def make_sb_matrix2(ifgdates):
"""
Make small baseline incidence-like matrix.
Composed of -1 at primary and 1 at secondary. (n_ifg, n_im)
Unknown is cumulative displacement.
"""
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_im = len(imdates)
n_ifg = len(ifgdates)
A = np.zeros((n_ifg, n_im), dtype=np.int16)
for ifgix, ifgd in enumerate(ifgdates):
primarydate = ifgd[:8]
primaryix = imdates.index(primarydate)
secondarydate = ifgd[-8:]
secondaryix = imdates.index(secondarydate)
A[ifgix, primaryix] = -1
A[ifgix, secondaryix] = 1
return A
def make_sb_matrix2(ifgdates):
"""
Make small baseline incidence-like matrix.
Composed of -1 at master and 1 at slave. (n_ifg, n_im)
Unknown is cumulative displacement.
"""
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_im = len(imdates)
n_ifg = len(ifgdates)
A = np.zeros((n_ifg, n_im), dtype=np.int16)
for ifgix, ifgd in enumerate(ifgdates):
masterdate = ifgd[:8]
masterix = imdates.index(masterdate)
slavedate = ifgd[-8:]
slaveix = imdates.index(slavedate)
A[ifgix, masterix] = -1
A[ifgix, slaveix] = 1
return A
def make_sb_matrix(ifgdates):
"""
Make small baseline incidence-like matrix.
Composed of 1 between primary and secondary. (n_ifg, n_im-1)
Unknown is incremental displacement.
"""
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_im = len(imdates)
n_ifg = len(ifgdates)
G = np.zeros((n_ifg, n_im - 1), dtype=np.int16)
for ifgix, ifgd in enumerate(ifgdates):
primarydate = ifgd[:8]
primaryix = imdates.index(primarydate)
secondarydate = ifgd[-8:]
secondaryix = imdates.index(secondarydate)
G[ifgix, primaryix:secondaryix] = 1
return G
def make_sb_matrix(ifgdates):
"""
Make small baseline incidence-like matrix.
Composed of 1 between master and slave. (n_ifg, n_im-1)
Unknown is incremental displacement.
"""
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_im = len(imdates)
n_ifg = len(ifgdates)
G = np.zeros((n_ifg, n_im - 1), dtype=np.int16)
for ifgix, ifgd in enumerate(ifgdates):
masterdate = ifgd[:8]
masterix = imdates.index(masterdate)
slavedate = ifgd[-8:]
slaveix = imdates.index(slavedate)
G[ifgix, masterix:slaveix] = 1
return G
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver=1.2; date=20200228; author="Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date, author), flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])), flush=True)
#%% Set default
in_dir = []
out_dir = []
gacosdir = 'GACOS'
resampleAlg = 'cubicspline'# None # 'cubic'
fillholeflag = False
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hi:o:g:z:", ["fillhole", "help"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-i':
in_dir = a
elif o == '-o':
out_dir = a
elif o == '-z': ## for backward-compatible
gacosdir = a
elif o == '-g':
gacosdir = a
elif o == "--fillhole":
fillholeflag = True
if not in_dir:
raise Usage('No input directory given, -i is not optional!')
elif not os.path.isdir(in_dir):
raise Usage('No {} dir exists!'.format(in_dir))
elif not os.path.exists(os.path.join(in_dir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(in_dir))
if not out_dir:
raise Usage('No output directory given, -o is not optional!')
if not os.path.isdir(gacosdir):
raise Usage('No {} dir exists!'.format(gacosdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" "+str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Read data information
### Directory
in_dir = os.path.abspath(in_dir)
gacosdir = os.path.abspath(gacosdir)
out_dir = os.path.abspath(out_dir)
if not os.path.exists(out_dir): os.mkdir(out_dir)
sltddir = os.path.join(os.path.join(out_dir),'sltd')
if not os.path.exists(sltddir): os.mkdir(sltddir)
### Get general info
mlipar = os.path.join(in_dir, 'slc.mli.par')
width_unw = int(io_lib.get_param_par(mlipar, 'range_samples'))
length_unw = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
speed_of_light = 299792458 #m/s
radar_frequency = float(io_lib.get_param_par(mlipar, 'radar_frequency')) #Hz
wavelength = speed_of_light/radar_frequency #meter
m2r_coef = 4*np.pi/wavelength
if wavelength > 0.2: ## L-band
cycle = 1.5 # 2pi/cycle for png
else: ## C-band
cycle = 3 # 2pi*3/cycle for png
### Get geo info. Grid registration
dempar = os.path.join(in_dir, 'EQA.dem_par')
width_geo = int(io_lib.get_param_par(dempar, 'width'))
length_geo = int(io_lib.get_param_par(dempar, 'nlines'))
dlat_geo = float(io_lib.get_param_par(dempar, 'post_lat')) #minus
dlon_geo = float(io_lib.get_param_par(dempar, 'post_lon'))
latn_geo = float(io_lib.get_param_par(dempar, 'corner_lat'))
lonw_geo = float(io_lib.get_param_par(dempar, 'corner_lon'))
lats_geo = latn_geo+dlat_geo*(length_geo-1)
lone_geo = lonw_geo+dlon_geo*(width_geo-1)
### Check coordinate
if width_unw!=width_geo or length_unw!=length_geo:
print('\n{} seems to contain files in radar coordinate!!\n'.format(in_dir), file=sys.stderr)
print('Not supported.\n'.format(in_dir), file=sys.stderr)
return 1
### Calc incidence angle from U.geo
ufile = os.path.join(in_dir, 'U.geo')
LOSu = io_lib.read_img(ufile, length_geo, width_geo)
LOSu[LOSu==0] = np.nan
### Get ifgdates and imdates
ifgdates = tools_lib.get_ifgdates(in_dir)
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_im = len(imdates)
#%% Process ztd files
print('\nConvert ztd/sltd.geo.tif files to sltd.geo files...', flush=True)
### First check if sltd already exist
imdates2 = []
for imd in imdates:
sltd_geofile = os.path.join(sltddir, imd+'.sltd.geo')
if not os.path.exists(sltd_geofile):
imdates2.append(imd)
n_im2 = len(imdates2)
if n_im-n_im2 > 0:
print(" {0:3}/{1:3} sltd already exist. Skip".format(n_im-n_im2, n_im), flush=True)
no_gacos_imfile = os.path.join(out_dir, 'no_gacos_im.txt')
if os.path.exists(no_gacos_imfile): os.remove(no_gacos_imfile)
for ix_im, imd in enumerate(imdates2):
if np.mod(ix_im, 10)==0:
print(' Finished {0:4}/{1:4}th sltd...'.format(ix_im, n_im2), flush=True)
ztdfile = os.path.join(gacosdir, imd+'.ztd')
sltdtiffile = os.path.join(gacosdir, imd+'.sltd.geo.tif')
if os.path.exists(sltdtiffile):
infile = os.path.basename(sltdtiffile)
try: ### Cut and resapmle. Already in rad.
sltd_geo = gdal.Warp("", sltdtiffile, format='MEM', outputBounds=(lonw_geo, lats_geo, lone_geo, latn_geo), width=width_geo, height=length_geo, resampleAlg=resampleAlg, srcNodata=0).ReadAsArray()
except: ## if broken
print (' {} cannot open. Skip'.format(infile), flush=True)
with open(no_gacos_imfile, mode='a') as fnogacos:
print('{}'.format(imd), file=fnogacos)
continue
elif os.path.exists(ztdfile):
infile = os.path.basename(ztdfile)
hdrfile = os.path.join(sltddir, imd+'.hdr')
bilfile = os.path.join(sltddir, imd+'.bil')
if os.path.exists(hdrfile): os.remove(hdrfile)
if os.path.exists(bilfile): os.remove(bilfile)
make_hdr(ztdfile+'.rsc', hdrfile)
os.symlink(os.path.relpath(ztdfile, sltddir), bilfile)
### Cut and resapmle ztd to geo
ztd_geo = gdal.Warp("", bilfile, format='MEM', outputBounds=(lonw_geo, lats_geo, lone_geo, latn_geo), width=width_geo, height=length_geo, resampleAlg=resampleAlg, srcNodata=0).ReadAsArray()
os.remove(hdrfile)
os.remove(bilfile)
### Meter to rad, slantrange
sltd_geo = ztd_geo/LOSu*m2r_coef ## LOSu=cos(inc)
else:
print(' There is no ztd|sltd.geo.tif for {}!'.format(imd), flush=True)
with open(no_gacos_imfile, mode='a') as fnogacos:
print('{}'.format(imd), file=fnogacos)
continue ## Next imd
### Skip if no data in the area
if np.all((sltd_geo==0)|np.isnan(sltd_geo)):
print(' There is no valid data in {}!'.format(infile), flush=True)
with open(no_gacos_imfile, mode='a') as fnogacos:
print('{}'.format(imd), file=fnogacos)
continue ## Next imd
### Fill hole is specified
if fillholeflag:
sltd_geo = fillhole(sltd_geo)
### Output as sltd.geo
sltd_geofile = os.path.join(sltddir, imd+'.sltd.geo')
sltd_geo.tofile(sltd_geofile)
#%% Correct unw files
print('\nCorrect unw data...', flush=True)
### Information files
gacinfofile = os.path.join(out_dir, 'GACOS_info.txt')
if not os.path.exists(gacinfofile):
### Add header
with open(gacinfofile, "w") as f:
print(' Phase STD (rad) Before After ReductionRate', file=f)
no_gacos_ifgfile = os.path.join(out_dir, 'no_gacos_ifg.txt')
if os.path.exists(no_gacos_ifgfile): os.remove(no_gacos_ifgfile)
### First check if already corrected unw exist
ifgdates2 = []
for i, ifgd in enumerate(ifgdates):
out_dir1 = os.path.join(out_dir, ifgd)
unw_corfile = os.path.join(out_dir1, ifgd+'.unw')
if not os.path.exists(unw_corfile):
ifgdates2.append(ifgd)
n_ifg2 = len(ifgdates2)
if n_ifg-n_ifg2 > 0:
print(" {0:3}/{1:3} corrected unw already exist. Skip".format(n_ifg-n_ifg2, n_ifg), flush=True)
### Correct
for i, ifgd in enumerate(ifgdates2):
if np.mod(i, 10)==0:
print(' Finished {0:4}/{1:4}th unw...'.format(i, n_ifg2), flush=True)
md = ifgd[:8]
sd = ifgd[-8:]
msltdfile = os.path.join(sltddir, md+'.sltd.geo')
ssltdfile = os.path.join(sltddir, sd+'.sltd.geo')
in_dir1 = os.path.join(in_dir, ifgd)
out_dir1 = os.path.join(out_dir, ifgd)
### Check if sltd available for both master and slave. If not continue
## Not use in tsa because loop cannot be closed
if not (os.path.exists(msltdfile) and os.path.exists(ssltdfile)):
print(' ztd file not available for {}'.format(ifgd), flush=True)
with open(no_gacos_ifgfile, mode='a') as fnogacos:
print('{}'.format(ifgd), file=fnogacos)
continue
### Prepare directory and file
if not os.path.exists(out_dir1): os.mkdir(out_dir1)
unwfile = os.path.join(in_dir1, ifgd+'.unw')
unw_corfile = os.path.join(out_dir1, ifgd+'.unw')
### Calculate dsltd
msltd = io_lib.read_img(msltdfile, length_unw, width_unw)
ssltd = io_lib.read_img(ssltdfile, length_unw, width_unw)
msltd[msltd==0] = np.nan
ssltd[ssltd==0] = np.nan
dsltd = ssltd-msltd
### Correct unw
unw = io_lib.read_img(unwfile, length_unw, width_unw)
unw[unw==0] = np.nan
unw_cor = unw-dsltd
unw_cor.tofile(unw_corfile)
### Output std
std_unw = np.nanstd(unw)
std_unwcor = np.nanstd(unw_cor)
rate = (std_unw-std_unwcor)/std_unw*100
with open(gacinfofile, "a") as f:
print('{0} {1:4.1f} {2:4.1f} {3:5.1f}%'.format(ifgd, std_unw, std_unwcor, rate), file=f)
### Link cc
if not os.path.exists(os.path.join(out_dir1, ifgd+'.cc')):
os.symlink(os.path.relpath(os.path.join(in_dir1, ifgd+'.cc'), out_dir1), os.path.join(out_dir1, ifgd+'.cc'))
### Output png for comparison
data3 = [np.angle(np.exp(1j*(data/cycle))*cycle) for data in [unw, unw_cor, dsltd]]
title3 = ['unw_org (STD: {:.1f} rad)'.format(std_unw), 'unw_cor (STD: {:.1f} rad)'.format(std_unwcor), 'dsltd ({:.1f}% reduced)'.format(rate)]
pngfile = os.path.join(out_dir1, ifgd+'.gacos.png')
plot_lib.make_3im_png(data3, pngfile, 'insar', title3, vmin=-np.pi, vmax=np.pi, cbar=False)
## Output png for corrected unw
pngfile = os.path.join(out_dir1, ifgd+'.unw.png')
title = '{} ({}pi/cycle)'.format(ifgd, cycle*2)
plot_lib.make_im_png(np.angle(np.exp(1j*unw_cor/cycle)*cycle), pngfile, 'insar', title, -np.pi, np.pi, cbar=False)
print("", flush=True)
#%% Create correlation png
pngfile = os.path.join(out_dir, 'GACOS_info.png')
plot_lib.plot_gacos_info(gacinfofile, pngfile)
#%% Copy other files
files = glob.glob(os.path.join(in_dir, '*'))
for file in files:
if not os.path.isdir(file): #not copy directory, only file
print('Copy {}'.format(os.path.basename(file)), flush=True)
shutil.copy(file, out_dir)
#%% Finish
elapsed_time = time.time()-start
hour = int(elapsed_time/3600)
minite = int(np.mod((elapsed_time/60),60))
sec = int(np.mod(elapsed_time,60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour,minite,sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(out_dir)))
if os.path.exists(no_gacos_ifgfile):
print('Caution: Some ifgs below are excluded due to GACOS unavailable')
with open(no_gacos_ifgfile) as f:
for line in f:
print(line, end='')
print('')
if os.path.exists(no_gacos_imfile):
print('GACOS data for the following dates are missing:')
with open(no_gacos_imfile) as f:
for line in f:
print(line, end='')
print('')
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = "1.7.1"
date = 20201028
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
### For parallel processing
global ifgdates2, geocdir, outdir, nlook, n_valid_thre, cycle, cmap
#%% Set default
geocdir = []
outdir = []
nlook = 1
radar_freq = 5.405e9
try:
n_para = len(os.sched_getaffinity(0))
except:
n_para = multi.cpu_count()
cmap = 'insar'
cycle = 3
n_valid_thre = 0.5
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hi:o:n:",
["help", "freq=", "n_para="])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-i':
geocdir = a
elif o == '-o':
outdir = a
elif o == '-n':
nlook = int(a)
elif o == '--freq':
radar_freq = float(a)
elif o == '--n_para':
n_para = int(a)
if not geocdir:
raise Usage('No GEOC directory given, -d is not optional!')
elif not os.path.isdir(geocdir):
raise Usage('No {} dir exists!'.format(geocdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Directory and file setting
geocdir = os.path.abspath(geocdir)
if not outdir:
outdir = os.path.join(os.path.dirname(geocdir),
'GEOCml{}'.format(nlook))
if not os.path.exists(outdir): os.mkdir(outdir)
mlipar = os.path.join(outdir, 'slc.mli.par')
dempar = os.path.join(outdir, 'EQA.dem_par')
no_unw_list = os.path.join(outdir, 'no_unw_list.txt')
if os.path.exists(no_unw_list): os.remove(no_unw_list)
bperp_file_in = os.path.join(geocdir, 'baselines')
bperp_file_out = os.path.join(outdir, 'baselines')
metadata_file = os.path.join(geocdir, 'metadata.txt')
if os.path.exists(metadata_file):
center_time = subp.check_output(['grep', 'center_time', metadata_file
]).decode().split('=')[1].strip()
else:
center_time = None
#%% ENU
for ENU in ['E', 'N', 'U']:
print('\nCreate {}'.format(ENU + '.geo'), flush=True)
enutif = glob.glob(os.path.join(geocdir, '*.geo.{}.tif'.format(ENU)))
### Download if not exist
if len(enutif) == 0:
print(' No *.geo.{}.tif found in {}'.format(
ENU, os.path.basename(geocdir)),
flush=True)
continue
else:
enutif = enutif[0] ## first one
### Create float
data = gdal.Open(enutif).ReadAsArray()
data[data == 0] = np.nan
if nlook != 1:
### Multilook
data = tools_lib.multilook(data, nlook, nlook)
outfile = os.path.join(outdir, ENU + '.geo')
data.tofile(outfile)
print(' {}.geo created'.format(ENU), flush=True)
#%% mli
print('\nCreate slc.mli', flush=True)
mlitif = glob.glob(os.path.join(geocdir, '*.geo.mli.tif'))
if len(mlitif) > 0:
mlitif = mlitif[0] ## First one
mli = np.float32(gdal.Open(mlitif).ReadAsArray())
mli[mli == 0] = np.nan
if nlook != 1:
### Multilook
mli = tools_lib.multilook(mli, nlook, nlook)
mlifile = os.path.join(outdir, 'slc.mli')
mli.tofile(mlifile)
mlipngfile = mlifile + '.png'
mli = np.log10(mli)
vmin = np.nanpercentile(mli, 5)
vmax = np.nanpercentile(mli, 95)
plot_lib.make_im_png(mli,
mlipngfile,
'gray',
'MLI (log10)',
vmin,
vmax,
cbar=True)
print(' slc.mli[.png] created', flush=True)
else:
print(' No *.geo.mli.tif found in {}'.format(
os.path.basename(geocdir)),
flush=True)
#%% hgt
print('\nCreate hgt', flush=True)
hgttif = glob.glob(os.path.join(geocdir, '*.geo.hgt.tif'))
if len(hgttif) > 0:
hgttif = hgttif[0] ## First one
hgt = np.float32(gdal.Open(hgttif).ReadAsArray())
hgt[hgt == 0] = np.nan
if nlook != 1:
### Multilook
hgt = tools_lib.multilook(hgt, nlook, nlook)
hgtfile = os.path.join(outdir, 'hgt')
hgt.tofile(hgtfile)
hgtpngfile = hgtfile + '.png'
vmax = np.nanpercentile(hgt, 99)
vmin = -vmax / 3 ## bnecause 1/4 of terrain is blue
plot_lib.make_im_png(hgt,
hgtpngfile,
'terrain',
'DEM (m)',
vmin,
vmax,
cbar=True)
print(' hgt[.png] created', flush=True)
else:
print(' No *.geo.hgt.tif found in {}'.format(
os.path.basename(geocdir)),
flush=True)
#%% tif -> float (with multilook/downsampling)
print('\nCreate unw and cc', flush=True)
ifgdates = tools_lib.get_ifgdates(geocdir)
n_ifg = len(ifgdates)
### First check if float already exist
ifgdates2 = []
for i, ifgd in enumerate(ifgdates):
ifgdir1 = os.path.join(outdir, ifgd)
unwfile = os.path.join(ifgdir1, ifgd + '.unw')
ccfile = os.path.join(ifgdir1, ifgd + '.cc')
if not (os.path.exists(unwfile) and os.path.exists(ccfile)):
ifgdates2.append(ifgd)
n_ifg2 = len(ifgdates2)
if n_ifg - n_ifg2 > 0:
print(" {0:3}/{1:3} unw and cc already exist. Skip".format(
n_ifg - n_ifg2, n_ifg),
flush=True)
if n_ifg2 > 0:
if n_para > n_ifg2:
n_para = n_ifg2
### Create float with parallel processing
print(' {} parallel processing...'.format(n_para), flush=True)
p = multi.Pool(n_para)
rc = p.map(convert_wrapper, range(n_ifg2))
p.close()
ifgd_ok = []
for i, _rc in enumerate(rc):
if _rc == 1:
with open(no_unw_list, 'a') as f:
print('{}'.format(ifgdates2[i]), file=f)
elif _rc == 0:
ifgd_ok = ifgdates2[i] ## readable tiff
### Read info
## If all float already exist, this will not be done, but no problem because
## par files should alerady exist!
if ifgd_ok:
unw_tiffile = os.path.join(geocdir, ifgd_ok,
ifgd_ok + '.geo.unw.tif')
geotiff = gdal.Open(unw_tiffile)
width = geotiff.RasterXSize
length = geotiff.RasterYSize
lon_w_p, dlon, _, lat_n_p, _, dlat = geotiff.GetGeoTransform()
## lat lon are in pixel registration. dlat is negative
lon_w_g = lon_w_p + dlon / 2
lat_n_g = lat_n_p + dlat / 2
## to grit registration by shifting half pixel inside
if nlook != 1:
width = int(width / nlook)
length = int(length / nlook)
dlon = dlon * nlook
dlat = dlat * nlook
#%% EQA.dem_par, slc.mli.par
if not os.path.exists(mlipar):
print('\nCreate slc.mli.par', flush=True)
# radar_freq = 5.405e9 ## fixed for Sentnel-1
with open(mlipar, 'w') as f:
print('range_samples: {}'.format(width), file=f)
print('azimuth_lines: {}'.format(length), file=f)
print('radar_frequency: {} Hz'.format(radar_freq), file=f)
if center_time is not None:
print('center_time: {}'.format(center_time), file=f)
if not os.path.exists(dempar):
print('\nCreate EQA.dem_par', flush=True)
text = [
"Gamma DIFF&GEO DEM/MAP parameter file", "title: DEM",
"DEM_projection: EQA", "data_format: REAL*4",
"DEM_hgt_offset: 0.00000",
"DEM_scale: 1.00000", "width: {}".format(width),
"nlines: {}".format(length),
"corner_lat: {} decimal degrees".format(lat_n_g),
"corner_lon: {} decimal degrees".format(lon_w_g),
"post_lat: {} decimal degrees".format(dlat),
"post_lon: {} decimal degrees".format(dlon), "",
"ellipsoid_name: WGS 84", "ellipsoid_ra: 6378137.000 m",
"ellipsoid_reciprocal_flattening: 298.2572236", "",
"datum_name: WGS 1984", "datum_shift_dx: 0.000 m",
"datum_shift_dy: 0.000 m",
"datum_shift_dz: 0.000 m",
"datum_scale_m: 0.00000e+00",
"datum_rotation_alpha: 0.00000e+00 arc-sec",
"datum_rotation_beta: 0.00000e+00 arc-sec",
"datum_rotation_gamma: 0.00000e+00 arc-sec",
"datum_country_list: Global Definition, WGS84, World\n"
]
with open(dempar, 'w') as f:
f.write('\n'.join(text))
#%% bperp
print('\nCopy baselines file', flush=True)
imdates = tools_lib.ifgdates2imdates(ifgdates)
if os.path.exists(bperp_file_in):
## Check exisiting bperp_file
if not io_lib.read_bperp_file(bperp_file_in, imdates):
print(' baselines file found, but not complete. Make dummy',
flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
else:
shutil.copyfile(bperp_file_in, bperp_file_out)
else:
print(' No valid baselines file exists. Make dummy.', flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(outdir)))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = 1.2
date = 20200227
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
frameID = []
startdate = 20141001
enddate = int(dt.date.today().strftime("%Y%m%d"))
get_gacos = False
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hf:s:e:",
["help", "get_gacos"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-f':
frameID = a
elif o == '-s':
startdate = int(a)
elif o == '-e':
enddate = int(a)
elif o == '--get_gacos':
get_gacos = True
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Determine frameID
wd = os.getcwd()
if not frameID: ## if frameID not indicated
_tmp = re.findall(r'\d{3}[AD]_\d{5}_\d{6}', wd)
##e.g., 021D_04972_131213
if len(_tmp) == 0:
print('\nFrame ID cannot be identified from dir name!',
file=sys.stderr)
print('Use -f option', file=sys.stderr)
return
else:
frameID = _tmp[0]
print('\nFrame ID is {}\n'.format(frameID), flush=True)
trackID = str(int(frameID[0:3]))
#%% Directory and file setting
outdir = os.path.join(wd, 'GEOC')
if not os.path.exists(outdir): os.mkdir(outdir)
os.chdir(outdir)
LiCSARweb = 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/'
#%% ENU and hgt
for ENU in ['E', 'N', 'U', 'hgt']:
enutif = '{}.geo.{}.tif'.format(frameID, ENU)
if os.path.exists(enutif):
print('{} already exist. Skip download.'.format(enutif),
flush=True)
continue
print('Download {}'.format(enutif), flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', enutif)
if not tools_lib.download_data(url, enutif):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
continue
#%% baselines and metadata.txt
print('Download baselines', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', 'baselines')
if not tools_lib.download_data(url, 'baselines'):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
print('Download metadata.txt', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', 'metadata.txt')
if not tools_lib.download_data(url, 'metadata.txt'):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
#%% mli
### Get available dates
url = os.path.join(LiCSARweb, trackID, frameID, 'products', 'epochs')
response = requests.get(url)
if not response.ok: ## Try new structure
url = os.path.join(LiCSARweb, trackID, frameID, 'epochs')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}"))
imdates_all = [tag.get("href")[0:8] for tag in tags]
_imdates = np.int32(np.array(imdates_all))
_imdates = (_imdates[(_imdates >= startdate) *
(_imdates <= enddate)]).astype('str').tolist()
## Find earliest date in which mli is available
imd1 = []
for imd in _imdates:
url_mli = os.path.join(url, imd, imd + '.geo.mli.tif')
response = requests.get(url_mli)
if response.ok:
imd1 = imd
break
### Download
if imd1:
print('Donwnloading {}.geo.mli.tif as {}.geo.mli.tif...'.format(
imd1, frameID),
flush=True)
url_mli = os.path.join(url, imd1, imd1 + '.geo.mli.tif')
mlitif = frameID + '.geo.mli.tif'
if os.path.exists(mlitif):
print(' {} already exist. Skip'.format(mlitif), flush=True)
elif not tools_lib.download_data(url_mli, mlitif):
print(' Error while downloading from {}'.format(url_mli),
file=sys.stderr,
flush=True)
else:
print('No mli available on {}'.format(url),
file=sys.stderr,
flush=True)
#%% GACOS if specified
if get_gacos:
gacosdir = os.path.join(wd, 'GACOS')
if not os.path.exists(gacosdir): os.mkdir(gacosdir)
### Get available dates
print('\nDownload GACOS data', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'epochs')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}"))
imdates_all = [tag.get("href")[0:8] for tag in tags]
_imdates = np.int32(np.array(imdates_all))
_imdates = (_imdates[(_imdates >= startdate) *
(_imdates <= enddate)]).astype('str').tolist()
### Extract available dates
imdates = []
for imd in _imdates:
url_sltd = os.path.join(url, imd, imd + '.sltd.geo.tif')
response = requests.get(url_sltd)
if response.ok:
imdates.append(imd)
n_im = len(imdates)
if n_im > 0:
print('{} GACOS data available from {} to {}'.format(
n_im, imdates[0], imdates[-1]),
flush=True)
else:
print('No GACOS data available from {} to {}'.format(
startdate, enddate),
flush=True)
### Download
for i, imd in enumerate(imdates):
print(' Donwnloading {} ({}/{})...'.format(imd, i + 1, n_im),
flush=True)
url_sltd = os.path.join(url, imd, imd + '.sltd.geo.tif')
path_sltd = os.path.join(gacosdir, imd + '.sltd.geo.tif')
if os.path.exists(path_sltd):
print(' {}.sltd.geo.tif already exist. Skip'.format(imd),
flush=True)
elif not tools_lib.download_data(url_sltd, path_sltd):
print(' Error while downloading from {}'.format(url_sltd),
file=sys.stderr,
flush=True)
#%% unw and cc
### Get available dates
print('\nDownload geotiff of unw and cc', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'products')
response = requests.get(url)
if not response.ok: ## Try new structure
url = os.path.join(LiCSARweb, trackID, frameID, 'interferograms')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}_\d{8}"))
ifgdates_all = [tag.get("href")[0:17] for tag in tags]
### Extract during start_date to end_date
ifgdates = []
for ifgd in ifgdates_all:
mimd = int(ifgd[:8])
simd = int(ifgd[-8:])
if mimd >= startdate and simd <= enddate:
ifgdates.append(ifgd)
n_ifg = len(ifgdates)
imdates = tools_lib.ifgdates2imdates(ifgdates)
print('{} IFGs available from {} to {}'.format(n_ifg, imdates[0],
imdates[-1]),
flush=True)
### Download
for i, ifgd in enumerate(ifgdates):
print(' Donwnloading {} ({}/{})...'.format(ifgd, i + 1, n_ifg),
flush=True)
url_unw = os.path.join(url, ifgd, ifgd + '.geo.unw.tif')
path_unw = os.path.join(ifgd, ifgd + '.geo.unw.tif')
if not os.path.exists(ifgd): os.mkdir(ifgd)
if os.path.exists(path_unw):
print(' {}.geo.unw.tif already exist. Skip'.format(ifgd),
flush=True)
elif not tools_lib.download_data(url_unw, path_unw):
print(' Error while downloading from {}'.format(url_unw),
file=sys.stderr,
flush=True)
url_cc = os.path.join(url, ifgd, ifgd + '.geo.cc.tif')
path_cc = os.path.join(ifgd, ifgd + '.geo.cc.tif')
if os.path.exists(path_cc):
print(' {}.geo.cc.tif already exist. Skip.'.format(ifgd),
flush=True)
if not tools_lib.download_data(url_cc, path_cc):
print(' Error while downloading from {}'.format(url_cc),
file=sys.stderr,
flush=True)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(outdir))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = "1.3.2"
date = 20201116
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
ifgdir = []
tsadir = []
coh_thre = 0.05
unw_cov_thre = 0.3
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hd:t:c:u:", ["help"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-d':
ifgdir = a
elif o == '-t':
tsadir = a
elif o == '-c':
coh_thre = float(a)
elif o == '-u':
unw_cov_thre = float(a)
if not ifgdir:
raise Usage('No data directory given, -d is not optional!')
elif not os.path.isdir(ifgdir):
raise Usage('No {} dir exists!'.format(ifgdir))
elif not os.path.exists(os.path.join(ifgdir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(ifgdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
print("\ncoh_thre : {}".format(coh_thre), flush=True)
print("unw_cov_thre : {}".format(unw_cov_thre), flush=True)
#%% Directory setting
ifgdir = os.path.abspath(ifgdir)
if not tsadir:
tsadir = os.path.join(os.path.dirname(ifgdir),
'TS_' + os.path.basename(ifgdir))
if not os.path.exists(tsadir): os.mkdir(tsadir)
ifg_rasdir = os.path.join(tsadir, '11ifg_ras')
bad_ifg_rasdir = os.path.join(tsadir, '11bad_ifg_ras')
if os.path.exists(ifg_rasdir): shutil.rmtree(ifg_rasdir)
if os.path.exists(bad_ifg_rasdir): shutil.rmtree(bad_ifg_rasdir)
os.mkdir(ifg_rasdir)
os.mkdir(bad_ifg_rasdir)
netdir = os.path.join(tsadir, 'network')
if not os.path.exists(netdir): os.mkdir(netdir)
infodir = os.path.join(tsadir, 'info')
if not os.path.exists(infodir): os.mkdir(infodir)
resultsdir = os.path.join(tsadir, 'results')
if not os.path.exists(resultsdir): os.mkdir(resultsdir)
#%% Read date, network information and size
### Get dates
ifgdates = tools_lib.get_ifgdates(ifgdir)
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_im = len(imdates)
### Get size
mlipar = os.path.join(ifgdir, 'slc.mli.par')
width = int(io_lib.get_param_par(mlipar, 'range_samples'))
length = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
print("\nSize : {} x {}".format(width, length), flush=True)
### Copy dempar and mli[png|par]
for file in ['slc.mli.par', 'EQA.dem_par']:
if os.path.exists(os.path.join(ifgdir, file)):
shutil.copy(os.path.join(ifgdir, file), infodir)
for file in ['slc.mli', 'slc.mli.png', 'hgt', 'hgt.png']:
if os.path.exists(os.path.join(ifgdir, file)):
shutil.copy(os.path.join(ifgdir, file), resultsdir)
#%% Read data
### Allocate memory
n_unw = np.zeros((length, width), dtype=np.float32)
coh_avg_ifg = []
n_unw_ifg = []
### Read data and calculate
print('\nReading unw and cc data...', flush=True)
## First, identify valid area (n_unw>im)
for ifgix, ifgd in enumerate(ifgdates):
if np.mod(ifgix, 100) == 0:
print(" {0:3}/{1:3}th unw to identify valid area...".format(
ifgix, n_ifg),
flush=True)
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
unw = io_lib.read_img(unwfile, length, width)
unw[unw == 0] = np.nan # Fill 0 with nan
n_unw += ~np.isnan(unw) # Summing number of unnan unw
## Identify valid area and calc rate_cov
bool_valid = (n_unw >= n_im)
n_unw_valid = bool_valid.sum()
## Read cc and unw data
for ifgix, ifgd in enumerate(ifgdates):
if np.mod(ifgix, 100) == 0:
print(" {0:3}/{1:3}th cc and unw...".format(ifgix, n_ifg),
flush=True)
## unw
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
unw = io_lib.read_img(unwfile, length, width)
unw[unw == 0] = np.nan # Fill 0 with nan
unw[~bool_valid] = np.nan # Fill sea area with nan
n_unw_ifg.append((~np.isnan(unw)).sum())
## cc
ccfile = os.path.join(ifgdir, ifgd, ifgd + '.cc')
if os.path.getsize(ccfile) == length * width:
coh = io_lib.read_img(ccfile, length, width, np.uint8)
coh = coh.astype(np.float32) / 255
coh[coh == 0] = np.nan
else:
coh = io_lib.read_img(ccfile, length, width)
coh_avg_ifg.append(np.nanmean(coh[bool_valid])) # Use valid area only
rate_cov = np.array(n_unw_ifg) / n_unw_valid
## Read bperp data or dummy
bperp_file = os.path.join(ifgdir, 'baselines')
if os.path.exists(bperp_file):
bperp = io_lib.read_bperp_file(bperp_file, imdates)
else: #dummy
bperp = np.random.random(n_im).tolist()
#%% Identify bad ifgs, link ras and output stats information
bad_ifgdates = []
ixs_bad_ifgdates = []
### Header of stats file
ifg_statsfile = os.path.join(infodir, '11ifg_stats.txt')
fstats = open(ifg_statsfile, 'w')
print('# Size: {0}({1}x{2}), n_valid: {3}'.format(width * length, width,
length, n_unw_valid),
file=fstats)
print('# unw_cov_thre: {0}, coh_thre: {1}'.format(unw_cov_thre, coh_thre),
file=fstats)
print('# ifg dates bperp dt unw_cov coh_av', file=fstats)
### Identify suffix of raster image (png, ras or bmp?)
unwfile = os.path.join(ifgdir, ifgdates[0], ifgdates[0] + '.unw')
if os.path.exists(unwfile + '.ras'):
suffix = '.ras'
elif os.path.exists(unwfile + '.bmp'):
suffix = '.bmp'
elif os.path.exists(unwfile + '.png'):
suffix = '.png'
else:
print('\nERROR: No browse image available for {}!\n'.format(unwfile),
file=sys.stderr)
return 2
for i, ifgd in enumerate(ifgdates):
rasname = ifgdates[i] + '.unw' + suffix
rasorg = os.path.join(ifgdir, ifgdates[i], rasname)
if not os.path.exists(rasorg):
print('\nERROR: No browse image {} available!\n'.format(rasorg),
file=sys.stderr)
return 2
### Identify bad ifgs and link ras
if rate_cov[i] < unw_cov_thre or coh_avg_ifg[i] < coh_thre:
bad_ifgdates.append(ifgdates[i])
ixs_bad_ifgdates.append(i)
rm_flag = '*'
os.symlink(os.path.relpath(rasorg, bad_ifg_rasdir),
os.path.join(bad_ifg_rasdir, rasname))
else:
os.symlink(os.path.relpath(rasorg, ifg_rasdir),
os.path.join(ifg_rasdir, rasname))
rm_flag = ''
### For stats file
ix_primary = imdates.index(ifgd[:8])
ix_secondary = imdates.index(ifgd[-8:])
bperp_ifg = bperp[ix_secondary] - bperp[ix_primary]
mday = dt.datetime.strptime(ifgd[:8], '%Y%m%d').toordinal()
sday = dt.datetime.strptime(ifgd[-8:], '%Y%m%d').toordinal()
dt_ifg = sday - mday
print('{0} {1:6.1f} {2:3} {3:5.3f} {4:5.3f} {5}'.format(
ifgd, bperp_ifg, dt_ifg, rate_cov[i], coh_avg_ifg[i], rm_flag),
file=fstats)
fstats.close()
### Output list of bad ifg
print('\n{0}/{1} ifgs are discarded from further processing.'.format(
len(bad_ifgdates), n_ifg))
print('ifg dates unw_cov coh_av')
bad_ifgfile = os.path.join(infodir, '11bad_ifg.txt')
with open(bad_ifgfile, 'w') as f:
for i, ifgd in enumerate(bad_ifgdates):
print('{}'.format(ifgd), file=f)
print('{} {:5.3f} {:5.3f}'.format(
ifgd, rate_cov[ixs_bad_ifgdates[i]],
coh_avg_ifg[ixs_bad_ifgdates[i]]),
flush=True)
#%% Identify removed image and output file
good_ifgdates = list(set(ifgdates) - set(bad_ifgdates))
good_ifgdates.sort()
good_imdates = tools_lib.ifgdates2imdates(good_ifgdates)
bad_imdates = list(set(imdates) - set(good_imdates))
bad_imdates.sort()
### Output list of removed image
bad_imfile = os.path.join(infodir, '11removed_image.txt')
with open(bad_imfile, 'w') as f:
for i in bad_imdates:
print('{}'.format(i), file=f)
#%% Plot network
pngfile = os.path.join(netdir, 'network11_all.png')
plot_lib.plot_network(ifgdates, bperp, [], pngfile)
pngfile = os.path.join(netdir, 'network11.png')
plot_lib.plot_network(ifgdates, bperp, bad_ifgdates, pngfile)
pngfile = os.path.join(netdir, 'network11_nobad.png')
plot_lib.plot_network(ifgdates,
bperp,
bad_ifgdates,
pngfile,
plot_bad=False)
#%% Finish
print('\nCheck network/*, 11bad_ifg_ras/* and 11ifg_ras/* in TS dir.')
print(
'If you want to change the bad ifgs to be discarded, re-run with different thresholds or edit bad_ifg11.txt before next step.'
