support UAVSAR reading and SET correction

mintpy/ifgram_inversion.py

@@ -190,10 +190,10 @@ def cmd_line_parse(iargs=None):
             inps.outfile = ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5']
 
         elif inps.obsDatasetName.startswith('azimuthOffset'):
-            inps.outfile = ['timeseriesAz.h5', 'residualInvAz.h5', 'numInvOffset.h5']
+            inps.outfile = ['timeseriesAz.h5', 'residualInvAz.h5', 'numInvOffAz.h5']
 
         elif inps.obsDatasetName.startswith('rangeOffset'):
-            inps.outfile = ['timeseriesRg.h5', 'residualInvRg.h5', 'numInvOffset.h5']
+            inps.outfile = ['timeseriesRg.h5', 'residualInvRg.h5', 'numInvOffRg.h5']
 
         elif inps.obsDatasetName.startswith('ion'):
             inps.outfile = ['timeseriesIon.h5', 'temporalCoherenceIon.h5', 'numInvIon.h5']
@@ -711,7 +711,7 @@ def mask_stack_obs(stack_obs, stack_obj, box, mask_ds_name=None, mask_threshold=
             msk_snr = np.multiply(msk_data <= mask_threshold * 5, obs_snr >= min_snr)
             msk[msk_snr] = 1
             if print_msg:
-                print('keep pixels with {} <= {} and SNR >= {}'.format(mask_ds_name, mask_threshold*5, min_snr))            
+                print('keep pixels with {} <= {} and SNR >= {}'.format(mask_ds_name, mask_threshold*5, min_snr))
 
         else:
             raise ValueError('Un-recognized mask dataset name: {}'.format(mask_ds_name))

mintpy/objects/resample.py

@@ -338,8 +338,14 @@ def mark_lat_lon_anomoly(lat, lon):
 
             # parameter 1 - lalo_step (output grid)
             if self.lalo_step is None:
-                self.lalo_step = ((src_lat1 - src_lat0) / (lut_lat.shape[0] - 1),
-                                  (src_lon1 - src_lon0) / (lut_lat.shape[1] - 1))
+                try:
+                    lat_c = (src_lat0 + src_lat1) / 2.
+                    lat_step, lon_step = ut.auto_lat_lon_step_size(self.src_meta, lat_c)
+                except AttributeError:
+                    lat_step = (src_lat1 - src_lat0) / (lut_lat.shape[0] - 1)
+                    lon_step = (src_lon1 - src_lon0) / (lut_lat.shape[1] - 1)
+                self.lalo_step = (abs(lat_step) * -1., abs(lon_step))
+
             else:
                 # ensure lat/lon step sign
                 self.lalo_step = (abs(self.lalo_step[0]) * -1.,

mintpy/prep_isce.py

@@ -10,6 +10,7 @@
 import sys
 import glob
 import argparse
+import numpy as np
 from mintpy.utils import ptime, readfile, writefile, isce_utils
 
 
@@ -24,8 +25,9 @@
   prep_isce.py -m 20120507_slc_crop.xml -g ./geometry                                                           #for stripmapApp
   prep_isce.py -d "pairs/*-*/insar" -m "pairs/*-*/150408.track.xml" -b baseline -g dates_resampled/150408/insar #for alosStack with 150408 as ref date
 
-  # offset stack from topsStack
-  prep_isce.py -d ./merged/offsets -f filtAz*.off -m ./reference/IW1.xml -b ./baselines -g ./merged/offsets/geom_reference
+  # offset stack
+  prep_isce.py -d ./offsets -f *Off*.bip -m ./../reference/IW1.xml -b ./../baselines -g ./offsets/geom_reference  #for topsStack
+  prep_isce.py -d ./offsets -f *Off*.bip -m ./SLC/*/data.dat       -b random         -g ./geometry                #for UAVSAR coregStack
 """
 
 def create_parser():
@@ -52,7 +54,9 @@ def create_parser():
 
     # geometry
     parser.add_argument('-b', '--baseline-dir', dest='baselineDir', type=str, default=None,
-                        help='Directory with baselines ')
+                        help='Directory with baselines.'
+                             'Set "random" to generate baseline with random value from [-10,10].'
+                             'Set "random-100" to generate baseline with random value from [-100,100].')
     parser.add_argument('-g', '--geometry-dir', dest='geometryDir', type=str, default=None, required=True,
                         help='Directory with geometry files ')
     parser.add_argument('--geom-files', dest='geometryFiles', type=str, nargs='*',
@@ -77,6 +81,10 @@ def cmd_line_parse(iargs = None):
         else:
             raise FileNotFoundError(inps.metaFile)
 
+    # random baseline input checking
+    if inps.baselineDir.lower().startswith('rand'):
+        inps.baselineDir = inps.baselineDir.lower().replace('_','-')
+
     return inps
 
 
@@ -156,6 +164,27 @@ def prepare_geometry(geom_dir, geom_files=[], metadata=dict(), processor='tops',
     return
 
