diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index d6c2df8a48ca..2ef2226dc0bf 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -444,7 +444,7 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
# of over numbers.
self.norm.autoscale_None(A)
dv = np.float64(self.norm.vmax) - np.float64(self.norm.vmin)
- vmid = self.norm.vmin + dv / 2
+ vmid = np.float64(self.norm.vmin) + dv / 2
fact = 1e7 if scaled_dtype == np.float64 else 1e4
newmin = vmid - dv * fact
if newmin < a_min:
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 635d30900349..1b9dd306a4dc 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -1124,3 +1124,83 @@ def test_exact_vmin():
@pytest.mark.flaky
def test_https_imread_smoketest():
v = mimage.imread('https://matplotlib.org/1.5.0/_static/logo2.png')
+
+
+# A basic ndarray subclass that implements a quantity
+# It does not implement an entire unit system or all quantity math.
+# There is just enough implemented to test handling of ndarray
+# subclasses.
+class QuantityND(np.ndarray):
+ def __new__(cls, input_array, units):
+ obj = np.asarray(input_array).view(cls)
+ obj.units = units
+ return obj
+
+ def __array_finalize__(self, obj):
+ self.units = getattr(obj, "units", None)
+
+ def __getitem__(self, item):
+ units = getattr(self, "units", None)
+ ret = super(QuantityND, self).__getitem__(item)
+ if isinstance(ret, QuantityND) or units is not None:
+ ret = QuantityND(ret, units)
+ return ret
+
+ def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
+ func = getattr(ufunc, method)
+ if "out" in kwargs:
+ raise NotImplementedError
+ if len(inputs) == 1:
+ i0 = inputs[0]
+ unit = getattr(i0, "units", "dimensionless")
+ out_arr = func(np.asarray(i0), **kwargs)
+ elif len(inputs) == 2:
+ i0 = inputs[0]
+ i1 = inputs[1]
+ u0 = getattr(i0, "units", "dimensionless")
+ u1 = getattr(i1, "units", "dimensionless")
+ u0 = u1 if u0 is None else u0
+ u1 = u0 if u1 is None else u1
+ if ufunc in [np.add, np.subtract]:
+ if u0 != u1:
+ raise ValueError
+ unit = u0
+ elif ufunc == np.multiply:
+ unit = f"{u0}*{u1}"
+ elif ufunc == np.divide:
+ unit = f"{u0}/({u1})"
+ else:
+ raise NotImplementedError
+ out_arr = func(i0.view(np.ndarray), i1.view(np.ndarray), **kwargs)
+ else:
+ raise NotImplementedError
+ if unit is None:
+ out_arr = np.array(out_arr)
+ else:
+ out_arr = QuantityND(out_arr, unit)
+ return out_arr
+
+ @property
+ def v(self):
+ return self.view(np.ndarray)
+
+
+def test_quantitynd():
+ q = QuantityND([1, 2], "m")
+ q0, q1 = q[:]
+ assert np.all(q.v == np.asarray([1, 2]))
+ assert q.units == "m"
+ assert np.all((q0 + q1).v == np.asarray([3]))
+ assert (q0 * q1).units == "m*m"
+ assert (q1 / q0).units == "m/(m)"
+ with pytest.raises(ValueError):
+ q0 + QuantityND(1, "s")
+
+
+def test_imshow_quantitynd():
+ # generate a dummy ndarray subclass
+ arr = QuantityND(np.ones((2, 2)), "m")
+ fig, ax = plt.subplots()
+ ax.imshow(arr)
+ # executing the draw should not raise an exception
+ fig.canvas.draw()
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