Use NumpyBilinearResampler instead of the deprecated resample_bilinear().

Signed-off-by: Daniel Scheffler <danschef@gfz-potsdam.de>

sensormapgeo/transformer_2d.py

@@ -48,7 +48,7 @@ with warnings.catch_warnings():
     # NOTE: In case of ImportError: dlopen: cannot load any more object with static TLS,
     #       one could add 'from pykdtree.kdtree import KDTree' here (before pyresample import)
     from pyresample.geometry import AreaDefinition, SwathDefinition, create_area_def
-    from pyresample.bilinear import resample_bilinear
+    from pyresample.bilinear import NumpyBilinearResampler
     from pyresample.kd_tree import resample_nearest, resample_gauss, resample_custom
 
 from .version import __version__ as _libver
@@ -102,10 +102,6 @@ class SensorMapGeometryTransformer(object):
                          sigmas=(radius_of_influence / 2))
         self.opts.update(opts)
 
-        if resamp_alg == 'bilinear':
-            del self.opts['radius_of_influence']
-            self.opts['radius'] = radius_of_influence
-
         # NOTE: If pykdtree is built with OpenMP support (default) the number of threads is controlled with the
         #       standard OpenMP environment variable OMP_NUM_THREADS. The nprocs argument has no effect on pykdtree.
         os.environ['OMP_NUM_THREADS'] = '%d' % (self.opts['nprocs'] if 'nprocs' in self.opts else 1)
@@ -284,34 +280,40 @@ class SensorMapGeometryTransformer(object):
         :param target_geo_def:  target geo definition
         :return:
         """
+        opts = self.opts.copy()
+
         if self.resamp_alg == 'nearest':
-            opts = {k: v for k, v in self.opts.items() if k not in ['sigmas']}
+            opts.pop('sigmas', None)
             result = resample_nearest(source_geo_def, data, target_geo_def, **opts).astype(data.dtype)
 
         elif self.resamp_alg == 'bilinear':
-            opts = {k: v for k, v in self.opts.items() if k not in ['sigmas']}
+            opts.pop('sigmas', None)
             with warnings.catch_warnings():
                 # suppress a UserWarning coming from pyresample v0.15.0
                 warnings.filterwarnings('ignore', category=UserWarning,
                                         message='You will likely lose important projection information when converting '
                                                 'to a PROJ string from another format.')
-                result = resample_bilinear(data, source_geo_def, target_geo_def, **opts).astype(data.dtype)
+                kw_rsp = dict(fill_value=opts.pop('fill_value', 0),
+                              nprocs=opts.pop('nprocs', 1))
+                result = \
+                    NumpyBilinearResampler(source_geo_def, target_geo_def, **opts)\
+                    .resample(data, **kw_rsp)\
+                    .astype(data.dtype)
 
         elif self.resamp_alg == 'gauss':
-            opts = {k: v for k, v in self.opts.items()}
-
             # ensure that sigmas are provided as list if data is 3-dimensional
             if data.ndim != 2:
+                n_sigmas = len(opts['sigmas'])  # noqa
+
                 if not isinstance(opts['sigmas'], list):
                     opts['sigmas'] = [opts['sigmas']] * data.ndim
-                if not len(opts['sigmas']) == data.ndim:
+                if not n_sigmas == data.ndim:
                     raise ValueError("The 'sigmas' parameter must have the same number of values like data.ndim."
-                                     "n_sigmas: %d; data.ndim: %d" % (len(opts['sigmas']), data.ndim))
+                                     "n_sigmas: %d; data.ndim: %d" % (n_sigmas, data.ndim))
 
             result = resample_gauss(source_geo_def, data, target_geo_def, **opts).astype(data.dtype)
 
         elif self.resamp_alg == 'custom':
-            opts = {k: v for k, v in self.opts.items()}
             if 'weight_funcs' not in opts:
                 raise ValueError(opts, "Options must contain a 'weight_funcs' item.")
             result = resample_custom(source_geo_def, data, target_geo_def, **opts).astype(data.dtype)
@@ -404,7 +406,6 @@ class SensorMapGeometryTransformer(object):
                           f"geometry to sensor geometry due to changes in upstream packages. Using 'gauss' instead. "
                           f"Note that bilinear resampling works in sensormapgeo<=0.5.0.", RuntimeWarning)
             self.resamp_alg = 'gauss'
-            self.opts['radius_of_influence'] = self.opts.pop('radius')
 
         # get area_definition
         self.area_definition = AreaDefinition('', '', '',  CRS(src_prj), data.shape[1], data.shape[0],