)
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(tsadir)))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = 1.6
date = 20200911
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
frameID = []
startdate = 20141001
enddate = int(dt.date.today().strftime("%Y%m%d"))
get_gacos = False
n_para = 4
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hf:s:e:",
["help", "get_gacos", "n_para="])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-f':
frameID = a
elif o == '-s':
startdate = int(a)
elif o == '-e':
enddate = int(a)
elif o == '--get_gacos':
get_gacos = True
elif o == '--n_para':
n_para = int(a)
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Determine frameID
wd = os.getcwd()
if not frameID: ## if frameID not indicated
_tmp = re.findall(r'\d{3}[AD]_\d{5}_\d{6}', wd)
##e.g., 021D_04972_131213
if len(_tmp) == 0:
print('\nFrame ID cannot be identified from dir name!',
file=sys.stderr)
print('Use -f option', file=sys.stderr)
return
else:
frameID = _tmp[0]
print('\nFrame ID is {}\n'.format(frameID), flush=True)
else:
print('\nFrame ID is {}\n'.format(frameID), flush=True)
trackID = str(int(frameID[0:3]))
#%% Directory and file setting
outdir = os.path.join(wd, 'GEOC')
if not os.path.exists(outdir): os.mkdir(outdir)
os.chdir(outdir)
LiCSARweb = 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/'
#%% ENU and hgt
for ENU in ['E', 'N', 'U', 'hgt']:
enutif = '{}.geo.{}.tif'.format(frameID, ENU)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', enutif)
if os.path.exists(enutif):
rc = tools_lib.comp_size_time(url, enutif)
if rc == 0:
print('{} already exist. Skip download.'.format(enutif),
flush=True)
continue
elif rc == 3:
print('{} not available. Skip download.'.format(enutif),
flush=True)
continue
else:
if rc == 1:
print("Size of {} is not identical.".format(enutif))
elif rc == 2:
print("Newer {} available.".format(enutif))
print('Download {}'.format(enutif), flush=True)
tools_lib.download_data(url, enutif)
#%% baselines and metadata.txt
print('Download baselines', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', 'baselines')
tools_lib.download_data(url, 'baselines')
print('Download metadata.txt', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', 'metadata.txt')
tools_lib.download_data(url, 'metadata.txt')
#%% mli
mlitif = frameID + '.geo.mli.tif'
if os.path.exists(mlitif):
print('{} already exist. Skip.'.format(mlitif), flush=True)
else:
### Get available dates
print('Searching earliest epoch for mli...', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'epochs')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}"))
imdates_all = [tag.get("href")[0:8] for tag in tags]
_imdates = np.int32(np.array(imdates_all))
_imdates = (_imdates[(_imdates >= startdate) *
(_imdates <= enddate)]).astype('str').tolist()
## Find earliest date in which mli is available
imd1 = []
for i, imd in enumerate(_imdates):
if np.mod(i, 10) == 0:
print("\r {0:3}/{1:3}".format(i, len(_imdates)),
end='',
flush=True)
url_epoch = os.path.join(url, imd)
response = requests.get(url_epoch)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tag = soup.find(href=re.compile(r"\d{8}.geo.mli.tif"))
if tag is not None:
print('\n{} found as earliest.'.format(imd))
imd1 = imd
break
### Download
if imd1:
print('Donwnloading {}.geo.mli.tif as {}.geo.mli.tif...'.format(
imd1, frameID),
flush=True)
url_mli = os.path.join(url, imd1, imd1 + '.geo.mli.tif')
tools_lib.download_data(url_mli, mlitif)
else:
print('\nNo mli available on {}'.format(url),
file=sys.stderr,
flush=True)
#%% GACOS if specified
if get_gacos:
gacosdir = os.path.join(wd, 'GACOS')
if not os.path.exists(gacosdir): os.mkdir(gacosdir)
### Get available dates
print('\nDownload GACOS data', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'epochs')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}"))
imdates_all = [tag.get("href")[0:8] for tag in tags]
_imdates = np.int32(np.array(imdates_all))
_imdates = (_imdates[(_imdates >= startdate) *
(_imdates <= enddate)]).astype('str').tolist()
print(' There are {} epochs from {} to {}'.format(
len(_imdates), startdate, enddate),
flush=True)
### Extract available dates
print(' Searching available epochs ({} parallel)...'.format(n_para),
flush=True)
args = [(i, len(_imdates),
os.path.join(url, imd, '{}.sltd.geo.tif'.format(imd)),
os.path.join(gacosdir, imd + '.sltd.geo.tif'))
for i, imd in enumerate(_imdates)]
p = multi.Pool(n_para)
rc = p.map(check_gacos_wrapper, args)
p.close()
n_im_existing = 0
n_im_unavailable = 0
imdates_dl = []
for i, rc1 in enumerate(rc):
if rc1 == 0: ## No need to download
n_im_existing = n_im_existing + 1
if rc1 == 3 or rc1 == 5: ## Can not download
n_im_unavailable = n_im_unavailable + 1
elif rc1 == 1 or rc1 == 2 or rc1 == 4: ## Need download
imdates_dl.append(_imdates[i])
n_im_dl = len(imdates_dl)
if n_im_existing > 0:
print(' {} GACOS data already downloaded'.format(n_im_existing),
flush=True)
if n_im_unavailable > 0:
print(' {} GACOS data unavailable'.format(n_im_unavailable),
flush=True)
### Download
if n_im_dl > 0:
print('{} GACOS data will be downloaded'.format(n_im_dl),
flush=True)
print('Download GACOS ({} parallel)...'.format(n_para), flush=True)
### Download
args = [(i, imd, n_im_dl,
os.path.join(url, imd, '{}.sltd.geo.tif'.format(imd)),
os.path.join(gacosdir, '{}.sltd.geo.tif'.format(imd)))
for i, imd in enumerate(imdates_dl)]
p = multi.Pool(n_para)
p.map(download_wrapper, args)
p.close()
else:
print('No GACOS data available from {} to {}'.format(
startdate, enddate),
flush=True)
#%% unw and cc
### Get available dates
print('\nDownload geotiff of unw and cc', flush=True)
url_ifgdir = os.path.join(LiCSARweb, trackID, frameID, 'interferograms')
response = requests.get(url_ifgdir)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}_\d{8}"))
ifgdates_all = [tag.get("href")[0:17] for tag in tags]
### Extract during start_date to end_date
ifgdates = []
for ifgd in ifgdates_all:
mimd = int(ifgd[:8])
simd = int(ifgd[-8:])
if mimd >= startdate and simd <= enddate:
ifgdates.append(ifgd)
n_ifg = len(ifgdates)
imdates = tools_lib.ifgdates2imdates(ifgdates)
print('{} IFGs available from {} to {}'.format(n_ifg, imdates[0],
imdates[-1]),
flush=True)
### Check if both unw and cc already donwloaded, new, and same size
print(
'Checking existing unw and cc ({} parallel, may take time)...'.format(
n_para),
flush=True)
## unw
args = [(i, n_ifg,
os.path.join(url_ifgdir, ifgd, '{}.geo.unw.tif'.format(ifgd)),
os.path.join(ifgd, '{}.geo.unw.tif'.format(ifgd)))
for i, ifgd in enumerate(ifgdates)]
p = multi.Pool(n_para)
rc = p.map(check_exist_wrapper, args)
p.close()
n_unw_existing = 0
unwdates_dl = []
for i, rc1 in enumerate(rc):
if rc1 == 0: ## No need to download
n_unw_existing = n_unw_existing + 1
if rc1 == 3 or rc1 == 5: ## Can not download
print(' {}.geo.unw.tif not available.'.format(ifgdates[i]),
flush=True)
elif rc1 == 1 or rc1 == 2 or rc1 == 4: ## Need download
unwdates_dl.append(ifgdates[i])
## cc
args = [(i, n_ifg,
os.path.join(url_ifgdir, ifgd, '{}.geo.cc.tif'.format(ifgd)),
os.path.join(ifgd, '{}.geo.cc.tif'.format(ifgd)))
for i, ifgd in enumerate(ifgdates)]
p = multi.Pool(n_para)
rc = p.map(check_exist_wrapper, args)
p.close()
n_cc_existing = 0
ccdates_dl = []
for i, rc1 in enumerate(rc):
if rc1 == 0: ## No need to download
n_cc_existing = n_cc_existing + 1
if rc1 == 3 or rc1 == 5: ## Can not download
print(' {}.geo.cc.tif not available.'.format(ifgdates[i]),
flush=True)
elif rc1 == 1 or rc1 == 2 or rc1 == 4: ## Need download
ccdates_dl.append(ifgdates[i])
n_unw_dl = len(unwdates_dl)
n_cc_dl = len(ccdates_dl)
print('{} unw already downloaded'.format(n_unw_existing), flush=True)
print('{} unw will be downloaded'.format(n_unw_dl), flush=True)
print('{} cc already downloaded'.format(n_cc_existing), flush=True)
print('{} cc will be downloaded'.format(n_cc_dl), flush=True)
### Download unw with parallel
if n_unw_dl != 0:
print('Download unw ({} parallel)...'.format(n_para), flush=True)
args = [(i, ifgd, n_unw_dl,
os.path.join(url_ifgdir, ifgd, '{}.geo.unw.tif'.format(ifgd)),
os.path.join(ifgd, '{}.geo.unw.tif'.format(ifgd)))
for i, ifgd in enumerate(unwdates_dl)]
p = multi.Pool(n_para)
p.map(download_wrapper, args)
p.close()
### Download cc with parallel
if n_cc_dl != 0:
print('Download cc ({} parallel)...'.format(n_para), flush=True)
args = [(i, ifgd, n_cc_dl,
os.path.join(url_ifgdir, ifgd, '{}.geo.cc.tif'.format(ifgd)),
os.path.join(ifgd, '{}.geo.cc.tif'.format(ifgd)))
for i, ifgd in enumerate(ccdates_dl)]
p = multi.Pool(n_para)
p.map(download_wrapper, args)
p.close()
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(outdir))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = "1.5.5"
date = 20201119
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
### For parallel processing
global imdates2, gacosdir, outputBounds, width_geo, length_geo, resampleAlg,\
sltddir, LOSu, m2r_coef, fillholeflag, ifgdates2,\
in_dir, out_dir, length_unw, width_unw, cycle, cmap_wrap
#%% Set default
in_dir = []
out_dir = []
gacosdir = 'GACOS'
resampleAlg = 'cubicspline' # None # 'cubic'
fillholeflag = False
try:
n_para = len(os.sched_getaffinity(0))
except:
n_para = multi.cpu_count()
q = multi.get_context('fork')
cmap_wrap = SCM.romaO
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hi:o:g:z:",
["fillhole", "help", "n_para="])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-i':
in_dir = a
elif o == '-o':
out_dir = a
elif o == '-z': ## for backward-compatible
gacosdir = a
elif o == '-g':
gacosdir = a
elif o == "--fillhole":
fillholeflag = True
elif o == '--n_para':
n_para = int(a)
if not in_dir:
raise Usage('No input directory given, -i is not optional!')
elif not os.path.isdir(in_dir):
raise Usage('No {} dir exists!'.format(in_dir))
elif not os.path.exists(os.path.join(in_dir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(in_dir))
if not out_dir:
raise Usage('No output directory given, -o is not optional!')
if not os.path.isdir(gacosdir):
raise Usage('No {} dir exists!'.format(gacosdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Read data information
### Directory
in_dir = os.path.abspath(in_dir)
gacosdir = os.path.abspath(gacosdir)
out_dir = os.path.abspath(out_dir)
if not os.path.exists(out_dir): os.mkdir(out_dir)
sltddir = os.path.join(os.path.join(out_dir), 'sltd')
if not os.path.exists(sltddir): os.mkdir(sltddir)
### Get general info
mlipar = os.path.join(in_dir, 'slc.mli.par')
width_unw = int(io_lib.get_param_par(mlipar, 'range_samples'))
length_unw = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
speed_of_light = 299792458 #m/s
radar_frequency = float(io_lib.get_param_par(mlipar,
'radar_frequency')) #Hz
wavelength = speed_of_light / radar_frequency #meter
m2r_coef = 4 * np.pi / wavelength
if wavelength > 0.2: ## L-band
cycle = 1.5 # 2pi/cycle for png
else: ## C-band
cycle = 3 # 2pi*3/cycle for png
### Get geo info. Grid registration
dempar = os.path.join(in_dir, 'EQA.dem_par')
width_geo = int(io_lib.get_param_par(dempar, 'width'))
length_geo = int(io_lib.get_param_par(dempar, 'nlines'))
dlat_geo = float(io_lib.get_param_par(dempar, 'post_lat')) #minus
dlon_geo = float(io_lib.get_param_par(dempar, 'post_lon'))
latn_geo = float(io_lib.get_param_par(dempar, 'corner_lat'))
lonw_geo = float(io_lib.get_param_par(dempar, 'corner_lon'))
lats_geo = latn_geo + dlat_geo * (length_geo - 1)
lone_geo = lonw_geo + dlon_geo * (width_geo - 1)
outputBounds = (lonw_geo, lats_geo, lone_geo, latn_geo)
### Check coordinate
if width_unw != width_geo or length_unw != length_geo:
print('\n{} seems to contain files in radar coordinate!!\n'.format(
in_dir),
file=sys.stderr)
print('Not supported.\n', file=sys.stderr)
return 1
### Calc incidence angle from U.geo
ufile = os.path.join(in_dir, 'U.geo')
LOSu = io_lib.read_img(ufile, length_geo, width_geo)
LOSu[LOSu == 0] = np.nan
### Get ifgdates and imdates
ifgdates = tools_lib.get_ifgdates(in_dir)
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_im = len(imdates)
#%% Process ztd files
print('\nConvert ztd/sltd.geo.tif files to sltd.geo files...', flush=True)
no_gacos_imfile = os.path.join(out_dir, 'no_gacos_im.txt')
if os.path.exists(no_gacos_imfile): os.remove(no_gacos_imfile)
### First check if sltd already exist
imdates2 = []
for imd in imdates:
sltd_geofile = os.path.join(sltddir, imd + '.sltd.geo')
if not os.path.exists(sltd_geofile):
imdates2.append(imd)
n_im2 = len(imdates2)
if n_im - n_im2 > 0:
print(" {0:3}/{1:3} sltd already exist. Skip".format(
n_im - n_im2, n_im),
flush=True)
if n_im2 > 0:
### Convert with parallel processing
if n_para > n_im2:
_n_para = n_im2
else:
_n_para = n_para
print(' {} parallel processing...'.format(_n_para), flush=True)
p = q.Pool(_n_para)
no_gacos_imds = p.map(convert_wrapper, range(n_im2))
p.close()
for imd in no_gacos_imds:
if imd is not None:
with open(no_gacos_imfile, mode='a') as fnogacos:
print('{}'.format(imd), file=fnogacos)
#%% Correct unw files
print('\nCorrect unw data...', flush=True)
### Information files
gacinfofile = os.path.join(out_dir, 'GACOS_info.txt')
if not os.path.exists(gacinfofile):
### Add header
with open(gacinfofile, "w") as f:
print(' Phase STD (rad) Before After ReductionRate', file=f)
no_gacos_ifgfile = os.path.join(out_dir, 'no_gacos_ifg.txt')
if os.path.exists(no_gacos_ifgfile): os.remove(no_gacos_ifgfile)
### First check if already corrected unw exist
ifgdates2 = []
for i, ifgd in enumerate(ifgdates):
out_dir1 = os.path.join(out_dir, ifgd)
unw_corfile = os.path.join(out_dir1, ifgd + '.unw')
if not os.path.exists(unw_corfile):
ifgdates2.append(ifgd)
n_ifg2 = len(ifgdates2)
if n_ifg - n_ifg2 > 0:
print(" {0:3}/{1:3} corrected unw already exist. Skip".format(
n_ifg - n_ifg2, n_ifg),
flush=True)
if n_ifg2 > 0:
### Correct with parallel processing
if n_para > n_ifg2:
_n_para = n_ifg2
else:
_n_para = n_para
print(' {} parallel processing...'.format(_n_para), flush=True)
p = q.Pool(_n_para)
_return = p.map(correct_wrapper, range(n_ifg2))
p.close()
for i in range(n_ifg2):
if _return[i][0] == 1:
with open(no_gacos_ifgfile, mode='a') as fnogacos:
print('{}'.format(_return[i][1]), file=fnogacos)
elif _return[i][0] == 2:
with open(gacinfofile, "a") as f:
print('{0} {1:4.1f} {2:4.1f} {3:5.1f}%'.format(
*_return[i][1]),
file=f)
print("", flush=True)
#%% Create correlation png
pngfile = os.path.join(out_dir, 'GACOS_info.png')
plot_lib.plot_gacos_info(gacinfofile, pngfile)
#%% Copy other files
files = glob.glob(os.path.join(in_dir, '*'))
for file in files:
if not os.path.isdir(file): #not copy directory, only file
print('Copy {}'.format(os.path.basename(file)), flush=True)
shutil.copy(file, out_dir)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(out_dir)))
if os.path.exists(no_gacos_ifgfile):
print('Caution: Some ifgs below are excluded due to GACOS unavailable')
with open(no_gacos_ifgfile) as f:
for line in f:
print(line, end='')
print('')
if os.path.exists(no_gacos_imfile):
print('GACOS data for the following dates are missing:')
with open(no_gacos_imfile) as f:
for line in f:
print(line, end='')
print('')
def plot_network(ifgdates, bperp, rm_ifgdates, pngfile, plot_bad=True):
"""
Plot network of interferometric pairs.
bperp can be dummy (-1~1).
