def main(argv):
#default settings
markerSize=16
markerSize2=16
markerColor='g'
markerColor2='red'
lineWidth=2
fontSize=16
unit='cm'
Save_timeseries='no'
dispTsFig='yes'
dispVelFig='yes'
dispContour='only'
contour_step=200
smoothContour='no'
radius=0;
edgeWidth=1.5
fig_dpi=300
if len(sys.argv)>2:
try:
opts, args = getopt.getopt(argv,"f:F:v:a:b:s:m:c:w:u:l:h:S:D:C:V:t:T:d:r:x:y:P:p:")
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 == '-S': Save_timeseries=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 == '-C': dispContour=arg
elif opt == '-V': contour_step=float(arg)
elif opt == '-t': minDate=arg
elif opt == '-T': maxDate=arg
elif opt == '-d': datesNot2show = arg.split()
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 == '-P': dispTsFig=arg
elif opt == '-p': dispVelFig=arg
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)
if not 'timeseries' in h5timeseries.keys():
print 'ERROR'
Usage(); sys.exit(1)
else: Usage(); sys.exit(1)
elif len(sys.argv)<2:
Usage(); sys.exit(1)
if unit in ('m','M'): unitFac=1
elif unit in ('cm','Cm','CM'): unitFac=100
elif unit in ('mm','Mm','MM','mM'): unitFac=1000
else:
print 'Warning:'
print 'wrong unit input!'
print 'cm is considered to display the displacement'
##############################################################
# Read time series file info
if not os.path.isfile(timeSeriesFile):
Usage();sys.exit(1)
h5timeseries = h5py.File(timeSeriesFile)
if not 'timeseries' in h5timeseries.keys():
Usage(); sys.exit(1)
dateList1 = h5timeseries['timeseries'].keys()
##############################################################
# Dates to show time series plot
import matplotlib.dates as mdates
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
yearsFmt = mdates.DateFormatter('%Y')
print '*******************'
print 'All dates existed:'
print dateList1
print '*******************'
try:
datesNot2show
print 'dates not to show: '+str(datesNot2show)
except: datesNot2show=[]
try:
minDate
minDateyy=yyyymmdd2years(minDate)
print 'minimum date: '+minDate
for date in dateList1:
yy=yyyymmdd2years(date)
if yy < minDateyy:
datesNot2show.append(date)
except: pass
try:
maxDate
maxDateyy=yyyymmdd2years(maxDate)
print 'maximum date: '+maxDate
for date in dateList1:
yy=yyyymmdd2years(date)
if yy > maxDateyy:
datesNot2show.append(date)
except: pass
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'
###################################################################
# Date info
dateIndex={}
for ni in range(len(dateList)):
dateIndex[dateList[ni]]=ni
tbase=[]
d1 = datetime.datetime(*time.strptime(dateList[0],"%Y%m%d")[0:5])
for ni in range(len(dateList)):
d2 = datetime.datetime(*time.strptime(dateList[ni],"%Y%m%d")[0:5])
diff = d2-d1
tbase.append(diff.days)
dates=[]
for ni in range(len(dateList)):
d = datetime.datetime(*time.strptime(dateList[ni],"%Y%m%d")[0:5])
dates.append(d)
datevector=[]
for i in range(len(dates)):
datevector.append(np.float(dates[i].year) + np.float(dates[i].month-1)/12 + np.float(dates[i].day-1)/365)
datevector2=[round(i,2) for i in datevector]
###########################################
# Plot Fig 1 - Velocity / last epoch of time series / DEM
import matplotlib.pyplot as plt
if dispVelFig in ('yes','Yes','y','Y','YES'):
fig = plt.figure()
ax=fig.add_subplot(111)
try:
velocityFile
h5file=h5py.File(velocityFile,'r')
k=h5file.keys()
dset= h5file[k[0]].get(k[0])
print 'display: ' + k[0]
except:
dset = h5timeseries['timeseries'].get(h5timeseries['timeseries'].keys()[-1])
print 'display: last epoch of timeseries'
#DEM/contour option
try:
demFile
import _readfile as readfile
if os.path.basename(demFile).split('.')[1]=='hgt': amp,dem,demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1]=='dem': dem,demRsc = readfile.read_dem(demFile)
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'):
print 'show DEM as basemap'
cmap_dem=plt.get_cmap('gray')
import _pysar_utilities as ut
plt.imshow(ut.hillshade(dem,50.0),cmap=cmap_dem)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'):
print 'show contour'
if smoothContour in ('yes','Yes','y','Y','YES'):
import scipy.ndimage as ndimage
dem=ndimage.gaussian_filter(dem,sigma=10.0,order=0)
contour_sequence=np.arange(-6000,9000,contour_step)
plt.contour(dem,contour_sequence,origin='lower',colors='black',alpha=0.5)
except: print 'No DEM file'
try: img=ax.imshow(dset,vmin=vmin,vmax=vmax)
except: img=ax.imshow(dset)
import matplotlib.patches as patches # need for draw rectangle of points selected on VelFig
##########################################
# Plot Fig 2 - Time series plot
import scipy.stats as stats
fig2 = plt.figure(2)
ax2=fig2.add_subplot(111)
try:
timeSeriesFile_2
h5timeseries_2=h5py.File(timeSeriesFile_2)
print 'plot 2nd time series'
except: pass
########### Plot Time Series with x/y ##########
try:
xsub
ysub
try: xmin=xsub[0]; xmax=xsub[1]+1; print 'x='+str(xsub[0])+':'+str(xsub[1])
except: xmin=xsub[0]-radius; xmax=xsub[0]+radius+1; print 'x='+str(xsub[0])+'+/-'+str(radius)
try: ymin=ysub[0]; ymax=ysub[1]+1; print 'y='+str(ysub[0])+':'+str(ysub[1])
except: ymin=ysub[0]-radius; ymax=ysub[0]+radius+1; print 'y='+str(ysub[0])+'+/-'+str(radius)
try:
fig
rectSelect=patches.Rectangle((xmin,ymin),radius*2+1,radius*2+1,fill=False,lw=edgeWidth)
ax.add_patch(rectSelect)
except: pass
Dis=[]
for date in dateList: Dis.append(h5timeseries['timeseries'].get(date)[ymin:ymax,xmin:xmax])
Dis0=array(Dis)
dis=Dis0*unitFac
dis=reshape(dis,(len(dateList),-1))
dis_mean=stats.nanmean(dis,1)
if (xmax-xmin)*(ymax-ymin)==1: dis_std=[0]*len(dateList)
else: dis_std=stats.nanstd(dis,1)
(_, 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)
print dis_mean
# x axis format
ax2.fmt_xdata = DateFormatter('%Y-%m-%d %H:%M:%S')
if unitFac==100: ax2.set_ylabel('Displacement [cm]',fontsize=fontSize)
elif unitFac==1000: ax2.set_ylabel('Displacement [mm]',fontsize=fontSize)
