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Fix spelling error in contains_branch_separately method name #30475

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Merged
timhoffm merged 1 commit into from
Sep 2, 2025
Merged

Fix spelling error in contains_branch_separately method name #30475

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6 changes: 3 additions & 3 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1183,7 +1183,7 @@ def hlines(self, y, xmin, xmax, colors=None, linestyles='solid',
if self.name == "rectilinear":
datalim = lines.get_datalim(self.transData)
t = lines.get_transform()
updatex, updatey = t.contains_branch_seperately(self.transData)
updatex, updatey = t.contains_branch_separately(self.transData)
minx = np.nanmin(datalim.xmin)
maxx = np.nanmax(datalim.xmax)
miny = np.nanmin(datalim.ymin)
Expand Down Expand Up @@ -1275,7 +1275,7 @@ def vlines(self, x, ymin, ymax, colors=None, linestyles='solid',
if self.name == "rectilinear":
datalim = lines.get_datalim(self.transData)
t = lines.get_transform()
updatex, updatey = t.contains_branch_seperately(self.transData)
updatex, updatey = t.contains_branch_separately(self.transData)
minx = np.nanmin(datalim.xmin)
maxx = np.nanmax(datalim.xmax)
miny = np.nanmin(datalim.ymin)
Expand Down Expand Up @@ -6809,7 +6809,7 @@ def _update_pcolor_lims(self, collection, coords):
hasattr(t, '_as_mpl_transform')):
t = t._as_mpl_transform(self.axes)

if t and any(t.contains_branch_seperately(self.transData)):
if t and any(t.contains_branch_separately(self.transData)):
trans_to_data = t - self.transData
coords = trans_to_data.transform(coords)

Expand Down
10 changes: 5 additions & 5 deletions lib/matplotlib/axes/_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2380,9 +2380,9 @@ def add_collection(self, collection, autolim=True):
# only update the dataLim for x/y if the collection uses transData
# in this direction.
x_is_data, y_is_data = (collection.get_transform()
.contains_branch_seperately(self.transData))
.contains_branch_separately(self.transData))
ox_is_data, oy_is_data = (collection.get_offset_transform()
.contains_branch_seperately(self.transData))
.contains_branch_separately(self.transData))
self.update_datalim(
points,
updatex=x_is_data or ox_is_data,
Expand Down Expand Up @@ -2451,7 +2451,7 @@ def _update_line_limits(self, line):

if line_trf == self.transData:
data_path = path
elif any(line_trf.contains_branch_seperately(self.transData)):
elif any(line_trf.contains_branch_separately(self.transData)):
# Compute the transform from line coordinates to data coordinates.
trf_to_data = line_trf - self.transData
# If transData is affine we can use the cached non-affine component
Expand All @@ -2474,7 +2474,7 @@ def _update_line_limits(self, line):
if not data_path.vertices.size:
return

updatex, updatey = line_trf.contains_branch_seperately(self.transData)
updatex, updatey = line_trf.contains_branch_separately(self.transData)
if self.name != "rectilinear":
# This block is mostly intended to handle axvline in polar plots,
# for which updatey would otherwise be True.
Expand Down Expand Up @@ -2527,7 +2527,7 @@ def _update_patch_limits(self, patch):
vertices = np.vstack(vertices)

patch_trf = patch.get_transform()
updatex, updatey = patch_trf.contains_branch_seperately(self.transData)
updatex, updatey = patch_trf.contains_branch_separately(self.transData)
if not (updatex or updatey):
return
if self.name != "rectilinear":
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/collections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -283,7 +283,7 @@ def get_datalim(self, transData):

offsets = self.get_offsets()

if any(transform.contains_branch_seperately(transData)):
if any(transform.contains_branch_separately(transData)):
# collections that are just in data units (like quiver)
# can properly have the axes limits set by their shape +
# offset. LineCollections that have no offsets can
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1333,7 +1333,7 @@ def _process_args(self, *args, corner_mask=None, algorithm=None, **kwargs):
# if the transform is not trans data, and some part of it
# contains transData, transform the xs and ys to data coordinates
if (t != self.axes.transData and
any(t.contains_branch_seperately(self.axes.transData))):
any(t.contains_branch_separately(self.axes.transData))):
trans_to_data = t - self.axes.transData
pts = np.vstack([x.flat, y.flat]).T
transformed_pts = trans_to_data.transform(pts)
Expand Down
4 changes: 2 additions & 2 deletions lib/matplotlib/tests/test_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -694,9 +694,9 @@ def test_contains_branch(self):
assert not self.stack1.contains_branch(self.tn1 + self.ta2)