Suffix of pngfile can be png, ps, pdf, or svg.
plot_bad
True : Plot bad ifgs by red lines
False : Do not plot bad ifgs
"""
imdates_all = tools_lib.ifgdates2imdates(ifgdates)
n_im_all = len(imdates_all)
idlist_all = [dt.datetime.strptime(x, '%Y%m%d').toordinal() for x in imdates_all]
ifgdates = list(set(ifgdates)-set(rm_ifgdates))
ifgdates.sort()
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_im = len(imdates)
idlist = [dt.datetime.strptime(x, '%Y%m%d').toordinal() for x in imdates]
### Identify gaps
G = inv_lib.make_sb_matrix(ifgdates)
ixs_inc_gap = np.where(G.sum(axis=0)==0)[0]
### Plot fig
figsize_x = np.round((idlist_all[-1]-idlist_all[0])/80)+2
fig = plt.figure(figsize=(figsize_x, 6))
ax = fig.add_axes([0.12, 0.12, 0.85,0.85])
### IFG blue lines
for i, ifgd in enumerate(ifgdates):
ix_m = imdates_all.index(ifgd[:8])
ix_s = imdates_all.index(ifgd[-8:])
label = 'IFG' if i==0 else '' #label only first
plt.plot([idlist_all[ix_m], idlist_all[ix_s]], [bperp[ix_m], bperp[ix_s]], color='b', alpha=0.6, zorder=2, label=label)
### IFG bad red lines
if plot_bad:
for i, ifgd in enumerate(rm_ifgdates):
ix_m = imdates_all.index(ifgd[:8])
ix_s = imdates_all.index(ifgd[-8:])
label = 'Removed IFG' if i==0 else '' #label only first
plt.plot([idlist_all[ix_m], idlist_all[ix_s]], [bperp[ix_m], bperp[ix_s]], color='r', alpha=0.6, zorder=6, label=label)
### Image points and dates
ax.scatter(idlist_all, bperp, alpha=0.6, zorder=4)
for i in range(n_im_all):
if bperp[i] > np.median(bperp): va='bottom'
else: va = 'top'
ax.annotate(imdates_all[i][4:6]+'/'+imdates_all[i][6:], (idlist_all[i], bperp[i]), ha='center', va=va, zorder=8)
### gaps
if len(ixs_inc_gap)!=0:
gap_idlist = []
for ix_gap in ixs_inc_gap:
gap_idlist.append((idlist[ix_gap]+idlist[ix_gap+1])/2)
plt.vlines(gap_idlist, 0, 1, transform=ax.get_xaxis_transform(), zorder=1, label='Gap', alpha=0.6, colors='k', linewidth=3)
### Locater
loc = ax.xaxis.set_major_locator(mdates.AutoDateLocator())
try: # Only support from Matplotlib 3.1
ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(loc))
except:
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y/%m/%d'))
for label in ax.get_xticklabels():
label.set_rotation(20)
label.set_horizontalalignment('right')
ax.grid(b=True, which='major')
### Add bold line every 1yr
ax.xaxis.set_minor_locator(mdates.YearLocator())
ax.grid(b=True, which='minor', linewidth=2)
ax.set_xlim((idlist_all[0]-10, idlist_all[-1]+10))
### Labels and legend
plt.xlabel('Time')
if np.all(np.abs(np.array(bperp))<=1): ## dummy
plt.ylabel('dummy')
else:
plt.ylabel('Bperp [m]')
plt.legend()
### Save
plt.savefig(pngfile)
plt.close()
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = 1.4
date = 20200228
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
geocdir = []
outdir = []
nlook = 1
frameID = []
cmap = 'insar'
cycle = 3
n_valid_thre = 0.5
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hi:o:n:f:", ["help"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-i':
geocdir = a
elif o == '-o':
outdir = a
elif o == '-n':
nlook = int(a)
elif o == '-f':
frameID = a
if not geocdir:
raise Usage('No GEOC directory given, -d is not optional!')
elif not os.path.isdir(geocdir):
raise Usage('No {} dir exists!'.format(geocdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Directory and file setting
geocdir = os.path.abspath(geocdir)
if not outdir:
outdir = os.path.join(os.path.dirname(geocdir),
'GEOCml{}'.format(nlook))
if not os.path.exists(outdir): os.mkdir(outdir)
mlipar = os.path.join(outdir, 'slc.mli.par')
dempar = os.path.join(outdir, 'EQA.dem_par')
no_unw_list = os.path.join(outdir, 'no_unw_list.txt')
if os.path.exists(no_unw_list): os.remove(no_unw_list)
bperp_file_in = os.path.join(geocdir, 'baselines')
bperp_file_out = os.path.join(outdir, 'baselines')
metadata_file = os.path.join(geocdir, 'metadata.txt')
if os.path.exists(metadata_file):
center_time = subp.check_output(['grep', 'center_time', metadata_file
]).decode().split('=')[1].strip()
else:
center_time = None
LiCSARweb = 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/'
### Frame ID even if not used
if not frameID: ## if not specified
_tmp = re.findall(r'\d{3}[AD]_\d{5}_\d{6}', geocdir)
##e.g., 021D_04972_131213
if len(_tmp) != 0: ## if not found, keep []
frameID = _tmp[0]
trackID = str(int(frameID[0:3]))
else:
trackID = str(int(frameID[0:3]))
#%% ENU
for ENU in ['E', 'N', 'U']:
print('\nCreate {}'.format(ENU + '.geo'), flush=True)
enutif = glob.glob(os.path.join(geocdir, '*.geo.{}.tif'.format(ENU)))
### Download if not exist
if len(enutif) == 0:
print(' No *.geo.{}.tif found in {}'.format(
ENU, os.path.basename(geocdir)),
flush=True)
if not frameID: ## if frameID not found above
print(' Frame ID cannot be identified from dir name!',
file=sys.stderr)
print(' Use -f option if you need {}.geo'.format(ENU),
file=sys.stderr)
continue
### Download tif
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata',
'{}.geo.{}.tif'.format(frameID, ENU))
enutif = os.path.join(geocdir,
'{}.geo.{}.tif'.format(frameID, ENU))
if not tools_lib.download_data(url, enutif):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
continue
else:
print(' {} dowonloaded from LiCSAR-portal'.format(
os.path.basename(url)),
flush=True)
else:
enutif = enutif[0] ## first one
### Create float
data = gdal.Open(enutif).ReadAsArray()
data[data == 0] = np.nan
if nlook != 1:
### Multilook
data = tools_lib.multilook(data, nlook, nlook)
outfile = os.path.join(outdir, ENU + '.geo')
data.tofile(outfile)
print(' {}.geo created'.format(ENU), flush=True)
#%% mli
mlitif = os.path.join(geocdir, '{}.geo.mli.tif'.format(frameID))
if os.path.exists(mlitif):
print('\nCreate slc.mli', flush=True)
mli = gdal.Open(mlitif).ReadAsArray()
mli[mli == 0] = np.nan
if nlook != 1:
### Multilook
mli = tools_lib.multilook(mli, nlook, nlook)
mlifile = os.path.join(outdir, 'slc.mli')
mli.tofile(mlifile)
mlipngfile = mlifile + '.png'
vmin = np.nanpercentile(mli, 5)
vmax = np.nanpercentile(mli, 95)
plot_lib.make_im_png(mli,
mlipngfile,
'gray',
'MLI',
vmin,
vmax,
cbar=True)
print(' slc.mli[.png] created', flush=True)
#%% hgt
hgttif = os.path.join(geocdir, '{}.geo.hgt.tif'.format(frameID))
if os.path.exists(hgttif):
print('\nCreate hgt', flush=True)
hgt = gdal.Open(hgttif).ReadAsArray()
hgt[hgt == 0] = np.nan
if nlook != 1:
### Multilook
hgt = tools_lib.multilook(hgt, nlook, nlook)
hgtfile = os.path.join(outdir, 'hgt')
hgt.tofile(hgtfile)
hgtpngfile = hgtfile + '.png'
vmax = np.nanpercentile(hgt, 99)
vmin = -vmax / 3 ## bnecause 1/4 of terrain is blue
plot_lib.make_im_png(hgt,
hgtpngfile,
'terrain',
'DEM (m)',
vmin,
vmax,
cbar=True)
print(' hgt[.png] created', flush=True)
#%% tif -> float (with multilook/downsampling)
print('\nCreate unw and cc', flush=True)
ifgdates = tools_lib.get_ifgdates(geocdir)
n_ifg = len(ifgdates)
### First check if float already exist
ifgdates2 = []
for i, ifgd in enumerate(ifgdates):
ifgdir1 = os.path.join(outdir, ifgd)
unwfile = os.path.join(ifgdir1, ifgd + '.unw')
ccfile = os.path.join(ifgdir1, ifgd + '.cc')
if not (os.path.exists(unwfile) and os.path.exists(ccfile)):
ifgdates2.append(ifgd)
n_ifg2 = len(ifgdates2)
if n_ifg - n_ifg2 > 0:
print(" {0:3}/{1:3} unw and cc already exist. Skip".format(
n_ifg - n_ifg2, n_ifg),
flush=True)
### Create
for i, ifgd in enumerate(ifgdates2):
if np.mod(i, 10) == 0:
print(" {0:3}/{1:3}th IFG...".format(i, n_ifg2), flush=True)
unw_tiffile = os.path.join(geocdir, ifgd, ifgd + '.geo.unw.tif')
cc_tiffile = os.path.join(geocdir, ifgd, ifgd + '.geo.cc.tif')
### Check if inputs exist
if not os.path.exists(unw_tiffile):
print(' No {} found. Skip'.format(ifgd + '.geo.unw.tif'),
flush=True)
with open(no_unw_list, 'a') as f:
print('{}'.format(ifgd), file=f)
continue
elif not os.path.exists(cc_tiffile):
print(' No {} found. Skip'.format(ifgd + '.geo.cc.tif'),
flush=True)
with open(no_unw_list, 'a') as f:
print('{}'.format(ifgd), file=f)
continue
### Output dir and files
ifgdir1 = os.path.join(outdir, ifgd)
if not os.path.exists(ifgdir1): os.mkdir(ifgdir1)
unwfile = os.path.join(ifgdir1, ifgd + '.unw')
ccfile = os.path.join(ifgdir1, ifgd + '.cc')
### Read data from geotiff
try:
unw = gdal.Open(unw_tiffile).ReadAsArray()
unw[unw == 0] = np.nan
except: ## if broken
print(' {} cannot open. Skip'.format(ifgd + '.geo.unw.tif'),
flush=True)
with open(no_unw_list, 'a') as f:
print('{}'.format(ifgd), file=f)
shutil.rmtree(ifgdir1)
continue
try:
cc = gdal.Open(cc_tiffile).ReadAsArray()
#if cc.dtype == np.uint8: ## New format since 201910
#cc = cc.astype(np.float32)/255
#cc[cc==0] = np.nan
except: ## if broken
print(' {} cannot open. Skip'.format(ifgd + '.geo.cc.tif'),
flush=True)
with open(no_unw_list, 'a') as f:
print('{}'.format(ifgd), file=f)
shutil.rmtree(ifgdir1)
continue
### Read info (only once)
## If all float already exist, this is not done, but no problem because
## par files should alerady be exits!
if not 'length' in locals():
geotiff = gdal.Open(unw_tiffile)
width = geotiff.RasterXSize
length = geotiff.RasterYSize
lon_w_p, dlon, _, lat_n_p, _, dlat = geotiff.GetGeoTransform()
## lat lon are in pixel registration. dlat is negative
lon_w_g = lon_w_p + dlon / 2
lat_n_g = lat_n_p + dlat / 2
## to grit registration by shifting half pixel inside
if nlook != 1:
width = int(width / nlook)
length = int(length / nlook)
dlon = dlon * nlook
dlat = dlat * nlook
### Multilook
if nlook != 1:
unw = tools_lib.multilook(unw, nlook, nlook, n_valid_thre)
cc = cc.astype(np.float32)
cc[cc == 0] = np.nan
cc = tools_lib.multilook(cc, nlook, nlook, n_valid_thre)
cc = cc.astype(np.uint8) ##nan->0, max255, auto-floored
### Output float
unw.tofile(unwfile)
cc.tofile(ccfile)
### Make png
unwpngfile = os.path.join(ifgdir1, ifgd + '.unw.png')
plot_lib.make_im_png(np.angle(np.exp(1j * unw / cycle) * cycle),
unwpngfile,
cmap,
ifgd + '.unw',
vmin=-np.pi,
vmax=np.pi,
cbar=False)
#%% EQA.dem_par, slc.mli.par
if not os.path.exists(mlipar):
print('\nCreate slc.mli.par', flush=True)
radar_freq = 5.405e9 ## fixed for Sentnel-1
with open(mlipar, 'w') as f:
print('range_samples: {}'.format(width), file=f)
print('azimuth_lines: {}'.format(length), file=f)
print('radar_frequency: {} Hz'.format(radar_freq), file=f)
if center_time is not None:
print('center_time: {}'.format(center_time), file=f)
if not os.path.exists(dempar):
print('\nCreate EQA.dem_par', flush=True)
text = [
"Gamma DIFF&GEO DEM/MAP parameter file", "title: DEM",
"DEM_projection: EQA", "data_format: REAL*4",
"DEM_hgt_offset: 0.00000",
"DEM_scale: 1.00000", "width: {}".format(width),
"nlines: {}".format(length),
"corner_lat: {} decimal degrees".format(lat_n_g),
"corner_lon: {} decimal degrees".format(lon_w_g),
"post_lat: {} decimal degrees".format(dlat),
"post_lon: {} decimal degrees".format(dlon), "",
"ellipsoid_name: WGS 84", "ellipsoid_ra: 6378137.000 m",
"ellipsoid_reciprocal_flattening: 298.2572236", "",
"datum_name: WGS 1984", "datum_shift_dx: 0.000 m",
"datum_shift_dy: 0.000 m",
"datum_shift_dz: 0.000 m",
"datum_scale_m: 0.00000e+00",
"datum_rotation_alpha: 0.00000e+00 arc-sec",
"datum_rotation_beta: 0.00000e+00 arc-sec",
"datum_rotation_gamma: 0.00000e+00 arc-sec",
"datum_country_list: Global Definition, WGS84, World\n"
]
with open(dempar, 'w') as f:
f.write('\n'.join(text))
#%% bperp
print('\nCopy baselines file', flush=True)
imdates = tools_lib.ifgdates2imdates(ifgdates)
if os.path.exists(bperp_file_in):
## Check exisiting bperp_file
if not io_lib.read_bperp_file(bperp_file_in, imdates):
print(' baselines file found, but not complete. Make dummy',
flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
else:
shutil.copyfile(bperp_file_in, bperp_file_out)
else:
print(' No valid baselines exists.', flush=True)
if not frameID: ## if frameID not found above
print(' Frame ID cannot be identified from dir name!')
print(' Make dummy.', flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
else:
print(' Try download.', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata',
'baselines')
if not tools_lib.download_data(url, bperp_file_out):
print(
' Error while downloading from {}.\n Make dummy.'.format(
url),
file=sys.stderr,
flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
else:
print(' {} dowonloaded from LiCSAR-portal'.format(
os.path.basename(url)),
flush=True)
if not io_lib.read_bperp_file(bperp_file_out, imdates):
print(' but not complete. Make dummy.', flush=True)
io_lib.make_dummy_bperp(bperp_file_out, imdates)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(outdir)))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = 1.0
date = 20200225
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
ifgfile = []
bperpfile = []
pngfile = 'network.png'
bad_ifgfile = []
plot_bad_flag = True
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hi:b:o:r:",
["help", "not_plot_bad"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-i':
ifgfile = a
elif o == '-b':
bperpfile = a
elif o == '-o':
pngfile = a
elif o == '-r':
bad_ifgfile = a
elif o == '--not_plot_bad':
plot_bad_flag = False
if not ifgfile:
raise Usage('No ifg list given, -i is not optional!')
elif not os.path.exists(ifgfile):
raise Usage('No {} exists!'.format(ifgfile))
elif not bperpfile:
raise Usage('No bperp list given, -b is not optional!')
elif not os.path.exists(bperpfile):
raise Usage('No {} exists!'.format(bperpfile))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Read info
ifgdates = io_lib.read_ifg_list(ifgfile)
imdates = tools_lib.ifgdates2imdates(ifgdates)
bperp = io_lib.read_bperp_file(bperpfile, imdates)
if bad_ifgfile:
bad_ifgdates = io_lib.read_ifg_list(bad_ifgfile)
else:
bad_ifgdates = []
#%% Plot image
plot_lib.plot_network(ifgdates, bperp, bad_ifgdates, pngfile,
plot_bad_flag)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output: {}\n'.format(pngfile), flush=True)
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
ifgdir = []
tsadir = []
refflag = 'auto' ## not supported
inv_alg = 'LS'
n_core = 1
memory_size = 4000
gamma = 0.0001
n_unw_r_thre = []
keep_incfile = False
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hd:t:r:", [
"help", "mem_size=", "gamma=", "n_unw_r_thre=", "keep_incfile",
"inv_alg=", "n_core="
])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-d':
ifgdir = a
elif o == '-t':
tsadir = a
elif o == '-r':
refflag = a
elif o == '--mem_size':
memory_size = float(a)
elif o == '--gamma':
gamma = float(a)
elif o == '--n_unw_r_thre':
n_unw_r_thre = float(a)
elif o == '--keep_incfile':
keep_incfile = True
elif o == '--inv_alg':
inv_alg = a
elif o == '--n_core':
n_core = int(a)
if not ifgdir:
raise Usage('No data directory given, -d is not optional!')
