61 lines
2.2 KiB
Diff
61 lines
2.2 KiB
Diff
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From 29ce2c226aafc170cb9b874e81b158c832322cf7 Mon Sep 17 00:00:00 2001
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From: Jody Klymak <jklymak@gmail.com>
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Date: Thu, 5 May 2022 04:38:49 +0000
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Subject: [PATCH] FIX: fix check_1d to also check for ndim
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Arrays sometimes don't have all the methods arrays should have, so
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add another check here. Plot requires both ndim and shape and this
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will extract the numpy array if x does not have those attributes.
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Otherwise leave the object alone, because unit support (currently only
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in plot) requires the object to retain the unit info.
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---
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lib/matplotlib/cbook/__init__.py | 7 ++++++-
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lib/matplotlib/tests/test_units.py | 19 +++++++++++++++++++
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2 files changed, 25 insertions(+), 1 deletion(-)
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diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
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index 774643fc9c99..5a955ed459c5 100644
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--- a/lib/matplotlib/cbook/__init__.py
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+++ b/lib/matplotlib/cbook/__init__.py
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@@ -1333,7 +1333,12 @@ def _check_1d(x):
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"""Convert scalars to 1D arrays; pass-through arrays as is."""
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# Unpack in case of e.g. Pandas or xarray object
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x = _unpack_to_numpy(x)
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- if not hasattr(x, 'shape') or len(x.shape) < 1:
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+ # plot requires `shape` and `ndim`. If passed an
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+ # object that doesn't provide them, then force to numpy array.
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+ # Note this will strip unit information.
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+ if (not hasattr(x, 'shape') or
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+ not hasattr(x, 'ndim') or
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+ len(x.shape) < 1):
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return np.atleast_1d(x)
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else:
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return x
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diff --git a/lib/matplotlib/tests/test_units.py b/lib/matplotlib/tests/test_units.py
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index 93a12cebb2c8..d3b8c5a71643 100644
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--- a/lib/matplotlib/tests/test_units.py
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+++ b/lib/matplotlib/tests/test_units.py
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@@ -264,3 +264,22 @@ def test_empty_default_limits(quantity_converter):
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fig.draw_without_rendering()
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assert ax.get_ylim() == (0, 100)
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assert ax.get_xlim() == (28.5, 31.5)
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+
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+
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+# test array-like objects...
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+class Kernel:
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+ def __init__(self, array):
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+ self._array = np.asanyarray(array)
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+
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+ def __array__(self):
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+ return self._array
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+
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+ @property
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+ def shape(self):
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+ return self._array.shape
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+
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+
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+def test_plot_kernel():
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+ # just a smoketest that fail
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+ kernel = Kernel([1, 2, 3, 4, 5])
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+ plt.plot(kernel)
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