def main(argv):
try:
file = argv[0]
alks = float(argv[1])
rlks = float(argv[2])
except:
try:
file = argv[0]
alks = float(argv[1])
rlks = float(argv[1])
except:
Usage()
sys.exit(1)
ext = os.path.splitext(file)[1]
outName = file.split('.')[0] + '_a' + str(int(alks)) + 'lks_r' + str(
int(rlks)) + 'lks' + ext
################################################################################
if ext == '.h5':
import h5py
h5file_mli = h5py.File(outName, 'w')
h5file = h5py.File(file, 'r')
k = h5file.keys()
if 'interferograms' in k: k[0] = 'interferograms'
elif 'coherence' in k: k[0] = 'coherence'
elif 'timeseries' in k: k[0] = 'timeseries'
if k[0] in ['interferograms', 'coherence', 'wrapped']:
print 'Multilooking the interferograms'
gg = h5file_mli.create_group(k[0])
igramList = h5file[k[0]].keys()
for igram in igramList:
print igram
unw = h5file[k[0]][igram].get(igram)
unwlks = multilook(unw, alks, rlks)
group = gg.create_group(igram)
dset = group.create_dataset(igram,
data=unwlks,
compression='gzip')
for key, value in h5file[k[0]][igram].attrs.iteritems():
group.attrs[key] = value
group.attrs['WIDTH'] = unwlks.shape[1]
group.attrs['FILE_LENGTH'] = unwlks.shape[0]
try:
group.attrs['Y_STEP'] = alks * float(group.attrs['Y_STEP'])
group.attrs['X_STEP'] = rlks * float(group.attrs['X_STEP'])
except:
group.attrs['AZIMUTH_PIXEL_SIZE'] = alks * float(
group.attrs['AZIMUTH_PIXEL_SIZE'])
group.attrs['RANGE_PIXEL_SIZE'] = rlks * float(
group.attrs['RANGE_PIXEL_SIZE'])
try:
dset1 = h5file['mask'].get('mask')
mask = dset1[0:dset1.shape[0], 0:dset1.shape[1]]
masklks = multilook(mask, alks, rlks)
group = h5file_mli.create_group('mask')
dset = group.create_dataset('mask',
data=masklks,
compression='gzip')
except:
print 'No mask group found.'
elif k[0] in [
'timeseries', 'temporal_coherence', 'velocity', 'mask', 'rmse'
]:
print 'Multilooking ' + k[0]
group = h5file_mli.create_group(k[0])
if k[0] == 'timeseries':
dateList = h5file[k[0]].keys()
for d in dateList:
print d
unw = h5file[k[0]].get(d)
unwlks = multilook(unw, alks, rlks)
dset = group.create_dataset(d,
data=unwlks,
compression='gzip')
elif k[0] in ['temporal_coherence', 'velocity', 'mask', 'rmse']:
dset1 = h5file[k[0]].get(k[0])
unw = dset1[0:dset1.shape[0], 0:dset1.shape[1]]
unwlks = multilook(unw, alks, rlks)
dset = group.create_dataset(k[0],
data=unwlks,
compression='gzip')
try:
dset1 = h5file['mask'].get('mask')
Mask = dset1[0:dset1.shape[0], 0:dset1.shape[1]]
Masklks = multilook(Mask, alks, rlks)
group = h5file_mli.create_group('mask')
dset = group.create_dataset('mask',
data=Masklks,
compression='gzip')
except:
print 'No mask group found.'
## Update attributes
for key, value in h5file[k[0]].attrs.iteritems():
group.attrs[key] = value
group.attrs['WIDTH'] = unwlks.shape[1]
group.attrs['FILE_LENGTH'] = unwlks.shape[0]
try:
group.attrs['Y_STEP'] = alks * float(group.attrs['Y_STEP'])
group.attrs['X_STEP'] = rlks * float(group.attrs['X_STEP'])
except:
group.attrs['AZIMUTH_PIXEL_SIZE'] = alks * float(
group.attrs['AZIMUTH_PIXEL_SIZE'])
group.attrs['RANGE_PIXEL_SIZE'] = rlks * float(
group.attrs['RANGE_PIXEL_SIZE'])
h5file.close()
h5file_mli.close()
################################################################################
elif ext in ['.unw','.cor','.hgt','.dem','.trans'] or\
ext in ['.jpeg','.jpg','.png','.ras','.bmp'] or\
ext in ['.mli','.slc']:
import pysar._readfile as readfile
import pysar._writefile as writefile
r = readfile.read_rsc_file(file + '.rsc')
if ext == '.int' or ext == '.slc':
a, p, r = readfile.read_complex64(file)
pmli = multilook(p, alks, rlks)
amli = multilook(a, alks, rlks)
r['FILE_LENGTH'] = str(pmli.shape[0])
r['WIDTH'] = str(pmli.shape[1])
elif ext == '.unw' or ext == '.cor' or ext == '.hgt':
a, p, r = readfile.read_float32(file)
pmli = multilook(p, alks, rlks)
amli = multilook(a, alks, rlks)
print 'writing >>>' + outName
writefile.write_float32(pmli, outName)
r['FILE_LENGTH'] = str(pmli.shape[0])
r['WIDTH'] = str(pmli.shape[1])
elif ext == ('.dem'):
d, r = readfile.read_dem(file)
dmli = multilook(d, alks, rlks)
print 'writing >>>' + outName
writefile.write_dem(dmli, outName)
r['FILE_LENGTH'] = str(dmli.shape[0])
r['WIDTH'] = str(dmli.shape[1])
elif ext in ['.jpeg', '.jpg', '.png', '.bmp']:
import Image
im = Image.open(file)
width = im.size[0] / int(rlks)
height = im.size[1] / int(alks)
imlks = im.resize((width, height), Image.NEAREST)
print 'writing >>>' + outName
imlks.save(outName)
r['FILE_LENGTH'] = str(height)
r['WIDTH'] = str(width)
## Update attributes
r['XMAX'] = str(int(r['WIDTH']) - 1)
r['YMAX'] = str(int(r['FILE_LENGTH']) - 1)
try:
r['Y_STEP'] = str(float(r['Y_STEP']) * alks)
r['X_STEP'] = str(float(r['X_STEP']) * rlks)
except:
r['AZIMUTH_PIXEL_SIZE'] = alks * float(r['AZIMUTH_PIXEL_SIZE'])
r['RANGE_PIXEL_SIZE'] = rlks * float(r['RANGE_PIXEL_SIZE'])
f = open(outName + '.rsc', 'w')
for k in r.keys():
f.write(k + ' ' + r[k] + '\n')
f.close()
def main(argv):
################# default values ################
flip_lr='no'
flip_ud='no'
disp_geo = 'yes'
#font_size=8
color_map='jet'
figs_rows=5
figs_cols=8
rewrapping='yes'
allData2display='yes'
Wspace = 0.1
Hspace = 0.1
title = 'out'
showRef = 'yes'
ref_color='k'
ref_symbol='s'
ref_size =10
dip_opposite = 'no'
saveFig='no'
dispFig='yes'
dispContour='only'
contour_step=200
contour_sigma=3.0
fig_dpi=300
################### get input args ###############
if len(sys.argv)>2:
try:
opts, args = getopt.getopt(argv,"h:D:O:G:S:f:m:M:v:u:s:c:e:d:r:p:w:i:j:t:R:a:b:k:x:y:C:V:P:o:g:l:L:")
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 == '-w': rewrapping = arg
elif opt == '-m': min = float(arg); rewrapping='no'
elif opt == '-M': max = float(arg); rewrapping='no'
elif opt == '-v': 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 == '-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 = [int(i) for i in arg.split(':')]; win_x.sort()
elif opt == '-y': win_y = [int(i) for i in arg.split(':')]; win_y.sort()
elif opt == '-G': disp_geo = arg
elif opt == '-O': dip_opposite=arg
elif opt == '-S': saveFig=arg
elif opt == '-C': dispContour=arg
elif opt == '-V': contour_step=float(arg)
elif opt == '-P': dispFig=arg
elif opt == '-o': figName=arg
elif opt == '-g': contour_sigma = float(arg)
elif opt == '-l': win_lat = [float(i) for i in arg.split(':')]; win_lat.sort()
elif opt == '-L': win_lon = [float(i) for i in arg.split(':')]; win_lon.sort()
elif len(sys.argv)==2:
if argv[0]=='-h': Usage(); sys.exit(1)
elif os.path.isfile(argv[0]): File = argv[0]
else:
print 'Input file does not existed: '+argv[0]; sys.exit(1)
elif len(sys.argv)<2: Usage(); sys.exit(1)
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),)
}
from matplotlib.colors import LinearSegmentedColormap
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
################################################
else: ccmap=plt.get_cmap(color_map)
##################################################
ext = os.path.splitext(File)[1]
