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#!/usr/bin/env python3 """ ======== Overview ======== This script: - copies file 130cum*.h5 to cum.h5 - copies folder 130results* to results - calcs n_unw, n_loop_err, coh_avg - assumbles all results into cum.h5 =============== Input & output files =============== Inputs in GEOCml*/ (--comp_cc_dir): - slc.mli.par - yyyymmdd_yyyymmdd/ - yyyymmdd_yyyymmdd.cc Inputs in GEOCml*/ (--unw_dir): - yyyymmdd_yyyymmdd/ - yyyymmdd_yyyymmdd.unw Inputs in TS_GEOCml*/ : - 130cum*.h5 : Cumulative displacement (time-seires) in mm from final iteration, to copy to cum.h5 - 130results* : Results from final iteration of automatic correction, to copy to results -vel[.png] : Velocity in mm/yr (positive means LOS decrease; uplift) - vintercept[.png] : Constant part of linear velocity (c for vt+c) in mm - resid_rms[.png] : RMS of residual in mm - n_gap[.png] : Number of gaps in SB network - n_ifg_noloop[.png] : Number of ifgs with no loop - maxTlen[.png] : Max length of continous SB network in year - info - 120ref.txt : Reference window Outputs in TS_GEOCml*/ : - cum.h5 : Cumulative displacement (time-seires) in mm - results/ - n_unw[.png] : Number of available unwrapped data to be used - coh_avg[.png] : Average coherence - n_loop_err[.png] : Number of remaining loop errors (>pi) in data to be used ===== Usage ===== LiCSBAS133_write_h5.py [-h] [-f FRAME_DIR] [-c COMP_CC_DIR] [-t TS_DIR] [--suffix SUFFIX] """ #%% Change log ''' v1.0 20220928 Qi Ou, Leeds Uni ''' #%% Import import os import time import shutil import numpy as np import h5py as h5 from pathlib import Path import argparse import sys import re import xarray as xr import LiCSBAS_io_lib as io_lib import LiCSBAS_tools_lib as tools_lib import LiCSBAS_loop_lib as loop_lib import LiCSBAS_plot_lib as plot_lib class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawDescriptionHelpFormatter): ''' Use a multiple inheritance approach to use features of both classes. The ArgumentDefaultsHelpFormatter class adds argument default values to the usage help message The RawDescriptionHelpFormatter class keeps the indentation and line breaks in the ___doc___ ''' pass def init_args(): global args parser = argparse.ArgumentParser(description=__doc__, formatter_class=CustomFormatter) parser.add_argument('-f', dest='frame_dir', default="./", help="directory of LiCSBAS output") # parser.add_argument('-d', dest='unw_dir', help="folder containing unw input to be corrected, if not given, use $comp_cc_dir_$suffix") parser.add_argument('-c', dest='comp_cc_dir', default="GEOCml10GACOS", help="folder containing connected components and coherence files") parser.add_argument('-t', dest='ts_dir', default="TS_GEOCml10GACOS", help="folder containing time series") parser.add_argument('-l', dest='ifg_list', default=None, type=str, help="text file containing a list of ifgs, if not given, all ifgs in -c are read") parser.add_argument('--suffix', default="", type=str, help="suffix of the final iteration") parser.add_argument('--stay', default=False, action='store_true', help="don't copy to results, save everything in results$suffix") args = parser.parse_args() def start(): global start_time # intialise and print info on screen start_time = time.time() ver="1.0"; date=20221020; author="Qi Ou" print("\n{} ver{} {} {}".format(os.path.basename(sys.argv[0]), ver, date, author), flush=True) print("{} {}".format(os.path.basename(sys.argv[0]), ' '.join(sys.argv[1:])), flush=True) def finish(): #%% Finish elapsed_time = time.time() - start_time 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{} {}".format(os.path.basename(sys.argv[0]), ' '.join(sys.argv[1:])), flush=True) print('Output directory: {}\n'.format(os.path.abspath(tsadir))) def set_input_output(): global ccdir, ifgdir, tsadir, infodir, last_result_dir, resultsdir, last_cumh5file, cumh5file, ifgdates # define input directories and file ccdir = os.path.abspath(os.path.join(args.frame_dir, args.comp_cc_dir)) if args.suffix == "1": ifgdir = os.path.abspath(os.path.join(args.frame_dir, args.comp_cc_dir)) else: ifgdir = os.path.abspath(os.path.join(args.frame_dir, args.comp_cc_dir+args.suffix)) if args.ifg_list: ifgdates = io_lib.read_ifg_list(args.ifg_list) else: ifgdates = tools_lib.get_ifgdates(ifgdir) tsadir = os.path.abspath(os.path.join(args.frame_dir, args.ts_dir)) infodir = os.path.join(tsadir, 'info') last_result_dir = os.path.join(tsadir, '130results{}'.format(args.suffix)) last_cumh5file = os.path.join(tsadir, '130cum{}.h5'.format(args.suffix)) # define output directory and file if args.stay: resultsdir = last_result_dir cumh5file = last_cumh5file else: resultsdir = os.path.join(tsadir, 'results') cumh5file = os.path.join(tsadir, 'cum.h5') # copy everything from last iter to final shutil.copyfile(last_cumh5file, cumh5file) shutil.copytree(last_result_dir, resultsdir, dirs_exist_ok=True) def