def main(argv):
inps = cmdLineParse()
if inps.template_file:
inps = read_template2inps(inps.template_file)
if inps.ref_date == 'no':
print 'No reference date input, skip this step.'
return inps.timeseries_file
elif inps.ref_date.lower() in ['auto']:
print '------------------------------------------------------------'
print 'auto choose reference date based on minimum residual RMS'
if not inps.resid_file:
inps.resid_file = os.path.splitext(
inps.timeseries_file)[0] + 'InvResid.h5'
rms_list, date_list = ut.get_residual_rms(inps.resid_file,
inps.mask_file,
inps.ramp_type)
ref_idx = np.argmin(rms_list)
inps.ref_date = date_list[ref_idx]
print 'date with minimum residual RMS: %s - %.4f' % (inps.ref_date,
rms_list[ref_idx])
print '------------------------------------------------------------'
elif os.path.isfile(inps.ref_date):
print 'read reference date from file: ' + inps.ref_date
inps.ref_date = ptime.read_date_list(inps.ref_date)[0]
# Referencing input file
inps.outfile = ref_date_file(inps.timeseries_file, inps.ref_date,
inps.outfile)
return inps.outfile
def main(argv):
inps = cmdLineParse()
if inps.template_file:
inps = read_template2inps(inps.template_file)
##### calculate timeseries of residual Root Mean Square
#std_list, date_list = ut.get_residual_std(inps.timeseries_file, inps.mask_file, inps.ramp_type)
rms_list, date_list = ut.get_residual_rms(inps.timeseries_file,
inps.mask_file, inps.ramp_type)
##### reference_date.txt
print '------------------------------------------------------------'
ref_idx = np.argmin(rms_list)
ref_date = date_list[ref_idx]
print 'date with minimum residual RMS: %s - %.4f' % (ref_date,
rms_list[ref_idx])
refTxtFile = 'reference_date.txt'
if (inps.save_reference_date and \
ut.update_file(refTxtFile, [inps.timeseries_file, inps.mask_file, inps.template_file],\
check_readable=False)):
f = open(refTxtFile, 'w')
f.write(ref_date + '\n')
f.close()
print 'save date to file: ' + refTxtFile
##### exclude_date.txt
print '------------------------------------------------------------'
ex_idx_list = [rms_list.index(i) for i in rms_list if i > inps.min_rms]
print 'date(s) with residual RMS > ' + str(inps.min_rms)
exTxtFile = 'exclude_date.txt'
if ex_idx_list:
if (inps.save_exclude_date and \
ut.update_file(exTxtFile, [inps.timeseries_file, inps.mask_file, inps.template_file],\
check_readable=False)):
f = open(exTxtFile, 'w')
for i in ex_idx_list:
print '%s - %.4f' % (date_list[i], rms_list[i])
f.write(date_list[i] + '\n')
f.close()
print 'save date(s) to file: ' + exTxtFile
else:
print 'None.'
##### Plot
fig_name = os.path.dirname(os.path.abspath(inps.timeseries_file))+\
'/rms_'+os.path.splitext(inps.timeseries_file)[0]
if inps.ramp_type != 'no':
fig_name += '_' + inps.ramp_type
fig_name += '.pdf'
if ut.update_file(fig_name, [exTxtFile, refTxtFile, inps.template_file],
check_readable=False):
if inps.fig_size:
fig = plt.figure(figsize=inps.fig_size)
else:
fig = plt.figure()
ax = fig.add_subplot(111)
font_size = 12
dates, datevector = ptime.date_list2vector(date_list)
try:
bar_width = ut.mode(np.diff(dates).tolist()) * 3 / 4
except:
bar_width = np.min(np.diff(dates).tolist()) * 3 / 4
x_list = [i - bar_width / 2 for i in dates]
rms_list = [i * 1000. for i in rms_list]
min_rms = inps.min_rms * 1000.
# Plot all dates
ax.bar(x_list, rms_list, bar_width.days)
#ax.bar(x_list, rms_list, bar_width.days)
# Plot reference date
#if inps.save_reference_date:
ax.bar(x_list[ref_idx],
rms_list[ref_idx],
bar_width.days,
label='Reference date')
# Plot exclude dates
#if ex_idx_list and inps.save_exclude_date:
if ex_idx_list:
ex_x_list = [x_list[i] for i in ex_idx_list]
ex_rms_list = [rms_list[i] for i in ex_idx_list]
ax.bar(ex_x_list,
ex_rms_list,
bar_width.days,
color='darkgray',
label='Exclude date(s)')
# Plot min_rms line
ax, xmin, xmax = ptime.auto_adjust_xaxis_date(
ax, datevector, font_size, every_year=inps.tick_year_num)
ax.plot(np.array([xmin, xmax]), np.array([min_rms, min_rms]), '--k')
# axis format
ax = pnet.auto_adjust_yaxis(ax,
rms_list + [min_rms],
font_size,
ymin=0.0)
ax.set_xlabel('Time [years]', fontsize=font_size)
ax.set_ylabel('Root Mean Square [mm]', fontsize=font_size)
ax.yaxis.set_ticks_position('both')
ax.tick_params(labelsize=font_size)
if inps.save_reference_date or inps.save_exclude_date:
plt.legend(fontsize=font_size)
# save figure
fig.savefig(fig_name, bbox_inches='tight', transparent=True)
print 'save figure to file: ' + fig_name
return