if ext == '.h5':
import h5py
h5file=h5py.File(File,'r')
k=h5file.keys()
if 'interferograms' in k: k[0] = 'interferograms'
elif 'coherence' in k: k[0] = 'coherence'
elif 'timeseries' in k: k[0] = 'timeseries'
print 'Input: '+str(k)
if k[0] in ('dem','velocity','mask','temporal_coherence','rmse'):
allData2display = 'no'
elif ext in ['.unw','.int','.cor','.hgt','.dem','.trans','.mli','.slc']:
import pysar._readfile as readfile
allData2display = 'no'
k = [ext]
else:
print 'File extension not recogized: '+ext
print 'Support file format:\n\
PySAR HDF5 files: velocity.h5, timeseries.h5, LoadedData.h5, ...\n\
ROI_PAC files: .unw .cor .int .hgt .dem .trans .mli'
sys.exit(1)
####################################################################
########################## Plot One ################################
if allData2display == 'no':
try: font_size
except: font_size=12
################# File Reading ##################
##### PySAR HDF5
if k[0] in ('dem','velocity','mask','temporal_coherence','rmse'):
atr = h5file[k[0]].attrs
dset = h5file[k[0]].get(k[0])
data = dset[0:dset.shape[0],0:dset.shape[1]]
# rewrapping
if rewrapping in ('yes','Yes','Y','y','YES'):
print 'Rewrapping disabled for '+k[0]
elif k[0] == 'timeseries':
dateList=h5file[k[0]].keys()
try:
epoch_number
except:
try:
epoch_date
if len(epoch_date)==6: epoch_date=yymmdd2yyyymmdd(epoch_date)
epoch_number=dateList.index(epoch_date)
except:
print 'Unrecognized epoch input!'; sys.exit(1)
print 'Displaying date: '+dateList[epoch_number]
atr = h5file[k[0]].attrs
dset = h5file[k[0]].get(dateList[epoch_number])
data = dset[0:dset.shape[0],0:dset.shape[1]]
# rewrapping
if rewrapping in ('yes','Yes','y','Y','YES'):
print 'Rewrapping. Set min/max to -pi/pi. Showing phase'
range2phase=4*np.pi/float(atr['WAVELENGTH']) #double-way, 2*2*pi/lamda
data=range2phase*data
data=rewrap(data)
min = -np.pi
max = np.pi
figUnit='(radian)'
elif rewrapping in ('no','No','N','n','NO'):
print 'No rewrapping. Showing displacement.'
figUnit='(m)'
elif k[0] in ('interferograms','coherence','wrapped'):
ifgramList=h5file[k[0]].keys()
try:
epoch_number
except:
for i in range(len(ifgramList)):
if epoch_date in ifgramList[i]: epoch_number = i
print 'Displaying: '+ifgramList[epoch_number]
atr = h5file[k[0]][ifgramList[epoch_number]].attrs
dset = h5file[k[0]][ifgramList[epoch_number]].get(ifgramList[epoch_number])
data = dset[0:dset.shape[0],0:dset.shape[1]]
# rewrapping
if k[0] in ('coherence','wrapped') and rewrapping in ('yes','Yes','y','Y','YES'):
print 'No rewrapping for coherence/wrapped files, set to "no"'
rewrapping='no'
if rewrapping in ('yes','Yes','y','Y','YES'):
print 'Rewrapping. Set min/max to -pi/pi.'
data = np.angle(np.exp(1j*data))
min = -np.pi
max = np.pi
##### ROI_PAC product
elif k[0] in ['.slc','.mli']:
data,p,atr = readfile.read_complex64(File)
data= np.nanlog10(data)
figUnit = '(dB)'
elif k[0] == '.int':
a,data,atr = readfile.read_complex64(File)
min = -np.pi
max = np.pi
rewrapping = 'no'
figUnit = '(radian)'
elif k[0] in ['.unw', '.cor', '.hgt', '.trans']:
a,data,atr = readfile.read_float32(File)
if k[0] == '.unw': figUnit = '(radian)'
elif k[0] == '.hgt': figUnit = '(m)'
if k[0] in ['.cor','.hgt','.trans']: rewrapping='no'
if rewrapping in ('yes','Yes','y','Y','True','true'):
print 'Rewrapping. Set min/max to -pi/pi.'
data = rewrap(data)
min = -np.pi
max = np.pi
elif k[0] == '.dem':
data,atr = readfile.read_dem(File)
figUnit = '(m)'
############## Data Option ##################
# Opposite Sign
if dip_opposite in ('yes','Yes','Y','y','YES'):
data=-1*data
# Subset
try: # y/latitude direction
win_lat
try:
atr['Y_FIRST']
win_y=[0]*2
win_y[0]=int((win_lat[1]-float(atr['Y_FIRST']))/float(atr['Y_STEP']))
win_y[1]=int((win_lat[0]-float(atr['Y_FIRST']))/float(atr['Y_STEP']))
if win_y[0]<0: win_y[0]=0; print 'input latitude > max latitude! Set to max'
print 'subset in latitude - '+str(win_lat[0])+':'+str(win_lat[1])
except: print 'Non-geocoded file, cannot use LatLon option'; Usage(); sys.exit(1)
except:
try:
win_y
print 'subset in y direction - '+str(win_y[0])+':'+str(win_y[1])
except: win_y = [0,int(atr['FILE_LENGTH'])]
try: # x/longitude direction
win_lon
try:
atr['X_FIRST']
win_x=[0]*2
win_x[0]=int((win_lon[0]-float(atr['X_FIRST']))/float(atr['X_STEP']))
win_x[1]=int((win_lon[1]-float(atr['X_FIRST']))/float(atr['X_STEP']))
if win_x[0]<0: win_x[0]=0; print 'input longitude > max longitude! Set to max'
print 'subset in longitude - '+str(win_lon[0])+':'+str(win_lon[1])
except: print 'Non-geocoded file, cannot use LatLon option'; Usage(); sys.exit(1)
except:
try:
win_x
print 'subset in x direction - '+str(win_x[0])+':'+str(win_x[1])
except: win_x = [0,int(atr['WIDTH'])]
data = data[win_y[0]:win_y[1],win_x[0]:win_x[1]]
# Reference Point
try:
xref=atr['ref_x']-win_x[0]
yref=atr['ref_y']-win_y[0]
except: print 'No reference point'
try:
xref=xref-atr['subset_x0']
yref=yref-atr['subset_y0']
except: print 'No subset'
# Geo coordinate
try:
lon_step = float(atr['X_STEP'])
lat_step = float(atr['Y_STEP'])
lon_unit = atr['Y_UNIT']
lat_unit = atr['X_UNIT']
ullon = float(atr['X_FIRST'])+win_x[0]*lon_step
ullat = float(atr['Y_FIRST'])+win_y[0]*lat_step
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'
# Flip
if flip_lr in ('yes','Yes','Y','y','YES'): data=np.fliplr(data); xref=np.shape(data)[1]-xref-1
if flip_ud in ('yes','Yes','Y','y','YES'): data=np.flipud(data); yref=np.shape(data)[0]-yref-1
# Colorbar Extend
data_min = np.nanmin(data)
data_max = np.nanmax(data)
try: min
except: min = data_min
try: max
except: max = data_max
if min <= data_min and max >= data_max: cb_extend='neither'
elif min > data_min and max >= data_max: cb_extend='min'
elif min <= data_min and max < data_max: cb_extend='max'
else: cb_extend='both'
############## DEM Option ##################
try:
demFile
print 'Show topography'
import pysar._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)
# Subset
dem = dem[win_y[0]:win_y[1],win_x[0]:win_x[1]]
# Flip
if flip_lr in ('yes','Yes','Y','y','YES'): dem=np.fliplr(dem)
if flip_ud in ('yes','Yes','Y','y','YES'): dem=np.flipud(dem)
# DEM data preparation
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'): #DEM basemap
print 'plot DEM as basemap'
cmap_dem=plt.get_cmap('gray')
import pysar._pysar_utilities as ut
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'): #contour
print 'plot contour'
#if smoothContour in ('yes','Yes','y','Y','YES'):
import scipy.ndimage as ndimage
dem=ndimage.gaussian_filter(dem,sigma=contour_sigma,order=0)
contour_sequence=np.arange(-6000,9000,contour_step)
except: print 'No DEM file'
############## Data Plot and Output ################
# Figure Title
if k[0]=='velocity': figTitle = 'Velocity (m/yr)'
elif k[0]=='temporal_coherence': figTitle = 'Temporal coherence'
elif k[0]=='dem': figTitle = 'DEM error'
elif k[0]=='rmse': figTitle = 'RMSE (m/yr)'
elif k[0]=='mask': figTitle = 'Pixels with no valid value.'
elif k[0]=='coherence': figTitle = ifgramList[epoch_number]
elif k[0]in('interferograms','wrapped'): figTitle = ifgramList[epoch_number]+' (radian)'
elif k[0]=='timeseries':
try: master_date=atr['ref_date']
except: master_date=atr['DATE']
if len(master_date)==6: master_date=yymmdd2yyyymmdd(master_date)
if dip_opposite in ('yes','Yes','Y','y','YES'): figTitle = dateList[epoch_number]+'_'+master_date+' '+figUnit
else: figTitle = master_date+'_'+dateList[epoch_number]+' '+figUnit
elif k[0] in ['.unw','.cor','.hgt','.dem','.trans','.mli','.slc']:
try: figTitle = File+' '+figUnit
except: figTitle = File
# Plot in Geo-coordinate: plot in map
if geocoord == 'yes' and disp_geo in ('yes','Yes','y','Y','YES'):
print 'display Lat/Lon'
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
try: plt.title(figTitle,fontsize=font_size)
except: pass
# Map - DEM - Data
from mpl_toolkits.basemap import Basemap
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat,
resolution='l', area_thresh=1., projection='cyl',suppress_ticks=False,ax=ax)
try:
demFile
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'):
m.imshow(ut.hillshade(np.flipud(dem),50.0),cmap=cmap_dem)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'):
import numpy.matlib
c_x = np.linspace(llcrnrlon,urcrnrlon,num=dem.shape[1],endpoint='FALSE').reshape(1,dem.shape[1])
c_xx= np.matlib.repmat(c_x,dem.shape[0],1)
c_y = np.linspace(llcrnrlat,urcrnrlat,num=dem.shape[0],endpoint='FALSE').reshape(dem.shape[0],1)
c_yy= np.matlib.repmat(c_y,1,dem.shape[1])
m.contour(c_xx,c_yy,np.flipud(dem),contour_sequence,origin='lower',colors='black',alpha=0.5,latlon='FALSE')
except: pass
try: im = m.imshow(np.flipud(data),cmap=ccmap,vmin=min,vmax=max)
except: im = m.imshow(np.flipud(data),cmap=ccmap)
# Reference Point
if showRef in ('yes','Yes','Y','y','YES'):
try:
refPoint=ref_color+ref_symbol
ref_lon = llcrnrlon + xref*lon_step
ref_lat = urcrnrlat + yref*lat_step
plt.plot(ref_lon,ref_lat,refPoint,ms=ref_size)
except: print 'No reference point'
# Colorbar
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
cax = divider.append_axes("right",size="5%", pad=0.30)
plt.colorbar(im,cax=cax,extend=cb_extend)
#plt.colorbar(im,cax=cax)
# Status bar
def format_coord(x,y):
col = int((x-ullon)/lon_step+0.5)
row = int((y-ullat)/lat_step+0.5)
if col>=0 and col<=data.shape[1] and row >=0 and row<=data.shape[0]:
z = data[row,col]
return 'lat=%.4f, lon=%.4f, value=%.4f'%(x,y,z)
else:
return 'lat=%.4f, lon=%.4f'%(x,y)
ax.format_coord = format_coord
# Plot in x/y coordinate: row and column
else:
fig = plt.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8])
try: plt.title(figTitle,fontsize=font_size)
except: pass
# Plot
try:
demFile
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'):
ax.imshow(ut.hillshade(dem,50.0),cmap=cmap_dem)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'):
ax.contour(dem,contour_sequence,origin='lower',colors='black',alpha=0.5)
except: pass
try: im = ax.imshow(data,cmap=ccmap, vmin=min, vmax=max)
except: im = ax.imshow(data,cmap=ccmap)
cbar = plt.colorbar(im,extend=cb_extend)
#cbar.set_label('m/yr')
# Reference Point
if showRef in ('yes','Yes','Y','y','YES'):
try:
refPoint=ref_color+ref_symbol
ax.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)
# Status bar
def format_coord(x,y):
col = int(x+0.5)
row = int(y+0.5)
if col>=0 and col<=data.shape[1] and row >=0 and row<=data.shape[0]:
z = data[row,col]
return 'x=%.4f, y=%.4f, value=%.4f'%(x,y,z)
else:
return 'x=%.4f, y=%.4f'%(x,y)
ax.format_coord = format_coord
# Save Figure
if saveFig in ('yes','Yes','Y','y','YES'):
try: figName
except:
if k[0]=='velocity': figName='velocity.pdf'
elif k[0]=='temporal_coherence': figName='temporal_coherence.pdf'
elif k[0]=='dem': figName='DEM_error.pdf'
elif k[0]=='rmse': figName='rmse.pdf'
elif k[0]=='mask': figName='mask.pdf'
elif k[0]=='timeseries':
figName=os.path.basename(File).split('.')[0]+'_'+dateList[epoch_number]+'.pdf'
elif k[0] in ('interferograms','coherence','wrapped'):
figName=ifgramList[epoch_number]+'.pdf'
elif k[0] in ['.unw','.cor','.hgt','.dem','.trans','.mli','.slc']:
figName=File+'.pdf'
plt.savefig(figName,dpi=fig_dpi)
print 'Saved figure to '+figName
# Show Figure
if dispFig in ('yes','Yes','Y','y','YES'):
plt.show()
####################################################################
########################## Plot All ################################
elif allData2display == 'yes':
try: font_size
except: font_size=8
if k[0] == 'timeseries':
atr = h5file[k[0]].attrs
# rewrapping
if rewrapping in ('yes','Yes','Y','y','YES'):
print 'Rewrapping. Set min/max to -pi/pi. Showing phase.'
