diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index 0ab02c403d0d..ce08e2470d2f 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -452,6 +452,8 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
# Always copy, and don't allow array subtypes.
A_scaled = np.array(A, dtype=scaled_dtype)
+ a_min = np.float64(a_min)
+ a_max = np.float64(a_max)
# Clip scaled data around norm if necessary. This is necessary
# for big numbers at the edge of float64's ability to represent
# changes. Applying a norm first would be good, but ruins the
diff --git a/lib/matplotlib/tests/test_colorbar.py b/lib/matplotlib/tests/test_colorbar.py
index 74742d8c2369..cd7f6c223dd3 100644
--- a/lib/matplotlib/tests/test_colorbar.py
+++ b/lib/matplotlib/tests/test_colorbar.py
@@ -1238,3 +1238,48 @@ def test_colorbar_format_string_and_old():
plt.imshow([[0, 1]])
cb = plt.colorbar(format="{x}%")
assert isinstance(cb._formatter, StrMethodFormatter)
+
+
+def test_colorbar_log_units():
+ class FakeQuantity(np.ndarray):
+ # this is a self-contained version of astropy.units.Quantity
+ # reduced to a bare minimum to reproduce
+ # https://github.com/astropy/astropy/issues/11306
+
+ def __new__(cls, value):
+ return np.array(value).view(cls)
+
+ def __array_ufunc__(self, function, method, *inputs, **kwargs):
+ def to_value(q):
+ value = q.view(np.ndarray)
+ if value.shape:
+ return value
+ else:
+ return value[()]
+
+ arrays = [to_value(q) for q in inputs]
+ result = super().__array_ufunc__(function, method, *arrays, **kwargs)
+ if function not in (np.minimum, np.maximum):
+ return result
+ else:
+ return self._new_view(result)
+
+ def _new_view(self, obj):
+ obj = np.array(obj, copy=False, subok=True)
+ view = obj.view(FakeQuantity)
+ return view
+
+ def __ne__(self, other):
+ return NotImplemented
+
+ def __float__(self):
+ raise RuntimeError("boom")
+
+ def item(self, *args):
+ return self._new_view(super().item(*args))
+
+ data = FakeQuantity([[1, 2], [3, 4]])
+ fig, ax = plt.subplots()
+ im = ax.imshow(data, norm=LogNorm())
+ fig.colorbar(im)
+ fig.canvas.draw()
diff --git a/lib/matplotlib/transforms.py b/lib/matplotlib/transforms.py
index 5003e2113930..4b0cd1cd035b 100644
--- a/lib/matplotlib/transforms.py
+++ b/lib/matplotlib/transforms.py
@@ -2853,15 +2853,15 @@ def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=True):
if (not np.isfinite(vmin)) or (not np.isfinite(vmax)):
return -expander, expander
+ # Expand vmin, vmax to float: if they were integer types, they can wrap
+ # around in abs (abs(np.int8(-128)) == -128) and vmax - vmin can overflow.
+ vmin, vmax = map(np.float64, (vmin, vmax))
+
swapped = False
if vmax < vmin:
vmin, vmax = vmax, vmin
swapped = True
- # Expand vmin, vmax to float: if they were integer types, they can wrap
- # around in abs (abs(np.int8(-128)) == -128) and vmax - vmin can overflow.
- vmin, vmax = map(float, [vmin, vmax])
-
maxabsvalue = max(abs(vmin), abs(vmax))
if maxabsvalue < (1e6 / tiny) * np.finfo(float).tiny:
vmin = -expander
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