def main(argv):
inps = cmdLineParse()
print '\n*************** Spatial Average ******************'
for File in inps.file:
mean_list, date_list = ut.spatial_average(File,
inps.mask_file,
saveList=True)
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
if inps.disp_fig and k == 'timeseries':
dates, datevector = ptime.date_list2vector(date_list)
# plot
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(dates,
mean_list,
'-ko',
lw=2,
ms=16,
alpha=0.7,
mfc='crimson')
ax.set_title('Spatial Average', fontsize=12)
ax = ptime.auto_adjust_xaxis_date(ax, datevector)[0]
ax.set_xlabel('Time [years]', fontsize=12)
ax.set_ylabel('Mean', fontsize=12)
plt.show()
def main(argv):
inps = cmdLineParse()
print '\n*************** Spatial Average ******************'
if inps.mask_file:
print 'reading mask file: ' + inps.mask_file
mask, mask_atr = readfile.read(inps.mask_file)
else:
mask = None
for File in inps.file:
mean_list = ut.spatial_average(File, mask, saveList=True)
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
if inps.disp_fig and k == 'timeseries':
# Get date list
h5file = h5py.File(File)
dateList = sorted(h5file[k].keys())
h5file.close()
dates, datevector = ptime.date_list2vector(dateList)
# plot
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(dates,
mean_list,
'-ko',
lw=2,
ms=16,
alpha=0.7,
mfc='crimson')
ax.set_title('Spatial Average', fontsize=12)
ax = ptime.auto_adjust_xaxis_date(ax, datevector)[0]
ax.set_xlabel('Time [years]', fontsize=12)
ax.set_ylabel('Mean', fontsize=12)
plt.show()
def main(argv):
inps = cmdLineParse()
if not inps.disp_fig:
plt.switch_backend('Agg')
if inps.template_file:
inps = read_template2inps(inps.template_file, inps)
##### 1. Read Info
# Read dateList and bperpList
ext = os.path.splitext(inps.file)[1]
if ext in ['.h5']:
atr = readfile.read_attribute(inps.file)
k = atr['FILE_TYPE']
print 'reading date and perpendicular baseline from ' + k + ' file: ' + os.path.basename(
inps.file)
if not k in multi_group_hdf5_file:
raise ValueError('only the following file type are supported:\n' +
str(multi_group_hdf5_file))
if not inps.coherence_file and k == 'coherence':
inps.coherence_file = inps.file
pbase_list = ut.perp_baseline_ifgram2timeseries(inps.file)[0]
date8_list = ptime.ifgram_date_list(inps.file)
else:
print 'reading date and perpendicular baseline from baseline list file: ' + inps.bl_list_file
date8_list, pbase_list = pnet.read_baseline_file(
inps.bl_list_file)[0:2]
print 'number of acquisitions : ' + str(len(date8_list))
# Read Pairs Info
print 'reading pairs info from file: ' + inps.file
date12_list = pnet.get_date12_list(inps.file)
print 'number of interferograms: ' + str(len(date12_list))
# Read drop_ifgram
date8_list_drop = []
date12_list_drop = []
if ext in ['.h5', '.he5']:
h5 = h5py.File(inps.file, 'r')
ifgram_list_all = sorted(h5[k].keys())
ifgram_list_keep = ut.check_drop_ifgram(h5)
date12_list_keep = ptime.list_ifgram2date12(ifgram_list_keep)
# Get date12_list_drop
date12_list_drop = sorted(
list(set(date12_list) - set(date12_list_keep)))
print 'number of interferograms marked as dropped: ' + str(
len(date12_list_drop))
print 'number of interferograms marked as kept : ' + str(
len(date12_list_keep))
# Get date_list_drop
m_dates = [i.split('-')[0] for i in date12_list_keep]
s_dates = [i.split('-')[1] for i in date12_list_keep]
date8_list_keep = ptime.yyyymmdd(sorted(list(set(m_dates + s_dates))))
date8_list_drop = sorted(list(set(date8_list) - set(date8_list_keep)))
print 'number of acquisitions marked as dropped: ' + str(
len(date8_list_drop))
# Read Coherence List
inps.coherence_list = None
if inps.coherence_file and os.path.isfile(inps.coherence_file):
if inps.mask_file and not os.path.isfile(inps.mask_file):
inps.mask_file = None
inps.coherence_list, inps.coh_date12_list = ut.spatial_average(inps.coherence_file, inps.mask_file, \
saveList=True, checkAoi=False)
if all(np.isnan(inps.coherence_list)):
print 'WARNING: all coherence value are nan! Do not use this and continue.'