else: ax2.set_ylabel('Displacement [m]' ,fontsize=fontSize)
ax2.set_xlabel('Time [years]',fontsize=fontSize)
ax2.set_title('x='+str(xmin)+':'+str(xmax-1)+', y='+str(ymin)+':'+str(ymax-1))
ax2.xaxis.set_major_locator(years)
ax2.xaxis.set_major_formatter(yearsFmt)
ax2.xaxis.set_minor_locator(months)
datemin = datetime.date(int(datevector[0]),1,1)
datemax = datetime.date(int(datevector[-1])+1,1,1)
ax2.set_xlim(datemin, datemax)
# y axis format
try:
lbound
hbound
ax2.set_ylim(lbound,hbound)
except:
ax2.set_ylim(nanmin(dis_mean-dis_std)-0.4*abs(nanmin(dis_mean)),\
nanmax(dis_mean+dis_std)+0.4*abs(nanmax(dis_mean)))
for tick in ax2.xaxis.get_major_ticks(): tick.label.set_fontsize(fontSize)
for tick in ax2.yaxis.get_major_ticks(): tick.label.set_fontsize(fontSize)
#fig2.autofmt_xdate() #adjust x overlap by rorating, may enble again
if Save_timeseries in ('yes','Yes','Y','y','YES'):
import scipy.io as sio
Delay={}
Delay['displacement']=Dis0
Delay['unit']='m'
Delay['time']=datevector
tsNameBase='ts_x'+str(xmin)+'_'+str(xmax-1)+'y'+str(ymin)+'_'+str(ymax-1)
sio.savemat(tsNameBase+'.mat', {'displacement': Delay})
print 'saved data to '+tsNameBase+'.mat'
plt.savefig(tsNameBase+'.pdf',dpi=fig_dpi)
print 'saved plot to '+tsNameBase+'.pdf'
def main(argv):
color_map='jet'
disp_opposite='no'
try: opts, args = getopt.getopt(argv,"h:f:d:o:x:y:m:M:i:c:")
except getopt.GetoptError: Usage() ; sys.exit(1)
if opts==[]: Usage() ; sys.exit(1)
for opt,arg in opts:
if opt in ("-h","--help"): Usage(); sys.exit()
elif opt == '-f': File = arg
elif opt == '-d': demFile=arg
elif opt == '-m': Vmin=float(arg)
elif opt == '-M': Vmax=float(arg)
elif opt == '-x': winx=arg.split(':')
elif opt == '-y': winy = arg.split(':')
elif opt == '-o': outName = arg
elif opt == '-i': disp_opposite = arg
elif opt == '-c': color_map=arg
h5file=h5py.File(File,'r')
k=h5file.keys()
print k[0]
#ccmap=plt.get_cmap(color_map)
################################################
cdict1 = {'red': ((0.0, 0.0, 0.0),
(0.5, 0.0, 0.0),
(0.6, 1.0, 1.0),
(0.8, 1.0, 1.0),
(1.0, 0.5, 0.5)),
'green': ((0.0, 0.0, 0.0),
(0.2, 0.0, 0.0),
(0.4, 1.0, 1.0),
(0.6, 1.0, 1.0),
(0.8, 0.0, 0.0),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.5, .5),
(0.2, 1.0, 1.0),
(0.4, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0),)
}
if color_map =='pysar_hsv':
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
else:
ccmap=plt.get_cmap(color_map)
print 'colormap is : '+ color_map
################################################
dset = h5file[k[0]].get(k[0])
data=dset[0:dset.shape[0],0:dset.shape[1]]
if disp_opposite in('yes','Yes','Y','y','YES'):
data=-1*data
try:
xref=h5file[k[0]].attrs['ref_x']
yref=h5file[k[0]].attrs['ref_y']
except:
print 'No reference point'
try:
ullon=float(h5file[k[0]].attrs['X_FIRST'])
ullat=float(h5file[k[0]].attrs['Y_FIRST'])
lon_step=float(h5file[k[0]].attrs['X_STEP'])
lat_step=float(h5file[k[0]].attrs['Y_STEP'])
lon_unit=h5file[k[0]].attrs['Y_UNIT']
lat_unit=h5file[k[0]].attrs['X_UNIT']
llcrnrlon=ullon
llcrnrlat=ullat+lat_step*data.shape[0]
urcrnrlon=ullon+lon_step*data.shape[1]
urcrnrlat=ullat
geocoord='yes'
print 'Input file is Geocoded'
except: geocoord='no'
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,
resolution='l', area_thresh=1., projection='cyl',suppress_ticks=False,ax=ax)
print demFile
demFile
if os.path.basename(demFile).split('.')[1]=='hgt':
amp,dem,demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1]=='dem':
dem,demRsc = readfile.read_real_int16(demFile)
#################################################################
try:
winx
wx=[int(i) for i in win_x.split()]
dem=dem[:,wx[0]:wx[1]]
data=data[:,wx[0]:wx[1]]
ullon=float(h5file[k[0]].attrs['X_FIRST'])+wx[0]
llcrnrlon=ullon
urcrnrlon=ullon+lon_step*data.shape[1]
except:
print ''
try:
winy
wy=[int(i) for i in winy.split()]
dem=dem[wy[0]:wy[1],:]
data=data[wy[0]:wy[1],:]
except:
print ''
################################################################
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,
resolution='l', area_thresh=1., projection='cyl',suppress_ticks=False,ax=ax)
cmap_dem=plt.get_cmap('gray')
m.imshow(ut.hillshade(np.flipud(dem),50.0),cmap=cmap_dem)
try:
im=m.imshow(np.flipud(data),vmin=Vmin,vmax=Vmax,cmap=ccmap)
# cb = m.colorbar(im,"right", size="5%", pad='2%')
except:
im=m.imshow(np.flipud(data))
try:
figName = outName
except:
outName=os.path.basename(File).replace('.h5','')
figName = outName + '.png'
plt.savefig(figName,pad_inches=0.0)
#plt.show()
h5file.close()
def main(argv):
color_map='jet'
disp_opposite='no'
try:
opts, args = getopt.getopt(argv,"h:f:d:o:x:y:m:M:i:c:")
except getopt.GetoptError:
Usage() ; sys.exit(1)
if opts==[]:
Usage() ; sys.exit(1)
for opt,arg in opts:
if opt in ("-h","--help"):
Usage()
sys.exit()
elif opt == '-f':
File = arg
elif opt == '-d':
demFile=arg
elif opt=='-m':
Vmin=float(arg)
elif opt=='-M':
Vmax=float(arg)
elif opt == '-x':
winx=arg.split(':')
elif opt == '-y':
winy = arg.split(':')
elif opt == '-o':
outName = arg
elif opt == '-i':
disp_opposite = arg
elif opt == '-c':
color_map=arg
h5file=h5py.File(File,'r')
k=h5file.keys()
print k[0]
# ccmap=plt.get_cmap(color_map)
################################################
cdict1 = {'red': ((0.0, 0.0, 0.0),
(0.5, 0.0, 0.0),
(0.6, 1.0, 1.0),
(0.8, 1.0, 1.0),
(1.0, 0.5, 0.5)),
'green': ((0.0, 0.0, 0.0),
(0.2, 0.0, 0.0),
(0.4, 1.0, 1.0),
(0.6, 1.0, 1.0),
(0.8, 0.0, 0.0),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.5, .5),
(0.2, 1.0, 1.0),
(0.4, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0),)
}
if color_map =='pysar_hsv':
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
else:
ccmap=plt.get_cmap(color_map)
print 'colormap is : '+ color_map
################################################
dset = h5file[k[0]].get(k[0])
data=dset[0:dset.shape[0],0:dset.shape[1]]
if disp_opposite in('yes','Yes','Y','y','YES'):