range2phase=4*np.pi/float(h5file['timeseries'].attrs['WAVELENGTH'])
min=-np.pi
max=np.pi
else: print 'No rewrapping. Showing displacement.'
elif k[0] in ('interferograms','coherence','wrapped'):
atr = h5file[k[0]][h5file[k[0]].keys()[0]].attrs
# rewrapping
if k[0] in ('coherence','wrapped') and rewrapping in ('yes','Yes','y','Y','YES'):
print 'No rewrapping for coherence/wrapped files, set to "no"'
rewrapping='no'
if rewrapping in ('yes','Yes','Y','y','YES'):
print 'Rewrapping. Set min/max to -pi/pi.'
min=-np.pi
max=np.pi
else: print 'No rewrapping'
### Subset Option ###
try: # y/latitude direction
win_lat
try:
atr['Y_FIRST']
win_y=[0]*2
win_y[0]=int((win_lat[1]-float(atr['Y_FIRST']))/float(atr['Y_STEP']))
win_y[1]=int((win_lat[0]-float(atr['Y_FIRST']))/float(atr['Y_STEP']))
if win_y[0]<0: win_y[0]=0; print 'input latitude > max latitude! Set to max'
print 'subset in latitude - '+str(win_lat[0])+':'+str(win_lat[1])
except: print 'Non-geocoded file, cannot use LatLon option'; Usage(); sys.exit(1)
except:
try:
win_y
print 'subset in y direction - '+str(win_y[0])+':'+str(win_y[1])
except: win_y = [0,int(atr['FILE_LENGTH'])]
try: # x/longitude direction
win_lon
try:
atr['X_FIRST']
win_x=[0]*2
win_x[0]=int((win_lon[0]-float(atr['X_FIRST']))/float(atr['X_STEP']))
win_x[1]=int((win_lon[1]-float(atr['X_FIRST']))/float(atr['X_STEP']))
if win_x[0]<0: win_x[0]=0; print 'input longitude > max longitude! Set to max'
print 'subset in longitude - '+str(win_lon[0])+':'+str(win_lon[1])
except: print 'Non-geocoded file, cannot use LatLon option'; Usage(); sys.exit(1)
except:
try:
win_x
print 'subset in x direction - '+str(win_x[0])+':'+str(win_x[1])
except: win_x = [0,int(atr['WIDTH'])]
# Figure Name
if saveFig in ('yes','Yes','Y','y','YES'):
try:
figName
figNameBase = os.path.basename(figName).split('.')[0]
figNameExt = os.path.basename(figName).split('.')[1]
except:
figNameBase = os.path.basename(File).split('.')[0]
figNameExt = '.pdf'
################## DEM Options ####################
try:
demFile
print 'Show topography'
import pysar._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)
# Subset
dem = dem[win_y[0]:win_y[1],win_x[0]:win_x[1]]
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'): #DEM basemap
print 'plot DEM as basemap'
cmap_dem=plt.get_cmap('gray')
import pysar._pysar_utilities as ut
hillshade_dem=ut.hillshade(dem,50.0)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'): #contour
print 'plot contour'
#if smoothContour in ('yes','Yes','y','Y','YES'):
import scipy.ndimage as ndimage
dem=ndimage.gaussian_filter(dem,sigma=contour_sigma,order=0)
contour_sequence=np.arange(-6000,9000,contour_step)
except: print 'No DEM file'
################## Plot Loop ####################
ifgramList=h5file[k[0]].keys()
nfigs = figs_rows*figs_cols
lifgram = len(ifgramList)
print 'number of epochs/interferograms to display:'+ str(lifgram)
kk=int(lifgram/nfigs)+1
ii=0
# plot (1,end-1) figures
for j in range(1,kk):
fig = plt.figure(j)
ii=(j-1)*nfigs+1
for i in range(ii,ii+nfigs):
print 'loading '+ifgramList[i-1]
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
# Data option
if k[0] == 'timeseries':
figTitle = ifgramList[i-1]
dset = h5file[k[0]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping in ('yes','Yes','Y','y','YES'):
data=range2phase*data
data=rewrap(data)
elif k[0] in ('interferograms','coherence','wrapped'):
figTitle = str(i)+' : '+h5file[k[0]][ifgramList[i-1]].attrs['DATE12']
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping in ('yes','Yes','Y','y','YES'):
data=np.angle(np.exp(1j*data))
data = data[win_y[0]:win_y[1],win_x[0]:win_x[1]]
# Plot
try:
demFile
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'):
plt.imshow(hillshade_dem,cmap=cmap_dem)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'):
plt.contour(dem,contour_sequence,origin='lower',colors='black',alpha=0.5)
except: pass
try: ax.imshow(data,cmap=ccmap,vmin=min,vmax=max)
except: ax.imshow(data,cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title=='out': ax.set_title(figTitle,fontsize=font_size)
elif title=='in': add_inner_title(ax, figTitle, loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
if saveFig in ('yes','Yes','Y','y','YES'):
figName=figNameBase+'_'+str(j)+figNameExt
plt.savefig(figName,dpi=fig_dpi)
# plot the last figure
fig = plt.figure(kk)
ii=(kk-1)*nfigs+1
for i in range(ii,lifgram+1):
print 'loading '+ifgramList[i-1]
ax = fig.add_subplot(figs_rows,figs_cols,i-ii+1)
# Data option
if k[0] == 'timeseries':
figTitle = ifgramList[i-1]
dset = h5file[k[0]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping in ('yes','Yes','Y','y','YES'):
data=range2phase*data
data=rewrap(data)
elif k[0] in ('interferograms','coherence','wrapped'):
figTitle = str(i)+' : '+h5file[k[0]][ifgramList[i-1]].attrs['DATE12']
dset = h5file[k[0]][ifgramList[i-1]].get(ifgramList[i-1])
data = dset[0:dset.shape[0],0:dset.shape[1]]
if rewrapping in ('yes','Yes','Y','y','YES'):
data=np.angle(np.exp(1j*data))
data = data[win_y[0]:win_y[1],win_x[0]:win_x[1]]
# Plot
try:
demFile
if dispContour in ('no','No','n','N','NO','yes','Yes','y','Y','YES'):
plt.imshow(hillshade_dem,cmap=cmap_dem)
if dispContour in ('only','Only','o','O','ONLY','yes','Yes','y','Y','YES'):
plt.contour(dem,contour_sequence,origin='lower',colors='black',alpha=0.5)
except: pass
try: ax.imshow(data,cmap=ccmap,vmin=min,vmax=max)
except: 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(figTitle,fontsize=font_size)
elif title =='in': add_inner_title(ax, figTitle, loc=1)
fig.subplots_adjust(wspace=Wspace,hspace=Hspace)
if saveFig in ('yes','Yes','Y','y','YES'):
figName=figNameBase+'_'+str(kk)+figNameExt
plt.savefig(figName,dpi=fig_dpi)
print 'Saved figure to '+figNameBase+'_*'+figNameExt
if dispFig in ('yes','Yes','Y','y','YES'):
plt.show()
####################################################################
####################################################################
try: h5file.close()
except: pass
def main(argv):
try:
file=argv[0]
alks=float(argv[1])
rlks=float(argv[2])
except:
try:
file=argv[0]
alks=float(argv[1])
rlks=float(argv[1])
except: Usage();sys.exit(1)
ext = os.path.splitext(file)[1]
outName=file.split('.')[0]+'_a'+str(int(alks))+'lks_r'+str(int(rlks))+'lks'+ext
################################################################################
if ext == '.h5':
import h5py
h5file_mli=h5py.File(outName,'w')
h5file=h5py.File(file,'r')
k=h5file.keys()
if 'interferograms' in k: k[0] = 'interferograms'
elif 'coherence' in k: k[0] = 'coherence'
elif 'timeseries' in k: k[0] = 'timeseries'
if k[0] in ['interferograms','coherence','wrapped']:
print 'Multilooking the interferograms'
gg = h5file_mli.create_group(k[0])
igramList=h5file[k[0]].keys()
for igram in igramList:
print igram
unw = h5file[k[0]][igram].get(igram)
unwlks=multilook(unw,alks,rlks)
group = gg.create_group(igram)
dset = group.create_dataset(igram, data=unwlks, compression='gzip')
for key, value in h5file[k[0]][igram].attrs.iteritems():
group.attrs[key] = value
group.attrs['WIDTH'] = unwlks.shape[1]
group.attrs['FILE_LENGTH'] = unwlks.shape[0]
try:
group.attrs['Y_STEP']=alks*float(group.attrs['Y_STEP'])
group.attrs['X_STEP']=rlks*float(group.attrs['X_STEP'])
except:
group.attrs['AZIMUTH_PIXEL_SIZE'] = alks*float(group.attrs['AZIMUTH_PIXEL_SIZE'])
group.attrs['RANGE_PIXEL_SIZE'] = rlks*float(group.attrs['RANGE_PIXEL_SIZE'])
try:
dset1=h5file['mask'].get('mask')
mask=dset1[0:dset1.shape[0],0:dset1.shape[1]]
masklks=multilook(mask,alks,rlks)
group=h5file_mli.create_group('mask')
dset = group.create_dataset('mask', data=masklks, compression='gzip')
except: print 'No mask group found.'
