def plot(self):
# Read data for transection
self.data_list = []
self.atr_list = []
for fname in self.file:
data, atr = readfile.read(fname, datasetName=self.dset)
data = pp.scale_data2disp_unit(data,
metadata=atr,
disp_unit=self.disp_unit)[0]
self.data_list.append(data)
self.atr_list.append(atr)
# Figure
self.fig, (self.ax_img,
self.ax_txn) = plt.subplots(1,
2,
num=self.figname,
figsize=self.fig_size)
# Axes 1 - map with view.prep/plot_slice()
self.ax_img = view.plot_slice(self.ax_img, self.data_img, self.atr,
self)[0]
# Axes 2 - transection
self.ax_txn.yaxis.tick_right()
self.ax_txn.yaxis.set_label_position("right")
# plot initial input transect
if self.start_yx and self.end_yx:
self.draw_line(self.start_yx, self.end_yx)
self.draw_transection(self.start_yx, self.end_yx, self.start_lalo,
self.end_lalo)
self.fig.subplots_adjust(left=0.05, wspace=0.25)
# save
if self.save_fig:
outfile = '{}.pdf'.format(self.outfile_base)
self.fig.savefig(outfile,
bbox_inches='tight',
transparent=True,
dpi=self.fig_dpi)
vprint('saved transect to', outfile)
self.cid = self.fig.canvas.mpl_connect('button_release_event',
self.select_point)
if self.disp_fig:
vprint('showing ...')
plt.show()
return
def plot_transect(ax, inps):
print('plot profiles')
# disp_unit/scale
if not inps.disp_unit:
inps.disp_unit = inps.atrList[0]['UNIT']
inps.disp_unit, inps.disp_scale = pp.scale_data2disp_unit(data=None,
metadata=inps.atrList[0],
disp_unit=inps.disp_unit)[1:3]
# Plot 2.1 - Input Files
value_min = 0
value_max = 0
for i in range(len(inps.file)):
# Profile Color based on Asc/Desc direction
if inps.atrList[i]['ORBIT_DIRECTION'][0].upper() == 'A':
p_color = 'crimson'
else:
p_color = 'royalblue'
# Plot
distance = inps.transectList[i][:, 0]/1000.0 # km
value = inps.transectList[i][:, 1]*inps.disp_scale - inps.disp_offset*i
ax.plot(distance, value, '.', color=p_color, markersize=inps.marker_size)
# Y Stat
value_min = np.nanmin([value_min, np.nanmin(value)])
value_max = np.nanmax([value_max, np.nanmax(value)])
# Y axis
if not inps.disp_min:
inps.disp_min = np.floor(value_min - (value_max-value_min)*1.2/len(inps.file))
if not inps.disp_max:
inps.disp_max = np.ceil(value_max)
ax.set_ylim(inps.disp_min, inps.disp_max)
ax.set_ylabel('Mean LOS Velocity ({})'.format(inps.disp_unit), fontsize=inps.font_size)
# X axis
ax.set_xlabel('Distance (km)', fontsize=inps.font_size)
ax.tick_params(which='both', direction='out', labelsize=inps.font_size)
# Plot 2.2 - DEM
if inps.dem:
ax2 = ax.twinx()
distance = inps.demTransectList[0][:, 0]/1000.0 # km
value = inps.demTransectList[0][:, 1]/1000.0 # km
ax2.fill_between(distance, 0, value, facecolor='gray')
# Y axis - display DEM in the bottom
value_min = np.nanmin(value)
value_max = np.nanmax(value)
if not inps.dem_disp_min:
inps.dem_disp_min = np.floor(value_min*2.0)/2.0
if not inps.dem_disp_max:
inps.dem_disp_max = np.ceil((value_max +
(value_max-value_min)*(len(inps.file)+0.0))*2.0)/2.0
ax2.set_ylim(inps.dem_disp_min, inps.dem_disp_max)
# Show lower part of yaxis
#dem_tick = ax2.yaxis.get_majorticklocs()
#dem_tick = dem_tick[:len(dem_tick)/2]
# ax2.set_yticks(dem_tick)
ax2.set_ylabel('Elevation (km)', fontsize=inps.font_size)
ax2.tick_params(which='both', direction='out', labelsize=inps.font_size)
# X axis - Shared
distanceMax = np.nanmax(inps.transectList[0][:, 0]/1000.0) # in km
plt.xlim(0, distanceMax)
plt.tight_layout()
return
def read_timeseries_data(inps):
"""Read data of time-series files
Parameters: inps : Namespace of input arguments
