorted(h5[k].keys())
epoch_num = len(epoch_list)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
h5out = h5py.File(fname_out,'w')
group = h5out.create_group(k)
print('writing >>> '+fname_out)
if k == 'timeseries':
print('number of acquisitions: '+str(epoch_num))
for i in range(epoch_num):
date = epoch_list[i]
data = h5[k].get(date)[:]
data_out = data_operation(data, operator, operand)
dset = group.create_dataset(date, data=data_out, compression='gzip')
prog_bar.update(i+1, suffix=date)
for key,value in atr.items():
group.attrs[key] = value
elif k in ['interferograms','wrapped','coherence']:
print('number of interferograms: '+str(epoch_num))
date12_list = ptime.list_ifgram2date12(epoch_list)
for i in range(epoch_num):
ifgram = epoch_list[i]
data = h5[k][ifgram].get(ifgram)[:]
data_out = data_operation(data, operator, operand)
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram, data=data_out, compression='gzip')
for key, value in h5[k][ifgram].attrs.items():
gg.attrs[key] = value
prog_bar.update(i+1, suffix=date12_list[i])
h5.close()
h5out.close()
prog_bar.close()
##### Duo datasets non-HDF5 File
elif k in ['.trans']:
rg, az, atr = readfile.read(fname)
rg_out = data_operation(rg, operator, operand)
az_out = data_operation(az, operator, operand)
print('writing >>> '+fname_out)
writefile.write(rg_out, az_out, atr, fname_out)
##### Single Dataset File
else:
data, atr = readfile.read(fname)
data_out = data_operation(data, operator, operand)
print('writing >>> '+fname_out)
writefile.write(data_out, atr, fname_out)
return fname_out
def subset_file(File, subset_dict_input, outFile=None):
'''Subset file with
Inputs:
File : str, path/name of file
outFile : str, path/name of output file
subset_dict : dict, subsut parameter, including the following items:
subset_x : list of 2 int, subset in x direction, default=None
subset_y : list of 2 int, subset in y direction, default=None
subset_lat : list of 2 float, subset in lat direction, default=None
subset_lon : list of 2 float, subset in lon direction, default=None
fill_value : float, optional. filled value for area outside of data coverage. default=None
None/not-existed to subset within data coverage only.
tight : bool, tight subset or not, for lookup table file, i.e. geomap*.trans
Outputs:
outFile : str, path/name of output file;
outFile = 'subset_'+File, if File is in current directory;
outFile = File, if File is not in the current directory.
'''
# Input File Info
try:
atr_dict = readfile.read_attribute(File)
except:
return None
width = int(atr_dict['WIDTH'])
length = int(atr_dict['FILE_LENGTH'])
k = atr_dict['FILE_TYPE']
print('subset ' + k + ' file: ' + File + ' ...')
subset_dict = subset_dict_input.copy()
# Read Subset Inputs into 4-tuple box in pixel and geo coord
pix_box, geo_box = subset_input_dict2box(subset_dict, atr_dict)
# if fill_value exists and not None, subset data and fill assigned value for area out of its coverage.
# otherwise, re-check subset to make sure it's within data coverage and initialize the matrix with np.nan
outfill = False
if 'fill_value' in list(subset_dict.keys()) and subset_dict['fill_value']:
outfill = True
else:
outfill = False
if not outfill:
pix_box = check_box_within_data_coverage(pix_box, atr_dict)
subset_dict['fill_value'] = np.nan
geo_box = box_pixel2geo(pix_box, atr_dict)
data_box = (0, 0, width, length)
print('data range in y/x: ' + str(data_box))
print('subset range in y/x: ' + str(pix_box))
print('data range in lat/lon: ' + str(box_pixel2geo(data_box, atr_dict)))
print('subset range in lat/lon: ' + str(geo_box))
if pix_box == data_box:
print('Subset range == data coverage, no need to subset. Skip.')
