############################################################ # Program is part of MintPy # # Copyright (c) 2013, Zhang Yunjun, Heresh Fattahi # # Author: Zhang Yunjun, Heresh Fattahi, 2013 # ############################################################ import os import warnings import numpy as np from matplotlib import pyplot as plt from mintpy.objects import ifgramStack from mintpy.utils import plot as pp, readfile, utils as ut # suppress UserWarning from matplotlib warnings.filterwarnings("ignore", category=UserWarning, module="matplotlib") ########################### Sub Function ############################# def read_network_info(inps): ext = os.path.splitext(inps.file)[1] print('read temporal/spatial baseline info from file:', inps.file) ## 1. Read date, pbase, date12 and coherence if ext == '.h5': stack_obj = ifgramStack(inps.file) stack_obj.open() inps.date12List = stack_obj.get_date12_list(dropIfgram=False) inps.dateList = stack_obj.get_date_list(dropIfgram=False) inps.pbaseList = stack_obj.get_perp_baseline_timeseries(dropIfgram=False) pbase12List = stack_obj.pbaseIfgram if inps.dsetName in readfile.get_dataset_list(inps.file): inps.cohList = ut.spatial_average( inps.file, datasetName=inps.dsetName, maskFile=inps.maskFile, saveList=True, checkAoi=False, )[0] elif inps.dsetName == 'pbase': inps.cohList = np.abs(stack_obj.pbaseIfgram).tolist() elif inps.dsetName == 'tbase': inps.cohList = stack_obj.tbaseIfgram.tolist() else: inps.cohList = None msg = f'{inps.dsetName} NOT found in file: {inps.file}! ' msg += 'Disable the color coding and continue' print(msg) elif ext == '.txt': inps.date12List = np.loadtxt(inps.file, dtype=bytes).astype(str)[:,0].tolist() # date12List --> dateList mDates = [i.split('_')[0] for i in inps.date12List] sDates = [i.split('_')[1] for i in inps.date12List] inps.dateList = sorted(list(set(mDates + sDates))) # pbase12List + date12List --> pbaseList pbase12List = np.loadtxt(inps.file, dtype=bytes).astype(float)[:,3] A = ifgramStack.get_design_matrix4timeseries(inps.date12List)[0] inps.pbaseList = np.zeros(len(inps.dateList), dtype=np.float32) inps.pbaseList[1:] = np.linalg.lstsq(A, np.array(pbase12List), rcond=None)[0] # cohList inps.cohList = np.loadtxt(inps.file, dtype=bytes).astype(float)[:,1] else: raise ValueError('un-recognized input file extension:', ext) print(f'number of acquisitions: {len(inps.dateList)}') print(f'number of interferograms: {len(inps.date12List)}') print(f'shift all perp baseline by {np.mean(inps.pbaseList)} to zero mean for plotting') inps.pbaseList -= np.mean(inps.pbaseList) # Optional: Read dropped date12 / date inps.dateList_drop = [] inps.date12List_drop = [] if ext == '.h5': inps.date12List_keep = ifgramStack(inps.file).get_date12_list(dropIfgram=True) inps.date12List_drop = sorted(list(set(inps.date12List) - set(inps.date12List_keep))) print('-'*50) print(f'number of interferograms marked as drop: {len(inps.date12List_drop)}') print(f'number of interferograms marked as keep: {len(inps.date12List_keep)}') mDates = [i.split('_')[0] for i in inps.date12List_keep] sDates = [i.split('_')[1] for i in inps.date12List_keep] inps.dateList_keep = sorted(list(set(mDates + sDates))) inps.dateList_drop = sorted(list(set(inps.dateList) - set(inps.dateList_keep))) print(f'number of acquisitions marked as drop: {len(inps.dateList_drop)}') if len(inps.dateList_drop) > 0: print(inps.dateList_drop) # check: pairs with invalid coherence / Bperp values (nan) # due to processing issues in the upstream insar processing flag_nan = np.logical_or(np.isnan(inps.cohList), np.isnan(pbase12List)) if np.sum(flag_nan) > 0: date12_nan = np.array(inps.date12List)[flag_nan].tolist() date12_nan = [x for x in date12_nan if x not in inps.date12List_drop] if len(date12_nan) > 0: msg = 'Invalid NaN value found in the following kept pairs for Bperp