def inputs(file_names, config_params):
[xdata,ydata] = netcdf_read_write.read_grd_xy(file_names[0]);
data_all=[];
date_pairs=[];
dates=[];
start_dt = dt.datetime.strptime(str(config_params.start_time),"%Y%m%d");
end_dt = dt.datetime.strptime(str(config_params.end_time),"%Y%m%d");
for ifile in file_names: # this happens to be in date order on my mac
pairname=ifile.split('/')[-1][0:15];
image1=pairname.split('_')[0];
image2=pairname.split('_')[1];
image1_dt = dt.datetime.strptime(image1,"%Y%j");
image2_dt = dt.datetime.strptime(image2,"%Y%j");
if image1_dt>=start_dt and image1_dt<= end_dt:
if image2_dt>=start_dt and image2_dt <= end_dt:
data = netcdf_read_write.read_grd(ifile);
data_all.append(data);
date_pairs.append(pairname); # returning something like '2016292_2016316' for each intf
dates.append(image1);
dates.append(image2);
dates=list(set(dates));
dates=sorted(dates);
print(dates);
print("Reading %d interferograms from %d acquisitions. " % (len(date_pairs), len(dates) ) );
return [xdata, ydata, data_all, dates, date_pairs];
def inputs(file_names, skip_file):
try:
[xdata, ydata] = netcdf_read_write.read_grd_xy(file_names[0])
# can read either netcdf3 or netcdf4.
except TypeError:
[xdata, ydata, _] = netcdf_read_write.read_netcdf4_xyz(file_names[0])
data_all = []
date_pairs = []
file_names = sorted(file_names)
# To force into date-ascending order.
for ifile in file_names: # Read the data
try:
data = netcdf_read_write.read_grd(ifile)
except TypeError:
[_, _, data] = netcdf_read_write.read_netcdf4_xyz(ifile)
data_all.append(data)
pairname = ifile.split('/')[-2][0:15]
date_pairs.append(pairname)
# returning something like '2016292_2016316' for each intf
print(pairname)
skip_intfs = []
if skip_file is not None:
ifile = open(skip_file, 'r')
for line in ifile:
skip_intfs.append(line.split()[0])
ifile.close()
return [xdata, ydata, data_all, date_pairs, skip_intfs]
def inputs(file_names, start_time, end_time, run_type):
# Read the input grd files. Support for netcdf3 and netcdf4.
try:
[xdata, ydata] = netcdf_read_write.read_grd_xy(file_names[0])
except TypeError:
[xdata, ydata, _] = netcdf_read_write.read_netcdf4_xyz(file_names[0])
data_all = []
date_pairs = []
dates = []
start_dt = dt.datetime.strptime(str(start_time), "%Y%m%d")
end_dt = dt.datetime.strptime(str(end_time), "%Y%m%d")
# Get the dates of the acquisitions from the file names.
for ifile in file_names: # this happens to be in date order on my mac
if run_type == 'test': # testing with Kang's format. "20171117_20171123/unwrap_new.grd"
pairname = ifile.split('/')[-2]
image1 = pairname.split('_')[0]
image2 = pairname.split('_')[1]
image1_dt = dt.datetime.strptime(image1, "%Y%m%d")
image2_dt = dt.datetime.strptime(image2, "%Y%m%d")
else: # the usual GMTSAR format
pairname = ifile.split('/')[-1][0:15]
image1 = pairname.split('_')[0]
image2 = pairname.split('_')[1]
image1_dt = dt.datetime.strptime(image1, "%Y%j")
image2_dt = dt.datetime.strptime(image2, "%Y%j")
if image1_dt >= start_dt and image1_dt <= end_dt:
if image2_dt >= start_dt and image2_dt <= end_dt:
try:
data = netcdf_read_write.read_grd(ifile)
except TypeError:
[_, _, data] = netcdf_read_write.read_netcdf4_xyz(ifile)
if run_type == "test":
data_all.append(data * -0.0555 / 4 / np.pi)
# mcandis preprocessing involves changing to LOS distances.
print(
"Converting phase to LOS (mm) with 55.5mm wavelength")
else:
data_all.append(data)
pairname = dt.datetime.strftime(
image1_dt, "%Y%j") + '_' + dt.datetime.strftime(
image2_dt, "%Y%j")
date_pairs.append(pairname)
# returning something like '2016292_2016316' for each intf
dates.append(dt.datetime.strftime(image1_dt, "%Y%j"))
dates.append(dt.datetime.strftime(image2_dt, "%Y%j"))
data_all = np.array(data_all)
