forked from s_ranjbar/city_retrofit
2087 lines
73 KiB
Python
2087 lines
73 KiB
Python
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"""
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Classes for the efficient drawing of large collections of objects that
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share most properties, e.g., a large number of line segments or
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polygons.
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The classes are not meant to be as flexible as their single element
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counterparts (e.g., you may not be able to select all line styles) but
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they are meant to be fast for common use cases (e.g., a large set of solid
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line segments).
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"""
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import math
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from numbers import Number
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import numpy as np
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import matplotlib as mpl
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from . import (_path, artist, cbook, cm, colors as mcolors, docstring,
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lines as mlines, path as mpath, transforms)
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import warnings
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@cbook._define_aliases({
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"antialiased": ["antialiaseds", "aa"],
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"edgecolor": ["edgecolors", "ec"],
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"facecolor": ["facecolors", "fc"],
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"linestyle": ["linestyles", "dashes", "ls"],
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"linewidth": ["linewidths", "lw"],
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})
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class Collection(artist.Artist, cm.ScalarMappable):
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"""
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Base class for Collections. Must be subclassed to be usable.
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All properties in a collection must be sequences or scalars;
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if scalars, they will be converted to sequences. The
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property of the ith element of the collection is::
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prop[i % len(props)]
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Exceptions are *capstyle* and *joinstyle* properties, these can
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only be set globally for the whole collection.
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Keyword arguments and default values:
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* *edgecolors*: None
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* *facecolors*: None
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* *linewidths*: None
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* *capstyle*: None
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* *joinstyle*: None
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* *antialiaseds*: None
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* *offsets*: None
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* *transOffset*: transforms.IdentityTransform()
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* *offset_position*: 'screen' (default) or 'data'
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* *norm*: None (optional for
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:class:`matplotlib.cm.ScalarMappable`)
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* *cmap*: None (optional for
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:class:`matplotlib.cm.ScalarMappable`)
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* *hatch*: None
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* *zorder*: 1
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*offsets* and *transOffset* are used to translate the patch after
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rendering (default no offsets). If offset_position is 'screen'
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(default) the offset is applied after the master transform has
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been applied, that is, the offsets are in screen coordinates. If
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offset_position is 'data', the offset is applied before the master
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transform, i.e., the offsets are in data coordinates.
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If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds*
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are None, they default to their :data:`matplotlib.rcParams` patch
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setting, in sequence form.
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The use of :class:`~matplotlib.cm.ScalarMappable` is optional. If
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the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not None
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(i.e., a call to set_array has been made), at draw time a call to
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scalar mappable will be made to set the face colors.
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"""
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_offsets = np.zeros((0, 2))
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_transOffset = transforms.IdentityTransform()
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#: Either a list of 3x3 arrays or an Nx3x3 array of transforms, suitable
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#: for the `all_transforms` argument to
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#: :meth:`~matplotlib.backend_bases.RendererBase.draw_path_collection`;
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#: each 3x3 array is used to initialize an
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#: :class:`~matplotlib.transforms.Affine2D` object.
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#: Each kind of collection defines this based on its arguments.
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_transforms = np.empty((0, 3, 3))
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# Whether to draw an edge by default. Set on a
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# subclass-by-subclass basis.
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_edge_default = False
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def __init__(self,
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edgecolors=None,
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facecolors=None,
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linewidths=None,
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linestyles='solid',
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capstyle=None,
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joinstyle=None,
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antialiaseds=None,
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offsets=None,
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transOffset=None,
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norm=None, # optional for ScalarMappable
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cmap=None, # ditto
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pickradius=5.0,
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hatch=None,
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urls=None,
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offset_position='screen',
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zorder=1,
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**kwargs
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):
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"""
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Create a Collection
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%(Collection)s
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"""
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artist.Artist.__init__(self)
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cm.ScalarMappable.__init__(self, norm, cmap)
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# list of un-scaled dash patterns
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# this is needed scaling the dash pattern by linewidth
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self._us_linestyles = [(None, None)]
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# list of dash patterns
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self._linestyles = [(None, None)]
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# list of unbroadcast/scaled linewidths
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self._us_lw = [0]
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self._linewidths = [0]
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self._is_filled = True # May be modified by set_facecolor().
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self._hatch_color = mcolors.to_rgba(mpl.rcParams['hatch.color'])
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self.set_facecolor(facecolors)
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self.set_edgecolor(edgecolors)
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self.set_linewidth(linewidths)
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self.set_linestyle(linestyles)
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self.set_antialiased(antialiaseds)
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self.set_pickradius(pickradius)
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self.set_urls(urls)
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self.set_hatch(hatch)
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self.set_offset_position(offset_position)
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self.set_zorder(zorder)
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if capstyle:
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self.set_capstyle(capstyle)
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else:
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self._capstyle = None
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if joinstyle:
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self.set_joinstyle(joinstyle)
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else:
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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)
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# Broadcast (2,) -> (1, 2) but nothing else.
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if offsets.shape == (2,):
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offsets = offsets[None, :]
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if transOffset is not None:
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self._offsets = offsets
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self._transOffset = transOffset
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else:
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self._uniform_offsets = offsets
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self._path_effects = None
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self.update(kwargs)
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self._paths = None
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def get_paths(self):
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return self._paths
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def set_paths(self):
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raise NotImplementedError
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def get_transforms(self):
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return self._transforms
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def get_offset_transform(self):
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t = self._transOffset
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if (not isinstance(t, transforms.Transform)
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and hasattr(t, '_as_mpl_transform')):
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t = t._as_mpl_transform(self.axes)
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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:
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paths = [transform.transform_path_non_affine(p) for p in paths]
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# Don't convert transform to transform.get_affine() here because
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# we may have transform.contains_branch(transData) but not
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# transforms.get_affine().contains_branch(transData). But later,
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# be careful to only apply the affine part that remains.
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if not transOffset.is_affine:
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offsets = transOffset.transform_non_affine(offsets)
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if isinstance(offsets, np.ma.MaskedArray):
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offsets = offsets.filled(np.nan)
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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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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.get_affine(), paths, self.get_transforms(),
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offsets, transOffset.get_affine().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.get_affine() +
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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
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# cases other than scatter plot legend
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return self.get_datalim(transforms.IdentityTransform())
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def _prepare_points(self):
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# Helper for drawing and hit testing.
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transform = self.get_transform()
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transOffset = self.get_offset_transform()
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offsets = self._offsets
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paths = self.get_paths()
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if self.have_units():
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paths = []
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for path in self.get_paths():
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vertices = path.vertices
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xs, ys = vertices[:, 0], vertices[:, 1]
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xs = self.convert_xunits(xs)
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ys = self.convert_yunits(ys)
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paths.append(mpath.Path(np.column_stack([xs, ys]), path.codes))
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if offsets.size:
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xs = self.convert_xunits(offsets[:, 0])
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ys = self.convert_yunits(offsets[:, 1])
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offsets = np.column_stack([xs, ys])
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if not transform.is_affine:
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paths = [transform.transform_path_non_affine(path)
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for path in paths]
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transform = transform.get_affine()
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if not transOffset.is_affine:
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offsets = transOffset.transform_non_affine(offsets)
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# This might have changed an ndarray into a masked array.
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transOffset = transOffset.get_affine()
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if isinstance(offsets, np.ma.MaskedArray):
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offsets = offsets.filled(np.nan)
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# Changing from a masked array to nan-filled ndarray
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# is probably most efficient at this point.
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return transform, transOffset, offsets, paths
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@artist.allow_rasterization
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def draw(self, renderer):
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if not self.get_visible():
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return
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renderer.open_group(self.__class__.__name__, self.get_gid())
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self.update_scalarmappable()
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transform, transOffset, offsets, paths = self._prepare_points()
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gc = renderer.new_gc()
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self._set_gc_clip(gc)
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gc.set_snap(self.get_snap())
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if self._hatch:
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gc.set_hatch(self._hatch)
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try:
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gc.set_hatch_color(self._hatch_color)
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except AttributeError:
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# if we end up with a GC that does not have this method
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cbook.warn_deprecated(
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"3.1", message="Your backend does not support setting the "
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"hatch color; such backends will become unsupported in "
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"Matplotlib 3.3.")
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if self.get_sketch_params() is not None:
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gc.set_sketch_params(*self.get_sketch_params())
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if self.get_path_effects():
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from matplotlib.patheffects import PathEffectRenderer
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renderer = PathEffectRenderer(self.get_path_effects(), renderer)
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# If the collection is made up of a single shape/color/stroke,
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# it can be rendered once and blitted multiple times, using
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# `draw_markers` rather than `draw_path_collection`. This is
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# *much* faster for Agg, and results in smaller file sizes in
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# PDF/SVG/PS.
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trans = self.get_transforms()
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facecolors = self.get_facecolor()
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edgecolors = self.get_edgecolor()
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do_single_path_optimization = False
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if (len(paths) == 1 and len(trans) <= 1 and
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len(facecolors) == 1 and len(edgecolors) == 1 and
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len(self._linewidths) == 1 and
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self._linestyles == [(None, None)] and
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len(self._antialiaseds) == 1 and len(self._urls) == 1 and
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self.get_hatch() is None):
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if len(trans):
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combined_transform = transforms.Affine2D(trans[0]) + transform
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else:
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combined_transform = transform
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extents = paths[0].get_extents(combined_transform)
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if (extents.width < self.figure.bbox.width
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and extents.height < self.figure.bbox.height):
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do_single_path_optimization = True
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if self._joinstyle:
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gc.set_joinstyle(self._joinstyle)
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if self._capstyle:
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gc.set_capstyle(self._capstyle)
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if do_single_path_optimization:
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gc.set_foreground(tuple(edgecolors[0]))
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gc.set_linewidth(self._linewidths[0])
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gc.set_dashes(*self._linestyles[0])
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gc.set_antialiased(self._antialiaseds[0])
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gc.set_url(self._urls[0])
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renderer.draw_markers(
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||
|
|
gc, paths[0], combined_transform.frozen(),
|
||
|
|
mpath.Path(offsets), transOffset, tuple(facecolors[0]))
|
||
|
|
else:
|
||
|
|
renderer.draw_path_collection(
|
||
|
|
gc, transform.frozen(), paths,
|
||
|
|
self.get_transforms(), offsets, transOffset,
|
||
|
|
self.get_facecolor(), self.get_edgecolor(),
|
||
|
|
self._linewidths, self._linestyles,
|
||
|
|
self._antialiaseds, self._urls,
|
||
|
|
self._offset_position)
|
||
|
|
|
||
|
|
gc.restore()
|
||
|
|
renderer.close_group(self.__class__.__name__)
|
||
|
|
self.stale = False
|
||
|
|
|
||
|
|
def set_pickradius(self, pr):
|
||
|
|
"""
|
||
|
|
Set the pick radius used for containment tests.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
d : float
|
||
|
|
Pick radius, in points.