Returns: ts_data : list of 3D np.array in size of (num_date, length, width)
mask : 2D np.array in size of (length, width)
inps : Namespace of input arguments
"""
## read list of 3D time-series
ts_data = []
for fname in inps.file:
msg = f'reading timeseries from file {fname}'
msg += f' with step of {inps.multilook_num} by {inps.multilook_num}' if inps.multilook_num > 1 else ''
vprint(msg)
data, atr = readfile.read(fname,
datasetName=inps.date_list,
box=inps.pix_box,
xstep=inps.multilook_num,
ystep=inps.multilook_num)
if inps.ref_yx and inps.ref_yx != (int(atr.get('REF_Y', -1)), int(atr.get('REF_X', -1))):
(ry, rx) = subset_and_multilook_yx(inps.ref_yx, inps.pix_box, inps.multilook_num)
ref_phase = data[:, ry, rx]
data -= np.tile(ref_phase.reshape(-1, 1, 1), (1, data.shape[-2], data.shape[-1]))
vprint('reference to pixel: {}'.format(inps.ref_yx))
if inps.ref_idx is not None:
vprint('reference to date: {}'.format(inps.date_list[inps.ref_idx]))
data -= np.tile(data[inps.ref_idx, :, :], (inps.num_date, 1, 1))
# Display Unit
(data,
inps.disp_unit,
inps.unit_fac) = pp.scale_data2disp_unit(data,
metadata=atr,
disp_unit=inps.disp_unit)
ts_data.append(data)
## mask file: input mask file + non-zero ts pixels - ref_point
mask = pp.read_mask(inps.file[0],
mask_file=inps.mask_file,
datasetName='displacement',
box=inps.pix_box,
xstep=inps.multilook_num,
ystep=inps.multilook_num,
print_msg=inps.print_msg)[0]
if mask is None:
mask = np.ones(ts_data[0].shape[-2:], np.bool_)
ts_stack = np.nansum(ts_data[0], axis=0)
mask[np.isnan(ts_stack)] = False
# keep all-zero value for unwrapError time-series
if atr['UNIT'] not in ['cycle']:
mask[ts_stack == 0.] = False
del ts_stack
# do not mask the reference point
if inps.ref_yx and inps.ref_yx != (int(atr.get('REF_Y', -1)), int(atr.get('REF_X', -1))):
(ry, rx) = subset_and_multilook_yx(inps.ref_yx, inps.pix_box, inps.multilook_num)
mask[ry, rx] = True
## default vlim
inps.dlim = [np.nanmin(ts_data[0]), np.nanmax(ts_data[0])]
if not inps.vlim:
inps.cmap_lut, inps.vlim = pp.auto_adjust_colormap_lut_and_disp_limit(ts_data[0],
num_multilook=10,
print_msg=inps.print_msg)
vprint('data range: {} {}'.format(inps.dlim, inps.disp_unit))
vprint('display range: {} {}'.format(inps.vlim, inps.disp_unit))
## default ylim
num_file = len(inps.file)
if not inps.ylim:
ts_data_mli = multilook_data(np.squeeze(ts_data[-1]), 4, 4)
if inps.zero_first:
ts_data_mli -= np.tile(ts_data_mli[inps.zero_idx, :, :], (inps.num_date, 1, 1))
ymin, ymax = (np.nanmin(ts_data_mli[inps.ex_flag != 0]),
np.nanmax(ts_data_mli[inps.ex_flag != 0]))
ybuffer = (ymax - ymin) * 0.05
inps.ylim = [ymin - ybuffer, ymax + ybuffer]
if inps.offset:
inps.ylim[1] += inps.offset * (num_file - 1)
del ts_data_mli
return ts_data, mask, inps
def read_init_info(inps):
# Time Series Info
atr = readfile.read_attribute(inps.file[0])
inps.key = atr['FILE_TYPE']
if inps.key == 'timeseries':
obj = timeseries(inps.file[0])
elif inps.key == 'giantTimeseries':
obj = giantTimeseries(inps.file[0])
elif inps.key == 'HDFEOS':
obj = HDFEOS(inps.file[0])
else:
raise ValueError('input file is {}, not timeseries.'.format(inps.key))
obj.open(print_msg=inps.print_msg)
inps.seconds = atr.get('CENTER_LINE_UTC', 0)
if not inps.file_label:
inps.file_label = []
for fname in inps.file:
fbase = os.path.splitext(os.path.basename(fname))[0]
fbase = fbase.replace('timeseries', '')
inps.file_label.append(fbase)
# default mask file
if not inps.mask_file and 'msk' not in inps.file[0]:
dir_name = os.path.dirname(inps.file[0])
if 'Y_FIRST' in atr.keys():
