diff --git a/LiCSBAS_lib/LiCSBAS_loop_lib.py b/LiCSBAS_lib/LiCSBAS_loop_lib.py index 8a45863..d116eff 100644 --- a/LiCSBAS_lib/LiCSBAS_loop_lib.py +++ b/LiCSBAS_lib/LiCSBAS_loop_lib.py @@ -8,6 +8,8 @@ ========= Changelog ========= +v1.5.1 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.5 20201006 Yu Morishita, GSI - Update make_loop_png v1.4 20200828 Yu Morishita, GSI @@ -27,7 +29,6 @@ import numpy as np import SCM import LiCSBAS_io_lib as io_lib -import LiCSBAS_tools_lib as tools_lib os.environ['QT_QPA_PLATFORM']='offscreen' import warnings @@ -120,12 +121,10 @@ def identify_bad_ifg(bad_ifg_cand, good_ifg): #%% def make_loop_png(unw12, unw23, unw13, loop_ph, png, titles4, cycle): - ### Load color map for InSAR - cdict = tools_lib.cmap_insar() - plt.register_cmap(cmap=mpl.colors.LinearSegmentedColormap('insar', cdict)) - plt.rcParams['axes.titlesize'] = 10 + cmap_wrap = SCM.romaO ### Settings + plt.rcParams['axes.titlesize'] = 10 data = [unw12, unw23, unw13] length, width = unw12.shape @@ -145,7 +144,7 @@ def make_loop_png(unw12, unw23, unw13, loop_ph, png, titles4, cycle): for i in range(3): data_wrapped = np.angle(np.exp(1j*(data[i]/cycle))*cycle) ax = fig.add_subplot(2, 2, i+1) #index start from 1 - ax.imshow(data_wrapped, vmin=-np.pi, vmax=+np.pi, cmap='insar', interpolation='nearest') + ax.imshow(data_wrapped, vmin=-np.pi, vmax=+np.pi, cmap=cmap_wrap, interpolation='nearest') ax.set_title('{}'.format(titles4[i])) ax.set_xticklabels([]) ax.set_yticklabels([]) diff --git a/LiCSBAS_lib/LiCSBAS_tools_lib.py b/LiCSBAS_lib/LiCSBAS_tools_lib.py index b4d9296..aef2b65 100644 --- a/LiCSBAS_lib/LiCSBAS_tools_lib.py +++ b/LiCSBAS_lib/LiCSBAS_tools_lib.py @@ -82,7 +82,7 @@ def comp_size_time(file_remote, file_local): #%% def cmap_insar(): """ - How to use cmap_insar: + How to use cmap_insar (GAMMA standard rainbow cmap): import matplotlib as mpl from matplotlib import pyplot as plt cdict = cmap_insar() diff --git a/bin/LiCSBAS02_ml_prep.py b/bin/LiCSBAS02_ml_prep.py index 98b5157..2de7913 100755 --- a/bin/LiCSBAS02_ml_prep.py +++ b/bin/LiCSBAS02_ml_prep.py @@ -1,10 +1,7 @@ #!/usr/bin/env python3 """ -v1.7.3 202011118 Yu Morishita, GSI +v1.7.4 202011119 Yu Morishita, GSI -======== -Overview -======== This script converts GeoTIFF files of unw and cc to float32 and uint8 format, respectively, for further time series analysis, and also downsamples (multilooks) data if specified. Existing files are not re-created to save time, i.e., only the newly available data will be processed. ==================== @@ -48,6 +45,8 @@ """ #%% Change log ''' +v1.7.4 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.7.3 20201118 Yu Morishita, GSI - Again Bug fix of multiprocessing v1.7.2 20201116 Yu Morishita, GSI @@ -82,7 +81,6 @@ #%% Import import getopt import os -import re import sys import time import shutil @@ -91,6 +89,7 @@ import numpy as np import subprocess as subp import multiprocessing as multi +import SCM import LiCSBAS_io_lib as io_lib import LiCSBAS_tools_lib as tools_lib import LiCSBAS_plot_lib as plot_lib @@ -109,12 +108,12 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.7.3"; date=202011118; author="Y. Morishita" + ver="1.7.4"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ### For parallel processing - global ifgdates2, geocdir, outdir, nlook, n_valid_thre, cycle, cmap + global ifgdates2, geocdir, outdir, nlook, n_valid_thre, cycle, cmap_wrap #%% Set default @@ -127,7 +126,7 @@ def main(argv=None): except: n_para = multi.cpu_count() - cmap = 'insar' + cmap_wrap = SCM.romaO cycle = 3 n_valid_thre = 0.5 q = multi.get_context('fork') @@ -444,7 +443,7 @@ def convert_wrapper(i): ### Make png unwpngfile = os.path.join(ifgdir1, ifgd+'.unw.png') - plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), unwpngfile, cmap, ifgd+'.unw', vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), unwpngfile, cmap_wrap, ifgd+'.unw', vmin=-np.pi, vmax=np.pi, cbar=False) return 0 diff --git a/bin/LiCSBAS03op_GACOS.py b/bin/LiCSBAS03op_GACOS.py index 6b36755..93fdca2 100755 --- a/bin/LiCSBAS03op_GACOS.py +++ b/bin/LiCSBAS03op_GACOS.