inps.coherence_list = None
# Check subset of date12 info between input file and coherence file
if not set(inps.coh_date12_list) >= set(date12_list):
print 'WARNING: not every pair/date12 from input file is in coherence file'
print 'turn off the color plotting of interferograms based on coherence'
inps.coherence_list = None
elif set(inps.coh_date12_list) > set(date12_list):
print 'extract coherence value for all pair/date12 in input file'
inps.coherence_list = [
inps.coherence_list[inps.coh_date12_list.index(i)]
for i in date12_list
]
#inps.coh_thres = 0.7
##### 2. Plot
inps.cbar_label = 'Average spatial coherence'
# Fig 1 - Baseline History
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_perp_baseline_hist(ax, date8_list, pbase_list, vars(inps),
date8_list_drop)
figName = 'BperpHistory' + inps.fig_ext
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight')
print 'save figure to ' + figName
# Fig 2 - Coherence Matrix
if inps.coherence_list:
figName = 'CoherenceMatrix' + inps.fig_ext
if inps.fig_size:
fig = plt.figure(figsize=inps.fig_size)
else:
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_coherence_matrix(ax, date12_list, inps.coherence_list,\
date12_list_drop, plot_dict=vars(inps))
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight', dpi=150)
print 'save figure to ' + figName
# Fig 3 - Min/Max Coherence History
if inps.coherence_list:
figName = 'CoherenceHistory' + inps.fig_ext
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_coherence_history(ax, date12_list, inps.coherence_list)
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight')
print 'save figure to ' + figName
# Fig 4 - Interferogram Network
if inps.fig_size:
fig = plt.figure(figsize=inps.fig_size)
else:
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_network(ax, date12_list, date8_list, pbase_list, vars(inps),
date12_list_drop)
figName = 'Network' + inps.fig_ext
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight')
print 'save figure to ' + figName
if inps.save_list:
txtFile = os.path.splitext(inps.file)[0] + '_date12_list.txt'
np.savetxt(txtFile, date12_list, fmt='%s')
print 'save pairs/date12 info to file: ' + txtFile
if inps.disp_fig:
plt.show()
def main(argv):
inps = cmdLineParse()
if not inps.disp_fig:
plt.switch_backend('Agg')
#print '\n******************** Plot Network **********************'
##### 1. Read Info
# Read dateList and bperpList
ext = os.path.splitext(inps.file)[1]
if ext in ['.h5']:
atr = readfile.read_attribute(inps.file)
k = atr['FILE_TYPE']
print 'reading date and perpendicular baseline from '+k+' file: '+os.path.basename(inps.file)
if not k in multi_group_hdf5_file:
raise ValueError('only the following file type are supported:\n'+str(multi_group_hdf5_file))
pbase_list = ut.perp_baseline_ifgram2timeseries(inps.file)[0]
date8_list = ptime.ifgram_date_list(inps.file)
else:
print 'reading date and perpendicular baseline from baseline list file: '+inps.bl_list_file
date8_list, pbase_list = pnet.read_baseline_file(inps.bl_list_file)[0:2]
print 'number of acquisitions : '+str(len(date8_list))
# Read Pairs Info
print 'reading pairs info from file: '+inps.file
date12_list = pnet.get_date12_list(inps.file)
print 'number of interferograms: '+str(len(date12_list))
# Read drop_ifgram
date8_list_drop = []
date12_list_drop = []
if ext in ['.h5','.he5']:
h5 = h5py.File(inps.file, 'r')
ifgram_list_all = sorted(h5[k].keys())
ifgram_list_keep = ut.check_drop_ifgram(h5, atr, ifgram_list_all)
date12_list_keep = ptime.list_ifgram2date12(ifgram_list_keep)
# Get date12_list_drop
date12_list_drop = sorted(list(set(date12_list) - set(date12_list_keep)))
print 'number of interferograms marked as dropped: '+str(len(date12_list_drop))
# Get date_list_drop
m_dates = [i.split('-')[0] for i in date12_list_keep]