inps.mask_file = os.path.join(dir_name, 'geo_maskTempCoh.h5')
else:
inps.mask_file = os.path.join(dir_name, 'maskTempCoh.h5')
if not os.path.isfile(inps.mask_file):
inps.mask_file = None
## date info
inps.date_list = obj.dateList
inps.num_date = len(inps.date_list)
if inps.start_date:
inps.date_list = [i for i in inps.date_list if int(i) >= int(inps.start_date)]
if inps.end_date:
inps.date_list = [i for i in inps.date_list if int(i) <= int(inps.end_date)]
inps.num_date = len(inps.date_list)
inps.dates, inps.yearList = ptime.date_list2vector(inps.date_list)
(inps.ex_date_list,
inps.ex_dates,
inps.ex_flag) = read_exclude_date(inps.ex_date_list, inps.date_list)
# reference date/index
if not inps.ref_date:
inps.ref_date = atr.get('REF_DATE', None)
if inps.ref_date:
inps.ref_idx = inps.date_list.index(inps.ref_date)
else:
inps.ref_idx = None
# date/index of interest for initial display
if not inps.idx:
if (not inps.ref_idx) or (inps.ref_idx < inps.num_date / 2.):
inps.idx = inps.num_date - 2
else:
inps.idx = 2
# Display Unit
(inps.disp_unit,
inps.unit_fac) = pp.scale_data2disp_unit(metadata=atr, disp_unit=inps.disp_unit)[1:3]
# Map info - coordinate unit
inps.coord_unit = atr.get('Y_UNIT', 'degrees').lower()
# Read Error List
inps.ts_plot_func = plot_ts_scatter
inps.error_ts = None
inps.ex_error_ts = None
if inps.error_file:
# assign plot function
inps.ts_plot_func = plot_ts_errorbar
# read error file
error_fc = np.loadtxt(inps.error_file, dtype=bytes).astype(str)
inps.error_ts = error_fc[:, 1].astype(np.float)*inps.unit_fac
# update error file with exlcude date
if inps.ex_date_list:
e_ts = inps.error_ts[:]
inps.ex_error_ts = e_ts[inps.ex_flag == 0]
inps.error_ts = e_ts[inps.ex_flag == 1]
# Zero displacement for 1st acquisition
if inps.zero_first:
inps.zero_idx = min(0, np.min(np.where(inps.ex_flag)[0]))
# default lookup table file and coordinate object
if not inps.lookup_file:
inps.lookup_file = ut.get_lookup_file('./inputs/geometryRadar.h5')
inps.coord = ut.coordinate(atr, inps.lookup_file)
## size and lalo info
inps.pix_box, inps.geo_box = subset.subset_input_dict2box(vars(inps), atr)
inps.pix_box = inps.coord.check_box_within_data_coverage(inps.pix_box)
inps.geo_box = inps.coord.box_pixel2geo(inps.pix_box)
data_box = (0, 0, int(atr['WIDTH']), int(atr['LENGTH']))
vprint('data coverage in y/x: '+str(data_box))
vprint('subset coverage in y/x: '+str(inps.pix_box))
vprint('data coverage in lat/lon: '+str(inps.coord.box_pixel2geo(data_box)))
vprint('subset coverage in lat/lon: '+str(inps.geo_box))
vprint('------------------------------------------------------------------------')
# calculate multilook_num
# ONLY IF:
# inps.multilook is True (no --nomultilook input) AND
# inps.multilook_num ==1 (no --multilook-num input)
# Note: inps.multilook is used for this check ONLY
# Note: multilooking is only applied to the 3D data cubes and their related operations:
# e.g. spatial indexing, referencing, etc. All the other variables are in the original grid
# so that users get the same result as the non-multilooked version.
if inps.multilook and inps.multilook_num == 1:
inps.multilook_num = pp.auto_multilook_num(inps.pix_box, inps.num_date,
max_memory=inps.maxMemory,
print_msg=inps.print_msg)
## reference pixel
if not inps.ref_lalo and 'REF_LAT' in atr.keys():
inps.ref_lalo = (float(atr['REF_LAT']), float(atr['REF_LON']))
if inps.ref_lalo:
# set longitude to [-180, 180)
if inps.coord_unit.lower().startswith('deg') and inps.ref_lalo[1] >= 180.:
inps.ref_lalo[1] -= 360.
