def main(argv): ## Default settings contour_step = 200.0 contour_sigma = 3.0 demShade = "yes" demContour = "yes" global markerSize, markderSize2, markerColor, markerColor2, rectColor global lineWidth, lineWidth2, edgeWidth, fontSize # global markerColor_ref, markerColor_ref2 markerSize = 16 markerSize2 = 16 markerColor = "crimson" # g markerColor2 = "lightgray" markerColor_ref = "white" markerColor_ref2 = "lightgray" rectColor = "black" lineWidth = 0 lineWidth2 = 0 edgeWidth = 1.5 fontSize = 16 global unit, radius, saveFig, dispFig, fig_dpi fig_dpi = 300 radius = 0 saveFig = "no" dispFig = "yes" unit = "cm" dispDisplacement = "no" dispOpposite = "no" dispContour = "only" smoothContour = "no" contour_step = 200 showRef = "yes" vel_alpha = 1.0 zero_start = "yes" global ref_xsub, ref_ysub, ref_date global h5timeseries_2, dates_2, dateList_2 global lbound, hbound ############### Check Inputs ################## if len(sys.argv) < 2: Usage() sys.exit(1) elif len(sys.argv) == 2: if argv[0] == "-h": Usage() sys.exit(1) elif os.path.isfile(argv[0]): timeSeriesFile = argv[0] h5timeseries = h5py.File(timeSeriesFile) k = h5timeseries.keys() if not "timeseries" in k: print "ERROR: Input file is " + k[0] + ".\n\tOnly timeseries is supported.\n" sys.exit(1) else: Usage() sys.exit(1) elif len(sys.argv) > 2: try: opts, args = getopt.getopt( argv, "f:F:v:a:b:s:m:c:w:u:l:h:D:V:t:T:d:r:x:y:X:Y:o:E:", [ "save", "nodisplay", "unit=", "exclude=", "ref-date=", "rect-color=", "zero-start=", "zoom-x=", "zoom-y=", "zoom-lon", "zoom-lat", "lalo=", "opposite", "dem-nocontour", "dem-noshade", "displacement", "contour-step=", "contour-smooth=", "LALO=", ], ) except getopt.GetoptError: Usage() sys.exit(1) for opt, arg in opts: if opt == "-f": timeSeriesFile = arg elif opt == "-F": timeSeriesFile_2 = arg elif opt == "-v": velocityFile = arg elif opt == "-a": vmin = float(arg) elif opt == "-b": vmax = float(arg) elif opt == "-s": fontSize = int(arg) elif opt == "-m": markerSize = int(arg) markerSize2 = int(arg) elif opt == "-c": markerColor = arg elif opt == "-w": lineWidth = int(arg) elif opt == "-u": unit = arg elif opt == "-l": lbound = float(arg) elif opt == "-h": hbound = float(arg) elif opt == "-D": demFile = arg elif opt == "-V": contour_step = float(arg) elif opt == "-t": minDate = arg elif opt == "-T": maxDate = arg elif opt == "-r": radius = abs(int(arg)) elif opt == "-x": xsub = [int(i) for i in arg.split(":")] xsub.sort() # dispVelFig='no' elif opt == "-y": ysub = [int(i) for i in arg.split(":")] ysub.sort() # dispVelFig='no' elif opt == "-X": ref_xsub = [int(i) for i in arg.split(":")] ref_xsub.sort() elif opt == "-Y": ref_ysub = [int(i) for i in arg.split(":")] ref_ysub.sort() # dispVelFig='no' elif opt == "--contour-step": contour_step = float(arg) elif opt == "--contour-smooth": contour_sigma = float(arg) elif opt == "--dem-nocontour": demContour = "no" elif opt == "--dem-noshade": demShade = "no" elif opt == "--displacement": dispDisplacement = "yes" elif opt in ["-E", "--exclude"]: datesNot2show = arg.split(",") elif opt in "--lalo": lalosub = [float(i) for i in arg.split(",")] elif opt in "--LALO": ref_lalosub = [float(i) for i in arg.split(",")] elif opt in ["--rect-color"]: rectColor = arg elif opt in ["--ref-date"]: ref_date = ptime.yyyymmdd(arg) elif opt in ["-u", "--unit"]: unit = arg.lower() elif opt == "--save": saveFig = "yes" elif opt == "--nodisplay": dispFig = "no" saveFig = "yes" elif opt == "--opposite": dispOpposite = "yes" elif opt == "--zero-start": zero_start = arg.lower() elif opt == "--zoom-x": win_x = [int(i) for i in arg.split(":")] win_x.sort() elif opt == "--zoom-y": win_y = [int(i) for i in arg.split(":")] win_y.sort() elif opt == "--zoom-lon": win_lon = [float(i) for i in arg.split(":")] win_lon.sort() elif opt == "--zoom-lat": win_lat = [float(i) for i in arg.split(":")] win_lat.sort() ############################################################## ## Read time series file info if not os.path.isfile(timeSeriesFile): print "\nERROR: Input time series file does not exist: " + timeSeriesFile + "\n" sys.exit(1) h5timeseries = h5py.File(timeSeriesFile) k = h5timeseries.keys() # read h5 file and its group type if not "timeseries" in k: print "ERROR: Input file is " + k[0] + ".\n\tOnly timeseries is supported.\n" sys.exit(1) atr = readfile.read_attributes(timeSeriesFile) dateList1 = h5timeseries["timeseries"].keys() dateList1 = sorted(dateList1) dates1, datevector1 = ptime.date_list2vector(dateList1) print "\n************ Time Series Display - Point *************" ##### Select Check try: lalosub xsub = subset.coord_geo2radar([lalosub[1]], atr, "longitude") ysub = subset.coord_geo2radar([lalosub[0]], atr, "latitude") xsub = [xsub] ysub = [ysub] if radius == 0: radius = 3 except: pass try: ref_lalosub ref_xsub = subset.coord_geo2radar([ref_lalosub[1]], atr, "longitude") ref_ysub = subset.coord_geo2radar([ref_lalosub[0]], atr, "latitude") ref_xsub = [ref_xsub] ref_ysub = [ref_ysub] if radius == 0: radius = 3 except: pass ############################################################## global dates, dateList, datevector_all, dateListMinMax print "*******************" print "All dates existed:" print dateList1 print "*******************" ## Check exclude date input try: datesNot2show if os.path.isfile(datesNot2show[0]): try: datesNot2show = ptime.read_date_list(datesNot2show[0]) except: print "Can not read date list file: " + datesNot2show[0] print "dates not to show: " + str(datesNot2show) except: datesNot2show = [] ## Check Min / Max Date dateListMinMax = [] try: minDate minDate = ptime.yyyymmdd(minDate) dateListMinMax.append(minDate) minDateyy = ptime.yyyymmdd2years(minDate) print "minimum date: " + minDate for date in dateList1: yy = ptime.yyyymmdd2years(date) if yy < minDateyy: datesNot2show.append(date) except: pass try: maxDate maxDate = ptime.yyyymmdd(maxDate) dateListMinMax.append(maxDate) maxDateyy = ptime.yyyymmdd2years(maxDate) print "maximum date: " + maxDate for date in dateList1: yy = ptime.yyyymmdd2years(date) if yy > maxDateyy: datesNot2show.append(date) except: pass dateListMinMax = sorted(dateListMinMax) if not dateListMinMax: print "no min/max date input." else: datesMinMax, dateVecMinMax = ptime.date_list2vector(dateListMinMax) ## Finalize Date List try: dateList = [] for date in dateList1: if date not in datesNot2show: dateList.append(date) print "--------------------------------------------" print "dates used to show time series displacements:" print dateList print "--------------------------------------------" except: dateList = dateList1 print "using all dates to show time series displacement" ## Read