# this allows easy indexing later on.
dates = list(set(dates))
dates = sorted(dates)
print(date_pairs)
print("Reading %d interferograms from %d acquisitions. " %
(len(date_pairs), len(dates)))
return [xdata, ydata, data_all, dates, date_pairs]
def inputs(file_names):
[xdata, ydata] = netcdf_read_write.read_grd_xy(file_names[0])
data_all = []
for ifile in file_names: # this happens to be in date order on my mac
data = netcdf_read_write.read_grd(ifile)
data_all.append(data)
date_pairs = []
for name in file_names:
pairname = name.split('/')[-2][0:15]
date_pairs.append(pairname)
# returning something like '2016292_2016316' for each intf
print(pairname)
return [xdata, ydata, data_all, date_pairs]
def readGRD(file_type):
# Read in SAR data from .grd formatted file
# INPUT FILES MUST BE LOCATED IN A GMTSAR DIRECTORY!
# Path_list format:
# 20170426_20170520/corr.grd
# 20170426_20170601/corr.grd
# 20170426_20170613/corr.grd
# ...
# Get list of file paths
path_list = glob.glob("*/" + file_type)
print('Number of files to read: ' + str(len(path_list)))
# Establish tuple
tupleGRD = collections.namedtuple('GRD_data',
['path_list', 'xdata', 'ydata', 'zdata'])
# Get dimensional data
try:
[xdata, ydata] = netcdf_read_write.read_grd_xy(
path_list[0]) # can read either netcdf3 or netcdf4.
except TypeError:
[xdata, ydata] = netcdf_read_write.read_netcdf4_xy(path_list[0])
# Loop through path_list to read in target datafiles
zdata = []
date_pairs = []
i = 0
for file in path_list:
try:
data = netcdf_read_write.read_grd(file)
except TypeError:
data = netcdf_read_write.read_netcdf4(file)
zdata.append(data)
pairname = file.split('/')[-2][0:19]
date_pairs.append(
pairname
) # returning something like '2016292_2016316' for each intf
if i == floor(len(path_list) / 2):
print('Halfway done reading...')
myData = tupleGRD(path_list=np.array(path_list),
xdata=np.array(xdata),
ydata=np.array(ydata),
zdata=np.array(zdata))
return myData
def reader_simple_format(file_names):
"""
An earlier reading function, works fast, useful for things like coherence statistics
"""
[xdata, ydata] = rwr.read_grd_xy(file_names[0]);
data_all = [];
for ifile in file_names: # this happens to be in date order on my mac
data = rwr.read_grd(ifile);
data_all.append(data);
date_pairs = [];
for name in file_names:
pairname = name.split('/')[-2][0:15];
date_pairs.append(pairname); # returning something like '2016292_2016316' for each intf
print(pairname)
return [xdata, ydata, data_all, date_pairs];
def inputs(file_names):
[xdata,ydata] = netcdf_read_write.read_grd_xy(file_names[0]);
data_all=[];
for ifile in file_names: # this happens to be in date order on my mac
data = netcdf_read_write.read_grd(ifile);
data_all.append(data);
date_pairs=[];
dates=[];
for name in file_names:
pairname=name.split('/')[-1][0:15];
date_pairs.append(pairname); # returning something like '2016292_2016316' for each intf
splitname=pairname.split('_');
dates.append(splitname[0])
dates.append(splitname[1])
dates=list(set(dates));
dates=sorted(dates);
print(dates);
print("%d interferograms read from %d acquisitions." % (len(date_pairs), len(dates)) );
return [xdata, ydata, data_all, dates, date_pairs];
def inputs(file_names):
try:
[xdata, ydata] = netcdf_read_write.read_grd_xy(
file_names[0]) # can read either netcdf3 or netcdf4.
except TypeError:
[xdata, ydata] = netcdf_read_write.read_netcdf4_xy(file_names[0])
data_all = []
file_names = sorted(file_names) # To force into date-ascending order.
titles = []
for ifile in file_names: # Read the data
try:
data = netcdf_read_write.read_grd(ifile)
except TypeError:
data = netcdf_read_write.read_netcdf4(ifile)
data_all.append(data)
# LOS_20161121_INT3.grd
titles.append(ifile[-17:-9])
return [xdata, ydata, data_all, titles]
def main_function():
# GLOBAL PARAMETERS
nfit=0
ivar=1
alt_ref=100
thresh_amp=0.2
subsampled_dem_grd="topo/topo_ra_subsampled_june.grd" # subsampled in the same way as the intf grd files.
demfile="topo/topo_radar.hgt"
example_rsc="rsc_files/example_sd.int.rsc"
# INPUTS
intf_list=glob.glob("intf_all/???????_???????");
print(intf_list);
# [width, length] = readbin.write_gmtsar2roipac_topo(subsampled_dem_grd,demfile); # copying the demfile into roipac format just in case we've switched the master.