|
||
|
|
"""
|
||
|
|
self._pickradius = pr
|
||
|
|
|
||
|
|
def get_pickradius(self):
|
||
|
|
return self._pickradius
|
||
|
|
|
||
|
|
def contains(self, mouseevent):
|
||
|
|
"""
|
||
|
|
Test whether the mouse event occurred in the collection.
|
||
|
|
|
||
|
|
Returns ``bool, dict(ind=itemlist)``, where every item in itemlist
|
||
|
|
contains the event.
|
||
|
|
"""
|
||
|
|
inside, info = self._default_contains(mouseevent)
|
||
|
|
if inside is not None:
|
||
|
|
return inside, info
|
||
|
|
|
||
|
|
if not self.get_visible():
|
||
|
|
return False, {}
|
||
|
|
|
||
|
|
pickradius = (
|
||
|
|
float(self._picker)
|
||
|
|
if isinstance(self._picker, Number) and
|
||
|
|
self._picker is not True # the bool, not just nonzero or 1
|
||
|
|
else self._pickradius)
|
||
|
|
|
||
|
|
if self.axes and self.get_offset_position() == "data":
|
||
|
|
self.axes._unstale_viewLim()
|
||
|
|
|
||
|
|
transform, transOffset, offsets, paths = self._prepare_points()
|
||
|
|
|
||
|
|
ind = _path.point_in_path_collection(
|
||
|
|
mouseevent.x, mouseevent.y, pickradius,
|
||
|
|
transform.frozen(), paths, self.get_transforms(),
|
||
|
|
offsets, transOffset, pickradius <= 0,
|
||
|
|
self.get_offset_position())
|
||
|
|
|
||
|
|
return len(ind) > 0, dict(ind=ind)
|
||
|
|
|
||
|
|
def set_urls(self, urls):
|
||
|
|
"""
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
urls : List[str] or None
|
||
|
|
"""
|
||
|
|
self._urls = urls if urls is not None else [None]
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_urls(self):
|
||
|
|
return self._urls
|
||
|
|
|
||
|
|
def set_hatch(self, hatch):
|
||
|
|
r"""
|
||
|
|
Set the hatching pattern
|
||
|
|
|
||
|
|
*hatch* can be one of::
|
||
|
|
|
||
|
|
/ - diagonal hatching
|
||
|
|
\ - back diagonal
|
||
|
|
| - vertical
|
||
|
|
- - horizontal
|
||
|
|
+ - crossed
|
||
|
|
x - crossed diagonal
|
||
|
|
o - small circle
|
||
|
|
O - large circle
|
||
|
|
. - dots
|
||
|
|
* - stars
|
||
|
|
|
||
|
|
Letters can be combined, in which case all the specified
|
||
|
|
hatchings are done. If same letter repeats, it increases the
|
||
|
|
density of hatching of that pattern.
|
||
|
|
|
||
|
|
Hatching is supported in the PostScript, PDF, SVG and Agg
|
||
|
|
backends only.
|
||
|
|
|
||
|
|
Unlike other properties such as linewidth and colors, hatching
|
||
|
|
can only be specified for the collection as a whole, not separately
|
||
|
|
for each member.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
hatch : {'/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}
|
||
|
|
"""
|
||
|
|
self._hatch = hatch
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_hatch(self):
|
||
|
|
"""Return the current hatching pattern."""
|
||
|
|
return self._hatch
|
||
|
|
|
||
|
|
def set_offsets(self, offsets):
|
||
|
|
"""
|
||
|
|
Set the offsets for the collection.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
offsets : array-like (N, 2) or (2,)
|
||
|
|
"""
|
||
|
|
offsets = np.asanyarray(offsets, float)
|
||
|
|
if offsets.shape == (2,): # Broadcast (2,) -> (1, 2) but nothing else.
|
||
|
|
offsets = offsets[None, :]
|
||
|
|
# This decision is based on how they are initialized above in __init__.
|
||
|
|
if self._uniform_offsets is None:
|
||
|
|
self._offsets = offsets
|
||
|
|
else:
|
||
|
|
self._uniform_offsets = offsets
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_offsets(self):
|
||
|
|
"""Return the offsets for the collection."""
|
||
|
|
# This decision is based on how they are initialized above in __init__.
|
||
|
|
if self._uniform_offsets is None:
|
||
|
|
return self._offsets
|
||
|
|
else:
|
||
|
|
return self._uniform_offsets
|
||
|
|
|
||
|
|
def set_offset_position(self, offset_position):
|
||
|
|
"""
|
||
|
|
Set how offsets are applied. If *offset_position* is 'screen'
|
||
|
|
(default) the offset is applied after the master transform has
|
||
|
|
been applied, that is, the offsets are in screen coordinates.
|
||
|
|
If offset_position is 'data', the offset is applied before the
|
||
|
|
master transform, i.e., the offsets are in data coordinates.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
offset_position : {'screen', 'data'}
|
||
|
|
"""
|
||
|
|
cbook._check_in_list(['screen', 'data'],
|
||
|
|
offset_position=offset_position)
|
||
|
|
self._offset_position = offset_position
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_offset_position(self):
|
||
|
|
"""
|
||
|
|
Returns how offsets are applied for the collection. If
|
||
|
|
*offset_position* is 'screen', the offset is applied after the
|
||
|
|
master transform has been applied, that is, the offsets are in
|
||
|
|
screen coordinates. If offset_position is 'data', the offset
|
||
|
|
is applied before the master transform, i.e., the offsets are
|
||
|
|
in data coordinates.
|
||
|
|
"""
|
||
|
|
return self._offset_position
|
||
|
|
|
||
|
|
def set_linewidth(self, lw):
|
||
|
|
"""
|
||
|
|
Set the linewidth(s) for the collection. *lw* can be a scalar
|
||
|
|
or a sequence; if it is a sequence the patches will cycle
|
||
|
|
through the sequence
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
lw : float or sequence of floats
|
||
|
|
"""
|
||
|
|
if lw is None:
|
||
|
|
lw = mpl.rcParams['patch.linewidth']
|
||
|
|
if lw is None:
|
||
|
|
lw = mpl.rcParams['lines.linewidth']
|
||
|
|
# get the un-scaled/broadcast lw
|
||
|
|
self._us_lw = np.atleast_1d(np.asarray(lw))
|
||
|
|
|
||
|
|
# scale all of the dash patterns.
|
||
|
|
self._linewidths, self._linestyles = self._bcast_lwls(
|
||
|
|
self._us_lw, self._us_linestyles)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_linestyle(self, ls):
|
||
|
|
"""
|
||
|
|
Set the linestyle(s) for the collection.
|
||
|
|
|
||
|
|
=========================== =================
|
||
|
|
linestyle description
|
||
|
|
=========================== =================
|
||
|
|
``'-'`` or ``'solid'`` solid line
|
||
|
|
``'--'`` or ``'dashed'`` dashed line
|
||
|
|
``'-.'`` or ``'dashdot'`` dash-dotted line
|
||
|
|
``':'`` or ``'dotted'`` dotted line
|
||
|
|
=========================== =================
|
||
|
|
|
||
|
|
Alternatively a dash tuple of the following form can be provided::
|
||
|
|
|
||
|
|
(offset, onoffseq),
|
||
|
|
|
||
|
|
where ``onoffseq`` is an even length tuple of on and off ink in points.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
ls : {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
|
||
|
|
The line style.
|
||
|
|
"""
|
||
|
|
try:
|
||
|
|
if isinstance(ls, str):
|
||
|
|
ls = cbook.ls_mapper.get(ls, ls)
|
||
|
|
dashes = [mlines._get_dash_pattern(ls)]
|
||
|
|
else:
|
||
|
|
try:
|
||
|
|
dashes = [mlines._get_dash_pattern(ls)]
|
||
|
|
except ValueError:
|
||
|
|
dashes = [mlines._get_dash_pattern(x) for x in ls]
|
||
|
|
|
||
|
|
except ValueError:
|
||
|
|
raise ValueError(
|
||
|
|
'Do not know how to convert {!r} to dashes'.format(ls))
|
||
|
|
|
||
|
|
# get the list of raw 'unscaled' dash patterns
|
||
|
|
self._us_linestyles = dashes
|
||
|
|
|
||
|
|
# broadcast and scale the lw and dash patterns
|
||
|
|
self._linewidths, self._linestyles = self._bcast_lwls(
|
||
|
|
self._us_lw, self._us_linestyles)
|
||
|
|
|
||
|
|
def set_capstyle(self, cs):
|
||
|
|
"""
|
||
|
|
Set the capstyle for the collection (for all its elements).
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
cs : {'butt', 'round', 'projecting'}
|
||
|
|
The capstyle
|
||
|
|
"""
|
||
|
|
cbook._check_in_list(('butt', 'round', 'projecting'), capstyle=cs)
|
||
|
|
self._capstyle = cs
|
||
|
|
|
||
|
|
def get_capstyle(self):
|
||
|
|
return self._capstyle
|
||
|
|
|
||
|
|
def set_joinstyle(self, js):
|
||
|
|
"""
|
||
|
|
Set the joinstyle for the collection (for all its elements).
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
js : {'miter', 'round', 'bevel'}
|
||
|
|
The joinstyle
|
||
|
|
"""
|
||
|
|
cbook._check_in_list(('miter', 'round', 'bevel'), joinstyle=js)
|
||
|
|
self._joinstyle = js
|
||
|
|
|
||
|
|
def get_joinstyle(self):
|
||
|
|
return self._joinstyle
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def _bcast_lwls(linewidths, dashes):
|
||
|
|
"""
|
||
|
|
Internal helper function to broadcast + scale ls/lw
|
||
|
|
|
||
|
|
In the collection drawing code, the linewidth and linestyle are cycled
|
||
|
|
through as circular buffers (via ``v[i % len(v)]``). Thus, if we are
|
||
|
|
going to scale the dash pattern at set time (not draw time) we need to
|
||
|
|
do the broadcasting now and expand both lists to be the same length.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
linewidths : list
|
||
|
|
line widths of collection
|
||
|
|
dashes : list
|
||
|
|
dash specification (offset, (dash pattern tuple))
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
linewidths, dashes : list
|
||
|
|
Will be the same length, dashes are scaled by paired linewidth
|
||
|
|
"""
|
||
|
|
if mpl.rcParams['_internal.classic_mode']:
|
||
|
|
return linewidths, dashes
|
||
|
|
# make sure they are the same length so we can zip them
|
||
|
|
if len(dashes) != len(linewidths):
|
||
|
|
l_dashes = len(dashes)
|
||
|
|
l_lw = len(linewidths)
|
||
|
|
gcd = math.gcd(l_dashes, l_lw)
|
||
|
|
dashes = list(dashes) * (l_lw // gcd)
|
||
|
|
linewidths = list(linewidths) * (l_dashes // gcd)
|
||
|
|
|
||
|
|
# scale the dash patters
|
||
|
|
dashes = [mlines._scale_dashes(o, d, lw)
|
||
|
|
for (o, d), lw in zip(dashes, linewidths)]
|
||
|
|
|
||
|
|
return linewidths, dashes
|
||
|
|
|
||
|
|
def set_antialiased(self, aa):
|
||
|
|
"""
|
||
|
|
Set the antialiasing state for rendering.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
aa : bool or sequence of bools
|
||
|
|
"""
|
||
|
|
if aa is None:
|
||
|
|
aa = mpl.rcParams['patch.antialiased']
|
||
|
|
self._antialiaseds = np.atleast_1d(np.asarray(aa, bool))
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_color(self, c):
|
||
|
|
"""
|
||
|
|
Set both the edgecolor and the facecolor.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
c : color or sequence of rgba tuples
|
||
|
|
|
||
|
|
See Also
|
||
|
|
--------
|
||
|
|
Collection.set_facecolor, Collection.set_edgecolor
|
||
|
|
For setting the edge or face color individually.