s_dates = [i.split('-')[1] for i in date12_list_keep]
date8_list_keep = ptime.yyyymmdd(sorted(list(set(m_dates + s_dates))))
date8_list_drop = sorted(list(set(date8_list) - set(date8_list_keep)))
print 'number of acquisitions marked as dropped: '+str(len(date8_list_drop))
# Read Coherence List
inps.coherence_list = None
if inps.coherence_file and os.path.isfile(inps.coherence_file):
ext = os.path.splitext(inps.coherence_file)[1]
if ext in ['.h5']:
listFile = os.path.splitext(inps.coherence_file)[0]+'_spatialAverage.txt'
if os.path.isfile(listFile):
print 'reading coherence value from existed '+listFile
fcoh = np.loadtxt(listFile, dtype=str)
inps.coherence_list = [float(i) for i in fcoh[:,1]]
inps.coh_date12_list = [i for i in fcoh[:,0]]
else:
print 'calculating average coherence value from '+inps.coherence_file
if inps.mask_file:
mask = readfile.read(inps.mask_file)[0]
else:
mask = None
inps.coherence_list = ut.spatial_average(inps.coherence_file, mask, saveList=True)
inps.coh_date12_list = pnet.get_date12_list(inps.coherence_file)
else:
print 'reading coherence value from '+inps.coherence_file
fcoh = np.loadtxt(inps.coherence_file, dtype=str)
inps.coherence_list = [float(i) for i in fcoh[:,1]]
inps.coh_date12_list = [i for i in fcoh[:,0]]
# Check length of coherence file and input file
if not set(inps.coh_date12_list) == set(date12_list):
print 'WARNING: input coherence list has different pairs/date12 from input file'
print 'turn off the color plotting of interferograms based on coherence'
inps.coherence_list = None
#inps.coh_thres = 0.7
##### 2. Plot
# Fig 1 - Baseline History
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_perp_baseline_hist(ax, date8_list, pbase_list, vars(inps), date8_list_drop)
figName = 'BperpHistory'+inps.fig_ext
if inps.save_fig:
fig.savefig(figName,bbox_inches='tight')
print 'save figure to '+figName
# Fig 2 - Coherence Matrix
if inps.coherence_list:
figName = 'CoherenceMatrix'+inps.fig_ext
if inps.fig_size:
fig = plt.figure(figsize=inps.fig_size)
else:
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_coherence_matrix(ax, date12_list, inps.coherence_list)
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight')
print 'save figure to '+figName
# Fig 3 - Min/Max Coherence History
if inps.coherence_list:
figName = 'CoherenceHistory'+inps.fig_ext
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_coherence_history(ax, date12_list, inps.coherence_list)
if inps.save_fig:
fig.savefig(figName, bbox_inches='tight')
print 'save figure to '+figName
# Fig 4 - Interferogram Network
if inps.fig_size:
fig = plt.figure(figsize=inps.fig_size)
else:
fig = plt.figure()
ax = fig.add_subplot(111)
ax = pnet.plot_network(ax, date12_list, date8_list, pbase_list, vars(inps), date12_list_drop)
figName = 'Network'+inps.fig_ext
if inps.save_fig:
fig.savefig(figName,bbox_inches='tight')
print 'save figure to '+figName
if inps.save_list:
txtFile = os.path.splitext(inps.file)[0]+'_date12_list.txt'
np.savetxt(txtFile, date12_list, fmt='%s')
print 'save pairs/date12 info to file: '+txtFile
if inps.disp_fig:
plt.show()
def seed_file_inps(File, inps=None, outFile=None):
'''Seed input file with option from input namespace
Return output file name if succeed; otherwise, return None
'''
# Optional inputs
if not outFile: outFile = 'Seeded_' + os.path.basename(File)
if not inps: inps = cmdLineParse([''])
print '----------------------------------------------------'
print 'seeding file: ' + File
# Get stack and mask
stack = ut.get_file_stack(File, inps.mask_file)
mask = ~np.isnan(stack)
if np.nansum(mask) == 0.0:
print '\n*****************************************************'
print 'ERROR:'
print 'There is no pixel that has valid phase value in all datasets.'