Date Info (x axis for time series display) dates, datevector = ptime.date_list2vector(dateList) datevector_all = list(datevector) ## Check reference date input try: ref_date if not ref_date in dateList: print "Reference date - " + ref_date + " - is not included in date list to show." sys.exit(1) else: print "reference date: " + ref_date except: if zero_start == "yes": ref_date = dateList[0] print "set the 1st date as reference for displacement display." else: pass ############################################################## ##### Plot Fig 1 - Velocity / last epoch of time series / DEM fig = plt.figure(1) ax = fig.add_subplot(111) ##### Check subset range width = int(atr["WIDTH"]) length = int(atr["FILE_LENGTH"]) print "file size: " + str(length) + ", " + str(width) try: win_y = subset.coord_geo2radar(win_lat, atr, "latitude") except: try: win_y except: win_y = [0, length] try: win_x = subset.coord_geo2radar(win_lon, atr, "longitude") except: try: win_x except: win_x = [0, width] win_y, win_x = subset.check_subset_range(win_y, win_x, atr) try: velocityFile try: vel, vel_atr = readfile.read(velocityFile) except: vel, vel_atr = readfile.read(timeSeriesFile, velocityFile) ax.set_title(velocityFile) print "display: " + velocityFile except: vel, vel_atr = readfile.read(timeSeriesFile, dateList1[-1]) ax.set_title("epoch: " + dateList1[-1]) print "display last epoch" ##### show displacement instead of phase if vel_atr["FILE_TYPE"] in ["interferograms", ".unw"] and dispDisplacement == "yes": print "show displacement" phase2range = -float(vel_atr["WAVELENGTH"]) / (4 * np.pi) vel *= phase2range else: dispDisplacement = "no" ## Reference Point if showRef == "yes": try: ax.plot(int(atr["ref_x"]), int(atr["ref_y"]), "ks", ms=6) except: pass if dispOpposite == "yes": print "show opposite value in figure/map 1" vel *= -1 ## Flip try: flip_lr except: try: flip_ud except: flip_lr, flip_ud = view.auto_flip_check(atr) ## Status bar ## Geo coordinate try: ullon = float(atr["X_FIRST"]) ullat = float(atr["Y_FIRST"]) lon_step = float(atr["X_STEP"]) lat_step = float(atr["Y_STEP"]) lon_unit = atr["Y_UNIT"] lat_unit = atr["X_UNIT"] geocoord = "yes" print "Input file is Geocoded" except: geocoord = "no" def format_coord(x, y): col = int(x + 0.5) row = int(y + 0.5) if col >= 0 and col <= width and row >= 0 and row <= length: z = vel[row, col] try: lon = ullon + x * lon_step lat = ullat + y * lat_step return "x=%.1f, y=%.1f, value=%.4f, lon=%.4f, lat=%.4f" % (x, y, z, lon, lat) except: return "x=%.1f, y=%.1f, value=%.4f" % (x, y, z) ax.format_coord = format_coord ## DEM try: demFile dem, demRsc = readfile.read(demFile) ax = view.plot_dem_yx(ax, dem, demShade, demContour, contour_step, contour_sigma) vel_alpha = 0.8 except: print "No DEM file" try: img = ax.imshow(vel, vmin=vmin, vmax=vmax, alpha=vel_alpha) except: img = ax.imshow(vel, alpha=vel_alpha) plt.colorbar(img) ## Zoom In (subset) if flip_lr == "yes": ax.set_xlim(win_x[1], win_x[0]) else: ax.set_xlim(win_x[0], win_x[1]) if flip_ud == "yes": ax.set_ylim(win_y[0], win_y[1]) else: ax.set_ylim(win_y[1], win_y[0]) ## Flip # if flip_lr == 'yes': fig.gca().invert_xaxis() # if flip_ud == 'yes': fig.gca().invert_yaxis() ########################################## ##### Plot Fig 2 - Time series plot # fig2 = plt.figure(num=2,figsize=(12,6)) fig2 = plt.figure(2, figsize=(12, 6)) ax2 = fig2.add_subplot(111) try: timeSeriesFile_2 h5timeseries_2 = h5py.File(timeSeriesFile_2) dateList_2 = h5timeseries_2["timeseries"].keys() dateList_2 = sorted(dateList_2) dates_2, datevector_2 = ptime.date_list2vector(dateList_2) datevector_all += list(set(datevector_2) - set(datevector_all)) datevector_all = sorted(datevector_all) except: pass ################################ Plot Code Package <start> ################################# def plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries): ax2.cla() print "\n-------------------------------------------------------------------------------" disp_min = 0 disp_max = 0 ############################# Plot Time Series ############################## global ref_xsub, ref_ysub ##### 1.1 Plot Reference time series try: ref_xsub ref_ysub ref_xsub, ref_ysub = check_yx(ref_xsub, ref_ysub, radius, ax, rectColor) print "----------------------------------------------------" print "Reference Point:" print "ref_x=" + str(ref_xsub[0]) + ":" + str(ref_xsub[1]) print "ref_y=" + str(ref_ysub[0]) + ":" + str(ref_ysub[1]) print "-----------------------------" print "Time series with all dates:" dis1, dis1_mean, dis1_std, dis1_vel = read_dis(ref_xsub, ref_ysub, dateList1, h5timeseries, unit) (_, caps, _) = ax2.errorbar( dates1, dis1_mean, yerr=dis1_std, fmt="-ks", ms=markerSize2, lw=0, alpha=1, mfc=markerColor_ref, mew=edgeWidth, elinewidth=edgeWidth, ecolor="black", capsize=markerSize * 0.5, ) for cap in caps: cap.set_markeredgewidth(edgeWidth) disp_min, disp_max = update_lim(disp_min, disp_max, dis1_mean, dis1_std) if not len(dateList) == len(dateList1): print "-----------------------------" print "Time series with dates of interest:" dis12, dis12_mean, dis12_std, dis12_vel = read_dis(ref_xsub, ref_ysub, dateList, h5timeseries, unit) (_, caps, _) = ax2.errorbar( dates, dis12_mean, yerr=dis12_std, fmt="-ks", ms=markerSize2, lw=0, alpha=1, mfc=markerColor_ref2, mew=edgeWidth, elinewidth=edgeWidth, ecolor="black", capsize=markerSize * 0.5, ) for cap in caps: cap.set_markeredgewidth(edgeWidth) disp_min, disp_max = update_lim(disp_min, disp_max, dis12_mean, dis12_std) except: pass ##### 1.2.0 Read y/x print "\n----------------------------------------------------" print "Point of Interest:" xsub, ysub = check_yx(xsub, ysub, radius, ax, rectColor) print "x=" + str(xsub[0]) + ":" + str(xsub[1]) print "y=" + str(ysub[0]) + ":" + str(ysub[1]) ##### 1.2.1 Plot 2nd time series try: timeSeriesFile_2 print "-----------------------------" print "2nd Time Series:" dis2, dis2_mean, dis2_std, dis2_vel = read_dis(xsub, ysub, dateList_2, h5timeseries_2, unit) (_, caps, _) = ax2.errorbar( dates_2, dis2_mean, yerr=dis2_std, fmt="-ko", ms=markerSize2, lw=0, alpha=1, mfc=markerColor2, elinewidth=0, ecolor="black", capsize=0, ) for cap in caps: cap.set_markeredgewidth(edgeWidth) disp_min, disp_max = update_lim(disp_min, disp_max, dis2_mean, dis2_std) except: pass ##### 1.2.2 Plot 1st time series print "-----------------------------" print "Time Series:" dis, dis_mean, dis_std, dis_vel = read_dis(xsub, ysub, dateList, h5timeseries, unit) (_, caps, _) = ax2.errorbar( dates, dis_mean, yerr=dis_std, fmt="-ko", ms=markerSize, lw=lineWidth, alpha=1, mfc=markerColor, elinewidth=edgeWidth, ecolor="black", capsize=markerSize * 