return File
# Calculate Subset/Overlap Index
pix_box4data, pix_box4subset = get_box_overlap_index(data_box, pix_box)
########################### Data Read and Write ######################
# Output File Name
if not outFile:
if os.getcwd() == os.path.dirname(os.path.abspath(File)):
if 'tight' in list(subset_dict.keys()) and subset_dict['tight']:
outFile = os.path.splitext(
File)[0] + '_tight' + os.path.splitext(File)[1]
else:
outFile = 'subset_' + os.path.basename(File)
else:
outFile = os.path.basename(File)
print('writing >>> ' + outFile)
##### Multiple Dataset File
if k in ['timeseries', 'interferograms', 'wrapped', 'coherence']:
##### Open Input File
h5file = h5py.File(File, 'r')
epochList = sorted(h5file[k].keys())
epochNum = len(epochList)
if k in multi_dataset_hdf5_file:
print('number of acquisitions: ' + str(epochNum))
else:
print('number of interferograms: ' + str(epochNum))
##### Open Output File
h5out = h5py.File(outFile)
group = h5out.create_group(k)
prog_bar = ptime.progress_bar(maxValue=epochNum)
## Loop
if k == 'timeseries':
for i in range(epochNum):
epoch = epochList[i]
dset = h5file[k].get(epoch)
data_overlap = dset[pix_box4data[1]:pix_box4data[3],
pix_box4data[0]:pix_box4data[2]]
data = np.ones(
(pix_box[3] - pix_box[1],
pix_box[2] - pix_box[0])) * subset_dict['fill_value']
data[pix_box4subset[1]:pix_box4subset[3],
pix_box4subset[0]:pix_box4subset[2]] = data_overlap
dset = group.create_dataset(epoch, data=data, compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
atr_dict = subset_attribute(atr_dict, pix_box)
for key, value in atr_dict.items():
group.attrs[key] = value
elif k in ['interferograms', 'wrapped', 'coherence']:
date12_list = ptime.list_ifgram2date12(epochList)
for i in range(epochNum):
epoch = epochList[i]
dset = h5file[k][epoch].get(epoch)
atr_dict = h5file[k][epoch].attrs
data_overlap = dset[pix_box4data[1]:pix_box4data[3],
pix_box4data[0]:pix_box4data[2]]
data = np.ones(
(pix_box[3] - pix_box[1],
pix_box[2] - pix_box[0])) * subset_dict['fill_value']
data[pix_box4subset[1]:pix_box4subset[3],
pix_box4subset[0]:pix_box4subset[2]] = data_overlap
atr_dict = subset_attribute(atr_dict, pix_box, print_msg=False)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in atr_dict.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
##### Single Dataset File
elif k in ['.jpeg', '.jpg', '.png', '.ras', '.bmp']:
data, atr_dict = readfile.read(File, pix_box)
atr_dict = subset_attribute(atr_dict, pix_box)
writefile.write(data, atr_dict, outFile)
elif k == '.trans':
rg_overlap, az_overlap, atr_dict = readfile.read(File, pix_box4data)
rg = np.ones((pix_box[3] - pix_box[1],
pix_box[2] - pix_box[0])) * subset_dict['fill_value']
rg[pix_box4subset[1]:pix_box4subset[3],
pix_box4subset[0]:pix_box4subset[2]] = rg_overlap
az = np.ones((pix_box[3] - pix_box[1],
pix_box[2] - pix_box[0])) * subset_dict['fill_value']
az[pix_box4subset[1]:pix_box4subset[3],
pix_box4subset[0]:pix_box4subset[2]] = az_overlap
atr_dict = subset_attribute(atr_dict, pix_box)
writefile.write(rg, az, atr_dict, outFile)
else:
data_overlap, atr_dict = readfile.read(File, pix_box4data)
data = np.ones((pix_box[3] - pix_box[1],
pix_box[2] - pix_box[0])) * subset_dict['fill_value']
data[pix_box4subset[1]:pix_box4subset[3],
pix_box4subset[0]:pix_box4subset[2]] = data_overlap
atr_dict = subset_attribute(atr_dict, pix_box)
writefile.write(data, atr_dict, outFile)
##### End Cleaning
try:
prog_bar.close()
h5file.close()
h5out.close()
except:
pass
return outFile
def modify_file_date12_list(File,
date12_to_rmv,
mark_attribute=False,
outFile=None):
'''Update multiple group hdf5 file using date12 to remove
Inputs:
File - multi_group HDF5 file, i.e. unwrapIfgram.h5, coherence.h5
date12_to_rmv - list of string indicating interferograms in YYMMDD-YYMMDD format
mark_attribute- bool, if True, change 'drop_ifgram' attribute only; otherwise, write
resutl to a new file
outFile - string, output file name
Output:
outFile - string, output file name, if mark_attribute=True, outFile = File
'''
k = readfile.read_attribute(File)['FILE_TYPE']
print(
'----------------------------------------------------------------------------'
)
print('file: ' + File)
if mark_attribute:
print(
"set drop_ifgram to 'yes' for all interferograms to remove, and 'no' for all the others."