|
||
|
|
"""
|
||
|
|
self.set_facecolor(c)
|
||
|
|
self.set_edgecolor(c)
|
||
|
|
|
||
|
|
def _set_facecolor(self, c):
|
||
|
|
if c is None:
|
||
|
|
c = mpl.rcParams['patch.facecolor']
|
||
|
|
|
||
|
|
self._is_filled = True
|
||
|
|
try:
|
||
|
|
if c.lower() == 'none':
|
||
|
|
self._is_filled = False
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
self._facecolors = mcolors.to_rgba_array(c, self._alpha)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_facecolor(self, c):
|
||
|
|
"""
|
||
|
|
Set the facecolor(s) of the collection. *c* can be a color (all patches
|
||
|
|
have same color), or a sequence of colors; if it is a sequence the
|
||
|
|
patches will cycle through the sequence.
|
||
|
|
|
||
|
|
If *c* is 'none', the patch will not be filled.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
c : color or sequence of colors
|
||
|
|
"""
|
||
|
|
self._original_facecolor = c
|
||
|
|
self._set_facecolor(c)
|
||
|
|
|
||
|
|
def get_facecolor(self):
|
||
|
|
return self._facecolors
|
||
|
|
|
||
|
|
def get_edgecolor(self):
|
||
|
|
if cbook._str_equal(self._edgecolors, 'face'):
|
||
|
|
return self.get_facecolor()
|
||
|
|
else:
|
||
|
|
return self._edgecolors
|
||
|
|
|
||
|
|
def _set_edgecolor(self, c):
|
||
|
|
set_hatch_color = True
|
||
|
|
if c is None:
|
||
|
|
if (mpl.rcParams['patch.force_edgecolor'] or
|
||
|
|
not self._is_filled or self._edge_default):
|
||
|
|
c = mpl.rcParams['patch.edgecolor']
|
||
|
|
else:
|
||
|
|
c = 'none'
|
||
|
|
set_hatch_color = False
|
||
|
|
|
||
|
|
self._is_stroked = True
|
||
|
|
try:
|
||
|
|
if c.lower() == 'none':
|
||
|
|
self._is_stroked = False
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
|
||
|
|
try:
|
||
|
|
if c.lower() == 'face': # Special case: lookup in "get" method.
|
||
|
|
self._edgecolors = 'face'
|
||
|
|
return
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
self._edgecolors = mcolors.to_rgba_array(c, self._alpha)
|
||
|
|
if set_hatch_color and len(self._edgecolors):
|
||
|
|
self._hatch_color = tuple(self._edgecolors[0])
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_edgecolor(self, c):
|
||
|
|
"""
|
||
|
|
Set the edgecolor(s) of the collection.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
c : color or sequence of colors or 'face'
|
||
|
|
The collection edgecolor(s). If a sequence, the patches cycle
|
||
|
|
through it. If 'face', match the facecolor.
|
||
|
|
"""
|
||
|
|
self._original_edgecolor = c
|
||
|
|
self._set_edgecolor(c)
|
||
|
|
|
||
|
|
def set_alpha(self, alpha):
|
||
|
|
# docstring inherited
|
||
|
|
super().set_alpha(alpha)
|
||
|
|
self.update_dict['array'] = True
|
||
|
|
self._set_facecolor(self._original_facecolor)
|
||
|
|
self._set_edgecolor(self._original_edgecolor)
|
||
|
|
|
||
|
|
def get_linewidth(self):
|
||
|
|
return self._linewidths
|
||
|
|
|
||
|
|
def get_linestyle(self):
|
||
|
|
return self._linestyles
|
||
|
|
|
||
|
|
def update_scalarmappable(self):
|
||
|
|
"""Update colors from the scalar mappable array, if it is not None."""
|
||
|
|
if self._A is None:
|
||
|
|
return
|
||
|
|
if self._A.ndim > 1:
|
||
|
|
raise ValueError('Collections can only map rank 1 arrays')
|
||
|
|
if not self.check_update("array"):
|
||
|
|
return
|
||
|
|
if self._is_filled:
|
||
|
|
self._facecolors = self.to_rgba(self._A, self._alpha)
|
||
|
|
elif self._is_stroked:
|
||
|
|
self._edgecolors = self.to_rgba(self._A, self._alpha)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_fill(self):
|
||
|
|
'return whether fill is set'
|
||
|
|
return self._is_filled
|
||
|
|
|
||
|
|
def update_from(self, other):
|
||
|
|
'copy properties from other to self'
|
||
|
|
|
||
|
|
artist.Artist.update_from(self, other)
|
||
|
|
self._antialiaseds = other._antialiaseds
|
||
|
|
self._original_edgecolor = other._original_edgecolor
|
||
|
|
self._edgecolors = other._edgecolors
|
||
|
|
self._original_facecolor = other._original_facecolor
|
||
|
|
self._facecolors = other._facecolors
|
||
|
|
self._linewidths = other._linewidths
|
||
|
|
self._linestyles = other._linestyles
|
||
|
|
self._us_linestyles = other._us_linestyles
|
||
|
|
self._pickradius = other._pickradius
|
||
|
|
self._hatch = other._hatch
|
||
|
|
|
||
|
|
# update_from for scalarmappable
|
||
|
|
self._A = other._A
|
||
|
|
self.norm = other.norm
|
||
|
|
self.cmap = other.cmap
|
||
|
|
# self.update_dict = other.update_dict # do we need to copy this? -JJL
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
|
||
|
|
# these are not available for the object inspector until after the
|
||
|
|
# class is built so we define an initial set here for the init
|
||
|
|
# function and they will be overridden after object defn
|
||
|
|
docstring.interpd.update(Collection="""\
|
||
|
|
Valid Collection keyword arguments:
|
||
|
|
|
||
|
|
* *edgecolors*: None
|
||
|
|
* *facecolors*: None
|
||
|
|
* *linewidths*: None
|
||
|
|
* *antialiaseds*: None
|
||
|
|
* *offsets*: None
|
||
|
|
* *transOffset*: transforms.IdentityTransform()
|
||
|
|
* *norm*: None (optional for
|
||
|
|
:class:`matplotlib.cm.ScalarMappable`)
|
||
|
|
* *cmap*: None (optional for
|
||
|
|
:class:`matplotlib.cm.ScalarMappable`)
|
||
|
|
|
||
|
|
*offsets* and *transOffset* are used to translate the patch after
|
||
|
|
rendering (default no offsets)
|
||
|
|
|
||
|
|
If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds*
|
||
|
|
are None, they default to their :data:`matplotlib.rcParams` patch
|
||
|
|
setting, in sequence form.
|
||
|
|
""")
|
||
|
|
|
||
|
|
|
||
|
|
class _CollectionWithSizes(Collection):
|
||
|
|
"""
|
||
|
|
Base class for collections that have an array of sizes.
|
||
|
|
"""
|
||
|
|
_factor = 1.0
|
||
|
|
|
||
|
|
def get_sizes(self):
|
||
|
|
"""
|
||
|
|
Returns the sizes of the elements in the collection. The
|
||
|
|
value represents the 'area' of the element.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
sizes : array
|
||
|
|
The 'area' of each element.
|
||
|
|
"""
|
||
|
|
return self._sizes
|
||
|
|
|
||
|
|
def set_sizes(self, sizes, dpi=72.0):
|
||
|
|
"""
|
||
|
|
Set the sizes of each member of the collection.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
sizes : ndarray or None
|
||
|
|
The size to set for each element of the collection. The
|
||
|
|
value is the 'area' of the element.
|
||
|
|
dpi : float
|
||
|
|
The dpi of the canvas. Defaults to 72.0.
|
||
|
|
"""
|
||
|
|
if sizes is None:
|
||
|
|
self._sizes = np.array([])
|
||
|
|
self._transforms = np.empty((0, 3, 3))
|
||
|
|
else:
|
||
|
|
self._sizes = np.asarray(sizes)
|
||
|
|
self._transforms = np.zeros((len(self._sizes), 3, 3))
|
||
|
|
scale = np.sqrt(self._sizes) * dpi / 72.0 * self._factor
|
||
|
|
self._transforms[:, 0, 0] = scale
|
||
|
|
self._transforms[:, 1, 1] = scale
|
||
|
|
self._transforms[:, 2, 2] = 1.0
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
@artist.allow_rasterization
|
||
|
|
def draw(self, renderer):
|
||
|
|
self.set_sizes(self._sizes, self.figure.dpi)
|
||
|
|
Collection.draw(self, renderer)
|
||
|
|
|
||
|
|
|
||
|
|
class PathCollection(_CollectionWithSizes):
|
||
|
|
"""
|
||
|
|
This is the most basic :class:`Collection` subclass.
|
||
|
|
A :class:`PathCollection` is e.g. created by a :meth:`~.Axes.scatter` plot.
|
||
|
|
"""
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self, paths, sizes=None, **kwargs):
|
||
|
|
"""
|
||
|
|
*paths* is a sequence of :class:`matplotlib.path.Path`
|
||
|
|
instances.