print 'Check the file!'
print 'Seeding failed'
sys.exit(1)
atr = readfile.read_attribute(File)
# 1. Reference using global average
if inps.method == 'global-average':
print '\n---------------------------------------------------------'
print 'Automatically Seeding using Global Spatial Average Value '
print '---------------------------------------------------------'
print 'Calculating the global spatial average value for each epoch'+\
' of all valid pixels ...'
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
box = (0, 0, width, length)
meanList = ut.spatial_average(File, mask, box)[0]
inps.ref_y = ''
inps.ref_x = ''
outFile = seed_file_reference_value(File, outFile, meanList,
inps.ref_y, inps.ref_x)
return outFile
# 2. Reference using specific pixel
# 2.1 Find reference y/x
if not inps.ref_y or not inps.ref_x:
if inps.coherence_file:
inps.method = 'max-coherence'
inps.ref_y, inps.ref_x = select_max_coherence_yx(
inps.coherence_file, mask, inps.min_coherence)
elif inps.method == 'random':
inps.ref_y, inps.ref_x = random_select_reference_yx(mask)
elif inps.method == 'manual':
inps = manual_select_reference_yx(stack, inps)
# 2.2 Seeding file with reference y/x
if inps.ref_y and inps.ref_x and mask[inps.ref_y, inps.ref_x]:
if inps.mark_attribute:
re_select = True
try:
ref_x_orig == int(atr['ref_x'])
ref_y_orig == int(atr['ref_y'])
if inps.ref_x == ref_x_orig and inps.ref_y == ref_y_orig:
re_select = False
print 'Same reference pixel is already selected/saved in file, skip updating file attributes'
except:
pass
if re_select:
print 'Add/update ref_x/y attribute to file: ' + File
atr_ref = dict()
atr_ref['ref_x'] = str(inps.ref_x)
atr_ref['ref_y'] = str(inps.ref_y)
print atr_ref
outFile = ut.add_attribute(File, atr_ref)
else:
print 'Referencing input file to pixel in y/x: (%d, %d)' % (
inps.ref_y, inps.ref_x)
box = (inps.ref_x, inps.ref_y, inps.ref_x + 1, inps.ref_y + 1)
refList = ut.spatial_average(File, mask, box)[0]
outFile = seed_file_reference_value(File, outFile, refList,
inps.ref_y, inps.ref_x)
else:
raise ValueError('Can not find reference y/x or Nan value.')
return outFile
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 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, inps.reset]):