elif k[0] in ['timeseries','temporal_coherence', 'velocity', 'mask', 'rmse']:
print 'Multilooking '+k[0]
group = h5file_mli.create_group(k[0])
if k[0] == 'timeseries':
dateList=h5file[k[0]].keys()
for d in dateList:
print d
unw = h5file[k[0]].get(d)
unwlks=multilook(unw,alks,rlks)
dset = group.create_dataset(d, data=unwlks, compression='gzip')
elif k[0] in ['temporal_coherence', 'velocity', 'mask', 'rmse']:
dset1 = h5file[k[0]].get(k[0])
unw = dset1[0:dset1.shape[0],0:dset1.shape[1]]
unwlks=multilook(unw,alks,rlks)
dset = group.create_dataset(k[0], data=unwlks, compression='gzip')
try:
dset1 = h5file['mask'].get('mask')
Mask = dset1[0:dset1.shape[0],0:dset1.shape[1]]
Masklks=multilook(Mask,alks,rlks)
group=h5file_mli.create_group('mask')
dset = group.create_dataset('mask', data=Masklks, compression='gzip')
except: print 'No mask group found.'
## Update attributes
for key,value in h5file[k[0]].attrs.iteritems(): group.attrs[key] = value
group.attrs['WIDTH'] = unwlks.shape[1]
group.attrs['FILE_LENGTH'] = unwlks.shape[0]
try:
group.attrs['Y_STEP']=alks*float(group.attrs['Y_STEP'])
group.attrs['X_STEP']=rlks*float(group.attrs['X_STEP'])
except:
group.attrs['AZIMUTH_PIXEL_SIZE'] = alks*float(group.attrs['AZIMUTH_PIXEL_SIZE'])
group.attrs['RANGE_PIXEL_SIZE'] = rlks*float(group.attrs['RANGE_PIXEL_SIZE'])
h5file.close()
h5file_mli.close()
################################################################################
elif ext in ['.unw','.cor','.hgt','.dem','.trans'] or\
ext in ['.jpeg','.jpg','.png','.ras','.bmp'] or\
ext in ['.mli','.slc']:
import pysar._readfile as readfile
import pysar._writefile as writefile
r = readfile.read_rsc_file(file + '.rsc')
if ext == '.int' or ext == '.slc':
a,p,r = readfile.read_complex64(file)
pmli=multilook(p,alks,rlks)
amli=multilook(a,alks,rlks)
r['FILE_LENGTH']=str(pmli.shape[0])
r['WIDTH'] =str(pmli.shape[1])
elif ext == '.unw' or ext == '.cor' or ext == '.hgt':
a,p,r = readfile.read_float32(file)
pmli=multilook(p,alks,rlks)
amli=multilook(a,alks,rlks)
print 'writing >>>'+outName
writefile.write_float32(pmli,outName)
r['FILE_LENGTH']=str(pmli.shape[0])
r['WIDTH'] =str(pmli.shape[1])
elif ext == ('.dem'):
d,r = readfile.read_dem(file)
dmli=multilook(d,alks,rlks)
print 'writing >>>'+outName
writefile.write_dem(dmli,outName)
r['FILE_LENGTH']=str(dmli.shape[0])
r['WIDTH'] =str(dmli.shape[1])
elif ext in ['.jpeg','.jpg','.png','.bmp']:
import Image
im = Image.open(file)
width = im.size[0] / int(rlks)
height = im.size[1] / int(alks)
imlks = im.resize((width, height), Image.NEAREST)
print 'writing >>>'+outName
imlks.save(outName)
r['FILE_LENGTH']=str(height)
r['WIDTH'] =str(width)
## Update attributes
r['XMAX']=str(int(r['WIDTH']) - 1)
r['YMAX']=str(int(r['FILE_LENGTH']) - 1)
try:
r['Y_STEP']=str(float(r['Y_STEP'])*alks)
r['X_STEP']=str(float(r['X_STEP'])*rlks)
except:
r['AZIMUTH_PIXEL_SIZE'] = alks*float(r['AZIMUTH_PIXEL_SIZE'])
r['RANGE_PIXEL_SIZE'] = rlks*float(r['RANGE_PIXEL_SIZE'])
f = open(outName+'.rsc','w')
for k in r.keys():
f.write(k+' '+r[k]+'\n')
f.close()
def main(argv):
################# default values ################
flip_lr = 'no'
flip_ud = 'no'
disp_geo = 'yes'
#font_size=8
color_map = 'jet'
figs_rows = 5
figs_cols = 8
rewrapping = 'yes'
allData2display = 'yes'
Wspace = 0.1
Hspace = 0.1
title = 'out'
showRef = 'yes'
ref_color = 'k'
ref_symbol = 's'
ref_size = 10
dip_opposite = 'no'
saveFig = 'no'
dispFig = 'yes'
dispContour = 'only'
contour_step = 200
contour_sigma = 3.0
fig_dpi = 300
################### get input args ###############
if len(sys.argv) > 2:
try:
opts, args = getopt.getopt(
argv,
"h:D:O:G:S:f:m:M:v:u:s:c:e:d:r:p:w:i:j:t:R:a:b:k:x:y:C:V:P:o:g:l:L:"
)
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 == '-w':
rewrapping = arg
elif opt == '-m':
min = float(arg)
rewrapping = 'no'
elif opt == '-M':
max = float(arg)
rewrapping = 'no'
elif opt == '-v':
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 == '-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 = [int(i) for i in arg.split(':')]
win_x.sort()
elif opt == '-y':
win_y = [int(i) for i in arg.split(':')]
win_y.sort()
elif opt == '-G':
disp_geo = arg
elif opt == '-O':
dip_opposite = arg
elif opt == '-S':
saveFig = arg
elif opt == '-C':
dispContour = arg
elif opt == '-V':
contour_step = float(arg)
elif opt == '-P':
dispFig = arg
elif opt == '-o':
figName = arg
elif opt == '-g':
contour_sigma = float(arg)
elif opt == '-l':
win_lat = [float(i) for i in arg.split(':')]
win_lat.sort()
elif opt == '-L':
win_lon = [float(i) for i in arg.split(':')]
win_lon.sort()
elif len(sys.argv) == 2:
if argv[0] == '-h':
Usage()
sys.exit(1)
elif os.path.isfile(argv[0]):
File = argv[0]
else:
print 'Input file does not existed: ' + argv[0]
sys.exit(1)
elif len(sys.argv) < 2:
Usage()
sys.exit(1)
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),
)
}
from matplotlib.colors import LinearSegmentedColormap
ccmap = LinearSegmentedColormap('BlueRed1', cdict1)
################################################
else:
ccmap = plt.get_cmap(color_map)
##################################################
ext = os.path.splitext(File)[1]
if ext == '.h5':
import h5py
h5file = h5py.File(File, 'r')
k = h5file.keys()
if 'interferograms' in k: k[0] = 'interferograms'
elif 'coherence' in k: k[0] = 'coherence'
elif 'timeseries' in k: k[0] = 'timeseries'
print 'Input: ' + str(k)
if k[0] in ('dem', 'velocity', 'mask', 'temporal_coherence', 'rmse'):
allData2display = 'no'
elif ext in [
'.unw', '.int', '.cor', '.hgt', '.dem', '.trans', '.mli', '.slc'
]:
import pysar._readfile as readfile
allData2display = 'no'
k = [ext]
else:
print 'File extension not recogized: ' + ext
print 'Support file format:\n\
PySAR HDF5 files: velocity.h5, timeseries.h5, LoadedData.h5, ...\n\
ROI_PAC files: .unw .cor .int .hgt .dem .trans .mli'
sys.exit(1)
####################################################################
########################## Plot One ################################
if allData2display == 'no':
try:
font_size
except:
font_size = 12
################# File Reading ##################
##### PySAR HDF5
if k[0] in ('dem', 'velocity', 'mask', 'temporal_coherence', 'rmse'):
atr = h5file[k[0]].attrs