elif not os.path.isdir(ifgdir):
raise Usage('No {} dir exists!'.format(ifgdir))
elif not os.path.exists(os.path.join(ifgdir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(ifgdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Directory settings
ifgdir = os.path.abspath(ifgdir)
if not tsadir:
tsadir = os.path.join(os.path.dirname(ifgdir),
'TS_' + os.path.basename(ifgdir))
if not os.path.isdir(tsadir):
print('\nNo {} exists!'.format(tsadir), file=sys.stderr)
return 1
tsadir = os.path.abspath(tsadir)
resultsdir = os.path.join(tsadir, 'results')
infodir = os.path.join(tsadir, 'info')
netdir = os.path.join(tsadir, 'network')
bad_ifg11file = os.path.join(infodir, '11bad_ifg.txt')
bad_ifg12file = os.path.join(infodir, '12bad_ifg.txt')
reffile = os.path.join(infodir, 'ref.txt')
incdir = os.path.join(tsadir, '13increment')
if not os.path.exists(incdir): os.mkdir(incdir)
resdir = os.path.join(tsadir, '13resid')
if not os.path.exists(resdir): os.mkdir(resdir)
restxtfile = os.path.join(infodir, '13resid.txt')
cumh5file = os.path.join(tsadir, 'cum.h5')
#%% Check files
try:
if not os.path.exists(bad_ifg11file):
raise Usage('No 11bad_ifg.txt file exists in {}!'.format(tsadir))
if not os.path.exists(bad_ifg12file):
raise Usage('No 12bad_ifg.txt file exists in {}!'.format(tsadir))
if not os.path.exists(reffile):
raise Usage('No ref.txt file exists in {}!'.format(tsadir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Check and set reference
if refflag == 'auto': # Automatic setting based on ref.txt
with open(reffile, "r") as f:
refarea = f.read().split()[0] #str, x1/x2/y1/y2
refx1, refx2, refy1, refy2 = [
int(s) for s in re.split('[:/]', refarea)
]
#%% Read data information
### Get size
mlipar = os.path.join(ifgdir, 'slc.mli.par')
width = int(io_lib.get_param_par(mlipar, 'range_samples'))
length = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
speed_of_light = 299792458 #m/s
radar_frequency = float(io_lib.get_param_par(mlipar,
'radar_frequency')) #Hz
wavelength = speed_of_light / radar_frequency #meter
coef_r2m = -wavelength / 4 / np.pi * 1000 #rad -> mm, positive is -LOS
### Calc pixel spacing depending on IFG or GEOC, used in later spatial filter
dempar = os.path.join(ifgdir, 'EQA.dem_par')
width_geo = int(io_lib.get_param_par(dempar, 'width'))
length_geo = int(io_lib.get_param_par(dempar, 'nlines'))
dlat = float(io_lib.get_param_par(dempar, 'post_lat')) #negative
dlon = float(io_lib.get_param_par(dempar, 'post_lon')) #positive
lat1 = float(io_lib.get_param_par(dempar, 'corner_lat'))
lon1 = float(io_lib.get_param_par(dempar, 'corner_lon'))
if width == width_geo and length == length_geo: ## Geocoded
print('In geographical coordinates', flush=True)
centerlat = lat1 + dlat * (length / 2)
ra = float(io_lib.get_param_par(dempar, 'ellipsoid_ra'))
recip_f = float(
io_lib.get_param_par(dempar, 'ellipsoid_reciprocal_flattening'))
rb = ra * (1 - 1 / recip_f) ## polar radius
pixsp_a = 2 * np.pi * rb / 360 * abs(dlat)
pixsp_r = 2 * np.pi * ra / 360 * dlon * np.cos(np.deg2rad(centerlat))
### Make ref.kml
reflat = lat1 + dlat * refy1
reflon = lon1 + dlon * refx1
make_point_kml(reflat, reflon, os.path.join(infodir, 'ref.kml'))
else:
print('In radar coordinates', flush=True)
pixsp_r_org = float(io_lib.get_param_par(mlipar,
'range_pixel_spacing'))
pixsp_a = float(io_lib.get_param_par(mlipar, 'azimuth_pixel_spacing'))
inc_agl = float(io_lib.get_param_par(mlipar, 'incidence_angle'))
pixsp_r = pixsp_r_org / np.sin(np.deg2rad(inc_agl))
### Set n_unw_r_thre and cycle depending on L- or C-band
if wavelength > 0.2: ## L-band
if not n_unw_r_thre: n_unw_r_thre = 0.5
cycle = 1.5 # 2pi/cycle for comparison png
elif wavelength <= 0.2: ## C-band
if not n_unw_r_thre: n_unw_r_thre = 1.0
cycle = 3 # 3*2pi/cycle for comparison png
#%% Read date and network information
### Get all ifgdates in ifgdir
ifgdates_all = tools_lib.get_ifgdates(ifgdir)
imdates_all = tools_lib.ifgdates2imdates(ifgdates_all)
n_im_all = len(imdates_all)
n_ifg_all = len(ifgdates_all)
### Read bad_ifg11 and 12
bad_ifg11 = io_lib.read_ifg_list(bad_ifg11file)
bad_ifg12 = io_lib.read_ifg_list(bad_ifg12file)
bad_ifg_all = list(set(bad_ifg11 + bad_ifg12))
bad_ifg_all.sort()
### Remove bad ifgs and images from list
ifgdates = list(set(ifgdates_all) - set(bad_ifg_all))
ifgdates.sort()
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_ifg_bad = len(set(bad_ifg11 + bad_ifg12))
n_im = len(imdates)
n_unw_thre = int(n_unw_r_thre * n_im)
### Make 13used_image.txt
imfile = os.path.join(infodir, '13used_image.txt')
with open(imfile, 'w') as f:
for i in imdates:
print('{}'.format(i), file=f)
### Calc dt in year
imdates_dt = ([
dt.datetime.strptime(imd, '%Y%m%d').toordinal() for imd in imdates
])
dt_cum = np.float32((np.array(imdates_dt) - imdates_dt[0]) / 365.25)
### Construct G and Aloop matrix for increment and n_gap
G = inv_lib.make_sb_matrix(ifgdates)
Aloop = loop_lib.make_loop_matrix(ifgdates)
n_loop = Aloop.shape[0] # (n_loop,n_ifg)
#%% Plot network
## Read bperp data or dummy
bperp_file = os.path.join(ifgdir, 'baselines')
if os.path.exists(bperp_file):
bperp_all = io_lib.read_bperp_file(bperp_file, imdates_all)
bperp = io_lib.read_bperp_file(bperp_file, imdates)
else: #dummy
bperp_all = np.random.random(len(imdates_all)).tolist()
bperp = np.random.random(n_im).tolist()
pngfile = os.path.join(netdir, 'network13_all.png')
plot_lib.plot_network(ifgdates_all, bperp_all, [], pngfile, pdf=True)
pngfile = os.path.join(netdir, 'network13.png')
plot_lib.plot_network(ifgdates_all,
bperp_all,
bad_ifg_all,
pngfile,
pdf=True)
pngfile = os.path.join(netdir, 'network13_nobad.png')
plot_lib.plot_network(ifgdates_all,
bperp_all,
bad_ifg_all,
pngfile,
plot_bad=False,
pdf=True)
#%% Get patch row number
if inv_alg == 'WLS':
n_store_data = n_ifg * 3 + n_im * 2 + n_im * 0.3 #
else:
n_store_data = n_ifg * 2 + n_im * 2 + n_im * 0.3 #not sure
n_patch, patchrow = tools_lib.get_patchrow(width, length, n_store_data,
memory_size)
#%% Display and output settings & paramters
print('')
print('Size of image (w,l) : {}, {}'.format(width, length))
print('# of all images : {}'.format(n_im_all))
print('# of images to be used : {}'.format(n_im))
print('# of all ifgs : {}'.format(n_ifg_all))
print('# of ifgs to be used : {}'.format(n_ifg))
print('# of removed ifgs : {}'.format(n_ifg_bad))
print('Threshold of used unw : {}'.format(n_unw_thre))
print('')
print('Reference area (X/Y) : {}:{}/{}:{}'.format(
refx1, refx2, refy1, refy2))
print('Allowed memory size : {} MB'.format(memory_size))
print('Number of patches : {}'.format(n_patch))
print('Inversion algorism : {}'.format(inv_alg))
print('Gamma value : {}'.format(gamma), flush=True)
with open(os.path.join(infodir, 'parameters.txt'), "w") as f:
print('range_samples: {}'.format(width), file=f)
print('azimuth_lines: {}'.format(length), file=f)
print('wavelength: {}'.format(wavelength), file=f)
print('n_im_all: {}'.format(n_im_all), file=f)
print('n_im: {}'.format(n_im), file=f)
print('n_ifg_all: {}'.format(n_ifg_all), file=f)
print('n_ifg: {}'.format(n_ifg), file=f)
print('n_ifg_bad: {}'.format(n_ifg_bad), file=f)
print('n_unw_thre: {}'.format(n_unw_thre), file=f)
print('ref_area: {}:{}/{}:{}'.format(refx1, refx2, refy1, refy2),
file=f)
print('memory_size: {} MB'.format(memory_size), file=f)
print('n_patch: {}'.format(n_patch), file=f)
print('inv_alg: {}'.format(inv_alg), file=f)
print('gamma: {}'.format(gamma), file=f)
print('pixel_spacing_r: {:.2f} m'.format(pixsp_r), file=f)
print('pixel_spacing_a: {:.2f} m'.format(pixsp_a), file=f)
#%% Ref phase for inversion
lengththis = refy2 - refy1
countf = width * refy1
countl = width * lengththis # Number to be read
ref_unw = []
for i, ifgd in enumerate(ifgdates):
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
f = open(unwfile, 'rb')
f.seek(countf * 4, os.SEEK_SET) #Seek for >=2nd path, 4 means byte
### Read unw data (mm) at ref area
unw = np.fromfile(f, dtype=np.float32, count=countl).reshape(
(lengththis, width))[:, refx1:refx2] * coef_r2m
unw[unw == 0] = np.nan
if np.all(np.isnan(unw)):
print('All nan in ref area in {}.'.format(ifgd))
print('Rerun LiCSBAS12.')
return 1
ref_unw.append(np.nanmean(unw))
f.close()
#%% Open cum.h5 for output
if os.path.exists(cumh5file): os.remove(cumh5file)
cumh5 = h5.File(cumh5file, 'w')
cumh5.create_dataset('imdates', data=[np.int32(imd) for imd in imdates])
cumh5.create_dataset('refarea', data=refarea)
if not np.all(np.abs(np.array(bperp)) <= 1): # if not dummy
cumh5.create_dataset('bperp', data=bperp)
cum = cumh5.require_dataset('cum', (n_im, length, width), dtype=np.float32)
vel = cumh5.require_dataset('vel', (length, width), dtype=np.float32)
vconst = cumh5.require_dataset('vintercept', (length, width),
dtype=np.float32)
gap = cumh5.require_dataset('gap', (n_im - 1, length, width),
dtype=np.int8)
if width == width_geo and length == length_geo: ## if geocoded
cumh5.create_dataset('corner_lat', data=lat1)
cumh5.create_dataset('corner_lon', data=lon1)
cumh5.create_dataset('post_lat', data=dlat)
cumh5.create_dataset('post_lon', data=dlon)
#%% For each patch
i_patch = 1
for rows in patchrow:
print('\nProcess {0}/{1}th line ({2}/{3}th patch)...'.format(
rows[1], patchrow[-1][-1], i_patch, n_patch),
flush=True)
start2 = time.time()
#%% Read data
### Allocate memory
lengththis = rows[1] - rows[0]
n_pt_all = lengththis * width
unwpatch = np.zeros((n_ifg, lengththis, width), dtype=np.float32)
if inv_alg == 'WLS':
cohpatch = np.zeros((n_ifg, lengththis, width), dtype=np.float32)
### For each ifg
print(" Reading {0} ifg's unw data...".format(n_ifg), flush=True)
countf = width * rows[0]
countl = width * lengththis
for i, ifgd in enumerate(ifgdates):
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
f = open(unwfile, 'rb')
f.seek(countf * 4, os.SEEK_SET) #Seek for >=2nd path, 4 means byte
### Read unw data (mm) at patch area
unw = np.fromfile(f, dtype=np.float32, count=countl).reshape(
(lengththis, width)) * coef_r2m
unw[unw == 0] = np.nan # Fill 0 with nan
unw = unw - ref_unw[i]
unwpatch[i] = unw
f.close()
### Read coh file at patch area for WLS
if inv_alg == 'WLS':
cohfile = os.path.join(ifgdir, ifgd, ifgd + '.cc')
f = open(cohfile, 'rb')
f.seek(countf * 4,
os.SEEK_SET) #Seek for >=2nd path, 4 means byte
cohpatch[i, :, :] = np.fromfile(f,
dtype=np.float32,
count=countl).reshape(
(lengththis, width))
unwpatch = unwpatch.reshape(
(n_ifg, n_pt_all)).transpose() #(n_pt_all, n_ifg)
### Calc variance from coherence for WLS
if inv_alg == 'WLS':
cohpatch = cohpatch.reshape(
(n_ifg, n_pt_all)).transpose() #(n_pt_all, n_ifg)
cohpatch[
cohpatch <
0.01] = 0.01 ## because negative value possible due to geocode
cohpatch[
cohpatch > 0.99] = 0.99 ## because >1 possible due to geocode
varpatch = (1 - cohpatch**2) / (2 * cohpatch**2)
del cohpatch
#%% Remove points with less valid data than n_unw_thre
ix_unnan_pt = np.where(
np.sum(~np.isnan(unwpatch), axis=1) > n_unw_thre)[0]
n_pt_unnan = len(ix_unnan_pt)
unwpatch = unwpatch[ix_unnan_pt, :] ## keep only unnan data
if inv_alg == 'WLS':
varpatch = varpatch[ix_unnan_pt, :] ## keep only unnan data
print(' {}/{} points removed due to not enough ifg data...'.format(
n_pt_all - n_pt_unnan, n_pt_all),
flush=True)
#%% Compute number of gaps, ifg_noloop, maxTlen point-by-point
ns_gap_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
gap_patch = np.zeros((n_im - 1, n_pt_all), dtype=np.int8)
ns_ifg_noloop_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
maxTlen_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
### n_gap
print('\n Identifing gaps and counting n_gap...', flush=True)
# ns_unw_unnan4inc = (np.matmul(np.int8(G[:, :, None]), (~np.isnan(unwpatch.T))[:, None, :])).sum(axis=0, dtype=np.int16) #n_ifg, n_im-1, n_pt -> n_im-1, n_pt
ns_unw_unnan4inc = np.array([
(G[:, i] * (~np.isnan(unwpatch))).sum(axis=1, dtype=np.int16)
for i in range(n_im - 1)
]) #n_ifg*(n_pt,n_ifg) -> (n_im-1,n_pt)
ns_gap_patch[ix_unnan_pt] = (ns_unw_unnan4inc == 0).sum(axis=0) #n_pt
gap_patch[:, ix_unnan_pt] = ns_unw_unnan4inc == 0
del ns_unw_unnan4inc
### n_ifg_noloop
print(' Counting n_ifg_noloop...', flush=True)
# n_ifg*(n_pt,n_ifg)->(n_loop,n_pt)
# Number of ifgs for each loop at eath point.
# 3 means complete loop, 1 or 2 means broken loop.
ns_ifg4loop = np.array([
(np.abs(Aloop[i, :]) * (~np.isnan(unwpatch))).sum(axis=1)
for i in range(n_loop)
])
bool_loop = (ns_ifg4loop == 3
) #(n_loop,n_pt) identify complete loop only
# n_loop*(n_loop,n_pt)*n_pt->(n_ifg,n_pt)
# Number of loops for each ifg at eath point.
ns_loop4ifg = np.array([((np.abs(Aloop[:, i]) * bool_loop.T).T *
(~np.isnan(unwpatch[:, i]))).sum(axis=0)
for i in range(n_ifg)]) #
ns_ifg_noloop_tmp = (ns_loop4ifg == 0).sum(axis=0) #n_pt
ns_nan_ifg = np.isnan(unwpatch).sum(axis=1) #n_pt, nan ifg count
ns_ifg_noloop_patch[ix_unnan_pt] = ns_ifg_noloop_tmp - ns_nan_ifg
del bool_loop, ns_ifg4loop, ns_loop4ifg
### maxTlen
_maxTlen = np.zeros((n_pt_unnan), dtype=np.float32) #temporaly
_Tlen = np.zeros((n_pt_unnan), dtype=np.float32) #temporaly
for imx in range(n_im - 1):
_Tlen = _Tlen + (dt_cum[imx + 1] - dt_cum[imx]) ## Adding dt
_Tlen[gap_patch[imx, ix_unnan_pt] == 1] = 0 ## reset to 0 if gap
_maxTlen[_maxTlen < _Tlen] = _Tlen[_maxTlen <
_Tlen] ## Set Tlen to maxTlen
maxTlen_patch[ix_unnan_pt] = _maxTlen
#%% Time series inversion
print('\n Small Baseline inversion by {}...\n'.format(inv_alg),
flush=True)
if inv_alg == 'WLS':
inc_tmp, vel_tmp, vconst_tmp = inv_lib.invert_nsbas_wls(
unwpatch, varpatch, G, dt_cum, gamma, n_core)
else:
inc_tmp, vel_tmp, vconst_tmp = inv_lib.invert_nsbas(
unwpatch, G, dt_cum, gamma, n_core)
### Set to valuables
inc_patch = np.zeros((n_im - 1, n_pt_all), dtype=np.float32) * np.nan
vel_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
vconst_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
inc_patch[:, ix_unnan_pt] = inc_tmp
vel_patch[ix_unnan_pt] = vel_tmp
vconst_patch[ix_unnan_pt] = vconst_tmp
### Calculate residuals
res_patch = np.zeros((n_ifg, n_pt_all), dtype=np.float32) * np.nan
res_patch[:, ix_unnan_pt] = unwpatch.T - np.dot(G, inc_tmp)
res_sumsq = np.nansum(res_patch**2, axis=0)
res_n = np.float32((~np.isnan(res_patch)).sum(axis=0))
res_n[res_n == 0] = np.nan # To avoid 0 division
res_rms_patch = np.sqrt(res_sumsq / res_n)
### Cumulative displacememt
cum_patch = np.zeros((n_im, n_pt_all), dtype=np.float32) * np.nan
cum_patch[1:, :] = np.cumsum(inc_patch, axis=0)
## Fill 1st image with 0 at unnan points from 2nd images
bool_unnan_pt = ~np.isnan(cum_patch[1, :])
cum_patch[0, bool_unnan_pt] = 0
## Drop (fill with nan) interpolated cum by 2 continuous gaps
for i in range(n_im - 2): ## from 1->n_im-1
gap2 = gap_patch[i, :] + gap_patch[i + 1, :]
bool_gap2 = (gap2 == 2
) ## true if 2 continuous gaps for each point
cum_patch[i + 1, :][bool_gap2] = np.nan
## Last (n_im th) image. 1 gap means interpolated
cum_patch[-1, :][gap_patch[-1, :] == 1] = np.nan
#%% Output data and image
### cum.h5 file
cum[:, rows[0]:rows[1], :] = cum_patch.reshape(
(n_im, lengththis, width))
vel[rows[0]:rows[1], :] = vel_patch.reshape((lengththis, width))
vconst[rows[0]:rows[1], :] = vconst_patch.reshape((lengththis, width))
gap[:, rows[0]:rows[1], :] = gap_patch.reshape(
(n_im - 1, lengththis, width))
### Others
openmode = 'w' if rows[0] == 0 else 'a' #w only 1st patch
## For each imd. cum and inc
for imx, imd in enumerate(imdates):
## Incremental displacement
if imd == imdates[-1]: continue #skip last
incfile = os.path.join(incdir,
'{0}_{1}.inc'.format(imd, imdates[imx + 1]))
with open(incfile, openmode) as f:
inc_patch[imx, :].tofile(f)
## For each ifgd. resid
for i, ifgd in enumerate(ifgdates):
resfile = os.path.join(resdir, '{0}.res'.format(ifgd))
with open(resfile, openmode) as f:
res_patch[i, :].tofile(f)
## velocity and noise indecies in results dir
names = [
'vel', 'vintercept', 'resid_rms', 'n_gap', 'n_ifg_noloop',
'maxTlen'
]
data = [
vel_patch, vconst_patch, res_rms_patch, ns_gap_patch,
ns_ifg_noloop_patch, maxTlen_patch
]
for i in range(len(names)):
file = os.path.join(resultsdir, names[i])
with open(file, openmode) as f:
data[i].tofile(f)
#%% Finish patch
elapsed_time2 = int(time.time() - start2)
hour2 = int(elapsed_time2 / 3600)
minite2 = int(np.mod((elapsed_time2 / 60), 60))
sec2 = int(np.mod(elapsed_time2, 60))
print(" Elapsed time for {0}th patch: {1:02}h {2:02}m {3:02}s".format(
i_patch, hour2, minite2, sec2),
flush=True)
i_patch += 1 #Next patch count
#%% Close h5 file
cumh5.close()
#%% Output png images
print('\nOutput png images...', flush=True)
### Incremental displacement
for imx, imd in enumerate(imdates):
if imd == imdates[-1]: continue #skip last for increment
## Comparison of increment and daisy chain pair
ifgd = '{}_{}'.format(imd, imdates[imx + 1])
incfile = os.path.join(incdir, '{}.inc'.format(ifgd))
unwfile = os.path.join(ifgdir, ifgd, '{}.unw'.format(ifgd))
pngfile = os.path.join(incdir, '{}.inc_comp.png'.format(ifgd))
inc = io_lib.read_img(incfile, length, width)
try:
unw = io_lib.read_img(unwfile, length, width) * coef_r2m
ix_ifg = ifgdates.index(ifgd)
unw = unw - ref_unw[ix_ifg]
except:
unw = np.zeros((length, width), dtype=np.float32) * np.nan
### Output png for comparison
data3 = [
np.angle(np.exp(1j * (data / coef_r2m / cycle)) * cycle)
for data in [unw, inc, inc - unw]
]
title3 = ['Daisy-chain IFG', 'Inverted', 'Difference']
pngfile = os.path.join(incdir, '{}.increment.png'.format(ifgd))
plot_lib.make_3im_png(data3,
pngfile,
'insar',
title3,
vmin=-np.pi,
vmax=np.pi,
cbar=False)
if not keep_incfile:
os.remove(incfile)