0.5, ) for cap in caps: cap.set_markeredgewidth(edgeWidth) disp_min, disp_max = update_lim(disp_min, disp_max, dis_mean, dis_std) ####################### Figure Format ####################### ## x axis format try: ax2 = ptime.adjust_xaxis_date(ax2, dateVecMinMax, fontSize) except: ax2 = ptime.adjust_xaxis_date(ax2, datevector_all, fontSize) ## y axis format ax2.set_ylabel("Displacement [" + unit + "]", fontsize=fontSize) try: lbound hbound ax2.set_ylim(lbound, hbound) except: disp_buf = 0.2 * (disp_max - disp_min) ax2.set_ylim(disp_min - disp_buf, disp_max + disp_buf) for tick in ax2.yaxis.get_major_ticks(): tick.label.set_fontsize(fontSize) ## title figTitle = "x=" + str(xsub[0]) + ":" + str(xsub[1]) + ", y=" + str(ysub[0]) + ":" + str(ysub[1]) try: lonc = ullon + (xsub[0] + xsub[1]) / 2.0 * lon_step latc = ullat + (ysub[0] + ysub[1]) / 2.0 * lat_step figTitle += ", lalo=" + "%.4f,%.4f" % (latc, lonc) except: pass ax2.set_title(figTitle) ################## Save and Output ##################### if saveFig == "yes": print "-----------------------------" Delay = {} Delay["displacement"] = dis Delay["unit"] = unit Delay["time"] = datevector Delay["velocity"] = dis_vel[0] Delay["velocity_unit"] = unit + "/yr" Delay["velocity_std"] = dis_vel[4] figBase = "x" + str(xsub[0]) + "_" + str(xsub[1] - 1) + "y" + str(ysub[0]) + "_" + str(ysub[1] - 1) sio.savemat(figBase + "_ts.mat", {"displacement": Delay}) print "saved " + figBase + "_ts.mat" fig2.savefig(figBase + "_ts.pdf", bbox_inches="tight", transparent=True, dpi=fig_dpi) print "saved " + figBase + "_ts.pdf" if dispFig == "no": fig.savefig(figBase + "_vel.png", bbox_inches="tight", transparent=True, dpi=fig_dpi) print "saved " + figBase + "_vel.png" ################################ Plot Code Package <end> ################################# ########### 1. Plot Time Series with x/y ########## try: xsub ysub plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries) except: print "No x/y input" pass ########### 2. Plot Time Series with Click ########## ## similar to 1. Plot Time Series with x/y def onclick(event): ax2.cla() xsub = [int(event.xdata)] ysub = [int(event.ydata)] plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries) if dispFig == "yes": plt.show() try: cid = fig.canvas.mpl_connect("button_press_event", onclick) except: pass if dispFig == "yes": plt.show()
def main(argv): ##### Default fontSize = 12 lineWidth = 2 markerColor = 'crimson' markerSize = 16 disp_fig = 'no' save_fig = 'yes' save_list = 'yes' ref_file = 'reference_date.txt' drop_file = 'drop_date.txt' ##### Check Inputs if len(sys.argv)>3: try: opts, args = getopt.getopt(argv,'h:f:m:o:x:y:',['help','circle=']) except getopt.GetoptError: print 'Error in reading input options!'; usage() ; sys.exit(1) for opt,arg in opts: if opt in ("-h","--help"): usage() ; sys.exit() elif opt == '-f': File = arg elif opt == '-m': maskFile = arg elif opt == '-x': xsub = [int(i) for i in arg.split(':')]; xsub.sort() elif opt == '-y': ysub = [int(i) for i in arg.split(':')]; ysub.sort() elif opt == '--circle' : cir_par = [i for i in arg.split(';')] #elif opt == '-o': outName = arg else: try: File = argv[0] except: usage(); sys.exit(1) try: maskFile = argv[1] except: pass try: atr = readfile.read_attribute(File) except: usage(); sys.exit(1) ext = os.path.splitext(File)[1].lower() FileBase = os.path.basename(File).split(ext)[0] outNameBase = 'spatialMean_'+FileBase print '\n*************** Spatial Average ******************' ##### Input File Info k = atr['FILE_TYPE'] print 'Input file is '+k width = int(atr['WIDTH']) length = int(atr['FILE_LENGTH']) h5file = h5py.File(File) epochList = h5file[k].keys() epochList = sorted(epochList) epochNum = len(epochList) print 'number of epoch: '+str(epochNum) if dates,datevector = ptime.date_list2vector(epochList) ##### Mask Info try: Mask_orig,Matr = readfile.read(maskFile) print 'mask file: '+maskFile Masking = 'yes' except: print 'No mask. Use the whole area for ramp estimation.' Masking = 'no' Mask_orig=np.ones((length,width)) Mask = np.zeros((length,width)) Mask[:] = Mask_orig[:] ## Bounding Subset try: xsub ysub ysub,xsub = subset.check_subset_range(ysub,xsub,atr) Mask[ysub[0]:ysub[1],xsub[0]:xsub[1]] = Mask_orig[ysub[0]:ysub[1],xsub[0]:xsub[1]]*2 #Mask[0:ysub[0],:] = 0 #Mask[ysub[1]:length,:] = 0 #Mask[:,0:xsub[0]] = 0 #Mask[:,xsub[1]:width] = 0 except: Mask = Mask_orig*2 print 'No subset input.' ## Circle Inputs try: cir_par for i in range(len(cir_par)): cir_idx = circle_index(atr,cir_par[i]) Mask[cir_idx] = Mask_orig[cir_idx] print 'Circle '+str(i)+': '+cir_par[i] except: print 'No circle of interest input.' ## Mask output idx = Mask == 2 idxNum = float(sum(sum(idx))) fig = plt.figure() plt.imshow(Mask,cmap='gray') plt.savefig(outNameBase+'_mask.png',bbox_inches='tight') print 'save mask to '+outNameBase+'_mask.png' #fig.clf() ##### Calculation meanList = np.zeros(epochNum) pixPercent = np.zeros(epochNum) pixT = 0.7 print 'calculating ...' print ' Date Mean Percentage' for i in range(epochNum): epoch = epochList[i] d = h5file[k].get(epoch)[:] #d[Mask==0] = np.nan meanList[i] = np.nanmean(d[idx]) pixPercent[i] = np.sum(d[idx] >= pixT)/idxNum print epoch+' : %.2f %.1f%%'%(meanList[i],pixPercent[i]*100) del d h5file.close() ##### Reference date - Max Value top3 = sorted(zip(meanList,epochList), reverse=True)[:3] print '------------ Top 3 Mean ------------------' print top3 ## Write to txt file fref = open(ref_file,'w') fref.write(str(top3[0][1])+'\n') fref.close() print 'write optimal reference date to '+ref_file idxMean = meanList == np.nanmax(meanList) ##### Drop dates - mean threshold #meanT = 0.7 #idxMean = meanList < meanT #print '------------ Mean Value < '+str(meanT)+' --------' #print np.array(epochList)[idxMean] #print meanList[idxMean] ##### Drop dates - good pixel percentage pixNumT = 0.7 print '------------ Good Pixel Percentage < %.0f%% -------'%(pixNumT*100) idxPix = pixPercent < pixNumT dropEpochList = np.array(epochList)[idxPix] print dropEpochList print pixPercent[idxPix] ## Write to txt file fdrop = open(drop_file,'w') for i in range(len(dropEpochList)): fdrop.write(str(dropEpochList[i])+'\n') fdrop.close() print 'write drop dates to '+drop_file print '-------------------------------------------' ##### Display fig = plt.figure(figsize=(12,12)) ax = fig.add_subplot(211) ax.plot(dates, meanList, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor) #ax.plot([dates[0],dates[-1]],[meanT,meanT], '--b', lw=lineWidth) #sc = ax.scatter(dates, np.tile(0.5,epochNum), c=meanList, s=22**2, alpha=0.3, vmin=0.0, vmax=1.0) #ax.scatter(np.array(dates)[idxMean], 