data=-1*data
try:
xref=h5file[k[0]].attrs['ref_x']
yref=h5file[k[0]].attrs['ref_y']
except:
print 'No reference point'
try:
ullon=float(h5file[k[0]].attrs['X_FIRST'])
ullat=float(h5file[k[0]].attrs['Y_FIRST'])
lon_step=float(h5file[k[0]].attrs['X_STEP'])
lat_step=float(h5file[k[0]].attrs['Y_STEP'])
lon_unit=h5file[k[0]].attrs['Y_UNIT']
lat_unit=h5file[k[0]].attrs['X_UNIT']
llcrnrlon=ullon
llcrnrlat=ullat+lat_step*data.shape[0]
urcrnrlon=ullon+lon_step*data.shape[1]
urcrnrlat=ullat
geocoord='yes'
print 'Input file is Geocoded'
except:
geocoord='no'
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,
resolution='l', area_thresh=1., projection='cyl',suppress_ticks=False,ax=ax)
print demFile
demFile
if os.path.basename(demFile).split('.')[1]=='hgt':
amp,dem,demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1]=='dem':
dem,demRsc = readfile.read_dem(demFile)
#################################################################
try:
winx
wx=[int(i) for i in win_x.split()]
dem=dem[:,wx[0]:wx[1]]
data=data[:,wx[0]:wx[1]]
ullon=float(h5file[k[0]].attrs['X_FIRST'])+wx[0]
llcrnrlon=ullon
urcrnrlon=ullon+lon_step*data.shape[1]
except:
print ''
try:
winy
wy=[int(i) for i in winy.split()]
dem=dem[wy[0]:wy[1],:]
data=data[wy[0]:wy[1],:]
except:
print ''
################################################################
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,
resolution='l', area_thresh=1., projection='cyl',suppress_ticks=False,ax=ax)
cmap_dem=plt.get_cmap('gray')
m.imshow(ut.hillshade(np.flipud(dem),50.0),cmap=cmap_dem)
try:
im=m.imshow(np.flipud(data),vmin=Vmin,vmax=Vmax,cmap=ccmap)
# cb = m.colorbar(im,"right", size="5%", pad='2%')
except:
im=m.imshow(np.flipud(data))
# cb = m.colorbar(im,"right", size="5%", pad='2%')
# m.bluemarble()
# cb = m.colorbar(im,"right", size="5%", pad='2%')
# parallels = np.arange(31.,34,0.5)
# m.drawparallels(parallels,labels=[1,0,0,1],linewidth=0.0)
# meridians = np.arange(-115.,-112.,0.5)
# m.drawmeridians(meridians,labels=[1,0,0,1],linewidth=0.0)
# m.drawmapscale()
# m = Basemap(llcrnrlon=-110.,llcrnrlat=0.,urcrnrlon=-20.,urcrnrlat=57.,
# projection='lcc',lat_1=20.,lat_2=40.,lon_0=-60.,
# resolution ='l',area_thresh=1000.)
# m.drawcoastlines()
# m.drawcountries()
# m.drawmapboundary(fill_color='#99ffff')
# m.fillcontinents(color='#cc9966',lake_color='#99ffff')
# m.drawparallels(np.arange(10,70,20),labels=[1,1,0,0])
# m.drawmeridians(np.arange(-100,0,20),labels=[0,0,0,1])
# plt.title('Atlantic Hurricane Tracks (Storms Reaching Category 4, 1851-2004)')
try:
figName = outName
except:
outName=os.path.basename(File).replace('.h5','')
figName = outName + '.png'
plt.savefig(figName,pad_inches=0.0)
# plt.show()
h5file.close()
def main(argv):
try:
opts, args = getopt.getopt(argv,"h:D:O:G:S:f:m:M:l:u:s:c:e:d:r:p:w:i:j:t:R:a:b:k:x:y:")
except getopt.GetoptError:
Usage() ; sys.exit(1)
flip_lr='no'
flip_ud='no'
disp_geo = 'no'
font_size=8
color_map='jet'
figs_rows=5
figs_cols=8
rewrapping='yes'
allData2display='yes'
Wspace = 0.1
Hspace = 0.1
title = 'out'
# title = 'None'
showRef = 'yes'
ref_color='k'
ref_symbol='s'
ref_size =10
dip_opposite = 'no'
saveFig='no'
if opts==[]:
Usage() ; sys.exit(1)
for opt,arg in opts:
if opt in ("-h","--help"):
Usage()
sys.exit()
elif opt == '-f':
File = arg
elif opt == '-D':
demFile=arg
elif opt == '-m':
min = float(arg)
elif opt == '-M':
max = float(arg)
elif opt == '-l':
flip_lr = arg
elif opt == '-u':
flip_ud = arg
elif opt == '-s':
font_size = int(arg)
elif opt == '-c':
color_map = arg
elif opt == '-e':
epoch_number = int(arg)
allData2display='no'
elif opt == '-d':
epoch_date = arg
allData2display='no'
elif opt == '-r':
figs_rows = int(arg)
elif opt == '-p':
figs_cols = int(arg)
elif opt == '-w':
rewrapping = arg
elif opt == '-i':
Wspace = float(arg)
elif opt == '-j':
Hspace = float(arg)
elif opt == '-t':
title = arg
elif opt == '-R':
showRef = arg
elif opt == '-a':
ref_color = arg
elif opt == '-b':
ref_symbol = arg
elif opt == 'k':
ref_size=int(arg)
elif opt == '-x':
win_x = arg
elif opt == '-y':
win_y = arg
elif opt == '-G':
disp_geo = arg
elif opt == '-O':
dip_opposite=arg
elif opt=='-S':
saveFig=arg
h5file=h5py.File(File,'r')
k=h5file.keys()
print k
if color_map == 'hsv':
################################################
cdict1 = {'red': ((0.0, 0.0, 0.0),
(0.5, 0.0, 0.0),
(0.6, 1.0, 1.0),
(0.8, 1.0, 1.0),
(1.0, 0.5, 0.5)),
'green': ((0.0, 0.0, 0.0),
(0.2, 0.0, 0.0),
(0.4, 1.0, 1.0),
(0.6, 1.0, 1.0),
(0.8, 0.0, 0.0),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.5, .5),
(0.2, 1.0, 1.0),
(0.4, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0),)
}
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
################################################
else:
ccmap=plt.get_cmap(color_map)
####################################################################
####################################################################
# if k[0]=='velocity' or k[0]=='temporal_coherence' or k[0]=='rmse':
if len(k)==1 and k[0] in ('dem','velocity','mask','temporal_coherence','rmse'):
dset = h5file[k[0]].get(k[0])
data=dset[0:dset.shape[0],0:dset.shape[1]]
if dip_opposite in('yes','Yes','Y','y','YES'):
data=-1*data
try:
xref=h5file[k[0]].attrs['ref_x']
yref=h5file[k[0]].attrs['ref_y']
except:
print 'No reference point'
# Yunjun, Mar 2015
try:
xref=xref-h5file[k[0]].attrs['subset_x0']
yref=yref-h5file[k[0]].attrs['subset_y0']
except:
print 'No subset'
try:
ullon=float(h5file[k[0]].attrs['X_FIRST'])
ullat=float(h5file[k[0]].attrs['Y_FIRST'])
lon_step=float(h5file[k[0]].attrs['X_STEP'])
lat_step=float(h5file[k[0]].attrs['Y_STEP'])
lon_unit=h5file[k[0]].attrs['Y_UNIT']
lat_unit=h5file[k[0]].attrs['X_UNIT']
llcrnrlon=ullon
llcrnrlat=ullat+lat_step*data.shape[0]
urcrnrlon=ullon+lon_step*data.shape[1]
urcrnrlat=ullat
geocoord='yes'
print 'Input file is Geocoded'
except:
geocoord='no'
try:
win_x
wx=[int(i) for i in win_x.split()]
data=data[:,wx[0]:wx[1]]
xref = xref-wx[0]
except:
print 'No subste in x direction'
try:
win_y
wy=[int(i) for i in win_y.split()]
data=data[wy[0]:wy[1],:]
yref = yref-wy[0]
except:
print 'No subset in y direction'
try:
min
except:
min=np.nanmin(data)
try:
max
except:
max=np.nanmax(data)
if flip_lr=='yes':
data=np.fliplr(data)
xref=np.shape(data)[1]-xref-1
if flip_ud=='yes':
data=np.flipud(data)
yref=np.shape(data)[0]-yref-1
try:
demFile
# amp,dem,demRsc = readfile.read_float32(demFile)
if os.path.basename(demFile).split('.')[1]=='hgt':
amp,dem,demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1]=='dem':
dem,demRsc = readfile.read_dem(demFile)
try:
win_x
wx=[int(i) for i in win_x.split()]
dem=dem[:,wx[0]:wx[1]]
except:
print ''
try:
win_y
wy=[int(i) for i in win_y.split()]
dem=dem[wy[0]:wy[1],:]
except:
print ''
if flip_lr=='yes':
dem=np.fliplr(dem)
if flip_ud=='yes':
dem=np.flipud(dem)
cmap_dem=plt.get_cmap('gray')
if disp_geo in ('yes','Yes','Y','y','YES') and geocoord in ('yes','Yes','Y','y','YES'):
print 'display geo'
# from mpl_toolkits.basemap import Basemap
# m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,resolution='f', area_thresh=1., projection='cyl')
# m.imshow(ut.hillshade(dem,50.0), interpolation='nearest', origin='upper')
# m.drawcoastlines(color='w',linewidth=0.8)
# m.drawmapboundary() # draw a line around the map region
# m.drawrivers()
# m.drawparallels(numpy.arange(int(d1.min()), int(d1.max()), 1),linewidth=0.2,labels=[1,0,0,0])
# m.drawmeridians(numpy.arange(int(d0.min()), int(d0.max()), 1),linewidth=0.2,labels=[0,0,0,1])
else:
print 'Not GEO'
plt.imshow(ut.hillshade(dem,50.0),cmap=cmap_dem)
except:
print 'No DEM file'
plt.imshow(data,cmap=ccmap, vmin=min, vmax=max)
plt.colorbar()
if k[0]=='velocity':
plt.title('Velocity (m/yr)',fontsize=font_size)
figName='velocity.pdf'
elif k[0]=='temporal_coherence':
plt.title('Temporal coherence',fontsize=font_size)
figName='temporal_coherence.pdf'
elif k[0]=='dem':
plt.title('DEM error',fontsize=font_size)
figName='DEM_error.pdf'
elif k[0]=='rmse':
plt.title('RMSE (m/yr)',fontsize=font_size)
figName='rmse.pdf'
elif k[0]=='mask':
plt.title('Pixels with no valid value.',fontsize=font_size)
figName='mask.pdf'
if showRef=='yes':
try:
refPoint=ref_color+ref_symbol
plt.plot(xref,yref,refPoint,ms=ref_size)
except:
print 'No reference point'
plt.xlim(0,np.shape(data)[1])
plt.ylim(np.shape(data)[0],0)
if saveFig=='yes':
plt.savefig(figName)
plt.show()
# plt.savefig('fig.pdf')
# fig = plt.figure()
# ax.imshow(data,vmin=min, vmax=max)
# ax.xaxis.label.set_fontsize(40)
####################################################################
####################################################################
if 'timeseries' in k and allData2display=='yes':
if rewrapping=='yes':
print 'rewrapping'
dateList=h5file['timeseries'].keys()
nfigs=figs_rows*figs_cols
ligram = len(dateList)
range2phase=4*np.pi/float(h5file['timeseries'].attrs['WAVELENGTH'])
# range2phase=4*np.pi/0.056
print 'number of timeseries epochs to display:'+ str(ligram)
kk=int(ligram/nfigs)+1
ii=0
for j in range(1,kk):
fig = plt.figure(j)
ii=(j-1)*nfigs+1
for i in range(ii,ii+nfigs):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
dset=h5file['timeseries'].get(dateList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
data=range2phase*data
# data=np.angle(np.exp(1j*data))
data=rewrap(data)
ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(dateList[i-1],fontsize=font_size)
elif title=='in':
add_inner_title(ax, dateList[i-1], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
figName=k[0]+'_'+str(j)+'.pdf'
if saveFig in ['yes','Yes','y','YES']:
plt.savefig(figName)
fig = plt.figure(kk)
ii=(kk-1)*nfigs+1
for i in range(ii,ligram+1):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
dset=h5file['timeseries'].get(dateList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
data=range2phase*data
# data=np.angle(np.exp(1j*data))
data=rewrap(data)
ax.imshow(data,cmap=ccmap)
ax.xaxis.label.set_fontsize(20)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(dateList[i-1],fontsize=font_size)
elif title =='in':
add_inner_title(ax, dateList[i-1], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
figName=k[0]+'_'+str(kk)+'.pdf'
if saveFig in ['yes','Yes','y','YES']:
plt.savefig(figName)
plt.show()
else:
print 'No rewrapping'
dateList=h5file['timeseries'].keys()
nfigs=figs_rows*figs_cols
ligram = len(dateList)
print 'number of timeseries epochs to display:'+ str(ligram)
kk=int(ligram/nfigs)+1
ii=0
for j in range(1,kk):
fig = plt.figure(j)
ii=(j-1)*nfigs+1
for i in range(ii,ii+nfigs):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
data=h5file['timeseries'].get(dateList[i-1])
try:
im=ax.imshow(data,cmap=ccmap,vmin=min,vmax=max)
# print 'here'
except:
im=ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(dateList[i-1],fontsize=font_size)
elif title=='in':
add_inner_title(ax, dateList[i-1], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
fig = plt.figure(kk)
ii=(kk-1)*nfigs+1
for i in range(ii,ligram+1):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
data=h5file['timeseries'].get(dateList[i-1])
try:
im=ax.imshow(data,cmap=ccmap,vmin=min,vmax=max)
except:
im=ax.imshow(data,cmap=ccmap)
ax.xaxis.label.set_fontsize(20)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(dateList[i-1],fontsize=font_size)
if title=='in':
add_inner_title(ax, dateList[i-1], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
plt.show()
####################################################################
####################################################################
elif 'timeseries' in k and allData2display=='no':
dateList=h5file['timeseries'].keys()
try:
epoch_number
except:
epoch_number=dateList.index(epoch_date)
range2phase=4*np.pi/float(h5file['timeseries'].attrs['WAVELENGTH'])