# ref_lalo --> ref_yx if not set in cmd
if not inps.ref_yx:
inps.ref_yx = inps.coord.geo2radar(inps.ref_lalo[0], inps.ref_lalo[1], print_msg=False)[0:2]
# use REF_Y/X if ref_yx not set in cmd
if not inps.ref_yx and 'REF_Y' in atr.keys():
inps.ref_yx = (int(atr['REF_Y']), int(atr['REF_X']))
# ref_yx --> ref_lalo if in geo-coord
# for plotting purpose only
if inps.ref_yx and 'Y_FIRST' in atr.keys():
inps.ref_lalo = inps.coord.radar2geo(inps.ref_yx[0], inps.ref_yx[1], print_msg=False)[0:2]
# do not plot native reference point if it's out of the coverage due to subset
if (inps.ref_yx and 'Y_FIRST' in atr.keys()
and inps.ref_yx == (int(atr.get('REF_Y',-999)), int(atr.get('REF_X',-999)))
and not ( inps.pix_box[0] <= inps.ref_yx[1] < inps.pix_box[2]
and inps.pix_box[1] <= inps.ref_yx[0] < inps.pix_box[3])):
inps.disp_ref_pixel = False
print('the native REF_Y/X is out of subset box, thus do not display')
## initial pixel coord
if inps.lalo:
inps.yx = inps.coord.geo2radar(inps.lalo[0], inps.lalo[1], print_msg=False)[0:2]
try:
inps.lalo = inps.coord.radar2geo(inps.yx[0], inps.yx[1], print_msg=False)[0:2]
except:
inps.lalo = None
## figure settings
# Flip up-down / left-right
if inps.auto_flip:
inps.flip_lr, inps.flip_ud = pp.auto_flip_direction(atr, print_msg=inps.print_msg)
# Transparency - Alpha
if not inps.transparency:
# Auto adjust transparency value when showing shaded relief DEM
if inps.dem_file and inps.disp_dem_shade:
inps.transparency = 0.7
else:
inps.transparency = 1.0
## display unit ans wrap
# if wrap_step == 2*np.pi (default value), set disp_unit_img = radian;
# otherwise set disp_unit_img = disp_unit
inps.disp_unit_img = inps.disp_unit
if inps.wrap:
inps.range2phase = -4. * np.pi / float(atr['WAVELENGTH'])
if 'cm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 100.
elif 'mm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1000.
elif 'm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1.
else:
raise ValueError('un-recognized display unit: {}'.format(inps.disp_unit))
if (inps.wrap_range[1] - inps.wrap_range[0]) == 2*np.pi:
inps.disp_unit_img = 'radian'
inps.vlim = inps.wrap_range
inps.cbar_label = 'Displacement [{}]'.format(inps.disp_unit_img)
## fit a suite of time func to the time series
inps.model, inps.num_param = ts2vel.read_inps2model(inps, date_list=inps.date_list)
# dense TS for plotting
inps.date_list_fit = ptime.get_date_range(inps.date_list[0], inps.date_list[-1])
inps.dates_fit = ptime.date_list2vector(inps.date_list_fit)[0]
inps.G_fit = time_func.get_design_matrix4time_func(
date_list=inps.date_list_fit,
model=inps.model,
seconds=inps.seconds)
return inps, atr
def read_timeseries_data(inps):
"""Read data of time-series files
Parameters: inps : Namespace of input arguments
Returns: ts_data : list of 3D np.array in size of (num_date, length, width)
mask : 2D np.array in size of (length, width)
inps : Namespace of input arguments
"""
# read list of 3D time-series
ts_data = []
for fname in inps.file:
vprint('reading timeseries from file {} ...'.format(fname))
data, atr = readfile.read(fname,
datasetName=inps.date_list,
box=inps.pix_box)
try:
ref_phase = data[:, inps.ref_yx[0] - inps.pix_box[1],
inps.ref_yx[1] - inps.pix_box[0]]
data -= np.tile(ref_phase.reshape(-1, 1, 1),
(1, data.shape[-2], data.shape[-1]))
vprint('reference to pixel: {}'.format(inps.ref_yx))
except:
pass
vprint('reference to date: {}'.format(inps.date_list[inps.ref_idx]))
