def design_matrix4deformation(inps):
# Date Info
ts_obj = timeseries(inps.timeseries_file)
ts_obj.open()
# Design matrix - temporal deformation model
print('-'*50)
print('correct topographic phase residual (DEM error) using Fattahi and Amelung (2013, IEEE-TGRS)')
msg = 'ordinal least squares (OLS) inversion with L2-norm minimization on: phase'
if inps.min_phase_velocity:
msg += ' velocity'
if inps.rangeDist.size != 1:
msg += ' (pixel-wisely)'
print(msg)
tbase = np.array(ts_obj.tbase, np.float32) / 365.25
# 1. Polynomial - 2D matrix in size of (numDate, polyOrder+1)
print("temporal deformation model: polynomial order = "+str(inps.poly_order))
A_def = np.ones((ts_obj.numDate, 1), np.float32)
for i in range(inps.poly_order):
Ai = np.array(tbase**(i+1) / gamma(i+2), np.float32).reshape(-1, 1)
A_def = np.hstack((A_def, Ai))
# 2. Step function - 2D matrix in size of (numDate, len(inps.step_date))
if inps.step_date:
print("temporal deformation model: step functions at "+str(inps.step_date))
t_steps = ptime.yyyymmdd2years(inps.step_date)
t = np.array(ptime.yyyymmdd2years(ts_obj.dateList))
for t_step in t_steps:
Ai = np.array(t > t_step, np.float32).reshape(-1, 1)
A_def = np.hstack((A_def, Ai))
print('-'*50)
return A_def
def correct_local_oscilator_drift(fname, rg_dist_file=None, out_file=None):
print('-'*50)
print('correct Local Oscilator Drift for Envisat using an empirical model (Marinkovic and Larsen, 2013)')
print('-'*50)
atr = readfile.read_attribute(fname)
# Check Sensor Type
platform = atr['PLATFORM']
print('platform: '+platform)
if not platform.lower() in ['env', 'envisat']:
print('No need to correct LOD for '+platform)
return
# output file name
if not out_file:
out_file = '{}_LODcor{}'.format(os.path.splitext(fname)[0], os.path.splitext(fname)[1])
# Get LOD ramp rate from empirical model
if not rg_dist_file:
print('calculate range distance from file metadata')
rg_dist = get_relative_range_distance(atr)
else:
print('read range distance from file: %s' % (rg_dist_file))
rg_dist = readfile.read(rg_dist_file, datasetName='slantRangeDistance', print_msg=False)[0]
rg_dist -= rg_dist[int(atr['REF_Y']), int(atr['REF_X'])]
ramp_rate = np.array(rg_dist * 3.87e-7, np.float32)
# Correct LOD Ramp for Input fname
range2phase = -4*np.pi / float(atr['WAVELENGTH'])
k = atr['FILE_TYPE']
if k == 'timeseries':
# read
obj = timeseries(fname)
obj.open()
data = obj.read()
# correct LOD
diff_year = np.array(obj.yearList)
diff_year -= diff_year[obj.refIndex]
for i in range(data.shape[0]):
data[i, :, :] -= ramp_rate * diff_year[i]
# write
obj_out = timeseries(out_file)
obj_out.write2hdf5(data, refFile=fname)
elif k in ['.unw']:
data, atr = readfile.read(fname)
dates = ptime.yyyymmdd2years(ptime.yyyymmdd(atr['DATE12'].split('-')))
dt = dates[1] - dates[0]
data -= ramp_rate * range2phase * dt
writefile.write(data, out_file=out_file, metadata=atr)
else:
print('No need to correct for LOD for %s file' % (k))
return out_file
def read_exclude_date(inps, dateListAll):
# Merge ex_date/startDate/endDate into ex_date
yy_list_all = ptime.yyyymmdd2years(dateListAll)
exDateList = []
# 1. template_file
if inps.template_file:
print('read option from template file: ' + inps.template_file)
inps = read_template2inps(inps.template_file, inps)
# 2. ex_date
input_ex_date = list(inps.excludeDate)
if input_ex_date:
for ex_date in input_ex_date:
if os.path.isfile(ex_date):
ex_date = ptime.read_date_list(ex_date)
else:
ex_date = [ptime.yyyymmdd(ex_date)]
exDateList += list(set(ex_date) - set(exDateList))
# delete dates not existed in input file
exDateList = list(set(exDateList).intersection(dateListAll))
print('exclude date:' + str(exDateList))
# 3. startDate
if inps.startDate:
print('start date: ' + inps.startDate)
yy_min = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.startDate))
for i in range(len(dateListAll)):
date = dateListAll[i]
if yy_list_all[i] < yy_min and date not in exDateList:
print(' remove date: ' + date)
exDateList.append(date)
# 4. endDate
if inps.endDate:
print('end date: ' + inps.endDate)
yy_max = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.endDate))
for i in range(len(dateListAll)):
date = dateListAll[i]
if yy_list_all[i] > yy_max and date not in exDateList:
print(' remove date: ' + date)
exDateList.append(date)
exDateList = list(set(exDateList))
return exDateList
def read_exclude_date(inps, dateListAll):
# Merge ex_date/startDate/endDate into ex_date
yy_list_all = ptime.yyyymmdd2years(dateListAll)
exDateList = []
# 1. template_file
if inps.template_file:
print('read option from template file: ' + inps.template_file)
inps = read_template2inps(inps.template_file, inps)
# 2. ex_date
exDateList += ptime.read_date_list(list(inps.excludeDate),
date_list_all=dateListAll)
if exDateList:
print('exclude date:' + str(exDateList))
# 3. startDate
if inps.startDate:
print('start date: ' + inps.startDate)
yy_min = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.startDate))
for i in range(len(dateListAll)):
date = dateListAll[i]
if yy_list_all[i] < yy_min and date not in exDateList:
print(' remove date: ' + date)
exDateList.append(date)
# 4. endDate
if inps.endDate:
print('end date: ' + inps.endDate)
yy_max = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.endDate))
for i in range(len(dateListAll)):
date = dateListAll[i]
if yy_list_all[i] > yy_max and date not in exDateList:
print(' remove date: ' + date)
exDateList.append(date)
exDateList = list(set(exDateList))
return exDateList