# range2phase=4*np.pi/0.056
dset=h5file['timeseries'].get(dateList[epoch_number])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping=='yes':
data=range2phase*data
# data=np.angle(np.exp(1j*data))
data=rewrap(data)
try:
min
except:
min=np.nanmin(data)
try:
max
except:
max=np.nanmax(data)
plt.imshow(data,cmap=ccmap,vmin=min,vmax=max)
plt.colorbar()
plt.show()
################################################################
################################################################
if k[0]in('interferograms','coherence','wrapped') and allData2display=='yes':
if k[0] in ('coherence','wrapped'):
rewrapping='no'
# color_map = 'gray'
# ccmap=plt.get_cmap(color_map)
if rewrapping=='yes':
ifgramList=h5file[k[0]].keys()
nfigs=figs_rows*figs_cols
ligram = len(ifgramList)
print 'number of '+k[0]+' to display:'+ str(ligram)
kk=int(ligram/nfigs)+1
ii=0
for j in range(1,kk):
fig = plt.figure(j)
ii=(j-1)*nfigs+1
for i in range(ii,ii+nfigs):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
data=np.angle(np.exp(1j*data))
ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(h5file[k[0]][ifgramList[i-1]].attrs['DATE12'],fontsize=font_size)
elif title=='in':
add_inner_title(ax, h5file[k[0]][ifgramList[i-1]].attrs['DATE12'], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
fig = plt.figure(kk)
ii=(kk-1)*nfigs+1
for i in range(ii,ligram+1):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
data=np.angle(np.exp(1j*data))
ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(h5file[k[0]][ifgramList[i-1]].attrs['DATE12'],fontsize=font_size)
elif title=='in':
add_inner_title(ax, h5file[k[0]][ifgramList[i-1]].attrs['DATE12'], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
plt.show()
else:
ifgramList=h5file[k[0]].keys()
nfigs=figs_rows*figs_cols
ligram = len(ifgramList)
print 'number of '+k[0]+' to display:'+ str(ligram)
kk=int(ligram/nfigs)+1
ii=0
for j in range(1,kk):
fig = plt.figure(j)
ii=(j-1)*nfigs+1
for i in range(ii,ii+nfigs):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
print 'loading '+ifgramList[i-1]
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
try:
ax.imshow(data,vmin=min,vmax=max,cmap=ccmap)
except:
ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(h5file[k[0]][ifgramList[i-1]].attrs['DATE12'],fontsize=font_size)
elif title=='in':
add_inner_title(ax, h5file[k[0]][ifgramList[i-1]].attrs['DATE12'], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
fig = plt.figure(kk)
ii=(kk-1)*nfigs+1
for i in range(ii,ligram+1):
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
print 'loading '+ifgramList[i-1]
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
#data = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
try:
ax.imshow(data,vmin=min,vmax=max,cmap=ccmap)
except:
ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out':
ax.set_title(h5file[k[0]][ifgramList[i-1]].attrs['DATE12'],fontsize=font_size)
elif title=='in':
add_inner_title(ax, h5file[k[0]][ifgramList[i-1]].attrs['DATE12'], loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
plt.show()
####################################################################
####################################################################
elif k[0]in('interferograms','coherence','wrapped') and allData2display=='no':
if k[0] in ('coherence','wrapped'):
rewrapping=='no'
ifgramList=h5file[k[0]].keys()
try:
epoch_number
except:
for i in range(len(ifgramList)):
if epoch_date in ifgramList[i]:
epoch_number = i
dset = h5file[k[0]][ifgramList[epoch_number]].get(ifgramList[epoch_number])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping=='yes':
data=np.angle(np.exp(1j*data))
if dip_opposite in('yes','Yes','Y','y','YES'):
data=-1*data
#DEM basemap
try:
demFile
if os.path.basename(demFile).split('.')[1]=='hgt':
amp,dem,demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1]=='dem':
dem,demRsc = readfile.read_dem(demFile)
try:
win_x
wx=[int(i) for i in win_x.split()]
dem=dem[:,wx[0]:wx[1]]
except:
print ''
try:
win_y
wy=[int(i) for i in win_y.split()]
dem=dem[wy[0]:wy[1],:]
except:
print ''
if flip_lr=='yes':
dem=np.fliplr(dem)
if flip_ud=='yes':
dem=np.flipud(dem)
cmap_dem=plt.get_cmap('gray')
if disp_geo in ('yes','Yes','Y','y','YES') and geocoord in ('yes','Yes','Y','y','YES'):
print 'display geo'
else:
print 'Not GEO'
plt.imshow(ut.hillshade(dem,50.0),cmap=cmap_dem)
except:
print 'No DEM file'
try:
plt.imshow(data,cmap=ccmap,vmin=min,vmax=max)
except:
plt.imshow(data,cmap=ccmap)
plt.colorbar()
# plt.title(h5file[k[0]][ifgramList[epoch_number]].attrs['DATE12'],fontsize=font_size)
plt.title(ifgramList[epoch_number],fontsize=font_size)
plt.show()
################################################################
################################################################
h5file.close()
def main(argv):
try:
opts, args = getopt.getopt(
argv, "h:D:O:G:S:f:m:M:l:u:s:c:e:d:r:p:w:i:j:t:R:a:b:k:x:y:")
except getopt.GetoptError:
Usage()
sys.exit(1)
flip_lr = 'no'
flip_ud = 'no'
disp_geo = 'no'
font_size = 8
color_map = 'jet'
figs_rows = 5
figs_cols = 8
rewrapping = 'yes'
allData2display = 'yes'
Wspace = 0.1
Hspace = 0.1
title = 'out'
# title = 'None'
showRef = 'yes'
ref_color = 'k'
ref_symbol = 's'
ref_size = 10
dip_opposite = 'no'
saveFig = 'no'
if opts == []:
Usage()
sys.exit(1)
for opt, arg in opts:
if opt in ("-h", "--help"):
Usage()
sys.exit()
elif opt == '-f':
File = arg
elif opt == '-D':
demFile = arg
elif opt == '-m':
min = float(arg)
elif opt == '-M':
max = float(arg)
elif opt == '-l':
flip_lr = arg
elif opt == '-u':
flip_ud = arg
elif opt == '-s':
font_size = int(arg)
elif opt == '-c':
color_map = arg
elif opt == '-e':
epoch_number = int(arg)
allData2display = 'no'
elif opt == '-d':
epoch_date = arg
allData2display = 'no'
elif opt == '-r':
figs_rows = int(arg)
elif opt == '-p':
figs_cols = int(arg)
elif opt == '-w':
rewrapping = arg
