Merge pull request #10768 from jinshifen33/bugfix-for-issue-10342

jklymak · web-flow · commit f49c7b3d85e3 · 2018-03-15T08:45:52.000-07:00
Fix crash when imshow encounters longdouble data
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -954,11 +954,6 @@ def __call__(self, value, clip=None):
             resdat -= vmin
             resdat /= (vmax - vmin)
             result = np.ma.array(resdat, mask=result.mask, copy=False)
-        # Agg cannot handle float128.  We actually only need 32-bit of
-        # precision, but on Windows, `np.dtype(np.longdouble) == np.float64`,
-        # so casting to float32 would lose precision on float64s as well.
-        if result.dtype == np.longdouble:
-            result = result.astype(np.float64)
         if is_scalar:
             result = result[0]
         return result
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
@@ -12,6 +12,7 @@
 from math import ceil
 import os
 import logging
+import warnings
 
 import numpy as np
 
@@ -264,8 +265,8 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
         and magnified by the magnification factor.
 
         `A` may be a greyscale image (MxN) with a dtype of `float32`,
-        `float64`, `uint16` or `uint8`, or an RGBA image (MxNx4) with
-        a dtype of `float32`, `float64`, or `uint8`.
+        `float64`, `float128`, `uint16` or `uint8`, or an RGBA image (MxNx4)
+        with a dtype of `float32`, `float64`, `float128`, or `uint8`.
 
         If `unsampled` is True, the image will not be scaled, but an
         appropriate affine transformation will be returned instead.
@@ -361,6 +362,13 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     a_min, a_max = np.int32(0), np.int32(1)
                 if inp_dtype.kind == 'f':
                     scaled_dtype = A.dtype
+                    # Cast to float64
+                    if A.dtype not in (np.float32, np.float16):
+                        if A.dtype != np.float64:
+                            warnings.warn(
+                                "Casting input data from '{0}' to 'float64'"
+                                "for imshow".format(A.dtype))
+                        scaled_dtype = np.float64
                 else:
                     # probably an integer of some type.
                     da = a_max.astype(np.float64) - a_min.astype(np.float64)
@@ -386,7 +394,7 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                 # of over numbers.
                 if self.norm.vmin is not None and self.norm.vmax is not None:
                     dv = (np.float64(self.norm.vmax) -
-                            np.float64(self.norm.vmin))
+                          np.float64(self.norm.vmin))
                     vmid = self.norm.vmin + dv / 2
                     newmin = vmid - dv * 1.e7
                     if newmin < a_min:
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
@@ -903,6 +903,8 @@ def test_empty_imshow(make_norm):
 def test_imshow_float128():
     fig, ax = plt.subplots()
     ax.imshow(np.zeros((3, 3), dtype=np.longdouble))
+    # Ensure that drawing doesn't cause crash
+    fig.canvas.draw()
 
 
 def test_imshow_bool():