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -v1.5.4 20201119 Yu Morishita, GSI +v1.5.5 20201119 Yu Morishita, GSI This script applies a tropospheric correction to unw data using GACOS data. GACOS data may be automatically downloaded from COMET-LiCS web at step01 (if available), or could be externally obtained by requesting on a GACOS web (http://www.gacos.net/). If you request the GACOS data through the GACOS web, the dates and time of interest can be found in baselines and slc.mli.par, respectively. These are also available on the COMET-LiCS web portal. Once the GACOS data are ready, download the tar.gz, uncompress it, and put into GACOS dir. @@ -49,6 +49,8 @@ """ #%% Change log ''' +v1.5.5 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.5.4 20201119 Yu Morishita, GSI - New GACOS format (ztd.tif) available v1.5.3 20201118 Yu Morishita, GSI @@ -85,6 +87,7 @@ import numpy as np from osgeo import gdal import multiprocessing as multi +import SCM import LiCSBAS_io_lib as io_lib import LiCSBAS_tools_lib as tools_lib import LiCSBAS_plot_lib as plot_lib @@ -159,14 +162,14 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.5.4"; date=20201119; author="Y. Morishita" + ver="1.5.5"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ### For parallel processing global imdates2, gacosdir, outputBounds, width_geo, length_geo, resampleAlg,\ sltddir, LOSu, m2r_coef, fillholeflag, ifgdates2,\ - in_dir, out_dir, length_unw, width_unw, cycle + in_dir, out_dir, length_unw, width_unw, cycle, cmap_wrap #%% Set default @@ -181,7 +184,7 @@ def main(argv=None): n_para = multi.cpu_count() q = multi.get_context('fork') - + cmap_wrap = SCM.romaO #%% Read options try: @@ -532,12 +535,12 @@ def correct_wrapper(i): data3 = [np.angle(np.exp(1j*(data/cycle))*cycle) for data in [unw, unw_cor, dsltd]] title3 = ['unw_org (STD: {:.1f} rad)'.format(std_unw), 'unw_cor (STD: {:.1f} rad)'.format(std_unwcor), 'dsltd ({:.1f}% reduced)'.format(rate)] pngfile = os.path.join(out_dir1, ifgd+'.gacos.png') - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) ## Output png for corrected unw pngfile = os.path.join(out_dir1, ifgd+'.unw.png') title = '{} ({}pi/cycle)'.format(ifgd, cycle*2) - plot_lib.make_im_png(np.angle(np.exp(1j*unw_cor/cycle)*cycle), pngfile, 'insar', title, -np.pi, np.pi, cbar=False) + plot_lib.make_im_png(np.angle(np.exp(1j*unw_cor/cycle)*cycle), pngfile, cmap_wrap, title, -np.pi, np.pi, cbar=False) return 2, [ifgd, std_unw, std_unwcor, rate] diff --git a/bin/LiCSBAS04op_mask_unw.py b/bin/LiCSBAS04op_mask_unw.py index 0ee697a..3f6add4 100755 --- a/bin/LiCSBAS04op_mask_unw.py +++ b/bin/LiCSBAS04op_mask_unw.py @@ -1,10 +1,7 @@ #!