data -= np.tile(data[inps.ref_idx, :, :], (inps.num_date, 1, 1))
# Display Unit
(data, inps.disp_unit,
inps.unit_fac) = pp.scale_data2disp_unit(data,
metadata=atr,
disp_unit=inps.disp_unit)
ts_data.append(data)
# Mask file: input mask file + non-zero ts pixels - ref_point
mask = np.ones(ts_data[0].shape[-2:], np.bool_)
msk = pp.read_mask(inps.file[0],
mask_file=inps.mask_file,
datasetName='displacement',
box=inps.pix_box,
print_msg=inps.print_msg)[0]
mask[msk == 0.] = False
del msk
ts_stack = np.sum(ts_data[0], axis=0)
mask[ts_stack == 0.] = False
mask[np.isnan(ts_stack)] = False
del ts_stack
#do not mask the reference point
try:
mask[inps.ref_yx[0] - inps.pix_box[1],
inps.ref_yx[1] - inps.pix_box[0]] = True
except:
pass
#vprint('masking data')
#ts_mask = np.tile(mask, (inps.num_date, 1, 1))
#for i in range(len(ts_data)):
# ts_data[i][ts_mask == 0] = np.nan
# try:
# ts_data[i][:, inps.ref_yx[0], inps.ref_yx[1]] = 0. # keep value on reference pixel
# except:
# pass
#del ts_mask
# default vlim
inps.dlim = [np.nanmin(ts_data[0]), np.nanmax(ts_data[0])]
ts_data_mli = multilook_data(np.squeeze(ts_data[0]), 10, 10)
if not inps.vlim:
inps.vlim = [
np.nanmin(ts_data_mli[inps.ex_flag != 0]),
np.nanmax(ts_data_mli[inps.ex_flag != 0])
]
vprint('data range: {} {}'.format(inps.dlim, inps.disp_unit))
vprint('display range: {} {}'.format(inps.vlim, inps.disp_unit))
# default ylim
num_file = len(inps.file)
if not inps.ylim:
ts_data_mli = multilook_data(np.squeeze(ts_data[-1]), 4, 4)
if inps.zero_first:
ts_data_mli -= np.tile(ts_data_mli[inps.zero_idx, :, :],
(inps.num_date, 1, 1))
ymin, ymax = (np.nanmin(ts_data_mli[inps.ex_flag != 0]),
np.nanmax(ts_data_mli[inps.ex_flag != 0]))
ybuffer = (ymax - ymin) * 0.05
inps.ylim = [ymin - ybuffer, ymax + ybuffer]
if inps.offset:
inps.ylim[1] += inps.offset * (num_file - 1)
del ts_data_mli
return ts_data, mask, inps
def read_init_info(inps):
# Time Series Info
ts_file0 = inps.file[0]
atr = readfile.read_attribute(ts_file0)
inps.key = atr['FILE_TYPE']
if inps.key == 'timeseries':
obj = timeseries(ts_file0)
elif inps.key == 'giantTimeseries':
obj = giantTimeseries(ts_file0)
elif inps.key == 'HDFEOS':
obj = HDFEOS(ts_file0)
else:
raise ValueError('input file is {}, not timeseries.'.format(inps.key))
obj.open(print_msg=inps.print_msg)
if not inps.file_label:
inps.file_label = [str(i) for i in list(range(len(inps.file)))]
# default mask file
if not inps.mask_file and 'masked' not in ts_file0:
dir_name = os.path.dirname(ts_file0)
if 'Y_FIRST' in atr.keys():
inps.mask_file = os.path.join(dir_name, 'geo_maskTempCoh.h5')
else:
inps.mask_file = os.path.join(dir_name, 'maskTempCoh.h5')
if not os.path.isfile(inps.mask_file):
inps.mask_file = None
# date info
inps.date_list = obj.dateList
inps.num_date = len(inps.date_list)
if inps.start_date:
inps.date_list = [
i for i in inps.date_list if int(i) >= int(inps.start_date)
]
if inps.end_date:
inps.date_list = [
i for i in inps.date_list if int(i) <= int(inps.end_date)
]
inps.num_date = len(inps.date_list)
inps.dates, inps.yearList = ptime.date_list2vector(inps.date_list)
(inps.ex_date_list, inps.ex_dates,
inps.ex_flag) = read_exclude_date(inps.ex_date_list, inps.date_list)
# initial display index
#if atr['REF_DATE'] in inps.date_list:
# inps.ref_idx = inps.date_list.index(atr['REF_DATE'])
#else:
# inps.ref_idx = 0
if inps.ref_date:
inps.ref_idx = inps.date_list.index(inps.ref_date)