)
h5 = h5py.File(File, 'r+')
ifgram_list = sorted(h5[k].keys())
for ifgram in ifgram_list:
if h5[k][ifgram].attrs['DATE12'] in date12_to_rmv:
h5[k][ifgram].attrs['drop_ifgram'] = 'yes'
else:
h5[k][ifgram].attrs['drop_ifgram'] = 'no'
h5.close()
outFile = File
else:
date12_orig = pnet.get_date12_list(File)
date12_to_write = sorted(list(set(date12_orig) - set(date12_to_rmv)))
print('number of interferograms in file : ' +
str(len(date12_orig)))
print('number of interferograms to keep/write: ' +
str(len(date12_to_write)))
print('list of interferograms to keep/write: ')
print(date12_to_write)
date12Num = len(date12_to_write)
if not outFile:
outFile = 'Modified_' + os.path.basename(File)
print('writing >>> ' + outFile)
h5out = h5py.File(outFile, 'w')
gg = h5out.create_group(k)
h5 = h5py.File(File, 'r')
igramList = sorted(h5[k].keys())
date12_list = ptime.list_ifgram2date12(igramList)
prog_bar = ptime.progress_bar(maxValue=date12Num, prefix='writing: ')
for i in range(date12Num):
date12 = date12_to_write[i]
idx = date12_orig.index(date12)
igram = igramList[idx]
data = h5[k][igram].get(igram)[:]
group = gg.create_group(igram)
dset = group.create_dataset(igram, data=data, compression='gzip')
for key, value in h5[k][igram].attrs.items():
group.attrs[key] = value
group.attrs['drop_ifgram'] = 'no'
prog_bar.update(i + 1, suffix=date12_list[i])
prog_bar.close()
h5.close()
h5out.close()
print('finished writing >>> ' + outFile)
return outFile
def add_files(fname_list, fname_out=None):
'''Generate sum of all input files
Inputs:
fname_list - list of string, path/name of input files to be added
fname_out - string, optional, path/name of output file
Output:
fname_out - string, path/name of output file
Example:
'mask_all.h5' = add_file(['mask_1.h5','mask_2.h5','mask_3.h5'], 'mask_all.h5')
'''
# Default output file name
ext = os.path.splitext(fname_list[0])[1]
if not fname_out:
fname_out = os.path.splitext(fname_list[0])[0]
for i in range(1, len(fname_list)):
fname_out += '_plus_' + os.path.splitext(
os.path.basename(fname_list[i]))[0]
fname_out += ext
# Basic Info
atr = readfile.read_attribute(fname_list[0])
k = atr['FILE_TYPE']
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
print('First input file is ' + atr['PROCESSOR'] + ' ' + k)
## Multi-dataset/group file
if k in multi_group_hdf5_file + multi_dataset_hdf5_file:
# File Type Check
for i in range(1, len(fname_list)):
ki = readfile.read_attribute(fname_list[i])['FILE_TYPE']
if (k in multi_dataset_hdf5_file and ki in multi_dataset_hdf5_file
or k in multi_group_hdf5_file
and ki in multi_group_hdf5_file):
pass
else:
print('Input files structure are not the same: ' + k +
' v.s. ' + ki)
sys.exit(1)
print('writing >>> ' + fname_out)
h5out = h5py.File(fname_out, 'w')
group = h5out.create_group(k)
h5 = h5py.File(fname_list[0], 'r')
epoch_list = sorted(h5[k].keys())
epoch_num = len(epoch_list)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
if k in multi_dataset_hdf5_file:
print('number of acquisitions: %d' % epoch_num)
for i in range(epoch_num):
epoch = epoch_list[i]
data = np.zeros((length, width))
for fname in fname_list:
h5file = h5py.File(fname, 'r')
d = h5file[k].get(epoch)[:]
data = add_matrix(data, d)
dset = group.create_dataset(epoch, data=data, compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