/usr/bin/env python3 """ -v1.3.3 20201118 Yu Morishita, GSI +v1.3.4 20201119 Yu Morishita, GSI -======== -Overview -======== This script masks specified areas or low coherence areas in the unw data. The masking is effective when the unw data include areas which have many unwrapping errors and are not of interest, and can improve the result of Step 1-2 (loop closure). Existing files are not re-created to save time, i.e., only the newly available data will be processed. This step is optional. =============== @@ -42,6 +39,8 @@ """ #%% Change log ''' +v1.3.4 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.3.3 20201118 Yu Morishita, GSI - Again Bug fix of multiprocessing v1.3.2 20201116 Yu Morishita, GSI @@ -67,6 +66,7 @@ import time import numpy as np import multiprocessing as multi +import SCM import LiCSBAS_io_lib as io_lib import LiCSBAS_tools_lib as tools_lib import LiCSBAS_plot_lib as plot_lib @@ -84,12 +84,12 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.3.3"; date=20201118; author="Y. Morishita" + ver="1.3.4"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ### For paralell processing - global ifgdates2, in_dir, out_dir, length, width, bool_mask, cycle + global ifgdates2, in_dir, out_dir, length, width, bool_mask, cycle, cmap_wrap #%% Set default @@ -104,6 +104,7 @@ def main(argv=None): n_para = multi.cpu_count() cmap_noise = 'viridis' + cmap_wrap = SCM.romaO q = multi.get_context('fork') @@ -314,7 +315,7 @@ def mask_wrapper(ifgix): ## Output png for masked unw pngfile = os.path.join(out_dir1, ifgd+'.unw.png') title = '{} ({}pi/cycle)'.format(ifgd, cycle*2) - plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), pngfile, 'insar', title, -np.pi, np.pi, cbar=False) + plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), pngfile, cmap_wrap, title, -np.pi, np.pi, cbar=False) #%% main diff --git a/bin/LiCSBAS05op_clip_unw.py b/bin/LiCSBAS05op_clip_unw.py index a4b65ae..b7a31bc 100755 --- a/bin/LiCSBAS05op_clip_unw.py +++ b/bin/LiCSBAS05op_clip_unw.py @@ -1,10 +1,7 @@ #!/usr/bin/env python3 """ -v1.2.3 20201118 Yu Morishita, GSI +v1.2.4 20201119 Yu Morishita, GSI -======== -Overview -======== This script clips a specified rectangular area of interest from unw and cc data. The clipping can make the data size smaller and processing faster, and improve the result of Step 1-2 (loop closure). Existing files are not re-created to save time, i.e., only the newly available data will be processed. This step is optional. =============== @@ -42,6 +39,8 @@ """ #%% Change log ''' +v1.2.4 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.2.3 20201118 Yu Morishita, GSI - Again Bug fix of multiprocessing v1.2.2 20201116 Yu Morishita, GSI @@ -67,6 +66,7 @@ import time import numpy as np import multiprocessing as multi +import SCM import LiCSBAS_io_lib as io_lib import LiCSBAS_tools_lib as tools_lib import LiCSBAS_plot_lib as plot_lib @@ -85,12 +85,12 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.2.3"; date=20201118; author="Y. Morishita" + ver="1.2.4"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ### For parallel processing - global ifgdates2, in_dir, out_dir, length, width, x1, x2, y1, y2,cycle + global ifgdates2, in_dir, out_dir, length, width, x1, x2, y1, y2,cycle, cmap_wrap #%% Set default @@ -104,6 +104,7 @@ def main(argv=None): n_para = multi.cpu_count() q = multi.get_context('fork') + cmap_wrap = SCM.romaO #%% Read options @@ -333,7 +334,7 @@ def clip_wrapper(ifgix): ## Output png for corrected unw pngfile = os.path.join(out_dir1, ifgd+'.unw.png') title = '{} ({}pi/cycle)'.format(ifgd, cycle*2) - plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), pngfile, 'insar', title, -np.pi, np.pi, cbar=False) + plot_lib.make_im_png(np.angle(np.exp(1j*unw/cycle)*cycle), pngfile, cmap_wrap, title, -np.pi, np.pi, cbar=False) #%% main diff --git a/bin/LiCSBAS13_sb_inv.py b/bin/LiCSBAS13_sb_inv.py index 68b36d7..e9ba662 100755 --- a/bin/LiCSBAS13_sb_inv.py +++ b/bin/LiCSBAS13_sb_inv.py @@ -1,10 +1,7 @@ #!