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#!/usr/bin/env python3 """ ======== Overview ======== This script makes a mask for time series using several noise indices. The pixel is masked if any of the values of the noise indices for a pixel is worse (larger or smaller) than a specified threshold. =============== Input & output files =============== Inputs in TS_GEOCml*/ : - results/[vel, coh_avg, n_unw, vstd, maxTlen, n_gap, stc, n_ifg_noloop, n_loop_err, resid_rms, n_nullify coh_avg_XX, n_loop_err_rat, loop_ph_avg_abs, n_gap_merged] - info/13parameters.txt Outputs in TS_GEOCml*/ - mask_ts[_mskd].png : Quick-look image of mask and noise indices - results/ - vel.mskd[.png] : Masked velocity - mask[.png] : Mask - info/15parameters.txt : List of used parameters ===== Usage ===== LiCSBAS15_mask_ts.py -t tsadir [-c coh_thre] [-u n_unw_r_thre] [-v vstd_thre] [-T maxTlen_thre] [-g n_gap_thre] [-s stc_thre] [-i n_ifg_noloop_thre] [-l n_loop_err_thre] [-r resid_rms_thre] [--vmin float] [--vmax float] [--keep_isolated] [--noautoadjust] [--avg_phase_bias float] [--n_gap_use_merged] -t Path to the TS_GEOCml* dir. -c Threshold of coh_avg (average coherence) -u Threshold of n_unw (number of used unwrap data) (Note this value is ratio to the number of images; i.e., 1.5*n_im) -v Threshold of vstd (std of the velocity (mm/yr)) -T Threshold of maxTlen (max time length of connected network (year)) -g Threshold of n_gap (number of gaps in network) -s Threshold of stc (spatio-temporal consistency (mm)) -i Threshold of n_ifg_noloop (number of pixels from ifgs with no loop) -l Threshold of n_loop_err (number of loop_err) - in case of nullification in step 12, this will apply the threshold on n_nullify NOTE: we now test and will update the -l parameter to be a ratio (<=1 where 1 means all bad). Future: default: 0.7 -L Threshold of n_loop_err_ratio (number of loop_err divided by number of loops). Use number 0-1. (preferred solution) -r Threshold of resid_rms (RMS of residuals in inversion (mm)) --v[min|max] Min|Max value for output figure of velocity (Default: auto) --avg_phase_bias Threshold of the average absolute loop phase misclosure (phase bias) [rad] to use for masking (Default: not use. --avg_phase_bias 1 can be recommended) --n_gap_use_merged Would use merged n_gaps instead of original (merging neighbouring gaps to one) --keep_isolated Keep (not mask) isolated pixels (Default: they are masked by stc) --noautoadjust Do not auto adjust threshold when all pixels are masked (Default: do auto adjust) --sbovl use the sbovl masking thresholds and indices --sbovl_abs use the sbovl abs results from previous step like bootvel_abs_notide_noiono --tide use tide corrected results (if exist) like bootvel_abs_notide --iono use iono corrected results (if exist) like bootvel_abs_notide_noiono ##TODO the corrections applied in the step 16 for the sboi before spatio-temporal filter, these flag was open to testing absolute sense of boi and its correction, need to be removed/organized after better testing. #MN Default thresholds: C-band : -c 0.05 -u 1.5 -v 100 -T 1 -g 10 -s 5 -i 50 -l 5 -r 2 L-band : -c 0.01 -u 1 -v 200 -T 1 -g 1 -s 10 -i 50 -l 1 -r 10 SBOI : -c 0.05 -u 0.5 -g 50 -s 10 -r 15 -i 1000 -L 0.5 """ #%% Change log ''' 20241115 ML, UoL - use of n_gaps_merge 20241103 MNergizci, UoL - add sbovl flag 20241107 ML, UoL - updated mask_ts.png 20240628 ML, UoL - use