for key, value in atr.items():
group.attrs[key] = value
h5out.close()
h5.close()
prog_bar.close()
elif k in multi_group_hdf5_file:
print('number of interferograms: %d' % epoch_num)
date12_list = ptime.list_ifgram2date12(epoch_list)
for i in range(epoch_num):
epoch = epoch_list[i]
data = np.zeros((length, width))
for fname in fname_list:
h5file = h5py.File(fname, 'r')
temp_k = list(h5file.keys())[0]
temp_epoch_list = sorted(h5file[temp_k].keys())
d = h5file[temp_k][temp_epoch_list[i]].get(
temp_epoch_list[i])[:]
data = add_matrix(data, d)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in h5[k][epoch].attrs.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
h5out.close()
h5.close()
prog_bar.close()
## Single dataset files
else:
data = np.zeros((length, width))
for fname in fname_list:
print('loading ' + fname)
d, r = readfile.read(fname)
data = add_matrix(data, d)
print('writing >>> ' + fname_out)
writefile.write(data, atr, fname_out)
return fname_out
def remove_surface(File, surf_type, maskFile=None, outFile=None, ysub=None):
start = time.time()
atr = readfile.read_attribute(File)
# Output File Name
if not outFile:
outFile = os.path.splitext(
File)[0] + '_' + surf_type + os.path.splitext(File)[1]
if maskFile:
Mask = readfile.read(maskFile)[0]
print('read mask file: ' + maskFile)
else:
Mask = np.ones((int(atr['FILE_LENGTH']), int(atr['WIDTH'])))
print('use mask of the whole area')
##### Input File Info
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
print('Input file is ' + k)
print('remove ramp type: ' + surf_type)
## Multiple Datasets File
if k in ['interferograms', 'coherence', 'wrapped', 'timeseries']:
h5file = h5py.File(File, 'r')
epochList = sorted(h5file[k].keys())
epoch_num = len(epochList)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
h5flat = h5py.File(outFile, 'w')
group = h5flat.create_group(k)
print('writing >>> ' + outFile)
if k in ['timeseries']:
print('number of acquisitions: ' + str(len(epochList)))
for i in range(epoch_num):
epoch = epochList[i]
data = h5file[k].get(epoch)[:]
if not ysub:
data_n, ramp = remove_data_surface(data, Mask, surf_type)
else:
data_n = remove_data_multiple_surface(data, Mask, surf_type,
ysub)
dset = group.create_dataset(epoch, data=data_n, compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
for key, value in h5file[k].attrs.items():
group.attrs[key] = value
elif k in ['interferograms', 'wrapped', 'coherence']:
print('number of interferograms: ' + str(len(epochList)))
date12_list = ptime.list_ifgram2date12(epochList)
for i in range(epoch_num):
epoch = epochList[i]
data = h5file[k][epoch].get(epoch)[:]
if not ysub:
data_n, ramp = remove_data_surface(data, Mask, surf_type)
else:
data_n = remove_data_multiple_surface(data, Mask, surf_type,
ysub)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data_n, compression='gzip')
for key, value in h5file[k][epoch].attrs.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
## Single Dataset File
else:
data, atr = readfile.read(File)
print('Removing ' + surf_type + ' from ' + k)
if not ysub:
data_n, ramp = remove_data_surface(data, Mask, surf_type)
else:
data_n = remove_data_multiple_surface(data, Mask, surf_type, ysub)
print('writing >>> ' + outFile)
writefile.write(data_n, atr, outFile)
try:
h5file.close()
h5flat.close()