read_length_width(): global length, width # read ifg size mlipar = os.path.join(ccdir, 'slc.mli.par') width = int(io_lib.get_param_par(mlipar, 'range_samples')) length = int(io_lib.get_param_par(mlipar, 'azimuth_lines')) def calc_n_unw(): print("Computing number of unw per pixel...") n_unw = np.zeros((length, width), dtype=np.float32) for ifgd in ifgdates: unwfile = os.path.join(ifgdir, ifgd, ifgd+'.unw') unw = io_lib.read_img(unwfile, length, width) unw[unw == 0] = np.nan # Fill 0 with nan n_unw += ~np.isnan(unw) # Summing number of unnan unw ### Write to file n_unw[n_unw == 0] = np.nan n_unwfile = os.path.join(resultsdir, 'n_unw') n_unw.tofile(n_unwfile) ### Save png title = 'Number of used unw data' cmap_noise = 'viridis' imdates = tools_lib.ifgdates2imdates(ifgdates) n_im = len(imdates) plot_lib.make_im_png(n_unw, n_unwfile+'.png', cmap_noise, title, n_im) return n_unw def calc_coh_avg(): print("Computing average coherence...") # calc n_unw and avg_coh of final data set coh_avg = np.zeros((length, width), dtype=np.float32) n_coh = np.zeros((length, width), dtype=np.int16) for ifgd in ifgdates: ccfile = os.path.join(ccdir, ifgd, ifgd+'.cc') if os.path.getsize(ccfile) == length*width: coh = io_lib.read_img(ccfile, length, width, np.uint8) coh = coh.astype(np.float32)/255 else: coh = io_lib.read_img(ccfile, length, width) coh[np.isnan(coh)] = 0 # Fill nan with 0 coh_avg += coh n_coh += (coh!=0) coh_avg[n_coh==0] = np.nan n_coh[n_coh==0] = 1 #to avoid zero division coh_avg = coh_avg/n_coh coh_avg[coh_avg==0] = np.nan ### Write to file coh_avgfile = os.path.join(resultsdir, 'coh_avg') coh_avg.tofile(coh_avgfile) ### Save png title = 'Average coherence' cmap_noise = 'viridis' plot_lib.make_im_png(coh_avg, coh_avgfile+'.png', cmap_noise, title) def calc_n_loop_error(n_unw): ''' same as loop_closure_4th in LiCSBAS12_loop_closure.py ''' print('Compute n_loop_error...', flush=True) # read reference reffile = os.path.join(infodir, '120ref.txt') with open(reffile, "r") as f: refarea = f.read().split()[0] # str, x1/x2/y1/y2 refx1, refx2, refy1, refy2 = [int(s) for s in re.split('[:/]', refarea)] # create 3D cube - False means presumed error in the loop a = np.full((length, width,len(ifgdates)), False) da = xr.DataArray( data=a, dims=[ "y", "x", "ifgd"], coords=dict(y=np.arange(length), x=np.arange(width), ifgd=ifgdates)) ### Get loop matrix Aloop = loop_lib.make_loop_matrix(ifgdates) n_loop = Aloop.shape[0] ### Count loop error by pixel n_loop_err = np.zeros((length, width), dtype=np.float32) for i in range(0, len(Aloop)): if np.mod(i, 100) == 0: print(" {0:3}/{1:3}th loop...".format(i, n_loop), flush=True) ### Read unw unw12, unw23, unw13, ifgd12, ifgd23, ifgd13 = loop_lib.read_unw_loop_ph(Aloop[i, :], ifgdates, ifgdir, length, width) ## Compute ref ref_unw12 = np.nanmean(unw12[refy1:refy2, refx1:refx2]) ref_unw23 = np.nanmean(unw23[refy1:refy2, refx1:refx2]) ref_unw13 = np.nanmean(unw13[refy1:refy2, refx1:refx2]) ## Calculate loop phase taking into account ref phase loop_ph = unw12 + unw23 - unw13 - (ref_unw12 + ref_unw23 - ref_unw13) ## Count number of loops with suspected unwrap error (>pi) loop_ph[np.isnan(loop_ph)] = 0 # to avoid warning is_ok = np.abs(loop_ph) < np.pi da.loc[:, :, ifgd12] = np.logical_or(da.loc[:, :, ifgd12], is_ok) da.loc[:, :, ifgd23] = np.logical_or(da.loc[:, :, ifgd23], is_ok) da.loc[:, :, ifgd13] = np.logical_or(da.loc[:, :, ifgd13], is_ok) n_loop_err = n_loop_err + ~is_ok # suspected unw error # write to file n_loop_err[np.isnan(n_unw)] = np.nan # n_loop_err = np.array(n_loop_err) n_loop_err_file = os.path.join(resultsdir, 'n_loop_err') n_loop_err.tofile(n_loop_err_file) # save png title = 'Number of unclosed loops' cmap_noise_r = 'viridis_r' plot_lib.make_im_png(n_loop_err, n_loop_err_file+'.png', cmap_noise_r, title) def write_h5(): # Write additional results to h5 print('\nWriting to HDF5 file...') cumh5 = h5.File(cumh5file, 'a') compress = 'gzip' indices = ['coh_avg', 'hgt', 'n_loop_err', 'n_unw', 'slc.mli'] for index in indices: print(index) file = os.path.join(resultsdir, index) if os.path.exists(file): data = io_lib.read_img(file, length, width) cumh5.create_dataset(index, data=data, compression=compress) else: print(' {} not exist in results dir. Skip'.format(index)) LOSvecs = ['E.geo', 'N.geo', 'U.geo'] for LOSvec in LOSvecs: file = os.path.join(ccdir, LOSvec) if os.path.exists(file): data = io_lib.read_img(file, length, width) cumh5.create_dataset(LOSvec, data=data, compression=compress) else: print(' {} not exist in GEOCml dir. Skip'.format(LOSvec)) cumh5.close() def main(): global ifgdates # intialise start() init_args() # directory settings set_input_output() read_length_width() # calc quality stats based on the final corrected unw n_unw = calc_n_unw() calc_coh_avg() calc_n_loop_error(n_unw) # compile all results to h5 write_h5() # report finish finish() if __name__ == '__main__': main()