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_xy(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(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 len(skip_file) > 0:
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_xy(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(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 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 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]