of avg_phase_bias 20231121 ML, UoL - use of n_nullify (with -l) and ratios of both loop_err and n_nullify with -L (should be better, will move to this, but now TO_CHECK status v1.8.2 20211129 Milan Lazecky, Uni of Leeds - Change default -i as global number of no_loop_ifgs + 1 v1.8.1 20200911 Yu Morishita, GSI - Change default to -i 50 v1.8 20200902 Yu Morishita, GSI - Use nearest interpolation to avoid expanded nan v1.7 20200224 Yu Morishita, Uni of Leeds and GSI - Change color of mask_ts.png - Update about parameters.txt v1.6 20200124 Yu Morishita, Uni of Leeds and GSI - Increase default vstd threshold because vstd is not useful v1.5 20200123 Yu Morishita, Uni of Leeds and GSI - Change default n_gap threshold for L-band to 1 v1.4 20200122 Yu Morishita, Uni of Leeds and GSI - Remove close fig which can cause error v1.3 20191128 Yu Morishita, Uni of Leeds and GSI - Add noautoadjust option v1.2 20190918 Yu Morishita, Uni of Leeds and GSI - Output mask_ts_mskd.png v1.1 20190906 Yu Morishita, Uni of Leeds and GSI - tight_layout and auto ajust of size for png v1.0 20190724 Yu Morishita, Uni of Leeds and GSI - Original implementation ''' #%% Import from LiCSBAS_meta import * import getopt import os, glob, re os.environ['QT_QPA_PLATFORM']='offscreen' import sys import time import numpy as np import cmcrameri.cm as cmc import LiCSBAS_io_lib as io_lib import LiCSBAS_plot_lib as plot_lib import warnings import matplotlib with warnings.catch_warnings(): ## To silence user warning warnings.simplefilter('ignore', UserWarning) matplotlib.use('Agg') from matplotlib import pyplot as plt from matplotlib.patches import Rectangle plt.rcParams['axes.titlesize'] = 10 class Usage(Exception): """Usage context manager""" def __init__(self, msg): self.msg = msg #%% def add_subplot(fig, i, data, vmin, vmax, cmap, title, refarea = None, refcolor = 'red'): ''' refarea should be as tuple, e.g. (refx1, refx2, refy1, refy2)''' ax = fig.add_subplot(3, 5, i+1) #index start from 1 im = ax.imshow(data, vmin=vmin, vmax=vmax, cmap=cmap, interpolation='nearest') fig.colorbar(im) ax.set_title('{0}'.format(title)) ax.set_xticklabels([]) ax.set_yticklabels([]) if refarea: refx1, refx2, refy1, refy2 = refarea if refx2-refx1 < 5 and refy2-refy1 < 5: linewidth = 2 refx1-=1 refx2 += 1 refy1 -= 1 refy2 += 1 else: linewidth = 1 rect = Rectangle((refx1-0.5, refy1-0.5), refx2-refx1, refy2-refy1, fill=False, edgecolor=refcolor, linewidth=linewidth) ax.add_patch(rect) return ax #%% Main def main(argv=None): #%% Check argv if argv == None: argv = sys.argv start = time.time() 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) #%% Set default tsadir = [] thre_dict = {} vmin = [] vmax = [] use_coh_freq = False keep_isolated = False auto_adjust = True n_gap_use_merged = False sbovl = False sbovl_abs = False cmap_vel = cmc.roma.reversed() cmap_noise = 'viridis' cmap_noise_r = 'viridis_r' # tide = False # iono = False #%% Read options try: try: opts, args = getopt.getopt(argv[1:], "ht:c:u:v:g:i:l:L:r:T:s:", ["version", "help", "vmin=", "vmax=", "avg_phase_bias=", "use_coh_freq", "keep_isolated", "noautoadjust","n_gap_use_merged","sbovl", "sbovl_abs", "tide", "iono"]) except getopt.error as msg: raise Usage(msg) for o, a in opts: if o == '-h' or o == '--help': print(__doc__) return 0 elif o == '-t': tsadir = a elif o == '-c': thre_dict['coh_avg'] = float(a) elif o == '-u': thre_dict['n_unw_r'] = float(a) elif