0.5, c=meanList[idxMean], s=22**2, alpha=1.0, vmin=0.0, vmax=1.0) ax = ptime.auto_adjust_xaxis_date(ax,datevector) ax.set_ylim(0,1) ax.set_title('Spatial Average Value', fontsize=fontSize) ax.set_xlabel('Time [years]', fontsize=fontSize) #cbar = plt.colorbar(sc) #cbar.set_label('Spatial Mean of Normalized Sum Epochs') ax = fig.add_subplot(212) ax.plot(dates, pixPercent, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor) ax.plot([dates[0],dates[-1]],[pixNumT,pixNumT], '--b', lw=lineWidth) ax = ptime.auto_adjust_xaxis_date(ax,datevector) ax.set_ylim(0,1) ax.set_title('Percenrage of Pixels with Value > '+str(pixNumT), fontsize=fontSize) ax.set_xlabel('Time [years]', fontsize=fontSize) vals = ax.get_yticks() ax.set_yticklabels(['{:3.0f}%'.format(i*100) for i in vals]) if save_fig == 'yes': plt.savefig(outNameBase+'.png',bbox_inches='tight') print 'save figure to '+outNameBase+'.png' if disp_fig == 'yes': plt.show() ##### Output if save_list == 'yes': epochList6 = ptime.yymmdd(epochList) fl = open(outNameBase+'.txt','w') for i in range(epochNum): str_line = epochList6[i]+' %.2f %.2f\n'%(meanList[i],pixPercent[i]) fl.write(str_line) fl.close() print 'write data to '+outNameBase+'.txt\n'
def main(argv): ##### Default fontSize = 12 lineWidth = 2 markerColor = 'crimson' markerSize = 16 disp_fig = 'no' save_fig = 'yes' save_list = 'yes' ref_file = 'reference_date.txt' drop_file = 'drop_date.txt' ##### Check Inputs if len(sys.argv)>3: try: opts, args = getopt.getopt(argv,'h:f:m:o:x:y:',['help','circle=']) except getopt.GetoptError: print 'Error in reading input options!'; Usage() ; sys.exit(1) for opt,arg in opts: if opt in ("-h","--help"): Usage() ; sys.exit() elif opt == '-f': File = arg elif opt == '-m': maskFile = arg elif opt == '-x': xsub = [int(i) for i in arg.split(':')]; xsub.sort() elif opt == '-y': ysub = [int(i) for i in arg.split(':')]; ysub.sort() elif opt == '--circle' : cir_par = [i for i in arg.split(';')] #elif opt == '-o': outName = arg else: try: File = argv[0] except: Usage(); sys.exit(1) try: maskFile = argv[1] except: pass try: atr = readfile.read_attributes(File) except: Usage(); sys.exit(1) ext = os.path.splitext(File)[1].lower() FileBase = os.path.basename(File).split(ext)[0] outNameBase = 'spatialMean_'+FileBase print '\n*************** Spatial Average ******************' ##### Input File Info k = atr['FILE_TYPE'] print 'Input file is '+k width = int(atr['WIDTH']) length = int(atr['FILE_LENGTH']) h5file = h5py.File(File) epochList = h5file[k].keys(); epochList = sorted(epochList) epochNum = len(epochList) print 'number of epoch: '+str(epochNum) dates,datevector = ptime.date_list2vector(epochList) ##### Mask Info try: Mask_orig,Matr = readfile.read(maskFile) print 'mask file: '+maskFile Masking = 'yes' except: print 'No mask. Use the whole area for ramp estimation.' Masking = 'no' Mask_orig=np.ones((length,width)) Mask = np.zeros((length,width)) Mask[:] = Mask_orig[:] ## Bounding Subset try: xsub ysub ysub,xsub = subset.check_subset_range(ysub,xsub,atr) Mask[ysub[0]:ysub[1],xsub[0]:xsub[1]] = Mask_orig[ysub[0]:ysub[1],xsub[0]:xsub[1]]*2 #Mask[0:ysub[0],:] = 0 #Mask[ysub[1]:length,:] = 0 #Mask[:,0:xsub[0]] = 0 #Mask[:,xsub[1]:width] = 0 except: Mask = Mask_orig*2 print 'No subset input.' ## Circle Inputs try: cir_par for i in range(len(cir_par)): cir_idx = circle_index(atr,cir_par[i]) Mask[cir_idx] = Mask_orig[cir_idx] print 'Circle '+str(i)+': '+cir_par[i] except: print 'No circle of interest input.' ## Mask output idx = Mask == 2 idxNum = float(sum(sum(idx))) fig = plt.figure() plt.imshow(Mask,cmap='gray') plt.savefig(outNameBase+'_mask.png',bbox_inches='tight') print 'save mask to '+outNameBase+'_mask.png' #fig.clf() ##### Calculation meanList = np.zeros(epochNum) pixPercent = np.zeros(epochNum) pixT = 0.7 print 'calculating ...' print ' Date Mean Percentage' for i in range(epochNum): epoch = epochList[i] d = h5file[k].get(epoch)[:] #d[Mask==0] = np.nan meanList[i] = np.nanmean(d[idx]) pixPercent[i] = np.sum(d[idx] >= pixT)/idxNum print epoch+' : %.2f %.1f%%'%(meanList[i],pixPercent[i]*100) del d h5file.close() ##### Reference date - Max Value top3 = sorted(zip(meanList,epochList), reverse=True)[:3] print '------------ Top 3 Mean ------------------' print top3 ## Write to txt file fref = open(ref_file,'w') fref.write(str(top3[0][1])+'\n') fref.close() print 'write optimal reference date to '+ref_file idxMean = meanList == np.nanmax(meanList) ##### Drop dates - mean threshold #meanT = 0.7 #idxMean = meanList < meanT #print '------------ Mean Value < '+str(meanT)+' --------' #print np.array(epochList)[idxMean] #print meanList[idxMean] ##### Drop dates - good pixel percentage pixNumT = 0.7 print '------------ Good Pixel Percentage < %.0f%% -------'%(pixNumT*100) idxPix = pixPercent < pixNumT dropEpochList = np.array(epochList)[idxPix] print dropEpochList print pixPercent[idxPix] ## Write to txt file fdrop = open(drop_file,'w') for i in range(len(dropEpochList)): fdrop.write(str(dropEpochList[i])+'\n') fdrop.close() print 'write drop dates to '+drop_file print '-------------------------------------------' ##### Display fig = plt.figure(figsize=(12,12)) ax = fig.add_subplot(211) ax.plot(dates, meanList, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor) #ax.plot([dates[0],dates[-1]],[meanT,meanT], '--b', lw=lineWidth) #sc = ax.scatter(dates, np.tile(0.5,epochNum), c=meanList, s=22**2, alpha=0.3, vmin=0.0, vmax=1.0) #ax.scatter(np.array(dates)[idxMean], 0.5, c=meanList[idxMean], s=22**2, alpha=1.0, vmin=0.0, vmax=1.0) ax = ptime.adjust_xaxis_date(ax,datevector) ax.set_ylim(0,1) ax.set_title('Spatial Average Value', fontsize=fontSize) ax.set_xlabel('Time [years]', fontsize=fontSize) #cbar = plt.colorbar(sc) #cbar.set_label('Spatial Mean of Normalized Sum Epochs') ax = fig.add_subplot(212) ax.plot(dates, pixPercent, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor) ax.plot([dates[0],dates[-1]],[pixNumT,pixNumT], '--b', lw=lineWidth) ax = ptime.adjust_xaxis_date(ax,datevector) ax.set_ylim(0,1) ax.set_title('Percenrage of Pixels with Value > '+str(pixNumT), fontsize=fontSize) ax.set_xlabel('Time [years]', fontsize=fontSize) vals = ax.get_yticks() ax.set_yticklabels(['{:3.0f}%'.format(i*100) for i in vals]) if save_fig == 'yes': plt.savefig(outNameBase+'.png',bbox_inches='tight') print 'save figure to '+outNameBase+'.png' if disp_fig == 'yes': plt.show() ##### Output if save_list == 'yes': epochList6 = ptime.yymmdd(epochList) fl = open(outNameBase+'.txt','w') for i in range(epochNum): str_line = epochList6[i]+' %.2f %.2f\n'%(meanList[i],pixPercent[i]) fl.write(str_line) fl.close() print 'write data to '+outNameBase+'.txt\n'