dset = h5file[k[0]].get(k[0])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
# rewrapping
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
print 'Rewrapping disabled for ' + k[0]
elif k[0] == 'timeseries':
dateList = h5file[k[0]].keys()
try:
epoch_number
except:
try:
epoch_date
if len(epoch_date) == 6:
epoch_date = yymmdd2yyyymmdd(epoch_date)
epoch_number = dateList.index(epoch_date)
except:
print 'Unrecognized epoch input!'
sys.exit(1)
print 'Displaying date: ' + dateList[epoch_number]
atr = h5file[k[0]].attrs
dset = h5file[k[0]].get(dateList[epoch_number])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
# rewrapping
if rewrapping in ('yes', 'Yes', 'y', 'Y', 'YES'):
print 'Rewrapping. Set min/max to -pi/pi. Showing phase'
range2phase = 4 * np.pi / float(
atr['WAVELENGTH']) #double-way, 2*2*pi/lamda
data = range2phase * data
data = rewrap(data)
min = -np.pi
max = np.pi
figUnit = '(radian)'
elif rewrapping in ('no', 'No', 'N', 'n', 'NO'):
print 'No rewrapping. Showing displacement.'
figUnit = '(m)'
elif k[0] in ('interferograms', 'coherence', 'wrapped'):
ifgramList = h5file[k[0]].keys()
try:
epoch_number
except:
for i in range(len(ifgramList)):
if epoch_date in ifgramList[i]: epoch_number = i
print 'Displaying: ' + ifgramList[epoch_number]
atr = h5file[k[0]][ifgramList[epoch_number]].attrs
dset = h5file[k[0]][ifgramList[epoch_number]].get(
ifgramList[epoch_number])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
# rewrapping
if k[0] in ('coherence',
'wrapped') and rewrapping in ('yes', 'Yes', 'y', 'Y',
'YES'):
print 'No rewrapping for coherence/wrapped files, set to "no"'
rewrapping = 'no'
if rewrapping in ('yes', 'Yes', 'y', 'Y', 'YES'):
print 'Rewrapping. Set min/max to -pi/pi.'
data = np.angle(np.exp(1j * data))
min = -np.pi
max = np.pi
##### ROI_PAC product
elif k[0] in ['.slc', '.mli']:
data, p, atr = readfile.read_complex64(File)
data = np.nanlog10(data)
figUnit = '(dB)'
elif k[0] == '.int':
a, data, atr = readfile.read_complex64(File)
min = -np.pi
max = np.pi
rewrapping = 'no'
figUnit = '(radian)'
elif k[0] in ['.unw', '.cor', '.hgt', '.trans']:
a, data, atr = readfile.read_float32(File)
if k[0] == '.unw': figUnit = '(radian)'
elif k[0] == '.hgt': figUnit = '(m)'
if k[0] in ['.cor', '.hgt', '.trans']: rewrapping = 'no'
if rewrapping in ('yes', 'Yes', 'y', 'Y', 'True', 'true'):
print 'Rewrapping. Set min/max to -pi/pi.'
data = rewrap(data)
min = -np.pi
max = np.pi
elif k[0] == '.dem':
data, atr = readfile.read_dem(File)
figUnit = '(m)'
############## Data Option ##################
# Opposite Sign
if dip_opposite in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = -1 * data
# Subset
try: # y/latitude direction
win_lat
try:
atr['Y_FIRST']
win_y = [0] * 2
win_y[0] = int((win_lat[1] - float(atr['Y_FIRST'])) /
float(atr['Y_STEP']))
win_y[1] = int((win_lat[0] - float(atr['Y_FIRST'])) /
float(atr['Y_STEP']))
if win_y[0] < 0:
win_y[0] = 0
print 'input latitude > max latitude! Set to max'
print 'subset in latitude - ' + str(win_lat[0]) + ':' + str(
win_lat[1])
except:
print 'Non-geocoded file, cannot use LatLon option'
Usage()
sys.exit(1)
except:
try:
win_y
print 'subset in y direction - ' + str(win_y[0]) + ':' + str(
win_y[1])
except:
win_y = [0, int(atr['FILE_LENGTH'])]
try: # x/longitude direction
win_lon
try:
atr['X_FIRST']
win_x = [0] * 2
win_x[0] = int((win_lon[0] - float(atr['X_FIRST'])) /
float(atr['X_STEP']))
win_x[1] = int((win_lon[1] - float(atr['X_FIRST'])) /
float(atr['X_STEP']))
if win_x[0] < 0:
win_x[0] = 0
print 'input longitude > max longitude! Set to max'
print 'subset in longitude - ' + str(win_lon[0]) + ':' + str(
win_lon[1])
except:
print 'Non-geocoded file, cannot use LatLon option'
Usage()
sys.exit(1)
except:
try:
win_x
print 'subset in x direction - ' + str(win_x[0]) + ':' + str(
win_x[1])
except:
win_x = [0, int(atr['WIDTH'])]
data = data[win_y[0]:win_y[1], win_x[0]:win_x[1]]
# Reference Point
try:
xref = atr['ref_x'] - win_x[0]
yref = atr['ref_y'] - win_y[0]
except:
print 'No reference point'
try:
xref = xref - atr['subset_x0']
yref = yref - atr['subset_y0']
except:
print 'No subset'
# Geo coordinate
try:
lon_step = float(atr['X_STEP'])
lat_step = float(atr['Y_STEP'])
lon_unit = atr['Y_UNIT']
lat_unit = atr['X_UNIT']
ullon = float(atr['X_FIRST']) + win_x[0] * lon_step
ullat = float(atr['Y_FIRST']) + win_y[0] * lat_step
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'
# Flip
if flip_lr in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = np.fliplr(data)
xref = np.shape(data)[1] - xref - 1
if flip_ud in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = np.flipud(data)
yref = np.shape(data)[0] - yref - 1
# Colorbar Extend
data_min = np.nanmin(data)
data_max = np.nanmax(data)
try:
min
except:
min = data_min
try:
max
except:
max = data_max
if min <= data_min and max >= data_max: cb_extend = 'neither'
elif min > data_min and max >= data_max: cb_extend = 'min'
elif min <= data_min and max < data_max: cb_extend = 'max'
else: cb_extend = 'both'
############## DEM Option ##################
try:
demFile
print 'Show topography'
import pysar._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)
# Subset
dem = dem[win_y[0]:win_y[1], win_x[0]:win_x[1]]
# Flip
if flip_lr in ('yes', 'Yes', 'Y', 'y', 'YES'): dem = np.fliplr(dem)
if flip_ud in ('yes', 'Yes', 'Y', 'y', 'YES'): dem = np.flipud(dem)
# DEM data preparation
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes', 'Yes', 'y',
'Y', 'YES'): #DEM basemap
print 'plot DEM as basemap'
cmap_dem = plt.get_cmap('gray')
import pysar._pysar_utilities as ut
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes', 'Yes',
'y', 'Y', 'YES'): #contour
print 'plot contour'
#if smoothContour in ('yes','Yes','y','Y','YES'):
import scipy.ndimage as ndimage
dem = ndimage.gaussian_filter(dem,
sigma=contour_sigma,
order=0)
contour_sequence = np.arange(-6000, 9000, contour_step)
except:
print 'No DEM file'
############## Data Plot and Output ################
# Figure Title
if k[0] == 'velocity': figTitle = 'Velocity (m/yr)'
elif k[0] == 'temporal_coherence': figTitle = 'Temporal coherence'
elif k[0] == 'dem': figTitle = 'DEM error'
elif k[0] == 'rmse': figTitle = 'RMSE (m/yr)'
elif k[0] == 'mask': figTitle = 'Pixels with no valid value.'
