diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index 7f6a023e91a5..14866cc1012c 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -534,9 +534,13 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
resampled_masked = np.ma.masked_array(A_resampled, out_mask)
# we have re-set the vmin/vmax to account for small errors
# that may have moved input values in/out of range
+ s_vmin, s_vmax = vrange
+ if isinstance(self.norm, mcolors.LogNorm):
+ if s_vmin < 0:
+ s_vmin = max(s_vmin, np.finfo(scaled_dtype).eps)
with cbook._setattr_cm(self.norm,
- vmin=vrange[0],
- vmax=vrange[1],
+ vmin=s_vmin,
+ vmax=s_vmax,
):
output = self.norm(resampled_masked)
else:
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 9e635b96d1b6..87e3c121d4c0 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -1117,3 +1117,22 @@ def test_exact_vmin():
@pytest.mark.flaky
def test_https_imread_smoketest():
v = mimage.imread('https://matplotlib.org/1.5.0/_static/logo2.png')
+
+
+@check_figures_equal(extensions=['png'])
+def test_huge_range_log(fig_test, fig_ref):
+ data = np.full((5, 5), -1, dtype=np.float64)
+ data[0:2, :] = 1E20
+
+ ax = fig_test.subplots()
+ im = ax.imshow(data, norm=colors.LogNorm(vmin=100, vmax=data.max()),
+ interpolation='nearest', cmap='viridis')
+
+ data = np.full((5, 5), -1, dtype=np.float64)
+ data[0:2, :] = 1000
+
+ cm = copy(plt.get_cmap('viridis'))
+ cm.set_under('w')
+ ax = fig_ref.subplots()
+ im = ax.imshow(data, norm=colors.Normalize(vmin=100, vmax=data.max()),
+ interpolation='nearest', cmap=cm)
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