elif opt == '-i':
Wspace = float(arg)
elif opt == '-j':
Hspace = float(arg)
elif opt == '-t':
title = arg
elif opt == '-R':
showRef = arg
elif opt == '-a':
ref_color = arg
elif opt == '-b':
ref_symbol = arg
elif opt == 'k':
ref_size = int(arg)
elif opt == '-x':
win_x = arg
elif opt == '-y':
win_y = arg
elif opt == '-G':
disp_geo = arg
elif opt == '-O':
dip_opposite = arg
elif opt == '-S':
saveFig = arg
h5file = h5py.File(File, 'r')
k = h5file.keys()
print k
if color_map == 'hsv':
################################################
cdict1 = {
'red': ((0.0, 0.0, 0.0), (0.5, 0.0, 0.0), (0.6, 1.0, 1.0),
(0.8, 1.0, 1.0), (1.0, 0.5, 0.5)),
'green': ((0.0, 0.0, 0.0), (0.2, 0.0, 0.0), (0.4, 1.0, 1.0),
(0.6, 1.0, 1.0), (0.8, 0.0, 0.0), (1.0, 0.0, 0.0)),
'blue': (
(0.0, 0.5, .5),
(0.2, 1.0, 1.0),
(0.4, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0),
)
}
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
################################################
else:
ccmap = plt.get_cmap(color_map)
####################################################################
####################################################################
# if k[0]=='velocity' or k[0]=='temporal_coherence' or k[0]=='rmse':
if len(k) == 1 and k[0] in ('dem', 'velocity', 'mask',
'temporal_coherence', 'rmse'):
dset = h5file[k[0]].get(k[0])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if dip_opposite in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = -1 * data
try:
xref = h5file[k[0]].attrs['ref_x']
yref = h5file[k[0]].attrs['ref_y']
except:
print 'No reference point'
# Yunjun, Mar 2015
try:
xref = xref - h5file[k[0]].attrs['subset_x0']
yref = yref - h5file[k[0]].attrs['subset_y0']
except:
print 'No subset'
try:
ullon = float(h5file[k[0]].attrs['X_FIRST'])
ullat = float(h5file[k[0]].attrs['Y_FIRST'])
lon_step = float(h5file[k[0]].attrs['X_STEP'])
lat_step = float(h5file[k[0]].attrs['Y_STEP'])
lon_unit = h5file[k[0]].attrs['Y_UNIT']
lat_unit = h5file[k[0]].attrs['X_UNIT']
llcrnrlon = ullon
llcrnrlat = ullat + lat_step * data.shape[0]
urcrnrlon = ullon + lon_step * data.shape[1]
urcrnrlat = ullat
geocoord = 'yes'
print 'Input file is Geocoded'
except:
geocoord = 'no'
try:
win_x
wx = [int(i) for i in win_x.split()]
data = data[:, wx[0]:wx[1]]
xref = xref - wx[0]
except:
print 'No subste in x direction'
try:
win_y
wy = [int(i) for i in win_y.split()]
data = data[wy[0]:wy[1], :]
yref = yref - wy[0]
except:
print 'No subset in y direction'
try:
min
except:
min = np.nanmin(data)
try:
max
except:
max = np.nanmax(data)
if flip_lr == 'yes':
data = np.fliplr(data)
xref = np.shape(data)[1] - xref - 1
if flip_ud == 'yes':
data = np.flipud(data)
yref = np.shape(data)[0] - yref - 1
try:
demFile
# amp,dem,demRsc = readfile.read_float32(demFile)
if os.path.basename(demFile).split('.')[1] == 'hgt':
amp, dem, demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1] == 'dem':
dem, demRsc = readfile.read_dem(demFile)
try:
win_x
wx = [int(i) for i in win_x.split()]
dem = dem[:, wx[0]:wx[1]]
except:
print ''
try:
win_y
wy = [int(i) for i in win_y.split()]
dem = dem[wy[0]:wy[1], :]
except:
print ''
if flip_lr == 'yes':
dem = np.fliplr(dem)
if flip_ud == 'yes':
dem = np.flipud(dem)
cmap_dem = plt.get_cmap('gray')
if disp_geo in ('yes', 'Yes', 'Y', 'y',
'YES') and geocoord in ('yes', 'Yes', 'Y', 'y',
'YES'):
print 'display geo'
# from mpl_toolkits.basemap import Basemap
# m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,resolution='f', area_thresh=1., projection='cyl')
# m.imshow(ut.hillshade(dem,50.0), interpolation='nearest', origin='upper')
# m.drawcoastlines(color='w',linewidth=0.8)
# m.drawmapboundary() # draw a line around the map region
# m.drawrivers()
# m.drawparallels(numpy.arange(int(d1.min()), int(d1.max()), 1),linewidth=0.2,labels=[1,0,0,0])
# m.drawmeridians(numpy.arange(int(d0.min()), int(d0.max()), 1),linewidth=0.2,labels=[0,0,0,1])
else:
print 'Not GEO'
plt.imshow(ut.hillshade(dem, 50.0), cmap=cmap_dem)
except:
print 'No DEM file'
plt.imshow(data, cmap=ccmap, vmin=min, vmax=max)
plt.colorbar()
if k[0] == 'velocity':
plt.title('Velocity (m/yr)', fontsize=font_size)
figName = 'velocity.pdf'
elif k[0] == 'temporal_coherence':
plt.title('Temporal coherence', fontsize=font_size)
figName = 'temporal_coherence.pdf'
elif k[0] == 'dem':
plt.title('DEM error', fontsize=font_size)
figName = 'DEM_error.pdf'
elif k[0] == 'rmse':
plt.title('RMSE (m/yr)', fontsize=font_size)
figName = 'rmse.pdf'
elif k[0] == 'mask':
plt.title('Pixels with no valid value.', fontsize=font_size)
figName = 'mask.pdf'
if showRef == 'yes':
try:
refPoint = ref_color + ref_symbol
plt.plot(xref, yref, refPoint, ms=ref_size)
except:
print 'No reference point'
plt.xlim(0, np.shape(data)[1])
plt.ylim(np.shape(data)[0], 0)
if saveFig == 'yes':
plt.savefig(figName)
plt.show()
# plt.savefig('fig.pdf')
# fig = plt.figure()
# ax.imshow(data,vmin=min, vmax=max)
# ax.xaxis.label.set_fontsize(40)
####################################################################
####################################################################
if 'timeseries' in k and allData2display == 'yes':
if rewrapping == 'yes':
print 'rewrapping'
dateList = h5file['timeseries'].keys()
nfigs = figs_rows * figs_cols
ligram = len(dateList)
range2phase = 4 * np.pi / float(
h5file['timeseries'].attrs['WAVELENGTH'])
# range2phase=4*np.pi/0.056
print 'number of timeseries epochs to display:' + str(ligram)
kk = int(ligram / nfigs) + 1
ii = 0
for j in range(1, kk):
fig = plt.figure(j)
ii = (j - 1) * nfigs + 1
for i in range(ii, ii + nfigs):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
dset = h5file['timeseries'].get(dateList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
data = range2phase * data
# data=np.angle(np.exp(1j*data))
data = rewrap(data)
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(dateList[i - 1], fontsize=font_size)
