geocode: add OMP_NUM_THREADS control

+ add geocode/check_num_processor() to check OMP_NUM_THREADS if it's defined in environment variable and use it if --nprocs is not specified.

+ set default --nprocs to 1 because 1) bonding between pykdtree and openmp is not clear yet and 2) the speedup is negligible for macport install and slows down for conda install

+ change default nprocs value to 1 in objects/resample.py

+ detect lookup table file in current directory besides the INPUTS directory.

pysar/geocode.py

@@ -70,8 +70,8 @@ def create_parser():
     parser.add_argument('--fill', dest='fillValue', type=float, default=np.nan,
                         help='Value used for points outside of the interpolation domain.\n' +
                              'Default: np.nan')
-    parser.add_argument('-n','--nprocs', dest='nprocs', type=int,
-                        help='number of processors to be used for calculation.\n' + 
+    parser.add_argument('-n','--nprocs', dest='nprocs', type=int, default=1,
+                        help='number of processors to be used for calculation. Default: 1\n' + 
                              'Note: Do not use more processes than available processor cores.')
     parser.add_argument('-p','--processor', dest='processor', type=str, choices={'pyresample', 'scipy'},
                         help='processor module used for interpolation.')
@@ -88,6 +88,12 @@ def create_parser():
 def cmd_line_parse(iargs=None):
     parser = create_parser()
     inps = parser.parse_args(args=iargs)
+
+    if inps.templateFile:
+        inps = read_template2inps(inps.templateFile, inps)
+
+    inps = _check_inps(inps)
+
     return inps
 
 
@@ -119,6 +125,7 @@ def _check_inps(inps):
     if None in inps.laloStep:
         inps.laloStep = None
 
+    inps.nprocs = check_num_processor(inps.nprocs)
     return inps
 
 
@@ -155,6 +162,26 @@ def read_template2inps(template_file, inps):
 
 
 ############################################################################################
+def check_num_processor(nprocs):
+    """Check number of processors
+    Note by Yunjun, 2019-05-02:
+    1. conda install pyresample will install pykdtree and openmp, but it seems not working
+        geocode.py is getting slower with more processors
+    2. macports seems to have minor speedup when more processors
+    Thus, default number of processors is set to 1; although the capability of using multiple
+    processors is written here.
+    """
+    if not nprocs:
+        #OMP_NUM_THREADS is defined in environment variable for OpenMP
+        if 'OMP_NUM_THREADS' in os.environ:
+            nprocs = int(os.getenv('OMP_NUM_THREADS'))
+        else:
+            nprocs = int(multiprocessing.cpu_count() / 2)
+    nprocs = min(multiprocessing.cpu_count(), nprocs)
+    print('number of processor to be used: {}'.format(nprocs))
+    return nprocs
+
+
 def metadata_radar2geo(atr_in, res_obj, print_msg=True):
     """update metadata for radar to geo coordinates"""
     atr = dict(atr_in)
@@ -249,9 +276,6 @@ def run_geocode(inps):
                        processor=inps.processor)
     res_obj.open()
 
-    if not inps.nprocs:
-        inps.nprocs = multiprocessing.cpu_count()
-
     # resample input files one by one
     for infile in inps.file:
         print('-' * 50+'\nresampling file: {}'.format(infile))
@@ -275,8 +299,11 @@ def run_geocode(inps):
             else:
                 data, atr = readfile.read(infile, datasetName=dsName, print_msg=False)
 
+            # keep timeseries data as 3D matrix when there is only one acquisition
+            # because readfile.read() will squeeze it to 2D
             if atr['FILE_TYPE'] == 'timeseries' and len(data.shape) == 2:
                 data = np.reshape(data, (1, data.shape[0], data.shape[1]))
+
             res_data = res_obj.run_resample(src_data=data,
                                             interp_method=inps.interpMethod,
                                             fill_value=inps.fillValue,
@@ -303,9 +330,6 @@ def run_geocode(inps):
 ######################################################################################
 def main(iargs=None):
     inps = cmd_line_parse(iargs)
-    if inps.templateFile:
-        inps = read_template2inps(inps.templateFile, inps)
-    inps = _check_inps(inps)
 
     run_geocode(inps)
     return

pysar/objects/resample.py

@@ -60,7 +60,7 @@ def open(self):
         elif self.processor == 'scipy' and 'Y_FIRST' in self.lut_metadata.keys():
             self.prepare_regular_grid_interpolator()
 
-    def run_resample(self, src_data, interp_method='nearest', fill_value=np.nan, nprocs=None, print_msg=True):
+    def run_resample(self, src_data, interp_method='nearest', fill_value=np.nan, nprocs=1, print_msg=True):
         """Run interpolation operation for input 2D/3D data
         Parameters: src_data      : 2D/3D np.array, source data to be geocoded
                     interp_method : string, nearest | linear
@@ -355,7 +355,7 @@ def get_segment_number(self, unit_size=1e6):
         num_segment = int(self.dest_def.size / unit_size + 0.5)
         return num_segment
 
-    def run_pyresample(self, src_data, interp_method='nearest', fill_value=np.nan, nprocs=None,
+    def run_pyresample(self, src_data, interp_method='nearest', fill_value=np.nan, nprocs=1,
                        radius=None, print_msg=True):
         """
         Resample input src_data into dest_data
@@ -377,17 +377,17 @@ def run_pyresample(self, src_data, interp_method='nearest', fill_value=np.nan, n
             else:
                 radius = self.get_radius_of_influence()
 
-        if not nprocs:
-            nprocs = multiprocessing.cpu_count()
-
         num_segment = self.get_segment_number()
 
         if interp_method.startswith('near'):
             if print_msg:
-                print('nearest resampling with kd_tree ({} segments) ...'.format(num_segment))
+                msg = 'nearest resampling with kd_tree '
+                msg += 'using {} processor cores in {} segments ...'.format(nprocs, num_segment)
+                print(msg)
             dest_data = pr.kd_tree.resample_nearest(self.src_def,
                                                     src_data,
                                                     self.dest_def,
+                                                    nprocs=nprocs,
                                                     fill_value=fill_value,
                                                     radius_of_influence=radius,
                                                     segments=num_segment,

pysar/utils/utils1.py

@@ -367,7 +367,7 @@ def get_lookup_file(filePattern=None, abspath=False, print_msg=True):
                        'geometryGeo_tight.h5', 'geometryGeo.h5',
                        'geomap*lks_tight.trans', 'geomap*lks.trans',
                        'sim*_tight.UTM_TO_RDC', 'sim*.UTM_TO_RDC']
-        filePattern = [os.path.join('INPUTS', i) for i in filePattern]
+        filePattern = [os.path.join('INPUTS', i) for i in filePattern] + filePattern
     existFiles = []
     try:
         existFiles = get_file_list(filePattern)