elif k[0] == 'coherence': figTitle = ifgramList[epoch_number]
elif k[0] in ('interferograms', 'wrapped'):
figTitle = ifgramList[epoch_number] + ' (radian)'
elif k[0] == 'timeseries':
try:
master_date = atr['ref_date']
except:
master_date = atr['DATE']
if len(master_date) == 6:
master_date = yymmdd2yyyymmdd(master_date)
if dip_opposite in ('yes', 'Yes', 'Y', 'y', 'YES'):
figTitle = dateList[
epoch_number] + '_' + master_date + ' ' + figUnit
else:
figTitle = master_date + '_' + dateList[
epoch_number] + ' ' + figUnit
elif k[0] in [
'.unw', '.cor', '.hgt', '.dem', '.trans', '.mli', '.slc'
]:
try:
figTitle = File + ' ' + figUnit
except:
figTitle = File
# Plot in Geo-coordinate: plot in map
if geocoord == 'yes' and disp_geo in ('yes', 'Yes', 'y', 'Y', 'YES'):
print 'display Lat/Lon'
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
try:
plt.title(figTitle, fontsize=font_size)
except:
pass
# Map - DEM - Data
from mpl_toolkits.basemap import Basemap
m = Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
area_thresh=1.,
projection='cyl',
suppress_ticks=False,
ax=ax)
try:
demFile
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes', 'Yes',
'y', 'Y', 'YES'):
m.imshow(ut.hillshade(np.flipud(dem), 50.0), cmap=cmap_dem)
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes',
'Yes', 'y', 'Y', 'YES'):
import numpy.matlib
c_x = np.linspace(llcrnrlon,
urcrnrlon,
num=dem.shape[1],
endpoint='FALSE').reshape(
1, dem.shape[1])
c_xx = np.matlib.repmat(c_x, dem.shape[0], 1)
c_y = np.linspace(llcrnrlat,
urcrnrlat,
num=dem.shape[0],
endpoint='FALSE').reshape(
dem.shape[0], 1)
c_yy = np.matlib.repmat(c_y, 1, dem.shape[1])
m.contour(c_xx,
c_yy,
np.flipud(dem),
contour_sequence,
origin='lower',
colors='black',
alpha=0.5,
latlon='FALSE')
except:
pass
try:
im = m.imshow(np.flipud(data), cmap=ccmap, vmin=min, vmax=max)
except:
im = m.imshow(np.flipud(data), cmap=ccmap)
# Reference Point
if showRef in ('yes', 'Yes', 'Y', 'y', 'YES'):
try:
refPoint = ref_color + ref_symbol
ref_lon = llcrnrlon + xref * lon_step
ref_lat = urcrnrlat + yref * lat_step
plt.plot(ref_lon, ref_lat, refPoint, ms=ref_size)
except:
print 'No reference point'
# Colorbar
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.30)
plt.colorbar(im, cax=cax, extend=cb_extend)
#plt.colorbar(im,cax=cax)
# Status bar
def format_coord(x, y):
col = int((x - ullon) / lon_step + 0.5)
row = int((y - ullat) / lat_step + 0.5)
if col >= 0 and col <= data.shape[
1] and row >= 0 and row <= data.shape[0]:
z = data[row, col]
return 'lat=%.4f, lon=%.4f, value=%.4f' % (x, y, z)
else:
return 'lat=%.4f, lon=%.4f' % (x, y)
ax.format_coord = format_coord
# Plot in x/y coordinate: row and column
else:
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
try:
plt.title(figTitle, fontsize=font_size)
except:
pass
# Plot
try:
demFile
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes', 'Yes',
'y', 'Y', 'YES'):
ax.imshow(ut.hillshade(dem, 50.0), cmap=cmap_dem)
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes',
'Yes', 'y', 'Y', 'YES'):
ax.contour(dem,
contour_sequence,
origin='lower',
colors='black',
alpha=0.5)
except:
pass
try:
im = ax.imshow(data, cmap=ccmap, vmin=min, vmax=max)
except:
im = ax.imshow(data, cmap=ccmap)
cbar = plt.colorbar(im, extend=cb_extend)
#cbar.set_label('m/yr')
# Reference Point
if showRef in ('yes', 'Yes', 'Y', 'y', 'YES'):
try:
refPoint = ref_color + ref_symbol
ax.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)
# Status bar
def format_coord(x, y):
col = int(x + 0.5)
row = int(y + 0.5)
if col >= 0 and col <= data.shape[
1] and row >= 0 and row <= data.shape[0]:
z = data[row, col]
return 'x=%.4f, y=%.4f, value=%.4f' % (x, y, z)
else:
return 'x=%.4f, y=%.4f' % (x, y)
ax.format_coord = format_coord
# Save Figure
if saveFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
try:
figName
except:
if k[0] == 'velocity': figName = 'velocity.pdf'
elif k[0] == 'temporal_coherence':
figName = 'temporal_coherence.pdf'
elif k[0] == 'dem':
figName = 'DEM_error.pdf'
elif k[0] == 'rmse':
figName = 'rmse.pdf'
elif k[0] == 'mask':
figName = 'mask.pdf'
elif k[0] == 'timeseries':
figName = os.path.basename(File).split(
'.')[0] + '_' + dateList[epoch_number] + '.pdf'
elif k[0] in ('interferograms', 'coherence', 'wrapped'):
figName = ifgramList[epoch_number] + '.pdf'
elif k[0] in [
'.unw', '.cor', '.hgt', '.dem', '.trans', '.mli',
'.slc'
]:
figName = File + '.pdf'
plt.savefig(figName, dpi=fig_dpi)
print 'Saved figure to ' + figName
# Show Figure
if dispFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
plt.show()
####################################################################
########################## Plot All ################################
elif allData2display == 'yes':
try:
font_size
except:
font_size = 8
if k[0] == 'timeseries':
atr = h5file[k[0]].attrs
# rewrapping
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
print 'Rewrapping. Set min/max to -pi/pi. Showing phase.'