prog_bar.close()
except:
pass
print('Remove ' + surf_type + ' took ' + str(time.time() - start) +
' secs')
return outFile
def main(argv):
inps = cmdLineParse()
atr = readfile.read_attribute(inps.velocity_file)
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
# Check subset input
if inps.subset_y:
inps.subset_y = sorted(inps.subset_y)
print('subset in y/azimuth direction: ' + str(inps.subset_y))
else:
inps.subset_y = [0, length]
if inps.subset_x:
inps.subset_x = sorted(inps.subset_x)
print('subset in x/range direction: ' + str(inps.subset_x))
else:
inps.subset_x = [0, width]
y0, y1 = inps.subset_y
x0, x1 = inps.subset_x
# Read velocity/rate
velocity = readfile.read(inps.velocity_file)[0]
print('read velocity file: ' + inps.velocity_file)
k = 'interferograms'
h5 = h5py.File(inps.ifgram_file, 'r')
ifgram_list = sorted(h5[k].keys())
ifgram_num = len(ifgram_list)
date12_list = ptime.list_ifgram2date12(ifgram_list)
print('number of interferograms: ' + str(ifgram_num))
##### Select interferograms with unwrapping error
if inps.percentage > 0.0:
mask = readfile.read(inps.mask_file)[0]
print('read mask for pixels with unwrapping error from file: ' +
inps.mask_file)
unw_err_ifgram_num = int(np.rint(inps.percentage * ifgram_num))
unw_err_ifgram_idx = random.sample(list(range(ifgram_num)),
unw_err_ifgram_num)
unw_err_ifgram_list = [ifgram_list[i] for i in unw_err_ifgram_idx]
unw_err_date12_list = [date12_list[i] for i in unw_err_ifgram_idx]
print(
'randomly choose the following %d interferograms with unwrapping error'
% unw_err_ifgram_num)
print(unw_err_date12_list)
unit_unw_err = 2.0 * np.pi * mask
else:
unw_err_ifgram_list = []
###### Generate simulated interferograms
m_dates = ptime.yyyymmdd([i.split('-')[0] for i in date12_list])
s_dates = ptime.yyyymmdd([i.split('-')[1] for i in date12_list])
range2phase = -4.0 * np.pi / float(atr['WAVELENGTH'])
print('writing simulated interferograms file: ' + inps.outfile)
h5out = h5py.File(inps.outfile, 'w')
group = h5out.create_group('interferograms')
for i in range(ifgram_num):
ifgram = ifgram_list[i]
# Get temporal baseline in years
t1 = datetime.datetime(*time.strptime(m_dates[i], "%Y%m%d")[0:5])
t2 = datetime.datetime(*time.strptime(s_dates[i], "%Y%m%d")[0:5])
dt = (t2 - t1)
dt = float(dt.days) / 365.25
# Simuated interferograms with unwrap error
unw = velocity * dt * range2phase
if ifgram in unw_err_ifgram_list:
rand_int = random.sample(list(range(1, 10)), 1)[0]
unw += rand_int * unit_unw_err
print(ifgram + ' - add unwrapping error of %d*2*pi' % rand_int)
else:
print(ifgram)
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram,
data=unw[y0:y1, x0:x1],
compression='gzip')
for key, value in h5[k][ifgram].attrs.items():
gg.attrs[key] = value
if ifgram in unw_err_ifgram_list:
gg.attrs['unwrap_error'] = 'yes'
else:
gg.attrs['unwrap_error'] = 'no'
gg.attrs['FILE_LENGTH'] = y1 - y0
gg.attrs['WIDTH'] = x1 - x0
h5.close()
h5out.close()
print('Done.')
return inps.outfile
def main(argv):
##### Inputs
try:
ifgram_file = argv[0]
timeseries_file = argv[1]
except:
usage()
sys.exit(1)
try:
outfile = argv[2]
except:
outfile = 'reconstructed_' + ifgram_file
atr = readfile.read_attribute(timeseries_file)
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
##### Read time-series file
print('loading timeseries ...')