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
"""
|
||
|
|
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self.set_paths(paths)
|
||
|
|
self.set_sizes(sizes)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_paths(self, paths):
|
||
|
|
self._paths = paths
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_paths(self):
|
||
|
|
return self._paths
|
||
|
|
|
||
|
|
def legend_elements(self, prop="colors", num="auto",
|
||
|
|
fmt=None, func=lambda x: x, **kwargs):
|
||
|
|
"""
|
||
|
|
Creates legend handles and labels for a PathCollection. This is useful
|
||
|
|
for obtaining a legend for a :meth:`~.Axes.scatter` plot. E.g.::
|
||
|
|
|
||
|
|
scatter = plt.scatter([1, 2, 3], [4, 5, 6], c=[7, 2, 3])
|
||
|
|
plt.legend(*scatter.legend_elements())
|
||
|
|
|
||
|
|
Also see the :ref:`automatedlegendcreation` example.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
prop : string, optional, default *"colors"*
|
||
|
|
Can be *"colors"* or *"sizes"*. In case of *"colors"*, the legend
|
||
|
|
handles will show the different colors of the collection. In case
|
||
|
|
of "sizes", the legend will show the different sizes.
|
||
|
|
num : int, None, "auto" (default), array-like, or `~.ticker.Locator`,
|
||
|
|
optional
|
||
|
|
Target number of elements to create.
|
||
|
|
If None, use all unique elements of the mappable array. If an
|
||
|
|
integer, target to use *num* elements in the normed range.
|
||
|
|
If *"auto"*, try to determine which option better suits the nature
|
||
|
|
of the data.
|
||
|
|
The number of created elements may slightly deviate from *num* due
|
||
|
|
to a `~.ticker.Locator` being used to find useful locations.
|
||
|
|
If a list or array, use exactly those elements for the legend.
|
||
|
|
Finally, a `~.ticker.Locator` can be provided.
|
||
|
|
fmt : str, `~matplotlib.ticker.Formatter`, or None (default)
|
||
|
|
The format or formatter to use for the labels. If a string must be
|
||
|
|
a valid input for a `~.StrMethodFormatter`. If None (the default),
|
||
|
|
use a `~.ScalarFormatter`.
|
||
|
|
func : function, default *lambda x: x*
|
||
|
|
Function to calculate the labels. Often the size (or color)
|
||
|
|
argument to :meth:`~.Axes.scatter` will have been pre-processed
|
||
|
|
by the user using a function *s = f(x)* to make the markers
|
||
|
|
visible; e.g. *size = np.log10(x)*. Providing the inverse of this
|
||
|
|
function here allows that pre-processing to be inverted, so that
|
||
|
|
the legend labels have the correct values;
|
||
|
|
e.g. *func = np.exp(x, 10)*.
|
||
|
|
kwargs : further parameters
|
||
|
|
Allowed keyword arguments are *color* and *size*. E.g. it may be
|
||
|
|
useful to set the color of the markers if *prop="sizes"* is used;
|
||
|
|
similarly to set the size of the markers if *prop="colors"* is
|
||
|
|
used. Any further parameters are passed onto the `.Line2D`
|
||
|
|
instance. This may be useful to e.g. specify a different
|
||
|
|
*markeredgecolor* or *alpha* for the legend handles.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
tuple (handles, labels)
|
||
|
|
with *handles* being a list of `.Line2D` objects
|
||
|
|
and *labels* a matching list of strings.
|
||
|
|
"""
|
||
|
|
handles = []
|
||
|
|
labels = []
|
||
|
|
hasarray = self.get_array() is not None
|
||
|
|
if fmt is None:
|
||
|
|
fmt = mpl.ticker.ScalarFormatter(useOffset=False, useMathText=True)
|
||
|
|
elif isinstance(fmt, str):
|
||
|
|
fmt = mpl.ticker.StrMethodFormatter(fmt)
|
||
|
|
fmt.create_dummy_axis()
|
||
|
|
|
||
|
|
if prop == "colors":
|
||
|
|
if not hasarray:
|
||
|
|
warnings.warn("Collection without array used. Make sure to "
|
||
|
|
"specify the values to be colormapped via the "
|
||
|
|
"`c` argument.")
|
||
|
|
return handles, labels
|
||
|
|
u = np.unique(self.get_array())
|
||
|
|
size = kwargs.pop("size", mpl.rcParams["lines.markersize"])
|
||
|
|
elif prop == "sizes":
|
||
|
|
u = np.unique(self.get_sizes())
|
||
|
|
color = kwargs.pop("color", "k")
|
||
|
|
else:
|
||
|
|
raise ValueError("Valid values for `prop` are 'colors' or "
|
||
|
|
f"'sizes'. You supplied '{prop}' instead.")
|
||
|
|
|
||
|
|
fmt.set_bounds(func(u).min(), func(u).max())
|
||
|
|
if num == "auto":
|
||
|
|
num = 9
|
||
|
|
if len(u) <= num:
|
||
|
|
num = None
|
||
|
|
if num is None:
|
||
|
|
values = u
|
||
|
|
label_values = func(values)
|
||
|
|
else:
|
||
|
|
if prop == "colors":
|
||
|
|
arr = self.get_array()
|
||
|
|
elif prop == "sizes":
|
||
|
|
arr = self.get_sizes()
|
||
|
|
if isinstance(num, mpl.ticker.Locator):
|
||
|
|
loc = num
|
||
|
|
elif np.iterable(num):
|
||
|
|
loc = mpl.ticker.FixedLocator(num)
|
||
|
|
else:
|
||
|
|
num = int(num)
|
||
|
|
loc = mpl.ticker.MaxNLocator(nbins=num, min_n_ticks=num-1,
|
||
|
|
steps=[1, 2, 2.5, 3, 5, 6, 8, 10])
|
||
|
|
label_values = loc.tick_values(func(arr).min(), func(arr).max())
|
||
|
|
cond = ((label_values >= func(arr).min()) &
|
||
|
|
(label_values <= func(arr).max()))
|
||
|
|
label_values = label_values[cond]
|
||
|
|
xarr = np.linspace(arr.min(), arr.max(), 256)
|
||
|
|
values = np.interp(label_values, func(xarr), xarr)
|
||
|
|
|
||
|
|
kw = dict(markeredgewidth=self.get_linewidths()[0],
|
||
|
|
alpha=self.get_alpha())
|
||
|
|
kw.update(kwargs)
|
||
|
|
|
||
|
|
for val, lab in zip(values, label_values):
|
||
|
|
if prop == "colors":
|
||
|
|
color = self.cmap(self.norm(val))
|
||
|
|
elif prop == "sizes":
|
||
|
|
size = np.sqrt(val)
|
||
|
|
if np.isclose(size, 0.0):
|
||
|
|
continue
|
||
|
|
h = mlines.Line2D([0], [0], ls="", color=color, ms=size,
|
||
|
|
marker=self.get_paths()[0], **kw)
|
||
|
|
handles.append(h)
|
||
|
|
if hasattr(fmt, "set_locs"):
|
||
|
|
fmt.set_locs(label_values)
|
||
|
|
l = fmt(lab)
|
||
|
|
labels.append(l)
|
||
|
|
|
||
|
|
return handles, labels
|
||
|
|
|
||
|
|
|
||
|
|
class PolyCollection(_CollectionWithSizes):
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self, verts, sizes=None, closed=True, **kwargs):
|
||
|
|
"""
|
||
|
|
*verts* is a sequence of ( *verts0*, *verts1*, ...) where
|
||
|
|
*verts_i* is a sequence of *xy* tuples of vertices, or an
|
||
|
|
equivalent :mod:`numpy` array of shape (*nv*, 2).
|
||
|
|
|
||
|
|
*sizes* is *None* (default) or a sequence of floats that
|
||
|
|
scale the corresponding *verts_i*. The scaling is applied
|
||
|
|
before the Artist master transform; if the latter is an identity
|
||
|
|
transform, then the overall scaling is such that if
|
||
|
|
*verts_i* specify a unit square, then *sizes_i* is the area
|
||
|
|
of that square in points^2.
|
||
|
|
If len(*sizes*) < *nv*, the additional values will be
|
||
|
|
taken cyclically from the array.
|
||
|
|
|
||
|
|
*closed*, when *True*, will explicitly close the polygon.
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
"""
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self.set_sizes(sizes)
|
||
|
|
self.set_verts(verts, closed)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_verts(self, verts, closed=True):
|
||
|
|
'''This allows one to delay initialization of the vertices.'''
|
||
|
|
if isinstance(verts, np.ma.MaskedArray):
|
||
|
|
verts = verts.astype(float).filled(np.nan)
|
||
|
|
# This is much faster than having Path do it one at a time.
|
||
|
|
if closed:
|
||
|
|
self._paths = []
|
||
|
|
for xy in verts:
|
||
|
|
if len(xy):
|
||
|
|
if isinstance(xy, np.ma.MaskedArray):
|
||
|
|
xy = np.ma.concatenate([xy, xy[0:1]])
|
||
|
|
else:
|
||
|
|
xy = np.asarray(xy)
|
||
|
|
xy = np.concatenate([xy, xy[0:1]])
|
||
|
|
codes = np.empty(xy.shape[0], dtype=mpath.Path.code_type)
|
||
|
|
codes[:] = mpath.Path.LINETO
|
||
|
|
codes[0] = mpath.Path.MOVETO
|
||
|
|
codes[-1] = mpath.Path.CLOSEPOLY
|
||
|
|
self._paths.append(mpath.Path(xy, codes))
|
||
|
|
else:
|
||
|
|
self._paths.append(mpath.Path(xy))
|
||
|
|
else:
|
||
|
|
self._paths = [mpath.Path(xy) for xy in verts]
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
set_paths = set_verts
|
||
|
|
|
||
|
|
def set_verts_and_codes(self, verts, codes):
|
||
|
|
"""This allows one to initialize vertices with path codes."""
|
||
|
|
if len(verts) != len(codes):
|
||
|
|
raise ValueError("'codes' must be a 1D list or array "
|
||
|
|
"with the same length of 'verts'")
|
||
|
|
self._paths = []
|
||
|
|
for xy, cds in zip(verts, codes):
|
||
|
|
if len(xy):
|
||
|
|
self._paths.append(mpath.Path(xy, cds))
|
||
|
|
else:
|
||
|
|
self._paths.append(mpath.Path(xy))
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
|
||
|
|
class BrokenBarHCollection(PolyCollection):
|
||
|
|
"""
|
||
|
|
A collection of horizontal bars spanning *yrange* with a sequence of
|
||
|
|
*xranges*.
|
||
|
|
"""
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self, xranges, yrange, **kwargs):
|
||
|
|
"""
|
||
|
|
*xranges*
|
||
|
|
sequence of (*xmin*, *xwidth*)
|
||
|
|
|
||
|
|
*yrange*
|
||
|
|
*ymin*, *ywidth*
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
"""
|
||
|
|
ymin, ywidth = yrange
|
||
|
|
ymax = ymin + ywidth
|
||
|
|
verts = [[(xmin, ymin),
|
||
|
|
(xmin, ymax),
|
||
|
|
(xmin + xwidth, ymax),
|
||
|
|
(xmin + xwidth, ymin),
|
||
|
|
(xmin, ymin)] for xmin, xwidth in xranges]
|
||
|
|
PolyCollection.__init__(self, verts, **kwargs)
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def span_where(x, ymin, ymax, where, **kwargs):
|
||
|
|
"""
|
||
|
|
Create a BrokenBarHCollection to plot horizontal bars from
|
||
|
|
over the regions in *x* where *where* is True. The bars range
|
||
|
|
on the y-axis from *ymin* to *ymax*
|
||
|
|
|
||
|
|
A :class:`BrokenBarHCollection` is returned. *kwargs* are
|
||
|
|
passed on to the collection.