range2phase = 4 * np.pi / float(
h5file['timeseries'].attrs['WAVELENGTH'])
min = -np.pi
max = np.pi
else:
print 'No rewrapping. Showing displacement.'
elif k[0] in ('interferograms', 'coherence', 'wrapped'):
atr = h5file[k[0]][h5file[k[0]].keys()[0]].attrs
# rewrapping
if k[0] in ('coherence',
'wrapped') and rewrapping in ('yes', 'Yes', 'y', 'Y',
'YES'):
print 'No rewrapping for coherence/wrapped files, set to "no"'
rewrapping = 'no'
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
print 'Rewrapping. Set min/max to -pi/pi.'
min = -np.pi
max = np.pi
else:
print 'No rewrapping'
### Subset Option ###
try: # y/latitude direction
win_lat
try:
atr['Y_FIRST']
win_y = [0] * 2
win_y[0] = int((win_lat[1] - float(atr['Y_FIRST'])) /
float(atr['Y_STEP']))
win_y[1] = int((win_lat[0] - float(atr['Y_FIRST'])) /
float(atr['Y_STEP']))
if win_y[0] < 0:
win_y[0] = 0
print 'input latitude > max latitude! Set to max'
print 'subset in latitude - ' + str(win_lat[0]) + ':' + str(
win_lat[1])
except:
print 'Non-geocoded file, cannot use LatLon option'
Usage()
sys.exit(1)
except:
try:
win_y
print 'subset in y direction - ' + str(win_y[0]) + ':' + str(
win_y[1])
except:
win_y = [0, int(atr['FILE_LENGTH'])]
try: # x/longitude direction
win_lon
try:
atr['X_FIRST']
win_x = [0] * 2
win_x[0] = int((win_lon[0] - float(atr['X_FIRST'])) /
float(atr['X_STEP']))
win_x[1] = int((win_lon[1] - float(atr['X_FIRST'])) /
float(atr['X_STEP']))
if win_x[0] < 0:
win_x[0] = 0
print 'input longitude > max longitude! Set to max'
print 'subset in longitude - ' + str(win_lon[0]) + ':' + str(
win_lon[1])
except:
print 'Non-geocoded file, cannot use LatLon option'
Usage()
sys.exit(1)
except:
try:
win_x
print 'subset in x direction - ' + str(win_x[0]) + ':' + str(
win_x[1])
except:
win_x = [0, int(atr['WIDTH'])]
# Figure Name
if saveFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
try:
figName
figNameBase = os.path.basename(figName).split('.')[0]
figNameExt = os.path.basename(figName).split('.')[1]
except:
figNameBase = os.path.basename(File).split('.')[0]
figNameExt = '.pdf'
################## DEM Options ####################
try:
demFile
print 'Show topography'
import pysar._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)
# Subset
dem = dem[win_y[0]:win_y[1], win_x[0]:win_x[1]]
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes', 'Yes', 'y',
'Y', 'YES'): #DEM basemap
print 'plot DEM as basemap'
cmap_dem = plt.get_cmap('gray')
import pysar._pysar_utilities as ut
hillshade_dem = ut.hillshade(dem, 50.0)
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes', 'Yes',
'y', 'Y', 'YES'): #contour
print 'plot contour'
#if smoothContour in ('yes','Yes','y','Y','YES'):
import scipy.ndimage as ndimage
dem = ndimage.gaussian_filter(dem,
sigma=contour_sigma,
order=0)
contour_sequence = np.arange(-6000, 9000, contour_step)
except:
print 'No DEM file'
################## Plot Loop ####################
ifgramList = h5file[k[0]].keys()
nfigs = figs_rows * figs_cols
lifgram = len(ifgramList)
print 'number of epochs/interferograms to display:' + str(lifgram)
kk = int(lifgram / nfigs) + 1
ii = 0
# plot (1,end-1) figures
for j in range(1, kk):
fig = plt.figure(j)
ii = (j - 1) * nfigs + 1
for i in range(ii, ii + nfigs):
print 'loading ' + ifgramList[i - 1]
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
# Data option
if k[0] == 'timeseries':
figTitle = ifgramList[i - 1]
dset = h5file[k[0]].get(ifgramList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = range2phase * data
data = rewrap(data)
elif k[0] in ('interferograms', 'coherence', 'wrapped'):
figTitle = str(i) + ' : ' + h5file[k[0]][ifgramList[
i - 1]].attrs['DATE12']
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i -
1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = np.angle(np.exp(1j * data))
data = data[win_y[0]:win_y[1], win_x[0]:win_x[1]]
# Plot
try:
demFile
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes',
'Yes', 'y', 'Y', 'YES'):
plt.imshow(hillshade_dem, cmap=cmap_dem)
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes',
'Yes', 'y', 'Y', 'YES'):
plt.contour(dem,
contour_sequence,
origin='lower',
colors='black',
alpha=0.5)
except:
pass
try:
ax.imshow(data, cmap=ccmap, vmin=min, vmax=max)
except:
ax.imshow(data, cmap=ccmap)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_xticks([])
ax.set_yticks([])
if title == 'out': ax.set_title(figTitle, fontsize=font_size)
elif title == 'in': add_inner_title(ax, figTitle, loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
if saveFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
figName = figNameBase + '_' + str(j) + figNameExt
plt.savefig(figName, dpi=fig_dpi)
# plot the last figure
fig = plt.figure(kk)
ii = (kk - 1) * nfigs + 1
for i in range(ii, lifgram + 1):
print 'loading ' + ifgramList[i - 1]
ax = fig.add_subplot(figs_rows, figs_cols, i - ii + 1)
# Data option
if k[0] == 'timeseries':
figTitle = ifgramList[i - 1]
dset = h5file[k[0]].get(ifgramList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = range2phase * data
data = rewrap(data)
elif k[0] in ('interferograms', 'coherence', 'wrapped'):
figTitle = str(i) + ' : ' + h5file[k[0]][ifgramList[
i - 1]].attrs['DATE12']
dset = h5file[k[0]][ifgramList[i - 1]].get(ifgramList[i - 1])
data = dset[0:dset.shape[0], 0:dset.shape[1]]
if rewrapping in ('yes', 'Yes', 'Y', 'y', 'YES'):
data = np.angle(np.exp(1j * data))
data = data[win_y[0]:win_y[1], win_x[0]:win_x[1]]
# Plot
try:
demFile
if dispContour in ('no', 'No', 'n', 'N', 'NO', 'yes', 'Yes',
'y', 'Y', 'YES'):
plt.imshow(hillshade_dem, cmap=cmap_dem)
if dispContour in ('only', 'Only', 'o', 'O', 'ONLY', 'yes',
'Yes', 'y', 'Y', 'YES'):
plt.contour(dem,
contour_sequence,
origin='lower',
colors='black',
alpha=0.5)
except:
pass
try:
ax.imshow(data, cmap=ccmap, vmin=min, vmax=max)
except:
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(figTitle, fontsize=font_size)
elif title == 'in': add_inner_title(ax, figTitle, loc=1)
fig.subplots_adjust(wspace=Wspace, hspace=Hspace)
if saveFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
figName = figNameBase + '_' + str(kk) + figNameExt
plt.savefig(figName, dpi=fig_dpi)
print 'Saved figure to ' + figNameBase + '_*' + figNameExt
if dispFig in ('yes', 'Yes', 'Y', 'y', 'YES'):
plt.show()
####################################################################
####################################################################
try:
h5file.close()
except:
pass