# COMPUTE
for data_dir in intf_list:
print(data_dir);
intf_name=data_dir.split('/')[1];
infile=data_dir+"/intf_sd.int";
infile_filtered=data_dir+"/intf_filt.int";
stratfile=data_dir+"/strat.unw"
outfile=data_dir+"/out.int"
outfile_filtered=data_dir+"/out_filtered.int"
# Pretty standard GMTSAR files.
phasefile=data_dir+"/phase.grd";
phasefilt_file=data_dir+"/phasefilt.grd";
ampfile=data_dir+"/amp.grd";
orig_phasefile=data_dir+"/orig_phase.grd";
orig_phasefilt_file=data_dir+"/orig_phasefilt.grd";
readbin.prep_files(phasefile, phasefilt_file, orig_phasefile, orig_phasefilt_file); # copy files into safekeeping if necessary
# MAKE BINARY INTERFEROGRAMS
[width, length] = readbin.write_gmtsar2roipac_phase(data_dir,orig_phasefile, orig_phasefilt_file, ampfile,infile,infile_filtered);
# width=661; length=1524
# # # RUN THE FORTRAN
print("\nRunning the fortran code to remove atmospheric artifacts from interferogram.")
subprocess.call(['cp',example_rsc,data_dir+'/intf_sd.int.rsc'],shell=False);
print("flatten_topo "+infile+" "+infile_filtered+" "+demfile+" "+outfile+" "+outfile_filtered+" "+str(nfit)+" "+str(ivar)+" "+str(alt_ref)+" "+str(thresh_amp)+" "+stratfile+"\n");
subprocess.call(["flatten_topo",infile,infile_filtered,demfile,outfile,outfile_filtered,str(nfit),str(ivar),str(alt_ref),str(thresh_amp),stratfile],shell=False);
subprocess.call(['mv','ncycle_topo',data_dir+'/ncycle_topo'],shell=False);
subprocess.call(['mv','ncycle_topo_az',data_dir+'/ncycle_topo_az'],shell=False);
# Output handling. First reading 1D arrays
[real,imag]=readbin.read_binary_roipac_real_imag(infile);
[phase_early,amp_early]=readbin.real_imag2phase_amp(real,imag);
[real,imag]=readbin.read_binary_roipac_real_imag(outfile);
[phase_out,amp_late]=readbin.real_imag2phase_amp(real,imag);
[real,imag]=readbin.read_binary_roipac_real_imag(outfile_filtered);
[phasefilt_out,amp_late]=readbin.real_imag2phase_amp(real,imag); # 1d arrays
# # Write the GRD files , fixing an issue with pixel node registration.
[xdata_p,ydata_p]=netcdf_read_write.read_grd_xy(orig_phasefile);
[xdata_pf,ydata_pf]=netcdf_read_write.read_grd_xy(orig_phasefilt_file);
phase_out_grd=np.reshape(phase_out,(length,width));
phasefilt_out_grd=np.reshape(phasefilt_out,(length,width));
netcdf_read_write.produce_output_netcdf(xdata_p, ydata_p, phase_out_grd, 'radians', phasefile);
netcdf_read_write.flip_if_necessary(phasefile);
origrange=subprocess.check_output('gmt grdinfo -I- '+orig_phasefile,shell=True); # fixing pixel node registration issue.
subprocess.call('gmt grdsample '+phasefile+' '+origrange.split()[0]+' -G'+phasefile+' -r', shell=True);
netcdf_read_write.produce_output_netcdf(xdata_pf, ydata_pf, phasefilt_out_grd, 'radians', phasefilt_file);
netcdf_read_write.flip_if_necessary(phasefilt_file);
origrange=subprocess.check_output('gmt grdinfo -I- '+orig_phasefilt_file,shell=True);
subprocess.call('gmt grdsample '+phasefilt_file+' '+origrange.split()[0]+' -G'+phasefilt_file+' -r', shell=True);
# Making plot
readbin.output_plots(phase_early, phasefilt_out, width, length, data_dir+"/"+intf_name+"_corrected.eps");
return;