|
||
|
|
"""
|
||
|
|
xranges = []
|
||
|
|
for ind0, ind1 in cbook.contiguous_regions(where):
|
||
|
|
xslice = x[ind0:ind1]
|
||
|
|
if not len(xslice):
|
||
|
|
continue
|
||
|
|
xranges.append((xslice[0], xslice[-1] - xslice[0]))
|
||
|
|
|
||
|
|
collection = BrokenBarHCollection(
|
||
|
|
xranges, [ymin, ymax - ymin], **kwargs)
|
||
|
|
return collection
|
||
|
|
|
||
|
|
|
||
|
|
class RegularPolyCollection(_CollectionWithSizes):
|
||
|
|
"""Draw a collection of regular polygons with *numsides*."""
|
||
|
|
|
||
|
|
_path_generator = mpath.Path.unit_regular_polygon
|
||
|
|
_factor = np.pi ** (-1/2)
|
||
|
|
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self,
|
||
|
|
numsides,
|
||
|
|
rotation=0,
|
||
|
|
sizes=(1,),
|
||
|
|
**kwargs):
|
||
|
|
"""
|
||
|
|
*numsides*
|
||
|
|
the number of sides of the polygon
|
||
|
|
|
||
|
|
*rotation*
|
||
|
|
the rotation of the polygon in radians
|
||
|
|
|
||
|
|
*sizes*
|
||
|
|
gives the area of the circle circumscribing the
|
||
|
|
regular polygon in points^2
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
|
||
|
|
Example: see :doc:`/gallery/event_handling/lasso_demo` for a
|
||
|
|
complete example::
|
||
|
|
|
||
|
|
offsets = np.random.rand(20, 2)
|
||
|
|
facecolors = [cm.jet(x) for x in np.random.rand(20)]
|
||
|
|
|
||
|
|
collection = RegularPolyCollection(
|
||
|
|
numsides=5, # a pentagon
|
||
|
|
rotation=0, sizes=(50,),
|
||
|
|
facecolors=facecolors,
|
||
|
|
edgecolors=("black",),
|
||
|
|
linewidths=(1,),
|
||
|
|
offsets=offsets,
|
||
|
|
transOffset=ax.transData,
|
||
|
|
)
|
||
|
|
"""
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self.set_sizes(sizes)
|
||
|
|
self._numsides = numsides
|
||
|
|
self._paths = [self._path_generator(numsides)]
|
||
|
|
self._rotation = rotation
|
||
|
|
self.set_transform(transforms.IdentityTransform())
|
||
|
|
|
||
|
|
def get_numsides(self):
|
||
|
|
return self._numsides
|
||
|
|
|
||
|
|
def get_rotation(self):
|
||
|
|
return self._rotation
|
||
|
|
|
||
|
|
@artist.allow_rasterization
|
||
|
|
def draw(self, renderer):
|
||
|
|
self.set_sizes(self._sizes, self.figure.dpi)
|
||
|
|
self._transforms = [
|
||
|
|
transforms.Affine2D(x).rotate(-self._rotation).get_matrix()
|
||
|
|
for x in self._transforms
|
||
|
|
]
|
||
|
|
Collection.draw(self, renderer)
|
||
|
|
|
||
|
|
|
||
|
|
class StarPolygonCollection(RegularPolyCollection):
|
||
|
|
"""Draw a collection of regular stars with *numsides* points."""
|
||
|
|
_path_generator = mpath.Path.unit_regular_star
|
||
|
|
|
||
|
|
|
||
|
|
class AsteriskPolygonCollection(RegularPolyCollection):
|
||
|
|
"""Draw a collection of regular asterisks with *numsides* points."""
|
||
|
|
_path_generator = mpath.Path.unit_regular_asterisk
|
||
|
|
|
||
|
|
|
||
|
|
class LineCollection(Collection):
|
||
|
|
"""
|
||
|
|
All parameters must be sequences or scalars; if scalars, they will
|
||
|
|
be converted to sequences. The property of the ith line
|
||
|
|
segment is::
|
||
|
|
|
||
|
|
prop[i % len(props)]
|
||
|
|
|
||
|
|
i.e., the properties cycle if the ``len`` of props is less than the
|
||
|
|
number of segments.
|
||
|
|
"""
|
||
|
|
|
||
|
|
_edge_default = True
|
||
|
|
|
||
|
|
def __init__(self, segments, # Can be None.
|
||
|
|
linewidths=None,
|
||
|
|
colors=None,
|
||
|
|
antialiaseds=None,
|
||
|
|
linestyles='solid',
|
||
|
|
offsets=None,
|
||
|
|
transOffset=None,
|
||
|
|
norm=None,
|
||
|
|
cmap=None,
|
||
|
|
pickradius=5,
|
||
|
|
zorder=2,
|
||
|
|
facecolors='none',
|
||
|
|
**kwargs
|
||
|
|
):
|
||
|
|
"""
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
segments
|
||
|
|
A sequence of (*line0*, *line1*, *line2*), where::
|
||
|
|
|
||
|
|
linen = (x0, y0), (x1, y1), ... (xm, ym)
|
||
|
|
|
||
|
|
or the equivalent numpy array with two columns. Each line
|
||
|
|
can be a different length.
|
||
|
|
|
||
|
|
colors : sequence, optional
|
||
|
|
A sequence of RGBA tuples (e.g., arbitrary color
|
||
|
|
strings, etc, not allowed).
|
||
|
|
|
||
|
|
antialiaseds : sequence, optional
|
||
|
|
A sequence of ones or zeros.
|
||
|
|
|
||
|
|
linestyles : str or tuple, optional
|
||
|
|
Either one of {'solid', 'dashed', 'dashdot', 'dotted'}, or
|
||
|
|
a dash tuple. The dash tuple is::
|
||
|
|
|
||
|
|
(offset, onoffseq)
|
||
|
|
|
||
|
|
where ``onoffseq`` is an even length tuple of on and off ink
|
||
|
|
in points.
|
||
|
|
|
||
|
|
norm : Normalize, optional
|
||
|
|
`~.colors.Normalize` instance.
|
||
|
|
|
||
|
|
cmap : str or Colormap, optional
|
||
|
|
Colormap name or `~.colors.Colormap` instance.
|
||
|
|
|
||
|
|
pickradius : float, optional
|
||
|
|
The tolerance in points for mouse clicks picking a line.
|
||
|
|
Default is 5 pt.
|
||
|
|
|
||
|
|
zorder : int, optional
|
||
|
|
zorder of the LineCollection. Default is 2.
|
||
|
|
|
||
|
|
facecolors : optional
|
||
|
|
The facecolors of the LineCollection. Default is 'none'.
|
||
|
|
Setting to a value other than 'none' will lead to a filled
|
||
|
|
polygon being drawn between points on each line.
|
||
|
|
|
||
|
|
Notes
|
||
|
|
-----
|
||
|
|
If *linewidths*, *colors*, or *antialiaseds* is None, they
|
||
|
|
default to their rcParams setting, in sequence form.
|
||
|
|
|
||
|
|
If *offsets* and *transOffset* are not None, then
|
||
|
|
*offsets* are transformed by *transOffset* and applied after
|
||
|
|
the segments have been transformed to display coordinates.
|
||
|
|
|
||
|
|
If *offsets* is not None but *transOffset* is None, then the
|
||
|
|
*offsets* are added to the segments before any transformation.
|
||
|
|
In this case, a single offset can be specified as::
|
||
|
|
|
||
|
|
offsets=(xo, yo)
|
||
|
|
|
||
|
|
and this value will be added cumulatively to each successive
|
||
|
|
segment, so as to produce a set of successively offset curves.
|
||
|
|
|
||
|
|
The use of :class:`~matplotlib.cm.ScalarMappable` is optional.
|
||
|
|
If the :class:`~matplotlib.cm.ScalarMappable` array
|
||
|
|
:attr:`~matplotlib.cm.ScalarMappable._A` is not None (i.e., a call to
|
||
|
|
:meth:`~matplotlib.cm.ScalarMappable.set_array` has been made), at
|
||
|
|
draw time a call to scalar mappable will be made to set the colors.
|
||
|
|
"""
|
||
|
|
if colors is None:
|
||
|
|
colors = mpl.rcParams['lines.color']
|
||
|
|
if linewidths is None:
|
||
|
|
linewidths = (mpl.rcParams['lines.linewidth'],)
|
||
|
|
if antialiaseds is None:
|
||
|
|
antialiaseds = (mpl.rcParams['lines.antialiased'],)
|
||
|
|
|
||
|
|
colors = mcolors.to_rgba_array(colors)
|
||
|
|
Collection.__init__(
|
||
|
|
self,
|
||
|
|
edgecolors=colors,
|
||
|
|
facecolors=facecolors,
|
||
|
|
linewidths=linewidths,
|
||
|
|
linestyles=linestyles,
|
||
|
|
antialiaseds=antialiaseds,
|
||
|
|
offsets=offsets,
|
||
|
|
transOffset=transOffset,
|
||
|
|
norm=norm,
|
||
|
|
cmap=cmap,
|
||
|
|
pickradius=pickradius,
|
||
|
|
zorder=zorder,
|
||
|
|
**kwargs)
|
||
|
|
|
||
|
|
self.set_segments(segments)
|
||
|
|
|
||
|
|
def set_segments(self, segments):
|
||
|
|
if segments is None:
|
||
|
|
return
|
||
|
|
_segments = []
|
||
|
|
|
||
|
|
for seg in segments:
|
||
|
|
if not isinstance(seg, np.ma.MaskedArray):
|
||
|
|
seg = np.asarray(seg, float)
|
||
|
|
_segments.append(seg)
|
||
|
|
|
||
|
|
if self._uniform_offsets is not None:
|
||
|
|
_segments = self._add_offsets(_segments)
|
||
|
|
|
||
|
|
self._paths = [mpath.Path(_seg) for _seg in _segments]
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
set_verts = set_segments # for compatibility with PolyCollection
|
||
|
|
set_paths = set_segments
|
||
|
|
|
||
|
|
def get_segments(self):
|
||
|
|
"""
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
segments : list
|
||
|
|
List of segments in the LineCollection. Each list item contains an
|
||
|
|
array of vertices.