or coherence! ' msg += '\n\tThey likely have issues, check them and maybe exclude them in your network.' msg += f'\n\t{date12_nan}' raise ValueError(msg) return inps def check_colormap(inps): """Check input colormaps.""" # adjust color jump if no --cmap-vlist is input if inps.cohList is not None and '--cmap-vlist' not in inps.argv: # use template value key = 'mintpy.network.minCoherence' if key in inps.template.keys(): inps.cmap_vlist[1] = max(0.01, float(inps.template[key])) # calculate from dropped interferograms, if there is any elif len(inps.date12List_drop) > 0: idx_drop = [inps.date12List.index(i) for i in inps.date12List_drop] coh_drop = [inps.cohList[i] for i in idx_drop] inps.cmap_vlist[1] = max(coh_drop) print(f'max coherence of excluded interferograms: {max(coh_drop)}') # update default cmap_vlist[0] value if the manually input cmap_vlist[1] is too small if inps.cmap_vlist[1] <= inps.cmap_vlist[0]: inps.cmap_vlist[0] = min(0, inps.cmap_vlist[1]) # in case the manually input list is not in order inps.cmap_vlist = sorted(inps.cmap_vlist) inps.colormap = pp.ColormapExt(inps.cmap_name, vlist=inps.cmap_vlist).colormap return inps ######################################################################## def plot_network(inps): """Plot all the network info.""" # matplotlib backend setting if not inps.disp_fig: plt.switch_backend('Agg') ##---------- read / calculate inps = read_network_info(inps) ##---------- plot settings # color maps inps = check_colormap(inps) # figure size if not inps.fig_size: num_date = len(inps.dateList) if num_date <= 100: inps.fig_size = [ 6, 4] elif num_date <= 200: inps.fig_size = [ 8, 4] elif num_date <= 300: inps.fig_size = [10, 4] else: inps.fig_size = [12, 4] # save figure kwargs = dict(bbox_inches='tight', transparent=True, dpi=inps.fig_dpi) # labels in y-axis and colorbar inps.ds_name, inps.cbar_label = { 'coherence' : ['Coherence', 'Average Spatial Coherence'], 'offsetSNR' : ['SNR', 'Average Spatial SNR'], 'tbase' : ['Temp Baseline', 'Temp Baseline [day]'], 'pbase' : ['Perp Baseline', 'Perp Baseline [m]'], }[inps.dsetName] # figure names ext = 'Ion.pdf' if os.path.basename(inps.file).startswith('ion') else '.pdf' fig_names = { 'coherence' : [i+ext for i in ['pbaseHistory', 'coherenceHistory', 'coherenceMatrix', 'network']], 'offsetSNR' : [i+ext for i in ['pbaseHistory', 'SNRHistory', 'SNRMatrix', 'network']], 'tbase' : [i+ext for i in ['pbaseHistory', 'tbaseHistory', 'tbaseMatrix', 'network']], 'pbase' : [i+ext for i in ['pbaseHistory', 'pbaseRangeHistory', 'pbaseMatrix', 'network']], }[inps.dsetName] ##---------- plot # Fig 1 - Baseline History fig, ax = plt.subplots(figsize=inps.fig_size) ax = pp.plot_perp_baseline_hist( ax, inps.dateList, inps.pbaseList, vars(inps), inps.dateList_drop, ) if inps.save_fig: fig.savefig(fig_names[0], **kwargs) print(f'save figure to {fig_names[0]}') if inps.cohList is not None: # Fig 2 - Min/Max Coherence History fig, ax = plt.subplots(figsize=inps.fig_size) ax = pp.plot_coherence_history( ax, inps.date12List, inps.cohList, p_dict=vars(inps), ) if inps.save_fig: fig.savefig(fig_names[1], **kwargs) print(f'save figure to {fig_names[2]}') # Fig 3 - Coherence Matrix fig_size3 = np.mean(inps.fig_size) fig, ax = plt.subplots(figsize=[fig_size3, fig_size3]) ax = pp.plot_coherence_matrix( ax, inps.date12List, inps.cohList, inps.date12List_drop, p_dict=vars(inps), )[0] if inps.save_fig: fig.savefig(fig_names[2], **kwargs) print(f'save figure to {fig_names[1]}') # Fig 4 - Interferogram Network fig, ax = plt.subplots(figsize=inps.fig_size) ax = pp.plot_network( ax, inps.date12List, inps.dateList, inps.pbaseList, vars(inps), inps.date12List_drop, ) if inps.save_fig: fig.savefig(fig_names[3], **kwargs) print(f'save figure to {fig_names[3]}') if inps.disp_fig: print('showing ...') plt.show() else: plt.close() return