o == '-v': thre_dict['vstd'] = float(a) elif o == '-T': thre_dict['maxTlen'] = float(a) elif o == '-g': thre_dict['n_gap'] = int(a) elif o == '-s': thre_dict['stc'] = float(a) elif o == '-i': thre_dict['n_ifg_noloop'] = int(a) elif o == '-l': thre_dict['n_loop_err'] = int(a) # TODO: after checking use of the ratio, remove this param and use the ratio only (below) elif o == '-L': thre_dict['n_loop_err_rat'] = float(a) #thre_dict['n_nullify_rat'] = float(a) # 2024/01: n_loop_err_Rat is now before nullification elif o == '-r': thre_dict['resid_rms'] = float(a) elif o == '--avg_phase_bias': thre_dict['loop_ph_avg_abs'] = float(a) elif o == '--vmin': vmin = float(a) elif o == '--vmax': vmax = float(a) elif o == '--use_coh_freq': use_coh_freq = True print('not used yet') elif o == '--keep_isolated': keep_isolated = True elif o == '--noautoadjust': auto_adjust = False elif o == '--n_gap_use_merged': n_gap_use_merged = True elif o == '--sbovl': sbovl = True elif o == '--sbovl_abs': sbovl = True sbovl_abs = True # elif o == '--tide': # tide = True # elif o == '--iono': # iono = True if not tsadir: raise Usage('No tsa directory given, -t is not optional!') elif not os.path.isdir(tsadir): raise Usage('No {} dir exists!'.format(tsadir)) elif not os.path.isdir(os.path.join(tsadir, 'results')): raise Usage('No results dir exists in {}!'.format(tsadir)) except Usage as err: print("\nERROR:", file=sys.stderr, end='') print(" "+str(err.msg), file=sys.stderr) print("\nFor help, use -h or --help.\n", file=sys.stderr) return 2 #%% Directory and file setting and get info tsadir = os.path.abspath(tsadir) resultsdir = os.path.join(tsadir,'results') inparmfile = os.path.join(tsadir, 'info', '13parameters.txt') if not os.path.exists(inparmfile): ## for old LiCSBAS13 or < ## gt: greater values than thre are masked ## lt: more little values than thre are masked (coh_avg, n_unw, maxTlen) if 'n_loop_err' in thre_dict and 'n_loop_err' not in names: names += ['n_loop_err'] units += [''] gt_lt += ['gt'] if 'loop_ph_avg_abs' in thre_dict: names += ['loop_ph_avg_abs'] units += ['rad'] gt_lt += ['gt'] ### Get size and ref width = int(io_lib.get_param_par(inparmfile, 'range_samples')) length = int(io_lib.get_param_par(inparmfile, 'azimuth_lines')) wavelength = float(io_lib.get_param_par(inparmfile, 'wavelength')) n_im = int(io_lib.get_param_par(inparmfile, 'n_im')) # %% Get both 12 and 13 ref points, used only for plotting: infodir = os.path.join(tsadir, 'info') ref12file = os.path.join(infodir, '120ref.txt') # first checking if the 120ref exists (would be prioritised by step 12) if not os.path.exists(ref12file): ref12file = os.path.join(infodir, '12ref.txt') ref13file = os.path.join(infodir, '13ref.txt') with open(ref12file, "r") as f: ref12area = f.read().split()[0] # str, x1/x2/y1/y2 ref12x1, ref12x2, ref12y1, ref12y2 = [int(s) for s in re.split('[:/]', ref12area)] with open(ref13file, "r") as f: ref13area = f.read().split()[0] # str, x1/x2/y1/y2 ref13x1, ref13x2, ref13y1, ref13y2 = [int(s) for s in re.split('[:/]', ref13area)] #%% Determine default thresholds depending on frequency band if not 'maxTlen' in thre_dict: thre_dict['maxTlen'] = 1 if (not 'n_loop_err_rat' in thre_dict) and ('n_loop_err_rat' in names): thre_dict['n_loop_err_rat'] = 0.7 if not 'n_ifg_noloop' in thre_dict: try: thre_dict['n_ifg_noloop'] = len(os.listdir(os.path.join(tsadir, '12no_loop_ifg_ras')))+1 