Closed as not planned
Closed as not planned
Description
Summary
For context, see numpy/numpy#10615
One way matplotlib currently hits the new deprecation warning (there might be others) can be reproduced as
# t.py
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()
ax.set_ylim(np.array([-1]), 1)$ python -Werror t.py
Traceback (most recent call last):
File "/Users/robcleme/dev/matplotlib/t.py", line 6, in <module>
ax.set_ylim(np.array([-1]), 1)
File "/Users/robcleme/dev/matplotlib/lib/matplotlib/axes/_base.py", line 3873, in set_ylim
return self.yaxis._set_lim(bottom, top, emit=emit, auto=auto)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/robcleme/dev/matplotlib/lib/matplotlib/axis.py", line 1214, in _set_lim
v0, v1 = self.get_major_locator().nonsingular(v0, v1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/robcleme/dev/matplotlib/lib/matplotlib/ticker.py", line 1644, in nonsingular
return mtransforms.nonsingular(v0, v1, expander=.05)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/robcleme/dev/matplotlib/lib/matplotlib/transforms.py", line 2844, in nonsingular
vmin, vmax = map(float, [vmin, vmax])
^^^^^^^^^^
DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
Proposed fix
The following patch resolves the one issue for which I included a reproducer
diff --git a/lib/matplotlib/transforms.py b/lib/matplotlib/transforms.py
index 03c8a9f97a..aa345fb295 100644
--- a/lib/matplotlib/transforms.py
+++ b/lib/matplotlib/transforms.py
@@ -2841,7 +2841,7 @@ def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=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])
+ vmin, vmax = map(lambda x: float(np.asarray(x).item()), [vmin, vmax])
maxabsvalue = max(abs(vmin), abs(vmax))
if maxabsvalue < (1e6 / tiny) * np.finfo(float).tiny:I will open a PR with this patch, but careful inspection is needed to make sure the rest of the code base is safe.