h5ts = h5py.File(timeseries_file, 'r')
date_list = sorted(h5ts['timeseries'].keys())
date_num = len(date_list)
timeseries = np.zeros((date_num, length * width))
print('number of acquisitions: ' + str(date_num))
prog_bar = ptime.progress_bar(maxValue=date_num)
for i in range(date_num):
date = date_list[i]
d = h5ts['timeseries'].get(date)[:]
timeseries[i, :] = d.flatten(0)
prog_bar.update(i + 1, suffix=date)
prog_bar.close()
h5ts.close()
del d
range2phase = -4 * np.pi / float(atr['WAVELENGTH'])
timeseries = range2phase * timeseries
##### Estimate interferograms from timeseries
print(
'estimating interferograms from timeseries using design matrix from input interferograms'
)
A, B = ut.design_matrix(ifgram_file)
p = -1 * np.ones([A.shape[0], 1])
Ap = np.hstack((p, A))
estData = np.dot(Ap, timeseries)
del timeseries
##### Write interferograms file
print('writing >>> ' + outfile)
h5 = h5py.File(ifgram_file, 'r')
ifgram_list = sorted(h5['interferograms'].keys())
ifgram_num = len(ifgram_list)
date12_list = ptime.list_ifgram2date12(ifgram_list)
h5out = h5py.File(outfile, 'w')
group = h5out.create_group('interferograms')
print('number of interferograms: ' + str(ifgram_num))
prog_bar = ptime.progress_bar(maxValue=ifgram_num)
for i in range(ifgram_num):
ifgram = ifgram_list[i]
data = np.reshape(estData[i, :], (length, width))
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram, data=data, compression='gzip')
for key, value in h5['interferograms'][ifgram].attrs.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
prog_bar.close()
h5.close()
h5out.close()
print('Done.')
return outfile
def multilook_file(infile, lks_y, lks_x, outfile=None):
lks_y = int(lks_y)
lks_x = int(lks_x)
## input file info
atr = readfile.read_attribute(infile)
k = atr['FILE_TYPE']
print('multilooking ' + k + ' file ' + infile)
print('number of looks in y / azimuth direction: %d' % lks_y)
print('number of looks in x / range direction: %d' % lks_x)
## output file name
if not outfile:
if os.getcwd() == os.path.dirname(os.path.abspath(infile)):
ext = os.path.splitext(infile)[1]
outfile = os.path.splitext(infile)[0] + '_' + str(
lks_y) + 'alks_' + str(lks_x) + 'rlks' + ext
else:
outfile = os.path.basename(infile)
print('writing >>> ' + outfile)
###############################################################################
## Read/Write multi-dataset files
if k in ['interferograms', 'coherence', 'wrapped', 'timeseries']:
h5 = h5py.File(infile, 'r')
epochList = sorted(h5[k].keys())
epoch_num = len(epochList)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
h5out = h5py.File(outfile, 'w')
group = h5out.create_group(k)
if k in ['interferograms', 'coherence', 'wrapped']:
date12_list = ptime.list_ifgram2date12(epochList)
print('number of interferograms: ' + str(len(epochList)))
for i in range(epoch_num):
epoch = epochList[i]
data = h5[k][epoch].get(epoch)[:]
atr = h5[k][epoch].attrs
data_mli = multilook_matrix(data, lks_y, lks_x)
atr_mli = multilook_attribute(atr,
lks_y,
lks_x,
print_msg=False)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch,
data=data_mli,
compression='gzip')
for key, value in atr_mli.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
elif k == 'timeseries':
print('number of acquisitions: ' + str(len(epochList)))
for i in range(epoch_num):
epoch = epochList[i]
data = h5[k].get(epoch)[:]
data_mli = multilook_matrix(data, lks_y, lks_x)
dset = group.create_dataset(epoch,
data=data_mli,
compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
atr = h5[k].attrs
atr_mli = multilook_attribute(atr, lks_y, lks_x)
for key, value in atr_mli.items():
group.attrs[key] = value
h5.close()
h5out.close()
prog_bar.close()
## Read/Write single-dataset files
elif k == '.trans':
rg, az, atr = readfile.read(infile)
rgmli = multilook_matrix(rg, lks_y, lks_x)
#rgmli *= 1.0/lks_x
azmli = multilook_matrix(az, lks_y, lks_x)
#azmli *= 1.0/lks_y
atr = multilook_attribute(atr, lks_y, lks_x)
writefile.write(rgmli, azmli, atr, outfile)
else:
data, atr = readfile.read(infile)
data_mli = multilook_matrix(data, lks_y, lks_x)
atr = multilook_attribute(atr, lks_y, lks_x)