### Residual for each ifg. png and txt.
cmap = 'jet'
with open(restxtfile, "w") as f:
print('# RMS of residual (mm)', file=f)
for ifgd in ifgdates:
infile = os.path.join(resdir, '{}.res'.format(ifgd))
resid = io_lib.read_img(infile, length, width)
resid_rms = np.sqrt(np.nanmean(resid**2))
with open(restxtfile, "a") as f:
print('{} {:5.2f}'.format(ifgd, resid_rms), file=f)
pngfile = infile + '.png'
title = 'Residual (mm) of {} (RMS:{:.2f}mm)'.format(ifgd, resid_rms)
plot_lib.make_im_png(resid, pngfile, cmap, title,
-wavelength / 2 * 1000, wavelength / 2 * 1000)
if not keep_incfile:
os.remove(infile)
### Velocity and noise indices
#names = ['vel', 'vconst', 'resid_rms', 'n_gap', 'n_ifg_noloop', 'maxTlen']
cmins = [None, None, None, None, None, None]
cmaxs = [None, None, None, None, None, None]
cmaps = ['jet', 'jet', 'viridis_r', 'viridis_r', 'viridis_r', 'viridis']
titles = [
'Velocity (mm/yr)', 'Intercept of velocity (mm)',
'RMS of residual (mm)', 'Number of gaps in SB network',
'Number of ifgs with no loops',
'Max length of connected SB network (yr)'
]
for i in range(len(names)):
file = os.path.join(resultsdir, names[i])
data = io_lib.read_img(file, length, width)
pngfile = file + '.png'
## Get color range if None
if cmins[i] is None:
cmins[i] = np.nanpercentile(data, 1)
if cmaxs[i] is None:
cmaxs[i] = np.nanpercentile(data, 99)
if cmins[i] == cmaxs[i]: cmins[i] = cmaxs[i] - 1
plot_lib.make_im_png(data, pngfile, cmaps[i], titles[i], cmins[i],
cmaxs[i])
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(tsadir)))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
#%% Set default
frameID = []
startdate = 20141001
enddate = int(dt.date.today().strftime("%Y%m%d"))
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hf:s:e:", ["help"])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-f':
frameID = a
elif o == '-s':
startdate = int(a)
elif o == '-e':
enddate = int(a)
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Determine frameID
wd = os.getcwd()
if not frameID: ## if frameID not indicated
_tmp = re.findall(r'\d{3}[AD]_\d{5}_\d{6}', wd)
##e.g., 021D_04972_131213
if len(_tmp) == 0:
print('\nFrame ID cannot be identified from dir name!',
file=sys.stderr)
print('Use -f option', file=sys.stderr)
return
else:
frameID = _tmp[0]
print('\nFrame ID is {}\n'.format(frameID), flush=True)
trackID = str(int(frameID[0:3]))
#%% Directory and file setting
outdir = os.path.join(wd, 'GEOC')
if not os.path.exists(outdir): os.mkdir(outdir)
os.chdir(outdir)
LiCSARweb = 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/'
#%% ENU
for ENU in ['E', 'N', 'U']:
enutif = '{}.geo.{}.tif'.format(frameID, ENU)
if os.path.exists(enutif):
print('{} already exist. Skip download.'.format(enutif),
flush=True)
continue
print('Download {}'.format(enutif), flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', enutif)
if not tools_lib.download_data(url, enutif):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
continue
#%% baselines
print('Download baselines', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'metadata', 'baselines')
if not tools_lib.download_data(url, 'baselines'):
print(' Error while downloading from {}'.format(url),
file=sys.stderr,
flush=True)
#%% unw and cc
### Get available dates
print('\nDownload geotiff of unw and cc', flush=True)
url = os.path.join(LiCSARweb, trackID, frameID, 'products')
response = requests.get(url)
response.encoding = response.apparent_encoding #avoid garble
html_doc = response.text
soup = BeautifulSoup(html_doc, "html.parser")
tags = soup.find_all(href=re.compile(r"\d{8}_\d{8}"))
ifgdates_all = [tag.get("href")[0:17] for tag in tags]
### Extract during start_date to end_date
ifgdates = []
for ifgd in ifgdates_all:
mimd = int(ifgd[:8])
simd = int(ifgd[-8:])
if mimd >= startdate and simd <= enddate:
ifgdates.append(ifgd)
n_ifg = len(ifgdates)
imdates = tools_lib.ifgdates2imdates(ifgdates)
print('{} IFGs available from {} to {}'.format(n_ifg, imdates[0],
imdates[-1]),
flush=True)
### Download
for i, ifgd in enumerate(ifgdates):
print(' Donwnloading {} ({}/{})...'.format(ifgd, i + 1, n_ifg),
flush=True)
url_unw = os.path.join(url, ifgd, ifgd + '.geo.unw.tif')
path_unw = os.path.join(ifgd, ifgd + '.geo.unw.tif')
if not os.path.exists(ifgd): os.mkdir(ifgd)
if os.path.exists(path_unw):
print(' {}.geo.unw.tif already exist. Skip'.format(ifgd),
flush=True)
elif not tools_lib.download_data(url_unw, path_unw):
print(' Error while downloading from {}'.format(url_unw),
file=sys.stderr,
flush=True)
url_cc = os.path.join(url, ifgd, ifgd + '.geo.cc.tif')
path_cc = os.path.join(ifgd, ifgd + '.geo.cc.tif')
if os.path.exists(path_cc):
print(' {}.geo.cc.tif already exist. Skip.'.format(ifgd),
flush=True)
if not tools_lib.download_data(url_cc, path_cc):
print(' Error while downloading from {}'.format(url_cc),
file=sys.stderr,
flush=True)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(outdir))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = 1.3
date = 20200907
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
global Aloop, ifgdates, ifgdir, length, width, loop_pngdir ## for parallel processing
#%% Set default
ifgdir = []
tsadir = []
loop_thre = 1.5
n_para = len(os.sched_getaffinity(0))
cmap_noise = 'viridis'
cmap_noise_r = 'viridis_r'
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hd:t:l:",
["help", "n_para="])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-d':
ifgdir = a
elif o == '-t':
tsadir = a
elif o == '-l':
loop_thre = float(a)
elif o == '--n_para':
n_para = int(a)
if not ifgdir:
raise Usage('No data directory given, -d is not optional!')
elif not os.path.isdir(ifgdir):
raise Usage('No {} dir exists!'.format(ifgdir))
elif not os.path.exists(os.path.join(ifgdir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(ifgdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
print("\nloop_thre : {} rad".format(loop_thre), flush=True)
#%% Directory setting
ifgdir = os.path.abspath(ifgdir)
if not tsadir:
tsadir = os.path.join(os.path.dirname(ifgdir),
'TS_' + os.path.basename(ifgdir))
if not os.path.isdir(tsadir):
print('\nNo {} exists!'.format(tsadir), file=sys.stderr)
return 1
tsadir = os.path.abspath(tsadir)
loopdir = os.path.join(tsadir, '12loop')
if not os.path.exists(loopdir): os.mkdir(loopdir)
loop_pngdir = os.path.join(loopdir, 'good_loop_png')
bad_loop_pngdir = os.path.join(loopdir, 'bad_loop_png')
bad_loop_cand_pngdir = os.path.join(loopdir, 'bad_loop_cand_png')
if os.path.exists(loop_pngdir):
shutil.move(loop_pngdir + '/', loop_pngdir + '_old') #move to old dir
if os.path.exists(bad_loop_pngdir):
for png in glob.glob(bad_loop_pngdir + '/*.png'):
shutil.move(png, loop_pngdir + '_old') #move to old dir
shutil.rmtree(bad_loop_pngdir)
if os.path.exists(bad_loop_cand_pngdir):
for png in glob.glob(bad_loop_cand_pngdir + '/*.png'):
shutil.move(png, loop_pngdir + '_old') #move to old dir
shutil.rmtree(bad_loop_cand_pngdir)
os.mkdir(loop_pngdir)
os.mkdir(bad_loop_pngdir)
os.mkdir(bad_loop_cand_pngdir)
ifg_rasdir = os.path.join(tsadir, '12ifg_ras')
if os.path.isdir(ifg_rasdir): shutil.rmtree(ifg_rasdir)
os.mkdir(ifg_rasdir)
bad_ifgrasdir = os.path.join(tsadir, '12bad_ifg_ras')
if os.path.isdir(bad_ifgrasdir): shutil.rmtree(bad_ifgrasdir)
os.mkdir(bad_ifgrasdir)
bad_ifg_candrasdir = os.path.join(tsadir, '12bad_ifg_cand_ras')
if os.path.isdir(bad_ifg_candrasdir): shutil.rmtree(bad_ifg_candrasdir)
os.mkdir(bad_ifg_candrasdir)
no_loop_ifgrasdir = os.path.join(tsadir, '12no_loop_ifg_ras')
if os.path.isdir(no_loop_ifgrasdir): shutil.rmtree(no_loop_ifgrasdir)
os.mkdir(no_loop_ifgrasdir)
infodir = os.path.join(tsadir, 'info')
if not os.path.exists(infodir): os.mkdir(infodir)
resultsdir = os.path.join(tsadir, 'results')
if not os.path.exists(resultsdir): os.mkdir(resultsdir)
netdir = os.path.join(tsadir, 'network')
#%% Read date, network information and size
### Get dates
ifgdates = tools_lib.get_ifgdates(ifgdir)
### Read bad_ifg11
bad_ifg11file = os.path.join(infodir, '11bad_ifg.txt')
bad_ifg11 = io_lib.read_ifg_list(bad_ifg11file)
### Remove bad ifgs and images from list
ifgdates = list(set(ifgdates) - set(bad_ifg11))
ifgdates.sort()
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_im = len(imdates)
### Get size
mlipar = os.path.join(ifgdir, 'slc.mli.par')
width = int(io_lib.get_param_par(mlipar, 'range_samples'))
length = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
### Get loop matrix
Aloop = loop_lib.make_loop_matrix(ifgdates)
n_loop = Aloop.shape[0]
### Extract no loop ifgs
ns_loop4ifg = np.abs(Aloop).sum(axis=0)
ixs_ifg_no_loop = np.where(ns_loop4ifg == 0)[0]
no_loop_ifg = [ifgdates[ix] for ix in ixs_ifg_no_loop]
#%% 1st loop closure check. First without reference
print('\n1st Loop closure check and make png for all possible {} loops,'.
format(n_loop),
flush=True)
print('with {} parallel processing...'.format(n_para), flush=True)
bad_ifg_cand = []
good_ifg = []
### Parallel processing
p = multi.Pool(n_para)
loop_ph_rms_ifg = np.array(p.map(loop_closure_1st_wrapper, range(n_loop)),
dtype=object)
p.close()
for i in range(n_loop):
### Find index of ifg
ix_ifg12, ix_ifg23 = np.where(Aloop[i, :] == 1)[0]
ix_ifg13 = np.where(Aloop[i, :] == -1)[0][0]
ifgd12 = ifgdates[ix_ifg12]
ifgd23 = ifgdates[ix_ifg23]
ifgd13 = ifgdates[ix_ifg13]
### List as good or bad candidate
if loop_ph_rms_ifg[i] >= loop_thre: #Bad loop including bad ifg.
bad_ifg_cand.extend([ifgd12, ifgd23, ifgd13])
else:
good_ifg.extend([ifgd12, ifgd23, ifgd13])
if os.path.exists(loop_pngdir + '_old/'):
shutil.rmtree(loop_pngdir + '_old/')
#%% Identify bad ifgs and output text
bad_ifg = loop_lib.identify_bad_ifg(bad_ifg_cand, good_ifg)
bad_ifgfile = os.path.join(loopdir, 'bad_ifg_loop.txt')
with open(bad_ifgfile, 'w') as f:
for i in bad_ifg:
print('{}'.format(i), file=f)
### Compute n_unw without bad_ifg11 and bad_ifg
n_unw = np.zeros((length, width), dtype=np.int16)
for ifgd in ifgdates:
if ifgd in bad_ifg:
continue
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
unw = io_lib.read_img(unwfile, length, width)
unw[unw == 0] = np.nan # Fill 0 with nan
n_unw += ~np.isnan(unw) # Summing number of unnan unw
#%% 2nd loop closure check without bad ifgs to define stable ref area
print('\n2nd Loop closure check without bad ifgs to define ref area...',
flush=True)
ns_loop_ph = np.zeros((length, width), dtype=np.float32)
ns_bad_loop = np.zeros((length, width), dtype=np.int16)
loop_ph_rms_points = np.zeros((length, width), dtype=np.float32)
for i in range(n_loop):
if np.mod(i, 100) == 0:
print(" {0:3}/{1:3}th loop...".format(i, n_loop), flush=True)
### Read unw
unw12, unw23, unw13, ifgd12, ifgd23, ifgd13 = loop_lib.read_unw_loop_ph(
Aloop[i, :], ifgdates, ifgdir, length, width)
### Skip if bad ifg is included
if ifgd12 in bad_ifg or ifgd23 in bad_ifg or ifgd13 in bad_ifg:
continue
## Calculate loop phase and rms at points
loop_ph = unw12 + unw23 - unw13
loop_2pin = int(np.round(np.nanmedian(loop_ph) /
(2 * np.pi))) * 2 * np.pi
loop_ph = loop_ph - loop_2pin #unbias
ns_loop_ph = ns_loop_ph + ~np.isnan(loop_ph)
loop_ph_sq = loop_ph**2
loop_ph_sq[np.isnan(loop_ph_sq)] = 0
loop_ph_rms_points = loop_ph_rms_points + loop_ph_sq
ns_bad_loop = ns_bad_loop + (loop_ph_sq > np.pi**2
) #suspected unw error
# ns_bad_loop = ns_bad_loop+(np.abs(loop_ph)>loop_thre)
## multiple nan seem to generate RuntimeWarning
ns_loop_ph[ns_loop_ph == 0] = np.nan # To avoid 0 division
loop_ph_rms_points = np.sqrt(loop_ph_rms_points / ns_loop_ph)
### Find stable ref area which have all n_unw and minimum ns_bad_loop and loop_ph_rms_points
mask1 = (n_unw == np.nanmax(n_unw))
min_ns_bad_loop = np.nanmin(ns_bad_loop)
while True:
mask2 = (ns_bad_loop == min_ns_bad_loop)
if np.all(~(mask1 * mask2)): ## All masked
min_ns_bad_loop = min_ns_bad_loop + 1 ## Make mask2 again
else:
break
loop_ph_rms_points_masked = loop_ph_rms_points * mask1 * mask2
loop_ph_rms_points_masked[loop_ph_rms_points_masked == 0] = np.nan
refyx = np.where(
loop_ph_rms_points_masked == np.nanmin(loop_ph_rms_points_masked))
refy1 = refyx[0][0] # start from 0, not 1
refy2 = refyx[0][
0] + 1 # shift +1 for python custom. start from 1 end with width
refx1 = refyx[1][0]
refx2 = refyx[1][0] + 1
### Save 12ref.txt
reffile = os.path.join(infodir, '12ref.txt')
with open(reffile, 'w') as f:
print('{0}:{1}/{2}:{3}'.format(refx1, refx2, refy1, refy2), file=f)
### Save loop_ph_rms_masked and png
loop_ph_rms_maskedfile = os.path.join(loopdir, 'loop_ph_rms_masked')
loop_ph_rms_points_masked.tofile(loop_ph_rms_maskedfile)
cmax = np.nanpercentile(loop_ph_rms_points_masked, 95)
pngfile = loop_ph_rms_maskedfile + '.png'
title = 'RMS of loop phase (rad)'
plot_lib.make_im_png(loop_ph_rms_points_masked, pngfile, cmap_noise_r,
title, None, cmax)
### Check ref exist in unw. If not, list as noref_ifg
noref_ifg = []
for ifgd in ifgdates:
if ifgd in bad_ifg:
continue
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
unw_ref = io_lib.read_img(unwfile, length, width)[refy1:refy2,
refx1:refx2]
unw_ref[unw_ref == 0] = np.nan # Fill 0 with nan
if np.all(np.isnan(unw_ref)):
noref_ifg.append(ifgd)
bad_ifgfile = os.path.join(loopdir, 'bad_ifg_noref.txt')
with open(bad_ifgfile, 'w') as f:
for i in noref_ifg:
print('{}'.format(i), file=f)
#%% 3rd loop closure check without bad ifgs wrt ref point
print('\n3rd loop closure check taking into account ref phase...',
flush=True)
bad_ifg_cand2 = []
good_ifg2 = []
loop_ph_rms_ifg2 = []
for i in range(n_loop):
if np.mod(i, 100) == 0:
print(" {0:3}/{1:3}th loop...".format(i, n_loop), flush=True)
### Read unw
unw12, unw23, unw13, ifgd12, ifgd23, ifgd13 = loop_lib.read_unw_loop_ph(
Aloop[i, :], ifgdates, ifgdir, length, width)
### Skip if bad ifg is included
if ifgd12 in bad_ifg or ifgd23 in bad_ifg or ifgd13 in bad_ifg:
loop_ph_rms_ifg2.append('--')
continue
### Skip if noref ifg is included
if ifgd12 in noref_ifg or ifgd23 in noref_ifg or ifgd13 in noref_ifg:
loop_ph_rms_ifg2.append('--')
continue
## Skip if no data in ref area in any unw. It is bad data.
ref_unw12 = np.nanmean(unw12[refy1:refy2, refx1:refx2])
ref_unw23 = np.nanmean(unw23[refy1:refy2, refx1:refx2])
ref_unw13 = np.nanmean(unw13[refy1:refy2, refx1:refx2])
## Calculate loop phase taking into account ref phase
loop_ph = unw12 + unw23 - unw13 - (ref_unw12 + ref_unw23 - ref_unw13)
loop_ph_rms_ifg2.append(np.sqrt(np.nanmean((loop_ph)**2)))
### List as good or bad candidate
if loop_ph_rms_ifg2[i] >= loop_thre: #Bad loop including bad ifg.