|
||
|
|
"""
|
||
|
|
segments = []
|
||
|
|
|
||
|
|
for path in self._paths:
|
||
|
|
vertices = [vertex for vertex, _ in path.iter_segments()]
|
||
|
|
vertices = np.asarray(vertices)
|
||
|
|
segments.append(vertices)
|
||
|
|
|
||
|
|
return segments
|
||
|
|
|
||
|
|
def _add_offsets(self, segs):
|
||
|
|
offsets = self._uniform_offsets
|
||
|
|
Nsegs = len(segs)
|
||
|
|
Noffs = offsets.shape[0]
|
||
|
|
if Noffs == 1:
|
||
|
|
for i in range(Nsegs):
|
||
|
|
segs[i] = segs[i] + i * offsets
|
||
|
|
else:
|
||
|
|
for i in range(Nsegs):
|
||
|
|
io = i % Noffs
|
||
|
|
segs[i] = segs[i] + offsets[io:io + 1]
|
||
|
|
return segs
|
||
|
|
|
||
|
|
def set_color(self, c):
|
||
|
|
"""
|
||
|
|
Set the color(s) of the LineCollection.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
c : color or list of colors
|
||
|
|
Matplotlib color argument (all patches have same color), or a
|
||
|
|
sequence or rgba tuples; if it is a sequence the patches will
|
||
|
|
cycle through the sequence.
|
||
|
|
"""
|
||
|
|
self.set_edgecolor(c)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_color(self):
|
||
|
|
return self._edgecolors
|
||
|
|
|
||
|
|
get_colors = get_color # for compatibility with old versions
|
||
|
|
|
||
|
|
|
||
|
|
class EventCollection(LineCollection):
|
||
|
|
"""
|
||
|
|
A collection of discrete events.
|
||
|
|
|
||
|
|
The events are given by a 1-dimensional array, usually the position of
|
||
|
|
something along an axis, such as time or length. They do not have an
|
||
|
|
amplitude and are displayed as vertical or horizontal parallel bars.
|
||
|
|
"""
|
||
|
|
|
||
|
|
_edge_default = True
|
||
|
|
|
||
|
|
def __init__(self,
|
||
|
|
positions, # Cannot be None.
|
||
|
|
orientation=None,
|
||
|
|
lineoffset=0,
|
||
|
|
linelength=1,
|
||
|
|
linewidth=None,
|
||
|
|
color=None,
|
||
|
|
linestyle='solid',
|
||
|
|
antialiased=None,
|
||
|
|
**kwargs
|
||
|
|
):
|
||
|
|
"""
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
positions : 1D array-like object
|
||
|
|
Each value is an event.
|
||
|
|
|
||
|
|
orientation : {None, 'horizontal', 'vertical'}, optional
|
||
|
|
The orientation of the **collection** (the event bars are along
|
||
|
|
the orthogonal direction). Defaults to 'horizontal' if not
|
||
|
|
specified or None.
|
||
|
|
|
||
|
|
lineoffset : scalar, optional, default: 0
|
||
|
|
The offset of the center of the markers from the origin, in the
|
||
|
|
direction orthogonal to *orientation*.
|
||
|
|
|
||
|
|
linelength : scalar, optional, default: 1
|
||
|
|
The total height of the marker (i.e. the marker stretches from
|
||
|
|
``lineoffset - linelength/2`` to ``lineoffset + linelength/2``).
|
||
|
|
|
||
|
|
linewidth : scalar or None, optional, default: None
|
||
|
|
If it is None, defaults to its rcParams setting, in sequence form.
|
||
|
|
|
||
|
|
color : color, sequence of colors or None, optional, default: None
|
||
|
|
If it is None, defaults to its rcParams setting, in sequence form.
|
||
|
|
|
||
|
|
linestyle : str or tuple, optional, default: 'solid'
|
||
|
|
Valid strings are ['solid', 'dashed', 'dashdot', 'dotted',
|
||
|
|
'-', '--', '-.', ':']. Dash tuples should be of the form::
|
||
|
|
|
||
|
|
(offset, onoffseq),
|
||
|
|
|
||
|
|
where *onoffseq* is an even length tuple of on and off ink
|
||
|
|
in points.
|
||
|
|
|
||
|
|
antialiased : {None, 1, 2}, optional
|
||
|
|
If it is None, defaults to its rcParams setting, in sequence form.
|
||
|
|
|
||
|
|
**kwargs : optional
|
||
|
|
Other keyword arguments are line collection properties. See
|
||
|
|
:class:`~matplotlib.collections.LineCollection` for a list of
|
||
|
|
the valid properties.
|
||
|
|
|
||
|
|
Examples
|
||
|
|
--------
|
||
|
|
.. plot:: gallery/lines_bars_and_markers/eventcollection_demo.py
|
||
|
|
"""
|
||
|
|
if positions is None:
|
||
|
|
raise ValueError('positions must be an array-like object')
|
||
|
|
# Force a copy of positions
|
||
|
|
positions = np.array(positions, copy=True)
|
||
|
|
segment = (lineoffset + linelength / 2.,
|
||
|
|
lineoffset - linelength / 2.)
|
||
|
|
if positions.size == 0:
|
||
|
|
segments = []
|
||
|
|
elif positions.ndim > 1:
|
||
|
|
raise ValueError('positions cannot be an array with more than '
|
||
|
|
'one dimension.')
|
||
|
|
elif (orientation is None or orientation.lower() == 'none' or
|
||
|
|
orientation.lower() == 'horizontal'):
|
||
|
|
positions.sort()
|
||
|
|
segments = [[(coord1, coord2) for coord2 in segment] for
|
||
|
|
coord1 in positions]
|
||
|
|
self._is_horizontal = True
|
||
|
|
elif orientation.lower() == 'vertical':
|
||
|
|
positions.sort()
|
||
|
|
segments = [[(coord2, coord1) for coord2 in segment] for
|
||
|
|
coord1 in positions]
|
||
|
|
self._is_horizontal = False
|
||
|
|
else:
|
||
|
|
cbook._check_in_list(['horizontal', 'vertical'],
|
||
|
|
orientation=orientation)
|
||
|
|
|
||
|
|
LineCollection.__init__(self,
|
||
|
|
segments,
|
||
|
|
linewidths=linewidth,
|
||
|
|
colors=color,
|
||
|
|
antialiaseds=antialiased,
|
||
|
|
linestyles=linestyle,
|
||
|
|
**kwargs)
|
||
|
|
|
||
|
|
self._linelength = linelength
|
||
|
|
self._lineoffset = lineoffset
|
||
|
|
|
||
|
|
def get_positions(self):
|
||
|
|
'''
|
||
|
|
return an array containing the floating-point values of the positions
|
||
|
|
'''
|
||
|
|
pos = 0 if self.is_horizontal() else 1
|
||
|
|
return [segment[0, pos] for segment in self.get_segments()]
|
||
|
|
|
||
|
|
def set_positions(self, positions):
|
||
|
|
'''
|
||
|
|
set the positions of the events to the specified value
|
||
|
|
'''
|
||
|
|
if positions is None or (hasattr(positions, 'len') and
|
||
|
|
len(positions) == 0):
|
||
|
|
self.set_segments([])
|
||
|
|
return
|
||
|
|
|
||
|
|
lineoffset = self.get_lineoffset()
|
||
|
|
linelength = self.get_linelength()
|
||
|
|
segment = (lineoffset + linelength / 2.,
|
||
|
|
lineoffset - linelength / 2.)
|
||
|
|
positions = np.asanyarray(positions)
|
||
|
|
positions.sort()
|
||
|
|
if self.is_horizontal():
|
||
|
|
segments = [[(coord1, coord2) for coord2 in segment] for
|
||
|
|
coord1 in positions]
|
||
|
|
else:
|
||
|
|
segments = [[(coord2, coord1) for coord2 in segment] for
|
||
|
|
coord1 in positions]
|
||
|
|
self.set_segments(segments)
|
||
|
|
|
||
|
|
def add_positions(self, position):
|
||
|
|
'''
|
||
|
|
add one or more events at the specified positions
|
||
|
|
'''
|
||
|
|
if position is None or (hasattr(position, 'len') and
|
||
|
|
len(position) == 0):
|
||
|
|
return
|
||
|
|
positions = self.get_positions()
|
||
|
|
positions = np.hstack([positions, np.asanyarray(position)])
|
||
|
|
self.set_positions(positions)
|
||
|
|
extend_positions = append_positions = add_positions
|
||
|
|
|
||
|
|
def is_horizontal(self):
|
||
|
|
'''
|
||
|
|
True if the eventcollection is horizontal, False if vertical
|
||
|
|
'''
|
||
|
|
return self._is_horizontal
|
||
|
|
|
||
|
|
def get_orientation(self):
|
||
|
|
"""
|
||
|
|
Return the orientation of the event line ('horizontal' or 'vertical').
|
||
|
|
"""
|
||
|
|
return 'horizontal' if self.is_horizontal() else 'vertical'
|
||
|
|
|
||
|
|
def switch_orientation(self):
|
||
|
|
'''
|
||
|
|
switch the orientation of the event line, either from vertical to
|
||
|
|
horizontal or vice versus
|
||
|
|
'''
|
||
|
|
segments = self.get_segments()
|
||
|
|
for i, segment in enumerate(segments):
|
||
|
|
segments[i] = np.fliplr(segment)
|
||
|
|
self.set_segments(segments)
|
||
|
|
self._is_horizontal = not self.is_horizontal()
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def set_orientation(self, orientation=None):
|
||
|
|
"""
|
||
|
|
Set the orientation of the event line.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
orientation: {'horizontal', 'vertical'} or None
|
||
|
|
Defaults to 'horizontal' if not specified or None.
|
||
|
|
"""
|
||
|
|
if (orientation is None or orientation.lower() == 'none' or
|
||
|
|
orientation.lower() == 'horizontal'):
|
||
|
|
is_horizontal = True
|
||
|
|
elif orientation.lower() == 'vertical':
|
||
|
|
is_horizontal = False
|
||
|
|
else:
|
||
|
|
cbook._check_in_list(['horizontal', 'vertical'],
|
||
|
|
orientation=orientation)
|
||
|
|
if is_horizontal == self.is_horizontal():
|
||
|
|
return
|
||
|
|
self.switch_orientation()
|
||
|
|
|
||
|
|
def get_linelength(self):
|
||
|
|
'''
|
||
|
|
get the length of the lines used to mark each event
|
||
|
|
'''
|
||
|
|
return self._linelength
|
||
|
|
|
||
|
|
def set_linelength(self, linelength):
|
||
|
|
'''
|
||
|
|
set the length of the lines used to mark each event
|
||
|
|
'''
|
||
|
|
if linelength == self.get_linelength():
|
||
|
|
return
|
||
|
|
lineoffset = self.get_lineoffset()
|
||
|
|
segments = self.get_segments()
|
||
|
|
pos = 1 if self.is_horizontal() else 0
|
||
|
|
for segment in segments:
|
||
|
|
segment[0, pos] = lineoffset + linelength / 2.
|
||
|
|
segment[1, pos] = lineoffset - linelength / 2.
