Prevent match_template from returning NaNs.

skimage/feature/_template.pyx

@@ -119,11 +119,11 @@ def match_template(np.ndarray[float, ndim=2, mode="c"] image,
             window_sum = integrate(image_sat, i, j, i_end, j_end)
             window_mean_sqr = window_sum * window_sum * inv_area
             window_sqr_sum = integrate(image_sqr_sat, i, j, i_end, j_end)
-            den = sqrt((window_sqr_sum - window_mean_sqr) * template_ssd)
-
-            if den == 0:
+            if window_sqr_sum <= window_mean_sqr:
                 corr[i, j] = 0
-            else:
-                corr[i, j] /= den
+                continue
+
+            den = sqrt((window_sqr_sum - window_mean_sqr) * template_ssd)
+            corr[i, j] /= den
     return corr
 

skimage/feature/tests/test_template.py

@@ -70,6 +70,21 @@ def test_normalization():
     assert np.allclose(result.flat[iflat_max], 1)
 
 
+def test_no_nans():
+    """Test that `match_template` doesn't return NaN values.
+
+    When image values are only slightly different, floating-point errors can
+    cause a subtraction inside of a square root to go negative (without an
+    explicit check that was added to `match_template`).
+    """
+    np.random.seed(1)
+    image = 10000 + np.random.normal(size=(20, 20))
+    template = np.ones((6, 6))
+    template[:3, :] = 0
+    result = match_template(image, template)
+    assert not np.any(np.isnan(result))
+
+
 def test_switched_arguments():
     image = np.ones((5, 5))
     template = np.ones((3, 3))