bad_ifg_cand2.extend([ifgd12, ifgd23, ifgd13])
else:
good_ifg2.extend([ifgd12, ifgd23, ifgd13])
#%% Identify additional bad ifgs and output text
bad_ifg2 = loop_lib.identify_bad_ifg(bad_ifg_cand2, good_ifg2)
bad_ifgfile = os.path.join(loopdir, 'bad_ifg_loopref.txt')
with open(bad_ifgfile, 'w') as f:
for i in bad_ifg2:
print('{}'.format(i), file=f)
#%% Output all bad ifg list and identify remaining candidate of bad ifgs
### Merge bad ifg, bad_ifg2, noref_ifg
bad_ifg_all = list(set(bad_ifg + bad_ifg2 + noref_ifg)) # Remove multiple
bad_ifg_all.sort()
ifgdates_good = list(set(ifgdates) - set(bad_ifg_all))
ifgdates_good.sort()
bad_ifgfile = os.path.join(infodir, '12bad_ifg.txt')
with open(bad_ifgfile, 'w') as f:
for i in bad_ifg_all:
print('{}'.format(i), file=f)
### Identify removed image and output file
imdates_good = tools_lib.ifgdates2imdates(ifgdates_good)
imdates_bad = list(set(imdates) - set(imdates_good))
imdates_bad.sort()
bad_imfile = os.path.join(infodir, '12removed_image.txt')
with open(bad_imfile, 'w') as f:
for i in imdates_bad:
print('{}'.format(i), file=f)
### Remaining candidate of bad ifg
bad_ifg_cand_res = list(set(bad_ifg_cand2) - set(bad_ifg_all))
bad_ifg_cand_res.sort()
bad_ifg_candfile = os.path.join(infodir, '12bad_ifg_cand.txt')
with open(bad_ifg_candfile, 'w') as f:
for i in bad_ifg_cand_res:
print('{}'.format(i), file=f)
#%% 4th loop to be used to calc n_loop_err and n_ifg_noloop
print('\n4th loop to compute statistics...', flush=True)
ns_loop_err = np.zeros((length, width), dtype=np.int16)
for i in range(n_loop):
if np.mod(i, 100) == 0:
print(" {0:3}/{1:3}th loop...".format(i, n_loop), flush=True)
### Read unw
unw12, unw23, unw13, ifgd12, ifgd23, ifgd13 = loop_lib.read_unw_loop_ph(
Aloop[i, :], ifgdates, ifgdir, length, width)
### Skip if bad ifg is included
if ifgd12 in bad_ifg_all or ifgd23 in bad_ifg_all or ifgd13 in bad_ifg_all:
continue
## Compute ref
ref_unw12 = np.nanmean(unw12[refy1:refy2, refx1:refx2])
ref_unw23 = np.nanmean(unw23[refy1:refy2, refx1:refx2])
ref_unw13 = np.nanmean(unw13[refy1:refy2, refx1:refx2])
## Calculate loop phase taking into account ref phase
loop_ph = unw12 + unw23 - unw13 - (ref_unw12 + ref_unw23 - ref_unw13)
## Count number of loops with suspected unwrap error (>pi)
loop_ph[np.isnan(loop_ph)] = 0 #to avoid warning
ns_loop_err = ns_loop_err + (np.abs(loop_ph) > np.pi
) #suspected unw error
#%% Output loop info, move bad_loop_png
loop_info_file = os.path.join(loopdir, 'loop_info.txt')
f = open(loop_info_file, 'w')
print('# loop_thre: {} rad. *: Removed w/o ref, **: Removed w/ ref'.format(
loop_thre),
file=f)
print('# /: Candidates of bad loops but causative ifgs unidentified',
file=f)
print('# image1 image2 image3 RMS w/oref w/ref', file=f)
for i in range(n_loop):
### Find index of ifg
ix_ifg12, ix_ifg23 = np.where(Aloop[i, :] == 1)[0]
ix_ifg13 = np.where(Aloop[i, :] == -1)[0][0]
ifgd12 = ifgdates[ix_ifg12]
ifgd23 = ifgdates[ix_ifg23]
ifgd13 = ifgdates[ix_ifg13]
imd1 = ifgd12[:8]
imd2 = ifgd23[:8]
imd3 = ifgd23[-8:]
## Move loop_png if bad ifg or bad ifg_cand is included
looppngfile = os.path.join(
loop_pngdir, '{0}_{1}_{2}_loop.png'.format(imd1, imd2, imd3))
badlooppngfile = os.path.join(
bad_loop_pngdir, '{0}_{1}_{2}_loop.png'.format(imd1, imd2, imd3))
badloopcandpngfile = os.path.join(
bad_loop_cand_pngdir,
'{0}_{1}_{2}_loop.png'.format(imd1, imd2, imd3))
badloopflag1 = ' '
badloopflag2 = ' '
if ifgd12 in bad_ifg or ifgd23 in bad_ifg or ifgd13 in bad_ifg:
badloopflag1 = '*'
shutil.move(looppngfile, badlooppngfile)
elif ifgd12 in bad_ifg2 or ifgd23 in bad_ifg2 or ifgd13 in bad_ifg2:
badloopflag2 = '**'
shutil.move(looppngfile, badlooppngfile)
elif ifgd12 in bad_ifg_cand_res or ifgd23 in bad_ifg_cand_res or ifgd13 in bad_ifg_cand_res:
badloopflag1 = '/'
if os.path.exists(looppngfile):
shutil.move(looppngfile, badloopcandpngfile)
if type(loop_ph_rms_ifg2[i]) == np.float32:
str_loop_ph_rms_ifg2 = "{:.2f}".format(loop_ph_rms_ifg2[i])
else: ## --
str_loop_ph_rms_ifg2 = loop_ph_rms_ifg2[i]
print('{0} {1} {2} {3:5.2f} {4} {5:5s} {6}'.format(
imd1, imd2, imd3, loop_ph_rms_ifg[i], badloopflag1,
str_loop_ph_rms_ifg2, badloopflag2),
file=f)
f.close()
#%% Saving coh_avg, n_unw, and n_loop_err only for good ifgs
print('\nSaving coh_avg, n_unw, and n_loop_err...', flush=True)
### Calc coh avg and n_unw
coh_avg = np.zeros((length, width), dtype=np.float32)
n_coh = np.zeros((length, width), dtype=np.int16)
n_unw = np.zeros((length, width), dtype=np.int16)
for ifgd in ifgdates_good:
ccfile = os.path.join(ifgdir, ifgd, ifgd + '.cc')
if os.path.getsize(ccfile) == length * width:
coh = io_lib.read_img(ccfile, length, width, np.uint8)
coh = coh.astype(np.float32) / 255
else:
coh = io_lib.read_img(ccfile, length, width)
coh[np.isnan(coh)] = 0 # Fill nan with 0
coh_avg += coh
n_coh += (coh != 0)
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
unw = io_lib.read_img(unwfile, length, width)
unw[unw == 0] = np.nan # Fill 0 with nan
n_unw += ~np.isnan(unw) # Summing number of unnan unw
coh_avg[n_coh == 0] = np.nan
n_coh[n_coh == 0] = 1 #to avoid zero division
coh_avg = coh_avg / n_coh
### Save files
n_unwfile = os.path.join(resultsdir, 'n_unw')
np.float32(n_unw).tofile(n_unwfile)
coh_avgfile = os.path.join(resultsdir, 'coh_avg')
coh_avg.tofile(coh_avgfile)
n_loop_errfile = os.path.join(resultsdir, 'n_loop_err')
np.float32(ns_loop_err).tofile(n_loop_errfile)
### Save png
title = 'Average coherence'
plot_lib.make_im_png(coh_avg, coh_avgfile + '.png', cmap_noise, title)
title = 'Number of used unw data'
plot_lib.make_im_png(n_unw, n_unwfile + '.png', cmap_noise, title, n_im)
title = 'Number of unclosed loops'
plot_lib.make_im_png(ns_loop_err, n_loop_errfile + '.png', cmap_noise_r,
title)
#%% Link ras
### First, identify suffix of raster image (ras, bmp, or png?)
unwfile = os.path.join(ifgdir, ifgdates[0], ifgdates[0] + '.unw')
if os.path.exists(unwfile + '.ras'):
suffix = '.ras'
elif os.path.exists(unwfile + '.bmp'):
suffix = '.bmp'
elif os.path.exists(unwfile + '.png'):
suffix = '.png'
for ifgd in ifgdates:
rasname = ifgd + '.unw' + suffix
rasorg = os.path.join(ifgdir, ifgd, rasname)
### Bad ifgs
if ifgd in bad_ifg_all:
os.symlink(os.path.relpath(rasorg, bad_ifgrasdir),
os.path.join(bad_ifgrasdir, rasname))
### Remaining bad ifg candidates
elif ifgd in bad_ifg_cand_res:
os.symlink(os.path.relpath(rasorg, bad_ifg_candrasdir),
os.path.join(bad_ifg_candrasdir, rasname))
### Good ifgs
else:
os.symlink(os.path.relpath(rasorg, ifg_rasdir),
os.path.join(ifg_rasdir, rasname))
if ifgd in no_loop_ifg:
os.symlink(os.path.relpath(rasorg, no_loop_ifgrasdir),
os.path.join(no_loop_ifgrasdir, rasname))
#%% Plot network
## Read bperp data or dummy
bperp_file = os.path.join(ifgdir, 'baselines')
if os.path.exists(bperp_file):
bperp = io_lib.read_bperp_file(bperp_file, imdates)
else: #dummy
bperp = np.random.random(n_im).tolist()
pngfile = os.path.join(netdir, 'network12_all.png')
plot_lib.plot_network(ifgdates, bperp, [], pngfile)
pngfile = os.path.join(netdir, 'network12.png')
plot_lib.plot_network(ifgdates, bperp, bad_ifg_all, pngfile)
pngfile = os.path.join(netdir, 'network12_nobad.png')
plot_lib.plot_network(ifgdates,
bperp,
bad_ifg_all,
pngfile,
plot_bad=False)
### Network info
## Identify gaps
G = inv_lib.make_sb_matrix(ifgdates_good)
ixs_inc_gap = np.where(G.sum(axis=0) == 0)[0]
## Connected network
ix1 = 0
connected_list = []
for ix2 in np.append(ixs_inc_gap,
len(imdates_good) - 1): #append for last image
imd1 = imdates_good[ix1]
imd2 = imdates_good[ix2]
dyear = (dt.datetime.strptime(imd2, '%Y%m%d').toordinal() -
dt.datetime.strptime(imd1, '%Y%m%d').toordinal()) / 365.25
n_im_connect = ix2 - ix1 + 1
connected_list.append(
[imdates_good[ix1], imdates_good[ix2], dyear, n_im_connect])
ix1 = ix2 + 1 # Next connection
#%% Caution about no_loop ifg, remaining large RMS loop and gap
### no_loop ifg
if len(no_loop_ifg) != 0:
no_loop_ifgfile = os.path.join(infodir, '12no_loop_ifg.txt')
with open(no_loop_ifgfile, 'w') as f:
print(
"\nThere are {} ifgs without loop, recommend to check manually in no_loop_ifg_ras12"
.format(len(no_loop_ifg)),
flush=True)
for ifgd in no_loop_ifg:
print('{}'.format(ifgd), flush=True)
print('{}'.format(ifgd), file=f)
### Remaining candidates of bad ifgs
if len(bad_ifg_cand_res) != 0:
print(
"\nThere are {} remaining candidates of bad ifgs but not identified."
.format(len(bad_ifg_cand_res)),
flush=True)
print("Check 12bad_ifg_cand_ras and loop/bad_loop_cand_png.",
flush=True)
# for ifgd in bad_ifg_cand_res:
# print('{}'.format(ifgd))
print('\n{0}/{1} ifgs are discarded from further processing.'.format(
len(bad_ifg_all), n_ifg),
flush=True)
for ifgd in bad_ifg_all:
print('{}'.format(ifgd), flush=True)
### Gap
gap_infofile = os.path.join(infodir, '12network_gap_info.txt')
with open(gap_infofile, 'w') as f:
if ixs_inc_gap.size != 0:
print("Gaps between:", file=f)
print("\nGaps in network between:", flush=True)
for ix in ixs_inc_gap:
print("{} {}".format(imdates_good[ix], imdates_good[ix + 1]),
file=f)
print("{} {}".format(imdates_good[ix], imdates_good[ix + 1]),
flush=True)
print("\nConnected network (year, n_image):", file=f)
print("\nConnected network (year, n_image):", flush=True)
for list1 in connected_list:
print("{0}-{1} ({2:.2f}, {3})".format(list1[0], list1[1], list1[2],
list1[3]),
file=f)
print("{0}-{1} ({2:.2f}, {3})".format(list1[0], list1[1], list1[2],
list1[3]),
flush=True)
print(
'\nIf you want to change the bad ifgs to be discarded, re-run with different thresholds before next step.',
flush=True)
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(tsadir)))
def main(argv=None):
#%% Check argv
if argv == None:
argv = sys.argv
start = time.time()
ver = "1.4.8"
date = 20210127
author = "Y. Morishita"
print("\n{} ver{} {} {}".format(os.path.basename(argv[0]), ver, date,
author),
flush=True)
print("{} {}".format(os.path.basename(argv[0]), ' '.join(argv[1:])),
flush=True)
## For parallel processing
global n_para_gap, G, Aloop, unwpatch, imdates, incdir, ifgdir, length, width,\
coef_r2m, ifgdates, ref_unw, cycle, keep_incfile, resdir, restxtfile, \
cmap_vel, cmap_wrap, wavelength
#%% Set default
ifgdir = []
tsadir = []
inv_alg = 'LS'
try:
n_para = len(os.sched_getaffinity(0))
except:
n_para = multi.cpu_count()
n_para_inv = 1
memory_size = 4000
gamma = 0.0001
n_unw_r_thre = []
keep_incfile = False
cmap_vel = SCM.roma.reversed()
cmap_noise = 'viridis'
cmap_noise_r = 'viridis_r'
cmap_wrap = SCM.romaO
# q = multi.get_context('fork')
q = multi.get_context('spawn')
compress = 'gzip'
#%% Read options
try:
try:
opts, args = getopt.getopt(argv[1:], "hd:t:", [
"help", "mem_size=", "gamma=", "n_unw_r_thre=", "keep_incfile",
"inv_alg=", "n_para="
])
except getopt.error as msg:
raise Usage(msg)
for o, a in opts:
if o == '-h' or o == '--help':
print(__doc__)
return 0
elif o == '-d':
ifgdir = a
elif o == '-t':
tsadir = a
elif o == '--mem_size':
memory_size = float(a)
elif o == '--gamma':
gamma = float(a)
elif o == '--n_unw_r_thre':
n_unw_r_thre = float(a)
elif o == '--keep_incfile':
keep_incfile = True
elif o == '--inv_alg':
inv_alg = a
elif o == '--n_para':
n_para = int(a)
if not ifgdir:
raise Usage('No data directory given, -d is not optional!')
elif not os.path.isdir(ifgdir):
raise Usage('No {} dir exists!'.format(ifgdir))
elif not os.path.exists(os.path.join(ifgdir, 'slc.mli.par')):
raise Usage('No slc.mli.par file exists in {}!'.format(ifgdir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Directory settings
ifgdir = os.path.abspath(ifgdir)
if not tsadir:
tsadir = os.path.join(os.path.dirname(ifgdir),
'TS_' + os.path.basename(ifgdir))
if not os.path.isdir(tsadir):
print('\nNo {} exists!'.format(tsadir), file=sys.stderr)
return 1
tsadir = os.path.abspath(tsadir)
resultsdir = os.path.join(tsadir, 'results')
infodir = os.path.join(tsadir, 'info')
netdir = os.path.join(tsadir, 'network')
bad_ifg11file = os.path.join(infodir, '11bad_ifg.txt')
bad_ifg12file = os.path.join(infodir, '12bad_ifg.txt')
reffile = os.path.join(infodir, '12ref.txt')
if not os.path.exists(reffile): ## for old LiCSBAS12 < v1.1
reffile = os.path.join(infodir, 'ref.txt')
incdir = os.path.join(tsadir, '13increment')
if not os.path.exists(incdir): os.mkdir(incdir)
resdir = os.path.join(tsadir, '13resid')
if not os.path.exists(resdir): os.mkdir(resdir)
restxtfile = os.path.join(infodir, '13resid.txt')
cumh5file = os.path.join(tsadir, 'cum.h5')
#%% Check files
try:
if not os.path.exists(bad_ifg11file):
raise Usage('No 11bad_ifg.txt file exists in {}!'.format(infodir))
if not os.path.exists(bad_ifg12file):
raise Usage('No 12bad_ifg.txt file exists in {}!'.format(infodir))
if not os.path.exists(reffile):
raise Usage('No 12ref.txt file exists in {}!'.format(infodir))
except Usage as err:
print("\nERROR:", file=sys.stderr, end='')
print(" " + str(err.msg), file=sys.stderr)
print("\nFor help, use -h or --help.\n", file=sys.stderr)
return 2
#%% Set preliminaly reference
with open(reffile, "r") as f:
refarea = f.read().split()[0] #str, x1/x2/y1/y2
refx1, refx2, refy1, refy2 = [int(s) for s in re.split('[:/]', refarea)]
#%% Check RAM
mem_avail = (psutil.virtual_memory().available) / 2**20 #MB
if memory_size > mem_avail / 2:
print('\nNot enough memory available compared to mem_size ({} MB).'.
format(memory_size))
print('Reduce mem_size automatically to {} MB.'.format(
int(mem_avail / 2)))
memory_size = int(mem_avail / 2)
#%% Read data information
### Get size
mlipar = os.path.join(ifgdir, 'slc.mli.par')
width = int(io_lib.get_param_par(mlipar, 'range_samples'))
length = int(io_lib.get_param_par(mlipar, 'azimuth_lines'))
speed_of_light = 299792458 #m/s
radar_frequency = float(io_lib.get_param_par(mlipar,
'radar_frequency')) #Hz
wavelength = speed_of_light / radar_frequency #meter
coef_r2m = -wavelength / 4 / np.pi * 1000 #rad -> mm, positive is -LOS
### Calc pixel spacing depending on IFG or GEOC, used in later spatial filter
dempar = os.path.join(ifgdir, 'EQA.dem_par')
width_geo = int(io_lib.get_param_par(dempar, 'width'))
length_geo = int(io_lib.get_param_par(dempar, 'nlines'))
dlat = float(io_lib.get_param_par(dempar, 'post_lat')) #negative
dlon = float(io_lib.get_param_par(dempar, 'post_lon')) #positive
lat1 = float(io_lib.get_param_par(dempar, 'corner_lat'))
lon1 = float(io_lib.get_param_par(dempar, 'corner_lon'))
if width == width_geo and length == length_geo: ## Geocoded
print('\nIn geographical coordinates', flush=True)
centerlat = lat1 + dlat * (length / 2)
ra = float(io_lib.get_param_par(dempar, 'ellipsoid_ra'))
recip_f = float(
io_lib.get_param_par(dempar, 'ellipsoid_reciprocal_flattening'))
rb = ra * (1 - 1 / recip_f) ## polar radius
pixsp_a = 2 * np.pi * rb / 360 * abs(dlat)
pixsp_r = 2 * np.pi * ra / 360 * dlon * np.cos(np.deg2rad(centerlat))
else:
print('\nIn radar coordinates', flush=True)
pixsp_r_org = float(io_lib.get_param_par(mlipar,
'range_pixel_spacing'))
pixsp_a = float(io_lib.get_param_par(mlipar, 'azimuth_pixel_spacing'))
inc_agl = float(io_lib.get_param_par(mlipar, 'incidence_angle'))
pixsp_r = pixsp_r_org / np.sin(np.deg2rad(inc_agl))
### Set n_unw_r_thre and cycle depending on L- or C-band
if wavelength > 0.2: ## L-band
if not n_unw_r_thre: n_unw_r_thre = 0.5
cycle = 1.5 # 2pi/cycle for comparison png
elif wavelength <= 0.2: ## C-band
if not n_unw_r_thre: n_unw_r_thre = 1.0
cycle = 3 # 3*2pi/cycle for comparison png
#%% Read date and network information
### Get all ifgdates in ifgdir
ifgdates_all = tools_lib.get_ifgdates(ifgdir)
imdates_all = tools_lib.ifgdates2imdates(ifgdates_all)
n_im_all = len(imdates_all)
n_ifg_all = len(ifgdates_all)
### Read bad_ifg11 and 12
bad_ifg11 = io_lib.read_ifg_list(bad_ifg11file)
bad_ifg12 = io_lib.read_ifg_list(bad_ifg12file)
bad_ifg_all = list(set(bad_ifg11 + bad_ifg12))
bad_ifg_all.sort()
### Remove bad ifgs and images from list
ifgdates = list(set(ifgdates_all) - set(bad_ifg_all))
ifgdates.sort()
imdates = tools_lib.ifgdates2imdates(ifgdates)
n_ifg = len(ifgdates)
n_ifg_bad = len(set(bad_ifg11 + bad_ifg12))
n_im = len(imdates)
n_unw_thre = int(n_unw_r_thre * n_im)
### Make 13used_image.txt
imfile = os.path.join(infodir, '13used_image.txt')
with open(imfile, 'w') as f:
for i in imdates:
print('{}'.format(i), file=f)
### Calc dt in year
imdates_dt = ([
dt.datetime.strptime(imd, '%Y%m%d').toordinal() for imd in imdates
])
dt_cum = np.float32((np.array(imdates_dt) - imdates_dt[0]) / 365.25)
### Construct G and Aloop matrix for increment and n_gap
G = inv_lib.make_sb_matrix(ifgdates)
Aloop = loop_lib.make_loop_matrix(ifgdates)
#%% Plot network
## Read bperp data or dummy
bperp_file = os.path.join(ifgdir, 'baselines')
if os.path.exists(bperp_file):
bperp_all = io_lib.read_bperp_file(bperp_file, imdates_all)
bperp = io_lib.read_bperp_file(bperp_file, imdates)
else: #dummy
bperp_all = np.random.random(len(imdates_all)).tolist()
bperp = np.random.random(n_im).tolist()
pngfile = os.path.join(netdir, 'network13_all.png')
plot_lib.plot_network(ifgdates_all, bperp_all, [], pngfile)
pngfile = os.path.join(netdir, 'network13.png')
plot_lib.plot_network(ifgdates_all, bperp_all, bad_ifg_all, pngfile)
pngfile = os.path.join(netdir, 'network13_nobad.png')
plot_lib.plot_network(ifgdates_all,
bperp_all,
bad_ifg_all,
pngfile,
plot_bad=False)
#%% Get patch row number
if inv_alg == 'WLS':
n_store_data = n_ifg * 3 + n_im * 2 + n_im * 0.3 #
else:
n_store_data = n_ifg * 2 + n_im * 2 + n_im * 0.3 #not sure
n_patch, patchrow = tools_lib.get_patchrow(width, length, n_store_data,
memory_size)
#%% Display and output settings & parameters
print('')
print('Size of image (w,l) : {}, {}'.format(width, length))
print('# of all images : {}'.format(n_im_all))
print('# of images to be used : {}'.format(n_im))
print('# of all ifgs : {}'.format(n_ifg_all))
print('# of ifgs to be used : {}'.format(n_ifg))
print('# of removed ifgs : {}'.format(n_ifg_bad))
print('Threshold of used unw : {}'.format(n_unw_thre))
print('')
print('Reference area (X/Y) : {}:{}/{}:{}'.format(
refx1, refx2, refy1, refy2))
print('Allowed memory size : {} MB'.format(memory_size))
print('Number of patches : {}'.format(n_patch))
print('Inversion algorism : {}'.format(inv_alg))
print('Gamma value : {}'.format(gamma), flush=True)
with open(os.path.join(infodir, '13parameters.txt'), "w") as f:
print('range_samples: {}'.format(width), file=f)
print('azimuth_lines: {}'.format(length), file=f)
print('wavelength: {}'.format(wavelength), file=f)
print('n_im_all: {}'.format(n_im_all), file=f)
print('n_im: {}'.format(n_im), file=f)
print('n_ifg_all: {}'.format(n_ifg_all), file=f)
print('n_ifg: {}'.format(n_ifg), file=f)
print('n_ifg_bad: {}'.format(n_ifg_bad), file=f)
print('n_unw_thre: {}'.format(n_unw_thre), file=f)
print('ref_area: {}:{}/{}:{}'.format(refx1, refx2, refy1, refy2),
file=f)
print('memory_size: {} MB'.format(memory_size), file=f)
print('n_patch: {}'.format(n_patch), file=f)
print('inv_alg: {}'.format(inv_alg), file=f)
print('gamma: {}'.format(gamma), file=f)
print('pixel_spacing_r: {:.2f} m'.format(pixsp_r), file=f)
print('pixel_spacing_a: {:.2f} m'.format(pixsp_a), file=f)
#%% Ref phase for inversion
lengththis = refy2 - refy1
countf = width * refy1
countl = width * lengththis # Number to be read
ref_unw = []
for i, ifgd in enumerate(ifgdates):
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
f = open(unwfile, 'rb')
f.seek(countf * 4, os.SEEK_SET) #Seek for >=2nd path, 4 means byte
### Read unw data (mm) at ref area
unw = np.fromfile(f, dtype=np.float32, count=countl).reshape(
(lengththis, width))[:, refx1:refx2] * coef_r2m
unw[unw == 0] = np.nan
if np.all(np.isnan(unw)):
print('All nan in ref area in {}.'.format(ifgd))
print('Rerun LiCSBAS12.')