# Display network for manually modification when there is no other modification input.
print 'No input option found to remove interferogram'
if inps.template_file:
print 'Keep all interferograms by enable --reset option'
inps.reset = True
else:
print 'To manually modify network, please use --manual option '
return
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
# 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,
check_drop_ifgram=True)
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:'
date12_to_rmv_temp = []
for date12 in date12_orig:
if date12 not in date12_to_keep:
date12_to_rmv.append(date12)
date12_to_rmv_temp.append(date12)
print date12_to_rmv_temp
# 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.lookup_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.lookup_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 = []
date12_to_rmv_temp = []
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)
date12_to_rmv_temp.append(date12)
print date12_to_rmv_temp
# 2.2 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]
date12_to_rmv_temp = []
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)
date12_to_rmv_temp.append(date12)
print 'number of pairs to drop: %d' % (len(date12_to_rmv_temp))
print date12_to_rmv_temp
# 2.3 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])
date12_to_rmv_temp = []
for i in range(len(ifg_bperp_list)):
if abs(ifg_bperp_list[i]) > inps.max_perp_baseline:
date12 = date12_orig[i]
date12_to_rmv.append(date12)
date12_to_rmv_temp.append(date12)
print 'number of pairs to drop: %d' % (len(date12_to_rmv_temp))
print date12_to_rmv_temp
# 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)
date12_to_rmv_temp = []
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)
date12_to_rmv_temp.append(date12)
print date12_to_rmv_temp
# 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))
date12_to_rmv_temp = []
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)
date12_to_rmv_temp.append(date12)
print date12_to_rmv_temp
# 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))
date12_to_rmv_temp = []
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)
date12_to_rmv_temp.append(date12)
print date12_to_rmv_temp
# 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 = sorted(list(set(date12_to_rmv)))
date12_keep = sorted(list(set(date12_orig) - set(date12_to_rmv)))
print '----------------------------------------------------------------------------'
print 'number of interferograms to remove: ' + str(len(date12_to_rmv))
print 'number of interferograms kept : ' + str(len(date12_keep))
##### 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, 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.'
date12_to_rmv = []
##### 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' and inps.update_aux:
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' and inps.update_aux:
inps.coherence_file = Modified_File
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)
# Touch spatial average txt file of coherence if it's existed
coh_spatialAverage_file = os.path.splitext(
Modified_File)[0] + '_spatialAverage.txt'
if os.path.isfile(coh_spatialAverage_file):
touchCmd = 'touch ' + coh_spatialAverage_file
print touchCmd
os.system(touchCmd)
# Plot result
if inps.plot:
print '\nplot modified network and save to file.'
plotCmd = 'plot_network.py ' + inps.coherence_file + ' --coherence ' + inps.coherence_file + ' --nodisplay'
if inps.template_file:
plotCmd += ' --template ' + inps.template_file
print plotCmd
os.system(plotCmd)
print 'Done.'
return
def seed_file_inps(File, inps=None, outFile=None):
'''Seed input file with option from input namespace
Return output file name if succeed; otherwise, return None
'''
# Optional inputs
if not outFile: outFile = 'Seeded_'+os.path.basename(File)
if not inps: inps = cmdLineParse([''])
print '----------------------------------------------------'
print 'seeding file: '+File
# Get stack and mask
stack = ut.get_file_stack(File, inps.mask_file)
mask = ~np.isnan(stack)
if np.nansum(mask) == 0.0:
print '\n*****************************************************'
print 'ERROR:'
print 'There is no pixel that has valid phase value in all datasets.'
print 'Check the file!'
print 'Seeding failed'
sys.exit(1)
# 1. Reference using global average
if inps.method == 'global-average':
print '\n---------------------------------------------------------'
print 'Automatically Seeding using Global Spatial Average Value '
print '---------------------------------------------------------'
print 'Calculating the global spatial average value for each epoch'+\
' of all valid pixels ...'
atr = readfile.read_attribute(File)
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
box = (0,0,width,length)
meanList = ut.spatial_average(File, mask, box)
inps.ref_y = ''
inps.ref_x = ''
outFile = seed_file_reference_value(File, outFile, meanList, inps.ref_y, inps.ref_x)
return outFile
# 2. Reference using specific pixel
# 2.1 Find reference y/x
if not inps.ref_y or not inps.ref_x:
if inps.coherence_file:
inps.method = 'max-coherence'
inps.ref_y, inps.ref_x = select_max_coherence_yx(inps.coherence_file, mask)
elif inps.method == 'random':
inps.ref_y, inps.ref_x = random_select_reference_yx(mask)
elif inps.method == 'manual':
inps = manual_select_reference_yx(stack, inps)
# 2.2 Seeding file with reference y/x
if inps.ref_y and inps.ref_x:
print 'Seed file with input reference y/x ...'