except: thre_dict['n_ifg_noloop'] = 500 if wavelength > 0.2: ## L-band if not 'coh_avg' in thre_dict: thre_dict['coh_avg'] = 0.01 if not 'n_unw_r' in thre_dict: thre_dict['n_unw_r'] = 1.0 if not 'vstd' in thre_dict: thre_dict['vstd'] = 200 if not 'n_gap' in thre_dict: thre_dict['n_gap'] = 1 if not 'stc' in thre_dict: thre_dict['stc'] = 10 if (not 'n_loop_err' in thre_dict) and ('n_loop_err' in names): thre_dict['n_loop_err'] = 1 if not 'resid_rms' in thre_dict: thre_dict['resid_rms'] = 10 if wavelength < 0.2: ## C-band if not 'coh_avg' in thre_dict: thre_dict['coh_avg'] = 0.15 if not 'n_unw_r' in thre_dict: thre_dict['n_unw_r'] = 1.5 if not 'vstd' in thre_dict: thre_dict['vstd'] = 100 if not 'n_gap' in thre_dict: thre_dict['n_gap'] = 10 if not 'stc' in thre_dict: thre_dict['stc'] = 10 # tested as more appropriate if not sbovl: if (not 'n_loop_err' in thre_dict) and ('n_loop_err' in names): thre_dict['n_loop_err'] = 5 if not 'resid_rms' in thre_dict: thre_dict['resid_rms'] = 15 thre_dict['n_unw'] = int(n_im*thre_dict['n_unw_r']) if n_gap_use_merged: thre_dict['n_gap_merged'] = thre_dict.pop('n_gap') #%% Read data # breakpoint() if sbovl_abs: # velfile = os.path.join(resultsdir,'vel_ransac_abs_notide_noiono') if tide and iono: velfile = os.path.join(resultsdir,'bootvel_abs_notide_noiono') elif tide and not iono: velfile = os.path.join(resultsdir,'bootvel_abs_notide') elif not tide and iono: velfile = os.path.join(resultsdir,'bootvel_abs_noiono') elif not tide and not iono: velfile = os.path.join(resultsdir,'bootvel_abs') #not exist velfile, so use vel if not os.path.exists(velfile): velfile = os.path.join(resultsdir,'vel') print(f'Using {velfile}') else: velfile = os.path.join(resultsdir,'vel') print(f'Using {velfile}') if not os.path.exists(velfile): raise FileNotFoundError(f"Velocity file not found: {velfile}") vel = io_lib.read_img(velfile, length, width) bool_nan = np.isnan(vel) bool_nan[vel==0] = True ## Ref point. Unmask later n_pt_all = (~bool_nan).sum() ## Number of unnan points data_dict = {} for name in names: file = os.path.join(resultsdir, name) data_dict[name] = io_lib.read_img(file, length, width) ## stc is always nan at isolted pixels. if keep_isolated: ## Give 0 to keep isolated pixels data_dict['stc'][np.isnan(data_dict['stc'])] = 0 else: ## Give stc_thre to remove isolated pixels data_dict['stc'][np.isnan(data_dict['stc'])] = thre_dict['stc']+1 #%% Make mask ### Evaluate only valid pixels in vel mask_pt = np.ones_like(vel)[~bool_nan] mskd_rate = [] for i, name in enumerate(names): _data = data_dict[name][~bool_nan] _thre = thre_dict[name] if gt_lt[i] == 'lt': ## coh_avg, n_unw, maxTlen ## Multiply -1 to treat as if gt _data = -1*_data _thre = -1*_thre ### First check if the thre masks not all pixels ### If all pixels are masked, change thre to the max/min value if auto_adjust: minvalue = np.nanmin(_data) if minvalue > _thre: print('\nAll pixels would be masked with {} thre of {}'.format(name, thre_dict[name]), flush=True) thre_dict[name] = np.ceil(minvalue) _thre = thre_dict[name] if gt_lt[i] == 'lt': thre_dict[name] = -1*thre_dict[name] print('Automatically change the thre to {} (ceil of min value)'.format(thre_dict[name]), flush=True) ### Make mask for this index with warnings.catch_warnings(): ## To silence RuntimeWarning of nan width: figsize_y = 9 if len(names) == 12: figsize_x = int(figsize_y*4/3*width/length+2) else: figsize_x = int(figsize_y * 5 / 3 * width / length + 2) # adding extra column if figsize_x < 6: figsize_x = 6 else: figsize_x = 12 if len(names) == 12: figsize_y = int(figsize_x/4*3*length/width) else: figsize_y = int(figsize_x / 5 * 3 * length / width) if figsize_y < 4: figsize_y = 4 fig = plt.figure(figsize = (figsize_x, figsize_y)) fig2 = plt.figure(figsize = (figsize_x, figsize_y)) ##First 3; vel.mskd, vel, mask data = [vel_mskd, vel, mask] titles = ['vel.mskd', 'vel', 'mask'] vmins = [vmin, vmin, 0] vmaxs = [vmax, vmax, 1] cmaps = [cmap_vel, cmap_vel, cmap_noise] refarea = (ref13x1, ref13x2, ref13y1, ref13y2) refcolor = 'black' for i in range(3): ax1 = add_subplot(fig, i, data[i], vmins[i], vmaxs[i], cmaps[i], titles[i], refarea, refcolor) i2 = 0 if i==1 else 1 if i==0 else 2 # inv vel and vel.mskd ax2 = add_subplot(fig2, i2, data[i], vmins[i], vmaxs[i], cmaps[i], titles[i], refarea, refcolor) # for mask, also show the previous refarea from step 12: rect1 = Rectangle((ref12x1 - 0.5, ref12y1 - 0.5), ref12x2 - ref12x1, ref12y2 - ref12y1, fill=False, edgecolor='red', linewidth=1) rect2 = Rectangle((ref12x1 - 0.5, ref12y1 - 0.5), ref12x2 - ref12x1, ref12y2 - ref12y1, fill=False, edgecolor='red', linewidth=1) ax1.add_patch(rect1) ax2.add_patch(rect2) ## Next 9+ noise indices mask_nan = mask.copy() mask_nan[mask==0] = np.nan for i, name in enumerate(names): data = data_dict[name] ## Mask nan in vel for each indeces except coh_avg and n_unw if not name == 'coh_avg' and not name == 'n_unw': data[bool_nan] = np.nan if gt_lt[i] == 'lt': ## coh_avg, n_unw, maxTlen cmap = cmap_noise vmin_n = thre_dict[name]*0.8 vmax_n = np.nanmax(data) else: cmap = cmap_noise_r vmin_n = 0 vmax_n = thre_dict[name]*1.2 # add refp12(0) for loop_err, and refp13 for resid_rms: # max: # names = ['coh_avg', 'n_unw', 'vstd', 'maxTlen', 'n_gap', 'stc', 'n_ifg_noloop', 'n_loop_err_rat', 'resid_rms', 'loop_ph_avg_abs', 'n_loop_err' ] if name in ['n_loop_err_rat', 'loop_ph_avg_abs', 'n_loop_err']: refarea = (ref12x1, ref12x2, ref12y1, ref12y2) refcolor = 'red' elif name in ['resid_rms', 'vstd']: refarea = (ref13x1, ref13x2, ref13y1, ref13y2) refcolor = 'black' else: refarea = None refcolor = None title = '{} {}({})'.format(name, units[i], thre_dict[name]) add_subplot(fig, i+3, data, vmin_n, vmax_n, cmap, title, refarea, refcolor) add_subplot(fig2, i+3, data*mask_nan, vmin_n, vmax_n, cmap, title, refarea, refcolor) #i+3 because 3 data already plotted fig.tight_layout() fig.savefig(maskts_png) fig2.tight_layout() fig2.savefig(maskts2_png) # plt.close(fig=fig) #%% Output vel.mskd and mask velmskdfile = velfile + '.mskd' vel_mskd.tofile(velmskdfile) pngfile = velmskdfile+'.png' title = 'Masked velocity (mm/yr)' plot_lib.make_im_png(vel_mskd, pngfile, cmap_vel, title, vmin, vmax) maskfile = os.path.join(resultsdir,'mask') mask.tofile(maskfile) pngfile = maskfile+'.png' title = 'Mask' plot_lib.make_im_png(mask, pngfile, cmap_noise, title, 0, 1) #%% Finish elapsed_time = time.time()-start hour = int(elapsed_time/3600) minite = int(np.mod((elapsed_time/60),60)) sec = int(np.mod(elapsed_time,60)) print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour,minite,sec)) print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0]))) print('Output png: {}\n'.format(os.path.abspath(maskts_png)), flush=True) #%% main if __name__ == "__main__": sys.exit(main())