elif title == 'in':
add_inner_title(ax, dateList[i - 1], loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
figName = k[0] + '_' + str(j) + '.pdf'
if saveFig in ['yes', 'Yes', 'y', 'YES']:
plt.savefig(figName)
fig = plt.figure(kk)
ii = (kk - 1) * nfigs + 1
for i in range(ii, ligram + 1):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
dset = h5file['timeseries'].get(dateList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
data = range2phase * data
# data=np.angle(np.exp(1j*data))
data = rewrap(data)
ax.imshow(data, cmap=ccmap)
ax.xaxis.label.set_fontsize(20)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(dateList[i - 1], fontsize=font_size)
elif title == 'in':
add_inner_title(ax, dateList[i - 1], loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
figName = k[0] + '_' + str(kk) + '.pdf'
if saveFig in ['yes', 'Yes', 'y', 'YES']:
plt.savefig(figName)
plt.show()
else:
print 'No rewrapping'
dateList = h5file['timeseries'].keys()
nfigs = figs_rows * figs_cols
ligram = len(dateList)
print 'number of timeseries epochs to display:' + str(ligram)
kk = int(ligram / nfigs) + 1
ii = 0
for j in range(1, kk):
fig = plt.figure(j)
ii = (j - 1) * nfigs + 1
for i in range(ii, ii + nfigs):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
data = h5file['timeseries'].get(dateList[i - 1])
try:
im = ax.imshow(data, cmap=ccmap, vmin=min, vmax=max)
# print 'here'
except:
im = ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(dateList[i - 1], fontsize=font_size)
elif title == 'in':
add_inner_title(ax, dateList[i - 1], loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
fig = plt.figure(kk)
ii = (kk - 1) * nfigs + 1
for i in range(ii, ligram + 1):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
data = h5file['timeseries'].get(dateList[i - 1])
try:
im = ax.imshow(data, cmap=ccmap, vmin=min, vmax=max)
except:
im = ax.imshow(data, cmap=ccmap)
ax.xaxis.label.set_fontsize(20)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(dateList[i - 1], fontsize=font_size)
if title == 'in':
add_inner_title(ax, dateList[i - 1], loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
plt.show()
####################################################################
####################################################################
elif 'timeseries' in k and allData2display == 'no':
dateList = h5file['timeseries'].keys()
try:
epoch_number
except:
epoch_number = dateList.index(epoch_date)
range2phase = 4 * np.pi / float(
h5file['timeseries'].attrs['WAVELENGTH'])
# range2phase=4*np.pi/0.056
dset = h5file['timeseries'].get(dateList[epoch_number])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping == 'yes':
data = range2phase * data
# data=np.angle(np.exp(1j*data))
data = rewrap(data)
try:
min
except:
min = np.nanmin(data)
try:
max
except:
max = np.nanmax(data)
plt.imshow(data, cmap=ccmap, vmin=min, vmax=max)
plt.colorbar()
plt.show()
################################################################
################################################################
if k[0] in ('interferograms', 'coherence',
'wrapped') and allData2display == 'yes':
if k[0] in ('coherence', 'wrapped'):
rewrapping = 'no'
# color_map = 'gray'
# ccmap=plt.get_cmap(color_map)
if rewrapping == 'yes':
ifgramList = h5file[k[0]].keys()
nfigs = figs_rows * figs_cols
ligram = len(ifgramList)
print 'number of ' + k[0] + ' to display:' + str(ligram)
kk = int(ligram / nfigs) + 1
ii = 0
for j in range(1, kk):
fig = plt.figure(j)
ii = (j - 1) * nfigs + 1
for i in range(ii, ii + nfigs):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i -
1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
data = np.angle(np.exp(1j * data))
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
fontsize=font_size)
elif title == 'in':
add_inner_title(
ax,
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
fig = plt.figure(kk)
ii = (kk - 1) * nfigs + 1
for i in range(ii, ligram + 1):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
data = np.angle(np.exp(1j * data))
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(h5file[k[0]][ifgramList[i -
1]].attrs['DATE12'],
fontsize=font_size)
elif title == 'in':
add_inner_title(
ax,
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
plt.show()
else:
ifgramList = h5file[k[0]].keys()
nfigs = figs_rows * figs_cols
ligram = len(ifgramList)
print 'number of ' + k[0] + ' to display:' + str(ligram)
kk = int(ligram / nfigs) + 1
ii = 0
for j in range(1, kk):
fig = plt.figure(j)
ii = (j - 1) * nfigs + 1
for i in range(ii, ii + nfigs):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
print 'loading ' + ifgramList[i - 1]
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i -
1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
try:
ax.imshow(data, vmin=min, vmax=max, cmap=ccmap)
except:
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
fontsize=font_size)
elif title == 'in':
add_inner_title(
ax,
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
fig = plt.figure(kk)
ii = (kk - 1) * nfigs + 1
for i in range(ii, ligram + 1):
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
print 'loading ' + ifgramList[i - 1]
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
#data = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
try:
ax.imshow(data, vmin=min, vmax=max, cmap=ccmap)
except:
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out':
ax.set_title(h5file[k[0]][ifgramList[i -
1]].attrs['DATE12'],
fontsize=font_size)
elif title == 'in':
add_inner_title(
ax,
h5file[k[0]][ifgramList[i - 1]].attrs['DATE12'],
loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
plt.show()
####################################################################
####################################################################
elif k[0] in ('interferograms', 'coherence',
'wrapped') and allData2display == 'no':
if k[0] in ('coherence', 'wrapped'):
