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Backport PR #22975 on branch v3.5.x (MNT: fix __array__ to numpy) #23064

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7 changes: 6 additions & 1 deletion lib/matplotlib/cbook/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -1302,7 +1302,12 @@ def _check_1d(x):
"""Convert scalars to 1D arrays; pass-through arrays as is."""
# Unpack in case of e.g. Pandas or xarray object
x = _unpack_to_numpy(x)
if not hasattr(x, 'shape') or len(x.shape) < 1:
# plot requires `shape` and `ndim`. If passed an
# object that doesn't provide them, then force to numpy array.
# Note this will strip unit information.
if (not hasattr(x, 'shape') or
not hasattr(x, 'ndim') or
len(x.shape) < 1):
return np.atleast_1d(x)
else:
return x
Expand Down
19 changes: 19 additions & 0 deletions lib/matplotlib/tests/test_units.py
Original file line number Diff line number Diff line change
Expand Up @@ -261,3 +261,22 @@ def test_empty_default_limits(quantity_converter):
fig.draw_without_rendering()
assert ax.get_ylim() == (0, 100)
assert ax.get_xlim() == (28.5, 31.5)


# test array-like objects...
class Kernel:
def __init__(self, array):
self._array = np.asanyarray(array)

def __array__(self):
return self._array

@property
def shape(self):
return self._array.shape


def test_plot_kernel():
# just a smoketest that fail
kernel = Kernel([1, 2, 3, 4, 5])
plt.plot(kernel)