|
||
|
|
self.set_segments(segments)
|
||
|
|
self._linelength = linelength
|
||
|
|
|
||
|
|
def get_lineoffset(self):
|
||
|
|
'''
|
||
|
|
get the offset of the lines used to mark each event
|
||
|
|
'''
|
||
|
|
return self._lineoffset
|
||
|
|
|
||
|
|
def set_lineoffset(self, lineoffset):
|
||
|
|
'''
|
||
|
|
set the offset of the lines used to mark each event
|
||
|
|
'''
|
||
|
|
if lineoffset == self.get_lineoffset():
|
||
|
|
return
|
||
|
|
linelength = self.get_linelength()
|
||
|
|
segments = self.get_segments()
|
||
|
|
pos = 1 if self.is_horizontal() else 0
|
||
|
|
for segment in segments:
|
||
|
|
segment[0, pos] = lineoffset + linelength / 2.
|
||
|
|
segment[1, pos] = lineoffset - linelength / 2.
|
||
|
|
self.set_segments(segments)
|
||
|
|
self._lineoffset = lineoffset
|
||
|
|
|
||
|
|
def get_linewidth(self):
|
||
|
|
"""Get the width of the lines used to mark each event."""
|
||
|
|
return super(EventCollection, self).get_linewidth()[0]
|
||
|
|
|
||
|
|
def get_linewidths(self):
|
||
|
|
return super(EventCollection, self).get_linewidth()
|
||
|
|
|
||
|
|
def get_color(self):
|
||
|
|
'''
|
||
|
|
get the color of the lines used to mark each event
|
||
|
|
'''
|
||
|
|
return self.get_colors()[0]
|
||
|
|
|
||
|
|
|
||
|
|
class CircleCollection(_CollectionWithSizes):
|
||
|
|
"""A collection of circles, drawn using splines."""
|
||
|
|
|
||
|
|
_factor = np.pi ** (-1/2)
|
||
|
|
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self, sizes, **kwargs):
|
||
|
|
"""
|
||
|
|
*sizes*
|
||
|
|
Gives the area of the circle in points^2
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
"""
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self.set_sizes(sizes)
|
||
|
|
self.set_transform(transforms.IdentityTransform())
|
||
|
|
self._paths = [mpath.Path.unit_circle()]
|
||
|
|
|
||
|
|
|
||
|
|
class EllipseCollection(Collection):
|
||
|
|
"""A collection of ellipses, drawn using splines."""
|
||
|
|
|
||
|
|
@docstring.dedent_interpd
|
||
|
|
def __init__(self, widths, heights, angles, units='points', **kwargs):
|
||
|
|
"""
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
widths : array-like
|
||
|
|
The lengths of the first axes (e.g., major axis lengths).
|
||
|
|
|
||
|
|
heights : array-like
|
||
|
|
The lengths of second axes.
|
||
|
|
|
||
|
|
angles : array-like
|
||
|
|
The angles of the first axes, degrees CCW from the x-axis.
|
||
|
|
|
||
|
|
units : {'points', 'inches', 'dots', 'width', 'height', 'x', 'y', 'xy'}
|
||
|
|
|
||
|
|
The units in which majors and minors are given; 'width' and
|
||
|
|
'height' refer to the dimensions of the axes, while 'x'
|
||
|
|
and 'y' refer to the *offsets* data units. 'xy' differs
|
||
|
|
from all others in that the angle as plotted varies with
|
||
|
|
the aspect ratio, and equals the specified angle only when
|
||
|
|
the aspect ratio is unity. Hence it behaves the same as
|
||
|
|
the :class:`~matplotlib.patches.Ellipse` with
|
||
|
|
``axes.transData`` as its transform.
|
||
|
|
|
||
|
|
Other Parameters
|
||
|
|
----------------
|
||
|
|
**kwargs
|
||
|
|
Additional kwargs inherited from the base :class:`Collection`.
|
||
|
|
|
||
|
|
%(Collection)s
|
||
|
|
"""
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self._widths = 0.5 * np.asarray(widths).ravel()
|
||
|
|
self._heights = 0.5 * np.asarray(heights).ravel()
|
||
|
|
self._angles = np.deg2rad(angles).ravel()
|
||
|
|
self._units = units
|
||
|
|
self.set_transform(transforms.IdentityTransform())
|
||
|
|
self._transforms = np.empty((0, 3, 3))
|
||
|
|
self._paths = [mpath.Path.unit_circle()]
|
||
|
|
|
||
|
|
def _set_transforms(self):
|
||
|
|
"""Calculate transforms immediately before drawing."""
|
||
|
|
|
||
|
|
ax = self.axes
|
||
|
|
fig = self.figure
|
||
|
|
|
||
|
|
if self._units == 'xy':
|
||
|
|
sc = 1
|
||
|
|
elif self._units == 'x':
|
||
|
|
sc = ax.bbox.width / ax.viewLim.width
|
||
|
|
elif self._units == 'y':
|
||
|
|
sc = ax.bbox.height / ax.viewLim.height
|
||
|
|
elif self._units == 'inches':
|
||
|
|
sc = fig.dpi
|
||
|
|
elif self._units == 'points':
|
||
|
|
sc = fig.dpi / 72.0
|
||
|
|
elif self._units == 'width':
|
||
|
|
sc = ax.bbox.width
|
||
|
|
elif self._units == 'height':
|
||
|
|
sc = ax.bbox.height
|
||
|
|
elif self._units == 'dots':
|
||
|
|
sc = 1.0
|
||
|
|
else:
|
||
|
|
raise ValueError('unrecognized units: %s' % self._units)
|
||
|
|
|
||
|
|
self._transforms = np.zeros((len(self._widths), 3, 3))
|
||
|
|
widths = self._widths * sc
|
||
|
|
heights = self._heights * sc
|
||
|
|
sin_angle = np.sin(self._angles)
|
||
|
|
cos_angle = np.cos(self._angles)
|
||
|
|
self._transforms[:, 0, 0] = widths * cos_angle
|
||
|
|
self._transforms[:, 0, 1] = heights * -sin_angle
|
||
|
|
self._transforms[:, 1, 0] = widths * sin_angle
|
||
|
|
self._transforms[:, 1, 1] = heights * cos_angle
|
||
|
|
self._transforms[:, 2, 2] = 1.0
|
||
|
|
|
||
|
|
_affine = transforms.Affine2D
|
||
|
|
if self._units == 'xy':
|
||
|
|
m = ax.transData.get_affine().get_matrix().copy()
|
||
|
|
m[:2, 2:] = 0
|
||
|
|
self.set_transform(_affine(m))
|
||
|
|
|
||
|
|
@artist.allow_rasterization
|
||
|
|
def draw(self, renderer):
|
||
|
|
self._set_transforms()
|
||
|
|
Collection.draw(self, renderer)
|
||
|
|
|
||
|
|
|
||
|
|
class PatchCollection(Collection):
|
||
|
|
"""
|
||
|
|
A generic collection of patches.
|
||
|
|
|
||
|
|
This makes it easier to assign a color map to a heterogeneous
|
||
|
|
collection of patches.
|
||
|
|
|
||
|
|
This also may improve plotting speed, since PatchCollection will
|
||
|
|
draw faster than a large number of patches.
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self, patches, match_original=False, **kwargs):
|
||
|
|
"""
|
||
|
|
*patches*
|
||
|
|
a sequence of Patch objects. This list may include
|
||
|
|
a heterogeneous assortment of different patch types.
|
||
|
|
|
||
|
|
*match_original*
|
||
|
|
If True, use the colors and linewidths of the original
|
||
|
|
patches. If False, new colors may be assigned by
|
||
|
|
providing the standard collection arguments, facecolor,
|
||
|
|
edgecolor, linewidths, norm or cmap.
|
||
|
|
|
||
|
|
If any of *edgecolors*, *facecolors*, *linewidths*,
|
||
|
|
*antialiaseds* are None, they default to their
|
||
|
|
:data:`matplotlib.rcParams` patch setting, in sequence form.
|
||
|
|
|
||
|
|
The use of :class:`~matplotlib.cm.ScalarMappable` is optional.
|
||
|
|
If the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not
|
||
|
|
None (i.e., a call to set_array has been made), at draw time a
|
||
|
|
call to scalar mappable will be made to set the face colors.
|
||
|
|
"""
|
||
|
|
|
||
|
|
if match_original:
|
||
|
|
def determine_facecolor(patch):
|
||
|
|
if patch.get_fill():
|
||
|
|
return patch.get_facecolor()
|
||
|
|
return [0, 0, 0, 0]
|
||
|
|
|
||
|
|
kwargs['facecolors'] = [determine_facecolor(p) for p in patches]
|
||
|
|
kwargs['edgecolors'] = [p.get_edgecolor() for p in patches]
|
||
|
|
kwargs['linewidths'] = [p.get_linewidth() for p in patches]
|
||
|
|
kwargs['linestyles'] = [p.get_linestyle() for p in patches]
|
||
|
|
kwargs['antialiaseds'] = [p.get_antialiased() for p in patches]
|
||
|
|
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
|
||
|
|
self.set_paths(patches)
|
||
|
|
|
||
|
|
def set_paths(self, patches):
|
||
|
|
paths = [p.get_transform().transform_path(p.get_path())
|
||
|
|
for p in patches]
|
||
|
|
self._paths = paths
|
||
|
|
|
||
|
|
|
||
|
|
class TriMesh(Collection):
|
||
|
|
"""
|
||
|
|
Class for the efficient drawing of a triangular mesh using Gouraud shading.
|
||
|
|
|
||
|
|
A triangular mesh is a `~matplotlib.tri.Triangulation` object.
|
||
|
|
"""
|
||
|
|
def __init__(self, triangulation, **kwargs):
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self._triangulation = triangulation
|
||
|
|
self._shading = 'gouraud'
|
||
|
|
self._is_filled = True
|
||
|
|
|
||
|
|
self._bbox = transforms.Bbox.unit()
|
||
|
|
|
||
|
|
# Unfortunately this requires a copy, unless Triangulation
|
||
|
|
# was rewritten.
|
||
|
|
xy = np.hstack((triangulation.x.reshape(-1, 1),
|
||
|
|
triangulation.y.reshape(-1, 1)))
|
||
|
|
self._bbox.update_from_data_xy(xy)
|
||
|
|
|
||
|
|
def get_paths(self):
|
||
|
|
if self._paths is None:
|
||
|
|
self.set_paths()
|
||
|
|
return self._paths
|
||
|
|
|
||
|
|
def set_paths(self):
|
||
|
|
self._paths = self.convert_mesh_to_paths(self._triangulation)
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def convert_mesh_to_paths(tri):
|
||
|
|
"""
|
||
|
|
Converts a given mesh into a sequence of `~.Path` objects.
|
||
|
|
|
||
|
|
This function is primarily of use to implementers of backends that do
|
||
|
|
not directly support meshes.