return 1
ref_unw.append(np.nanmean(unw))
f.close()
#%% Open cum.h5 for output
if os.path.exists(cumh5file): os.remove(cumh5file)
cumh5 = h5.File(cumh5file, 'w')
cumh5.create_dataset('imdates', data=[np.int32(imd) for imd in imdates])
if not np.all(np.abs(np.array(bperp)) <= 1): # if not dummy
cumh5.create_dataset('bperp', data=bperp)
cum = cumh5.require_dataset('cum', (n_im, length, width),
dtype=np.float32,
compression=compress)
vel = cumh5.require_dataset('vel', (length, width),
dtype=np.float32,
compression=compress)
vconst = cumh5.require_dataset('vintercept', (length, width),
dtype=np.float32,
compression=compress)
gap = cumh5.require_dataset('gap', (n_im - 1, length, width),
dtype=np.int8,
compression=compress)
if width == width_geo and length == length_geo: ## if geocoded
cumh5.create_dataset('corner_lat', data=lat1)
cumh5.create_dataset('corner_lon', data=lon1)
cumh5.create_dataset('post_lat', data=dlat)
cumh5.create_dataset('post_lon', data=dlon)
#%% For each patch
for i_patch, rows in enumerate(patchrow):
print('\nProcess {0}/{1}th line ({2}/{3}th patch)...'.format(
rows[1], patchrow[-1][-1], i_patch + 1, n_patch),
flush=True)
start2 = time.time()
#%% Read data
### Allocate memory
lengththis = rows[1] - rows[0]
n_pt_all = lengththis * width
unwpatch = np.zeros((n_ifg, lengththis, width), dtype=np.float32)
if inv_alg == 'WLS':
cohpatch = np.zeros((n_ifg, lengththis, width), dtype=np.float32)
### For each ifg
print(" Reading {0} ifg's unw data...".format(n_ifg), flush=True)
countf = width * rows[0]
countl = width * lengththis
for i, ifgd in enumerate(ifgdates):
unwfile = os.path.join(ifgdir, ifgd, ifgd + '.unw')
f = open(unwfile, 'rb')
f.seek(countf * 4,
os.SEEK_SET) #Seek for >=2nd patch, 4 means byte
### Read unw data (mm) at patch area
unw = np.fromfile(f, dtype=np.float32, count=countl).reshape(
(lengththis, width)) * coef_r2m
unw[unw == 0] = np.nan # Fill 0 with nan
unw = unw - ref_unw[i]
unwpatch[i] = unw
f.close()
### Read coh file at patch area for WLS
if inv_alg == 'WLS':
cohfile = os.path.join(ifgdir, ifgd, ifgd + '.cc')
f = open(cohfile, 'rb')
if os.path.getsize(cohfile) == length * width: ## uint8 format
f.seek(countf, os.SEEK_SET) #Seek for >=2nd patch
cohpatch[i, :, :] = (np.fromfile(
f, dtype=np.uint8, count=countl).reshape(
(lengththis, width))).astype(np.float32) / 255
else: ## old float32 format
f.seek(countf * 4,
os.SEEK_SET) #Seek for >=2nd patch, 4 means byte
cohpatch[i, :, :] = np.fromfile(f,
dtype=np.float32,
count=countl).reshape(
(lengththis, width))
cohpatch[cohpatch == 0] = np.nan
unwpatch = unwpatch.reshape(
(n_ifg, n_pt_all)).transpose() #(n_pt_all, n_ifg)
### Calc variance from coherence for WLS
if inv_alg == 'WLS':
cohpatch = cohpatch.reshape(
(n_ifg, n_pt_all)).transpose() #(n_pt_all, n_ifg)
cohpatch[
cohpatch <
0.01] = 0.01 ## because negative value possible due to geocode
cohpatch[
cohpatch > 0.99] = 0.99 ## because >1 possible due to geocode
varpatch = (1 - cohpatch**2) / (2 * cohpatch**2)
del cohpatch
#%% Remove points with less valid data than n_unw_thre
ix_unnan_pt = np.where(
np.sum(~np.isnan(unwpatch), axis=1) > n_unw_thre)[0]
n_pt_unnan = len(ix_unnan_pt)
unwpatch = unwpatch[ix_unnan_pt, :] ## keep only unnan data
if inv_alg == 'WLS':
varpatch = varpatch[ix_unnan_pt, :] ## keep only unnan data
print(' {}/{} points removed due to not enough ifg data...'.format(
n_pt_all - n_pt_unnan, n_pt_all),
flush=True)
#%% Compute number of gaps, ifg_noloop, maxTlen point-by-point
if n_pt_unnan != 0:
ns_gap_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
gap_patch = np.zeros((n_im - 1, n_pt_all), dtype=np.int8)
ns_ifg_noloop_patch = np.zeros(
(n_pt_all), dtype=np.float32) * np.nan
maxTlen_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
### Determine n_para
n_pt_patch_min = 1000
if n_pt_patch_min * n_para > n_pt_unnan:
## Too much n_para
n_para_gap = int(np.floor(n_pt_unnan / n_pt_patch_min))
if n_para_gap == 0: n_para_gap = 1
else:
n_para_gap = n_para
print('\n Identifing gaps, and counting n_gap and n_ifg_noloop,')
print(' with {} parallel processing...'.format(n_para_gap),
flush=True)
### Devide unwpatch by n_para for parallel processing
p = q.Pool(n_para_gap)
# _result = np.array(p.map(count_gaps_wrapper, range(n_para_gap)), dtype=object)
_result = np.array(p.map(count_gaps_wrapper,
[(i, n_para_gap, G, Aloop, unwpatch)
for i in range(n_para_gap)]),
dtype=object)
p.close()
ns_gap_patch[ix_unnan_pt] = np.hstack(_result[:, 0]) #n_pt
gap_patch[:, ix_unnan_pt] = np.hstack(_result[:, 1]) #n_im-1, n_pt
ns_ifg_noloop_patch[ix_unnan_pt] = np.hstack(_result[:, 2])
### maxTlen
_maxTlen = np.zeros((n_pt_unnan), dtype=np.float32) #temporaly
_Tlen = np.zeros((n_pt_unnan), dtype=np.float32) #temporaly
for imx in range(n_im - 1):
_Tlen = _Tlen + (dt_cum[imx + 1] - dt_cum[imx]) ## Adding dt
_Tlen[gap_patch[imx,
ix_unnan_pt] == 1] = 0 ## reset to 0 if gap
_maxTlen[_maxTlen < _Tlen] = _Tlen[
_maxTlen < _Tlen] ## Set Tlen to maxTlen
maxTlen_patch[ix_unnan_pt] = _maxTlen
#%% Time series inversion
print('\n Small Baseline inversion by {}...\n'.format(inv_alg),
flush=True)
if inv_alg == 'WLS':
inc_tmp, vel_tmp, vconst_tmp = inv_lib.invert_nsbas_wls(
unwpatch, varpatch, G, dt_cum, gamma, n_para_inv)
else:
inc_tmp, vel_tmp, vconst_tmp = inv_lib.invert_nsbas(
unwpatch, G, dt_cum, gamma, n_para_inv)
### Set to valuables
inc_patch = np.zeros(
(n_im - 1, n_pt_all), dtype=np.float32) * np.nan
vel_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
vconst_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
inc_patch[:, ix_unnan_pt] = inc_tmp
vel_patch[ix_unnan_pt] = vel_tmp
vconst_patch[ix_unnan_pt] = vconst_tmp
### Calculate residuals
res_patch = np.zeros((n_ifg, n_pt_all), dtype=np.float32) * np.nan
res_patch[:, ix_unnan_pt] = unwpatch.T - np.dot(G, inc_tmp)
res_sumsq = np.nansum(res_patch**2, axis=0)
res_n = np.float32((~np.isnan(res_patch)).sum(axis=0))
res_n[res_n == 0] = np.nan # To avoid 0 division
res_rms_patch = np.sqrt(res_sumsq / res_n)
### Cumulative displacememt
cum_patch = np.zeros((n_im, n_pt_all), dtype=np.float32) * np.nan
cum_patch[1:, :] = np.cumsum(inc_patch, axis=0)
## Fill 1st image with 0 at unnan points from 2nd images
bool_unnan_pt = ~np.isnan(cum_patch[1, :])
cum_patch[0, bool_unnan_pt] = 0
## Drop (fill with nan) interpolated cum by 2 continuous gaps
for i in range(n_im - 2): ## from 1->n_im-1
gap2 = gap_patch[i, :] + gap_patch[i + 1, :]
bool_gap2 = (gap2 == 2
) ## true if 2 continuous gaps for each point
cum_patch[i + 1, :][bool_gap2] = np.nan
## Last (n_im th) image. 1 gap means interpolated
cum_patch[-1, :][gap_patch[-1, :] == 1] = np.nan
#%% Fill by np.nan if n_pt_unnan == 0
else:
cum_patch = np.zeros((n_im, n_pt_all), dtype=np.float32) * np.nan
vel_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
vconst_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
gap_patch = np.zeros((n_im - 1, n_pt_all), dtype=np.int8)
inc_patch = np.zeros(
(n_im - 1, n_pt_all), dtype=np.float32) * np.nan
res_patch = np.zeros((n_ifg, n_pt_all), dtype=np.float32) * np.nan
res_rms_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
ns_gap_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
ns_ifg_noloop_patch = np.zeros(
(n_pt_all), dtype=np.float32) * np.nan
maxTlen_patch = np.zeros((n_pt_all), dtype=np.float32) * np.nan
#%% Output data and image
### cum.h5 file
cum[:, rows[0]:rows[1], :] = cum_patch.reshape(
(n_im, lengththis, width))
vel[rows[0]:rows[1], :] = vel_patch.reshape((lengththis, width))
vconst[rows[0]:rows[1], :] = vconst_patch.reshape((lengththis, width))
gap[:, rows[0]:rows[1], :] = gap_patch.reshape(
(n_im - 1, lengththis, width))
### Others
openmode = 'w' if rows[0] == 0 else 'a' #w only 1st patch
## For each imd. cum and inc
for imx, imd in enumerate(imdates):
## Incremental displacement
if imd == imdates[-1]: continue #skip last
incfile = os.path.join(incdir,
'{0}_{1}.inc'.format(imd, imdates[imx + 1]))
with open(incfile, openmode) as f:
inc_patch[imx, :].tofile(f)
## For each ifgd. resid
for i, ifgd in enumerate(ifgdates):
resfile = os.path.join(resdir, '{0}.res'.format(ifgd))
with open(resfile, openmode) as f:
res_patch[i, :].tofile(f)
## velocity and noise indecies in results dir
names = [
'vel', 'vintercept', 'resid_rms', 'n_gap', 'n_ifg_noloop',
'maxTlen'
]
data = [
vel_patch, vconst_patch, res_rms_patch, ns_gap_patch,
ns_ifg_noloop_patch, maxTlen_patch
]
for i in range(len(names)):
file = os.path.join(resultsdir, names[i])
with open(file, openmode) as f:
data[i].tofile(f)
#%% Finish patch
elapsed_time2 = int(time.time() - start2)
hour2 = int(elapsed_time2 / 3600)
minite2 = int(np.mod((elapsed_time2 / 60), 60))
sec2 = int(np.mod(elapsed_time2, 60))
print(" Elapsed time for {0}th patch: {1:02}h {2:02}m {3:02}s".format(
i_patch + 1, hour2, minite2, sec2),
flush=True)
#%% Find stable ref point
print('\nFind stable reference point...', flush=True)
### Compute RMS of time series with reference to all points
sumsq_cum_wrt_med = np.zeros((length, width), dtype=np.float32)
for i in range(n_im):
sumsq_cum_wrt_med = sumsq_cum_wrt_med + (cum[i, :, :] -
np.nanmedian(cum[i, :, :]))**2
rms_cum_wrt_med = np.sqrt(sumsq_cum_wrt_med / n_im)
### Mask by minimum n_gap
n_gap = io_lib.read_img(os.path.join(resultsdir, 'n_gap'), length, width)
min_n_gap = np.nanmin(n_gap)
mask_n_gap = np.float32(n_gap == min_n_gap)
mask_n_gap[mask_n_gap == 0] = np.nan
rms_cum_wrt_med = rms_cum_wrt_med * mask_n_gap
### Find stable reference
min_rms = np.nanmin(rms_cum_wrt_med)
refy1s, refx1s = np.where(rms_cum_wrt_med == min_rms)
refy1s, refx1s = refy1s[0], refx1s[0] ## Only first index
refy2s, refx2s = refy1s + 1, refx1s + 1
print('Selected ref: {}:{}/{}:{}'.format(refx1s, refx2s, refy1s, refy2s),
flush=True)
### Rerferencing cumulative displacement and vel to new stable ref
for i in range(n_im):
cum[i, :, :] = cum[i, :, :] - cum[i, refy1s, refx1s]
vel = vel - vel[refy1s, refx1s]
vconst = vconst - vconst[refy1s, refx1s]
### Save image
rms_cum_wrt_med_file = os.path.join(infodir, '13rms_cum_wrt_med')
with open(rms_cum_wrt_med_file, 'w') as f:
rms_cum_wrt_med.tofile(f)
pngfile = os.path.join(infodir, '13rms_cum_wrt_med.png')
plot_lib.make_im_png(rms_cum_wrt_med, pngfile, cmap_noise_r,
'RMS of cum wrt median (mm)',
np.nanpercentile(rms_cum_wrt_med, 1),
np.nanpercentile(rms_cum_wrt_med, 99))
### Save ref
cumh5.create_dataset('refarea',
data='{}:{}/{}:{}'.format(refx1s, refx2s, refy1s,
refy2s))
refsfile = os.path.join(infodir, '13ref.txt')
with open(refsfile, 'w') as f:
print('{}:{}/{}:{}'.format(refx1s, refx2s, refy1s, refy2s), file=f)
if width == width_geo and length == length_geo: ## Geocoded
### Make ref_stable.kml
reflat = lat1 + dlat * refy1s
reflon = lon1 + dlon * refx1s
io_lib.make_point_kml(reflat, reflon,
os.path.join(infodir, '13ref.kml'))
#%% Close h5 file
cumh5.close()
#%% Output png images
### Incremental displacement
_n_para = n_im - 1 if n_para > n_im - 1 else n_para
print(
'\nOutput increment png images with {} parallel processing...'.format(
_n_para),
flush=True)
p = q.Pool(_n_para)
# p.map(inc_png_wrapper, range(n_im-1))
p.map(inc_png_wrapper,
[(i, imdates, incdir, ifgdir, length, width, coef_r2m, ifgdates,
ref_unw, cycle, cmap_wrap, keep_incfile) for i in range(n_im - 1)])
p.close()
### Residual for each ifg. png and txt.
with open(restxtfile, "w") as f:
print('# RMS of residual (mm)', file=f)
_n_para = n_ifg if n_para > n_ifg else n_para
print('\nOutput residual png images with {} parallel processing...'.format(
_n_para),
flush=True)
p = q.Pool(_n_para)
# p.map(resid_png_wrapper, range(n_ifg))
p.map(resid_png_wrapper, [(i, ifgdates, resdir, length, width, restxtfile,
cmap_vel, wavelength, keep_incfile)
for i in range(n_ifg)])
p.close()
### Velocity and noise indices
cmins = [None, None, None, None, None, None]
cmaxs = [None, None, None, None, None, None]
cmaps = [
cmap_vel, cmap_vel, cmap_noise_r, cmap_noise_r, cmap_noise_r,
cmap_noise
]
titles = [
'Velocity (mm/yr)', 'Intercept of velocity (mm)',
'RMS of residual (mm)', 'Number of gaps in SB network',
'Number of ifgs with no loops',
'Max length of connected SB network (yr)'
]
print('\nOutput noise png images...', flush=True)
for i in range(len(names)):
file = os.path.join(resultsdir, names[i])
data = io_lib.read_img(file, length, width)
pngfile = file + '.png'
## Get color range if None
if cmins[i] is None:
cmins[i] = np.nanpercentile(data, 1)
if cmaxs[i] is None:
cmaxs[i] = np.nanpercentile(data, 99)
if cmins[i] == cmaxs[i]: cmins[i] = cmaxs[i] - 1
plot_lib.make_im_png(data, pngfile, cmaps[i], titles[i], cmins[i],
cmaxs[i])
#%% Finish
elapsed_time = time.time() - start
hour = int(elapsed_time / 3600)
minite = int(np.mod((elapsed_time / 60), 60))
sec = int(np.mod(elapsed_time, 60))
print("\nElapsed time: {0:02}h {1:02}m {2:02}s".format(hour, minite, sec))
print('\n{} Successfully finished!!\n'.format(os.path.basename(argv[0])))
print('Output directory: {}\n'.format(os.path.relpath(tsadir)))