/usr/bin/env python3 """ -v1.4.5 20201118 Yu Morishita, GSI +v1.4.6 20201119 Yu Morishita, GSI -======== -Overview -======== This script inverts the SB network of unw to obtain the time series and velocity using NSBAS (López-Quiroz et al., 2009; Doin et al., 2011) approach. A stable reference point is determined after the inversion. RMS of the time series @@ -72,6 +69,8 @@ """ #%% Change log ''' +v1.4.6 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.4.5 20201118 Yu Morishita, GSI - Again Bug fix of multiprocessing v1.4.4 20201116 Yu Morishita, GSI @@ -132,14 +131,14 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.4.5"; date=20201118; author="Y. Morishita" + ver="1.4.6"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ## For parallel processing global n_para_gap, G, Aloop, unwpatch, imdates, incdir, ifgdir, length, width,\ coef_r2m, ifgdates, ref_unw, cycle, keep_incfile, resdir, restxtfile, \ - cmap_vel, wavelength + cmap_vel, cmap_wrap, wavelength #%% Set default @@ -161,6 +160,7 @@ def main(argv=None): cmap_vel = SCM.roma.reversed() cmap_noise = 'viridis' cmap_noise_r = 'viridis_r' + cmap_wrap = SCM.romaO q = multi.get_context('fork') @@ -827,7 +827,7 @@ def inc_png_wrapper(imx): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [unw, inc, inc-unw]] title3 = ['Daisy-chain IFG ({}pi/cycle)'.format(cycle*2), 'Inverted ({}pi/cycle)'.format(cycle*2), 'Difference ({}pi/cycle)'.format(cycle*2)] pngfile = os.path.join(incdir, '{}.increment.png'.format(ifgd)) - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) if not keep_incfile: os.remove(incfile) diff --git a/bin/LiCSBAS16_filt_ts.py b/bin/LiCSBAS16_filt_ts.py index f71ba8c..6506076 100755 --- a/bin/LiCSBAS16_filt_ts.py +++ b/bin/LiCSBAS16_filt_ts.py @@ -1,10 +1,7 @@ #!/usr/bin/env python3 """ -v1.4.3 20201118 Yu Morishita, GSI +v1.4.4 20201119 Yu Morishita, GSI -======== -Overview -======== This script applies spatio-temporal filter (HP in time and LP in space with gaussian kernel, same as StaMPS) to the time series of displacement. Deramping (1D, bilinear, or 2D polynomial) can also be applied if -r option is used. Topography-correlated components (linear with elevation) can also be subtracted with --hgt_linear option simultaneously with deramping before spatio-temporal filtering. The impact of filtering (deramp and linear elevation as well) can be visually checked by showing 16filt*/*png. A stable reference point is determined after the filtering as well as Step 1-3. =============== @@ -67,6 +64,8 @@ """ #%% Change log ''' +v1.4.4 20201119 Yu Morishita, GSI + - Change default cmap for wrapped phase from insar to SCM.romaO v1.4.3 20201118 Yu Morishita, GSI - Again Bug fix of multiprocessing v1.4.2 20201116 Yu Morishita, GSI @@ -123,14 +122,14 @@ def main(argv=None): argv = sys.argv start = time.time() - ver="1.4.3"; date=20201118; author="Y. Morishita" + ver="1.4.4"; date=20201119; author="Y. Morishita" print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True) ## for parallel processing global cum, mask, deg_ramp, hgt_linearflag, hgt, hgt_min, hgt_max,\ filtcumdir, filtincdir, imdates, cycle, coef_r2m, models, \ - filtwidth_yr, filtwidth_km, dt_cum, x_stddev, y_stddev, mask2 + filtwidth_yr, filtwidth_km, dt_cum, x_stddev, y_stddev, mask2, cmap_wrap ## global cum_org from hdf5 contaminate in paralell warpper? So pass them by arg. @@ -157,6 +156,7 @@ def main(argv=None): cmap_vel = SCM.roma.reversed() cmap_noise_r = 'viridis_r' + cmap_wrap = SCM.romaO q = multi.get_context('fork') @@ -599,7 +599,7 @@ def deramp_wrapper(args): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [cum_bf, fit_hgt, _cum*mask]] title3 = ['Before hgt-linear (STD: {:.1f}mm)'.format(std_before), 'hgt-linear phase ({:.1f}mm/km)'.format(model[-1]*1000), 'After hgt-linear (STD: {:.1f}mm)'.format(std_after)] pngfile = os.path.join(filtcumdir, imdates[i]+'_hgt_linear.png') - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) pngfile = os.path.join(filtcumdir, imdates[i]+'_hgt_corr.png') title = '{} ({:.1f}mm/km, based on {}<=hgt<={})'.format(imdates[i], model[-1]*1000, hgt_min, hgt_max) @@ -615,7 +615,7 @@ def deramp_wrapper(args): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [_cum_org*mask, ramp, _cum_org*mask-ramp]] pngfile = os.path.join(filtcumdir, imdates[i]+'_deramp.png') deramp_title3 = ['Before deramp ({}pi/cycle)'.format(cycle*2), 'ramp phase (deg:{})'.format(deg_ramp), 'After deramp ({}pi/cycle)'.format(cycle*2)] - plot_lib.make_3im_png(data3, pngfile, 'insar', deramp_title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, deramp_title3, vmin=-np.pi, vmax=np.pi, cbar=False) return _cum, model @@ -637,7 +637,7 @@ def deramp_wrapper2(args): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [inc+fit_hgt-fit_hgt1, fit_hgt-fit_hgt1, inc]] title3 = ['Before hgt-linear (STD: {:.1f}mm)'.format(std_before), 'hgt-linear phase ({:.1f}mm/km)'.format((models[i][-1]-models[i-1][-1])*1000), 'After hgt-linear (STD: {:.1f}mm)'.format(std_after)] pngfile = os.path.join(filtincdir, '{}_{}_hgt_linear.png'.format(imdates[i-1], imdates[i])) - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) pngfile = os.path.join(filtincdir, '{}_{}_hgt_corr.png'.format(imdates[i-1], imdates[i])) title = '{}_{} ({:.1f}mm/km, based on {}<=hgt<={})'.format(imdates[i-1], imdates[i], (models[i][-1]-models[i-1][-1])*1000, hgt_min, hgt_max) @@ -657,7 +657,7 @@ def deramp_wrapper2(args): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [inc_org, ramp-ramp1, inc_org-(ramp-ramp1)]] pngfile = os.path.join(filtincdir, '{}_{}_deramp.png'.format(imdates[i-1], imdates[i])) deramp_title3 = ['Before deramp ({}pi/cycle)'.format(cycle*2), 'ramp phase (deg:{})'.format(deg_ramp), 'After deramp ({}pi/cycle)'.format(cycle*2)] - plot_lib.make_3im_png(data3, pngfile, 'insar', deramp_title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, deramp_title3, vmin=-np.pi, vmax=np.pi, cbar=False) #%% @@ -711,7 +711,7 @@ def filter_wrapper(i): data3 = [np.angle(np.exp(1j*(data/coef_r2m/cycle))*cycle) for data in [cum[i, :, :]*mask, cum_hptlps*mask, _cum_filt*mask]] title3 = ['Before filter ({}pi/cycle)'.format(cycle*2), 'Filter phase ({}pi/cycle)'.format(cycle*2), 'After filter ({}pi/cycle)'.format(cycle*2)] pngfile = os.path.join(filtcumdir, imdates[i]+'_filt.png') - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) return _cum_filt @@ -729,7 +729,7 @@ def filter_wrapper2(args): 'Filter phase ({}pi/cycle)'.format(cycle*2), 'After filter ({}pi/cycle)'.format(cycle*2)] pngfile = os.path.join(filtincdir, '{}_{}_filt.png'.format(imdates[i-1], imdates[i])) - plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False) + plot_lib.make_3im_png(data3, pngfile, cmap_wrap, title3, vmin=-np.pi, vmax=np.pi, cbar=False) #%% main diff --git a/bin/LiCSBAS_disp_img.py b/bin/LiCSBAS_disp_img.py index f4485cd..afd56ce 100755 --- a/bin/LiCSBAS_disp_img.py +++ b/bin/LiCSBAS_disp_img.py @@ -2,9 +2,6 @@ """ v1.9 20201111 Yu Morishita, GSI -======== -Overview -======== This script displays an image file. ===== @@ -20,7 +17,7 @@ -c Colormap name (see below for available colormap) - https://matplotlib.org/tutorials/colors/colormaps.html - http://www.fabiocrameri.ch/colourmaps.php - - insar + - insar (GAMMA standard rainbow color for wrapped phase) (Default: SCM.roma_r, reverse of SCM.roma) --cmin|cmax Min|max values of color (Default: None (auto)) --auto_crange % of color range used for automatic determination (Default: 99)