|
||
|
|
"""
|
||
|
|
triangles = tri.get_masked_triangles()
|
||
|
|
verts = np.stack((tri.x[triangles], tri.y[triangles]), axis=-1)
|
||
|
|
return [mpath.Path(x) for x in verts]
|
||
|
|
|
||
|
|
@artist.allow_rasterization
|
||
|
|
def draw(self, renderer):
|
||
|
|
if not self.get_visible():
|
||
|
|
return
|
||
|
|
renderer.open_group(self.__class__.__name__, gid=self.get_gid())
|
||
|
|
transform = self.get_transform()
|
||
|
|
|
||
|
|
# Get a list of triangles and the color at each vertex.
|
||
|
|
tri = self._triangulation
|
||
|
|
triangles = tri.get_masked_triangles()
|
||
|
|
|
||
|
|
verts = np.stack((tri.x[triangles], tri.y[triangles]), axis=-1)
|
||
|
|
|
||
|
|
self.update_scalarmappable()
|
||
|
|
colors = self._facecolors[triangles]
|
||
|
|
|
||
|
|
gc = renderer.new_gc()
|
||
|
|
self._set_gc_clip(gc)
|
||
|
|
gc.set_linewidth(self.get_linewidth()[0])
|
||
|
|
renderer.draw_gouraud_triangles(gc, verts, colors, transform.frozen())
|
||
|
|
gc.restore()
|
||
|
|
renderer.close_group(self.__class__.__name__)
|
||
|
|
|
||
|
|
|
||
|
|
class QuadMesh(Collection):
|
||
|
|
"""
|
||
|
|
Class for the efficient drawing of a quadrilateral mesh.
|
||
|
|
|
||
|
|
A quadrilateral mesh consists of a grid of vertices. The
|
||
|
|
dimensions of this array are (*meshWidth* + 1, *meshHeight* +
|
||
|
|
1). Each vertex in the mesh has a different set of "mesh
|
||
|
|
coordinates" representing its position in the topology of the
|
||
|
|
mesh. For any values (*m*, *n*) such that 0 <= *m* <= *meshWidth*
|
||
|
|
and 0 <= *n* <= *meshHeight*, the vertices at mesh coordinates
|
||
|
|
(*m*, *n*), (*m*, *n* + 1), (*m* + 1, *n* + 1), and (*m* + 1, *n*)
|
||
|
|
form one of the quadrilaterals in the mesh. There are thus
|
||
|
|
(*meshWidth* * *meshHeight*) quadrilaterals in the mesh. The mesh
|
||
|
|
need not be regular and the polygons need not be convex.
|
||
|
|
|
||
|
|
A quadrilateral mesh is represented by a (2 x ((*meshWidth* + 1) *
|
||
|
|
(*meshHeight* + 1))) numpy array *coordinates*, where each row is
|
||
|
|
the *x* and *y* coordinates of one of the vertices. To define the
|
||
|
|
function that maps from a data point to its corresponding color,
|
||
|
|
use the :meth:`set_cmap` method. Each of these arrays is indexed in
|
||
|
|
row-major order by the mesh coordinates of the vertex (or the mesh
|
||
|
|
coordinates of the lower left vertex, in the case of the
|
||
|
|
colors).
|
||
|
|
|
||
|
|
For example, the first entry in *coordinates* is the
|
||
|
|
coordinates of the vertex at mesh coordinates (0, 0), then the one
|
||
|
|
at (0, 1), then at (0, 2) .. (0, meshWidth), (1, 0), (1, 1), and
|
||
|
|
so on.
|
||
|
|
|
||
|
|
*shading* may be 'flat', or 'gouraud'
|
||
|
|
"""
|
||
|
|
def __init__(self, meshWidth, meshHeight, coordinates,
|
||
|
|
antialiased=True, shading='flat', **kwargs):
|
||
|
|
Collection.__init__(self, **kwargs)
|
||
|
|
self._meshWidth = meshWidth
|
||
|
|
self._meshHeight = meshHeight
|
||
|
|
# By converting to floats now, we can avoid that on every draw.
|
||
|
|
self._coordinates = np.asarray(coordinates, float).reshape(
|
||
|
|
(meshHeight + 1, meshWidth + 1, 2))
|
||
|
|
self._antialiased = antialiased
|
||
|
|
self._shading = shading
|
||
|
|
|
||
|
|
self._bbox = transforms.Bbox.unit()
|
||
|
|
self._bbox.update_from_data_xy(coordinates.reshape(
|
||
|
|
((meshWidth + 1) * (meshHeight + 1), 2)))
|
||
|
|
|
||
|
|
def get_paths(self):
|
||
|
|
if self._paths is None:
|
||
|
|
self.set_paths()
|
||
|
|
return self._paths
|
||
|
|
|
||
|
|
def set_paths(self):
|
||
|
|
self._paths = self.convert_mesh_to_paths(
|
||
|
|
self._meshWidth, self._meshHeight, self._coordinates)
|
||
|
|
self.stale = True
|
||
|
|
|
||
|
|
def get_datalim(self, transData):
|
||
|
|
return (self.get_transform() - transData).transform_bbox(self._bbox)
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def convert_mesh_to_paths(meshWidth, meshHeight, coordinates):
|
||
|
|
"""
|
||
|
|
Converts a given mesh into a sequence of `~.Path` objects.
|
||
|
|
|
||
|
|
This function is primarily of use to implementers of backends that do
|
||
|
|
not directly support quadmeshes.
|
||
|
|
"""
|
||
|
|
if isinstance(coordinates, np.ma.MaskedArray):
|
||
|
|
c = coordinates.data
|
||
|
|
else:
|
||
|
|
c = coordinates
|
||
|
|
points = np.concatenate((
|
||
|
|
c[:-1, :-1],
|
||
|
|
c[:-1, 1:],
|
||
|
|
c[1:, 1:],
|
||
|
|
c[1:, :-1],
|
||
|
|
c[:-1, :-1]
|
||
|
|
), axis=2)
|
||
|
|
points = points.reshape((meshWidth * meshHeight, 5, 2))
|
||
|
|
return [mpath.Path(x) for x in points]
|
||
|
|
|
||
|
|
def convert_mesh_to_triangles(self, meshWidth, meshHeight, coordinates):
|
||
|
|
"""
|
||
|
|
Converts a given mesh into a sequence of triangles, each point
|
||
|
|
with its own color. This is useful for experiments using
|
||
|
|
`draw_gouraud_triangle`.
|
||
|
|
"""
|
||
|
|
if isinstance(coordinates, np.ma.MaskedArray):
|
||
|
|
p = coordinates.data
|
||
|
|
else:
|
||
|
|
p = coordinates
|
||
|
|
|
||
|
|
p_a = p[:-1, :-1]
|
||
|
|
p_b = p[:-1, 1:]
|
||
|
|
p_c = p[1:, 1:]
|
||
|
|
p_d = p[1:, :-1]
|
||
|
|
p_center = (p_a + p_b + p_c + p_d) / 4.0
|
||
|
|
|
||
|
|
triangles = np.concatenate((
|
||
|
|
p_a, p_b, p_center,
|
||
|
|
p_b, p_c, p_center,
|
||
|
|
p_c, p_d, p_center,
|
||
|
|
p_d, p_a, p_center,
|
||
|
|
), axis=2)
|
||
|
|
triangles = triangles.reshape((meshWidth * meshHeight * 4, 3, 2))
|
||
|
|
|
||
|
|
c = self.get_facecolor().reshape((meshHeight + 1, meshWidth + 1, 4))
|
||
|
|
c_a = c[:-1, :-1]
|
||
|
|
c_b = c[:-1, 1:]
|
||
|
|
c_c = c[1:, 1:]
|
||
|
|
c_d = c[1:, :-1]
|
||
|
|
c_center = (c_a + c_b + c_c + c_d) / 4.0
|
||
|
|
|
||
|
|
colors = np.concatenate((
|
||
|
|
c_a, c_b, c_center,
|
||
|
|
c_b, c_c, c_center,
|
||
|
|
c_c, c_d, c_center,
|
||
|
|
c_d, c_a, c_center,
|
||
|
|
), axis=2)
|
||
|
|
colors = colors.reshape((meshWidth * meshHeight * 4, 3, 4))
|
||
|
|
|
||
|
|
return triangles, colors
|
||
|
|
|
||
|
|
@artist.allow_rasterization
|
||
|
|
def draw(self, renderer):
|
||
|
|
if not self.get_visible():
|
||
|
|
return
|
||
|
|
renderer.open_group(self.__class__.__name__, self.get_gid())
|
||
|
|
transform = self.get_transform()
|
||
|
|
transOffset = self.get_offset_transform()
|
||
|
|
offsets = self._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])
|
||
|
|
|
||
|
|
self.update_scalarmappable()
|
||
|
|
|
||
|
|
if not transform.is_affine:
|
||
|
|
coordinates = self._coordinates.reshape((-1, 2))
|
||
|
|
coordinates = transform.transform(coordinates)
|
||
|
|
coordinates = coordinates.reshape(self._coordinates.shape)
|
||
|
|
transform = transforms.IdentityTransform()
|
||
|
|
else:
|
||
|
|
coordinates = self._coordinates
|
||
|
|
|
||
|
|
if not transOffset.is_affine:
|
||
|
|
offsets = transOffset.transform_non_affine(offsets)
|
||
|
|
transOffset = transOffset.get_affine()
|
||
|
|
|
||
|
|
gc = renderer.new_gc()
|
||
|
|
self._set_gc_clip(gc)
|
||
|
|
gc.set_linewidth(self.get_linewidth()[0])
|
||
|
|
|
||
|
|
if self._shading == 'gouraud':
|
||
|
|
triangles, colors = self.convert_mesh_to_triangles(
|
||
|
|
self._meshWidth, self._meshHeight, coordinates)
|
||
|
|
renderer.draw_gouraud_triangles(
|
||
|
|
gc, triangles, colors, transform.frozen())
|
||
|
|
else:
|
||
|
|
renderer.draw_quad_mesh(
|
||
|
|
gc, transform.frozen(), self._meshWidth, self._meshHeight,
|
||
|
|
coordinates, offsets, transOffset, self.get_facecolor(),
|
||
|
|
self._antialiased, self.get_edgecolors())
|
||
|
|
gc.restore()
|
||
|
|
renderer.close_group(self.__class__.__name__)
|
||
|
|
self.stale = False
|
||
|
|
|
||
|
|
|
||
|
|
patchstr = artist.kwdoc(Collection)
|
||
|
|
for k in ('QuadMesh', 'TriMesh', 'PolyCollection', 'BrokenBarHCollection',
|
||
|
|
'RegularPolyCollection', 'PathCollection',
|
||
|
|
'StarPolygonCollection', 'PatchCollection',
|
||
|
|
'CircleCollection', 'Collection',):
|
||
|
|
docstring.interpd.update({k: patchstr})
|
||
|
|
docstring.interpd.update(LineCollection=artist.kwdoc(LineCollection))
|