@@ -518,19 +518,17 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
518518if isinstance (self .norm ,mcolors .NoNorm ):
519519A_resampled = A_resampled .astype (A .dtype )
520520
521+ # Compute out_mask (what screen pixels include "bad" data
522+ # pixels) and out_alpha (to what extent screen pixels are
523+ # covered by data pixels: 0 outside the data extent, 1 inside
524+ # (even for bad data), and intermediate values at the edges).
521525mask = (np .where (A .mask ,np .float32 (np .nan ),np .float32 (1 ))
522526if A .mask .shape == A .shape # nontrivial mask
523527else np .ones_like (A ,np .float32 ))
524528# we always have to interpolate the mask to account for
525529# non-affine transformations
526530out_alpha = _resample (self ,mask ,out_shape ,t ,resample = True )
527531del mask # Make sure we don't use mask anymore!
528- # Agg updates out_alpha in place. If the pixel has no image
529- # data it will not be updated (and still be 0 as we initialized
530- # it), if input data that would go into that output pixel than
531- # it will be `nan`, if all the input data for a pixel is good
532- # it will be 1, and if there is _some_ good data in that output
533- # pixel it will be between [0, 1] (such as a rotated image).
534532out_mask = np .isnan (out_alpha )
535533out_alpha [out_mask ]= 1
536534# Apply the pixel-by-pixel alpha values if present