diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 6d3d5b936729..4f0679048329 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -3285,26 +3285,17 @@ def _upcast_err(err):
"""
Safely handle tuple of containers that carry units.
- If the units are carried on the values then casting to object
- arrays preserves the units, but if the units are on the containers
- this will not work.
-
This function covers the case where the input to the xerr/yerr is a
length 2 tuple of equal length ndarray-subclasses that carry the
unit information in the container.
- We defer coercing the units to be consistent to the underlying unit
+ If we have a tuple of nested numpy array (subclasses), we defer
+ coercing the units to be consistent to the underlying unit
library (and implicitly the broadcasting).
- If we do not have a tuple of nested numpy array (subclasses),
- fallback to casting to an object array.
-
+ Otherwise, fallback to casting to an object array.
"""
- # we are here because we the container is not a numpy array, but it
- # _is_ iterable (likely a list or a tuple but maybe something more
- # exotic)
-
if (
# make sure it is not a scalar
np.iterable(err) and
@@ -3316,14 +3307,17 @@ def _upcast_err(err):
# fails.
isinstance(cbook.safe_first_element(err), np.ndarray)
):
- # grab the type of the first element, we will try to promote
- # the outer container to match the inner container
+ # Get the type of the first element
atype = type(cbook.safe_first_element(err))
- # you can not directly pass data to the init of `np.ndarray`
+ # Promote the outer container to match the inner container
if atype is np.ndarray:
+ # Converts using np.asarray, because data cannot
+ # be directly passed to init of np.ndarray
return np.asarray(err, dtype=object)
- # but you can for unyt and astropy uints
+ # If atype is not np.ndarray, directly pass data to init.
+ # This works for types such as unyts and astropy units
return atype(err)
+ # Otherwise wrap it in an object array
return np.asarray(err, dtype=object)
if xerr is not None and not isinstance(xerr, np.ndarray):
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