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FIX: Handle no-offsets in collection datalim (alternative) #22946

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merged 2 commits into from
May 1, 2022
Merged

FIX: Handle no-offsets in collection datalim (alternative) #22946

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de4a94c
FIX: Handle no-offsets in collection datalim
greglucas Apr 30, 2022
e953840
MNT: Use get_offsets() to handle the default/None case
greglucas Apr 30, 2022
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MNT: Use get_offsets() to handle the default/None case 
This avoids carrying around an extra offsetsNone/has_offsets variable
to keep track of the default case. Instead calling get_offsets() to
return the default zeros case, and then internally checking the
None/default case in get_datalim() which is the only place where this
information is needed.
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@greglucas
greglucas committed May 1, 2022
commit e95384083dd2319a1b720789244c68c8d1c516bb
92 changes: 44 additions & 48 deletions lib/matplotlib/collections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,6 @@ class Collection(artist.Artist, cm.ScalarMappable):
mappable will be used to set the ``facecolors`` and ``edgecolors``,
ignoring those that were manually passed in.
"""
_offsets = np.zeros((0, 2))
#: Either a list of 3x3 arrays or an Nx3x3 array (representing N
#: transforms), suitable for the `all_transforms` argument to
#: `~matplotlib.backend_bases.RendererBase.draw_path_collection`;
Expand Down Expand Up @@ -193,16 +192,12 @@ def __init__(self,
else:
self._joinstyle = None

# default to zeros
self._offsets = np.zeros((1, 2))
self._has_offsets = offsets is not None

if self._has_offsets:
if offsets is not None:
offsets = np.asanyarray(offsets, float)
# Broadcast (2,) -> (1, 2) but nothing else.
if offsets.shape == (2,):
offsets = offsets[None, :]
self._offsets = offsets
self._offsets = offsets

self._offset_transform = offset_transform

Expand Down Expand Up @@ -264,9 +259,12 @@ def get_datalim(self, transData):
# if the offsets are in some coords other than data,
# then don't use them for autoscaling.
return transforms.Bbox.null()
offsets = self._offsets
offsets = self.get_offsets()

paths = self.get_paths()
if not len(paths):
# No paths to transform
return transforms.Bbox.null()

if not transform.is_affine:
paths = [transform.transform_path_non_affine(p) for p in paths]
Expand All @@ -275,35 +273,34 @@ def get_datalim(self, transData):
# transforms.get_affine().contains_branch(transData). But later,
# be careful to only apply the affine part that remains.

if isinstance(offsets, np.ma.MaskedArray):
offsets = offsets.filled(np.nan)
# get_path_collection_extents handles nan but not masked arrays

if len(paths):
if any(transform.contains_branch_seperately(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
# also use this algorithm (like streamplot).
return mpath.get_path_collection_extents(
transform.get_affine() - transData, paths,
self.get_transforms(),
offset_trf.transform_non_affine(offsets),
offset_trf.get_affine().frozen())

if self._has_offsets:
# this is for collections that have their paths (shapes)
# in physical, axes-relative, or figure-relative units
# (i.e. like scatter). We can't uniquely set limits based on
# those shapes, so we just set the limits based on their
# location.
offsets = (offset_trf - transData).transform(offsets)
# note A-B means A B^{-1}
offsets = np.ma.masked_invalid(offsets)
if not offsets.mask.all():
bbox = transforms.Bbox.null()
bbox.update_from_data_xy(offsets)
return bbox
if any(transform.contains_branch_seperately(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
# also use this algorithm (like streamplot).
if isinstance(offsets, np.ma.MaskedArray):
offsets = offsets.filled(np.nan)
# get_path_collection_extents handles nan but not masked arrays
return mpath.get_path_collection_extents(
transform.get_affine() - transData, paths,
self.get_transforms(),
offset_trf.transform_non_affine(offsets),
offset_trf.get_affine().frozen())

# NOTE: None is the default case where no offsets were passed in
if self._offsets is not None:
# this is for collections that have their paths (shapes)
# in physical, axes-relative, or figure-relative units
# (i.e. like scatter). We can't uniquely set limits based on
# those shapes, so we just set the limits based on their
# location.
offsets = (offset_trf - transData).transform(offsets)
# note A-B means A B^{-1}
offsets = np.ma.masked_invalid(offsets)
if not offsets.mask.all():
bbox = transforms.Bbox.null()
bbox.update_from_data_xy(offsets)
return bbox
return transforms.Bbox.null()

def get_window_extent(self, renderer):
Expand All @@ -316,7 +313,7 @@ def _prepare_points(self):

transform = self.get_transform()
offset_trf = self.get_offset_transform()
offsets = self._offsets
offsets = self.get_offsets()
paths = self.get_paths()

if self.have_units():
Expand All @@ -327,10 +324,9 @@ def _prepare_points(self):
xs = self.convert_xunits(xs)
ys = self.convert_yunits(ys)
paths.append(mpath.Path(np.column_stack([xs, ys]), path.codes))
if offsets.size:
xs = self.convert_xunits(offsets[:, 0])
ys = self.convert_yunits(offsets[:, 1])
offsets = np.column_stack([xs, ys])
xs = self.convert_xunits(offsets[:, 0])
ys = self.convert_yunits(offsets[:, 1])
offsets = np.column_stack([xs, ys])

if not transform.is_affine:
paths = [transform.transform_path_non_affine(path)
Expand Down Expand Up @@ -559,7 +555,8 @@ def set_offsets(self, offsets):

def get_offsets(self):
"""Return the offsets for the collection."""
return self._offsets
# Default to zeros in the no-offset (None) case
return np.zeros((1, 2)) if self._offsets is None else self._offsets

def _get_default_linewidth(self):
# This may be overridden in a subclass.
Expand Down Expand Up @@ -2156,13 +2153,12 @@ def draw(self, renderer):
renderer.open_group(self.__class__.__name__, self.get_gid())
transform = self.get_transform()
offset_trf = self.get_offset_transform()
offsets = self._offsets
offsets = self.get_offsets()

if self.have_units():
if len(self._offsets):
xs = self.convert_xunits(self._offsets[:, 0])
ys = self.convert_yunits(self._offsets[:, 1])
offsets = np.column_stack([xs, ys])
xs = self.convert_xunits(offsets[:, 0])
ys = self.convert_yunits(offsets[:, 1])
offsets = np.column_stack([xs, ys])

self.update_scalarmappable()

Expand Down