writefile.write(data_mli, atr, outfile)
return outfile
def filter_file(fname, filter_type, filter_par=None, fname_out=None):
'''Filter 2D matrix with selected filter
Inputs:
fname : string, name/path of file to be filtered
filter_type : string, filter type
filter_par : string, optional, parameter for low/high pass filter
for low/highpass_avg, it's kernel size in int
for low/highpass_gaussain, it's sigma in float
Output:
fname_out : string, optional, output file name/path
'''
# Basic info
atr = readfile.read_attribute(fname)
k = atr['FILE_TYPE']
try:
ref_yx = [int(atr['ref_y']), int(atr['ref_x'])]
except:
ref_yx = None
filter_type = filter_type.lower()
MSG = 'filtering ' + k + ' file: ' + fname + ' using ' + filter_type + ' filter'
if filter_type.endswith('avg'):
if not filter_par:
filter_par = 5
MSG += ' with kernel size of %d' % int(filter_par)
elif filter_type.endswith('gaussian'):
if not filter_par:
filter_par = 3.0
MSG += ' with sigma of %.1f' % filter_par
print(MSG)
if not fname_out:
ext = os.path.splitext(fname)[1]
fname_out = os.path.splitext(fname)[0] + '_' + filter_type + ext
##### Multiple Dataset File
if k in multi_group_hdf5_file + multi_dataset_hdf5_file:
h5 = h5py.File(fname, 'r')
epoch_list = sorted(h5[k].keys())
epoch_num = len(epoch_list)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
h5out = h5py.File(fname_out, 'w')
group = h5out.create_group(k)
print('writing >>> ' + fname_out)
if k == 'timeseries':
print('number of acquisitions: ' + str(epoch_num))
for i in range(epoch_num):
date = epoch_list[i]
data = h5[k].get(date)[:]
data_filt = filter_data(data, filter_type, filter_par)
if ref_yx:
data_filt -= data_filt[ref_yx[0], ref_yx[1]]
dset = group.create_dataset(date,
data=data_filt,
compression='gzip')
prog_bar.update(i + 1, suffix=date)
for key, value in atr.items():
group.attrs[key] = value
elif k in ['interferograms', 'wrapped', 'coherence']:
print('number of interferograms: ' + str(epoch_num))
date12_list = ptime.list_ifgram2date12(epoch_list)
for i in range(epoch_num):
ifgram = epoch_list[i]
data = h5[k][ifgram].get(ifgram)[:]
data_filt = filter_data(data, filter_type, filter_par)
if ref_yx and k in ['interferograms']:
data_filt -= data_filt[ref_yx[0], ref_yx[1]]
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram,
data=data_filt,
compression='gzip')
for key, value in h5[k][ifgram].attrs.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
h5.close()
h5out.close()
prog_bar.close()
##### Single Dataset File
else:
data, atr = readfile.read(fname)
data_filt = filter_data(data, filter_type, filter_par)
if ref_yx and k in ['.unw', 'velocity']:
data_filt -= data_filt[ref_yx[0], ref_yx[1]]
print('writing >>> ' + fname_out)
writefile.write(data_filt, atr, fname_out)
return fname_out
def geocode_file_with_geo_lut(fname,
lut_file=None,
method='nearest',
fill_value=np.nan,
fname_out=None):
'''Geocode file using ROI_PAC/Gamma lookup table file.
Related module: scipy.interpolate.RegularGridInterpolator
Inputs:
fname : string, file to be geocoded
lut_file : string, optional, lookup table file genereated by ROIPAC or Gamma
i.e. geomap_4rlks.trans from ROI_PAC
sim_150911-150922.UTM_TO_RDC from Gamma
method : string, optional, interpolation/resampling method, supporting nearest, linear
fill_value : value used for points outside of the interpolation domain.
If None, values outside the domain are extrapolated.
fname_out : string, optional, output geocoded filename
Output:
fname_out : string, optional, output geocoded filename
'''
start = time.time()
## Default Inputs and outputs
if not fname_out:
fname_out = 'geo_' + fname
# Default lookup table file:
atr_rdr = readfile.read_attribute(fname)
if not lut_file:
if atr_rdr['INSAR_PROCESSOR'] == 'roipac':
lut_file = ['geomap*lks_tight.trans', 'geomap*lks.trans']
elif atr_rdr['INSAR_PROCESSOR'] == 'gamma':
lut_file = ['sim*_tight.UTM_TO_RDC', 'sim*.UTM_TO_RDC']
try:
lut_file = ut.get_file_list(lut_file)[0]
except:
lut_file = None
if not lut_file:
sys.exit(
'ERROR: No lookup table file found! Can not geocoded without it.')
