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FIX: change autolim exclude shapes not in data co-ordinates
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‎doc/api/next_api_changes/2019-03-04-AL.rst‎

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@@ -13,6 +13,41 @@ without an explicit call to `Axes.autoscale_view`.
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In some cases, this can result in different limits being reported. If this is
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an issue, consider triggering a draw with `fig.canvas.draw`.
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Autoscaling changes for Collections
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```````````````````````````````````
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Autoscaling has also changed for artists that are based on the `.Collection`
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class. Previously, the method that calculates the automatic limits
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`.Collection.get_datalim` tried to take into account the size of objects
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in the collection and make the limits large enough to not clip any of the
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object, i.e., for `.Axes.scatter` it would make the limits large enough to not
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clip any markers in the scatter. This is problematic when the object size is
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specified in physical space, or figure-relative space, because the transform
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from physical units to data limits requires knowing the data limits, and
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becomes invalid when the new limits are applied. This is an inverse
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problem that is theoretically solvable (if the object is physically smaller
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than the axes), but the extra complexity was not deemed worth it, particularly
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as the most common use case is for markers in scatter that are usually small
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enough to be accommodated by the default data limit margins.
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While the new behavior is algorithmically simpler, it is conditional on
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properties of the `.Collection` object:
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1. ``offsets = None``, ``transform`` is a child of `.Axes.transData`: use the paths
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for the automatic limits (i.e. for `.LineCollection` in `Axes.streamplot`).
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2. ``offsets != None``, and ``offset_transform`` is child of `.Axes.transData`:
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a) ``transform`` is child of `.Axes.transData`: use the ``path + offset`` for
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limits (i.e., for `.Axes.bar`).
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b) ``transform`` is not a child of `.Axes.transData`: just use the offsets
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for the limits (i.e. for scatter)
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3. otherwise return a null `.Bbox`.
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While this seems complicated, the logic is simply to use the information from
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the object that are in data space for the limits, but not information that is
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in physical units.
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LogLocator.nonsingular now maintains the orders of its arguments
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````````````````````````````````````````````````````````````````
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‎lib/matplotlib/collections.py‎

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@@ -146,6 +146,8 @@ def __init__(self,
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self._joinstyle = None
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self._offsets = np.zeros((1, 2))
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# save if offsets passed in were none...
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self._offsetsNone = offsets is None
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self._uniform_offsets = None
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if offsets is not None:
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offsets = np.asanyarray(offsets, float)
@@ -179,9 +181,30 @@ def get_offset_transform(self):
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return t
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def get_datalim(self, transData):
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# Get the automatic datalim of the collection.
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#
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# This operation depends on the transforms for the data in the
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# collection and whether the collection has offsets.
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#
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# 1) offsets = None, transform child of transData: use the paths for
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# the automatic limits (i.e. for LineCollection in streamline).
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# 2) offsets != None: offset_transform is child of transData:
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# a) transform is child of transData: use the path + offset for
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# limits (i.e for bar).
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# b) transform is not a child of transData: just use the offsets
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# for the limits (i.e. for scatter)
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# 3) otherwise return a null Bbox.
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transform = self.get_transform()
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transOffset = self.get_offset_transform()
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if (not self._offsetsNone and
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not transOffset.contains_branch(transData)):
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# if there are offsets but in some co-ords other than data,
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# then don't use them for autoscaling.
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return transforms.Bbox.null()
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offsets = self._offsets
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paths = self.get_paths()
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if not transform.is_affine:
@@ -196,13 +219,30 @@ def get_datalim(self, transData):
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# get_path_collection_extents handles nan but not masked arrays
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if len(paths) and len(offsets):
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result = mpath.get_path_collection_extents(
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transform.frozen(), paths, self.get_transforms(),
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offsets, transOffset.frozen())
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result = result.inverse_transformed(transData)
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else:
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result = transforms.Bbox.null()
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return result
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if transform.contains_branch(transData):
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# collections that are just in data units (like quiver)
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# can properly have the axes limits set by their shape +
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# offset. LineCollections that have no offsets can
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# also use this algorithm (like streamplot).
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result = mpath.get_path_collection_extents(
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transform.frozen(), paths, self.get_transforms(),
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offsets, transOffset.frozen())
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return result.inverse_transformed(transData)
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if not self._offsetsNone:
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# this is for collections that have their paths (shapes)
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# in physical, axes-relative, or figure-relative units
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# (i.e. like scatter). We can't uniquely set limits based on
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# those shapes, so we just set the limits based on their
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# location.
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# Finish the transform:
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offsets = (transOffset +
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transData.inverted()).transform(offsets)
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offsets = np.ma.masked_invalid(offsets)
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if not offsets.mask.all():
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points = np.row_stack((offsets.min(axis=0),
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offsets.max(axis=0)))
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return transforms.Bbox(points)
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return transforms.Bbox.null()
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def get_window_extent(self, renderer):
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# TODO: check to ensure that this does not fail for
@@ -1299,7 +1339,6 @@ def __init__(self, segments, # Can be None.
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antialiaseds = (mpl.rcParams['lines.antialiased'],)
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colors = mcolors.to_rgba_array(colors)
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Collection.__init__(
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self,
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edgecolors=colors,

‎lib/matplotlib/tests/baseline_images/test_axes/scatter.pdf‎

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‎lib/matplotlib/tests/baseline_images/test_axes/scatter.png‎

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