else:
inps.ref_idx = 3
if not inps.idx:
if inps.ref_idx < inps.num_date / 2.:
inps.idx = inps.num_date - 3
else:
inps.idx = 3
# Display Unit
(inps.disp_unit,
inps.unit_fac) = pp.scale_data2disp_unit(metadata=atr,
disp_unit=inps.disp_unit)[1:3]
# Map info - coordinate unit
inps.coord_unit = atr.get('Y_UNIT', 'degrees').lower()
# Read Error List
inps.ts_plot_func = plot_ts_scatter
inps.error_ts = None
inps.ex_error_ts = None
if inps.error_file:
# assign plot function
inps.ts_plot_func = plot_ts_errorbar
# read error file
error_fc = np.loadtxt(inps.error_file, dtype=bytes).astype(str)
inps.error_ts = error_fc[:, 1].astype(np.float) * inps.unit_fac
# update error file with exlcude date
if inps.ex_date_list:
e_ts = inps.error_ts[:]
inps.ex_error_ts = e_ts[inps.ex_flag == 0]
inps.error_ts = e_ts[inps.ex_flag == 1]
# Zero displacement for 1st acquisition
if inps.zero_first:
inps.zero_idx = min(0, np.min(np.where(inps.ex_flag)[0]))
# default lookup table file
if not inps.lookup_file:
inps.lookup_file = ut.get_lookup_file('./inputs/geometryRadar.h5')
inps.coord = ut.coordinate(atr, inps.lookup_file)
# size and lalo info
inps.pix_box, inps.geo_box = subset.subset_input_dict2box(vars(inps), atr)
inps.pix_box = inps.coord.check_box_within_data_coverage(inps.pix_box)
inps.geo_box = inps.coord.box_pixel2geo(inps.pix_box)
data_box = (0, 0, int(atr['WIDTH']), int(atr['LENGTH']))
vprint('data coverage in y/x: ' + str(data_box))
vprint('subset coverage in y/x: ' + str(inps.pix_box))
vprint('data coverage in lat/lon: ' +
str(inps.coord.box_pixel2geo(data_box)))
vprint('subset coverage in lat/lon: ' + str(inps.geo_box))
vprint(
'------------------------------------------------------------------------'
)
# reference pixel
if not inps.ref_lalo and 'REF_LAT' in atr.keys():
inps.ref_lalo = (float(atr['REF_LAT']), float(atr['REF_LON']))
if inps.ref_lalo:
if inps.ref_lalo[1] > 180.:
inps.ref_lalo[1] -= 360.
inps.ref_yx = inps.coord.geo2radar(inps.ref_lalo[0],
inps.ref_lalo[1],
print_msg=False)[0:2]
if not inps.ref_yx and 'REF_Y' in atr.keys():
inps.ref_yx = [int(atr['REF_Y']), int(atr['REF_X'])]
# Initial Pixel Coord
if inps.lalo:
inps.yx = inps.coord.geo2radar(inps.lalo[0],
inps.lalo[1],
print_msg=False)[0:2]
try:
inps.lalo = inps.coord.radar2geo(inps.yx[0],
inps.yx[1],
print_msg=False)[0:2]
except:
inps.lalo = None
# Flip up-down / left-right
if inps.auto_flip:
inps.flip_lr, inps.flip_ud = pp.auto_flip_direction(
atr, print_msg=inps.print_msg)
# Transparency - Alpha
if not inps.transparency:
# Auto adjust transparency value when showing shaded relief DEM
if inps.dem_file and inps.disp_dem_shade:
inps.transparency = 0.7
else:
inps.transparency = 1.0
# display unit ans wrap
# if wrap_step == 2*np.pi (default value), set disp_unit_img = radian;
# otherwise set disp_unit_img = disp_unit
inps.disp_unit_img = inps.disp_unit
if inps.wrap:
inps.range2phase = -4. * np.pi / float(atr['WAVELENGTH'])
if 'cm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 100.
elif 'mm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1000.
elif 'm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1.
else:
raise ValueError('un-recognized display unit: {}'.format(
inps.disp_unit))
if (inps.wrap_range[1] - inps.wrap_range[0]) == 2 * np.pi:
inps.disp_unit_img = 'radian'
inps.vlim = inps.wrap_range
inps.cbar_label = 'Displacement [{}]'.format(inps.disp_unit_img)
return inps, atr