rewrapping == 'no'
ifgramList = h5file[k[0]].keys()
try:
epoch_number
except:
for i in range(len(ifgramList)):
if epoch_date in ifgramList[i]:
epoch_number = i
dset = h5file[k[0]][ifgramList[epoch_number]].get(
ifgramList[epoch_number])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping == 'yes':
data = np.angle(np.exp(1j * data))
if dip_opposite in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = -1 * data
#DEM basemap
try:
demFile
if os.path.basename(demFile).split('.')[1] == 'hgt':
amp, dem, demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1] == 'dem':
dem, demRsc = readfile.read_dem(demFile)
try:
win_x
wx = [int(i) for i in win_x.split()]
dem = dem[:, wx[0]:wx[1]]
except:
print ''
try:
win_y
wy = [int(i) for i in win_y.split()]
dem = dem[wy[0]:wy[1], :]
except:
print ''
if flip_lr == 'yes':
dem = np.fliplr(dem)
if flip_ud == 'yes':
dem = np.flipud(dem)
cmap_dem = plt.get_cmap('gray')
if disp_geo in ('yes', 'Yes', 'Y', 'y',
'YES') and geocoord in ('yes', 'Yes', 'Y', 'y',
'YES'):
print 'display geo'
else:
print 'Not GEO'
plt.imshow(ut.hillshade(dem, 50.0), cmap=cmap_dem)
except:
print 'No DEM file'
try:
plt.imshow(data, cmap=ccmap, vmin=min, vmax=max)
except:
plt.imshow(data, cmap=ccmap)
plt.colorbar()
# plt.title(h5file[k[0]][ifgramList[epoch_number]].attrs['DATE12'],fontsize=font_size)
plt.title(ifgramList[epoch_number], fontsize=font_size)
plt.show()
################################################################
################################################################
h5file.close()
def main(argv):
color_map = 'jet'
disp_opposite = 'no'
try:
opts, args = getopt.getopt(argv, "h:f:d:o:x:y:m:M:i:c:")
except getopt.GetoptError:
Usage()
sys.exit(1)
if opts == []:
Usage()
sys.exit(1)
for opt, arg in opts:
if opt in ("-h", "--help"):
Usage()
sys.exit()
elif opt == '-f':
File = arg
elif opt == '-d':
demFile = arg
elif opt == '-m':
Vmin = float(arg)
elif opt == '-M':
Vmax = float(arg)
elif opt == '-x':
winx = arg.split(':')
elif opt == '-y':
winy = arg.split(':')
elif opt == '-o':
outName = arg
elif opt == '-i':
disp_opposite = arg
elif opt == '-c':
color_map = arg
h5file = h5py.File(File, 'r')
k = h5file.keys()
print k[0]
# ccmap=plt.get_cmap(color_map)
################################################
cdict1 = {
'red': ((0.0, 0.0, 0.0), (0.5, 0.0, 0.0), (0.6, 1.0, 1.0),
(0.8, 1.0, 1.0), (1.0, 0.5, 0.5)),
'green': ((0.0, 0.0, 0.0), (0.2, 0.0, 0.0), (0.4, 1.0, 1.0),
(0.6, 1.0, 1.0), (0.8, 0.0, 0.0), (1.0, 0.0, 0.0)),
'blue': (
(0.0, 0.5, .5),
(0.2, 1.0, 1.0),
(0.4, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0),
)
}
if color_map == 'pysar_hsv':
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
else:
ccmap = plt.get_cmap(color_map)
print 'colormap is : ' + color_map
################################################
dset = h5file[k[0]].get(k[0])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if disp_opposite in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = -1 * data
try:
xref = h5file[k[0]].attrs['ref_x']
yref = h5file[k[0]].attrs['ref_y']
except:
print 'No reference point'
try:
ullon = float(h5file[k[0]].attrs['X_FIRST'])
ullat = float(h5file[k[0]].attrs['Y_FIRST'])
lon_step = float(h5file[k[0]].attrs['X_STEP'])
lat_step = float(h5file[k[0]].attrs['Y_STEP'])
lon_unit = h5file[k[0]].attrs['Y_UNIT']
lat_unit = h5file[k[0]].attrs['X_UNIT']
llcrnrlon = ullon
llcrnrlat = ullat + lat_step * data.shape[0]
urcrnrlon = ullon + lon_step * data.shape[1]
urcrnrlat = ullat
geocoord = 'yes'
print 'Input file is Geocoded'
except:
geocoord = 'no'
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
m = Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
area_thresh=1.,
projection='cyl',
suppress_ticks=False,
ax=ax)
print demFile
demFile
if os.path.basename(demFile).split('.')[1] == 'hgt':
amp, dem, demRsc = readfile.read_float32(demFile)
elif os.path.basename(demFile).split('.')[1] == 'dem':
dem, demRsc = readfile.read_dem(demFile)
#################################################################
try:
winx
wx = [int(i) for i in win_x.split()]
dem = dem[:, wx[0]:wx[1]]
data = data[:, wx[0]:wx[1]]
ullon = float(h5file[k[0]].attrs['X_FIRST']) + wx[0]
llcrnrlon = ullon
urcrnrlon = ullon + lon_step * data.shape[1]
except:
print ''
try:
winy
wy = [int(i) for i in winy.split()]
dem = dem[wy[0]:wy[1], :]
data = data[wy[0]:wy[1], :]
except:
print ''
################################################################
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
m = Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
area_thresh=1.,
projection='cyl',
suppress_ticks=False,
ax=ax)
cmap_dem = plt.get_cmap('gray')
m.imshow(ut.hillshade(np.flipud(dem), 50.0), cmap=cmap_dem)
try:
im = m.imshow(np.flipud(data), vmin=Vmin, vmax=Vmax, cmap=ccmap)
# cb = m.colorbar(im,"right", size="5%", pad='2%')
except:
im = m.imshow(np.flipud(data))
# cb = m.colorbar(im,"right", size="5%", pad='2%')
# m.bluemarble()
# cb = m.colorbar(im,"right", size="5%", pad='2%')
# parallels = np.arange(31.,34,0.5)
# m.drawparallels(parallels,labels=[1,0,0,1],linewidth=0.0)
# meridians = np.arange(-115.,-112.,0.5)
# m.drawmeridians(meridians,labels=[1,0,0,1],linewidth=0.0)
# m.drawmapscale()
# m = Basemap(llcrnrlon=-110.,llcrnrlat=0.,urcrnrlon=-20.,urcrnrlat=57.,
# projection='lcc',lat_1=20.,lat_2=40.,lon_0=-60.,
# resolution ='l',area_thresh=1000.)
# m.drawcoastlines()
# m.drawcountries()
# m.drawmapboundary(fill_color='#99ffff')
# m.fillcontinents(color='#cc9966',lake_color='#99ffff')
# m.drawparallels(np.arange(10,70,20),labels=[1,1,0,0])
# m.drawmeridians(np.arange(-100,0,20),labels=[0,0,0,1])
# plt.title('Atlantic Hurricane Tracks (Storms Reaching Category 4, 1851-2004)')
try:
figName = outName
except:
outName = os.path.basename(File).replace('.h5', '')
figName = outName + '.png'
plt.savefig(figName, pad_inches=0.0)
# plt.show()
h5file.close()