if mask[inps.ref_y, inps.ref_x]:
print 'Referencing input file to pixel in y/x: (%d, %d)'%(inps.ref_y, inps.ref_x)
box = (inps.ref_x, inps.ref_y, inps.ref_x+1, inps.ref_y+1)
refList = ut.spatial_average(File, mask, box)
outFile = seed_file_reference_value(File, outFile, refList, inps.ref_y, inps.ref_x)
else:
print '\nInput reference y/x has NaN value in file stacking, skip seeding.'
return None
else:
sys.exit('ERROR: can not find reference y/x! Seeding FAILED.')
return outFile
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 '\n****************** Network Modification ********************'
if (not inps.reference_file and not inps.template_file and\
not inps.max_temp_baseline and not inps.max_perp_baseline and\
not inps.drop_ifg_index and not inps.drop_date and \
not inps.coherence_file):
# Display network for manually modification when there is no other modification input.
print 'No input found to remove interferogram, continue by display the network to select it manually ...'
inps.disp_network = True
# Update inps if template is input
if inps.template_file:
inps = update_inps_with_template(inps, inps.template_file)
# Convert index : input to continous index list
if inps.drop_ifg_index:
ifg_index = list(inps.drop_ifg_index)
inps.drop_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.drop_ifg_index.append(j)
elif len(index_temp) == 1:
inps.drop_ifg_index.append(int(index))
else:
print 'Unrecoganized input: ' + index
inps.drop_ifg_index = sorted(inps.drop_ifg_index)
if max(inps.drop_ifg_index) > len(date12_orig):
raise Exception('Input index out of range!\n'+\
'input index:'+str(inps.drop_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_file:
print '----------------------------------------------------------------------------'
print 'use coherence-based network modification from coherence file: ' + inps.coherence_file
# Calculate spatial average coherence
if not inps.mask_file:
mask = readfile.read(inps.mask_file)[0]
print 'mask coherence with file: ' + inps.mask_file
else:
mask = None
cohTextFile = os.path.splitext(
inps.coherence_file)[0] + '_spatialAverage.list'
if os.path.isfile(cohTextFile):
print 'average coherence in space has been calculated before and store in file: ' + cohTextFile
print 'read it directly, or delete it and re-run the script to re-calculate the list'
cohTxt = np.loadtxt(cohTextFile, dtype=str)
mean_coherence_list = [float(i) for i in cohTxt[:, 1]]
coh_date12_list = [i for i in cohTxt[:, 0]]
else:
print 'calculating average coherence of each interferogram ...'
mean_coherence_list = ut.spatial_average(inps.coherence_file,
mask,
saveList=True)
coh_date12_list = pnet.get_date12_list(inps.coherence_file)
print 'date12 with average coherence < ' + str(
inps.min_coherence) + ': '
for i in range(len(coh_date12_list)):
if mean_coherence_list[i] < inps.min_coherence:
date12 = coh_date12_list[i]
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.igram_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 drop_ifg_index
if inps.drop_ifg_index:
print '----------------------------------------------------------------------------'
print 'drop date12/pair with the following index number:'
for index in inps.drop_ifg_index:
date12 = date12_orig[index - 1]
date12_to_rmv.append(date12)
print str(index) + ' ' + date12
# 2.5 Update date12_to_rmv from drop_date
if inps.drop_date:
inps.drop_date = ptime.yymmdd(inps.drop_date)
print '----------------------------------------------------------------------------'
print 'Drop pairs including the following dates: \n' + str(
inps.drop_date)
for i in range(len(date12_orig)):
date1, date2 = date12_orig[i].split('-')
if (date1 in inps.drop_date) or (date2 in inps.drop_date):
date12 = date12_orig[i]
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
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)
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
outFile = 'Modified_Mask.h5'
print 'writing >>> ' + outFile
ut.nonzero_mask(Modified_File, outFile)
elif k == 'coherence':
print 'update average spatial coherence for input ' + k + ' file based on: ' + Modified_File
outFile = 'Modified_average_spatial_coherence.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'
print plotCmd
os.system(plotCmd)
print 'Done.'
