Added fill_value option for extrapolation.

src/tirl/interpolators/scipyinterpolator.py

@@ -18,6 +18,7 @@
 
 # DEPENDENCIES
 
+import warnings
 import numpy as np
 
 
@@ -42,6 +43,13 @@ class ScipyInterpolator(Interpolator):
         kw = {k: v for k, v in self.kwargs.get("ipkwargs", dict()).items()}
         # Override the ones that were specified for the call
         kw.update(ipkwargs)
+        mode = kw.get("mode", None)
+
+        # Set default fill value unless the mode parameter was given
+        if mode is None:
+            mode = "constant"
+            cval = self.kwargs.get("fill_value")
+            kw.update(mode=mode, cval=cval)
 
         if isinstance(coordinates, (tuple, list)):
             coordinates = np.asarray(coordinates).reshape((1, -1))
@@ -57,7 +65,8 @@ class ScipyInterpolator(Interpolator):
 class ScipyRegularGridInterpolator(Interpolator):
 
     def __init__(self, source, tensor_axes=(), radius=1, hold=False,
-                 threads=-1, verbose=False, ipkwargs=None, **kwargs):
+                 threads=-1, verbose=False, ipkwargs=None, fill_value=None,
+                 **kwargs):
         """
         Initialisation of ScipyRegularGridInterpolator
 
@@ -65,7 +74,7 @@ class ScipyRegularGridInterpolator(Interpolator):
         # Set default arguments for the RegularGridInterpolator.
         # These parameters will repress out-of-bounds errors when values need
         # to be interpolated outside the domain of known values.
-        default_ipkwargs = dict(bounds_error=False, fill_value=ts.FILL_VALUE)
+        default_ipkwargs = dict(bounds_error=False, fill_value=fill_value)
         if isinstance(ipkwargs, dict):
             default_ipkwargs.update(ipkwargs)
         ipkwargs = default_ipkwargs
@@ -73,8 +82,11 @@ class ScipyRegularGridInterpolator(Interpolator):
         # Call parent-class initialisation
         super(ScipyRegularGridInterpolator, self).__init__(
             source, tensor_axes=tensor_axes, radius=radius, hold=hold,
-            threads=threads, verbose=verbose, ipkwargs=ipkwargs, **kwargs)
+            threads=threads, verbose=verbose, ipkwargs=ipkwargs,
+            fill_value=fill_value, **kwargs)
 
+        if self.ipkwargs.get("fill_value", None) is None:
+            self.ipkwargs.update(fill_value=ts.FILL_VALUE)
 
     def interpolate(self, coordinates, input_array=None, **ipkwargs):
         """
@@ -104,9 +116,10 @@ class ScipyRegularGridInterpolator(Interpolator):
 class ScipyNearestNeighbours(Interpolator):
 
     def __init__(self, source, tensor_axes=(), radius=1, hold=False,
-                 threads=-1, verbose=False, ipkwargs=None, **kwargs):
+                 threads=-1, verbose=False, ipkwargs=None, fill_value=None,
+                 **kwargs):
         """
-        Initialisation of ScipyRegularGridInterpolator
+        Initialisation of ScipyNearestNeighboursr
 
         """
         # Set default arguments for the RegularGridInterpolator.
@@ -117,11 +130,18 @@ class ScipyNearestNeighbours(Interpolator):
             default_ipkwargs.update(ipkwargs)
         ipkwargs = default_ipkwargs
 
+        # Note: the fill_value parameter lands in the kwargs, as it is not used
+        # by this interpolator.
+        if fill_value is not None:
+            warnings.warn(f"The fill_value parameter was ignored by "
+                          f"{self.__class__.__name__}")
+
         # Call parent-class initialisation
         super(ScipyNearestNeighbours, self).__init__(
             source, tensor_axes=tensor_axes, radius=radius, hold=hold,
             threads=threads, verbose=verbose, ipkwargs=ipkwargs, **kwargs)
 
+
     def interpolate(self, coordinates, input_array=None, **ipkwargs):
 
         from scipy.interpolate import NearestNDInterpolator