Make the filternorm prop of Images a boolean rather than a {0,1} scalar.

anntzer · anntzer · commit 9c6342d7fa6a · 2018-02-13T17:23:59.000+01:00
This seems a bit more pythonic and the C-API handles bools just as well.
Also filternorm and filterrad are always defined (as bool and float,
respectively, so no need to add `... or 0.0` when passing them to the
C-API.
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -5410,13 +5410,13 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
         shape : scalars (columns, rows), optional, default: None
             For raw buffer images
 
-        filternorm : scalar, optional, default: 1
-            A parameter for the antigrain image resize filter.  From the
-            antigrain documentation, if `filternorm` = 1, the filter
+        filternorm : bool, optional, default: True
+            A parameter for the antigrain image resize filter (see the
+            antigrain documentation). If *filternorm* is set, the filter
             normalizes integer values and corrects the rounding errors. It
             doesn't do anything with the source floating point values, it
             corrects only integers according to the rule of 1.0 which means
-            that any sum of pixel weights must be equal to 1.0.  So, the
+            that any sum of pixel weights must be equal to 1.0. So, the
             filter function must produce a graph of the proper shape.
 
         filterrad : scalar, optional, default: 4.0
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
@@ -206,7 +206,7 @@ def __init__(self, ax,
                  norm=None,
                  interpolation=None,
                  origin=None,
-                 filternorm=1,
+                 filternorm=True,
                  filterrad=4.0,
                  resample=False,
                  **kwargs
@@ -412,8 +412,8 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                                 t,
                                 _interpd_[self.get_interpolation()],
                                 self.get_resample(), 1.0,
-                                self.get_filternorm() or 0.0,
-                                self.get_filterrad() or 0.0)
+                                self.get_filternorm(),
+                                self.get_filterrad())
 
                 # we are done with A_scaled now, remove from namespace
                 # to be sure!
@@ -447,8 +447,8 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                                 t,
                                 _interpd_[self.get_interpolation()],
                                 True, 1,
-                                self.get_filternorm() or 0.0,
-                                self.get_filterrad() or 0.0)
+                                self.get_filternorm(),
+                                self.get_filterrad())
                 # we are done with the mask, delete from namespace to be sure!
                 del mask
                 # Agg updates the out_mask in place.  If the pixel has
@@ -481,7 +481,7 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                 _image.resample(
                     A, output, t, _interpd_[self.get_interpolation()],
                     self.get_resample(), alpha,
-                    self.get_filternorm() or 0.0, self.get_filterrad() or 0.0)
+                    self.get_filternorm(), self.get_filterrad())
 
             # at this point output is either a 2D array of normed data
             # (of int or float)
@@ -720,20 +720,17 @@ def get_resample(self):
 
     def set_filternorm(self, filternorm):
         """
-        Set whether the resize filter norms the weights -- see
-        help for imshow
+        Set whether the resize filter normalizes the weights.
 
-        ACCEPTS: 0 or 1
-        """
-        if filternorm:
-            self._filternorm = 1
-        else:
-            self._filternorm = 0
+        See help for `~.Axes.imshow`.
 
+        .. ACCEPTS: bool
+        """
+        self._filternorm = bool(filternorm)
         self.stale = True
 
     def get_filternorm(self):
-        """Return the filternorm setting."""
+        """Return whether the resize filter normalizes the weights."""
         return self._filternorm
 
     def set_filterrad(self, filterrad):