return
else:
print 'No interferogram dropped, skip update.'
return
def main(argv):
inps = cmdLineParse()
if not inps.disp_fig:
plt.switch_backend('Agg')
print '\n******************** Plot Network **********************'
# Output figure name
figName1 = 'BperpHist' + inps.fig_ext
figName2 = 'Network' + inps.fig_ext
if 'Modified' in inps.file:
figName1 = 'BperpHist_Modified' + inps.fig_ext
figName2 = 'Network_Modified' + inps.fig_ext
##### 1. Read Info
# Read dateList and bperpList
ext = os.path.splitext(inps.file)[1]
if ext in ['.h5']:
k = readfile.read_attribute(inps.file)['FILE_TYPE']
print 'reading date and perpendicular baseline from ' + k + ' file: ' + os.path.basename(
inps.file)
if not k in multi_group_hdf5_file:
print 'ERROR: only the following file type are supported:\n' + str(
multi_group_hdf5_file)
sys.exit(1)
Bp = ut.Baseline_timeseries(inps.file)
date8List = ptime.igram_date_list(inps.file)
date6List = ptime.yymmdd(date8List)
else:
print 'reading date and perpendicular baseline from baseline list file: ' + inps.bl_list_file
date8List, Bp = pnet.read_baseline_file(inps.bl_list_file)[0:2]
date6List = ptime.yymmdd(date8List)
print 'number of acquisitions: ' + str(len(date8List))
# Read Pairs Info
print 'reading pairs info from file: ' + inps.file
date12_list = pnet.get_date12_list(inps.file)
pairs_idx = pnet.date12_list2index(date12_list, date6List)
print 'number of pairs : ' + str(len(pairs_idx))
# Read Coherence List
inps.coherence_list = None
if inps.coherence_file and os.path.isfile(inps.coherence_file):
ext = os.path.splitext(inps.coherence_file)[1]
if ext in ['.h5']:
listFile = os.path.splitext(
inps.coherence_file)[0] + '_spatialAverage.list'
if os.path.isfile(listFile):
print 'reading coherence value from existed ' + listFile
fcoh = np.loadtxt(listFile, dtype=str)
inps.coherence_list = [float(i) for i in fcoh[:, 1]]
coh_date12_list = [i for i in fcoh[:, 0]]
else:
print 'calculating average coherence value from ' + inps.coherence_file
inps.coherence_list = ut.spatial_average(inps.coherence_file,
saveList=True)
coh_date12_list = pnet.get_date12_list(inps.coherence_file)
else:
print 'reading coherence value from ' + inps.coherence_file
fcoh = np.loadtxt(inps.coherence_file, dtype=str)
inps.coherence_list = [float(i) for i in fcoh[:, 1]]
coh_date12_list = [i for i in fcoh[:, 0]]
# Check length of coherence file and input file
if not set(coh_date12_list) == set(date12_list):
print 'WARNING: input coherence list has different pairs/date12 from input file'
print 'turn off the color plotting of interferograms based on coherence'
inps.coherence_list = None
##### 2. Plot
# Fig 1 - Baseline History
fig1 = plt.figure(1)
ax1 = fig1.add_subplot(111)
ax1 = pnet.plot_perp_baseline_hist(ax1, date8List, Bp, vars(inps))
if inps.save_fig:
fig1.savefig(figName1, bbox_inches='tight')
print 'save figure to ' + figName1
# Fig 2 - Interferogram Network
fig2 = plt.figure(2)
ax2 = fig2.add_subplot(111)
ax2 = pnet.plot_network(ax2, pairs_idx, date8List, Bp, vars(inps))
if inps.save_fig:
fig2.savefig(figName2, bbox_inches='tight')
print 'save figure to ' + figName2
if inps.save_list:
txtFile = os.path.splitext(inps.file)[0] + '_date12.list'
np.savetxt(txtFile, date12_list, fmt='%s')
print 'save pairs/date12 info to file: ' + txtFile
if inps.disp_fig:
plt.show()