## Original coordinates: row/column number in radar file
print('------------------------------------------------------')
print('geocoding file: ' + fname)
len_rdr = int(atr_rdr['FILE_LENGTH'])
wid_rdr = int(atr_rdr['WIDTH'])
pts_rdr = (np.arange(len_rdr), np.arange(wid_rdr))
## New coordinates: data value in lookup table
print('reading lookup table file: ' + lut_file)
rg, az, atr_lut = readfile.read(lut_file)
len_geo = int(atr_lut['FILE_LENGTH'])
wid_geo = int(atr_lut['WIDTH'])
# adjustment if input radar file has been subseted.
if 'subset_x0' in list(atr_rdr.keys()):
x0 = float(atr_rdr['subset_x0'])
y0 = float(atr_rdr['subset_y0'])
rg -= x0
az -= y0
print(
'\tinput radar coord file has been subsetted, adjust lookup table value'
)
# extract pixels only available in radar file (get ride of invalid corners)
idx = (az > 0.0) * (az <= len_rdr) * (rg > 0.0) * (rg <= wid_rdr)
pts_geo = np.hstack((az[idx].reshape(-1, 1), rg[idx].reshape(-1, 1)))
del az, rg
print('geocoding using scipy.interpolate.RegularGridInterpolator ...')
data_geo = np.empty((len_geo, wid_geo)) * fill_value
k = atr_rdr['FILE_TYPE']
##### Multiple Dataset File
if k in multi_group_hdf5_file + multi_dataset_hdf5_file:
h5 = h5py.File(fname, 'r')
epoch_list = sorted(h5[k].keys())
epoch_num = len(epoch_list)
prog_bar = ptime.progress_bar(maxValue=epoch_num)
h5out = h5py.File(fname_out, 'w')
group = h5out.create_group(k)
print('writing >>> ' + fname_out)
if k == 'timeseries':
print('number of acquisitions: ' + str(epoch_num))
for i in range(epoch_num):
date = epoch_list[i]
data = h5[k].get(date)[:]
RGI_func = RGI(pts_rdr,
data,
method,
bounds_error=False,
fill_value=fill_value)
data_geo.fill(fill_value)
data_geo[idx] = RGI_func(pts_geo)
dset = group.create_dataset(date,
data=data_geo,
compression='gzip')
prog_bar.update(i + 1, suffix=date)
prog_bar.close()
print('update attributes')
atr = geocode_attribute_with_geo_lut(atr_rdr, atr_lut)
for key, value in atr.items():
group.attrs[key] = value
elif k in ['interferograms', 'wrapped', 'coherence']:
print('number of interferograms: ' + str(epoch_num))
date12_list = ptime.list_ifgram2date12(epoch_list)
for i in range(epoch_num):
ifgram = epoch_list[i]
data = h5[k][ifgram].get(ifgram)[:]
RGI_func = RGI(pts_rdr,
data,
method,
bounds_error=False,
fill_value=fill_value)
data_geo.fill(fill_value)
data_geo[idx] = RGI_func(pts_geo)
gg = group.create_group(ifgram)
dset = gg.create_dataset(ifgram,
data=data_geo,
compression='gzip')
atr = geocode_attribute_with_geo_lut(h5[k][ifgram].attrs,
atr_lut,
print_msg=False)
for key, value in atr.items():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12_list[i])
h5.close()
h5out.close()
##### Single Dataset File
else:
print('reading ' + fname)
data = readfile.read(fname)[0]
RGI_func = RGI(pts_rdr,
data,
method,
bounds_error=False,
fill_value=fill_value)
data_geo.fill(fill_value)
data_geo[idx] = RGI_func(pts_geo)
print('update attributes')
atr = geocode_attribute_with_geo_lut(atr_rdr, atr_lut)
print('writing >>> ' + fname_out)
writefile.write(data_geo, atr, fname_out)
del data_geo
s = time.time() - start
m, s = divmod(s, 60)
h, m = divmod(m, 60)
print('Time used: %02d hours %02d mins %02d secs' % (h, m, s))
return fname_out