blend = mtransforms.BlendedGenericTransform(self.tn2, self.stack2)
x, y = blend.contains_branch_seperately(self.stack2_subset)
x, y = blend.contains_branch_separately(self.stack2_subset)
stack_blend = self.tn3 + blend
sx, sy = stack_blend.contains_branch_seperately(self.stack2_subset)
sx, sy = stack_blend.contains_branch_separately(self.stack2_subset)
assert x is sx is False
assert y is sy is True

Expand Down
19 changes: 12 additions & 7 deletions lib/matplotlib/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1418,24 +1418,29 @@ def contains_branch(self, other):
return True
return False

def contains_branch_seperately(self, other_transform):
def contains_branch_separately(self, other_transform):
"""
Return whether the given branch is a sub-tree of this transform on
each separate dimension.

A common use for this method is to identify if a transform is a blended
transform containing an Axes' data transform. e.g.::

x_isdata, y_isdata = trans.contains_branch_seperately(ax.transData)
x_isdata, y_isdata = trans.contains_branch_separately(ax.transData)

"""
if self.output_dims != 2:
raise ValueError('contains_branch_seperately only supports '
raise ValueError('contains_branch_separately only supports '
'transforms with 2 output dimensions')
# for a non-blended transform each separate dimension is the same, so
# just return the appropriate shape.
return (self.contains_branch(other_transform), ) * 2

# Permanent alias for backwards compatibility (historical typo)
def contains_branch_seperately(self, other_transform):
""":meta private:"""
return self.contains_branch_separately(other_transform)

def __sub__(self, other):
"""
Compose *self* with the inverse of *other*, cancelling identical terms
Expand Down Expand Up @@ -2185,7 +2190,7 @@ def __eq__(self, other):
else:
return NotImplemented

def contains_branch_seperately(self, transform):
def contains_branch_separately(self, transform):
return (self._x.contains_branch(transform),
self._y.contains_branch(transform))

Expand Down Expand Up @@ -2411,14 +2416,14 @@ def _iter_break_from_left_to_right(self):
for left, right in self._b._iter_break_from_left_to_right():
yield self._a + left, right

def contains_branch_seperately(self, other_transform):
def contains_branch_separately(self, other_transform):
# docstring inherited
if self.output_dims != 2:
raise ValueError('contains_branch_seperately only supports '
raise ValueError('contains_branch_separately only supports '
'transforms with 2 output dimensions')
if self == other_transform:
return (True, True)
return self._b.contains_branch_seperately(other_transform)
return self._b.contains_branch_separately(other_transform)

depth = property(lambda self: self._a.depth + self._b.depth)
is_affine = property(lambda self: self._a.is_affine and self._b.is_affine)
Expand Down
5 changes: 3 additions & 2 deletions lib/matplotlib/transforms.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -189,9 +189,10 @@ class Transform(TransformNode):
@property
def depth(self) -> int: ...
def contains_branch(self, other: Transform) -> bool: ...
def contains_branch_seperately(
def contains_branch_separately(
self, other_transform: Transform
) -> Sequence[bool]: ...
contains_branch_seperately = contains_branch_separately # Alias (historical typo)
def __sub__(self, other: Transform) -> Transform: ...
def __array__(self, *args, **kwargs) -> np.ndarray: ...
def transform(self, values: ArrayLike) -> np.ndarray: ...
Expand Down Expand Up @@ -252,7 +253,7 @@ class IdentityTransform(Affine2DBase): ...

class _BlendedMixin:
def __eq__(self, other: object) -> bool: ...
def contains_branch_seperately(self, transform: Transform) -> Sequence[bool]: ...
def contains_branch_separately(self, transform: Transform) -> Sequence[bool]: ...

class BlendedGenericTransform(_BlendedMixin, Transform):
input_dims: Literal[2]
Expand Down
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