 
+def gen_random_baseline_timeseries(dset_dir, dset_file, max_bperp=10):
+    """Generate a baseline time series with random values.
+    """
+    # list of dates
+    fnames = glob.glob(os.path.join(dset_dir, '*', dset_file))
+    date12s = sorted([os.path.basename(os.path.dirname(x)) for x in fnames])
+    date1s = [x.split('_')[0] for x in date12s]
+    date2s = [x.split('_')[1] for x in date12s]
+    date_list = sorted(list(set(date1s + date2s)))
+
+    # list of bperp
+    bperp_list = [0] + np.random.randint(-max_bperp, max_bperp, len(date_list)-1).tolist()
+
+    # prepare output
+    bDict = {}
+    for date_str, bperp in zip(date_list, bperp_list):
+        bDict[date_str] = [bperp, bperp]
+
+    return bDict
+
+
 def prepare_stack(inputDir, filePattern, metadata=dict(), baseline_dict=dict(), processor='tops', update_mode=True):
     print('preparing RSC file for ', filePattern)
     if processor in ['tops', 'stripmap']:
@@ -221,8 +250,18 @@ def main(iargs=None):
     # read baseline info
     baseline_dict = {}
     if inps.baselineDir:
-        baseline_dict = isce_utils.read_baseline_timeseries(inps.baselineDir,
-                                                            processor=inps.processor)
+        if inps.baselineDir.startswith('rand') and inps.dsetDir and inps.dsetFiles:
+            if '-' in inps.baselineDir:
+                max_bperp = float(inps.baselineDir.split('-')[1])
+            else:
+                max_bperp = 10
+            baseline_dict = gen_random_baseline_timeseries(dset_dir=inps.dsetDir,
+                                                           dset_file=inps.dsetFiles[0],
+                                                           max_bperp=max_bperp)
+
+        else:
+            baseline_dict = isce_utils.read_baseline_timeseries(inps.baselineDir,
+                                                                processor=inps.processor)
 
     # prepare metadata for ifgram file
     if inps.dsetDir and inps.dsetFiles:

mintpy/smallbaselineApp.py

@@ -443,7 +443,7 @@ def generate_ifgram_aux_file(self):
         dsNames = readfile.get_dataset_list(stack_file)
         mask_file = os.path.join(self.workDir, 'maskConnComp.h5')
         coh_file = os.path.join(self.workDir, 'avgSpatialCoh.h5')
-        snr_file = os.path.join(self.workDir, 'avgSpatialSnr.h5')
+        snr_file = os.path.join(self.workDir, 'avgSpatialSNR.h5')
 
         # 1) generate mask file from the common connected components
         if any('phase' in i.lower() for i in dsNames):

mintpy/solid_earth_tides.py

@@ -216,23 +216,31 @@ def get_datetime_list(ts_file, date_wise_acq_time=False):
         sensingMid = [dt.datetime.strptime(i, date_str_format) for i in sensingMidStr]
 
     elif date_wise_acq_time and all(os.path.isdir(i) for i in xml_dirs):
-        # opt 2. read sensingMid in xml files
+        # opt 2. read sensingMid in xml files [for Sentinel-1 with topsStack]
         print('read exact datetime info in XML files from ISCE-2/topsStack results in directory:', proj_dir)
         from mintpy.utils import isce_utils
         sensingMid = isce_utils.get_sensing_datetime_list(proj_dir, date_list=date_list)[0]
 
         # plot
         plot_sensingMid_variation(sensingMid)
 
+    elif "T" in date_list[0]:
+        # opt 3. use the time info in the `date` dataset [as provided by UAVSAR stack]
+        date_format = ptime.get_date_str_format(date_list[0])
+        sensingMid = [dt.datetime.strptime(i, date_format) for i in date_list]
+
     else:
-        # opt 3. use constant time of the day for all acquisitions
-        msg =  'Use the same time of the day for all acquisitions from CENTER_LINE_UTC\n'
-        msg += 'With <= 1 min variation for Sentinel-1A/B for example, this simplication has negligible impact on SET calculation.'
-        print(msg)
+        # opt 4. use constant time of the day for all acquisitions
         atr = readfile.read_attribute(ts_file)
         utc_sec = dt.timedelta(seconds=float(atr['CENTER_LINE_UTC']))
         sensingMid = [dt.datetime.strptime(i, '%Y%m%d') + utc_sec for i in date_list]
 
+        msg =  'Use the same time of the day for all acquisitions from CENTER_LINE_UTC\n'
+        if atr.get('PLATFORM', 'Unknow').lower().startswith('sen'):
+            msg += 'With <= 1 min variation for Sentinel-1A/B for example, this simplication has negligible impact on SET calculation.'
+        print(msg)
+
+
     return sensingMid
 
 

mintpy/utils/plot.py

@@ -1446,7 +1446,9 @@ def prepare_dem_background(dem, inps=None, print_msg=True):
                                  vmax=inps.shade_max)
         dem_shade[np.isnan(dem_shade[:, :, 0])] = np.nan
         if print_msg:
-            print('show shaded relief DEM')
+            msg = f'show shaded relief DEM [min/max: {inps.shade_min}/{inps.shade_max} m; '
+            msg += f'exag: {inps.shade_exag}; az/alt deg: {inps.shade_azdeg}/{inps.shade_altdeg}]'
+            print(msg)
 
     # prepare contour
     if inps.disp_dem_contour: